// //
//-----------------------------------------------------//
-/*
- --------------------------------------------------------------------
- Code developed by S. C. Phatak, Institute of Physics,
+/* --------------------------------------------------------------------
+ Code developed by S. C. Phatak, Institute of Physics,
Bhubaneswar 751 005 ( phatak@iopb.res.in ) Given the energy deposited
( or ADC value ) in each cell of supermodule ( pmd or cpv ), the code
- builds up superclusters and breaks them into clusters. The input is
+ builds up superclusters and breaks them into clusters. The input is
in array fEdepCell[kNDIMX][kNDIMY] and cluster information is in array
- fClusters[5][5000]. integer fClno gives total number of clusters in the
+ fClusters[5][5000]. integer fClno gives total number of clusters in the
supermodule.
fEdepCell, fClno and fClusters are the only global ( public ) variables.
- Others are local ( private ) to the code.
-
+ Others are local ( private ) to the code.
At the moment, the data is read for whole detector ( all supermodules
and pmd as well as cpv. This will have to be modify later )
-
LAST UPDATE : October 23, 2002
------------------------------------------------------------------------
-*/
-
+-----------------------------------------------------------------------*/
#include "Riostream.h"
#include <TNtuple.h>
#include <TObjArray.h>
+#include <stdio.h>
+
#include "AliPMDcluster.h"
#include "AliPMDClustering.h"
-#include <stdio.h>
+#include "AliLog.h"
ClassImp(AliPMDClustering)
const Double_t AliPMDClustering::fgkSqroot3by2=0.8660254; // sqrt(3.)/2.
-AliPMDClustering::AliPMDClustering()
+AliPMDClustering::AliPMDClustering():
+ fCutoff(0.0)
{
- fDebug = 0;
- fCutoff = 0.0;
for(int i = 0; i < kNDIMX; i++)
{
for(int j = 0; j < kNDIMY; j++)
{
fCoord[0][i][j] = i+j/2.;
fCoord[1][i][j] = fgkSqroot3by2*j;
+ fEdepCell[i][j] = 0;
}
}
}
+// ------------------------------------------------------------------------ //
AliPMDClustering::~AliPMDClustering()
{
}
-
-void AliPMDClustering::DoClust(Double_t celladc[48][96], TObjArray *pmdcont)
+// ------------------------------------------------------------------------ //
+void AliPMDClustering::DoClust(Int_t idet, Int_t ismn, Double_t celladc[48][96], TObjArray *pmdcont)
{
// main function to call other necessary functions to do clustering
//
AliPMDcluster *pmdcl = 0;
-
- int i, i1, i2, j, nmx1, incr;
+ /*
+ int id and jd defined to read the input data.
+ It is assumed that for data we have 0 <= id <= 48
+ and 0 <= jd <=96
+ */
+ int i, i1, i2, j, nmx1, incr, id, jd;
double cutoff, ave;
- Float_t clusdata[5];
+ Float_t clusdata[7];
const float ktwobysqrt3 = 1.1547; // 2./sqrt(3.)
-
- for (i = 0; i < kNDIMX; i++)
+ for (id = 0; id < kNDIMXr; id++)
{
- for (j = 0; j < kNDIMY; j++)
+ for (jd = 0; jd < kNDIMYr; jd++)
{
- fEdepCell[i][j] = celladc[i][j];
+ j=jd;
+ i=id+(kNDIMYr/2-1)-(jd/2);
+ fEdepCell[i][j] = celladc[id][jd];
}
}
Order(); // order the data
- cutoff = fCutoff; // cutoff used to discard cells having ener. dep.
- ave=0.;
+ cutoff = fCutoff; // cutoff used to discard cells having ener. dep.
+ ave=0.;
nmx1=-1;
-
+
for(j=0;j<kNMX; j++)
{
i1 = fIord[0][j];
if (fEdepCell[i1][i2] > cutoff ) nmx1 = nmx1 + 1;
}
// nmx1 --- number of cells having ener dep >= cutoff
- if (fDebug == 1)
- {
- cout << " nmx1 " << nmx1 << endl;
- }
+
+ AliDebug(1,Form("Number of cells having energy >= %f are %d",cutoff,nmx1));
+
+ // if (nmx1 == 0 | nmx1 == -1) return;
+
+ if (nmx1 == 0) nmx1 = 1;
ave=ave/nmx1;
- if (fDebug == 1)
- {
- cout <<"kNMX " << kNMX << " nmx1 " << nmx1<< " ave "<<ave<<
- " cutoff " << cutoff << endl;
- }
-
+
+ AliDebug(1,Form("Number of cells in a SuperM = %d and Average = %f",
+ kNMX,ave));
+
incr = CrClust(ave, cutoff, nmx1);
-
RefClust(incr);
+
+ AliDebug(1,Form("Detector Plane = %d Serial Module No = %d Number of clusters = %d",idet, ismn, fClno));
- if (fDebug == 1)
- {
- cout << "fClno " << fClno << endl;
- }
-
- for(i1=0; i1<fClno; i1++)
+ for(i1=0; i1<=fClno; i1++)
{
Float_t cluXC = (Float_t) fClusters[0][i1];
Float_t cluYC = (Float_t) fClusters[1][i1];
Float_t cluRAD = (Float_t) fClusters[4][i1];
Float_t cluY0 = ktwobysqrt3*cluYC;
Float_t cluX0 = cluXC - cluY0/2.;
- clusdata[0] = cluX0;
+ //
+ // Cluster X centroid is back transformed
+ //
+ clusdata[0] = cluX0 - (48-1) + cluY0/2.;
clusdata[1] = cluY0;
clusdata[2] = cluADC;
clusdata[3] = cluCELLS;
clusdata[4] = cluRAD;
-
- pmdcl = new AliPMDcluster(clusdata);
+
+ pmdcl = new AliPMDcluster(idet, ismn, clusdata);
pmdcont->Add(pmdcl);
}
- delete pmdcl;
-
}
-
+// ------------------------------------------------------------------------ //
void AliPMDClustering::Order()
{
// Sorting algorithm
// sorts the ADC values from higher to lower
//
- double dd[kNMX], adum;
- // matrix fEdepCell converted into
+ double dd[kNMX];
+ // matrix fEdepCell converted into
// one dimensional array dd. adum a place holder for double
- int i, j, i1, i2, iord1[kNMX], itst, idum;
- // information of
+ int i, j, i1, i2, iord1[kNMX];
+ // information of
// ordering is stored in iord1, original array not ordered
//
// define arrays dd and iord1
dd[i] = fEdepCell[i1][i2];
}
}
- // sort and store sorting information in iord1
- for(j=1; j < kNMX; j++)
- {
- itst = 0;
- adum = dd[j];
- idum = iord1[j];
- for(i1=0; i1 < j ; i1++)
- {
- if(adum > dd[i1] && itst == 0)
- {
- itst = 1;
- for(i2=j-1; i2 >= i1 ; i2=i2--)
- {
- dd[i2+1] = dd[i2];
- iord1[i2+1] = iord1[i2];
- }
- dd[i1] = adum;
- iord1[i1] = idum;
- }
- }
- }
+ // sort and store sorting information in iord1
+// for(j=1; j < kNMX; j++)
+// {
+// itst = 0;
+// adum = dd[j];
+// idum = iord1[j];
+// for(i1=0; i1 < j ; i1++)
+// {
+// if(adum > dd[i1] && itst == 0)
+// {
+// itst = 1;
+// for(i2=j-1; i2 >= i1 ; i2=i2--)
+// {
+// dd[i2+1] = dd[i2];
+// iord1[i2+1] = iord1[i2];
+// }
+// dd[i1] = adum;
+// iord1[i1] = idum;
+// }
+// }
+// }
+
+ TMath::Sort(kNMX,dd,iord1); //PH Using much better algorithm...
// store the sorted information in fIord for later use
for(i=0; i<kNMX; i++)
{
j = iord1[i];
- i2 = j/kNDIMX;
- i1 = j-i2*kNDIMX;
- fIord[0][i]=i1;
+ i2 = j/kNDIMX;
+ i1 = j-i2*kNDIMX;
+ fIord[0][i]=i1;
fIord[1][i]=i2;
}
}
-
+// ------------------------------------------------------------------------ //
int AliPMDClustering::CrClust(double ave, double cutoff, int nmx1)
{
// Does crude clustering
int i,j,k,id1,id2,icl, numcell, clust[2][5000];
int jd1,jd2, icell, cellcount;
static int neibx[6]={1,0,-1,-1,0,1}, neiby[6]={0,1,1,0,-1,-1};
- // neibx and neiby define ( incremental ) (i,j) for the neighbours of a
+ // neibx and neiby define ( incremental ) (i,j) for the neighbours of a
// cell. There are six neighbours.
// cellcount --- total number of cells having nonzero ener dep
// numcell --- number of cells in a given supercluster
// ofstream ofl0("cells_loc",ios::out);
- // initialize fInfocl[2][kNDIMX][kNDIMY]
+ // initialize fInfocl[2][kNDIMX][kNDIMY]
- if (fDebug == 1)
- {
- printf(" *** Inside CrClust ** kNMX = %d nmx1 = %d kNDIMX = %d kNDIMY = %d ave = %f cutoff = %f\n",
- kNMX,nmx1,kNDIMX,kNDIMY,ave,cutoff);
- }
+ AliDebug(1,Form("kNMX = %d nmx1 = %d kNDIMX = %d kNDIMY = %d ave = %f cutoff = %f",kNMX,nmx1,kNDIMX,kNDIMY,ave,cutoff));
+
for (j=0; j < kNDIMX; j++){
for(k=0; k < kNDIMY; k++){
- fInfocl[0][j][k] = 0;
+ fInfocl[0][j][k] = 0;
fInfocl[1][j][k] = 0;
}
}
for(i=0; i < kNMX; i++){
fInfcl[0][i] = -1;
- id1=fIord[0][i];
+ id1=fIord[0][i];
id2=fIord[1][i];
if(fEdepCell[id1][id2] <= cutoff){fInfocl[0][id1][id2]=-1;}
}
// ---------------------------------------------------------------
- // crude clustering begins. Start with cell having largest adc
+ // crude clustering begins. Start with cell having largest adc
// count and loop over the cells in descending order of adc count
// ---------------------------------------------------------------
icl=-1;
cellcount=-1;
for(icell=0; icell <= nmx1; icell++){
- id1=fIord[0][icell];
- id2=fIord[1][icell];
+ id1=fIord[0][icell];
+ id2=fIord[1][icell];
if(fInfocl[0][id1][id2] == 0 ){
// ---------------------------------------------------------------
- // icl -- cluster #, numcell -- # of cells in it, clust -- stores
- // coordinates of the cells in a cluster, fInfocl[0][i1][i2] is 1 for
- // primary and 2 for secondary cells,
+ // icl -- cluster #, numcell -- # of cells in it, clust -- stores
+ // coordinates of the cells in a cluster, fInfocl[0][i1][i2] is 1 for
+ // primary and 2 for secondary cells,
// fInfocl[1][i1][i2] stores cluster #
// ---------------------------------------------------------------
- icl=icl+1;
- numcell=0;
- cellcount=cellcount+1;
- fInfocl[0][id1][id2]=1;
+ icl=icl+1;
+ numcell=0;
+ cellcount = cellcount + 1;
+ fInfocl[0][id1][id2]=1;
fInfocl[1][id1][id2]=icl;
- fInfcl[0][cellcount]=icl;
- fInfcl[1][cellcount]=id1;
+ fInfcl[0][cellcount]=icl;
+ fInfcl[1][cellcount]=id1;
fInfcl[2][cellcount]=id2;
-
clust[0][numcell]=id1;
clust[1][numcell]=id2;
for(i=1; i<5000; i++)clust[0][i]=0;
// check for adc count in neib. cells. If ne 0 put it in this clust
// ---------------------------------------------------------------
for(i=0; i<6; i++){
- jd1=id1+neibx[i];
+ jd1=id1+neibx[i];
jd2=id2+neiby[i];
- if( (jd1 >= 0 && jd1 < kNDIMX) && (jd2 >= 0 && jd2 < kNDIMY) &&
+ if( (jd1 >= 0 && jd1 < kNDIMX) && (jd2 >= 0 && jd2 < kNDIMY) &&
fInfocl[0][jd1][jd2] == 0){
numcell=numcell+1;
- fInfocl[0][jd1][jd2]=2;
+ fInfocl[0][jd1][jd2]=2;
fInfocl[1][jd1][jd2]=icl;
clust[0][numcell]=jd1;
clust[1][numcell]=jd2;
cellcount=cellcount+1;
- fInfcl[0][cellcount]=icl;
- fInfcl[1][cellcount]=jd1;
+ fInfcl[0][cellcount]=icl;
+ fInfcl[1][cellcount]=jd1;
fInfcl[2][cellcount]=jd2;
}
}
// ---------------------------------------------------------------
- // check adc count for neighbour's neighbours recursively and
+ // check adc count for neighbour's neighbours recursively and
// if nonzero, add these to the cluster.
// ---------------------------------------------------------------
for(i=1;i < 5000;i++){
if(clust[0][i] != 0){
- id1=clust[0][i];
+ id1=clust[0][i];
id2=clust[1][i];
for(j=0; j<6 ; j++){
- jd1=id1+neibx[j];
+ jd1=id1+neibx[j];
jd2=id2+neiby[j];
- if( (jd1 >= 0 && jd1 < kNDIMX) && (jd2 >= 0 && jd2 < kNDIMY) &&
+ if( (jd1 >= 0 && jd1 < kNDIMX) && (jd2 >= 0 && jd2 < kNDIMY) &&
fInfocl[0][jd1][jd2] == 0 ){
- fInfocl[0][jd1][jd2] = 2;
+ fInfocl[0][jd1][jd2] = 2;
fInfocl[1][jd1][jd2] = icl;
- numcell = numcell + 1;
+ numcell = numcell + 1;
clust[0][numcell] = jd1;
clust[1][numcell] = jd2;
cellcount = cellcount+1;
- fInfcl[0][cellcount] = icl;
- fInfcl[1][cellcount] = jd1;
+ fInfcl[0][cellcount] = icl;
+ fInfcl[1][cellcount] = jd1;
fInfcl[2][cellcount] = jd2;
}
}
}
}
// for(icell=0; icell<=cellcount; icell++){
- // ofl0 << fInfcl[0][icell] << " " << fInfcl[1][icell] << " " <<
+ // ofl0 << fInfcl[0][icell] << " " << fInfcl[1][icell] << " " <<
// fInfcl[2][icell] << endl;
// }
return cellcount;
}
-
+// ------------------------------------------------------------------------ //
void AliPMDClustering::RefClust(int incr)
{
// Does the refining of clusters
// Takes the big patch and does gaussian fitting and
// finds out the more refined clusters
//
- int i, j, k, i1, i2, id, icl, ncl[4500], iord[4500], itest;
+ int i, j, k, i1, i2, id, icl, ncl[4500], iord[4500], itest;
int ihld;
int ig, nsupcl, lev1[20], lev2[20];
double x[4500], y[4500], z[4500], x1, y1, z1, x2, y2, z2, dist;
for(i=0; i<4500; i++){ncl[i]=-1;}
for(i=0; i<incr; i++){
if(fInfcl[0][i] != nsupcl){ nsupcl=nsupcl+1; }
+ if (nsupcl > 4500) {
+ AliWarning("RefClust: Too many superclusters!");
+ nsupcl = 4500;
+ break;
+ }
ncl[nsupcl]=ncl[nsupcl]+1;
}
- if (fDebug == 1)
- {
- cout << " # of cells " <<incr+1 << " # of superclusters " << nsupcl+1
- << endl;
- }
+
+ AliDebug(1,Form("Number of cells = %d Number of Superclusters = %d",
+ incr+1,nsupcl+1));
+
id=-1;
icl=-1;
for(i=0; i<nsupcl; i++){
- if(ncl[i] == 0){
- id=id+1;
+ if(ncl[i] == 0){
+ id=id+1;
icl=icl+1;
// one cell super-clusters --> single cluster
// cluster center at the centyer of the cell
// cluster radius = half cell dimension
- fClno = fClno + 1;
- i1 = fInfcl[1][id];
+ if (fClno >= 5000) {
+ AliWarning("RefClust: Too many clusters! more than 5000");
+ return;
+ }
+ fClno = fClno + 1;
+ i1 = fInfcl[1][id];
i2 = fInfcl[2][id];
- fClusters[0][fClno] = fCoord[0][i1][i2];
+ fClusters[0][fClno] = fCoord[0][i1][i2];
fClusters[1][fClno] = fCoord[1][i1][i2];
- fClusters[2][fClno] = fEdepCell[i1][i2];
- fClusters[3][fClno] = 1.;
+ fClusters[2][fClno] = fEdepCell[i1][i2];
+ fClusters[3][fClno] = 1.;
fClusters[4][fClno] = 0.5;
- //ofl1 << icl << " " << fCoord[0][i1][i2] << " " << fCoord[1][i1][i2] <<
- //" " << fEdepCell[i1][i2] << " " << fClusters[3][fClno] <<endl;
+ //ofl1 << icl << " " << fCoord[0][i1][i2] << " " << fCoord[1][i1][i2] <<
+ //" " << fEdepCell[i1][i2] << " " << fClusters[3][fClno] <<endl;
}else if(ncl[i] == 1){
// two cell super-cluster --> single cluster
// cluster center is at ener. dep.-weighted mean of two cells
// cluster radius == half cell dimension
- id = id + 1;
+ id = id + 1;
icl = icl+1;
- fClno = fClno+1;
- i1 = fInfcl[1][id];
- i2 = fInfcl[2][id];
+ if (fClno >= 5000) {
+ AliWarning("RefClust: Too many clusters! more than 5000");
+ return;
+ }
+ fClno = fClno+1;
+ i1 = fInfcl[1][id];
+ i2 = fInfcl[2][id];
x1 = fCoord[0][i1][i2];
- y1 = fCoord[1][i1][i2];
+ y1 = fCoord[1][i1][i2];
z1 = fEdepCell[i1][i2];
- id = id+1;
- i1 = fInfcl[1][id];
+ id = id+1;
+ i1 = fInfcl[1][id];
i2 = fInfcl[2][id];
- x2 = fCoord[0][i1][i2];
- y2 = fCoord[1][i1][i2];
+ x2 = fCoord[0][i1][i2];
+ y2 = fCoord[1][i1][i2];
z2 = fEdepCell[i1][i2];
- fClusters[0][fClno] = (x1*z1+x2*z2)/(z1+z2);
+ fClusters[0][fClno] = (x1*z1+x2*z2)/(z1+z2);
fClusters[1][fClno] = (y1*z1+y2*z2)/(z1+z2);
- fClusters[2][fClno] = z1+z2;
- fClusters[3][fClno] = 2.;
+ fClusters[2][fClno] = z1+z2;
+ fClusters[3][fClno] = 2.;
fClusters[4][fClno] = 0.5;
//ofl1 << icl << " " << fClusters[0][fClno] << " " << fClusters[1][fClno]
- // << " " << fClusters[2][fClno] << " " <<fClusters[3][fClno] <<endl;
- }else{
-
- id = id + 1;
+ // << " " << fClusters[2][fClno] << " " <<fClusters[3][fClno] <<endl;
+ }
+ else{
+ id = id + 1;
iord[0] = 0;
- // super-cluster of more than two cells - broken up into smaller
- // clusters gaussian centers computed. (peaks separated by > 1 cell)
+ // super-cluster of more than two cells - broken up into smaller
+ // clusters gaussian centers computed. (peaks separated by > 1 cell)
// Begin from cell having largest energy deposited This is first
// cluster center
- i1 = fInfcl[1][id];
+ i1 = fInfcl[1][id];
i2 = fInfcl[2][id];
- x[0] = fCoord[0][i1][i2];
- y[0] = fCoord[1][i1][i2];
+ x[0] = fCoord[0][i1][i2];
+ y[0] = fCoord[1][i1][i2];
z[0] = fEdepCell[i1][i2];
iord[0] = 0;
for(j=1;j<=ncl[i];j++){
id = id + 1;
- i1 = fInfcl[1][id];
+ i1 = fInfcl[1][id];
i2 = fInfcl[2][id];
iord[j] = j;
- x[j] = fCoord[0][i1][i2];
- y[j] = fCoord[1][i1][i2];
+ x[j] = fCoord[0][i1][i2];
+ y[j] = fCoord[1][i1][i2];
z[j] = fEdepCell[i1][i2];
}
- // arranging cells within supercluster in decreasing order
+ // arranging cells within supercluster in decreasing order
for(j=1;j<=ncl[i];j++){
itest=0;
ihld=iord[j];
}
}
-
- // compute the number of Gaussians and their centers ( first
- // guess )
+ // compute the number of Gaussians and their centers ( first
+ // guess )
// centers must be separated by cells having smaller ener. dep.
// neighbouring centers should be either strong or well-separated
ig=0;
- xc[ig]=x[iord[0]];
- yc[ig]=y[iord[0]];
+ xc[ig]=x[iord[0]];
+ yc[ig]=y[iord[0]];
zc[ig]=z[iord[0]];
for(j=1;j<=ncl[i];j++){
- itest=-1;
- x1=x[iord[j]];
+ itest=-1;
+ x1=x[iord[j]];
y1=y[iord[j]];
for(k=0;k<=ig;k++){
- x2=xc[k]; y2=yc[k];
+ x2=xc[k]; y2=yc[k];
rr=Distance(x1,y1,x2,y2);
if( rr >= 1.1 && rr < 1.8 && z[iord[j]] > zc[k]/4.)
itest=itest+1;
if( rr >= 1.8 && rr < 2.1 && z[iord[j]] > zc[k]/10.)
itest=itest+1;
if( rr >= 2.1)itest=itest+1;
- }
+ }
if(itest == ig){
- ig=ig+1;
- xc[ig]=x1;
- yc[ig]=y1;
+ ig=ig+1;
+ xc[ig]=x1;
+ yc[ig]=y1;
zc[ig]=z[iord[j]];
}
}
GaussFit(ncl[i], ig, x[0], y[0] ,z[0], xc[0], yc[0], zc[0], rc[0]);
icl=icl+ig+1;
// compute the number of cells belonging to each cluster.
- // cell is shared between several clusters ( if they are equidistant
+ // cell is shared between several clusters ( if they are equidistant
// from it ) in the ratio of cluster energy deposition
for(j=0; j<=ig; j++){
cells[j]=0.;
}
if(ig > 0){
for(j=0; j<=ncl[i]; j++){
- lev1[0]=0;
+ lev1[0]=0;
lev2[0]=0;
for(k=0; k<=ig; k++){
dist=Distance(x[j], y[j], xc[k], yc[k]);
if(dist < sqrt(3.) ){
- lev1[0]++;
- i1=lev1[0];
+ lev1[0]++;
+ i1=lev1[0];
lev1[i1]=k;
}else{
if(dist < 2.1){
- lev2[0]++;
- i1=lev2[0];
+ lev2[0]++;
+ i1=lev2[0];
lev2[i1]=k;
}
}
}
}
for(j=0; j<=ig; j++){
- fClno = fClno + 1;
- fClusters[0][fClno] = xc[j];
- fClusters[1][fClno] = yc[j];
+ if (fClno >= 5000) {
+ AliWarning("RefClust: Too many clusters! more than 5000");
+ return;
+ }
+ fClno = fClno + 1;
+ fClusters[0][fClno] = xc[j];
+ fClusters[1][fClno] = yc[j];
fClusters[2][fClno] = zc[j];
fClusters[4][fClno] = rc[j];
if(ig == 0){
}
}
}
-
+// ------------------------------------------------------------------------ //
void AliPMDClustering::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)
{
// Does gaussian fitting
//
- int i, j, i1, i2, jmax, novar, idd, jj;
- double xx[4500], yy[4500], zz[4500], xxc[4500], yyc[4500];
+ int i, j, i1, i2, novar, idd, jj;
+ double xx[4500], yy[4500], zz[4500], xxc[4500], yyc[4500];
double a[4500], b[4500], c[4500], d[4500], ha[4500], hb[4500];
double hc[4500], hd[4500], zzc[4500], rrc[4500];
int neib[4500][50];
double sum, dx, dy, str, str1, aint, sum1, rr, dum;
double x1, x2, y1, y2;
- str = 0.;
- str1 = 0.;
- rr = 0.3;
+ str = 0.;
+ str1 = 0.;
+ rr = 0.3;
novar = 0;
j = 0; // Just put not to see the compiler warning, BKN
for(i=0; i<=ncell; i++)
{
- xx[i] = *(&x+i);
- yy[i] = *(&y+i);
+ xx[i] = *(&x+i);
+ yy[i] = *(&y+i);
zz[i] = *(&z+i);
str = str + zz[i];
}
for(i=0; i<=nclust; i++)
{
- xxc[i] = *(&xc+i);
- yyc[i] = *(&yc+i);
- zzc[i] = *(&zc+i);
- str1 = str1 + zzc[i];
+ xxc[i] = *(&xc+i);
+ yyc[i] = *(&yc+i);
+ zzc[i] = *(&zc+i);
+ str1 = str1 + zzc[i];
rrc[i] = 0.5;
}
for(i=0; i<=nclust; i++)
{
zzc[i] = str/str1*zzc[i];
- ha[i] = xxc[i];
- hb[i] = yyc[i];
- hc[i] = zzc[i];
+ ha[i] = xxc[i];
+ hb[i] = yyc[i];
+ hc[i] = zzc[i];
hd[i] = rrc[i];
- x1 = xxc[i];
+ x1 = xxc[i];
y1 = yyc[i];
}
for(i=0; i<=ncell; i++){
- idd=0;
- x1=xx[i];
+ idd=0;
+ x1=xx[i];
y1=yy[i];
for(j=0; j<=nclust; j++){
- x2=xxc[j];
+ x2=xxc[j];
y2=yyc[j];
if(Distance(x1,y1,x2,y2) <= 3.){ idd=idd+1; neib[i][idd]=j; }
}
-
neib[i][0]=idd;
}
sum=0.;
for(i1=0; i1<=ncell; i1++){
- aint=0.;
+ aint=0.;
idd=neib[i1][0];
for(i2=1; i2<=idd; i2++){
jj=neib[i1][i2];
- dx=xx[i1]-xxc[jj];
- dy=yy[i1]-yyc[jj];
+ dx=xx[i1]-xxc[jj];
+ dy=yy[i1]-yyc[jj];
dum=rrc[j]*rrc[jj]+rr*rr;
aint=aint+exp(-(dx*dx+dy*dy)/dum)*zzc[idd]*rr*rr/dum;
}
sum=sum+(aint-zz[i1])*(aint-zz[i1])/str;
}
- jmax=nclust*1000;
- if(nclust > 20)jmax=20000;
- for(j=0; j<jmax; j++){
+// jmax=nclust*1000;
+// if(nclust > 20)jmax=20000;
+// for(j=0; j<jmax; j++){
str1=0.;
for(i=0; i<=nclust; i++){
- a[i]=xxc[i]+0.6*(Ranmar()-0.5);
+ a[i]=xxc[i]+0.6*(Ranmar()-0.5);
b[i]=yyc[i]+0.6*(Ranmar()-0.5);
- c[i]=zzc[i]*(1.+(Ranmar()-0.5)*0.2);
+ c[i]=zzc[i]*(1.+(Ranmar()-0.5)*0.2);
str1=str1+zzc[i];
d[i]=rrc[i]*(1.+(Ranmar()-0.5)*0.1);
if(d[i] < 0.25)d[i]=0.25;
for(i=0; i<=nclust; i++){ c[i]=c[i]*str/str1; }
sum1=0.;
for(i1=0; i1<=ncell; i1++){
- aint=0.;
+ aint=0.;
idd=neib[i1][0];
for(i2=1; i2<=idd; i2++){
jj=neib[i1][i2];
- dx=xx[i1]-a[jj];
- dy=yy[i1]-b[jj];
+ dx=xx[i1]-a[jj];
+ dy=yy[i1]-b[jj];
dum=d[jj]*d[jj]+rr*rr;
aint=aint+exp(-(dx*dx+dy*dy)/dum)*c[i2]*rr*rr/dum;
}
if(sum1 < sum){
for(i2=0; i2<=nclust; i2++){
- xxc[i2]=a[i2];
- yyc[i2]=b[i2];
- zzc[i2]=c[i2];
- rrc[i2]=d[i2];
+ xxc[i2]=a[i2];
+ yyc[i2]=b[i2];
+ zzc[i2]=c[i2];
+ rrc[i2]=d[i2];
sum=sum1;
-
}
}
- }
+// }
for(j=0; j<=nclust; j++){
- *(&xc+j)=xxc[j];
- *(&yc+j)=yyc[j];
- *(&zc+j)=zzc[j];
+ *(&xc+j)=xxc[j];
+ *(&yc+j)=yyc[j];
+ *(&zc+j)=zzc[j];
*(&rc+j)=rrc[j];
}
}
-
-
+// ------------------------------------------------------------------------ //
double AliPMDClustering::Distance(double x1, double y1, double x2, double y2)
{
return sqrt((x1-x2)*(x1-x2) + (y1-y2)*(y1-y2));
}
-
+// ------------------------------------------------------------------------ //
double AliPMDClustering::Ranmar() const
{
// Universal random number generator proposed by Marsaglia and Zaman
if(ii > 31328 ) ii = ii - ( ii / 31328 ) * 31328;
if(jj > 30081 ) jj = jj - ( jj / 30081 ) * 30081;
itest=itest+1;
- if((( ii > 0 ) && ( ii <= 31328 )) && (( jj > 0 ) &&
+ if((( ii > 0 ) && ( ii <= 31328 )) && (( jj > 0 ) &&
( jj <= 30081 ))){
- i1=ii/177+2; i2=ii-(i1-2)*177+2; i3=jj/169+1; i4=jj-(i3-1)*169;
+ i1=ii/177+2; i2=ii-(i1-2)*177+2; i3=jj/169+1; i4=jj-(i3-1)*169;
i4 = jj - (i3-1)*169;
count1=0;
while ( count1 < 97 ){
u[count1] = s;
count1 = count1 +1;
}
- c = 362436./16777216.; cd = 7654321./16777216.;
+ c = 362436./16777216.; cd = 7654321./16777216.;
cm = 16777213./16777216.;
}
else{
- cout << " wrong initialization " << endl;
+ AliWarning("Wrong initialization");
}
}
else{
uni = u[i] - u[j];
if( uni < 0.) uni = uni + 1;
- u[i] = uni;
+ u[i] = uni;
i = i -1;
if( i < 0 ) i = 96;
j = j - 1;
if( uni < 0. )uni = uni+1.;
}
return uni;
-}
-
+}
+// ------------------------------------------------------------------------ //
void AliPMDClustering::SetEdepCut(Float_t decut)
{
fCutoff = decut;
}
-void AliPMDClustering::SetDebug(Int_t idebug)
-{
- fDebug = idebug;
-}
+// ------------------------------------------------------------------------ //