Compute source power spectral density (PSD).
Raw
The raw data.
InverseOperator
The inverse operator.
float
The regularization parameter.
Use minimum norm, dSPM (default), sLORETA, or eLORETA.
float
The beginning of the time interval of interest (in seconds). Use 0. for the beginning of the file.
float
| None
The end of the time interval of interest (in seconds). If None stop at the end of the file.
float
The lower frequency of interest.
float
The upper frequency of interest.
int
Window size for the FFT. Should be a power of 2.
float
The overlap fraction between windows. Should be between 0 and 1. 0 means no overlap.
None
| “normal”If “normal”, rather than pooling the orientations by taking the norm, only the radial component is kept. This is only implemented when working with loose orientations.
Label
Restricts the source estimates to a given label.
int
The number of averages used to scale the noise covariance matrix.
If True, the true dimension of data is estimated before running the time-frequency transforms. It reduces the computation times e.g. with a dataset that was maxfiltered (true dim is 64).
If True, do not call prepare_inverse_operator()
.
dict
| None
Additional options for eLORETA. See Notes of apply_inverse()
.
New in version 0.16.
int
or None
Split inverse operator into inv_split parts in order to save memory.
New in version 0.17.
float
| str
The bandwidth of the multi taper windowing function in Hz. Can also be a string (e.g., ‘hann’) to use a single window.
For backward compatibility, the default is ‘hann’.
New in version 0.17.
Use adaptive weights to combine the tapered spectra into PSD (slow, use n_jobs >> 1 to speed up computation).
New in version 0.17.
Only use tapers with more than 90% spectral concentration within bandwidth.
New in version 0.17.
int
| None
The number of jobs to run in parallel. If -1
, it is set
to the number of CPU cores. Requires the joblib
package.
None
(default) is a marker for ‘unset’ that will be interpreted
as n_jobs=1
(sequential execution) unless the call is performed under
a joblib.parallel_backend()
context manager that sets another
value for n_jobs
.
It is only used if adaptive=True.
New in version 0.17.
If True, return the sensor PSDs as an EvokedArray.
New in version 0.17.
If True (default False), return output it decibels.
New in version 0.17.
str
| int
| None
Control verbosity of the logging output. If None
, use the default
verbosity level. See the logging documentation and
mne.verbose()
for details. Should only be passed as a keyword
argument.
SourceEstimate
| VolSourceEstimate
The PSD of each of the sources.
EvokedArray
The PSD of each sensor. Only returned if return_sensor
is True.
See also
Notes
Each window is multiplied by a window before processing, so using a non-zero overlap is recommended.
This function is different from compute_source_psd_epochs()
in that:
bandwidth='hann'
by default, skipping multitaper estimation
For convenience it wraps
mne.make_fixed_length_events()
and mne.Epochs
.
Otherwise the two should produce identical results.
mne.minimum_norm.compute_source_psd
#Compute source power spectral density (PSD) in a label
Compute source power spectral density (PSD) of VectorView and OPM data