Local point-by-point indexing notebook

ImageD11/nbGui/S3DXRD/1_2_3_S3DXRD_pbp_indexing_local.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# There is a bug with the current version of ImageD11 in the site-wide Jupyter env.\n",
+    "# This has been fixed here: https://github.com/FABLE-3DXRD/ImageD11/commit/4af88b886b1775585e868f2339a0eb975401468f\n",
+    "# Until a new release has been made and added to the env, we need to get the latest version of ImageD11 from GitHub\n",
+    "# Put it in your home directory\n",
+    "# USER: Change the path below to point to your local copy of ImageD11:\n",
+    "\n",
+    "import os\n",
+    "\n",
+    "username = os.environ.get(\"USER\")\n",
+    "\n",
+    "id11_code_path = f\"/home/esrf/{username}/Code/ImageD11\"\n",
+    "\n",
+    "import sys\n",
+    "\n",
+    "sys.path.insert(0, id11_code_path)\n",
+    "\n",
+    "os.environ['OMP_NUM_THREADS']='1'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "from matplotlib import pyplot as plt\n",
+    "%matplotlib ipympl\n",
+    "\n",
+    "import ImageD11.sinograms.point_by_point\n",
+    "import ImageD11.sinograms.dataset\n",
+    "import ImageD11.sinograms.properties\n",
+    "import ImageD11.columnfile\n",
+    "\n",
+    "import ImageD11.nbGui.nb_utils as utils"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# NOTE: For old datasets before the new directory layout structure, we don't distinguish between RAW_DATA and PROCESSED_DATA\n",
+    "\n",
+    "### USER: specify your experimental directory\n",
+    "\n",
+    "rawdata_path = \"/home/esrf/james1997a/Data/ihma439/id11/20231211/RAW_DATA\"\n",
+    "\n",
+    "!ls -lrt {rawdata_path}\n",
+    "\n",
+    "### USER: specify where you want your processed data to go\n",
+    "\n",
+    "processed_data_root_dir = \"/home/esrf/james1997a/Data/ihma439/id11/20231211/PROCESSED_DATA/James/20240226\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# USER: pick a sample and a dataset you want to segment\n",
+    "\n",
+    "sample = \"FeAu_0p5_tR_nscope\"\n",
+    "dataset = \"top_250um\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# desination of H5 files\n",
+    "\n",
+    "dset_path = os.path.join(processed_data_root_dir, sample, f\"{sample}_{dataset}\", f\"{sample}_{dataset}_dataset.h5\")\n",
+    "\n",
+    "# USER: specify the path to the parameter file\n",
+    "\n",
+    "par_path = os.path.join(processed_data_root_dir, 'Fe_refined.par')\n",
+    "\n",
+    "e2dx_path = os.path.join(processed_data_root_dir, '../../CeO2/e2dx_E-08-0173_20231127.edf')\n",
+    "e2dy_path = os.path.join(processed_data_root_dir, '../../CeO2/e2dy_E-08-0173_20231127.edf')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Load the dataset\n",
+    "dset = ImageD11.sinograms.dataset.load(dset_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Import the 2D columnfile, or make it if it doesn't exist\n",
+    "\n",
+    "if os.path.exists(dset.col2dfile):\n",
+    "    cf_2d = ImageD11.columnfile.colfile_from_hdf(dset.col2dfile)\n",
+    "else:\n",
+    "    # Import 2D peaks, make a spatially corrected columnfile, save it\n",
+    "    peaks_table = ImageD11.sinograms.properties.pks_table.load(dset.pksfile)\n",
+    "\n",
+    "    # Grab the 2d peak centroids\n",
+    "    peaks_2d = peaks_table.pk2d(dset.omega, dset.dty)\n",
+    "    cf_2d = utils.tocolf(peaks_2d, par_path, e2dx_path, e2dy_path)\n",
+    "\n",
+    "    # save the 2D peaks to file so we don't have to spatially correct them again\n",
+    "    ImageD11.columnfile.colfile_to_hdf(cf_2d, dset.col2dfile)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# filter the columnfile to discard weak peaks\n",
+    "\n",
+    "cf_2d.filter(cf_2d.Number_of_pixels > 5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "pbp_object = ImageD11.sinograms.point_by_point.PBP(par_path,\n",
+    "                                                    dset,\n",
+    "                                                    hkl_tol=0.01,\n",
+    "                                                    fpks=0.9,\n",
+    "                                                    ds_tol=0.01,\n",
+    "                                                    etacut=0.1,\n",
+    "                                                    ifrac=1./300,\n",
+    "                                                    cosine_tol=np.cos(np.radians(90 - 0.25)),\n",
+    "                                                    y0=-7.985,\n",
+    "                                                    symmetry=\"cubic\",\n",
+    "                                                    foridx=[0, 1, 2, 3, 4, 5],\n",
+    "                                                    forgen=[5, 1],\n",
+    "                                                    uniqcut=0.9)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "pbp_object.setpeaks(cf_2d)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "fig, ax = pbp_object.iplot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "dset.pbpfile = os.path.join(dset.analysispath, dset.dsname + '_pbp_index.pbp')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "pbp_object.point_by_point(dset.pbpfile, loglevel=3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (main)",
+   "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": "3.11.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}