New parameters added (Max curvature) (Marian)
[u/mrichter/AliRoot.git] / PMD / AliPMDClusteringV1.cxx
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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// //
18// Source File : PMDClustering.cxx, Version 00 //
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 */
85 int i, i1, i2, j, nmx1, incr, id, jd;
86 Int_t celldataX[15], celldataY[15];
87 Float_t clusdata[7];
88
89 Double_t cutoff, ave;
90
91 const float ktwobysqrt3 = 1.1547; // 2./sqrt(3.)
92
93 for (id = 0; id < kNDIMXr; id++)
94 {
95 for (jd = 0; jd < kNDIMYr; jd++)
96 {
97 j=jd;
98 i=id+(kNDIMYr/2-1)-(jd/2);
99 fEdepCell[i][j] = celladc[id][jd];
100 }
101 }
102 Order(); // order the data
103 cutoff = fCutoff; // cutoff used to discard cells having ener. dep.
104 ave=0.;
105 nmx1=-1;
106
107 for(j=0;j<kNMX; j++)
108 {
109 i1 = fIord[0][j];
110 i2 = fIord[1][j];
111 if (fEdepCell[i1][i2] > 0.) {ave = ave + fEdepCell[i1][i2];}
112 if (fEdepCell[i1][i2] > cutoff ) nmx1 = nmx1 + 1;
113 }
114 // nmx1 --- number of cells having ener dep >= cutoff
115
116 AliDebug(1,Form("Number of cells having energy >= %f are %d",cutoff,nmx1));
117
118 // if (nmx1 == 0 | nmx1 == -1) return;
119
120 if (nmx1 == 0) nmx1 = 1;
121 ave=ave/nmx1;
122
123 AliDebug(1,Form("Number of cells in a SuperM = %d and Average = %f",
124 kNMX,ave));
125
126 incr = CrClust(ave, cutoff, nmx1);
127 RefClust(incr);
128
129 AliDebug(1,Form("Detector Plane = %d Serial Module No = %d Number of clusters = %d",idet, ismn, fClno));
130
131 for(i1=0; i1<=fClno; i1++)
132 {
133 Float_t cluXC = (Float_t) fClusters[0][i1];
134 Float_t cluYC = (Float_t) fClusters[1][i1];
135 Float_t cluADC = (Float_t) fClusters[2][i1];
136 Float_t cluCELLS = (Float_t) fClusters[3][i1];
137 Float_t cluRAD = (Float_t) fClusters[4][i1];
138 Float_t cluY0 = ktwobysqrt3*cluYC;
139 Float_t cluX0 = cluXC - cluY0/2.;
140 //
141 // Cluster X centroid is back transformed
142 //
143 clusdata[0] = cluX0 - (48-1) + cluY0/2.;
144 clusdata[1] = cluY0;
145 clusdata[2] = cluADC;
146 clusdata[3] = cluCELLS;
147 clusdata[4] = cluRAD;
148 clusdata[5] = 0.;
149
150 //
151 // Cells associated with a cluster
152 //
153 for (Int_t ihit = 0; ihit < 15; ihit++)
154 {
155 celldataX[ihit] = 2;
156 celldataY[ihit] = 5;
157 }
158
159 pmdcl = new AliPMDcluster(idet, ismn, clusdata, celldataX, celldataY);
160 pmdcont->Add(pmdcl);
161 }
162}
163// ------------------------------------------------------------------------ //
164void AliPMDClusteringV1::Order()
165{
166 // Sorting algorithm
167 // sorts the ADC values from higher to lower
168 //
169 double dd[kNMX];
170 // matrix fEdepCell converted into
171 // one dimensional array dd. adum a place holder for double
172 int i, j, i1, i2, iord1[kNMX];
173 // information of
174 // ordering is stored in iord1, original array not ordered
175 //
176 // define arrays dd and iord1
177 for(i1=0; i1 < kNDIMX; i1++)
178 {
179 for(i2=0; i2 < kNDIMY; i2++)
180 {
181 i = i1 + i2*kNDIMX;
182 iord1[i] = i;
183 dd[i] = fEdepCell[i1][i2];
184 }
185 }
186
187 TMath::Sort(kNMX,dd,iord1); //PH Using much better algorithm...
188 // store the sorted information in fIord for later use
189 for(i=0; i<kNMX; i++)
190 {
191 j = iord1[i];
192 i2 = j/kNDIMX;
193 i1 = j-i2*kNDIMX;
194 fIord[0][i]=i1;
195 fIord[1][i]=i2;
196 }
197}
198// ------------------------------------------------------------------------ //
199int AliPMDClusteringV1::CrClust(double ave, double cutoff, int nmx1)
200{
201 // Does crude clustering
202 // Finds out only the big patch by just searching the
203 // connected cells
204 //
205 int i,j,k,id1,id2,icl, numcell, clust[2][5000];
206 int jd1,jd2, icell, cellcount;
207 static int neibx[6]={1,0,-1,-1,0,1}, neiby[6]={0,1,1,0,-1,-1};
208 // neibx and neiby define ( incremental ) (i,j) for the neighbours of a
209 // cell. There are six neighbours.
210 // cellcount --- total number of cells having nonzero ener dep
211 // numcell --- number of cells in a given supercluster
212 // ofstream ofl0("cells_loc",ios::out);
213 // initialize fInfocl[2][kNDIMX][kNDIMY]
214
215 AliDebug(1,Form("kNMX = %d nmx1 = %d kNDIMX = %d kNDIMY = %d ave = %f cutoff = %f",kNMX,nmx1,kNDIMX,kNDIMY,ave,cutoff));
216
217 for (j=0; j < kNDIMX; j++){
218 for(k=0; k < kNDIMY; k++){
219 fInfocl[0][j][k] = 0;
220 fInfocl[1][j][k] = 0;
221 }
222 }
223 for(i=0; i < kNMX; i++){
224 fInfcl[0][i] = -1;
225 id1=fIord[0][i];
226 id2=fIord[1][i];
227 if(fEdepCell[id1][id2] <= cutoff){fInfocl[0][id1][id2]=-1;}
228 }
229 // ---------------------------------------------------------------
230 // crude clustering begins. Start with cell having largest adc
231 // count and loop over the cells in descending order of adc count
232 // ---------------------------------------------------------------
233 icl=-1;
234 cellcount=-1;
235 for(icell=0; icell <= nmx1; icell++){
236 id1=fIord[0][icell];
237 id2=fIord[1][icell];
238 if(fInfocl[0][id1][id2] == 0 ){
239 // ---------------------------------------------------------------
240 // icl -- cluster #, numcell -- # of cells in it, clust -- stores
241 // coordinates of the cells in a cluster, fInfocl[0][i1][i2] is 1 for
242 // primary and 2 for secondary cells,
243 // fInfocl[1][i1][i2] stores cluster #
244 // ---------------------------------------------------------------
245 icl=icl+1;
246 numcell=0;
247 cellcount = cellcount + 1;
248 fInfocl[0][id1][id2]=1;
249 fInfocl[1][id1][id2]=icl;
250 fInfcl[0][cellcount]=icl;
251 fInfcl[1][cellcount]=id1;
252 fInfcl[2][cellcount]=id2;
253
254 clust[0][numcell]=id1;
255 clust[1][numcell]=id2;
256 for(i=1; i<5000; i++)clust[0][i]=0;
257 // ---------------------------------------------------------------
258 // check for adc count in neib. cells. If ne 0 put it in this clust
259 // ---------------------------------------------------------------
260 for(i=0; i<6; i++){
261 jd1=id1+neibx[i];
262 jd2=id2+neiby[i];
263 if( (jd1 >= 0 && jd1 < kNDIMX) && (jd2 >= 0 && jd2 < kNDIMY) &&
264 fInfocl[0][jd1][jd2] == 0){
265 numcell=numcell+1;
266 fInfocl[0][jd1][jd2]=2;
267 fInfocl[1][jd1][jd2]=icl;
268 clust[0][numcell]=jd1;
269 clust[1][numcell]=jd2;
270 cellcount=cellcount+1;
271 fInfcl[0][cellcount]=icl;
272 fInfcl[1][cellcount]=jd1;
273 fInfcl[2][cellcount]=jd2;
274 }
275 }
276 // ---------------------------------------------------------------
277 // check adc count for neighbour's neighbours recursively and
278 // if nonzero, add these to the cluster.
279 // ---------------------------------------------------------------
280 for(i=1;i < 5000;i++){
281 if(clust[0][i] != 0){
282 id1=clust[0][i];
283 id2=clust[1][i];
284 for(j=0; j<6 ; j++){
285 jd1=id1+neibx[j];
286 jd2=id2+neiby[j];
287 if( (jd1 >= 0 && jd1 < kNDIMX) && (jd2 >= 0 && jd2 < kNDIMY) &&
288 fInfocl[0][jd1][jd2] == 0 ){
289 fInfocl[0][jd1][jd2] = 2;
290 fInfocl[1][jd1][jd2] = icl;
291 numcell = numcell + 1;
292 clust[0][numcell] = jd1;
293 clust[1][numcell] = jd2;
294 cellcount = cellcount+1;
295 fInfcl[0][cellcount] = icl;
296 fInfcl[1][cellcount] = jd1;
297 fInfcl[2][cellcount] = jd2;
298 }
299 }
300 }
301 }
302 }
303 }
304 // for(icell=0; icell<=cellcount; icell++){
305 // ofl0 << fInfcl[0][icell] << " " << fInfcl[1][icell] << " " <<
306 // fInfcl[2][icell] << endl;
307 // }
308 return cellcount;
309}
310// ------------------------------------------------------------------------ //
311void AliPMDClusteringV1::RefClust(int incr)
312{
313 // Does the refining of clusters
314 // Takes the big patch and does gaussian fitting and
315 // finds out the more refined clusters
316 //
317 int i, j, k, i1, i2, id, icl, ncl[4500], iord[4500], itest;
318 int ihld;
319 int ig, nsupcl, lev1[20], lev2[20];
320 double x[4500], y[4500], z[4500], x1, y1, z1, x2, y2, z2, dist;
321 double xc[4500], yc[4500], zc[4500], cells[4500], sum, rc[4500], rr;
322 // fClno counts the final clusters
323 // nsupcl = # of superclusters; ncl[i]= # of cells in supercluster i
324 // x, y and z store (x,y) coordinates of and energy deposited in a cell
325 // xc, yc store (x,y) coordinates of the cluster center
326 // zc stores the energy deposited in a cluster
327 // rc is cluster radius
328 // finally the cluster information is put in 2-dimensional array clusters
329 // ofstream ofl1("checking.5",ios::app);
330 fClno = -1;
331 nsupcl = -1;
332 for(i=0; i<4500; i++){ncl[i]=-1;}
333 for(i=0; i<incr; i++){
334 if(fInfcl[0][i] != nsupcl){ nsupcl=nsupcl+1; }
335 if (nsupcl > 4500) {
336 AliWarning("RefClust: Too many superclusters!");
337 nsupcl = 4500;
338 break;
339 }
340 ncl[nsupcl]=ncl[nsupcl]+1;
341 }
342
343 AliDebug(1,Form("Number of cells = %d Number of Superclusters = %d",
344 incr+1,nsupcl+1));
345
346 id=-1;
347 icl=-1;
348 for(i=0; i<nsupcl; i++){
349 if(ncl[i] == 0){
350 id=id+1;
351 icl=icl+1;
352 // one cell super-clusters --> single cluster
353 // cluster center at the centyer of the cell
354 // cluster radius = half cell dimension
355 if (fClno >= 5000) {
356 AliWarning("RefClust: Too many clusters! more than 5000");
357 return;
358 }
359 fClno = fClno + 1;
360 i1 = fInfcl[1][id];
361 i2 = fInfcl[2][id];
362 fClusters[0][fClno] = fCoord[0][i1][i2];
363 fClusters[1][fClno] = fCoord[1][i1][i2];
364 fClusters[2][fClno] = fEdepCell[i1][i2];
365 fClusters[3][fClno] = 1.;
366 fClusters[4][fClno] = 0.5;
367
368 //ofl1 << icl << " " << fCoord[0][i1][i2] << " " << fCoord[1][i1][i2] <<
369 //" " << fEdepCell[i1][i2] << " " << fClusters[3][fClno] <<endl;
370 }else if(ncl[i] == 1){
371 // two cell super-cluster --> single cluster
372 // cluster center is at ener. dep.-weighted mean of two cells
373 // cluster radius == half cell dimension
374 id = id + 1;
375 icl = icl+1;
376 if (fClno >= 5000) {
377 AliWarning("RefClust: Too many clusters! more than 5000");
378 return;
379 }
380 fClno = fClno+1;
381 i1 = fInfcl[1][id];
382 i2 = fInfcl[2][id];
383 x1 = fCoord[0][i1][i2];
384 y1 = fCoord[1][i1][i2];
385 z1 = fEdepCell[i1][i2];
386
387
388 id = id+1;
389 i1 = fInfcl[1][id];
390 i2 = fInfcl[2][id];
391 x2 = fCoord[0][i1][i2];
392 y2 = fCoord[1][i1][i2];
393 z2 = fEdepCell[i1][i2];
394
395 fClusters[0][fClno] = (x1*z1+x2*z2)/(z1+z2);
396 fClusters[1][fClno] = (y1*z1+y2*z2)/(z1+z2);
397 fClusters[2][fClno] = z1+z2;
398 fClusters[3][fClno] = 2.;
399 fClusters[4][fClno] = 0.5;
400
401
402 //ofl1 << icl << " " << fClusters[0][fClno] << " " << fClusters[1][fClno]
403 // << " " << fClusters[2][fClno] << " " <<fClusters[3][fClno] <<endl;
404 }
405 else{
406 id = id + 1;
407 iord[0] = 0;
408 // super-cluster of more than two cells - broken up into smaller
409 // clusters gaussian centers computed. (peaks separated by > 1 cell)
410 // Begin from cell having largest energy deposited This is first
411 // cluster center
412 i1 = fInfcl[1][id];
413 i2 = fInfcl[2][id];
414 x[0] = fCoord[0][i1][i2];
415 y[0] = fCoord[1][i1][i2];
416 z[0] = fEdepCell[i1][i2];
417 iord[0] = 0;
418 for(j=1;j<=ncl[i];j++){
419
420 id = id + 1;
421 i1 = fInfcl[1][id];
422 i2 = fInfcl[2][id];
423 iord[j] = j;
424 x[j] = fCoord[0][i1][i2];
425 y[j] = fCoord[1][i1][i2];
426 z[j] = fEdepCell[i1][i2];
427 }
428 // arranging cells within supercluster in decreasing order
429 for(j=1;j<=ncl[i];j++){
430 itest=0;
431 ihld=iord[j];
432 for(i1=0;i1<j;i1++){
433 if(itest == 0 && z[iord[i1]] < z[ihld]){
434 itest=1;
435 for(i2=j-1;i2>=i1;i2--){
436 iord[i2+1]=iord[i2];
437 }
438 iord[i1]=ihld;
439 }
440 }
441 }
442
443 // compute the number of Gaussians and their centers ( first
444 // guess )
445 // centers must be separated by cells having smaller ener. dep.
446 // neighbouring centers should be either strong or well-separated
447 ig=0;
448 xc[ig]=x[iord[0]];
449 yc[ig]=y[iord[0]];
450 zc[ig]=z[iord[0]];
451 for(j=1;j<=ncl[i];j++){
452 itest=-1;
453 x1=x[iord[j]];
454 y1=y[iord[j]];
455 for(k=0;k<=ig;k++){
456 x2=xc[k]; y2=yc[k];
457 rr=Distance(x1,y1,x2,y2);
458 if( rr >= 1.1 && rr < 1.8 && z[iord[j]] > zc[k]/4.)
459 itest=itest+1;
460 if( rr >= 1.8 && rr < 2.1 && z[iord[j]] > zc[k]/10.)
461 itest=itest+1;
462 if( rr >= 2.1)itest=itest+1;
463 }
464 if(itest == ig){
465 ig=ig+1;
466 xc[ig]=x1;
467 yc[ig]=y1;
468 zc[ig]=z[iord[j]];
469 }
470 }
471 // for(j=0; j<=ig; j++){
472 //ofl1 << icl+j+1 << " " << xc[j] << " " <<yc[j] <<" "<<zc[j]<<endl;
473 //}
474 // GaussFit to adjust cluster parameters to minimize
475 GaussFit(ncl[i], ig, x[0], y[0] ,z[0], xc[0], yc[0], zc[0], rc[0]);
476 icl=icl+ig+1;
477 // compute the number of cells belonging to each cluster.
478 // cell is shared between several clusters ( if they are equidistant
479 // from it ) in the ratio of cluster energy deposition
480 for(j=0; j<=ig; j++){
481 cells[j]=0.;
482 }
483 if(ig > 0){
484 for(j=0; j<=ncl[i]; j++){
93c7ebb0 485 lev1[j]=0;
486 lev2[j]=0;
3edbbba2 487 for(k=0; k<=ig; k++){
488 dist=Distance(x[j], y[j], xc[k], yc[k]);
489 if(dist < sqrt(3.) ){
490 lev1[0]++;
491 i1=lev1[0];
492 lev1[i1]=k;
493 }else{
494 if(dist < 2.1){
495 lev2[0]++;
496 i1=lev2[0];
497 lev2[i1]=k;
498 }
499 }
500 }
501 if(lev1[0] != 0){
502 if(lev1[0] == 1){cells[lev1[1]]=cells[lev1[1]]+1.;}
503 else{
504 sum=0.;
505 for(k=1; k<=lev1[0]; k++){
506 sum=sum+zc[lev1[k]];
507 }
508 for(k=1; k<=lev1[0]; k++){
509 cells[lev1[k]]=cells[lev1[k]]+zc[lev1[k]]/sum;
510 }
511 }
512 }else{
513 if(lev2[0] == 0){cells[lev2[1]]=cells[lev2[1]]+1.;}
514 else{
515 sum=0.;
516 for(k=1; k<=lev2[0]; k++){
517 sum=sum+zc[lev2[k]];
518 }
519 for(k=1; k<=lev2[0]; k++){
520 cells[lev2[k]]=cells[lev2[k]]+zc[lev2[k]]/sum;
521 }
522 }
523 }
524 }
525 }
526 for(j=0; j<=ig; j++){
527 if (fClno >= 5000) {
528 AliWarning("RefClust: Too many clusters! more than 5000");
529 return;
530 }
531 fClno = fClno + 1;
532 fClusters[0][fClno] = xc[j];
533 fClusters[1][fClno] = yc[j];
534 fClusters[2][fClno] = zc[j];
535 fClusters[4][fClno] = rc[j];
536 if(ig == 0){
537 fClusters[3][fClno] = ncl[i];
538 }else{
539 fClusters[3][fClno] = cells[j];
540 }
541 }
542 }
543 }
544}
545// ------------------------------------------------------------------------ //
546void 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)
547{
548 // Does gaussian fitting
549 //
550 int i, j, i1, i2, novar, idd, jj;
551 double xx[4500], yy[4500], zz[4500], xxc[4500], yyc[4500];
552 double a[4500], b[4500], c[4500], d[4500], ha[4500], hb[4500];
553 double hc[4500], hd[4500], zzc[4500], rrc[4500];
554 int neib[4500][50];
555 double sum, dx, dy, str, str1, aint, sum1, rr, dum;
556 double x1, x2, y1, y2;
557 str = 0.;
558 str1 = 0.;
559 rr = 0.3;
560 novar = 0;
561 j = 0; // Just put not to see the compiler warning, BKN
562
563 for(i=0; i<=ncell; i++)
564 {
565 xx[i] = *(&x+i);
566 yy[i] = *(&y+i);
567 zz[i] = *(&z+i);
568 str = str + zz[i];
569 }
570 for(i=0; i<=nclust; i++)
571 {
572 xxc[i] = *(&xc+i);
573 yyc[i] = *(&yc+i);
574 zzc[i] = *(&zc+i);
575 str1 = str1 + zzc[i];
576 rrc[i] = 0.5;
577 }
578 for(i=0; i<=nclust; i++)
579 {
580 zzc[i] = str/str1*zzc[i];
581 ha[i] = xxc[i];
582 hb[i] = yyc[i];
583 hc[i] = zzc[i];
584 hd[i] = rrc[i];
585 x1 = xxc[i];
586 y1 = yyc[i];
587 }
588 for(i=0; i<=ncell; i++){
589 idd=0;
590 x1=xx[i];
591 y1=yy[i];
592 for(j=0; j<=nclust; j++){
593 x2=xxc[j];
594 y2=yyc[j];
595 if(Distance(x1,y1,x2,y2) <= 3.){ idd=idd+1; neib[i][idd]=j; }
596 }
597 neib[i][0]=idd;
598 }
599 sum=0.;
600 for(i1=0; i1<=ncell; i1++){
601 aint=0.;
602 idd=neib[i1][0];
603 for(i2=1; i2<=idd; i2++){
604 jj=neib[i1][i2];
605 dx=xx[i1]-xxc[jj];
606 dy=yy[i1]-yyc[jj];
607 dum=rrc[j]*rrc[jj]+rr*rr;
608 aint=aint+exp(-(dx*dx+dy*dy)/dum)*zzc[idd]*rr*rr/dum;
609 }
610 sum=sum+(aint-zz[i1])*(aint-zz[i1])/str;
611 }
612// jmax=nclust*1000;
613// if(nclust > 20)jmax=20000;
614// for(j=0; j<jmax; j++){
615 str1=0.;
616 for(i=0; i<=nclust; i++){
617 a[i]=xxc[i]+0.6*(Ranmar()-0.5);
618 b[i]=yyc[i]+0.6*(Ranmar()-0.5);
619 c[i]=zzc[i]*(1.+(Ranmar()-0.5)*0.2);
620 str1=str1+zzc[i];
621 d[i]=rrc[i]*(1.+(Ranmar()-0.5)*0.1);
622 if(d[i] < 0.25)d[i]=0.25;
623 }
624 for(i=0; i<=nclust; i++){ c[i]=c[i]*str/str1; }
625 sum1=0.;
626 for(i1=0; i1<=ncell; i1++){
627 aint=0.;
628 idd=neib[i1][0];
629 for(i2=1; i2<=idd; i2++){
630 jj=neib[i1][i2];
631 dx=xx[i1]-a[jj];
632 dy=yy[i1]-b[jj];
633 dum=d[jj]*d[jj]+rr*rr;
634 aint=aint+exp(-(dx*dx+dy*dy)/dum)*c[i2]*rr*rr/dum;
635 }
636 sum1=sum1+(aint-zz[i1])*(aint-zz[i1])/str;
637 }
638
639 if(sum1 < sum){
640 for(i2=0; i2<=nclust; i2++){
641 xxc[i2]=a[i2];
642 yyc[i2]=b[i2];
643 zzc[i2]=c[i2];
644 rrc[i2]=d[i2];
645 sum=sum1;
646 }
647 }
648// }
649 for(j=0; j<=nclust; j++){
650 *(&xc+j)=xxc[j];
651 *(&yc+j)=yyc[j];
652 *(&zc+j)=zzc[j];
653 *(&rc+j)=rrc[j];
654 }
655}
656// ------------------------------------------------------------------------ //
657double AliPMDClusteringV1::Distance(double x1, double y1, double x2, double y2)
658{
659 return sqrt((x1-x2)*(x1-x2) + (y1-y2)*(y1-y2));
660}
661// ------------------------------------------------------------------------ //
662double AliPMDClusteringV1::Ranmar() const
663{
664 // Universal random number generator proposed by Marsaglia and Zaman
665 // in report FSU-SCRI-87-50
666
667 // clock_t start;
668 int ii, jj;
669 static int i=96, j=32, itest=0, i1, i2, i3, i4, i5;
670 static double u[97], c, cd, cm, s, t;
671 static double uni;
672 int count1,count2,idum;
673 /* $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$ */
674 if (itest == 0) {
675 //*******************************************************
676 // following three lines if the seed to be provided by computer
677 // start = time(NULL);
678 // ii=start;
679 // jj=start;
680 //*******************************************************
681 //following two lines for fixed seed ( during testing only. Else
682 //use preceeing three lines
683 ii=8263;
684 jj=5726;
685 if(ii > 31328 ) ii = ii - ( ii / 31328 ) * 31328;
686 if(jj > 30081 ) jj = jj - ( jj / 30081 ) * 30081;
687 itest=itest+1;
688 if((( ii > 0 ) && ( ii <= 31328 )) && (( jj > 0 ) &&
689 ( jj <= 30081 ))){
690 i1=ii/177+2; i2=ii-(i1-2)*177+2; i3=jj/169+1; i4=jj-(i3-1)*169;
691 i4 = jj - (i3-1)*169;
692 count1=0;
693 while ( count1 < 97 ){
694 s=0.;
695 t=0.5;
696 count2=0;
697 while( count2 < 24 ){
698 idum=i1*i2/179;
699 idum=( i1*i2 - (i1*i2/179)*179 ) * i3;
700 i5=idum-(idum/179)*179;
701 i1=i2; i2=i3; i3=i5; idum=53*i4+1; i4=idum-(idum/169)*169;
702 if( i4*i5-((i4*i5)/64)*64 >= 32 ) s=s+t;
703 t=0.5*t;
704 count2=count2+1;
705 }
706 u[count1] = s;
707 count1 = count1 +1;
708 }
709 c = 362436./16777216.; cd = 7654321./16777216.;
710 cm = 16777213./16777216.;
711 }
712 else{
713 AliWarning("Wrong initialization");
714 }
715 }
716 else{
717 uni = u[i] - u[j];
718 if( uni < 0.) uni = uni + 1;
719 u[i] = uni;
720 i = i -1;
721 if( i < 0 ) i = 96;
722 j = j - 1;
723 if ( j < 0 ) j = 96;
724 c = c - cd;
725 if( c < 0. ) c = c+cm;
726 uni = uni-c ;
727 if( uni < 0. )uni = uni+1.;
728 }
729 return uni;
730}
731// ------------------------------------------------------------------------ //
732void AliPMDClusteringV1::SetEdepCut(Float_t decut)
733{
734 fCutoff = decut;
735}
736// ------------------------------------------------------------------------ //