/// <summary>
/// Compute rigid motion using the singular value decomposition (SVD).
/// Returns the best transformation that moves X towards Y minimizing the mean squared error (MSE),
/// such that y = x*R + offset
/// </summary>
/// <param name="x">The list of source points (read-only)</param>
/// <param name="y">The list of destination points (read-only)</param>
/// <param name="R">The output rotation matrix (3x3)</param>
/// <param name="offset">The output offset (3D vector)</param>
public static void ComputeRigidMotion(List <Vector3> x, List <Vector3> y, out double[,] R, out double[] offset)
{
if (x.Count == 0)
{
// Extreme corner case
R = AMath.Matrix.Identity(3);
offset = new double[] { 0, 0, 0 };
return;
}
double[,] X = new double[x.Count, 3];
double[,] Y = new double[y.Count, 3];
for (int i = 0; i < x.Count; i++)
{
X[i, 0] = x[i][0];
X[i, 1] = x[i][1];
X[i, 2] = x[i][2];
Y[i, 0] = y[i][0];
Y[i, 1] = y[i][1];
Y[i, 2] = y[i][2];
}
var Xc = Accord.Statistics.Measures.Mean(X, 0);
var Yc = Accord.Statistics.Measures.Mean(Y, 0);
var H = AMath.Matrix.TransposeAndDot(AMath.Elementwise.Subtract(Y, Yc, 0), AMath.Elementwise.Subtract(X, Xc, 0));
var svd = new AMath.Decompositions.SingularValueDecomposition(H);
R = AMath.Matrix.DotWithTransposed(svd.RightSingularVectors, svd.LeftSingularVectors);
if (AMath.Matrix.Determinant(R) < 0) // Check whether the determinant is -1
{
// We have an improper rotation, i.e. a reflection transformation.
double[,] V = svd.RightSingularVectors;
V[0, 2] *= -1;
V[1, 2] *= -1;
V[2, 2] *= -1;
R = AMath.Matrix.DotWithTransposed(V, svd.LeftSingularVectors); // Now the determinant is +1
}
offset = AMath.Elementwise.Subtract(Yc, AMath.Matrix.Dot(Xc, R));
}
public override void Init(IRepository repository)
{
authorByRevision = repository.SelectionDSL()
.Commits().TillRevision(model.PredictionRelease)
.ToDictionary(x => x.Revision, x => x.Author);
int releaseRevisionOrderedNumber = repository.Queryable <Commit>()
.Single(x => x.Revision == model.PredictionRelease).OrderedNumber;
var codeByAuthorAndFile =
(
from cb in repository.Queryable <CodeBlock>()
join m in repository.Queryable <Modification>() on cb.ModificationID equals m.ID
join c in repository.Queryable <Commit>() on m.CommitID equals c.ID
join f in repository.Queryable <ProjectFile>() on m.FileID equals f.ID
where
cb.Size > 0
&&
c.OrderedNumber <= releaseRevisionOrderedNumber
group cb by new { Author = c.Author, FileID = f.ID } into g
select new
{
Author = g.Key.Author,
FileID = g.Key.FileID,
CodeSize = g.Sum(x => x.Size)
}
).ToArray();
var allFiles = model.AllFiles.Select(x => x.ID).ToArray();
var allAuthors = repository.SelectionDSL()
.Commits().TillRevision(model.PredictionRelease)
.Select(x => x.Author).Distinct().ToArray();
int numberOfFiles = allFiles.Count();
int numberOfAuthors = allAuthors.Count();
int numberOfEquations = numberOfFiles + numberOfAuthors + 1;
double[,] equations = new double[numberOfEquations, numberOfEquations];
double[] results = new double[numberOfEquations];
int equation = 0;
double locAdded = codeByAuthorAndFile.Sum(x => x.CodeSize);
for (int i = 0; i < allFiles.Length; i++)
{
double locAddedInFile = codeByAuthorAndFile
.Where(x => x.FileID == allFiles[i])
.Sum(x => x.CodeSize);
equations[numberOfEquations - 1, i] = locAddedInFile / locAdded;
equations[equation, i] = 1;
if (locAddedInFile > 0)
{
double dcd = repository.SelectionDSL()
.Commits()
.TillRevision(model.PredictionRelease)
.Files()
.IdIs(allFiles[i])
.Modifications().InCommits().InFiles()
.CodeBlocks().InModifications().CalculateDefectCodeDensity(model.PredictionRelease);
for (int j = 0; j < allAuthors.Length; j++)
{
double locAddedInFileByAuthor = codeByAuthorAndFile
.Where(x => x.FileID == allFiles[i] && x.Author == allAuthors[j])
.Sum(x => x.CodeSize);
equations[equation, numberOfFiles + j] = (locAddedInFileByAuthor / locAddedInFile);
}
results[equation] = dcd;
}
equation++;
}
for (int i = 0; i < allAuthors.Length; i++)
{
double locAddedByAuthor = codeByAuthorAndFile
.Where(x => x.Author == allAuthors[i])
.Sum(x => x.CodeSize);
equations[numberOfEquations - 1, numberOfFiles + i] = locAddedByAuthor / locAdded;
equations[equation, numberOfFiles + i] = 1;
if (locAddedByAuthor > 0)
{
double dcd = repository.SelectionDSL()
.Commits()
.AuthorIs(allAuthors[i])
.TillRevision(model.PredictionRelease)
.Modifications().InCommits()
.CodeBlocks().InModifications().CalculateDefectCodeDensity(model.PredictionRelease);
for (int j = 0; j < allFiles.Length; j++)
{
double locAddedByAuthorInFile = codeByAuthorAndFile
.Where(x => x.Author == allAuthors[i] && x.FileID == allFiles[j])
.Sum(x => x.CodeSize);
equations[equation, j] = (locAddedByAuthorInFile / locAddedByAuthor);
}
results[equation] = dcd;
}
equation++;
}
results[numberOfEquations - 1] = repository.SelectionDSL()
.Commits()
.TillRevision(model.PredictionRelease)
.Modifications().InCommits()
.CodeBlocks().InModifications().CalculateDefectCodeDensity(model.PredictionRelease);
int varCount = equations.GetUpperBound(1) + 1;
double[,] normalEquations = new double[varCount, varCount];
double[] normalResults = new double[varCount];
Func <double[, ], double[], int, int, double> nc = (e, r, n1, n2) =>
{
double sum = 0;
for (int i = 0; i < numberOfEquations; i++)
{
if (n2 < numberOfEquations)
{
sum += e[i, n1] * e[i, n2];
}
else
{
sum += e[i, n1] * r[i];
}
}
return(sum);
};
for (int i = 0; i < varCount; i++)
{
for (int j = 0; j < varCount; j++)
{
normalEquations[i, j] = nc(equations, results, i, j);
}
normalResults[i] = nc(equations, results, i, numberOfEquations);
}
var DCD = new Accord.Math.Decompositions.SingularValueDecomposition(normalEquations).Solve(normalResults);
DCDF = new Dictionary <int, double>();
DCDA = new Dictionary <string, double>();
double DCD_min = 0.001;
for (int i = 0; i < allFiles.Length; i++)
{
DCDF.Add(allFiles[i], DCD[i] > 0 ? DCD[i] : DCD_min);
}
for (int i = 0; i < allAuthors.Length; i++)
{
DCDA.Add(allAuthors[i], DCD[numberOfFiles + i] > 0 ? DCD[numberOfFiles + i] : DCD_min);
}
}
public override void Init(IRepositoryResolver repositories)
{
authorByRevision = repositories.SelectionDSL()
.Commits().TillRevision(model.PredictionRelease)
.ToDictionary(x => x.Revision, x => x.Author);
int releaseRevisionOrderedNumber = repositories.Repository<Commit>()
.Single(x => x.Revision == model.PredictionRelease).OrderedNumber;
var codeByAuthorAndFile =
(
from cb in repositories.Repository<CodeBlock>()
join m in repositories.Repository<Modification>() on cb.ModificationID equals m.ID
join c in repositories.Repository<Commit>() on m.CommitID equals c.ID
join f in repositories.Repository<ProjectFile>() on m.FileID equals f.ID
where
cb.Size > 0
&&
c.OrderedNumber <= releaseRevisionOrderedNumber
group cb by new { Author = c.Author, FileID = f.ID } into g
select new
{
Author = g.Key.Author,
FileID = g.Key.FileID,
CodeSize = g.Sum(x => x.Size)
}
).ToArray();
var allFiles = model.AllFiles.Select(x => x.ID).ToArray();
var allAuthors = repositories.SelectionDSL()
.Commits().TillRevision(model.PredictionRelease)
.Select(x => x.Author).Distinct().ToArray();
int numberOfFiles = allFiles.Count();
int numberOfAuthors = allAuthors.Count();
int numberOfEquations = numberOfFiles + numberOfAuthors + 1;
double[,] equations = new double[numberOfEquations,numberOfEquations];
double[] results = new double[numberOfEquations];
int equation = 0;
double locAdded = codeByAuthorAndFile.Sum(x => x.CodeSize);
for (int i = 0; i < allFiles.Length; i++)
{
double locAddedInFile = codeByAuthorAndFile
.Where(x => x.FileID == allFiles[i])
.Sum(x => x.CodeSize);
equations[numberOfEquations-1, i] = locAddedInFile / locAdded;
equations[equation, i] = 1;
if (locAddedInFile > 0)
{
double dcd = repositories.SelectionDSL()
.Commits()
.TillRevision(model.PredictionRelease)
.Files()
.IdIs(allFiles[i])
.Modifications().InCommits().InFiles()
.CodeBlocks().InModifications().CalculateDefectCodeDensity(model.PredictionRelease);
for (int j = 0; j < allAuthors.Length; j++)
{
double locAddedInFileByAuthor = codeByAuthorAndFile
.Where(x => x.FileID == allFiles[i] && x.Author == allAuthors[j])
.Sum(x => x.CodeSize);
equations[equation, numberOfFiles + j] = (locAddedInFileByAuthor / locAddedInFile);
}
results[equation] = dcd;
}
equation++;
}
for (int i = 0; i < allAuthors.Length; i++)
{
double locAddedByAuthor = codeByAuthorAndFile
.Where(x => x.Author == allAuthors[i])
.Sum(x => x.CodeSize);
equations[numberOfEquations-1, numberOfFiles + i] = locAddedByAuthor / locAdded;
equations[equation, numberOfFiles + i] = 1;
if (locAddedByAuthor > 0)
{
double dcd = repositories.SelectionDSL()
.Commits()
.AuthorIs(allAuthors[i])
.TillRevision(model.PredictionRelease)
.Modifications().InCommits()
.CodeBlocks().InModifications().CalculateDefectCodeDensity(model.PredictionRelease);
for (int j = 0; j < allFiles.Length; j++)
{
double locAddedByAuthorInFile = codeByAuthorAndFile
.Where(x => x.Author == allAuthors[i] && x.FileID == allFiles[j])
.Sum(x => x.CodeSize);
equations[equation, j] = (locAddedByAuthorInFile / locAddedByAuthor);
}
results[equation] = dcd;
}
equation++;
}
results[numberOfEquations-1] = repositories.SelectionDSL()
.Commits()
.TillRevision(model.PredictionRelease)
.Modifications().InCommits()
.CodeBlocks().InModifications().CalculateDefectCodeDensity(model.PredictionRelease);
int varCount = equations.GetUpperBound(1)+1;
double[,] normalEquations = new double[varCount, varCount];
double[] normalResults = new double[varCount];
Func<double[,],double[],int,int,double> nc = (e, r, n1, n2) =>
{
double sum = 0;
for (int i = 0; i < numberOfEquations; i++)
{
if (n2 < numberOfEquations)
{
sum += e[i,n1] * e[i,n2];
}
else
{
sum += e[i,n1] * r[i];
}
}
return sum;
};
for (int i = 0; i < varCount; i++)
{
for (int j = 0; j < varCount; j++)
{
normalEquations[i,j] = nc(equations,results,i,j);
}
normalResults[i] = nc(equations,results,i,numberOfEquations);
}
var DCD = new Accord.Math.Decompositions.SingularValueDecomposition(normalEquations).Solve(normalResults);
DCDF = new Dictionary<int,double>();
DCDA = new Dictionary<string,double>();
double DCD_min = 0.001;
for (int i = 0; i < allFiles.Length; i++)
{
DCDF.Add(allFiles[i], DCD[i] > 0 ? DCD[i] : DCD_min);
}
for (int i = 0; i < allAuthors.Length; i++)
{
DCDA.Add(allAuthors[i], DCD[numberOfFiles + i] > 0 ? DCD[numberOfFiles + i] : DCD_min);
}
}
private static void svdUsingAccord(double[,] matrix)
{
var svdd = new Accord.Math.Decompositions.SingularValueDecomposition(matrix);
//svd.U() * svd.W() * svd.VT()
}
