// This macro creates a fake MCerPhotEvt container (with some clusters // that simulate the starfield seen by the DC currents) and then applies // the image cleaning and the Hillas algorithm to recognize and classify // the clusters. // void test_findstar(); { // Empty container and task lists MParList plist; MTaskList tlist; // cout << "0" <SetNumPhotons(0.); switch (pixid) { case 10: dcpix->SetNumPhotons(1.5); case 3: dcpix->SetNumPhotons(1.1); case 9: dcpix->SetNumPhotons(1.1); case 22: dcpix->SetNumPhotons(1.1); case 23: dcpix->SetNumPhotons(1.1); case 24: dcpix->SetNumPhotons(1.1); case 11: dcpix->SetNumPhotons(1.1); }; }; // end loop over pixels if (!(FindStartPixels(DCEvt, startpixs, geom))) cout << "Error calling the FindStartPixels function!!" << endl; return; }; Int_t FindStartPixels(MCerPhotEvt *evt, TArrayF *startpixs, MGeomCam *geom) { // look for all the pixels with a DC higher than the DC of neighbour pixels // loop over all pixels MCerPhotEvtIter Next(evt, kFALSE); for (Int_t pixid=0; pixidGetNumPhotons(); // DC of current pixel // look for the max DC in the neighbors pixels Float_t macDC = 0; for (Int_t j=0; jGetNumPhotons() > maxDC) maxDC = evt[pix.GetNeighbor(j)]->GetNumPhotons(); // a starting pixel was found: it is added to the array and the pointer // to the array is increased by 1 if ( currDC > maxDC) *(startpixs++) = currDC; } return 1; } Int_t FindCluster(Int_t startpix, Int_t cluster, MGeomCam *geom) { return 1; } ;