As proposed in https://github.com/numpy/numpy/issues/24687
Dynamicists frequently use the matrix representation of the cross product (https://en.m.wikipedia.org/wiki/Cross_product#Conversion_to_matrix_multiplication), and the lack of a skew symmetric operator in NumPy is a frequent source of annoyance. I propose either adding a skew function to linalg that returns the skew symmetric matrix of a vector `np.cross(a, np.identity(a.shape[0]) * -1)` (from https://stackoverflow.com/questions/66707295/numpy-cross-product-matrix-function), or more radically, making the second argument `b` of np.cross optional and have `np.cross(a)` return the matrix representation of [a x]. For the latter, would need to consider the interaction with other kwargs and different input shapes. _______________________________________________ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-le...@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: arch...@mail-archive.com
