NumPy is the fundamental package for scientific computing with Python.
Keywords for this software
References in zbMATH (referenced in 292 articles )
Showing results 281 to 292 of 292.
- Kiusalaas, Jaan: Numerical methods in engineering with Python. (2010)
- Koutsawa, Yao; Belouettar, Salim; Makradi, Ahmed; Nasser, Houssein: Sensitivities of effective properties computed using micromechanics differential schemes and high-order Taylor series: application to piezo-polymer composites (2010)
- Rasch, Arno; Bücker, H. Martin: EFCOSS: an interactive environment facilitating optimal experimental design (2010)
- Bakker, Mark: Sinusoidal pumping of groundwater near cylindrical inhomogeneities (2009)
- Drummond, L. Anthony; Galiano, Vicente; Migallón, Violeta; Penadés, Jose: Interfaces for parallel numerical linear algebra libraries in high level languages (2009)
- Drummond, L. Anthony; Galiano, Vicente; Migallón, Violeta; Penadés, Jose: PyACTS: A Python based interface to ACTS tools and parallel scientific applications (2009)
- Langtangen, Hans Petter: Python scripting for computational science (2008)
- Sala, Marzio; Spotz, William F.; Heroux, Michael A.: PyTrilinos: High-performance distributed-memory solvers for Python (2008)
- Cai, Xing; Langtangen, Hans Petter: Parallelizing PDE solvers using the Python programming language (2006)
- Decook, Rhonda; Nettleton, Dan; Foster, Carol; Wurtele, Eve S.: Identifying differentially expressed genes in unreplicated multiple-treatment microarray timecourse experiments (2006)
- Kirby, Robert C.: Algorithm 839: FIAT, a new paradigm for computing finite element basis functions (2004)
- Barnard, John: MiPy: a system for generating multiple imputations (2000)