{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Cimetidine tutorial: indexing, spacegroup determination & structure solution\n", "In this notebook, you can:\n", "* Load the powder diffraction data and create the PowderPattern object\n", "* Find the diffraction peaks and index them (determine the unit cell)\n", "* Perform a profile fit to optimise the background and reflection profiles\n", "* Determine the spacegroup\n", "* Add a molecule to describe the contents of the Crystal structure\n", "* Solve the Crystal structure using a Monte-Carlo/Parallel tempering algorithm\n", "* Save the best result to a CIF file and to Fox .xmlgz format\n", "\n", "Notes:\n", "* This is an *ideal* case for structure solution from powder diffraction - a clean powder diffraction data easily indexed, an unambiguous spacegroup, and a relatively simple structure.\n", "* It is important to follow the steps relatively linearly and avoid going back to previous cells until you know better. For example to avoid adding multiple times Scatterer/Molecule objects in the crystal structure, or multiple crystalline phases to the powder pattern with the same crystal, etc..." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Imports" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# 'widget' allows live update and works in both classical notebooks and jupyter-lab.\n", "# Otherwise 'notebook', 'ipympl', 'inline' can be used\n", "%matplotlib widget\n", "\n", "import os\n", "import pyobjcryst\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from pyobjcryst.crystal import *\n", "from pyobjcryst.powderpattern import *\n", "from pyobjcryst.indexing import *\n", "from pyobjcryst.molecule import *\n", "from pyobjcryst.globaloptim import MonteCarlo\n", "from pyobjcryst.io import xml_cryst_file_save_global\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Create powder pattern object, download data if necessary" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Imported powder pattern: 7699 points, 2theta= 8.010 -> 84.990, step= 0.010\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "3f34531dc9e64573a36bff683962b002", "version_major": 2, "version_minor": 0 }, "image/png": "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", "text/html": [ "\n", "
3Dmol.js failed to load for some reason. Please check your browser console for error messages.
3Dmol.js failed to load for some reason. Please check your browser console for error messages.
3Dmol.js failed to load for some reason. Please check your browser console for error messages.
3Dmol.js failed to load for some reason. Please check your browser console for error messages.