Computational Modeling and Visualization of Physical Systems with Python

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Publisher :
ISBN 13 : 9781119355403
Total Pages : pages
Book Rating : 4.3/5 (554 download)

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Book Synopsis Computational Modeling and Visualization of Physical Systems with Python by : Jianyi Jay Wang

Download or read book Computational Modeling and Visualization of Physical Systems with Python written by Jianyi Jay Wang and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computational Modeling and Visualization of Physical Systems with Python

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Publisher : John Wiley & Sons
ISBN 13 : 1119239885
Total Pages : 494 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Computational Modeling and Visualization of Physical Systems with Python by : Jay Wang

Download or read book Computational Modeling and Visualization of Physical Systems with Python written by Jay Wang and published by John Wiley & Sons. This book was released on 2015-12-21 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Modeling, by Jay Wang introduces computational modeling and visualization of physical systems that are commonly found in physics and related areas. The authors begin with a framework that integrates model building, algorithm development, and data visualization for problem solving via scientific computing. Through carefully selected problems, methods, and projects, the reader is guided to learning and discovery by actively doing rather than just knowing physics.

A Student's Guide to Python for Physical Modeling

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Publisher : Princeton University Press
ISBN 13 : 0691223661
Total Pages : 241 pages
Book Rating : 4.6/5 (912 download)

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Book Synopsis A Student's Guide to Python for Physical Modeling by : Jesse M. Kinder

Download or read book A Student's Guide to Python for Physical Modeling written by Jesse M. Kinder and published by Princeton University Press. This book was released on 2021-08-03 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

A Student's Guide to Python for Physical Modeling

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Publisher : Princeton University Press
ISBN 13 : 0691180571
Total Pages : 168 pages
Book Rating : 4.6/5 (911 download)

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Book Synopsis A Student's Guide to Python for Physical Modeling by : Jesse M. Kinder

Download or read book A Student's Guide to Python for Physical Modeling written by Jesse M. Kinder and published by Princeton University Press. This book was released on 2018-01-30 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fully updated tutorial on the basics of the Python programming language for science students Python is a computer programming language that is rapidly gaining popularity throughout the sciences. This fully updated 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 tutorial focuses on fundamentals and introduces a wide range of useful techniques, including: Basic Python programming and scripting Numerical arrays Two- and three-dimensional graphics Monte Carlo simulations Numerical methods, including solving ordinary differential equations Image processing Animation Numerous code samples and exercises—with solutions—illustrate new ideas as they are introduced. Web-based resources also accompany this guide and include code samples, data sets, and more. This current edition brings the discussion of the Python language, Spyder development environment, and Anaconda distribution up to date. In addition, a new appendix introduces Jupyter notebooks.

Modeling and Simulation in Python

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Publisher : No Starch Press
ISBN 13 : 1718502176
Total Pages : 277 pages
Book Rating : 4.7/5 (185 download)

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Book Synopsis Modeling and Simulation in Python by : Allen B. Downey

Download or read book Modeling and Simulation in Python written by Allen B. Downey and published by No Starch Press. This book was released on 2023-05-30 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling and Simulation in Python teaches readers how to analyze real-world scenarios using the Python programming language, requiring no more than a background in high school math. Modeling and Simulation in Python is a thorough but easy-to-follow introduction to physical modeling—that is, the art of describing and simulating real-world systems. Readers are guided through modeling things like world population growth, infectious disease, bungee jumping, baseball flight trajectories, celestial mechanics, and more while simultaneously developing a strong understanding of fundamental programming concepts like loops, vectors, and functions. Clear and concise, with a focus on learning by doing, the author spares the reader abstract, theoretical complexities and gets right to hands-on examples that show how to produce useful models and simulations.

Introduction to Computation in Physical Sciences

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Publisher : Springer Nature
ISBN 13 : 3031176464
Total Pages : 264 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Introduction to Computation in Physical Sciences by : Jay Wang

Download or read book Introduction to Computation in Physical Sciences written by Jay Wang and published by Springer Nature. This book was released on 2023-01-25 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a practical and comprehensive introduction to computational problem solving from the viewpoints of practitioners in both academic and industrial worlds. The authors present scientific problem-solving using computation and aim to increase computational thinking, which is the mindset and skillset required to solve scientific problems with computational methodologies via model building, simulation, data analysis, and visualization using the Python programming language. Topics and examples span fundamental areas of physical science as well as contemporary topics including quantum computing, neural networks, machine learning, global warming, and energy balance. The book features unique and innovative techniques and practices including: intentional scaffolding to help beginners learn computational problem solving; multimodal computing environments including cloud-based platforms and just-in-time computing; emphasis and connection between both numerical and symbolic computations; and extensive exercise sets carefully designed for further exploration as project assignments or self-paced study. The book is suitable for introductory level readers in physical sciences, engineering, and related STEM disciplines. Specifically, the book is appropriate for use in either a standalone course on computation and modeling and as a resource for readers interested in learning about proven techniques in interactive computing.

Introduction to Computation and Programming Using Python, second edition

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Publisher : MIT Press
ISBN 13 : 0262529629
Total Pages : 466 pages
Book Rating : 4.2/5 (625 download)

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Book Synopsis Introduction to Computation and Programming Using Python, second edition by : John V. Guttag

Download or read book Introduction to Computation and Programming Using Python, second edition written by John V. Guttag and published by MIT Press. This book was released on 2016-08-12 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging 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 in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. 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. 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. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.

An Introduction to Computer Simulation Methods

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Publisher : Addison Wesley Publishing Company
ISBN 13 :
Total Pages : 412 pages
Book Rating : 4.:/5 ( download)

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Book Synopsis An Introduction to Computer Simulation Methods by : Harvey Gould

Download or read book An Introduction to Computer Simulation Methods written by Harvey Gould and published by Addison Wesley Publishing Company. This book was released on 1988 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Bioinformatics Programming Using Python

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449382908
Total Pages : 526 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis Bioinformatics Programming Using Python by : Mitchell L Model

Download or read book Bioinformatics Programming Using Python written by Mitchell L Model and published by "O'Reilly Media, Inc.". This book was released on 2009-12-08 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: Powerful, flexible, and easy to use, Python is an ideal language for building software tools and applications for life science research and development. This unique book shows you how to program with Python, using code examples taken directly from bioinformatics. In a short time, you'll be using sophisticated techniques and Python modules that are particularly effective for bioinformatics programming. Bioinformatics Programming Using Python is perfect for anyone involved with bioinformatics -- researchers, support staff, students, and software developers interested in writing bioinformatics applications. You'll find it useful whether you already use Python, write code in another language, or have no programming experience at all. It's an excellent self-instruction tool, as well as a handy reference when facing the challenges of real-life programming tasks. Become familiar with Python's fundamentals, including ways to develop simple applications Learn how to use Python modules for pattern matching, structured text processing, online data retrieval, and database access Discover generalized patterns that cover a large proportion of how Python code is used in bioinformatics Learn how to apply the principles and techniques of object-oriented programming Benefit from the "tips and traps" section in each chapter

A Primer on Scientific Programming with Python

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Publisher : Springer
ISBN 13 : 3662498871
Total Pages : 942 pages
Book Rating : 4.6/5 (624 download)

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Book Synopsis A Primer on Scientific Programming with Python by : Hans Petter Langtangen

Download or read book A Primer on Scientific Programming with Python written by Hans Petter Langtangen and published by Springer. This book was released on 2016-07-28 with total page 942 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Python for Scientists

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Publisher : Cambridge University Press
ISBN 13 : 1316641236
Total Pages : 272 pages
Book Rating : 4.3/5 (166 download)

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Book Synopsis Python for Scientists by : John M. Stewart

Download or read book Python for Scientists written by John M. Stewart and published by Cambridge University Press. This book was released on 2017-07-20 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientific Python is taught from scratch in this book via copious, downloadable, useful and adaptable code snippets. Everything the working scientist needs to know is covered, quickly providing researchers and research students with the skills to start using Python effectively.

Effective Computation in Physics

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491901586
Total Pages : 567 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Effective Computation in Physics by : Anthony Scopatz

Download or read book Effective Computation in Physics written by Anthony Scopatz and published by "O'Reilly Media, Inc.". This book was released on 2015-06-25 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: More physicists today are taking on the role of software developer as part of their research, but software development isnâ??t always easy or obvious, even for physicists. This practical book teaches essential software development skills to help you automate and accomplish nearly any aspect of research in a physics-based field. Written by two PhDs in nuclear engineering, this book includes practical examples drawn from a working knowledge of physics concepts. Youâ??ll learn how to use the Python programming language to perform everything from collecting and analyzing data to building software and publishing your results. In four parts, this book includes: Getting Started: Jump into Python, the command line, data containers, functions, flow control and logic, and classes and objects Getting It Done: Learn about regular expressions, analysis and visualization, NumPy, storing data in files and HDF5, important data structures in physics, computing in parallel, and deploying software Getting It Right: Build pipelines and software, learn to use local and remote version control, and debug and test your code Getting It Out There: Document your code, process and publish your findings, and collaborate efficiently; dive into software licenses, ownership, and copyright procedures

Matter & Interactions

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Publisher :
ISBN 13 : 9780471373889
Total Pages : 0 pages
Book Rating : 4.3/5 (738 download)

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Book Synopsis Matter & Interactions by : Ruth W. Chabay

Download or read book Matter & Interactions written by Ruth W. Chabay and published by . This book was released on 1999 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Python Scripting for Computational Science

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Publisher : Springer Science & Business Media
ISBN 13 : 3662054507
Total Pages : 743 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Python Scripting for Computational Science by : Hans Petter Langtangen

Download or read book Python Scripting for Computational Science written by Hans Petter Langtangen and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 743 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scripting with Python makes you productive and increases the reliability of your scientific work. Here, the author teaches you how to develop tailored, flexible, and efficient working environments built from small programs (scripts) written in Python. The focus is on examples and applications of relevance to computational science: gluing existing applications and tools, e.g. for automating simulation, data analysis, and visualization; steering simulations and computational experiments; equipping programs with graphical user interfaces; making computational Web services; creating interactive interfaces with a Maple/Matlab-like syntax to numerical applications in C/C++ or Fortran; and building flexible object-oriented programming interfaces to existing C/C++ or Fortran libraries.

Hands-On Simulation Modeling with Python

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Publisher : Packt Publishing Ltd
ISBN 13 : 1838988653
Total Pages : 347 pages
Book Rating : 4.8/5 (389 download)

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Book Synopsis Hands-On Simulation Modeling with Python by : Giuseppe Ciaburro

Download or read book Hands-On Simulation Modeling with Python written by Giuseppe Ciaburro and published by Packt Publishing Ltd. This book was released on 2020-07-17 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Enhance your simulation modeling skills by creating and analyzing digital prototypes of a physical model using Python programming with this comprehensive guide Key Features Learn to create a digital prototype of a real model using hands-on examples Evaluate the performance and output of your prototype using simulation modeling techniques Understand various statistical and physical simulations to improve systems using Python Book Description Simulation modeling helps you to create digital prototypes of physical models to analyze how they work and predict their performance in the real world. With this comprehensive guide, you'll understand various computational statistical simulations using Python. Starting with the fundamentals of simulation modeling, you'll understand concepts such as randomness and explore data generating processes, resampling methods, and bootstrapping techniques. You'll then cover key algorithms such as Monte Carlo simulations and Markov decision processes, which are used to develop numerical simulation models, and discover how they can be used to solve real-world problems. As you advance, you'll develop simulation models to help you get accurate results and enhance decision-making processes. Using optimization techniques, you'll learn to modify the performance of a model to improve results and make optimal use of resources. The book will guide you in creating a digital prototype using practical use cases for financial engineering, prototyping project management to improve planning, and simulating physical phenomena using neural networks. By the end of this book, you'll have learned how to construct and deploy simulation models of your own to overcome real-world challenges. What you will learn Gain an overview of the different types of simulation models Get to grips with the concepts of randomness and data generation process Understand how to work with discrete and continuous distributions Work with Monte Carlo simulations to calculate a definite integral Find out how to simulate random walks using Markov chains Obtain robust estimates of confidence intervals and standard errors of population parameters Discover how to use optimization methods in real-life applications Run efficient simulations to analyze real-world systems Who this book is for Hands-On Simulation Modeling with Python is for simulation developers and engineers, model designers, and anyone already familiar with the basic computational methods that are used to study the behavior of systems. This book will help you explore advanced simulation techniques such as Monte Carlo methods, statistical simulations, and much more using Python. Working knowledge of Python programming language is required.

Python for Data Science For Dummies

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Publisher : John Wiley & Sons
ISBN 13 : 1118843983
Total Pages : 432 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Python for Data Science For Dummies by : John Paul Mueller

Download or read book Python for Data Science For Dummies written by John Paul Mueller and published by John Wiley & Sons. This book was released on 2015-06-23 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unleash the power of Python for your data analysis projects with For Dummies! Python is the preferred programming language for data scientists and combines the best features of Matlab, Mathematica, and R into libraries specific to data analysis and visualization. Python for Data Science For Dummies shows you how to take advantage of Python programming to acquire, organize, process, and analyze large amounts of information and use basic statistics concepts to identify trends and patterns. You’ll get familiar with the Python development environment, manipulate data, design compelling visualizations, and solve scientific computing challenges as you work your way through this user-friendly guide. Covers the fundamentals of Python data analysis programming and statistics to help you build a solid foundation in data science concepts like probability, random distributions, hypothesis testing, and regression models Explains objects, functions, modules, and libraries and their role in data analysis Walks you through some of the most widely-used libraries, including NumPy, SciPy, BeautifulSoup, Pandas, and MatPlobLib Whether you’re new to data analysis or just new to Python, Python for Data Science For Dummies is your practical guide to getting a grip on data overload and doing interesting things with the oodles of information you uncover.

Computational Physics

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Publisher : John Wiley & Sons
ISBN 13 : 3527413154
Total Pages : 647 pages
Book Rating : 4.5/5 (274 download)

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Book Synopsis Computational Physics by : Rubin H. Landau

Download or read book Computational Physics written by Rubin H. Landau and published by John Wiley & Sons. This book was released on 2015-09-08 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of computation and simulation has become an essential part of the scientific process. Being able to transform a theory into an algorithm requires significant theoretical insight, detailed physical and mathematical understanding, and a working level of competency in programming. This upper-division text provides an unusually broad survey of the topics of modern computational physics from a multidisciplinary, computational science point of view. Its philosophy is rooted in learning by doing (assisted by many model programs), with new scientific materials as well as with the Python programming language. Python has become very popular, particularly for physics education and large scientific projects. It is probably the easiest programming language to learn for beginners, yet is also used for mainstream scientific computing, and has packages for excellent graphics and even symbolic manipulations. The text is designed for an upper-level undergraduate or beginning graduate course and provides the reader with the essential knowledge to understand computational tools and mathematical methods well enough to be successful. As part of the teaching of using computers to solve scientific problems, the reader is encouraged to work through a sample problem stated at the beginning of each chapter or unit, which involves studying the text, writing, debugging and running programs, visualizing the results, and the expressing in words what has been done and what can be concluded. Then there are exercises and problems at the end of each chapter for the reader to work on their own (with model programs given for that purpose).