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A high-level M/EEG Python library for EEG inverse solutions

Project description

invertmeeg - A high-level M/EEG Python library for EEG inverse solutions :dart:

This package contains various (>50) approaches to solve the M/EEG inverse problems :leftwards_arrow_with_hook:. It integrates with the mne-python framework.

Read the Documentation here!

Install the package from pypi:

pip install invertmeeg

To check if the installation works run:

python -c 'import invert'

To test the package simply run:

pytest tests

To calculate an inverse solution using minimum norm estimates simply type:

from invert import Solver

# fwd = ...
# evoked = ...

# Create a Solver instance
solver_name = "MNE"
solver = Solver(solver_name)

# Calculate the inverse operator
solver.make_inverse_operator(fwd)

# Apply the inverse operator to your data
stc = solver.apply_inverse_operator(evoked)

# Plot the resulting source estimate
stc.plot()

There are many solvers implemented in the package, and you can find them here!

I am looking for collaborators! If you are interested you can write an :email: to lukas_hecker@web.de

If you use this package and publish results, please cite as:

@Misc{invertmeeg2022,
  author =   {{Lukas Hecker}},
  title =    {{invertmeeg}: A high-level M/EEG Python library for EEG inverse solutions.},
  howpublished = {\url{https://github.com/LukeTheHecker/invert}},
  year = {since 2022}
}

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