Advanced scientific computing library built on NumPy, providing algorithms for optimization, integration, interpolation, and more.
Official docs: https://docs.scipy.org/ Search patterns: scipy.integrate.quad, scipy.optimize.minimize, scipy.interpolate, scipy.stats, scipy.signal
| Integration | integrate | quad(f, 0, 1) | | Optimization | optimize | minimize(f, x0) | | Interpolation | interpolate | interp1d(x, y) | | Linear algebra | linalg | linalg.solve(A, b) | | Signal processing | signal | signal.butter(4, 0.5) | | Statistics | stats | stats.norm.pdf(x) | | ODEs | integrate | solveivp(f, tspan, y0) |
Comprehensive guide for SciPy - the fundamental library for scientific and technical computing in Python. Use for integration, optimization, interpolation, linear algebra, signal processing, statistics, ODEs, Fourier transforms, and advanced scientific algorithms. Built on NumPy and essential for research and engineering. Source: tondevrel/scientific-agent-skills.