Author : Naveen S.Sapare 1
Date of Publication :2nd September 2020
Abstract: By definition Scientific Computing is one branch of applied computer science and mathematics which is growing rapidly and has assortment of technical tools required to apply on a particular models of mathematics, computational models, and simulations developed to solve issues in many domains like science, engineering, and humanity problems. To form and implement a numerical model we need a support of high level language. Python having numerous rich libraries to integrate establishes platform which can be utilized for developing any mathematical models used in scientific related application. In this paper we are going to discuss such libraries which serve as core libraries in solving mathematical problems in scientific computing. And also needed essential math theoretical skills and programming that are used to implement and solve given numerical problem. As python and MATLAB are two major programming languages used in many scientific application. This paper reveals experimental study conducted on chosen mathematical problem and result on chosen problem of mathematics using python over its libraries and MATLAB on different configured hardware.
- A. Nagpal and G. Gabrani, “Python for Data Analytics , Scientific and Technical Applications,” 1999.
- J. Unpingco, “Some Comparative Benchmarks for Linear Algebra Computations in MATLAB and Scientific Python,” pp. 503–505, 2008, doi: 10.1109/DoD.HPCMP.UGC.2008.49.
- R. Chudoba, R. Rypl, and M. Vorechovsky, “Using Python for scientific computing : Efficient and flexible evaluation of the statistical characteristics of functions with multivariate random inputs Using Python for scientific computing : efficient and flexible evaluation of the statistical characteristics of functions with multivariate random inputs,” no. February, 2013, doi: 10.1016/j.cpc.2012.08.021.
- T. Oliphant and C. Analytics, “Python for Scientific Computing,” no. December, 2014, doi: 10.1109/MCSE.2007.58.
- N. Ari and N. M. Mscs, “Symbolic python,” pp. 1–8, 2014.
- A. Sheela, “Combination of NumPy , SciPy and Matplotlib / Pylab - a good alternative methodology to MATLAB - A Comparative analysis.”
- O. Important et al., “MATLAB vs Python : Why and How to Make the Switch MATLAB vs Python : Comparing Features and Philosophy,” pp. 1–54, 2020.