用于出版质量图的 Python Pylab pcolor 选项

我正在尝试使用 DFT（离散傅立叶变换）图pcolor在Python中。我之前一直使用 Mathematica 8.0 来执行此操作，但我发现 Mathematica 8.0 中的颜色条与我尝试表示的数据具有不良的一对一相关性。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，DFT 矩阵中存在大量零或少量数字或少量高频能量。

当我使用 mathematica 绘制此图时，结果如下：

颜色条关闭了，我想我想用 python 来绘制它。 我的Python代码（我从here http://glowingpython.blogspot.com/2012/10/visualizing-correlation-matrices.html) is:

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：

现在这是我的问题/问题列表： 我喜欢 python 绘制它的方式，并且想使用它，但是......

1. 如何让所有代表“0”的“蓝色”消失，就像我的数学图中那样？
2. 如何旋转绘图以使左上角出现亮红点？
3. 我设置“dpi”的方式正确吗？
4. 我应该使用哪些有用的参考资料来增强我对 Python 的热爱？

我浏览了这里的其他问题和 numpy 的用户手册，但没有找到太多帮助。

我计划发布这些数据，正确掌握所有细节非常重要！:)

Edit:

修改后的Python代码和结果图！人们会对此提出哪些改进以使其值得发表？

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)

以下内容将使您更接近您想要的：

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()

默认情况下可用的颜色图列表是here http://www.scipy.org/Cookbook/Matplotlib/Show_colormaps。你需要一个一开始是白色的。

如果这些都不满足您的需求，您可以尝试生成自己的，首先查看LinearSegmentedColormap http://matplotlib.org/api/colors_api.html#matplotlib.colors.LinearSegmentedColormap.