diff --git a/hit2023v2/eventbuilder.cpp b/hit2023v2/eventbuilder.cpp
index 999da26..224759f 100644
--- a/hit2023v2/eventbuilder.cpp
+++ b/hit2023v2/eventbuilder.cpp
@@ -64,7 +64,7 @@ void EventBuilder::onNewData(DataReceiver* receiver)
         //1. Background subtraction.
 
         frame_counter++;
-
+/*
         while (frame_counter<10000){
             for (unsigned int dev_nr = 0; dev_nr < nrReceivers; dev_nr++){
                 for (unsigned int ch = 0; ch < channelCounts[dev_nr]; ch++)
@@ -84,7 +84,7 @@ void EventBuilder::onNewData(DataReceiver* receiver)
                 currentFrame[dev_nr].sensor_data[ch]-=backgroundFrame[dev_nr].sensor_data[ch] ;
             }
         }
-
+*/
 
 
         lastFrameMutex.lock();
@@ -108,13 +108,13 @@ void EventBuilder::onNewData(DataReceiver* receiver)
 
         //log data
         if (loggingData) logDataToFile();
-        //HIT_ANALYSE_V2 hit_analyse_v2;//create the object
-       // QString dataString = hit_analyse_v2.analyseBeamData(currentFrame);
-
+        HIT_ANALYSE_V2 hit_analyse_v2;//create the object
+        QString dataString = hit_analyse_v2.analyseBeamData(currentFrame);
+        std::cerr << dataString.toStdString() << std::endl;
         // Call sendData method of the UDP server
-        QString dataString = QString::number(intensity) + ',' + QString::number(position) + ',' + QString::number(focus);
-        QByteArray data = dataString.toUtf8();
-        udpServer.sendData(data);
+       // QString dataString = QString::number(intensity) + ',' + QString::number(position) + ',' + QString::number(focus);
+        //QByteArray data = dataString.toUtf8();
+       // udpServer.sendData(data);
 
     }
 
diff --git a/hit2023v2/hit_analyse_v2.cpp b/hit2023v2/hit_analyse_v2.cpp
index 6a096f4..41a7874 100644
--- a/hit2023v2/hit_analyse_v2.cpp
+++ b/hit2023v2/hit_analyse_v2.cpp
@@ -8,6 +8,32 @@ HIT_ANALYSE_V2::HIT_ANALYSE_V2(QObject *parent) : QObject(parent)
 
 }
 
+// Define your own functions for matrix operations
+struct Matrix2x2 {
+    double data[2][2];
+};
+
+Matrix2x2 InvertMatrix2x2(const Matrix2x2& mat) {
+    Matrix2x2 result;
+    double det = mat.data[0][0] * mat.data[1][1] - mat.data[0][1] * mat.data[1][0];
+    if (det != 0.0) {
+        double invDet = 1.0 / det;
+        result.data[0][0] = mat.data[1][1] * invDet;
+        result.data[0][1] = -mat.data[0][1] * invDet;
+        result.data[1][0] = -mat.data[1][0] * invDet;
+        result.data[1][1] = mat.data[0][0] * invDet;
+    } else {
+        // Handle the case when the matrix is not invertible
+        // You might want to implement error handling here.
+        std::cerr << "Matrix not invertible! " << std::endl;
+    }
+    return result;
+}
+
+struct Vector2 {
+    double data[2];
+};
+
 QString HIT_ANALYSE_V2::analyseBeamData(QVector<BufferData> dataframe){
 
     double position=0.1;
@@ -20,7 +46,8 @@ QString HIT_ANALYSE_V2::analyseBeamData(QVector<BufferData> dataframe){
 
     std::vector<double> signal_list(vector_length);
     std::vector<double> channel_list(vector_length);
-
+    std::vector<double> short_signal_list;
+    std::vector<double> short_channel_list;
 
     // Create a random number generator with a Gaussian distribution
     std::random_device rd;
@@ -31,20 +58,24 @@ QString HIT_ANALYSE_V2::analyseBeamData(QVector<BufferData> dataframe){
     std::vector<short int> result(vector_length);
 
     // Fill the vector with random values
-    for (int i = 0; i < vector_length; ++i) {
-        result[i] = static_cast<short int>(dist(gen));
-        signal_list.push_back(result[i]);
-        channel_list.push_back(i);
+    for (int i = 0; i < vector_length; i++) {
+        double randomValue = dist(gen);
+        result[i] = static_cast<short int>(std::round(randomValue));
+        signal_list[i] = result[i];
+        channel_list[i] = i;
+        //std::cerr << vector_length<< " " << channel_list[i] << " " << signal_list[i] <<std::endl;
+
     }
     //add a gaussian profile, focus is FWHM, position is random between 50 and 250
     position = 50 + (rand() % (int)(250 - 50 + 1));
-    for  (int i = 0; i < vector_length; ++i) {
+    for  (int i = 0; i < vector_length; i++) {
         signal_list[i] += intensity*exp(-4*log(2)*pow((channel_list[i]-position)/focus,2));
+      //  std::cerr << vector_length<< " " << channel_list[i] << " " << signal_list[i] <<std::endl;
     }
 
 
 
-
+/*
     // Fill signal_list and channel_list with your data
 
     double SumT = 0.0, SumS = 0.0, SumS2 = 0.0, SumST = 0.0, SumT2 = 0.0, SumY = 0.0, SumYS = 0.0, SumYT = 0.0;
@@ -138,6 +169,151 @@ QString HIT_ANALYSE_V2::analyseBeamData(QVector<BufferData> dataframe){
     //sigma = sqrt(1.0 / (2.0 * ABC_0));
     focus = 2.3548/sqrt(2*p);
     intensity = b;
+*/
+    double SumArea = 0.0, SumY2 = 0.0, SumXY2 = 0.0, SumX2Y2 = 0.0, SumX3Y2 = 0.0;
+    double SumY2LnY = 0.0, SumXY2LnY = 0.0, Ymax = 0.0, Pomax = 0.0;
+    double fac_c = 0.0, Yn = 0.0, sigma = 0.0, amp = 0.0;
+    double SumYYP = 0.0, SumYYM = 0.0, MeanY = 0.0, window_start = 0.0, window_end = 0.0;
+
+    // ...
+
+    Matrix2x2 M1, M1inv;
+    Vector2 ABC, M2;
+
+    for (int i = 0; i < vector_length; i++) {
+        if (signal_list[i] > Ymax) {
+            Ymax = signal_list[i];
+            Pomax = channel_list[i];
+        }
+        if (i > 0 && signal_list[i] > 20) {
+            SumArea += signal_list[i] * (channel_list[i] - channel_list[i - 1]);
+        }
+    }
+
+    // Estimate sigma
+    sigma = SumArea / Ymax / 2.5066;
+
+    // Set a +-3 sigma window
+    window_start = Pomax - 3 * sigma;
+    window_end = Pomax + 3 * sigma;
+ //   std::cerr<< Pomax << " " << Ymax <<  " " << sigma << std::endl;
+
+
+    for (int i = 0; i < vector_length; i++) {
+        if (signal_list[i] > 20 && channel_list[i] > window_start && channel_list[i] < window_end) {
+            short_signal_list.push_back(signal_list[i]);
+            short_channel_list.push_back(channel_list[i]);
+        }
+    }
+    signal_list.clear();
+    channel_list.clear();
+    // Recalculate SumArea using the sieved data
+    SumArea = 0.0;
+    for (int i = 1; i < short_signal_list.size(); i++) {
+        SumArea += short_signal_list[i] * (short_channel_list[i] - short_channel_list[i - 1]);
+    }
+
+
+    const int shortlist_length = short_channel_list.size();
+
+    if (shortlist_length <= 3) {
+        intensity = -1;
+        focus = -1;
+        position = -128;
+        dataString += QString::number(intensity) + ',' + QString::number(position) + ',' + QString::number(focus)
+                      + ',' + QString::number(0);
+
+
+        return dataString;
+    }
+
+    // Re-Estimate sigma
+    sigma = SumArea / Ymax / 2.5066;
+    fac_c = -1.0 / (2.0 * sigma * sigma);
+   // std::cerr << sigma << std::endl;
+    for(int k=0; k<shortlist_length;k++){
+
+        SumY2 += short_signal_list[k]*short_signal_list[k];
+        SumXY2 += short_signal_list[k]*short_signal_list[k]*short_channel_list[k];
+        SumX2Y2 +=  short_signal_list[k]*short_signal_list[k]*short_channel_list[k]*short_channel_list[k];
+        SumX3Y2 +=  short_signal_list[k]*short_signal_list[k]*short_channel_list[k]*short_channel_list[k]*short_channel_list[k];
+
+        SumY2LnY += short_signal_list[k]*short_signal_list[k]*log(short_signal_list[k]);
+        SumXY2LnY += short_channel_list[k]*short_signal_list[k]*short_signal_list[k]*log(short_signal_list[k]);
+      //  std::cerr<< shortlist_length << " " << short_channel_list[k] << " " << short_signal_list[k] << " " << short_signal_list[k] << " " << log(short_signal_list[k]) << std::endl;
+        MeanY+=short_signal_list[k];
+    }
+    MeanY/=shortlist_length;
+
+    // Use custom matrix and vector functions for calculations
+    M1.data[0][0] = SumY2;
+    M1.data[0][1] = SumXY2;
+    M1.data[1][0] = SumXY2;
+    M1.data[1][1] = SumX2Y2;
+
+  //  std::cerr << M1.data[0][0]  << " " << M1.data[0][1] << " " << M1.data[1][0] << " " << M1.data[1][1] << std::endl;
+    M2.data[0] = SumY2LnY - fac_c * SumX2Y2;
+    M2.data[1] = SumXY2LnY - fac_c * SumX3Y2;
+  //  std::cerr << M2.data[0] << " " << M2.data[1]  << std::endl;
+    M1inv = InvertMatrix2x2(M1);
+    ABC.data[0] = M1inv.data[0][0] * M2.data[0] + M1inv.data[0][1] * M2.data[1];
+    ABC.data[1] = M1inv.data[1][0] * M2.data[0] + M1inv.data[1][1] * M2.data[1];
+
+   // std::cerr << ABC.data[0]  << " " << ABC.data[1] << std::endl;
+
+
+//iterate to improve the fit.
+    int N_iter = 1;
+    for (int i = 0; i < N_iter; i++) {
+        SumY2 = 0.0;
+        SumXY2 = 0.0;
+        SumX2Y2 = 0.0;
+        SumX3Y2 = 0.0;
+        SumY2LnY = 0.0;
+        SumXY2LnY = 0.0;
+
+        for (int k = 0; k < shortlist_length; k++) {
+            Yn = exp(ABC.data[0] + ABC.data[1] * short_channel_list[k] + fac_c * short_channel_list[k] * short_channel_list[k]);
+            SumY2 += Yn * Yn;
+            SumXY2 += Yn * Yn * short_channel_list[k];
+            SumX2Y2 += Yn * Yn * short_channel_list[k] * short_channel_list[k];
+            SumX3Y2 += Yn * Yn * short_channel_list[k] * short_channel_list[k] * short_channel_list[k];
+            SumY2LnY += Yn * Yn * log(short_signal_list[k]);
+            SumXY2LnY += short_channel_list[k] * Yn * Yn * log(short_signal_list[k]);
+        }
+
+        M1.data[0][0] = SumY2;
+        M1.data[0][1] = SumXY2;
+        M1.data[1][0] = SumXY2;
+        M1.data[1][1] = SumX2Y2;
+
+        M2.data[0] = SumY2LnY - fac_c * SumX2Y2;
+        M2.data[1] = SumXY2LnY - fac_c * SumX3Y2;
+
+        M1inv = InvertMatrix2x2(M1);
+        ABC.data[0] = M1inv.data[0][0] * M2.data[0] + M1inv.data[0][1] * M2.data[1];
+        ABC.data[1] = M1inv.data[1][0] * M2.data[0] + M1inv.data[1][1] * M2.data[1];
+    }
+
+    position = -ABC.data[1]/fac_c/2;
+
+    amp = exp(ABC.data[0]-ABC.data[1]*ABC.data[1]/4/fac_c);
+
+    sigma=SumArea/amp/2.5066;
+
+    // cout << sigma << " " << mean << " " << amp << endl;
+
+
+    for(int k=0; k<shortlist_length;k++){
+        SumYYM+= (short_signal_list[k]-MeanY)*(short_signal_list[k]-MeanY);
+        SumYYP+= (amp*exp(-(short_channel_list[k]-position)*(short_channel_list[k]-position)/2/(sigma*sigma)) - MeanY )*(amp*exp(-(short_channel_list[k]-position)*(short_channel_list[k]-position)/2/(sigma*sigma)) - MeanY );
+    }
+
+
+
+    focus = 2.3548*sigma;
+    intensity = amp;
+    double R_squared = SumYYP/SumYYM;
 
     dataString += QString::number(intensity) + ',' + QString::number(position) + ',' + QString::number(focus)
                          + ',' + QString::number(R_squared);
@@ -148,6 +324,8 @@ QString HIT_ANALYSE_V2::analyseBeamData(QVector<BufferData> dataframe){
 
 }
 
+
+
 HIT_ANALYSE_V2::~HIT_ANALYSE_V2()
 {
 
diff --git a/hit2023v2/release/hit2023v2.exe b/hit2023v2/release/hit2023v2.exe
index 68d2eed..cc5b417 100644
Binary files a/hit2023v2/release/hit2023v2.exe and b/hit2023v2/release/hit2023v2.exe differ