public static YCbCr ConvertRgbtoYCbCr(RGB pixel)
{
DoubleVector rgbMatrix = new DoubleVector(pixel.GetAsArray());
DoubleVector yCbCrMatrix =
DoubleVector.Add(NMathFunctions.Product(_conversionMatrix, rgbMatrix), _prefixMatrix);
yCbCrMatrix = DoubleVector.Subtract(yCbCrMatrix, _offsetMatrix);
return(new YCbCr((int)(yCbCrMatrix[0] + 0.5),
(int)(yCbCrMatrix[1] + 0.5),
(int)(yCbCrMatrix[2] + 0.5)));
}
/// <summary>
/// 奇异值分解 singular value decomposition
/// </summary>
public static void DoSvd()
{
Utility.Status("Creating SVD");
// 源文件数, 源文件中所有独特词数目, 源文件-索引, 源文件单词-索引
int totalNumberOfSourceFiles = TfDictionary.Count;
int totalDistinctTermsInAllSourceFiles = IdfDictionary.Count;
Dictionary <string, int> allSourceFilesWithIndex = TfDictionary.Keys.Select((x, index) => new { Name = x, Index = index }).ToDictionary(x => x.Name, x => x.Index);
Dictionary <string, int> allSourceWordsWithIndex = IdfDictionary.Keys.Select((x, index) => new { Name = x, Index = index }).ToDictionary(x => x.Name, x => x.Index);
// 源码矩阵 行数: 源码中单词数, 源文件数
double[,] sourceMatrix = new double[totalDistinctTermsInAllSourceFiles, totalNumberOfSourceFiles];
foreach (var fileNameWithTfDictionary in TfDictionary)
{
// 文件索引
int fileIndex = allSourceFilesWithIndex[fileNameWithTfDictionary.Key];
foreach (var fileWordWithTf in fileNameWithTfDictionary.Value)
{
sourceMatrix[allSourceWordsWithIndex[fileWordWithTf.Key], fileIndex] = fileWordWithTf.Value;
}
}
// 创建矩阵
DoubleMatrix generalMatrix = new DoubleMatrix(sourceMatrix);
// 奇异值分解 A = U S V.T
var svd = new DoubleSVDecomp(generalMatrix);
_uk = new Dictionary <int, DoubleMatrix>();
_sk = new Dictionary <int, DoubleMatrix>();
_vkTranspose = new Dictionary <int, DoubleMatrix>();
Utility.LsiKs.Where(x => x <= svd.Cols).ToList().ForEach(k =>
{
// 创建k维矩阵
Utility.Status("Creating k matrix of size " + k);
DoubleMatrix U = svd.LeftVectors;
DoubleMatrix V = svd.RightVectors;
// 通过数组创建矩阵, 行优先存储, 可再改
_uk.Add(k, Utility.GetDimMatrix(U, U.Rows, k));
_sk.Add(k, Utility.GetDiagonal(svd.SingularValues, k));
_vkTranspose.Add(k, NMathFunctions.Transpose(Utility.GetDimMatrix(V, V.Rows, k)));
});
}
/// <summary>
/// 计算 LSI 方法
/// </summary>
/// <param name="outputFolderPath"></param>
/// <param name="bugName"></param>
/// <param name="queryText"></param>
public static void ComputeLsi(string outputFolderPath, string bugName, List <string> queryText)
{
Utility.Status("Creating LSI: " + bugName);
// 所有源码中的总独特词数 源文件 - 索引, 源文件单词 - 索引
int totalDistinctTermsInAllSourceFiles = IdfDictionary.Count;
Dictionary <string, int> allSourceFilesWithIndex = TfDictionary.Keys.Select((x, index) => new { Name = x, Index = index }).ToDictionary(x => x.Name, x => x.Index);
Dictionary <string, int> allSourceWordsWithIndex = IdfDictionary.Keys.Select((x, index) => new { Name = x, Index = index }).ToDictionary(x => x.Name, x => x.Index);
// 为查询创建一个 1xm 的向量
double[,] queryMatrixTranspose = new double[1, totalDistinctTermsInAllSourceFiles];
queryText.ForEach(queryWord =>
{
if (allSourceWordsWithIndex.ContainsKey(queryWord))
{
queryMatrixTranspose[0, allSourceWordsWithIndex[queryWord]] = queryMatrixTranspose[0, allSourceWordsWithIndex[queryWord]] + 1;
}
});
// k列的 U 矩阵
var ks = _uk.Keys.Where(x => !File.Exists(outputFolderPath + LsiOutputFolderName + x + ".txt")).ToList();
// 为每个维度的矩阵计算相似度
foreach (var k in ks)
{
Utility.Status("Creating LSI for " + bugName + " where k=" + k);
var uk = _uk[k];
var sk = _sk[k];
var vkTranspose = _vkTranspose[k];
DoubleMatrix q = new DoubleMatrix(queryMatrixTranspose);
//qv = q * uk * sk.I [1xm,mxn,nxn = 1xn]
DoubleMatrix qv = NMathFunctions.Product(q, uk);
qv = NMathFunctions.Product(qv, NMathFunctions.Inverse(sk));
List <double> qDoubles = qv.Row(0).ToArray().ToList();
var similarityList = allSourceFilesWithIndex.Select(doc => new KeyValuePair <string, double>(doc.Key, Utility.GetSimilarity(qDoubles, vkTranspose.Col(doc.Value).ToArray().ToList())));
File.WriteAllLines(outputFolderPath + LsiOutputFolderName + k + ".txt", similarityList.OrderByDescending(x => x.Value).Select(x => x.Key + " " + x.Value.ToString("##.00000")));
}
Utility.Status("Completed LSI: " + bugName);
}
public static DoubleMatrix Advanced(DoubleMatrix x)
{
return(NMathFunctions.Product(NMathFunctions.Product(A, x), At));
}
private DoubleHermitianMatrix Create_SOIP_Matrix(Direction p, Direction dV, Direction sigma, double k, int nx, int ny)
{
DoubleHermitianMatrix result = new DoubleHermitianMatrix(2 * nx * ny);
double theta;
Band_Data dV_data;
if (dV == Direction.x)
{
dV_data = dV_x;
theta = theta_x;
}
else if (dV == Direction.y)
{
dV_data = dV_y;
theta = theta_y;
}
else if (dV == Direction.z)
{
dV_data = new Band_Data(nx, ny, 0.0);
theta = 0.0;
}
else
{
throw new Exception("Error - It's completely impossible to get here");
}
if (p == Direction.x)
{
if (sigma == Direction.x)
{
throw new InvalidArgumentException("Error - no spin-orbit interaction between p_x and sigma_x");
}
else if (sigma == Direction.y)
{
throw new NotImplementedException();
}
else if (sigma == Direction.z)
{
for (int i = 0; i < nx; i++)
{
for (int j = 0; j < ny; j++)
{
// off-diagonal couplings in x backward
if (i != 0)
{
// for up -> up
result[i * ny + j, i *ny + j - ny] = NMathFunctions.Exp(-1.0 * I * theta * dV_data.mat[i, j]) * tx;
// for down -> down
result[i * ny + j + nx * ny, i *ny + j - ny + nx * ny] = NMathFunctions.Exp(I * theta * dV_data.mat[i, j]) * tx;
}
// off-diagonal couplings in x forward
if (i != nx - 1)
{
// for up -> up
result[i * ny + j, i *ny + j + ny] = NMathFunctions.Exp(-1.0 * I * theta * dV_data.mat[i, j]) * tx;
// for down -> down
result[i * ny + j + nx * ny, i *ny + j + ny + nx * ny] = NMathFunctions.Exp(I * theta * dV_data.mat[i, j]) * tx;
}
// and diagonal couplings
result[i * ny + j, i *ny + j] = -2.0 * Math.Cos(theta * dV_data.mat[i, j]) * tx;
result[i * ny + j + nx * ny, i *ny + j + nx * ny] = -2.0 * Math.Cos(theta * dV_data.mat[i, j]) * tx;
}
}
}
else
{
throw new Exception("Error - It's completely impossible to get here");
}
}
else if (p == Direction.y)
{
if (sigma == Direction.x)
{
throw new NotImplementedException();
}
else if (sigma == Direction.y)
{
throw new InvalidArgumentException("Error - no spin-orbit interaction between p_y and sigma_y");
}
else if (sigma == Direction.z)
{
for (int i = 0; i < nx; i++)
{
for (int j = 0; j < ny; j++)
{
// off-diagonal couplings in y backward
if (j != 0)
{
// for up -> up
result[i * ny + j, i *ny + j - 1] = NMathFunctions.Exp(-1.0 * I * theta * dV_data.mat[i, j]) * ty;
// for down -> down
result[i * ny + j + nx * ny, i *ny + j - 1 + nx * ny] = NMathFunctions.Exp(I * theta * dV_data.mat[i, j]) * ty;
}
// off-diagonal couplings in y forward
if (j != ny - 1)
{
// for up -> up
result[i * ny + j, i *ny + j + 1] = NMathFunctions.Exp(-1.0 * I * theta * dV_data.mat[i, j]) * ty;
// for down -> down
result[i * ny + j + nx * ny, i *ny + j + 1 + nx * ny] = NMathFunctions.Exp(I * theta * dV_data.mat[i, j]) * ty;
}
// and diagonal couplings
result[i * ny + j, i *ny + j] = -2.0 * Math.Cos(theta * dV_data.mat[i, j]) * ty;
result[i * ny + j + nx * ny, i *ny + j + nx * ny] = -2.0 * Math.Cos(theta * dV_data.mat[i, j]) * ty;
}
}
}
else
{
throw new Exception("Error - It's completely impossible to get here");
}
}
else if (p == Direction.z)
{
throw new NotImplementedException("Error - at the moment, when momentum is in the direction of the wire, you should use a different method");
}
else
{
throw new Exception("Error - It's completely impossible to get here");
}
return(result);
}
public double LibaryConditinalNumber()
{
return(NMathFunctions.ConditionNumber(NMathFunctions.TransposeProduct(Matrix, Matrix), NormType.OneNorm));
}
public DoubleVector Solve(DoubleVector v)
{
return(NMathFunctions.Solve(Matrix, v));
}
public double ComputeNormAgainst(DoubleVector b, DoubleVector xRes)
{
return(new DoubleVector(b - NMathFunctions.Product(Matrix, xRes)).TwoNorm());
}
DoubleComplexMatrix Product(DoubleComplexMatrix A, DoubleComplexMatrix B)
{
return(NMathFunctions.Product(A, B));
}
DoubleComplexMatrix Product(DoubleHermitianMatrix A, DoubleComplexMatrix B)
{
return(new DoubleComplexMatrix(NMathFunctions.Product(MatrixFunctions.ToGeneralMatrix(A), B)));
}
private Coordinate Positioning_Proximity()
{
List <Gateway> gateways = IndoorPositioningClient.GetGateways();
/* get the Rssi values of the beacon in question from the server */
RssiValue[] rssiValues = IndoorPositioningClient.GetRssi(gateways.Count);
CoordinateAndDistance[] cooDist = new CoordinateAndDistance[gateways.Count];
for (int i = 0; i < gateways.Count; i++)
{
cooDist[i] = new CoordinateAndDistance()
{
coordinate = new Coordinate()
{
Xaxis = (int)GetGatewayXaxis(gateways[i]),
Yaxis = (int)GetGatewayYaxis(gateways[i]),
},
dist = rssiValues[i].Rssi
};
}
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(cooDist[0].coordinate);
}
//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(cooDist[0].coordinate);
}
//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(cooDist[0].coordinate);
}
//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];
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
});
}
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
});
}
