Search results for "python arithmetic"
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R 780.00
Arithmetik in Rechenanlagen
Dieses Buch entstand aus einer Reihe von Vorlesungen und Seminaren an der Universitat Saarbrlicken. Es enthalt eine vergleichende Be- schreibung von schnellen und kostenglinstigen Algorithmen zur Reali- sierung arithmetischer Operationen in Digitalrechnern. Obwohl fast aIle Informatiker und nicht wenige Wissenschaftler an- derer Fachrichtungen mit diesen Problemen mehr oder weniger inten- siv konfrontiert werden, behandeln deutschsprachige Fachblicher mit allgemeinerer Zielsetzung diese Fragen nur am Rande oder in ver- gleichsweise kurzen Kapiteln; dies flihrt zwangslaufig zu einer Be- schrankung auf die Beschreibung der bekanntesten und einfachsten Verfahren. In der englischsprachigen Literatur gibt es zwar mehre- re ausgezeichnete Standardwerke (zu erwahnen ist hier in erster Li- nie Flores "The Logic of computer Arithmetic"), doch sind diese oft nur schwer zuganglich und meist alteren Datums; viele wichtige Re- sultate wird man dort also vergeblich suchen. Der Mangel an neueren Blichern liber Rechnerarithmetik kann nicht dar auf zurlickgeflihrt werden, daB aIle interessierenden Probleme be- reits in Standardwerken abgehandelt sind: die Anzahl und die Rele- vanz der in jlingster Zeit veroffentlichten Arbeiten beweist das Ge- genteil. Die Hauptursache daflir liegt nach meiner Ansicht vielmehr in der oft uneinheitlichen Darstellung und der zu starken Beschran- kung vieler Arbeiten auf ein bestimmtes Maschinenkonzept oder auf eine zur Zeit verfligbare bzw. in Entwicklung befindliche Baustein- serie, wodurch eine zusammenfassende Ubersicht sehr erschwert wird.
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Introduction to Digital Music with Python Programming
Introduction to Digital Music with Python Programming provides a foundation in music and code for the beginner. It shows how coding empowers new forms of creative expression while simplifying and automating many of the tedious aspects of production and composition.With the help of online, interactive examples, this book covers the fundamentals of rhythm, chord structure, and melodic composition alongside the basics of digital production. Each new concept is anchored in a real-world musical example that will have you making beats in a matter of minutes.Music is also a great way to learn core programming concepts such as loops, variables, lists, and functions, Introduction to Digital Music with Python Programming is designed for beginners of all backgrounds, including high school students, undergraduates, and aspiring professionals, and requires no previous experience with music or code.
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R 780.00
Expert Python Programming -
Become an ace Python programmer by learning best coding practices and advance-level concepts with Python 3.5About This Book• Based on the latest stable version of Python (version 3.5)• Creating well manageable code that will run in various environments with different sets of dependencies• Packed with advanced concepts and best practices to write efficient Python codeWho This Book Is ForThe book would appeal to web developers and Python programmers who want to start using version 3.5 and write code efficiently. Basic knowledge of Python programming is expected.What You Will Learn• Conventions and best practices that are widely adopted in the python community• Package python code effectively for community and production use• Easy and lightweight ways to automate code deployment on remote systems• Improve your code's quality, reliability, and performance• Write concurrent code in python• Extend python with code written in different languagesIn DetailPython is a dynamic programming language, used in a wide range of domains by programmers who find it simple, yet powerful. Even if you find writing Python code easy, writing code that is efficient and easy to maintain and reuse is a challenge.The focus of the book is to familiarize you with common conventions, best practices, useful tools and standards used by python professionals on a daily basis when working with code.You will begin with knowing new features in Python 3.5 and quick tricks for improving productivity. Next, you will learn advanced and useful python syntax elements brought to this new version. Using advanced object-oriented concepts and mechanisms available in python, you will learn different approaches to implement metaprogramming. You will learn to choose good names, write packages, and create standalone executables easily.You will also be using some powerful tools such as buildout and vitualenv to release and deploy the code on remote servers for production use. Moving on, you will learn to effectively create Python extensions with C, C++, cython, and pyrex. The important factors while writing code such as code management tools, writing clear documentation, and test-driven development are also covered.You will now dive deeper to make your code efficient with general rules of optimization, strategies for finding bottlenecks, and selected tools for application optimization.By the end of the book, you will be an expert in writing efficient and maintainable code.Style and approach An easy-to-follow guide that covers industry followed best practices in Python programming
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Practical Pharmaceutical Calculations
This book develops both the student's mental arithmetic and mathematics and describes the basic arithmetic operations. It explores a reference source formula to calculate quantities of ingredients required to make a given amount of a pharmaceutical product.
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Learning Scientific Programming with Python
Learn to master basic programming tasks from scratch with real-life, scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to gain proficiency quickly. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving on to the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualization, this textbook also discusses the use of Jupyter Notebooks to build rich-media, shareable documents for scientific analysis. The second edition features a new chapter on data analysis with the pandas library and comprehensive updates, and new exercises and examples. A final chapter introduces more advanced topics such as floating-point precision and algorithm stability, and extensive online resources support further study. This textbook represents a targeted package for students requiring a solid foundation in Python programming.
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Python
This title is part of UC Press's Voices Revived program, which commemorates University of California Press’s mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived makes high-quality, peer-reviewed scholarship accessible once again using print-on-demand technology. This title was originally published in 1959.
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Introduction to Python for Science and Engineering
Introduction to Python for Science and Engineering offers a quick and incisive introduction to the Python programming language for use in any science or engineering discipline. The approach is pedagogical and “bottom up,” which means starting with examples and extracting more general principles from that experience. No prior programming experience is assumed.Readers will learn the basics of Python syntax, data structures, input and output, conditionals and loops, user-defined functions, plotting, animation, and visualization. They will also learn how to use Python for numerical analysis, including curve fitting, random numbers, linear algebra, solutions to nonlinear equations, numerical integration, solutions to differential equations, and fast Fourier transforms.Readers learn how to interact and program with Python using JupyterLab and Spyder, two simple and widely used integrated development environments.All the major Python libraries for science and engineering are covered, including NumPy, SciPy, Matplotlib, and Pandas. Other packages are also introduced, including Numba, which can render Python numerical calculations as fast as compiled computer languages such as C but without their complex overhead.
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