# scipy.signal.gausspulse

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

  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 float, 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

  `scipy.signal.morlet`

  Examples

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

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