Python for MATLAB Development: Extend MATLAB with 300,000+ Modules from the Python Package Index
Autor Albert Danialen Limba Engleză Paperback – 12 mar 2022
Python for MATLAB Development shows you how to enhance MATLAB with Python solutions to a vast array of computational problems in science, engineering, optimization, statistics, finance, and simulation. It is three books in one:
- A thorough Python tutorial that leverages your existing MATLAB knowledge with a comprehensive collection of MATLAB/Python equivalent expressions
- A reference guide to setting up and managing a Python environment that integrates cleanly with MATLAB
- A collection of recipes that demonstrate Python solutions invoked directly from MATLAB
- Run faster with numba
- Distribute work to a compute cluster with dask
- Find symbolic solutions to integrals, derivatives, and series summations with SymPy
- Overlay data on maps with Cartopy
- Solve mixed-integer linear programming problems with PuLP
- Interact with Redis via pyredis, PostgreSQL via psycopg2, and MongoDB via pymongo
- Read and write file formats that are not natively understood by MATLAB, such as SQLite, YAML, and ini
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Specificații
ISBN-13: 9781484272220
ISBN-10: 1484272226
Pagini: 700
Ilustrații: XXVIII, 700 p. 76 illus., 71 illus. in color.
Dimensiuni: 178 x 254 mm
Greutate: 1.24 kg
Ediția:1st ed.
Editura: Apress
Colecția Apress
Locul publicării:Berkeley, CA, United States
ISBN-10: 1484272226
Pagini: 700
Ilustrații: XXVIII, 700 p. 76 illus., 71 illus. in color.
Dimensiuni: 178 x 254 mm
Greutate: 1.24 kg
Ediția:1st ed.
Editura: Apress
Colecția Apress
Locul publicării:Berkeley, CA, United States
Cuprins
1 Introduction.- 2 Installation.- 3 Language Basics.- 4 Data Containers.- 5 Dates and Times.- 6 Call Python Functions from MATLAB.- 7 Input and Output.- 8 Interacting with the File System.- 9 Interacting with the Operating System and External Executables.- 10 Object Oriented Programming.- 11 NumPy and SciPy.- 12 Plotting.- 13 Tables and Dataframes.- 14 High Performance Computing.- 15 Language Pitfalls.- Appendix A MATLAB/Python Recipe Index.- Appendix B Generating Sample Data with Faker.- Appendix C Finite Element Source Listing.- Appendix D Python-to-MATLAB and MATLAB-to-Python Variable Converters.- Appendix E A Utility to Patch Cartopy to Use Requests.
Notă biografică
Albert Danial is an aerospace engineer with 30 years of experience, currently working for Northrop Grumman near Los Angeles. Before Northrop Grumman, he was a member of the NASTRAN Numerical Methods team at MSC Software and a systems analyst at SPARTA. He has a Bachelor of Aerospace Engineering degree from the Georgia Institute of Technology, and Masters and Ph.D. degrees in Aeronautics and Astronautics from Purdue University. He is the author of cloc, the open source code counter.
Al has used MATLAB since 1990 and Python since 2006 for algorithm prototyping, earth science data processing, spacecraft mission planning, optimization, visualization, and countless utilities that simplify daily engineering work.
Textul de pe ultima copertă
MATLAB can run Python code!
Python for MATLAB Development shows you how to enhance MATLAB with Python solutions to a vast array of computational problems in science, engineering, artificial intelligence, statistics, finance, and simulation. It is three books in one:
You will:
Python for MATLAB Development shows you how to enhance MATLAB with Python solutions to a vast array of computational problems in science, engineering, artificial intelligence, statistics, finance, and simulation. It is three books in one:
- A thorough Python tutorial that leverages your existing MATLAB knowledge with a comprehensive collection of MATLAB/Python equivalent expressions
- A reference guide to setting up and managing a Python environment that integrates cleanly with MATLAB
- A collection of recipes that demonstrate Python solutions invoked directly from MATLAB
You will:
- Find symbolic solutions to integrals, derivatives, and series summations with SymPy
- Overlay data on maps with Cartopy
- Solve mixed-integer linear programming problems with PuLP
- Accelerate computationally-intensive tasks with numba
- Run large computations in parallel with dask
- Interact with Redis via pyredis, PostgreSQL via psycopg2, and MongoDB via pymongo
- Read and write file formats that are not natively understood by MATLAB, such as SQLite, YAML, and ini
Caracteristici
Teaches how to expand MATLAB's power using Python Learn Python rapidly with side-by-side MATLAB code examples Only guide that provides practical examples of calling Python code from MATLAB