带有seaborn clustermap的下三角掩码

Question

使用seaborn的聚类图进行分层聚类时如何掩盖下三角形？

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt

#pearson coefficients
corr = np.corrcoef(np.random.randn(10, 200))

#lower triangle
mask = np.tril(np.ones_like(corr))
fig, ax = plt.subplots(figsize=(6,6))

#heatmap works as expected
sns.heatmap(corr, cmap="Blues", mask=mask, cbar=False)

#clustermap not so much
sns.clustermap(corr, cmap="Blues", mask=mask, figsize=(6,6))
plt.show()

Answer 1

嗯，根据相似性对值clustermap 进行聚类。这会更改行和列的顺序。

您可以创建一个常规聚类图，然后在第二步中应用掩码：

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt

corr = np.corrcoef(np.random.randn(10, 200))

g = sns.clustermap(corr, cmap="Blues", figsize=(6, 6))

mask = np.tril(np.ones_like(corr))
values = g.ax_heatmap.collections[0].get_array().reshape(corr.shape)
new_values = np.ma.array(values, mask=mask)
g.ax_heatmap.collections[0].set_array(new_values)

plt.show()