/// <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);
}
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
});
}