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 236 articles )

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  1. Albin, Nathan; Fernando, Nethali; Poggi-Corradini, Pietro: Modulus metrics on networks (2019)
  2. Andreas F. Haselsteiner; Jannik Lehmkuhl; Tobias Pape; Kai-Lukas Windmeier; Klaus-Dieter Thoben: ViroCon: A software to compute multivariate extremes using the environmental contour method (2019) not zbMATH
  3. Budanur, Nazmi Burak; Fleury, Marc: State space geometry of the chaotic pilot-wave hydrodynamics (2019)
  4. Campillo-Funollet, Eduard; Venkataraman, Chandrasekhar; Madzvamuse, Anotida: Bayesian parameter identification for Turing systems on stationary and evolving domains (2019)
  5. Carrillo, José Antonio; Craig, Katy; Patacchini, Francesco S.: A blob method for diffusion (2019)
  6. Ghosh, Souvik; Loiseau, Jean-Christophe; Breugem, Wim-Paul; Brandt, Luca: Modal and non-modal linear stability of Poiseuille flow through a channel with a porous substrate (2019)
  7. Michael Slugocki , Allison B. Sekuler, Patrick Bennett: BayesFit: A tool for modeling psychophysical data using Bayesian inference (2019) not zbMATH
  8. Miyaji, Tomoyuki; Okamoto, Hisashi: Existence proof of unimodal solutions of the Proudman-Johnson equation via interval analysis (2019)
  9. Toccaceli, Paolo; Gammerman, Alexander: Combination of inductive Mondrian conformal predictors (2019)
  10. Ansmann, Gerrit: Efficiently and easily integrating differential equations with JiTCODE, JiTCDDE, and JiTCSDE (2018)
  11. Bahsoun, Wael; Galatolo, Stefano; Nisoli, Isaia; Niu, Xiaolong: A rigorous computational approach to linear response (2018)
  12. Bánhelyi, Balázs; Csendes, Tibor; Lévai, Balázs; Pál, László; Zombori, Dániel: The GLOBAL optimization algorithm. Newly updated with Java implementation and parallelization (2018)
  13. Benjamin J. Fulton; Erik A. Petigura; Sarah Blunt; Evan Sinukoff: RadVel: The Radial Velocity Modeling Toolkit (2018) arXiv
  14. Benyuan Liu; Bin Yang; Canhua Xu; Junying Xia; Meng Dai; Zhenyu Ji; Fusheng You; Xiuzhen Dong; Xuetao Shi; Feng Fu: pyEIT: A python based framework for Electrical Impedance Tomography (2018) not zbMATH
  15. Bisotti, M.-A., Cortés-Ortuño, D., Pepper, R., Wang, W., Beg, M., Kluyver, T., Fangohr, H.: Fidimag - A Finite Difference Atomistic and Micromagnetic Simulation Package (2018) not zbMATH
  16. Blais, Bruno; Ilinca, Florin: Development and validation of a stabilized immersed boundary CFD model for freezing and melting with natural convection (2018)
  17. Broughton, S. Allen; Bryan, Kurt: Discrete Fourier analysis and wavelets. Applications to signal and image processing (2018)
  18. C. M. Biwer; Collin D. Capano; Soumi De; Miriam Cabero; Duncan A. Brown; Alexander H. Nitz; V. Raymond: PyCBC Inference: A Python-based parameter estimation toolkit for compact binary coalescence signals (2018) arXiv
  19. Collin J. Wilkinson, Yihong Z. Mauro, John C. Mauro: RelaxPy: Python code for modeling of glass relaxation behavior (2018) not zbMATH
  20. Czuppon, Peter; Gokhale, Chaitanya S.: Disentangling eco-evolutionary effects on trait fixation (2018)

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