SciPy

Release

1.6.3

Date

April 25, 2021

SciPy (pronounced “Sigh Pie”) is open-source software for mathematics, science, and engineering.

• Installing and upgrading
• SciPy API
• Release Notes

Tutorial

Tutorials with worked examples and background information for most SciPy submodules.

• SciPy Tutorial
  • Introduction
  • Special functions (scipy.special)
  • Integration (scipy.integrate)
  • Optimization (scipy.optimize)
  • Interpolation (scipy.interpolate)
  • Fourier Transforms (scipy.fft)
  • Signal Processing (scipy.signal)
  • Linear Algebra (scipy.linalg)
  • Sparse eigenvalue problems with ARPACK
  • Compressed Sparse Graph Routines (scipy.sparse.csgraph)
  • Spatial data structures and algorithms (scipy.spatial)
  • Statistics (scipy.stats)
  • Multidimensional image processing (scipy.ndimage)
  • File IO (scipy.io)

Developer Documentation

If you’re interested in contributing to SciPy, start here:

• SciPy Code of Conduct
• Ways to Contribute
• SciPy contributor guide

To get an overview of where help or new features are desired or planned, see the roadmap:

• SciPy Roadmap
• Detailed SciPy Roadmap
• Toolchain Roadmap

For a more detailed look at how the SciPy project works:

• SciPy Core Developer Guide
• Deciding on new features
• SciPy API Development Guide
• SciPy Project Governance

API Reference

The exact API of all functions and classes, as given by the docstrings. The API documents expected types and allowed features for all functions, and all parameters available for the algorithms.

• Clustering package (scipy.cluster)
• Constants (scipy.constants)
• Discrete Fourier transforms (scipy.fft)
• Legacy discrete Fourier transforms (scipy.fftpack)
• Integration and ODEs (scipy.integrate)
• Interpolation (scipy.interpolate)
• Input and output (scipy.io)
• Linear algebra (scipy.linalg)
• Miscellaneous routines (scipy.misc)
• Multidimensional image processing (scipy.ndimage)
• Orthogonal distance regression (scipy.odr)
• Optimization and root finding (scipy.optimize)
• Signal processing (scipy.signal)
• Sparse matrices (scipy.sparse)
• Sparse linear algebra (scipy.sparse.linalg)
• Compressed sparse graph routines (scipy.sparse.csgraph)
• Spatial algorithms and data structures (scipy.spatial)
• Special functions (scipy.special)
• Statistical functions (scipy.stats)
• Statistical functions for masked arrays (scipy.stats.mstats)
• Low-level callback functions