[Numpy-discussion] untenable matrix behavior in SVN

Timothy Hochberg tim.hochberg@ieee....
Tue Apr 29 14:22:18 CDT 2008


Let me throw out a couple of more thoughts:

First, there seems to be disagreement about what a row_vector and
column_vector are (and even if they are sensible concepts, but let's leave
that aside for moment). One school of thought is that they are
one-dimensional objects that have some orientation (hence row/column). They
correspond, more or less, to covariant and contravariant tensors, although I
can never recall which is which.  The second view, which I suspect is
influenced by MatLab and its ilk, is  that they are 2-dimensional 1xN and
Nx1 arrays. It's my view that the pseudo tensor approach is more powerful,
but it does require some metainformation be added to the array. This
metadata can either take the form of making the different objects different
classes, which leads to the matrix/row/column formulation, or adding some
sort of tag to the array object (proposal #5, which so far lacks any
detail).

Second, most of the stuff that we have been discussing so far is primarily
about notational convenience. However, there is matrix related stuff that is
at best poorly supported now, namely operations on stacks of arrays (or
vectors). As a concrete example, I at times need to work with stacks of
small matrices. If I do the operations one by one, the overhead is
prohibitive, however, most of that overhead can be avoided. For example, I
rewrote some of the linalg routines to work on stacks of matrices and
inverse is seven times faster for a 100x10x10 array (a stack of 100 10x10
matrices) when operating on a stack than when operating on the matrices one
at a time. This is a result of sharing the setup overhead, the C routines
that called are the same in either case.
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