Python 颜色映射，但所有零值都映射到黑色 [英] Python color map but with all zero values mapped to black

问题描述

我有一个对应于格点的元素的方形阵列.一些元素为零，其余元素在 1 到 2700 之间变化.使用 imshow 和 OrRd 颜色图，我希望所有大于 0 的点阵站点都显示相应的颜色，但重要的是，所有值为 0 的站点都是显示为黑色.我尝试定义一个新的颜色映射如下:

I have a square array of elements which correspond to lattice sites. Some of the elements are zero and the rest vary between 1 and about 2700. Using imshow and the OrRd colour map, I want all lattice sites greater than 0 to display the corresponding colour but importantly, all sites with value 0 to be displayed as black. I have tried defining a new color map as follows:

colors = [(0,0,0)] + [(pylab.cm.OrRd(i)) for i in range(1,256)] 
new_map = matplotlib.colors.LinearSegmentedColormap.from_list('new_map', colors, N=256)

但是我的数组中的值范围太大，因此很多非零值显示为黑色.

but the range of values in my array is too large and so a lot of non-zero values get displayed as black.

非常感谢.

推荐答案

Matplotlib 的颜色图有一个 set_bad 和 set_under 属性，可用于此目的.这个例子展示了如何使用 set_bad

The colormaps of Matplotlib have a set_bad and set_under property which can be used for this. This example shows how to use the set_bad

import matplotlib.pyplot as plt
import numpy as np

# make some data
a = np.random.randn(10,10)

# mask some 'bad' data, in your case you would have: data == 0
a = np.ma.masked_where(a < 0.05, a)

# cmap = plt.cm.OrRd

# for mpl 3.3 and higher use
cmap = mpl.cm.get_cmap("OrRd").copy()

cmap.set_bad(color='black')

im = plt.imshow(a, interpolation='none', cmap=cmap)

要使用 set_under 变体，您必须将 vmin 关键字添加到绘图命令中，并且设置略高于零(但低于任何其他有效值):

To use the set_under variant you have to add the vmin keyword to the plotting command and setting is slightly above zero (but below any other valid value):

cmap.set_under(color='black')    
im = plt.imshow(a, interpolation='none', cmap=cmap, vmin=0.0000001)

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