embeddedLibrary/test/test_dataAcquisition.c

#include <stdio.h>
#include <stdlib.h>
#include <assert.h>
#include <math.h>
#include "../include/dataAcquisition.h"

#define TEST_NUMBER 18

#define NUMBER_OF_SENSORS 5
#define SLIDING_WINDOW_SIZE 10

#define AVERAGE_UNCERTAINTY 0.01
#define STD_UNCERTAINTY 0.01

#define M_PI 3.14159265358979323846

#define NORMAL_DISTRIBUTION_MEAN 10.0
#define NORMAL_DISTRIBUTION_STDDEV 2.0

// Testing the initialization and the instantiation of the sensors' number and sliding window size for uniform distribution
void test_initializeReadings_uniform()
{
    initializeReadings(NUMBER_OF_SENSORS, SLIDING_WINDOW_SIZE);
    assert(getSensorsNumber() == NUMBER_OF_SENSORS);
    assert(getSlidingWindowSize() == SLIDING_WINDOW_SIZE);
}

// Testing the logic of add readings to see if the sliding window is full for uniform distribution
void test_addReading_uniform()
{
    for (int sensor = 0; sensor < NUMBER_OF_SENSORS; sensor++)
    {
        for (int value = 1; value <= SLIDING_WINDOW_SIZE; value++)
        {
            addReading(value, sensor);
        }
    }
    assert(isFull(NUMBER_OF_SENSORS - 1) == true); // Assuming the last sensor acquired the data
}

// Testing the logic of average methods for uniform distribution
void test_averageOnSensor_uniform()
{
    //printf("Average on sensor %d: %f\n", NUMBER_OF_SENSORS - 1, getAverageOnSensor(NUMBER_OF_SENSORS - 1));
    float average = getAverageOnSensor(NUMBER_OF_SENSORS - 1);
    float expected_average = (SLIDING_WINDOW_SIZE + 1) / 2.0;
    assert(fabs(average - expected_average) < AVERAGE_UNCERTAINTY);
}

void test_standardDeviationOnSensor_uniform()
{
    //printf("Standard deviation on sensor %d: %f\n", NUMBER_OF_SENSORS - 1, getStandardDeviationOnSensor(NUMBER_OF_SENSORS - 1));
    float standard_deviation = getStandardDeviationOnSensor(NUMBER_OF_SENSORS - 1);
    float expected_standard_deviation = 2.872281323269;
    assert(fabs(standard_deviation - expected_standard_deviation) < STD_UNCERTAINTY);
}

void test_averageOnAllSensors_uniform()
{
    //printf("Average on all sensors: %f\n", getAverageOnAllSensors());
    float average = getAverageOnAllSensors();
    float expected_average = SLIDING_WINDOW_SIZE;
    assert(fabs(average - expected_average) < AVERAGE_UNCERTAINTY);
}

void test_standardDeviationOnAllSensors_uniform()
{
    //printf("Standard deviation on all sensors: %f\n", getStandardDeviationOnAllSensors());
    float standard_deviation = getStandardDeviationOnAllSensors();
    float expected_standard_deviation = 0;
    assert(fabs(standard_deviation - expected_standard_deviation) < STD_UNCERTAINTY);
}

void test_overallAverage_uniform()
{
    //printf("Overall average on all sensors: %f\n", getOverallAverage());
    float average = getOverallAverage();
    float expected_overall_average = (SLIDING_WINDOW_SIZE + 1) / 2.0;
    assert(fabs(average - expected_overall_average) < AVERAGE_UNCERTAINTY);
}

void test_overallStandardDeviation_uniform()
{
    //printf("Overall standard deviation: %f\n", getOverallStandardDeviation());
    float standard_deviation = getStandardDeviationOnSensor(NUMBER_OF_SENSORS - 1);
    float expected_standard_deviation = 2.872281323269;
    assert(fabs(standard_deviation - expected_standard_deviation) < STD_UNCERTAINTY);
}

void test_anomalyDetect_uniform()
{
    float average = getOverallAverage();
    float standard_deviation = getOverallStandardDeviation();
    anomalyDetect(average, standard_deviation);
    //printf("Outlier count: %i\n", getOutlierCount());
    assert(fabs(getOutlierCount() - 0) < 0.01);

    // Adding an outlier
    addReading(20, NUMBER_OF_SENSORS - 1);
    average = getOverallAverage();
    standard_deviation = getOverallStandardDeviation();
    anomalyDetect(average, standard_deviation);
    //printf("Outlier count: %i\n", getOutlierCount());
    assert(fabs(getOutlierCount() - 1) < 0.01);
}

void test_freeReadings()
{
    assert(freeReadings() == true);
}

// TODO: Test all the functions with a normal distribution

// TODO: Evaluate the normal distribution with the anomaly detection

void test_initializeReadings_normal()
{
    initializeReadings(NUMBER_OF_SENSORS, SLIDING_WINDOW_SIZE);
    assert(getSensorsNumber() == NUMBER_OF_SENSORS);
    assert(getSlidingWindowSize() == SLIDING_WINDOW_SIZE);
}

void test_addReading_normal()
{

    for (int sensor = 0; sensor < NUMBER_OF_SENSORS; sensor++)
    {
        for (int i = 0; i < SLIDING_WINDOW_SIZE; i++)
        {
            float u1 = (float)rand() / RAND_MAX;
            float u2 = (float)rand() / RAND_MAX;
            float z0 = sqrt(-2.0 * log(u1)) * cos(2.0 * M_PI * u2);
            float value = NORMAL_DISTRIBUTION_MEAN + z0 * NORMAL_DISTRIBUTION_STDDEV;
            addReading(value, sensor);
        }
    }
    assert(isFull(NUMBER_OF_SENSORS - 1) == true); // Assuming the last sensor acquired the data
}

void test_averageOnSensor_normal()
{
    //printf("Average on sensor %d: %f\n", NUMBER_OF_SENSORS - 1, getAverageOnSensor(NUMBER_OF_SENSORS - 1));
    float average = getAverageOnSensor(NUMBER_OF_SENSORS - 1);
    assert(fabs(average - NORMAL_DISTRIBUTION_MEAN) < AVERAGE_UNCERTAINTY * 50);
}

void test_standardDeviationOnSensor_normal()
{
    //printf("Standard deviation on sensor %d: %f\n", NUMBER_OF_SENSORS - 1, getStandardDeviationOnSensor(NUMBER_OF_SENSORS - 1));
    float standard_deviation = getStandardDeviationOnSensor(NUMBER_OF_SENSORS - 1);
    assert(fabs(standard_deviation - NORMAL_DISTRIBUTION_STDDEV) < STD_UNCERTAINTY * 50);
}

void test_averageOnAllSensors_normal()
{
    //printf("Average on all sensors: %f\n", getAverageOnAllSensors());
    float average = getAverageOnAllSensors();
    assert(fabs(average - NORMAL_DISTRIBUTION_MEAN) < AVERAGE_UNCERTAINTY * 50);
}

void test_standardDeviationOnAllSensors_normal()
{
    //printf("Standard deviation on all sensors: %f\n", getStandardDeviationOnAllSensors());
    float standard_deviation = getStandardDeviationOnAllSensors();
    assert(fabs(standard_deviation - NORMAL_DISTRIBUTION_STDDEV) < STD_UNCERTAINTY * 50);
}

void test_overallAverage_normal()
{
    //printf("Overall average on all sensors: %f\n", getOverallAverage());
    float average = getOverallAverage();
    assert(fabs(average - NORMAL_DISTRIBUTION_MEAN) < AVERAGE_UNCERTAINTY * 50);
}

void test_overallStandardDeviation_normal()
{
    //printf("Overall standard deviation: %f\n", getOverallStandardDeviation());
    float standard_deviation = getStandardDeviationOnSensor(NUMBER_OF_SENSORS - 1);
    assert(fabs(standard_deviation - NORMAL_DISTRIBUTION_STDDEV) < STD_UNCERTAINTY * 50);
}

void test_anomalyDetect_normal()
{
    float average = getOverallAverage();
    float standard_deviation = getOverallStandardDeviation();
    anomalyDetect(average, standard_deviation);
    //printf("Outlier count: %i\n", getOutlierCount());
    assert(fabs(NUMBER_OF_SENSORS * SLIDING_WINDOW_SIZE * 0.05 >= getOutlierCount())); // Assuming 5% of the data is outliers

    // Adding an outlier
    addReading(NORMAL_DISTRIBUTION_MEAN * 100, NUMBER_OF_SENSORS - 1);
    average = getOverallAverage();
    standard_deviation = getOverallStandardDeviation();
    anomalyDetect(average, standard_deviation);
    //printf("Outlier count: %i\n", getOutlierCount());
    assert(fabs(NUMBER_OF_SENSORS * SLIDING_WINDOW_SIZE * 0.05 + 1 >= getOutlierCount())); // Assuming 5% of the data is outliers and adding one more
}

int main() {
    int tests_run = 0;
    int tests_passed = 0;
    
    printf("=== Test Suite ===\n");
    
    #define RUN_TEST(test) do { \
        printf("Progress: %.2f%%, Running %s...", (tests_run / (float)TEST_NUMBER) * 100, #test); \
        test(); \
        tests_run++; \
        tests_passed++; \
        printf("OK\n"); \
    } while(0)
    
    srand(42);
    
    RUN_TEST(test_initializeReadings_uniform);
    RUN_TEST(test_addReading_uniform);
    RUN_TEST(test_averageOnSensor_uniform);
    RUN_TEST(test_standardDeviationOnSensor_uniform);
    RUN_TEST(test_averageOnAllSensors_uniform);
    RUN_TEST(test_standardDeviationOnAllSensors_uniform);
    RUN_TEST(test_overallAverage_uniform);
    RUN_TEST(test_overallStandardDeviation_uniform);
    RUN_TEST(test_anomalyDetect_uniform);
    RUN_TEST(test_addReading_normal);
    RUN_TEST(test_averageOnSensor_normal);
    RUN_TEST(test_standardDeviationOnSensor_normal);
    RUN_TEST(test_averageOnAllSensors_normal);
    RUN_TEST(test_standardDeviationOnAllSensors_normal);
    RUN_TEST(test_overallAverage_normal);
    RUN_TEST(test_overallStandardDeviation_normal);
    RUN_TEST(test_anomalyDetect_normal);
    RUN_TEST(test_freeReadings);

    printf("\n=== Results ===\n");
    printf("Tests run: %d\n", tests_run);
    printf("Tests passed: %d\n", tests_passed);
    printf("Test coverage: %.2f%%\n", (tests_passed / (float)tests_run) * 100);
    return 0;
}