{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Render\n", "\n", "This is done through rendering the figure first and then reload it in a FuncAnimation with imshow.\n", "Therefore the zoom function is limited to the resolution of the figure." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import tqdm\n", "\n", "from smpl import animation, plot" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## live-render" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%matplotlib notebook \n", "plt.ioff()\n", "\n", "\n", "def update(a):\n", " plot.function(lambda x: a * x**2, xmin=0, xmax=5, init=True, tight=False)\n", "\n", "\n", "ani = animation.animate(\n", " update=update, frames=np.linspace(0, 10, 200), interval=10, blit=True\n", ")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "## pre-render" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%matplotlib notebook \n", "plt.ioff()\n", "for a in tqdm.tqdm(np.linspace(0, 10, 200)):\n", " # no need to bind a here since the lambda is only evaluated in the function\n", " plot.function(lambda x: a * x**2, xmin=0, xmax=5, init=True, tight=False)\n", " animation.frame()\n", "\n", "# ani.save(\"test.gif\")\n", "ani = animation.animate(interval=10, blit=True)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Save" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "ani.save(\"test.gif\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "\n", "from smpl import animation, plot\n", "\n", "for a in np.linspace(0, 10, 200):\n", " # no need to bind a here since the lambda is only evaluated in the function\n", " plot.function(lambda x: a * x**2, xmin=0, xmax=5, init=True, tight=False)\n", " animation.frame()\n", "\n", "ani = animation.animate(interval=10, blit=True)\n", "ani.widget_gif()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "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": "3.9.15" }, "widgets": { "application/vnd.jupyter.widget-state+json": { "state": {}, "version_major": 2, "version_minor": 0 } } }, "nbformat": 4, "nbformat_minor": 4 }