Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. matplotlib can be used in python scripts, the python and ipython shell (ala MATLAB®* or Mathematica®†), web application servers, and six graphical user interface toolkits.


References in zbMATH (referenced in 61 articles )

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  1. Morra, Gabriele: Pythonic geodynamics. Implementations for fast computing (2018)
  2. Bryan W. Weber, Chih-Jen Sung: UConnRCMPy: Python-based data analysis for rapid compression machines (2017) arXiv
  3. Chrétien, Stéphane; Darses, Sébastien; Guyeux, Christophe; Clarkson, Paul: On the pinning controllability of complex networks using perturbation theory of extreme singular values. Application to synchronisation in power grids (2017)
  4. Douglas De Rizzo Meneghetti, Plinio Thomaz Aquino Junior: Computerized Adaptive Testing Simulation Through the Package catsim (2017) arXiv
  5. Leon Thurner, Alexander Scheidler, Florian Schaefer, Jan-Hendrik Menke, Julian Dollichon, Friederike Meier, Steffen Meinecke, Martin Braun: Pandapower - an Open Source Python Tool for Convenient Modeling, Analysis and Optimization of Electric Power Systems (2017) arXiv
  6. Matthew Wood, Regina Caputo, Eric Charles, Mattia Di Mauro, Jeffrey Magill, Jeremy Perkins for the Fermi-LAT Collaboration: Fermipy: An open-source Python package for analysis of Fermi-LAT Data (2017) arXiv
  7. Miller, Jonah M.; Schnetter, Erik: An operator-based local discontinuous Galerkin method compatible with the BSSN formulation of the Einstein equations (2017)
  8. Myers, A.; Colella, P.; Straalen, B.van: A 4th-order particle-in-cell method with phase-space remapping for the Vlasov-Poisson equation (2017)
  9. Pierre Fernique, Christophe Pradal: AutoWIG: Automatic Generation of Python Bindings for C++ Libraries (2017) arXiv
  10. Woyand, Hans-Bernhard: Python for engineers and natural scientists. Introduction to programming, mathematical applications and visualizations. With numerous pictures and tables as well as 68 exercises (2017)
  11. Abali, B.Emek; Wu, Cheng-Chieh; Müller, Wolfgang H.: An energy-based method to determine material constants in nonlinear rheology with applications (2016)
  12. Berger-Vergiat, Luc; McAuliffe, Colin; Waisman, Haim: Parallel preconditioners for monolithic solution of shear bands (2016)
  13. Craig, Katy; Bertozzi, Andrea L.: A blob method for the aggregation equation (2016)
  14. Davis, Jon H.: Methods of applied mathematics with a software overview (2016)
  15. Hicken, Jason E.; del Rey Fernández, David C.; Zingg, David W.: Multidimensional summation-by-parts operators: general theory and application to simplex elements (2016)
  16. Hoel, Håkon; Häppölä, Juho; Tempone, Raúl: Construction of a mean square error adaptive Euler-Maruyama method with applications in multilevel Monte Carlo (2016)
  17. Keip, Marc-Andre; Rambausek, Matthias: A multiscale approach to the computational characterization of magnetorheological elastomers (2016)
  18. Kraus, Michael; Tassi, Emanuele; Grasso, Daniela: Variational integrators for reduced magnetohydrodynamics (2016)
  19. Langtangen, Hans Petter: Finite difference computing with exponential decay models (2016)
  20. Linge, Svein; Langtangen, Hans Petter: Programming for computations -- Python. A gentle introduction to numerical simulations with Python (2016)

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