test/src/TestDiffFilter.cpp

   1 /* Copyright_License {
   2
   3  XCSoar Glide Computer - http://www.xcsoar.org/
   4  Copyright (C) 2000-2013 The XCSoar Project
   5  A detailed list of copyright holders can be found in the file "AUTHORS".
   6
   7  This program is free software; you can redistribute it and/or
   8  modify it under the terms of the GNU General Public License
   9  as published by the Free Software Foundation; either version 2
  10  of the License, or (at your option) any later version.
  11
  12  This program is distributed in the hope that it will be useful,
  13  but WITHOUT ANY WARRANTY; without even the implied warranty of
  14  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  15  GNU General Public License for more details.
  16
  17  You should have received a copy of the GNU General Public License
  18  along with this program; if not, write to the Free Software
  19  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.
  20  }
  21  */
  22
  23 #include "Math/DiffFilter.hpp"
  24 #include "TestUtil.hpp"
  25
  26 #include <cstdio>
  27
  28 int
  29 main(int argc, char **argv)
  30 {
  31   plan_tests(192 + 232 + 40);
  32
  33   DiffFilter df(fixed(0));
  34
  35   // Test steady-state response scaling
  36   for (long dY = 1; dY <= 10000000; dY *= 10) {
  37     df.Reset();
  38     for (int Y = dY; Y < 30 * dY; Y += dY) {
  39       if (Y < 6 * dY)
  40         // Give the filter time to calm down before testing for steady state
  41         df.Update(fixed(Y));
  42       else {
  43         // test if the filter response is close enough to dX
  44         //
  45         // the discrete filter design results in steady-state error
  46         // of approximately 3.4507 percent
  47         fixed error = fabs((df.Update(fixed(Y)) - fixed(dY)) / dY);
  48         ok1(error < fixed(0.035));
  49       }
  50     }
  51   }
  52
  53   // Test steady-state response scaling with reset(0, dX) call
  54   for (long dY = 1; dY <= 10000000; dY *= 10) {
  55     df.Reset(fixed(0), fixed(dY));
  56     for (int Y = dY; Y < 30 * dY; Y += dY) {
  57       // test if the filter response is close enough to dX
  58       //
  59       // the discrete filter design results in steady-state error
  60       // of approximately 3.4507 percent
  61       fixed error = fabs((df.Update(fixed(Y)) - fixed(dY)) / dY);
  62       ok1(error < fixed(0.035));
  63     }
  64   }
  65
  66   df.Reset();
  67   fixed p = fixed_two_pi / fixed(10);
  68   for (int X = 0; X < 50; X += 1) {
  69     // Y = sin(2 * pi * (X/10)
  70     fixed Y = fixed(sin(p * X));
  71
  72     fixed dY_shifted = fixed(cos(p * (X - 3))) * p;
  73     fixed dY_filter = df.Update(fixed(Y));
  74     fixed error = fabs(dY_filter - dY_shifted);
  75     if (X >= 10)
  76       ok1(error < fixed(0.05));
  77   }
  78
  79   return exit_status();
  80 }