3dpcp/.svn/pristine/6f/6f4edefa29dbba22a7dd5c544e01723fbe8d4b04.svn-base
2012-09-16 14:33:11 +02:00

160 lines
5.1 KiB
Text

//#define WANT_STREAM
#include "include.h"
#include "newmat.h"
#include "tmt.h"
#ifdef use_namespace
using namespace NEWMAT;
#endif
/**************************** test program ******************************/
void trymat3()
{
Tracer et("Third test of Matrix package");
Tracer::PrintTrace();
{
Tracer et1("Stage 1");
int i,j;
SymmetricMatrix S(7);
for (i=1;i<=7;i++) for (j=1;j<=i;j++) S(i,j)=i*i+j;
S=-S+2.0;
DiagonalMatrix D(7);
for (i=1;i<=7;i++) D(i,i)=S(i,i);
Matrix M4(7,7); { M4=D+(D+4.0); M4=M4-D*2.0; M4=M4-4.0; Print(M4); }
SymmetricMatrix S2=D; Matrix M2=S2; { M2=-D+M2; Print(M2); }
UpperTriangularMatrix U2=D; { M2=U2; M2=D-M2; Print(M2); }
LowerTriangularMatrix L2=D; { M2=L2; M2=D-M2; Print(M2); }
M2=D; M2=M2-D; Print(M2);
for (i=1;i<=7;i++) for (j=1;j<=i;j++) L2(i,j)=2.0-i*i-j;
U2=L2.t(); D=D.t(); S=S.t();
M4=(L2-1.0)+(U2+1.0)-D-S; Print(M4);
M4=(-L2+1.0)+(-U2-1.0)+D+S; Print(M4);
}
{
Tracer et1("Stage 2");
int i,j;
DiagonalMatrix D(6);
for (i=1;i<=6;i++) D(i,i)=i*3.0+i*i+2.0;
UpperTriangularMatrix U2(7); LowerTriangularMatrix L2(7);
for (i=1;i<=7;i++) for (j=1;j<=i;j++) L2(i,j)=2.0-i*i+j;
{ U2=L2.t(); }
DiagonalMatrix D1(7); for (i=1;i<=7;i++) D1(i,i)=(i-2)*(i-4);
Matrix M2(6,7);
for (i=1;i<=6;i++) for (j=1;j<=7;j++) M2(i,j)=2.0+i*j+i*i+2.0*j*j;
Matrix MD=D; SymmetricMatrix MD1(1); MD1=D1;
Matrix MX=MD*M2*MD1 - D*(M2*D1); Print(MX);
MX=MD*M2*MD1 - (D*M2)*D1; Print(MX);
{
D.ReSize(7); for (i=1;i<=7;i++) D(i,i)=i*3.0+i*i+2.0;
LowerTriangularMatrix LD(1); LD=D;
UpperTriangularMatrix UD(1); UD=D;
M2=U2; M2=LD*M2*MD1 - D*(U2*D1); Print(M2);
M2=U2; M2=UD*M2*MD1 - (D*U2)*D1; Print(M2);
M2=L2; M2=LD*M2*MD1 - D*(L2*D1); Print(M2);
M2=L2; M2=UD*M2*MD1 - (D*L2)*D1; Print(M2);
}
}
{
Tracer et1("Stage 3");
// test inverse * scalar
DiagonalMatrix D(6);
for (int i=1;i<=6;i++) D(i)=i*i;
DiagonalMatrix E = D.i() * 4.0;
DiagonalMatrix I(6); I = 1.0;
E=D*E-I*4.0; Print(E);
E = D.i() / 0.25; E=D*E-I*4.0; Print(E);
}
{
Tracer et1("Stage 4");
Matrix sigma(3,3); Matrix sigmaI(3,3);
sigma = 0; sigma(1,1) = 1.0; sigma(2,2) = 1.0; sigma(3,3) = 1.0;
sigmaI = sigma.i();
sigmaI -= sigma; Clean(sigmaI, 0.000000001); Print(sigmaI);
}
{
Tracer et1("Stage 5");
Matrix X(5,5); DiagonalMatrix DM(5);
for (int i=1; i<=5; i++) for (int j=1; j<=5; j++)
X(i,j) = (23*i+59*j) % 43;
DM << 1 << 8 << -7 << 2 << 3;
Matrix Y = X.i() * DM; Y = X * Y - DM;
Clean(Y, 0.000000001); Print(Y);
}
{
Tracer et1("Stage 6"); // test reverse function
ColumnVector CV(10), RCV(10);
CV << 2 << 7 << 1 << 6 << -3 << 1 << 8 << -4 << 0 << 17;
RCV << 17 << 0 << -4 << 8 << 1 << -3 << 6 << 1 << 7 << 2;
ColumnVector X = CV - RCV.Reverse(); Print(X);
RowVector Y = CV.t() - RCV.t().Reverse(); Print(Y);
DiagonalMatrix D = CV.AsDiagonal() - RCV.AsDiagonal().Reverse();
Print(D);
X = CV & CV.Rows(1,9).Reverse();
ColumnVector Z(19);
Z.Rows(1,10) = RCV.Reverse(); Z.Rows(11,19) = RCV.Rows(2,10);
X -= Z; Print(X); Z -= Z.Reverse(); Print(Z);
Matrix A(3,3); A << 1 << 2 << 3 << 4 << 5 << 6 << 7 << 8 << 9;
Matrix B(3,3); B << 9 << 8 << 7 << 6 << 5 << 4 << 3 << 2 << 1;
Matrix Diff = A - B.Reverse(); Print(Diff);
Diff = (-A).Reverse() + B; Print(Diff);
UpperTriangularMatrix U;
U << A.Reverse(); Diff = U; U << B; Diff -= U; Print(Diff);
U << (-A).Reverse(); Diff = U; U << B; Diff += U; Print(Diff);
}
{
Tracer et1("Stage 7"); // test IsSingular function
ColumnVector XX(4);
Matrix A(3,3);
A = 0;
CroutMatrix B1 = A;
XX(1) = B1.IsSingular() ? 0 : 1;
A << 1 << 3 << 6
<< 7 << 11 << 13
<< 2 << 4 << 1;
CroutMatrix B2(A);
XX(2) = B2.IsSingular() ? 1 : 0;
BandMatrix C(3,1,1); C.Inject(A);
BandLUMatrix B3(C);
XX(3) = B3.IsSingular() ? 1 : 0;
C = 0;
BandLUMatrix B4(C);
XX(4) = B4.IsSingular() ? 0 : 1;
Print(XX);
}
{
Tracer et1("Stage 8"); // inverse with vector of 0s
Matrix A(3,3); Matrix Z(3,3); ColumnVector X(6);
A << 1 << 3 << 6
<< 7 << 11 << 13
<< 2 << 4 << 1;
Z = 0;
Matrix B = (A | Z) & (Z | A); // 6 * 6 matrix
X = 0.0;
X = B.i() * X;
Print(X);
// also check inverse with non-zero Y
Matrix Y(3,3);
Y << 0.0 << 1.0 << 1.0
<< 5.0 << 0.0 << 5.0
<< 3.0 << 3.0 << 0.0;
Matrix YY = Y & Y; // stack Y matrices
YY = B.i() * YY;
Matrix Y1 = A.i() * Y;
YY -= Y1 & Y1; Clean(YY, 0.000000001); Print(YY);
Y1 = A * Y1 - Y; Clean(Y1, 0.000000001); Print(Y1);
}
}