{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Plotting Glyphs (Vectors or PolyData)\n\nUse vectors in a dataset to plot and orient glyphs/geometric objects.\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import numpy as np\nimport pyvista as pv\nfrom pyvista import examples" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Example dataset with normals\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "mesh = examples.load_random_hills()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Glyphying can be done via the\n`pyvista.DataSetFilters.glyph`{.interpreted-text role=\"func\"} filter\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "help(mesh.glyph)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Sometimes you might not want glyphs for every node in the input dataset.\nIn this case, you can choose to build glyphs for a subset of the input\ndataset by using a merging tolerance. Here we specify a merging\ntolerance of five percent which equates to five percent of the bounding\nbox\\'s length.\n\ncreate a subset of arrows using the glyph filter\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "arrows = ..." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "pl = pv.Plotter()\npl.add_mesh(arrows, color=\"black\")\npl.add_mesh(mesh, scalars=\"Elevation\", cmap=\"terrain\", smooth_shading=True)\npl.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A common approach is to load vectors directly to the mesh object and\nthen access the `pyvista.DataSet.arrows`{.interpreted-text role=\"attr\"}\nproperty to produce glyphs.\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "sphere = pv.Sphere(radius=3.14)\n\n# make cool swirly pattern\nvectors = np.vstack(\n (\n np.sin(sphere.points[:, 0]),\n np.cos(sphere.points[:, 1]),\n np.cos(sphere.points[:, 2]),\n )\n).T\nvectors" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# add and scale\nsphere[\"vectors\"] = vectors * 0.3\nsphere.set_active_vectors(\"vectors\")\n\n# plot just the arrows\nsphere.arrows.plot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Plot the arrows and the sphere.\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "pl = pv.Plotter()\npl.add_mesh(sphere.arrows, lighting=False, scalar_bar_args={\"title\": \"Vector Magnitude\"})\npl.add_mesh(sphere, color=\"grey\", ambient=0.6, opacity=0.5, show_edges=False)\npl.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```{=html}\n<center>\n <a target=\"_blank\" href=\"https://colab.research.google.com/github/pyvista/pyvista-tutorial/blob/gh-pages/notebooks/tutorial/04_filters/exercises/e_glyphs.ipynb\">\n <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/ width=\"150px\">\n </a>\n</center>\n```\n" ] } ], "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": "3.12.11" } }, "nbformat": 4, "nbformat_minor": 0 }