private void button6_Click(object sender, EventArgs e)
{
var percent = double.Parse(this.maskedTextBox3.Text) / 100;
_nnEndIndexAk = Convert.ToInt32(this._acer.Count * percent);
_nnEndIndexQk = Convert.ToInt32(this._quercus.Count * percent);
var k = int.Parse(this.textBox9.Text);
var inputs = this._acer.GetRange(0, _nnEndIndexAk).Concat(this._quercus.GetRange(0, _nnEndIndexQk)).ToArray();
var outputs = this._acer.GetRange(0, _nnEndIndexAk).Select(_ => 0)
.Concat(this._quercus.GetRange(0, _nnEndIndexQk).Select(_ => 1)).ToArray();
this.knnClassifier = new KnnClassifier(k, 2, inputs, outputs, Distance.Euclidean);
}
private Coordinate Positioning_Knn(List <AdjustedFingerprinting> fingerprintings)
{
/* run the knn classifier on the data */
KnnClassifier classifier = new KnnClassifier();
/* After fetching and processing the fingerprinting data, I am able to get the class count.
* Basically, each of the reference point is a class to be classified to. */
int numClasses = IndoorPositioningClient.GetPoints(environment.EnvironmentId).Count;
int gatewayCount = fingerprintings[0].RssiValueAndGateway.Count;
/* get the Rssi values of the beacon in question from the server */
RssiValue[] rssiValues = IndoorPositioningClient.GetRssi(gatewayCount);
/* we will use also gateway count on the area as K constant */
Coordinate coordinate = classifier.Classify(rssiValues, fingerprintings, numClasses, 3);
return(coordinate);
}
private Coordinate Positioning_KnnProximity(List <AdjustedFingerprinting> fingerprintings)
{
int k = 3;
/* run the knn classifier on the data */
KnnClassifier classifier = new KnnClassifier();
/* After fetching and processing the fingerprinting data, I am able to get the class count.
* Basically, each of the reference point is a class to be classified to. */
int numClasses = IndoorPositioningClient.GetPoints(environment.EnvironmentId).Count;
int gatewayCount = fingerprintings[0].RssiValueAndGateway.Count;
/* get the Rssi values of the beacon in question from the server */
RssiValue[] rssiValues = IndoorPositioningClient.GetRssi(gatewayCount);
/* we will use also gateway count on the area as K constant */
CoordinateAndDistance[] cooDist = classifier.GetNearestNeighbors(rssiValues, fingerprintings, numClasses, k);
Coordinate coordinateFirstAndSecondLine = new Coordinate();
Coordinate coordinateFirstAndThirdLine = new Coordinate();
Coordinate coordinateSecondAndThirdLine = new Coordinate();
/* Create a vector from the coordinates */
/* Measure the first point of crossing the first and second line*/
DoubleMatrix matrixFirstAndSecondLine = new DoubleMatrix(new double[, ]
{
{
cooDist[0].coordinate.Xaxis - cooDist[1].coordinate.Xaxis,
cooDist[0].coordinate.Yaxis - cooDist[1].coordinate.Yaxis
},
{
cooDist[0].coordinate.Xaxis - cooDist[2].coordinate.Xaxis,
cooDist[0].coordinate.Yaxis - cooDist[2].coordinate.Yaxis
}
});
/* If the determinant value of the matrix is 0, it means this matrix cannot be inverted.
* We can have the exact point values with one of the reference points. */
if (NMathFunctions.Determinant(matrixFirstAndSecondLine) == 0)
{
return(classifier.Vote(cooDist, fingerprintings, numClasses, k));
}
//matrixFirstAndSecondLine = matrixFirstAndSecondLine.Transform((p) => p * 2);
DoubleMatrix inversedMatrixFirstAndSecondLine = NMathFunctions.Inverse(matrixFirstAndSecondLine);
DoubleVector vectorFirstAndSecondLine = new DoubleVector(new double[]
{
cooDist[0].coordinate.GetNormPow() - cooDist[1].coordinate.GetNormPow() - cooDist[0].GetDistPow() + cooDist[1].GetDistPow(),
cooDist[0].coordinate.GetNormPow() - cooDist[2].coordinate.GetNormPow() - cooDist[0].GetDistPow() + cooDist[2].GetDistPow()
});
vectorFirstAndSecondLine = vectorFirstAndSecondLine.Transform((p) => p / 2);
DoubleVector coordinateVectorFirstAndSecondLine = NMathFunctions.Product(inversedMatrixFirstAndSecondLine,
vectorFirstAndSecondLine);
coordinateFirstAndSecondLine.Xaxis = (int)coordinateVectorFirstAndSecondLine[0];
coordinateFirstAndSecondLine.Yaxis = (int)coordinateVectorFirstAndSecondLine[1];
/* Measure the first point of crossing the first and third line*/
DoubleMatrix matrixFirstAndThirdLine = new DoubleMatrix(new double[, ]
{
{
cooDist[0].coordinate.Xaxis - cooDist[1].coordinate.Xaxis,
cooDist[0].coordinate.Yaxis - cooDist[1].coordinate.Yaxis
},
{
cooDist[1].coordinate.Xaxis - cooDist[2].coordinate.Xaxis,
cooDist[1].coordinate.Yaxis - cooDist[2].coordinate.Yaxis
}
});
/* If the determinant value of the matrix is 0, it means this matrix cannot be inverted.
* We can have the exact point values with one of the reference points. */
if (NMathFunctions.Determinant(matrixFirstAndThirdLine) == 0)
{
return(classifier.Vote(cooDist, fingerprintings, numClasses, k));
}
//matrixFirstAndThirdLine = matrixFirstAndThirdLine.Transform((p) => p * 2);
DoubleMatrix inversedMatrixFirstAndThirdLine = NMathFunctions.Inverse(matrixFirstAndThirdLine);
DoubleVector vectorFirstAndThirdLine = new DoubleVector(new double[]
{
cooDist[0].coordinate.GetNormPow() - cooDist[1].coordinate.GetNormPow() - cooDist[0].GetDistPow() + cooDist[1].GetDistPow(),
cooDist[1].coordinate.GetNormPow() - cooDist[2].coordinate.GetNormPow() - cooDist[1].GetDistPow() + cooDist[2].GetDistPow()
});
vectorFirstAndThirdLine = vectorFirstAndThirdLine.Transform((p) => p / 2);
DoubleVector coordinateVectorFirstAndThirdLine = NMathFunctions.Product(inversedMatrixFirstAndThirdLine,
vectorFirstAndThirdLine);
coordinateFirstAndThirdLine.Xaxis = (int)coordinateVectorFirstAndThirdLine[0];
coordinateFirstAndThirdLine.Yaxis = (int)coordinateVectorFirstAndThirdLine[1];
/* Measure the first point of crossing the first and third line*/
DoubleMatrix matrixSecondAndThirdLine = new DoubleMatrix(new double[, ]
{
{
cooDist[0].coordinate.Xaxis - cooDist[2].coordinate.Xaxis,
cooDist[0].coordinate.Yaxis - cooDist[2].coordinate.Yaxis
},
{
cooDist[1].coordinate.Xaxis - cooDist[2].coordinate.Xaxis,
cooDist[1].coordinate.Yaxis - cooDist[2].coordinate.Yaxis
}
});
/* If the determinant value of the matrix is 0, it means this matrix cannot be inverted.
* We can have the exact point values with one of the reference points. */
if (NMathFunctions.Determinant(matrixSecondAndThirdLine) == 0)
{
return(classifier.Vote(cooDist, fingerprintings, numClasses, k));
}
//matrixSecondAndThirdLine = matrixSecondAndThirdLine.Transform((p) => p * 2);
DoubleMatrix inversedMatrixSecondAndThirdLine = NMathFunctions.Inverse(matrixSecondAndThirdLine);
DoubleVector vectorSecondAndThirdLine = new DoubleVector(new double[]
{
cooDist[0].coordinate.GetNormPow() - cooDist[2].coordinate.GetNormPow() - cooDist[0].GetDistPow() + cooDist[2].GetDistPow(),
cooDist[1].coordinate.GetNormPow() - cooDist[2].coordinate.GetNormPow() - cooDist[1].GetDistPow() + cooDist[2].GetDistPow()
});
vectorSecondAndThirdLine = vectorSecondAndThirdLine.Transform((p) => p / 2);
DoubleVector coordinateVectorSecondAndThirdLine = NMathFunctions.Product(inversedMatrixSecondAndThirdLine,
vectorSecondAndThirdLine);
coordinateSecondAndThirdLine.Xaxis = (int)coordinateVectorSecondAndThirdLine[0];
coordinateSecondAndThirdLine.Yaxis = (int)coordinateVectorSecondAndThirdLine[1];
//DoubleMatrix matrixFirstAndThirdLine = new DoubleMatrix(new double[,]
//{
// {
// cooDist[0].coordinate.Xaxis - cooDist[1].coordinate.Xaxis,
// cooDist[0].coordinate.Yaxis - cooDist[1].coordinate.Yaxis
// },
// {
// cooDist[0].coordinate.Xaxis - cooDist[2].coordinate.Xaxis,
// cooDist[0].coordinate.Yaxis - cooDist[2].coordinate.Yaxis
// },
// {
// cooDist[1].coordinate.Xaxis - cooDist[2].coordinate.Xaxis,
// cooDist[1].coordinate.Yaxis - cooDist[2].coordinate.Yaxis
// }
//});
//DoubleMatrix inversedMatrix = NMathFunctions.Inverse(matrix);
//DoubleVector vector = new DoubleVector(new double[]
//{
// cooDist[0].coordinate.GetNormPow() - cooDist[1].coordinate.GetNormPow() - cooDist[0].GetDistPow() + cooDist[1].GetDistPow(),
// cooDist[0].coordinate.GetNormPow() - cooDist[2].coordinate.GetNormPow() - cooDist[0].GetDistPow() + cooDist[2].GetDistPow(),
// cooDist[1].coordinate.GetNormPow() - cooDist[2].coordinate.GetNormPow() - cooDist[1].GetDistPow() + cooDist[2].GetDistPow()
//});
//DoubleVector coordinateVector = NMathFunctions.Product(inversedMatrix, vector);
//coordinate.Xaxis = (int)coordinateVector[0];
//coordinate.Xaxis = (int)coordinateVector[1];
//Matrix linesMatrix = new Matrix(
// cooDist[0].coordinate.Xaxis - cooDist[1].coordinate.Xaxis,
// cooDist[0].coordinate.Yaxis - cooDist[1].coordinate.Yaxis,
// cooDist[0].coordinate.Xaxis - cooDist[2].coordinate.Xaxis,
// cooDist[0].coordinate.Yaxis - cooDist[2].coordinate.Yaxis,
// cooDist[1].coordinate.Xaxis - cooDist[2].coordinate.Xaxis,
// cooDist[1].coordinate.Yaxis - cooDist[2].coordinate.Yaxis);
////Vector distances = new Vector(
//// coordinateAndDistances[0].coordinate.Xaxis - coordinateAndDistances[1].coordinate.Xaxis,);
int xaxis =
(coordinateFirstAndSecondLine.Xaxis +
coordinateFirstAndThirdLine.Xaxis +
coordinateSecondAndThirdLine.Xaxis) / 3;
int yaxis =
(coordinateFirstAndSecondLine.Yaxis +
coordinateFirstAndThirdLine.Yaxis +
coordinateSecondAndThirdLine.Yaxis) / 3;
Debug.WriteLine("Xaxis:" + xaxis);
Debug.WriteLine("Yaxis:" + yaxis);
return(new Coordinate()
{
Xaxis = xaxis,
Yaxis = yaxis
});
}
