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 : int, optional

Center frequency (Hz). Default is 1000.

bw : float, optional

Fractional bandwidth in frequency domain of pulse (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:

>>> 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, '--')

(Source code)