Bachelorarbeit/ConditionMonitoring/MLLinReg.cpp

#include "MLLinReg.h"
#include "SystemConfig.h"
#include <easylogging++.h>
#include <fstream>
#include <iomanip>

MLLinReg::MLLinReg(CappedStorage *storage) : MLAnalyzer(storage)
{
    criticalResidualCurrent = SystemConfig::getFloatConfigParameter("crit_residual_current");
    criticalTimeRangeSec =  SystemConfig::getIntConfigParameter("crit_residual_timerange") * SECONDS_IN_WEEK;

    Theta.resize(2, 1);
}



MLAlert MLLinReg::updateModel()
{
    if(t0 == 0 && data->getX().rows() != 0) {LOG(INFO) << std::setprecision(12) << std::fixed << "t_0 = " << (data->getX())(0, 1); t0 = (data->getX())(0, 1);}
    if(++updateCounter < updateRate)
        return MLAlert(CustomAlertTypes::NO_ALERT, "");
    updateCounter = 0;
    LOG(INFO) << "Update Linear Regression Model";
    normalEquation();
    bool error = checkCritical();

    if(error){
        //Return an alert object if tendency is critical
        std::stringstream ans;
        ans << "Received critical tendency in the next " << std::round(criticalTimeRangeSec/SECONDS_IN_WEEK) << " seconds";

        //LOG(INFO) << "Theta values: " << Theta(0) << "   " << Theta(1);
        //if(first){
        //    std::ofstream file;
        //    std::stringstream ss;
        //    file.open("debug_lin_reg.txt", std::ios::out);
        //    if(file.is_open()){
        //        file << std::setprecision(12) << std::fixed << "Theta: " << Theta(0) << "   " << Theta(1) << std::endl;
        //        file << std::setprecision(12) << std::fixed << "X: " << data->getX()(data->getX().rows()-1, 1) << std::endl;
        //        file << std::setprecision(12) << std::fixed << "y: " << data->getY()(data->getY().rows()-1) << std::endl;
        //        file << std::setprecision(12) << std::fixed << "t0: " << t0 << std::endl;
        //        file << std::setprecision(12) << std::fixed << std::endl;
        //        file.close();
        //    }
        //    first = false;
        //}
        return MLAlert(CustomAlertTypes::CRIT_RCM_TENDENCY, ans.str());
    }
    else
        return MLAlert(CustomAlertTypes::NO_ALERT, "");
}


bool MLLinReg::checkCritical(){
    //Check, if the critical value is reached within the specified time range
    if(data->getM() == 0)
        return false;
    //Offset, to avoid checking with little data and receive faulty results
    if(data->getM() < 100)
        return false;
    return (Theta(0) + Theta(1) * ((data->getX())((data->getX()).rows()-1, 1) + criticalTimeRangeSec))
            >= criticalResidualCurrent;
}


//Numerical approach to solve univariate Linear Regression Model
void MLLinReg::normalEquation() {
    Theta = Eigen::MatrixXd::Zero(2, 1);
    Theta = (data->getX().transpose() * data->getX()).inverse() * data->getX().transpose() * data->getY();
    if(data->getX().rows() > 500){
        LOG(INFO) << Theta(0) << "   " << Theta(1);
        LOG(INFO) << data->getX().rows();
    }
}