| Parameters: |
- raw : instance of Raw
The raw data
- inverse_operator : instance of InverseOperator
The inverse operator
- lambda2: float
The regularization parameter
- method: “MNE” | “dSPM” | “sLORETA”
Use minimum norm, dSPM (default), sLORETA, or eLORETA.
- tmin : float
The beginning of the time interval of interest (in seconds).
Use 0. for the beginning of the file.
- tmax : float | None
The end of the time interval of interest (in seconds). If None
stop at the end of the file.
- fmin : float
The lower frequency of interest
- fmax : float
The upper frequency of interest
- n_fft: int
Window size for the FFT. Should be a power of 2.
- overlap: float
The overlap fraction between windows. Should be between 0 and 1.
0 means no overlap.
- pick_ori : 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: Label
Restricts the source estimates to a given label
- nave : int
The number of averages used to scale the noise covariance matrix.
- pca: bool
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).
- prepared : bool
If True, do not call prepare_inverse_operator().
- method_params : dict | None
Additional options for eLORETA. See Notes of apply_inverse().
- inv_split : int or None
Split inverse operator into inv_split parts in order to save memory.
- bandwidth : 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’.
- adaptive : bool
Use adaptive weights to combine the tapered spectra into PSD
(slow, use n_jobs >> 1 to speed up computation).
- low_bias : bool
Only use tapers with more than 90{‘verbose’: ‘n verbose : bool, str, int, or Nonen If not None, override default verbose level (see mne.verbose()n and Logging documentation for more).’, ‘verbose_meth’: ‘n verbose : bool, str, int, or Nonen If not None, override default verbose level (see mne.verbose()n and Logging documentation for more). Defaults to self.verbose.’, ‘picks_header’: ‘picks : str | list | slice | None’, ‘picks_base’: ‘picks : str | list | slice | Nonen Channels to include. Slices and lists of integers will ben interpreted as channel indices. In lists, channel type stringsn (e.g., [\'meg\', \'eeg\']) will pick channels of thosen types, channel name strings (e.g., [\'MEG0111\', \'MEG2623\']n will pick the given channels. Can also be the string valuesn “all” to pick all channels, or “data” to pick data channels.n None (default) will pick ‘, ‘picks_all’: ‘picks : str | list | slice | Nonen Channels to include. Slices and lists of integers will ben interpreted as channel indices. In lists, channel type stringsn (e.g., [\'meg\', \'eeg\']) will pick channels of thosen types, channel name strings (e.g., [\'MEG0111\', \'MEG2623\']n will pick the given channels. Can also be the string valuesn “all” to pick all channels, or “data” to pick data channels.n None (default) will pick all channels.’, ‘picks_all_data’: ‘picks : str | list | slice | Nonen Channels to include. Slices and lists of integers will ben interpreted as channel indices. In lists, channel type stringsn (e.g., [\'meg\', \'eeg\']) will pick channels of thosen types, channel name strings (e.g., [\'MEG0111\', \'MEG2623\']n will pick the given channels. Can also be the string valuesn “all” to pick all channels, or “data” to pick data channels.n None (default) will pick all data channels.’, ‘picks_all_data_noref’: ‘picks : str | list | slice | Nonen Channels to include. Slices and lists of integers will ben interpreted as channel indices. In lists, channel type stringsn (e.g., [\'meg\', \'eeg\']) will pick channels of thosen types, channel name strings (e.g., [\'MEG0111\', \'MEG2623\']n will pick the given channels. Can also be the string valuesn “all” to pick all channels, or “data” to pick data channels.n None (default) will pick all data channels(excluding reference MEG channels).’, ‘picks_good_data’: ‘picks : str | list | slice | Nonen Channels to include. Slices and lists of integers will ben interpreted as channel indices. In lists, channel type stringsn (e.g., [\'meg\', \'eeg\']) will pick channels of thosen types, channel name strings (e.g., [\'MEG0111\', \'MEG2623\']n will pick the given channels. Can also be the string valuesn “all” to pick all channels, or “data” to pick data channels.n None (default) will pick good data channels.’, ‘picks_good_data_noref’: ‘picks : str | list | slice | Nonen Channels to include. Slices and lists of integers will ben interpreted as channel indices. In lists, channel type stringsn (e.g., [\'meg\', \'eeg\']) will pick channels of thosen types, channel name strings (e.g., [\'MEG0111\', \'MEG2623\']n will pick the given channels. Can also be the string valuesn “all” to pick all channels, or “data” to pick data channels.n None (default) will pick good data channels(excluding reference MEG channels).’, ‘picks_nostr’: ‘n picks : list | slice | Nonen Channels to include. Slices and lists of integers will ben interpreted as channel indices. None (default) will pick all channels.’}pectral concentration within
bandwidth.
- n_jobs : int
Number of parallel jobs to use (only used if adaptive=True).
- return_sensor : bool
If True, return the sensor PSDs as an EvokedArray.
- dB : bool
If True (default False), return output it decibels.
- verbose : bool, str, int, or None
If not None, override default verbose level (see mne.verbose()
and Logging documentation for more).
|
|---|
