{ "cells": [ { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Geodesic Paths {#geodesic_example}\n\nCalculates the geodesic path between two vertices using Dijkstra\\'s\nalgorithm\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import pyvista as pv\nfrom pyvista import examples\n\n# Load a global topography surface and decimate it\nland = examples.download_topo_land().triangulate().decimate(0.98)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Get the geodesic path as a new `pyvista.PolyData`{.interpreted-text\nrole=\"class\"} object:\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "cape_town = land.find_closest_point((0.790801, 0.264598, -0.551942))\ndubai = land.find_closest_point((0.512642, 0.745898, 0.425255))\nbangkok = land.find_closest_point((-0.177077, 0.955419, 0.236273))\nrome = land.find_closest_point((0.718047, 0.163038, 0.676684))\n\na = land.geodesic(cape_town, dubai)\nb = land.geodesic(cape_town, bangkok)\nc = land.geodesic(cape_town, rome)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Render the path along the land surface\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "p = pv.Plotter()\np.add_mesh(a + b + c, line_width=10, color=\"red\", label=\"Geodesic Path\")\np.add_mesh(land, show_edges=True)\np.add_legend()\np.camera_position = [\n (3.5839785524183934, 2.3915238111304924, 1.3993738227478327),\n (-0.06842917033182638, 0.15467201157962263, -0.07331693636555875),\n (-0.34851770951584765, -0.04724188391065845, 0.9361108965066047),\n]\n\np.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "How long is that path?\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "distance = land.geodesic_distance(cape_town, rome)\ndistance" ] } ], "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": "3.12.2" } }, "nbformat": 4, "nbformat_minor": 0 }