SciPy (pronounced ”Sigh Pie”) is open-source software for mathematics, science, and engineering. It is also the name of a very popular conference on scientific programming with Python. The SciPy library depends on NumPy, which provides convenient and fast N-dimensional array manipulation. The SciPy library is built to work with NumPy arrays, and provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization. Together, they run on all popular operating systems, are quick to install, and are free of charge. NumPy and SciPy are easy to use, but powerful enough to be depended upon by some of the world’s leading scientists and engineers. If you need to manipulate numbers on a computer and display or publish the results, give SciPy a try!

References in zbMATH (referenced in 373 articles )

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  1. Allen, Henry R.; Ptashnyk, Mariya: Mathematical modelling of auxin transport in plant tissues: flux meets signalling and growth (2020)
  2. Benedek Rozemberczki, Oliver Kiss, Rik Sarkar: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (2020) arXiv
  3. Drzisga, Daniel; Keith, Brendan; Wohlmuth, Barbara: The surrogate matrix methodology: low-cost assembly for isogeometric analysis (2020)
  4. Duncan N. Johnstone, Ben H. Martineau, Phillip Crout, Paul A. Midgley, Alexander S. Eggeman: Density-based clustering of crystal orientations and misorientations and the orix python library (2020) arXiv
  5. Emerson Boeira; Diego Eckhard: pyvrft: A Python package for the Virtual Reference Feedback Tuning, a direct data-driven control method (2020) not zbMATH
  6. Fernando Pérez-García, Rachel Sparks, Sebastien Ourselin: TorchIO: a Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning (2020) arXiv
  7. Fjordholm, U. S.; Lye, K.; Mishra, S.; Weber, F.: Statistical solutions of hyperbolic systems of conservation laws: numerical approximation (2020)
  8. González-González, José M.; Vázquez-Méndez, Miguel E.; Diéguez-Aranda, Ulises: A note on the regularity of a new metric for measuring even-flow in forest planning (2020)
  9. Hicken, Jason E.: Entropy-stable, high-order summation-by-parts discretizations without interface penalties (2020)
  10. Hishinuma, Kazuhiro; Iiduka, Hideaki: Fixed point quasiconvex subgradient method (2020)
  11. Iago Pereira Lemos; Antônio Marcos Gonçalves Lima; Marcus Antônio Viana Duarte: thresholdmodeling: A Python package for modeling excesses over a threshold using the Peak-Over-Threshold Method and the Generalized Pareto Distribution (2020) not zbMATH
  12. J. Magnus Rahm; Paul Erhart: WulffPack: A Python package for Wulff constructions (2020) not zbMATH
  13. Joel C. Miller, Tony TIng: EoN (Epidemics on Networks): a fast, flexible Python package for simulation, analytic approximation, and analysis of epidemics on networks (2020) arXiv
  14. Khristenko, Ustim; Constantinescu, Andrei; Tallec, Patrick Le; Oden, J. Tinsley; Wohlmuth, Barbara: A statistical framework for generating microstructures of two-phase random materials: application to fatigue analysis (2020)
  15. Kumar, Abhishek; Pothérat, Alban: Mixed baroclinic convection in a cavity (2020)
  16. Landel, Julien R.; Peaudecerf, François J.; Temprano-Coleto, Fernando; Gibou, Frédéric; Goldstein, Raymond E.; Luzzatto-Fegiz, Paolo: A theory for the slip and drag of superhydrophobic surfaces with surfactant (2020)
  17. Landet, Tormod; Mardal, Kent-Andre; Mortensen, Mikael: Slope limiting the velocity field in a discontinuous Galerkin divergence-free two-phase flow solver (2020)
  18. Linge, Svein; Langtangen, Hans Petter: Programming for computations -- Python. A gentle introduction to numerical simulations with Python 3.6 (2020)
  19. Michael Ortner; Lucas Gabriel; Coliado Bandeira: Magpylib: A free Python package for magnetic field computation (2020) not zbMATH
  20. Muammar El Khatib, Wibe A de Jong: ML4Chem: A Machine Learning Package for Chemistry and Materials Science (2020) arXiv

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