IPython: a system for interactive scientific computing. IPython provides a rich architecture for interactive computing with: A powerful interactive shell. A kernel for Jupyter. Support for interactive data visualization and use of GUI toolkits. Flexible, embeddable interpreters to load into your own projects. Easy to use, high performance tools for parallel computing.

References in zbMATH (referenced in 72 articles )

Showing results 1 to 20 of 72.
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  1. Carter Lee Rhea, Julie Hlavacek-Larrondo, Laurie Rousseau-Nepton, Benjamin Vigneron, Louis-Simon Guité: LUCI: A Python package for SITELLE spectral analysis (2021) arXiv
  2. Dutta, R., Schoengens, M., Pacchiardi, L., Ummadisingu, A., Widmer, N., Künzli, P., Onnela, J.-P., Mira, A: ABCpy: A High-Performance Computing Perspective to Approximate Bayesian Computation (2021) not zbMATH
  3. Lefebvre, William; Miller, Enzo: Linear-quadratic stochastic delayed control and deep learning resolution (2021)
  4. Rink, Thomas; Rodejohann, Werner; Schmitz, Kai: Leptogenesis and low-energy CP violation in a type-II-dominated left-right seesaw model (2021)
  5. Schoenholz, Samuel S.; Cubuk, Ekin D.: JAX, M.D. a framework for differentiable physics (2021)
  6. Staub, Ruben; Steinmann, Stephan N.: Efficient recursive least squares solver for rank-deficient matrices (2021)
  7. Damiani, Leonardo Hax; Kosakowski, Georg; Glaus, Martin A.; Churakov, Sergey V.: A framework for reactive transport modeling using FEniCS-Reaktoro: governing equations and benchmarking results (2020)
  8. Golman, Boris; Andreev, Vsevolod V.; Skrzypacz, Piotr: Dead-core solutions for slightly non-isothermal diffusion-reaction problems with power-law kinetics (2020)
  9. Linge, Svein; Langtangen, Hans Petter: Programming for computations -- Python. A gentle introduction to numerical simulations with Python 3.6 (2020)
  10. Navah, Farshad; Nadarajah, Siva: On the verification of CFD solvers of all orders of accuracy on curved wall-bounded domains and for realistic RANS flows (2020)
  11. Kulyabov, D. S.; Korol’kova, A. V.; Sevast’yanov, L. A.: New features in the second version of the Cadabra computer algebra system (2019)
  12. Leah Wasser, Maxwell B. Joseph, Joe McGlinchy, Jenny Palomino, Korinek, Nathan, Chris Holdgraf, Tim Head: EarthPy: A Python package that makes it easier toexplore and plot raster and vector data using opensource Python tools (2019) not zbMATH
  13. Michael Hippke, Trevor J. David, Gijs D. Mulders, René Heller: Wotan: Comprehensive time-series de-trending in Python (2019) arXiv
  14. Project Jupyter, Douglas Blank, David Bourgin, Alexander Brown, Matthias Bussonnier, Jonathan Frederic, Brian Granger, Thomas L. Griffiths, Jessica Hamrick, Kyle Kelley, M Pacer, Logan Page, Fernando Perez, Benjamin Ragan-Kelley, Jordan W. Suchow, Carol Willing: nbgrader: A Tool for Creating and Grading Assignments in the Jupyter Notebook (2019) not zbMATH
  15. Rising Odegua: DataSist: A Python-based library for easy data analysis, visualization and modeling (2019) arXiv
  16. Wielemaker, Jan; Riguzzi, Fabrizio; Kowalski, Robert A.; Lager, Torbjörn; Sadri, Fariba; Calejo, Miguel: Using SWISH to realize interactive web-based tutorials for logic-based languages (2019)
  17. Yadu Babuji, Anna Woodard, Zhuozhao Li, Daniel S. Katz, Ben Clifford, Rohan Kumar, Lukasz Lacinski, Ryan Chard, Justin M. Wozniak, Ian Foster, Michael Wilde, Kyle Chard: Parsl: Pervasive Parallel Programming in Python (2019) arXiv
  18. Zhukov, Oleg A.; Kazakova, Tatiana A.; Maksimov, Georgy V.; Brazhe, Alexey R.: Cost of auditory sharpness: model-based estimate of energy use by auditory brainstem “octopus” neurons (2019)
  19. Abreu, Rafael; Su, Zeming; Kamm, Jochen; Gao, Jinghuai: On the accuracy of the complex-step-finite-difference method (2018)
  20. D.M. Straub: flavio: a Python package for flavour and precision phenomenology in the Standard Model and beyond (2018) arXiv

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