pybic.ApplySTFT

pybic.ApplySTFT(sig, samprate=1.0, subint=512, step=256, nfreq=256, t0=0, detrend=False, errlim=1000000000000000.0, window='hann')[source]

Calculate short-time Fourier transform (STFT) of time-series.

Parameters:

  • sig (ndarray) – Time series to be analyzed.

  • samprate (float) – Sampling rate in Hz.

  • subint (int) – Subinterval size in samples.

  • step (int) – Subinterval step in samples.

  • nfreq (int) – Number of frequency bins.

  • t0 (float) – Initial time.

  • detrend (bool) – Detrend data in each subinterval.

  • errlim (float) – Max threshold of mean power spectrum.

  • window (str) – Desired window function.

Returns:

spec,afft,freq_vec,time_vec,err,Ntoss = ApplySTFT(...)

  • spec (ndarray) - STFT spectrogram (w/ shape (len(sig)/limFreq)).

  • afft (ndarray) - Power spectrum.

  • freq_vec (ndarray) - Frequency vector.

  • time_vec (ndarray) - Time vector.

  • err (ndarray) - Mean spectrogram vs time.

  • Ntoss (int) - Number of omitted intervals.

Return type:

list