1 /***************************************************************************
2 * Copyright(c) 1998-1999, ALICE Experiment at CERN, All rights reserved. *
4 * Author: The ALICE Off-line Project. *
5 * Contributors are mentioned in the code where appropriate. *
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 **************************************************************************/
18 //-----------------------------------------------------//
20 // Source File : PMDClusteringV1.cxx, Version 00 //
22 // Date : September 26 2002 //
24 // clustering code for alice pmd //
26 //-----------------------------------------------------//
28 /* --------------------------------------------------------------------
29 Code developed by S. C. Phatak, Institute of Physics,
30 Bhubaneswar 751 005 ( phatak@iopb.res.in ) Given the energy deposited
31 ( or ADC value ) in each cell of supermodule ( pmd or cpv ), the code
32 builds up superclusters and breaks them into clusters. The input is
33 in array edepcell[kNMX] and cluster information is in a
34 TObjarray. Integer clno gives total number of clusters in the
37 fClusters is the only global ( public ) variables.
38 Others are local ( private ) to the code.
39 At the moment, the data is read for whole detector ( all supermodules
40 and pmd as well as cpv. This will have to be modify later )
41 LAST UPDATE : October 23, 2002
42 -----------------------------------------------------------------------*/
44 #include <Riostream.h>
47 #include <TObjArray.h>
51 #include "AliPMDcludata.h"
52 #include "AliPMDcluster.h"
53 #include "AliPMDClustering.h"
54 #include "AliPMDClusteringV1.h"
57 ClassImp(AliPMDClusteringV1)
59 const Double_t AliPMDClusteringV1::fgkSqroot3by2=0.8660254; // sqrt(3.)/2.
61 AliPMDClusteringV1::AliPMDClusteringV1():
62 fPMDclucont(new TObjArray()),
65 for(Int_t i = 0; i < kNDIMX; i++)
67 for(Int_t j = 0; j < kNDIMY; j++)
69 fCoord[0][i][j] = i+j/2.;
70 fCoord[1][i][j] = fgkSqroot3by2*j;
74 // ------------------------------------------------------------------------ //
75 AliPMDClusteringV1::AliPMDClusteringV1(const AliPMDClusteringV1& pmdclv1):
76 AliPMDClustering(pmdclv1),
81 AliError("Copy constructor not allowed ");
84 // ------------------------------------------------------------------------ //
85 AliPMDClusteringV1 &AliPMDClusteringV1::operator=(const AliPMDClusteringV1& /*pmdclv1*/)
88 AliError("Assignment operator not allowed ");
91 // ------------------------------------------------------------------------ //
92 AliPMDClusteringV1::~AliPMDClusteringV1()
96 // ------------------------------------------------------------------------ //
97 void AliPMDClusteringV1::DoClust(Int_t idet, Int_t ismn,
98 Double_t celladc[48][96], TObjArray *pmdcont)
100 // main function to call other necessary functions to do clustering
103 AliPMDcluster *pmdcl = 0;
105 Int_t i, j, nmx1, incr, id, jd;
106 Int_t celldataX[15], celldataY[15];
108 Double_t cutoff, ave;
109 Double_t edepcell[kNMX];
111 const float ktwobysqrt3 = 1.1547; // 2./sqrt(3.)
113 // ndimXr and ndimYr are different because of different module size
123 else if (ismn >= 12 && ismn <= 23)
130 for (Int_t i = 0; i < kNDIMX; i++)
132 for (Int_t j = 0; j < kNDIMY; j++)
134 fCellTrNo[i][j] = -1;
140 for (id = 0; id < ndimXr; id++)
142 for (jd = 0; jd < ndimYr; jd++)
145 i = id+(ndimYr/2-1)-(jd/2);
147 Int_t ij = i + j*kNDIMX;
151 edepcell[ij] = celladc[jd][id];
152 fCellTrNo[i][j] = jd*10000+id; // for association
154 else if (ismn >= 12 && ismn <= 23)
156 edepcell[ij] = celladc[id][jd];
157 fCellTrNo[i][j] = id*10000+jd; // for association
164 TMath::Sort(kNMX,edepcell,iord1);// order the data
165 cutoff = fCutoff; // cutoff to discard cells
168 for(i = 0;i < kNMX; i++)
174 if(edepcell[i] > cutoff )
180 AliDebug(1,Form("Number of cells having energy >= %f are %d",cutoff,nmx1));
182 if (nmx1 == 0) nmx1 = 1;
185 AliDebug(1,Form("Number of cells in a SuperM = %d and Average = %f",
188 incr = CrClust(ave, cutoff, nmx1,iord1, edepcell );
189 RefClust(incr,edepcell);
190 Int_t nentries1 = fPMDclucont->GetEntries();
191 AliDebug(1,Form("Detector Plane = %d Serial Module No = %d Number of clusters = %d",idet, ismn, nentries1));
192 AliDebug(1,Form("Total number of clusters/module = %d",nentries1));
194 for (Int_t ient1 = 0; ient1 < nentries1; ient1++)
196 AliPMDcludata *pmdcludata =
197 (AliPMDcludata*)fPMDclucont->UncheckedAt(ient1);
198 Float_t cluXC = pmdcludata->GetClusX();
199 Float_t cluYC = pmdcludata->GetClusY();
200 Float_t cluADC = pmdcludata->GetClusADC();
201 Float_t cluCELLS = pmdcludata->GetClusCells();
202 Float_t cluSIGX = pmdcludata->GetClusSigmaX();
203 Float_t cluSIGY = pmdcludata->GetClusSigmaY();
205 Float_t cluY0 = ktwobysqrt3*cluYC;
206 Float_t cluX0 = cluXC - cluY0/2.;
209 // Cluster X centroid is back transformed
213 clusdata[0] = cluX0 - (24-1) + cluY0/2.;
215 else if ( ismn >= 12 && ismn <= 23)
217 clusdata[0] = cluX0 - (48-1) + cluY0/2.;
221 clusdata[2] = cluADC;
222 clusdata[3] = cluCELLS;
223 clusdata[4] = cluSIGX;
224 clusdata[5] = cluSIGY;
227 // Cells associated with a cluster
230 for (Int_t ihit = 0; ihit < 15; ihit++)
234 celldataX[ihit] = pmdcludata->GetCellXY(ihit)%10000;
235 celldataY[ihit] = pmdcludata->GetCellXY(ihit)/10000;
237 else if (ismn >= 12 && ismn <= 23)
239 celldataX[ihit] = pmdcludata->GetCellXY(ihit)/10000;
240 celldataY[ihit] = pmdcludata->GetCellXY(ihit)%10000;
243 pmdcl = new AliPMDcluster(idet, ismn, clusdata, celldataX, celldataY);
247 fPMDclucont->Clear();
250 // ------------------------------------------------------------------------ //
251 Int_t AliPMDClusteringV1::CrClust(Double_t ave, Double_t cutoff, Int_t nmx1,
252 Int_t iord1[], Double_t edepcell[])
254 // Does crude clustering
255 // Finds out only the big patch by just searching the
258 Int_t i,j,k,id1,id2,icl, numcell, clust[2][5000];
259 Int_t jd1,jd2, icell, cellcount;
260 static Int_t neibx[6]={1,0,-1,-1,0,1}, neiby[6]={0,1,1,0,-1,-1};
262 AliDebug(1,Form("kNMX = %d nmx1 = %d kNDIMX = %d kNDIMY = %d ave = %f cutoff = %f",kNMX,nmx1,kNDIMX,kNDIMY,ave,cutoff));
264 for (j = 0; j < kNDIMX; j++)
266 for(k = 0; k < kNDIMY; k++)
268 fInfocl[0][j][k] = 0;
269 fInfocl[1][j][k] = 0;
272 for(i=0; i < kNMX; i++)
280 if(edepcell[j] <= cutoff)
282 fInfocl[0][id1][id2] = -1;
286 // ---------------------------------------------------------------
287 // crude clustering begins. Start with cell having largest adc
288 // count and loop over the cells in descending order of adc count
289 // ---------------------------------------------------------------
294 for(icell = 0; icell <= nmx1; icell++)
300 if(fInfocl[0][id1][id2] == 0 )
305 fInfocl[0][id1][id2] = 1;
306 fInfocl[1][id1][id2] = icl;
307 fInfcl[0][cellcount] = icl;
308 fInfcl[1][cellcount] = id1;
309 fInfcl[2][cellcount] = id2;
311 clust[0][numcell] = id1;
312 clust[1][numcell] = id2;
314 for(i = 1; i < 5000; i++)
318 // ---------------------------------------------------------------
319 // check for adc count in neib. cells. If ne 0 put it in this clust
320 // ---------------------------------------------------------------
321 for(i = 0; i < 6; i++)
323 jd1 = id1 + neibx[i];
324 jd2 = id2 + neiby[i];
325 if( (jd1 >= 0 && jd1 < kNDIMX) && (jd2 >= 0 && jd2 < kNDIMY) &&
326 fInfocl[0][jd1][jd2] == 0)
329 fInfocl[0][jd1][jd2] = 2;
330 fInfocl[1][jd1][jd2] = icl;
331 clust[0][numcell] = jd1;
332 clust[1][numcell] = jd2;
334 fInfcl[0][cellcount] = icl;
335 fInfcl[1][cellcount] = jd1;
336 fInfcl[2][cellcount] = jd2;
339 // ---------------------------------------------------------------
340 // check adc count for neighbour's neighbours recursively and
341 // if nonzero, add these to the cluster.
342 // ---------------------------------------------------------------
343 for(i = 1; i < 5000;i++)
349 for(j = 0; j < 6 ; j++)
351 jd1 = id1 + neibx[j];
352 jd2 = id2 + neiby[j];
353 if( (jd1 >= 0 && jd1 < kNDIMX) &&
354 (jd2 >= 0 && jd2 < kNDIMY) &&
355 fInfocl[0][jd1][jd2] == 0 )
357 fInfocl[0][jd1][jd2] = 2;
358 fInfocl[1][jd1][jd2] = icl;
360 clust[0][numcell] = jd1;
361 clust[1][numcell] = jd2;
363 fInfcl[0][cellcount] = icl;
364 fInfcl[1][cellcount] = jd1;
365 fInfcl[2][cellcount] = jd2;
374 // ------------------------------------------------------------------------ //
375 void AliPMDClusteringV1::RefClust(Int_t incr, Double_t edepcell[])
377 // Does the refining of clusters
378 // Takes the big patch and does gaussian fitting and
379 // finds out the more refined clusters
384 AliPMDcludata *pmdcludata = 0;
388 const Int_t kdim = 4500;
390 Int_t i, j, k, i1, i2, id, icl, itest,ihld, ig, nsupcl,clno;
392 Int_t ncl[kdim], iord[kdim], lev1[20], lev2[20];
395 Double_t x1, y1, z1, x2, y2, z2, dist,rr,sum;
396 Double_t x[kdim], y[kdim], z[kdim];
397 Double_t xc[kdim], yc[kdim], zc[kdim], cells[kdim], rc[kdim];
400 for(i = 0; i<kdim; i++)
404 if (i < 6) clusdata[i] = 0.;
405 if (i < 15) clxy[i] = 0;
408 // clno counts the final clusters
409 // nsupcl = # of superclusters; ncl[i]= # of cells in supercluster i
410 // x, y and z store (x,y) coordinates of and energy deposited in a cell
411 // xc, yc store (x,y) coordinates of the cluster center
412 // zc stores the energy deposited in a cluster
413 // rc is cluster radius
418 for(i = 0; i <= incr; i++)
420 if(fInfcl[0][i] != nsupcl)
426 AliWarning("RefClust: Too many superclusters!");
433 AliDebug(1,Form("Number of cells = %d Number of Superclusters = %d",
438 for(i = 0; i <= nsupcl; i++)
446 AliWarning("RefClust: Too many clusters! more than 5000");
453 Int_t i12 = i1 + i2*kNDIMX;
455 clusdata[0] = fCoord[0][i1][i2];
456 clusdata[1] = fCoord[1][i1][i2];
457 clusdata[2] = edepcell[i12];
462 clxy[0] = fCellTrNo[i1][i2]; //association
463 for(Int_t icltr = 1; icltr < 15; icltr++)
467 pmdcludata = new AliPMDcludata(clusdata,clxy);
468 fPMDclucont->Add(pmdcludata);
476 AliWarning("RefClust: Too many clusters! more than 5000");
482 Int_t i12 = i1 + i2*kNDIMX;
484 x1 = fCoord[0][i1][i2];
485 y1 = fCoord[1][i1][i2];
487 clxy[0] = fCellTrNo[i1][i2]; //asso
492 Int_t i22 = i1 + i2*kNDIMX;
493 x2 = fCoord[0][i1][i2];
494 y2 = fCoord[1][i1][i2];
496 clxy[1] = fCellTrNo[i1][i2]; //asso
497 for(Int_t icltr = 2; icltr < 15; icltr++)
502 clusdata[0] = (x1*z1+x2*z2)/(z1+z2);
503 clusdata[1] = (y1*z1+y2*z2)/(z1+z2);
508 pmdcludata = new AliPMDcludata(clusdata,clxy);
509 fPMDclucont->Add(pmdcludata);
515 // super-cluster of more than two cells - broken up into smaller
516 // clusters gaussian centers computed. (peaks separated by > 1 cell)
517 // Begin from cell having largest energy deposited This is first
521 Int_t i12 = i1 + i2*kNDIMX;
523 x[0] = fCoord[0][i1][i2];
524 y[0] = fCoord[1][i1][i2];
525 z[0] = edepcell[i12];
527 t[0] = fCellTrNo[i1][i2]; //asso
530 for(j = 1; j <= ncl[i]; j++)
535 Int_t i12 = i1 + i2*kNDIMX;
538 x[j] = fCoord[0][i1][i2];
539 y[j] = fCoord[1][i1][i2];
540 z[j] = edepcell[i12];
542 t[j] = fCellTrNo[i1][i2]; //asso
545 // arranging cells within supercluster in decreasing order
547 for(j = 1;j <= ncl[i]; j++)
551 for(i1 = 0; i1 < j; i1++)
553 if(itest == 0 && z[iord[i1]] < z[ihld])
556 for(i2 = j-1; i2 >= i1; i2--)
558 iord[i2+1] = iord[i2];
564 // compute the number of Gaussians and their centers ( first
566 // centers must be separated by cells having smaller ener. dep.
567 // neighbouring centers should be either strong or well-separated
572 for(j = 1; j <= ncl[i]; j++)
577 for(k = 0; k <= ig; k++)
581 rr = Distance(x1,y1,x2,y2);
582 if(rr >= 1.1 && rr < 1.8 && z[iord[j]] > zc[k]/4.)itest++;
583 if(rr >= 1.8 && rr < 2.1 && z[iord[j]] > zc[k]/10.)itest++;
584 if( rr >= 2.1)itest++;
594 GaussFit(ncl[i], ig, x[0], y[0] ,z[0], xc[0], yc[0], zc[0], rc[0]);
596 // compute the number of cells belonging to each cluster.
597 // cell is shared between several clusters ( if they are equidistant
598 // from it ) in the ratio of cluster energy deposition
601 cellCount = new Int_t [ig+1];
602 cellXY = new Int_t *[jj];
603 for(Int_t ij = 0; ij < 15; ij++) cellXY[ij] = new Int_t [ig+1];
605 for(j = 0; j <= ig; j++)
613 for(j = 0; j <= ncl[i]; j++)
617 for(k = 0; k <= ig; k++)
619 dist = Distance(x[j], y[j], xc[k], yc[k]);
620 if(dist < TMath::Sqrt(3.) )
623 if (cellCount[k] < 15)
625 cellXY[cellCount[k]][k] = t[j];
652 for(k = 1; k <= lev1[0]; k++)
656 for(k = 1; k <= lev1[0]; k++)
658 cells[lev1[k]] += zc[lev1[k]]/sum;
671 for( k = 1; k <= lev2[0]; k++)
675 for(k = 1; k <= lev2[0]; k++)
677 cells[lev2[k]] += zc[lev2[k]]/sum;
684 // zero rest of the cell array
686 for( k = 0; k <= ig; k++)
688 for(Int_t icltr = cellCount[k]; icltr < 15; icltr++)
690 cellXY[icltr][k] = -1;
695 for(j = 0; j <= ig; j++)
700 AliWarning("RefClust: Too many clusters! more than 5000");
710 clusdata[3] = ncl[i];
714 clusdata[3] = cells[j];
718 for (Int_t ii=0; ii < 15; ii++)
720 clxy[ii] = cellXY[ii][j];
722 pmdcludata = new AliPMDcludata(clusdata,clxy);
723 fPMDclucont->Add(pmdcludata);
726 for(Int_t jj = 0; jj < 15; jj++)delete [] cellXY[jj];
731 // ------------------------------------------------------------------------ //
732 void AliPMDClusteringV1::GaussFit(Int_t ncell, Int_t nclust, Double_t &x,
733 Double_t &y ,Double_t &z, Double_t &xc,
734 Double_t &yc, Double_t &zc, Double_t &rc)
736 // Does gaussian fitting
739 const Int_t kdim = 4500;
740 Int_t i, j, i1, i2, novar, idd, jj;
741 Int_t neib[kdim][50];
743 Double_t sum, dx, dy, str, str1, aint, sum1, rr, dum;
744 Double_t x1, x2, y1, y2;
745 Double_t xx[kdim], yy[kdim], zz[kdim], xxc[kdim], yyc[kdim];
746 Double_t a[kdim], b[kdim], c[kdim], d[kdim], ha[kdim], hb[kdim];
747 Double_t hc[kdim], hd[kdim], zzc[kdim], rrc[kdim];
757 for(i = 0; i <= ncell; i++)
764 for(i=0; i<=nclust; i++)
772 for(i = 0; i <= nclust; i++)
774 zzc[i] = str/str1*zzc[i];
783 for(i = 0; i <= ncell; i++)
788 for(j = 0; j <= nclust; j++)
792 if(Distance(x1,y1,x2,y2) <= 3.)
801 for(i1 = 0; i1 <= ncell; i1++)
805 for(i2 = 1; i2 <= idd; i2++)
808 dx = xx[i1] - xxc[jj];
809 dy = yy[i1] - yyc[jj];
810 dum = rrc[j]*rrc[jj] + rr*rr;
811 aint += exp(-(dx*dx+dy*dy)/dum)*zzc[idd]*rr*rr/dum;
813 sum += (aint - zz[i1])*(aint - zz[i1])/str;
817 for(i = 0; i <= nclust; i++)
819 a[i] = xxc[i] + 0.6*(rnd.Uniform() - 0.5);
820 b[i] = yyc[i] + 0.6*(rnd.Uniform() - 0.5);
821 c[i] = zzc[i]*(1.+ ( rnd.Uniform() - 0.5)*0.2);
823 d[i] = rrc[i]*(1.+ ( rnd.Uniform() - 0.5)*0.1);
830 for(i = 0; i <= nclust; i++)
832 c[i] = c[i]*str/str1;
836 for(i1 = 0; i1 <= ncell; i1++)
840 for(i2 = 1; i2 <= idd; i2++)
845 dum = d[jj]*d[jj]+rr*rr;
846 aint += exp(-(dx*dx+dy*dy)/dum)*c[i2]*rr*rr/dum;
848 sum1 += (aint - zz[i1])*(aint - zz[i1])/str;
853 for(i2 = 0; i2 <= nclust; i2++)
862 for(j = 0; j <= nclust; j++)
870 // ------------------------------------------------------------------------ //
871 Double_t AliPMDClusteringV1::Distance(Double_t x1, Double_t y1,
872 Double_t x2, Double_t y2)
874 return TMath::Sqrt((x1-x2)*(x1-x2) + (y1-y2)*(y1-y2));
876 // ------------------------------------------------------------------------ //
877 void AliPMDClusteringV1::SetEdepCut(Float_t decut)
881 // ------------------------------------------------------------------------ //