tmtg.cpp
Go to the documentation of this file.
00001 
00002 
00003 
00006 
00007 
00008 //#define WANT_STREAM
00009 
00010 #define WANT_MATH                   // for sqrt
00011 
00012 #include "include.h"
00013 
00014 #include "newmatap.h"
00015 
00016 #include "tmt.h"
00017 
00018 #ifdef use_namespace
00019 using namespace NEWMAT;
00020 #endif
00021 
00022 
00023 
00024 void trymatg()
00025 {
00026 //   cout << "\nSixteenth test of Matrix package\n";
00027 //   cout << "\n";
00028    Tracer et("Sixteenth test of Matrix package");
00029    Tracer::PrintTrace();
00030 
00031    int i,j;
00032    Matrix M(4,7);
00033    for (i=1; i<=4; i++) for (j=1; j<=7; j++) M(i,j) = 100 * i + j;
00034    ColumnVector CV = M.AsColumn();
00035    {
00036       Tracer et1("Stage 1");
00037       RowVector test(7);
00038       test(1) = SumSquare(M);
00039       test(2) = SumSquare(CV);
00040       test(3) = SumSquare(CV.t());
00041       test(4) = SumSquare(CV.AsDiagonal());
00042       test(5) = SumSquare(M.AsColumn());
00043       test(6) = Matrix(CV.t()*CV)(1,1);
00044       test(7) = (CV.t()*CV).AsScalar();
00045       test = test - 2156560.0; Print(test);
00046    }
00047 
00048    UpperTriangularMatrix U(6);
00049    for (i=1; i<=6; i++) for (j=i; j<=6; j++) U(i,j) = i + (i-j) * (i-j);
00050    M = U; DiagonalMatrix D; D << U;
00051    LowerTriangularMatrix L = U.t(); SymmetricMatrix S; S << (L+U)/2.0;
00052    {
00053       Tracer et1("Stage 2");
00054       RowVector test(6);
00055       test(1) = U.Trace();
00056       test(2) = L.Trace();
00057       test(3) = D.Trace();
00058       test(4) = S.Trace();
00059       test(5) = M.Trace();
00060       test(6) = ((L+U)/2.0).Trace();
00061       test = test - 21; Print(test);
00062       test(1) = LogDeterminant(U).Value();
00063       test(2) = LogDeterminant(L).Value();
00064       test(3) = LogDeterminant(D).Value();
00065       test(4) = LogDeterminant(D).Value();
00066       test(5) = LogDeterminant((L+D)/2.0).Value();
00067       test(6) = Determinant((L+D)/2.0);
00068       test = test - 720; Clean(test,0.000000001); Print(test);
00069    }
00070 
00071    {
00072       Tracer et1("Stage 3");
00073       S << L*U; M = S;
00074       RowVector test(8);
00075       test(1) = LogDeterminant(S).Value();
00076       test(2) = LogDeterminant(M).Value();
00077       test(3) = LogDeterminant(L*U).Value();
00078       test(4) = LogDeterminant(Matrix(L*L)).Value();
00079       test(5) = Determinant(S);
00080       test(6) = Determinant(M);
00081       test(7) = Determinant(L*U);
00082       test(8) = Determinant(Matrix(L*L));
00083       test = test - 720.0 * 720.0; Clean(test,0.00000001); Print(test);
00084    }
00085 
00086    {
00087       Tracer et1("Stage 4");
00088       M = S * S;
00089       Matrix SX = S;
00090       RowVector test(3);
00091       test(1) = SumSquare(S);
00092       test(2) = SumSquare(SX);
00093       test(3) = Trace(M);
00094                 test = test - 3925961.0; Print(test);
00095    }
00096    {
00097       Tracer et1("Stage 5");
00098       SymmetricMatrix SM(10), SN(10);
00099       Real S = 0.0;
00100       for (i=1; i<=10; i++) for (j=i; j<=10; j++)
00101       {
00102          SM(i,j) = 1.5 * i - j; SN(i,j) = SM(i,j) * SM(i,j);
00103          if (SM(i,j) < 0.0)   SN(i,j) = - SN(i,j);
00104          S += SN(i,j) * ((i==j) ? 1.0 : 2.0);
00105       }
00106       Matrix M = SM, N = SN; RowVector test(4);
00107       test(1) = SumAbsoluteValue(SN);
00108       test(2) = SumAbsoluteValue(-SN);
00109       test(3) = SumAbsoluteValue(N);
00110       test(4) = SumAbsoluteValue(-N);
00111       test = test - 1168.75; Print(test);
00112       test(1) = Sum(SN);
00113       test(2) = -Sum(-SN);
00114       test(3) = Sum(N);
00115       test(4) = -Sum(-N);
00116       test = test - S; Print(test);
00117       test(1) = MaximumAbsoluteValue(SM);
00118       test(2) = MaximumAbsoluteValue(-SM);
00119       test(3) = MaximumAbsoluteValue(M);
00120       test(4) = MaximumAbsoluteValue(-M);
00121       test = test - 8.5; Print(test);
00122    }
00123    {
00124       Tracer et1("Stage 6");
00125       Matrix M(15,20); Real value = 0.0;
00126       for (i=1; i<=15; i++) { for (j=1; j<=20; j++) M(i,j) = 1.5 * i - j; }
00127       for (i=1; i<=20; i++)
00128       { Real v = SumAbsoluteValue(M.Column(i)); if (value<v) value = v; }
00129       RowVector test(3);
00130       test(1) = value;
00131       test(2) = Norm1(M);
00132       test(3) = NormInfinity(M.t());
00133       test = test - 165; Print(test);
00134       test.ReSize(5);
00135       ColumnVector CV = M.AsColumn(); M = CV.t();
00136       test(1) = Norm1(CV.t());
00137       test(2) = MaximumAbsoluteValue(M);
00138       test(3) = NormInfinity(CV);
00139       test(4) = Norm1(M);
00140       test(5) = NormInfinity(M.t());
00141       test = test - 21.5; Print(test);
00142    }
00143    {
00144       Tracer et1("Stage 7");
00145       Matrix M(15,20);
00146       for (i=1; i<=15; i++) { for (j=1; j<=20; j++) M(i,j) = 2.5 * i - j; }
00147       SymmetricMatrix SM; SM << M * M.t();
00148       ColumnVector test(6);
00149       test(1) = sqrt(SumSquare(M)) - NormFrobenius(M);
00150       Real a = sqrt(SumSquare(SM));
00151       test(2) = NormFrobenius(M * M.t()) - a;
00152       test(3) = SM.NormFrobenius() - a;
00153       test(4) = (M * M.t()).NormFrobenius() - a;
00154       test(5) = NormFrobenius(SM) - a;
00155       test(6) = Trace(SM) - M.SumSquare();
00156       Clean(test, 0.00000001); Print(test);
00157   }
00158 
00159 //   cout << "\nEnd of Sixteenth test\n";
00160 }
00161 
00162 


kni
Author(s): Martin Günther
autogenerated on Thu Aug 27 2015 13:40:07