因为需要将结果动画保存为MP4视频文件需要ffmepg软件的的支持。
一:安装ffmpeg软件: ffmpeg是一套可以用来记录、转换数字音频、视频,并能将其转化为流的开源计算机程序。采用LGPL或GPL许可证。它提供了录制、转换以及流化音视频的完整解决方案。下载网址为:https://ffmpeg.zeranoe.com/builds/。本实验下载的是windows 64位Static的版本,下载的压缩包为ffmpeg-20190407-ecdaa4b-win64-static.zip,解压,然后将bin目录加入系统环境变量的路径中,例如解压后bin目录为C:\ProgramFiles\ffmpeg-20190407-ecdaa4b-win64-static\bin。 最后,测试ffmpeg是否配置成功:打开Windows的cmd窗口,输入:ffmpeg -version。如果能看到如下ffmpeg关于软件版本的信息表示成功了。 ffmpeg version N-93542-gecdaa4b4fa Copyright (c) 2000-2019 the FFmpeg developers built with gcc 8.2.1 (GCC) 20190212 configuration: --enable-gpl --enable-version3 --enable-sdl2 --enable-fontconfig --enable-gnutls --enable-iconv --enable-libass --enable-libdav1d --enable-libblu ray --enable-libfreetype --enable-libmp3lame --enable-libopencore-amrnb --enable -libopencore-amrwb --enable-libopenjpeg --enable-libopus --enable-libshine --ena ble-libsnappy --enable-libsoxr --enable-libtheora --enable-libtwolame --enable-l ibvpx --enable-libwavpack --enable-libwebp --enable-libx264 --enable-libx265 --e nable-libxml2 --enable-libzimg --enable-lzma --enable-zlib --enable-gmp --enable -libvidstab --enable-libvorbis --enable-libvo-amrwbenc --enable-libmysofa --enab le-libspeex --enable-libxvid --enable-libaom --enable-libmfx --enable-amf --enab le-ffnvcodec --enable-cuvid --enable-d3d11va --enable-nvenc --enable-nvdec --ena ble-dxva2 --enable-avisynth --enable-libopenmpt libavutil 56. 26.100 / 56. 26.100 libavcodec 58. 48.101 / 58. 48.101 libavformat 58. 27.100 / 58. 27.100 libavdevice 58. 7.100 / 58. 7.100 libavfilter 7. 48.100 / 7. 48.100 libswscale 5. 4.100 / 5. 4.100 libswresample 3. 4.100 / 3. 4.100 libpostproc 55. 4.100 / 55. 4.100
二、运行保存Python示例程序
示例程序一:正弦波动画
""" A simple example of an animated plot """ import numpy as np from matplotlib import pyplot as plt from matplotlib import animation # First set up the figure, the axis, and the plot element we want to animate fig = plt.figure() # create our line object which will be modified in the animation ax = plt.axes(xlim=(0, 2), ylim=(-2, 2)) # we simply plot an empty line: we'll add data to the line later line, = ax.plot([], [], lw=2) # initialization function: plot the background of each frame def init(): line.set_data([], []) return line, # animation function. This is called sequentially # It takes a single parameter, the frame number i def animate(i): x = np.linspace(0, 2, 1000) y = np.sin(2 * np.pi * (x - 0.01 * i)) # update the data line.set_data(x, y) return line, # Makes an animation by repeatedly calling a function func # frames can be a generator, an iterable, or a number of frames. # interval draws a new frame every interval milliseconds. # blit=True means only re-draw the parts that have changed. # 在这里设置一个200帧的动画,每帧之间间隔20毫秒 anim = animation.FuncAnimation(fig, animate, init_func=init, frames=200, interval=20, blit=True) # save the animation as an mp4. This requires ffmpeg or mencoder to be # installed. The extra_args ensure that the x264 codec is used, so that # the video can be embedded in html5. You may need to adjust this for # your system: for more information, see # http://matplotlib.sourceforge.net/api/animation_api.html #保存的动画视频文件名为当前文件夹下的basic_animation.mp4,帧率为30帧每秒,格式为MP4。 anim.save('basic_animation.mp4', fps=30, extra_args=['-vcodec', 'libx264']) plt.show() # plt.show() 会一直循环播放动画
示例程序2:贝叶斯曲线动画
import math import numpy as np import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimation def beta_pdf(x, a, b): return (x ** (a - 1) * (1 - x) ** (b - 1) * math.gamma(a + b) / (math.gamma(a) * math.gamma(b))) class UpdateDist(object): def __init__(self, ax, prob=0.5): self.success = 0 self.prob = prob self.line, = ax.plot([], [], 'k-') self.x = np.linspace(0, 1, 200) self.ax = ax # Set up plot parameters self.ax.set_xlim(0, 1) self.ax.set_ylim(0, 15) self.ax.grid(True) # This vertical line represents the theoretical value, to # which the plotted distribution should converge. self.ax.axvline(prob, linestyle='--', color='black') def init(self): self.success = 0 self.line.set_data([], []) return self.line, def __call__(self, i): # This way the plot can continuously run and we just keep # watching new realizations of the process if i == 0: return self.init() # Choose success based on exceed a threshold with a uniform pick if np.random.rand(1, ) < self.prob: self.success += 1 y = beta_pdf(self.x, self.success + 1, (i - self.success) + 1) self.line.set_data(self.x, y) return self.line, # Fixing random state for reproducibility np.random.seed(19680801) fig, ax = plt.subplots() ud = UpdateDist(ax, prob=0.7) anim = FuncAnimation(fig, ud, frames=np.arange(100), init_func=ud.init, interval=5, blit=True) #保存动画视频文件名为当前文件夹下的bayes_animation.mp4,帧率为30帧每秒,格式为MP4。 anim.save('bayes_animation.mp4', fps=30, extra_args=['-vcodec', 'libx264']) plt.show() 三:运行程序并查看结果。 请注意,以上程序直接在Python的IDE环境中运行,例如PyCharm和Jupyter Notebook,运行可能报错或者只显示一张静态的空白图。 正确的方式是在Windows的cmd命令窗口下,执行命令:python 代码文件名.py。才能看到动态的结果,并且得到相应的MP4文件。