Add multiple np.newaxis as needed?

Question

I want to pairwise and compare (with <=) all elements of two NumPy ndarrays A and B, where both arrays can have arbitrary dimensions m and n, such that the result is an array of dimension m + n.

I know how to do it forgiven dimension of B.

1. The scalar: A <= B
2. The one-dimensional: A[..., np.newaxis] <= B
3. The two-dimensional: A[..., np.newaxis, np.newaxis] <= B

I am trying to insert as many as np.newaxis as there are dimensions in the second array.

Do I have any syntax like np.newaxis * B.ndim, or another way?

Answer 1

You have a builtin for that:

np.less_equal.outer(A,B)

Another way would be with reshaping to accomodate new axes -

A.reshape(list(A.shape)+[1]*B.ndim) <= B

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