multiply a vector and a matrix to create a 3D matrix in numpy-CodePudding

I have a matrix A of zise MxN, and vector b of size L. how can I create a matrix C of size MxNxL such that:

C[m, n, k] = A[m, n] * b[k]

pretty much the same as dot product of two vectors to create 2D matrix, but with one dimention higher.

I had tried some variations of a dot product but I couldnt find it.

CodePudding user response：

You don't want a dot product (sum of the product over an axis), but a simple product that creates a new dimension.

Use broadcasting:

C = A[..., None] * b

Example:

A = np.ones((2,3))
b = np.ones(4)

C = A[..., None] * b

C.shape
# (2, 3, 4)

CodePudding user response：

The most intuitive way to solve your problem is using np.einsum. It follows the maths equation you wrote in the question itself.

A = np.ones((2,3))
b = np.ones(4)

C = np.einsum('ij, k -> ijk', A,b)
C.shape
# (2, 3, 4)