Processing ......
FreeComputerBooks.com
Links to Free Computer, Mathematics, Technical Books all over the World
 
Introduction to Python for Computational Science and Engineering - A Beginner's Guide
Top Free Python Books 🌠 - 100% Free or Open Source!
  • Title Introduction to Python for Computational Science and Engineering - A Beginner's Guide
  • Author(s) Hans Fangohr
  • Publisher: University of Southampton (2022);
  • Hardcover/Paperback N/A
  • eBook PDF (265 pages)
  • Language: English
  • ISBN-10: N/A
  • ISBN-13: N/A
  • Share This:  

This book summarises a number of core ideas relevant to Computational Engineering and Scientific Computing using Python. The emphasis is on introducing some basic Python (programming) concepts that are relevant for numerical algorithms. The later chapters touch upon numerical libraries such as numpy and scipy each of which deserves much more space than provided here. We aim to enable the reader to learn independently how to use other functionality of these libraries using the available documentation (online and through the packages itself).

This open book is out of copyright. You can download Introduction to Python for Computational Science and Engineering ebook for free in PDF format (2.9 MB).

About the Authors
  • Hans Fangohr is a Professor of Computational Modelling within Engineering and Physical Sciences at the University of Southampton.
Reviews, Ratings, and Recommendations: Related Book Categories: Read and Download Links: Similar Books:
  • Introduction to Scientific Programming with Python

    This book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, assuming little or no prior experience in programming.

  • Programming for Computations - Python (Svein Linge, et al)

    This book presents computer programming as a key method for solving mathematical problems using Python. Each treated concept is illustrated and explained in detail by means of working examples. It is intended for novice programmers and engineers.

  • Solving PDEs in Python: The FEniCS Tutorial I (H. Langtangen)

    This book offers a concise and gentle introduction to finite element programming in Python based on the popular FEniCS software library. Using a series of examples, it guides readers through the essential steps to quickly solving a PDE in FEniCS.

  • Developing Graphics Frameworks with Python and OpenGL

    It shows you how to create software for rendering complete three-dimensional scenes, explains the foundational theoretical concepts as well as the practical programming techniques that will enable you to create your own animated and interactive worlds.

  • Python and OpenGL for Scientific Visualization (Nicolas P. Rougier)

    The goal of this book is to reconcile Python programmers with OpenGL, providing both an introduction to modern OpenGL and a set of basic and advanced techniques in order to achieve both fast, scalable & beautiful scientific visualizations.

  • Scientific Visualisation: Python and Matplotlib (Nicolas P. Rougier)

    Matplotlib provides a large library of customizable plots, along with a comprehensive set of backends. Through practical, hands-on and straightforward examples, the book guides you through Data Visualization and Exploration using Python and Matplotlib.

  • From Python to NumPy (Nicolas P. Rougier)

    NumPy is one of the most important scientific computing libraries available for Python. This book teaches you how to achieve expert level competency to perform complex operations, with in-depth coverage of advanced concepts.

  • Guide to NumPy (Travis E. Oliphant)

    This book is for programmers, scientists, or engineers, who have basic Python knowledge and would like to be able to do numerical computations with Python. It will give you a solid foundation in NumPy arrays and universal functions.

  • NumPy Tutorials (Usman Malik, Anne Bonner, et al)

    They provide everything you need to know to get started with NumPy. They also explain the basics of NumPy such as its architecture and environment, discusses the various array functions, types of indexing, etc. With examples for better understanding.

  • Scipy Lecture Notes (Emmanuelle Gouillart, et al)

    This book is the teaching material on the scientific Python ecosystem, a quick introduction to central tools and techniques. It is for programmers from beginner to expert. Work on real-world problems with SciPy, NumPy, Pandas, scikit-image, and other Python libraries.

  • SciPy Programming Succinctly (James McCaffrey)

    This book offers readers a quick, thorough grounding in knowledge of the Python open source extension SciPy. The SciPy library, accompanied by its interdependent NumPy, offers Python programmers advanced functions that work with arrays and matrices.

  • Automate the Boring Stuff with Python (Albert Sweigart)

    Learn how to use Python to write programs that do in minutes what would take you hours to do by hand - no prior programming experience required. You'll create Python programs that effortlessly perform useful and impressive feats of automation.

  • Python for Everybody: Exploring Data in Python 3

    This book is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.

  • Problem Solving with Algorithms/Data Structures using Python

    This is a textbook about computer science. It is also about Python. However, there is much more. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science.

  • Fundamentals of Python Programming (Richard L. Halterman)

    It focuses on introducing programming techniques and developing good habits. To that end, our approach avoids some of the more esoteric features of Python and concentrates on the programming basics that transfer directly to other imperative programming.

  • O'Reilly® Think Python, 2nd Edition (Allen B. Downey)

    This hands-on guide takes you through the Python programming language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. 2nd edition updated for Python 3.

  • The Big Book of Small Python Projects: 81 Easy Practice Programs

    This book demonstrates how to combine different libraries and frameworks to build amazing things. It picks up where the complete beginner books leave off, expanding on existing concepts and introducing new tools that you'll use every day.

  • Practical Python Projects (Yasoob Khalid)

    This collection of 81 Python projects will have you making digital art, games, animations, counting programs, and more right away. Once you see how the code works, you’ll practice re-creating the programs and experiment by adding your own custom touches.

Book Categories
:
Other Categories
Resources and Links