fsfw/contrib/fsfw_contrib/etl-20.39.4/test/test_pseudo_moving_average.cpp

/******************************************************************************
The MIT License(MIT)

Embedded Template Library.
https://github.com/ETLCPP/etl
https://www.etlcpp.com

Copyright(c) 2018 John Wellbelove

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#include "unit_test_framework.h"

#include <array>
#include <algorithm>

#include "etl/pseudo_moving_average.h"
#include "etl/scaled_rounding.h"

namespace
{
  const size_t SAMPLE_SIZE = 10UL;
  const size_t SCALING = 100UL;

  SUITE(test_pseudo_moving_average)
  {
    //*************************************************************************
    TEST(integral_signed_average_positive)
    {
      using PMA = etl::pseudo_moving_average<int, SAMPLE_SIZE, SCALING>;
      PMA cma(0);

      CHECK_EQUAL(0, cma.value());

      cma.add(9);
      cma.add(1);
      cma.add(8);
      cma.add(2);
      cma.add(7);
      cma.add(3);
      cma.add(6);
      cma.add(4);
      cma.add(5);

      CHECK_EQUAL(280, cma.value());
    }

    //*************************************************************************
    TEST(integral_signed_average_positive_via_iterator)
    {
      std::array<int, 9> data{ 9, 1, 8, 2, 7, 3, 6, 4, 5 };

      using PMA = etl::pseudo_moving_average<int, SAMPLE_SIZE, SCALING>;
      PMA cma(0);

      CHECK_EQUAL(0, cma.value());

      std::copy(data.begin(), data.end(), cma.input());

      CHECK_EQUAL(280, cma.value());
    }

    //*************************************************************************
    TEST(integral_signed_average_negative)
    {
      using PMA = etl::pseudo_moving_average<int, SAMPLE_SIZE, SCALING>;
      PMA cma(0);

      CHECK_EQUAL(0, cma.value());

      cma.add(-9);
      cma.add(-1);
      cma.add(-8);
      cma.add(-2);
      cma.add(-7);
      cma.add(-3);
      cma.add(-6);
      cma.add(-4);
      cma.add(-5);

      CHECK_EQUAL(-280, cma.value());
    }

    //*************************************************************************
    TEST(integral_signed_average_negative_via_iterator)
    {
      std::array<int, 9> data{ -9, -1, -8, -2, -7, -3, -6, -4, -5 };

      using PMA = etl::pseudo_moving_average<int, SAMPLE_SIZE, SCALING>;
      PMA cma(0);

      CHECK_EQUAL(0, cma.value());

      std::copy(data.begin(), data.end(), cma.input());

      CHECK_EQUAL(-280, cma.value());
    }

    //*************************************************************************
    TEST(integral_unsigned_average_positive)
    {
      using PMA = etl::pseudo_moving_average<unsigned int, SAMPLE_SIZE, SCALING>;
      PMA cma(0U);

      CHECK_EQUAL(0U, cma.value());

      cma.add(9U);
      cma.add(1U);
      cma.add(8U);
      cma.add(2U);
      cma.add(7U);
      cma.add(3U);
      cma.add(6U);
      cma.add(4U);
      cma.add(5U);

      CHECK_EQUAL(280U, cma.value());
    }

    //*************************************************************************
    TEST(integral_unsigned_average_positive_via_iterator)
    {
      std::array<unsigned int, 9> data{ 9U, 1U, 8U, 2U, 7U, 3U, 6U, 4U, 5U };

      using PMA = etl::pseudo_moving_average<unsigned int, SAMPLE_SIZE, SCALING>;
      PMA cma(0U);

      CHECK_EQUAL(0U, cma.value());

      std::copy(data.begin(), data.end(), cma.input());

      CHECK_EQUAL(280U, cma.value());
    }

    //*************************************************************************
    TEST(integral_signed_average_positive_runtime_sample_size)
    {
      using PMA = etl::pseudo_moving_average<int, 0U, SCALING>;
      PMA cma(0, SAMPLE_SIZE * 2U);

      CHECK_EQUAL(0, cma.value());

      cma.set_sample_size(SAMPLE_SIZE);

      cma.add(9);
      cma.add(1);
      cma.add(8);
      cma.add(2);
      cma.add(7);
      cma.add(3);
      cma.add(6);
      cma.add(4);
      cma.add(5);

      CHECK_EQUAL(280, cma.value());
    }

    //*************************************************************************
    TEST(integral_signed_average_positive_runtime_sample_size_via_iterator)
    {
      std::array<int, 9> data{ 9, 1, 8, 2, 7, 3, 6, 4, 5 };

      using PMA = etl::pseudo_moving_average<int, 0U, SCALING>;
      PMA cma(0, SAMPLE_SIZE * 2U);

      CHECK_EQUAL(0, cma.value());

      cma.set_sample_size(SAMPLE_SIZE);

      std::copy(data.begin(), data.end(), cma.input());

      CHECK_EQUAL(280, cma.value());
    }

    //*************************************************************************
    TEST(integral_signed_average_negative_runtime_sample_size)
    {
      using PMA = etl::pseudo_moving_average<int, 0U, SCALING>;
      PMA cma(0, SAMPLE_SIZE * 2U);

      CHECK_EQUAL(0, cma.value());

      cma.set_sample_size(SAMPLE_SIZE);

      cma.add(-9);
      cma.add(-1);
      cma.add(-8);
      cma.add(-2);
      cma.add(-7);
      cma.add(-3);
      cma.add(-6);
      cma.add(-4);
      cma.add(-5);

      CHECK_EQUAL(-280, cma.value());
    }

    //*************************************************************************
    TEST(integral_signed_average_negative_runtime_sample_size_via_iterator)
    {
      std::array<int, 9> data{ -9, -1, -8, -2, -7, -3, -6, -4, -5 };

      using PMA = etl::pseudo_moving_average<int, 0U, SCALING>;
      PMA cma(0, SAMPLE_SIZE * 2U);

      CHECK_EQUAL(0, cma.value());

      cma.set_sample_size(SAMPLE_SIZE);

      std::copy(data.begin(), data.end(), cma.input());

      CHECK_EQUAL(-280, cma.value());
    }

    //*************************************************************************
    TEST(integral_unsigned_average_positive_runtime_sample_size)
    {
      using PMA = etl::pseudo_moving_average<unsigned int, 0U, SCALING>;
      PMA cma(0U, SAMPLE_SIZE * 2U);

      CHECK_EQUAL(0U, cma.value());

      cma.set_sample_size(SAMPLE_SIZE);

      cma.add(9U);
      cma.add(1U);
      cma.add(8U);
      cma.add(2U);
      cma.add(7U);
      cma.add(3U);
      cma.add(6U);
      cma.add(4U);
      cma.add(5U);

      CHECK_EQUAL(280U, cma.value());
    }

    //*************************************************************************
    TEST(integral_unsigned_average_positive_runtime_sample_size_via_iterator)
    {
      std::array<unsigned int, 9> data{ 9U, 1U, 8U, 2U, 7U, 3U, 6U, 4U, 5U };

      using PMA = etl::pseudo_moving_average<int, 0U, SCALING>;
      PMA cma(0U, SAMPLE_SIZE * 2U);

      CHECK_EQUAL(0U, cma.value());

      cma.set_sample_size(SAMPLE_SIZE);

      std::copy(data.begin(), data.end(), cma.input());

      CHECK_EQUAL(280U, cma.value());
    }

    //*************************************************************************
    TEST(floating_point_average)
    {
      using PMA = etl::pseudo_moving_average<double, SAMPLE_SIZE>;
      PMA cma(0);

      CHECK_EQUAL(0.0, cma.value());

      cma.add(9.0);
      cma.add(1.0);
      cma.add(8.0);
      cma.add(2.0);
      cma.add(7.0);
      cma.add(3.0);
      cma.add(6.0);
      cma.add(4.0);
      cma.add(5.0);

      CHECK_CLOSE(2.82, cma.value(), 0.01);
    }

    //*************************************************************************
    TEST(floating_point_average_via_iterator)
    {
      std::array<double, 9> data{ 9.0, 1.0, 8.0, 2.0, 7.0, 3.0, 6.0, 4.0, 5.0 };

      using PMA = etl::pseudo_moving_average<double, SAMPLE_SIZE>;
      PMA cma(0);

      CHECK_EQUAL(0.0, cma.value());

      std::copy(data.begin(), data.end(), cma.input());

      CHECK_CLOSE(2.82, cma.value(), 0.01);
    }

    //*************************************************************************
    TEST(floating_point_average_runtime_sample_size)
    {
      using PMA = etl::pseudo_moving_average<double, 0U>;
      PMA cma(0, SAMPLE_SIZE * 2);

      CHECK_EQUAL(0.0, cma.value());

      cma.set_sample_size(SAMPLE_SIZE);

      cma.add(9.0);
      cma.add(1.0);
      cma.add(8.0);
      cma.add(2.0);
      cma.add(7.0);
      cma.add(3.0);
      cma.add(6.0);
      cma.add(4.0);
      cma.add(5.0);

      CHECK_CLOSE(2.82, cma.value(), 0.01);
    }

    //*************************************************************************
    TEST(floating_point_average_runtime_sample_size_via_iterator)
    {
      std::array<double, 9> data{ 9.0, 1.0, 8.0, 2.0, 7.0, 3.0, 6.0, 4.0, 5.0 };

      using PMA = etl::pseudo_moving_average<double, 0U>;
      PMA cma(0, SAMPLE_SIZE * 2);

      CHECK_EQUAL(0.0, cma.value());

      cma.set_sample_size(SAMPLE_SIZE);

      std::copy(data.begin(), data.end(), cma.input());

      CHECK_CLOSE(2.82, cma.value(), 0.01);
    }
  };
}