Introducing Python

Written in the wake of the advent of Relativity by an author who made important contributions to projective and differential geometry, and topology, this early Cambridge Tract in Mathematics and Theoretical Physics aimed to assist students of the time from the fields of differential geometry and mathematical physics. Beginning by introducing formal preliminaries, the text continues, bringing the underlying differential invariant theory that to this day remains relevant in a range of geometrical and physical applications, to the fore.

本書是一部系統性探討海洋與沿岸波浪的專業著作，兼顧物理意義與統計分析，適合研究所學生、研究人員與工程實務者閱讀。內容從觀測技術談起，介紹現地量測與遙測方法，並逐步建立描述波浪的參數與統計架構。書中詳述線性波理論在外海與近岸水域的應用，說明波浪在不同水深與地形條件下的行為差異，並深入介紹 SWAN 波浪模式，協助讀者理解現代數值模擬在工程與研究中的角色。全書結構嚴謹、插圖清楚，是理解風生波浪與海岸波動不可或缺的參考書。Waves in Oceanic and Coastal Waters describes the observation, analysis and prediction of wind-generated waves in the open ocean, in shelf seas, and in coastal regions with islands, channels, tidal flats and inlets, estuaries, fjords and lagoons. Most of this richly illustrated book is devoted to the physical aspects of waves. After introducing observation techniques for waves, both at sea and from space, the book defines the parameters that characterise waves. Using basic statistical and physical concepts, the author discusses the prediction of waves in oceanic and coastal waters, first in terms of generalised observations, and then in terms of the more theoretical framework of the spectral energy balance. He gives the results of established theories and also the direction in wh

Python is one of the most popular programming languages, widely used for data analysis and modelling, and is fast becoming the leading choice for scientists and engineers. Unlike other textbooks introducing Python, typically organised by language syntax, this book uses many examples from across Biology, Chemistry, Physics, Earth science, and Engineering to teach and motivate students in science and engineering. The text is organised by the tasks and workflows students undertake day-to-day, helping them see the connections between programming tools and their disciplines. The pace of study is carefully developed for complete beginners, and a spiral pedagogy is used so concepts are introduced across multiple chapters, allowing readers to engage with topics more than once. “Try This!” exercises and online Jupyter notebooks encourage students to test their new knowledge, and further develop their programming skills. Online solutions are available for instructors, alongside discipline-specif

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 quickly gain proficiency. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving onto the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualisation, this textbook also discusses the use of IPython notebooks to build rich-media, shareable documents for scientific analysis. Including a final chapter introducing challenging topics such as floating-point precision and algorithm stability, and with extensive online resources to support advanced study, this textbook represents a targe

Specifically designed for linguists, this book provides an introduction to programming using Python for those with little to no experience of coding. Python is one of the most popular and widely-used programming languages as it's also available for free and runs on any operating system. All examples in the text involve language data and can be adapted or used directly for language research. The text focuses on key language-related issues: searching, text manipulation, text encoding and internet data, providing an excellent resource for language research. More experienced users of Python will also benefit from the advanced chapters on graphical user interfaces and functional programming.

Specifically designed for linguists, this book provides an introduction to programming using Python for those with little to no experience of coding. Python is one of the most popular and widely-used programming languages as it's also available for free and runs on any operating system. All examples in the text involve language data and can be adapted or used directly for language research. The text focuses on key language-related issues: searching, text manipulation, text encoding and internet data, providing an excellent resource for language research. More experienced users of Python will also benefit from the advanced chapters on graphical user interfaces and functional programming.

Text is everywhere, and it is a fantastic resource for social scientists. However, because it is so abundant, and because language is so variable, it is often difficult to extract the information we want. There is a whole subfield of AI concerned with text analysis (natural language processing). Many of the basic analysis methods developed are now readily available as Python implementations. This Element will teach you when to use which method, the mathematical background of how it works, and the Python code to implement it.

Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. Accompanying the mathematical derivations are full implementations of dozens of numerical methods in Python, as well as more than 250 end-of-chapter problems. Numerical methods and physics examples are clearly separated, allowing this introductory book to be later used as a reference; the penultimate section in each chapter is an in depth project, tackling physics problems which cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the

Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. Accompanying the mathematical derivations are full implementations of dozens of numerical methods in Python, as well as more than 250 end-of-chapter problems. Numerical methods and physics examples are clearly separated, allowing this introductory book to be later used as a reference; the penultimate section in each chapter is an in depth project, tackling physics problems which cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the

Python is today's fastest growing programming language. This engaging and refreshingly different guide breaks down the skills into clear step-by-step chunks and explains the theory using brief easy-to-understand language. Rather than bamboozling readers with pages of mind-numbing technical jargon, this book includes 150 practical challenges, putting the power in the reader's hands. Through creating programs to solve these challenges the reader will quickly progress from mastering the basics to confidently using subroutines, a graphical user interface, and linking to external text, csv and SQL files. This book is perfect for anyone who wants to learn how to program with Python. In particular, students starting out in computer science and teachers who want to improve their confidence in Python will find here a set of ready-made challenges for classroom use.

Syntax is the system of rules that we subconsciously follow when we build sentences. Whereas the grammar of English (or other languages) might look like a rather chaotic set of arbitrary patterns, linguistic science has revealed that these patterns can actually be understood as the result of a small number of grammatical principles. This lively introductory textbook is designed for undergraduate students in linguistics, English and modern languages with relatively little background in the subject, offering the necessary tools for the analysis of phrases and sentences while at the same time introducing state-of-the-art syntactic theory in an accessible and engaging way. Guiding students through a variety of intriguing puzzles, striking facts and novel ideas, Introducing Syntax presents contemporary insights into syntactic theory in one clear and coherent narrative, avoiding unnecessary detail and enabling readers to understand the rationale behind technicalities. Aids to learning includ

Syntax is the system of rules that we subconsciously follow when we build sentences. Whereas the grammar of English (or other languages) might look like a rather chaotic set of arbitrary patterns, linguistic science has revealed that these patterns can actually be understood as the result of a small number of grammatical principles. This lively introductory textbook is designed for undergraduate students in linguistics, English and modern languages with relatively little background in the subject, offering the necessary tools for the analysis of phrases and sentences while at the same time introducing state-of-the-art syntactic theory in an accessible and engaging way. Guiding students through a variety of intriguing puzzles, striking facts and novel ideas, Introducing Syntax presents contemporary insights into syntactic theory in one clear and coherent narrative, avoiding unnecessary detail and enabling readers to understand the rationale behind technicalities. Aids to learning includ

Scientific Python is a significant public domain alternative to expensive proprietary software packages. This book teaches from scratch everything the working scientist needs to know using copious, downloadable, useful and adaptable code snippets. Readers will discover how easy it is to implement and test non-trivial mathematical algorithms and will be guided through the many freely available add-on modules. A range of examples, relevant to many different fields, illustrate the language's capabilities. The author also shows how to use pre-existing legacy code (usually in Fortran77) within the Python environment, thus avoiding the need to master the original code. In this new edition, several chapters have been re-written to reflect the IPython notebook style. With an extended index, an entirely new chapter discussing SymPy and a substantial increase in the number of code snippets, researchers and research students will be able to quickly acquire all the skills needed for using Python e

Volume introducing key frames of analysis and themes that shaped world history, and surveying the earliest phases of human history.

Do you have a biological question that could be readily answered by computational techniques, but little experience in programming? Do you want to learn more about the core techniques used in computational biology and bioinformatics? Written in an accessible style, this guide provides a foundation for both newcomers to computer programming and those interested in learning more about computational biology. The chapters guide the reader through: a complete beginners' course to programming in Python, with an introduction to computing jargon; descriptions of core bioinformatics methods with working Python examples; scientific computing techniques, including image analysis, statistics and machine learning. This book also functions as a language reference written in straightforward English, covering the most common Python language elements and a glossary of computing and biological terms. This title will teach undergraduates, postgraduates and professionals working in the life sciences how t

Introduces Python as a powerful tool for the investigation of problems in computational biology, for novices and experienced programmers alike.

"Python is a free, open source, easy-to-use software tool that offers a significant alternative to proprietary packages such as MATLAB and Mathematica. This book covers everything the working scientis

"Python is a free, open source, easy-to-use software tool that offers a significant alternative to proprietary packages such as MATLAB and Mathematica. This book covers everything the working scientis

All social and policy researchers need to synthesize data into a visual representation. Producing good visualizations combines creativity and technique. This book teaches the techniques and basics to produce a variety of visualizations, allowing readers to communicate data and analyses in a creative and effective way. Visuals for tables, time series, maps, text, and networks are carefully explained and organized, showing how to choose the right plot for the type of data being analysed and displayed. Examples are drawn from public policy, public safety, education, political tweets, and public health. The presentation proceeds step by step, starting from the basics, in the programming languages R and Python so that readers learn the coding skills while simultaneously becoming familiar with the advantages and disadvantages of each visualization. No prior knowledge of either Python or R is required. Code for all the visualizations are available from the book's website.

All social and policy researchers need to synthesize data into a visual representation. Producing good visualizations combines creativity and technique. This book teaches the techniques and basics to produce a variety of visualizations, allowing readers to communicate data and analyses in a creative and effective way. Visuals for tables, time series, maps, text, and networks are carefully explained and organized, showing how to choose the right plot for the type of data being analysed and displayed. Examples are drawn from public policy, public safety, education, political tweets, and public health. The presentation proceeds step by step, starting from the basics, in the programming languages R and Python so that readers learn the coding skills while simultaneously becoming familiar with the advantages and disadvantages of each visualization. No prior knowledge of either Python or R is required. Code for all the visualizations are available from the book's website.

This accessible and entertaining textbook introduces students to both traditional and more contemporary approaches to sociolinguistics in a real-world context, addressing current social problems that students are likely to care about, such as racism, inequality, political conflict, belonging, and issues around gender and sexuality. Each chapter includes exercises, case studies and ideas for small-scale research projects, encouraging students to think critically about the different theories and approaches to language and society, and to interrogate their own beliefs about language and communication. The book gives students a grounding in the traditional concepts and techniques upon which sociolinguistics is built, while also introducing new developments from the last decade, such as translanguaging, multimodality, superdiversity, linguistic landscapes and language and digital media. Students will also have online access to more detailed examples, links to video and audio files, and more

This accessible and entertaining textbook introduces students to both traditional and more contemporary approaches to sociolinguistics in a real-world context, addressing current social problems that students are likely to care about, such as racism, inequality, political conflict, belonging, and issues around gender and sexuality. Each chapter includes exercises, case studies and ideas for small-scale research projects, encouraging students to think critically about the different theories and approaches to language and society, and to interrogate their own beliefs about language and communication. The book gives students a grounding in the traditional concepts and techniques upon which sociolinguistics is built, while also introducing new developments from the last decade, such as translanguaging, multimodality, superdiversity, linguistic landscapes and language and digital media. Students will also have online access to more detailed examples, links to video and audio files, and more

Want to kill it at your job interview in the tech industry? Want to win that coding competition? Learn all the algorithmic techniques and programming skills you need from two experienced coaches, problem setters, and jurors for coding competitions. The authors highlight the versatility of each algorithm by considering a variety of problems and show how to implement algorithms in simple and efficient code. Readers can expect to master 128 algorithms in Python and discover the right way to tackle a problem and quickly implement a solution of low complexity. Classic problems like Dijkstra's shortest path algorithm and Knuth-Morris-Pratt's string matching algorithm are featured alongside lesser known data structures like Fenwick trees and Knuth's dancing links. The book provides a framework to tackle algorithmic problem solving, including: Definition, Complexity, Applications, Algorithm, Key Information, Implementation, Variants, In Practice, and Problems. Python code included in the book

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-p

Assuming no prior linguistics background, this introductory textbook summarises key topics and issues from workplace discourse research in a clear and accessible manner. The topics covered include how people issue directives, use humour and social talk, and how they manage conflict and disagreement. The role of language in the enactment of identity is also explored, in particular leadership, gender, and cultural identity, along with the implications and applications of workplace research for training and communications skills development. Over 160 international examples are provided as illustration, which come from a wide range of workplace settings, countries and languages. The examples focus on authentic spoken discourse, to demonstrate how theory captures the patterns found in everyday interaction. Introducing Language in the Workplace provides an excellent up-to-date resource for linguistics courses as well as other courses that cover workplace discourse, such as business communica

Assuming no prior linguistics background, this introductory textbook summarises key topics and issues from workplace discourse research in a clear and accessible manner. The topics covered include how people issue directives, use humour and social talk, and how they manage conflict and disagreement. The role of language in the enactment of identity is also explored, in particular leadership, gender, and cultural identity, along with the implications and applications of workplace research for training and communications skills development. Over 160 international examples are provided as illustration, which come from a wide range of workplace settings, countries and languages. The examples focus on authentic spoken discourse, to demonstrate how theory captures the patterns found in everyday interaction. Introducing Language in the Workplace provides an excellent up-to-date resource for linguistics courses as well as other courses that cover workplace discourse, such as business communica

How humans produce and understand language is clearly introduced in this textbook for students with only a basic knowledge of linguistics. With a logical, flexible structure Introducing Psycholinguistics steps through the central topics of production and comprehension of language and the interaction between them. Students will gain an understanding of the processes and representations involved in language use, aided by a comprehensive glossary, concepts defined in the margins and online flashcards that allow students to check their understanding of all the key terms and concepts of the subject. Examples and exercises throughout each topic reinforce understanding and encourage students to consider what language users might carry around in their heads as part of their linguistic knowledge, and how this stored knowledge relates to the structures and rules proposed by theoretical linguistics. Students will gain hands-on experience of experimental methods, with online demonstrations of tech

Are you looking for a genuine introduction to the linguistics of English that provides a broad overview of the subject that sustains students' interest and avoids excessive detail? Introducing English Linguistics accomplishes this goal in two ways. First, it takes a top-down approach to language, beginning with the largest unit of linguistic structure, the text, and working its way down through successively smaller structures (sentences, words, and finally speech sounds). The advantage of presenting language this way is that students are first given the larger picture - they study language in context - and then see how the smaller pieces of language are a consequence of the larger goals of linguistic communication. Second, the book does not contain invented examples, as is the case with most comparable texts, but instead takes its sample materials from the major computerised databases of spoken and written English, giving students a more realistic view of language.

Are you looking for a genuine introduction to the linguistics of English that provides a broad overview of the subject that sustains students' interest and avoids excessive detail? Introducing English Linguistics accomplishes this goal in two ways. First, it takes a top-down approach to language, beginning with the largest unit of linguistic structure, the text, and working its way down through successively smaller structures (sentences, words, and finally speech sounds). The advantage of presenting language this way is that students are first given the larger picture - they study language in context - and then see how the smaller pieces of language are a consequence of the larger goals of linguistic communication. Second, the book does not contain invented examples, as is the case with most comparable texts, but instead takes its sample materials from the major computerised databases of spoken and written English, giving students a more realistic view of language.

A no-nonsense introduction to software design using the Python programming language. Written for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters. The focus is on the programming process, with special emphasis on debugging. The book includes a wide range of exercises, from short examples to substantial projects, so that students have ample opportunity to practise each new concept. Exercise solutions and code examples are available from thinkpython.com, along with Swampy, a suite of Python programs that is used in some of the exercises.

A no-nonsense introduction to software design using the Python programming language. Written for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters. The focus is on the programming process, with special emphasis on debugging. The book includes a wide range of exercises, from short examples to substantial projects, so that students have ample opportunity to practise each new concept. Exercise solutions and code examples are available from thinkpython.com, along with Swampy, a suite of Python programs that is used in some of the exercises.

Offering a new perspective, this textbook demystifies the operation of electric machines by providing an integrated understanding of electromagnetic fields, electric circuits, numerical analysis, and computer programming. It presents fundamental concepts in a rigorous manner, emphasising underlying physical modelling assumptions and limitations, and provides detailed explanations of how to implement the finite element method to explore these concepts using Python. It includes explanations of the conversion of concepts into algorithms, and algorithms into code, and examples building in complexity, from simple linear-motion electromagnets to rotating machines. Over 100 theoretical and computational end-of-chapter exercises test understanding, with solutions for instructors and downloadable Python code available online. Ideal for graduates and senior undergraduates studying electric machines, electric machine design and control, and power electronic converters and power systems engineerin

Ideal for entry-level and experienced researchers working in materials science and engineering, this unique book introduces a new subfield of materials science and mechanics of materials: network materials. A comprehensive review of their mechanical behaviours allows readers to understand, design, and enhance the performance of these material systems, across a range of materials including cytoskeletons, connective tissue, and thermoset polymers. By introducing simple models, supported by experimental data, the book provides the necessary fundamental knowledge to assist readers to design and develop their own material systems. By presenting each of these previously disparate material systems within a unified theoretical framework, this book provides a consolidated presentation of the mechanics of networks and their interactions, introducing parameters that define the stochastic structure of the network, and discussing their mechanical behaviour. It is an ideal text for those new to this

This comprehensive guide to Bayesian methods in astronomy enables hands-on work by supplying complete R, JAGS, Python, and Stan code, to use directly or to adapt. It begins by examining the normal model from both frequentist and Bayesian perspectives and then progresses to a full range of Bayesian generalized linear and mixed or hierarchical models, as well as additional types of models such as ABC and INLA. The book provides code that is largely unavailable elsewhere and includes details on interpreting and evaluating Bayesian models. Initial discussions offer models in synthetic form so that readers can easily adapt them to their own data; later the models are applied to real astronomical data. The consistent focus is on hands-on modeling, analysis of data, and interpretations that address scientific questions. A must-have for astronomers, its concrete approach will also be attractive to researchers in the sciences more generally.

Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.

Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.

Reader for intermediate students of ancient Greek introducing three of ancient Greece's most important authors, Homer, Herodotus and Sophocles.

Reader for intermediate students of ancient Greek introducing three of ancient Greece's most important authors, Euripides, Thucydides and Plato.

Computing is revolutionizing the practice of biology. This book, which assumes no prior computing experience, provides students with the tools to write their own Python programs and to understand fundamental concepts in computational biology and bioinformatics. Each major part of the book begins with a compelling biological question, followed by the algorithmic ideas and programming tools necessary to explore it: the origins of pathogenicity are examined using gene finding, the evolutionary history of sex determination systems is studied using sequence alignment, and the origin of modern humans is addressed using phylogenetic methods. In addition to providing general programming skills, this book explores the design of efficient algorithms, simulation, NP-hardness, and the maximum likelihood method, among other key concepts and methods. Easy-to-read and designed to equip students with the skills to write programs for solving a range of biological problems, the book is accompanied by nu

Computing is revolutionizing the practice of biology. This book, which assumes no prior computing experience, provides students with the tools to write their own Python programs and to understand fundamental concepts in computational biology and bioinformatics. Each major part of the book begins with a compelling biological question, followed by the algorithmic ideas and programming tools necessary to explore it: the origins of pathogenicity are examined using gene finding, the evolutionary history of sex determination systems is studied using sequence alignment, and the origin of modern humans is addressed using phylogenetic methods. In addition to providing general programming skills, this book explores the design of efficient algorithms, simulation, NP-hardness, and the maximum likelihood method, among other key concepts and methods. Easy-to-read and designed to equip students with the skills to write programs for solving a range of biological problems, the book is accompanied by nu