im2dhist VS hist

I recently added im2dhisteq to my repository and because it was very slow, I searched for a new way to make my code run faster, as I was already using numpy built-in functions and there were no (at least easy) other way to optimize the code using just numpy. I recently found out about Numba, which is advertised to run my codes 1000 times faster, but as I later found out the degree of that is actually very dependant on your code. After reading through their website and through a long series of trials and erros I learned how to write a code that is Numba-friendly and is satisfyingly faster than my base code. website of Numba: Numba Proof: My code: https://github.com/Mamdasn/im2dhisteq In my repository, in addition to the Numba-flavord versions, I released the Numba-less versions, which are accessible here: im2dhisteq and imhist. You can check them out and compare them to come to a base understanding of how Numba-friendly codes looks like.

Both projects are part of Scikit-HEP, but like many Scikit-HEP projects (Awkward, iminuit, cookie, etc.), are more generally applicable than just High Energy Physics (HEP). See https://github.com/scikit-hep/hist and https://github.com/scikit-hep/boost-histogram , drop us a star if this is useful for you!