我是靠谱客的博主 细心柠檬,最近开发中收集的这篇文章主要介绍Python利用matplotlib.animation和matplotlib.pyplot和ffmpeg录制动画并保存为MP4文件,觉得挺不错的,现在分享给大家,希望可以做个参考。

概述

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:ProgramFilesffmpeg-20190407-ecdaa4b-win64-staticbin。 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。

最后

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