scipy.signal.

gausspulse#

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:

tndarray or the string ‘cutoff’: Input array.
fcfloat, optional: Center frequency (e.g. Hz). Default is 1000.
bwfloat, optional: Fractional bandwidth in frequency domain of pulse (e.g. Hz). Default is 0.5.
bwrfloat, optional: Reference level at which fractional bandwidth is calculated (dB). Default is -6.
tprfloat, 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.
retquadbool, optional: If True, return the quadrature (imaginary) as well as the real part of the signal. Default is False.
retenvbool, optional: If True, return the envelope of the signal. Default is False.

Returns:

yIndarray: Real part of signal. Always returned.
yQndarray: Imaginary part of signal. Only returned if retquad is True.
yenvndarray: Envelope of signal. Only returned if retenv is True.

Notes

Array API Standard Support

gausspulse has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

Library	CPU	GPU
NumPy	✅	n/a
CuPy	n/a	⛔
PyTorch	⛔	⛔
JAX	⛔	⛔
Dask	⛔	n/a

See Support for the array API standard for more information.

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, '--')

../../_images/scipy-signal-gausspulse-1.png