Implementacao De Dft Programado Em Python
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Implementação De Dft Programado Em Python
Author: Vitor Amadeu Souza
language: pt-BR
Publisher: Clube de Autores
Release Date: 2025-07-04
Neste livro, o leitor encontrará uma abordagem prática e acessível para compreender a Transformada Discreta de Fourier (DFT) aplicada à análise de sinais no domínio da frequência utilizando a linguagem Python. Por meio de um exemplo claro e bem estruturado, como a decomposição de um sinal composto por duas senóides e ruído branco, é possível observar como a DFT permite identificar as frequências componentes de um sinal e visualizá-las de forma precisa em um gráfico espectral. O código apresentado mostra como gerar sinais artificiais, calcular a DFT com a biblioteca NumPy e detectar automaticamente os picos de frequência com o auxílio do Scipy, evidenciando a presença de componentes periódicas mesmo em meio ao ruído. Com o suporte da visualização gráfica oferecida pelo Matplotlib, o leitor poderá interpretar os resultados com maior clareza e segurança. Este material é ideal para estudantes, professores e profissionais das áreas de engenharia, ciência de dados e física que desejam dominar as técnicas fundamentais da análise espectral e aprender a aplicar transformadas digitais de forma efetiva em projetos reais com Python.
Python for Quantum Chemistry
Quantum chemistry requires ever higher computational performance, with more and more sophisticated and dedicated Python scripts being required to solve challenging problems. Although resources for basic use of Python are widely (and often freely) available online and in literature, truly cohesive materials for advanced Python programming skills are lacking.Qiming Sun, a developer of the popular Python package PySCF, provides a comprehensive, end-to-end practical resource for researchers and engineers who have basic Python programming experiences chiefly in computational chemistry but want to take their use of the software forwards to the next level, the book provides an insightful exploration of Numpy, Pandas, and other data analysis tools. Readers will learn how to manage their Python computational projects in a professional way, with various tools and protocols for computational chemistry research and general scientific computing tasks exhibited and analysed from a technical perspective. Multiple programming paradigms including object-oriented, functional, meta-programming, dynamic, concurrent, and vector-oriented are illustrated in various technology scenarios allowing readers to properly use them to enhance their program projects. Readers will also learn how to use the presented optimization technologies to speed up their Python applications, even to the level as fast as a native C++ implementation. The applications of these technologies are then demonstrated using quantum chemistry Python applications.Python for Quantum Chemistry: A Full Stack Programming Guide is written primarily for graduate students, researchers and software engineers working primarily in the fields of theoretical chemistry, computational chemistry, condensed matter physics, material modelling, molecular simulations, and quantum computing. - End-to end guide for advanced Python programming skills and tools related to quantum chemistry research - Tackles the following questions: How can you ensure the Python runtime is manageable when the preliminary implementation becomes complicated or evolves many branches? How do I ensure that others' Python program works properly in my project? How do I make my Python project reusable for others? - Covers in depth the crucial topic of Python code optimization methods with high-performance computing technologies - Provides examples of Python applications with cutting-edge technologies such as automatic code generation, cloud computing, and GPGPU - Includes discussion of Python runtime mechanism and advanced Python technologies
The Python Audio Cookbook
The Python Audio Cookbook offers an introduction to Python for sound and multimedia applications, with chapters that cover writing your first Python programs, controlling Pyo with physical computing, and writing your own GUI, among many other topics. Guiding the reader through a variety of audio synthesis techniques, the book empowers readers to combine their projects with popular platforms, from the Arduino to Twitter, and state-of-the-art practices such as AI. The Python Audio Cookbook balances accessible explanations for theoretical concepts, including Python syntax, audio processing and machine learning, with practical applications. This book is an essential introductory guide to Python for sound and multimedia practitioners, as well as programmers interested in audio applications.