仅绘制热图的上/下三角形

Doug提供的答案的问题在于它依赖于这样一个事实:颜色映射将零值映射为白色。这意味着不包括白色的颜色映射是不有用的。解决的关键是 cm.set_bad 功能。您可以用无或numpy屏蔽数组屏蔽矩阵中不需要的部分,以及 set_bad 变为白色,而不是默认的黑色。采用Doug的例子,我们得到以下结果:

import numpy as NP
from matplotlib import pyplot as PLT
from matplotlib import cm as CM

A = NP.random.randint(10, 100, 100).reshape(10, 10)
mask =  NP.tri(A.shape[0], k=-1)
A = NP.ma.array(A, mask=mask) # mask out the lower triangle
fig = PLT.figure()
ax1 = fig.add_subplot(111)
cmap = CM.get_cmap('jet', 10) # jet doesn't have white color
cmap.set_bad('w') # default value is 'k'
ax1.imshow(A, interpolation="nearest", cmap=cmap)
ax1.grid(True)
PLT.show()

import numpy as NP
from matplotlib import pyplot as PLT
from matplotlib import cm as CM

A = NP.random.randint(10, 100, 100).reshape(10, 10)
# create an upper triangular 'matrix' from A
A2 = NP.triu(A)
fig = PLT.figure()
ax1 = fig.add_subplot(111)
# use dir(matplotlib.cm) to get a list of the installed colormaps
# the "_r" means "reversed" and accounts for why zero values are plotted as white
cmap = CM.get_cmap('gray_r', 10)
ax1.imshow(A2, interpolation="nearest", cmap=cmap)
ax1.grid(True)
PLT.show()

plot http://img444.imageshack.us/img444/9585/cmapgrayr.png

可以在一个白色矩阵上绘制上部/下部透明的图。

a =random((10,10))
imshow(a, interpolation='nearest')

b = ones(a.shape+(4,)) # «white» matrix with alpha=1
for i in range(a.shape[0]):
    for j in range(i, a.shape[1]):
        b[i,j,3] = 0   # upper triangle, alpha = 0
imshow(b, interpolation='nearest')

upper/lower triangle of a heatmap http://lh5.ggpht.com/_ZgVr3-a-Z00/S4P3_BWByKI/AAAAAAAAAXE/UsJpokz6LKE/pp.png

用 seaborn , matplotlib 和 numpy ,一个快速的解决方案是:

import matplotlib.pyplot as plt
import seaborn as sns

# Say your matrix object (e.g. np.array) is corr_mat

# Get the upper triangle without the diagonal 
corr_mat = np.triu(corr_mat, k=1)

# Plot the heatmap
ax = sns.heatmap(corr_mat)

请参阅 西伯恩 联机文档进行补充。