Python for MATLAB Development
Python for MATLAB Development

Author: Albert Danial

Publisher: Apress

Published: 2022-03-26

Total Pages: 700

ISBN-13: 9781484272220

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MATLAB can run Python code! Python for MATLAB Development shows you how to enhance MATLAB with Python solutions to a vast array of computational problems in science, engineering, optimization, statistics, finance, and simulation. It is three books in one: A thorough Python tutorial that leverages your existing MATLAB knowledge with a comprehensive collection of MATLAB/Python equivalent expressions A reference guide to setting up and managing a Python environment that integrates cleanly with MATLAB A collection of recipes that demonstrate Python solutions invoked directly from MATLAB This book shows how to call Python functions to enhance MATLAB's capabilities. Specifically, you'll see how Python helps MATLAB: Run faster with numba Distribute work to a compute cluster with dask Find symbolic solutions to integrals, derivatives, and series summations with SymPy Overlay data on maps with Cartopy Solve mixed-integer linear programming problems with PuLP Interact with Redis via pyredis, PostgreSQL via psycopg2, and MongoDB via pymongo Read and write file formats that are not natively understood by MATLAB, such as SQLite, YAML, and ini Who This Book Is For MATLAB developers who are new to Python and other developers with some prior experience with MATLAB, R, IDL, or Mathematica.

Introduction to Modeling and Simulation with MATLAB® and Python
Introduction to Modeling and Simulation with MATLAB® and Python

Author: Steven I. Gordon

Publisher: CRC Press

Published: 2017-07-12

Total Pages: 211

ISBN-13: 1498773885

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Introduction to Modeling and Simulation with MATLAB and Python is intended for students and professionals in science, social science, and engineering that wish to learn the principles of computer modeling, as well as basic programming skills. The book content focuses on meeting a set of basic modeling and simulation competencies that were developed as part of several National Science Foundation grants. Even though computer science students are much more expert programmers, they are not often given the opportunity to see how those skills are being applied to solve complex science and engineering problems and may also not be aware of the libraries used by scientists to create those models. The book interleaves chapters on modeling concepts and related exercises with programming concepts and exercises. The authors start with an introduction to modeling and its importance to current practices in the sciences and engineering. They introduce each of the programming environments and the syntax used to represent variables and compute mathematical equations and functions. As students gain more programming expertise, the authors return to modeling concepts, providing starting code for a variety of exercises where students add additional code to solve the problem and provide an analysis of the outcomes. In this way, the book builds both modeling and programming expertise with a "just-in-time" approach so that by the end of the book, students can take on relatively simple modeling example on their own. Each chapter is supplemented with references to additional reading, tutorials, and exercises that guide students to additional help and allows them to practice both their programming and analytical modeling skills. In addition, each of the programming related chapters is divided into two parts – one for MATLAB and one for Python. In these chapters, the authors also refer to additional online tutorials that students can use if they are having difficulty with any of the topics. The book culminates with a set of final project exercise suggestions that incorporate both the modeling and programming skills provided in the rest of the volume. Those projects could be undertaken by individuals or small groups of students. The companion website at http://www.intromodeling.com provides updates to instructions when there are substantial changes in software versions, as well as electronic copies of exercises and the related code. The website also offers a space where people can suggest additional projects they are willing to share as well as comments on the existing projects and exercises throughout the book. Solutions and lecture notes will also be available for qualifying instructors.

The Elements of MATLAB Style
The Elements of MATLAB Style

Author: Richard K. Johnson

Publisher: Cambridge University Press

Published: 2010-12-31

Total Pages: 181

ISBN-13: 1139496409

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The Elements of MATLAB Style is a guide for both new and experienced MATLAB programmers. It provides a comprehensive collection of standards and guidelines for creating solid MATLAB code that will be easy to understand, enhance, and maintain. It is written for both individuals and those working in teams in which consistency is critical. This is the only book devoted to MATLAB style and best programming practices, focusing on how MATLAB code can be written in order to maximize its effectiveness. Just as Strunk and White's The Elements of Style provides rules for writing in the English language, this book provides conventions for formatting, naming, documentation, programming and testing. It includes many concise examples of correct and incorrect usage, as well as coverage of the latest language features. The author also provides recommendations on use of the integrated development environment features that help produce better, more consistent software.

Python for Mechanical and Aerospace Engineering
Python for Mechanical and Aerospace Engineering

Author: Alex Kenan

Publisher: Alex Kenan

Published: 2021-01-01

Total Pages: 210

ISBN-13: 1736060600

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The traditional computer science courses for engineering focus on the fundamentals of programming without demonstrating the wide array of practical applications for fields outside of computer science. Thus, the mindset of “Java/Python is for computer science people or programmers, and MATLAB is for engineering” develops. MATLAB tends to dominate the engineering space because it is viewed as a batteries-included software kit that is focused on functional programming. Everything in MATLAB is some sort of array, and it lends itself to engineering integration with its toolkits like Simulink and other add-ins. The downside of MATLAB is that it is proprietary software, the license is expensive to purchase, and it is more limited than Python for doing tasks besides calculating or data capturing. This book is about the Python programming language. Specifically, it is about Python in the context of mechanical and aerospace engineering. Did you know that Python can be used to model a satellite orbiting the Earth? You can find the completed programs and a very helpful 595 page NSA Python tutorial at the book’s GitHub page at https://www.github.com/alexkenan/pymae. Read more about the book, including a sample part of Chapter 5, at https://pymae.github.io

Introduction to Radar Using Python and MATLAB
Introduction to Radar Using Python and MATLAB

Author: Lee Andrew (Andy) Harrison

Publisher: Artech House

Published: 2019-10-31

Total Pages: 491

ISBN-13: 1630815993

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This comprehensive resource provides readers with the tools necessary to perform analysis of various waveforms for use in radar systems. It provides information about how to produce synthetic aperture (SAR) images by giving a tomographic formulation and implementation for SAR imaging. Tracking filter fundamentals, and each parameter associated with the filter and how each affects tracking performance are also presented. Various radar cross section measurement techniques are covered, along with waveform selection analysis through the study of the ambiguity function for each particular waveform from simple linear frequency modulation (LFM) waveforms to more complicated coded waveforms. The text includes the Python tool suite, which allows the reader to analyze and predict radar performance for various scenarios and applications. Also provided are MATLAB® scripts corresponding to the Python tools. The software includes a user-friendly graphical user interface (GUI) that provides visualizations of the concepts being covered. Users have full access to both the Python and MATLAB source code to modify for their application. With examples using the tool suite are given at the end of each chapter, this text gives readers a clear understanding of how important target scattering is in areas of target detection, target tracking, pulse integration, and target discrimination.

MATLAB® Recipes for Earth Sciences
MATLAB® Recipes for Earth Sciences

Author: Martin H. Trauth

Publisher: Springer Science & Business Media

Published: 2007

Total Pages: 294

ISBN-13: 3540727485

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Introduces methods of data analysis in geosciences using MATLAB such as basic statistics for univariate, bivariate and multivariate datasets, jackknife and bootstrap resampling schemes, processing of digital elevation models, gridding and contouring, geostatistics and kriging, processing and georeferencing of satellite images, digitizing from the screen, linear and nonlinear time-series analysis and the application of linear time-invariant and adaptive filters. Includes a brief description of each method and numerous examples demonstrating how MATLAB can be used on data sets from earth sciences.

Computational Framework for the Finite Element Method in MATLAB® and Python
Computational Framework for the Finite Element Method in MATLAB® and Python

Author: Pavel Sumets

Publisher: CRC Press

Published: 2022-08-11

Total Pages: 166

ISBN-13: 1000610020

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Computational Framework for the Finite Element Method in MATLAB® and Python aims to provide a programming framework for coding linear FEM using matrix-based MATLAB® language and Python scripting language. It describes FEM algorithm implementation in the most generic formulation so that it is possible to apply this algorithm to as many application problems as possible. Readers can follow the step-by-step process of developing algorithms with clear explanations of its underlying mathematics and how to put it into MATLAB and Python code. The content is focused on aspects of numerical methods and coding FEM rather than FEM mathematical analysis. However, basic mathematical formulations for numerical techniques which are needed to implement FEM are provided. Particular attention is paid to an efficient programming style using sparse matrices. Features Contains ready-to-use coding recipes allowing fast prototyping and solving of mathematical problems using FEM Suitable for upper-level undergraduates and graduates in applied mathematics, science or engineering Both MATLAB and Python programming codes are provided to give readers more flexibility in the practical framework implementation

Quickstart Python
Quickstart Python

Author: Christoph Schäfer

Publisher: Springer Nature

Published: 2021-12-08

Total Pages: 61

ISBN-13: 3658335521

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Christoph Schäfer introduces the great world of programming with Python and provides a quick introduction to independent script development. He points out how the programming language Python has established itself in recent years alongside MATLAB and R as a standard at scientific workplaces in research and development, and shows that the great popularity of Python is based on its easy extensibility: It is very easy to use modules from other developers in your own scripts and programs. In particular, the author presents the modules NumPy, SciPy and Matplotlib, which offer scientists and engineers a perfect development environment for scientific and technical computing, for applications in physics, chemistry, biology and computer science. Python is also used in the latest applications in the highly topical fields of Big Data Science and Machine Learning. The author: Dr. Christoph Schäfer teaches and researches in the Department of Computational Physics at the Institute of Astronomy and Astrophysics at the Eberhard Karls University of Tübingen. This Springer essential is a translation of the original German 1st edition essentials, Schnellstart Python by Christoph Schäfer, published by Springer Fachmedien Wiesbaden GmbH, part of Springer Nature in 2019. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation. Springer Nature works continuously to further the development of tools for the production of books and on the related technologies to support the authors.

Accelerating MATLAB Performance
Accelerating MATLAB Performance

Author: Yair M. Altman

Publisher: CRC Press

Published: 2014-12-11

Total Pages: 768

ISBN-13: 1482211300

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The MATLAB programming environment is often perceived as a platform suitable for prototyping and modeling but not for "serious" applications. One of the main complaints is that MATLAB is just too slow. Accelerating MATLAB Performance aims to correct this perception by describing multiple ways to greatly improve MATLAB program speed. Packed with tho

Practical Numerical and Scientific Computing with MATLAB® and Python
Practical Numerical and Scientific Computing with MATLAB® and Python

Author: Eihab B. M. Bashier

Publisher: CRC Press

Published: 2020-03-18

Total Pages: 349

ISBN-13: 0429666829

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Practical Numerical and Scientific Computing with MATLAB® and Python concentrates on the practical aspects of numerical analysis and linear and non-linear programming. It discusses the methods for solving different types of mathematical problems using MATLAB and Python. Although the book focuses on the approximation problem rather than on error analysis of mathematical problems, it provides practical ways to calculate errors. The book is divided into three parts, covering topics in numerical linear algebra, methods of interpolation, numerical differentiation and integration, solutions of differential equations, linear and non-linear programming problems, and optimal control problems. This book has the following advantages: It adopts the programming languages, MATLAB and Python, which are widely used among academics, scientists, and engineers, for ease of use and contain many libraries covering many scientific and engineering fields. It contains topics that are rarely found in other numerical analysis books, such as ill-conditioned linear systems and methods of regularization to stabilize their solutions, nonstandard finite differences methods for solutions of ordinary differential equations, and the computations of the optimal controls. It provides a practical explanation of how to apply these topics using MATLAB and Python. It discusses software libraries to solve mathematical problems, such as software Gekko, pulp, and pyomo. These libraries use Python for solutions to differential equations and static and dynamic optimization problems. Most programs in the book can be applied in versions prior to MATLAB 2017b and Python 3.7.4 without the need to modify these programs. This book is aimed at newcomers and middle-level students, as well as members of the scientific community who are interested in solving math problems using MATLAB or Python.