numpy-具有2d数组的多个3d数组 [英] Numpy - multiple 3d array with a 2d array

问题描述

我正在尝试以下操作:

给定一个矩阵A(x，y，3)和另一个矩阵B(3，3)，我想返回一个(x，y，3)矩阵，其中A的第3维乘以值的B(类似于将RGB图像转换为灰色时的情况，只是将那些"RGB"值乘以矩阵而不是标量)...

Given a matrix A (x, y ,3) and another matrix B (3, 3), I would like to return a (x, y, 3) matrix in which the 3rd dimension of A is multiplied by the values of B (similar when an RGB image is transformed into gray, only that those "RGB" values are multiplied by a matrix and not scalars)...

这是我尝试过的:

np.multiply(B, A)
np.einsum('ijk,jl->ilk', B, A)
np.einsum('ijk,jl->ilk', A, B)

所有尺寸均未对齐失败.

All of them failed with dimensions not aligned.

我想念什么?

推荐答案

您可以使用

You can use np.tensordot -

np.tensordot(A,B,axes=((2),(1)))

相关帖子，以了解tensordot .

einsum等价于-

np.einsum('ijk,lk->ijl', A, B)

我们也可以使用A.dot(B.T)，但这将在幕后循环.因此，可能不是最理想的解决方案，但这是一个紧凑的解决方案，

We can also use A.dot(B.T), but that would be looping under the hoods. So, might not be the most preferred one, but it's a compact solution,

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