`scipy.signal._czt:czt_points`

source: /scipy/signal/_czt.py :53

Signature

def czt_points ( m , w = None , a = (1+0j) )

Summary

Return the points at which the chirp z-transform is computed.

Parameters

m : int: The number of points desired.
w : complex, optional: The ratio between points in each step. Defaults to equally spaced points around the entire unit circle.
a : complex, optional: The starting point in the complex plane. Default is 1+0j.

Returns

out : ndarray: The points in the Z plane at which CZT samples the z-transform, when called with arguments m, w, and a, as complex numbers.

Notes

Array API Standard Support

czt_points 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 dev-arrayapi for more information.

Examples

Plot the points of a 16-point FFT:

import numpy as np
from scipy.signal import czt_points
points = czt_points(16)
import matplotlib.pyplot as plt

✓

plt.plot(points.real, points.imag, 'o')
plt.gca().add_patch(plt.Circle((0,0), radius=1, fill=False, alpha=.3))
plt.axis('equal')

✗

plt.show()

✓

and a 91-point logarithmic spiral that crosses the unit circle:

m, w, a = 91, 0.995*np.exp(-1j*np.pi*.05), 0.8*np.exp(1j*np.pi/6)
points = czt_points(m, w, a)

✓

plt.plot(points.real, points.imag, 'o')
plt.gca().add_patch(plt.Circle((0,0), radius=1, fill=False, alpha=.3))
plt.axis('equal')

✗

plt.show()

✓

Aliases

scipy.signal.czt_points