First of all I've started using some of the new math and prob stuff "for real" and it's all fantastic work. Thank you.
Was looking for a routine for sums of a matrix along the either the rows or cols axis. See http://docs.scipy.org/doc/numpy/reference/generated/numpy.sum.html I didn't notice anything but looks straightforward with matrix-map-rows/cols or similar. As I started one thing I noticed was the treatment of Matrix Rows and Cols as themselves a Matrix and not as a flat Array. > matrix-row - : (All (A) ((Array A) Integer -> (Array A))) #<procedure:matrix-row> > (matrix-row m 0) - : (Array Positive-Byte) (array #[#[1 2]]) In lieu of (array #[#[1 2]]) I would have expected (array #[1 2]). In other words, a row or column of a matrix is a row or column vector. in fact currently > (matrix-row (matrix-row (matrix-row (matrix-row m 0) 0) 0) 0) - : (Array Positive-Byte) (array #[#[1 2]]) What is the advantage of current approach? Thanks, Ray
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