用于出版质量图的Python Pylab pcolor选项

Question

我试图pcolor在python中使用DFT(离散傅立叶变换)图.我以前一直在使用Mathematica 8.0来做这个,但我发现mathematica 8.0中的colorbar与我试图表示的数据有一对一的不良关联.例如,这是我正在绘制的数据:

[[0.,0.,0.10664,0.,0.,0.,0.0412719,0.,0.,0.],
[0.,0.351894,0.,0.17873,0.,0.,0.,0.,0.,0.],
[0.10663,0.,0.178183,0.,0.,0.,0.0405148,0.,0.,0.],
[0.,0.177586,0.,0.,0.,0.0500377,0.,0.,0.,0.],
[0.,0.,0.,0.,0.0588906,0.,0.,0.,0.,0.],
[0.,0.,0.,0.0493811,0.,0.,0.,0.,0.,0.],
[0.0397341,0.,0.0399249,0.,0.,0.,0.,0.,0.,0.],
[0.,0.,0.,0.,0.,0.,0.,0.,0.,0.],
[0.,0.,0.,0.,0.,0.,0.,0.,0.,0.],
[0.,0.,0.,0.,0.,0.,0.,0.,0.,0.]]

因此,它在DFT矩阵或少量高频能量中有很多零或小数.

当我使用mathematica绘制这个时,这就是结果:

颜色条是关闭的,我想我想用python来绘制它.我的python代码(我从这里劫持)是:

from numpy import corrcoef, sum, log, arange
from numpy.random import rand
#from pylab import pcolor, show, colorbar, xticks, yticks
from pylab import *


data = np.array([[0.,0.,0.10664,0.,0.,0.,0.0412719,0.,0.,0.],
[0.,0.351894,0.,0.17873,0.,0.,0.,0.,0.,0.], 
[0.10663,0.,0.178183,0.,0.,0.,0.0405148,0.,0.,0.],
[0.,0.177586,0.,0.,0.,0.0500377,0.,0.,0.,0.],
[0.,0.,0.,0.,0.0588906,0.,0.,0.,0.,0.],
[0.,0.,0.,0.0493811,0.,0.,0.,0.,0.,0.],
[0.0397341,0.,0.0399249,0.,0.,0.,0.,0.,0.,0.],
[0.,0.,0.,0.,0.,0.,0.,0.,0.,0.],
[0.,0.,0.,0.,0.,0.,0.,0.,0.,0.],
[0.,0.,0.,0.,0.,0.,0.,0.,0.,0.]], np.float)

pcolor(data)
colorbar()
yticks(arange(0.5,10.5),range(0,10))
xticks(arange(0.5,10.5),range(0,10))
#show()
savefig('/home/mydir/foo.eps',figsize=(4,4),dpi=100)

这个python代码绘制为:

现在这里是我的问题/问题列表:我喜欢python如何绘制这个并且想要使用它但是......

1. 如何使所有代表"0"的"蓝色"像我在mathematica情节中那样消失？
2. 如何旋转绘图以在左上角有明亮的红点？
3. 我设置"dpi"的方式是正确的吗？
4. 我应该用什么有用的参考来加强我对python的热爱？

我已经查看了这里的其他问题和numpy的用户手册,但发现没什么帮助.

我计划发布这些数据,这对我来说非常重要! :)

编辑:

修改了python代码和结果图!为了使出版物值得,有人会对此提出哪些改进建议？

from numpy import corrcoef, sum, log, arange, save
from numpy.random import rand

from pylab import *


data = np.array([[0.,0.,0.10664,0.,0.,0.,0.0412719,0.,0.,0.],
[0.,0.351894,0.,0.17873,0.,0.,0.,0.,0.,0.],
[0.10663,0.,0.178183,0.,0.,0.,0.0405148,0.,0.,0.],   
[0.,0.177586,0.,0.,0.,0.0500377,0.,0.,0.,0.],
[0.,0.,0.,0.,0.0588906,0.,0.,0.,0.,0.],
[0.,0.,0.,0.0493811,0.,0.,0.,0.,0.,0.],
[0.0397341,0.,0.0399249,0.,0.,0.,0.,0.,0.,0.],
[0.,0.,0.,0.,0.,0.,0.,0.,0.,0.],
[0.,0.,0.,0.,0.,0.,0.,0.,0.,0.],
[0.,0.,0.,0.,0.,0.,0.,0.,0.,0.]], np.float)

v1 = abs(data).max()
v2 = abs(data).min()
pcolor(data, cmap="binary")
colorbar()
#xlabel("X", fontsize=12, fontweight="bold")
#ylabel("Y", fontsize=12, fontweight="bold")
xticks(arange(0.5,10.5),range(0,10),fontsize=19)
yticks(arange(0.5,10.5),range(0,10),fontsize=19)
axis([0,7,0,7])
#show()


savefig('/home/mydir/Desktop/py_dft.eps',figsize=(4,4),dpi=600)

Answer 1

以下内容将使您更接近您想要的内容:

import matplotlib.pyplot as plt

plt.pcolor(data, cmap=plt.cm.OrRd)
plt.yticks(np.arange(0.5,10.5),range(0,10))
plt.xticks(np.arange(0.5,10.5),range(0,10))
plt.colorbar()
plt.gca().invert_yaxis()
plt.gca().set_aspect('equal')
plt.show()

默认情况下,可用的色彩映射列表在此处.你需要一个白色的.

如果这些都不符合您的需求,您可以尝试自己创建,从查看开始LinearSegmentedColormap.