Time-Frequency#

mne.time_frequency:

Time frequency analysis tools.

AverageTFR(info, data, times, freqs, nave[, ...])

Container for Time-Frequency data.

EpochsTFR(info, data, times, freqs[, ...])

Container for Time-Frequency data on epochs.

CrossSpectralDensity(data, ch_names, ...[, ...])

Cross-spectral density.

Spectrum(inst, method, fmin, fmax, tmin, ...)

Data object for spectral representations of continuous data.

EpochsSpectrum(inst, method, fmin, fmax, ...)

Data object for spectral representations of epoched data.

Functions that operate on mne-python objects:

csd_tfr(epochs_tfr[, tmin, tmax, picks, ...])

Compute covariance matrices across frequencies for TFR epochs.

csd_fourier(epochs[, fmin, fmax, tmin, ...])

Estimate cross-spectral density from an array using short-time fourier.

csd_multitaper(epochs[, fmin, fmax, tmin, ...])

Estimate cross-spectral density from epochs using a multitaper method.

csd_morlet(epochs, frequencies[, tmin, ...])

Estimate cross-spectral density from epochs using Morlet wavelets.

pick_channels_csd(csd[, include, exclude, ...])

Pick channels from cross-spectral density matrix.

read_csd(fname)

Read a CrossSpectralDensity object from an HDF5 file.

fit_iir_model_raw(raw[, order, picks, tmin, ...])

Fit an AR model to raw data and creates the corresponding IIR filter.

tfr_morlet(inst, freqs, n_cycles[, use_fft, ...])

Compute Time-Frequency Representation (TFR) using Morlet wavelets.

tfr_multitaper(inst, freqs, n_cycles[, ...])

Compute Time-Frequency Representation (TFR) using DPSS tapers.

tfr_stockwell(inst[, fmin, fmax, n_fft, ...])

Compute Time-Frequency Representation (TFR) using Stockwell Transform.

read_tfrs(fname[, condition, verbose])

Read TFR datasets from hdf5 file.

write_tfrs(fname, tfr[, overwrite, verbose])

Write a TFR dataset to hdf5.

read_spectrum(fname)

Load a mne.time_frequency.Spectrum object from disk.

Functions that operate on np.ndarray objects:

csd_array_fourier(X, sfreq[, t0, fmin, ...])

Estimate cross-spectral density from an array using short-time fourier.

csd_array_multitaper(X, sfreq[, t0, fmin, ...])

Estimate cross-spectral density from an array using a multitaper method.

csd_array_morlet(X, sfreq, frequencies[, ...])

Estimate cross-spectral density from an array using Morlet wavelets.

dpss_windows(N, half_nbw, Kmax, *[, sym, ...])

Compute Discrete Prolate Spheroidal Sequences.

morlet(sfreq, freqs[, n_cycles, sigma, ...])

Compute Morlet wavelets for the given frequency range.

stft(x, wsize[, tstep, verbose])

STFT Short-Term Fourier Transform using a sine window.

istft(X[, tstep, Tx])

ISTFT Inverse Short-Term Fourier Transform using a sine window.

stftfreq(wsize[, sfreq])

Compute frequencies of stft transformation.

psd_array_multitaper(x, sfreq[, fmin, fmax, ...])

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

psd_array_welch(x, sfreq[, fmin, fmax, ...])

Compute power spectral density (PSD) using Welch's method.

tfr_array_morlet(epoch_data, sfreq, freqs[, ...])

Compute Time-Frequency Representation (TFR) using Morlet wavelets.

tfr_array_multitaper(epoch_data, sfreq, freqs)

Compute Time-Frequency Representation (TFR) using DPSS tapers.

tfr_array_stockwell(data, sfreq[, fmin, ...])

Compute power and intertrial coherence using Stockwell (S) transform.

mne.time_frequency.tfr:

A module which implements the time-frequency estimation.

Morlet code inspired by Matlab code from Sheraz Khan & Brainstorm & SPM

cwt(X, Ws[, use_fft, mode, decim])

Compute time-frequency decomposition with continuous wavelet transform.

morlet(sfreq, freqs[, n_cycles, sigma, ...])

Compute Morlet wavelets for the given frequency range.