bundles / scipy latest / scipy / signal / _filter_design / zpk2tf
function
scipy.signal._filter_design:zpk2tf
Signature
def zpk2tf ( z , p , k ) Summary
Return polynomial transfer function representation from zeros and poles
Parameters
z: array_likeZeros of the transfer function.
p: array_likePoles of the transfer function.
k: floatSystem gain.
Returns
b: ndarrayNumerator polynomial coefficients.
a: ndarrayDenominator polynomial coefficients.
Notes
Array API Standard Support
zpk2tf 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 ⚠️ no JIT ⛔ Dask ⚠️ computes graph n/a ==================== ==================== ====================
The CuPy and JAX backends both support only 1d input.
See
dev-arrayapifor more information.
Examples
Find the polynomial representation of a transfer function H(s) using its 'zpk' (Zero-Pole-Gain) representation. .. math:: H(z) = 5 \frac { (s - 2)(s - 6) } { (s - 1)(s - 8) }from scipy.signal import zpk2tf z = [2, 6] p = [1, 8] k = 5✓
zpk2tf(z, p, k)
✗Aliases
-
scipy.signal.zpk2tf