hist
Histogramming for analysis powered by boost-histogram (by scikit-hep)
im2dhist
This small piece of code is intended to help researchers, especially in field of image processing, to easily calculate two dimensional histogram of a given image. (by Mamdasn)
hist | im2dhist | |
---|---|---|
1 | 1 | |
123 | 6 | |
0.8% | - | |
7.4 | 4.8 | |
8 days ago | 3 months ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 only |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
hist
Posts with mentions or reviews of hist.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-09-21.
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Histogramming libraries for Python updated (boost-histogram / Hist)
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!
im2dhist
Posts with mentions or reviews of im2dhist.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-05-04.
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Using numba my code runs faster by about 20 times 😲
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.
What are some alternatives?
When comparing hist and im2dhist you can also consider the following projects:
iminuit - Jupyter-friendly Python interface for C++ MINUIT2
im2dhisteq - This module attempts to enhance contrast of a given image by equalizing its two dimensional histogram.
pyhf - pure-Python HistFactory implementation with tensors and autodiff
imhblpce - This module attempts to enhance contrast of a given image by employing a method called HBLPCE.
color-matcher - automatic color-grading