mne.minimum_norm.read_inverse_operator#
- mne.minimum_norm.read_inverse_operator(fname, *, verbose=None)[source]#
Read the inverse operator decomposition from a FIF file.
- Parameters:
- fname
str
The name of the FIF file, which ends with -inv.fif or -inv.fif.gz.
- verbose
bool
|str
|int
|None
Control verbosity of the logging output. If
None
, use the default verbosity level. See the logging documentation andmne.verbose()
for details. Should only be passed as a keyword argument.
- fname
- Returns:
- invinstance of
InverseOperator
The inverse operator.
- invinstance of
See also
Examples using mne.minimum_norm.read_inverse_operator
#
Overview of MEG/EEG analysis with MNE-Python
Visualize source time courses (stcs)
Permutation t-test on source data with spatio-temporal clustering
Repeated measures ANOVA on source data with spatio-temporal clustering
Corrupt known signal with point spread
Compute Power Spectral Density of inverse solution from single epochs
Compute power and phase lock in label of the source space
Compute source power spectral density (PSD) in a label
Compute induced power in the source space with dSPM
Compute MNE-dSPM inverse solution on single epochs
Compute sLORETA inverse solution on raw data
Compute MNE-dSPM inverse solution on evoked data in volume source space
Generate a functional label from source estimates
Extracting the time series of activations in a label
Morph volumetric source estimate
Visualize source leakage among labels using a circular graph
Estimate data SNR using an inverse
Plotting the full vector-valued MNE solution