Hardcore Programming For Mechanical Engineers

Hardcore Programming for Mechanical Engineers is for intermediate programmers who want to write good applications that solve tough engineering problems – from scratch. This book will teach you how to solve engineering problems with Python. The “hardcore” approach means that you will learn to get the correct results by coding everything from scratch. Forget relying on third-party software – there are no shortcuts on the path to proficiency. Instead, using familiar concepts from linear algebra, geometry and physics, you’ll write your own libraries, draw your own primitives, and build your own applications. Author Angel Sola covers core programming techniques mechanical engineers need to know, with a focus on high-quality code and automated unit testing for error-free implementations. After basic primers on Python and using the command line, you’ll quickly develop a geometry toolbox, filling it with lines and shapes for diagramming problems. As your understanding grows chapter-by-chapter, you’ll create vector graphics and animations for dynamic simulations; you’ll code algorithms that can do complex numerical computations; and you’ll put all of this knowledge together to build a complete structural analysis application that solves a 2D truss problem – similar to the software projects conducted by real-world mechanical engineers. You'll learn: • How to use geometric primitives, like points and polygons, and implement matrices • Best practices for clean code, including unit testing, encapsulation, and expressive names • Processes for drawing images to the screen and creating animations inside Tkinter’s Canvas widget • How to write programs that read from a file, parse the data, and produce vector images • Numerical methods for solving large systems of linear equations, like the Cholesky decomposition algorithm

Hardcore Programming for Mechanical Engineers is for intermediate programmers who want to write good applications that solve tough engineering problems – from scratch. What if you could solve challenging engineering problems with Python programming? With this book’s hardcore approach, you’ll learn how to code solutions from scratch using linear algebra, geometry, and physics to write custom libraries, draw primitives, and build applications. Ángel Sola Orbaiceta covers core programming techniques for mechanical engineers, with a focus on crafting high-quality code and leveraging automated unit testing for error-free implementations. You’ll develop a geometry toolbox, filling it with lines and shapes to diagram engineering problems; create vector graphics and animations for mechanical simulations; and code algorithms to perform complex calculations. As a capstone you’ll combine these lessons to build a complete structural analysis application to solve a 2D truss problem that you might encounter in the field. Learn how to: Use regular expressions to elegantly parse file input Refine your code with unit testing, encapsulation, and descriptive names Draw images onscreen and create animations with Tkinter’s Canvas widget Solve systems of linear equations using the Cholesky decomposition algorithm Build an application that visualizes a truss structure’s stresses and strains Stop relying on third-party software—there are no shortcuts on the path to proficiency. With Hardcore Programming for Mechanical Engineers, you’ll hone your programming skills to get correct results every time.

Provides an introduction to numerical methods for students in engineering. It uses Python 3, an easy-to-use, high-level programming language.

Make cool stuff. If you're a designer or artist without a lot of programming experience, this book will teach you to work with 2D and 3D graphics, sound, physical interaction, and electronic circuitry to create all sorts of interesting and compelling experiences -- online and off. Programming Interactivity explains programming and electrical engineering basics, and introduces three freely available tools created specifically for artists and designers: Processing, a Java-based programming language and environment for building projects on the desktop, Web, or mobile phones Arduino, a system that integrates a microcomputer prototyping board, IDE, and programming language for creating your own hardware and controls OpenFrameworks, a coding framework simplified for designers and artists, using the powerful C++ programming language BTW, you don't have to wait until you finish the book to actually make something. You'll get working code samples you can use right away, along with the background and technical information you need to design, program, build, and troubleshoot your own projects. The cutting edge design techniques and discussions with leading artists and designers will give you the tools and inspiration to let your imagination take flight.

Regarding the controversial and thought-provoking assessments in this handbook, many software professionals might disagree with the authors, but all will embrace the debate. Glass identifies many of the key problems hampering success in this field. Each fact is supported by insightful discussion and detailed references.

"Lego Mindstorms" allows you to build and program simple robots, but wouldn't it be nice to take programming to the next level? This book starts off with the basics and each chapter progresses to even more ambitious projects.

Ever wished you could spy on your computer with a handy incantation or bewitch your programs to debug themselves - now you can by becoming a Linux wizard! Okay, reading these zines won't actually make you a wizard, but you'll sure feel like one after you learn some neat Linux tricks. With this collected edition of Julia Evans's wildly popular Linux zines, you'll view programming in a way you never have before - now on fancier paper!

In Math for Programmers you’ll explore important mathematical concepts through hands-on coding. Filled with graphics and more than 300 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest fields. As you tackle the basics of linear algebra, calculus, and machine learning, you’ll master the key Python libraries used to turn them into real-world software applications. Summary To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer. Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest programming fields. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Skip the mathematical jargon: This one-of-a-kind book uses Python to teach the math you need to build games, simulations, 3D graphics, and machine learning algorithms. Discover how algebra and calculus come alive when you see them in code! About the book In Math for Programmers you’ll explore important mathematical concepts through hands-on coding. Filled with graphics and more than 300 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest fields. As you tackle the basics of linear algebra, calculus, and machine learning, you’ll master the key Python libraries used to turn them into real-world software applications. What's inside Vector geometry for computer graphics Matrices and linear transformations Core concepts from calculus Simulation and optimization Image and audio processing Machine learning algorithms for regression and classification About the reader For programmers with basic skills in algebra. About the author Paul Orland is a programmer, software entrepreneur, and math enthusiast. He is co-founder of Tachyus, a start-up building predictive analytics software for the energy industry. You can find him online at www.paulor.land. Table of Contents 1 Learning math with code PART I - VECTORS AND GRAPHICS 2 Drawing with 2D vectors 3 Ascending to the 3D world 4 Transforming vectors and graphics 5 Computing transformations with matrices 6 Generalizing to higher dimensions 7 Solving systems of linear equations PART 2 - CALCULUS AND PHYSICAL SIMULATION 8 Understanding rates of change 9 Simulating moving objects 10 Working with symbolic expressions 11 Simulating force fields 12 Optimizing a physical system 13 Analyzing sound waves with a Fourier series PART 3 - MACHINE LEARNING APPLICATIONS 14 Fitting functions to data 15 Classifying data with logistic regression 16 Training neural networks