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[英]Get the max of the sum of consecutive non-nans values along an axis in 3D numpy array
[英]Python: Find max value along one axis in 3d matrix, make non-max values zero
我有一个如下所示的 3-d 矩阵,并希望沿轴 1 取最大值,并将所有非最大值保持为零。
A = np.random.rand(3,3,2)
[[[0.34444547, 0.50260393],
[0.93374423, 0.39021899],
[0.94485653, 0.9264881 ]],
[[0.95446736, 0.335068 ],
[0.35971558, 0.11732342],
[0.72065402, 0.36436023]],
[[0.56911013, 0.04456443],
[0.17239996, 0.96278067],
[0.26004909, 0.06767436]]]
想要的结果:
[[0 , 0 ],
[0 , 0 ],
[0.94485653, 0.9264881]],
[[0.95446736, 0 ],
[0 , 0 ],
[0 , 0.36436023]],
[[0.56911013, 0 ],
[0 , 0.96278067],
[0 , 0 ]]])
我试过了:
B = np.zeros_like(A) #return matrix of zero with same shape as A
max_idx = np.argmax(A, axis=1) #index along axis 1 with max value
array([[2, 0],
[2, 2],
[0, 2],
[0, 1]])
C = np.max(A, axis=1, keepdims = True) #gives a (4,1,2) matrix of max value along axis 1
array([[[0.95377958, 0.92940525]],
[[0.94485653, 0.9264881 ]],
[[0.95446736, 0.36436023]],
[[0.56911013, 0.96278067]]])
但我不知道如何将这些想法结合在一起以获得我想要的输出。 请帮忙!!
您可以从max_idx
获得最大值的3 维索引。 max_idx
中的值是max_idx
沿轴 1 的索引。 有六个值,因为您的其他轴是 3 和 2 (3 x 2 = 6)。 您只需要了解 numpy 通过它们获取其他每个轴的索引的顺序。 您首先遍历最后一个轴:
d0, d1, d2 = A.shape
a0 = [i for i in range(d0) for _ in range(d2)] # [0, 0, 1, 1, 2, 2]
a1 = max_idx.flatten() # [2, 2, 0, 2, 0, 1]
a2 = [k for _ in range(d0) for k in range(d2)] # [0, 1, 0, 1, 0, 1]
B[a0, a1, a2] = A[a0, a1, a2]
输出:
array([[[0. , 0. ],
[0. , 0. ],
[0.94485653, 0.9264881 ]],
[[0.95446736, 0. ],
[0. , 0. ],
[0. , 0.36436023]],
[[0.56911013, 0. ],
[0. , 0.96278067],
[0. , 0. ]]])
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