相關主題
商品描述
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.
商品描述(中文翻譯)
《科學與工程的 Python 入門》提供了一個快速且深入的 Python 程式語言介紹，適用於任何科學或工程領域。這種方法是以教學為導向的「自下而上」，意味著從範例開始，並從這些經驗中提取更一般的原則。無需具備先前的程式設計經驗。
讀者將學習 Python 語法、資料結構、輸入與輸出、條件語句與迴圈、使用者定義函數、繪圖、動畫和視覺化的基本知識。他們還將學習如何使用 Python 進行數值分析，包括曲線擬合、隨機數、線性代數、非線性方程的解、數值積分、微分方程的解以及快速傅立葉變換。
讀者將學習如何使用 JupyterLab 和 Spyder 這兩個簡單且廣泛使用的整合開發環境來互動和編程。
所有主要的 Python 科學與工程庫都涵蓋在內，包括 NumPy、SciPy、Matplotlib 和 Pandas。還介紹了其他套件，包括 Numba，它可以使 Python 的數值計算速度與 C 等編譯型計算機語言一樣快，但沒有其複雜的開銷。
作者簡介
David J. Pine has taught physics and chemical engineering for over 40 years at four different institutions: Cornell University (as a graduate student), Haverford College, UCSB, and NYU, where he is a Professor of Physics, Mathematics, and Chemical & Biomolecular Engineering. He has taught a broad spectrum of courses, including numerical methods. He does research on optical materials and in experimental soft-matter physics, which is concerned with materials such as polymers, emulsions, and colloids.
作者簡介(中文翻譯)
David J. Pine 在四所不同的機構教授物理和化學工程已超過 40 年：康奈爾大學（作為研究生）、哈佛福德學院、加州大學聖巴巴拉分校（UCSB）和紐約大學（NYU），目前擔任物理、數學以及化學與生物分子工程的教授。他教授的課程範圍廣泛，包括數值方法。他的研究領域包括光學材料以及實驗軟物質物理，該領域關注的材料包括聚合物、乳液和膠體。
