SciPy

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 182 articles )

Showing results 1 to 20 of 182.
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  1. Ansmann, Gerrit: Efficiently and easily integrating differential equations with JiTCODE, JiTCDDE, and JiTCSDE (2018)
  2. Bahsoun, Wael; Galatolo, Stefano; Nisoli, Isaia; Niu, Xiaolong: A rigorous computational approach to linear response (2018)
  3. Blais, Bruno; Ilinca, Florin: Development and validation of a stabilized immersed boundary CFD model for freezing and melting with natural convection (2018)
  4. Erickson, Collin B.; Ankenman, Bruce E.; Sanchez, Susan M.: Comparison of Gaussian process modeling software (2018)
  5. Ignatiev, Alexey; Morgado, Antonio; Marques-Silva, Joao: PySAT: A Python toolkit for prototyping with SAT oracles (2018)
  6. K.T. Schütt, P. Kessel, M. Gastegger, K. Nicoli, A. Tkatchenko, K.-R. Müller: SchNetPack: A Deep Learning Toolbox For Atomistic Systems (2018) arXiv
  7. Liew, A.; Pagonakis, D.; Van Mele, T.; Block, P.: Load-path optimisation of funicular networks (2018)
  8. McRae, Andrew T. T.; Cotter, Colin J.; Budd, Chris J.: Optimal-transport -- based mesh adaptivity on the plane and sphere using finite elements (2018)
  9. Minjie Zhu, Frank McKenna, Michael H. Scott: OpenSeesPy: Python library for the OpenSees finite element framework (2018)
  10. Phillip Weinberg, Marin Bukov: QuSpin: a Python Package for Dynamics and Exact Diagonalisation of Quantum Many Body Systems. Part II: bosons, fermions and higher spins (2018) arXiv
  11. Salman, Sinan; Alaswad, Suzan: Alleviating road network congestion: traffic pattern optimization using Markov chain traffic assignment (2018)
  12. Sanderson, Conrad; Curtin, Ryan: A user-friendly hybrid sparse matrix class in C++ (2018)
  13. Sankaranarayanan, Sriram; Feijoo, Felipe; Siddiqui, Sauleh: Sensitivity and covariance in stochastic complementarity problems with an application to north American natural gas markets (2018)
  14. Al-Hinai, Omar; Wheeler, Mary F.; Yotov, Ivan: A generalized mimetic finite difference method and two-point flux schemes over Voronoi diagrams (2017)
  15. Allen, Henry R.; Ptashnyk, Mariya: Mathematical modelling and analysis of the brassinosteroid and gibberellin signalling pathways and their interactions (2017)
  16. Benjamin Guedj, Bhargav Srinivasa Desikan: Pycobra: A Python Toolbox for Ensemble Learning and Visualisation (2017) arXiv
  17. Boyle, Michael: The integration of angular velocity (2017)
  18. Bryan W. Weber, Chih-Jen Sung: UConnRCMPy: Python-based data analysis for rapid compression machines (2017) arXiv
  19. Budanur, Nazmi Burak; Cvitanović, Predrag: Unstable manifolds of relative periodic orbits in the symmetry-reduced state space of the Kuramoto-Sivashinsky system (2017)
  20. Carmen Moret-Tatay, Daniel Gamermann, Esperanza Navarro-Pardo, Pedro Fernandez de Cordoba: ExGUtils: A python package for statistical analysis with the ex-gaussian probability density (2017) arXiv

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