diff --git a/.gitignore b/.gitignore
index 763513e..c493ffc 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1 +1,3 @@
 .ipynb_checkpoints
+*.DS_Store
+*__pycache__/
\ No newline at end of file
diff --git a/000363/MAP/demo/README.md b/000363/MAP/demo/README.md
new file mode 100644
index 0000000..a9d24d9
--- /dev/null
+++ b/000363/MAP/demo/README.md
@@ -0,0 +1,9 @@
+This folder contains a notebook that demonstrates how to work with dandiset 000363. 
+
+`browse_map_ephys_data.ipynb` demonstrates how to navigate a single `.nwb` file from
+dataset 000363. This dataset was generated from the [map
+ephys](https://github.com/mesoscale-activity-map/map-ephys) pipeline. 
+
+The notebook demonstrates the contents of the `.nwb` file including acquiring the ccf
+coordinates, creating rasters aligned to specific events, and browsing the dandiset
+without downloading the file locally.
\ No newline at end of file
diff --git a/000363/MAP/demo/browse_map_ephys_data.ipynb b/000363/MAP/demo/browse_map_ephys_data.ipynb
new file mode 100644
index 0000000..d2d492b
--- /dev/null
+++ b/000363/MAP/demo/browse_map_ephys_data.ipynb
@@ -0,0 +1,2005 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Browse datasets on DANDI\n",
+    "\n",
+    "This notebook will provide instructions to read a dataset from DANDI and browse\n",
+    "the corresponding NWB file. The full set of instructions on NWB can be found\n",
+    "[here](https://pynwb.readthedocs.io/en/stable/index.html). \n",
+    "\n",
+    "The following packages are necessary to run this notebook. Please install them\n",
+    "to your conda environment by typing each of the code blocks in your terminal:\n",
+    "\n",
+    "1. pynwb:\n",
+    "\n",
+    "    ```pip install pynwb```\n",
+    "\n",
+    "2. nwbwidgets:\n",
+    "\n",
+    "    ```pip install nwbwidgets```\n",
+    "\n",
+    "3. fsspec, requests, and aiohttp\n",
+    "\n",
+    "    ```pip install fsspec requests aiohttp```\n",
+    "\n",
+    "\n",
+    "This notebook allows you to stream data directly from DANDI to preview the contents of\n",
+    "the `.nwb` file. We currently recommend downloading the `.nwb`\n",
+    "file of interest to your local machine after you explore it with the nwbwidget\n",
+    "to ensure optimal performance for downstream analyses. \n",
+    "\n",
+    "If you want to explore the NWB file in streaming mode, you will find\n",
+    "instructions at the bottom of the notebook to do so. Please note that converting\n",
+    "the `units` object to a dataframe takes a long time in this mode and it is\n",
+    "recommended that you bring objects into memory one at a time for best performance.\n",
+    "\n",
+    "The dataset used in this notebook can be found at\n",
+    "[https://dandiarchive.org/dandiset/000363?pos=1](https://dandiarchive.org/dandiset/000363?pos=1)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pynwb\n",
+    "import fsspec\n",
+    "import h5py\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "from pynwb import NWBHDF5IO\n",
+    "from nwbwidgets import nwb2widget\n",
+    "from nwbwidgets.panel import Panel\n",
+    "from dandi.dandiapi import DandiAPIClient"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The nwbwidgets `Panel()` class allows you to generate an exploratory widget for\n",
+    "any NWB file. This file can be on your local machine or on DANDI archive. To\n",
+    "find your dataset on DANDI please follow the steps below:\n",
+    "\n",
+    "1. Click on the `DANDI` radio button on the left side of the top panel.\n",
+    "2. Find your Dandiset: the MAP data is at Dandiset ID `000363`. \n",
+    "3. Find the file you want to browse.\n",
+    "4. Click load file to generate a widget that allows you to explore the contents\n",
+    "   of the `.nwb` file. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f4729bd5bb454ca598457ae51c3a9b3a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Panel(children=(HBox(children=(VBox(children=(RadioButtons(layout=Layout(width='100px'), options=('Local dir',…"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "fe2905db64fa450f98d2bd828260c866",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Loading dandiset metadata:   0%|          | 0/296 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\kusha\\miniconda3\\envs\\mapEphysNWB\\lib\\site-packages\\hdmf\\spec\\namespace.py:531: UserWarning: Ignoring cached namespace 'hdmf-common' version 1.6.0 because version 1.7.0 is already loaded.\n",
+      "  warn(\"Ignoring cached namespace '%s' version %s because version %s is already loaded.\"\n",
+      "c:\\Users\\kusha\\miniconda3\\envs\\mapEphysNWB\\lib\\site-packages\\hdmf\\spec\\namespace.py:531: UserWarning: Ignoring cached namespace 'hdmf-experimental' version 0.3.0 because version 0.4.0 is already loaded.\n",
+      "  warn(\"Ignoring cached namespace '%s' version %s because version %s is already loaded.\"\n"
+     ]
+    }
+   ],
+   "source": [
+    "Panel()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Once you have found the file you want to use, please download it and update the\n",
+    "path below to point to the `.nwb` file on your local machine relative to the\n",
+    "current working directory."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "io = NWBHDF5IO(\"../../dandiset/sub-449141_ses-20190530T173316_behavior+ecephys+ogen.nwb\", mode=\"r\")\n",
+    "nwbfile = io.read()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Performing exploratory and downstream analyses requires extracting data from the\n",
+    "NWB file and bringing it into memory. Below, we extract behavior trials and\n",
+    "units from ephys into dataframes - `trials_df` and `units_df`, respectively.  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "trials_df = nwbfile.trials.to_dataframe()\n",
+    "units_df = nwbfile.units.to_dataframe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>start_time</th>\n",
+       "      <th>stop_time</th>\n",
+       "      <th>trial</th>\n",
+       "      <th>photostim_onset</th>\n",
+       "      <th>photostim_power</th>\n",
+       "      <th>photostim_duration</th>\n",
+       "      <th>trial_uid</th>\n",
+       "      <th>task</th>\n",
+       "      <th>task_protocol</th>\n",
+       "      <th>trial_instruction</th>\n",
+       "      <th>early_lick</th>\n",
+       "      <th>outcome</th>\n",
+       "      <th>auto_water</th>\n",
+       "      <th>free_water</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>id</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.0000</td>\n",
+       "      <td>5.5544</td>\n",
+       "      <td>1</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>1</td>\n",
+       "      <td>audio delay</td>\n",
+       "      <td>1</td>\n",
+       "      <td>right</td>\n",
+       "      <td>early</td>\n",
+       "      <td>hit</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>11.8208</td>\n",
+       "      <td>22.2921</td>\n",
+       "      <td>2</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>2</td>\n",
+       "      <td>audio delay</td>\n",
+       "      <td>1</td>\n",
+       "      <td>right</td>\n",
+       "      <td>early</td>\n",
+       "      <td>hit</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>24.0940</td>\n",
+       "      <td>30.4805</td>\n",
+       "      <td>3</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>3</td>\n",
+       "      <td>audio delay</td>\n",
+       "      <td>1</td>\n",
+       "      <td>right</td>\n",
+       "      <td>early</td>\n",
+       "      <td>hit</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>33.1364</td>\n",
+       "      <td>39.9460</td>\n",
+       "      <td>4</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>4</td>\n",
+       "      <td>audio delay</td>\n",
+       "      <td>1</td>\n",
+       "      <td>right</td>\n",
+       "      <td>early</td>\n",
+       "      <td>ignore</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>41.7374</td>\n",
+       "      <td>46.7201</td>\n",
+       "      <td>5</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>5</td>\n",
+       "      <td>audio delay</td>\n",
+       "      <td>1</td>\n",
+       "      <td>right</td>\n",
+       "      <td>no early</td>\n",
+       "      <td>hit</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>655</th>\n",
+       "      <td>4766.5699</td>\n",
+       "      <td>4771.5319</td>\n",
+       "      <td>656</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>656</td>\n",
+       "      <td>audio delay</td>\n",
+       "      <td>1</td>\n",
+       "      <td>right</td>\n",
+       "      <td>no early</td>\n",
+       "      <td>hit</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>656</th>\n",
+       "      <td>4773.9950</td>\n",
+       "      <td>4778.8603</td>\n",
+       "      <td>657</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>657</td>\n",
+       "      <td>audio delay</td>\n",
+       "      <td>1</td>\n",
+       "      <td>right</td>\n",
+       "      <td>no early</td>\n",
+       "      <td>hit</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>657</th>\n",
+       "      <td>4781.3120</td>\n",
+       "      <td>4785.1642</td>\n",
+       "      <td>658</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>658</td>\n",
+       "      <td>audio delay</td>\n",
+       "      <td>1</td>\n",
+       "      <td>left</td>\n",
+       "      <td>no early</td>\n",
+       "      <td>miss</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>658</th>\n",
+       "      <td>4787.8274</td>\n",
+       "      <td>4792.9458</td>\n",
+       "      <td>659</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>659</td>\n",
+       "      <td>audio delay</td>\n",
+       "      <td>1</td>\n",
+       "      <td>left</td>\n",
+       "      <td>no early</td>\n",
+       "      <td>hit</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>659</th>\n",
+       "      <td>4795.4072</td>\n",
+       "      <td>4799.2389</td>\n",
+       "      <td>660</td>\n",
+       "      <td>1.891</td>\n",
+       "      <td>5.500</td>\n",
+       "      <td>0.5000</td>\n",
+       "      <td>660</td>\n",
+       "      <td>audio delay</td>\n",
+       "      <td>1</td>\n",
+       "      <td>left</td>\n",
+       "      <td>no early</td>\n",
+       "      <td>miss</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>660 rows × 14 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     start_time  stop_time  trial photostim_onset photostim_power  \\\n",
+       "id                                                                  \n",
+       "0        0.0000     5.5544      1             N/A             N/A   \n",
+       "1       11.8208    22.2921      2             N/A             N/A   \n",
+       "2       24.0940    30.4805      3             N/A             N/A   \n",
+       "3       33.1364    39.9460      4             N/A             N/A   \n",
+       "4       41.7374    46.7201      5             N/A             N/A   \n",
+       "..          ...        ...    ...             ...             ...   \n",
+       "655   4766.5699  4771.5319    656             N/A             N/A   \n",
+       "656   4773.9950  4778.8603    657             N/A             N/A   \n",
+       "657   4781.3120  4785.1642    658             N/A             N/A   \n",
+       "658   4787.8274  4792.9458    659             N/A             N/A   \n",
+       "659   4795.4072  4799.2389    660           1.891           5.500   \n",
+       "\n",
+       "    photostim_duration  trial_uid         task  task_protocol  \\\n",
+       "id                                                              \n",
+       "0                  N/A          1  audio delay              1   \n",
+       "1                  N/A          2  audio delay              1   \n",
+       "2                  N/A          3  audio delay              1   \n",
+       "3                  N/A          4  audio delay              1   \n",
+       "4                  N/A          5  audio delay              1   \n",
+       "..                 ...        ...          ...            ...   \n",
+       "655                N/A        656  audio delay              1   \n",
+       "656                N/A        657  audio delay              1   \n",
+       "657                N/A        658  audio delay              1   \n",
+       "658                N/A        659  audio delay              1   \n",
+       "659             0.5000        660  audio delay              1   \n",
+       "\n",
+       "    trial_instruction early_lick outcome  auto_water  free_water  \n",
+       "id                                                                \n",
+       "0               right      early     hit           0           0  \n",
+       "1               right      early     hit           0           0  \n",
+       "2               right      early     hit           0           0  \n",
+       "3               right      early  ignore           0           0  \n",
+       "4               right   no early     hit           0           0  \n",
+       "..                ...        ...     ...         ...         ...  \n",
+       "655             right   no early     hit           0           0  \n",
+       "656             right   no early     hit           0           0  \n",
+       "657              left   no early    miss           0           0  \n",
+       "658              left   no early     hit           0           0  \n",
+       "659              left   no early    miss           0           0  \n",
+       "\n",
+       "[660 rows x 14 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "trials_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
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+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>unit</th>\n",
+       "      <th>sampling_rate</th>\n",
+       "      <th>unit_quality</th>\n",
+       "      <th>unit_posx</th>\n",
+       "      <th>unit_posy</th>\n",
+       "      <th>unit_amp</th>\n",
+       "      <th>unit_snr</th>\n",
+       "      <th>isi_violation</th>\n",
+       "      <th>avg_firing_rate</th>\n",
+       "      <th>drift_metric</th>\n",
+       "      <th>...</th>\n",
+       "      <th>velocity_above</th>\n",
+       "      <th>velocity_below</th>\n",
+       "      <th>classification</th>\n",
+       "      <th>anno_name</th>\n",
+       "      <th>spike_times</th>\n",
+       "      <th>obs_intervals</th>\n",
+       "      <th>electrodes</th>\n",
+       "      <th>electrode_group</th>\n",
+       "      <th>waveform_mean</th>\n",
+       "      <th>waveform_sd</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>id</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
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+       "      <th></th>\n",
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+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>good</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>147.217681</td>\n",
+       "      <td>8.037514</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.413650</td>\n",
+       "      <td>0.018182</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.686771</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>unlabelled</td>\n",
+       "      <td></td>\n",
+       "      <td>[19.228361858212644, 25.16561393995109, 28.914...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>l...</td>\n",
+       "      <td>17216703352 1-301 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[2.5724660462776656, 2.1456866197183095, 1.966...</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>multi</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>86.126430</td>\n",
+       "      <td>4.787742</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.095506</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>unlabelled</td>\n",
+       "      <td></td>\n",
+       "      <td>[8.136125511297582, 8.235526053858877, 14.2586...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>l...</td>\n",
+       "      <td>17216703352 1-301 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[0.16850490196078433, 0.4238153594771242, 0.19...</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>good</td>\n",
+       "      <td>43.0</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>64.746094</td>\n",
+       "      <td>3.552861</td>\n",
+       "      <td>0.002653</td>\n",
+       "      <td>17.324200</td>\n",
+       "      <td>0.154545</td>\n",
+       "      <td>...</td>\n",
+       "      <td>10.988300</td>\n",
+       "      <td>-6.180940</td>\n",
+       "      <td>unlabelled</td>\n",
+       "      <td></td>\n",
+       "      <td>[-0.3295540305365834, -0.19785331167015974, 0....</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>l...</td>\n",
+       "      <td>17216703352 1-301 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[-2.0531439012096775, -1.9397366431451613, -1....</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>good</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>60.0</td>\n",
+       "      <td>56.539984</td>\n",
+       "      <td>2.954013</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.285685</td>\n",
+       "      <td>0.072727</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.515078</td>\n",
+       "      <td>0.480740</td>\n",
+       "      <td>good</td>\n",
+       "      <td>Anterior olfactory nucleus</td>\n",
+       "      <td>[16.85488223630304, 17.939621490504805, 18.021...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>l...</td>\n",
+       "      <td>17216703352 1-301 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[0.7641921397379913, 0.56632096069869, 0.82901...</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>good</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>60.036058</td>\n",
+       "      <td>3.331454</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.005410</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.262633</td>\n",
+       "      <td>-0.343385</td>\n",
+       "      <td>unlabelled</td>\n",
+       "      <td></td>\n",
+       "      <td>[17.38181844582985, 441.68083391373926, 564.16...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>l...</td>\n",
+       "      <td>17216703352 1-301 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[-0.18028846153846154, 0.3605769230769231, -0....</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2111</th>\n",
+       "      <td>505</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>good</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>1440.0</td>\n",
+       "      <td>297.534180</td>\n",
+       "      <td>6.342309</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.099875</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-0.343388</td>\n",
+       "      <td>good</td>\n",
+       "      <td>Midbrain reticular nucleus</td>\n",
+       "      <td>[15.20743573111292, 16.26698295628765, 16.4064...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>18005107871 1-384 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[-4.755859375, -5.0830078125, -3.9892578125, -...</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2112</th>\n",
+       "      <td>506</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>good</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>1560.0</td>\n",
+       "      <td>98.612035</td>\n",
+       "      <td>2.571565</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.019559</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>24.037200</td>\n",
+       "      <td>-1.373550</td>\n",
+       "      <td>unlabelled</td>\n",
+       "      <td></td>\n",
+       "      <td>[8.793836569035015, 277.82287333129483, 354.28...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>18005107871 1-384 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[5.759640957446808, 5.659906914893617, 6.65724...</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2113</th>\n",
+       "      <td>507</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>multi</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>1640.0</td>\n",
+       "      <td>172.346166</td>\n",
+       "      <td>4.056073</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.121098</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>8.928090</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>unlabelled</td>\n",
+       "      <td></td>\n",
+       "      <td>[1.2496709899752019, 33.18653497590302, 34.357...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>18005107871 1-384 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[-2.009503865979381, -2.3477770618556697, -2.7...</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2114</th>\n",
+       "      <td>508</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>multi</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>2300.0</td>\n",
+       "      <td>124.163167</td>\n",
+       "      <td>3.079136</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.052642</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.637721</td>\n",
+       "      <td>-0.722299</td>\n",
+       "      <td>unlabelled</td>\n",
+       "      <td></td>\n",
+       "      <td>[1.2787047039727852, 1.4934741865060008, 80.67...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>18005107871 1-384 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[-1.1950345849802373, -1.0653409090909092, -1....</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2115</th>\n",
+       "      <td>509</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>multi</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>2740.0</td>\n",
+       "      <td>106.171875</td>\n",
+       "      <td>3.267464</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.002081</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-1.327770</td>\n",
+       "      <td>-0.302509</td>\n",
+       "      <td>unlabelled</td>\n",
+       "      <td></td>\n",
+       "      <td>[134.56330014589082, 877.815221847931, 877.999...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>18005107871 1-384 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[3.28125, 2.578125, -0.9375, -1.640625, 3.9843...</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>2116 rows × 36 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      unit  sampling_rate unit_quality  unit_posx  unit_posy    unit_amp  \\\n",
+       "id                                                                         \n",
+       "0        0          30000         good       59.0        0.0  147.217681   \n",
+       "1        1          30000        multi       11.0       20.0   86.126430   \n",
+       "2        2          30000         good       43.0       20.0   64.746094   \n",
+       "3        3          30000         good       11.0       60.0   56.539984   \n",
+       "4        4          30000         good       27.0       40.0   60.036058   \n",
+       "...    ...            ...          ...        ...        ...         ...   \n",
+       "2111   505          30000         good       59.0     1440.0  297.534180   \n",
+       "2112   506          30000         good       59.0     1560.0   98.612035   \n",
+       "2113   507          30000        multi       59.0     1640.0  172.346166   \n",
+       "2114   508          30000        multi       11.0     2300.0  124.163167   \n",
+       "2115   509          30000        multi       11.0     2740.0  106.171875   \n",
+       "\n",
+       "      unit_snr  isi_violation  avg_firing_rate  drift_metric  ...  \\\n",
+       "id                                                            ...   \n",
+       "0     8.037514       0.000000         0.413650      0.018182  ...   \n",
+       "1     4.787742       0.000000         0.095506      0.000000  ...   \n",
+       "2     3.552861       0.002653        17.324200      0.154545  ...   \n",
+       "3     2.954013       0.000000         0.285685      0.072727  ...   \n",
+       "4     3.331454       0.000000         0.005410      1.000000  ...   \n",
+       "...        ...            ...              ...           ...  ...   \n",
+       "2111  6.342309       0.000000         0.099875      0.000000  ...   \n",
+       "2112  2.571565       0.000000         0.019559      1.000000  ...   \n",
+       "2113  4.056073       0.000000         0.121098      0.000000  ...   \n",
+       "2114  3.079136       0.000000         0.052642      0.000000  ...   \n",
+       "2115  3.267464       0.000000         0.002081      1.000000  ...   \n",
+       "\n",
+       "      velocity_above  velocity_below  classification  \\\n",
+       "id                                                     \n",
+       "0           0.686771             NaN      unlabelled   \n",
+       "1           0.000000        0.000000      unlabelled   \n",
+       "2          10.988300       -6.180940      unlabelled   \n",
+       "3          -0.515078        0.480740            good   \n",
+       "4          -0.262633       -0.343385      unlabelled   \n",
+       "...              ...             ...             ...   \n",
+       "2111        0.000000       -0.343388            good   \n",
+       "2112       24.037200       -1.373550      unlabelled   \n",
+       "2113        8.928090             NaN      unlabelled   \n",
+       "2114        0.637721       -0.722299      unlabelled   \n",
+       "2115       -1.327770       -0.302509      unlabelled   \n",
+       "\n",
+       "                       anno_name  \\\n",
+       "id                                 \n",
+       "0                                  \n",
+       "1                                  \n",
+       "2                                  \n",
+       "3     Anterior olfactory nucleus   \n",
+       "4                                  \n",
+       "...                          ...   \n",
+       "2111  Midbrain reticular nucleus   \n",
+       "2112                               \n",
+       "2113                               \n",
+       "2114                               \n",
+       "2115                               \n",
+       "\n",
+       "                                            spike_times  \\\n",
+       "id                                                        \n",
+       "0     [19.228361858212644, 25.16561393995109, 28.914...   \n",
+       "1     [8.136125511297582, 8.235526053858877, 14.2586...   \n",
+       "2     [-0.3295540305365834, -0.19785331167015974, 0....   \n",
+       "3     [16.85488223630304, 17.939621490504805, 18.021...   \n",
+       "4     [17.38181844582985, 441.68083391373926, 564.16...   \n",
+       "...                                                 ...   \n",
+       "2111  [15.20743573111292, 16.26698295628765, 16.4064...   \n",
+       "2112  [8.793836569035015, 277.82287333129483, 354.28...   \n",
+       "2113  [1.2496709899752019, 33.18653497590302, 34.357...   \n",
+       "2114  [1.2787047039727852, 1.4934741865060008, 80.67...   \n",
+       "2115  [134.56330014589082, 877.815221847931, 877.999...   \n",
+       "\n",
+       "                                          obs_intervals  \\\n",
+       "id                                                        \n",
+       "0     [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "1     [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "2     [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "3     [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "4     [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "...                                                 ...   \n",
+       "2111  [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "2112  [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "2113  [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "2114  [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "2115  [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "\n",
+       "                                             electrodes  \\\n",
+       "id                                                        \n",
+       "0                                                  l...   \n",
+       "1                                                  l...   \n",
+       "2                                                  l...   \n",
+       "3                                                  l...   \n",
+       "4                                                  l...   \n",
+       "...                                                 ...   \n",
+       "2111                                                ...   \n",
+       "2112                                                ...   \n",
+       "2113                                                ...   \n",
+       "2114                                                ...   \n",
+       "2115                                                ...   \n",
+       "\n",
+       "                                        electrode_group  \\\n",
+       "id                                                        \n",
+       "0     17216703352 1-301 pynwb.ecephys.ElectrodeGroup...   \n",
+       "1     17216703352 1-301 pynwb.ecephys.ElectrodeGroup...   \n",
+       "2     17216703352 1-301 pynwb.ecephys.ElectrodeGroup...   \n",
+       "3     17216703352 1-301 pynwb.ecephys.ElectrodeGroup...   \n",
+       "4     17216703352 1-301 pynwb.ecephys.ElectrodeGroup...   \n",
+       "...                                                 ...   \n",
+       "2111  18005107871 1-384 pynwb.ecephys.ElectrodeGroup...   \n",
+       "2112  18005107871 1-384 pynwb.ecephys.ElectrodeGroup...   \n",
+       "2113  18005107871 1-384 pynwb.ecephys.ElectrodeGroup...   \n",
+       "2114  18005107871 1-384 pynwb.ecephys.ElectrodeGroup...   \n",
+       "2115  18005107871 1-384 pynwb.ecephys.ElectrodeGroup...   \n",
+       "\n",
+       "                                          waveform_mean  waveform_sd  \n",
+       "id                                                                    \n",
+       "0     [2.5724660462776656, 2.1456866197183095, 1.966...        [nan]  \n",
+       "1     [0.16850490196078433, 0.4238153594771242, 0.19...        [nan]  \n",
+       "2     [-2.0531439012096775, -1.9397366431451613, -1....        [nan]  \n",
+       "3     [0.7641921397379913, 0.56632096069869, 0.82901...        [nan]  \n",
+       "4     [-0.18028846153846154, 0.3605769230769231, -0....        [nan]  \n",
+       "...                                                 ...          ...  \n",
+       "2111  [-4.755859375, -5.0830078125, -3.9892578125, -...        [nan]  \n",
+       "2112  [5.759640957446808, 5.659906914893617, 6.65724...        [nan]  \n",
+       "2113  [-2.009503865979381, -2.3477770618556697, -2.7...        [nan]  \n",
+       "2114  [-1.1950345849802373, -1.0653409090909092, -1....        [nan]  \n",
+       "2115  [3.28125, 2.578125, -0.9375, -1.640625, 3.9843...        [nan]  \n",
+       "\n",
+       "[2116 rows x 36 columns]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "units_df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The units dataframe contains information such as `unit_quality`, `spike_times`,\n",
+    "and even the CCF location of the electrode for each unit. In the cell below, we'll write a\n",
+    "function that returns the x, y and z CCF coordinates for a given unit in the\n",
+    "`units_df`.\n",
+    "\n",
+    "**Please Note:** x, y, and z are described in the pipeline as follows:\n",
+    "\n",
+    "    ccf_x   :  int   # (um)  Left-to-Right (ML axis)\n",
+    "    ccf_y   :  int   # (um)  Superior-to-Inferior (DV axis)\n",
+    "    ccf_z   :  int   # (um)  Anterior-to-Posterior (AP axis)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_ccf(unit_number):\n",
+    "    x = float(units_df.electrodes[unit_number].reset_index().x.values)\n",
+    "    y = float(units_df.electrodes[unit_number].reset_index().y.values)\n",
+    "    z = float(units_df.electrodes[unit_number].reset_index().z.values)\n",
+    "    return x, y, z"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "x_ccf = 7200.0\n",
+      "y_ccf = 2400.0\n",
+      "z_ccf = 2500.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "x_ccf, y_ccf, z_ccf = get_ccf(unit_number=150)\n",
+    "\n",
+    "print(f\"x_ccf = {x_ccf}\")\n",
+    "print(f\"y_ccf = {y_ccf}\")\n",
+    "print(f\"z_ccf = {z_ccf}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can further filter the dataframes to suit your analysis goals. For example,\n",
+    "we will filter the `trials_df` to only show the entries that contain `photostim`\n",
+    "and where the outcome is a `hit`.\n",
+    "We will also filter the `units_df` to only show units with \"good\"\n",
+    "`classification` quality."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "trials = trials_df.query(\"photostim_onset != 'N/A' and outcome == 'hit'\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "units = units_df.query(\"classification == 'good'\").reset_index()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>unit</th>\n",
+       "      <th>sampling_rate</th>\n",
+       "      <th>unit_quality</th>\n",
+       "      <th>unit_posx</th>\n",
+       "      <th>unit_posy</th>\n",
+       "      <th>unit_amp</th>\n",
+       "      <th>unit_snr</th>\n",
+       "      <th>isi_violation</th>\n",
+       "      <th>avg_firing_rate</th>\n",
+       "      <th>...</th>\n",
+       "      <th>velocity_above</th>\n",
+       "      <th>velocity_below</th>\n",
+       "      <th>classification</th>\n",
+       "      <th>anno_name</th>\n",
+       "      <th>spike_times</th>\n",
+       "      <th>obs_intervals</th>\n",
+       "      <th>electrodes</th>\n",
+       "      <th>electrode_group</th>\n",
+       "      <th>waveform_mean</th>\n",
+       "      <th>waveform_sd</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>good</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>60.0</td>\n",
+       "      <td>56.539984</td>\n",
+       "      <td>2.954013</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.285685</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.515078</td>\n",
+       "      <td>0.480740</td>\n",
+       "      <td>good</td>\n",
+       "      <td>Anterior olfactory nucleus</td>\n",
+       "      <td>[16.85488223630304, 17.939621490504805, 18.021...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>l...</td>\n",
+       "      <td>17216703352 1-301 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[0.7641921397379913, 0.56632096069869, 0.82901...</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>8</td>\n",
+       "      <td>8</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>good</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>300.0</td>\n",
+       "      <td>114.756332</td>\n",
+       "      <td>5.388086</td>\n",
+       "      <td>0.037909</td>\n",
+       "      <td>3.299630</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.371609</td>\n",
+       "      <td>0.426272</td>\n",
+       "      <td>good</td>\n",
+       "      <td>Anterior olfactory nucleus</td>\n",
+       "      <td>[-0.02451903222055085, 0.44261685089614433, 1....</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>l...</td>\n",
+       "      <td>17216703352 1-301 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[-1.3679750504032258, -1.216765372983871, -1.1...</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>9</td>\n",
+       "      <td>9</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>good</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>320.0</td>\n",
+       "      <td>337.810382</td>\n",
+       "      <td>13.569296</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.196630</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.902027</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>good</td>\n",
+       "      <td>Anterior olfactory nucleus</td>\n",
+       "      <td>[-0.3466541238745928, -0.3245873367600467, 1.5...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>l...</td>\n",
+       "      <td>17216703352 1-301 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[-5.366918665276329, -5.335147288842545, -5.42...</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>good</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>340.0</td>\n",
+       "      <td>236.101562</td>\n",
+       "      <td>8.838941</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.249688</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.166600</td>\n",
+       "      <td>-1.983600</td>\n",
+       "      <td>good</td>\n",
+       "      <td>Anterior olfactory nucleus</td>\n",
+       "      <td>[3.5245003395101864, 19.96236586465118, 24.589...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>l...</td>\n",
+       "      <td>17216703352 1-301 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[-3.87109375, -3.41015625, -3.62890625, -4.511...</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>13</td>\n",
+       "      <td>13</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>good</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>360.0</td>\n",
+       "      <td>251.819987</td>\n",
+       "      <td>12.015720</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.554932</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.904400</td>\n",
+       "      <td>-2.895710</td>\n",
+       "      <td>good</td>\n",
+       "      <td>Anterior olfactory nucleus</td>\n",
+       "      <td>[3.5243336719337925, 3.5277003569769483, 3.537...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>l...</td>\n",
+       "      <td>17216703352 1-301 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[4.350042182227221, 4.002038807649043, 4.17076...</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>529</th>\n",
+       "      <td>2091</td>\n",
+       "      <td>485</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>good</td>\n",
+       "      <td>43.0</td>\n",
+       "      <td>1860.0</td>\n",
+       "      <td>126.615050</td>\n",
+       "      <td>2.959896</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.417601</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.343388</td>\n",
+       "      <td>good</td>\n",
+       "      <td>Midbrain reticular nucleus</td>\n",
+       "      <td>[8.770836267475506, 49.82652010675252, 51.0380...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>18005107871 1-384 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[1.079035874439462, 0.5745515695067265, -0.304...</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>530</th>\n",
+       "      <td>2095</td>\n",
+       "      <td>489</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>good</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>2400.0</td>\n",
+       "      <td>163.973921</td>\n",
+       "      <td>4.276903</td>\n",
+       "      <td>0.069031</td>\n",
+       "      <td>7.943780</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.970959</td>\n",
+       "      <td>-1.013810</td>\n",
+       "      <td>good</td>\n",
+       "      <td>Superior colliculus, motor related, intermedia...</td>\n",
+       "      <td>[-0.46711818570510166, -0.13818053963374188, 0...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>18005107871 1-384 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[-0.4069841675178754, -0.7229954034729316, -1....</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>531</th>\n",
+       "      <td>2108</td>\n",
+       "      <td>502</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>multi</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>3580.0</td>\n",
+       "      <td>75.383828</td>\n",
+       "      <td>4.470425</td>\n",
+       "      <td>0.126795</td>\n",
+       "      <td>3.250500</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3.139550</td>\n",
+       "      <td>-2.609750</td>\n",
+       "      <td>good</td>\n",
+       "      <td>Retrosplenial area, ventral part, layer 1</td>\n",
+       "      <td>[3.584401600887656, 3.585334946458187, 3.98587...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>18005107871 1-384 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[2.6987909416581375, 2.5068769191402254, 2.516...</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>532</th>\n",
+       "      <td>2110</td>\n",
+       "      <td>504</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>good</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>3620.0</td>\n",
+       "      <td>143.412537</td>\n",
+       "      <td>7.007097</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.421970</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.905650</td>\n",
+       "      <td>-1.695770</td>\n",
+       "      <td>good</td>\n",
+       "      <td>Retrosplenial area, ventral part, layer 1</td>\n",
+       "      <td>[22.52149829326651, 37.43265731395145, 73.9456...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>18005107871 1-384 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[1.9138313609467454, 2.0005085059171597, 2.142...</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>533</th>\n",
+       "      <td>2111</td>\n",
+       "      <td>505</td>\n",
+       "      <td>30000</td>\n",
+       "      <td>good</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>1440.0</td>\n",
+       "      <td>297.534180</td>\n",
+       "      <td>6.342309</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.099875</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-0.343388</td>\n",
+       "      <td>good</td>\n",
+       "      <td>Midbrain reticular nucleus</td>\n",
+       "      <td>[15.20743573111292, 16.26698295628765, 16.4064...</td>\n",
+       "      <td>[[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>18005107871 1-384 pynwb.ecephys.ElectrodeGroup...</td>\n",
+       "      <td>[-4.755859375, -5.0830078125, -3.9892578125, -...</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>534 rows × 37 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       id  unit  sampling_rate unit_quality  unit_posx  unit_posy    unit_amp  \\\n",
+       "0       3     3          30000         good       11.0       60.0   56.539984   \n",
+       "1       8     8          30000         good       11.0      300.0  114.756332   \n",
+       "2       9     9          30000         good       27.0      320.0  337.810382   \n",
+       "3      10    10          30000         good       11.0      340.0  236.101562   \n",
+       "4      13    13          30000         good       59.0      360.0  251.819987   \n",
+       "..    ...   ...            ...          ...        ...        ...         ...   \n",
+       "529  2091   485          30000         good       43.0     1860.0  126.615050   \n",
+       "530  2095   489          30000         good       27.0     2400.0  163.973921   \n",
+       "531  2108   502          30000        multi       11.0     3580.0   75.383828   \n",
+       "532  2110   504          30000         good       11.0     3620.0  143.412537   \n",
+       "533  2111   505          30000         good       59.0     1440.0  297.534180   \n",
+       "\n",
+       "      unit_snr  isi_violation  avg_firing_rate  ...  velocity_above  \\\n",
+       "0     2.954013       0.000000         0.285685  ...       -0.515078   \n",
+       "1     5.388086       0.037909         3.299630  ...        0.371609   \n",
+       "2    13.569296       0.000000         1.196630  ...        0.902027   \n",
+       "3     8.838941       0.000000         0.249688  ...        2.166600   \n",
+       "4    12.015720       0.000000         0.554932  ...        1.904400   \n",
+       "..         ...            ...              ...  ...             ...   \n",
+       "529   2.959896       0.000000         0.417601  ...        0.000000   \n",
+       "530   4.276903       0.069031         7.943780  ...        0.970959   \n",
+       "531   4.470425       0.126795         3.250500  ...        3.139550   \n",
+       "532   7.007097       0.000000         0.421970  ...        1.905650   \n",
+       "533   6.342309       0.000000         0.099875  ...        0.000000   \n",
+       "\n",
+       "     velocity_below  classification  \\\n",
+       "0          0.480740            good   \n",
+       "1          0.426272            good   \n",
+       "2          0.000000            good   \n",
+       "3         -1.983600            good   \n",
+       "4         -2.895710            good   \n",
+       "..              ...             ...   \n",
+       "529        0.343388            good   \n",
+       "530       -1.013810            good   \n",
+       "531       -2.609750            good   \n",
+       "532       -1.695770            good   \n",
+       "533       -0.343388            good   \n",
+       "\n",
+       "                                             anno_name  \\\n",
+       "0                           Anterior olfactory nucleus   \n",
+       "1                           Anterior olfactory nucleus   \n",
+       "2                           Anterior olfactory nucleus   \n",
+       "3                           Anterior olfactory nucleus   \n",
+       "4                           Anterior olfactory nucleus   \n",
+       "..                                                 ...   \n",
+       "529                         Midbrain reticular nucleus   \n",
+       "530  Superior colliculus, motor related, intermedia...   \n",
+       "531          Retrosplenial area, ventral part, layer 1   \n",
+       "532          Retrosplenial area, ventral part, layer 1   \n",
+       "533                         Midbrain reticular nucleus   \n",
+       "\n",
+       "                                           spike_times  \\\n",
+       "0    [16.85488223630304, 17.939621490504805, 18.021...   \n",
+       "1    [-0.02451903222055085, 0.44261685089614433, 1....   \n",
+       "2    [-0.3466541238745928, -0.3245873367600467, 1.5...   \n",
+       "3    [3.5245003395101864, 19.96236586465118, 24.589...   \n",
+       "4    [3.5243336719337925, 3.5277003569769483, 3.537...   \n",
+       "..                                                 ...   \n",
+       "529  [8.770836267475506, 49.82652010675252, 51.0380...   \n",
+       "530  [-0.46711818570510166, -0.13818053963374188, 0...   \n",
+       "531  [3.584401600887656, 3.585334946458187, 3.98587...   \n",
+       "532  [22.52149829326651, 37.43265731395145, 73.9456...   \n",
+       "533  [15.20743573111292, 16.26698295628765, 16.4064...   \n",
+       "\n",
+       "                                         obs_intervals  \\\n",
+       "0    [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "1    [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "2    [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "3    [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "4    [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "..                                                 ...   \n",
+       "529  [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "530  [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "531  [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "532  [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "533  [[0.0, 5.5544], [11.8208, 22.2921], [24.094, 3...   \n",
+       "\n",
+       "                                            electrodes  \\\n",
+       "0                                                 l...   \n",
+       "1                                                 l...   \n",
+       "2                                                 l...   \n",
+       "3                                                 l...   \n",
+       "4                                                 l...   \n",
+       "..                                                 ...   \n",
+       "529                                                ...   \n",
+       "530                                                ...   \n",
+       "531                                                ...   \n",
+       "532                                                ...   \n",
+       "533                                                ...   \n",
+       "\n",
+       "                                       electrode_group  \\\n",
+       "0    17216703352 1-301 pynwb.ecephys.ElectrodeGroup...   \n",
+       "1    17216703352 1-301 pynwb.ecephys.ElectrodeGroup...   \n",
+       "2    17216703352 1-301 pynwb.ecephys.ElectrodeGroup...   \n",
+       "3    17216703352 1-301 pynwb.ecephys.ElectrodeGroup...   \n",
+       "4    17216703352 1-301 pynwb.ecephys.ElectrodeGroup...   \n",
+       "..                                                 ...   \n",
+       "529  18005107871 1-384 pynwb.ecephys.ElectrodeGroup...   \n",
+       "530  18005107871 1-384 pynwb.ecephys.ElectrodeGroup...   \n",
+       "531  18005107871 1-384 pynwb.ecephys.ElectrodeGroup...   \n",
+       "532  18005107871 1-384 pynwb.ecephys.ElectrodeGroup...   \n",
+       "533  18005107871 1-384 pynwb.ecephys.ElectrodeGroup...   \n",
+       "\n",
+       "                                         waveform_mean  waveform_sd  \n",
+       "0    [0.7641921397379913, 0.56632096069869, 0.82901...        [nan]  \n",
+       "1    [-1.3679750504032258, -1.216765372983871, -1.1...        [nan]  \n",
+       "2    [-5.366918665276329, -5.335147288842545, -5.42...        [nan]  \n",
+       "3    [-3.87109375, -3.41015625, -3.62890625, -4.511...        [nan]  \n",
+       "4    [4.350042182227221, 4.002038807649043, 4.17076...        [nan]  \n",
+       "..                                                 ...          ...  \n",
+       "529  [1.079035874439462, 0.5745515695067265, -0.304...        [nan]  \n",
+       "530  [-0.4069841675178754, -0.7229954034729316, -1....        [nan]  \n",
+       "531  [2.6987909416581375, 2.5068769191402254, 2.516...        [nan]  \n",
+       "532  [1.9138313609467454, 2.0005085059171597, 2.142...        [nan]  \n",
+       "533  [-4.755859375, -5.0830078125, -3.9892578125, -...        [nan]  \n",
+       "\n",
+       "[534 rows x 37 columns]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "units"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can align spikes from good units to photostim onset and plot rasters to\n",
+    "explore how and whether there is evoked neural activity at `photostim_onset`. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "before = 1.0  # in seconds\n",
+    "after = 3.0\n",
+    "\n",
+    "# Get the stimulus times for all stimuli\n",
+    "stim_on_times =trials[\"start_time\"] + trials[\"photostim_onset\"].values.astype(\"float\")\n",
+    "\n",
+    "for unit in range(3):\n",
+    "    unit_spike_times = units[\"spike_times\"][unit]\n",
+    "    trial_spikes = []\n",
+    "    for time in stim_on_times:\n",
+    "        # Compute spike times relative to stimulus onset\n",
+    "        aligned_spikes = unit_spike_times - time\n",
+    "        # Keep only spike times in a given time window around the stimulus onset\n",
+    "        aligned_spikes = aligned_spikes[\n",
+    "            (-before < aligned_spikes) & (aligned_spikes < after)\n",
+    "        ]\n",
+    "        trial_spikes.append(aligned_spikes)\n",
+    "    fig, axs = plt.subplots(2, 1, sharex=\"all\")\n",
+    "    plt.xlabel(\"time (s)\")\n",
+    "    axs[0].eventplot(trial_spikes)\n",
+    "\n",
+    "    axs[0].set_ylabel(\"trial\")\n",
+    "    axs[0].set_title(\"unit {}\".format(unit))\n",
+    "    axs[0].axvline(0, color=[0.5, 0.5, 0.5])\n",
+    "\n",
+    "    axs[1].hist(np.hstack(trial_spikes), 30)\n",
+    "    axs[1].axvline(0, color=[0.5, 0.5, 0.5])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The NWB file also contains behavior tracking data which is found in `nwbfile.acquisition`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'BehavioralEvents': BehavioralEvents pynwb.behavior.BehavioralEvents at 0x2750574574512\n",
+       " Fields:\n",
+       "   time_series: {\n",
+       "     delay_start_times <class 'pynwb.base.TimeSeries'>,\n",
+       "     delay_stop_times <class 'pynwb.base.TimeSeries'>,\n",
+       "     go_start_times <class 'pynwb.base.TimeSeries'>,\n",
+       "     go_stop_times <class 'pynwb.base.TimeSeries'>,\n",
+       "     left_lick_times <class 'pynwb.base.TimeSeries'>,\n",
+       "     photostim_start_times <class 'pynwb.base.TimeSeries'>,\n",
+       "     photostim_stop_times <class 'pynwb.base.TimeSeries'>,\n",
+       "     presample_start_times <class 'pynwb.base.TimeSeries'>,\n",
+       "     presample_stop_times <class 'pynwb.base.TimeSeries'>,\n",
+       "     right_lick_times <class 'pynwb.base.TimeSeries'>,\n",
+       "     sample_start_times <class 'pynwb.base.TimeSeries'>,\n",
+       "     sample_stop_times <class 'pynwb.base.TimeSeries'>,\n",
+       "     trialend_start_times <class 'pynwb.base.TimeSeries'>,\n",
+       "     trialend_stop_times <class 'pynwb.base.TimeSeries'>\n",
+       "   },\n",
+       " 'BehavioralTimeSeries': BehavioralTimeSeries pynwb.behavior.BehavioralTimeSeries at 0x2750574822736\n",
+       " Fields:\n",
+       "   time_series: {\n",
+       "     Camera0_side_JawTracking <class 'pynwb.base.TimeSeries'>,\n",
+       "     Camera0_side_NoseTracking <class 'pynwb.base.TimeSeries'>,\n",
+       "     Camera0_side_TongueTracking <class 'pynwb.base.TimeSeries'>\n",
+       "   }}"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nwbfile.acquisition"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The cell below fetches the timestamps for jaw tracking for camera 0. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "camera0_jawTracking_ts = nwbfile.acquisition[\"BehavioralTimeSeries\"][\"Camera0_side_JawTracking\"].timestamps[:]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Here, we can create a function to plot trialized jaw movement overlaid with\n",
+    "spiking activity from a particular unit"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_trialized_jaw_movement(unit, title='left lick trials', trial_offset=0, trial_limit=10, xlim=(-0.5, 1)):   \n",
+    "    tongue_likelihood = nwbfile.acquisition['BehavioralTimeSeries']['Camera0_side_TongueTracking'].data[:, -1]\n",
+    "    \n",
+    "    tracking_y = nwbfile.acquisition['BehavioralTimeSeries']['Camera0_side_JawTracking'].data[:, 0]\n",
+    "    tracking_ts = nwbfile.acquisition['BehavioralTimeSeries']['Camera0_side_JawTracking'].timestamps\n",
+    "    \n",
+    "    left_licks_trials = nwbfile.trials.to_dataframe().query(\"trial_instruction == 'left' and early_lick == 'no early' and outcome == 'hit'\")\n",
+    "    right_licks_trials = nwbfile.trials.to_dataframe().query(\"trial_instruction == 'right' and early_lick == 'no early' and outcome == 'hit'\")\n",
+    "    left_lick_times = nwbfile.acquisition['BehavioralEvents']['left_lick_times'].timestamps\n",
+    "    right_lick_times = nwbfile.acquisition['BehavioralEvents']['right_lick_times'].timestamps\n",
+    "    \n",
+    "    fig, axs = plt.subplots(1, 2, figsize=(16, 8))\n",
+    "    h_spacing = 150\n",
+    "    \n",
+    "    unit_data = units_df.query(f'id == {unit}').iloc[0]\n",
+    "    \n",
+    "    for conditioned_trials_df, lick_times, ax, ax_name, spk_color in zip(\n",
+    "        (left_licks_trials, right_licks_trials),\n",
+    "        (left_lick_times, right_lick_times),\n",
+    "        axs, \n",
+    "        ('left lick trials', 'right lick trials'),\n",
+    "        ('b', 'r')): \n",
+    "        \n",
+    "        if trial_offset < 1 and isinstance(trial_offset, float):\n",
+    "            offset = int(len(conditioned_trials_df) * trial_offset)\n",
+    "        else:\n",
+    "            offset = trial_offset\n",
+    "        \n",
+    "        trial_numbers = conditioned_trials_df.trial[offset:offset+trial_limit].values\n",
+    "\n",
+    "        _, row_ind, _ = np.intersect1d(trials_df.trial.values, trial_numbers, return_indices=True)\n",
+    "\n",
+    "        for tr_id, row_id in enumerate(row_ind):\n",
+    "            trial_data = trials_df.iloc[row_id]\n",
+    "            align_time = lick_times[np.logical_and(lick_times >= trial_data.start_time, \n",
+    "                                           lick_times < trial_data.stop_time)][0]\n",
+    "\n",
+    "            trk_feat = tracking_y[np.logical_and(tracking_ts >= align_time + xlim[0], \n",
+    "                                                           tracking_ts < align_time + xlim[-1])]\n",
+    "            tongue_out_bool = tongue_likelihood[np.logical_and(tracking_ts >= align_time + xlim[0], \n",
+    "                                                           tracking_ts < align_time + xlim[-1])] > 0.9\n",
+    "\n",
+    "            spike_times = unit_data.spike_times[np.logical_and(unit_data.spike_times >= align_time + xlim[0], \n",
+    "                                                           unit_data.spike_times < align_time + xlim[-1])]\n",
+    "            spike_times -= align_time\n",
+    "\n",
+    "            tvec = np.linspace(*xlim, len(trk_feat))\n",
+    "\n",
+    "            # plot\n",
+    "            ax.plot(tvec, trk_feat + tr_id * h_spacing, '.k', markersize=1)\n",
+    "            ax.plot(tvec[tongue_out_bool], trk_feat[tongue_out_bool] + tr_id * h_spacing, '.', color='lime', markersize=2)\n",
+    "            ax.plot(spike_times, np.full_like(spike_times, trk_feat[tongue_out_bool].mean() + h_spacing/10) + tr_id * h_spacing,\n",
+    "                    '|', color=spk_color, markersize=4)\n",
+    "\n",
+    "\n",
+    "        ax.set_title(ax_name)\n",
+    "        ax.axvline(x=0, linestyle='--', color='k')\n",
+    "\n",
+    "        # cosmetic\n",
+    "        ax.set_xlim(xlim)\n",
+    "        ax.set_yticks([])\n",
+    "        ax.spines['left'].set_visible(False)\n",
+    "        ax.spines['right'].set_visible(False)\n",
+    "        ax.spines['top'].set_visible(False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\kusha\\AppData\\Local\\Temp\\ipykernel_32764\\3554794887.py:29: FutureWarning: The behavior of `series[i:j]` with an integer-dtype index is deprecated. In a future version, this will be treated as *label-based* indexing, consistent with e.g. `series[i]` lookups. To retain the old behavior, use `series.iloc[i:j]`. To get the future behavior, use `series.loc[i:j]`.\n",
+      "  trial_numbers = conditioned_trials_df.trial[offset:offset+trial_limit].values\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1600x800 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_trialized_jaw_movement(unit=12, trial_offset=0.5, trial_limit=15)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If you would like to work with a `.nwb` file without downloading it locally,\n",
+    "please follow the steps below: \n",
+    "\n",
+    "1. Once you find a dataset you want to work with, please update the filepath\n",
+    "variable below to match the file path on DANDI. \n",
+    "\n",
+    "2. Once updated, run the three cells below.\n",
+    "\n",
+    "The `.nwb` file is now streaming and you can bring items into memory by using code\n",
+    "similar to that in the fourth cell below this comment. \n",
+    "\n",
+    "**Please ensure the file path information is entered correctly and you are\n",
+    "working with your intended dataset.**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dandiset_id = \"000363\" \n",
+    "filepath = \"sub-440956/sub-440956_ses-20190207T120657_behavior+ecephys+ogen.nwb\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\kusha\\miniconda3\\envs\\mapEphysNWB\\lib\\site-packages\\hdmf\\spec\\namespace.py:531: UserWarning: Ignoring cached namespace 'hdmf-common' version 1.5.1 because version 1.7.0 is already loaded.\n",
+      "  warn(\"Ignoring cached namespace '%s' version %s because version %s is already loaded.\"\n",
+      "c:\\Users\\kusha\\miniconda3\\envs\\mapEphysNWB\\lib\\site-packages\\hdmf\\spec\\namespace.py:531: UserWarning: Ignoring cached namespace 'core' version 2.5.0 because version 2.6.0-alpha is already loaded.\n",
+      "  warn(\"Ignoring cached namespace '%s' version %s because version %s is already loaded.\"\n",
+      "c:\\Users\\kusha\\miniconda3\\envs\\mapEphysNWB\\lib\\site-packages\\hdmf\\spec\\namespace.py:531: UserWarning: Ignoring cached namespace 'hdmf-experimental' version 0.2.0 because version 0.4.0 is already loaded.\n",
+      "  warn(\"Ignoring cached namespace '%s' version %s because version %s is already loaded.\"\n"
+     ]
+    }
+   ],
+   "source": [
+    "with DandiAPIClient() as client:\n",
+    "    asset = client.get_dandiset(dandiset_id, \"draft\").get_asset_by_path(filepath)\n",
+    "    s3_url = asset.get_content_url(follow_redirects=1, strip_query=True)\n",
+    "fs=fsspec.filesystem(\"http\")\n",
+    "file = h5py.File(fs.open(s3_url, \"rb\"))\n",
+    "io = pynwb.NWBHDF5IO(file=file, load_namespaces=True)\n",
+    "nwbfile_stream = io.read()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <style>\n",
+       "            .container-fields {\n",
+       "                font-family: \"Open Sans\", Arial, sans-serif;\n",
+       "            }\n",
+       "            .container-fields .field-value {\n",
+       "                color: #00788E;\n",
+       "            }\n",
+       "            .container-fields details > summary {\n",
+       "                cursor: pointer;\n",
+       "                display: list-item;\n",
+       "            }\n",
+       "            .container-fields details > summary:hover {\n",
+       "                color: #0A6EAA;\n",
+       "            }\n",
+       "        </style>\n",
+       "        \n",
+       "        <script>\n",
+       "            function copyToClipboard(text) {\n",
+       "                navigator.clipboard.writeText(text).then(function() {\n",
+       "                    console.log('Copied to clipboard: ' + text);\n",
+       "                }, function(err) {\n",
+       "                    console.error('Could not copy text: ', err);\n",
+       "                });\n",
+       "            }\n",
+       "\n",
+       "            document.addEventListener('DOMContentLoaded', function() {\n",
+       "                let fieldKeys = document.querySelectorAll('.container-fields .field-key');\n",
+       "                fieldKeys.forEach(function(fieldKey) {\n",
+       "                    fieldKey.addEventListener('click', function() {\n",
+       "                        let accessCode = fieldKey.getAttribute('title').replace('Access code: ', '');\n",
+       "                        copyToClipboard(accessCode);\n",
+       "                    });\n",
+       "                });\n",
+       "            });\n",
+       "        </script>\n",
+       "        <div class='container-wrap'><div class='container-header'><div class='xr-obj-type'><h3>root (NWBFile)</h3></div></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['session_description']\">session_description:</span> <span class=\"field-value\"></span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['identifier']\">identifier:</span> <span class=\"field-value\">SC015_20190207_120657_s1</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['session_start_time']\">session_start_time:</span> <span class=\"field-value\">2019-02-07 12:06:57-06:00</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['timestamps_reference_time']\">timestamps_reference_time:</span> <span class=\"field-value\">2019-02-07 12:06:57-06:00</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['file_create_date']\"><b>file_create_date</b></summary><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-value\" title=\".fields['file_create_date'][0]\">2023-04-25 12:08:21.159278-05:00</span></div></details><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['experimenter']\">experimenter:</span> <span class=\"field-value\">('susu',)</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['related_publications']\">related_publications:</span> <span class=\"field-value\">('',)</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['acquisition']\"><b>acquisition (2)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents']\"><b>BehavioralEvents</b></summary><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']\"><b>time_series (14)</b></summary><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_start_times']\"><b>delay_start_times</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_start_times'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_start_times'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_start_times'].fields['description']\">description:</span> <span class=\"field-value\">Timestamps for event type: delay - Start Time</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_start_times'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_start_times'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_start_times'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_start_times'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_start_times'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_start_times'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_start_times'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_stop_times']\"><b>delay_stop_times</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_stop_times'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_stop_times'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_stop_times'].fields['description']\">description:</span> <span class=\"field-value\">Timestamps for event type: delay - Stop Time</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_stop_times'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_stop_times'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_stop_times'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_stop_times'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_stop_times'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_stop_times'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['delay_stop_times'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_start_times']\"><b>go_start_times</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_start_times'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_start_times'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_start_times'].fields['description']\">description:</span> <span class=\"field-value\">Timestamps for event type: go - Start Time</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_start_times'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_start_times'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_start_times'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_start_times'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_start_times'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_start_times'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_start_times'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_stop_times']\"><b>go_stop_times</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_stop_times'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_stop_times'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_stop_times'].fields['description']\">description:</span> <span class=\"field-value\">Timestamps for event type: go - Stop Time</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_stop_times'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_stop_times'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_stop_times'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_stop_times'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_stop_times'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_stop_times'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['go_stop_times'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['left_lick_times']\"><b>left_lick_times</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['left_lick_times'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['left_lick_times'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['left_lick_times'].fields['description']\">description:</span> <span class=\"field-value\">Timestamps for event type: left lick</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['left_lick_times'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['left_lick_times'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['left_lick_times'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['left_lick_times'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['left_lick_times'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['left_lick_times'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['left_lick_times'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_start_times']\"><b>photostim_start_times</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_start_times'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_start_times'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_start_times'].fields['description']\">description:</span> <span class=\"field-value\">Timestamps of the photo-stimulation and the corresponding powers (in mW) being applied</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_start_times'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_start_times'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_start_times'].fields['unit']\">unit:</span> <span class=\"field-value\">mW</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_start_times'].fields['control']\"><b>control</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_start_times'].fields['control_description']\"><b>control_description</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_start_times'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_start_times'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_start_times'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_start_times'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_stop_times']\"><b>photostim_stop_times</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_stop_times'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_stop_times'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_stop_times'].fields['description']\">description:</span> <span class=\"field-value\">Timestamps of the photo-stimulation being switched off</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_stop_times'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_stop_times'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_stop_times'].fields['unit']\">unit:</span> <span class=\"field-value\">mW</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_stop_times'].fields['control']\"><b>control</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_stop_times'].fields['control_description']\"><b>control_description</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_stop_times'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_stop_times'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_stop_times'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['photostim_stop_times'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_start_times']\"><b>presample_start_times</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_start_times'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_start_times'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_start_times'].fields['description']\">description:</span> <span class=\"field-value\">Timestamps for event type: presample - Start Time</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_start_times'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_start_times'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_start_times'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_start_times'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_start_times'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_start_times'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_start_times'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_stop_times']\"><b>presample_stop_times</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_stop_times'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_stop_times'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_stop_times'].fields['description']\">description:</span> <span class=\"field-value\">Timestamps for event type: presample - Stop Time</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_stop_times'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_stop_times'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_stop_times'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_stop_times'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_stop_times'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_stop_times'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['presample_stop_times'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['right_lick_times']\"><b>right_lick_times</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['right_lick_times'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['right_lick_times'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['right_lick_times'].fields['description']\">description:</span> <span class=\"field-value\">Timestamps for event type: right lick</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['right_lick_times'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['right_lick_times'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['right_lick_times'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['right_lick_times'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['right_lick_times'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['right_lick_times'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['right_lick_times'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_start_times']\"><b>sample_start_times</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_start_times'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_start_times'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_start_times'].fields['description']\">description:</span> <span class=\"field-value\">Timestamps for event type: sample - Start Time</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_start_times'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_start_times'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_start_times'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_start_times'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_start_times'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_start_times'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_start_times'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_stop_times']\"><b>sample_stop_times</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_stop_times'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_stop_times'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_stop_times'].fields['description']\">description:</span> <span class=\"field-value\">Timestamps for event type: sample - Stop Time</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_stop_times'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_stop_times'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_stop_times'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_stop_times'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_stop_times'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_stop_times'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['sample_stop_times'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_start_times']\"><b>trialend_start_times</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_start_times'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_start_times'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_start_times'].fields['description']\">description:</span> <span class=\"field-value\">Timestamps for event type: trialend - Start Time</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_start_times'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_start_times'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_start_times'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_start_times'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_start_times'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_start_times'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_start_times'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_stop_times']\"><b>trialend_stop_times</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_stop_times'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_stop_times'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_stop_times'].fields['description']\">description:</span> <span class=\"field-value\">Timestamps for event type: trialend - Stop Time</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_stop_times'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_stop_times'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_stop_times'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_stop_times'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_stop_times'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_stop_times'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralEvents'].fields['time_series']['trialend_stop_times'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details></details></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralTimeSeries']\"><b>BehavioralTimeSeries</b></summary><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']\"><b>time_series (3)</b></summary><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_JawTracking']\"><b>Camera0_side_JawTracking</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_JawTracking'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_JawTracking'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_JawTracking'].fields['description']\">description:</span> <span class=\"field-value\">Time series for JawTracking position: ('jaw_x', 'jaw_y', 'jaw_likelihood')</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_JawTracking'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_JawTracking'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_JawTracking'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_JawTracking'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_JawTracking'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_JawTracking'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_JawTracking'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_NoseTracking']\"><b>Camera0_side_NoseTracking</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_NoseTracking'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_NoseTracking'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_NoseTracking'].fields['description']\">description:</span> <span class=\"field-value\">Time series for NoseTracking position: ('nose_x', 'nose_y', 'nose_likelihood')</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_NoseTracking'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_NoseTracking'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_NoseTracking'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_NoseTracking'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_NoseTracking'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_NoseTracking'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_NoseTracking'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_TongueTracking']\"><b>Camera0_side_TongueTracking</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_TongueTracking'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_TongueTracking'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_TongueTracking'].fields['description']\">description:</span> <span class=\"field-value\">Time series for TongueTracking position: ('tongue_x', 'tongue_y', 'tongue_likelihood')</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_TongueTracking'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_TongueTracking'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_TongueTracking'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_TongueTracking'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_TongueTracking'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_TongueTracking'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['BehavioralTimeSeries'].fields['time_series']['Camera0_side_TongueTracking'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details></details></details></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['keywords']\"><b>keywords</b></summary></details><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['epoch_tags']\">epoch_tags:</span> <span class=\"field-value\">set()</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['electrodes']\"><b>electrodes</b></summary><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrodes'].fields['description']\">description:</span> <span class=\"field-value\">metadata about extracellular electrodes</span></div><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['electrodes'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrodes'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('location', 'group', 'group_name', 'electrode', 'shank', 'shank_col', 'shank_row', 'x', 'y', 'z', 'imp', 'filtering', 'rel_x', 'rel_y', 'rel_z')</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrodes'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorData object at 0x00000280086C19D0>, <hdmf.common.table.VectorData object at 0x00000280086C1910>, <hdmf.common.table.VectorData object at 0x00000280086C17C0>, <hdmf.common.table.VectorData object at 0x00000280086C1790>, <hdmf.common.table.VectorData object at 0x00000280086C1B50>, <hdmf.common.table.VectorData object at 0x00000280086C1BB0>, <hdmf.common.table.VectorData object at 0x00000280086C1C10>, <hdmf.common.table.VectorData object at 0x00000280086C1C70>, <hdmf.common.table.VectorData object at 0x00000280086C1CD0>, <hdmf.common.table.VectorData object at 0x00000280086C1D30>, <hdmf.common.table.VectorData object at 0x00000280086C1970>, <hdmf.common.table.VectorData object at 0x00000280086C17F0>, <hdmf.common.table.VectorData object at 0x00000280086C1A30>, <hdmf.common.table.VectorData object at 0x00000280086C1A90>, <hdmf.common.table.VectorData object at 0x00000280086C1AF0>)</span></div></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['electrode_groups']\"><b>electrode_groups (4)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['electrode_groups']['17131309211 1-281']\"><b>17131309211 1-281</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrode_groups']['17131309211 1-281'].fields['description']\">description:</span> <span class=\"field-value\">{\"probe\": \"17131309211\", \"probe_type\": \"neuropixels 1.0 - 3B\", \"electrode_config_name\": \"1-281\", \"subject_id\": 440956, \"session\": 1, \"insertion_number\": 1, \"probe_comment\": \"\", \"electrode_config_hash\": \"1497a7be87e3c11ebd33da9f574200d9\"}</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrode_groups']['17131309211 1-281'].fields['location']\">location:</span> <span class=\"field-value\">{\"brain_regions\": \"left ALM\", \"skull_reference\": \"Bregma\", \"ap_location\": \"2500.00\", \"ml_location\": \"-1500.00\", \"depth\": \"-2600.00\", \"theta\": \"15.00\", \"phi\": \"135.00\", \"beta\": \"-135.00\"}</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['electrode_groups']['17131309211 1-281'].fields['device']\"><b>device</b></summary><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrode_groups']['17131309211 1-281'].fields['device'].fields['description']\">description:</span> <span class=\"field-value\">neuropixels 1.0 - 3B</span></div></details></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['electrode_groups']['17216703352 1-281']\"><b>17216703352 1-281</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrode_groups']['17216703352 1-281'].fields['description']\">description:</span> <span class=\"field-value\">{\"probe\": \"17216703352\", \"probe_type\": \"neuropixels 1.0 - 3B\", \"electrode_config_name\": \"1-281\", \"subject_id\": 440956, \"session\": 1, \"insertion_number\": 2, \"probe_comment\": \"\", \"electrode_config_hash\": \"1497a7be87e3c11ebd33da9f574200d9\"}</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrode_groups']['17216703352 1-281'].fields['location']\">location:</span> <span class=\"field-value\">{\"brain_regions\": \"right ALM\", \"skull_reference\": \"Bregma\", \"ap_location\": \"2500.00\", \"ml_location\": \"1500.00\", \"depth\": \"-2600.00\", \"theta\": \"15.00\", \"phi\": \"45.00\", \"beta\": \"-45.00\"}</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['electrode_groups']['17216703352 1-281'].fields['device']\"><b>device</b></summary><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrode_groups']['17216703352 1-281'].fields['device'].fields['description']\">description:</span> <span class=\"field-value\">neuropixels 1.0 - 3B</span></div></details></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['electrode_groups']['18005117122 1-384']\"><b>18005117122 1-384</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrode_groups']['18005117122 1-384'].fields['description']\">description:</span> <span class=\"field-value\">{\"probe\": \"18005117122\", \"probe_type\": \"neuropixels 1.0 - 3B\", \"electrode_config_name\": \"1-384\", \"subject_id\": 440956, \"session\": 1, \"insertion_number\": 4, \"probe_comment\": \"\", \"electrode_config_hash\": \"4ae1f6ed4687467836d43369e548fe00\"}</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrode_groups']['18005117122 1-384'].fields['location']\">location:</span> <span class=\"field-value\">{\"brain_regions\": \"right Striatum\", \"skull_reference\": \"Bregma\", \"ap_location\": \"0.00\", \"ml_location\": \"2500.00\", \"depth\": \"-4200.00\", \"theta\": \"10.00\", \"phi\": \"0.00\", \"beta\": \"60.00\"}</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['electrode_groups']['18005117122 1-384'].fields['device']\"><b>device</b></summary><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrode_groups']['18005117122 1-384'].fields['device'].fields['description']\">description:</span> <span class=\"field-value\">neuropixels 1.0 - 3B</span></div></details></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['electrode_groups']['18005118502 1-384']\"><b>18005118502 1-384</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrode_groups']['18005118502 1-384'].fields['description']\">description:</span> <span class=\"field-value\">{\"probe\": \"18005118502\", \"probe_type\": \"neuropixels 1.0 - 3B\", \"electrode_config_name\": \"1-384\", \"subject_id\": 440956, \"session\": 1, \"insertion_number\": 3, \"probe_comment\": \"\", \"electrode_config_hash\": \"4ae1f6ed4687467836d43369e548fe00\"}</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrode_groups']['18005118502 1-384'].fields['location']\">location:</span> <span class=\"field-value\">{\"brain_regions\": \"left Striatum\", \"skull_reference\": \"Bregma\", \"ap_location\": \"0.00\", \"ml_location\": \"-2500.00\", \"depth\": \"-4200.00\", \"theta\": \"10.00\", \"phi\": \"180.00\", \"beta\": \"120.00\"}</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['electrode_groups']['18005118502 1-384'].fields['device']\"><b>device</b></summary><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrode_groups']['18005118502 1-384'].fields['device'].fields['description']\">description:</span> <span class=\"field-value\">neuropixels 1.0 - 3B</span></div></details></details></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['devices']\"><b>devices (5)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['devices']['17131309211 (neuropixels 1.0 - 3B)']\"><b>17131309211 (neuropixels 1.0 - 3B)</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['devices']['17131309211 (neuropixels 1.0 - 3B)'].fields['description']\">description:</span> <span class=\"field-value\">neuropixels 1.0 - 3B</span></div></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['devices']['17216703352 (neuropixels 1.0 - 3B)']\"><b>17216703352 (neuropixels 1.0 - 3B)</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['devices']['17216703352 (neuropixels 1.0 - 3B)'].fields['description']\">description:</span> <span class=\"field-value\">neuropixels 1.0 - 3B</span></div></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['devices']['18005117122 (neuropixels 1.0 - 3B)']\"><b>18005117122 (neuropixels 1.0 - 3B)</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['devices']['18005117122 (neuropixels 1.0 - 3B)'].fields['description']\">description:</span> <span class=\"field-value\">neuropixels 1.0 - 3B</span></div></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['devices']['18005118502 (neuropixels 1.0 - 3B)']\"><b>18005118502 (neuropixels 1.0 - 3B)</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['devices']['18005118502 (neuropixels 1.0 - 3B)'].fields['description']\">description:</span> <span class=\"field-value\">neuropixels 1.0 - 3B</span></div></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['devices']['OBIS470']\"><b>OBIS470</b></summary></details></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['ogen_sites']\"><b>ogen_sites (2)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['ogen_sites']['OBIS470_4']\"><b>OBIS470_4</b></summary><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['ogen_sites']['OBIS470_4'].fields['device']\"><b>device</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['ogen_sites']['OBIS470_4'].fields['description']\">description:</span> <span class=\"field-value\">excitation_duration: 0.5000</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['ogen_sites']['OBIS470_4'].fields['excitation_lambda']\">excitation_lambda:</span> <span class=\"field-value\">473.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['ogen_sites']['OBIS470_4'].fields['location']\">location:</span> <span class=\"field-value\">[{\"skull_reference\": \"Bregma\", \"ap_location\": \"2500.00\", \"ml_location\": \"-1500.00\", \"depth\": \"0.00\", \"theta\": \"15.00\", \"phi\": \"15.00\", \"brain_area\": \"ALM\"}]</span></div></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['ogen_sites']['OBIS470_6']\"><b>OBIS470_6</b></summary><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['ogen_sites']['OBIS470_6'].fields['device']\"><b>device</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['ogen_sites']['OBIS470_6'].fields['description']\">description:</span> <span class=\"field-value\">excitation_duration: 0.5000</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['ogen_sites']['OBIS470_6'].fields['excitation_lambda']\">excitation_lambda:</span> <span class=\"field-value\">473.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['ogen_sites']['OBIS470_6'].fields['location']\">location:</span> <span class=\"field-value\">[{\"skull_reference\": \"Bregma\", \"ap_location\": \"2500.00\", \"ml_location\": \"-1500.00\", \"depth\": \"0.00\", \"theta\": \"15.00\", \"phi\": \"15.00\", \"brain_area\": \"ALM\"}, {\"skull_reference\": \"Bregma\", \"ap_location\": \"2500.00\", \"ml_location\": \"1500.00\", \"depth\": \"0.00\", \"theta\": \"15.00\", \"phi\": \"15.00\", \"brain_area\": \"ALM\"}]</span></div></details></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['intervals']\"><b>intervals (1)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['intervals']['trials']\"><b>trials</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['intervals']['trials'].fields['description']\">description:</span> <span class=\"field-value\">experimental trials</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['intervals']['trials'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['intervals']['trials'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('start_time', 'stop_time', 'trial', 'photostim_onset', 'photostim_power', 'photostim_duration', 'trial_uid', 'task', 'task_protocol', 'trial_instruction', 'early_lick', 'outcome', 'auto_water', 'free_water')</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['intervals']['trials'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorData object at 0x00000280086C1C40>, <hdmf.common.table.VectorData object at 0x00000280086C1B80>, <hdmf.common.table.VectorData object at 0x00000280086CB0D0>, <hdmf.common.table.VectorData object at 0x00000280086C1F10>, <hdmf.common.table.VectorData object at 0x00000280086C1F70>, <hdmf.common.table.VectorData object at 0x00000280086C1EB0>, <hdmf.common.table.VectorData object at 0x00000280086CB190>, <hdmf.common.table.VectorData object at 0x00000280086C1DC0>, <hdmf.common.table.VectorData object at 0x00000280086CB070>, <hdmf.common.table.VectorData object at 0x00000280086CB130>, <hdmf.common.table.VectorData object at 0x00000280086C1D90>, <hdmf.common.table.VectorData object at 0x00000280086C1E50>, <hdmf.common.table.VectorData object at 0x00000280086C1850>, <hdmf.common.table.VectorData object at 0x00000280086C1DF0>)</span></div></details></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['subject']\"><b>subject</b></summary><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['description']\">description:</span> <span class=\"field-value\">SC015</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['sex']\">sex:</span> <span class=\"field-value\">M</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['species']\">species:</span> <span class=\"field-value\">Mus musculus</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['subject_id']\">subject_id:</span> <span class=\"field-value\">440956</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['date_of_birth']\">date_of_birth:</span> <span class=\"field-value\">2018-10-09 00:00:00-05:00</span></div></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['trials']\"><b>trials</b></summary><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['trials'].fields['description']\">description:</span> <span class=\"field-value\">experimental trials</span></div><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['trials'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['trials'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('start_time', 'stop_time', 'trial', 'photostim_onset', 'photostim_power', 'photostim_duration', 'trial_uid', 'task', 'task_protocol', 'trial_instruction', 'early_lick', 'outcome', 'auto_water', 'free_water')</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['trials'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorData object at 0x00000280086C1C40>, <hdmf.common.table.VectorData object at 0x00000280086C1B80>, <hdmf.common.table.VectorData object at 0x00000280086CB0D0>, <hdmf.common.table.VectorData object at 0x00000280086C1F10>, <hdmf.common.table.VectorData object at 0x00000280086C1F70>, <hdmf.common.table.VectorData object at 0x00000280086C1EB0>, <hdmf.common.table.VectorData object at 0x00000280086CB190>, <hdmf.common.table.VectorData object at 0x00000280086C1DC0>, <hdmf.common.table.VectorData object at 0x00000280086CB070>, <hdmf.common.table.VectorData object at 0x00000280086CB130>, <hdmf.common.table.VectorData object at 0x00000280086C1D90>, <hdmf.common.table.VectorData object at 0x00000280086C1E50>, <hdmf.common.table.VectorData object at 0x00000280086C1850>, <hdmf.common.table.VectorData object at 0x00000280086C1DF0>)</span></div></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['units']\"><b>units</b></summary><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['units'].fields['description']\">description:</span> <span class=\"field-value\">Autogenerated by NWBFile</span></div><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['units'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['units'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('unit', 'sampling_rate', 'unit_quality', 'unit_posx', 'unit_posy', 'unit_amp', 'unit_snr', 'isi_violation', 'avg_firing_rate', 'drift_metric', 'presence_ratio', 'amplitude_cutoff', 'isolation_distance', 'l_ratio', 'd_prime', 'nn_hit_rate', 'nn_miss_rate', 'silhouette_score', 'max_drift', 'cumulative_drift', 'duration', 'halfwidth', 'pt_ratio', 'repolarization_slope', 'recovery_slope', 'spread', 'velocity_above', 'velocity_below', 'classification', 'anno_name', 'spike_times', 'obs_intervals', 'electrodes', 'electrode_group', 'waveform_mean', 'waveform_sd')</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['units'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorData object at 0x000002800863F550>, <hdmf.common.table.VectorData object at 0x000002800863F820>, <hdmf.common.table.VectorData object at 0x00000280085FB730>, <hdmf.common.table.VectorData object at 0x000002800863F2B0>, <hdmf.common.table.VectorData object at 0x000002800863FE50>, <hdmf.common.table.VectorData object at 0x000002800863F2E0>, <hdmf.common.table.VectorData object at 0x0000028008631FA0>, <hdmf.common.table.VectorData object at 0x00000280086CB760>, <hdmf.common.table.VectorData object at 0x00000280086CB4C0>, <hdmf.common.table.VectorData object at 0x00000280086CB640>, <hdmf.common.table.VectorData object at 0x000002800863FDC0>, <hdmf.common.table.VectorData object at 0x00000280086CB400>, <hdmf.common.table.VectorData object at 0x00000280086CB7C0>, <hdmf.common.table.VectorData object at 0x00000280086CB820>, <hdmf.common.table.VectorData object at 0x00000280086CB5E0>, <hdmf.common.table.VectorData object at 0x000002800863FFD0>, <hdmf.common.table.VectorData object at 0x000002800863FDF0>, <hdmf.common.table.VectorData object at 0x000002800863F7F0>, <hdmf.common.table.VectorData object at 0x00000280086CB880>, <hdmf.common.table.VectorData object at 0x00000280086CB580>, <hdmf.common.table.VectorData object at 0x00000280086CB6A0>, <hdmf.common.table.VectorData object at 0x00000280086CB700>, <hdmf.common.table.VectorData object at 0x000002800863F4C0>, <hdmf.common.table.VectorData object at 0x000002800863FA90>, <hdmf.common.table.VectorData object at 0x000002800863FAC0>, <hdmf.common.table.VectorData object at 0x000002800863F580>, <hdmf.common.table.VectorData object at 0x0000028008631550>, <hdmf.common.table.VectorData object at 0x0000028008631640>, <hdmf.common.table.VectorData object at 0x00000280086CB520>, <hdmf.common.table.VectorData object at 0x00000280086CB460>, <hdmf.common.table.VectorIndex object at 0x00000280086C1820>, <hdmf.common.table.VectorData object at 0x00000280086C1EE0>, <hdmf.common.table.VectorIndex object at 0x00000280086C1E20>, <hdmf.common.table.VectorData object at 0x00000280086C1CA0>, <hdmf.common.table.VectorIndex object at 0x00000280086C1FD0>, electrodes hdmf.common.table.DynamicTableRegion at 0x2748920410656\n",
+       "    Target table: electrodes hdmf.common.table.DynamicTable at 0x2748920370704\n",
+       ", <hdmf.common.table.VectorData object at 0x00000280086CB280>, <hdmf.common.table.VectorData object at 0x00000280086CB160>, <hdmf.common.table.VectorData object at 0x00000280086CB2E0>)</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['units'].fields['waveform_unit']\">waveform_unit:</span> <span class=\"field-value\">volts</span></div></details><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['experiment_description']\">experiment_description:</span> <span class=\"field-value\">high tone vs. low tone</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['institution']\">institution:</span> <span class=\"field-value\">Janelia Research Campus</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_collection']\">data_collection:</span> <span class=\"field-value\"></span></div></div>"
+      ],
+      "text/plain": [
+       "root pynwb.file.NWBFile at 0x2748919558688\n",
+       "Fields:\n",
+       "  acquisition: {\n",
+       "    BehavioralEvents <class 'pynwb.behavior.BehavioralEvents'>,\n",
+       "    BehavioralTimeSeries <class 'pynwb.behavior.BehavioralTimeSeries'>\n",
+       "  }\n",
+       "  devices: {\n",
+       "    17131309211 (neuropixels 1.0 - 3B) <class 'pynwb.device.Device'>,\n",
+       "    17216703352 (neuropixels 1.0 - 3B) <class 'pynwb.device.Device'>,\n",
+       "    18005117122 (neuropixels 1.0 - 3B) <class 'pynwb.device.Device'>,\n",
+       "    18005118502 (neuropixels 1.0 - 3B) <class 'pynwb.device.Device'>,\n",
+       "    OBIS470 <class 'pynwb.device.Device'>\n",
+       "  }\n",
+       "  electrode_groups: {\n",
+       "    17131309211 1-281 <class 'pynwb.ecephys.ElectrodeGroup'>,\n",
+       "    17216703352 1-281 <class 'pynwb.ecephys.ElectrodeGroup'>,\n",
+       "    18005117122 1-384 <class 'pynwb.ecephys.ElectrodeGroup'>,\n",
+       "    18005118502 1-384 <class 'pynwb.ecephys.ElectrodeGroup'>\n",
+       "  }\n",
+       "  electrodes: electrodes <class 'hdmf.common.table.DynamicTable'>\n",
+       "  experiment_description: high tone vs. low tone\n",
+       "  experimenter: ['susu']\n",
+       "  file_create_date: [datetime.datetime(2023, 4, 25, 12, 8, 21, 159278, tzinfo=tzoffset(None, -18000))]\n",
+       "  identifier: SC015_20190207_120657_s1\n",
+       "  institution: Janelia Research Campus\n",
+       "  intervals: {\n",
+       "    trials <class 'pynwb.epoch.TimeIntervals'>\n",
+       "  }\n",
+       "  keywords: <StrDataset for HDF5 dataset \"keywords\": shape (1,), type \"|O\">\n",
+       "  ogen_sites: {\n",
+       "    OBIS470_4 <class 'pynwb.ogen.OptogeneticStimulusSite'>,\n",
+       "    OBIS470_6 <class 'pynwb.ogen.OptogeneticStimulusSite'>\n",
+       "  }\n",
+       "  related_publications: ['']\n",
+       "  session_start_time: 2019-02-07 12:06:57-06:00\n",
+       "  subject: subject pynwb.file.Subject at 0x2748920369984\n",
+       "Fields:\n",
+       "  date_of_birth: 2018-10-09 00:00:00-05:00\n",
+       "  description: SC015\n",
+       "  sex: M\n",
+       "  species: Mus musculus\n",
+       "  subject_id: 440956\n",
+       "\n",
+       "  timestamps_reference_time: 2019-02-07 12:06:57-06:00\n",
+       "  trials: trials <class 'pynwb.epoch.TimeIntervals'>\n",
+       "  units: units <class 'pynwb.misc.Units'>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nwbfile_stream"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([   3.0615,   10.4911,   17.3014,   27.2102,   35.2372,   42.905 ,\n",
+       "         49.7081,   56.5462,   63.2105,   72.5735,   79.2202,   85.9121,\n",
+       "         92.7641,   99.6109,  106.76  ,  116.3083,  122.0923,  127.5653,\n",
+       "        132.9223,  138.5094,  143.8852,  149.3363,  156.0039,  162.8571,\n",
+       "        169.6084,  176.8017,  187.2051,  193.9074,  201.7581,  207.6403,\n",
+       "        213.0816,  218.8675,  227.4653,  238.0169,  244.8202,  251.4951,\n",
+       "        259.8815,  266.7619,  274.0136,  281.0376,  286.9664,  292.8265,\n",
+       "        298.5257,  304.507 ,  310.8796,  319.829 ,  326.9991,  334.2257,\n",
+       "        343.1744,  351.5623,  357.7447,  363.1195,  368.747 ,  374.229 ,\n",
+       "        380.9804,  387.861 ,  394.8456,  402.903 ,  409.7502,  415.9349,\n",
+       "        421.4966,  427.0599,  432.4702,  440.0814,  446.9801,  453.5642,\n",
+       "        458.9952,  464.777 ,  470.2857,  475.6348,  482.8147,  489.7204,\n",
+       "        496.8337,  502.1852,  508.4031,  514.0713,  519.5604,  525.4693,\n",
+       "        533.5183,  540.1865,  546.609 ,  553.3516,  559.3192,  564.9274,\n",
+       "        571.8408,  578.6202,  585.4115,  592.0502,  598.5403,  604.113 ,\n",
+       "        609.6726,  615.3222,  621.482 ,  628.8424,  635.5277,  641.1466,\n",
+       "        647.8861,  654.524 ,  662.4597,  668.7303,  674.2622,  679.8691,\n",
+       "        687.3476,  694.7024,  701.8313,  708.8122,  715.5963,  721.2613,\n",
+       "        728.0117,  733.819 ,  740.7576,  747.2409,  752.8439,  758.4469,\n",
+       "        765.3189,  772.1975,  778.0954,  783.711 ,  789.8348,  795.4362,\n",
+       "        803.3813,  810.2268,  816.2674,  823.1371,  830.7652,  837.1315,\n",
+       "        842.7459,  848.6374,  854.5288,  861.4798,  867.4804,  873.2311,\n",
+       "        880.0694,  886.9565,  893.791 ,  899.6515,  906.5144,  915.4797,\n",
+       "        922.2182,  928.2243,  935.2025,  942.1355,  947.9049,  953.9881,\n",
+       "        959.7521,  965.4442,  971.8904,  979.3864,  986.1739,  991.7749,\n",
+       "        997.8248, 1005.4567, 1011.4929, 1018.4516, 1024.0857, 1032.8678,\n",
+       "       1040.0284, 1048.1081, 1053.7386, 1061.3482, 1067.3598, 1073.5459,\n",
+       "       1081.0744, 1088.0905, 1093.7267, 1099.3782, 1106.3492, 1113.7095,\n",
+       "       1121.0334, 1128.1796, 1136.5811, 1144.1801, 1150.2133, 1156.9586,\n",
+       "       1164.0074, 1170.8265, 1178.9861, 1185.6197, 1193.5744, 1201.2893,\n",
+       "       1208.2729, 1215.1117, 1221.3972, 1228.2218, 1235.1996, 1242.0493,\n",
+       "       1248.8307, 1255.7514, 1262.5618, 1269.6227, 1276.4573, 1282.8724,\n",
+       "       1289.781 , 1298.0529, 1304.9496, 1310.7095, 1317.6408, 1323.7209,\n",
+       "       1330.6749, 1337.547 , 1344.6158, 1350.2868, 1357.197 , 1364.1247,\n",
+       "       1373.3989, 1380.7206, 1387.1818, 1392.7917, 1398.7521, 1404.4882,\n",
+       "       1411.2463, 1418.4645, 1425.4206, 1431.4931, 1438.5164, 1445.4296,\n",
+       "       1452.6841, 1459.5578, 1465.2738, 1472.2254, 1479.1548, 1486.0814,\n",
+       "       1492.9945, 1500.4024, 1507.9126, 1515.1422, 1522.0199, 1527.9301,\n",
+       "       1534.112 , 1541.1924, 1548.1025, 1554.3979, 1560.2494, 1567.3377,\n",
+       "       1573.2397, 1580.1079, 1588.0388, 1594.8545, 1602.0475, 1607.8144,\n",
+       "       1613.8026, 1620.8349, 1627.6857, 1633.2791, 1639.2581, 1646.3069,\n",
+       "       1653.3472, 1659.348 , 1666.3821, 1673.2448, 1680.7812, 1688.254 ,\n",
+       "       1695.1875, 1702.056 , 1708.9938, 1718.3716, 1726.6969, 1733.6456,\n",
+       "       1740.5025, 1746.6062, 1752.3556, 1759.3398, 1766.2942, 1772.0469,\n",
+       "       1779.0226, 1785.8113, 1792.8843, 1799.7211, 1806.1827, 1811.9459,\n",
+       "       1817.4387, 1824.4164, 1831.5255, 1838.3327, 1847.9201, 1855.0521,\n",
+       "       1862.4418, 1869.2029, 1876.7185, 1883.6657, 1890.1301, 1895.7593,\n",
+       "       1902.8746, 1909.9185, 1917.18  , 1924.2328, 1930.4628, 1935.9326,\n",
+       "       1942.9056, 1949.7816, 1956.8511, 1964.0187, 1971.0863, 1978.244 ,\n",
+       "       1985.6911, 1992.7111, 1999.6399, 2008.0716, 2014.2828, 2021.2891,\n",
+       "       2028.3184, 2035.6347, 2041.7165, 2048.9987, 2056.7764, 2064.5651,\n",
+       "       2071.6463, 2077.7539, 2083.4884, 2089.1549, 2096.6003, 2103.7163,\n",
+       "       2111.7586, 2117.7629, 2123.4962, 2130.5302, 2138.8126, 2145.6863,\n",
+       "       2152.7347, 2158.9162, 2165.9785, 2172.5589, 2178.0028, 2183.8062,\n",
+       "       2189.8809, 2196.9408, 2203.983 , 2211.0387, 2218.178 , 2224.4173,\n",
+       "       2230.1544, 2235.9259, 2241.4429, 2248.4345, 2255.538 , 2262.9897,\n",
+       "       2270.0826, 2277.2559, 2284.2673, 2291.2929, 2298.4562, 2305.4346,\n",
+       "       2312.5212, 2319.476 , 2326.438 , 2333.4585, 2339.9448, 2349.9509,\n",
+       "       2357.1298, 2364.3269, 2370.2008, 2377.4106, 2384.6028, 2391.7107,\n",
+       "       2397.9439, 2405.7404, 2411.4053, 2419.0319, 2426.117 , 2433.139 ,\n",
+       "       2440.3165, 2447.3106, 2454.4401, 2461.6609, 2468.8032, 2475.9751,\n",
+       "       2482.9792, 2490.0071])"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nwbfile_stream.acquisition[\"BehavioralEvents\"].time_series[\"go_start_times\"].timestamps[:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "mapEphysNWB",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.13"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/000363/MAP/demo/environment.yml b/000363/MAP/demo/environment.yml
new file mode 100644
index 0000000..f526d71
--- /dev/null
+++ b/000363/MAP/demo/environment.yml
@@ -0,0 +1,11 @@
+name: base
+dependencies:
+  - pynwb
+  - nwbwidgets
+  - fsspec
+  - requests
+  - aiohttp
+  - dandi
+  - numpy
+  - matplotlib
+  - pandas
\ No newline at end of file
diff --git a/000402/MICrONS/demo/000402_microns_demo.ipynb b/000402/MICrONS/demo/000402_microns_demo.ipynb
index 148ce35..ebe25ce 100644
--- a/000402/MICrONS/demo/000402_microns_demo.ipynb
+++ b/000402/MICrONS/demo/000402_microns_demo.ipynb
@@ -1068,7 +1068,7 @@
     "The two photon data contains 50000 imaging volumes collected at ~8.6 Hz, with six fields per volume.\n",
     "The center of the volume was placed at the junction of primary visual cortex (VISp) and three higher visual areas, lateromedial area (VISlm), rostrolateral area (VISrl) and anterolateral area (VISal).\n",
     "\n",
-    "The imaging data for each field is stored in a `TwoPhotonSeries` object which can be accessed from `nwbfile.acqusition`.\n",
+    "The imaging data for each field is stored in a `TwoPhotonSeries` object which can be accessed from `nwbfile.acquisition`.\n",
     "\n",
     "The information about the imaging plane can accessed as `nwbfile.acquisition[\"TwoPhotonSeries1\"].imaging_plane` or from `nwbfile.imaging_planes[\"ImagingPlane1\"]`."
    ]
diff --git a/000409/IBL/03_analysis_Imbizo_2023.ipynb b/000409/IBL/03_analysis_Imbizo_2023.ipynb
index ba437ba..bf145b5 100644
--- a/000409/IBL/03_analysis_Imbizo_2023.ipynb
+++ b/000409/IBL/03_analysis_Imbizo_2023.ipynb
@@ -63,11 +63,11 @@
     "\n",
     "#### Encoding 🔛\n",
     "If you were to rely on a single unit to predict the choice value, which one would you chose, and what would be the magnitude of the difference between its response to left or right choices?\n",
-    "- Note: This analysis contatenates the activity across trials\n",
+    "- Note: This analysis concatenates the activity across trials\n",
     "\n",
     "#### Manifold 📈\n",
     "Using all units in a given brain region, when exactly would you be able to differentiate between the left or right choice in our time window of interest?\n",
-    "- Note: This analysis contatenates the activity across trials\n",
+    "- Note: This analysis concatenates the activity across trials\n",
     "\n",
     "#### Decoding ⏭\n",
     "For a given trial, if you were a downstream neuron receiving the activity from all units in a given region as input, would you be able to differentiate left versus right choices?\n",
@@ -1240,7 +1240,7 @@
     "\n",
     "Now, we will study **_when_ the neural activity representing left or right choices differs** before the first movement.\n",
     "\n",
-    "We will use a dimentionality approach (Manifold) to measure the distance between the left and right choice representation during the time window of interest."
+    "We will use a dimensionality approach (Manifold) to measure the distance between the left and right choice representation during the time window of interest."
    ]
   },
   {
@@ -1985,7 +1985,7 @@
     "We list below a few continuous variables:\n",
     "\n",
     "- the `wheel speed` and `position`\n",
-    "- the `paw positionn`     (loading documentation [here](https://int-brain-lab.github.io/iblenv/notebooks_external/loading_video_data.html))  TODO CHANGE FOR NWB DOC\n",
+    "- the `paw position`     (loading documentation [here](https://int-brain-lab.github.io/iblenv/notebooks_external/loading_video_data.html))  TODO CHANGE FOR NWB DOC\n",
     "- the `motion energy`     (loading documentation [here](https://int-brain-lab.github.io/iblenv/notebooks_external/loading_video_data.html))\n",
     "\n",
     "Using e.g. linear regression, you can try to decode the values of these continuous variables using neural data.\n",
@@ -2015,7 +2015,7 @@
     "\n",
     "Use the output from the video segmentation algorithm (loading documentation [here](https://int-brain-lab.github.io/iblenv/notebooks_external/loading_video_data.html)), e.g. the paw position (`paw_R`) to see if there are any `stereotypical movements`.\n",
     "\n",
-    "Use an `unsupervised classifer` method to segregate different kinds of movement the animals makes, and assess whether there are particular patterns of occurrence.\n",
+    "Use an `unsupervised classifier` method to segregate different kinds of movement the animals makes, and assess whether there are particular patterns of occurrence.\n",
     "\n",
     "Assess whether these stereotypical movements can be `decoded` from the neural activity using the techniques of this tutorial (Encoding or Decoding).\n"
    ]
diff --git a/000559/dattalab/markowitz_gillis_nature_2023/README.md b/000559/dattalab/markowitz_gillis_nature_2023/README.md
new file mode 100644
index 0000000..1394d40
--- /dev/null
+++ b/000559/dattalab/markowitz_gillis_nature_2023/README.md
@@ -0,0 +1,13 @@
+# Figure Reproductions for Dandiset 000559
+
+This submission provides three figure reproductions for the Dandiset 000559, which corresponds to the 2023 Nature paper: [Spontaneous behavior is structured by reinforcement without explicit reward](https://doi.org/10.1038/s41586-022-05611-2) by Markowitz et al.
+
+Each notebook provides an example of how to access the critical data and metadata from the three types of experiments in the dataset:
+
+- `reproduce_figure1d.ipynb` demonstrates how the behavioral kinematic variables (position, velocity, etc.), along with the fluorescence traces, are stored for the reinforcement photometry experiments
+- `reproduce_figure_S1.ipynb` shows how the fluorescence images for the _in vitro_ experiments are stored
+- `reproduce_figure_S3.ipynb` displays how are the keypoint data, along with associated fluorescence traces, are stored for the keypoint tracking experiments
+
+Note: `reproduce_figure1d.ipynb` and `reproduce_figure_S1.ipynb` use the conda environment defined by the 
+`environment.yaml` file, but `reproduce_figure_S3.ipynb` uses a different environment defined by the 
+`environment_S3.yaml` due to dependency conflicts.
\ No newline at end of file
diff --git a/000559/dattalab/markowitz_gillis_nature_2023/analysis_configuration.toml b/000559/dattalab/markowitz_gillis_nature_2023/analysis_configuration.toml
new file mode 100644
index 0000000..8de9066
--- /dev/null
+++ b/000559/dattalab/markowitz_gillis_nature_2023/analysis_configuration.toml
@@ -0,0 +1,337 @@
+# DATA_DIRS IS NO LONGER USED, LEFT FOR HISTORICAL REASONS
+[data_dirs]
+root = "/home/markowitzmeister_gmail_com/jeff_win_share/reinforcement_data" # root directory
+reinforcement = [
+	"_aggregate_results_arhmm_03",
+	"_aggregate_results_arhmm_04",
+	"_aggregate_results_arhmm_05",
+	"_aggregate_results_arhmm_06",
+	"_aggregate_results_arhmm_07",
+	"_aggregate_results_arhmm_08",
+	"_aggregate_results_arhmm_09",
+#	"_aggregate_results_arhmm_10",
+	"_aggregate_results_arhmm_11",
+#	"_aggregate_results_arhmm_12",
+]
+reinforcement_photometry = [
+	"_aggregate_results_arhmm_photometry_02/",
+	"_aggregate_results_arhmm_photometry_03/",
+]
+reinforcement_scalar = [
+	"_aggregate_results_arhmm_scalar_01/",
+	"_aggregate_results_arhmm_scalar_03/",
+]
+excitation = [
+	"_aggregate_results_arhmm_excitation_01/",
+	"_aggregate_results_arhmm_excitation_02/",
+	"_aggregate_results_arhmm_excitation_03/",
+#	"_aggregate_results_arhmm_excitation_04/",
+]
+excitation_photometry = ["_aggregate_results_arhmm_photometry_excitation_02/"]
+excitation_pulsed = ["_aggregate_results_arhmm_excitation_pulsed_01/"]
+excitation_pulsed_photometry = [
+	"_aggregate_results_arhmm_photometry_excitation_pulsed_01/",
+]
+photometry = [
+	"_aggregate_results_arhmm_photometry_06/",
+	"_aggregate_results_arhmm_photometry_07/",
+	"_aggregate_results_arhmm_photometry_08/",
+]
+
+# REPLACE BASEDIR WITH WHERE YOU DOWNLOAD DATA -
+# ALTERNATIVELY USE _reformat_zenodo_download.ipynb TO REPLACE BASEDIR PROGRAMMATICALLY
+[raw_data]
+dlight = "/Volumes/T7/CatalystNeuro/NWB/Datta/dopamine-reinforces-spontaneous-behavior/dlight_raw_data/"
+rl_modeling = "/Volumes/T7/CatalystNeuro/NWB/Datta/dopamine-reinforces-spontaneous-behavior/rl_raw_data/"
+closed_loop_behavior = "/Volumes/T7/CatalystNeuro/NWB/Datta/dopamine-reinforces-spontaneous-behavior/optoda_raw_data/"
+realtime_package = "/Volumes/T7/CatalystNeuro/NWB/Datta/dopamine-reinforces-spontaneous-behavior/realtime_package/"
+hek_cells = "/Volumes/T7/CatalystNeuro/NWB/Datta/dopamine-reinforces-spontaneous-behavior/hek_raw_data/"
+misc = "/Volumes/T7/CatalystNeuro/NWB/Datta/dopamine-reinforces-spontaneous-behavior/misc_raw_data/"
+keypoints = "/Volumes/T7/CatalystNeuro/NWB/Datta/dopamine-reinforces-spontaneous-behavior/keypoints_raw_data/"
+
+
+[intermediate_results]
+dlight = "/Volumes/T7/CatalystNeuro/NWB/Datta/dopamine-reinforces-spontaneous-behavior/dlight_intermediate_results/"
+closed_loop_behavior = "/Volumes/T7/CatalystNeuro/NWB/Datta/dopamine-reinforces-spontaneous-behavior/optoda_intermediate_results/"
+rl_modeling = "/Volumes/T7/CatalystNeuro/NWB/Datta/dopamine-reinforces-spontaneous-behavior/rl_intermediate_results/"
+misc = "/Volumes/T7/CatalystNeuro/NWB/Datta/dopamine-reinforces-spontaneous-behavior/misc_intermediate_results/"
+hek_cells = "/Volumes/T7/CatalystNeuro/NWB/Datta/dopamine-reinforces-spontaneous-behavior/hek_intermediate_results/"
+
+
+[figures]
+store_dir = "/Volumes/T7/CatalystNeuro/NWB/Datta/dopamine-reinforces-spontaneous-behavior/panels/"
+
+
+[common]
+fs = 30.0
+missing_frame_cutoff = 0.05
+largest_gap_cutoff = 300
+last_timestamp_cutoff = 1750
+first_timestamp_cutoff = 180
+
+
+[dlight_common]
+dff_threshold = 1.5
+dlight_reference_corr_threshold = 0.6
+
+[dlight_snippet]
+dataframe_filename = "_jeff-cache/merged_feedback_dataframe_debounce11.parquet" # NO LONGER USED
+scalars.hampel_filter.threshold = 10.0
+reference.filter.corner_fs = 3.0
+reference.filter.order = 2
+rolling_z.window = 600
+rolling_z.min_periods = 30
+rolling_z.center = true
+# HERE YOU WILL WANT TO RUN MULTIPLE TIMES
+snippet_grab.window_bounds = [-3, 3] # short window
+# snippet_grab.window_bounds = [-10, 10] # long window, save appended to longwin
+# snippet_grab.gb_key = "uuid"
+snippet_grab.label_key = "predicted_syllable" # online 
+# snippet_grab.label_key= "predicted_syllable (offline)" # offline
+# snippet_grab.label_key = "movement_initiations" # movement initiations
+# LONG WINDOW KEYS, USE THESE KEYS FOR [-10, 10]
+# data_keys = [
+# 	"signal_reref_dff",
+# 	"signal_reref_dff_z",
+# 	"velocity_2d_mm",
+# 	"height_ave_mm",
+# 	"feedback_status",
+# 	"acceleration_2d_mm",
+# 	"jerk_2d_mm",
+# 	"angle",
+# 	"angle_unwrapped",
+# 	"velocity_angle",
+# 	"velocity_height",
+# 	"timestamp",
+# ]
+# SHORT WINDOW KEYS, USE THESE KEYS FOR [-3, 3]
+data_keys = [
+	"signal_reref_dff",
+	"signal_reref_dff_z",	
+	"velocity_2d_mm",
+	"height_ave_mm",
+	"centroid_x_mm",
+	"centroid_y_mm",
+	"feedback_status",
+	"acceleration_2d_mm",
+	"jerk_2d_mm",
+	"angle",
+	"angle_unwrapped",
+	"velocity_angle",
+	"velocity_height",
+	"pc00",
+	"pc01",
+	"pc02",
+	"pc03",
+	"pc04",
+	"pc05",
+	"pc06",
+	"pc07",
+	"pc08",
+	"pc09",
+	"timestamp",
+]
+meta_keys = [
+	"uuid",
+	"mouse_id",
+	"session_number",
+	"target_syllable",
+	"stim_duration",
+	"date",
+	"trial_count",
+	"opsin",
+	"area",
+]
+convs.target_syllable = "int16"
+convs.session_number = "int8"
+convs.signal_reference_corr = "float32"
+convs.signal_max = "float32"
+convs.reference_max = "float32"
+convs.uuid = "category"
+convs.mouse_id = "category"
+convs.area = "category"
+
+[dlight_basic_analysis]
+scalars = [
+	"velocity_2d_mm",
+	"acceleration_2d_mm",
+	"jerk_2d_mm",
+	"velocity_angle",
+	"velocity_height",
+]
+timescale_correlation.bins = [0.25, 60.1, 0.5]
+timescale_correlation.nshuffles = 1000
+dlight_key = "signal_reref_dff_z"
+
+[dlight_regression]
+scalars = [
+	"velocity_2d_mm",
+	"acceleration_2d_mm",
+	"velocity_angle",
+	"velocity_height",
+]
+
+[dlight_transition_features]
+use_offline = true # run feature computation once set to true and once set to false
+renormalize = false
+pre_window = [-0.5, 5.0]
+windows = [
+	[
+		-0.2,
+		0.3,
+	],
+	[
+		-0.1,
+		0.4,
+	],
+	[
+		-0.3,
+		0.3,
+	],
+	[
+		0.0,
+		0.5,
+	],
+	[
+		0.0,
+		0.3,
+	],
+	[
+		0.0,
+		0.6,
+	],
+	[
+		0.0,
+		1.0,
+	],
+	[
+		0.0,
+		inf,
+	],
+]
+# scalars included along with the features
+scalars = [
+	"velocity_2d_mm",
+	"acceleration_2d_mm",
+	"jerk_2d_mm",
+	"velocity_angle",
+	"velocity_height",
+	"centroid_x_mm",
+	"centroid_y_mm",
+]
+# metadata included in the features
+meta_keys = [
+	"uuid",
+	"timestamp",
+	"syllable",
+	"mouse_id",
+	"session_number",
+	"stim_duration",
+	"duration",
+	"target_syllable",
+	"signal_max",
+	"reference_max",
+	"signal_reference_corr",
+	"date",
+	"area",
+	"opsin",
+]
+# channels to compute features over
+proc_keys = [
+	"signal_reref_dff_z",
+]
+
+[dlight_encoding_features]
+label_key = "predicted_syllable (offline)"
+window_sizes = [5, 10, 25, 50, 100, 200, 300, 400, 800, 1600]
+average_variant.bins = [5, 10, 25, 50, 100, 200, 300, 400, 800, 1600]
+
+[dlight_lagged_correlations]
+nshuffles = 1000
+use_offline = true
+use_renormalized = false
+estimate_within_bin = true
+use_neural_features = [
+	"signal_reref_dff_z_max",
+]
+use_windows = ["(0.0, 0.3)"] # what we're using in paper
+
+correlation_method = "pandas"
+correlation_kwargs.method = "pearson"
+usage_and_scalars.bins = [10, 400, 20]
+usage_and_scalars.scalars = [
+	"velocity_2d_mm",
+]
+usage_and_scalars.correlation_keys = ["syllable", "mouse_id", "bin"]
+entropy.bins = [5, 52, 5]
+entropy.ndlight_bins = 10 # bin dlight then aggregate tm stats
+entropy.dlight_bin_keys = [
+	"mouse_id",
+	"syllable",
+] # compute dlight bin cutoffs over these keys
+entropy.pre_agg_keys = [
+	"uuid",
+	"mouse_id",
+	"bin",
+	"dlight_bin_feature",
+	"dlight_bin",
+] # this first aggregate just reduces data size
+entropy.agg_keys = [
+	"mouse_id",
+	"bin",
+	"dlight_bin_feature",
+	"dlight_bin",
+] # compute entropy with these keys, last key is chopped off and used in correlation
+entropy.correlation_keys = [
+	"dlight_bin_feature",
+	"bin",
+] # final groupby, then correlation is averaged
+entropy.corr_kwargs.method = "spearman"
+entropy.tm_truncate = 36
+clustering.nclusters = 4
+clustering.bin_size = 60
+clustering.use_features = [
+	"velocity_2d_mm",
+	"acceleration_2d_mm",
+	"jerk_2d_mm",
+	"velocity_angle",
+	"velocity_height",
+]
+clustering.display_features = [
+	"velocity_2d_mm",
+	"acceleration_2d_mm",
+	"jerk_2d_mm",
+	"velocity_angle",
+	"velocity_height",
+]
+usage_and_scalars_shifted.bins = [10]
+stim.use_windows = ["(0.0, 0.6)", "(0.0, 1.0)"]
+stim.estimate_within_bin = true
+
+
+[closed_loop_behavior]
+partition_cols = ["experiment_type", "area", "mouse_id"]
+dataframe_filename = "_jeff-cache/feedback_dataframe_debounce11.parquet" # not used, left for historical reasons
+learning_timecourse.bin_size = 30
+learning_timecourse.bin_overlap = 0
+learning_timecourse.baseline = "m"
+learning_timecourse.meta_keys = [
+	"mouse_id",
+	"session_number",
+	"syllable_group",
+	"target_syllable",
+	"stim_duration",
+	"area (pooled)",
+	"experiment_type",
+	"area",
+	"genotype",
+	"uuid",
+	"date",
+	"opsin",
+	"power",
+	"sex",
+	"cohort",
+]
+
+[dask]
+# address = "tcp://10.10.0.21:35679" # only uncomment if you are going to use a dask scheduler for long-running computations
diff --git a/000559/dattalab/markowitz_gillis_nature_2023/environment.yaml b/000559/dattalab/markowitz_gillis_nature_2023/environment.yaml
new file mode 100644
index 0000000..3dea3b5
--- /dev/null
+++ b/000559/dattalab/markowitz_gillis_nature_2023/environment.yaml
@@ -0,0 +1,18 @@
+# run: conda env create --file environment.yaml
+name: datta_notebook_env
+channels:
+    - conda-forge
+dependencies:
+    - python==3.10
+    - ipywidgets
+    - pip
+    - pip:
+      - cellpose==1.0.2
+      - scikit-image
+      - imagecodecs
+      - ipykernel
+      - seaborn
+      - matplotlib
+      - tqdm
+      - toml
+      - datta-lab-to-nwb @ git+https://github.com/catalystneuro/datta-lab-to-nwb.git@main
diff --git a/000559/dattalab/markowitz_gillis_nature_2023/environment_S3.yaml b/000559/dattalab/markowitz_gillis_nature_2023/environment_S3.yaml
new file mode 100644
index 0000000..e4a7286
--- /dev/null
+++ b/000559/dattalab/markowitz_gillis_nature_2023/environment_S3.yaml
@@ -0,0 +1,22 @@
+# run: conda env create --file environment.yaml
+name: datta_figureS3_env # The reproduce_figure_S3.ipynb notebook has conflicting dependencies with the other notebooks
+channels:
+    - conda-forge
+dependencies:
+    - python==3.10
+    - ipywidgets
+    - pip
+    - pip:
+      - ipykernel
+      - seaborn
+      - matplotlib
+      - tqdm
+      - toml
+      - pynwb
+      - h5py
+      - fsspec
+      - dandi
+      - bokeh == 2.4.3
+      - numba == 0.57.1
+      - aiohttp
+      - rl_analysis @ git+https://github.com/dattalab/dopamine-reinforces-spontaneous-behavior.git@main
\ No newline at end of file
diff --git a/000559/dattalab/markowitz_gillis_nature_2023/reproduce_figure1d.ipynb b/000559/dattalab/markowitz_gillis_nature_2023/reproduce_figure1d.ipynb
new file mode 100644
index 0000000..2258e5c
--- /dev/null
+++ b/000559/dattalab/markowitz_gillis_nature_2023/reproduce_figure1d.ipynb
@@ -0,0 +1,257 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from stream_nwbfile import stream_nwbfile\n",
+    "DANDISET_ID = '000559'\n",
+    "file_path = ('sub-dlight-chrimson-1/sub-dlight-chrimson-1_'\n",
+    "             'ses-reinforcement-photometry-2891f649-4fbd-4119-a807-b8ef507edfab_behavior+image+ogen+ophys.nwb'\n",
+    ")\n",
+    "nwbfile, io = stream_nwbfile(DANDISET_ID, file_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sorted_index2id = {\n",
+    "    0: 74,\n",
+    "    1: 20,\n",
+    "    2: 22,\n",
+    "    3: 17,\n",
+    "    4: 86,\n",
+    "    5: 8,\n",
+    "    6: 12,\n",
+    "    7: 91,\n",
+    "    8: 27,\n",
+    "    9: 64,\n",
+    "    10: 95,\n",
+    "    11: 71,\n",
+    "    12: 19,\n",
+    "    13: 44,\n",
+    "    14: 39,\n",
+    "    15: 25,\n",
+    "    16: 65,\n",
+    "    17: 58,\n",
+    "    18: 41,\n",
+    "    19: 47,\n",
+    "    20: 53,\n",
+    "    21: 57,\n",
+    "    22: 94,\n",
+    "    23: 76,\n",
+    "    24: 35,\n",
+    "    25: 92,\n",
+    "    26: 72,\n",
+    "    27: 7,\n",
+    "    28: 5,\n",
+    "    29: 77,\n",
+    "    30: 67,\n",
+    "    31: 33,\n",
+    "    32: 66,\n",
+    "    33: 42,\n",
+    "    34: 15,\n",
+    "    35: 30,\n",
+    "    36: 56,\n",
+    "    37: 11,\n",
+    "    38: 45,\n",
+    "    39: 13,\n",
+    "    40: 73,\n",
+    "    41: 62,\n",
+    "    42: 31,\n",
+    "    43: 59,\n",
+    "    44: 10,\n",
+    "    45: 75,\n",
+    "    46: 4,\n",
+    "    47: 54,\n",
+    "    48: 43,\n",
+    "    49: 26,\n",
+    "    50: 60,\n",
+    "    51: 85,\n",
+    "    52: 29,\n",
+    "    53: 80,\n",
+    "    54: 68,\n",
+    "    55: 38,\n",
+    "    56: 63,\n",
+    "    57: -5\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from pynwb import NWBHDF5IO\n",
+    "from neuroconv.utils import load_dict_from_file\n",
+    "import matplotlib.pyplot as plt\n",
+    "import colorcet as cc\n",
+    "\n",
+    "def reproduce_fig1d(nwbfile, io):\n",
+    "    n_frames = 361\n",
+    "    start = 3520\n",
+    "    start_time = nwbfile.processing[\"behavior\"][\"BehavioralSyllableOffline\"].timestamps[start]\n",
+    "    stop_time = nwbfile.processing[\"behavior\"][\"BehavioralSyllableOffline\"].timestamps[start + n_frames]\n",
+    "    photometry_timestamps = nwbfile.processing[\"ophys\"][\"ReferenceDfOverF\"].timestamps[:]\n",
+    "\n",
+    "    signal_dff = nwbfile.processing[\"ophys\"][\"SignalDfOverF\"].data[:]\n",
+    "    signal_dff = signal_dff[np.logical_and(photometry_timestamps >= start_time, photometry_timestamps < stop_time)]\n",
+    "    reference_dff = nwbfile.processing[\"ophys\"][\"ReferenceDfOverF\"].data[:]\n",
+    "    reference_dff = reference_dff[\n",
+    "        np.logical_and(photometry_timestamps >= start_time, photometry_timestamps < stop_time)\n",
+    "    ]\n",
+    "\n",
+    "    moseq_extract_timestamps = nwbfile.processing[\"behavior\"][\"moseq_extract_group\"].position.spatial_series['position'].timestamps[:]\n",
+    "    moseq_extract_timemask = np.logical_and(moseq_extract_timestamps >= start_time, moseq_extract_timestamps < stop_time)\n",
+    "    moseq_extract_time = moseq_extract_timestamps[moseq_extract_timemask] - start_time\n",
+    "    position = pd.DataFrame(\n",
+    "        nwbfile.processing[\"behavior\"][\"moseq_extract_group\"].position.spatial_series['position'].data,\n",
+    "        columns=[\"x\", \"y\", \"height\"]\n",
+    "    )\n",
+    "    angle = pd.Series(nwbfile.processing[\"behavior\"][\"moseq_extract_group\"].heading_2d.spatial_series['heading_2d'].data)\n",
+    "    syllables = pd.Series(nwbfile.processing[\"behavior\"][\"BehavioralSyllableOffline\"].data).map(sorted_index2id)\n",
+    "    vel_height = position[\"height\"].interpolate(limit_direction=\"both\").diff(2) \n",
+    "    vel_height = vel_height[moseq_extract_timemask].to_numpy() / 2 * 30\n",
+    "    velocity = np.sqrt(\n",
+    "        position[\"x\"].interpolate(limit_direction=\"both\").diff() ** 2\n",
+    "        + position[\"y\"].interpolate(limit_direction=\"both\").diff() ** 2\n",
+    "    )\n",
+    "    acc = velocity.diff(2)\n",
+    "    acc = acc[moseq_extract_timemask].to_numpy() * 30\n",
+    "    vel = velocity[moseq_extract_timemask].to_numpy() * 30\n",
+    "    vel_angle = angle.interpolate(limit_direction=\"both\").diff(2) * 30 * -1\n",
+    "    vel_angle[np.abs(vel_angle) > 100] = np.NaN # remove artifacts\n",
+    "    vel_angle = vel_angle.interpolate(limit_direction=\"both\")\n",
+    "    vel_angle = vel_angle[moseq_extract_timemask].to_numpy()\n",
+    "    syllables = syllables.iloc[start : start + n_frames].to_numpy()\n",
+    "    t = np.arange(n_frames) / 30\n",
+    "\n",
+    "    time = t\n",
+    "    fig, ax = plt.subplots(6, 1)\n",
+    "    fig.dpi = 200\n",
+    "\n",
+    "    ax[0].plot(moseq_extract_time, vel, color=\"k\")\n",
+    "    ax[0].set_xlim(time[0], time[-1])\n",
+    "    ax[0].set_xticks([time[0], time[-1]])\n",
+    "    ax[0].set_xticklabels([])\n",
+    "    ax[0].set_ylim(0, 15 * 30)\n",
+    "    ax[0].set_yticks([0, 15 * 30])\n",
+    "    ax[0].set_ylabel(\"mm/s\")\n",
+    "    ax[0].text(0, 1, \"Velocity\", transform=ax[0].transAxes)\n",
+    "    ax[0].spines[\"top\"].set_visible(False)\n",
+    "    ax[0].spines[\"right\"].set_visible(False)\n",
+    "\n",
+    "    ax[1].plot(moseq_extract_time, acc, color=\"k\")\n",
+    "    ax[1].set_xlim(time[0], time[-1])\n",
+    "    ax[1].set_xticks([time[0], time[-1]])\n",
+    "    ax[1].set_xticklabels([])\n",
+    "    ax[1].set_ylim(-5 * 30, 5 * 30)\n",
+    "    ax[1].set_ylabel(\"mm/s2\")\n",
+    "    ax[1].set_yticks([-150, 0, 150])\n",
+    "    ax[1].text(0, 1, \"Acceleration\", transform=ax[1].transAxes)\n",
+    "    ax[1].spines[\"top\"].set_visible(False)\n",
+    "    ax[1].spines[\"right\"].set_visible(False)\n",
+    "\n",
+    "    ax[2].plot(moseq_extract_time, vel_angle, color=\"k\")\n",
+    "    ax[2].set_xlim(time[0], time[-1])\n",
+    "    ax[2].set_xticks([time[0], time[-1]])\n",
+    "    ax[2].set_xticklabels([])\n",
+    "    ax[2].set_ylim(-0.55 * 30, 0.55 * 30)\n",
+    "    ax[2].set_yticks([-16, 0, 16])\n",
+    "    ax[2].set_ylabel(\"rad/s\")\n",
+    "    ax[2].text(0, 1, \"Angular velocity\", transform=ax[2].transAxes)\n",
+    "    ax[2].spines[\"top\"].set_visible(False)\n",
+    "    ax[2].spines[\"right\"].set_visible(False)\n",
+    "\n",
+    "    ax[3].plot(moseq_extract_time, vel_height, color=\"k\")\n",
+    "    ax[3].set_xlim(time[0], time[-1])\n",
+    "    ax[3].set_xticks([time[0], time[-1]])\n",
+    "    ax[3].set_xticklabels([])\n",
+    "    ax[3].set_ylim(-5 * 30, 5 * 30)\n",
+    "    ax[3].set_yticks([-5 * 30, 0, 5 * 30])\n",
+    "    ax[3].set_ylabel(\"mm/s\")\n",
+    "    ax[3].text(0, 1, \"Height Velocity\", transform=ax[3].transAxes)\n",
+    "    ax[3].spines[\"top\"].set_visible(False)\n",
+    "    ax[3].spines[\"right\"].set_visible(False)\n",
+    "\n",
+    "    ax[4].imshow(syllables[np.newaxis, :], aspect=\"auto\", interpolation=\"none\", cmap=cc.cm.glasbey, vmin=0)\n",
+    "    ax[4].set_xticks([])\n",
+    "    ax[4].set_yticks([])\n",
+    "    ax[4].text(0, 1.1, \"Syllable\", transform=ax[4].transAxes)\n",
+    "\n",
+    "    ax[5].plot(time, reference_dff, color=\"#afafaf\")\n",
+    "    ax[5].plot(time, signal_dff, color=\"g\")\n",
+    "    ax[5].set_ylim(-0.02, 0.07)\n",
+    "    ax[5].set_yticks([-0.02, 0.07])\n",
+    "    ax[5].set_xlim(time[0], time[-1])\n",
+    "    ax[5].set_xticks([time[0], time[-1]])\n",
+    "    ax[5].set_ylabel(\"dF/F0\")\n",
+    "    ax[5].set_xlabel(\"Time (seconds)\")\n",
+    "    ax[5].spines[\"top\"].set_visible(False)\n",
+    "    ax[5].spines[\"right\"].set_visible(False)\n",
+    "\n",
+    "    plt.subplots_adjust(hspace=0.55)\n",
+    "    plt.suptitle(\"Figure 1d\")\n",
+    "    plt.show()\n",
+    "\n",
+    "    io.close()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1280x960 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "reproduce_fig1d(nwbfile=nwbfile, io=io)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "datta_notebook_env",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/000559/dattalab/markowitz_gillis_nature_2023/reproduce_figure_S1.ipynb b/000559/dattalab/markowitz_gillis_nature_2023/reproduce_figure_S1.ipynb
new file mode 100644
index 0000000..08ef2b3
--- /dev/null
+++ b/000559/dattalab/markowitz_gillis_nature_2023/reproduce_figure_S1.ipynb
@@ -0,0 +1,463 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a2958d80117746a085724ba936f5da6c",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/3 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from tqdm.auto import tqdm\n",
+    "from skimage import morphology\n",
+    "from skimage import filters\n",
+    "from skimage import measure, draw\n",
+    "from cellpose import models\n",
+    "from scipy.optimize import curve_fit\n",
+    "from scipy.stats import zscore\n",
+    "from collections import defaultdict\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.rcParams.update(plt.rcParamsDefault)\n",
+    "import seaborn as sns\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "from stream_nwbfile import stream_nwbfile\n",
+    "\n",
+    "DANDISET_ID = '000559'\n",
+    "hek_path = 'sub-HEK293'\n",
+    "file_paths = [\n",
+    "    hek_path + '/sub-HEK293_ses-exp3_ophys.nwb',\n",
+    "    hek_path + '/sub-HEK293_ses-exp4_ophys.nwb',\n",
+    "    hek_path + '/sub-HEK293_ses-exp5_ophys.nwb',\n",
+    "]\n",
+    "\n",
+    "\n",
+    "nwbfiles, ios = zip(*[stream_nwbfile(DANDISET_ID, file_path) for file_path in tqdm(file_paths)])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def reproduce_figS1abcd(file_paths, nwbfiles):\n",
+    "    model = models.Cellpose(model_type=\"cyto2\", gpu=True)\n",
+    "    parameters = [\n",
+    "        {\"lag\": int(5), \"trim\": np.inf, \"start\": 5, \"onset\": 88, \"offset\": 200},\n",
+    "        {\"lag\": int(5), \"trim\": int(135), \"start\": 5, \"onset\": 40, \"offset\": np.inf},\n",
+    "        {\"lag\": int(5), \"trim\": int(280), \"start\": 5, \"onset\": 50, \"offset\": 170},\n",
+    "    ]\n",
+    "    hampel_parameters = {\"win\": 10, \"threshold\": 2}\n",
+    "    channels = [0, 0]\n",
+    "\n",
+    "    results = nested_dict()\n",
+    "    baseline_func = bi_exp_decay\n",
+    "    baseline_kwargs = {\"p0\": (0.5, -1e-3, 0.5, -1e-3, 0), \"maxfev\": int(1e5)}\n",
+    "    fallback_func = linear_decay\n",
+    "    fallback_kwargs = {\"p0\": (-0.1, 0), \"maxfev\": int(1e3)}\n",
+    "\n",
+    "    for file_path, nwbfile, _parameters in tqdm(zip(file_paths, nwbfiles, parameters), total=len(parameters)):\n",
+    "        raw_signal = np.array(nwbfile.acquisition[\"Signal1PSeries\"].data)\n",
+    "        raw_reference = np.array(nwbfile.acquisition[\"Reference1PSeries\"].data)\n",
+    "        scale_dat = np.array(nwbfile.acquisition[\"Images\"][\"ScaleImage\"].data)\n",
+    "        grid_spacing_um = nwbfile.imaging_planes[\"ReferenceImagingPlane\"].grid_spacing[0]\n",
+    "        masks, flows, styles, diams = model.eval(\n",
+    "            (np.max(raw_signal[:25], axis=0)),\n",
+    "            diameter=None,\n",
+    "            channels=channels,\n",
+    "            cellprob_threshold=0,\n",
+    "        )\n",
+    "\n",
+    "        props = measure.regionprops(masks)\n",
+    "\n",
+    "        diameters = np.array([_.major_axis_length for _ in props])\n",
+    "        centroids = np.array([_.centroid for _ in props])\n",
+    "\n",
+    "        cells = np.unique(masks)\n",
+    "        cells = cells[cells > 0]\n",
+    "        cells = cells[diameters > 30]\n",
+    "        centroids = centroids[diameters > 30]\n",
+    "\n",
+    "        traces_dlight = []\n",
+    "        traces_isos = []\n",
+    "        for _cell, _centroid in zip(cells, centroids):\n",
+    "            rr, cc = draw.disk(_centroid, 7)\n",
+    "            _cell_mask = masks == _cell\n",
+    "            _cell_mask[rr, cc] = 0\n",
+    "\n",
+    "            _cell_trace = []\n",
+    "            for _raw_dat in raw_signal:\n",
+    "                _cell_trace.append(_raw_dat[_cell_mask].mean())\n",
+    "            traces_dlight.append(simple_hampel(np.array(_cell_trace), **hampel_parameters))\n",
+    "            _cell_trace = []\n",
+    "            for _raw_dat in raw_reference:\n",
+    "                _cell_trace.append(_raw_dat[_cell_mask].mean())\n",
+    "            traces_isos.append(simple_hampel(np.array(_cell_trace), **hampel_parameters))\n",
+    "\n",
+    "        traces_dlight = np.array(traces_dlight)\n",
+    "        traces_isos = np.array(traces_isos)\n",
+    "\n",
+    "        right_edge = int(np.minimum(_parameters[\"trim\"], traces_dlight.shape[1]))\n",
+    "        xvec = np.arange(_parameters[\"start\"], right_edge)\n",
+    "        baseline = np.arange(0, _parameters[\"onset\"] - _parameters[\"start\"])\n",
+    "        if _parameters[\"offset\"] < len(xvec):\n",
+    "            post_stim = np.arange(_parameters[\"offset\"] - _parameters[\"start\"], len(xvec))\n",
+    "            use_region = np.concatenate([baseline, post_stim])\n",
+    "        else:\n",
+    "            use_region = baseline\n",
+    "\n",
+    "        trim_traces_dlight = traces_dlight[:, xvec]\n",
+    "        trim_traces_isos = traces_isos[:, xvec]\n",
+    "\n",
+    "        traces_dlight_baserem = np.zeros_like(trim_traces_dlight)\n",
+    "        baseline_dlight = np.zeros_like(trim_traces_dlight)\n",
+    "\n",
+    "        for i, _trace in tqdm(enumerate(trim_traces_dlight), total=len(trim_traces_dlight)):\n",
+    "            offset = _trace[0]\n",
+    "            try:\n",
+    "                params = curve_fit(baseline_func, use_region, _trace[use_region] - offset, **baseline_kwargs)\n",
+    "                fit_curve = baseline_func(xvec, *params[0]) + offset\n",
+    "            except:\n",
+    "                params = curve_fit(fallback_func, use_region, _trace[use_region] - offset, **fallback_kwargs)\n",
+    "                fit_curve = fallback_func(xvec, *params[0]) + offset\n",
+    "            traces_dlight_baserem[i] = (_trace - fit_curve) / fit_curve\n",
+    "            baseline_dlight[i] = fit_curve\n",
+    "\n",
+    "        traces_isos_baserem = np.zeros_like(trim_traces_dlight)\n",
+    "        baseline_isos = np.zeros_like(trim_traces_dlight)\n",
+    "\n",
+    "        for i, _trace in tqdm(enumerate(trim_traces_isos), total=len(trim_traces_isos)):\n",
+    "            offset = _trace[0]\n",
+    "            try:\n",
+    "                params = curve_fit(baseline_func, use_region, _trace[use_region] - offset, **baseline_kwargs)\n",
+    "                fit_curve = baseline_func(xvec, *params[0]) + offset\n",
+    "            except:\n",
+    "                params = curve_fit(fallback_func, use_region, _trace[use_region] - offset, **fallback_kwargs)\n",
+    "                fit_curve = fallback_func(xvec, *params[0]) + offset\n",
+    "            traces_isos_baserem[i] = (_trace - fit_curve) / fit_curve\n",
+    "            baseline_isos[i] = fit_curve\n",
+    "\n",
+    "        results[file_path][\"dlight\"][\"baseline_rem\"] = traces_dlight_baserem\n",
+    "        results[file_path][\"isos\"][\"baseline_rem\"] = traces_isos_baserem\n",
+    "        results[file_path][\"dlight\"][\"raw\"] = trim_traces_dlight\n",
+    "        results[file_path][\"isos\"][\"raw\"] = trim_traces_isos\n",
+    "        results[file_path][\"dlight\"][\"fit_baseline\"] = baseline_dlight\n",
+    "        results[file_path][\"isos\"][\"fit_baseline\"] = baseline_isos\n",
+    "        results[file_path][\"rois\"] = masks\n",
+    "\n",
+    "    onsets = np.array([_[\"onset\"] for _ in parameters])\n",
+    "    lens = np.array([len(_[\"dlight\"][\"baseline_rem\"][0]) for _ in results.values()])\n",
+    "    max_onset = onsets.max()\n",
+    "    diffs_onset = max_onset - np.array(onsets)\n",
+    "    lens += diffs_onset\n",
+    "    max_lens = lens.max()\n",
+    "    diffs_len = max_lens - lens\n",
+    "    padder = lambda x, y, z: np.pad(x, [(0, 0), (y, z)], mode=\"constant\", constant_values=np.nan)\n",
+    "    dlight_traces = [_[\"dlight\"][\"baseline_rem\"] for _ in results.values()]\n",
+    "    isos_traces = [_[\"isos\"][\"baseline_rem\"] for _ in results.values()]\n",
+    "    dlight_traces_raw = [_[\"dlight\"][\"raw\"] for _ in results.values()]\n",
+    "    isos_traces_raw = [_[\"isos\"][\"raw\"] for _ in results.values()]\n",
+    "    dlight_traces = [padder(_, _onset, _offset) for _, _onset, _offset in zip(dlight_traces, diffs_onset, diffs_len)]\n",
+    "    isos_traces = [padder(_, _onset, _offset) for _, _onset, _offset in zip(isos_traces, diffs_onset, diffs_len)]\n",
+    "    dlight_traces_raw = [\n",
+    "        padder(_, _onset, _offset) for _, _onset, _offset in zip(dlight_traces_raw, diffs_onset, diffs_len)\n",
+    "    ]\n",
+    "    isos_traces_raw = [\n",
+    "        padder(_, _onset, _offset) for _, _onset, _offset in zip(isos_traces_raw, diffs_onset, diffs_len)\n",
+    "    ]\n",
+    "    dlight_traces = np.vstack(dlight_traces)\n",
+    "    isos_traces = np.vstack(isos_traces)\n",
+    "    dlight_traces_raw = np.vstack(dlight_traces_raw)\n",
+    "    isos_traces_raw = np.vstack(isos_traces_raw)\n",
+    "    use_onset = 100\n",
+    "    use_duration = 15\n",
+    "    use_offset = 0\n",
+    "    maxvals = np.nanmax(dlight_traces[:, use_onset + use_offset : use_onset + use_duration], axis=1)\n",
+    "    use_rois = maxvals > 0.05\n",
+    "    clean_image = lambda x: filters.median(x, morphology.disk(3))\n",
+    "    max_projs_dlight = []\n",
+    "    max_projs_isos = []\n",
+    "    max_projs_masks = []\n",
+    "    for file_path, nwbfile in zip(file_paths, nwbfiles):\n",
+    "        raw_signal = np.array(nwbfile.acquisition[\"Signal1PSeries\"].data)\n",
+    "        raw_reference = np.array(nwbfile.acquisition[\"Reference1PSeries\"].data)\n",
+    "        max_projs_dlight.append(clean_image(np.max(raw_signal[:25], axis=0)))\n",
+    "        max_projs_isos.append(clean_image(np.max(raw_reference[:25], axis=0)))\n",
+    "        max_projs_masks.append(results[file_path][\"rois\"] > 0)\n",
+    "    rng = np.random.default_rng(0)\n",
+    "\n",
+    "    plot1c(dlight_traces, isos_traces, max_onset, use_rois)\n",
+    "    plot_1d(\n",
+    "        baseline_func,\n",
+    "        baseline_kwargs,\n",
+    "        dlight_traces,\n",
+    "        isos_traces,\n",
+    "        results,\n",
+    "        use_rois,\n",
+    "        use_onset,\n",
+    "        use_offset,\n",
+    "        use_duration,\n",
+    "        rng,\n",
+    "    )\n",
+    "    plot_1a(max_projs_dlight, max_projs_isos, scale_dat, grid_spacing_um)\n",
+    "    plot_1b(max_projs_dlight, max_projs_isos, max_projs_masks, rng)\n",
+    "\n",
+    "    for io in ios:\n",
+    "        io.close()\n",
+    "\n",
+    "\n",
+    "def plot_1b(max_projs_dlight, max_projs_isos, max_projs_masks, rng):\n",
+    "    x = np.concatenate([zscore(_[_mask].ravel()) for _, _mask in zip(max_projs_dlight, max_projs_masks)])\n",
+    "    y = np.concatenate([zscore(_[_mask].ravel()) for _, _mask in zip(max_projs_isos, max_projs_masks)])\n",
+    "    nans = np.isnan(x) | np.isnan(y)\n",
+    "    x = x[~nans]\n",
+    "    y = y[~nans]\n",
+    "    bootparams = []\n",
+    "    for _boot in tqdm(range(1000)):\n",
+    "        idx = rng.choice(np.arange(len(x)), size=len(x), replace=True)\n",
+    "        bootparams.append(curve_fit(linear_decay, x[idx], y[idx])[0])\n",
+    "    xvals = np.arange(x.min(), x.max())\n",
+    "    bootvals = []\n",
+    "    for _params in bootparams:\n",
+    "        bootvals.append(linear_decay(xvals, *_params))\n",
+    "    bootci = np.quantile(bootvals, [0.025, 0.975], axis=0)\n",
+    "    m, b = np.mean(bootparams, axis=0)\n",
+    "    mci, bci = np.std(bootparams, axis=0)\n",
+    "    fig, ax = plt.subplots(1, figsize=(4, 4))\n",
+    "    ax.scatter(x, y, 0.15, alpha=0.5, rasterized=True)\n",
+    "    ax.axis(\"square\")\n",
+    "    plt.xlim(-3, 8)\n",
+    "    plt.ylim(-3, 8)\n",
+    "    plt.xticks(np.arange(-3, 10, 3))\n",
+    "    plt.yticks(np.arange(-3, 10, 3))\n",
+    "    plt.plot(plt.xlim(), plt.ylim(), color=plt.rcParams[\"axes.edgecolor\"], zorder=-100, lw=1.5)\n",
+    "    plt.xlabel(\"480 nm\")\n",
+    "    plt.ylabel(\"400 nm\")\n",
+    "    ax.plot(xvals, np.mean(bootvals, axis=0), color=\"b\", zorder=-150, lw=0.5)\n",
+    "    ax.fill_between(\n",
+    "        xvals,\n",
+    "        bootci[1],\n",
+    "        bootci[0],\n",
+    "        color=\"b\",\n",
+    "        alpha=0.75,\n",
+    "        zorder=-200,\n",
+    "        lw=0,\n",
+    "        edgecolor=None,\n",
+    "    )\n",
+    "    ax.set_title(f\"400nm={m:.3f} * 480nm +/- {mci:.3f}\")\n",
+    "    fig.tight_layout()\n",
+    "    fig.suptitle(\"Extended Data Figure 1b\", y=1.05)\n",
+    "    plt.show()\n",
+    "\n",
+    "\n",
+    "def plot_1a(max_projs_dlight, max_projs_isos, scale_dat, grid_spacing_um):\n",
+    "    cmap = sns.dark_palette([0, 1, 0], as_cmap=True)\n",
+    "    kwargs = {\"cmap\": cmap}\n",
+    "    fig, ax = plt.subplots(3, 1, figsize=(4, 10))\n",
+    "    scale_bar_um = 20\n",
+    "    scale_bar_px = int(scale_bar_um / grid_spacing_um)\n",
+    "    plot_projs_dlight = max_projs_dlight[1].copy()\n",
+    "    plot_projs_dlight[10 : 10 + scale_bar_px, 15:25] = np.max(plot_projs_dlight)\n",
+    "    ax[0].imshow(np.flipud(plot_projs_dlight.T), **kwargs)\n",
+    "    ax[0].set_title(\"480 nm\")\n",
+    "    ax[1].imshow(np.flipud(max_projs_isos[1].T), **kwargs)\n",
+    "    ax[1].set_title(\"400 nm\")\n",
+    "    ax[2].imshow(np.flipud(scale_dat.T), **kwargs)\n",
+    "    ax[2].set_title(\"scale (.01 mm per div)\")\n",
+    "    for _ax in ax:\n",
+    "        _ax.axis(\"off\")\n",
+    "    fig.suptitle(\"Extended Data Figure 1a\", y=0.95)\n",
+    "    plt.show()\n",
+    "\n",
+    "\n",
+    "def plot_1d(\n",
+    "    baseline_func,\n",
+    "    baseline_kwargs,\n",
+    "    dlight_traces,\n",
+    "    isos_traces,\n",
+    "    results,\n",
+    "    use_rois,\n",
+    "    use_onset,\n",
+    "    use_offset,\n",
+    "    use_duration,\n",
+    "    rng,\n",
+    "):\n",
+    "    _trace = list(results.values())[2][\"dlight\"][\"raw\"][10]\n",
+    "    use_region = np.concatenate([np.arange(50), np.arange(150, len(_trace))])\n",
+    "    xvec = np.arange(len(_trace))\n",
+    "    offset = _trace[0]\n",
+    "    baseline_kwargs[\"maxfev\"] = int(1e6)\n",
+    "    params = curve_fit(baseline_func, use_region, _trace[use_region] - offset, **baseline_kwargs)\n",
+    "    fit_curve = baseline_func(xvec, *params[0]) + offset\n",
+    "    x = np.nanmean(dlight_traces[use_rois, use_onset + use_offset : use_onset + use_duration], axis=1)\n",
+    "    y = np.nanmean(isos_traces[use_rois, use_onset + use_offset : use_onset + use_duration], axis=1)\n",
+    "    nans = np.isnan(x) | np.isnan(y)\n",
+    "    x = x[~nans]\n",
+    "    y = y[~nans]\n",
+    "    bootparams = []\n",
+    "    for _boot in range(1000):\n",
+    "        idx = rng.choice(np.arange(len(x)), size=len(x), replace=True)\n",
+    "        bootparams.append(curve_fit(linear_decay, x[idx], y[idx])[0])\n",
+    "    xvals = np.arange(-5, 60)\n",
+    "    bootvals = []\n",
+    "    for _params in bootparams:\n",
+    "        bootvals.append(linear_decay(xvals, *_params))\n",
+    "    bootci = np.quantile(bootvals, [0.025, 0.975], axis=0)\n",
+    "    m, b = np.mean(bootparams, axis=0)\n",
+    "    mci, bci = np.std(bootparams, axis=0)\n",
+    "    fig, ax = plt.subplots(1, figsize=(4, 4))\n",
+    "    duration = 30\n",
+    "    plt.scatter(\n",
+    "        dlight_traces[use_rois, use_onset + use_offset : use_onset + duration].mean(axis=1) * 100,\n",
+    "        isos_traces[use_rois, use_onset + use_offset : use_onset + duration].mean(axis=1) * 100,\n",
+    "        20,\n",
+    "    )\n",
+    "    ax.axis(\"square\")\n",
+    "    ax.set_ylim(-5, 60)\n",
+    "    ax.set_xlim(-5, 60)\n",
+    "    # plt.xticks(-.05, .6)\n",
+    "    ax.set_xticks(np.arange(-5, 65, 15))\n",
+    "    ax.set_yticks(np.arange(-5, 65, 15))\n",
+    "    ax.set_xlabel(\"480 excitation\")\n",
+    "    ax.set_ylabel(\"400 excitation\")\n",
+    "    ax.plot(\n",
+    "        ax.get_xlim(),\n",
+    "        ax.get_ylim(),\n",
+    "        color=plt.rcParams[\"axes.edgecolor\"],\n",
+    "        lw=1,\n",
+    "        zorder=-100,\n",
+    "    )\n",
+    "    ax.plot(xvals, np.mean(bootvals, axis=0), color=\"b\", zorder=-150, lw=0.5)\n",
+    "    ax.fill_between(xvals, bootci[1], bootci[0], color=\"b\", alpha=0.5, zorder=-200, edgecolor=None, lw=0)\n",
+    "    ax.set_title(f\"400nm={m:.3f} * 480nm +/- {mci:.3f}\")\n",
+    "    fig.tight_layout()\n",
+    "    fig.suptitle(\"Extended Data Figure 1d\", y=1.05)\n",
+    "    plt.show()\n",
+    "\n",
+    "\n",
+    "def plot1c(dlight_traces, isos_traces, max_onset, use_rois):\n",
+    "    camera_fs = 0.25\n",
+    "    xticks = np.array([0, 210])\n",
+    "    xticklabels = (xticks / camera_fs) / 60\n",
+    "    cmap = plt.matplotlib.cm.magma.copy()\n",
+    "    kwargs = {\n",
+    "        \"aspect\": \"auto\",\n",
+    "        \"norm\": plt.matplotlib.colors.Normalize(vmin=0, vmax=0.25),\n",
+    "        \"cmap\": cmap,\n",
+    "    }\n",
+    "    cmap.set_bad(cmap(kwargs[\"norm\"](0)))\n",
+    "    sns.set_context(\"paper\")\n",
+    "    fig, ax = plt.subplots(1, 2, figsize=(5, 4), sharey=True, sharex=True)\n",
+    "    ax[0].imshow(dlight_traces[use_rois], **kwargs)\n",
+    "    ax[0].set_title(\"480 nm\")\n",
+    "    ax[0].set_yticks([])\n",
+    "    ax[0].set_ylabel(\"ROI\")\n",
+    "    h = ax[1].imshow(isos_traces[use_rois], **kwargs)\n",
+    "    ax[1].set_title(\"400 nm\")\n",
+    "    for _ax in ax:\n",
+    "        _ax.axvline(x=max_onset, color=\"w\", linestyle=\"--\")\n",
+    "        _ax.axvline(x=max_onset + 85, color=\"w\", linestyle=\"--\")\n",
+    "\n",
+    "        _ax.set_xticks(xticks)\n",
+    "        _ax.set_xticklabels(xticklabels)\n",
+    "    fig.supxlabel(\"Time (minutes)\")\n",
+    "    fig.tight_layout()\n",
+    "    fig.colorbar(h, ax=ax.ravel(), label=\"dF/F0\")\n",
+    "    fig.suptitle(\"Extended Data Figure 1c\", y=1.05)\n",
+    "    plt.show()\n",
+    "\n",
+    "\n",
+    "def bi_exp_decay(t, A1, K1, A2, K2, C):\n",
+    "    return A1 * np.exp(K1 * t) + A2 * np.exp(K2 * t) + C\n",
+    "\n",
+    "\n",
+    "def linear_decay(t, M, B):\n",
+    "    return M * t + B\n",
+    "\n",
+    "\n",
+    "def simple_hampel(trace, win=6, threshold=3):\n",
+    "    use_series = pd.Series(trace)\n",
+    "    meds = use_series.rolling(win, 1, center=True).median()\n",
+    "    mad = lambda x: (x - x.median()).abs().median()\n",
+    "    diffs = use_series.rolling(win, 1, center=True).apply(mad)\n",
+    "    threshold = diffs > threshold\n",
+    "    trace[threshold] = meds[threshold]\n",
+    "    return trace\n",
+    "\n",
+    "\n",
+    "def nested_dict():\n",
+    "    return defaultdict(nested_dict)\n",
+    "\n",
+    "\n",
+    "def lagged_diff(traces, lag, axis=0):\n",
+    "    if axis == 0:\n",
+    "        return traces[lag:] - traces[:-lag]\n",
+    "    else:\n",
+    "        return traces[:, lag:] - traces[:, :-lag]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'nwbfiles' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[5], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m reproduce_figS1abcd(file_paths, \u001b[43mnwbfiles\u001b[49m)\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'nwbfiles' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "reproduce_figS1abcd(file_paths, nwbfiles)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "datta_env",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/000559/dattalab/markowitz_gillis_nature_2023/reproduce_figure_S3.ipynb b/000559/dattalab/markowitz_gillis_nature_2023/reproduce_figure_S3.ipynb
new file mode 100644
index 0000000..fd821e7
--- /dev/null
+++ b/000559/dattalab/markowitz_gillis_nature_2023/reproduce_figure_S3.ipynb
@@ -0,0 +1,621 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "59201b8c274043a9b35bac73475e8229",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/5 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "A newer version (0.59.1) of dandi/dandi-cli is available. You are using 0.54.0\n",
+      "/opt/anaconda3/envs/datta_figureS3_env/lib/python3.10/site-packages/hdmf/utils.py:668: UserWarning: Ignoring cached namespace 'hdmf-common' version 1.6.0 because version 1.8.0 is already loaded.\n",
+      "  return func(args[0], **pargs)\n",
+      "/opt/anaconda3/envs/datta_figureS3_env/lib/python3.10/site-packages/hdmf/utils.py:668: UserWarning: Ignoring cached namespace 'hdmf-experimental' version 0.3.0 because version 0.5.0 is already loaded.\n",
+      "  return func(args[0], **pargs)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import os\n",
+    "import toml\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "from scipy import signal\n",
+    "from toolz import partial\n",
+    "from tqdm.auto import tqdm\n",
+    "\n",
+    "from rl_analysis.util import zscore\n",
+    "from sklearn.linear_model import LinearRegression\n",
+    "from rl_analysis.photometry.signal import rolling_fluor_normalization, rereference\n",
+    "\n",
+    "from pynwb import NWBHDF5IO\n",
+    "from pathlib import Path\n",
+    "import yaml\n",
+    "\n",
+    "from stream_nwbfile import stream_nwbfile\n",
+    "\n",
+    "DANDISET_ID = '000559'\n",
+    "file_paths = [\n",
+    "    'sub-dls-dlight-9/sub-dls-dlight-9_ses-keypoint-dls-dlight-9_image+ophys.nwb',\n",
+    "    'sub-dls-dlight-10/sub-dls-dlight-10_ses-keypoint-dls-dlight-10_image+ophys.nwb',\n",
+    "    'sub-dls-dlight-11/sub-dls-dlight-11_ses-keypoint-dls-dlight-11_image+ophys.nwb',\n",
+    "    'sub-dls-dlight-12/sub-dls-dlight-12_ses-keypoint-dls-dlight-12_image+ophys.nwb',\n",
+    "    'sub-dls-dlight-13/sub-dls-dlight-13_ses-keypoint-dls-dlight-13_image+ophys.nwb'\n",
+    "]\n",
+    "\n",
+    "\n",
+    "nwbfiles, ios = zip(*[stream_nwbfile(DANDISET_ID, file_path) for file_path in tqdm(file_paths)])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def _partial(df, x, y, window=range(-30, 30)):\n",
+    "    # new approach - remove transfer function here\n",
+    "    X = [df[x].shift(i).rename(index=str(i)) for i in window]\n",
+    "    X = pd.DataFrame(X).T\n",
+    "\n",
+    "    X[y] = df[y]\n",
+    "    X = X.dropna()\n",
+    "\n",
+    "    mdl = LinearRegression()\n",
+    "    mdl.fit(X.drop(columns=[y]), X[y])\n",
+    "    p = mdl.predict(X.drop(columns=[y]))\n",
+    "    df.loc[X.index, f\"{y} partial\"] = X[y] - p\n",
+    "    df[f\"{y} partial (z)\"] = zscore(df[f\"{y} partial\"])\n",
+    "    return df\n",
+    "\n",
+    "\n",
+    "# rereference the dLight signal to remove motion artifact\n",
+    "def filter_signal(v):\n",
+    "    sos = signal.butter(2, 3, output=\"sos\", fs=30.0)\n",
+    "    f = signal.sosfiltfilt(sos, v)\n",
+    "    return f\n",
+    "\n",
+    "\n",
+    "def get_z(x, y, bw_adjust=1, subsample_factor=100):\n",
+    "    from scipy.stats import gaussian_kde\n",
+    "\n",
+    "    xy = np.vstack([x[::subsample_factor], y[::subsample_factor]])\n",
+    "    kernel = gaussian_kde(xy)\n",
+    "    kernel.set_bandwidth(kernel.scotts_factor() * bw_adjust)\n",
+    "    z = kernel(np.vstack([x, y]))\n",
+    "    return z\n",
+    "\n",
+    "\n",
+    "def partial_out(df, xs, y):\n",
+    "    assert isinstance(xs, list)\n",
+    "    X = df[xs]\n",
+    "    y = df[y]\n",
+    "    mdl = LinearRegression()\n",
+    "    mdl.fit(X, y)\n",
+    "    p = mdl.predict(X)\n",
+    "    return zscore(y - p)\n",
+    "\n",
+    "\n",
+    "def compute_keypoint_velocity(kp, n=2):\n",
+    "    return (kp[n:] - kp[:-n]) / n\n",
+    "\n",
+    "\n",
+    "def compute_global_velocity(kp, n=2):\n",
+    "    # nframes X nkeypoints X 3\n",
+    "    kp = np.nanmean(kp[:, :3], axis=1)\n",
+    "    v = (kp[n:] - kp[:-n]) / n\n",
+    "    # only consider the first 3 points as they are the spine\n",
+    "    return np.linalg.norm(v, axis=1)\n",
+    "\n",
+    "\n",
+    "def bin_data(data, timescale, n_offsets=0, neural_agg=\"mean\", data_agg=\"mean\", window=range(-15, 15)):\n",
+    "    step = timescale / (n_offsets + 1)\n",
+    "    offsets = np.arange(0, timescale, step)\n",
+    "\n",
+    "    time = np.arange(0, 1500, timescale)  # step through 0-1500 seconds at this timescale\n",
+    "\n",
+    "    aggs = []\n",
+    "    for offset in offsets:\n",
+    "        cuts = pd.cut(data[\"timestamp\"], time + offset, labels=False).astype(\"Int16\").rename(\"time bin\")\n",
+    "        data[\"time bin\"] = cuts\n",
+    "        agg = data.groupby([\"mouse_id\", \"time bin\"]).agg(neural_agg)\n",
+    "        agg[\"offset\"] = offset\n",
+    "        aggs.append(agg)\n",
+    "    agg_matrix = pd.concat(aggs).reset_index()\n",
+    "    agg_matrix[\"timescale\"] = timescale\n",
+    "    agg_matrix = agg_matrix.sort_values(by=[\"mouse_id\", \"timestamp\"])\n",
+    "\n",
+    "    # partial out velocity\n",
+    "    for dim in (\"2d\", \"3d\"):\n",
+    "        agg_matrix = agg_matrix.groupby(\"mouse_id\", group_keys=False).apply(\n",
+    "            _partial, x=f\"body speed {dim} (z)\", y=f\"forelimb speed {dim} (z)\", window=window\n",
+    "        )\n",
+    "    # partial out 2d velocity from 3d forelimb speed\n",
+    "    agg_matrix = agg_matrix.groupby(\"mouse_id\", group_keys=False).apply(\n",
+    "        _partial, x=\"body speed 2d (z)\", y=\"forelimb speed 3d (z)\", window=window\n",
+    "    )\n",
+    "    # partial velocity from dlight\n",
+    "    agg_matrix = agg_matrix.groupby(\"mouse_id\", group_keys=False).apply(\n",
+    "        _partial, x=\"body speed 2d (z)\", y=\"dlight_reref_dff (z)\", window=window\n",
+    "    )\n",
+    "\n",
+    "    if isinstance(neural_agg, str):\n",
+    "        agg_matrix[\"neural_agg\"] = neural_agg\n",
+    "    elif hasattr(neural_agg, \"__name__\"):\n",
+    "        agg_matrix[\"neural_agg\"] = neural_agg.__name__\n",
+    "\n",
+    "    return agg_matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def reproduce_figS3(nwbfile_paths, nwbfiles, config_path, ios):\n",
+    "    print(\"reproducing figure S3\")\n",
+    "    with open(config_path, \"r\") as f:\n",
+    "        config = toml.load(f)\n",
+    "    dlight_config = config[\"dlight_basic_analysis\"]\n",
+    "    index_to_name = {\n",
+    "        0: \"rostral_spine\",\n",
+    "        1: \"medial_spine\",\n",
+    "        2: \"caudal_spine\",\n",
+    "        3: \"tail_base\",\n",
+    "        4: \"tail_tip\",\n",
+    "        5: \"head_center\",\n",
+    "        6: \"left_ear\",\n",
+    "        7: \"right_ear\",\n",
+    "        8: \"nose\",\n",
+    "        9: \"left_hind_ankle\",\n",
+    "        10: \"left_hindpaw\",\n",
+    "        11: \"right_hind_ankle\",\n",
+    "        12: \"right_hindpaw\",\n",
+    "        13: \"left_forepaw\",\n",
+    "        14: \"right_forepaw\",\n",
+    "    }\n",
+    "    data = {}\n",
+    "    for nwbfile, nwbfile_path in zip(nwbfiles, nwbfile_paths):\n",
+    "        timestamps = (\n",
+    "            nwbfile.processing[\"behavior\"]\n",
+    "            .data_interfaces[\"keypoints\"]\n",
+    "            .pose_estimation_series[\"rostral_spine\"]\n",
+    "            .timestamps[:]\n",
+    "        )\n",
+    "        positions_median = np.zeros((len(timestamps), 15, 3))\n",
+    "        for i, name in index_to_name.items():\n",
+    "            positions_median[:, i, :] = (\n",
+    "                nwbfile.processing[\"behavior\"].data_interfaces[\"keypoints\"].pose_estimation_series[name].data[:]\n",
+    "            )\n",
+    "        data[os.path.basename(nwbfile_path)] = {\n",
+    "            \"dlight\": nwbfile.processing[\"ophys\"].data_interfaces[\"SignalF\"].data[:],\n",
+    "            \"uv\": nwbfile.processing[\"ophys\"].data_interfaces[\"UVReferenceF\"].data[:],\n",
+    "            \"positions_median\": positions_median,\n",
+    "        }\n",
+    "        summary_image = (\n",
+    "            nwbfile.processing[\"behavior\"].data_interfaces[\"summary_images\"].images[\"summary_image\"].data[:]\n",
+    "        )\n",
+    "\n",
+    "    plot_3a(summary_image=summary_image)\n",
+    "\n",
+    "    window = range(-10, 10)\n",
+    "    dfs = {}\n",
+    "\n",
+    "    for k, v in data.items():\n",
+    "        speed = compute_global_velocity(v[\"positions_median\"])\n",
+    "        kp_vels = compute_keypoint_velocity(v[\"positions_median\"])\n",
+    "        kp_speed = np.linalg.norm(kp_vels, axis=2)\n",
+    "\n",
+    "        speed_2d = compute_global_velocity(v[\"positions_median\"][..., :2])\n",
+    "        kp_vels_2d = compute_keypoint_velocity(v[\"positions_median\"][..., :2])\n",
+    "        kp_speed_2d = np.linalg.norm(kp_vels_2d, axis=2)\n",
+    "\n",
+    "        dlight_df = pd.DataFrame(\n",
+    "            {\n",
+    "                \"dLight\": rolling_fluor_normalization(v[\"dlight\"][2:], normalizer=\"zscore\"),\n",
+    "                \"body speed 3d\": speed,\n",
+    "                \"right forepaw 3d\": kp_speed[:, 14],\n",
+    "                \"left forepaw 3d\": kp_speed[:, 13],\n",
+    "                \"right hindpaw 3d\": kp_speed[:, 12],\n",
+    "                \"left hindpaw 3d\": kp_speed[:, 10],\n",
+    "                \"forelimb speed 3d\": np.nanmean(kp_speed[:, [13, 14]], axis=1),\n",
+    "                \"hindlimb speed 3d\": np.nanmean(kp_speed[:, [10, 12]], axis=1),\n",
+    "                \"body speed 2d\": speed_2d,\n",
+    "                \"right forepaw 2d\": kp_speed_2d[:, 14],\n",
+    "                \"left forepaw 2d\": kp_speed_2d[:, 13],\n",
+    "                \"right hindpaw 2d\": kp_speed_2d[:, 12],\n",
+    "                \"left hindpaw 2d\": kp_speed_2d[:, 10],\n",
+    "                \"forelimb speed 2d\": np.nanmean(kp_speed_2d[:, [13, 14]], axis=1),\n",
+    "                \"hindlimb speed 2d\": np.nanmean(kp_speed_2d[:, [10, 12]], axis=1),\n",
+    "                \"mouse\": k,\n",
+    "            }\n",
+    "        )\n",
+    "        y = []\n",
+    "\n",
+    "        for dimension in (\"2d\", \"3d\"):\n",
+    "            X = [dlight_df[f\"body speed {dimension}\"].shift(i) for i in window]\n",
+    "            X = pd.DataFrame(np.array(X).T, columns=map(str, window), index=dlight_df.index)\n",
+    "\n",
+    "            X[f\"forelimb speed {dimension}\"] = dlight_df[f\"forelimb speed {dimension}\"]\n",
+    "            X = X.dropna()\n",
+    "\n",
+    "            mdl = LinearRegression()\n",
+    "\n",
+    "            mdl.fit(\n",
+    "                X.drop(columns=[f\"forelimb speed {dimension}\"]),\n",
+    "                X[[f\"forelimb speed {dimension}\"]],\n",
+    "            )\n",
+    "\n",
+    "            X[f\"forelimb partial {dimension}\"] = (\n",
+    "                X[f\"forelimb speed {dimension}\"]\n",
+    "                - mdl.predict(X.drop(columns=[f\"forelimb speed {dimension}\"])).squeeze()\n",
+    "            )\n",
+    "            X[f\"forelimb partial {dimension} (z)\"] = zscore(X[f\"forelimb partial {dimension}\"])\n",
+    "            X[f\"forelimb speed {dimension} (z)\"] = zscore(X[f\"forelimb speed {dimension}\"])\n",
+    "            if dimension == \"2d\":\n",
+    "                X[\"dLight\"] = dlight_df[\"dLight\"]\n",
+    "                X[\"dLight (z)\"] = zscore(X[\"dLight\"])\n",
+    "                X[\"timestamp\"] = np.arange(len(X)) / 30\n",
+    "                X[\"mouse_id\"] = k\n",
+    "            X[f\"speed {dimension} (z)\"] = zscore(X[\"0\"])\n",
+    "\n",
+    "            y.append(X.drop(columns=map(str, window)))\n",
+    "        dfs[k] = pd.concat(y, axis=1)\n",
+    "\n",
+    "    df = pd.concat(dfs.values())\n",
+    "\n",
+    "    secs = 30 * 10\n",
+    "    threshold = 1.96\n",
+    "    window = range(-secs, secs)\n",
+    "    dff_func = partial(rolling_fluor_normalization, window_size=5, quantile=0.1, normalizer=\"dff\")\n",
+    "    dfs = {}\n",
+    "\n",
+    "    for k, v in tqdm(data.items()):\n",
+    "        speed = compute_global_velocity(v[\"positions_median\"])\n",
+    "        kp_vels = compute_keypoint_velocity(v[\"positions_median\"])\n",
+    "        kp_speed = np.linalg.norm(kp_vels, axis=2)\n",
+    "\n",
+    "        speed_2d = compute_global_velocity(v[\"positions_median\"][..., :2])\n",
+    "        kp_vels_2d = compute_keypoint_velocity(v[\"positions_median\"][..., :2])\n",
+    "        kp_speed_2d = np.linalg.norm(kp_vels_2d, axis=2)\n",
+    "\n",
+    "        signal_dff = dff_func(v[\"dlight\"][2:])\n",
+    "        reference_dff = dff_func(v[\"uv\"][2:])\n",
+    "\n",
+    "        dlight_df = pd.DataFrame(\n",
+    "            {\n",
+    "                \"dlight_dff\": signal_dff,\n",
+    "                \"reference_dff\": reference_dff,\n",
+    "                \"body speed 3d\": speed,\n",
+    "                \"right forepaw 3d\": kp_speed[:, 14],\n",
+    "                \"left forepaw 3d\": kp_speed[:, 13],\n",
+    "                \"right hindpaw 3d\": kp_speed[:, 12],\n",
+    "                \"left hindpaw 3d\": kp_speed[:, 10],\n",
+    "                \"forelimb speed 3d\": np.nanmean(kp_speed[:, [13, 14]], axis=1),\n",
+    "                \"hindlimb speed 3d\": np.nanmean(kp_speed[:, [10, 12]], axis=1),\n",
+    "                \"body speed 2d\": speed_2d,\n",
+    "                \"right forepaw 2d\": kp_speed_2d[:, 14],\n",
+    "                \"left forepaw 2d\": kp_speed_2d[:, 13],\n",
+    "                \"right hindpaw 2d\": kp_speed_2d[:, 12],\n",
+    "                \"left hindpaw 2d\": kp_speed_2d[:, 10],\n",
+    "                \"forelimb speed 2d\": np.nanmean(kp_speed_2d[:, [13, 14]], axis=1),\n",
+    "                \"hindlimb speed 2d\": np.nanmean(kp_speed_2d[:, [10, 12]], axis=1),\n",
+    "                \"height\": v[\"positions_median\"][2:, 5, 2],\n",
+    "                \"mouse_id\": k,\n",
+    "                \"timestamp\": np.arange(len(speed)) / 30,\n",
+    "            }\n",
+    "        )\n",
+    "        nans = dlight_df[\"dlight_dff\"].isna()\n",
+    "        x = dlight_df.loc[~nans]\n",
+    "        dlight_df[\"dlight_reref_dff\"] = rereference(\n",
+    "            pd.Series(filter_signal(x[\"reference_dff\"]), index=x.index),\n",
+    "            x[\"dlight_dff\"],\n",
+    "            center=False,\n",
+    "            clip=False,\n",
+    "        )[\"rereference\"]\n",
+    "        dlight_df[\"dlight_reref_dff\"] = rolling_fluor_normalization(\n",
+    "            dlight_df[\"dlight_reref_dff\"], normalizer=\"zscore\", window_size=20\n",
+    "        )\n",
+    "        z_cols = [x for x in dlight_df.columns if x not in (\"mouse_id\", \"timestamp\")]\n",
+    "\n",
+    "        dlight_df[[f\"{c} (z)\" for c in z_cols]] = zscore(dlight_df[z_cols])\n",
+    "        dlight_df[\"peak_rate_cross\"] = 0\n",
+    "        z = dlight_df[\"dlight_reref_dff (z)\"].to_numpy()\n",
+    "        dlight_df.loc[dlight_df.index[1:], \"peak_rate_cross\"] = (z[:-1] < threshold) & (z[1:] > threshold)\n",
+    "        y = []\n",
+    "\n",
+    "        # partial body speed from dLight\n",
+    "        dlight_df = _partial(dlight_df, x=\"body speed 2d (z)\", y=\"dlight_reref_dff (z)\", window=window)\n",
+    "\n",
+    "        dfs[k] = dlight_df\n",
+    "    df = pd.concat(dfs.values())\n",
+    "    df[\"peak_rate_cross\"] = df[\"peak_rate_cross\"].astype(float)\n",
+    "\n",
+    "    results = bin_data(data=df, timescale=0.4, n_offsets=0, window=range(1))\n",
+    "\n",
+    "    forelimb_partial = results.groupby(\"mouse_id\", sort=False).apply(\n",
+    "        partial_out,\n",
+    "        xs=[\n",
+    "            \"height\",\n",
+    "            \"body speed 2d\",\n",
+    "            \"body speed 3d\",\n",
+    "        ],\n",
+    "        y=\"forelimb speed 3d\",\n",
+    "    )\n",
+    "    results[\"forelimb_partial\"] = forelimb_partial.droplevel(0)\n",
+    "\n",
+    "    forelimb_partial = results.groupby(\"mouse_id\", sort=False).apply(\n",
+    "        partial_out,\n",
+    "        xs=[\n",
+    "            \"height\",\n",
+    "            \"body speed 2d\",\n",
+    "            \"body speed 3d\",\n",
+    "        ],\n",
+    "        y=\"dlight_reref_dff (z)\",\n",
+    "    )\n",
+    "    results[\"dlight_partial\"] = forelimb_partial.droplevel(0)\n",
+    "\n",
+    "    corrs = results.groupby([\"timescale\", \"mouse_id\", \"neural_agg\"]).corr(method=\"pearson\")\n",
+    "    corrs.index = corrs.index.rename(\"feature\", level=-1)\n",
+    "    plot_3c(results=results)\n",
+    "\n",
+    "    timescales = np.arange(*dlight_config[\"timescale_correlation\"][\"bins\"])\n",
+    "\n",
+    "    func = partial(bin_data, data=df, n_offsets=4, window=range(1))\n",
+    "    results_list = [func(timescale=t) for t in tqdm(timescales)]\n",
+    "\n",
+    "    results = pd.concat(results_list)\n",
+    "\n",
+    "    corrs = results.groupby([\"timescale\", \"mouse_id\", \"neural_agg\"]).corr(method=\"pearson\")\n",
+    "    corrs.index = corrs.index.rename(\"feature\", level=-1)\n",
+    "    plot_3b(corrs=corrs)\n",
+    "\n",
+    "    for io in ios:\n",
+    "        io.close()\n",
+    "\n",
+    "\n",
+    "def plot_3a(summary_image):\n",
+    "    fig = plt.figure()\n",
+    "    plt.imshow(summary_image)\n",
+    "    plt.show()\n",
+    "\n",
+    "\n",
+    "def plot_3c(results):\n",
+    "    tmp = results.dropna()\n",
+    "    x = tmp[\"dlight_reref_dff (z)\"]\n",
+    "    y = tmp[\"body speed 2d (z)\"]\n",
+    "    z = get_z(x, y, 1, subsample_factor=100)\n",
+    "\n",
+    "    fig = plt.figure(figsize=(2, 2), dpi=300)\n",
+    "    plt.scatter(x, y, c=z, s=2, alpha=0.3, cmap=\"inferno\", linewidths=0)\n",
+    "    ax = sns.regplot(\n",
+    "        data=results,\n",
+    "        x=\"dlight_reref_dff (z)\",\n",
+    "        y=\"body speed 2d (z)\",\n",
+    "        n_boot=100,\n",
+    "        line_kws=dict(color=\"darkorange\"),\n",
+    "        ci=95,\n",
+    "        scatter=False,\n",
+    "    )\n",
+    "    ax.set(ylabel=\"2D velocity (z)\", xlabel=\"dF/F0 (z)\")\n",
+    "    sns.despine()\n",
+    "    plt.xlabel(\"dF/F0 (z)\")\n",
+    "    plt.ylabel(\"2D velocity (z)\")\n",
+    "    plt.show()\n",
+    "\n",
+    "    tmp = results.dropna()\n",
+    "    x = tmp[\"dlight_partial\"]\n",
+    "    y = tmp[\"forelimb speed 3d (z)\"]\n",
+    "    z = get_z(x, y, 1, subsample_factor=100)\n",
+    "\n",
+    "    fig = plt.figure(figsize=(2, 2), dpi=300)\n",
+    "    fig.dpi = 300\n",
+    "    plt.scatter(x, y, c=z, s=2, alpha=0.3, cmap=\"inferno\", linewidths=0)\n",
+    "    ax = sns.regplot(\n",
+    "        data=results,\n",
+    "        x=\"dlight_partial\",\n",
+    "        y=\"forelimb speed 3d (z)\",\n",
+    "        n_boot=100,\n",
+    "        line_kws=dict(color=\"darkorange\"),\n",
+    "        ci=95,\n",
+    "        scatter=False,\n",
+    "    )\n",
+    "    ax.set(ylabel=\"3D forelimb velocity (z)\", xlabel=\"dF/F0 (partialed; z)\")\n",
+    "    sns.despine()\n",
+    "    plt.xlabel(\"dF/F0 (partialed; z)\")\n",
+    "    plt.ylabel(\"3D forelimb velocity (z)\")\n",
+    "    plt.show()\n",
+    "\n",
+    "\n",
+    "def plot_3b(corrs):\n",
+    "    dlight_to_vel_corrs = corrs.xs(\"dlight_reref_dff (z)\", level=\"feature\")\n",
+    "    # dlight_to_vel_corrs = corrs.xs(\"dlight_dff\", level=\"feature\")\n",
+    "\n",
+    "    c_ave = dlight_to_vel_corrs.groupby([\"mouse_id\", \"timescale\", \"neural_agg\"]).mean()\n",
+    "    c_ave = c_ave.melt(ignore_index=False)\n",
+    "\n",
+    "    fig = plt.figure(figsize=(2, 2), dpi=200)\n",
+    "    ax = sns.lineplot(\n",
+    "        data=c_ave.reset_index(),\n",
+    "        x=\"timescale\",\n",
+    "        y=\"value\",\n",
+    "        hue=\"variable\",\n",
+    "        n_boot=100,\n",
+    "        hue_order=[\"body speed 2d (z)\"],\n",
+    "        errorbar=(\"ci\", 68),\n",
+    "        err_kws=dict(lw=0),\n",
+    "    )\n",
+    "    ax.axhline(0, ls=\"--\", c=\"k\")\n",
+    "    ax.set(ylabel=\"Correlation (Pearson R)\", xlabel=\"Bin duration (s)\", ylim=(-0.25, 0.2))\n",
+    "    plt.legend(frameon=False, loc=\"upper left\", bbox_to_anchor=(1, 1))\n",
+    "    sns.despine()\n",
+    "    plt.show()\n",
+    "\n",
+    "    dlight_to_vel_corrs = corrs.xs(\"peak_rate_cross\", level=\"feature\")\n",
+    "    c_ave = dlight_to_vel_corrs.groupby([\"mouse_id\", \"timescale\", \"neural_agg\"]).mean()\n",
+    "    c_ave = c_ave.melt(ignore_index=False)\n",
+    "\n",
+    "    fig = plt.figure(figsize=(2, 2), dpi=200)\n",
+    "    ax = sns.lineplot(\n",
+    "        data=c_ave.reset_index(),\n",
+    "        x=\"timescale\",\n",
+    "        y=\"value\",\n",
+    "        hue=\"variable\",\n",
+    "        n_boot=100,\n",
+    "        hue_order=[\"body speed 2d (z)\"],\n",
+    "        errorbar=(\"ci\", 68),\n",
+    "        err_kws=dict(lw=0),\n",
+    "    )\n",
+    "    ax.axhline(0, ls=\"--\", c=\"k\")\n",
+    "    ax.set(ylabel=\"Correlation (Pearson r)\", xlabel=\"Bin duration (s)\", ylim=(-0.25, 0.2))\n",
+    "    plt.legend(frameon=False, loc=\"upper left\", bbox_to_anchor=(1, 1))\n",
+    "    sns.despine()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "reproducing figure S3\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "26396f4224714d72a6a6c8d88fcec3c0",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/5 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "eb9275b08060445789d8e2624471f618",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/120 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 400x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 400x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "config_path = \"analysis_configuration.toml\"\n",
+    "reproduce_figS3(nwbfile_paths=file_paths, nwbfiles=nwbfiles, config_path=config_path, ios=ios)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "datta_notebook_env",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/000559/dattalab/markowitz_gillis_nature_2023/stream_nwbfile.py b/000559/dattalab/markowitz_gillis_nature_2023/stream_nwbfile.py
new file mode 100644
index 0000000..b5cff46
--- /dev/null
+++ b/000559/dattalab/markowitz_gillis_nature_2023/stream_nwbfile.py
@@ -0,0 +1,35 @@
+from pynwb import NWBHDF5IO
+from fsspec import filesystem
+from h5py import File
+from dandi.dandiapi import DandiAPIClient
+
+def stream_nwbfile(DANDISET_ID, file_path):
+    '''Stream NWB file from DANDI archive.
+    
+    Parameters
+    ----------
+    DANDISET_ID : str
+        Dandiset ID
+    file_path : str
+        Path to NWB file in DANDI archive
+    
+    Returns
+    -------
+    nwbfile : NWBFile
+        NWB file
+    io : NWBHDF5IO
+        NWB IO object (for closing)
+        
+    Notes
+    -----
+    The io object must be closed after use.
+    '''
+    with DandiAPIClient() as client:
+        asset = client.get_dandiset(DANDISET_ID, 'draft').get_asset_by_path(file_path)
+        s3_url = asset.get_content_url(follow_redirects=1, strip_query=True)
+    fs = filesystem("http")
+    file_system = fs.open(s3_url, "rb")
+    file = File(file_system, mode="r")
+    io = NWBHDF5IO(file=file, load_namespaces=True)
+    nwbfile = io.read()
+    return nwbfile, io
\ No newline at end of file
diff --git a/000582/Sargolini2006/000582_Sargolini2006_demo.ipynb b/000582/Sargolini2006/000582_Sargolini2006_demo.ipynb
new file mode 100644
index 0000000..0caef73
--- /dev/null
+++ b/000582/Sargolini2006/000582_Sargolini2006_demo.ipynb
@@ -0,0 +1,154587 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "6746672a",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "# Educational notebook based on Sargolini 2006\n",
+    "\n",
+    "\n",
+    "This tutorial demonstrates how to access the dataset published in [Sargolini et al. (Science, 2006)](https://doi.org/10.1126/science.1125572) using `dandi`.\n",
+    "\n",
+    "The [dataset](https://dandiarchive.org/dandiset/000582/draft) contains spike times for recorded grid cells from the medial entorhinal cortex (MEC) in rats that explored two-dimensional environments. The behavioral data includes position from the tracking LED(s).\n",
+    "\n",
+    "\n",
+    "#### Contents:\n",
+    "\n",
+    "* [Streaming NWB files](#stream-nwb)\n",
+    "* [Accessing data and metadata](#access-nwb)\n",
+    "* [Accessing behavior data](#position)\n",
+    "* [Accessing spike times](#spike-times)\n",
+    "* [Showing rate maps](#rate-maps)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1dce9ed7",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## Streaming NWB files <a class=\"anchor\" id=\"stream-nwb\"></a>\n",
+    "\n",
+    "This section demonstrates how to access the files on DANDI without downloading them.\n",
+    "\n",
+    "Based on the [Streaming NWB files](https://pynwb.readthedocs.io/en/stable/tutorials/advanced_io/streaming.html) tutorial from `PyNWB`.\n",
+    "\n",
+    "The `DandiAPIClient` can be used to get the S3 URL of the NWB file stored in the DANDI Archive."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "528383c1",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%%\n"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from dandi.dandiapi import DandiAPIClient\n",
+    "\n",
+    "dandiset_id, nwbfile_path = \"000582\", \"sub-10073/sub-10073_ses-17010302_behavior+ecephys.nwb\" # file size ~15.6MB\n",
+    "\n",
+    "# Get the location of the file on DANDI\n",
+    "with DandiAPIClient() as client:\n",
+    "    asset = client.get_dandiset(dandiset_id, 'draft').get_asset_by_path(nwbfile_path)\n",
+    "    s3_url = asset.get_content_url(follow_redirects=1, strip_query=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e3baab9f",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "Create a virtual filesystem using `fsspec` which will take care of requesting data from the S3 bucket whenever data is read from the virtual file."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "25589af3",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "is_executing": true,
+     "name": "#%%\n"
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <style>\n",
+       "            .container-fields {\n",
+       "                font-family: \"Open Sans\", Arial, sans-serif;\n",
+       "            }\n",
+       "            .container-fields .field-value {\n",
+       "                color: #00788E;\n",
+       "            }\n",
+       "            .container-fields details > summary {\n",
+       "                cursor: pointer;\n",
+       "                display: list-item;\n",
+       "            }\n",
+       "            .container-fields details > summary:hover {\n",
+       "                color: #0A6EAA;\n",
+       "            }\n",
+       "        </style>\n",
+       "        \n",
+       "        <script>\n",
+       "            function copyToClipboard(text) {\n",
+       "                navigator.clipboard.writeText(text).then(function() {\n",
+       "                    console.log('Copied to clipboard: ' + text);\n",
+       "                }, function(err) {\n",
+       "                    console.error('Could not copy text: ', err);\n",
+       "                });\n",
+       "            }\n",
+       "\n",
+       "            document.addEventListener('DOMContentLoaded', function() {\n",
+       "                let fieldKeys = document.querySelectorAll('.container-fields .field-key');\n",
+       "                fieldKeys.forEach(function(fieldKey) {\n",
+       "                    fieldKey.addEventListener('click', function() {\n",
+       "                        let accessCode = fieldKey.getAttribute('title').replace('Access code: ', '');\n",
+       "                        copyToClipboard(accessCode);\n",
+       "                    });\n",
+       "                });\n",
+       "            });\n",
+       "        </script>\n",
+       "        <div class='container-wrap'><div class='container-header'><div class='xr-obj-type'><h3>root (NWBFile)</h3></div></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['session_description']\">session_description:</span> <span class=\"field-value\">This session includes spike and position times for recorded cells from a Long Evans rat that was running in a 1 x 1 meter enclosure. The cells were recorded in the dorsocaudal 25% portion of the medial entorhinal cortex (MEC).Position is given for two LEDs to enable calculation of head direction.</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['identifier']\">identifier:</span> <span class=\"field-value\">294b7de1-a624-44d8-b1a1-28028dd2cf0c</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['session_start_time']\">session_start_time:</span> <span class=\"field-value\">1900-01-01 00:00:00+01:00</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['timestamps_reference_time']\">timestamps_reference_time:</span> <span class=\"field-value\">1900-01-01 00:00:00+01:00</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['file_create_date']\"><b>file_create_date</b></summary><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-value\" title=\".fields['file_create_date'][0]\">2023-09-16 15:50:09.775622+02:00</span></div></details><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['experimenter']\">experimenter:</span> <span class=\"field-value\">('Sargolini, Francesca',)</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['related_publications']\">related_publications:</span> <span class=\"field-value\">('https://doi.org/10.1126/science.1125572',)</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['acquisition']\"><b>acquisition (1)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['ElectricalSeries']\"><b>ElectricalSeries</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['ElectricalSeries'].fields['starting_time']\">starting_time:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['ElectricalSeries'].fields['rate']\">rate:</span> <span class=\"field-value\">4800.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['ElectricalSeries'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['ElectricalSeries'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['ElectricalSeries'].fields['description']\">description:</span> <span class=\"field-value\">The EEG signals from one electrode amplified 8000-10000 times, lowpass-filtered at 500 Hz (single pole), and stored at 4800 Hz (16 bits/sample).</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['ElectricalSeries'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1e-06</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['ElectricalSeries'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['ElectricalSeries'].fields['unit']\">unit:</span> <span class=\"field-value\">volts</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['ElectricalSeries'].fields['data']\"><b>data</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['ElectricalSeries'].fields['starting_time_unit']\">starting_time_unit:</span> <span class=\"field-value\">seconds</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['ElectricalSeries'].fields['electrodes']\"><b>electrodes</b></summary><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['ElectricalSeries'].fields['electrodes'].fields['description']\">description:</span> <span class=\"field-value\">all electrodes</span></div><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['ElectricalSeries'].fields['electrodes'].fields['table']\"><b>table</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['ElectricalSeries'].fields['electrodes'].fields['table'].fields['description']\">description:</span> <span class=\"field-value\">metadata about extracellular electrodes</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['ElectricalSeries'].fields['electrodes'].fields['table'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['ElectricalSeries'].fields['electrodes'].fields['table'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('location', 'group', 'group_name')</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['ElectricalSeries'].fields['electrodes'].fields['table'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorData object at 0x287e5b790>, <hdmf.common.table.VectorData object at 0x287e5b090>, <hdmf.common.table.VectorData object at 0x287e5b350>)</span></div></details></details></details></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['keywords']\"><b>keywords</b></summary></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['processing']\"><b>processing (2)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior']\"><b>behavior</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['description']\">description:</span> <span class=\"field-value\">Processed behavioral data.</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']\"><b>data_interfaces (1)</b></summary><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position']\"><b>Position</b></summary><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']\"><b>spatial_series (1)</b></summary><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesLED1']\"><b>SpatialSeriesLED1</b></summary><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesLED1'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesLED1'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesLED1'].fields['description']\">description:</span> <span class=\"field-value\">Position (x, y) for the first tracking LED.</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesLED1'].fields['conversion']\">conversion:</span> <span class=\"field-value\">0.01</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesLED1'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesLED1'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesLED1'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesLED1'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesLED1'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesLED1'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesLED1'].fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is not known.</span></div></details></details></details></details></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['processing']['ecephys']\"><b>ecephys</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ecephys'].fields['description']\">description:</span> <span class=\"field-value\">Processed electrical series data.</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']\"><b>data_interfaces (1)</b></summary><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP']\"><b>LFP</b></summary><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']\"><b>electrical_series (1)</b></summary><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP']\"><b>ElectricalSeriesLFP</b></summary><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP'].fields['starting_time']\">starting_time:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP'].fields['rate']\">rate:</span> <span class=\"field-value\">250.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP'].fields['description']\">description:</span> <span class=\"field-value\">The EEG signals from one electrode stored at 250 Hz.</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1e-06</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP'].fields['unit']\">unit:</span> <span class=\"field-value\">volts</span></div><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP'].fields['data']\"><b>data</b></summary></details><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP'].fields['starting_time_unit']\">starting_time_unit:</span> <span class=\"field-value\">seconds</span></div><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP'].fields['electrodes']\"><b>electrodes</b></summary><div style=\"margin-left: 140px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP'].fields['electrodes'].fields['description']\">description:</span> <span class=\"field-value\">all electrodes</span></div><details><summary style=\"display: list-item; margin-left: 140px;\" class=\"container-fields field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP'].fields['electrodes'].fields['table']\"><b>table</b></summary><div style=\"margin-left: 160px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP'].fields['electrodes'].fields['table'].fields['description']\">description:</span> <span class=\"field-value\">metadata about extracellular electrodes</span></div><details><summary style=\"display: list-item; margin-left: 160px;\" class=\"container-fields field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP'].fields['electrodes'].fields['table'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 160px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP'].fields['electrodes'].fields['table'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('location', 'group', 'group_name')</span></div><div style=\"margin-left: 160px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ecephys'].fields['data_interfaces']['LFP'].fields['electrical_series']['ElectricalSeriesLFP'].fields['electrodes'].fields['table'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorData object at 0x287e5b790>, <hdmf.common.table.VectorData object at 0x287e5b090>, <hdmf.common.table.VectorData object at 0x287e5b350>)</span></div></details></details></details></details></details></details></details></details><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['epoch_tags']\">epoch_tags:</span> <span class=\"field-value\">set()</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['electrodes']\"><b>electrodes</b></summary><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrodes'].fields['description']\">description:</span> <span class=\"field-value\">metadata about extracellular electrodes</span></div><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['electrodes'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrodes'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('location', 'group', 'group_name')</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrodes'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorData object at 0x287e5b790>, <hdmf.common.table.VectorData object at 0x287e5b090>, <hdmf.common.table.VectorData object at 0x287e5b350>)</span></div></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['electrode_groups']\"><b>electrode_groups (1)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['electrode_groups']['ElectrodeGroup']\"><b>ElectrodeGroup</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrode_groups']['ElectrodeGroup'].fields['description']\">description:</span> <span class=\"field-value\">The name of the ElectrodeGroup this electrode is a part of.</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrode_groups']['ElectrodeGroup'].fields['location']\">location:</span> <span class=\"field-value\">MEC</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['electrode_groups']['ElectrodeGroup'].fields['device']\"><b>device</b></summary><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['electrode_groups']['ElectrodeGroup'].fields['device'].fields['description']\">description:</span> <span class=\"field-value\">The device used to record EEG signals.</span></div></details></details></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['devices']\"><b>devices (1)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['devices']['EEG']\"><b>EEG</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['devices']['EEG'].fields['description']\">description:</span> <span class=\"field-value\">The device used to record EEG signals.</span></div></details></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['subject']\"><b>subject</b></summary><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['age']\">age:</span> <span class=\"field-value\">P3M/P5M</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['age__reference']\">age__reference:</span> <span class=\"field-value\">birth</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['description']\">description:</span> <span class=\"field-value\">A Long Evans rat.</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['sex']\">sex:</span> <span class=\"field-value\">M</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['species']\">species:</span> <span class=\"field-value\">Rattus norvegicus</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['subject_id']\">subject_id:</span> <span class=\"field-value\">10073</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['weight']\">weight:</span> <span class=\"field-value\">0.35/0.45</span></div></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['units']\"><b>units</b></summary><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['units'].fields['description']\">description:</span> <span class=\"field-value\">Autogenerated by NWBFile</span></div><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['units'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['units'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('unit_name', 'spike_times', 'histology', 'hemisphere', 'depth')</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['units'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorData object at 0x287e8d4d0>, <hdmf.common.table.VectorIndex object at 0x287e8d390>, <hdmf.common.table.VectorData object at 0x287e8d650>, <hdmf.common.table.VectorData object at 0x287e8dad0>, <hdmf.common.table.VectorData object at 0x287e8d910>, <hdmf.common.table.VectorData object at 0x287e8ce50>)</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['units'].fields['waveform_unit']\">waveform_unit:</span> <span class=\"field-value\">volts</span></div></details><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['experiment_description']\">experiment_description:</span> <span class=\"field-value\">The sample includes conjunctive cells and head direction cells from layers III and V of medial entorhinal cortex and have been published in Sargolini et al. (Science, 2006).</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['session_id']\">session_id:</span> <span class=\"field-value\">17010302</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab']\">lab:</span> <span class=\"field-value\">Moser</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['institution']\">institution:</span> <span class=\"field-value\">Centre for the Biology of Memory, Norwegian University of Science and Technology</span></div></div>"
+      ],
+      "text/plain": [
+       "root pynwb.file.NWBFile at 0x10869655760\n",
+       "Fields:\n",
+       "  acquisition: {\n",
+       "    ElectricalSeries <class 'pynwb.ecephys.ElectricalSeries'>\n",
+       "  }\n",
+       "  devices: {\n",
+       "    EEG <class 'pynwb.device.Device'>\n",
+       "  }\n",
+       "  electrode_groups: {\n",
+       "    ElectrodeGroup <class 'pynwb.ecephys.ElectrodeGroup'>\n",
+       "  }\n",
+       "  electrodes: electrodes <class 'hdmf.common.table.DynamicTable'>\n",
+       "  experiment_description: The sample includes conjunctive cells and head direction cells from layers III and V of medial entorhinal cortex and have been published in Sargolini et al. (Science, 2006).\n",
+       "  experimenter: ['Sargolini, Francesca']\n",
+       "  file_create_date: [datetime.datetime(2023, 9, 16, 15, 50, 9, 775622, tzinfo=tzoffset(None, 7200))]\n",
+       "  identifier: 294b7de1-a624-44d8-b1a1-28028dd2cf0c\n",
+       "  institution: Centre for the Biology of Memory, Norwegian University of Science and Technology\n",
+       "  keywords: <StrDataset for HDF5 dataset \"keywords\": shape (3,), type \"|O\">\n",
+       "  lab: Moser\n",
+       "  processing: {\n",
+       "    behavior <class 'pynwb.base.ProcessingModule'>,\n",
+       "    ecephys <class 'pynwb.base.ProcessingModule'>\n",
+       "  }\n",
+       "  related_publications: ['https://doi.org/10.1126/science.1125572']\n",
+       "  session_description: This session includes spike and position times for recorded cells from a Long Evans rat that was running in a 1 x 1 meter enclosure. The cells were recorded in the dorsocaudal 25% portion of the medial entorhinal cortex (MEC).Position is given for two LEDs to enable calculation of head direction.\n",
+       "  session_id: 17010302\n",
+       "  session_start_time: 1900-01-01 00:00:00+01:00\n",
+       "  subject: subject pynwb.file.Subject at 0x10869908176\n",
+       "Fields:\n",
+       "  age: P3M/P5M\n",
+       "  age__reference: birth\n",
+       "  description: A Long Evans rat.\n",
+       "  sex: M\n",
+       "  species: Rattus norvegicus\n",
+       "  subject_id: 10073\n",
+       "  weight: 0.35/0.45\n",
+       "\n",
+       "  timestamps_reference_time: 1900-01-01 00:00:00+01:00\n",
+       "  units: units <class 'pynwb.misc.Units'>"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from fsspec.implementations.cached import CachingFileSystem\n",
+    "from fsspec import filesystem\n",
+    "from h5py import File\n",
+    "from pynwb import NWBHDF5IO\n",
+    "\n",
+    "# first, create a virtual filesystem based on the http protocol\n",
+    "fs=filesystem(\"http\")\n",
+    "\n",
+    "# create a cache to save downloaded data to disk (optional)\n",
+    "fs = CachingFileSystem(\n",
+    "    fs=fs,\n",
+    "    cache_storage=\"nwb-cache\",  # Local folder for the cache\n",
+    ")\n",
+    "\n",
+    "file_system = fs.open(s3_url, \"rb\")\n",
+    "file = File(file_system, mode=\"r\")\n",
+    "# Open the file with NWBHDF5IO\n",
+    "io = NWBHDF5IO(file=file, load_namespaces=True)\n",
+    "\n",
+    "nwbfile = io.read()\n",
+    "nwbfile"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6db38c3d",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## Access data and metadata <a class=\"anchor\" id=\"access-nwb\"></a>\n",
+    "\n",
+    "This section demonstrates how to access the data in the NWB files."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "268b092f-30dc-4bb2-9dc9-1d126616d49b",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "source": [
+    "### Subject\n",
+    "\n",
+    "The `nwbfile.subject` field holds information about the experimental subject, such as age (in [ISO 8601 Duration format](https://en.wikipedia.org/wiki/ISO_8601#Durations)), sex, and species in latin binomial nomenclature."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "02cb1664",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%%\n"
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <style>\n",
+       "            .container-fields {\n",
+       "                font-family: \"Open Sans\", Arial, sans-serif;\n",
+       "            }\n",
+       "            .container-fields .field-value {\n",
+       "                color: #00788E;\n",
+       "            }\n",
+       "            .container-fields details > summary {\n",
+       "                cursor: pointer;\n",
+       "                display: list-item;\n",
+       "            }\n",
+       "            .container-fields details > summary:hover {\n",
+       "                color: #0A6EAA;\n",
+       "            }\n",
+       "        </style>\n",
+       "        \n",
+       "        <script>\n",
+       "            function copyToClipboard(text) {\n",
+       "                navigator.clipboard.writeText(text).then(function() {\n",
+       "                    console.log('Copied to clipboard: ' + text);\n",
+       "                }, function(err) {\n",
+       "                    console.error('Could not copy text: ', err);\n",
+       "                });\n",
+       "            }\n",
+       "\n",
+       "            document.addEventListener('DOMContentLoaded', function() {\n",
+       "                let fieldKeys = document.querySelectorAll('.container-fields .field-key');\n",
+       "                fieldKeys.forEach(function(fieldKey) {\n",
+       "                    fieldKey.addEventListener('click', function() {\n",
+       "                        let accessCode = fieldKey.getAttribute('title').replace('Access code: ', '');\n",
+       "                        copyToClipboard(accessCode);\n",
+       "                    });\n",
+       "                });\n",
+       "            });\n",
+       "        </script>\n",
+       "        <div class='container-wrap'><div class='container-header'><div class='xr-obj-type'><h3>subject (Subject)</h3></div></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['age']\">age:</span> <span class=\"field-value\">P3M/P5M</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['age__reference']\">age__reference:</span> <span class=\"field-value\">birth</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['description']\">description:</span> <span class=\"field-value\">A Long Evans rat.</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['sex']\">sex:</span> <span class=\"field-value\">M</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['species']\">species:</span> <span class=\"field-value\">Rattus norvegicus</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject_id']\">subject_id:</span> <span class=\"field-value\">10073</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['weight']\">weight:</span> <span class=\"field-value\">0.35/0.45</span></div></div>"
+      ],
+      "text/plain": [
+       "subject pynwb.file.Subject at 0x10869908176\n",
+       "Fields:\n",
+       "  age: P3M/P5M\n",
+       "  age__reference: birth\n",
+       "  description: A Long Evans rat.\n",
+       "  sex: M\n",
+       "  species: Rattus norvegicus\n",
+       "  subject_id: 10073\n",
+       "  weight: 0.35/0.45"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nwbfile.subject"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8d607786",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## Accessing behavior data <a class=\"anchor\" id=\"position\"></a>\n",
+    "\n",
+    "The \"behavior\" processing module holds the behavior data in the NWB file which can be accessed as\n",
+    "`nwbfile.processing[\"behavior\"]`.\n",
+    "\n",
+    "### Position\n",
+    "\n",
+    "The position data is stored in a `SpatialSeries` object which can be accessed from the \"Position\" container as `nwbfile.processing[\"behavior\"][\"Position\"]`.\n",
+    "\n",
+    "\n",
+    "Note that not all sessions have position data from two tracking LEDs."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "90c0b29a",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%%\n"
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <style>\n",
+       "            .container-fields {\n",
+       "                font-family: \"Open Sans\", Arial, sans-serif;\n",
+       "            }\n",
+       "            .container-fields .field-value {\n",
+       "                color: #00788E;\n",
+       "            }\n",
+       "            .container-fields details > summary {\n",
+       "                cursor: pointer;\n",
+       "                display: list-item;\n",
+       "            }\n",
+       "            .container-fields details > summary:hover {\n",
+       "                color: #0A6EAA;\n",
+       "            }\n",
+       "        </style>\n",
+       "        \n",
+       "        <script>\n",
+       "            function copyToClipboard(text) {\n",
+       "                navigator.clipboard.writeText(text).then(function() {\n",
+       "                    console.log('Copied to clipboard: ' + text);\n",
+       "                }, function(err) {\n",
+       "                    console.error('Could not copy text: ', err);\n",
+       "                });\n",
+       "            }\n",
+       "\n",
+       "            document.addEventListener('DOMContentLoaded', function() {\n",
+       "                let fieldKeys = document.querySelectorAll('.container-fields .field-key');\n",
+       "                fieldKeys.forEach(function(fieldKey) {\n",
+       "                    fieldKey.addEventListener('click', function() {\n",
+       "                        let accessCode = fieldKey.getAttribute('title').replace('Access code: ', '');\n",
+       "                        copyToClipboard(accessCode);\n",
+       "                    });\n",
+       "                });\n",
+       "            });\n",
+       "        </script>\n",
+       "        <div class='container-wrap'><div class='container-header'><div class='xr-obj-type'><h3>SpatialSeriesLED1 (SpatialSeries)</h3></div></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['description']\">description:</span> <span class=\"field-value\">Position (x, y) for the first tracking LED.</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['conversion']\">conversion:</span> <span class=\"field-value\">0.01</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is not known.</span></div></div>"
+      ],
+      "text/plain": [
+       "SpatialSeriesLED1 pynwb.behavior.SpatialSeries at 0x10869907472\n",
+       "Fields:\n",
+       "  comments: no comments\n",
+       "  conversion: 0.01\n",
+       "  data: <HDF5 dataset \"data\": shape (30000, 2), type \"<f8\">\n",
+       "  description: Position (x, y) for the first tracking LED.\n",
+       "  interval: 1\n",
+       "  offset: 0.0\n",
+       "  reference_frame: (0,0) is not known.\n",
+       "  resolution: -1.0\n",
+       "  timestamps: <HDF5 dataset \"timestamps\": shape (30000,), type \"<f8\">\n",
+       "  timestamps_unit: seconds\n",
+       "  unit: meters"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "spatial_series = nwbfile.processing[\"behavior\"][\"Position\"][\"SpatialSeriesLED1\"]\n",
+    "spatial_series"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "b9158a6c",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%%\n"
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "        <script type=\"text/javascript\">\n",
+       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
+       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
+       "        if (typeof require !== 'undefined') {\n",
+       "        require.undef(\"plotly\");\n",
+       "        define('plotly', function(require, exports, module) {\n",
+       "            /**\n",
+       "* plotly.js v2.26.0\n",
+       "* Copyright 2012-2023, Plotly, Inc.\n",
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F=e.borderwidth,B=e.borderpad,N=F+B,j=R.append(\"rect\").attr(\"class\",\"bg\").style(\"stroke-width\",F+\"px\").call(u.stroke,e.bordercolor).call(u.fill,e.bgcolor),U=e.width||e.height,V=w._topclips.selectAll(\"#\"+L).data(U?[0]:[]);V.enter().append(\"clipPath\").classed(\"annclip\",!0).attr(\"id\",L).append(\"rect\"),V.exit().remove();var H=e.font,q=w._meta?o.templateString(e.text,w._meta):e.text,G=R.append(\"text\").classed(\"annotation-text\",!0).text(q);k.annotationText?G.call(h.makeEditable,{delegate:R,gd:t}).call(Y).on(\"edit\",(function(r){e.text=r,this.call(Y),S(\"text\",r),y&&y.autorange&&M(y._name+\".autorange\",!0),x&&x.autorange&&M(x._name+\".autorange\",!0),i.call(\"_guiRelayout\",t,E())})):G.call(Y)}else n.selectAll(\"#\"+L).remove();function Z(t){var n={index:r,annotation:e._input,fullAnnotation:e,event:t};return a&&(n.subplotId=a),n}function Y(r){return 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kt,At=function(r,n){O.selectAll(\".annotation-arrow-g\").remove();var l=C.x.head,f=C.y.head,h=C.x.tail+r,p=C.y.tail+n,v=C.x.text+r,b=C.y.text+n,_=o.rotationXYMatrix(P,v,b),w=o.apply2DTransform(_),A=o.apply2DTransform2(_),L=+j.attr(\"width\"),D=+j.attr(\"height\"),z=v-.5*L,F=z+L,B=b-.5*D,N=B+D,U=[[z,B,z,N],[z,N,F,N],[F,N,F,B],[F,B,z,B]].map(A);if(!U.reduce((function(t,e){return t^!!o.segmentsIntersect(l,f,l+1e6,f+1e6,e[0],e[1],e[2],e[3])}),!1)){U.forEach((function(t){var e=o.segmentsIntersect(h,p,l,f,t[0],t[1],t[2],t[3]);e&&(h=e.x,p=e.y)}));var V=e.arrowwidth,H=e.arrowcolor,q=e.arrowside,G=O.append(\"g\").style({opacity:u.opacity(H)}).classed(\"annotation-arrow-g\",!0),Z=G.append(\"path\").attr(\"d\",\"M\"+h+\",\"+p+\"L\"+l+\",\"+f).style(\"stroke-width\",V+\"px\").call(u.stroke,u.rgb(H));if(g(Z,q,e),k.annotationPosition&&Z.node().parentNode&&!a){var Y=l,W=f;if(e.standoff){var X=Math.sqrt(Math.pow(l-h,2)+Math.pow(f-p,2));Y+=e.standoff*(h-l)/X,W+=e.standoff*(p-f)/X}var J,K,$=G.append(\"path\").classed(\"annotation-arrow\",!0).classed(\"anndrag\",!0).classed(\"cursor-move\",!0).attr({d:\"M3,3H-3V-3H3ZM0,0L\"+(h-Y)+\",\"+(p-W),transform:s(Y,W)}).style(\"stroke-width\",V+6+\"px\").call(u.stroke,\"rgba(0,0,0,0)\").call(u.fill,\"rgba(0,0,0,0)\");d.init({element:$.node(),gd:t,prepFn:function(){var t=c.getTranslate(R);J=t.x,K=t.y,y&&y.autorange&&M(y._name+\".autorange\",!0),x&&x.autorange&&M(x._name+\".autorange\",!0)},moveFn:function(t,r){var n=w(J,K),i=n[0]+t,a=n[1]+r;R.call(c.setTranslate,i,a),S(\"x\",m(y,t,\"x\",T,e)),S(\"y\",m(x,r,\"y\",T,e)),e.axref===e.xref&&S(\"ax\",m(y,t,\"ax\",T,e)),e.ayref===e.yref&&S(\"ay\",m(x,r,\"ay\",T,e)),G.attr(\"transform\",s(t,r)),I.attr({transform:\"rotate(\"+P+\",\"+i+\",\"+a+\")\"})},doneFn:function(){i.call(\"_guiRelayout\",t,E());var 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e=t._fullLayout;e._infolayer.selectAll(\".annotation\").remove();for(var r=0;r<e.annotations.length;r++)e.annotations[r].visible&&y(t,r);return a.previousPromises(t)},drawOne:y,drawRaw:x}},13011:function(t,e,r){\"use strict\";var n=r(39898),i=r(7901),a=r(82884),o=r(71828),s=o.strScale,l=o.strRotate,u=o.strTranslate;t.exports=function(t,e,r){var o,c,f,h,p=t.node(),d=a[r.arrowhead||0],v=a[r.startarrowhead||0],g=(r.arrowwidth||1)*(r.arrowsize||1),y=(r.arrowwidth||1)*(r.startarrowsize||1),m=e.indexOf(\"start\")>=0,x=e.indexOf(\"end\")>=0,b=d.backoff*g+r.standoff,_=v.backoff*y+r.startstandoff;if(\"line\"===p.nodeName){o={x:+t.attr(\"x1\"),y:+t.attr(\"y1\")},c={x:+t.attr(\"x2\"),y:+t.attr(\"y2\")};var w=o.x-c.x,T=o.y-c.y;if(h=(f=Math.atan2(T,w))+Math.PI,b&&_&&b+_>Math.sqrt(w*w+T*T))return void D();if(b){if(b*b>w*w+T*T)return void D();var k=b*Math.cos(f),A=b*Math.sin(f);c.x+=k,c.y+=A,t.attr({x2:c.x,y2:c.y})}if(_){if(_*_>w*w+T*T)return void D();var 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n=r(92605),i=r(44317);t.exports={moduleType:\"component\",name:\"annotations\",layoutAttributes:r(50215),supplyLayoutDefaults:r(84046),includeBasePlot:r(76325)(\"annotations\"),calcAutorange:r(3749),draw:n.draw,drawOne:n.drawOne,drawRaw:n.drawRaw,hasClickToShow:i.hasClickToShow,onClick:i.onClick,convertCoords:r(94128)}},26997:function(t,e,r){\"use strict\";var n=r(50215),i=r(30962).overrideAll,a=r(44467).templatedArray;t.exports=i(a(\"annotation\",{visible:n.visible,x:{valType:\"any\"},y:{valType:\"any\"},z:{valType:\"any\"},ax:{valType:\"number\"},ay:{valType:\"number\"},xanchor:n.xanchor,xshift:n.xshift,yanchor:n.yanchor,yshift:n.yshift,text:n.text,textangle:n.textangle,font:n.font,width:n.width,height:n.height,opacity:n.opacity,align:n.align,valign:n.valign,bgcolor:n.bgcolor,bordercolor:n.bordercolor,borderpad:n.borderpad,borderwidth:n.borderwidth,showarrow:n.showarrow,arrowcolor:n.arrowcolor,arrowhead:n.arrowhead,startarrowhead:n.startarrowhead,arrowside:n.arrowside,arrowsize:n.arrowsize,startarrowsize:n.startarrowsize,arrowwidth:n.arrowwidth,standoff:n.standoff,startstandoff:n.startstandoff,hovertext:n.hovertext,hoverlabel:n.hoverlabel,captureevents:n.captureevents}),\"calc\",\"from-root\")},5485:function(t,e,r){\"use strict\";var n=r(71828),i=r(89298);function a(t,e){var r=e.fullSceneLayout.domain,a=e.fullLayout._size,o={pdata:null,type:\"linear\",autorange:!1,range:[-1/0,1/0]};t._xa={},n.extendFlat(t._xa,o),i.setConvert(t._xa),t._xa._offset=a.l+r.x[0]*a.w,t._xa.l2p=function(){return.5*(1+t._pdata[0]/t._pdata[3])*a.w*(r.x[1]-r.x[0])},t._ya={},n.extendFlat(t._ya,o),i.setConvert(t._ya),t._ya._offset=a.t+(1-r.y[1])*a.h,t._ya.l2p=function(){return.5*(1-t._pdata[1]/t._pdata[3])*a.h*(r.y[1]-r.y[0])}}t.exports=function(t){for(var e=t.fullSceneLayout.annotations,r=0;r<e.length;r++)a(e[r],t);t.fullLayout._infolayer.selectAll(\".annotation-\"+t.id).remove()}},20226:function(t,e,r){\"use strict\";var n=r(71828),i=r(89298),a=r(85501),o=r(25625),s=r(26997);function l(t,e,r,a){function l(r,i){return n.coerce(t,e,s,r,i)}function u(t){var n=t+\"axis\",a={_fullLayout:{}};return a._fullLayout[n]=r[n],i.coercePosition(e,a,l,t,t,.5)}l(\"visible\")&&(o(t,e,a.fullLayout,l),u(\"x\"),u(\"y\"),u(\"z\"),n.noneOrAll(t,e,[\"x\",\"y\",\"z\"]),e.xref=\"x\",e.yref=\"y\",e.zref=\"z\",l(\"xanchor\"),l(\"yanchor\"),l(\"xshift\"),l(\"yshift\"),e.showarrow&&(e.axref=\"pixel\",e.ayref=\"pixel\",l(\"ax\",-10),l(\"ay\",-30),n.noneOrAll(t,e,[\"ax\",\"ay\"])))}t.exports=function(t,e,r){a(t,e,{name:\"annotations\",handleItemDefaults:l,fullLayout:r.fullLayout})}},82188:function(t,e,r){\"use strict\";var n=r(92605).drawRaw,i=r(63538),a=[\"x\",\"y\",\"z\"];t.exports=function(t){for(var e=t.fullSceneLayout,r=t.dataScale,o=e.annotations,s=0;s<o.length;s++){for(var l=o[s],u=!1,c=0;c<3;c++){var f=a[c],h=l[f],p=e[f+\"axis\"].r2fraction(h);if(p<0||p>1){u=!0;break}}u?t.fullLayout._infolayer.select(\".annotation-\"+t.id+'[data-index=\"'+s+'\"]').remove():(l._pdata=i(t.glplot.cameraParams,[e.xaxis.r2l(l.x)*r[0],e.yaxis.r2l(l.y)*r[1],e.zaxis.r2l(l.z)*r[2]]),n(t.graphDiv,l,s,t.id,l._xa,l._ya))}}},2468:function(t,e,r){\"use strict\";var n=r(73972),i=r(71828);t.exports={moduleType:\"component\",name:\"annotations3d\",schema:{subplots:{scene:{annotations:r(26997)}}},layoutAttributes:r(26997),handleDefaults:r(20226),includeBasePlot:function(t,e){var r=n.subplotsRegistry.gl3d;if(r)for(var a=r.attrRegex,o=Object.keys(t),s=0;s<o.length;s++){var l=o[s];a.test(l)&&(t[l].annotations||[]).length&&(i.pushUnique(e._basePlotModules,r),i.pushUnique(e._subplots.gl3d,l))}},convert:r(5485),draw:r(82188)}},7561:function(t,e,r){\"use 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n=l(t*f*.8,2),i=l(.8*t,2),a=l(1.6*t,2),o=l(4*t,2),s=\"A \"+o+\",\"+o+\" 0 0 1 \";return g(e,r,\"M-\"+n+\",\"+i+s+n+\",\"+i+s+\"0,-\"+a+s+\"-\"+n+\",\"+i+\"Z\")}},\"star-triangle-down\":{n:20,f:function(t,e,r){if(v(e))return u;var n=l(t*f*.8,2),i=l(.8*t,2),a=l(1.6*t,2),o=l(4*t,2),s=\"A \"+o+\",\"+o+\" 0 0 1 \";return g(e,r,\"M\"+n+\",-\"+i+s+\"-\"+n+\",-\"+i+s+\"0,\"+a+s+n+\",-\"+i+\"Z\")}},\"star-square\":{n:21,f:function(t,e,r){if(v(e))return u;var n=l(1.1*t,2),i=l(2*t,2),a=\"A \"+i+\",\"+i+\" 0 0 1 \";return g(e,r,\"M-\"+n+\",-\"+n+a+\"-\"+n+\",\"+n+a+n+\",\"+n+a+n+\",-\"+n+a+\"-\"+n+\",-\"+n+\"Z\")}},\"star-diamond\":{n:22,f:function(t,e,r){if(v(e))return u;var n=l(1.4*t,2),i=l(1.9*t,2),a=\"A \"+i+\",\"+i+\" 0 0 1 \";return g(e,r,\"M-\"+n+\",0\"+a+\"0,\"+n+a+n+\",0\"+a+\"0,-\"+n+a+\"-\"+n+\",0Z\")}},\"diamond-tall\":{n:23,f:function(t,e,r){if(v(e))return u;var n=l(.7*t,2),i=l(1.4*t,2);return g(e,r,\"M0,\"+i+\"L\"+n+\",0L0,-\"+i+\"L-\"+n+\",0Z\")}},\"diamond-wide\":{n:24,f:function(t,e,r){if(v(e))return u;var n=l(1.4*t,2),i=l(.7*t,2);return g(e,r,\"M0,\"+i+\"L\"+n+\",0L0,-\"+i+\"L-\"+n+\",0Z\")}},hourglass:{n:25,f:function(t,e,r){if(v(e))return u;var n=l(t,2);return g(e,r,\"M\"+n+\",\"+n+\"H-\"+n+\"L\"+n+\",-\"+n+\"H-\"+n+\"Z\")},noDot:!0},bowtie:{n:26,f:function(t,e,r){if(v(e))return u;var n=l(t,2);return g(e,r,\"M\"+n+\",\"+n+\"V-\"+n+\"L-\"+n+\",\"+n+\"V-\"+n+\"Z\")},noDot:!0},\"circle-cross\":{n:27,f:function(t,e,r){if(v(e))return u;var n=l(t,2);return g(e,r,\"M0,\"+n+\"V-\"+n+\"M\"+n+\",0H-\"+n+\"M\"+n+\",0A\"+n+\",\"+n+\" 0 1,1 0,-\"+n+\"A\"+n+\",\"+n+\" 0 0,1 \"+n+\",0Z\")},needLine:!0,noDot:!0},\"circle-x\":{n:28,f:function(t,e,r){if(v(e))return u;var n=l(t,2),i=l(t/c,2);return g(e,r,\"M\"+i+\",\"+i+\"L-\"+i+\",-\"+i+\"M\"+i+\",-\"+i+\"L-\"+i+\",\"+i+\"M\"+n+\",0A\"+n+\",\"+n+\" 0 1,1 0,-\"+n+\"A\"+n+\",\"+n+\" 0 0,1 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ot,st,lt,ut,ct=d.select(\"g.legend\"),ft=H(r,ct.node()),ht=ft.width+2*S,pt=ft.height+2*S,dt=W[0],vt=(dt.x0+dt.x1)/2,gt=(dt.y0+dt.y1)/2,yt=!(g.traceIs(dt.trace,\"bar-like\")||g.traceIs(dt.trace,\"box-violin\"));\"y\"===P?yt?(st=gt-S,ot=gt+S):(st=Math.min.apply(null,W.map((function(t){return Math.min(t.y0,t.y1)}))),ot=Math.max.apply(null,W.map((function(t){return Math.max(t.y0,t.y1)})))):st=ot=o.mean(W.map((function(t){return(t.y0+t.y1)/2})))-pt/2,\"x\"===P?yt?(lt=vt+S,ut=vt-S):(lt=Math.max.apply(null,W.map((function(t){return Math.max(t.x0,t.x1)}))),ut=Math.min.apply(null,W.map((function(t){return Math.min(t.x0,t.x1)})))):lt=ut=o.mean(W.map((function(t){return(t.x0+t.x1)/2})))-ht/2;var mt,xt,bt=E._offset,_t=L._offset;return ut+=bt-ht,st+=_t-pt,mt=(lt+=bt)+ht<B&&lt>=0?lt:ut+ht<B&&ut>=0?ut:bt+ht<B?bt:lt-vt<vt-ut+ht?B-ht:0,mt+=S,xt=(ot+=_t)+pt<N&&ot>=0?ot:st+pt<N&&st>=0?st:_t+pt<N?_t:ot-gt<gt-st+pt?N-pt:0,xt+=S,ct.attr(\"transform\",s(mt-1,xt-1)),ct}var wt=d.selectAll(\"g.hovertext\").data(t,(function(t){return C(t)}));return wt.enter().append(\"g\").classed(\"hovertext\",!0).each((function(){var t=n.select(this);t.append(\"rect\").call(p.fill,p.addOpacity(f,.8)),t.append(\"text\").classed(\"name\",!0),t.append(\"path\").style(\"stroke-width\",\"1px\"),t.append(\"text\").classed(\"nums\",!0).call(h.font,T,k)})),wt.exit().remove(),wt.each((function(t){var e=n.select(this).attr(\"transform\",\"\"),o=t.color;Array.isArray(o)&&(o=o[t.eventData[0].pointNumber]);var d=t.bgcolor||o,v=p.combine(p.opacity(d)?d:p.defaultLine,f),g=p.combine(p.opacity(o)?o:p.defaultLine,f),y=t.borderColor||p.contrast(v),m=I(t,j,a,i,D,e),x=m[0],b=m[1],w=e.select(\"text.nums\").call(h.font,t.fontFamily||T,t.fontSize||k,t.fontColor||y).text(x).attr(\"data-notex\",1).call(c.positionText,0,0).call(c.convertToTspans,r),A=e.select(\"text.name\"),E=0,L=0;if(b&&b!==x){A.call(h.font,t.fontFamily||T,t.fontSize||k,g).text(b).attr(\"data-notex\",1).call(c.positionText,0,0).call(c.convertToTspans,r);var C=H(r,A.node());E=C.width+2*S,L=C.height+2*S}else A.remove(),e.select(\"rect\").remove();e.select(\"path\").style({fill:v,stroke:y});var P=t.xa._offset+(t.x0+t.x1)/2,O=t.ya._offset+(t.y0+t.y1)/2,z=Math.abs(t.x1-t.x0),R=Math.abs(t.y1-t.y0),U=H(r,w.node()),V=U.width/i._invScaleX,q=U.height/i._invScaleY;t.ty0=(F-U.top)/i._invScaleY,t.bx=V+2*S,t.by=Math.max(q+2*S,L),t.anchor=\"start\",t.txwidth=V,t.tx2width=E,t.offset=0;var 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n,i,o=r.container,s=r.fullLayout,l=s._size,u=r.event,c=!!e.hLinePoint,f=!!e.vLinePoint;if(o.selectAll(\".spikeline\").remove(),f||c){var d=p.combine(s.plot_bgcolor,s.paper_bgcolor);if(c){var g,y,m=e.hLinePoint;n=m&&m.xa,\"cursor\"===(i=m&&m.ya).spikesnap?(g=u.pointerX,y=u.pointerY):(g=n._offset+m.x,y=i._offset+m.y);var x,b,_=a.readability(m.color,d)<1.5?p.contrast(d):m.color,w=i.spikemode,T=i.spikethickness,k=i.spikecolor||_,A=v.getPxPosition(t,i);if(-1!==w.indexOf(\"toaxis\")||-1!==w.indexOf(\"across\")){if(-1!==w.indexOf(\"toaxis\")&&(x=A,b=g),-1!==w.indexOf(\"across\")){var 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n=r(85555),i=r(44467).templatedArray;r(24695),t.exports=i(\"image\",{visible:{valType:\"boolean\",dflt:!0,editType:\"arraydraw\"},source:{valType:\"string\",editType:\"arraydraw\"},layer:{valType:\"enumerated\",values:[\"below\",\"above\"],dflt:\"above\",editType:\"arraydraw\"},sizex:{valType:\"number\",dflt:0,editType:\"arraydraw\"},sizey:{valType:\"number\",dflt:0,editType:\"arraydraw\"},sizing:{valType:\"enumerated\",values:[\"fill\",\"contain\",\"stretch\"],dflt:\"contain\",editType:\"arraydraw\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,editType:\"arraydraw\"},x:{valType:\"any\",dflt:0,editType:\"arraydraw\"},y:{valType:\"any\",dflt:0,editType:\"arraydraw\"},xanchor:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"left\",editType:\"arraydraw\"},yanchor:{valType:\"enumerated\",values:[\"top\",\"middle\",\"bottom\"],dflt:\"top\",editType:\"arraydraw\"},xref:{valType:\"enumerated\",values:[\"paper\",n.idRegex.x.toString()],dflt:\"paper\",editType:\"arraydraw\"},yref:{valType:\"enumerated\",values:[\"paper\",n.idRegex.y.toString()],dflt:\"paper\",editType:\"arraydraw\"},editType:\"arraydraw\"})},75378:function(t,e,r){\"use 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b=Object.keys(l._plots);for(r=0;r<b.length;r++){e=b[r];var _=l._plots[e];if(_.imagelayer){var w=_.imagelayer.selectAll(\"image\").data(c[e]||[]);w.enter().append(\"image\"),w.exit().remove(),w.each((function(t){g.bind(this)(t),y.bind(this)(t)}))}}}},68804:function(t,e,r){\"use strict\";t.exports={moduleType:\"component\",name:\"images\",layoutAttributes:r(69819),supplyLayoutDefaults:r(81603),includeBasePlot:r(76325)(\"images\"),draw:r(80750),convertCoords:r(75378)}},33030:function(t,e,r){\"use strict\";var n=r(41940),i=r(22399);t.exports={_isSubplotObj:!0,visible:{valType:\"boolean\",dflt:!0,editType:\"legend\"},bgcolor:{valType:\"color\",editType:\"legend\"},bordercolor:{valType:\"color\",dflt:i.defaultLine,editType:\"legend\"},borderwidth:{valType:\"number\",min:0,dflt:0,editType:\"legend\"},font:n({editType:\"legend\"}),grouptitlefont:n({editType:\"legend\"}),orientation:{valType:\"enumerated\",values:[\"v\",\"h\"],dflt:\"v\",editType:\"legend\"},traceorder:{valType:\"flaglist\",flags:[\"reversed\",\"grouped\"],extras:[\"normal\"],editType:\"legend\"},tracegroupgap:{valType:\"number\",min:0,dflt:10,editType:\"legend\"},entrywidth:{valType:\"number\",min:0,editType:\"legend\"},entrywidthmode:{valType:\"enumerated\",values:[\"fraction\",\"pixels\"],dflt:\"pixels\",editType:\"legend\"},itemsizing:{valType:\"enumerated\",values:[\"trace\",\"constant\"],dflt:\"trace\",editType:\"legend\"},itemwidth:{valType:\"number\",min:30,dflt:30,editType:\"legend\"},itemclick:{valType:\"enumerated\",values:[\"toggle\",\"toggleothers\",!1],dflt:\"toggle\",editType:\"legend\"},itemdoubleclick:{valType:\"enumerated\",values:[\"toggle\",\"toggleothers\",!1],dflt:\"toggleothers\",editType:\"legend\"},groupclick:{valType:\"enumerated\",values:[\"toggleitem\",\"togglegroup\"],dflt:\"togglegroup\",editType:\"legend\"},x:{valType:\"number\",editType:\"legend\"},xref:{valType:\"enumerated\",dflt:\"paper\",values:[\"container\",\"paper\"],editType:\"layoutstyle\"},xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\",editType:\"legend\"},y:{valType:\"number\",editType:\"legend\"},yref:{valType:\"enumerated\",dflt:\"paper\",values:[\"container\",\"paper\"],editType:\"layoutstyle\"},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],editType:\"legend\"},uirevision:{valType:\"any\",editType:\"none\"},valign:{valType:\"enumerated\",values:[\"top\",\"middle\",\"bottom\"],dflt:\"middle\",editType:\"legend\"},title:{text:{valType:\"string\",dflt:\"\",editType:\"legend\"},font:n({editType:\"legend\"}),side:{valType:\"enumerated\",values:[\"top\",\"left\",\"top 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A=v._isShape;(v.showlegend||v._dfltShowLegend&&!(v._module&&v._module.attributes&&v._module.attributes.showlegend&&!1===v._module.attributes.showlegend.dflt))&&(x++,v.showlegend&&(b=!0,(!A&&n.traceIs(v,\"pie-like\")||!0===v._input.showlegend)&&x++),i.coerceFont(g,\"legendgrouptitle.font\",m)),(!A&&n.traceIs(v,\"bar\")&&\"stack\"===r.barmode||-1!==[\"tonextx\",\"tonexty\"].indexOf(v.fill))&&(_=u.isGrouped({traceorder:_})?\"grouped+reversed\":\"reversed\"),void 0!==v.legendgroup&&\"\"!==v.legendgroup&&(_=u.isReversed({traceorder:_})?\"reversed+grouped\":\"grouped\")}var M=i.coerce(e,r,l,\"showlegend\",b&&x>(\"legend\"===t?1:0));if(!1===M&&(r[t]=void 0),(!1!==M||f.uirevision)&&(p(\"uirevision\",r.uirevision),!1!==M)){p(\"borderwidth\");var 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t.showlegend})),y=v.concat(g),m=d.trace;m._isShape&&(m=m._fullInput);var x,b,_,w,T,k=m.legendgroup,A={},M=[],S=[],E=[],L=(s.shapes||[]).map((function(t){return t._input})),C=!1,P=m.legend,O=m._fullInput;if(O&&O._isShape||!n.traceIs(m,\"pie-like\")){var I,D=k&&k.length,z=[];if(D)for(x=0;x<y.length;x++)(I=y[x]).visible&&I.legendgroup===k&&z.push(x);if(\"toggle\"===l){var R;switch(m.visible){case!0:R=\"legendonly\";break;case!1:R=!1;break;case\"legendonly\":R=!0}if(D)if(h)for(x=0;x<y.length;x++){var F=y[x];!1!==F.visible&&F.legendgroup===k&&tt(F,R)}else tt(m,R);else tt(m,R)}else if(\"toggleothers\"===l){var 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u(t,\"Pan\")},attr:\"dragmode\",val:\"pan\",icon:o.pan,click:f},c.select2d={name:\"select2d\",_cat:\"select\",title:function(t){return u(t,\"Box Select\")},attr:\"dragmode\",val:\"select\",icon:o.selectbox,click:f},c.lasso2d={name:\"lasso2d\",_cat:\"lasso\",title:function(t){return u(t,\"Lasso Select\")},attr:\"dragmode\",val:\"lasso\",icon:o.lasso,click:f},c.drawclosedpath={name:\"drawclosedpath\",title:function(t){return u(t,\"Draw closed freeform\")},attr:\"dragmode\",val:\"drawclosedpath\",icon:o.drawclosedpath,click:f},c.drawopenpath={name:\"drawopenpath\",title:function(t){return u(t,\"Draw open freeform\")},attr:\"dragmode\",val:\"drawopenpath\",icon:o.drawopenpath,click:f},c.drawline={name:\"drawline\",title:function(t){return u(t,\"Draw line\")},attr:\"dragmode\",val:\"drawline\",icon:o.drawline,click:f},c.drawrect={name:\"drawrect\",title:function(t){return u(t,\"Draw rectangle\")},attr:\"dragmode\",val:\"drawrect\",icon:o.drawrect,click:f},c.drawcircle={name:\"drawcircle\",title:function(t){return u(t,\"Draw circle\")},attr:\"dragmode\",val:\"drawcircle\",icon:o.drawcircle,click:f},c.eraseshape={name:\"eraseshape\",title:function(t){return u(t,\"Erase active shape\")},icon:o.eraseshape,click:s},c.zoomIn2d={name:\"zoomIn2d\",_cat:\"zoomin\",title:function(t){return u(t,\"Zoom in\")},attr:\"zoom\",val:\"in\",icon:o.zoom_plus,click:f},c.zoomOut2d={name:\"zoomOut2d\",_cat:\"zoomout\",title:function(t){return u(t,\"Zoom out\")},attr:\"zoom\",val:\"out\",icon:o.zoom_minus,click:f},c.autoScale2d={name:\"autoScale2d\",_cat:\"autoscale\",title:function(t){return u(t,\"Autoscale\")},attr:\"zoom\",val:\"auto\",icon:o.autoscale,click:f},c.resetScale2d={name:\"resetScale2d\",_cat:\"resetscale\",title:function(t){return u(t,\"Reset axes\")},attr:\"zoom\",val:\"reset\",icon:o.home,click:f},c.hoverClosestCartesian={name:\"hoverClosestCartesian\",_cat:\"hoverclosest\",title:function(t){return u(t,\"Show closest data on hover\")},attr:\"hovermode\",val:\"closest\",icon:o.tooltip_basic,gravity:\"ne\",click:f},c.hoverCompareCartesian={name:\"hoverCompareCartesian\",_cat:\"hoverCompare\",title:function(t){return u(t,\"Compare data on hover\")},attr:\"hovermode\",val:function(t){return t._fullLayout._isHoriz?\"y\":\"x\"},icon:o.tooltip_compare,gravity:\"ne\",click:f},c.zoom3d={name:\"zoom3d\",_cat:\"zoom\",title:function(t){return u(t,\"Zoom\")},attr:\"scene.dragmode\",val:\"zoom\",icon:o.zoombox,click:h},c.pan3d={name:\"pan3d\",_cat:\"pan\",title:function(t){return u(t,\"Pan\")},attr:\"scene.dragmode\",val:\"pan\",icon:o.pan,click:h},c.orbitRotation={name:\"orbitRotation\",title:function(t){return u(t,\"Orbital rotation\")},attr:\"scene.dragmode\",val:\"orbit\",icon:o[\"3d_rotate\"],click:h},c.tableRotation={name:\"tableRotation\",title:function(t){return u(t,\"Turntable rotation\")},attr:\"scene.dragmode\",val:\"turntable\",icon:o[\"z-axis\"],click:h},c.resetCameraDefault3d={name:\"resetCameraDefault3d\",_cat:\"resetCameraDefault\",title:function(t){return u(t,\"Reset camera to default\")},attr:\"resetDefault\",icon:o.home,click:p},c.resetCameraLastSave3d={name:\"resetCameraLastSave3d\",_cat:\"resetCameraLastSave\",title:function(t){return u(t,\"Reset camera to last save\")},attr:\"resetLastSave\",icon:o.movie,click:p},c.hoverClosest3d={name:\"hoverClosest3d\",_cat:\"hoverclosest\",title:function(t){return u(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:o.tooltip_basic,gravity:\"ne\",click:function(t,e){var r=d(t,e);n.call(\"_guiRelayout\",t,r)}},c.zoomInGeo={name:\"zoomInGeo\",_cat:\"zoomin\",title:function(t){return u(t,\"Zoom in\")},attr:\"zoom\",val:\"in\",icon:o.zoom_plus,click:v},c.zoomOutGeo={name:\"zoomOutGeo\",_cat:\"zoomout\",title:function(t){return u(t,\"Zoom out\")},attr:\"zoom\",val:\"out\",icon:o.zoom_minus,click:v},c.resetGeo={name:\"resetGeo\",_cat:\"reset\",title:function(t){return u(t,\"Reset\")},attr:\"reset\",val:null,icon:o.autoscale,click:v},c.hoverClosestGeo={name:\"hoverClosestGeo\",_cat:\"hoverclosest\",title:function(t){return u(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:o.tooltip_basic,gravity:\"ne\",click:y},c.hoverClosestGl2d={name:\"hoverClosestGl2d\",_cat:\"hoverclosest\",title:function(t){return u(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:o.tooltip_basic,gravity:\"ne\",click:y},c.hoverClosestPie={name:\"hoverClosestPie\",_cat:\"hoverclosest\",title:function(t){return u(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:\"closest\",icon:o.tooltip_basic,gravity:\"ne\",click:y},c.resetViewSankey={name:\"resetSankeyGroup\",title:function(t){return u(t,\"Reset view\")},icon:o.home,click:function(t){for(var e={\"node.groups\":[],\"node.x\":[],\"node.y\":[]},r=0;r<t._fullData.length;r++){var i=t._fullData[r]._viewInitial;e[\"node.groups\"].push(i.node.groups.slice()),e[\"node.x\"].push(i.node.x.slice()),e[\"node.y\"].push(i.node.y.slice())}n.call(\"restyle\",t,e)}},c.toggleHover={name:\"toggleHover\",title:function(t){return u(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:o.tooltip_basic,gravity:\"ne\",click:function(t,e){var r=d(t,e);r.hovermode=g(t),n.call(\"_guiRelayout\",t,r)}},c.resetViews={name:\"resetViews\",title:function(t){return u(t,\"Reset views\")},icon:o.home,click:function(t,e){var r=e.currentTarget;r.setAttribute(\"data-attr\",\"zoom\"),r.setAttribute(\"data-val\",\"reset\"),f(t,e),r.setAttribute(\"data-attr\",\"resetLastSave\"),p(t,e),x(t,\"geo\"),x(t,\"mapbox\")}},c.toggleSpikelines={name:\"toggleSpikelines\",title:function(t){return u(t,\"Toggle Spike Lines\")},icon:o.spikeline,attr:\"_cartesianSpikesEnabled\",val:\"on\",click:function(t){var e=t._fullLayout,r=e._cartesianSpikesEnabled;e._cartesianSpikesEnabled=\"on\"===r?\"off\":\"on\",n.call(\"_guiRelayout\",t,function(t){for(var e=\"on\"===t._fullLayout._cartesianSpikesEnabled,r=a.list(t,null,!0),n={},i=0;i<r.length;i++){var o=r[i];n[o._name+\".showspikes\"]=!!e||o._showSpikeInitial}return n}(t))}},c.resetViewMapbox={name:\"resetViewMapbox\",_cat:\"resetView\",title:function(t){return u(t,\"Reset view\")},attr:\"reset\",icon:o.home,click:function(t){x(t,\"mapbox\")}},c.zoomInMapbox={name:\"zoomInMapbox\",_cat:\"zoomin\",title:function(t){return u(t,\"Zoom in\")},attr:\"zoom\",val:\"in\",icon:o.zoom_plus,click:m},c.zoomOutMapbox={name:\"zoomOutMapbox\",_cat:\"zoomout\",title:function(t){return u(t,\"Zoom out\")},attr:\"zoom\",val:\"out\",icon:o.zoom_minus,click:m}},93348:function(t,e,r){\"use strict\";var n=r(26023),i=Object.keys(n),a=[\"drawline\",\"drawopenpath\",\"drawclosedpath\",\"drawcircle\",\"drawrect\",\"eraseshape\"],o=[\"v1hovermode\",\"hoverclosest\",\"hovercompare\",\"togglehover\",\"togglespikelines\"].concat(a),s=[];i.forEach((function(t){!function(t){if(-1===o.indexOf(t._cat||t.name)){var e=t.name,r=(t._cat||t.name).toLowerCase();-1===s.indexOf(e)&&s.push(e),-1===s.indexOf(r)&&s.push(r)}}(n[t])})),s.sort(),t.exports={DRAW_MODES:a,backButtons:o,foreButtons:s}},35750:function(t,e,r){\"use strict\";var n=r(71828),i=r(7901),a=r(44467),o=r(42068);t.exports=function(t,e){var r=t.modebar||{},s=a.newContainer(e,\"modebar\");function l(t,e){return n.coerce(r,s,o,t,e)}l(\"orientation\"),l(\"bgcolor\",i.addOpacity(e.paper_bgcolor,.5));var u=i.contrast(i.rgb(e.modebar.bgcolor));l(\"color\",i.addOpacity(u,.3)),l(\"activecolor\",i.addOpacity(u,.7)),l(\"uirevision\",e.uirevision),l(\"add\"),l(\"remove\")}},64168:function(t,e,r){\"use strict\";t.exports={moduleType:\"component\",name:\"modebar\",layoutAttributes:r(42068),supplyLayoutDefaults:r(35750),manage:r(14192)}},14192:function(t,e,r){\"use strict\";var n=r(41675),i=r(34098),a=r(73972),o=r(23469).isUnifiedHover,s=r(37676),l=r(26023),u=r(93348).DRAW_MODES,c=r(71828).extendDeep;t.exports=function(t){var e=t._fullLayout,r=t._context,f=e._modeBar;if(r.displayModeBar||r.watermark){if(!Array.isArray(r.modeBarButtonsToRemove))throw new Error([\"*modeBarButtonsToRemove* configuration options\",\"must be an array.\"].join(\" \"));if(!Array.isArray(r.modeBarButtonsToAdd))throw new Error([\"*modeBarButtonsToAdd* configuration options\",\"must be an array.\"].join(\" \"));var h,p=r.modeBarButtons;h=Array.isArray(p)&&p.length?function(t){for(var e=c([],t),r=0;r<e.length;r++)for(var n=e[r],i=0;i<n.length;i++){var a=n[i];if(\"string\"==typeof a){if(void 0===l[a])throw new Error([\"*modeBarButtons* configuration options\",\"invalid button name\"].join(\" \"));e[r][i]=l[a]}}return e}(p):!r.displayModeBar&&r.watermark?[]:function(t){var e=t._fullLayout,r=t._fullData,s=t._context;function c(t,e){if(\"string\"==typeof e){if(e.toLowerCase()===t.toLowerCase())return!0}else{var r=e.name,n=e._cat||e.name;if(r===t||n===t.toLowerCase())return!0}return!1}var f=e.modebar.add;\"string\"==typeof f&&(f=[f]);var h=e.modebar.remove;\"string\"==typeof h&&(h=[h]);var p=s.modeBarButtonsToAdd.concat(f.filter((function(t){for(var e=0;e<s.modeBarButtonsToRemove.length;e++)if(c(t,s.modeBarButtonsToRemove[e]))return!1;return!0}))),d=s.modeBarButtonsToRemove.concat(h.filter((function(t){for(var e=0;e<s.modeBarButtonsToAdd.length;e++)if(c(t,s.modeBarButtonsToAdd[e]))return!1;return!0}))),v=e._has(\"cartesian\"),g=e._has(\"gl3d\"),y=e._has(\"geo\"),m=e._has(\"pie\"),x=e._has(\"funnelarea\"),b=e._has(\"gl2d\"),_=e._has(\"ternary\"),w=e._has(\"mapbox\"),T=e._has(\"polar\"),k=e._has(\"smith\"),A=e._has(\"sankey\"),M=function(t){for(var e=n.list({_fullLayout:t},null,!0),r=0;r<e.length;r++)if(!e[r].fixedrange)return!1;return!0}(e),S=o(e.hovermode),E=[];function L(t){if(t.length){for(var e=[],r=0;r<t.length;r++){for(var n=t[r],i=l[n],a=i.name.toLowerCase(),o=(i._cat||i.name).toLowerCase(),s=!1,u=0;u<d.length;u++){var c=d[u].toLowerCase();if(c===a||c===o){s=!0;break}}s||e.push(l[n])}E.push(e)}}var C=[\"toImage\"];s.showEditInChartStudio?C.push(\"editInChartStudio\"):s.showSendToCloud&&C.push(\"sendDataToCloud\"),L(C);var P=[],O=[],I=[],D=[];(v||b||m||x||_)+y+g+w+T+k>1?(O=[\"toggleHover\"],I=[\"resetViews\"]):y?(P=[\"zoomInGeo\",\"zoomOutGeo\"],O=[\"hoverClosestGeo\"],I=[\"resetGeo\"]):g?(O=[\"hoverClosest3d\"],I=[\"resetCameraDefault3d\",\"resetCameraLastSave3d\"]):w?(P=[\"zoomInMapbox\",\"zoomOutMapbox\"],O=[\"toggleHover\"],I=[\"resetViewMapbox\"]):b?O=[\"hoverClosestGl2d\"]:m?O=[\"hoverClosestPie\"]:A?(O=[\"hoverClosestCartesian\",\"hoverCompareCartesian\"],I=[\"resetViewSankey\"]):O=[\"toggleHover\"],v&&(O=[\"toggleSpikelines\",\"hoverClosestCartesian\",\"hoverCompareCartesian\"]),(function(t){for(var e=0;e<t.length;e++)if(!a.traceIs(t[e],\"noHover\"))return!1;return!0}(r)||S)&&(O=[]),!v&&!b||M||(P=[\"zoomIn2d\",\"zoomOut2d\",\"autoScale2d\"],\"resetViews\"!==I[0]&&(I=[\"resetScale2d\"])),g?D=[\"zoom3d\",\"pan3d\",\"orbitRotation\",\"tableRotation\"]:(v||b)&&!M||_?D=[\"zoom2d\",\"pan2d\"]:w||y?D=[\"pan2d\"]:T&&(D=[\"zoom2d\"]),function(t){for(var e=!1,r=0;r<t.length&&!e;r++){var n=t[r];n._module&&n._module.selectPoints&&(a.traceIs(n,\"scatter-like\")?(i.hasMarkers(n)||i.hasText(n))&&(e=!0):a.traceIs(n,\"box-violin\")&&\"all\"!==n.boxpoints&&\"all\"!==n.points||(e=!0))}return e}(r)&&D.push(\"select2d\",\"lasso2d\");var z=[],R=function(t){-1===z.indexOf(t)&&-1!==O.indexOf(t)&&z.push(t)};if(Array.isArray(p)){for(var F=[],B=0;B<p.length;B++){var N=p[B];\"string\"==typeof N?(N=N.toLowerCase(),-1!==u.indexOf(N)?(e._has(\"mapbox\")||e._has(\"cartesian\"))&&D.push(N):\"togglespikelines\"===N?R(\"toggleSpikelines\"):\"togglehover\"===N?R(\"toggleHover\"):\"hovercompare\"===N?R(\"hoverCompareCartesian\"):\"hoverclosest\"===N?(R(\"hoverClosestCartesian\"),R(\"hoverClosestGeo\"),R(\"hoverClosest3d\"),R(\"hoverClosestGl2d\"),R(\"hoverClosestPie\")):\"v1hovermode\"===N&&(R(\"toggleHover\"),R(\"hoverClosestCartesian\"),R(\"hoverCompareCartesian\"),R(\"hoverClosestGeo\"),R(\"hoverClosest3d\"),R(\"hoverClosestGl2d\"),R(\"hoverClosestPie\"))):F.push(N)}p=F}return L(D),L(P.concat(I)),L(z),function(t,e){if(e.length)if(Array.isArray(e[0]))for(var r=0;r<e.length;r++)t.push(e[r]);else t.push(e);return t}(E,p)}(t),f?f.update(t,h):e._modeBar=s(t,h)}else f&&(f.destroy(),delete e._modeBar)}},37676:function(t,e,r){\"use strict\";var n=r(39898),i=r(92770),a=r(71828),o=r(24255),s=r(11506).version,l=new DOMParser;function u(t){this.container=t.container,this.element=document.createElement(\"div\"),this.update(t.graphInfo,t.buttons),this.container.appendChild(this.element)}var c=u.prototype;c.update=function(t,e){this.graphInfo=t;var r=this.graphInfo._context,n=this.graphInfo._fullLayout,i=\"modebar-\"+n._uid;this.element.setAttribute(\"id\",i),this._uid=i,this.element.className=\"modebar\",\"hover\"===r.displayModeBar&&(this.element.className+=\" modebar--hover ease-bg\"),\"v\"===n.modebar.orientation&&(this.element.className+=\" vertical\",e=e.reverse());var o=n.modebar,s=\"hover\"===r.displayModeBar?\".js-plotly-plot .plotly:hover \":\"\";a.deleteRelatedStyleRule(i),a.addRelatedStyleRule(i,s+\"#\"+i+\" .modebar-group\",\"background-color: \"+o.bgcolor),a.addRelatedStyleRule(i,\"#\"+i+\" .modebar-btn .icon path\",\"fill: \"+o.color),a.addRelatedStyleRule(i,\"#\"+i+\" .modebar-btn:hover .icon path\",\"fill: \"+o.activecolor),a.addRelatedStyleRule(i,\"#\"+i+\" .modebar-btn.active .icon path\",\"fill: \"+o.activecolor);var l=!this.hasButtons(e),u=this.hasLogo!==r.displaylogo,c=this.locale!==r.locale;if(this.locale=r.locale,(l||u||c)&&(this.removeAllButtons(),this.updateButtons(e),r.watermark||r.displaylogo)){var f=this.getLogo();r.watermark&&(f.className=f.className+\" watermark\"),\"v\"===n.modebar.orientation?this.element.insertBefore(f,this.element.childNodes[0]):this.element.appendChild(f),this.hasLogo=!0}this.updateActiveButton()},c.updateButtons=function(t){var e=this;this.buttons=t,this.buttonElements=[],this.buttonsNames=[],this.buttons.forEach((function(t){var r=e.createGroup();t.forEach((function(t){var n=t.name;if(!n)throw new Error(\"must provide button 'name' in button config\");if(-1!==e.buttonsNames.indexOf(n))throw new Error(\"button name '\"+n+\"' is taken\");e.buttonsNames.push(n);var i=e.createButton(t);e.buttonElements.push(i),r.appendChild(i)})),e.element.appendChild(r)}))},c.createGroup=function(){var t=document.createElement(\"div\");return t.className=\"modebar-group\",t},c.createButton=function(t){var e=this,r=document.createElement(\"a\");r.setAttribute(\"rel\",\"tooltip\"),r.className=\"modebar-btn\";var i=t.title;void 0===i?i=t.name:\"function\"==typeof i&&(i=i(this.graphInfo)),(i||0===i)&&r.setAttribute(\"data-title\",i),void 0!==t.attr&&r.setAttribute(\"data-attr\",t.attr);var a=t.val;if(void 0!==a&&(\"function\"==typeof a&&(a=a(this.graphInfo)),r.setAttribute(\"data-val\",a)),\"function\"!=typeof t.click)throw new Error(\"must provide button 'click' function in button config\");r.addEventListener(\"click\",(function(r){t.click(e.graphInfo,r),e.updateActiveButton(r.currentTarget)})),r.setAttribute(\"data-toggle\",t.toggle||!1),t.toggle&&n.select(r).classed(\"active\",!0);var s=t.icon;return\"function\"==typeof s?r.appendChild(s()):r.appendChild(this.createIcon(s||o.question)),r.setAttribute(\"data-gravity\",t.gravity||\"n\"),r},c.createIcon=function(t){var e,r=i(t.height)?Number(t.height):t.ascent-t.descent,n=\"http://www.w3.org/2000/svg\";if(t.path){(e=document.createElementNS(n,\"svg\")).setAttribute(\"viewBox\",[0,0,t.width,r].join(\" \")),e.setAttribute(\"class\",\"icon\");var a=document.createElementNS(n,\"path\");a.setAttribute(\"d\",t.path),t.transform?a.setAttribute(\"transform\",t.transform):void 0!==t.ascent&&a.setAttribute(\"transform\",\"matrix(1 0 0 -1 0 \"+t.ascent+\")\"),e.appendChild(a)}return t.svg&&(e=l.parseFromString(t.svg,\"application/xml\").childNodes[0]),e.setAttribute(\"height\",\"1em\"),e.setAttribute(\"width\",\"1em\"),e},c.updateActiveButton=function(t){var e=this.graphInfo._fullLayout,r=void 0!==t?t.getAttribute(\"data-attr\"):null;this.buttonElements.forEach((function(t){var i=t.getAttribute(\"data-val\")||!0,o=t.getAttribute(\"data-attr\"),s=\"true\"===t.getAttribute(\"data-toggle\"),l=n.select(t);if(s)o===r&&l.classed(\"active\",!l.classed(\"active\"));else{var u=null===o?o:a.nestedProperty(e,o).get();l.classed(\"active\",u===i)}}))},c.hasButtons=function(t){var e=this.buttons;if(!e)return!1;if(t.length!==e.length)return!1;for(var r=0;r<t.length;++r){if(t[r].length!==e[r].length)return!1;for(var n=0;n<t[r].length;n++)if(t[r][n].name!==e[r][n].name)return!1}return!0},c.getLogo=function(){var t=this.createGroup(),e=document.createElement(\"a\");return e.href=\"https://plotly.com/\",e.target=\"_blank\",e.setAttribute(\"data-title\",a._(this.graphInfo,\"Produced 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n=r(41940),i=r(22399),a=(0,r(44467).templatedArray)(\"button\",{visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},step:{valType:\"enumerated\",values:[\"month\",\"year\",\"day\",\"hour\",\"minute\",\"second\",\"all\"],dflt:\"month\",editType:\"plot\"},stepmode:{valType:\"enumerated\",values:[\"backward\",\"todate\"],dflt:\"backward\",editType:\"plot\"},count:{valType:\"number\",min:0,dflt:1,editType:\"plot\"},label:{valType:\"string\",editType:\"plot\"},editType:\"plot\"});t.exports={visible:{valType:\"boolean\",editType:\"plot\"},buttons:a,x:{valType:\"number\",min:-2,max:3,editType:\"plot\"},xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\",editType:\"plot\"},y:{valType:\"number\",min:-2,max:3,editType:\"plot\"},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"bottom\",editType:\"plot\"},font:n({editType:\"plot\"}),bgcolor:{valType:\"color\",dflt:i.lightLine,editType:\"plot\"},activecolor:{valType:\"color\",editType:\"plot\"},bordercolor:{valType:\"color\",dflt:i.defaultLine,editType:\"plot\"},borderwidth:{valType:\"number\",min:0,dflt:0,editType:\"plot\"},editType:\"plot\"}},89573:function(t){\"use 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n=r(32485),i=r(3937);t.exports={moduleType:\"component\",name:\"selections\",layoutAttributes:r(8389),supplyLayoutDefaults:r(59402),supplyDrawNewSelectionDefaults:r(90849),includeBasePlot:r(76325)(\"selections\"),draw:n.draw,drawOne:n.drawOne,reselect:i.reselect,prepSelect:i.prepSelect,clearOutline:i.clearOutline,clearSelectionsCache:i.clearSelectionsCache,selectOnClick:i.selectOnClick}},3937:function(t,e,r){\"use strict\";var n=r(52142),i=r(38258),a=r(73972),o=r(91424).dashStyle,s=r(7901),l=r(30211),u=r(23469).makeEventData,c=r(64505),f=c.freeMode,h=c.rectMode,p=c.drawMode,d=c.openMode,v=c.selectMode,g=r(30477),y=r(21459),m=r(42359),x=r(51873).clearOutline,b=r(60165),_=b.handleEllipse,w=b.readPaths,T=r(90551).newShapes,k=r(35855),A=r(32485).activateLastSelection,M=r(71828),S=M.sorterAsc,E=r(61082),L=r(79990),C=r(41675).getFromId,P=r(33306),O=r(61549).redrawReglTraces,I=r(34122),D=I.MINSELECT,z=E.filter,R=E.tester,F=r(75549),B=F.p2r,N=F.axValue,j=F.getTransform;function U(t){return 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n=r(50215),i=r(41940),a=r(82196).line,o=r(79952).P,s=r(1426).extendFlat,l=r(44467).templatedArray,u=(r(24695),r(9012)),c=r(5386).R,f=r(37281);t.exports=l(\"shape\",{visible:s({},u.visible,{editType:\"calc+arraydraw\"}),showlegend:{valType:\"boolean\",dflt:!1,editType:\"calc+arraydraw\"},legend:s({},u.legend,{editType:\"calc+arraydraw\"}),legendgroup:s({},u.legendgroup,{editType:\"calc+arraydraw\"}),legendgrouptitle:{text:s({},u.legendgrouptitle.text,{editType:\"calc+arraydraw\"}),font:i({editType:\"calc+arraydraw\"}),editType:\"calc+arraydraw\"},legendrank:s({},u.legendrank,{editType:\"calc+arraydraw\"}),legendwidth:s({},u.legendwidth,{editType:\"calc+arraydraw\"}),type:{valType:\"enumerated\",values:[\"circle\",\"rect\",\"path\",\"line\"],editType:\"calc+arraydraw\"},layer:{valType:\"enumerated\",values:[\"below\",\"above\"],dflt:\"above\",editType:\"arraydraw\"},xref:s({},n.xref,{}),xsizemode:{valType:\"enumerated\",values:[\"scaled\",\"pixel\"],dflt:\"scaled\",editType:\"calc+arraydraw\"},xanchor:{valType:\"any\",editType:\"calc+arraydraw\"},x0:{valType:\"any\",editType:\"calc+arraydraw\"},x1:{valType:\"any\",editType:\"calc+arraydraw\"},yref:s({},n.yref,{}),ysizemode:{valType:\"enumerated\",values:[\"scaled\",\"pixel\"],dflt:\"scaled\",editType:\"calc+arraydraw\"},yanchor:{valType:\"any\",editType:\"calc+arraydraw\"},y0:{valType:\"any\",editType:\"calc+arraydraw\"},y1:{valType:\"any\",editType:\"calc+arraydraw\"},path:{valType:\"string\",editType:\"calc+arraydraw\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,editType:\"arraydraw\"},line:{color:s({},a.color,{editType:\"arraydraw\"}),width:s({},a.width,{editType:\"calc+arraydraw\"}),dash:s({},o,{editType:\"arraydraw\"}),editType:\"calc+arraydraw\"},fillcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"arraydraw\"},fillrule:{valType:\"enumerated\",values:[\"evenodd\",\"nonzero\"],dflt:\"evenodd\",editType:\"arraydraw\"},editable:{valType:\"boolean\",dflt:!1,editType:\"calc+arraydraw\"},label:{text:{valType:\"string\",dflt:\"\",editType:\"arraydraw\"},texttemplate:c({},{keys:Object.keys(f)}),font:i({editType:\"calc+arraydraw\",colorEditType:\"arraydraw\"}),textposition:{valType:\"enumerated\",values:[\"top 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n=r(7901),i=r(71828);t.exports=function(t,e,r){if(r(\"newshape.visible\"),r(\"newshape.name\"),r(\"newshape.showlegend\"),r(\"newshape.legend\"),r(\"newshape.legendwidth\"),r(\"newshape.legendgroup\"),r(\"newshape.legendgrouptitle.text\"),i.coerceFont(r,\"newshape.legendgrouptitle.font\"),r(\"newshape.legendrank\"),r(\"newshape.drawdirection\"),r(\"newshape.layer\"),r(\"newshape.fillcolor\"),r(\"newshape.fillrule\"),r(\"newshape.opacity\"),r(\"newshape.line.width\")){var a=(t||{}).plot_bgcolor||\"#FFF\";r(\"newshape.line.color\",n.contrast(a)),r(\"newshape.line.dash\")}var o=\"drawline\"===t.dragmode,s=r(\"newshape.label.text\"),l=r(\"newshape.label.texttemplate\");if(s||l){r(\"newshape.label.textangle\");var u=r(\"newshape.label.textposition\",o?\"middle\":\"middle center\");r(\"newshape.label.xanchor\"),r(\"newshape.label.yanchor\",function(t,e){return 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p=2*h*Math.PI/a;f.push([s+u*Math.cos(p),l+c*Math.sin(p)])}return f},e.ellipseOver=function(t){var e=t.x0,r=t.y0,n=t.x1,i=t.y1,a=n-e,s=i-r,l=((e-=a)+n)/2,u=((r-=s)+i)/2;return{x0:l-(a*=o),y0:u-(s*=o),x1:l+a,y1:u+s}},e.fixDatesForPaths=function(t,e,r){var n=\"date\"===e.type,i=\"date\"===r.type;if(!n&&!i)return t;for(var a=0;a<t.length;a++)for(var o=0;o<t[a].length;o++)for(var s=0;s+2<t[a][o].length;s+=2)n&&(t[a][o][s+1]=t[a][o][s+1].replace(\" \",\"_\")),i&&(t[a][o][s+2]=t[a][o][s+2].replace(\" \",\"_\"));return t}},90551:function(t,e,r){\"use strict\";var n=r(64505),i=n.drawMode,a=n.openMode,o=r(89995),s=o.i000,l=o.i090,u=o.i180,c=o.i270,f=o.cos45,h=o.sin45,p=r(75549),d=p.p2r,v=p.r2p,g=r(51873).clearOutline,y=r(60165),m=y.readPaths,x=y.writePaths,b=y.ellipseOver,_=y.fixDatesForPaths;function w(t,e,r){var n,i=t[0][0],o=e.gd,p=i.getAttribute(\"d\"),g=o._fullLayout.newshape,y=e.plotinfo,w=e.isActiveShape,T=y.xaxis,k=y.yaxis,A=!!y.domain||!y.xaxis,M=!!y.domain||!y.yaxis,S=a(r),E=m(p,o,y,w),L={editable:!0,visible:g.visible,name:g.name,showlegend:g.showlegend,legend:g.legend,legendwidth:g.legendwidth,legendgroup:g.legendgroup,legendgrouptitle:{text:g.legendgrouptitle.text,font:g.legendgrouptitle.font},legendrank:g.legendrank,label:g.label,xref:A?\"paper\":T._id,yref:M?\"paper\":k._id,layer:g.layer,opacity:g.opacity,line:{color:g.line.color,width:g.line.width,dash:g.line.dash}};if(S||(L.fillcolor=g.fillcolor,L.fillrule=g.fillrule),1===E.length&&(n=E[0]),n&&5===n.length&&\"drawrect\"===r)L.type=\"rect\",L.x0=n[0][1],L.y0=n[0][2],L.x1=n[2][1],L.y1=n[2][2];else if(n&&\"drawline\"===r)L.type=\"line\",L.x0=n[0][1],L.y0=n[0][2],L.x1=n[1][1],L.y1=n[1][2];else if(n&&\"drawcircle\"===r){L.type=\"circle\";var C=n[s][1],P=n[l][1],O=n[u][1],I=n[c][1],D=n[s][2],z=n[l][2],R=n[u][2],F=n[c][2],B=y.xaxis&&(\"date\"===y.xaxis.type||\"log\"===y.xaxis.type),N=y.yaxis&&(\"date\"===y.yaxis.type||\"log\"===y.yaxis.type);B&&(C=v(y.xaxis,C),P=v(y.xaxis,P),O=v(y.xaxis,O),I=v(y.xaxis,I)),N&&(D=v(y.yaxis,D),z=v(y.yaxis,z),R=v(y.yaxis,R),F=v(y.yaxis,F));var j=(P+I)/2,U=(D+R)/2,V=b({x0:j,y0:U,x1:j+(I-P+O-C)/2*f,y1:U+(F-z+R-D)/2*h});B&&(V.x0=d(y.xaxis,V.x0),V.x1=d(y.xaxis,V.x1)),N&&(V.y0=d(y.yaxis,V.y0),V.y1=d(y.yaxis,V.y1)),L.x0=V.x0,L.y0=V.y0,L.x1=V.x1,L.y1=V.y1}else L.type=\"path\",T&&k&&_(E,T,k),L.path=x(E),n=null;return L}t.exports={newShapes:function(t,e){if(t.length&&t[0][0]){var r=e.gd,n=e.isActiveShape,a=e.dragmode,o=(r.layout||{}).shapes||[];if(!i(a)&&void 0!==n){var s=r._fullLayout._activeShapeIndex;if(s<o.length)switch(r._fullLayout.shapes[s].type){case\"rect\":a=\"drawrect\";break;case\"circle\":a=\"drawcircle\";break;case\"line\":a=\"drawline\";break;case\"path\":var l=o[s].path||\"\";a=\"Z\"===l[l.length-1]?\"drawclosedpath\":\"drawopenpath\"}}var u=w(t,e,a);g(r);for(var c=e.editHelpers,f=(c||{}).modifyItem,h=[],p=0;p<o.length;p++){var d=r._fullLayout.shapes[p];if(h[p]=d._input,void 0!==n&&p===r._fullLayout._activeShapeIndex){var v=u;switch(d.type){case\"line\":case\"rect\":case\"circle\":f(\"x0\",v.x0),f(\"x1\",v.x1),f(\"y0\",v.y0),f(\"y1\",v.y1);break;case\"path\":f(\"path\",v.path)}}}return void 0===n?(h.push(u),h):c?c.getUpdateObj():{}}},createShapeObj:w}},51873:function(t){\"use strict\";t.exports={clearOutlineControllers:function(t){var e=t._fullLayout._zoomlayer;e&&e.selectAll(\".outline-controllers\").remove()},clearOutline:function(t){var e=t._fullLayout._zoomlayer;e&&e.selectAll(\".select-outline\").remove(),t._fullLayout._outlining=!1}}},30477:function(t,e,r){\"use strict\";var n=r(21459),i=r(71828),a=r(89298);e.rangeToShapePosition=function(t){return\"log\"===t.type?t.r2d:function(t){return 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n=r._dims;o.setTranslate(e,n.lx+r.pad.l,n.ly+r.pad.t),e.call(S,r,!1),e.call(x,r)}(t,n.select(this),e)}))}}},23243:function(t,e,r){\"use strict\";var n=r(98292);t.exports={moduleType:\"component\",name:n.name,layoutAttributes:r(75067),supplyLayoutDefaults:r(12343),draw:r(44504)}},92998:function(t,e,r){\"use strict\";var n=r(39898),i=r(92770),a=r(74875),o=r(73972),s=r(71828),l=s.strTranslate,u=r(91424),c=r(7901),f=r(63893),h=r(37822),p=r(18783).OPPOSITE_SIDE,d=/ [XY][0-9]* /;t.exports={draw:function(t,e,r){var v,g=r.propContainer,y=r.propName,m=r.placeholder,x=r.traceIndex,b=r.avoid||{},_=r.attributes,w=r.transform,T=r.containerGroup,k=t._fullLayout,A=1,M=!1,S=g.title,E=(S&&S.text?S.text:\"\").trim(),L=S&&S.font?S.font:{},C=L.family,P=L.size,O=L.color;\"title.text\"===y?v=\"titleText\":-1!==y.indexOf(\"axis\")?v=\"axisTitleText\":y.indexOf(!0)&&(v=\"colorbarTitleText\");var I=t._context.edits[v];\"\"===E?A=0:E.replace(d,\" % \")===m.replace(d,\" % 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y(t,e,r,a,o){r||(r=e).attr(\"pointer-events\",\"all\");var l=function(t){return-1==+t.attr(f.menuIndexAttrName)}(r)&&\"buttons\"!==o.type?[]:o.buttons,u=\"dropdown\"===o.type?f.dropdownButtonClassName:f.buttonClassName,c=r.selectAll(\"g.\"+u).data(s.filterVisible(l)),h=c.enter().append(\"g\").classed(u,!0),p=c.exit();\"dropdown\"===o.type?(h.attr(\"opacity\",\"0\").transition().attr(\"opacity\",\"1\"),p.transition().attr(\"opacity\",\"0\").remove()):p.remove();var d=0,g=0,y=o._dims,x=-1!==[\"up\",\"down\"].indexOf(o.direction);\"dropdown\"===o.type&&(x?g=y.headerHeight+f.gapButtonHeader:d=y.headerWidth+f.gapButtonHeader),\"dropdown\"===o.type&&\"up\"===o.direction&&(g=-f.gapButtonHeader+f.gapButton-y.openHeight),\"dropdown\"===o.type&&\"left\"===o.direction&&(d=-f.gapButtonHeader+f.gapButton-y.openWidth);var b={x:y.lx+d+o.pad.l,y:y.ly+g+o.pad.t,yPad:f.gapButton,xPad:f.gapButton,index:0},k={l:b.x+o.borderwidth,t:b.y+o.borderwidth};c.each((function(s,l){var 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e=!!t.hbar,r=!!t.vbar;e&&t.hbar.transition().attr(\"opacity\",\"0\").each(\"end\",(function(){e=!1,r||t.disable()})),r&&t.vbar.transition().attr(\"opacity\",\"0\").each(\"end\",(function(){r=!1,e||t.disable()}))}(a))}function m(t,e,r,n){t.call(x,e).call(b,e,r,n)}function x(t,e){s.ensureSingle(t,\"rect\",f.itemRectClassName,(function(t){t.attr({rx:f.rx,ry:f.ry,\"shape-rendering\":\"crispEdges\"})})).call(a.stroke,e.bordercolor).call(a.fill,e.bgcolor).style(\"stroke-width\",e.borderwidth+\"px\")}function b(t,e,r,n){var i=s.ensureSingle(t,\"text\",f.itemTextClassName,(function(t){t.attr({\"text-anchor\":\"start\",\"data-notex\":1})})),a=r.label,u=n._fullLayout._meta;u&&(a=s.templateString(a,u)),i.call(o.font,e.font).text(a).call(l.convertToTspans,n)}function _(t,e){var r=e.active;t.each((function(t,i){var o=n.select(this);i===r&&e.showactive&&o.select(\"rect.\"+f.itemRectClassName).call(a.fill,f.activeColor)}))}function w(t){t.select(\"rect.\"+f.itemRectClassName).call(a.fill,f.hoverColor)}function T(t,e){t.select(\"rect.\"+f.itemRectClassName).call(a.fill,e.bgcolor)}function k(t,e){var r=e._dims={width1:0,height1:0,heights:[],widths:[],totalWidth:0,totalHeight:0,openWidth:0,openHeight:0,lx:0,ly:0},a=o.tester.selectAll(\"g.\"+f.dropdownButtonClassName).data(s.filterVisible(e.buttons));a.enter().append(\"g\").classed(f.dropdownButtonClassName,!0);var u=-1!==[\"up\",\"down\"].indexOf(e.direction);a.each((function(i,a){var s=n.select(this);s.call(m,e,i,t);var 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t.constructor(0),s=D(t,e);r<0?(n=s,i=a):(n=a,i=s)}else if(n=new t.constructor(r),i=new t.constructor(t.length+e.length-r),r===e.length)n.set(e),i.set(t);else if(r<e.length){var l=e.length-r;n.set(e.subarray(l)),i.set(t),i.set(e.subarray(0,l),t.length)}else{var u=r-e.length,c=t.length-u;n.set(t.subarray(c)),n.set(e,u),i.set(t.subarray(0,c))}else n=t.concat(e),i=r>=0&&r<n.length?n.splice(0,n.length-r):[];return[n,i]})),l=e.redraw(r),c=[r,s.update,i,s.maxPoints];return u.add(r,e.prependTraces,c,t,arguments),l},e.moveTraces=function t(r,n,i){var a,s=[],l=[],c=t,f=t,h=[r=o.getGraphDiv(r),i,n],p=[r,n,i];if(O(r,n,i),n=Array.isArray(n)?n:[n],void 0===i)for(i=[],a=0;a<n.length;a++)i.push(-n.length+a);for(i=Array.isArray(i)?i:[i],n=C(n,r.data.length-1),i=C(i,r.data.length-1),a=0;a<r.data.length;a++)-1===n.indexOf(a)&&s.push(r.data[a]);for(a=0;a<n.length;a++)l.push({newIndex:i[a],trace:r.data[n[a]]});for(l.sort((function(t,e){return t.newIndex-e.newIndex})),a=0;a<l.length;a+=1)s.splice(l[a].newIndex,0,l[a].trace);r.data=s;var d=e.redraw(r);return u.add(r,c,h,f,p),d},e.prependTraces=function t(r,n,i,a){var s=I(r=o.getGraphDiv(r),n,i,a,(function(t,e,r){var n,i;if(o.isTypedArray(t))if(r<=0){var a=new t.constructor(0),s=D(e,t);r<0?(n=s,i=a):(n=a,i=s)}else if(n=new t.constructor(r),i=new t.constructor(t.length+e.length-r),r===e.length)n.set(e),i.set(t);else if(r<e.length){var l=e.length-r;n.set(e.subarray(0,l)),i.set(e.subarray(l)),i.set(t,l)}else{var u=r-e.length;n.set(e),n.set(t.subarray(0,u),e.length),i.set(t.subarray(u))}else n=e.concat(t),i=r>=0&&r<n.length?n.splice(r,n.length):[];return[n,i]})),l=e.redraw(r),c=[r,s.update,i,s.maxPoints];return u.add(r,e.extendTraces,c,t,arguments),l},e.newPlot=function(t,r,n,i){return t=o.getGraphDiv(t),h.cleanPlot([],{},t._fullData||[],t._fullLayout||{}),h.purge(t),e._doPlot(t,r,n,i)},e._doPlot=function(t,r,i,a){var s;if(t=o.getGraphDiv(t),l.init(t),o.isPlainObject(r)){var u=r;r=u.data,i=u.layout,a=u.config,s=u.frames}if(!1===l.triggerHandler(t,\"plotly_beforeplot\",[r,i,a]))return Promise.reject();r||i||o.isPlotDiv(t)||o.warn(\"Calling _doPlot as if redrawing but this container doesn't yet have a plot.\",t),L(t,a),i||(i={}),n.select(t).classed(\"js-plotly-plot\",!0),d.makeTester(),Array.isArray(t._promises)||(t._promises=[]);var f=0===(t.data||[]).length&&Array.isArray(r);Array.isArray(r)&&(_.cleanData(r),f?t.data=r:t.data.push.apply(t.data,r),t.empty=!1),t.layout&&!f||(t.layout=_.cleanLayout(i)),h.supplyDefaults(t);var v=t._fullLayout,m=v._has(\"cartesian\");v._replotting=!0,(f||v._shouldCreateBgLayer)&&(function(t){var e=n.select(t),r=t._fullLayout;if(r._calcInverseTransform=ot,r._calcInverseTransform(t),r._container=e.selectAll(\".plot-container\").data([0]),r._container.enter().insert(\"div\",\":first-child\").classed(\"plot-container\",!0).classed(\"plotly\",!0),r._paperdiv=r._container.selectAll(\".svg-container\").data([0]),r._paperdiv.enter().append(\"div\").classed(\"user-select-none\",!0).classed(\"svg-container\",!0).style(\"position\",\"relative\"),r._glcontainer=r._paperdiv.selectAll(\".gl-container\").data([{}]),r._glcontainer.enter().append(\"div\").classed(\"gl-container\",!0),r._paperdiv.selectAll(\".main-svg\").remove(),r._paperdiv.select(\".modebar-container\").remove(),r._paper=r._paperdiv.insert(\"svg\",\":first-child\").classed(\"main-svg\",!0),r._toppaper=r._paperdiv.append(\"svg\").classed(\"main-svg\",!0),r._modebardiv=r._paperdiv.append(\"div\"),delete r._modeBar,r._hoverpaper=r._paperdiv.append(\"svg\").classed(\"main-svg\",!0),!r._uid){var i={};n.selectAll(\"defs\").each((function(){this.id&&(i[this.id.split(\"-\")[1]]=1)})),r._uid=o.randstr(i)}r._paperdiv.selectAll(\".main-svg\").attr(y.svgAttrs),r._defs=r._paper.append(\"defs\").attr(\"id\",\"defs-\"+r._uid),r._clips=r._defs.append(\"g\").classed(\"clips\",!0),r._topdefs=r._toppaper.append(\"defs\").attr(\"id\",\"topdefs-\"+r._uid),r._topclips=r._topdefs.append(\"g\").classed(\"clips\",!0),r._bgLayer=r._paper.append(\"g\").classed(\"bglayer\",!0),r._draggers=r._paper.append(\"g\").classed(\"draglayer\",!0);var a=r._paper.append(\"g\").classed(\"layer-below\",!0);r._imageLowerLayer=a.append(\"g\").classed(\"imagelayer\",!0),r._shapeLowerLayer=a.append(\"g\").classed(\"shapelayer\",!0),r._cartesianlayer=r._paper.append(\"g\").classed(\"cartesianlayer\",!0),r._polarlayer=r._paper.append(\"g\").classed(\"polarlayer\",!0),r._smithlayer=r._paper.append(\"g\").classed(\"smithlayer\",!0),r._ternarylayer=r._paper.append(\"g\").classed(\"ternarylayer\",!0),r._geolayer=r._paper.append(\"g\").classed(\"geolayer\",!0),r._funnelarealayer=r._paper.append(\"g\").classed(\"funnelarealayer\",!0),r._pielayer=r._paper.append(\"g\").classed(\"pielayer\",!0),r._iciclelayer=r._paper.append(\"g\").classed(\"iciclelayer\",!0),r._treemaplayer=r._paper.append(\"g\").classed(\"treemaplayer\",!0),r._sunburstlayer=r._paper.append(\"g\").classed(\"sunburstlayer\",!0),r._indicatorlayer=r._toppaper.append(\"g\").classed(\"indicatorlayer\",!0),r._glimages=r._paper.append(\"g\").classed(\"glimages\",!0);var s=r._toppaper.append(\"g\").classed(\"layer-above\",!0);r._imageUpperLayer=s.append(\"g\").classed(\"imagelayer\",!0),r._shapeUpperLayer=s.append(\"g\").classed(\"shapelayer\",!0),r._selectionLayer=r._toppaper.append(\"g\").classed(\"selectionlayer\",!0),r._infolayer=r._toppaper.append(\"g\").classed(\"infolayer\",!0),r._menulayer=r._toppaper.append(\"g\").classed(\"menulayer\",!0),r._zoomlayer=r._toppaper.append(\"g\").classed(\"zoomlayer\",!0),r._hoverlayer=r._hoverpaper.append(\"g\").classed(\"hoverlayer\",!0),r._modebardiv.classed(\"modebar-container\",!0).style(\"position\",\"absolute\").style(\"top\",\"0px\").style(\"right\",\"0px\"),t.emit(\"plotly_framework\")}(t),v._shouldCreateBgLayer&&delete v._shouldCreateBgLayer),d.initGradients(t),d.initPatterns(t),f&&p.saveShowSpikeInitial(t);var x=!t.calcdata||t.calcdata.length!==(t._fullData||[]).length;x&&h.doCalcdata(t);for(var b=0;b<t.calcdata.length;b++)t.calcdata[b][0].trace=t._fullData[b];t._context.responsive?t._responsiveChartHandler||(t._responsiveChartHandler=function(){o.isHidden(t)||h.resize(t)},window.addEventListener(\"resize\",t._responsiveChartHandler)):o.clearResponsive(t);var T=o.extendFlat({},v._size),k=0;function A(){if(h.clearAutoMarginIds(t),w.drawMarginPushers(t),p.allowAutoMargin(t),t._fullLayout.title.text&&t._fullLayout.title.automargin&&h.allowAutoMargin(t,\"title.automargin\"),v._has(\"pie\"))for(var e=t._fullData,r=0;r<e.length;r++){var n=e[r];\"pie\"===n.type&&n.automargin&&h.allowAutoMargin(t,\"pie.\"+n.uid+\".automargin\")}return h.doAutoMargin(t),h.previousPromises(t)}function S(){t._transitioning||(w.doAutoRangeAndConstraints(t),f&&p.saveRangeInitial(t),c.getComponentMethod(\"rangeslider\",\"calcAutorange\")(t))}var E=[h.previousPromises,function(){if(s)return e.addFrames(t,s)},function e(){for(var r=v._basePlotModules,n=0;n<r.length;n++)r[n].drawFramework&&r[n].drawFramework(t);!v._glcanvas&&v._has(\"gl\")&&(v._glcanvas=v._glcontainer.selectAll(\".gl-canvas\").data([{key:\"contextLayer\",context:!0,pick:!1},{key:\"focusLayer\",context:!1,pick:!1},{key:\"pickLayer\",context:!1,pick:!0}],(function(t){return t.key})),v._glcanvas.enter().append(\"canvas\").attr(\"class\",(function(t){return\"gl-canvas gl-canvas-\"+t.key.replace(\"Layer\",\"\")})).style({position:\"absolute\",top:0,left:0,overflow:\"visible\",\"pointer-events\":\"none\"}));var i=t._context.plotGlPixelRatio;if(v._glcanvas){v._glcanvas.attr(\"width\",v.width*i).attr(\"height\",v.height*i).style(\"width\",v.width+\"px\").style(\"height\",v.height+\"px\");var a=v._glcanvas.data()[0].regl;if(a&&(Math.floor(v.width*i)!==a._gl.drawingBufferWidth||Math.floor(v.height*i)!==a._gl.drawingBufferHeight)){var s=\"WebGL context buffer and canvas dimensions do not match due to browser/WebGL bug.\";if(!k)return o.log(s+\" Clearing 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g){if(c=Q(i,K)){if(d=c.head,v=c.tail,a=c.attr||d+\".uirevision\",(u=(l=s(n,a).get())&&tt(a,e))&&u===l){if(null===(f=g[i])&&(f=void 0),nt(p=(h=s(e,i)).get(),f)){void 0===p&&\"autorange\"===v&&y.push(d),h.set(R(s(n,i).get()));continue}if(\"autorange\"===v||\"range[\"===v.substr(0,6)){var b=g[d+\".range[0]\"],_=g[d+\".range[1]\"],w=g[d+\".autorange\"];if(w||null===w&&null===b&&null===_){if(!(d in m)){var T=s(e,d).get();m[d]=T&&(T.autorange||!1!==T.autorange&&(!T.range||2!==T.range.length))}if(m[d]){h.set(R(s(n,i).get()));continue}}}}}else o.warn(\"unrecognized GUI edit: \"+i);delete g[i],c&&\"range[\"===c.tail.substr(0,6)&&(x[c.head]=1)}for(var k=0;k<y.length;k++){var A=y[k];if(x[A]){var M=s(e,A).get();M&&delete M.autorange}}var S=n._tracePreGUI;for(var E in S){var L,C=S[E],P=null;for(i in C){if(!P){var O=et(E,r);if(O<0){delete S[E];break}var I=rt(E,t,(L=r[O]._fullInput).index);if(I<0){delete 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c={getValObject:function(t){var e=f.getTraceValObject(l,t);return!l._module.animatable&&e.anim&&(e.anim=!1),e},flags:u,immutable:n,transition:i,newDataRevision:a,gd:t},p={};for(s=0;s<e.length;s++)if(r[s]){if(l=r[s]._fullInput,h.hasMakesDataTransform(l)&&(l=r[s]),p[l.uid])continue;p[l.uid]=1,it(e[s]._fullInput,l,[],c)}return(u.calc||u.plot)&&(u.fullReplot=!0),i&&u.nChanges&&u.nChangesAnim&&(u.anim=u.nChanges===u.nChangesAnim&&o?\"all\":\"some\"),u}(t,u,y,x,b,A);if(W(t)&&(k.layoutReplot=!0),S.calc||k.calc){t.calcdata=void 0;for(var E=Object.getOwnPropertyNames(m),C=0;C<E.length;C++){var P=E[C],O=P.substring(0,5);if(\"xaxis\"===O||\"yaxis\"===O){var I=m[P]._emptyCategories;I&&I()}}}else h.supplyDefaultsUpdateCalc(t.calcdata,y);var D=[];if(a&&(t._transitionData={},h.createTransitionData(t),D.push((function(){return e.addFrames(t,a)}))),m.transition&&!v&&(S.anim||k.anim))k.ticks&&D.push(w.doTicksRelayout),h.doCalcdata(t),w.doAutoRangeAndConstraints(t),D.push((function(){return h.transitionFromReact(t,S,k,p)}));else if(S.fullReplot||k.layoutReplot||v)t._fullLayout._skipDefaults=!0,D.push(e._doPlot);else{for(var z in k.arrays){var F=k.arrays[z];if(F.length){var B=c.getComponentMethod(z,\"drawOne\");if(B!==o.noop)for(var N=0;N<F.length;N++)B(t,F[N]);else{var j=c.getComponentMethod(z,\"draw\");if(j===o.noop)throw new Error(\"cannot draw components: \"+z);j(t)}}}D.push(h.previousPromises),S.style&&D.push(w.doTraceStyle),(S.colorbars||k.colorbars)&&D.push(w.doColorBars),k.legend&&D.push(w.doLegend),k.layoutstyle&&D.push(w.layoutStyles),k.axrange&&H(D),k.ticks&&D.push(w.doTicksRelayout),k.modebar&&D.push(w.doModeBar),k.camera&&D.push(w.doCamera),D.push(M)}D.push(h.rehover,h.redrag,h.reselect),(l=o.syncOrAsync(D,t))&&l.then||(l=Promise.resolve(t))}else l=e.newPlot(t,r,n,i);return l.then((function(){return t.emit(\"plotly_react\",{data:r,layout:n}),t}))},e.redraw=function(t){if(t=o.getGraphDiv(t),!o.isPlotDiv(t))throw new Error(\"This element is not a Plotly plot: 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l=s.simpleMap(e.range,e.r2l);n=[l[0],.8*l[0]+.2*l[1]]}if(t.range=s.simpleMap(n,e.l2r),t._isMinor=!0,q.prepTicks(t,r),a){var u=i(e.dtick),c=i(t.dtick),f=u?e.dtick:+e.dtick.substring(1),h=c?t.dtick:+t.dtick.substring(1);u&&c?et(f,h)?f===2*A&&h===2*M&&(t.dtick=A):f===2*A&&h===3*M?t.dtick=A:f!==A||(e._input.minor||{}).nticks?rt(f/h,2.5)?t.dtick=f/2:t.dtick=f:t.dtick=M:\"M\"===String(e.dtick).charAt(0)?c?t.dtick=\"M1\":et(f,h)?f>=12&&2===h&&(t.dtick=\"M3\"):t.dtick=e.dtick:\"L\"===String(t.dtick).charAt(0)?\"L\"===String(e.dtick).charAt(0)?et(f,h)||(t.dtick=rt(f/h,2.5)?e.dtick/2:e.dtick):t.dtick=\"D1\":\"D2\"===t.dtick&&+e.dtick>1&&(t.dtick=1)}t.range=e.range}void 0===e.minor._tick0Init&&(t.tick0=e.tick0)},q.prepTicks=function(t,e){var r=s.simpleMap(t.range,t.r2l,void 0,void 0,e);if(\"auto\"===t.tickmode||!t.dtick){var n,a=t.nticks;a||(\"category\"===t.type||\"multicategory\"===t.type?(n=t.tickfont?s.bigFont(t.tickfont.size||12):15,a=t._length/n):(n=\"y\"===t._id.charAt(0)?40:80,a=s.constrain(t._length/n,4,9)+1),\"radialaxis\"===t._name&&(a*=2)),t.minor&&\"array\"!==t.minor.tickmode||\"array\"===t.tickmode&&(a*=100),t._roughDTick=Math.abs(r[1]-r[0])/a,q.autoTicks(t,t._roughDTick),t._minDtick>0&&t.dtick<2*t._minDtick&&(t.dtick=t._minDtick,t.tick0=t.l2r(t._forceTick0))}\"period\"===t.ticklabelmode&&function(t){var e;function r(){return!(i(t.dtick)||\"M\"!==t.dtick.charAt(0))}var n=r(),a=q.getTickFormat(t);if(a){var o=t._dtickInit!==t.dtick;/%[fLQsSMX]/.test(a)||(/%[HI]/.test(a)?(e=E,o&&!n&&t.dtick<E&&(t.dtick=E)):/%p/.test(a)?(e=S,o&&!n&&t.dtick<S&&(t.dtick=S)):/%[Aadejuwx]/.test(a)?(e=M,o&&!n&&t.dtick<M&&(t.dtick=M)):/%[UVW]/.test(a)?(e=A,o&&!n&&t.dtick<A&&(t.dtick=A)):/%[Bbm]/.test(a)?(e=T,o&&(n?nt(t.dtick)<1:t.dtick<k)&&(t.dtick=\"M1\")):/%[q]/.test(a)?(e=b,o&&(n?nt(t.dtick)<3:t.dtick<_)&&(t.dtick=\"M3\")):/%[Yy]/.test(a)&&(e=y,o&&(n?nt(t.dtick)<12:t.dtick<m)&&(t.dtick=\"M12\")))}(n=r())&&t.tick0===t._dowTick0&&(t.tick0=t._rawTick0),t._definedDelta=e}(t),t.tick0||(t.tick0=\"date\"===t.type?\"2000-01-01\":0),\"date\"===t.type&&t.dtick<.1&&(t.dtick=.1),vt(t)},q.calcTicks=function(t,e){for(var r,n,a=t.type,o=t.calendar,l=t.ticklabelstep,u=\"period\"===t.ticklabelmode,c=s.simpleMap(t.range,t.r2l,void 0,void 0,e),f=c[1]<c[0],h=Math.min(c[0],c[1]),p=Math.max(c[0],c[1]),d=Math.max(1e3,t._length||0),v=[],L=[],C=[],P=[],I=t.minor&&(t.minor.ticks||t.minor.showgrid),D=1;D>=(I?0:1);D--){var z=!D;D?(t._dtickInit=t.dtick,t._tick0Init=t.tick0):(t.minor._dtickInit=t.minor.dtick,t.minor._tick0Init=t.minor.tick0);var R=D?t:s.extendFlat({},t,t.minor);if(z?q.prepMinorTicks(R,t,e):q.prepTicks(R,e),\"array\"!==R.tickmode)if(\"sync\"!==R.tickmode){var F=K(c),B=F[0],N=F[1],j=i(R.dtick),U=\"log\"===a&&!(j||\"L\"===R.dtick.charAt(0)),V=q.tickFirst(R,e);if(D){if(t._tmin=V,V<B!==f)break;\"category\"!==a&&\"multicategory\"!==a||(N=f?Math.max(-.5,N):Math.min(t._categories.length-.5,N))}var H,G,Z=null,Y=V;D&&(j?G=t.dtick:\"date\"===a?\"string\"==typeof t.dtick&&\"M\"===t.dtick.charAt(0)&&(G=T*t.dtick.substring(1)):G=t._roughDTick,H=Math.round((t.r2l(Y)-t.r2l(t.tick0))/G)-1);var W=R.dtick;for(R.rangebreaks&&R._tick0Init!==R.tick0&&(Y=zt(Y,t),f||(Y=q.tickIncrement(Y,W,!f,o))),D&&u&&(Y=q.tickIncrement(Y,W,!f,o),H--);f?Y>=N:Y<=N;Y=q.tickIncrement(Y,W,f,o)){if(D&&H++,R.rangebreaks&&!f){if(Y<B)continue;if(R.maskBreaks(Y)===O&&zt(Y,R)>=p)break}if(C.length>d||Y===Z)break;Z=Y;var X={value:Y};D?(U&&Y!==(0|Y)&&(X.simpleLabel=!0),l>1&&H%l&&(X.skipLabel=!0),C.push(X)):(X.minor=!0,P.push(X))}}else C=[],v=at(t);else D?(C=[],v=ot(t)):(P=[],L=ot(t))}if(I&&!(\"inside\"===t.minor.ticks&&\"outside\"===t.ticks||\"outside\"===t.minor.ticks&&\"inside\"===t.ticks)){for(var J=C.map((function(t){return t.value})),$=[],Q=0;Q<P.length;Q++){var tt=P[Q],et=tt.value;if(-1===J.indexOf(et)){for(var rt=!1,nt=0;!rt&&nt<C.length;nt++)1e7+C[nt].value===1e7+et&&(rt=!0);rt||$.push(tt)}}P=$}if(u&&function(t,e,r){for(var n=0;n<t.length;n++){var i=t[n].value,a=n,o=n+1;n<t.length-1?(a=n,o=n+1):n>0?(a=n-1,o=n):(a=n,o=n);var s,l=t[a].value,u=t[o].value,c=Math.abs(u-l),f=r||c,h=0;f>=m?h=c>=m&&c<=g?c:y:r===b&&f>=_?h=c>=_&&c<=x?c:b:f>=k?h=c>=k&&c<=w?c:T:r===A&&f>=A?h=A:f>=M?h=M:r===S&&f>=S?h=S:r===E&&f>=E&&(h=E),h>=c&&(h=c,s=!0);var p=i+h;if(e.rangebreaks&&h>0){for(var d=0,v=0;v<84;v++){var L=(v+.5)/84;e.maskBreaks(i*(1-L)+L*p)!==O&&d++}(h*=d/84)||(t[n].drop=!0),s&&c>A&&(h=c)}(h>0||0===n)&&(t[n].periodX=i+h/2)}}(C,t,t._definedDelta),t.rangebreaks){var it=\"y\"===t._id.charAt(0),st=1;\"auto\"===t.tickmode&&(st=t.tickfont?t.tickfont.size:12);var lt=NaN;for(r=C.length-1;r>-1;r--)if(C[r].drop)C.splice(r,1);else{C[r].value=zt(C[r].value,t);var ut=t.c2p(C[r].value);(it?lt>ut-st:lt<ut+st)?C.splice(f?r+1:r,1):lt=ut}}Dt(t)&&360===Math.abs(c[1]-c[0])&&C.pop(),t._tmax=(C[C.length-1]||{}).value,t._prevDateHead=\"\",t._inCalcTicks=!0;var ct,ft,ht=function(e){e.text=\"\",t._prevDateHead=n};for(C=C.concat(P),r=0;r<C.length;r++){var pt=C[r].minor,dt=C[r].value;pt?L.push({x:dt,minor:!0}):(n=t._prevDateHead,ct=q.tickText(t,dt,!1,C[r].simpleLabel),void 0!==(ft=C[r].periodX)&&(ct.periodX=ft,(ft>p||ft<h)&&(ft>p&&(ct.periodX=p),ft<h&&(ct.periodX=h),ht(ct))),C[r].skipLabel&&ht(ct),v.push(ct))}return v=v.concat(L),t._inCalcTicks=!1,u&&v.length&&(v[0].noTick=!0),v};var st=[2,5,10],lt=[1,2,3,6,12],ut=[1,2,5,10,15,30],ct=[1,2,3,7,14],ft=[-.046,0,.301,.477,.602,.699,.778,.845,.903,.954,1],ht=[-.301,0,.301,.699,1],pt=[15,30,45,90,180];function dt(t,e,r){return e*s.roundUp(t/e,r)}function vt(t){var e=t.dtick;if(t._tickexponent=0,i(e)||\"string\"==typeof e||(e=1),\"category\"!==t.type&&\"multicategory\"!==t.type||(t._tickround=null),\"date\"===t.type){var r=t.r2l(t.tick0),n=t.l2r(r).replace(/(^-|i)/g,\"\"),a=n.length;if(\"M\"===String(e).charAt(0))a>10||\"01-01\"!==n.substr(5)?t._tickround=\"d\":t._tickround=+e.substr(1)%12==0?\"y\":\"m\";else if(e>=M&&a<=10||e>=15*M)t._tickround=\"d\";else if(e>=L&&a<=16||e>=E)t._tickround=\"M\";else if(e>=C&&a<=19||e>=L)t._tickround=\"S\";else{var o=t.l2r(r+e).replace(/^-/,\"\").length;t._tickround=Math.max(a,o)-20,t._tickround<0&&(t._tickround=4)}}else if(i(e)||\"L\"===e.charAt(0)){var s=t.range.map(t.r2d||Number);i(e)||(e=Number(e.substr(1))),t._tickround=2-Math.floor(Math.log(e)/Math.LN10+.01);var l=Math.max(Math.abs(s[0]),Math.abs(s[1])),u=Math.floor(Math.log(l)/Math.LN10+.01),c=void 0===t.minexponent?3:t.minexponent;Math.abs(u)>c&&(mt(t.exponentformat)&&!xt(u)?t._tickexponent=3*Math.round((u-1)/3):t._tickexponent=u)}else t._tickround=null}function gt(t,e,r){var n=t.tickfont||{};return{x:e,dx:0,dy:0,text:r||\"\",fontSize:n.size,font:n.family,fontColor:n.color}}q.autoTicks=function(t,e,r){var n;function a(t){return Math.pow(t,Math.floor(Math.log(e)/Math.LN10))}if(\"date\"===t.type){t.tick0=s.dateTick0(t.calendar,0);var o=2*e;if(o>y)e/=y,n=a(10),t.dtick=\"M\"+12*dt(e,n,st);else if(o>T)e/=T,t.dtick=\"M\"+dt(e,1,lt);else if(o>M){if(t.dtick=dt(e,M,t._hasDayOfWeekBreaks?[1,2,7,14]:ct),!r){var l=q.getTickFormat(t),u=\"period\"===t.ticklabelmode;u&&(t._rawTick0=t.tick0),/%[uVW]/.test(l)?t.tick0=s.dateTick0(t.calendar,2):t.tick0=s.dateTick0(t.calendar,1),u&&(t._dowTick0=t.tick0)}}else o>E?t.dtick=dt(e,E,lt):o>L?t.dtick=dt(e,L,ut):o>C?t.dtick=dt(e,C,ut):(n=a(10),t.dtick=dt(e,n,st))}else if(\"log\"===t.type){t.tick0=0;var c=s.simpleMap(t.range,t.r2l);if(t._isMinor&&(e*=1.5),e>.7)t.dtick=Math.ceil(e);else if(Math.abs(c[1]-c[0])<1){var f=1.5*Math.abs((c[1]-c[0])/e);e=Math.abs(Math.pow(10,c[1])-Math.pow(10,c[0]))/f,n=a(10),t.dtick=\"L\"+dt(e,n,st)}else t.dtick=e>.3?\"D2\":\"D1\"}else\"category\"===t.type||\"multicategory\"===t.type?(t.tick0=0,t.dtick=Math.ceil(Math.max(e,1))):Dt(t)?(t.tick0=0,n=1,t.dtick=dt(e,n,pt)):(t.tick0=0,n=a(10),t.dtick=dt(e,n,st));if(0===t.dtick&&(t.dtick=1),!i(t.dtick)&&\"string\"!=typeof t.dtick){var h=t.dtick;throw t.dtick=1,\"ax.dtick error: \"+String(h)}},q.tickIncrement=function(t,e,r,a){var o=r?-1:1;if(i(e))return s.increment(t,o*e);var l=e.charAt(0),u=o*Number(e.substr(1));if(\"M\"===l)return s.incrementMonth(t,u,a);if(\"L\"===l)return Math.log(Math.pow(10,t)+u)/Math.LN10;if(\"D\"===l){var c=\"D2\"===e?ht:ft,f=t+.01*o,h=s.roundUp(s.mod(f,1),c,r);return Math.floor(f)+Math.log(n.round(Math.pow(10,h),1))/Math.LN10}throw\"unrecognized dtick 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s=t._fullLayout;ut=s._has(\"scattergl\"),ct=s._has(\"splom\"),ft=s._has(\"svg\")}r+=e.yaxis._shift,mt();var xt=function(t,e,r){return t?\"nsew\"===t?r?\"\":\"pan\"===e?\"move\":\"crosshair\":t.toLowerCase()+\"-resize\":\"pointer\"}(at+it,t._fullLayout.dragmode,gt),bt=D(e,v+y+\"drag\",xt,r,s,u,f);if(ot&&!gt)return bt.onmousedown=null,bt.style.pointerEvents=\"none\",bt;var _t,wt,Tt,kt,At,Mt,St,Et,Lt,Ct,Pt={element:bt,gd:t,plotinfo:e};function Ot(){Pt.plotinfo.selection=!1,M(t)}function It(t,r){var i=Pt.gd;if(i._fullLayout._activeShapeIndex>=0)i._fullLayout._deactivateShape(i);else{var o=i._fullLayout.clickmode;if(H(i),2!==t||yt||qt(),gt)o.indexOf(\"select\")>-1&&S(r,i,J,K,e.id,Pt),o.indexOf(\"event\")>-1&&p.click(i,r,e.id);else if(1===t&&yt){var s=v?I:O,u=\"s\"===v||\"w\"===y?0:1,f=s._name+\".range[\"+u+\"]\",h=function(t,e){var r,n=t.range[e],i=Math.abs(n-t.range[1-e]);return\"date\"===t.type?n:\"log\"===t.type?(r=Math.ceil(Math.max(0,-Math.log(i)/Math.LN10))+3,a(\".\"+r+\"g\")(Math.pow(10,n))):(r=Math.floor(Math.log(Math.abs(n))/Math.LN10)-Math.floor(Math.log(i)/Math.LN10)+4,a(\".\"+String(r)+\"g\")(n))}(s,u),d=\"left\",g=\"middle\";if(s.fixedrange)return;v?(g=\"n\"===v?\"top\":\"bottom\",\"right\"===s.side&&(d=\"right\")):\"e\"===y&&(d=\"right\"),i._context.showAxisRangeEntryBoxes&&n.select(bt).call(c.makeEditable,{gd:i,immediate:!0,background:i._fullLayout.paper_bgcolor,text:String(h),fill:s.tickfont?s.tickfont.color:\"#444\",horizontalAlign:d,verticalAlign:g}).on(\"edit\",(function(t){var e=s.d2r(t);void 0!==e&&l.call(\"_guiRelayout\",i,f,e)}))}}}function Dt(e,r){if(t._transitioningWithDuration)return!1;var n=Math.max(0,Math.min(tt,pt*e+_t)),i=Math.max(0,Math.min(et,dt*r+wt)),a=Math.abs(n-_t),o=Math.abs(i-wt);function 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n=r(39898),i=r(27362),a=i.geoPath,o=i.geoDistance,s=r(65704),l=r(73972),u=r(71828),c=u.strTranslate,f=r(7901),h=r(91424),p=r(30211),d=r(74875),v=r(89298),g=r(71739).getAutoRange,y=r(28569),m=r(47322).prepSelect,x=r(47322).clearOutline,b=r(47322).selectOnClick,_=r(74455),w=r(78776),T=r(41327),k=r(90973),A=r(96892).zL;function M(t){this.id=t.id,this.graphDiv=t.graphDiv,this.container=t.container,this.topojsonURL=t.topojsonURL,this.isStatic=t.staticPlot,this.topojsonName=null,this.topojson=null,this.projection=null,this.scope=null,this.viewInitial=null,this.fitScale=null,this.bounds=null,this.midPt=null,this.hasChoropleth=!1,this.traceHash={},this.layers={},this.basePaths={},this.dataPaths={},this.dataPoints={},this.clipDef=null,this.clipRect=null,this.bgRect=null,this.makeFramework()}var S=M.prototype;function E(t,e){var r=w.clipPad,n=t[0]+r,i=t[1]-r,a=e[0]+r,o=e[1]-r;n>0&&i<0&&(i+=360);var 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0)&&r(\"lakecolor\"),r(\"showrivers\",!!x&&void 0)&&(r(\"rivercolor\"),r(\"riverwidth\")),r(\"showcountries\",d&&\"usa\"!==c&&x)&&(r(\"countrycolor\"),r(\"countrywidth\")),(\"usa\"===c||\"north america\"===c&&50===u)&&(r(\"showsubunits\",x),r(\"subunitcolor\"),r(\"subunitwidth\")),d||r(\"showframe\",x)&&(r(\"framecolor\"),r(\"framewidth\")),r(\"bgcolor\"),r(\"fitbounds\")&&(delete e.projection.scale,d?(delete e.center.lon,delete e.center.lat):y?(delete e.center.lon,delete e.center.lat,delete e.projection.rotation.lon,delete e.projection.rotation.lat,delete e.lonaxis.range,delete e.lataxis.range):(delete e.center.lon,delete e.center.lat,delete e.projection.rotation.lon))}t.exports=function(t,e,r){i(t,e,r,{type:\"geo\",attributes:s,handleDefaults:u,fullData:r,partition:\"y\"})}},74455:function(t,e,r){\"use strict\";var n=r(39898),i=r(71828),a=r(73972),o=Math.PI/180,s=180/Math.PI,l={cursor:\"pointer\"},u={cursor:\"auto\"};function c(t,e){return 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r,i={r:e.rotate(),k:e.scale()},a=c(0,e),h=function(t){for(var e=0,r=arguments.length,i=[];++e<r;)i.push(arguments[e]);var a=n.dispatch.apply(null,i);return a.of=function(e,r){return function(i){var o;try{o=i.sourceEvent=n.event,i.target=t,n.event=i,a[i.type].apply(e,r)}finally{n.event=o}}},a}(a,\"zoomstart\",\"zoom\",\"zoomend\"),p=0,d=a.on;function y(t){var r=e.rotate();t(\"projection.rotation.lon\",-r[0]),t(\"projection.rotation.lat\",-r[1])}return a.on(\"zoomstart\",(function(){n.select(this).style(l);var t,u,c,f,y,b,_,w,T,k,A,M=n.mouse(this),S=e.rotate(),E=S,L=e.translate(),C=(u=.5*(t=S)[0]*o,c=.5*t[1]*o,f=.5*t[2]*o,y=Math.sin(u),b=Math.cos(u),_=Math.sin(c),w=Math.cos(c),T=Math.sin(f),[b*w*(k=Math.cos(f))+y*_*T,y*w*k-b*_*T,b*_*k+y*w*T,b*w*T-y*_*k]);r=v(e,M),d.call(a,\"zoom\",(function(){var t,a,o,l,u,c,f,p,d,y,b=n.mouse(this);if(e.scale(i.k=n.event.scale),r){if(v(e,b)){e.rotate(S).translate(L);var _=v(e,b),w=function(t,e){if(t&&e){var 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f=0;f<t.length;f++)a=t[f],\"gl2d\"===e&&n.traceIs(a,\"gl2d\")?a[l[0]]===o&&a[l[1]]===s&&u.push(a):a[l]===r&&u.push(a);return u}},75071:function(t,e,r){\"use strict\";var n=r(16825),i=r(1195),a=r(48956),o=r(85555),s=r(38520);function l(t,e){this.element=t,this.plot=e,this.mouseListener=null,this.wheelListener=null,this.lastInputTime=Date.now(),this.lastPos=[0,0],this.boxEnabled=!1,this.boxInited=!1,this.boxStart=[0,0],this.boxEnd=[0,0],this.dragStart=[0,0]}t.exports=function(t){var e=t.mouseContainer,r=t.glplot,u=new l(e,r);function c(){t.xaxis.autorange=!1,t.yaxis.autorange=!1}function f(e,n,i){var a,s,l=t.calcDataBox(),f=r.viewBox,h=u.lastPos[0],p=u.lastPos[1],d=o.MINDRAG*r.pixelRatio,v=o.MINZOOM*r.pixelRatio;function g(e,r,n){var i=Math.min(r,n),a=Math.max(r,n);i!==a?(l[e]=i,l[e+2]=a,u.dataBox=l,t.setRanges(l)):(t.selectBox.selectBox=[0,0,1,1],t.glplot.setDirty())}switch(n*=r.pixelRatio,i*=r.pixelRatio,i=f[3]-f[1]-i,t.fullLayout.dragmode){case\"zoom\":if(e){var y=n/(f[2]-f[0])*(l[2]-l[0])+l[0],m=i/(f[3]-f[1])*(l[3]-l[1])+l[1];u.boxInited||(u.boxStart[0]=y,u.boxStart[1]=m,u.dragStart[0]=n,u.dragStart[1]=i),u.boxEnd[0]=y,u.boxEnd[1]=m,u.boxInited=!0,u.boxEnabled||u.boxStart[0]===u.boxEnd[0]&&u.boxStart[1]===u.boxEnd[1]||(u.boxEnabled=!0);var x=Math.abs(u.dragStart[0]-n)<v,b=Math.abs(u.dragStart[1]-i)<v;if(!function(){for(var e=t.graphDiv._fullLayout._axisConstraintGroups,r=t.xaxis._id,n=t.yaxis._id,i=0;i<e.length;i++)if(-1!==e[i][r]){if(-1!==e[i][n])return!0;break}return!1}()||x&&b)x&&(u.boxEnd[0]=u.boxStart[0]),b&&(u.boxEnd[1]=u.boxStart[1]);else{a=u.boxEnd[0]-u.boxStart[0],s=u.boxEnd[1]-u.boxStart[1];var 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o=a.prototype,s=[\"xaxis\",\"yaxis\"];o.merge=function(t){var e,r,n,a,o,l,u,c,f,h,p;for(this.titleEnable=!1,this.backgroundColor=i(t.plot_bgcolor),h=0;h<2;++h){var d=(e=s[h]).charAt(0);for(n=(r=t[this.scene[e]._name]).title.text===this.scene.fullLayout._dfltTitle[d]?\"\":r.title.text,p=0;p<=2;p+=2)this.labelEnable[h+p]=!1,this.labels[h+p]=n,this.labelColor[h+p]=i(r.title.font.color),this.labelFont[h+p]=r.title.font.family,this.labelSize[h+p]=r.title.font.size,this.labelPad[h+p]=this.getLabelPad(e,r),this.tickEnable[h+p]=!1,this.tickColor[h+p]=i((r.tickfont||{}).color),this.tickAngle[h+p]=\"auto\"===r.tickangle?0:Math.PI*-r.tickangle/180,this.tickPad[h+p]=this.getTickPad(r),this.tickMarkLength[h+p]=0,this.tickMarkWidth[h+p]=r.tickwidth||0,this.tickMarkColor[h+p]=i(r.tickcolor),this.borderLineEnable[h+p]=!1,this.borderLineColor[h+p]=i(r.linecolor),this.borderLineWidth[h+p]=r.linewidth||0;u=this.hasSharedAxis(r),o=this.hasAxisInDfltPos(e,r)&&!u,l=this.hasAxisInAltrPos(e,r)&&!u,a=r.mirror||!1,c=u?-1!==String(a).indexOf(\"all\"):!!a,f=u?\"allticks\"===a:-1!==String(a).indexOf(\"ticks\"),o?this.labelEnable[h]=!0:l&&(this.labelEnable[h+2]=!0),o?this.tickEnable[h]=r.showticklabels:l&&(this.tickEnable[h+2]=r.showticklabels),(o||c)&&(this.borderLineEnable[h]=r.showline),(l||c)&&(this.borderLineEnable[h+2]=r.showline),(o||f)&&(this.tickMarkLength[h]=this.getTickMarkLength(r)),(l||f)&&(this.tickMarkLength[h+2]=this.getTickMarkLength(r)),this.gridLineEnable[h]=r.showgrid,this.gridLineColor[h]=i(r.gridcolor),this.gridLineWidth[h]=r.gridwidth,this.zeroLineEnable[h]=r.zeroline,this.zeroLineColor[h]=i(r.zerolinecolor),this.zeroLineWidth[h]=r.zerolinewidth}},o.hasSharedAxis=function(t){var e=this.scene,r=e.fullLayout._subplots.gl2d;return 0!==n.findSubplotsWithAxis(r,t).indexOf(e.id)},o.hasAxisInDfltPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"bottom\"===r:\"yaxis\"===t?\"left\"===r:void 0},o.hasAxisInAltrPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"top\"===r:\"yaxis\"===t?\"right\"===r:void 0},o.getLabelPad=function(t,e){var r=1.5,n=e.title.font.size,i=e.showticklabels;return\"xaxis\"===t?\"top\"===e.side?n*(r+(i?1:0))-10:n*(r+(i?.5:0))-10:\"yaxis\"===t?\"right\"===e.side?10+n*(r+(i?1:.5)):10+n*(r+(i?.5:0)):void 0},o.getTickPad=function(t){return\"outside\"===t.ticks?10+t.ticklen:15},o.getTickMarkLength=function(t){if(!t.ticks)return 0;var e=t.ticklen;return\"inside\"===t.ticks?-e:e},t.exports=function(t){return new a(t)}},4796:function(t,e,r){\"use strict\";var n=r(30962).overrideAll,i=r(92918),a=r(10820),o=r(77922),s=r(85555),l=r(93612),u=r(528),c=r(27659).NG;e.name=\"gl2d\",e.attr=[\"xaxis\",\"yaxis\"],e.idRoot=[\"x\",\"y\"],e.idRegex=s.idRegex,e.attrRegex=s.attrRegex,e.attributes=r(89502),e.supplyLayoutDefaults=function(t,e,r){e._has(\"cartesian\")||l.supplyLayoutDefaults(t,e,r)},e.layoutAttrOverrides=n(l.layoutAttributes,\"plot\",\"from-root\"),e.baseLayoutAttrOverrides=n({plot_bgcolor:a.plot_bgcolor,hoverlabel:u.hoverlabel},\"plot\",\"nested\"),e.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl2d,a=0;a<n.length;a++){var o=n[a],s=e._plots[o],l=c(r,\"gl2d\",o),u=s._scene2d;void 0===u&&(u=new i({id:o,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),s._scene2d=u),u.plot(l,t.calcdata,e,t.layout)}},e.clean=function(t,e,r,n){for(var i=n._subplots.gl2d||[],a=0;a<i.length;a++){var o=i[a],s=n._plots[o];s._scene2d&&0===c(t,\"gl2d\",o).length&&(s._scene2d.destroy(),delete n._plots[o])}l.clean.apply(this,arguments)},e.drawFramework=function(t){t._context.staticPlot||l.drawFramework(t)},e.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){var i=e._plots[r[n]]._scene2d,a=i.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":a,x:0,y:0,width:\"100%\",height:\"100%\",preserveAspectRatio:\"none\"}),i.destroy()}},e.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++)e._plots[r[n]]._scene2d.updateFx(e.dragmode)}},92918:function(t,e,r){\"use strict\";var n,i,a=r(73972),o=r(89298),s=r(30211),l=r(9330).gl_plot2d,u=r(9330).gl_spikes2d,c=r(9330).gl_select_box,f=r(40372),h=r(82961),p=r(75071),d=r(58617),v=r(99082),g=v.enforce,y=v.clean,m=r(71739).doAutoRange,x=r(64505),b=x.drawMode,_=x.selectMode,w=[\"xaxis\",\"yaxis\"],T=r(85555).SUBPLOT_PATTERN;function k(t,e){this.container=t.container,this.graphDiv=t.graphDiv,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.scrollZoom=this.graphDiv._context._scrollZoom.cartesian,this.fullData=null,this.updateRefs(e),this.makeFramework(),this.stopped||(this.glplotOptions=h(this),this.glplotOptions.merge(e),this.glplot=l(this.glplotOptions),this.camera=p(this),this.traces={},this.spikes=u(this.glplot),this.selectBox=c(this.glplot,{innerFill:!1,outerFill:!0}),this.lastButtonState=0,this.pickResult=null,this.isMouseOver=!0,this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw())}t.exports=k;var A=k.prototype;A.makeFramework=function(){if(this.staticPlot){if(!(i||(n=document.createElement(\"canvas\"),i=f({canvas:n,preserveDrawingBuffer:!1,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"Error creating static canvas/context for image server\");this.canvas=n,this.gl=i}else{var t=this.container.querySelector(\".gl-canvas-focus\"),e=f({canvas:t,preserveDrawingBuffer:!0,premultipliedAlpha:!0});if(!e)return d(this),void(this.stopped=!0);this.canvas=t,this.gl=e}var r=this.canvas;r.style.width=\"100%\",r.style.height=\"100%\",r.style.position=\"absolute\",r.style.top=\"0px\",r.style.left=\"0px\",r.style[\"pointer-events\"]=\"none\",this.updateSize(r);var a=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");a.style.position=\"absolute\",a.style.top=a.style.left=\"0px\",a.style.width=a.style.height=\"100%\",a.style[\"z-index\"]=20,a.style[\"pointer-events\"]=\"none\";var o=this.mouseContainer=document.createElement(\"div\");o.style.position=\"absolute\",o.style[\"pointer-events\"]=\"auto\",this.pickCanvas=this.container.querySelector(\".gl-canvas-pick\");var s=this.container;s.appendChild(a),s.appendChild(o);var l=this;o.addEventListener(\"mouseout\",(function(){l.isMouseOver=!1,l.unhover()})),o.addEventListener(\"mouseover\",(function(){l.isMouseOver=!0}))},A.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(n),this.updateSize(this.canvas);var e=this.glplot.gl,r=e.drawingBufferWidth,i=e.drawingBufferHeight;e.clearColor(1,1,1,0),e.clear(e.COLOR_BUFFER_BIT|e.DEPTH_BUFFER_BIT),this.glplot.setDirty(),this.glplot.draw(),e.bindFramebuffer(e.FRAMEBUFFER,null);var a=new Uint8Array(r*i*4);e.readPixels(0,0,r,i,e.RGBA,e.UNSIGNED_BYTE,a);for(var o=0,s=i-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var u=0;u<4;++u){var c=a[4*(r*o+l)+u];a[4*(r*o+l)+u]=a[4*(r*s+l)+u],a[4*(r*s+l)+u]=c}var f=document.createElement(\"canvas\");f.width=r,f.height=i;var h,p=f.getContext(\"2d\",{willReadFrequently:!0}),d=p.createImageData(r,i);switch(d.data.set(a),p.putImageData(d,0,0),t){case\"jpeg\":h=f.toDataURL(\"image/jpeg\");break;case\"webp\":h=f.toDataURL(\"image/webp\");break;default:h=f.toDataURL(\"image/png\")}return this.staticPlot&&this.container.removeChild(n),h},A.updateSize=function(t){t||(t=this.canvas);var e=this.pixelRatio,r=this.fullLayout,n=r.width,i=r.height,a=0|Math.ceil(e*n),o=0|Math.ceil(e*i);return t.width===a&&t.height===o||(t.width=a,t.height=o),t},A.computeTickMarks=function(){this.xaxis.setScale(),this.yaxis.setScale();for(var t=[o.calcTicks(this.xaxis),o.calcTicks(this.yaxis)],e=0;e<2;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=t[e][r].text+\"\";return t},A.updateRefs=function(t){this.fullLayout=t;var e=this.id.match(T),r=\"xaxis\"+e[1],n=\"yaxis\"+e[2];this.xaxis=this.fullLayout[r],this.yaxis=this.fullLayout[n]},A.relayoutCallback=function(){var t=this.graphDiv,e=this.xaxis,r=this.yaxis,n=t.layout,i={},o=i[e._name+\".range\"]=e.range.slice(),s=i[r._name+\".range\"]=r.range.slice();i[e._name+\".autorange\"]=e.autorange,i[r._name+\".autorange\"]=r.autorange,a.call(\"_storeDirectGUIEdit\",t.layout,t._fullLayout._preGUI,i);var l=n[e._name];l.range=o,l.autorange=e.autorange;var u=n[r._name];u.range=s,u.autorange=r.autorange,i.lastInputTime=this.camera.lastInputTime,t.emit(\"plotly_relayout\",i)},A.cameraChanged=function(){var t=this.camera;this.glplot.setDataBox(this.calcDataBox());var e=this.computeTickMarks();(function(t,e){for(var r=0;r<2;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1})(e,this.glplotOptions.ticks)&&(this.glplotOptions.ticks=e,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions),this.handleAnnotations())},A.handleAnnotations=function(){for(var t=this.graphDiv,e=this.fullLayout.annotations,r=0;r<e.length;r++){var n=e[r];n.xref===this.xaxis._id&&n.yref===this.yaxis._id&&a.getComponentMethod(\"annotations\",\"drawOne\")(t,r)}},A.destroy=function(){if(this.glplot){var t=this.traces;t&&Object.keys(t).map((function(e){t[e].dispose(),delete t[e]})),this.glplot.dispose(),this.container.removeChild(this.svgContainer),this.container.removeChild(this.mouseContainer),this.fullData=null,this.glplot=null,this.stopped=!0,this.camera.mouseListener.enabled=!1,this.mouseContainer.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null}},A.plot=function(t,e,r){var n=this.glplot;this.updateRefs(r),this.xaxis.clearCalc(),this.yaxis.clearCalc(),this.updateTraces(t,e),this.updateFx(r.dragmode);var i=r.width,a=r.height;this.updateSize(this.canvas);var o=this.glplotOptions;o.merge(r),o.screenBox=[0,0,i,a];var s={_fullLayout:{_axisConstraintGroups:r._axisConstraintGroups,xaxis:this.xaxis,yaxis:this.yaxis,_size:r._size}};y(s,this.xaxis),y(s,this.yaxis);var l,u,c=r._size,f=this.xaxis.domain,h=this.yaxis.domain;for(o.viewBox=[c.l+f[0]*c.w,c.b+h[0]*c.h,i-c.r-(1-f[1])*c.w,a-c.t-(1-h[1])*c.h],this.mouseContainer.style.width=c.w*(f[1]-f[0])+\"px\",this.mouseContainer.style.height=c.h*(h[1]-h[0])+\"px\",this.mouseContainer.height=c.h*(h[1]-h[0]),this.mouseContainer.style.left=c.l+f[0]*c.w+\"px\",this.mouseContainer.style.top=c.t+(1-h[1])*c.h+\"px\",u=0;u<2;++u)(l=this[w[u]])._length=o.viewBox[u+2]-o.viewBox[u],m(this.graphDiv,l),l.setScale();g(s),o.ticks=this.computeTickMarks(),o.dataBox=this.calcDataBox(),o.merge(r),n.update(o),this.glplot.draw()},A.calcDataBox=function(){var t=this.xaxis,e=this.yaxis,r=t.range,n=e.range,i=t.r2l,a=e.r2l;return[i(r[0]),a(n[0]),i(r[1]),a(n[1])]},A.setRanges=function(t){var e=this.xaxis,r=this.yaxis,n=e.l2r,i=r.l2r;e.range=[n(t[0]),n(t[2])],r.range=[i(t[1]),i(t[3])]},A.updateTraces=function(t,e){var r,n,i,a=Object.keys(this.traces);this.fullData=t;t:for(r=0;r<a.length;r++){var o=a[r],s=this.traces[o];for(n=0;n<t.length;n++)if((i=t[n]).uid===o&&i.type===s.type)continue t;s.dispose(),delete this.traces[o]}for(r=0;r<t.length;r++){i=t[r];var l=e[r],u=this.traces[i.uid];u?u.update(i,l):(u=i._module.plot(this,i,l),this.traces[i.uid]=u)}this.glplot.objects.sort((function(t,e){return t._trace.index-e._trace.index}))},A.updateFx=function(t){_(t)||b(t)?(this.pickCanvas.style[\"pointer-events\"]=\"none\",this.mouseContainer.style[\"pointer-events\"]=\"none\"):(this.pickCanvas.style[\"pointer-events\"]=\"auto\",this.mouseContainer.style[\"pointer-events\"]=\"auto\"),this.mouseContainer.style.cursor=\"pan\"===t?\"move\":\"zoom\"===t?\"crosshair\":null},A.emitPointAction=function(t,e){for(var r,n=t.trace.uid,i=t.pointIndex,a=0;a<this.fullData.length;a++)this.fullData[a].uid===n&&(r=this.fullData[a]);var o={x:t.traceCoord[0],y:t.traceCoord[1],curveNumber:r.index,pointNumber:i,data:r._input,fullData:this.fullData,xaxis:this.xaxis,yaxis:this.yaxis};s.appendArrayPointValue(o,r,i),this.graphDiv.emit(e,{points:[o]})},A.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=1===this.lastButtonState&&0===r.buttons,i=this.fullLayout;this.lastButtonState=r.buttons,this.cameraChanged();var a,o=r.x*t.pixelRatio,l=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&\"zoom\"===i.dragmode){this.selectBox.enabled=!0;for(var u=this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],c=0;c<2;c++)e.boxStart[c]===e.boxEnd[c]&&(u[c]=t.dataBox[c],u[c+2]=t.dataBox[c+2]);t.setDirty()}else if(!e.panning&&this.isMouseOver){this.selectBox.enabled=!1;var f=i._size,h=this.xaxis.domain,p=this.yaxis.domain,d=(a=t.pick(o/t.pixelRatio+f.l+h[0]*f.w,l/t.pixelRatio-(f.t+(1-p[1])*f.h)))&&a.object._trace.handlePick(a);if(d&&n&&this.emitPointAction(d,\"plotly_click\"),a&&\"skip\"!==a.object._trace.hoverinfo&&i.hovermode&&d&&(!this.lastPickResult||this.lastPickResult.traceUid!==d.trace.uid||this.lastPickResult.dataCoord[0]!==d.dataCoord[0]||this.lastPickResult.dataCoord[1]!==d.dataCoord[1])){var v=d;this.lastPickResult={traceUid:d.trace?d.trace.uid:null,dataCoord:d.dataCoord.slice()},this.spikes.update({center:a.dataCoord}),v.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(a.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(a.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio],this.emitPointAction(d,\"plotly_hover\");var g=this.fullData[v.trace.index]||{},y=v.pointIndex,m=s.castHoverinfo(g,i,y);if(m&&\"all\"!==m){var x=m.split(\"+\");-1===x.indexOf(\"x\")&&(v.traceCoord[0]=void 0),-1===x.indexOf(\"y\")&&(v.traceCoord[1]=void 0),-1===x.indexOf(\"z\")&&(v.traceCoord[2]=void 0),-1===x.indexOf(\"text\")&&(v.textLabel=void 0),-1===x.indexOf(\"name\")&&(v.name=void 0)}s.loneHover({x:v.screenCoord[0],y:v.screenCoord[1],xLabel:this.hoverFormatter(\"xaxis\",v.traceCoord[0]),yLabel:this.hoverFormatter(\"yaxis\",v.traceCoord[1]),zLabel:v.traceCoord[2],text:v.textLabel,name:v.name,color:s.castHoverOption(g,y,\"bgcolor\")||v.color,borderColor:s.castHoverOption(g,y,\"bordercolor\"),fontFamily:s.castHoverOption(g,y,\"font.family\"),fontSize:s.castHoverOption(g,y,\"font.size\"),fontColor:s.castHoverOption(g,y,\"font.color\"),nameLength:s.castHoverOption(g,y,\"namelength\"),textAlign:s.castHoverOption(g,y,\"align\")},{container:this.svgContainer,gd:this.graphDiv})}}a||this.unhover(),t.draw()}},A.unhover=function(){this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,this.graphDiv.emit(\"plotly_unhover\"),s.loneUnhover(this.svgContainer))},A.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return o.tickText(r,r.c2l(e),\"hover\").text}}},58547:function(t,e,r){\"use strict\";var n=r(30962).overrideAll,i=r(528),a=r(33539),o=r(27659).NG,s=r(71828),l=r(77922),u=\"gl3d\",c=\"scene\";e.name=u,e.attr=c,e.idRoot=c,e.idRegex=e.attrRegex=s.counterRegex(\"scene\"),e.attributes=r(59084),e.layoutAttributes=r(65500),e.baseLayoutAttrOverrides=n({hoverlabel:i.hoverlabel},\"plot\",\"nested\"),e.supplyLayoutDefaults=r(24682),e.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots[u],i=0;i<n.length;i++){var s=n[i],l=o(r,u,s),c=e[s],f=c.camera,h=c._scene;h||(h=new a({id:s,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio,camera:f},e),c._scene=h),h.viewInitial||(h.viewInitial={up:{x:f.up.x,y:f.up.y,z:f.up.z},eye:{x:f.eye.x,y:f.eye.y,z:f.eye.z},center:{x:f.center.x,y:f.center.y,z:f.center.z}}),h.plot(l,e,t.layout)}},e.clean=function(t,e,r,n){for(var i=n._subplots[u]||[],a=0;a<i.length;a++){var o=i[a];!e[o]&&n[o]._scene&&(n[o]._scene.destroy(),n._infolayer&&n._infolayer.selectAll(\".annotation-\"+o).remove())}},e.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots[u],n=e._size,i=0;i<r.length;i++){var a=e[r[i]],o=a.domain,s=a._scene,c=s.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:l.svg,\"xlink:href\":c,x:n.l+n.w*o.x[0],y:n.t+n.h*(1-o.y[1]),width:n.w*(o.x[1]-o.x[0]),height:n.h*(o.y[1]-o.y[0]),preserveAspectRatio:\"none\"}),s.destroy()}},e.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),c+e}},e.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots[u],n=0;n<r.length;n++)e[r[n]]._scene.updateFx(e.dragmode,e.hovermode)}},59084:function(t){\"use strict\";t.exports={scene:{valType:\"subplotid\",dflt:\"scene\",editType:\"calc+clearAxisTypes\"}}},77894:function(t,e,r){\"use strict\";var n=r(7901),i=r(13838),a=r(1426).extendFlat,o=r(30962).overrideAll;t.exports=o({visible:i.visible,showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:n.defaultLine},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},color:i.color,categoryorder:i.categoryorder,categoryarray:i.categoryarray,title:{text:i.title.text,font:i.title.font},type:a({},i.type,{values:[\"-\",\"linear\",\"log\",\"date\",\"category\"]}),autotypenumbers:i.autotypenumbers,autorange:i.autorange,autorangeoptions:{minallowed:i.autorangeoptions.minallowed,maxallowed:i.autorangeoptions.maxallowed,clipmin:i.autorangeoptions.clipmin,clipmax:i.autorangeoptions.clipmax,include:i.autorangeoptions.include,editType:\"plot\"},rangemode:i.rangemode,minallowed:i.minallowed,maxallowed:i.maxallowed,range:a({},i.range,{items:[{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}},{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}}],anim:!1}),tickmode:i.minor.tickmode,nticks:i.nticks,tick0:i.tick0,dtick:i.dtick,tickvals:i.tickvals,ticktext:i.ticktext,ticks:i.ticks,mirror:i.mirror,ticklen:i.ticklen,tickwidth:i.tickwidth,tickcolor:i.tickcolor,showticklabels:i.showticklabels,labelalias:i.labelalias,tickfont:i.tickfont,tickangle:i.tickangle,tickprefix:i.tickprefix,showtickprefix:i.showtickprefix,ticksuffix:i.ticksuffix,showticksuffix:i.showticksuffix,showexponent:i.showexponent,exponentformat:i.exponentformat,minexponent:i.minexponent,separatethousands:i.separatethousands,tickformat:i.tickformat,tickformatstops:i.tickformatstops,hoverformat:i.hoverformat,showline:i.showline,linecolor:i.linecolor,linewidth:i.linewidth,showgrid:i.showgrid,gridcolor:a({},i.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:i.gridwidth,zeroline:i.zeroline,zerolinecolor:i.zerolinecolor,zerolinewidth:i.zerolinewidth,_deprecated:{title:i._deprecated.title,titlefont:i._deprecated.titlefont}},\"plot\",\"from-root\")},3277:function(t,e,r){\"use strict\";var n=r(84267).mix,i=r(71828),a=r(44467),o=r(77894),s=r(951),l=r(71453),u=[\"xaxis\",\"yaxis\",\"zaxis\"];t.exports=function(t,e,r){var c,f;function h(t,e){return i.coerce(c,f,o,t,e)}for(var p=0;p<u.length;p++){var d=u[p];c=t[d]||{},(f=a.newContainer(e,d))._id=d[0]+r.scene,f._name=d,s(c,f,h,r),l(c,f,h,{font:r.font,letter:d[0],data:r.data,showGrid:!0,noTickson:!0,noTicklabelmode:!0,noTicklabelstep:!0,noTicklabelposition:!0,noTicklabeloverflow:!0,bgColor:r.bgColor,calendar:r.calendar},r.fullLayout),h(\"gridcolor\",n(f.color,r.bgColor,72.72727272727273).toRgbString()),h(\"title.text\",d[0]),f.setScale=i.noop,h(\"showspikes\")&&(h(\"spikesides\"),h(\"spikethickness\"),h(\"spikecolor\",f.color)),h(\"showaxeslabels\"),h(\"showbackground\")&&h(\"backgroundcolor\")}}},30422:function(t,e,r){\"use strict\";var n=r(78614),i=r(71828),a=[\"xaxis\",\"yaxis\",\"zaxis\"];function o(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=this.tickPad.slice(),this._defaultLabelPad=this.labelPad.slice(),this._defaultLineTickLength=this.lineTickLength.slice()}o.prototype.merge=function(t,e){for(var r=this,o=0;o<3;++o){var s=e[a[o]];s.visible?(r.labels[o]=t._meta?i.templateString(s.title.text,t._meta):s.title.text,\"font\"in s.title&&(s.title.font.color&&(r.labelColor[o]=n(s.title.font.color)),s.title.font.family&&(r.labelFont[o]=s.title.font.family),s.title.font.size&&(r.labelSize[o]=s.title.font.size)),\"showline\"in s&&(r.lineEnable[o]=s.showline),\"linecolor\"in s&&(r.lineColor[o]=n(s.linecolor)),\"linewidth\"in s&&(r.lineWidth[o]=s.linewidth),\"showgrid\"in s&&(r.gridEnable[o]=s.showgrid),\"gridcolor\"in s&&(r.gridColor[o]=n(s.gridcolor)),\"gridwidth\"in s&&(r.gridWidth[o]=s.gridwidth),\"log\"===s.type?r.zeroEnable[o]=!1:\"zeroline\"in s&&(r.zeroEnable[o]=s.zeroline),\"zerolinecolor\"in s&&(r.zeroLineColor[o]=n(s.zerolinecolor)),\"zerolinewidth\"in s&&(r.zeroLineWidth[o]=s.zerolinewidth),\"ticks\"in s&&s.ticks?r.lineTickEnable[o]=!0:r.lineTickEnable[o]=!1,\"ticklen\"in s&&(r.lineTickLength[o]=r._defaultLineTickLength[o]=s.ticklen),\"tickcolor\"in s&&(r.lineTickColor[o]=n(s.tickcolor)),\"tickwidth\"in s&&(r.lineTickWidth[o]=s.tickwidth),\"tickangle\"in s&&(r.tickAngle[o]=\"auto\"===s.tickangle?-3600:Math.PI*-s.tickangle/180),\"showticklabels\"in s&&(r.tickEnable[o]=s.showticklabels),\"tickfont\"in s&&(s.tickfont.color&&(r.tickColor[o]=n(s.tickfont.color)),s.tickfont.family&&(r.tickFont[o]=s.tickfont.family),s.tickfont.size&&(r.tickSize[o]=s.tickfont.size)),\"mirror\"in s?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(s.mirror)?(r.lineTickMirror[o]=!0,r.lineMirror[o]=!0):!0===s.mirror?(r.lineTickMirror[o]=!1,r.lineMirror[o]=!0):(r.lineTickMirror[o]=!1,r.lineMirror[o]=!1):r.lineMirror[o]=!1,\"showbackground\"in s&&!1!==s.showbackground?(r.backgroundEnable[o]=!0,r.backgroundColor[o]=n(s.backgroundcolor)):r.backgroundEnable[o]=!1):(r.tickEnable[o]=!1,r.labelEnable[o]=!1,r.lineEnable[o]=!1,r.lineTickEnable[o]=!1,r.gridEnable[o]=!1,r.zeroEnable[o]=!1,r.backgroundEnable[o]=!1)}},t.exports=function(t,e){var r=new o;return r.merge(t,e),r}},24682:function(t,e,r){\"use strict\";var n=r(71828),i=r(7901),a=r(73972),o=r(49119),s=r(3277),l=r(65500),u=r(27659).NG,c=\"gl3d\";function f(t,e,r,n){for(var o=r(\"bgcolor\"),l=i.combine(o,n.paper_bgcolor),f=[\"up\",\"center\",\"eye\"],h=0;h<f.length;h++)r(\"camera.\"+f[h]+\".x\"),r(\"camera.\"+f[h]+\".y\"),r(\"camera.\"+f[h]+\".z\");r(\"camera.projection.type\");var p=!!r(\"aspectratio.x\")&&!!r(\"aspectratio.y\")&&!!r(\"aspectratio.z\"),d=r(\"aspectmode\",p?\"manual\":\"auto\");p||(t.aspectratio=e.aspectratio={x:1,y:1,z:1},\"manual\"===d&&(e.aspectmode=\"auto\"),t.aspectmode=e.aspectmode);var v=u(n.fullData,c,n.id);s(t,e,{font:n.font,scene:n.id,data:v,bgColor:l,calendar:n.calendar,autotypenumbersDflt:n.autotypenumbersDflt,fullLayout:n.fullLayout}),a.getComponentMethod(\"annotations3d\",\"handleDefaults\")(t,e,n);var g=n.getDfltFromLayout(\"dragmode\");if(!1!==g&&!g)if(g=\"orbit\",t.camera&&t.camera.up){var y=t.camera.up.x,m=t.camera.up.y,x=t.camera.up.z;0!==x&&(y&&m&&x?x/Math.sqrt(y*y+m*m+x*x)>.999&&(g=\"turntable\"):g=\"turntable\")}else g=\"turntable\";r(\"dragmode\",g),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}t.exports=function(t,e,r){var i=e._basePlotModules.length>1;o(t,e,r,{type:c,attributes:l,handleDefaults:f,fullLayout:e,font:e.font,fullData:r,getDfltFromLayout:function(e){if(!i)return n.validate(t[e],l[e])?t[e]:void 0},autotypenumbersDflt:e.autotypenumbers,paper_bgcolor:e.paper_bgcolor,calendar:e.calendar})}},65500:function(t,e,r){\"use strict\";var n=r(77894),i=r(27670).Y,a=r(1426).extendFlat,o=r(71828).counterRegex;function s(t,e,r){return{x:{valType:\"number\",dflt:t,editType:\"camera\"},y:{valType:\"number\",dflt:e,editType:\"camera\"},z:{valType:\"number\",dflt:r,editType:\"camera\"},editType:\"camera\"}}t.exports={_arrayAttrRegexps:[o(\"scene\",\".annotations\",!0)],bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"plot\"},camera:{up:a(s(0,0,1),{}),center:a(s(0,0,0),{}),eye:a(s(1.25,1.25,1.25),{}),projection:{type:{valType:\"enumerated\",values:[\"perspective\",\"orthographic\"],dflt:\"perspective\",editType:\"calc\"},editType:\"calc\"},editType:\"camera\"},domain:i({name:\"scene\",editType:\"plot\"}),aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\",editType:\"plot\",impliedEdits:{\"aspectratio.x\":void 0,\"aspectratio.y\":void 0,\"aspectratio.z\":void 0}},aspectratio:{x:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},y:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},z:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},editType:\"plot\",impliedEdits:{aspectmode:\"manual\"}},xaxis:n,yaxis:n,zaxis:n,dragmode:{valType:\"enumerated\",values:[\"orbit\",\"turntable\",\"zoom\",\"pan\",!1],editType:\"plot\"},hovermode:{valType:\"enumerated\",values:[\"closest\",!1],dflt:\"closest\",editType:\"modebar\"},uirevision:{valType:\"any\",editType:\"none\"},editType:\"plot\",_deprecated:{cameraposition:{valType:\"info_array\",editType:\"camera\"}}}},13133:function(t,e,r){\"use strict\";var n=r(78614),i=[\"xaxis\",\"yaxis\",\"zaxis\"];function a(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}a.prototype.merge=function(t){for(var e=0;e<3;++e){var r=t[i[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=n(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},t.exports=function(t){var e=new a;return e.merge(t),e}},96085:function(t,e,r){\"use strict\";t.exports=function(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,s=t.fullSceneLayout,l=[[],[],[]],u=0;u<3;++u){var c=s[a[u]];if(c._length=(r[u].hi-r[u].lo)*r[u].pixelsPerDataUnit/t.dataScale[u],Math.abs(c._length)===1/0||isNaN(c._length))l[u]=[];else{c._input_range=c.range.slice(),c.range[0]=r[u].lo/t.dataScale[u],c.range[1]=r[u].hi/t.dataScale[u],c._m=1/(t.dataScale[u]*r[u].pixelsPerDataUnit),c.range[0]===c.range[1]&&(c.range[0]-=1,c.range[1]+=1);var f=c.tickmode;if(\"auto\"===c.tickmode){c.tickmode=\"linear\";var h=c.nticks||i.constrain(c._length/40,4,9);n.autoTicks(c,Math.abs(c.range[1]-c.range[0])/h)}for(var p=n.calcTicks(c,{msUTC:!0}),d=0;d<p.length;++d)p[d].x=p[d].x*t.dataScale[u],\"date\"===c.type&&(p[d].text=p[d].text.replace(/\\<br\\>/g,\" \"));l[u]=p,c.tickmode=f}}for(e.ticks=l,u=0;u<3;++u)for(o[u]=.5*(t.glplot.bounds[0][u]+t.glplot.bounds[1][u]),d=0;d<2;++d)e.bounds[d][u]=t.glplot.bounds[d][u];t.contourLevels=function(t){for(var e=new Array(3),r=0;r<3;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}(l)};var n=r(89298),i=r(71828),a=[\"xaxis\",\"yaxis\",\"zaxis\"],o=[0,0,0]},63538:function(t){\"use strict\";function e(t,e){var r,n,i=[0,0,0,0];for(r=0;r<4;++r)for(n=0;n<4;++n)i[n]+=t[4*r+n]*e[r];return i}t.exports=function(t,r){return e(t.projection,e(t.view,e(t.model,[r[0],r[1],r[2],1])))}},33539:function(t,e,r){\"use strict\";var n,i,a=r(9330).gl_plot3d,o=a.createCamera,s=a.createScene,l=r(40372),u=r(38520),c=r(73972),f=r(71828),h=f.preserveDrawingBuffer(),p=r(89298),d=r(30211),v=r(78614),g=r(58617),y=r(63538),m=r(30422),x=r(13133),b=r(96085),_=r(71739).applyAutorangeOptions,w=!1;function T(t,e){var r=document.createElement(\"div\"),n=t.container;this.graphDiv=t.graphDiv;var i=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");i.style.position=\"absolute\",i.style.top=i.style.left=\"0px\",i.style.width=i.style.height=\"100%\",i.style[\"z-index\"]=20,i.style[\"pointer-events\"]=\"none\",r.appendChild(i),this.svgContainer=i,r.id=t.id,r.style.position=\"absolute\",r.style.top=r.style.left=\"0px\",r.style.width=r.style.height=\"100%\",n.appendChild(r),this.fullLayout=e,this.id=t.id||\"scene\",this.fullSceneLayout=e[this.id],this.plotArgs=[[],{},{}],this.axesOptions=m(e,e[this.id]),this.spikeOptions=x(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=this.pixelRatio||t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],this.convertAnnotations=c.getComponentMethod(\"annotations3d\",\"convert\"),this.drawAnnotations=c.getComponentMethod(\"annotations3d\",\"draw\"),this.initializeGLPlot()}var k=T.prototype;k.prepareOptions=function(){var t=this,e={canvas:t.canvas,gl:t.gl,glOptions:{preserveDrawingBuffer:h,premultipliedAlpha:!0,antialias:!0},container:t.container,axes:t.axesOptions,spikes:t.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1,cameraObject:t.camera,pixelRatio:t.pixelRatio};if(t.staticMode){if(!(i||(n=document.createElement(\"canvas\"),i=l({canvas:n,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"error creating static canvas/context for image server\");e.gl=i,e.canvas=n}return e};var A=!0;k.tryCreatePlot=function(){var t=this,e=t.prepareOptions(),r=!0;try{t.glplot=s(e)}catch(n){if(t.staticMode||!A||h)r=!1;else{f.warn([\"webgl setup failed possibly due to\",\"false preserveDrawingBuffer config.\",\"The mobile/tablet device may not be detected by is-mobile module.\",\"Enabling preserveDrawingBuffer in second attempt to create webgl scene...\"].join(\" \"));try{h=e.glOptions.preserveDrawingBuffer=!0,t.glplot=s(e)}catch(t){h=e.glOptions.preserveDrawingBuffer=!1,r=!1}}}return A=!1,r},k.initializeGLCamera=function(){var t=this,e=t.fullSceneLayout.camera,r=\"orthographic\"===e.projection.type;t.camera=o(t.container,{center:[e.center.x,e.center.y,e.center.z],eye:[e.eye.x,e.eye.y,e.eye.z],up:[e.up.x,e.up.y,e.up.z],_ortho:r,zoomMin:.01,zoomMax:100,mode:\"orbit\"})},k.initializeGLPlot=function(){var t=this;if(t.initializeGLCamera(),!t.tryCreatePlot())return g(t);t.traces={},t.make4thDimension();var e=t.graphDiv,r=e.layout,n=function(){var e={};return t.isCameraChanged(r)&&(e[t.id+\".camera\"]=t.getCamera()),t.isAspectChanged(r)&&(e[t.id+\".aspectratio\"]=t.glplot.getAspectratio(),\"manual\"!==r[t.id].aspectmode&&(t.fullSceneLayout.aspectmode=r[t.id].aspectmode=e[t.id+\".aspectmode\"]=\"manual\")),e},i=function(t){if(!1!==t.fullSceneLayout.dragmode){var e=n();t.saveLayout(r),t.graphDiv.emit(\"plotly_relayout\",e)}};return t.glplot.canvas&&(t.glplot.canvas.addEventListener(\"mouseup\",(function(){i(t)})),t.glplot.canvas.addEventListener(\"touchstart\",(function(){w=!0})),t.glplot.canvas.addEventListener(\"wheel\",(function(r){if(e._context._scrollZoom.gl3d){if(t.camera._ortho){var n=r.deltaX>r.deltaY?1.1:1/1.1,a=t.glplot.getAspectratio();t.glplot.setAspectratio({x:n*a.x,y:n*a.y,z:n*a.z})}i(t)}}),!!u&&{passive:!1}),t.glplot.canvas.addEventListener(\"mousemove\",(function(){if(!1!==t.fullSceneLayout.dragmode&&0!==t.camera.mouseListener.buttons){var e=n();t.graphDiv.emit(\"plotly_relayouting\",e)}})),t.staticMode||t.glplot.canvas.addEventListener(\"webglcontextlost\",(function(r){e&&e.emit&&e.emit(\"plotly_webglcontextlost\",{event:r,layer:t.id})}),!1)),t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=function(){t.render()},!0},k.render=function(){var t,e=this,r=e.graphDiv,n=e.svgContainer,i=e.container.getBoundingClientRect();r._fullLayout._calcInverseTransform(r);var a=r._fullLayout._invScaleX,o=r._fullLayout._invScaleY,s=i.width*a,l=i.height*o;n.setAttributeNS(null,\"viewBox\",\"0 0 \"+s+\" \"+l),n.setAttributeNS(null,\"width\",s),n.setAttributeNS(null,\"height\",l),b(e),e.glplot.axes.update(e.axesOptions);for(var u=Object.keys(e.traces),c=null,h=e.glplot.selection,v=0;v<u.length;++v)\"skip\"!==(t=e.traces[u[v]]).data.hoverinfo&&t.handlePick(h)&&(c=t),t.setContourLevels&&t.setContourLevels();function g(t,r,n){var i=e.fullSceneLayout[t+\"axis\"];return\"log\"!==i.type&&(r=i.d2l(r)),p.hoverLabelText(i,r,n)}if(null!==c){var m=y(e.glplot.cameraParams,h.dataCoordinate);t=c.data;var x,_=r._fullData[t.index],T=h.index,k={xLabel:g(\"x\",h.traceCoordinate[0],t.xhoverformat),yLabel:g(\"y\",h.traceCoordinate[1],t.yhoverformat),zLabel:g(\"z\",h.traceCoordinate[2],t.zhoverformat)},A=d.castHoverinfo(_,e.fullLayout,T),M=(A||\"\").split(\"+\"),S=A&&\"all\"===A;_.hovertemplate||S||(-1===M.indexOf(\"x\")&&(k.xLabel=void 0),-1===M.indexOf(\"y\")&&(k.yLabel=void 0),-1===M.indexOf(\"z\")&&(k.zLabel=void 0),-1===M.indexOf(\"text\")&&(h.textLabel=void 0),-1===M.indexOf(\"name\")&&(c.name=void 0));var E=[];\"cone\"===t.type||\"streamtube\"===t.type?(k.uLabel=g(\"x\",h.traceCoordinate[3],t.uhoverformat),(S||-1!==M.indexOf(\"u\"))&&E.push(\"u: \"+k.uLabel),k.vLabel=g(\"y\",h.traceCoordinate[4],t.vhoverformat),(S||-1!==M.indexOf(\"v\"))&&E.push(\"v: \"+k.vLabel),k.wLabel=g(\"z\",h.traceCoordinate[5],t.whoverformat),(S||-1!==M.indexOf(\"w\"))&&E.push(\"w: \"+k.wLabel),k.normLabel=h.traceCoordinate[6].toPrecision(3),(S||-1!==M.indexOf(\"norm\"))&&E.push(\"norm: \"+k.normLabel),\"streamtube\"===t.type&&(k.divergenceLabel=h.traceCoordinate[7].toPrecision(3),(S||-1!==M.indexOf(\"divergence\"))&&E.push(\"divergence: \"+k.divergenceLabel)),h.textLabel&&E.push(h.textLabel),x=E.join(\"<br>\")):\"isosurface\"===t.type||\"volume\"===t.type?(k.valueLabel=p.hoverLabelText(e._mockAxis,e._mockAxis.d2l(h.traceCoordinate[3]),t.valuehoverformat),E.push(\"value: \"+k.valueLabel),h.textLabel&&E.push(h.textLabel),x=E.join(\"<br>\")):x=h.textLabel;var L={x:h.traceCoordinate[0],y:h.traceCoordinate[1],z:h.traceCoordinate[2],data:_._input,fullData:_,curveNumber:_.index,pointNumber:T};d.appendArrayPointValue(L,_,T),t._module.eventData&&(L=_._module.eventData(L,h,_,{},T));var C={points:[L]};if(e.fullSceneLayout.hovermode){var 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I,D,z,B=g.makeRectDragger(c,T,\"crosshair\",-x,-x,m,m),N={element:B,gd:u};!1===t.dragmode&&(N.dragmode=!1),V(n.select(B),v.visible&&h<f,{transform:l(b,_)}),N.prepFn=function(){I=null,D=null,z=null,N.moveFn=j,N.doneFn=H,w(u)},N.clampFn=function(t,e){return Math.sqrt(t*t+e*e)<S.MINDRAG&&(t=0,e=0),[t,e]},y.init(N)}function j(t,e){if(I)I(t,e);else{var n=[t,-e],a=[Math.cos(M),Math.sin(M)],s=Math.abs(o.dot(n,a)/Math.sqrt(o.dot(n,n)));isNaN(s)||(I=s<.5?q:G)}var l={};!function(t){null!==D?t[i.id+\".radialaxis.angle\"]=D:null!==z&&(t[i.id+\".radialaxis.range[\"+r+\"]\"]=z)}(l),u.emit(\"plotly_relayouting\",l)}function H(){null!==D?a.call(\"_guiRelayout\",u,i.id+\".radialaxis.angle\",D):null!==z&&a.call(\"_guiRelayout\",u,i.id+\".radialaxis.range[\"+r+\"]\",z)}function q(t,e){if(0!==r){var n=b+t,a=_+e;D=Math.atan2(d-a,n-p),i.vangles&&(D=U(D,i.vangles)),D=F(D);var o=l(p,d)+s(-D);c[\"radial-axis\"].attr(\"transform\",o),c[\"radial-line\"].select(\"line\").attr(\"transform\",o);var 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f=n(a);this.distinctPositions=f.vals,1===f.vals.length&&r!==1/0?this.minDiff=r:this.minDiff=Math.min(f.minDiff,r);var h=(e.posAxis||{}).type;\"category\"!==h&&\"multicategory\"!==h||(this.minDiff=1),this.binWidth=this.minDiff,this.bins={}}i.prototype.put=function(t,e){var r=this.getLabel(t,e),n=this.bins[r]||0;return this.bins[r]=n+e,n},i.prototype.get=function(t,e){var r=this.getLabel(t,e);return this.bins[r]||0},i.prototype.getLabel=function(t,e){return(e<0&&this.sepNegVal?\"v\":\"^\")+(this.overlapNoMerge?t:Math.round(t/this.binWidth))}},16688:function(t,e,r){\"use strict\";var n=r(39898),i=r(7901),a=r(91424),o=r(71828),s=r(73972),l=r(72597).resizeText,u=r(1486),c=u.textfont,f=u.insidetextfont,h=u.outsidetextfont,p=r(69383);function d(t,e,r){a.pointStyle(t.selectAll(\"path\"),e,r),v(t,e,r)}function v(t,e,r){t.selectAll(\"text\").each((function(t){var i=n.select(this),s=o.ensureUniformFontSize(r,g(i,t,e,r));a.font(i,s)}))}function g(t,e,r,n){var 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n=r(7901),i=r(52075).hasColorscale,a=r(1586),o=r(71828).coercePattern;t.exports=function(t,e,r,s,l){var u=r(\"marker.color\",s),c=i(t,\"marker\");c&&a(t,e,l,r,{prefix:\"marker.\",cLetter:\"c\"}),r(\"marker.line.color\",n.defaultLine),i(t,\"marker.line\")&&a(t,e,l,r,{prefix:\"marker.line.\",cLetter:\"c\"}),r(\"marker.line.width\"),r(\"marker.opacity\"),o(r,\"marker.pattern\",u,c),r(\"selected.marker.color\"),r(\"unselected.marker.color\")}},72597:function(t,e,r){\"use strict\";var n=r(39898),i=r(71828);function a(t){return\"_\"+t+\"Text_minsize\"}t.exports={recordMinTextSize:function(t,e,r){if(r.uniformtext.mode){var n=a(t),i=r.uniformtext.minsize,o=e.scale*e.fontSize;e.hide=o<i,r[n]=r[n]||1/0,e.hide||(r[n]=Math.min(r[n],Math.max(o,i)))}},clearMinTextSize:function(t,e){e[a(t)]=void 0},resizeText:function(t,e,r){var a=t._fullLayout,o=a[\"_\"+r+\"Text_minsize\"];if(o){var 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r=t._fullLayout,o=e.subplot,l=r[o].radialaxis,u=r[o].angularaxis,c=l.makeCalcdata(e,\"r\"),f=u.makeCalcdata(e,\"theta\"),h=e._length,p=new Array(h),d=c,v=f,g=0;g<h;g++)p[g]={p:v[g],s:d[g]};function y(t){var r=e[t];void 0!==r&&(e[\"_\"+t]=Array.isArray(r)?u.makeCalcdata(e,t):u.d2c(r,e.thetaunit))}return\"linear\"===u.type&&(y(\"width\"),y(\"offset\")),n(e,\"marker\")&&i(t,e,{vals:e.marker.color,containerStr:\"marker\",cLetter:\"c\"}),n(e,\"marker.line\")&&i(t,e,{vals:e.marker.line.color,containerStr:\"marker.line\",cLetter:\"c\"}),a(p,e),s(p,e),p},crossTraceCalc:function(t,e,r){for(var n=t.calcdata,i=[],a=0;a<n.length;a++){var s=n[a],c=s[0].trace;!0===c.visible&&l(c,\"bar\")&&c.subplot===r&&i.push(s)}var f=u({},e.radialaxis,{_id:\"x\"}),h=e.angularaxis;o(t,h,f,i,{mode:e.barmode,norm:e.barnorm,gap:e.bargap,groupgap:e.bargroupgap})}}},6135:function(t,e,r){\"use strict\";var n=r(71828),i=r(22184).handleRThetaDefaults,a=r(98340),o=r(55023);t.exports=function(t,e,r,s){function l(r,i){return 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R,F,B,N,j,U,V=k+T,H=Boolean(C);if(\"positive\"===P?(M=w*(C?1:.5),R=V,S=R=k):\"negative\"===P?(M=R=k,S=w*(C?1:.5),F=V):(M=S=w,R=F=V),(E.boxpoints||E.points)&&v>0){var q=E.pointpos,G=E.jitter,Z=E.marker.size/2,Y=0;q+G>=0&&((Y=V*(q+G))>M?(H=!0,j=Z,B=Y):Y>R&&(j=Z,B=M)),Y<=M&&(B=M);var W=0;q-G<=0&&((W=-V*(q-G))>S?(H=!0,U=Z,N=W):W>F&&(U=Z,N=S)),W<=S&&(N=S)}else B=M,N=S;var X=new Array(u.length);for(l=0;l<u.length;l++)X[l]=u[l].pos;E._extremes[h]=n.findExtremes(o,X,{padded:H,vpadminus:N,vpadplus:B,vpadLinearized:!0,ppadminus:{x:U,y:j}[p],ppadplus:{x:j,y:U}[p]})}}}t.exports={crossTraceCalc:function(t,e){for(var r=t.calcdata,n=e.xaxis,i=e.yaxis,a=0;a<o.length;a++){for(var l=o[a],u=\"h\"===l?i:n,c=[],f=0;f<r.length;f++){var h=r[f],p=h[0].t,d=h[0].trace;!0!==d.visible||\"box\"!==d.type&&\"candlestick\"!==d.type||p.empty||(d.orientation||\"v\")!==l||d.xaxis!==n._id||d.yaxis!==i._id||c.push(f)}s(\"box\",t,c,u)}},setPositionOffset:s}},36411:function(t,e,r){\"use strict\";var 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b=t.selectAll(\"path.box\").data(\"violin\"!==r.type||r.box.visible?i.identity:[]);b.enter().append(\"path\").style(\"vector-effect\",o?\"none\":\"non-scaling-stroke\").attr(\"class\",\"box\"),b.exit().remove(),b.each((function(t){if(t.empty)return\"M0,0Z\";var e=f.c2l(t.pos+p,!0),a=f.l2p(e-s)+v,o=f.l2p(e+l)+v,b=h?(a+o)/2:f.l2p(e)+v,_=r.whiskerwidth,w=h?a*_+(1-_)*b:f.l2p(e-d)+v,T=h?o*_+(1-_)*b:f.l2p(e+d)+v,k=f.l2p(e-s*x)+v,A=f.l2p(e+l*x)+v,M=\"sd\"===r.sizemode,S=c.c2p(M?t.mean-t.sd:t.q1,!0),E=M?c.c2p(t.mean+t.sd,!0):c.c2p(t.q3,!0),L=i.constrain(M?c.c2p(t.mean,!0):c.c2p(t.med,!0),Math.min(S,E)+1,Math.max(S,E)-1),C=void 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t.forEach((function(t){t.t=n,t.trace=r})),t}:[]);f.enter().append(\"g\").attr(\"class\",\"points\"),f.exit().remove();var h=f.selectAll(\"path\").data((function(t){var e,n,a=t.pts2,o=Math.max((t.max-t.min)/10,t.q3-t.q1),s=1e-9*o,f=.01*o,h=[],p=0;if(r.jitter){if(0===o)for(p=1,h=new Array(a.length),e=0;e<a.length;e++)h[e]=1;else for(e=0;e<a.length;e++){var d=Math.max(0,e-5),v=a[d].v,g=Math.min(a.length-1,e+5),y=a[g].v;\"all\"!==c&&(a[e].v<t.lf?y=Math.min(y,t.lf):v=Math.max(v,t.uf));var m=Math.sqrt(f*(g-d)/(y-v+s))||0;m=i.constrain(Math.abs(m),0,1),h.push(m),p=Math.max(m,p)}n=2*r.jitter/(p||1)}for(e=0;e<a.length;e++){var x=a[e],b=x.v,_=r.jitter?n*h[e]*(i.pseudoRandom()-.5):0,w=t.pos+u+l*(r.pointpos+_);\"h\"===r.orientation?(x.y=w,x.x=b):(x.x=w,x.y=b),\"suspectedoutliers\"===c&&b<t.uo&&b>t.lo&&(x.so=!0)}return a}));h.enter().append(\"path\").classed(\"point\",!0),h.exit().remove(),h.call(a.translatePoints,o,s)}function l(t,e,r,a){var o,s,l=e.val,u=e.pos,c=!!u.rangebreaks,f=a.bPos,h=a.bPosPxOffset||0,p=r.boxmean||(r.meanline||{}).visible;Array.isArray(a.bdPos)?(o=a.bdPos[0],s=a.bdPos[1]):(o=a.bdPos,s=a.bdPos);var d=t.selectAll(\"path.mean\").data(\"box\"===r.type&&r.boxmean||\"violin\"===r.type&&r.box.visible&&r.meanline.visible?i.identity:[]);d.enter().append(\"path\").attr(\"class\",\"mean\").style({fill:\"none\",\"vector-effect\":\"non-scaling-stroke\"}),d.exit().remove(),d.each((function(t){var e=u.c2l(t.pos+f,!0),i=u.l2p(e-o)+h,a=u.l2p(e+s)+h,d=c?(i+a)/2:u.l2p(e)+h,v=l.c2p(t.mean,!0),g=l.c2p(t.mean-t.sd,!0),y=l.c2p(t.mean+t.sd,!0);\"h\"===r.orientation?n.select(this).attr(\"d\",\"M\"+v+\",\"+i+\"V\"+a+(\"sd\"===p?\"m0,0L\"+g+\",\"+d+\"L\"+v+\",\"+i+\"L\"+y+\",\"+d+\"Z\":\"\")):n.select(this).attr(\"d\",\"M\"+i+\",\"+v+\"H\"+a+(\"sd\"===p?\"m0,0L\"+d+\",\"+g+\"L\"+i+\",\"+v+\"L\"+d+\",\"+y+\"Z\":\"\"))}))}t.exports={plot:function(t,e,r,a){var u=t._context.staticPlot,c=e.xaxis,f=e.yaxis;i.makeTraceGroups(a,r,\"trace boxes\").each((function(t){var e,r,i=n.select(this),a=t[0],h=a.t,p=a.trace;h.wdPos=h.bdPos*p.whiskerwidth,!0!==p.visible||h.empty?i.remove():(\"h\"===p.orientation?(e=f,r=c):(e=c,r=f),o(i,{pos:e,val:r},p,h,u),s(i,{x:c,y:f},p,h),l(i,{pos:e,val:r},p,h))}))},plotBoxAndWhiskers:o,plotPoints:s,plotBoxMean:l}},24626:function(t){\"use strict\";t.exports=function(t,e){var r,n,i=t.cd,a=t.xaxis,o=t.yaxis,s=[];if(!1===e)for(r=0;r<i.length;r++)for(n=0;n<(i[r].pts||[]).length;n++)i[r].pts[n].selected=0;else for(r=0;r<i.length;r++)for(n=0;n<(i[r].pts||[]).length;n++){var l=i[r].pts[n],u=a.c2p(l.x),c=o.c2p(l.y);e.contains([u,c],null,l.i,t)?(s.push({pointNumber:l.i,x:a.c2d(l.x),y:o.c2d(l.y)}),l.selected=1):l.selected=0}return s}},58063:function(t,e,r){\"use strict\";var n=r(39898),i=r(7901),a=r(91424);t.exports={style:function(t,e,r){var o=r||n.select(t).selectAll(\"g.trace.boxes\");o.style(\"opacity\",(function(t){return 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t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})).attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"perpendicular\"===t.parcatsViewModel.arrangement?\"ns-resize\":\"move\"})),k(D),E.exit().remove(),S.append(\"text\").attr(\"class\",\"catlabel\").attr(\"pointer-events\",\"none\");var z=e._fullLayout.paper_bgcolor;M.select(\"text.catlabel\").attr(\"text-anchor\",(function(t){return d(t)?\"start\":\"end\"})).attr(\"alignment-baseline\",\"middle\").style(\"text-shadow\",f.makeTextShadow(z)).style(\"fill\",\"rgb(0, 0, 0)\").attr(\"x\",(function(t){return d(t)?t.width+5:-5})).attr(\"y\",(function(t){return t.height/2})).text((function(t){return t.model.categoryLabel})).each((function(t){u.font(n.select(this),t.parcatsViewModel.categorylabelfont),f.convertToTspans(n.select(this),e)})),S.append(\"text\").attr(\"class\",\"dimlabel\"),M.select(\"text.dimlabel\").attr(\"text-anchor\",\"middle\").attr(\"alignment-baseline\",\"baseline\").attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"ew-resize\"})).attr(\"x\",(function(t){return t.width/2})).attr(\"y\",-5).text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})).each((function(t){u.font(n.select(this),t.parcatsViewModel.labelfont)})),M.selectAll(\"rect.bandrect\").on(\"mouseover\",L).on(\"mouseout\",C),M.exit().remove(),A.call(n.behavior.drag().origin((function(t){return{x:t.x,y:0}})).on(\"dragstart\",P).on(\"drag\",O).on(\"dragend\",I)),h.each((function(t){t.traceSelection=n.select(this),t.pathSelection=n.select(this).selectAll(\"g.paths\").selectAll(\"path.path\"),t.dimensionSelection=n.select(this).selectAll(\"g.dimensions\").selectAll(\"g.dimension\")})),h.exit().remove()}function p(t){return t.key}function d(t){var e=t.parcatsViewModel.dimensions.length,r=t.parcatsViewModel.dimensions[e-1].model.dimensionInd;return t.model.dimensionInd===r}function v(t,e){return t.model.rawColor>e.model.rawColor?1:t.model.rawColor<e.model.rawColor?-1:0}function g(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){s.raiseToTop(this),w(n.select(this));var e=m(t),r=x(t);if(t.parcatsViewModel.graphDiv.emit(\"plotly_hover\",{points:e,event:n.event,constraints:r}),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\")){var i,a,l,u=n.mouse(this)[0],f=t.parcatsViewModel.graphDiv,h=t.parcatsViewModel.trace,p=f._fullLayout,d=p._paperdiv.node().getBoundingClientRect(),v=t.parcatsViewModel.graphDiv.getBoundingClientRect();for(l=0;l<t.leftXs.length-1;l++)if(t.leftXs[l]+t.dimWidths[l]-2<=u&&u<=t.leftXs[l+1]+2){var g=t.parcatsViewModel.dimensions[l],y=t.parcatsViewModel.dimensions[l+1];i=(g.x+g.width+y.x)/2,a=(t.topYs[l]+t.topYs[l+1]+t.height)/2;break}var b=t.parcatsViewModel.x+i,_=t.parcatsViewModel.y+a,T=c.mostReadable(t.model.color,[\"black\",\"white\"]),k=t.model.count,A=k/t.parcatsViewModel.model.count,M={countLabel:k,probabilityLabel:A.toFixed(3)},S=[];-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&S.push([\"Count:\",M.countLabel].join(\" \")),-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&S.push([\"P:\",M.probabilityLabel].join(\" \"));var E=S.join(\"<br>\"),L=n.mouse(f)[0];o.loneHover({trace:h,x:b-d.left+v.left,y:_-d.top+v.top,text:E,color:t.model.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:10,fontColor:T,idealAlign:L<b?\"right\":\"left\",hovertemplate:(h.line||{}).hovertemplate,hovertemplateLabels:M,eventData:[{data:h._input,fullData:h,count:k,probability:A}]},{container:p._hoverlayer.node(),outerContainer:p._paper.node(),gd:f})}}}function y(t){if(!t.parcatsViewModel.dragDimension&&(_(n.select(this)),o.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()),t.parcatsViewModel.pathSelection.sort(v),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\"))){var e=m(t),r=x(t);t.parcatsViewModel.graphDiv.emit(\"plotly_unhover\",{points:e,event:n.event,constraints:r})}}function m(t){for(var e=[],r=D(t.parcatsViewModel),n=0;n<t.model.valueInds.length;n++){var i=t.model.valueInds[n];e.push({curveNumber:r,pointNumber:i})}return e}function x(t){for(var e={},r=t.parcatsViewModel.model.dimensions,n=0;n<r.length;n++){var i=r[n],a=i.categories[t.model.categoryInds[n]];e[i.containerInd]=a.categoryValue}return void 0!==t.model.rawColor&&(e.color=t.model.rawColor),e}function b(t){if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){var e=m(t),r=x(t);t.parcatsViewModel.graphDiv.emit(\"plotly_click\",{points:e,event:n.event,constraints:r})}}function _(t){t.attr(\"fill\",(function(t){return t.model.color})).attr(\"fill-opacity\",.6).attr(\"stroke\",\"lightgray\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1)}function w(t){t.attr(\"fill-opacity\",.8).attr(\"stroke\",(function(t){return c.mostReadable(t.model.color,[\"black\",\"white\"])})).attr(\"stroke-width\",.3)}function T(t){t.select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",1).attr(\"stroke-opacity\",1)}function k(t){t.attr(\"stroke\",\"black\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1).attr(\"fill-opacity\",1)}function A(t){var e=t.parcatsViewModel.pathSelection,r=t.categoryViewModel.model.dimensionInd,n=t.categoryViewModel.model.categoryInd;return e.filter((function(e){return e.model.categoryInds[r]===n&&e.model.color===t.color}))}function M(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=n.select(t.parentNode).selectAll(\"rect.bandrect\"),l=[];s.each((function(t){A(t).each((function(t){Array.prototype.push.apply(l,m(t))}))}));var u={};u[a.dimensionInd]=a.categoryValue,o.emit(e,{points:l,event:r,constraints:u})}function S(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=A(i),l=[];s.each((function(t){Array.prototype.push.apply(l,m(t))}));var u={};u[a.dimensionInd]=a.categoryValue,void 0!==i.rawColor&&(u.color=i.rawColor),o.emit(e,{points:l,event:r,constraints:u})}function E(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=n.select(r.parentNode).select(\"rect.catrect\"),u=l.node().getBoundingClientRect(),c=l.datum(),f=c.parcatsViewModel,h=f.model.dimensions[c.model.dimensionInd],p=f.trace,d=u.top+u.height/2;f.dimensions.length>1&&h.displayInd===f.dimensions.length-1?(i=u.left,a=\"left\"):(i=u.left+u.width,a=\"right\");var v=c.model.count,g=c.model.categoryLabel,y=v/c.parcatsViewModel.model.count,m={countLabel:v,categoryLabel:g,probabilityLabel:y.toFixed(3)},x=[];-1!==c.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&x.push([\"Count:\",m.countLabel].join(\" \")),-1!==c.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&x.push([\"P(\"+m.categoryLabel+\"):\",m.probabilityLabel].join(\" \"));var b=x.join(\"<br>\");return{trace:p,x:o*(i-e.left),y:s*(d-e.top),text:b,color:\"lightgray\",borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:12,fontColor:\"black\",idealAlign:a,hovertemplate:p.hovertemplate,hovertemplateLabels:m,eventData:[{data:p._input,fullData:p,count:v,category:g,probability:y}]}}function L(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){if(n.mouse(this)[1]<-1)return;var e,r=t.parcatsViewModel.graphDiv,i=r._fullLayout,a=i._paperdiv.node().getBoundingClientRect(),l=t.parcatsViewModel.hoveron,u=this;\"color\"===l?(function(t){var e=n.select(t).datum(),r=A(e);w(r),r.each((function(){s.raiseToTop(this)})),n.select(t.parentNode).selectAll(\"rect.bandrect\").filter((function(t){return t.color===e.color})).each((function(){s.raiseToTop(this),n.select(this).attr(\"stroke\",\"black\").attr(\"stroke-width\",1.5)}))}(u),S(u,\"plotly_hover\",n.event)):(function(t){n.select(t.parentNode).selectAll(\"rect.bandrect\").each((function(t){var e=A(t);w(e),e.each((function(){s.raiseToTop(this)}))})),n.select(t.parentNode).select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",2.5)}(u),M(u,\"plotly_hover\",n.event)),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\")&&(\"category\"===l?e=E(r,a,u):\"color\"===l?e=function(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=r.getBoundingClientRect(),u=n.select(r).datum(),f=u.categoryViewModel,h=f.parcatsViewModel,p=h.model.dimensions[f.model.dimensionInd],d=h.trace,v=l.y+l.height/2;h.dimensions.length>1&&p.displayInd===h.dimensions.length-1?(i=l.left,a=\"left\"):(i=l.left+l.width,a=\"right\");var g=f.model.categoryLabel,y=u.parcatsViewModel.model.count,m=0;u.categoryViewModel.bands.forEach((function(t){t.color===u.color&&(m+=t.count)}));var x=f.model.count,b=0;h.pathSelection.each((function(t){t.model.color===u.color&&(b+=t.model.count)}));var _=m/y,w=m/b,T=m/x,k={countLabel:y,categoryLabel:g,probabilityLabel:_.toFixed(3)},A=[];-1!==f.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&A.push([\"Count:\",k.countLabel].join(\" \")),-1!==f.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&(A.push(\"P(color ∩ \"+g+\"): \"+k.probabilityLabel),A.push(\"P(\"+g+\" | color): \"+w.toFixed(3)),A.push(\"P(color | \"+g+\"): \"+T.toFixed(3)));var M=A.join(\"<br>\"),S=c.mostReadable(u.color,[\"black\",\"white\"]);return{trace:d,x:o*(i-e.left),y:s*(v-e.top),text:M,color:u.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontColor:S,fontSize:10,idealAlign:a,hovertemplate:d.hovertemplate,hovertemplateLabels:k,eventData:[{data:d._input,fullData:d,category:g,count:y,probability:_,categorycount:x,colorcount:b,bandcolorcount:m}]}}(r,a,u):\"dimension\"===l&&(e=function(t,e,r){var i=[];return n.select(r.parentNode.parentNode).selectAll(\"g.category\").select(\"rect.catrect\").each((function(){i.push(E(t,e,this))})),i}(r,a,u)),e&&o.loneHover(e,{container:i._hoverlayer.node(),outerContainer:i._paper.node(),gd:r}))}}function C(t){var e=t.parcatsViewModel;e.dragDimension||(_(e.pathSelection),T(e.dimensionSelection.selectAll(\"g.category\")),k(e.dimensionSelection.selectAll(\"g.category\").selectAll(\"rect.bandrect\")),o.loneUnhover(e.graphDiv._fullLayout._hoverlayer.node()),e.pathSelection.sort(v),-1!==e.hoverinfoItems.indexOf(\"skip\"))||(\"color\"===t.parcatsViewModel.hoveron?S(this,\"plotly_unhover\",n.event):M(this,\"plotly_unhover\",n.event))}function P(t){\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragDimensionDisplayInd=t.model.displayInd,t.initialDragDimensionDisplayInds=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),t.dragHasMoved=!1,t.dragCategoryDisplayInd=null,n.select(this).selectAll(\"g.category\").select(\"rect.catrect\").each((function(e){var r=n.mouse(this)[0],i=n.mouse(this)[1];-2<=r&&r<=e.width+2&&-2<=i&&i<=e.height+2&&(t.dragCategoryDisplayInd=e.model.displayInd,t.initialDragCategoryDisplayInds=t.model.categories.map((function(t){return t.displayInd})),e.model.dragY=e.y,s.raiseToTop(this.parentNode),n.select(this.parentNode).selectAll(\"rect.bandrect\").each((function(e){e.y<i&&i<=e.y+e.height&&(t.potentialClickBand=this)})))})),t.parcatsViewModel.dragDimension=t,o.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()))}function O(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragHasMoved=!0,null!==t.dragDimensionDisplayInd)){var e=t.dragDimensionDisplayInd,r=e-1,i=e+1,a=t.parcatsViewModel.dimensions[e];if(null!==t.dragCategoryDisplayInd){var o=a.categories[t.dragCategoryDisplayInd];o.model.dragY+=n.event.dy;var s=o.model.dragY,l=o.model.displayInd,u=a.categories,c=u[l-1],f=u[l+1];void 0!==c&&s<c.y+c.height/2&&(o.model.displayInd=c.model.displayInd,c.model.displayInd=l),void 0!==f&&s+o.height>f.y+f.height/2&&(o.model.displayInd=f.model.displayInd,f.model.displayInd=l),t.dragCategoryDisplayInd=o.model.displayInd}if(null===t.dragCategoryDisplayInd||\"freeform\"===t.parcatsViewModel.arrangement){a.model.dragX=n.event.x;var h=t.parcatsViewModel.dimensions[r],p=t.parcatsViewModel.dimensions[i];void 0!==h&&a.model.dragX<h.x+h.width&&(a.model.displayInd=h.model.displayInd,h.model.displayInd=e),void 0!==p&&a.model.dragX+a.width>p.x&&(a.model.displayInd=p.model.displayInd,p.model.displayInd=t.dragDimensionDisplayInd),t.dragDimensionDisplayInd=a.model.displayInd}j(t.parcatsViewModel),N(t.parcatsViewModel),R(t.parcatsViewModel),z(t.parcatsViewModel)}}function I(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&null!==t.dragDimensionDisplayInd){n.select(this).selectAll(\"text\").attr(\"font-weight\",\"normal\");var e={},r=D(t.parcatsViewModel),i=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),o=t.initialDragDimensionDisplayInds.some((function(t,e){return t!==i[e]}));o&&i.forEach((function(r,n){var i=t.parcatsViewModel.model.dimensions[n].containerInd;e[\"dimensions[\"+i+\"].displayindex\"]=r}));var s=!1;if(null!==t.dragCategoryDisplayInd){var l=t.model.categories.map((function(t){return t.displayInd}));if(s=t.initialDragCategoryDisplayInds.some((function(t,e){return t!==l[e]}))){var u=t.model.categories.slice().sort((function(t,e){return t.displayInd-e.displayInd})),c=u.map((function(t){return t.categoryValue})),f=u.map((function(t){return t.categoryLabel}));e[\"dimensions[\"+t.model.containerInd+\"].categoryarray\"]=[c],e[\"dimensions[\"+t.model.containerInd+\"].ticktext\"]=[f],e[\"dimensions[\"+t.model.containerInd+\"].categoryorder\"]=\"array\"}}-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")&&!t.dragHasMoved&&t.potentialClickBand&&(\"color\"===t.parcatsViewModel.hoveron?S(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent):M(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent)),t.model.dragX=null,null!==t.dragCategoryDisplayInd&&(t.parcatsViewModel.dimensions[t.dragDimensionDisplayInd].categories[t.dragCategoryDisplayInd].model.dragY=null,t.dragCategoryDisplayInd=null),t.dragDimensionDisplayInd=null,t.parcatsViewModel.dragDimension=null,t.dragHasMoved=null,t.potentialClickBand=null,j(t.parcatsViewModel),N(t.parcatsViewModel),n.transition().duration(300).ease(\"cubic-in-out\").each((function(){R(t.parcatsViewModel,!0),z(t.parcatsViewModel,!0)})).each(\"end\",(function(){(o||s)&&a.restyle(t.parcatsViewModel.graphDiv,e,[r])}))}}function D(t){for(var e,r=t.graphDiv._fullData,n=0;n<r.length;n++)if(t.key===r[n].uid){e=n;break}return e}function z(t,e){var r;void 0===e&&(e=!1),t.pathSelection.data((function(t){return t.paths}),p),(r=t.pathSelection,e?r.transition():r).attr(\"d\",(function(t){return t.svgD}))}function R(t,e){function r(t){return e?t.transition():t}void 0===e&&(e=!1),t.dimensionSelection.data((function(t){return t.dimensions}),p);var i=t.dimensionSelection.selectAll(\"g.category\").data((function(t){return t.categories}),p);r(t.dimensionSelection).attr(\"transform\",(function(t){return l(t.x,0)})),r(i).attr(\"transform\",(function(t){return l(0,t.y)})),i.select(\".dimlabel\").text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})),i.select(\".catlabel\").attr(\"text-anchor\",(function(t){return d(t)?\"start\":\"end\"})).attr(\"x\",(function(t){return d(t)?t.width+5:-5})).each((function(t){var e,r;d(t)?(e=t.width+5,r=\"start\"):(e=-5,r=\"end\"),n.select(this).selectAll(\"tspan\").attr(\"x\",e).attr(\"text-anchor\",r)}));var a=i.selectAll(\"rect.bandrect\").data((function(t){return t.bands}),p),o=a.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"cursor\",\"move\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.color})).attr(\"fill-opacity\",0);a.attr(\"fill\",(function(t){return t.color})).attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})),k(o),a.each((function(){s.raiseToTop(this)})),a.exit().remove()}function F(t,e,r){var n,i=r[0],a=e.margin||{l:80,r:80,t:100,b:80},o=i.trace,s=o.domain,l=e.width,u=e.height,c=Math.floor(l*(s.x[1]-s.x[0])),f=Math.floor(u*(s.y[1]-s.y[0])),h=s.x[0]*l+a.l,p=e.height-s.y[1]*e.height+a.t,d=o.line.shape;n=\"all\"===o.hoverinfo?[\"count\",\"probability\"]:(o.hoverinfo||\"\").split(\"+\");var v={trace:o,key:o.uid,model:i,x:h,y:p,width:c,height:f,hoveron:o.hoveron,hoverinfoItems:n,arrangement:o.arrangement,bundlecolors:o.bundlecolors,sortpaths:o.sortpaths,labelfont:o.labelfont,categorylabelfont:o.tickfont,pathShape:d,dragDimension:null,margin:a,paths:[],dimensions:[],graphDiv:t,traceSelection:null,pathSelection:null,dimensionSelection:null};return i.dimensions&&(j(v),N(v)),v}function B(t,e,r,n,a){var o,s,l=[],u=[];for(s=0;s<r.length-1;s++)o=i(r[s]+t[s],t[s+1]),l.push(o(a)),u.push(o(1-a));var c=\"M \"+t[0]+\",\"+e[0];for(c+=\"l\"+r[0]+\",0 \",s=1;s<r.length;s++)c+=\"C\"+l[s-1]+\",\"+e[s-1]+\" \"+u[s-1]+\",\"+e[s]+\" \"+t[s]+\",\"+e[s],c+=\"l\"+r[s]+\",0 \";for(c+=\"l0,\"+n+\" \",c+=\"l -\"+r[r.length-1]+\",0 \",s=r.length-2;s>=0;s--)c+=\"C\"+u[s]+\",\"+(e[s+1]+n)+\" \"+l[s]+\",\"+(e[s]+n)+\" \"+(t[s]+r[s])+\",\"+(e[s]+n),c+=\"l-\"+r[s]+\",0 \";return c+\"Z\"}function N(t){var e=t.dimensions,r=t.model,n=e.map((function(t){return t.categories.map((function(t){return t.y}))})),i=t.model.dimensions.map((function(t){return t.categories.map((function(t){return t.displayInd}))})),a=t.model.dimensions.map((function(t){return t.displayInd})),o=t.dimensions.map((function(t){return t.model.dimensionInd})),s=e.map((function(t){return t.x})),l=e.map((function(t){return t.width})),u=[];for(var c in r.paths)r.paths.hasOwnProperty(c)&&u.push(r.paths[c]);function f(t){var e=t.categoryInds.map((function(t,e){return i[e][t]}));return o.map((function(t){return e[t]}))}u.sort((function(e,r){var n=f(e),i=f(r);return\"backward\"===t.sortpaths&&(n.reverse(),i.reverse()),n.push(e.valueInds[0]),i.push(r.valueInds[0]),t.bundlecolors&&(n.unshift(e.rawColor),i.unshift(r.rawColor)),n<i?-1:n>i?1:0}));for(var h=new Array(u.length),p=e[0].model.count,d=e[0].categories.map((function(t){return t.height})).reduce((function(t,e){return t+e})),v=0;v<u.length;v++){var g,y=u[v];g=p>0?d*(y.count/p):0;for(var m,x=new Array(n.length),b=0;b<y.categoryInds.length;b++){var 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n=r(50693),i=r(13838),a=r(41940),o=r(27670).Y,s=r(1426).extendFlat,l=r(44467).templatedArray;t.exports={domain:o({name:\"parcoords\",trace:!0,editType:\"plot\"}),labelangle:{valType:\"angle\",dflt:0,editType:\"plot\"},labelside:{valType:\"enumerated\",values:[\"top\",\"bottom\"],dflt:\"top\",editType:\"plot\"},labelfont:a({editType:\"plot\"}),tickfont:a({editType:\"plot\"}),rangefont:a({editType:\"plot\"}),dimensions:l(\"dimension\",{label:{valType:\"string\",editType:\"plot\"},tickvals:s({},i.tickvals,{editType:\"plot\"}),ticktext:s({},i.ticktext,{editType:\"plot\"}),tickformat:s({},i.tickformat,{editType:\"plot\"}),visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},range:{valType:\"info_array\",items:[{valType:\"number\",editType:\"plot\"},{valType:\"number\",editType:\"plot\"}],editType:\"plot\"},constraintrange:{valType:\"info_array\",freeLength:!0,dimensions:\"1-2\",items:[{valType:\"any\",editType:\"plot\"},{valType:\"any\",editType:\"plot\"}],editType:\"plot\"},multiselect:{valType:\"boolean\",dflt:!0,editType:\"plot\"},values:{valType:\"data_array\",editType:\"calc\"},editType:\"calc\"}),line:s({editType:\"calc\"},n(\"line\",{colorscaleDflt:\"Viridis\",autoColorDflt:!1,editTypeOverride:\"calc\"})),unselected:{line:{color:{valType:\"color\",dflt:\"#7f7f7f\",editType:\"plot\"},opacity:{valType:\"number\",min:0,max:1,dflt:\"auto\",editType:\"plot\"},editType:\"plot\"},editType:\"plot\"}}},57920:function(t,e,r){\"use 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s(\"line.colorscale\"),a(t,e,o,s,{prefix:\"line.\",cLetter:\"c\"}),l.length;e.line.color=r}return 1/0}(t,e,r,l,c);o(e,l,c),Array.isArray(v)&&v.length||(e.visible=!1),h(e,v,\"values\",g);var y={family:l.font.family,size:Math.round(l.font.size/1.2),color:l.font.color};n.coerceFont(c,\"labelfont\",y),n.coerceFont(c,\"tickfont\",y),n.coerceFont(c,\"rangefont\",y),c(\"labelangle\"),c(\"labelside\"),c(\"unselected.line.color\"),c(\"unselected.line.opacity\")}},1602:function(t,e,r){\"use strict\";var n=r(71828).isTypedArray;e.convertTypedArray=function(t){return n(t)?Array.prototype.slice.call(t):t},e.isOrdinal=function(t){return!!t.tickvals},e.isVisible=function(t){return t.visible||!(\"visible\"in t)}},67618:function(t,e,r){\"use strict\";var n=r(71791);n.plot=r(21341),t.exports=n},83398:function(t,e,r){\"use strict\";var n=r(56068),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nattribute vec4 p01_04, p05_08, p09_12, p13_16,\\n               p17_20, p21_24, p25_28, p29_32,\\n               p33_36, p37_40, p41_44, p45_48,\\n               p49_52, p53_56, p57_60, colors;\\n\\nuniform mat4 dim0A, dim1A, dim0B, dim1B, dim0C, dim1C, dim0D, dim1D,\\n             loA, hiA, loB, hiB, loC, hiC, loD, hiD;\\n\\nuniform vec2 resolution, viewBoxPos, viewBoxSize;\\nuniform float maskHeight;\\nuniform float drwLayer; // 0: context, 1: focus, 2: pick\\nuniform vec4 contextColor;\\nuniform sampler2D maskTexture, palette;\\n\\nbool isPick    = (drwLayer > 1.5);\\nbool isContext = (drwLayer < 0.5);\\n\\nconst vec4 ZEROS = vec4(0.0, 0.0, 0.0, 0.0);\\nconst vec4 UNITS = vec4(1.0, 1.0, 1.0, 1.0);\\n\\nfloat val(mat4 p, mat4 v) {\\n    return dot(matrixCompMult(p, v) * UNITS, UNITS);\\n}\\n\\nfloat axisY(float ratio, mat4 A, mat4 B, mat4 C, mat4 D) {\\n    float y1 = val(A, dim0A) + val(B, dim0B) + val(C, dim0C) + val(D, dim0D);\\n    float y2 = val(A, dim1A) + val(B, dim1B) + val(C, dim1C) + val(D, dim1D);\\n    return y1 * (1.0 - ratio) + y2 * ratio;\\n}\\n\\nint iMod(int a, int b) {\\n    return a - b * (a / b);\\n}\\n\\nbool fOutside(float p, float lo, float hi) {\\n    return (lo < hi) && (lo > p || p > hi);\\n}\\n\\nbool vOutside(vec4 p, vec4 lo, vec4 hi) {\\n    return (\\n        fOutside(p[0], lo[0], hi[0]) ||\\n        fOutside(p[1], lo[1], hi[1]) ||\\n        fOutside(p[2], lo[2], hi[2]) ||\\n        fOutside(p[3], lo[3], hi[3])\\n    );\\n}\\n\\nbool mOutside(mat4 p, mat4 lo, mat4 hi) {\\n    return (\\n        vOutside(p[0], lo[0], hi[0]) ||\\n        vOutside(p[1], lo[1], hi[1]) ||\\n        vOutside(p[2], lo[2], hi[2]) ||\\n        vOutside(p[3], lo[3], hi[3])\\n    );\\n}\\n\\nbool outsideBoundingBox(mat4 A, mat4 B, mat4 C, mat4 D) {\\n    return mOutside(A, loA, hiA) ||\\n           mOutside(B, loB, hiB) ||\\n           mOutside(C, loC, hiC) ||\\n           mOutside(D, loD, hiD);\\n}\\n\\nbool outsideRasterMask(mat4 A, mat4 B, mat4 C, mat4 D) {\\n    mat4 pnts[4];\\n    pnts[0] = A;\\n    pnts[1] = B;\\n    pnts[2] = C;\\n    pnts[3] = D;\\n\\n    for(int i = 0; i < 4; ++i) {\\n        for(int j = 0; j < 4; ++j) {\\n            for(int k = 0; k < 4; ++k) {\\n                if(0 == iMod(\\n                    int(255.0 * texture2D(maskTexture,\\n                        vec2(\\n                            (float(i * 2 + j / 2) + 0.5) / 8.0,\\n                            (pnts[i][j][k] * (maskHeight - 1.0) + 1.0) / maskHeight\\n                        ))[3]\\n                    ) / int(pow(2.0, float(iMod(j * 4 + k, 8)))),\\n                    2\\n                )) return true;\\n            }\\n        }\\n    }\\n    return false;\\n}\\n\\nvec4 position(bool isContext, float v, mat4 A, mat4 B, mat4 C, mat4 D) {\\n    float x = 0.5 * sign(v) + 0.5;\\n    float y = axisY(x, A, B, C, D);\\n    float z = 1.0 - abs(v);\\n\\n    z += isContext ? 0.0 : 2.0 * float(\\n        outsideBoundingBox(A, B, C, D) ||\\n        outsideRasterMask(A, B, C, D)\\n    );\\n\\n    return vec4(\\n        2.0 * (vec2(x, y) * viewBoxSize + viewBoxPos) / resolution - 1.0,\\n        z,\\n        1.0\\n    );\\n}\\n\\nvoid main() {\\n    mat4 A = mat4(p01_04, p05_08, p09_12, p13_16);\\n    mat4 B = mat4(p17_20, p21_24, p25_28, p29_32);\\n    mat4 C = mat4(p33_36, p37_40, p41_44, p45_48);\\n    mat4 D = mat4(p49_52, p53_56, p57_60, ZEROS);\\n\\n    float v = colors[3];\\n\\n    gl_Position = position(isContext, v, A, B, C, D);\\n\\n    fragColor =\\n        isContext ? vec4(contextColor) :\\n        isPick ? vec4(colors.rgb, 1.0) : texture2D(palette, vec2(abs(v), 0.5));\\n}\\n\"]),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n    gl_FragColor = fragColor;\\n}\\n\"]),o=r(25706).maxDimensionCount,s=r(71828),l=1e-6,u=new Uint8Array(4),c=new Uint8Array(4),f={shape:[256,1],format:\"rgba\",type:\"uint8\",mag:\"nearest\",min:\"nearest\"};function h(t,e,r,n,i){var a=t._gl;a.enable(a.SCISSOR_TEST),a.scissor(e,r,n,i),t.clear({color:[0,0,0,0],depth:1})}function p(t,e,r,n,i,a){var o=a.key;r.drawCompleted||(function(t){t.read({x:0,y:0,width:1,height:1,data:u})}(t),r.drawCompleted=!0),function s(l){var u=Math.min(n,i-l*n);0===l&&(window.cancelAnimationFrame(r.currentRafs[o]),delete r.currentRafs[o],h(t,a.scissorX,a.scissorY,a.scissorWidth,a.viewBoxSize[1])),r.clearOnly||(a.count=2*u,a.offset=2*l*n,e(a),l*n+u<i&&(r.currentRafs[o]=window.requestAnimationFrame((function(){s(l+1)}))),r.drawCompleted=!1)}(0)}function d(t,e){for(var r=new Array(256),n=0;n<256;n++)r[n]=t(n/255).concat(e);return r}function v(t,e){return(t>>>8*e)%256/255}function g(t,e,r){for(var n=new Array(8*e),i=0,a=0;a<e;a++)for(var o=0;o<2;o++)for(var s=0;s<4;s++){var l=4*t+s,u=r[64*a+l];63===l&&0===o&&(u*=-1),n[i++]=u}return n}function y(t){var e=\"0\"+t;return e.substr(e.length-2)}function m(t){return t<o?\"p\"+y(t+1)+\"_\"+y(t+4):\"colors\"}function x(t,e,r,n,i,a,o,l,u,c,f,h,p,d){for(var v=[[],[]],g=0;g<64;g++)v[0][g]=g===i?1:0,v[1][g]=g===a?1:0;o*=d,l*=d,u*=d,c*=d;var y=t.lines.canvasOverdrag*d,m=t.domain,x=t.canvasWidth*d,b=t.canvasHeight*d,_=t.pad.l*d,w=t.pad.b*d,T=t.layoutHeight*d,k=t.layoutWidth*d,A=t.deselectedLines.color,M=t.deselectedLines.opacity;return s.extendFlat({key:f,resolution:[x,b],viewBoxPos:[o+y,l],viewBoxSize:[u,c],i0:i,i1:a,dim0A:v[0].slice(0,16),dim0B:v[0].slice(16,32),dim0C:v[0].slice(32,48),dim0D:v[0].slice(48,64),dim1A:v[1].slice(0,16),dim1B:v[1].slice(16,32),dim1C:v[1].slice(32,48),dim1D:v[1].slice(48,64),drwLayer:h,contextColor:[A[0]/255,A[1]/255,A[2]/255,\"auto\"!==M?A[3]*M:Math.max(1/255,Math.pow(1/t.lines.color.length,1/3))],scissorX:(n===e?0:o+y)+(_-y)+k*m.x[0],scissorWidth:(n===r?x-o+y:u+.5)+(n===e?o+y:0),scissorY:l+w+T*m.y[0],scissorHeight:c,viewportX:_-y+k*m.x[0],viewportY:w+T*m.y[0],viewportWidth:x,viewportHeight:b},p)}function b(t){var e=2047,r=Math.max(0,Math.floor(t[0]*e),0),n=Math.min(e,Math.ceil(t[1]*e),e);return[Math.min(r,n),Math.max(r,n)]}t.exports=function(t,e){var r,n,u,y,_,w=e.context,T=e.pick,k=e.regl,A=k._gl,M=A.getParameter(A.ALIASED_LINE_WIDTH_RANGE),S=Math.max(M[0],Math.min(M[1],e.viewModel.plotGlPixelRatio)),E={currentRafs:{},drawCompleted:!0,clearOnly:!1},L=function(t){for(var e={},r=0;r<=o;r+=4)e[m(r)]=t.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array(0)});return e}(k),C=k.texture(f),P=[];I(e);var O=k({profile:!1,blend:{enable:w,func:{srcRGB:\"src alpha\",dstRGB:\"one minus src 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I(t){r=t.model,n=t.viewModel,u=n.dimensions.slice(),y=u[0]?u[0].values.length:0;var e=r.lines,i=T?e.color.map((function(t,r){return r/e.color.length})):e.color,a=function(t,e,r){for(var n,i=new Array(t*(o+4)),a=0,s=0;s<t;s++){for(var u=0;u<o;u++)i[a++]=u<e.length?e[u].paddedUnitValues[s]:.5;i[a++]=v(s,2),i[a++]=v(s,1),i[a++]=v(s,0),i[a++]=(n=r[s],Math.max(l,Math.min(.999999,n)))}return i}(y,u,i);!function(t,e,r){for(var n=0;n<=o;n+=4)t[m(n)](g(n/4,e,r))}(L,y,a),w||T||(C=k.texture(s.extendFlat({data:d(r.unitToColor,255)},f)))}return{render:function(t,e,n){var i,a,o,s=t.length,l=1/0,c=-1/0;for(i=0;i<s;i++)t[i].dim0.canvasX<l&&(l=t[i].dim0.canvasX,a=i),t[i].dim1.canvasX>c&&(c=t[i].dim1.canvasX,o=i);0===s&&h(k,0,0,r.canvasWidth,r.canvasHeight);var f=function(t){var e,r,n,i=[[],[]];for(n=0;n<64;n++){var a=!t&&n<u.length?u[n].brush.filter.getBounds():[-1/0,1/0];i[0][n]=a[0],i[1][n]=a[1]}var o=new Array(16384);for(e=0;e<16384;e++)o[e]=255;if(!t)for(e=0;e<u.length;e++){var s=e%8,l=(e-s)/8,c=Math.pow(2,s),f=u[e].brush.filter.get();if(!(f.length<2)){var h=b(f[0])[1];for(r=1;r<f.length;r++){var p=b(f[r]);for(n=h+1;n<p[0];n++)o[8*n+l]&=~c;h=Math.max(h,p[1])}}}var d={shape:[8,2048],format:\"alpha\",type:\"uint8\",mag:\"nearest\",min:\"nearest\",data:o};return _?_(d):_=k.texture(d),{maskTexture:_,maskHeight:2048,loA:i[0].slice(0,16),loB:i[0].slice(16,32),loC:i[0].slice(32,48),loD:i[0].slice(48,64),hiA:i[1].slice(0,16),hiB:i[1].slice(16,32),hiC:i[1].slice(32,48),hiD:i[1].slice(48,64)}}(w);for(i=0;i<s;i++){var d=t[i],v=d.dim0.crossfilterDimensionIndex,g=d.dim1.crossfilterDimensionIndex,m=d.canvasX,A=d.canvasY,M=m+d.panelSizeX,S=d.plotGlPixelRatio;if(e||!P[v]||P[v][0]!==m||P[v][1]!==M){P[v]=[m,M];var L=x(r,a,o,i,v,g,m,A,d.panelSizeX,d.panelSizeY,d.dim0.crossfilterDimensionIndex,w?0:T?2:1,f,S);E.clearOnly=n;var C=e?r.lines.blockLineCount:y;p(k,O,E,C,y,L)}}},readPixel:function(t,e){return k.read({x:t,y:e,width:1,height:1,data:c}),c},readPixels:function(t,e,r,n){var i=new Uint8Array(4*r*n);return k.read({x:t,y:e,width:r,height:n,data:i}),i},destroy:function(){for(var e in t.style[\"pointer-events\"]=\"none\",C.destroy(),_&&_.destroy(),L)L[e].destroy()},update:I}}},94397:function(t){\"use strict\";t.exports=function(t,e,r,n){var i,a;for(n||(n=1/0),i=0;i<e.length;i++)(a=e[i]).visible&&(n=Math.min(n,a[r].length));for(n===1/0&&(n=0),t._length=n,i=0;i<e.length;i++)(a=e[i]).visible&&(a._length=n);return n}},17171:function(t,e,r){\"use strict\";var n=r(39898),i=r(71828),a=i.numberFormat,o=r(36652),s=r(89298),l=i.strRotate,u=i.strTranslate,c=r(63893),f=r(91424),h=r(21081),p=r(28984),d=p.keyFun,v=p.repeat,g=p.unwrap,y=r(1602),m=r(25706),x=r(57920),b=r(83398);function _(t,e,r){return i.aggNums(t,null,e,r)}function w(t,e){return k(_(Math.min,t,e),_(Math.max,t,e))}function T(t){var e=t.range;return e?k(e[0],e[1]):w(t.values,t._length)}function k(t,e){return!isNaN(t)&&isFinite(t)||(t=0),!isNaN(e)&&isFinite(e)||(e=0),t===e&&(0===t?(t-=1,e+=1):(t*=.9,e*=1.1)),[t,e]}function A(t,e,r,i,o){var s,l,u=T(r);return i?n.scale.ordinal().domain(i.map((s=a(r.tickformat),l=o,l?function(t,e){var r=l[e];return null==r?s(t):r}:s))).range(i.map((function(r){var n=(r-u[0])/(u[1]-u[0]);return t-e+n*(2*e-t)}))):n.scale.linear().domain(u).range([t-e,e])}function M(t){if(t.tickvals){var e=T(t);return n.scale.ordinal().domain(t.tickvals).range(t.tickvals.map((function(t){return(t-e[0])/(e[1]-e[0])})))}}function S(t){var e=t.map((function(t){return t[0]})),r=t.map((function(t){var e=o(t[1]);return n.rgb(\"rgb(\"+e[0]+\",\"+e[1]+\",\"+e[2]+\")\")})),i=\"rgb\".split(\"\").map((function(t){return n.scale.linear().clamp(!0).domain(e).range(r.map((i=t,function(t){return t[i]})));var i}));return function(t){return i.map((function(e){return e(t)}))}}function E(t){return t.dimensions.some((function(t){return t.brush.filterSpecified}))}function L(t,e,r){var a=g(e),s=a.trace,l=y.convertTypedArray(a.lineColor),u=s.line,c={color:o(s.unselected.line.color),opacity:s.unselected.line.opacity},f=h.extractOpts(u),p=f.reversescale?h.flipScale(a.cscale):a.cscale,d=s.domain,v=s.dimensions,x=t.width,b=s.labelangle,_=s.labelside,w=s.labelfont,k=s.tickfont,A=s.rangefont,M=i.extendDeepNoArrays({},u,{color:l.map(n.scale.linear().domain(T({values:l,range:[f.min,f.max],_length:s._length}))),blockLineCount:m.blockLineCount,canvasOverdrag:m.overdrag*m.canvasPixelRatio}),E=Math.floor(x*(d.x[1]-d.x[0])),L=Math.floor(t.height*(d.y[1]-d.y[0])),C=t.margin||{l:80,r:80,t:100,b:80},P=E,O=L;return{key:r,colCount:v.filter(y.isVisible).length,dimensions:v,tickDistance:m.tickDistance,unitToColor:S(p),lines:M,deselectedLines:c,labelAngle:b,labelSide:_,labelFont:w,tickFont:k,rangeFont:A,layoutWidth:x,layoutHeight:t.height,domain:d,translateX:d.x[0]*x,translateY:t.height-d.y[1]*t.height,pad:C,canvasWidth:P*m.canvasPixelRatio+2*M.canvasOverdrag,canvasHeight:O*m.canvasPixelRatio,width:P,height:O,canvasPixelRatio:m.canvasPixelRatio}}function C(t,e,r){var o=r.width,s=r.height,l=r.dimensions,u=r.canvasPixelRatio,c=function(t){return o*t/Math.max(1,r.colCount-1)},f=m.verticalPadding/s,h=function(t,e){return n.scale.linear().range([e,t-e])}(s,m.verticalPadding),p={key:r.key,xScale:c,model:r,inBrushDrag:!1},d={};return p.dimensions=l.filter(y.isVisible).map((function(o,l){var v=function(t,e){return n.scale.linear().domain(T(t)).range([e,1-e])}(o,f),g=d[o.label];d[o.label]=(g||0)+1;var b=o.label+(g?\"__\"+g:\"\"),_=o.constraintrange,w=_&&_.length;w&&!Array.isArray(_[0])&&(_=[_]);var k=w?_.map((function(t){return t.map(v)})):[[-1/0,1/0]],S=o.values;S.length>o._length&&(S=S.slice(0,o._length));var L,C=o.tickvals;function P(t,e){return{val:t,text:L[e]}}function O(t,e){return t.val-e.val}if(Array.isArray(C)&&C.length){L=o.ticktext,Array.isArray(L)&&L.length?L.length>C.length?L=L.slice(0,C.length):C.length>L.length&&(C=C.slice(0,L.length)):L=C.map(a(o.tickformat));for(var I=1;I<C.length;I++)if(C[I]<C[I-1]){for(var D=C.map(P).sort(O),z=0;z<C.length;z++)C[z]=D[z].val,L[z]=D[z].text;break}}else C=void 0;return S=y.convertTypedArray(S),{key:b,label:o.label,tickFormat:o.tickformat,tickvals:C,ticktext:L,ordinal:y.isOrdinal(o),multiselect:o.multiselect,xIndex:l,crossfilterDimensionIndex:l,visibleIndex:o._index,height:s,values:S,paddedUnitValues:S.map(v),unitTickvals:C&&C.map(v),xScale:c,x:c(l),canvasX:c(l)*u,unitToPaddedPx:h,domainScale:A(s,m.verticalPadding,o,C,L),ordinalScale:M(o),parent:p,model:r,brush:x.makeBrush(t,w,k,(function(){t.linePickActive(!1)}),(function(){var e=p;e.focusLayer&&e.focusLayer.render(e.panels,!0);var r=E(e);!t.contextShown()&&r?(e.contextLayer&&e.contextLayer.render(e.panels,!0),t.contextShown(!0)):t.contextShown()&&!r&&(e.contextLayer&&e.contextLayer.render(e.panels,!0,!0),t.contextShown(!1))}),(function(r){if(p.focusLayer.render(p.panels,!0),p.pickLayer&&p.pickLayer.render(p.panels,!0),t.linePickActive(!0),e&&e.filterChanged){var n=v.invert,a=r.map((function(t){return t.map(n).sort(i.sorterAsc)})).sort((function(t,e){return t[0]-e[0]}));e.filterChanged(p.key,o._index,a)}}))}})),p}function P(t){t.classed(m.cn.axisExtentText,!0).attr(\"text-anchor\",\"middle\").style(\"cursor\",\"default\")}function O(t,e){var r=\"top\"===e?1:-1,n=t*Math.PI/180;return{dir:r,dx:Math.sin(n),dy:Math.cos(n),degrees:t}}function I(t,e,r){for(var n=e.panels||(e.panels=[]),i=t.data(),a=0;a<i.length-1;a++){var o=n[a]||(n[a]={}),s=i[a],l=i[a+1];o.dim0=s,o.dim1=l,o.canvasX=s.canvasX,o.panelSizeX=l.canvasX-s.canvasX,o.panelSizeY=e.model.canvasHeight,o.y=0,o.canvasY=0,o.plotGlPixelRatio=r}}function D(t,e){return s.tickText(t._ax,e,!1).text}function z(t,e){if(t.ordinal)return\"\";var r=t.domainScale.domain(),n=r[e?r.length-1:0];return D(t.model.dimensions[t.visibleIndex],n)}t.exports=function(t,e,r,a){var o=t._context.staticPlot,h=t._fullLayout,p=h._toppaper,_=h._glcontainer,T=t._context.plotGlPixelRatio,A=t._fullLayout.paper_bgcolor;!function(t){for(var e=0;e<t.length;e++)for(var r=0;r<t[e].length;r++)for(var n=t[e][r].trace,i=n.dimensions,a=0;a<i.length;a++){var o=i[a].values,l=i[a]._ax;l&&(l.range?l.range=k(l.range[0],l.range[1]):l.range=w(o,n._length),l.dtick||(l.dtick=.01*(Math.abs(l.range[1]-l.range[0])||1)),l.tickformat=i[a].tickformat,s.calcTicks(l),l.cleanRange())}}(e);var M,S,R=(M=!0,S=!1,{linePickActive:function(t){return arguments.length?M=!!t:M},contextShown:function(t){return arguments.length?S=!!t:S}}),F=e.filter((function(t){return g(t).trace.visible})).map(L.bind(0,r)).map(C.bind(0,R,a));_.each((function(t,e){return i.extendFlat(t,F[e])}));var B=_.selectAll(\".gl-canvas\").each((function(t){t.viewModel=F[0],t.viewModel.plotGlPixelRatio=T,t.viewModel.paperColor=A,t.model=t.viewModel?t.viewModel.model:null})),N=null;B.filter((function(t){return t.pick})).style(\"pointer-events\",o?\"none\":\"auto\").on(\"mousemove\",(function(t){if(R.linePickActive()&&t.lineLayer&&a&&a.hover){var e=n.event,r=this.width,i=this.height,o=n.mouse(this),s=o[0],l=o[1];if(s<0||l<0||s>=r||l>=i)return;var u=t.lineLayer.readPixel(s,i-1-l),c=0!==u[3],f=c?u[2]+256*(u[1]+256*u[0]):null,h={x:s,y:l,clientX:e.clientX,clientY:e.clientY,dataIndex:t.model.key,curveNumber:f};f!==N&&(c?a.hover(h):a.unhover&&a.unhover(h),N=f)}})),B.style(\"opacity\",(function(t){return t.pick?0:1})),p.style(\"background\",\"rgba(255, 255, 255, 0)\");var j=p.selectAll(\".\"+m.cn.parcoords).data(F,d);j.exit().remove(),j.enter().append(\"g\").classed(m.cn.parcoords,!0).style(\"shape-rendering\",\"crispEdges\").style(\"pointer-events\",\"none\"),j.attr(\"transform\",(function(t){return u(t.model.translateX,t.model.translateY)}));var U=j.selectAll(\".\"+m.cn.parcoordsControlView).data(v,d);U.enter().append(\"g\").classed(m.cn.parcoordsControlView,!0),U.attr(\"transform\",(function(t){return u(t.model.pad.l,t.model.pad.t)}));var V=U.selectAll(\".\"+m.cn.yAxis).data((function(t){return 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e=t.model.height/t.model.tickDistance,r=t.domainScale,i=r.domain();n.select(this).call(n.svg.axis().orient(\"left\").tickSize(4).outerTickSize(2).ticks(e,t.tickFormat).tickValues(t.ordinal?i:null).tickFormat((function(e){return y.isOrdinal(t)?e:D(t.model.dimensions[t.visibleIndex],e)})).scale(r)),f.font(q.selectAll(\"text\"),t.model.tickFont)})),q.selectAll(\".domain, .tick>line\").attr(\"fill\",\"none\").attr(\"stroke\",\"black\").attr(\"stroke-opacity\",.25).attr(\"stroke-width\",\"1px\"),q.selectAll(\"text\").style(\"text-shadow\",c.makeTextShadow(A)).style(\"cursor\",\"default\");var G=H.selectAll(\".\"+m.cn.axisHeading).data(v,d);G.enter().append(\"g\").classed(m.cn.axisHeading,!0);var Z=G.selectAll(\".\"+m.cn.axisTitle).data(v,d);Z.enter().append(\"text\").classed(m.cn.axisTitle,!0).attr(\"text-anchor\",\"middle\").style(\"cursor\",\"ew-resize\").style(\"pointer-events\",o?\"none\":\"auto\"),Z.text((function(t){return t.label})).each((function(e){var 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J=Y.selectAll(\".\"+m.cn.axisExtentBottom).data(v,d);J.enter().append(\"g\").classed(m.cn.axisExtentBottom,!0),J.attr(\"transform\",(function(t){return u(0,t.model.height+m.axisExtentOffset)}));var K=J.selectAll(\".\"+m.cn.axisExtentBottomText).data(v,d);K.enter().append(\"text\").classed(m.cn.axisExtentBottomText,!0).attr(\"dy\",\"0.75em\").call(P),K.text((function(t){return z(t,!1)})).each((function(t){f.font(n.select(this),t.model.rangeFont)})),x.ensureAxisBrush(H,A,t)}},21341:function(t,e,r){\"use strict\";var n=r(17171),i=r(79749),a=r(1602).isVisible,o={};function s(t,e,r){var n=e.indexOf(r),i=t.indexOf(n);return-1===i&&(i+=e.length),i}(t.exports=function(t,e){var r=t._fullLayout;if(i(t,[],o)){var l={},u={},c={},f={},h=r._size;e.forEach((function(e,r){var n=e[0].trace;c[r]=n.index;var i=f[r]=n._fullInput.index;l[r]=t.data[i].dimensions,u[r]=t.data[i].dimensions.slice()})),n(t,e,{width:h.w,height:h.h,margin:{t:h.t,r:h.r,b:h.b,l:h.l}},{filterChanged:function(e,n,i){var a=u[e][n],o=i.map((function(t){return t.slice()})),s=\"dimensions[\"+n+\"].constraintrange\",l=r._tracePreGUI[t._fullData[c[e]]._fullInput.uid];if(void 0===l[s]){var h=a.constraintrange;l[s]=h||null}var p=t._fullData[c[e]].dimensions[n];o.length?(1===o.length&&(o=o[0]),a.constraintrange=o,p.constraintrange=o.slice(),o=[o]):(delete a.constraintrange,delete p.constraintrange,o=null);var d={};d[s]=o,t.emit(\"plotly_restyle\",[d,[f[e]]])},hover:function(e){t.emit(\"plotly_hover\",e)},unhover:function(e){t.emit(\"plotly_unhover\",e)},axesMoved:function(e,r){var n=function(t,e){return function(r,n){return s(t,e,r)-s(t,e,n)}}(r,u[e].filter(a));l[e].sort(n),u[e].filter((function(t){return!a(t)})).sort((function(t){return u[e].indexOf(t)})).forEach((function(t){l[e].splice(l[e].indexOf(t),1),l[e].splice(u[e].indexOf(t),0,t)})),t.emit(\"plotly_restyle\",[{dimensions:[l[e]]},[f[e]]])}})}}).reglPrecompiled=o},34e3:function(t,e,r){\"use strict\";var n=r(9012),i=r(27670).Y,a=r(41940),o=r(22399),s=r(5386).fF,l=r(5386).si,u=r(1426).extendFlat,c=r(79952).u,f=a({editType:\"plot\",arrayOk:!0,colorEditType:\"plot\"});t.exports={labels:{valType:\"data_array\",editType:\"calc\"},label0:{valType:\"number\",dflt:0,editType:\"calc\"},dlabel:{valType:\"number\",dflt:1,editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},marker:{colors:{valType:\"data_array\",editType:\"calc\"},line:{color:{valType:\"color\",dflt:o.defaultLine,arrayOk:!0,editType:\"style\"},width:{valType:\"number\",min:0,dflt:0,arrayOk:!0,editType:\"style\"},editType:\"calc\"},pattern:c,editType:\"calc\"},text:{valType:\"data_array\",editType:\"plot\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"style\"},scalegroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"value\",\"percent\"],extras:[\"none\"],editType:\"calc\"},hoverinfo:u({},n.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:s({},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),texttemplate:l({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),textposition:{valType:\"enumerated\",values:[\"inside\",\"outside\",\"auto\",\"none\"],dflt:\"auto\",arrayOk:!0,editType:\"plot\"},textfont:u({},f,{}),insidetextorientation:{valType:\"enumerated\",values:[\"horizontal\",\"radial\",\"tangential\",\"auto\"],dflt:\"auto\",editType:\"plot\"},insidetextfont:u({},f,{}),outsidetextfont:u({},f,{}),automargin:{valType:\"boolean\",dflt:!1,editType:\"plot\"},title:{text:{valType:\"string\",dflt:\"\",editType:\"plot\"},font:u({},f,{}),position:{valType:\"enumerated\",values:[\"top 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n=r(74875);e.name=\"pie\",e.plot=function(t,r,i,a){n.plotBasePlot(e.name,t,r,i,a)},e.clean=function(t,r,i,a){n.cleanBasePlot(e.name,t,r,i,a)}},32354:function(t,e,r){\"use strict\";var n=r(92770),i=r(84267),a=r(7901),o={};function s(t){return function(e,r){return!!e&&!!(e=i(e)).isValid()&&(e=a.addOpacity(e,e.getAlpha()),t[r]||(t[r]=e),e)}}function l(t,e){var r,n=JSON.stringify(t),a=e[n];if(!a){for(a=t.slice(),r=0;r<t.length;r++)a.push(i(t[r]).lighten(20).toHexString());for(r=0;r<t.length;r++)a.push(i(t[r]).darken(20).toHexString());e[n]=a}return a}t.exports={calc:function(t,e){var r,i,a=[],o=t._fullLayout,l=o.hiddenlabels||[],u=e.labels,c=e.marker.colors||[],f=e.values,h=e._length,p=e._hasValues&&h;if(e.dlabel)for(u=new Array(h),r=0;r<h;r++)u[r]=String(e.label0+r*e.dlabel);var d={},v=s(o[\"_\"+e.type+\"colormap\"]),g=0,y=!1;for(r=0;r<h;r++){var m,x,b;if(p){if(m=f[r],!n(m))continue;m=+m}else m=1;void 0!==(x=u[r])&&\"\"!==x||(x=r);var _=d[x=String(x)];void 0===_?(d[x]=a.length,(b=-1!==l.indexOf(x))||(g+=m),a.push({v:m,label:x,color:v(c[r],x),i:r,pts:[r],hidden:b})):(y=!0,(i=a[_]).v+=m,i.pts.push(r),i.hidden||(g+=m),!1===i.color&&c[r]&&(i.color=v(c[r],x)))}return a=a.filter((function(t){return t.v>=0})),(\"funnelarea\"===e.type?y:e.sort)&&a.sort((function(t,e){return e.v-t.v})),a[0]&&(a[0].vTotal=g),a},crossTraceCalc:function(t,e){var r=(e||{}).type;r||(r=\"pie\");var n=t._fullLayout,i=t.calcdata,a=n[r+\"colorway\"],s=n[\"_\"+r+\"colormap\"];n[\"extend\"+r+\"colors\"]&&(a=l(a,o));for(var u=0,c=0;c<i.length;c++){var f=i[c];if(f[0].trace.type===r)for(var h=0;h<f.length;h++){var p=f[h];!1===p.color&&(s[p.label]?p.color=s[p.label]:(s[p.label]=p.color=a[u%a.length],u++))}}},makePullColorFn:s,generateExtendedColors:l}},37434:function(t,e,r){\"use strict\";var n=r(92770),i=r(71828),a=r(34e3),o=r(27670).c,s=r(90769).handleText,l=r(71828).coercePattern;function u(t,e){var r=Array.isArray(t),a=i.isArrayOrTypedArray(e),o=Math.min(r?t.length:1/0,a?e.length:1/0);if(isFinite(o)||(o=0),o&&a){for(var s,l=0;l<o;l++){var u=e[l];if(n(u)&&u>0){s=!0;break}}s||(o=0)}return{hasLabels:r,hasValues:a,len:o}}function c(t,e,r,n,i){n(\"marker.line.width\")&&n(\"marker.line.color\",i?void 0:r.paper_bgcolor);var a=n(\"marker.colors\");l(n,\"marker.pattern\",a),t.marker&&!e.marker.pattern.fgcolor&&(e.marker.pattern.fgcolor=t.marker.colors),e.marker.pattern.bgcolor||(e.marker.pattern.bgcolor=r.paper_bgcolor)}t.exports={handleLabelsAndValues:u,handleMarkerDefaults:c,supplyDefaults:function(t,e,r,n){function l(r,n){return i.coerce(t,e,a,r,n)}var f=u(l(\"labels\"),l(\"values\")),h=f.len;if(e._hasLabels=f.hasLabels,e._hasValues=f.hasValues,!e._hasLabels&&e._hasValues&&(l(\"label0\"),l(\"dlabel\")),h){e._length=h,c(t,e,n,l,!0),l(\"scalegroup\");var p,d=l(\"text\"),v=l(\"texttemplate\");if(v||(p=l(\"textinfo\",Array.isArray(d)?\"text+percent\":\"percent\")),l(\"hovertext\"),l(\"hovertemplate\"),v||p&&\"none\"!==p){var g=l(\"textposition\");s(t,e,n,l,g,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),(Array.isArray(g)||\"auto\"===g||\"outside\"===g)&&l(\"automargin\"),(\"inside\"===g||\"auto\"===g||Array.isArray(g))&&l(\"insidetextorientation\")}o(e,n,l);var y=l(\"hole\");if(l(\"title.text\")){var m=l(\"title.position\",y?\"middle center\":\"top center\");y||\"middle center\"!==m||(e.title.position=\"top center\"),i.coerceFont(l,\"title.font\",n.font)}l(\"sort\"),l(\"direction\"),l(\"rotation\"),l(\"pull\")}else e.visible=!1}}},20007:function(t,e,r){\"use strict\";var n=r(23469).appendArrayMultiPointValues;t.exports=function(t,e){var r={curveNumber:e.index,pointNumbers:t.pts,data:e._input,fullData:e,label:t.label,color:t.color,value:t.v,percent:t.percent,text:t.text,bbox:t.bbox,v:t.v};return 1===t.pts.length&&(r.pointNumber=r.i=t.pts[0]),n(r,e,t.pts),\"funnelarea\"===e.type&&(delete r.v,delete r.i),r}},22209:function(t,e,r){\"use strict\";var n=r(91424),i=r(7901);t.exports=function(t,e,r,a){var o=r.marker.pattern;o&&o.shape?n.pointStyle(t,r,a,e):i.fill(t,e.color)}},53581:function(t,e,r){\"use strict\";var n=r(71828);function i(t){return-1!==t.indexOf(\"e\")?t.replace(/[.]?0+e/,\"e\"):-1!==t.indexOf(\".\")?t.replace(/[.]?0+$/,\"\"):t}e.formatPiePercent=function(t,e){var r=i((100*t).toPrecision(3));return n.numSeparate(r,e)+\"%\"},e.formatPieValue=function(t,e){var r=i(t.toPrecision(10));return n.numSeparate(r,e)},e.getFirstFilled=function(t,e){if(Array.isArray(t))for(var r=0;r<e.length;r++){var n=t[e[r]];if(n||0===n||\"\"===n)return n}},e.castOption=function(t,r){return Array.isArray(t)?e.getFirstFilled(t,r):t||void 0},e.getRotationAngle=function(t){return(\"auto\"===t?0:t)*Math.PI/180}},58810:function(t,e,r){\"use strict\";t.exports={attributes:r(34e3),supplyDefaults:r(37434).supplyDefaults,supplyLayoutDefaults:r(92097),layoutAttributes:r(92774),calc:r(32354).calc,crossTraceCalc:r(32354).crossTraceCalc,plot:r(14575).plot,style:r(68357),styleOne:r(63463),moduleType:\"trace\",name:\"pie\",basePlotModule:r(13584),categories:[\"pie-like\",\"pie\",\"showLegend\"],meta:{}}},92774:function(t){\"use strict\";t.exports={hiddenlabels:{valType:\"data_array\",editType:\"calc\"},piecolorway:{valType:\"colorlist\",editType:\"calc\"},extendpiecolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},92097:function(t,e,r){\"use strict\";var n=r(71828),i=r(92774);t.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"piecolorway\",e.colorway),r(\"extendpiecolors\")}},14575:function(t,e,r){\"use strict\";var n=r(39898),i=r(74875),a=r(30211),o=r(7901),s=r(91424),l=r(71828),u=l.strScale,c=l.strTranslate,f=r(63893),h=r(72597),p=h.recordMinTextSize,d=h.clearMinTextSize,v=r(97313).TEXTPAD,g=r(53581),y=r(20007),m=r(71828).isValidTextValue;function x(t,e,r){var i=r[0],o=i.cx,s=i.cy,u=i.trace,c=\"funnelarea\"===u.type;\"_hasHoverLabel\"in u||(u._hasHoverLabel=!1),\"_hasHoverEvent\"in u||(u._hasHoverEvent=!1),t.on(\"mouseover\",(function(t){var r=e._fullLayout,f=e._fullData[u.index];if(!e._dragging&&!1!==r.hovermode){var h=f.hoverinfo;if(Array.isArray(h)&&(h=a.castHoverinfo({hoverinfo:[g.castOption(h,t.pts)],_module:u._module},r,0)),\"all\"===h&&(h=\"label+text+value+percent+name\"),f.hovertemplate||\"none\"!==h&&\"skip\"!==h&&h){var p=t.rInscribed||0,d=o+t.pxmid[0]*(1-p),v=s+t.pxmid[1]*(1-p),m=r.separators,x=[];if(h&&-1!==h.indexOf(\"label\")&&x.push(t.label),t.text=g.castOption(f.hovertext||f.text,t.pts),h&&-1!==h.indexOf(\"text\")){var b=t.text;l.isValidTextValue(b)&&x.push(b)}t.value=t.v,t.valueLabel=g.formatPieValue(t.v,m),h&&-1!==h.indexOf(\"value\")&&x.push(t.valueLabel),t.percent=t.v/i.vTotal,t.percentLabel=g.formatPiePercent(t.percent,m),h&&-1!==h.indexOf(\"percent\")&&x.push(t.percentLabel);var _=f.hoverlabel,w=_.font,T=[];a.loneHover({trace:u,x0:d-p*i.r,x1:d+p*i.r,y:v,_x0:c?o+t.TL[0]:d-p*i.r,_x1:c?o+t.TR[0]:d+p*i.r,_y0:c?s+t.TL[1]:v-p*i.r,_y1:c?s+t.BL[1]:v+p*i.r,text:x.join(\"<br>\"),name:f.hovertemplate||-1!==h.indexOf(\"name\")?f.name:void 0,idealAlign:t.pxmid[0]<0?\"left\":\"right\",color:g.castOption(_.bgcolor,t.pts)||t.color,borderColor:g.castOption(_.bordercolor,t.pts),fontFamily:g.castOption(w.family,t.pts),fontSize:g.castOption(w.size,t.pts),fontColor:g.castOption(w.color,t.pts),nameLength:g.castOption(_.namelength,t.pts),textAlign:g.castOption(_.align,t.pts),hovertemplate:g.castOption(f.hovertemplate,t.pts),hovertemplateLabels:t,eventData:[y(t,f)]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:e,inOut_bbox:T}),t.bbox=T[0],u._hasHoverLabel=!0}u._hasHoverEvent=!0,e.emit(\"plotly_hover\",{points:[y(t,f)],event:n.event})}})),t.on(\"mouseout\",(function(t){var r=e._fullLayout,i=e._fullData[u.index],o=n.select(this).datum();u._hasHoverEvent&&(t.originalEvent=n.event,e.emit(\"plotly_unhover\",{points:[y(o,i)],event:n.event}),u._hasHoverEvent=!1),u._hasHoverLabel&&(a.loneUnhover(r._hoverlayer.node()),u._hasHoverLabel=!1)})),t.on(\"click\",(function(t){var r=e._fullLayout,i=e._fullData[u.index];e._dragging||!1===r.hovermode||(e._hoverdata=[y(t,i)],a.click(e,n.event))}))}function b(t,e,r){var n=g.castOption(t.insidetextfont.color,e.pts);!n&&t._input.textfont&&(n=g.castOption(t._input.textfont.color,e.pts));var i=g.castOption(t.insidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,a=g.castOption(t.insidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size;return{color:n||o.contrast(e.color),family:i,size:a}}function _(t,e){for(var r,n,i=0;i<t.length;i++)if((n=(r=t[i][0]).trace).title.text){var a=n.title.text;n._meta&&(a=l.templateString(a,n._meta));var o=s.tester.append(\"text\").attr(\"data-notex\",1).text(a).call(s.font,n.title.font).call(f.convertToTspans,e),u=s.bBox(o.node(),!0);r.titleBox={width:u.width,height:u.height},o.remove()}}function w(t,e,r){var n=r.r||e.rpx1,i=e.rInscribed;if(e.startangle===e.stopangle)return{rCenter:1-i,scale:0,rotate:0,textPosAngle:0};var a,o=e.ring,s=1===o&&Math.abs(e.startangle-e.stopangle)===2*Math.PI,l=e.halfangle,u=e.midangle,c=r.trace.insidetextorientation,f=\"horizontal\"===c,h=\"tangential\"===c,p=\"radial\"===c,d=\"auto\"===c,v=[];if(!d){var g,y=function(r,i){if(function(t,e){var r=t.startangle,n=t.stopangle;return r>e&&e>n||r<e&&e<n}(e,r)){var s=Math.abs(r-e.startangle),l=Math.abs(r-e.stopangle),u=s<l?s:l;(a=\"tan\"===i?k(t,n,o,u,0):T(t,n,o,u,Math.PI/2)).textPosAngle=r,v.push(a)}};if(f||h){for(g=4;g>=-4;g-=2)y(Math.PI*g,\"tan\");for(g=4;g>=-4;g-=2)y(Math.PI*(g+1),\"tan\")}if(f||p){for(g=4;g>=-4;g-=2)y(Math.PI*(g+1.5),\"rad\");for(g=4;g>=-4;g-=2)y(Math.PI*(g+.5),\"rad\")}}if(s||d||f){var m=Math.sqrt(t.width*t.width+t.height*t.height);if((a={scale:i*n*2/m,rCenter:1-i,rotate:0}).textPosAngle=(e.startangle+e.stopangle)/2,a.scale>=1)return a;v.push(a)}(d||p)&&((a=T(t,n,o,l,u)).textPosAngle=(e.startangle+e.stopangle)/2,v.push(a)),(d||h)&&((a=k(t,n,o,l,u)).textPosAngle=(e.startangle+e.stopangle)/2,v.push(a));for(var x=0,b=0,_=0;_<v.length;_++){var w=v[_].scale;if(b<w&&(b=w,x=_),!d&&b>=1)break}return v[x]}function T(t,e,r,n,i){e=Math.max(0,e-2*v);var a=t.width/t.height,o=S(a,n,e,r);return{scale:2*o/t.height,rCenter:A(a,o/e),rotate:M(i)}}function k(t,e,r,n,i){e=Math.max(0,e-2*v);var a=t.height/t.width,o=S(a,n,e,r);return{scale:2*o/t.width,rCenter:A(a,o/e),rotate:M(i+Math.PI/2)}}function A(t,e){return Math.cos(e)-t*e}function M(t){return(180/Math.PI*t+720)%180-90}function S(t,e,r,n){var i=t+1/(2*Math.tan(e));return r*Math.min(1/(Math.sqrt(i*i+.5)+i),n/(Math.sqrt(t*t+n/2)+t))}function E(t,e){return t.v!==e.vTotal||e.trace.hole?Math.min(1/(1+1/Math.sin(t.halfangle)),t.ring/2):1}function L(t,e){var r=e.pxmid[0],n=e.pxmid[1],i=t.width/2,a=t.height/2;return r<0&&(i*=-1),n<0&&(a*=-1),{scale:1,rCenter:1,rotate:0,x:i+Math.abs(a)*(i>0?1:-1)/2,y:a/(1+r*r/(n*n)),outside:!0}}function C(t,e){var r,n,i,a=t.trace,o={x:t.cx,y:t.cy},s={tx:0,ty:0};s.ty+=a.title.font.size,i=O(a),-1!==a.title.position.indexOf(\"top\")?(o.y-=(1+i)*t.r,s.ty-=t.titleBox.height):-1!==a.title.position.indexOf(\"bottom\")&&(o.y+=(1+i)*t.r);var l,u=t.r/(void 0===(l=t.trace.aspectratio)?1:l),c=e.w*(a.domain.x[1]-a.domain.x[0])/2;return-1!==a.title.position.indexOf(\"left\")?(c+=u,o.x-=(1+i)*u,s.tx+=t.titleBox.width/2):-1!==a.title.position.indexOf(\"center\")?c*=2:-1!==a.title.position.indexOf(\"right\")&&(c+=u,o.x+=(1+i)*u,s.tx-=t.titleBox.width/2),r=c/t.titleBox.width,n=P(t,e)/t.titleBox.height,{x:o.x,y:o.y,scale:Math.min(r,n),tx:s.tx,ty:s.ty}}function P(t,e){var r=t.trace,n=e.h*(r.domain.y[1]-r.domain.y[0]);return Math.min(t.titleBox.height,n/2)}function O(t){var e,r=t.pull;if(!r)return 0;if(Array.isArray(r))for(r=0,e=0;e<t.pull.length;e++)t.pull[e]>r&&(r=t.pull[e]);return r}function I(t,e){for(var r=[],n=0;n<t.length;n++){var i=t[n][0],a=i.trace,o=a.domain,s=e.w*(o.x[1]-o.x[0]),l=e.h*(o.y[1]-o.y[0]);a.title.text&&\"middle center\"!==a.title.position&&(l-=P(i,e));var u=s/2,c=l/2;\"funnelarea\"!==a.type||a.scalegroup||(c/=a.aspectratio),i.r=Math.min(u,c)/(1+O(a)),i.cx=e.l+e.w*(a.domain.x[1]+a.domain.x[0])/2,i.cy=e.t+e.h*(1-a.domain.y[0])-l/2,a.title.text&&-1!==a.title.position.indexOf(\"bottom\")&&(i.cy-=P(i,e)),a.scalegroup&&-1===r.indexOf(a.scalegroup)&&r.push(a.scalegroup)}!function(t,e){for(var r,n,i,a=0;a<e.length;a++){var o=1/0,s=e[a];for(n=0;n<t.length;n++)if((i=(r=t[n][0]).trace).scalegroup===s){var l;if(\"pie\"===i.type)l=r.r*r.r;else if(\"funnelarea\"===i.type){var u,c;i.aspectratio>1?c=(u=r.r)/i.aspectratio:u=(c=r.r)*i.aspectratio,l=(u*=(1+i.baseratio)/2)*c}o=Math.min(o,l/r.vTotal)}for(n=0;n<t.length;n++)if((i=(r=t[n][0]).trace).scalegroup===s){var f=o*r.vTotal;\"funnelarea\"===i.type&&(f/=(1+i.baseratio)/2,f/=i.aspectratio),r.r=Math.sqrt(f)}}}(t,r)}function D(t,e){return[t*Math.sin(e),-t*Math.cos(e)]}function z(t,e,r){var n=t._fullLayout,i=r.trace,a=i.texttemplate,o=i.textinfo;if(!a&&o&&\"none\"!==o){var s,u=o.split(\"+\"),c=function(t){return-1!==u.indexOf(t)},f=c(\"label\"),h=c(\"text\"),p=c(\"value\"),d=c(\"percent\"),v=n.separators;if(s=f?[e.label]:[],h){var y=g.getFirstFilled(i.text,e.pts);m(y)&&s.push(y)}p&&s.push(g.formatPieValue(e.v,v)),d&&s.push(g.formatPiePercent(e.v/r.vTotal,v)),e.text=s.join(\"<br>\")}if(a){var x=l.castOption(i,e.i,\"texttemplate\");if(x){var b=function(t){return{label:t.label,value:t.v,valueLabel:g.formatPieValue(t.v,n.separators),percent:t.v/r.vTotal,percentLabel:g.formatPiePercent(t.v/r.vTotal,n.separators),color:t.color,text:t.text,customdata:l.castOption(i,t.i,\"customdata\")}}(e),_=g.getFirstFilled(i.text,e.pts);(m(_)||\"\"===_)&&(b.text=_),e.text=l.texttemplateString(x,b,t._fullLayout._d3locale,b,i._meta||{})}else e.text=\"\"}}function R(t,e){var r=t.rotate*Math.PI/180,n=Math.cos(r),i=Math.sin(r),a=(e.left+e.right)/2,o=(e.top+e.bottom)/2;t.textX=a*n-o*i,t.textY=a*i+o*n,t.noCenter=!0}t.exports={plot:function(t,e){var r=t._context.staticPlot,a=t._fullLayout,h=a._size;d(\"pie\",a),_(e,t),I(e,h);var v=l.makeTraceGroups(a._pielayer,e,\"trace\").each((function(e){var d=n.select(this),v=e[0],y=v.trace;!function(t){var e,r,n,i=t[0],a=i.r,o=i.trace,s=g.getRotationAngle(o.rotation),l=2*Math.PI/i.vTotal,u=\"px0\",c=\"px1\";if(\"counterclockwise\"===o.direction){for(e=0;e<t.length&&t[e].hidden;e++);if(e===t.length)return;s+=l*t[e].v,l*=-1,u=\"px1\",c=\"px0\"}for(n=D(a,s),e=0;e<t.length;e++)(r=t[e]).hidden||(r[u]=n,r.startangle=s,s+=l*r.v/2,r.pxmid=D(a,s),r.midangle=s,n=D(a,s+=l*r.v/2),r.stopangle=s,r[c]=n,r.largeArc=r.v>i.vTotal/2?1:0,r.halfangle=Math.PI*Math.min(r.v/i.vTotal,.5),r.ring=1-o.hole,r.rInscribed=E(r,i))}(e),d.attr(\"stroke-linejoin\",\"round\"),d.each((function(){var m=n.select(this).selectAll(\"g.slice\").data(e);m.enter().append(\"g\").classed(\"slice\",!0),m.exit().remove();var _=[[[],[]],[[],[]]],T=!1;m.each((function(i,o){if(i.hidden)n.select(this).selectAll(\"path,g\").remove();else{i.pointNumber=i.i,i.curveNumber=y.index,_[i.pxmid[1]<0?0:1][i.pxmid[0]<0?0:1].push(i);var u=v.cx,c=v.cy,h=n.select(this),d=h.selectAll(\"path.surface\").data([i]);if(d.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":r?\"none\":\"all\"}),h.call(x,t,e),y.pull){var m=+g.castOption(y.pull,i.pts)||0;m>0&&(u+=m*i.pxmid[0],c+=m*i.pxmid[1])}i.cxFinal=u,i.cyFinal=c;var k=y.hole;if(i.v===v.vTotal){var A=\"M\"+(u+i.px0[0])+\",\"+(c+i.px0[1])+P(i.px0,i.pxmid,!0,1)+P(i.pxmid,i.px0,!0,1)+\"Z\";k?d.attr(\"d\",\"M\"+(u+k*i.px0[0])+\",\"+(c+k*i.px0[1])+P(i.px0,i.pxmid,!1,k)+P(i.pxmid,i.px0,!1,k)+\"Z\"+A):d.attr(\"d\",A)}else{var M=P(i.px0,i.px1,!0,1);if(k){var S=1-k;d.attr(\"d\",\"M\"+(u+k*i.px1[0])+\",\"+(c+k*i.px1[1])+P(i.px1,i.px0,!1,k)+\"l\"+S*i.px0[0]+\",\"+S*i.px0[1]+M+\"Z\")}else d.attr(\"d\",\"M\"+u+\",\"+c+\"l\"+i.px0[0]+\",\"+i.px0[1]+M+\"Z\")}z(t,i,v);var E=g.castOption(y.textposition,i.pts),C=h.selectAll(\"g.slicetext\").data(i.text&&\"none\"!==E?[0]:[]);C.enter().append(\"g\").classed(\"slicetext\",!0),C.exit().remove(),C.each((function(){var r=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),h=l.ensureUniformFontSize(t,\"outside\"===E?function(t,e,r){return{color:g.castOption(t.outsidetextfont.color,e.pts)||g.castOption(t.textfont.color,e.pts)||r.color,family:g.castOption(t.outsidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,size:g.castOption(t.outsidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size}}(y,i,a.font):b(y,i,a.font));r.text(i.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,h).call(f.convertToTspans,t);var d,m=s.bBox(r.node());if(\"outside\"===E)d=L(m,i);else if(d=w(m,i,v),\"auto\"===E&&d.scale<1){var x=l.ensureUniformFontSize(t,y.outsidetextfont);r.call(s.font,x),d=L(m=s.bBox(r.node()),i)}var _=d.textPosAngle,k=void 0===_?i.pxmid:D(v.r,_);if(d.targetX=u+k[0]*d.rCenter+(d.x||0),d.targetY=c+k[1]*d.rCenter+(d.y||0),R(d,m),d.outside){var A=d.targetY;i.yLabelMin=A-m.height/2,i.yLabelMid=A,i.yLabelMax=A+m.height/2,i.labelExtraX=0,i.labelExtraY=0,T=!0}d.fontSize=h.size,p(y.type,d,a),e[o].transform=d,l.setTransormAndDisplay(r,d)}))}function P(t,e,r,n){var a=n*(e[0]-t[0]),o=n*(e[1]-t[1]);return\"a\"+n*v.r+\",\"+n*v.r+\" 0 \"+i.largeArc+(r?\" 1 \":\" 0 \")+a+\",\"+o}}));var k=n.select(this).selectAll(\"g.titletext\").data(y.title.text?[0]:[]);if(k.enter().append(\"g\").classed(\"titletext\",!0),k.exit().remove(),k.each((function(){var e,r=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),i=y.title.text;y._meta&&(i=l.templateString(i,y._meta)),r.text(i).attr({class:\"titletext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,y.title.font).call(f.convertToTspans,t),e=\"middle center\"===y.title.position?function(t){var 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t.link.label===i})).style(\"fill-opacity\",(function(t){return t.tinyColorAlpha})),r&&h(e,t).selectAll(u.sankeyNode).filter(g(t)).call(m)}function _(t,e){var r=t.hoverlabel||{},n=i.nestedProperty(r,e).get();return!Array.isArray(n)&&n}t.exports=function(t,e){for(var r=t._fullLayout,i=r._paper,h=r._size,v=0;v<t._fullData.length;v++)if(t._fullData[v].visible&&t._fullData[v].type===u.sankey&&!t._fullData[v]._viewInitial){var g=t._fullData[v].node;t._fullData[v]._viewInitial={node:{groups:g.groups.slice(),x:g.x.slice(),y:g.y.slice()}}}var w=c(t,\"source:\")+\" \",T=c(t,\"target:\")+\" \",k=c(t,\"concentration:\")+\" \",A=c(t,\"incoming flow count:\")+\" \",M=c(t,\"outgoing flow count:\")+\" \";o(t,i,e,{width:h.w,height:h.h,margin:{t:h.t,r:h.r,b:h.b,l:h.l}},{linkEvents:{hover:function(e,r,i){!1!==t._fullLayout.hovermode&&(n.select(e).call(x.bind(0,r,i,!0)),\"skip\"!==r.link.trace.link.hoverinfo&&(r.link.fullData=r.link.trace,t.emit(\"plotly_hover\",{event:n.event,points:[r.link]})))},follow:function(e,i){if(!1!==t._fullLayout.hovermode){var o=i.link.trace.link;if(\"none\"!==o.hoverinfo&&\"skip\"!==o.hoverinfo){for(var u=[],c=0,h=0;h<i.flow.links.length;h++){var v=i.flow.links[h];if(\"closest\"!==t._fullLayout.hovermode||i.link.pointNumber===v.pointNumber){i.link.pointNumber===v.pointNumber&&(c=h),v.fullData=v.trace,o=i.link.trace.link;var g=m(v),y={valueLabel:a(i.valueFormat)(v.value)+i.valueSuffix};u.push({x:g[0],y:g[1],name:y.valueLabel,text:[v.label||\"\",w+v.source.label,T+v.target.label,v.concentrationscale?k+a(\"%0.2f\")(v.flow.labelConcentration):\"\"].filter(f).join(\"<br>\"),color:_(o,\"bgcolor\")||l.addOpacity(v.color,1),borderColor:_(o,\"bordercolor\"),fontFamily:_(o,\"font.family\"),fontSize:_(o,\"font.size\"),fontColor:_(o,\"font.color\"),nameLength:_(o,\"namelength\"),textAlign:_(o,\"align\"),idealAlign:n.event.x<g[0]?\"right\":\"left\",hovertemplate:o.hovertemplate,hovertemplateLabels:y,eventData:[v]})}}s.loneHover(u,{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:t,anchorIndex:c}).each((function(){i.link.concentrationscale||p(this,.65),d(this)}))}}function m(t){var e,r;t.circular?(e=(t.circularPathData.leftInnerExtent+t.circularPathData.rightInnerExtent)/2,r=t.circularPathData.verticalFullExtent):(e=(t.source.x1+t.target.x0)/2,r=(t.y0+t.y1)/2);var n=[e,r];return\"v\"===t.trace.orientation&&n.reverse(),n[0]+=i.parent.translateX,n[1]+=i.parent.translateY,n}},unhover:function(e,i,a){!1!==t._fullLayout.hovermode&&(n.select(e).call(b.bind(0,i,a,!0)),\"skip\"!==i.link.trace.link.hoverinfo&&(i.link.fullData=i.link.trace,t.emit(\"plotly_unhover\",{event:n.event,points:[i.link]})),s.loneUnhover(r._hoverlayer.node()))},select:function(e,r){var i=r.link;i.originalEvent=n.event,t._hoverdata=[i],s.click(t,{target:!0})}},nodeEvents:{hover:function(e,r,i){!1!==t._fullLayout.hovermode&&(n.select(e).call(y,r,i),\"skip\"!==r.node.trace.node.hoverinfo&&(r.node.fullData=r.node.trace,t.emit(\"plotly_hover\",{event:n.event,points:[r.node]})))},follow:function(e,i){if(!1!==t._fullLayout.hovermode){var o=i.node.trace.node;if(\"none\"!==o.hoverinfo&&\"skip\"!==o.hoverinfo){var l=n.select(e).select(\".\"+u.nodeRect),c=t._fullLayout._paperdiv.node().getBoundingClientRect(),h=l.node().getBoundingClientRect(),v=h.left-2-c.left,g=h.right+2-c.left,y=h.top+h.height/4-c.top,m={valueLabel:a(i.valueFormat)(i.node.value)+i.valueSuffix};i.node.fullData=i.node.trace,t._fullLayout._calcInverseTransform(t);var x=t._fullLayout._invScaleX,b=t._fullLayout._invScaleY,w=s.loneHover({x0:x*v,x1:x*g,y:b*y,name:a(i.valueFormat)(i.node.value)+i.valueSuffix,text:[i.node.label,A+i.node.targetLinks.length,M+i.node.sourceLinks.length].filter(f).join(\"<br>\"),color:_(o,\"bgcolor\")||i.tinyColorHue,borderColor:_(o,\"bordercolor\"),fontFamily:_(o,\"font.family\"),fontSize:_(o,\"font.size\"),fontColor:_(o,\"font.color\"),nameLength:_(o,\"namelength\"),textAlign:_(o,\"align\"),idealAlign:\"left\",hovertemplate:o.hovertemplate,hovertemplateLabels:m,eventData:[i.node]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:t});p(w,.85),d(w)}}},unhover:function(e,i,a){!1!==t._fullLayout.hovermode&&(n.select(e).call(m,i,a),\"skip\"!==i.node.trace.node.hoverinfo&&(i.node.fullData=i.node.trace,t.emit(\"plotly_unhover\",{event:n.event,points:[i.node]})),s.loneUnhover(r._hoverlayer.node()))},select:function(e,r,i){var a=r.node;a.originalEvent=n.event,t._hoverdata=[a],n.select(e).call(m,r,i),s.click(t,{target:!0})}}})}},3393:function(t,e,r){\"use strict\";var n=r(49887),i=r(81684).k4,a=r(39898),o=r(30838),s=r(86781),l=r(85247),u=r(84267),c=r(7901),f=r(91424),h=r(71828),p=h.strTranslate,d=h.strRotate,v=r(28984),g=v.keyFun,y=v.repeat,m=v.unwrap,x=r(63893),b=r(73972),_=r(18783),w=_.CAP_SHIFT,T=_.LINE_SPACING;function k(t,e,r){var n,i=m(e),a=i.trace,c=a.domain,f=\"h\"===a.orientation,p=a.node.pad,d=a.node.thickness,v=t.width*(c.x[1]-c.x[0]),g=t.height*(c.y[1]-c.y[0]),y=i._nodes,x=i._links,b=i.circular;(n=b?s.sankeyCircular().circularLinkGap(0):o.sankey()).iterations(l.sankeyIterations).size(f?[v,g]:[g,v]).nodeWidth(d).nodePadding(p).nodeId((function(t){return t.pointNumber})).nodes(y).links(x);var _,w,T,k=n();for(var A in n.nodePadding()<p&&h.warn(\"node.pad was reduced to \",n.nodePadding(),\" to fit within the figure.\"),i._groupLookup){var M,S=parseInt(i._groupLookup[A]);for(_=0;_<k.nodes.length;_++)if(k.nodes[_].pointNumber===S){M=k.nodes[_];break}if(M){var E={pointNumber:parseInt(A),x0:M.x0,x1:M.x1,y0:M.y0,y1:M.y1,partOfGroup:!0,sourceLinks:[],targetLinks:[]};k.nodes.unshift(E),M.childrenNodes.unshift(E)}}if(function(){for(_=0;_<k.nodes.length;_++){var t,e,r=k.nodes[_],n={};for(w=0;w<r.targetLinks.length;w++)t=(e=r.targetLinks[w]).source.pointNumber+\":\"+e.target.pointNumber,n.hasOwnProperty(t)||(n[t]=[]),n[t].push(e);var i=Object.keys(n);for(w=0;w<i.length;w++){var a=n[t=i[w]],o=0,s={};for(T=0;T<a.length;T++)s[(e=a[T]).label]||(s[e.label]=0),s[e.label]+=e.value,o+=e.value;for(T=0;T<a.length;T++)(e=a[T]).flow={value:o,labelConcentration:s[e.label]/o,concentration:e.value/o,links:a},e.concentrationscale&&(e.color=u(e.concentrationscale(e.flow.labelConcentration)))}var l=0;for(w=0;w<r.sourceLinks.length;w++)l+=r.sourceLinks[w].value;for(w=0;w<r.sourceLinks.length;w++)(e=r.sourceLinks[w]).concentrationOut=e.value/l;var c=0;for(w=0;w<r.targetLinks.length;w++)c+=r.targetLinks[w].value;for(w=0;w<r.targetLinks.length;w++)(e=r.targetLinks[w]).concenrationIn=e.value/c}}(),a.node.x.length&&a.node.y.length){for(_=0;_<Math.min(a.node.x.length,a.node.y.length,k.nodes.length);_++)if(a.node.x[_]&&a.node.y[_]){var L=[a.node.x[_]*v,a.node.y[_]*g];k.nodes[_].x0=L[0]-d/2,k.nodes[_].x1=L[0]+d/2;var C=k.nodes[_].y1-k.nodes[_].y0;k.nodes[_].y0=L[1]-C/2,k.nodes[_].y1=L[1]+C/2}\"snap\"===a.arrangement&&function(t){var e,r,n=t.map((function(t,e){return{x0:t.x0,index:e}})).sort((function(t,e){return t.x0-e.x0})),i=[],a=-1,o=-1/0;for(_=0;_<n.length;_++){var s=t[n[_].index];s.x0>o+d&&(a+=1,e=s.x0),o=s.x0,i[a]||(i[a]=[]),i[a].push(s),r=e-s.x0,s.x0+=r,s.x1+=r}return i}(y=k.nodes).forEach((function(t){var e,r,n,i=0,a=t.length;for(t.sort((function(t,e){return t.y0-e.y0})),n=0;n<a;++n)(e=t[n]).y0>=i||(r=i-e.y0)>1e-6&&(e.y0+=r,e.y1+=r),i=e.y1+p})),n.update(k)}return{circular:b,key:r,trace:a,guid:h.randstr(),horizontal:f,width:v,height:g,nodePad:a.node.pad,nodeLineColor:a.node.line.color,nodeLineWidth:a.node.line.width,linkLineColor:a.link.line.color,linkLineWidth:a.link.line.width,linkArrowLength:a.link.arrowlen,valueFormat:a.valueformat,valueSuffix:a.valuesuffix,textFont:a.textfont,translateX:c.x[0]*t.width+t.margin.l,translateY:t.height-c.y[1]*t.height+t.margin.t,dragParallel:f?g:v,dragPerpendicular:f?v:g,arrangement:a.arrangement,sankey:n,graph:k,forceLayouts:{},interactionState:{dragInProgress:!1,hovered:!1}}}function A(t,e,r){var n=u(e.color),i=e.source.label+\"|\"+e.target.label+\"__\"+r;return e.trace=t.trace,e.curveNumber=t.trace.index,{circular:t.circular,key:i,traceId:t.key,pointNumber:e.pointNumber,link:e,tinyColorHue:c.tinyRGB(n),tinyColorAlpha:n.getAlpha(),linkPath:M,linkLineColor:t.linkLineColor,linkLineWidth:t.linkLineWidth,linkArrowLength:t.linkArrowLength,valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,parent:t,interactionState:t.interactionState,flow:e.flow}}function M(){return function(t){var e=t.linkArrowLength;if(t.link.circular)return function(t,e){var r=t.width/2,n=t.circularPathData;return\"top\"===t.circularLinkType?\"M \"+(n.targetX-e)+\" \"+(n.targetY+r)+\" L\"+(n.rightInnerExtent-e)+\" \"+(n.targetY+r)+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightSmallArcRadius+r)+\" 0 0 1 \"+(n.rightFullExtent-r-e)+\" \"+(n.targetY-n.rightSmallArcRadius)+\"L\"+(n.rightFullExtent-r-e)+\" \"+n.verticalRightInnerExtent+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightLargeArcRadius+r)+\" 0 0 1 \"+(n.rightInnerExtent-e)+\" \"+(n.verticalFullExtent-r)+\"L\"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftLargeArcRadius+r)+\" 0 0 1 \"+(n.leftFullExtent+r)+\" \"+n.verticalLeftInnerExtent+\"L\"+(n.leftFullExtent+r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftSmallArcRadius+r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY-r)+\"L\"+n.leftInnerExtent+\" \"+(n.sourceY-r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 0 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 0 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent+r)+\"L\"+(n.rightInnerExtent-e)+\" \"+(n.verticalFullExtent+r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 0 \"+(n.rightFullExtent+r-e)+\" \"+n.verticalRightInnerExtent+\"L\"+(n.rightFullExtent+r-e)+\" \"+(n.targetY-n.rightSmallArcRadius)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightSmallArcRadius-r)+\" 0 0 0 \"+(n.rightInnerExtent-e)+\" \"+(n.targetY-r)+\"L\"+(n.targetX-e)+\" \"+(n.targetY-r)+(e>0?\"L\"+n.targetX+\" \"+n.targetY:\"\")+\"Z\":\"M \"+(n.targetX-e)+\" \"+(n.targetY-r)+\" L\"+(n.rightInnerExtent-e)+\" \"+(n.targetY-r)+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightSmallArcRadius+r)+\" 0 0 0 \"+(n.rightFullExtent-r-e)+\" \"+(n.targetY+n.rightSmallArcRadius)+\"L\"+(n.rightFullExtent-r-e)+\" \"+n.verticalRightInnerExtent+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightLargeArcRadius+r)+\" 0 0 0 \"+(n.rightInnerExtent-e)+\" \"+(n.verticalFullExtent+r)+\"L\"+n.leftInnerExtent+\" \"+(n.verticalFullExtent+r)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftLargeArcRadius+r)+\" 0 0 0 \"+(n.leftFullExtent+r)+\" \"+n.verticalLeftInnerExtent+\"L\"+(n.leftFullExtent+r)+\" \"+(n.sourceY+n.leftSmallArcRadius)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftSmallArcRadius+r)+\" 0 0 0 \"+n.leftInnerExtent+\" \"+(n.sourceY-r)+\"L\"+n.sourceX+\" \"+(n.sourceY-r)+\"L\"+n.sourceX+\" \"+(n.sourceY+r)+\"L\"+n.leftInnerExtent+\" \"+(n.sourceY+r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 1 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY+n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"L\"+(n.rightInnerExtent-e)+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 1 \"+(n.rightFullExtent+r-e)+\" \"+n.verticalRightInnerExtent+\"L\"+(n.rightFullExtent+r-e)+\" \"+(n.targetY+n.rightSmallArcRadius)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightSmallArcRadius-r)+\" 0 0 1 \"+(n.rightInnerExtent-e)+\" \"+(n.targetY+r)+\"L\"+(n.targetX-e)+\" \"+(n.targetY+r)+(e>0?\"L\"+n.targetX+\" \"+n.targetY:\"\")+\"Z\"}(t.link,e);var r=Math.abs((t.link.target.x0-t.link.source.x1)/2);e>r&&(e=r);var n=t.link.source.x1,a=t.link.target.x0-e,o=i(n,a),s=o(.5),l=o(.5),u=t.link.y0-t.link.width/2,c=t.link.y0+t.link.width/2,f=t.link.y1-t.link.width/2,h=t.link.y1+t.link.width/2,p=\"M\"+n+\",\"+u,d=\"C\"+s+\",\"+u+\" \"+l+\",\"+f+\" \"+a+\",\"+f,v=\"C\"+l+\",\"+h+\" \"+s+\",\"+c+\" \"+n+\",\"+c,g=e>0?\"L\"+(a+e)+\",\"+(f+t.link.width/2):\"\";return p+d+(g+=\"L\"+a+\",\"+h)+v+\"Z\"}}function S(t,e){var r=u(e.color),n=l.nodePadAcross,i=t.nodePad/2;e.dx=e.x1-e.x0,e.dy=e.y1-e.y0;var a=e.dx,o=Math.max(.5,e.dy),s=\"node_\"+e.pointNumber;return e.group&&(s=h.randstr()),e.trace=t.trace,e.curveNumber=t.trace.index,{index:e.pointNumber,key:s,partOfGroup:e.partOfGroup||!1,group:e.group,traceId:t.key,trace:t.trace,node:e,nodePad:t.nodePad,nodeLineColor:t.nodeLineColor,nodeLineWidth:t.nodeLineWidth,textFont:t.textFont,size:t.horizontal?t.height:t.width,visibleWidth:Math.ceil(a),visibleHeight:o,zoneX:-n,zoneY:-i,zoneWidth:a+2*n,zoneHeight:o+2*i,labelY:t.horizontal?e.dy/2+1:e.dx/2+1,left:1===e.originalLayer,sizeAcross:t.width,forceLayouts:t.forceLayouts,horizontal:t.horizontal,darkBackground:r.getBrightness()<=128,tinyColorHue:c.tinyRGB(r),tinyColorAlpha:r.getAlpha(),valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,graph:t.graph,arrangement:t.arrangement,uniqueNodeLabelPathId:[t.guid,t.key,s].join(\"_\"),interactionState:t.interactionState,figure:t}}function E(t){t.attr(\"transform\",(function(t){return p(t.node.x0.toFixed(3),t.node.y0.toFixed(3))}))}function L(t){t.call(E)}function 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b=u<2||i[0]!==i[u-1]||o[0]!==o[u-1];b&&(\"tozerox\"===y||\"tonextx\"===y&&(p||\"h\"===d))?m.tozero=!0:(e.error_y||{}).visible||\"tonexty\"!==y&&\"tozeroy\"!==y&&(l.hasMarkers(e)||l.hasText(e))||(m.padded=!1,m.ppad=0),b&&(\"tozeroy\"===y||\"tonexty\"===y&&(p||\"v\"===d))?x.tozero=!0:\"tonextx\"!==y&&\"tozerox\"!==y||(x.padded=!1),f&&(e._extremes[f]=a.findExtremes(r,i,m)),h&&(e._extremes[h]=a.findExtremes(n,o,x))}function p(t,e){if(l.hasMarkers(t)){var r,n=t.marker,o=1.6*(t.marker.sizeref||1);if(r=\"area\"===t.marker.sizemode?function(t){return Math.max(Math.sqrt((t||0)/o),3)}:function(t){return Math.max((t||0)/o,3)},i.isArrayOrTypedArray(n.size)){var s={type:\"linear\"};a.setConvert(s);for(var u=s.makeCalcdata(t.marker,\"size\"),c=new Array(e),f=0;f<e;f++)c[f]=r(u[f]);return c}return r(n.size)}}function d(t,e){var r=v(e),n=t._firstScatter;n[r]||(n[r]=e.uid)}function v(t){var e=t.stackgroup;return t.xaxis+t.yaxis+t.type+(e?\"-\"+e:\"\")}function g(t,e,r,n){var i=t.stackgroup;if(i){var 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n=r(52075).hasColorscale,i=r(78803),a=r(34098);t.exports=function(t,e){a.hasLines(e)&&n(e,\"line\")&&i(t,e,{vals:e.line.color,containerStr:\"line\",cLetter:\"c\"}),a.hasMarkers(e)&&(n(e,\"marker\")&&i(t,e,{vals:e.marker.color,containerStr:\"marker\",cLetter:\"c\"}),n(e,\"marker.line\")&&i(t,e,{vals:e.marker.line.color,containerStr:\"marker.line\",cLetter:\"c\"}))}},47581:function(t){\"use strict\";t.exports={PTS_LINESONLY:20,minTolerance:.2,toleranceGrowth:10,maxScreensAway:20,eventDataKeys:[]}},72626:function(t,e,r){\"use strict\";var n=r(47761),i=r(11661).setGroupPositions;function a(t,e,r,n,i,a,o){i[n]=!0;var s={i:null,gap:!0,s:0};if(s[o]=r,t.splice(e,0,s),e&&r===t[e-1][o]){var l=t[e-1];s.s=l.s,s.i=l.i,s.gap=l.gap}else a&&(s.s=function(t,e,r,n){var i=t[e-1],a=t[e+1];return a?i?i.s+(a.s-i.s)*(r-i[n])/(a[n]-i[n]):a.s:i.s}(t,e,r,o));e||(t[0].t=t[1].t,t[0].trace=t[1].trace,delete t[1].t,delete 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n=r(82196),i=r(9012),a=r(5386).fF,o=r(5386).si,s=r(50693),l=r(1426).extendFlat,u=n.marker,c=n.line,f=u.line;t.exports={carpet:{valType:\"string\",editType:\"calc\"},a:{valType:\"data_array\",editType:\"calc\"},b:{valType:\"data_array\",editType:\"calc\"},mode:l({},n.mode,{dflt:\"markers\"}),text:l({},n.text,{}),texttemplate:o({editType:\"plot\"},{keys:[\"a\",\"b\",\"text\"]}),hovertext:l({},n.hovertext,{}),line:{color:c.color,width:c.width,dash:c.dash,backoff:c.backoff,shape:l({},c.shape,{values:[\"linear\",\"spline\"]}),smoothing:c.smoothing,editType:\"calc\"},connectgaps:n.connectgaps,fill:l({},n.fill,{values:[\"none\",\"toself\",\"tonext\"],dflt:\"none\"}),fillcolor:n.fillcolor,marker:l({symbol:u.symbol,opacity:u.opacity,maxdisplayed:u.maxdisplayed,angle:u.angle,angleref:u.angleref,standoff:u.standoff,size:u.size,sizeref:u.sizeref,sizemin:u.sizemin,sizemode:u.sizemode,line:l({width:f.width,editType:\"calc\"},s(\"marker.line\")),gradient:u.gradient,editType:\"calc\"},s(\"marker\")),textfont:n.textfont,textposition:n.textposition,selected:n.selected,unselected:n.unselected,hoverinfo:l({},i.hoverinfo,{flags:[\"a\",\"b\",\"text\",\"name\"]}),hoveron:n.hoveron,hovertemplate:a()}},34618:function(t,e,r){\"use 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r,n,i=e._length,o=e.marker,l={},u=s.isArrayOrTypedArray(o.symbol),f=s.isArrayOrTypedArray(o.angle),d=s.isArrayOrTypedArray(o.color),v=s.isArrayOrTypedArray(o.line.color),g=s.isArrayOrTypedArray(o.opacity),y=s.isArrayOrTypedArray(o.size),m=s.isArrayOrTypedArray(o.line.width);if(u||(n=p.isOpenSymbol(o.symbol)),u||d||v||g||f){l.symbols=new Array(i),l.angles=new Array(i),l.colors=new Array(i),l.borderColors=new Array(i);var x=o.symbol,b=o.angle,_=c(o,o.opacity,i),w=c(o.line,o.opacity,i);if(!Array.isArray(w[0])){var T=w;for(w=Array(i),r=0;r<i;r++)w[r]=T}if(!Array.isArray(_[0])){var k=_;for(_=Array(i),r=0;r<i;r++)_[r]=k}if(!Array.isArray(x)){var A=x;for(x=Array(i),r=0;r<i;r++)x[r]=A}if(!Array.isArray(b)){var M=b;for(b=Array(i),r=0;r<i;r++)b[r]=M}for(l.symbols=x,l.angles=b,l.colors=_,l.borderColors=w,r=0;r<i;r++)u&&(n=p.isOpenSymbol(o.symbol[r])),n&&(w[r]=_[r].slice(),_[r]=_[r].slice(),_[r][3]=0);for(l.opacity=e.opacity,l.markers=new Array(i),r=0;r<i;r++)l.markers[r]=E({mx:l.symbols[r],ma:l.angles[r]},e)}else n?(l.color=a(o.color,\"uint8\"),l.color[3]=0,l.borderColor=a(o.color,\"uint8\")):(l.color=a(o.color,\"uint8\"),l.borderColor=a(o.line.color,\"uint8\")),l.opacity=e.opacity*o.opacity,l.marker=E({mx:o.symbol,ma:o.angle},e);var S,L=h(e,1);if(y||m){var C,P=l.sizes=new Array(i),O=l.borderSizes=new Array(i),I=0;if(y){for(r=0;r<i;r++)P[r]=L(o.size[r]),I+=P[r];C=I/i}else for(S=L(o.size),r=0;r<i;r++)P[r]=S;if(m)for(r=0;r<i;r++)O[r]=o.line.width[r];else for(S=o.line.width,r=0;r<i;r++)O[r]=S;l.sizeAvg=C}else l.size=L(o&&o.size||10),l.borderSizes=L(o.line.width);return l}function b(t,e,r){var n=e.marker,i={};return r?(r.marker&&r.marker.symbol?i=x(0,s.extendFlat({},n,r.marker)):r.marker&&(r.marker.size&&(i.size=r.marker.size),r.marker.color&&(i.colors=r.marker.color),void 0!==r.marker.opacity&&(i.opacity=r.marker.opacity)),i):i}function _(t,e,r){var n={};if(!r)return n;if(r.textfont){var i={opacity:1,text:e.text,texttemplate:e.texttemplate,textposition:e.textposition,textfont:s.extendFlat({},e.textfont)};r.textfont&&s.extendFlat(i.textfont,r.textfont),n=m(t,i)}return n}function w(t,e,r){var n={capSize:2*e.width*r,lineWidth:e.thickness*r,color:e.color};return e.copy_ystyle&&(n=t.error_y),n}var T=d.SYMBOL_SDF_SIZE,k=d.SYMBOL_SIZE,A=d.SYMBOL_STROKE,M={},S=l.symbolFuncs[0](.05*k);function E(t,e){var r,n,a=t.mx;if(\"circle\"===a)return null;var o=l.symbolNumber(a),s=l.symbolFuncs[o%100],u=!!l.symbolNoDot[o%100],c=!!l.symbolNoFill[o%100],f=p.isDotSymbol(a);if(t.ma&&(a+=\"_\"+t.ma),M[a])return M[a];var h=l.getMarkerAngle(t,e);return r=f&&!u?s(1.1*k,h)+S:s(k,h),n=i(r,{w:T,h:T,viewBox:[-k,-k,k,k],stroke:c?A:-A}),M[a]=n,n||null}t.exports={style:function(t,e){var r,n={marker:void 0,markerSel:void 0,markerUnsel:void 0,line:void 0,fill:void 0,errorX:void 0,errorY:void 0,text:void 0,textSel:void 0,textUnsel:void 0},i=t._context.plotGlPixelRatio;if(!0!==e.visible)return n;if(f.hasText(e)&&(n.text=m(t,e),n.textSel=_(t,e,e.selected),n.textUnsel=_(t,e,e.unselected)),f.hasMarkers(e)&&(n.marker=x(0,e),n.markerSel=b(0,e,e.selected),n.markerUnsel=b(0,e,e.unselected),!e.unselected&&s.isArrayOrTypedArray(e.marker.opacity))){var a=e.marker.opacity;for(n.markerUnsel.opacity=new Array(a.length),r=0;r<a.length;r++)n.markerUnsel.opacity[r]=v*a[r]}if(f.hasLines(e)){n.line={overlay:!0,thickness:e.line.width*i,color:e.line.color,opacity:e.opacity};var o=(d.DASHES[e.line.dash]||[1]).slice();for(r=0;r<o.length;++r)o[r]*=e.line.width*i;n.line.dashes=o}return e.error_x&&e.error_x.visible&&(n.errorX=w(e,e.error_x,i)),e.error_y&&e.error_y.visible&&(n.errorY=w(e,e.error_y,i)),e.fill&&\"none\"!==e.fill&&(n.fill={closed:!0,fill:e.fillcolor,thickness:0}),n},markerStyle:x,markerSelection:b,linePositions:function(t,e,r){var n,i,a=r.length,o=a/2;if(f.hasLines(e)&&o)if(\"hv\"===e.line.shape){for(n=[],i=0;i<o-1;i++)isNaN(r[2*i])||isNaN(r[2*i+1])?n.push(NaN,NaN,NaN,NaN):(n.push(r[2*i],r[2*i+1]),isNaN(r[2*i+2])||isNaN(r[2*i+3])?n.push(NaN,NaN):n.push(r[2*i+2],r[2*i+1]));n.push(r[a-2],r[a-1])}else if(\"hvh\"===e.line.shape){for(n=[],i=0;i<o-1;i++)if(isNaN(r[2*i])||isNaN(r[2*i+1])||isNaN(r[2*i+2])||isNaN(r[2*i+3]))isNaN(r[2*i])||isNaN(r[2*i+1])?n.push(NaN,NaN):n.push(r[2*i],r[2*i+1]),n.push(NaN,NaN);else{var s=(r[2*i]+r[2*i+2])/2;n.push(r[2*i],r[2*i+1],s,r[2*i+1],s,r[2*i+3])}n.push(r[a-2],r[a-1])}else if(\"vhv\"===e.line.shape){for(n=[],i=0;i<o-1;i++)if(isNaN(r[2*i])||isNaN(r[2*i+1])||isNaN(r[2*i+2])||isNaN(r[2*i+3]))isNaN(r[2*i])||isNaN(r[2*i+1])?n.push(NaN,NaN):n.push(r[2*i],r[2*i+1]),n.push(NaN,NaN);else{var l=(r[2*i+1]+r[2*i+3])/2;n.push(r[2*i],r[2*i+1],r[2*i],l,r[2*i+2],l)}n.push(r[a-2],r[a-1])}else if(\"vh\"===e.line.shape){for(n=[],i=0;i<o-1;i++)isNaN(r[2*i])||isNaN(r[2*i+1])?n.push(NaN,NaN,NaN,NaN):(n.push(r[2*i],r[2*i+1]),isNaN(r[2*i+2])||isNaN(r[2*i+3])?n.push(NaN,NaN):n.push(r[2*i],r[2*i+3]));n.push(r[a-2],r[a-1])}else n=r;var u=!1;for(i=0;i<n.length;i++)if(isNaN(n[i])){u=!0;break}var c=u||n.length>d.TOO_MANY_POINTS||f.hasMarkers(e)?\"rect\":\"round\";if(u&&e.connectgaps){var h=n[0],p=n[1];for(i=0;i<n.length;i+=2)isNaN(n[i])||isNaN(n[i+1])?(n[i]=h,n[i+1]=p):(h=n[i],p=n[i+1])}return{join:c,positions:n}},errorBarPositions:function(t,e,r,i,a){var s=o.getComponentMethod(\"errorbars\",\"makeComputeError\"),l=u.getFromId(t,e.xaxis,\"x\"),c=u.getFromId(t,e.yaxis,\"y\"),f=r.length/2,h={};function p(t,i){var a=i._id.charAt(0),o=e[\"error_\"+a];if(o&&o.visible&&(\"linear\"===i.type||\"log\"===i.type)){for(var l=s(o),u={x:0,y:1}[a],c={x:[0,1,2,3],y:[2,3,0,1]}[a],p=new Float64Array(4*f),d=1/0,v=-1/0,g=0,y=0;g<f;g++,y+=4){var m=t[g];if(n(m)){var x=r[2*g+u],b=l(m,g),_=b[0],w=b[1];if(n(_)&&n(w)){var T=m-_,k=m+w;p[y+c[0]]=x-i.c2l(T),p[y+c[1]]=i.c2l(k)-x,p[y+c[2]]=0,p[y+c[3]]=0,d=Math.min(d,m-_),v=Math.max(v,m+w)}}}h[a]={positions:r,errors:p,_bnds:[d,v]}}}return p(i,l),p(a,c),h},textPosition:function(t,e,r,n){var i,a=e._length,o={};if(f.hasMarkers(e)){var s=r.font,l=r.align,u=r.baseline;for(o.offset=new Array(a),i=0;i<a;i++){var c=n.sizes?n.sizes[i]:n.size,h=Array.isArray(s)?s[i].size:s.size,p=Array.isArray(l)?l.length>1?l[i]:l[0]:l,d=Array.isArray(u)?u.length>1?u[i]:u[0]:u,v=g[p],y=g[d],m=c?c/.8+1:0,x=-y*m-.5*y;o.offset[i]=[v*m/h,x/h]}}return o}}},47148:function(t,e,r){\"use strict\";var n=r(71828),i=r(73972),a=r(68645),o=r(42341),s=r(47581),l=r(34098),u=r(67513),c=r(73927),f=r(49508),h=r(11058),p=r(28908),d=r(82410);t.exports=function(t,e,r,v){function g(r,i){return n.coerce(t,e,o,r,i)}var y=!!t.marker&&a.isOpenSymbol(t.marker.symbol),m=l.isBubble(t),x=u(t,e,v,g);if(x){c(t,e,v,g),g(\"xhoverformat\"),g(\"yhoverformat\");var b=x<s.PTS_LINESONLY?\"lines+markers\":\"lines\";g(\"text\"),g(\"hovertext\"),g(\"hovertemplate\"),g(\"mode\",b),l.hasLines(e)&&(g(\"connectgaps\"),h(t,e,r,v,g),g(\"line.shape\")),l.hasMarkers(e)&&(f(t,e,r,v,g,{noAngleRef:!0,noStandOff:!0}),g(\"marker.line.width\",y||m?1:0)),l.hasText(e)&&(g(\"texttemplate\"),d(t,e,v,g));var _=(e.line||{}).color,w=(e.marker||{}).color;g(\"fill\"),\"none\"!==e.fill&&p(t,e,r,g);var T=i.getComponentMethod(\"errorbars\",\"supplyDefaults\");T(t,e,_||w||r,{axis:\"y\"}),T(t,e,_||w||r,{axis:\"x\",inherit:\"y\"}),n.coerceSelectionMarkerOpacity(e,g)}else e.visible=!1}},5345:function(t,e,r){\"use strict\";var n=r(71828),i=r(7901),a=r(37822).DESELECTDIM;t.exports={styleTextSelection:function(t){var e,r,o=t[0],s=o.trace,l=o.t,u=l._scene,c=l.index,f=u.selectBatch[c],h=u.unselectBatch[c],p=u.textOptions[c],d=u.textSelectedOptions[c]||{},v=u.textUnselectedOptions[c]||{},g=n.extendFlat({},p);if(f.length||h.length){var y=d.color,m=v.color,x=p.color,b=Array.isArray(x);for(g.color=new Array(s._length),e=0;e<f.length;e++)r=f[e],g.color[r]=y||(b?x[r]:x);for(e=0;e<h.length;e++){r=h[e];var _=b?x[r]:x;g.color[r]=m||(y?_:i.addOpacity(_,a))}}u.glText[c].update(g)}}},68101:function(t,e,r){\"use strict\";var n=r(8225);t.exports=function(t,e,r){var i=t.i;return\"x\"in t||(t.x=e._x[i]),\"y\"in t||(t.y=e._y[i]),n(t,e,r)}},68645:function(t,e,r){\"use strict\";var n=r(78232);e.isOpenSymbol=function(t){return\"string\"==typeof t?n.OPEN_RE.test(t):t%200>100},e.isDotSymbol=function(t){return\"string\"==typeof t?n.DOT_RE.test(t):t>200}},20794:function(t,e,r){\"use strict\";var n=r(73972),i=r(71828),a=r(34603);function o(t,e,r,o){var s=t.xa,l=t.ya,u=t.distance,c=t.dxy,f=t.index,h={pointNumber:f,x:e[f],y:r[f]};h.tx=Array.isArray(o.text)?o.text[f]:o.text,h.htx=Array.isArray(o.hovertext)?o.hovertext[f]:o.hovertext,h.data=Array.isArray(o.customdata)?o.customdata[f]:o.customdata,h.tp=Array.isArray(o.textposition)?o.textposition[f]:o.textposition;var p=o.textfont;p&&(h.ts=i.isArrayOrTypedArray(p.size)?p.size[f]:p.size,h.tc=Array.isArray(p.color)?p.color[f]:p.color,h.tf=Array.isArray(p.family)?p.family[f]:p.family);var d=o.marker;d&&(h.ms=i.isArrayOrTypedArray(d.size)?d.size[f]:d.size,h.mo=i.isArrayOrTypedArray(d.opacity)?d.opacity[f]:d.opacity,h.mx=i.isArrayOrTypedArray(d.symbol)?d.symbol[f]:d.symbol,h.ma=i.isArrayOrTypedArray(d.angle)?d.angle[f]:d.angle,h.mc=i.isArrayOrTypedArray(d.color)?d.color[f]:d.color);var v=d&&d.line;v&&(h.mlc=Array.isArray(v.color)?v.color[f]:v.color,h.mlw=i.isArrayOrTypedArray(v.width)?v.width[f]:v.width);var g=d&&d.gradient;g&&\"none\"!==g.type&&(h.mgt=Array.isArray(g.type)?g.type[f]:g.type,h.mgc=Array.isArray(g.color)?g.color[f]:g.color);var y=s.c2p(h.x,!0),m=l.c2p(h.y,!0),x=h.mrc||1,b=o.hoverlabel;b&&(h.hbg=Array.isArray(b.bgcolor)?b.bgcolor[f]:b.bgcolor,h.hbc=Array.isArray(b.bordercolor)?b.bordercolor[f]:b.bordercolor,h.hts=i.isArrayOrTypedArray(b.font.size)?b.font.size[f]:b.font.size,h.htc=Array.isArray(b.font.color)?b.font.color[f]:b.font.color,h.htf=Array.isArray(b.font.family)?b.font.family[f]:b.font.family,h.hnl=i.isArrayOrTypedArray(b.namelength)?b.namelength[f]:b.namelength);var _=o.hoverinfo;_&&(h.hi=Array.isArray(_)?_[f]:_);var w=o.hovertemplate;w&&(h.ht=Array.isArray(w)?w[f]:w);var T={};T[t.index]=h;var k=o._origX,A=o._origY,M=i.extendFlat({},t,{color:a(o,h),x0:y-x,x1:y+x,xLabelVal:k?k[f]:h.x,y0:m-x,y1:m+x,yLabelVal:A?A[f]:h.y,cd:T,distance:u,spikeDistance:c,hovertemplate:h.ht});return h.htx?M.text=h.htx:h.tx?M.text=h.tx:o.text&&(M.text=o.text),i.fillText(h,o,M),n.getComponentMethod(\"errorbars\",\"hoverInfo\")(h,o,M),M}t.exports={hoverPoints:function(t,e,r,n){var i,a,s,l,u,c,f,h,p,d,v=t.cd,g=v[0].t,y=v[0].trace,m=t.xa,x=t.ya,b=g.x,_=g.y,w=m.c2p(e),T=x.c2p(r),k=t.distance;if(g.tree){var A=m.p2c(w-k),M=m.p2c(w+k),S=x.p2c(T-k),E=x.p2c(T+k);i=\"x\"===n?g.tree.range(Math.min(A,M),Math.min(x._rl[0],x._rl[1]),Math.max(A,M),Math.max(x._rl[0],x._rl[1])):g.tree.range(Math.min(A,M),Math.min(S,E),Math.max(A,M),Math.max(S,E))}else i=g.ids;var L=k;if(\"x\"===n){var C=!!y.xperiodalignment,P=!!y.yperiodalignment;for(c=0;c<i.length;c++){if(l=b[a=i[c]],f=Math.abs(m.c2p(l)-w),C){var O=m.c2p(y._xStarts[a]),I=m.c2p(y._xEnds[a]);f=w>=Math.min(O,I)&&w<=Math.max(O,I)?0:1/0}if(f<L){if(L=f,u=_[a],h=x.c2p(u)-T,P){var D=x.c2p(y._yStarts[a]),z=x.c2p(y._yEnds[a]);h=T>=Math.min(D,z)&&T<=Math.max(D,z)?0:1/0}d=Math.sqrt(f*f+h*h),s=i[c]}}}else for(c=i.length-1;c>-1;c--)l=b[a=i[c]],u=_[a],f=m.c2p(l)-w,h=x.c2p(u)-T,(p=Math.sqrt(f*f+h*h))<L&&(L=d=p,s=a);return t.index=s,t.distance=L,t.dxy=d,void 0===s?[t]:[o(t,b,_,y)]},calcHover:o}},68868:function(t,e,r){\"use strict\";var n=r(72156);n.plot=r(26787),t.exports=n},26787:function(t,e,r){\"use strict\";var n=r(11870),i=r(46075),a=r(3593),o=r(42505),s=r(71828),l=r(64505).selectMode,u=r(79749),c=r(34098),f=r(68687),h=r(5345).styleTextSelection,p={};function d(t,e,r,n){var i=t._size,a=t.width*n,o=t.height*n,s=i.l*n,l=i.b*n,u=i.r*n,c=i.t*n,f=i.w*n,h=i.h*n;return[s+e.domain[0]*f,l+r.domain[0]*h,a-u-(1-e.domain[1])*f,o-c-(1-r.domain[1])*h]}(t.exports=function(t,e,r){if(r.length){var v,g,y=t._fullLayout,m=e._scene,x=e.xaxis,b=e.yaxis;if(m)if(u(t,[\"ANGLE_instanced_arrays\",\"OES_element_index_uint\"],p)){var 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n=r(5386).fF,i=r(5386).si,a=r(19316),o=r(82196),s=r(23585),l=r(9012),u=r(50693),c=r(1426).extendFlat,f=r(30962).overrideAll,h=r(23585),p=a.line,d=a.marker;t.exports=f({lon:a.lon,lat:a.lat,cluster:{enabled:{valType:\"boolean\"},maxzoom:c({},h.layers.maxzoom,{}),step:{valType:\"number\",arrayOk:!0,dflt:-1,min:-1},size:{valType:\"number\",arrayOk:!0,dflt:20,min:0},color:{valType:\"color\",arrayOk:!0},opacity:c({},d.opacity,{dflt:1})},mode:c({},o.mode,{dflt:\"markers\"}),text:c({},o.text,{}),texttemplate:i({editType:\"plot\"},{keys:[\"lat\",\"lon\",\"text\"]}),hovertext:c({},o.hovertext,{}),line:{color:p.color,width:p.width},connectgaps:o.connectgaps,marker:c({symbol:{valType:\"string\",dflt:\"circle\",arrayOk:!0},angle:{valType:\"number\",dflt:\"auto\",arrayOk:!0},allowoverlap:{valType:\"boolean\",dflt:!1},opacity:d.opacity,size:d.size,sizeref:d.sizeref,sizemin:d.sizemin,sizemode:d.sizemode},u(\"marker\")),fill:a.fill,fillcolor:o.fillcolor,textfont:s.layers.symbol.textfont,textposition:s.layers.symbol.textposition,below:{valType:\"string\"},selected:{marker:o.selected.marker},unselected:{marker:o.unselected.marker},hoverinfo:c({},l.hoverinfo,{flags:[\"lon\",\"lat\",\"text\",\"name\"]}),hovertemplate:n()},\"calc\",\"nested\")},15790:function(t,e,r){\"use 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r,a=e[0].trace,b=!0===a.visible&&0!==a._length,_=\"none\"!==a.fill,w=c.hasLines(a),T=c.hasMarkers(a),k=c.hasText(a),A=T&&\"circle\"===a.marker.symbol,M=T&&\"circle\"!==a.marker.symbol,S=a.cluster&&a.cluster.enabled,E=v(\"fill\"),L=v(\"line\"),C=v(\"circle\"),P=v(\"symbol\"),O={fill:E,line:L,circle:C,symbol:P};if(!b)return O;if((_||w)&&(r=o.calcTraceToLineCoords(e)),_&&(E.geojson=o.makePolygon(r),E.layout.visibility=\"visible\",i.extendFlat(E.paint,{\"fill-color\":a.fillcolor})),w&&(L.geojson=o.makeLine(r),L.layout.visibility=\"visible\",i.extendFlat(L.paint,{\"line-width\":a.line.width,\"line-color\":a.line.color,\"line-opacity\":a.opacity})),A){var I=function(t){var e,r,a,o,c=t[0].trace,f=c.marker,h=c.selectedpoints,p=i.isArrayOrTypedArray(f.color),d=i.isArrayOrTypedArray(f.size),v=i.isArrayOrTypedArray(f.opacity);function g(t){return c.opacity*t}p&&(r=s.hasColorscale(c,\"marker\")?s.makeColorScaleFuncFromTrace(f):i.identity),d&&(a=u(c)),v&&(o=function(t){return 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a.marker&&\"auto\"!==a.marker.angle&&i.extendFlat(P.layout,{\"icon-rotate\":{type:\"identity\",property:\"angle\"},\"icon-rotation-alignment\":\"map\"}),P.layout[\"icon-allow-overlap\"]=a.marker.allowoverlap,i.extendFlat(P.paint,{\"icon-opacity\":a.opacity*a.marker.opacity,\"icon-color\":a.marker.color})),k)){var D=(a.marker||{}).size,z=f(a.textposition,D);i.extendFlat(P.layout,{\"text-size\":a.textfont.size,\"text-anchor\":z.anchor,\"text-offset\":z.offset,\"text-font\":a.textfont.family.split(\", \")}),i.extendFlat(P.paint,{\"text-color\":a.textfont.color,\"text-opacity\":a.opacity})}return O}},76645:function(t,e,r){\"use strict\";var n=r(71828),i=r(34098),a=r(49508),o=r(11058),s=r(82410),l=r(28908),u=r(99181),c=[\"Metropolis Black Italic\",\"Metropolis Black\",\"Metropolis Bold Italic\",\"Metropolis Bold\",\"Metropolis Extra Bold Italic\",\"Metropolis Extra Bold\",\"Metropolis Extra Light Italic\",\"Metropolis Extra Light\",\"Metropolis Light Italic\",\"Metropolis Light\",\"Metropolis Medium Italic\",\"Metropolis Medium\",\"Metropolis Regular Italic\",\"Metropolis Regular\",\"Metropolis Semi Bold Italic\",\"Metropolis Semi Bold\",\"Metropolis Thin Italic\",\"Metropolis Thin\",\"Open Sans Bold Italic\",\"Open Sans Bold\",\"Open Sans Extra Bold Italic\",\"Open Sans Extra Bold\",\"Open Sans Italic\",\"Open Sans Light Italic\",\"Open Sans Light\",\"Open Sans Regular\",\"Open Sans Semibold Italic\",\"Open Sans Semibold\",\"Klokantech Noto Sans Bold\",\"Klokantech Noto Sans CJK Bold\",\"Klokantech Noto Sans CJK Regular\",\"Klokantech Noto Sans Italic\",\"Klokantech Noto Sans Regular\"];t.exports=function(t,e,r,f){function h(r,i){return n.coerce(t,e,u,r,i)}function p(r,i){return n.coerce2(t,e,u,r,i)}var d=function(t,e,r){var n=r(\"lon\")||[],i=r(\"lat\")||[],a=Math.min(n.length,i.length);return 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n=r(35948),i=r(20794).calcHover;t.exports={hoverPoints:function(t,e,r){var a=t.cd[0].trace,o=t.scene.matrixOptions.cdata,s=t.xa,l=t.ya,u=s.c2p(e),c=l.c2p(r),f=t.distance,h=n.getDimIndex(a,s),p=n.getDimIndex(a,l);if(!1===h||!1===p)return[t];for(var d,v,g=o[h],y=o[p],m=f,x=0;x<g.length;x++){var b=g[x],_=y[x],w=s.c2p(b)-u,T=l.c2p(_)-c,k=Math.sqrt(w*w+T*T);k<m&&(m=v=k,d=x)}return t.index=d,t.distance=m,t.dxy=v,void 0===d?[t]:[i(t,g,y,a)]}}},6419:function(t,e,r){\"use strict\";var n=r(65017);n.basePlotModule=r(16947),t.exports=n},79410:function(t,e,r){\"use strict\";var n=r(60487),i=r(71828),a=r(41675),o=r(64505).selectMode;function s(t,e){var r,s,l,u,c,f=t._fullLayout,h=f._size,p=e.trace,d=e.t,v=f._splomScenes[p.uid],g=v.matrixOptions,y=g.cdata,m=f._glcanvas.data()[0].regl,x=f.dragmode;if(0!==y.length){g.lower=p.showupperhalf,g.upper=p.showlowerhalf,g.diagonal=p.diagonal.visible;var b=p._visibleDims,_=y.length,w=v.viewOpts={};for(w.ranges=new Array(_),w.domains=new 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B=i.extendFlat({},g,v.unselectedOptions,w),N=i.extendFlat({},g,v.selectedOptions,w);v.matrix.update(B,N),P=!1}}else d.xpx=d.ypx=null;if(P){var j=i.extendFlat({},g,w);v.matrix.update(j,null)}}}t.exports=function(t,e,r){if(r.length)for(var n=0;n<r.length;n++)s(t,r[n][0])}},10164:function(t,e,r){\"use strict\";var n=r(71828);t.exports=function(t,e){var r=t._fullLayout,i=e.uid,a=r._splomScenes;a||(a=r._splomScenes={});var o={dirty:!0,selectBatch:[],unselectBatch:[]},s=a[e.uid];return s||((s=a[i]=n.extendFlat({},o,{matrix:!1,selectBatch:[],unselectBatch:[]})).draw=function(){s.matrix&&s.matrix.draw&&(s.selectBatch.length||s.unselectBatch.length?s.matrix.draw(s.unselectBatch,s.selectBatch):s.matrix.draw()),s.dirty=!1},s.destroy=function(){s.matrix&&s.matrix.destroy&&s.matrix.destroy(),s.matrixOptions=null,s.selectBatch=null,s.unselectBatch=null,s=null}),s.dirty||n.extendFlat(s,o),s}},8689:function(t,e,r){\"use strict\";var n=r(71828),i=n.pushUnique,a=r(34098),o=r(35948);t.exports=function(t,e){var r=t.cd,s=r[0].trace,l=r[0].t,u=t.scene,c=u.matrixOptions.cdata,f=t.xaxis,h=t.yaxis,p=[];if(!u)return p;var d=!a.hasMarkers(s)&&!a.hasText(s);if(!0!==s.visible||d)return p;var v=o.getDimIndex(s,f),g=o.getDimIndex(s,h);if(!1===v||!1===g)return p;var y=l.xpx[v],m=l.ypx[g],x=c[v],b=c[g],_=(t.scene.selectBatch||[]).slice(),w=[];if(!1!==e&&!e.degenerate)for(var T=0;T<x.length;T++)e.contains([y[T],m[T]],null,T,t)?(p.push({pointNumber:T,x:x[T],y:b[T]}),i(_,T)):-1!==_.indexOf(T)?i(_,T):w.push(T);var k=u.matrixOptions;return _.length||w.length?u.selectBatch.length||u.unselectBatch.length||u.matrix.update(u.unselectedOptions,n.extendFlat({},k,u.selectedOptions,u.viewOpts)):u.matrix.update(k,null),u.selectBatch=_,u.unselectBatch=w,p}},21850:function(t,e,r){\"use strict\";var n=r(50693),i=r(12663).axisHoverFormat,a=r(5386).fF,o=r(2418),s=r(9012),l=r(1426).extendFlat,u={x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},u:{valType:\"data_array\",editType:\"calc\"},v:{valType:\"data_array\",editType:\"calc\"},w:{valType:\"data_array\",editType:\"calc\"},starts:{x:{valType:\"data_array\",editType:\"calc\"},y:{valType:\"data_array\",editType:\"calc\"},z:{valType:\"data_array\",editType:\"calc\"},editType:\"calc\"},maxdisplayed:{valType:\"integer\",min:0,dflt:1e3,editType:\"calc\"},sizeref:{valType:\"number\",editType:\"calc\",min:0,dflt:1},text:{valType:\"string\",dflt:\"\",editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",editType:\"calc\"},hovertemplate:a({editType:\"calc\"},{keys:[\"tubex\",\"tubey\",\"tubez\",\"tubeu\",\"tubev\",\"tubew\",\"norm\",\"divergence\"]}),uhoverformat:i(\"u\",1),vhoverformat:i(\"v\",1),whoverformat:i(\"w\",1),xhoverformat:i(\"x\"),yhoverformat:i(\"y\"),zhoverformat:i(\"z\"),showlegend:l({},s.showlegend,{dflt:!1})};l(u,n(\"\",{colorAttr:\"u/v/w 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L=function(){m=0,M=[],S=[],E=[]};(!m||m<M.length*S.length*E.length)&&L();var C=function(t){return\"x\"===t?v:\"y\"===t?g:y},P=function(t){return\"x\"===t?M:\"y\"===t?S:E},O=function(t){return t[m-1]<t[0]?-1:1},I=C(A[1]),D=C(A[3]),z=C(A[5]),R=P(A[1]).length,F=P(A[3]).length,B=P(A[5]).length,N=!1,j=function(t,e,r){return R*(F*t+e)+r},U=O(C(A[1])),V=O(C(A[3])),H=O(C(A[5]));for(e=0;e<B-1;e++){for(r=0;r<F-1;r++){for(i=0;i<R-1;i++){var q=j(e,r,i),G=j(e,r,i+1),Z=j(e,r+1,i),Y=j(e+1,r,i);if(I[q]*U<I[G]*U&&D[q]*V<D[Z]*V&&z[q]*H<z[Y]*H||(N=!0),N)break}if(N)break}if(N)break}return N&&(n.warn(\"Encountered arbitrary coordinates! 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y=n[c];r.xMax=Math.max(r.xMax,y),r.xMin=Math.min(r.xMin,y);var m=o[c];r.yMax=Math.max(r.yMax,m),r.yMin=Math.min(r.yMin,m);var x=l[c];r.zMax=Math.max(r.zMax,x),r.zMin=Math.min(r.zMin,x)}e._slen=u,e._normMax=f,e._xbnds=[r.xMin,r.xMax],e._ybnds=[r.yMin,r.yMax],e._zbnds=[r.zMin,r.zMax]},filter:s,processGrid:a}},90154:function(t,e,r){\"use strict\";var n=r(9330).gl_streamtube3d,i=n.createTubeMesh,a=r(71828),o=r(81697).parseColorScale,s=r(21081).extractOpts,l=r(90060),u={xaxis:0,yaxis:1,zaxis:2};function c(t,e){this.scene=t,this.uid=e,this.mesh=null,this.data=null}var f=c.prototype;function h(t){var e=t.length;return e>2?t.slice(1,e-1):2===e?[(t[0]+t[1])/2]:t}function p(t){var e=t.length;return 1===e?[.5,.5]:[t[1]-t[0],t[e-1]-t[e-2]]}function d(t,e){var r=t.fullSceneLayout,i=t.dataScale,c=e._len,f={};function d(t,e){var n=r[e],o=i[u[e]];return a.simpleMap(t,(function(t){return 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e.listPath(t,\"label\").join(\"/\")+\"/\"},e.formatValue=o.formatPieValue,e.formatPercent=function(t,e){var r=n.formatPercent(t,0);return\"0%\"===r&&(r=o.formatPiePercent(t,e)),r}},87619:function(t,e,r){\"use strict\";t.exports={moduleType:\"trace\",name:\"sunburst\",basePlotModule:r(66888),categories:[],animatable:!0,attributes:r(57564),layoutAttributes:r(2654),supplyDefaults:r(17094),supplyLayoutDefaults:r(57034),calc:r(52147).calc,crossTraceCalc:r(52147).crossTraceCalc,plot:r(24714).plot,style:r(29969).style,colorbar:r(4898),meta:{}}},2654:function(t){\"use strict\";t.exports={sunburstcolorway:{valType:\"colorlist\",editType:\"calc\"},extendsunburstcolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},57034:function(t,e,r){\"use strict\";var n=r(71828),i=r(2654);t.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"sunburstcolorway\",e.colorway),r(\"extendsunburstcolors\")}},24714:function(t,e,r){\"use strict\";var 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s,l=b.getPtId(t.parent);T.each((function(t){if(b.getPtId(t)===l)return s=t}));var u,c=s.children;c.forEach((function(t,e){if(b.getPtId(t)===r)return u=e}));var f=c.length,h=a(s.x0,s.x1);e={rpx0:I,rpx1:I,x0:h(u/f),x1:h((u+1)/f)}}return a(n,e)}(t);return function(t){return Z(e(t))}})),t.select(\"g.slicetext\").attr(\"opacity\",0)})).remove():T.exit().remove(),T.order();var X=null;if(_&&R){var J=b.getPtId(R);T.each((function(t){null===X&&b.getPtId(t)===J&&(X=t.x1)}))}var K=T;function $(t){var e=t.parent,r=F[b.getPtId(e)],n={};if(r){var i=e.children,o=i.indexOf(t),s=i.length,l=a(r.x0,r.x1);n.x0=l(o/s),n.x1=l(o/s)}else n.x0=n.x1=0;return n}_&&(K=K.transition().each(\"end\",(function(){var e=n.select(this);b.setSliceCursor(e,t,{hideOnRoot:!0,hideOnLeaves:!0,isTransitioning:!1})}))),K.each((function(i){var u=n.select(this),f=s.ensureSingle(u,\"path\",\"surface\",(function(t){t.style(\"pointer-events\",h?\"none\":\"all\")}));i.rpx0=q(i.y0),i.rpx1=q(i.y1),i.xmid=(i.x0+i.x1)/2,i.pxmid=G(i.rpx1,i.xmid),i.midangle=-(i.xmid-Math.PI/2),i.startangle=-(i.x0-Math.PI/2),i.stopangle=-(i.x1-Math.PI/2),i.halfangle=.5*Math.min(s.angleDelta(i.x0,i.x1)||Math.PI,Math.PI),i.ring=1-i.rpx0/i.rpx1,i.rInscribed=function(t){return 0===t.rpx0&&s.isFullCircle([t.x0,t.x1])?1:Math.max(0,Math.min(1/(1+1/Math.sin(t.halfangle)),t.ring/2))}(i),_?f.transition().attrTween(\"d\",(function(t){var e=function(t){var e,r=F[b.getPtId(t)],n={x0:t.x0,x1:t.x1,rpx0:t.rpx0,rpx1:t.rpx1};if(r)e=r;else if(R)if(t.parent)if(X){var i=(t.x1>X?2*Math.PI:0)+V;e={x0:i,x1:i}}else e={rpx0:I,rpx1:I},s.extendFlat(e,$(t));else e={rpx0:0,rpx1:0};else e={x0:V,x1:V};return a(e,n)}(t);return function(t){return Z(e(t))}})):f.attr(\"d\",Z),u.call(m,S,t,r,{eventDataKeys:x.eventDataKeys,transitionTime:x.CLICK_TRANSITION_TIME,transitionEasing:x.CLICK_TRANSITION_EASING}).call(b.setSliceCursor,t,{hideOnRoot:!0,hideOnLeaves:!0,isTransitioning:t._transitioning}),f.call(g,i,A,t);var p=s.ensureSingle(u,\"g\",\"slicetext\"),w=s.ensureSingle(p,\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),T=s.ensureUniformFontSize(t,b.determineTextFont(A,i,y.font));w.text(e.formatSliceLabel(i,S,A,r,y)).classed(\"slicetext\",!0).attr(\"text-anchor\",\"middle\").call(o.font,T).call(l.convertToTspans,t);var M=o.bBox(w.node());i.transform=v(M,i,k),i.transform.targetX=Y(i),i.transform.targetY=W(i);var E=function(t,e){var r=t.transform;return d(r,e),r.fontSize=T.size,c(A.type,r,y),s.getTextTransform(r)};_?w.transition().attrTween(\"transform\",(function(t){var e=function(t){var e,r=F[b.getPtId(t)],n=t.transform;if(r)e=r;else if(e={rpx1:t.rpx1,transform:{textPosAngle:n.textPosAngle,scale:0,rotate:n.rotate,rCenter:n.rCenter,x:n.x,y:n.y}},R)if(t.parent)if(X){var i=t.x1>X?2*Math.PI:0;e.x0=e.x1=i}else s.extendFlat(e,$(t));else e.x0=e.x1=V;else e.x0=e.x1=V;var o=a(e.transform.textPosAngle,t.transform.textPosAngle),l=a(e.rpx1,t.rpx1),u=a(e.x0,t.x0),f=a(e.x1,t.x1),h=a(e.transform.scale,n.scale),p=a(e.transform.rotate,n.rotate),d=0===n.rCenter?3:0===e.transform.rCenter?1/3:1,v=a(e.transform.rCenter,n.rCenter);return function(t){var e=l(t),r=u(t),i=f(t),a=function(t){return v(Math.pow(t,d))}(t),s={pxmid:G(e,(r+i)/2),rpx1:e,transform:{textPosAngle:o(t),rCenter:a,x:n.x,y:n.y}};return c(A.type,n,y),{transform:{targetX:Y(s),targetY:W(s),scale:h(t),rotate:p(t),rCenter:a}}}}(t);return function(t){return E(e(t),M)}})):w.attr(\"transform\",E(i,M))}))}function w(t){return e=t.rpx1,r=t.transform.textPosAngle,[e*Math.sin(r),-e*Math.cos(r)];var e,r}e.plot=function(t,e,r,i){var a,o,s=t._fullLayout,l=s._sunburstlayer,u=!r,c=!s.uniformtext.mode&&b.hasTransition(r);f(\"sunburst\",s),(a=l.selectAll(\"g.trace.sunburst\").data(e,(function(t){return t[0].trace.uid}))).enter().append(\"g\").classed(\"trace\",!0).classed(\"sunburst\",!0).attr(\"stroke-linejoin\",\"round\"),a.order(),c?(i&&(o=i()),n.transition().duration(r.duration).ease(r.easing).each(\"end\",(function(){o&&o()})).each(\"interrupt\",(function(){o&&o()})).each((function(){l.selectAll(\"g.trace\").each((function(e){_(t,e,this,r)}))}))):(a.each((function(e){_(t,e,this,r)})),s.uniformtext.mode&&y(t,s._sunburstlayer.selectAll(\".trace\"),\"sunburst\")),u&&a.exit().remove()},e.formatSliceLabel=function(t,e,r,n,i){var a=r.texttemplate,o=r.textinfo;if(!(a||o&&\"none\"!==o))return\"\";var l=i.separators,u=n[0],c=t.data.data,f=u.hierarchy,h=b.isHierarchyRoot(t),p=b.getParent(f,t),d=b.getValue(t);if(!a){var v,g=o.split(\"+\"),y=function(t){return-1!==g.indexOf(t)},m=[];if(y(\"label\")&&c.label&&m.push(c.label),c.hasOwnProperty(\"v\")&&y(\"value\")&&m.push(b.formatValue(c.v,l)),!h){y(\"current path\")&&m.push(b.getPath(t.data));var x=0;y(\"percent parent\")&&x++,y(\"percent entry\")&&x++,y(\"percent root\")&&x++;var _=x>1;if(x){var w,T=function(t){v=b.formatPercent(w,l),_&&(v+=\" of \"+t),m.push(v)};y(\"percent parent\")&&!h&&(w=d/b.getValue(p),T(\"parent\")),y(\"percent entry\")&&(w=d/b.getValue(e),T(\"entry\")),y(\"percent root\")&&(w=d/b.getValue(f),T(\"root\"))}}return y(\"text\")&&(v=s.castOption(r,c.i,\"text\"),s.isValidTextValue(v)&&m.push(v)),m.join(\"<br>\")}var k=s.castOption(r,c.i,\"texttemplate\");if(!k)return\"\";var A={};c.label&&(A.label=c.label),c.hasOwnProperty(\"v\")&&(A.value=c.v,A.valueLabel=b.formatValue(c.v,l)),A.currentPath=b.getPath(t.data),h||(A.percentParent=d/b.getValue(p),A.percentParentLabel=b.formatPercent(A.percentParent,l),A.parent=b.getPtLabel(p)),A.percentEntry=d/b.getValue(e),A.percentEntryLabel=b.formatPercent(A.percentEntry,l),A.entry=b.getPtLabel(e),A.percentRoot=d/b.getValue(f),A.percentRootLabel=b.formatPercent(A.percentRoot,l),A.root=b.getPtLabel(f),c.hasOwnProperty(\"color\")&&(A.color=c.color);var M=s.castOption(r,c.i,\"text\");return(s.isValidTextValue(M)||\"\"===M)&&(A.text=M),A.customdata=s.castOption(r,c.i,\"customdata\"),s.texttemplateString(k,A,i._d3locale,A,r._meta||{})}},29969:function(t,e,r){\"use strict\";var n=r(39898),i=r(7901),a=r(71828),o=r(72597).resizeText,s=r(43467);function l(t,e,r,n){var 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f=t.exports=u(l({z:{valType:\"data_array\"},x:{valType:\"data_array\"},y:{valType:\"data_array\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertemplate:o(),xhoverformat:a(\"x\"),yhoverformat:a(\"y\"),zhoverformat:a(\"z\"),connectgaps:{valType:\"boolean\",dflt:!1,editType:\"calc\"},surfacecolor:{valType:\"data_array\"}},i(\"\",{colorAttr:\"z or 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n=r(78803);t.exports=function(t,e){e.surfacecolor?n(t,e,{vals:e.surfacecolor,containerStr:\"\",cLetter:\"c\"}):n(t,e,{vals:e.z,containerStr:\"\",cLetter:\"c\"})}},43768:function(t,e,r){\"use strict\";var n=r(9330).gl_surface3d,i=r(9330).ndarray,a=r(9330).ndarray_linear_interpolate.d2,o=r(824),s=r(43907),l=r(71828).isArrayOrTypedArray,u=r(81697).parseColorScale,c=r(78614),f=r(21081).extractOpts;function h(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var p=h.prototype;p.getXat=function(t,e,r,n){var i=l(this.data.x)?l(this.data.x[0])?this.data.x[e][t]:this.data.x[t]:t;return void 0===r?i:n.d2l(i,0,r)},p.getYat=function(t,e,r,n){var i=l(this.data.y)?l(this.data.y[0])?this.data.y[e][t]:this.data.y[e]:e;return void 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A=[!0,!0,!0],M=[\"x\",\"y\",\"z\"];for(e=0;e<3;++e){var S=t.contours[M[e]];A[e]=S.highlight,w.showContour[e]=S.show||S.highlight,w.showContour[e]&&(w.contourProject[e]=[S.project.x,S.project.y,S.project.z],S.show?(this.showContour[e]=!0,w.levels[e]=m[e],p.highlightColor[e]=w.contourColor[e]=c(S.color),S.usecolormap?p.highlightTint[e]=w.contourTint[e]=0:p.highlightTint[e]=w.contourTint[e]=1,w.contourWidth[e]=S.width,this.contourStart[e]=S.start,this.contourEnd[e]=S.end,this.contourSize[e]=S.size):(this.showContour[e]=!1,this.contourStart[e]=null,this.contourEnd[e]=null,this.contourSize[e]=0),S.highlight&&(w.dynamicColor[e]=c(S.highlightcolor),w.dynamicWidth[e]=S.highlightwidth))}(function(t){var e=t[0].rgb,r=t[t.length-1].rgb;return e[0]===r[0]&&e[1]===r[1]&&e[2]===r[2]&&e[3]===r[3]})(d)&&(w.vertexColor=!0),w.objectOffset=this.objectOffset,w.coords=b,p.update(w),p.visible=t.visible,p.enableDynamic=A,p.enableHighlight=A,p.snapToData=!0,\"lighting\"in 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n=r(50215),i=r(1426).extendFlat,a=r(30962).overrideAll,o=r(41940),s=r(27670).Y,l=r(12663).descriptionOnlyNumbers;(t.exports=a({domain:s({name:\"table\",trace:!0}),columnwidth:{valType:\"number\",arrayOk:!0,dflt:null},columnorder:{valType:\"data_array\"},header:{values:{valType:\"data_array\",dflt:[]},format:{valType:\"data_array\",dflt:[],description:l(\"cell value\")},prefix:{valType:\"string\",arrayOk:!0,dflt:null},suffix:{valType:\"string\",arrayOk:!0,dflt:null},height:{valType:\"number\",dflt:28},align:i({},n.align,{arrayOk:!0}),line:{width:{valType:\"number\",arrayOk:!0,dflt:1},color:{valType:\"color\",arrayOk:!0,dflt:\"grey\"}},fill:{color:{valType:\"color\",arrayOk:!0,dflt:\"white\"}},font:i({},o({arrayOk:!0}))},cells:{values:{valType:\"data_array\",dflt:[]},format:{valType:\"data_array\",dflt:[],description:l(\"cell 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L=Math.max(o(e.header.line.width),o(e.cells.line.width)),C={key:e.uid+t._context.staticPlot,translateX:g.x[0]*t._fullLayout._size.w,translateY:t._fullLayout._size.h*(1-g.y[1]),size:t._fullLayout._size,width:y,maxLineWidth:L,height:m,columnOrder:M,groupHeight:m,rowBlocks:k,headerRowBlocks:T,scrollY:0,cells:i({},e.cells,{values:r}),headerCells:i({},e.header,{values:v}),gdColumns:v.map((function(t){return t[0]})),gdColumnsOriginalOrder:v.map((function(t){return t[0]})),prevPages:[0,0],scrollbarState:{scrollbarScrollInProgress:!1},columns:v.map((function(t,e){var r=A[t];return A[t]=(r||0)+1,{key:t+\"__\"+A[t],label:t,specIndex:e,xIndex:M[e],xScale:c,x:void 0,calcdata:void 0,columnWidth:S[e]}}))};return C.columns.forEach((function(t){t.calcdata=C,t.x=c(t)})),C}},56269:function(t,e,r){\"use strict\";var n=r(1426).extendFlat;e.splitToPanels=function(t){var e=[0,0],r=n({},t,{key:\"header\",type:\"header\",page:0,prevPages:e,currentRepaint:[null,null],dragHandle:!0,values:t.calcdata.headerCells.values[t.specIndex],rowBlocks:t.calcdata.headerRowBlocks,calcdata:n({},t.calcdata,{cells:t.calcdata.headerCells})});return[n({},t,{key:\"cells1\",type:\"cells\",page:0,prevPages:e,currentRepaint:[null,null],dragHandle:!1,values:t.calcdata.cells.values[t.specIndex],rowBlocks:t.calcdata.rowBlocks}),n({},t,{key:\"cells2\",type:\"cells\",page:1,prevPages:e,currentRepaint:[null,null],dragHandle:!1,values:t.calcdata.cells.values[t.specIndex],rowBlocks:t.calcdata.rowBlocks}),r]},e.splitToCells=function(t){var e=function(t){var e=t.rowBlocks[t.page],r=e?e.rows[0].rowIndex:0;return[r,e?r+e.rows.length:0]}(t);return(t.values||[]).slice(e[0],e[1]).map((function(r,n){return{keyWithinBlock:n+(\"string\"==typeof r&&r.match(/[<$&> 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a.indexOf(t)})),s=o.length;s<n;s++)o.push(s);e(\"columnorder\",o)}(e,s),s(\"cells.values\"),s(\"cells.format\"),s(\"cells.align\"),s(\"cells.prefix\"),s(\"cells.suffix\"),s(\"cells.height\"),s(\"cells.line.width\"),s(\"cells.line.color\"),s(\"cells.fill.color\"),n.coerceFont(s,\"cells.font\",n.extendFlat({},o.font)),e._length=null}},96595:function(t,e,r){\"use strict\";t.exports={attributes:r(44464),supplyDefaults:r(39754),calc:r(76333),plot:r(36736),moduleType:\"trace\",name:\"table\",basePlotModule:r(99469),categories:[\"noOpacity\"],meta:{}}},36736:function(t,e,r){\"use strict\";var n=r(49850),i=r(39898),a=r(71828).numberFormat,o=r(28984),s=r(91424),l=r(63893),u=r(71828).raiseToTop,c=r(71828).strTranslate,f=r(71828).cancelTransition,h=r(51018),p=r(56269),d=r(7901);function v(t){return Math.ceil(t.calcdata.maxLineWidth/2)}function g(t,e){return\"clip\"+t._fullLayout._uid+\"_scrollAreaBottomClip_\"+e.key}function y(t,e){return\"clip\"+t._fullLayout._uid+\"_columnBoundaryClippath_\"+e.calcdata.key+\"_\"+e.specIndex}function m(t){return[].concat.apply([],t.map((function(t){return t}))).map((function(t){return t.__data__}))}function x(t,e,r){var a=t.selectAll(\".\"+n.cn.scrollbarKit).data(o.repeat,o.keyFun);a.enter().append(\"g\").classed(n.cn.scrollbarKit,!0).style(\"shape-rendering\",\"geometricPrecision\"),a.each((function(t){var e=t.scrollbarState;e.totalHeight=function(t){var e=t.rowBlocks;return z(e,e.length-1)+(e.length?R(e[e.length-1],1/0):1)}(t),e.scrollableAreaHeight=t.groupHeight-S(t),e.currentlyVisibleHeight=Math.min(e.totalHeight,e.scrollableAreaHeight),e.ratio=e.currentlyVisibleHeight/e.totalHeight,e.barLength=Math.max(e.ratio*e.currentlyVisibleHeight,n.goldenRatio*n.scrollbarWidth),e.barWiggleRoom=e.currentlyVisibleHeight-e.barLength,e.wiggleRoom=Math.max(0,e.totalHeight-e.scrollableAreaHeight),e.topY=0===e.barWiggleRoom?0:t.scrollY/e.wiggleRoom*e.barWiggleRoom,e.bottomY=e.topY+e.barLength,e.dragMultiplier=e.wiggleRoom/e.barWiggleRoom})).attr(\"transform\",(function(t){var e=t.width+n.scrollbarWidth/2+n.scrollbarOffset;return c(e,S(t))}));var s=a.selectAll(\".\"+n.cn.scrollbar).data(o.repeat,o.keyFun);s.enter().append(\"g\").classed(n.cn.scrollbar,!0);var l=s.selectAll(\".\"+n.cn.scrollbarSlider).data(o.repeat,o.keyFun);l.enter().append(\"g\").classed(n.cn.scrollbarSlider,!0),l.attr(\"transform\",(function(t){return c(0,t.scrollbarState.topY||0)}));var u=l.selectAll(\".\"+n.cn.scrollbarGlyph).data(o.repeat,o.keyFun);u.enter().append(\"line\").classed(n.cn.scrollbarGlyph,!0).attr(\"stroke\",\"black\").attr(\"stroke-width\",n.scrollbarWidth).attr(\"stroke-linecap\",\"round\").attr(\"y1\",n.scrollbarWidth/2),u.attr(\"y2\",(function(t){return t.scrollbarState.barLength-n.scrollbarWidth/2})).attr(\"stroke-opacity\",(function(t){return t.columnDragInProgress||!t.scrollbarState.barWiggleRoom||r?0:.4})),u.transition().delay(0).duration(0),u.transition().delay(n.scrollbarHideDelay).duration(n.scrollbarHideDuration).attr(\"stroke-opacity\",0);var f=s.selectAll(\".\"+n.cn.scrollbarCaptureZone).data(o.repeat,o.keyFun);f.enter().append(\"line\").classed(n.cn.scrollbarCaptureZone,!0).attr(\"stroke\",\"white\").attr(\"stroke-opacity\",.01).attr(\"stroke-width\",n.scrollbarCaptureWidth).attr(\"stroke-linecap\",\"butt\").attr(\"y1\",0).on(\"mousedown\",(function(r){var n=i.event.y,a=this.getBoundingClientRect(),o=r.scrollbarState,s=n-a.top,l=i.scale.linear().domain([0,o.scrollableAreaHeight]).range([0,o.totalHeight]).clamp(!0);o.topY<=s&&s<=o.bottomY||L(e,t,null,l(s-o.barLength/2))(r)})).call(i.behavior.drag().origin((function(t){return i.event.stopPropagation(),t.scrollbarState.scrollbarScrollInProgress=!0,t})).on(\"drag\",L(e,t)).on(\"dragend\",(function(){}))),f.attr(\"y2\",(function(t){return t.scrollbarState.scrollableAreaHeight})),e._context.staticPlot&&(u.remove(),f.remove())}function b(t,e,r,a){var l=function(t){var e=t.selectAll(\".\"+n.cn.columnCells).data(o.repeat,o.keyFun);return e.enter().append(\"g\").classed(n.cn.columnCells,!0),e.exit().remove(),e}(r),u=function(t){var e=t.selectAll(\".\"+n.cn.columnCell).data(p.splitToCells,(function(t){return t.keyWithinBlock}));return e.enter().append(\"g\").classed(n.cn.columnCell,!0),e.exit().remove(),e}(l);!function(t){t.each((function(t,e){var r=t.calcdata.cells.font,n=t.column.specIndex,i={size:T(r.size,n,e),color:T(r.color,n,e),family:T(r.family,n,e)};t.rowNumber=t.key,t.align=T(t.calcdata.cells.align,n,e),t.cellBorderWidth=T(t.calcdata.cells.line.width,n,e),t.font=i}))}(u);var c=function(t){var e=t.selectAll(\".\"+n.cn.cellRect).data(o.repeat,(function(t){return t.keyWithinBlock}));return e.enter().append(\"rect\").classed(n.cn.cellRect,!0),e}(u);!function(t){t.attr(\"width\",(function(t){return t.column.columnWidth})).attr(\"stroke-width\",(function(t){return t.cellBorderWidth})).each((function(t){var e=i.select(this);d.stroke(e,T(t.calcdata.cells.line.color,t.column.specIndex,t.rowNumber)),d.fill(e,T(t.calcdata.cells.fill.color,t.column.specIndex,t.rowNumber))}))}(c);var f=function(t){var e=t.selectAll(\".\"+n.cn.cellTextHolder).data(o.repeat,(function(t){return t.keyWithinBlock}));return e.enter().append(\"g\").classed(n.cn.cellTextHolder,!0).style(\"shape-rendering\",\"geometricPrecision\"),e}(u),h=function(t){var e=t.selectAll(\".\"+n.cn.cellText).data(o.repeat,(function(t){return t.keyWithinBlock}));return e.enter().append(\"text\").classed(n.cn.cellText,!0).style(\"cursor\",(function(){return\"auto\"})).on(\"mousedown\",(function(){i.event.stopPropagation()})),e}(f);!function(t){t.each((function(t){s.font(i.select(this),t.font)}))}(h),_(h,e,a,t),D(u)}function _(t,e,r,o){t.text((function(t){var e=t.column.specIndex,r=t.rowNumber,i=t.value,o=\"string\"==typeof i,s=o&&i.match(/<br>/i),l=!o||s;t.mayHaveMarkup=o&&i.match(/[<&>]/);var u,c=\"string\"==typeof(u=i)&&u.match(n.latexCheck);t.latex=c;var f,h,p=c?\"\":T(t.calcdata.cells.prefix,e,r)||\"\",d=c?\"\":T(t.calcdata.cells.suffix,e,r)||\"\",v=c?null:T(t.calcdata.cells.format,e,r)||null,g=p+(v?a(v)(t.value):t.value)+d;if(t.wrappingNeeded=!t.wrapped&&!l&&!c&&(f=w(g)),t.cellHeightMayIncrease=s||c||t.mayHaveMarkup||(void 0===f?w(g):f),t.needsConvertToTspans=t.mayHaveMarkup||t.wrappingNeeded||t.latex,t.wrappingNeeded){var y=(\" 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k(t,e,r){t.transition().ease(n.releaseTransitionEase).duration(n.releaseTransitionDuration).attr(\"transform\",c(e.x,r))}function A(t){return\"cells\"===t.type}function M(t){return\"header\"===t.type}function S(t){return(t.rowBlocks.length?t.rowBlocks[0].auxiliaryBlocks:[]).reduce((function(t,e){return t+R(e,1/0)}),0)}function E(t,e,r){var n=m(e)[0];if(void 0!==n){var i=n.rowBlocks,a=n.calcdata,o=z(i,i.length),s=n.calcdata.groupHeight-S(n),l=a.scrollY=Math.max(0,Math.min(o-s,a.scrollY)),u=function(t,e,r){for(var n=[],i=0,a=0;a<t.length;a++){for(var o=t[a],s=o.rows,l=0,u=0;u<s.length;u++)l+=s[u].rowHeight;o.allRowsHeight=l,e<i+l&&e+r>i&&n.push(a),i+=l}return n}(i,l,s);1===u.length&&(u[0]===i.length-1?u.unshift(u[0]-1):u.push(u[0]+1)),u[0]%2&&u.reverse(),e.each((function(t,e){t.page=u[e],t.scrollY=l})),e.attr(\"transform\",(function(t){var e=z(t.rowBlocks,t.page)-t.scrollY;return c(0,e)})),t&&(C(t,r,e,u,n.prevPages,n,0),C(t,r,e,u,n.prevPages,n,1),x(r,t))}}function L(t,e,r,a){return function(o){var s=o.calcdata?o.calcdata:o,l=e.filter((function(t){return s.key===t.key})),u=r||s.scrollbarState.dragMultiplier,c=s.scrollY;s.scrollY=void 0===a?s.scrollY+u*i.event.dy:a;var f=l.selectAll(\".\"+n.cn.yColumn).selectAll(\".\"+n.cn.columnBlock).filter(A);return E(t,f,l),s.scrollY===c}}function C(t,e,r,n,i,a,o){n[o]!==i[o]&&(clearTimeout(a.currentRepaint[o]),a.currentRepaint[o]=setTimeout((function(){var a=r.filter((function(t,e){return e===o&&n[e]!==i[e]}));b(t,e,a,r),i[o]=n[o]})))}function P(t,e,r,a){return function(){var o=i.select(e.parentNode);o.each((function(t){var e=t.fragments;o.selectAll(\"tspan.line\").each((function(t,r){e[r].width=this.getComputedTextLength()}));var 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r=!t._context.staticPlot,a=t._fullLayout._paper.selectAll(\".\"+n.cn.table).data(e.map((function(e){var r=o.unwrap(e).trace;return h(t,r)})),o.keyFun);a.exit().remove(),a.enter().append(\"g\").classed(n.cn.table,!0).attr(\"overflow\",\"visible\").style(\"box-sizing\",\"content-box\").style(\"position\",\"absolute\").style(\"left\",0).style(\"overflow\",\"visible\").style(\"shape-rendering\",\"crispEdges\").style(\"pointer-events\",\"all\"),a.attr(\"width\",(function(t){return t.width+t.size.l+t.size.r})).attr(\"height\",(function(t){return t.height+t.size.t+t.size.b})).attr(\"transform\",(function(t){return c(t.translateX,t.translateY)}));var l=a.selectAll(\".\"+n.cn.tableControlView).data(o.repeat,o.keyFun),d=l.enter().append(\"g\").classed(n.cn.tableControlView,!0).style(\"box-sizing\",\"content-box\");if(r){var _=\"onwheel\"in document?\"wheel\":\"mousewheel\";d.on(\"mousemove\",(function(e){l.filter((function(t){return 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c=[\"\",\"0\",\"00\",\"000\",\"0000\",\"00000\",\"000000\",\"0000000\",\"00000000\",\"000000000\",\"0000000000\",\"00000000000\",\"000000000000\",\"0000000000000\",\"00000000000000\",\"000000000000000\",\"0000000000000000\",\"00000000000000000\",\"000000000000000000\",\"0000000000000000000\",\"00000000000000000000\",\"000000000000000000000\",\"0000000000000000000000\",\"00000000000000000000000\",\"000000000000000000000000\",\"0000000000000000000000000\"],f=[0,0,25,16,12,11,10,9,8,8,7,7,7,7,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5],h=[0,0,33554432,43046721,16777216,48828125,60466176,40353607,16777216,43046721,1e7,19487171,35831808,62748517,7529536,11390625,16777216,24137569,34012224,47045881,64e6,4084101,5153632,6436343,7962624,9765625,11881376,14348907,17210368,20511149,243e5,28629151,33554432,39135393,45435424,52521875,60466176];function p(t,e,r){r.negative=e.negative^t.negative;var n=t.length+e.length|0;r.length=n,n=n-1|0;var i=0|t.words[0],a=0|e.words[0],o=i*a,s=67108863&o,l=o/67108864|0;r.words[0]=s;for(var u=1;u<n;u++){for(var c=l>>>26,f=67108863&l,h=Math.min(u,e.length-1),p=Math.max(0,u-t.length+1);p<=h;p++){var d=u-p|0;c+=(o=(i=0|t.words[d])*(a=0|e.words[p])+f)/67108864|0,f=67108863&o}r.words[u]=0|f,l=0|c}return 0!==l?r.words[u]=0|l:r.length--,r.strip()}a.prototype.toString=function(t,e){var r;if(e=0|e||1,16===(t=t||10)||\"hex\"===t){r=\"\";for(var i=0,a=0,o=0;o<this.length;o++){var s=this.words[o],l=(16777215&(s<<i|a)).toString(16);r=0!=(a=s>>>24-i&16777215)||o!==this.length-1?c[6-l.length]+l+r:l+r,(i+=2)>=26&&(i-=26,o--)}for(0!==a&&(r=a.toString(16)+r);r.length%e!=0;)r=\"0\"+r;return 0!==this.negative&&(r=\"-\"+r),r}if(t===(0|t)&&t>=2&&t<=36){var u=f[t],p=h[t];r=\"\";var d=this.clone();for(d.negative=0;!d.isZero();){var v=d.modn(p).toString(t);r=(d=d.idivn(p)).isZero()?v+r:c[u-v.length]+v+r}for(this.isZero()&&(r=\"0\"+r);r.length%e!=0;)r=\"0\"+r;return 0!==this.negative&&(r=\"-\"+r),r}n(!1,\"Base 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32-Math.clz32(t)}:a.prototype._countBits=function(t){var e=t,r=0;return e>=4096&&(r+=13,e>>>=13),e>=64&&(r+=7,e>>>=7),e>=8&&(r+=4,e>>>=4),e>=2&&(r+=2,e>>>=2),r+e},a.prototype._zeroBits=function(t){if(0===t)return 26;var e=t,r=0;return 0==(8191&e)&&(r+=13,e>>>=13),0==(127&e)&&(r+=7,e>>>=7),0==(15&e)&&(r+=4,e>>>=4),0==(3&e)&&(r+=2,e>>>=2),0==(1&e)&&r++,r},a.prototype.bitLength=function(){var t=this.words[this.length-1],e=this._countBits(t);return 26*(this.length-1)+e},a.prototype.zeroBits=function(){if(this.isZero())return 0;for(var t=0,e=0;e<this.length;e++){var r=this._zeroBits(this.words[e]);if(t+=r,26!==r)break}return t},a.prototype.byteLength=function(){return Math.ceil(this.bitLength()/8)},a.prototype.toTwos=function(t){return 0!==this.negative?this.abs().inotn(t).iaddn(1):this.clone()},a.prototype.fromTwos=function(t){return this.testn(t-1)?this.notn(t).iaddn(1).ineg():this.clone()},a.prototype.isNeg=function(){return 0!==this.negative},a.prototype.neg=function(){return this.clone().ineg()},a.prototype.ineg=function(){return this.isZero()||(this.negative^=1),this},a.prototype.iuor=function(t){for(;this.length<t.length;)this.words[this.length++]=0;for(var e=0;e<t.length;e++)this.words[e]=this.words[e]|t.words[e];return this.strip()},a.prototype.ior=function(t){return n(0==(this.negative|t.negative)),this.iuor(t)},a.prototype.or=function(t){return this.length>t.length?this.clone().ior(t):t.clone().ior(this)},a.prototype.uor=function(t){return this.length>t.length?this.clone().iuor(t):t.clone().iuor(this)},a.prototype.iuand=function(t){var e;e=this.length>t.length?t:this;for(var r=0;r<e.length;r++)this.words[r]=this.words[r]&t.words[r];return this.length=e.length,this.strip()},a.prototype.iand=function(t){return n(0==(this.negative|t.negative)),this.iuand(t)},a.prototype.and=function(t){return this.length>t.length?this.clone().iand(t):t.clone().iand(this)},a.prototype.uand=function(t){return this.length>t.length?this.clone().iuand(t):t.clone().iuand(this)},a.prototype.iuxor=function(t){var e,r;this.length>t.length?(e=this,r=t):(e=t,r=this);for(var n=0;n<r.length;n++)this.words[n]=e.words[n]^r.words[n];if(this!==e)for(;n<e.length;n++)this.words[n]=e.words[n];return this.length=e.length,this.strip()},a.prototype.ixor=function(t){return n(0==(this.negative|t.negative)),this.iuxor(t)},a.prototype.xor=function(t){return this.length>t.length?this.clone().ixor(t):t.clone().ixor(this)},a.prototype.uxor=function(t){return this.length>t.length?this.clone().iuxor(t):t.clone().iuxor(this)},a.prototype.inotn=function(t){n(\"number\"==typeof t&&t>=0);var e=0|Math.ceil(t/26),r=t%26;this._expand(e),r>0&&e--;for(var i=0;i<e;i++)this.words[i]=67108863&~this.words[i];return r>0&&(this.words[i]=~this.words[i]&67108863>>26-r),this.strip()},a.prototype.notn=function(t){return this.clone().inotn(t)},a.prototype.setn=function(t,e){n(\"number\"==typeof t&&t>=0);var r=t/26|0,i=t%26;return this._expand(r+1),this.words[r]=e?this.words[r]|1<<i:this.words[r]&~(1<<i),this.strip()},a.prototype.iadd=function(t){var e,r,n;if(0!==this.negative&&0===t.negative)return this.negative=0,e=this.isub(t),this.negative^=1,this._normSign();if(0===this.negative&&0!==t.negative)return t.negative=0,e=this.isub(t),t.negative=1,e._normSign();this.length>t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a<n.length;a++)e=(0|r.words[a])+(0|n.words[a])+i,this.words[a]=67108863&e,i=e>>>26;for(;0!==i&&a<r.length;a++)e=(0|r.words[a])+i,this.words[a]=67108863&e,i=e>>>26;if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;a<r.length;a++)this.words[a]=r.words[a];return this},a.prototype.add=function(t){var e;return 0!==t.negative&&0===this.negative?(t.negative=0,e=this.sub(t),t.negative^=1,e):0===t.negative&&0!==this.negative?(this.negative=0,e=t.sub(this),this.negative=1,e):this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},a.prototype.isub=function(t){if(0!==t.negative){t.negative=0;var e=this.iadd(t);return t.negative=1,e._normSign()}if(0!==this.negative)return this.negative=0,this.iadd(t),this.negative=1,this._normSign();var r,n,i=this.cmp(t);if(0===i)return this.negative=0,this.length=1,this.words[0]=0,this;i>0?(r=this,n=t):(r=t,n=this);for(var a=0,o=0;o<n.length;o++)a=(e=(0|r.words[o])-(0|n.words[o])+a)>>26,this.words[o]=67108863&e;for(;0!==a&&o<r.length;o++)a=(e=(0|r.words[o])+a)>>26,this.words[o]=67108863&e;if(0===a&&o<r.length&&r!==this)for(;o<r.length;o++)this.words[o]=r.words[o];return this.length=Math.max(this.length,o),r!==this&&(this.negative=1),this.strip()},a.prototype.sub=function(t){return this.clone().isub(t)};var d=function(t,e,r){var n,i,a,o=t.words,s=e.words,l=r.words,u=0,c=0|o[0],f=8191&c,h=c>>>13,p=0|o[1],d=8191&p,v=p>>>13,g=0|o[2],y=8191&g,m=g>>>13,x=0|o[3],b=8191&x,_=x>>>13,w=0|o[4],T=8191&w,k=w>>>13,A=0|o[5],M=8191&A,S=A>>>13,E=0|o[6],L=8191&E,C=E>>>13,P=0|o[7],O=8191&P,I=P>>>13,D=0|o[8],z=8191&D,R=D>>>13,F=0|o[9],B=8191&F,N=F>>>13,j=0|s[0],U=8191&j,V=j>>>13,H=0|s[1],q=8191&H,G=H>>>13,Z=0|s[2],Y=8191&Z,W=Z>>>13,X=0|s[3],J=8191&X,K=X>>>13,$=0|s[4],Q=8191&$,tt=$>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,it=0|s[6],at=8191&it,ot=it>>>13,st=0|s[7],lt=8191&st,ut=st>>>13,ct=0|s[8],ft=8191&ct,ht=ct>>>13,pt=0|s[9],dt=8191&pt,vt=pt>>>13;r.negative=t.negative^e.negative,r.length=19;var gt=(u+(n=Math.imul(f,U))|0)+((8191&(i=(i=Math.imul(f,V))+Math.imul(h,U)|0))<<13)|0;u=((a=Math.imul(h,V))+(i>>>13)|0)+(gt>>>26)|0,gt&=67108863,n=Math.imul(d,U),i=(i=Math.imul(d,V))+Math.imul(v,U)|0,a=Math.imul(v,V);var yt=(u+(n=n+Math.imul(f,q)|0)|0)+((8191&(i=(i=i+Math.imul(f,G)|0)+Math.imul(h,q)|0))<<13)|0;u=((a=a+Math.imul(h,G)|0)+(i>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(y,U),i=(i=Math.imul(y,V))+Math.imul(m,U)|0,a=Math.imul(m,V),n=n+Math.imul(d,q)|0,i=(i=i+Math.imul(d,G)|0)+Math.imul(v,q)|0,a=a+Math.imul(v,G)|0;var mt=(u+(n=n+Math.imul(f,Y)|0)|0)+((8191&(i=(i=i+Math.imul(f,W)|0)+Math.imul(h,Y)|0))<<13)|0;u=((a=a+Math.imul(h,W)|0)+(i>>>13)|0)+(mt>>>26)|0,mt&=67108863,n=Math.imul(b,U),i=(i=Math.imul(b,V))+Math.imul(_,U)|0,a=Math.imul(_,V),n=n+Math.imul(y,q)|0,i=(i=i+Math.imul(y,G)|0)+Math.imul(m,q)|0,a=a+Math.imul(m,G)|0,n=n+Math.imul(d,Y)|0,i=(i=i+Math.imul(d,W)|0)+Math.imul(v,Y)|0,a=a+Math.imul(v,W)|0;var xt=(u+(n=n+Math.imul(f,J)|0)|0)+((8191&(i=(i=i+Math.imul(f,K)|0)+Math.imul(h,J)|0))<<13)|0;u=((a=a+Math.imul(h,K)|0)+(i>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(T,U),i=(i=Math.imul(T,V))+Math.imul(k,U)|0,a=Math.imul(k,V),n=n+Math.imul(b,q)|0,i=(i=i+Math.imul(b,G)|0)+Math.imul(_,q)|0,a=a+Math.imul(_,G)|0,n=n+Math.imul(y,Y)|0,i=(i=i+Math.imul(y,W)|0)+Math.imul(m,Y)|0,a=a+Math.imul(m,W)|0,n=n+Math.imul(d,J)|0,i=(i=i+Math.imul(d,K)|0)+Math.imul(v,J)|0,a=a+Math.imul(v,K)|0;var bt=(u+(n=n+Math.imul(f,Q)|0)|0)+((8191&(i=(i=i+Math.imul(f,tt)|0)+Math.imul(h,Q)|0))<<13)|0;u=((a=a+Math.imul(h,tt)|0)+(i>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(M,U),i=(i=Math.imul(M,V))+Math.imul(S,U)|0,a=Math.imul(S,V),n=n+Math.imul(T,q)|0,i=(i=i+Math.imul(T,G)|0)+Math.imul(k,q)|0,a=a+Math.imul(k,G)|0,n=n+Math.imul(b,Y)|0,i=(i=i+Math.imul(b,W)|0)+Math.imul(_,Y)|0,a=a+Math.imul(_,W)|0,n=n+Math.imul(y,J)|0,i=(i=i+Math.imul(y,K)|0)+Math.imul(m,J)|0,a=a+Math.imul(m,K)|0,n=n+Math.imul(d,Q)|0,i=(i=i+Math.imul(d,tt)|0)+Math.imul(v,Q)|0,a=a+Math.imul(v,tt)|0;var _t=(u+(n=n+Math.imul(f,rt)|0)|0)+((8191&(i=(i=i+Math.imul(f,nt)|0)+Math.imul(h,rt)|0))<<13)|0;u=((a=a+Math.imul(h,nt)|0)+(i>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(L,U),i=(i=Math.imul(L,V))+Math.imul(C,U)|0,a=Math.imul(C,V),n=n+Math.imul(M,q)|0,i=(i=i+Math.imul(M,G)|0)+Math.imul(S,q)|0,a=a+Math.imul(S,G)|0,n=n+Math.imul(T,Y)|0,i=(i=i+Math.imul(T,W)|0)+Math.imul(k,Y)|0,a=a+Math.imul(k,W)|0,n=n+Math.imul(b,J)|0,i=(i=i+Math.imul(b,K)|0)+Math.imul(_,J)|0,a=a+Math.imul(_,K)|0,n=n+Math.imul(y,Q)|0,i=(i=i+Math.imul(y,tt)|0)+Math.imul(m,Q)|0,a=a+Math.imul(m,tt)|0,n=n+Math.imul(d,rt)|0,i=(i=i+Math.imul(d,nt)|0)+Math.imul(v,rt)|0,a=a+Math.imul(v,nt)|0;var wt=(u+(n=n+Math.imul(f,at)|0)|0)+((8191&(i=(i=i+Math.imul(f,ot)|0)+Math.imul(h,at)|0))<<13)|0;u=((a=a+Math.imul(h,ot)|0)+(i>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(O,U),i=(i=Math.imul(O,V))+Math.imul(I,U)|0,a=Math.imul(I,V),n=n+Math.imul(L,q)|0,i=(i=i+Math.imul(L,G)|0)+Math.imul(C,q)|0,a=a+Math.imul(C,G)|0,n=n+Math.imul(M,Y)|0,i=(i=i+Math.imul(M,W)|0)+Math.imul(S,Y)|0,a=a+Math.imul(S,W)|0,n=n+Math.imul(T,J)|0,i=(i=i+Math.imul(T,K)|0)+Math.imul(k,J)|0,a=a+Math.imul(k,K)|0,n=n+Math.imul(b,Q)|0,i=(i=i+Math.imul(b,tt)|0)+Math.imul(_,Q)|0,a=a+Math.imul(_,tt)|0,n=n+Math.imul(y,rt)|0,i=(i=i+Math.imul(y,nt)|0)+Math.imul(m,rt)|0,a=a+Math.imul(m,nt)|0,n=n+Math.imul(d,at)|0,i=(i=i+Math.imul(d,ot)|0)+Math.imul(v,at)|0,a=a+Math.imul(v,ot)|0;var Tt=(u+(n=n+Math.imul(f,lt)|0)|0)+((8191&(i=(i=i+Math.imul(f,ut)|0)+Math.imul(h,lt)|0))<<13)|0;u=((a=a+Math.imul(h,ut)|0)+(i>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(z,U),i=(i=Math.imul(z,V))+Math.imul(R,U)|0,a=Math.imul(R,V),n=n+Math.imul(O,q)|0,i=(i=i+Math.imul(O,G)|0)+Math.imul(I,q)|0,a=a+Math.imul(I,G)|0,n=n+Math.imul(L,Y)|0,i=(i=i+Math.imul(L,W)|0)+Math.imul(C,Y)|0,a=a+Math.imul(C,W)|0,n=n+Math.imul(M,J)|0,i=(i=i+Math.imul(M,K)|0)+Math.imul(S,J)|0,a=a+Math.imul(S,K)|0,n=n+Math.imul(T,Q)|0,i=(i=i+Math.imul(T,tt)|0)+Math.imul(k,Q)|0,a=a+Math.imul(k,tt)|0,n=n+Math.imul(b,rt)|0,i=(i=i+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,a=a+Math.imul(_,nt)|0,n=n+Math.imul(y,at)|0,i=(i=i+Math.imul(y,ot)|0)+Math.imul(m,at)|0,a=a+Math.imul(m,ot)|0,n=n+Math.imul(d,lt)|0,i=(i=i+Math.imul(d,ut)|0)+Math.imul(v,lt)|0,a=a+Math.imul(v,ut)|0;var kt=(u+(n=n+Math.imul(f,ft)|0)|0)+((8191&(i=(i=i+Math.imul(f,ht)|0)+Math.imul(h,ft)|0))<<13)|0;u=((a=a+Math.imul(h,ht)|0)+(i>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(B,U),i=(i=Math.imul(B,V))+Math.imul(N,U)|0,a=Math.imul(N,V),n=n+Math.imul(z,q)|0,i=(i=i+Math.imul(z,G)|0)+Math.imul(R,q)|0,a=a+Math.imul(R,G)|0,n=n+Math.imul(O,Y)|0,i=(i=i+Math.imul(O,W)|0)+Math.imul(I,Y)|0,a=a+Math.imul(I,W)|0,n=n+Math.imul(L,J)|0,i=(i=i+Math.imul(L,K)|0)+Math.imul(C,J)|0,a=a+Math.imul(C,K)|0,n=n+Math.imul(M,Q)|0,i=(i=i+Math.imul(M,tt)|0)+Math.imul(S,Q)|0,a=a+Math.imul(S,tt)|0,n=n+Math.imul(T,rt)|0,i=(i=i+Math.imul(T,nt)|0)+Math.imul(k,rt)|0,a=a+Math.imul(k,nt)|0,n=n+Math.imul(b,at)|0,i=(i=i+Math.imul(b,ot)|0)+Math.imul(_,at)|0,a=a+Math.imul(_,ot)|0,n=n+Math.imul(y,lt)|0,i=(i=i+Math.imul(y,ut)|0)+Math.imul(m,lt)|0,a=a+Math.imul(m,ut)|0,n=n+Math.imul(d,ft)|0,i=(i=i+Math.imul(d,ht)|0)+Math.imul(v,ft)|0,a=a+Math.imul(v,ht)|0;var At=(u+(n=n+Math.imul(f,dt)|0)|0)+((8191&(i=(i=i+Math.imul(f,vt)|0)+Math.imul(h,dt)|0))<<13)|0;u=((a=a+Math.imul(h,vt)|0)+(i>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,q),i=(i=Math.imul(B,G))+Math.imul(N,q)|0,a=Math.imul(N,G),n=n+Math.imul(z,Y)|0,i=(i=i+Math.imul(z,W)|0)+Math.imul(R,Y)|0,a=a+Math.imul(R,W)|0,n=n+Math.imul(O,J)|0,i=(i=i+Math.imul(O,K)|0)+Math.imul(I,J)|0,a=a+Math.imul(I,K)|0,n=n+Math.imul(L,Q)|0,i=(i=i+Math.imul(L,tt)|0)+Math.imul(C,Q)|0,a=a+Math.imul(C,tt)|0,n=n+Math.imul(M,rt)|0,i=(i=i+Math.imul(M,nt)|0)+Math.imul(S,rt)|0,a=a+Math.imul(S,nt)|0,n=n+Math.imul(T,at)|0,i=(i=i+Math.imul(T,ot)|0)+Math.imul(k,at)|0,a=a+Math.imul(k,ot)|0,n=n+Math.imul(b,lt)|0,i=(i=i+Math.imul(b,ut)|0)+Math.imul(_,lt)|0,a=a+Math.imul(_,ut)|0,n=n+Math.imul(y,ft)|0,i=(i=i+Math.imul(y,ht)|0)+Math.imul(m,ft)|0,a=a+Math.imul(m,ht)|0;var Mt=(u+(n=n+Math.imul(d,dt)|0)|0)+((8191&(i=(i=i+Math.imul(d,vt)|0)+Math.imul(v,dt)|0))<<13)|0;u=((a=a+Math.imul(v,vt)|0)+(i>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,Y),i=(i=Math.imul(B,W))+Math.imul(N,Y)|0,a=Math.imul(N,W),n=n+Math.imul(z,J)|0,i=(i=i+Math.imul(z,K)|0)+Math.imul(R,J)|0,a=a+Math.imul(R,K)|0,n=n+Math.imul(O,Q)|0,i=(i=i+Math.imul(O,tt)|0)+Math.imul(I,Q)|0,a=a+Math.imul(I,tt)|0,n=n+Math.imul(L,rt)|0,i=(i=i+Math.imul(L,nt)|0)+Math.imul(C,rt)|0,a=a+Math.imul(C,nt)|0,n=n+Math.imul(M,at)|0,i=(i=i+Math.imul(M,ot)|0)+Math.imul(S,at)|0,a=a+Math.imul(S,ot)|0,n=n+Math.imul(T,lt)|0,i=(i=i+Math.imul(T,ut)|0)+Math.imul(k,lt)|0,a=a+Math.imul(k,ut)|0,n=n+Math.imul(b,ft)|0,i=(i=i+Math.imul(b,ht)|0)+Math.imul(_,ft)|0,a=a+Math.imul(_,ht)|0;var St=(u+(n=n+Math.imul(y,dt)|0)|0)+((8191&(i=(i=i+Math.imul(y,vt)|0)+Math.imul(m,dt)|0))<<13)|0;u=((a=a+Math.imul(m,vt)|0)+(i>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,J),i=(i=Math.imul(B,K))+Math.imul(N,J)|0,a=Math.imul(N,K),n=n+Math.imul(z,Q)|0,i=(i=i+Math.imul(z,tt)|0)+Math.imul(R,Q)|0,a=a+Math.imul(R,tt)|0,n=n+Math.imul(O,rt)|0,i=(i=i+Math.imul(O,nt)|0)+Math.imul(I,rt)|0,a=a+Math.imul(I,nt)|0,n=n+Math.imul(L,at)|0,i=(i=i+Math.imul(L,ot)|0)+Math.imul(C,at)|0,a=a+Math.imul(C,ot)|0,n=n+Math.imul(M,lt)|0,i=(i=i+Math.imul(M,ut)|0)+Math.imul(S,lt)|0,a=a+Math.imul(S,ut)|0,n=n+Math.imul(T,ft)|0,i=(i=i+Math.imul(T,ht)|0)+Math.imul(k,ft)|0,a=a+Math.imul(k,ht)|0;var Et=(u+(n=n+Math.imul(b,dt)|0)|0)+((8191&(i=(i=i+Math.imul(b,vt)|0)+Math.imul(_,dt)|0))<<13)|0;u=((a=a+Math.imul(_,vt)|0)+(i>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,Q),i=(i=Math.imul(B,tt))+Math.imul(N,Q)|0,a=Math.imul(N,tt),n=n+Math.imul(z,rt)|0,i=(i=i+Math.imul(z,nt)|0)+Math.imul(R,rt)|0,a=a+Math.imul(R,nt)|0,n=n+Math.imul(O,at)|0,i=(i=i+Math.imul(O,ot)|0)+Math.imul(I,at)|0,a=a+Math.imul(I,ot)|0,n=n+Math.imul(L,lt)|0,i=(i=i+Math.imul(L,ut)|0)+Math.imul(C,lt)|0,a=a+Math.imul(C,ut)|0,n=n+Math.imul(M,ft)|0,i=(i=i+Math.imul(M,ht)|0)+Math.imul(S,ft)|0,a=a+Math.imul(S,ht)|0;var Lt=(u+(n=n+Math.imul(T,dt)|0)|0)+((8191&(i=(i=i+Math.imul(T,vt)|0)+Math.imul(k,dt)|0))<<13)|0;u=((a=a+Math.imul(k,vt)|0)+(i>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,rt),i=(i=Math.imul(B,nt))+Math.imul(N,rt)|0,a=Math.imul(N,nt),n=n+Math.imul(z,at)|0,i=(i=i+Math.imul(z,ot)|0)+Math.imul(R,at)|0,a=a+Math.imul(R,ot)|0,n=n+Math.imul(O,lt)|0,i=(i=i+Math.imul(O,ut)|0)+Math.imul(I,lt)|0,a=a+Math.imul(I,ut)|0,n=n+Math.imul(L,ft)|0,i=(i=i+Math.imul(L,ht)|0)+Math.imul(C,ft)|0,a=a+Math.imul(C,ht)|0;var Ct=(u+(n=n+Math.imul(M,dt)|0)|0)+((8191&(i=(i=i+Math.imul(M,vt)|0)+Math.imul(S,dt)|0))<<13)|0;u=((a=a+Math.imul(S,vt)|0)+(i>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,at),i=(i=Math.imul(B,ot))+Math.imul(N,at)|0,a=Math.imul(N,ot),n=n+Math.imul(z,lt)|0,i=(i=i+Math.imul(z,ut)|0)+Math.imul(R,lt)|0,a=a+Math.imul(R,ut)|0,n=n+Math.imul(O,ft)|0,i=(i=i+Math.imul(O,ht)|0)+Math.imul(I,ft)|0,a=a+Math.imul(I,ht)|0;var Pt=(u+(n=n+Math.imul(L,dt)|0)|0)+((8191&(i=(i=i+Math.imul(L,vt)|0)+Math.imul(C,dt)|0))<<13)|0;u=((a=a+Math.imul(C,vt)|0)+(i>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,lt),i=(i=Math.imul(B,ut))+Math.imul(N,lt)|0,a=Math.imul(N,ut),n=n+Math.imul(z,ft)|0,i=(i=i+Math.imul(z,ht)|0)+Math.imul(R,ft)|0,a=a+Math.imul(R,ht)|0;var Ot=(u+(n=n+Math.imul(O,dt)|0)|0)+((8191&(i=(i=i+Math.imul(O,vt)|0)+Math.imul(I,dt)|0))<<13)|0;u=((a=a+Math.imul(I,vt)|0)+(i>>>13)|0)+(Ot>>>26)|0,Ot&=67108863,n=Math.imul(B,ft),i=(i=Math.imul(B,ht))+Math.imul(N,ft)|0,a=Math.imul(N,ht);var It=(u+(n=n+Math.imul(z,dt)|0)|0)+((8191&(i=(i=i+Math.imul(z,vt)|0)+Math.imul(R,dt)|0))<<13)|0;u=((a=a+Math.imul(R,vt)|0)+(i>>>13)|0)+(It>>>26)|0,It&=67108863;var Dt=(u+(n=Math.imul(B,dt))|0)+((8191&(i=(i=Math.imul(B,vt))+Math.imul(N,dt)|0))<<13)|0;return u=((a=Math.imul(N,vt))+(i>>>13)|0)+(Dt>>>26)|0,Dt&=67108863,l[0]=gt,l[1]=yt,l[2]=mt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=Tt,l[8]=kt,l[9]=At,l[10]=Mt,l[11]=St,l[12]=Et,l[13]=Lt,l[14]=Ct,l[15]=Pt,l[16]=Ot,l[17]=It,l[18]=Dt,0!==u&&(l[19]=u,r.length++),r};function v(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(d=p),a.prototype.mulTo=function(t,e){var r,n=this.length+t.length;return r=10===this.length&&10===t.length?d(this,t,e):n<63?p(this,t,e):n<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,i=0,a=0;a<r.length-1;a++){var o=i;i=0;for(var s=67108863&n,l=Math.min(a,e.length-1),u=Math.max(0,a-t.length+1);u<=l;u++){var c=a-u,f=(0|t.words[c])*(0|e.words[u]),h=67108863&f;s=67108863&(h=h+s|0),i+=(o=(o=o+(f/67108864|0)|0)+(h>>>26)|0)>>>26,o&=67108863}r.words[a]=s,n=o,o=i}return 0!==n?r.words[a]=n:r.length--,r.strip()}(this,t,e):v(this,t,e),r},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=a.prototype._countBits(t)-1,n=0;n<t;n++)e[n]=this.revBin(n,r,t);return e},g.prototype.revBin=function(t,e,r){if(0===t||t===r-1)return t;for(var n=0,i=0;i<e;i++)n|=(1&t)<<e-i-1,t>>=1;return n},g.prototype.permute=function(t,e,r,n,i,a){for(var o=0;o<a;o++)n[o]=e[t[o]],i[o]=r[t[o]]},g.prototype.transform=function(t,e,r,n,i,a){this.permute(a,t,e,r,n,i);for(var o=1;o<i;o<<=1)for(var s=o<<1,l=Math.cos(2*Math.PI/s),u=Math.sin(2*Math.PI/s),c=0;c<i;c+=s)for(var f=l,h=u,p=0;p<o;p++){var d=r[c+p],v=n[c+p],g=r[c+p+o],y=n[c+p+o],m=f*g-h*y;y=f*y+h*g,g=m,r[c+p]=d+g,n[c+p]=v+y,r[c+p+o]=d-g,n[c+p+o]=v-y,p!==s&&(m=l*f-u*h,h=l*h+u*f,f=m)}},g.prototype.guessLen13b=function(t,e){var r=1|Math.max(e,t),n=1&r,i=0;for(r=r/2|0;r;r>>>=1)i++;return 1<<i+1+n},g.prototype.conjugate=function(t,e,r){if(!(r<=1))for(var n=0;n<r/2;n++){var i=t[n];t[n]=t[r-n-1],t[r-n-1]=i,i=e[n],e[n]=-e[r-n-1],e[r-n-1]=-i}},g.prototype.normalize13b=function(t,e){for(var r=0,n=0;n<e/2;n++){var i=8192*Math.round(t[2*n+1]/e)+Math.round(t[2*n]/e)+r;t[n]=67108863&i,r=i<67108864?0:i/67108864|0}return t},g.prototype.convert13b=function(t,e,r,i){for(var a=0,o=0;o<e;o++)a+=0|t[o],r[2*o]=8191&a,a>>>=13,r[2*o+1]=8191&a,a>>>=13;for(o=2*e;o<i;++o)r[o]=0;n(0===a),n(0==(-8192&a))},g.prototype.stub=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=0;return e},g.prototype.mulp=function(t,e,r){var n=2*this.guessLen13b(t.length,e.length),i=this.makeRBT(n),a=this.stub(n),o=new Array(n),s=new Array(n),l=new Array(n),u=new Array(n),c=new Array(n),f=new Array(n),h=r.words;h.length=n,this.convert13b(t.words,t.length,o,n),this.convert13b(e.words,e.length,u,n),this.transform(o,a,s,l,n,i),this.transform(u,a,c,f,n,i);for(var p=0;p<n;p++){var d=s[p]*c[p]-l[p]*f[p];l[p]=s[p]*f[p]+l[p]*c[p],s[p]=d}return this.conjugate(s,l,n),this.transform(s,l,h,a,n,i),this.conjugate(h,a,n),this.normalize13b(h,n),r.negative=t.negative^e.negative,r.length=t.length+e.length,r.strip()},a.prototype.mul=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},a.prototype.mulf=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),v(this,t,e)},a.prototype.imul=function(t){return this.clone().mulTo(t,this)},a.prototype.imuln=function(t){n(\"number\"==typeof t),n(t<67108864);for(var e=0,r=0;r<this.length;r++){var i=(0|this.words[r])*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[r]=67108863&a}return 0!==e&&(this.words[r]=e,this.length++),this},a.prototype.muln=function(t){return this.clone().imuln(t)},a.prototype.sqr=function(){return this.mul(this)},a.prototype.isqr=function(){return this.imul(this.clone())},a.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r<e.length;r++){var n=r/26|0,i=r%26;e[r]=(t.words[n]&1<<i)>>>i}return e}(t);if(0===e.length)return new a(1);for(var r=this,n=0;n<e.length&&0===e[n];n++,r=r.sqr());if(++n<e.length)for(var i=r.sqr();n<e.length;n++,i=i.sqr())0!==e[n]&&(r=r.mul(i));return r},a.prototype.iushln=function(t){n(\"number\"==typeof t&&t>=0);var e,r=t%26,i=(t-r)/26,a=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e<this.length;e++){var s=this.words[e]&a,l=(0|this.words[e])-s<<r;this.words[e]=l|o,o=s>>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==i){for(e=this.length-1;e>=0;e--)this.words[e+i]=this.words[e];for(e=0;e<i;e++)this.words[e]=0;this.length+=i}return this.strip()},a.prototype.ishln=function(t){return n(0===this.negative),this.iushln(t)},a.prototype.iushrn=function(t,e,r){var i;n(\"number\"==typeof t&&t>=0),i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<<a,l=r;if(i-=o,i=Math.max(0,i),l){for(var u=0;u<o;u++)l.words[u]=this.words[u];l.length=o}if(0===o);else if(this.length>o)for(this.length-=o,u=0;u<this.length;u++)this.words[u]=this.words[u+o];else this.words[0]=0,this.length=1;var c=0;for(u=this.length-1;u>=0&&(0!==c||u>=i);u--){var f=0|this.words[u];this.words[u]=c<<26-a|f>>>a,c=f&s}return l&&0!==c&&(l.words[l.length++]=c),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},a.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},a.prototype.shln=function(t){return this.clone().ishln(t)},a.prototype.ushln=function(t){return this.clone().iushln(t)},a.prototype.shrn=function(t){return this.clone().ishrn(t)},a.prototype.ushrn=function(t){return this.clone().iushrn(t)},a.prototype.testn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,i=1<<e;return!(this.length<=r||!(this.words[r]&i))},a.prototype.imaskn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,\"imaskn works only with positive numbers\"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},a.prototype.maskn=function(t){return this.clone().imaskn(t)},a.prototype.iaddn=function(t){return n(\"number\"==typeof t),n(t<67108864),t<0?this.isubn(-t):0!==this.negative?1===this.length&&(0|this.words[0])<t?(this.words[0]=t-(0|this.words[0]),this.negative=0,this):(this.negative=0,this.isubn(t),this.negative=1,this):this._iaddn(t)},a.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},a.prototype.isubn=function(t){if(n(\"number\"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},a.prototype.addn=function(t){return this.clone().iaddn(t)},a.prototype.subn=function(t){return this.clone().isubn(t)},a.prototype.iabs=function(){return this.negative=0,this},a.prototype.abs=function(){return this.clone().iabs()},a.prototype._ishlnsubmul=function(t,e,r){var i,a,o=t.length+r;this._expand(o);var s=0;for(i=0;i<t.length;i++){a=(0|this.words[i+r])+s;var l=(0|t.words[i])*e;s=((a-=67108863&l)>>26)-(l/67108864|0),this.words[i+r]=67108863&a}for(;i<this.length-r;i++)s=(a=(0|this.words[i+r])+s)>>26,this.words[i+r]=67108863&a;if(0===s)return this.strip();for(n(-1===s),s=0,i=0;i<this.length;i++)s=(a=-(0|this.words[i])+s)>>26,this.words[i]=67108863&a;return this.negative=1,this.strip()},a.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),i=t,o=0|i.words[i.length-1];0!=(r=26-this._countBits(o))&&(i=i.ushln(r),n.iushln(r),o=0|i.words[i.length-1]);var s,l=n.length-i.length;if(\"mod\"!==e){(s=new a(null)).length=l+1,s.words=new Array(s.length);for(var u=0;u<s.length;u++)s.words[u]=0}var c=n.clone()._ishlnsubmul(i,1,l);0===c.negative&&(n=c,s&&(s.words[l]=1));for(var f=l-1;f>=0;f--){var h=67108864*(0|n.words[i.length+f])+(0|n.words[i.length+f-1]);for(h=Math.min(h/o|0,67108863),n._ishlnsubmul(i,h,f);0!==n.negative;)h--,n.negative=0,n._ishlnsubmul(i,1,f),n.isZero()||(n.negative^=1);s&&(s.words[f]=h)}return s&&s.strip(),n.strip(),\"div\"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},a.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new a(0),mod:new a(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),\"mod\"!==e&&(i=s.div.neg()),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:i,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),\"mod\"!==e&&(i=s.div.neg()),{div:i,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new a(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new a(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new a(this.modn(t.words[0]))}:this._wordDiv(t,e);var i,o,s},a.prototype.div=function(t){return this.divmod(t,\"div\",!1).div},a.prototype.mod=function(t){return this.divmod(t,\"mod\",!1).mod},a.prototype.umod=function(t){return this.divmod(t,\"mod\",!0).mod},a.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},a.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,i=this.length-1;i>=0;i--)r=(e*r+(0|this.words[i]))%t;return r},a.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var i=(0|this.words[r])+67108864*e;this.words[r]=i/t|0,e=i%t}return this.strip()},a.prototype.divn=function(t){return this.clone().idivn(t)},a.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i=new a(1),o=new a(0),s=new a(0),l=new a(1),u=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++u;for(var c=r.clone(),f=e.clone();!e.isZero();){for(var h=0,p=1;0==(e.words[0]&p)&&h<26;++h,p<<=1);if(h>0)for(e.iushrn(h);h-- >0;)(i.isOdd()||o.isOdd())&&(i.iadd(c),o.isub(f)),i.iushrn(1),o.iushrn(1);for(var d=0,v=1;0==(r.words[0]&v)&&d<26;++d,v<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(c),l.isub(f)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),i.isub(s),o.isub(l)):(r.isub(e),s.isub(i),l.isub(o))}return{a:s,b:l,gcd:r.iushln(u)}},a.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i,o=new a(1),s=new a(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var u=0,c=1;0==(e.words[0]&c)&&u<26;++u,c<<=1);if(u>0)for(e.iushrn(u);u-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var f=0,h=1;0==(r.words[0]&h)&&f<26;++f,h<<=1);if(f>0)for(r.iushrn(f);f-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);e.cmp(r)>=0?(e.isub(r),o.isub(s)):(r.isub(e),s.isub(o))}return(i=0===e.cmpn(1)?o:s).cmpn(0)<0&&i.iadd(t),i},a.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},a.prototype.invm=function(t){return this.egcd(t).a.umod(t)},a.prototype.isEven=function(){return 0==(1&this.words[0])},a.prototype.isOdd=function(){return 1==(1&this.words[0])},a.prototype.andln=function(t){return this.words[0]&t},a.prototype.bincn=function(t){n(\"number\"==typeof t);var e=t%26,r=(t-e)/26,i=1<<e;if(this.length<=r)return this._expand(r+1),this.words[r]|=i,this;for(var a=i,o=r;0!==a&&o<this.length;o++){var s=0|this.words[o];a=(s+=a)>>>26,s&=67108863,this.words[o]=s}return 0!==a&&(this.words[o]=a,this.length++),this},a.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},a.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,\"Number is too big\");var i=0|this.words[0];e=i===t?0:i<t?-1:1}return 0!==this.negative?0|-e:e},a.prototype.cmp=function(t){if(0!==this.negative&&0===t.negative)return-1;if(0===this.negative&&0!==t.negative)return 1;var e=this.ucmp(t);return 0!==this.negative?0|-e:e},a.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=0|this.words[r],i=0|t.words[r];if(n!==i){n<i?e=-1:n>i&&(e=1);break}}return e},a.prototype.gtn=function(t){return 1===this.cmpn(t)},a.prototype.gt=function(t){return 1===this.cmp(t)},a.prototype.gten=function(t){return this.cmpn(t)>=0},a.prototype.gte=function(t){return this.cmp(t)>=0},a.prototype.ltn=function(t){return-1===this.cmpn(t)},a.prototype.lt=function(t){return-1===this.cmp(t)},a.prototype.lten=function(t){return this.cmpn(t)<=0},a.prototype.lte=function(t){return this.cmp(t)<=0},a.prototype.eqn=function(t){return 0===this.cmpn(t)},a.prototype.eq=function(t){return 0===this.cmp(t)},a.red=function(t){return new T(t)},a.prototype.toRed=function(t){return n(!this.red,\"Already a number in reduction context\"),n(0===this.negative,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},a.prototype.fromRed=function(){return n(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},a.prototype._forceRed=function(t){return this.red=t,this},a.prototype.forceRed=function(t){return n(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},a.prototype.redAdd=function(t){return n(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},a.prototype.redIAdd=function(t){return n(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},a.prototype.redSub=function(t){return n(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},a.prototype.redISub=function(t){return n(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},a.prototype.redShl=function(t){return n(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},a.prototype.redMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},a.prototype.redIMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},a.prototype.redSqr=function(){return n(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},a.prototype.redISqr=function(){return n(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},a.prototype.redSqrt=function(){return n(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},a.prototype.redInvm=function(){return n(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},a.prototype.redNeg=function(){return n(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},a.prototype.redPow=function(t){return n(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var y={k256:null,p224:null,p192:null,p25519:null};function m(t,e){this.name=t,this.p=new a(e,16),this.n=this.p.bitLength(),this.k=new a(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}function x(){m.call(this,\"k256\",\"ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f\")}function b(){m.call(this,\"p224\",\"ffffffff ffffffff ffffffff ffffffff 00000000 00000000 00000001\")}function _(){m.call(this,\"p192\",\"ffffffff ffffffff ffffffff fffffffe ffffffff ffffffff\")}function w(){m.call(this,\"25519\",\"7fffffffffffffff ffffffffffffffff ffffffffffffffff ffffffffffffffed\")}function T(t){if(\"string\"==typeof t){var e=a._prime(t);this.m=e.p,this.prime=e}else n(t.gtn(1),\"modulus must be greater than 1\"),this.m=t,this.prime=null}function k(t){T.call(this,t),this.shift=this.m.bitLength(),this.shift%26!=0&&(this.shift+=26-this.shift%26),this.r=new a(1).iushln(this.shift),this.r2=this.imod(this.r.sqr()),this.rinv=this.r._invmp(this.m),this.minv=this.rinv.mul(this.r).isubn(1).div(this.m),this.minv=this.minv.umod(this.r),this.minv=this.r.sub(this.minv)}m.prototype._tmp=function(){var t=new a(null);return t.words=new Array(Math.ceil(this.n/13)),t},m.prototype.ireduce=function(t){var e,r=t;do{this.split(r,this.tmp),e=(r=(r=this.imulK(r)).iadd(this.tmp)).bitLength()}while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):void 0!==r.strip?r.strip():r._strip(),r},m.prototype.split=function(t,e){t.iushrn(this.n,0,e)},m.prototype.imulK=function(t){return t.imul(this.k)},i(x,m),x.prototype.split=function(t,e){for(var r=4194303,n=Math.min(t.length,9),i=0;i<n;i++)e.words[i]=t.words[i];if(e.length=n,t.length<=9)return t.words[0]=0,void(t.length=1);var a=t.words[9];for(e.words[e.length++]=a&r,i=10;i<t.length;i++){var o=0|t.words[i];t.words[i-10]=(o&r)<<4|a>>>22,a=o}a>>>=22,t.words[i-10]=a,0===a&&t.length>10?t.length-=10:t.length-=9},x.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e=0,r=0;r<t.length;r++){var n=0|t.words[r];e+=977*n,t.words[r]=67108863&e,e=64*n+(e/67108864|0)}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},i(b,m),i(_,m),i(w,m),w.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*(0|t.words[r])+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},a._prime=function(t){if(y[t])return y[t];var e;if(\"k256\"===t)e=new x;else if(\"p224\"===t)e=new b;else if(\"p192\"===t)e=new _;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);e=new w}return y[t]=e,e},T.prototype._verify1=function(t){n(0===t.negative,\"red works only with positives\"),n(t.red,\"red works only with red numbers\")},T.prototype._verify2=function(t,e){n(0==(t.negative|e.negative),\"red works only with positives\"),n(t.red&&t.red===e.red,\"red works only with red numbers\")},T.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.umod(this.m)._forceRed(this)},T.prototype.neg=function(t){return t.isZero()?t.clone():this.m.sub(t)._forceRed(this)},T.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},T.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},T.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},T.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},T.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.ushln(e))},T.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},T.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},T.prototype.isqr=function(t){return this.imul(t,t.clone())},T.prototype.sqr=function(t){return this.mul(t,t)},T.prototype.sqrt=function(t){if(t.isZero())return t.clone();var e=this.m.andln(3);if(n(e%2==1),3===e){var r=this.m.add(new a(1)).iushrn(2);return this.pow(t,r)}for(var i=this.m.subn(1),o=0;!i.isZero()&&0===i.andln(1);)o++,i.iushrn(1);n(!i.isZero());var s=new a(1).toRed(this),l=s.redNeg(),u=this.m.subn(1).iushrn(1),c=this.m.bitLength();for(c=new a(2*c*c).toRed(this);0!==this.pow(c,u).cmp(l);)c.redIAdd(l);for(var f=this.pow(c,i),h=this.pow(t,i.addn(1).iushrn(1)),p=this.pow(t,i),d=o;0!==p.cmp(s);){for(var v=p,g=0;0!==v.cmp(s);g++)v=v.redSqr();n(g<d);var y=this.pow(f,new a(1).iushln(d-g-1));h=h.redMul(y),f=y.redSqr(),p=p.redMul(f),d=g}return h},T.prototype.invm=function(t){var e=t._invmp(this.m);return 0!==e.negative?(e.negative=0,this.imod(e).redNeg()):this.imod(e)},T.prototype.pow=function(t,e){if(e.isZero())return new a(1).toRed(this);if(0===e.cmpn(1))return t.clone();var r=new Array(16);r[0]=new a(1).toRed(this),r[1]=t;for(var n=2;n<r.length;n++)r[n]=this.mul(r[n-1],t);var i=r[0],o=0,s=0,l=e.bitLength()%26;for(0===l&&(l=26),n=e.length-1;n>=0;n--){for(var u=e.words[n],c=l-1;c>=0;c--){var 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s=(o=a.left=r(o)).right=r(o.right),a.left=s.right,o.right=s.left,s.right=a,s.left=o,s._color=a._color,a._color=1,o._color=1,e._color=1,i(a),i(o),i(s),l>1&&((u=t[l-2]).right===a?u.right=s:u.left=s),void(t[l-1]=s);if(1===o._color){if(0===a._color)return a._color=1,void(a.left=n(0,o));a.left=n(0,o);continue}var u;o=r(o),a.left=o.right,o.right=a,o._color=a._color,a._color=0,i(a),i(o),l>1&&((u=t[l-2]).right===a?u.right=o:u.left=o),t[l-1]=o,t[l]=a,l+1<t.length?t[l+1]=e:t.push(e),l+=2}}}(o),p.left===s?p.left=null:p.right=null,new a(this.tree._compare,o[0])},Object.defineProperty(f,\"key\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].key},enumerable:!0}),Object.defineProperty(f,\"value\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].value},enumerable:!0}),Object.defineProperty(f,\"index\",{get:function(){var t=0,e=this._stack;if(0===e.length){var r=this.tree.root;return r?r._count:0}e[e.length-1].left&&(t=e[e.length-1].left._count);for(var n=e.length-2;n>=0;--n)e[n+1]===e[n].right&&(++t,e[n].left&&(t+=e[n].left._count));return t},enumerable:!0}),f.next=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.right)for(e=e.right;e;)t.push(e),e=e.left;else for(t.pop();t.length>0&&t[t.length-1].right===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(f,\"hasNext\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].right)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].left===t[e])return!0;return!1}}),f.update=function(t){var r=this._stack;if(0===r.length)throw new Error(\"Can't update empty node!\");var n=new Array(r.length),i=r[r.length-1];n[n.length-1]=new e(i._color,i.key,t,i.left,i.right,i._count);for(var o=r.length-2;o>=0;--o)(i=r[o]).left===r[o+1]?n[o]=new e(i._color,i.key,i.value,n[o+1],i.right,i._count):n[o]=new e(i._color,i.key,i.value,i.left,n[o+1],i._count);return new a(this.tree._compare,n[0])},f.prev=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.left)for(e=e.left;e;)t.push(e),e=e.right;else for(t.pop();t.length>0&&t[t.length-1].left===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(f,\"hasPrev\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].left)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].right===t[e])return!0;return!1}})},7453:function(t,e,r){\"use strict\";t.exports=function(t,e){var r=new c(t);return r.update(e),r};var n=r(9557),i=r(1681),a=r(1011),o=r(2864),s=r(8468),l=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]);function u(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function c(t){this.gl=t,this.pixelRatio=1,this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.autoTicks=!0,this.tickSpacing=[1,1,1],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickAlign=[\"auto\",\"auto\",\"auto\"],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[10,10,10],this.lastCubeProps={cubeEdges:[0,0,0],axis:[0,0,0]},this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=\"sans-serif\",this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelAlign=[\"auto\",\"auto\",\"auto\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[10,10,10],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[0,0,0],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!1,!1,!1],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._firstInit=!0,this._text=null,this._lines=null,this._background=a(t)}var f=c.prototype;function h(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}f.update=function(t){function e(e,r,n){if(n in t){var i,a=t[n],o=this[n];(e?Array.isArray(a)&&Array.isArray(a[0]):Array.isArray(a))?this[n]=i=[r(a[0]),r(a[1]),r(a[2])]:this[n]=i=[r(a),r(a),r(a)];for(var s=0;s<3;++s)if(i[s]!==o[s])return!0}return!1}t=t||{};var r,a=e.bind(this,!1,Number),o=e.bind(this,!1,Boolean),l=e.bind(this,!1,String),u=e.bind(this,!0,(function(t){if(Array.isArray(t)){if(3===t.length)return[+t[0],+t[1],+t[2],1];if(4===t.length)return[+t[0],+t[1],+t[2],+t[3]]}return[0,0,0,1]})),c=!1,f=!1;if(\"bounds\"in t)for(var h=t.bounds,p=0;p<2;++p)for(var d=0;d<3;++d)h[p][d]!==this.bounds[p][d]&&(f=!0),this.bounds[p][d]=h[p][d];if(\"ticks\"in t)for(r=t.ticks,c=!0,this.autoTicks=!1,p=0;p<3;++p)this.tickSpacing[p]=0;else a(\"tickSpacing\")&&(this.autoTicks=!0,f=!0);if(this._firstInit&&(\"ticks\"in t||\"tickSpacing\"in t||(this.autoTicks=!0),f=!0,c=!0,this._firstInit=!1),f&&this.autoTicks&&(r=s.create(this.bounds,this.tickSpacing),c=!0),c){for(p=0;p<3;++p)r[p].sort((function(t,e){return t.x-e.x}));s.equal(r,this.ticks)?c=!1:this.ticks=r}o(\"tickEnable\"),l(\"tickFont\")&&(c=!0),a(\"tickSize\"),a(\"tickAngle\"),a(\"tickPad\"),u(\"tickColor\");var v=l(\"labels\");l(\"labelFont\")&&(v=!0),o(\"labelEnable\"),a(\"labelSize\"),a(\"labelPad\"),u(\"labelColor\"),o(\"lineEnable\"),o(\"lineMirror\"),a(\"lineWidth\"),u(\"lineColor\"),o(\"lineTickEnable\"),o(\"lineTickMirror\"),a(\"lineTickLength\"),a(\"lineTickWidth\"),u(\"lineTickColor\"),o(\"gridEnable\"),a(\"gridWidth\"),u(\"gridColor\"),o(\"zeroEnable\"),u(\"zeroLineColor\"),a(\"zeroLineWidth\"),o(\"backgroundEnable\"),u(\"backgroundColor\"),this._text?this._text&&(v||c)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=n(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&c&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=i(this.gl,this.bounds,this.ticks))};var p=[new h,new h,new h];function d(t,e,r,n,i){for(var a=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,u=n[e],c=0;c<3;++c)if(e!==c){var f=a,h=s,p=o,d=l;u&1<<c&&(f=s,h=a,p=l,d=o),f[c]=r[0][c],h[c]=r[1][c],i[c]>0?(p[c]=-1,d[c]=0):(p[c]=0,d[c]=1)}}var v=[0,0,0],g={model:l,view:l,projection:l,_ortho:!1};f.isOpaque=function(){return!0},f.isTransparent=function(){return!1},f.drawTransparent=function(t){};var y=[0,0,0],m=[0,0,0],x=[0,0,0];f.draw=function(t){t=t||g;for(var e=this.gl,r=t.model||l,n=t.view||l,i=t.projection||l,a=this.bounds,s=t._ortho||!1,c=o(r,n,i,a,s),f=c.cubeEdges,h=c.axis,b=n[12],_=n[13],w=n[14],T=n[15],k=(s?2:1)*this.pixelRatio*(i[3]*b+i[7]*_+i[11]*w+i[15]*T)/e.drawingBufferHeight,A=0;A<3;++A)this.lastCubeProps.cubeEdges[A]=f[A],this.lastCubeProps.axis[A]=h[A];var M=p;for(A=0;A<3;++A)d(p[A],A,this.bounds,f,h);e=this.gl;var S,E,L,C=v;for(A=0;A<3;++A)this.backgroundEnable[A]?C[A]=h[A]:C[A]=0;for(this._background.draw(r,n,i,a,C,this.backgroundColor),this._lines.bind(r,n,i,this),A=0;A<3;++A){var P=[0,0,0];h[A]>0?P[A]=a[1][A]:P[A]=a[0][A];for(var O=0;O<2;++O){var I=(A+1+O)%3,D=(A+1+(1^O))%3;this.gridEnable[I]&&this._lines.drawGrid(I,D,this.bounds,P,this.gridColor[I],this.gridWidth[I]*this.pixelRatio)}for(O=0;O<2;++O)I=(A+1+O)%3,D=(A+1+(1^O))%3,this.zeroEnable[D]&&Math.min(a[0][D],a[1][D])<=0&&Math.max(a[0][D],a[1][D])>=0&&this._lines.drawZero(I,D,this.bounds,P,this.zeroLineColor[D],this.zeroLineWidth[D]*this.pixelRatio)}for(A=0;A<3;++A){this.lineEnable[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].primalOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio),this.lineMirror[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].mirrorOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio);var z=u(y,M[A].primalMinor),R=u(m,M[A].mirrorMinor),F=this.lineTickLength;for(O=0;O<3;++O){var B=k/r[5*O];z[O]*=F[O]*B,R[O]*=F[O]*B}this.lineTickEnable[A]&&this._lines.drawAxisTicks(A,M[A].primalOffset,z,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio),this.lineTickMirror[A]&&this._lines.drawAxisTicks(A,M[A].mirrorOffset,R,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio)}function N(t){(L=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,i=(t+2)%3,a=e[n],o=e[i],s=r[n],l=r[i];a>0&&l>0||a>0&&l<0||a<0&&l>0||a<0&&l<0?N(n):(o>0&&s>0||o>0&&s<0||o<0&&s>0||o<0&&s<0)&&N(i)}for(this._lines.unbind(),this._text.bind(r,n,i,this.pixelRatio),A=0;A<3;++A){var U=M[A].primalMinor,V=M[A].mirrorMinor,H=u(x,M[A].primalOffset);for(O=0;O<3;++O)this.lineTickEnable[A]&&(H[O]+=k*U[O]*Math.max(this.lineTickLength[O],0)/r[5*O]);var q=[0,0,0];if(q[A]=1,this.tickEnable[A]){for(-3600===this.tickAngle[A]?(this.tickAngle[A]=0,this.tickAlign[A]=\"auto\"):this.tickAlign[A]=-1,E=1,\"auto\"===(S=[this.tickAlign[A],.5,E])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),L=[0,0,0],j(A,U,V),O=0;O<3;++O)H[O]+=k*U[O]*this.tickPad[O]/r[5*O];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],H,this.tickColor[A],q,L,S)}if(this.labelEnable[A]){for(E=0,L=[0,0,0],this.labels[A].length>4&&(N(A),E=1),\"auto\"===(S=[this.labelAlign[A],.5,E])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),O=0;O<3;++O)H[O]+=k*U[O]*this.labelPad[O]/r[5*O];H[A]+=.5*(a[0][A]+a[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],H,this.labelColor[A],[0,0,0],L,S)}}this._text.unbind()},f.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},1011:function(t,e,r){\"use strict\";t.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var u=(l+1)%3,c=(l+2)%3,f=[0,0,0],h=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),f[l]=p,h[l]=p;for(var d=-1;d<=1;d+=2){f[u]=d;for(var v=-1;v<=1;v+=2)f[c]=v,e.push(f[0],f[1],f[2],h[0],h[1],h[2]),s+=1}var g=u;u=c,c=g}var y=n(t,new Float32Array(e)),m=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=i(t,[{buffer:y,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:y,type:t.FLOAT,size:3,offset:12,stride:24}],m),b=a(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,y,x,b)};var n=r(5827),i=r(2944),a=r(1943).bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,i,a){for(var o=!1,s=0;s<3;++s)o=o||i[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:i,colors:a},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},2864:function(t,e,r){\"use strict\";t.exports=function(t,e,r,a,p){i(s,e,t),i(s,r,s);for(var m=0,x=0;x<2;++x){c[2]=a[x][2];for(var b=0;b<2;++b){c[1]=a[b][1];for(var _=0;_<2;++_)c[0]=a[_][0],h(l[m],c,s),m+=1}}var w=-1;for(x=0;x<8;++x){for(var T=l[x][3],k=0;k<3;++k)u[x][k]=l[x][k]/T;p&&(u[x][2]*=-1),T<0&&(w<0||u[x][2]<u[w][2])&&(w=x)}if(w<0){w=0;for(var A=0;A<3;++A){for(var M=(A+2)%3,S=(A+1)%3,E=-1,L=-1,C=0;C<2;++C){var P=(I=C<<A)+(C<<M)+(1-C<<S),O=I+(1-C<<M)+(C<<S);o(u[I],u[P],u[O],f)<0||(C?E=1:L=1)}if(E<0||L<0)L>E&&(w|=1<<A);else{for(C=0;C<2;++C){P=(I=C<<A)+(C<<M)+(1-C<<S),O=I+(1-C<<M)+(C<<S);var I,D=d([l[I],l[P],l[O],l[I+(1<<M)+(1<<S)]]);C?E=D:L=D}L>E&&(w|=1<<A)}}}var z=7^w,R=-1;for(x=0;x<8;++x)x!==w&&x!==z&&(R<0||u[R][1]>u[x][1])&&(R=x);var F=-1;for(x=0;x<3;++x)(N=R^1<<x)!==w&&N!==z&&(F<0&&(F=N),(S=u[N])[0]<u[F][0]&&(F=N));var B=-1;for(x=0;x<3;++x){var N;(N=R^1<<x)!==w&&N!==z&&N!==F&&(B<0&&(B=N),(S=u[N])[0]>u[B][0]&&(B=N))}var j=v;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^B)]=R&B;var U=7^B;U===w||U===z?(U=7^F,j[n.log2(B^U)]=U&B):j[n.log2(F^U)]=U&F;var V=g,H=w;for(A=0;A<3;++A)V[A]=H&1<<A?-1:1;return y};var n=r(2288),i=r(104),a=r(4670),o=r(417),s=new Array(16),l=new Array(8),u=new Array(8),c=new Array(3),f=[0,0,0];function h(t,e,r){for(var n=0;n<4;++n){t[n]=r[12+n];for(var i=0;i<3;++i)t[n]+=e[i]*r[4*i+n]}}!function(){for(var t=0;t<8;++t)l[t]=[1,1,1,1],u[t]=[1,1,1]}();var p=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]];function d(t){for(var e=0;e<p.length;++e)if((t=a.positive(t,p[e])).length<3)return 0;var r=t[0],n=r[0]/r[3],i=r[1]/r[3],o=0;for(e=1;e+1<t.length;++e){var s=t[e],l=t[e+1],u=s[0]/s[3]-n,c=s[1]/s[3]-i,f=l[0]/l[3]-n,h=l[1]/l[3]-i;o+=Math.abs(u*h-c*f)}return o}var v=[1,1,1],g=[0,0,0],y={cubeEdges:v,axis:g}},1681:function(t,e,r){\"use strict\";t.exports=function(t,e,r){var o=[],s=[0,0,0],l=[0,0,0],u=[0,0,0],c=[0,0,0];o.push(0,0,1,0,1,1,0,0,-1,0,0,-1,0,1,1,0,1,-1);for(var f=0;f<3;++f){for(var h=o.length/3|0,d=0;d<r[f].length;++d){var v=+r[f][d].x;o.push(v,0,1,v,1,1,v,0,-1,v,0,-1,v,1,1,v,1,-1)}var g=o.length/3|0;s[f]=h,l[f]=g-h,h=o.length/3|0;for(var y=0;y<r[f].length;++y)v=+r[f][y].x,o.push(v,0,1,v,1,1,v,0,-1,v,0,-1,v,1,1,v,1,-1);g=o.length/3|0,u[f]=h,c[f]=g-h}var m=n(t,new Float32Array(o)),x=i(t,[{buffer:m,type:t.FLOAT,size:3,stride:0,offset:0}]),b=a(t);return b.attributes.position.location=0,new p(t,m,x,b,l,s,c,u)};var n=r(5827),i=r(2944),a=r(1943).j,o=[0,0,0],s=[0,0,0],l=[0,0,0],u=[0,0,0],c=[1,1];function f(t){return t[0]=t[1]=t[2]=0,t}function h(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function p(t,e,r,n,i,a,o,s){this.gl=t,this.vertBuffer=e,this.vao=r,this.shader=n,this.tickCount=i,this.tickOffset=a,this.gridCount=o,this.gridOffset=s}var d=p.prototype;d.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,c[0]=this.gl.drawingBufferWidth,c[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=c,this.vao.bind()},d.unbind=function(){this.vao.unbind()},d.drawAxisLine=function(t,e,r,n,i){var a=f(s);this.shader.uniforms.majorAxis=s,a[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=a;var o,c=h(u,r);c[t]+=e[0][t],this.shader.uniforms.offset=c,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=n,(o=f(l))[(t+2)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6),(o=f(l))[(t+1)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6)},d.drawAxisTicks=function(t,e,r,n,i){if(this.tickCount[t]){var a=f(o);a[t]=1,this.shader.uniforms.majorAxis=a,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=n,this.shader.uniforms.lineWidth=i;var s=f(l);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},d.drawGrid=function(t,e,r,n,i,a){if(this.gridCount[t]){var c=f(s);c[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=c;var p=h(u,n);p[e]+=r[0][e],this.shader.uniforms.offset=p;var d=f(o);d[t]=1,this.shader.uniforms.majorAxis=d;var v=f(l);v[t]=1,this.shader.uniforms.screenAxis=v,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},d.drawZero=function(t,e,r,n,i,a){var o=f(s);this.shader.uniforms.majorAxis=o,o[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=o;var c=h(u,n);c[t]+=r[0][t],this.shader.uniforms.offset=c;var p=f(l);p[e]=1,this.shader.uniforms.screenAxis=p,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,6)},d.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},1943:function(t,e,r){\"use strict\";var n=r(6832),i=r(5158),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\\nuniform float lineWidth;\\nuniform vec2 screenShape;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nvoid main() {\\n  vec3 major = position.x * majorAxis;\\n  vec3 minor = position.y * minorAxis;\\n\\n  vec3 vPosition = major + minor + offset;\\n  vec3 pPosition = project(vPosition);\\n  vec3 offset = project(vPosition + screenAxis * position.z);\\n\\n  vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\\n\\n  gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);e.j=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"}])};var s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, axis, alignDir, alignOpt;\\nuniform float scale, angle, pixelScale;\\nuniform vec2 resolution;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nfloat computeViewAngle(vec3 a, vec3 b) {\\n  vec3 A = project(a);\\n  vec3 B = project(b);\\n\\n  return atan(\\n    (B.y - A.y) * resolution.y,\\n    (B.x - A.x) * resolution.x\\n  );\\n}\\n\\nconst float PI = 3.141592;\\nconst float TWO_PI = 2.0 * PI;\\nconst float HALF_PI = 0.5 * PI;\\nconst float ONE_AND_HALF_PI = 1.5 * PI;\\n\\nint option = int(floor(alignOpt.x + 0.001));\\nfloat hv_ratio =       alignOpt.y;\\nbool enableAlign =    (alignOpt.z != 0.0);\\n\\nfloat mod_angle(float a) {\\n  return mod(a, PI);\\n}\\n\\nfloat positive_angle(float a) {\\n  return mod_angle((a < 0.0) ?\\n    a + TWO_PI :\\n    a\\n  );\\n}\\n\\nfloat look_upwards(float a) {\\n  float b = positive_angle(a);\\n  return ((b > HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\\n    b - PI :\\n    b;\\n}\\n\\nfloat look_horizontal_or_vertical(float a, float ratio) {\\n  // ratio controls the ratio between being horizontal to (vertical + horizontal)\\n  // if ratio is set to 0.5 then it is 50%, 50%.\\n  // when using a higher ratio e.g. 0.75 the result would\\n  // likely be more horizontal than vertical.\\n\\n  float b = positive_angle(a);\\n\\n  return\\n    (b < (      ratio) * HALF_PI) ? 0.0 :\\n    (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\\n    (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\\n    (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\\n                                    0.0;\\n}\\n\\nfloat roundTo(float a, float b) {\\n  return float(b * floor((a + 0.5 * b) / b));\\n}\\n\\nfloat look_round_n_directions(float a, int n) {\\n  float b = positive_angle(a);\\n  float div = TWO_PI / float(n);\\n  float c = roundTo(b, div);\\n  return look_upwards(c);\\n}\\n\\nfloat applyAlignOption(float rawAngle, float delta) {\\n  return\\n    (option >  2) ? look_round_n_directions(rawAngle + delta, option) :       // option 3-n: round to n directions\\n    (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\\n    (option == 1) ? rawAngle + delta :       // use free angle, and flip to align with one direction of the axis\\n    (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\\n    (option ==-1) ? 0.0 :                    // useful for backward compatibility, all texts remains horizontal\\n                    rawAngle;                // otherwise return back raw input angle\\n}\\n\\nbool isAxisTitle = (axis.x == 0.0) &&\\n                   (axis.y == 0.0) &&\\n                   (axis.z == 0.0);\\n\\nvoid main() {\\n  //Compute world offset\\n  float axisDistance = position.z;\\n  vec3 dataPosition = axisDistance * axis + offset;\\n\\n  float beta = angle; // i.e. user defined attributes for each tick\\n\\n  float axisAngle;\\n  float clipAngle;\\n  float flip;\\n\\n  if (enableAlign) {\\n    axisAngle = (isAxisTitle) ? HALF_PI :\\n                      computeViewAngle(dataPosition, dataPosition + axis);\\n    clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\\n\\n    axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\\n    clipAngle += (sin(clipAngle) < 0.0) ? PI : 0.0;\\n\\n    flip = (dot(vec2(cos(axisAngle), sin(axisAngle)),\\n                vec2(sin(clipAngle),-cos(clipAngle))) > 0.0) ? 1.0 : 0.0;\\n\\n    beta += applyAlignOption(clipAngle, flip * PI);\\n  }\\n\\n  //Compute plane offset\\n  vec2 planeCoord = position.xy * pixelScale;\\n\\n  mat2 planeXform = scale * mat2(\\n     cos(beta), sin(beta),\\n    -sin(beta), cos(beta)\\n  );\\n\\n  vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n  //Compute clip position\\n  vec3 clipPosition = project(dataPosition);\\n\\n  //Apply text offset in clip coordinates\\n  clipPosition += vec3(viewOffset, 0.0);\\n\\n  //Done\\n  gl_Position = vec4(clipPosition, 1.0);\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);e.f=function(t){return i(t,s,l,null,[{name:\"position\",type:\"vec3\"}])};var u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 enable;\\nuniform vec3 bounds[2];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n\\n  vec3 signAxis = sign(bounds[1] - bounds[0]);\\n\\n  vec3 realNormal = signAxis * normal;\\n\\n  if(dot(realNormal, enable) > 0.0) {\\n    vec3 minRange = min(bounds[0], bounds[1]);\\n    vec3 maxRange = max(bounds[0], bounds[1]);\\n    vec3 nPosition = mix(minRange, maxRange, 0.5 * (position + 1.0));\\n    gl_Position = projection * view * model * vec4(nPosition, 1.0);\\n  } else {\\n    gl_Position = vec4(0,0,0,0);\\n  }\\n\\n  colorChannel = abs(realNormal);\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 colors[3];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n  gl_FragColor = colorChannel.x * colors[0] +\\n                 colorChannel.y * colors[1] +\\n                 colorChannel.z * colors[2];\\n}\"]);e.bg=function(t){return i(t,u,c,null,[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}])}},9557:function(t,e,r){\"use strict\";t.exports=function(t,e,r,i,o,l){var u=n(t),f=a(t,[{buffer:u,size:3}]),h=s(t);h.attributes.position.location=0;var p=new c(t,h,u,f);return p.update(e,r,i,o,l),p};var n=r(5827),a=r(2944),o=r(875),s=r(1943).f,l=window||i.global||{},u=l.__TEXT_CACHE||{};function c(t,e,r,n){this.gl=t,this.shader=e,this.buffer=r,this.vao=n,this.tickOffset=this.tickCount=this.labelOffset=this.labelCount=null}l.__TEXT_CACHE={};var f=c.prototype,h=[0,0];f.bind=function(t,e,r,n){this.vao.bind(),this.shader.bind();var i=this.shader.uniforms;i.model=t,i.view=e,i.projection=r,i.pixelScale=n,h[0]=this.gl.drawingBufferWidth,h[1]=this.gl.drawingBufferHeight,this.shader.uniforms.resolution=h},f.unbind=function(){this.vao.unbind()},f.update=function(t,e,r,n,i){var a=[];function s(t,e,r,n,i,s){var l=u[r];l||(l=u[r]={});var c=l[e];c||(c=l[e]=function(t,e){try{return o(t,e)}catch(e){return console.warn('error vectorizing text:\"'+t+'\" error:',e),{cells:[],positions:[]}}}(e,{triangles:!0,font:r,textAlign:\"center\",textBaseline:\"middle\",lineSpacing:i,styletags:s}));for(var f=(n||12)/12,h=c.positions,p=c.cells,d=0,v=p.length;d<v;++d)for(var g=p[d],y=2;y>=0;--y){var m=h[g[y]];a.push(f*m[0],-f*m[1],t)}}for(var l=[0,0,0],c=[0,0,0],f=[0,0,0],h=[0,0,0],p={breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},d=0;d<3;++d){f[d]=a.length/3|0,s(.5*(t[0][d]+t[1][d]),e[d],r[d],12,1.25,p),h[d]=(a.length/3|0)-f[d],l[d]=a.length/3|0;for(var v=0;v<n[d].length;++v)n[d][v].text&&s(n[d][v].x,n[d][v].text,n[d][v].font||i,n[d][v].fontSize||12,1.25,p);c[d]=(a.length/3|0)-l[d]}this.buffer.update(a),this.tickOffset=l,this.tickCount=c,this.labelOffset=f,this.labelCount=h},f.drawTicks=function(t,e,r,n,i,a,o,s){this.tickCount[t]&&(this.shader.uniforms.axis=a,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t]))},f.drawLabel=function(t,e,r,n,i,a,o,s){this.labelCount[t]&&(this.shader.uniforms.axis=a,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.labelCount[t],this.labelOffset[t]))},f.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()}},8468:function(t,e){\"use strict\";function r(t,e){var r=t+\"\",n=r.indexOf(\".\"),i=0;n>=0&&(i=r.length-n-1);var a=Math.pow(10,i),o=Math.round(t*e*a),s=o+\"\";if(s.indexOf(\"e\")>=0)return s;var l=o/a,u=o%a;o<0?(l=0|-Math.ceil(l),u=0|-u):(l=0|Math.floor(l),u|=0);var c=\"\"+l;if(o<0&&(c=\"-\"+c),i){for(var f=\"\"+u;f.length<i;)f=\"0\"+f;return c+\".\"+f}return c}e.create=function(t,e){for(var n=[],i=0;i<3;++i){for(var a=[],o=(t[0][i],t[1][i],0);o*e[i]<=t[1][i];++o)a.push({x:o*e[i],text:r(e[i],o)});for(o=-1;o*e[i]>=t[0][i];--o)a.push({x:o*e[i],text:r(e[i],o)});n.push(a)}return n},e.equal=function(t,e){for(var r=0;r<3;++r){if(t[r].length!==e[r].length)return!1;for(var n=0;n<t[r].length;++n){var i=t[r][n],a=e[r][n];if(i.x!==a.x||i.text!==a.text||i.font!==a.font||i.fontColor!==a.fontColor||i.fontSize!==a.fontSize||i.dx!==a.dx||i.dy!==a.dy)return!1}}return!0}},2771:function(t,e,r){\"use strict\";t.exports=function(t,e,r,l,f){var h=e.model||u,p=e.view||u,y=e.projection||u,m=e._ortho||!1,x=t.bounds,b=(f=f||a(h,p,y,x,m)).axis;o(c,p,h),o(c,y,c);for(var _=v,w=0;w<3;++w)_[w].lo=1/0,_[w].hi=-1/0,_[w].pixelsPerDataUnit=1/0;var T=n(s(c,c));s(c,c);for(var k=0;k<3;++k){var A=(k+1)%3,M=(k+2)%3,S=g;t:for(w=0;w<2;++w){var E=[];if(b[k]<0!=!!w){S[k]=x[w][k];for(var L=0;L<2;++L){S[A]=x[L^w][A];for(var C=0;C<2;++C)S[M]=x[C^L^w][M],E.push(S.slice())}var P=m?5:4;for(L=P;L===P;++L){if(0===E.length)continue t;E=i.positive(E,T[L])}for(L=0;L<E.length;++L){M=E[L];var O=d(g,c,M,r,l);for(C=0;C<3;++C)_[C].lo=Math.min(_[C].lo,M[C]),_[C].hi=Math.max(_[C].hi,M[C]),C!==k&&(_[C].pixelsPerDataUnit=Math.min(_[C].pixelsPerDataUnit,Math.abs(O[C])))}}}}return _};var n=r(5795),i=r(4670),a=r(2864),o=r(104),s=r(2142),l=r(6342),u=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),c=new Float32Array(16);function f(t,e,r){this.lo=t,this.hi=e,this.pixelsPerDataUnit=r}var h=[0,0,0,1],p=[0,0,0,1];function d(t,e,r,n,i){for(var a=0;a<3;++a){for(var o=h,s=p,u=0;u<3;++u)s[u]=o[u]=r[u];s[3]=o[3]=1,s[a]+=1,l(s,s,e),s[3]<0&&(t[a]=1/0),o[a]-=1,l(o,o,e),o[3]<0&&(t[a]=1/0);var c=(o[0]/o[3]-s[0]/s[3])*n,f=(o[1]/o[3]-s[1]/s[3])*i;t[a]=.25*Math.sqrt(c*c+f*f)}return t}var v=[new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0)],g=[0,0,0]},5827:function(t,e,r){\"use strict\";var n=r(5306),i=r(7498),a=r(5050),o=[\"uint8\",\"uint8_clamped\",\"uint16\",\"uint32\",\"int8\",\"int16\",\"int32\",\"float32\"];function s(t,e,r,n,i){this.gl=t,this.type=e,this.handle=r,this.length=n,this.usage=i}var l=s.prototype;function u(t,e,r,n,i,a){var o=i.length*i.BYTES_PER_ELEMENT;if(a<0)return t.bufferData(e,i,n),o;if(o+a>r)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,a,i),r}function c(t,e){for(var r=n.malloc(t.length,e),i=t.length,a=0;a<i;++a)r[a]=t[a];return r}l.bind=function(){this.gl.bindBuffer(this.type,this.handle)},l.unbind=function(){this.gl.bindBuffer(this.type,null)},l.dispose=function(){this.gl.deleteBuffer(this.handle)},l.update=function(t,e){if(\"number\"!=typeof e&&(e=-1),this.bind(),\"object\"==typeof t&&void 0!==t.shape){var r=t.dtype;if(o.indexOf(r)<0&&(r=\"float32\"),this.type===this.gl.ELEMENT_ARRAY_BUFFER&&(r=gl.getExtension(\"OES_element_index_uint\")&&\"uint16\"!==r?\"uint32\":\"uint16\"),r===t.dtype&&function(t,e){for(var r=1,n=e.length-1;n>=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=u(this.gl,this.type,this.length,this.usage,t.data,e):this.length=u(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=a(s,t.shape);i.assign(l,t),this.length=u(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var f;f=this.type===this.gl.ELEMENT_ARRAY_BUFFER?c(t,\"uint16\"):c(t,\"float32\"),this.length=u(this.gl,this.type,this.length,this.usage,e<0?f:f.subarray(0,t.length),e),n.free(f)}else if(\"object\"==typeof t&&\"number\"==typeof t.length)this.length=u(this.gl,this.type,this.length,this.usage,t,e);else{if(\"number\"!=typeof t&&void 0!==t)throw new Error(\"gl-buffer: Invalid data type\");if(e>=0)throw new Error(\"gl-buffer: Cannot specify offset when resizing buffer\");(t|=0)<=0&&(t=1),this.gl.bufferData(this.type,0|t,this.usage),this.length=t}},t.exports=function(t,e,r,n){if(r=r||t.ARRAY_BUFFER,n=n||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error(\"gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER\");if(n!==t.DYNAMIC_DRAW&&n!==t.STATIC_DRAW&&n!==t.STREAM_DRAW)throw new Error(\"gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW\");var i=t.createBuffer(),a=new s(t,r,i,0,n);return a.update(e),a}},1140:function(t,e,r){\"use strict\";var n=r(2858);t.exports=function(t,e){var r=t.positions,i=t.vectors,a={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),a;for(var o=0,s=1/0,l=-1/0,u=1/0,c=-1/0,f=1/0,h=-1/0,p=null,d=null,v=[],g=1/0,y=!1,m=0;m<r.length;m++){var x=r[m];s=Math.min(x[0],s),l=Math.max(x[0],l),u=Math.min(x[1],u),c=Math.max(x[1],c),f=Math.min(x[2],f),h=Math.max(x[2],h);var b=i[m];if(n.length(b)>o&&(o=n.length(b)),m){var _=2*n.distance(p,x)/(n.length(d)+n.length(b));_?(g=Math.min(g,_),y=!1):y=!0}y||(p=x,d=b),v.push(b)}var w=[s,u,f],T=[l,c,h];e&&(e[0]=w,e[1]=T),0===o&&(o=1);var k=1/o;isFinite(g)||(g=1),a.vectorScale=g;var A=t.coneSize||.5;t.absoluteConeSize&&(A=t.absoluteConeSize*k),a.coneScale=A,m=0;for(var M=0;m<r.length;m++)for(var S=(x=r[m])[0],E=x[1],L=x[2],C=v[m],P=n.length(C)*k,O=0;O<8;O++){a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vertexIntensity.push(P,P,P),a.vertexIntensity.push(P,P,P);var I=a.positions.length;a.cells.push([I-6,I-5,I-4],[I-3,I-2,I-1])}return a};var i=r(7234);t.exports.createMesh=r(5028),t.exports.createConeMesh=function(e,r){return t.exports.createMesh(e,r,{shaders:i,traceType:\"cone\"})}},5028:function(t,e,r){\"use strict\";var n=r(5158),i=r(5827),a=r(2944),o=r(8931),s=r(104),l=r(7437),u=r(5050),c=r(9156),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e,r,n,i,a,o,s,l,u,c){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.pickShader=n,this.trianglePositions=i,this.triangleVectors=a,this.triangleColors=s,this.triangleUVs=l,this.triangleIds=o,this.triangleVAO=u,this.triangleCount=0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.traceType=c,this.tubeScale=1,this.coneScale=2,this.vectorScale=1,this.coneOffset=.25,this._model=f,this._view=f,this._projection=f,this._resolution=[1,1]}var p=h.prototype;p.isOpaque=function(){return this.opacity>=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(t){this.pickId=t},p.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),void 0!==t.tubeScale&&(this.tubeScale=t.tubeScale),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=c({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return u(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,i=t.vectors;if(n&&r&&i){var a=[],o=[],s=[],l=[],f=[];this.cells=r,this.positions=n,this.vectors=i;var h=t.meshColor||[1,1,1,1],p=t.vertexIntensity,d=1/0,v=-1/0;if(p)if(t.vertexIntensityBounds)d=+t.vertexIntensityBounds[0],v=+t.vertexIntensityBounds[1];else for(var g=0;g<p.length;++g){var y=p[g];d=Math.min(d,y),v=Math.max(v,y)}else for(g=0;g<n.length;++g)y=n[g][2],d=Math.min(d,y),v=Math.max(v,y);for(this.intensity=p||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n),this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],g=0;g<n.length;++g)for(var m=n[g],x=0;x<3;++x)!isNaN(m[x])&&isFinite(m[x])&&(this.bounds[0][x]=Math.min(this.bounds[0][x],m[x]),this.bounds[1][x]=Math.max(this.bounds[1][x],m[x]));var b=0;t:for(g=0;g<r.length;++g){var _=r[g];if(3===_.length){for(x=0;x<3;++x){m=n[T=_[x]];for(var w=0;w<3;++w)if(isNaN(m[w])||!isFinite(m[w]))continue t}for(x=0;x<3;++x){var T;m=n[T=_[2-x]],a.push(m[0],m[1],m[2],m[3]);var k=i[T];o.push(k[0],k[1],k[2],k[3]||0);var A,M=h;3===M.length?s.push(M[0],M[1],M[2],1):s.push(M[0],M[1],M[2],M[3]),A=p?[(p[T]-d)/(v-d),0]:[(m[2]-d)/(v-d),0],l.push(A[0],A[1]),f.push(g)}b+=1}}this.triangleCount=b,this.trianglePositions.update(a),this.triangleVectors.update(o),this.triangleColors.update(s),this.triangleUVs.update(l),this.triangleIds.update(new Uint32Array(f))}},p.drawTransparent=p.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var u={model:r,view:n,projection:i,inverseModel:f.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,texture:0};u.inverseModel=l(u.inverseModel,u.model),e.disable(e.CULL_FACE),this.texture.bind(0);var c=new Array(16);for(s(c,u.view,u.model),s(c,u.projection,c),l(c,c),o=0;o<3;++o)u.eyePosition[o]=c[12+o]/c[15];var h=c[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*c[4*o+3];for(o=0;o<3;++o){for(var p=c[12+o],d=0;d<3;++d)p+=c[4*d+o]*this.lightPosition[d];u.lightPosition[o]=p/h}if(this.triangleCount>0){var v=this.triShader;v.bind(),v.uniforms=u,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},p.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind())},p.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3),i={position:n,dataCoordinate:n,index:Math.floor(r[1]/48)};return\"cone\"===this.traceType?i.index=Math.floor(r[1]/48):\"streamtube\"===this.traceType&&(i.intensity=this.intensity[r[1]],i.velocity=this.vectors[r[1]].slice(0,3),i.divergence=this.vectors[r[1]][3],i.index=e),i},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()},t.exports=function(t,e,r){var s=r.shaders;1===arguments.length&&(t=(e=t).gl);var l=function(t,e){var r=n(t,e.meshShader.vertex,e.meshShader.fragment,null,e.meshShader.attributes);return r.attributes.position.location=0,r.attributes.color.location=2,r.attributes.uv.location=3,r.attributes.vector.location=4,r}(t,s),c=function(t,e){var r=n(t,e.pickShader.vertex,e.pickShader.fragment,null,e.pickShader.attributes);return r.attributes.position.location=0,r.attributes.id.location=1,r.attributes.vector.location=4,r}(t,s),f=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));f.generateMipmap(),f.minFilter=t.LINEAR_MIPMAP_LINEAR,f.magFilter=t.LINEAR;var p=i(t),d=i(t),v=i(t),g=i(t),y=i(t),m=new h(t,f,l,c,p,d,y,v,g,a(t,[{buffer:p,type:t.FLOAT,size:4},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:v,type:t.FLOAT,size:4},{buffer:g,type:t.FLOAT,size:2},{buffer:d,type:t.FLOAT,size:4}]),r.traceType||\"cone\");return m.update(e),m}},7234:function(t,e,r){var n=r(6832),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec3 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, coneScale, coneOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * conePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(conePosition, 1.0);\\n  vec4 t_position  = view * conePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = conePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float vectorScale, coneScale, coneOffset;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector.xyz), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n  gl_Position = projection * view * conePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec3\"}]},e.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec3\"}]}},1950:function(t){t.exports={0:\"NONE\",1:\"ONE\",2:\"LINE_LOOP\",3:\"LINE_STRIP\",4:\"TRIANGLES\",5:\"TRIANGLE_STRIP\",6:\"TRIANGLE_FAN\",256:\"DEPTH_BUFFER_BIT\",512:\"NEVER\",513:\"LESS\",514:\"EQUAL\",515:\"LEQUAL\",516:\"GREATER\",517:\"NOTEQUAL\",518:\"GEQUAL\",519:\"ALWAYS\",768:\"SRC_COLOR\",769:\"ONE_MINUS_SRC_COLOR\",770:\"SRC_ALPHA\",771:\"ONE_MINUS_SRC_ALPHA\",772:\"DST_ALPHA\",773:\"ONE_MINUS_DST_ALPHA\",774:\"DST_COLOR\",775:\"ONE_MINUS_DST_COLOR\",776:\"SRC_ALPHA_SATURATE\",1024:\"STENCIL_BUFFER_BIT\",1028:\"FRONT\",1029:\"BACK\",1032:\"FRONT_AND_BACK\",1280:\"INVALID_ENUM\",1281:\"INVALID_VALUE\",1282:\"INVALID_OPERATION\",1285:\"OUT_OF_MEMORY\",1286:\"INVALID_FRAMEBUFFER_OPERATION\",2304:\"CW\",2305:\"CCW\",2849:\"LINE_WIDTH\",2884:\"CULL_FACE\",2885:\"CULL_FACE_MODE\",2886:\"FRONT_FACE\",2928:\"DEPTH_RANGE\",2929:\"DEPTH_TEST\",2930:\"DEPTH_WRITEMASK\",2931:\"DEPTH_CLEAR_VALUE\",2932:\"DEPTH_FUNC\",2960:\"STENCIL_TEST\",2961:\"STENCIL_CLEAR_VALUE\",2962:\"STENCIL_FUNC\",2963:\"STENCIL_VALUE_MASK\",2964:\"STENCIL_FAIL\",2965:\"STENCIL_PASS_DEPTH_FAIL\",2966:\"STENCIL_PASS_DEPTH_PASS\",2967:\"STENCIL_REF\",2968:\"STENCIL_WRITEMASK\",2978:\"VIEWPORT\",3024:\"DITHER\",3042:\"BLEND\",3088:\"SCISSOR_BOX\",3089:\"SCISSOR_TEST\",3106:\"COLOR_CLEAR_VALUE\",3107:\"COLOR_WRITEMASK\",3317:\"UNPACK_ALIGNMENT\",3333:\"PACK_ALIGNMENT\",3379:\"MAX_TEXTURE_SIZE\",3386:\"MAX_VIEWPORT_DIMS\",3408:\"SUBPIXEL_BITS\",3410:\"RED_BITS\",3411:\"GREEN_BITS\",3412:\"BLUE_BITS\",3413:\"ALPHA_BITS\",3414:\"DEPTH_BITS\",3415:\"STENCIL_BITS\",3553:\"TEXTURE_2D\",4352:\"DONT_CARE\",4353:\"FASTEST\",4354:\"NICEST\",5120:\"BYTE\",5121:\"UNSIGNED_BYTE\",5122:\"SHORT\",5123:\"UNSIGNED_SHORT\",5124:\"INT\",5125:\"UNSIGNED_INT\",5126:\"FLOAT\",5386:\"INVERT\",5890:\"TEXTURE\",6401:\"STENCIL_INDEX\",6402:\"DEPTH_COMPONENT\",6406:\"ALPHA\",6407:\"RGB\",6408:\"RGBA\",6409:\"LUMINANCE\",6410:\"LUMINANCE_ALPHA\",7680:\"KEEP\",7681:\"REPLACE\",7682:\"INCR\",7683:\"DECR\",7936:\"VENDOR\",7937:\"RENDERER\",7938:\"VERSION\",9728:\"NEAREST\",9729:\"LINEAR\",9984:\"NEAREST_MIPMAP_NEAREST\",9985:\"LINEAR_MIPMAP_NEAREST\",9986:\"NEAREST_MIPMAP_LINEAR\",9987:\"LINEAR_MIPMAP_LINEAR\",10240:\"TEXTURE_MAG_FILTER\",10241:\"TEXTURE_MIN_FILTER\",10242:\"TEXTURE_WRAP_S\",10243:\"TEXTURE_WRAP_T\",10497:\"REPEAT\",10752:\"POLYGON_OFFSET_UNITS\",16384:\"COLOR_BUFFER_BIT\",32769:\"CONSTANT_COLOR\",32770:\"ONE_MINUS_CONSTANT_COLOR\",32771:\"CONSTANT_ALPHA\",32772:\"ONE_MINUS_CONSTANT_ALPHA\",32773:\"BLEND_COLOR\",32774:\"FUNC_ADD\",32777:\"BLEND_EQUATION_RGB\",32778:\"FUNC_SUBTRACT\",32779:\"FUNC_REVERSE_SUBTRACT\",32819:\"UNSIGNED_SHORT_4_4_4_4\",32820:\"UNSIGNED_SHORT_5_5_5_1\",32823:\"POLYGON_OFFSET_FILL\",32824:\"POLYGON_OFFSET_FACTOR\",32854:\"RGBA4\",32855:\"RGB5_A1\",32873:\"TEXTURE_BINDING_2D\",32926:\"SAMPLE_ALPHA_TO_COVERAGE\",32928:\"SAMPLE_COVERAGE\",32936:\"SAMPLE_BUFFERS\",32937:\"SAMPLES\",32938:\"SAMPLE_COVERAGE_VALUE\",32939:\"SAMPLE_COVERAGE_INVERT\",32968:\"BLEND_DST_RGB\",32969:\"BLEND_SRC_RGB\",32970:\"BLEND_DST_ALPHA\",32971:\"BLEND_SRC_ALPHA\",33071:\"CLAMP_TO_EDGE\",33170:\"GENERATE_MIPMAP_HINT\",33189:\"DEPTH_COMPONENT16\",33306:\"DEPTH_STENCIL_ATTACHMENT\",33635:\"UNSIGNED_SHORT_5_6_5\",33648:\"MIRRORED_REPEAT\",33901:\"ALIASED_POINT_SIZE_RANGE\",33902:\"ALIASED_LINE_WIDTH_RANGE\",33984:\"TEXTURE0\",33985:\"TEXTURE1\",33986:\"TEXTURE2\",33987:\"TEXTURE3\",33988:\"TEXTURE4\",33989:\"TEXTURE5\",33990:\"TEXTURE6\",33991:\"TEXTURE7\",33992:\"TEXTURE8\",33993:\"TEXTURE9\",33994:\"TEXTURE10\",33995:\"TEXTURE11\",33996:\"TEXTURE12\",33997:\"TEXTURE13\",33998:\"TEXTURE14\",33999:\"TEXTURE15\",34e3:\"TEXTURE16\",34001:\"TEXTURE17\",34002:\"TEXTURE18\",34003:\"TEXTURE19\",34004:\"TEXTURE20\",34005:\"TEXTURE21\",34006:\"TEXTURE22\",34007:\"TEXTURE23\",34008:\"TEXTURE24\",34009:\"TEXTURE25\",34010:\"TEXTURE26\",34011:\"TEXTURE27\",34012:\"TEXTURE28\",34013:\"TEXTURE29\",34014:\"TEXTURE30\",34015:\"TEXTURE31\",34016:\"ACTIVE_TEXTURE\",34024:\"MAX_RENDERBUFFER_SIZE\",34041:\"DEPTH_STENCIL\",34055:\"INCR_WRAP\",34056:\"DECR_WRAP\",34067:\"TEXTURE_CUBE_MAP\",34068:\"TEXTURE_BINDING_CUBE_MAP\",34069:\"TEXTURE_CUBE_MAP_POSITIVE_X\",34070:\"TEXTURE_CUBE_MAP_NEGATIVE_X\",34071:\"TEXTURE_CUBE_MAP_POSITIVE_Y\",34072:\"TEXTURE_CUBE_MAP_NEGATIVE_Y\",34073:\"TEXTURE_CUBE_MAP_POSITIVE_Z\",34074:\"TEXTURE_CUBE_MAP_NEGATIVE_Z\",34076:\"MAX_CUBE_MAP_TEXTURE_SIZE\",34338:\"VERTEX_ATTRIB_ARRAY_ENABLED\",34339:\"VERTEX_ATTRIB_ARRAY_SIZE\",34340:\"VERTEX_ATTRIB_ARRAY_STRIDE\",34341:\"VERTEX_ATTRIB_ARRAY_TYPE\",34342:\"CURRENT_VERTEX_ATTRIB\",34373:\"VERTEX_ATTRIB_ARRAY_POINTER\",34466:\"NUM_COMPRESSED_TEXTURE_FORMATS\",34467:\"COMPRESSED_TEXTURE_FORMATS\",34660:\"BUFFER_SIZE\",34661:\"BUFFER_USAGE\",34816:\"STENCIL_BACK_FUNC\",34817:\"STENCIL_BACK_FAIL\",34818:\"STENCIL_BACK_PASS_DEPTH_FAIL\",34819:\"STENCIL_BACK_PASS_DEPTH_PASS\",34877:\"BLEND_EQUATION_ALPHA\",34921:\"MAX_VERTEX_ATTRIBS\",34922:\"VERTEX_ATTRIB_ARRAY_NORMALIZED\",34930:\"MAX_TEXTURE_IMAGE_UNITS\",34962:\"ARRAY_BUFFER\",34963:\"ELEMENT_ARRAY_BUFFER\",34964:\"ARRAY_BUFFER_BINDING\",34965:\"ELEMENT_ARRAY_BUFFER_BINDING\",34975:\"VERTEX_ATTRIB_ARRAY_BUFFER_BINDING\",35040:\"STREAM_DRAW\",35044:\"STATIC_DRAW\",35048:\"DYNAMIC_DRAW\",35632:\"FRAGMENT_SHADER\",35633:\"VERTEX_SHADER\",35660:\"MAX_VERTEX_TEXTURE_IMAGE_UNITS\",35661:\"MAX_COMBINED_TEXTURE_IMAGE_UNITS\",35663:\"SHADER_TYPE\",35664:\"FLOAT_VEC2\",35665:\"FLOAT_VEC3\",35666:\"FLOAT_VEC4\",35667:\"INT_VEC2\",35668:\"INT_VEC3\",35669:\"INT_VEC4\",35670:\"BOOL\",35671:\"BOOL_VEC2\",35672:\"BOOL_VEC3\",35673:\"BOOL_VEC4\",35674:\"FLOAT_MAT2\",35675:\"FLOAT_MAT3\",35676:\"FLOAT_MAT4\",35678:\"SAMPLER_2D\",35680:\"SAMPLER_CUBE\",35712:\"DELETE_STATUS\",35713:\"COMPILE_STATUS\",35714:\"LINK_STATUS\",35715:\"VALIDATE_STATUS\",35716:\"INFO_LOG_LENGTH\",35717:\"ATTACHED_SHADERS\",35718:\"ACTIVE_UNIFORMS\",35719:\"ACTIVE_UNIFORM_MAX_LENGTH\",35720:\"SHADER_SOURCE_LENGTH\",35721:\"ACTIVE_ATTRIBUTES\",35722:\"ACTIVE_ATTRIBUTE_MAX_LENGTH\",35724:\"SHADING_LANGUAGE_VERSION\",35725:\"CURRENT_PROGRAM\",36003:\"STENCIL_BACK_REF\",36004:\"STENCIL_BACK_VALUE_MASK\",36005:\"STENCIL_BACK_WRITEMASK\",36006:\"FRAMEBUFFER_BINDING\",36007:\"RENDERBUFFER_BINDING\",36048:\"FRAMEBUFFER_ATTACHMENT_OBJECT_TYPE\",36049:\"FRAMEBUFFER_ATTACHMENT_OBJECT_NAME\",36050:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_LEVEL\",36051:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_CUBE_MAP_FACE\",36053:\"FRAMEBUFFER_COMPLETE\",36054:\"FRAMEBUFFER_INCOMPLETE_ATTACHMENT\",36055:\"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT\",36057:\"FRAMEBUFFER_INCOMPLETE_DIMENSIONS\",36061:\"FRAMEBUFFER_UNSUPPORTED\",36064:\"COLOR_ATTACHMENT0\",36096:\"DEPTH_ATTACHMENT\",36128:\"STENCIL_ATTACHMENT\",36160:\"FRAMEBUFFER\",36161:\"RENDERBUFFER\",36162:\"RENDERBUFFER_WIDTH\",36163:\"RENDERBUFFER_HEIGHT\",36164:\"RENDERBUFFER_INTERNAL_FORMAT\",36168:\"STENCIL_INDEX8\",36176:\"RENDERBUFFER_RED_SIZE\",36177:\"RENDERBUFFER_GREEN_SIZE\",36178:\"RENDERBUFFER_BLUE_SIZE\",36179:\"RENDERBUFFER_ALPHA_SIZE\",36180:\"RENDERBUFFER_DEPTH_SIZE\",36181:\"RENDERBUFFER_STENCIL_SIZE\",36194:\"RGB565\",36336:\"LOW_FLOAT\",36337:\"MEDIUM_FLOAT\",36338:\"HIGH_FLOAT\",36339:\"LOW_INT\",36340:\"MEDIUM_INT\",36341:\"HIGH_INT\",36346:\"SHADER_COMPILER\",36347:\"MAX_VERTEX_UNIFORM_VECTORS\",36348:\"MAX_VARYING_VECTORS\",36349:\"MAX_FRAGMENT_UNIFORM_VECTORS\",37440:\"UNPACK_FLIP_Y_WEBGL\",37441:\"UNPACK_PREMULTIPLY_ALPHA_WEBGL\",37442:\"CONTEXT_LOST_WEBGL\",37443:\"UNPACK_COLORSPACE_CONVERSION_WEBGL\",37444:\"BROWSER_DEFAULT_WEBGL\"}},6603:function(t,e,r){var n=r(1950);t.exports=function(t){return n[t]}},3110:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl,r=n(e),o=i(e,[{buffer:r,type:e.FLOAT,size:3,offset:0,stride:40},{buffer:r,type:e.FLOAT,size:4,offset:12,stride:40},{buffer:r,type:e.FLOAT,size:3,offset:28,stride:40}]),l=a(e);l.attributes.position.location=0,l.attributes.color.location=1,l.attributes.offset.location=2;var u=new s(e,r,o,l);return u.update(t),u};var n=r(5827),i=r(2944),a=r(7667),o=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function s(t,e,r,n){this.gl=t,this.shader=n,this.buffer=e,this.vao=r,this.pixelRatio=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lineWidth=[1,1,1],this.capSize=[10,10,10],this.lineCount=[0,0,0],this.lineOffset=[0,0,0],this.opacity=1,this.hasAlpha=!1}var l=s.prototype;function u(t,e){for(var r=0;r<3;++r)t[0][r]=Math.min(t[0][r],e[r]),t[1][r]=Math.max(t[1][r],e[r])}l.isOpaque=function(){return!this.hasAlpha},l.isTransparent=function(){return this.hasAlpha},l.drawTransparent=l.draw=function(t){var e=this.gl,r=this.shader.uniforms;this.shader.bind();var n=r.view=t.view||o,i=r.projection=t.projection||o;r.model=t.model||o,r.clipBounds=this.clipBounds,r.opacity=this.opacity;var a=n[12],s=n[13],l=n[14],u=n[15],c=(t._ortho?2:1)*this.pixelRatio*(i[3]*a+i[7]*s+i[11]*l+i[15]*u)/e.drawingBufferHeight;this.vao.bind();for(var f=0;f<3;++f)e.lineWidth(this.lineWidth[f]*this.pixelRatio),r.capSize=this.capSize[f]*c,this.lineCount[f]&&e.drawArrays(e.LINES,this.lineOffset[f],this.lineCount[f]);this.vao.unbind()};var c=function(){for(var t=new Array(3),e=0;e<3;++e){for(var r=[],n=1;n<=2;++n)for(var i=-1;i<=1;i+=2){var a=[0,0,0];a[(n+e)%3]=i,r.push(a)}t[e]=r}return t}();function f(t,e,r,n){for(var i=c[n],a=0;a<i.length;++a){var o=i[a];t.push(e[0],e[1],e[2],r[0],r[1],r[2],r[3],o[0],o[1],o[2])}return i.length}l.update=function(t){\"lineWidth\"in(t=t||{})&&(this.lineWidth=t.lineWidth,Array.isArray(this.lineWidth)||(this.lineWidth=[this.lineWidth,this.lineWidth,this.lineWidth])),\"capSize\"in t&&(this.capSize=t.capSize,Array.isArray(this.capSize)||(this.capSize=[this.capSize,this.capSize,this.capSize])),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var e=t.color||[[0,0,0],[0,0,0],[0,0,0]],r=t.position,n=t.error;if(Array.isArray(e[0])||(e=[e,e,e]),r&&n){var i=[],a=r.length,o=0;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.lineCount=[0,0,0];for(var s=0;s<3;++s){this.lineOffset[s]=o;t:for(var l=0;l<a;++l){for(var c=r[l],h=0;h<3;++h)if(isNaN(c[h])||!isFinite(c[h]))continue t;var p,d=n[l],v=e[s];Array.isArray(v[0])&&(v=e[l]),3===v.length?v=[v[0],v[1],v[2],1]:4===v.length&&(v=[v[0],v[1],v[2],v[3]],!this.hasAlpha&&v[3]<1&&(this.hasAlpha=!0)),isNaN(d[0][s])||isNaN(d[1][s])||(d[0][s]<0&&((p=c.slice())[s]+=d[0][s],i.push(c[0],c[1],c[2],v[0],v[1],v[2],v[3],0,0,0,p[0],p[1],p[2],v[0],v[1],v[2],v[3],0,0,0),u(this.bounds,p),o+=2+f(i,p,v,s)),d[1][s]>0&&((p=c.slice())[s]+=d[1][s],i.push(c[0],c[1],c[2],v[0],v[1],v[2],v[3],0,0,0,p[0],p[1],p[2],v[0],v[1],v[2],v[3],0,0,0),u(this.bounds,p),o+=2+f(i,p,v,s)))}this.lineCount[s]=o-this.lineOffset[s]}this.buffer.update(i)}},l.dispose=function(){this.shader.dispose(),this.buffer.dispose(),this.vao.dispose()}},7667:function(t,e,r){\"use strict\";var n=r(6832),i=r(5158),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, offset;\\nattribute vec4 color;\\nuniform mat4 model, view, projection;\\nuniform float capSize;\\nvarying vec4 fragColor;\\nvarying vec3 fragPosition;\\n\\nvoid main() {\\n  vec4 worldPosition  = model * vec4(position, 1.0);\\n  worldPosition       = (worldPosition / worldPosition.w) + vec4(capSize * offset, 0.0);\\n  gl_Position         = projection * view * worldPosition;\\n  fragColor           = color;\\n  fragPosition        = position;\\n}\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float opacity;\\nvarying vec3 fragPosition;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if (\\n    outOfRange(clipBounds[0], clipBounds[1], fragPosition) ||\\n    fragColor.a * opacity == 0.\\n  ) discard;\\n\\n  gl_FragColor = opacity * fragColor;\\n}\"]);t.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"offset\",type:\"vec3\"}])}},4234:function(t,e,r){\"use strict\";var n=r(8931);t.exports=function(t,e,r,n){i||(i=t.FRAMEBUFFER_UNSUPPORTED,a=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,o=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,s=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var u=t.getExtension(\"WEBGL_draw_buffers\");if(!l&&u&&function(t,e){var r=t.getParameter(e.MAX_COLOR_ATTACHMENTS_WEBGL);l=new Array(r+1);for(var n=0;n<=r;++n){for(var i=new Array(r),a=0;a<n;++a)i[a]=t.COLOR_ATTACHMENT0+a;for(a=n;a<r;++a)i[a]=t.NONE;l[n]=i}}(t,u),Array.isArray(e)&&(n=r,r=0|e[1],e=0|e[0]),\"number\"!=typeof e)throw new Error(\"gl-fbo: Missing shape parameter\");var c=t.getParameter(t.MAX_RENDERBUFFER_SIZE);if(e<0||e>c||r<0||r>c)throw new Error(\"gl-fbo: Parameters are too large for FBO\");var f=1;if(\"color\"in(n=n||{})){if((f=Math.max(0|n.color,0))<0)throw new Error(\"gl-fbo: Must specify a nonnegative number of colors\");if(f>1){if(!u)throw new Error(\"gl-fbo: Multiple draw buffer extension not supported\");if(f>t.getParameter(u.MAX_COLOR_ATTACHMENTS_WEBGL))throw new Error(\"gl-fbo: Context does not support \"+f+\" draw buffers\")}}var h=t.UNSIGNED_BYTE,p=t.getExtension(\"OES_texture_float\");if(n.float&&f>0){if(!p)throw new Error(\"gl-fbo: Context does not support floating point textures\");h=t.FLOAT}else n.preferFloat&&f>0&&p&&(h=t.FLOAT);var v=!0;\"depth\"in n&&(v=!!n.depth);var g=!1;return\"stencil\"in n&&(g=!!n.stencil),new d(t,e,r,h,f,v,g,u)};var i,a,o,s,l=null;function u(t){return[t.getParameter(t.FRAMEBUFFER_BINDING),t.getParameter(t.RENDERBUFFER_BINDING),t.getParameter(t.TEXTURE_BINDING_2D)]}function c(t,e){t.bindFramebuffer(t.FRAMEBUFFER,e[0]),t.bindRenderbuffer(t.RENDERBUFFER,e[1]),t.bindTexture(t.TEXTURE_2D,e[2])}function f(t){switch(t){case i:throw new Error(\"gl-fbo: Framebuffer unsupported\");case a:throw new Error(\"gl-fbo: Framebuffer incomplete attachment\");case o:throw new Error(\"gl-fbo: Framebuffer incomplete dimensions\");case s:throw new Error(\"gl-fbo: Framebuffer incomplete missing attachment\");default:throw new Error(\"gl-fbo: Framebuffer failed for unspecified reason\")}}function h(t,e,r,i,a,o){if(!i)return null;var s=n(t,e,r,a,i);return s.magFilter=t.NEAREST,s.minFilter=t.NEAREST,s.mipSamples=1,s.bind(),t.framebufferTexture2D(t.FRAMEBUFFER,o,t.TEXTURE_2D,s.handle,0),s}function p(t,e,r,n,i){var a=t.createRenderbuffer();return t.bindRenderbuffer(t.RENDERBUFFER,a),t.renderbufferStorage(t.RENDERBUFFER,n,e,r),t.framebufferRenderbuffer(t.FRAMEBUFFER,i,t.RENDERBUFFER,a),a}function d(t,e,r,n,i,a,o,s){this.gl=t,this._shape=[0|e,0|r],this._destroyed=!1,this._ext=s,this.color=new Array(i);for(var d=0;d<i;++d)this.color[d]=null;this._color_rb=null,this.depth=null,this._depth_rb=null,this._colorType=n,this._useDepth=a,this._useStencil=o;var v=this,g=[0|e,0|r];Object.defineProperties(g,{0:{get:function(){return v._shape[0]},set:function(t){return v.width=t}},1:{get:function(){return v._shape[1]},set:function(t){return v.height=t}}}),this._shapeVector=g,function(t){var e=u(t.gl),r=t.gl,n=t.handle=r.createFramebuffer(),i=t._shape[0],a=t._shape[1],o=t.color.length,s=t._ext,d=t._useStencil,v=t._useDepth,g=t._colorType;r.bindFramebuffer(r.FRAMEBUFFER,n);for(var y=0;y<o;++y)t.color[y]=h(r,i,a,g,r.RGBA,r.COLOR_ATTACHMENT0+y);0===o?(t._color_rb=p(r,i,a,r.RGBA4,r.COLOR_ATTACHMENT0),s&&s.drawBuffersWEBGL(l[0])):o>1&&s.drawBuffersWEBGL(l[o]);var m=r.getExtension(\"WEBGL_depth_texture\");m?d?t.depth=h(r,i,a,m.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):v&&(t.depth=h(r,i,a,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):v&&d?t._depth_rb=p(r,i,a,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):v?t._depth_rb=p(r,i,a,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=p(r,i,a,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){for(t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null),y=0;y<t.color.length;++y)t.color[y].dispose(),t.color[y]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),c(r,e),f(x)}c(r,e)}(this)}var v=d.prototype;function g(t,e,r){if(t._destroyed)throw new Error(\"gl-fbo: Can't resize destroyed FBO\");if(t._shape[0]!==e||t._shape[1]!==r){var n=t.gl,i=n.getParameter(n.MAX_RENDERBUFFER_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var a=u(n),o=0;o<t.color.length;++o)t.color[o].shape=t._shape;t._color_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._color_rb),n.renderbufferStorage(n.RENDERBUFFER,n.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&n.renderbufferStorage(n.RENDERBUFFER,n.STENCIL_INDEX,t._shape[0],t._shape[1])),n.bindFramebuffer(n.FRAMEBUFFER,t.handle);var s=n.checkFramebufferStatus(n.FRAMEBUFFER);s!==n.FRAMEBUFFER_COMPLETE&&(t.dispose(),c(n,a),f(s)),c(n,a)}}Object.defineProperties(v,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error(\"gl-fbo: Shape vector must be length 2\");var e=0|t[0],r=0|t[1];return g(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return g(this,t|=0,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t|=0,g(this,this._shape[0],t),t},enumerable:!1}}),v.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},v.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},3530:function(t,e,r){var n=r(8974).sprintf,i=r(6603),a=r(9365),o=r(8008);t.exports=function(t,e,r){\"use strict\";var s=a(e)||\"of unknown name (see npm glsl-shader-name)\",l=\"unknown type\";void 0!==r&&(l=r===i.FRAGMENT_SHADER?\"fragment\":\"vertex\");for(var u=n(\"Error compiling %s shader %s:\\n\",l,s),c=n(\"%s%s\",u,t),f=t.split(\"\\n\"),h={},p=0;p<f.length;p++){var d=f[p];if(\"\"!==d&&\"\\0\"!==d){var v=parseInt(d.split(\":\")[2]);if(isNaN(v))throw new Error(n(\"Could not parse error: %s\",d));h[v]=d}}var g=o(e).split(\"\\n\");for(p=0;p<g.length;p++)if((h[p+3]||h[p+2]||h[p+1])&&(u+=g[p]+\"\\n\",h[p+1])){var y=h[p+1];y=y.substr(y.split(\":\",3).join(\":\").length+1).trim(),u+=n(\"^^^ %s\\n\\n\",y)}return{long:u.trim(),short:c.trim()}}},6386:function(t,e,r){\"use strict\";t.exports=function(t,e){var r=t.gl,n=new u(t,o(r,l.vertex,l.fragment),o(r,l.pickVertex,l.pickFragment),s(r),s(r),s(r),s(r));return n.update(e),t.addObject(n),n};var n=r(5070),i=r(9560),a=r(5306),o=r(5158),s=r(5827),l=r(1292);function u(t,e,r,n,i,a,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.weightBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.xData=[],this.yData=[],this.shape=[0,0],this.bounds=[1/0,1/0,-1/0,-1/0],this.pickOffset=0}var c,f=u.prototype,h=[0,0,1,0,0,1,1,0,1,1,0,1];f.draw=(c=[1,0,0,0,1,0,0,0,1],function(){var t=this.plot,e=this.shader,r=this.bounds,n=this.numVertices;if(!(n<=0)){var i=t.gl,a=t.dataBox,o=r[2]-r[0],s=r[3]-r[1],l=a[2]-a[0],u=a[3]-a[1];c[0]=2*o/l,c[4]=2*s/u,c[6]=2*(r[0]-a[0])/l-1,c[7]=2*(r[1]-a[1])/u-1,e.bind();var f=e.uniforms;f.viewTransform=c,f.shape=this.shape;var h=e.attributes;this.positionBuffer.bind(),h.position.pointer(),this.weightBuffer.bind(),h.weight.pointer(i.UNSIGNED_BYTE,!1),this.colorBuffer.bind(),h.color.pointer(i.UNSIGNED_BYTE,!0),i.drawArrays(i.TRIANGLES,0,n)}}),f.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,i=this.pickShader,a=this.bounds,o=this.numVertices;if(!(o<=0)){var s=n.gl,l=n.dataBox,u=a[2]-a[0],c=a[3]-a[1],f=l[2]-l[0],h=l[3]-l[1];t[0]=2*u/f,t[4]=2*c/h,t[6]=2*(a[0]-l[0])/f-1,t[7]=2*(a[1]-l[1])/h-1;for(var p=0;p<4;++p)e[p]=r>>8*p&255;this.pickOffset=r,i.bind();var d=i.uniforms;d.viewTransform=t,d.pickOffset=e,d.shape=this.shape;var v=i.attributes;return this.positionBuffer.bind(),v.position.pointer(),this.weightBuffer.bind(),v.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),v.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.shape[0]*this.shape[1];if(r<n||r>=n+i)return null;var a=r-n,o=this.xData,s=this.yData;return{object:this,pointId:a,dataCoord:[o[a%this.shape[0]],s[a/this.shape[0]|0]]}},f.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||i(e[0]),o=t.y||i(e[1]),s=t.z||new Float32Array(e[0]*e[1]),l=!1!==t.zsmooth;this.xData=r,this.yData=o;var u,c,f,p,d=t.colorLevels||[0],v=t.colorValues||[0,0,0,1],g=d.length,y=this.bounds;l?(u=y[0]=r[0],c=y[1]=o[0],f=y[2]=r[r.length-1],p=y[3]=o[o.length-1]):(u=y[0]=r[0]+(r[1]-r[0])/2,c=y[1]=o[0]+(o[1]-o[0])/2,f=y[2]=r[r.length-1]+(r[r.length-1]-r[r.length-2])/2,p=y[3]=o[o.length-1]+(o[o.length-1]-o[o.length-2])/2);var m=1/(f-u),x=1/(p-c),b=e[0],_=e[1];this.shape=[b,_];var w=(l?(b-1)*(_-1):b*_)*(h.length>>>1);this.numVertices=w;for(var T=a.mallocUint8(4*w),k=a.mallocFloat32(2*w),A=a.mallocUint8(2*w),M=a.mallocUint32(w),S=0,E=l?b-1:b,L=l?_-1:_,C=0;C<L;++C){var P,O;l?(P=x*(o[C]-c),O=x*(o[C+1]-c)):(P=C<_-1?x*(o[C]-(o[C+1]-o[C])/2-c):x*(o[C]-(o[C]-o[C-1])/2-c),O=C<_-1?x*(o[C]+(o[C+1]-o[C])/2-c):x*(o[C]+(o[C]-o[C-1])/2-c));for(var I=0;I<E;++I){var D,z;l?(D=m*(r[I]-u),z=m*(r[I+1]-u)):(D=I<b-1?m*(r[I]-(r[I+1]-r[I])/2-u):m*(r[I]-(r[I]-r[I-1])/2-u),z=I<b-1?m*(r[I]+(r[I+1]-r[I])/2-u):m*(r[I]+(r[I]-r[I-1])/2-u));for(var R=0;R<h.length;R+=2){var F,B,N,j,U=h[R],V=h[R+1],H=s[l?(C+V)*b+(I+U):C*b+I],q=n.le(d,H);if(q<0)F=v[0],B=v[1],N=v[2],j=v[3];else if(q===g-1)F=v[4*g-4],B=v[4*g-3],N=v[4*g-2],j=v[4*g-1];else{var G=(H-d[q])/(d[q+1]-d[q]),Z=1-G,Y=4*q,W=4*(q+1);F=Z*v[Y]+G*v[W],B=Z*v[Y+1]+G*v[W+1],N=Z*v[Y+2]+G*v[W+2],j=Z*v[Y+3]+G*v[W+3]}T[4*S]=255*F,T[4*S+1]=255*B,T[4*S+2]=255*N,T[4*S+3]=255*j,k[2*S]=.5*D+.5*z,k[2*S+1]=.5*P+.5*O,A[2*S]=U,A[2*S+1]=V,M[S]=C*b+I,S+=1}}}this.positionBuffer.update(k),this.weightBuffer.update(A),this.colorBuffer.update(T),this.idBuffer.update(M),a.free(k),a.free(T),a.free(A),a.free(M)},f.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.weightBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},1292:function(t,e,r){\"use strict\";var n=r(6832);t.exports={fragment:n([\"precision lowp float;\\n#define GLSLIFY 1\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\"]),vertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 color;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  fragColor = color;\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"]),pickFragment:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nuniform vec2 shape;\\nuniform vec4 pickOffset;\\n\\nvoid main() {\\n  vec2 d = step(.5, vWeight);\\n  vec4 id = fragId + pickOffset;\\n  id.x += d.x + d.y*shape.x;\\n\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  gl_FragColor = id/255.;\\n}\\n\"]),pickVertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nvoid main() {\\n  vWeight = weight;\\n\\n  fragId = pickId;\\n\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"])}},248:function(t,e,r){var n=r(6832),i=r(5158),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  vec4 startPoint = project(position);\\n  vec4 endPoint   = project(nextPosition);\\n\\n  vec2 A = startPoint.xy / startPoint.w;\\n  vec2 B =   endPoint.xy /   endPoint.w;\\n\\n  float clipAngle = atan(\\n    (B.y - A.y) * screenShape.y,\\n    (B.x - A.x) * screenShape.x\\n  );\\n\\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(\\n    sin(clipAngle),\\n    -cos(clipAngle)\\n  ) / screenShape;\\n\\n  gl_Position = vec4(startPoint.xy + startPoint.w * offset, startPoint.zw);\\n\\n  worldPosition = position;\\n  pixelArcLength = arcLength;\\n  fragColor = color;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3      clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float     dashScale;\\nuniform float     opacity;\\n\\nvarying vec3    worldPosition;\\nvarying float   pixelArcLength;\\nvarying vec4    fragColor;\\n\\nvoid main() {\\n  if (\\n    outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\\n    fragColor.a * opacity == 0.\\n  ) discard;\\n\\n  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n  if(dashWeight < 0.5) {\\n    discard;\\n  }\\n  gl_FragColor = fragColor * opacity;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX  1.70141184e38\\n#define FLOAT_MIN  1.17549435e-38\\n\\n// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl\\nvec4 packFloat(float v) {\\n  float av = abs(v);\\n\\n  //Handle special cases\\n  if(av < FLOAT_MIN) {\\n    return vec4(0.0, 0.0, 0.0, 0.0);\\n  } else if(v > FLOAT_MAX) {\\n    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n  } else if(v < -FLOAT_MAX) {\\n    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n  }\\n\\n  vec4 c = vec4(0,0,0,0);\\n\\n  //Compute exponent and mantissa\\n  float e = floor(log2(av));\\n  float m = av * pow(2.0, -e) - 1.0;\\n\\n  //Unpack mantissa\\n  c[1] = floor(128.0 * m);\\n  m -= c[1] / 128.0;\\n  c[2] = floor(32768.0 * m);\\n  m -= c[2] / 32768.0;\\n  c[3] = floor(8388608.0 * m);\\n\\n  //Unpack exponent\\n  float ebias = e + 127.0;\\n  c[0] = floor(ebias / 2.0);\\n  ebias -= c[0] * 2.0;\\n  c[1] += floor(ebias) * 128.0;\\n\\n  //Unpack sign bit\\n  c[0] += 128.0 * step(0.0, -v);\\n\\n  //Scale back to range\\n  return c / 255.0;\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\\n\\n  gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz);\\n}\"]),l=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];e.createShader=function(t){return i(t,a,o,null,l)},e.createPickShader=function(t){return i(t,a,s,null,l)}},6086:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl||t.scene&&t.scene.gl,r=f(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var o=h(e);o.attributes.position.location=0,o.attributes.nextPosition.location=1,o.attributes.arcLength.location=2,o.attributes.lineWidth.location=3,o.attributes.color.location=4;for(var s=n(e),l=i(e,[{buffer:s,size:3,offset:0,stride:48},{buffer:s,size:3,offset:12,stride:48},{buffer:s,size:1,offset:24,stride:48},{buffer:s,size:1,offset:28,stride:48},{buffer:s,size:4,offset:32,stride:48}]),c=u(new Array(1024),[256,1,4]),p=0;p<1024;++p)c.data[p]=255;var d=a(e,c);d.wrap=e.REPEAT;var v=new y(e,r,o,s,l,d);return v.update(t),v};var n=r(5827),i=r(2944),a=r(8931),o=new Uint8Array(4),s=new Float32Array(o.buffer),l=r(5070),u=r(5050),c=r(248),f=c.createShader,h=c.createPickShader,p=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function d(t,e){for(var r=0,n=0;n<3;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function v(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function g(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function y(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.hasAlpha=!1,this.dirty=!0,this.pixelRatio=1}var m=y.prototype;m.isTransparent=function(){return this.hasAlpha},m.isOpaque=function(){return!this.hasAlpha},m.pickSlots=1,m.setPickBase=function(t){this.pickId=t},m.drawTransparent=m.draw=function(t){if(this.vertexCount){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,clipBounds:v(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},m.drawPick=function(t){if(this.vertexCount){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,pickId:this.pickId,clipBounds:v(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},m.update=function(t){var e,r;this.dirty=!0;var n=!!t.connectGaps;\"dashScale\"in t&&(this.dashScale=t.dashScale),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var i=[],a=[],o=[],s=0,c=0,f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],h=t.position||t.positions;if(h){var p=t.color||t.colors||[0,0,0,1],v=t.lineWidth||1,g=!1;t:for(e=1;e<h.length;++e){var y,m,x,b=h[e-1],_=h[e];for(a.push(s),o.push(b.slice()),r=0;r<3;++r){if(isNaN(b[r])||isNaN(_[r])||!isFinite(b[r])||!isFinite(_[r])){if(!n&&i.length>0){for(var w=0;w<24;++w)i.push(i[i.length-12]);c+=2,g=!0}continue t}f[0][r]=Math.min(f[0][r],b[r],_[r]),f[1][r]=Math.max(f[1][r],b[r],_[r])}Array.isArray(p[0])?(y=p.length>e-1?p[e-1]:p.length>0?p[p.length-1]:[0,0,0,1],m=p.length>e?p[e]:p.length>0?p[p.length-1]:[0,0,0,1]):y=m=p,3===y.length&&(y=[y[0],y[1],y[2],1]),3===m.length&&(m=[m[0],m[1],m[2],1]),!this.hasAlpha&&y[3]<1&&(this.hasAlpha=!0),x=Array.isArray(v)?v.length>e-1?v[e-1]:v.length>0?v[v.length-1]:[0,0,0,1]:v;var T=s;if(s+=d(b,_),g){for(r=0;r<2;++r)i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,y[0],y[1],y[2],y[3]);c+=2,g=!1}i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,y[0],y[1],y[2],y[3],b[0],b[1],b[2],_[0],_[1],_[2],T,-x,y[0],y[1],y[2],y[3],_[0],_[1],_[2],b[0],b[1],b[2],s,-x,m[0],m[1],m[2],m[3],_[0],_[1],_[2],b[0],b[1],b[2],s,x,m[0],m[1],m[2],m[3]),c+=4}}if(this.buffer.update(i),a.push(s),o.push(h[h.length-1].slice()),this.bounds=f,this.vertexCount=c,this.points=o,this.arcLength=a,\"dashes\"in t){var k=t.dashes.slice();for(k.unshift(0),e=1;e<k.length;++e)k[e]=k[e-1]+k[e];var A=u(new Array(1024),[256,1,4]);for(e=0;e<256;++e){for(r=0;r<4;++r)A.set(e,0,r,0);1&l.le(k,k[k.length-1]*e/255)?A.set(e,0,0,0):A.set(e,0,0,255)}this.texture.setPixels(A)}},m.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()},m.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=function(t,e,r,n){return o[0]=0,o[1]=r,o[2]=e,o[3]=t,s[0]}(t.value[0],t.value[1],t.value[2]),r=l.le(this.arcLength,e);if(r<0)return null;if(r===this.arcLength.length-1)return new g(this.arcLength[this.arcLength.length-1],this.points[this.points.length-1].slice(),r);for(var n=this.points[r],i=this.points[Math.min(r+1,this.points.length-1)],a=(e-this.arcLength[r])/(this.arcLength[r+1]-this.arcLength[r]),u=1-a,c=[0,0,0],f=0;f<3;++f)c[f]=u*n[f]+a*i[f];var h=Math.min(a<.5?r:r+1,this.points.length-1);return new g(e,c,h,this.points[h])}},7332:function(t){t.exports=function(t){var e=new Float32Array(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e}},9823:function(t){t.exports=function(){var t=new Float32Array(16);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},7787:function(t){t.exports=function(t){var e=t[0],r=t[1],n=t[2],i=t[3],a=t[4],o=t[5],s=t[6],l=t[7],u=t[8],c=t[9],f=t[10],h=t[11],p=t[12],d=t[13],v=t[14],g=t[15];return(e*o-r*a)*(f*g-h*v)-(e*s-n*a)*(c*g-h*d)+(e*l-i*a)*(c*v-f*d)+(r*s-n*o)*(u*g-h*p)-(r*l-i*o)*(u*v-f*p)+(n*l-i*s)*(u*d-c*p)}},5950:function(t){t.exports=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r+r,s=n+n,l=i+i,u=r*o,c=n*o,f=n*s,h=i*o,p=i*s,d=i*l,v=a*o,g=a*s,y=a*l;return t[0]=1-f-d,t[1]=c+y,t[2]=h-g,t[3]=0,t[4]=c-y,t[5]=1-u-d,t[6]=p+v,t[7]=0,t[8]=h+g,t[9]=p-v,t[10]=1-u-f,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},7280:function(t){t.exports=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=n+n,l=i+i,u=a+a,c=n*s,f=n*l,h=n*u,p=i*l,d=i*u,v=a*u,g=o*s,y=o*l,m=o*u;return t[0]=1-(p+v),t[1]=f+m,t[2]=h-y,t[3]=0,t[4]=f-m,t[5]=1-(c+v),t[6]=d+g,t[7]=0,t[8]=h+y,t[9]=d-g,t[10]=1-(c+p),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}},9947:function(t){t.exports=function(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},7437:function(t){t.exports=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],f=e[9],h=e[10],p=e[11],d=e[12],v=e[13],g=e[14],y=e[15],m=r*s-n*o,x=r*l-i*o,b=r*u-a*o,_=n*l-i*s,w=n*u-a*s,T=i*u-a*l,k=c*v-f*d,A=c*g-h*d,M=c*y-p*d,S=f*g-h*v,E=f*y-p*v,L=h*y-p*g,C=m*L-x*E+b*S+_*M-w*A+T*k;return C?(C=1/C,t[0]=(s*L-l*E+u*S)*C,t[1]=(i*E-n*L-a*S)*C,t[2]=(v*T-g*w+y*_)*C,t[3]=(h*w-f*T-p*_)*C,t[4]=(l*M-o*L-u*A)*C,t[5]=(r*L-i*M+a*A)*C,t[6]=(g*b-d*T-y*x)*C,t[7]=(c*T-h*b+p*x)*C,t[8]=(o*E-s*M+u*k)*C,t[9]=(n*M-r*E-a*k)*C,t[10]=(d*w-v*b+y*m)*C,t[11]=(f*b-c*w-p*m)*C,t[12]=(s*A-o*S-l*k)*C,t[13]=(r*S-n*A+i*k)*C,t[14]=(v*x-d*_-g*m)*C,t[15]=(c*_-f*x+h*m)*C,t):null}},3012:function(t,e,r){var n=r(9947);t.exports=function(t,e,r,i){var a,o,s,l,u,c,f,h,p,d,v=e[0],g=e[1],y=e[2],m=i[0],x=i[1],b=i[2],_=r[0],w=r[1],T=r[2];return Math.abs(v-_)<1e-6&&Math.abs(g-w)<1e-6&&Math.abs(y-T)<1e-6?n(t):(f=v-_,h=g-w,p=y-T,a=x*(p*=d=1/Math.sqrt(f*f+h*h+p*p))-b*(h*=d),o=b*(f*=d)-m*p,s=m*h-x*f,(d=Math.sqrt(a*a+o*o+s*s))?(a*=d=1/d,o*=d,s*=d):(a=0,o=0,s=0),l=h*s-p*o,u=p*a-f*s,c=f*o-h*a,(d=Math.sqrt(l*l+u*u+c*c))?(l*=d=1/d,u*=d,c*=d):(l=0,u=0,c=0),t[0]=a,t[1]=l,t[2]=f,t[3]=0,t[4]=o,t[5]=u,t[6]=h,t[7]=0,t[8]=s,t[9]=c,t[10]=p,t[11]=0,t[12]=-(a*v+o*g+s*y),t[13]=-(l*v+u*g+c*y),t[14]=-(f*v+h*g+p*y),t[15]=1,t)}},104:function(t){t.exports=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],u=e[6],c=e[7],f=e[8],h=e[9],p=e[10],d=e[11],v=e[12],g=e[13],y=e[14],m=e[15],x=r[0],b=r[1],_=r[2],w=r[3];return t[0]=x*n+b*s+_*f+w*v,t[1]=x*i+b*l+_*h+w*g,t[2]=x*a+b*u+_*p+w*y,t[3]=x*o+b*c+_*d+w*m,x=r[4],b=r[5],_=r[6],w=r[7],t[4]=x*n+b*s+_*f+w*v,t[5]=x*i+b*l+_*h+w*g,t[6]=x*a+b*u+_*p+w*y,t[7]=x*o+b*c+_*d+w*m,x=r[8],b=r[9],_=r[10],w=r[11],t[8]=x*n+b*s+_*f+w*v,t[9]=x*i+b*l+_*h+w*g,t[10]=x*a+b*u+_*p+w*y,t[11]=x*o+b*c+_*d+w*m,x=r[12],b=r[13],_=r[14],w=r[15],t[12]=x*n+b*s+_*f+w*v,t[13]=x*i+b*l+_*h+w*g,t[14]=x*a+b*u+_*p+w*y,t[15]=x*o+b*c+_*d+w*m,t}},5268:function(t){t.exports=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),u=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*u,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*u,t[15]=1,t}},1120:function(t){t.exports=function(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t}},4422:function(t){t.exports=function(t,e,r,n){var i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,w,T,k,A,M,S,E=n[0],L=n[1],C=n[2],P=Math.sqrt(E*E+L*L+C*C);return Math.abs(P)<1e-6?null:(E*=P=1/P,L*=P,C*=P,i=Math.sin(r),o=1-(a=Math.cos(r)),s=e[0],l=e[1],u=e[2],c=e[3],f=e[4],h=e[5],p=e[6],d=e[7],v=e[8],g=e[9],y=e[10],m=e[11],x=E*E*o+a,b=L*E*o+C*i,_=C*E*o-L*i,w=E*L*o-C*i,T=L*L*o+a,k=C*L*o+E*i,A=E*C*o+L*i,M=L*C*o-E*i,S=C*C*o+a,t[0]=s*x+f*b+v*_,t[1]=l*x+h*b+g*_,t[2]=u*x+p*b+y*_,t[3]=c*x+d*b+m*_,t[4]=s*w+f*T+v*k,t[5]=l*w+h*T+g*k,t[6]=u*w+p*T+y*k,t[7]=c*w+d*T+m*k,t[8]=s*A+f*M+v*S,t[9]=l*A+h*M+g*S,t[10]=u*A+p*M+y*S,t[11]=c*A+d*M+m*S,e!==t&&(t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t)}},6109:function(t){t.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[4],o=e[5],s=e[6],l=e[7],u=e[8],c=e[9],f=e[10],h=e[11];return e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[4]=a*i+u*n,t[5]=o*i+c*n,t[6]=s*i+f*n,t[7]=l*i+h*n,t[8]=u*i-a*n,t[9]=c*i-o*n,t[10]=f*i-s*n,t[11]=h*i-l*n,t}},7115:function(t){t.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],u=e[8],c=e[9],f=e[10],h=e[11];return e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[0]=a*i-u*n,t[1]=o*i-c*n,t[2]=s*i-f*n,t[3]=l*i-h*n,t[8]=a*n+u*i,t[9]=o*n+c*i,t[10]=s*n+f*i,t[11]=l*n+h*i,t}},5240:function(t){t.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],u=e[4],c=e[5],f=e[6],h=e[7];return e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[0]=a*i+u*n,t[1]=o*i+c*n,t[2]=s*i+f*n,t[3]=l*i+h*n,t[4]=u*i-a*n,t[5]=c*i-o*n,t[6]=f*i-s*n,t[7]=h*i-l*n,t}},3668:function(t){t.exports=function(t,e,r){var n=r[0],i=r[1],a=r[2];return t[0]=e[0]*n,t[1]=e[1]*n,t[2]=e[2]*n,t[3]=e[3]*n,t[4]=e[4]*i,t[5]=e[5]*i,t[6]=e[6]*i,t[7]=e[7]*i,t[8]=e[8]*a,t[9]=e[9]*a,t[10]=e[10]*a,t[11]=e[11]*a,t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t}},998:function(t){t.exports=function(t,e,r){var n,i,a,o,s,l,u,c,f,h,p,d,v=r[0],g=r[1],y=r[2];return e===t?(t[12]=e[0]*v+e[4]*g+e[8]*y+e[12],t[13]=e[1]*v+e[5]*g+e[9]*y+e[13],t[14]=e[2]*v+e[6]*g+e[10]*y+e[14],t[15]=e[3]*v+e[7]*g+e[11]*y+e[15]):(n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],u=e[6],c=e[7],f=e[8],h=e[9],p=e[10],d=e[11],t[0]=n,t[1]=i,t[2]=a,t[3]=o,t[4]=s,t[5]=l,t[6]=u,t[7]=c,t[8]=f,t[9]=h,t[10]=p,t[11]=d,t[12]=n*v+s*g+f*y+e[12],t[13]=i*v+l*g+h*y+e[13],t[14]=a*v+u*g+p*y+e[14],t[15]=o*v+c*g+d*y+e[15]),t}},2142:function(t){t.exports=function(t,e){if(t===e){var r=e[1],n=e[2],i=e[3],a=e[6],o=e[7],s=e[11];t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=r,t[6]=e[9],t[7]=e[13],t[8]=n,t[9]=a,t[11]=e[14],t[12]=i,t[13]=o,t[14]=s}else t[0]=e[0],t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=e[1],t[5]=e[5],t[6]=e[9],t[7]=e[13],t[8]=e[2],t[9]=e[6],t[10]=e[10],t[11]=e[14],t[12]=e[3],t[13]=e[7],t[14]=e[11],t[15]=e[15];return t}},4340:function(t,e,r){\"use strict\";var n=r(957),i=r(7309);function a(t,e){for(var r=[0,0,0,0],n=0;n<4;++n)for(var i=0;i<4;++i)r[i]+=t[4*n+i]*e[n];return r}function o(t,e,r,n,i){for(var o=a(n,a(r,a(e,[t[0],t[1],t[2],1]))),s=0;s<3;++s)o[s]/=o[3];return[.5*i[0]*(1+o[0]),.5*i[1]*(1-o[1])]}function s(t,e){for(var r=[0,0,0],n=0;n<t.length;++n)for(var i=t[n],a=e[n],o=0;o<3;++o)r[o]+=a*i[o];return r}t.exports=function(t,e,r,a,l,u){if(1===t.length)return[0,t[0].slice()];for(var c=new Array(t.length),f=0;f<t.length;++f)c[f]=o(t[f],r,a,l,u);var h=0,p=1/0;for(f=0;f<c.length;++f){for(var d=0,v=0;v<2;++v)d+=Math.pow(c[f][v]-e[v],2);d<p&&(p=d,h=f)}var g=function(t,e){if(2===t.length){for(var r=0,a=0,o=0;o<2;++o)r+=Math.pow(e[o]-t[0][o],2),a+=Math.pow(e[o]-t[1][o],2);return(r=Math.sqrt(r))+(a=Math.sqrt(a))<1e-6?[1,0]:[a/(r+a),r/(a+r)]}if(3===t.length){var s=[0,0];return i(t[0],t[1],t[2],e,s),n(t,s)}return[]}(c,e),y=0;for(f=0;f<3;++f){if(g[f]<-.001||g[f]>1.0001)return null;y+=g[f]}return Math.abs(y-1)>.001?null:[h,s(t,g),g]}},2056:function(t,e,r){var n=r(6832),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n           , view\\n           , projection\\n           , inverseModel;\\nuniform vec3 eyePosition\\n           , lightPosition;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  gl_Position      = project(position);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * vec4(position , 1.0);\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal  = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  f_color          = color;\\n  f_data           = position;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n            , fresnel\\n            , kambient\\n            , kdiffuse\\n            , kspecular;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (f_color.a == 0.0 ||\\n    outOfRange(clipBounds[0], clipBounds[1], f_data)\\n  ) discard;\\n\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\\n\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * f_color.a;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_color = color;\\n  f_data  = position;\\n  f_uv    = uv;\\n}\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\\n\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\\n  } else {\\n    gl_Position = projection * view * model * vec4(position, 1.0);\\n  }\\n  gl_PointSize = pointSize;\\n  f_color = color;\\n  f_uv = uv;\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\\n  if(dot(pointR, pointR) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_id        = id;\\n  f_position  = position;\\n}\"]),f=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]),h=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3  position;\\nattribute float pointSize;\\nattribute vec4  id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\\n  } else {\\n    gl_Position  = projection * view * model * vec4(position, 1.0);\\n    gl_PointSize = pointSize;\\n  }\\n  f_id         = id;\\n  f_position   = position;\\n}\"]),p=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n}\"]),d=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n  gl_FragColor = vec4(contourColor, 1.0);\\n}\\n\"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},e.wireShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},e.pointShader={vertex:l,fragment:u,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},e.pickShader={vertex:c,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},e.pointPickShader={vertex:h,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},e.contourShader={vertex:p,fragment:d,attributes:[{name:\"position\",type:\"vec3\"}]}},8116:function(t,e,r){\"use strict\";var n=r(5158),i=r(5827),a=r(2944),o=r(8931),s=r(115),l=r(104),u=r(7437),c=r(5050),f=r(9156),h=r(7212),p=r(5306),d=r(2056),v=r(4340),g=d.meshShader,y=d.wireShader,m=d.pointShader,x=d.pickShader,b=d.pointPickShader,_=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function T(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,T,k,A,M,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=c,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=u,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=g,this.edgeUVs=y,this.edgeIds=v,this.edgeVAO=m,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=T,this.pointSizes=k,this.pointIds=b,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=M,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var k=T.prototype;function A(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}function M(t){var e=n(t,m.vertex,m.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function S(t){var e=n(t,x.vertex,x.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e}function E(t){var e=n(t,b.vertex,b.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function L(t){var e=n(t,_.vertex,_.fragment);return e.attributes.position.location=0,e}k.isOpaque=function(){return!this.hasAlpha},k.isTransparent=function(){return this.hasAlpha},k.pickSlots=1,k.setPickBase=function(t){this.pickId=t},k.highlight=function(t){if(t&&this.contourEnable){for(var e=h(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l<a;++l)for(var u=r[l],c=0;c<2;++c){var f=u[0];2===u.length&&(f=u[c]);for(var d=n[f][0],v=n[f][1],g=i[f],y=1-g,m=this.positions[d],x=this.positions[v],b=0;b<3;++b)o[s++]=g*m[b]+y*x[b]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),p.free(o)}else this.contourCount=0},k.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=t.opacity,this.opacity<1&&(this.hasAlpha=!0)),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale,this.hasAlpha=!0),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),t.texture?(this.texture.dispose(),this.texture=o(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t,e){for(var r=f({colormap:t,nshades:256,format:\"rgba\"}),n=new Uint8Array(1024),i=0;i<256;++i){for(var a=r[i],o=0;o<3;++o)n[4*i+o]=a[o];n[4*i+3]=e?255*A(i/255,e):255*a[3]}return c(n,[256,256,4],[4,0,1])}(t.colormap,this.opacityscale)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var i=[],a=[],l=[],u=[],h=[],p=[],d=[],v=[],g=[],y=[],m=[],x=[],b=[],_=[];this.cells=r,this.positions=n;var w=t.vertexNormals,T=t.cellNormals,k=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,M=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!T&&(T=s.faceNormals(r,n,M)),T||w||(w=s.vertexNormals(r,n,k));var S=t.vertexColors,E=t.cellColors,L=t.meshColor||[1,1,1,1],C=t.vertexUVs,P=t.vertexIntensity,O=t.cellUVs,I=t.cellIntensity,D=1/0,z=-1/0;if(!C&&!O)if(P)if(t.vertexIntensityBounds)D=+t.vertexIntensityBounds[0],z=+t.vertexIntensityBounds[1];else for(var R=0;R<P.length;++R){var F=P[R];D=Math.min(D,F),z=Math.max(z,F)}else if(I)if(t.cellIntensityBounds)D=+t.cellIntensityBounds[0],z=+t.cellIntensityBounds[1];else for(R=0;R<I.length;++R)F=I[R],D=Math.min(D,F),z=Math.max(z,F);else for(R=0;R<n.length;++R)F=n[R][2],D=Math.min(D,F),z=Math.max(z,F);this.intensity=P||I||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n),this.pickVertex=!(I||E);var B=t.pointSizes,N=t.pointSize||1;for(this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],R=0;R<n.length;++R)for(var j=n[R],U=0;U<3;++U)!isNaN(j[U])&&isFinite(j[U])&&(this.bounds[0][U]=Math.min(this.bounds[0][U],j[U]),this.bounds[1][U]=Math.max(this.bounds[1][U],j[U]));var V=0,H=0,q=0;t:for(R=0;R<r.length;++R){var G=r[R];switch(G.length){case 1:for(j=n[Y=G[0]],U=0;U<3;++U)if(isNaN(j[U])||!isFinite(j[U]))continue t;y.push(j[0],j[1],j[2]),W=S?S[Y]:E?E[R]:L,this.opacityscale&&P?a.push(W[0],W[1],W[2],this.opacity*A((P[Y]-D)/(z-D),this.opacityscale)):3===W.length?m.push(W[0],W[1],W[2],this.opacity):(m.push(W[0],W[1],W[2],W[3]*this.opacity),W[3]<1&&(this.hasAlpha=!0)),X=C?C[Y]:P?[(P[Y]-D)/(z-D),0]:O?O[R]:I?[(I[R]-D)/(z-D),0]:[(j[2]-D)/(z-D),0],x.push(X[0],X[1]),B?b.push(B[Y]):b.push(N),_.push(R),q+=1;break;case 2:for(U=0;U<2;++U){j=n[Y=G[U]];for(var Z=0;Z<3;++Z)if(isNaN(j[Z])||!isFinite(j[Z]))continue t}for(U=0;U<2;++U)j=n[Y=G[U]],p.push(j[0],j[1],j[2]),W=S?S[Y]:E?E[R]:L,this.opacityscale&&P?a.push(W[0],W[1],W[2],this.opacity*A((P[Y]-D)/(z-D),this.opacityscale)):3===W.length?d.push(W[0],W[1],W[2],this.opacity):(d.push(W[0],W[1],W[2],W[3]*this.opacity),W[3]<1&&(this.hasAlpha=!0)),X=C?C[Y]:P?[(P[Y]-D)/(z-D),0]:O?O[R]:I?[(I[R]-D)/(z-D),0]:[(j[2]-D)/(z-D),0],v.push(X[0],X[1]),g.push(R);H+=1;break;case 3:for(U=0;U<3;++U)for(j=n[Y=G[U]],Z=0;Z<3;++Z)if(isNaN(j[Z])||!isFinite(j[Z]))continue t;for(U=0;U<3;++U){var Y,W,X,J;j=n[Y=G[2-U]],i.push(j[0],j[1],j[2]),(W=S?S[Y]:E?E[R]:L)?this.opacityscale&&P?a.push(W[0],W[1],W[2],this.opacity*A((P[Y]-D)/(z-D),this.opacityscale)):3===W.length?a.push(W[0],W[1],W[2],this.opacity):(a.push(W[0],W[1],W[2],W[3]*this.opacity),W[3]<1&&(this.hasAlpha=!0)):a.push(.5,.5,.5,1),X=C?C[Y]:P?[(P[Y]-D)/(z-D),0]:O?O[R]:I?[(I[R]-D)/(z-D),0]:[(j[2]-D)/(z-D),0],u.push(X[0],X[1]),J=w?w[Y]:T[R],l.push(J[0],J[1],J[2]),h.push(R)}V+=1}}this.pointCount=q,this.edgeCount=H,this.triangleCount=V,this.pointPositions.update(y),this.pointColors.update(m),this.pointUVs.update(x),this.pointSizes.update(b),this.pointIds.update(new Uint32Array(_)),this.edgePositions.update(p),this.edgeColors.update(d),this.edgeUVs.update(v),this.edgeIds.update(new Uint32Array(g)),this.trianglePositions.update(i),this.triangleColors.update(a),this.triangleUVs.update(u),this.triangleNormals.update(l),this.triangleIds.update(new Uint32Array(h))}},k.drawTransparent=k.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,inverseModel:w.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],contourColor:this.contourColor,texture:0};s.inverseModel=u(s.inverseModel,s.model),e.disable(e.CULL_FACE),this.texture.bind(0);var c=new Array(16);for(l(c,s.view,s.model),l(c,s.projection,c),u(c,c),o=0;o<3;++o)s.eyePosition[o]=c[12+o]/c[15];var f,h=c[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*c[4*o+3];for(o=0;o<3;++o){for(var p=c[12+o],d=0;d<3;++d)p+=c[4*d+o]*this.lightPosition[d];s.lightPosition[o]=p/h}this.triangleCount>0&&((f=this.triShader).bind(),f.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&this.lineWidth>0&&((f=this.lineShader).bind(),f.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0&&((f=this.pointShader).bind(),f.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()),this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((f=this.contourShader).bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},k.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255};(s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},k.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=t.coord[0],s=t.coord[1];if(!this.pickVertex){var l=this.positions[r[0]],u=this.positions[r[1]],c=this.positions[r[2]],f=[(l[0]+u[0]+c[0])/3,(l[1]+u[1]+c[1])/3,(l[2]+u[2]+c[2])/3];return{_cellCenter:!0,position:[o,s],index:e,cell:r,cellId:e,intensity:this.intensity[e],dataCoordinate:f}}var h=v(i,[o*this.pixelRatio,this._resolution[1]-s*this.pixelRatio],this._model,this._view,this._projection,this._resolution);if(!h)return null;var p=h[2],d=0;for(a=0;a<r.length;++a)d+=p[a]*this.intensity[r[a]];return{position:h[1],index:r[h[0]],cell:r,cellId:e,intensity:d,dataCoordinate:this.positions[r[h[0]]]}},k.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},t.exports=function(t,e){if(1===arguments.length&&(t=(e=t).gl),!(t.getExtension(\"OES_standard_derivatives\")||t.getExtension(\"MOZ_OES_standard_derivatives\")||t.getExtension(\"WEBKIT_OES_standard_derivatives\")))throw new Error(\"derivatives not supported\");var r=function(t){var e=n(t,g.vertex,g.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}(t),s=function(t){var e=n(t,y.vertex,y.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}(t),l=M(t),u=S(t),f=E(t),h=L(t),p=o(t,c(new Uint8Array([255,255,255,255]),[1,1,4]));p.generateMipmap(),p.minFilter=t.LINEAR_MIPMAP_LINEAR,p.magFilter=t.LINEAR;var d=i(t),v=i(t),m=i(t),x=i(t),b=i(t),_=a(t,[{buffer:d,type:t.FLOAT,size:3},{buffer:b,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:v,type:t.FLOAT,size:4},{buffer:m,type:t.FLOAT,size:2},{buffer:x,type:t.FLOAT,size:3}]),w=i(t),k=i(t),A=i(t),C=i(t),P=a(t,[{buffer:w,type:t.FLOAT,size:3},{buffer:C,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:k,type:t.FLOAT,size:4},{buffer:A,type:t.FLOAT,size:2}]),O=i(t),I=i(t),D=i(t),z=i(t),R=i(t),F=a(t,[{buffer:O,type:t.FLOAT,size:3},{buffer:R,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:I,type:t.FLOAT,size:4},{buffer:D,type:t.FLOAT,size:2},{buffer:z,type:t.FLOAT,size:1}]),B=i(t),N=new T(t,p,r,s,l,u,f,h,d,b,v,m,x,_,w,C,k,A,P,O,R,I,D,z,F,B,a(t,[{buffer:B,type:t.FLOAT,size:3}]));return N.update(e),N}},4554:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl;return new o(t,n(e,[0,0,0,1,1,0,1,1]),i(e,a.boxVert,a.lineFrag))};var n=r(5827),i=r(5158),a=r(2709);function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,u=o.prototype;u.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},u.drawBox=(s=[0,0],l=[0,0],function(t,e,r,n,i){var a=this.plot,o=this.shader,u=a.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,o.uniforms.lo=s,o.uniforms.hi=l,o.uniforms.color=i,u.drawArrays(u.TRIANGLE_STRIP,0,4)}),u.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},3016:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl;return new s(t,n(e),i(e,o.gridVert,o.gridFrag),i(e,o.tickVert,o.gridFrag))};var n=r(5827),i=r(5158),a=r(5070),o=r(2709);function s(t,e,r,n){this.plot=t,this.vbo=e,this.shader=r,this.tickShader=n,this.ticks=[[],[]]}function l(t,e){return t-e}var u,c,f,h,p,d=s.prototype;d.draw=(u=[0,0],c=[0,0],f=[0,0],function(){for(var t=this.plot,e=this.vbo,r=this.shader,n=this.ticks,i=t.gl,a=t._tickBounds,o=t.dataBox,s=t.viewBox,l=t.gridLineWidth,h=t.gridLineColor,p=t.gridLineEnable,d=t.pixelRatio,v=0;v<2;++v){var g=a[v],y=a[v+2]-g,m=.5*(o[v+2]+o[v]),x=o[v+2]-o[v];c[v]=2*y/x,u[v]=2*(g-m)/x}r.bind(),e.bind(),r.attributes.dataCoord.pointer(),r.uniforms.dataShift=u,r.uniforms.dataScale=c;var b=0;for(v=0;v<2;++v){f[0]=f[1]=0,f[v]=1,r.uniforms.dataAxis=f,r.uniforms.lineWidth=l[v]/(s[v+2]-s[v])*d,r.uniforms.color=h[v];var _=6*n[v].length;p[v]&&_&&i.drawArrays(i.TRIANGLES,b,_),b+=_}}),d.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],i=[0,0],o=[0,0];return function(){for(var s=this.plot,u=this.vbo,c=this.tickShader,f=this.ticks,h=s.gl,p=s._tickBounds,d=s.dataBox,v=s.viewBox,g=s.pixelRatio,y=s.screenBox,m=y[2]-y[0],x=y[3]-y[1],b=v[2]-v[0],_=v[3]-v[1],w=0;w<2;++w){var T=p[w],k=p[w+2]-T,A=.5*(d[w+2]+d[w]),M=d[w+2]-d[w];e[w]=2*k/M,t[w]=2*(T-A)/M}e[0]*=b/m,t[0]*=b/m,e[1]*=_/x,t[1]*=_/x,c.bind(),u.bind(),c.attributes.dataCoord.pointer();var S=c.uniforms;S.dataShift=t,S.dataScale=e;var E=s.tickMarkLength,L=s.tickMarkWidth,C=s.tickMarkColor,P=6*f[0].length,O=Math.min(a.ge(f[0],(d[0]-p[0])/(p[2]-p[0]),l),f[0].length),I=Math.min(a.gt(f[0],(d[2]-p[0])/(p[2]-p[0]),l),f[0].length),D=0+6*O,z=6*Math.max(0,I-O),R=Math.min(a.ge(f[1],(d[1]-p[1])/(p[3]-p[1]),l),f[1].length),F=Math.min(a.gt(f[1],(d[3]-p[1])/(p[3]-p[1]),l),f[1].length),B=P+6*R,N=6*Math.max(0,F-R);i[0]=2*(v[0]-E[1])/m-1,i[1]=(v[3]+v[1])/x-1,o[0]=E[1]*g/m,o[1]=L[1]*g/x,N&&(S.color=C[1],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(v[2]+v[0])/m-1,i[1]=2*(v[1]-E[0])/x-1,o[0]=L[0]*g/m,o[1]=E[0]*g/x,z&&(S.color=C[0],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,D,z)),i[0]=2*(v[2]+E[3])/m-1,i[1]=(v[3]+v[1])/x-1,o[0]=E[3]*g/m,o[1]=L[3]*g/x,N&&(S.color=C[3],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(v[2]+v[0])/m-1,i[1]=2*(v[3]+E[2])/x-1,o[0]=L[2]*g/m,o[1]=E[2]*g/x,z&&(S.color=C[2],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,D,z))}}(),d.update=(h=[1,1,-1,-1,1,-1],p=[1,-1,1,1,-1,-1],function(t){for(var e=t.ticks,r=t.bounds,n=new Float32Array(18*(e[0].length+e[1].length)),i=(this.plot.zeroLineEnable,0),a=[[],[]],o=0;o<2;++o)for(var s=a[o],l=e[o],u=r[o],c=r[o+2],f=0;f<l.length;++f){var d=(l[f].x-u)/(c-u);s.push(d);for(var v=0;v<6;++v)n[i++]=d,n[i++]=h[v],n[i++]=p[v]}this.ticks=a,this.vbo.update(n)}),d.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},1154:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl;return new o(t,n(e,[-1,-1,-1,1,1,-1,1,1]),i(e,a.lineVert,a.lineFrag))};var n=r(5827),i=r(5158),a=r(2709);function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,u=o.prototype;u.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},u.drawLine=(s=[0,0],l=[0,0],function(t,e,r,n,i,a){var o=this.plot,u=this.shader,c=o.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,u.uniforms.start=s,u.uniforms.end=l,u.uniforms.width=i*o.pixelRatio,u.uniforms.color=a,c.drawArrays(c.TRIANGLE_STRIP,0,4)}),u.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},2709:function(t,e,r){\"use strict\";var n=r(6832),i=n([\"precision lowp float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = vec4(color.xyz * color.w, color.w);\\n}\\n\"]);t.exports={lineVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 start, end;\\nuniform float width;\\n\\nvec2 perp(vec2 v) {\\n  return vec2(v.y, -v.x);\\n}\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  vec2 delta = normalize(perp(start - end));\\n  vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\\n  gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\\n}\\n\"]),lineFrag:i,textVert:n([\"#define GLSLIFY 1\\nattribute vec3 textCoordinate;\\n\\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\\nuniform float angle;\\n\\nvoid main() {\\n  float dataOffset  = textCoordinate.z;\\n  vec2 glyphOffset  = textCoordinate.xy;\\n  mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\\n  vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\\n    glyphMatrix * glyphOffset * textScale + screenOffset;\\n  gl_Position = vec4(screenCoordinate, 0, 1);\\n}\\n\"]),textFrag:i,gridVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale;\\nuniform float lineWidth;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\\n  gl_Position = vec4(pos, 0, 1);\\n}\\n\"]),gridFrag:i,boxVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 lo, hi;\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\\n}\\n\"]),tickVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\\n}\\n\"])}},5613:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl;return new l(t,n(e),i(e,s.textVert,s.textFrag))};var n=r(5827),i=r(5158),a=r(6946),o=r(5070),s=r(2709);function l(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}var u,c,f,h,p,d,v=l.prototype;v.drawTicks=(u=[0,0],c=[0,0],f=[0,0],function(t){var e=this.plot,r=this.shader,n=this.tickX[t],i=this.tickOffset[t],a=e.gl,s=e.viewBox,l=e.dataBox,h=e.screenBox,p=e.pixelRatio,d=e.tickEnable,v=e.tickPad,g=e.tickColor,y=e.tickAngle,m=e.labelEnable,x=e.labelPad,b=e.labelColor,_=e.labelAngle,w=this.labelOffset[t],T=this.labelCount[t],k=o.lt(n,l[t]),A=o.le(n,l[t+2]);u[0]=u[1]=0,u[t]=1,c[t]=(s[2+t]+s[t])/(h[2+t]-h[t])-1;var M=2/h[2+(1^t)]-h[1^t];c[1^t]=M*s[1^t]-1,d[t]&&(c[1^t]-=M*p*v[t],k<A&&i[A]>i[k]&&(r.uniforms.dataAxis=u,r.uniforms.screenOffset=c,r.uniforms.color=g[t],r.uniforms.angle=y[t],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),m[t]&&T&&(c[1^t]-=M*p*x[t],r.uniforms.dataAxis=f,r.uniforms.screenOffset=c,r.uniforms.color=b[t],r.uniforms.angle=_[t],a.drawArrays(a.TRIANGLES,w,T)),c[1^t]=M*s[2+(1^t)]-1,d[t+2]&&(c[1^t]+=M*p*v[t+2],k<A&&i[A]>i[k]&&(r.uniforms.dataAxis=u,r.uniforms.screenOffset=c,r.uniforms.color=g[t+2],r.uniforms.angle=y[t+2],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),m[t+2]&&T&&(c[1^t]+=M*p*x[t+2],r.uniforms.dataAxis=f,r.uniforms.screenOffset=c,r.uniforms.color=b[t+2],r.uniforms.angle=_[t+2],a.drawArrays(a.TRIANGLES,w,T))}),v.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,u=r.pixelRatio;if(this.titleCount){for(var c=0;c<2;++c)e[c]=2*(o[c]*u-a[c])/(a[2+c]-a[c])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}}(),v.bind=(h=[0,0],p=[0,0],d=[0,0],function(){var t=this.plot,e=this.shader,r=t._tickBounds,n=t.dataBox,i=t.screenBox,a=t.viewBox;e.bind();for(var o=0;o<2;++o){var s=r[o],l=r[o+2]-s,u=.5*(n[o+2]+n[o]),c=n[o+2]-n[o],f=a[o],v=a[o+2]-f,g=i[o],y=i[o+2]-g;p[o]=2*l/c*v/y,h[o]=2*(s-u)/c*v/y}d[1]=2*t.pixelRatio/(i[3]-i[1]),d[0]=d[1]*(i[3]-i[1])/(i[2]-i[0]),e.uniforms.dataScale=p,e.uniforms.dataShift=h,e.uniforms.textScale=d,this.vbo.bind(),e.attributes.textCoordinate.pointer()}),v.update=function(t){var e,r,n,i,o,s=[],l=t.ticks,u=t.bounds;for(o=0;o<2;++o){var c=[Math.floor(s.length/3)],f=[-1/0],h=l[o];for(e=0;e<h.length;++e){var p=h[e],d=p.x,v=p.text,g=p.font||\"sans-serif\";i=p.fontSize||12;for(var y=1/(u[o+2]-u[o]),m=u[o],x=v.split(\"\\n\"),b=0;b<x.length;b++)for(n=a(g,x[b]).data,r=0;r<n.length;r+=2)s.push(n[r]*i,-n[r+1]*i-b*i*1.2,(d-m)*y);c.push(Math.floor(s.length/3)),f.push(d)}this.tickOffset[o]=c,this.tickX[o]=f}for(o=0;o<2;++o){for(this.labelOffset[o]=Math.floor(s.length/3),n=a(t.labelFont[o],t.labels[o],{textAlign:\"center\"}).data,i=t.labelSize[o],e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.labelCount[o]=Math.floor(s.length/3)-this.labelOffset[o]}for(this.titleOffset=Math.floor(s.length/3),n=a(t.titleFont,t.title).data,i=t.titleSize,e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.titleCount=Math.floor(s.length/3)-this.titleOffset,this.vbo.update(s)},v.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},2117:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl,r=new l(e,n(e,[e.drawingBufferWidth,e.drawingBufferHeight]));return r.grid=i(r),r.text=a(r),r.line=o(r),r.box=s(r),r.update(t),r};var n=r(2611),i=r(3016),a=r(5613),o=r(1154),s=r(4554);function l(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-1/0,-1/0],this.static=!1,this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}var u=l.prototype;function c(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function f(t,e){return t.x-e.x}u.setDirty=function(){this.dirty=this.pickDirty=!0},u.setOverlayDirty=function(){this.dirty=!0},u.nextDepthValue=function(){return this._depthCounter++/65536},u.draw=function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,i=this.pixelRatio,a=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){if(this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),this.borderColor){t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var u=this.borderColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT)}t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var c=this.backgroundColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var f=this.zeroLineEnable,h=this.zeroLineColor,p=this.zeroLineWidth;if(f[0]||f[1]){o.bind();for(var d=0;d<2;++d)if(f[d]&&n[d]<=0&&n[d+2]>=0){var v=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(v,e[1],v,e[3],p[d],h[d]):o.drawLine(e[0],v,e[2],v,p[d],h[d])}}for(d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var g=this.borderLineEnable,y=this.borderLineWidth,m=this.borderLineColor;for(g[1]&&o.drawLine(r[0],r[1]-.5*y[1]*i,r[0],r[3]+.5*y[3]*i,y[1],m[1]),g[0]&&o.drawLine(r[0]-.5*y[0]*i,r[1],r[2]+.5*y[2]*i,r[1],y[0],m[0]),g[3]&&o.drawLine(r[2],r[1]-.5*y[1]*i,r[2],r[3]+.5*y[3]*i,y[3],m[3]),g[2]&&o.drawLine(r[0]-.5*y[0]*i,r[3],r[2]+.5*y[2]*i,r[3],y[2],m[2]),s.bind(),d=0;d<2;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();var x=this.overlays;for(d=0;d<x.length;++d)x[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}},u.drawPick=function(){if(!this.static){var t=this.pickBuffer;this.gl,this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}},u.pick=function(t,e){if(!this.static){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),u=this.objects,c=0;c<u.length;++c){var f=u[c].pick(a,o,l);if(f)return f}return null}},u.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},u.setDataBox=function(t){var e=this.dataBox;(e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3])&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},u.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},u.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]),this.screenBox,this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,i=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/i,10,10/i]),this.borderColor=!1!==t.borderColor&&(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=c(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=c(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=c(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t)||!!t.titleEnable,this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=c(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=c(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=c(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var a=t.ticks||[[],[]],o=this._tickBounds;o[0]=o[1]=1/0,o[2]=o[3]=-1/0;for(var s=0;s<2;++s){var l=a[s].slice(0);0!==l.length&&(l.sort(f),o[s]=Math.min(o[s],l[0].x),o[s+2]=Math.max(o[s+2],l[l.length-1].x))}this.grid.update({bounds:o,ticks:a}),this.text.update({bounds:o,ticks:a,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.static=!!t.static,this.setDirty()},u.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();for(this.objects.length=0,t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},u.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},u.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},u.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},u.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},4296:function(t,e,r){\"use strict\";t.exports=function(t,e){t=t||document.body;var r=[.01,1/0];\"distanceLimits\"in(e=e||{})&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]),\"zoomMin\"in e&&(r[0]=e.zoomMin),\"zoomMax\"in e&&(r[1]=e.zoomMax);var u=i({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||\"orbit\",distanceLimits:r}),c=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],f=0,h=t.clientWidth,p=t.clientHeight,d={keyBindingMode:\"rotate\",enableWheel:!0,view:u,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:u.modes,_ortho:e._ortho||e.projection&&\"orthographic\"===e.projection.type||!1,tick:function(){var e=n(),r=this.delay,i=e-2*r;u.idle(e-r),u.recalcMatrix(i),u.flush(e-(100+2*r));for(var a=!0,o=u.computedMatrix,s=0;s<16;++s)a=a&&c[s]===o[s],c[s]=o[s];var l=t.clientWidth===h&&t.clientHeight===p;return h=t.clientWidth,p=t.clientHeight,a?!l:(f=Math.exp(u.computedRadius[0]),!0)},lookAt:function(t,e,r){u.lookAt(u.lastT(),t,e,r)},rotate:function(t,e,r){u.rotate(u.lastT(),t,e,r)},pan:function(t,e,r){u.pan(u.lastT(),t,e,r)},translate:function(t,e,r){u.translate(u.lastT(),t,e,r)}};return Object.defineProperties(d,{matrix:{get:function(){return u.computedMatrix},set:function(t){return u.setMatrix(u.lastT(),t),u.computedMatrix},enumerable:!0},mode:{get:function(){return u.getMode()},set:function(t){var e=u.computedUp.slice(),r=u.computedEye.slice(),i=u.computedCenter.slice();if(u.setMode(t),\"turntable\"===t){var a=n();u._active.lookAt(a,r,i,e),u._active.lookAt(a+500,r,i,[0,0,1]),u._active.flush(a)}return u.getMode()},enumerable:!0},center:{get:function(){return u.computedCenter},set:function(t){return u.lookAt(u.lastT(),null,t),u.computedCenter},enumerable:!0},eye:{get:function(){return u.computedEye},set:function(t){return u.lookAt(u.lastT(),t),u.computedEye},enumerable:!0},up:{get:function(){return u.computedUp},set:function(t){return u.lookAt(u.lastT(),null,null,t),u.computedUp},enumerable:!0},distance:{get:function(){return f},set:function(t){return u.setDistance(u.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return u.getDistanceLimits(r)},set:function(t){return u.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener(\"contextmenu\",(function(t){return t.preventDefault(),!1})),d._lastX=-1,d._lastY=-1,d._lastMods={shift:!1,control:!1,alt:!1,meta:!1},d.enableMouseListeners=function(){function e(e,r,i,a){var o=d.keyBindingMode;if(!1!==o){var s=\"rotate\"===o,l=\"pan\"===o,c=\"zoom\"===o,h=!!a.control,p=!!a.alt,v=!!a.shift,g=!!(1&e),y=!!(2&e),m=!!(4&e),x=1/t.clientHeight,b=x*(r-d._lastX),_=x*(i-d._lastY),w=d.flipX?1:-1,T=d.flipY?1:-1,k=Math.PI*d.rotateSpeed,A=n();if(-1!==d._lastX&&-1!==d._lastY&&((s&&g&&!h&&!p&&!v||g&&!h&&!p&&v)&&u.rotate(A,w*k*b,-T*k*_,0),(l&&g&&!h&&!p&&!v||y||g&&h&&!p&&!v)&&u.pan(A,-d.translateSpeed*b*f,d.translateSpeed*_*f,0),c&&g&&!h&&!p&&!v||m||g&&!h&&p&&!v)){var M=-d.zoomSpeed*_/window.innerHeight*(A-u.lastT())*100;u.pan(A,0,0,f*(Math.exp(M)-1))}return d._lastX=r,d._lastY=i,d._lastMods=a,!0}}d.mouseListener=a(t,e),t.addEventListener(\"touchstart\",(function(r){var n=s(r.changedTouches[0],t);e(0,n[0],n[1],d._lastMods),e(1,n[0],n[1],d._lastMods)}),!!l&&{passive:!0}),t.addEventListener(\"touchmove\",(function(r){var n=s(r.changedTouches[0],t);e(1,n[0],n[1],d._lastMods),r.preventDefault()}),!!l&&{passive:!1}),t.addEventListener(\"touchend\",(function(t){e(0,d._lastX,d._lastY,d._lastMods)}),!!l&&{passive:!0}),d.wheelListener=o(t,(function(t,e){if(!1!==d.keyBindingMode&&d.enableWheel){var r=d.flipX?1:-1,i=d.flipY?1:-1,a=n();if(Math.abs(t)>Math.abs(e))u.rotate(a,0,0,-t*r*Math.PI*d.rotateSpeed/window.innerWidth);else if(!d._ortho){var o=-d.zoomSpeed*i*e/window.innerHeight*(a-u.lastT())/20;u.pan(a,0,0,f*(Math.exp(o)-1))}}}),!0)},d.enableMouseListeners(),d};var n=r(8161),i=r(1152),a=r(6145),o=r(6475),s=r(2565),l=r(5233)},8245:function(t,e,r){var n=r(6832),i=r(5158),a=n([\"precision mediump float;\\n#define GLSLIFY 1\\nattribute vec2 position;\\nvarying vec2 uv;\\nvoid main() {\\n  uv = position;\\n  gl_Position = vec4(position, 0, 1);\\n}\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D accumBuffer;\\nvarying vec2 uv;\\n\\nvoid main() {\\n  vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\\n  gl_FragColor = min(vec4(1,1,1,1), accum);\\n}\"]);t.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec2\"}])}},1059:function(t,e,r){\"use strict\";var n=r(4296),i=r(7453),a=r(2771),o=r(6496),s=r(2611),l=r(4234),u=r(8126),c=r(6145),f=r(1120),h=r(5268),p=r(8245),d=r(2321)({tablet:!0,featureDetect:!0});function v(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function g(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}return e>0?(r=Math.round(Math.pow(10,e)),Math.ceil(t/r)*r):Math.ceil(t)}function y(t){return\"boolean\"!=typeof t||t}t.exports={createScene:function(t){(t=t||{}).camera=t.camera||{};var e=t.canvas;e||(e=document.createElement(\"canvas\"),t.container?t.container.appendChild(e):document.body.appendChild(e));var r=t.gl;if(r||(t.glOptions&&(d=!!t.glOptions.preserveDrawingBuffer),r=function(t,e){var r=null;try{(r=t.getContext(\"webgl\",e))||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}(e,t.glOptions||{premultipliedAlpha:!0,antialias:!0,preserveDrawingBuffer:d})),!r)throw new Error(\"webgl not supported\");var m=t.bounds||[[-10,-10,-10],[10,10,10]],x=new v,b=l(r,r.drawingBufferWidth,r.drawingBufferHeight,{preferFloat:!d}),_=p(r),w=t.cameraObject&&!0===t.cameraObject._ortho||t.camera.projection&&\"orthographic\"===t.camera.projection.type||!1,T={eye:t.camera.eye||[2,0,0],center:t.camera.center||[0,0,0],up:t.camera.up||[0,1,0],zoomMin:t.camera.zoomMax||.1,zoomMax:t.camera.zoomMin||100,mode:t.camera.mode||\"turntable\",_ortho:w},k=t.axes||{},A=i(r,k);A.enable=!k.disable;var M=t.spikes||{},S=o(r,M),E=[],L=[],C=[],P=[],O=!0,I=!0,D={view:null,projection:new Array(16),model:new Array(16),_ortho:!1},z=(I=!0,[r.drawingBufferWidth,r.drawingBufferHeight]),R=t.cameraObject||n(e,T),F={gl:r,contextLost:!1,pixelRatio:t.pixelRatio||1,canvas:e,selection:x,camera:R,axes:A,axesPixels:null,spikes:S,bounds:m,objects:E,shape:z,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:y(t.autoResize),autoBounds:y(t.autoBounds),autoScale:!!t.autoScale,autoCenter:y(t.autoCenter),clipToBounds:y(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:D,oncontextloss:null,mouseListener:null,_stopped:!1,getAspectratio:function(){return{x:this.aspect[0],y:this.aspect[1],z:this.aspect[2]}},setAspectratio:function(t){this.aspect[0]=t.x,this.aspect[1]=t.y,this.aspect[2]=t.z,I=!0},setBounds:function(t,e){this.bounds[0][t]=e.min,this.bounds[1][t]=e.max},setClearColor:function(t){this.clearColor=t},clearRGBA:function(){this.gl.clearColor(this.clearColor[0],this.clearColor[1],this.clearColor[2],this.clearColor[3]),this.gl.clear(this.gl.COLOR_BUFFER_BIT|this.gl.DEPTH_BUFFER_BIT)}},B=[r.drawingBufferWidth/F.pixelRatio|0,r.drawingBufferHeight/F.pixelRatio|0];function N(){if(!F._stopped&&F.autoResize){var t=e.parentNode,r=1,n=1;t&&t!==document.body?(r=t.clientWidth,n=t.clientHeight):(r=window.innerWidth,n=window.innerHeight);var i=0|Math.ceil(r*F.pixelRatio),a=0|Math.ceil(n*F.pixelRatio);if(i!==e.width||a!==e.height){e.width=i,e.height=a;var o=e.style;o.position=o.position||\"absolute\",o.left=\"0px\",o.top=\"0px\",o.width=r+\"px\",o.height=n+\"px\",O=!0}}}function j(){for(var t=E.length,e=P.length,n=0;n<e;++n)C[n]=0;t:for(n=0;n<t;++n){var i=E[n],a=i.pickSlots;if(a){for(var o=0;o<e;++o)if(C[o]+a<255){L[n]=o,i.setPickBase(C[o]+1),C[o]+=a;continue t}var l=s(r,z);L[n]=e,P.push(l),C.push(a),i.setPickBase(1),e+=1}else L[n]=-1}for(;e>0&&0===C[e-1];)C.pop(),P.pop().dispose()}function U(){if(F.contextLost)return!0;r.isContextLost()&&(F.contextLost=!0,F.mouseListener.enabled=!1,F.selection.object=null,F.oncontextloss&&F.oncontextloss())}F.autoResize&&N(),window.addEventListener(\"resize\",N),F.update=function(t){F._stopped||(t=t||{},O=!0,I=!0)},F.add=function(t){F._stopped||(t.axes=A,E.push(t),L.push(-1),O=!0,I=!0,j())},F.remove=function(t){if(!F._stopped){var e=E.indexOf(t);e<0||(E.splice(e,1),L.pop(),O=!0,I=!0,j())}},F.dispose=function(){if(!F._stopped&&(F._stopped=!0,window.removeEventListener(\"resize\",N),e.removeEventListener(\"webglcontextlost\",U),F.mouseListener.enabled=!1,!F.contextLost)){A.dispose(),S.dispose();for(var t=0;t<E.length;++t)E[t].dispose();for(b.dispose(),t=0;t<P.length;++t)P[t].dispose();_.dispose(),r=null,A=null,S=null,E=[]}},F._mouseRotating=!1,F._prevButtons=0,F.enableMouseListeners=function(){F.mouseListener=c(e,(function(t,e,r){if(!F._stopped){var n=P.length,i=E.length,a=x.object;x.distance=1/0,x.mouse[0]=e,x.mouse[1]=r,x.object=null,x.screen=null,x.dataCoordinate=x.dataPosition=null;var o=!1;if(t&&F._prevButtons)F._mouseRotating=!0;else{F._mouseRotating&&(I=!0),F._mouseRotating=!1;for(var s=0;s<n;++s){var l=P[s].query(e,B[1]-r-1,F.pickRadius);if(l){if(l.distance>x.distance)continue;for(var u=0;u<i;++u){var c=E[u];if(L[u]===s){var f=c.pick(l);f&&(x.buttons=t,x.screen=l.coord,x.distance=l.distance,x.object=c,x.index=f.distance,x.dataPosition=f.position,x.dataCoordinate=f.dataCoordinate,x.data=f,o=!0)}}}}}a&&a!==x.object&&(a.highlight&&a.highlight(null),O=!0),x.object&&(x.object.highlight&&x.object.highlight(x.data),O=!0),(o=o||x.object!==a)&&F.onselect&&F.onselect(x),1&t&&!(1&F._prevButtons)&&F.onclick&&F.onclick(x),F._prevButtons=t}}))},e.addEventListener(\"webglcontextlost\",U);var V=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],H=[V[0].slice(),V[1].slice()];function q(){if(!U()){N();var t=F.camera.tick();D.view=F.camera.matrix,O=O||t,I=I||t,A.pixelRatio=F.pixelRatio,S.pixelRatio=F.pixelRatio;var e=E.length,n=V[0],i=V[1];n[0]=n[1]=n[2]=1/0,i[0]=i[1]=i[2]=-1/0;for(var o=0;o<e;++o){(C=E[o]).pixelRatio=F.pixelRatio,C.axes=F.axes,O=O||!!C.dirty,I=I||!!C.dirty;var s=C.bounds;if(s)for(var l=s[0],c=s[1],p=0;p<3;++p)n[p]=Math.min(n[p],l[p]),i[p]=Math.max(i[p],c[p])}var d=F.bounds;if(F.autoBounds)for(p=0;p<3;++p){if(i[p]<n[p])n[p]=-1,i[p]=1;else{n[p]===i[p]&&(n[p]-=1,i[p]+=1);var v=.05*(i[p]-n[p]);n[p]=n[p]-v,i[p]=i[p]+v}d[0][p]=n[p],d[1][p]=i[p]}var y=!1;for(p=0;p<3;++p)y=y||H[0][p]!==d[0][p]||H[1][p]!==d[1][p],H[0][p]=d[0][p],H[1][p]=d[1][p];if(I=I||y,O=O||y){if(y){var m=[0,0,0];for(o=0;o<3;++o)m[o]=g((d[1][o]-d[0][o])/10);A.autoTicks?A.update({bounds:d,tickSpacing:m}):A.update({bounds:d})}var T=r.drawingBufferWidth,k=r.drawingBufferHeight;for(z[0]=T,z[1]=k,B[0]=0|Math.max(T/F.pixelRatio,1),B[1]=0|Math.max(k/F.pixelRatio,1),function(t,e){var r=t.bounds,n=t.cameraParams,i=n.projection,a=n.model,o=t.gl.drawingBufferWidth,s=t.gl.drawingBufferHeight,l=t.zNear,u=t.zFar,c=t.fovy,p=o/s;e?(h(i,-p,p,-1,1,l,u),n._ortho=!0):(f(i,c,p,l,u),n._ortho=!1);for(var d=0;d<16;++d)a[d]=0;a[15]=1;var v=0;for(d=0;d<3;++d)v=Math.max(v,r[1][d]-r[0][d]);for(d=0;d<3;++d)t.autoScale?a[5*d]=t.aspect[d]/(r[1][d]-r[0][d]):a[5*d]=1/v,t.autoCenter&&(a[12+d]=.5*-a[5*d]*(r[0][d]+r[1][d]))}(F,w),o=0;o<e;++o)(C=E[o]).axesBounds=d,F.clipToBounds&&(C.clipBounds=d);x.object&&(F.snapToData?S.position=x.dataCoordinate:S.position=x.dataPosition,S.bounds=d),I&&(I=!1,function(){if(!U()){r.colorMask(!0,!0,!0,!0),r.depthMask(!0),r.disable(r.BLEND),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL);for(var t=E.length,e=P.length,n=0;n<e;++n){var i=P[n];i.shape=B,i.begin();for(var a=0;a<t;++a)if(L[a]===n){var o=E[a];o.drawPick&&(o.pixelRatio=1,o.drawPick(D))}i.end()}}}()),F.axesPixels=a(F.axes,D,T,k),F.onrender&&F.onrender(),r.bindFramebuffer(r.FRAMEBUFFER,null),r.viewport(0,0,T,k),F.clearRGBA(),r.depthMask(!0),r.colorMask(!0,!0,!0,!0),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL),r.disable(r.BLEND),r.disable(r.CULL_FACE);var M=!1;for(A.enable&&(M=M||A.isTransparent(),A.draw(D)),S.axes=A,x.object&&S.draw(D),r.disable(r.CULL_FACE),o=0;o<e;++o)(C=E[o]).axes=A,C.pixelRatio=F.pixelRatio,C.isOpaque&&C.isOpaque()&&C.draw(D),C.isTransparent&&C.isTransparent()&&(M=!0);if(M){for(b.shape=z,b.bind(),r.clear(r.DEPTH_BUFFER_BIT),r.colorMask(!1,!1,!1,!1),r.depthMask(!0),r.depthFunc(r.LESS),A.enable&&A.isTransparent()&&A.drawTransparent(D),o=0;o<e;++o)(C=E[o]).isOpaque&&C.isOpaque()&&C.draw(D);for(r.enable(r.BLEND),r.blendEquation(r.FUNC_ADD),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.colorMask(!0,!0,!0,!0),r.depthMask(!1),r.clearColor(0,0,0,0),r.clear(r.COLOR_BUFFER_BIT),A.isTransparent()&&A.drawTransparent(D),o=0;o<e;++o){var C;(C=E[o]).isTransparent&&C.isTransparent()&&C.drawTransparent(D)}r.bindFramebuffer(r.FRAMEBUFFER,null),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.disable(r.DEPTH_TEST),_.bind(),b.color[0].bind(0),_.uniforms.accumBuffer=0,u(r),r.disable(r.BLEND)}for(O=!1,o=0;o<e;++o)E[o].dirty=!1}}}return F.enableMouseListeners(),function t(){F._stopped||F.contextLost||(q(),requestAnimationFrame(t))}(),F.redraw=function(){F._stopped||(O=!0,q())},F},createCamera:n}},8023:function(t,e,r){var n=r(6832);e.pointVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform float pointCloud;\\n\\nhighp float rand(vec2 co) {\\n  highp float a = 12.9898;\\n  highp float b = 78.233;\\n  highp float c = 43758.5453;\\n  highp float d = dot(co.xy, vec2(a, b));\\n  highp float e = mod(d, 3.14);\\n  return fract(sin(e) * c);\\n}\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n    // if we don't jitter the point size a bit, overall point cloud\\n    // saturation 'jumps' on zooming, which is disturbing and confusing\\n  gl_PointSize = pointSize * ((19.5 + rand(position)) / 20.0);\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    // get the same square surface as circle would be\\n    gl_PointSize *= 0.886;\\n  }\\n}\"]),e.pointFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\nuniform float pointCloud;\\n\\nvoid main() {\\n  float radius;\\n  vec4 baseColor;\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    if(centerFraction == 1.0) {\\n      gl_FragColor = color;\\n    } else {\\n      gl_FragColor = mix(borderColor, color, centerFraction);\\n    }\\n  } else {\\n    radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n    if(radius > 1.0) {\\n      discard;\\n    }\\n    baseColor = mix(borderColor, color, step(radius, centerFraction));\\n    gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\\n  }\\n}\\n\"]),e.pickVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  fragId = id;\\n}\\n\"]),e.pickFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\\n\"])},8271:function(t,e,r){\"use strict\";var n=r(5158),i=r(5827),a=r(5306),o=r(8023);function s(t,e,r,n,i){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=i,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}t.exports=function(t,e){var r=t.gl,a=new s(t,i(r),i(r),n(r,o.pointVertex,o.pointFragment),n(r,o.pickVertex,o.pickFragment));return a.update(e),t.addObject(a),a};var l,u,c=s.prototype;c.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},c.update=function(t){var e;function r(e,r){return e in t?t[e]:r}t=t||{},this.sizeMin=r(\"sizeMin\",.5),this.sizeMax=r(\"sizeMax\",20),this.color=r(\"color\",[1,0,0,1]).slice(),this.areaRatio=r(\"areaRatio\",1),this.borderColor=r(\"borderColor\",[0,0,0,1]).slice(),this.blend=r(\"blend\",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,o=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,s=t.positions,l=i?s:a.mallocFloat32(s.length),u=o?t.idToIndex:a.mallocInt32(n);if(i||l.set(s),!o)for(l.set(s),e=0;e<n;e++)u[e]=e;this.points=s,this.offsetBuffer.update(l),this.pickBuffer.update(u),i||a.free(l),o||a.free(u),this.pointCount=n,this.pickOffset=0},c.unifiedDraw=(l=[1,0,0,0,1,0,0,0,1],u=[0,0,0,0],function(t){var e=void 0!==t,r=e?this.pickShader:this.shader,n=this.plot.gl,i=this.plot.dataBox;if(0===this.pointCount)return t;var a=i[2]-i[0],o=i[3]-i[1],s=function(t,e){var r,n=0,i=t.length>>>1;for(r=0;r<i;r++){var a=t[2*r],o=t[2*r+1];a>=e[0]&&a<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}(this.points,i),c=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(s,.33333)));l[0]=2/a,l[4]=2/o,l[6]=-2*i[0]/a-1,l[7]=-2*i[1]/o-1,this.offsetBuffer.bind(),r.bind(),r.attributes.position.pointer(),r.uniforms.matrix=l,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointCloud=c<5,r.uniforms.pointSize=c,r.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),e&&(u[0]=255&t,u[1]=t>>8&255,u[2]=t>>16&255,u[3]=t>>24&255,this.pickBuffer.bind(),r.attributes.pickId.pointer(n.UNSIGNED_BYTE),r.uniforms.pickOffset=u,this.pickOffset=t);var f=n.getParameter(n.BLEND),h=n.getParameter(n.DITHER);return f&&!this.blend&&n.disable(n.BLEND),h&&n.disable(n.DITHER),n.drawArrays(n.POINTS,0,this.pointCount),f&&!this.blend&&n.enable(n.BLEND),h&&n.enable(n.DITHER),t+this.pointCount}),c.draw=c.unifiedDraw,c.drawPick=c.unifiedDraw,c.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(r<n||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},6093:function(t){t.exports=function(t,e,r,n){var i,a,o,s,l,u=e[0],c=e[1],f=e[2],h=e[3],p=r[0],d=r[1],v=r[2],g=r[3];return(a=u*p+c*d+f*v+h*g)<0&&(a=-a,p=-p,d=-d,v=-v,g=-g),1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n),t[0]=s*u+l*p,t[1]=s*c+l*d,t[2]=s*f+l*v,t[3]=s*h+l*g,t}},8240:function(t){\"use strict\";t.exports=function(t){return t||0===t?t.toString():\"\"}},4123:function(t,e,r){\"use strict\";var n=r(875);t.exports=function(t,e,r){var a=i[e];if(a||(a=i[e]={}),t in a)return a[t];var o={textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},triangles:!0},s=n(t,o);o.triangles=!1;var l,u,c=n(t,o);if(r&&1!==r){for(l=0;l<s.positions.length;++l)for(u=0;u<s.positions[l].length;++u)s.positions[l][u]/=r;for(l=0;l<c.positions.length;++l)for(u=0;u<c.positions[l].length;++u)c.positions[l][u]/=r}var f=[[1/0,1/0],[-1/0,-1/0]],h=c.positions.length;for(l=0;l<h;++l){var p=c.positions[l];for(u=0;u<2;++u)f[0][u]=Math.min(f[0][u],p[u]),f[1][u]=Math.max(f[1][u],p[u])}return a[t]=[s,c,f]};var i={}},9282:function(t,e,r){var n=r(5158),i=r(6832),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = 1.0;\\n    if(distance(highlightId, id) < 0.0001) {\\n      scale = highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1);\\n    vec4 viewPosition = view * worldPosition;\\n    viewPosition = viewPosition / viewPosition.w;\\n    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = pixelRatio;\\n    if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n      scale *= highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1.0);\\n    vec4 viewPosition = view * worldPosition;\\n    vec4 clipPosition = projection * viewPosition;\\n    clipPosition /= clipPosition.w;\\n\\n    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float lscale = pixelRatio * scale;\\n    if(distance(highlightId, id) < 0.0001) {\\n      lscale *= highlightScale;\\n    }\\n\\n    vec4 clipCenter   = projection * view * model * vec4(position, 1);\\n    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n    vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = dataPosition;\\n  }\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (\\n    outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\\n    interpColor.a * opacity == 0.\\n  ) discard;\\n  gl_FragColor = interpColor * opacity;\\n}\\n\"]),u=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\\n\\n  gl_FragColor = vec4(pickGroup, pickId.bgr);\\n}\"]),c=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:c},h={vertex:o,fragment:l,attributes:c},p={vertex:s,fragment:l,attributes:c},d={vertex:a,fragment:u,attributes:c},v={vertex:o,fragment:u,attributes:c},g={vertex:s,fragment:u,attributes:c};function y(t,e){var r=n(t,e),i=r.attributes;return i.position.location=0,i.color.location=1,i.glyph.location=2,i.id.location=3,r}e.createPerspective=function(t){return y(t,f)},e.createOrtho=function(t){return y(t,h)},e.createProject=function(t){return y(t,p)},e.createPickPerspective=function(t){return y(t,d)},e.createPickOrtho=function(t){return y(t,v)},e.createPickProject=function(t){return y(t,g)}},2182:function(t,e,r){\"use strict\";var n=r(3596),i=r(5827),a=r(2944),o=r(5306),s=r(104),l=r(9282),u=r(4123),c=r(8240),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function p(t,e,r,n){return h(n,n),h(n,n),h(n,n)}function d(t,e){this.index=t,this.dataCoordinate=this.position=e}function v(t){return!0===t||t>1?1:t}function g(t,e,r,n,i,a,o,s,l,u,c,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=a,this.glyphBuffer=o,this.idBuffer=s,this.vao=l,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.hasAlpha=!1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.projectHasAlpha=!1,this.pickId=0,this.pickPerspectiveShader=u,this.pickOrthoShader=c,this.pickProjectShader=f,this.points=[],this._selectResult=new d(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.dirty=!0}t.exports=function(t){var e=t.gl,r=l.createPerspective(e),n=l.createOrtho(e),o=l.createProject(e),s=l.createPickPerspective(e),u=l.createPickOrtho(e),c=l.createPickProject(e),f=i(e),h=i(e),p=i(e),d=i(e),v=new g(e,r,n,o,f,h,p,d,a(e,[{buffer:f,size:3,type:e.FLOAT},{buffer:h,size:4,type:e.FLOAT},{buffer:p,size:2,type:e.FLOAT},{buffer:d,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),s,u,c);return v.update(t),v};var y=g.prototype;y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.isTransparent=function(){if(this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectHasAlpha)return!0;return!1},y.isOpaque=function(){if(!this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&!this.projectHasAlpha)return!0;return!1};var m=[0,0],x=[0,0,0],b=[0,0,0],_=[0,0,0,1],w=[0,0,0,1],T=f.slice(),k=[0,0,0],A=[[0,0,0],[0,0,0]];function M(t){return t[0]=t[1]=t[2]=0,t}function S(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function E(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}var L=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];function C(t,e,r,n,i,a,o){var l=r.gl;if((a===r.projectHasAlpha||o)&&function(t,e,r,n){var i,a=e.axesProject,o=e.gl,l=t.uniforms,u=r.model||f,c=r.view||f,h=r.projection||f,d=e.axesBounds,v=function(t){for(var e=A,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}(e.clipBounds);i=e.axes&&e.axes.lastCubeProps?e.axes.lastCubeProps.axis:[1,1,1],m[0]=2/o.drawingBufferWidth,m[1]=2/o.drawingBufferHeight,t.bind(),l.view=c,l.projection=h,l.screenSize=m,l.highlightId=e.highlightId,l.highlightScale=e.highlightScale,l.clipBounds=v,l.pickGroup=e.pickId/255,l.pixelRatio=n;for(var g=0;g<3;++g)if(a[g]){l.scale=e.projectScale[g],l.opacity=e.projectOpacity[g];for(var y=T,L=0;L<16;++L)y[L]=0;for(L=0;L<4;++L)y[5*L]=1;y[5*g]=0,i[g]<0?y[12+g]=d[0][g]:y[12+g]=d[1][g],s(y,u,y),l.model=y;var C=(g+1)%3,P=(g+2)%3,O=M(x),I=M(b);O[C]=1,I[P]=1;var D=p(0,0,0,S(_,O)),z=p(0,0,0,S(w,I));if(Math.abs(D[1])>Math.abs(z[1])){var R=D;D=z,z=R,R=O,O=I,I=R;var F=C;C=P,P=F}D[0]<0&&(O[C]=-1),z[1]>0&&(I[P]=-1);var B=0,N=0;for(L=0;L<4;++L)B+=Math.pow(u[4*C+L],2),N+=Math.pow(u[4*P+L],2);O[C]/=Math.sqrt(B),I[P]/=Math.sqrt(N),l.axes[0]=O,l.axes[1]=I,l.fragClipBounds[0]=E(k,v[0],g,-1e8),l.fragClipBounds[1]=E(k,v[1],g,1e8),e.vao.bind(),e.vao.draw(o.TRIANGLES,e.vertexCount),e.lineWidth>0&&(o.lineWidth(e.lineWidth*n),e.vao.draw(o.LINES,e.lineVertexCount,e.vertexCount)),e.vao.unbind()}}(e,r,n,i),a===r.hasAlpha||o){t.bind();var u=t.uniforms;u.model=n.model||f,u.view=n.view||f,u.projection=n.projection||f,m[0]=2/l.drawingBufferWidth,m[1]=2/l.drawingBufferHeight,u.screenSize=m,u.highlightId=r.highlightId,u.highlightScale=r.highlightScale,u.fragClipBounds=L,u.clipBounds=r.axes.bounds,u.opacity=r.opacity,u.pickGroup=r.pickId/255,u.pixelRatio=i,r.vao.bind(),r.vao.draw(l.TRIANGLES,r.vertexCount),r.lineWidth>0&&(l.lineWidth(r.lineWidth*i),r.vao.draw(l.LINES,r.lineVertexCount,r.vertexCount)),r.vao.unbind()}}function P(t,e,r,i){var a;a=Array.isArray(t)?e<t.length?t[e]:void 0:t,a=c(a);var o=!0;n(a)&&(a=\"▼\",o=!1);var s=u(a,r,i);return{mesh:s[0],lines:s[1],bounds:s[2],visible:o}}y.draw=function(t){C(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!1,!1)},y.drawTransparent=function(t){C(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!0,!1)},y.drawPick=function(t){C(this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader,this.pickProjectShader,this,t,1,!0,!0)},y.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;i<3;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},y.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},y.update=function(t){if(\"perspective\"in(t=t||{})&&(this.useOrtho=!t.perspective),\"orthographic\"in t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(this.projectHasAlpha=!1,\"projectOpacity\"in t){Array.isArray(t.projectOpacity)?this.projectOpacity=t.projectOpacity.slice():(r=+t.projectOpacity,this.projectOpacity=[r,r,r]);for(var n=0;n<3;++n)this.projectOpacity[n]=v(this.projectOpacity[n]),this.projectOpacity[n]<1&&(this.projectHasAlpha=!0)}this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=v(t.opacity),this.opacity<1&&(this.hasAlpha=!0)),this.dirty=!0;var i,a,s=t.position,l=t.font||\"normal\",u=t.alignment||[0,0];if(2===u.length)i=u[0],a=u[1];else for(i=[],a=[],n=0;n<u.length;++n)i[n]=u[n][0],a[n]=u[n][1];var c=[1/0,1/0,1/0],f=[-1/0,-1/0,-1/0],h=t.glyph,p=t.color,d=t.size,g=t.angle,y=t.lineColor,m=-1,x=0,b=0,_=0;if(s.length){_=s.length;t:for(n=0;n<_;++n){for(var w=s[n],T=0;T<3;++T)if(isNaN(w[T])||!isFinite(w[T]))continue t;var k=(N=P(h,n,l,this.pixelRatio)).mesh,A=N.lines,M=N.bounds;x+=3*k.cells.length,b+=2*A.edges.length}}var S=x+b,E=o.mallocFloat(3*S),L=o.mallocFloat(4*S),C=o.mallocFloat(2*S),O=o.mallocUint32(S);if(S>0){var I=0,D=x,z=[0,0,0,1],R=[0,0,0,1],F=Array.isArray(p)&&Array.isArray(p[0]),B=Array.isArray(y)&&Array.isArray(y[0]);t:for(n=0;n<_;++n){for(m+=1,w=s[n],T=0;T<3;++T){if(isNaN(w[T])||!isFinite(w[T]))continue t;f[T]=Math.max(f[T],w[T]),c[T]=Math.min(c[T],w[T])}k=(N=P(h,n,l,this.pixelRatio)).mesh,A=N.lines,M=N.bounds;var N,j=N.visible;if(j)if(Array.isArray(p)){if(3===(U=F?n<p.length?p[n]:[0,0,0,0]:p).length){for(T=0;T<3;++T)z[T]=U[T];z[3]=1}else if(4===U.length){for(T=0;T<4;++T)z[T]=U[T];!this.hasAlpha&&U[3]<1&&(this.hasAlpha=!0)}}else z[0]=z[1]=z[2]=0,z[3]=1;else z=[1,1,1,0];if(j)if(Array.isArray(y)){var U;if(3===(U=B?n<y.length?y[n]:[0,0,0,0]:y).length){for(T=0;T<3;++T)R[T]=U[T];R[T]=1}else if(4===U.length){for(T=0;T<4;++T)R[T]=U[T];!this.hasAlpha&&U[3]<1&&(this.hasAlpha=!0)}}else R[0]=R[1]=R[2]=0,R[3]=1;else R=[1,1,1,0];var V=.5;j?Array.isArray(d)?V=n<d.length?+d[n]:12:d?V=+d:this.useOrtho&&(V=12):V=0;var H=0;Array.isArray(g)?H=n<g.length?+g[n]:0:g&&(H=+g);var q=Math.cos(H),G=Math.sin(H);for(w=s[n],T=0;T<3;++T)f[T]=Math.max(f[T],w[T]),c[T]=Math.min(c[T],w[T]);var Z=i,Y=a;Z=0,Array.isArray(i)?Z=n<i.length?i[n]:0:i&&(Z=i),Y=0,Array.isArray(a)?Y=n<a.length?a[n]:0:a&&(Y=a);var W=[Z*=Z>0?1-M[0][0]:Z<0?1+M[1][0]:1,Y*=Y>0?1-M[0][1]:Y<0?1+M[1][1]:1],X=k.cells||[],J=k.positions||[];for(T=0;T<X.length;++T)for(var K=X[T],$=0;$<3;++$){for(var Q=0;Q<3;++Q)E[3*I+Q]=w[Q];for(Q=0;Q<4;++Q)L[4*I+Q]=z[Q];O[I]=m;var tt=J[K[$]];C[2*I]=V*(q*tt[0]-G*tt[1]+W[0]),C[2*I+1]=V*(G*tt[0]+q*tt[1]+W[1]),I+=1}for(X=A.edges,J=A.positions,T=0;T<X.length;++T)for(K=X[T],$=0;$<2;++$){for(Q=0;Q<3;++Q)E[3*D+Q]=w[Q];for(Q=0;Q<4;++Q)L[4*D+Q]=R[Q];O[D]=m,tt=J[K[$]],C[2*D]=V*(q*tt[0]-G*tt[1]+W[0]),C[2*D+1]=V*(G*tt[0]+q*tt[1]+W[1]),D+=1}}}this.bounds=[c,f],this.points=s,this.pointCount=s.length,this.vertexCount=x,this.lineVertexCount=b,this.pointBuffer.update(E),this.colorBuffer.update(L),this.glyphBuffer.update(C),this.idBuffer.update(O),o.free(E),o.free(L),o.free(C),o.free(O)},y.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()}},1884:function(t,e,r){\"use strict\";var n=r(6832);e.boxVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 vertex;\\n\\nuniform vec2 cornerA, cornerB;\\n\\nvoid main() {\\n  gl_Position = vec4(mix(cornerA, cornerB, vertex), 0, 1);\\n}\\n\"]),e.boxFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = color;\\n}\\n\"])},6623:function(t,e,r){\"use strict\";var n=r(5158),i=r(5827),a=r(1884);function o(t,e,r){this.plot=t,this.boxBuffer=e,this.boxShader=r,this.enabled=!0,this.selectBox=[1/0,1/0,-1/0,-1/0],this.borderColor=[0,0,0,1],this.innerFill=!1,this.innerColor=[0,0,0,.25],this.outerFill=!0,this.outerColor=[0,0,0,.5],this.borderWidth=10}t.exports=function(t,e){var r=t.gl,s=new o(t,i(r,[0,0,0,1,1,0,1,1]),n(r,a.boxVertex,a.boxFragment));return s.update(e),t.addOverlay(s),s};var s=o.prototype;s.draw=function(){if(this.enabled){var t=this.plot,e=this.selectBox,r=this.borderWidth,n=(this.innerFill,this.innerColor),i=(this.outerFill,this.outerColor),a=this.borderColor,o=t.box,s=t.screenBox,l=t.dataBox,u=t.viewBox,c=t.pixelRatio,f=(e[0]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],h=(e[1]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1],p=(e[2]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],d=(e[3]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1];if(f=Math.max(f,u[0]),h=Math.max(h,u[1]),p=Math.min(p,u[2]),d=Math.min(d,u[3]),!(p<f||d<h)){o.bind();var v=s[2]-s[0],g=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,v,h,i),o.drawBox(0,h,f,d,i),o.drawBox(0,d,v,g,i),o.drawBox(p,h,v,d,i)),this.innerFill&&o.drawBox(f,h,p,d,n),r>0){var y=r*c;o.drawBox(f-y,h-y,p+y,h+y,a),o.drawBox(f-y,d-y,p+y,d+y,a),o.drawBox(f-y,h-y,f+y,d+y,a),o.drawBox(p-y,h-y,p+y,d+y,a)}}}},s.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},s.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},2611:function(t,e,r){\"use strict\";t.exports=function(t,e){var r=e[0],a=e[1];return new l(t,n(t,r,a,{}),i.mallocUint8(r*a*4))};var n=r(4234),i=r(5306),a=r(5050),o=r(2288).nextPow2;function s(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function l(t,e,r){this.gl=t,this.fbo=e,this.buffer=r,this._readTimeout=null;var 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h=u,p=c,d=0;d<3;++d)i&&i[d]<0?(h[d]=this.bounds[0][d],p[d]=this.bounds[1][d]):(h[d]=this.bounds[1][d],p[d]=this.bounds[0][d]);for(f[0]=e.drawingBufferWidth,f[1]=e.drawingBufferHeight,n.uniforms.model=a,n.uniforms.view=s,n.uniforms.projection=l,n.uniforms.coordinates=[this.position,h,p],n.uniforms.colors=this.colors,n.uniforms.screenShape=f,d=0;d<3;++d)n.uniforms.lineWidth=this.lineWidth[d]*this.pixelRatio,this.enabled[d]&&(r.draw(e.TRIANGLES,6,6*d),this.drawSides[d]&&r.draw(e.TRIANGLES,12,18+12*d));r.unbind()},l.update=function(t){t&&(\"bounds\"in t&&(this.bounds=t.bounds),\"position\"in t&&(this.position=t.position),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"colors\"in t&&(this.colors=t.colors),\"enabled\"in t&&(this.enabled=t.enabled),\"drawSides\"in t&&(this.drawSides=t.drawSides))},l.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},9578:function(t,e,r){var n=r(6832),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n  float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, tubeScale;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * tubePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(tubePosition, 1.0);\\n  vec4 t_position  = view * tubePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = tubePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n  float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float tubeScale;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  gl_Position = projection * view * tubePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec4\"}]},e.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec4\"}]}},7307:function(t,e,r){\"use strict\";var n=r(2858),i=r(4020),a=[\"xyz\",\"xzy\",\"yxz\",\"yzx\",\"zxy\",\"zyx\"],o=function(t,e){var r,n=t.length;for(r=0;r<n;r++){var i=t[r];if(i===e)return r;if(i>e)return r-1}return r},s=function(t,e,r){return t<e?e:t>r?r:t},l=function(t){var e=1/0;t.sort((function(t,e){return t-e}));for(var r=t.length,n=1;n<r;n++){var i=Math.abs(t[n]-t[n-1]);i<e&&(e=i)}return e};t.exports=function(t,e){var r=t.startingPositions,u=t.maxLength||1e3,c=t.tubeSize||1,f=t.absoluteTubeSize,h=t.gridFill||\"+x+y+z\",p={};-1!==h.indexOf(\"-x\")&&(p.reversedX=!0),-1!==h.indexOf(\"-y\")&&(p.reversedY=!0),-1!==h.indexOf(\"-z\")&&(p.reversedZ=!0),p.filled=a.indexOf(h.replace(/-/g,\"\").replace(/\\+/g,\"\"));var d=t.getVelocity||function(e){return function(t,e,r){var i=e.vectors,a=e.meshgrid,l=t[0],u=t[1],c=t[2],f=a[0].length,h=a[1].length,p=a[2].length,d=o(a[0],l),v=o(a[1],u),g=o(a[2],c),y=d+1,m=v+1,x=g+1;if(d=s(d,0,f-1),y=s(y,0,f-1),v=s(v,0,h-1),m=s(m,0,h-1),g=s(g,0,p-1),x=s(x,0,p-1),d<0||v<0||g<0||y>f-1||m>h-1||x>p-1)return n.create();var b,_,w,T,k,A,M=a[0][d],S=a[0][y],E=a[1][v],L=a[1][m],C=a[2][g],P=(l-M)/(S-M),O=(u-E)/(L-E),I=(c-C)/(a[2][x]-C);switch(isFinite(P)||(P=.5),isFinite(O)||(O=.5),isFinite(I)||(I=.5),r.reversedX&&(d=f-1-d,y=f-1-y),r.reversedY&&(v=h-1-v,m=h-1-m),r.reversedZ&&(g=p-1-g,x=p-1-x),r.filled){case 5:k=g,A=x,w=v*p,T=m*p,b=d*p*h,_=y*p*h;break;case 4:k=g,A=x,b=d*p,_=y*p,w=v*p*f,T=m*p*f;break;case 3:w=v,T=m,k=g*h,A=x*h,b=d*h*p,_=y*h*p;break;case 2:w=v,T=m,b=d*h,_=y*h,k=g*h*f,A=x*h*f;break;case 1:b=d,_=y,k=g*f,A=x*f,w=v*f*p,T=m*f*p;break;default:b=d,_=y,w=v*f,T=m*f,k=g*f*h,A=x*f*h}var D=i[b+w+k],z=i[b+w+A],R=i[b+T+k],F=i[b+T+A],B=i[_+w+k],N=i[_+w+A],j=i[_+T+k],U=i[_+T+A],V=n.create(),H=n.create(),q=n.create(),G=n.create();n.lerp(V,D,B,P),n.lerp(H,z,N,P),n.lerp(q,R,j,P),n.lerp(G,F,U,P);var Z=n.create(),Y=n.create();n.lerp(Z,V,q,O),n.lerp(Y,H,G,O);var W=n.create();return n.lerp(W,Z,Y,I),W}(e,t,p)},v=t.getDivergence||function(t,e){var r=n.create(),i=1e-4;n.add(r,t,[i,0,0]);var a=d(r);n.subtract(a,a,e),n.scale(a,a,1/i),n.add(r,t,[0,i,0]);var o=d(r);n.subtract(o,o,e),n.scale(o,o,1/i),n.add(r,t,[0,0,i]);var s=d(r);return n.subtract(s,s,e),n.scale(s,s,1/i),n.add(r,a,o),n.add(r,r,s),r},g=[],y=e[0][0],m=e[0][1],x=e[0][2],b=e[1][0],_=e[1][1],w=e[1][2],T=function(t){var e=t[0],r=t[1],n=t[2];return!(e<y||e>b||r<m||r>_||n<x||n>w)},k=10*n.distance(e[0],e[1])/u,A=k*k,M=1,S=0,E=r.length;E>1&&(M=function(t){for(var e=[],r=[],n=[],i={},a={},o={},s=t.length,u=0;u<s;u++){var c=t[u],f=c[0],h=c[1],p=c[2];i[f]||(e.push(f),i[f]=!0),a[h]||(r.push(h),a[h]=!0),o[p]||(n.push(p),o[p]=!0)}var d=l(e),v=l(r),g=l(n),y=Math.min(d,v,g);return isFinite(y)?y:1}(r));for(var L=0;L<E;L++){var C=n.create();n.copy(C,r[L]);var P=[C],O=[],I=d(C),D=C;O.push(I);var z=[],R=v(C,I),F=n.length(R);isFinite(F)&&F>S&&(S=F),z.push(F),g.push({points:P,velocities:O,divergences:z});for(var B=0;B<100*u&&P.length<u&&T(C);){B++;var N=n.clone(I),j=n.squaredLength(N);if(0===j)break;j>A&&n.scale(N,N,k/Math.sqrt(j)),n.add(N,N,C),I=d(N),n.squaredDistance(D,N)-A>-1e-4*A&&(P.push(N),D=N,O.push(I),R=v(N,I),F=n.length(R),isFinite(F)&&F>S&&(S=F),z.push(F)),C=N}}var U=function(t,e,r,a){for(var o=0,s=0;s<t.length;s++)for(var l=t[s].velocities,u=0;u<l.length;u++)o=Math.max(o,n.length(l[u]));var c=t.map((function(t){return function(t,e,r,a){for(var o=t.points,s=t.velocities,l=t.divergences,u=[],c=[],f=[],h=[],p=[],d=[],v=0,g=0,y=i.create(),m=i.create(),x=0;x<o.length;x++){var b=o[x],_=s[x],w=l[x];0===e&&(w=.05*r),g=n.length(_)/a,y=i.create(),n.copy(y,_),y[3]=w;for(var T=0;T<8;T++)p[T]=[b[0],b[1],b[2],T];if(h.length>0)for(T=0;T<8;T++){var k=(T+1)%8;u.push(h[T],p[T],p[k],p[k],h[k],h[T]),f.push(m,y,y,y,m,m),d.push(v,g,g,g,v,v);var A=u.length;c.push([A-6,A-5,A-4],[A-3,A-2,A-1])}var M=h;h=p,p=M;var S=m;m=y,y=S;var E=v;v=g,g=E}return{positions:u,cells:c,vectors:f,vertexIntensity:d}}(t,r,a,o)})),f=[],h=[],p=[],d=[];for(s=0;s<c.length;s++){var v=c[s],g=f.length;for(f=f.concat(v.positions),p=p.concat(v.vectors),d=d.concat(v.vertexIntensity),u=0;u<v.cells.length;u++){var y=v.cells[u],m=[];h.push(m);for(var x=0;x<y.length;x++)m.push(y[x]+g)}}return{positions:f,cells:h,vectors:p,vertexIntensity:d,colormap:e}}(g,t.colormap,S,M);return f?U.tubeScale=f:(0===S&&(S=1),U.tubeScale=.5*c*M/S),U};var u=r(9578),c=r(1140).createMesh;t.exports.createTubeMesh=function(t,e){return c(t,e,{shaders:u,traceType:\"streamtube\"})}},9054:function(t,e,r){var n=r(5158),i=r(6832),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute vec3 f;\\nattribute vec3 normal;\\n\\nuniform vec3 objectOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 localCoordinate = vec3(uv.zw, f.x);\\n  worldCoordinate = objectOffset + localCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n  vec4 clipPosition = projection * view * worldPosition;\\n  gl_Position = clipPosition;\\n  kill = f.y;\\n  value = f.z;\\n  planeCoordinate = uv.xy;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * worldPosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  lightDirection = lightPosition - cameraCoordinate.xyz;\\n  eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\\n\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat beckmannSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness) {\\n  return beckmannDistribution(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform float vertexColor;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  if (\\n    kill > 0.0 ||\\n    vColor.a == 0.0 ||\\n    outOfRange(clipBounds[0], clipBounds[1], worldCoordinate)\\n  ) discard;\\n\\n  vec3 N = normalize(surfaceNormal);\\n  vec3 V = normalize(eyeDirection);\\n  vec3 L = normalize(lightDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = max(beckmannSpecular(L, V, N, roughness), 0.);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  //decide how to interpolate color — in vertex or in fragment\\n  vec4 surfaceColor =\\n    step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) +\\n    step(.5, vertexColor) * vColor;\\n\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\\n}\\n\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute float f;\\n\\nuniform vec3 objectOffset;\\nuniform mat3 permutation;\\nuniform mat4 model, view, projection;\\nuniform float height, zOffset;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 dataCoordinate = permutation * vec3(uv.xy, height);\\n  worldCoordinate = objectOffset + dataCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n\\n  vec4 clipPosition = projection * view * worldPosition;\\n  clipPosition.z += zOffset;\\n\\n  gl_Position = clipPosition;\\n  value = f + objectOffset.z;\\n  kill = -1.0;\\n  planeCoordinate = uv.zw;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Don't do lighting for contours\\n  surfaceNormal   = vec3(1,0,0);\\n  eyeDirection    = vec3(0,1,0);\\n  lightDirection  = vec3(0,0,1);\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n  float vh = 255.0 * v;\\n  float upper = floor(vh);\\n  float lower = fract(vh);\\n  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n  if ((kill > 0.0) ||\\n      (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\\n\\n  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\\n\"]);e.createShader=function(t){var e=n(t,a,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},e.createPickShader=function(t){var e=n(t,a,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},e.createContourShader=function(t){var e=n(t,s,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},e.createPickContourShader=function(t){var e=n(t,s,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},3754:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl,r=m(e),n=b(e),s=x(e),l=_(e),u=i(e),c=a(e,[{buffer:u,size:4,stride:w,offset:0},{buffer:u,size:3,stride:w,offset:16},{buffer:u,size:3,stride:w,offset:28}]),f=i(e),h=a(e,[{buffer:f,size:4,stride:20,offset:0},{buffer:f,size:1,stride:20,offset:16}]),p=i(e),d=a(e,[{buffer:p,size:2,type:e.FLOAT}]),v=o(e,1,S,e.RGBA,e.UNSIGNED_BYTE);v.minFilter=e.LINEAR,v.magFilter=e.LINEAR;var g=new E(e,[0,0],[[0,0,0],[0,0,0]],r,n,u,c,v,s,l,f,h,p,d,[0,0,0]),y={levels:[[],[],[]]};for(var T in t)y[T]=t[T];return y.colormap=y.colormap||\"jet\",g.update(y),g};var n=r(2288),i=r(5827),a=r(2944),o=r(8931),s=r(5306),l=r(9156),u=r(7498),c=r(7382),f=r(5050),h=r(4162),p=r(104),d=r(7437),v=r(5070),g=r(9144),y=r(9054),m=y.createShader,x=y.createContourShader,b=y.createPickShader,_=y.createPickContourShader,w=40,T=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],k=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],A=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];function M(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}!function(){for(var t=0;t<3;++t){var e=A[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();var S=256;function E(t,e,r,n,i,a,o,l,u,c,h,p,d,v,g){this.gl=t,this.shape=e,this.bounds=r,this.objectOffset=g,this.intensityBounds=[],this._shader=n,this._pickShader=i,this._coordinateBuffer=a,this._vao=o,this._colorMap=l,this._contourShader=u,this._contourPickShader=c,this._contourBuffer=h,this._contourVAO=p,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new M([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=v,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var L=E.prototype;L.genColormap=function(t,e){var r=!1,n=c([l({colormap:t,nshades:S,format:\"rgba\"}).map((function(t,n){var i=e?function(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}(n/255,e):t[3];return i<1&&(r=!0),[t[0],t[1],t[2],255*i]}))]);return u.divseq(n,255),this.hasAlphaScale=r,n},L.isTransparent=function(){return this.opacity<1||this.hasAlphaScale},L.isOpaque=function(){return!this.isTransparent()},L.pickSlots=1,L.setPickBase=function(t){this.pickId=t};var C=[0,0,0],P={showSurface:!1,showContour:!1,projections:[T.slice(),T.slice(),T.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function O(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||C,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=P.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],p(l,t.model,l);var u=P.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)u[i][n]=t.clipBounds[i][n];u[0][r]=-1e8,u[1][r]=1e8}return P.showSurface=o,P.showContour=s,P}var I={model:T,view:T,projection:T,inverseModel:T.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},D=T.slice(),z=[1,0,0,0,1,0,0,0,1];function R(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=I;n.model=t.model||T,n.view=t.view||T,n.projection=t.projection||T,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],o=0;o<3;++o)a[o]=Math.min(Math.max(this.clipBounds[i][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=z,n.vertexColor=this.vertexColor;var s=D;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),i=0;i<3;++i)n.eyePosition[i]=s[12+i]/s[15];var l=s[15];for(i=0;i<3;++i)l+=this.lightPosition[i]*s[4*i+3];for(i=0;i<3;++i){var u=s[12+i];for(o=0;o<3;++o)u+=s[4*o+i]*this.lightPosition[o];n.lightPosition[i]=u/l}var c=O(n,this);if(c.showSurface){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)this.surfaceProject[i]&&this.vertexCount&&(this._shader.uniforms.model=c.projections[i],this._shader.uniforms.clipBounds=c.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(c.showContour){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var h=this._contourVAO;for(h.bind(),i=0;i<3;++i)for(f.uniforms.permutation=A[i],r.lineWidth(this.contourWidth[i]*this.pixelRatio),o=0;o<this.contourLevels[i].length;++o)o===this.highlightLevel[i]?(f.uniforms.contourColor=this.highlightColor[i],f.uniforms.contourTint=this.highlightTint[i]):0!==o&&o-1!==this.highlightLevel[i]||(f.uniforms.contourColor=this.contourColor[i],f.uniforms.contourTint=this.contourTint[i]),this._contourCounts[i][o]&&(f.uniforms.height=this.contourLevels[i][o],h.draw(r.LINES,this._contourCounts[i][o],this._contourOffsets[i][o]));for(i=0;i<3;++i)for(f.uniforms.model=c.projections[i],f.uniforms.clipBounds=c.clipBounds[i],o=0;o<3;++o)if(this.contourProject[i][o]){f.uniforms.permutation=A[o],r.lineWidth(this.contourWidth[o]*this.pixelRatio);for(var v=0;v<this.contourLevels[o].length;++v)v===this.highlightLevel[o]?(f.uniforms.contourColor=this.highlightColor[o],f.uniforms.contourTint=this.highlightTint[o]):0!==v&&v-1!==this.highlightLevel[o]||(f.uniforms.contourColor=this.contourColor[o],f.uniforms.contourTint=this.contourTint[o]),this._contourCounts[o][v]&&(f.uniforms.height=this.contourLevels[o][v],h.draw(r.LINES,this._contourCounts[o][v],this._contourOffsets[o][v]))}for(h.unbind(),(h=this._dynamicVAO).bind(),i=0;i<3;++i)if(0!==this._dynamicCounts[i])for(f.uniforms.model=n.model,f.uniforms.clipBounds=n.clipBounds,f.uniforms.permutation=A[i],r.lineWidth(this.dynamicWidth[i]*this.pixelRatio),f.uniforms.contourColor=this.dynamicColor[i],f.uniforms.contourTint=this.dynamicTint[i],f.uniforms.height=this.dynamicLevel[i],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]),o=0;o<3;++o)this.contourProject[o][i]&&(f.uniforms.model=c.projections[o],f.uniforms.clipBounds=c.clipBounds[o],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]));h.unbind()}}L.draw=function(t){return R.call(this,t,!1)},L.drawTransparent=function(t){return R.call(this,t,!0)};var F={model:T,view:T,projection:T,inverseModel:T,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,objectOffset:[0,0,0],permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};function B(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function N(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function j(t){if(Array.isArray(t)){if(Array.isArray(t))return[N(t[0]),N(t[1]),N(t[2])];var e=N(t);return[e.slice(),e.slice(),e.slice()]}}L.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=F;r.model=t.model||T,r.view=t.view||T,r.projection=t.projection||T,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.objectOffset=this.objectOffset,r.permutation=z;for(var n=0;n<2;++n)for(var i=r.clipBounds[n],a=0;a<3;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var o=O(r,this);if(o.showSurface){for(this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount),n=0;n<3;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=o.projections[n],this._pickShader.uniforms.clipBounds=o.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(o.showContour){var s=this._contourPickShader;s.bind(),s.uniforms=r;var l=this._contourVAO;for(l.bind(),a=0;a<3;++a)for(e.lineWidth(this.contourWidth[a]*this.pixelRatio),s.uniforms.permutation=A[a],n=0;n<this.contourLevels[a].length;++n)this._contourCounts[a][n]&&(s.uniforms.height=this.contourLevels[a][n],l.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n]));for(n=0;n<3;++n)for(s.uniforms.model=o.projections[n],s.uniforms.clipBounds=o.clipBounds[n],a=0;a<3;++a)if(this.contourProject[n][a]){s.uniforms.permutation=A[a],e.lineWidth(this.contourWidth[a]*this.pixelRatio);for(var u=0;u<this.contourLevels[a].length;++u)this._contourCounts[a][u]&&(s.uniforms.height=this.contourLevels[a][u],l.draw(e.LINES,this._contourCounts[a][u],this._contourOffsets[a][u]))}l.unbind()}},L.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var u=r.position;u[0]=u[1]=u[2]=0;for(var c=0;c<2;++c)for(var f=c?a:1-a,h=0;h<2;++h)for(var p=i+c,d=s+h,g=f*(h?l:1-l),y=0;y<3;++y)u[y]+=this._field[y].get(p,d)*g;for(var m=this._pickResult.level,x=0;x<3;++x)if(m[x]=v.le(this.contourLevels[x],u[x]),m[x]<0)this.contourLevels[x].length>0&&(m[x]=0);else if(m[x]<this.contourLevels[x].length-1){var b=this.contourLevels[x][m[x]],_=this.contourLevels[x][m[x]+1];Math.abs(b-u[x])>Math.abs(_-u[x])&&(m[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],y=0;y<3;++y)r.dataCoordinate[y]=this._field[y].get(r.index[0],r.index[1]);return r},L.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();u.assign(t.lo(1,1).hi(r[0],r[1]),e),u.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),u.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),u.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),u.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},L.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=B(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=B(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=B(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=j(t.contourColor)),\"contourProject\"in t&&(this.contourProject=B(t.contourProject,(function(t){return B(t,Boolean)}))),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=j(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=B(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=B(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0),\"colormap\"in t&&this._colorMap.setPixels(this.genColormap(t.colormap,this.opacityscale));var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var i=(e.shape[0]+2)*(e.shape[1]+2);i>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(i))),this._field[2]=f(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var l=t.coords;if(!Array.isArray(l)||3!==l.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var u=l[o];for(y=0;y<2;++y)if(u.shape[y]!==a[y])throw new Error(\"gl-surface: coords have incorrect shape\");this.padField(this._field[o],u)}}else if(t.ticks){var c=t.ticks;if(!Array.isArray(c)||2!==c.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var p=c[o];if((Array.isArray(p)||p.length)&&(p=f(p)),p.shape[0]!==a[o])throw new Error(\"gl-surface: invalid tick length\");var d=f(p.data,a);d.stride[o]=p.stride[0],d.stride[1^o]=0,this.padField(this._field[o],d)}}else{for(o=0;o<2;++o){var v=[0,0];v[o]=1,this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2],v,0)}this._field[0].set(0,0,0);for(var y=0;y<a[0];++y)this._field[0].set(y+1,0,y);for(this._field[0].set(a[0]+1,0,a[0]-1),this._field[1].set(0,0,0),y=0;y<a[1];++y)this._field[1].set(0,y+1,y);this._field[1].set(0,a[1]+1,a[1]-1)}var m=this._field,x=f(s.mallocFloat(3*m[2].size*2),[3,a[0]+2,a[1]+2,2]);for(o=0;o<3;++o)g(x.pick(o),m[o],\"mirror\");var b=f(s.mallocFloat(3*m[2].size),[a[0]+2,a[1]+2,3]);for(o=0;o<a[0]+2;++o)for(y=0;y<a[1]+2;++y){var _=x.get(0,o,y,0),w=x.get(0,o,y,1),T=x.get(1,o,y,0),A=x.get(1,o,y,1),M=x.get(2,o,y,0),S=x.get(2,o,y,1),E=T*S-A*M,L=M*w-S*_,C=_*A-w*T,P=Math.sqrt(E*E+L*L+C*C);P<1e-8?(P=Math.max(Math.abs(E),Math.abs(L),Math.abs(C)))<1e-8?(C=1,L=E=0,P=1):P=1/P:P=1/Math.sqrt(P),b.set(o,y,0,E*P),b.set(o,y,1,L*P),b.set(o,y,2,C*P)}s.free(x.data);var O=[1/0,1/0,1/0],I=[-1/0,-1/0,-1/0],D=1/0,z=-1/0,R=(a[0]-1)*(a[1]-1)*6,F=s.mallocFloat(n.nextPow2(10*R)),N=0,U=0;for(o=0;o<a[0]-1;++o)t:for(y=0;y<a[1]-1;++y){for(var V=0;V<2;++V)for(var H=0;H<2;++H)for(var q=0;q<3;++q){var G=this._field[q].get(1+o+V,1+y+H);if(isNaN(G)||!isFinite(G))continue t}for(q=0;q<6;++q){var Z=o+k[q][0],Y=y+k[q][1],W=this._field[0].get(Z+1,Y+1),X=this._field[1].get(Z+1,Y+1);G=this._field[2].get(Z+1,Y+1),E=b.get(Z+1,Y+1,0),L=b.get(Z+1,Y+1,1),C=b.get(Z+1,Y+1,2),t.intensity&&(J=t.intensity.get(Z,Y));var J=t.intensity?t.intensity.get(Z,Y):G+this.objectOffset[2];F[N++]=Z,F[N++]=Y,F[N++]=W,F[N++]=X,F[N++]=G,F[N++]=0,F[N++]=J,F[N++]=E,F[N++]=L,F[N++]=C,O[0]=Math.min(O[0],W+this.objectOffset[0]),O[1]=Math.min(O[1],X+this.objectOffset[1]),O[2]=Math.min(O[2],G+this.objectOffset[2]),D=Math.min(D,J),I[0]=Math.max(I[0],W+this.objectOffset[0]),I[1]=Math.max(I[1],X+this.objectOffset[1]),I[2]=Math.max(I[2],G+this.objectOffset[2]),z=Math.max(z,J),U+=1}}for(t.intensityBounds&&(D=+t.intensityBounds[0],z=+t.intensityBounds[1]),o=6;o<N;o+=10)F[o]=(F[o]-D)/(z-D);this._vertexCount=U,this._coordinateBuffer.update(F.subarray(0,N)),s.freeFloat(F),s.free(b.data),this.bounds=[O,I],this.intensity=t.intensity||this._field[2],this.intensityBounds[0]===D&&this.intensityBounds[1]===z||(r=!0),this.intensityBounds=[D,z]}if(\"levels\"in t){var K=t.levels;for(K=Array.isArray(K[0])?K.slice():[[],[],K],o=0;o<3;++o)K[o]=K[o].slice(),K[o].sort((function(t,e){return t-e}));for(o=0;o<3;++o)for(y=0;y<K[o].length;++y)K[o][y]-=this.objectOffset[o];t:for(o=0;o<3;++o){if(K[o].length!==this.contourLevels[o].length){r=!0;break}for(y=0;y<K[o].length;++y)if(K[o][y]!==this.contourLevels[o][y]){r=!0;break t}}this.contourLevels=K}if(r){m=this._field,a=this.shape;for(var $=[],Q=0;Q<3;++Q){var tt=this.contourLevels[Q],et=[],rt=[],nt=[0,0,0];for(o=0;o<tt.length;++o){var it=h(this._field[Q],tt[o]);et.push($.length/5|0),U=0;t:for(y=0;y<it.cells.length;++y){var at=it.cells[y];for(q=0;q<2;++q){var ot=it.positions[at[q]],st=ot[0],lt=0|Math.floor(st),ut=st-lt,ct=ot[1],ft=0|Math.floor(ct),ht=ct-ft,pt=!1;e:for(var dt=0;dt<3;++dt){nt[dt]=0;var vt=(Q+dt+1)%3;for(V=0;V<2;++V){var gt=V?ut:1-ut;for(Z=0|Math.min(Math.max(lt+V,0),a[0]),H=0;H<2;++H){var yt=H?ht:1-ht;if(Y=0|Math.min(Math.max(ft+H,0),a[1]),G=dt<2?this._field[vt].get(Z,Y):(this.intensity.get(Z,Y)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(G)||isNaN(G)){pt=!0;break e}var mt=gt*yt;nt[dt]+=mt*G}}}if(pt){if(q>0){for(var xt=0;xt<5;++xt)$.pop();U-=1}continue t}$.push(nt[0],nt[1],ot[0],ot[1],nt[2]),U+=1}}rt.push(U)}this._contourOffsets[Q]=et,this._contourCounts[Q]=rt}var bt=s.mallocFloat($.length);for(o=0;o<$.length;++o)bt[o]=$[o];this._contourBuffer.update(bt),s.freeFloat(bt)}},L.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)s.freeFloat(this._field[t].data)},L.highlight=function(t){var e,r;if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;for(r=this.snapToData?t.dataCoordinate:t.position,e=0;e<3;++e)r[e]-=this.objectOffset[e];if(this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=s.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var l=(o+1)%3,u=(o+2)%3,c=this._field[o],f=this._field[l],p=this._field[u],d=h(c,r[o]),v=d.cells,g=d.positions;for(this._dynamicOffsets[o]=n,e=0;e<v.length;++e)for(var y=v[e],m=0;m<2;++m){var x=g[y[m]],b=+x[0],_=0|b,w=0|Math.min(_+1,i[0]),T=b-_,k=1-T,A=+x[1],M=0|A,S=0|Math.min(M+1,i[1]),E=A-M,L=1-E,C=k*L,P=k*E,O=T*L,I=T*E,D=C*f.get(_,M)+P*f.get(_,S)+O*f.get(w,M)+I*f.get(w,S),z=C*p.get(_,M)+P*p.get(_,S)+O*p.get(w,M)+I*p.get(w,S);if(isNaN(D)||isNaN(z)){m&&(n-=1);break}a[2*n+0]=D,a[2*n+1]=z,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),s.freeFloat(a)}}},8931:function(t,e,r){\"use strict\";var n=r(5050),i=r(7498),a=r(5306);t.exports=function(t){if(arguments.length<=1)throw new Error(\"gl-texture2d: Missing arguments for texture2d constructor\");if(o||function(t){o=[t.LINEAR,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_NEAREST],s=[t.NEAREST,t.LINEAR,t.NEAREST_MIPMAP_NEAREST,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_LINEAR],l=[t.REPEAT,t.CLAMP_TO_EDGE,t.MIRRORED_REPEAT]}(t),\"number\"==typeof arguments[1])return g(t,arguments[1],arguments[2],arguments[3]||t.RGBA,arguments[4]||t.UNSIGNED_BYTE);if(Array.isArray(arguments[1]))return g(t,0|arguments[1][0],0|arguments[1][1],arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(\"object\"==typeof arguments[1]){var e=arguments[1],r=u(e)?e:e.raw;if(r)return function(t,e,r,n,i,a){var o=v(t);return t.texImage2D(t.TEXTURE_2D,0,i,i,a,e),new h(t,o,r,n,i,a)}(t,r,0|e.width,0|e.height,arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(e.shape&&e.data&&e.stride)return function(t,e){var r=e.dtype,o=e.shape.slice(),s=t.getParameter(t.MAX_TEXTURE_SIZE);if(o[0]<0||o[0]>s||o[1]<0||o[1]>s)throw new Error(\"gl-texture2d: Invalid texture size\");var l=d(o,e.stride.slice()),u=0;\"float32\"===r?u=t.FLOAT:\"float64\"===r?(u=t.FLOAT,l=!1,r=\"float32\"):\"uint8\"===r?u=t.UNSIGNED_BYTE:(u=t.UNSIGNED_BYTE,l=!1,r=\"uint8\");var f,p,g=0;if(2===o.length)g=t.LUMINANCE,o=[o[0],o[1],1],e=n(e.data,o,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==o.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===o[2])g=t.ALPHA;else if(2===o[2])g=t.LUMINANCE_ALPHA;else if(3===o[2])g=t.RGB;else{if(4!==o[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");g=t.RGBA}}u!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(u=t.UNSIGNED_BYTE,l=!1);var y=e.size;if(l)f=0===e.offset&&e.data.length===y?e.data:e.data.subarray(e.offset,e.offset+y);else{var m=[o[2],o[2]*o[0],1];p=a.malloc(y,r);var x=n(p,o,m,0);\"float32\"!==r&&\"float64\"!==r||u!==t.UNSIGNED_BYTE?i.assign(x,e):c(x,e),f=p.subarray(0,y)}var b=v(t);return t.texImage2D(t.TEXTURE_2D,0,g,o[0],o[1],0,g,u,f),l||a.free(p),new h(t,b,o[0],o[1],g,u)}(t,e)}throw new Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")};var o=null,s=null,l=null;function u(t){return\"undefined\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\"undefined\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\"undefined\"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement||\"undefined\"!=typeof ImageData&&t instanceof ImageData}var c=function(t,e){i.muls(t,e,255)};function f(t,e,r){var n=t.gl,i=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-texture2d: Invalid texture size\");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function h(t,e,r,n,i,a){this.gl=t,this.handle=e,this.format=i,this.type=a,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}var p=h.prototype;function d(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function v(t){var e=t.createTexture();return t.bindTexture(t.TEXTURE_2D,e),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),e}function g(t,e,r,n,i){var a=t.getParameter(t.MAX_TEXTURE_SIZE);if(e<0||e>a||r<0||r>a)throw new Error(\"gl-texture2d: Invalid texture shape\");if(i===t.FLOAT&&!t.getExtension(\"OES_texture_float\"))throw new Error(\"gl-texture2d: Floating point textures not supported on this platform\");var o=v(t);return t.texImage2D(t.TEXTURE_2D,0,n,e,r,0,n,i,null),new h(t,o,e,r,n,i)}Object.defineProperties(p,{minFilter:{get:function(){return this._minFilter},set:function(t){this.bind();var 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n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],u=e[8],c=e[9],f=e[10],h=e[11];return e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[0]=a*i-u*n,t[1]=o*i-c*n,t[2]=s*i-f*n,t[3]=l*i-h*n,t[8]=a*n+u*i,t[9]=o*n+c*i,t[10]=s*n+f*i,t[11]=l*n+h*i,t}},15692:function(t){t.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],u=e[4],c=e[5],f=e[6],h=e[7];return e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[0]=a*i+u*n,t[1]=o*i+c*n,t[2]=s*i+f*n,t[3]=l*i+h*n,t[4]=u*i-a*n,t[5]=c*i-o*n,t[6]=f*i-s*n,t[7]=h*i-l*n,t}},10789:function(t){t.exports=function(t,e,r){var n=r[0],i=r[1],a=r[2];return t[0]=e[0]*n,t[1]=e[1]*n,t[2]=e[2]*n,t[3]=e[3]*n,t[4]=e[4]*i,t[5]=e[5]*i,t[6]=e[6]*i,t[7]=e[7]*i,t[8]=e[8]*a,t[9]=e[9]*a,t[10]=e[10]*a,t[11]=e[11]*a,t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t}},6726:function(t){t.exports=function(t){return\"mat4(\"+t[0]+\", \"+t[1]+\", \"+t[2]+\", \"+t[3]+\", \"+t[4]+\", \"+t[5]+\", \"+t[6]+\", \"+t[7]+\", \"+t[8]+\", \"+t[9]+\", \"+t[10]+\", \"+t[11]+\", \"+t[12]+\", \"+t[13]+\", \"+t[14]+\", \"+t[15]+\")\"}},31283:function(t){t.exports=function(t,e,r){var n,i,a,o,s,l,u,c,f,h,p,d,v=r[0],g=r[1],y=r[2];return e===t?(t[12]=e[0]*v+e[4]*g+e[8]*y+e[12],t[13]=e[1]*v+e[5]*g+e[9]*y+e[13],t[14]=e[2]*v+e[6]*g+e[10]*y+e[14],t[15]=e[3]*v+e[7]*g+e[11]*y+e[15]):(n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],u=e[6],c=e[7],f=e[8],h=e[9],p=e[10],d=e[11],t[0]=n,t[1]=i,t[2]=a,t[3]=o,t[4]=s,t[5]=l,t[6]=u,t[7]=c,t[8]=f,t[9]=h,t[10]=p,t[11]=d,t[12]=n*v+s*g+f*y+e[12],t[13]=i*v+l*g+h*y+e[13],t[14]=a*v+u*g+p*y+e[14],t[15]=o*v+c*g+d*y+e[15]),t}},88654:function(t){t.exports=function(t,e){if(t===e){var r=e[1],n=e[2],i=e[3],a=e[6],o=e[7],s=e[11];t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=r,t[6]=e[9],t[7]=e[13],t[8]=n,t[9]=a,t[11]=e[14],t[12]=i,t[13]=o,t[14]=s}else t[0]=e[0],t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=e[1],t[5]=e[5],t[6]=e[9],t[7]=e[13],t[8]=e[2],t[9]=e[6],t[10]=e[10],t[11]=e[14],t[12]=e[3],t[13]=e[7],t[14]=e[11],t[15]=e[15];return t}},42505:function(t,e,r){\"use strict\";var n=r(72791),i=r(71299),a=r(98580),o=r(12018),s=r(83522),l=r(25075),u=r(68016),c=r(58404),f=r(18863),h=r(10973),p=r(25677),d=r(75686),v=r(53545),g=r(56131),y=r(32879),m=r(30120),x=r(13547).nextPow2,b=new s,_=!1;if(document.body){var w=document.body.appendChild(document.createElement(\"div\"));w.style.font=\"italic small-caps bold condensed 16px/2 cursive\",getComputedStyle(w).fontStretch&&(_=!0),document.body.removeChild(w)}var T=function(t){!function(t){return\"function\"==typeof t&&t._gl&&t.prop&&t.texture&&t.buffer}(t)?this.gl=o(t):(t={regl:t},this.gl=t.regl._gl),this.shader=b.get(this.gl),this.shader?this.regl=this.shader.regl:this.regl=t.regl||a({gl:this.gl}),this.charBuffer=this.regl.buffer({type:\"uint8\",usage:\"stream\"}),this.sizeBuffer=this.regl.buffer({type:\"float\",usage:\"stream\"}),this.shader||(this.shader=this.createShader(),b.set(this.gl,this.shader)),this.batch=[],this.fontSize=[],this.font=[],this.fontAtlas=[],this.draw=this.shader.draw.bind(this),this.render=function(){this.regl._refresh(),this.draw(this.batch)},this.canvas=this.gl.canvas,this.update(h(t)?t:{})};T.prototype.createShader=function(){var t=this.regl,e=t({blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst 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float fontSize, charStep, em, align, baseline;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tuniform vec4 color;\\n\\t\\t\\tuniform vec2 atlasSize, atlasDim, scale, translate, positionOffset;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\tvec2 offset = floor(em * (vec2(align + charOffset, baseline)\\n\\t\\t\\t\\t\\t+ vec2(positionOffset.x, -positionOffset.y)))\\n\\t\\t\\t\\t\\t/ (viewport.zw * scale.xy);\\n\\n\\t\\t\\t\\tvec2 position = (position + translate) * scale;\\n\\t\\t\\t\\tposition += offset * scale;\\n\\n\\t\\t\\t\\tcharCoord = position * viewport.zw + viewport.xy;\\n\\n\\t\\t\\t\\tgl_Position = vec4(position * 2. - 1., 0, 1);\\n\\n\\t\\t\\t\\tgl_PointSize = charStep;\\n\\n\\t\\t\\t\\tcharId.x = mod(char, atlasDim.x);\\n\\t\\t\\t\\tcharId.y = floor(char / atlasDim.x);\\n\\n\\t\\t\\t\\tcharWidth = width * em;\\n\\n\\t\\t\\t\\tfontColor = color / 255.;\\n\\t\\t\\t}\",frag:\"\\n\\t\\t\\tprecision highp float;\\n\\t\\t\\tuniform float fontSize, charStep, opacity;\\n\\t\\t\\tuniform vec2 atlasSize;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tuniform sampler2D atlas;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\n\\t\\t\\tfloat lightness(vec4 color) {\\n\\t\\t\\t\\treturn color.r * 0.299 + color.g * 0.587 + color.b * 0.114;\\n\\t\\t\\t}\\n\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\tvec2 uv = gl_FragCoord.xy - charCoord + charStep * .5;\\n\\t\\t\\t\\tfloat halfCharStep = floor(charStep * .5 + .5);\\n\\n\\t\\t\\t\\t// invert y and shift by 1px (FF expecially needs that)\\n\\t\\t\\t\\tuv.y = charStep - uv.y;\\n\\n\\t\\t\\t\\t// ignore points outside of character bounding box\\n\\t\\t\\t\\tfloat halfCharWidth = ceil(charWidth * .5);\\n\\t\\t\\t\\tif (floor(uv.x) > halfCharStep + halfCharWidth ||\\n\\t\\t\\t\\t\\tfloor(uv.x) < halfCharStep - halfCharWidth) return;\\n\\n\\t\\t\\t\\tuv += charId * charStep;\\n\\t\\t\\t\\tuv = uv / atlasSize;\\n\\n\\t\\t\\t\\tvec4 color = fontColor;\\n\\t\\t\\t\\tvec4 mask = texture2D(atlas, uv);\\n\\n\\t\\t\\t\\tfloat maskY = lightness(mask);\\n\\t\\t\\t\\t// float colorY = lightness(color);\\n\\t\\t\\t\\tcolor.a *= maskY;\\n\\t\\t\\t\\tcolor.a *= opacity;\\n\\n\\t\\t\\t\\t// color.a += .1;\\n\\n\\t\\t\\t\\t// antialiasing, see yiq color space y-channel formula\\n\\t\\t\\t\\t// color.rgb += (1. - color.rgb) * (1. - mask.rgb);\\n\\n\\t\\t\\t\\tgl_FragColor = color;\\n\\t\\t\\t}\"});return{regl:t,draw:e,atlas:{}}},T.prototype.update=function(t){var e=this;if(\"string\"==typeof t)t={text:t};else if(!t)return;null!=(t=i(t,{position:\"position positions coord coords coordinates\",font:\"font fontFace fontface typeface cssFont css-font family fontFamily\",fontSize:\"fontSize fontsize size font-size\",text:\"text texts chars characters value values symbols\",align:\"align alignment textAlign textbaseline\",baseline:\"baseline textBaseline textbaseline\",direction:\"dir direction textDirection\",color:\"color colour fill fill-color fillColor textColor textcolor\",kerning:\"kerning kern\",range:\"range dataBox\",viewport:\"vp viewport viewBox viewbox viewPort\",opacity:\"opacity alpha transparency visible visibility opaque\",offset:\"offset positionOffset padding shift indent indentation\"},!0)).opacity&&(Array.isArray(t.opacity)?this.opacity=t.opacity.map((function(t){return parseFloat(t)})):this.opacity=parseFloat(t.opacity)),null!=t.viewport&&(this.viewport=f(t.viewport),this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null==this.viewport&&(this.viewport={x:0,y:0,width:this.gl.drawingBufferWidth,height:this.gl.drawingBufferHeight},this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null!=t.kerning&&(this.kerning=t.kerning),null!=t.offset&&(\"number\"==typeof t.offset&&(t.offset=[t.offset,0]),this.positionOffset=m(t.offset)),t.direction&&(this.direction=t.direction),t.range&&(this.range=t.range,this.scale=[1/(t.range[2]-t.range[0]),1/(t.range[3]-t.range[1])],this.translate=[-t.range[0],-t.range[1]]),t.scale&&(this.scale=t.scale),t.translate&&(this.translate=t.translate),this.scale||(this.scale=[1/this.viewport.width,1/this.viewport.height]),this.translate||(this.translate=[0,0]),this.font.length||t.font||(t.font=T.baseFontSize+\"px sans-serif\");var r,a=!1,o=!1;if(t.font&&(Array.isArray(t.font)?t.font:[t.font]).forEach((function(t,r){if(\"string\"==typeof t)try{t=n.parse(t)}catch(e){t=n.parse(T.baseFontSize+\"px \"+t)}else t=n.parse(n.stringify(t));var i=n.stringify({size:T.baseFontSize,family:t.family,stretch:_?t.stretch:void 0,variant:t.variant,weight:t.weight,style:t.style}),s=p(t.size),l=Math.round(s[0]*d(s[1]));if(l!==e.fontSize[r]&&(o=!0,e.fontSize[r]=l),!(e.font[r]&&i==e.font[r].baseString||(a=!0,e.font[r]=T.fonts[i],e.font[r]))){var u=t.family.join(\", \"),c=[t.style];t.style!=t.variant&&c.push(t.variant),t.variant!=t.weight&&c.push(t.weight),_&&t.weight!=t.stretch&&c.push(t.stretch),e.font[r]={baseString:i,family:u,weight:t.weight,stretch:t.stretch,style:t.style,variant:t.variant,width:{},kerning:{},metrics:y(u,{origin:\"top\",fontSize:T.baseFontSize,fontStyle:c.join(\" \")})},T.fonts[i]=e.font[r]}})),(a||o)&&this.font.forEach((function(r,i){var a=n.stringify({size:e.fontSize[i],family:r.family,stretch:_?r.stretch:void 0,variant:r.variant,weight:r.weight,style:r.style});if(e.fontAtlas[i]=e.shader.atlas[a],!e.fontAtlas[i]){var o=r.metrics;e.shader.atlas[a]=e.fontAtlas[i]={fontString:a,step:2*Math.ceil(e.fontSize[i]*o.bottom*.5),em:e.fontSize[i],cols:0,rows:0,height:0,width:0,chars:[],ids:{},texture:e.regl.texture()}}null==t.text&&(t.text=e.text)})),\"string\"==typeof t.text&&t.position&&t.position.length>2){for(var 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Math.atan2(this.y-t.y,this.x-t.x)},angleWith:function(t){return this.angleWithSep(t.x,t.y)},angleWithSep:function(t,e){return Math.atan2(this.x*e-this.y*t,this.x*t+this.y*e)},_matMult:function(t){var e=t[0]*this.x+t[1]*this.y,r=t[2]*this.x+t[3]*this.y;return this.x=e,this.y=r,this},_add:function(t){return this.x+=t.x,this.y+=t.y,this},_sub:function(t){return this.x-=t.x,this.y-=t.y,this},_mult:function(t){return this.x*=t,this.y*=t,this},_div:function(t){return this.x/=t,this.y/=t,this},_multByPoint:function(t){return this.x*=t.x,this.y*=t.y,this},_divByPoint:function(t){return this.x/=t.x,this.y/=t.y,this},_unit:function(){return this._div(this.mag()),this},_perp:function(){var t=this.y;return this.y=this.x,this.x=-t,this},_rotate:function(t){var e=Math.cos(t),r=Math.sin(t),n=e*this.x-r*this.y,i=r*this.x+e*this.y;return this.x=n,this.y=i,this},_rotateAround:function(t,e){var r=Math.cos(t),n=Math.sin(t),i=e.x+r*(this.x-e.x)-n*(this.y-e.y),a=e.y+n*(this.x-e.x)+r*(this.y-e.y);return 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r.width=t.width,r.height=t.height,n.drawImage(t,0,0,t.width,t.height),n.getImageData(-e,-e,t.width+2*e,t.height+2*e)},resolveURL:function(t){return C||(C=self.document.createElement(\"a\")),C.href=t,C.href},hardwareConcurrency:self.navigator.hardwareConcurrency||4,get devicePixelRatio(){return self.devicePixelRatio},get prefersReducedMotion(){return!!self.matchMedia&&(null==P&&(P=self.matchMedia(\"(prefers-reduced-motion: reduce)\")),P.matches)}},B={API_URL:\"https://api.mapbox.com\",get EVENTS_URL(){return this.API_URL?0===this.API_URL.indexOf(\"https://api.mapbox.cn\")?\"https://events.mapbox.cn/events/v2\":0===this.API_URL.indexOf(\"https://api.mapbox.com\")?\"https://events.mapbox.com/events/v2\":null:null},FEEDBACK_URL:\"https://apps.mapbox.com/feedback\",REQUIRE_ACCESS_TOKEN:!0,ACCESS_TOKEN:null,MAX_PARALLEL_IMAGE_REQUESTS:16},N={supported:!1,testSupport:function(t){!j&&I&&(U?V(t):O=t)}},j=!1,U=!1;function V(t){var 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Date.now()>this._skuTokenExpiresAt},q.prototype.transformRequest=function(t,e){return this._transformRequestFn&&this._transformRequestFn(t,e)||{url:t}},q.prototype.normalizeStyleURL=function(t,e){if(!G(t))return t;var r=X(t);return r.path=\"/styles/v1\"+r.path,this._makeAPIURL(r,this._customAccessToken||e)},q.prototype.normalizeGlyphsURL=function(t,e){if(!G(t))return t;var r=X(t);return r.path=\"/fonts/v1\"+r.path,this._makeAPIURL(r,this._customAccessToken||e)},q.prototype.normalizeSourceURL=function(t,e){if(!G(t))return t;var r=X(t);return r.path=\"/v4/\"+r.authority+\".json\",r.params.push(\"secure\"),this._makeAPIURL(r,this._customAccessToken||e)},q.prototype.normalizeSpriteURL=function(t,e,r,n){var i=X(t);return G(t)?(i.path=\"/styles/v1\"+i.path+\"/sprite\"+e+r,this._makeAPIURL(i,this._customAccessToken||n)):(i.path+=\"\"+e+r,J(i))},q.prototype.normalizeTileURL=function(t,e){if(this._isSkuTokenExpired()&&this._createSkuToken(),t&&!G(t))return t;var r=X(t),n=F.devicePixelRatio>=2||512===e?\"@2x\":\"\",i=N.supported?\".webp\":\"$1\";r.path=r.path.replace(/(\\.(png|jpg)\\d*)(?=$)/,\"\"+n+i),r.path=r.path.replace(/^.+\\/v4\\//,\"/\"),r.path=\"/v4\"+r.path;var a=this._customAccessToken||function(t){for(var e=0,r=t;e<r.length;e+=1){var n=r[e].match(/^access_token=(.*)$/);if(n)return n[1]}return null}(r.params)||B.ACCESS_TOKEN;return B.REQUIRE_ACCESS_TOKEN&&a&&this._skuToken&&r.params.push(\"sku=\"+this._skuToken),this._makeAPIURL(r,a)},q.prototype.canonicalizeTileURL=function(t,e){var r=X(t);if(!r.path.match(/(^\\/v4\\/)/)||!r.path.match(/\\.[\\w]+$/))return t;var n=\"mapbox://tiles/\";n+=r.path.replace(\"/v4/\",\"\");var i=r.params;return e&&(i=i.filter((function(t){return!t.match(/^access_token=/)}))),i.length&&(n+=\"?\"+i.join(\"&\")),n},q.prototype.canonicalizeTileset=function(t,e){for(var r=!!e&&G(e),n=[],i=0,a=t.tiles||[];i<a.length;i+=1){var o=a[i];Y(o)?n.push(this.canonicalizeTileURL(o,r)):n.push(o)}return n},q.prototype._makeAPIURL=function(t,e){var r=\"See https://www.mapbox.com/api-documentation/#access-tokens-and-token-scopes\",n=X(B.API_URL);if(t.protocol=n.protocol,t.authority=n.authority,\"/\"!==n.path&&(t.path=\"\"+n.path+t.path),!B.REQUIRE_ACCESS_TOKEN)return J(t);if(!(e=e||B.ACCESS_TOKEN))throw new Error(\"An API access token is required to use Mapbox GL. \"+r);if(\"s\"===e[0])throw new Error(\"Use a public access token (pk.*) with Mapbox GL, not a secret access token (sk.*). \"+r);return t.params=t.params.filter((function(t){return-1===t.indexOf(\"access_token\")})),t.params.push(\"access_token=\"+e),J(t)};var Z=/^((https?:)?\\/\\/)?([^\\/]+\\.)?mapbox\\.c(n|om)(\\/|\\?|$)/i;function Y(t){return Z.test(t)}var W=/^(\\w+):\\/\\/([^/?]*)(\\/[^?]+)?\\??(.+)?/;function X(t){var e=t.match(W);if(!e)throw new Error(\"Unable to parse URL object\");return{protocol:e[1],authority:e[2],path:e[3]||\"/\",params:e[4]?e[4].split(\"&\"):[]}}function J(t){var e=t.params.length?\"?\"+t.params.join(\"&\"):\"\";return t.protocol+\"://\"+t.authority+t.path+e}var K=\"mapbox.eventData\";function $(t){if(!t)return null;var e,r=t.split(\".\");if(!r||3!==r.length)return null;try{return JSON.parse((e=r[1],decodeURIComponent(self.atob(e).split(\"\").map((function(t){return\"%\"+(\"00\"+t.charCodeAt(0).toString(16)).slice(-2)})).join(\"\"))))}catch(t){return null}}var Q=function(t){this.type=t,this.anonId=null,this.eventData={},this.queue=[],this.pendingRequest=null};Q.prototype.getStorageKey=function(t){var e,r,n=$(B.ACCESS_TOKEN);return e=n&&n.u?(r=n.u,self.btoa(encodeURIComponent(r).replace(/%([0-9A-F]{2})/g,(function(t,e){return String.fromCharCode(Number(\"0x\"+e))})))):B.ACCESS_TOKEN||\"\",t?K+\".\"+t+\":\"+e:K+\":\"+e},Q.prototype.fetchEventData=function(){var t=L(\"localStorage\"),e=this.getStorageKey(),r=this.getStorageKey(\"uuid\");if(t)try{var n=self.localStorage.getItem(e);n&&(this.eventData=JSON.parse(n));var 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r=this.queue.shift(),n=r.id,i=r.timestamp;n&&this.success[n]||(this.anonId||this.fetchEventData(),v(this.anonId)||(this.anonId=d()),this.postEvent(i,{skuToken:this.skuToken},(function(t){t||n&&(e.success[n]=!0)}),t))}},e}(Q),nt=function(t){function e(e){t.call(this,\"appUserTurnstile\"),this._customAccessToken=e}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.postTurnstileEvent=function(t,e){B.EVENTS_URL&&B.ACCESS_TOKEN&&Array.isArray(t)&&t.some((function(t){return G(t)||Y(t)}))&&this.queueRequest(Date.now(),e)},e.prototype.processRequests=function(t){var e=this;if(!this.pendingRequest&&0!==this.queue.length){this.anonId&&this.eventData.lastSuccess&&this.eventData.tokenU||this.fetchEventData();var r=$(B.ACCESS_TOKEN),n=r?r.u:B.ACCESS_TOKEN,i=n!==this.eventData.tokenU;v(this.anonId)||(this.anonId=d(),i=!0);var a=this.queue.shift();if(this.eventData.lastSuccess){var o=new Date(this.eventData.lastSuccess),s=new 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n(t){return(t=Math.round(t))<0?0:t>255?255:t}function i(t){return t<0?0:t>1?1:t}function a(t){return\"%\"===t[t.length-1]?n(parseFloat(t)/100*255):n(parseInt(t))}function o(t){return\"%\"===t[t.length-1]?i(parseFloat(t)/100):i(parseFloat(t))}function s(t,e,r){return r<0?r+=1:r>1&&(r-=1),6*r<1?t+(e-t)*r*6:2*r<1?e:3*r<2?t+(e-t)*(2/3-r)*6:t}try{e.parseCSSColor=function(t){var e,i=t.replace(/ /g,\"\").toLowerCase();if(i in r)return r[i].slice();if(\"#\"===i[0])return 4===i.length?(e=parseInt(i.substr(1),16))>=0&&e<=4095?[(3840&e)>>4|(3840&e)>>8,240&e|(240&e)>>4,15&e|(15&e)<<4,1]:null:7===i.length&&(e=parseInt(i.substr(1),16))>=0&&e<=16777215?[(16711680&e)>>16,(65280&e)>>8,255&e,1]:null;var l=i.indexOf(\"(\"),u=i.indexOf(\")\");if(-1!==l&&u+1===i.length){var c=i.substr(0,l),f=i.substr(l+1,u-(l+1)).split(\",\"),h=1;switch(c){case\"rgba\":if(4!==f.length)return null;h=o(f.pop());case\"rgb\":return 3!==f.length?null:[a(f[0]),a(f[1]),a(f[2]),h];case\"hsla\":if(4!==f.length)return 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se=function(t,e,r){this.sensitivity=t?e?\"variant\":\"case\":e?\"accent\":\"base\",this.locale=r,this.collator=new Intl.Collator(this.locale?this.locale:[],{sensitivity:this.sensitivity,usage:\"search\"})};se.prototype.compare=function(t,e){return this.collator.compare(t,e)},se.prototype.resolvedLocale=function(){return new Intl.Collator(this.locale?this.locale:[]).resolvedOptions().locale};var le=function(t,e,r,n,i){this.text=t,this.image=e,this.scale=r,this.fontStack=n,this.textColor=i},ue=function(t){this.sections=t};ue.fromString=function(t){return new ue([new le(t,null,null,null,null)])},ue.prototype.isEmpty=function(){return 0===this.sections.length||!this.sections.some((function(t){return 0!==t.text.length||t.image&&0!==t.image.name.length}))},ue.factory=function(t){return t instanceof ue?t:ue.fromString(t)},ue.prototype.toString=function(){return 0===this.sections.length?\"\":this.sections.map((function(t){return t.text})).join(\"\")},ue.prototype.serialize=function(){for(var t=[\"format\"],e=0,r=this.sections;e<r.length;e+=1){var n=r[e];if(n.image)t.push([\"image\",n.image.name]);else{t.push(n.text);var i={};n.fontStack&&(i[\"text-font\"]=[\"literal\",n.fontStack.split(\",\")]),n.scale&&(i[\"font-scale\"]=n.scale),n.textColor&&(i[\"text-color\"]=[\"rgba\"].concat(n.textColor.toArray())),t.push(i)}}return t};var ce=function(t){this.name=t.name,this.available=t.available};function fe(t,e,r,n){return\"number\"==typeof t&&t>=0&&t<=255&&\"number\"==typeof e&&e>=0&&e<=255&&\"number\"==typeof r&&r>=0&&r<=255?void 0===n||\"number\"==typeof n&&n>=0&&n<=1?null:\"Invalid rgba value [\"+[t,e,r,n].join(\", \")+\"]: 'a' must be between 0 and 1.\":\"Invalid rgba value [\"+(\"number\"==typeof n?[t,e,r,n]:[t,e,r]).join(\", \")+\"]: 'r', 'g', and 'b' must be between 0 and 255.\"}function he(t){if(null===t)return!0;if(\"string\"==typeof t)return!0;if(\"boolean\"==typeof t)return!0;if(\"number\"==typeof t)return!0;if(t instanceof oe)return!0;if(t instanceof se)return!0;if(t 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ve=function(t,e){this.type=t,this.value=e};ve.parse=function(t,e){if(2!==t.length)return e.error(\"'literal' expression requires exactly one argument, but found \"+(t.length-1)+\" instead.\");if(!he(t[1]))return e.error(\"invalid value\");var r=t[1],n=pe(r),i=e.expectedType;return\"array\"!==n.kind||0!==n.N||!i||\"array\"!==i.kind||\"number\"==typeof i.N&&0!==i.N||(n=i),new ve(n,r)},ve.prototype.evaluate=function(){return this.value},ve.prototype.eachChild=function(){},ve.prototype.outputDefined=function(){return!0},ve.prototype.serialize=function(){return\"array\"===this.type.kind||\"object\"===this.type.kind?[\"literal\",this.value]:this.value instanceof oe?[\"rgba\"].concat(this.value.toArray()):this.value instanceof ue?this.value.serialize():this.value};var ge=function(t){this.name=\"ExpressionEvaluationError\",this.message=t};ge.prototype.toJSON=function(){return this.message};var ye={string:qt,number:Ht,boolean:Gt,object:Yt},me=function(t,e){this.type=t,this.args=e};me.parse=function(t,e){if(t.length<2)return e.error(\"Expected at least one argument.\");var r,n=1,i=t[0];if(\"array\"===i){var a,o;if(t.length>2){var s=t[1];if(\"string\"!=typeof s||!(s in ye)||\"object\"===s)return e.error('The item type argument of \"array\" must be one of string, number, boolean',1);a=ye[s],n++}else a=Wt;if(t.length>3){if(null!==t[2]&&(\"number\"!=typeof t[2]||t[2]<0||t[2]!==Math.floor(t[2])))return e.error('The length argument to \"array\" must be a positive integer literal',2);o=t[2],n++}r=$t(a,o)}else r=ye[i];for(var l=[];n<t.length;n++){var u=e.parse(t[n],n,Wt);if(!u)return null;l.push(u)}return new me(r,l)},me.prototype.evaluate=function(t){for(var e=0;e<this.args.length;e++){var r=this.args[e].evaluate(t);if(!ee(this.type,pe(r)))return r;if(e===this.args.length-1)throw new ge(\"Expected value to be of type \"+Qt(this.type)+\", but found \"+Qt(pe(r))+\" instead.\")}return null},me.prototype.eachChild=function(t){this.args.forEach(t)},me.prototype.outputDefined=function(){return this.args.every((function(t){return t.outputDefined()}))},me.prototype.serialize=function(){var t=this.type,e=[t.kind];if(\"array\"===t.kind){var r=t.itemType;if(\"string\"===r.kind||\"number\"===r.kind||\"boolean\"===r.kind){e.push(r.kind);var n=t.N;(\"number\"==typeof n||this.args.length>1)&&e.push(n)}}return e.concat(this.args.map((function(t){return t.serialize()})))};var xe=function(t){this.type=Jt,this.sections=t};xe.parse=function(t,e){if(t.length<2)return e.error(\"Expected at least one argument.\");var r=t[1];if(!Array.isArray(r)&&\"object\"==typeof r)return e.error(\"First argument must be an image or text section.\");for(var n=[],i=!1,a=1;a<=t.length-1;++a){var o=t[a];if(i&&\"object\"==typeof o&&!Array.isArray(o)){i=!1;var s=null;if(o[\"font-scale\"]&&!(s=e.parse(o[\"font-scale\"],1,Ht)))return null;var l=null;if(o[\"text-font\"]&&!(l=e.parse(o[\"text-font\"],1,$t(qt))))return null;var u=null;if(o[\"text-color\"]&&!(u=e.parse(o[\"text-color\"],1,Zt)))return null;var c=n[n.length-1];c.scale=s,c.font=l,c.textColor=u}else{var f=e.parse(t[a],1,Wt);if(!f)return null;var h=f.type.kind;if(\"string\"!==h&&\"value\"!==h&&\"null\"!==h&&\"resolvedImage\"!==h)return e.error(\"Formatted text type must be 'string', 'value', 'image' or 'null'.\");i=!0,n.push({content:f,scale:null,font:null,textColor:null})}}return new xe(n)},xe.prototype.evaluate=function(t){return new ue(this.sections.map((function(e){var r=e.content.evaluate(t);return pe(r)===Kt?new le(\"\",r,null,null,null):new le(de(r),null,e.scale?e.scale.evaluate(t):null,e.font?e.font.evaluate(t).join(\",\"):null,e.textColor?e.textColor.evaluate(t):null)})))},xe.prototype.eachChild=function(t){for(var e=0,r=this.sections;e<r.length;e+=1){var n=r[e];t(n.content),n.scale&&t(n.scale),n.font&&t(n.font),n.textColor&&t(n.textColor)}},xe.prototype.outputDefined=function(){return!1},xe.prototype.serialize=function(){for(var t=[\"format\"],e=0,r=this.sections;e<r.length;e+=1){var n=r[e];t.push(n.content.serialize());var i={};n.scale&&(i[\"font-scale\"]=n.scale.serialize()),n.font&&(i[\"text-font\"]=n.font.serialize()),n.textColor&&(i[\"text-color\"]=n.textColor.serialize()),t.push(i)}return t};var be=function(t){this.type=Kt,this.input=t};be.parse=function(t,e){if(2!==t.length)return e.error(\"Expected two arguments.\");var r=e.parse(t[1],1,qt);return r?new be(r):e.error(\"No image name provided.\")},be.prototype.evaluate=function(t){var e=this.input.evaluate(t),r=ce.fromString(e);return r&&t.availableImages&&(r.available=t.availableImages.indexOf(e)>-1),r},be.prototype.eachChild=function(t){t(this.input)},be.prototype.outputDefined=function(){return!1},be.prototype.serialize=function(){return[\"image\",this.input.serialize()]};var 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a=Je(e,n),o=e[a],s=e[a+1],l=xr.interpolationFactor(this.interpolation,n,o,s),u=r[a].evaluate(t),c=r[a+1].evaluate(t);return\"interpolate\"===this.operator?Qe[this.type.kind.toLowerCase()](u,c,l):\"interpolate-hcl\"===this.operator?yr.reverse(yr.interpolate(yr.forward(u),yr.forward(c),l)):gr.reverse(gr.interpolate(gr.forward(u),gr.forward(c),l))},xr.prototype.eachChild=function(t){t(this.input);for(var e=0,r=this.outputs;e<r.length;e+=1)t(r[e])},xr.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))},xr.prototype.serialize=function(){var t;t=\"linear\"===this.interpolation.name?[\"linear\"]:\"exponential\"===this.interpolation.name?1===this.interpolation.base?[\"linear\"]:[\"exponential\",this.interpolation.base]:[\"cubic-bezier\"].concat(this.interpolation.controlPoints);for(var e=[this.operator,t,this.input.serialize()],r=0;r<this.labels.length;r++)e.push(this.labels[r],this.outputs[r].serialize());return e};var _r=function(t,e){this.type=t,this.args=e};_r.parse=function(t,e){if(t.length<2)return e.error(\"Expectected at least one argument.\");var r=null,n=e.expectedType;n&&\"value\"!==n.kind&&(r=n);for(var i=[],a=0,o=t.slice(1);a<o.length;a+=1){var s=o[a],l=e.parse(s,1+i.length,r,void 0,{typeAnnotation:\"omit\"});if(!l)return null;r=r||l.type,i.push(l)}var u=n&&i.some((function(t){return ee(n,t.type)}));return new _r(u?Wt:r,i)},_r.prototype.evaluate=function(t){for(var e,r=null,n=0,i=0,a=this.args;i<a.length&&(n++,(r=a[i].evaluate(t))&&r instanceof ce&&!r.available&&(e||(e=r.name),r=null,n===this.args.length&&(r=e)),null===r);i+=1);return r},_r.prototype.eachChild=function(t){this.args.forEach(t)},_r.prototype.outputDefined=function(){return this.args.every((function(t){return t.outputDefined()}))},_r.prototype.serialize=function(){var t=[\"coalesce\"];return this.eachChild((function(e){t.push(e.serialize())})),t};var wr=function(t,e){this.type=e.type,this.bindings=[].concat(t),this.result=e};wr.prototype.evaluate=function(t){return this.result.evaluate(t)},wr.prototype.eachChild=function(t){for(var e=0,r=this.bindings;e<r.length;e+=1)t(r[e][1]);t(this.result)},wr.parse=function(t,e){if(t.length<4)return e.error(\"Expected at least 3 arguments, but found \"+(t.length-1)+\" instead.\");for(var r=[],n=1;n<t.length-1;n+=2){var i=t[n];if(\"string\"!=typeof i)return e.error(\"Expected string, but found \"+typeof i+\" instead.\",n);if(/[^a-zA-Z0-9_]/.test(i))return e.error(\"Variable names must contain only alphanumeric characters or '_'.\",n);var a=e.parse(t[n+1],n+1);if(!a)return null;r.push([i,a])}var o=e.parse(t[t.length-1],t.length-1,e.expectedType,r);return o?new wr(r,o):null},wr.prototype.outputDefined=function(){return this.result.outputDefined()},wr.prototype.serialize=function(){for(var t=[\"let\"],e=0,r=this.bindings;e<r.length;e+=1){var n=r[e],i=n[0],a=n[1];t.push(i,a.serialize())}return 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kr=function(t,e){this.type=Gt,this.needle=t,this.haystack=e};kr.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,Wt),n=e.parse(t[2],2,Wt);return r&&n?re(r.type,[Gt,qt,Ht,Vt,Wt])?new kr(r,n):e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+Qt(r.type)+\" instead\"):null},kr.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!r)return!1;if(!ne(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new ge(\"Expected first argument to be of type boolean, string, number or null, but found \"+Qt(pe(e))+\" instead.\");if(!ne(r,[\"string\",\"array\"]))throw new ge(\"Expected second argument to be of type array or string, but found \"+Qt(pe(r))+\" instead.\");return r.indexOf(e)>=0},kr.prototype.eachChild=function(t){t(this.needle),t(this.haystack)},kr.prototype.outputDefined=function(){return!0},kr.prototype.serialize=function(){return[\"in\",this.needle.serialize(),this.haystack.serialize()]};var Ar=function(t,e,r){this.type=Ht,this.needle=t,this.haystack=e,this.fromIndex=r};Ar.parse=function(t,e){if(t.length<=2||t.length>=5)return e.error(\"Expected 3 or 4 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,Wt),n=e.parse(t[2],2,Wt);if(!r||!n)return null;if(!re(r.type,[Gt,qt,Ht,Vt,Wt]))return e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+Qt(r.type)+\" instead\");if(4===t.length){var i=e.parse(t[3],3,Ht);return i?new Ar(r,n,i):null}return new Ar(r,n)},Ar.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!ne(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new ge(\"Expected first argument to be of type boolean, string, number or 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Er(r.type,r,n)},Er.prototype.evaluate=function(t){var e=this.input.evaluate(t),r=this.beginIndex.evaluate(t);if(!ne(e,[\"string\",\"array\"]))throw new ge(\"Expected first argument to be of type array or string, but found \"+Qt(pe(e))+\" instead.\");if(this.endIndex){var n=this.endIndex.evaluate(t);return e.slice(r,n)}return e.slice(r)},Er.prototype.eachChild=function(t){t(this.input),t(this.beginIndex),this.endIndex&&t(this.endIndex)},Er.prototype.outputDefined=function(){return!1},Er.prototype.serialize=function(){if(null!=this.endIndex&&void 0!==this.endIndex){var t=this.endIndex.serialize();return[\"slice\",this.input.serialize(),this.beginIndex.serialize(),t]}return[\"slice\",this.input.serialize(),this.beginIndex.serialize()]};var Or=Pr(\"==\",(function(t,e,r){return e===r}),Cr),Ir=Pr(\"!=\",(function(t,e,r){return e!==r}),(function(t,e,r,n){return!Cr(0,e,r,n)})),Dr=Pr(\"<\",(function(t,e,r){return e<r}),(function(t,e,r,n){return 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e=[],a=t.value,s=t.key;if(\"array\"!==Jr(a))return[new zt(s,a,\"array expected, \"+Jr(a)+\" found\")];if(2!==a.length)return[new zt(s,a,\"array length 2 expected, length \"+a.length+\" found\")];if(u){if(\"object\"!==Jr(a[0]))return[new zt(s,a,\"object expected, \"+Jr(a[0])+\" found\")];if(void 0===a[0].zoom)return[new zt(s,a,\"object stop key must have zoom\")];if(void 0===a[0].value)return[new zt(s,a,\"object stop key must have value\")];if(n&&n>Bt(a[0].zoom))return[new zt(s,a[0].zoom,\"stop zoom values must appear in ascending order\")];Bt(a[0].zoom)!==n&&(n=Bt(a[0].zoom),r=void 0,o={}),e=e.concat(dn({key:s+\"[0]\",value:a[0],valueSpec:{zoom:{}},style:t.style,styleSpec:t.styleSpec,objectElementValidators:{zoom:gn,value:h}}))}else e=e.concat(h({key:s+\"[0]\",value:a[0],valueSpec:{},style:t.style,styleSpec:t.styleSpec},a));return sn(Nt(a[1]))?e.concat([new zt(s+\"[1]\",a[1],\"expressions are not allowed in function 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t.length<=1?\"any\"!==r:\"==\"===r?Mn(t[1],t[2],\"==\"):\"!=\"===r?Ln(Mn(t[1],t[2],\"==\")):\"<\"===r||\">\"===r||\"<=\"===r||\">=\"===r?Mn(t[1],t[2],r):\"any\"===r?(e=t.slice(1),[\"any\"].concat(e.map(An))):\"all\"===r?[\"all\"].concat(t.slice(1).map(An)):\"none\"===r?[\"all\"].concat(t.slice(1).map(An).map(Ln)):\"in\"===r?Sn(t[1],t.slice(2)):\"!in\"===r?Ln(Sn(t[1],t.slice(2))):\"has\"===r?En(t[1]):\"!has\"===r?Ln(En(t[1])):\"within\"!==r||t}function Mn(t,e,r){switch(t){case\"$type\":return[\"filter-type-\"+r,e];case\"$id\":return[\"filter-id-\"+r,e];default:return[\"filter-\"+r,t,e]}}function Sn(t,e){if(0===e.length)return!1;switch(t){case\"$type\":return[\"filter-type-in\",[\"literal\",e]];case\"$id\":return[\"filter-id-in\",[\"literal\",e]];default:return e.length>200&&!e.some((function(t){return typeof t!=typeof e[0]}))?[\"filter-in-large\",t,[\"literal\",e.sort(Tn)]]:[\"filter-in-small\",t,[\"literal\",e]]}}function 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r=t.key,n=t.style,i=t.styleSpec,a=t.value,o=t.objectKey,s=i[e+\"_\"+t.layerType];if(!s)return[];var l=o.match(/^(.*)-transition$/);if(\"paint\"===e&&l&&s[l[1]]&&s[l[1]].transition)return Un({key:r,value:a,valueSpec:i.transition,style:n,styleSpec:i});var u,c=t.valueSpec||s[o];if(!c)return[new zt(r,a,'unknown property \"'+o+'\"')];if(\"string\"===Jr(a)&&Yr(c)&&!c.tokens&&(u=/^{([^}]+)}$/.exec(a)))return[new zt(r,a,'\"'+o+'\" does not support interpolation syntax\\nUse an identity property function instead: `{ \"type\": \"identity\", \"property\": '+JSON.stringify(u[1])+\" }`.\")];var f=[];return\"symbol\"===t.layerType&&(\"text-field\"===o&&n&&!n.glyphs&&f.push(new zt(r,a,'use of \"text-field\" requires a style \"glyphs\" property')),\"text-font\"===o&&Kr(Nt(a))&&\"identity\"===Bt(a.type)&&f.push(new zt(r,a,'\"text-font\" does not support identity 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h=i.sources&&i.sources[r.source],p=h&&Bt(h.type);h?\"vector\"===p&&\"raster\"===s?e.push(new zt(n,r.source,'layer \"'+r.id+'\" requires a raster source')):\"raster\"===p&&\"raster\"!==s?e.push(new zt(n,r.source,'layer \"'+r.id+'\" requires a vector source')):\"vector\"!==p||r[\"source-layer\"]?\"raster-dem\"===p&&\"hillshade\"!==s?e.push(new zt(n,r.source,\"raster-dem source can only be used with layer type 'hillshade'.\")):\"line\"!==s||!r.paint||!r.paint[\"line-gradient\"]||\"geojson\"===p&&h.lineMetrics||e.push(new zt(n,r,'layer \"'+r.id+'\" specifies a line-gradient, which requires a GeoJSON source with `lineMetrics` enabled.')):e.push(new zt(n,r,'layer \"'+r.id+'\" must specify a \"source-layer\"')):e.push(new zt(n,r.source,'source \"'+r.source+'\" not found'))}else e.push(new zt(n,r,'missing required property \"source\"'));return e=e.concat(dn({key:n,value:r,valueSpec:a.layer,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{\"*\":function(){return[]},type:function(){return Un({key:n+\".type\",value:r.type,valueSpec:a.layer.type,style:t.style,styleSpec:t.styleSpec,object:r,objectKey:\"type\"})},filter:Cn,layout:function(t){return dn({layer:r,key:t.key,value:t.value,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{\"*\":function(t){return Dn(Ft({layerType:s},t))}}})},paint:function(t){return dn({layer:r,key:t.key,value:t.value,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{\"*\":function(t){return In(Ft({layerType:s},t))}}})}}})),e}function Rn(t){var e=t.value,r=t.key,n=Jr(e);return\"string\"!==n?[new zt(r,e,\"string expected, \"+n+\" found\")]:[]}var Fn={promoteId:function(t){var e=t.key,r=t.value;if(\"string\"===Jr(r))return Rn({key:e,value:r});var n=[];for(var i in r)n.push.apply(n,Rn({key:e+\".\"+i,value:r[i]}));return n}};function Bn(t){var e=t.value,r=t.key,n=t.styleSpec,i=t.style;if(!e.type)return[new zt(r,e,'\"type\" is required')];var a,o=Bt(e.type);switch(o){case\"vector\":case\"raster\":case\"raster-dem\":return dn({key:r,value:e,valueSpec:n[\"source_\"+o.replace(\"-\",\"_\")],style:t.style,styleSpec:n,objectElementValidators:Fn});case\"geojson\":if(a=dn({key:r,value:e,valueSpec:n.source_geojson,style:i,styleSpec:n,objectElementValidators:Fn}),e.cluster)for(var s in e.clusterProperties){var l=e.clusterProperties[s],u=l[0],c=l[1],f=\"string\"==typeof u?[u,[\"accumulated\"],[\"get\",s]]:u;a.push.apply(a,mn({key:r+\".\"+s+\".map\",value:c,expressionContext:\"cluster-map\"})),a.push.apply(a,mn({key:r+\".\"+s+\".reduce\",value:f,expressionContext:\"cluster-reduce\"}))}return a;case\"video\":return dn({key:r,value:e,valueSpec:n.source_video,style:i,styleSpec:n});case\"image\":return dn({key:r,value:e,valueSpec:n.source_image,style:i,styleSpec:n});case\"canvas\":return[new zt(r,null,\"Please use runtime APIs to add canvas sources, rather than including them in stylesheets.\",\"source.canvas\")];default:return xn({key:r+\".type\",value:e.type,valueSpec:{values:[\"vector\",\"raster\",\"raster-dem\",\"geojson\",\"video\",\"image\"]},style:i,styleSpec:n})}}function Nn(t){var e=t.value,r=t.styleSpec,n=r.light,i=t.style,a=[],o=Jr(e);if(void 0===e)return a;if(\"object\"!==o)return a.concat([new zt(\"light\",e,\"object expected, \"+o+\" found\")]);for(var s in e){var l=s.match(/^(.*)-transition$/);a=l&&n[l[1]]&&n[l[1]].transition?a.concat(Un({key:s,value:e[s],valueSpec:r.transition,style:i,styleSpec:r})):n[s]?a.concat(Un({key:s,value:e[s],valueSpec:n[s],style:i,styleSpec:r})):a.concat([new zt(s,e[s],'unknown property \"'+s+'\"')])}return a}var jn={\"*\":function(){return[]},array:vn,boolean:function(t){var e=t.value,r=t.key,n=Jr(e);return\"boolean\"!==n?[new zt(r,e,\"boolean expected, \"+n+\" found\")]:[]},number:gn,color:function(t){var e=t.key,r=t.value,n=Jr(r);return\"string\"!==n?[new zt(e,r,\"color 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o=i[$n+a],s=i[$n+a+1];n.push(o===s?null:i.subarray(o,s))}var l=i[$n+n.length],u=i[$n+n.length+1];this.keys=i.subarray(l,u),this.bboxes=i.subarray(u),this.insert=this._insertReadonly}else{this.d=e+2*r;for(var c=0;c<this.d*this.d;c++)n.push([]);this.keys=[],this.bboxes=[]}this.n=e,this.extent=t,this.padding=r,this.scale=e/t,this.uid=0;var f=r/e*t;this.min=-f,this.max=t+f}Qn.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertCell,this.uid++),this.keys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},Qn.prototype._insertReadonly=function(){throw\"Cannot insert into a GridIndex created from an ArrayBuffer.\"},Qn.prototype._insertCell=function(t,e,r,n,i,a){this.cells[i].push(a)},Qn.prototype.query=function(t,e,r,n,i){var a=this.min,o=this.max;if(t<=a&&e<=a&&o<=r&&o<=n&&!i)return Array.prototype.slice.call(this.keys);var s=[];return this._forEachCell(t,e,r,n,this._queryCell,s,{},i),s},Qn.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=this.cells[i];if(null!==l)for(var u=this.keys,c=this.bboxes,f=0;f<l.length;f++){var h=l[f];if(void 0===o[h]){var p=4*h;(s?s(c[p+0],c[p+1],c[p+2],c[p+3]):t<=c[p+2]&&e<=c[p+3]&&r>=c[p+0]&&n>=c[p+1])?(o[h]=!0,a.push(u[h])):o[h]=!1}}},Qn.prototype._forEachCell=function(t,e,r,n,i,a,o,s){for(var l=this._convertToCellCoord(t),u=this._convertToCellCoord(e),c=this._convertToCellCoord(r),f=this._convertToCellCoord(n),h=l;h<=c;h++)for(var p=u;p<=f;p++){var d=this.d*p+h;if((!s||s(this._convertFromCellCoord(h),this._convertFromCellCoord(p),this._convertFromCellCoord(h+1),this._convertFromCellCoord(p+1)))&&i.call(this,t,e,r,n,d,a,o,s))return}},Qn.prototype._convertFromCellCoord=function(t){return(t-this.padding)/this.scale},Qn.prototype._convertToCellCoord=function(t){return Math.max(0,Math.min(this.d-1,Math.floor(t*this.scale)+this.padding))},Qn.prototype.toArrayBuffer=function(){if(this.arrayBuffer)return this.arrayBuffer;for(var t=this.cells,e=$n+this.cells.length+1+1,r=0,n=0;n<this.cells.length;n++)r+=this.cells[n].length;var i=new Int32Array(e+r+this.keys.length+this.bboxes.length);i[0]=this.extent,i[1]=this.n,i[2]=this.padding;for(var a=e,o=0;o<t.length;o++){var s=t[o];i[$n+o]=a,i.set(s,a),a+=s.length}return i[$n+t.length]=a,i.set(this.keys,a),a+=this.keys.length,i[$n+t.length+1]=a,i.set(this.bboxes,a),a+=this.bboxes.length,i.buffer};var ti=self.ImageData,ei=self.ImageBitmap,ri={};function ni(t,e,r){void 0===r&&(r={}),Object.defineProperty(e,\"_classRegistryKey\",{value:t,writeable:!1}),ri[t]={klass:e,omit:r.omit||[],shallow:r.shallow||[]}}for(var ii in ni(\"Object\",Object),Kn.serialize=function(t,e){var r=t.toArrayBuffer();return e&&e.push(r),{buffer:r}},Kn.deserialize=function(t){return new Kn(t.buffer)},ni(\"Grid\",Kn),ni(\"Color\",oe),ni(\"Error\",Error),ni(\"ResolvedImage\",ce),ni(\"StylePropertyFunction\",hn),ni(\"StyleExpression\",on,{omit:[\"_evaluator\"]}),ni(\"ZoomDependentExpression\",cn),ni(\"ZoomConstantExpression\",un),ni(\"CompoundExpression\",Ae,{omit:[\"_evaluate\"]}),jr)jr[ii]._classRegistryKey||ni(\"Expression_\"+ii,jr[ii]);function ai(t){return t&&\"undefined\"!=typeof ArrayBuffer&&(t instanceof ArrayBuffer||t.constructor&&\"ArrayBuffer\"===t.constructor.name)}function oi(t){return ei&&t instanceof ei}function si(t,e){if(null==t||\"boolean\"==typeof t||\"number\"==typeof t||\"string\"==typeof t||t instanceof Boolean||t instanceof Number||t instanceof String||t instanceof Date||t instanceof RegExp)return t;if(ai(t)||oi(t))return e&&e.push(t),t;if(ArrayBuffer.isView(t)){var r=t;return e&&e.push(r.buffer),r}if(t instanceof ti)return e&&e.push(t.data.buffer),t;if(Array.isArray(t)){for(var n=[],i=0,a=t;i<a.length;i+=1){var o=a[i];n.push(si(o,e))}return n}if(\"object\"==typeof t){var s=t.constructor,l=s._classRegistryKey;if(!l)throw new Error(\"can't serialize object of unregistered class\");var u=s.serialize?s.serialize(t,e):{};if(!s.serialize){for(var c in t)if(t.hasOwnProperty(c)&&!(ri[l].omit.indexOf(c)>=0)){var f=t[c];u[c]=ri[l].shallow.indexOf(c)>=0?f:si(f,e)}t instanceof Error&&(u.message=t.message)}if(u.$name)throw new Error(\"$name property is reserved for worker serialization logic.\");return\"Object\"!==l&&(u.$name=l),u}throw new Error(\"can't serialize object of type \"+typeof t)}function li(t){if(null==t||\"boolean\"==typeof t||\"number\"==typeof t||\"string\"==typeof t||t instanceof Boolean||t instanceof Number||t instanceof String||t instanceof Date||t instanceof RegExp||ai(t)||oi(t)||ArrayBuffer.isView(t)||t instanceof ti)return t;if(Array.isArray(t))return t.map(li);if(\"object\"==typeof t){var e=t.$name||\"Object\",r=ri[e].klass;if(!r)throw new Error(\"can't deserialize unregistered class 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Aboriginal Syllabics\":function(t){return t>=5120&&t<=5759},Khmer:function(t){return t>=6016&&t<=6143},\"Unified Canadian Aboriginal Syllabics Extended\":function(t){return t>=6320&&t<=6399},\"General Punctuation\":function(t){return t>=8192&&t<=8303},\"Letterlike Symbols\":function(t){return t>=8448&&t<=8527},\"Number Forms\":function(t){return t>=8528&&t<=8591},\"Miscellaneous Technical\":function(t){return t>=8960&&t<=9215},\"Control Pictures\":function(t){return t>=9216&&t<=9279},\"Optical Character Recognition\":function(t){return t>=9280&&t<=9311},\"Enclosed Alphanumerics\":function(t){return t>=9312&&t<=9471},\"Geometric Shapes\":function(t){return t>=9632&&t<=9727},\"Miscellaneous Symbols\":function(t){return t>=9728&&t<=9983},\"Miscellaneous Symbols and Arrows\":function(t){return t>=11008&&t<=11263},\"CJK Radicals Supplement\":function(t){return t>=11904&&t<=12031},\"Kangxi Radicals\":function(t){return t>=12032&&t<=12255},\"Ideographic Description 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t&&t.indexOf(\"NetworkError\")>-1&&(Ti=_i),wi&&wi(t)};function Mi(){Si.fire(new Pt(\"pluginStateChange\",{pluginStatus:Ti,pluginURL:ki}))}var Si=new It,Ei=function(){return Ti},Li=function(){if(Ti!==mi||!ki)throw new Error(\"rtl-text-plugin cannot be downloaded unless a pluginURL is specified\");Ti=xi,Mi(),ki&&kt({url:ki},(function(t){t?Ai(t):(Ti=bi,Mi())}))},Ci={applyArabicShaping:null,processBidirectionalText:null,processStyledBidirectionalText:null,isLoaded:function(){return Ti===bi||null!=Ci.applyArabicShaping},isLoading:function(){return Ti===xi},setState:function(t){Ti=t.pluginStatus,ki=t.pluginURL},isParsed:function(){return null!=Ci.applyArabicShaping&&null!=Ci.processBidirectionalText&&null!=Ci.processStyledBidirectionalText},getPluginURL:function(){return ki}},Pi=function(t,e){this.zoom=t,e?(this.now=e.now,this.fadeDuration=e.fadeDuration,this.zoomHistory=e.zoomHistory,this.transition=e.transition):(this.now=0,this.fadeDuration=0,this.zoomHistory=new 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b(this._values[t].transition)},Di.prototype.setTransition=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new Ii(this._values[t].property)),this._values[t].transition=b(e)||void 0},Di.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i);var a=this.getTransition(n);void 0!==a&&(t[n+\"-transition\"]=a)}return t},Di.prototype.transitioned=function(t,e){for(var r=new Ri(this._properties),n=0,i=Object.keys(this._values);n<i.length;n+=1){var a=i[n];r._values[a]=this._values[a].transitioned(t,e._values[a])}return r},Di.prototype.untransitioned=function(){for(var t=new Ri(this._properties),e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e];t._values[n]=this._values[n].untransitioned()}return t};var zi=function(t,e,r,n,i){this.property=t,this.value=e,this.begin=i+n.delay||0,this.end=this.begin+n.duration||0,t.specification.transition&&(n.delay||n.duration)&&(this.prior=r)};zi.prototype.possiblyEvaluate=function(t,e,r){var n=t.now||0,i=this.value.possiblyEvaluate(t,e,r),a=this.prior;if(a){if(n>this.end)return this.prior=null,i;if(this.value.isDataDriven())return this.prior=null,i;if(n<this.begin)return a.possiblyEvaluate(t,e,r);var o=(n-this.begin)/(this.end-this.begin);return this.property.interpolate(a.possiblyEvaluate(t,e,r),i,function(t){if(t<=0)return 0;if(t>=1)return 1;var e=t*t,r=e*t;return 4*(t<.5?r:3*(t-e)+r-.75)}(o))}return i};var Ri=function(t){this._properties=t,this._values=Object.create(t.defaultTransitioningPropertyValues)};Ri.prototype.possiblyEvaluate=function(t,e,r){for(var n=new Ni(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n},Ri.prototype.hasTransition=function(){for(var t=0,e=Object.keys(this._values);t<e.length;t+=1){var r=e[t];if(this._values[r].prior)return!0}return!1};var Fi=function(t){this._properties=t,this._values=Object.create(t.defaultPropertyValues)};Fi.prototype.getValue=function(t){return b(this._values[t].value)},Fi.prototype.setValue=function(t,e){this._values[t]=new Oi(this._values[t].property,null===e?void 0:b(e))},Fi.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i)}return t},Fi.prototype.possiblyEvaluate=function(t,e,r){for(var n=new Ni(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n};var Bi=function(t,e,r){this.property=t,this.value=e,this.parameters=r};Bi.prototype.isConstant=function(){return\"constant\"===this.value.kind},Bi.prototype.constantOr=function(t){return\"constant\"===this.value.kind?this.value.value:t},Bi.prototype.evaluate=function(t,e,r,n){return this.property.evaluate(this.value,this.parameters,t,e,r,n)};var Ni=function(t){this._properties=t,this._values=Object.create(t.defaultPossiblyEvaluatedValues)};Ni.prototype.get=function(t){return this._values[t]};var ji=function(t){this.specification=t};ji.prototype.possiblyEvaluate=function(t,e){return t.expression.evaluate(e)},ji.prototype.interpolate=function(t,e,r){var n=Qe[this.specification.type];return n?n(t,e,r):t};var Ui=function(t,e){this.specification=t,this.overrides=e};Ui.prototype.possiblyEvaluate=function(t,e,r,n){return\"constant\"===t.expression.kind||\"camera\"===t.expression.kind?new Bi(this,{kind:\"constant\",value:t.expression.evaluate(e,null,{},r,n)},e):new Bi(this,t.expression,e)},Ui.prototype.interpolate=function(t,e,r){if(\"constant\"!==t.value.kind||\"constant\"!==e.value.kind)return t;if(void 0===t.value.value||void 0===e.value.value)return new Bi(this,{kind:\"constant\",value:void 0},t.parameters);var n=Qe[this.specification.type];return n?new Bi(this,{kind:\"constant\",value:n(t.value.value,e.value.value,r)},t.parameters):t},Ui.prototype.evaluate=function(t,e,r,n,i,a){return\"constant\"===t.kind?t.value:t.evaluate(e,r,n,i,a)};var Vi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0===t.value)return new Bi(this,{kind:\"constant\",value:void 0},e);if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n),a=\"resolvedImage\"===t.property.specification.type&&\"string\"!=typeof i?i.name:i,o=this._calculate(a,a,a,e);return new Bi(this,{kind:\"constant\",value:o},e)}if(\"camera\"===t.expression.kind){var s=this._calculate(t.expression.evaluate({zoom:e.zoom-1}),t.expression.evaluate({zoom:e.zoom}),t.expression.evaluate({zoom:e.zoom+1}),e);return new Bi(this,{kind:\"constant\",value:s},e)}return new Bi(this,t.expression,e)},e.prototype.evaluate=function(t,e,r,n,i,a){if(\"source\"===t.kind){var o=t.evaluate(e,r,n,i,a);return this._calculate(o,o,o,e)}return\"composite\"===t.kind?this._calculate(t.evaluate({zoom:Math.floor(e.zoom)-1},r,n),t.evaluate({zoom:Math.floor(e.zoom)},r,n),t.evaluate({zoom:Math.floor(e.zoom)+1},r,n),e):t.value},e.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},e.prototype.interpolate=function(t){return t},e}(Ui),Hi=function(t){this.specification=t};Hi.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0!==t.value){if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n);return this._calculate(i,i,i,e)}return this._calculate(t.expression.evaluate(new Pi(Math.floor(e.zoom-1),e)),t.expression.evaluate(new Pi(Math.floor(e.zoom),e)),t.expression.evaluate(new Pi(Math.floor(e.zoom+1),e)),e)}},Hi.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},Hi.prototype.interpolate=function(t){return t};var qi=function(t){this.specification=t};qi.prototype.possiblyEvaluate=function(t,e,r,n){return!!t.expression.evaluate(e,null,{},r,n)},qi.prototype.interpolate=function(){return!1};var Gi=function(t){for(var e in this.properties=t,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},this.overridableProperties=[],t){var r=t[e];r.specification.overridable&&this.overridableProperties.push(e);var n=this.defaultPropertyValues[e]=new Oi(r,void 0),i=this.defaultTransitionablePropertyValues[e]=new Ii(r);this.defaultTransitioningPropertyValues[e]=i.untransitioned(),this.defaultPossiblyEvaluatedValues[e]=n.possiblyEvaluate({})}};ni(\"DataDrivenProperty\",Ui),ni(\"DataConstantProperty\",ji),ni(\"CrossFadedDataDrivenProperty\",Vi),ni(\"CrossFadedProperty\",Hi),ni(\"ColorRampProperty\",qi);var Zi=\"-transition\",Yi=function(t){function e(e,r){if(t.call(this),this.id=e.id,this.type=e.type,this._featureFilter={filter:function(){return!0},needGeometry:!1},\"custom\"!==e.type&&(this.metadata=e.metadata,this.minzoom=e.minzoom,this.maxzoom=e.maxzoom,\"background\"!==e.type&&(this.source=e.source,this.sourceLayer=e[\"source-layer\"],this.filter=e.filter),r.layout&&(this._unevaluatedLayout=new Fi(r.layout)),r.paint)){for(var n in this._transitionablePaint=new Di(r.paint),e.paint)this.setPaintProperty(n,e.paint[n],{validate:!1});for(var i in e.layout)this.setLayoutProperty(i,e.layout[i],{validate:!1});this._transitioningPaint=this._transitionablePaint.untransitioned(),this.paint=new Ni(r.paint)}}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getCrossfadeParameters=function(){return this._crossfadeParameters},e.prototype.getLayoutProperty=function(t){return\"visibility\"===t?this.visibility:this._unevaluatedLayout.getValue(t)},e.prototype.setLayoutProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".layout.\"+t;if(this._validate(Xn,n,t,e,r))return}\"visibility\"!==t?this._unevaluatedLayout.setValue(t,e):this.visibility=e},e.prototype.getPaintProperty=function(t){return y(t,Zi)?this._transitionablePaint.getTransition(t.slice(0,-11)):this._transitionablePaint.getValue(t)},e.prototype.setPaintProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".paint.\"+t;if(this._validate(Wn,n,t,e,r))return!1}if(y(t,Zi))return this._transitionablePaint.setTransition(t.slice(0,-11),e||void 0),!1;var i=this._transitionablePaint._values[t],a=\"cross-faded-data-driven\"===i.property.specification[\"property-type\"],o=i.value.isDataDriven(),s=i.value;this._transitionablePaint.setValue(t,e),this._handleSpecialPaintPropertyUpdate(t);var l=this._transitionablePaint._values[t].value;return l.isDataDriven()||o||a||this._handleOverridablePaintPropertyUpdate(t,s,l)},e.prototype._handleSpecialPaintPropertyUpdate=function(t){},e.prototype._handleOverridablePaintPropertyUpdate=function(t,e,r){return!1},e.prototype.isHidden=function(t){return!!(this.minzoom&&t<this.minzoom)||!!(this.maxzoom&&t>=this.maxzoom)||\"none\"===this.visibility},e.prototype.updateTransitions=function(t){this._transitioningPaint=this._transitionablePaint.transitioned(t,this._transitioningPaint)},e.prototype.hasTransition=function(){return this._transitioningPaint.hasTransition()},e.prototype.recalculate=function(t,e){t.getCrossfadeParameters&&(this._crossfadeParameters=t.getCrossfadeParameters()),this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(t,void 0,e)),this.paint=this._transitioningPaint.possiblyEvaluate(t,void 0,e)},e.prototype.serialize=function(){var t={id:this.id,type:this.type,source:this.source,\"source-layer\":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return this.visibility&&(t.layout=t.layout||{},t.layout.visibility=this.visibility),x(t,(function(t,e){return!(void 0===t||\"layout\"===e&&!Object.keys(t).length||\"paint\"===e&&!Object.keys(t).length)}))},e.prototype._validate=function(t,e,r,n,i){return void 0===i&&(i={}),(!i||!1!==i.validate)&&Jn(this,t.call(Zn,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:Dt,style:{glyphs:!0,sprite:!0}}))},e.prototype.is3D=function(){return!1},e.prototype.isTileClipped=function(){return!1},e.prototype.hasOffscreenPass=function(){return!1},e.prototype.resize=function(){},e.prototype.isStateDependent=function(){for(var t in this.paint._values){var e=this.paint.get(t);if(e instanceof Bi&&Yr(e.property.specification)&&(\"source\"===e.value.kind||\"composite\"===e.value.kind)&&e.value.isStateDependent)return!0}return!1},e}(It),Wi={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array},Xi=function(t,e){this._structArray=t,this._pos1=e*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8},Ji=function(){this.isTransferred=!1,this.capacity=-1,this.resize(0)};function Ki(t,e){void 0===e&&(e=1);var r=0,n=0;return{members:t.map((function(t){var i,a=(i=t.type,Wi[i].BYTES_PER_ELEMENT),o=r=$i(r,Math.max(e,a)),s=t.components||1;return n=Math.max(n,a),r+=a*s,{name:t.name,type:t.type,components:s,offset:o}})),size:$i(r,Math.max(n,e)),alignment:e}}function $i(t,e){return Math.ceil(t/e)*e}Ji.serialize=function(t,e){return t._trim(),e&&(t.isTransferred=!0,e.push(t.arrayBuffer)),{length:t.length,arrayBuffer:t.arrayBuffer}},Ji.deserialize=function(t){var e=Object.create(this.prototype);return e.arrayBuffer=t.arrayBuffer,e.length=t.length,e.capacity=t.arrayBuffer.byteLength/e.bytesPerElement,e._refreshViews(),e},Ji.prototype._trim=function(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())},Ji.prototype.clear=function(){this.length=0},Ji.prototype.resize=function(t){this.reserve(t),this.length=t},Ji.prototype.reserve=function(t){if(t>this.capacity){this.capacity=Math.max(t,Math.floor(5*this.capacity),128),this.arrayBuffer=new ArrayBuffer(this.capacity*this.bytesPerElement);var e=this.uint8;this._refreshViews(),e&&this.uint8.set(e)}},Ji.prototype._refreshViews=function(){throw new Error(\"_refreshViews() must be implemented by each concrete StructArray layout\")};var Qi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.int16[n+0]=e,this.int16[n+1]=r,t},e}(Ji);Qi.prototype.bytesPerElement=4,ni(\"StructArrayLayout2i4\",Qi);var ta=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new 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this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Ji);ea.prototype.bytesPerElement=12,ni(\"StructArrayLayout2i4i12\",ea);var ra=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=4*t,l=8*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.uint8[l+4]=n,this.uint8[l+5]=i,this.uint8[l+6]=a,this.uint8[l+7]=o,t},e}(Ji);ra.prototype.bytesPerElement=8,ni(\"StructArrayLayout2i4ub8\",ra);var na=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,u){var c=this.length;return this.resize(c+1),this.emplace(c,t,e,r,n,i,a,o,s,l,u)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,u,c){var f=9*t,h=18*t;return this.uint16[f+0]=e,this.uint16[f+1]=r,this.uint16[f+2]=n,this.uint16[f+3]=i,this.uint16[f+4]=a,this.uint16[f+5]=o,this.uint16[f+6]=s,this.uint16[f+7]=l,this.uint8[h+16]=u,this.uint8[h+17]=c,t},e}(Ji);na.prototype.bytesPerElement=18,ni(\"StructArrayLayout8ui2ub18\",na);var ia=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,u,c,f){var h=this.length;return this.resize(h+1),this.emplace(h,t,e,r,n,i,a,o,s,l,u,c,f)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,u,c,f,h){var p=12*t;return this.int16[p+0]=e,this.int16[p+1]=r,this.int16[p+2]=n,this.int16[p+3]=i,this.uint16[p+4]=a,this.uint16[p+5]=o,this.uint16[p+6]=s,this.uint16[p+7]=l,this.int16[p+8]=u,this.int16[p+9]=c,this.int16[p+10]=f,this.int16[p+11]=h,t},e}(Ji);ia.prototype.bytesPerElement=24,ni(\"StructArrayLayout4i4ui4i24\",ia);var aa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.float32[i+0]=e,this.float32[i+1]=r,this.float32[i+2]=n,t},e}(Ji);aa.prototype.bytesPerElement=12,ni(\"StructArrayLayout3f12\",aa);var oa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.uint32[r+0]=e,t},e}(Ji);oa.prototype.bytesPerElement=4,ni(\"StructArrayLayout1ul4\",oa);var sa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l){var u=this.length;return this.resize(u+1),this.emplace(u,t,e,r,n,i,a,o,s,l)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,u){var c=10*t,f=5*t;return this.int16[c+0]=e,this.int16[c+1]=r,this.int16[c+2]=n,this.int16[c+3]=i,this.int16[c+4]=a,this.int16[c+5]=o,this.uint32[f+3]=s,this.uint16[c+8]=l,this.uint16[c+9]=u,t},e}(Ji);sa.prototype.bytesPerElement=20,ni(\"StructArrayLayout6i1ul2ui20\",sa);var la=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Ji);la.prototype.bytesPerElement=12,ni(\"StructArrayLayout2i2i2i12\",la);var ua=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i){var a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n,i)},e.prototype.emplace=function(t,e,r,n,i,a){var o=4*t,s=8*t;return this.float32[o+0]=e,this.float32[o+1]=r,this.float32[o+2]=n,this.int16[s+6]=i,this.int16[s+7]=a,t},e}(Ji);ua.prototype.bytesPerElement=16,ni(\"StructArrayLayout2f1f2i16\",ua);var ca=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=12*t,o=3*t;return this.uint8[a+0]=e,this.uint8[a+1]=r,this.float32[o+1]=n,this.float32[o+2]=i,t},e}(Ji);ca.prototype.bytesPerElement=12,ni(\"StructArrayLayout2ub2f12\",ca);var fa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return 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this.int16[m+0]=e,this.int16[m+1]=r,this.uint16[m+2]=n,this.uint16[m+3]=i,this.uint32[x+2]=a,this.uint32[x+3]=o,this.uint32[x+4]=s,this.uint16[m+10]=l,this.uint16[m+11]=u,this.uint16[m+12]=c,this.float32[x+7]=f,this.float32[x+8]=h,this.uint8[b+36]=p,this.uint8[b+37]=d,this.uint8[b+38]=v,this.uint32[x+10]=g,this.int16[m+22]=y,t},e}(Ji);ha.prototype.bytesPerElement=48,ni(\"StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48\",ha);var pa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,w,T,k,A,M,S){var E=this.length;return this.resize(E+1),this.emplace(E,t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,w,T,k,A,M,S)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,w,T,k,A,M,S,E){var L=34*t,C=17*t;return this.int16[L+0]=e,this.int16[L+1]=r,this.int16[L+2]=n,this.int16[L+3]=i,this.int16[L+4]=a,this.int16[L+5]=o,this.int16[L+6]=s,this.int16[L+7]=l,this.uint16[L+8]=u,this.uint16[L+9]=c,this.uint16[L+10]=f,this.uint16[L+11]=h,this.uint16[L+12]=p,this.uint16[L+13]=d,this.uint16[L+14]=v,this.uint16[L+15]=g,this.uint16[L+16]=y,this.uint16[L+17]=m,this.uint16[L+18]=x,this.uint16[L+19]=b,this.uint16[L+20]=_,this.uint16[L+21]=w,this.uint16[L+22]=T,this.uint32[C+12]=k,this.float32[C+13]=A,this.float32[C+14]=M,this.float32[C+15]=S,this.float32[C+16]=E,t},e}(Ji);pa.prototype.bytesPerElement=68,ni(\"StructArrayLayout8i15ui1ul4f68\",pa);var da=function(t){function e(){t.apply(this,arguments)}return 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this.float32[a+0]=e,this.float32[a+1]=r,this.float32[a+2]=n,this.float32[a+3]=i,t},e}(Ji);ba.prototype.bytesPerElement=16,ni(\"StructArrayLayout4f16\",ba);var _a=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorPointX:{configurable:!0},anchorPointY:{configurable:!0},x1:{configurable:!0},y1:{configurable:!0},x2:{configurable:!0},y2:{configurable:!0},featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0},anchorPoint:{configurable:!0}};return r.anchorPointX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorPointY.get=function(){return this._structArray.int16[this._pos2+1]},r.x1.get=function(){return this._structArray.int16[this._pos2+2]},r.y1.get=function(){return this._structArray.int16[this._pos2+3]},r.x2.get=function(){return this._structArray.int16[this._pos2+4]},r.y2.get=function(){return 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this._structArray.uint32[this._pos4+10]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+10]=t},r.associatedIconIndex.get=function(){return this._structArray.int16[this._pos2+22]},Object.defineProperties(e.prototype,r),e}(Xi);Ta.prototype.size=48;var ka=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new Ta(this,t)},e}(ha);ni(\"PlacedSymbolArray\",ka);var Aa=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},rightJustifiedTextSymbolIndex:{configurable:!0},centerJustifiedTextSymbolIndex:{configurable:!0},leftJustifiedTextSymbolIndex:{configurable:!0},verticalPlacedTextSymbolIndex:{configurable:!0},placedIconSymbolIndex:{configurable:!0},verticalPlacedIconSymbolIndex:{configurable:!0},key:{configurable:!0},textBoxStartIndex:{configurable:!0},textBoxEndIndex:{configurable:!0},verticalTextBoxStartIndex:{configurable:!0},verticalTextBoxEndIndex:{configurable:!0},iconBoxStartIndex:{configurable:!0},iconBoxEndIndex:{configurable:!0},verticalIconBoxStartIndex:{configurable:!0},verticalIconBoxEndIndex:{configurable:!0},featureIndex:{configurable:!0},numHorizontalGlyphVertices:{configurable:!0},numVerticalGlyphVertices:{configurable:!0},numIconVertices:{configurable:!0},numVerticalIconVertices:{configurable:!0},useRuntimeCollisionCircles:{configurable:!0},crossTileID:{configurable:!0},textBoxScale:{configurable:!0},textOffset0:{configurable:!0},textOffset1:{configurable:!0},collisionCircleDiameter:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.rightJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+2]},r.centerJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+3]},r.leftJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+4]},r.verticalPlacedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+5]},r.placedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+6]},r.verticalPlacedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+7]},r.key.get=function(){return this._structArray.uint16[this._pos2+8]},r.textBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.textBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+10]},r.verticalTextBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+11]},r.verticalTextBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+12]},r.iconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+13]},r.iconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+14]},r.verticalIconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+15]},r.verticalIconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+16]},r.featureIndex.get=function(){return this._structArray.uint16[this._pos2+17]},r.numHorizontalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+18]},r.numVerticalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+19]},r.numIconVertices.get=function(){return this._structArray.uint16[this._pos2+20]},r.numVerticalIconVertices.get=function(){return this._structArray.uint16[this._pos2+21]},r.useRuntimeCollisionCircles.get=function(){return 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t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){this.current!==t&&(this.current=t,this.gl.uniform1i(this.location,t))},e}(Ga),Ya=function(t){function e(e,r){t.call(this,e,r),this.current=0}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){this.current!==t&&(this.current=t,this.gl.uniform1f(this.location,t))},e}(Ga),Wa=function(t){function e(e,r){t.call(this,e,r),this.current=[0,0]}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){t[0]===this.current[0]&&t[1]===this.current[1]||(this.current=t,this.gl.uniform2f(this.location,t[0],t[1]))},e}(Ga),Xa=function(t){function e(e,r){t.call(this,e,r),this.current=[0,0,0]}return 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Float32Array(16),Qa=function(t){function e(e,r){t.call(this,e,r),this.current=$a}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){if(t[12]!==this.current[12]||t[0]!==this.current[0])return this.current=t,void this.gl.uniformMatrix4fv(this.location,!1,t);for(var e=1;e<16;e++)if(t[e]!==this.current[e]){this.current=t,this.gl.uniformMatrix4fv(this.location,!1,t);break}},e}(Ga);function to(t){return[Ia(255*t.r,255*t.g),Ia(255*t.b,255*t.a)]}var eo=function(t,e,r){this.value=t,this.uniformNames=e.map((function(t){return\"u_\"+t})),this.type=r};eo.prototype.setUniform=function(t,e,r){t.set(r.constantOr(this.value))},eo.prototype.getBinding=function(t,e,r){return\"color\"===this.type?new Ka(t,e):new Ya(t,e)};var ro=function(t,e){this.uniformNames=e.map((function(t){return\"u_\"+t})),this.patternFrom=null,this.patternTo=null,this.pixelRatioFrom=1,this.pixelRatioTo=1};ro.prototype.setConstantPatternPositions=function(t,e){this.pixelRatioFrom=e.pixelRatio,this.pixelRatioTo=t.pixelRatio,this.patternFrom=e.tlbr,this.patternTo=t.tlbr},ro.prototype.setUniform=function(t,e,r,n){var i=\"u_pattern_to\"===n?this.patternTo:\"u_pattern_from\"===n?this.patternFrom:\"u_pixel_ratio_to\"===n?this.pixelRatioTo:\"u_pixel_ratio_from\"===n?this.pixelRatioFrom:null;i&&t.set(i)},ro.prototype.getBinding=function(t,e,r){return\"u_pattern\"===r.substr(0,9)?new Ja(t,e):new Ya(t,e)};var no=function(t,e,r,n){this.expression=t,this.type=r,this.maxValue=0,this.paintVertexAttributes=e.map((function(t){return{name:\"a_\"+t,type:\"Float32\",components:\"color\"===r?2:1,offset:0}})),this.paintVertexArray=new n};no.prototype.populatePaintArray=function(t,e,r,n,i){var a=this.paintVertexArray.length,o=this.expression.evaluate(new Pi(0),e,{},n,[],i);this.paintVertexArray.resize(t),this._setPaintValue(a,t,o)},no.prototype.updatePaintArray=function(t,e,r,n){var i=this.expression.evaluate({zoom:0},r,n);this._setPaintValue(t,e,i)},no.prototype._setPaintValue=function(t,e,r){if(\"color\"===this.type)for(var n=to(r),i=t;i<e;i++)this.paintVertexArray.emplace(i,n[0],n[1]);else{for(var a=t;a<e;a++)this.paintVertexArray.emplace(a,r);this.maxValue=Math.max(this.maxValue,Math.abs(r))}},no.prototype.upload=function(t){this.paintVertexArray&&this.paintVertexArray.arrayBuffer&&(this.paintVertexBuffer&&this.paintVertexBuffer.buffer?this.paintVertexBuffer.updateData(this.paintVertexArray):this.paintVertexBuffer=t.createVertexBuffer(this.paintVertexArray,this.paintVertexAttributes,this.expression.isStateDependent))},no.prototype.destroy=function(){this.paintVertexBuffer&&this.paintVertexBuffer.destroy()};var io=function(t,e,r,n,i,a){this.expression=t,this.uniformNames=e.map((function(t){return\"u_\"+t+\"_t\"})),this.type=r,this.useIntegerZoom=n,this.zoom=i,this.maxValue=0,this.paintVertexAttributes=e.map((function(t){return{name:\"a_\"+t,type:\"Float32\",components:\"color\"===r?4:2,offset:0}})),this.paintVertexArray=new a};io.prototype.populatePaintArray=function(t,e,r,n,i){var a=this.expression.evaluate(new Pi(this.zoom),e,{},n,[],i),o=this.expression.evaluate(new Pi(this.zoom+1),e,{},n,[],i),s=this.paintVertexArray.length;this.paintVertexArray.resize(t),this._setPaintValue(s,t,a,o)},io.prototype.updatePaintArray=function(t,e,r,n){var i=this.expression.evaluate({zoom:this.zoom},r,n),a=this.expression.evaluate({zoom:this.zoom+1},r,n);this._setPaintValue(t,e,i,a)},io.prototype._setPaintValue=function(t,e,r,n){if(\"color\"===this.type)for(var i=to(r),a=to(n),o=t;o<e;o++)this.paintVertexArray.emplace(o,i[0],i[1],a[0],a[1]);else{for(var s=t;s<e;s++)this.paintVertexArray.emplace(s,r,n);this.maxValue=Math.max(this.maxValue,Math.abs(r),Math.abs(n))}},io.prototype.upload=function(t){this.paintVertexArray&&this.paintVertexArray.arrayBuffer&&(this.paintVertexBuffer&&this.paintVertexBuffer.buffer?this.paintVertexBuffer.updateData(this.paintVertexArray):this.paintVertexBuffer=t.createVertexBuffer(this.paintVertexArray,this.paintVertexAttributes,this.expression.isStateDependent))},io.prototype.destroy=function(){this.paintVertexBuffer&&this.paintVertexBuffer.destroy()},io.prototype.setUniform=function(t,e){var r=this.useIntegerZoom?Math.floor(e.zoom):e.zoom,n=u(this.expression.interpolationFactor(r,this.zoom,this.zoom+1),0,1);t.set(n)},io.prototype.getBinding=function(t,e,r){return new Ya(t,e)};var ao=function(t,e,r,n,i,a){this.expression=t,this.type=e,this.useIntegerZoom=r,this.zoom=n,this.layerId=a,this.zoomInPaintVertexArray=new i,this.zoomOutPaintVertexArray=new i};ao.prototype.populatePaintArray=function(t,e,r){var n=this.zoomInPaintVertexArray.length;this.zoomInPaintVertexArray.resize(t),this.zoomOutPaintVertexArray.resize(t),this._setPaintValues(n,t,e.patterns&&e.patterns[this.layerId],r)},ao.prototype.updatePaintArray=function(t,e,r,n,i){this._setPaintValues(t,e,r.patterns&&r.patterns[this.layerId],i)},ao.prototype._setPaintValues=function(t,e,r,n){if(n&&r){var i=r.min,a=r.mid,o=r.max,s=n[i],l=n[a],u=n[o];if(s&&l&&u)for(var c=t;c<e;c++)this.zoomInPaintVertexArray.emplace(c,l.tl[0],l.tl[1],l.br[0],l.br[1],s.tl[0],s.tl[1],s.br[0],s.br[1],l.pixelRatio,s.pixelRatio),this.zoomOutPaintVertexArray.emplace(c,l.tl[0],l.tl[1],l.br[0],l.br[1],u.tl[0],u.tl[1],u.br[0],u.br[1],l.pixelRatio,u.pixelRatio)}},ao.prototype.upload=function(t){this.zoomInPaintVertexArray&&this.zoomInPaintVertexArray.arrayBuffer&&this.zoomOutPaintVertexArray&&this.zoomOutPaintVertexArray.arrayBuffer&&(this.zoomInPaintVertexBuffer=t.createVertexBuffer(this.zoomInPaintVertexArray,Da.members,this.expression.isStateDependent),this.zoomOutPaintVertexBuffer=t.createVertexBuffer(this.zoomOutPaintVertexArray,Da.members,this.expression.isStateDependent))},ao.prototype.destroy=function(){this.zoomOutPaintVertexBuffer&&this.zoomOutPaintVertexBuffer.destroy(),this.zoomInPaintVertexBuffer&&this.zoomInPaintVertexBuffer.destroy()};var oo=function(t,e,r,n){this.binders={},this.layoutAttributes=n,this._buffers=[];var i=[];for(var a in t.paint._values)if(r(a)){var o=t.paint.get(a);if(o instanceof Bi&&Yr(o.property.specification)){var s=lo(a,t.type),l=o.value,u=o.property.specification.type,c=o.property.useIntegerZoom,f=o.property.specification[\"property-type\"],h=\"cross-faded\"===f||\"cross-faded-data-driven\"===f;if(\"constant\"===l.kind)this.binders[a]=h?new ro(l.value,s):new eo(l.value,s,u),i.push(\"/u_\"+a);else if(\"source\"===l.kind||h){var p=uo(a,u,\"source\");this.binders[a]=h?new ao(l,u,c,e,p,t.id):new no(l,s,u,p),i.push(\"/a_\"+a)}else{var d=uo(a,u,\"composite\");this.binders[a]=new io(l,s,u,c,e,d),i.push(\"/z_\"+a)}}}this.cacheKey=i.sort().join(\"\")};oo.prototype.getMaxValue=function(t){var e=this.binders[t];return e instanceof no||e instanceof io?e.maxValue:0},oo.prototype.populatePaintArrays=function(t,e,r,n,i){for(var a in this.binders){var o=this.binders[a];(o instanceof no||o instanceof io||o instanceof ao)&&o.populatePaintArray(t,e,r,n,i)}},oo.prototype.setConstantPatternPositions=function(t,e){for(var r in this.binders){var n=this.binders[r];n instanceof ro&&n.setConstantPatternPositions(t,e)}},oo.prototype.updatePaintArrays=function(t,e,r,n,i){var a=!1;for(var o in t)for(var s=0,l=e.getPositions(o);s<l.length;s+=1){var u=l[s],c=r.feature(u.index);for(var f in this.binders){var h=this.binders[f];if((h instanceof no||h instanceof io||h instanceof ao)&&!0===h.expression.isStateDependent){var p=n.paint.get(f);h.expression=p.value,h.updatePaintArray(u.start,u.end,c,t[o],i),a=!0}}}return a},oo.prototype.defines=function(){var t=[];for(var e in this.binders){var r=this.binders[e];(r instanceof eo||r instanceof ro)&&t.push.apply(t,r.uniformNames.map((function(t){return\"#define HAS_UNIFORM_\"+t})))}return t},oo.prototype.getPaintVertexBuffers=function(){return this._buffers},oo.prototype.getUniforms=function(t,e){var r=[];for(var n in this.binders){var i=this.binders[n];if(i instanceof eo||i instanceof ro||i instanceof io)for(var a=0,o=i.uniformNames;a<o.length;a+=1){var s=o[a];if(e[s]){var l=i.getBinding(t,e[s],s);r.push({name:s,property:n,binding:l})}}}return r},oo.prototype.setUniforms=function(t,e,r,n){for(var i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.name,l=o.property,u=o.binding;this.binders[l].setUniform(u,n,r.get(l),s)}},oo.prototype.updatePaintBuffers=function(t){for(var e in this._buffers=[],this.binders){var r=this.binders[e];if(t&&r instanceof ao){var n=2===t.fromScale?r.zoomInPaintVertexBuffer:r.zoomOutPaintVertexBuffer;n&&this._buffers.push(n)}else(r instanceof no||r instanceof io)&&r.paintVertexBuffer&&this._buffers.push(r.paintVertexBuffer)}},oo.prototype.upload=function(t){for(var e in this.binders){var r=this.binders[e];(r instanceof no||r instanceof io||r instanceof ao)&&r.upload(t)}this.updatePaintBuffers()},oo.prototype.destroy=function(){for(var t in this.binders){var e=this.binders[t];(e instanceof no||e instanceof io||e instanceof ao)&&e.destroy()}};var so=function(t,e,r,n){void 0===n&&(n=function(){return!0}),this.programConfigurations={};for(var i=0,a=e;i<a.length;i+=1){var o=a[i];this.programConfigurations[o.id]=new oo(o,r,n,t)}this.needsUpload=!1,this._featureMap=new ja,this._bufferOffset=0};function lo(t,e){return{\"text-opacity\":[\"opacity\"],\"icon-opacity\":[\"opacity\"],\"text-color\":[\"fill_color\"],\"icon-color\":[\"fill_color\"],\"text-halo-color\":[\"halo_color\"],\"icon-halo-color\":[\"halo_color\"],\"text-halo-blur\":[\"halo_blur\"],\"icon-halo-blur\":[\"halo_blur\"],\"text-halo-width\":[\"halo_width\"],\"icon-halo-width\":[\"halo_width\"],\"line-gap-width\":[\"gapwidth\"],\"line-pattern\":[\"pattern_to\",\"pattern_from\",\"pixel_ratio_to\",\"pixel_ratio_from\"],\"fill-pattern\":[\"pattern_to\",\"pattern_from\",\"pixel_ratio_to\",\"pixel_ratio_from\"],\"fill-extrusion-pattern\":[\"pattern_to\",\"pattern_from\",\"pixel_ratio_to\",\"pixel_ratio_from\"]}[t]||[t.replace(e+\"-\",\"\").replace(/-/g,\"_\")]}function uo(t,e,r){var n={color:{source:xa,composite:ba},number:{source:da,composite:xa}},i=function(t){return{\"line-pattern\":{source:na,composite:na},\"fill-pattern\":{source:na,composite:na},\"fill-extrusion-pattern\":{source:na,composite:na}}[t]}(t);return i&&i[r]||n[e][r]}so.prototype.populatePaintArrays=function(t,e,r,n,i,a){for(var o in this.programConfigurations)this.programConfigurations[o].populatePaintArrays(t,e,n,i,a);void 0!==e.id&&this._featureMap.add(e.id,r,this._bufferOffset,t),this._bufferOffset=t,this.needsUpload=!0},so.prototype.updatePaintArrays=function(t,e,r,n){for(var i=0,a=r;i<a.length;i+=1){var o=a[i];this.needsUpload=this.programConfigurations[o.id].updatePaintArrays(t,this._featureMap,e,o,n)||this.needsUpload}},so.prototype.get=function(t){return this.programConfigurations[t]},so.prototype.upload=function(t){if(this.needsUpload){for(var e in this.programConfigurations)this.programConfigurations[e].upload(t);this.needsUpload=!1}},so.prototype.destroy=function(){for(var t in this.programConfigurations)this.programConfigurations[t].destroy()},ni(\"ConstantBinder\",eo),ni(\"CrossFadedConstantBinder\",ro),ni(\"SourceExpressionBinder\",no),ni(\"CrossFadedCompositeBinder\",ao),ni(\"CompositeExpressionBinder\",io),ni(\"ProgramConfiguration\",oo,{omit:[\"_buffers\"]}),ni(\"ProgramConfigurationSet\",so);var co=8192;var fo,ho=(fo=15,{min:-1*Math.pow(2,fo-1),max:Math.pow(2,fo-1)-1});function po(t){for(var e=co/t.extent,r=t.loadGeometry(),n=0;n<r.length;n++)for(var i=r[n],a=0;a<i.length;a++){var o=i[a];o.x=Math.round(o.x*e),o.y=Math.round(o.y*e),(o.x<ho.min||o.x>ho.max||o.y<ho.min||o.y>ho.max)&&(w(\"Geometry exceeds allowed extent, reduce your vector tile buffer size\"),o.x=u(o.x,ho.min,ho.max),o.y=u(o.y,ho.min,ho.max))}return r}function vo(t,e,r,n,i){t.emplaceBack(2*e+(n+1)/2,2*r+(i+1)/2)}var go=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new Qi,this.indexArray=new fa,this.segments=new Oa,this.programConfigurations=new so(Pa,t.layers,t.zoom),this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};function yo(t,e){for(var r=0;r<t.length;r++)if(Mo(e,t[r]))return!0;for(var n=0;n<e.length;n++)if(Mo(t,e[n]))return!0;return!!_o(t,e)}function mo(t,e,r){return!!Mo(t,e)||!!To(e,t,r)}function xo(t,e){if(1===t.length)return Ao(e,t[0]);for(var r=0;r<e.length;r++)for(var n=e[r],i=0;i<n.length;i++)if(Mo(t,n[i]))return!0;for(var a=0;a<t.length;a++)if(Ao(e,t[a]))return!0;for(var o=0;o<e.length;o++)if(_o(t,e[o]))return!0;return!1}function bo(t,e,r){if(t.length>1){if(_o(t,e))return!0;for(var n=0;n<e.length;n++)if(To(e[n],t,r))return!0}for(var i=0;i<t.length;i++)if(To(t[i],e,r))return!0;return!1}function _o(t,e){if(0===t.length||0===e.length)return!1;for(var r=0;r<t.length-1;r++)for(var 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n=t.readVarint()>>3;e=1===n?t.readString():2===n?t.readFloat():3===n?t.readDouble():4===n?t.readVarint64():5===n?t.readVarint():6===n?t.readSVarint():7===n?t.readBoolean():null}return e}(r))}function Xs(t,e,r){if(3===t){var n=new Zs(r,r.readVarint()+r.pos);n.length&&(e[n.name]=n)}}Ys.prototype.feature=function(t){if(t<0||t>=this._features.length)throw new Error(\"feature index out of bounds\");this._pbf.pos=this._features[t];var e=this._pbf.readVarint()+this._pbf.pos;return new Vs(this._pbf,e,this.extent,this._keys,this._values)};var Js={VectorTile:function(t,e){this.layers=t.readFields(Xs,{},e)},VectorTileFeature:Vs,VectorTileLayer:Zs},Ks=Js.VectorTileFeature.types,$s=Math.pow(2,13);function Qs(t,e,r,n,i,a,o,s){t.emplaceBack(e,r,2*Math.floor(n*$s)+o,i*$s*2,a*$s*2,Math.round(s))}var tl=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new ea,this.indexArray=new fa,this.programConfigurations=new so(Us,t.layers,t.zoom),this.segments=new Oa,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};function el(t,e){return t.x===e.x&&(t.x<0||t.x>co)||t.y===e.y&&(t.y<0||t.y>co)}tl.prototype.populate=function(t,e,r){this.features=[],this.hasPattern=zs(\"fill-extrusion\",this.layers,e);for(var n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.feature,s=a.id,l=a.index,u=a.sourceLayerIndex,c=this.layers[0]._featureFilter.needGeometry,f={type:o.type,id:s,properties:o.properties,geometry:c?po(o):[]};if(this.layers[0]._featureFilter.filter(new Pi(this.zoom),f,r)){var h={id:s,sourceLayerIndex:u,index:l,geometry:c?f.geometry:po(o),properties:o.properties,type:o.type,patterns:{}};void 0!==o.id&&(h.id=o.id),this.hasPattern?this.features.push(Rs(\"fill-extrusion\",this.layers,h,this.zoom,e)):this.addFeature(h,h.geometry,l,r,{}),e.featureIndex.insert(o,h.geometry,l,u,this.index,!0)}}},tl.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.features;n<i.length;n+=1){var a=i[n],o=a.geometry;this.addFeature(a,o,a.index,e,r)}},tl.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},tl.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},tl.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},tl.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Us),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},tl.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},tl.prototype.addFeature=function(t,e,r,n,i){for(var a=0,o=Is(e,500);a<o.length;a+=1){for(var s=o[a],l=0,u=0,c=s;u<c.length;u+=1)l+=c[u].length;for(var f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray),h=0,p=s;h<p.length;h+=1){var d=p[h];if(0!==d.length&&!((O=d).every((function(t){return t.x<0}))||O.every((function(t){return t.x>co}))||O.every((function(t){return t.y<0}))||O.every((function(t){return t.y>co}))))for(var v=0,g=0;g<d.length;g++){var y=d[g];if(g>=1){var m=d[g-1];if(!el(y,m)){f.vertexLength+4>Oa.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));var x=y.sub(m)._perp()._unit(),b=m.dist(y);v+b>32768&&(v=0),Qs(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,0,v),Qs(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,1,v),v+=b,Qs(this.layoutVertexArray,m.x,m.y,x.x,x.y,0,0,v),Qs(this.layoutVertexArray,m.x,m.y,x.x,x.y,0,1,v);var _=f.vertexLength;this.indexArray.emplaceBack(_,_+2,_+1),this.indexArray.emplaceBack(_+1,_+2,_+3),f.vertexLength+=4,f.primitiveLength+=2}}}}if(f.vertexLength+l>Oa.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(l,this.layoutVertexArray,this.indexArray)),\"Polygon\"===Ks[t.type]){for(var w=[],T=[],k=f.vertexLength,A=0,M=s;A<M.length;A+=1){var S=M[A];if(0!==S.length){S!==s[0]&&T.push(w.length/2);for(var E=0;E<S.length;E++){var L=S[E];Qs(this.layoutVertexArray,L.x,L.y,0,0,1,1,0),w.push(L.x),w.push(L.y)}}}for(var C=es(w,T),P=0;P<C.length;P+=3)this.indexArray.emplaceBack(k+C[P],k+C[P+2],k+C[P+1]);f.primitiveLength+=C.length/3,f.vertexLength+=l}}var O;this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},ni(\"FillExtrusionBucket\",tl,{omit:[\"layers\",\"features\"]});var rl={paint:new Gi({\"fill-extrusion-opacity\":new ji(Dt[\"paint_fill-extrusion\"][\"fill-extrusion-opacity\"]),\"fill-extrusion-color\":new Ui(Dt[\"paint_fill-extrusion\"][\"fill-extrusion-color\"]),\"fill-extrusion-translate\":new ji(Dt[\"paint_fill-extrusion\"][\"fill-extrusion-translate\"]),\"fill-extrusion-translate-anchor\":new ji(Dt[\"paint_fill-extrusion\"][\"fill-extrusion-translate-anchor\"]),\"fill-extrusion-pattern\":new Vi(Dt[\"paint_fill-extrusion\"][\"fill-extrusion-pattern\"]),\"fill-extrusion-height\":new Ui(Dt[\"paint_fill-extrusion\"][\"fill-extrusion-height\"]),\"fill-extrusion-base\":new Ui(Dt[\"paint_fill-extrusion\"][\"fill-extrusion-base\"]),\"fill-extrusion-vertical-gradient\":new ji(Dt[\"paint_fill-extrusion\"][\"fill-extrusion-vertical-gradient\"])})},nl=function(t){function e(e){t.call(this,e,rl)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.createBucket=function(t){return new tl(t)},e.prototype.queryRadius=function(){return Lo(this.paint.get(\"fill-extrusion-translate\"))},e.prototype.is3D=function(){return!0},e.prototype.queryIntersectsFeature=function(t,e,r,n,i,o,s,l){var u=Co(t,this.paint.get(\"fill-extrusion-translate\"),this.paint.get(\"fill-extrusion-translate-anchor\"),o.angle,s),c=this.paint.get(\"fill-extrusion-height\").evaluate(e,r),f=this.paint.get(\"fill-extrusion-base\").evaluate(e,r),h=function(t,e,r,n){for(var i=[],o=0,s=t;o<s.length;o+=1){var l=s[o],u=[l.x,l.y,n,1];No(u,u,e),i.push(new a(u[0]/u[3],u[1]/u[3]))}return i}(u,l,0,0),p=function(t,e,r,n){for(var i=[],o=[],s=n[8]*e,l=n[9]*e,u=n[10]*e,c=n[11]*e,f=n[8]*r,h=n[9]*r,p=n[10]*r,d=n[11]*r,v=0,g=t;v<g.length;v+=1){for(var y=[],m=[],x=0,b=g[v];x<b.length;x+=1){var _=b[x],w=_.x,T=_.y,k=n[0]*w+n[4]*T+n[12],A=n[1]*w+n[5]*T+n[13],M=n[2]*w+n[6]*T+n[14],S=n[3]*w+n[7]*T+n[15],E=M+u,L=S+c,C=k+f,P=A+h,O=M+p,I=S+d,D=new a((k+s)/L,(A+l)/L);D.z=E/L,y.push(D);var z=new a(C/I,P/I);z.z=O/I,m.push(z)}i.push(y),o.push(m)}return[i,o]}(n,f,c,l);return function(t,e,r){var n=1/0;xo(r,e)&&(n=al(r,e[0]));for(var i=0;i<e.length;i++)for(var a=e[i],o=t[i],s=0;s<a.length-1;s++){var l=a[s],u=a[s+1],c=o[s],f=[l,u,o[s+1],c,l];yo(r,f)&&(n=Math.min(n,al(r,f)))}return n!==1/0&&n}(p[0],p[1],h)},e}(Yi);function il(t,e){return t.x*e.x+t.y*e.y}function al(t,e){if(1===t.length){for(var r,n=0,i=e[n++];!r||i.equals(r);)if(!(r=e[n++]))return 1/0;for(;n<e.length;n++){var a=e[n],o=t[0],s=r.sub(i),l=a.sub(i),u=o.sub(i),c=il(s,s),f=il(s,l),h=il(l,l),p=il(u,s),d=il(u,l),v=c*h-f*f,g=(h*p-f*d)/v,y=(c*d-f*p)/v,m=1-g-y,x=i.z*m+r.z*g+a.z*y;if(isFinite(x))return x}return 1/0}for(var b=1/0,_=0,w=e;_<w.length;_+=1){var T=w[_];b=Math.min(b,T.z)}return b}var ol=Ki([{name:\"a_pos_normal\",components:2,type:\"Int16\"},{name:\"a_data\",components:4,type:\"Uint8\"}],4).members,sl=Js.VectorTileFeature.types,ll=Math.cos(Math.PI/180*37.5),ul=Math.pow(2,14)/.5,cl=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.patternFeatures=[],this.layoutVertexArray=new ra,this.indexArray=new fa,this.programConfigurations=new so(ol,t.layers,t.zoom),this.segments=new Oa,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};cl.prototype.populate=function(t,e,r){this.hasPattern=zs(\"line\",this.layers,e);for(var n=this.layers[0].layout.get(\"line-sort-key\"),i=[],a=0,o=t;a<o.length;a+=1){var s=o[a],l=s.feature,u=s.id,c=s.index,f=s.sourceLayerIndex,h=this.layers[0]._featureFilter.needGeometry,p={type:l.type,id:u,properties:l.properties,geometry:h?po(l):[]};if(this.layers[0]._featureFilter.filter(new Pi(this.zoom),p,r)){h||(p.geometry=po(l));var d=n?n.evaluate(p,{},r):void 0,v={id:u,properties:l.properties,type:l.type,sourceLayerIndex:f,index:c,geometry:p.geometry,patterns:{},sortKey:d};i.push(v)}}n&&i.sort((function(t,e){return t.sortKey-e.sortKey}));for(var g=0,y=i;g<y.length;g+=1){var m=y[g],x=m,b=x.geometry,_=x.index,w=x.sourceLayerIndex;if(this.hasPattern){var T=Rs(\"line\",this.layers,m,this.zoom,e);this.patternFeatures.push(T)}else this.addFeature(m,b,_,r,{});var k=t[_].feature;e.featureIndex.insert(k,b,_,w,this.index)}},cl.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},cl.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.patternFeatures;n<i.length;n+=1){var a=i[n];this.addFeature(a,a.geometry,a.index,e,r)}},cl.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},cl.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},cl.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,ol),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},cl.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},cl.prototype.addFeature=function(t,e,r,n,i){for(var a=this.layers[0].layout,o=a.get(\"line-join\").evaluate(t,{}),s=a.get(\"line-cap\"),l=a.get(\"line-miter-limit\"),u=a.get(\"line-round-limit\"),c=0,f=e;c<f.length;c+=1){var h=f[c];this.addLine(h,t,o,s,l,u)}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},cl.prototype.addLine=function(t,e,r,n,i,a){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,e.properties&&e.properties.hasOwnProperty(\"mapbox_clip_start\")&&e.properties.hasOwnProperty(\"mapbox_clip_end\")){this.clipStart=+e.properties.mapbox_clip_start,this.clipEnd=+e.properties.mapbox_clip_end;for(var o=0;o<t.length-1;o++)this.totalDistance+=t[o].dist(t[o+1]);this.updateScaledDistance()}for(var s=\"Polygon\"===sl[e.type],l=t.length;l>=2&&t[l-1].equals(t[l-2]);)l--;for(var u=0;u<l-1&&t[u].equals(t[u+1]);)u++;if(!(l<(s?3:2))){\"bevel\"===r&&(i=1.05);var c,f=this.overscaling<=16?15*co/(512*this.overscaling):0,h=this.segments.prepareSegment(10*l,this.layoutVertexArray,this.indexArray),p=void 0,d=void 0,v=void 0,g=void 0;this.e1=this.e2=-1,s&&(c=t[l-2],g=t[u].sub(c)._unit()._perp());for(var y=u;y<l;y++)if(!(d=y===l-1?s?t[u+1]:void 0:t[y+1])||!t[y].equals(d)){g&&(v=g),c&&(p=c),c=t[y],g=d?d.sub(c)._unit()._perp():v;var m=(v=v||g).add(g);0===m.x&&0===m.y||m._unit();var x=v.x*g.x+v.y*g.y,b=m.x*g.x+m.y*g.y,_=0!==b?1/b:1/0,w=2*Math.sqrt(2-2*b),T=b<ll&&p&&d,k=v.x*g.y-v.y*g.x>0;if(T&&y>u){var A=c.dist(p);if(A>2*f){var M=c.sub(c.sub(p)._mult(f/A)._round());this.updateDistance(p,M),this.addCurrentVertex(M,v,0,0,h),p=M}}var S=p&&d,E=S?r:s?\"butt\":n;if(S&&\"round\"===E&&(_<a?E=\"miter\":_<=2&&(E=\"fakeround\")),\"miter\"===E&&_>i&&(E=\"bevel\"),\"bevel\"===E&&(_>2&&(E=\"flipbevel\"),_<i&&(E=\"miter\")),p&&this.updateDistance(p,c),\"miter\"===E)m._mult(_),this.addCurrentVertex(c,m,0,0,h);else if(\"flipbevel\"===E){if(_>100)m=g.mult(-1);else{var L=_*v.add(g).mag()/v.sub(g).mag();m._perp()._mult(L*(k?-1:1))}this.addCurrentVertex(c,m,0,0,h),this.addCurrentVertex(c,m.mult(-1),0,0,h)}else if(\"bevel\"===E||\"fakeround\"===E){var C=-Math.sqrt(_*_-1),P=k?C:0,O=k?0:C;if(p&&this.addCurrentVertex(c,v,P,O,h),\"fakeround\"===E)for(var I=Math.round(180*w/Math.PI/20),D=1;D<I;D++){var z=D/I;if(.5!==z){var R=z-.5;z+=z*R*(z-1)*((1.0904+x*(x*(3.55645-1.43519*x)-3.2452))*R*R+(.848013+x*(.215638*x-1.06021)))}var F=g.sub(v)._mult(z)._add(v)._unit()._mult(k?-1:1);this.addHalfVertex(c,F.x,F.y,!1,k,0,h)}d&&this.addCurrentVertex(c,g,-P,-O,h)}else if(\"butt\"===E)this.addCurrentVertex(c,m,0,0,h);else if(\"square\"===E){var B=p?1:-1;this.addCurrentVertex(c,m,B,B,h)}else\"round\"===E&&(p&&(this.addCurrentVertex(c,v,0,0,h),this.addCurrentVertex(c,v,1,1,h,!0)),d&&(this.addCurrentVertex(c,g,-1,-1,h,!0),this.addCurrentVertex(c,g,0,0,h)));if(T&&y<l-1){var N=c.dist(d);if(N>2*f){var j=c.add(d.sub(c)._mult(f/N)._round());this.updateDistance(c,j),this.addCurrentVertex(j,g,0,0,h),c=j}}}}},cl.prototype.addCurrentVertex=function(t,e,r,n,i,a){void 0===a&&(a=!1);var o=e.x+e.y*r,s=e.y-e.x*r,l=-e.x+e.y*n,u=-e.y-e.x*n;this.addHalfVertex(t,o,s,a,!1,r,i),this.addHalfVertex(t,l,u,a,!0,-n,i),this.distance>ul/2&&0===this.totalDistance&&(this.distance=0,this.addCurrentVertex(t,e,r,n,i,a))},cl.prototype.addHalfVertex=function(t,e,r,n,i,a,o){var s=t.x,l=t.y,u=.5*this.scaledDistance;this.layoutVertexArray.emplaceBack((s<<1)+(n?1:0),(l<<1)+(i?1:0),Math.round(63*e)+128,Math.round(63*r)+128,1+(0===a?0:a<0?-1:1)|(63&u)<<2,u>>6);var c=o.vertexLength++;this.e1>=0&&this.e2>=0&&(this.indexArray.emplaceBack(this.e1,this.e2,c),o.primitiveLength++),i?this.e2=c:this.e1=c},cl.prototype.updateScaledDistance=function(){this.scaledDistance=this.totalDistance>0?(this.clipStart+(this.clipEnd-this.clipStart)*this.distance/this.totalDistance)*(ul-1):this.distance},cl.prototype.updateDistance=function(t,e){this.distance+=t.dist(e),this.updateScaledDistance()},ni(\"LineBucket\",cl,{omit:[\"layers\",\"patternFeatures\"]});var fl=new Gi({\"line-cap\":new ji(Dt.layout_line[\"line-cap\"]),\"line-join\":new Ui(Dt.layout_line[\"line-join\"]),\"line-miter-limit\":new ji(Dt.layout_line[\"line-miter-limit\"]),\"line-round-limit\":new ji(Dt.layout_line[\"line-round-limit\"]),\"line-sort-key\":new Ui(Dt.layout_line[\"line-sort-key\"])}),hl={paint:new Gi({\"line-opacity\":new Ui(Dt.paint_line[\"line-opacity\"]),\"line-color\":new Ui(Dt.paint_line[\"line-color\"]),\"line-translate\":new ji(Dt.paint_line[\"line-translate\"]),\"line-translate-anchor\":new ji(Dt.paint_line[\"line-translate-anchor\"]),\"line-width\":new Ui(Dt.paint_line[\"line-width\"]),\"line-gap-width\":new Ui(Dt.paint_line[\"line-gap-width\"]),\"line-offset\":new Ui(Dt.paint_line[\"line-offset\"]),\"line-blur\":new Ui(Dt.paint_line[\"line-blur\"]),\"line-dasharray\":new Hi(Dt.paint_line[\"line-dasharray\"]),\"line-pattern\":new Vi(Dt.paint_line[\"line-pattern\"]),\"line-gradient\":new qi(Dt.paint_line[\"line-gradient\"])}),layout:fl},pl=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(e,r){return r=new Pi(Math.floor(r.zoom),{now:r.now,fadeDuration:r.fadeDuration,zoomHistory:r.zoomHistory,transition:r.transition}),t.prototype.possiblyEvaluate.call(this,e,r)},e.prototype.evaluate=function(e,r,n,i){return r=f({},r,{zoom:Math.floor(r.zoom)}),t.prototype.evaluate.call(this,e,r,n,i)},e}(Ui),dl=new pl(hl.paint.properties[\"line-width\"].specification);dl.useIntegerZoom=!0;var vl=function(t){function e(e){t.call(this,e,hl)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._handleSpecialPaintPropertyUpdate=function(t){\"line-gradient\"===t&&this._updateGradient()},e.prototype._updateGradient=function(){var t=this._transitionablePaint._values[\"line-gradient\"].value.expression;this.gradient=Jo(t,\"lineProgress\"),this.gradientTexture=null},e.prototype.recalculate=function(e,r){t.prototype.recalculate.call(this,e,r),this.paint._values[\"line-floorwidth\"]=dl.possiblyEvaluate(this._transitioningPaint._values[\"line-width\"].value,e)},e.prototype.createBucket=function(t){return new cl(t)},e.prototype.queryRadius=function(t){var e=t,r=gl(Eo(\"line-width\",this,e),Eo(\"line-gap-width\",this,e)),n=Eo(\"line-offset\",this,e);return r/2+Math.abs(n)+Lo(this.paint.get(\"line-translate\"))},e.prototype.queryIntersectsFeature=function(t,e,r,n,i,o,s){var l=Co(t,this.paint.get(\"line-translate\"),this.paint.get(\"line-translate-anchor\"),o.angle,s),u=s/2*gl(this.paint.get(\"line-width\").evaluate(e,r),this.paint.get(\"line-gap-width\").evaluate(e,r)),c=this.paint.get(\"line-offset\").evaluate(e,r);return c&&(n=function(t,e){for(var r=[],n=new a(0,0),i=0;i<t.length;i++){for(var o=t[i],s=[],l=0;l<o.length;l++){var u=o[l-1],c=o[l],f=o[l+1],h=0===l?n:c.sub(u)._unit()._perp(),p=l===o.length-1?n:f.sub(c)._unit()._perp(),d=h._add(p)._unit(),v=d.x*p.x+d.y*p.y;d._mult(1/v),s.push(d._mult(e)._add(c))}r.push(s)}return r}(n,c*s)),function(t,e,r){for(var n=0;n<e.length;n++){var i=e[n];if(t.length>=3)for(var a=0;a<i.length;a++)if(Mo(t,i[a]))return!0;if(bo(t,i,r))return!0}return!1}(l,n,u)},e.prototype.isTileClipped=function(){return!0},e}(Yi);function gl(t,e){return e>0?e+2*t:t}var 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Yl=3;function Wl(t,e,r){1===t&&r.readMessage(Xl,e)}function Xl(t,e,r){if(3===t){var n=r.readMessage(Jl,{}),i=n.id,a=n.bitmap,o=n.width,s=n.height,l=n.left,u=n.top,c=n.advance;e.push({id:i,bitmap:new Yo({width:o+2*Yl,height:s+2*Yl},a),metrics:{width:o,height:s,left:l,top:u,advance:c}})}}function Jl(t,e,r){1===t?e.id=r.readVarint():2===t?e.bitmap=r.readBytes():3===t?e.width=r.readVarint():4===t?e.height=r.readVarint():5===t?e.left=r.readSVarint():6===t?e.top=r.readSVarint():7===t&&(e.advance=r.readVarint())}var Kl=Yl;function $l(t){for(var e=0,r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];e+=a.w*a.h,r=Math.max(r,a.w)}t.sort((function(t,e){return e.h-t.h}));for(var o=[{x:0,y:0,w:Math.max(Math.ceil(Math.sqrt(e/.95)),r),h:1/0}],s=0,l=0,u=0,c=t;u<c.length;u+=1)for(var f=c[u],h=o.length-1;h>=0;h--){var p=o[h];if(!(f.w>p.w||f.h>p.h)){if(f.x=p.x,f.y=p.y,l=Math.max(l,f.y+f.h),s=Math.max(s,f.x+f.w),f.w===p.w&&f.h===p.h){var d=o.pop();h<o.length&&(o[h]=d)}else 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t.dispatchRenderCallbacks(this.haveRenderCallbacks),t.updatedImages)this.patchUpdatedImage(this.iconPositions[r],t.getImage(r),e),this.patchUpdatedImage(this.patternPositions[r],t.getImage(r),e)},ru.prototype.patchUpdatedImage=function(t,e,r){if(t&&e&&t.version!==e.version){t.version=e.version;var n=t.tl,i=n[0],a=n[1];r.update(e.data,void 0,{x:i,y:a})}},ni(\"ImagePosition\",tu),ni(\"ImageAtlas\",ru);var nu={horizontal:1,vertical:2,horizontalOnly:3},iu=-17;var au=function(){this.scale=1,this.fontStack=\"\",this.imageName=null};au.forText=function(t,e){var r=new au;return r.scale=t||1,r.fontStack=e,r},au.forImage=function(t){var e=new au;return e.imageName=t,e};var ou=function(){this.text=\"\",this.sectionIndex=[],this.sections=[],this.imageSectionID=null};function su(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v){var g,y=ou.fromFeature(t,i);f===nu.vertical&&y.verticalizePunctuation();var m=Ci.processBidirectionalText,x=Ci.processStyledBidirectionalText;if(m&&1===y.sections.length){g=[];for(var b=0,_=m(y.toString(),vu(y,u,a,e,n,p,d));b<_.length;b+=1){var w=_[b],T=new ou;T.text=w,T.sections=y.sections;for(var k=0;k<w.length;k++)T.sectionIndex.push(0);g.push(T)}}else if(x){g=[];for(var A=0,M=x(y.text,y.sectionIndex,vu(y,u,a,e,n,p,d));A<M.length;A+=1){var S=M[A],E=new ou;E.text=S[0],E.sectionIndex=S[1],E.sections=y.sections,g.push(E)}}else g=function(t,e){for(var r=[],n=t.text,i=0,a=0,o=e;a<o.length;a+=1){var s=o[a];r.push(t.substring(i,s)),i=s}return i<n.length&&r.push(t.substring(i,n.length)),r}(y,vu(y,u,a,e,n,p,d));var L=[],C={positionedLines:L,text:y.toString(),top:c[1],bottom:c[1],left:c[0],right:c[0],writingMode:f,iconsInText:!1,verticalizable:!1};return function(t,e,r,n,i,a,o,s,l,u,c,f){for(var h=0,p=iu,d=0,v=0,g=\"right\"===s?1:\"left\"===s?0:.5,y=0,m=0,x=i;m<x.length;m+=1){var b=x[m];b.trim();var _=b.getMaxScale(),w=(_-1)*kl,T={positionedGlyphs:[],lineOffset:0};t.positionedLines[y]=T;var k=T.positionedGlyphs,A=0;if(b.length()){for(var M=0;M<b.length();M++){var S=b.getSection(M),E=b.getSectionIndex(M),L=b.getCharCode(M),C=0,P=null,O=null,I=null,D=kl,z=!(l===nu.horizontal||!c&&!hi(L)||c&&(lu[L]||di(L)));if(S.imageName){var R=n[S.imageName];if(!R)continue;I=S.imageName,t.iconsInText=t.iconsInText||!0,O=R.paddedRect;var F=R.displaySize;S.scale=S.scale*kl/f,P={width:F[0],height:F[1],left:Ql,top:-Kl,advance:z?F[1]:F[0]},C=w+(kl-F[1]*S.scale),D=P.advance;var B=z?F[0]*S.scale-kl*_:F[1]*S.scale-kl*_;B>0&&B>A&&(A=B)}else{var N=r[S.fontStack],j=N&&N[L];if(j&&j.rect)O=j.rect,P=j.metrics;else{var U=e[S.fontStack],V=U&&U[L];if(!V)continue;P=V.metrics}C=(_-S.scale)*kl}z?(t.verticalizable=!0,k.push({glyph:L,imageName:I,x:h,y:p+C,vertical:z,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:O}),h+=D*S.scale+u):(k.push({glyph:L,imageName:I,x:h,y:p+C,vertical:z,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:O}),h+=P.advance*S.scale+u)}if(0!==k.length){var H=h-u;d=Math.max(H,d),yu(k,0,k.length-1,g,A)}h=0;var q=a*_+A;T.lineOffset=Math.max(A,w),p+=q,v=Math.max(q,v),++y}else p+=a,++y}var G=p-iu,Z=gu(o),Y=Z.horizontalAlign,W=Z.verticalAlign;(function(t,e,r,n,i,a,o,s,l){var u=(e-r)*i,c=0;c=a!==o?-s*n-iu:(-n*l+.5)*o;for(var f=0,h=t;f<h.length;f+=1)for(var p=0,d=h[f].positionedGlyphs;p<d.length;p+=1){var v=d[p];v.x+=u,v.y+=c}})(t.positionedLines,g,Y,W,d,v,a,G,i.length),t.top+=-W*G,t.bottom=t.top+G,t.left+=-Y*d,t.right=t.left+d}(C,e,r,n,g,o,s,l,f,u,h,v),!function(t){for(var e=0,r=t;e<r.length;e+=1)if(0!==r[e].positionedGlyphs.length)return!1;return!0}(L)&&C}ou.fromFeature=function(t,e){for(var r=new ou,n=0;n<t.sections.length;n++){var i=t.sections[n];i.image?r.addImageSection(i):r.addTextSection(i,e)}return r},ou.prototype.length=function(){return this.text.length},ou.prototype.getSection=function(t){return this.sections[this.sectionIndex[t]]},ou.prototype.getSectionIndex=function(t){return this.sectionIndex[t]},ou.prototype.getCharCode=function(t){return this.text.charCodeAt(t)},ou.prototype.verticalizePunctuation=function(){this.text=function(t){for(var e=\"\",r=0;r<t.length;r++){var n=t.charCodeAt(r+1)||null,i=t.charCodeAt(r-1)||null;n&&pi(n)&&!Tl[t[r+1]]||i&&pi(i)&&!Tl[t[r-1]]||!Tl[t[r]]?e+=t[r]:e+=Tl[t[r]]}return e}(this.text)},ou.prototype.trim=function(){for(var t=0,e=0;e<this.text.length&&lu[this.text.charCodeAt(e)];e++)t++;for(var r=this.text.length,n=this.text.length-1;n>=0&&n>=t&&lu[this.text.charCodeAt(n)];n--)r--;this.text=this.text.substring(t,r),this.sectionIndex=this.sectionIndex.slice(t,r)},ou.prototype.substring=function(t,e){var r=new ou;return r.text=this.text.substring(t,e),r.sectionIndex=this.sectionIndex.slice(t,e),r.sections=this.sections,r},ou.prototype.toString=function(){return this.text},ou.prototype.getMaxScale=function(){var t=this;return this.sectionIndex.reduce((function(e,r){return Math.max(e,t.sections[r].scale)}),0)},ou.prototype.addTextSection=function(t,e){this.text+=t.text,this.sections.push(au.forText(t.scale,t.fontStack||e));for(var r=this.sections.length-1,n=0;n<t.text.length;++n)this.sectionIndex.push(r)},ou.prototype.addImageSection=function(t){var e=t.image?t.image.name:\"\";if(0!==e.length){var r=this.getNextImageSectionCharCode();r?(this.text+=String.fromCharCode(r),this.sections.push(au.forImage(e)),this.sectionIndex.push(this.sections.length-1)):w(\"Reached maximum number of images 6401\")}else w(\"Can't add FormattedSection with an empty image.\")},ou.prototype.getNextImageSectionCharCode=function(){return this.imageSectionID?this.imageSectionID>=63743?null:++this.imageSectionID:(this.imageSectionID=57344,this.imageSectionID)};var lu={9:!0,10:!0,11:!0,12:!0,13:!0,32:!0},uu={};function cu(t,e,r,n,i,a){if(e.imageName){var o=n[e.imageName];return o?o.displaySize[0]*e.scale*kl/a+i:0}var s=r[e.fontStack],l=s&&s[t];return l?l.metrics.advance*e.scale+i:0}function fu(t,e,r,n){var i=Math.pow(t-e,2);return n?t<e?i/2:2*i:i+Math.abs(r)*r}function hu(t,e,r){var n=0;return 10===t&&(n-=1e4),r&&(n+=150),40!==t&&65288!==t||(n+=50),41!==e&&65289!==e||(n+=50),n}function pu(t,e,r,n,i,a){for(var o=null,s=fu(e,r,i,a),l=0,u=n;l<u.length;l+=1){var c=u[l],f=fu(e-c.x,r,i,a)+c.badness;f<=s&&(o=c,s=f)}return{index:t,x:e,priorBreak:o,badness:s}}function du(t){return t?du(t.priorBreak).concat(t.index):[]}function vu(t,e,r,n,i,a,o){if(\"point\"!==a)return[];if(!t)return[];for(var s=[],l=function(t,e,r,n,i,a){for(var o=0,s=0;s<t.length();s++){var l=t.getSection(s);o+=cu(t.getCharCode(s),l,n,i,e,a)}return o/Math.max(1,Math.ceil(o/r))}(t,e,r,n,i,o),u=t.text.indexOf(\"​\")>=0,c=0,f=0;f<t.length();f++){var h=t.getSection(f),p=t.getCharCode(f);if(lu[p]||(c+=cu(p,h,n,i,e,o)),f<t.length()-1){var d=!((v=p)<11904||!(ci[\"Bopomofo Extended\"](v)||ci.Bopomofo(v)||ci[\"CJK Compatibility Forms\"](v)||ci[\"CJK Compatibility 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yu(t,e,r,n,i){if(n||i)for(var a=t[r],o=a.metrics.advance*a.scale,s=(t[r].x+o)*n,l=e;l<=r;l++)t[l].x-=s,t[l].y+=i}function mu(t,e,r,n,i,a){var o,s=t.image;if(s.content){var l=s.content,u=s.pixelRatio||1;o=[l[0]/u,l[1]/u,s.displaySize[0]-l[2]/u,s.displaySize[1]-l[3]/u]}var c,f,h,p,d=e.left*a,v=e.right*a;\"width\"===r||\"both\"===r?(p=i[0]+d-n[3],f=i[0]+v+n[1]):f=(p=i[0]+(d+v-s.displaySize[0])/2)+s.displaySize[0];var g=e.top*a,y=e.bottom*a;return\"height\"===r||\"both\"===r?(c=i[1]+g-n[0],h=i[1]+y+n[2]):h=(c=i[1]+(g+y-s.displaySize[1])/2)+s.displaySize[1],{image:s,top:c,right:f,bottom:h,left:p,collisionPadding:o}}uu[10]=!0,uu[32]=!0,uu[38]=!0,uu[40]=!0,uu[41]=!0,uu[43]=!0,uu[45]=!0,uu[47]=!0,uu[173]=!0,uu[183]=!0,uu[8203]=!0,uu[8208]=!0,uu[8211]=!0,uu[8231]=!0;var xu=function(t){function e(e,r,n,i){t.call(this,e,r),this.angle=n,void 0!==i&&(this.segment=i)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.clone=function(){return new 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Oa,this.collisionVertexArray=new ca};oc.prototype.upload=function(t){this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,this.layoutAttributes),this.indexBuffer=t.createIndexBuffer(this.indexArray),this.collisionVertexBuffer=t.createVertexBuffer(this.collisionVertexArray,xl.members,!0)},oc.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.collisionVertexBuffer.destroy())},ni(\"CollisionBuffers\",oc);var sc=function(t){this.collisionBoxArray=t.collisionBoxArray,this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.pixelRatio=t.pixelRatio,this.sourceLayerIndex=t.sourceLayerIndex,this.hasPattern=!1,this.hasRTLText=!1,this.sortKeyRanges=[],this.collisionCircleArray=[],this.placementInvProjMatrix=Do([]),this.placementViewportMatrix=Do([]);var e=this.layers[0]._unevaluatedLayout._values;this.textSizeData=_u(this.zoom,e[\"text-size\"]),this.iconSizeData=_u(this.zoom,e[\"icon-size\"]);var r=this.layers[0].layout,n=r.get(\"symbol-sort-key\"),i=r.get(\"symbol-z-order\");this.sortFeaturesByKey=\"viewport-y\"!==i&&void 0!==n.constantOr(1);var a=\"viewport-y\"===i||\"auto\"===i&&!this.sortFeaturesByKey;this.sortFeaturesByY=a&&(r.get(\"text-allow-overlap\")||r.get(\"icon-allow-overlap\")||r.get(\"text-ignore-placement\")||r.get(\"icon-ignore-placement\")),\"point\"===r.get(\"symbol-placement\")&&(this.writingModes=r.get(\"text-writing-mode\").map((function(t){return nu[t]}))),this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id})),this.sourceID=t.sourceID};sc.prototype.createArrays=function(){this.text=new ac(new so(yl.members,this.layers,this.zoom,(function(t){return/^text/.test(t)}))),this.icon=new ac(new so(yl.members,this.layers,this.zoom,(function(t){return/^icon/.test(t)}))),this.glyphOffsetArray=new Sa,this.lineVertexArray=new Ea,this.symbolInstances=new Ma},sc.prototype.calculateGlyphDependencies=function(t,e,r,n,i){for(var a=0;a<t.length;a++)if(e[t.charCodeAt(a)]=!0,(r||n)&&i){var o=Tl[t.charAt(a)];o&&(e[o.charCodeAt(0)]=!0)}},sc.prototype.populate=function(t,e,r){var n=this.layers[0],i=n.layout,a=i.get(\"text-font\"),o=i.get(\"text-field\"),s=i.get(\"icon-image\"),l=(\"constant\"!==o.value.kind||o.value.value instanceof ue&&!o.value.value.isEmpty()||o.value.value.toString().length>0)&&(\"constant\"!==a.value.kind||a.value.value.length>0),u=\"constant\"!==s.value.kind||!!s.value.value||Object.keys(s.parameters).length>0,c=i.get(\"symbol-sort-key\");if(this.features=[],l||u){for(var f=e.iconDependencies,h=e.glyphDependencies,p=e.availableImages,d=new Pi(this.zoom),v=0,g=t;v<g.length;v+=1){var y=g[v],m=y.feature,x=y.id,b=y.index,_=y.sourceLayerIndex,w=n._featureFilter.needGeometry,T={type:m.type,id:x,properties:m.properties,geometry:w?po(m):[]};if(n._featureFilter.filter(d,T,r)){w||(T.geometry=po(m));var k=void 0;if(l){var A=n.getValueAndResolveTokens(\"text-field\",T,r,p),M=ue.factory(A);ic(M)&&(this.hasRTLText=!0),(!this.hasRTLText||\"unavailable\"===Ei()||this.hasRTLText&&Ci.isParsed())&&(k=wl(M,n,T))}var S=void 0;if(u){var E=n.getValueAndResolveTokens(\"icon-image\",T,r,p);S=E instanceof ce?E:ce.fromString(E)}if(k||S){var L=this.sortFeaturesByKey?c.evaluate(T,{},r):void 0,C={id:x,text:k,icon:S,index:b,sourceLayerIndex:_,geometry:po(m),properties:m.properties,type:tc[m.type],sortKey:L};if(this.features.push(C),S&&(f[S.name]=!0),k){var P=a.evaluate(T,{},r).join(\",\"),O=\"map\"===i.get(\"text-rotation-alignment\")&&\"point\"!==i.get(\"symbol-placement\");this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(nu.vertical)>=0;for(var I=0,D=k.sections;I<D.length;I+=1){var z=D[I];if(z.image)f[z.image.name]=!0;else{var R=fi(k.toString()),F=z.fontStack||P,B=h[F]=h[F]||{};this.calculateGlyphDependencies(z.text,B,O,this.allowVerticalPlacement,R)}}}}}}\"line\"===i.get(\"symbol-placement\")&&(this.features=function(t){var e={},r={},n=[],i=0;function a(e){n.push(t[e]),i++}function o(t,e,i){var a=r[t];return delete r[t],r[e]=a,n[a].geometry[0].pop(),n[a].geometry[0]=n[a].geometry[0].concat(i[0]),a}function s(t,r,i){var a=e[r];return delete e[r],e[t]=a,n[a].geometry[0].shift(),n[a].geometry[0]=i[0].concat(n[a].geometry[0]),a}function l(t,e,r){var n=r?e[0][e[0].length-1]:e[0][0];return t+\":\"+n.x+\":\"+n.y}for(var u=0;u<t.length;u++){var c=t[u],f=c.geometry,h=c.text?c.text.toString():null;if(h){var p=l(h,f),d=l(h,f,!0);if(p in r&&d in e&&r[p]!==e[d]){var v=s(p,d,f),g=o(p,d,n[v].geometry);delete e[p],delete r[d],r[l(h,n[g].geometry,!0)]=g,n[v].geometry=null}else p in r?o(p,d,f):d in e?s(p,d,f):(a(u),e[p]=i-1,r[d]=i-1)}else a(u)}return n.filter((function(t){return t.geometry}))}(this.features)),this.sortFeaturesByKey&&this.features.sort((function(t,e){return t.sortKey-e.sortKey}))}},sc.prototype.update=function(t,e,r){this.stateDependentLayers.length&&(this.text.programConfigurations.updatePaintArrays(t,e,this.layers,r),this.icon.programConfigurations.updatePaintArrays(t,e,this.layers,r))},sc.prototype.isEmpty=function(){return 0===this.symbolInstances.length&&!this.hasRTLText},sc.prototype.uploadPending=function(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload},sc.prototype.upload=function(t){!this.uploaded&&this.hasDebugData()&&(this.textCollisionBox.upload(t),this.iconCollisionBox.upload(t)),this.text.upload(t,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(t,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0},sc.prototype.destroyDebugData=function(){this.textCollisionBox.destroy(),this.iconCollisionBox.destroy()},sc.prototype.destroy=function(){this.text.destroy(),this.icon.destroy(),this.hasDebugData()&&this.destroyDebugData()},sc.prototype.addToLineVertexArray=function(t,e){var r=this.lineVertexArray.length;if(void 0!==t.segment){for(var n=t.dist(e[t.segment+1]),i=t.dist(e[t.segment]),a={},o=t.segment+1;o<e.length;o++)a[o]={x:e[o].x,y:e[o].y,tileUnitDistanceFromAnchor:n},o<e.length-1&&(n+=e[o+1].dist(e[o]));for(var s=t.segment||0;s>=0;s--)a[s]={x:e[s].x,y:e[s].y,tileUnitDistanceFromAnchor:i},s>0&&(i+=e[s-1].dist(e[s]));for(var l=0;l<e.length;l++){var u=a[l];this.lineVertexArray.emplaceBack(u.x,u.y,u.tileUnitDistanceFromAnchor)}}return{lineStartIndex:r,lineLength:this.lineVertexArray.length-r}},sc.prototype.addSymbols=function(t,e,r,n,i,a,o,s,l,u,c,f){for(var h=t.indexArray,p=t.layoutVertexArray,d=t.segments.prepareSegment(4*e.length,p,h,a.sortKey),v=this.glyphOffsetArray.length,g=d.vertexLength,y=this.allowVerticalPlacement&&o===nu.vertical?Math.PI/2:0,m=a.text&&a.text.sections,x=0;x<e.length;x++){var b=e[x],_=b.tl,w=b.tr,T=b.bl,k=b.br,A=b.tex,M=b.pixelOffsetTL,S=b.pixelOffsetBR,E=b.minFontScaleX,L=b.minFontScaleY,C=b.glyphOffset,P=b.isSDF,O=b.sectionIndex,I=d.vertexLength,D=C[1];rc(p,s.x,s.y,_.x,D+_.y,A.x,A.y,r,P,M.x,M.y,E,L),rc(p,s.x,s.y,w.x,D+w.y,A.x+A.w,A.y,r,P,S.x,M.y,E,L),rc(p,s.x,s.y,T.x,D+T.y,A.x,A.y+A.h,r,P,M.x,S.y,E,L),rc(p,s.x,s.y,k.x,D+k.y,A.x+A.w,A.y+A.h,r,P,S.x,S.y,E,L),nc(t.dynamicLayoutVertexArray,s,y),h.emplaceBack(I,I+1,I+2),h.emplaceBack(I+1,I+2,I+3),d.vertexLength+=4,d.primitiveLength+=2,this.glyphOffsetArray.emplaceBack(C[0]),x!==e.length-1&&O===e[x+1].sectionIndex||t.programConfigurations.populatePaintArrays(p.length,a,a.index,{},f,m&&m[O])}t.placedSymbolArray.emplaceBack(s.x,s.y,v,this.glyphOffsetArray.length-v,g,l,u,s.segment,r?r[0]:0,r?r[1]:0,n[0],n[1],o,0,!1,0,c)},sc.prototype._addCollisionDebugVertex=function(t,e,r,n,i,a){return e.emplaceBack(0,0),t.emplaceBack(r.x,r.y,n,i,Math.round(a.x),Math.round(a.y))},sc.prototype.addCollisionDebugVertices=function(t,e,r,n,i,o,s){var l=i.segments.prepareSegment(4,i.layoutVertexArray,i.indexArray),u=l.vertexLength,c=i.layoutVertexArray,f=i.collisionVertexArray,h=s.anchorX,p=s.anchorY;this._addCollisionDebugVertex(c,f,o,h,p,new a(t,e)),this._addCollisionDebugVertex(c,f,o,h,p,new a(r,e)),this._addCollisionDebugVertex(c,f,o,h,p,new a(r,n)),this._addCollisionDebugVertex(c,f,o,h,p,new a(t,n)),l.vertexLength+=4;var d=i.indexArray;d.emplaceBack(u,u+1),d.emplaceBack(u+1,u+2),d.emplaceBack(u+2,u+3),d.emplaceBack(u+3,u),l.primitiveLength+=4},sc.prototype.addDebugCollisionBoxes=function(t,e,r,n){for(var i=t;i<e;i++){var a=this.collisionBoxArray.get(i),o=a.x1,s=a.y1,l=a.x2,u=a.y2;this.addCollisionDebugVertices(o,s,l,u,n?this.textCollisionBox:this.iconCollisionBox,a.anchorPoint,r)}},sc.prototype.generateCollisionDebugBuffers=function(){this.hasDebugData()&&this.destroyDebugData(),this.textCollisionBox=new oc(la,bl.members,ya),this.iconCollisionBox=new oc(la,bl.members,ya);for(var t=0;t<this.symbolInstances.length;t++){var e=this.symbolInstances.get(t);this.addDebugCollisionBoxes(e.textBoxStartIndex,e.textBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.verticalTextBoxStartIndex,e.verticalTextBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.iconBoxStartIndex,e.iconBoxEndIndex,e,!1),this.addDebugCollisionBoxes(e.verticalIconBoxStartIndex,e.verticalIconBoxEndIndex,e,!1)}},sc.prototype._deserializeCollisionBoxesForSymbol=function(t,e,r,n,i,a,o,s,l){for(var u={},c=e;c<r;c++){var f=t.get(c);u.textBox={x1:f.x1,y1:f.y1,x2:f.x2,y2:f.y2,anchorPointX:f.anchorPointX,anchorPointY:f.anchorPointY},u.textFeatureIndex=f.featureIndex;break}for(var h=n;h<i;h++){var p=t.get(h);u.verticalTextBox={x1:p.x1,y1:p.y1,x2:p.x2,y2:p.y2,anchorPointX:p.anchorPointX,anchorPointY:p.anchorPointY},u.verticalTextFeatureIndex=p.featureIndex;break}for(var d=a;d<o;d++){var v=t.get(d);u.iconBox={x1:v.x1,y1:v.y1,x2:v.x2,y2:v.y2,anchorPointX:v.anchorPointX,anchorPointY:v.anchorPointY},u.iconFeatureIndex=v.featureIndex;break}for(var g=s;g<l;g++){var y=t.get(g);u.verticalIconBox={x1:y.x1,y1:y.y1,x2:y.x2,y2:y.y2,anchorPointX:y.anchorPointX,anchorPointY:y.anchorPointY},u.verticalIconFeatureIndex=y.featureIndex;break}return u},sc.prototype.deserializeCollisionBoxes=function(t){this.collisionArrays=[];for(var e=0;e<this.symbolInstances.length;e++){var r=this.symbolInstances.get(e);this.collisionArrays.push(this._deserializeCollisionBoxesForSymbol(t,r.textBoxStartIndex,r.textBoxEndIndex,r.verticalTextBoxStartIndex,r.verticalTextBoxEndIndex,r.iconBoxStartIndex,r.iconBoxEndIndex,r.verticalIconBoxStartIndex,r.verticalIconBoxEndIndex))}},sc.prototype.hasTextData=function(){return this.text.segments.get().length>0},sc.prototype.hasIconData=function(){return this.icon.segments.get().length>0},sc.prototype.hasDebugData=function(){return this.textCollisionBox&&this.iconCollisionBox},sc.prototype.hasTextCollisionBoxData=function(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0},sc.prototype.hasIconCollisionBoxData=function(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},sc.prototype.addIndicesForPlacedSymbol=function(t,e){for(var r=t.placedSymbolArray.get(e),n=r.vertexStartIndex+4*r.numGlyphs,i=r.vertexStartIndex;i<n;i+=4)t.indexArray.emplaceBack(i,i+1,i+2),t.indexArray.emplaceBack(i+1,i+2,i+3)},sc.prototype.getSortedSymbolIndexes=function(t){if(this.sortedAngle===t&&void 0!==this.symbolInstanceIndexes)return this.symbolInstanceIndexes;for(var e=Math.sin(t),r=Math.cos(t),n=[],i=[],a=[],o=0;o<this.symbolInstances.length;++o){a.push(o);var s=this.symbolInstances.get(o);n.push(0|Math.round(e*s.anchorX+r*s.anchorY)),i.push(s.featureIndex)}return a.sort((function(t,e){return n[t]-n[e]||i[e]-i[t]})),a},sc.prototype.addToSortKeyRanges=function(t,e){var r=this.sortKeyRanges[this.sortKeyRanges.length-1];r&&r.sortKey===e?r.symbolInstanceEnd=t+1:this.sortKeyRanges.push({sortKey:e,symbolInstanceStart:t,symbolInstanceEnd:t+1})},sc.prototype.sortFeatures=function(t){var e=this;if(this.sortFeaturesByY&&this.sortedAngle!==t&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var r=0,n=this.symbolInstanceIndexes;r<n.length;r+=1){var i=n[r],a=this.symbolInstances.get(i);this.featureSortOrder.push(a.featureIndex),[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t,r,n){t>=0&&n.indexOf(t)===r&&e.addIndicesForPlacedSymbol(e.text,t)})),a.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,a.verticalPlacedTextSymbolIndex),a.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.placedIconSymbolIndex),a.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},ni(\"SymbolBucket\",sc,{omit:[\"layers\",\"collisionBoxArray\",\"features\",\"compareText\"]}),sc.MAX_GLYPHS=65535,sc.addDynamicAttributes=nc;var lc=new Gi({\"symbol-placement\":new ji(Dt.layout_symbol[\"symbol-placement\"]),\"symbol-spacing\":new ji(Dt.layout_symbol[\"symbol-spacing\"]),\"symbol-avoid-edges\":new ji(Dt.layout_symbol[\"symbol-avoid-edges\"]),\"symbol-sort-key\":new Ui(Dt.layout_symbol[\"symbol-sort-key\"]),\"symbol-z-order\":new ji(Dt.layout_symbol[\"symbol-z-order\"]),\"icon-allow-overlap\":new ji(Dt.layout_symbol[\"icon-allow-overlap\"]),\"icon-ignore-placement\":new ji(Dt.layout_symbol[\"icon-ignore-placement\"]),\"icon-optional\":new ji(Dt.layout_symbol[\"icon-optional\"]),\"icon-rotation-alignment\":new ji(Dt.layout_symbol[\"icon-rotation-alignment\"]),\"icon-size\":new Ui(Dt.layout_symbol[\"icon-size\"]),\"icon-text-fit\":new ji(Dt.layout_symbol[\"icon-text-fit\"]),\"icon-text-fit-padding\":new ji(Dt.layout_symbol[\"icon-text-fit-padding\"]),\"icon-image\":new Ui(Dt.layout_symbol[\"icon-image\"]),\"icon-rotate\":new Ui(Dt.layout_symbol[\"icon-rotate\"]),\"icon-padding\":new ji(Dt.layout_symbol[\"icon-padding\"]),\"icon-keep-upright\":new ji(Dt.layout_symbol[\"icon-keep-upright\"]),\"icon-offset\":new Ui(Dt.layout_symbol[\"icon-offset\"]),\"icon-anchor\":new Ui(Dt.layout_symbol[\"icon-anchor\"]),\"icon-pitch-alignment\":new ji(Dt.layout_symbol[\"icon-pitch-alignment\"]),\"text-pitch-alignment\":new ji(Dt.layout_symbol[\"text-pitch-alignment\"]),\"text-rotation-alignment\":new ji(Dt.layout_symbol[\"text-rotation-alignment\"]),\"text-field\":new Ui(Dt.layout_symbol[\"text-field\"]),\"text-font\":new Ui(Dt.layout_symbol[\"text-font\"]),\"text-size\":new Ui(Dt.layout_symbol[\"text-size\"]),\"text-max-width\":new Ui(Dt.layout_symbol[\"text-max-width\"]),\"text-line-height\":new ji(Dt.layout_symbol[\"text-line-height\"]),\"text-letter-spacing\":new Ui(Dt.layout_symbol[\"text-letter-spacing\"]),\"text-justify\":new Ui(Dt.layout_symbol[\"text-justify\"]),\"text-radial-offset\":new Ui(Dt.layout_symbol[\"text-radial-offset\"]),\"text-variable-anchor\":new ji(Dt.layout_symbol[\"text-variable-anchor\"]),\"text-anchor\":new Ui(Dt.layout_symbol[\"text-anchor\"]),\"text-max-angle\":new ji(Dt.layout_symbol[\"text-max-angle\"]),\"text-writing-mode\":new ji(Dt.layout_symbol[\"text-writing-mode\"]),\"text-rotate\":new Ui(Dt.layout_symbol[\"text-rotate\"]),\"text-padding\":new ji(Dt.layout_symbol[\"text-padding\"]),\"text-keep-upright\":new ji(Dt.layout_symbol[\"text-keep-upright\"]),\"text-transform\":new Ui(Dt.layout_symbol[\"text-transform\"]),\"text-offset\":new Ui(Dt.layout_symbol[\"text-offset\"]),\"text-allow-overlap\":new ji(Dt.layout_symbol[\"text-allow-overlap\"]),\"text-ignore-placement\":new ji(Dt.layout_symbol[\"text-ignore-placement\"]),\"text-optional\":new ji(Dt.layout_symbol[\"text-optional\"])}),uc={paint:new Gi({\"icon-opacity\":new Ui(Dt.paint_symbol[\"icon-opacity\"]),\"icon-color\":new Ui(Dt.paint_symbol[\"icon-color\"]),\"icon-halo-color\":new Ui(Dt.paint_symbol[\"icon-halo-color\"]),\"icon-halo-width\":new Ui(Dt.paint_symbol[\"icon-halo-width\"]),\"icon-halo-blur\":new Ui(Dt.paint_symbol[\"icon-halo-blur\"]),\"icon-translate\":new ji(Dt.paint_symbol[\"icon-translate\"]),\"icon-translate-anchor\":new ji(Dt.paint_symbol[\"icon-translate-anchor\"]),\"text-opacity\":new Ui(Dt.paint_symbol[\"text-opacity\"]),\"text-color\":new Ui(Dt.paint_symbol[\"text-color\"],{runtimeType:Zt,getOverride:function(t){return t.textColor},hasOverride:function(t){return!!t.textColor}}),\"text-halo-color\":new Ui(Dt.paint_symbol[\"text-halo-color\"]),\"text-halo-width\":new Ui(Dt.paint_symbol[\"text-halo-width\"]),\"text-halo-blur\":new Ui(Dt.paint_symbol[\"text-halo-blur\"]),\"text-translate\":new ji(Dt.paint_symbol[\"text-translate\"]),\"text-translate-anchor\":new ji(Dt.paint_symbol[\"text-translate-anchor\"])}),layout:lc},cc=function(t){this.type=t.property.overrides?t.property.overrides.runtimeType:Vt,this.defaultValue=t};cc.prototype.evaluate=function(t){if(t.formattedSection){var e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default},cc.prototype.eachChild=function(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)},cc.prototype.outputDefined=function(){return!1},cc.prototype.serialize=function(){return null},ni(\"FormatSectionOverride\",cc,{omit:[\"defaultValue\"]});var fc=function(t){function e(e){t.call(this,e,uc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.recalculate=function(e,r){if(t.prototype.recalculate.call(this,e,r),\"auto\"===this.layout.get(\"icon-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"icon-rotation-alignment\"]=\"map\":this.layout._values[\"icon-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"text-rotation-alignment\"]=\"map\":this.layout._values[\"text-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-pitch-alignment\")&&(this.layout._values[\"text-pitch-alignment\"]=this.layout.get(\"text-rotation-alignment\")),\"auto\"===this.layout.get(\"icon-pitch-alignment\")&&(this.layout._values[\"icon-pitch-alignment\"]=this.layout.get(\"icon-rotation-alignment\")),\"point\"===this.layout.get(\"symbol-placement\")){var n=this.layout.get(\"text-writing-mode\");if(n){for(var i=[],a=0,o=n;a<o.length;a+=1){var s=o[a];i.indexOf(s)<0&&i.push(s)}this.layout._values[\"text-writing-mode\"]=i}else this.layout._values[\"text-writing-mode\"]=[\"horizontal\"]}this._setPaintOverrides()},e.prototype.getValueAndResolveTokens=function(t,e,r,n){var i=this.layout.get(t).evaluate(e,{},r,n),a=this._unevaluatedLayout._values[t];return a.isDataDriven()||sn(a.value)||!i?i:function(t,e){return e.replace(/{([^{}]+)}/g,(function(e,r){return r in t?String(t[r]):\"\"}))}(e.properties,i)},e.prototype.createBucket=function(t){return new sc(t)},e.prototype.queryRadius=function(){return 0},e.prototype.queryIntersectsFeature=function(){return!1},e.prototype._setPaintOverrides=function(){for(var t=0,r=uc.paint.overridableProperties;t<r.length;t+=1){var n=r[t];if(e.hasPaintOverride(this.layout,n)){var i,a=this.paint.get(n),o=new cc(a),s=new on(o,a.property.specification);i=\"constant\"===a.value.kind||\"source\"===a.value.kind?new un(\"source\",s):new cn(\"composite\",s,a.value.zoomStops,a.value._interpolationType),this.paint._values[n]=new Bi(a.property,i,a.parameters)}}},e.prototype._handleOverridablePaintPropertyUpdate=function(t,r,n){return!(!this.layout||r.isDataDriven()||n.isDataDriven())&&e.hasPaintOverride(this.layout,t)},e.hasPaintOverride=function(t,e){var r=t.get(\"text-field\"),n=uc.paint.properties[e],i=!1,a=function(t){for(var e=0,r=t;e<r.length;e+=1){var a=r[e];if(n.overrides&&n.overrides.hasOverride(a))return void(i=!0)}};if(\"constant\"===r.value.kind&&r.value.value instanceof ue)a(r.value.value.sections);else if(\"source\"===r.value.kind){var o=function(t){if(!i)if(t instanceof ve&&pe(t.value)===Jt){var e=t.value;a(e.sections)}else t instanceof xe?a(t.sections):t.eachChild(o)},s=r.value;s._styleExpression&&o(s._styleExpression.expression)}return i},e}(Yi),hc={paint:new Gi({\"background-color\":new ji(Dt.paint_background[\"background-color\"]),\"background-pattern\":new Hi(Dt.paint_background[\"background-pattern\"]),\"background-opacity\":new ji(Dt.paint_background[\"background-opacity\"])})},pc=function(t){function e(e){t.call(this,e,hc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Yi),dc={paint:new Gi({\"raster-opacity\":new ji(Dt.paint_raster[\"raster-opacity\"]),\"raster-hue-rotate\":new ji(Dt.paint_raster[\"raster-hue-rotate\"]),\"raster-brightness-min\":new ji(Dt.paint_raster[\"raster-brightness-min\"]),\"raster-brightness-max\":new ji(Dt.paint_raster[\"raster-brightness-max\"]),\"raster-saturation\":new ji(Dt.paint_raster[\"raster-saturation\"]),\"raster-contrast\":new ji(Dt.paint_raster[\"raster-contrast\"]),\"raster-resampling\":new ji(Dt.paint_raster[\"raster-resampling\"]),\"raster-fade-duration\":new ji(Dt.paint_raster[\"raster-fade-duration\"])})},vc=function(t){function e(e){t.call(this,e,dc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Yi);var gc=function(t){function e(e){t.call(this,e,{}),this.implementation=e}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.is3D=function(){return\"3d\"===this.implementation.renderingMode},e.prototype.hasOffscreenPass=function(){return void 0!==this.implementation.prerender},e.prototype.recalculate=function(){},e.prototype.updateTransitions=function(){},e.prototype.hasTransition=function(){},e.prototype.serialize=function(){},e.prototype.onAdd=function(t){this.implementation.onAdd&&this.implementation.onAdd(t,t.painter.context.gl)},e.prototype.onRemove=function(t){this.implementation.onRemove&&this.implementation.onRemove(t,t.painter.context.gl)},e}(Yi),yc={circle:Uo,heatmap:Ko,hillshade:Qo,fill:js,\"fill-extrusion\":nl,line:vl,symbol:fc,background:pc,raster:vc};var mc=self.HTMLImageElement,xc=self.HTMLCanvasElement,bc=self.HTMLVideoElement,_c=self.ImageData,wc=self.ImageBitmap,Tc=function(t,e,r,n){this.context=t,this.format=r,this.texture=t.gl.createTexture(),this.update(e,n)};Tc.prototype.update=function(t,e,r){var n=t.width,i=t.height,a=!(this.size&&this.size[0]===n&&this.size[1]===i||r),o=this.context,s=o.gl;if(this.useMipmap=Boolean(e&&e.useMipmap),s.bindTexture(s.TEXTURE_2D,this.texture),o.pixelStoreUnpackFlipY.set(!1),o.pixelStoreUnpack.set(1),o.pixelStoreUnpackPremultiplyAlpha.set(this.format===s.RGBA&&(!e||!1!==e.premultiply)),a)this.size=[n,i],t instanceof mc||t instanceof xc||t instanceof bc||t instanceof _c||wc&&t instanceof wc?s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,s.UNSIGNED_BYTE,t):s.texImage2D(s.TEXTURE_2D,0,this.format,n,i,0,this.format,s.UNSIGNED_BYTE,t.data);else{var l=r||{x:0,y:0},u=l.x,c=l.y;t instanceof mc||t instanceof xc||t instanceof bc||t instanceof _c||wc&&t instanceof wc?s.texSubImage2D(s.TEXTURE_2D,0,u,c,s.RGBA,s.UNSIGNED_BYTE,t):s.texSubImage2D(s.TEXTURE_2D,0,u,c,n,i,s.RGBA,s.UNSIGNED_BYTE,t.data)}this.useMipmap&&this.isSizePowerOfTwo()&&s.generateMipmap(s.TEXTURE_2D)},Tc.prototype.bind=function(t,e,r){var n=this.context.gl;n.bindTexture(n.TEXTURE_2D,this.texture),r!==n.LINEAR_MIPMAP_NEAREST||this.isSizePowerOfTwo()||(r=n.LINEAR),t!==this.filter&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,t),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,r||t),this.filter=t),e!==this.wrap&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,e),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,e),this.wrap=e)},Tc.prototype.isSizePowerOfTwo=function(){return this.size[0]===this.size[1]&&Math.log(this.size[0])/Math.LN2%1==0},Tc.prototype.destroy=function(){this.context.gl.deleteTexture(this.texture),this.texture=null};var kc=function(t){var e=this;this._callback=t,this._triggered=!1,\"undefined\"!=typeof MessageChannel&&(this._channel=new MessageChannel,this._channel.port2.onmessage=function(){e._triggered=!1,e._callback()})};kc.prototype.trigger=function(){var t=this;this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout((function(){t._triggered=!1,t._callback()}),0))},kc.prototype.remove=function(){delete this._channel,this._callback=function(){}};var Ac=function(t,e,r){this.target=t,this.parent=e,this.mapId=r,this.callbacks={},this.tasks={},this.taskQueue=[],this.cancelCallbacks={},g([\"receive\",\"process\"],this),this.invoker=new kc(this.process),this.target.addEventListener(\"message\",this.receive,!1),this.globalScope=A()?t:self};function Mc(t,e,r){var n=2*Math.PI*6378137/256/Math.pow(2,r);return[t*n-2*Math.PI*6378137/2,e*n-2*Math.PI*6378137/2]}Ac.prototype.send=function(t,e,r,n,i){var a=this;void 0===i&&(i=!1);var o=Math.round(1e18*Math.random()).toString(36).substring(0,10);r&&(this.callbacks[o]=r);var s=E(this.globalScope)?void 0:[];return this.target.postMessage({id:o,type:t,hasCallback:!!r,targetMapId:n,mustQueue:i,sourceMapId:this.mapId,data:si(e,s)},s),{cancel:function(){r&&delete a.callbacks[o],a.target.postMessage({id:o,type:\"<cancel>\",targetMapId:n,sourceMapId:a.mapId})}}},Ac.prototype.receive=function(t){var e=t.data,r=e.id;if(r&&(!e.targetMapId||this.mapId===e.targetMapId))if(\"<cancel>\"===e.type){delete this.tasks[r];var n=this.cancelCallbacks[r];delete this.cancelCallbacks[r],n&&n()}else A()||e.mustQueue?(this.tasks[r]=e,this.taskQueue.push(r),this.invoker.trigger()):this.processTask(r,e)},Ac.prototype.process=function(){if(this.taskQueue.length){var t=this.taskQueue.shift(),e=this.tasks[t];delete this.tasks[t],this.taskQueue.length&&this.invoker.trigger(),e&&this.processTask(t,e)}},Ac.prototype.processTask=function(t,e){var r=this;if(\"<response>\"===e.type){var n=this.callbacks[t];delete this.callbacks[t],n&&(e.error?n(li(e.error)):n(null,li(e.data)))}else{var i=!1,a=E(this.globalScope)?void 0:[],o=e.hasCallback?function(e,n){i=!0,delete r.cancelCallbacks[t],r.target.postMessage({id:t,type:\"<response>\",sourceMapId:r.mapId,error:e?si(e):null,data:si(n,a)},a)}:function(t){i=!0},s=null,l=li(e.data);if(this.parent[e.type])s=this.parent[e.type](e.sourceMapId,l,o);else if(this.parent.getWorkerSource){var u=e.type.split(\".\");s=this.parent.getWorkerSource(e.sourceMapId,u[0],l.source)[u[1]](l,o)}else o(new Error(\"Could not find function \"+e.type));!i&&s&&s.cancel&&(this.cancelCallbacks[t]=s.cancel)}},Ac.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener(\"message\",this.receive,!1)};var Sc=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Sc.prototype.setNorthEast=function(t){return this._ne=t instanceof Lc?new Lc(t.lng,t.lat):Lc.convert(t),this},Sc.prototype.setSouthWest=function(t){return this._sw=t instanceof Lc?new Lc(t.lng,t.lat):Lc.convert(t),this},Sc.prototype.extend=function(t){var e,r,n=this._sw,i=this._ne;if(t instanceof Lc)e=t,r=t;else{if(!(t instanceof Sc)){if(Array.isArray(t)){if(4===t.length||t.every(Array.isArray)){var a=t;return this.extend(Sc.convert(a))}var o=t;return this.extend(Lc.convert(o))}return this}if(e=t._sw,r=t._ne,!e||!r)return this}return n||i?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),i.lng=Math.max(r.lng,i.lng),i.lat=Math.max(r.lat,i.lat)):(this._sw=new Lc(e.lng,e.lat),this._ne=new Lc(r.lng,r.lat)),this},Sc.prototype.getCenter=function(){return new Lc((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Sc.prototype.getSouthWest=function(){return this._sw},Sc.prototype.getNorthEast=function(){return this._ne},Sc.prototype.getNorthWest=function(){return new Lc(this.getWest(),this.getNorth())},Sc.prototype.getSouthEast=function(){return new Lc(this.getEast(),this.getSouth())},Sc.prototype.getWest=function(){return this._sw.lng},Sc.prototype.getSouth=function(){return this._sw.lat},Sc.prototype.getEast=function(){return this._ne.lng},Sc.prototype.getNorth=function(){return this._ne.lat},Sc.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Sc.prototype.toString=function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"},Sc.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Sc.prototype.contains=function(t){var e=Lc.convert(t),r=e.lng,n=e.lat,i=this._sw.lat<=n&&n<=this._ne.lat,a=this._sw.lng<=r&&r<=this._ne.lng;return this._sw.lng>this._ne.lng&&(a=this._sw.lng>=r&&r>=this._ne.lng),i&&a},Sc.convert=function(t){return!t||t instanceof Sc?t:new Sc(t)};var Ec=6371008.8,Lc=function(t,e){if(isNaN(t)||isNaN(e))throw new Error(\"Invalid LngLat object: (\"+t+\", \"+e+\")\");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")};Lc.prototype.wrap=function(){return new Lc(c(this.lng,-180,180),this.lat)},Lc.prototype.toArray=function(){return[this.lng,this.lat]},Lc.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},Lc.prototype.distanceTo=function(t){var e=Math.PI/180,r=this.lat*e,n=t.lat*e,i=Math.sin(r)*Math.sin(n)+Math.cos(r)*Math.cos(n)*Math.cos((t.lng-this.lng)*e);return Ec*Math.acos(Math.min(i,1))},Lc.prototype.toBounds=function(t){void 0===t&&(t=0);var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Sc(new Lc(this.lng-r,this.lat-e),new Lc(this.lng+r,this.lat+e))},Lc.convert=function(t){if(t instanceof Lc)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new Lc(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&\"object\"==typeof t&&null!==t)return new Lc(Number(\"lng\"in t?t.lng:t.lon),Number(t.lat));throw new Error(\"`LngLatLike` argument must be specified as a LngLat instance, an object {lng: <lng>, lat: <lat>}, an object {lon: <lng>, lat: <lat>}, or an array of [<lng>, <lat>]\")};var Cc=2*Math.PI*Ec;function Pc(t){return Cc*Math.cos(t*Math.PI/180)}function Oc(t){return(180+t)/360}function Ic(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Dc(t,e){return t/Pc(e)}function zc(t){var e=180-360*t;return 360/Math.PI*Math.atan(Math.exp(e*Math.PI/180))-90}var Rc=function(t,e,r){void 0===r&&(r=0),this.x=+t,this.y=+e,this.z=+r};Rc.fromLngLat=function(t,e){void 0===e&&(e=0);var r=Lc.convert(t);return new Rc(Oc(r.lng),Ic(r.lat),Dc(e,r.lat))},Rc.prototype.toLngLat=function(){return new Lc(360*this.x-180,zc(this.y))},Rc.prototype.toAltitude=function(){return t=this.z,e=this.y,t*Pc(zc(e));var t,e},Rc.prototype.meterInMercatorCoordinateUnits=function(){return 1/Cc*(t=zc(this.y),1/Math.cos(t*Math.PI/180));var t};var Fc=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=jc(0,t,t,e,r)};Fc.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},Fc.prototype.url=function(t,e){var r,n,i,a,o,s=(r=this.x,n=this.y,i=this.z,a=Mc(256*r,256*(n=Math.pow(2,i)-n-1),i),o=Mc(256*(r+1),256*(n+1),i),a[0]+\",\"+a[1]+\",\"+o[0]+\",\"+o[1]),l=function(t,e,r){for(var n,i=\"\",a=t;a>0;a--)i+=(e&(n=1<<a-1)?1:0)+(r&n?2:0);return i}(this.z,this.x,this.y);return t[(this.x+this.y)%t.length].replace(\"{prefix}\",(this.x%16).toString(16)+(this.y%16).toString(16)).replace(\"{z}\",String(this.z)).replace(\"{x}\",String(this.x)).replace(\"{y}\",String(\"tms\"===e?Math.pow(2,this.z)-this.y-1:this.y)).replace(\"{quadkey}\",l).replace(\"{bbox-epsg-3857}\",s)},Fc.prototype.getTilePoint=function(t){var e=Math.pow(2,this.z);return new a((t.x*e-this.x)*co,(t.y*e-this.y)*co)},Fc.prototype.toString=function(){return this.z+\"/\"+this.x+\"/\"+this.y};var Bc=function(t,e){this.wrap=t,this.canonical=e,this.key=jc(t,e.z,e.z,e.x,e.y)},Nc=function(t,e,r,n,i){this.overscaledZ=t,this.wrap=e,this.canonical=new Fc(r,+n,+i),this.key=jc(e,t,r,n,i)};function jc(t,e,r,n,i){(t*=2)<0&&(t=-1*t-1);var a=1<<r;return(a*a*t+a*i+n).toString(36)+r.toString(36)+e.toString(36)}Nc.prototype.equals=function(t){return this.overscaledZ===t.overscaledZ&&this.wrap===t.wrap&&this.canonical.equals(t.canonical)},Nc.prototype.scaledTo=function(t){var e=this.canonical.z-t;return t>this.canonical.z?new Nc(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new Nc(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},Nc.prototype.calculateScaledKey=function(t,e){var r=this.canonical.z-t;return t>this.canonical.z?jc(this.wrap*+e,t,this.canonical.z,this.canonical.x,this.canonical.y):jc(this.wrap*+e,t,t,this.canonical.x>>r,this.canonical.y>>r)},Nc.prototype.isChildOf=function(t){if(t.wrap!==this.wrap)return!1;var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ<this.overscaledZ&&t.canonical.x===this.canonical.x>>e&&t.canonical.y===this.canonical.y>>e},Nc.prototype.children=function(t){if(this.overscaledZ>=t)return[new Nc(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new Nc(e,this.wrap,e,r,n),new Nc(e,this.wrap,e,r+1,n),new Nc(e,this.wrap,e,r,n+1),new Nc(e,this.wrap,e,r+1,n+1)]},Nc.prototype.isLessThan=function(t){return this.wrap<t.wrap||!(this.wrap>t.wrap)&&(this.overscaledZ<t.overscaledZ||!(this.overscaledZ>t.overscaledZ)&&(this.canonical.x<t.canonical.x||!(this.canonical.x>t.canonical.x)&&this.canonical.y<t.canonical.y))},Nc.prototype.wrapped=function(){return new Nc(this.overscaledZ,0,this.canonical.z,this.canonical.x,this.canonical.y)},Nc.prototype.unwrapTo=function(t){return new Nc(this.overscaledZ,t,this.canonical.z,this.canonical.x,this.canonical.y)},Nc.prototype.overscaleFactor=function(){return Math.pow(2,this.overscaledZ-this.canonical.z)},Nc.prototype.toUnwrapped=function(){return new Bc(this.wrap,this.canonical)},Nc.prototype.toString=function(){return this.overscaledZ+\"/\"+this.canonical.x+\"/\"+this.canonical.y},Nc.prototype.getTilePoint=function(t){return this.canonical.getTilePoint(new Rc(t.x-this.wrap,t.y))},ni(\"CanonicalTileID\",Fc),ni(\"OverscaledTileID\",Nc,{omit:[\"posMatrix\"]});var Uc=function(t,e,r){if(this.uid=t,e.height!==e.width)throw new RangeError(\"DEM tiles must be square\");if(r&&\"mapbox\"!==r&&\"terrarium\"!==r)return w('\"'+r+'\" is not a valid encoding type. Valid types include \"mapbox\" and \"terrarium\".');this.stride=e.height;var n=this.dim=e.height-2;this.data=new Uint32Array(e.data.buffer),this.encoding=r||\"mapbox\";for(var i=0;i<n;i++)this.data[this._idx(-1,i)]=this.data[this._idx(0,i)],this.data[this._idx(n,i)]=this.data[this._idx(n-1,i)],this.data[this._idx(i,-1)]=this.data[this._idx(i,0)],this.data[this._idx(i,n)]=this.data[this._idx(i,n-1)];this.data[this._idx(-1,-1)]=this.data[this._idx(0,0)],this.data[this._idx(n,-1)]=this.data[this._idx(n-1,0)],this.data[this._idx(-1,n)]=this.data[this._idx(0,n-1)],this.data[this._idx(n,n)]=this.data[this._idx(n-1,n-1)]};Uc.prototype.get=function(t,e){var r=new Uint8Array(this.data.buffer),n=4*this._idx(t,e);return(\"terrarium\"===this.encoding?this._unpackTerrarium:this._unpackMapbox)(r[n],r[n+1],r[n+2])},Uc.prototype.getUnpackVector=function(){return\"terrarium\"===this.encoding?[256,1,1/256,32768]:[6553.6,25.6,.1,1e4]},Uc.prototype._idx=function(t,e){if(t<-1||t>=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError(\"out of range source coordinates for DEM data\");return(e+1)*this.stride+(t+1)},Uc.prototype._unpackMapbox=function(t,e,r){return(256*t*256+256*e+r)/10-1e4},Uc.prototype._unpackTerrarium=function(t,e,r){return 256*t+e+r/256-32768},Uc.prototype.getPixels=function(){return new Wo({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},Uc.prototype.backfillBorder=function(t,e,r){if(this.dim!==t.dim)throw new Error(\"dem dimension mismatch\");var n=e*this.dim,i=e*this.dim+this.dim,a=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=i-1;break;case 1:i=n+1}switch(r){case-1:a=o-1;break;case 1:o=a+1}for(var s=-e*this.dim,l=-r*this.dim,u=a;u<o;u++)for(var c=n;c<i;c++)this.data[this._idx(c,u)]=t.data[this._idx(c+s,u+l)]},ni(\"DEMData\",Uc);var Vc=function(t){this._stringToNumber={},this._numberToString=[];for(var e=0;e<t.length;e++){var r=t[e];this._stringToNumber[r]=e,this._numberToString[e]=r}};Vc.prototype.encode=function(t){return this._stringToNumber[t]},Vc.prototype.decode=function(t){return this._numberToString[t]};var Hc=function(t,e,r,n,i){this.type=\"Feature\",this._vectorTileFeature=t,t._z=e,t._x=r,t._y=n,this.properties=t.properties,this.id=i},qc={geometry:{configurable:!0}};qc.geometry.get=function(){return void 0===this._geometry&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry},qc.geometry.set=function(t){this._geometry=t},Hc.prototype.toJSON=function(){var t={geometry:this.geometry};for(var e in this)\"_geometry\"!==e&&\"_vectorTileFeature\"!==e&&(t[e]=this[e]);return t},Object.defineProperties(Hc.prototype,qc);var Gc=function(){this.state={},this.stateChanges={},this.deletedStates={}};Gc.prototype.updateState=function(t,e,r){var n=String(e);if(this.stateChanges[t]=this.stateChanges[t]||{},this.stateChanges[t][n]=this.stateChanges[t][n]||{},f(this.stateChanges[t][n],r),null===this.deletedStates[t])for(var i in this.deletedStates[t]={},this.state[t])i!==n&&(this.deletedStates[t][i]=null);else if(this.deletedStates[t]&&null===this.deletedStates[t][n])for(var a in this.deletedStates[t][n]={},this.state[t][n])r[a]||(this.deletedStates[t][n][a]=null);else for(var o in r)this.deletedStates[t]&&this.deletedStates[t][n]&&null===this.deletedStates[t][n][o]&&delete this.deletedStates[t][n][o]},Gc.prototype.removeFeatureState=function(t,e,r){if(null!==this.deletedStates[t]){var n=String(e);if(this.deletedStates[t]=this.deletedStates[t]||{},r&&void 0!==e)null!==this.deletedStates[t][n]&&(this.deletedStates[t][n]=this.deletedStates[t][n]||{},this.deletedStates[t][n][r]=null);else if(void 0!==e)if(this.stateChanges[t]&&this.stateChanges[t][n])for(r in this.deletedStates[t][n]={},this.stateChanges[t][n])this.deletedStates[t][n][r]=null;else this.deletedStates[t][n]=null;else this.deletedStates[t]=null}},Gc.prototype.getState=function(t,e){var r=String(e),n=this.state[t]||{},i=this.stateChanges[t]||{},a=f({},n[r],i[r]);if(null===this.deletedStates[t])return{};if(this.deletedStates[t]){var o=this.deletedStates[t][e];if(null===o)return{};for(var s in o)delete a[s]}return a},Gc.prototype.initializeTileState=function(t,e){t.setFeatureState(this.state,e)},Gc.prototype.coalesceChanges=function(t,e){var r={};for(var n in this.stateChanges){this.state[n]=this.state[n]||{};var i={};for(var a in this.stateChanges[n])this.state[n][a]||(this.state[n][a]={}),f(this.state[n][a],this.stateChanges[n][a]),i[a]=this.state[n][a];r[n]=i}for(var o in this.deletedStates){this.state[o]=this.state[o]||{};var s={};if(null===this.deletedStates[o])for(var l in this.state[o])s[l]={},this.state[o][l]={};else for(var u in this.deletedStates[o]){if(null===this.deletedStates[o][u])this.state[o][u]={};else for(var c=0,h=Object.keys(this.deletedStates[o][u]);c<h.length;c+=1){var p=h[c];delete this.state[o][u][p]}s[u]=this.state[o][u]}r[o]=r[o]||{},f(r[o],s)}if(this.stateChanges={},this.deletedStates={},0!==Object.keys(r).length)for(var d in t)t[d].setFeatureState(r,e)};var Zc=function(t,e){this.tileID=t,this.x=t.canonical.x,this.y=t.canonical.y,this.z=t.canonical.z,this.grid=new Kn(co,16,0),this.grid3D=new Kn(co,16,0),this.featureIndexArray=new Ca,this.promoteId=e};function Yc(t,e,r,n,i){return m(t,(function(t,a){var o=e instanceof Ni?e.get(a):null;return o&&o.evaluate?o.evaluate(r,n,i):o}))}function Wc(t){for(var e=1/0,r=1/0,n=-1/0,i=-1/0,a=0,o=t;a<o.length;a+=1){var s=o[a];e=Math.min(e,s.x),r=Math.min(r,s.y),n=Math.max(n,s.x),i=Math.max(i,s.y)}return{minX:e,minY:r,maxX:n,maxY:i}}function Xc(t,e){return e-t}Zc.prototype.insert=function(t,e,r,n,i,a){var o=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(r,n,i);for(var s=a?this.grid3D:this.grid,l=0;l<e.length;l++){for(var u=e[l],c=[1/0,1/0,-1/0,-1/0],f=0;f<u.length;f++){var h=u[f];c[0]=Math.min(c[0],h.x),c[1]=Math.min(c[1],h.y),c[2]=Math.max(c[2],h.x),c[3]=Math.max(c[3],h.y)}c[0]<co&&c[1]<co&&c[2]>=0&&c[3]>=0&&s.insert(o,c[0],c[1],c[2],c[3])}},Zc.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new Js.VectorTile(new Sl(this.rawTileData)).layers,this.sourceLayerCoder=new Vc(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"])),this.vtLayers},Zc.prototype.query=function(t,e,r,n){var i=this;this.loadVTLayers();for(var o=t.params||{},s=co/t.tileSize/t.scale,l=wn(o.filter),u=t.queryGeometry,c=t.queryPadding*s,f=Wc(u),h=this.grid.query(f.minX-c,f.minY-c,f.maxX+c,f.maxY+c),p=Wc(t.cameraQueryGeometry),d=0,v=this.grid3D.query(p.minX-c,p.minY-c,p.maxX+c,p.maxY+c,(function(e,r,n,i){return function(t,e,r,n,i){for(var o=0,s=t;o<s.length;o+=1){var l=s[o];if(e<=l.x&&r<=l.y&&n>=l.x&&i>=l.y)return!0}var u=[new a(e,r),new a(e,i),new a(n,i),new a(n,r)];if(t.length>2)for(var c=0,f=u;c<f.length;c+=1)if(Mo(t,f[c]))return!0;for(var h=0;h<t.length-1;h++)if(So(t[h],t[h+1],u))return!0;return!1}(t.cameraQueryGeometry,e-c,r-c,n+c,i+c)}));d<v.length;d+=1){var g=v[d];h.push(g)}h.sort(Xc);for(var y,m={},x=function(a){var c=h[a];if(c!==y){y=c;var f=i.featureIndexArray.get(c),p=null;i.loadMatchingFeature(m,f.bucketIndex,f.sourceLayerIndex,f.featureIndex,l,o.layers,o.availableImages,e,r,n,(function(e,r,n){return p||(p=po(e)),r.queryIntersectsFeature(u,e,n,p,i.z,t.transform,s,t.pixelPosMatrix)}))}},b=0;b<h.length;b++)x(b);return m},Zc.prototype.loadMatchingFeature=function(t,e,r,n,i,a,o,s,l,u,c){var f=this.bucketLayerIDs[e];if(!a||function(t,e){for(var r=0;r<t.length;r++)if(e.indexOf(t[r])>=0)return!0;return!1}(a,f)){var h=this.sourceLayerCoder.decode(r),p=this.vtLayers[h].feature(n);if(i.filter(new Pi(this.tileID.overscaledZ),p))for(var d=this.getId(p,h),v=0;v<f.length;v++){var g=f[v];if(!(a&&a.indexOf(g)<0)){var y=s[g];if(y){var m={};void 0!==d&&u&&(m=u.getState(y.sourceLayer||\"_geojsonTileLayer\",d));var x=l[g];x.paint=Yc(x.paint,y.paint,p,m,o),x.layout=Yc(x.layout,y.layout,p,m,o);var b=!c||c(p,y,m);if(b){var _=new Hc(p,this.z,this.x,this.y,d);_.layer=x;var w=t[g];void 0===w&&(w=t[g]=[]),w.push({featureIndex:n,feature:_,intersectionZ:b})}}}}}},Zc.prototype.lookupSymbolFeatures=function(t,e,r,n,i,a,o,s){var l={};this.loadVTLayers();for(var u=wn(i),c=0,f=t;c<f.length;c+=1){var h=f[c];this.loadMatchingFeature(l,r,n,h,u,a,o,s,e)}return l},Zc.prototype.hasLayer=function(t){for(var e=0,r=this.bucketLayerIDs;e<r.length;e+=1)for(var n=0,i=r[e];n<i.length;n+=1)if(t===i[n])return!0;return!1},Zc.prototype.getId=function(t,e){var r=t.id;if(this.promoteId){var n=\"string\"==typeof this.promoteId?this.promoteId:this.promoteId[e];\"boolean\"==typeof(r=t.properties[n])&&(r=Number(r))}return r},ni(\"FeatureIndex\",Zc,{omit:[\"rawTileData\",\"sourceLayerCoder\"]});var Jc=function(t,e){this.tileID=t,this.uid=p(),this.uses=0,this.tileSize=e,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.hasRTLText=!1,this.dependencies={},this.expiredRequestCount=0,this.state=\"loading\"};Jc.prototype.registerFadeDuration=function(t){var e=t+this.timeAdded;e<F.now()||this.fadeEndTime&&e<this.fadeEndTime||(this.fadeEndTime=e)},Jc.prototype.wasRequested=function(){return\"errored\"===this.state||\"loaded\"===this.state||\"reloading\"===this.state},Jc.prototype.loadVectorData=function(t,e,r){if(this.hasData()&&this.unloadVectorData(),this.state=\"loaded\",t){for(var n in t.featureIndex&&(this.latestFeatureIndex=t.featureIndex,t.rawTileData?(this.latestRawTileData=t.rawTileData,this.latestFeatureIndex.rawTileData=t.rawTileData):this.latestRawTileData&&(this.latestFeatureIndex.rawTileData=this.latestRawTileData)),this.collisionBoxArray=t.collisionBoxArray,this.buckets=function(t,e){var r={};if(!e)return r;for(var n=function(){var t=a[i],n=t.layerIds.map((function(t){return e.getLayer(t)})).filter(Boolean);if(0!==n.length){t.layers=n,t.stateDependentLayerIds&&(t.stateDependentLayers=t.stateDependentLayerIds.map((function(t){return n.filter((function(e){return e.id===t}))[0]})));for(var o=0,s=n;o<s.length;o+=1){var l=s[o];r[l.id]=t}}},i=0,a=t;i<a.length;i+=1)n();return r}(t.buckets,e.style),this.hasSymbolBuckets=!1,this.buckets){var i=this.buckets[n];if(i instanceof sc){if(this.hasSymbolBuckets=!0,!r)break;i.justReloaded=!0}}if(this.hasRTLText=!1,this.hasSymbolBuckets)for(var a in this.buckets){var o=this.buckets[a];if(o instanceof sc&&o.hasRTLText){this.hasRTLText=!0,Ci.isLoading()||Ci.isLoaded()||\"deferred\"!==Ei()||Li();break}}for(var s in this.queryPadding=0,this.buckets){var l=this.buckets[s];this.queryPadding=Math.max(this.queryPadding,e.style.getLayer(s).queryRadius(l))}t.imageAtlas&&(this.imageAtlas=t.imageAtlas),t.glyphAtlasImage&&(this.glyphAtlasImage=t.glyphAtlasImage)}else this.collisionBoxArray=new wa},Jc.prototype.unloadVectorData=function(){for(var t in this.buckets)this.buckets[t].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state=\"unloaded\"},Jc.prototype.getBucket=function(t){return this.buckets[t.id]},Jc.prototype.upload=function(t){for(var e in this.buckets){var r=this.buckets[e];r.uploadPending()&&r.upload(t)}var n=t.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new Tc(t,this.imageAtlas.image,n.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new Tc(t,this.glyphAtlasImage,n.ALPHA),this.glyphAtlasImage=null)},Jc.prototype.prepare=function(t){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(t,this.imageAtlasTexture)},Jc.prototype.queryRenderedFeatures=function(t,e,r,n,i,a,o,s,l,u){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:n,cameraQueryGeometry:i,scale:a,tileSize:this.tileSize,pixelPosMatrix:u,transform:s,params:o,queryPadding:this.queryPadding*l},t,e,r):{}},Jc.prototype.querySourceFeatures=function(t,e){var r=this.latestFeatureIndex;if(r&&r.rawTileData){var n=r.loadVTLayers(),i=e?e.sourceLayer:\"\",a=n._geojsonTileLayer||n[i];if(a)for(var o=wn(e&&e.filter),s=this.tileID.canonical,l=s.z,u=s.x,c=s.y,f={z:l,x:u,y:c},h=0;h<a.length;h++){var p=a.feature(h);if(o.filter(new Pi(this.tileID.overscaledZ),p)){var d=r.getId(p,i),v=new Hc(p,l,u,c,d);v.tile=f,t.push(v)}}}},Jc.prototype.hasData=function(){return\"loaded\"===this.state||\"reloading\"===this.state||\"expired\"===this.state},Jc.prototype.patternsLoaded=function(){return this.imageAtlas&&!!Object.keys(this.imageAtlas.patternPositions).length},Jc.prototype.setExpiryData=function(t){var e=this.expirationTime;if(t.cacheControl){var r=M(t.cacheControl);r[\"max-age\"]&&(this.expirationTime=Date.now()+1e3*r[\"max-age\"])}else t.expires&&(this.expirationTime=new Date(t.expires).getTime());if(this.expirationTime){var n=Date.now(),i=!1;if(this.expirationTime>n)i=!1;else if(e)if(this.expirationTime<e)i=!0;else{var a=this.expirationTime-e;a?this.expirationTime=n+Math.max(a,3e4):i=!0}else i=!0;i?(this.expiredRequestCount++,this.state=\"expired\"):this.expiredRequestCount=0}},Jc.prototype.getExpiryTimeout=function(){if(this.expirationTime)return this.expiredRequestCount?1e3*(1<<Math.min(this.expiredRequestCount-1,31)):Math.min(this.expirationTime-(new Date).getTime(),Math.pow(2,31)-1)},Jc.prototype.setFeatureState=function(t,e){if(this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData&&0!==Object.keys(t).length){var r=this.latestFeatureIndex.loadVTLayers();for(var n in this.buckets)if(e.style.hasLayer(n)){var i=this.buckets[n],a=i.layers[0].sourceLayer||\"_geojsonTileLayer\",o=r[a],s=t[a];if(o&&s&&0!==Object.keys(s).length){i.update(s,o,this.imageAtlas&&this.imageAtlas.patternPositions||{});var l=e&&e.style&&e.style.getLayer(n);l&&(this.queryPadding=Math.max(this.queryPadding,l.queryRadius(i)))}}}},Jc.prototype.holdingForFade=function(){return void 0!==this.symbolFadeHoldUntil},Jc.prototype.symbolFadeFinished=function(){return!this.symbolFadeHoldUntil||this.symbolFadeHoldUntil<F.now()},Jc.prototype.clearFadeHold=function(){this.symbolFadeHoldUntil=void 0},Jc.prototype.setHoldDuration=function(t){this.symbolFadeHoldUntil=F.now()+t},Jc.prototype.setDependencies=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1)r[i[n]]=!0;this.dependencies[t]=r},Jc.prototype.hasDependency=function(t,e){for(var r=0,n=t;r<n.length;r+=1){var i=n[r],a=this.dependencies[i];if(a)for(var o=0,s=e;o<s.length;o+=1)if(a[s[o]])return!0}return!1};var Kc=self.performance,$c=function(t){this._marks={start:[t.url,\"start\"].join(\"#\"),end:[t.url,\"end\"].join(\"#\"),measure:t.url.toString()},Kc.mark(this._marks.start)};$c.prototype.finish=function(){Kc.mark(this._marks.end);var t=Kc.getEntriesByName(this._marks.measure);return 0===t.length&&(Kc.measure(this._marks.measure,this._marks.start,this._marks.end),t=Kc.getEntriesByName(this._marks.measure),Kc.clearMarks(this._marks.start),Kc.clearMarks(this._marks.end),Kc.clearMeasures(this._marks.measure)),t},t.Actor=Ac,t.AlphaImage=Yo,t.CanonicalTileID=Fc,t.CollisionBoxArray=wa,t.Color=oe,t.DEMData=Uc,t.DataConstantProperty=ji,t.DictionaryCoder=Vc,t.EXTENT=co,t.ErrorEvent=Ot,t.EvaluationParameters=Pi,t.Event=Pt,t.Evented=It,t.FeatureIndex=Zc,t.FillBucket=Fs,t.FillExtrusionBucket=tl,t.ImageAtlas=ru,t.ImagePosition=tu,t.LineBucket=cl,t.LngLat=Lc,t.LngLatBounds=Sc,t.MercatorCoordinate=Rc,t.ONE_EM=kl,t.OverscaledTileID=Nc,t.Point=a,t.Point$1=a,t.Properties=Gi,t.Protobuf=Sl,t.RGBAImage=Wo,t.RequestManager=q,t.RequestPerformance=$c,t.ResourceType=xt,t.SegmentVector=Oa,t.SourceFeatureState=Gc,t.StructArrayLayout1ui2=ma,t.StructArrayLayout2f1f2i16=ua,t.StructArrayLayout2i4=Qi,t.StructArrayLayout3ui6=fa,t.StructArrayLayout4i8=ta,t.SymbolBucket=sc,t.Texture=Tc,t.Tile=Jc,t.Transitionable=Di,t.Uniform1f=Ya,t.Uniform1i=Za,t.Uniform2f=Wa,t.Uniform3f=Xa,t.Uniform4f=Ja,t.UniformColor=Ka,t.UniformMatrix4f=Qa,t.UnwrappedTileID=Bc,t.ValidationError=zt,t.WritingMode=nu,t.ZoomHistory=ui,t.add=function(t,e,r){return t[0]=e[0]+r[0],t[1]=e[1]+r[1],t[2]=e[2]+r[2],t},t.addDynamicAttributes=nc,t.asyncAll=function(t,e,r){if(!t.length)return r(null,[]);var n=t.length,i=new Array(t.length),a=null;t.forEach((function(t,o){e(t,(function(t,e){t&&(a=t),i[o]=e,0==--n&&r(a,i)}))}))},t.bezier=s,t.bindAll=g,t.browser=F,t.cacheEntryPossiblyAdded=function(t){++yt>ct&&(t.getActor().send(\"enforceCacheSizeLimit\",ut),yt=0)},t.clamp=u,t.clearTileCache=function(t){var e=self.caches.delete(lt);t&&e.catch(t).then((function(){return t()}))},t.clipLine=Ou,t.clone=function(t){var e=new Io(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e},t.clone$1=b,t.clone$2=function(t){var e=new Io(3);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e},t.collisionCircleLayout=_l,t.config=B,t.create=function(){var t=new Io(16);return Io!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[11]=0,t[12]=0,t[13]=0,t[14]=0),t[0]=1,t[5]=1,t[10]=1,t[15]=1,t},t.create$1=function(){var t=new Io(9);return Io!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[5]=0,t[6]=0,t[7]=0),t[0]=1,t[4]=1,t[8]=1,t},t.create$2=function(){var t=new Io(4);return Io!=Float32Array&&(t[1]=0,t[2]=0),t[0]=1,t[3]=1,t},t.createCommonjsModule=e,t.createExpression=ln,t.createLayout=Ki,t.createStyleLayer=function(t){return\"custom\"===t.type?new gc(t):new yc[t.type](t)},t.cross=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=r[0],s=r[1],l=r[2];return t[0]=i*l-a*s,t[1]=a*o-n*l,t[2]=n*s-i*o,t},t.deepEqual=function t(e,r){if(Array.isArray(e)){if(!Array.isArray(r)||e.length!==r.length)return!1;for(var n=0;n<e.length;n++)if(!t(e[n],r[n]))return!1;return!0}if(\"object\"==typeof e&&null!==e&&null!==r){if(\"object\"!=typeof r)return!1;if(Object.keys(e).length!==Object.keys(r).length)return!1;for(var i in e)if(!t(e[i],r[i]))return!1;return!0}return e===r},t.dot=function(t,e){return t[0]*e[0]+t[1]*e[1]+t[2]*e[2]},t.dot$1=function(t,e){return t[0]*e[0]+t[1]*e[1]+t[2]*e[2]+t[3]*e[3]},t.ease=l,t.emitValidationErrors=Jn,t.endsWith=y,t.enforceCacheSizeLimit=function(t){ht(),tt&&tt.then((function(e){e.keys().then((function(r){for(var n=0;n<r.length-t;n++)e.delete(r[n])}))}))},t.evaluateSizeForFeature=wu,t.evaluateSizeForZoom=Tu,t.evaluateVariableOffset=Yu,t.evented=Si,t.extend=f,t.featureFilter=wn,t.filterObject=x,t.fromRotation=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=r,t[2]=0,t[3]=-r,t[4]=n,t[5]=0,t[6]=0,t[7]=0,t[8]=1,t},t.getAnchorAlignment=gu,t.getAnchorJustification=Wu,t.getArrayBuffer=kt,t.getImage=Et,t.getJSON=function(t,e){return Tt(f(t,{type:\"json\"}),e)},t.getRTLTextPluginStatus=Ei,t.getReferrer=_t,t.getVideo=function(t,e){var r,n,i=self.document.createElement(\"video\");i.muted=!0,i.onloadstart=function(){e(null,i)};for(var a=0;a<t.length;a++){var 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c={},e.tags)c[f]=e.tags[f];c.mapbox_clip_start=i.start/i.size,c.mapbox_clip_end=i.end/i.size}var h={geometry:o,type:\"Polygon\"===a||\"MultiPolygon\"===a?3:\"LineString\"===a||\"MultiLineString\"===a?2:1,tags:c};null!==e.id&&(h.id=e.id),t.features.push(h)}}function wt(t,e,r,n,i,a){var o=n*n;if(n>0&&e.size<(i?o:n))r.numPoints+=e.length/3;else{for(var s=[],l=0;l<e.length;l+=3)(0===n||e[l+2]>o)&&(r.numSimplified++,s.push(e[l]),s.push(e[l+1])),r.numPoints++;i&&function(t,e){for(var r=0,n=0,i=t.length,a=i-2;n<i;a=n,n+=2)r+=(t[n]-t[a])*(t[n+1]+t[a+1]);if(r>0===e)for(n=0,i=t.length;n<i/2;n+=2){var o=t[n],s=t[n+1];t[n]=t[i-2-n],t[n+1]=t[i-1-n],t[i-2-n]=o,t[i-1-n]=s}}(s,a),t.push(s)}}function Tt(t,e){var r=(e=this.options=function(t,e){for(var r in e)t[r]=e[r];return t}(Object.create(this.options),e)).debug;if(r&&console.time(\"preprocess data\"),e.maxZoom<0||e.maxZoom>24)throw new Error(\"maxZoom should be in the 0-24 range\");if(e.promoteId&&e.generateId)throw new Error(\"promoteId and generateId cannot be used together.\");var n=function(t,e){var r=[];if(\"FeatureCollection\"===t.type)for(var n=0;n<t.features.length;n++)rt(r,t.features[n],e,n);else\"Feature\"===t.type?rt(r,t,e):rt(r,{geometry:t},e);return r}(t,e);this.tiles={},this.tileCoords=[],r&&(console.timeEnd(\"preprocess data\"),console.log(\"index: maxZoom: %d, maxPoints: %d\",e.indexMaxZoom,e.indexMaxPoints),console.time(\"generate tiles\"),this.stats={},this.total=0),(n=function(t,e){var r=e.buffer/e.extent,n=t,i=lt(t,1,-1-r,r,0,-1,2,e),a=lt(t,1,1-r,2+r,0,-1,2,e);return(i||a)&&(n=lt(t,1,-r,1+r,0,-1,2,e)||[],i&&(n=gt(i,1).concat(n)),a&&(n=n.concat(gt(a,-1)))),n}(n,e)).length&&this.splitTile(n,0,0,0),r&&(n.length&&console.log(\"features: %d, points: %d\",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd(\"generate tiles\"),console.log(\"tiles generated:\",this.total,JSON.stringify(this.stats)))}function kt(t,e,r){return 32*((1<<t)*r+e)+t}function At(t,e){var r=t.tileID.canonical;if(!this._geoJSONIndex)return e(null,null);var n=this._geoJSONIndex.getTile(r.z,r.x,r.y);if(!n)return e(null,null);var i=new g(n.features),a=_(i);0===a.byteOffset&&a.byteLength===a.buffer.byteLength||(a=new Uint8Array(a)),e(null,{vectorTile:i,rawData:a.buffer})}V.prototype.load=function(t){var e=this.options,r=e.log,n=e.minZoom,i=e.maxZoom,a=e.nodeSize;r&&console.time(\"total time\");var o=\"prepare \"+t.length+\" points\";r&&console.time(o),this.points=t;for(var s=[],l=0;l<t.length;l++)t[l].geometry&&s.push(q(t[l],l));this.trees[i+1]=new j(s,J,K,a,Float32Array),r&&console.timeEnd(o);for(var u=i;u>=n;u--){var c=+Date.now();s=this._cluster(s,u),this.trees[u]=new j(s,J,K,a,Float32Array),r&&console.log(\"z%d: %d clusters in %dms\",u,s.length,+Date.now()-c)}return r&&console.timeEnd(\"total time\"),this},V.prototype.getClusters=function(t,e){var r=((t[0]+180)%360+360)%360-180,n=Math.max(-90,Math.min(90,t[1])),i=180===t[2]?180:((t[2]+180)%360+360)%360-180,a=Math.max(-90,Math.min(90,t[3]));if(t[2]-t[0]>=360)r=-180,i=180;else if(r>i){var o=this.getClusters([r,n,180,a],e),s=this.getClusters([-180,n,i,a],e);return o.concat(s)}for(var l=this.trees[this._limitZoom(e)],u=[],c=0,f=l.range(Y(r),W(a),Y(i),W(n));c<f.length;c+=1){var h=f[c],p=l.points[h];u.push(p.numPoints?G(p):this.points[p.index])}return u},V.prototype.getChildren=function(t){var e=this._getOriginId(t),r=this._getOriginZoom(t),n=\"No cluster with the specified id.\",i=this.trees[r];if(!i)throw new Error(n);var a=i.points[e];if(!a)throw new Error(n);for(var o=this.options.radius/(this.options.extent*Math.pow(2,r-1)),s=[],l=0,u=i.within(a.x,a.y,o);l<u.length;l+=1){var c=u[l],f=i.points[c];f.parentId===t&&s.push(f.numPoints?G(f):this.points[f.index])}if(0===s.length)throw new Error(n);return s},V.prototype.getLeaves=function(t,e,r){e=e||10,r=r||0;var n=[];return this._appendLeaves(n,t,e,r,0),n},V.prototype.getTile=function(t,e,r){var n=this.trees[this._limitZoom(t)],i=Math.pow(2,t),a=this.options,o=a.extent,s=a.radius/o,l=(r-s)/i,u=(r+1+s)/i,c={features:[]};return this._addTileFeatures(n.range((e-s)/i,l,(e+1+s)/i,u),n.points,e,r,i,c),0===e&&this._addTileFeatures(n.range(1-s/i,l,1,u),n.points,i,r,i,c),e===i-1&&this._addTileFeatures(n.range(0,l,s/i,u),n.points,-1,r,i,c),c.features.length?c:null},V.prototype.getClusterExpansionZoom=function(t){for(var e=this._getOriginZoom(t)-1;e<=this.options.maxZoom;){var r=this.getChildren(t);if(e++,1!==r.length)break;t=r[0].properties.cluster_id}return e},V.prototype._appendLeaves=function(t,e,r,n,i){for(var a=0,o=this.getChildren(e);a<o.length;a+=1){var s=o[a],l=s.properties;if(l&&l.cluster?i+l.point_count<=n?i+=l.point_count:i=this._appendLeaves(t,l.cluster_id,r,n,i):i<n?i++:t.push(s),t.length===r)break}return i},V.prototype._addTileFeatures=function(t,e,r,n,i,a){for(var o=0,s=t;o<s.length;o+=1){var l=e[s[o]],u=l.numPoints,c={type:1,geometry:[[Math.round(this.options.extent*(l.x*i-r)),Math.round(this.options.extent*(l.y*i-n))]],tags:u?Z(l):this.points[l.index].properties},f=void 0;u?f=l.id:this.options.generateId?f=l.index:this.points[l.index].id&&(f=this.points[l.index].id),void 0!==f&&(c.id=f),a.features.push(c)}},V.prototype._limitZoom=function(t){return Math.max(this.options.minZoom,Math.min(t,this.options.maxZoom+1))},V.prototype._cluster=function(t,e){for(var r=[],n=this.options,i=n.radius,a=n.extent,o=n.reduce,s=i/(a*Math.pow(2,e)),l=0;l<t.length;l++){var u=t[l];if(!(u.zoom<=e)){u.zoom=e;for(var c=this.trees[e+1],f=c.within(u.x,u.y,s),h=u.numPoints||1,p=u.x*h,d=u.y*h,v=o&&h>1?this._map(u,!0):null,g=(l<<5)+(e+1)+this.points.length,y=0,m=f;y<m.length;y+=1){var x=m[y],b=c.points[x];if(!(b.zoom<=e)){b.zoom=e;var _=b.numPoints||1;p+=b.x*_,d+=b.y*_,h+=_,b.parentId=g,o&&(v||(v=this._map(u,!0)),o(v,this._map(b)))}}1===h?r.push(u):(u.parentId=g,r.push(H(p/h,d/h,g,h,v)))}}return r},V.prototype._getOriginId=function(t){return t-this.points.length>>5},V.prototype._getOriginZoom=function(t){return(t-this.points.length)%32},V.prototype._map=function(t,e){if(t.numPoints)return e?X({},t.properties):t.properties;var r=this.points[t.index].properties,n=this.options.map(r);return e&&n===r?X({},n):n},Tt.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},Tt.prototype.splitTile=function(t,e,r,n,i,a,o){for(var s=[t,e,r,n],l=this.options,u=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var c=1<<e,f=kt(e,r,n),h=this.tiles[f];if(!h&&(u>1&&console.time(\"creation\"),h=this.tiles[f]=bt(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),u)){u>1&&(console.log(\"tile z%d-%d-%d (features: %d, points: %d, simplified: %d)\",e,r,n,h.numFeatures,h.numPoints,h.numSimplified),console.timeEnd(\"creation\"));var p=\"z\"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(h.source=t,i){if(e===l.maxZoom||e===i)continue;var d=1<<i-e;if(r!==Math.floor(a/d)||n!==Math.floor(o/d))continue}else if(e===l.indexMaxZoom||h.numPoints<=l.indexMaxPoints)continue;if(h.source=null,0!==t.length){u>1&&console.time(\"clipping\");var v,g,y,m,x,b,_=.5*l.buffer/l.extent,w=.5-_,T=.5+_,k=1+_;v=g=y=m=null,x=lt(t,c,r-_,r+T,0,h.minX,h.maxX,l),b=lt(t,c,r+w,r+k,0,h.minX,h.maxX,l),t=null,x&&(v=lt(x,c,n-_,n+T,1,h.minY,h.maxY,l),g=lt(x,c,n+w,n+k,1,h.minY,h.maxY,l),x=null),b&&(y=lt(b,c,n-_,n+T,1,h.minY,h.maxY,l),m=lt(b,c,n+w,n+k,1,h.minY,h.maxY,l),b=null),u>1&&console.timeEnd(\"clipping\"),s.push(v||[],e+1,2*r,2*n),s.push(g||[],e+1,2*r,2*n+1),s.push(y||[],e+1,2*r+1,2*n),s.push(m||[],e+1,2*r+1,2*n+1)}}},Tt.prototype.getTile=function(t,e,r){var n=this.options,i=n.extent,a=n.debug;if(t<0||t>24)return null;var o=1<<t,s=kt(t,e=(e%o+o)%o,r);if(this.tiles[s])return mt(this.tiles[s],i);a>1&&console.log(\"drilling down to z%d-%d-%d\",t,e,r);for(var l,u=t,c=e,f=r;!l&&u>0;)u--,c=Math.floor(c/2),f=Math.floor(f/2),l=this.tiles[kt(u,c,f)];return l&&l.source?(a>1&&console.log(\"found parent tile z%d-%d-%d\",u,c,f),a>1&&console.time(\"drilling down\"),this.splitTile(l.source,u,c,f,t,e,r),a>1&&console.timeEnd(\"drilling down\"),this.tiles[s]?mt(this.tiles[s],i):null):null};var Mt=function(e){function r(t,r,n,i){e.call(this,t,r,n,At),i&&(this.loadGeoJSON=i)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadData=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),this._pendingCallback=e,this._pendingLoadDataParams=t,this._state&&\"Idle\"!==this._state?this._state=\"NeedsLoadData\":(this._state=\"Coalescing\",this._loadData())},r.prototype._loadData=function(){var e=this;if(this._pendingCallback&&this._pendingLoadDataParams){var r=this._pendingCallback,n=this._pendingLoadDataParams;delete this._pendingCallback,delete this._pendingLoadDataParams;var i=!!(n&&n.request&&n.request.collectResourceTiming)&&new t.RequestPerformance(n.request);this.loadGeoJSON(n,(function(a,o){if(a||!o)return r(a);if(\"object\"!=typeof o)return r(new Error(\"Input data given to '\"+n.source+\"' is not a valid GeoJSON object.\"));f(o,!0);try{e._geoJSONIndex=n.cluster?new V(function(e){var r=e.superclusterOptions,n=e.clusterProperties;if(!n||!r)return r;for(var i={},a={},o={accumulated:null,zoom:0},s={properties:null},l=Object.keys(n),u=0,c=l;u<c.length;u+=1){var f=c[u],h=n[f],p=h[0],d=h[1],v=t.createExpression(d),g=t.createExpression(\"string\"==typeof p?[p,[\"accumulated\"],[\"get\",f]]:p);i[f]=v.value,a[f]=g.value}return r.map=function(t){s.properties=t;for(var e={},r=0,n=l;r<n.length;r+=1){var a=n[r];e[a]=i[a].evaluate(o,s)}return e},r.reduce=function(t,e){s.properties=e;for(var r=0,n=l;r<n.length;r+=1){var i=n[r];o.accumulated=t[i],t[i]=a[i].evaluate(o,s)}},r}(n)).load(o.features):function(t,e){return new Tt(t,e)}(o,n.geojsonVtOptions)}catch(a){return r(a)}e.loaded={};var s={};if(i){var l=i.finish();l&&(s.resourceTiming={},s.resourceTiming[n.source]=JSON.parse(JSON.stringify(l)))}r(null,s)}))}},r.prototype.coalesce=function(){\"Coalescing\"===this._state?this._state=\"Idle\":\"NeedsLoadData\"===this._state&&(this._state=\"Coalescing\",this._loadData())},r.prototype.reloadTile=function(t,r){var n=this.loaded,i=t.uid;return n&&n[i]?e.prototype.reloadTile.call(this,t,r):this.loadTile(t,r)},r.prototype.loadGeoJSON=function(e,r){if(e.request)t.getJSON(e.request,r);else{if(\"string\"!=typeof e.data)return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON object.\"));try{return r(null,JSON.parse(e.data))}catch(t){return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON object.\"))}}},r.prototype.removeSource=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),e()},r.prototype.getClusterExpansionZoom=function(t,e){try{e(null,this._geoJSONIndex.getClusterExpansionZoom(t.clusterId))}catch(t){e(t)}},r.prototype.getClusterChildren=function(t,e){try{e(null,this._geoJSONIndex.getChildren(t.clusterId))}catch(t){e(t)}},r.prototype.getClusterLeaves=function(t,e){try{e(null,this._geoJSONIndex.getLeaves(t.clusterId,t.limit,t.offset))}catch(t){e(t)}},r}(l);var St=function(e){var r=this;this.self=e,this.actor=new t.Actor(e,this),this.layerIndexes={},this.availableImages={},this.workerSourceTypes={vector:l,geojson:Mt},this.workerSources={},this.demWorkerSources={},this.self.registerWorkerSource=function(t,e){if(r.workerSourceTypes[t])throw new Error('Worker source with name \"'+t+'\" already registered.');r.workerSourceTypes[t]=e},this.self.registerRTLTextPlugin=function(e){if(t.plugin.isParsed())throw new Error(\"RTL text plugin already registered.\");t.plugin.applyArabicShaping=e.applyArabicShaping,t.plugin.processBidirectionalText=e.processBidirectionalText,t.plugin.processStyledBidirectionalText=e.processStyledBidirectionalText}};return St.prototype.setReferrer=function(t,e){this.referrer=e},St.prototype.setImages=function(t,e,r){for(var n in this.availableImages[t]=e,this.workerSources[t]){var i=this.workerSources[t][n];for(var a in i)i[a].availableImages=e}r()},St.prototype.setLayers=function(t,e,r){this.getLayerIndex(t).replace(e),r()},St.prototype.updateLayers=function(t,e,r){this.getLayerIndex(t).update(e.layers,e.removedIds),r()},St.prototype.loadTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).loadTile(e,r)},St.prototype.loadDEMTile=function(t,e,r){this.getDEMWorkerSource(t,e.source).loadTile(e,r)},St.prototype.reloadTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).reloadTile(e,r)},St.prototype.abortTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).abortTile(e,r)},St.prototype.removeTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).removeTile(e,r)},St.prototype.removeDEMTile=function(t,e){this.getDEMWorkerSource(t,e.source).removeTile(e)},St.prototype.removeSource=function(t,e,r){if(this.workerSources[t]&&this.workerSources[t][e.type]&&this.workerSources[t][e.type][e.source]){var n=this.workerSources[t][e.type][e.source];delete this.workerSources[t][e.type][e.source],void 0!==n.removeSource?n.removeSource(e,r):r()}},St.prototype.loadWorkerSource=function(t,e,r){try{this.self.importScripts(e.url),r()}catch(t){r(t.toString())}},St.prototype.syncRTLPluginState=function(e,r,n){try{t.plugin.setState(r);var i=t.plugin.getPluginURL();if(t.plugin.isLoaded()&&!t.plugin.isParsed()&&null!=i){this.self.importScripts(i);var a=t.plugin.isParsed();n(a?void 0:new Error(\"RTL Text Plugin failed to import scripts from \"+i),a)}}catch(t){n(t.toString())}},St.prototype.getAvailableImages=function(t){var e=this.availableImages[t];return e||(e=[]),e},St.prototype.getLayerIndex=function(t){var e=this.layerIndexes[t];return e||(e=this.layerIndexes[t]=new n),e},St.prototype.getWorkerSource=function(t,e,r){var n=this;if(this.workerSources[t]||(this.workerSources[t]={}),this.workerSources[t][e]||(this.workerSources[t][e]={}),!this.workerSources[t][e][r]){var i={send:function(e,r,i){n.actor.send(e,r,i,t)}};this.workerSources[t][e][r]=new this.workerSourceTypes[e](i,this.getLayerIndex(t),this.getAvailableImages(t))}return this.workerSources[t][e][r]},St.prototype.getDEMWorkerSource=function(t,e){return this.demWorkerSources[t]||(this.demWorkerSources[t]={}),this.demWorkerSources[t][e]||(this.demWorkerSources[t][e]=new c),this.demWorkerSources[t][e]},St.prototype.enforceCacheSizeLimit=function(e,r){t.enforceCacheSizeLimit(r)},\"undefined\"!=typeof WorkerGlobalScope&&void 0!==t.window&&t.window instanceof WorkerGlobalScope&&(t.window.worker=new St(t.window)),St})),n(0,(function(t){var e=t.createCommonjsModule((function(t){function e(t){return!r(t)}function r(t){return\"undefined\"!=typeof window&&\"undefined\"!=typeof 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t=document.createElement(\"canvas\");t.width=t.height=1;var e=t.getContext(\"2d\");if(!e)return!1;var r=e.getImageData(0,0,1,1);return r&&r.width===t.width}()?(r=t&&t.failIfMajorPerformanceCaveat,void 0===n[r]&&(n[r]=function(t){var r=function(t){var r=document.createElement(\"canvas\"),n=Object.create(e.webGLContextAttributes);return n.failIfMajorPerformanceCaveat=t,r.probablySupportsContext?r.probablySupportsContext(\"webgl\",n)||r.probablySupportsContext(\"experimental-webgl\",n):r.supportsContext?r.supportsContext(\"webgl\",n)||r.supportsContext(\"experimental-webgl\",n):r.getContext(\"webgl\",n)||r.getContext(\"experimental-webgl\",n)}(t);if(!r)return!1;var n=r.createShader(r.VERTEX_SHADER);return!(!n||r.isContextLost())&&(r.shaderSource(n,\"void main() {}\"),r.compileShader(n),!0===r.getShaderParameter(n,r.COMPILE_STATUS))}(r)),n[r]?void 0:\"insufficient WebGL support\"):\"insufficient Canvas/getImageData support\":\"insufficient ArrayBuffer support\":\"insufficient 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s=i([\"transform\",\"WebkitTransform\"]);r.setTransform=function(t,e){t.style[s]=e};var l=!1;try{var u=Object.defineProperty({},\"passive\",{get:function(){l=!0}});t.window.addEventListener(\"test\",u,u),t.window.removeEventListener(\"test\",u,u)}catch(t){l=!1}r.addEventListener=function(t,e,r,n){void 0===n&&(n={}),\"passive\"in n&&l?t.addEventListener(e,r,n):t.addEventListener(e,r,n.capture)},r.removeEventListener=function(t,e,r,n){void 0===n&&(n={}),\"passive\"in n&&l?t.removeEventListener(e,r,n):t.removeEventListener(e,r,n.capture)};var c=function(e){e.preventDefault(),e.stopPropagation(),t.window.removeEventListener(\"click\",c,!0)};function f(t){var e=t.userImage;return!!(e&&e.render&&e.render())&&(t.data.replace(new Uint8Array(e.data.buffer)),!0)}r.suppressClick=function(){t.window.addEventListener(\"click\",c,!0),t.window.setTimeout((function(){t.window.removeEventListener(\"click\",c,!0)}),0)},r.mousePos=function(e,r){var n=e.getBoundingClientRect();return new 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n=r[e],i=n.ids,a=n.callback;this._notify(i,a)}this.requestors=[]}},r.prototype.getImage=function(t){return this.images[t]},r.prototype.addImage=function(t,e){this._validate(t,e)&&(this.images[t]=e)},r.prototype._validate=function(e,r){var n=!0;return this._validateStretch(r.stretchX,r.data&&r.data.width)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchX\" value'))),n=!1),this._validateStretch(r.stretchY,r.data&&r.data.height)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchY\" value'))),n=!1),this._validateContent(r.content,r)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"content\" value'))),n=!1),n},r.prototype._validateStretch=function(t,e){if(!t)return!0;for(var r=0,n=0,i=t;n<i.length;n+=1){var 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s=this.images[o];s?n[o]={data:s.data.clone(),pixelRatio:s.pixelRatio,sdf:s.sdf,version:s.version,stretchX:s.stretchX,stretchY:s.stretchY,content:s.content,hasRenderCallback:Boolean(s.userImage&&s.userImage.render)}:t.warnOnce('Image \"'+o+'\" could not be loaded. Please make sure you have added the image with map.addImage() or a \"sprite\" property in your style. You can provide missing images by listening for the \"styleimagemissing\" map event.')}r(null,n)},r.prototype.getPixelSize=function(){var t=this.atlasImage;return{width:t.width,height:t.height}},r.prototype.getPattern=function(e){var r=this.patterns[e],n=this.getImage(e);if(!n)return null;if(r&&r.position.version===n.version)return r.position;if(r)r.position.version=n.version;else{var i={w:n.data.width+2,h:n.data.height+2,x:0,y:0},a=new t.ImagePosition(i,n);this.patterns[e]={bin:i,position:a}}return this._updatePatternAtlas(),this.patterns[e].position},r.prototype.bind=function(e){var r=e.gl;this.atlasTexture?this.dirty&&(this.atlasTexture.update(this.atlasImage),this.dirty=!1):this.atlasTexture=new t.Texture(e,this.atlasImage,r.RGBA),this.atlasTexture.bind(r.LINEAR,r.CLAMP_TO_EDGE)},r.prototype._updatePatternAtlas=function(){var e=[];for(var r in this.patterns)e.push(this.patterns[r].bin);var n=t.potpack(e),i=n.w,a=n.h,o=this.atlasImage;for(var s in o.resize({width:i||1,height:a||1}),this.patterns){var l=this.patterns[s].bin,u=l.x+1,c=l.y+1,f=this.images[s].data,h=f.width,p=f.height;t.RGBAImage.copy(f,o,{x:0,y:0},{x:u,y:c},{width:h,height:p}),t.RGBAImage.copy(f,o,{x:0,y:p-1},{x:u,y:c-1},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:u,y:c+p},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:h-1,y:0},{x:u-1,y:c},{width:1,height:p}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:u+h,y:c},{width:1,height:p})}this.dirty=!0},r.prototype.beginFrame=function(){this.callbackDispatchedThisFrame={}},r.prototype.dispatchRenderCallbacks=function(t){for(var e=0,r=t;e<r.length;e+=1){var n=r[e];if(!this.callbackDispatchedThisFrame[n]){this.callbackDispatchedThisFrame[n]=!0;var i=this.images[n];f(i)&&this.updateImage(n,i)}}},r}(t.Evented);var p=g,d=g,v=1e20;function g(t,e,r,n,i,a){this.fontSize=t||24,this.buffer=void 0===e?3:e,this.cutoff=n||.25,this.fontFamily=i||\"sans-serif\",this.fontWeight=a||\"normal\",this.radius=r||8;var o=this.size=this.fontSize+2*this.buffer;this.canvas=document.createElement(\"canvas\"),this.canvas.width=this.canvas.height=o,this.ctx=this.canvas.getContext(\"2d\"),this.ctx.font=this.fontWeight+\" \"+this.fontSize+\"px \"+this.fontFamily,this.ctx.textBaseline=\"middle\",this.ctx.fillStyle=\"black\",this.gridOuter=new Float64Array(o*o),this.gridInner=new Float64Array(o*o),this.f=new Float64Array(o),this.d=new Float64Array(o),this.z=new Float64Array(o+1),this.v=new Int16Array(o),this.middle=Math.round(o/2*(navigator.userAgent.indexOf(\"Gecko/\")>=0?1.2:1))}function y(t,e,r,n,i,a,o){for(var s=0;s<e;s++){for(var l=0;l<r;l++)n[l]=t[l*e+s];for(m(n,i,a,o,r),l=0;l<r;l++)t[l*e+s]=i[l]}for(l=0;l<r;l++){for(s=0;s<e;s++)n[s]=t[l*e+s];for(m(n,i,a,o,e),s=0;s<e;s++)t[l*e+s]=Math.sqrt(i[s])}}function m(t,e,r,n,i){r[0]=0,n[0]=-v,n[1]=+v;for(var a=1,o=0;a<i;a++){for(var s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);s<=n[o];)o--,s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);r[++o]=a,n[o]=s,n[o+1]=+v}for(a=0,o=0;a<i;a++){for(;n[o+1]<a;)o++;e[a]=(a-r[o])*(a-r[o])+t[r[o]]}}g.prototype.draw=function(t){this.ctx.clearRect(0,0,this.size,this.size),this.ctx.fillText(t,this.buffer,this.middle);for(var e=this.ctx.getImageData(0,0,this.size,this.size),r=new Uint8ClampedArray(this.size*this.size),n=0;n<this.size*this.size;n++){var i=e.data[4*n+3]/255;this.gridOuter[n]=1===i?0:0===i?v:Math.pow(Math.max(0,.5-i),2),this.gridInner[n]=1===i?v:0===i?0:Math.pow(Math.max(0,i-.5),2)}for(y(this.gridOuter,this.size,this.size,this.f,this.d,this.v,this.z),y(this.gridInner,this.size,this.size,this.f,this.d,this.v,this.z),n=0;n<this.size*this.size;n++){var a=this.gridOuter[n]-this.gridInner[n];r[n]=Math.max(0,Math.min(255,Math.round(255-255*(a/this.radius+this.cutoff))))}return r},p.default=d;var x=function(t,e){this.requestManager=t,this.localIdeographFontFamily=e,this.entries={}};x.prototype.setURL=function(t){this.url=t},x.prototype.getGlyphs=function(e,r){var n=this,i=[];for(var a in e)for(var o=0,s=e[a];o<s.length;o+=1){var l=s[o];i.push({stack:a,id:l})}t.asyncAll(i,(function(t,e){var r=t.stack,i=t.id,a=n.entries[r];a||(a=n.entries[r]={glyphs:{},requests:{},ranges:{}});var o=a.glyphs[i];if(void 0===o){if(o=n._tinySDF(a,r,i))return a.glyphs[i]=o,void e(null,{stack:r,id:i,glyph:o});var s=Math.floor(i/256);if(256*s>65535)e(new Error(\"glyphs > 65535 not supported\"));else if(a.ranges[s])e(null,{stack:r,id:i,glyph:o});else{var l=a.requests[s];l||(l=a.requests[s]=[],x.loadGlyphRange(r,s,n.url,n.requestManager,(function(t,e){if(e){for(var r in e)n._doesCharSupportLocalGlyph(+r)||(a.glyphs[+r]=e[+r]);a.ranges[s]=!0}for(var i=0,o=l;i<o.length;i+=1)(0,o[i])(t,e);delete a.requests[s]}))),l.push((function(t,n){t?e(t):n&&e(null,{stack:r,id:i,glyph:n[i]||null})}))}}else e(null,{stack:r,id:i,glyph:o})}),(function(t,e){if(t)r(t);else if(e){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.stack,l=o.id,u=o.glyph;(n[s]||(n[s]={}))[l]=u&&{id:u.id,bitmap:u.bitmap.clone(),metrics:u.metrics}}r(null,n)}}))},x.prototype._doesCharSupportLocalGlyph=function(e){return!!this.localIdeographFontFamily&&(t.isChar[\"CJK Unified Ideographs\"](e)||t.isChar[\"Hangul Syllables\"](e)||t.isChar.Hiragana(e)||t.isChar.Katakana(e))},x.prototype._tinySDF=function(e,r,n){var i=this.localIdeographFontFamily;if(i&&this._doesCharSupportLocalGlyph(n)){var a=e.tinySDF;if(!a){var o=\"400\";/bold/i.test(r)?o=\"900\":/medium/i.test(r)?o=\"500\":/light/i.test(r)&&(o=\"200\"),a=e.tinySDF=new x.TinySDF(24,3,8,.25,i,o)}return{id:n,bitmap:new t.AlphaImage({width:30,height:30},a.draw(String.fromCharCode(n))),metrics:{width:24,height:24,left:0,top:-8,advance:24}}}},x.loadGlyphRange=function(e,r,n,i,a){var o=256*r,s=o+255,l=i.transformRequest(i.normalizeGlyphsURL(n).replace(\"{fontstack}\",e).replace(\"{range}\",o+\"-\"+s),t.ResourceType.Glyphs);t.getArrayBuffer(l,(function(e,r){if(e)a(e);else if(r){for(var n={},i=0,o=t.parseGlyphPBF(r);i<o.length;i+=1){var s=o[i];n[s.id]=s}a(null,n)}}))},x.TinySDF=p;var b=function(){this.specification=t.styleSpec.light.position};b.prototype.possiblyEvaluate=function(e,r){return t.sphericalToCartesian(e.expression.evaluate(r))},b.prototype.interpolate=function(e,r,n){return{x:t.number(e.x,r.x,n),y:t.number(e.y,r.y,n),z:t.number(e.z,r.z,n)}};var _=new t.Properties({anchor:new t.DataConstantProperty(t.styleSpec.light.anchor),position:new b,color:new t.DataConstantProperty(t.styleSpec.light.color),intensity:new t.DataConstantProperty(t.styleSpec.light.intensity)}),w=\"-transition\",T=function(e){function r(r){e.call(this),this._transitionable=new t.Transitionable(_),this.setLight(r),this._transitioning=this._transitionable.untransitioned()}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getLight=function(){return this._transitionable.serialize()},r.prototype.setLight=function(e,r){if(void 0===r&&(r={}),!this._validate(t.validateLight,e,r))for(var n in e){var i=e[n];t.endsWith(n,w)?this._transitionable.setTransition(n.slice(0,-11),i):this._transitionable.setValue(n,i)}},r.prototype.updateTransitions=function(t){this._transitioning=this._transitionable.transitioned(t,this._transitioning)},r.prototype.hasTransition=function(){return this._transitioning.hasTransition()},r.prototype.recalculate=function(t){this.properties=this._transitioning.possiblyEvaluate(t)},r.prototype._validate=function(e,r,n){return(!n||!1!==n.validate)&&t.emitValidationErrors(this,e.call(t.validateStyle,t.extend({value:r,style:{glyphs:!0,sprite:!0},styleSpec:t.styleSpec})))},r}(t.Evented),k=function(t,e){this.width=t,this.height=e,this.nextRow=0,this.data=new Uint8Array(this.width*this.height),this.dashEntry={}};k.prototype.getDash=function(t,e){var r=t.join(\",\")+String(e);return this.dashEntry[r]||(this.dashEntry[r]=this.addDash(t,e)),this.dashEntry[r]},k.prototype.getDashRanges=function(t,e,r){var n=[],i=t.length%2==1?-t[t.length-1]*r:0,a=t[0]*r,o=!0;n.push({left:i,right:a,isDash:o,zeroLength:0===t[0]});for(var s=t[0],l=1;l<t.length;l++){o=!o;var u=t[l];i=s*r,a=(s+=u)*r,n.push({left:i,right:a,isDash:o,zeroLength:0===u})}return n},k.prototype.addRoundDash=function(t,e,r){for(var n=e/2,i=-r;i<=r;i++)for(var a=this.nextRow+r+i,o=this.width*a,s=0,l=t[s],u=0;u<this.width;u++){u/l.right>1&&(l=t[++s]);var c=Math.abs(u-l.left),f=Math.abs(u-l.right),h=Math.min(c,f),p=void 0,d=i/r*(n+1);if(l.isDash){var v=n-Math.abs(d);p=Math.sqrt(h*h+v*v)}else p=n-Math.sqrt(h*h+d*d);this.data[o+u]=Math.max(0,Math.min(255,p+128))}},k.prototype.addRegularDash=function(t){for(var e=t.length-1;e>=0;--e){var r=t[e],n=t[e+1];r.zeroLength?t.splice(e,1):n&&n.isDash===r.isDash&&(n.left=r.left,t.splice(e,1))}var i=t[0],a=t[t.length-1];i.isDash===a.isDash&&(i.left=a.left-this.width,a.right=i.right+this.width);for(var o=this.width*this.nextRow,s=0,l=t[s],u=0;u<this.width;u++){u/l.right>1&&(l=t[++s]);var c=Math.abs(u-l.left),f=Math.abs(u-l.right),h=Math.min(c,f),p=l.isDash?h:-h;this.data[o+u]=Math.max(0,Math.min(255,p+128))}},k.prototype.addDash=function(e,r){var n=r?7:0,i=2*n+1;if(this.nextRow+i>this.height)return t.warnOnce(\"LineAtlas out of space\"),null;for(var a=0,o=0;o<e.length;o++)a+=e[o];if(0!==a){var s=this.width/a,l=this.getDashRanges(e,this.width,s);r?this.addRoundDash(l,s,n):this.addRegularDash(l)}var u={y:(this.nextRow+n+.5)/this.height,height:2*n/this.height,width:a};return this.nextRow+=i,this.dirty=!0,u},k.prototype.bind=function(t){var e=t.gl;this.texture?(e.bindTexture(e.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,e.texSubImage2D(e.TEXTURE_2D,0,0,0,this.width,this.height,e.ALPHA,e.UNSIGNED_BYTE,this.data))):(this.texture=e.createTexture(),e.bindTexture(e.TEXTURE_2D,this.texture),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_S,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_T,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texImage2D(e.TEXTURE_2D,0,e.ALPHA,this.width,this.height,0,e.ALPHA,e.UNSIGNED_BYTE,this.data))};var A=function e(r,n){this.workerPool=r,this.actors=[],this.currentActor=0,this.id=t.uniqueId();for(var i=this.workerPool.acquire(this.id),a=0;a<i.length;a++){var o=i[a],s=new e.Actor(o,n,this.id);s.name=\"Worker \"+a,this.actors.push(s)}};function M(e,r,n){var i=function(i,a){if(i)return n(i);if(a){var o=t.pick(t.extend(a,e),[\"tiles\",\"minzoom\",\"maxzoom\",\"attribution\",\"mapbox_logo\",\"bounds\",\"scheme\",\"tileSize\",\"encoding\"]);a.vector_layers&&(o.vectorLayers=a.vector_layers,o.vectorLayerIds=o.vectorLayers.map((function(t){return t.id}))),o.tiles=r.canonicalizeTileset(o,e.url),n(null,o)}};return e.url?t.getJSON(r.transformRequest(r.normalizeSourceURL(e.url),t.ResourceType.Source),i):t.browser.frame((function(){return i(null,e)}))}A.prototype.broadcast=function(e,r,n){n=n||function(){},t.asyncAll(this.actors,(function(t,n){t.send(e,r,n)}),n)},A.prototype.getActor=function(){return this.currentActor=(this.currentActor+1)%this.actors.length,this.actors[this.currentActor]},A.prototype.remove=function(){this.actors.forEach((function(t){t.remove()})),this.actors=[],this.workerPool.release(this.id)},A.Actor=t.Actor;var S=function(e,r,n){this.bounds=t.LngLatBounds.convert(this.validateBounds(e)),this.minzoom=r||0,this.maxzoom=n||24};S.prototype.validateBounds=function(t){return Array.isArray(t)&&4===t.length?[Math.max(-180,t[0]),Math.max(-90,t[1]),Math.min(180,t[2]),Math.min(90,t[3])]:[-180,-90,180,90]},S.prototype.contains=function(e){var r=Math.pow(2,e.z),n=Math.floor(t.mercatorXfromLng(this.bounds.getWest())*r),i=Math.floor(t.mercatorYfromLat(this.bounds.getNorth())*r),a=Math.ceil(t.mercatorXfromLng(this.bounds.getEast())*r),o=Math.ceil(t.mercatorYfromLat(this.bounds.getSouth())*r);return e.x>=n&&e.x<a&&e.y>=i&&e.y<o};var E=function(e){function r(r,n,i,a){if(e.call(this),this.id=r,this.dispatcher=i,this.type=\"vector\",this.minzoom=0,this.maxzoom=22,this.scheme=\"xyz\",this.tileSize=512,this.reparseOverscaled=!0,this.isTileClipped=!0,this._loaded=!1,t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\",\"promoteId\"])),this._options=t.extend({type:\"vector\"},n),this._collectResourceTiming=n.collectResourceTiming,512!==this.tileSize)throw new Error(\"vector tile sources must have a tileSize of 512\");this.setEventedParent(a)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=M(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new S(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles,e.map._requestManager._customAccessToken),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken,e.map._requestManager._customAccessToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme)),i={request:this.map._requestManager.transformRequest(n,t.ResourceType.Tile),uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,tileSize:this.tileSize*e.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};function a(n,i){return delete e.request,e.aborted?r(null):n&&404!==n.status?r(n):(i&&i.resourceTiming&&(e.resourceTiming=i.resourceTiming),this.map._refreshExpiredTiles&&i&&e.setExpiryData(i),e.loadVectorData(i,this.map.painter),t.cacheEntryPossiblyAdded(this.dispatcher),r(null),void(e.reloadCallback&&(this.loadTile(e,e.reloadCallback),e.reloadCallback=null)))}i.request.collectResourceTiming=this._collectResourceTiming,e.actor&&\"expired\"!==e.state?\"loading\"===e.state?e.reloadCallback=r:e.request=e.actor.send(\"reloadTile\",i,a.bind(this)):(e.actor=this.dispatcher.getActor(),e.request=e.actor.send(\"loadTile\",i,a.bind(this)))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.actor&&t.actor.send(\"abortTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.unloadTile=function(t){t.unloadVectorData(),t.actor&&t.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.hasTransition=function(){return!1},r}(t.Evented),L=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.dispatcher=i,this.setEventedParent(a),this.type=\"raster\",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme=\"xyz\",this.tileSize=512,this._loaded=!1,this._options=t.extend({type:\"raster\"},n),t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\"]))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=M(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new S(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.loadTile=function(e,r){var n=this,i=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);e.request=t.getImage(this.map._requestManager.transformRequest(i,t.ResourceType.Tile),(function(i,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(i)e.state=\"errored\",r(i);else if(a){n.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=n.map.painter.context,s=o.gl;e.texture=n.map.painter.getTileTexture(a.width),e.texture?e.texture.update(a,{useMipmap:!0}):(e.texture=new t.Texture(o,a,s.RGBA,{useMipmap:!0}),e.texture.bind(s.LINEAR,s.CLAMP_TO_EDGE,s.LINEAR_MIPMAP_NEAREST),o.extTextureFilterAnisotropic&&s.texParameterf(s.TEXTURE_2D,o.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,o.extTextureFilterAnisotropicMax)),e.state=\"loaded\",t.cacheEntryPossiblyAdded(n.dispatcher),r(null)}}))},r.prototype.abortTile=function(t,e){t.request&&(t.request.cancel(),delete t.request),e()},r.prototype.unloadTile=function(t,e){t.texture&&this.map.painter.saveTileTexture(t.texture),e()},r.prototype.hasTransition=function(){return!1},r}(t.Evented),C=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),this.type=\"raster-dem\",this.maxzoom=22,this._options=t.extend({type:\"raster-dem\"},n),this.encoding=n.encoding||\"mapbox\"}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.serialize=function(){return{type:\"raster-dem\",url:this.url,tileSize:this.tileSize,tiles:this.tiles,bounds:this.bounds,encoding:this.encoding}},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);function i(t,n){t&&(e.state=\"errored\",r(t)),n&&(e.dem=n,e.needsHillshadePrepare=!0,e.state=\"loaded\",r(null))}e.request=t.getImage(this.map._requestManager.transformRequest(n,t.ResourceType.Tile),function(n,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(n)e.state=\"errored\",r(n);else if(a){this.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=t.window.ImageBitmap&&a instanceof t.window.ImageBitmap&&t.offscreenCanvasSupported()?a:t.browser.getImageData(a,1),s={uid:e.uid,coord:e.tileID,source:this.id,rawImageData:o,encoding:this.encoding};e.actor&&\"expired\"!==e.state||(e.actor=this.dispatcher.getActor(),e.actor.send(\"loadDEMTile\",s,i.bind(this)))}}.bind(this)),e.neighboringTiles=this._getNeighboringTiles(e.tileID)},r.prototype._getNeighboringTiles=function(e){var r=e.canonical,n=Math.pow(2,r.z),i=(r.x-1+n)%n,a=0===r.x?e.wrap-1:e.wrap,o=(r.x+1+n)%n,s=r.x+1===n?e.wrap+1:e.wrap,l={};return l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y).key]={backfilled:!1},r.y>0&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+1<n&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y+1).key]={backfilled:!1}),l},r.prototype.unloadTile=function(t){t.demTexture&&this.map.painter.saveTileTexture(t.demTexture),t.fbo&&(t.fbo.destroy(),delete t.fbo),t.dem&&delete t.dem,delete t.neighboringTiles,t.state=\"unloaded\",t.actor&&t.actor.send(\"removeDEMTile\",{uid:t.uid,source:this.id})},r}(L),P=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.type=\"geojson\",this.minzoom=0,this.maxzoom=18,this.tileSize=512,this.isTileClipped=!0,this.reparseOverscaled=!0,this._removed=!1,this._loaded=!1,this.actor=i.getActor(),this.setEventedParent(a),this._data=n.data,this._options=t.extend({},n),this._collectResourceTiming=n.collectResourceTiming,this._resourceTiming=[],void 0!==n.maxzoom&&(this.maxzoom=n.maxzoom),n.type&&(this.type=n.type),n.attribution&&(this.attribution=n.attribution),this.promoteId=n.promoteId;var o=t.EXTENT/this.tileSize;this.workerOptions=t.extend({source:this.id,cluster:n.cluster||!1,geojsonVtOptions:{buffer:(void 0!==n.buffer?n.buffer:128)*o,tolerance:(void 0!==n.tolerance?n.tolerance:.375)*o,extent:t.EXTENT,maxZoom:this.maxzoom,lineMetrics:n.lineMetrics||!1,generateId:n.generateId||!1},superclusterOptions:{maxZoom:void 0!==n.clusterMaxZoom?Math.min(n.clusterMaxZoom,this.maxzoom-1):this.maxzoom-1,extent:t.EXTENT,radius:(n.clusterRadius||50)*o,log:!1,generateId:n.generateId||!1},clusterProperties:n.clusterProperties},n.workerOptions)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(r){if(r)e.fire(new t.ErrorEvent(r));else{var n={dataType:\"source\",sourceDataType:\"metadata\"};e._collectResourceTiming&&e._resourceTiming&&e._resourceTiming.length>0&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event(\"data\",n))}}))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(e){if(e)r.fire(new t.ErrorEvent(e));else{var n={dataType:\"source\",sourceDataType:\"content\"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event(\"data\",n))}})),this},r.prototype.getClusterExpansionZoom=function(t,e){return this.actor.send(\"geojson.getClusterExpansionZoom\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterChildren=function(t,e){return this.actor.send(\"geojson.getClusterChildren\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterLeaves=function(t,e,r,n){return this.actor.send(\"geojson.getClusterLeaves\",{source:this.id,clusterId:t,limit:e,offset:r},n),this},r.prototype._updateWorkerData=function(e){var r=this;this._loaded=!1;var n=t.extend({},this.workerOptions),i=this._data;\"string\"==typeof i?(n.request=this.map._requestManager.transformRequest(t.browser.resolveURL(i),t.ResourceType.Source),n.request.collectResourceTiming=this._collectResourceTiming):n.data=JSON.stringify(i),this.actor.send(this.type+\".loadData\",n,(function(t,i){r._removed||i&&i.abandoned||(r._loaded=!0,i&&i.resourceTiming&&i.resourceTiming[r.id]&&(r._resourceTiming=i.resourceTiming[r.id].slice(0)),r.actor.send(r.type+\".coalesce\",{source:n.source},null),e(t))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.loadTile=function(e,r){var n=this,i=e.actor?\"reloadTile\":\"loadTile\";e.actor=this.actor;var a={type:this.type,uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};e.request=this.actor.send(i,a,(function(t,a){return delete e.request,e.unloadVectorData(),e.aborted?r(null):t?r(t):(e.loadVectorData(a,n.map.painter,\"reloadTile\"===i),r(null))}))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id})},r.prototype.onRemove=function(){this._removed=!0,this.actor.send(\"removeSource\",{type:this.type,source:this.id})},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),O=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]),I=function(e){function r(t,r,n,i){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type=\"image\",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(i),this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(e,r){var n=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this.url=this.options.url,t.getImage(this.map._requestManager.transformRequest(this.url,t.ResourceType.Image),(function(i,a){n._loaded=!0,i?n.fire(new t.ErrorEvent(i)):a&&(n.image=a,e&&(n.coordinates=e),r&&r(),n._finishLoading())}))},r.prototype.loaded=function(){return this._loaded},r.prototype.updateImage=function(t){var e=this;return this.image&&t.url?(this.options.url=t.url,this.load(t.coordinates,(function(){e.texture=null})),this):this},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){var r=this;this.coordinates=e;var n=e.map(t.MercatorCoordinate.fromLngLat);this.tileID=function(e){for(var r=1/0,n=1/0,i=-1/0,a=-1/0,o=0,s=e;o<s.length;o+=1){var l=s[o];r=Math.min(r,l.x),n=Math.min(n,l.y),i=Math.max(i,l.x),a=Math.max(a,l.y)}var u=i-r,c=a-n,f=Math.max(u,c),h=Math.max(0,Math.floor(-Math.log(f)/Math.LN2)),p=Math.pow(2,h);return new t.CanonicalTileID(h,Math.floor((r+i)/2*p),Math.floor((n+a)/2*p))}(n),this.minzoom=this.maxzoom=this.tileID.z;var i=n.map((function(t){return r.tileID.getTilePoint(t)._round()}));return this._boundsArray=new t.StructArrayLayout4i8,this._boundsArray.emplaceBack(i[0].x,i[0].y,0,0),this._boundsArray.emplaceBack(i[1].x,i[1].y,t.EXTENT,0),this._boundsArray.emplaceBack(i[3].x,i[3].y,0,t.EXTENT),this._boundsArray.emplaceBack(i[2].x,i[2].y,t.EXTENT,t.EXTENT),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})),this},r.prototype.prepare=function(){if(0!==Object.keys(this.tiles).length&&this.image){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture||(this.texture=new t.Texture(e,this.image,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.loadTile=function(t,e){this.tileID&&this.tileID.equals(t.tileID.canonical)?(this.tiles[String(t.tileID.wrap)]=t,t.buckets={},e(null)):(t.state=\"errored\",e(null))},r.prototype.serialize=function(){return{type:\"image\",url:this.options.url,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return!1},r}(t.Evented);var D=function(e){function r(t,r,n,i){e.call(this,t,r,n,i),this.roundZoom=!0,this.type=\"video\",this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1;var r=this.options;this.urls=[];for(var n=0,i=r.urls;n<i.length;n+=1){var a=i[n];this.urls.push(this.map._requestManager.transformRequest(a,t.ResourceType.Source).url)}t.getVideo(this.urls,(function(r,n){e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(e.video=n,e.video.loop=!0,e.video.addEventListener(\"playing\",(function(){e.map.triggerRepaint()})),e.map&&e.video.play(),e._finishLoading())}))},r.prototype.pause=function(){this.video&&this.video.pause()},r.prototype.play=function(){this.video&&this.video.play()},r.prototype.seek=function(e){if(this.video){var r=this.video.seekable;e<r.start(0)||e>r.end(0)?this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+this.id,null,\"Playback for this video can be set only between the \"+r.start(0)+\" and \"+r.end(0)+\"-second mark.\"))):this.video.currentTime=e}},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new t.Texture(e,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(I),z=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),n.coordinates?Array.isArray(n.coordinates)&&4===n.coordinates.length&&!n.coordinates.some((function(t){return!Array.isArray(t)||2!==t.length||t.some((function(t){return\"number\"!=typeof t}))}))||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"coordinates\" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"coordinates\"'))),n.animate&&\"boolean\"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'optional \"animate\" property must be a boolean value'))),n.canvas?\"string\"==typeof n.canvas||n.canvas instanceof t.window.HTMLCanvasElement||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"canvas\" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"canvas\"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof t.window.HTMLCanvasElement?this.options.canvas:t.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error(\"Canvas dimensions cannot be less than or equal to zero.\"))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var e=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,e=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,e=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var r=this.map.painter.context,n=r.gl;for(var i in this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(e||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new t.Texture(r,this.canvas,n.RGBA,{premultiply:!0}),this.tiles){var a=this.tiles[i];\"loaded\"!==a.state&&(a.state=\"loaded\",a.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"canvas\",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];t<e.length;t+=1){var r=e[t];if(isNaN(r)||r<=0)return!0}return!1},r}(I),R={vector:E,raster:L,\"raster-dem\":C,geojson:P,video:D,image:I,canvas:z};function F(e,r){var n=t.identity([]);return t.translate(n,n,[1,1,0]),t.scale(n,n,[.5*e.width,.5*e.height,1]),t.multiply(n,n,e.calculatePosMatrix(r.toUnwrapped()))}function B(t,e,r,n,i,a){var o=function(t,e,r){if(t)for(var n=0,i=t;n<i.length;n+=1){var a=e[i[n]];if(a&&a.source===r&&\"fill-extrusion\"===a.type)return!0}else for(var o in e){var s=e[o];if(s.source===r&&\"fill-extrusion\"===s.type)return!0}return!1}(i&&i.layers,e,t.id),s=a.maxPitchScaleFactor(),l=t.tilesIn(n,s,o);l.sort(N);for(var u=[],c=0,f=l;c<f.length;c+=1){var h=f[c];u.push({wrappedTileID:h.tileID.wrapped().key,queryResults:h.tile.queryRenderedFeatures(e,r,t._state,h.queryGeometry,h.cameraQueryGeometry,h.scale,i,a,s,F(t.transform,h.tileID))})}var p=function(t){for(var e={},r={},n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.queryResults,s=a.wrappedTileID,l=r[s]=r[s]||{};for(var u in o)for(var c=o[u],f=l[u]=l[u]||{},h=e[u]=e[u]||[],p=0,d=c;p<d.length;p+=1){var v=d[p];f[v.featureIndex]||(f[v.featureIndex]=!0,h.push(v))}}return e}(u);for(var d in p)p[d].forEach((function(e){var r=e.feature,n=t.getFeatureState(r.layer[\"source-layer\"],r.id);r.source=r.layer.source,r.layer[\"source-layer\"]&&(r.sourceLayer=r.layer[\"source-layer\"]),r.state=n}));return p}function N(t,e){var r=t.tileID,n=e.tileID;return r.overscaledZ-n.overscaledZ||r.canonical.y-n.canonical.y||r.wrap-n.wrap||r.canonical.x-n.canonical.x}var j=function(t,e){this.max=t,this.onRemove=e,this.reset()};j.prototype.reset=function(){for(var t in this.data)for(var e=0,r=this.data[t];e<r.length;e+=1){var n=r[e];n.timeout&&clearTimeout(n.timeout),this.onRemove(n.value)}return this.data={},this.order=[],this},j.prototype.add=function(t,e,r){var n=this,i=t.wrapped().key;void 0===this.data[i]&&(this.data[i]=[]);var a={value:e,timeout:void 0};if(void 0!==r&&(a.timeout=setTimeout((function(){n.remove(t,a)}),r)),this.data[i].push(a),this.order.push(i),this.order.length>this.max){var o=this._getAndRemoveByKey(this.order[0]);o&&this.onRemove(o)}return this},j.prototype.has=function(t){return t.wrapped().key in this.data},j.prototype.getAndRemove=function(t){return this.has(t)?this._getAndRemoveByKey(t.wrapped().key):null},j.prototype._getAndRemoveByKey=function(t){var e=this.data[t].shift();return e.timeout&&clearTimeout(e.timeout),0===this.data[t].length&&delete this.data[t],this.order.splice(this.order.indexOf(t),1),e.value},j.prototype.getByKey=function(t){var e=this.data[t];return e?e[0].value:null},j.prototype.get=function(t){return this.has(t)?this.data[t.wrapped().key][0].value:null},j.prototype.remove=function(t,e){if(!this.has(t))return this;var r=t.wrapped().key,n=void 0===e?0:this.data[r].indexOf(e),i=this.data[r][n];return this.data[r].splice(n,1),i.timeout&&clearTimeout(i.timeout),0===this.data[r].length&&delete this.data[r],this.onRemove(i.value),this.order.splice(this.order.indexOf(r),1),this},j.prototype.setMaxSize=function(t){for(this.max=t;this.order.length>this.max;){var e=this._getAndRemoveByKey(this.order[0]);e&&this.onRemove(e)}return this},j.prototype.filter=function(t){var e=[];for(var r in this.data)for(var n=0,i=this.data[r];n<i.length;n+=1){var a=i[n];t(a.value)||e.push(a)}for(var o=0,s=e;o<s.length;o+=1){var l=s[o];this.remove(l.value.tileID,l)}};var U=function(t,e,r){this.context=t;var n=t.gl;this.buffer=n.createBuffer(),this.dynamicDraw=Boolean(r),this.context.unbindVAO(),t.bindElementBuffer.set(this.buffer),n.bufferData(n.ELEMENT_ARRAY_BUFFER,e.arrayBuffer,this.dynamicDraw?n.DYNAMIC_DRAW:n.STATIC_DRAW),this.dynamicDraw||delete e.arrayBuffer};U.prototype.bind=function(){this.context.bindElementBuffer.set(this.buffer)},U.prototype.updateData=function(t){var e=this.context.gl;this.context.unbindVAO(),this.bind(),e.bufferSubData(e.ELEMENT_ARRAY_BUFFER,0,t.arrayBuffer)},U.prototype.destroy=function(){var t=this.context.gl;this.buffer&&(t.deleteBuffer(this.buffer),delete this.buffer)};var V={Int8:\"BYTE\",Uint8:\"UNSIGNED_BYTE\",Int16:\"SHORT\",Uint16:\"UNSIGNED_SHORT\",Int32:\"INT\",Uint32:\"UNSIGNED_INT\",Float32:\"FLOAT\"},H=function(t,e,r,n){this.length=e.length,this.attributes=r,this.itemSize=e.bytesPerElement,this.dynamicDraw=n,this.context=t;var i=t.gl;this.buffer=i.createBuffer(),t.bindVertexBuffer.set(this.buffer),i.bufferData(i.ARRAY_BUFFER,e.arrayBuffer,this.dynamicDraw?i.DYNAMIC_DRAW:i.STATIC_DRAW),this.dynamicDraw||delete e.arrayBuffer};H.prototype.bind=function(){this.context.bindVertexBuffer.set(this.buffer)},H.prototype.updateData=function(t){var e=this.context.gl;this.bind(),e.bufferSubData(e.ARRAY_BUFFER,0,t.arrayBuffer)},H.prototype.enableAttributes=function(t,e){for(var r=0;r<this.attributes.length;r++){var n=this.attributes[r],i=e.attributes[n.name];void 0!==i&&t.enableVertexAttribArray(i)}},H.prototype.setVertexAttribPointers=function(t,e,r){for(var n=0;n<this.attributes.length;n++){var i=this.attributes[n],a=e.attributes[i.name];void 0!==a&&t.vertexAttribPointer(a,i.components,t[V[i.type]],!1,this.itemSize,i.offset+this.itemSize*(r||0))}},H.prototype.destroy=function(){var t=this.context.gl;this.buffer&&(t.deleteBuffer(this.buffer),delete this.buffer)};var q=function(t){this.gl=t.gl,this.default=this.getDefault(),this.current=this.default,this.dirty=!1};q.prototype.get=function(){return this.current},q.prototype.set=function(t){},q.prototype.getDefault=function(){return this.default},q.prototype.setDefault=function(){this.set(this.default)};var G=function(e){function r(){e.apply(this,arguments)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getDefault=function(){return t.Color.transparent},r.prototype.set=function(t){var e=this.current;(t.r!==e.r||t.g!==e.g||t.b!==e.b||t.a!==e.a||this.dirty)&&(this.gl.clearColor(t.r,t.g,t.b,t.a),this.current=t,this.dirty=!1)},r}(q),Z=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return 1},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.clearDepth(t),this.current=t,this.dirty=!1)},e}(q),Y=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return 0},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.clearStencil(t),this.current=t,this.dirty=!1)},e}(q),W=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return[!0,!0,!0,!0]},e.prototype.set=function(t){var e=this.current;(t[0]!==e[0]||t[1]!==e[1]||t[2]!==e[2]||t[3]!==e[3]||this.dirty)&&(this.gl.colorMask(t[0],t[1],t[2],t[3]),this.current=t,this.dirty=!1)},e}(q),X=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return!0},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.depthMask(t),this.current=t,this.dirty=!1)},e}(q),J=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return 255},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.stencilMask(t),this.current=t,this.dirty=!1)},e}(q),K=function(t){function e(){t.apply(this,arguments)}return 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t=this.gl;return[t.ONE,t.ZERO]},e.prototype.set=function(t){var e=this.current;(t[0]!==e[0]||t[1]!==e[1]||this.dirty)&&(this.gl.blendFunc(t[0],t[1]),this.current=t,this.dirty=!1)},e}(q),at=function(e){function r(){e.apply(this,arguments)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getDefault=function(){return t.Color.transparent},r.prototype.set=function(t){var e=this.current;(t.r!==e.r||t.g!==e.g||t.b!==e.b||t.a!==e.a||this.dirty)&&(this.gl.blendColor(t.r,t.g,t.b,t.a),this.current=t,this.dirty=!1)},r}(q),ot=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return this.gl.FUNC_ADD},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.blendEquation(t),this.current=t,this.dirty=!1)},e}(q),st=function(t){function e(){t.apply(this,arguments)}return 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e=this.current;(t[0]!==e[0]||t[1]!==e[1]||t[2]!==e[2]||t[3]!==e[3]||this.dirty)&&(this.gl.viewport(t[0],t[1],t[2],t[3]),this.current=t,this.dirty=!1)},e}(q),pt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.bindFramebuffer(e.FRAMEBUFFER,t),this.current=t,this.dirty=!1}},e}(q),dt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.bindRenderbuffer(e.RENDERBUFFER,t),this.current=t,this.dirty=!1}},e}(q),vt=function(t){function e(){t.apply(this,arguments)}return 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e(e){t.call(this,e),this.vao=e.extVertexArrayObject}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){this.vao&&(t!==this.current||this.dirty)&&(this.vao.bindVertexArrayOES(t),this.current=t,this.dirty=!1)},e}(q),xt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return 4},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.pixelStorei(e.UNPACK_ALIGNMENT,t),this.current=t,this.dirty=!1}},e}(q),bt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return!1},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.pixelStorei(e.UNPACK_PREMULTIPLY_ALPHA_WEBGL,t),this.current=t,this.dirty=!1}},e}(q),_t=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return!1},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.pixelStorei(e.UNPACK_FLIP_Y_WEBGL,t),this.current=t,this.dirty=!1}},e}(q),wt=function(t){function e(e,r){t.call(this,e),this.context=e,this.parent=r}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return null},e}(q),Tt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.setDirty=function(){this.dirty=!0},e.prototype.set=function(t){if(t!==this.current||this.dirty){this.context.bindFramebuffer.set(this.parent);var e=this.gl;e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0),this.current=t,this.dirty=!1}},e}(wt),kt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){if(t!==this.current||this.dirty){this.context.bindFramebuffer.set(this.parent);var e=this.gl;e.framebufferRenderbuffer(e.FRAMEBUFFER,e.DEPTH_ATTACHMENT,e.RENDERBUFFER,t),this.current=t,this.dirty=!1}},e}(wt),At=function(t,e,r,n){this.context=t,this.width=e,this.height=r;var i=t.gl,a=this.framebuffer=i.createFramebuffer();this.colorAttachment=new Tt(t,a),n&&(this.depthAttachment=new kt(t,a))};At.prototype.destroy=function(){var t=this.context.gl,e=this.colorAttachment.get();if(e&&t.deleteTexture(e),this.depthAttachment){var r=this.depthAttachment.get();r&&t.deleteRenderbuffer(r)}t.deleteFramebuffer(this.framebuffer)};var Mt=function(t,e,r){this.func=t,this.mask=e,this.range=r};Mt.ReadOnly=!1,Mt.ReadWrite=!0,Mt.disabled=new Mt(519,Mt.ReadOnly,[0,1]);var St=7680,Et=function(t,e,r,n,i,a){this.test=t,this.ref=e,this.mask=r,this.fail=n,this.depthFail=i,this.pass=a};Et.disabled=new Et({func:519,mask:0},0,0,St,St,St);var Lt=function(t,e,r){this.blendFunction=t,this.blendColor=e,this.mask=r};Lt.Replace=[1,0],Lt.disabled=new Lt(Lt.Replace,t.Color.transparent,[!1,!1,!1,!1]),Lt.unblended=new Lt(Lt.Replace,t.Color.transparent,[!0,!0,!0,!0]),Lt.alphaBlended=new Lt([1,771],t.Color.transparent,[!0,!0,!0,!0]);var Ct=function(t,e,r){this.enable=t,this.mode=e,this.frontFace=r};Ct.disabled=new Ct(!1,1029,2305),Ct.backCCW=new Ct(!0,1029,2305);var Pt=function(t){this.gl=t,this.extVertexArrayObject=this.gl.getExtension(\"OES_vertex_array_object\"),this.clearColor=new G(this),this.clearDepth=new Z(this),this.clearStencil=new Y(this),this.colorMask=new W(this),this.depthMask=new X(this),this.stencilMask=new J(this),this.stencilFunc=new K(this),this.stencilOp=new $(this),this.stencilTest=new Q(this),this.depthRange=new tt(this),this.depthTest=new et(this),this.depthFunc=new rt(this),this.blend=new nt(this),this.blendFunc=new it(this),this.blendColor=new at(this),this.blendEquation=new ot(this),this.cullFace=new st(this),this.cullFaceSide=new lt(this),this.frontFace=new ut(this),this.program=new ct(this),this.activeTexture=new ft(this),this.viewport=new ht(this),this.bindFramebuffer=new pt(this),this.bindRenderbuffer=new dt(this),this.bindTexture=new vt(this),this.bindVertexBuffer=new gt(this),this.bindElementBuffer=new yt(this),this.bindVertexArrayOES=this.extVertexArrayObject&&new mt(this),this.pixelStoreUnpack=new xt(this),this.pixelStoreUnpackPremultiplyAlpha=new bt(this),this.pixelStoreUnpackFlipY=new _t(this),this.extTextureFilterAnisotropic=t.getExtension(\"EXT_texture_filter_anisotropic\")||t.getExtension(\"MOZ_EXT_texture_filter_anisotropic\")||t.getExtension(\"WEBKIT_EXT_texture_filter_anisotropic\"),this.extTextureFilterAnisotropic&&(this.extTextureFilterAnisotropicMax=t.getParameter(this.extTextureFilterAnisotropic.MAX_TEXTURE_MAX_ANISOTROPY_EXT)),this.extTextureHalfFloat=t.getExtension(\"OES_texture_half_float\"),this.extTextureHalfFloat&&(t.getExtension(\"OES_texture_half_float_linear\"),this.extRenderToTextureHalfFloat=t.getExtension(\"EXT_color_buffer_half_float\")),this.extTimerQuery=t.getExtension(\"EXT_disjoint_timer_query\")};Pt.prototype.setDefault=function(){this.unbindVAO(),this.clearColor.setDefault(),this.clearDepth.setDefault(),this.clearStencil.setDefault(),this.colorMask.setDefault(),this.depthMask.setDefault(),this.stencilMask.setDefault(),this.stencilFunc.setDefault(),this.stencilOp.setDefault(),this.stencilTest.setDefault(),this.depthRange.setDefault(),this.depthTest.setDefault(),this.depthFunc.setDefault(),this.blend.setDefault(),this.blendFunc.setDefault(),this.blendColor.setDefault(),this.blendEquation.setDefault(),this.cullFace.setDefault(),this.cullFaceSide.setDefault(),this.frontFace.setDefault(),this.program.setDefault(),this.activeTexture.setDefault(),this.bindFramebuffer.setDefault(),this.pixelStoreUnpack.setDefault(),this.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.pixelStoreUnpackFlipY.setDefault()},Pt.prototype.setDirty=function(){this.clearColor.dirty=!0,this.clearDepth.dirty=!0,this.clearStencil.dirty=!0,this.colorMask.dirty=!0,this.depthMask.dirty=!0,this.stencilMask.dirty=!0,this.stencilFunc.dirty=!0,this.stencilOp.dirty=!0,this.stencilTest.dirty=!0,this.depthRange.dirty=!0,this.depthTest.dirty=!0,this.depthFunc.dirty=!0,this.blend.dirty=!0,this.blendFunc.dirty=!0,this.blendColor.dirty=!0,this.blendEquation.dirty=!0,this.cullFace.dirty=!0,this.cullFaceSide.dirty=!0,this.frontFace.dirty=!0,this.program.dirty=!0,this.activeTexture.dirty=!0,this.viewport.dirty=!0,this.bindFramebuffer.dirty=!0,this.bindRenderbuffer.dirty=!0,this.bindTexture.dirty=!0,this.bindVertexBuffer.dirty=!0,this.bindElementBuffer.dirty=!0,this.extVertexArrayObject&&(this.bindVertexArrayOES.dirty=!0),this.pixelStoreUnpack.dirty=!0,this.pixelStoreUnpackPremultiplyAlpha.dirty=!0,this.pixelStoreUnpackFlipY.dirty=!0},Pt.prototype.createIndexBuffer=function(t,e){return new U(this,t,e)},Pt.prototype.createVertexBuffer=function(t,e,r){return new H(this,t,e,r)},Pt.prototype.createRenderbuffer=function(t,e,r){var n=this.gl,i=n.createRenderbuffer();return this.bindRenderbuffer.set(i),n.renderbufferStorage(n.RENDERBUFFER,t,e,r),this.bindRenderbuffer.set(null),i},Pt.prototype.createFramebuffer=function(t,e,r){return new At(this,t,e,r)},Pt.prototype.clear=function(t){var e=t.color,r=t.depth,n=this.gl,i=0;e&&(i|=n.COLOR_BUFFER_BIT,this.clearColor.set(e),this.colorMask.set([!0,!0,!0,!0])),void 0!==r&&(i|=n.DEPTH_BUFFER_BIT,this.depthRange.set([0,1]),this.clearDepth.set(r),this.depthMask.set(!0)),n.clear(i)},Pt.prototype.setCullFace=function(t){!1===t.enable?this.cullFace.set(!1):(this.cullFace.set(!0),this.cullFaceSide.set(t.mode),this.frontFace.set(t.frontFace))},Pt.prototype.setDepthMode=function(t){t.func!==this.gl.ALWAYS||t.mask?(this.depthTest.set(!0),this.depthFunc.set(t.func),this.depthMask.set(t.mask),this.depthRange.set(t.range)):this.depthTest.set(!1)},Pt.prototype.setStencilMode=function(t){t.test.func!==this.gl.ALWAYS||t.mask?(this.stencilTest.set(!0),this.stencilMask.set(t.mask),this.stencilOp.set([t.fail,t.depthFail,t.pass]),this.stencilFunc.set({func:t.test.func,ref:t.ref,mask:t.test.mask})):this.stencilTest.set(!1)},Pt.prototype.setColorMode=function(e){t.deepEqual(e.blendFunction,Lt.Replace)?this.blend.set(!1):(this.blend.set(!0),this.blendFunc.set(e.blendFunction),this.blendColor.set(e.blendColor)),this.colorMask.set(e.mask)},Pt.prototype.unbindVAO=function(){this.extVertexArrayObject&&this.bindVertexArrayOES.set(null)};var Ot=function(e){function r(r,n,i){var a=this;e.call(this),this.id=r,this.dispatcher=i,this.on(\"data\",(function(t){\"source\"===t.dataType&&\"metadata\"===t.sourceDataType&&(a._sourceLoaded=!0),a._sourceLoaded&&!a._paused&&\"source\"===t.dataType&&\"content\"===t.sourceDataType&&(a.reload(),a.transform&&a.update(a.transform))})),this.on(\"error\",(function(){a._sourceErrored=!0})),this._source=function(e,r,n,i){var a=new R[r.type](e,r,n,i);if(a.id!==e)throw new Error(\"Expected Source id to be \"+e+\" instead of \"+a.id);return t.bindAll([\"load\",\"abort\",\"unload\",\"serialize\",\"prepare\"],a),a}(r,n,i,this),this._tiles={},this._cache=new j(0,this._unloadTile.bind(this)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._loadedParentTiles={},this._coveredTiles={},this._state=new t.SourceFeatureState}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.onAdd=function(t){this.map=t,this._maxTileCacheSize=t?t._maxTileCacheSize:null,this._source&&this._source.onAdd&&this._source.onAdd(t)},r.prototype.onRemove=function(t){this._source&&this._source.onRemove&&this._source.onRemove(t)},r.prototype.loaded=function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded)return!1;if(!this._source.loaded())return!1;for(var t in this._tiles){var e=this._tiles[t];if(\"loaded\"!==e.state&&\"errored\"!==e.state)return!1}return!0},r.prototype.getSource=function(){return this._source},r.prototype.pause=function(){this._paused=!0},r.prototype.resume=function(){if(this._paused){var t=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,t&&this.reload(),this.transform&&this.update(this.transform)}},r.prototype._loadTile=function(t,e){return this._source.loadTile(t,e)},r.prototype._unloadTile=function(t){if(this._source.unloadTile)return this._source.unloadTile(t,(function(){}))},r.prototype._abortTile=function(t){if(this._source.abortTile)return this._source.abortTile(t,(function(){}))},r.prototype.serialize=function(){return this._source.serialize()},r.prototype.prepare=function(t){for(var e in this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null),this._tiles){var r=this._tiles[e];r.upload(t),r.prepare(this.map.style.imageManager)}},r.prototype.getIds=function(){return t.values(this._tiles).map((function(t){return t.tileID})).sort(It).map((function(t){return t.key}))},r.prototype.getRenderableIds=function(e){var r=this,n=[];for(var i in this._tiles)this._isIdRenderable(i,e)&&n.push(this._tiles[i]);return e?n.sort((function(e,n){var i=e.tileID,a=n.tileID,o=new t.Point(i.canonical.x,i.canonical.y)._rotate(r.transform.angle),s=new t.Point(a.canonical.x,a.canonical.y)._rotate(r.transform.angle);return i.overscaledZ-a.overscaledZ||s.y-o.y||s.x-o.x})).map((function(t){return t.tileID.key})):n.map((function(t){return t.tileID})).sort(It).map((function(t){return t.key}))},r.prototype.hasRenderableParent=function(t){var e=this.findLoadedParent(t,0);return!!e&&this._isIdRenderable(e.tileID.key)},r.prototype._isIdRenderable=function(t,e){return this._tiles[t]&&this._tiles[t].hasData()&&!this._coveredTiles[t]&&(e||!this._tiles[t].holdingForFade())},r.prototype.reload=function(){if(this._paused)this._shouldReloadOnResume=!0;else for(var t in this._cache.reset(),this._tiles)\"errored\"!==this._tiles[t].state&&this._reloadTile(t,\"reloading\")},r.prototype._reloadTile=function(t,e){var r=this._tiles[t];r&&(\"loading\"!==r.state&&(r.state=e),this._loadTile(r,this._tileLoaded.bind(this,r,t,e)))},r.prototype._tileLoaded=function(e,r,n,i){if(i)return e.state=\"errored\",void(404!==i.status?this._source.fire(new t.ErrorEvent(i,{tile:e})):this.update(this.transform));e.timeAdded=t.browser.now(),\"expired\"===n&&(e.refreshedUponExpiration=!0),this._setTileReloadTimer(r,e),\"raster-dem\"===this.getSource().type&&e.dem&&this._backfillDEM(e),this._state.initializeTileState(e,this.map?this.map.painter:null),this._source.fire(new t.Event(\"data\",{dataType:\"source\",tile:e,coord:e.tileID}))},r.prototype._backfillDEM=function(t){for(var e=this.getRenderableIds(),r=0;r<e.length;r++){var n=e[r];if(t.neighboringTiles&&t.neighboringTiles[n]){var i=this.getTileByID(n);a(t,i),a(i,t)}}function a(t,e){t.needsHillshadePrepare=!0;var r=e.tileID.canonical.x-t.tileID.canonical.x,n=e.tileID.canonical.y-t.tileID.canonical.y,i=Math.pow(2,t.tileID.canonical.z),a=e.tileID.key;0===r&&0===n||Math.abs(n)>1||(Math.abs(r)>1&&(1===Math.abs(r+i)?r+=i:1===Math.abs(r-i)&&(r-=i)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[a]&&(t.neighboringTiles[a].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype._retainLoadedChildren=function(t,e,r,n){for(var i in this._tiles){var a=this._tiles[i];if(!(n[i]||!a.hasData()||a.tileID.overscaledZ<=e||a.tileID.overscaledZ>r)){for(var o=a.tileID;a&&a.tileID.overscaledZ>e+1;){var s=a.tileID.scaledTo(a.tileID.overscaledZ-1);(a=this._tiles[s.key])&&a.hasData()&&(o=s)}for(var l=o;l.overscaledZ>e;)if(t[(l=l.scaledTo(l.overscaledZ-1)).key]){n[o.key]=o;break}}}},r.prototype.findLoadedParent=function(t,e){if(t.key in this._loadedParentTiles){var r=this._loadedParentTiles[t.key];return r&&r.tileID.overscaledZ>=e?r:null}for(var n=t.overscaledZ-1;n>=e;n--){var i=t.scaledTo(n),a=this._getLoadedTile(i);if(a)return a}},r.prototype._getLoadedTile=function(t){var e=this._tiles[t.key];return e&&e.hasData()?e:this._cache.getByKey(t.wrapped().key)},r.prototype.updateCacheSize=function(t){var e=(Math.ceil(t.width/this._source.tileSize)+1)*(Math.ceil(t.height/this._source.tileSize)+1),r=Math.floor(5*e),n=\"number\"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,r):r;this._cache.setMaxSize(n)},r.prototype.handleWrapJump=function(t){var e=(t-(void 0===this._prevLng?t:this._prevLng))/360,r=Math.round(e);if(this._prevLng=t,r){var n={};for(var i in this._tiles){var a=this._tiles[i];a.tileID=a.tileID.unwrapTo(a.tileID.wrap+r),n[a.tileID.key]=a}for(var o in this._tiles=n,this._timers)clearTimeout(this._timers[o]),delete this._timers[o];for(var s in this._tiles){var l=this._tiles[s];this._setTileReloadTimer(s,l)}}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var i;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?i=e.getVisibleUnwrappedCoordinates(this._source.tileID).map((function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)})):(i=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(i=i.filter((function(t){return n._source.hasTile(t)})))):i=[];var a=e.coveringZoomLevel(this._source),o=Math.max(a-r.maxOverzooming,this._source.minzoom),s=Math.max(a+r.maxUnderzooming,this._source.minzoom),l=this._updateRetainedTiles(i,a);if(Dt(this._source.type)){for(var u={},c={},f=0,h=Object.keys(l);f<h.length;f+=1){var p=h[f],d=l[p],v=this._tiles[p];if(v&&!(v.fadeEndTime&&v.fadeEndTime<=t.browser.now())){var g=this.findLoadedParent(d,o);g&&(this._addTile(g.tileID),u[g.tileID.key]=g.tileID),c[p]=d}}for(var y in this._retainLoadedChildren(c,a,s,l),u)l[y]||(this._coveredTiles[y]=!0,l[y]=u[y])}for(var m in l)this._tiles[m].clearFadeHold();for(var x=0,b=t.keysDifference(this._tiles,l);x<b.length;x+=1){var _=b[x],w=this._tiles[_];w.hasSymbolBuckets&&!w.holdingForFade()?w.setHoldDuration(this.map._fadeDuration):w.hasSymbolBuckets&&!w.symbolFadeFinished()||this._removeTile(_)}this._updateLoadedParentTileCache()}},r.prototype.releaseSymbolFadeTiles=function(){for(var t in this._tiles)this._tiles[t].holdingForFade()&&this._removeTile(t)},r.prototype._updateRetainedTiles=function(t,e){for(var n={},i={},a=Math.max(e-r.maxOverzooming,this._source.minzoom),o=Math.max(e+r.maxUnderzooming,this._source.minzoom),s={},l=0,u=t;l<u.length;l+=1){var c=u[l],f=this._addTile(c);n[c.key]=c,f.hasData()||e<this._source.maxzoom&&(s[c.key]=c)}this._retainLoadedChildren(s,e,o,n);for(var h=0,p=t;h<p.length;h+=1){var d=p[h],v=this._tiles[d.key];if(!v.hasData()){if(e+1>this._source.maxzoom){var g=d.children(this._source.maxzoom)[0],y=this.getTile(g);if(y&&y.hasData()){n[g.key]=g;continue}}else{var m=d.children(this._source.maxzoom);if(n[m[0].key]&&n[m[1].key]&&n[m[2].key]&&n[m[3].key])continue}for(var x=v.wasRequested(),b=d.overscaledZ-1;b>=a;--b){var _=d.scaledTo(b);if(i[_.key])break;if(i[_.key]=!0,!(v=this.getTile(_))&&x&&(v=this._addTile(_)),v&&(n[_.key]=_,x=v.wasRequested(),v.hasData()))break}}}return n},r.prototype._updateLoadedParentTileCache=function(){for(var t in this._loadedParentTiles={},this._tiles){for(var e=[],r=void 0,n=this._tiles[t].tileID;n.overscaledZ>0;){if(n.key in this._loadedParentTiles){r=this._loadedParentTiles[n.key];break}e.push(n.key);var i=n.scaledTo(n.overscaledZ-1);if(r=this._getLoadedTile(i))break;n=i}for(var a=0,o=e;a<o.length;a+=1){var s=o[a];this._loadedParentTiles[s]=r}}},r.prototype._addTile=function(e){var r=this._tiles[e.key];if(r)return r;(r=this._cache.getAndRemove(e))&&(this._setTileReloadTimer(e.key,r),r.tileID=e,this._state.initializeTileState(r,this.map?this.map.painter:null),this._cacheTimers[e.key]&&(clearTimeout(this._cacheTimers[e.key]),delete this._cacheTimers[e.key],this._setTileReloadTimer(e.key,r)));var n=Boolean(r);return n||(r=new t.Tile(e,this._source.tileSize*e.overscaleFactor()),this._loadTile(r,this._tileLoaded.bind(this,r,e.key,r.state))),r?(r.uses++,this._tiles[e.key]=r,n||this._source.fire(new t.Event(\"dataloading\",{tile:r,coord:r.tileID,dataType:\"source\"})),r):null},r.prototype._setTileReloadTimer=function(t,e){var r=this;t in this._timers&&(clearTimeout(this._timers[t]),delete this._timers[t]);var n=e.getExpiryTimeout();n&&(this._timers[t]=setTimeout((function(){r._reloadTile(t,\"expired\"),delete r._timers[t]}),n))},r.prototype._removeTile=function(t){var e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this._timers[t]&&(clearTimeout(this._timers[t]),delete this._timers[t]),e.uses>0||(e.hasData()&&\"reloading\"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r,n){var i=this,a=[],o=this.transform;if(!o)return a;for(var s=n?o.getCameraQueryGeometry(e):e,l=e.map((function(t){return o.pointCoordinate(t)})),u=s.map((function(t){return o.pointCoordinate(t)})),c=this.getIds(),f=1/0,h=1/0,p=-1/0,d=-1/0,v=0,g=u;v<g.length;v+=1){var y=g[v];f=Math.min(f,y.x),h=Math.min(h,y.y),p=Math.max(p,y.x),d=Math.max(d,y.y)}for(var m=function(e){var n=i._tiles[c[e]];if(!n.holdingForFade()){var s=n.tileID,v=Math.pow(2,o.zoom-n.tileID.overscaledZ),g=r*n.queryPadding*t.EXTENT/n.tileSize/v,y=[s.getTilePoint(new t.MercatorCoordinate(f,h)),s.getTilePoint(new t.MercatorCoordinate(p,d))];if(y[0].x-g<t.EXTENT&&y[0].y-g<t.EXTENT&&y[1].x+g>=0&&y[1].y+g>=0){var m=l.map((function(t){return s.getTilePoint(t)})),x=u.map((function(t){return s.getTilePoint(t)}));a.push({tile:n,tileID:s,queryGeometry:m,cameraQueryGeometry:x,scale:v})}}},x=0;x<c.length;x++)m(x);return a},r.prototype.getVisibleCoordinates=function(t){for(var e=this,r=this.getRenderableIds(t).map((function(t){return e._tiles[t].tileID})),n=0,i=r;n<i.length;n+=1){var a=i[n];a.posMatrix=this.transform.calculatePosMatrix(a.toUnwrapped())}return r},r.prototype.hasTransition=function(){if(this._source.hasTransition())return!0;if(Dt(this._source.type))for(var e in this._tiles){var r=this._tiles[e];if(void 0!==r.fadeEndTime&&r.fadeEndTime>=t.browser.now())return!0}return!1},r.prototype.setFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.updateState(t,e,r)},r.prototype.removeFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.removeFeatureState(t,e,r)},r.prototype.getFeatureState=function(t,e){return t=t||\"_geojsonTileLayer\",this._state.getState(t,e)},r.prototype.setDependencies=function(t,e,r){var n=this._tiles[t];n&&n.setDependencies(e,r)},r.prototype.reloadTilesForDependencies=function(t,e){for(var r in this._tiles)this._tiles[r].hasDependency(t,e)&&this._reloadTile(r,\"reloading\");this._cache.filter((function(r){return!r.hasDependency(t,e)}))},r}(t.Evented);function It(t,e){var r=Math.abs(2*t.wrap)-+(t.wrap<0),n=Math.abs(2*e.wrap)-+(e.wrap<0);return t.overscaledZ-e.overscaledZ||n-r||e.canonical.y-t.canonical.y||e.canonical.x-t.canonical.x}function Dt(t){return\"raster\"===t||\"image\"===t||\"video\"===t}function zt(){return new t.window.Worker(na.workerUrl)}Ot.maxOverzooming=10,Ot.maxUnderzooming=3;var Rt=\"mapboxgl_preloaded_worker_pool\",Ft=function(){this.active={}};Ft.prototype.acquire=function(t){if(!this.workers)for(this.workers=[];this.workers.length<Ft.workerCount;)this.workers.push(new zt);return this.active[t]=!0,this.workers.slice()},Ft.prototype.release=function(t){delete this.active[t],0===this.numActive()&&(this.workers.forEach((function(t){t.terminate()})),this.workers=null)},Ft.prototype.isPreloaded=function(){return!!this.active[Rt]},Ft.prototype.numActive=function(){return Object.keys(this.active).length};var Bt,Nt=Math.floor(t.browser.hardwareConcurrency/2);function jt(){return Bt||(Bt=new Ft),Bt}function Ut(e,r){var n={};for(var i in e)\"ref\"!==i&&(n[i]=e[i]);return t.refProperties.forEach((function(t){t in r&&(n[t]=r[t])})),n}function Vt(t){t=t.slice();for(var e=Object.create(null),r=0;r<t.length;r++)e[t[r].id]=t[r];for(var n=0;n<t.length;n++)\"ref\"in t[n]&&(t[n]=Ut(t[n],e[t[n].ref]));return t}Ft.workerCount=Math.max(Math.min(Nt,6),1);var Ht={setStyle:\"setStyle\",addLayer:\"addLayer\",removeLayer:\"removeLayer\",setPaintProperty:\"setPaintProperty\",setLayoutProperty:\"setLayoutProperty\",setFilter:\"setFilter\",addSource:\"addSource\",removeSource:\"removeSource\",setGeoJSONSourceData:\"setGeoJSONSourceData\",setLayerZoomRange:\"setLayerZoomRange\",setLayerProperty:\"setLayerProperty\",setCenter:\"setCenter\",setZoom:\"setZoom\",setBearing:\"setBearing\",setPitch:\"setPitch\",setSprite:\"setSprite\",setGlyphs:\"setGlyphs\",setTransition:\"setTransition\",setLight:\"setLight\"};function qt(t,e,r){r.push({command:Ht.addSource,args:[t,e[t]]})}function Gt(t,e,r){e.push({command:Ht.removeSource,args:[t]}),r[t]=!0}function Zt(t,e,r,n){Gt(t,r,n),qt(t,e,r)}function Yt(e,r,n){var i;for(i in e[n])if(e[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;for(i in r[n])if(r[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;return!0}function Wt(e,r,n,i,a,o){var s;for(s in r=r||{},e=e||{})e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}));for(s in r)r.hasOwnProperty(s)&&!e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}))}function Xt(t){return t.id}function Jt(t,e){return t[e.id]=e,t}function Kt(e,r){if(!e)return[{command:Ht.setStyle,args:[r]}];var n=[];try{if(!t.deepEqual(e.version,r.version))return[{command:Ht.setStyle,args:[r]}];t.deepEqual(e.center,r.center)||n.push({command:Ht.setCenter,args:[r.center]}),t.deepEqual(e.zoom,r.zoom)||n.push({command:Ht.setZoom,args:[r.zoom]}),t.deepEqual(e.bearing,r.bearing)||n.push({command:Ht.setBearing,args:[r.bearing]}),t.deepEqual(e.pitch,r.pitch)||n.push({command:Ht.setPitch,args:[r.pitch]}),t.deepEqual(e.sprite,r.sprite)||n.push({command:Ht.setSprite,args:[r.sprite]}),t.deepEqual(e.glyphs,r.glyphs)||n.push({command:Ht.setGlyphs,args:[r.glyphs]}),t.deepEqual(e.transition,r.transition)||n.push({command:Ht.setTransition,args:[r.transition]}),t.deepEqual(e.light,r.light)||n.push({command:Ht.setLight,args:[r.light]});var i={},a=[];!function(e,r,n,i){var a;for(a in r=r||{},e=e||{})e.hasOwnProperty(a)&&(r.hasOwnProperty(a)||Gt(a,n,i));for(a in r)r.hasOwnProperty(a)&&(e.hasOwnProperty(a)?t.deepEqual(e[a],r[a])||(\"geojson\"===e[a].type&&\"geojson\"===r[a].type&&Yt(e,r,a)?n.push({command:Ht.setGeoJSONSourceData,args:[a,r[a].data]}):Zt(a,r,n,i)):qt(a,r,n))}(e.sources,r.sources,a,i);var o=[];e.layers&&e.layers.forEach((function(t){i[t.source]?n.push({command:Ht.removeLayer,args:[t.id]}):o.push(t)})),n=n.concat(a),function(e,r,n){r=r||[];var i,a,o,s,l,u,c,f=(e=e||[]).map(Xt),h=r.map(Xt),p=e.reduce(Jt,{}),d=r.reduce(Jt,{}),v=f.slice(),g=Object.create(null);for(i=0,a=0;i<f.length;i++)o=f[i],d.hasOwnProperty(o)?a++:(n.push({command:Ht.removeLayer,args:[o]}),v.splice(v.indexOf(o,a),1));for(i=0,a=0;i<h.length;i++)o=h[h.length-1-i],v[v.length-1-i]!==o&&(p.hasOwnProperty(o)?(n.push({command:Ht.removeLayer,args:[o]}),v.splice(v.lastIndexOf(o,v.length-a),1)):a++,u=v[v.length-i],n.push({command:Ht.addLayer,args:[d[o],u]}),v.splice(v.length-i,0,o),g[o]=!0);for(i=0;i<h.length;i++)if(s=p[o=h[i]],l=d[o],!g[o]&&!t.deepEqual(s,l))if(t.deepEqual(s.source,l.source)&&t.deepEqual(s[\"source-layer\"],l[\"source-layer\"])&&t.deepEqual(s.type,l.type)){for(c in Wt(s.layout,l.layout,n,o,null,Ht.setLayoutProperty),Wt(s.paint,l.paint,n,o,null,Ht.setPaintProperty),t.deepEqual(s.filter,l.filter)||n.push({command:Ht.setFilter,args:[o,l.filter]}),t.deepEqual(s.minzoom,l.minzoom)&&t.deepEqual(s.maxzoom,l.maxzoom)||n.push({command:Ht.setLayerZoomRange,args:[o,l.minzoom,l.maxzoom]}),s)s.hasOwnProperty(c)&&\"layout\"!==c&&\"paint\"!==c&&\"filter\"!==c&&\"metadata\"!==c&&\"minzoom\"!==c&&\"maxzoom\"!==c&&(0===c.indexOf(\"paint.\")?Wt(s[c],l[c],n,o,c.slice(6),Ht.setPaintProperty):t.deepEqual(s[c],l[c])||n.push({command:Ht.setLayerProperty,args:[o,c,l[c]]}));for(c in l)l.hasOwnProperty(c)&&!s.hasOwnProperty(c)&&\"layout\"!==c&&\"paint\"!==c&&\"filter\"!==c&&\"metadata\"!==c&&\"minzoom\"!==c&&\"maxzoom\"!==c&&(0===c.indexOf(\"paint.\")?Wt(s[c],l[c],n,o,c.slice(6),Ht.setPaintProperty):t.deepEqual(s[c],l[c])||n.push({command:Ht.setLayerProperty,args:[o,c,l[c]]}))}else n.push({command:Ht.removeLayer,args:[o]}),u=v[v.lastIndexOf(o)+1],n.push({command:Ht.addLayer,args:[l,u]})}(o,r.layers,n)}catch(t){console.warn(\"Unable to compute style diff:\",t),n=[{command:Ht.setStyle,args:[r]}]}return n}var $t=function(t,e){this.reset(t,e)};$t.prototype.reset=function(t,e){this.points=t||[],this._distances=[0];for(var r=1;r<this.points.length;r++)this._distances[r]=this._distances[r-1]+this.points[r].dist(this.points[r-1]);this.length=this._distances[this._distances.length-1],this.padding=Math.min(e||0,.5*this.length),this.paddedLength=this.length-2*this.padding},$t.prototype.lerp=function(e){if(1===this.points.length)return this.points[0];e=t.clamp(e,0,1);for(var r=1,n=this._distances[r],i=e*this.paddedLength+this.padding;n<i&&r<this._distances.length;)n=this._distances[++r];var a=r-1,o=this._distances[a],s=n-o,l=s>0?(i-o)/s:0;return this.points[a].mult(1-l).add(this.points[r].mult(l))};var Qt=function(t,e,r){var n=this.boxCells=[],i=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var a=0;a<this.xCellCount*this.yCellCount;a++)n.push([]),i.push([]);this.circleKeys=[],this.boxKeys=[],this.bboxes=[],this.circles=[],this.width=t,this.height=e,this.xScale=this.xCellCount/t,this.yScale=this.yCellCount/e,this.boxUid=0,this.circleUid=0};function te(e,r,n,i,a){var o=t.create();return r?(t.scale(o,o,[1/a,1/a,1]),n||t.rotateZ(o,o,i.angle)):t.multiply(o,i.labelPlaneMatrix,e),o}function ee(e,r,n,i,a){if(r){var o=t.clone(e);return t.scale(o,o,[a,a,1]),n||t.rotateZ(o,o,-i.angle),o}return i.glCoordMatrix}function re(e,r){var n=[e.x,e.y,0,1];pe(n,n,r);var i=n[3];return{point:new t.Point(n[0]/i,n[1]/i),signedDistanceFromCamera:i}}function ne(t,e){return.5+t/e*.5}function ie(t,e){var r=t[0]/t[3],n=t[1]/t[3];return r>=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function ae(e,r,n,i,a,o,s,l){var u=i?e.textSizeData:e.iconSizeData,c=t.evaluateSizeForZoom(u,n.transform.zoom),f=[256/n.width*2+1,256/n.height*2+1],h=i?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;h.clear();for(var p=e.lineVertexArray,d=i?e.text.placedSymbolArray:e.icon.placedSymbolArray,v=n.transform.width/n.transform.height,g=!1,y=0;y<d.length;y++){var m=d.get(y);if(m.hidden||m.writingMode===t.WritingMode.vertical&&!g)he(m.numGlyphs,h);else{g=!1;var x=[m.anchorX,m.anchorY,0,1];if(t.transformMat4(x,x,r),ie(x,f)){var b=x[3],_=ne(n.transform.cameraToCenterDistance,b),w=t.evaluateSizeForFeature(u,c,m),T=s?w/_:w*_,k=new t.Point(m.anchorX,m.anchorY),A=re(k,a).point,M={},S=le(m,T,!1,l,r,a,o,e.glyphOffsetArray,p,h,A,k,M,v);g=S.useVertical,(S.notEnoughRoom||g||S.needsFlipping&&le(m,T,!0,l,r,a,o,e.glyphOffsetArray,p,h,A,k,M,v).notEnoughRoom)&&he(m.numGlyphs,h)}else he(m.numGlyphs,h)}}i?e.text.dynamicLayoutVertexBuffer.updateData(h):e.icon.dynamicLayoutVertexBuffer.updateData(h)}function oe(t,e,r,n,i,a,o,s,l,u,c){var f=s.glyphStartIndex+s.numGlyphs,h=s.lineStartIndex,p=s.lineStartIndex+s.lineLength,d=e.getoffsetX(s.glyphStartIndex),v=e.getoffsetX(f-1),g=ce(t*d,r,n,i,a,o,s.segment,h,p,l,u,c);if(!g)return null;var y=ce(t*v,r,n,i,a,o,s.segment,h,p,l,u,c);return y?{first:g,last:y}:null}function se(e,r,n,i){return e===t.WritingMode.horizontal&&Math.abs(n.y-r.y)>Math.abs(n.x-r.x)*i?{useVertical:!0}:(e===t.WritingMode.vertical?r.y<n.y:r.x>n.x)?{needsFlipping:!0}:null}function le(e,r,n,i,a,o,s,l,u,c,f,h,p,d){var v,g=r/24,y=e.lineOffsetX*g,m=e.lineOffsetY*g;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,b=e.lineStartIndex,_=e.lineStartIndex+e.lineLength,w=oe(g,l,y,m,n,f,h,e,u,o,p);if(!w)return{notEnoughRoom:!0};var T=re(w.first.point,s).point,k=re(w.last.point,s).point;if(i&&!n){var A=se(e.writingMode,T,k,d);if(A)return A}v=[w.first];for(var M=e.glyphStartIndex+1;M<x-1;M++)v.push(ce(g*l.getoffsetX(M),y,m,n,f,h,e.segment,b,_,u,o,p));v.push(w.last)}else{if(i&&!n){var S=re(h,a).point,E=e.lineStartIndex+e.segment+1,L=new t.Point(u.getx(E),u.gety(E)),C=re(L,a),P=C.signedDistanceFromCamera>0?C.point:ue(h,L,S,1,a),O=se(e.writingMode,S,P,d);if(O)return O}var I=ce(g*l.getoffsetX(e.glyphStartIndex),y,m,n,f,h,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,u,o,p);if(!I)return{notEnoughRoom:!0};v=[I]}for(var D=0,z=v;D<z.length;D+=1){var R=z[D];t.addDynamicAttributes(c,R.point,R.angle)}return{}}function ue(t,e,r,n,i){var a=re(t.add(t.sub(e)._unit()),i).point,o=r.sub(a);return r.add(o._mult(n/o.mag()))}function ce(e,r,n,i,a,o,s,l,u,c,f,h){var p=i?e-r:e+r,d=p>0?1:-1,v=0;i&&(d*=-1,v=Math.PI),d<0&&(v+=Math.PI);for(var g=d>0?l+s:l+s+1,y=a,m=a,x=0,b=0,_=Math.abs(p),w=[];x+b<=_;){if((g+=d)<l||g>=u)return null;if(m=y,w.push(y),void 0===(y=h[g])){var T=new t.Point(c.getx(g),c.gety(g)),k=re(T,f);if(k.signedDistanceFromCamera>0)y=h[g]=k.point;else{var A=g-d;y=ue(0===x?o:new t.Point(c.getx(A),c.gety(A)),T,m,_-x+1,f)}}x+=b,b=m.dist(y)}var M=(_-x)/b,S=y.sub(m),E=S.mult(M)._add(m);E._add(S._unit()._perp()._mult(n*d));var L=v+Math.atan2(y.y-m.y,y.x-m.x);return w.push(E),{point:E,angle:L,path:w}}Qt.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Qt.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},Qt.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},Qt.prototype._insertBoxCell=function(t,e,r,n,i,a){this.boxCells[i].push(a)},Qt.prototype._insertCircleCell=function(t,e,r,n,i,a){this.circleCells[i].push(a)},Qt.prototype._query=function(t,e,r,n,i,a){if(r<0||t>this.width||n<0||e>this.height)return!i&&[];var o=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(i)return!0;for(var s=0;s<this.boxKeys.length;s++)o.push({key:this.boxKeys[s],x1:this.bboxes[4*s],y1:this.bboxes[4*s+1],x2:this.bboxes[4*s+2],y2:this.bboxes[4*s+3]});for(var l=0;l<this.circleKeys.length;l++){var u=this.circles[3*l],c=this.circles[3*l+1],f=this.circles[3*l+2];o.push({key:this.circleKeys[l],x1:u-f,y1:c-f,x2:u+f,y2:c+f})}return a?o.filter(a):o}var h={hitTest:i,seenUids:{box:{},circle:{}}};return this._forEachCell(t,e,r,n,this._queryCell,o,h,a),i?o.length>0:o},Qt.prototype._queryCircle=function(t,e,r,n,i){var a=t-r,o=t+r,s=e-r,l=e+r;if(o<0||a>this.width||l<0||s>this.height)return!n&&[];var u=[],c={hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}};return this._forEachCell(a,s,o,l,this._queryCellCircle,u,c,i),n?u.length>0:u},Qt.prototype.query=function(t,e,r,n,i){return this._query(t,e,r,n,!1,i)},Qt.prototype.hitTest=function(t,e,r,n,i){return this._query(t,e,r,n,!0,i)},Qt.prototype.hitTestCircle=function(t,e,r,n){return this._queryCircle(t,e,r,!0,n)},Qt.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=o.seenUids,u=this.boxCells[i];if(null!==u)for(var c=this.bboxes,f=0,h=u;f<h.length;f+=1){var p=h[f];if(!l.box[p]){l.box[p]=!0;var d=4*p;if(t<=c[d+2]&&e<=c[d+3]&&r>=c[d+0]&&n>=c[d+1]&&(!s||s(this.boxKeys[p]))){if(o.hitTest)return a.push(!0),!0;a.push({key:this.boxKeys[p],x1:c[d],y1:c[d+1],x2:c[d+2],y2:c[d+3]})}}}var v=this.circleCells[i];if(null!==v)for(var g=this.circles,y=0,m=v;y<m.length;y+=1){var x=m[y];if(!l.circle[x]){l.circle[x]=!0;var b=3*x;if(this._circleAndRectCollide(g[b],g[b+1],g[b+2],t,e,r,n)&&(!s||s(this.circleKeys[x]))){if(o.hitTest)return a.push(!0),!0;var _=g[b],w=g[b+1],T=g[b+2];a.push({key:this.circleKeys[x],x1:_-T,y1:w-T,x2:_+T,y2:w+T})}}}},Qt.prototype._queryCellCircle=function(t,e,r,n,i,a,o,s){var l=o.circle,u=o.seenUids,c=this.boxCells[i];if(null!==c)for(var f=this.bboxes,h=0,p=c;h<p.length;h+=1){var d=p[h];if(!u.box[d]){u.box[d]=!0;var v=4*d;if(this._circleAndRectCollide(l.x,l.y,l.radius,f[v+0],f[v+1],f[v+2],f[v+3])&&(!s||s(this.boxKeys[d])))return a.push(!0),!0}}var g=this.circleCells[i];if(null!==g)for(var y=this.circles,m=0,x=g;m<x.length;m+=1){var b=x[m];if(!u.circle[b]){u.circle[b]=!0;var _=3*b;if(this._circlesCollide(y[_],y[_+1],y[_+2],l.x,l.y,l.radius)&&(!s||s(this.circleKeys[b])))return a.push(!0),!0}}},Qt.prototype._forEachCell=function(t,e,r,n,i,a,o,s){for(var l=this._convertToXCellCoord(t),u=this._convertToYCellCoord(e),c=this._convertToXCellCoord(r),f=this._convertToYCellCoord(n),h=l;h<=c;h++)for(var p=u;p<=f;p++){var d=this.xCellCount*p+h;if(i.call(this,t,e,r,n,d,a,o,s))return}},Qt.prototype._convertToXCellCoord=function(t){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(t*this.xScale)))},Qt.prototype._convertToYCellCoord=function(t){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(t*this.yScale)))},Qt.prototype._circlesCollide=function(t,e,r,n,i,a){var o=n-t,s=i-e,l=r+a;return l*l>o*o+s*s},Qt.prototype._circleAndRectCollide=function(t,e,r,n,i,a,o){var s=(a-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var u=(o-i)/2,c=Math.abs(e-(i+u));if(c>u+r)return!1;if(l<=s||c<=u)return!0;var f=l-s,h=c-u;return f*f+h*h<=r*r};var fe=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function he(t,e){for(var r=0;r<t;r++){var n=e.length;e.resize(n+4),e.float32.set(fe,3*n)}}function pe(t,e,r){var n=e[0],i=e[1];return t[0]=r[0]*n+r[4]*i+r[12],t[1]=r[1]*n+r[5]*i+r[13],t[3]=r[3]*n+r[7]*i+r[15],t}var de=100,ve=function(t,e,r){void 0===e&&(e=new Qt(t.width+200,t.height+200,25)),void 0===r&&(r=new Qt(t.width+200,t.height+200,25)),this.transform=t,this.grid=e,this.ignoredGrid=r,this.pitchfactor=Math.cos(t._pitch)*t.cameraToCenterDistance,this.screenRightBoundary=t.width+de,this.screenBottomBoundary=t.height+de,this.gridRightBoundary=t.width+200,this.gridBottomBoundary=t.height+200};function ge(e,r,n){return r*(t.EXTENT/(e.tileSize*Math.pow(2,n-e.tileID.overscaledZ)))}ve.prototype.placeCollisionBox=function(t,e,r,n,i){var a=this.projectAndGetPerspectiveRatio(n,t.anchorPointX,t.anchorPointY),o=r*a.perspectiveRatio,s=t.x1*o+a.point.x,l=t.y1*o+a.point.y,u=t.x2*o+a.point.x,c=t.y2*o+a.point.y;return!this.isInsideGrid(s,l,u,c)||!e&&this.grid.hitTest(s,l,u,c,i)?{box:[],offscreen:!1}:{box:[s,l,u,c],offscreen:this.isOffscreen(s,l,u,c)}},ve.prototype.placeCollisionCircles=function(e,r,n,i,a,o,s,l,u,c,f,h,p){var d=[],v=new t.Point(r.anchorX,r.anchorY),g=re(v,o),y=ne(this.transform.cameraToCenterDistance,g.signedDistanceFromCamera),m=(c?a/y:a*y)/t.ONE_EM,x=re(v,s).point,b=oe(m,i,r.lineOffsetX*m,r.lineOffsetY*m,!1,x,v,r,n,s,{}),_=!1,w=!1,T=!0;if(b){for(var k=.5*h*y+p,A=new t.Point(-100,-100),M=new t.Point(this.screenRightBoundary,this.screenBottomBoundary),S=new $t,E=b.first,L=b.last,C=[],P=E.path.length-1;P>=1;P--)C.push(E.path[P]);for(var O=1;O<L.path.length;O++)C.push(L.path[O]);var I=2.5*k;if(l){var D=C.map((function(t){return re(t,l)}));C=D.some((function(t){return t.signedDistanceFromCamera<=0}))?[]:D.map((function(t){return t.point}))}var z=[];if(C.length>0){for(var R=C[0].clone(),F=C[0].clone(),B=1;B<C.length;B++)R.x=Math.min(R.x,C[B].x),R.y=Math.min(R.y,C[B].y),F.x=Math.max(F.x,C[B].x),F.y=Math.max(F.y,C[B].y);z=R.x>=A.x&&F.x<=M.x&&R.y>=A.y&&F.y<=M.y?[C]:F.x<A.x||R.x>M.x||F.y<A.y||R.y>M.y?[]:t.clipLine([C],A.x,A.y,M.x,M.y)}for(var N=0,j=z;N<j.length;N+=1){var U=j[N];S.reset(U,.25*k);var V;V=S.length<=.5*k?1:Math.ceil(S.paddedLength/I)+1;for(var H=0;H<V;H++){var q=H/Math.max(V-1,1),G=S.lerp(q),Z=G.x+de,Y=G.y+de;d.push(Z,Y,k,0);var W=Z-k,X=Y-k,J=Z+k,K=Y+k;if(T=T&&this.isOffscreen(W,X,J,K),w=w||this.isInsideGrid(W,X,J,K),!e&&this.grid.hitTestCircle(Z,Y,k,f)&&(_=!0,!u))return{circles:[],offscreen:!1,collisionDetected:_}}}}return{circles:!u&&_||!w?[]:d,offscreen:T,collisionDetected:_}},ve.prototype.queryRenderedSymbols=function(e){if(0===e.length||0===this.grid.keysLength()&&0===this.ignoredGrid.keysLength())return{};for(var r=[],n=1/0,i=1/0,a=-1/0,o=-1/0,s=0,l=e;s<l.length;s+=1){var u=l[s],c=new t.Point(u.x+de,u.y+de);n=Math.min(n,c.x),i=Math.min(i,c.y),a=Math.max(a,c.x),o=Math.max(o,c.y),r.push(c)}for(var f={},h={},p=0,d=this.grid.query(n,i,a,o).concat(this.ignoredGrid.query(n,i,a,o));p<d.length;p+=1){var v=d[p],g=v.key;if(void 0===f[g.bucketInstanceId]&&(f[g.bucketInstanceId]={}),!f[g.bucketInstanceId][g.featureIndex]){var y=[new t.Point(v.x1,v.y1),new t.Point(v.x2,v.y1),new t.Point(v.x2,v.y2),new t.Point(v.x1,v.y2)];t.polygonIntersectsPolygon(r,y)&&(f[g.bucketInstanceId][g.featureIndex]=!0,void 0===h[g.bucketInstanceId]&&(h[g.bucketInstanceId]=[]),h[g.bucketInstanceId].push(g.featureIndex))}}return h},ve.prototype.insertCollisionBox=function(t,e,r,n,i){var a={bucketInstanceId:r,featureIndex:n,collisionGroupID:i};(e?this.ignoredGrid:this.grid).insert(a,t[0],t[1],t[2],t[3])},ve.prototype.insertCollisionCircles=function(t,e,r,n,i){for(var a=e?this.ignoredGrid:this.grid,o={bucketInstanceId:r,featureIndex:n,collisionGroupID:i},s=0;s<t.length;s+=4)a.insertCircle(o,t[s],t[s+1],t[s+2])},ve.prototype.projectAndGetPerspectiveRatio=function(e,r,n){var i=[r,n,0,1];return pe(i,i,e),{point:new t.Point((i[0]/i[3]+1)/2*this.transform.width+de,(-i[1]/i[3]+1)/2*this.transform.height+de),perspectiveRatio:.5+this.transform.cameraToCenterDistance/i[3]*.5}},ve.prototype.isOffscreen=function(t,e,r,n){return r<de||t>=this.screenRightBoundary||n<de||e>this.screenBottomBoundary},ve.prototype.isInsideGrid=function(t,e,r,n){return r>=0&&t<this.gridRightBoundary&&n>=0&&e<this.gridBottomBoundary},ve.prototype.getViewportMatrix=function(){var e=t.identity([]);return t.translate(e,e,[-100,-100,0]),e};var ye=function(t,e,r,n){this.opacity=t?Math.max(0,Math.min(1,t.opacity+(t.placed?e:-e))):n&&r?1:0,this.placed=r};ye.prototype.isHidden=function(){return 0===this.opacity&&!this.placed};var me=function(t,e,r,n,i){this.text=new ye(t?t.text:null,e,r,i),this.icon=new ye(t?t.icon:null,e,n,i)};me.prototype.isHidden=function(){return this.text.isHidden()&&this.icon.isHidden()};var xe=function(t,e,r){this.text=t,this.icon=e,this.skipFade=r},be=function(){this.invProjMatrix=t.create(),this.viewportMatrix=t.create(),this.circles=[]},_e=function(t,e,r,n,i){this.bucketInstanceId=t,this.featureIndex=e,this.sourceLayerIndex=r,this.bucketIndex=n,this.tileID=i},we=function(t){this.crossSourceCollisions=t,this.maxGroupID=0,this.collisionGroups={}};function Te(e,r,n,i,a){var o=t.getAnchorAlignment(e),s=-(o.horizontalAlign-.5)*r,l=-(o.verticalAlign-.5)*n,u=t.evaluateVariableOffset(e,i);return new t.Point(s+u[0]*a,l+u[1]*a)}function ke(e,r,n,i,a,o){var s=e.x1,l=e.x2,u=e.y1,c=e.y2,f=e.anchorPointX,h=e.anchorPointY,p=new t.Point(r,n);return i&&p._rotate(a?o:-o),{x1:s+p.x,y1:u+p.y,x2:l+p.x,y2:c+p.y,anchorPointX:f,anchorPointY:h}}we.prototype.get=function(t){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[t]){var e=++this.maxGroupID;this.collisionGroups[t]={ID:e,predicate:function(t){return t.collisionGroupID===e}}}return this.collisionGroups[t]};var Ae=function(t,e,r,n){this.transform=t.clone(),this.collisionIndex=new ve(this.transform),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=e,this.retainedQueryData={},this.collisionGroups=new we(r),this.collisionCircleArrays={},this.prevPlacement=n,n&&(n.prevPlacement=void 0),this.placedOrientations={}};function Me(t,e,r,n,i){t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0)}Ae.prototype.getBucketParts=function(e,r,n,i){var a=n.getBucket(r),o=n.latestFeatureIndex;if(a&&o&&r.id===a.layerIds[0]){var s=n.collisionBoxArray,l=a.layers[0].layout,u=Math.pow(2,this.transform.zoom-n.tileID.overscaledZ),c=n.tileSize/t.EXTENT,f=this.transform.calculatePosMatrix(n.tileID.toUnwrapped()),h=\"map\"===l.get(\"text-pitch-alignment\"),p=\"map\"===l.get(\"text-rotation-alignment\"),d=ge(n,1,this.transform.zoom),v=te(f,h,p,this.transform,d),g=null;if(h){var y=ee(f,h,p,this.transform,d);g=t.multiply([],this.transform.labelPlaneMatrix,y)}this.retainedQueryData[a.bucketInstanceId]=new _e(a.bucketInstanceId,o,a.sourceLayerIndex,a.index,n.tileID);var m={bucket:a,layout:l,posMatrix:f,textLabelPlaneMatrix:v,labelToScreenMatrix:g,scale:u,textPixelRatio:c,holdingForFade:n.holdingForFade(),collisionBoxArray:s,partiallyEvaluatedTextSize:t.evaluateSizeForZoom(a.textSizeData,this.transform.zoom),collisionGroup:this.collisionGroups.get(a.sourceID)};if(i)for(var x=0,b=a.sortKeyRanges;x<b.length;x+=1){var _=b[x],w=_.sortKey,T=_.symbolInstanceStart,k=_.symbolInstanceEnd;e.push({sortKey:w,symbolInstanceStart:T,symbolInstanceEnd:k,parameters:m})}else e.push({symbolInstanceStart:0,symbolInstanceEnd:a.symbolInstances.length,parameters:m})}},Ae.prototype.attemptAnchorPlacement=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d){var v,g=[f.textOffset0,f.textOffset1],y=Te(t,r,n,g,i),m=this.collisionIndex.placeCollisionBox(ke(e,y.x,y.y,a,o,this.transform.angle),c,s,l,u.predicate);if(!d||0!==this.collisionIndex.placeCollisionBox(ke(d,y.x,y.y,a,o,this.transform.angle),c,s,l,u.predicate).box.length)return m.box.length>0?(this.prevPlacement&&this.prevPlacement.variableOffsets[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID].text&&(v=this.prevPlacement.variableOffsets[f.crossTileID].anchor),this.variableOffsets[f.crossTileID]={textOffset:g,width:r,height:n,anchor:t,textBoxScale:i,prevAnchor:v},this.markUsedJustification(h,t,f,p),h.allowVerticalPlacement&&(this.markUsedOrientation(h,p,f),this.placedOrientations[f.crossTileID]=p),{shift:y,placedGlyphBoxes:m}):void 0},Ae.prototype.placeLayerBucketPart=function(e,r,n){var i=this,a=e.parameters,o=a.bucket,s=a.layout,l=a.posMatrix,u=a.textLabelPlaneMatrix,c=a.labelToScreenMatrix,f=a.textPixelRatio,h=a.holdingForFade,p=a.collisionBoxArray,d=a.partiallyEvaluatedTextSize,v=a.collisionGroup,g=s.get(\"text-optional\"),y=s.get(\"icon-optional\"),m=s.get(\"text-allow-overlap\"),x=s.get(\"icon-allow-overlap\"),b=\"map\"===s.get(\"text-rotation-alignment\"),_=\"map\"===s.get(\"text-pitch-alignment\"),w=\"none\"!==s.get(\"icon-text-fit\"),T=\"viewport-y\"===s.get(\"symbol-z-order\"),k=m&&(x||!o.hasIconData()||y),A=x&&(m||!o.hasTextData()||g);!o.collisionArrays&&p&&o.deserializeCollisionBoxes(p);var M=function(e,a){if(!r[e.crossTileID])if(h)i.placements[e.crossTileID]=new xe(!1,!1,!1);else{var p,T=!1,M=!1,S=!0,E=null,L={box:null,offscreen:null},C={box:null,offscreen:null},P=null,O=null,I=0,D=0,z=0;a.textFeatureIndex?I=a.textFeatureIndex:e.useRuntimeCollisionCircles&&(I=e.featureIndex),a.verticalTextFeatureIndex&&(D=a.verticalTextFeatureIndex);var R=a.textBox;if(R){var F=function(r){var n=t.WritingMode.horizontal;if(o.allowVerticalPlacement&&!r&&i.prevPlacement){var a=i.prevPlacement.placedOrientations[e.crossTileID];a&&(i.placedOrientations[e.crossTileID]=a,n=a,i.markUsedOrientation(o,n,e))}return n},B=function(r,n){if(o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&a.verticalTextBox)for(var i=0,s=o.writingModes;i<s.length&&(s[i]===t.WritingMode.vertical?(L=n(),C=L):L=r(),!(L&&L.box&&L.box.length));i+=1);else L=r()};if(s.get(\"text-variable-anchor\")){var N=s.get(\"text-variable-anchor\");if(i.prevPlacement&&i.prevPlacement.variableOffsets[e.crossTileID]){var j=i.prevPlacement.variableOffsets[e.crossTileID];N.indexOf(j.anchor)>0&&(N=N.filter((function(t){return t!==j.anchor}))).unshift(j.anchor)}var U=function(t,r,n){for(var a=t.x2-t.x1,s=t.y2-t.y1,u=e.textBoxScale,c=w&&!x?r:null,h={box:[],offscreen:!1},p=m?2*N.length:N.length,d=0;d<p;++d){var g=N[d%N.length],y=d>=N.length,k=i.attemptAnchorPlacement(g,t,a,s,u,b,_,f,l,v,y,e,o,n,c);if(k&&(h=k.placedGlyphBoxes)&&h.box&&h.box.length){T=!0,E=k.shift;break}}return h};B((function(){return U(R,a.iconBox,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox,n=L&&L.box&&L.box.length;return o.allowVerticalPlacement&&!n&&e.numVerticalGlyphVertices>0&&r?U(r,a.verticalIconBox,t.WritingMode.vertical):{box:null,offscreen:null}})),L&&(T=L.box,S=L.offscreen);var V=F(L&&L.box);if(!T&&i.prevPlacement){var H=i.prevPlacement.variableOffsets[e.crossTileID];H&&(i.variableOffsets[e.crossTileID]=H,i.markUsedJustification(o,H.anchor,e,V))}}else{var q=function(t,r){var n=i.collisionIndex.placeCollisionBox(t,m,f,l,v.predicate);return n&&n.box&&n.box.length&&(i.markUsedOrientation(o,r,e),i.placedOrientations[e.crossTileID]=r),n};B((function(){return q(R,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox;return o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&r?q(r,t.WritingMode.vertical):{box:null,offscreen:null}})),F(L&&L.box&&L.box.length)}}if(T=(p=L)&&p.box&&p.box.length>0,S=p&&p.offscreen,e.useRuntimeCollisionCircles){var G=o.text.placedSymbolArray.get(e.centerJustifiedTextSymbolIndex),Z=t.evaluateSizeForFeature(o.textSizeData,d,G),Y=s.get(\"text-padding\"),W=e.collisionCircleDiameter;P=i.collisionIndex.placeCollisionCircles(m,G,o.lineVertexArray,o.glyphOffsetArray,Z,l,u,c,n,_,v.predicate,W,Y),T=m||P.circles.length>0&&!P.collisionDetected,S=S&&P.offscreen}if(a.iconFeatureIndex&&(z=a.iconFeatureIndex),a.iconBox){var X=function(t){var e=w&&E?ke(t,E.x,E.y,b,_,i.transform.angle):t;return i.collisionIndex.placeCollisionBox(e,x,f,l,v.predicate)};M=C&&C.box&&C.box.length&&a.verticalIconBox?(O=X(a.verticalIconBox)).box.length>0:(O=X(a.iconBox)).box.length>0,S=S&&O.offscreen}var J=g||0===e.numHorizontalGlyphVertices&&0===e.numVerticalGlyphVertices,K=y||0===e.numIconVertices;if(J||K?K?J||(M=M&&T):T=M&&T:M=T=M&&T,T&&p&&p.box&&(C&&C.box&&D?i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,D,v.ID):i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,I,v.ID)),M&&O&&i.collisionIndex.insertCollisionBox(O.box,s.get(\"icon-ignore-placement\"),o.bucketInstanceId,z,v.ID),P&&(T&&i.collisionIndex.insertCollisionCircles(P.circles,s.get(\"text-ignore-placement\"),o.bucketInstanceId,I,v.ID),n)){var $=o.bucketInstanceId,Q=i.collisionCircleArrays[$];void 0===Q&&(Q=i.collisionCircleArrays[$]=new be);for(var tt=0;tt<P.circles.length;tt+=4)Q.circles.push(P.circles[tt+0]),Q.circles.push(P.circles[tt+1]),Q.circles.push(P.circles[tt+2]),Q.circles.push(P.collisionDetected?1:0)}i.placements[e.crossTileID]=new xe(T||k,M||A,S||o.justReloaded),r[e.crossTileID]=!0}};if(T)for(var S=o.getSortedSymbolIndexes(this.transform.angle),E=S.length-1;E>=0;--E){var L=S[E];M(o.symbolInstances.get(L),o.collisionArrays[L])}else for(var C=e.symbolInstanceStart;C<e.symbolInstanceEnd;C++)M(o.symbolInstances.get(C),o.collisionArrays[C]);if(n&&o.bucketInstanceId in this.collisionCircleArrays){var P=this.collisionCircleArrays[o.bucketInstanceId];t.invert(P.invProjMatrix,l),P.viewportMatrix=this.collisionIndex.getViewportMatrix()}o.justReloaded=!1},Ae.prototype.markUsedJustification=function(e,r,n,i){var a,o={left:n.leftJustifiedTextSymbolIndex,center:n.centerJustifiedTextSymbolIndex,right:n.rightJustifiedTextSymbolIndex};a=i===t.WritingMode.vertical?n.verticalPlacedTextSymbolIndex:o[t.getAnchorJustification(r)];for(var s=0,l=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex,n.verticalPlacedTextSymbolIndex];s<l.length;s+=1){var u=l[s];u>=0&&(e.text.placedSymbolArray.get(u).crossTileID=a>=0&&u!==a?0:n.crossTileID)}},Ae.prototype.markUsedOrientation=function(e,r,n){for(var i=r===t.WritingMode.horizontal||r===t.WritingMode.horizontalOnly?r:0,a=r===t.WritingMode.vertical?r:0,o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];o<s.length;o+=1){var l=s[o];e.text.placedSymbolArray.get(l).placedOrientation=i}n.verticalPlacedTextSymbolIndex&&(e.text.placedSymbolArray.get(n.verticalPlacedTextSymbolIndex).placedOrientation=a)},Ae.prototype.commit=function(t){this.commitTime=t,this.zoomAtLastRecencyCheck=this.transform.zoom;var e=this.prevPlacement,r=!1;this.prevZoomAdjustment=e?e.zoomAdjustment(this.transform.zoom):0;var n=e?e.symbolFadeChange(t):1,i=e?e.opacities:{},a=e?e.variableOffsets:{},o=e?e.placedOrientations:{};for(var s in this.placements){var l=this.placements[s],u=i[s];u?(this.opacities[s]=new me(u,n,l.text,l.icon),r=r||l.text!==u.text.placed||l.icon!==u.icon.placed):(this.opacities[s]=new me(null,n,l.text,l.icon,l.skipFade),r=r||l.text||l.icon)}for(var c in i){var f=i[c];if(!this.opacities[c]){var h=new me(f,n,!1,!1);h.isHidden()||(this.opacities[c]=h,r=r||f.text.placed||f.icon.placed)}}for(var p in a)this.variableOffsets[p]||!this.opacities[p]||this.opacities[p].isHidden()||(this.variableOffsets[p]=a[p]);for(var d in o)this.placedOrientations[d]||!this.opacities[d]||this.opacities[d].isHidden()||(this.placedOrientations[d]=o[d]);r?this.lastPlacementChangeTime=t:\"number\"!=typeof this.lastPlacementChangeTime&&(this.lastPlacementChangeTime=e?e.lastPlacementChangeTime:t)},Ae.prototype.updateLayerOpacities=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1){var a=i[n],o=a.getBucket(t);o&&a.latestFeatureIndex&&t.id===o.layerIds[0]&&this.updateBucketOpacities(o,r,a.collisionBoxArray)}},Ae.prototype.updateBucketOpacities=function(e,r,n){var i=this;e.hasTextData()&&e.text.opacityVertexArray.clear(),e.hasIconData()&&e.icon.opacityVertexArray.clear(),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexArray.clear(),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexArray.clear();var a=e.layers[0].layout,o=new me(null,0,!1,!1,!0),s=a.get(\"text-allow-overlap\"),l=a.get(\"icon-allow-overlap\"),u=a.get(\"text-variable-anchor\"),c=\"map\"===a.get(\"text-rotation-alignment\"),f=\"map\"===a.get(\"text-pitch-alignment\"),h=\"none\"!==a.get(\"icon-text-fit\"),p=new me(null,0,s&&(l||!e.hasIconData()||a.get(\"icon-optional\")),l&&(s||!e.hasTextData()||a.get(\"text-optional\")),!0);!e.collisionArrays&&n&&(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData())&&e.deserializeCollisionBoxes(n);for(var d=function(t,e,r){for(var n=0;n<e/4;n++)t.opacityVertexArray.emplaceBack(r)},v=function(n){var a=e.symbolInstances.get(n),s=a.numHorizontalGlyphVertices,l=a.numVerticalGlyphVertices,v=a.crossTileID,g=r[v],y=i.opacities[v];g?y=o:y||(y=p,i.opacities[v]=y),r[v]=!0;var m=s>0||l>0,x=a.numIconVertices>0,b=i.placedOrientations[a.crossTileID],_=b===t.WritingMode.vertical,w=b===t.WritingMode.horizontal||b===t.WritingMode.horizontalOnly;if(m){var T=De(y.text),k=_?ze:T;d(e.text,s,k);var A=w?ze:T;d(e.text,l,A);var M=y.text.isHidden();[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t){t>=0&&(e.text.placedSymbolArray.get(t).hidden=M||_?1:0)})),a.verticalPlacedTextSymbolIndex>=0&&(e.text.placedSymbolArray.get(a.verticalPlacedTextSymbolIndex).hidden=M||w?1:0);var S=i.variableOffsets[a.crossTileID];S&&i.markUsedJustification(e,S.anchor,a,b);var E=i.placedOrientations[a.crossTileID];E&&(i.markUsedJustification(e,\"left\",a,E),i.markUsedOrientation(e,E,a))}if(x){var L=De(y.icon),C=!(h&&a.verticalPlacedIconSymbolIndex&&_);if(a.placedIconSymbolIndex>=0){var P=C?L:ze;d(e.icon,a.numIconVertices,P),e.icon.placedSymbolArray.get(a.placedIconSymbolIndex).hidden=y.icon.isHidden()}if(a.verticalPlacedIconSymbolIndex>=0){var O=C?ze:L;d(e.icon,a.numVerticalIconVertices,O),e.icon.placedSymbolArray.get(a.verticalPlacedIconSymbolIndex).hidden=y.icon.isHidden()}}if(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData()){var I=e.collisionArrays[n];if(I){var D=new t.Point(0,0);if(I.textBox||I.verticalTextBox){var z=!0;if(u){var R=i.variableOffsets[v];R?(D=Te(R.anchor,R.width,R.height,R.textOffset,R.textBoxScale),c&&D._rotate(f?i.transform.angle:-i.transform.angle)):z=!1}I.textBox&&Me(e.textCollisionBox.collisionVertexArray,y.text.placed,!z||_,D.x,D.y),I.verticalTextBox&&Me(e.textCollisionBox.collisionVertexArray,y.text.placed,!z||w,D.x,D.y)}var F=Boolean(!w&&I.verticalIconBox);I.iconBox&&Me(e.iconCollisionBox.collisionVertexArray,y.icon.placed,F,h?D.x:0,h?D.y:0),I.verticalIconBox&&Me(e.iconCollisionBox.collisionVertexArray,y.icon.placed,!F,h?D.x:0,h?D.y:0)}}},g=0;g<e.symbolInstances.length;g++)v(g);if(e.sortFeatures(this.transform.angle),this.retainedQueryData[e.bucketInstanceId]&&(this.retainedQueryData[e.bucketInstanceId].featureSortOrder=e.featureSortOrder),e.hasTextData()&&e.text.opacityVertexBuffer&&e.text.opacityVertexBuffer.updateData(e.text.opacityVertexArray),e.hasIconData()&&e.icon.opacityVertexBuffer&&e.icon.opacityVertexBuffer.updateData(e.icon.opacityVertexArray),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexBuffer&&e.iconCollisionBox.collisionVertexBuffer.updateData(e.iconCollisionBox.collisionVertexArray),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexBuffer&&e.textCollisionBox.collisionVertexBuffer.updateData(e.textCollisionBox.collisionVertexArray),e.bucketInstanceId in this.collisionCircleArrays){var y=this.collisionCircleArrays[e.bucketInstanceId];e.placementInvProjMatrix=y.invProjMatrix,e.placementViewportMatrix=y.viewportMatrix,e.collisionCircleArray=y.circles,delete this.collisionCircleArrays[e.bucketInstanceId]}},Ae.prototype.symbolFadeChange=function(t){return 0===this.fadeDuration?1:(t-this.commitTime)/this.fadeDuration+this.prevZoomAdjustment},Ae.prototype.zoomAdjustment=function(t){return Math.max(0,(this.transform.zoom-t)/1.5)},Ae.prototype.hasTransitions=function(t){return this.stale||t-this.lastPlacementChangeTime<this.fadeDuration},Ae.prototype.stillRecent=function(t,e){var r=this.zoomAtLastRecencyCheck===e?1-this.zoomAdjustment(e):1;return this.zoomAtLastRecencyCheck=e,this.commitTime+this.fadeDuration*r>t},Ae.prototype.setStale=function(){this.stale=!0};var Se=Math.pow(2,25),Ee=Math.pow(2,24),Le=Math.pow(2,17),Ce=Math.pow(2,16),Pe=Math.pow(2,9),Oe=Math.pow(2,8),Ie=Math.pow(2,1);function De(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*Se+e*Ee+r*Le+e*Ce+r*Pe+e*Oe+r*Ie+e}var ze=0,Re=function(t){this._sortAcrossTiles=\"viewport-y\"!==t.layout.get(\"symbol-z-order\")&&void 0!==t.layout.get(\"symbol-sort-key\").constantOr(1),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};Re.prototype.continuePlacement=function(t,e,r,n,i){for(var a=this._bucketParts;this._currentTileIndex<t.length;){var o=t[this._currentTileIndex];if(e.getBucketParts(a,n,o,this._sortAcrossTiles),this._currentTileIndex++,i())return!0}for(this._sortAcrossTiles&&(this._sortAcrossTiles=!1,a.sort((function(t,e){return t.sortKey-e.sortKey})));this._currentPartIndex<a.length;){var s=a[this._currentPartIndex];if(e.placeLayerBucketPart(s,this._seenCrossTileIDs,r),this._currentPartIndex++,i())return!0}return!1};var Fe=function(t,e,r,n,i,a,o){this.placement=new Ae(t,i,a,o),this._currentPlacementIndex=e.length-1,this._forceFullPlacement=r,this._showCollisionBoxes=n,this._done=!1};Fe.prototype.isDone=function(){return this._done},Fe.prototype.continuePlacement=function(e,r,n){for(var i=this,a=t.browser.now(),o=function(){var e=t.browser.now()-a;return!i._forceFullPlacement&&e>2};this._currentPlacementIndex>=0;){var s=r[e[this._currentPlacementIndex]],l=this.placement.collisionIndex.transform.zoom;if(\"symbol\"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(this._inProgressLayer||(this._inProgressLayer=new Re(s)),this._inProgressLayer.continuePlacement(n[s.source],this.placement,this._showCollisionBoxes,s,o))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},Fe.prototype.commit=function(t){return this.placement.commit(t),this.placement};var Be=512/t.EXTENT/2,Ne=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0;n<e.length;n++){var i=e.get(n),a=i.key;this.indexedSymbolInstances[a]||(this.indexedSymbolInstances[a]=[]),this.indexedSymbolInstances[a].push({crossTileID:i.crossTileID,coord:this.getScaledCoordinates(i,t)})}};Ne.prototype.getScaledCoordinates=function(e,r){var n=r.canonical.z-this.tileID.canonical.z,i=Be/Math.pow(2,n);return{x:Math.floor((r.canonical.x*t.EXTENT+e.anchorX)*i),y:Math.floor((r.canonical.y*t.EXTENT+e.anchorY)*i)}},Ne.prototype.findMatches=function(t,e,r){for(var n=this.tileID.canonical.z<e.canonical.z?1:Math.pow(2,this.tileID.canonical.z-e.canonical.z),i=0;i<t.length;i++){var a=t.get(i);if(!a.crossTileID){var o=this.indexedSymbolInstances[a.key];if(o)for(var s=this.getScaledCoordinates(a,e),l=0,u=o;l<u.length;l+=1){var c=u[l];if(Math.abs(c.coord.x-s.x)<=n&&Math.abs(c.coord.y-s.y)<=n&&!r[c.crossTileID]){r[c.crossTileID]=!0,a.crossTileID=c.crossTileID;break}}}}};var je=function(){this.maxCrossTileID=0};je.prototype.generate=function(){return++this.maxCrossTileID};var Ue=function(){this.indexes={},this.usedCrossTileIDs={},this.lng=0};Ue.prototype.handleWrapJump=function(t){var e=Math.round((t-this.lng)/360);if(0!==e)for(var r in this.indexes){var n=this.indexes[r],i={};for(var a in n){var o=n[a];o.tileID=o.tileID.unwrapTo(o.tileID.wrap+e),i[o.tileID.key]=o}this.indexes[r]=i}this.lng=t},Ue.prototype.addBucket=function(t,e,r){if(this.indexes[t.overscaledZ]&&this.indexes[t.overscaledZ][t.key]){if(this.indexes[t.overscaledZ][t.key].bucketInstanceId===e.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(t.overscaledZ,this.indexes[t.overscaledZ][t.key])}for(var n=0;n<e.symbolInstances.length;n++)e.symbolInstances.get(n).crossTileID=0;this.usedCrossTileIDs[t.overscaledZ]||(this.usedCrossTileIDs[t.overscaledZ]={});var i=this.usedCrossTileIDs[t.overscaledZ];for(var a in this.indexes){var o=this.indexes[a];if(Number(a)>t.overscaledZ)for(var s in o){var l=o[s];l.tileID.isChildOf(t)&&l.findMatches(e.symbolInstances,t,i)}else{var u=o[t.scaledTo(Number(a)).key];u&&u.findMatches(e.symbolInstances,t,i)}}for(var c=0;c<e.symbolInstances.length;c++){var f=e.symbolInstances.get(c);f.crossTileID||(f.crossTileID=r.generate(),i[f.crossTileID]=!0)}return void 0===this.indexes[t.overscaledZ]&&(this.indexes[t.overscaledZ]={}),this.indexes[t.overscaledZ][t.key]=new Ne(t,e.symbolInstances,e.bucketInstanceId),!0},Ue.prototype.removeBucketCrossTileIDs=function(t,e){for(var r in e.indexedSymbolInstances)for(var n=0,i=e.indexedSymbolInstances[r];n<i.length;n+=1){var a=i[n];delete this.usedCrossTileIDs[t][a.crossTileID]}},Ue.prototype.removeStaleBuckets=function(t){var e=!1;for(var r in this.indexes){var n=this.indexes[r];for(var i in n)t[n[i].bucketInstanceId]||(this.removeBucketCrossTileIDs(r,n[i]),delete n[i],e=!0)}return e};var Ve=function(){this.layerIndexes={},this.crossTileIDs=new je,this.maxBucketInstanceId=0,this.bucketsInCurrentPlacement={}};Ve.prototype.addLayer=function(t,e,r){var n=this.layerIndexes[t.id];void 0===n&&(n=this.layerIndexes[t.id]=new Ue);var i=!1,a={};n.handleWrapJump(r);for(var o=0,s=e;o<s.length;o+=1){var l=s[o],u=l.getBucket(t);u&&t.id===u.layerIds[0]&&(u.bucketInstanceId||(u.bucketInstanceId=++this.maxBucketInstanceId),n.addBucket(l.tileID,u,this.crossTileIDs)&&(i=!0),a[u.bucketInstanceId]=!0)}return n.removeStaleBuckets(a)&&(i=!0),i},Ve.prototype.pruneUnusedLayers=function(t){var e={};for(var r in t.forEach((function(t){e[t]=!0})),this.layerIndexes)e[r]||delete this.layerIndexes[r]};var He=function(e,r){return t.emitValidationErrors(e,r&&r.filter((function(t){return\"source.canvas\"!==t.identifier})))},qe=t.pick(Ht,[\"addLayer\",\"removeLayer\",\"setPaintProperty\",\"setLayoutProperty\",\"setFilter\",\"addSource\",\"removeSource\",\"setLayerZoomRange\",\"setLight\",\"setTransition\",\"setGeoJSONSourceData\"]),Ge=t.pick(Ht,[\"setCenter\",\"setZoom\",\"setBearing\",\"setPitch\"]),Ze=function(){var e={},r=t.styleSpec.$version;for(var n in t.styleSpec.$root){var i=t.styleSpec.$root[n];if(i.required){var a;null!=(a=\"version\"===n?r:\"array\"===i.type?[]:{})&&(e[n]=a)}}return e}(),Ye=function(e){function r(n,i){var a=this;void 0===i&&(i={}),e.call(this),this.map=n,this.dispatcher=new A(jt(),this),this.imageManager=new h,this.imageManager.setEventedParent(this),this.glyphManager=new x(n._requestManager,i.localIdeographFontFamily),this.lineAtlas=new k(256,512),this.crossTileSymbolIndex=new Ve,this._layers={},this._serializedLayers={},this._order=[],this.sourceCaches={},this.zoomHistory=new t.ZoomHistory,this._loaded=!1,this._availableImages=[],this._resetUpdates(),this.dispatcher.broadcast(\"setReferrer\",t.getReferrer());var o=this;this._rtlTextPluginCallback=r.registerForPluginStateChange((function(e){var r={pluginStatus:e.pluginStatus,pluginURL:e.pluginURL};o.dispatcher.broadcast(\"syncRTLPluginState\",r,(function(e,r){if(t.triggerPluginCompletionEvent(e),r&&r.every((function(t){return t})))for(var n in o.sourceCaches)o.sourceCaches[n].reload()}))})),this.on(\"data\",(function(t){if(\"source\"===t.dataType&&\"metadata\"===t.sourceDataType){var e=a.sourceCaches[t.sourceId];if(e){var r=e.getSource();if(r&&r.vectorLayerIds)for(var n in a._layers){var i=a._layers[n];i.source===r.id&&a._validateLayer(i)}}}}))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadURL=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"}));var i=\"boolean\"==typeof r.validate?r.validate:!t.isMapboxURL(e);e=this.map._requestManager.normalizeStyleURL(e,r.accessToken);var a=this.map._requestManager.transformRequest(e,t.ResourceType.Style);this._request=t.getJSON(a,(function(e,r){n._request=null,e?n.fire(new t.ErrorEvent(e)):r&&n._load(r,i)}))},r.prototype.loadJSON=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._request=t.browser.frame((function(){n._request=null,n._load(e,!1!==r.validate)}))},r.prototype.loadEmpty=function(){this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._load(Ze,!1)},r.prototype._load=function(e,r){if(!r||!He(this,t.validateStyle(e))){for(var n in this._loaded=!0,this.stylesheet=e,e.sources)this.addSource(n,e.sources[n],{validate:!1});e.sprite?this._loadSprite(e.sprite):this.imageManager.setLoaded(!0),this.glyphManager.setURL(e.glyphs);var i=Vt(this.stylesheet.layers);this._order=i.map((function(t){return t.id})),this._layers={},this._serializedLayers={};for(var a=0,o=i;a<o.length;a+=1){var s=o[a];(s=t.createStyleLayer(s)).setEventedParent(this,{layer:{id:s.id}}),this._layers[s.id]=s,this._serializedLayers[s.id]=s.serialize()}this.dispatcher.broadcast(\"setLayers\",this._serializeLayers(this._order)),this.light=new T(this.stylesheet.light),this.fire(new t.Event(\"data\",{dataType:\"style\"})),this.fire(new t.Event(\"style.load\"))}},r.prototype._loadSprite=function(e){var r=this;this._spriteRequest=function(e,r,n){var i,a,o,s=t.browser.devicePixelRatio>1?\"@2x\":\"\",l=t.getJSON(r.transformRequest(r.normalizeSpriteURL(e,s,\".json\"),t.ResourceType.SpriteJSON),(function(t,e){l=null,o||(o=t,i=e,c())})),u=t.getImage(r.transformRequest(r.normalizeSpriteURL(e,s,\".png\"),t.ResourceType.SpriteImage),(function(t,e){u=null,o||(o=t,a=e,c())}));function c(){if(o)n(o);else if(i&&a){var e=t.browser.getImageData(a),r={};for(var s in i){var l=i[s],u=l.width,c=l.height,f=l.x,h=l.y,p=l.sdf,d=l.pixelRatio,v=l.stretchX,g=l.stretchY,y=l.content,m=new t.RGBAImage({width:u,height:c});t.RGBAImage.copy(e,m,{x:f,y:h},{x:0,y:0},{width:u,height:c}),r[s]={data:m,pixelRatio:d,sdf:p,stretchX:v,stretchY:g,content:y}}n(null,r)}}return{cancel:function(){l&&(l.cancel(),l=null),u&&(u.cancel(),u=null)}}}(e,this.map._requestManager,(function(e,n){if(r._spriteRequest=null,e)r.fire(new t.ErrorEvent(e));else if(n)for(var i in n)r.imageManager.addImage(i,n[i]);r.imageManager.setLoaded(!0),r._availableImages=r.imageManager.listImages(),r.dispatcher.broadcast(\"setImages\",r._availableImages),r.fire(new t.Event(\"data\",{dataType:\"style\"}))}))},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var i=r.getSource();(\"geojson\"===i.type||i.vectorLayerIds&&-1===i.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer \"'+n+'\" does not exist on source \"'+i.id+'\" as specified by style layer \"'+e.id+'\"')))}}},r.prototype.loaded=function(){if(!this._loaded)return!1;if(Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=this._layers[i];\"custom\"!==a.type&&e.push(a.serialize())}return e},r.prototype.hasTransitions=function(){if(this.light&&this.light.hasTransition())return!0;for(var t in this.sourceCaches)if(this.sourceCaches[t].hasTransition())return!0;for(var e in this._layers)if(this._layers[e].hasTransition())return!0;return!1},r.prototype._checkLoaded=function(){if(!this._loaded)throw new Error(\"Style is not done loading\")},r.prototype.update=function(e){if(this._loaded){var r=this._changed;if(this._changed){var n=Object.keys(this._updatedLayers),i=Object.keys(this._removedLayers);for(var a in(n.length||i.length)&&this._updateWorkerLayers(n,i),this._updatedSources){var o=this._updatedSources[a];\"reload\"===o?this._reloadSource(a):\"clear\"===o&&this._clearSource(a)}for(var s in this._updateTilesForChangedImages(),this._updatedPaintProps)this._layers[s].updateTransitions(e);this.light.updateTransitions(e),this._resetUpdates()}for(var l in this.sourceCaches)this.sourceCaches[l].used=!1;for(var u=0,c=this._order;u<c.length;u+=1){var f=c[u],h=this._layers[f];h.recalculate(e,this._availableImages),!h.isHidden(e.zoom)&&h.source&&(this.sourceCaches[h.source].used=!0)}this.light.recalculate(e),this.z=e.zoom,r&&this.fire(new t.Event(\"data\",{dataType:\"style\"}))}},r.prototype._updateTilesForChangedImages=function(){var t=Object.keys(this._changedImages);if(t.length){for(var e in this.sourceCaches)this.sourceCaches[e].reloadTilesForDependencies([\"icons\",\"patterns\"],t);this._changedImages={}}},r.prototype._updateWorkerLayers=function(t,e){this.dispatcher.broadcast(\"updateLayers\",{layers:this._serializeLayers(t),removedIds:e})},r.prototype._resetUpdates=function(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={},this._changedImages={}},r.prototype.setState=function(e){var r=this;if(this._checkLoaded(),He(this,t.validateStyle(e)))return!1;(e=t.clone$1(e)).layers=Vt(e.layers);var n=Kt(this.serialize(),e).filter((function(t){return!(t.command in Ge)}));if(0===n.length)return!1;var i=n.filter((function(t){return!(t.command in qe)}));if(i.length>0)throw new Error(\"Unimplemented: \"+i.map((function(t){return t.command})).join(\", \")+\".\");return n.forEach((function(t){\"setTransition\"!==t.command&&r[t.command].apply(r,t.args)})),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"An image with this name already exists.\")));this.imageManager.addImage(e,r),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.updateImage=function(t,e){this.imageManager.updateImage(t,e)},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"No image with this name exists.\")));this.imageManager.removeImage(e),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},r.prototype.addSource=function(e,r,n){var i=this;if(void 0===n&&(n={}),this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error(\"There is already a source with this ID\");if(!r.type)throw new Error(\"The type property must be defined, but the only the following properties were given: \"+Object.keys(r).join(\", \")+\".\");if(!([\"vector\",\"raster\",\"geojson\",\"video\",\"image\"].indexOf(r.type)>=0&&this._validate(t.validateStyle.source,\"sources.\"+e,r,null,n))){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var a=this.sourceCaches[e]=new Ot(e,r,this.dispatcher);a.style=this,a.setEventedParent(this,(function(){return{isSourceLoaded:i.loaded(),source:a.serialize(),sourceId:e}})),a.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error(\"There is no source with this ID\");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source \"'+e+'\" cannot be removed while layer \"'+r+'\" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event(\"data\",{sourceDataType:\"metadata\",dataType:\"source\",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=e.id;if(this.getLayer(i))this.fire(new t.ErrorEvent(new Error('Layer with id \"'+i+'\" already exists on this map')));else{var a;if(\"custom\"===e.type){if(He(this,t.validateCustomStyleLayer(e)))return;a=t.createStyleLayer(e)}else{if(\"object\"==typeof e.source&&(this.addSource(i,e.source),e=t.clone$1(e),e=t.extend(e,{source:i})),this._validate(t.validateStyle.layer,\"layers.\"+i,e,{arrayIndex:-1},n))return;a=t.createStyleLayer(e),this._validateLayer(a),a.setEventedParent(this,{layer:{id:i}}),this._serializedLayers[a.id]=a.serialize()}var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.')));else{if(this._order.splice(o,0,i),this._layerOrderChanged=!0,this._layers[i]=a,this._removedLayers[i]&&a.source&&\"custom\"!==a.type){var s=this._removedLayers[i];delete this._removedLayers[i],s.type!==a.type?this._updatedSources[a.source]=\"clear\":(this._updatedSources[a.source]=\"reload\",this.sourceCaches[a.source].pause())}this._updateLayer(a),a.onAdd&&a.onAdd(this.map)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var i=r?this._order.indexOf(r):this._order.length;r&&-1===i?this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.'))):(this._order.splice(i,0,e),this._layerOrderChanged=!0)}}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be moved.\")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._serializedLayers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e],r.onRemove&&r.onRemove(this.map)}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be removed.\")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.hasLayer=function(t){return t in this._layers},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);i?i.minzoom===r&&i.maxzoom===n||(null!=r&&(i.minzoom=r),null!=n&&(i.maxzoom=n),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot have zoom extent.\")))},r.prototype.setFilter=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=this.getLayer(e);if(i){if(!t.deepEqual(i.filter,r))return null==r?(i.filter=void 0,void this._updateLayer(i)):void(this._validate(t.validateStyle.filter,\"layers.\"+i.id+\".filter\",r,null,n)||(i.filter=t.clone$1(r),this._updateLayer(i)))}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be filtered.\")))},r.prototype.getFilter=function(e){return t.clone$1(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getLayoutProperty(r),n)||(a.setLayoutProperty(r,n,i),this._updateLayer(a)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getLayoutProperty=function(e,r){var n=this.getLayer(e);if(n)return n.getLayoutProperty(r);this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style.\")))},r.prototype.setPaintProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getPaintProperty(r),n)||(a.setPaintProperty(r,n,i)&&this._updateLayer(a),this._changed=!0,this._updatedPaintProps[e]=!0):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.setFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=e.sourceLayer,a=this.sourceCaches[n];if(void 0!==a){var o=a.getSource().type;\"geojson\"===o&&i?this.fire(new t.ErrorEvent(new Error(\"GeoJSON sources cannot have a sourceLayer parameter.\"))):\"vector\"!==o||i?(void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),a.setFeatureState(i,e.id,r)):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.removeFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=this.sourceCaches[n];if(void 0!==i){var a=i.getSource().type,o=\"vector\"===a?e.sourceLayer:void 0;\"vector\"!==a||o?r&&\"string\"!=typeof e.id&&\"number\"!=typeof e.id?this.fire(new t.ErrorEvent(new Error(\"A feature id is requred to remove its specific state property.\"))):i.removeFeatureState(o,e.id,r):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.getFeatureState=function(e){this._checkLoaded();var r=e.source,n=e.sourceLayer,i=this.sourceCaches[r];if(void 0!==i){if(\"vector\"!==i.getSource().type||n)return void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),i.getFeatureState(n,e.id);this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+r+\"' does not exist in the map's style.\")))},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,(function(t){return t.serialize()})),layers:this._serializeLayers(this._order)},(function(t){return void 0!==t}))},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&\"raster\"!==this.sourceCaches[t.source].getSource().type&&(this._updatedSources[t.source]=\"reload\",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenAndSortRenderedFeatures=function(t){for(var e=this,r=function(t){return\"fill-extrusion\"===e._layers[t].type},n={},i=[],a=this._order.length-1;a>=0;a--){var o=this._order[a];if(r(o)){n[o]=a;for(var s=0,l=t;s<l.length;s+=1){var u=l[s][o];if(u)for(var c=0,f=u;c<f.length;c+=1){var h=f[c];i.push(h)}}}}i.sort((function(t,e){return e.intersectionZ-t.intersectionZ}));for(var p=[],d=this._order.length-1;d>=0;d--){var v=this._order[d];if(r(v))for(var g=i.length-1;g>=0;g--){var y=i[g].feature;if(n[y.layer.id]<d)break;p.push(y),i.pop()}else for(var m=0,x=t;m<x.length;m+=1){var b=x[m][v];if(b)for(var _=0,w=b;_<w.length;_+=1){var T=w[_];p.push(T.feature)}}}return p},r.prototype.queryRenderedFeatures=function(e,r,n){r&&r.filter&&this._validate(t.validateStyle.filter,\"queryRenderedFeatures.filter\",r.filter,null,r);var i={};if(r&&r.layers){if(!Array.isArray(r.layers))return this.fire(new t.ErrorEvent(new Error(\"parameters.layers must be an Array.\"))),[];for(var a=0,o=r.layers;a<o.length;a+=1){var s=o[a],l=this._layers[s];if(!l)return this.fire(new t.ErrorEvent(new Error(\"The layer '\"+s+\"' does not exist in the map's style and cannot be queried for features.\"))),[];i[l.source]=!0}}var u=[];for(var c in r.availableImages=this._availableImages,this.sourceCaches)r.layers&&!i[c]||u.push(B(this.sourceCaches[c],this._layers,this._serializedLayers,e,r,n));return this.placement&&u.push(function(t,e,r,n,i,a,o){for(var s={},l=a.queryRenderedSymbols(n),u=[],c=0,f=Object.keys(l).map(Number);c<f.length;c+=1){var h=f[c];u.push(o[h])}u.sort(N);for(var p=function(){var r=v[d],n=r.featureIndex.lookupSymbolFeatures(l[r.bucketInstanceId],e,r.bucketIndex,r.sourceLayerIndex,i.filter,i.layers,i.availableImages,t);for(var a in n){var o=s[a]=s[a]||[],u=n[a];u.sort((function(t,e){var n=r.featureSortOrder;if(n){var i=n.indexOf(t.featureIndex);return n.indexOf(e.featureIndex)-i}return e.featureIndex-t.featureIndex}));for(var c=0,f=u;c<f.length;c+=1){var h=f[c];o.push(h)}}},d=0,v=u;d<v.length;d+=1)p();var g=function(e){s[e].forEach((function(n){var i=n.feature,a=t[e],o=r[a.source].getFeatureState(i.layer[\"source-layer\"],i.id);i.source=i.layer.source,i.layer[\"source-layer\"]&&(i.sourceLayer=i.layer[\"source-layer\"]),i.state=o}))};for(var y in s)g(y);return s}(this._layers,this._serializedLayers,this.sourceCaches,e,r,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(u)},r.prototype.querySourceFeatures=function(e,r){r&&r.filter&&this._validate(t.validateStyle.filter,\"querySourceFeatures.filter\",r.filter,null,r);var n=this.sourceCaches[e];return n?function(t,e){for(var r=t.getRenderableIds().map((function(e){return t.getTileByID(e)})),n=[],i={},a=0;a<r.length;a++){var o=r[a],s=o.tileID.canonical.key;i[s]||(i[s]=!0,o.querySourceFeatures(n,e))}return n}(n,r):[]},r.prototype.addSourceType=function(t,e,n){return r.getSourceType(t)?n(new Error('A source type called \"'+t+'\" already exists.')):(r.setSourceType(t,e),e.workerSourceURL?void this.dispatcher.broadcast(\"loadWorkerSource\",{name:t,url:e.workerSourceURL},n):n(null,null))},r.prototype.getLight=function(){return this.light.getLight()},r.prototype.setLight=function(e,r){void 0===r&&(r={}),this._checkLoaded();var n=this.light.getLight(),i=!1;for(var a in e)if(!t.deepEqual(e[a],n[a])){i=!0;break}if(i){var o={now:t.browser.now(),transition:t.extend({duration:300,delay:0},this.stylesheet.transition)};this.light.setLight(e,r),this.light.updateTransitions(o)}},r.prototype._validate=function(e,r,n,i,a){return void 0===a&&(a={}),(!a||!1!==a.validate)&&He(this,e.call(t.validateStyle,t.extend({key:r,style:this.serialize(),value:n,styleSpec:t.styleSpec},i)))},r.prototype._remove=function(){for(var e in this._request&&(this._request.cancel(),this._request=null),this._spriteRequest&&(this._spriteRequest.cancel(),this._spriteRequest=null),t.evented.off(\"pluginStateChange\",this._rtlTextPluginCallback),this._layers)this._layers[e].setEventedParent(null);for(var r in this.sourceCaches)this.sourceCaches[r].clearTiles(),this.sourceCaches[r].setEventedParent(null);this.imageManager.setEventedParent(null),this.setEventedParent(null),this.dispatcher.remove()},r.prototype._clearSource=function(t){this.sourceCaches[t].clearTiles()},r.prototype._reloadSource=function(t){this.sourceCaches[t].resume(),this.sourceCaches[t].reload()},r.prototype._updateSources=function(t){for(var e in this.sourceCaches)this.sourceCaches[e].update(t)},r.prototype._generateCollisionBoxes=function(){for(var t in this.sourceCaches)this._reloadSource(t)},r.prototype._updatePlacement=function(e,r,n,i,a){void 0===a&&(a=!1);for(var o=!1,s=!1,l={},u=0,c=this._order;u<c.length;u+=1){var f=c[u],h=this._layers[f];if(\"symbol\"===h.type){if(!l[h.source]){var p=this.sourceCaches[h.source];l[h.source]=p.getRenderableIds(!0).map((function(t){return p.getTileByID(t)})).sort((function(t,e){return e.tileID.overscaledZ-t.tileID.overscaledZ||(t.tileID.isLessThan(e.tileID)?-1:1)}))}var d=this.crossTileSymbolIndex.addLayer(h,l[h.source],e.center.lng);o=o||d}}if(this.crossTileSymbolIndex.pruneUnusedLayers(this._order),((a=a||this._layerOrderChanged||0===n)||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(t.browser.now(),e.zoom))&&(this.pauseablePlacement=new Fe(e,this._order,a,r,n,i,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,l),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(t.browser.now()),s=!0),o&&this.pauseablePlacement.placement.setStale()),s||o)for(var v=0,g=this._order;v<g.length;v+=1){var y=g[v],m=this._layers[y];\"symbol\"===m.type&&this.placement.updateLayerOpacities(m,l[m.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(t.browser.now())},r.prototype._releaseSymbolFadeTiles=function(){for(var t in this.sourceCaches)this.sourceCaches[t].releaseSymbolFadeTiles()},r.prototype.getImages=function(t,e,r){this.imageManager.getImages(e.icons,r),this._updateTilesForChangedImages();var n=this.sourceCaches[e.source];n&&n.setDependencies(e.tileID.key,e.type,e.icons)},r.prototype.getGlyphs=function(t,e,r){this.glyphManager.getGlyphs(e.stacks,r)},r.prototype.getResource=function(e,r,n){return t.makeRequest(r,n)},r}(t.Evented);Ye.getSourceType=function(t){return R[t]},Ye.setSourceType=function(t,e){R[t]=e},Ye.registerForPluginStateChange=t.registerForPluginStateChange;var We=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2}]),Xe=_r(\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\",\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\\nvec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0\\n);}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;}\"),Je=_r(\"uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),Ke=_r(\"uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}\"),$e=_r(\"varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=v_data.xy;float extrude_length=length(extrude);lowp float antialiasblur=v_data.z;float antialiased_blur=-max(blur,antialiasblur);float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main(void) {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,0,1);} else {gl_Position=u_matrix*vec4(circle_center,0,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}lowp float antialiasblur=1.0/u_device_pixel_ratio/(radius+stroke_width);v_data=vec3(extrude.x,extrude.y,antialiasblur);}\"),Qe=_r(\"void main() {gl_FragColor=vec4(1.0);}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),tr=_r(\"uniform highp float u_intensity;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main() {\\n#pragma mapbox: initialize highp float weight\\nfloat d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#pragma mapbox: define mediump float radius\\nconst highp float ZERO=1.0/255.0/16.0;\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main(void) {\\n#pragma mapbox: initialize highp float weight\\n#pragma mapbox: initialize mediump float radius\\nvec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,0,1);gl_Position=u_matrix*pos;}\"),er=_r(\"uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(0.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}\"),rr=_r(\"varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}\",\"attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}\"),nr=_r(\"varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}\",\"attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd  =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz  /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}\"),ir=_r(\"uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}\",\"attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,0,1);}\"),ar=_r(\"#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_FragColor=color*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);}\"),or=_r(\"varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),sr=_r(\"uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),lr=_r(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}\"),ur=_r(\"varying vec4 v_color;void main() {gl_FragColor=v_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\\n#pragma mapbox: define highp float base\\n#pragma mapbox: define highp float height\\n#pragma mapbox: define highp vec4 color\\nvoid main() {\\n#pragma mapbox: initialize highp float base\\n#pragma mapbox: initialize highp float height\\n#pragma mapbox: initialize highp vec4 color\\nvec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}\"),cr=_r(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\\n? a_pos\\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}\"),fr=_r(\"#ifdef GL_ES\\nprecision highp float;\\n#endif\\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform float u_maxzoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggeration=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/ pow(2.0,(u_zoom-u_maxzoom)*exaggeration+19.2562-u_zoom);gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}\"),hr=_r(\"uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\\n#define PI 3.141592653589793\\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}\"),pr=_r(\"uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),dr=_r(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,vec2(v_lineprogress,0.5));gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define MAX_LINE_DISTANCE 32767.0\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_lineprogress=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0/MAX_LINE_DISTANCE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),vr=_r(\"uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}\"),gr=_r(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}\"),yr=_r(\"uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}\"),mr=_r(\"uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}\"),xr=_r(\"#define SDF_PX 8.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}\"),br=_r(\"#define SDF_PX 8.0\\n#define SDF 1.0\\n#define ICON 0.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\nreturn;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}\");function _r(t,e){var r=/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,n={};return{fragmentSource:t=t.replace(r,(function(t,e,r,i,a){return n[a]=!0,\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"\\n#ifdef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"})),vertexSource:e=e.replace(r,(function(t,e,r,i,a){var o=\"float\"===i?\"vec2\":\"vec4\",s=a.match(/color/)?\"color\":o;return n[a]?\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+a+\" = a_\"+a+\";\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = a_\"+a+\";\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"}))}}var wr=Object.freeze({__proto__:null,prelude:Xe,background:Je,backgroundPattern:Ke,circle:$e,clippingMask:Qe,heatmap:tr,heatmapTexture:er,collisionBox:rr,collisionCircle:nr,debug:ir,fill:ar,fillOutline:or,fillOutlinePattern:sr,fillPattern:lr,fillExtrusion:ur,fillExtrusionPattern:cr,hillshadePrepare:fr,hillshade:hr,line:pr,lineGradient:dr,linePattern:vr,lineSDF:gr,raster:yr,symbolIcon:mr,symbolSDF:xr,symbolTextAndIcon:br}),Tr=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};Tr.prototype.bind=function(t,e,r,n,i,a,o,s){this.context=t;for(var l=this.boundPaintVertexBuffers.length!==n.length,u=0;!l&&u<n.length;u++)this.boundPaintVertexBuffers[u]!==n[u]&&(l=!0);var c=!this.vao||this.boundProgram!==e||this.boundLayoutVertexBuffer!==r||l||this.boundIndexBuffer!==i||this.boundVertexOffset!==a||this.boundDynamicVertexBuffer!==o||this.boundDynamicVertexBuffer2!==s;!t.extVertexArrayObject||c?this.freshBind(e,r,n,i,a,o,s):(t.bindVertexArrayOES.set(this.vao),o&&o.bind(),i&&i.dynamicDraw&&i.bind(),s&&s.bind())},Tr.prototype.freshBind=function(t,e,r,n,i,a,o){var s,l=t.numAttributes,u=this.context,c=u.gl;if(u.extVertexArrayObject)this.vao&&this.destroy(),this.vao=u.extVertexArrayObject.createVertexArrayOES(),u.bindVertexArrayOES.set(this.vao),s=0,this.boundProgram=t,this.boundLayoutVertexBuffer=e,this.boundPaintVertexBuffers=r,this.boundIndexBuffer=n,this.boundVertexOffset=i,this.boundDynamicVertexBuffer=a,this.boundDynamicVertexBuffer2=o;else{s=u.currentNumAttributes||0;for(var f=l;f<s;f++)c.disableVertexAttribArray(f)}e.enableAttributes(c,t);for(var h=0,p=r;h<p.length;h+=1)p[h].enableAttributes(c,t);a&&a.enableAttributes(c,t),o&&o.enableAttributes(c,t),e.bind(),e.setVertexAttribPointers(c,t,i);for(var d=0,v=r;d<v.length;d+=1){var g=v[d];g.bind(),g.setVertexAttribPointers(c,t,i)}a&&(a.bind(),a.setVertexAttribPointers(c,t,i)),n&&n.bind(),o&&(o.bind(),o.setVertexAttribPointers(c,t,i)),u.currentNumAttributes=l},Tr.prototype.destroy=function(){this.vao&&(this.context.extVertexArrayObject.deleteVertexArrayOES(this.vao),this.vao=null)};var kr=function(t,e,r,n,i){var a=t.gl;this.program=a.createProgram();var o=r?r.defines():[];i&&o.push(\"#define OVERDRAW_INSPECTOR;\");var s=o.concat(Xe.fragmentSource,e.fragmentSource).join(\"\\n\"),l=o.concat(Xe.vertexSource,e.vertexSource).join(\"\\n\"),u=a.createShader(a.FRAGMENT_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(u,s),a.compileShader(u),a.attachShader(this.program,u);var c=a.createShader(a.VERTEX_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(c,l),a.compileShader(c),a.attachShader(this.program,c);for(var f=r?r.layoutAttributes:[],h=0;h<f.length;h++)a.bindAttribLocation(this.program,h,f[h].name);a.linkProgram(this.program),a.deleteShader(c),a.deleteShader(u),this.numAttributes=a.getProgramParameter(this.program,a.ACTIVE_ATTRIBUTES),this.attributes={};for(var p={},d=0;d<this.numAttributes;d++){var v=a.getActiveAttrib(this.program,d);v&&(this.attributes[v.name]=a.getAttribLocation(this.program,v.name))}for(var g=a.getProgramParameter(this.program,a.ACTIVE_UNIFORMS),y=0;y<g;y++){var m=a.getActiveUniform(this.program,y);m&&(p[m.name]=a.getUniformLocation(this.program,m.name))}this.fixedUniforms=n(t,p),this.binderUniforms=r?r.getUniforms(t,p):[]}}};function Ar(t,e,r){var n=1/ge(r,1,e.transform.tileZoom),i=Math.pow(2,r.tileID.overscaledZ),a=r.tileSize*Math.pow(2,e.transform.tileZoom)/i,o=a*(r.tileID.canonical.x+r.tileID.wrap*i),s=a*r.tileID.canonical.y;return{u_image:0,u_texsize:r.imageAtlasTexture.size,u_scale:[n,t.fromScale,t.toScale],u_fade:t.t,u_pixel_coord_upper:[o>>16,s>>16],u_pixel_coord_lower:[65535&o,65535&s]}}kr.prototype.draw=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v){var g,y=t.gl;if(!this.failedToCreate){for(var m in t.program.set(this.program),t.setDepthMode(r),t.setStencilMode(n),t.setColorMode(i),t.setCullFace(a),this.fixedUniforms)this.fixedUniforms[m].set(o[m]);p&&p.setUniforms(t,this.binderUniforms,f,{zoom:h});for(var x=(g={},g[y.LINES]=2,g[y.TRIANGLES]=3,g[y.LINE_STRIP]=1,g)[e],b=0,_=c.get();b<_.length;b+=1){var w=_[b],T=w.vaos||(w.vaos={});(T[s]||(T[s]=new Tr)).bind(t,this,l,p?p.getPaintVertexBuffers():[],u,w.vertexOffset,d,v),y.drawElements(e,w.primitiveLength*x,y.UNSIGNED_SHORT,w.primitiveOffset*x*2)}}};var Mr=function(e,r,n,i){var a=r.style.light,o=a.properties.get(\"position\"),s=[o.x,o.y,o.z],l=t.create$1();\"viewport\"===a.properties.get(\"anchor\")&&t.fromRotation(l,-r.transform.angle),t.transformMat3(s,s,l);var u=a.properties.get(\"color\");return{u_matrix:e,u_lightpos:s,u_lightintensity:a.properties.get(\"intensity\"),u_lightcolor:[u.r,u.g,u.b],u_vertical_gradient:+n,u_opacity:i}},Sr=function(e,r,n,i,a,o,s){return t.extend(Mr(e,r,n,i),Ar(o,r,s),{u_height_factor:-Math.pow(2,a.overscaledZ)/s.tileSize/8})},Er=function(t){return{u_matrix:t}},Lr=function(e,r,n,i){return t.extend(Er(e),Ar(n,r,i))},Cr=function(t,e){return{u_matrix:t,u_world:e}},Pr=function(e,r,n,i,a){return t.extend(Lr(e,r,n,i),{u_world:a})},Or=function(e,r,n,i){var a,o,s=e.transform;if(\"map\"===i.paint.get(\"circle-pitch-alignment\")){var l=ge(n,1,s.zoom);a=!0,o=[l,l]}else a=!1,o=s.pixelsToGLUnits;return{u_camera_to_center_distance:s.cameraToCenterDistance,u_scale_with_map:+(\"map\"===i.paint.get(\"circle-pitch-scale\")),u_matrix:e.translatePosMatrix(r.posMatrix,n,i.paint.get(\"circle-translate\"),i.paint.get(\"circle-translate-anchor\")),u_pitch_with_map:+a,u_device_pixel_ratio:t.browser.devicePixelRatio,u_extrude_scale:o}},Ir=function(t,e,r){var n=ge(r,1,e.zoom),i=Math.pow(2,e.zoom-r.tileID.overscaledZ),a=r.tileID.overscaleFactor();return{u_matrix:t,u_camera_to_center_distance:e.cameraToCenterDistance,u_pixels_to_tile_units:n,u_extrude_scale:[e.pixelsToGLUnits[0]/(n*i),e.pixelsToGLUnits[1]/(n*i)],u_overscale_factor:a}},Dr=function(t,e,r){return{u_matrix:t,u_inv_matrix:e,u_camera_to_center_distance:r.cameraToCenterDistance,u_viewport_size:[r.width,r.height]}},zr=function(t,e,r){return void 0===r&&(r=1),{u_matrix:t,u_color:e,u_overlay:0,u_overlay_scale:r}},Rr=function(t){return{u_matrix:t}},Fr=function(t,e,r,n){return{u_matrix:t,u_extrude_scale:ge(e,1,r),u_intensity:n}},Br=function(e,r,n,i){var a=t.create();t.ortho(a,0,e.width,e.height,0,0,1);var o=e.context.gl;return{u_matrix:a,u_world:[o.drawingBufferWidth,o.drawingBufferHeight],u_image:n,u_color_ramp:i,u_opacity:r.paint.get(\"heatmap-opacity\")}},Nr=function(e,r,n){var i=n.paint.get(\"hillshade-shadow-color\"),a=n.paint.get(\"hillshade-highlight-color\"),o=n.paint.get(\"hillshade-accent-color\"),s=n.paint.get(\"hillshade-illumination-direction\")*(Math.PI/180);\"viewport\"===n.paint.get(\"hillshade-illumination-anchor\")&&(s-=e.transform.angle);var l,u,c,f=!e.options.moving;return{u_matrix:e.transform.calculatePosMatrix(r.tileID.toUnwrapped(),f),u_image:0,u_latrange:(l=r.tileID,u=Math.pow(2,l.canonical.z),c=l.canonical.y,[new t.MercatorCoordinate(0,c/u).toLngLat().lat,new t.MercatorCoordinate(0,(c+1)/u).toLngLat().lat]),u_light:[n.paint.get(\"hillshade-exaggeration\"),s],u_shadow:i,u_highlight:a,u_accent:o}},jr=function(e,r,n){var i=r.stride,a=t.create();return t.ortho(a,0,t.EXTENT,-t.EXTENT,0,0,1),t.translate(a,a,[0,-t.EXTENT,0]),{u_matrix:a,u_image:1,u_dimension:[i,i],u_zoom:e.overscaledZ,u_maxzoom:n,u_unpack:r.getUnpackVector()}};var Ur=function(e,r,n){var i=e.transform;return{u_matrix:Zr(e,r,n),u_ratio:1/ge(r,1,i.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_units_to_pixels:[1/i.pixelsToGLUnits[0],1/i.pixelsToGLUnits[1]]}},Vr=function(e,r,n){return t.extend(Ur(e,r,n),{u_image:0})},Hr=function(e,r,n,i){var a=e.transform,o=Gr(r,a);return{u_matrix:Zr(e,r,n),u_texsize:r.imageAtlasTexture.size,u_ratio:1/ge(r,1,a.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_image:0,u_scale:[o,i.fromScale,i.toScale],u_fade:i.t,u_units_to_pixels:[1/a.pixelsToGLUnits[0],1/a.pixelsToGLUnits[1]]}},qr=function(e,r,n,i,a){var o=e.transform,s=e.lineAtlas,l=Gr(r,o),u=\"round\"===n.layout.get(\"line-cap\"),c=s.getDash(i.from,u),f=s.getDash(i.to,u),h=c.width*a.fromScale,p=f.width*a.toScale;return t.extend(Ur(e,r,n),{u_patternscale_a:[l/h,-c.height/2],u_patternscale_b:[l/p,-f.height/2],u_sdfgamma:s.width/(256*Math.min(h,p)*t.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:c.y,u_tex_y_b:f.y,u_mix:a.t})};function Gr(t,e){return 1/ge(t,1,e.tileZoom)}function Zr(t,e,r){return t.translatePosMatrix(e.tileID.posMatrix,e,r.paint.get(\"line-translate\"),r.paint.get(\"line-translate-anchor\"))}var Yr=function(t,e,r,n,i){return{u_matrix:t,u_tl_parent:e,u_scale_parent:r,u_buffer_scale:1,u_fade_t:n.mix,u_opacity:n.opacity*i.paint.get(\"raster-opacity\"),u_image0:0,u_image1:1,u_brightness_low:i.paint.get(\"raster-brightness-min\"),u_brightness_high:i.paint.get(\"raster-brightness-max\"),u_saturation_factor:(o=i.paint.get(\"raster-saturation\"),o>0?1-1/(1.001-o):-o),u_contrast_factor:(a=i.paint.get(\"raster-contrast\"),a>0?1/(1-a):1+a),u_spin_weights:Wr(i.paint.get(\"raster-hue-rotate\"))};var a,o};function Wr(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}var Xr,Jr=function(t,e,r,n,i,a,o,s,l,u){var c=i.transform;return{u_is_size_zoom_constant:+(\"constant\"===t||\"source\"===t),u_is_size_feature_constant:+(\"constant\"===t||\"camera\"===t),u_size_t:e?e.uSizeT:0,u_size:e?e.uSize:0,u_camera_to_center_distance:c.cameraToCenterDistance,u_pitch:c.pitch/360*2*Math.PI,u_rotate_symbol:+r,u_aspect_ratio:c.width/c.height,u_fade_change:i.options.fadeDuration?i.symbolFadeChange:1,u_matrix:a,u_label_plane_matrix:o,u_coord_matrix:s,u_is_text:+l,u_pitch_with_map:+n,u_texsize:u,u_texture:0}},Kr=function(e,r,n,i,a,o,s,l,u,c,f){var h=a.transform;return t.extend(Jr(e,r,n,i,a,o,s,l,u,c),{u_gamma_scale:i?Math.cos(h._pitch)*h.cameraToCenterDistance:1,u_device_pixel_ratio:t.browser.devicePixelRatio,u_is_halo:+f})},$r=function(e,r,n,i,a,o,s,l,u,c){return t.extend(Kr(e,r,n,i,a,o,s,l,!0,u,!0),{u_texsize_icon:c,u_texture_icon:1})},Qr=function(t,e,r){return{u_matrix:t,u_opacity:e,u_color:r}},tn=function(e,r,n,i,a,o){return t.extend(function(t,e,r,n){var i=r.imageManager.getPattern(t.from.toString()),a=r.imageManager.getPattern(t.to.toString()),o=r.imageManager.getPixelSize(),s=o.width,l=o.height,u=Math.pow(2,n.tileID.overscaledZ),c=n.tileSize*Math.pow(2,r.transform.tileZoom)/u,f=c*(n.tileID.canonical.x+n.tileID.wrap*u),h=c*n.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:i.tl,u_pattern_br_a:i.br,u_pattern_tl_b:a.tl,u_pattern_br_b:a.br,u_texsize:[s,l],u_mix:e.t,u_pattern_size_a:i.displaySize,u_pattern_size_b:a.displaySize,u_scale_a:e.fromScale,u_scale_b:e.toScale,u_tile_units_to_pixels:1/ge(n,1,r.transform.tileZoom),u_pixel_coord_upper:[f>>16,h>>16],u_pixel_coord_lower:[65535&f,65535&h]}}(i,o,n,a),{u_matrix:e,u_opacity:r})},en={fillExtrusion:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fillExtrusionPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_height_factor:new t.Uniform1f(e,r.u_height_factor),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fill:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},fillPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},fillOutline:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world)}},fillOutlinePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},circle:function(e,r){return{u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_scale_with_map:new t.Uniform1i(e,r.u_scale_with_map),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},collisionBox:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pixels_to_tile_units:new t.Uniform1f(e,r.u_pixels_to_tile_units),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_overscale_factor:new t.Uniform1f(e,r.u_overscale_factor)}},collisionCircle:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_inv_matrix:new t.UniformMatrix4f(e,r.u_inv_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_viewport_size:new t.Uniform2f(e,r.u_viewport_size)}},debug:function(e,r){return{u_color:new t.UniformColor(e,r.u_color),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_overlay:new t.Uniform1i(e,r.u_overlay),u_overlay_scale:new t.Uniform1f(e,r.u_overlay_scale)}},clippingMask:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmap:function(e,r){return{u_extrude_scale:new t.Uniform1f(e,r.u_extrude_scale),u_intensity:new t.Uniform1f(e,r.u_intensity),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmapTexture:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_color_ramp:new t.Uniform1i(e,r.u_color_ramp),u_opacity:new t.Uniform1f(e,r.u_opacity)}},hillshade:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_latrange:new t.Uniform2f(e,r.u_latrange),u_light:new t.Uniform2f(e,r.u_light),u_shadow:new t.UniformColor(e,r.u_shadow),u_highlight:new t.UniformColor(e,r.u_highlight),u_accent:new t.UniformColor(e,r.u_accent)}},hillshadePrepare:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_dimension:new t.Uniform2f(e,r.u_dimension),u_zoom:new t.Uniform1f(e,r.u_zoom),u_maxzoom:new t.Uniform1f(e,r.u_maxzoom),u_unpack:new t.Uniform4f(e,r.u_unpack)}},line:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels)}},lineGradient:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_image:new t.Uniform1i(e,r.u_image)}},linePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_texsize:new t.Uniform2f(e,r.u_texsize),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_image:new t.Uniform1i(e,r.u_image),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},lineSDF:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_patternscale_a:new t.Uniform2f(e,r.u_patternscale_a),u_patternscale_b:new t.Uniform2f(e,r.u_patternscale_b),u_sdfgamma:new t.Uniform1f(e,r.u_sdfgamma),u_image:new t.Uniform1i(e,r.u_image),u_tex_y_a:new t.Uniform1f(e,r.u_tex_y_a),u_tex_y_b:new t.Uniform1f(e,r.u_tex_y_b),u_mix:new t.Uniform1f(e,r.u_mix)}},raster:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_tl_parent:new t.Uniform2f(e,r.u_tl_parent),u_scale_parent:new t.Uniform1f(e,r.u_scale_parent),u_buffer_scale:new t.Uniform1f(e,r.u_buffer_scale),u_fade_t:new t.Uniform1f(e,r.u_fade_t),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image0:new t.Uniform1i(e,r.u_image0),u_image1:new t.Uniform1i(e,r.u_image1),u_brightness_low:new t.Uniform1f(e,r.u_brightness_low),u_brightness_high:new t.Uniform1f(e,r.u_brightness_high),u_saturation_factor:new t.Uniform1f(e,r.u_saturation_factor),u_contrast_factor:new t.Uniform1f(e,r.u_contrast_factor),u_spin_weights:new t.Uniform3f(e,r.u_spin_weights)}},symbolIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture)}},symbolSDF:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},symbolTextAndIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texsize_icon:new t.Uniform2f(e,r.u_texsize_icon),u_texture:new t.Uniform1i(e,r.u_texture),u_texture_icon:new t.Uniform1i(e,r.u_texture_icon),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},background:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_color:new t.UniformColor(e,r.u_color)}},backgroundPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image:new t.Uniform1i(e,r.u_image),u_pattern_tl_a:new t.Uniform2f(e,r.u_pattern_tl_a),u_pattern_br_a:new t.Uniform2f(e,r.u_pattern_br_a),u_pattern_tl_b:new t.Uniform2f(e,r.u_pattern_tl_b),u_pattern_br_b:new t.Uniform2f(e,r.u_pattern_br_b),u_texsize:new t.Uniform2f(e,r.u_texsize),u_mix:new t.Uniform1f(e,r.u_mix),u_pattern_size_a:new t.Uniform2f(e,r.u_pattern_size_a),u_pattern_size_b:new t.Uniform2f(e,r.u_pattern_size_b),u_scale_a:new t.Uniform1f(e,r.u_scale_a),u_scale_b:new t.Uniform1f(e,r.u_scale_b),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_tile_units_to_pixels:new t.Uniform1f(e,r.u_tile_units_to_pixels)}}};function rn(e,r,n,i,a,o,s){for(var l=e.context,u=l.gl,c=e.useProgram(\"collisionBox\"),f=[],h=0,p=0,d=0;d<i.length;d++){var v=i[d],g=r.getTile(v),y=g.getBucket(n);if(y){var m=v.posMatrix;0===a[0]&&0===a[1]||(m=e.translatePosMatrix(v.posMatrix,g,a,o));var x=s?y.textCollisionBox:y.iconCollisionBox,b=y.collisionCircleArray;if(b.length>0){var _=t.create(),w=m;t.mul(_,y.placementInvProjMatrix,e.transform.glCoordMatrix),t.mul(_,_,y.placementViewportMatrix),f.push({circleArray:b,circleOffset:p,transform:w,invTransform:_}),p=h+=b.length/4}x&&c.draw(l,u.LINES,Mt.disabled,Et.disabled,e.colorModeForRenderPass(),Ct.disabled,Ir(m,e.transform,g),n.id,x.layoutVertexBuffer,x.indexBuffer,x.segments,null,e.transform.zoom,null,null,x.collisionVertexBuffer)}}if(s&&f.length){var T=e.useProgram(\"collisionCircle\"),k=new t.StructArrayLayout2f1f2i16;k.resize(4*h),k._trim();for(var A=0,M=0,S=f;M<S.length;M+=1)for(var E=S[M],L=0;L<E.circleArray.length/4;L++){var C=4*L,P=E.circleArray[C+0],O=E.circleArray[C+1],I=E.circleArray[C+2],D=E.circleArray[C+3];k.emplace(A++,P,O,I,D,0),k.emplace(A++,P,O,I,D,1),k.emplace(A++,P,O,I,D,2),k.emplace(A++,P,O,I,D,3)}(!Xr||Xr.length<2*h)&&(Xr=function(e){var r=2*e,n=new t.StructArrayLayout3ui6;n.resize(r),n._trim();for(var i=0;i<r;i++){var a=6*i;n.uint16[a+0]=4*i+0,n.uint16[a+1]=4*i+1,n.uint16[a+2]=4*i+2,n.uint16[a+3]=4*i+2,n.uint16[a+4]=4*i+3,n.uint16[a+5]=4*i+0}return n}(h));for(var z=l.createIndexBuffer(Xr,!0),R=l.createVertexBuffer(k,t.collisionCircleLayout.members,!0),F=0,B=f;F<B.length;F+=1){var N=B[F],j=Dr(N.transform,N.invTransform,e.transform);T.draw(l,u.TRIANGLES,Mt.disabled,Et.disabled,e.colorModeForRenderPass(),Ct.disabled,j,n.id,R,z,t.SegmentVector.simpleSegment(0,2*N.circleOffset,N.circleArray.length,N.circleArray.length/2),null,e.transform.zoom,null,null,null)}R.destroy(),z.destroy()}}var nn=t.identity(new Float32Array(16));function an(e,r,n,i,a,o){var s=t.getAnchorAlignment(e),l=-(s.horizontalAlign-.5)*r,u=-(s.verticalAlign-.5)*n,c=t.evaluateVariableOffset(e,i);return new t.Point((l/a+c[0])*o,(u/a+c[1])*o)}function on(e,r,n,i,a,o,s,l,u,c,f){var h=e.text.placedSymbolArray,p=e.text.dynamicLayoutVertexArray,d=e.icon.dynamicLayoutVertexArray,v={};p.clear();for(var g=0;g<h.length;g++){var y=h.get(g),m=e.allowVerticalPlacement&&!y.placedOrientation,x=y.hidden||!y.crossTileID||m?null:i[y.crossTileID];if(x){var b=new t.Point(y.anchorX,y.anchorY),_=re(b,n?l:s),w=ne(o.cameraToCenterDistance,_.signedDistanceFromCamera),T=a.evaluateSizeForFeature(e.textSizeData,c,y)*w/t.ONE_EM;n&&(T*=e.tilePixelRatio/u);for(var k=x.width,A=x.height,M=an(x.anchor,k,A,x.textOffset,x.textBoxScale,T),S=n?re(b.add(M),s).point:_.point.add(r?M.rotate(-o.angle):M),E=e.allowVerticalPlacement&&y.placedOrientation===t.WritingMode.vertical?Math.PI/2:0,L=0;L<y.numGlyphs;L++)t.addDynamicAttributes(p,S,E);f&&y.associatedIconIndex>=0&&(v[y.associatedIconIndex]={shiftedAnchor:S,angle:E})}else he(y.numGlyphs,p)}if(f){d.clear();for(var C=e.icon.placedSymbolArray,P=0;P<C.length;P++){var O=C.get(P);if(O.hidden)he(O.numGlyphs,d);else{var I=v[P];if(I)for(var D=0;D<O.numGlyphs;D++)t.addDynamicAttributes(d,I.shiftedAnchor,I.angle);else he(O.numGlyphs,d)}}e.icon.dynamicLayoutVertexBuffer.updateData(d)}e.text.dynamicLayoutVertexBuffer.updateData(p)}function sn(t,e,r){return r.iconsInText&&e?\"symbolTextAndIcon\":t?\"symbolSDF\":\"symbolIcon\"}function ln(e,r,n,i,a,o,s,l,u,c,f,h){for(var p=e.context,d=p.gl,v=e.transform,g=\"map\"===l,y=\"map\"===u,m=g&&\"point\"!==n.layout.get(\"symbol-placement\"),x=g&&!y&&!m,b=void 0!==n.layout.get(\"symbol-sort-key\").constantOr(1),_=e.depthModeForSublayer(0,Mt.ReadOnly),w=n.layout.get(\"text-variable-anchor\"),T=[],k=0,A=i;k<A.length;k+=1){var M=A[k],S=r.getTile(M),E=S.getBucket(n);if(E){var L=a?E.text:E.icon;if(L&&L.segments.get().length){var C=L.programConfigurations.get(n.id),P=a||E.sdfIcons,O=a?E.textSizeData:E.iconSizeData,I=y||0!==v.pitch,D=e.useProgram(sn(P,a,E),C),z=t.evaluateSizeForZoom(O,v.zoom),R=void 0,F=[0,0],B=void 0,N=void 0,j=null,U=void 0;if(a){if(B=S.glyphAtlasTexture,N=d.LINEAR,R=S.glyphAtlasTexture.size,E.iconsInText){F=S.imageAtlasTexture.size,j=S.imageAtlasTexture;var V=\"composite\"===O.kind||\"camera\"===O.kind;U=I||e.options.rotating||e.options.zooming||V?d.LINEAR:d.NEAREST}}else{var H=1!==n.layout.get(\"icon-size\").constantOr(0)||E.iconsNeedLinear;B=S.imageAtlasTexture,N=P||e.options.rotating||e.options.zooming||H||I?d.LINEAR:d.NEAREST,R=S.imageAtlasTexture.size}var q=ge(S,1,e.transform.zoom),G=te(M.posMatrix,y,g,e.transform,q),Z=ee(M.posMatrix,y,g,e.transform,q),Y=w&&E.hasTextData(),W=\"none\"!==n.layout.get(\"icon-text-fit\")&&Y&&E.hasIconData();m&&ae(E,M.posMatrix,e,a,G,Z,y,c);var X=e.translatePosMatrix(M.posMatrix,S,o,s),J=m||a&&w||W?nn:G,K=e.translatePosMatrix(Z,S,o,s,!0),$=P&&0!==n.paint.get(a?\"text-halo-width\":\"icon-halo-width\").constantOr(1),Q={program:D,buffers:L,uniformValues:P?E.iconsInText?$r(O.kind,z,x,y,e,X,J,K,R,F):Kr(O.kind,z,x,y,e,X,J,K,a,R,!0):Jr(O.kind,z,x,y,e,X,J,K,a,R),atlasTexture:B,atlasTextureIcon:j,atlasInterpolation:N,atlasInterpolationIcon:U,isSDF:P,hasHalo:$};if(b)for(var tt=0,et=L.segments.get();tt<et.length;tt+=1){var rt=et[tt];T.push({segments:new t.SegmentVector([rt]),sortKey:rt.sortKey,state:Q})}else T.push({segments:L.segments,sortKey:0,state:Q})}}}b&&T.sort((function(t,e){return t.sortKey-e.sortKey}));for(var nt=0,it=T;nt<it.length;nt+=1){var at=it[nt],ot=at.state;if(p.activeTexture.set(d.TEXTURE0),ot.atlasTexture.bind(ot.atlasInterpolation,d.CLAMP_TO_EDGE),ot.atlasTextureIcon&&(p.activeTexture.set(d.TEXTURE1),ot.atlasTextureIcon&&ot.atlasTextureIcon.bind(ot.atlasInterpolationIcon,d.CLAMP_TO_EDGE)),ot.isSDF){var st=ot.uniformValues;ot.hasHalo&&(st.u_is_halo=1,un(ot.buffers,at.segments,n,e,ot.program,_,f,h,st)),st.u_is_halo=0}un(ot.buffers,at.segments,n,e,ot.program,_,f,h,ot.uniformValues)}}function un(t,e,r,n,i,a,o,s,l){var u=n.context,c=u.gl;i.draw(u,c.TRIANGLES,a,o,s,Ct.disabled,l,r.id,t.layoutVertexBuffer,t.indexBuffer,e,r.paint,n.transform.zoom,t.programConfigurations.get(r.id),t.dynamicLayoutVertexBuffer,t.opacityVertexBuffer)}function cn(t,e,r,n,i,a,o){var s,l,u,c,f,h=t.context.gl,p=r.paint.get(\"fill-pattern\"),d=p&&p.constantOr(1),v=r.getCrossfadeParameters();o?(l=d&&!r.getPaintProperty(\"fill-outline-color\")?\"fillOutlinePattern\":\"fillOutline\",s=h.LINES):(l=d?\"fillPattern\":\"fill\",s=h.TRIANGLES);for(var g=0,y=n;g<y.length;g+=1){var m=y[g],x=e.getTile(m);if(!d||x.patternsLoaded()){var b=x.getBucket(r);if(b){var _=b.programConfigurations.get(r.id),w=t.useProgram(l,_);d&&(t.context.activeTexture.set(h.TEXTURE0),x.imageAtlasTexture.bind(h.LINEAR,h.CLAMP_TO_EDGE),_.updatePaintBuffers(v));var T=p.constantOr(null);if(T&&x.imageAtlas){var k=x.imageAtlas,A=k.patternPositions[T.to.toString()],M=k.patternPositions[T.from.toString()];A&&M&&_.setConstantPatternPositions(A,M)}var S=t.translatePosMatrix(m.posMatrix,x,r.paint.get(\"fill-translate\"),r.paint.get(\"fill-translate-anchor\"));if(o){c=b.indexBuffer2,f=b.segments2;var E=[h.drawingBufferWidth,h.drawingBufferHeight];u=\"fillOutlinePattern\"===l&&d?Pr(S,t,v,x,E):Cr(S,E)}else c=b.indexBuffer,f=b.segments,u=d?Lr(S,t,v,x):Er(S);w.draw(t.context,s,i,t.stencilModeForClipping(m),a,Ct.disabled,u,r.id,b.layoutVertexBuffer,c,f,r.paint,t.transform.zoom,_)}}}}function fn(t,e,r,n,i,a,o){for(var s=t.context,l=s.gl,u=r.paint.get(\"fill-extrusion-pattern\"),c=u.constantOr(1),f=r.getCrossfadeParameters(),h=r.paint.get(\"fill-extrusion-opacity\"),p=0,d=n;p<d.length;p+=1){var v=d[p],g=e.getTile(v),y=g.getBucket(r);if(y){var m=y.programConfigurations.get(r.id),x=t.useProgram(c?\"fillExtrusionPattern\":\"fillExtrusion\",m);c&&(t.context.activeTexture.set(l.TEXTURE0),g.imageAtlasTexture.bind(l.LINEAR,l.CLAMP_TO_EDGE),m.updatePaintBuffers(f));var b=u.constantOr(null);if(b&&g.imageAtlas){var _=g.imageAtlas,w=_.patternPositions[b.to.toString()],T=_.patternPositions[b.from.toString()];w&&T&&m.setConstantPatternPositions(w,T)}var k=t.translatePosMatrix(v.posMatrix,g,r.paint.get(\"fill-extrusion-translate\"),r.paint.get(\"fill-extrusion-translate-anchor\")),A=r.paint.get(\"fill-extrusion-vertical-gradient\"),M=c?Sr(k,t,A,h,v,f,g):Mr(k,t,A,h);x.draw(s,s.gl.TRIANGLES,i,a,o,Ct.backCCW,M,r.id,y.layoutVertexBuffer,y.indexBuffer,y.segments,r.paint,t.transform.zoom,m)}}}function hn(t,e,r,n,i,a){var o=t.context,s=o.gl,l=e.fbo;if(l){var u=t.useProgram(\"hillshade\");o.activeTexture.set(s.TEXTURE0),s.bindTexture(s.TEXTURE_2D,l.colorAttachment.get());var c=Nr(t,e,r);u.draw(o,s.TRIANGLES,n,i,a,Ct.disabled,c,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}}function pn(e,r,n,i,a,o,s){var l=e.context,u=l.gl,c=r.dem;if(c&&c.data){var f=c.dim,h=c.stride,p=c.getPixels();if(l.activeTexture.set(u.TEXTURE1),l.pixelStoreUnpackPremultiplyAlpha.set(!1),r.demTexture=r.demTexture||e.getTileTexture(h),r.demTexture){var d=r.demTexture;d.update(p,{premultiply:!1}),d.bind(u.NEAREST,u.CLAMP_TO_EDGE)}else r.demTexture=new t.Texture(l,p,u.RGBA,{premultiply:!1}),r.demTexture.bind(u.NEAREST,u.CLAMP_TO_EDGE);l.activeTexture.set(u.TEXTURE0);var v=r.fbo;if(!v){var g=new t.Texture(l,{width:f,height:f,data:null},u.RGBA);g.bind(u.LINEAR,u.CLAMP_TO_EDGE),(v=r.fbo=l.createFramebuffer(f,f,!0)).colorAttachment.set(g.texture)}l.bindFramebuffer.set(v.framebuffer),l.viewport.set([0,0,f,f]),e.useProgram(\"hillshadePrepare\").draw(l,u.TRIANGLES,a,o,s,Ct.disabled,jr(r.tileID,c,i),n.id,e.rasterBoundsBuffer,e.quadTriangleIndexBuffer,e.rasterBoundsSegments),r.needsHillshadePrepare=!1}}function dn(e,r,n,i,a){var o=i.paint.get(\"raster-fade-duration\");if(o>0){var s=t.browser.now(),l=(s-e.timeAdded)/o,u=r?(s-r.timeAdded)/o:-1,c=n.getSource(),f=a.coveringZoomLevel({tileSize:c.tileSize,roundZoom:c.roundZoom}),h=!r||Math.abs(r.tileID.overscaledZ-f)>Math.abs(e.tileID.overscaledZ-f),p=h&&e.refreshedUponExpiration?1:t.clamp(h?l:1-u,0,1);return e.refreshedUponExpiration&&l>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}var vn=new t.Color(1,0,0,1),gn=new t.Color(0,1,0,1),yn=new t.Color(0,0,1,1),mn=new t.Color(1,0,1,1),xn=new t.Color(0,1,1,1);function bn(t){var e=t.transform.padding;_n(t,t.transform.height-(e.top||0),3,vn),_n(t,e.bottom||0,3,gn),wn(t,e.left||0,3,yn),wn(t,t.transform.width-(e.right||0),3,mn);var r=t.transform.centerPoint;!function(t,e,r,n){var i=20,a=2;Tn(t,e-a/2,r-i/2,a,i,n),Tn(t,e-i/2,r-a/2,i,a,n)}(t,r.x,t.transform.height-r.y,xn)}function _n(t,e,r,n){Tn(t,0,e+r/2,t.transform.width,r,n)}function wn(t,e,r,n){Tn(t,e-r/2,0,r,t.transform.height,n)}function Tn(e,r,n,i,a,o){var s=e.context,l=s.gl;l.enable(l.SCISSOR_TEST),l.scissor(r*t.browser.devicePixelRatio,n*t.browser.devicePixelRatio,i*t.browser.devicePixelRatio,a*t.browser.devicePixelRatio),s.clear({color:o}),l.disable(l.SCISSOR_TEST)}function kn(e,r,n){var i=e.context,a=i.gl,o=n.posMatrix,s=e.useProgram(\"debug\"),l=Mt.disabled,u=Et.disabled,c=e.colorModeForRenderPass(),f=\"$debug\";i.activeTexture.set(a.TEXTURE0),e.emptyTexture.bind(a.LINEAR,a.CLAMP_TO_EDGE),s.draw(i,a.LINE_STRIP,l,u,c,Ct.disabled,zr(o,t.Color.red),f,e.debugBuffer,e.tileBorderIndexBuffer,e.debugSegments);var h=r.getTileByID(n.key).latestRawTileData,p=h&&h.byteLength||0,d=Math.floor(p/1024),v=r.getTile(n).tileSize,g=512/Math.min(v,512)*(n.overscaledZ/e.transform.zoom)*.5,y=n.canonical.toString();n.overscaledZ!==n.canonical.z&&(y+=\" => \"+n.overscaledZ),function(t,e){t.initDebugOverlayCanvas();var r=t.debugOverlayCanvas,n=t.context.gl,i=t.debugOverlayCanvas.getContext(\"2d\");i.clearRect(0,0,r.width,r.height),i.shadowColor=\"white\",i.shadowBlur=2,i.lineWidth=1.5,i.strokeStyle=\"white\",i.textBaseline=\"top\",i.font=\"bold 36px Open Sans, sans-serif\",i.fillText(e,5,5),i.strokeText(e,5,5),t.debugOverlayTexture.update(r),t.debugOverlayTexture.bind(n.LINEAR,n.CLAMP_TO_EDGE)}(e,y+\" \"+d+\"kb\"),s.draw(i,a.TRIANGLES,l,u,Lt.alphaBlended,Ct.disabled,zr(o,t.Color.transparent,g),f,e.debugBuffer,e.quadTriangleIndexBuffer,e.debugSegments)}var An={symbol:function(e,r,n,i,a){if(\"translucent\"===e.renderPass){var o=Et.disabled,s=e.colorModeForRenderPass();n.layout.get(\"text-variable-anchor\")&&function(e,r,n,i,a,o,s){for(var l=r.transform,u=\"map\"===a,c=\"map\"===o,f=0,h=e;f<h.length;f+=1){var p=h[f],d=i.getTile(p),v=d.getBucket(n);if(v&&v.text&&v.text.segments.get().length){var g=v.textSizeData,y=t.evaluateSizeForZoom(g,l.zoom),m=ge(d,1,r.transform.zoom),x=te(p.posMatrix,c,u,r.transform,m),b=\"none\"!==n.layout.get(\"icon-text-fit\")&&v.hasIconData();if(y){var _=Math.pow(2,l.zoom-d.tileID.overscaledZ);on(v,u,c,s,t.symbolSize,l,x,p.posMatrix,_,y,b)}}}}(i,e,n,r,n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),a),0!==n.paint.get(\"icon-opacity\").constantOr(1)&&ln(e,r,n,i,!1,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),n.layout.get(\"icon-rotation-alignment\"),n.layout.get(\"icon-pitch-alignment\"),n.layout.get(\"icon-keep-upright\"),o,s),0!==n.paint.get(\"text-opacity\").constantOr(1)&&ln(e,r,n,i,!0,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),n.layout.get(\"text-keep-upright\"),o,s),r.map.showCollisionBoxes&&(rn(e,r,n,i,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),!0),rn(e,r,n,i,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),!1))}},circle:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"circle-opacity\"),o=n.paint.get(\"circle-stroke-width\"),s=n.paint.get(\"circle-stroke-opacity\"),l=void 0!==n.layout.get(\"circle-sort-key\").constantOr(1);if(0!==a.constantOr(1)||0!==o.constantOr(1)&&0!==s.constantOr(1)){for(var u=e.context,c=u.gl,f=e.depthModeForSublayer(0,Mt.ReadOnly),h=Et.disabled,p=e.colorModeForRenderPass(),d=[],v=0;v<i.length;v++){var g=i[v],y=r.getTile(g),m=y.getBucket(n);if(m){var x=m.programConfigurations.get(n.id),b={programConfiguration:x,program:e.useProgram(\"circle\",x),layoutVertexBuffer:m.layoutVertexBuffer,indexBuffer:m.indexBuffer,uniformValues:Or(e,g,y,n)};if(l)for(var _=0,w=m.segments.get();_<w.length;_+=1){var T=w[_];d.push({segments:new t.SegmentVector([T]),sortKey:T.sortKey,state:b})}else d.push({segments:m.segments,sortKey:0,state:b})}}l&&d.sort((function(t,e){return t.sortKey-e.sortKey}));for(var k=0,A=d;k<A.length;k+=1){var M=A[k],S=M.state,E=S.programConfiguration,L=S.program,C=S.layoutVertexBuffer,P=S.indexBuffer,O=S.uniformValues,I=M.segments;L.draw(u,c.TRIANGLES,f,h,p,Ct.disabled,O,n.id,C,P,I,n.paint,e.transform.zoom,E)}}}},heatmap:function(e,r,n,i){if(0!==n.paint.get(\"heatmap-opacity\"))if(\"offscreen\"===e.renderPass){var a=e.context,o=a.gl,s=Et.disabled,l=new Lt([o.ONE,o.ONE],t.Color.transparent,[!0,!0,!0,!0]);(function(t,e,r){var n=t.gl;t.activeTexture.set(n.TEXTURE1),t.viewport.set([0,0,e.width/4,e.height/4]);var i=r.heatmapFbo;if(i)n.bindTexture(n.TEXTURE_2D,i.colorAttachment.get()),t.bindFramebuffer.set(i.framebuffer);else{var a=n.createTexture();n.bindTexture(n.TEXTURE_2D,a),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,n.LINEAR),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,n.LINEAR),i=r.heatmapFbo=t.createFramebuffer(e.width/4,e.height/4,!1),function(t,e,r,n){var i=t.gl,a=t.extRenderToTextureHalfFloat?t.extTextureHalfFloat.HALF_FLOAT_OES:i.UNSIGNED_BYTE;i.texImage2D(i.TEXTURE_2D,0,i.RGBA,e.width/4,e.height/4,0,i.RGBA,a,null),n.colorAttachment.set(r)}(t,e,a,i)}})(a,e,n),a.clear({color:t.Color.transparent});for(var u=0;u<i.length;u++){var c=i[u];if(!r.hasRenderableParent(c)){var f=r.getTile(c),h=f.getBucket(n);if(h){var p=h.programConfigurations.get(n.id),d=e.useProgram(\"heatmap\",p),v=e.transform.zoom;d.draw(a,o.TRIANGLES,Mt.disabled,s,l,Ct.disabled,Fr(c.posMatrix,f,v,n.paint.get(\"heatmap-intensity\")),n.id,h.layoutVertexBuffer,h.indexBuffer,h.segments,n.paint,e.transform.zoom,p)}}}a.viewport.set([0,0,e.width,e.height])}else\"translucent\"===e.renderPass&&(e.context.setColorMode(e.colorModeForRenderPass()),function(e,r){var n=e.context,i=n.gl,a=r.heatmapFbo;if(a){n.activeTexture.set(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,a.colorAttachment.get()),n.activeTexture.set(i.TEXTURE1);var o=r.colorRampTexture;o||(o=r.colorRampTexture=new t.Texture(n,r.colorRamp,i.RGBA)),o.bind(i.LINEAR,i.CLAMP_TO_EDGE),e.useProgram(\"heatmapTexture\").draw(n,i.TRIANGLES,Mt.disabled,Et.disabled,e.colorModeForRenderPass(),Ct.disabled,Br(e,r,0,1),r.id,e.viewportBuffer,e.quadTriangleIndexBuffer,e.viewportSegments,r.paint,e.transform.zoom)}}(e,n))},line:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"line-opacity\"),o=n.paint.get(\"line-width\");if(0!==a.constantOr(1)&&0!==o.constantOr(1)){var s=e.depthModeForSublayer(0,Mt.ReadOnly),l=e.colorModeForRenderPass(),u=n.paint.get(\"line-dasharray\"),c=n.paint.get(\"line-pattern\"),f=c.constantOr(1),h=n.paint.get(\"line-gradient\"),p=n.getCrossfadeParameters(),d=f?\"linePattern\":u?\"lineSDF\":h?\"lineGradient\":\"line\",v=e.context,g=v.gl,y=!0;if(h){v.activeTexture.set(g.TEXTURE0);var m=n.gradientTexture;if(!n.gradient)return;m||(m=n.gradientTexture=new t.Texture(v,n.gradient,g.RGBA)),m.bind(g.LINEAR,g.CLAMP_TO_EDGE)}for(var x=0,b=i;x<b.length;x+=1){var _=b[x],w=r.getTile(_);if(!f||w.patternsLoaded()){var T=w.getBucket(n);if(T){var k=T.programConfigurations.get(n.id),A=e.context.program.get(),M=e.useProgram(d,k),S=y||M.program!==A,E=c.constantOr(null);if(E&&w.imageAtlas){var L=w.imageAtlas,C=L.patternPositions[E.to.toString()],P=L.patternPositions[E.from.toString()];C&&P&&k.setConstantPatternPositions(C,P)}var O=f?Hr(e,w,n,p):u?qr(e,w,n,u,p):h?Vr(e,w,n):Ur(e,w,n);f?(v.activeTexture.set(g.TEXTURE0),w.imageAtlasTexture.bind(g.LINEAR,g.CLAMP_TO_EDGE),k.updatePaintBuffers(p)):u&&(S||e.lineAtlas.dirty)&&(v.activeTexture.set(g.TEXTURE0),e.lineAtlas.bind(v)),M.draw(v,g.TRIANGLES,s,e.stencilModeForClipping(_),l,Ct.disabled,O,n.id,T.layoutVertexBuffer,T.indexBuffer,T.segments,n.paint,e.transform.zoom,k),y=!1}}}}}},fill:function(e,r,n,i){var a=n.paint.get(\"fill-color\"),o=n.paint.get(\"fill-opacity\");if(0!==o.constantOr(1)){var s=e.colorModeForRenderPass(),l=n.paint.get(\"fill-pattern\"),u=e.opaquePassEnabledForLayer()&&!l.constantOr(1)&&1===a.constantOr(t.Color.transparent).a&&1===o.constantOr(0)?\"opaque\":\"translucent\";if(e.renderPass===u){var c=e.depthModeForSublayer(1,\"opaque\"===e.renderPass?Mt.ReadWrite:Mt.ReadOnly);cn(e,r,n,i,c,s,!1)}if(\"translucent\"===e.renderPass&&n.paint.get(\"fill-antialias\")){var f=e.depthModeForSublayer(n.getPaintProperty(\"fill-outline-color\")?2:0,Mt.ReadOnly);cn(e,r,n,i,f,s,!0)}}},\"fill-extrusion\":function(t,e,r,n){var i=r.paint.get(\"fill-extrusion-opacity\");if(0!==i&&\"translucent\"===t.renderPass){var a=new Mt(t.context.gl.LEQUAL,Mt.ReadWrite,t.depthRangeFor3D);if(1!==i||r.paint.get(\"fill-extrusion-pattern\").constantOr(1))fn(t,e,r,n,a,Et.disabled,Lt.disabled),fn(t,e,r,n,a,t.stencilModeFor3D(),t.colorModeForRenderPass());else{var o=t.colorModeForRenderPass();fn(t,e,r,n,a,Et.disabled,o)}}},hillshade:function(t,e,r,n){if(\"offscreen\"===t.renderPass||\"translucent\"===t.renderPass){for(var i=t.context,a=e.getSource().maxzoom,o=t.depthModeForSublayer(0,Mt.ReadOnly),s=t.colorModeForRenderPass(),l=\"translucent\"===t.renderPass?t.stencilConfigForOverlap(n):[{},n],u=l[0],c=0,f=l[1];c<f.length;c+=1){var h=f[c],p=e.getTile(h);p.needsHillshadePrepare&&\"offscreen\"===t.renderPass?pn(t,p,r,a,o,Et.disabled,s):\"translucent\"===t.renderPass&&hn(t,p,r,o,u[h.overscaledZ],s)}i.viewport.set([0,0,t.width,t.height])}},raster:function(t,e,r,n){if(\"translucent\"===t.renderPass&&0!==r.paint.get(\"raster-opacity\")&&n.length)for(var i=t.context,a=i.gl,o=e.getSource(),s=t.useProgram(\"raster\"),l=t.colorModeForRenderPass(),u=o instanceof I?[{},n]:t.stencilConfigForOverlap(n),c=u[0],f=u[1],h=f[f.length-1].overscaledZ,p=!t.options.moving,d=0,v=f;d<v.length;d+=1){var g=v[d],y=t.depthModeForSublayer(g.overscaledZ-h,1===r.paint.get(\"raster-opacity\")?Mt.ReadWrite:Mt.ReadOnly,a.LESS),m=e.getTile(g),x=t.transform.calculatePosMatrix(g.toUnwrapped(),p);m.registerFadeDuration(r.paint.get(\"raster-fade-duration\"));var b=e.findLoadedParent(g,0),_=dn(m,b,e,r,t.transform),w=void 0,T=void 0,k=\"nearest\"===r.paint.get(\"raster-resampling\")?a.NEAREST:a.LINEAR;i.activeTexture.set(a.TEXTURE0),m.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),i.activeTexture.set(a.TEXTURE1),b?(b.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),w=Math.pow(2,b.tileID.overscaledZ-m.tileID.overscaledZ),T=[m.tileID.canonical.x*w%1,m.tileID.canonical.y*w%1]):m.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST);var A=Yr(x,T||[0,0],w||1,_,r);o instanceof I?s.draw(i,a.TRIANGLES,y,Et.disabled,l,Ct.disabled,A,r.id,o.boundsBuffer,t.quadTriangleIndexBuffer,o.boundsSegments):s.draw(i,a.TRIANGLES,y,c[g.overscaledZ],l,Ct.disabled,A,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}},background:function(t,e,r){var n=r.paint.get(\"background-color\"),i=r.paint.get(\"background-opacity\");if(0!==i){var a=t.context,o=a.gl,s=t.transform,l=s.tileSize,u=r.paint.get(\"background-pattern\");if(!t.isPatternMissing(u)){var c=!u&&1===n.a&&1===i&&t.opaquePassEnabledForLayer()?\"opaque\":\"translucent\";if(t.renderPass===c){var f=Et.disabled,h=t.depthModeForSublayer(0,\"opaque\"===c?Mt.ReadWrite:Mt.ReadOnly),p=t.colorModeForRenderPass(),d=t.useProgram(u?\"backgroundPattern\":\"background\"),v=s.coveringTiles({tileSize:l});u&&(a.activeTexture.set(o.TEXTURE0),t.imageManager.bind(t.context));for(var g=r.getCrossfadeParameters(),y=0,m=v;y<m.length;y+=1){var x=m[y],b=t.transform.calculatePosMatrix(x.toUnwrapped()),_=u?tn(b,i,t,u,{tileID:x,tileSize:l},g):Qr(b,i,n);d.draw(a,o.TRIANGLES,h,f,p,Ct.disabled,_,r.id,t.tileExtentBuffer,t.quadTriangleIndexBuffer,t.tileExtentSegments)}}}}},debug:function(t,e,r){for(var n=0;n<r.length;n++)kn(t,e,r[n])},custom:function(t,e,r){var n=t.context,i=r.implementation;if(\"offscreen\"===t.renderPass){var a=i.prerender;a&&(t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),a.call(i,n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState())}else if(\"translucent\"===t.renderPass){t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),n.setStencilMode(Et.disabled);var o=\"3d\"===i.renderingMode?new Mt(t.context.gl.LEQUAL,Mt.ReadWrite,t.depthRangeFor3D):t.depthModeForSublayer(0,Mt.ReadOnly);n.setDepthMode(o),i.render(n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState(),n.bindFramebuffer.set(null)}}},Mn=function(t,e){this.context=new Pt(t),this.transform=e,this._tileTextures={},this.setup(),this.numSublayers=Ot.maxUnderzooming+Ot.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new Ve,this.gpuTimers={}};Mn.prototype.resize=function(e,r){if(this.width=e*t.browser.devicePixelRatio,this.height=r*t.browser.devicePixelRatio,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(var n=0,i=this.style._order;n<i.length;n+=1){var a=i[n];this.style._layers[a].resize()}},Mn.prototype.setup=function(){var e=this.context,r=new t.StructArrayLayout2i4;r.emplaceBack(0,0),r.emplaceBack(t.EXTENT,0),r.emplaceBack(0,t.EXTENT),r.emplaceBack(t.EXTENT,t.EXTENT),this.tileExtentBuffer=e.createVertexBuffer(r,We.members),this.tileExtentSegments=t.SegmentVector.simpleSegment(0,0,4,2);var n=new t.StructArrayLayout2i4;n.emplaceBack(0,0),n.emplaceBack(t.EXTENT,0),n.emplaceBack(0,t.EXTENT),n.emplaceBack(t.EXTENT,t.EXTENT),this.debugBuffer=e.createVertexBuffer(n,We.members),this.debugSegments=t.SegmentVector.simpleSegment(0,0,4,5);var i=new t.StructArrayLayout4i8;i.emplaceBack(0,0,0,0),i.emplaceBack(t.EXTENT,0,t.EXTENT,0),i.emplaceBack(0,t.EXTENT,0,t.EXTENT),i.emplaceBack(t.EXTENT,t.EXTENT,t.EXTENT,t.EXTENT),this.rasterBoundsBuffer=e.createVertexBuffer(i,O.members),this.rasterBoundsSegments=t.SegmentVector.simpleSegment(0,0,4,2);var a=new t.StructArrayLayout2i4;a.emplaceBack(0,0),a.emplaceBack(1,0),a.emplaceBack(0,1),a.emplaceBack(1,1),this.viewportBuffer=e.createVertexBuffer(a,We.members),this.viewportSegments=t.SegmentVector.simpleSegment(0,0,4,2);var o=new t.StructArrayLayout1ui2;o.emplaceBack(0),o.emplaceBack(1),o.emplaceBack(3),o.emplaceBack(2),o.emplaceBack(0),this.tileBorderIndexBuffer=e.createIndexBuffer(o);var s=new t.StructArrayLayout3ui6;s.emplaceBack(0,1,2),s.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=e.createIndexBuffer(s),this.emptyTexture=new t.Texture(e,{width:1,height:1,data:new Uint8Array([0,0,0,0])},e.gl.RGBA);var l=this.context.gl;this.stencilClearMode=new Et({func:l.ALWAYS,mask:0},0,255,l.ZERO,l.ZERO,l.ZERO)},Mn.prototype.clearStencil=function(){var e=this.context,r=e.gl;this.nextStencilID=1,this.currentStencilSource=void 0;var n=t.create();t.ortho(n,0,this.width,this.height,0,0,1),t.scale(n,n,[r.drawingBufferWidth,r.drawingBufferHeight,0]),this.useProgram(\"clippingMask\").draw(e,r.TRIANGLES,Mt.disabled,this.stencilClearMode,Lt.disabled,Ct.disabled,Rr(n),\"$clipping\",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)},Mn.prototype._renderTileClippingMasks=function(t,e){if(this.currentStencilSource!==t.source&&t.isTileClipped()&&e&&e.length){this.currentStencilSource=t.source;var r=this.context,n=r.gl;this.nextStencilID+e.length>256&&this.clearStencil(),r.setColorMode(Lt.disabled),r.setDepthMode(Mt.disabled);var i=this.useProgram(\"clippingMask\");this._tileClippingMaskIDs={};for(var a=0,o=e;a<o.length;a+=1){var s=o[a],l=this._tileClippingMaskIDs[s.key]=this.nextStencilID++;i.draw(r,n.TRIANGLES,Mt.disabled,new Et({func:n.ALWAYS,mask:0},l,255,n.KEEP,n.KEEP,n.REPLACE),Lt.disabled,Ct.disabled,Rr(s.posMatrix),\"$clipping\",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}},Mn.prototype.stencilModeFor3D=function(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();var t=this.nextStencilID++,e=this.context.gl;return new Et({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)},Mn.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new Et({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},Mn.prototype.stencilConfigForOverlap=function(t){var e,r=this.context.gl,n=t.sort((function(t,e){return e.overscaledZ-t.overscaledZ})),i=n[n.length-1].overscaledZ,a=n[0].overscaledZ-i+1;if(a>1){this.currentStencilSource=void 0,this.nextStencilID+a>256&&this.clearStencil();for(var o={},s=0;s<a;s++)o[s+i]=new Et({func:r.GEQUAL,mask:255},s+this.nextStencilID,255,r.KEEP,r.KEEP,r.REPLACE);return this.nextStencilID+=a,[o,n]}return[(e={},e[i]=Et.disabled,e),n]},Mn.prototype.colorModeForRenderPass=function(){var e=this.context.gl;if(this._showOverdrawInspector){var r=1/8;return new Lt([e.CONSTANT_COLOR,e.ONE],new t.Color(r,r,r,0),[!0,!0,!0,!0])}return\"opaque\"===this.renderPass?Lt.unblended:Lt.alphaBlended},Mn.prototype.depthModeForSublayer=function(t,e,r){if(!this.opaquePassEnabledForLayer())return Mt.disabled;var n=1-((1+this.currentLayer)*this.numSublayers+t)*this.depthEpsilon;return new Mt(r||this.context.gl.LEQUAL,e,[n,n])},Mn.prototype.opaquePassEnabledForLayer=function(){return this.currentLayer<this.opaquePassCutoff},Mn.prototype.render=function(e,r){var n=this;this.style=e,this.options=r,this.lineAtlas=e.lineAtlas,this.imageManager=e.imageManager,this.glyphManager=e.glyphManager,this.symbolFadeChange=e.placement.symbolFadeChange(t.browser.now()),this.imageManager.beginFrame();var i=this.style._order,a=this.style.sourceCaches;for(var o in a){var s=a[o];s.used&&s.prepare(this.context)}var l,u,c={},f={},h={};for(var p in a){var d=a[p];c[p]=d.getVisibleCoordinates(),f[p]=c[p].slice().reverse(),h[p]=d.getVisibleCoordinates(!0).reverse()}this.opaquePassCutoff=1/0;for(var v=0;v<i.length;v++){var g=i[v];if(this.style._layers[g].is3D()){this.opaquePassCutoff=v;break}}this.renderPass=\"offscreen\";for(var y=0,m=i;y<m.length;y+=1){var x=m[y],b=this.style._layers[x];if(b.hasOffscreenPass()&&!b.isHidden(this.transform.zoom)){var _=f[b.source];(\"custom\"===b.type||_.length)&&this.renderLayer(this,a[b.source],b,_)}}for(this.context.bindFramebuffer.set(null),this.context.clear({color:r.showOverdrawInspector?t.Color.black:t.Color.transparent,depth:1}),this.clearStencil(),this._showOverdrawInspector=r.showOverdrawInspector,this.depthRangeFor3D=[0,1-(e._order.length+2)*this.numSublayers*this.depthEpsilon],this.renderPass=\"opaque\",this.currentLayer=i.length-1;this.currentLayer>=0;this.currentLayer--){var w=this.style._layers[i[this.currentLayer]],T=a[w.source],k=c[w.source];this._renderTileClippingMasks(w,k),this.renderLayer(this,T,w,k)}for(this.renderPass=\"translucent\",this.currentLayer=0;this.currentLayer<i.length;this.currentLayer++){var A=this.style._layers[i[this.currentLayer]],M=a[A.source],S=(\"symbol\"===A.type?h:f)[A.source];this._renderTileClippingMasks(A,c[A.source]),this.renderLayer(this,M,A,S)}this.options.showTileBoundaries&&(t.values(this.style._layers).forEach((function(t){t.source&&!t.isHidden(n.transform.zoom)&&(t.source!==(u&&u.id)&&(u=n.style.sourceCaches[t.source]),(!l||l.getSource().maxzoom<u.getSource().maxzoom)&&(l=u))})),l&&An.debug(this,l,l.getVisibleCoordinates())),this.options.showPadding&&bn(this),this.context.setDefault()},Mn.prototype.renderLayer=function(t,e,r,n){r.isHidden(this.transform.zoom)||(\"background\"===r.type||\"custom\"===r.type||n.length)&&(this.id=r.id,this.gpuTimingStart(r),An[r.type](t,e,r,n,this.style.placement.variableOffsets),this.gpuTimingEnd())},Mn.prototype.gpuTimingStart=function(t){if(this.options.gpuTiming){var e=this.context.extTimerQuery,r=this.gpuTimers[t.id];r||(r=this.gpuTimers[t.id]={calls:0,cpuTime:0,query:e.createQueryEXT()}),r.calls++,e.beginQueryEXT(e.TIME_ELAPSED_EXT,r.query)}},Mn.prototype.gpuTimingEnd=function(){if(this.options.gpuTiming){var t=this.context.extTimerQuery;t.endQueryEXT(t.TIME_ELAPSED_EXT)}},Mn.prototype.collectGpuTimers=function(){var t=this.gpuTimers;return this.gpuTimers={},t},Mn.prototype.queryGpuTimers=function(t){var e={};for(var r in t){var n=t[r],i=this.context.extTimerQuery,a=i.getQueryObjectEXT(n.query,i.QUERY_RESULT_EXT)/1e6;i.deleteQueryEXT(n.query),e[r]=a}return e},Mn.prototype.translatePosMatrix=function(e,r,n,i,a){if(!n[0]&&!n[1])return e;var o=a?\"map\"===i?this.transform.angle:0:\"viewport\"===i?-this.transform.angle:0;if(o){var s=Math.sin(o),l=Math.cos(o);n=[n[0]*l-n[1]*s,n[0]*s+n[1]*l]}var u=[a?n[0]:ge(r,n[0],this.transform.zoom),a?n[1]:ge(r,n[1],this.transform.zoom),0],c=new Float32Array(16);return t.translate(c,e,u),c},Mn.prototype.saveTileTexture=function(t){var e=this._tileTextures[t.size[0]];e?e.push(t):this._tileTextures[t.size[0]]=[t]},Mn.prototype.getTileTexture=function(t){var e=this._tileTextures[t];return e&&e.length>0?e.pop():null},Mn.prototype.isPatternMissing=function(t){if(!t)return!1;if(!t.from||!t.to)return!0;var e=this.imageManager.getPattern(t.from.toString()),r=this.imageManager.getPattern(t.to.toString());return!e||!r},Mn.prototype.useProgram=function(t,e){this.cache=this.cache||{};var r=\"\"+t+(e?e.cacheKey:\"\")+(this._showOverdrawInspector?\"/overdraw\":\"\");return this.cache[r]||(this.cache[r]=new kr(this.context,wr[t],e,en[t],this._showOverdrawInspector)),this.cache[r]},Mn.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},Mn.prototype.setBaseState=function(){var t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)},Mn.prototype.initDebugOverlayCanvas=function(){if(null==this.debugOverlayCanvas){this.debugOverlayCanvas=t.window.document.createElement(\"canvas\"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512;var e=this.context.gl;this.debugOverlayTexture=new t.Texture(this.context,this.debugOverlayCanvas,e.RGBA)}},Mn.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var Sn=function(t,e){this.points=t,this.planes=e};Sn.fromInvProjectionMatrix=function(e,r,n){var i=Math.pow(2,n),a=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map((function(r){return t.transformMat4([],r,e)})).map((function(e){return t.scale$1([],e,1/e[3]/r*i)})),o=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map((function(e){var r=t.sub([],a[e[0]],a[e[1]]),n=t.sub([],a[e[2]],a[e[1]]),i=t.normalize([],t.cross([],r,n)),o=-t.dot(i,a[e[1]]);return i.concat(o)}));return new Sn(a,o)};var En=function(e,r){this.min=e,this.max=r,this.center=t.scale$2([],t.add([],this.min,this.max),.5)};En.prototype.quadrant=function(e){for(var r=[e%2==0,e<2],n=t.clone$2(this.min),i=t.clone$2(this.max),a=0;a<r.length;a++)n[a]=r[a]?this.min[a]:this.center[a],i[a]=r[a]?this.center[a]:this.max[a];return i[2]=this.max[2],new En(n,i)},En.prototype.distanceX=function(t){return Math.max(Math.min(this.max[0],t[0]),this.min[0])-t[0]},En.prototype.distanceY=function(t){return Math.max(Math.min(this.max[1],t[1]),this.min[1])-t[1]},En.prototype.intersects=function(e){for(var r=[[this.min[0],this.min[1],0,1],[this.max[0],this.min[1],0,1],[this.max[0],this.max[1],0,1],[this.min[0],this.max[1],0,1]],n=!0,i=0;i<e.planes.length;i++){for(var a=e.planes[i],o=0,s=0;s<r.length;s++)o+=t.dot$1(a,r[s])>=0;if(0===o)return 0;o!==r.length&&(n=!1)}if(n)return 2;for(var l=0;l<3;l++){for(var u=Number.MAX_VALUE,c=-Number.MAX_VALUE,f=0;f<e.points.length;f++){var h=e.points[f][l]-this.min[l];u=Math.min(u,h),c=Math.max(c,h)}if(c<0||u>this.max[l]-this.min[l])return 0}return 1};var Ln=function(t,e,r,n){if(void 0===t&&(t=0),void 0===e&&(e=0),void 0===r&&(r=0),void 0===n&&(n=0),isNaN(t)||t<0||isNaN(e)||e<0||isNaN(r)||r<0||isNaN(n)||n<0)throw new Error(\"Invalid value for edge-insets, top, bottom, left and right must all be numbers\");this.top=t,this.bottom=e,this.left=r,this.right=n};Ln.prototype.interpolate=function(e,r,n){return null!=r.top&&null!=e.top&&(this.top=t.number(e.top,r.top,n)),null!=r.bottom&&null!=e.bottom&&(this.bottom=t.number(e.bottom,r.bottom,n)),null!=r.left&&null!=e.left&&(this.left=t.number(e.left,r.left,n)),null!=r.right&&null!=e.right&&(this.right=t.number(e.right,r.right,n)),this},Ln.prototype.getCenter=function(e,r){var n=t.clamp((this.left+e-this.right)/2,0,e),i=t.clamp((this.top+r-this.bottom)/2,0,r);return new t.Point(n,i)},Ln.prototype.equals=function(t){return this.top===t.top&&this.bottom===t.bottom&&this.left===t.left&&this.right===t.right},Ln.prototype.clone=function(){return new Ln(this.top,this.bottom,this.left,this.right)},Ln.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var Cn=function(e,r,n,i,a){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=void 0===a||a,this._minZoom=e||0,this._maxZoom=r||22,this._minPitch=null==n?0:n,this._maxPitch=null==i?60:i,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new Ln,this._posMatrixCache={},this._alignedPosMatrixCache={}},Pn={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};Cn.prototype.clone=function(){var t=new Cn(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._edgeInsets=this._edgeInsets.clone(),t._calcMatrices(),t},Pn.minZoom.get=function(){return this._minZoom},Pn.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},Pn.maxZoom.get=function(){return this._maxZoom},Pn.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},Pn.minPitch.get=function(){return this._minPitch},Pn.minPitch.set=function(t){this._minPitch!==t&&(this._minPitch=t,this.pitch=Math.max(this.pitch,t))},Pn.maxPitch.get=function(){return this._maxPitch},Pn.maxPitch.set=function(t){this._maxPitch!==t&&(this._maxPitch=t,this.pitch=Math.min(this.pitch,t))},Pn.renderWorldCopies.get=function(){return this._renderWorldCopies},Pn.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},Pn.worldSize.get=function(){return this.tileSize*this.scale},Pn.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},Pn.size.get=function(){return new t.Point(this.width,this.height)},Pn.bearing.get=function(){return-this.angle/Math.PI*180},Pn.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=t.create$2(),t.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},Pn.pitch.get=function(){return this._pitch/Math.PI*180},Pn.pitch.set=function(e){var r=t.clamp(e,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},Pn.fov.get=function(){return this._fov/Math.PI*180},Pn.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},Pn.zoom.get=function(){return this._zoom},Pn.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},Pn.center.get=function(){return this._center},Pn.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},Pn.padding.get=function(){return this._edgeInsets.toJSON()},Pn.padding.set=function(t){this._edgeInsets.equals(t)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,t,1),this._calcMatrices())},Pn.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},Cn.prototype.isPaddingEqual=function(t){return this._edgeInsets.equals(t)},Cn.prototype.interpolatePadding=function(t,e,r){this._unmodified=!1,this._edgeInsets.interpolate(t,e,r),this._constrain(),this._calcMatrices()},Cn.prototype.coveringZoomLevel=function(t){var e=(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize));return Math.max(0,e)},Cn.prototype.getVisibleUnwrappedCoordinates=function(e){var r=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var n=this.pointCoordinate(new t.Point(0,0)),i=this.pointCoordinate(new t.Point(this.width,0)),a=this.pointCoordinate(new t.Point(this.width,this.height)),o=this.pointCoordinate(new t.Point(0,this.height)),s=Math.floor(Math.min(n.x,i.x,a.x,o.x)),l=Math.floor(Math.max(n.x,i.x,a.x,o.x)),u=s-1;u<=l+1;u++)0!==u&&r.push(new t.UnwrappedTileID(u,e));return r},Cn.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&r<e.minzoom)return[];void 0!==e.maxzoom&&r>e.maxzoom&&(r=e.maxzoom);var i=t.MercatorCoordinate.fromLngLat(this.center),a=Math.pow(2,r),o=[a*i.x,a*i.y,0],s=Sn.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,r),l=e.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(l=r);var u=function(t){return{aabb:new En([t*a,0,0],[(t+1)*a,a,0]),zoom:0,x:0,y:0,wrap:t,fullyVisible:!1}},c=[],f=[],h=r,p=e.reparseOverscaled?n:r;if(this._renderWorldCopies)for(var d=1;d<=3;d++)c.push(u(-d)),c.push(u(d));for(c.push(u(0));c.length>0;){var v=c.pop(),g=v.x,y=v.y,m=v.fullyVisible;if(!m){var x=v.aabb.intersects(s);if(0===x)continue;m=2===x}var b=v.aabb.distanceX(o),_=v.aabb.distanceY(o),w=Math.max(Math.abs(b),Math.abs(_)),T=3+(1<<h-v.zoom)-2;if(v.zoom===h||w>T&&v.zoom>=l)f.push({tileID:new t.OverscaledTileID(v.zoom===h?p:v.zoom,v.wrap,v.zoom,g,y),distanceSq:t.sqrLen([o[0]-.5-g,o[1]-.5-y])});else for(var k=0;k<4;k++){var A=(g<<1)+k%2,M=(y<<1)+(k>>1);c.push({aabb:v.aabb.quadrant(k),zoom:v.zoom+1,x:A,y:M,wrap:v.wrap,fullyVisible:m})}}return f.sort((function(t,e){return t.distanceSq-e.distanceSq})).map((function(t){return t.tileID}))},Cn.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},Pn.unmodified.get=function(){return this._unmodified},Cn.prototype.zoomScale=function(t){return Math.pow(2,t)},Cn.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},Cn.prototype.project=function(e){var r=t.clamp(e.lat,-this.maxValidLatitude,this.maxValidLatitude);return new t.Point(t.mercatorXfromLng(e.lng)*this.worldSize,t.mercatorYfromLat(r)*this.worldSize)},Cn.prototype.unproject=function(e){return new t.MercatorCoordinate(e.x/this.worldSize,e.y/this.worldSize).toLngLat()},Pn.point.get=function(){return this.project(this.center)},Cn.prototype.setLocationAtPoint=function(e,r){var n=this.pointCoordinate(r),i=this.pointCoordinate(this.centerPoint),a=this.locationCoordinate(e),o=new t.MercatorCoordinate(a.x-(n.x-i.x),a.y-(n.y-i.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())},Cn.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},Cn.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},Cn.prototype.locationCoordinate=function(e){return t.MercatorCoordinate.fromLngLat(e)},Cn.prototype.coordinateLocation=function(t){return t.toLngLat()},Cn.prototype.pointCoordinate=function(e){var r=[e.x,e.y,0,1],n=[e.x,e.y,1,1];t.transformMat4(r,r,this.pixelMatrixInverse),t.transformMat4(n,n,this.pixelMatrixInverse);var i=r[3],a=n[3],o=r[0]/i,s=n[0]/a,l=r[1]/i,u=n[1]/a,c=r[2]/i,f=n[2]/a,h=c===f?0:(0-c)/(f-c);return new t.MercatorCoordinate(t.number(o,s,h)/this.worldSize,t.number(l,u,h)/this.worldSize)},Cn.prototype.coordinatePoint=function(e){var r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix),new t.Point(r[0]/r[3],r[1]/r[3])},Cn.prototype.getBounds=function(){return(new t.LngLatBounds).extend(this.pointLocation(new t.Point(0,0))).extend(this.pointLocation(new t.Point(this.width,0))).extend(this.pointLocation(new t.Point(this.width,this.height))).extend(this.pointLocation(new t.Point(0,this.height)))},Cn.prototype.getMaxBounds=function(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new t.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null},Cn.prototype.setMaxBounds=function(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},Cn.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,i=r?this._alignedPosMatrixCache:this._posMatrixCache;if(i[n])return i[n];var a=e.canonical,o=this.worldSize/this.zoomScale(a.z),s=a.x+Math.pow(2,a.z)*e.wrap,l=t.identity(new Float64Array(16));return t.translate(l,l,[s*o,a.y*o,0]),t.scale(l,l,[o/t.EXTENT,o/t.EXTENT,1]),t.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),i[n]=new Float32Array(l),i[n]},Cn.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},Cn.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,i,a=-90,o=90,s=-180,l=180,u=this.size,c=this._unmodified;if(this.latRange){var f=this.latRange;a=t.mercatorYfromLat(f[1])*this.worldSize,e=(o=t.mercatorYfromLat(f[0])*this.worldSize)-a<u.y?u.y/(o-a):0}if(this.lngRange){var h=this.lngRange;s=t.mercatorXfromLng(h[0])*this.worldSize,r=(l=t.mercatorXfromLng(h[1])*this.worldSize)-s<u.x?u.x/(l-s):0}var p=this.point,d=Math.max(r||0,e||0);if(d)return this.center=this.unproject(new t.Point(r?(l+s)/2:p.x,e?(o+a)/2:p.y)),this.zoom+=this.scaleZoom(d),this._unmodified=c,void(this._constraining=!1);if(this.latRange){var v=p.y,g=u.y/2;v-g<a&&(i=a+g),v+g>o&&(i=o-g)}if(this.lngRange){var y=p.x,m=u.x/2;y-m<s&&(n=s+m),y+m>l&&(n=l-m)}void 0===n&&void 0===i||(this.center=this.unproject(new t.Point(void 0!==n?n:p.x,void 0!==i?i:p.y))),this._unmodified=c,this._constraining=!1}},Cn.prototype._calcMatrices=function(){if(this.height){var e=this._fov/2,r=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(e)*this.height;var n=Math.PI/2+this._pitch,i=this._fov*(.5+r.y/this.height),a=Math.sin(i)*this.cameraToCenterDistance/Math.sin(t.clamp(Math.PI-n-i,.01,Math.PI-.01)),o=this.point,s=o.x,l=o.y,u=1.01*(Math.cos(Math.PI/2-this._pitch)*a+this.cameraToCenterDistance),c=this.height/50,f=new Float64Array(16);t.perspective(f,this._fov,this.width/this.height,c,u),f[8]=2*-r.x/this.width,f[9]=2*r.y/this.height,t.scale(f,f,[1,-1,1]),t.translate(f,f,[0,0,-this.cameraToCenterDistance]),t.rotateX(f,f,this._pitch),t.rotateZ(f,f,this.angle),t.translate(f,f,[-s,-l,0]),this.mercatorMatrix=t.scale([],f,[this.worldSize,this.worldSize,this.worldSize]),t.scale(f,f,[1,1,t.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=f,this.invProjMatrix=t.invert([],this.projMatrix);var h=this.width%2/2,p=this.height%2/2,d=Math.cos(this.angle),v=Math.sin(this.angle),g=s-Math.round(s)+d*h+v*p,y=l-Math.round(l)+d*p+v*h,m=new Float64Array(f);if(t.translate(m,m,[g>.5?g-1:g,y>.5?y-1:y,0]),this.alignedProjMatrix=m,f=t.create(),t.scale(f,f,[this.width/2,-this.height/2,1]),t.translate(f,f,[1,-1,0]),this.labelPlaneMatrix=f,f=t.create(),t.scale(f,f,[1,-1,1]),t.translate(f,f,[-1,-1,0]),t.scale(f,f,[2/this.width,2/this.height,1]),this.glCoordMatrix=f,this.pixelMatrix=t.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),!(f=t.invert(new Float64Array(16),this.pixelMatrix)))throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=f,this._posMatrixCache={},this._alignedPosMatrixCache={}}},Cn.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.Point(0,0)),r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},Cn.prototype.getCameraPoint=function(){var e=this._pitch,r=Math.tan(e)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.Point(0,r))},Cn.prototype.getCameraQueryGeometry=function(e){var r=this.getCameraPoint();if(1===e.length)return[e[0],r];for(var n=r.x,i=r.y,a=r.x,o=r.y,s=0,l=e;s<l.length;s+=1){var u=l[s];n=Math.min(n,u.x),i=Math.min(i,u.y),a=Math.max(a,u.x),o=Math.max(o,u.y)}return[new t.Point(n,i),new t.Point(a,i),new t.Point(a,o),new t.Point(n,o),new t.Point(n,i)]},Object.defineProperties(Cn.prototype,Pn);var On=function(e){var r,n,i,a,o;this._hashName=e&&encodeURIComponent(e),t.bindAll([\"_getCurrentHash\",\"_onHashChange\",\"_updateHash\"],this),this._updateHash=(r=this._updateHashUnthrottled.bind(this),n=300,i=!1,a=null,o=function(){a=null,i&&(r(),a=setTimeout(o,n),i=!1)},function(){return i=!0,a||o(),a})};On.prototype.addTo=function(e){return this._map=e,t.window.addEventListener(\"hashchange\",this._onHashChange,!1),this._map.on(\"moveend\",this._updateHash),this},On.prototype.remove=function(){return t.window.removeEventListener(\"hashchange\",this._onHashChange,!1),this._map.off(\"moveend\",this._updateHash),clearTimeout(this._updateHash()),delete this._map,this},On.prototype.getHashString=function(e){var r=this._map.getCenter(),n=Math.round(100*this._map.getZoom())/100,i=Math.ceil((n*Math.LN2+Math.log(512/360/.5))/Math.LN10),a=Math.pow(10,i),o=Math.round(r.lng*a)/a,s=Math.round(r.lat*a)/a,l=this._map.getBearing(),u=this._map.getPitch(),c=\"\";if(c+=e?\"/\"+o+\"/\"+s+\"/\"+n:n+\"/\"+s+\"/\"+o,(l||u)&&(c+=\"/\"+Math.round(10*l)/10),u&&(c+=\"/\"+Math.round(u)),this._hashName){var f=this._hashName,h=!1,p=t.window.location.hash.slice(1).split(\"&\").map((function(t){var e=t.split(\"=\")[0];return e===f?(h=!0,e+\"=\"+c):t})).filter((function(t){return t}));return h||p.push(f+\"=\"+c),\"#\"+p.join(\"&\")}return\"#\"+c},On.prototype._getCurrentHash=function(){var e,r=this,n=t.window.location.hash.replace(\"#\",\"\");return this._hashName?(n.split(\"&\").map((function(t){return t.split(\"=\")})).forEach((function(t){t[0]===r._hashName&&(e=t)})),(e&&e[1]||\"\").split(\"/\")):n.split(\"/\")},On.prototype._onHashChange=function(){var t=this._getCurrentHash();if(t.length>=3&&!t.some((function(t){return isNaN(t)}))){var e=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(t[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:e,pitch:+(t[4]||0)}),!0}return!1},On.prototype._updateHashUnthrottled=function(){var e=this.getHashString();try{t.window.history.replaceState(t.window.history.state,\"\",e)}catch(t){}};var In={linearity:.3,easing:t.bezier(0,0,.3,1)},Dn=t.extend({deceleration:2500,maxSpeed:1400},In),zn=t.extend({deceleration:20,maxSpeed:1400},In),Rn=t.extend({deceleration:1e3,maxSpeed:360},In),Fn=t.extend({deceleration:1e3,maxSpeed:90},In),Bn=function(t){this._map=t,this.clear()};function Nn(t,e){(!t.duration||t.duration<e.duration)&&(t.duration=e.duration,t.easing=e.easing)}function jn(e,r,n){var i=n.maxSpeed,a=n.linearity,o=n.deceleration,s=t.clamp(e*a/(r/1e3),-i,i),l=Math.abs(s)/(o*a);return{easing:n.easing,duration:1e3*l,amount:s*(l/2)}}Bn.prototype.clear=function(){this._inertiaBuffer=[]},Bn.prototype.record=function(e){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:t.browser.now(),settings:e})},Bn.prototype._drainInertiaBuffer=function(){for(var e=this._inertiaBuffer,r=t.browser.now();e.length>0&&r-e[0].time>160;)e.shift()},Bn.prototype._onMoveEnd=function(e){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var r={zoom:0,bearing:0,pitch:0,pan:new t.Point(0,0),pinchAround:void 0,around:void 0},n=0,i=this._inertiaBuffer;n<i.length;n+=1){var a=i[n].settings;r.zoom+=a.zoomDelta||0,r.bearing+=a.bearingDelta||0,r.pitch+=a.pitchDelta||0,a.panDelta&&r.pan._add(a.panDelta),a.around&&(r.around=a.around),a.pinchAround&&(r.pinchAround=a.pinchAround)}var o=this._inertiaBuffer[this._inertiaBuffer.length-1].time-this._inertiaBuffer[0].time,s={};if(r.pan.mag()){var l=jn(r.pan.mag(),o,t.extend({},Dn,e||{}));s.offset=r.pan.mult(l.amount/r.pan.mag()),s.center=this._map.transform.center,Nn(s,l)}if(r.zoom){var u=jn(r.zoom,o,zn);s.zoom=this._map.transform.zoom+u.amount,Nn(s,u)}if(r.bearing){var c=jn(r.bearing,o,Rn);s.bearing=this._map.transform.bearing+t.clamp(c.amount,-179,179),Nn(s,c)}if(r.pitch){var f=jn(r.pitch,o,Fn);s.pitch=this._map.transform.pitch+f.amount,Nn(s,f)}if(s.zoom||s.bearing){var h=void 0===r.pinchAround?r.around:r.pinchAround;s.around=h?this._map.unproject(h):this._map.getCenter()}return this.clear(),t.extend(s,{noMoveStart:!0})}};var Un=function(e){function n(n,i,a,o){void 0===o&&(o={});var s=r.mousePos(i.getCanvasContainer(),a),l=i.unproject(s);e.call(this,n,t.extend({point:s,lngLat:l,originalEvent:a},o)),this._defaultPrevented=!1,this.target=i}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Vn=function(e){function n(n,i,a){var o=\"touchend\"===n?a.changedTouches:a.touches,s=r.touchPos(i.getCanvasContainer(),o),l=s.map((function(t){return i.unproject(t)})),u=s.reduce((function(t,e,r,n){return t.add(e.div(n.length))}),new t.Point(0,0)),c=i.unproject(u);e.call(this,n,{points:s,point:u,lngLats:l,lngLat:c,originalEvent:a}),this._defaultPrevented=!1}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Hn=function(t){function e(e,r,n){t.call(this,e,{originalEvent:n}),this._defaultPrevented=!1}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={defaultPrevented:{configurable:!0}};return e.prototype.preventDefault=function(){this._defaultPrevented=!0},r.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(e.prototype,r),e}(t.Event),qn=function(t,e){this._map=t,this._clickTolerance=e.clickTolerance};qn.prototype.reset=function(){delete this._mousedownPos},qn.prototype.wheel=function(t){return this._firePreventable(new Hn(t.type,this._map,t))},qn.prototype.mousedown=function(t,e){return this._mousedownPos=e,this._firePreventable(new Un(t.type,this._map,t))},qn.prototype.mouseup=function(t){this._map.fire(new Un(t.type,this._map,t))},qn.prototype.click=function(t,e){this._mousedownPos&&this._mousedownPos.dist(e)>=this._clickTolerance||this._map.fire(new Un(t.type,this._map,t))},qn.prototype.dblclick=function(t){return this._firePreventable(new Un(t.type,this._map,t))},qn.prototype.mouseover=function(t){this._map.fire(new Un(t.type,this._map,t))},qn.prototype.mouseout=function(t){this._map.fire(new Un(t.type,this._map,t))},qn.prototype.touchstart=function(t){return this._firePreventable(new Vn(t.type,this._map,t))},qn.prototype.touchmove=function(t){this._map.fire(new Vn(t.type,this._map,t))},qn.prototype.touchend=function(t){this._map.fire(new Vn(t.type,this._map,t))},qn.prototype.touchcancel=function(t){this._map.fire(new Vn(t.type,this._map,t))},qn.prototype._firePreventable=function(t){if(this._map.fire(t),t.defaultPrevented)return{}},qn.prototype.isEnabled=function(){return!0},qn.prototype.isActive=function(){return!1},qn.prototype.enable=function(){},qn.prototype.disable=function(){};var Gn=function(t){this._map=t};Gn.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},Gn.prototype.mousemove=function(t){this._map.fire(new Un(t.type,this._map,t))},Gn.prototype.mousedown=function(){this._delayContextMenu=!0},Gn.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new Un(\"contextmenu\",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},Gn.prototype.contextmenu=function(t){this._delayContextMenu?this._contextMenuEvent=t:this._map.fire(new Un(t.type,this._map,t)),this._map.listens(\"contextmenu\")&&t.preventDefault()},Gn.prototype.isEnabled=function(){return!0},Gn.prototype.isActive=function(){return!1},Gn.prototype.enable=function(){},Gn.prototype.disable=function(){};var Zn=function(t,e){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),this._clickTolerance=e.clickTolerance||1};function Yn(t,e){for(var r={},n=0;n<t.length;n++)r[t[n].identifier]=e[n];return r}Zn.prototype.isEnabled=function(){return!!this._enabled},Zn.prototype.isActive=function(){return!!this._active},Zn.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},Zn.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},Zn.prototype.mousedown=function(t,e){this.isEnabled()&&t.shiftKey&&0===t.button&&(r.disableDrag(),this._startPos=this._lastPos=e,this._active=!0)},Zn.prototype.mousemoveWindow=function(t,e){if(this._active){var n=e;if(!(this._lastPos.equals(n)||!this._box&&n.dist(this._startPos)<this._clickTolerance)){var i=this._startPos;this._lastPos=n,this._box||(this._box=r.create(\"div\",\"mapboxgl-boxzoom\",this._container),this._container.classList.add(\"mapboxgl-crosshair\"),this._fireEvent(\"boxzoomstart\",t));var a=Math.min(i.x,n.x),o=Math.max(i.x,n.x),s=Math.min(i.y,n.y),l=Math.max(i.y,n.y);r.setTransform(this._box,\"translate(\"+a+\"px,\"+s+\"px)\"),this._box.style.width=o-a+\"px\",this._box.style.height=l-s+\"px\"}}},Zn.prototype.mouseupWindow=function(e,n){var i=this;if(this._active&&0===e.button){var a=this._startPos,o=n;if(this.reset(),r.suppressClick(),a.x!==o.x||a.y!==o.y)return this._map.fire(new t.Event(\"boxzoomend\",{originalEvent:e})),{cameraAnimation:function(t){return t.fitScreenCoordinates(a,o,i._map.getBearing(),{linear:!0})}};this._fireEvent(\"boxzoomcancel\",e)}},Zn.prototype.keydown=function(t){this._active&&27===t.keyCode&&(this.reset(),this._fireEvent(\"boxzoomcancel\",t))},Zn.prototype.reset=function(){this._active=!1,this._container.classList.remove(\"mapboxgl-crosshair\"),this._box&&(r.remove(this._box),this._box=null),r.enableDrag(),delete this._startPos,delete this._lastPos},Zn.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,{originalEvent:r}))};var Wn=function(t){this.reset(),this.numTouches=t.numTouches};Wn.prototype.reset=function(){delete this.centroid,delete this.startTime,delete this.touches,this.aborted=!1},Wn.prototype.touchstart=function(e,r,n){(this.centroid||n.length>this.numTouches)&&(this.aborted=!0),this.aborted||(void 0===this.startTime&&(this.startTime=e.timeStamp),n.length===this.numTouches&&(this.centroid=function(e){for(var r=new t.Point(0,0),n=0,i=e;n<i.length;n+=1){var a=i[n];r._add(a)}return r.div(e.length)}(r),this.touches=Yn(n,r)))},Wn.prototype.touchmove=function(t,e,r){if(!this.aborted&&this.centroid){var n=Yn(r,e);for(var i in this.touches){var a=this.touches[i],o=n[i];(!o||o.dist(a)>30)&&(this.aborted=!0)}}},Wn.prototype.touchend=function(t,e,r){if((!this.centroid||t.timeStamp-this.startTime>500)&&(this.aborted=!0),0===r.length){var n=!this.aborted&&this.centroid;if(this.reset(),n)return n}};var Xn=function(t){this.singleTap=new Wn(t),this.numTaps=t.numTaps,this.reset()};Xn.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},Xn.prototype.touchstart=function(t,e,r){this.singleTap.touchstart(t,e,r)},Xn.prototype.touchmove=function(t,e,r){this.singleTap.touchmove(t,e,r)},Xn.prototype.touchend=function(t,e,r){var n=this.singleTap.touchend(t,e,r);if(n){var i=t.timeStamp-this.lastTime<500,a=!this.lastTap||this.lastTap.dist(n)<30;if(i&&a||this.reset(),this.count++,this.lastTime=t.timeStamp,this.lastTap=n,this.count===this.numTaps)return this.reset(),n}};var Jn=function(){this._zoomIn=new Xn({numTouches:1,numTaps:2}),this._zoomOut=new Xn({numTouches:2,numTaps:1}),this.reset()};Jn.prototype.reset=function(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()},Jn.prototype.touchstart=function(t,e,r){this._zoomIn.touchstart(t,e,r),this._zoomOut.touchstart(t,e,r)},Jn.prototype.touchmove=function(t,e,r){this._zoomIn.touchmove(t,e,r),this._zoomOut.touchmove(t,e,r)},Jn.prototype.touchend=function(t,e,r){var n=this,i=this._zoomIn.touchend(t,e,r),a=this._zoomOut.touchend(t,e,r);return i?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()+1,around:e.unproject(i)},{originalEvent:t})}}):a?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()-1,around:e.unproject(a)},{originalEvent:t})}}):void 0},Jn.prototype.touchcancel=function(){this.reset()},Jn.prototype.enable=function(){this._enabled=!0},Jn.prototype.disable=function(){this._enabled=!1,this.reset()},Jn.prototype.isEnabled=function(){return this._enabled},Jn.prototype.isActive=function(){return this._active};var Kn=function(t){this.reset(),this._clickTolerance=t.clickTolerance||1};Kn.prototype.reset=function(){this._active=!1,this._moved=!1,delete this._lastPoint,delete this._eventButton},Kn.prototype._correctButton=function(t,e){return!1},Kn.prototype._move=function(t,e){return{}},Kn.prototype.mousedown=function(t,e){if(!this._lastPoint){var n=r.mouseButton(t);this._correctButton(t,n)&&(this._lastPoint=e,this._eventButton=n)}},Kn.prototype.mousemoveWindow=function(t,e){var r=this._lastPoint;if(r&&(t.preventDefault(),this._moved||!(e.dist(r)<this._clickTolerance)))return this._moved=!0,this._lastPoint=e,this._move(r,e)},Kn.prototype.mouseupWindow=function(t){r.mouseButton(t)===this._eventButton&&(this._moved&&r.suppressClick(),this.reset())},Kn.prototype.enable=function(){this._enabled=!0},Kn.prototype.disable=function(){this._enabled=!1,this.reset()},Kn.prototype.isEnabled=function(){return this._enabled},Kn.prototype.isActive=function(){return this._active};var $n=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.mousedown=function(e,r){t.prototype.mousedown.call(this,e,r),this._lastPoint&&(this._active=!0)},e.prototype._correctButton=function(t,e){return 0===e&&!t.ctrlKey},e.prototype._move=function(t,e){return{around:e,panDelta:e.sub(t)}},e}(Kn),Qn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=.8*(e.x-t.x);if(r)return this._active=!0,{bearingDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Kn),ti=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=-.5*(e.y-t.y);if(r)return this._active=!0,{pitchDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Kn),ei=function(t){this._minTouches=1,this._clickTolerance=t.clickTolerance||1,this.reset()};ei.prototype.reset=function(){this._active=!1,this._touches={},this._sum=new t.Point(0,0)},ei.prototype.touchstart=function(t,e,r){return this._calculateTransform(t,e,r)},ei.prototype.touchmove=function(t,e,r){if(this._active)return t.preventDefault(),this._calculateTransform(t,e,r)},ei.prototype.touchend=function(t,e,r){this._calculateTransform(t,e,r),this._active&&r.length<this._minTouches&&this.reset()},ei.prototype.touchcancel=function(){this.reset()},ei.prototype._calculateTransform=function(e,r,n){n.length>0&&(this._active=!0);var i=Yn(n,r),a=new t.Point(0,0),o=new t.Point(0,0),s=0;for(var l in i){var u=i[l],c=this._touches[l];c&&(a._add(u),o._add(u.sub(c)),s++,i[l]=u)}if(this._touches=i,!(s<this._minTouches)&&o.mag()){var f=o.div(s);if(this._sum._add(f),!(this._sum.mag()<this._clickTolerance))return{around:a.div(s),panDelta:f}}},ei.prototype.enable=function(){this._enabled=!0},ei.prototype.disable=function(){this._enabled=!1,this.reset()},ei.prototype.isEnabled=function(){return this._enabled},ei.prototype.isActive=function(){return this._active};var ri=function(){this.reset()};function ni(t,e,r){for(var n=0;n<t.length;n++)if(t[n].identifier===r)return e[n]}ri.prototype.reset=function(){this._active=!1,delete this._firstTwoTouches},ri.prototype._start=function(t){},ri.prototype._move=function(t,e,r){return{}},ri.prototype.touchstart=function(t,e,r){this._firstTwoTouches||r.length<2||(this._firstTwoTouches=[r[0].identifier,r[1].identifier],this._start([e[0],e[1]]))},ri.prototype.touchmove=function(t,e,r){if(this._firstTwoTouches){t.preventDefault();var n=this._firstTwoTouches,i=n[0],a=n[1],o=ni(r,e,i),s=ni(r,e,a);if(o&&s){var l=this._aroundCenter?null:o.add(s).div(2);return this._move([o,s],l,t)}}},ri.prototype.touchend=function(t,e,n){if(this._firstTwoTouches){var i=this._firstTwoTouches,a=i[0],o=i[1],s=ni(n,e,a),l=ni(n,e,o);s&&l||(this._active&&r.suppressClick(),this.reset())}},ri.prototype.touchcancel=function(){this.reset()},ri.prototype.enable=function(t){this._enabled=!0,this._aroundCenter=!!t&&\"center\"===t.around},ri.prototype.disable=function(){this._enabled=!1,this.reset()},ri.prototype.isEnabled=function(){return this._enabled},ri.prototype.isActive=function(){return this._active};function ii(t,e){return Math.log(t/e)/Math.LN2}var ai=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._distance,delete this._startDistance},e.prototype._start=function(t){this._startDistance=this._distance=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._distance;if(this._distance=t[0].dist(t[1]),this._active||!(Math.abs(ii(this._distance,this._startDistance))<.1))return this._active=!0,{zoomDelta:ii(this._distance,r),pinchAround:e}},e}(ri);function oi(t,e){return 180*t.angleWith(e)/Math.PI}var si=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._minDiameter,delete this._startVector,delete this._vector},e.prototype._start=function(t){this._startVector=this._vector=t[0].sub(t[1]),this._minDiameter=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._vector;if(this._vector=t[0].sub(t[1]),this._active||!this._isBelowThreshold(this._vector))return this._active=!0,{bearingDelta:oi(this._vector,r),pinchAround:e}},e.prototype._isBelowThreshold=function(t){this._minDiameter=Math.min(this._minDiameter,t.mag());var e=25/(Math.PI*this._minDiameter)*360,r=oi(t,this._startVector);return Math.abs(r)<e},e}(ri);function li(t){return Math.abs(t.y)>Math.abs(t.x)}var ui=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},e.prototype._start=function(t){this._lastPoints=t,li(t[0].sub(t[1]))&&(this._valid=!1)},e.prototype._move=function(t,e,r){var n=t[0].sub(this._lastPoints[0]),i=t[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(n,i,r.timeStamp),this._valid)return this._lastPoints=t,this._active=!0,{pitchDelta:(n.y+i.y)/2*-.5}},e.prototype.gestureBeginsVertically=function(t,e,r){if(void 0!==this._valid)return this._valid;var n=t.mag()>=2,i=e.mag()>=2;if(n||i){if(!n||!i)return void 0===this._firstMove&&(this._firstMove=r),r-this._firstMove<100&&void 0;var a=t.y>0==e.y>0;return li(t)&&li(e)&&a}},e}(ri),ci={panStep:100,bearingStep:15,pitchStep:10},fi=function(){var t=ci;this._panStep=t.panStep,this._bearingStep=t.bearingStep,this._pitchStep=t.pitchStep};function hi(t){return t*(2-t)}fi.prototype.reset=function(){this._active=!1},fi.prototype.keydown=function(t){var e=this;if(!(t.altKey||t.ctrlKey||t.metaKey)){var r=0,n=0,i=0,a=0,o=0;switch(t.keyCode){case 61:case 107:case 171:case 187:r=1;break;case 189:case 109:case 173:r=-1;break;case 37:t.shiftKey?n=-1:(t.preventDefault(),a=-1);break;case 39:t.shiftKey?n=1:(t.preventDefault(),a=1);break;case 38:t.shiftKey?i=1:(t.preventDefault(),o=-1);break;case 40:t.shiftKey?i=-1:(t.preventDefault(),o=1);break;default:return}return{cameraAnimation:function(s){var l=s.getZoom();s.easeTo({duration:300,easeId:\"keyboardHandler\",easing:hi,zoom:r?Math.round(l)+r*(t.shiftKey?2:1):l,bearing:s.getBearing()+n*e._bearingStep,pitch:s.getPitch()+i*e._pitchStep,offset:[-a*e._panStep,-o*e._panStep],center:s.getCenter()},{originalEvent:t})}}}},fi.prototype.enable=function(){this._enabled=!0},fi.prototype.disable=function(){this._enabled=!1,this.reset()},fi.prototype.isEnabled=function(){return this._enabled},fi.prototype.isActive=function(){return this._active};var pi=4.000244140625,di=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._handler=r,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=.0022222222222222222,t.bindAll([\"_onWheel\",\"_onTimeout\",\"_onScrollFrame\",\"_onScrollFinished\"],this)};di.prototype.setZoomRate=function(t){this._defaultZoomRate=t},di.prototype.setWheelZoomRate=function(t){this._wheelZoomRate=t},di.prototype.isEnabled=function(){return!!this._enabled},di.prototype.isActive=function(){return!!this._active||void 0!==this._finishTimeout},di.prototype.isZooming=function(){return!!this._zooming},di.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&\"center\"===t.around)},di.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},di.prototype.wheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.window.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=t.browser.now(),i=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%pi==0?this._type=\"wheel\":0!==r&&Math.abs(r)<4?this._type=\"trackpad\":i>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(i*r)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this._active||this._start(e)),e.preventDefault()}},di.prototype._onTimeout=function(t){this._type=\"wheel\",this._delta-=this._lastValue,this._active||this._start(t)},di.prototype._start=function(e){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var n=r.mousePos(this._el,e);this._around=t.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(n)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},di.prototype.renderFrame=function(){return this._onScrollFrame()},di.prototype._onScrollFrame=function(){var e=this;if(this._frameId&&(this._frameId=null,this.isActive())){var r=this._map.transform;if(0!==this._delta){var n=\"wheel\"===this._type&&Math.abs(this._delta)>pi?this._wheelZoomRate:this._defaultZoomRate,i=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==i&&(i=1/i);var a=\"number\"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(a*i))),\"wheel\"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var o,s=\"number\"==typeof this._targetZoom?this._targetZoom:r.zoom,l=this._startZoom,u=this._easing,c=!1;if(\"wheel\"===this._type&&l&&u){var f=Math.min((t.browser.now()-this._lastWheelEventTime)/200,1),h=u(f);o=t.number(l,s,h),f<1?this._frameId||(this._frameId=!0):c=!0}else o=s,c=!0;return this._active=!0,c&&(this._active=!1,this._finishTimeout=setTimeout((function(){e._zooming=!1,e._handler._triggerRenderFrame(),delete e._targetZoom,delete e._finishTimeout}),200)),{noInertia:!0,needsRenderFrame:!c,zoomDelta:o-r.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},di.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,i=(t.browser.now()-n.start)/n.duration,a=n.easing(i+.01)-n.easing(i),o=.27/Math.sqrt(a*a+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=t.bezier(o,s,.25,1)}return this._prevEase={start:t.browser.now(),duration:e,easing:r},r},di.prototype.reset=function(){this._active=!1};var vi=function(t,e){this._clickZoom=t,this._tapZoom=e};vi.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},vi.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},vi.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},vi.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var gi=function(){this.reset()};gi.prototype.reset=function(){this._active=!1},gi.prototype.dblclick=function(t,e){return t.preventDefault(),{cameraAnimation:function(r){r.easeTo({duration:300,zoom:r.getZoom()+(t.shiftKey?-1:1),around:r.unproject(e)},{originalEvent:t})}}},gi.prototype.enable=function(){this._enabled=!0},gi.prototype.disable=function(){this._enabled=!1,this.reset()},gi.prototype.isEnabled=function(){return this._enabled},gi.prototype.isActive=function(){return this._active};var yi=function(){this._tap=new Xn({numTouches:1,numTaps:1}),this.reset()};yi.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},yi.prototype.touchstart=function(t,e,r){this._swipePoint||(this._tapTime&&t.timeStamp-this._tapTime>500&&this.reset(),this._tapTime?r.length>0&&(this._swipePoint=e[0],this._swipeTouch=r[0].identifier):this._tap.touchstart(t,e,r))},yi.prototype.touchmove=function(t,e,r){if(this._tapTime){if(this._swipePoint){if(r[0].identifier!==this._swipeTouch)return;var n=e[0],i=n.y-this._swipePoint.y;return this._swipePoint=n,t.preventDefault(),this._active=!0,{zoomDelta:i/128}}}else this._tap.touchmove(t,e,r)},yi.prototype.touchend=function(t,e,r){this._tapTime?this._swipePoint&&0===r.length&&this.reset():this._tap.touchend(t,e,r)&&(this._tapTime=t.timeStamp)},yi.prototype.touchcancel=function(){this.reset()},yi.prototype.enable=function(){this._enabled=!0},yi.prototype.disable=function(){this._enabled=!1,this.reset()},yi.prototype.isEnabled=function(){return this._enabled},yi.prototype.isActive=function(){return this._active};var mi=function(t,e,r){this._el=t,this._mousePan=e,this._touchPan=r};mi.prototype.enable=function(t){this._inertiaOptions=t||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add(\"mapboxgl-touch-drag-pan\")},mi.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove(\"mapboxgl-touch-drag-pan\")},mi.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},mi.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var xi=function(t,e,r){this._pitchWithRotate=t.pitchWithRotate,this._mouseRotate=e,this._mousePitch=r};xi.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},xi.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},xi.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},xi.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var bi=function(t,e,r,n){this._el=t,this._touchZoom=e,this._touchRotate=r,this._tapDragZoom=n,this._rotationDisabled=!1,this._enabled=!0};bi.prototype.enable=function(t){this._touchZoom.enable(t),this._rotationDisabled||this._touchRotate.enable(t),this._tapDragZoom.enable(),this._el.classList.add(\"mapboxgl-touch-zoom-rotate\")},bi.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove(\"mapboxgl-touch-zoom-rotate\")},bi.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},bi.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},bi.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},bi.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var _i=function(t){return t.zoom||t.drag||t.pitch||t.rotate},wi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(t.Event);function Ti(t){return t.panDelta&&t.panDelta.mag()||t.zoomDelta||t.bearingDelta||t.pitchDelta}var ki=function(e,n){this._map=e,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new Bn(e),this._bearingSnap=n.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(n),t.bindAll([\"handleEvent\",\"handleWindowEvent\"],this);var i=this._el;this._listeners=[[i,\"touchstart\",{passive:!1}],[i,\"touchmove\",{passive:!1}],[i,\"touchend\",void 0],[i,\"touchcancel\",void 0],[i,\"mousedown\",void 0],[i,\"mousemove\",void 0],[i,\"mouseup\",void 0],[t.window.document,\"mousemove\",{capture:!0}],[t.window.document,\"mouseup\",void 0],[i,\"mouseover\",void 0],[i,\"mouseout\",void 0],[i,\"dblclick\",void 0],[i,\"click\",void 0],[i,\"keydown\",{capture:!1}],[i,\"keyup\",void 0],[i,\"wheel\",{passive:!1}],[i,\"contextmenu\",void 0],[t.window,\"blur\",void 0]];for(var a=0,o=this._listeners;a<o.length;a+=1){var s=o[a],l=s[0],u=s[1],c=s[2];r.addEventListener(l,u,l===t.window.document?this.handleWindowEvent:this.handleEvent,c)}};ki.prototype.destroy=function(){for(var e=0,n=this._listeners;e<n.length;e+=1){var i=n[e],a=i[0],o=i[1],s=i[2];r.removeEventListener(a,o,a===t.window.document?this.handleWindowEvent:this.handleEvent,s)}},ki.prototype._addDefaultHandlers=function(t){var e=this._map,r=e.getCanvasContainer();this._add(\"mapEvent\",new qn(e,t));var n=e.boxZoom=new Zn(e,t);this._add(\"boxZoom\",n);var i=new Jn,a=new gi;e.doubleClickZoom=new vi(a,i),this._add(\"tapZoom\",i),this._add(\"clickZoom\",a);var o=new yi;this._add(\"tapDragZoom\",o);var s=e.touchPitch=new ui;this._add(\"touchPitch\",s);var l=new Qn(t),u=new ti(t);e.dragRotate=new xi(t,l,u),this._add(\"mouseRotate\",l,[\"mousePitch\"]),this._add(\"mousePitch\",u,[\"mouseRotate\"]);var c=new $n(t),f=new ei(t);e.dragPan=new mi(r,c,f),this._add(\"mousePan\",c),this._add(\"touchPan\",f,[\"touchZoom\",\"touchRotate\"]);var h=new si,p=new ai;e.touchZoomRotate=new bi(r,p,h,o),this._add(\"touchRotate\",h,[\"touchPan\",\"touchZoom\"]),this._add(\"touchZoom\",p,[\"touchPan\",\"touchRotate\"]);var d=e.scrollZoom=new di(e,this);this._add(\"scrollZoom\",d,[\"mousePan\"]);var v=e.keyboard=new fi;this._add(\"keyboard\",v),this._add(\"blockableMapEvent\",new Gn(e));for(var g=0,y=[\"boxZoom\",\"doubleClickZoom\",\"tapDragZoom\",\"touchPitch\",\"dragRotate\",\"dragPan\",\"touchZoomRotate\",\"scrollZoom\",\"keyboard\"];g<y.length;g+=1){var m=y[g];t.interactive&&t[m]&&e[m].enable(t[m])}},ki.prototype._add=function(t,e,r){this._handlers.push({handlerName:t,handler:e,allowed:r}),this._handlersById[t]=e},ki.prototype.stop=function(){if(!this._updatingCamera){for(var t=0,e=this._handlers;t<e.length;t+=1)e[t].handler.reset();this._inertia.clear(),this._fireEvents({},{}),this._changes=[]}},ki.prototype.isActive=function(){for(var t=0,e=this._handlers;t<e.length;t+=1)if(e[t].handler.isActive())return!0;return!1},ki.prototype.isZooming=function(){return!!this._eventsInProgress.zoom||this._map.scrollZoom.isZooming()},ki.prototype.isRotating=function(){return!!this._eventsInProgress.rotate},ki.prototype.isMoving=function(){return Boolean(_i(this._eventsInProgress))||this.isZooming()},ki.prototype._blockedByActive=function(t,e,r){for(var n in t)if(n!==r&&(!e||e.indexOf(n)<0))return!0;return!1},ki.prototype.handleWindowEvent=function(t){this.handleEvent(t,t.type+\"Window\")},ki.prototype._getMapTouches=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=i.target;this._el.contains(a)&&e.push(i)}return e},ki.prototype.handleEvent=function(t,e){if(\"blur\"!==t.type){this._updatingCamera=!0;for(var n=\"renderFrame\"===t.type?void 0:t,i={needsRenderFrame:!1},a={},o={},s=t.touches?this._getMapTouches(t.touches):void 0,l=s?r.touchPos(this._el,s):r.mousePos(this._el,t),u=0,c=this._handlers;u<c.length;u+=1){var f=c[u],h=f.handlerName,p=f.handler,d=f.allowed;if(p.isEnabled()){var v=void 0;this._blockedByActive(o,d,h)?p.reset():p[e||t.type]&&(v=p[e||t.type](t,l,s),this.mergeHandlerResult(i,a,v,h,n),v&&v.needsRenderFrame&&this._triggerRenderFrame()),(v||p.isActive())&&(o[h]=p)}}var g={};for(var y in this._previousActiveHandlers)o[y]||(g[y]=n);this._previousActiveHandlers=o,(Object.keys(g).length||Ti(i))&&(this._changes.push([i,a,g]),this._triggerRenderFrame()),(Object.keys(o).length||Ti(i))&&this._map._stop(!0),this._updatingCamera=!1;var m=i.cameraAnimation;m&&(this._inertia.clear(),this._fireEvents({},{}),this._changes=[],m(this._map))}else this.stop()},ki.prototype.mergeHandlerResult=function(e,r,n,i,a){if(n){t.extend(e,n);var o={handlerName:i,originalEvent:n.originalEvent||a};void 0!==n.zoomDelta&&(r.zoom=o),void 0!==n.panDelta&&(r.drag=o),void 0!==n.pitchDelta&&(r.pitch=o),void 0!==n.bearingDelta&&(r.rotate=o)}},ki.prototype._applyChanges=function(){for(var e={},r={},n={},i=0,a=this._changes;i<a.length;i+=1){var o=a[i],s=o[0],l=o[1],u=o[2];s.panDelta&&(e.panDelta=(e.panDelta||new t.Point(0,0))._add(s.panDelta)),s.zoomDelta&&(e.zoomDelta=(e.zoomDelta||0)+s.zoomDelta),s.bearingDelta&&(e.bearingDelta=(e.bearingDelta||0)+s.bearingDelta),s.pitchDelta&&(e.pitchDelta=(e.pitchDelta||0)+s.pitchDelta),void 0!==s.around&&(e.around=s.around),void 0!==s.pinchAround&&(e.pinchAround=s.pinchAround),s.noInertia&&(e.noInertia=s.noInertia),t.extend(r,l),t.extend(n,u)}this._updateMapTransform(e,r,n),this._changes=[]},ki.prototype._updateMapTransform=function(t,e,r){var n=this._map,i=n.transform;if(!Ti(t))return this._fireEvents(e,r);var a=t.panDelta,o=t.zoomDelta,s=t.bearingDelta,l=t.pitchDelta,u=t.around,c=t.pinchAround;void 0!==c&&(u=c),n._stop(!0),u=u||n.transform.centerPoint;var f=i.pointLocation(a?u.sub(a):u);s&&(i.bearing+=s),l&&(i.pitch+=l),o&&(i.zoom+=o),i.setLocationAtPoint(f,u),this._map._update(),t.noInertia||this._inertia.record(t),this._fireEvents(e,r)},ki.prototype._fireEvents=function(e,r){var n=this,i=_i(this._eventsInProgress),a=_i(e),o={};for(var s in e){var l=e[s].originalEvent;this._eventsInProgress[s]||(o[s+\"start\"]=l),this._eventsInProgress[s]=e[s]}for(var u in!i&&a&&this._fireEvent(\"movestart\",a.originalEvent),o)this._fireEvent(u,o[u]);for(var c in e.rotate&&(this._bearingChanged=!0),a&&this._fireEvent(\"move\",a.originalEvent),e){var f=e[c].originalEvent;this._fireEvent(c,f)}var h,p={};for(var d in this._eventsInProgress){var v=this._eventsInProgress[d],g=v.handlerName,y=v.originalEvent;this._handlersById[g].isActive()||(delete this._eventsInProgress[d],h=r[g]||y,p[d+\"end\"]=h)}for(var m in p)this._fireEvent(m,p[m]);var x=_i(this._eventsInProgress);if((i||a)&&!x){this._updatingCamera=!0;var b=this._inertia._onMoveEnd(this._map.dragPan._inertiaOptions),_=function(t){return 0!==t&&-n._bearingSnap<t&&t<n._bearingSnap};b?(_(b.bearing||this._map.getBearing())&&(b.bearing=0),this._map.easeTo(b,{originalEvent:h})):(this._map.fire(new t.Event(\"moveend\",{originalEvent:h})),_(this._map.getBearing())&&this._map.resetNorth()),this._bearingChanged=!1,this._updatingCamera=!1}},ki.prototype._fireEvent=function(e,r){this._map.fire(new t.Event(e,r?{originalEvent:r}:{}))},ki.prototype._triggerRenderFrame=function(){var t=this;void 0===this._frameId&&(this._frameId=this._map._requestRenderFrame((function(e){delete t._frameId,t.handleEvent(new wi(\"renderFrame\",{timeStamp:e})),t._applyChanges()})))};var Ai=function(e){function r(r,n){e.call(this),this._moving=!1,this._zooming=!1,this.transform=r,this._bearingSnap=n.bearingSnap,t.bindAll([\"_renderFrameCallback\"],this)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getCenter=function(){return new t.LngLat(this.transform.center.lng,this.transform.center.lat)},r.prototype.setCenter=function(t,e){return this.jumpTo({center:t},e)},r.prototype.panBy=function(e,r,n){return e=t.Point.convert(e).mult(-1),this.panTo(this.transform.center,t.extend({offset:e},r),n)},r.prototype.panTo=function(e,r,n){return this.easeTo(t.extend({center:e},r),n)},r.prototype.getZoom=function(){return this.transform.zoom},r.prototype.setZoom=function(t,e){return this.jumpTo({zoom:t},e),this},r.prototype.zoomTo=function(e,r,n){return this.easeTo(t.extend({zoom:e},r),n)},r.prototype.zoomIn=function(t,e){return this.zoomTo(this.getZoom()+1,t,e),this},r.prototype.zoomOut=function(t,e){return this.zoomTo(this.getZoom()-1,t,e),this},r.prototype.getBearing=function(){return this.transform.bearing},r.prototype.setBearing=function(t,e){return this.jumpTo({bearing:t},e),this},r.prototype.getPadding=function(){return this.transform.padding},r.prototype.setPadding=function(t,e){return this.jumpTo({padding:t},e),this},r.prototype.rotateTo=function(e,r,n){return this.easeTo(t.extend({bearing:e},r),n)},r.prototype.resetNorth=function(e,r){return this.rotateTo(0,t.extend({duration:1e3},e),r),this},r.prototype.resetNorthPitch=function(e,r){return this.easeTo(t.extend({bearing:0,pitch:0,duration:1e3},e),r),this},r.prototype.snapToNorth=function(t,e){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(t,e):this},r.prototype.getPitch=function(){return this.transform.pitch},r.prototype.setPitch=function(t,e){return this.jumpTo({pitch:t},e),this},r.prototype.cameraForBounds=function(e,r){return e=t.LngLatBounds.convert(e),this._cameraForBoxAndBearing(e.getNorthWest(),e.getSouthEast(),0,r)},r.prototype._cameraForBoxAndBearing=function(e,r,n,i){var a={top:0,bottom:0,right:0,left:0};if(\"number\"==typeof(i=t.extend({padding:a,offset:[0,0],maxZoom:this.transform.maxZoom},i)).padding){var o=i.padding;i.padding={top:o,bottom:o,right:o,left:o}}i.padding=t.extend(a,i.padding);var s=this.transform,l=s.padding,u=s.project(t.LngLat.convert(e)),c=s.project(t.LngLat.convert(r)),f=u.rotate(-n*Math.PI/180),h=c.rotate(-n*Math.PI/180),p=new t.Point(Math.max(f.x,h.x),Math.max(f.y,h.y)),d=new t.Point(Math.min(f.x,h.x),Math.min(f.y,h.y)),v=p.sub(d),g=(s.width-(l.left+l.right+i.padding.left+i.padding.right))/v.x,y=(s.height-(l.top+l.bottom+i.padding.top+i.padding.bottom))/v.y;if(!(y<0||g<0)){var m=Math.min(s.scaleZoom(s.scale*Math.min(g,y)),i.maxZoom),x=t.Point.convert(i.offset),b=(i.padding.left-i.padding.right)/2,_=(i.padding.top-i.padding.bottom)/2,w=new t.Point(x.x+b,x.y+_).mult(s.scale/s.zoomScale(m));return{center:s.unproject(u.add(c).div(2).sub(w)),zoom:m,bearing:n}}t.warnOnce(\"Map cannot fit within canvas with the given bounds, padding, and/or offset.\")},r.prototype.fitBounds=function(t,e,r){return this._fitInternal(this.cameraForBounds(t,e),e,r)},r.prototype.fitScreenCoordinates=function(e,r,n,i,a){return this._fitInternal(this._cameraForBoxAndBearing(this.transform.pointLocation(t.Point.convert(e)),this.transform.pointLocation(t.Point.convert(r)),n,i),i,a)},r.prototype._fitInternal=function(e,r,n){return e?(delete(r=t.extend(e,r)).padding,r.linear?this.easeTo(r,n):this.flyTo(r,n)):this},r.prototype.jumpTo=function(e,r){this.stop();var n=this.transform,i=!1,a=!1,o=!1;return\"zoom\"in e&&n.zoom!==+e.zoom&&(i=!0,n.zoom=+e.zoom),void 0!==e.center&&(n.center=t.LngLat.convert(e.center)),\"bearing\"in e&&n.bearing!==+e.bearing&&(a=!0,n.bearing=+e.bearing),\"pitch\"in e&&n.pitch!==+e.pitch&&(o=!0,n.pitch=+e.pitch),null==e.padding||n.isPaddingEqual(e.padding)||(n.padding=e.padding),this.fire(new t.Event(\"movestart\",r)).fire(new t.Event(\"move\",r)),i&&this.fire(new t.Event(\"zoomstart\",r)).fire(new t.Event(\"zoom\",r)).fire(new t.Event(\"zoomend\",r)),a&&this.fire(new t.Event(\"rotatestart\",r)).fire(new t.Event(\"rotate\",r)).fire(new t.Event(\"rotateend\",r)),o&&this.fire(new t.Event(\"pitchstart\",r)).fire(new t.Event(\"pitch\",r)).fire(new t.Event(\"pitchend\",r)),this.fire(new t.Event(\"moveend\",r))},r.prototype.easeTo=function(e,r){var n=this;this._stop(!1,e.easeId),(!1===(e=t.extend({offset:[0,0],duration:500,easing:t.ease},e)).animate||!e.essential&&t.browser.prefersReducedMotion)&&(e.duration=0);var i=this.transform,a=this.getZoom(),o=this.getBearing(),s=this.getPitch(),l=this.getPadding(),u=\"zoom\"in e?+e.zoom:a,c=\"bearing\"in e?this._normalizeBearing(e.bearing,o):o,f=\"pitch\"in e?+e.pitch:s,h=\"padding\"in e?e.padding:i.padding,p=t.Point.convert(e.offset),d=i.centerPoint.add(p),v=i.pointLocation(d),g=t.LngLat.convert(e.center||v);this._normalizeCenter(g);var y,m,x=i.project(v),b=i.project(g).sub(x),_=i.zoomScale(u-a);e.around&&(y=t.LngLat.convert(e.around),m=i.locationPoint(y));var w={moving:this._moving,zooming:this._zooming,rotating:this._rotating,pitching:this._pitching};return this._zooming=this._zooming||u!==a,this._rotating=this._rotating||o!==c,this._pitching=this._pitching||f!==s,this._padding=!i.isPaddingEqual(h),this._easeId=e.easeId,this._prepareEase(r,e.noMoveStart,w),clearTimeout(this._easeEndTimeoutID),this._ease((function(e){if(n._zooming&&(i.zoom=t.number(a,u,e)),n._rotating&&(i.bearing=t.number(o,c,e)),n._pitching&&(i.pitch=t.number(s,f,e)),n._padding&&(i.interpolatePadding(l,h,e),d=i.centerPoint.add(p)),y)i.setLocationAtPoint(y,m);else{var v=i.zoomScale(i.zoom-a),g=u>a?Math.min(2,_):Math.max(.5,_),w=Math.pow(g,1-e),T=i.unproject(x.add(b.mult(e*w)).mult(v));i.setLocationAtPoint(i.renderWorldCopies?T.wrap():T,d)}n._fireMoveEvents(r)}),(function(t){n._afterEase(r,t)}),e),this},r.prototype._prepareEase=function(e,r,n){void 0===n&&(n={}),this._moving=!0,r||n.moving||this.fire(new t.Event(\"movestart\",e)),this._zooming&&!n.zooming&&this.fire(new t.Event(\"zoomstart\",e)),this._rotating&&!n.rotating&&this.fire(new t.Event(\"rotatestart\",e)),this._pitching&&!n.pitching&&this.fire(new t.Event(\"pitchstart\",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event(\"move\",e)),this._zooming&&this.fire(new t.Event(\"zoom\",e)),this._rotating&&this.fire(new t.Event(\"rotate\",e)),this._pitching&&this.fire(new t.Event(\"pitch\",e))},r.prototype._afterEase=function(e,r){if(!this._easeId||!r||this._easeId!==r){delete this._easeId;var n=this._zooming,i=this._rotating,a=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,n&&this.fire(new t.Event(\"zoomend\",e)),i&&this.fire(new t.Event(\"rotateend\",e)),a&&this.fire(new t.Event(\"pitchend\",e)),this.fire(new t.Event(\"moveend\",e))}},r.prototype.flyTo=function(e,r){var n=this;if(!e.essential&&t.browser.prefersReducedMotion){var i=t.pick(e,[\"center\",\"zoom\",\"bearing\",\"pitch\",\"around\"]);return this.jumpTo(i,r)}this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var a=this.transform,o=this.getZoom(),s=this.getBearing(),l=this.getPitch(),u=this.getPadding(),c=\"zoom\"in e?t.clamp(+e.zoom,a.minZoom,a.maxZoom):o,f=\"bearing\"in e?this._normalizeBearing(e.bearing,s):s,h=\"pitch\"in e?+e.pitch:l,p=\"padding\"in e?e.padding:a.padding,d=a.zoomScale(c-o),v=t.Point.convert(e.offset),g=a.centerPoint.add(v),y=a.pointLocation(g),m=t.LngLat.convert(e.center||y);this._normalizeCenter(m);var x=a.project(y),b=a.project(m).sub(x),_=e.curve,w=Math.max(a.width,a.height),T=w/d,k=b.mag();if(\"minZoom\"in e){var A=t.clamp(Math.min(e.minZoom,o,c),a.minZoom,a.maxZoom),M=w/a.zoomScale(A-o);_=Math.sqrt(M/k*2)}var S=_*_;function E(t){var e=(T*T-w*w+(t?-1:1)*S*S*k*k)/(2*(t?T:w)*S*k);return Math.log(Math.sqrt(e*e+1)-e)}function L(t){return(Math.exp(t)-Math.exp(-t))/2}function C(t){return(Math.exp(t)+Math.exp(-t))/2}var P=E(0),O=function(t){return C(P)/C(P+_*t)},I=function(t){return w*((C(P)*(L(e=P+_*t)/C(e))-L(P))/S)/k;var e},D=(E(1)-P)/_;if(Math.abs(k)<1e-6||!isFinite(D)){if(Math.abs(w-T)<1e-6)return this.easeTo(e,r);var z=T<w?-1:1;D=Math.abs(Math.log(T/w))/_,I=function(){return 0},O=function(t){return Math.exp(z*_*t)}}if(\"duration\"in e)e.duration=+e.duration;else{var R=\"screenSpeed\"in e?+e.screenSpeed/_:+e.speed;e.duration=1e3*D/R}return e.maxDuration&&e.duration>e.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=s!==f,this._pitching=h!==l,this._padding=!a.isPaddingEqual(p),this._prepareEase(r,!1),this._ease((function(e){var i=e*D,d=1/O(i);a.zoom=1===e?c:o+a.scaleZoom(d),n._rotating&&(a.bearing=t.number(s,f,e)),n._pitching&&(a.pitch=t.number(l,h,e)),n._padding&&(a.interpolatePadding(u,p,e),g=a.centerPoint.add(v));var y=1===e?m:a.unproject(x.add(b.mult(I(i))).mult(d));a.setLocationAtPoint(a.renderWorldCopies?y.wrap():y,g),n._fireMoveEvents(r)}),(function(){return n._afterEase(r)}),e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){return this._stop()},r.prototype._stop=function(t,e){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var r=this._onEaseEnd;delete this._onEaseEnd,r.call(this,e)}if(!t){var n=this.handlers;n&&n.stop()}return this},r.prototype._ease=function(e,r,n){!1===n.animate||0===n.duration?(e(1),r()):(this._easeStart=t.browser.now(),this._easeOptions=n,this._onEaseFrame=e,this._onEaseEnd=r,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var e=Math.min((t.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(e)),e<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)<n&&(e-=360),Math.abs(e+360-r)<n&&(e+=360),e},r.prototype._normalizeCenter=function(t){var e=this.transform;if(e.renderWorldCopies&&!e.lngRange){var r=t.lng-e.center.lng;t.lng+=r>180?-360:r<-180?360:0}},r}(t.Evented),Mi=function(e){void 0===e&&(e={}),this.options=e,t.bindAll([\"_updateEditLink\",\"_updateData\",\"_updateCompact\"],this)};Mi.prototype.getDefaultPosition=function(){return\"bottom-right\"},Mi.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-attrib\"),this._innerContainer=r.create(\"div\",\"mapboxgl-ctrl-attrib-inner\",this._container),e&&this._container.classList.add(\"mapboxgl-compact\"),this._updateAttributions(),this._updateEditLink(),this._map.on(\"styledata\",this._updateData),this._map.on(\"sourcedata\",this._updateData),this._map.on(\"moveend\",this._updateEditLink),void 0===e&&(this._map.on(\"resize\",this._updateCompact),this._updateCompact()),this._container},Mi.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"styledata\",this._updateData),this._map.off(\"sourcedata\",this._updateData),this._map.off(\"moveend\",this._updateEditLink),this._map.off(\"resize\",this._updateCompact),this._map=void 0,this._attribHTML=void 0},Mi.prototype._updateEditLink=function(){var e=this._editLink;e||(e=this._editLink=this._container.querySelector(\".mapbox-improve-map\"));var r=[{key:\"owner\",value:this.styleOwner},{key:\"id\",value:this.styleId},{key:\"access_token\",value:this._map._requestManager._customAccessToken||t.config.ACCESS_TOKEN}];if(e){var n=r.reduce((function(t,e,n){return e.value&&(t+=e.key+\"=\"+e.value+(n<r.length-1?\"&\":\"\")),t}),\"?\");e.href=t.config.FEEDBACK_URL+\"/\"+n+(this._map._hash?this._map._hash.getHashString(!0):\"\"),e.rel=\"noopener nofollow\"}},Mi.prototype._updateData=function(t){!t||\"metadata\"!==t.sourceDataType&&\"style\"!==t.dataType||(this._updateAttributions(),this._updateEditLink())},Mi.prototype._updateAttributions=function(){if(this._map.style){var t=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?t=t.concat(this.options.customAttribution.map((function(t){return\"string\"!=typeof t?\"\":t}))):\"string\"==typeof this.options.customAttribution&&t.push(this.options.customAttribution)),this._map.style.stylesheet){var e=this._map.style.stylesheet;this.styleOwner=e.owner,this.styleId=e.id}var r=this._map.style.sourceCaches;for(var n in r){var i=r[n];if(i.used){var a=i.getSource();a.attribution&&t.indexOf(a.attribution)<0&&t.push(a.attribution)}}t.sort((function(t,e){return t.length-e.length}));var o=(t=t.filter((function(e,r){for(var n=r+1;n<t.length;n++)if(t[n].indexOf(e)>=0)return!1;return!0}))).join(\" | \");o!==this._attribHTML&&(this._attribHTML=o,t.length?(this._innerContainer.innerHTML=o,this._container.classList.remove(\"mapboxgl-attrib-empty\")):this._container.classList.add(\"mapboxgl-attrib-empty\"),this._editLink=null)}},Mi.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add(\"mapboxgl-compact\"):this._container.classList.remove(\"mapboxgl-compact\")};var Si=function(){t.bindAll([\"_updateLogo\"],this),t.bindAll([\"_updateCompact\"],this)};Si.prototype.onAdd=function(t){this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl\");var e=r.create(\"a\",\"mapboxgl-ctrl-logo\");return e.target=\"_blank\",e.rel=\"noopener nofollow\",e.href=\"https://www.mapbox.com/\",e.setAttribute(\"aria-label\",this._map._getUIString(\"LogoControl.Title\")),e.setAttribute(\"rel\",\"noopener nofollow\"),this._container.appendChild(e),this._container.style.display=\"none\",this._map.on(\"sourcedata\",this._updateLogo),this._updateLogo(),this._map.on(\"resize\",this._updateCompact),this._updateCompact(),this._container},Si.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"sourcedata\",this._updateLogo),this._map.off(\"resize\",this._updateCompact)},Si.prototype.getDefaultPosition=function(){return\"bottom-left\"},Si.prototype._updateLogo=function(t){t&&\"metadata\"!==t.sourceDataType||(this._container.style.display=this._logoRequired()?\"block\":\"none\")},Si.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t)if(t[e].getSource().mapbox_logo)return!0;return!1}},Si.prototype._updateCompact=function(){var t=this._container.children;if(t.length){var e=t[0];this._map.getCanvasContainer().offsetWidth<250?e.classList.add(\"mapboxgl-compact\"):e.classList.remove(\"mapboxgl-compact\")}};var Ei=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};Ei.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},Ei.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;r<n.length;r+=1){var i=n[r];if(i.id===t)return void(i.cancelled=!0)}},Ei.prototype.run=function(t){void 0===t&&(t=0);var e=this._currentlyRunning=this._queue;this._queue=[];for(var r=0,n=e;r<n.length;r+=1){var i=n[r];if(!i.cancelled&&(i.callback(t),this._cleared))break}this._cleared=!1,this._currentlyRunning=!1},Ei.prototype.clear=function(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]};var Li={\"FullscreenControl.Enter\":\"Enter fullscreen\",\"FullscreenControl.Exit\":\"Exit fullscreen\",\"GeolocateControl.FindMyLocation\":\"Find my location\",\"GeolocateControl.LocationNotAvailable\":\"Location not available\",\"LogoControl.Title\":\"Mapbox logo\",\"NavigationControl.ResetBearing\":\"Reset bearing to north\",\"NavigationControl.ZoomIn\":\"Zoom in\",\"NavigationControl.ZoomOut\":\"Zoom out\",\"ScaleControl.Feet\":\"ft\",\"ScaleControl.Meters\":\"m\",\"ScaleControl.Kilometers\":\"km\",\"ScaleControl.Miles\":\"mi\",\"ScaleControl.NauticalMiles\":\"nm\"},Ci=t.window.HTMLImageElement,Pi=t.window.HTMLElement,Oi=t.window.ImageBitmap,Ii=60,Di={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:-2,maxZoom:22,minPitch:0,maxPitch:Ii,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,touchPitch:!0,bearingSnap:7,clickTolerance:3,pitchWithRotate:!0,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,renderWorldCopies:!0,refreshExpiredTiles:!0,maxTileCacheSize:null,localIdeographFontFamily:\"sans-serif\",transformRequest:null,accessToken:null,fadeDuration:300,crossSourceCollisions:!0},zi=function(n){function i(e){var r=this;if(null!=(e=t.extend({},Di,e)).minZoom&&null!=e.maxZoom&&e.minZoom>e.maxZoom)throw new Error(\"maxZoom must be greater than or equal to minZoom\");if(null!=e.minPitch&&null!=e.maxPitch&&e.minPitch>e.maxPitch)throw new Error(\"maxPitch must be greater than or equal to minPitch\");if(null!=e.minPitch&&e.minPitch<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(null!=e.maxPitch&&e.maxPitch>Ii)throw new Error(\"maxPitch must be less than or equal to 60\");var i=new Cn(e.minZoom,e.maxZoom,e.minPitch,e.maxPitch,e.renderWorldCopies);if(n.call(this,i,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._antialias=e.antialias,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossSourceCollisions=e.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new Ei,this._controls=[],this._mapId=t.uniqueId(),this._locale=t.extend({},Li,e.locale),this._requestManager=new t.RequestManager(e.transformRequest,e.accessToken),\"string\"==typeof e.container){if(this._container=t.window.document.getElementById(e.container),!this._container)throw new Error(\"Container '\"+e.container+\"' not found.\")}else{if(!(e.container instanceof Pi))throw new Error(\"Invalid type: 'container' must be a String or HTMLElement.\");this._container=e.container}if(e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll([\"_onWindowOnline\",\"_onWindowResize\",\"_contextLost\",\"_contextRestored\"],this),this._setupContainer(),this._setupPainter(),void 0===this.painter)throw new Error(\"Failed to initialize WebGL.\");this.on(\"move\",(function(){return r._update(!1)})),this.on(\"moveend\",(function(){return r._update(!1)})),this.on(\"zoom\",(function(){return r._update(!0)})),void 0!==t.window&&(t.window.addEventListener(\"online\",this._onWindowOnline,!1),t.window.addEventListener(\"resize\",this._onWindowResize,!1)),this.handlers=new ki(this,e);var a=\"string\"==typeof e.hash&&e.hash||void 0;this._hash=e.hash&&new On(a).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),e.bounds&&(this.resize(),this.fitBounds(e.bounds,t.extend({},e.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=e.localIdeographFontFamily,e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new Mi({customAttribution:e.customAttribution})),this.addControl(new Si,e.logoPosition),this.on(\"style.load\",(function(){r.transform.unmodified&&r.jumpTo(r.style.stylesheet)})),this.on(\"data\",(function(e){r._update(\"style\"===e.dataType),r.fire(new t.Event(e.dataType+\"data\",e))})),this.on(\"dataloading\",(function(e){r.fire(new t.Event(e.dataType+\"dataloading\",e))}))}n&&(i.__proto__=n),i.prototype=Object.create(n&&n.prototype),i.prototype.constructor=i;var a={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return i.prototype._getMapId=function(){return this._mapId},i.prototype.addControl=function(e,r){if(void 0===r&&e.getDefaultPosition&&(r=e.getDefaultPosition()),void 0===r&&(r=\"top-right\"),!e||!e.onAdd)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.\")));var n=e.onAdd(this);this._controls.push(e);var i=this._controlPositions[r];return-1!==r.indexOf(\"bottom\")?i.insertBefore(n,i.firstChild):i.appendChild(n),this},i.prototype.removeControl=function(e){if(!e||!e.onRemove)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.\")));var r=this._controls.indexOf(e);return r>-1&&this._controls.splice(r,1),e.onRemove(this),this},i.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],i=r[1];this._resizeCanvas(n,i),this.transform.resize(n,i),this.painter.resize(n,i);var a=!this._moving;return a&&(this.stop(),this.fire(new t.Event(\"movestart\",e)).fire(new t.Event(\"move\",e))),this.fire(new t.Event(\"resize\",e)),a&&this.fire(new t.Event(\"moveend\",e)),this},i.prototype.getBounds=function(){return this.transform.getBounds()},i.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},i.prototype.setMaxBounds=function(e){return this.transform.setMaxBounds(t.LngLatBounds.convert(e)),this._update()},i.prototype.setMinZoom=function(t){if((t=null==t?-2:t)>=-2&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()<t&&this.setZoom(t),this;throw new Error(\"minZoom must be between -2 and the current maxZoom, inclusive\")},i.prototype.getMinZoom=function(){return this.transform.minZoom},i.prototype.setMaxZoom=function(t){if((t=null==t?22:t)>=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be greater than the current minZoom\")},i.prototype.getMaxZoom=function(){return this.transform.maxZoom},i.prototype.setMinPitch=function(t){if((t=null==t?0:t)<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(t>=0&&t<=this.transform.maxPitch)return this.transform.minPitch=t,this._update(),this.getPitch()<t&&this.setPitch(t),this;throw new Error(\"minPitch must be between 0 and the current maxPitch, inclusive\")},i.prototype.getMinPitch=function(){return this.transform.minPitch},i.prototype.setMaxPitch=function(t){if((t=null==t?Ii:t)>Ii)throw new Error(\"maxPitch must be less than or equal to 60\");if(t>=this.transform.minPitch)return this.transform.maxPitch=t,this._update(),this.getPitch()>t&&this.setPitch(t),this;throw new Error(\"maxPitch must be greater than the current minPitch\")},i.prototype.getMaxPitch=function(){return this.transform.maxPitch},i.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},i.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update()},i.prototype.project=function(e){return this.transform.locationPoint(t.LngLat.convert(e))},i.prototype.unproject=function(e){return this.transform.pointLocation(t.Point.convert(e))},i.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},i.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},i.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},i.prototype._createDelegatedListener=function(t,e,r){var n,i=this;if(\"mouseenter\"===t||\"mouseover\"===t){var a=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){var o=i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[];o.length?a||(a=!0,r.call(i,new Un(t,i,n.originalEvent,{features:o}))):a=!1},mouseout:function(){a=!1}}}}if(\"mouseleave\"===t||\"mouseout\"===t){var o=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){(i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,r.call(i,new Un(t,i,n.originalEvent)))},mouseout:function(e){o&&(o=!1,r.call(i,new Un(t,i,e.originalEvent)))}}}}return{layer:e,listener:r,delegates:(n={},n[t]=function(t){var n=i.getLayer(e)?i.queryRenderedFeatures(t.point,{layers:[e]}):[];n.length&&(t.features=n,r.call(i,t),delete t.features)},n)}},i.prototype.on=function(t,e,r){if(void 0===r)return n.prototype.on.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(i),i.delegates)this.on(a,i.delegates[a]);return this},i.prototype.once=function(t,e,r){if(void 0===r)return n.prototype.once.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in i.delegates)this.once(a,i.delegates[a]);return this},i.prototype.off=function(t,e,r){var i=this;if(void 0===r)return n.prototype.off.call(this,t,e);return this._delegatedListeners&&this._delegatedListeners[t]&&function(n){for(var a=n[t],o=0;o<a.length;o++){var s=a[o];if(s.layer===e&&s.listener===r){for(var l in s.delegates)i.off(l,s.delegates[l]);return a.splice(o,1),i}}}(this._delegatedListeners),this},i.prototype.queryRenderedFeatures=function(e,r){if(!this.style)return[];var n;if(void 0!==r||void 0===e||e instanceof t.Point||Array.isArray(e)||(r=e,e=void 0),r=r||{},(e=e||[[0,0],[this.transform.width,this.transform.height]])instanceof t.Point||\"number\"==typeof e[0])n=[t.Point.convert(e)];else{var i=t.Point.convert(e[0]),a=t.Point.convert(e[1]);n=[i,new t.Point(a.x,i.y),a,new t.Point(i.x,a.y),i]}return this.style.queryRenderedFeatures(n,r,this.transform)},i.prototype.querySourceFeatures=function(t,e){return this.style.querySourceFeatures(t,e)},i.prototype.setStyle=function(e,r){return!1!==(r=t.extend({},{localIdeographFontFamily:this._localIdeographFontFamily},r)).diff&&r.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&e?(this._diffStyle(e,r),this):(this._localIdeographFontFamily=r.localIdeographFontFamily,this._updateStyle(e,r))},i.prototype._getUIString=function(t){var e=this._locale[t];if(null==e)throw new Error(\"Missing UI string '\"+t+\"'\");return e},i.prototype._updateStyle=function(t,e){return this.style&&(this.style.setEventedParent(null),this.style._remove()),t?(this.style=new Ye(this,e||{}),this.style.setEventedParent(this,{style:this.style}),\"string\"==typeof t?this.style.loadURL(t):this.style.loadJSON(t),this):(delete this.style,this)},i.prototype._lazyInitEmptyStyle=function(){this.style||(this.style=new Ye(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())},i.prototype._diffStyle=function(e,r){var n=this;if(\"string\"==typeof e){var i=this._requestManager.normalizeStyleURL(e),a=this._requestManager.transformRequest(i,t.ResourceType.Style);t.getJSON(a,(function(e,i){e?n.fire(new t.ErrorEvent(e)):i&&n._updateDiff(i,r)}))}else\"object\"==typeof e&&this._updateDiff(e,r)},i.prototype._updateDiff=function(e,r){try{this.style.setState(e)&&this._update(!0)}catch(n){t.warnOnce(\"Unable to perform style diff: \"+(n.message||n.error||n)+\".  Rebuilding the style from scratch.\"),this._updateStyle(e,r)}},i.prototype.getStyle=function(){if(this.style)return this.style.serialize()},i.prototype.isStyleLoaded=function(){return this.style?this.style.loaded():t.warnOnce(\"There is no style added to the map.\")},i.prototype.addSource=function(t,e){return this._lazyInitEmptyStyle(),this.style.addSource(t,e),this._update(!0)},i.prototype.isSourceLoaded=function(e){var r=this.style&&this.style.sourceCaches[e];if(void 0!==r)return r.loaded();this.fire(new t.ErrorEvent(new Error(\"There is no source with ID '\"+e+\"'\")))},i.prototype.areTilesLoaded=function(){var t=this.style&&this.style.sourceCaches;for(var e in t){var r=t[e]._tiles;for(var n in r){var i=r[n];if(\"loaded\"!==i.state&&\"errored\"!==i.state)return!1}}return!0},i.prototype.addSourceType=function(t,e,r){return this._lazyInitEmptyStyle(),this.style.addSourceType(t,e,r)},i.prototype.removeSource=function(t){return this.style.removeSource(t),this._update(!0)},i.prototype.getSource=function(t){return this.style.getSource(t)},i.prototype.addImage=function(e,r,n){void 0===n&&(n={});var i=n.pixelRatio;void 0===i&&(i=1);var a=n.sdf;void 0===a&&(a=!1);var o=n.stretchX,s=n.stretchY,l=n.content;this._lazyInitEmptyStyle();if(r instanceof Ci||Oi&&r instanceof Oi){var u=t.browser.getImageData(r),c=u.width,f=u.height,h=u.data;this.style.addImage(e,{data:new t.RGBAImage({width:c,height:f},h),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0})}else{if(void 0===r.width||void 0===r.height)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));var p=r.width,d=r.height,v=r.data,g=r;this.style.addImage(e,{data:new t.RGBAImage({width:p,height:d},new Uint8Array(v)),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0,userImage:g}),g.onAdd&&g.onAdd(this,e)}},i.prototype.updateImage=function(e,r){var n=this.style.getImage(e);if(!n)return this.fire(new t.ErrorEvent(new Error(\"The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.\")));var i=r instanceof Ci||Oi&&r instanceof Oi?t.browser.getImageData(r):r,a=i.width,o=i.height,s=i.data;if(void 0===a||void 0===o)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));if(a!==n.data.width||o!==n.data.height)return this.fire(new t.ErrorEvent(new Error(\"The width and height of the updated image must be that same as the previous version of the image\")));var l=!(r instanceof Ci||Oi&&r instanceof Oi);n.data.replace(s,l),this.style.updateImage(e,n)},i.prototype.hasImage=function(e){return e?!!this.style.getImage(e):(this.fire(new t.ErrorEvent(new Error(\"Missing required image id\"))),!1)},i.prototype.removeImage=function(t){this.style.removeImage(t)},i.prototype.loadImage=function(e,r){t.getImage(this._requestManager.transformRequest(e,t.ResourceType.Image),r)},i.prototype.listImages=function(){return this.style.listImages()},i.prototype.addLayer=function(t,e){return this._lazyInitEmptyStyle(),this.style.addLayer(t,e),this._update(!0)},i.prototype.moveLayer=function(t,e){return this.style.moveLayer(t,e),this._update(!0)},i.prototype.removeLayer=function(t){return this.style.removeLayer(t),this._update(!0)},i.prototype.getLayer=function(t){return this.style.getLayer(t)},i.prototype.setLayerZoomRange=function(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0)},i.prototype.setFilter=function(t,e,r){return void 0===r&&(r={}),this.style.setFilter(t,e,r),this._update(!0)},i.prototype.getFilter=function(t){return this.style.getFilter(t)},i.prototype.setPaintProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setPaintProperty(t,e,r,n),this._update(!0)},i.prototype.getPaintProperty=function(t,e){return this.style.getPaintProperty(t,e)},i.prototype.setLayoutProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setLayoutProperty(t,e,r,n),this._update(!0)},i.prototype.getLayoutProperty=function(t,e){return this.style.getLayoutProperty(t,e)},i.prototype.setLight=function(t,e){return void 0===e&&(e={}),this._lazyInitEmptyStyle(),this.style.setLight(t,e),this._update(!0)},i.prototype.getLight=function(){return this.style.getLight()},i.prototype.setFeatureState=function(t,e){return this.style.setFeatureState(t,e),this._update()},i.prototype.removeFeatureState=function(t,e){return this.style.removeFeatureState(t,e),this._update()},i.prototype.getFeatureState=function(t){return this.style.getFeatureState(t)},i.prototype.getContainer=function(){return this._container},i.prototype.getCanvasContainer=function(){return this._canvasContainer},i.prototype.getCanvas=function(){return this._canvas},i.prototype._containerDimensions=function(){var t=0,e=0;return this._container&&(t=this._container.clientWidth||400,e=this._container.clientHeight||300),[t,e]},i.prototype._detectMissingCSS=function(){\"rgb(250, 128, 114)\"!==t.window.getComputedStyle(this._missingCSSCanary).getPropertyValue(\"background-color\")&&t.warnOnce(\"This page appears to be missing CSS declarations for Mapbox GL JS, which may cause the map to display incorrectly. Please ensure your page includes mapbox-gl.css, as described in https://www.mapbox.com/mapbox-gl-js/api/.\")},i.prototype._setupContainer=function(){var t=this._container;t.classList.add(\"mapboxgl-map\"),(this._missingCSSCanary=r.create(\"div\",\"mapboxgl-canary\",t)).style.visibility=\"hidden\",this._detectMissingCSS();var e=this._canvasContainer=r.create(\"div\",\"mapboxgl-canvas-container\",t);this._interactive&&e.classList.add(\"mapboxgl-interactive\"),this._canvas=r.create(\"canvas\",\"mapboxgl-canvas\",e),this._canvas.addEventListener(\"webglcontextlost\",this._contextLost,!1),this._canvas.addEventListener(\"webglcontextrestored\",this._contextRestored,!1),this._canvas.setAttribute(\"tabindex\",\"0\"),this._canvas.setAttribute(\"aria-label\",\"Map\");var n=this._containerDimensions();this._resizeCanvas(n[0],n[1]);var i=this._controlContainer=r.create(\"div\",\"mapboxgl-control-container\",t),a=this._controlPositions={};[\"top-left\",\"top-right\",\"bottom-left\",\"bottom-right\"].forEach((function(t){a[t]=r.create(\"div\",\"mapboxgl-ctrl-\"+t,i)}))},i.prototype._resizeCanvas=function(e,r){var n=t.browser.devicePixelRatio||1;this._canvas.width=n*e,this._canvas.height=n*r,this._canvas.style.width=e+\"px\",this._canvas.style.height=r+\"px\"},i.prototype._setupPainter=function(){var r=t.extend({},e.webGLContextAttributes,{failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1}),n=this._canvas.getContext(\"webgl\",r)||this._canvas.getContext(\"experimental-webgl\",r);n?(this.painter=new Mn(n,this.transform),t.webpSupported.testSupport(n)):this.fire(new t.ErrorEvent(new Error(\"Failed to initialize WebGL\")))},i.prototype._contextLost=function(e){e.preventDefault(),this._frame&&(this._frame.cancel(),this._frame=null),this.fire(new t.Event(\"webglcontextlost\",{originalEvent:e}))},i.prototype._contextRestored=function(e){this._setupPainter(),this.resize(),this._update(),this.fire(new t.Event(\"webglcontextrestored\",{originalEvent:e}))},i.prototype.loaded=function(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()},i.prototype._update=function(t){return this.style?(this._styleDirty=this._styleDirty||t,this._sourcesDirty=!0,this.triggerRepaint(),this):this},i.prototype._requestRenderFrame=function(t){return this._update(),this._renderTaskQueue.add(t)},i.prototype._cancelRenderFrame=function(t){this._renderTaskQueue.remove(t)},i.prototype._render=function(e){var r,n=this,i=0,a=this.painter.context.extTimerQuery;if(this.listens(\"gpu-timing-frame\")&&(r=a.createQueryEXT(),a.beginQueryEXT(a.TIME_ELAPSED_EXT,r),i=t.browser.now()),this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(e),!this._removed){var o=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;var s=this.transform.zoom,l=t.browser.now();this.style.zoomHistory.update(s,l);var u=new t.EvaluationParameters(s,{now:l,fadeDuration:this._fadeDuration,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),c=u.crossFadingFactor();1===c&&c===this._crossFadingFactor||(o=!0,this._crossFadingFactor=c),this.style.update(u)}if(this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,this._fadeDuration,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:this._fadeDuration,showPadding:this.showPadding,gpuTiming:!!this.listens(\"gpu-timing-layer\")}),this.fire(new t.Event(\"render\")),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(new t.Event(\"load\"))),this.style&&(this.style.hasTransitions()||o)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles(),this.listens(\"gpu-timing-frame\")){var f=t.browser.now()-i;a.endQueryEXT(a.TIME_ELAPSED_EXT,r),setTimeout((function(){var e=a.getQueryObjectEXT(r,a.QUERY_RESULT_EXT)/1e6;a.deleteQueryEXT(r),n.fire(new t.Event(\"gpu-timing-frame\",{cpuTime:f,gpuTime:e}))}),50)}if(this.listens(\"gpu-timing-layer\")){var h=this.painter.collectGpuTimers();setTimeout((function(){var e=n.painter.queryGpuTimers(h);n.fire(new t.Event(\"gpu-timing-layer\",{layerTimes:e}))}),50)}return this._sourcesDirty||this._styleDirty||this._placementDirty||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&(this._fullyLoaded||(this._fullyLoaded=!0),this.fire(new t.Event(\"idle\"))),this}},i.prototype.remove=function(){this._hash&&this._hash.remove();for(var e=0,r=this._controls;e<r.length;e+=1)r[e].onRemove(this);this._controls=[],this._frame&&(this._frame.cancel(),this._frame=null),this._renderTaskQueue.clear(),this.painter.destroy(),this.handlers.destroy(),delete this.handlers,this.setStyle(null),void 0!==t.window&&(t.window.removeEventListener(\"resize\",this._onWindowResize,!1),t.window.removeEventListener(\"online\",this._onWindowOnline,!1));var n=this.painter.context.gl.getExtension(\"WEBGL_lose_context\");n&&n.loseContext(),Ri(this._canvasContainer),Ri(this._controlContainer),Ri(this._missingCSSCanary),this._container.classList.remove(\"mapboxgl-map\"),this._removed=!0,this.fire(new t.Event(\"remove\"))},i.prototype.triggerRepaint=function(){var e=this;this.style&&!this._frame&&(this._frame=t.browser.frame((function(t){e._frame=null,e._render(t)})))},i.prototype._onWindowOnline=function(){this._update()},i.prototype._onWindowResize=function(t){this._trackResize&&this.resize({originalEvent:t})._update()},a.showTileBoundaries.get=function(){return!!this._showTileBoundaries},a.showTileBoundaries.set=function(t){this._showTileBoundaries!==t&&(this._showTileBoundaries=t,this._update())},a.showPadding.get=function(){return!!this._showPadding},a.showPadding.set=function(t){this._showPadding!==t&&(this._showPadding=t,this._update())},a.showCollisionBoxes.get=function(){return!!this._showCollisionBoxes},a.showCollisionBoxes.set=function(t){this._showCollisionBoxes!==t&&(this._showCollisionBoxes=t,t?this.style._generateCollisionBoxes():this._update())},a.showOverdrawInspector.get=function(){return!!this._showOverdrawInspector},a.showOverdrawInspector.set=function(t){this._showOverdrawInspector!==t&&(this._showOverdrawInspector=t,this._update())},a.repaint.get=function(){return!!this._repaint},a.repaint.set=function(t){this._repaint!==t&&(this._repaint=t,this.triggerRepaint())},a.vertices.get=function(){return!!this._vertices},a.vertices.set=function(t){this._vertices=t,this._update()},i.prototype._setCacheLimits=function(e,r){t.setCacheLimits(e,r)},a.version.get=function(){return t.version},Object.defineProperties(i.prototype,a),i}(Ai);function Ri(t){t.parentNode&&t.parentNode.removeChild(t)}var Fi={showCompass:!0,showZoom:!0,visualizePitch:!1},Bi=function(e){var n=this;this.options=t.extend({},Fi,e),this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this.options.showZoom&&(t.bindAll([\"_setButtonTitle\",\"_updateZoomButtons\"],this),this._zoomInButton=this._createButton(\"mapboxgl-ctrl-zoom-in\",(function(t){return n._map.zoomIn({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomInButton).setAttribute(\"aria-hidden\",!0),this._zoomOutButton=this._createButton(\"mapboxgl-ctrl-zoom-out\",(function(t){return n._map.zoomOut({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomOutButton).setAttribute(\"aria-hidden\",!0)),this.options.showCompass&&(t.bindAll([\"_rotateCompassArrow\"],this),this._compass=this._createButton(\"mapboxgl-ctrl-compass\",(function(t){n.options.visualizePitch?n._map.resetNorthPitch({},{originalEvent:t}):n._map.resetNorth({},{originalEvent:t})})),this._compassIcon=r.create(\"span\",\"mapboxgl-ctrl-icon\",this._compass),this._compassIcon.setAttribute(\"aria-hidden\",!0))};Bi.prototype._updateZoomButtons=function(){var t=this._map.getZoom();this._zoomInButton.disabled=t===this._map.getMaxZoom(),this._zoomOutButton.disabled=t===this._map.getMinZoom()},Bi.prototype._rotateCompassArrow=function(){var t=this.options.visualizePitch?\"scale(\"+1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)+\") rotateX(\"+this._map.transform.pitch+\"deg) rotateZ(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\":\"rotate(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\";this._compassIcon.style.transform=t},Bi.prototype.onAdd=function(t){return this._map=t,this.options.showZoom&&(this._setButtonTitle(this._zoomInButton,\"ZoomIn\"),this._setButtonTitle(this._zoomOutButton,\"ZoomOut\"),this._map.on(\"zoom\",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this._setButtonTitle(this._compass,\"ResetBearing\"),this.options.visualizePitch&&this._map.on(\"pitch\",this._rotateCompassArrow),this._map.on(\"rotate\",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new Ni(this._map,this._compass,this.options.visualizePitch)),this._container},Bi.prototype.onRemove=function(){r.remove(this._container),this.options.showZoom&&this._map.off(\"zoom\",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off(\"pitch\",this._rotateCompassArrow),this._map.off(\"rotate\",this._rotateCompassArrow),this._handler.off(),delete this._handler),delete this._map},Bi.prototype._createButton=function(t,e){var n=r.create(\"button\",t,this._container);return n.type=\"button\",n.addEventListener(\"click\",e),n},Bi.prototype._setButtonTitle=function(t,e){var r=this._map._getUIString(\"NavigationControl.\"+e);t.title=r,t.setAttribute(\"aria-label\",r)};var Ni=function(e,n,i){void 0===i&&(i=!1),this._clickTolerance=10,this.element=n,this.mouseRotate=new Qn({clickTolerance:e.dragRotate._mouseRotate._clickTolerance}),this.map=e,i&&(this.mousePitch=new ti({clickTolerance:e.dragRotate._mousePitch._clickTolerance})),t.bindAll([\"mousedown\",\"mousemove\",\"mouseup\",\"touchstart\",\"touchmove\",\"touchend\",\"reset\"],this),r.addEventListener(n,\"mousedown\",this.mousedown),r.addEventListener(n,\"touchstart\",this.touchstart,{passive:!1}),r.addEventListener(n,\"touchmove\",this.touchmove),r.addEventListener(n,\"touchend\",this.touchend),r.addEventListener(n,\"touchcancel\",this.reset)};function ji(e,r,n){if(e=new t.LngLat(e.lng,e.lat),r){var i=new t.LngLat(e.lng-360,e.lat),a=new t.LngLat(e.lng+360,e.lat),o=n.locationPoint(e).distSqr(r);n.locationPoint(i).distSqr(r)<o?e=i:n.locationPoint(a).distSqr(r)<o&&(e=a)}for(;Math.abs(e.lng-n.center.lng)>180;){var s=n.locationPoint(e);if(s.x>=0&&s.y>=0&&s.x<=n.width&&s.y<=n.height)break;e.lng>n.center.lng?e.lng-=360:e.lng+=360}return e}Ni.prototype.down=function(t,e){this.mouseRotate.mousedown(t,e),this.mousePitch&&this.mousePitch.mousedown(t,e),r.disableDrag()},Ni.prototype.move=function(t,e){var r=this.map,n=this.mouseRotate.mousemoveWindow(t,e);if(n&&n.bearingDelta&&r.setBearing(r.getBearing()+n.bearingDelta),this.mousePitch){var i=this.mousePitch.mousemoveWindow(t,e);i&&i.pitchDelta&&r.setPitch(r.getPitch()+i.pitchDelta)}},Ni.prototype.off=function(){var t=this.element;r.removeEventListener(t,\"mousedown\",this.mousedown),r.removeEventListener(t,\"touchstart\",this.touchstart,{passive:!1}),r.removeEventListener(t,\"touchmove\",this.touchmove),r.removeEventListener(t,\"touchend\",this.touchend),r.removeEventListener(t,\"touchcancel\",this.reset),this.offTemp()},Ni.prototype.offTemp=function(){r.enableDrag(),r.removeEventListener(t.window,\"mousemove\",this.mousemove),r.removeEventListener(t.window,\"mouseup\",this.mouseup)},Ni.prototype.mousedown=function(e){this.down(t.extend({},e,{ctrlKey:!0,preventDefault:function(){return e.preventDefault()}}),r.mousePos(this.element,e)),r.addEventListener(t.window,\"mousemove\",this.mousemove),r.addEventListener(t.window,\"mouseup\",this.mouseup)},Ni.prototype.mousemove=function(t){this.move(t,r.mousePos(this.element,t))},Ni.prototype.mouseup=function(t){this.mouseRotate.mouseupWindow(t),this.mousePitch&&this.mousePitch.mouseupWindow(t),this.offTemp()},Ni.prototype.touchstart=function(t){1!==t.targetTouches.length?this.reset():(this._startPos=this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.down({type:\"mousedown\",button:0,ctrlKey:!0,preventDefault:function(){return t.preventDefault()}},this._startPos))},Ni.prototype.touchmove=function(t){1!==t.targetTouches.length?this.reset():(this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.move({preventDefault:function(){return t.preventDefault()}},this._lastPos))},Ni.prototype.touchend=function(t){0===t.targetTouches.length&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)<this._clickTolerance&&this.element.click(),this.reset()},Ni.prototype.reset=function(){this.mouseRotate.reset(),this.mousePitch&&this.mousePitch.reset(),delete this._startPos,delete this._lastPos,this.offTemp()};var Ui={center:\"translate(-50%,-50%)\",top:\"translate(-50%,0)\",\"top-left\":\"translate(0,0)\",\"top-right\":\"translate(-100%,0)\",bottom:\"translate(-50%,-100%)\",\"bottom-left\":\"translate(0,-100%)\",\"bottom-right\":\"translate(-100%,-100%)\",left:\"translate(0,-50%)\",right:\"translate(-100%,-50%)\"};function Vi(t,e,r){var n=t.classList;for(var i in Ui)n.remove(\"mapboxgl-\"+r+\"-anchor-\"+i);n.add(\"mapboxgl-\"+r+\"-anchor-\"+e)}var Hi,qi=function(e){function n(n,i){var a=this;if(e.call(this),(n instanceof t.window.HTMLElement||i)&&(n=t.extend({element:n},i)),t.bindAll([\"_update\",\"_onMove\",\"_onUp\",\"_addDragHandler\",\"_onMapClick\",\"_onKeyPress\"],this),this._anchor=n&&n.anchor||\"center\",this._color=n&&n.color||\"#3FB1CE\",this._draggable=n&&n.draggable||!1,this._state=\"inactive\",this._rotation=n&&n.rotation||0,this._rotationAlignment=n&&n.rotationAlignment||\"auto\",this._pitchAlignment=n&&n.pitchAlignment&&\"auto\"!==n.pitchAlignment?n.pitchAlignment:this._rotationAlignment,n&&n.element)this._element=n.element,this._offset=t.Point.convert(n&&n.offset||[0,0]);else{this._defaultMarker=!0,this._element=r.create(\"div\"),this._element.setAttribute(\"aria-label\",\"Map marker\");var o=r.createNS(\"http://www.w3.org/2000/svg\",\"svg\");o.setAttributeNS(null,\"display\",\"block\"),o.setAttributeNS(null,\"height\",\"41px\"),o.setAttributeNS(null,\"width\",\"27px\"),o.setAttributeNS(null,\"viewBox\",\"0 0 27 41\");var s=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");s.setAttributeNS(null,\"stroke\",\"none\"),s.setAttributeNS(null,\"stroke-width\",\"1\"),s.setAttributeNS(null,\"fill\",\"none\"),s.setAttributeNS(null,\"fill-rule\",\"evenodd\");var l=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");l.setAttributeNS(null,\"fill-rule\",\"nonzero\");var u=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");u.setAttributeNS(null,\"transform\",\"translate(3.0, 29.0)\"),u.setAttributeNS(null,\"fill\",\"#000000\");for(var c=0,f=[{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"9.5\",ry:\"4.77275007\"},{rx:\"8.5\",ry:\"4.29549936\"},{rx:\"7.5\",ry:\"3.81822308\"},{rx:\"6.5\",ry:\"3.34094679\"},{rx:\"5.5\",ry:\"2.86367051\"},{rx:\"4.5\",ry:\"2.38636864\"}];c<f.length;c+=1){var h=f[c],p=r.createNS(\"http://www.w3.org/2000/svg\",\"ellipse\");p.setAttributeNS(null,\"opacity\",\"0.04\"),p.setAttributeNS(null,\"cx\",\"10.5\"),p.setAttributeNS(null,\"cy\",\"5.80029008\"),p.setAttributeNS(null,\"rx\",h.rx),p.setAttributeNS(null,\"ry\",h.ry),u.appendChild(p)}var d=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");d.setAttributeNS(null,\"fill\",this._color);var v=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");v.setAttributeNS(null,\"d\",\"M27,13.5 C27,19.074644 20.250001,27.000002 14.75,34.500002 C14.016665,35.500004 12.983335,35.500004 12.25,34.500002 C6.7499993,27.000002 0,19.222562 0,13.5 C0,6.0441559 6.0441559,0 13.5,0 C20.955844,0 27,6.0441559 27,13.5 Z\"),d.appendChild(v);var g=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");g.setAttributeNS(null,\"opacity\",\"0.25\"),g.setAttributeNS(null,\"fill\",\"#000000\");var y=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");y.setAttributeNS(null,\"d\",\"M13.5,0 C6.0441559,0 0,6.0441559 0,13.5 C0,19.222562 6.7499993,27 12.25,34.5 C13,35.522727 14.016664,35.500004 14.75,34.5 C20.250001,27 27,19.074644 27,13.5 C27,6.0441559 20.955844,0 13.5,0 Z M13.5,1 C20.415404,1 26,6.584596 26,13.5 C26,15.898657 24.495584,19.181431 22.220703,22.738281 C19.945823,26.295132 16.705119,30.142167 13.943359,33.908203 C13.743445,34.180814 13.612715,34.322738 13.5,34.441406 C13.387285,34.322738 13.256555,34.180814 13.056641,33.908203 C10.284481,30.127985 7.4148684,26.314159 5.015625,22.773438 C2.6163816,19.232715 1,15.953538 1,13.5 C1,6.584596 6.584596,1 13.5,1 Z\"),g.appendChild(y);var m=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");m.setAttributeNS(null,\"transform\",\"translate(6.0, 7.0)\"),m.setAttributeNS(null,\"fill\",\"#FFFFFF\");var x=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");x.setAttributeNS(null,\"transform\",\"translate(8.0, 8.0)\");var b=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");b.setAttributeNS(null,\"fill\",\"#000000\"),b.setAttributeNS(null,\"opacity\",\"0.25\"),b.setAttributeNS(null,\"cx\",\"5.5\"),b.setAttributeNS(null,\"cy\",\"5.5\"),b.setAttributeNS(null,\"r\",\"5.4999962\");var _=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");_.setAttributeNS(null,\"fill\",\"#FFFFFF\"),_.setAttributeNS(null,\"cx\",\"5.5\"),_.setAttributeNS(null,\"cy\",\"5.5\"),_.setAttributeNS(null,\"r\",\"5.4999962\"),x.appendChild(b),x.appendChild(_),l.appendChild(u),l.appendChild(d),l.appendChild(g),l.appendChild(m),l.appendChild(x),o.appendChild(l),this._element.appendChild(o),this._offset=t.Point.convert(n&&n.offset||[0,-14])}this._element.classList.add(\"mapboxgl-marker\"),this._element.addEventListener(\"dragstart\",(function(t){t.preventDefault()})),this._element.addEventListener(\"mousedown\",(function(t){t.preventDefault()})),this._element.addEventListener(\"focus\",(function(){var t=a._map.getContainer();t.scrollTop=0,t.scrollLeft=0})),Vi(this._element,this._anchor,\"marker\"),this._popup=null}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(t){return this.remove(),this._map=t,t.getCanvasContainer().appendChild(this._element),t.on(\"move\",this._update),t.on(\"moveend\",this._update),this.setDraggable(this._draggable),this._update(),this._map.on(\"click\",this._onMapClick),this},n.prototype.remove=function(){return this._map&&(this._map.off(\"click\",this._onMapClick),this._map.off(\"move\",this._update),this._map.off(\"moveend\",this._update),this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler),this._map.off(\"mouseup\",this._onUp),this._map.off(\"touchend\",this._onUp),this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),delete this._map),r.remove(this._element),this._popup&&this._popup.remove(),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this},n.prototype.getElement=function(){return this._element},n.prototype.setPopup=function(t){if(this._popup&&(this._popup.remove(),this._popup=null,this._element.removeEventListener(\"keypress\",this._onKeyPress),this._originalTabIndex||this._element.removeAttribute(\"tabindex\")),t){if(!(\"offset\"in t.options)){var e=13.5,r=Math.sqrt(Math.pow(e,2)/2);t.options.offset=this._defaultMarker?{top:[0,0],\"top-left\":[0,0],\"top-right\":[0,0],bottom:[0,-38.1],\"bottom-left\":[r,-1*(24.6+r)],\"bottom-right\":[-r,-1*(24.6+r)],left:[e,-24.6],right:[-13.5,-24.6]}:this._offset}this._popup=t,this._lngLat&&this._popup.setLngLat(this._lngLat),this._originalTabIndex=this._element.getAttribute(\"tabindex\"),this._originalTabIndex||this._element.setAttribute(\"tabindex\",\"0\"),this._element.addEventListener(\"keypress\",this._onKeyPress)}return this},n.prototype._onKeyPress=function(t){var e=t.code,r=t.charCode||t.keyCode;\"Space\"!==e&&\"Enter\"!==e&&32!==r&&13!==r||this.togglePopup()},n.prototype._onMapClick=function(t){var e=t.originalEvent.target,r=this._element;this._popup&&(e===r||r.contains(e))&&this.togglePopup()},n.prototype.getPopup=function(){return this._popup},n.prototype.togglePopup=function(){var t=this._popup;return t?(t.isOpen()?t.remove():t.addTo(this._map),this):this},n.prototype._update=function(t){if(this._map){this._map.transform.renderWorldCopies&&(this._lngLat=ji(this._lngLat,this._pos,this._map.transform)),this._pos=this._map.project(this._lngLat)._add(this._offset);var e=\"\";\"viewport\"===this._rotationAlignment||\"auto\"===this._rotationAlignment?e=\"rotateZ(\"+this._rotation+\"deg)\":\"map\"===this._rotationAlignment&&(e=\"rotateZ(\"+(this._rotation-this._map.getBearing())+\"deg)\");var n=\"\";\"viewport\"===this._pitchAlignment||\"auto\"===this._pitchAlignment?n=\"rotateX(0deg)\":\"map\"===this._pitchAlignment&&(n=\"rotateX(\"+this._map.getPitch()+\"deg)\"),t&&\"moveend\"!==t.type||(this._pos=this._pos.round()),r.setTransform(this._element,Ui[this._anchor]+\" translate(\"+this._pos.x+\"px, \"+this._pos.y+\"px) \"+n+\" \"+e)}},n.prototype.getOffset=function(){return this._offset},n.prototype.setOffset=function(e){return this._offset=t.Point.convert(e),this._update(),this},n.prototype._onMove=function(e){this._pos=e.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents=\"none\",\"pending\"===this._state&&(this._state=\"active\",this.fire(new t.Event(\"dragstart\"))),this.fire(new t.Event(\"drag\"))},n.prototype._onUp=function(){this._element.style.pointerEvents=\"auto\",this._positionDelta=null,this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),\"active\"===this._state&&this.fire(new t.Event(\"dragend\")),this._state=\"inactive\"},n.prototype._addDragHandler=function(t){this._element.contains(t.originalEvent.target)&&(t.preventDefault(),this._positionDelta=t.point.sub(this._pos).add(this._offset),this._state=\"pending\",this._map.on(\"mousemove\",this._onMove),this._map.on(\"touchmove\",this._onMove),this._map.once(\"mouseup\",this._onUp),this._map.once(\"touchend\",this._onUp))},n.prototype.setDraggable=function(t){return this._draggable=!!t,this._map&&(t?(this._map.on(\"mousedown\",this._addDragHandler),this._map.on(\"touchstart\",this._addDragHandler)):(this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler))),this},n.prototype.isDraggable=function(){return this._draggable},n.prototype.setRotation=function(t){return this._rotation=t||0,this._update(),this},n.prototype.getRotation=function(){return this._rotation},n.prototype.setRotationAlignment=function(t){return this._rotationAlignment=t||\"auto\",this._update(),this},n.prototype.getRotationAlignment=function(){return this._rotationAlignment},n.prototype.setPitchAlignment=function(t){return this._pitchAlignment=t&&\"auto\"!==t?t:this._rotationAlignment,this._update(),this},n.prototype.getPitchAlignment=function(){return this._pitchAlignment},n}(t.Evented),Gi={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0};var Zi=0,Yi=!1,Wi=function(e){function n(r){e.call(this),this.options=t.extend({},Gi,r),t.bindAll([\"_onSuccess\",\"_onError\",\"_onZoom\",\"_finish\",\"_setupUI\",\"_updateCamera\",\"_updateMarker\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.onAdd=function(e){return this._map=e,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),n=this._setupUI,void 0!==Hi?n(Hi):void 0!==t.window.navigator.permissions?t.window.navigator.permissions.query({name:\"geolocation\"}).then((function(t){Hi=\"denied\"!==t.state,n(Hi)})):(Hi=!!t.window.navigator.geolocation,n(Hi)),this._container;var n},n.prototype.onRemove=function(){void 0!==this._geolocationWatchID&&(t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),r.remove(this._container),this._map.off(\"zoom\",this._onZoom),this._map=void 0,Zi=0,Yi=!1},n.prototype._isOutOfMapMaxBounds=function(t){var e=this._map.getMaxBounds(),r=t.coords;return e&&(r.longitude<e.getWest()||r.longitude>e.getEast()||r.latitude<e.getSouth()||r.latitude>e.getNorth())},n.prototype._setErrorState=function(){switch(this._watchState){case\"WAITING_ACTIVE\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"ACTIVE_LOCK\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\");break;case\"BACKGROUND\":this._watchState=\"BACKGROUND_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\")}},n.prototype._onSuccess=function(e){if(this._map){if(this._isOutOfMapMaxBounds(e))return this._setErrorState(),this.fire(new t.Event(\"outofmaxbounds\",e)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"BACKGROUND\":case\"BACKGROUND_ERROR\":this._watchState=\"BACKGROUND\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\")}this.options.showUserLocation&&\"OFF\"!==this._watchState&&this._updateMarker(e),this.options.trackUserLocation&&\"ACTIVE_LOCK\"!==this._watchState||this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"geolocate\",e)),this._finish()}},n.prototype._updateCamera=function(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude),n=e.coords.accuracy,i=this._map.getBearing(),a=t.extend({bearing:i},this.options.fitBoundsOptions);this._map.fitBounds(r.toBounds(n),a,{geolocateSource:!0})},n.prototype._updateMarker=function(e){if(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude);this._accuracyCircleMarker.setLngLat(r).addTo(this._map),this._userLocationDotMarker.setLngLat(r).addTo(this._map),this._accuracy=e.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},n.prototype._updateCircleRadius=function(){var t=this._map._container.clientHeight/2,e=this._map.unproject([0,t]),r=this._map.unproject([1,t]),n=e.distanceTo(r),i=Math.ceil(2*this._accuracy/n);this._circleElement.style.width=i+\"px\",this._circleElement.style.height=i+\"px\"},n.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},n.prototype._onError=function(e){if(this._map){if(this.options.trackUserLocation)if(1===e.code){this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.disabled=!0;var r=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.title=r,this._geolocateButton.setAttribute(\"aria-label\",r),void 0!==this._geolocationWatchID&&this._clearWatch()}else{if(3===e.code&&Yi)return;this._setErrorState()}\"OFF\"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"error\",e)),this._finish()}},n.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},n.prototype._setupUI=function(e){var n=this;if(this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this._geolocateButton=r.create(\"button\",\"mapboxgl-ctrl-geolocate\",this._container),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._geolocateButton).setAttribute(\"aria-hidden\",!0),this._geolocateButton.type=\"button\",!1===e){t.warnOnce(\"Geolocation support is not available so the GeolocateControl will be disabled.\");var i=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.disabled=!0,this._geolocateButton.title=i,this._geolocateButton.setAttribute(\"aria-label\",i)}else{var a=this._map._getUIString(\"GeolocateControl.FindMyLocation\");this._geolocateButton.title=a,this._geolocateButton.setAttribute(\"aria-label\",a)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this._watchState=\"OFF\"),this.options.showUserLocation&&(this._dotElement=r.create(\"div\",\"mapboxgl-user-location-dot\"),this._userLocationDotMarker=new qi(this._dotElement),this._circleElement=r.create(\"div\",\"mapboxgl-user-location-accuracy-circle\"),this._accuracyCircleMarker=new qi({element:this._circleElement,pitchAlignment:\"map\"}),this.options.trackUserLocation&&(this._watchState=\"OFF\"),this._map.on(\"zoom\",this._onZoom)),this._geolocateButton.addEventListener(\"click\",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on(\"movestart\",(function(e){var r=e.originalEvent&&\"resize\"===e.originalEvent.type;e.geolocateSource||\"ACTIVE_LOCK\"!==n._watchState||r||(n._watchState=\"BACKGROUND\",n._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\"),n._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),n.fire(new t.Event(\"trackuserlocationend\")))}))},n.prototype.trigger=function(){if(!this._setup)return t.warnOnce(\"Geolocate control triggered before added to a map\"),!1;if(this.options.trackUserLocation){switch(this._watchState){case\"OFF\":this._watchState=\"WAITING_ACTIVE\",this.fire(new t.Event(\"trackuserlocationstart\"));break;case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":case\"BACKGROUND_ERROR\":Zi--,Yi=!1,this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this.fire(new t.Event(\"trackuserlocationend\"));break;case\"BACKGROUND\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event(\"trackuserlocationstart\"))}switch(this._watchState){case\"WAITING_ACTIVE\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_LOCK\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"BACKGROUND\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\");break;case\"BACKGROUND_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\")}if(\"OFF\"===this._watchState&&void 0!==this._geolocationWatchID)this._clearWatch();else if(void 0===this._geolocationWatchID){var e;this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"true\"),++Zi>1?(e={maximumAge:6e5,timeout:0},Yi=!0):(e=this.options.positionOptions,Yi=!1),this._geolocationWatchID=t.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,e)}}else t.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},n.prototype._clearWatch=function(){t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this.options.showUserLocation&&this._updateMarker(null)},n}(t.Evented),Xi={maxWidth:100,unit:\"metric\"},Ji=function(e){this.options=t.extend({},Xi,e),t.bindAll([\"_onMove\",\"setUnit\"],this)};function Ki(t,e,r){var n=r&&r.maxWidth||100,i=t._container.clientHeight/2,a=t.unproject([0,i]),o=t.unproject([n,i]),s=a.distanceTo(o);if(r&&\"imperial\"===r.unit){var l=3.2808*s;l>5280?$i(e,n,l/5280,t._getUIString(\"ScaleControl.Miles\")):$i(e,n,l,t._getUIString(\"ScaleControl.Feet\"))}else r&&\"nautical\"===r.unit?$i(e,n,s/1852,t._getUIString(\"ScaleControl.NauticalMiles\")):s>=1e3?$i(e,n,s/1e3,t._getUIString(\"ScaleControl.Kilometers\")):$i(e,n,s,t._getUIString(\"ScaleControl.Meters\"))}function $i(t,e,r,n){var i,a,o,s=(i=r,(a=Math.pow(10,(\"\"+Math.floor(i)).length-1))*((o=i/a)>=10?10:o>=5?5:o>=3?3:o>=2?2:o>=1?1:function(t){var e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(o))),l=s/r;t.style.width=e*l+\"px\",t.innerHTML=s+\"&nbsp;\"+n}Ji.prototype.getDefaultPosition=function(){return\"bottom-left\"},Ji.prototype._onMove=function(){Ki(this._map,this._container,this.options)},Ji.prototype.onAdd=function(t){return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-scale\",t.getContainer()),this._map.on(\"move\",this._onMove),this._onMove(),this._container},Ji.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"move\",this._onMove),this._map=void 0},Ji.prototype.setUnit=function(t){this.options.unit=t,Ki(this._map,this._container,this.options)};var Qi=function(e){this._fullscreen=!1,e&&e.container&&(e.container instanceof t.window.HTMLElement?this._container=e.container:t.warnOnce(\"Full screen control 'container' must be a DOM element.\")),t.bindAll([\"_onClickFullscreen\",\"_changeIcon\"],this),\"onfullscreenchange\"in t.window.document?this._fullscreenchange=\"fullscreenchange\":\"onmozfullscreenchange\"in t.window.document?this._fullscreenchange=\"mozfullscreenchange\":\"onwebkitfullscreenchange\"in t.window.document?this._fullscreenchange=\"webkitfullscreenchange\":\"onmsfullscreenchange\"in t.window.document&&(this._fullscreenchange=\"MSFullscreenChange\")};Qi.prototype.onAdd=function(e){return this._map=e,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display=\"none\",t.warnOnce(\"This device does not support fullscreen mode.\")),this._controlContainer},Qi.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,t.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},Qi.prototype._checkFullscreenSupport=function(){return!!(t.window.document.fullscreenEnabled||t.window.document.mozFullScreenEnabled||t.window.document.msFullscreenEnabled||t.window.document.webkitFullscreenEnabled)},Qi.prototype._setupUI=function(){var e=this._fullscreenButton=r.create(\"button\",\"mapboxgl-ctrl-fullscreen\",this._controlContainer);r.create(\"span\",\"mapboxgl-ctrl-icon\",e).setAttribute(\"aria-hidden\",!0),e.type=\"button\",this._updateTitle(),this._fullscreenButton.addEventListener(\"click\",this._onClickFullscreen),t.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},Qi.prototype._updateTitle=function(){var t=this._getTitle();this._fullscreenButton.setAttribute(\"aria-label\",t),this._fullscreenButton.title=t},Qi.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?\"FullscreenControl.Exit\":\"FullscreenControl.Enter\")},Qi.prototype._isFullscreen=function(){return this._fullscreen},Qi.prototype._changeIcon=function(){(t.window.document.fullscreenElement||t.window.document.mozFullScreenElement||t.window.document.webkitFullscreenElement||t.window.document.msFullscreenElement)===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-shrink\"),this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-fullscreen\"),this._updateTitle())},Qi.prototype._onClickFullscreen=function(){this._isFullscreen()?t.window.document.exitFullscreen?t.window.document.exitFullscreen():t.window.document.mozCancelFullScreen?t.window.document.mozCancelFullScreen():t.window.document.msExitFullscreen?t.window.document.msExitFullscreen():t.window.document.webkitCancelFullScreen&&t.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var ta={closeButton:!0,closeOnClick:!0,className:\"\",maxWidth:\"240px\"},ea=function(e){function n(r){e.call(this),this.options=t.extend(Object.create(ta),r),t.bindAll([\"_update\",\"_onClose\",\"remove\",\"_onMouseMove\",\"_onMouseUp\",\"_onDrag\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(e){return this._map&&this.remove(),this._map=e,this.options.closeOnClick&&this._map.on(\"click\",this._onClose),this.options.closeOnMove&&this._map.on(\"move\",this._onClose),this._map.on(\"remove\",this.remove),this._update(),this._trackPointer?(this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"mouseup\",this._onMouseUp),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")):this._map.on(\"move\",this._update),this.fire(new t.Event(\"open\")),this},n.prototype.isOpen=function(){return!!this._map},n.prototype.remove=function(){return this._content&&r.remove(this._content),this._container&&(r.remove(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"move\",this._onClose),this._map.off(\"click\",this._onClose),this._map.off(\"remove\",this.remove),this._map.off(\"mousemove\",this._onMouseMove),this._map.off(\"mouseup\",this._onMouseUp),this._map.off(\"drag\",this._onDrag),delete this._map),this.fire(new t.Event(\"close\")),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on(\"move\",this._update),this._map.off(\"mousemove\",this._onMouseMove),this._container&&this._container.classList.remove(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.remove(\"mapboxgl-track-pointer\")),this},n.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off(\"move\",this._update),this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"drag\",this._onDrag),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")),this},n.prototype.getElement=function(){return this._container},n.prototype.setText=function(e){return this.setDOMContent(t.window.document.createTextNode(e))},n.prototype.setHTML=function(e){var r,n=t.window.document.createDocumentFragment(),i=t.window.document.createElement(\"body\");for(i.innerHTML=e;r=i.firstChild;)n.appendChild(r);return this.setDOMContent(n)},n.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},n.prototype.setMaxWidth=function(t){return this.options.maxWidth=t,this._update(),this},n.prototype.setDOMContent=function(t){return this._createContent(),this._content.appendChild(t),this._update(),this},n.prototype.addClassName=function(t){this._container&&this._container.classList.add(t)},n.prototype.removeClassName=function(t){this._container&&this._container.classList.remove(t)},n.prototype.toggleClassName=function(t){if(this._container)return this._container.classList.toggle(t)},n.prototype._createContent=function(){this._content&&r.remove(this._content),this._content=r.create(\"div\",\"mapboxgl-popup-content\",this._container),this.options.closeButton&&(this._closeButton=r.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.setAttribute(\"aria-label\",\"Close popup\"),this._closeButton.innerHTML=\"&#215;\",this._closeButton.addEventListener(\"click\",this._onClose))},n.prototype._onMouseUp=function(t){this._update(t.point)},n.prototype._onMouseMove=function(t){this._update(t.point)},n.prototype._onDrag=function(t){this._update(t.point)},n.prototype._update=function(t){var e=this,n=this._lngLat||this._trackPointer;if(this._map&&n&&this._content&&(this._container||(this._container=r.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=r.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(\" \").forEach((function(t){return e._container.classList.add(t)})),this._trackPointer&&this._container.classList.add(\"mapboxgl-popup-track-pointer\")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=ji(this._lngLat,this._pos,this._map.transform)),!this._trackPointer||t)){var i=this._pos=this._trackPointer&&t?t:this._map.project(this._lngLat),a=this.options.anchor,o=ra(this.options.offset);if(!a){var s,l=this._container.offsetWidth,u=this._container.offsetHeight;s=i.y+o.bottom.y<u?[\"top\"]:i.y>this._map.transform.height-u?[\"bottom\"]:[],i.x<l/2?s.push(\"left\"):i.x>this._map.transform.width-l/2&&s.push(\"right\"),a=0===s.length?\"bottom\":s.join(\"-\")}var c=i.add(o[a]).round();r.setTransform(this._container,Ui[a]+\" translate(\"+c.x+\"px,\"+c.y+\"px)\"),Vi(this._container,a,\"popup\")}},n.prototype._onClose=function(){this.remove()},n}(t.Evented);function ra(e){if(e){if(\"number\"==typeof e){var r=Math.round(Math.sqrt(.5*Math.pow(e,2)));return{center:new t.Point(0,0),top:new t.Point(0,e),\"top-left\":new t.Point(r,r),\"top-right\":new t.Point(-r,r),bottom:new t.Point(0,-e),\"bottom-left\":new t.Point(r,-r),\"bottom-right\":new t.Point(-r,-r),left:new t.Point(e,0),right:new t.Point(-e,0)}}if(e instanceof t.Point||Array.isArray(e)){var n=t.Point.convert(e);return{center:n,top:n,\"top-left\":n,\"top-right\":n,bottom:n,\"bottom-left\":n,\"bottom-right\":n,left:n,right:n}}return{center:t.Point.convert(e.center||[0,0]),top:t.Point.convert(e.top||[0,0]),\"top-left\":t.Point.convert(e[\"top-left\"]||[0,0]),\"top-right\":t.Point.convert(e[\"top-right\"]||[0,0]),bottom:t.Point.convert(e.bottom||[0,0]),\"bottom-left\":t.Point.convert(e[\"bottom-left\"]||[0,0]),\"bottom-right\":t.Point.convert(e[\"bottom-right\"]||[0,0]),left:t.Point.convert(e.left||[0,0]),right:t.Point.convert(e.right||[0,0])}}return ra(new t.Point(0,0))}var na={version:t.version,supported:e,setRTLTextPlugin:t.setRTLTextPlugin,getRTLTextPluginStatus:t.getRTLTextPluginStatus,Map:zi,NavigationControl:Bi,GeolocateControl:Wi,AttributionControl:Mi,ScaleControl:Ji,FullscreenControl:Qi,Popup:ea,Marker:qi,Style:Ye,LngLat:t.LngLat,LngLatBounds:t.LngLatBounds,Point:t.Point,MercatorCoordinate:t.MercatorCoordinate,Evented:t.Evented,config:t.config,prewarm:function(){jt().acquire(Rt)},clearPrewarmedResources:function(){var t=Bt;t&&(t.isPreloaded()&&1===t.numActive()?(t.release(Rt),Bt=null):console.warn(\"Could not clear WebWorkers since there are active Map instances that still reference it. 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e=[u(t.region,!1)];c.push(e);for(var r=0;r<t.children.length;r++)e.push(h(t.children[r]))}function h(t){for(var e=0;e<t.children.length;e++)f(t.children[e]);return u(t.region,!0)}for(s=0;s<a.children.length;s++)f(a.children[s]);return c.length<=0?{type:\"Polygon\",coordinates:[]}:1==c.length?{type:\"Polygon\",coordinates:c[0]}:{type:\"MultiPolygon\",coordinates:c}}};t.exports=e},87263:function(t,e,r){var n=r(26859);t.exports=function(t,e,r){function i(t,e,n){return{id:r?r.segmentId():-1,start:t,end:e,myFill:{above:n.myFill.above,below:n.myFill.below},otherFill:null}}var a=n.create();function o(t,r){a.insertBefore(t,(function(n){return i=t.isStart,a=t.pt,o=r,s=n.isStart,l=n.pt,u=n.other.pt,(0!==(c=e.pointsCompare(a,l))?c:e.pointsSame(o,u)?0:i!==s?i?1:-1:e.pointAboveOrOnLine(o,s?l:u,s?u:l)?1:-1)<0;var i,a,o,s,l,u,c}))}function s(t,e){var r=function(t,e){var r=n.node({isStart:!0,pt:t.start,seg:t,primary:e,other:null,status:null});return o(r,t.end),r}(t,e);return function(t,e,r){var i=n.node({isStart:!1,pt:e.end,seg:e,primary:r,other:t,status:null});t.other=i,o(i,t.pt)}(r,t,e),r}function l(t,e){var n=i(e,t.seg.end,t.seg);return function(t,e){r&&r.segmentChop(t.seg,e),t.other.remove(),t.seg.end=e,t.other.pt=e,o(t.other,t.pt)}(t,e),s(n,t.primary)}function u(i,o){var s=n.create();function u(t){return s.findTransition((function(r){var n,i,a,o,s,l;return n=t,i=r.ev,a=n.seg.start,o=n.seg.end,s=i.seg.start,l=i.seg.end,(e.pointsCollinear(a,s,l)?e.pointsCollinear(o,s,l)||e.pointAboveOrOnLine(o,s,l)?1:-1:e.pointAboveOrOnLine(a,s,l)?1:-1)>0}))}function c(t,n){var i=t.seg,a=n.seg,o=i.start,s=i.end,u=a.start,c=a.end;r&&r.checkIntersection(i,a);var f=e.linesIntersect(o,s,u,c);if(!1===f){if(!e.pointsCollinear(o,s,u))return!1;if(e.pointsSame(o,c)||e.pointsSame(s,u))return!1;var h=e.pointsSame(o,u),p=e.pointsSame(s,c);if(h&&p)return n;var d=!h&&e.pointBetween(o,u,c),v=!p&&e.pointBetween(s,u,c);if(h)return v?l(n,s):l(t,c),n;d&&(p||(v?l(n,s):l(t,c)),l(n,o))}else 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a=n[t],o=n[i],s=a[a.length-1],l=a[a.length-2],u=o[0],c=o[1];e.pointsCollinear(l,s,u)&&(r&&r.chainRemoveTail(t,s),a.pop(),s=l),e.pointsCollinear(s,u,c)&&(r&&r.chainRemoveHead(i,u),o.shift()),r&&r.chainJoin(t,i),n[t]=a.concat(o),n.splice(i,1)}})),i}},55968:function(t){function e(t,e,r){var n=[];return t.forEach((function(t){var i=(t.myFill.above?8:0)+(t.myFill.below?4:0)+(t.otherFill&&t.otherFill.above?2:0)+(t.otherFill&&t.otherFill.below?1:0);0!==e[i]&&n.push({id:r?r.segmentId():-1,start:t.start,end:t.end,myFill:{above:1===e[i],below:2===e[i]},otherFill:null})})),r&&r.selected(n),n}var r={union:function(t,r){return e(t,[0,2,1,0,2,2,0,0,1,0,1,0,0,0,0,0],r)},intersect:function(t,r){return e(t,[0,0,0,0,0,2,0,2,0,0,1,1,0,2,1,0],r)},difference:function(t,r){return e(t,[0,0,0,0,2,0,2,0,1,1,0,0,0,1,2,0],r)},differenceRev:function(t,r){return e(t,[0,2,1,0,0,0,1,1,0,2,0,2,0,0,0,0],r)},xor:function(t,r){return e(t,[0,2,1,0,2,0,0,1,1,0,0,2,0,1,2,0],r)}};t.exports=r},14847:function(t,e,r){\"use 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t&&(t=x[t]),null!=t&&t&&t.count&&t.color&&t.opacity&&t.positions&&t.positions.length>1&&(t.scaleRatio=[t.scale[0]*t.viewport.width,t.scale[1]*t.viewport.height],r(t),t.after&&t.after(t))}function T(t){if(t){null!=t.length?\"number\"==typeof t[0]&&(t=[{positions:t}]):Array.isArray(t)||(t=[t]);var e=0,r=0;if(b.groups=x=t.map((function(t,u){var c=x[u];return t?(\"function\"==typeof t?t={after:t}:\"number\"==typeof t[0]&&(t={positions:t}),t=o(t,{color:\"color colors fill\",capSize:\"capSize cap capsize cap-size\",lineWidth:\"lineWidth line-width width line thickness\",opacity:\"opacity alpha\",range:\"range dataBox\",viewport:\"viewport viewBox\",errors:\"errors error\",positions:\"positions position data points\"}),c||(x[u]=c={id:u,scale:null,translate:null,scaleFract:null,translateFract:null,draw:!0},t=s({},m,t)),a(c,t,[{lineWidth:function(t){return.5*+t},capSize:function(t){return.5*+t},opacity:parseFloat,errors:function(t){return t=l(t),r+=t.length,t},positions:function(t,r){return t=l(t,\"float64\"),r.count=Math.floor(t.length/2),r.bounds=n(t,2),r.offset=e,e+=r.count,t}},{color:function(t,e){var r=e.count;if(t||(t=\"transparent\"),!Array.isArray(t)||\"number\"==typeof t[0]){var n=t;t=Array(r);for(var a=0;a<r;a++)t[a]=n}if(t.length<r)throw Error(\"Not enough colors\");for(var o=new Uint8Array(4*r),s=0;s<r;s++){var l=i(t[s],\"uint8\");o.set(l,4*s)}return o},range:function(t,e,r){var n=e.bounds;return t||(t=n),e.scale=[1/(t[2]-t[0]),1/(t[3]-t[1])],e.translate=[-t[0],-t[1]],e.scaleFract=f(e.scale),e.translateFract=f(e.translate),t},viewport:function(t){var e;return Array.isArray(t)?e={x:t[0],y:t[1],width:t[2]-t[0],height:t[3]-t[1]}:t?(e={x:t.x||t.left||0,y:t.y||t.top||0},t.right?e.width=t.right-e.x:e.width=t.w||t.width||0,t.bottom?e.height=t.bottom-e.y:e.height=t.h||t.height||0):e={x:0,y:0,width:y.drawingBufferWidth,height:y.drawingBufferHeight},e}}]),c):c})),e||r){var h=x.reduce((function(t,e,r){return t+(e?e.count:0)}),0),g=new Float64Array(2*h),_=new Uint8Array(4*h),w=new Float32Array(4*h);x.forEach((function(t,e){if(t){var r=t.positions,n=t.count,i=t.offset,a=t.color,o=t.errors;n&&(_.set(a,4*i),w.set(o,4*i),g.set(r,2*i))}}));var T=c(g);u(T);var k=f(g,T);p(k),d(_),v(w)}}}function k(){u.destroy(),p.destroy(),d.destroy(),v.destroy(),g.destroy()}};var h=[[1,0,0,1,0,0],[1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,1,0,0],[1,0,0,1,0,0],[1,0,-1,0,0,1],[1,0,-1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,1],[1,0,-1,0,0,1],[-1,0,-1,0,0,1],[-1,0,-1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,1],[-1,0,-1,0,0,1],[0,1,1,0,0,0],[0,1,-1,0,0,0],[0,-1,-1,0,0,0],[0,-1,-1,0,0,0],[0,1,1,0,0,0],[0,-1,1,0,0,0],[0,1,0,-1,1,0],[0,1,0,-1,-1,0],[0,1,0,1,-1,0],[0,1,0,1,1,0],[0,1,0,-1,1,0],[0,1,0,1,-1,0],[0,-1,0,-1,1,0],[0,-1,0,-1,-1,0],[0,-1,0,1,-1,0],[0,-1,0,1,1,0],[0,-1,0,-1,1,0],[0,-1,0,1,-1,0]]},46075:function(t,e,r){\"use strict\";var n=r(25075),i=r(21527),a=r(56131),o=r(56068),s=r(71299),l=r(30120),u=r(11474),c=r(54),f=r(57060),h=f.float32,p=f.fract32,d=r(83522),v=r(18863),g=r(6851);function y(t,e){if(!(this instanceof y))return new y(t,e);if(\"function\"==typeof t?(e||(e={}),e.regl=t):e=t,e.length&&(e.positions=e),!(t=e.regl).hasExtension(\"ANGLE_instanced_arrays\"))throw Error(\"regl-error2d: `ANGLE_instanced_arrays` extension should be enabled\");this.gl=t._gl,this.regl=t,this.passes=[],this.shaders=y.shaders.has(t)?y.shaders.get(t):y.shaders.set(t,y.createShaders(t)).get(t),this.update(e)}t.exports=y,y.dashMult=2,y.maxPatternLength=256,y.precisionThreshold=3e6,y.maxPoints=1e4,y.maxLines=2048,y.shaders=new d,y.createShaders=function(t){var e,r=t.buffer({usage:\"static\",type:\"float\",data:[0,1,0,0,1,1,1,0]}),n={primitive:\"triangle strip\",instances:t.prop(\"count\"),count:4,offset:0,uniforms:{miterMode:function(t,e){return\"round\"===e.join?2:1},miterLimit:t.prop(\"miterLimit\"),scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),thickness:t.prop(\"thickness\"),dashTexture:t.prop(\"dashTexture\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),dashLength:t.prop(\"dashLength\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]},depth:t.prop(\"depth\")},blend:{enable:!0,color:[0,0,0,0],equation:{rgb:\"add\",alpha:\"add\"},func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},depth:{enable:function(t,e){return!e.overlay}},stencil:{enable:!1},scissor:{enable:!0,box:t.prop(\"viewport\")},viewport:t.prop(\"viewport\")},i=t(a({vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, aCoordFract, bCoordFract;\\nattribute vec4 color;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvec2 project(vec2 position, vec2 positionFract, vec2 scale, vec2 scaleFract, vec2 translate, vec2 translateFract) {\\n\\t// the order is important\\n\\treturn position * scale + translate\\n       + positionFract * scale + translateFract\\n       + position * scaleFract\\n       + positionFract * scaleFract;\\n}\\n\\nvoid main() {\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineOffset = lineTop * 2. - 1.;\\n\\n\\tvec2 diff = (bCoord + bCoordFract - aCoord - aCoordFract);\\n\\ttangent = normalize(diff * scale * viewport.zw);\\n\\tvec2 normal = vec2(-tangent.y, tangent.x);\\n\\n\\tvec2 position = project(aCoord, aCoordFract, scale, scaleFract, translate, translateFract) * lineStart\\n\\t\\t+ project(bCoord, bCoordFract, scale, scaleFract, translate, translateFract) * lineEnd\\n\\n\\t\\t+ thickness * normal * .5 * lineOffset / viewport.zw;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform float dashLength, pixelRatio, thickness, opacity, id;\\nuniform sampler2D dashTexture;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvoid main() {\\n\\tfloat alpha = 1.;\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashLength) * .5 + .25;\\n\\tfloat dash = texture2D(dashTexture, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},aCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8,divisor:1},bCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:16,divisor:1},color:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1}}},n));try{e=t(a({cull:{enable:!0,face:\"back\"},vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, nextCoord, prevCoord;\\nattribute vec4 aColor, bColor;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, translate;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\nuniform float miterLimit, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 tangent;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nconst float REVERSE_THRESHOLD = -.875;\\nconst float MIN_DIFF = 1e-6;\\n\\n// TODO: possible optimizations: avoid overcalculating all for vertices and calc just one instead\\n// TODO: precalculate dot products, normalize things beforehead etc.\\n// TODO: refactor to rectangular algorithm\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nbool isNaN( float val ){\\n  return ( val < 0.0 || 0.0 < val || val == 0.0 ) ? false : true;\\n}\\n\\nvoid main() {\\n\\tvec2 aCoord = aCoord, bCoord = bCoord, prevCoord = prevCoord, nextCoord = nextCoord;\\n\\n  vec2 adjustedScale;\\n  adjustedScale.x = (abs(scale.x) < MIN_DIFF) ? MIN_DIFF : scale.x;\\n  adjustedScale.y = (abs(scale.y) < MIN_DIFF) ? MIN_DIFF : scale.y;\\n\\n  vec2 scaleRatio = adjustedScale * viewport.zw;\\n\\tvec2 normalWidth = thickness / scaleRatio;\\n\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineBot = 1. - lineTop;\\n\\n\\tfragColor = (lineStart * aColor + lineEnd * bColor) / 255.;\\n\\n\\tif (isNaN(aCoord.x) || isNaN(aCoord.y) || isNaN(bCoord.x) || isNaN(bCoord.y)) return;\\n\\n\\tif (aCoord == prevCoord) prevCoord = aCoord + normalize(bCoord - aCoord);\\n\\tif (bCoord == nextCoord) nextCoord = bCoord - normalize(bCoord - aCoord);\\n\\n\\tvec2 prevDiff = aCoord - prevCoord;\\n\\tvec2 currDiff = bCoord - aCoord;\\n\\tvec2 nextDiff = nextCoord - bCoord;\\n\\n\\tvec2 prevTangent = normalize(prevDiff * scaleRatio);\\n\\tvec2 currTangent = normalize(currDiff * scaleRatio);\\n\\tvec2 nextTangent = normalize(nextDiff * scaleRatio);\\n\\n\\tvec2 prevNormal = vec2(-prevTangent.y, prevTangent.x);\\n\\tvec2 currNormal = vec2(-currTangent.y, currTangent.x);\\n\\tvec2 nextNormal = vec2(-nextTangent.y, nextTangent.x);\\n\\n\\tvec2 startJoinDirection = normalize(prevTangent - currTangent);\\n\\tvec2 endJoinDirection = normalize(currTangent - nextTangent);\\n\\n\\t// collapsed/unidirectional segment cases\\n\\t// FIXME: there should be more elegant solution\\n\\tvec2 prevTanDiff = abs(prevTangent - currTangent);\\n\\tvec2 nextTanDiff = abs(nextTangent - currTangent);\\n\\tif (max(prevTanDiff.x, prevTanDiff.y) < MIN_DIFF) {\\n\\t\\tstartJoinDirection = currNormal;\\n\\t}\\n\\tif (max(nextTanDiff.x, nextTanDiff.y) < MIN_DIFF) {\\n\\t\\tendJoinDirection = currNormal;\\n\\t}\\n\\tif (aCoord == bCoord) {\\n\\t\\tendJoinDirection = startJoinDirection;\\n\\t\\tcurrNormal = prevNormal;\\n\\t\\tcurrTangent = prevTangent;\\n\\t}\\n\\n\\ttangent = currTangent;\\n\\n\\t//calculate join shifts relative to normals\\n\\tfloat startJoinShift = dot(currNormal, startJoinDirection);\\n\\tfloat endJoinShift = dot(currNormal, endJoinDirection);\\n\\n\\tfloat startMiterRatio = abs(1. / startJoinShift);\\n\\tfloat endMiterRatio = abs(1. / endJoinShift);\\n\\n\\tvec2 startJoin = startJoinDirection * startMiterRatio;\\n\\tvec2 endJoin = endJoinDirection * endMiterRatio;\\n\\n\\tvec2 startTopJoin, startBotJoin, endTopJoin, endBotJoin;\\n\\tstartTopJoin = sign(startJoinShift) * startJoin * .5;\\n\\tstartBotJoin = -startTopJoin;\\n\\n\\tendTopJoin = sign(endJoinShift) * endJoin * .5;\\n\\tendBotJoin = -endTopJoin;\\n\\n\\tvec2 aTopCoord = aCoord + normalWidth * startTopJoin;\\n\\tvec2 bTopCoord = bCoord + normalWidth * endTopJoin;\\n\\tvec2 aBotCoord = aCoord + normalWidth * startBotJoin;\\n\\tvec2 bBotCoord = bCoord + normalWidth * endBotJoin;\\n\\n\\t//miter anti-clipping\\n\\tfloat baClipping = distToLine(bCoord, aCoord, aBotCoord) / dot(normalize(normalWidth * endBotJoin), normalize(normalWidth.yx * vec2(-startBotJoin.y, startBotJoin.x)));\\n\\tfloat abClipping = distToLine(aCoord, bCoord, bTopCoord) / dot(normalize(normalWidth * startBotJoin), normalize(normalWidth.yx * vec2(-endBotJoin.y, endBotJoin.x)));\\n\\n\\t//prevent close to reverse direction switch\\n\\tbool prevReverse = dot(currTangent, prevTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, prevNormal)) * min(length(prevDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\tbool nextReverse = dot(currTangent, nextTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, nextNormal)) * min(length(nextDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\n\\tif (prevReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * startJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / startMiterRatio, 1.);\\n\\t\\taBotCoord = aCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\taTopCoord = aCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!nextReverse && baClipping > 0. && baClipping < length(normalWidth * endBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\tbTopCoord -= normalWidth * endTopJoin;\\n\\t\\tbTopCoord += normalize(endTopJoin * normalWidth) * baClipping;\\n\\t}\\n\\n\\tif (nextReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * endJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / endMiterRatio, 1.);\\n\\t\\tbBotCoord = bCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\tbTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\taBotCoord -= normalWidth * startBotJoin;\\n\\t\\taBotCoord += normalize(startBotJoin * normalWidth) * abClipping;\\n\\t}\\n\\n\\tvec2 aTopPosition = (aTopCoord) * adjustedScale + translate;\\n\\tvec2 aBotPosition = (aBotCoord) * adjustedScale + translate;\\n\\n\\tvec2 bTopPosition = (bTopCoord) * adjustedScale + translate;\\n\\tvec2 bBotPosition = (bBotCoord) * adjustedScale + translate;\\n\\n\\t//position is normalized 0..1 coord on the screen\\n\\tvec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * lineBot) * lineEnd;\\n\\n\\tstartCoord = aCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\tendCoord = bCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\n\\tgl_Position = vec4(position  * 2.0 - 1.0, depth, 1);\\n\\n\\tenableStartMiter = step(dot(currTangent, prevTangent), .5);\\n\\tenableEndMiter = step(dot(currTangent, nextTangent), .5);\\n\\n\\t//bevel miter cutoffs\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n\\n\\t//round miter cutoffs\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * abs(dot(startJoinDirection, currNormal)) * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * abs(dot(endJoinDirection, currNormal)) * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform float dashLength, pixelRatio, thickness, opacity, id, miterMode;\\nuniform sampler2D dashTexture;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nvoid main() {\\n\\tfloat alpha = 1., distToStart, distToEnd;\\n\\tfloat cutoff = thickness * .5;\\n\\n\\t//bevel miter\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToStart + 1., 0.), 1.);\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToEnd + 1., 0.), 1.);\\n\\t\\t}\\n\\t}\\n\\n\\t// round miter\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - startCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - endCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashLength) * .5 + .25;\\n\\tfloat dash = texture2D(dashTexture, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * 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main() {\\n\\tfloat depth = (MAX_LINES - 4. - id) / (MAX_LINES);\\n\\n\\tvec2 position = position * scale + translate\\n       + positionFract * scale + translateFract\\n       + position * scaleFract\\n       + positionFract * scaleFract;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n\\tfragColor.a *= opacity;\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n\\tgl_FragColor = 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t=this,e=[],r=arguments.length;r--;)e[r]=arguments[r];return(e.length?e:this.passes).forEach((function(e,r){var n;if(e&&Array.isArray(e))return(n=t).draw.apply(n,e);\"number\"==typeof e&&(e=t.passes[e]),e&&e.count>1&&e.opacity&&(t.regl._refresh(),e.fill&&e.triangles&&e.triangles.length>2&&t.shaders.fill(e),e.thickness&&(e.scale[0]*e.viewport.width>y.precisionThreshold||e.scale[1]*e.viewport.height>y.precisionThreshold||\"rect\"===e.join||!e.join&&(e.thickness<=2||e.count>=y.maxPoints)?t.shaders.rect(e):t.shaders.miter(e)))})),this},y.prototype.update=function(t){var e=this;if(t){null!=t.length?\"number\"==typeof t[0]&&(t=[{positions:t}]):Array.isArray(t)||(t=[t]);var r=this.regl,o=this.gl;if(t.forEach((function(t,f){var d=e.passes[f];if(void 0!==t)if(null!==t){if(\"number\"==typeof t[0]&&(t={positions:t}),t=s(t,{positions:\"positions points data coords\",thickness:\"thickness lineWidth lineWidths line-width linewidth width stroke-width strokewidth strokeWidth\",join:\"lineJoin linejoin 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Uint8Array})},t=a({},y.defaults,t)),null!=t.thickness&&(d.thickness=parseFloat(t.thickness)),null!=t.opacity&&(d.opacity=parseFloat(t.opacity)),null!=t.miterLimit&&(d.miterLimit=parseFloat(t.miterLimit)),null!=t.overlay&&(d.overlay=!!t.overlay,f<y.maxLines&&(d.depth=2*(y.maxLines-1-f%y.maxLines)/y.maxLines-1)),null!=t.join&&(d.join=t.join),null!=t.hole&&(d.hole=t.hole),null!=t.fill&&(d.fill=t.fill?n(t.fill,\"uint8\"):null),null!=t.viewport&&(d.viewport=v(t.viewport)),d.viewport||(d.viewport=v([o.drawingBufferWidth,o.drawingBufferHeight])),null!=t.close&&(d.close=t.close),null===t.positions&&(t.positions=[]),t.positions){var m,x;if(t.positions.x&&t.positions.y){var b=t.positions.x,_=t.positions.y;x=d.count=Math.max(b.length,_.length),m=new Float64Array(2*x);for(var w=0;w<x;w++)m[2*w]=b[w],m[2*w+1]=_[w]}else m=l(t.positions,\"float64\"),x=d.count=Math.floor(m.length/2);var T=d.bounds=i(m,2);if(d.fill){for(var k=[],A={},M=0,S=0,E=0,L=d.count;S<L;S++){var C=m[2*S],P=m[2*S+1];isNaN(C)||isNaN(P)||null==C||null==P?(C=m[2*M],P=m[2*M+1],A[S]=M):M=S,k[E++]=C,k[E++]=P}if(t.splitNull){d.count-1 in A||(A[d.count]=d.count-1);var O=Object.keys(A).map(Number).sort((function(t,e){return t-e})),I=[],D=0,z=null!=d.hole?d.hole[0]:null;if(null!=z){var R=g(O,(function(t){return t>=z}));(O=O.slice(0,R)).push(z)}for(var F=function(t){var e=k.slice(2*D,2*O[t]).concat(z?k.slice(2*z):[]),r=(d.hole||[]).map((function(e){return e-z+(O[t]-D)})),n=u(e,r);n=n.map((function(e){return e+D+(e+D<O[t]?0:z-O[t])})),I.push.apply(I,n),D=O[t]+1},B=0;B<O.length;B++)F(B);for(var N=0,j=I.length;N<j;N++)null!=A[I[N]]&&(I[N]=A[I[N]]);d.triangles=I}else{for(var U=u(k,d.hole||[]),V=0,H=U.length;V<H;V++)null!=A[U[V]]&&(U[V]=A[U[V]]);d.triangles=U}}var q=new Float64Array(m);c(q,2,T);var G=new Float64Array(2*x+6);d.close?m[0]===m[2*x-2]&&m[1]===m[2*x-1]?(G[0]=q[2*x-4],G[1]=q[2*x-3]):(G[0]=q[2*x-2],G[1]=q[2*x-1]):(G[0]=q[0],G[1]=q[1]),G.set(q,2),d.close?m[0]===m[2*x-2]&&m[1]===m[2*x-1]?(G[2*x+2]=q[2],G[2*x+3]=q[3],d.count-=1):(G[2*x+2]=q[0],G[2*x+3]=q[1],G[2*x+4]=q[2],G[2*x+5]=q[3]):(G[2*x+2]=q[2*x-2],G[2*x+3]=q[2*x-1],G[2*x+4]=q[2*x-2],G[2*x+5]=q[2*x-1]);var Z=h(G);d.positionBuffer(Z);var Y=p(G,Z);d.positionFractBuffer(Y)}if(t.range?d.range=t.range:d.range||(d.range=d.bounds),(t.range||t.positions)&&d.count){var W=d.bounds,X=W[2]-W[0],J=W[3]-W[1],K=d.range[2]-d.range[0],$=d.range[3]-d.range[1];d.scale=[X/K,J/$],d.translate=[-d.range[0]/K+W[0]/K||0,-d.range[1]/$+W[1]/$||0],d.scaleFract=p(d.scale),d.translateFract=p(d.translate)}if(t.dashes){var Q,tt=0;if(!t.dashes||t.dashes.length<2)tt=1,Q=new Uint8Array([255,255,255,255,255,255,255,255]);else{tt=0;for(var et=0;et<t.dashes.length;++et)tt+=t.dashes[et];Q=new Uint8Array(tt*y.dashMult);for(var rt=0,nt=255,it=0;it<2;it++)for(var at=0;at<t.dashes.length;++at){for(var ot=0,st=t.dashes[at]*y.dashMult*.5;ot<st;++ot)Q[rt++]=nt;nt^=255}}d.dashLength=tt,d.dashTexture({channels:1,data:Q,width:Q.length,height:1,mag:\"linear\",min:\"linear\"},0,0)}if(t.color){var lt=d.count,ut=t.color;ut||(ut=\"transparent\");var ct=new Uint8Array(4*lt+4);if(Array.isArray(ut)&&\"number\"!=typeof ut[0]){for(var ft=0;ft<lt;ft++){var ht=n(ut[ft],\"uint8\");ct.set(ht,4*ft)}ct.set(n(ut[0],\"uint8\"),4*lt)}else for(var pt=n(ut,\"uint8\"),dt=0;dt<lt+1;dt++)ct.set(pt,4*dt);d.colorBuffer({usage:\"dynamic\",type:\"uint8\",data:ct})}}else e.passes[f]=null})),t.length<this.passes.length){for(var f=t.length;f<this.passes.length;f++){var d=this.passes[f];d&&(d.colorBuffer.destroy(),d.positionBuffer.destroy(),d.dashTexture.destroy())}this.passes.length=t.length}for(var m=[],x=0;x<this.passes.length;x++)null!==this.passes[x]&&m.push(this.passes[x]);return this.passes=m,this}},y.prototype.destroy=function(){return this.passes.forEach((function(t){t.colorBuffer.destroy(),t.positionBuffer.destroy(),t.dashTexture.destroy()})),this.passes.length=0,this}},11870:function(t,e,r){\"use strict\";function n(t,e){return function(t){if(Array.isArray(t))return t}(t)||function(t,e){var r=null==t?null:\"undefined\"!=typeof Symbol&&t[Symbol.iterator]||t[\"@@iterator\"];if(null!=r){var n,i,a,o,s=[],l=!0,u=!1;try{if(a=(r=r.call(t)).next,0===e){if(Object(r)!==r)return;l=!1}else for(;!(l=(n=a.call(r)).done)&&(s.push(n.value),s.length!==e);l=!0);}catch(t){u=!0,i=t}finally{try{if(!l&&null!=r.return&&(o=r.return(),Object(o)!==o))return}finally{if(u)throw i}}return s}}(t,e)||i(t,e)||function(){throw new TypeError(\"Invalid attempt to destructure non-iterable instance.\\nIn order to be iterable, non-array objects must have a [Symbol.iterator]() method.\")}()}function i(t,e){if(t){if(\"string\"==typeof t)return a(t,e);var r=Object.prototype.toString.call(t).slice(8,-1);return\"Object\"===r&&t.constructor&&(r=t.constructor.name),\"Map\"===r||\"Set\"===r?Array.from(t):\"Arguments\"===r||/^(?:Ui|I)nt(?:8|16|32)(?:Clamped)?Array$/.test(r)?a(t,e):void 0}}function a(t,e){(null==e||e>t.length)&&(e=t.length);for(var r=0,n=new Array(e);r<e;r++)n[r]=t[r];return n}var o=r(25075),s=r(21527),l=r(6475),u=r(88294),c=r(56131),f=r(56068),h=r(71299),p=r(93447),d=r(30120),v=r(62683),g=r(57060),y=r(18863),m=x;function x(t,e){var r=this;if(!(this instanceof x))return new x(t,e);\"function\"==typeof t?(e||(e={}),e.regl=t):(e=t,t=null),e&&e.length&&(e.positions=e);var n,i=(t=e.regl)._gl,a=[];this.tooManyColors=v,n=t.texture({data:new Uint8Array(1020),width:255,height:1,type:\"uint8\",format:\"rgba\",wrapS:\"clamp\",wrapT:\"clamp\",mag:\"nearest\",min:\"nearest\"}),c(this,{regl:t,gl:i,groups:[],markerCache:[null],markerTextures:[null],palette:a,paletteIds:{},paletteTexture:n,maxColors:255,maxSize:100,canvas:i.canvas}),this.update(e);var o={uniforms:{constPointSize:!!e.constPointSize,opacity:t.prop(\"opacity\"),paletteSize:function(t,e){return[r.tooManyColors?0:255,n.height]},pixelRatio:t.context(\"pixelRatio\"),scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translate:t.prop(\"translate\"),translateFract:t.prop(\"translateFract\"),markerTexture:t.prop(\"markerTexture\"),paletteTexture:n},attributes:{x:function(t,e){return e.xAttr||{buffer:e.positionBuffer,stride:8,offset:0}},y:function(t,e){return e.yAttr||{buffer:e.positionBuffer,stride:8,offset:4}},xFract:function(t,e){return e.xAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:0}},yFract:function(t,e){return e.yAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:4}},size:function(t,e){return e.size.length?{buffer:e.sizeBuffer,stride:2,offset:0}:{constant:[Math.round(255*e.size/r.maxSize)]}},borderSize:function(t,e){return e.borderSize.length?{buffer:e.sizeBuffer,stride:2,offset:1}:{constant:[Math.round(255*e.borderSize/r.maxSize)]}},colorId:function(t,e){return e.color.length?{buffer:e.colorBuffer,stride:r.tooManyColors?8:4,offset:0}:{constant:r.tooManyColors?a.slice(4*e.color,4*e.color+4):[e.color]}},borderColorId:function(t,e){return e.borderColor.length?{buffer:e.colorBuffer,stride:r.tooManyColors?8:4,offset:r.tooManyColors?4:2}:{constant:r.tooManyColors?a.slice(4*e.borderColor,4*e.borderColor+4):[e.borderColor]}},isActive:function(t,e){return!0===e.activation?{constant:[1]}:e.activation?e.activation:{constant:[0]}}},blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},scissor:{enable:!0,box:t.prop(\"viewport\")},viewport:t.prop(\"viewport\"),stencil:{enable:!1},depth:{enable:!1},elements:t.prop(\"elements\"),count:t.prop(\"count\"),offset:t.prop(\"offset\"),primitive:\"points\"},s=c({},o);s.frag=f([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform float opacity;\\nuniform sampler2D markerTexture;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragWidth, fragBorderColorLevel, fragColorLevel;\\n\\nfloat smoothStep(float x, float y) {\\n  return 1.0 / (1.0 + exp(50.0*(x - y)));\\n}\\n\\nvoid main() {\\n  float dist = texture2D(markerTexture, gl_PointCoord).r, delta = fragWidth;\\n\\n  // max-distance alpha\\n  if (dist < 0.003) discard;\\n\\n  // null-border case\\n  if (fragBorderColorLevel == fragColorLevel || fragBorderColor.a == 0.) {\\n    float colorAmt = smoothstep(.5 - delta, .5 + delta, dist);\\n    gl_FragColor = vec4(fragColor.rgb, colorAmt * fragColor.a * opacity);\\n  }\\n  else {\\n    float borderColorAmt = smoothstep(fragBorderColorLevel - delta, fragBorderColorLevel + delta, dist);\\n    float colorAmt = smoothstep(fragColorLevel - delta, fragColorLevel + delta, dist);\\n\\n    vec4 color = fragBorderColor;\\n    color.a *= borderColorAmt;\\n    color = mix(color, fragColor, colorAmt);\\n    color.a *= opacity;\\n\\n    gl_FragColor = color;\\n  }\\n\\n}\\n\"]),s.vert=f([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, borderSize;\\nattribute vec4 colorId, borderColorId;\\nattribute float isActive;\\n\\nuniform bool constPointSize;\\nuniform float pixelRatio;\\nuniform vec2 scale, scaleFract, translate, translateFract, paletteSize;\\nuniform sampler2D paletteTexture;\\n\\nconst float maxSize = 100.;\\nconst float borderLevel = .5;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragPointSize, fragBorderRadius, fragWidth, fragBorderColorLevel, fragColorLevel;\\n\\nfloat pointSizeScale = (constPointSize) ? 2. : pixelRatio;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n  return isDirect ? id / 255. : texture2D(paletteTexture,\\n    vec2(\\n      (id.x + .5) / paletteSize.x,\\n      (id.y + .5) / paletteSize.y\\n    )\\n  );\\n}\\n\\nvoid main() {\\n  // ignore inactive points\\n  if (isActive == 0.) return;\\n\\n  vec2 position = vec2(x, y);\\n  vec2 positionFract = vec2(xFract, yFract);\\n\\n  vec4 color = getColor(colorId);\\n  vec4 borderColor = getColor(borderColorId);\\n\\n  float size = size * maxSize / 255.;\\n  float borderSize = borderSize * maxSize / 255.;\\n\\n  gl_PointSize = 2. * size * pointSizeScale;\\n  fragPointSize = size * pixelRatio;\\n\\n  vec2 pos = (position + translate) * scale\\n      + (positionFract + translateFract) * scale\\n      + (position + translate) * scaleFract\\n      + (positionFract + translateFract) * scaleFract;\\n\\n  gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n  fragColor = color;\\n  fragBorderColor = borderColor;\\n  fragWidth = 1. / gl_PointSize;\\n\\n  fragBorderColorLevel = clamp(borderLevel - borderLevel * borderSize / size, 0., 1.);\\n  fragColorLevel = clamp(borderLevel + (1. - borderLevel) * borderSize / size, 0., 1.);\\n}\"]),this.drawMarker=t(s);var l=c({},o);l.frag=f([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragBorderRadius, fragWidth;\\n\\nuniform float opacity;\\n\\nfloat smoothStep(float edge0, float edge1, float x) {\\n\\tfloat t;\\n\\tt = clamp((x - edge0) / (edge1 - edge0), 0.0, 1.0);\\n\\treturn t * t * (3.0 - 2.0 * t);\\n}\\n\\nvoid main() {\\n\\tfloat radius, alpha = 1.0, delta = fragWidth;\\n\\n\\tradius = length(2.0 * gl_PointCoord.xy - 1.0);\\n\\n\\tif (radius > 1.0 + delta) {\\n\\t\\tdiscard;\\n\\t}\\n\\n\\talpha -= smoothstep(1.0 - delta, 1.0 + delta, radius);\\n\\n\\tfloat borderRadius = fragBorderRadius;\\n\\tfloat ratio = smoothstep(borderRadius - delta, borderRadius + delta, radius);\\n\\tvec4 color = mix(fragColor, fragBorderColor, ratio);\\n\\tcolor.a *= alpha * opacity;\\n\\tgl_FragColor = color;\\n}\\n\"]),l.vert=f([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, borderSize;\\nattribute vec4 colorId, borderColorId;\\nattribute float isActive;\\n\\nuniform bool constPointSize;\\nuniform float pixelRatio;\\nuniform vec2 paletteSize, scale, scaleFract, translate, translateFract;\\nuniform sampler2D paletteTexture;\\n\\nconst float maxSize = 100.;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragBorderRadius, fragWidth;\\n\\nfloat pointSizeScale = (constPointSize) ? 2. : pixelRatio;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n  return isDirect ? id / 255. : texture2D(paletteTexture,\\n    vec2(\\n      (id.x + .5) / paletteSize.x,\\n      (id.y + .5) / paletteSize.y\\n    )\\n  );\\n}\\n\\nvoid main() {\\n  // ignore inactive points\\n  if (isActive == 0.) return;\\n\\n  vec2 position = vec2(x, y);\\n  vec2 positionFract = vec2(xFract, yFract);\\n\\n  vec4 color = getColor(colorId);\\n  vec4 borderColor = getColor(borderColorId);\\n\\n  float size = size * maxSize / 255.;\\n  float borderSize = borderSize * maxSize / 255.;\\n\\n  gl_PointSize = (size + borderSize) * pointSizeScale;\\n\\n  vec2 pos = (position + translate) * scale\\n      + (positionFract + translateFract) * scale\\n      + (position + translate) * scaleFract\\n      + (positionFract + translateFract) * scaleFract;\\n\\n  gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n  fragBorderRadius = 1. - 2. * borderSize / (size + borderSize);\\n  fragColor = color;\\n  fragBorderColor = borderColor.a == 0. || borderSize == 0. ? vec4(color.rgb, 0.) : borderColor;\\n  fragWidth = 1. / gl_PointSize;\\n}\\n\"]),v&&(l.frag=l.frag.replace(\"smoothstep\",\"smoothStep\"),s.frag=s.frag.replace(\"smoothstep\",\"smoothStep\")),this.drawCircle=t(l)}x.defaults={color:\"black\",borderColor:\"transparent\",borderSize:0,size:12,opacity:1,marker:void 0,viewport:null,range:null,pixelSize:null,count:0,offset:0,bounds:null,positions:[],snap:1e4},x.prototype.render=function(){return arguments.length&&this.update.apply(this,arguments),this.draw(),this},x.prototype.draw=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];var i=this.groups;if(1===r.length&&Array.isArray(r[0])&&(null===r[0][0]||Array.isArray(r[0][0]))&&(r=r[0]),this.regl._refresh(),r.length)for(var a=0;a<r.length;a++)this.drawItem(a,r[a]);else i.forEach((function(e,r){t.drawItem(r)}));return this},x.prototype.drawItem=function(t,e){var r,n=this.groups,o=n[t];if(\"number\"==typeof e&&(t=e,o=n[e],e=null),o&&o.count&&o.opacity){o.activation[0]&&this.drawCircle(this.getMarkerDrawOptions(0,o,e));for(var s=[],l=1;l<o.activation.length;l++)o.activation[l]&&(!0===o.activation[l]||o.activation[l].data.length)&&s.push.apply(s,function(t){if(Array.isArray(t))return a(t)}(r=this.getMarkerDrawOptions(l,o,e))||function(t){if(\"undefined\"!=typeof Symbol&&null!=t[Symbol.iterator]||null!=t[\"@@iterator\"])return Array.from(t)}(r)||i(r)||function(){throw new TypeError(\"Invalid attempt to spread non-iterable instance.\\nIn order to be iterable, non-array objects must have a [Symbol.iterator]() method.\")}());s.length&&this.drawMarker(s)}},x.prototype.getMarkerDrawOptions=function(t,e,r){var i=e.range,a=e.tree,o=e.viewport,s=e.activation,l=e.selectionBuffer,u=e.count;if(this.regl,!a)return r?[c({},e,{markerTexture:this.markerTextures[t],activation:s[t],count:r.length,elements:r,offset:0})]:[c({},e,{markerTexture:this.markerTextures[t],activation:s[t],offset:0})];var f=[],h=a.range(i,{lod:!0,px:[(i[2]-i[0])/o.width,(i[3]-i[1])/o.height]});if(r){for(var p=s[t].data,d=new Uint8Array(u),v=0;v<r.length;v++){var g=r[v];d[g]=p?p[g]:1}l.subdata(d)}for(var y=h.length;y--;){var m=n(h[y],2),x=m[0],b=m[1];f.push(c({},e,{markerTexture:this.markerTextures[t],activation:r?l:s[t],offset:x,count:b-x}))}return f},x.prototype.update=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];if(r.length){1===r.length&&Array.isArray(r[0])&&(r=r[0]);var i=this.groups,a=this.gl,o=this.regl,l=this.maxSize,f=this.maxColors,v=this.palette;this.groups=i=r.map((function(e,r){var n=i[r];if(void 0===e)return n;null===e?e={positions:null}:\"function\"==typeof e?e={ondraw:e}:\"number\"==typeof e[0]&&(e={positions:e}),null===(e=h(e,{positions:\"positions data points\",snap:\"snap cluster lod tree\",size:\"sizes size radius\",borderSize:\"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline\",color:\"colors color fill fill-color fillColor\",borderColor:\"borderColors borderColor stroke stroke-color strokeColor\",marker:\"markers marker shape\",range:\"range dataBox databox\",viewport:\"viewport viewPort viewBox viewbox\",opacity:\"opacity alpha transparency\",bounds:\"bound bounds boundaries limits\",tooManyColors:\"tooManyColors palette paletteMode optimizePalette enablePalette\"})).positions&&(e.positions=[]),null!=e.tooManyColors&&(t.tooManyColors=e.tooManyColors),n||(i[r]=n={id:r,scale:null,translate:null,scaleFract:null,translateFract:null,activation:[],selectionBuffer:o.buffer({data:new Uint8Array(0),usage:\"stream\",type:\"uint8\"}),sizeBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),colorBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),positionBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"float\"}),positionFractBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"float\"})},e=c({},x.defaults,e)),e.positions&&!(\"marker\"in e)&&(e.marker=n.marker,delete n.marker),e.marker&&!(\"positions\"in e)&&(e.positions=n.positions,delete n.positions);var m=0,b=0;if(p(n,e,[{snap:!0,size:function(t,e){return null==t&&(t=x.defaults.size),m+=t&&t.length?1:0,t},borderSize:function(t,e){return null==t&&(t=x.defaults.borderSize),m+=t&&t.length?1:0,t},opacity:parseFloat,color:function(e,r){return null==e&&(e=x.defaults.color),e=t.updateColor(e),b++,e},borderColor:function(e,r){return null==e&&(e=x.defaults.borderColor),e=t.updateColor(e),b++,e},bounds:function(t,e,r){return\"range\"in r||(r.range=null),t},positions:function(t,e,r){var n=e.snap,i=e.positionBuffer,a=e.positionFractBuffer,l=e.selectionBuffer;if(t.x||t.y)return t.x.length?e.xAttr={buffer:o.buffer(t.x),offset:0,stride:4,count:t.x.length}:e.xAttr={buffer:t.x.buffer,offset:4*t.x.offset||0,stride:4*(t.x.stride||1),count:t.x.count},t.y.length?e.yAttr={buffer:o.buffer(t.y),offset:0,stride:4,count:t.y.length}:e.yAttr={buffer:t.y.buffer,offset:4*t.y.offset||0,stride:4*(t.y.stride||1),count:t.y.count},e.count=Math.max(e.xAttr.count,e.yAttr.count),t;t=d(t,\"float64\");var c=e.count=Math.floor(t.length/2),f=e.bounds=c?s(t,2):null;if(r.range||e.range||(delete e.range,r.range=f),r.marker||e.marker||(delete e.marker,r.marker=null),n&&(!0===n||c>n)?e.tree=u(t,{bounds:f}):n&&n.length&&(e.tree=n),e.tree){var h={primitive:\"points\",usage:\"static\",data:e.tree,type:\"uint32\"};e.elements?e.elements(h):e.elements=o.elements(h)}var p=g.float32(t);return i({data:p,usage:\"dynamic\"}),a({data:g.fract32(t,p),usage:\"dynamic\"}),l({data:new Uint8Array(c),type:\"uint8\",usage:\"stream\"}),t}},{marker:function(e,r,n){var i=r.activation;if(i.forEach((function(t){return t&&t.destroy&&t.destroy()})),i.length=0,e&&\"number\"!=typeof e[0]){for(var a=[],s=0,l=Math.min(e.length,r.count);s<l;s++){var u=t.addMarker(e[s]);a[u]||(a[u]=new Uint8Array(r.count)),a[u][s]=1}for(var c=0;c<a.length;c++)if(a[c]){var f={data:a[c],type:\"uint8\",usage:\"static\"};i[c]?i[c](f):i[c]=o.buffer(f),i[c].data=a[c]}}else i[t.addMarker(e)]=!0;return e},range:function(t,e,r){var n=e.bounds;if(n)return t||(t=n),e.scale=[1/(t[2]-t[0]),1/(t[3]-t[1])],e.translate=[-t[0],-t[1]],e.scaleFract=g.fract(e.scale),e.translateFract=g.fract(e.translate),t},viewport:function(t){return y(t||[a.drawingBufferWidth,a.drawingBufferHeight])}}]),m){var _=n,w=_.count,T=_.size,k=_.borderSize,A=_.sizeBuffer,M=new Uint8Array(2*w);if(T.length||k.length)for(var S=0;S<w;S++)M[2*S]=Math.round(255*(null==T[S]?T:T[S])/l),M[2*S+1]=Math.round(255*(null==k[S]?k:k[S])/l);A({data:M,usage:\"dynamic\"})}if(b){var E,L=n,C=L.count,P=L.color,O=L.borderColor,I=L.colorBuffer;if(t.tooManyColors){if(P.length||O.length){E=new Uint8Array(8*C);for(var D=0;D<C;D++){var z=P[D];E[8*D]=v[4*z],E[8*D+1]=v[4*z+1],E[8*D+2]=v[4*z+2],E[8*D+3]=v[4*z+3];var R=O[D];E[8*D+4]=v[4*R],E[8*D+5]=v[4*R+1],E[8*D+6]=v[4*R+2],E[8*D+7]=v[4*R+3]}}}else if(P.length||O.length){E=new Uint8Array(4*C+2);for(var F=0;F<C;F++)null!=P[F]&&(E[4*F]=P[F]%f,E[4*F+1]=Math.floor(P[F]/f)),null!=O[F]&&(E[4*F+2]=O[F]%f,E[4*F+3]=Math.floor(O[F]/f))}I({data:E||new Uint8Array(0),type:\"uint8\",usage:\"dynamic\"})}return n}))}},x.prototype.addMarker=function(t){var e,r=this.markerTextures,n=this.regl,i=this.markerCache,a=null==t?0:i.indexOf(t);if(a>=0)return a;if(t instanceof Uint8Array||t instanceof Uint8ClampedArray)e=t;else{e=new Uint8Array(t.length);for(var o=0,s=t.length;o<s;o++)e[o]=255*t[o]}var l=Math.floor(Math.sqrt(e.length));return a=r.length,i.push(t),r.push(n.texture({channels:1,data:e,radius:l,mag:\"linear\",min:\"linear\"})),a},x.prototype.updateColor=function(t){var e=this.paletteIds,r=this.palette,n=this.maxColors;Array.isArray(t)||(t=[t]);var i=[];if(\"number\"==typeof t[0]){var a=[];if(Array.isArray(t))for(var s=0;s<t.length;s+=4)a.push(t.slice(s,s+4));else for(var u=0;u<t.length;u+=4)a.push(t.subarray(u,u+4));t=a}for(var c=0;c<t.length;c++){var f=t[c];f=o(f,\"uint8\");var h=l(f,!1);if(null==e[h]){var p=r.length;e[h]=Math.floor(p/4),r[p]=f[0],r[p+1]=f[1],r[p+2]=f[2],r[p+3]=f[3]}i[c]=e[h]}return!this.tooManyColors&&r.length>4*n&&(this.tooManyColors=!0),this.updatePalette(r),1===i.length?i[0]:i},x.prototype.updatePalette=function(t){if(!this.tooManyColors){var e=this.maxColors,r=this.paletteTexture,n=Math.ceil(.25*t.length/e);if(n>1)for(var i=.25*(t=t.slice()).length%e;i<n*e;i++)t.push(0,0,0,0);r.height<n&&r.resize(e,n),r.subimage({width:Math.min(.25*t.length,e),height:n,data:t},0,0)}},x.prototype.destroy=function(){return this.groups.forEach((function(t){t.sizeBuffer.destroy(),t.positionBuffer.destroy(),t.positionFractBuffer.destroy(),t.colorBuffer.destroy(),t.activation.forEach((function(t){return t&&t.destroy&&t.destroy()})),t.selectionBuffer.destroy(),t.elements&&t.elements.destroy()})),this.groups.length=0,this.paletteTexture.destroy(),this.markerTextures.forEach((function(t){return t&&t.destroy&&t.destroy()})),this};var b=r(56131);t.exports=function(t,e){var r=new m(t,e),n=r.render.bind(r);return b(n,{render:n,update:r.update.bind(r),draw:r.draw.bind(r),destroy:r.destroy.bind(r),regl:r.regl,gl:r.gl,canvas:r.gl.canvas,groups:r.groups,markers:r.markerCache,palette:r.palette}),n}},60487:function(t,e,r){\"use strict\";var n=r(11870),i=r(71299),a=r(21527),o=r(5877),s=r(57471),l=r(18863),u=r(30120);function c(t,e){if(!(this instanceof c))return new c(t,e);this.traces=[],this.passes={},this.regl=t,this.scatter=n(t),this.canvas=this.scatter.canvas}function f(t,e,r){return(null!=t.id?t.id:t)<<16|(255&e)<<8|255&r}function h(t,e,r){var n,i,a,o,s=t[e],l=t[r];return s.length>2?(s[0],s[2],n=s[1],i=s[3]):s.length?(n=s[0],i=s[1]):(s.x,n=s.y,s.x,s.width,i=s.y+s.height),l.length>2?(a=l[0],o=l[2],l[1],l[3]):l.length?(a=l[0],o=l[1]):(a=l.x,l.y,o=l.x+l.width,l.y,l.height),[a,n,o,i]}function p(t){if(\"number\"==typeof t)return[t,t,t,t];if(2===t.length)return[t[0],t[1],t[0],t[1]];var e=l(t);return[e.x,e.y,e.x+e.width,e.y+e.height]}t.exports=c,c.prototype.render=function(){for(var t,e=this,r=[],n=arguments.length;n--;)r[n]=arguments[n];return r.length&&(t=this).update.apply(t,r),this.regl.attributes.preserveDrawingBuffer?this.draw():(this.dirty?null==this.planned&&(this.planned=o((function(){e.draw(),e.dirty=!0,e.planned=null}))):(this.draw(),this.dirty=!0,o((function(){e.dirty=!1}))),this)},c.prototype.update=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=0;n<e.length;n++)this.updateItem(n,e[n]);this.traces=this.traces.filter(Boolean);for(var i=[],a=0,o=0;o<this.traces.length;o++){for(var s=this.traces[o],l=this.traces[o].passes,u=0;u<l.length;u++)i.push(this.passes[l[u]]);s.passOffset=a,a+=s.passes.length}return(t=this.scatter).update.apply(t,i),this}},c.prototype.updateItem=function(t,e){var r=this.regl;if(null===e)return this.traces[t]=null,this;if(!e)return this;var n,o=i(e,{data:\"data items columns rows values dimensions samples x\",snap:\"snap cluster\",size:\"sizes size radius\",color:\"colors color fill fill-color fillColor\",opacity:\"opacity alpha transparency 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Uint8Array}),color:\"black\",marker:null,size:12,borderColor:\"transparent\",borderSize:1,viewport:l([r._gl.drawingBufferWidth,r._gl.drawingBufferHeight]),padding:[0,0,0,0],opacity:1,diagonal:!0,upper:!0,lower:!0});if(null!=o.color&&(s.color=o.color),null!=o.size&&(s.size=o.size),null!=o.marker&&(s.marker=o.marker),null!=o.borderColor&&(s.borderColor=o.borderColor),null!=o.borderSize&&(s.borderSize=o.borderSize),null!=o.opacity&&(s.opacity=o.opacity),o.viewport&&(s.viewport=l(o.viewport)),null!=o.diagonal&&(s.diagonal=o.diagonal),null!=o.upper&&(s.upper=o.upper),null!=o.lower&&(s.lower=o.lower),o.data){s.buffer(u(o.data)),s.columns=o.data.length,s.count=o.data[0].length,s.bounds=[];for(var c=0;c<s.columns;c++)s.bounds[c]=a(o.data[c],1)}o.range&&(s.range=o.range,n=s.range&&\"number\"!=typeof s.range[0]),o.domain&&(s.domain=o.domain);var d=!1;null!=o.padding&&(Array.isArray(o.padding)&&o.padding.length===s.columns&&\"number\"==typeof o.padding[o.padding.length-1]?(s.padding=o.padding.map(p),d=!0):s.padding=p(o.padding));var v=s.columns,g=s.count,y=s.viewport.width,m=s.viewport.height,x=s.viewport.x,b=s.viewport.y,_=y/v,w=m/v;s.passes=[];for(var T=0;T<v;T++)for(var k=0;k<v;k++)if((s.diagonal||k!==T)&&(s.upper||!(T>k))&&(s.lower||!(T<k))){var A=f(s.id,T,k),M=this.passes[A]||(this.passes[A]={});if(o.data&&(o.transpose?M.positions={x:{buffer:s.buffer,offset:k,count:g,stride:v},y:{buffer:s.buffer,offset:T,count:g,stride:v}}:M.positions={x:{buffer:s.buffer,offset:k*g,count:g},y:{buffer:s.buffer,offset:T*g,count:g}},M.bounds=h(s.bounds,T,k)),o.domain||o.viewport||o.data){var S=d?h(s.padding,T,k):s.padding;if(s.domain){var E=h(s.domain,T,k),L=E[0],C=E[1],P=E[2],O=E[3];M.viewport=[x+L*y+S[0],b+C*m+S[1],x+P*y-S[2],b+O*m-S[3]]}else M.viewport=[x+k*_+_*S[0],b+T*w+w*S[1],x+(k+1)*_-_*S[2],b+(T+1)*w-w*S[3]]}o.color&&(M.color=s.color),o.size&&(M.size=s.size),o.marker&&(M.marker=s.marker),o.borderSize&&(M.borderSize=s.borderSize),o.borderColor&&(M.borderColor=s.borderColor),o.opacity&&(M.opacity=s.opacity),o.range&&(M.range=n?h(s.range,T,k):s.range||M.bounds),s.passes.push(A)}return this},c.prototype.draw=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=[],i=0;i<e.length;i++)if(\"number\"==typeof e[i]){var a=this.traces[e[i]],o=a.passes,l=a.passOffset;n.push.apply(n,s(l,l+o.length))}else if(e[i].length){var u=e[i],c=this.traces[i],f=c.passes,h=c.passOffset;f=f.map((function(t,e){n[h+e]=u}))}(t=this.scatter).draw.apply(t,n)}else this.scatter.draw();return this},c.prototype.destroy=function(){return this.traces.forEach((function(t){t.buffer&&t.buffer.destroy&&t.buffer.destroy()})),this.traces=null,this.passes=null,this.scatter.destroy(),this}},98580:function(t){t.exports=function(){function t(t,e){this.id=Z++,this.type=t,this.data=e}function e(t){if(0===t.length)return[];var r=t.charAt(0),n=t.charAt(t.length-1);if(1<t.length&&r===n&&('\"'===r||\"'\"===r))return['\"'+t.substr(1,t.length-2).replace(/\\\\/g,\"\\\\\\\\\").replace(/\"/g,'\\\\\"')+'\"'];if(r=/\\[(false|true|null|\\d+|'[^']*'|\"[^\"]*\")\\]/.exec(t))return e(t.substr(0,r.index)).concat(e(r[1])).concat(e(t.substr(r.index+r[0].length)));if(1===(r=t.split(\".\")).length)return['\"'+t.replace(/\\\\/g,\"\\\\\\\\\").replace(/\"/g,'\\\\\"')+'\"'];for(t=[],n=0;n<r.length;++n)t=t.concat(e(r[n]));return t}function r(t){return\"[\"+e(t).join(\"][\")+\"]\"}function n(t){return\"string\"==typeof t?t.split():t}function i(t){return\"string\"==typeof t?document.querySelector(t):t}function a(t){var e,r,a,o,s=t||{};t={};var 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e=Math.floor(t/400)+1;t-=400*(e-1),t+=t>15?16:0;var r=Math.floor(t/32)+1,n=t-32*(r-1)+1;return this.newDate(e<=0?e-1:e,r,n)}});var o={20:\"Fruitbat\",21:\"Anchovy\"};n.calendars.discworld=a},37715:function(t,e,r){var n=r(63489),i=r(56131);function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new 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n=r(56131);function i(){this.regionalOptions=[],this.regionalOptions[\"\"]={invalidCalendar:\"Calendar {0} not found\",invalidDate:\"Invalid {0} date\",invalidMonth:\"Invalid {0} month\",invalidYear:\"Invalid {0} year\",differentCalendars:\"Cannot mix {0} and {1} dates\"},this.local=this.regionalOptions[\"\"],this.calendars={},this._localCals={}}function a(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(u.local.invalidDate||u.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name)}function o(t,e){return\"000000\".substring(0,e-(t=\"\"+t).length)+t}function s(){this.shortYearCutoff=\"+10\"}function l(t){this.local=this.regionalOptions[t]||this.regionalOptions[\"\"]}n(i.prototype,{instance:function(t,e){t=(t||\"gregorian\").toLowerCase(),e=e||\"\";var r=this._localCals[t+\"-\"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+\"-\"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[\"\"].invalidCalendar).replace(/\\{0\\}/,t);return r},newDate:function(t,e,r,n,i){return(n=(null!=t&&t.year?t.calendar():\"string\"==typeof n?this.instance(n,i):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+\"\").replace(/[0-9]/g,(function(e){return t[e]}))}},substituteChineseDigits:function(t,e){return function(r){for(var n=\"\",i=0;r>0;){var a=r%10;n=(0===a?\"\":t[a]+e[i])+n,i++,r=Math.floor(r/10)}return 0===n.indexOf(t[1]+e[1])&&(n=n.substr(1)),n||t[0]}}}),n(a.prototype,{newDate:function(t,e,r){return this._calendar.newDate(null==t?this:t,e,r)},year:function(t){return 0===arguments.length?this._year:this.set(t,\"y\")},month:function(t){return 0===arguments.length?this._month:this.set(t,\"m\")},day:function(t){return 0===arguments.length?this._day:this.set(t,\"d\")},date:function(t,e,r){if(!this._calendar.isValid(t,e,r))throw(u.local.invalidDate||u.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name);return this._year=t,this._month=e,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(t,e){return this._calendar.add(this,t,e)},set:function(t,e){return this._calendar.set(this,t,e)},compareTo:function(t){if(this._calendar.name!==t._calendar.name)throw(u.local.differentCalendars||u.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this._calendar.local.name).replace(/\\{1\\}/,t._calendar.local.name);var e=this._year!==t._year?this._year-t._year:this._month!==t._month?this.monthOfYear()-t.monthOfYear():this._day-t._day;return 0===e?0:e<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(t){return this._calendar.fromJD(t)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(t){return this._calendar.fromJSDate(t)},toString:function(){return(this.year()<0?\"-\":\"\")+o(Math.abs(this.year()),4)+\"-\"+o(this.month(),2)+\"-\"+o(this.day(),2)}}),n(s.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),r=t.day(),e=t.month(),t=t.year()),new a(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear);return(e.year()<0?\"-\":\"\")+o(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,u.local.invalidMonth||u.regionalOptions[\"\"].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(t,e){var r=(e+this.firstMonth-2*this.minMonth)%this.monthsInYear(t)+this.minMonth;return this._validate(t,r,this.minDay,u.local.invalidMonth||u.regionalOptions[\"\"].invalidMonth),r},daysInYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear);return this.leapYear(e)?366:365},dayOfYear:function(t,e,r){var n=this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate);return n.toJD()-this.newDate(n.year(),this.fromMonthOfYear(n.year(),this.minMonth),this.minDay).toJD()+1},daysInWeek:function(){return 7},dayOfWeek:function(t,e,r){var n=this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(t,e,r){return this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),{}},add:function(t,e,r){return this._validate(t,this.minMonth,this.minDay,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),this._correctAdd(t,this._add(t,e,r),e,r)},_add:function(t,e,r){if(this._validateLevel++,\"d\"===r||\"w\"===r){var n=t.toJD()+e*(\"w\"===r?this.daysInWeek():1),i=t.calendar().fromJD(n);return this._validateLevel--,[i.year(),i.month(),i.day()]}try{var a=t.year()+(\"y\"===r?e:0),o=t.monthOfYear()+(\"m\"===r?e:0);i=t.day(),\"y\"===r?(t.month()!==this.fromMonthOfYear(a,o)&&(o=this.newDate(a,t.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(a)),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o)))):\"m\"===r&&(function(t){for(;o<t.minMonth;)a--,o+=t.monthsInYear(a);for(var e=t.monthsInYear(a);o>e-1+t.minMonth;)a++,o-=e,e=t.monthsInYear(a)}(this),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o))));var s=[a,this.fromMonthOfYear(a,o),i];return this._validateLevel--,s}catch(t){throw 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n=this.newDate(t,e,r);return n.add(4-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,u.local.invalidMonth||u.regionalOptions[\"\"].invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var n=this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate);t=n.year(),e=n.month(),r=n.day(),t<0&&t++,e<3&&(e+=12,t--);var i=Math.floor(t/100),a=2-i+Math.floor(i/4);return Math.floor(365.25*(t+4716))+Math.floor(30.6001*(e+1))+r+a-1524.5},fromJD:function(t){var e=Math.floor(t+.5),r=Math.floor((e-1867216.25)/36524.25),n=1524+(r=e+1+r-Math.floor(r/4)),i=Math.floor((n-122.1)/365.25),a=Math.floor(365.25*i),o=Math.floor((n-a)/30.6001),s=n-a-Math.floor(30.6001*o),l=o-(o>13.5?13:1),u=i-(l>2.5?4716:4715);return u<=0&&u--,this.newDate(u,l,s)},toJSDate:function(t,e,r){var n=this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),i=new Date(n.year(),n.month()-1,n.day());return i.setHours(0),i.setMinutes(0),i.setSeconds(0),i.setMilliseconds(0),i.setHours(i.getHours()>12?i.getHours()+2:0),i},fromJSDate:function(t){return this.newDate(t.getFullYear(),t.getMonth()+1,t.getDate())}});var u=t.exports=new i;u.cdate=a,u.baseCalendar=s,u.calendars.gregorian=l},94338:function(t,e,r){var n=r(56131),i=r(63489);n(i.regionalOptions[\"\"],{invalidArguments:\"Invalid arguments\",invalidFormat:\"Cannot format a date from another calendar\",missingNumberAt:\"Missing number at position {0}\",unknownNameAt:\"Unknown name at position {0}\",unexpectedLiteralAt:\"Unexpected literal at position {0}\",unexpectedText:\"Additional text found at end\"}),i.local=i.regionalOptions[\"\"],n(i.cdate.prototype,{formatDate:function(t,e){return\"string\"!=typeof 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(meters)\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"Y (meters)\"},\"scaleanchor\":\"x\"},\"legend\":{\"tracegroupgap\":0},\"margin\":{\"t\":60}},                        {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('26213e76-f060-4493-8a97-59cf53ccb720');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Showing the trace of position\n",
+    "\n",
+    "import plotly.express as px\n",
+    "\n",
+    "fig = px.line(\n",
+    "    x=spatial_series.data[:, 0] * spatial_series.conversion,\n",
+    "    y=spatial_series.data[:, 1] * spatial_series.conversion,\n",
+    "    labels=dict(x=\"X (meters)\", y=\"Y (meters)\"),\n",
+    ")\n",
+    "fig.update_layout(yaxis=dict(scaleanchor=\"x\"))\n",
+    "\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3e505f44",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%% md\n"
+    },
+    "tags": []
+   },
+   "source": [
+    "### For interactive visualization of the position\n",
+    "\n",
+    "Visit [Neurosift](https://flatironinstitute.github.io/neurosift/?p=/nwb&url=https://dandiarchive.s3.amazonaws.com/blobs/ec1/842/ec1842a0-2229-4096-8dcd-d42b49f9dd49)\n",
+    "\n",
+    "\n",
+    "<img src=\"images/neurosift_position.png\" alt=\"Neurosift\" />"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "361f4e66",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## Accessing spike times <a class=\"anchor\" id=\"spike-times\"></a>\n",
+    "\n",
+    "The `Units` table holds the spike times which can be accessed as `nwbfile.units` and can also be converted to a pandas `DataFrame`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "5f3560b3",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>unit_name</th>\n",
+       "      <th>spike_times</th>\n",
+       "      <th>histology</th>\n",
+       "      <th>hemisphere</th>\n",
+       "      <th>depth</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>id</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>t1c1</td>\n",
+       "      <td>[0.7903958333333333, 0.794, 0.8111666666666667...</td>\n",
+       "      <td>MEC LII</td>\n",
+       "      <td></td>\n",
+       "      <td>0.0024</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>t2c1</td>\n",
+       "      <td>[1.0451354166666667, 1.7003854166666668, 2.315...</td>\n",
+       "      <td>MEC LII</td>\n",
+       "      <td></td>\n",
+       "      <td>0.0024</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>t2c3</td>\n",
+       "      <td>[0.18273958333333334, 0.5340729166666667, 0.57...</td>\n",
+       "      <td>MEC LII</td>\n",
+       "      <td></td>\n",
+       "      <td>0.0024</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>t3c1</td>\n",
+       "      <td>[1.0358229166666666, 1.04803125, 1.69642708333...</td>\n",
+       "      <td>MEC LII</td>\n",
+       "      <td></td>\n",
+       "      <td>0.0024</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>t3c2</td>\n",
+       "      <td>[2.43025, 2.4398333333333335, 3.17965625, 3.39...</td>\n",
+       "      <td>MEC LII</td>\n",
+       "      <td></td>\n",
+       "      <td>0.0024</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>t3c3</td>\n",
+       "      <td>[2.1157708333333334, 2.425427083333333, 3.3630...</td>\n",
+       "      <td>MEC LII</td>\n",
+       "      <td></td>\n",
+       "      <td>0.0024</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>t3c4</td>\n",
+       "      <td>[0.07945833333333334, 2.244947916666667, 3.173...</td>\n",
+       "      <td>MEC LII</td>\n",
+       "      <td></td>\n",
+       "      <td>0.0024</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>t4c1</td>\n",
+       "      <td>[2.4301666666666666, 2.439770833333333, 3.1795...</td>\n",
+       "      <td>MEC LII</td>\n",
+       "      <td></td>\n",
+       "      <td>0.0024</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   unit_name                                        spike_times histology  \\\n",
+       "id                                                                          \n",
+       "0       t1c1  [0.7903958333333333, 0.794, 0.8111666666666667...   MEC LII   \n",
+       "1       t2c1  [1.0451354166666667, 1.7003854166666668, 2.315...   MEC LII   \n",
+       "2       t2c3  [0.18273958333333334, 0.5340729166666667, 0.57...   MEC LII   \n",
+       "3       t3c1  [1.0358229166666666, 1.04803125, 1.69642708333...   MEC LII   \n",
+       "4       t3c2  [2.43025, 2.4398333333333335, 3.17965625, 3.39...   MEC LII   \n",
+       "5       t3c3  [2.1157708333333334, 2.425427083333333, 3.3630...   MEC LII   \n",
+       "6       t3c4  [0.07945833333333334, 2.244947916666667, 3.173...   MEC LII   \n",
+       "7       t4c1  [2.4301666666666666, 2.439770833333333, 3.1795...   MEC LII   \n",
+       "\n",
+       "   hemisphere   depth  \n",
+       "id                     \n",
+       "0              0.0024  \n",
+       "1              0.0024  \n",
+       "2              0.0024  \n",
+       "3              0.0024  \n",
+       "4              0.0024  \n",
+       "5              0.0024  \n",
+       "6              0.0024  \n",
+       "7              0.0024  "
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nwbfile.units.to_dataframe()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5ad173ae",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "### For interactive visualization of spike times\n",
+    "\n",
+    "Visit [Neurosift](https://flatironinstitute.github.io/neurosift/?p=/nwb&url=https://dandiarchive.s3.amazonaws.com/blobs/ec1/842/ec1842a0-2229-4096-8dcd-d42b49f9dd49)\n",
+    "\n",
+    "<img src=\"images/neurosift_units_and_position.png\" alt=\"Neurosift\" />"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0c9d80db",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## Visualizing rate maps <a class=\"anchor\" id=\"rate-maps\"></a>\n",
+    "\n",
+    "This section demonstrates how to show the rate maps of the recorded cells.\n",
+    "We will use [PYthon Neural Analysis Package](https://pynapple-org.github.io/pynapple/) (`pynapple`) to calculate the rate maps.\n",
+    "\n",
+    "Using the `compute_2d_tuning_curves()` function we can compute firing rate as a function of position (map of neural activity as the animal explored the environment)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "74c5af70",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%%\n"
+    },
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "#!pip install pynapple"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "08711569",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%%\n"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import pynapple as nap\n",
+    "\n",
+    "position_over_time = nap.TsdFrame(\n",
+    "    d=spatial_series.data[:],\n",
+    "    t=spatial_series.timestamps[:],\n",
+    "    columns=[\"x\",\"y\"],\n",
+    ")\n",
+    "spike_times_group = nap.TsGroup({cell_id: nap.Ts(spikes) for cell_id, spikes in enumerate(nwbfile.units[\"spike_times\"])})\n",
+    "\n",
+    "num_bins = 15\n",
+    "rate_maps, position_bins = nap.compute_2d_tuning_curves(\n",
+    "    spike_times_group,\n",
+    "    position_over_time,\n",
+    "    num_bins,\n",
+    ")\n"
+   ]
+  },
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+   "id": "c1bbb7ec-54c7-4405-af14-4a84f98039b1",
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+    "tags": []
+   },
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from MEC LII\"}},                        {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('4ae3d2c4-9e4a-41c7-91e8-6ba239459523');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
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+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
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+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import plotly.express as px\n",
+    "\n",
+    "cell_ind = 1\n",
+    "unit_name = nwbfile.units[\"unit_name\"][cell_ind]\n",
+    "layer = nwbfile.units[\"histology\"][cell_ind]\n",
+    "\n",
+    "fig = px.imshow(rate_maps[cell_ind], color_continuous_scale=\"viridis\")\n",
+    "\n",
+    "fig.update_xaxes(showticklabels=False)\n",
+    "fig.update_yaxes(showticklabels=False)\n",
+    "fig.update_layout(title=f\"{unit_name} from {layer}\", coloraxis_showscale=False)\n",
+    "\n",
+    "\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b02861ea-c46a-4615-acfc-ff1ee7c2eb68",
+   "metadata": {},
+   "source": [
+    "<img src=\"images/rate_map_t2c1.png\" alt=\"ratemap\" />"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "84ab0bd8-8b6f-4da3-9e32-97eeaf1a0648",
+   "metadata": {},
+   "source": [
+    "## Visualizing grid cells activity\n",
+    "\n",
+    "To determine whether the firing fields of individual cells formed a grid structure, we will calculate the spatial autocorrelation for the rate map of each cell.\n",
+    "\n",
+    "The autocorrelograms are based on Pearson’s product moment correlation coefficient with\n",
+    "corrections for edge effects and unvisited locations.  With λ (x, y) denoting the average rate of a cell at location (x, y), the autocorrelation between the fields with spatial lags of τx and τy was estimated as:\n",
+    "\n",
+    "<img src=\"images/autocorrelation_equation.png\" alt=\"autocorr\" />\n",
+    "\n",
+    "where the summation is over all n pixels in λ (x, y) for which rate was estimated for both λ (x, y) and λ (x - τx, y - τy). Autocorrelations were not estimated for lags of τx, τy where n < 20.\n",
+    "\n",
+    "The degree of spatial periodicity (gridness) can be determined for each cell by rotating the autocorrelation map for each cell in steps of 6 degrees (from 0 to 180 degrees) and computing the correlation between the rotated map and the original. The correlation is confined to the area defined by a circle around the peaks that are closest to the centre of the map, and the central peak is not included in the analysis.\n",
+    "\n",
+    "The ‘gridness’ of a cell can be expressed as the difference between the lowest correlation at 60 and 120 degrees (where a peak correlation would be expected due to the triangular nature of the grid) and the highest correlation at 30, 90, and 150 degrees (where the minimum correlation would be expected). When the correlations at 60 and 120 degrees of rotation exceeded each of the correlations at 30, 90 and 150 degrees (gridness > 0), the cell was classified as a grid cell.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "57b3664b-2a49-47e3-b834-ce5bf6594b84",
+   "metadata": {},
+   "source": [
+    "<img src=\"images/rate_map.png\" alt=\"Ratemap\" />"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "3e62c0f1-b57c-44e7-99f1-20c35d11b8fc",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "def create_coer_arr(arr, rad_min=None, rad_max=None):\n",
+    "    \"\"\" Creating an array for correlation(tau_x, tau_y)\n",
+    "    I will take tau_x from the range (-arr.shape[0]+1, arr.shape[0]-1) and the same for tau_y\n",
+    "    \"\"\"\n",
+    "    sh_x, sh_y = arr.shape\n",
+    "    # creating an array full of nan's\n",
+    "    coer_arr = np.full((2*sh_x-1, 2*sh_y-1), np.nan)\n",
+    "    for ii in range(0, 2*(sh_x-1)):\n",
+    "        for jj in range(0, 2*(sh_y-1)):\n",
+    "            # shifting tau_x/y\n",
+    "            tau_x = ii-sh_x+1\n",
+    "            tau_y = jj-sh_y+1\n",
+    "            # if rad_max and rad_min is provided, I only calculate the correlation for points between rad_min and rad_max\n",
+    "            if rad_max is not None and ((tau_x**2 + tau_y**2)**0.5 > rad_max):\n",
+    "                continue\n",
+    "            if rad_min is not None and ((tau_x**2 + tau_y**2)**0.5 < rad_min):\n",
+    "                continue\n",
+    "            coer_arr[ii, jj] = pearson_autocor(arr, lag_x=tau_x, lag_y=tau_y)\n",
+    "    return coer_arr\n",
+    "\n",
+    "def pearson_autocor(arr, lag_x, lag_y):\n",
+    "    \"\"\" Calculating Pearson autocorrelation for an array that can contain NaN values.\"\"\"\n",
+    "    sh_x, sh_y = arr.shape\n",
+    "    if abs(lag_x) >= sh_x or abs(lag_y) >= sh_y:\n",
+    "        raise Exception(f\"abs(lag_x), abs(lag_y) have to be smaller than {sh_x}, {sh_y}, but {lag_x}, {lag_y} provided\")\n",
+    "\n",
+    "    # calculating sum for elements that meet the requirements\n",
+    "    n = 0\n",
+    "    sum1, sum2, sum3, sum4, sum5 = 0, 0, 0, 0, 0\n",
+    "    for ii in range(0, sh_x):\n",
+    "        for jj in range(0, sh_y):\n",
+    "            # checking if the indices are within the array\n",
+    "            if 0 <= ii-lag_x < sh_x and 0 <= jj-lag_y < sh_y:\n",
+    "                # checking if both values (in ii,jj and shifted) are not nan\n",
+    "                if not np.isnan(arr[ii, jj]) and not np.isnan(arr[ii-lag_x, jj-lag_y]):\n",
+    "                    \n",
+    "                    n += 1\n",
+    "                    sum1 += arr[ii, jj] * arr[ii-lag_x, jj-lag_y]\n",
+    "                    sum2 += arr[ii, jj] \n",
+    "                    sum3 += arr[ii-lag_x, jj-lag_y]\n",
+    "        \n",
+    "                    sum4 += (arr[ii, jj])**2\n",
+    "                    sum5 += (arr[ii-lag_x, jj-lag_y])**2\n",
+    "\n",
+    "              \n",
+    "    # according to the paper they had this limit for number of points\n",
+    "    if n < 20:\n",
+    "        return np.nan\n",
+    "\n",
+    "    numerator = n * sum1 - sum2 * sum3\n",
+    "    denominator = (n * sum4 - sum2**2)**0.5 * (n * sum5 - sum3**2)**0.5\n",
+    "    cor = numerator / denominator\n",
+    "\n",
+    "    return cor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "4fb17ed7",
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+     "text": [
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+         "autorange": true,
+         "domain": [
+          0.35555555555555557,
+          0.6444444444444445
+         ],
+         "range": [
+          -0.5,
+          98.5
+         ],
+         "showticklabels": false
+        },
+        "xaxis3": {
+         "anchor": "y3",
+         "autorange": true,
+         "domain": [
+          0.7111111111111111,
+          1
+         ],
+         "range": [
+          0,
+          180
+         ],
+         "showticklabels": true,
+         "tickmode": "array",
+         "tickvals": [
+          30,
+          60,
+          90,
+          120,
+          150,
+          180
+         ],
+         "title": {
+          "text": "Rotation (deg)"
+         },
+         "type": "linear"
+        },
+        "yaxis": {
+         "anchor": "x",
+         "autorange": true,
+         "domain": [
+          0,
+          1
+         ],
+         "range": [
+          -0.5,
+          14.5
+         ],
+         "showticklabels": false
+        },
+        "yaxis2": {
+         "anchor": "x2",
+         "autorange": true,
+         "domain": [
+          0,
+          1
+         ],
+         "range": [
+          -0.5,
+          98.5
+         ],
+         "showticklabels": false
+        },
+        "yaxis3": {
+         "anchor": "x3",
+         "autorange": true,
+         "domain": [
+          0,
+          1
+         ],
+         "range": [
+          -0.2682807627658728,
+          1.0667516190929112
+         ],
+         "showticklabels": true,
+         "title": {
+          "text": "Correlation (r)"
+         },
+         "type": "linear"
+        }
+       }
+      },
+      "image/png": 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+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
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+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        },
+        "title": {
+         "text": "MEC LII: Gridness score 0.43"
+        },
+        "xaxis": {
+         "anchor": "y",
+         "autorange": true,
+         "domain": [
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+          0.2888888888888889
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+         "range": [
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+         "range": [
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+         "range": [
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+         "showticklabels": true,
+         "tickmode": "array",
+         "tickvals": [
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+          60,
+          90,
+          120,
+          150,
+          180
+         ],
+         "title": {
+          "text": "Rotation (deg)"
+         },
+         "type": "linear"
+        },
+        "yaxis": {
+         "anchor": "x",
+         "autorange": true,
+         "domain": [
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+         "range": [
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+        "yaxis2": {
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+         "showticklabels": false
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+         "domain": [
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+         "range": [
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+         "showticklabels": true,
+         "title": {
+          "text": "Correlation (r)"
+         },
+         "type": "linear"
+        }
+       }
+      },
+      "image/png": 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+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        },
+        "title": {
+         "text": "MEC LII: Gridness score 0.62"
+        },
+        "xaxis": {
+         "anchor": "y",
+         "autorange": true,
+         "domain": [
+          0,
+          0.2888888888888889
+         ],
+         "range": [
+          -0.5,
+          14.5
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+         "showticklabels": false
+        },
+        "xaxis2": {
+         "anchor": "y2",
+         "autorange": true,
+         "domain": [
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+          0.6444444444444445
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+         "range": [
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+          98.5
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+         "showticklabels": false
+        },
+        "xaxis3": {
+         "anchor": "y3",
+         "autorange": true,
+         "domain": [
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+          1
+         ],
+         "range": [
+          0,
+          180
+         ],
+         "showticklabels": true,
+         "tickmode": "array",
+         "tickvals": [
+          30,
+          60,
+          90,
+          120,
+          150,
+          180
+         ],
+         "title": {
+          "text": "Rotation (deg)"
+         },
+         "type": "linear"
+        },
+        "yaxis": {
+         "anchor": "x",
+         "autorange": true,
+         "domain": [
+          0,
+          1
+         ],
+         "range": [
+          -0.5,
+          14.5
+         ],
+         "showticklabels": false
+        },
+        "yaxis2": {
+         "anchor": "x2",
+         "autorange": true,
+         "domain": [
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+         ],
+         "range": [
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+          98.5
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+         "showticklabels": false
+        },
+        "yaxis3": {
+         "anchor": "x3",
+         "autorange": true,
+         "domain": [
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+          1
+         ],
+         "range": [
+          -0.3105162510626742,
+          1.0689745395296144
+         ],
+         "showticklabels": true,
+         "title": {
+          "text": "Correlation (r)"
+         },
+         "type": "linear"
+        }
+       }
+      },
+      "image/png": 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+         "range": [
+          -0.5,
+          14.5
+         ],
+         "showticklabels": false
+        },
+        "xaxis2": {
+         "anchor": "y2",
+         "autorange": true,
+         "domain": [
+          0.35555555555555557,
+          0.6444444444444445
+         ],
+         "range": [
+          -0.5,
+          98.5
+         ],
+         "showticklabels": false
+        },
+        "xaxis3": {
+         "anchor": "y3",
+         "autorange": true,
+         "domain": [
+          0.7111111111111111,
+          1
+         ],
+         "range": [
+          0,
+          180
+         ],
+         "showticklabels": true,
+         "tickmode": "array",
+         "tickvals": [
+          30,
+          60,
+          90,
+          120,
+          150,
+          180
+         ],
+         "title": {
+          "text": "Rotation (deg)"
+         },
+         "type": "linear"
+        },
+        "yaxis": {
+         "anchor": "x",
+         "autorange": true,
+         "domain": [
+          0,
+          1
+         ],
+         "range": [
+          -0.5,
+          14.5
+         ],
+         "showticklabels": false
+        },
+        "yaxis2": {
+         "anchor": "x2",
+         "autorange": true,
+         "domain": [
+          0,
+          1
+         ],
+         "range": [
+          -0.5,
+          98.5
+         ],
+         "showticklabels": false
+        },
+        "yaxis3": {
+         "anchor": "x3",
+         "autorange": true,
+         "domain": [
+          0,
+          1
+         ],
+         "range": [
+          -0.086013509587828,
+          1.05715860576766
+         ],
+         "showticklabels": true,
+         "title": {
+          "text": "Correlation (r)"
+         },
+         "type": "linear"
+        }
+       }
+      },
+      "image/png": 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mbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05},\"mapbox\":{\"style\":\"light\"}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,0.2888888888888889],\"showticklabels\":false},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"showticklabels\":false},\"xaxis2\":{\"anchor\":\"y2\",\"domain\":[0.35555555555555557,0.6444444444444445],\"showticklabels\":false},\"yaxis2\":{\"anchor\":\"x2\",\"domain\":[0.0,1.0],\"showticklabels\":false},\"xaxis3\":{\"anchor\":\"y3\",\"domain\":[0.7111111111111111,1.0],\"showticklabels\":true,\"title\":{\"text\":\"Rotation (deg)\"},\"tickmode\":\"array\",\"tickvals\":[30,60,90,120,150,180]},\"yaxis3\":{\"anchor\":\"x3\",\"domain\":[0.0,1.0],\"showticklabels\":true,\"title\":{\"text\":\"Correlation (r)\"}},\"annotations\":[{\"font\":{\"size\":16},\"showarrow\":false,\"text\":\"t4c1 rate map\",\"x\":0.14444444444444446,\"xanchor\":\"center\",\"xref\":\"paper\",\"y\":1.0,\"yanchor\":\"bottom\",\"yref\":\"paper\"},{\"font\":{\"size\":16},\"showarrow\":false,\"text\":\"t4c1 auto-correlation\",\"x\":0.5,\"xanchor\":\"center\",\"xref\":\"paper\",\"y\":1.0,\"yanchor\":\"bottom\",\"yref\":\"paper\"},{\"font\":{\"size\":16},\"showarrow\":false,\"text\":\"periodicity\",\"x\":0.8555555555555556,\"xanchor\":\"center\",\"xref\":\"paper\",\"y\":1.0,\"yanchor\":\"bottom\",\"yref\":\"paper\"}],\"title\":{\"text\":\"MEC LII: Gridness score 0.22\"}},                        {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('93d7a062-b8cd-4b3b-9405-f4f3dc386268');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import plotly.express as px\n",
+    "from plotly.subplots import make_subplots\n",
+    "import plotly.graph_objects as go\n",
+    "from scipy.ndimage import rotate\n",
+    "import scipy\n",
+    "\n",
+    "rate_maps_50_bin, _ = nap.compute_2d_tuning_curves(\n",
+    "    spike_times_group,\n",
+    "    position_over_time,\n",
+    "    50,\n",
+    ")\n",
+    "\n",
+    "for cell_ind in range(len(rate_maps)):\n",
+    "    unit_name = nwbfile.units[\"unit_name\"][cell_ind]\n",
+    "    layer = nwbfile.units[\"histology\"][cell_ind]\n",
+    "    fig = make_subplots(\n",
+    "        rows=1,\n",
+    "        cols=3,\n",
+    "        subplot_titles=(f'{unit_name} rate map', f'{unit_name} auto-correlation', \"periodicity\"),\n",
+    "    )\n",
+    "\n",
+    "    rate_map_plot = go.Heatmap(z=rate_maps[cell_ind], colorscale='Viridis', showscale=False)\n",
+    "    fig.add_trace(rate_map_plot, row=1, col=1)\n",
+    "\n",
+    "    # Compute auto-correlation\n",
+    "    autocorr = create_coer_arr(rate_maps_50_bin[cell_ind], rad_max=34, rad_min=6)\n",
+    "    autocorr_nonan = np.nan_to_num(autocorr, copy=True, nan=0.0)\n",
+    "\n",
+    "    correlations = []\n",
+    "    angles = np.arange(0, 186, 6)\n",
+    "    for angle in angles:\n",
+    "        autocorr_nonan_rotated = rotate(autocorr_nonan, angle=angle, reshape=False)\n",
+    "        cor = scipy.stats.pearsonr(autocorr_nonan_rotated.flatten(), autocorr_nonan.flatten())[0]\n",
+    "        correlations.append(cor)\n",
+    "    \n",
+    "    gridness = max(correlations[10], correlations[20]) - max(correlations[5], correlations[15], correlations[25])\n",
+    "    gridness = np.round(gridness, 2)\n",
+    "    \n",
+    "    autocorr_rate_map = go.Heatmap(z=autocorr, colorscale='Viridis', showscale=False)\n",
+    "    fig.add_trace(autocorr_rate_map, row=1, col=2)\n",
+    "    \n",
+    "    line_trace = go.Scatter(\n",
+    "        x=angles,\n",
+    "        y=correlations,\n",
+    "        mode='lines',\n",
+    "        marker=dict(color=\"black\"),\n",
+    "        \n",
+    "    )\n",
+    "    \n",
+    "    fig.add_trace(line_trace, row=1, col=3)\n",
+    "\n",
+    "    fig.update_xaxes(showticklabels=False)\n",
+    "    fig.update_yaxes(showticklabels=False)\n",
+    "    \n",
+    "    fig.update_xaxes(showticklabels=True, row=1, col=3, title_text=\"Rotation (deg)\")\n",
+    "    fig.update_yaxes(showticklabels=True, row=1, col=3, title_text=\"Correlation (r)\")\n",
+    "    \n",
+    "    fig.update_layout(\n",
+    "        title=f\"{layer}: Gridness score {gridness}\",\n",
+    "        xaxis3 = dict(\n",
+    "            tickmode=\"array\",\n",
+    "            tickvals=[30, 60, 90, 120, 150, 180],\n",
+    "        )\n",
+    "    )\n",
+    "\n",
+    "    fig.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/000582/Sargolini2006/README.md b/000582/Sargolini2006/README.md
new file mode 100644
index 0000000..3d7511b
--- /dev/null
+++ b/000582/Sargolini2006/README.md
@@ -0,0 +1,19 @@
+# Educational notebook based on Sargolini 2006
+
+This example notebook demonstrates how to access the dataset published in [Sargolini et al. (Science, 2006)](https://doi.org/10.1126/science.1125572) using `dandi`.
+The dataset contains spike times for recorded grid cells from the Medial Entorhinal Cortex (MEC) in rats that explored two-dimensional environments. The behavioral data includes position from the tracking LED(s).
+
+## Installing the dependencies
+
+```bash
+git clone https://github.com/dandi/example-notebooks
+cd example-notebooks/000582/Sargolini2006
+conda env create --file environment.yml
+conda activate sargolini-2006-env
+```
+
+## Running the notebook
+
+```bash
+jupyter notebook 000582_Sargolini2006_demo.ipynb 
+```
diff --git a/000582/Sargolini2006/environment.yml b/000582/Sargolini2006/environment.yml
new file mode 100644
index 0000000..2be6ff8
--- /dev/null
+++ b/000582/Sargolini2006/environment.yml
@@ -0,0 +1,12 @@
+name: sargolini-2006-env
+channels:
+  - defaults
+dependencies:
+  - pip
+  - python>=3.9
+  - pip:
+      - dandi==0.56.1
+      - jupyter
+      - plotly==5.17.0
+      - pynapple==0.3.6
+      - pynwb==2.5.0
diff --git a/000582/Sargolini2006/images/autocorrelation_equation.png b/000582/Sargolini2006/images/autocorrelation_equation.png
new file mode 100644
index 0000000..ecb145e
Binary files /dev/null and b/000582/Sargolini2006/images/autocorrelation_equation.png differ
diff --git a/000582/Sargolini2006/images/neurosift_position.png b/000582/Sargolini2006/images/neurosift_position.png
new file mode 100644
index 0000000..e3b0976
Binary files /dev/null and b/000582/Sargolini2006/images/neurosift_position.png differ
diff --git a/000582/Sargolini2006/images/neurosift_units_and_position.png b/000582/Sargolini2006/images/neurosift_units_and_position.png
new file mode 100644
index 0000000..0453171
Binary files /dev/null and b/000582/Sargolini2006/images/neurosift_units_and_position.png differ
diff --git a/000582/Sargolini2006/images/rate_map.png b/000582/Sargolini2006/images/rate_map.png
new file mode 100644
index 0000000..c3e4f82
Binary files /dev/null and b/000582/Sargolini2006/images/rate_map.png differ
diff --git a/000582/Sargolini2006/images/rate_map_t2c1.png b/000582/Sargolini2006/images/rate_map_t2c1.png
new file mode 100644
index 0000000..f241210
Binary files /dev/null and b/000582/Sargolini2006/images/rate_map_t2c1.png differ
diff --git a/000582/Sargolini2006/requirements.txt b/000582/Sargolini2006/requirements.txt
new file mode 100644
index 0000000..bc5ec00
--- /dev/null
+++ b/000582/Sargolini2006/requirements.txt
@@ -0,0 +1,5 @@
+dandi==0.56.1
+jupyter
+plotly==5.17.0
+pynapple==0.3.6
+pynwb==2.5.0
diff --git a/archive_analysis/dandiset_size_plot.ipynb b/archive_analysis/dandiset_size_plot.ipynb
new file mode 100644
index 0000000..d8caa00
--- /dev/null
+++ b/archive_analysis/dandiset_size_plot.ipynb
@@ -0,0 +1,174 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "cb625fe3-1767-4d89-b10b-3d8b45dc18a9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "from datetime import datetime\n",
+    "from tqdm import tqdm\n",
+    "from dandi.dandiapi import DandiAPIClient"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "0bae8e29",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_last_author(metadata):\n",
+    "    if 'contributor' not in metadata:\n",
+    "        return ''\n",
+    "    contributors = metadata['contributor']\n",
+    "    contributors = [\n",
+    "        x for x in contributors \n",
+    "        if x[\"schemaKey\"] == \"Person\" \n",
+    "        and x[\"includeInCitation\"]\n",
+    "    ]\n",
+    "    if not len(contributors):\n",
+    "        return ''\n",
+    "    return contributors[-1][\"name\"]\n",
+    "\n",
+    "def get_data_standard(assetsSummary):\n",
+    "    if 'dataStandard' not in assetsSummary:\n",
+    "        return None\n",
+    "    if not len(assetsSummary['dataStandard']):\n",
+    "        return None\n",
+    "    return assetsSummary['dataStandard'][0].get('identifier', None)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "9fd46fe8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "91it [00:04, 19.68it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "data = []\n",
+    "with DandiAPIClient() as client:\n",
+    "    for dandiset in tqdm(client.get_dandisets()):\n",
+    "        metadata = dandiset.get_raw_metadata()\n",
+    "        assetsSummary = metadata['assetsSummary']\n",
+    "        if get_data_standard(assetsSummary) == 'RRID:SCR_015242':  # NWB\n",
+    "            data.append(\n",
+    "                dict(\n",
+    "                    identifier=dandiset.identifier,\n",
+    "                    created=dandiset.created,\n",
+    "                    size=assetsSummary['numberOfBytes']/1e12,  # TB\n",
+    "                    last_author=get_last_author(metadata),\n",
+    "                    sessions=assetsSummary[\"numberOfFiles\"],\n",
+    "                    subject=assetsSummary.get(\"numberOfSubjects\", 0)\n",
+    "                ) \n",
+    "            )\n",
+    "            \n",
+    "df = pd.DataFrame(data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "d5e4a94f-43c5-47eb-9de3-8be527ac07b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_progress_by_author(df, column_name='size', ax=None, nkeep=9):\n",
+    "    if ax is None:\n",
+    "        fig, ax = plt.subplots(figsize=(10,6))\n",
+    "\n",
+    "    top_authors = df.groupby('last_author').sum().sort_values(column_name, ascending=False).index.values\n",
+    "\n",
+    "    use_author = lambda x: x if x.strip() in top_authors else 'other'\n",
+    "\n",
+    "    top_authors = top_authors[np.logical_not(np.isin(top_authors, ('', 'Last, First')))][:nkeep]\n",
+    "\n",
+    "    df['author_or_other'] = df['last_author'].apply(use_author)\n",
+    "    \n",
+    "    order = np.argsort(df[df['author_or_other'] != 'other'].groupby('author_or_other')['created'].min()).values\n",
+    "    \n",
+    "    top_authors = top_authors[order]\n",
+    "\n",
+    "    data = [np.cumsum(df[column_name] * (df['author_or_other'] == author).astype('int')).to_numpy()\n",
+    "            for author in list(top_authors) + ['other']]\n",
+    "\n",
+    "\n",
+    "    Y = np.vstack(data)\n",
+    "    x = [x.to_pydatetime() for x in df['created']]\n",
+    "\n",
+    "    Y = np.hstack((np.zeros((10,1)), np.repeat(Y, 2, axis=1)))\n",
+    "    x = np.hstack((np.repeat(x, 2), datetime.now()))\n",
+    "\n",
+    "    _ = plt.stackplot(x, Y, labels=list(top_authors) + ['other'])\n",
+    "\n",
+    "    fig.autofmt_xdate()\n",
+    "    plt.legend(loc=2)\n",
+    "    ax.set_xlim((min([_.date() for _ in x]), max([_.date() for _ in x])))\n",
+    "\n",
+    "    return ax\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "07d01e58-c067-43cd-b694-ecb10b546cc2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = plot_progress_by_author(df, 'size')\n",
+    "ax.set_title('top NWB contributors by last author')\n",
+    "ax.set_ylabel('size (TB)')\n",
+    "ax.grid('on')\n",
+    "\n",
+    "plt.savefig('dandi_timeline.pdf')\n",
+    "plt.savefig('dandi_timeline.png', bbox_inches='tight')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tutorials/cosyne_2020/NWB_tutorial_2019.ipynb b/tutorials/cosyne_2020/NWB_tutorial_2019.ipynb
index 54b3a42..67898ce 100755
--- a/tutorials/cosyne_2020/NWB_tutorial_2019.ipynb
+++ b/tutorials/cosyne_2020/NWB_tutorial_2019.ipynb
@@ -141,7 +141,7 @@
    "metadata": {},
    "source": [
     "## Electrodes table\n",
-    "Extracellular electrodes are stored in a `electrodes`, which is a `DynamicTable`. `electrodes` has several required fields: x, y, z, impedance, location, filtering, and electrode_group. Here, we also demonstate how to add optional columns to a table by adding the `'label'` column.<img src=\"images/electrodes_table.png\" width=\"300\">"
+    "Extracellular electrodes are stored in a `electrodes`, which is a `DynamicTable`. `electrodes` has several required fields: x, y, z, impedance, location, filtering, and electrode_group. Here, we also demonstrate how to add optional columns to a table by adding the `'label'` column.<img src=\"images/electrodes_table.png\" width=\"300\">"
    ]
   },
   {
diff --git a/tutorials/cosyne_2020/NWB_tutorial_2019.m b/tutorials/cosyne_2020/NWB_tutorial_2019.m
index 8ad35ad..9841aff 100755
--- a/tutorials/cosyne_2020/NWB_tutorial_2019.m
+++ b/tutorials/cosyne_2020/NWB_tutorial_2019.m
@@ -69,7 +69,7 @@
 % Extracellular |electrodes| are stored in a electrodes, which is a 
 % |DynamicTable|. |electrodes| has several required fields: x, y, z, 
 % impedance, location, filtering, and electrode_group. Here, we also 
-% demonstate how to add optional columns to a table by adding the |'label'|
+% demonstrate how to add optional columns to a table by adding the |'label'|
 % column.
 
 shank_channels = [3, 4];