查看“Matplotlib”的源代码

* ''' ipython中事先执行 %matplotlib '''
* 参见 [https://matplotlib.org/index.html] [http://www.cnblogs.com/wei-li/archive/2012/05/23/2506940.html]

==plot==
*'''import matplotlib.plot as plt'''

*初始化 clear
 plt.clf()
* Tweak spacing to prevent clipping of ylabel
 plt.tight_layout()

* 简单的例子
 import numpy as np
 import matplotlib.pyplot as plt
 x = np.arange(0, 5, 0.1);
 y = np.sin(x)
 plt.clf()  #clear the current figure
 plt.subplot(211)
 plt.plot(x, y)
 plt.show()
 plt.xlim(0,3)  #调整坐标范围
:* options for the color characters are: 'r' , 'g' , 'b' = blue, 'c' = cyan, 'm' = magenta, 'y' = yellow, 'k' = black, 'w' = white
:* Options for line styles are:  '-' = solid, '--' = dashed, ':' = dotted, '-.' = dot-dashed, '.' = points,  'o' = filled circles,  '^' = filled triangles
:* marker style [https://matplotlib.org/api/markers_api.html]

*直方图 num_bins = 50
 fig, ax = plt.subplots()
 # the histogram of the data
 n, bins, patches = ax.hist(x, 50, normed=1)

*对数坐标 
:semilogx  #x轴对数
:semilogy  #y轴对数
:set_xscale("log", nonposx='clip')
:set_yscale("log", nonposy='clip')

* 误差棒 
:errorbar(x, y, xerr=0.1 * x, yerr=5.0 + 0.75 * y, ls='None', marker='s') #ls='None' 不连线

*grid
:ax.grid()

*设置坐标轴的极限
:ax.set_ylim(ymin=0.1)
:参见[https://matplotlib.org/gallery/scales/log_demo.html]

*产生多个图形窗口
 plt.figure(1)
 plt.figure(2)

*pmesh,pcolormesh: 画二维的平面分布的图
*colorbar

==图像==
* matplotlib里面可以用axes.imshow()
 delta = 0.025
 x = y = np.arange(-3.0, 3.0, delta)
 X, Y = np.meshgrid(x, y)
 Z = np.exp(-X**2 - Y**2)
 fig, ax = plt.subplots()
 im = ax.imshow(Z, interpolation='bilinear', cmap=cm.RdYlGn,
               origin='lower', extent=[-3, 3, -3, 3],
               vmax=abs(Z).max(), vmin=-abs(Z).max())     #lower 就是把index[0,0]放在左下，extent是数轴上标志的范围
* pylot.imshow(Z)

== 保存图片文件==
*plt.savefig("filename.png")
*plt.savefig('SFH_LMC_miles.pdf',format='pdf')
*保存文件一片空白
:在 plt.show() 后调用了 plt.savefig() ，在 plt.show() 后实际上已经创建了一个新的空白的图片（坐标轴），这时候你再 plt.savefig() 就会保存这个新生成的空白图片。
::plt.show() 放在最后，或者
     # gcf: Get Current Figure
    fig = plt.gcf()
    plt.show()
    fig1.savefig('tessstttyyy.png', dpi=100)