NumPy and Octave (qestion and discussion)
Johann Hibschman
johann at physics.berkeley.edu
Sun May 28 20:32:33 EDT 2000
Huaiyu Zhu writes:
> So my point is that perhaps the importance of numerical computation warrant
> an (expressional) syntax that's more convenient. I think this can be done
> without conflict with python's general syntax. It just need to be different
> from NumPy's special choices.
> To see why one would want this, consider an example. Suppose one wants to
> build a learning machine that learns to play chess. Python would be a very
> good language to write the overall structure, like players, the world, etc.
> But the actual learning algorithm (neural network, statistics, etc) needs
> lots of numerical computation which are very well expressed in matlab/
> octave. Can this be done efficiently in python? Right now writing these in
> NumPy is just too tedious and error-prone.
I've been using NumPy to do various problems in theoretical
astrophysics, without any problem. In my experience, I use the
NumPy-style element-wise array combinations more often than I use
actual matrix math. I don't mind having to write matrixmultiply the
few times I have to treat my 2D arrays as matrices.
This is clearly not your experience, but it may help you understand
why there isn't more of a groundswell of support in favor of
specializing NumPy more towards linear algebra.
Syntax helps, such as ' for transpose, will simply not happen, due to
python's general-purpose nature. Introducing new operators will also
likely not happen.
--Johann
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Johann Hibschman johann at physics.berkeley.edu
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