[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 2415 2012-02-17 10:25:29Z WataruKawasaki $ |
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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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[2415] | 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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[125] | 51 | using namespace casa; |
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[91] | 52 | |
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[890] | 53 | Fitter::Fitter() |
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[91] | 54 | { |
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| 55 | } |
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| 56 | |
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[890] | 57 | Fitter::~Fitter() |
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[91] | 58 | { |
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[517] | 59 | reset(); |
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[91] | 60 | } |
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| 61 | |
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[890] | 62 | void Fitter::clear() |
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[91] | 63 | { |
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[517] | 64 | for (uInt i=0;i< funcs_.nelements();++i) { |
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| 65 | delete funcs_[i]; funcs_[i] = 0; |
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| 66 | } |
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[612] | 67 | funcs_.resize(0,True); |
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[517] | 68 | parameters_.resize(); |
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[1232] | 69 | fixedpar_.resize(); |
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[517] | 70 | error_.resize(); |
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| 71 | thefit_.resize(); |
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| 72 | estimate_.resize(); |
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| 73 | chisquared_ = 0.0; |
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[91] | 74 | } |
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[517] | 75 | |
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[890] | 76 | void Fitter::reset() |
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[91] | 77 | { |
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[517] | 78 | clear(); |
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| 79 | x_.resize(); |
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| 80 | y_.resize(); |
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| 81 | m_.resize(); |
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[91] | 82 | } |
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| 83 | |
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| 84 | |
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[890] | 85 | bool Fitter::computeEstimate() { |
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[517] | 86 | if (x_.nelements() == 0 || y_.nelements() == 0) |
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| 87 | throw (AipsError("No x/y data specified.")); |
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[91] | 88 | |
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[517] | 89 | if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) == 0) |
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| 90 | return false; |
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| 91 | uInt n = funcs_.nelements(); |
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| 92 | SpectralEstimate estimator(n); |
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| 93 | estimator.setQ(5); |
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| 94 | Int mn,mx; |
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| 95 | mn = 0; |
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| 96 | mx = m_.nelements()-1; |
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| 97 | for (uInt i=0; i<m_.nelements();++i) { |
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| 98 | if (m_[i]) { |
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| 99 | mn = i; |
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| 100 | break; |
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[108] | 101 | } |
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[517] | 102 | } |
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[2163] | 103 | // use Int to suppress compiler warning |
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| 104 | for (Int j=m_.nelements()-1; j>=0;--j) { |
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[517] | 105 | if (m_[j]) { |
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| 106 | mx = j; |
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| 107 | break; |
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[108] | 108 | } |
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[517] | 109 | } |
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[1067] | 110 | //mn = 0+x_.nelements()/10; |
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| 111 | //mx = x_.nelements()-x_.nelements()/10; |
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[517] | 112 | estimator.setRegion(mn,mx); |
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| 113 | //estimator.setWindowing(True); |
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| 114 | SpectralList listGauss = estimator.estimate(x_, y_); |
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| 115 | parameters_.resize(n*3); |
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| 116 | Gaussian1D<Float>* g = 0; |
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| 117 | for (uInt i=0; i<n;i++) { |
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| 118 | g = dynamic_cast<Gaussian1D<Float>* >(funcs_[i]); |
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| 119 | if (g) { |
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[2394] | 120 | const GaussianSpectralElement *gauss = dynamic_cast<const GaussianSpectralElement *>(listGauss[i]) ; |
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| 121 | (*g)[0] = gauss->getAmpl(); |
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| 122 | (*g)[1] = gauss->getCenter(); |
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| 123 | (*g)[2] = gauss->getFWHM(); |
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| 124 | // (*g)[0] = listGauss[i].getAmpl(); |
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| 125 | // (*g)[1] = listGauss[i].getCenter(); |
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| 126 | // (*g)[2] = listGauss[i].getFWHM(); |
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[91] | 127 | } |
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[517] | 128 | } |
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| 129 | estimate_.resize(); |
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| 130 | listGauss.evaluate(estimate_,x_); |
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| 131 | return true; |
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[91] | 132 | } |
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| 133 | |
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[890] | 134 | std::vector<float> Fitter::getEstimate() const |
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[91] | 135 | { |
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[517] | 136 | if (estimate_.nelements() == 0) |
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| 137 | throw (AipsError("No estimate set.")); |
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| 138 | std::vector<float> stlout; |
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| 139 | estimate_.tovector(stlout); |
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| 140 | return stlout; |
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[91] | 141 | } |
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| 142 | |
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| 143 | |
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[890] | 144 | bool Fitter::setExpression(const std::string& expr, int ncomp) |
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[91] | 145 | { |
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[517] | 146 | clear(); |
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| 147 | if (expr == "gauss") { |
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| 148 | if (ncomp < 1) throw (AipsError("Need at least one gaussian to fit.")); |
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| 149 | funcs_.resize(ncomp); |
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[1932] | 150 | funcnames_.clear(); |
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| 151 | funccomponents_.clear(); |
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[517] | 152 | for (Int k=0; k<ncomp; ++k) { |
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| 153 | funcs_[k] = new Gaussian1D<Float>(); |
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[1932] | 154 | funcnames_.push_back(expr); |
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| 155 | funccomponents_.push_back(3); |
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[517] | 156 | } |
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[1819] | 157 | } else if (expr == "lorentz") { |
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| 158 | if (ncomp < 1) throw (AipsError("Need at least one lorentzian to fit.")); |
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| 159 | funcs_.resize(ncomp); |
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[1932] | 160 | funcnames_.clear(); |
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| 161 | funccomponents_.clear(); |
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[1819] | 162 | for (Int k=0; k<ncomp; ++k) { |
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| 163 | funcs_[k] = new Lorentzian1D<Float>(); |
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[1932] | 164 | funcnames_.push_back(expr); |
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| 165 | funccomponents_.push_back(3); |
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[1819] | 166 | } |
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[2047] | 167 | } else if (expr == "sinusoid") { |
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| 168 | if (ncomp < 1) throw (AipsError("Need at least one sinusoid to fit.")); |
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| 169 | funcs_.resize(ncomp); |
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| 170 | funcnames_.clear(); |
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| 171 | funccomponents_.clear(); |
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| 172 | for (Int k=0; k<ncomp; ++k) { |
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| 173 | funcs_[k] = new Sinusoid1D<Float>(); |
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| 174 | funcnames_.push_back(expr); |
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| 175 | funccomponents_.push_back(3); |
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| 176 | } |
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| 177 | } else if (expr == "poly") { |
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| 178 | funcs_.resize(1); |
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| 179 | funcnames_.clear(); |
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| 180 | funccomponents_.clear(); |
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| 181 | funcs_[0] = new Polynomial<Float>(ncomp); |
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| 182 | funcnames_.push_back(expr); |
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| 183 | funccomponents_.push_back(ncomp); |
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[517] | 184 | } else { |
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[1819] | 185 | LogIO os( LogOrigin( "Fitter", "setExpression()", WHERE ) ) ; |
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| 186 | os << LogIO::WARN << " compiled functions not yet implemented" << LogIO::POST; |
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[517] | 187 | //funcs_.resize(1); |
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| 188 | //funcs_[0] = new CompiledFunction<Float>(); |
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| 189 | //funcs_[0]->setFunction(String(expr)); |
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| 190 | return false; |
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| 191 | } |
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| 192 | return true; |
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[91] | 193 | } |
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| 194 | |
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[890] | 195 | bool Fitter::setData(std::vector<float> absc, std::vector<float> spec, |
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[91] | 196 | std::vector<bool> mask) |
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| 197 | { |
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| 198 | x_.resize(); |
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| 199 | y_.resize(); |
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| 200 | m_.resize(); |
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| 201 | // convert std::vector to casa Vector |
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| 202 | Vector<Float> tmpx(absc); |
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| 203 | Vector<Float> tmpy(spec); |
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| 204 | Vector<Bool> tmpm(mask); |
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| 205 | AlwaysAssert(tmpx.nelements() == tmpy.nelements(), AipsError); |
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| 206 | x_ = tmpx; |
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| 207 | y_ = tmpy; |
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| 208 | m_ = tmpm; |
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| 209 | return true; |
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| 210 | } |
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| 211 | |
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[890] | 212 | std::vector<float> Fitter::getResidual() const |
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[91] | 213 | { |
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| 214 | if (residual_.nelements() == 0) |
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| 215 | throw (AipsError("Function not yet fitted.")); |
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| 216 | std::vector<float> stlout; |
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| 217 | residual_.tovector(stlout); |
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| 218 | return stlout; |
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| 219 | } |
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| 220 | |
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[890] | 221 | std::vector<float> Fitter::getFit() const |
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[91] | 222 | { |
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| 223 | Vector<Float> out = thefit_; |
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| 224 | std::vector<float> stlout; |
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| 225 | out.tovector(stlout); |
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| 226 | return stlout; |
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| 227 | |
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| 228 | } |
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| 229 | |
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[890] | 230 | std::vector<float> Fitter::getErrors() const |
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[91] | 231 | { |
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| 232 | Vector<Float> out = error_; |
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| 233 | std::vector<float> stlout; |
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| 234 | out.tovector(stlout); |
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| 235 | return stlout; |
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| 236 | } |
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| 237 | |
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[890] | 238 | bool Fitter::setParameters(std::vector<float> params) |
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[91] | 239 | { |
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| 240 | Vector<Float> tmppar(params); |
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| 241 | if (funcs_.nelements() == 0) |
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| 242 | throw (AipsError("Function not yet set.")); |
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| 243 | if (parameters_.nelements() > 0 && tmppar.nelements() != parameters_.nelements()) |
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| 244 | throw (AipsError("Number of parameters inconsistent with function.")); |
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[1232] | 245 | if (parameters_.nelements() == 0) { |
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[91] | 246 | parameters_.resize(tmppar.nelements()); |
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[1232] | 247 | if (tmppar.nelements() != fixedpar_.nelements()) { |
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| 248 | fixedpar_.resize(tmppar.nelements()); |
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| 249 | fixedpar_ = False; |
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| 250 | } |
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| 251 | } |
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[91] | 252 | if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) { |
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| 253 | uInt count = 0; |
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| 254 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 255 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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| 256 | (funcs_[j]->parameters())[i] = tmppar[count]; |
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| 257 | parameters_[count] = tmppar[count]; |
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| 258 | ++count; |
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| 259 | } |
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| 260 | } |
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[1819] | 261 | } else if (dynamic_cast<Lorentzian1D<Float>* >(funcs_[0]) != 0) { |
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| 262 | uInt count = 0; |
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| 263 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 264 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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| 265 | (funcs_[j]->parameters())[i] = tmppar[count]; |
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| 266 | parameters_[count] = tmppar[count]; |
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| 267 | ++count; |
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| 268 | } |
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| 269 | } |
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[2047] | 270 | } else if (dynamic_cast<Sinusoid1D<Float>* >(funcs_[0]) != 0) { |
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| 271 | uInt count = 0; |
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| 272 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 273 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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| 274 | (funcs_[j]->parameters())[i] = tmppar[count]; |
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| 275 | parameters_[count] = tmppar[count]; |
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| 276 | ++count; |
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| 277 | } |
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| 278 | } |
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| 279 | } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) { |
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| 280 | for (uInt i=0; i < funcs_[0]->nparameters(); ++i) { |
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| 281 | parameters_[i] = tmppar[i]; |
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| 282 | (funcs_[0]->parameters())[i] = tmppar[i]; |
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| 283 | } |
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[91] | 284 | } |
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[1232] | 285 | // reset |
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| 286 | if (params.size() == 0) { |
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| 287 | parameters_.resize(); |
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| 288 | fixedpar_.resize(); |
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| 289 | } |
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[91] | 290 | return true; |
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| 291 | } |
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| 292 | |
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[890] | 293 | bool Fitter::setFixedParameters(std::vector<bool> fixed) |
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[91] | 294 | { |
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| 295 | if (funcs_.nelements() == 0) |
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| 296 | throw (AipsError("Function not yet set.")); |
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[1232] | 297 | if (fixedpar_.nelements() > 0 && fixed.size() != fixedpar_.nelements()) |
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[91] | 298 | throw (AipsError("Number of mask elements inconsistent with function.")); |
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[1232] | 299 | if (fixedpar_.nelements() == 0) { |
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| 300 | fixedpar_.resize(parameters_.nelements()); |
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| 301 | fixedpar_ = False; |
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| 302 | } |
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[91] | 303 | if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) { |
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| 304 | uInt count = 0; |
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| 305 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 306 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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[1232] | 307 | funcs_[j]->mask(i) = !fixed[count]; |
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| 308 | fixedpar_[count] = fixed[count]; |
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[91] | 309 | ++count; |
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| 310 | } |
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| 311 | } |
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[1819] | 312 | } else if (dynamic_cast<Lorentzian1D<Float>* >(funcs_[0]) != 0) { |
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| 313 | uInt count = 0; |
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| 314 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 315 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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| 316 | funcs_[j]->mask(i) = !fixed[count]; |
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| 317 | fixedpar_[count] = fixed[count]; |
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| 318 | ++count; |
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| 319 | } |
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| 320 | } |
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[2047] | 321 | } else if (dynamic_cast<Sinusoid1D<Float>* >(funcs_[0]) != 0) { |
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| 322 | uInt count = 0; |
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| 323 | for (uInt j=0; j < funcs_.nelements(); ++j) { |
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| 324 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) { |
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| 325 | funcs_[j]->mask(i) = !fixed[count]; |
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| 326 | fixedpar_[count] = fixed[count]; |
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| 327 | ++count; |
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| 328 | } |
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| 329 | } |
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| 330 | } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) { |
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| 331 | for (uInt i=0; i < funcs_[0]->nparameters(); ++i) { |
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| 332 | fixedpar_[i] = fixed[i]; |
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| 333 | funcs_[0]->mask(i) = !fixed[i]; |
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| 334 | } |
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[91] | 335 | } |
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| 336 | return true; |
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| 337 | } |
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| 338 | |
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[890] | 339 | std::vector<float> Fitter::getParameters() const { |
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[91] | 340 | Vector<Float> out = parameters_; |
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| 341 | std::vector<float> stlout; |
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| 342 | out.tovector(stlout); |
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| 343 | return stlout; |
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| 344 | } |
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| 345 | |
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[890] | 346 | std::vector<bool> Fitter::getFixedParameters() const { |
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[108] | 347 | Vector<Bool> out(parameters_.nelements()); |
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| 348 | if (fixedpar_.nelements() == 0) { |
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[1232] | 349 | return std::vector<bool>(); |
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[108] | 350 | //throw (AipsError("No parameter mask set.")); |
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| 351 | } else { |
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| 352 | out = fixedpar_; |
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| 353 | } |
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| 354 | std::vector<bool> stlout; |
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| 355 | out.tovector(stlout); |
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| 356 | return stlout; |
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[91] | 357 | } |
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| 358 | |
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[890] | 359 | float Fitter::getChisquared() const { |
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[91] | 360 | return chisquared_; |
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| 361 | } |
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| 362 | |
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[890] | 363 | bool Fitter::fit() { |
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[517] | 364 | NonLinearFitLM<Float> fitter; |
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| 365 | CompoundFunction<Float> func; |
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[612] | 366 | |
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| 367 | uInt n = funcs_.nelements(); |
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[517] | 368 | for (uInt i=0; i<n; ++i) { |
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| 369 | func.addFunction(*funcs_[i]); |
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| 370 | } |
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[612] | 371 | |
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[517] | 372 | fitter.setFunction(func); |
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| 373 | fitter.setMaxIter(50+n*10); |
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| 374 | // Convergence criterium |
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| 375 | fitter.setCriteria(0.001); |
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[612] | 376 | |
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[517] | 377 | // Fit |
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| 378 | Vector<Float> sigma(x_.nelements()); |
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| 379 | sigma = 1.0; |
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[890] | 380 | |
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[517] | 381 | parameters_.resize(); |
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| 382 | parameters_ = fitter.fit(x_, y_, sigma, &m_); |
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[1067] | 383 | if ( !fitter.converged() ) { |
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| 384 | return false; |
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| 385 | } |
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[517] | 386 | std::vector<float> ps; |
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| 387 | parameters_.tovector(ps); |
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| 388 | setParameters(ps); |
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[612] | 389 | |
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[517] | 390 | error_.resize(); |
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| 391 | error_ = fitter.errors(); |
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[612] | 392 | |
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[517] | 393 | chisquared_ = fitter.getChi2(); |
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[890] | 394 | |
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[517] | 395 | residual_.resize(); |
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| 396 | residual_ = y_; |
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| 397 | fitter.residual(residual_,x_); |
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| 398 | // use fitter.residual(model=True) to get the model |
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| 399 | thefit_.resize(x_.nelements()); |
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| 400 | fitter.residual(thefit_,x_,True); |
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| 401 | return true; |
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| 402 | } |
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[483] | 403 | |
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[1391] | 404 | bool Fitter::lfit() { |
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| 405 | LinearFit<Float> fitter; |
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| 406 | CompoundFunction<Float> func; |
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[483] | 407 | |
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[1391] | 408 | uInt n = funcs_.nelements(); |
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| 409 | for (uInt i=0; i<n; ++i) { |
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| 410 | func.addFunction(*funcs_[i]); |
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| 411 | } |
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| 412 | |
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| 413 | fitter.setFunction(func); |
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| 414 | //fitter.setMaxIter(50+n*10); |
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| 415 | // Convergence criterium |
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| 416 | //fitter.setCriteria(0.001); |
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| 417 | |
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| 418 | // Fit |
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| 419 | Vector<Float> sigma(x_.nelements()); |
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| 420 | sigma = 1.0; |
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| 421 | |
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| 422 | parameters_.resize(); |
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| 423 | parameters_ = fitter.fit(x_, y_, sigma, &m_); |
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| 424 | std::vector<float> ps; |
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| 425 | parameters_.tovector(ps); |
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| 426 | setParameters(ps); |
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| 427 | |
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| 428 | error_.resize(); |
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| 429 | error_ = fitter.errors(); |
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| 430 | |
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| 431 | chisquared_ = fitter.getChi2(); |
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| 432 | |
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| 433 | residual_.resize(); |
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| 434 | residual_ = y_; |
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| 435 | fitter.residual(residual_,x_); |
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| 436 | // use fitter.residual(model=True) to get the model |
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| 437 | thefit_.resize(x_.nelements()); |
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| 438 | fitter.residual(thefit_,x_,True); |
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| 439 | return true; |
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| 440 | } |
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| 441 | |
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[890] | 442 | std::vector<float> Fitter::evaluate(int whichComp) const |
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| 443 | { |
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[517] | 444 | std::vector<float> stlout; |
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[890] | 445 | uInt idx = uInt(whichComp); |
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[517] | 446 | Float y; |
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| 447 | if ( idx < funcs_.nelements() ) { |
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| 448 | for (uInt i=0; i<x_.nelements(); ++i) { |
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| 449 | y = (*funcs_[idx])(x_[i]); |
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| 450 | stlout.push_back(float(y)); |
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| 451 | } |
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| 452 | } |
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| 453 | return stlout; |
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| 454 | } |
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[483] | 455 | |
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[1932] | 456 | STFitEntry Fitter::getFitEntry() const |
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| 457 | { |
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| 458 | STFitEntry fit; |
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| 459 | fit.setParameters(getParameters()); |
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| 460 | fit.setErrors(getErrors()); |
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| 461 | fit.setComponents(funccomponents_); |
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| 462 | fit.setFunctions(funcnames_); |
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| 463 | fit.setParmasks(getFixedParameters()); |
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| 464 | return fit; |
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| 465 | } |
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