Source code for deltasigma._evalTF
# -*- coding: utf-8 -*-
# _evalTF.py
# This module provides the evalTF function.
# Copyright 2013 Giuseppe Venturini
# This file is part of python-deltasigma.
#
# python-deltasigma is a 1:1 Python replacement of Richard Schreier's
# MATLAB delta sigma toolbox (aka "delsigma"), upon which it is heavily based.
# The delta sigma toolbox is (c) 2009, Richard Schreier.
#
# python-deltasigma is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# LICENSE file for the licensing terms.
"""This module provides the evalTF() function, used to evaluate a tf at the
point(s) given by the user.
"""
import numpy as np
from ._evalRPoly import evalRPoly
from ._utils import _get_zpk, _is_num_den, _is_zpk
[docs]def evalTF(tf, z):
"""Evaluates the rational function ``tf`` at the point(s)
given in ``z``.
**Parameters:**
tf : object
the LTI description of the CT system, which can be in one of the
following forms:
* an LTI object,
* a zpk tuple,
* a (num, den) tuple,
* an ABCD matrix (internally converted to zpk representation),
* a list-like containing the A, B, C, D matrices (also internally converted to zpk representation).
z : scalar or 1d ndarray
The z values for which ``tf`` is to be evaluated.
**Returns:**
tf(z) : scalar or 1d-ndarray
The result.
"""
# Original comment in deltasig:
# In Matlab 5, the ss/freqresp() function does nearly the same thing.
# in our case a transfer function is a scipy LTI object
if (hasattr(tf, 'inputs') and not tf.inputs == 1) or \
(hasattr(tf, 'outputs') and not tf.outputs == 1):
raise TypeError("Only SISO transfer functions can be evaluated.")
if hasattr(tf, 'num') and hasattr(tf, 'den'):
h = np.polyval(tf.num, z) / np.polyval(tf.den, z)
elif (hasattr(tf, 'zeros') and hasattr(tf, 'poles')):
# LTI objects have poles and zeros
zeros = tf.zeros
poles = tf.poles
k = tf.gain
h = k*evalRPoly(zeros, z)/evalRPoly(poles, z)
# we try not to convert the given representation to another one
elif _is_num_den(tf):
num, den = tf[0], tf[1]
h = np.polyval(num, z)/np.polyval(den, z)
elif _is_zpk(tf):
zeros, poles, k = tf
h = k*evalRPoly(zeros, z)/evalRPoly(poles, z)
else:
# ABCD and A, B, C, D will be converted through _utils
zeros, poles, k = _get_zpk(tf)
h = k*evalRPoly(zeros, z)/evalRPoly(poles, z)
return h