source: trunk/src/STFitter.cpp @ 1391

Last change on this file since 1391 was 1391, checked in by Malte Marquarding, 17 years ago

merge from alma branch to get alma/GBT support. Commented out fluxUnit changes as they are using a chnaged interface to PKSreader/writer. Also commented out progress meter related code.

  • Property svn:eol-style set to native
  • Property svn:keywords set to Author Date Id Revision
File size: 10.0 KB
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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 1391 2007-07-30 01:59:36Z MalteMarquarding $
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  fixedpar_.resize();
67  error_.resize();
68  thefit_.resize();
69  estimate_.resize();
70  chisquared_ = 0.0;
71}
72
73void Fitter::reset()
74{
75  clear();
76  x_.resize();
77  y_.resize();
78  m_.resize();
79}
80
81
82bool Fitter::computeEstimate() {
83  if (x_.nelements() == 0 || y_.nelements() == 0)
84    throw (AipsError("No x/y data specified."));
85
86  if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) == 0)
87    return false;
88  uInt n = funcs_.nelements();
89  SpectralEstimate estimator(n);
90  estimator.setQ(5);
91  Int mn,mx;
92  mn = 0;
93  mx = m_.nelements()-1;
94  for (uInt i=0; i<m_.nelements();++i) {
95    if (m_[i]) {
96      mn = i;
97      break;
98    }
99  }
100  for (uInt j=m_.nelements()-1; j>=0;--j) {
101    if (m_[j]) {
102      mx = j;
103      break;
104    }
105  }
106  //mn = 0+x_.nelements()/10;
107  //mx = x_.nelements()-x_.nelements()/10;
108  estimator.setRegion(mn,mx);
109  //estimator.setWindowing(True);
110  SpectralList listGauss = estimator.estimate(x_, y_);
111  parameters_.resize(n*3);
112  Gaussian1D<Float>* g = 0;
113  for (uInt i=0; i<n;i++) {
114    g = dynamic_cast<Gaussian1D<Float>* >(funcs_[i]);
115    if (g) {
116      (*g)[0] = listGauss[i].getAmpl();
117      (*g)[1] = listGauss[i].getCenter();
118      (*g)[2] = listGauss[i].getFWHM();
119    }
120  }
121  estimate_.resize();
122  listGauss.evaluate(estimate_,x_);
123  return true;
124}
125
126std::vector<float> Fitter::getEstimate() const
127{
128  if (estimate_.nelements() == 0)
129    throw (AipsError("No estimate set."));
130  std::vector<float> stlout;
131  estimate_.tovector(stlout);
132  return stlout;
133}
134
135
136bool Fitter::setExpression(const std::string& expr, int ncomp)
137{
138  clear();
139  if (expr == "gauss") {
140    if (ncomp < 1) throw (AipsError("Need at least one gaussian to fit."));
141    funcs_.resize(ncomp);
142    for (Int k=0; k<ncomp; ++k) {
143      funcs_[k] = new Gaussian1D<Float>();
144    }
145  } else if (expr == "poly") {
146    funcs_.resize(1);
147    funcs_[0] = new Polynomial<Float>(ncomp);
148  } else {
149    cerr << " compiled functions not yet implemented" << endl;
150    //funcs_.resize(1);
151    //funcs_[0] = new CompiledFunction<Float>();
152    //funcs_[0]->setFunction(String(expr));
153    return false;
154  }
155  return true;
156}
157
158bool Fitter::setData(std::vector<float> absc, std::vector<float> spec,
159                       std::vector<bool> mask)
160{
161    x_.resize();
162    y_.resize();
163    m_.resize();
164    // convert std::vector to casa Vector
165    Vector<Float> tmpx(absc);
166    Vector<Float> tmpy(spec);
167    Vector<Bool> tmpm(mask);
168    AlwaysAssert(tmpx.nelements() == tmpy.nelements(), AipsError);
169    x_ = tmpx;
170    y_ = tmpy;
171    m_ = tmpm;
172    return true;
173}
174
175std::vector<float> Fitter::getResidual() const
176{
177    if (residual_.nelements() == 0)
178        throw (AipsError("Function not yet fitted."));
179    std::vector<float> stlout;
180    residual_.tovector(stlout);
181    return stlout;
182}
183
184std::vector<float> Fitter::getFit() const
185{
186    Vector<Float> out = thefit_;
187    std::vector<float> stlout;
188    out.tovector(stlout);
189    return stlout;
190
191}
192
193std::vector<float> Fitter::getErrors() const
194{
195    Vector<Float> out = error_;
196    std::vector<float> stlout;
197    out.tovector(stlout);
198    return stlout;
199}
200
201bool Fitter::setParameters(std::vector<float> params)
202{
203    Vector<Float> tmppar(params);
204    if (funcs_.nelements() == 0)
205        throw (AipsError("Function not yet set."));
206    if (parameters_.nelements() > 0 && tmppar.nelements() != parameters_.nelements())
207        throw (AipsError("Number of parameters inconsistent with function."));
208    if (parameters_.nelements() == 0) {
209        parameters_.resize(tmppar.nelements());
210        if (tmppar.nelements() != fixedpar_.nelements()) {
211            fixedpar_.resize(tmppar.nelements());
212            fixedpar_ = False;
213        }
214    }
215    if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) {
216        uInt count = 0;
217        for (uInt j=0; j < funcs_.nelements(); ++j) {
218            for (uInt i=0; i < funcs_[j]->nparameters(); ++i) {
219                (funcs_[j]->parameters())[i] = tmppar[count];
220                parameters_[count] = tmppar[count];
221                ++count;
222            }
223        }
224    } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) {
225        for (uInt i=0; i < funcs_[0]->nparameters(); ++i) {
226            parameters_[i] = tmppar[i];
227            (funcs_[0]->parameters())[i] =  tmppar[i];
228        }
229    }
230    // reset
231    if (params.size() == 0) {
232        parameters_.resize();
233        fixedpar_.resize();
234    }
235    return true;
236}
237
238bool Fitter::setFixedParameters(std::vector<bool> fixed)
239{
240    if (funcs_.nelements() == 0)
241        throw (AipsError("Function not yet set."));
242    if (fixedpar_.nelements() > 0 && fixed.size() != fixedpar_.nelements())
243        throw (AipsError("Number of mask elements inconsistent with function."));
244    if (fixedpar_.nelements() == 0) {
245        fixedpar_.resize(parameters_.nelements());
246        fixedpar_ = False;
247    }
248    if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) {
249        uInt count = 0;
250        for (uInt j=0; j < funcs_.nelements(); ++j) {
251            for (uInt i=0; i < funcs_[j]->nparameters(); ++i) {
252                funcs_[j]->mask(i) = !fixed[count];
253                fixedpar_[count] = fixed[count];
254                ++count;
255            }
256        }
257    } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) {
258        for (uInt i=0; i < funcs_[0]->nparameters(); ++i) {
259            fixedpar_[i] = fixed[i];
260            funcs_[0]->mask(i) =  !fixed[i];
261        }
262    }
263    return true;
264}
265
266std::vector<float> Fitter::getParameters() const {
267    Vector<Float> out = parameters_;
268    std::vector<float> stlout;
269    out.tovector(stlout);
270    return stlout;
271}
272
273std::vector<bool> Fitter::getFixedParameters() const {
274  Vector<Bool> out(parameters_.nelements());
275  if (fixedpar_.nelements() == 0) {
276    return std::vector<bool>();
277    //throw (AipsError("No parameter mask set."));
278  } else {
279    out = fixedpar_;
280  }
281  std::vector<bool> stlout;
282  out.tovector(stlout);
283  return stlout;
284}
285
286float Fitter::getChisquared() const {
287    return chisquared_;
288}
289
290bool Fitter::fit() {
291  NonLinearFitLM<Float> fitter;
292  CompoundFunction<Float> func;
293
294  uInt n = funcs_.nelements();
295  for (uInt i=0; i<n; ++i) {
296    func.addFunction(*funcs_[i]);
297  }
298
299  fitter.setFunction(func);
300  fitter.setMaxIter(50+n*10);
301  // Convergence criterium
302  fitter.setCriteria(0.001);
303
304  // Fit
305  Vector<Float> sigma(x_.nelements());
306  sigma = 1.0;
307
308  parameters_.resize();
309  parameters_ = fitter.fit(x_, y_, sigma, &m_);
310  if ( !fitter.converged() ) {
311     return false;
312  }
313  std::vector<float> ps;
314  parameters_.tovector(ps);
315  setParameters(ps);
316
317  error_.resize();
318  error_ = fitter.errors();
319
320  chisquared_ = fitter.getChi2();
321
322  residual_.resize();
323  residual_ =  y_;
324  fitter.residual(residual_,x_);
325  // use fitter.residual(model=True) to get the model
326  thefit_.resize(x_.nelements());
327  fitter.residual(thefit_,x_,True);
328  return true;
329}
330
331bool Fitter::lfit() {
332  LinearFit<Float> fitter;
333  CompoundFunction<Float> func;
334
335  uInt n = funcs_.nelements();
336  for (uInt i=0; i<n; ++i) {
337    func.addFunction(*funcs_[i]);
338  }
339
340  fitter.setFunction(func);
341  //fitter.setMaxIter(50+n*10);
342  // Convergence criterium
343  //fitter.setCriteria(0.001);
344
345  // Fit
346  Vector<Float> sigma(x_.nelements());
347  sigma = 1.0;
348
349  parameters_.resize();
350  parameters_ = fitter.fit(x_, y_, sigma, &m_);
351  std::vector<float> ps;
352  parameters_.tovector(ps);
353  setParameters(ps);
354
355  error_.resize();
356  error_ = fitter.errors();
357
358  chisquared_ = fitter.getChi2();
359
360  residual_.resize();
361  residual_ =  y_;
362  fitter.residual(residual_,x_);
363  // use fitter.residual(model=True) to get the model
364  thefit_.resize(x_.nelements());
365  fitter.residual(thefit_,x_,True);
366  return true;
367}
368
369std::vector<float> Fitter::evaluate(int whichComp) const
370{
371  std::vector<float> stlout;
372  uInt idx = uInt(whichComp);
373  Float y;
374  if ( idx < funcs_.nelements() ) {
375    for (uInt i=0; i<x_.nelements(); ++i) {
376      y = (*funcs_[idx])(x_[i]);
377      stlout.push_back(float(y));
378    }
379  }
380  return stlout;
381}
382
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