- SciPy
SciPy provides algorithms for optimization, integration, interpolation, eigenvalue problems, algebraic equations, differential equations, statistics and many other classes of problems
- SciPy - Installation
Here is a step-by-step guide to setting up a project to use SciPy, with uv, a Python package manager Install uv following, the instructions in the uv documentation
- SciPy documentation — SciPy v1. 16. 0 Manual
Want to build from source rather than use a Python distribution or pre-built SciPy binary? This guide will describe how to set up your build environment, and how to build SciPy itself, including the many options for customizing that build
- Numpy and Scipy Documentation
Numpy and Scipy Documentation Welcome! This is the documentation for Numpy and Scipy For contributors: Numpy developer guide Scipy developer guide Latest releases: Complete Numpy Manual [HTML+zip] Numpy Reference Guide [PDF] Numpy User Guide [PDF] F2Py Guide SciPy Documentation [HTML+zip]
- SciPy - Beginner Installation Guide
To try out SciPy, you don’t even need to install it! You can use SciPy in your browser at https: jupyter org try-jupyter lab - just open a Python Notebook, then write import scipy in one of the notebook “cells” and hit play
- derivative — SciPy v1. 16. 0 Manual
An object similar to an instance of scipy optimize OptimizeResult with the following attributes The descriptions are written as though the values will be scalars; however, if f returns an array, the outputs will be arrays of the same shape
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