Mastering Python Scientific Computing

Hemant Kumar Mehta

Mastering Python Scientific Computing
  • 出版商: Packt Publishing
  • 出版日期: 2015-09-28
  • 售價: $1,710
  • 貴賓價: 9.5 折 $1,625
  • 語言: 英文
  • 頁數: 300
  • 裝訂: Paperback
  • ISBN: 1783288825
  • ISBN-13: 9781783288823
  • 相關分類: Python、程式語言

    • 海外代購書籍(需單獨結帳)

商品描述

A complete guide for Python programmers to master scientific computing using Python APIs and tools

About This Book

  • The basics of scientific computing to advanced concepts involving parallel and large scale computation are all covered.
  • Most of the Python APIs and tools used in scientific computing are discussed in detail
  • The concepts are discussed with suitable example programs

Who This Book Is For

If you are a Python programmer and want to get your hands on scientific computing, this book is for you. The book expects you to have had exposure to various concepts of Python programming.

What You Will Learn

  • Fundamentals and components of scientific computing
  • Scientific computing data management
  • Performing numerical computing using NumPy and SciPy
  • Concepts and programming for symbolic computing using SymPy
  • Using the plotting library matplotlib for data visualization
  • Data analysis and visualization using Pandas, matplotlib, and IPython
  • Performing parallel and high performance computing
  • Real-life case studies and best practices of scientific computing

In Detail

In today's world, along with theoretical and experimental work, scientific computing has become an important part of scientific disciplines. Numerical calculations, simulations and computer modeling in this day and age form the vast majority of both experimental and theoretical papers. In the scientific method, replication and reproducibility are two important contributing factors. A complete and concrete scientific result should be reproducible and replicable. Python is suitable for scientific computing. A large community of users, plenty of help and documentation, a large collection of scientific libraries and environments, great performance, and good support makes Python a great choice for scientific computing.

At present Python is among the top choices for developing scientific workflow and the book targets existing Python developers to master this domain using Python. The main things to learn in the book are the concept of scientific workflow, managing scientific workflow data and performing computation on this data using Python.

The book discusses NumPy, SciPy, SymPy, matplotlib, Pandas and IPython with several example programs.

Style and approach

This book follows a hands-on approach to explain the complex concepts related to scientific computing. It details various APIs using appropriate examples.

商品描述(中文翻譯)

Python程式設計師的完整指南，以Python API和工具來掌握科學計算

關於本書



  • 從科學計算的基礎到涉及並行和大規模計算的高級概念，全部都有涵蓋。

  • 詳細討論了科學計算中使用的大部分Python API和工具。

  • 通過適當的示例程式來討論這些概念。

本書適合對象


如果你是一位Python程式設計師，並且想要進入科學計算領域，這本書適合你。本書預期讀者對Python程式設計的各種概念有所了解。

你將學到什麼



  • 科學計算的基礎和組件

  • 科學計算數據管理

  • 使用NumPy和SciPy進行數值計算

  • 使用SymPy進行符號計算的概念和程式設計

  • 使用matplotlib進行數據可視化

  • 使用Pandas、matplotlib和IPython進行數據分析和可視化

  • 進行並行和高性能計算

  • 科學計算的實際案例研究和最佳實踐

詳細內容


在當今世界，除了理論和實驗工作外，科學計算已成為科學學科的重要組成部分。數值計算、模擬和計算機建模在當今時代佔了實驗和理論論文的絕大多數。在科學方法中，複製性和可重複性是兩個重要的貢獻因素。一個完整和具體的科學結果應該是可重複和可複製的。Python非常適合進行科學計算。龐大的用戶社區、豐富的幫助和文檔、大量的科學庫和環境、出色的性能和良好的支援使Python成為進行科學計算的絕佳選擇。

目前，Python是開發科學工作流程的首選之一，本書旨在幫助現有的Python開發人員通過Python來掌握這個領域。本書的主要學習內容是科學工作流程的概念、管理科學工作流程數據以及使用Python對這些數據進行計算。

本書討論了NumPy、SciPy、SymPy、matplotlib、Pandas和IPython，並提供了多個示例程式。

風格和方法


本書採用實踐方法來解釋與科學計算相關的複雜概念，並通過適當的示例來詳細介紹各種API。

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