I prefer Perry's longstanding suggestion: things that do not add to
distribution complexity should go into numpy. If it compiles as
easily as numpy itself, it should go into numpy where sensible. It
remains a fact of life that numpy gets a wider distribution than
scipy, and some packages are hesitant to require scipy as a prereq
because of the additional complexity or building fortran, etc. I
would be nice to have as much as possible in the most widely
distributed package IMO.
That is a much better policy in my view.
I (gently) encourage this group (Travis?) to make this the policy for Numpy/Scipy.
From my view as a newbie to numpy/scipy/matplotlib it isn't clear where I should look for what functionality. Matplotlib plots the spectrogram but it only supports two or three window functions. Numpy supports 4 or 5 window functions and Scipy apparently supports more but Matplotlib doesn't support Scipy. Of course this is a minor example and I could just write the window function myself and then use it in Matplotlib but I want to give back so that the project can grow. I'd really like to be able to leave Matlab behind and encourage everyone else to do the same but there are still these annoyances that need to be worked out.
Thanks
Greg
Linux. Because rebooting is for adding hardware.
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