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invertmeeg

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

This package provides 82 inverse solvers for M/EEG source imaging, integrating with the mne-python framework. It covers minimum norm methods, beamformers, Bayesian approaches, sparse recovery, subspace methods, and deep learning models in a unified API.

Highlights

  • 82 inverse solvers accessible through a single Solver("solver_id") interface
  • Automatic regularization (GCV, L-curve, product methods)
  • Returns standard mne.SourceEstimate objects
  • Simulation utilities for benchmarking
  • Getting Started — install, extras, and a minimal end-to-end example
  • Solvers — browse solver families and per-solver API docs
  • Benchmarks — interactive benchmark dashboard (static, GitHub Pages friendly)
  • API Reference — full Python API via mkdocstrings

Quick Example

from invert import Solver

# fwd = ...   (mne.Forward object)
# evoked = ... (mne.Evoked object)

solver = Solver("MNE")
solver.make_inverse_operator(fwd)
stc = solver.apply_inverse_operator(evoked)
stc.plot()