]>
Commit | Line | Data |
---|---|---|
0dd3a2ac | 1 | /************************************************************************** |
2 | * Copyright(c) 2006-07, ALICE Experiment at CERN, All rights reserved. * | |
3 | * * | |
4 | * Author: The ALICE Off-line Project. * | |
5 | * Contributors are mentioned in the code where appropriate. * | |
6 | * * | |
7 | * Permission to use, copy, modify and distribute this software and its * | |
8 | * documentation strictly for non-commercial purposes is hereby granted * | |
9 | * without fee, provided that the above copyright notice appears in all * | |
10 | * copies and that both the copyright notice and this permission notice * | |
11 | * appear in the supporting documentation. The authors make no claims * | |
12 | * about the suitability of this software for any purpose. It is * | |
13 | * provided "as is" without express or implied warranty. * | |
14 | **************************************************************************/ | |
15 | ||
37733f30 | 16 | //------------------------------------------------------------------------- |
17 | // Implementation of the AliSplineFit class | |
52fdcd41 | 18 | // The class performs a spline fit on an incoming TGraph. The graph is |
19 | // divided into several parts (identified by knots between each part). | |
37733f30 | 20 | // Spline fits are performed on each part. According to user parameters, |
52fdcd41 | 21 | // the function, first and second derivative are requested to be continuous |
37733f30 | 22 | // at each knot. |
23 | // Origin: Marian Ivanov, CERN, Marian.Ivanov@cern.ch | |
24 | // Adjustments by Haavard Helstrup, Haavard.Helstrup@cern.ch | |
25 | //------------------------------------------------------------------------- | |
26 | ||
0dd3a2ac | 27 | |
28 | #include "AliSplineFit.h" | |
52fdcd41 | 29 | |
deebe992 | 30 | ClassImp(AliSplineFit) |
0dd3a2ac | 31 | |
52fdcd41 | 32 | TLinearFitter* AliSplineFit::fitterStatic() |
deebe992 | 33 | { |
34 | static TLinearFitter* fit = new TLinearFitter(4,"pol3",""); | |
35 | return fit; | |
36 | } | |
0dd3a2ac | 37 | |
38 | AliSplineFit::AliSplineFit() : | |
39 | fBDump(kFALSE), | |
40 | fGraph (0), | |
41 | fNmin (0), | |
52fdcd41 | 42 | fMinPoints(0), |
0dd3a2ac | 43 | fSigma (0), |
44 | fMaxDelta (0), | |
45 | fN0 (0), | |
46 | fParams (0), | |
47 | fCovars (0), | |
48 | fIndex (0), | |
49 | fN (0), | |
50 | fChi2 (0.0), | |
51 | fX (0), | |
52 | fY0 (0), | |
53 | fY1 (0), | |
54 | fChi2I (0) | |
55 | // | |
56 | // Default constructor | |
57 | // | |
58 | { } | |
59 | ||
60 | ||
61 | ||
62 | AliSplineFit::AliSplineFit(const AliSplineFit& source) : | |
63 | TObject(source), | |
64 | fBDump (source.fBDump), | |
65 | fGraph (source.fGraph), | |
66 | fNmin (source.fNmin), | |
52fdcd41 | 67 | fMinPoints (source.fMinPoints), |
0dd3a2ac | 68 | fSigma (source.fSigma), |
69 | fMaxDelta (source.fMaxDelta), | |
70 | fN0 (source.fN0), | |
52fdcd41 | 71 | fParams (0), |
72 | fCovars (0), | |
73 | fIndex (0), | |
0dd3a2ac | 74 | fN (source.fN), |
52fdcd41 | 75 | fChi2 (0.0), |
76 | fX (0), | |
77 | fY0 (0), | |
78 | fY1 (0), | |
79 | fChi2I (source.fChi2I) | |
0dd3a2ac | 80 | { |
81 | // | |
82 | // Copy constructor | |
83 | // | |
84 | fIndex = new Int_t[fN0]; | |
85 | fParams = new TClonesArray("TVectorD",fN0); | |
86 | fCovars = new TClonesArray("TMatrixD",fN0); | |
87 | fParams = (TClonesArray*)source.fParams->Clone(); | |
88 | fCovars = (TClonesArray*)source.fCovars->Clone(); | |
89 | for (Int_t i=0; i<fN0; i++) fIndex[i] = source.fIndex[i]; | |
52fdcd41 | 90 | |
0dd3a2ac | 91 | fX = new Double_t[fN]; |
92 | fY0 = new Double_t[fN]; | |
93 | fY1 = new Double_t[fN]; | |
94 | fChi2I = new Double_t[fN]; | |
95 | for (Int_t i=0; i<fN; i++){ | |
96 | fX[i] = source.fX[i]; | |
97 | fY0[i] = source.fY0[i]; | |
98 | fY1[i] = source.fY1[i]; | |
8625679a | 99 | fChi2I[i] = source.fChi2I[i]; |
0dd3a2ac | 100 | } |
101 | } | |
102 | AliSplineFit& AliSplineFit::operator=(const AliSplineFit& source){ | |
103 | // | |
104 | // assignment operator | |
52fdcd41 | 105 | // |
0dd3a2ac | 106 | if (&source == this) return *this; |
107 | ||
108 | // | |
109 | // reassign memory as previous fit could have a different size | |
110 | // | |
111 | ||
52fdcd41 | 112 | if ( fN0 != source.fN0) { |
0dd3a2ac | 113 | |
114 | delete fParams; | |
115 | delete fCovars; | |
116 | delete []fIndex; | |
117 | ||
118 | fN0 = source.fN0; | |
119 | fIndex = new Int_t[fN0]; | |
120 | fParams = new TClonesArray("TVectorD",fN0); | |
121 | fCovars = new TClonesArray("TMatrixD",fN0); | |
122 | } | |
52fdcd41 | 123 | if ( fN != source.fN) { |
0dd3a2ac | 124 | |
125 | delete []fX; | |
126 | delete []fY0; | |
127 | delete []fY1; | |
128 | delete []fChi2I; | |
52fdcd41 | 129 | fN = source.fN; |
0dd3a2ac | 130 | fX = new Double_t[fN]; |
131 | fY0 = new Double_t[fN]; | |
132 | fY1 = new Double_t[fN]; | |
133 | fChi2I = new Double_t[fN]; | |
134 | } | |
135 | ||
136 | // use copy constructor (without reassigning memory) to copy values | |
52fdcd41 | 137 | |
0dd3a2ac | 138 | new (this) AliSplineFit(source); |
52fdcd41 | 139 | |
0dd3a2ac | 140 | return *this; |
141 | } | |
142 | ||
52fdcd41 | 143 | |
0dd3a2ac | 144 | AliSplineFit::~AliSplineFit(){ |
145 | // | |
146 | // destructor. Don't delete fGraph, as this normally comes as input parameter | |
147 | // | |
148 | delete []fX; | |
149 | delete []fY0; | |
150 | delete []fY1; | |
151 | delete []fChi2I; | |
152 | delete fParams; | |
153 | delete fCovars; | |
154 | delete []fIndex; | |
155 | } | |
156 | ||
157 | Double_t AliSplineFit::Eval(Double_t x, Int_t deriv) const{ | |
158 | // | |
159 | // evaluate value at x | |
160 | // deriv = 0: function value | |
161 | // = 1: first derivative | |
162 | // = 2: 2nd derivative | |
163 | // = 3: 3rd derivative | |
164 | // | |
165 | // a2 = -(3*a0 -3*b0 + 2*a1*dx +b1*dx)/(dx*dx) | |
52fdcd41 | 166 | // a3 = -(-2*a0+2*b0 - a1*dx - b1*dx)/(dx*dx*dx) |
0dd3a2ac | 167 | |
168 | Int_t index = TMath::BinarySearch(fN,fX,x); | |
169 | if (index<0) index =0; | |
170 | if (index>fN-2) index =fN-2; | |
171 | // | |
172 | Double_t dx = x-fX[index]; | |
173 | Double_t dxc = fX[index+1]-fX[index]; | |
36a8d844 | 174 | if (dxc<=0) return fY0[index]; |
0dd3a2ac | 175 | Double_t y0 = fY0[index]; |
176 | Double_t y1 = fY1[index]; | |
177 | Double_t y01 = fY0[index+1]; | |
178 | Double_t y11 = fY1[index+1]; | |
179 | Double_t y2 = -(3.*y0-3.*y01+2*y1*dxc+y11*dxc)/(dxc*dxc); | |
180 | Double_t y3 = -(-2.* y0 + 2*y01 - y1*dxc - y11*dxc) /(dxc*dxc*dxc); | |
181 | Double_t val = y0+y1*dx+y2*dx*dx+y3*dx*dx*dx; | |
182 | if (deriv==1) val = y1+2.*y2*dx+3.*y3*dx*dx; | |
183 | if (deriv==2) val = 2.*y2+6.*y3*dx; | |
184 | if (deriv==3) val = 6*y3; | |
185 | return val; | |
186 | } | |
187 | ||
188 | ||
189 | TGraph * AliSplineFit::GenerGraph(Int_t npoints, Double_t fraction, Double_t s1, Double_t s2, Double_t s3, Int_t der){ | |
190 | // | |
191 | // generate random graph | |
192 | // xrange 0,1 | |
193 | // yrange 0,1 | |
194 | // s1, s2, s3 - sigma of derivative | |
195 | // fraction - | |
196 | ||
197 | Double_t *value = new Double_t[npoints]; | |
198 | Double_t *time = new Double_t[npoints]; | |
199 | Double_t d0=0, d1=0,d2=0,d3=0; | |
200 | value[0] = d0; | |
201 | time[0] = 0; | |
202 | for(Int_t i=1; i<npoints; i++){ | |
203 | Double_t dtime = 1./npoints; | |
204 | Double_t dd1 = dtime; | |
205 | Double_t dd2 = dd1*dd1; | |
206 | Double_t dd3 = dd2*dd1; | |
207 | d0 += d1*dd1 + d2*dd2/2. + d3*dd3/6.; | |
208 | d1 += d2*dd1 +d3*dd2/2; | |
209 | d2 += d3*dd1; | |
210 | value[i] = d0; | |
211 | time[i] = time[i-1]+dtime; | |
212 | d1 =(1.-fraction)*d1+fraction*(gRandom->Exp(s1))*(gRandom->Rndm()-0.5); | |
213 | d2 =(1.-fraction)*d2+fraction*(gRandom->Exp(s2))*(gRandom->Rndm()-0.5); | |
214 | d3 =(1.-fraction)*d3+fraction*(gRandom->Exp(s3))*(gRandom->Rndm()-0.5); | |
215 | if (gRandom->Rndm()<fraction) d3 =(1.-fraction)*d3+fraction*(gRandom->BreitWigner(0,s3)); | |
216 | } | |
217 | Double_t dmean = (value[npoints-1]-value[0])/(time[npoints-1]-time[0]); | |
218 | Double_t min = value[0]; | |
219 | Double_t max = value[0]; | |
220 | for (Int_t i=0; i<npoints; i++){ | |
221 | value[i] = value[i]-dmean*(time[i]-time[0]); | |
222 | if (value[i]<min) min=value[i]; | |
223 | if (value[i]>max) max=value[i]; | |
224 | } | |
225 | ||
226 | for (Int_t i=0; i<npoints; i++){ | |
227 | value[i] = (value[i]-min)/(max-min); | |
228 | } | |
229 | if (der==1) for (Int_t i=1; i<npoints; i++){ | |
230 | value[i-1] = (value[i]-value[i-1])/(time[i]-time[i-1]); | |
231 | } | |
232 | ||
233 | TGraph * graph = new TGraph(npoints,time,value); | |
52fdcd41 | 234 | |
0dd3a2ac | 235 | delete [] value; |
236 | delete [] time; | |
237 | return graph; | |
238 | } | |
239 | ||
240 | ||
241 | TGraph * AliSplineFit::GenerNoise(TGraph * graph0, Double_t sigma0){ | |
242 | // | |
243 | // add noise to graph | |
244 | // | |
245 | ||
246 | Int_t npoints=graph0->GetN(); | |
247 | Double_t *value = new Double_t[npoints]; | |
248 | Double_t *time = new Double_t[npoints]; | |
249 | for(Int_t i=0; i<npoints; i++){ | |
250 | time[i] = graph0->GetX()[i]; | |
251 | value[i] = graph0->GetY()[i]+gRandom->Gaus(0,sigma0); | |
252 | } | |
253 | TGraph * graph = new TGraph(npoints,time,value); | |
254 | ||
255 | delete [] value; | |
256 | delete [] time; | |
257 | return graph; | |
258 | } | |
52fdcd41 | 259 | |
0dd3a2ac | 260 | |
261 | TGraph * AliSplineFit::MakeGraph(Double_t xmin, Double_t xmax, Int_t npoints, Int_t deriv) const { | |
262 | // | |
263 | // if npoints<=0 draw derivative | |
264 | // | |
265 | ||
266 | TGraph *graph =0; | |
267 | if (npoints<=0) { | |
268 | if (deriv<=0) return new TGraph(fN,fX,fY0); | |
269 | if (deriv==1) return new TGraph(fN,fX,fY1); | |
270 | if (deriv>2) return new TGraph(fN-1,fX,fChi2I); | |
271 | } | |
272 | Double_t * x = new Double_t[npoints+1]; | |
273 | Double_t * y = new Double_t[npoints+1]; | |
274 | for (Int_t ip=0; ip<=npoints; ip++){ | |
275 | x[ip] = xmin+ (xmax-xmin)*(Double_t(ip)/Double_t(npoints)); | |
276 | y[ip] = Eval(x[ip],deriv); | |
277 | } | |
278 | ||
279 | graph = new TGraph(npoints,x,y); | |
280 | delete [] x; | |
281 | delete [] y; | |
282 | return graph; | |
283 | } | |
284 | ||
285 | TGraph * AliSplineFit::MakeDiff(TGraph * graph0) const { | |
286 | // | |
52fdcd41 | 287 | // Make graph of difference to reference graph |
0dd3a2ac | 288 | // |
289 | ||
290 | Int_t npoints=graph0->GetN(); | |
291 | TGraph *graph =0; | |
292 | Double_t * x = new Double_t[npoints]; | |
293 | Double_t * y = new Double_t[npoints]; | |
294 | for (Int_t ip=0; ip<npoints; ip++){ | |
295 | x[ip] = graph0->GetX()[ip]; | |
296 | y[ip] = Eval(x[ip],0)-graph0->GetY()[ip]; | |
297 | } | |
298 | graph = new TGraph(npoints,x,y); | |
299 | delete [] x; | |
300 | delete [] y; | |
301 | return graph; | |
302 | } | |
303 | ||
304 | ||
305 | TH1F * AliSplineFit::MakeDiffHisto(TGraph * graph0) const { | |
306 | // | |
52fdcd41 | 307 | // Make histogram of difference to reference graph |
0dd3a2ac | 308 | // |
309 | ||
310 | Int_t npoints=graph0->GetN(); | |
6389ff30 | 311 | Float_t min=1e38,max=-1e38; |
0dd3a2ac | 312 | for (Int_t ip=0; ip<npoints; ip++){ |
313 | Double_t x = graph0->GetX()[ip]; | |
314 | Double_t y = Eval(x,0)-graph0->GetY()[ip]; | |
315 | if (ip==0) { | |
316 | min = y; | |
317 | max = y; | |
318 | }else{ | |
319 | if (y<min) min=y; | |
320 | if (y>max) max=y; | |
52fdcd41 | 321 | } |
0dd3a2ac | 322 | } |
323 | ||
324 | TH1F *his = new TH1F("hdiff","hdiff", 100, min, max); | |
325 | for (Int_t ip=0; ip<npoints; ip++){ | |
326 | Double_t x = graph0->GetX()[ip]; | |
327 | Double_t y = Eval(x,0)-graph0->GetY()[ip]; | |
328 | his->Fill(y); | |
329 | } | |
330 | ||
331 | return his; | |
332 | } | |
333 | ||
334 | ||
335 | ||
336 | void AliSplineFit::InitKnots(TGraph * graph, Int_t min, Int_t iter, Double_t maxDelta){ | |
337 | // | |
52fdcd41 | 338 | // initialize knots + estimate sigma of noise + make initial parameters |
0dd3a2ac | 339 | // |
340 | // | |
341 | ||
342 | const Double_t kEpsilon = 1.e-7; | |
343 | fGraph = graph; | |
344 | fNmin = min; | |
345 | fMaxDelta = maxDelta; | |
346 | Int_t npoints = fGraph->GetN(); | |
52fdcd41 | 347 | |
348 | // Make simple spline if too few points in graph | |
349 | ||
350 | if (npoints < fMinPoints ) { | |
351 | CopyGraph(); | |
352 | return; | |
353 | } | |
354 | ||
0dd3a2ac | 355 | fN0 = (npoints/fNmin)+1; |
356 | Float_t delta = Double_t(npoints)/Double_t(fN0-1); | |
357 | ||
358 | fParams = new TClonesArray("TVectorD",fN0); | |
359 | fCovars = new TClonesArray("TMatrixD",fN0); | |
360 | fIndex = new Int_t[fN0]; | |
361 | TLinearFitter fitterLocal(4,"pol3"); // local fitter | |
362 | Double_t sigma2 =0; | |
363 | ||
364 | ||
365 | Double_t yMin=graph->GetY()[0]; | |
366 | Double_t yMax=graph->GetY()[0]; | |
367 | ||
368 | for (Int_t iKnot=0; iKnot<fN0; iKnot++){ | |
369 | Int_t index0 = TMath::Nint(Double_t(iKnot)*Double_t(delta)); | |
370 | Int_t index1 = TMath::Min(TMath::Nint(Double_t(iKnot+1)*Double_t(delta)),npoints-1); | |
371 | Int_t indexM = (iKnot>0) ? fIndex[iKnot-1]:index0; | |
372 | fIndex[iKnot]=TMath::Min(index0, npoints-1); | |
373 | Float_t startX =graph->GetX()[fIndex[iKnot]]; | |
374 | ||
375 | for (Int_t ipoint=indexM; ipoint<index1; ipoint++){ | |
376 | Double_t dxl =graph->GetX()[ipoint]-startX; | |
377 | Double_t y = graph->GetY()[ipoint]; | |
378 | if (y<yMin) yMin=y; | |
379 | if (y>yMax) yMax=y; | |
380 | fitterLocal.AddPoint(&dxl,y,1); | |
381 | } | |
382 | ||
383 | fitterLocal.Eval(); | |
384 | sigma2 += fitterLocal.GetChisquare()/Double_t((index1-indexM)-4.); | |
385 | TMatrixD * covar = new ((*fCovars)[iKnot]) TMatrixD(4,4); | |
386 | TVectorD * param = new ((*fParams)[iKnot]) TVectorD(4); | |
387 | fitterLocal.GetParameters(*param); | |
388 | fitterLocal.GetCovarianceMatrix(*covar); | |
389 | fitterLocal.ClearPoints(); | |
390 | } | |
391 | fSigma =TMath::Sqrt(sigma2/Double_t(fN0)); // mean sigma | |
392 | Double_t tDiff = ((yMax-yMin)+TMath::Abs(yMax)+TMath::Abs(yMin))*kEpsilon; | |
393 | fSigma += tDiff+fMaxDelta/TMath::Sqrt(npoints); | |
394 | fMaxDelta +=tDiff; | |
395 | for (Int_t iKnot=0; iKnot<fN0; iKnot++){ | |
396 | TMatrixD & cov = *((TMatrixD*)fCovars->At(iKnot)); | |
397 | cov*=fSigma*fSigma; | |
52fdcd41 | 398 | } |
0dd3a2ac | 399 | OptimizeKnots(iter); |
400 | ||
401 | fN = 0; | |
402 | for (Int_t iKnot=0; iKnot<fN0; iKnot++) if (fIndex[iKnot]>=0) fN++; | |
403 | fX = new Double_t[fN]; | |
404 | fY0 = new Double_t[fN]; | |
405 | fY1 = new Double_t[fN]; | |
406 | fChi2I = new Double_t[fN]; | |
407 | Int_t iKnot=0; | |
408 | for (Int_t i=0; i<fN0; i++){ | |
52fdcd41 | 409 | if (fIndex[i]<0) continue; |
0dd3a2ac | 410 | if (iKnot>=fN) { |
411 | printf("AliSplineFit::InitKnots: Knot number > Max knot number\n"); | |
412 | break; | |
413 | } | |
414 | TVectorD * param = (TVectorD*) fParams->At(i); | |
415 | fX[iKnot] = fGraph->GetX()[fIndex[i]]; | |
416 | fY0[iKnot] = (*param)(0); | |
52fdcd41 | 417 | fY1[iKnot] = (*param)(1); |
0dd3a2ac | 418 | fChi2I[iKnot] = 0; |
419 | iKnot++; | |
420 | } | |
421 | } | |
422 | ||
423 | ||
424 | Int_t AliSplineFit::OptimizeKnots(Int_t nIter){ | |
425 | // | |
426 | // | |
427 | // | |
428 | const Double_t kMaxChi2= 5; | |
429 | Int_t nKnots=0; | |
430 | TTreeSRedirector cstream("SplineIter.root"); | |
431 | for (Int_t iIter=0; iIter<nIter; iIter++){ | |
432 | if (fBDump) cstream<<"Fit"<< | |
433 | "iIter="<<iIter<< | |
434 | "fit.="<<this<< | |
435 | "\n"; | |
436 | nKnots=2; | |
437 | for (Int_t iKnot=1; iKnot<fN0-1; iKnot++){ | |
438 | if (fIndex[iKnot]<0) continue; //disabled knot | |
439 | Double_t chi2 = CheckKnot(iKnot); | |
440 | Double_t startX = fGraph->GetX()[fIndex[iKnot]]; | |
441 | if (fBDump) { | |
442 | TMatrixD * covar = (TMatrixD*)fCovars->At(iKnot); | |
443 | TVectorD * param = (TVectorD*)fParams->At(iKnot); | |
444 | cstream<<"Chi2"<< | |
445 | "iIter="<<iIter<< | |
446 | "iKnot="<<iKnot<< | |
447 | "chi2="<<chi2<< | |
448 | "x="<<startX<< | |
449 | "param="<<param<< | |
450 | "covar="<<covar<< | |
451 | "\n"; | |
452 | } | |
453 | if (chi2>kMaxChi2) { nKnots++;continue;} | |
454 | fIndex[iKnot]*=-1; | |
455 | Int_t iPrevious=iKnot-1; | |
456 | Int_t iNext =iKnot+1; | |
457 | while (fIndex[iPrevious]<0) iPrevious--; | |
458 | while (fIndex[iNext]<0) iNext++; | |
459 | RefitKnot(iPrevious); | |
460 | RefitKnot(iNext); | |
461 | iKnot++; | |
462 | while (iKnot<fN0-1&& fIndex[iKnot]<0) iKnot++; | |
463 | } | |
464 | } | |
465 | return nKnots; | |
466 | } | |
467 | ||
468 | ||
469 | Bool_t AliSplineFit::RefitKnot(Int_t iKnot){ | |
470 | // | |
471 | // | |
472 | // | |
0dd3a2ac | 473 | |
474 | Int_t iPrevious=(iKnot>0) ?iKnot-1: 0; | |
475 | Int_t iNext =(iKnot<fN0)?iKnot+1: fN0-1; | |
476 | while (iPrevious>0&&fIndex[iPrevious]<0) iPrevious--; | |
477 | while (iNext<fN0&&fIndex[iNext]<0) iNext++; | |
478 | if (iPrevious<0) iPrevious=0; | |
479 | if (iNext>=fN0) iNext=fN0-1; | |
480 | ||
481 | Double_t startX = fGraph->GetX()[fIndex[iKnot]]; | |
deebe992 | 482 | AliSplineFit::fitterStatic()->ClearPoints(); |
0dd3a2ac | 483 | Int_t indPrev = fIndex[iPrevious]; |
484 | Int_t indNext = fIndex[iNext]; | |
485 | Double_t *graphX = fGraph->GetX(); | |
486 | Double_t *graphY = fGraph->GetY(); | |
487 | ||
488 | // make arrays for points to fit (to save time) | |
489 | ||
490 | Int_t nPoints = indNext-indPrev; | |
491 | Double_t *xPoint = new Double_t[3*nPoints]; | |
492 | Double_t *yPoint = &xPoint[nPoints]; | |
493 | Double_t *ePoint = &xPoint[2*nPoints]; | |
494 | Int_t indVec=0; | |
495 | for (Int_t iPoint=indPrev; iPoint<indNext; iPoint++, indVec++){ | |
496 | Double_t dxl = graphX[iPoint]-startX; | |
497 | Double_t y = graphY[iPoint]; | |
498 | xPoint[indVec] = dxl; | |
499 | yPoint[indVec] = y; | |
500 | ePoint[indVec] = fSigma; | |
deebe992 | 501 | // ePoint[indVec] = fSigma+TMath::Abs(y)*kEpsilon; |
502 | // AliSplineFit::fitterStatic.AddPoint(&dxl,y,fSigma+TMath::Abs(y)*kEpsilon); | |
0dd3a2ac | 503 | } |
deebe992 | 504 | AliSplineFit::fitterStatic()->AssignData(nPoints,1,xPoint,yPoint,ePoint); |
505 | AliSplineFit::fitterStatic()->Eval(); | |
0dd3a2ac | 506 | |
507 | // delete temporary arrays | |
508 | ||
509 | delete [] xPoint; | |
510 | ||
511 | TMatrixD * covar = (TMatrixD*)fCovars->At(iKnot); | |
512 | TVectorD * param = (TVectorD*)fParams->At(iKnot); | |
deebe992 | 513 | AliSplineFit::fitterStatic()->GetParameters(*param); |
514 | AliSplineFit::fitterStatic()->GetCovarianceMatrix(*covar); | |
0dd3a2ac | 515 | return 0; |
516 | } | |
517 | ||
518 | ||
519 | Float_t AliSplineFit::CheckKnot(Int_t iKnot){ | |
520 | // | |
521 | // | |
522 | // | |
523 | ||
524 | Int_t iPrevious=iKnot-1; | |
525 | Int_t iNext =iKnot+1; | |
526 | while (fIndex[iPrevious]<0) iPrevious--; | |
527 | while (fIndex[iNext]<0) iNext++; | |
528 | TVectorD &pPrevious = *((TVectorD*)fParams->At(iPrevious)); | |
529 | TVectorD &pNext = *((TVectorD*)fParams->At(iNext)); | |
530 | TVectorD &pKnot = *((TVectorD*)fParams->At(iKnot)); | |
531 | TMatrixD &cPrevious = *((TMatrixD*)fCovars->At(iPrevious)); | |
532 | TMatrixD &cNext = *((TMatrixD*)fCovars->At(iNext)); | |
533 | TMatrixD &cKnot = *((TMatrixD*)fCovars->At(iKnot)); | |
534 | Double_t xPrevious = fGraph->GetX()[fIndex[iPrevious]]; | |
535 | Double_t xNext = fGraph->GetX()[fIndex[iNext]]; | |
536 | Double_t xKnot = fGraph->GetX()[fIndex[iKnot]]; | |
537 | ||
538 | // extra variables introduced to save processing time | |
539 | ||
540 | Double_t dxc = xNext-xPrevious; | |
541 | Double_t invDxc = 1./dxc; | |
542 | Double_t invDxc2 = invDxc*invDxc; | |
543 | TMatrixD tPrevious(4,4); | |
544 | TMatrixD tNext(4,4); | |
545 | ||
546 | tPrevious(0,0) = 1; tPrevious(1,1) = 1; | |
547 | tPrevious(2,0) = -3.*invDxc2; | |
548 | tPrevious(2,1) = -2.*invDxc; | |
549 | tPrevious(3,0) = 2.*invDxc2*invDxc; | |
550 | tPrevious(3,1) = 1.*invDxc2; | |
551 | tNext(2,0) = 3.*invDxc2; tNext(2,1) = -1*invDxc; | |
552 | tNext(3,0) = -2.*invDxc2*invDxc; tNext(3,1) = 1.*invDxc2; | |
553 | TMatrixD tpKnot(4,4); | |
554 | TMatrixD tpNext(4,4); | |
555 | Double_t dx = xKnot-xPrevious; | |
556 | tpKnot(0,0) = 1; tpKnot(1,1) = 1; tpKnot(2,2) = 1; tpKnot(3,3) = 1; | |
557 | tpKnot(0,1) = dx; tpKnot(0,2) = dx*dx; tpKnot(0,3) = dx*dx*dx; | |
558 | tpKnot(1,2) = 2.*dx; tpKnot(1,3) = 3.*dx*dx; | |
559 | tpKnot(2,3) = 3.*dx; | |
560 | Double_t dxn = xNext-xPrevious; | |
561 | tpNext(0,0) = 1; tpNext(1,1) = 1; tpNext(2,2) = 1; tpNext(3,3) = 1; | |
562 | tpNext(0,1) = dxn; tpNext(0,2) = dxn*dxn; tpNext(0,3) = dxn*dxn*dxn; | |
563 | tpNext(1,2) = 2.*dxn; tpNext(1,3) = 3.*dxn*dxn; | |
564 | tpNext(2,3) = 3.*dxn; | |
565 | ||
566 | // | |
567 | // matrix and vector at previous | |
568 | // | |
569 | ||
570 | TVectorD sPrevious = tPrevious*pPrevious+tNext*pNext; | |
571 | TVectorD sKnot = tpKnot*sPrevious; | |
52fdcd41 | 572 | TVectorD sNext = tpNext*sPrevious; |
0dd3a2ac | 573 | |
574 | TMatrixD csPrevious00(tPrevious, TMatrixD::kMult,cPrevious); | |
575 | csPrevious00 *= tPrevious.T(); | |
576 | TMatrixD csPrevious01(tNext,TMatrixD::kMult,cNext); | |
577 | csPrevious01*=tNext.T(); | |
578 | TMatrixD csPrevious(csPrevious00,TMatrixD::kPlus,csPrevious01); | |
579 | TMatrixD csKnot(tpKnot,TMatrixD::kMult,csPrevious); | |
580 | csKnot*=tpKnot.T(); | |
581 | TMatrixD csNext(tpNext,TMatrixD::kMult,csPrevious); | |
582 | csNext*=tpNext.T(); | |
583 | ||
584 | TVectorD dPrevious = pPrevious-sPrevious; | |
585 | TVectorD dKnot = pKnot-sKnot; | |
586 | TVectorD dNext = pNext-sNext; | |
587 | // | |
588 | // | |
589 | TMatrixD prec(4,4); | |
590 | prec(0,0) = (fMaxDelta*fMaxDelta); | |
591 | prec(1,1) = prec(0,0)*invDxc2; | |
592 | prec(2,2) = prec(1,1)*invDxc2; | |
593 | prec(3,3) = prec(2,2)*invDxc2; | |
594 | ||
595 | // prec(0,0) = (fMaxDelta*fMaxDelta); | |
596 | // prec(1,1) = (fMaxDelta*fMaxDelta)/(dxc*dxc); | |
597 | // prec(2,2) = (fMaxDelta*fMaxDelta)/(dxc*dxc*dxc*dxc); | |
598 | // prec(3,3) = (fMaxDelta*fMaxDelta)/(dxc*dxc*dxc*dxc*dxc*dxc); | |
599 | ||
600 | csPrevious+=cPrevious; | |
601 | csPrevious+=prec; | |
602 | csPrevious.Invert(); | |
603 | Double_t chi2P = dPrevious*(csPrevious*dPrevious); | |
604 | ||
605 | csKnot+=cKnot; | |
606 | csKnot+=prec; | |
607 | csKnot.Invert(); | |
608 | Double_t chi2K = dKnot*(csKnot*dKnot); | |
609 | ||
610 | csNext+=cNext; | |
611 | csNext+=prec; | |
612 | csNext.Invert(); | |
613 | Double_t chi2N = dNext*(csNext*dNext); | |
614 | ||
615 | return (chi2P+chi2K+chi2N)/8.; | |
616 | ||
617 | ||
618 | } | |
52fdcd41 | 619 | |
0dd3a2ac | 620 | void AliSplineFit::SplineFit(Int_t nder){ |
621 | // | |
622 | // Cubic spline fit of graph | |
52fdcd41 | 623 | // |
0dd3a2ac | 624 | // nder |
625 | // nder<0 - no continuity requirement | |
626 | // =0 - continous 0 derivative | |
627 | // =1 - continous 1 derivative | |
52fdcd41 | 628 | // >1 - continous 2 derivative |
0dd3a2ac | 629 | // |
630 | if (!fGraph) return; | |
631 | TGraph * graph = fGraph; | |
632 | if (nder>1) nder=2; | |
633 | Int_t nknots = fN; | |
a551f6ec | 634 | if (nknots < 2 ) return; |
0dd3a2ac | 635 | Int_t npoints = graph->GetN(); |
6ec4e3e3 | 636 | if (npoints < fMinPoints ) return; |
0dd3a2ac | 637 | // |
638 | // | |
639 | // spline fit | |
640 | // each knot 4 parameters | |
52fdcd41 | 641 | // |
0dd3a2ac | 642 | TMatrixD *pmatrix = 0; |
643 | TVectorD *pvalues = 0; | |
644 | if (nder>1){ | |
645 | pmatrix = new TMatrixD(4*(nknots-1)+3*(nknots-2), 4*(nknots-1)+3*(nknots-2)); | |
646 | pvalues = new TVectorD(4*(nknots-1)+3*(nknots-2)); | |
647 | } | |
648 | if (nder==1){ | |
649 | pmatrix = new TMatrixD(4*(nknots-1)+2*(nknots-2), 4*(nknots-1)+2*(nknots-2)); | |
650 | pvalues = new TVectorD(4*(nknots-1)+2*(nknots-2)); | |
651 | } | |
652 | if (nder==0){ | |
653 | pmatrix = new TMatrixD(4*(nknots-1)+1*(nknots-2), 4*(nknots-1)+1*(nknots-2)); | |
654 | pvalues = new TVectorD(4*(nknots-1)+1*(nknots-2)); | |
655 | } | |
656 | if (nder<0){ | |
657 | pmatrix = new TMatrixD(4*(nknots-1)+0*(nknots-2), 4*(nknots-1)+0*(nknots-2)); | |
658 | pvalues = new TVectorD(4*(nknots-1)+0*(nknots-2)); | |
659 | } | |
660 | ||
661 | ||
662 | TMatrixD &matrix = *pmatrix; | |
663 | TVectorD &values = *pvalues; | |
664 | Int_t current = 0; | |
665 | // | |
666 | // defined extra variables (current4 etc.) to save processing time. | |
667 | // fill normal matrices, then copy to sparse matrix. | |
668 | // | |
669 | Double_t *graphX = graph->GetX(); | |
670 | Double_t *graphY = graph->GetY(); | |
671 | for (Int_t ip=0;ip<npoints;ip++){ | |
672 | if (current<nknots-2&&graphX[ip]>fX[current+1]) current++; | |
673 | Double_t xmiddle = (fX[current+1]+fX[current])*0.5; | |
674 | Double_t x1 = graphX[ip]- xmiddle; | |
675 | Double_t x2 = x1*x1; | |
676 | Double_t x3 = x2*x1; | |
677 | Double_t x4 = x2*x2; | |
678 | Double_t x5 = x3*x2; | |
679 | Double_t x6 = x3*x3; | |
680 | Double_t y = graphY[ip]; | |
681 | Int_t current4 = 4*current; | |
682 | ||
683 | matrix(current4 , current4 )+=1; | |
684 | matrix(current4 , current4+1)+=x1; | |
685 | matrix(current4 , current4+2)+=x2; | |
686 | matrix(current4 , current4+3)+=x3; | |
687 | // | |
688 | matrix(current4+1, current4 )+=x1; | |
689 | matrix(current4+1, current4+1)+=x2; | |
690 | matrix(current4+1, current4+2)+=x3; | |
691 | matrix(current4+1, current4+3)+=x4; | |
692 | // | |
693 | matrix(current4+2, current4 )+=x2; | |
694 | matrix(current4+2, current4+1)+=x3; | |
695 | matrix(current4+2, current4+2)+=x4; | |
696 | matrix(current4+2, current4+3)+=x5; | |
697 | // | |
698 | matrix(current4+3, current4 )+=x3; | |
699 | matrix(current4+3, current4+1)+=x4; | |
700 | matrix(current4+3, current4+2)+=x5; | |
701 | matrix(current4+3, current4+3)+=x6; | |
702 | // | |
703 | values(current4 ) += y; | |
704 | values(current4+1) += y*x1; | |
705 | values(current4+2) += y*x2; | |
706 | values(current4+3) += y*x3; | |
707 | } | |
708 | // | |
709 | // constraint 0 | |
710 | // | |
711 | Int_t offset =4*(nknots-1)-1; | |
712 | if (nder>=0) for (Int_t iknot = 1; iknot<nknots-1; iknot++){ | |
713 | ||
714 | Double_t dxm = (fX[iknot]-fX[iknot-1])*0.5; | |
715 | Double_t dxp = -(fX[iknot+1]-fX[iknot])*0.5; | |
716 | Double_t dxm2 = dxm*dxm; | |
717 | Double_t dxp2 = dxp*dxp; | |
718 | Double_t dxm3 = dxm2*dxm; | |
719 | Double_t dxp3 = dxp2*dxp; | |
720 | Int_t iknot4 = 4*iknot; | |
721 | Int_t iknot41 = 4*(iknot-1); | |
722 | Int_t offsKnot = offset+iknot; | |
723 | // | |
724 | // condition on knot | |
725 | // | |
726 | // a0[i] = a0m[i-1] + a1m[i-1]*dxm + a2m[i-1]*dxm^2 + a3m[i-1]*dxm^3 | |
727 | // a0[i] = a0m[i-0] + a1m[i-0]*dxp + a2m[i-0]*dxp^2 + a3m[i-0]*dxp^3 | |
728 | // (a0m[i-1] + a1m[i-1]*dxm + a2m[i-1]*dxm^2 + a3m[i-1]*dxm^3) - | |
729 | // (a0m[i-0] + a1m[i-0]*dxp + a2m[i-0]*dxp^2 + a3m[i-0]*dxp^3) = 0 | |
730 | ||
731 | matrix(offsKnot, iknot41 )=1; | |
732 | matrix(offsKnot, iknot4 )=-1; | |
733 | ||
734 | matrix(offsKnot, iknot41+1)=dxm; | |
735 | matrix(offsKnot, iknot4 +1)=-dxp; | |
736 | ||
737 | matrix(offsKnot, iknot41+2)=dxm2; | |
738 | matrix(offsKnot, iknot4 +2)=-dxp2; | |
739 | ||
740 | matrix(offsKnot, iknot41+3)=dxm3; | |
741 | matrix(offsKnot, iknot4 +3)=-dxp3; | |
742 | ||
743 | matrix(iknot41 , offsKnot)=1; | |
744 | matrix(iknot41+1, offsKnot)=dxm; | |
745 | matrix(iknot41+2, offsKnot)=dxm2; | |
746 | matrix(iknot41+3, offsKnot)=dxm3; | |
747 | matrix(iknot4 , offsKnot)=-1; | |
748 | matrix(iknot4+1, offsKnot)=-dxp; | |
749 | matrix(iknot4+2, offsKnot)=-dxp2; | |
750 | matrix(iknot4+3, offsKnot)=-dxp3; | |
751 | } | |
752 | // | |
753 | // constraint 1 | |
754 | // | |
755 | offset =4*(nknots-1)-1+(nknots-2); | |
756 | if (nder>=1)for (Int_t iknot = 1; iknot<nknots-1; iknot++){ | |
757 | ||
758 | Double_t dxm = (fX[iknot]-fX[iknot-1])*0.5; | |
759 | Double_t dxp = -(fX[iknot+1]-fX[iknot])*0.5; | |
760 | Double_t dxm2 = dxm*dxm; | |
761 | Double_t dxp2 = dxp*dxp; | |
762 | Int_t iknot4 = 4*iknot; | |
763 | Int_t iknot41 = 4*(iknot-1); | |
764 | Int_t offsKnot = offset+iknot; | |
765 | // | |
766 | // condition on knot derivation | |
767 | // | |
768 | // a0d[i] = a1m[i-1] + 2*a2m[i-1]*dxm + 3*a3m[i-1]*dxm^2 | |
769 | // a0d[i] = a1m[i-0] + 2*a2m[i-0]*dxp + 3*a3m[i-0]*dxp^2 | |
770 | ||
771 | // | |
772 | matrix(offsKnot, iknot41+1)= 1; | |
773 | matrix(offsKnot, iknot4 +1)=-1; | |
774 | ||
775 | matrix(offsKnot, iknot41+2)= 2.*dxm; | |
776 | matrix(offsKnot, iknot4 +2)=-2.*dxp; | |
777 | ||
778 | matrix(offsKnot, iknot41+3)= 3.*dxm2; | |
779 | matrix(offsKnot, iknot4 +3)=-3.*dxp2; | |
780 | ||
781 | matrix(iknot41+1, offsKnot)=1; | |
782 | matrix(iknot41+2, offsKnot)=2.*dxm; | |
783 | matrix(iknot41+3, offsKnot)=3.*dxm2; | |
784 | ||
785 | matrix(iknot4+1, offsKnot)=-1.; | |
786 | matrix(iknot4+2, offsKnot)=-2.*dxp; | |
787 | matrix(iknot4+3, offsKnot)=-3.*dxp2; | |
788 | } | |
789 | // | |
790 | // constraint 2 | |
791 | // | |
792 | offset =4*(nknots-1)-1+2*(nknots-2); | |
793 | if (nder>=2) for (Int_t iknot = 1; iknot<nknots-1; iknot++){ | |
794 | ||
795 | Double_t dxm = (fX[iknot]-fX[iknot-1])*0.5; | |
796 | Double_t dxp = -(fX[iknot+1]-fX[iknot])*0.5; | |
797 | Int_t iknot4 = 4*iknot; | |
798 | Int_t iknot41 = 4*(iknot-1); | |
799 | Int_t offsKnot = offset+iknot; | |
800 | // | |
801 | // condition on knot second derivative | |
802 | // | |
803 | // a0dd[i] = 2*a2m[i-1] + 6*a3m[i-1]*dxm | |
804 | // a0dd[i] = 2*a2m[i-0] + 6*a3m[i-0]*dxp | |
805 | // | |
806 | // | |
807 | matrix(offsKnot, iknot41+2)= 2.; | |
808 | matrix(offsKnot, iknot4 +2)=-2.; | |
809 | ||
810 | matrix(offsKnot, iknot41+3)= 6.*dxm; | |
811 | matrix(offsKnot, iknot4 +3)=-6.*dxp; | |
812 | ||
813 | matrix(iknot41+2, offsKnot)=2.; | |
814 | matrix(iknot41+3, offsKnot)=6.*dxm; | |
815 | ||
816 | matrix(iknot4+2, offsKnot)=-2.; | |
817 | matrix(iknot4+3, offsKnot)=-6.*dxp; | |
818 | } | |
819 | ||
820 | // sparse matrix to do fit | |
821 | ||
822 | TMatrixDSparse smatrix(matrix); | |
823 | TDecompSparse svd(smatrix,0); | |
824 | Bool_t ok; | |
825 | const TVectorD results = svd.Solve(values,ok); | |
826 | ||
827 | for (Int_t iknot = 0; iknot<nknots-1; iknot++){ | |
828 | ||
829 | Double_t dxm = -(fX[iknot+1]-fX[iknot])*0.5; | |
830 | ||
831 | fY0[iknot] = results(4*iknot)+ results(4*iknot+1)*dxm+results(4*iknot+2)*dxm*dxm+ | |
832 | results(4*iknot+3)*dxm*dxm*dxm; | |
833 | ||
834 | fY1[iknot] = results(4*iknot+1)+2.*results(4*iknot+2)*dxm+ | |
835 | 3*results(4*iknot+3)*dxm*dxm; | |
836 | } | |
837 | Int_t iknot2= nknots-1; | |
838 | Int_t iknot = nknots-2; | |
839 | Double_t dxm = (fX[iknot2]-fX[iknot2-1])*0.5; | |
840 | ||
841 | fY0[iknot2] = results(4*iknot)+ results(4*iknot+1)*dxm+results(4*iknot+2)*dxm*dxm+ | |
842 | results(4*iknot+3)*dxm*dxm*dxm; | |
843 | ||
844 | fY1[iknot2] = results(4*iknot+1)+2.*results(4*iknot+2)*dxm+ | |
845 | 3*results(4*iknot+3)*dxm*dxm; | |
846 | ||
847 | delete pmatrix; | |
848 | delete pvalues; | |
849 | ||
850 | } | |
851 | ||
852 | ||
853 | ||
854 | ||
855 | ||
856 | void AliSplineFit::MakeKnots0(TGraph * graph, Double_t maxdelta, Int_t minpoints){ | |
857 | // | |
858 | // make knots - restriction max distance and minimum points | |
859 | // | |
860 | ||
861 | Int_t npoints = graph->GetN(); | |
862 | Double_t *xknots = new Double_t[npoints]; | |
863 | Int_t nknots =0; | |
864 | Int_t ipoints =0; | |
865 | // | |
866 | // generate knots | |
867 | // | |
868 | for (Int_t ip=0;ip<npoints;ip++){ | |
869 | if (graph->GetX()[ip]-xknots[nknots-1]>maxdelta && ipoints>minpoints){ | |
870 | xknots[nknots] = graph->GetX()[ip]; | |
871 | ipoints=1; | |
872 | nknots++; | |
873 | } | |
874 | ipoints++; | |
875 | } | |
876 | if (npoints-ipoints>minpoints){ | |
877 | xknots[nknots] = graph->GetX()[npoints-1]; | |
878 | nknots++; | |
879 | }else{ | |
880 | xknots[nknots-1] = graph->GetX()[npoints-1]; | |
881 | } | |
882 | ||
883 | fN = nknots; | |
884 | fX = new Double_t[nknots]; | |
885 | fY0 = new Double_t[nknots]; | |
886 | fY1 = new Double_t[nknots]; | |
887 | fChi2I= new Double_t[nknots]; | |
888 | for (Int_t i=0; i<nknots; i++) fX[i]= xknots[i]; | |
889 | delete [] xknots; | |
890 | } | |
891 | ||
892 | ||
893 | ||
894 | ||
a6e0ebfe | 895 | void AliSplineFit::MakeSmooth(TGraph * graph, Float_t ratio, Option_t * type){ |
0dd3a2ac | 896 | // |
897 | // Interface to GraphSmooth | |
898 | // | |
899 | ||
900 | TGraphSmooth smooth; | |
901 | Int_t npoints2 = TMath::Nint(graph->GetN()*ratio); | |
902 | TGraph * graphT0 = smooth.SmoothKern(graph,type,ratio); | |
903 | if (!graphT0) return; | |
904 | TGraph graphT1(npoints2); | |
905 | for (Int_t ipoint=0; ipoint<npoints2; ipoint++){ | |
906 | Int_t pointS = TMath::Nint(ipoint/ratio); | |
907 | if (ipoint==npoints2-1) pointS=graph->GetN()-1; | |
908 | graphT1.SetPoint(ipoint, graphT0->GetX()[pointS] , graphT0->GetY()[pointS]); | |
909 | } | |
910 | TSpline3 spline2("spline", &graphT1); | |
911 | Update(&spline2, npoints2); | |
912 | } | |
913 | ||
914 | ||
915 | void AliSplineFit::Update(TSpline3 *spline, Int_t nknots){ | |
916 | // | |
917 | // | |
918 | // | |
919 | ||
920 | fN = nknots; | |
921 | fX = new Double_t[nknots]; | |
922 | fY0 = new Double_t[nknots]; | |
923 | fY1 = new Double_t[nknots]; | |
924 | Double_t d0, d1; | |
925 | fChi2I= 0; | |
926 | for (Int_t i=0; i<nknots; i++) { | |
927 | spline->GetCoeff(i,fX[i],fY0[i], fY1[i],d0,d1); | |
928 | } | |
929 | } | |
930 | ||
931 | ||
932 | ||
933 | ||
934 | void AliSplineFit::Test(Int_t npoints, Int_t ntracks, Float_t snoise){ | |
935 | // | |
936 | // test function | |
937 | // | |
938 | ||
939 | AliSplineFit fit; | |
940 | AliSplineFit fitS; | |
941 | TGraph * graph0=0; | |
942 | TGraph * graph1=0; | |
943 | ||
944 | TTreeSRedirector *pcstream = new TTreeSRedirector("TestSmooth.root"); | |
945 | for (Int_t i=0; i<ntracks; i++){ | |
946 | graph0 = AliSplineFit::GenerGraph(npoints,0.05,0,0,1,0); | |
947 | graph1 = AliSplineFit::GenerNoise(graph0,snoise); | |
948 | fit.InitKnots(graph1, 10,10, 0.00); | |
949 | TGraph *d0 = fit.MakeDiff(graph0); | |
950 | TGraph *g0 = fit.MakeGraph(0,1,1000,0); | |
951 | fit.SplineFit(2); | |
952 | TH1F * h2 = fit.MakeDiffHisto(graph0); | |
953 | TGraph *d2 = fit.MakeDiff(graph0); | |
954 | TGraph *g2 = fit.MakeGraph(0,1,1000,0); | |
955 | fit.SplineFit(1); | |
956 | TH1F * h1 = fit.MakeDiffHisto(graph0); | |
957 | TGraph *d1 = fit.MakeDiff(graph0); | |
958 | TGraph *g1 = fit.MakeGraph(0,1,1000,0); | |
959 | ||
960 | Float_t ratio = Float_t(fit.fN)/Float_t(npoints); | |
961 | fitS.MakeSmooth(graph1,ratio,"box"); | |
962 | TGraph *dS = fitS.MakeDiff(graph0); | |
963 | TGraph *gS = fit.MakeGraph(0,1,1000,0); | |
964 | ||
965 | TH1F * hS = fitS.MakeDiffHisto(graph0); | |
966 | Double_t mean2 = h2->GetMean(); | |
967 | Double_t sigma2 = h2->GetRMS(); | |
968 | Double_t mean1 = h1->GetMean(); | |
969 | Double_t sigma1 = h1->GetRMS(); | |
970 | Double_t meanS = hS->GetMean(); | |
971 | Double_t sigmaS = hS->GetRMS(); | |
972 | char fname[100]; | |
973 | if (fit.fN<20){ | |
974 | sprintf(fname,"pol%d",fit.fN); | |
975 | }else{ | |
976 | sprintf(fname,"pol%d",19); | |
977 | } | |
978 | TF1 fpol("fpol",fname); | |
979 | graph1->Fit(&fpol); | |
980 | TGraph dpol(*graph1); | |
981 | TGraph gpol(*graph1); | |
982 | for (Int_t ipoint=0; ipoint<graph1->GetN(); ipoint++){ | |
983 | dpol.GetY()[ipoint]= graph0->GetY()[ipoint]- | |
984 | fpol.Eval(graph0->GetX()[ipoint]); | |
985 | gpol.GetY()[ipoint]= fpol.Eval(graph0->GetX()[ipoint]); | |
986 | } | |
987 | (*pcstream)<<"Test"<< | |
988 | "Event="<<i<< | |
989 | "Graph0.="<<graph0<< | |
990 | "Graph1.="<<graph1<< | |
991 | "G0.="<<g0<< | |
992 | "G1.="<<g1<< | |
993 | "G2.="<<g2<< | |
994 | "GS.="<<gS<< | |
995 | "GP.="<<&gpol<< | |
996 | "D0.="<<d0<< | |
997 | "D1.="<<d1<< | |
998 | "D2.="<<d2<< | |
999 | "DS.="<<dS<< | |
1000 | "DP.="<<&dpol<< | |
1001 | "Npoints="<<fit.fN<< | |
1002 | "Mean1="<<mean1<< | |
1003 | "Mean2="<<mean2<< | |
1004 | "MeanS="<<meanS<< | |
1005 | "Sigma1="<<sigma1<< | |
1006 | "Sigma2="<<sigma2<< | |
1007 | "SigmaS="<<sigmaS<< | |
1008 | "\n"; | |
1009 | ||
1010 | delete graph0; | |
1011 | delete graph1; | |
1012 | delete g1; | |
1013 | delete g2; | |
1014 | delete gS; | |
1015 | delete h1; | |
1016 | delete h2; | |
1017 | delete hS; | |
1018 | } | |
52fdcd41 | 1019 | delete pcstream; |
0dd3a2ac | 1020 | } |
8625679a | 1021 | |
1022 | void AliSplineFit::Cleanup(){ | |
1023 | // | |
1024 | // deletes extra information to reduce amount of information stored on the data | |
1025 | // base | |
1026 | ||
6ec4e3e3 | 1027 | // delete fGraph; fGraph=0; // Don't delete fGraph -- input parameter |
8625679a | 1028 | delete fParams; fParams=0; |
1029 | delete fCovars; fCovars=0; | |
1030 | delete [] fIndex; fIndex=0; | |
1031 | delete [] fChi2I; fChi2I=0; | |
1032 | } | |
52fdcd41 | 1033 | |
1034 | ||
1035 | void AliSplineFit::CopyGraph() { | |
1036 | // | |
1037 | // enter graph points directly to fit parameters | |
1038 | // (to bee used when too few points are available) | |
1039 | // | |
6ec4e3e3 | 1040 | fN = fGraph->GetN(); |
52fdcd41 | 1041 | fX = new Double_t[fN]; |
1042 | fY0 = new Double_t[fN]; | |
1043 | fY1 = new Double_t[fN]; | |
1044 | for (Int_t i=0; i<fN; i++ ) { | |
1045 | fX[i] = fGraph->GetX()[i]; | |
6ec4e3e3 | 1046 | fY0[i] = fGraph->GetY()[i]; |
52fdcd41 | 1047 | fY1[i] = 0; |
1048 | } | |
1049 | } |