Module quantum_inferno.utilities.short_time_fft

Methods for calculating frequency and time-frequency representations of signals. Try to match all the defaults…

Functions

def get_stft_object_tukey(sample_rate_hz: float, tukey_alpha: float, segment_length: int, overlap_length: int, scaling: str = 'magnitude') ‑> scipy.signal._short_time_fft.ShortTimeFFT

Return the Short-Time Fourier Transform (STFT) object with a Tukey window using ShortTimeFFT class Calculates the number of fft points based on the segment length using ceil_power_of_two rounding method

:param sample_rate_hz: sample rate of the signal :param tukey_alpha: shape parameter of the Tukey window :param segment_length: length of the segment :param overlap_length: length of the overlap :param scaling: scaling of the STFT (default is magnitude, other options are 'psd' and None) :return: ShortTimeFFT object

def istft_tukey(stft_to_invert: numpy.ndarray, sample_rate_hz: float, tukey_alpha: float, segment_length: int, overlap_length: int, scaling: str = 'magnitude') ‑> Tuple[numpy.ndarray, numpy.ndarray]

Calculate the inverse Short-Time Fourier Transform (iSTFT) of a signal with a Tukey window using ShortTimeFFT class

:param stft_to_invert: The STFT to be inverted :param sample_rate_hz: sample rate of the signal :param tukey_alpha: shape parameter of the Tukey window :param segment_length: length of the segment :param overlap_length: length of the overlap :param scaling: scaling of the STFT (default is None, other options are 'magnitude' and 'psd) :return: timestamps and iSTFT of the signal

def spectrogram_tukey(timeseries: numpy.ndarray, sample_rate_hz: float, tukey_alpha: float, segment_length: int, overlap_length: int, scaling: str = 'magnitude', padding: str = 'zeros') ‑> Tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray]

Calculate the Spectrogram of a signal with a Tukey window using ShortTimeFFT class Returns the time, frequency, and spectrogram similar to legacy scipy.signal.spectrogram

:param timeseries: input signal :param sample_rate_hz: sample rate of the signal :param tukey_alpha: shape parameter of the Tukey window :param segment_length: length of the segment :param overlap_length: length of the overlap :param scaling: scaling of the spectrogram (default is 'magnitude', other options are 'psd' and None) :param padding: padding of the signal (default is 'zeros', other options are 'periodic' and 'constant') :return: time, frequency, and magnitude of the STFT

def stft_tukey(timeseries: numpy.ndarray, sample_rate_hz: float, tukey_alpha: float, segment_length: int, overlap_length: int, scaling: str = 'magnitude', padding: str = 'zeros') ‑> Tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray]

Calculate the Short-Time Fourier Transform (STFT) of a signal with a Tukey window using ShortTimeFFT class Returns the time, frequency, and magnitude of the STFT similar to legacy scipy.signal.stft

:param timeseries: input signal :param sample_rate_hz: sample rate of the signal :param tukey_alpha: shape parameter of the Tukey window :param segment_length: length of the segment :param overlap_length: length of the overlap :param scaling: scaling of the STFT (default is None, other options are 'magnitude' and 'psd) :param padding: padding method for the STFT (default is 'zeros', other options are 'edge', 'even', and 'odd') :return: time, frequency, and magnitude of the STFT