[91] | 1 | //#---------------------------------------------------------------------------
|
---|
[890] | 2 | //# Fitter.cc: A Fitter class for spectra
|
---|
[91] | 3 | //#--------------------------------------------------------------------------
|
---|
| 4 | //# Copyright (C) 2004
|
---|
[125] | 5 | //# ATNF
|
---|
[91] | 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 | //#
|
---|
[891] | 29 | //# $Id: STFitter.cpp 1616 2009-08-07 05:49:27Z TakeshiNakazato $
|
---|
[91] | 30 | //#---------------------------------------------------------------------------
|
---|
[125] | 31 | #include <casa/aips.h>
|
---|
[91] | 32 | #include <casa/Arrays/ArrayMath.h>
|
---|
| 33 | #include <casa/Arrays/ArrayLogical.h>
|
---|
[1616] | 34 | #include <casa/Logging/LogIO.h>
|
---|
[91] | 35 | #include <scimath/Fitting.h>
|
---|
| 36 | #include <scimath/Fitting/LinearFit.h>
|
---|
| 37 | #include <scimath/Functionals/CompiledFunction.h>
|
---|
| 38 | #include <scimath/Functionals/CompoundFunction.h>
|
---|
| 39 | #include <scimath/Functionals/Gaussian1D.h>
|
---|
| 40 | #include <scimath/Functionals/Polynomial.h>
|
---|
| 41 | #include <scimath/Mathematics/AutoDiff.h>
|
---|
| 42 | #include <scimath/Mathematics/AutoDiffMath.h>
|
---|
| 43 | #include <scimath/Fitting/NonLinearFitLM.h>
|
---|
| 44 | #include <components/SpectralComponents/SpectralEstimate.h>
|
---|
| 45 |
|
---|
[894] | 46 | #include "STFitter.h"
|
---|
| 47 |
|
---|
[91] | 48 | using namespace asap;
|
---|
[125] | 49 | using namespace casa;
|
---|
[91] | 50 |
|
---|
[890] | 51 | Fitter::Fitter()
|
---|
[91] | 52 | {
|
---|
| 53 | }
|
---|
| 54 |
|
---|
[890] | 55 | Fitter::~Fitter()
|
---|
[91] | 56 | {
|
---|
[517] | 57 | reset();
|
---|
[91] | 58 | }
|
---|
| 59 |
|
---|
[890] | 60 | void Fitter::clear()
|
---|
[91] | 61 | {
|
---|
[517] | 62 | for (uInt i=0;i< funcs_.nelements();++i) {
|
---|
| 63 | delete funcs_[i]; funcs_[i] = 0;
|
---|
| 64 | }
|
---|
[612] | 65 | funcs_.resize(0,True);
|
---|
[517] | 66 | parameters_.resize();
|
---|
[1232] | 67 | fixedpar_.resize();
|
---|
[517] | 68 | error_.resize();
|
---|
| 69 | thefit_.resize();
|
---|
| 70 | estimate_.resize();
|
---|
| 71 | chisquared_ = 0.0;
|
---|
[91] | 72 | }
|
---|
[517] | 73 |
|
---|
[890] | 74 | void Fitter::reset()
|
---|
[91] | 75 | {
|
---|
[517] | 76 | clear();
|
---|
| 77 | x_.resize();
|
---|
| 78 | y_.resize();
|
---|
| 79 | m_.resize();
|
---|
[91] | 80 | }
|
---|
| 81 |
|
---|
| 82 |
|
---|
[890] | 83 | bool Fitter::computeEstimate() {
|
---|
[517] | 84 | if (x_.nelements() == 0 || y_.nelements() == 0)
|
---|
| 85 | throw (AipsError("No x/y data specified."));
|
---|
[91] | 86 |
|
---|
[517] | 87 | if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) == 0)
|
---|
| 88 | return false;
|
---|
| 89 | uInt n = funcs_.nelements();
|
---|
| 90 | SpectralEstimate estimator(n);
|
---|
| 91 | estimator.setQ(5);
|
---|
| 92 | Int mn,mx;
|
---|
| 93 | mn = 0;
|
---|
| 94 | mx = m_.nelements()-1;
|
---|
| 95 | for (uInt i=0; i<m_.nelements();++i) {
|
---|
| 96 | if (m_[i]) {
|
---|
| 97 | mn = i;
|
---|
| 98 | break;
|
---|
[108] | 99 | }
|
---|
[517] | 100 | }
|
---|
| 101 | for (uInt j=m_.nelements()-1; j>=0;--j) {
|
---|
| 102 | if (m_[j]) {
|
---|
| 103 | mx = j;
|
---|
| 104 | break;
|
---|
[108] | 105 | }
|
---|
[517] | 106 | }
|
---|
[1067] | 107 | //mn = 0+x_.nelements()/10;
|
---|
| 108 | //mx = x_.nelements()-x_.nelements()/10;
|
---|
[517] | 109 | estimator.setRegion(mn,mx);
|
---|
| 110 | //estimator.setWindowing(True);
|
---|
| 111 | SpectralList listGauss = estimator.estimate(x_, y_);
|
---|
| 112 | parameters_.resize(n*3);
|
---|
| 113 | Gaussian1D<Float>* g = 0;
|
---|
| 114 | for (uInt i=0; i<n;i++) {
|
---|
| 115 | g = dynamic_cast<Gaussian1D<Float>* >(funcs_[i]);
|
---|
| 116 | if (g) {
|
---|
| 117 | (*g)[0] = listGauss[i].getAmpl();
|
---|
| 118 | (*g)[1] = listGauss[i].getCenter();
|
---|
| 119 | (*g)[2] = listGauss[i].getFWHM();
|
---|
[91] | 120 | }
|
---|
[517] | 121 | }
|
---|
| 122 | estimate_.resize();
|
---|
| 123 | listGauss.evaluate(estimate_,x_);
|
---|
| 124 | return true;
|
---|
[91] | 125 | }
|
---|
| 126 |
|
---|
[890] | 127 | std::vector<float> Fitter::getEstimate() const
|
---|
[91] | 128 | {
|
---|
[517] | 129 | if (estimate_.nelements() == 0)
|
---|
| 130 | throw (AipsError("No estimate set."));
|
---|
| 131 | std::vector<float> stlout;
|
---|
| 132 | estimate_.tovector(stlout);
|
---|
| 133 | return stlout;
|
---|
[91] | 134 | }
|
---|
| 135 |
|
---|
| 136 |
|
---|
[890] | 137 | bool Fitter::setExpression(const std::string& expr, int ncomp)
|
---|
[91] | 138 | {
|
---|
[517] | 139 | clear();
|
---|
| 140 | if (expr == "gauss") {
|
---|
| 141 | if (ncomp < 1) throw (AipsError("Need at least one gaussian to fit."));
|
---|
| 142 | funcs_.resize(ncomp);
|
---|
| 143 | for (Int k=0; k<ncomp; ++k) {
|
---|
| 144 | funcs_[k] = new Gaussian1D<Float>();
|
---|
| 145 | }
|
---|
| 146 | } else if (expr == "poly") {
|
---|
| 147 | funcs_.resize(1);
|
---|
| 148 | funcs_[0] = new Polynomial<Float>(ncomp);
|
---|
| 149 | } else {
|
---|
[1616] | 150 | //cerr << " compiled functions not yet implemented" << endl;
|
---|
| 151 | LogIO os( LogOrigin( "Fitter", "setExpression()", WHERE ) ) ;
|
---|
| 152 | os << LogIO::WARN << " compiled functions not yet implemented" << LogIO::POST;
|
---|
[517] | 153 | //funcs_.resize(1);
|
---|
| 154 | //funcs_[0] = new CompiledFunction<Float>();
|
---|
| 155 | //funcs_[0]->setFunction(String(expr));
|
---|
| 156 | return false;
|
---|
| 157 | }
|
---|
| 158 | return true;
|
---|
[91] | 159 | }
|
---|
| 160 |
|
---|
[890] | 161 | bool Fitter::setData(std::vector<float> absc, std::vector<float> spec,
|
---|
[91] | 162 | std::vector<bool> mask)
|
---|
| 163 | {
|
---|
| 164 | x_.resize();
|
---|
| 165 | y_.resize();
|
---|
| 166 | m_.resize();
|
---|
| 167 | // convert std::vector to casa Vector
|
---|
| 168 | Vector<Float> tmpx(absc);
|
---|
| 169 | Vector<Float> tmpy(spec);
|
---|
| 170 | Vector<Bool> tmpm(mask);
|
---|
| 171 | AlwaysAssert(tmpx.nelements() == tmpy.nelements(), AipsError);
|
---|
| 172 | x_ = tmpx;
|
---|
| 173 | y_ = tmpy;
|
---|
| 174 | m_ = tmpm;
|
---|
| 175 | return true;
|
---|
| 176 | }
|
---|
| 177 |
|
---|
[890] | 178 | std::vector<float> Fitter::getResidual() const
|
---|
[91] | 179 | {
|
---|
| 180 | if (residual_.nelements() == 0)
|
---|
| 181 | throw (AipsError("Function not yet fitted."));
|
---|
| 182 | std::vector<float> stlout;
|
---|
| 183 | residual_.tovector(stlout);
|
---|
| 184 | return stlout;
|
---|
| 185 | }
|
---|
| 186 |
|
---|
[890] | 187 | std::vector<float> Fitter::getFit() const
|
---|
[91] | 188 | {
|
---|
| 189 | Vector<Float> out = thefit_;
|
---|
| 190 | std::vector<float> stlout;
|
---|
| 191 | out.tovector(stlout);
|
---|
| 192 | return stlout;
|
---|
| 193 |
|
---|
| 194 | }
|
---|
| 195 |
|
---|
[890] | 196 | std::vector<float> Fitter::getErrors() const
|
---|
[91] | 197 | {
|
---|
| 198 | Vector<Float> out = error_;
|
---|
| 199 | std::vector<float> stlout;
|
---|
| 200 | out.tovector(stlout);
|
---|
| 201 | return stlout;
|
---|
| 202 | }
|
---|
| 203 |
|
---|
[890] | 204 | bool Fitter::setParameters(std::vector<float> params)
|
---|
[91] | 205 | {
|
---|
| 206 | Vector<Float> tmppar(params);
|
---|
| 207 | if (funcs_.nelements() == 0)
|
---|
| 208 | throw (AipsError("Function not yet set."));
|
---|
| 209 | if (parameters_.nelements() > 0 && tmppar.nelements() != parameters_.nelements())
|
---|
| 210 | throw (AipsError("Number of parameters inconsistent with function."));
|
---|
[1232] | 211 | if (parameters_.nelements() == 0) {
|
---|
[91] | 212 | parameters_.resize(tmppar.nelements());
|
---|
[1232] | 213 | if (tmppar.nelements() != fixedpar_.nelements()) {
|
---|
| 214 | fixedpar_.resize(tmppar.nelements());
|
---|
| 215 | fixedpar_ = False;
|
---|
| 216 | }
|
---|
| 217 | }
|
---|
[91] | 218 | if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) {
|
---|
| 219 | uInt count = 0;
|
---|
| 220 | for (uInt j=0; j < funcs_.nelements(); ++j) {
|
---|
| 221 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) {
|
---|
| 222 | (funcs_[j]->parameters())[i] = tmppar[count];
|
---|
| 223 | parameters_[count] = tmppar[count];
|
---|
| 224 | ++count;
|
---|
| 225 | }
|
---|
| 226 | }
|
---|
| 227 | } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) {
|
---|
| 228 | for (uInt i=0; i < funcs_[0]->nparameters(); ++i) {
|
---|
| 229 | parameters_[i] = tmppar[i];
|
---|
| 230 | (funcs_[0]->parameters())[i] = tmppar[i];
|
---|
| 231 | }
|
---|
| 232 | }
|
---|
[1232] | 233 | // reset
|
---|
| 234 | if (params.size() == 0) {
|
---|
| 235 | parameters_.resize();
|
---|
| 236 | fixedpar_.resize();
|
---|
| 237 | }
|
---|
[91] | 238 | return true;
|
---|
| 239 | }
|
---|
| 240 |
|
---|
[890] | 241 | bool Fitter::setFixedParameters(std::vector<bool> fixed)
|
---|
[91] | 242 | {
|
---|
| 243 | if (funcs_.nelements() == 0)
|
---|
| 244 | throw (AipsError("Function not yet set."));
|
---|
[1232] | 245 | if (fixedpar_.nelements() > 0 && fixed.size() != fixedpar_.nelements())
|
---|
[91] | 246 | throw (AipsError("Number of mask elements inconsistent with function."));
|
---|
[1232] | 247 | if (fixedpar_.nelements() == 0) {
|
---|
| 248 | fixedpar_.resize(parameters_.nelements());
|
---|
| 249 | fixedpar_ = False;
|
---|
| 250 | }
|
---|
[91] | 251 | if (dynamic_cast<Gaussian1D<Float>* >(funcs_[0]) != 0) {
|
---|
| 252 | uInt count = 0;
|
---|
| 253 | for (uInt j=0; j < funcs_.nelements(); ++j) {
|
---|
| 254 | for (uInt i=0; i < funcs_[j]->nparameters(); ++i) {
|
---|
[1232] | 255 | funcs_[j]->mask(i) = !fixed[count];
|
---|
| 256 | fixedpar_[count] = fixed[count];
|
---|
[91] | 257 | ++count;
|
---|
| 258 | }
|
---|
| 259 | }
|
---|
| 260 | } else if (dynamic_cast<Polynomial<Float>* >(funcs_[0]) != 0) {
|
---|
| 261 | for (uInt i=0; i < funcs_[0]->nparameters(); ++i) {
|
---|
[1232] | 262 | fixedpar_[i] = fixed[i];
|
---|
| 263 | funcs_[0]->mask(i) = !fixed[i];
|
---|
[91] | 264 | }
|
---|
| 265 | }
|
---|
| 266 | return true;
|
---|
| 267 | }
|
---|
| 268 |
|
---|
[890] | 269 | std::vector<float> Fitter::getParameters() const {
|
---|
[91] | 270 | Vector<Float> out = parameters_;
|
---|
| 271 | std::vector<float> stlout;
|
---|
| 272 | out.tovector(stlout);
|
---|
| 273 | return stlout;
|
---|
| 274 | }
|
---|
| 275 |
|
---|
[890] | 276 | std::vector<bool> Fitter::getFixedParameters() const {
|
---|
[108] | 277 | Vector<Bool> out(parameters_.nelements());
|
---|
| 278 | if (fixedpar_.nelements() == 0) {
|
---|
[1232] | 279 | return std::vector<bool>();
|
---|
[108] | 280 | //throw (AipsError("No parameter mask set."));
|
---|
| 281 | } else {
|
---|
| 282 | out = fixedpar_;
|
---|
| 283 | }
|
---|
| 284 | std::vector<bool> stlout;
|
---|
| 285 | out.tovector(stlout);
|
---|
| 286 | return stlout;
|
---|
[91] | 287 | }
|
---|
| 288 |
|
---|
[890] | 289 | float Fitter::getChisquared() const {
|
---|
[91] | 290 | return chisquared_;
|
---|
| 291 | }
|
---|
| 292 |
|
---|
[890] | 293 | bool Fitter::fit() {
|
---|
[517] | 294 | NonLinearFitLM<Float> fitter;
|
---|
| 295 | CompoundFunction<Float> func;
|
---|
[612] | 296 |
|
---|
| 297 | uInt n = funcs_.nelements();
|
---|
[517] | 298 | for (uInt i=0; i<n; ++i) {
|
---|
| 299 | func.addFunction(*funcs_[i]);
|
---|
| 300 | }
|
---|
[612] | 301 |
|
---|
[517] | 302 | fitter.setFunction(func);
|
---|
| 303 | fitter.setMaxIter(50+n*10);
|
---|
| 304 | // Convergence criterium
|
---|
| 305 | fitter.setCriteria(0.001);
|
---|
[612] | 306 |
|
---|
[517] | 307 | // Fit
|
---|
| 308 | Vector<Float> sigma(x_.nelements());
|
---|
| 309 | sigma = 1.0;
|
---|
[890] | 310 |
|
---|
[517] | 311 | parameters_.resize();
|
---|
| 312 | parameters_ = fitter.fit(x_, y_, sigma, &m_);
|
---|
[1067] | 313 | if ( !fitter.converged() ) {
|
---|
| 314 | return false;
|
---|
| 315 | }
|
---|
[517] | 316 | std::vector<float> ps;
|
---|
| 317 | parameters_.tovector(ps);
|
---|
| 318 | setParameters(ps);
|
---|
[612] | 319 |
|
---|
[517] | 320 | error_.resize();
|
---|
| 321 | error_ = fitter.errors();
|
---|
[612] | 322 |
|
---|
[517] | 323 | chisquared_ = fitter.getChi2();
|
---|
[890] | 324 |
|
---|
[517] | 325 | residual_.resize();
|
---|
| 326 | residual_ = y_;
|
---|
| 327 | fitter.residual(residual_,x_);
|
---|
| 328 | // use fitter.residual(model=True) to get the model
|
---|
| 329 | thefit_.resize(x_.nelements());
|
---|
| 330 | fitter.residual(thefit_,x_,True);
|
---|
| 331 | return true;
|
---|
| 332 | }
|
---|
[483] | 333 |
|
---|
[1387] | 334 | bool Fitter::lfit() {
|
---|
| 335 | LinearFit<Float> fitter;
|
---|
| 336 | CompoundFunction<Float> func;
|
---|
[483] | 337 |
|
---|
[1387] | 338 | uInt n = funcs_.nelements();
|
---|
| 339 | for (uInt i=0; i<n; ++i) {
|
---|
| 340 | func.addFunction(*funcs_[i]);
|
---|
| 341 | }
|
---|
| 342 |
|
---|
| 343 | fitter.setFunction(func);
|
---|
| 344 | //fitter.setMaxIter(50+n*10);
|
---|
| 345 | // Convergence criterium
|
---|
| 346 | //fitter.setCriteria(0.001);
|
---|
| 347 |
|
---|
| 348 | // Fit
|
---|
| 349 | Vector<Float> sigma(x_.nelements());
|
---|
| 350 | sigma = 1.0;
|
---|
| 351 |
|
---|
| 352 | parameters_.resize();
|
---|
| 353 | parameters_ = fitter.fit(x_, y_, sigma, &m_);
|
---|
| 354 | std::vector<float> ps;
|
---|
| 355 | parameters_.tovector(ps);
|
---|
| 356 | setParameters(ps);
|
---|
| 357 |
|
---|
| 358 | error_.resize();
|
---|
| 359 | error_ = fitter.errors();
|
---|
| 360 |
|
---|
| 361 | chisquared_ = fitter.getChi2();
|
---|
| 362 |
|
---|
| 363 | residual_.resize();
|
---|
| 364 | residual_ = y_;
|
---|
| 365 | fitter.residual(residual_,x_);
|
---|
| 366 | // use fitter.residual(model=True) to get the model
|
---|
| 367 | thefit_.resize(x_.nelements());
|
---|
| 368 | fitter.residual(thefit_,x_,True);
|
---|
| 369 | return true;
|
---|
| 370 | }
|
---|
| 371 |
|
---|
[890] | 372 | std::vector<float> Fitter::evaluate(int whichComp) const
|
---|
| 373 | {
|
---|
[517] | 374 | std::vector<float> stlout;
|
---|
[890] | 375 | uInt idx = uInt(whichComp);
|
---|
[517] | 376 | Float y;
|
---|
| 377 | if ( idx < funcs_.nelements() ) {
|
---|
| 378 | for (uInt i=0; i<x_.nelements(); ++i) {
|
---|
| 379 | y = (*funcs_[idx])(x_[i]);
|
---|
| 380 | stlout.push_back(float(y));
|
---|
| 381 | }
|
---|
| 382 | }
|
---|
| 383 | return stlout;
|
---|
| 384 | }
|
---|
[483] | 385 |
|
---|