IOT_healthdata_shift_detection/CVM-TS-SD-EWMA.cpp at main · Harsh-git98/IOT_healthdata_shift_detection · GitHub

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#include<iostream>
#include<vector>
#include <algorithm>
#include <cmath>
#include <fstream>
#include <sstream>

using namespace std;
# define BETA 0.1
# define lamda 0.08
# define zeta 0.01
#define L 3
#define m 20
struct CSVRow {
    int column1;
    int column2;
    int column3;
};
// 55 90 170

CSVRow parseCSV(const string& line) {
    CSVRow row;
    stringstream ss(line);
    char comma; // to read the comma
    ss >> row.column1 >> comma >> row.column2 >> comma >> row.column3;
    return row;
}
double calculatecvmstatistics(const vector<double>& fx) {
    int n = fx.size();

    double cvmstat = 0.0;

    for (int i = 0; i < n; ++i) {
        double x = fx[i];
        double y = static_cast<double>(i + 1) / n;
        cvmstat += pow(x - y, 2);
    }

    cvmstat /= n;

    return cvmstat;
}


int main()
{
   string filename = "data.csv";

    ifstream file(filename);


    if (!file.is_open()) {
        cerr << "Error opening file: " << filename << endl;
        return 1;
    }

    double time[200]={0};
    double heartbeat[200]={0};
    double num[200]={0};

    string line;
    int p=0;
    while (getline(file, line)) {

        CSVRow row = parseCSV(line);
        num[p]=row.column1;
        time[p]=row.column2;
        heartbeat[p]=row.column3;
        p++;

    }


    file.close();


    // training phase for 50
    double mean=0;
    for(int i=0;i<5;i++)
    {
        mean=heartbeat[i]+mean;

    }
    mean=mean/5;
    double z[200]={0};
    z[0]=mean;
    double error[200]={0};
    for(int i=1;i<=5;i++)
    {
        z[i]=lamda*heartbeat[i]+(1-lamda)*z[i-1];
        error[i]=heartbeat[i]-z[i-1];
    }


    double variance=0;

    for(int i=1;i<5;i++)
    {
        variance=variance+(error[i]*error[i])/5;
    }


    double var[200]={0};
    var[5]=variance;
    double ucl[200]={0};
    double lcl[200]={0};

    for(int i=6;i<200;i++)
    {
        z[i]=lamda*heartbeat[i]+(1-lamda)*z[i-1];
        error[i]=abs(heartbeat[i]-z[i-1]);
        var[i]=abs(zeta*error[i]*error[i]+(1-zeta)*var[i-1]);
        ucl[i]=z[i-1]+L*abs((abs(var[i-1])));
        lcl[i]=z[i-1]-L*abs((abs(var[i-1])));

        if(heartbeat[i]>lcl[i] && heartbeat[i]<ucl[i])
        {
            continue;
        }
        else{


            vector<double> f1;
            vector<double> f2;
            for(int j=i-(m-1);j<i;j++)
            {
                f1.push_back(heartbeat[j]);
            }
            for(int j=i+1;j<i+m;j++)
            {
                f2.push_back(heartbeat[j]);
            }
            sort(f1.begin(),f1.end());
            sort(f2.begin(),f2.end());
            double f1ans= calculatecvmstatistics(f1);

            double f2ans=calculatecvmstatistics(f2);

            double diff=abs(f1ans-f2ans);
            cout<<f1ans<<" "<<f2ans<<" "<<diff<<" "<<f1ans*0.05<<" "<<f2ans*0.05<<endl;


            if(diff<0.05*f1ans || diff<0.05*f2ans){
            cout<<"covariate shift is found at time:"<<time[i]<<endl;
            }
            else{
                cout<<"covariate detected and rejected at time:"<<time[i]<<endl;
            }

        }
    }
    for(int i=0;i<200;i++)
    {
        cout<<time[i]<<" "<<heartbeat[i]<<" "<<error[i]<<" "<<var[i]<<" "<<z[i]<<" "<<ucl[i]<<" "<<lcl[i]<<" "<<endl;
    }


}