//#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); } }