FUTURE FOR SCIENTIFIC COMPUTING USING PYTHON

  • Rakesh Kumar Software Engineer at DigiCollect GIS, Bangalore, INDIA
Keywords: IPython, Matplotlib, NumPy, Python, Pandas, Scientific Computing, Sympy, SciPy

Abstract

Computational science (scientific computing or scientific computation) is concerned with constructing mathematical models as well as quantitative analysis techniques and using computers to analyze as well as solve scientific problems. In practical use, it is basically the application of computer simulation as well as other forms of computation from numerical analysis and theoretical computer science to problems in different scientific disciplines. The scientific computing approach is to gain understanding, basically through the analysis of mathematical models implemented on computers. Python is frequently used for highperformance scientific applications and widely used in academia as well as scientific projects because it is easy to write and performs well. Due to its high performance nature, scientific computing in Python often utilizes external libraries like NumPy, SciPy and Matplotlib etc.

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Published
2015-07-31
How to Cite
Kumar, R. (2015). FUTURE FOR SCIENTIFIC COMPUTING USING PYTHON. International Journal of Engineering Technologies and Management Research, 2(1), 30-41. https://doi.org/10.29121/ijetmr.v2.i1.2015.28