Scientific Computing With Python Second Edition
DOWNLOAD
Download Scientific Computing With Python Second Edition PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Scientific Computing With Python Second Edition book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Scientific Computing With Python Second Edition
DOWNLOAD
Author : CLAUS. FUHRER
language : en
Publisher:
Release Date : 2021-07-23
Scientific Computing With Python Second Edition written by CLAUS. FUHRER and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-23 with categories.
Leverage this example-packed, comprehensive guide for all your Python computational needs Key Features: Learn the first steps within Python to highly specialized concepts Explore examples and code snippets taken from typical programming situations within scientific computing. Delve into essential computer science concepts like iterating, object-oriented programming, testing, and MPI presented in strong connection to applications within scientific computing. Book Description: Python has tremendous potential within the scientific computing domain. This updated edition of Scientific Computing with Python features new chapters on graphical user interfaces, efficient data processing, and parallel computing to help you perform mathematical and scientific computing efficiently using Python. This book will help you to explore new Python syntax features and create different models using scientific computing principles. The book presents Python alongside mathematical applications and demonstrates how to apply Python concepts in computing with the help of examples involving Python 3.8. You'll use pandas for basic data analysis to understand the modern needs of scientific computing, and cover data module improvements and built-in features. You'll also explore numerical computation modules such as NumPy and SciPy, which enable fast access to highly efficient numerical algorithms. By learning to use the plotting module Matplotlib, you will be able to represent your computational results in talks and publications. A special chapter is devoted to SymPy, a tool for bridging symbolic and numerical computations. By the end of this Python book, you'll have gained a solid understanding of task automation and how to implement and test mathematical algorithms within the realm of scientific computing. What You Will Learn: Understand the building blocks of computational mathematics, linear algebra, and related Python objects Use Matplotlib to create high-quality figures and graphics to draw and visualize results Apply object-oriented programming (OOP) to scientific computing in Python Discover how to use pandas to enter the world of data processing Handle exceptions for writing reliable and usable code Cover manual and automatic aspects of testing for scientific programming Get to grips with parallel computing to increase computation speed Who this book is for: This book is for students with a mathematical background, university teachers designing modern courses in programming, data scientists, researchers, developers, and anyone who wants to perform scientific computation in Python.
Scientific Computing With Python
DOWNLOAD
Author : Claus Fuhrer
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-07-30
Scientific Computing With Python written by Claus Fuhrer and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-30 with Computers categories.
Leverage this example-packed, comprehensive guide for all your Python computational needs Key FeaturesLearn the first steps within Python to highly specialized conceptsExplore examples and code snippets taken from typical programming situations within scientific computing.Delve into essential computer science concepts like iterating, object-oriented programming, testing, and MPI presented in strong connection to applications within scientific computing.Book Description Python has tremendous potential within the scientific computing domain. This updated edition of Scientific Computing with Python features new chapters on graphical user interfaces, efficient data processing, and parallel computing to help you perform mathematical and scientific computing efficiently using Python. This book will help you to explore new Python syntax features and create different models using scientific computing principles. The book presents Python alongside mathematical applications and demonstrates how to apply Python concepts in computing with the help of examples involving Python 3.8. You'll use pandas for basic data analysis to understand the modern needs of scientific computing, and cover data module improvements and built-in features. You'll also explore numerical computation modules such as NumPy and SciPy, which enable fast access to highly efficient numerical algorithms. By learning to use the plotting module Matplotlib, you will be able to represent your computational results in talks and publications. A special chapter is devoted to SymPy, a tool for bridging symbolic and numerical computations. By the end of this Python book, you'll have gained a solid understanding of task automation and how to implement and test mathematical algorithms within the realm of scientific computing. What you will learnUnderstand the building blocks of computational mathematics, linear algebra, and related Python objectsUse Matplotlib to create high-quality figures and graphics to draw and visualize resultsApply object-oriented programming (OOP) to scientific computing in PythonDiscover how to use pandas to enter the world of data processingHandle exceptions for writing reliable and usable codeCover manual and automatic aspects of testing for scientific programmingGet to grips with parallel computing to increase computation speedWho this book is for This book is for students with a mathematical background, university teachers designing modern courses in programming, data scientists, researchers, developers, and anyone who wants to perform scientific computation in Python.
Numerical Python
DOWNLOAD
Author : Robert Johansson
language : en
Publisher: Apress
Release Date : 2018-12-24
Numerical Python written by Robert Johansson and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-24 with Computers categories.
Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute solutions and mathematically model applications in big data, cloud computing, financial engineering, business management and more. Numerical Python, Second Edition, presents many brand-new case study examples of applications in data science and statistics using Python, along with extensions to many previous examples. Each of these demonstrates the power of Python for rapid development and exploratory computing due to its simple and high-level syntax and multiple options for data analysis. After reading this book, readers will be familiar with many computing techniques including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain-specific computational problems, such as differential equation solving, data analysis, statistical modeling and machine learning. What You'll Learn Work with vectors and matrices using NumPy Plot and visualize data with Matplotlib Perform data analysis tasks with Pandas and SciPy Review statistical modeling and machine learning with statsmodels and scikit-learn Optimize Python code using Numba and Cython Who This Book Is For Developers who want to understand how to use Python and its related ecosystem for numerical computing.
Learning Scipy For Numerical And Scientific Computing Second Edition
DOWNLOAD
Author : Sergio Rojas
language : en
Publisher: Packt Publishing
Release Date : 2015-02-26
Learning Scipy For Numerical And Scientific Computing Second Edition written by Sergio Rojas and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-26 with Computers categories.
A Student S Guide To Python For Physical Modeling
DOWNLOAD
Author : Jesse M. Kinder
language : en
Publisher: Princeton University Press
Release Date : 2021-08-03
A Student S Guide To Python For Physical Modeling written by Jesse M. Kinder and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-03 with Science categories.
A fully updated tutorial on the basics of the Python programming language for science students Python is a computer programming language that has gained popularity throughout the sciences. This fully updated second edition of A Student's Guide to Python for Physical Modeling aims to help you, the student, teach yourself enough of the Python programming language to get started with physical modeling. You will learn how to install an open-source Python programming environment and use it to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; and simulation. No prior programming experience is assumed. This guide introduces a wide range of useful tools, including: Basic Python programming and scripting Numerical arrays Two- and three-dimensional graphics Animation Monte Carlo simulations Numerical methods, including solving ordinary differential equations Image processing Numerous code samples and exercises—with solutions—illustrate new ideas as they are introduced. This guide also includes supplemental online resources: code samples, data sets, tutorials, and more. This edition includes new material on symbolic calculations with SymPy, an introduction to Python libraries for data science and machine learning (pandas and sklearn), and a primer on Python classes and object-oriented programming. A new appendix also introduces command line tools and version control with Git.
Learning Scipy For Numerical And Scientific Computing Second Edition
DOWNLOAD
Author : Sergio J. Rojas G.
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-02-26
Learning Scipy For Numerical And Scientific Computing Second Edition written by Sergio J. Rojas G. and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-26 with Computers categories.
This book targets programmers and scientists who have basic Python knowledge and who are keen to perform scientific and numerical computations with SciPy.
Learning Scipy For Numerical And Scientific Computing Second Edition
DOWNLOAD
Author : Sergio G.
language : en
Publisher:
Release Date : 2015
Learning Scipy For Numerical And Scientific Computing Second Edition written by Sergio G. and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Numerical analysis categories.
Quick solutions to complex numerical problems in physics, applied mathematics, and science with SciPy In Detail SciPy is an open source Python library used to perform scientific computing. The SciPy (Scientific Python) package extends the functionality of NumPy with a substantial collection of useful algorithms. The book starts with a brief description of the SciPy libraries, followed by a chapter that is a fun and fast-paced primer on array creation, manipulation, and problem-solving. You will also learn how to use SciPy in linear algebra, which includes topics such as computation of eigenvalues and eigenvectors. Furthermore, the book is based on interesting subjects such as definition and manipulation of functions, computation of derivatives, integration, interpolation, and regression. You will also learn how to use SciPy in signal processing and how applications of SciPy can be used to collect, organize, analyze, and interpret data. By the end of the book, you will have fast, accurate, and easy-to-code solutions for numerical and scientific computing applications. What You Will Learn Get to know the benefits of using the combination of Python, NumPy, SciPy, and matplotlib as a programming environment for scientific purposes Create and manipulate an object array used by SciPy Use SciPy with large matrices to compute eigenvalues and eigenvectors Focus on construction, acquisition, quality improvement, compression, and feature extraction of signals Make use of SciPy to collect, organize, analyze, and interpret data, with examples taken from statistics and clustering Acquire the skill of constructing a triangulation of points, convex hulls, Voronoi diagrams, and many similar applications Find out ways that SciPy can be used with other languages such as C/C++, Fortran, and MATLAB/Octave Downloading the example code for this book. You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
Introduction To Computation And Programming Using Python Revised And Expanded Edition
DOWNLOAD
Author : John V. Guttag
language : en
Publisher: MIT Press
Release Date : 2013-08-09
Introduction To Computation And Programming Using Python Revised And Expanded Edition written by John V. Guttag and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-09 with Computers categories.
An introductory text that teaches students the art of computational problem solving, covering topics that range from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of “data science” for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in a massive open online course (or MOOC) offered by the pioneering MIT-Harvard collaboration edX. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.
A Primer On Scientific Programming With Python
DOWNLOAD
Author : Hans Petter Langtangen
language : en
Publisher: Springer
Release Date : 2016-07-28
A Primer On Scientific Programming With Python written by Hans Petter Langtangen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-28 with Computers categories.
The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011 This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science. Alex Small, IEEE, CiSE Vol. 14 (2), March /April 2012 “This fourth edition is a wonderful, inclusive textbook that covers pretty much everything one needs to know to go from zero to fairly sophisticated scientific programming in Python...” Joan Horvath, Computing Reviews, March 2015
Scientific Computing
DOWNLOAD
Author : Michael T. Heath
language : en
Publisher: SIAM
Release Date : 2018-11-14
Scientific Computing written by Michael T. Heath and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-14 with Science categories.
This book differs from traditional numerical analysis texts in that it focuses on the motivation and ideas behind the algorithms presented rather than on detailed analyses of them. It presents a broad overview of methods and software for solving mathematical problems arising in computational modeling and data analysis, including proper problem formulation, selection of effective solution algorithms, and interpretation of results.? In the 20 years since its original publication, the modern, fundamental perspective of this book has aged well, and it continues to be used in the classroom. This Classics edition has been updated to include pointers to Python software and the Chebfun package, expansions on barycentric formulation for Lagrange polynomial interpretation and stochastic methods, and the availability of about 100 interactive educational modules that dynamically illustrate the concepts and algorithms in the book. Scientific Computing: An Introductory Survey, Second Edition is intended as both a textbook and a reference for computationally oriented disciplines that need to solve mathematical problems.