source: branches/Release2.0/src/STFitter.cpp@ 1733

Last change on this file since 1733 was 894, checked in by mar637, 19 years ago

asap2 naming changes
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1//#---------------------------------------------------------------------------
2//# Fitter.cc: A Fitter class for spectra
3//#--------------------------------------------------------------------------
4//# Copyright (C) 2004
5//# ATNF
6//#
7//# This program is free software; you can redistribute it and/or modify it
8//# under the terms of the GNU General Public License as published by the Free
9//# Software Foundation; either version 2 of the License, or (at your option)
10//# any later version.
11//#
12//# This program is distributed in the hope that it will be useful, but
13//# WITHOUT ANY WARRANTY; without even the implied warranty of
14//# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
15//# Public License for more details.
16//#
17//# You should have received a copy of the GNU General Public License along
18//# with this program; if not, write to the Free Software Foundation, Inc.,
19//# 675 Massachusetts Ave, Cambridge, MA 02139, USA.
20//#
21//# Correspondence concerning this software should be addressed as follows:
22//# Internet email: Malte.Marquarding@csiro.au
23//# Postal address: Malte Marquarding,
24//# Australia Telescope National Facility,
25//# P.O. Box 76,
26//# Epping, NSW, 2121,
27//# AUSTRALIA
28//#
29//# $Id: STFitter.cpp 894 2006-03-08 03:03:25Z mar637 $
30//#---------------------------------------------------------------------------
31#include <casa/aips.h>
32#include <casa/Arrays/ArrayMath.h>
33#include <casa/Arrays/ArrayLogical.h>
34#include <scimath/Fitting.h>
35#include <scimath/Fitting/LinearFit.h>
36#include <scimath/Functionals/CompiledFunction.h>
37#include <scimath/Functionals/CompoundFunction.h>
38#include <scimath/Functionals/Gaussian1D.h>
39#include <scimath/Functionals/Polynomial.h>
40#include <scimath/Mathematics/AutoDiff.h>
41#include <scimath/Mathematics/AutoDiffMath.h>
42#include <scimath/Fitting/NonLinearFitLM.h>
43#include <components/SpectralComponents/SpectralEstimate.h>
44
45#include "STFitter.h"
46
47using namespace asap;
48using namespace casa;
49
50Fitter::Fitter()
51{
52}
53
54Fitter::~Fitter()
55{
56 reset();
57}
58
59void Fitter::clear()
60{
61 for (uInt i=0;i< funcs_.nelements();++i) {
62 delete funcs_[i]; funcs_[i] = 0;
63 }
64 funcs_.resize(0,True);
65 parameters_.resize();
66 error_.resize();
67 thefit_.resize();
68 estimate_.resize();
69 chisquared_ = 0.0;
70}
71
72void Fitter::reset()
73{
74 clear();
75 x_.resize();
76 y_.resize();
77 m_.resize();
78}
79
80
81bool Fitter::computeEstimate() {
82 if (x_.nelements() == 0 || y_.nelements() == 0)
83 throw (AipsError("No x/y data specified."));
84
85 if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) == 0)
86 return false;
87 uInt n = funcs_.nelements();
88 SpectralEstimate estimator(n);
89 estimator.setQ(5);
90 Int mn,mx;
91 mn = 0;
92 mx = m_.nelements()-1;
93 for (uInt i=0; i<m_.nelements();++i) {
94 if (m_[i]) {
95 mn = i;
96 break;
97 }
98 }
99 for (uInt j=m_.nelements()-1; j>=0;--j) {
100 if (m_[j]) {
101 mx = j;
102 break;
103 }
104 }
105 mn = 0+x_.nelements()/10;
106 mx = x_.nelements()-x_.nelements()/10;
107 estimator.setRegion(mn,mx);
108 //estimator.setWindowing(True);
109 SpectralList listGauss = estimator.estimate(x_, y_);
110 parameters_.resize(n*3);
111 Gaussian1D<Float>* g = 0;
112 for (uInt i=0; i<n;i++) {
113 g = dynamic_cast<Gaussian1D<Float>* >(funcs_[i]);
114 if (g) {
115 (*g)[0] = listGauss[i].getAmpl();
116 (*g)[1] = listGauss[i].getCenter();
117 (*g)[2] = listGauss[i].getFWHM();
118 }
119 }
120 estimate_.resize();
121 listGauss.evaluate(estimate_,x_);
122 return true;
123}
124
125std::vector<float> Fitter::getEstimate() const
126{
127 if (estimate_.nelements() == 0)
128 throw (AipsError("No estimate set."));
129 std::vector<float> stlout;
130 estimate_.tovector(stlout);
131 return stlout;
132}
133
134
135bool Fitter::setExpression(const std::string& expr, int ncomp)
136{
137 clear();
138 if (expr == "gauss") {
139 if (ncomp < 1) throw (AipsError("Need at least one gaussian to fit."));
140 funcs_.resize(ncomp);
141 for (Int k=0; k<ncomp; ++k) {
142 funcs_[k] = new Gaussian1D<Float>();
143 }
144 } else if (expr == "poly") {
145 funcs_.resize(1);
146 funcs_[0] = new Polynomial<Float>(ncomp);
147 } else {
148 cerr << " compiled functions not yet implemented" << endl;
149 //funcs_.resize(1);
150 //funcs_[0] = new CompiledFunction<Float>();
151 //funcs_[0]->setFunction(String(expr));
152 return false;
153 }
154 return true;
155}
156
157bool Fitter::setData(std::vector<float> absc, std::vector<float> spec,
158 std::vector<bool> mask)
159{
160 x_.resize();
161 y_.resize();
162 m_.resize();
163 // convert std::vector to casa Vector
164 Vector<Float> tmpx(absc);
165 Vector<Float> tmpy(spec);
166 Vector<Bool> tmpm(mask);
167 AlwaysAssert(tmpx.nelements() == tmpy.nelements(), AipsError);
168 x_ = tmpx;
169 y_ = tmpy;
170 m_ = tmpm;
171 return true;
172}
173
174std::vector<float> Fitter::getResidual() const
175{
176 if (residual_.nelements() == 0)
177 throw (AipsError("Function not yet fitted."));
178 std::vector<float> stlout;
179 residual_.tovector(stlout);
180 return stlout;
181}
182
183std::vector<float> Fitter::getFit() const
184{
185 Vector<Float> out = thefit_;
186 std::vector<float> stlout;
187 out.tovector(stlout);
188 return stlout;
189
190}
191
192std::vector<float> Fitter::getErrors() const
193{
194 Vector<Float> out = error_;
195 std::vector<float> stlout;
196 out.tovector(stlout);
197 return stlout;
198}
199
200bool Fitter::setParameters(std::vector<float> params)
201{
202 Vector<Float> tmppar(params);
203 if (funcs_.nelements() == 0)
204 throw (AipsError("Function not yet set."));
205 if (parameters_.nelements() > 0 && tmppar.nelements() != parameters_.nelements())
206 throw (AipsError("Number of parameters inconsistent with function."));
207 if (parameters_.nelements() == 0)
208 parameters_.resize(tmppar.nelements());
209 fixedpar_.resize(tmppar.nelements());
210 fixedpar_ = False;
211 if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) {
212 uInt count = 0;
213 for (uInt j=0; j < funcs_.nelements(); ++j) {
214 for (uInt i=0; i < funcs_[j]->nparameters(); ++i) {
215 (funcs_[j]->parameters())[i] = tmppar[count];
216 parameters_[count] = tmppar[count];
217 ++count;
218 }
219 }
220 } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) {
221 for (uInt i=0; i < funcs_[0]->nparameters(); ++i) {
222 parameters_[i] = tmppar[i];
223 (funcs_[0]->parameters())[i] = tmppar[i];
224 }
225 }
226 return true;
227}
228
229bool Fitter::setFixedParameters(std::vector<bool> fixed)
230{
231 Vector<Bool> tmp(fixed);
232 if (funcs_.nelements() == 0)
233 throw (AipsError("Function not yet set."));
234 if (fixedpar_.nelements() > 0 && tmp.nelements() != fixedpar_.nelements())
235 throw (AipsError("Number of mask elements inconsistent with function."));
236 if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) {
237 uInt count = 0;
238 for (uInt j=0; j < funcs_.nelements(); ++j) {
239 for (uInt i=0; i < funcs_[j]->nparameters(); ++i) {
240 funcs_[j]->mask(i) = !tmp[count];
241 fixedpar_[count] = !tmp[count];
242 ++count;
243 }
244 }
245 } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) {
246 for (uInt i=0; i < funcs_[0]->nparameters(); ++i) {
247 fixedpar_[i] = tmp[i];
248 funcs_[0]->mask(i) = tmp[i];
249 }
250 }
251 //fixedpar_ = !tmpmsk;
252 return true;
253}
254
255std::vector<float> Fitter::getParameters() const {
256 Vector<Float> out = parameters_;
257 std::vector<float> stlout;
258 out.tovector(stlout);
259 return stlout;
260}
261
262std::vector<bool> Fitter::getFixedParameters() const {
263 Vector<Bool> out(parameters_.nelements());
264 if (fixedpar_.nelements() == 0) {
265 out = False;
266 //throw (AipsError("No parameter mask set."));
267 } else {
268 out = fixedpar_;
269 }
270 std::vector<bool> stlout;
271 out.tovector(stlout);
272 return stlout;
273}
274
275float Fitter::getChisquared() const {
276 return chisquared_;
277}
278
279bool Fitter::fit() {
280 NonLinearFitLM<Float> fitter;
281 CompoundFunction<Float> func;
282
283 uInt n = funcs_.nelements();
284 for (uInt i=0; i<n; ++i) {
285 func.addFunction(*funcs_[i]);
286 }
287
288 fitter.setFunction(func);
289 fitter.setMaxIter(50+n*10);
290 // Convergence criterium
291 fitter.setCriteria(0.001);
292
293 // Fit
294 Vector<Float> sigma(x_.nelements());
295 sigma = 1.0;
296
297 parameters_.resize();
298 parameters_ = fitter.fit(x_, y_, sigma, &m_);
299 std::vector<float> ps;
300 parameters_.tovector(ps);
301 setParameters(ps);
302
303 error_.resize();
304 error_ = fitter.errors();
305
306 chisquared_ = fitter.getChi2();
307
308 residual_.resize();
309 residual_ = y_;
310 fitter.residual(residual_,x_);
311
312 // use fitter.residual(model=True) to get the model
313 thefit_.resize(x_.nelements());
314 fitter.residual(thefit_,x_,True);
315 return true;
316}
317
318
319std::vector<float> Fitter::evaluate(int whichComp) const
320{
321 std::vector<float> stlout;
322 uInt idx = uInt(whichComp);
323 Float y;
324 if ( idx < funcs_.nelements() ) {
325 for (uInt i=0; i<x_.nelements(); ++i) {
326 y = (*funcs_[idx])(x_[i]);
327 stlout.push_back(float(y));
328 }
329 }
330 return stlout;
331}
332
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