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)

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).

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)

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)

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)

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.