SciPy - Scientific Computing

Advanced scientific computing library built on NumPy, providing algorithms for optimization, integration, interpolation, and more.

When to Use

• Integrating functions (numerical integration, ODEs)
• Optimizing functions (minimization, root finding, curve fitting)
• Interpolating data (1D, 2D, splines)
• Advanced linear algebra (sparse matrices, decompositions)
• Signal processing (filtering, Fourier transforms, wavelets)
• Statistical analysis (distributions, hypothesis tests)
• Image processing (filters, morphology, measurements)
• Spatial algorithms (distance matrices, clustering, Voronoi)
• Special mathematical functions (Bessel, gamma, error functions)
• Solving differential equations (ODEs, PDEs)

Reference Documentation