我有多维数组。一旦它在最后一个维度中具有临界值，我想改变维度的尾部。
np.random.seed(100)
arr = np.random.uniform(size=100).reshape([2,5,2,5])
# array([[[[ 0.54340494, 0.27836939, 0.42451759, 0.84477613, 0.00471886],
# [ 0.12156912, 0.67074908, 0.82585276, 0.13670659, 0.57509333]],
# [[ 0.89132195, 0.20920212, 0.18532822, 0.10837689, 0.21969749],
# [ 0.97862378, 0.81168315, 0.17194101, 0.81622475, 0.27407375]],
# [[ 0.43170418, 0.94002982, 0.81764938, 0.33611195, 0.17541045],
# [ 0.37283205, 0.00568851, 0.25242635, 0.79566251, 0.01525497]],
# [[ 0.59884338, 0.60380454, 0.10514769, 0.38194344, 0.03647606],
# [ 0.89041156, 0.98092086, 0.05994199, 0.89054594, 0.5769015 ]],
# [[ 0.74247969, 0.63018394, 0.58184219, 0.02043913, 0.21002658],
# [ 0.54468488, 0.76911517, 0.25069523, 0.28589569, 0.85239509]]],
# [[[ 0.97500649, 0.88485329, 0.35950784, 0.59885895, 0.35479561],
# [ 0.34019022, 0.17808099, 0.23769421, 0.04486228, 0.50543143]],
# [[ 0.37625245, 0.5928054 , 0.62994188, 0.14260031, 0.9338413 ],
# [ 0.94637988, 0.60229666, 0.38776628, 0.363188 , 0.20434528]],
# [[ 0.27676506, 0.24653588, 0.173608 , 0.96660969, 0.9570126 ],
# [ 0.59797368, 0.73130075, 0.34038522, 0.0920556 , 0.46349802]],
# [[ 0.50869889, 0.08846017, 0.52803522, 0.99215804, 0.39503593],
# [ 0.33559644, 0.80545054, 0.75434899, 0.31306644, 0.63403668]],
# [[ 0.54040458, 0.29679375, 0.1107879 , 0.3126403 , 0.45697913],
# [ 0.65894007, 0.25425752, 0.64110126, 0.20012361, 0.65762481]]]])
假设临界值为0.80。在我们看到高于 的值后，我们需要改变所有进一步的值0.80。我们关注前两个“行”。代表用[3,2]选择后np.argmax。
where_bigger = np.argmax(arr >= 0.80, axis = 3)
# array([[[3, 2], ## used as example later !!!!!!!!!
# [0, 0],
# [1, 0],
# [0, 0],
# [0, 4]],
# [[0, 0],
# [4, 0],
# [3, 0],
# [3, 1],
# [0, 0]]])
例如，我们首先关注带有索引3的元素[3,2]（参见上面的 !!!!）。一旦我们发现值高于0.80（此类索引3），所有以下值都应替换为np.na
arr[0,0,0,3] ## 0.84477613 comes as first element in [3,2]
# [ 0.54340494, 0.27836939, 0.42451759, 0.84477613, np.na]
与此类似，我们关注元素2out，[3,2]需要将所有后续元素设置为np.na
arr[0,0,1,2] ## 0.82585276 comes as second element in [3,2]
# [ 0.12156912, 0.67074908, 0.82585276, np.na, np.na]
最后，我们对 argmax 找到的所有元素重复它：
# array([[[[ 0.54340494, 0.27836939, 0.42451759, 0.84477613, np.na],
# [ 0.12156912, 0.67074908, 0.82585276, np.na, np.na]],
# [[ 0.89132195, np.na, np.na, np.na, np.na],
# [ 0.97862378, np.na, np.na, np.na, np.na]],
# [[ 0.43170418, 0.94002982, np.na, np.na, np.na],
# ...
是否可以在不循环的情况下一次调整整个数组？可能有可能与切片有关。我想使用一些类似的方法
arr[where_bigger:] = np.na，但这显然是错误的。到目前为止，我无法进一步进步。