numpy:堆叠被遮罩的数组并计算最小/最大 [英] Numpy: Stacking masked Arrays and calculating min/max

问题描述

我正在使用蒙版数组，我想计算不同数组/列的最大值.如果整个数组都被遮罩，我会遇到问题.

I'm working with masked arrays and I want to calculate the max of different arrays/columns. I have problems, if the whole array is masked.

示例:

import numpy as np

x = np.ma.array(np.array([1,2,3,4,100]),mask=[True,True,True, True, True])
y = 5

print(np.max(np.hstack((x, y))))
print np.max((np.max(y), np.max(x)))
print(np.max((np.hstack((np.max(x), 5)))))

结果:

100
nan
--

我发现结果很奇怪，因为结果应该是5.为什么hstack()忽略了 遮罩数组的遮罩?

I find the result odd, because the result should be 5. Why is hstack() ignoring the mask of the masked array?

推荐答案

对于带掩码的数组，您需要使用带掩码的例程，即numpy.ma.应该在方法名称之前:

With masked arrays, you need to use masked routines, that is numpy.ma. should precede method name:

>>> np.ma.hstack((x, y))
masked_array(data = [-- -- -- -- -- 5],
             mask = [ True  True  True  True  True False],
       fill_value = 999999)

>>> np.ma.max(np.ma.hstack((x, y)))
5

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