如何识别numpy数组中具有最大平均值的列？ [英] How can I identify the column with the greatest average in a numpy array?

问题描述

给出以下数组：

    complete_matrix = numpy.array([
    [0, 1, 2, 4],
    [1, 0, 3, 5],
    [2, 3, 0, 6]])

我想确定平均值最高的列，不包括对角线零。因此，在这种情况下，我将能够确定complete_matrix [：，3]为平均值最高的列。

I would like to identify the column with the highest average, excluding the diagonal zeros. So, in this case, I would be able to identify complete_matrix[:,3] as being the column with the highest average.

推荐答案

这个问题与这里的问题是否有所不同：在numpy数组中查找具有最高平均值的行

Is this question different from the one here: Finding the row with the highest average in a numpy array

据我了解，唯一的区别是这篇文章中的矩阵不是方阵。如果这是故意的，则可以尝试使用权重。由于我无法完全理解您的意图，因此以下解决方案将0权重分配给零项，否则分配1权重：

As far as I understand, the only difference is the matrix in this post isn't a square matrix. In case this was deliberate, you could try using weights. Since I do not understand your intent fully, the following solution assigns 0 weight to zero entries, 1 otherwise:

numpy.argmax(numpy.average(complete_matrix,axis=0, weights=complete_matrix!=0))

您可以随时创建一个权重矩阵，其中对角线条目的权重为0，否则为1。

You can always create a weight matrix where the weight is 0 for diagonal entries, and 1 otherwise.

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