[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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[2444] | 4 | //# Copyright (C) 2004-2012 |
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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 2675 2012-10-19 08:06:59Z TakeshiNakazato $ |
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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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[1819] | 34 | #include <casa/Logging/LogIO.h> |
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[91] | 35 | #include <scimath/Fitting.h> |
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| 36 | #include <scimath/Fitting/LinearFit.h> |
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| 37 | #include <scimath/Functionals/CompiledFunction.h> |
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| 38 | #include <scimath/Functionals/CompoundFunction.h> |
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| 39 | #include <scimath/Functionals/Gaussian1D.h> |
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[2675] | 40 | //#include <scimath/Functionals/Lorentzian1D.h> |
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| 41 | #include "Lorentzian1D.h" |
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[2047] | 42 | #include <scimath/Functionals/Sinusoid1D.h> |
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[91] | 43 | #include <scimath/Functionals/Polynomial.h> |
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| 44 | #include <scimath/Mathematics/AutoDiff.h> |
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| 45 | #include <scimath/Mathematics/AutoDiffMath.h> |
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| 46 | #include <scimath/Fitting/NonLinearFitLM.h> |
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| 47 | #include <components/SpectralComponents/SpectralEstimate.h> |
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| 48 | |
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[894] | 49 | #include "STFitter.h" |
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| 50 | |
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[91] | 51 | using namespace asap; |
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[125] | 52 | using namespace casa; |
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[91] | 53 | |
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[890] | 54 | Fitter::Fitter() |
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[91] | 55 | { |
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| 56 | } |
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| 57 | |
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[890] | 58 | Fitter::~Fitter() |
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[91] | 59 | { |
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[517] | 60 | reset(); |
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[91] | 61 | } |
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| 62 | |
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[890] | 63 | void Fitter::clear() |
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[91] | 64 | { |
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[517] | 65 | for (uInt i=0;i< funcs_.nelements();++i) { |
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| 66 | delete funcs_[i]; funcs_[i] = 0; |
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| 67 | } |
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[612] | 68 | funcs_.resize(0,True); |
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[517] | 69 | parameters_.resize(); |
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[1232] | 70 | fixedpar_.resize(); |
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[517] | 71 | error_.resize(); |
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| 72 | thefit_.resize(); |
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| 73 | estimate_.resize(); |
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| 74 | chisquared_ = 0.0; |
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[91] | 75 | } |
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[517] | 76 | |
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[890] | 77 | void Fitter::reset() |
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[91] | 78 | { |
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[517] | 79 | clear(); |
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| 80 | x_.resize(); |
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| 81 | y_.resize(); |
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| 82 | m_.resize(); |
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[2666] | 83 | constraints_.clear(); |
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[91] | 84 | } |
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| 85 | |
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| 86 | |
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[890] | 87 | bool Fitter::computeEstimate() { |
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[517] | 88 | if (x_.nelements() == 0 || y_.nelements() == 0) |
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| 89 | throw (AipsError("No x/y data specified.")); |
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[91] | 90 | |
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[517] | 91 | if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) == 0) |
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| 92 | return false; |
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| 93 | uInt n = funcs_.nelements(); |
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| 94 | SpectralEstimate estimator(n); |
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| 95 | estimator.setQ(5); |
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| 96 | Int mn,mx; |
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| 97 | mn = 0; |
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| 98 | mx = m_.nelements()-1; |
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| 99 | for (uInt i=0; i<m_.nelements();++i) { |
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| 100 | if (m_[i]) { |
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| 101 | mn = i; |
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| 102 | break; |
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[108] | 103 | } |
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[517] | 104 | } |
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[2163] | 105 | // use Int to suppress compiler warning |
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| 106 | for (Int j=m_.nelements()-1; j>=0;--j) { |
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[517] | 107 | if (m_[j]) { |
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| 108 | mx = j; |
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| 109 | break; |
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[108] | 110 | } |
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[517] | 111 | } |
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[1067] | 112 | //mn = 0+x_.nelements()/10; |
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| 113 | //mx = x_.nelements()-x_.nelements()/10; |
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[517] | 114 | estimator.setRegion(mn,mx); |
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| 115 | //estimator.setWindowing(True); |
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| 116 | SpectralList listGauss = estimator.estimate(x_, y_); |
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| 117 | parameters_.resize(n*3); |
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| 118 | Gaussian1D<Float>* g = 0; |
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| 119 | for (uInt i=0; i<n;i++) { |
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[2675] | 120 | // g = dynamic_cast<Gaussian1D<Float>* >(funcs_[i]); |
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| 121 | // if (g) { |
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| 122 | // const GaussianSpectralElement *gauss = |
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| 123 | // dynamic_cast<const GaussianSpectralElement *>(listGauss[i]) ; |
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| 124 | // (*g)[0] = gauss->getAmpl(); |
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| 125 | // (*g)[1] = gauss->getCenter(); |
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| 126 | // (*g)[2] = gauss->getFWHM(); |
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| 127 | // /* |
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| 128 | // (*g)[0] = listGauss[i].getAmpl(); |
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| 129 | // (*g)[1] = listGauss[i].getCenter(); |
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| 130 | // (*g)[2] = listGauss[i].getFWHM(); |
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| 131 | // */ |
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| 132 | // } |
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[517] | 133 | } |
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| 134 | estimate_.resize(); |
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| 135 | listGauss.evaluate(estimate_,x_); |
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| 136 | return true; |
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[91] | 137 | } |
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| 138 | |
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[890] | 139 | std::vector<float> Fitter::getEstimate() const |
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[91] | 140 | { |
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[517] | 141 | if (estimate_.nelements() == 0) |
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| 142 | throw (AipsError("No estimate set.")); |
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| 143 | std::vector<float> stlout; |
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| 144 | estimate_.tovector(stlout); |
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| 145 | return stlout; |
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[91] | 146 | } |
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| 147 | |
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| 148 | |
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[890] | 149 | bool Fitter::setExpression(const std::string& expr, int ncomp) |
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[91] | 150 | { |
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[517] | 151 | clear(); |
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| 152 | if (expr == "gauss") { |
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| 153 | if (ncomp < 1) throw (AipsError("Need at least one gaussian to fit.")); |
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| 154 | funcs_.resize(ncomp); |
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[1932] | 155 | funcnames_.clear(); |
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| 156 | funccomponents_.clear(); |
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[517] | 157 | for (Int k=0; k<ncomp; ++k) { |
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| 158 | funcs_[k] = new Gaussian1D<Float>(); |
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[1932] | 159 | funcnames_.push_back(expr); |
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| 160 | funccomponents_.push_back(3); |
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[517] | 161 | } |
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[1819] | 162 | } else if (expr == "lorentz") { |
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| 163 | if (ncomp < 1) throw (AipsError("Need at least one lorentzian to fit.")); |
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| 164 | funcs_.resize(ncomp); |
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[1932] | 165 | funcnames_.clear(); |
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| 166 | funccomponents_.clear(); |
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[1819] | 167 | for (Int k=0; k<ncomp; ++k) { |
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| 168 | funcs_[k] = new Lorentzian1D<Float>(); |
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[1932] | 169 | funcnames_.push_back(expr); |
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| 170 | funccomponents_.push_back(3); |
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[1819] | 171 | } |
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[2047] | 172 | } else if (expr == "sinusoid") { |
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| 173 | if (ncomp < 1) throw (AipsError("Need at least one sinusoid to fit.")); |
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| 174 | funcs_.resize(ncomp); |
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| 175 | funcnames_.clear(); |
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| 176 | funccomponents_.clear(); |
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| 177 | for (Int k=0; k<ncomp; ++k) { |
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| 178 | funcs_[k] = new Sinusoid1D<Float>(); |
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| 179 | funcnames_.push_back(expr); |
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| 180 | funccomponents_.push_back(3); |
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| 181 | } |
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| 182 | } else if (expr == "poly") { |
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| 183 | funcs_.resize(1); |
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| 184 | funcnames_.clear(); |
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| 185 | funccomponents_.clear(); |
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| 186 | funcs_[0] = new Polynomial<Float>(ncomp); |
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| 187 | funcnames_.push_back(expr); |
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| 188 | funccomponents_.push_back(ncomp); |
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[517] | 189 | } else { |
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[1819] | 190 | LogIO os( LogOrigin( "Fitter", "setExpression()", WHERE ) ) ; |
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| 191 | os << LogIO::WARN << " compiled functions not yet implemented" << LogIO::POST; |
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[517] | 192 | //funcs_.resize(1); |
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| 193 | //funcs_[0] = new CompiledFunction<Float>(); |
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| 194 | //funcs_[0]->setFunction(String(expr)); |
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| 195 | return false; |
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| 196 | } |
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| 197 | return true; |
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[91] | 198 | } |
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| 199 | |
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[890] | 200 | bool Fitter::setData(std::vector<float> absc, std::vector<float> spec, |
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[91] | 201 | std::vector<bool> mask) |
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| 202 | { |
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| 203 | x_.resize(); |
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| 204 | y_.resize(); |
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| 205 | m_.resize(); |
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| 206 | // convert std::vector to casa Vector |
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| 207 | Vector<Float> tmpx(absc); |
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| 208 | Vector<Float> tmpy(spec); |
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| 209 | Vector<Bool> tmpm(mask); |
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| 210 | AlwaysAssert(tmpx.nelements() == tmpy.nelements(), AipsError); |
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| 211 | x_ = tmpx; |
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| 212 | y_ = tmpy; |
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| 213 | m_ = tmpm; |
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| 214 | return true; |
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| 215 | } |
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| 216 | |
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[890] | 217 | std::vector<float> Fitter::getResidual() const |
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[91] | 218 | { |
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| 219 | if (residual_.nelements() == 0) |
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| 220 | throw (AipsError("Function not yet fitted.")); |
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| 221 | std::vector<float> stlout; |
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| 222 | residual_.tovector(stlout); |
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| 223 | return stlout; |
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| 224 | } |
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| 225 | |
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[890] | 226 | std::vector<float> Fitter::getFit() const |
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[91] | 227 | { |
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| 228 | Vector<Float> out = thefit_; |
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| 229 | std::vector<float> stlout; |
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| 230 | out.tovector(stlout); |
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| 231 | return stlout; |
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| 232 | |
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| 233 | } |
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| 234 | |
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[890] | 235 | std::vector<float> Fitter::getErrors() const |
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[91] | 236 | { |
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| 237 | Vector<Float> out = error_; |
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| 238 | std::vector<float> stlout; |
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| 239 | out.tovector(stlout); |
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| 240 | return stlout; |
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| 241 | } |
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| 242 | |
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[890] | 243 | bool Fitter::setParameters(std::vector<float> params) |
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[91] | 244 | { |
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| 245 | Vector<Float> tmppar(params); |
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| 246 | if (funcs_.nelements() == 0) |
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| 247 | throw (AipsError("Function not yet set.")); |
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| 248 | if (parameters_.nelements() > 0 && tmppar.nelements() != parameters_.nelements()) |
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| 249 | throw (AipsError("Number of parameters inconsistent with function.")); |
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[1232] | 250 | if (parameters_.nelements() == 0) { |
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[91] | 251 | parameters_.resize(tmppar.nelements()); |
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[1232] | 252 | if (tmppar.nelements() != fixedpar_.nelements()) { |
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| 253 | fixedpar_.resize(tmppar.nelements()); |
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| 254 | fixedpar_ = False; |
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| 255 | } |
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| 256 | } |
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[91] | 257 | if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) { |
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| 258 | uInt count = 0; |
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| 259 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 260 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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| 261 | (funcs_[j]->parameters())[i] = tmppar[count]; |
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| 262 | parameters_[count] = tmppar[count]; |
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| 263 | ++count; |
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| 264 | } |
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| 265 | } |
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[1819] | 266 | } else if (dynamic_cast<Lorentzian1D<Float>* >(funcs_[0]) != 0) { |
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| 267 | uInt count = 0; |
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| 268 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 269 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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| 270 | (funcs_[j]->parameters())[i] = tmppar[count]; |
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| 271 | parameters_[count] = tmppar[count]; |
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| 272 | ++count; |
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| 273 | } |
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| 274 | } |
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[2047] | 275 | } else if (dynamic_cast<Sinusoid1D<Float>* >(funcs_[0]) != 0) { |
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| 276 | uInt count = 0; |
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| 277 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 278 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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| 279 | (funcs_[j]->parameters())[i] = tmppar[count]; |
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| 280 | parameters_[count] = tmppar[count]; |
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| 281 | ++count; |
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| 282 | } |
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| 283 | } |
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| 284 | } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) { |
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| 285 | for (uInt i=0; i < funcs_[0]->nparameters(); ++i) { |
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| 286 | parameters_[i] = tmppar[i]; |
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| 287 | (funcs_[0]->parameters())[i] = tmppar[i]; |
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| 288 | } |
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[91] | 289 | } |
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[1232] | 290 | // reset |
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| 291 | if (params.size() == 0) { |
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| 292 | parameters_.resize(); |
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| 293 | fixedpar_.resize(); |
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| 294 | } |
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[91] | 295 | return true; |
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| 296 | } |
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| 297 | |
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[2666] | 298 | void Fitter::addConstraint(const std::vector<float>& constraint) |
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| 299 | { |
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| 300 | if (funcs_.nelements() == 0) |
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| 301 | throw (AipsError("Function not yet set.")); |
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| 302 | constraints_.push_back(constraint); |
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| 303 | |
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| 304 | } |
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| 305 | |
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| 306 | void Fitter::applyConstraints(GenericL2Fit<Float>& fitter) |
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| 307 | { |
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| 308 | std::vector<std::vector<float> >::const_iterator it; |
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| 309 | for (it = constraints_.begin(); it != constraints_.end(); ++it) { |
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| 310 | Vector<Float> tmp(*it); |
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| 311 | fitter.addConstraint(tmp(Slice(0,tmp.nelements()-1)), |
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| 312 | tmp(tmp.nelements()-1)); |
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| 313 | } |
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| 314 | } |
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| 315 | |
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[890] | 316 | bool Fitter::setFixedParameters(std::vector<bool> fixed) |
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[91] | 317 | { |
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| 318 | if (funcs_.nelements() == 0) |
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| 319 | throw (AipsError("Function not yet set.")); |
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[1232] | 320 | if (fixedpar_.nelements() > 0 && fixed.size() != fixedpar_.nelements()) |
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[91] | 321 | throw (AipsError("Number of mask elements inconsistent with function.")); |
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[1232] | 322 | if (fixedpar_.nelements() == 0) { |
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| 323 | fixedpar_.resize(parameters_.nelements()); |
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| 324 | fixedpar_ = False; |
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| 325 | } |
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[91] | 326 | if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) { |
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| 327 | uInt count = 0; |
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| 328 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 329 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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[1232] | 330 | funcs_[j]->mask(i) = !fixed[count]; |
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| 331 | fixedpar_[count] = fixed[count]; |
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[91] | 332 | ++count; |
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| 333 | } |
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| 334 | } |
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[1819] | 335 | } else if (dynamic_cast<Lorentzian1D<Float>* >(funcs_[0]) != 0) { |
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| 336 | uInt count = 0; |
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| 337 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 338 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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| 339 | funcs_[j]->mask(i) = !fixed[count]; |
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| 340 | fixedpar_[count] = fixed[count]; |
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| 341 | ++count; |
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| 342 | } |
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| 343 | } |
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[2047] | 344 | } else if (dynamic_cast<Sinusoid1D<Float>* >(funcs_[0]) != 0) { |
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| 345 | uInt count = 0; |
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| 346 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 347 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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| 348 | funcs_[j]->mask(i) = !fixed[count]; |
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| 349 | fixedpar_[count] = fixed[count]; |
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| 350 | ++count; |
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| 351 | } |
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| 352 | } |
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| 353 | } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) { |
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| 354 | for (uInt i=0; i < funcs_[0]->nparameters(); ++i) { |
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| 355 | fixedpar_[i] = fixed[i]; |
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| 356 | funcs_[0]->mask(i) = !fixed[i]; |
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| 357 | } |
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[91] | 358 | } |
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| 359 | return true; |
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| 360 | } |
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| 361 | |
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[890] | 362 | std::vector<float> Fitter::getParameters() const { |
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[91] | 363 | Vector<Float> out = parameters_; |
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| 364 | std::vector<float> stlout; |
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| 365 | out.tovector(stlout); |
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| 366 | return stlout; |
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| 367 | } |
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| 368 | |
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[890] | 369 | std::vector<bool> Fitter::getFixedParameters() const { |
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[108] | 370 | Vector<Bool> out(parameters_.nelements()); |
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| 371 | if (fixedpar_.nelements() == 0) { |
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[1232] | 372 | return std::vector<bool>(); |
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[108] | 373 | //throw (AipsError("No parameter mask set.")); |
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| 374 | } else { |
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| 375 | out = fixedpar_; |
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| 376 | } |
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| 377 | std::vector<bool> stlout; |
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| 378 | out.tovector(stlout); |
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| 379 | return stlout; |
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[91] | 380 | } |
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| 381 | |
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[890] | 382 | float Fitter::getChisquared() const { |
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[91] | 383 | return chisquared_; |
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| 384 | } |
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| 385 | |
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[890] | 386 | bool Fitter::fit() { |
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[517] | 387 | NonLinearFitLM<Float> fitter; |
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| 388 | CompoundFunction<Float> func; |
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[612] | 389 | |
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| 390 | uInt n = funcs_.nelements(); |
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[517] | 391 | for (uInt i=0; i<n; ++i) { |
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| 392 | func.addFunction(*funcs_[i]); |
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| 393 | } |
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[612] | 394 | |
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[517] | 395 | fitter.setFunction(func); |
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| 396 | fitter.setMaxIter(50+n*10); |
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| 397 | // Convergence criterium |
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| 398 | fitter.setCriteria(0.001); |
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[2666] | 399 | applyConstraints(fitter); |
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[612] | 400 | |
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[517] | 401 | // Fit |
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[2580] | 402 | // Vector<Float> sigma(x_.nelements()); |
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| 403 | // sigma = 1.0; |
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[890] | 404 | |
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[517] | 405 | parameters_.resize(); |
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[2580] | 406 | // parameters_ = fitter.fit(x_, y_, sigma, &m_); |
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| 407 | parameters_ = fitter.fit(x_, y_, &m_); |
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[1067] | 408 | if ( !fitter.converged() ) { |
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| 409 | return false; |
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| 410 | } |
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[517] | 411 | std::vector<float> ps; |
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| 412 | parameters_.tovector(ps); |
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| 413 | setParameters(ps); |
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[612] | 414 | |
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[517] | 415 | error_.resize(); |
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| 416 | error_ = fitter.errors(); |
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[612] | 417 | |
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[517] | 418 | chisquared_ = fitter.getChi2(); |
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[890] | 419 | |
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[517] | 420 | // use fitter.residual(model=True) to get the model |
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| 421 | thefit_.resize(x_.nelements()); |
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| 422 | fitter.residual(thefit_,x_,True); |
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[2580] | 423 | residual_.resize(x_.nelements()); |
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| 424 | residual_ = y_ - thefit_ ; |
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[517] | 425 | return true; |
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| 426 | } |
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[483] | 427 | |
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[1391] | 428 | bool Fitter::lfit() { |
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| 429 | LinearFit<Float> fitter; |
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| 430 | CompoundFunction<Float> func; |
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[483] | 431 | |
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[1391] | 432 | uInt n = funcs_.nelements(); |
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| 433 | for (uInt i=0; i<n; ++i) { |
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| 434 | func.addFunction(*funcs_[i]); |
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| 435 | } |
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| 436 | |
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| 437 | fitter.setFunction(func); |
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[2666] | 438 | applyConstraints(fitter); |
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[1391] | 439 | |
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| 440 | parameters_.resize(); |
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[2580] | 441 | parameters_ = fitter.fit(x_, y_, &m_); |
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[1391] | 442 | std::vector<float> ps; |
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| 443 | parameters_.tovector(ps); |
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| 444 | setParameters(ps); |
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| 445 | |
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| 446 | error_.resize(); |
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| 447 | error_ = fitter.errors(); |
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| 448 | |
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| 449 | chisquared_ = fitter.getChi2(); |
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| 450 | |
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| 451 | thefit_.resize(x_.nelements()); |
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| 452 | fitter.residual(thefit_,x_,True); |
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[2580] | 453 | residual_.resize(x_.nelements()); |
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| 454 | residual_ = y_ - thefit_ ; |
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[1391] | 455 | return true; |
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| 456 | } |
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| 457 | |
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[890] | 458 | std::vector<float> Fitter::evaluate(int whichComp) const |
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| 459 | { |
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[517] | 460 | std::vector<float> stlout; |
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[890] | 461 | uInt idx = uInt(whichComp); |
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[517] | 462 | Float y; |
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| 463 | if ( idx < funcs_.nelements() ) { |
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| 464 | for (uInt i=0; i<x_.nelements(); ++i) { |
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| 465 | y = (*funcs_[idx])(x_[i]); |
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| 466 | stlout.push_back(float(y)); |
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| 467 | } |
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| 468 | } |
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| 469 | return stlout; |
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| 470 | } |
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[483] | 471 | |
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[1932] | 472 | STFitEntry Fitter::getFitEntry() const |
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| 473 | { |
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| 474 | STFitEntry fit; |
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| 475 | fit.setParameters(getParameters()); |
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| 476 | fit.setErrors(getErrors()); |
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| 477 | fit.setComponents(funccomponents_); |
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| 478 | fit.setFunctions(funcnames_); |
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| 479 | fit.setParmasks(getFixedParameters()); |
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| 480 | return fit; |
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| 481 | } |
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