[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 3106 2016-10-04 07:20:50Z 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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[2725] | 40 | #include <scimath/Functionals/Lorentzian1D.h> |
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[2047] | 41 | #include <scimath/Functionals/Sinusoid1D.h> |
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[91] | 42 | #include <scimath/Functionals/Polynomial.h> |
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| 43 | #include <scimath/Mathematics/AutoDiff.h> |
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| 44 | #include <scimath/Mathematics/AutoDiffMath.h> |
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| 45 | #include <scimath/Fitting/NonLinearFitLM.h> |
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| 46 | #include <components/SpectralComponents/SpectralEstimate.h> |
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| 47 | |
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[894] | 48 | #include "STFitter.h" |
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| 49 | |
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[91] | 50 | using namespace asap; |
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[3106] | 51 | using namespace casacore; |
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[125] | 52 | using namespace casa; |
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[91] | 53 | |
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[3106] | 54 | namespace asap { |
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| 55 | |
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[890] | 56 | Fitter::Fitter() |
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[91] | 57 | { |
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| 58 | } |
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| 59 | |
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[890] | 60 | Fitter::~Fitter() |
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[91] | 61 | { |
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[517] | 62 | reset(); |
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[91] | 63 | } |
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| 64 | |
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[890] | 65 | void Fitter::clear() |
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[91] | 66 | { |
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[517] | 67 | for (uInt i=0;i< funcs_.nelements();++i) { |
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| 68 | delete funcs_[i]; funcs_[i] = 0; |
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| 69 | } |
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[612] | 70 | funcs_.resize(0,True); |
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[517] | 71 | parameters_.resize(); |
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[1232] | 72 | fixedpar_.resize(); |
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[517] | 73 | error_.resize(); |
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| 74 | thefit_.resize(); |
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| 75 | estimate_.resize(); |
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| 76 | chisquared_ = 0.0; |
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[91] | 77 | } |
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[517] | 78 | |
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[890] | 79 | void Fitter::reset() |
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[91] | 80 | { |
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[517] | 81 | clear(); |
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| 82 | x_.resize(); |
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| 83 | y_.resize(); |
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| 84 | m_.resize(); |
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[2666] | 85 | constraints_.clear(); |
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[91] | 86 | } |
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| 87 | |
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| 88 | |
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[890] | 89 | bool Fitter::computeEstimate() { |
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[517] | 90 | if (x_.nelements() == 0 || y_.nelements() == 0) |
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| 91 | throw (AipsError("No x/y data specified.")); |
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[91] | 92 | |
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[3087] | 93 | if (funcs_.size() == 0) { |
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| 94 | throw AipsError("No fit function specified."); |
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| 95 | } |
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| 96 | |
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[517] | 97 | if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) == 0) |
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| 98 | return false; |
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| 99 | uInt n = funcs_.nelements(); |
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| 100 | SpectralEstimate estimator(n); |
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| 101 | estimator.setQ(5); |
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| 102 | Int mn,mx; |
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| 103 | mn = 0; |
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| 104 | mx = m_.nelements()-1; |
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| 105 | for (uInt i=0; i<m_.nelements();++i) { |
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| 106 | if (m_[i]) { |
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| 107 | mn = i; |
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| 108 | break; |
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[108] | 109 | } |
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[517] | 110 | } |
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[2163] | 111 | // use Int to suppress compiler warning |
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| 112 | for (Int j=m_.nelements()-1; j>=0;--j) { |
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[517] | 113 | if (m_[j]) { |
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| 114 | mx = j; |
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| 115 | break; |
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[108] | 116 | } |
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[517] | 117 | } |
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[1067] | 118 | //mn = 0+x_.nelements()/10; |
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| 119 | //mx = x_.nelements()-x_.nelements()/10; |
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[517] | 120 | estimator.setRegion(mn,mx); |
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| 121 | //estimator.setWindowing(True); |
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| 122 | SpectralList listGauss = estimator.estimate(x_, y_); |
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| 123 | parameters_.resize(n*3); |
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[3087] | 124 | Gaussian1D<Float>* g = 0; |
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| 125 | for (uInt i=0; i<n;i++) { |
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| 126 | g = dynamic_cast<Gaussian1D<Float>* >(funcs_[i]); |
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| 127 | if (g) { |
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| 128 | const GaussianSpectralElement *gauss = |
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| 129 | dynamic_cast<const GaussianSpectralElement *>(listGauss[i]) ; |
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| 130 | (*g)[0] = gauss->getAmpl(); |
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| 131 | (*g)[1] = gauss->getCenter(); |
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| 132 | (*g)[2] = gauss->getFWHM(); |
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| 133 | /* |
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| 134 | (*g)[0] = listGauss[i].getAmpl(); |
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| 135 | (*g)[1] = listGauss[i].getCenter(); |
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| 136 | (*g)[2] = listGauss[i].getFWHM(); |
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| 137 | */ |
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| 138 | } |
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| 139 | } |
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[517] | 140 | estimate_.resize(); |
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| 141 | listGauss.evaluate(estimate_,x_); |
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| 142 | return true; |
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[91] | 143 | } |
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| 144 | |
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[890] | 145 | std::vector<float> Fitter::getEstimate() const |
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[91] | 146 | { |
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[517] | 147 | if (estimate_.nelements() == 0) |
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| 148 | throw (AipsError("No estimate set.")); |
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| 149 | std::vector<float> stlout; |
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| 150 | estimate_.tovector(stlout); |
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| 151 | return stlout; |
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[91] | 152 | } |
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| 153 | |
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| 154 | |
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[890] | 155 | bool Fitter::setExpression(const std::string& expr, int ncomp) |
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[91] | 156 | { |
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[517] | 157 | clear(); |
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| 158 | if (expr == "gauss") { |
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| 159 | if (ncomp < 1) throw (AipsError("Need at least one gaussian to fit.")); |
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| 160 | funcs_.resize(ncomp); |
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[1932] | 161 | funcnames_.clear(); |
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| 162 | funccomponents_.clear(); |
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[517] | 163 | for (Int k=0; k<ncomp; ++k) { |
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| 164 | funcs_[k] = new Gaussian1D<Float>(); |
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[1932] | 165 | funcnames_.push_back(expr); |
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| 166 | funccomponents_.push_back(3); |
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[517] | 167 | } |
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[1819] | 168 | } else if (expr == "lorentz") { |
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| 169 | if (ncomp < 1) throw (AipsError("Need at least one lorentzian to fit.")); |
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| 170 | funcs_.resize(ncomp); |
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[1932] | 171 | funcnames_.clear(); |
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| 172 | funccomponents_.clear(); |
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[1819] | 173 | for (Int k=0; k<ncomp; ++k) { |
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| 174 | funcs_[k] = new Lorentzian1D<Float>(); |
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[1932] | 175 | funcnames_.push_back(expr); |
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| 176 | funccomponents_.push_back(3); |
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[1819] | 177 | } |
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[2047] | 178 | } else if (expr == "sinusoid") { |
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| 179 | if (ncomp < 1) throw (AipsError("Need at least one sinusoid to fit.")); |
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| 180 | funcs_.resize(ncomp); |
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| 181 | funcnames_.clear(); |
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| 182 | funccomponents_.clear(); |
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| 183 | for (Int k=0; k<ncomp; ++k) { |
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| 184 | funcs_[k] = new Sinusoid1D<Float>(); |
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| 185 | funcnames_.push_back(expr); |
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| 186 | funccomponents_.push_back(3); |
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| 187 | } |
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| 188 | } else if (expr == "poly") { |
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| 189 | funcs_.resize(1); |
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| 190 | funcnames_.clear(); |
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| 191 | funccomponents_.clear(); |
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| 192 | funcs_[0] = new Polynomial<Float>(ncomp); |
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| 193 | funcnames_.push_back(expr); |
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| 194 | funccomponents_.push_back(ncomp); |
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[517] | 195 | } else { |
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[1819] | 196 | LogIO os( LogOrigin( "Fitter", "setExpression()", WHERE ) ) ; |
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| 197 | os << LogIO::WARN << " compiled functions not yet implemented" << LogIO::POST; |
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[517] | 198 | //funcs_.resize(1); |
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| 199 | //funcs_[0] = new CompiledFunction<Float>(); |
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| 200 | //funcs_[0]->setFunction(String(expr)); |
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| 201 | return false; |
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| 202 | } |
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| 203 | return true; |
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[91] | 204 | } |
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| 205 | |
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[890] | 206 | bool Fitter::setData(std::vector<float> absc, std::vector<float> spec, |
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[91] | 207 | std::vector<bool> mask) |
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| 208 | { |
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| 209 | x_.resize(); |
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| 210 | y_.resize(); |
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| 211 | m_.resize(); |
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| 212 | // convert std::vector to casa Vector |
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| 213 | Vector<Float> tmpx(absc); |
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| 214 | Vector<Float> tmpy(spec); |
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| 215 | Vector<Bool> tmpm(mask); |
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| 216 | AlwaysAssert(tmpx.nelements() == tmpy.nelements(), AipsError); |
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| 217 | x_ = tmpx; |
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| 218 | y_ = tmpy; |
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| 219 | m_ = tmpm; |
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| 220 | return true; |
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| 221 | } |
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| 222 | |
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[890] | 223 | std::vector<float> Fitter::getResidual() const |
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[91] | 224 | { |
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| 225 | if (residual_.nelements() == 0) |
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| 226 | throw (AipsError("Function not yet fitted.")); |
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| 227 | std::vector<float> stlout; |
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| 228 | residual_.tovector(stlout); |
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| 229 | return stlout; |
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| 230 | } |
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| 231 | |
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[890] | 232 | std::vector<float> Fitter::getFit() const |
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[91] | 233 | { |
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| 234 | Vector<Float> out = thefit_; |
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| 235 | std::vector<float> stlout; |
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| 236 | out.tovector(stlout); |
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| 237 | return stlout; |
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| 238 | |
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| 239 | } |
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| 240 | |
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[890] | 241 | std::vector<float> Fitter::getErrors() const |
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[91] | 242 | { |
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| 243 | Vector<Float> out = error_; |
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| 244 | std::vector<float> stlout; |
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| 245 | out.tovector(stlout); |
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| 246 | return stlout; |
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| 247 | } |
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| 248 | |
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[890] | 249 | bool Fitter::setParameters(std::vector<float> params) |
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[91] | 250 | { |
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| 251 | Vector<Float> tmppar(params); |
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| 252 | if (funcs_.nelements() == 0) |
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| 253 | throw (AipsError("Function not yet set.")); |
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| 254 | if (parameters_.nelements() > 0 && tmppar.nelements() != parameters_.nelements()) |
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| 255 | throw (AipsError("Number of parameters inconsistent with function.")); |
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[1232] | 256 | if (parameters_.nelements() == 0) { |
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[91] | 257 | parameters_.resize(tmppar.nelements()); |
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[1232] | 258 | if (tmppar.nelements() != fixedpar_.nelements()) { |
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| 259 | fixedpar_.resize(tmppar.nelements()); |
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| 260 | fixedpar_ = False; |
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| 261 | } |
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| 262 | } |
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[91] | 263 | if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) { |
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| 264 | uInt count = 0; |
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| 265 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 266 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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| 267 | (funcs_[j]->parameters())[i] = tmppar[count]; |
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| 268 | parameters_[count] = tmppar[count]; |
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| 269 | ++count; |
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| 270 | } |
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| 271 | } |
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[1819] | 272 | } else if (dynamic_cast<Lorentzian1D<Float>* >(funcs_[0]) != 0) { |
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| 273 | uInt count = 0; |
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| 274 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 275 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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| 276 | (funcs_[j]->parameters())[i] = tmppar[count]; |
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| 277 | parameters_[count] = tmppar[count]; |
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| 278 | ++count; |
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| 279 | } |
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| 280 | } |
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[2047] | 281 | } else if (dynamic_cast<Sinusoid1D<Float>* >(funcs_[0]) != 0) { |
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| 282 | uInt count = 0; |
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| 283 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 284 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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| 285 | (funcs_[j]->parameters())[i] = tmppar[count]; |
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| 286 | parameters_[count] = tmppar[count]; |
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| 287 | ++count; |
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| 288 | } |
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| 289 | } |
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| 290 | } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) { |
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| 291 | for (uInt i=0; i < funcs_[0]->nparameters(); ++i) { |
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| 292 | parameters_[i] = tmppar[i]; |
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| 293 | (funcs_[0]->parameters())[i] = tmppar[i]; |
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| 294 | } |
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[91] | 295 | } |
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[1232] | 296 | // reset |
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| 297 | if (params.size() == 0) { |
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| 298 | parameters_.resize(); |
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| 299 | fixedpar_.resize(); |
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| 300 | } |
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[91] | 301 | return true; |
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| 302 | } |
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| 303 | |
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[2666] | 304 | void Fitter::addConstraint(const std::vector<float>& constraint) |
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| 305 | { |
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| 306 | if (funcs_.nelements() == 0) |
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| 307 | throw (AipsError("Function not yet set.")); |
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| 308 | constraints_.push_back(constraint); |
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| 309 | |
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| 310 | } |
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| 311 | |
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| 312 | void Fitter::applyConstraints(GenericL2Fit<Float>& fitter) |
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| 313 | { |
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| 314 | std::vector<std::vector<float> >::const_iterator it; |
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| 315 | for (it = constraints_.begin(); it != constraints_.end(); ++it) { |
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| 316 | Vector<Float> tmp(*it); |
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| 317 | fitter.addConstraint(tmp(Slice(0,tmp.nelements()-1)), |
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| 318 | tmp(tmp.nelements()-1)); |
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| 319 | } |
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| 320 | } |
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| 321 | |
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[890] | 322 | bool Fitter::setFixedParameters(std::vector<bool> fixed) |
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[91] | 323 | { |
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| 324 | if (funcs_.nelements() == 0) |
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| 325 | throw (AipsError("Function not yet set.")); |
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[1232] | 326 | if (fixedpar_.nelements() > 0 && fixed.size() != fixedpar_.nelements()) |
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[91] | 327 | throw (AipsError("Number of mask elements inconsistent with function.")); |
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[1232] | 328 | if (fixedpar_.nelements() == 0) { |
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| 329 | fixedpar_.resize(parameters_.nelements()); |
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| 330 | fixedpar_ = False; |
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| 331 | } |
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[91] | 332 | if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) { |
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| 333 | uInt count = 0; |
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| 334 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 335 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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[1232] | 336 | funcs_[j]->mask(i) = !fixed[count]; |
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| 337 | fixedpar_[count] = fixed[count]; |
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[91] | 338 | ++count; |
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| 339 | } |
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| 340 | } |
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[1819] | 341 | } else if (dynamic_cast<Lorentzian1D<Float>* >(funcs_[0]) != 0) { |
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| 342 | uInt count = 0; |
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| 343 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 344 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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| 345 | funcs_[j]->mask(i) = !fixed[count]; |
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| 346 | fixedpar_[count] = fixed[count]; |
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| 347 | ++count; |
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| 348 | } |
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| 349 | } |
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[2047] | 350 | } else if (dynamic_cast<Sinusoid1D<Float>* >(funcs_[0]) != 0) { |
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| 351 | uInt count = 0; |
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| 352 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 353 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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| 354 | funcs_[j]->mask(i) = !fixed[count]; |
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| 355 | fixedpar_[count] = fixed[count]; |
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| 356 | ++count; |
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| 357 | } |
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| 358 | } |
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| 359 | } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) { |
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| 360 | for (uInt i=0; i < funcs_[0]->nparameters(); ++i) { |
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| 361 | fixedpar_[i] = fixed[i]; |
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| 362 | funcs_[0]->mask(i) = !fixed[i]; |
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| 363 | } |
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[91] | 364 | } |
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| 365 | return true; |
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| 366 | } |
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| 367 | |
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[890] | 368 | std::vector<float> Fitter::getParameters() const { |
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[91] | 369 | Vector<Float> out = parameters_; |
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| 370 | std::vector<float> stlout; |
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| 371 | out.tovector(stlout); |
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| 372 | return stlout; |
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| 373 | } |
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| 374 | |
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[890] | 375 | std::vector<bool> Fitter::getFixedParameters() const { |
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[108] | 376 | Vector<Bool> out(parameters_.nelements()); |
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| 377 | if (fixedpar_.nelements() == 0) { |
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[1232] | 378 | return std::vector<bool>(); |
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[108] | 379 | //throw (AipsError("No parameter mask set.")); |
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| 380 | } else { |
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| 381 | out = fixedpar_; |
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| 382 | } |
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| 383 | std::vector<bool> stlout; |
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| 384 | out.tovector(stlout); |
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| 385 | return stlout; |
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[91] | 386 | } |
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| 387 | |
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[890] | 388 | float Fitter::getChisquared() const { |
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[91] | 389 | return chisquared_; |
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| 390 | } |
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| 391 | |
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[890] | 392 | bool Fitter::fit() { |
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[517] | 393 | NonLinearFitLM<Float> fitter; |
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| 394 | CompoundFunction<Float> func; |
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[612] | 395 | |
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| 396 | uInt n = funcs_.nelements(); |
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[517] | 397 | for (uInt i=0; i<n; ++i) { |
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| 398 | func.addFunction(*funcs_[i]); |
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| 399 | } |
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[612] | 400 | |
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[517] | 401 | fitter.setFunction(func); |
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| 402 | fitter.setMaxIter(50+n*10); |
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| 403 | // Convergence criterium |
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| 404 | fitter.setCriteria(0.001); |
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[2666] | 405 | applyConstraints(fitter); |
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[612] | 406 | |
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[517] | 407 | // Fit |
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[2580] | 408 | // Vector<Float> sigma(x_.nelements()); |
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| 409 | // sigma = 1.0; |
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[890] | 410 | |
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[517] | 411 | parameters_.resize(); |
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[2580] | 412 | // parameters_ = fitter.fit(x_, y_, sigma, &m_); |
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| 413 | parameters_ = fitter.fit(x_, y_, &m_); |
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[1067] | 414 | if ( !fitter.converged() ) { |
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| 415 | return false; |
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| 416 | } |
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[517] | 417 | std::vector<float> ps; |
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| 418 | parameters_.tovector(ps); |
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| 419 | setParameters(ps); |
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[612] | 420 | |
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[517] | 421 | error_.resize(); |
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| 422 | error_ = fitter.errors(); |
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[612] | 423 | |
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[517] | 424 | chisquared_ = fitter.getChi2(); |
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[890] | 425 | |
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[517] | 426 | // use fitter.residual(model=True) to get the model |
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| 427 | thefit_.resize(x_.nelements()); |
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| 428 | fitter.residual(thefit_,x_,True); |
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[2580] | 429 | residual_.resize(x_.nelements()); |
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| 430 | residual_ = y_ - thefit_ ; |
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[517] | 431 | return true; |
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| 432 | } |
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[483] | 433 | |
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[1391] | 434 | bool Fitter::lfit() { |
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| 435 | LinearFit<Float> fitter; |
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| 436 | CompoundFunction<Float> func; |
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[483] | 437 | |
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[1391] | 438 | uInt n = funcs_.nelements(); |
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| 439 | for (uInt i=0; i<n; ++i) { |
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| 440 | func.addFunction(*funcs_[i]); |
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| 441 | } |
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| 442 | |
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| 443 | fitter.setFunction(func); |
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[2666] | 444 | applyConstraints(fitter); |
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[1391] | 445 | |
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| 446 | parameters_.resize(); |
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[2580] | 447 | parameters_ = fitter.fit(x_, y_, &m_); |
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[1391] | 448 | std::vector<float> ps; |
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| 449 | parameters_.tovector(ps); |
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| 450 | setParameters(ps); |
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| 451 | |
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| 452 | error_.resize(); |
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| 453 | error_ = fitter.errors(); |
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| 454 | |
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| 455 | chisquared_ = fitter.getChi2(); |
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| 456 | |
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| 457 | thefit_.resize(x_.nelements()); |
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| 458 | fitter.residual(thefit_,x_,True); |
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[2580] | 459 | residual_.resize(x_.nelements()); |
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| 460 | residual_ = y_ - thefit_ ; |
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[1391] | 461 | return true; |
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| 462 | } |
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| 463 | |
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[890] | 464 | std::vector<float> Fitter::evaluate(int whichComp) const |
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| 465 | { |
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[517] | 466 | std::vector<float> stlout; |
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[890] | 467 | uInt idx = uInt(whichComp); |
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[517] | 468 | Float y; |
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| 469 | if ( idx < funcs_.nelements() ) { |
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| 470 | for (uInt i=0; i<x_.nelements(); ++i) { |
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| 471 | y = (*funcs_[idx])(x_[i]); |
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| 472 | stlout.push_back(float(y)); |
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| 473 | } |
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| 474 | } |
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| 475 | return stlout; |
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| 476 | } |
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[483] | 477 | |
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[1932] | 478 | STFitEntry Fitter::getFitEntry() const |
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| 479 | { |
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| 480 | STFitEntry fit; |
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| 481 | fit.setParameters(getParameters()); |
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| 482 | fit.setErrors(getErrors()); |
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| 483 | fit.setComponents(funccomponents_); |
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| 484 | fit.setFunctions(funcnames_); |
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| 485 | fit.setParmasks(getFixedParameters()); |
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| 486 | return fit; |
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| 487 | } |
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[3106] | 488 | |
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| 489 | } |
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