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scipy/SciPy
SciPy extends NumPy with mature scientific algorithms. It is the right layer when a project needs trustworthy routines for optimisation, integration, interpolation, statistics, signal processing, sparse matrices or differential equations.
Overview
SciPy extends NumPy with mature scientific algorithms. It is the right layer when a project needs trustworthy routines for optimisation, integration, interpolation, statistics, signal processing, sparse matrices or differential equations.
What you can do
- Optimise functions, fit models and solve constrained numerical problems.
- Integrate functions, solve ODEs and use specialised linear-algebra routines.
- Analyse signals, images and experimental data with established methods.
How to start
- Read the official documentation and introductory guide.
- Reproduce one small example before adapting it to your own problem.
- Keep the repository link nearby for issues, releases and contribution guidance.