对出版质量地块的Python Pylab令pColor选项(Python Pylab pcolor

我试图让DFT（离散傅立叶变换）使用绘制pcolor的蟒蛇。我以前一直使用Mathematica 8.0这样做，但我发现，在数学8.0彩条有坏与我尝试表示数据一比一的关系。举例来说，这里是我策划的数据：

[[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，它在高频能量的DFT矩阵或少量大量零或小的数字。

当我绘制此使用Mathematica，这就是结果：

色条是关闭的，我想我会喜欢与蟒蛇绘制这个代替。我的Python代码（即我从被劫持的位置）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)

而这个Python代码地块为：

现在，这里是我的问题的问题/清单：我喜欢Python和情节这一点，并想利用这一点，但...

如何让所有的“蓝色”代表“0”走开像它在我的数学阴谋呢？
怎样旋转的情节在左上角的鲜红斑？
我设置的方式，“DPI”，是正确的？
任何有用的参考资料，我应该使用，加强对蟒蛇我的爱？

我已经通过在这里的其他问题和numpy的用户手册看起来却发现没有太大的帮助。

我计划在发布此数据，这是比较重要的是，我得到的所有的点点滴滴吧！ :)

编辑：

修改Python代码和生成的情节！一个有什么建议改进这使它出版物值得？

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:

下面将让你更接近你想要什么：

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()

可用色彩映射的默认列表是在这里。你需要一个开出白色。

如果没有这些适合您的需求，您可以尝试生成自己的，通过看开始LinearSegmentedColormap 。

Answer 2:

只是为了记录在案，在数学9.0：

GraphicsGrid@{{MatrixPlot[l, 
    ColorFunction -> (ColorData["TemperatureMap"][Rescale[#, {Min@l, Max@l}]] &), 
    ColorFunctionScaling -> False], BarLegend[{"TemperatureMap", {0, Max@l}}]}}