source: branches/Release12/src/SDFitter.cc@ 2941

Last change on this file since 2941 was 612, checked in by mar637, 20 years ago

Fix for asap0017
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  • Property svn:keywords set to Author Date Id Revision
File size: 8.9 KB
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1//#---------------------------------------------------------------------------
2//# SDFitter.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:
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 "SDFitter.h"
46using namespace asap;
47using namespace casa;
48
49SDFitter::SDFitter()
50{
51}
52
53SDFitter::~SDFitter()
54{
55 reset();
56}
57
58void SDFitter::clear()
59{
60 for (uInt i=0;i< funcs_.nelements();++i) {
61 delete funcs_[i]; funcs_[i] = 0;
62 }
63 funcs_.resize(0,True);
64 parameters_.resize();
65 error_.resize();
66 thefit_.resize();
67 estimate_.resize();
68 chisquared_ = 0.0;
69}
70
71void SDFitter::reset()
72{
73 clear();
74 x_.resize();
75 y_.resize();
76 m_.resize();
77}
78
79
80bool SDFitter::computeEstimate() {
81 if (x_.nelements() == 0 || y_.nelements() == 0)
82 throw (AipsError("No x/y data specified."));
83
84 if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) == 0)
85 return false;
86 uInt n = funcs_.nelements();
87 SpectralEstimate estimator(n);
88 estimator.setQ(5);
89 Int mn,mx;
90 mn = 0;
91 mx = m_.nelements()-1;
92 for (uInt i=0; i<m_.nelements();++i) {
93 if (m_[i]) {
94 mn = i;
95 break;
96 }
97 }
98 for (uInt j=m_.nelements()-1; j>=0;--j) {
99 if (m_[j]) {
100 mx = j;
101 break;
102 }
103 }
104 mn = 0+x_.nelements()/10;
105 mx = x_.nelements()-x_.nelements()/10;
106 estimator.setRegion(mn,mx);
107 //estimator.setWindowing(True);
108 SpectralList listGauss = estimator.estimate(x_, y_);
109 parameters_.resize(n*3);
110 Gaussian1D<Float>* g = 0;
111 for (uInt i=0; i<n;i++) {
112 g = dynamic_cast<Gaussian1D<Float>* >(funcs_[i]);
113 if (g) {
114 (*g)[0] = listGauss[i].getAmpl();
115 (*g)[1] = listGauss[i].getCenter();
116 (*g)[2] = listGauss[i].getFWHM();
117 }
118 }
119 estimate_.resize();
120 listGauss.evaluate(estimate_,x_);
121 return true;
122}
123
124std::vector<float> SDFitter::getEstimate() const
125{
126 if (estimate_.nelements() == 0)
127 throw (AipsError("No estimate set."));
128 std::vector<float> stlout;
129 estimate_.tovector(stlout);
130 return stlout;
131}
132
133
134bool SDFitter::setExpression(const std::string& expr, int ncomp)
135{
136 clear();
137 if (expr == "gauss") {
138 if (ncomp < 1) throw (AipsError("Need at least one gaussian to fit."));
139 funcs_.resize(ncomp);
140 for (Int k=0; k<ncomp; ++k) {
141 funcs_[k] = new Gaussian1D<Float>();
142 }
143 } else if (expr == "poly") {
144 funcs_.resize(1);
145 funcs_[0] = new Polynomial<Float>(ncomp);
146 } else {
147 cerr << " compiled functions not yet implemented" << endl;
148 //funcs_.resize(1);
149 //funcs_[0] = new CompiledFunction<Float>();
150 //funcs_[0]->setFunction(String(expr));
151 return false;
152 }
153 return true;
154}
155
156bool SDFitter::setData(std::vector<float> absc, std::vector<float> spec,
157 std::vector<bool> mask)
158{
159 x_.resize();
160 y_.resize();
161 m_.resize();
162 // convert std::vector to casa Vector
163 Vector<Float> tmpx(absc);
164 Vector<Float> tmpy(spec);
165 Vector<Bool> tmpm(mask);
166 AlwaysAssert(tmpx.nelements() == tmpy.nelements(), AipsError);
167 x_ = tmpx;
168 y_ = tmpy;
169 m_ = tmpm;
170 return true;
171}
172
173std::vector<float> SDFitter::getResidual() const
174{
175 if (residual_.nelements() == 0)
176 throw (AipsError("Function not yet fitted."));
177 std::vector<float> stlout;
178 residual_.tovector(stlout);
179 return stlout;
180}
181
182std::vector<float> SDFitter::getFit() const
183{
184 Vector<Float> out = thefit_;
185 std::vector<float> stlout;
186 out.tovector(stlout);
187 return stlout;
188
189}
190
191std::vector<float> SDFitter::getErrors() const
192{
193 Vector<Float> out = error_;
194 std::vector<float> stlout;
195 out.tovector(stlout);
196 return stlout;
197}
198
199bool SDFitter::setParameters(std::vector<float> params)
200{
201 Vector<Float> tmppar(params);
202 if (funcs_.nelements() == 0)
203 throw (AipsError("Function not yet set."));
204 if (parameters_.nelements() > 0 && tmppar.nelements() != parameters_.nelements())
205 throw (AipsError("Number of parameters inconsistent with function."));
206 if (parameters_.nelements() == 0)
207 parameters_.resize(tmppar.nelements());
208 fixedpar_.resize(tmppar.nelements());
209 fixedpar_ = False;
210 if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) {
211 uInt count = 0;
212 for (uInt j=0; j < funcs_.nelements(); ++j) {
213 for (uInt i=0; i < funcs_[j]->nparameters(); ++i) {
214 (funcs_[j]->parameters())[i] = tmppar[count];
215 parameters_[count] = tmppar[count];
216 ++count;
217 }
218 }
219 } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) {
220 for (uInt i=0; i < funcs_[0]->nparameters(); ++i) {
221 parameters_[i] = tmppar[i];
222 (funcs_[0]->parameters())[i] = tmppar[i];
223 }
224 }
225 return true;
226}
227
228bool SDFitter::setFixedParameters(std::vector<bool> fixed)
229{
230 Vector<Bool> tmp(fixed);
231 if (funcs_.nelements() == 0)
232 throw (AipsError("Function not yet set."));
233 if (fixedpar_.nelements() > 0 && tmp.nelements() != fixedpar_.nelements())
234 throw (AipsError("Number of mask elements inconsistent with function."));
235 if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) {
236 uInt count = 0;
237 for (uInt j=0; j < funcs_.nelements(); ++j) {
238 for (uInt i=0; i < funcs_[j]->nparameters(); ++i) {
239 funcs_[j]->mask(i) = !tmp[count];
240 fixedpar_[count] = !tmp[count];
241 ++count;
242 }
243 }
244 } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) {
245 for (uInt i=0; i < funcs_[0]->nparameters(); ++i) {
246 fixedpar_[i] = tmp[i];
247 funcs_[0]->mask(i) = tmp[i];
248 }
249 }
250 //fixedpar_ = !tmpmsk;
251 return true;
252}
253
254std::vector<float> SDFitter::getParameters() const {
255 Vector<Float> out = parameters_;
256 std::vector<float> stlout;
257 out.tovector(stlout);
258 return stlout;
259}
260
261std::vector<bool> SDFitter::getFixedParameters() const {
262 Vector<Bool> out(parameters_.nelements());
263 if (fixedpar_.nelements() == 0) {
264 out = False;
265 //throw (AipsError("No parameter mask set."));
266 } else {
267 out = fixedpar_;
268 }
269 std::vector<bool> stlout;
270 out.tovector(stlout);
271 return stlout;
272}
273
274float SDFitter::getChisquared() const {
275 return chisquared_;
276}
277
278bool SDFitter::fit() {
279 NonLinearFitLM<Float> fitter;
280 CompoundFunction<Float> func;
281
282 uInt n = funcs_.nelements();
283 for (uInt i=0; i<n; ++i) {
284 func.addFunction(*funcs_[i]);
285 }
286
287 fitter.setFunction(func);
288 fitter.setMaxIter(50+n*10);
289 // Convergence criterium
290 fitter.setCriteria(0.001);
291
292 // Fit
293 Vector<Float> sigma(x_.nelements());
294 sigma = 1.0;
295
296 parameters_.resize();
297 parameters_ = fitter.fit(x_, y_, sigma, &m_);
298 std::vector<float> ps;
299 parameters_.tovector(ps);
300 setParameters(ps);
301
302 error_.resize();
303 error_ = fitter.errors();
304
305 chisquared_ = fitter.getChi2();
306
307 residual_.resize();
308 residual_ = y_;
309 fitter.residual(residual_,x_);
310
311 // use fitter.residual(model=True) to get the model
312 thefit_.resize(x_.nelements());
313 fitter.residual(thefit_,x_,True);
314 return true;
315}
316
317
318std::vector<float> SDFitter::evaluate(int whichComp) const
319{
320 std::vector<float> stlout;
321 uInt idx = uInt(whichComp);
322 Float y;
323 if ( idx < funcs_.nelements() ) {
324 for (uInt i=0; i<x_.nelements(); ++i) {
325 y = (*funcs_[idx])(x_[i]);
326 stlout.push_back(float(y));
327 }
328 }
329 return stlout;
330}
331
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