Python for scientists
By: Stewart, John M.Material type: BookPublisher: New Delhi : Cambridge University Press, ©2014Description: xii, 220 p. : ill, ; 25 cm.ISBN: 9781107529199.Subject(s): Science -- Data processing | Python (Computer program language) | COMPUTERS / General
|Item type||Current location||Collection||Call number||Status||Notes||Date due||Barcode||Item holds|
|Books||IIITD Reference||Computer Science and Engineering||005.133 STE-P (Browse shelf)||Not for loan||DBT Project Grant||007661|
Browsing IIITD Shelves , Shelving location: Reference , Collection code: Computer Science and Engineering Close shelf browser
|004.68 WU-W Wireless ad hoc networking :||005.10 TSU-M Managing software projects||005.133 KAN-E Exploring C||005.133 STE-P Python for scientists||005.265 IRV-A Assembly language for x86 processors||005.453 WOL-H High performance compilers for parallel computing||006.3 VAP-S Statistical learning theory|
Includes bibliographical references (pages 216-217) and index.
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.
"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"--