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:
>>> 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:
>>> from oct2py import import octave
>>> # to add a folder use:
>>> octave.addpath('/path/to/directory')
>>> # to add folder with all subfolder in it use:
>>> octave.addpath(octave.genpath('/path/to/directory'))
...
To get the output of .m file after setting the path, use:
>>> x = np.array([[1, 2], [3, 4]], dtype=float)
>>> #use nout='max_nout' to automatically choose max possible nout
>>> out, oclass = octave.roundtrip(x,nout=2)
>>> import pprint
>>> pprint.pprint([x, x.dtype, out, oclass, out.dtype])
[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.
- 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.
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:
$ pip install oct2py
If using conda, it is available on conda-forge:
$ conda install -c conda-forge oct2py
Documentation is available online.
For version information, see the Revision History.