syncopy.specest.mtmfft.mtmfft¶

syncopy.specest.mtmfft.
mtmfft
(trl_dat, samplerate=None, foi=None, nTaper=1, timeAxis=0, taper=<function hann>, taperopt={}, pad='nextpow2', padtype='zero', padlength=None, keeptapers=True, polyremoval=None, output_fmt='pow', noCompute=False, chunkShape=None)[source]¶ Compute (multi)tapered Fourier transform of multichannel time series data
 Parameters
trl_dat (2D
numpy.ndarray
) – Uniformly sampled multichannel timeseriessamplerate (float) – Samplerate of trl_dat in Hz
foi (1D
numpy.ndarray
) – Frequencies of interest (Hz) for output. If desired frequencies cannot be matched exactly the closest possible frequencies (respecting data length and padding) are used.nTaper (int) – Number of filter windows to use
timeAxis (int) – Index of running time axis in trl_dat (0 or 1)
taper (callable) – Taper function to use, one of
availableTapers
taperopt (dict) – Additional keyword arguments passed to the taper function. For further details, please refer to the SciPy docs
pad (str) – Padding mode; one of ‘absolute’, ‘relative’, ‘maxlen’, or ‘nextpow2’. See
syncopy.padding()
for more information.padtype (str) – Values to be used for padding. Can be ‘zero’, ‘nan’, ‘mean’, ‘localmean’, ‘edge’ or ‘mirror’. See
syncopy.padding()
for more information.padlength (None, bool or positive scalar) – Number of samples to pad to data (if pad is ‘absolute’ or ‘relative’). See
syncopy.padding()
for more information.keeptapers (bool) – If True, results of Fourier transform are preserved for each taper, otherwise spectrum is averaged across tapers.
polyremoval (int or None) – FIXME: Not implemented yet Order of polynomial used for detrending data in the time domain prior to spectral analysis. A value of 0 corresponds to subtracting the mean (“demeaning”),
polyremoval = 1
removes linear trends (subtracting the least squares fit of a linear polynomial),polyremoval = N
for N > 1 subtracts a polynomial of order N (N = 2
quadratic,N = 3
cubic etc.). If polyremoval is None, no detrending is performed.output_fmt (str) – Output of spectral estimation; one of
availableOutputs
noCompute (bool) – Preprocessing flag. If True, do not perform actual calculation but instead return expected shape and
numpy.dtype
of output array.chunkShape (None or tuple) – If not None, represents shape of output spec (respecting provided values of nTaper, keeptapers etc.)
 Returns
spec – Complex or real spectrum of (padded) input data.
 Return type
Notes
This method is intended to be used as
computeFunction()
inside aComputationalRoutine
. Thus, input parameters are presumed to be forwarded from a parent metafunction. Consequently, this function does not perform any error checking and operates under the assumption that all inputs have been externally validated and crosschecked.The computational heavy lifting in this code is performed by NumPy’s reference implementation of the Fast Fourier Transform
numpy.fft.fft()
.See also
syncopy.freqanalysis()
parent metafunction
MultiTaperFFT()
ComputationalRoutine
instance that calls this method ascomputeFunction()
numpy.fft.fft()
NumPy’s FFT implementation