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Python for scientists[electronic res...

Stewart, John M., (1943 July 1-)

Python for scientists[electronic resource] /

レコード種別:	コンピュータ・メディア : 単行資料
[NT 15000414] null:	005.133
タイトル / 著者:	Python for scientists/ John M. Stewart.
著者:	Stewart, John M.,
出版された:	Cambridge : : Cambridge University Press,, 2014.
記述:	xii, 220 p. : : ill., digital ;; 24 cm.
主題:	Science - Data processing.
主題:	Python (Computer program language)
国際標準図書番号 (ISBN) :	9781107447875
国際標準図書番号 (ISBN) :	9781107061392
国際標準図書番号 (ISBN) :	9781107686427
[NT 15000228] null:	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.
[NT 15000229] null:	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.
電子資源:	https://doi.org/10.1017/CBO9781107447875

Python for scientists[electronic resource] /
Stewart, John M.,1943 July 1-

Python for scientists[electronic resource] /John M. Stewart. - Cambridge :Cambridge University Press,2014. - xii, 220 p. :ill., digital ;24 cm.

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.

ISBN: 9781107447875Subjects--Topical Terms:

466953
Science
--Data processing.

LC Class. No.: Q183.9 / .S865 2014

Dewey Class. No.: 005.133

Python for scientists[electronic resource] /
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245 1 0 $a Python for scientists $h [electronic resource] / $c John M. Stewart.
260 $a Cambridge : $b Cambridge University Press, $c 2014.
300 $a xii, 220 p. : $b ill., digital ; $c 24 cm.
505 8 $a 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.
520 $a 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.
650 0 $a Science $x Data processing. $3 466953
650 0 $a Python (Computer program language) $3 339754
856 4 0 $u https://doi.org/10.1017/CBO9781107447875

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