Scientific Programmers Toolkit

The Scientific Programmer's Toolkit: Turbo Pascal Edition presents a complete software environment for anyone writing programs in mathematical, engineering, or science areas. This toolkit package is designed for use with Turbo Pascal, the de facto standard Pascal system for PC and compatible machines. The book and its software provides an integrated software library of programming tools. The programs and routines fall into three categories: graphical, mathematical, and utilities. Routines are further subdivided into three levels that reflect the experience of the user. For graphics and text handling routines there is also a Level 0, which provides an interface to the machine operating system. By using hierarchically structured routines, the clearly written text, and a wide range of example programs, software users can construct a user-friendly interface with minimal effort. The levels structure makes it easy for newcomers to use the Toolkit, and with growing experience, users can achieve more elaborate effects. The Scientific Programmer's Toolkit will be useful to consultants, researchers, and students in any quantitative profession or science, in private or public sector research establishments, or in secondary and higher education.

Collection of mathematical and graphical routines together with utility and user-interface routines along with a framework for writing programs in mathematical, engineering or science areas.

This open access book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, making it suitable for students and researchers with little or no prior experience in programming. The book uses relevant examples from mathematics and the natural sciences to present programming as a practical toolbox that can quickly enable readers to write their own programs for data processing and mathematical modeling. These tools include file reading, plotting, simple text analysis, and using NumPy for numerical computations, which are fundamental building blocks of all programs in data science and computational science. At the same time, readers are introduced to the fundamental concepts of programming, including variables, functions, loops, classes, and object-oriented programming. Accordingly, the book provides a sound basis for further computer science and programming studies.

The Globus Toolkit is a key technology in Grid Computing, the exciting new computing paradigm that allows users to share processing power, data, storage, and other computing resources across institutional and geographic boundaries. Globus Toolkit 4: Programming Java Services provides an introduction to the latest version of this widely acclaimed toolkit. Based on the popular web-based The Globus Toolkit 4 Programmer's Tutorial, this book far surpasses that document, providing greater detail, quick reference appendices, and many additional examples. If you’re making the leap into Grid Computing using the Globus Toolkit, you’ll want Globus Toolkit 4: Programming Java Services at your side as you take your first steps. Written for newcomers to Globus Toolkit, but filled with useful information for experienced users. Clearly situates Globus application development within the context of Web Services and evolving Grid standards. Provides detailed coverage of Web Services programming with the Globus Toolkit's Java WS Core component. Covers basic aspects of developing secure services using the Grid Security Infrastructure (GSI). Uses simple, didactic examples throughout the book, but also includes a more elaborate example, the FileBuy application, that showcases common design patterns found in Globus applications. Concludes with useful reference appendices.

The book provides an introduction to common programming tools and methods in numerical mathematics and scientific computing. Unlike widely used standard approaches, it does not focus on any particular language but aims to explain the key underlying concepts. In general, new concepts are first introduced in the particularly user-friendly Python language and then transferred and expanded in various scientific programming environments from C / C ++, Julia and MATLAB to Maple. This includes different approaches to distributed computing. The fact that different languages are studied and compared also makes the book useful for mathematicians and practitioners trying to decide which programming language to use for which purposes.

The book teaches students to model a scientific problem and write a computer program in C language to solve that problem. It introduces the basics of C language, and then describes and discusses algorithms commonly used in scientific applications (e.g. searching, graphs, statistics, equation solving, Monte Carlo methods etc.).