NumPy
SciPy
NumPy  SciPy  

272  50  
26,510  12,532  
1.4%  1.6%  
10.0  9.9  
5 days ago  1 day ago  
Python  Python  
GNU General Public License v3.0 or later  BSD 3clause "New" or "Revised" License 
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NumPy

Dot vs Matrix vs Elementwise multiplication in PyTorch
In NumPy with @, dot() or matmul():
 NumPy 2.0.0 Beta1

Elementwise vs Matrix vs Dot multiplication
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by elementwise multiplication.
 JSON dans les projets data science : Trucs & Astuces

JSON in data science projects: tips & tricks
Data science projects often use numpy. However, numpy objects are not JSONserializable and therefore require conversion to standard python objects in order to be saved:

Introducing Flama for Robust Machine Learning APIs
numpy: A library for scientific computing in Python
 help with installing numpy, please

A Comprehensive Guide to NumPy Arrays
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy.

Why do all the popular projects use relative imports in __init__ files if PEP 8 recommends absolute?
I was looking at all the big projects like numpy, pytorch, flask, etc.

NumPy 2.0 development status & announcements: major CAPI and Python API cleanup
I wish the NumPy devs would more thoroughly consider adding full fluent API support, e.g. x.sqrt().ceil(). [Issue #24081]
SciPy

What Is a Schur Decomposition?
I guess it is a rite of passage to rewrite it. I'm doing it for SciPy too together with Propack in [1]. Somebody already mentioned your repo. Thank you for your efforts.
[1]: https://github.com/scipy/scipy/issues/18566

Fortran codes are causing problems
Fortran codes have caused many problems for the Python package Scipy, and some of them are now being rewritten in C: e.g., https://github.com/scipy/scipy/pull/19121. Not only does R have many Fortran codes, there are also many R packages using Fortran codes: https://github.com/rdevel/rsvn, https://github.com/cran?q=&type=&language=fortran&sort=. Modern Fortran is a fine language but most legacy Fortran codes use the F77 style. When I update the R package quantreg, which uses many Fortran codes, I get a lot of warning messages. Not sure how the Fortran codes in the R ecosystem will be dealt with in the future, but they recently caused an issue in R due to the lack of compiler support for Fortran: https://blog.rproject.org/2023/08/23/willrworkon64bitarmwindows/index.html. Some renowned packages like glmnet already have their Fortran codes rewritten in C/C++: https://cran.rproject.org/web/packages/glmnet/news/news.html

[D] Which BLAS library to choose for apple silicon?
There are several lessons here: a) vanilla condaforge numpy and scipy versions come with openblas, and it works pretty well, b) do not use netlib unless your matrices are small and you need to do a lot of SVDs, or idek why c) Apple's veclib/accelerate is super fast, but it is also numerically unstable. So much so that the scipy's devs dropped any support of it back in 2018. Like dang. That said, they are apparently are bring it back in, since the 13.3 release of macOS Ventura saw some major improvements in accelerate performance.

SciPy: Interested in adopting PRIMA, but little appetite for more Fortran code
First, if you read through that scipy issue (https://github.com/scipy/scipy/issues/18118 ) the author was willing and able to relicense PRIMA under a 3clause BSD license which is perfectly acceptable for scipy.
For the numerical recipes reference, there is a mention that scipy uses a slightly improved version of Powell's algorithm that is originally due to Forman Acton and presumably published in his popular book on numerical analysis, and that also happens to be described & included in numerical recipes. That is, unless the code scipy uses is copied from numerical recipes, which I presume it isn't, NR having the same algorithm doesn't mean that every other independent implementation of that algorithm falls under NR copyright.
 numerically evaluating wavelets?
 Fortran in SciPy: Get rid of linalg.interpolative Fortran code

Optimization Without Using Derivatives
Reading the discussions under a previous thread titled "More Descent, Less Gradient"( https://news.ycombinator.com/item?id=23004026 ), I guess people might be interested in PRIMA ( www.libprima.net ), which provides the reference implementation for Powell's renowned gradient/derivativefree (zerothorder) optimization methods, namely COBYLA, UOBYQA, NEWUOA, BOBYQA, and LINCOA.
PRIMA solves general nonlinear optimizaton problems without using derivatives. It implements Powell's solvers in modern Fortran, compling with the Fortran 2008 standard. The implementation is faithful, in the sense of being mathmatically equivalent to Powell's Fortran 77 implementation, but with a better numerical performance. In contrast to the 7939 lines of Fortran 77 code with 244 GOTOs, the new implementation is structured and modularized.
There is a discussion to include the PRIMA solvers into SciPy ( https://github.com/scipy/scipy/issues/18118 ), replacing the buggy and unmaintained Fortran 77 version of COBYLA, and making the other four solvers available to all SciPy users.
 What can I contribute to SciPy (or other) with my pure math skill? I’m pen and paper mathematician

Emerging Technologies: Rust in HPC
if that makes your eyes bleed, what do you think about this? https://github.com/scipy/scipy/blob/main/scipy/special/specfun/specfun.f (heh)
 Python
What are some alternatives?
SymPy  A computer algebra system written in pure Python
Pandas  Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
statsmodels  Statsmodels: statistical modeling and econometrics in Python
blaze  NumPy and Pandas interface to Big Data
Numba  NumPy aware dynamic Python compiler using LLVM
astropy  Astronomy and astrophysics core library
Nim  Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
ortools  Google's Operations Research tools:
manim  Animation engine for explanatory math videos
PyMC  Bayesian Modeling and Probabilistic Programming in Python