{ "cells": [ { "cell_type": "markdown", "metadata": { "nbsphinx": "hidden" }, "source": [ "This notebook is part of the *orix* documentation https://orix.readthedocs.io. Links to the documentation won’t work from the notebook." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Visualizing Crystal Poles in the Pole Density Function\n", "\n", "In this tutorial we will quantify the distribution of crystallographic poles, which is useful, for example, in texture analysis, using the Pole Distribution Function (PDF)." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", "from mpl_toolkits.mplot3d import Axes3D\n", "from orix import plot\n", "from orix.crystal_map import Phase\n", "from orix.data import ti_orientations\n", "from orix.sampling import sample_S2\n", "from orix.vector import Miller, Vector3d\n", "\n", "# We'll want our plots to look a bit larger than the default size\n", "plt.rcParams.update(\n", " {\n", " \"figure.figsize\": (10, 5),\n", " \"lines.markersize\": 2,\n", " \"font.size\": 15,\n", " \"axes.grid\": False,\n", " }\n", ")\n", "w, h = plt.rcParams[\"figure.figsize\"]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First, we load some sample orientations from a Titanium sample dataset which represent crystal orientations in the sample reference frame.\n", "These orientations have a defined $622$ point group symmetry:\n", "\n", "