https://github.com/cmadan/awesome-matlab
A curated list of awesome MATLAB toolboxes, applications, software and resources.
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A curated list of awesome MATLAB toolboxes, applications, software and resources.
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# Awesome MATLAB [](https://github.com/sindresorhus/awesome)
A curated list of awesome MATLAB toolboxes, applications, software and resources.
Inspired by [awesome-R](https://github.com/qinwf/awesome-R).
- [Awesome MATLAB](#awesome-)
- [3rd Party Commercial Toolboxes](#3rd-party-commercial-toolboxes)
- [Cool](#cool)
- [Database Management](#database-management)
- [Games](#games)
- [Hardware](#hardware)
- [Image Processing and Computer Vision](#image-processing-and-computer-vision)
- [Model Reduction](#model-reduction)
- [Computational Mechanics](#computational-mechanics)
- [Interfacing with other languages](#interfacing-with-other-languages)
- [Interfacing with other programs](#interfacing-with-other-programs)
- [Learning MATLAB](#learning-matlab)
- [Making Figures](#making-figures)
- [MATLAB-like environments](#matlab-like-environments)
- [Miscellaneous Free Toolboxes](#miscellaneous-free-toolboxes)
- [Resources](#resources)
- [Websites](#websites)
- [Blogs](#blogs)
- [Books](#books)
- [Reference Cards](#reference-cards)
- [Social Media](#social-media)
- [MOOCs](#moocs)
- [Tips and Tricks](#tips-and-tricks)
- [Contributing](#contributing)
## 3rd Party Commercial Toolboxes
*High quality commercial toolboxes from organisations other than The MathWorks*
* [Multiprecision Toolbox for MATLAB](http://www.advanpix.com/) - This toolbox equips MATLAB with a new multiple precision floating-point numeric type and an extensive set of mathematical functions that are capable of computations with arbitrary precision.
* [NAG Toolbox for MATLAB](http://www.nag.co.uk/numeric/MB/start.asp) - Over 1700 functions across numerous areas of numerical mathematics. Developed by The Numerical Algorithms Group (NAG).
* [MOSEK Optimization Tools](https://www.mosek.com) - The [MOSEK tools](https://mosek.com/resources/downloads) provide access to the powerful MOSEK optimization solvers from inside the MATLAB environment either by a classical [Toolobx](http://docs.mosek.com/7.1/tools/index.html) or by the modern object-oriented API [Fusion](http://docs.mosek.com/7.1/matlabfusion/index.html) .
* [FEATool Multiphysics](http://www.precisesimulation.com) - Finite Element FEM Simulation toolbox for Matlab and Octave featuring an easy to use GUI, integrated CAD, geometry, grid generation, solvers, and postprocessing functionality.
## Cool
*Fun projects that make you say 'Cool!'*
- [Engima](http://blogs.mathworks.com/pick/2015/10/30/enigma/) - MATLAB version of the Enigma machine
## Database Management
*Toolboxes for managing data*
* [Database toolbox](http://uk.mathworks.com/products/database/) - Official database toolbox from The MathWorks.
* [go-redis](https://github.com/markuman/go-redis/) - Free Redis Mex client for MATLAB.
* [mex-sqlite3](https://github.com/rmartinjak/mex-sqlite3) - Free Sqlite3 Mex client for MATLAB.
* [dotenv for MATLAB](https://github.com/mathworks/dotenv-for-MATLAB) - Manage database configuration environment variables
## Games
*Fully playable games developed in MATLAB.*
* [2048](http://uk.mathworks.com/matlabcentral/fileexchange/46124-2048-matlab-edition) - 2048 is a game originally created by Gabriele Cirulli. This is a MATLAB implementation of the game.
* [Flappy bird](http://uk.mathworks.com/matlabcentral/fileexchange/45795-flappy-bird-for-matlab) - As one of the most popular games on app stores before being taken down, Flappy Bird does not need any further introduction. Now, it has come back alive, on MATLAB.
## Hardware
* [MATLAB Mobile](http://uk.mathworks.com/products/matlab-mobile/) - MATLAB on Android and iOS mobile phones and tablets.
* [Octave](https://play.google.com/store/apps/details?id=com.octave) - Octave on Android.
* [Raspberry Pi Support from MATLAB](http://uk.mathworks.com/hardware-support/raspberry-pi-matlab.html) - Acquire sensor and image data from your connected Raspberry Pi.
* [Rasperry Pi IO Support for Octave](http://github.com/octave-de/octave-rpi-gpio) - Control Rasperry Pi GPIO Port from Octave.
* [CPU Info](https://de.mathworks.com/matlabcentral/fileexchange/33155-cpu-info) - Read various bits of information about the CPU and operating system.
## Image Processing and Computer Vision
* [Computer Vision System Toolbox](http://uk.mathworks.com/products/computer-vision/) - The official computer vision toolbox from The MathWorks.
* [Image Processing Toolbox](http://uk.mathworks.com/products/image/) - The official Image Processing Toolbox from The MathWorks.
* [MatConvNet](http://www.vlfeat.org/matconvnet/) - MatConvNet is a free MATLAB toolbox implementing Convolutional Neural Networks (CNNs) for computer vision applications. It is simple, efficient, and can run and learn state-of-the-art CNNs. It provides pre-trained CNNs for image classification, segmentation, face recognition, and text detection.
* [Piotr's Image and Video Toolbox](https://github.com/pdollar/toolbox) - This free toolbox facilitates the manipulation of images and video in MATLAB. Its purpose is to complement, not replace, MATLAB's Image Processing Toolbox.
* [VLFeat](http://www.vlfeat.org/) - The VLFeat free and open source library implements popular computer vision algorithms specializing in image understanding and local features extraction and matching. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout.
* [MexOpenCV](https://github.com/kyamagu/mexopencv) - MATLAB MEX interface for [OpenCV](http://opencv.org), i.e. one of the leading libraries for computer vision.
* [Zoning Aggregated Hypercolumns for Keyword Spotting](https://github.com/sfikas/zah) - An image descriptor, suitable for keyword spotting, that is computed as a function of Convolutional Neural Network intermediate layer responses.
## Model Reduction
* [SLICOT](http://slicot.org/matlab-toolboxes/model-reduction) - SLICOT Model and Controller Reduction Toolbox.
* [emgr](http://gramian.de) - EMpirical GRamian framework for model reduction of input-output systems.
* [MORE](http://w3.onera.fr/more/) - a MOdel REduction Toolbox.
* [drtoolbox](https://lvdmaaten.github.io/drtoolbox/) - Matlab Toolbox for Dimensionality Reduction.
* [SiMpLIfy](http://simplifytoolbox.tumblr.com/) - Structured ModeL reductIon.
* [MORLAB](http://www.mpi-magdeburg.mpg.de/1657682/morlab) - Model Order Reduction Laboratory.
* [MORPACK](http://tu-dresden.de/die_tu_dresden/fakultaeten/fakultaet_maschinenwesen/ifkm/dmt/forschung/forschungsthemen/morpack) - Model Order Reduction PACKage.
* [MatMOREMBS](http://www.itm.uni-stuttgart.de/research/model_reduction/MOREMBS_MatMorembs_en.php) - Matlab Model Order Reduction of Elastic Multibody Systems.
* [RBmatlab](https://www.ians.uni-stuttgart.de:8443/agh/gitblit/summary/software%2Fmatlab%2Frbmatlabrelease.git) - is a MATLAB library for model order reduction with Reduced Basis Methods for various discretization types and application settings.
* [MESS](http://www.mpi-magdeburg.mpg.de/projects/mess) - The Matrix Equations Sparse Solvers library, is the successor to the Lyapack Toolbox.
* [KerMor](http://www.ians.uni-stuttgart.de/MoRePaS/software/kermor/) - Model order reduction for nonlinear dynamical systems and nonlinear approximation.
* [SUMO](http://sumo.intec.ugent.be/SUMO) - SUrrogate MOdelling lab.
* [SMORES](https://web.archive.org/web/20151115030532/http://bnbond.com/software/smores/) - A Matlab tool for Simulation and Model Order Reduction of Electrical Systems.
* [MRedTool](https://web.archive.org/web/20080727002739/http://scowl.ge.uiuc.edu/~ssivakum/research.html) - a MATLAB toolbox for model reduction of multi-dimensional systems.
* [Nonlinear Model Reduction Routines for MATLAB](http://homepages.rpi.edu/~hahnj/Model_Reduction) - Empirical balanced truncation toolbox.
* [DMD Book](http://dmdbook.com/CODE.zip) - Dynamic Mode Decomposition Book Companion Code.
* [hapod](http://git.io/hapod) - Hierarchical Approximate Proper Orthogonal Decomposition.
## Computational Mechanics
* [GIBBON](https://www.gibboncode.org/) - An open-source ([get the source here](https://github.com/gibbonCode/GIBBON)) MATLAB toolbox for computational (bio)mechanics, computational geometry, image segmentation, meshing, lattice structure creation, and finite element analysis (by linking with the open source package [FEBio](https://febio.org/) and the commercial package ABAQUS).
## Interfacing with other languages
* [C/C++ mex routines](http://uk.mathworks.com/help/matlab/write-cc-mex-files.html) - C/C++ MEX files allow to call C/C++ functions from within MATLAB.
* [Fortran mex routines](http://uk.mathworks.com/help/matlab/write-fortran-mex-files.html) - Fortran MEX routines allow you to call Fortran code from within MATLAB.
* [MATLAB Engine for Python](http://uk.mathworks.com/help/matlab/matlab_external/get-started-with-matlab-engine-for-python.html) - The MATLAB Engine for Python provides a Python package named `matlab` that enables you to call MATLAB functions from within Python.
* [Python](http://uk.mathworks.com/help/matlab/call-python-libraries.html) - How to call Python functions from within MATLAB.
* [matlab kernel](https://github.com/calysto/matlab_kernel) - To run MATLAB code inside IPython / Jupyter notebooks.
* [octave kernel](https://github.com/calysto/octave_kernel) - To run Octave code inside IPython / Jupyter notebooks.
* [MATLink](http://matlink.org/) - To run MATLAB code inside Mathematica / Wolfram Language notebooks.
## Interfacing with other programs
* [MATLAB QuickLook](https://github.com/jaketmp/matlab-quicklook) - QuickLook preview generator for MAT files. This shows the contents of your MAT files in Finder. The binary is only compatible with 64 bit OS X.
* [MATLAB-git](https://github.com/manur/MATLAB-git) - A thin wrapper to call `git` from within a MATLAB console.
* [JSONlab](https://github.com/fangq/jsonlab) - Toolbox to encode/decode [JSON](http://www.json.org) data files from within MATLAB and Octave.
## Learning MATLAB
* [Software Carpentry lessons in MATLAB](http://swcarpentry.github.io/matlab-novice-inflammation/) - Teaching basic lab skills for research computing.
* [YAGTOM: Yet Another Guide TO MATLAB](http://ubcmatlabguide.github.io) - This MATLAB tutorial starts from the basics and builds up to advanced concepts such as object-oriented programming (Note the [Speedup Tricks](https://ubcmatlabguide.github.io/html/speedup.html)).
* [MATLAB Academy - MATLAB Onramp](https://matlabacademy.mathworks.com/) - Brief MATLAB introduction including language syntax and common workflows. Free for all.
* [Control Tutorials for MATLAB and Simulink](http://ctms.engin.umich.edu/CTMS/index.php?aux=Home) - This site contains quite a bit control theory, some practical applications and how to implement these in MATLAB and SimuLink.
* [Rosetta Code (MATLAB category)](http://rosettacode.org/wiki/Category:MATLAB) - Rosetta Code is a community comparing algorithms in different languages.
## Making Figures
*Third-party tools to produce publication quality figures.*
* [export_fig](https://github.com/altmany/export_fig) - produces better vector/bitmap graphics than standalone MATLAB.
* [matlab2tikz](https://github.com/matlab2tikz/matlab2tikz) - exports MATLAB figures to TikZ code for seamless inclusion in LaTeX documents.
* [plot2svg](http://www.mathworks.com/matlabcentral/fileexchange/7401-scalable-vector-graphics--svg--export-of-figures) - exports MATLAB figures to Scalable Vector Graphics format. This is particularly useful in older MATLAB versions that don't support `print -dsvg`.
* [Plotly MATLAB Library](https://plot.ly/matlab/) - exports MATLAB figures to the online plotting service [plot.ly](https://plot.ly).
* [saveFigure](https://github.com/djoshea/matlab-save-figure) - exports MATLAB figures to PDF, SVG, EPS and PNG with improved support for transparancy.
* [hq-matlab-figs](http://dgleich.github.io/hq-matlab-figs/) - Creating high-quality graphics in MATLAB for papers and presentations.
* [matplotlib colormaps](https://de.mathworks.com/matlabcentral/fileexchange/62729-matplotlib-2-0-colormaps--perceptually-uniform-and-beautiful) - Perceptually uniform colormaps.
* [antijet](https://git.io/antijet) - An alternative to the problematic "jet"-colormap.
* [xkcdify](https://www.mathworks.com/matlabcentral/fileexchange/38499-xkcdify) - xkcd-style plots.
* [wgPlot](https://mathworks.com/matlabcentral/fileexchange/24035-wgplot-weighted-graph-plot--a-better-version-of-gplot) - a better version of gplot
## MATLAB-like environments
* [GNU Octave](https://www.gnu.org/software/octave/) - GNU Octave is a high-level interpreted language, primarily intended for numerical computations. It can run many MATLAB programs unmodified.
* [Scilab](http://www.scilab.org/) - Scilab is free and open source software for numerical computation providing a powerful computing environment for engineering and scientific applications.
* [MathScript](http://www.ni.com/labview/mathscript/) - MathScript is an interpreter for MATLAB code for the [LabView](http://www.ni.com/labview/) programming language.
## Miscellaneous Free Toolboxes
*High quality free toolboxes in subject areas that don't yet have their own section*
* [Chebfun](http://www.chebfun.org/) - Chebfun is an open-source package for computing with functions to about 15-digit accuracy.
* [IFISS](http://www.maths.manchester.ac.uk/~djs/ifiss/) - IFISS is a graphical package for the interactive numerical study of incompressible flow problems which can be run under MATLAB or Octave.
* [Wavelab](http://statweb.stanford.edu/~wavelab/Wavelab_850/index_wavelab850.html) - WaveLab is a collection of MATLAB functions related to wavelet analysis.
* [MPITB](http://www.ugr.es/~jfernand/mpitb_eng.html) - MPI Toolbox for Matlab ([MPI Toolbox for Octave](http://www.ugr.es/~jfernand/mpitb.html)).
* [Lightspeed](http://research.microsoft.com/en-us/um/people/minka/software/lightspeed/) - Microsoft Lightspeed Utilities Toolbox.
* [bct](http://www.brain-connectivity-toolbox.net/) - Brain Connectivity Toolbox.
* [OpenCL Toolbox](https://github.com/imaginairy-user/opencl-toolbox/) - OpenCL support for MATLAB.
* [UQLab](http://www.uqlab.com/) - The Framework for Uncertainty Quantification.
* [Octave Forge](http://octave.sourceforge.net/) - Extra packages for GNU Octave.
* [Matrix Computation Toolbox](http://www.maths.manchester.ac.uk/~higham/mctoolbox/) - for constructing test matrices, computing matrix factorizations, visualizing matrices, and carrying out direct search optimization.
* [GRANSO](http://timmitchell.com/software/GRANSO/index.html) - GRadient-based Algorithm for Non-Smooth Optimization.
* [ROSTAPACK](http://www.timmitchell.com/software/ROSTAPACK/index.html) - RObust STAbility PACKage.
* [CAAM 551](http://www.caam.rice.edu/~caam551/MatlabCode/matlabcode.html) - Advanced Numerical Linear Algebra.
* [EliteQuant](https://github.com/EliteQuant/EliteQuant_Matlab) - Unified quantitative backtesting and live trading platform.
* [SMASH](https://github.com/SMASHtoolbox/release) - Sandia Matlab AnalysiS Hierarchy toolbox.
* [munum](https://bitbucket.org/kvasnica/munum) - MATLAB Library for universal numbers.
# Resources
Where to discover new MATLAB resources.
## Websites
* [MATLAB File Exchange](http://uk.mathworks.com/matlabcentral/fileexchange/) - File Exchange lets you find and share custom applications, classes, code examples, drivers, functions, Simulink models, scripts, and videos.
* [Cody](http://uk.mathworks.com/matlabcentral/cody/) - A website with programming challenges that consist of writing MATLAB code. A fun way to improve your skills.
* [ThingSpeak](https://thingspeak.com) - An internet of things (IoT) platform that allows to collect, analyze and act upon various data sources. You can enter your own MATLAB code to process and plot your data.
* [Octave-Online](http://octave-online.net/) - An online Octave interpreter.
* [Matlab FAQ on Wikia](http://matlab.wikia.com/wiki/FAQ)
* [MATLAB category on DMOZ](https://www.dmoz.org/Science/Math/Software/MATLAB)
* [Programming Community Curated Resources For Learning Matlab](https://hackr.io/tutorials/learn-matlab)
## Blogs
* [Cleve's Corner: Cleve Moler on Mathematics and Computing](http://blogs.mathworks.com/cleve/) - Cleve Moler is the author of the first MATLAB, one of the founders of The MathWorks, and is currently Chief Mathematician at the company.
* [Developer Zone](http://blogs.mathworks.com/developer/) - Developing, testing, and integrating production grade software using MATLAB.
* [Guy and Seth on Simulink](http://blogs.mathworks.com/seth/) - Guy Rouleau and Seth Popinchalk are Application Engineers for The MathWorks.
* [Loren on the art of MATLAB](http://blogs.mathworks.com/loren/) - Loren Shure works on design of the MATLAB language at The MathWorks.
* [Steve on Image Processing](http://blogs.mathworks.com/steve/) - Steve Eddins has developed MATLAB and image processing capabilities for The MathWorks since 1993.
* [Undocumented MATLAB](http://undocumentedmatlab.com) - Yair Altman blogs about the hidden underbelly of MATLAB. This is the place to be for discovering new and awesome features.
* [WalkingRandomly](http://www.walkingrandomly.com/?cat=11) - The MATLAB tag of WalkingRandomly.
* [xcorr: comp neuro](http://xcorr.net/?s=matlab) - MATLAB relevant post of XCORR.
* [Matlab Geeks](http://matlabgeeks.com/) - Matlab Blog, Tutorials and Expertise.
## Books
* [Accelerating MATLAB Performance: 1001 tips to speed up MATLAB programs](https://www.crcpress.com/Accelerating-MATLAB-Performance-1001-tips-to-speed-up-MATLAB-programs/Altman/9781482211290) - A superb guide to making MATLAB code faster.
* [The Elements of MATLAB Style](http://www.cambridge.org/us/academic/subjects/computer-science/scientific-computing-scientific-software/elements-matlab-style) - Coding guidelines for the MATLAB language.
* [MATLAB for Dummies](http://eu.wiley.com/WileyCDA/WileyTitle/productCd-111882010X.html) - A good beginners book.
* [MATLAB Guide](http://www.ma.man.ac.uk/~higham/mg/) - by Desmond and Nicholas Higham. One of the best books for learning MATLAB
* [Undocumented Secrets of MATLAB-Java Programming](https://www.crcpress.com/Undocumented-Secrets-of-MATLAB-Java-Programming/Altman/9781439869031#isbn) - A great guide on MATLAB and its Java interface (e.g. for GUIs or interaction with JVM software).
* [Data-Driven Science and Engineering: Machine Learning, Dynamical Systems and Control](http://www.databookuw.com/) - This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science
## Reference Cards
* [MATLAB Quick Reference](http://www.robots.ox.ac.uk/~dwm/Courses/1P5_2011/MatlabQuickRef1v1.pdf) - by Eric Peasley, Department of Engineering Science, University of Oxford
* [MATLAB Quick Reference App](https://play.google.com/store/apps/details?id=leo.anag.mathlab.help.DesktopToolsAndDevelopmentEnvironment) - for Android.
## Social Media
* [MATLAB Reddit](https://www.reddit.com/r/matlab/)
* [Octave Reddit](https://www.reddit.com/r/octave/)
* [MATLAB on Facebook](https://www.facebook.com/MATLAB) - Official Facebook page for MATLAB
* [MATLAB on Stack Overflow](http://stackoverflow.com/questions/tagged/matlab) - Stack Overflow is a community of 4.7 million programmers, just like you, helping each other.
* [Octave on Stack Overflow](http://stackoverflow.com/questions/tagged/octave) - and Stack Overflow has an extensive back catalogue of many answered questions.
* [MATLAB on Twitter](https://twitter.com/MATLAB) - Official MATLAB twitter account
* [Matlab Tricks Club](https://www.facebook.com/MatlabTricksClub/) - A Community Page about MATLAB
## MOOCs
*Massive open online courses.*
* [Linear Algebra: Foundations to Frontiers](http://www.ulaff.net/index.html) - Hands-on introduction to Linear Algebra using MATLAB.
## Tips and Tricks
* [Advanced Programming Techniques in MATLAB](https://www.mathworks.com/content/dam/mathworks/mathworks-dot-com/campaigns/portals/files/intel/may-12-2015-advanced-matlab.pdf) - Slides by Loren Shure.
* [Guidelines for writing clean and fast code in MATLAB](http://www.mathworks.com/matlabcentral/fileexchange/22943-guidelines-for-writing-clean-and-fast-code-in-matlab) - A guide with best practices in MATLAB programming to which anybody can [contribute](https://github.com/nschloe/matlab-guidelines).
* [Writing Fast MATLAB Code](http://www.csc.kth.se/utbildning/kth/kurser/DN2255/ndiff13/matopt.pdf)
* [MATLAB Array Manipulation Tips and Tricks](http://cseweb.ucsd.edu/~datorres/docs/MatlabTip.pdf)
* [MATLAB Vectorization Tricks](http://www-h.eng.cam.ac.uk/help/tpl/programs/Matlab/tricks.html)
* [Matlab / Octave Efficiency Notes](http://homepages.inf.ed.ac.uk/imurray2/compnotes/matlab_octave_efficiency.html)
* [Matlab Tips and Tricks](http://www.ee.columbia.edu/~marios/matlab/matlab_tricks.html)
* [MATLAB Style Guide 1](http://note.sonots.com/Matlab/MatlabCodingStyle.html)
* [MATLAB Style Guide 2](http://sites.google.com/site/matlabstyleguidelines/)
* [Octave and MATLAB Snippets](https://git.io/mtips) - Collection of code snippets.
* [knkutils](https://github.com/kendrickkay/knkutils) - MATLAB utility functions written by Kendrick Kay.
* [Alex's MATLAB Library](https://github.com/alexschlegel/matlab_lib)
* [Advanced Numerical Linear Algebra](http://www.caam.rice.edu/~caam551/MatlabCode/matlabcode.html) - MATLAB Code
* [Lanczos Algorithm for SVD](http://bickson.blogspot.de/2011/10/lanczos-algorithm-for-svd-singule-value.html) - MATLAB Code
* [Jie Chen's Software](https://jie-chen-ibm.appspot.com/software.html) - Collection of companion codes (mostly MATLAB).
* [SSP RK](http://sspsite.org/matlab_scripts.html) - Strong Stability Preserving Runge-Kutta Codes.
* [BV78](http://faculty.smu.edu/shampine/current.html) - Shampine's Adaptive Block Vectorized Runge-Kutta 7-8.
* [MATLAB Style Guidelines 2.0](http://www.datatool.com/downloads/MatlabStyle2%20book.pdf) - by R. Johnson.
* [parrun.sh](https://gist.github.com/precisesimulation/94395a41e53abf01da4d073b3b746493) - MATLAB and OCTAVE Parallel Job Script.
# Contributing
Your contributions are always welcome!
This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License - [CC BY-NC-SA 4.0](http://creativecommons.org/licenses/by-nc-sa/4.0/legalcode)
Owner
- Name: Christopher Madan
- Login: cMadan
- Kind: user
- Company: University of Nottingham
- Website: http://www.cmadan.com
- Twitter: cMadan
- Repositories: 6
- Profile: https://github.com/cMadan
Assistant Professor in Psychology