[244] | 1 | #include "machdefs.h"
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[220] | 2 | #include "peida.h"
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| 3 | #include "linfit.h"
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| 4 |
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[540] | 5 | LinFitter::LinFitter()
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[220] | 6 | {
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[540] | 7 | }
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| 8 |
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| 9 | LinFitter::~LinFitter()
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| 10 | {
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| 11 | }
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| 12 |
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| 13 | double LinFitter::LinFit(const Vector& x, const Vector& y, int nf,
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| 14 | double (*f)(int, double), Vector& c)
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| 15 | {
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[220] | 16 | int n = x.NElts();
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| 17 | if (n != y.NElts()) THROW(sizeMismatchErr);
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| 18 |
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[514] | 19 | Matrix fx(nf, n);
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[220] | 20 | for (int i=0; i<nf; i++)
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| 21 | for (int j=0; j<n; j++)
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| 22 | fx(i,j) = f(i,x(j));
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| 23 |
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| 24 | return LinFit(fx,y,c);
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| 25 | }
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| 26 |
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| 27 |
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| 28 |
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[540] | 29 | double LinFitter::LinFit(const Matrix& fx, const Vector& y, Vector& c)
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[220] | 30 | {
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| 31 | int n = y.NElts();
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| 32 | if ( n != fx.NCol()) THROW(sizeMismatchErr);
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| 33 |
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| 34 | int nf = fx.NRows();
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| 35 |
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[514] | 36 | Matrix a(nf,nf);
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[220] | 37 |
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| 38 | for (int j=0; j<nf; j++)
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| 39 | for (int k=j; k<nf; k++)
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| 40 | a(j,k) = a(k,j) = fx.Row(j) * fx.Row(k);
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| 41 |
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| 42 | c = fx * y;
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| 43 |
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[514] | 44 | if (Matrix::GausPiv(a,c) == 0) THROW(singMatxErr);
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[220] | 45 |
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| 46 | double xi2 = 0;
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| 47 |
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| 48 | for (int k=0; k<n; k++) {
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| 49 | double x = 0;
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| 50 | for (int i=0; i<nf; i++)
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| 51 | x += c(i) * fx(i,k);
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| 52 | x -= y(k);
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| 53 | xi2 += x*x;
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| 54 | }
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| 55 | return xi2;
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| 56 | }
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| 57 |
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| 58 |
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| 59 |
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[540] | 60 | double LinFitter::LinFit(const Vector& x, const Vector& y, const Vector& errY2, int nf,
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| 61 | double (*f)(int, double), Vector& c, Vector& errC)
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[220] | 62 | {
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| 63 | int n = x.NElts();
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| 64 | if (n != y.NElts()) THROW(sizeMismatchErr);
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| 65 |
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[514] | 66 | Matrix fx(nf, n);
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[220] | 67 | for (int i=0; i<nf; i++)
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| 68 | for (int j=0; j<n; j++)
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| 69 | fx(i,j) = f(i,x(j));
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| 70 |
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| 71 | return LinFit(fx,y,errY2,c,errC);
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| 72 | }
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| 73 |
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| 74 |
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[540] | 75 | double LinFitter::LinFit(const Matrix& fx, const Vector& y, const Vector& errY2,
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[514] | 76 | Vector& c, Vector& errC)
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[220] | 77 | {
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| 78 | int n = y.NElts();
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| 79 | if ( n != errY2.NElts()) THROW(sizeMismatchErr);
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| 80 | if ( n != fx.NCol()) THROW(sizeMismatchErr);
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| 81 |
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| 82 | int nf = fx.NRows();
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| 83 |
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[514] | 84 | Matrix a(nf,nf);
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[220] | 85 |
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| 86 | c.Realloc(nf);
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| 87 | errC.Realloc(nf);
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| 88 |
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| 89 | for (int j=0; j<nf; j++)
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| 90 | for (int k=j; k<nf; k++) {
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| 91 | double x=0;
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| 92 | for (int l=0; l<n; l++)
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| 93 | x += fx(j,l) * fx(k,l) / errY2(l); // Matrice a inverser
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| 94 | a(j,k) = a(k,j) = x;
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| 95 | }
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| 96 |
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[514] | 97 | Matrix d(nf,nf+1);
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[220] | 98 | for (int k=0; k<nf; k++) {
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| 99 | double x=0;
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| 100 | for (int l=0; l<n; l++)
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| 101 | x += fx(k,l) * y(l) / errY2(l); // Second membre 1ere colonne
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| 102 | d(k,0) = x;
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| 103 | for (int m=1; m<=nf; m++)
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| 104 | d(k,m) = (k==m) ? 1 : 0; // Reste second membre = Id.
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| 105 | }
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| 106 |
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[514] | 107 | if (Matrix::GausPiv(a,d) == 0) THROW(singMatxErr);
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[220] | 108 |
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| 109 | for (int l=0; l<nf; l++) {
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| 110 | c(l) = d(l,0); // Parametres = 1ere colonne
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| 111 | errC(l) = d(l,l+1); // Erreurs = diag inverse.
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| 112 | }
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| 113 |
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| 114 | double xi2 = 0;
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| 115 |
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| 116 | for (int jj=0; jj<n; jj++) {
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| 117 | double x = 0;
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| 118 | for (int ii=0; ii<nf; ii++)
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| 119 | x += c(ii) * fx(ii,jj);
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| 120 | x -= y(jj);
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| 121 | xi2 += x*x/errY2(jj);
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| 122 | }
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| 123 | return xi2;
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| 124 | }
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[521] | 125 |
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| 126 |
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