{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Animation\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "%matplotlib inline\n", "\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "from matplotlib import animation, rc\n", "from IPython.display import HTML\n", "\n", "\n", "# First set up the figure, the axis, and the plot element we want to animate\n", "fig, ax = plt.subplots()\n", "\n", "ax.set_xlim(( 0, 2))\n", "ax.set_ylim((-2, 2))\n", "\n", "line, = ax.plot([], [], lw=2)\n", "\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\n", "# initialization function: plot the background of each frame\n", "def init():\n", " line.set_data([], [])\n", " return (line,)\n", "\n", "# animation function. This is called sequentially\n", "def animate(i):\n", " x = np.linspace(0, 2, 1000)\n", " y = np.sin(2 * np.pi * (x - 0.01 * i))\n", " line.set_data(x, y)\n", " return (line,)\n", "\n", "# call the animator. blit=True means only re-draw the parts that have changed.\n", "anim = animation.FuncAnimation(fig, animate, init_func=init,\n", " frames=100, interval=20, blit=True)\n", "\n", "HTML(anim.to_html5_video())" ] } ], "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": "3.5.2" }, "main_language": "python" }, "nbformat": 4, "nbformat_minor": 2 }