`scipy.signal._waveforms:sweep_poly`

source: build-install/usr/lib/python3.14/site-packages/scipy/signal/_waveforms.py:481

Signature

def sweep_poly(t, poly, phi = 0)

Summary

Frequency-swept cosine generator, with a time-dependent frequency.

Extended Summary

This function generates a sinusoidal function whose instantaneous frequency varies with time. The frequency at time t is given by the polynomial poly.

Parameters

t : ndarray

Times at which to evaluate the waveform.

poly : 1-D array_like or instance of numpy.poly1d

The desired frequency expressed as a polynomial. If poly is a list or ndarray of length n, then the elements of poly are the coefficients of the polynomial, and the instantaneous frequency is

f(t) = poly[0]*t**(n-1) + poly[1]*t**(n-2) + ... + poly[n-1]

If poly is an instance of numpy.poly1d, then the instantaneous frequency is

f(t) = poly(t)

phi : float, optional

Phase offset, in degrees, Default: 0.

Returns

sweep_poly : ndarray: A numpy array containing the signal evaluated at t with the requested time-varying frequency. More precisely, the function returns cos(phase + (pi/180)*phi), where phase is the integral (from 0 to t) of 2 * pi * f(t); f(t) is defined above.

Notes

If poly is a list or ndarray of length n, then the elements of poly are the coefficients of the polynomial, and the instantaneous frequency is:

f(t) = poly[0]*t**(n-1) + poly[1]*t**(n-2) + ... + poly[n-1]

If poly is an instance of numpy.poly1d, then the instantaneous frequency is:

f(t) = poly(t)

Finally, the output s is:

cos(phase + (pi/180)*phi)

where phase is the integral from 0 to t of 2 * pi * f(t), f(t) as defined above.

Examples

Compute the waveform with instantaneous frequency:: f(t) = 0.025*t**3 - 0.36*t**2 + 1.25*t + 2 over the interval 0 <= t <= 10.

import numpy as np
from scipy.signal import sweep_poly
p = np.poly1d([0.025, -0.36, 1.25, 2.0])
t = np.linspace(0, 10, 5001)
w = sweep_poly(t, p)

✓

Plot it:

import matplotlib.pyplot as plt

✓

plt.subplot(2, 1, 1)
plt.plot(t, w)
plt.title("Sweep Poly\nwith frequency " +
          "$f(t) = 0.025t^3 - 0.36t^2 + 1.25t + 2$")
plt.subplot(2, 1, 2)
plt.plot(t, p(t), 'r', label='f(t)')
plt.legend()
plt.xlabel('t')

✗

Text(0.5, 0, 't')

plt.tight_layout()
plt.show()

✓

`scipy.signal._waveforms:sweep_poly`

Signature

Summary

Extended Summary

Parameters

Returns

Notes

Examples

See also

Aliases

Referenced by

This package