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$ pip install matlab_kernel
or pip install git+https://github.com/Calysto/matlab_kernel for the dev version.
To use the kernel, run one of:
$ jupyter notebook # In the notebook interface, select Matlab from the 'New' menu $ jupyter qtconsole --kernel matlab $ jupyter console --kernel matlab
To remove from kernel listings:
$ jupyter kernelspec remove matlab
The kernel can be configured by adding an matlab_kernel_config.py file to the jupyter config path. The MatlabKernel class offers plot_settings as a configurable traits. The available plot settings are: ‘format’, ‘backend’, ‘width’, ‘height’, and ‘resolution’.
cat ~/.jupyter/matlab_kernel_config.py c.MatlabKernel.plot_settings = dict(format='svg')
Kernel Times Out While Starting
If the kernel is not starting, try running the following from a terminal.
Please include that output if opening an issue.
Kernel is Not Listed
If the kernel is not listed as an available kernel, first try the following command:
python -m matlab_kernel install --user
If the kernel is still not listed, verify that the following point to the same version of python:
which python # use "where" if using cmd.exe which jupyter
The Matlab kernel is based on MetaKernel, which means it features a standard set of magics. For a full list of magics, run %lsmagic in a cell.
A sample notebook is available online.
A note about plotting. After each call to Matlab, we ask Matlab to save any open figures to image files whose format and resolution are defined using the %plot magic. The resulting image is shown inline in the notebook. You can use %plot native to raise normal Matlab windows instead.
Advanced Installation Notes
We automatically install a Jupyter kernelspec when installing the python package. This location can be found using jupyter kernelspec list. If the default location is not desired, you can remove the directory for the octave kernel, and install using python -m matlab_kernel install. See python -m matlab_kernel install --help for available options.
It has been reported that Matlab version 2016b works fine. However, Matlab 2014b does not work with Python 3.5.
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