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我有一个二维数据数组。我需要平均每两行,并返回一个高度为一半的数组的平均值。为了平均目的,我还需要忽略所有 NaN 值。例如:

>>> x = numpy.array([[ 1,  nan,  3,  4,  5],
... [ 6,  7,  8,  9, nan],
... [11, 12, 13, 14, nan],
... [16, nan, 18, 19, nan]])

该函数需要返回:

>>> x
array([[3.5,  7,  5.5,  6.5,  5],
[13.5, 12, 15.5, 16.5, nan]])
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1 回答 1

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This should do the trick:

numpy.ma.average(numpy.ma.masked_invalid(x).reshape(-1, 2, x.shape[-1]), 1)

For me it returns

masked_array(data =
 [[3.5 7.0 5.5 6.5 5.0]
 [13.5 12.0 15.5 16.5 --]],
             mask =
 [[False False False False False]
 [False False False False  True]],
       fill_value = 1e+20)
于 2012-09-11T04:33:11.250 回答