Introduction to Python Programming And Data Structure By Liang

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

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.

This new edition of Andrew Radford's outstanding resource for students is a step-by-step, practical introduction to English syntax and syntactic principles, written by a globally-renowned expert in the field. Assuming little or no prior background in syntax, Radford outlines key concepts and how they can be used to describe various aspects of English sentence structure. Each chapter contains core modules focusing on a specific topic, a summary recapitulating the main points of the chapter, and a bibliographical section providing references to original source material. This edition has been extensively updated, with new analyses, exercise materials, references and a brand-new chapter on adjuncts. Students will benefit from the online workbook, which contains a vast amount of exercise material for each module, including self-study materials and a student answerbook for these. Teachers will value the extensive PowerPoints outlining module contents and the comprehensive teacher answerbook,

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

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

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

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

Infectious disease accounts for more death and disability globally than either non-infectious disease or injury. This book contains a breadth of different quantitative approaches to understanding the patterns of infectious diseases in populations, and the design of control strategies to lessen their effect. The contributors bring a great variety of mathematical expertise (including deterministic and stochastic modelling and statistical data analysis) and involvement in a wide range of applied fields across the spectrum of biological, medical and social sciences. The aim is to increase interaction between specialities by describing research on many of the infectious diseases that affect humans, including both viral diseases like measles and AIDS and tropical parasitic infections. The papers are divided into groups dealing with problems relating to transmissible diseases, vaccination strategies, the consequences of treatment interventions, the dynamics of immunity, heterogeneity of popu

Infectious disease accounts for more death and disability globally than either non-infectious disease or injury. This book contains a breadth of different quantitative approaches to understanding the patterns of infectious diseases in populations, and the design of control strategies to lessen their effect. The contributors bring a great variety of mathematical expertise (including deterministic and stochastic modelling and statistical data analysis) and involvement in a wide range of applied fields across the spectrum of biological, medical and social sciences. The aim is to increase interaction between specialities by describing research on many of the infectious diseases that affect humans, including both viral diseases like measles and AIDS and tropical parasitic infections. The papers are divided into groups dealing with problems relating to transmissible diseases, vaccination strategies, the consequences of treatment interventions, the dynamics of immunity, heterogeneity of popu

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.

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

This book introduces the field of data science in a practical and accessible manner, using a hands-on approach that assumes no prior knowledge of the subject. The foundational ideas and techniques of data science are provided independently from technology, allowing students to easily develop a firm understanding of the subject without a strong technical background, as well as being presented with material that will have continual relevance even after tools and technologies change. Using popular data science tools such as Python and R, the book offers many examples of real-life applications, with practice ranging from small to big data. A suite of online material for both instructors and students provides a strong supplement to the book, including datasets, chapter slides, solutions, sample exams and curriculum suggestions. This entry-level textbook is ideally suited to readers from a range of disciplines wishing to build a practical, working knowledge of data science.

With the arrival of genomics and genome sequencing projects, biology has been transformed into an incredibly data-rich science. The vast amount of information generated has made computational analysis critical and has increased demand for skilled bioinformaticians. Designed for biologists without previous programming experience, this textbook provides a hands-on introduction to Unix, Perl and other tools used in sequence bioinformatics. Relevant biological topics are used throughout the book and are combined with practical bioinformatics examples, leading students through the process from biological problem to computational solution. All of the Perl scripts, sequence and database files used in the book are available for download at the accompanying website, allowing the reader to easily follow each example using their own computer. Programming examples are kept at an introductory level, avoiding complex mathematics that students often find daunting. The book demonstrates that even simp

With the arrival of genomics and genome sequencing projects, biology has been transformed into an incredibly data-rich science. The vast amount of information generated has made computational analysis critical and has increased demand for skilled bioinformaticians. Designed for biologists without previous programming experience, this textbook provides a hands-on introduction to Unix, Perl and other tools used in sequence bioinformatics. Relevant biological topics are used throughout the book and are combined with practical bioinformatics examples, leading students through the process from biological problem to computational solution. All of the Perl scripts, sequence and database files used in the book are available for download at the accompanying website, allowing the reader to easily follow each example using their own computer. Programming examples are kept at an introductory level, avoiding complex mathematics that students often find daunting. The book demonstrates that even simp

Scala is a highly expressive, concise and scalable language. It is also the most prominent method of the new and exciting methodology known as object-functional programming. In this book, the authors show how Scala grows to the needs of the programmer, whether professional or hobbyist. They teach Scala with a step-by-step approach and explain how to exploit the full power of the industry-proven JVM technology. Readers can then dive into specially chosen design challenges and implementation problems, inspired by the trials of real-world software engineering. It also helps readers to embrace the power of static typing and automatic type inference. In addition, the book shows how to use the dual-object and functional-oriented natures combined at Scala's core, and so write code that is less 'boilerplate', giving a genuine increase in productivity.

Most of the time we communicate using language without considering the complex activity we are undertaking, forming words and sentences in a split second. This book introduces the analysis of language structure, combining both description and theory within a single, practical text. It begins by examining words and parts of words, and then looks at how words work together to form sentences that communicate meaning. Sentence patterns across languages are also studied, looking at the similarities and the differences we find in how languages communicate meaning. The book also discusses how context can affect how we structure our sentences: the context of a particular language and its structures, the context of old and new information for us and our addressee(s), and the context of our culture.

Most of the time we communicate using language without considering the complex activity we are undertaking, forming words and sentences in a split second. This book introduces the analysis of language structure, combining both description and theory within a single, practical text. It begins by examining words and parts of words, and then looks at how words work together to form sentences that communicate meaning. Sentence patterns across languages are also studied, looking at the similarities and the differences we find in how languages communicate meaning. The book also discusses how context can affect how we structure our sentences: the context of a particular language and its structures, the context of old and new information for us and our addressee(s), and the context of our culture.

Scala is a highly expressive, concise and scalable language. It is also the most prominent method of the new and exciting methodology known as object-functional programming. In this book, the authors show how Scala grows to the needs of the programmer, whether professional or hobbyist. They teach Scala with a step-by-step approach and explain how to exploit the full power of the industry-proven JVM technology. Readers can then dive into specially chosen design challenges and implementation problems, inspired by the trials of real-world software engineering. It also helps readers to embrace the power of static typing and automatic type inference. In addition, the book shows how to use the dual-object and functional-oriented natures combined at Scala's core, and so write code that is less 'boilerplate', giving a genuine increase in productivity.

X-ray absorption fine structure spectroscopy (XAFS) is a powerful and versatile technique for studying structures of materials in chemistry, physics, biology and other fields. This textbook is a comprehensive, practical guide to carrying out and interpreting XAFS experiments. Assuming only undergraduate-level physics and mathematics, the textbook is ideally suited for graduate students in physics and chemistry starting XAFS-based research. It contains concise executable example programs in Mathematica 7. Supplementary material available at www.cambridge.org/9780521767750 includes Mathematica code from the book, related Mathematica programs, and worked data analysis examples. The textbook addresses experiment, theory, and data analysis, but is not tied to specific data analysis programs or philosophies. This makes it accessible to a broad audience in the sciences, and a useful guide for researchers entering the subject.

Using fundamental physics, the theory of stellar structure and evolution can predict how stars are born, how their complex internal structure changes, what nuclear fuel they burn, and their ultimate fate. This textbook is a stimulating introduction for undergraduates in astronomy, physics and applied mathematics, taking a course on the physics of stars. It uniquely emphasises the basic physical principles governing stellar structure and evolution. This second edition contains two new chapters on mass loss from stars and interacting binary stars, and new exercises. Clear and methodical, it explains the processes in simple terms, while maintaining mathematical rigour. Starting from general principles, this textbook leads students step-by-step to a global, comprehensive understanding of the subject. Fifty exercises and full solutions allow students to test their understanding. No prior knowledge of astronomy is required, and only a basic background in physics and mathematics is necessary.

The Sound Structure of English provides a clear introduction to English phonetics and phonology. Tailored to suit the needs of individual, one-term course modules, it assumes no prior knowledge of the subject, and presents the basic facts in a straightforward manner, making it the ideal text for beginners. Students are guided step-by-step through the main concepts and techniques of phonetic and phonological analysis, aided by concise chapter summaries, suggestions for further reading, and a comprehensive glossary of all the terms introduced. Each chapter is accompanied by an engaging set of exercises and discussion questions, encouraging students to consolidate and develop their learning, and providing essential self-study material. The book is accompanied by a companion website, featuring solutions to the exercises and useful additional resources. Providing the essential knowledge and skills for those embarking on the study of English sounds, it is set to become the leading introducti

The Sound Structure of English provides a clear introduction to English phonetics and phonology. Tailored to suit the needs of individual, one-term course modules, it assumes no prior knowledge of the subject, and presents the basic facts in a straightforward manner, making it the ideal text for beginners. Students are guided step-by-step through the main concepts and techniques of phonetic and phonological analysis, aided by concise chapter summaries, suggestions for further reading, and a comprehensive glossary of all the terms introduced. Each chapter is accompanied by an engaging set of exercises and discussion questions, encouraging students to consolidate and develop their learning, and providing essential self-study material. The book is accompanied by a companion website, featuring solutions to the exercises and useful additional resources. Providing the essential knowledge and skills for those embarking on the study of English sounds, it is set to become the leading introducti

International agreements, such as those governing arms control or the environment, virtually always require some degree of verification of information, in order that compliance can be established. To ensure that the verification process can be regarded as efficient, effective and impartial, it is important to have a mathematical model of it. One can be derived by applying methods from statistics and the theory of non-cooperative games, developed in part by John Nash, who received a Nobel prize in 1994 for his work. The methods permit the development of rational verification strategies, as well as such fundamental concepts as guaranteed probability of detection, timeliness of inspections and the deterrence of illegal activity. In this 1996 book, the required theory is introduced gradually in the context of specific real-world examples. The only prerequisites are simple calculus and statistics, so the book should be accessible to a broad range of scientists and non-scientists, in industr

International agreements, such as those governing arms control or the environment, virtually always require some degree of verification of information, in order that compliance can be established. To ensure that the verification process can be regarded as efficient, effective and impartial, it is important to have a mathematical model of it. One can be derived by applying methods from statistics and the theory of non-cooperative games, developed in part by John Nash, who received a Nobel prize in 1994 for his work. The methods permit the development of rational verification strategies, as well as such fundamental concepts as guaranteed probability of detection, timeliness of inspections and the deterrence of illegal activity. In this 1996 book, the required theory is introduced gradually in the context of specific real-world examples. The only prerequisites are simple calculus and statistics, so the book should be accessible to a broad range of scientists and non-scientists, in industr

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.

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.

Experimental data can often be associated with or indexed by certain symmetrically interesting structures or sets of labels that appear, for example, in the study of short symbolic sequences in molecular biology, in preference or voting data, in (corneal) curvature data, and in studies of the handedness and entropy of symbolic sequences and elementary images. The symmetry studies introduced in this book describe the interplay among symmetry transformations that are characteristic of these sets of labels, their resulting classification, the algebraic decomposition of the data indexed by them, and the statistical analysis of the invariants induced by those decompositions. The overall purpose is to facilitate and guide the statistical study of the structured data from both a descriptive and inferential perspective. The text combines notions of algebra and statistics and develops a systematic methodology to better explore the interplay between symmetry-related research questions and their

This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter.

This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter.

Numbers are part of our everyday experience and their properties have fascinated mankind since ancient times. Deciding whether a number is prime and if not, what its factors are, are both fundamental problems. In recent years analysis and solution of these problems have assumed commercial significance since large primes are an essential feature of secure methods of information transmission. The purely mathematical fascination that led to the development of methods for primality testing has been supplemented by the need to test within reasonable timescales, and computational methods have entered at all levels of number theory. In this book, Peter Giblin describes, in the context of an introduction to the theory of numbers, some of the more elementary methods for factorization and primality testing; that is, methods independent of a knowledge of other areas of mathematics. Indeed everything is developed from scratch so the mathematical prerequisites are minimal. An essential feature of t

Linear algebra is something all mathematics undergraduates and many other students, in subjects ranging from engineering to economics, have to learn. The fifth edition of this hugely successful textbook retains the quality of earlier editions while at the same time seeing numerous minor improvements and major additions. The latter include: a new chapter on singular values and singular vectors, including ways to analyze a matrix of data; a revised chapter on computing in linear algebra, with professional-level algorithms and code that can be downloaded for a variety of languages; a new section on linear algebra and cryptography; and a new chapter on linear algebra in probability and statistics. A dedicated and active website also offers solutions to exercises as well as new exercises from many different sources (e.g. practice problems, exams, development of textbook examples), plus codes in MATLAB, Julia, and Python.

The gas and dust between the stars emit across the electromagnetic spectrum and are found in a range of physical conditions from diffuse plasmas to cold, dense molecules. Through their study we see how quantum processes shape the structure of our Galaxy and fluid mechanics sets the stellar mass scale. The Interstellar Medium is a very broad subject with layers of complexity, a long history and a steady flow of new results. This comprehensive yet accessible textbook provides a self-contained one-semester course for advanced undergraduate or beginning graduate students. It is written in a style that students can follow by themselves and allows instructors to use class time to go deeper into the details or show applications to current research. It makes extensive use of publicly accessible data to illustrate specific points and to encourage students to learn by performing their own analyses.

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.

This third edition provides a concise yet approachable introduction to seismic theory, designed as a first course for graduate students or advanced undergraduate students. It clearly explains the fundamental concepts, emphasizing intuitive understanding over lengthy derivations, and outlines the different types of seismic waves and how they can be used to resolve Earth structure and understand earthquakes. New material and updates have been added throughout, including ambient noise methods, shear-wave splitting, back-projection, migration and velocity analysis in reflection seismology, earthquake rupture directivity, and fault weakening mechanisms. A wealth of both reworked and new examples, review questions and computer-based exercises in MATLAB®/Python give students the opportunity to apply the techniques they have learned to compute results of interest and to illustrate Earth's seismic properties. More advanced sections, which are not needed to understand the other material, are fla

This third edition provides a concise yet approachable introduction to seismic theory, designed as a first course for graduate students or advanced undergraduate students. It clearly explains the fundamental concepts, emphasizing intuitive understanding over lengthy derivations, and outlines the different types of seismic waves and how they can be used to resolve Earth structure and understand earthquakes. New material and updates have been added throughout, including ambient noise methods, shear-wave splitting, back-projection, migration and velocity analysis in reflection seismology, earthquake rupture directivity, and fault weakening mechanisms. A wealth of both reworked and new examples, review questions and computer-based exercises in MATLAB®/Python give students the opportunity to apply the techniques they have learned to compute results of interest and to illustrate Earth's seismic properties. More advanced sections, which are not needed to understand the other material, are fla

Designed for both one- and two-semester courses, this textbook provides a succinct and easy-to-read introduction to crystal structures and structure-property relations. By linking together the fundamentals of bond strength and the arrangement of atoms in space with the mechanical, optical, magnetic and electrical properties that they control, students will gain an intuitive understanding of how different materials are suited to particular applications. The systematics of crystal structures are described for both organic and inorganic materials, with coverage including small molecular crystals, polymers, metals, ceramics and semiconductors. Hundreds of figures and practice problems help students gain an advanced, 3D understanding of how structure governs behavior, and a wealth of examples throughout show how the underlying theory is translated into practical devices. With solutions, video lectures and overheads available online for instructors, this is an excellent resource for graduate