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:: python
>>> oc = oct2py.Oct2Py()
>>> x = oc.zeros(3,3)
>>> print(x, x.dtype)
[[ 0. 0. 0.]
[ 0. 0. 0.]
[ 0. 0. 0.]] float64
...
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.
zerosabove). - 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/master/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-cli 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 Revision History_.
.. _online: https://oct2py.readthedocs.io/en/latest/
.. _History: https://github.com/blink1073/oct2py/blob/master/HISTORY.rst