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