Guide to NumPy
Date: 11 July 2011 | Posted by: pool
pdf | 378 pages | 2 Mb
NumPy builds on (and is a successor to) the successful Numeric array object. Its goal is to create the corner-stone for a useful environment for scientific computing. In order to better understand the people surrounding NumPy and (its library-package) SciPy, I will explain a little about how SciPy and (current) NumPy originated. In 1998, as a graduate student studying biomedical imaging at the Mayo Clinic in Rochester, MN, I came across Python and its numerical extension (Numeric) while I was looking for ways to analyze large data sets for Magnetic Resonance Imaging and Ultrasound using a high-level language. I quickly fell in love with Python programming which is a remarkable statement to make about a programming language. If I had not seen others with the same view, I might have seriously doubted my sanity. I became rather involved in the Numeric Python community, adding the C-API chapter to the Numeric documentation (for which Paul Dubois graciously made me a coauthor)...
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