Python for scientists

By:

Stewart, John M

Material type: Text

9781107529199

Subject(s):

DDC classification:

005.133 23 STE-P

LOC classification:

Q183.9 .S865 2014

Contents:

Machine generated contents note: Preface; 1. Introduction; 2. Getting started with IPython; 3. A short Python tutorial; 4. Numpy; 5. Two-dimensional graphics; 6. Three-dimensional graphics; 7. Ordinary differential equations; 8. Partial differential equations: a pseudospectral approach; 9. Case study: multigrid; 10. Appendix A. Installing a Python environment; Appendix B. Fortran77 subroutines for pseudospectral methods; References; Index.

Summary: "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 scientist needs to know to start using Python effectively. The author explains scientific Python from scratch, showing how easy it is to implement and test non-trivial mathematical algorithms and guiding the reader through the many freely available add-on modules. A range of examples, relevant to many different fields, illustrate the program's capabilities. In particular, readers are shown how to use pre-existing legacy code (usually in Fortran77) within the Python environment, thus avoiding the need to master the original code. Instead of exercises the book contains useful snippets of tested code which the reader can adapt to handle problems in their own field, allowing students and researchers with little computer expertise to get up and running as soon as possible"--

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Holdings
Item type	Current library	Collection	Call number	Status	Notes	Date due	Barcode	Item holds
Books	IIITD Reference	Computer Science and Engineering	005.133 STE-P (Browse shelf(Opens below))	Available	DBT Project Grant		007661

Total holds: 0

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Previous	005.10 TSU-M Managing software projects	005.133 GUT-I Introduction to computation and programming using python :	005.133 KAN-E Exploring C	005.133 STE-P Python for scientists	005.265 IRV-A Assembly language for x86 processors	005.453 AHO-C Compilers : principles, techniques, and tools	005.453 WOL-H High performance compilers for parallel computing	Next

Includes bibliographical references (pages 216-217) and index.

"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 scientist needs to know to start using Python effectively. The author explains scientific Python from scratch, showing how easy it is to implement and test non-trivial mathematical algorithms and guiding the reader through the many freely available add-on modules. A range of examples, relevant to many different fields, illustrate the program's capabilities. In particular, readers are shown how to use pre-existing legacy code (usually in Fortran77) within the Python environment, thus avoiding the need to master the original code. Instead of exercises the book contains useful snippets of tested code which the reader can adapt to handle problems in their own field, allowing students and researchers with little computer expertise to get up and running as soon as possible"--

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