python/test/tf.py

   1 #!/usr/bin/env python
   2 import os, sys
   3
   4 sys.path.insert(0, os.getcwd())
   5 prefix = os.path.join(sys.path[0], "build")
   6 if not os.path.exists(prefix):
   7     os.mkdir(prefix)
   8 try:
   9     import liba as a
  10     import numpy as np
  11 except Exception as e:
  12     print(e)
  13     exit()
  14
  15
  16 class TF:
  17     def num_get(self):
  18         return self._num
  19
  20     def num_set(self, num):
  21         self._num = np.array(num, dtype=float)
  22         self.input = np.array(len(num) * [0.0], dtype=float)
  23
  24     num = property(num_get, num_set, None, None)
  25
  26     def den_get(self):
  27         return den
  28
  29     def den_set(self, den):
  30         self._den = np.array(den, dtype=float)
  31         self.output = np.array(len(den) * [0.0], dtype=float)
  32
  33     den = property(den_get, den_set, None, None)
  34
  35     def __init__(self, num, den):
  36         self.num = num
  37         self.den = den
  38
  39     def __call__(self, input: float) -> float:
  40         self.input = np.roll(self.input, 1)
  41         self.input[0] = input  # type: ignore
  42         output = self._num @ self.input - self._den @ self.output  # type: ignore
  43         self.output = np.roll(self.output, 1)
  44         self.output[0] = output  # type: ignore
  45         return output
  46
  47
  48 Ts = 0.001
  49 data = np.arange(0, 0.2, Ts)
  50
  51 try:
  52     import control.matlab as ct
  53
  54     sysc = ct.tf(133, [1, 25, 0])
  55     sysd = ct.c2d(sysc, Ts)
  56     print(sysc, sysd)
  57
  58     [[num]], [[den]] = ct.tfdata(sysd)
  59 except ModuleNotFoundError:
  60     num = [6.59492796e-05, 6.54019884e-05]
  61     den = [1.0, -1.97530991, 0.97530991]
  62 except Exception as e:
  63     print(e)
  64     exit()
  65
  66 tf = a.tf(num, den[1:])
  67 tf_ = TF(num, den[1:])
  68
  69 for t in data:
  70     t = t * 1000
  71     tf_(t)
  72     tf(t)
  73 print(tf_.num, tf_.den, tf_.input, tf_.output)
  74 print(tf.num, tf.den, tf.input, tf.output)