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ImageMagick
is a powerful, stable and open source toolset and development kit that can be used to read, write and process image files in more than 200 basic formats, including Formats such as PNG, JPEG, GIF, HEIC, TIFF, DPX, EXR, WebP, Postscript, PDF and SVG. Using ImageMagick, you can dynamically generate images according to the needs of web applications. You can also perform operations such as changing the size, rotating, sharpening, subtracting color, or adding special effects to an image (or a group of images), and the results of the operation are displayed in the same format or Save in other formats, the operation of images can be done through the command line or through C/C, Perl, Java, PHP, Python or Ruby programming. ImageMagic's main focus is on performance, reducing bugs, and providing stable APIs and ABIs.
ImageMagick's functions are usually used through the command line, but can also be used programmatically. Programming can choose to call through these interfaces: G2F (Ada), MagickCore (C), MagickWand (C), ChMagick (Ch), ImageMagickObject (COM), Magick (C), JMagick (Java), JuliaIO (Julia), L- Magick (Lisp), Lua (LuaJIT), NMagick (Neko/haXe), Magick.NET (.NET), PascalMagick (Pascal), PerlMagick (Perl), MagickWand for PHP (PHP), IMagick (PHP), PythonMagick (Python ), magick (R), RMagick (Ruby), or TclMagick (Tcl/TK).
Windows Download
Address:
http://www.lfd.uci.edu/~gohlke/pythonlibs/#pythonmagick
Download the "PythonMagick" whl file corresponding to the OS version and Python version, and then install it with the "pip" path whl complete file name in CMD. For example:
pip install C:\Users\Student\Desktop\PythonMagick-0.9.12-cp35-none-win_amd64.whl
Or download through anaconda
Related recommendations : "python video tutorial"
Example
import sys import numpy as np import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimation fig, ax = plt.subplots() fig.set_tight_layout(True) # 询问图形在屏幕上的大小和DPI(每英寸点数) # 注意当把图形保存为文件时,需要为此单独再提供一个DPI print('fig size: {0} DPI, size in inches {1}'.format( fig.get_dpi(), fig.get_size_inches())) # 绘制一个保持不变(不会被重新绘制)的散点图以及初始直线 x = np.arange(0, 20, 0.1) ax.scatter(x, x + np.random.normal(0, 3.0, len(x))) line, = ax.plot(x, x - 5, 'r-', linewidth=2) def update(i): label = 'timestep {0}'.format(i) print(label) # 更新直线和轴(用一个新X轴标签) # 以元组形式返回这一帧需要重新绘制的物体 line.set_ydata(x - 5 + i) ax.set_xlabel(label) return line, ax if __name__ == '__main__': # 会为每一帧调用Update函数 # 这里FunAnimation设置一个10帧动画,每帧间隔200ms anim = FuncAnimation(fig, update, frames=np.arange(0, 10), interval=200) if len(sys.argv) > 1 and sys.argv[1] == 'save': anim.save('line.gif', dpi=80, writer='imagemagick') else: # Plt.show()会一直循环动画 plt.show()
There are two points to note: In the chart Scattered points don't move, what does move are straight lines. The X-axis title changes every frame.
If you want to change to a cooler theme, you can use the seaborn library, just add:
import seaborn
Then you will get the following GIF:
A little reminder: Although the GIF here only has 10 frames and the graphic content is very simple, each frame is still about 160k. Because GIF animations do not use cross-frame compression, this makes GIF images with relatively long frames become very large. Minimizing the number of frames and making each frame smaller (by adjusting the figure size or DPI in matplotlib) can more or less help alleviate this problem.
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