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, 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 This book shows how to call Python functions to enhance MATLAB's capabilities. Specifically, you'll see how Python helps 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 Who This Book Is For MATLAB developers who are new to Python and other developers with some prior experience with MATLAB, R, IDL, or Mathematica.
Chapter 1: Introduction
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, 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 This book shows how to call Python functions to enhance MATLAB's capabilities. Specifically, you'll see how Python helps 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 Who This Book Is For MATLAB developers who are new to Python and other developers with some prior experience with MATLAB, R, IDL, or Mathematica.
Chapter 1: Introduction
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.
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.
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