It doesn't need to be on pypi to be imported into other projects. The general solution when you have functionality that * you need in multiple projects * you're unhappy with/can't find existing OS implementations * you're not sure you can build a performant, tested implementation that fits in existing open source projects is to put it in a package on github, then add that github direct url to the requirements of your other projects.
-Jake Jake Stevens-Haas Ph.D. Candidate Applied Mathematics University of Washington +1-(908)-462-4196 jacob.stevens.h...@gmail.com j...@uw.edu On Sun, Jul 21, 2024 at 10:06 AM Joseph Fox-Rabinovitz < jfoxrabinov...@gmail.com> wrote: > There's also an implementation in scikit-guess, which I mostly maintain. > > On Sun, Jul 21, 2024, 00:38 Dom Grigonis <dom.grigo...@gmail.com> wrote: > >> For statistics functions there is `scipy` package. >> >> If you are referring to pdf of n-dimensional gaussian distribution, >> `scipy.stats.multivariate_normal.pdf` should do the trick. >> >> If you are referring to something else, then a bit of clarification would >> be helpful. >> >> Regards, >> dg >> >> > On 20 Jul 2024, at 09:04, tomnewton...@gmail.com wrote: >> > >> > Hello, >> > >> > Apologies if either (a) this is the wrong place to post this or (b) >> this functionality already exists and I didn't manage to find it. >> > >> > I have found myself many times in the past wishing that some sort of >> N-D Gaussian function exists in NumPy. For example, when I wish to test >> that some plot or data analysis method is working correctly, being able to >> call `np.gauss()` on a (M,N) array of coordinates or passing it the arrays >> generated by a meshgrid, along with tuples for sigma and mu, would be very >> convienient. >> > >> > I could write such a function myself, but that would not be convenient >> to reuse (copying the function to every program/project I want to use it >> in), and many other mathematical functions have "convenience" functions in >> NumPy (such as the square root). More importantly, I imagine that any such >> function that was written into NumPy by the people who regularly contribute >> to the project would be far better than one I wrote myself, as I am not >> tremendously good at programming. >> > >> > Regards, >> > Tom >> > _______________________________________________ >> > NumPy-Discussion mailing list -- numpy-discussion@python.org >> > To unsubscribe send an email to numpy-discussion-le...@python.org >> > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ >> > Member address: dom.grigo...@gmail.com >> >> _______________________________________________ >> NumPy-Discussion mailing list -- numpy-discussion@python.org >> To unsubscribe send an email to numpy-discussion-le...@python.org >> https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ >> Member address: jfoxrabinov...@gmail.com >> > _______________________________________________ > NumPy-Discussion mailing list -- numpy-discussion@python.org > To unsubscribe send an email to numpy-discussion-le...@python.org > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ > Member address: jacob.stevens.h...@gmail.com >
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