Hi, core NumPy doesn't seem to support a lot of output arguments, or common composite operations. For example, a common operation is something like
a = outer(b,c) or a += outer(b,c) There are some workarounds, but they aren't pretty. Consistently providing output arguments throughout NumPy would help; is there any reason this isn't being done? For example, it would be nice if "outer" supported: outer(b,c,output=a) outer(b,c,increment=a) outer(b,c,increment=a,scale=eps) or maybe one could specify an accumulation ufunc, with addition, multiplication, min, and max being fast, and with an optional scale parameter. Another approach might be to provide, in addition to the convenient high-level NumPy operations, direct bindings for BLAS and/or similar libraries, with Fortran-like procedural interfaces, but I can't find any such libraries in NumPy or SciPy. Am I missing something? It seems like writing native code to speed up these kinds of operations isn't really so great because (1) it unnecessarily complicates development and packaging, and (2) is likely to perform worse than BLAS and similar libraries. How are other people handling these cases? Thanks, Tom
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