source: trunk/src/SDFitter.cc@ 95

Last change on this file since 95 was 91, checked in by mar637, 20 years ago

New Fitter class for ASAP.
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File size: 9.8 KB
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1//#---------------------------------------------------------------------------
2//# SDFitter.cc: A Fitter class for spectra
3//#--------------------------------------------------------------------------
4//# Copyright (C) 2004
5//# Malte Marquarding, 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/Arrays/ArrayMath.h>
32#include <casa/Arrays/ArrayLogical.h>
33#include <scimath/Fitting.h>
34#include <scimath/Fitting/LinearFit.h>
35#include <scimath/Functionals/CompiledFunction.h>
36#include <scimath/Functionals/CompoundFunction.h>
37#include <scimath/Functionals/Gaussian1D.h>
38#include <scimath/Functionals/Polynomial.h>
39#include <scimath/Mathematics/AutoDiff.h>
40#include <scimath/Mathematics/AutoDiffMath.h>
41#include <scimath/Fitting/NonLinearFitLM.h>
42#include <components/SpectralComponents/SpectralEstimate.h>
43
44#include "SDFitter.h"
45using namespace asap;
46
47SDFitter::SDFitter()
48{
49}
50
51SDFitter::~SDFitter()
52{
53 reset();
54}
55
56void SDFitter::clear()
57{
58 for (uInt i=0;i< funcs_.nelements();++i) {
59 delete funcs_[i]; funcs_[i] = 0;
60 };
61 funcs_.resize(0, True);
62 parameters_.resize();
63 error_.resize();
64 thefit_.resize();
65 estimate_.resize();
66 chisquared_ = 0.0;
67}
68void SDFitter::reset()
69{
70 clear();
71 x_.resize();
72 y_.resize();
73 m_.resize();
74}
75
76
77bool SDFitter::computeEstimate() {
78 if (x_.nelements() == 0 || y_.nelements() == 0)
79 throw (AipsError("No x/y data specified."));
80
81 if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) == 0)
82 return false;
83 uInt n = funcs_.nelements();
84 SpectralEstimate estimator(n);
85 estimator.setQ(5);
86 //estimator.setWindowing(True);
87 SpectralList listGauss = estimator.estimate(x_, y_);
88 Gaussian1D<Float>* g;
89 parameters_.resize(n*3);
90 uInt count = 0;
91 cout << "n = " << n << endl;
92 for (uInt i=0; i<n;i++) {
93 g = dynamic_cast<Gaussian1D<Float>* >(funcs_[i]);
94 if (g) {
95 (*g)[0] = listGauss[i].getAmpl();
96 (*g)[1] = listGauss[i].getCenter();
97 (*g)[2] = listGauss[i].getFWHM();
98 ++count;
99 }
100 }
101 estimate_.resize();
102 listGauss.evaluate(estimate_,x_);
103 return true;
104}
105
106std::vector<float> SDFitter::getEstimate() const
107{
108 if (estimate_.nelements() == 0)
109 throw (AipsError("No estimate set."));
110 std::vector<float> stlout;
111 estimate_.tovector(stlout);
112 return stlout;
113}
114
115
116bool SDFitter::setExpression(const std::string& expr, int ncomp)
117{
118 clear();
119 if (expr == "gauss") {
120 if (ncomp < 1) throw (AipsError("Need at least one gaussian to fit."));
121 funcs_.resize(ncomp);
122 for (Int k=0; k<ncomp; ++k) {
123 funcs_[k] = new Gaussian1D<Float>();
124 }
125 } else if (expr == "poly") {
126 funcs_.resize(1);
127 funcs_[0] = new Polynomial<Float>(ncomp);
128 } else {
129 cerr << " compiled functions not yet implemented" << endl;
130 //funcs_.resize(1);
131 //funcs_[0] = new CompiledFunction<Float>();
132 //funcs_[0]->setFunction(String(expr));
133 return false;
134 };
135 return true;
136}
137
138bool SDFitter::setData(std::vector<float> absc, std::vector<float> spec,
139 std::vector<bool> mask)
140{
141 x_.resize();
142 y_.resize();
143 m_.resize();
144 // convert std::vector to casa Vector
145 Vector<Float> tmpx(absc);
146 Vector<Float> tmpy(spec);
147 Vector<Bool> tmpm(mask);
148 AlwaysAssert(tmpx.nelements() == tmpy.nelements(), AipsError);
149 x_ = tmpx;
150 y_ = tmpy;
151 m_ = tmpm;
152 return true;
153}
154
155std::vector<float> SDFitter::getResidual() const
156{
157 if (residual_.nelements() == 0)
158 throw (AipsError("Function not yet fitted."));
159 std::vector<float> stlout;
160 residual_.tovector(stlout);
161 return stlout;
162}
163
164std::vector<float> SDFitter::getFit() const
165{
166 Vector<Float> out = thefit_;
167 std::vector<float> stlout;
168 out.tovector(stlout);
169 return stlout;
170
171}
172
173std::vector<float> SDFitter::getErrors() const
174{
175 Vector<Float> out = error_;
176 std::vector<float> stlout;
177 out.tovector(stlout);
178 return stlout;
179}
180
181bool SDFitter::setParameters(std::vector<float> params)
182{
183 Vector<Float> tmppar(params);
184 if (funcs_.nelements() == 0)
185 throw (AipsError("Function not yet set."));
186 if (parameters_.nelements() > 0 && tmppar.nelements() != parameters_.nelements())
187 throw (AipsError("Number of parameters inconsistent with function."));
188 if (parameters_.nelements() == 0)
189 parameters_.resize(tmppar.nelements());
190 fixedpar_.resize(tmppar.nelements());
191 fixedpar_ = False;
192 if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) {
193 uInt count = 0;
194 for (uInt j=0; j < funcs_.nelements(); ++j) {
195 for (uInt i=0; i < funcs_[j]->nparameters(); ++i) {
196 (funcs_[j]->parameters())[i] = tmppar[count];
197 parameters_[count] = tmppar[count];
198 ++count;
199 }
200 }
201 } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) {
202 for (uInt i=0; i < funcs_[0]->nparameters(); ++i) {
203 parameters_[i] = tmppar[i];
204 (funcs_[0]->parameters())[i] = tmppar[i];
205 }
206 }
207 return true;
208}
209
210bool SDFitter::setFixedParameters(std::vector<bool> fixed)
211{
212 Vector<Bool> tmp(fixed);
213 if (funcs_.nelements() == 0)
214 throw (AipsError("Function not yet set."));
215 if (fixedpar_.nelements() > 0 && tmp.nelements() != fixedpar_.nelements())
216 throw (AipsError("Number of mask elements inconsistent with function."));
217 if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) {
218 uInt count = 0;
219 for (uInt j=0; j < funcs_.nelements(); ++j) {
220 for (uInt i=0; i < funcs_[j]->nparameters(); ++i) {
221 funcs_[j]->mask(i) = !tmp[count];
222 fixedpar_[count] = !tmp[count];
223 ++count;
224 }
225 }
226 } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) {
227 for (uInt i=0; i < funcs_[0]->nparameters(); ++i) {
228 fixedpar_[i] = tmp[i];
229 funcs_[0]->mask(i) = tmp[i];
230 }
231 }
232 //fixedpar_ = !tmpmsk;
233 return true;
234}
235
236std::vector<float> SDFitter::getParameters() const {
237 Vector<Float> out = parameters_;
238 std::vector<float> stlout;
239 out.tovector(stlout);
240 return stlout;
241}
242
243std::vector<bool> SDFitter::getFixedParameters() const {
244 if (fixedpar_.nelements() == 0)
245 throw (AipsError("No parameter mask set."));
246 Vector<Bool> out = fixedpar_;
247 std::vector<bool> stlout;
248 out.tovector(stlout);
249 return stlout;
250}
251
252float SDFitter::getChisquared() const {
253 return chisquared_;
254}
255
256bool SDFitter::fit() {
257 NonLinearFitLM<Float> fitter;
258 //CompiledFunction<AutoDiff<Float> > comp;
259 //Polynomial<AutoDiff<Float> > poly;
260 CompoundFunction<AutoDiff<Float> > func;
261 if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) {
262 //computeEstimates();
263 for (uInt i=0; i<funcs_.nelements(); i++) {
264 Gaussian1D<AutoDiff<Float> > gauss;
265 for (uInt j=0; j<funcs_[i]->nparameters(); j++) {
266 gauss[j] = AutoDiff<Float>((*funcs_[i])[j], gauss.nparameters(), j);
267 gauss.mask(j) = funcs_[i]->mask(j);
268 }
269 func.addFunction(gauss);
270 }
271 } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) {
272 Polynomial<AutoDiff<Float> > poly(funcs_[0]->nparameters()-1);
273 for (uInt j=0; j<funcs_[0]->nparameters(); j++) {
274 poly[j] = AutoDiff<Float>(0, poly.nparameters(), j);
275 poly.mask(j) = funcs_[0]->mask(j);
276 }
277 func.addFunction(poly);
278 } else if (dynamic_cast<CompiledFunction<Float>* >(funcs_[0]) != 0) {
279
280// CompiledFunction<AutoDiff<Float> > comp;
281// for (uInt j=0; j<funcs_[0]->nparameters(); j++) {
282// comp[j] = AutoDiff<Float>(0, comp.nparameters(), j);
283// comp.mask(j) = funcs_[0]->mask(j);
284// }
285// func.addFunction(comp);
286
287 cout << "NYI." << endl;
288 } else {
289 throw (AipsError("Fitter not set up correctly."));
290 }
291 fitter.setFunction(func);
292 fitter.setMaxIter(50+funcs_.nelements()*10);
293 // Convergence criterium
294 fitter.setCriteria(0.001);
295 // Fit
296 Vector<Float> sigma(x_.nelements());
297 sigma = 1.0;
298 //Vector<Float> sol;
299 parameters_.resize();
300 //Vector<Float> err;
301 error_.resize();
302 parameters_ = fitter.fit(x_, y_, sigma, &m_);
303 /*
304 CompoundFunction<Float> f;
305 for (uInt i=0; i<funcs_.nelements(); i++) {
306 f.addFunction(*funcs_[i]);
307 }
308 f.parameters().setParameters(parameters_);
309 */
310 error_ = fitter.errors();
311 chisquared_ = fitter.getChi2();
312 residual_.resize();
313 residual_ = y_;
314 fitter.residual(residual_,x_);
315 // use fitter.residual(model=True) to get the model
316 thefit_.resize(x_.nelements());
317 fitter.residual(thefit_,x_,True);
318 return true;
319}
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