[91] | 1 | //#--------------------------------------------------------------------------- |
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[890] | 2 | //# Fitter.cc: A Fitter class for spectra |
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[91] | 3 | //#-------------------------------------------------------------------------- |
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| 4 | //# Copyright (C) 2004 |
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[125] | 5 | //# ATNF |
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[91] | 6 | //# |
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| 7 | //# This program is free software; you can redistribute it and/or modify it |
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| 8 | //# under the terms of the GNU General Public License as published by the Free |
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| 9 | //# Software Foundation; either version 2 of the License, or (at your option) |
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| 10 | //# any later version. |
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| 11 | //# |
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| 12 | //# This program is distributed in the hope that it will be useful, but |
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| 13 | //# WITHOUT ANY WARRANTY; without even the implied warranty of |
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| 14 | //# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General |
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| 15 | //# Public License for more details. |
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| 16 | //# |
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| 17 | //# You should have received a copy of the GNU General Public License along |
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| 18 | //# with this program; if not, write to the Free Software Foundation, Inc., |
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| 19 | //# 675 Massachusetts Ave, Cambridge, MA 02139, USA. |
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| 20 | //# |
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| 21 | //# Correspondence concerning this software should be addressed as follows: |
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| 22 | //# Internet email: Malte.Marquarding@csiro.au |
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| 23 | //# Postal address: Malte Marquarding, |
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| 24 | //# Australia Telescope National Facility, |
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| 25 | //# P.O. Box 76, |
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| 26 | //# Epping, NSW, 2121, |
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| 27 | //# AUSTRALIA |
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| 28 | //# |
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[891] | 29 | //# $Id: STFitter.cpp 1067 2006-07-04 01:24:55Z mar637 $ |
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[91] | 30 | //#--------------------------------------------------------------------------- |
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[125] | 31 | #include <casa/aips.h> |
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[91] | 32 | #include <casa/Arrays/ArrayMath.h> |
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| 33 | #include <casa/Arrays/ArrayLogical.h> |
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| 34 | #include <scimath/Fitting.h> |
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| 35 | #include <scimath/Fitting/LinearFit.h> |
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| 36 | #include <scimath/Functionals/CompiledFunction.h> |
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| 37 | #include <scimath/Functionals/CompoundFunction.h> |
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| 38 | #include <scimath/Functionals/Gaussian1D.h> |
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| 39 | #include <scimath/Functionals/Polynomial.h> |
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| 40 | #include <scimath/Mathematics/AutoDiff.h> |
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| 41 | #include <scimath/Mathematics/AutoDiffMath.h> |
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| 42 | #include <scimath/Fitting/NonLinearFitLM.h> |
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| 43 | #include <components/SpectralComponents/SpectralEstimate.h> |
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| 44 | |
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[894] | 45 | #include "STFitter.h" |
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| 46 | |
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[91] | 47 | using namespace asap; |
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[125] | 48 | using namespace casa; |
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[91] | 49 | |
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[890] | 50 | Fitter::Fitter() |
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[91] | 51 | { |
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| 52 | } |
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| 53 | |
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[890] | 54 | Fitter::~Fitter() |
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[91] | 55 | { |
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[517] | 56 | reset(); |
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[91] | 57 | } |
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| 58 | |
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[890] | 59 | void Fitter::clear() |
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[91] | 60 | { |
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[517] | 61 | for (uInt i=0;i< funcs_.nelements();++i) { |
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| 62 | delete funcs_[i]; funcs_[i] = 0; |
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| 63 | } |
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[612] | 64 | funcs_.resize(0,True); |
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[517] | 65 | parameters_.resize(); |
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| 66 | error_.resize(); |
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| 67 | thefit_.resize(); |
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| 68 | estimate_.resize(); |
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| 69 | chisquared_ = 0.0; |
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[91] | 70 | } |
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[517] | 71 | |
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[890] | 72 | void Fitter::reset() |
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[91] | 73 | { |
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[517] | 74 | clear(); |
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| 75 | x_.resize(); |
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| 76 | y_.resize(); |
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| 77 | m_.resize(); |
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[91] | 78 | } |
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| 79 | |
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| 80 | |
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[890] | 81 | bool Fitter::computeEstimate() { |
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[517] | 82 | if (x_.nelements() == 0 || y_.nelements() == 0) |
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| 83 | throw (AipsError("No x/y data specified.")); |
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[91] | 84 | |
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[517] | 85 | if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) == 0) |
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| 86 | return false; |
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| 87 | uInt n = funcs_.nelements(); |
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| 88 | SpectralEstimate estimator(n); |
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| 89 | estimator.setQ(5); |
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| 90 | Int mn,mx; |
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| 91 | mn = 0; |
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| 92 | mx = m_.nelements()-1; |
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| 93 | for (uInt i=0; i<m_.nelements();++i) { |
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| 94 | if (m_[i]) { |
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| 95 | mn = i; |
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| 96 | break; |
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[108] | 97 | } |
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[517] | 98 | } |
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| 99 | for (uInt j=m_.nelements()-1; j>=0;--j) { |
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| 100 | if (m_[j]) { |
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| 101 | mx = j; |
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| 102 | break; |
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[108] | 103 | } |
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[517] | 104 | } |
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[1067] | 105 | //mn = 0+x_.nelements()/10; |
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| 106 | //mx = x_.nelements()-x_.nelements()/10; |
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[517] | 107 | estimator.setRegion(mn,mx); |
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| 108 | //estimator.setWindowing(True); |
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| 109 | SpectralList listGauss = estimator.estimate(x_, y_); |
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| 110 | parameters_.resize(n*3); |
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| 111 | Gaussian1D<Float>* g = 0; |
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| 112 | for (uInt i=0; i<n;i++) { |
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| 113 | g = dynamic_cast<Gaussian1D<Float>* >(funcs_[i]); |
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| 114 | if (g) { |
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| 115 | (*g)[0] = listGauss[i].getAmpl(); |
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| 116 | (*g)[1] = listGauss[i].getCenter(); |
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| 117 | (*g)[2] = listGauss[i].getFWHM(); |
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[91] | 118 | } |
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[517] | 119 | } |
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| 120 | estimate_.resize(); |
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| 121 | listGauss.evaluate(estimate_,x_); |
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| 122 | return true; |
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[91] | 123 | } |
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| 124 | |
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[890] | 125 | std::vector<float> Fitter::getEstimate() const |
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[91] | 126 | { |
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[517] | 127 | if (estimate_.nelements() == 0) |
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| 128 | throw (AipsError("No estimate set.")); |
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| 129 | std::vector<float> stlout; |
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| 130 | estimate_.tovector(stlout); |
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| 131 | return stlout; |
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[91] | 132 | } |
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| 133 | |
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| 134 | |
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[890] | 135 | bool Fitter::setExpression(const std::string& expr, int ncomp) |
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[91] | 136 | { |
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[517] | 137 | clear(); |
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| 138 | if (expr == "gauss") { |
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| 139 | if (ncomp < 1) throw (AipsError("Need at least one gaussian to fit.")); |
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| 140 | funcs_.resize(ncomp); |
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| 141 | for (Int k=0; k<ncomp; ++k) { |
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| 142 | funcs_[k] = new Gaussian1D<Float>(); |
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| 143 | } |
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| 144 | } else if (expr == "poly") { |
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| 145 | funcs_.resize(1); |
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| 146 | funcs_[0] = new Polynomial<Float>(ncomp); |
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| 147 | } else { |
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| 148 | cerr << " compiled functions not yet implemented" << endl; |
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| 149 | //funcs_.resize(1); |
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| 150 | //funcs_[0] = new CompiledFunction<Float>(); |
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| 151 | //funcs_[0]->setFunction(String(expr)); |
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| 152 | return false; |
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| 153 | } |
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| 154 | return true; |
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[91] | 155 | } |
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| 156 | |
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[890] | 157 | bool Fitter::setData(std::vector<float> absc, std::vector<float> spec, |
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[91] | 158 | std::vector<bool> mask) |
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| 159 | { |
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| 160 | x_.resize(); |
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| 161 | y_.resize(); |
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| 162 | m_.resize(); |
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| 163 | // convert std::vector to casa Vector |
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| 164 | Vector<Float> tmpx(absc); |
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| 165 | Vector<Float> tmpy(spec); |
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| 166 | Vector<Bool> tmpm(mask); |
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| 167 | AlwaysAssert(tmpx.nelements() == tmpy.nelements(), AipsError); |
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| 168 | x_ = tmpx; |
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| 169 | y_ = tmpy; |
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| 170 | m_ = tmpm; |
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| 171 | return true; |
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| 172 | } |
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| 173 | |
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[890] | 174 | std::vector<float> Fitter::getResidual() const |
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[91] | 175 | { |
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| 176 | if (residual_.nelements() == 0) |
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| 177 | throw (AipsError("Function not yet fitted.")); |
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| 178 | std::vector<float> stlout; |
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| 179 | residual_.tovector(stlout); |
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| 180 | return stlout; |
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| 181 | } |
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| 182 | |
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[890] | 183 | std::vector<float> Fitter::getFit() const |
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[91] | 184 | { |
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| 185 | Vector<Float> out = thefit_; |
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| 186 | std::vector<float> stlout; |
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| 187 | out.tovector(stlout); |
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| 188 | return stlout; |
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| 189 | |
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| 190 | } |
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| 191 | |
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[890] | 192 | std::vector<float> Fitter::getErrors() const |
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[91] | 193 | { |
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| 194 | Vector<Float> out = error_; |
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| 195 | std::vector<float> stlout; |
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| 196 | out.tovector(stlout); |
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| 197 | return stlout; |
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| 198 | } |
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| 199 | |
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[890] | 200 | bool Fitter::setParameters(std::vector<float> params) |
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[91] | 201 | { |
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| 202 | Vector<Float> tmppar(params); |
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| 203 | if (funcs_.nelements() == 0) |
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| 204 | throw (AipsError("Function not yet set.")); |
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| 205 | if (parameters_.nelements() > 0 && tmppar.nelements() != parameters_.nelements()) |
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| 206 | throw (AipsError("Number of parameters inconsistent with function.")); |
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| 207 | if (parameters_.nelements() == 0) |
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| 208 | parameters_.resize(tmppar.nelements()); |
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| 209 | fixedpar_.resize(tmppar.nelements()); |
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| 210 | fixedpar_ = False; |
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| 211 | if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) { |
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| 212 | uInt count = 0; |
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| 213 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 214 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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| 215 | (funcs_[j]->parameters())[i] = tmppar[count]; |
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| 216 | parameters_[count] = tmppar[count]; |
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| 217 | ++count; |
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| 218 | } |
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| 219 | } |
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| 220 | } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) { |
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| 221 | for (uInt i=0; i < funcs_[0]->nparameters(); ++i) { |
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| 222 | parameters_[i] = tmppar[i]; |
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| 223 | (funcs_[0]->parameters())[i] = tmppar[i]; |
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| 224 | } |
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| 225 | } |
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| 226 | return true; |
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| 227 | } |
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| 228 | |
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[890] | 229 | bool Fitter::setFixedParameters(std::vector<bool> fixed) |
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[91] | 230 | { |
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| 231 | Vector<Bool> tmp(fixed); |
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| 232 | if (funcs_.nelements() == 0) |
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| 233 | throw (AipsError("Function not yet set.")); |
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| 234 | if (fixedpar_.nelements() > 0 && tmp.nelements() != fixedpar_.nelements()) |
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| 235 | throw (AipsError("Number of mask elements inconsistent with function.")); |
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| 236 | if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) { |
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| 237 | uInt count = 0; |
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| 238 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 239 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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| 240 | funcs_[j]->mask(i) = !tmp[count]; |
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| 241 | fixedpar_[count] = !tmp[count]; |
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| 242 | ++count; |
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| 243 | } |
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| 244 | } |
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| 245 | } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) { |
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| 246 | for (uInt i=0; i < funcs_[0]->nparameters(); ++i) { |
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| 247 | fixedpar_[i] = tmp[i]; |
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| 248 | funcs_[0]->mask(i) = tmp[i]; |
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| 249 | } |
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| 250 | } |
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| 251 | //fixedpar_ = !tmpmsk; |
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| 252 | return true; |
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| 253 | } |
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| 254 | |
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[890] | 255 | std::vector<float> Fitter::getParameters() const { |
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[91] | 256 | Vector<Float> out = parameters_; |
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| 257 | std::vector<float> stlout; |
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| 258 | out.tovector(stlout); |
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| 259 | return stlout; |
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| 260 | } |
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| 261 | |
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[890] | 262 | std::vector<bool> Fitter::getFixedParameters() const { |
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[108] | 263 | Vector<Bool> out(parameters_.nelements()); |
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| 264 | if (fixedpar_.nelements() == 0) { |
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| 265 | out = False; |
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| 266 | //throw (AipsError("No parameter mask set.")); |
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| 267 | } else { |
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| 268 | out = fixedpar_; |
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| 269 | } |
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| 270 | std::vector<bool> stlout; |
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| 271 | out.tovector(stlout); |
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| 272 | return stlout; |
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[91] | 273 | } |
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| 274 | |
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[890] | 275 | float Fitter::getChisquared() const { |
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[91] | 276 | return chisquared_; |
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| 277 | } |
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| 278 | |
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[890] | 279 | bool Fitter::fit() { |
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[517] | 280 | NonLinearFitLM<Float> fitter; |
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| 281 | CompoundFunction<Float> func; |
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[612] | 282 | |
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| 283 | uInt n = funcs_.nelements(); |
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[517] | 284 | for (uInt i=0; i<n; ++i) { |
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| 285 | func.addFunction(*funcs_[i]); |
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| 286 | } |
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[612] | 287 | |
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[517] | 288 | fitter.setFunction(func); |
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| 289 | fitter.setMaxIter(50+n*10); |
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| 290 | // Convergence criterium |
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| 291 | fitter.setCriteria(0.001); |
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[612] | 292 | |
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[517] | 293 | // Fit |
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| 294 | Vector<Float> sigma(x_.nelements()); |
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| 295 | sigma = 1.0; |
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[890] | 296 | |
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[517] | 297 | parameters_.resize(); |
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| 298 | parameters_ = fitter.fit(x_, y_, sigma, &m_); |
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[1067] | 299 | if ( !fitter.converged() ) { |
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| 300 | return false; |
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| 301 | } |
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[517] | 302 | std::vector<float> ps; |
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| 303 | parameters_.tovector(ps); |
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| 304 | setParameters(ps); |
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[612] | 305 | |
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[517] | 306 | error_.resize(); |
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| 307 | error_ = fitter.errors(); |
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[612] | 308 | |
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[517] | 309 | chisquared_ = fitter.getChi2(); |
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[890] | 310 | |
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[517] | 311 | residual_.resize(); |
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| 312 | residual_ = y_; |
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| 313 | fitter.residual(residual_,x_); |
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[612] | 314 | |
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[517] | 315 | // use fitter.residual(model=True) to get the model |
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| 316 | thefit_.resize(x_.nelements()); |
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| 317 | fitter.residual(thefit_,x_,True); |
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| 318 | return true; |
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| 319 | } |
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[483] | 320 | |
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| 321 | |
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[890] | 322 | std::vector<float> Fitter::evaluate(int whichComp) const |
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| 323 | { |
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[517] | 324 | std::vector<float> stlout; |
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[890] | 325 | uInt idx = uInt(whichComp); |
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[517] | 326 | Float y; |
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| 327 | if ( idx < funcs_.nelements() ) { |
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| 328 | for (uInt i=0; i<x_.nelements(); ++i) { |
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| 329 | y = (*funcs_[idx])(x_[i]); |
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| 330 | stlout.push_back(float(y)); |
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| 331 | } |
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| 332 | } |
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| 333 | return stlout; |
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| 334 | } |
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[483] | 335 | |
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