gausspulse(t, fc=1000, bw=0.5, bwr=-6, tpr=-60, retquad=False, retenv=False)
exp(-a t^2) exp(1j*2*pi*fc*t).
If :None:None:`retquad`
is True, then return the real and imaginary parts (in-phase and quadrature). If :None:None:`retenv`
is True, then return the envelope (unmodulated signal). Otherwise, return the real part of the modulated sinusoid.
Input array.
Center frequency (e.g. Hz). Default is 1000.
Fractional bandwidth in frequency domain of pulse (e.g. Hz). Default is 0.5.
Reference level at which fractional bandwidth is calculated (dB). Default is -6.
If t
is 'cutoff', then the function returns the cutoff time for when the pulse amplitude falls below :None:None:`tpr`
(in dB). Default is -60.
If True, return the quadrature (imaginary) as well as the real part of the signal. Default is False.
If True, return the envelope of the signal. Default is False.
Real part of signal. Always returned.
Imaginary part of signal. Only returned if :None:None:`retquad`
is True.
Envelope of signal. Only returned if :None:None:`retenv`
is True.
Return a Gaussian modulated sinusoid:
Plot real component, imaginary component, and envelope for a 5 Hz pulse, sampled at 100 Hz for 2 seconds:
>>> from scipy import signalSee :
... 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, '--')
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.signal._wavelets.morlet
scipy.signal._wavelets.cwt
scipy.signal._waveforms.gausspulse
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