本文整理汇总了C#中System.Matrix.GetTranspose方法的典型用法代码示例。如果您正苦于以下问题：C# Matrix.GetTranspose方法的具体用法？C# Matrix.GetTranspose怎么用？C# Matrix.GetTranspose使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类System.Matrix的用法示例。
在下文中一共展示了Matrix.GetTranspose方法的6个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C#代码示例。
示例1: SimulateLiberalStageTwo
private static Matrix SimulateLiberalStageTwo(Matrix M, Matrix EA1, Matrix C, Matrix D, Matrix JC, double br)
{
Matrix JCC = JC * C;
Matrix DC = D * C;
int n = M.Rows;
Matrix AM = M * EA1;
Matrix R = new Matrix(n);
for (int i = 0; i < R.Rows; ++i)
for (int j = 0; j < R.Cols; ++j)
if (i != j && (M[i, j] > 0 || AM[i, j] > 0))
R[i, j] = 1;
else
R[i, j] = 0;
Matrix EE = M * M;
Matrix BEE = new Matrix(n);
for (int i = 0; i < R.Rows; ++i)
for (int j = 0; j < R.Cols; ++j)
if (i != j && EE[i, j] > 0)
BEE[i, j] = 1;
else
BEE[i, j] = 0;
Matrix CR = R * C;
Vector AO = new Vector(n);
for (int i = 0; i < AO.Size; ++i)
{
double sum = br * (CR.GetRowSum(i) - C[i, i]);
if (sum <= C[i, i])
AO[i] = 0;
else
AO[i] = sum;
}
Matrix F = Matrix.Ones(n, n);
F.SetDiagonalFromVector(Vector.Zero(n));
Matrix PAN = (F - R) * C;
Matrix PAC = BEE * C;
Matrix EA = Matrix.Zero(n, n);
UpdateEAMatrix(AO, DC, EA);
UpdateEAMatrix(AO, PAC, EA);
UpdateEAMatrix(AO, PAN, EA);
UpdateEAMatrix(AO, JCC, EA);
Matrix BEA = new Matrix(n);
for (int i = 0; i < n; ++i)
for (int j = 0; j < n; ++j)
BEA[i, j] = EA[i, j] < double.Epsilon ? 0 : 1;
Matrix BEAT = BEA.GetTranspose();
AO.Clear();
PAC.Clear();
EA.Clear();
DC.Clear();
return (BEA + BEAT) / 2;
}示例2: SimulateLiberalStageOne
private static Matrix SimulateLiberalStageOne(SymmetricBinaryMatrix G, Matrix C, Matrix R, Vector P, Matrix D, Matrix JC, double br)
{
Matrix DC = D * C;
Matrix JCC = JC * C;
int n = C.Rows;
if (R == null)
{
R = new Matrix(n);
for (int i = 0; i < R.Rows; ++i)
for (int j = 0; j < R.Cols; ++j)
if (G.GetValue(i, j) || P[i] == 1 || P[j] == 1)
R[i, j] = 1;
else
R[i, j] = 0;
}
Matrix CR = R * C;
Vector AO = new Vector(n);
for (int i = 0; i < AO.Size; ++i)
{
if (Algorithms.MaxValue<double>(CR.GetRowEnumerator(i)) <= 0.0)
AO[i] = 0;
else
AO[i] = br * (CR.GetRowSum(i) - C[i, i] );
}
Matrix F = Matrix.Ones(n, n);
F.SetDiagonalFromVector(Vector.Zero(n));
Matrix PAN = (F - R) * C;
Matrix EA = Matrix.Zero(n, n);
UpdateEAMatrix(AO, DC, EA);
UpdateEAMatrix(AO, PAN, EA);
UpdateEAMatrix(AO, JCC, EA);
Matrix BEA = new Matrix(n);
for (int i = 0; i < n; ++i)
for (int j = 0; j < n; ++j)
BEA[i, j] = EA[i, j] < double.Epsilon ? 0 : 1;
Matrix BEAT = BEA.GetTranspose();
return (BEA + BEAT) / 2;
}示例3: NAPTStageOneHelper1
// for steps 13-24 in stage one
private static void NAPTStageOneHelper1(Matrix CAP, Matrix SRG, Matrix SRGC, Matrix PAN, Matrix UA11, Matrix CUA11, Vector AOC,
ref Matrix DP1, ref Matrix FA1, int stage, Matrix AC)
{
// 13. Calculate the expected alliance matrix A11
// Sum across rows of A11?
Matrix A11 = new Matrix(CUA11.Rows, CUA11.Cols);
if (stage == 1)
{
for (int i = 0; i < CUA11.Rows; i++)
{
for (int j = 0; j < CUA11.Cols; j++)
{
if (i == j)
A11[i, j] = CAP[i, i];
else if (CUA11[i, j] == CUA11.GetMaxInRow(i))
A11[i, j] = CAP[j, j];
else
A11[i, j] = 0;
}
}
}
else // stage 2 is different
{
for (int i = 0; i < CUA11.Rows; i++)
{
for (int j = 0; j < CUA11.Cols; j++)
{
if (AC[i, j] > 0)
A11[i, j] = AC[i, j];
else if (CUA11[i, j] > 0)
A11[i, j] = CUA11[i, j];
else
A11[i, j] = 0;
}
}
}
/*
// 14. Update the AOC vector to AOC11
Vector AOC11 = new Vector(AOC.Size);
for (int i = 0; i < A11.Rows; i++)
{
if (A11.GetRowSum(i) >= AOC[i])
AOC11[i] = 0;
else
AOC11[i] = AOC[i] - A11.GetRowSum(i);
}
*/
// 14. Update the AOC vector to AOC11
// (modified to compare to SRG CAP instead of AOC) -------- this one is correct ------
Vector AOC11 = new Vector(AOC.Size);
for (int i = 0; i < A11.Rows; i++)
{
if (A11.GetRowSum(i) >= SRGC.GetRowSum(i))
AOC11[i] = 0;
else
AOC11[i] = SRGC.GetRowSum(i) - A11.GetRowSum(i);
}
// 17. Subtract Sum(AOC12) - Sum(AOC11). If result is equal to zero, stop run and go back to step #x
// If the result is less than zero, repeat steps 11-16 by calculating UA13, CUA13, A13, AOC13
//
// This method incorporates steps 15-16
Matrix new_A = UpdateAOC(UA11, CUA11, AOC11, CAP, SRGC, A11, PAN, stage);
// 18. Generate an aliiance offer matrix AO1 which is a binarized version of A1x (where x is the number
// of the last A matrix
//new_A.Binarize();
// Recently updated as of 3:59AM 7/17/2012 (subject to change)
Matrix AO1 = new Matrix(new_A.Rows, new_A.Cols);
for (int i = 0; i < AO1.Rows; i++)
{
for (int j = 0; j < AO1.Cols; j++)
{
if (i == j)
AO1[i, j] = 0;
else if (new_A[i, j] > 0)
AO1[i, j] = 1;
else
AO1[i, j] = 0;
}
}
// 19. Transpose AO1
Matrix AO1_T = AO1.GetTranspose();
// 20. Generate a Defence Pacts matrix DP1 = AO1 * AO1'
DP1 = new Matrix(AO1.Rows, AO1_T.Cols);
for (int i = 0; i < AO1.Rows; i++)
for (int j = 0; j < AO1_T.Cols; j++)
DP1[i, j] = AO1[i, j] * AO1_T[i, j];
// 21. Generate an Allies of Enemies AE1 matrix AE1 = SRG x DP1
Matrix AE1 = SRG * DP1;
//.........这里部分代码省略.........
示例4: UpdateSimplifiedRealistStageTwo
//.........这里部分代码省略.........
if (AOC[i] == 0 || EA[i, j] != 0) ;
else if (PAN[i, j] > 0 && EEC[i, j] == EEM[i])
EA[i, j] = EEC[i, j];
else EA[i, j] = 0;
}
//for (int i = 0; i < n; ++i)
// for (int j = 0; j < n; ++j)
// {
// if (AOC[i] == 0 || EA[i, j] > 0) ;
// else if (EEC[i, j] == EEM[i]) EA[i, j] = EEC[i, j];
// else EA[i, j] = 0;
// }
} while ((!previousEA.IsSameAs(EA)) && !EEC.IsAllZero && !AOC.IsZeroVector);
if (!AOC.IsZeroVector)
{
//for (int i = 0; i < n; ++i)
// for (int j = 0; j < n; ++j)
// if (PAC[i, j] > 0 && TempEEC[i, j] != 0) PAC[i, j] = 0;
//PAC.CopyLabelsFrom(C);
//MatrixWriter.WriteMatrixToMatrixFile(PAC, outputFile);
Vector PAM = new Vector(n);
for (int i = 0; i < n; ++i)
PAM[i] = Algorithms.MaxValue<double>(PAC.GetRowEnumerator(i));
for (int i = 0; i < n; ++i)
for (int j = 0; j < n; ++j)
if (AOC[i] != 0 && PAC[i, j] == PAM[i] && EA[i, j] == 0)
EA[i, j] = PAC[i, j];
do
{
EA.CloneTo(previousEA);
for (int i = 0; i < n; ++i)
SEA[i] = EA.GetRowSum(i) + C[i, i];
for (int i = 0; i < n; ++i)
{
if (SRGC[i] <= SEA[i]) AOC[i] = 0;
else AOC[i] = 1 - SEA[i] / SRGC[i];
}
//Matrix output = new Matrix(n, n + 4);
//for (int i = 0; i < n; i++)
// for (int j = 0; j < n; j++)
// output[i, j] = EA[i, j];
//for (int i = 0; i < n; ++i)
// output[i, n] = SEA[i];
//for (int i = 0; i < n; ++i)
// output[i, n + 1] = SRGC[i];
//for (int i = 0; i < n; ++i)
// output[i, n + 2] = AOC[i];
//for (int i = 0; i < n; ++i)
// output[i, n + 3] = 1111;
//output.CopyLabelsFrom(C);
//MatrixWriter.WriteMatrixToMatrixFile(output, outputFile);
for (int i = 0; i < n; ++i)
for (int j = 0; j < n; ++j)
if (PAC[i, j] == PAM[i]) PAC[i, j] = 0;
//PAC.CopyLabelsFrom(C);
//MatrixWriter.WriteMatrixToMatrixFile(PAC, outputFile);
for (int i = 0; i < n; ++i)
PAM[i] = Algorithms.MaxValue<double>(PAC.GetRowEnumerator(i));
for (int i = 0; i < n; ++i)
for (int j = 0; j < n; ++j)
if (AOC[i] != 0 && PAC[i, j] == PAM[i] && EA[i, j] == 0)
EA[i, j] = PAC[i, j];
} while ((!previousEA.IsSameAs(EA)) && !PAC.IsAllZero && !AOC.IsZeroVector);
}//if AOC is not all zero
Matrix EAT = EA.GetTranspose();
Matrix EAF = new Matrix(n);
for (int i = 0; i < n; ++i)
for (int j = 0; j < n; ++j)
EAF[i, j] = EA[i, j] * EAT[i, j];
for (int i = 0; i < n; ++i)
for (int j = 0; j < n; ++j)
{
if (EAF[i, j] != 0) BEA[i, j] = 1;
else BEA[i, j] = 0;
}
return BEA;
}示例5: SimulateSimplifiedRealistStageOne
//.........这里部分代码省略.........
EA.CloneTo(previousEA);
for (int i = 0; i < n; ++i)
SEA[i] = EA.GetRowSum(i) + C[i, i];
for (int i = 0; i < n; ++i)
{
if (SRGC[i] <= SEA[i]) AOC[i] = 0;
else AOC[i] = 1 - SEA[i] / SRGC[i];
}
for (int i = 0; i < n; ++i)
for (int j = 0; j < n; ++j)
if (EEC[i, j] == EEM[i]) EEC[i, j] = 0;
for (int i = 0; i < n; ++i)
EEM[i] = Algorithms.MaxValue<double>(EEC.GetRowEnumerator(i));
for (int i = 0; i < n; ++i)
for (int j = 0; j < n; ++j)
{
//if (AOC[i] != 0 && EEC[i, j] == EEM[i] && EA[i, j] == 0)
// EA[i, j] = EEC[i, j];
if (AOC[i] == 0 || EA[i, j] != 0);
else if (PAN[i, j] > 0 && EEC[i, j] == EEM[i])
EA[i, j] = EEC[i, j];
else EA[i, j] = 0;
}
} while ((!previousEA.IsSameAs(EA)) && !EEC.IsAllZero && !AOC.IsZeroVector);
if (!AOC.IsZeroVector)
{
for (int i = 0; i < n; ++i)
for (int j = 0; j < n; ++j)
if (PAC[i, j] > 0 && EEC[i, j] != 0) PAC[i, j] = 0;
Vector PAM = new Vector(n);
for (int i = 0; i < n; ++i)
PAM[i] = Algorithms.MaxValue<double>(PAC.GetRowEnumerator(i));
for (int i = 0; i < n; ++i)
for (int j = 0; j < n; ++j)
if (AOC[i] != 0 && PAC[i, j] == PAM[i] && EA[i, j] == 0)
EA[i, j] = PAC[i, j];
EA.CopyLabelsFrom(C);
do
{
EA.CloneTo(previousEA);
for (int i = 0; i < n; ++i)
SEA[i] = EA.GetRowSum(i) + C[i, i];
for (int i = 0; i < n; ++i)
{
if (SRGC[i] <= SEA[i]) AOC[i] = 0;
else AOC[i] = 1 - SEA[i] / SRGC[i];
}
for (int i = 0; i < n; ++i)
for (int j = 0; j < n; ++j)
if (PAC[i, j] == PAM[i]) PAC[i, j] = 0;
for (int i = 0; i < n; ++i)
PAM[i] = Algorithms.MaxValue<double>(PAC.GetRowEnumerator(i));
for (int i = 0; i < n; ++i)
for (int j = 0; j < n; ++j)
if (AOC[i] != 0 && PAC[i, j] == PAM[i] && EA[i, j] == 0)
EA[i, j] = PAC[i, j];
EA.CopyLabelsFrom(C);
} while ((!previousEA.IsSameAs(EA)) && !PAC.IsAllZero && !AOC.IsZeroVector);
}//if AOC is not all zero
Matrix EAT = EA.GetTranspose();
Matrix EAF = new Matrix(n);
for (int i = 0; i < n; ++i)
for (int j = 0; j < n; ++j)
EAF[i, j] = EA[i, j] * EAT[i, j];
Matrix BEA = new Matrix(n);
for (int i = 0; i < n; ++i)
for (int j = 0; j < n; ++j)
{
if (EAF[i, j] != 0) BEA[i, j] = 1;
else BEA[i, j] = 0;
}
return BEA;
}示例6: SolveLeastSquareQR
// Solve least square problem by QR-decomposition:
// minimize ||M*x - b||. Returns x.
//
// The method works only for well-determined (#rows = #columns) and over-determined (#rows > #columns) systems.
//
public Vector SolveLeastSquareQR( Vector b )
{
int l = Rows > Columns ? Columns : Rows;
//////////////////////////////////////////////////////////////////////////
// QR-decompose this = q*r
Matrix Q = new Matrix( Rows, Columns );
Matrix R = new Matrix( Columns, Columns );
// Make vectors x out of columns. Vectors g will populate q-matrix.
Vector[] x = new Vector[Columns];
Vector[] g = new Vector[Columns];
for ( int k=0; k < Columns; k++ )
{
x[k] = new Vector( Rows );
g[k] = new Vector( Rows );
for( int i=0; i < Rows; i++ )
x[k].m[i] = m[i,k];
}
// The main loop
for ( int k=0; k < Columns; k++ )
{
// Calculate r(k,k): norm of x[k]
R.m[k,k] = Math.Sqrt( x[k].Dot( x[k] ) );
if ( R.m[k,k] == 0.0 )
{
for ( int i=0; i < Rows; i++ )
g[k].m[i] = 0.0;
}
else
{ // set g-s
for ( int i=0; i < Rows; i++ )
{
double temp = 1.0 / R.m[k,k];
g[k].m[i] = x[k].m[i] * temp;
}
}
// Calculate non-diagonal elements of r-matrix
for ( int j=k+1; j < Columns; j++ )
{
R.m[j,k] = 0.0;
for ( int i=0; i < Rows; i++ )
R.m[k,j] += x[j].m[i] * g[k].m[i];
}
// Reset x-s
for ( int j=k+1; j < Columns; j++ )
for ( int i=0; i < Rows; i++ )
x[j].m[i] -= R.m[k,j] * g[k].m[i];
}
// Make q out of g-s
for( int i=0; i < Rows; i++ )
for( int k=0; k < Columns; k++ )
Q.m[i,k] = g[k].m[i];
//////////////////////////////////////////////////////////////////////////
// Solve R*x = Q.setToAdjoint()*b
Q = Q.GetTranspose();
Vector y = Q * b;
Vector Result = R.SolveBackwardSubstitution( y );
return Result;
}