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Reference Guide
TMinuitMinimizer.cxx
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1 // @(#)root/minuit:$Id$
2 // Author: L. Moneta Wed Oct 25 16:28:55 2006
3 
4 /**********************************************************************
5  * *
6  * Copyright (c) 2006 LCG ROOT Math Team, CERN/PH-SFT *
7  * *
8  * *
9  **********************************************************************/
10 
11 // Implementation file for class TMinuitMinimizer
12 
13 #include "TMinuitMinimizer.h"
14 #include "Math/IFunction.h"
15 #include "Fit/ParameterSettings.h"
16 
17 #include "TMinuit.h"
18 #include "TROOT.h"
19 
20 #include "TGraph.h" // needed for scan
21 #include "TError.h"
22 
23 #include "TMatrixDSym.h" // needed for inverting the matrix
24 
25 #include "ThreadLocalStorage.h"
26 
27 #include <iostream>
28 #include <cassert>
29 #include <algorithm>
30 #include <functional>
31 #include <cmath>
32 
33 //______________________________________________________________________________
34 //
35 // TMinuitMinimizer class implementing the ROOT::Math::Minimizer interface using
36 // TMinuit.
37 // This class is normally instantiates using the plug-in manager
38 // (plug-in with name Minuit or TMinuit)
39 // In addition the user can choose the minimizer algorithm: Migrad (the default one), Simplex, or Minimize (combined Migrad + Simplex)
40 //
41 //__________________________________________________________________________________________
42 
43 // initialize the static instances
44 
45 // Implement a thread local static member
47  TTHREAD_TLS(ROOT::Math::IMultiGenFunction *) fgFunc = nullptr;
48  return fgFunc;
49 }
51 bool TMinuitMinimizer::fgUsed = false;
52 bool TMinuitMinimizer::fgUseStaticMinuit = true; // default case use static Minuit instance
53 
55 
56 
57 TMinuitMinimizer::TMinuitMinimizer(ROOT::Minuit::EMinimizerType type, unsigned int ndim ) :
58  fUsed(false),
59  fMinosRun(false),
60  fDim(ndim),
61  fType(type),
62  fMinuit(0)
63 {
64  // Constructor for TMinuitMinimier class via an enumeration specifying the minimization
65  // algorithm type. Supported types are : kMigrad, kSimplex, kCombined (a combined
66  // Migrad + Simplex minimization) and kMigradImproved (a Migrad mininimization folloed by an
67  // improved search for global minima). The default type is Migrad (kMigrad).
68 
69  // initialize if npar is given
70  if (fDim > 0) InitTMinuit(fDim);
71 }
72 
73 TMinuitMinimizer::TMinuitMinimizer(const char * type, unsigned int ndim ) :
74  fUsed(false),
75  fMinosRun(false),
76  fDim(ndim),
77  fMinuit(0)
78 {
79  // constructor from a char * for the algorithm type, used by the plug-in manager
80  // The names supported (case unsensitive) are:
81  // Migrad (default), Simplex, Minimize (for the combined Migrad+ Simplex) and Migrad_imp
82 
83  // select type from the string
84  std::string algoname(type);
85  std::transform(algoname.begin(), algoname.end(), algoname.begin(), (int(*)(int)) tolower );
86 
88  if (algoname == "simplex") algoType = ROOT::Minuit::kSimplex;
89  if (algoname == "minimize" ) algoType = ROOT::Minuit::kCombined;
90  if (algoname == "migradimproved" ) algoType = ROOT::Minuit::kMigradImproved;
91  if (algoname == "scan" ) algoType = ROOT::Minuit::kScan;
92  if (algoname == "seek" ) algoType = ROOT::Minuit::kSeek;
93 
94  fType = algoType;
95 
96  // initialize if npar is given
97  if (fDim > 0) InitTMinuit(fDim);
98 
99 }
100 
102 {
103  // Destructor implementation.
104  if (fMinuit && !fgUseStaticMinuit) {
105  delete fMinuit;
106  fgMinuit = 0;
107  }
108 }
109 
111  Minimizer()
112 {
113  // Implementation of copy constructor (it is private).
114 }
115 
117 {
118  // Implementation of assignment operator (private)
119  if (this == &rhs) return *this; // time saving self-test
120  return *this;
121 }
122 
124  // static method to control usage of global TMinuit instance
125  bool prev = fgUseStaticMinuit;
126  fgUseStaticMinuit = on;
127  return prev;
128 }
129 
131 
132  // when called a second time check dimension - create only if needed
133  // initialize the minuit instance - recreating a new one if needed
134  if (fMinuit ==0 || dim > fMinuit->fMaxpar) {
135 
136  // case not using the global instance - recreate it all the time
137  if (fgUseStaticMinuit) {
138 
139  // re-use gMinuit as static instance of TMinuit
140  // which can be accessed by the user after minimization
141  // check if fgMinuit is different than gMinuit
142  // case 1: fgMinuit not zero but fgMinuit has been deleted (not in gROOT): set to zero
143  // case 2: fgMinuit not zero and exists in global list : set fgMinuit to gMinuit
144  // case 3: fgMinuit zero - and gMinuit not zero: create a new instance locally to avoid conflict
145  if (fgMinuit != gMinuit) {
146  // if object exists in gROOT remove it to avoid a memory leak
147  if (fgMinuit ) {
148  if (gROOT->GetListOfSpecials()->FindObject(fgMinuit) == 0) {
149  // case 1: object does not exists in gROOT - means it has been deleted
150  fgMinuit = 0;
151  }
152  else {
153  // case 2: object exists - but gMinuit points to something else
154  // restore gMinuit to the one used before by TMinuitMinimizer
155  gMinuit = fgMinuit;
156  }
157  }
158  else {
159  // case 3: avoid reusing existing one - mantain fgMinuit to zero
160  // otherwise we will get a double delete if user deletes externally gMinuit
161  // in this case we will loose gMinuit instance
162 // fgMinuit = gMinuit;
163 // fgUsed = true; // need to reset in case other gMinuit instance is later used
164  }
165  }
166 
167  // check if need to create a new TMinuit instance
168  if (fgMinuit == 0) {
169  fgUsed = false;
170  fgMinuit = new TMinuit(dim);
171  }
172  else if (fgMinuit->GetNumPars() != int(dim) ) {
173  delete fgMinuit;
174  fgUsed = false;
175  fgMinuit = new TMinuit(dim);
176  }
177 
178  fMinuit = fgMinuit;
179  }
180 
181  else {
182  // re- create all the time a new instance of TMinuit (fgUseStaticMinuit is false)
183  if (fMinuit) delete fMinuit;
184  fMinuit = new TMinuit(dim);
185  fgMinuit = fMinuit;
186  fgUsed = false;
187  }
188 
189  } // endif fMinuit ==0 || dim > fMaxpar
190 
191  fDim = dim;
192 
194 
195  // set print level in TMinuit
196  double arglist[1];
197  int ierr= 0;
198  // TMinuit level is shift by 1 -1 means 0;
199  arglist[0] = PrintLevel() - 1;
200  fMinuit->mnexcm("SET PRINT",arglist,1,ierr);
201  if (PrintLevel() <= 0) SuppressMinuitWarnings();
202 }
203 
204 
206  // Set the objective function to be minimized, by passing a function object implement the
207  // basic multi-dim Function interface. In this case the derivatives will be
208  // calculated by Minuit
209  // Here a TMinuit instance is created since only at this point we know the number of parameters
210 
211 
212  fDim = func.NDim();
213 
214  // create TMinuit if needed
215  InitTMinuit(fDim);
216 
217  // assign to the static pointer (NO Thread safety here)
220 
221  // switch off gradient calculations
222  double arglist[1];
223  int ierr = 0;
224  fMinuit->mnexcm("SET NOGrad",arglist,0,ierr);
225 }
226 
228  // Set the objective function to be minimized, by passing a function object implement the
229  // multi-dim gradient Function interface. In this case the function derivatives are provided
230  // by the user via this interface and there not calculated by Minuit.
231 
232  fDim = func.NDim();
233 
234  // create TMinuit if needed
235  InitTMinuit(fDim);
236 
237  // assign to the static pointer (NO Thread safety here)
240 
241  // set gradient
242  // by default do not check gradient calculation
243  // it cannot be done here, check can be done only after having defined the parameters
244  double arglist[1];
245  int ierr = 0;
246  arglist[0] = 1;
247  fMinuit->mnexcm("SET GRAD",arglist,1,ierr);
248 }
249 
250 void TMinuitMinimizer::Fcn( int &, double * , double & f, double * x , int /* iflag */) {
251  // implementation of FCN static function used internally by TMinuit.
252  // Adapt IMultiGenFunction interface to TMinuit FCN static function
253  f = GetGlobalFuncPtr()->operator()(x);
254 }
255 
256 void TMinuitMinimizer::FcnGrad( int &, double * g, double & f, double * x , int iflag ) {
257  // implementation of FCN static function used internally by TMinuit.
258  // Adapt IMultiGradFunction interface to TMinuit FCN static function in the case of user
259  // provided gradient.
261 
262  assert(gFunc != 0);
263  f = gFunc->operator()(x);
264 
265  // calculates also derivatives
266  if (iflag == 2) gFunc->Gradient(x,g);
267 }
268 
269 bool TMinuitMinimizer::SetVariable(unsigned int ivar, const std::string & name, double val, double step) {
270  // set a free variable.
271  if (!CheckMinuitInstance()) return false;
272 
273  fUsed = fgUsed;
274 
275  // clear after minimization when setting params
276  if (fUsed) DoClear();
277 
278  // check if parameter was defined and in case it was fixed, release it
279  DoReleaseFixParameter(ivar);
280 
281  int iret = fMinuit->DefineParameter(ivar , name.c_str(), val, step, 0., 0. );
282  return (iret == 0);
283 }
284 
285 bool TMinuitMinimizer::SetLimitedVariable(unsigned int ivar, const std::string & name, double val, double step, double lower, double upper) {
286  // set a limited variable.
287  if (!CheckMinuitInstance()) return false;
288 
289  fUsed = fgUsed;
290 
291  // clear after minimization when setting params
292  if (fUsed) DoClear();
293 
294  // check if parameter was defined and in case it was fixed, release it
295  DoReleaseFixParameter(ivar);
296 
297  int iret = fMinuit->DefineParameter(ivar, name.c_str(), val, step, lower, upper );
298  return (iret == 0);
299 }
300 
301 bool TMinuitMinimizer::SetLowerLimitedVariable(unsigned int ivar , const std::string & name , double val , double step , double lower ) {
302  // set a lower limited variable
303  // since is not supported in TMinuit , just use a artificial large value
304  Warning("TMinuitMinimizer::SetLowerLimitedVariable","not implemented - use as upper limit 1.E7 instead of +inf");
305  return SetLimitedVariable(ivar, name, val , step, lower, lower+ 1.E7); // use 1.E7 which will make TMinuit happy
306 }
307 
308 bool TMinuitMinimizer::SetUpperLimitedVariable(unsigned int ivar , const std::string & name , double val , double step , double upper ) {
309  // set a upper limited variable
310  // since is not supported in TMinuit , just use a artificial large negative value
311  Warning("TMinuitMinimizer::SetUpperLimitedVariable","not implemented - use as lower limit -1.E7 instead of -inf");
312  return SetLimitedVariable(ivar, name, val , step, upper -1.E7, upper);
313 }
314 
315 
317  // check instance of fMinuit
318  if (fMinuit == 0) {
319  Error("TMinuitMinimizer::CheckMinuitInstance","Invalid TMinuit pointer. Need to call first SetFunction");
320  return false;
321  }
322  return true;
323 }
324 
325 bool TMinuitMinimizer::CheckVarIndex(unsigned int ivar) const {
326  // check index of Variable (assume fMinuit exists)
327  if ((int) ivar >= fMinuit->fNu ) {
328  Error("TMinuitMinimizer::CheckVarIndex","Invalid parameter index");
329  return false;
330  }
331  return true;
332 }
333 
334 
335 bool TMinuitMinimizer::SetFixedVariable(unsigned int ivar, const std::string & name, double val) {
336  // set a fixed variable.
337  if (!CheckMinuitInstance()) return false;
338 
339  // clear after minimization when setting params
340  fUsed = fgUsed;
341 
342  // clear after minimization when setting params
343  if (fUsed) DoClear();
344 
345  // put an arbitrary step (0.1*abs(value) otherwise TMinuit consider the parameter as constant
346  // constant parameters are treated differently (they are ignored inside TMinuit and not considered in the
347  // total list of parameters)
348  double step = ( val != 0) ? 0.1 * std::abs(val) : 0.1;
349  int iret = fMinuit->DefineParameter(ivar, name.c_str(), val, step, 0., 0. );
350  if (iret == 0) iret = fMinuit->FixParameter(ivar);
351  return (iret == 0);
352 }
353 
354 bool TMinuitMinimizer::SetVariableValue(unsigned int ivar, double val) {
355  // set the value of an existing variable
356  // parameter must exist or return false
357  if (!CheckMinuitInstance()) return false;
358 
359  double arglist[2];
360  int ierr = 0;
361 
362  arglist[0] = ivar+1; // TMinuit starts from 1
363  arglist[1] = val;
364  fMinuit->mnexcm("SET PAR",arglist,2,ierr);
365  return (ierr==0);
366 }
367 
368 bool TMinuitMinimizer::SetVariableStepSize(unsigned int ivar, double step) {
369  // set the step-size of an existing variable
370  // parameter must exist or return false
371  if (!CheckMinuitInstance()) return false;
372  // need to re-implement re-calling mnparm
373  // get first current parameter values and limits
374  double curval,err, lowlim, uplim;
375  int iuint; // internal index
376  TString name;
377  fMinuit->mnpout(ivar, name, curval, err, lowlim, uplim,iuint);
378  if (iuint == -1) return false;
379  int iret = fMinuit->DefineParameter(ivar, name, curval, step, lowlim, uplim );
380  return (iret == 0);
381 
382 }
383 
384 bool TMinuitMinimizer::SetVariableLowerLimit(unsigned int ivar, double lower ) {
385  // set the limits of an existing variable
386  // parameter must exist or return false
387  Warning("TMinuitMinimizer::SetVariableLowerLimit","not implemented - use as upper limit 1.E30 instead of +inf");
388  return SetVariableLimits(ivar, lower, 1.E30);
389 }
390 bool TMinuitMinimizer::SetVariableUpperLimit(unsigned int ivar, double upper ) {
391  // set the limits of an existing variable
392  // parameter must exist or return false
393  Warning("TMinuitMinimizer::SetVariableUpperLimit","not implemented - - use as lower limit -1.E30 instead of +inf");
394  return SetVariableLimits(ivar, -1.E30, upper);
395 }
396 
397 bool TMinuitMinimizer::SetVariableLimits(unsigned int ivar, double lower, double upper) {
398  // set the limits of an existing variable
399  // parameter must exist or return false
400 
401  if (!CheckMinuitInstance()) return false;
402  // need to re-implement re-calling mnparm
403  // get first current parameter values and limits
404  double curval,err, lowlim, uplim;
405  int iuint; // internal index
406  TString name;
407  fMinuit->mnpout(ivar, name, curval, err, lowlim, uplim,iuint);
408  if (iuint == -1) return false;
409  int iret = fMinuit->DefineParameter(ivar, name, curval, err, lower, upper );
410  return (iret == 0);
411 
412 }
413 
414 bool TMinuitMinimizer::FixVariable(unsigned int ivar) {
415  // Fix an existing variable
416  if (!CheckMinuitInstance()) return false;
417  if (!CheckVarIndex(ivar)) return false;
418  int iret = fMinuit->FixParameter(ivar);
419  return (iret == 0);
420 }
421 
422 bool TMinuitMinimizer::ReleaseVariable(unsigned int ivar) {
423  // Fix an existing variable
424  if (!CheckMinuitInstance()) return false;
425  if (!CheckVarIndex(ivar)) return false;
426  int iret = fMinuit->Release(ivar);
427  return (iret == 0);
428 }
429 
430 bool TMinuitMinimizer::IsFixedVariable(unsigned int ivar) const {
431  // query if variable is fixed
432  if (!CheckMinuitInstance()) return false;
433  if (!CheckVarIndex(ivar)) return false;
434  return (fMinuit->fNiofex[ivar] == 0 );
435 }
436 
438  // retrieve variable settings (all set info on the variable)
439  if (!CheckMinuitInstance()) return false;
440  if (!CheckVarIndex(ivar)) return false;
441  double curval,err, lowlim, uplim;
442  int iuint; // internal index
443  TString name;
444  fMinuit->mnpout(ivar, name, curval, err, lowlim, uplim,iuint);
445  if (iuint == -1) return false;
446  var.Set(name.Data(), curval, err, lowlim, uplim);
447  if (IsFixedVariable(ivar)) var.Fix();
448  return true;
449 }
450 
451 
452 
453 std::string TMinuitMinimizer::VariableName(unsigned int ivar) const {
454  // return the variable name
455  if (!CheckMinuitInstance()) return std::string();
456  if (!CheckVarIndex(ivar)) return std::string();
457  return std::string(fMinuit->fCpnam[ivar]);
458 }
459 
460 int TMinuitMinimizer::VariableIndex(const std::string & ) const {
461  // return variable index
462  Error("TMinuitMinimizer::VariableIndex"," find index of a variable from its name is not implemented in TMinuit");
463  return -1;
464 }
465 
467  // perform the minimization using the algorithm chosen previously by the user
468  // By default Migrad is used.
469  // Return true if the found minimum is valid and update internal chached values of
470  // minimum values, errors and covariance matrix.
471  // Status of minimizer is set to:
472  // migradResult + 10*minosResult + 100*hesseResult + 1000*improveResult
473 
474 
475  if (fMinuit == 0) {
476  Error("TMinuitMinimizer::Minimize","invalid TMinuit pointer. Need to call first SetFunction and SetVariable");
477  return false;
478  }
479 
480 
481  // total number of parameter defined in Minuit is fNu
482  if (fMinuit->fNu < static_cast<int>(fDim) ) {
483  Error("TMinuitMinimizer::Minimize","The total number of defined parameters is different than the function dimension, npar = %d, dim = %d",fMinuit->fNu, fDim);
484  return false;
485  }
486 
487  int printlevel = PrintLevel();
488 
489  // total number of free parameter is 0
490  if (fMinuit->fNpar <= 0) {
491  // retrieve parameters values from TMinuit
492  RetrieveParams();
493  fMinuit->fAmin = (*GetGlobalFuncPtr())(&fParams.front());
494  if (printlevel > 0) Info("TMinuitMinimizer::Minimize","There are no free parameter - just compute the function value");
495  return true;
496  }
497 
498 
499  double arglist[10];
500  int ierr = 0;
501 
502 
503  // set error and print level
504  arglist[0] = ErrorDef();
505  fMinuit->mnexcm("SET Err",arglist,1,ierr);
506 
507  arglist[0] = printlevel - 1;
508  fMinuit->mnexcm("SET PRINT",arglist,1,ierr);
509 
510  // suppress warning in case Printlevel() == 0
511  if (printlevel == 0) fMinuit->mnexcm("SET NOW",arglist,0,ierr);
512 
513  // set precision if needed
514  if (Precision() > 0) {
515  arglist[0] = Precision();
516  fMinuit->mnexcm("SET EPS",arglist,1,ierr);
517  }
518 
519  // set strategy
520  int strategy = Strategy();
521  if (strategy >=0 && strategy <=2 ) {
522  arglist[0] = strategy;
523  fMinuit->mnexcm("SET STR",arglist,1,ierr);
524  }
525 
526  arglist[0] = MaxFunctionCalls();
527  arglist[1] = Tolerance();
528 
529  int nargs = 2;
530 
531  switch (fType){
533  // case of Migrad
534  fMinuit->mnexcm("MIGRAD",arglist,nargs,ierr);
535  break;
537  // case of combined (Migrad+ simplex)
538  fMinuit->mnexcm("MINIMIZE",arglist,nargs,ierr);
539  break;
541  // case of Simlex
542  fMinuit->mnexcm("SIMPLEX",arglist,nargs,ierr);
543  break;
544  case ROOT::Minuit::kScan:
545  // case of Scan (scan all parameters with default values)
546  nargs = 0;
547  fMinuit->mnexcm("SCAN",arglist,nargs,ierr);
548  break;
549  case ROOT::Minuit::kSeek:
550  // case of Seek (random find minimum in a hypercube around current parameter values
551  // use Tolerance as measures for standard deviation (if < 1) used default value in Minuit ( supposed to be 3)
552  nargs = 1;
553  if (arglist[1] >= 1.) nargs = 2;
554  fMinuit->mnexcm("SEEK",arglist,nargs,ierr);
555  break;
556  default:
557  // default: use Migrad
558  fMinuit->mnexcm("MIGRAD",arglist,nargs,ierr);
559 
560  }
561 
562  fgUsed = true;
563  fUsed = true;
564 
565  fStatus = ierr;
566  int minErrStatus = ierr;
567 
568  if (printlevel>2) Info("TMinuitMinimizer::Minimize","Finished to run MIGRAD - status %d",ierr);
569 
570  // run improved if needed
571  if (ierr == 0 && fType == ROOT::Minuit::kMigradImproved) {
572  fMinuit->mnexcm("IMPROVE",arglist,1,ierr);
573  fStatus += 1000*ierr;
574  if (printlevel>2) Info("TMinuitMinimizer::Minimize","Finished to run IMPROVE - status %d",ierr);
575  }
576 
577 
578  // check if Hesse needs to be run
579  // Migrad runs inside it automatically for strategy >=1. Do also
580  // in case improve or other minimizers are used
581  if (minErrStatus == 0 && (IsValidError() || ( strategy >=1 && CovMatrixStatus() < 3) ) ) {
582  fMinuit->mnexcm("HESSE",arglist,1,ierr);
583  fStatus += 100*ierr;
584  if (printlevel>2) Info("TMinuitMinimizer::Minimize","Finished to run HESSE - status %d",ierr);
585  }
586 
587  // retrieve parameters and errors from TMinuit
588  RetrieveParams();
589 
590  if (minErrStatus == 0) {
591 
592  // store global min results (only if minimization is OK)
593  // ignore cases when Hesse or IMprove return error different than zero
595 
596  // need to re-run Minos again if requested
597  fMinosRun = false;
598 
599  return true;
600 
601  }
602  return false;
603 
604 }
605 
607  // retrieve from TMinuit minimum parameter values
608  // and errors
609 
610  assert(fMinuit != 0);
611 
612  // get parameter values
613  if (fParams.size() != fDim) fParams.resize( fDim);
614  if (fErrors.size() != fDim) fErrors.resize( fDim);
615  for (unsigned int i = 0; i < fDim; ++i) {
616  fMinuit->GetParameter( i, fParams[i], fErrors[i]);
617  }
618 }
619 
621  // get covariance error matrix from TMinuit
622  // when some parameters are fixed filled the corresponding rows and column with zero's
623 
624  assert(fMinuit != 0);
625 
626  unsigned int nfree = NFree();
627 
628  unsigned int ndim2 = fDim*fDim;
629  if (fCovar.size() != ndim2 ) fCovar.resize(fDim*fDim);
630  if (nfree >= fDim) { // no fixed parameters
631  fMinuit->mnemat(&fCovar.front(), fDim);
632  }
633  else {
634  // case of fixed params need to take care
635  std::vector<double> tmpMat(nfree*nfree);
636  fMinuit->mnemat(&tmpMat.front(), nfree);
637 
638  unsigned int l = 0;
639  for (unsigned int i = 0; i < fDim; ++i) {
640 
641  if ( fMinuit->fNiofex[i] > 0 ) { // not fixed ?
642  unsigned int m = 0;
643  for (unsigned int j = 0; j <= i; ++j) {
644  if ( fMinuit->fNiofex[j] > 0 ) { //not fixed
645  fCovar[i*fDim + j] = tmpMat[l*nfree + m];
646  fCovar[j*fDim + i] = fCovar[i*fDim + j];
647  m++;
648  }
649  }
650  l++;
651  }
652  }
653 
654  }
655 }
656 
657 unsigned int TMinuitMinimizer::NCalls() const {
658  // return total number of function calls
659  if (fMinuit == 0) return 0;
660  return fMinuit->fNfcn;
661 }
662 
664  // return minimum function value
665 
666  // use part of code from mnstat
667  if (!fMinuit) return 0;
668  double minval = fMinuit->fAmin;
669  if (minval == fMinuit->fUndefi) return 0;
670  return minval;
671 }
672 
673 double TMinuitMinimizer::Edm() const {
674  // return expected distance from the minimum
675 
676  // use part of code from mnstat
677  if (!fMinuit) return -1;
678  if (fMinuit->fAmin == fMinuit->fUndefi || fMinuit->fEDM == fMinuit->fBigedm) return fMinuit->fUp;
679  return fMinuit->fEDM;
680 }
681 
682 unsigned int TMinuitMinimizer::NFree() const {
683  // return number of free parameters
684  if (!fMinuit) return 0;
685  if (fMinuit->fNpar < 0) return 0;
686  return fMinuit->fNpar;
687 }
688 
689 bool TMinuitMinimizer::GetCovMatrix(double * cov) const {
690  // get covariance matrix
691  int covStatus = CovMatrixStatus();
692  if ( fCovar.size() != fDim*fDim || covStatus < 2) {
693  Error("TMinuitMinimizer::GetHessianMatrix","Hessian matrix has not been computed - status %d",covStatus);
694  return false;
695  }
696  std::copy(fCovar.begin(), fCovar.end(), cov);
697  TMatrixDSym cmat(fDim,cov);
698  return true;
699 }
700 
701 bool TMinuitMinimizer::GetHessianMatrix(double * hes) const {
702  // get Hessian - inverse of covariance matrix
703  // just invert it
704  // but need to get the compact form to avoid the zero for the fixed parameters
705  int covStatus = CovMatrixStatus();
706  if ( fCovar.size() != fDim*fDim || covStatus < 2) {
707  Error("TMinuitMinimizer::GetHessianMatrix","Hessian matrix has not been computed - status %d",covStatus);
708  return false;
709  }
710  // case of fixed params need to take care
711  unsigned int nfree = NFree();
712  TMatrixDSym mat(nfree);
713  fMinuit->mnemat(mat.GetMatrixArray(), nfree);
714  // invert the matrix
715  // probably need to check if failed. In that case inverse is equal to original
716  mat.Invert();
717 
718  unsigned int l = 0;
719  for (unsigned int i = 0; i < fDim; ++i) {
720  if ( fMinuit->fNiofex[i] > 0 ) { // not fixed ?
721  unsigned int m = 0;
722  for (unsigned int j = 0; j <= i; ++j) {
723  if ( fMinuit->fNiofex[j] > 0 ) { //not fixed
724  hes[i*fDim + j] = mat(l,m);
725  hes[j*fDim + i] = hes[i*fDim + j];
726  m++;
727  }
728  }
729  l++;
730  }
731  }
732  return true;
733 }
734 // if ( fCovar.size() != fDim*fDim ) return false;
735 // TMatrixDSym mat(fDim, &fCovar.front() );
736 // std::copy(mat.GetMatrixArray(), mat.GetMatrixArray()+ mat.GetNoElements(), hes);
737 // return true;
738 // }
739 
741  // return status of covariance matrix
742  // status: 0= not calculated at all
743  // 1= approximation only, not accurate
744  // 2= full matrix, but forced positive-definite
745  // 3= full accurate covariance matrix
746 
747  // use part of code from mnstat
748  if (!fMinuit) return 0;
749  if (fMinuit->fAmin == fMinuit->fUndefi) return 0;
750  return fMinuit->fISW[1];
751 }
752 
753 double TMinuitMinimizer::GlobalCC(unsigned int i) const {
754  // global correlation coefficient for parameter i
755  if (!fMinuit) return 0;
756  if (!fMinuit->fGlobcc) return 0;
757  if (int(i) >= fMinuit->fNu) return 0;
758  // get internal number in Minuit
759  int iin = fMinuit->fNiofex[i];
760  // index in TMinuit starts from 1
761  if (iin < 1) return 0;
762  return fMinuit->fGlobcc[iin-1];
763 }
764 
765 bool TMinuitMinimizer::GetMinosError(unsigned int i, double & errLow, double & errUp, int ) {
766  // Perform Minos analysis for the given parameter i
767 
768  if (fMinuit == 0) {
769  Error("TMinuitMinimizer::GetMinosError","invalid TMinuit pointer. Need to call first SetFunction and SetVariable");
770  return false;
771  }
772 
773  // check if parameter is fixed
774  if (fMinuit->fNiofex[i] == 0 ) {
775  if (PrintLevel() > 0) Info("TMinuitMinimizer::GetMinosError","Parameter %s is fixed. There are no Minos error to calculate. Ignored.",VariableName(i).c_str());
776  errLow = 0; errUp = 0;
777  return true;
778  }
779 
780  double arglist[2];
781  int ierr = 0;
782 
783 
784  // set error, print level, precision and strategy if they have changed
785  if (fMinuit->fUp != ErrorDef() ) {
786  arglist[0] = ErrorDef();
787  fMinuit->mnexcm("SET Err",arglist,1,ierr);
788  }
789 
790  if (fMinuit->fISW[4] != (PrintLevel()-1) ) {
791  arglist[0] = PrintLevel()-1;
792  fMinuit->mnexcm("SET PRINT",arglist,1,ierr);
793  // suppress warning in case Printlevel() == 0
794  if (PrintLevel() == 0) fMinuit->mnexcm("SET NOW",arglist,0,ierr);
795  }
796  if (fMinuit->fIstrat != Strategy() ) {
797  arglist[0] = Strategy();
798  fMinuit->mnexcm("SET STR",arglist,1,ierr);
799  }
800 
801  if (Precision() > 0 && fMinuit->fEpsma2 != Precision() ) {
802  arglist[0] = Precision();
803  fMinuit->mnexcm("SET EPS",arglist,1,ierr);
804  }
805 
806 
807  // syntax of MINOS is MINOS [maxcalls] [parno]
808  // if parno = 0 all parameters are done
809  arglist[0] = MaxFunctionCalls();
810  arglist[1] = i+1; // par number starts from 1 in TMInuit
811 
812  int nargs = 2;
813  fMinuit->mnexcm("MINOS",arglist,nargs,ierr);
814  bool isValid = (ierr == 0);
815  // check also the status from fCstatu
816  if (isValid && fMinuit->fCstatu != "SUCCESSFUL") {
817  if (fMinuit->fCstatu == "FAILURE" ) {
818  // in this case MINOS failed on all prameter, so it is not valid !
819  ierr = 5;
820  isValid = false;
821  }
822  if (fMinuit->fCstatu == "PROBLEMS") ierr = 6;
823  ierr = 7; // this should be the case UNCHANGED
824  }
825 
826  fStatus += 10*ierr;
827 
828  fMinosRun = true;
829 
830  double errParab = 0;
831  double gcor = 0;
832  // what returns if parameter fixed or constant or at limit ?
833  fMinuit->mnerrs(i,errUp,errLow, errParab, gcor);
834 
835  // do not flag errors case of PROBLEMS or UNCHANGED (
836  return isValid;
837 
838 }
839 
841  // reset TMinuit
842 
843  fMinuit->mncler();
844 
845  //reset the internal Minuit random generator to its initial state
846  double val = 3;
847  int inseed = 12345;
848  fMinuit->mnrn15(val,inseed);
849 
850  fUsed = false;
851  fgUsed = false;
852 
853 }
854 
856  // check if a parameter is defined and in case it was fixed released
857  // TMinuit is not able to release free parameters by redefining them
858  // so we need to force the release
859  if (fMinuit == 0) return;
860  if (fMinuit->GetNumFixedPars() == 0) return;
861  // check if parameter has already been defined
862  if (int(ivar) >= fMinuit->GetNumPars() ) return;
863 
864  // check if parameter is fixed
865  for (int i = 0; i < fMinuit->fNpfix; ++i) {
866  if (fMinuit->fIpfix[i] == ivar+1 ) {
867  // parameter is fixed
868  fMinuit->Release(ivar);
869  return;
870  }
871  }
872 
873 }
874 
875 
877  // print-out results using classic Minuit format (mnprin)
878  if (fMinuit == 0) return;
879 
880  // print minimizer result
881  if (PrintLevel() > 2)
883  else
885 }
886 
888  // suppress Minuit2 warnings
889  double arglist = 0;
890  int ierr = 0;
891  if (nowarn)
892  fMinuit->mnexcm("SET NOW",&arglist,0,ierr);
893  else
894  fMinuit->mnexcm("SET WAR",&arglist,0,ierr);
895 }
896 
897 
898 bool TMinuitMinimizer::Contour(unsigned int ipar, unsigned int jpar, unsigned int &npoints, double * x, double * y) {
899  // contour plot for parameter i and j
900  // need a valid FunctionMinimum otherwise exits
901  if (fMinuit == 0) {
902  Error("TMinuitMinimizer::Contour"," invalid TMinuit instance");
903  return false;
904  }
905 
906  // set error and print level
907  double arglist[1];
908  int ierr = 0;
909  arglist[0] = ErrorDef();
910  fMinuit->mnexcm("SET Err",arglist,1,ierr);
911 
912  arglist[0] = PrintLevel()-1;
913  fMinuit->mnexcm("SET PRINT",arglist,1,ierr);
914 
915  // suppress warning in case Printlevel() == 0
916  if (PrintLevel() == 0) fMinuit->mnexcm("SET NOW",arglist,0,ierr);
917 
918  // set precision if needed
919  if (Precision() > 0) {
920  arglist[0] = Precision();
921  fMinuit->mnexcm("SET EPS",arglist,1,ierr);
922  }
923 
924 
925  if (npoints < 4) {
926  Error("TMinuitMinimizer::Contour","Cannot make contour with so few points");
927  return false;
928  }
929  int npfound = 0;
930  // parameter numbers in mncont start from zero
931  fMinuit->mncont( ipar,jpar,npoints, x, y,npfound);
932  if (npfound<4) {
933  // mncont did go wrong
934  Error("TMinuitMinimizer::Contour","Cannot find more than 4 points");
935  return false;
936  }
937  if (npfound!=(int)npoints) {
938  // mncont did go wrong
939  Warning("TMinuitMinimizer::Contour","Returning only %d points ",npfound);
940  npoints = npfound;
941  }
942  return true;
943 
944 }
945 
946 bool TMinuitMinimizer::Scan(unsigned int ipar, unsigned int & nstep, double * x, double * y, double xmin, double xmax) {
947  // scan a parameter (variable) around the minimum value
948  // the parameters must have been set before
949  // if xmin=0 && xmax == 0 by default scan around 2 sigma of the error
950  // if the errors are also zero then scan from min and max of parameter range
951  // (if parameters are limited Minuit scan from min and max instead of 2 sigma by default)
952  // (force in that case to use errors)
953 
954  // scan is not implemented for TMinuit, the way to return the array is only via the graph
955  if (fMinuit == 0) {
956  Error("TMinuitMinimizer::Scan"," invalid TMinuit instance");
957  return false;
958  }
959 
960  // case of default xmin and xmax
961  if (xmin >= xmax && (int) ipar < fMinuit->GetNumPars() ) {
962  double val = 0; double err = 0;
963  TString name;
964  double xlow = 0; double xup = 0 ;
965  int iuint = 0;
966  // in mnpout index starts from ze
967  fMinuit->mnpout( ipar, name, val, err, xlow, xup, iuint);
968  // redefine 2 sigma for all parameters by default (TMinuit does 1 sigma and range if limited)
969  if (iuint > 0 && err > 0) {
970  xmin = val - 2.*err;
971  xmax = val + 2 * err;
972  }
973  }
974 
975  double arglist[4];
976  int ierr = 0;
977 
978  arglist[0] = PrintLevel()-1;
979  fMinuit->mnexcm("SET PRINT",arglist,1,ierr);
980  // suppress warning in case Printlevel() == 0
981  if (PrintLevel() == 0) fMinuit->mnexcm("SET NOW",arglist,0,ierr);
982 
983  // set precision if needed
984  if (Precision() > 0) {
985  arglist[0] = Precision();
986  fMinuit->mnexcm("SET EPS",arglist,1,ierr);
987  }
988 
989  if (nstep == 0) return false;
990  arglist[0] = ipar+1; // TMinuit starts from 1
991  arglist[1] = nstep+2; // TMinuit deletes two points
992  int nargs = 2;
993  if (xmax > xmin ) {
994  arglist[2] = xmin;
995  arglist[3] = xmax;
996  nargs = 4;
997  }
998  fMinuit->mnexcm("SCAN",arglist,nargs,ierr);
999  if (ierr) {
1000  Error("TMinuitMinimizer::Scan"," Error executing command SCAN");
1001  return false;
1002  }
1003  // get TGraph object
1004  TGraph * gr = dynamic_cast<TGraph *>(fMinuit->GetPlot() );
1005  if (!gr) {
1006  Error("TMinuitMinimizer::Scan"," Error in returned graph object");
1007  return false;
1008  }
1009  nstep = std::min(gr->GetN(), (int) nstep);
1010 
1011 
1012  std::copy(gr->GetX(), gr->GetX()+nstep, x);
1013  std::copy(gr->GetY(), gr->GetY()+nstep, y);
1014  nstep = gr->GetN();
1015  return true;
1016 }
1017 
1019  // perform calculation of Hessian
1020 
1021  if (fMinuit == 0) {
1022  Error("TMinuitMinimizer::Hesse","invalid TMinuit pointer. Need to call first SetFunction and SetVariable");
1023  return false;
1024  }
1025 
1026 
1027  double arglist[10];
1028  int ierr = 0;
1029 
1030  // set error and print level
1031  arglist[0] = ErrorDef();
1032  fMinuit->mnexcm("SET ERR",arglist,1,ierr);
1033 
1034  int printlevel = PrintLevel();
1035  arglist[0] = printlevel - 1;
1036  fMinuit->mnexcm("SET PRINT",arglist,1,ierr);
1037 
1038  // suppress warning in case Printlevel() == 0
1039  if (printlevel == 0) fMinuit->mnexcm("SET NOW",arglist,0,ierr);
1040 
1041  // set precision if needed
1042  if (Precision() > 0) {
1043  arglist[0] = Precision();
1044  fMinuit->mnexcm("SET EPS",arglist,1,ierr);
1045  }
1046 
1047  arglist[0] = MaxFunctionCalls();
1048 
1049  fMinuit->mnexcm("HESSE",arglist,1,ierr);
1050  fStatus += 100*ierr;
1051 
1052  if (ierr != 0) return false;
1053 
1054  // retrieve results (parameter and error matrix)
1055  // only if result is OK
1056 
1057  RetrieveParams();
1059 
1060  return true;
1061 }
1062 
1063 
1064 // } // end namespace Fit
1065 
1066 // } // end namespace ROOT
1067 
virtual bool SetUpperLimitedVariable(unsigned int ivar, const std::string &name, double val, double step, double upper)
set upper limit variable (override if minimizer supports them )
Interface (abstract class) for multi-dimensional functions providing a gradient calculation.
Definition: IFunction.h:330
virtual bool SetVariableStepSize(unsigned int, double)
set the step size of an existing variable
virtual bool Minimize()
method to perform the minimization
Int_t fIstrat
Definition: TMinuit.h:150
Int_t * fIpfix
Definition: TMinuit.h:129
virtual void mnprin(Int_t inkode, Double_t fval)
Prints the values of the parameters at the time of the call.
Definition: TMinuit.cxx:6313
virtual Int_t GetNumFixedPars() const
returns the number of currently fixed parameters
Definition: TMinuit.cxx:864
Double_t * fGlobcc
Definition: TMinuit.h:74
double ErrorDef() const
return the statistical scale used for calculate the error is typically 1 for Chi2 and 0...
Definition: Minimizer.h:434
float xmin
Definition: THbookFile.cxx:93
virtual double GlobalCC(unsigned int) const
global correlation coefficient for variable i
TString fCstatu
Definition: TMinuit.h:167
virtual int VariableIndex(const std::string &name) const
get index of variable given a variable given a name return always -1 .
virtual bool IsFixedVariable(unsigned int) const
query if an existing variable is fixed (i.e.
static TMinuit * fgMinuit
virtual bool SetLowerLimitedVariable(unsigned int ivar, const std::string &name, double val, double step, double lower)
set lower limit variable (override if minimizer supports them )
Implementation in C++ of the Minuit package written by Fred James.
Definition: TMinuit.h:27
Namespace for new ROOT classes and functions.
Definition: StringConv.hxx:21
virtual void mnemat(Double_t *emat, Int_t ndim)
Calculates the external error matrix from the internal matrix.
Definition: TMinuit.cxx:2510
std::vector< double > fParams
Class, describing value, limits and step size of the parameters Provides functionality also to set/re...
void RetrieveParams()
retrieve minimum parameters and errors from TMinuit
TMinuitMinimizer & operator=(const TMinuitMinimizer &rhs)
Assignment operator.
static void FcnGrad(int &, double *g, double &f, double *, int)
implementation of FCN for Minuit when user provided gradient is used
#define R__ASSERT(e)
Definition: TError.h:96
#define gROOT
Definition: TROOT.h:375
Basic string class.
Definition: TString.h:129
virtual bool SetVariableUpperLimit(unsigned int, double)
set the upper-limit of an existing variable
virtual bool SetLimitedVariable(unsigned int ivar, const std::string &name, double val, double step, double, double)
set upper/lower limited variable (override if minimizer supports them )
virtual bool GetVariableSettings(unsigned int, ROOT::Fit::ParameterSettings &) const
get variable settings in a variable object (like ROOT::Fit::ParamsSettings)
virtual const Element * GetMatrixArray() const
Definition: TMatrixTSym.h:189
virtual void Gradient(const double *x, double *grad) const
Evaluate all the vector of function derivatives (gradient) at a point x.
Definition: IFunction.h:350
Minimizer()
Default constructor.
Definition: Minimizer.h:85
virtual bool SetFixedVariable(unsigned int, const std::string &, double)
set fixed variable (override if minimizer supports them )
virtual bool GetCovMatrix(double *cov) const
Fill the passed array with the covariance matrix elements if the variable is fixed or const the value...
virtual Int_t GetParameter(Int_t parNo, Double_t &currentValue, Double_t &currentError) const
return parameter value and error
Definition: TMinuit.cxx:850
int PrintLevel() const
minimizer configuration parameters
Definition: Minimizer.h:411
virtual Int_t FixParameter(Int_t parNo)
fix a parameter
Definition: TMinuit.cxx:836
void SuppressMinuitWarnings(bool nowarn=true)
suppress the minuit warnings (if called with false will enable them) By default they are suppressed o...
void InitTMinuit(int ndim)
initialize the TMinuit instance
R__EXTERN TMinuit * gMinuit
Definition: TMinuit.h:271
Double_t x[n]
Definition: legend1.C:17
Int_t fNpar
Definition: TMinuit.h:41
bool CheckMinuitInstance() const
check TMinuit instance
Double_t fUndefi
Definition: TMinuit.h:60
int printlevel
Double_t fBigedm
Definition: TMinuit.h:61
virtual void mnrn15(Double_t &val, Int_t &inseed)
This is a super-portable random number generator.
Definition: TMinuit.cxx:6626
virtual bool Hesse()
perform a full calculation of the Hessian matrix for error calculation
bool IsValidError() const
return true if Minimizer has performed a detailed error validation (e.g. run Hesse for Minuit) ...
Definition: Minimizer.h:437
void Info(const char *location, const char *msgfmt,...)
void Fix()
fix the parameter
Double_t fAmin
Definition: TMinuit.h:49
virtual bool ReleaseVariable(unsigned int)
release an existing variable
void Error(const char *location, const char *msgfmt,...)
virtual bool Scan(unsigned int i, unsigned int &nstep, double *x, double *y, double xmin=0, double xmax=0)
scan a parameter i around the minimum.
double Tolerance() const
absolute tolerance
Definition: Minimizer.h:420
virtual std::string VariableName(unsigned int ivar) const
return reference to the objective function virtual const ROOT::Math::IGenFunction & Function() const;...
virtual bool FixVariable(unsigned int)
fix an existing variable
virtual void mnpout(Int_t iuext, TString &chnam, Double_t &val, Double_t &err, Double_t &xlolim, Double_t &xuplim, Int_t &iuint) const
Provides the user with information concerning the current status.
Definition: TMinuit.cxx:6256
Documentation for the abstract class IBaseFunctionMultiDim.
Definition: IFunction.h:62
virtual Int_t DefineParameter(Int_t parNo, const char *name, Double_t initVal, Double_t initErr, Double_t lowerLimit, Double_t upperLimit)
Define a parameter.
Definition: TMinuit.cxx:704
static bool fgUseStaticMinuit
void DoReleaseFixParameter(int ivar)
release a parameter that is fixed when it is redefined
virtual void mncont(Int_t ke1, Int_t ke2, Int_t nptu, Double_t *xptu, Double_t *yptu, Int_t &ierrf)
Find points along a contour where FCN is minimum.
Definition: TMinuit.cxx:1404
static ROOT::Math::IMultiGenFunction *& GetGlobalFuncPtr()
Int_t fNpfix
Definition: TMinuit.h:37
TString * fCpnam
Character to be plotted at the X,Y contour positions.
Definition: TMinuit.h:165
int Strategy() const
strategy
Definition: Minimizer.h:427
virtual void mncler()
Resets the parameter list to UNDEFINED.
Definition: TMinuit.cxx:1112
virtual bool SetVariableValue(unsigned int, double)
set the value of an existing variable
bool CheckVarIndex(unsigned int ivar) const
check parameter
static void Fcn(int &, double *, double &f, double *, int)
implementation of FCN for Minuit
TMarker * m
Definition: textangle.C:8
virtual bool SetVariableLowerLimit(unsigned int, double)
set the lower-limit of an existing variable
void RetrieveErrorMatrix()
retrieve error matrix from TMinuit
double Precision() const
precision of minimizer in the evaluation of the objective function ( a value <=0 corresponds to the l...
Definition: Minimizer.h:424
Int_t GetN() const
Definition: TGraph.h:122
TLine * l
Definition: textangle.C:4
float xmax
Definition: THbookFile.cxx:93
void Warning(const char *location, const char *msgfmt,...)
virtual void mnerrs(Int_t number, Double_t &eplus, Double_t &eminus, Double_t &eparab, Double_t &gcc)
Utility routine to get MINOS errors.
Definition: TMinuit.cxx:2587
virtual unsigned int NFree() const
number of free variables (real dimension of the problem) this is <= Function().NDim() which is the to...
TGraphErrors * gr
Definition: legend1.C:25
Int_t * fNiofex
Definition: TMinuit.h:127
void Set(const std::string &name, double value, double step)
set value and name (unlimited parameter)
Double_t * GetX() const
Definition: TGraph.h:129
PyObject * fType
virtual void SetFunction(const ROOT::Math::IMultiGenFunction &func)
set the function to minimize
Double_t fEDM
Definition: TMinuit.h:51
Int_t fNfcn
Definition: TMinuit.h:145
ROOT::Minuit::EMinimizerType fType
#define ClassImp(name)
Definition: Rtypes.h:336
double f(double x)
virtual bool SetVariableLimits(unsigned int ivar, double lower, double upper)
set the limits of an existing variable
~TMinuitMinimizer()
Destructor (no operations)
virtual double MinValue() const
return minimum function value
virtual Int_t Release(Int_t parNo)
release a parameter
Definition: TMinuit.cxx:903
TMinuitMinimizer(ROOT::Minuit::EMinimizerType type=ROOT::Minuit::kMigrad, unsigned int ndim=0)
Default constructor.
int type
Definition: TGX11.cxx:120
Double_t y[n]
Definition: legend1.C:17
double func(double *x, double *p)
Definition: stressTF1.cxx:213
virtual void mnexcm(const char *comand, Double_t *plist, Int_t llist, Int_t &ierflg)
Interprets a command and takes appropriate action.
Definition: TMinuit.cxx:2673
TMatrixTSym< Element > & Invert(Double_t *det=0)
Invert the matrix and calculate its determinant Notice that the LU decomposition is used instead of B...
unsigned int MaxFunctionCalls() const
max number of function calls
Definition: Minimizer.h:414
virtual unsigned int NCalls() const
number of function calls to reach the minimum
TMinuitMinimizer class: ROOT::Math::Minimizer implementation based on TMinuit.
Double_t * GetY() const
Definition: TGraph.h:130
virtual void PrintResults()
return reference to the objective function virtual const ROOT::Math::IGenFunction & Function() const ...
virtual TObject * GetPlot() const
Definition: TMinuit.h:200
virtual bool GetHessianMatrix(double *h) const
Fill the passed array with the Hessian matrix elements The Hessian matrix is the matrix of the second...
A Graph is a graphics object made of two arrays X and Y with npoints each.
Definition: TGraph.h:41
Double_t fEpsma2
Definition: TMinuit.h:57
Double_t fUp
Definition: TMinuit.h:50
virtual double Edm() const
return expected distance reached from the minimum
std::vector< double > fCovar
Int_t fMaxpar
Definition: TMinuit.h:39
const int strategy
Definition: testNdimFit.cxx:46
virtual void SetFCN(void(*fcn)(Int_t &, Double_t *, Double_t &f, Double_t *, Int_t))
To set the address of the minimization function.
Definition: TMinuit.cxx:929
virtual Int_t GetNumPars() const
returns the total number of parameters that have been defined as fixed or free.
Definition: TMinuit.cxx:881
static bool UseStaticMinuit(bool on=true)
static function to switch on/off usage of static global TMinuit instance (gMinuit) By default it is u...
virtual bool Contour(unsigned int i, unsigned int j, unsigned int &npoints, double *xi, double *xj)
find the contour points (xi,xj) of the function for parameter i and j around the minimum The contour ...
Int_t fNu
Definition: TMinuit.h:130
std::vector< double > fErrors
virtual int CovMatrixStatus() const
return status of covariance matrix
virtual unsigned int NDim() const =0
Retrieve the dimension of the function.
Int_t fISW[7]
Definition: TMinuit.h:141
virtual bool SetVariable(unsigned int ivar, const std::string &name, double val, double step)
set free variable
virtual bool GetMinosError(unsigned int i, double &errLow, double &errUp, int=0)
minos error for variable i, return false if Minos failed
const char * Data() const
Definition: TString.h:347