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3edbbba2 1/***************************************************************************
2 * Copyright(c) 1998-1999, 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
16//-----------------------------------------------------//
17// //
01c4d84a 18// Source File : PMDClusteringV1.cxx, Version 00 //
3edbbba2 19// //
20// Date : September 26 2002 //
21// //
22// clustering code for alice pmd //
23// //
24//-----------------------------------------------------//
25
26/* --------------------------------------------------------------------
27 Code developed by S. C. Phatak, Institute of Physics,
28 Bhubaneswar 751 005 ( phatak@iopb.res.in ) Given the energy deposited
29 ( or ADC value ) in each cell of supermodule ( pmd or cpv ), the code
30 builds up superclusters and breaks them into clusters. The input is
31 in array fEdepCell[kNDIMX][kNDIMY] and cluster information is in array
32 fClusters[5][5000]. integer fClno gives total number of clusters in the
33 supermodule.
34
35 fEdepCell, fClno and fClusters are the only global ( public ) variables.
36 Others are local ( private ) to the code.
37 At the moment, the data is read for whole detector ( all supermodules
38 and pmd as well as cpv. This will have to be modify later )
39 LAST UPDATE : October 23, 2002
40-----------------------------------------------------------------------*/
41
42#include "Riostream.h"
43#include <TNtuple.h>
44#include <TObjArray.h>
45#include <stdio.h>
46
47#include "AliPMDcluster.h"
48#include "AliPMDClustering.h"
49#include "AliPMDClusteringV1.h"
50#include "AliLog.h"
51
52ClassImp(AliPMDClusteringV1)
53
54const Double_t AliPMDClusteringV1::fgkSqroot3by2=0.8660254; // sqrt(3.)/2.
55
56AliPMDClusteringV1::AliPMDClusteringV1():
57 fCutoff(0.0)
58{
59 for(int i = 0; i < kNDIMX; i++)
60 {
61 for(int j = 0; j < kNDIMY; j++)
62 {
63 fCoord[0][i][j] = i+j/2.;
64 fCoord[1][i][j] = fgkSqroot3by2*j;
65 fEdepCell[i][j] = 0;
66 }
67 }
68}
69// ------------------------------------------------------------------------ //
70AliPMDClusteringV1::~AliPMDClusteringV1()
71{
72
73}
74// ------------------------------------------------------------------------ //
75void AliPMDClusteringV1::DoClust(Int_t idet, Int_t ismn, Double_t celladc[48][96], TObjArray *pmdcont)
76{
77 // main function to call other necessary functions to do clustering
78 //
79 AliPMDcluster *pmdcl = 0;
80 /*
81 int id and jd defined to read the input data.
82 It is assumed that for data we have 0 <= id <= 48
83 and 0 <= jd <=96
84 */
01c4d84a 85
3edbbba2 86 int i, i1, i2, j, nmx1, incr, id, jd;
87 Int_t celldataX[15], celldataY[15];
0709b99f 88 Float_t clusdata[6];
3edbbba2 89
90 Double_t cutoff, ave;
91
92 const float ktwobysqrt3 = 1.1547; // 2./sqrt(3.)
93
01c4d84a 94 // ndimXr and ndimYr are different because of different module size
95
96 Int_t ndimXr =0;
97 Int_t ndimYr =0;
98
99 if (ismn < 12)
100 {
101 ndimXr = 96;
102 ndimYr = 48;
103 }
104 else if (ismn >= 12 && ismn <= 23)
105 {
106 ndimXr = 48;
107 ndimYr = 96;
108 }
109
110 for (Int_t i =0; i < kNDIMX; i++)
3edbbba2 111 {
01c4d84a 112 for (Int_t j =0; j < kNDIMY; j++)
113 {
114 fEdepCell[i][j] = 0;
115 fCellTrNo[i][j] = -1;
116 }
117 }
118
119 for (id = 0; id < ndimXr; id++)
120 {
121 for (jd = 0; jd < ndimYr; jd++)
3edbbba2 122 {
123 j=jd;
01c4d84a 124 i=id+(ndimYr/2-1)-(jd/2);
125
126 if (ismn < 12)
127 {
128 fEdepCell[i][j] = celladc[jd][id];
129 fCellTrNo[i][j] = jd*10000+id; /* for association */
130 }
131 else if (ismn >= 12 && ismn <= 23)
132 {
133 fEdepCell[i][j] = celladc[id][jd];
134 fCellTrNo[i][j] = id*10000+jd; /* for association */
135 }
136
3edbbba2 137 }
138 }
139 Order(); // order the data
140 cutoff = fCutoff; // cutoff used to discard cells having ener. dep.
141 ave=0.;
142 nmx1=-1;
143
144 for(j=0;j<kNMX; j++)
145 {
146 i1 = fIord[0][j];
147 i2 = fIord[1][j];
148 if (fEdepCell[i1][i2] > 0.) {ave = ave + fEdepCell[i1][i2];}
149 if (fEdepCell[i1][i2] > cutoff ) nmx1 = nmx1 + 1;
150 }
3edbbba2 151
152 AliDebug(1,Form("Number of cells having energy >= %f are %d",cutoff,nmx1));
153
3edbbba2 154 if (nmx1 == 0) nmx1 = 1;
155 ave=ave/nmx1;
156
157 AliDebug(1,Form("Number of cells in a SuperM = %d and Average = %f",
158 kNMX,ave));
159
160 incr = CrClust(ave, cutoff, nmx1);
161 RefClust(incr);
162
163 AliDebug(1,Form("Detector Plane = %d Serial Module No = %d Number of clusters = %d",idet, ismn, fClno));
01c4d84a 164
3edbbba2 165
166 for(i1=0; i1<=fClno; i1++)
167 {
168 Float_t cluXC = (Float_t) fClusters[0][i1];
169 Float_t cluYC = (Float_t) fClusters[1][i1];
170 Float_t cluADC = (Float_t) fClusters[2][i1];
171 Float_t cluCELLS = (Float_t) fClusters[3][i1];
172 Float_t cluRAD = (Float_t) fClusters[4][i1];
173 Float_t cluY0 = ktwobysqrt3*cluYC;
174 Float_t cluX0 = cluXC - cluY0/2.;
01c4d84a 175
176
3edbbba2 177 //
178 // Cluster X centroid is back transformed
179 //
01c4d84a 180 if (ismn < 12)
181 {
182 clusdata[0] = cluX0 - (24-1) + cluY0/2.;
183 }
184 else if (ismn >= 12 && ismn <= 23)
185 {
186 clusdata[0] = cluX0 - (48-1) + cluY0/2.;
187 }
188
189 clusdata[1] = cluY0;
190 clusdata[2] = cluADC;
191 clusdata[3] = cluCELLS;
192 clusdata[4] = cluRAD;
193 clusdata[5] = 0.;
3edbbba2 194
195 //
196 // Cells associated with a cluster
197 //
198 for (Int_t ihit = 0; ihit < 15; ihit++)
199 {
01c4d84a 200
201 if (ismn < 12)
202 {
203 celldataX[ihit] = fClTr[ihit][i1]%10000;
204 celldataY[ihit] = fClTr[ihit][i1]/10000;
205 }
206 else if (ismn >= 12 && ismn <= 23)
207 {
208 celldataX[ihit] = fClTr[ihit][i1]/10000;
209 celldataY[ihit] = fClTr[ihit][i1]%10000;
210 }
3edbbba2 211 }
0709b99f 212 //printf("%d %f %f\n",idet,cluXC,cluYC );
3edbbba2 213 pmdcl = new AliPMDcluster(idet, ismn, clusdata, celldataX, celldataY);
214 pmdcont->Add(pmdcl);
215 }
216}
217// ------------------------------------------------------------------------ //
218void AliPMDClusteringV1::Order()
219{
220 // Sorting algorithm
221 // sorts the ADC values from higher to lower
222 //
223 double dd[kNMX];
224 // matrix fEdepCell converted into
225 // one dimensional array dd. adum a place holder for double
226 int i, j, i1, i2, iord1[kNMX];
227 // information of
228 // ordering is stored in iord1, original array not ordered
229 //
230 // define arrays dd and iord1
231 for(i1=0; i1 < kNDIMX; i1++)
232 {
233 for(i2=0; i2 < kNDIMY; i2++)
234 {
235 i = i1 + i2*kNDIMX;
236 iord1[i] = i;
237 dd[i] = fEdepCell[i1][i2];
238 }
239 }
240
241 TMath::Sort(kNMX,dd,iord1); //PH Using much better algorithm...
242 // store the sorted information in fIord for later use
243 for(i=0; i<kNMX; i++)
244 {
245 j = iord1[i];
246 i2 = j/kNDIMX;
247 i1 = j-i2*kNDIMX;
248 fIord[0][i]=i1;
249 fIord[1][i]=i2;
250 }
251}
252// ------------------------------------------------------------------------ //
253int AliPMDClusteringV1::CrClust(double ave, double cutoff, int nmx1)
254{
255 // Does crude clustering
256 // Finds out only the big patch by just searching the
257 // connected cells
258 //
259 int i,j,k,id1,id2,icl, numcell, clust[2][5000];
260 int jd1,jd2, icell, cellcount;
261 static int neibx[6]={1,0,-1,-1,0,1}, neiby[6]={0,1,1,0,-1,-1};
262 // neibx and neiby define ( incremental ) (i,j) for the neighbours of a
263 // cell. There are six neighbours.
264 // cellcount --- total number of cells having nonzero ener dep
265 // numcell --- number of cells in a given supercluster
266 // ofstream ofl0("cells_loc",ios::out);
267 // initialize fInfocl[2][kNDIMX][kNDIMY]
268
269 AliDebug(1,Form("kNMX = %d nmx1 = %d kNDIMX = %d kNDIMY = %d ave = %f cutoff = %f",kNMX,nmx1,kNDIMX,kNDIMY,ave,cutoff));
270
271 for (j=0; j < kNDIMX; j++){
272 for(k=0; k < kNDIMY; k++){
273 fInfocl[0][j][k] = 0;
274 fInfocl[1][j][k] = 0;
275 }
276 }
277 for(i=0; i < kNMX; i++){
278 fInfcl[0][i] = -1;
279 id1=fIord[0][i];
280 id2=fIord[1][i];
281 if(fEdepCell[id1][id2] <= cutoff){fInfocl[0][id1][id2]=-1;}
282 }
283 // ---------------------------------------------------------------
284 // crude clustering begins. Start with cell having largest adc
285 // count and loop over the cells in descending order of adc count
286 // ---------------------------------------------------------------
287 icl=-1;
288 cellcount=-1;
289 for(icell=0; icell <= nmx1; icell++){
290 id1=fIord[0][icell];
291 id2=fIord[1][icell];
292 if(fInfocl[0][id1][id2] == 0 ){
293 // ---------------------------------------------------------------
294 // icl -- cluster #, numcell -- # of cells in it, clust -- stores
295 // coordinates of the cells in a cluster, fInfocl[0][i1][i2] is 1 for
296 // primary and 2 for secondary cells,
297 // fInfocl[1][i1][i2] stores cluster #
298 // ---------------------------------------------------------------
299 icl=icl+1;
300 numcell=0;
301 cellcount = cellcount + 1;
302 fInfocl[0][id1][id2]=1;
303 fInfocl[1][id1][id2]=icl;
304 fInfcl[0][cellcount]=icl;
305 fInfcl[1][cellcount]=id1;
306 fInfcl[2][cellcount]=id2;
307
308 clust[0][numcell]=id1;
309 clust[1][numcell]=id2;
310 for(i=1; i<5000; i++)clust[0][i]=0;
311 // ---------------------------------------------------------------
312 // check for adc count in neib. cells. If ne 0 put it in this clust
313 // ---------------------------------------------------------------
314 for(i=0; i<6; i++){
315 jd1=id1+neibx[i];
316 jd2=id2+neiby[i];
317 if( (jd1 >= 0 && jd1 < kNDIMX) && (jd2 >= 0 && jd2 < kNDIMY) &&
318 fInfocl[0][jd1][jd2] == 0){
319 numcell=numcell+1;
320 fInfocl[0][jd1][jd2]=2;
321 fInfocl[1][jd1][jd2]=icl;
322 clust[0][numcell]=jd1;
323 clust[1][numcell]=jd2;
324 cellcount=cellcount+1;
325 fInfcl[0][cellcount]=icl;
326 fInfcl[1][cellcount]=jd1;
327 fInfcl[2][cellcount]=jd2;
328 }
329 }
330 // ---------------------------------------------------------------
331 // check adc count for neighbour's neighbours recursively and
332 // if nonzero, add these to the cluster.
333 // ---------------------------------------------------------------
334 for(i=1;i < 5000;i++){
335 if(clust[0][i] != 0){
336 id1=clust[0][i];
337 id2=clust[1][i];
338 for(j=0; j<6 ; j++){
339 jd1=id1+neibx[j];
340 jd2=id2+neiby[j];
341 if( (jd1 >= 0 && jd1 < kNDIMX) && (jd2 >= 0 && jd2 < kNDIMY) &&
342 fInfocl[0][jd1][jd2] == 0 ){
343 fInfocl[0][jd1][jd2] = 2;
344 fInfocl[1][jd1][jd2] = icl;
345 numcell = numcell + 1;
346 clust[0][numcell] = jd1;
347 clust[1][numcell] = jd2;
348 cellcount = cellcount+1;
349 fInfcl[0][cellcount] = icl;
350 fInfcl[1][cellcount] = jd1;
351 fInfcl[2][cellcount] = jd2;
352 }
353 }
354 }
355 }
356 }
357 }
0709b99f 358
3edbbba2 359 // for(icell=0; icell<=cellcount; icell++){
360 // ofl0 << fInfcl[0][icell] << " " << fInfcl[1][icell] << " " <<
361 // fInfcl[2][icell] << endl;
0709b99f 362 //}
363
3edbbba2 364 return cellcount;
365}
366// ------------------------------------------------------------------------ //
367void AliPMDClusteringV1::RefClust(int incr)
368{
369 // Does the refining of clusters
370 // Takes the big patch and does gaussian fitting and
371 // finds out the more refined clusters
372 //
373 int i, j, k, i1, i2, id, icl, ncl[4500], iord[4500], itest;
374 int ihld;
375 int ig, nsupcl, lev1[20], lev2[20];
376 double x[4500], y[4500], z[4500], x1, y1, z1, x2, y2, z2, dist;
377 double xc[4500], yc[4500], zc[4500], cells[4500], sum, rc[4500], rr;
0709b99f 378
379
01c4d84a 380 //asso
381 Int_t t[4500],cellCount[4500];
382 for(i=0; i<4500; i++)
383 {
384 t[i]=-1;
385 cellCount[i]=0;
386 }
0709b99f 387
388
3edbbba2 389 // fClno counts the final clusters
390 // nsupcl = # of superclusters; ncl[i]= # of cells in supercluster i
391 // x, y and z store (x,y) coordinates of and energy deposited in a cell
392 // xc, yc store (x,y) coordinates of the cluster center
393 // zc stores the energy deposited in a cluster
394 // rc is cluster radius
395 // finally the cluster information is put in 2-dimensional array clusters
0709b99f 396 //ofstream ofl1("checking.5",ios::app);
3edbbba2 397 fClno = -1;
398 nsupcl = -1;
399 for(i=0; i<4500; i++){ncl[i]=-1;}
0709b99f 400 for(i=0; i<= incr; i++){
3edbbba2 401 if(fInfcl[0][i] != nsupcl){ nsupcl=nsupcl+1; }
402 if (nsupcl > 4500) {
403 AliWarning("RefClust: Too many superclusters!");
404 nsupcl = 4500;
405 break;
406 }
0709b99f 407
3edbbba2 408 ncl[nsupcl]=ncl[nsupcl]+1;
409 }
410
411 AliDebug(1,Form("Number of cells = %d Number of Superclusters = %d",
412 incr+1,nsupcl+1));
3edbbba2 413 id=-1;
414 icl=-1;
0709b99f 415 for(i=0; i<=nsupcl; i++) {
3edbbba2 416 if(ncl[i] == 0){
417 id=id+1;
418 icl=icl+1;
419 // one cell super-clusters --> single cluster
420 // cluster center at the centyer of the cell
421 // cluster radius = half cell dimension
422 if (fClno >= 5000) {
423 AliWarning("RefClust: Too many clusters! more than 5000");
424 return;
425 }
426 fClno = fClno + 1;
427 i1 = fInfcl[1][id];
428 i2 = fInfcl[2][id];
429 fClusters[0][fClno] = fCoord[0][i1][i2];
430 fClusters[1][fClno] = fCoord[1][i1][i2];
431 fClusters[2][fClno] = fEdepCell[i1][i2];
432 fClusters[3][fClno] = 1.;
433 fClusters[4][fClno] = 0.5;
434
0709b99f 435 //association
01c4d84a 436
437 fClTr[0][fClno]=fCellTrNo[i1][i2];
438 for(Int_t icltr=1;icltr<14;icltr++)
439 {
440 fClTr[icltr][fClno]=-1;
441 }
442
443 //ofl1 << icl << " " << fCoord[0][i1][i2] << " " << fCoord[1][i1][i2] <<
3edbbba2 444 //" " << fEdepCell[i1][i2] << " " << fClusters[3][fClno] <<endl;
0709b99f 445
3edbbba2 446 }else if(ncl[i] == 1){
447 // two cell super-cluster --> single cluster
448 // cluster center is at ener. dep.-weighted mean of two cells
449 // cluster radius == half cell dimension
450 id = id + 1;
451 icl = icl+1;
452 if (fClno >= 5000) {
453 AliWarning("RefClust: Too many clusters! more than 5000");
454 return;
455 }
456 fClno = fClno+1;
457 i1 = fInfcl[1][id];
458 i2 = fInfcl[2][id];
459 x1 = fCoord[0][i1][i2];
460 y1 = fCoord[1][i1][i2];
461 z1 = fEdepCell[i1][i2];
462
01c4d84a 463 //asso
464 fClTr[0][fClno]=fCellTrNo[i1][i2];
465 //
3edbbba2 466
467 id = id+1;
468 i1 = fInfcl[1][id];
469 i2 = fInfcl[2][id];
470 x2 = fCoord[0][i1][i2];
471 y2 = fCoord[1][i1][i2];
472 z2 = fEdepCell[i1][i2];
473
01c4d84a 474 //asso
475
476 fClTr[1][fClno]=fCellTrNo[i1][i2];
477 for(Int_t icltr=2;icltr<14;icltr++)
478 {
479 fClTr[icltr][fClno] = -1;
480 }
481 //
482
3edbbba2 483 fClusters[0][fClno] = (x1*z1+x2*z2)/(z1+z2);
484 fClusters[1][fClno] = (y1*z1+y2*z2)/(z1+z2);
485 fClusters[2][fClno] = z1+z2;
486 fClusters[3][fClno] = 2.;
487 fClusters[4][fClno] = 0.5;
488
489
490 //ofl1 << icl << " " << fClusters[0][fClno] << " " << fClusters[1][fClno]
0709b99f 491 // << " " << fClusters[2][fClno] << " " <<fClusters[3][fClno] <<endl;
3edbbba2 492 }
493 else{
01c4d84a 494
495 //asso
496 for(Int_t icg=0;icg<4500;icg++)
497 {
498 cellCount[icg]=0;
499 }
500 //
501
3edbbba2 502 id = id + 1;
503 iord[0] = 0;
504 // super-cluster of more than two cells - broken up into smaller
505 // clusters gaussian centers computed. (peaks separated by > 1 cell)
506 // Begin from cell having largest energy deposited This is first
507 // cluster center
508 i1 = fInfcl[1][id];
509 i2 = fInfcl[2][id];
510 x[0] = fCoord[0][i1][i2];
511 y[0] = fCoord[1][i1][i2];
512 z[0] = fEdepCell[i1][i2];
01c4d84a 513
514 //asso
515 t[0]=fCellTrNo[i1][i2];
516 //
517
3edbbba2 518 iord[0] = 0;
519 for(j=1;j<=ncl[i];j++){
520
521 id = id + 1;
522 i1 = fInfcl[1][id];
523 i2 = fInfcl[2][id];
524 iord[j] = j;
525 x[j] = fCoord[0][i1][i2];
526 y[j] = fCoord[1][i1][i2];
527 z[j] = fEdepCell[i1][i2];
01c4d84a 528
529 //asso
530 t[j]=fCellTrNo[i1][i2];
531 //
532
533
3edbbba2 534 }
535 // arranging cells within supercluster in decreasing order
536 for(j=1;j<=ncl[i];j++){
537 itest=0;
538 ihld=iord[j];
539 for(i1=0;i1<j;i1++){
540 if(itest == 0 && z[iord[i1]] < z[ihld]){
541 itest=1;
542 for(i2=j-1;i2>=i1;i2--){
543 iord[i2+1]=iord[i2];
544 }
545 iord[i1]=ihld;
546 }
547 }
548 }
549
550 // compute the number of Gaussians and their centers ( first
551 // guess )
552 // centers must be separated by cells having smaller ener. dep.
553 // neighbouring centers should be either strong or well-separated
554 ig=0;
555 xc[ig]=x[iord[0]];
556 yc[ig]=y[iord[0]];
557 zc[ig]=z[iord[0]];
558 for(j=1;j<=ncl[i];j++){
559 itest=-1;
560 x1=x[iord[j]];
561 y1=y[iord[j]];
562 for(k=0;k<=ig;k++){
563 x2=xc[k]; y2=yc[k];
564 rr=Distance(x1,y1,x2,y2);
565 if( rr >= 1.1 && rr < 1.8 && z[iord[j]] > zc[k]/4.)
566 itest=itest+1;
567 if( rr >= 1.8 && rr < 2.1 && z[iord[j]] > zc[k]/10.)
568 itest=itest+1;
569 if( rr >= 2.1)itest=itest+1;
570 }
571 if(itest == ig){
572 ig=ig+1;
573 xc[ig]=x1;
574 yc[ig]=y1;
575 zc[ig]=z[iord[j]];
576 }
577 }
578 // for(j=0; j<=ig; j++){
579 //ofl1 << icl+j+1 << " " << xc[j] << " " <<yc[j] <<" "<<zc[j]<<endl;
580 //}
581 // GaussFit to adjust cluster parameters to minimize
582 GaussFit(ncl[i], ig, x[0], y[0] ,z[0], xc[0], yc[0], zc[0], rc[0]);
583 icl=icl+ig+1;
584 // compute the number of cells belonging to each cluster.
585 // cell is shared between several clusters ( if they are equidistant
586 // from it ) in the ratio of cluster energy deposition
587 for(j=0; j<=ig; j++){
588 cells[j]=0.;
589 }
590 if(ig > 0){
591 for(j=0; j<=ncl[i]; j++){
93c7ebb0 592 lev1[j]=0;
593 lev2[j]=0;
3edbbba2 594 for(k=0; k<=ig; k++){
595 dist=Distance(x[j], y[j], xc[k], yc[k]);
596 if(dist < sqrt(3.) ){
01c4d84a 597
598 //asso
599 fClTr[cellCount[k]][fClno+k+1]=t[j];
600 cellCount[k]++;
601 //
602
3edbbba2 603 lev1[0]++;
604 i1=lev1[0];
605 lev1[i1]=k;
606 }else{
607 if(dist < 2.1){
608 lev2[0]++;
609 i1=lev2[0];
610 lev2[i1]=k;
611 }
612 }
613 }
614 if(lev1[0] != 0){
615 if(lev1[0] == 1){cells[lev1[1]]=cells[lev1[1]]+1.;}
616 else{
617 sum=0.;
618 for(k=1; k<=lev1[0]; k++){
619 sum=sum+zc[lev1[k]];
620 }
621 for(k=1; k<=lev1[0]; k++){
622 cells[lev1[k]]=cells[lev1[k]]+zc[lev1[k]]/sum;
623 }
624 }
625 }else{
626 if(lev2[0] == 0){cells[lev2[1]]=cells[lev2[1]]+1.;}
627 else{
628 sum=0.;
629 for(k=1; k<=lev2[0]; k++){
630 sum=sum+zc[lev2[k]];
631 }
632 for(k=1; k<=lev2[0]; k++){
633 cells[lev2[k]]=cells[lev2[k]]+zc[lev2[k]]/sum;
634 }
635 }
636 }
637 }
638 }
01c4d84a 639
640 // zero rest of the cell array
641 //asso
642 for(k=0; k<=ig; k++)
643 {
644 for(Int_t icltr=cellCount[k];icltr<14;icltr++)
645 {
646 fClTr[icltr][fClno]=-1;
647 }
648 }
649 //
650
651
652
3edbbba2 653 for(j=0; j<=ig; j++){
654 if (fClno >= 5000) {
655 AliWarning("RefClust: Too many clusters! more than 5000");
656 return;
657 }
658 fClno = fClno + 1;
659 fClusters[0][fClno] = xc[j];
660 fClusters[1][fClno] = yc[j];
661 fClusters[2][fClno] = zc[j];
662 fClusters[4][fClno] = rc[j];
663 if(ig == 0){
664 fClusters[3][fClno] = ncl[i];
665 }else{
666 fClusters[3][fClno] = cells[j];
667 }
668 }
669 }
670 }
671}
672// ------------------------------------------------------------------------ //
673void AliPMDClusteringV1::GaussFit(Int_t ncell, Int_t nclust, Double_t &x, Double_t &y ,Double_t &z, Double_t &xc, Double_t &yc, Double_t &zc, Double_t &rc)
674{
675 // Does gaussian fitting
676 //
677 int i, j, i1, i2, novar, idd, jj;
678 double xx[4500], yy[4500], zz[4500], xxc[4500], yyc[4500];
679 double a[4500], b[4500], c[4500], d[4500], ha[4500], hb[4500];
680 double hc[4500], hd[4500], zzc[4500], rrc[4500];
681 int neib[4500][50];
682 double sum, dx, dy, str, str1, aint, sum1, rr, dum;
683 double x1, x2, y1, y2;
684 str = 0.;
685 str1 = 0.;
686 rr = 0.3;
687 novar = 0;
688 j = 0; // Just put not to see the compiler warning, BKN
689
690 for(i=0; i<=ncell; i++)
691 {
692 xx[i] = *(&x+i);
693 yy[i] = *(&y+i);
694 zz[i] = *(&z+i);
695 str = str + zz[i];
696 }
697 for(i=0; i<=nclust; i++)
698 {
699 xxc[i] = *(&xc+i);
700 yyc[i] = *(&yc+i);
701 zzc[i] = *(&zc+i);
702 str1 = str1 + zzc[i];
703 rrc[i] = 0.5;
704 }
705 for(i=0; i<=nclust; i++)
706 {
707 zzc[i] = str/str1*zzc[i];
708 ha[i] = xxc[i];
709 hb[i] = yyc[i];
710 hc[i] = zzc[i];
711 hd[i] = rrc[i];
712 x1 = xxc[i];
713 y1 = yyc[i];
714 }
715 for(i=0; i<=ncell; i++){
716 idd=0;
717 x1=xx[i];
718 y1=yy[i];
719 for(j=0; j<=nclust; j++){
720 x2=xxc[j];
721 y2=yyc[j];
722 if(Distance(x1,y1,x2,y2) <= 3.){ idd=idd+1; neib[i][idd]=j; }
723 }
724 neib[i][0]=idd;
725 }
726 sum=0.;
727 for(i1=0; i1<=ncell; i1++){
728 aint=0.;
729 idd=neib[i1][0];
730 for(i2=1; i2<=idd; i2++){
731 jj=neib[i1][i2];
732 dx=xx[i1]-xxc[jj];
733 dy=yy[i1]-yyc[jj];
734 dum=rrc[j]*rrc[jj]+rr*rr;
735 aint=aint+exp(-(dx*dx+dy*dy)/dum)*zzc[idd]*rr*rr/dum;
736 }
737 sum=sum+(aint-zz[i1])*(aint-zz[i1])/str;
738 }
739// jmax=nclust*1000;
740// if(nclust > 20)jmax=20000;
741// for(j=0; j<jmax; j++){
742 str1=0.;
743 for(i=0; i<=nclust; i++){
744 a[i]=xxc[i]+0.6*(Ranmar()-0.5);
745 b[i]=yyc[i]+0.6*(Ranmar()-0.5);
746 c[i]=zzc[i]*(1.+(Ranmar()-0.5)*0.2);
747 str1=str1+zzc[i];
748 d[i]=rrc[i]*(1.+(Ranmar()-0.5)*0.1);
749 if(d[i] < 0.25)d[i]=0.25;
750 }
751 for(i=0; i<=nclust; i++){ c[i]=c[i]*str/str1; }
752 sum1=0.;
753 for(i1=0; i1<=ncell; i1++){
754 aint=0.;
755 idd=neib[i1][0];
756 for(i2=1; i2<=idd; i2++){
757 jj=neib[i1][i2];
758 dx=xx[i1]-a[jj];
759 dy=yy[i1]-b[jj];
760 dum=d[jj]*d[jj]+rr*rr;
761 aint=aint+exp(-(dx*dx+dy*dy)/dum)*c[i2]*rr*rr/dum;
762 }
763 sum1=sum1+(aint-zz[i1])*(aint-zz[i1])/str;
764 }
765
766 if(sum1 < sum){
767 for(i2=0; i2<=nclust; i2++){
768 xxc[i2]=a[i2];
769 yyc[i2]=b[i2];
770 zzc[i2]=c[i2];
771 rrc[i2]=d[i2];
772 sum=sum1;
773 }
774 }
775// }
776 for(j=0; j<=nclust; j++){
777 *(&xc+j)=xxc[j];
778 *(&yc+j)=yyc[j];
779 *(&zc+j)=zzc[j];
780 *(&rc+j)=rrc[j];
781 }
782}
783// ------------------------------------------------------------------------ //
784double AliPMDClusteringV1::Distance(double x1, double y1, double x2, double y2)
785{
786 return sqrt((x1-x2)*(x1-x2) + (y1-y2)*(y1-y2));
787}
788// ------------------------------------------------------------------------ //
789double AliPMDClusteringV1::Ranmar() const
790{
791 // Universal random number generator proposed by Marsaglia and Zaman
792 // in report FSU-SCRI-87-50
793
794 // clock_t start;
795 int ii, jj;
796 static int i=96, j=32, itest=0, i1, i2, i3, i4, i5;
797 static double u[97], c, cd, cm, s, t;
798 static double uni;
799 int count1,count2,idum;
800 /* $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$ */
801 if (itest == 0) {
802 //*******************************************************
803 // following three lines if the seed to be provided by computer
804 // start = time(NULL);
805 // ii=start;
806 // jj=start;
807 //*******************************************************
808 //following two lines for fixed seed ( during testing only. Else
809 //use preceeing three lines
810 ii=8263;
811 jj=5726;
812 if(ii > 31328 ) ii = ii - ( ii / 31328 ) * 31328;
813 if(jj > 30081 ) jj = jj - ( jj / 30081 ) * 30081;
814 itest=itest+1;
815 if((( ii > 0 ) && ( ii <= 31328 )) && (( jj > 0 ) &&
816 ( jj <= 30081 ))){
817 i1=ii/177+2; i2=ii-(i1-2)*177+2; i3=jj/169+1; i4=jj-(i3-1)*169;
818 i4 = jj - (i3-1)*169;
819 count1=0;
820 while ( count1 < 97 ){
821 s=0.;
822 t=0.5;
823 count2=0;
824 while( count2 < 24 ){
825 idum=i1*i2/179;
826 idum=( i1*i2 - (i1*i2/179)*179 ) * i3;
827 i5=idum-(idum/179)*179;
828 i1=i2; i2=i3; i3=i5; idum=53*i4+1; i4=idum-(idum/169)*169;
829 if( i4*i5-((i4*i5)/64)*64 >= 32 ) s=s+t;
830 t=0.5*t;
831 count2=count2+1;
832 }
833 u[count1] = s;
834 count1 = count1 +1;
835 }
836 c = 362436./16777216.; cd = 7654321./16777216.;
837 cm = 16777213./16777216.;
838 }
839 else{
840 AliWarning("Wrong initialization");
841 }
842 }
843 else{
844 uni = u[i] - u[j];
845 if( uni < 0.) uni = uni + 1;
846 u[i] = uni;
847 i = i -1;
848 if( i < 0 ) i = 96;
849 j = j - 1;
850 if ( j < 0 ) j = 96;
851 c = c - cd;
852 if( c < 0. ) c = c+cm;
853 uni = uni-c ;
854 if( uni < 0. )uni = uni+1.;
855 }
856 return uni;
857}
858// ------------------------------------------------------------------------ //
859void AliPMDClusteringV1::SetEdepCut(Float_t decut)
860{
861 fCutoff = decut;
862}
863// ------------------------------------------------------------------------ //