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Book Cover
E-book
Author Mehta, Hemant Kumar, author

Title Mastering Python scientific computing : a complete guide for Python programmers to master scientific computing using Python APIs and tools / Hemant Kumar Mehta
Published Birmingham, UK : Packt Publishing, 2015

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Description 1 online resource (1 volume) : illustrations
Series Community experience distilled
Community experience distilled.
Contents Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: The Landscape of Scientific Computing -- and Why Python?; Definition of scientific computing; A simple flow of the scientific computation process; Examples from scientific/engineering domains; A strategy for solving complex problems; Approximation, errors, and associated concepts and terms; Error analysis; Conditioning, stability, and accuracy; Backward and forward error analysis; Is it okay to ignore these errors?; Computer arithmetic and floating-point numbers
The background of the Python programming languageThe guiding principles of the Python language; Why Python for scientific computing?; Compact and readable code; Holistic language design; Free and open source; Language interoperability; Portable and extensible; Hierarchical module system; Graphical user interface packages; Data structures; Python's testing framework; Available libraries; The downsides of Python; Summary; Chapter 2: A Deeper Dive into Scientific Workflows and the Ingredients of Scientific Computing Recipes; Mathematical components of scientific computations
A system of linear equationsA system of nonlinear equations; Optimization; Interpolation; Extrapolation; Numerical integration; Numerical differentiation; Differential equations; The initial value problem; The boundary value problem; Random number generator; Python scientific computing; Introduction to NumPy; The SciPy library; The SciPy Subpackage; Data analysis using pandas; A brief idea of interactive programming using IPython; IPython parallel computing; IPython Notebook; Symbolic computing Using SymPy; The features of SymPy; Why SymPy?; The plotting library; Summary
Chapter 3: Efficiently Fabricating and Managing Scientific DataThe basic concepts of data; Data storage software and toolkits; Files; Structured files; Unstructured files; Database; Possible operations on data; Scientific data format; Ready-to-use standard datasets; Data generation; Synthetic data generation (fabrication); Using Python's built-in functions for random number generation; Bookkeeping functions; Functions for integer random number generation; Functions for sequences; Statistical-distribution-based functions; Nondeterministic random number generator
Designing and implementing random number generators based on statistical distributionsA program with simple logic to generate five-digit random numbers; A brief note about large-scale datasets; Summary; Chapter 4: Scientific Computing APIs for Python; Numerical scientific computing in Python; The NumPy package; The ndarrays data structure; File handling; Some sample NumPy programs; The SciPy package; The optimization package; The interpolation package; Integration and differential equations in SciPy; The stats module; Clustering package and spatial algorithms in SciPy
Notes Includes index
English
Online resource; title from cover page (Safari, viewed October 12, 2015)
Subject Python (Computer program language)
Computer science.
Electronic data processing.
computer science.
data processing.
COMPUTERS -- Programming Languages -- Python.
Electronic data processing
Computer science
Python (Computer program language)
Form Electronic book
ISBN 9781783288830
1783288833
Other Titles Complete guide for Python programmers to master scientific computing using Python APIs and tools