mne.decoding.PSDEstimator¶

class mne.decoding.PSDEstimator(sfreq=6.283185307179586, fmin=0, fmax=inf, bandwidth=None, adaptive=False, low_bias=True, n_jobs=1, normalization=’length’, verbose=None)[source]¶

Compute power spectrum density (PSD) using a multi-taper method.

Parameters:

sfreq : float The sampling frequency. fmin : float The lower frequency of interest. fmax : float The upper frequency of interest. bandwidth : float The bandwidth of the multi taper windowing function in Hz. 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% spectral concentration within bandwidth. n_jobs : int Number of parallel jobs to use (only used if adaptive=True). normalization : str Either “full” or “length” (default). If “full”, the PSD will be normalized by the sampling rate as well as the length of the signal (as in nitime). verbose : bool, str, int, or None If not None, override default verbose level (see mne.verbose() and Logging documentation for more).

See also

psd_multitaper

Methods

__hash__() <==> hash(x)
fit(epochs_data, y)	Compute power spectrum density (PSD) using a multi-taper method.
fit_transform(X[, y])	Fit to data, then transform it.
transform(epochs_data[, y])	Compute power spectrum density (PSD) using a multi-taper method.

__hash__() <==> hash(x)¶

fit(epochs_data, y)[source]¶

Compute power spectrum density (PSD) using a multi-taper method.

Parameters:	epochs_data : array, shape (n_epochs, n_channels, n_times) The data. y : array, shape (n_epochs,) The label for each epoch
Returns:	self : instance of PSDEstimator returns the modified instance

fit_transform(X, y=None, **fit_params)[source]¶

Fit to data, then transform it.

Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X.

Parameters:	X : numpy array of shape [n_samples, n_features] Training set. y : numpy array of shape [n_samples] Target values.
Returns:	X_new : numpy array of shape [n_samples, n_features_new] Transformed array.

transform(epochs_data, y=None)[source]¶

Compute power spectrum density (PSD) using a multi-taper method.

Parameters:	epochs_data : array, shape (n_epochs, n_channels, n_times) The data y : None | array, shape (n_epochs,) The label for each epoch. If None not used. Defaults to None.
Returns:	psd : array, shape (n_signals, len(freqs)) or (len(freqs),) The computed PSD.