2个树状图和凝聚态相关矩阵的热图 [英] 2 Dendrograms + Heatmap from condensed correlationmatrix with scipy

问题描述

我尝试创建如下所示的内容:对ontop层次聚类的结果进行分析数据在python中的矩阵

I try to create something like this: plotting results of hierarchical clustering ontop of a matrix of data in python

不幸的是，当我尝试执行代码时，收到以下警告:

Unfortunatelly when I try to execute the code, I get the following warnings:

Warning (from warnings module):
  File "C:\Users\USER1\Desktop\test.py", line 15
    Y = sch.linkage(D, method='centroid')
ClusterWarning: scipy.cluster: The symmetric non-negative hollow observation matrix looks suspiciously like an uncondensed distance matrix

Warning (from warnings module):
  File "C:\Users\USER1\Desktop\test.py", line 22
    Y = sch.linkage(D, method='single')
ClusterWarning: scipy.cluster: The symmetric non-negative hollow observation matrix looks suspiciously like an uncondensed distance matrix

此外，还会打开一个小窗口，但会崩溃...

In addition, a small window opens but crashes ...

推荐答案

您链接到的代码有问题:它将平方距离矩阵传递给

That code that you linked to has a problem: it passes the square distance matrix to linkage. The first argument of linkage has been a frequent source of confusion, so in recent versions of scipy, the code generates a warning if something that looks like a square distance matrix is passed in.

您必须修改代码，以不将平方距离矩阵传递给 linkage .如果您已经有了这样的矩阵，则可以使用

You'll have to modify your code to not pass a square distance matrix to linkage. If you already have a such a matrix, you can convert it to the condensed form expected by linkage with the function scipy.spatial.distance.squareform.

为避免进一步的混乱，我更新了链接答案中的代码，以使它将压缩的距离矩阵传递给 linkage .

To avoid further confusion, I updated the code in the linked answer so that it passes a condensed distance matrix to linkage.

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