{ "cells": [ { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import sys\n", "\n", "sys.path.append(\"../..\") # add the pde package to the python path\n", "import pde" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# initialize the grid, an initial condition, and the PDE\n", "grid = pde.UnitGrid([32, 32])\n", "field = pde.ScalarField.random_uniform(grid, -1, 1)\n", "eq = pde.DiffusionPDE()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# try our explicit solver\n", "solver = pde.EulerSolver(eq)\n", "controller = pde.Controller(solver, t_range=1)\n", "sol1 = controller.run(field, dt=1e-3);" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# try the standard scipy solver\n", "solver = pde.ScipySolver(eq)\n", "controller = pde.Controller(solver, t_range=1)\n", "sol2 = controller.run(field);" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# plot both fields and give the deviation as the title\n", "title = f\"Mean squared deviation: {((sol1 - sol2) ** 2).average:.2g}\"\n", "pde.FieldCollection([sol1, sol2]).plot(title=title)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.12.0" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false 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