Add sections for proof of concept

_config.yml

@@ -10,7 +10,7 @@ logo: assets/logo.png
 # Information about where the book exists on the web
 repository:
   url: https://github.com/fablabbcn/smartcitizen-analysis-books  # Online location of your book
-  path_to_book: docs  # Optional path to your book, relative to the repository root
+  # path_to_book: books  # Optional path to your book, relative to the repository root
   branch: main  # Which branch of the repository should be used when creating links (optional)
 
 ###### ---------------------------

_toc.yml

@@ -3,9 +3,17 @@
 # Learn more at https://jupyterbook.org/customize/toc.html
 
 format: jb-book
-root: docs/intro
-chapters:
-- file: docs/markdown
-- file: docs/markdown-notebooks
-- file: docs/notebooks
-- file: docs/test
+root: intro
+parts:
+- caption: Development
+  chapters:
+  - file: development/240513_battery-test
+  # - file: development/240719-liu-co2-gps
+
+- caption: Deliveries
+  chapters:
+  - file: deliveries/240719_glasgow-2
+
+# - caption: Insights
+#   chapters:
+#   - file: deliveries/240719_glasgow-2

deliveries/240719_glasgow-2.ipynb

@@ -0,0 +1,226 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "557f54fd-3387-45e1-a4dc-3fafb80753c5",
+   "metadata": {},
+   "source": [
+    "# Glasgow Batch #2\n",
+    "\n",
+    "Smart Citizen Kit 2.1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "54d8d6f4-8a42-4f32-b65d-226d0901be7b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import smartcitizen_connector\n",
+    "import scdata as sc\n",
+    "import time\n",
+    "now = time.localtime()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d5ac091a-dfab-4b5a-b9c4-9133230f7678",
+   "metadata": {},
+   "source": [
+    "## Get devices"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "736b9afb-6a5d-4e17-9b05-78270ea4bc91",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = smartcitizen_connector.search_by_query(endpoint='devices',\n",
+    "                                            search_items=[{\n",
+    "                                                'key': 'postprocessing_id', \n",
+    "                                                'value': 'not_null',\n",
+    "                                                'full': True\n",
+    "                                            }])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2b55009c-805c-4c90-991d-ce202e23d9cb",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "devices = []\n",
+    "for item in df['postprocessing']:\n",
+    "    print (item['device_id'], df.loc[item['device_id'], 'name'], item['meta'])\n",
+    "    if item['meta'] == 'delivery-glasgow 2.1-2':\n",
+    "        devices.append(item['device_id'])\n",
+    "#     if item['meta'] == 'delivery-glasgow-ref':\n",
+    "#       devices.append(item['device_id'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f2e5f2da-8b6a-4646-85f8-a66e9639a084",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "test = sc.Test(name=f'GLASGOW_BATCH_2.1_2',\n",
+    "            devices=[sc.Device(blueprint='sc_air', params=sc.APIParams(id=id)) for id in devices],\n",
+    "        force_recreate = True)\n",
+    "test.options.cache=True"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "208ae3a1-6f07-4849-91c0-63925e77df03",
+   "metadata": {},
+   "source": [
+    "## Load"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "669a1c6e-9324-419e-ac34-decdda6fd6de",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "test = sc.Test(name=f'GLASGOW_BATCH_2.1_2')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d61138dd-7e69-47b1-beaa-a478fbe76531",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "await test.load()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "638cc01c-67cb-483e-bb40-bc733472f837",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "traces = {\n",
+    "            \"1\": {\"devices\": \"all\",\n",
+    "                  \"channel\": \"TEMP\",\n",
+    "                  \"subplot\": 1}\n",
+    "        }\n",
+    "\n",
+    "test.ts_uplot(traces = traces, \n",
+    "              formatting = {'width':1000, \n",
+    "                            'title': 'Temperature', \n",
+    "                            'ylabel': {1: 'Temperature (degC)'}\n",
+    "                           }, \n",
+    "              options = {'frequency': '5Min', 'min_date': '2024-07-10'})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7c1f6f99-fd7b-47ca-9434-bbc768eee636",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "traces = {\n",
+    "            \"1\": {\"devices\": 17642,\n",
+    "                  \"channel\": \"BATT\",\n",
+    "                  \"subplot\": 1}\n",
+    "        }\n",
+    "\n",
+    "test.ts_uplot(traces = traces, \n",
+    "              formatting = {'width':1000, \n",
+    "                            'title': 'Battery', \n",
+    "                            'ylabel': {1: 'Temperature (degC)'}\n",
+    "                           }, \n",
+    "              options = {'frequency': '5Min'})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4f335eb0-6d86-4e5e-ad3b-72c9a19ecf90",
+   "metadata": {},
+   "source": [
+    "## Data completeness"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b7ae9489-7479-43b5-8083-850e2625b40f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "import datetime\n",
+    "\n",
+    "from scdata.tools.date import localise_date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9628726a-3a64-40b6-9fee-11402f29236c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for device in test.devices:\n",
+    "    a = localise_date(datetime.datetime.now(), 'UTC') - device.handler.json.last_reading_at\n",
+    "    hours_ago = round(a.total_seconds() / 3600)\n",
+    "    print (device.id, device.handler.json.last_reading_at, hours_ago)\n",
+    "    plt.figure(figsize=(15,6))\n",
+    "    sns.heatmap(test.get_device(device.id).data.isna().transpose(),\n",
+    "                cmap=\"YlGnBu\",\n",
+    "                cbar_kws={'label': 'Missing Data'}).set(title=f'{test.name}: {device.id} - ({device.handler.json.name}) {hours_ago}h')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2af0b933-7283-46f7-b401-117299b5e40f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.11.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}