000			02023nam a22002297a 4500
999			_c2433 _d2433
003			OSt
005			20200224132220.0
008			200117b ||||| |||| 00| 0 eng d
020			_a978-93-5213-605-6
028			_bAllied Informatics, Jaipur _c7084 _d13/01/2020 _q2019-20
040			_aBSDU _bEnglish _cBSDU
082			_a005.133 _bNUN
100			_aNunez-Iglesias, Walt
245			_aElegant Scipy: The art of scientific python
260			_aMumbai _bShroff Publishers & Distributors Pvt. Ltd. _c2019
300			_a251
504			_aAll Indian Reprints of O'Reilly are printed in Grayscale. Welcome to Scientific Python and its community. If you’re a scientist who programs with Python, this practical guide not only teaches you the fundamental parts of SciPy and libraries related to it, but also gives you a taste for beautiful, easy-to-read code that you can use in practice. You’ll learn how to write elegant code that’s clear, concise, and efficient at executing the task at hand. Throughout the book, you’ll work with examples from the wider scientific Python ecosystem, using code that illustrates principles outlined in the book. Using actual scientific data, you’ll work on real-world problems with SciPy, NumPy, Pandas, scikit-image, and other Python libraries. Explore the NumPy array, the data structure that underlies numerical scientific computation Use quantile normalization to ensure that measurements fit a specific distribution Represent separate regions in an image with a Region Adjacency Graph Convert temporal or spatial data into frequency domain data with the Fast Fourier Transform Solve sparse matrix problems, including image segmentations, with SciPy’s sparse module Perform linear algebra by using SciPy packages Explore image alignment (registration) with SciPy’s optimize module Process large datasets with Python data streaming primitives and the Toolz library
650			_aPython
700			_aStefan van der
700			_a Dashnow, Harriet
942			_2ddc _cBK