cupyx.scipy.signal.gausspulse#

cupyx.scipy.signal.gausspulse(t, fc=1000, bw=0.5, bwr=-6, tpr=-60, retquad=False, retenv=False)[source]#

Return a Gaussian modulated sinusoid:

exp(-a t^2) exp(1j*2*pi*fc*t).

If retquad is True, then return the real and imaginary parts (in-phase and quadrature). If retenv is True, then return the envelope (unmodulated signal). Otherwise, return the real part of the modulated sinusoid.

Parameters:

  • t (ndarray or the string 'cutoff') – Input array.

  • fc (int, optional) – Center frequency (e.g. Hz). Default is 1000.

  • bw (float, optional) – Fractional bandwidth in frequency domain of pulse (e.g. Hz). Default is 0.5.

  • bwr (float, optional) – Reference level at which fractional bandwidth is calculated (dB). Default is -6.

  • tpr (float, optional) – If t is ‘cutoff’, then the function returns the cutoff time for when the pulse amplitude falls below tpr (in dB). Default is -60.

  • retquad (bool, optional) – If True, return the quadrature (imaginary) as well as the real part of the signal. Default is False.

  • retenv (bool, optional) – If True, return the envelope of the signal. Default is False.

Returns:

  • yI (ndarray) – Real part of signal. Always returned.

  • yQ (ndarray) – Imaginary part of signal. Only returned if retquad is True.

  • yenv (ndarray) – Envelope of signal. Only returned if retenv is True.

See also

cupyx.scipy.signal.morlet

Examples

Plot real component, imaginary component, and envelope for a 5 Hz pulse, sampled at 100 Hz for 2 seconds:

>>> import cupyx.scipy.signal
>>> import cupy as cp
>>> import matplotlib.pyplot as plt
>>> t = cupy.linspace(-1, 1, 2 * 100, endpoint=False)
>>> i, q, e = cupyx.scipy.signal.gausspulse(t, fc=5, retquad=True, retenv=True)
>>> plt.plot(cupy.asnumpy(t), cupy.asnumpy(i), cupy.asnumpy(t), cupy.asnumpy(q),
             cupy.asnumpy(t), cupy.asnumpy(e), '--')