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Leverage this example-packed, comprehensive guide for all your Python computational needsKey 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 DescriptionPython 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 forThis 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.

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Numerical Analysis is an interdisciplinary topic which develops its strength only when viewed in close connection with applications. Nowadays, mechanical engineers having computer simulation as a daily engineering tool have to learn more and more techniques from that field. Mathematicians, on the other hand, are increasingly confronted with the need for developing special purpose methods and codes. This requires a broad interdisciplinary understanding and a sense for model-method interactions. With this monograph we give an introduction to selected topics of Numerical Anal­ ysis based on these facts. We dedicate our presentations to an interesting discipline in computational engineering: multibody dynamics. Though the basic ideas and methods apply to other engineering fields too, we emphasize on having one homo­ geneous class of applications. Both authors worked through many years in teams developing multibody codes. Interdisciplinary work also includes transferring ideas from one field to the other and a big amount of teaching -and that was the idea of this book. This book is intended for students of mathematics, engineering and computer sci­ ence, as well as for people already concerned with the solution of related topics in university and industry. After a short introduction to multibody systems and the mathematical formulation of the equations of motion, different numerical methods used to solve simulation tasks are presented. The presentation is supported by a simple model of a truck. This truck model will follow the reader from the title page to the appendix in various versions, specially adapted to the topics.