Oct2Py: Python to GNU Octave Bridge
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Oct2Py allows you to seamlessly call M-files and Octave functions from Python.
It manages the Octave session for you, sharing data behind the scenes using
MAT files. Usage is as simple as:
.. code-block:: pycon
>>> import oct2py
>>> oc = oct2py.Oct2Py()
>>> x = oc.zeros(3, 3)
>>> print(x, x.dtype)
[[0. 0. 0.]
[0. 0. 0.]
[0. 0. 0.]] float64
To run .m function, you need to explicitly add the path to .m file using:
.. code-block:: pycon
>>> from oct2py import octave
>>> # to add a folder use:
>>> octave.addpath("/path/to/directory") # doctest: +SKIP
>>> # to add folder with all subfolder in it use:
>>> octave.addpath(octave.genpath("/path/to/directory")) # doctest: +SKIP
>>> # to run the .m file :
>>> octave.run("fileName.m") # doctest: +SKIP
To get the output of .m file after setting the path, use:
.. code-block:: pycon
>>> import numpy as np
>>> from oct2py import octave
>>> x = np.array([[1, 2], [3, 4]], dtype=float)
>>> # use nout='max_nout' to automatically choose max possible nout
>>> octave.addpath("./example") # doctest: +SKIP
>>> out, oclass = octave.roundtrip(x, nout=2) # doctest: +SKIP
>>> import pprint # doctest: +SKIP
>>> pprint.pprint([x, x.dtype, out, oclass, out.dtype]) # doctest: +SKIP
[array([[1., 2.],
[3., 4.]]),
dtype('float64'),
array([[1., 2.],
[3., 4.]]),
'double',
dtype('<f8')]
If you want to run legacy m-files, do not have MATLAB®, and do not fully
trust a code translator, this is your library.
Features
- Supports all Octave datatypes and most Python datatypes and Numpy dtypes.
- Provides OctaveMagic_ for IPython, including inline plotting in notebooks.
- Supports cell arrays and structs/struct arrays with arbitrary nesting.
- Supports sparse matrices.
- Builds methods on the fly linked to Octave commands (e.g.
zeros
above). - Thread-safety: each Oct2Py object uses an independent Octave session.
- Can be used as a context manager.
- Supports Unicode characters.
- Supports logging of session commands.
- Optional timeout command parameter to prevent runaway Octave sessions.
.. _OctaveMagic: https://nbviewer.jupyter.org/github/blink1073/oct2py/blob/main/example/octavemagic_extension.ipynb?create=1
Installation
You must have GNU Octave installed and in your PATH
environment variable.
Alternatively, you can set an OCTAVE_EXECUTABLE
or OCTAVE
environment
variable that points to octave
executable itself.
You must have the Numpy and Scipy libraries for Python installed.
See the installation instructions_ for more details.
Once the dependencies have been installed, run:
.. code-block:: bash
$ pip install oct2py
If using conda, it is available on conda-forge:
.. code-block:: bash
$ conda install -c conda-forge oct2py
.. _instructions: http://blink1073.github.io/oct2py/source/installation.html
Documentation
Documentation is available online_.
For version information, see the Changelog_.
.. _online: https://oct2py.readthedocs.io/en/latest/
.. _Changelog: https://github.com/blink1073/oct2py/blob/main/CHANGELOG.md