If you want to update MNE-Python to a newer version, there are a few different options, depending on how you originally installed it.
To update via the MNE-Python installers, simply download and run the latest installer for your platform. MNE-Python will be installed in parallel to your existing installation, which you may uninstall or delete if you don’t need it anymore.
If you’re not using the MNE-Python installers, keep reading.
Upgrading MNE-Python only#
If you wish to update MNE-Python only and leave other packages in their current
state, you can usually safely do this with
pip, even if you originally
installed via conda. With the
mne environment active
conda activate name_of_environment), do:
$ pip install -U mne
Upgrading all packages#
Generally speaking, if you want to upgrade your whole software stack including all the dependencies, the best approach is to re-create it as a new virtual environment, because neither conda nor pip are fool-proof at making sure all packages remain compatible with one another during upgrades.
Here we’ll demonstrate renaming the old environment first, as a safety measure.
We’ll assume that the existing environment is called
mne and you want to
rename the old one so that the new, upgraded environment can be called
Before running the below command, ensure that your existing MNE conda
environment is not activated. Run
conda deactivate if in doubt.
$ conda rename --name=mne old_mne # rename existing "mne" env to "old_mne"
Then, just follow our regular installation instructions, Install via pip or conda.
If you installed extra packages into your old
you’ll need to repeat that process after re-creating the updated
environment. Comparing the output of
conda list --name old_mne versus
conda list --name mne will show you what is missing from the new
environment. On Linux, you can automate that comparison like this:
$ diff <(conda list -n mne | cut -d " " -f 1 | sort) <(conda list -n old_mne | cut -d " " -f 1 | sort) | grep "^>" | cut -d " " -f 2
Upgrading to the development version#
Sometimes, new features or bugfixes become available that are important to your
research and you just can’t wait for the next official release of MNE-Python to
start taking advantage of them. In such cases, you can use
pip to install
the development version of MNE-Python. Ensure to activate the MNE conda
environment first by running
conda activate name_of_environment.
$ pip install -U --no-deps git+https://github.com/mne-tools/mne-python@main