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In today's information age, scientists and engineers must quickly and efficiently analyze extremely large sets of data. One of the best tools to accomplish this is Interactive Data Language (IDL®), a programming and visualization environment that facilitates numerical modeling, data analysis, and image processing. IDL's high-level language and powerful graphics capabilities allow users to write more flexible programs much faster than is possible with other programming languages. An Introduction to Programming with IDL enables students new to programming, as well as those with experience in other programming languages, to rapidly harness IDL's capabilities: fast, interactive performance; array syntax; dynamic data typing; and built-in graphics. Each concept is illustrated with sample code, including many complete short programs. - Margin notes throughout the text quickly point readers to the relevant sections of IDL manuals - End-of-chapter summaries and exercises help reinforce learning - Students who purchase the book are eligible for a substantial discount on a student version of the IDL software
1 : Introduction -- 2 : Fundamentals of IDL Syntax -- 3 : Writing IDL Programs -- 4 : Input and Output -- 5 : Direct Graphics -- 6 : Plotting Data -- 7 : Displaying Images -- 8 : Creating Graphical Output -- 9 : Graphical User Interfaces (GUIs) -- Appendix A : IDL on the Internet -- Appendix B : Mathematical Routines -- Appendix C : Widget Event Structures -- Appendix D : Widget Properties -- Appendix E : Graphics Device Properties.
Modern IDL is an opinionated guide to using IDL, including information about recent versions of IDL, advanced topics, and best practices. Modern IDL is also a useful reference guide for both beginners and advanced users, collecting tables and lists of items that are scattered through the online help.
"Java Programming with CORBA" - jetzt erscheint der Bestseller in der 3. aktualisierten und erweiterten Auflage. Anerkannte Experten zeigen anhand fortgeschrittener Techniken und Beispielen aus der Praxis, wie man einfache und komplexe Javaprogramme mit CORBA entwirft. Zunächst geben sie einen kurzen Überblick über CORBA, Java, Oject Request Brokers (ORBs) und EJB Komponenten und erläutern dann, wie man diese Technologien einsetzt, um komplette Java-Anwendungen zu entwickeln. Diese Neuauflage wurde um 50% neues Material erweitert, um den Neuerungen der kürzlich erschienenen 3. Version von CORBA Rechnung zu tragen. Topaktuelle Themen, wie z.B. Portabel Object Adaptor (POA), Remote Method Innovation (RMI) over IIOP und EJB werden ausführlich diskutiert. Mit einer Fülle detaillierter Codebeispiele. Der unverzichtbare Leitfaden für jeden Java-Entwickler und -Programmierer.
Here is the CORBA book that every C++ software engineer has been waiting for. Advanced CORBA® Programming with C++ provides designers and developers with the tools required to understand CORBA technology at the architectural, design, and source code levels. This book offers hands-on explanations for building efficient applications, as well as lucid examples that provide practical advice on avoiding costly mistakes. With this book as a guide, programmers will find the support they need to successfully undertake industrial-strength CORBA development projects. The content is systematically arranged and presented so the book may be used as both a tutorial and a reference. The rich example programs in this definitive text show CORBA developers how to write clearer code that is more maintainable, portable, and efficient. The authors' detailed coverage of the IDL-to-C++ mapping moves beyond the mechanics of the APIs to discuss topics such as potential pitfalls and efficiency. An in-depth presentation of the new Portable Object Adapter (POA) explains how to take advantage of its numerous features to create scalable and high-performance servers. In addition, detailed discussion of advanced topics, such as garbage collection and multithreading, provides developers with the knowledge they need to write commercial applications. Other highlights In-depth coverage of IDL, including common idioms and design trade-offs Complete and detailed explanations of the Life Cycle, Naming, Trading, and Event Services Discussion of IIOP and implementation repositories Insight into the dynamic aspects of CORBA, such as dynamic typing and the new DynAny interfaces Advice on selecting appropriate application architectures and designs Detailed, portable, and vendor-independent source code
Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL and Python, Third Edition introduces techniques used in the processing of remote sensing digital imagery. It emphasizes the development and implementation of statistically motivated, data-driven techniques. The author achieves this by tightly interweaving theory, algorithms, and computer codes. See What’s New in the Third Edition: Inclusion of extensive code in Python, with a cloud computing example New material on synthetic aperture radar (SAR) data analysis New illustrations in all chapters Extended theoretical development The material is self-contained and illustrated with many programming examples in IDL. The illustrations and applications in the text can be plugged in to the ENVI system in a completely transparent fashion and used immediately both for study and for processing of real imagery. The inclusion of Python-coded versions of the main image analysis algorithms discussed make it accessible to students and teachers without expensive ENVI/IDL licenses. Furthermore, Python platforms can take advantage of new cloud services that essentially provide unlimited computational power. The book covers both multispectral and polarimetric radar image analysis techniques in a way that makes both the differences and parallels clear and emphasizes the importance of choosing appropriate statistical methods. Each chapter concludes with exercises, some of which are small programming projects, intended to illustrate or justify the foregoing development, making this self-contained text ideal for self-study or classroom use.
Groovy Programming is an introduction to the Java-based scripting language Groovy. Groovy has much in common with popular scripting languages such as Perl, Python, and Ruby, but is written in a Java-like syntax. And, unlike these other languages, Groovy is sanctioned by the Java community for use on the Java platform. Since it is based on Java, applications written in Groovy can make full use of the Java Application Programmer Interfaces (APIs). This means Groovy can integrate seamlessly with applications written in Java, while avoiding the complexities of the full Java language. This bare-bones structure also means Groovy can be used as an introduction to Java and to programming in general. Its simpler constructions and modern origins make it ideal as a first language and for introducing principles such as object-oriented programming.This book introduces all the major aspects of Groovy development and emphasizes Groovy's potential as a learning tool. Case studies and exercises are included, along with numerous programming examples. The book begins assuming only a general familiarity with Java programming, and progresses to discuss advanced topics such as GUI builders, Groovlets, Unit Testing, and Groovy SQL. - The first comprehensive book on Groovy programming that shows how writing applications and scripts for the Java platform is fast and easy - Written by leading software engineers and acclaimed computing instructors - Offers numerous programming examples, code samples, detailed case studies, exercises for self-study, and a companion website with a Windows-based Groovy editor
Designed for undergraduates, An Introduction to High-Performance Scientific Computing assumes a basic knowledge of numerical computation and proficiency in Fortran or C programming and can be used in any science, computer science, applied mathematics, or engineering department or by practicing scientists and engineers, especially those associated with one of the national laboratories or supercomputer centers. This text evolved from a new curriculum in scientific computing that was developed to teach undergraduate science and engineering majors how to use high-performance computing systems (supercomputers) in scientific and engineering applications. Designed for undergraduates, An Introduction to High-Performance Scientific Computing assumes a basic knowledge of numerical computation and proficiency in Fortran or C programming and can be used in any science, computer science, applied mathematics, or engineering department or by practicing scientists and engineers, especially those associated with one of the national laboratories or supercomputer centers. The authors begin with a survey of scientific computing and then provide a review of background (numerical analysis, IEEE arithmetic, Unix, Fortran) and tools (elements of MATLAB, IDL, AVS). Next, full coverage is given to scientific visualization and to the architectures (scientific workstations and vector and parallel supercomputers) and performance evaluation needed to solve large-scale problems. The concluding section on applications includes three problems (molecular dynamics, advection, and computerized tomography) that illustrate the challenge of solving problems on a variety of computer architectures as well as the suitability of a particular architecture to solving a particular problem. Finally, since this can only be a hands-on course with extensive programming and experimentation with a variety of architectures and programming paradigms, the authors have provided a laboratory manual and supporting software via anonymous ftp. Scientific and Engineering Computation series
Despite using them every day, most software engineers know little about how programming languages are designed and implemented. For many, their only experience with that corner of computer science was a terrifying "compilers" class that they suffered through in undergrad and tried to blot from their memory as soon as they had scribbled their last NFA to DFA conversion on the final exam. That fearsome reputation belies a field that is rich with useful techniques and not so difficult as some of its practitioners might have you believe. A better understanding of how programming languages are built will make you a stronger software engineer and teach you concepts and data structures you'll use the rest of your coding days. You might even have fun. This book teaches you everything you need to know to implement a full-featured, efficient scripting language. You'll learn both high-level concepts around parsing and semantics and gritty details like bytecode representation and garbage collection. Your brain will light up with new ideas, and your hands will get dirty and calloused. Starting from main(), you will build a language that features rich syntax, dynamic typing, garbage collection, lexical scope, first-class functions, closures, classes, and inheritance. All packed into a few thousand lines of clean, fast code that you thoroughly understand because you wrote each one yourself.