Julia interface to MNE-Python via PythonCall
This package uses PythonCall to make
MNE-Python available from within Julia. Unsurprisingly,
MNE-Python and its dependencies need to be installed in order for this to work
and PyMNE will attempt to install when the package is built: this should happen
more or less automatically via CondaPkg.
You can configure various options via CondaPkg.
In the same philosophy as PythonCall, this allows for the transparent use of
MNE-Python from within Julia.
The major things the package does are wrap the installation of MNE in the
package installation and load all the MNE functionality into the module
namespace.
After that, it's just a Python package accessible via using PyMNE in
Julia. The usual conversion rules and behaviors from PythonCall apply.
The tests test a few conversion gotchas, especially
compared to prior versions of this package, which were based on
PyCall.
You need to explicitly convert vectors of strings to a PyList. For instance
data = raw.get_data(picks=["Oz","Cz"])does not work, whereas
data = raw.get_data(picks=pylist(["Oz","Cz"]))works. The underlying logic is, that the automatic conversion of ["A","B"]is to a juliacall.VectorValue which behaves similar to a pyList - but is apparently not recognized properly by MNE (a vector of int, surprisingly, works though).
For example, in Python you can access the MNE docs like this:
import mne
mne.open_docs()With PyMNE, you can do this from within Julia.
using PyMNE
PyMNE.open_docs()The PythonCall infrastructure also means that Python docstrings are available in Julia:
help?> PyMNE.open_docs
Python function open_docs.
Launch a new web browser tab with the MNE documentation.
Parameters
----------
kind : str | None
Can be "api" (default), "tutorials", or "examples".
The default can be changed by setting the configuration value
MNE_DOCS_KIND.
version : str | None
Can be "stable" (default) or "dev".
The default can be changed by setting the configuration value
MNE_DOCS_VERSION.