SciPy (pronounced "Sigh Pie") is an open-source software for mathematics, science, and engineering. It includes modules for statistics, optimization, integration, linear algebra, Fourier transforms, signal and image processing, ODE solvers, and more.
SciPy is built to work with NumPy arrays, and provides many user-friendly and efficient numerical routines, such as routines for numerical integration and optimization. Together, they run on all popular operating systems, are quick to install, and are free of charge. NumPy and SciPy are easy to use, but powerful enough to be depended upon by some of the world's leading scientists and engineers. If you need to manipulate numbers on a computer and display or publish the results, give SciPy a try!
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1.14.031 May 2024 03:15
minor feature:
lt;h1 gt;SciPy 1.14.0 Release Notes lt;/h1 gt;.
lt;p gt; lt;strong gt;Note lt;/strong gt;: SciPy lt;code gt;1.14.0 lt;/code gt; is not released yet! lt;/p gt;.
lt;p gt;SciPy lt;code gt;1.14.0 lt;/code gt; is the culmination of 3 months of hard work. It contains lt;br gt;.
Many new features, numerous -, improved test coverage and better lt;br gt;
Documentation. There have been a number of deprecations and API changes lt;br gt;
in this release, which are documented below. All users are encouraged to lt;br gt;
Upgrade to this release, as there are a large number of -and lt;br gt;
Optimizations. Before upgrading, we recommend that users check that lt;br gt;
Their own code does not use deprecated SciPy functionality (to do so, lt;br gt;
Run your code with lt;code gt;python -Wd lt;/code gt; and check for lt;code gt;DeprecationWarning lt;/code gt; s). lt;br gt;
Our development attention will now shift to -releases on the lt;br gt;
1.14.x branch, and on adding new features on the main branch. lt;/p gt;
lt;p gt;This release requires Python lt;code gt;3.10+ lt;/code gt; and NumPy lt;code gt;1.23.5 lt;/code gt; or greater. lt;/p gt;.
lt;p gt;For running on PyPy, PyPy3 6.0+ is required. lt;/p gt;.
lt;h1 gt;Highlights of this release lt;/h1 gt;.
lt;ul gt;.
lt;li gt;SciPy now supports the new Accelerate library introduced in macOS 13.3, and lt;br gt;.
Has wheels built against Accelerate for macOS amp;gt;=14 resulting in significant lt;br gt;
Performance improvements for many linear algebra operations. lt;/li gt;
lt;li gt;A new method, lt;code gt;cobyqa lt;/code gt;, has been added to lt;code gt;scipy.optimize.minimize lt;/code gt; - this lt;br gt;.
is an interface for COBYQA (Constrained Optimization BY Quadratic lt;br gt;
Approximations), a derivative-free optimization solver, designed to lt;br gt;
Supersede COBYLA, developed by the Department of Applied Mathematics, The lt;br gt;
Hong Kong Polytechnic University. lt;/li gt;
lt;li gt; lt;code gt;scipy.sparse.linalg.spso
1.13.124 May 2024 04:05
minor feature:
lt;h1 gt;SciPy 1.13.1 Release Notes lt;/h1 gt;.
lt;p gt;SciPy lt;code gt;1.13.1 lt;/code gt; is a -release with no new features lt;br gt;.
Compared to lt;code gt;1.13.0 lt;/code gt;. The version of OpenBLAS shipped with lt;br gt;
The PyPI binaries has been increased to lt;code gt;0.3.27 lt;/code gt;. lt;/p gt;
lt;h1 gt;Authors lt;/h1 gt;.
lt;ul gt;.
lt;li gt;Name (commits) lt;/li gt;.
lt;li gt;h-vetinari (1) lt;/li gt;.
lt;li gt;Jake Bowhay (2) lt;/li gt;.
lt;li gt;Evgeni Burovski (6) lt;/li gt;.
lt;li gt;Sean Cheah (2) lt;/li gt;.
lt;li gt;Lucas Colley (2) lt;/li gt;.
lt;li gt;DWesl (2) lt;/li gt;.
lt;li gt;Ralf Gommers (7) lt;/li gt;.
lt;li gt;Ben Greiner (1) + lt;/li gt;.
lt;li gt;Matt Haberland (2) lt;/li gt;.
lt;li gt;Gregory R. Lee (1) lt;/li gt;.
lt;li gt;Philip Loche (1) + lt;/li gt;.
lt;li gt;Sijo Valayakkad Manikandan (1) + lt;/li gt;.
lt;li gt;Matti Picus (1) lt;/li gt;.
lt;li gt;Tyler Reddy (62) lt;/li gt;.
lt;li gt;Atsushi Sakai (1) lt;/li gt;.
lt;li gt;Daniel Schmitz (2) lt;/li gt;.
lt;li gt;Dan Schult (3) lt;/li gt;.
lt;li gt;Scott Shambaugh (2) lt;/li gt;.
lt;li gt;Edgar Andrés Margffoy Tuay (1) lt;/li gt;.
lt;/ul gt;.
lt;p gt;A total of 19 people contributed to this release. lt;br gt;.
People with a "+" by their names contributed a patch for the first time. lt;br gt;
This list of names is automatically generated, and may not be fully complete. lt;/p gt;
1.13.003 Apr 2024 09:57
major feature:
Highlights of this release
Support for NumPy 2.0.0.
Interactive examples have been added to the documentation, allowing users to run the examples locally on embedded Jupyterlite notebooks in their browser.
Preliminary 1D array support for the COO and DOK sparse formats.
Several scipy.stats functions have gained support for additional axis, nan_policy, and keepdims arguments. scipy.stats also has several performance and accuracy improvements.