WebSVN – f9daq – Blame – /cvi/apps/sa02_daq/macros/febana.cxx

Rev	Author	Line No.	Line
326	f9daq	1	#include <stdio.h>
		2	#include <stdlib.h>
		3	#include <TROOT.h>
		4	#include <TF1.h>
		5	#include <TH1F.h>
		6	#include <TH1D.h>
		7	#include <TH2D.h>
		8	#include <TCanvas.h>
		9	#include <TStyle.h>
		10	#include <TSystem.h>
		11	#include <TFile.h>
		12	#include <TDirectory.h>
		13	#include <TPaveText.h>
		14	#include <TStatistic.h>
		15	#include <TNamed.h>
		16	#include <TAxis.h>
		17	#include <TPDF.h>
		18	#include <TFitResult.h>
		19
		20
		21	int febana(int run){
		22	const int hid=1;
		23	char name[128];
		24	const char * hname = "h2d_0";
		25	int brd[4];
		26
		27	sprintf(name,"%s;%d",hname,hid); //you define histogram h2d_0;1 test pulse, h2d_0;2 offset
		28	TH2D h = (TH2D ) gDirectory->Get(name); //this tell you directory to your histogram
		29	//serialNumber = h->GetTitle();
		30	/******radeliti hočem serijsko številko******************/
		31	char b0[255], b1[255], b2[255], b3[255], b00[255], b01[255], b10[255], b11[255], b20[255], b21[255], b30[255], b31[255];
		32
		33	//sscanf(serialNumber,"%s%s%s%s",b0,b1,b2,b3);
		34	sscanf(h->GetTitle(),"%s%s%s%s",b0,b1,b2,b3);
		35	sscanf(b0, "%[^=]=%s", b00, b01); //b01 je serijska številka od borda0
		36	sscanf(b1, "%[^=]=%s", b10, b11); //b11 je serijska številka od borda1
		37	sscanf(b2, "%[^=]=%s", b20, b21); //b21 je serijska številka od borda2
		38	sscanf(b3, "%[^=]=%s", b30, b31); //b31 je serijska številka od borda3
		39	/*****************************************************************************/
		40	/******radeliti hočem serijsko številko boarda******************/
		41	for (int k=0;k<4;k++){
		42	sprintf(name,"vth1_%d_0",k); //you define histogram vth1_0_0;1
		43	TH2D * h0 = (TH2D *) gDirectory->Get(name); //this tell you directory to your histogram
		44	if (!h0) continue;
		45	sscanf(h0->GetTitle(),"%s%s%s%s sn=%d",&brd[k]);
		46	printf("sn = %d\n",brd[k]);
		47	}
		48	/*******************Ofset scanning****************************************/
		49	int nx=0;
		50	int imax=36;
		51
		52	for (int i=2;i<=imax;i++){
		53	sprintf(name,"h2d_0;%d",i);
		54	TH2D h2dp=(TH2D ) gDirectory->Get(name); // directory do grafoz z offset scanningom
		55	if (h2dp) nx++;
		56	}
		57
		58	TCanvas *c55= new TCanvas("c55","Offset scanning",1000,800); //definiramo canvase
		59	c55->Divide(8,4); //razdelimo canvase
		60
		61	TCanvas *ccoarse[4];
		62	TCanvas *cfine[4];
		63	for (int i=0;i<4;i++){
		64	sprintf(name,"ccoarse%d",i);
		65	ccoarse[i]= new TCanvas(name,name,1000,800);
		66	ccoarse[i]->Divide(4,4);
		67	sprintf(name,"cfine%d",i);
		68	cfine[i]= new TCanvas(name,name,1000,800);
		69	cfine[i]->Divide(4,4);
		70	}
		71
		72
		73
		74
		75	TH2D *hfeb[4];
		76	TH2D *hcoarsemean[4];
		77	TH2D *hfinemean[4];
		78	TH2D *hmean[4];
		79
		80	sprintf(name,"h2d_0;2");
		81	TH2D h2dz=(TH2D ) gDirectory->Get(name);
		82	if (!h2dz) {
		83	printf("Histogram %s not found.\n");
		84	return 0;
		85	}
		86
		87
		88	for (int n=0;n<4;n++){
		89	sprintf(name,"board%d", n);
		90
		91	hfeb[n]= new TH2D(name, name,h2dz->GetNbinsX()/4, -0.5,143.5, h2dz->GetNbinsY() , h2dz->GetYaxis()->GetXmin(), h2dz->GetYaxis()->GetXmax() );
		92	sprintf(name,"hcoarsemean_%d", n);
		93	hcoarsemean[n]= new TH2D(name,"Mean rough;HAPD ch;decoded offset",144,-0.5,143.5,16,-0.5,15.5);
		94	sprintf(name,"hmean_%d", n);
		95	hmean[n]= new TH2D(name,"Mean;HAPD ch;offset",144,-0.5,144,nx,-0.5,nx-0.5);
		96	hmean[n]->SetMinimum(300);
		97	hmean[n]->SetMaximum(700);
		98	sprintf(name,"hfinemean_%d", n);
		99	hfinemean[n]= new TH2D(name,"Mean fine;HAPD ch;decoded offset",144,-0.5,143.5,16,-0.5,15.5);
		100	}
		101
		102
		103
		104	int i0;
		105	int i01;
		106	for (int i=2;i<nx+2;i++){
		107
		108	sprintf(name,"h2d_0;%d",i);
		109	printf("%s\n",name);
		110	TH2D h2d=(TH2D ) gDirectory->Get(name);
		111	for (int x=0;x<h2d->GetNbinsX();x++){
		112	for (int y=0;y<h2d->GetNbinsY();y++){
		113	float val = h2d->GetBinContent(x+1,y+1);
		114	hfeb[x/144]->SetBinContent(x%144+1, y+1,val);
		115	}
		116	}
		117
		118	if(i<18){ //popravimo našo skalo za coarse scanning
		119	int j= (i-2)%8;
		120	int k= (i-2)/8;
		121	int j0= -(1-j/1)*1;
		122	int k0= (1-k/1)*8;
		123	i0=j0+k0+1;
		124	} else i0=50; //ker imamo še fine scannig, bo pri njih vrednost x-koordinate enaka 50 (za lažjo obdelovo podatkov)
		125
		126	if(i>17){ //popravimo našo skalo za fine scanning
		127	int j= (i-18)%8;
		128	int k= (i-18)/8;
		129	int j0= -(1-j/1)*1;
		130	int k0= (1-k/1)*8;
		131	i01=j0+k0+1;
		132	} else i01=50; //ker imamo še coarse scannig, bo pri njih vrednost x-koordinate enaka 50 (za lažjo obdelovo podatkov)
		133
		134	if (h2d){
		135	sprintf(name,"%s %s %s %s graf %d",b01, b11, b21, b31, i-1);
		136	h2d->SetTitle(name);
		137	if (i>1) {
		138	c55->cd(i-1);
		139	h2d->DrawCopy("colz"); //narišemo vse grafe on 4 boardov za Offset scanning
		140	}
		141	}
		142
		143	for (int board=0;board<4;board++){
		144	if (hfeb[board]){
		145	if (i>1&&i<18) {
		146	sprintf(name,"Coarse scanning board %d scan %d",brd[board], i-1);
		147	hfeb[board]->SetTitle(name);
		148	ccoarse[board]->cd(i-1);
		149	hfeb[board]->DrawCopy("colz"); //coarse offset scanning board0
		150	}else{
		151	sprintf(name,"Fine scanning board %d scan %d",brd[board], i-17);
		152	hfeb[board]->SetTitle(name);
		153	cfine[board]->cd(i-17);
		154	hfeb[board]->DrawCopy("colz"); //fine offset scanning board0
		155	}
		156
		157	TF1 *f = new TF1("fit","gaus", 0 , 1000); //definiraš gaussovski fit
		158
		159	for (int ch=0;ch<hfeb[board]->GetNbinsX();ch++){
		160
		161	TH1D *hy0 = hfeb[board]->ProjectionY("_py",ch+1,ch+1); //narediš projekcije za vsak kanal
		162	hy0->Fit(f,"QWWN"); //narediš fit čez projekcije
		163
		164	double mean = hy0->GetMean(); //prebereš mean
		165	hcoarsemean[board]->Fill(ch,i0,mean); //napolniš grafe
		166	hmean[board]->Fill(ch,i-2,mean);
		167	hfinemean[board]->Fill(ch,i01,mean);
		168
		169	}
		170	}
		171	}
		172
		173
		174
		175
		176	}
		177
		178	for (int board=0;board<4;board++){
		179	sprintf(name,"board %d.pdf", brd[board]);
		180	printf("board pri pdf %s\n",name);
		181	ccoarse[board]->Print(name,"pdf");
		182	cfine[board]->Print(name,"pdf");
		183	}
		184
		185
		186	/**************mean and slope together**************************/
		187
		188	TF1 *f0 = new TF1("mlin","pol1", 0 , 127); //linearni fit definiran za vse grafe
		189	TCanvas * cfit[4];
		190	TH1F *hpoolfine[4];
		191	TH1F *hfitcoarse[4];
		192	TH1F *hfitfine [4];
		193	TH1F *hpoolcoarse[4];
		194	for (int board=0;board<4;board++){
		195
		196	hcoarsemean[board]->FitSlicesY(f0);
		197	sprintf(name,"%s_1",hcoarsemean[board]->GetName());
		198	printf("%s\n",name);
		199	hfitcoarse[board] = ((TH1F * ) gDirectory->Get(name));
		200
		201	hfinemean[board]->FitSlicesY(f0);
		202	sprintf(name,"%s_1",hfinemean[board]->GetName());
		203	printf("%s\n",name);
		204	hfitfine[board] = ((TH1F * ) gDirectory->Get(name));
		205
		206	sprintf(name,"cfit%d",board);
		207	printf("%s\n",name);
		208	cfit[board]= new TCanvas(name,name,1000,800);
		209	cfit[board]->Divide(1,3);
		210	cfit[board]->cd(1);
		211	hmean[board]->ProjectionY("hprojection1_1",1,1)->Draw();
		212	hmean[board]->ProjectionY("hprojection1_3",3,3)->Draw("same");
		213	hmean[board]->ProjectionY("hprojection1_10",10,10)->Draw("same");
		214	hmean[board]->ProjectionY("hprojection1_15",15,15)->Draw("same");
		215
		216	cfit[board]->cd(3);
		217	gStyle->SetOptStat(1);
		218
		219	sprintf(name,"hpoolfine_%d",board);
		220	printf("%s\n",name);
		221	hpoolfine[board] = new TH1F(name,"Fine slope together",10,-1.5,-0.7);
		222	for (int ch=0;ch<hfitfine[board]->GetNbinsX();ch++){
		223	hpoolfine[board]->Fill(hfitfine[board]->GetBinContent(ch+1));
		224	}
		225	hpoolfine[board]->Draw();
		226
		227	cfit[board]->cd(2);
		228	gStyle->SetOptStat(1);
		229
		230	sprintf(name,"hpoolcoarse_%d",board);
		231	printf("%s\n",name);
		232	hpoolcoarse[board] = new TH1F(name,"Coarse slope together",10,-17,-10);
		233	for (int ch=0;ch<hfitcoarse[board]->GetNbinsX();ch++){
		234	hpoolcoarse[board]->Fill(hfitcoarse[board]->GetBinContent(ch+1));
		235	}
		236	hpoolcoarse[board]->Draw();
		237	sprintf(name,"board %d.pdf", brd[board]);
		238	printf("%s\n",name);
		239	//c20->Print(name,"pdf");
		240
		241	}
		242
		243	//return;
		244	/**************************OffsetVariation board0********************************************/
		245	TCanvas *c0coarse[4];
		246	TCanvas *c0fine[4];
		247
		248	for (int board=0;board<4;board++){
		249
		250
		251	sprintf(name,"hcoarsemean_%d",board);
		252	TH2D h0coarse=(TH2D ) gDirectory->Get(name);
		253	sprintf(name,"hfinemean_%d",board);
		254	TH2D h0fine=(TH2D ) gDirectory->Get(name);
		255	char nv[20];
		256	char opt[20];
		257	int first =0;
		258	sprintf(name,"c0coarse%d",board);
		259	c0coarse[board]= new TCanvas(name,name,1000,800);
		260	c0coarse[board]->Divide(4,2);
		261	sprintf(name,"c0fine%d",board);
		262	c0fine[board]= new TCanvas(name,name,1000,800);
		263	c0fine[board]->Divide(4,2);
		264	//return;
		265	for (int chip=0;chip<4; chip++){
		266	c0coarse[board]->cd(chip+1);
		267	first=0;
		268	for (int ch=0+chip36;ch<(36+chip36);ch++) {
		269	sprintf(nv,"hxc_%d",ch);
		270	TH1D* h0coarsep= h0coarse->ProjectionY(nv,ch+1,ch+1);
		271	//TFitResultPtr r0 = h0coarsep>Fit(f0,"SQN");
		272	//double chi0= r0->Chi2();
		273	if (first) sprintf(opt,"same"); else {
		274	h0coarsep->GetXaxis()->SetRangeUser(300,1000);
		275	sprintf(opt,"");
		276	}
		277	sprintf(name,"Coarse mean chip %d",chip);
		278	h0coarsep->SetTitle(name);
		279	h0coarsep->SetMinimum(350);
		280	h0coarsep->SetMaximum(750);
		281	h0coarsep->Draw(opt);
		282	first=1;
		283	}
		284	}
		285	gStyle->SetOptStat(1);
		286	for (int chip=0;chip<4;chip++){
		287	c0coarse[board]->cd(chip+5);
		288	sprintf(name,"hslopecoarse%dchip%d",board,chip);
		289	TH1F *hpool = new TH1F(name,name,10,-17,-10);
		290	for (int ch=0+chip36;ch<(36+chip36);ch++){
		291	hpool->Fill(hfitcoarse[board]->GetBinContent(ch+1));
		292	}
		293	hpool->Draw();
		294	}
		295
		296
		297	for (int chip=0;chip<4; chip++){
		298	c0fine[board]->cd(chip+1);
		299	first=0;
		300	for (int ch=0+chip36;ch<(36+chip36);ch++) {
		301	sprintf(nv,"hxf_%d",ch);
		302	TH1D* h0finep= h0fine->ProjectionY(nv,ch+1,ch+1);
		303	TFitResultPtr r0 = h0finep->Fit(f0,"SQN");
		304	double chi0= r0->Chi2();
		305	if (first) sprintf(opt,"same"); else {
		306	h0finep->GetXaxis()->SetRangeUser(300,1000);
		307	sprintf(opt,"");
		308	}
		309	sprintf(name,"Fine mean chip %d",chip);
		310	h0finep->SetTitle(name);
		311	h0finep->SetMinimum(400);
		312	h0finep->SetMaximum(600);
		313	h0finep->Draw(opt);
		314	first=1;
		315	}
		316	}
		317
		318
		319	for (int chip=0;chip<4;chip++){
		320	c0fine[board]->cd(chip+5);
		321	sprintf(name,"hslopefine%dchip%d",board,chip);
		322	TH1F *hpool = new TH1F(name,name,10,-1.5,-0.7);
		323	for (int ch=0+chip36;ch<(36+chip36);ch++){
		324	hpool->Fill(hfitfine[board]->GetBinContent(ch+1));
		325	}
		326	hpool->Draw();
		327	}
		328
		329
		330
		331	c0coarse[board]->Update();
		332	c0fine[board]->Update();
		333	/* sprintf(pngname,"C:\\home\\anze\\print\\scan\\Offset Variation\\%s %s.png",Offset0,b01);
		334	c0v->SaveAs(pngname, "png");*/
		335	sprintf(name,"board %d.pdf", brd[board]);
		336	c0coarse[board]->Print(name,"pdf");
		337	sprintf(name,"board %d.pdf)", brd[board]);
		338	c0fine[board]->Print(name,"pdf");
		339	}
		340
		341	/**********************Slope************************************************/
		342	/FILE fp1 = fopen("Slope vsi.txt","at");
		343	if (fp1!=NULL) {
		344	fprintf(fp1,"%s , %f , %f , %f , %f , %f , %f , %f , %f , %f , %f\n",b01,hpool0->GetMean(),hpool01->GetMean(), hpool0100->GetMean(), hpool0101->GetMean(), hpool0102->GetMean(), hpool0103->GetMean(), hpool0104->GetMean(), hpool0105->GetMean(), hpool0106->GetMean(), hpool0107->GetMean());
		345	fprintf(fp1,"%s , %f , %f , %f , %f , %f , %f , %f , %f , %f , %f\n",b11,hpool1->GetMean(),hpool11->GetMean(), hpool1110->GetMean(), hpool1111->GetMean(), hpool1112->GetMean(), hpool1113->GetMean(), hpool1114->GetMean(), hpool1115->GetMean(), hpool1116->GetMean(), hpool1117->GetMean());
		346	fprintf(fp1,"%s , %f , %f , %f , %f , %f , %f , %f , %f , %f , %f\n",b21,hpool2->GetMean(),hpool21->GetMean(), hpool2120->GetMean(), hpool2121->GetMean(), hpool2122->GetMean(), hpool2123->GetMean(), hpool2124->GetMean(), hpool2125->GetMean(), hpool2126->GetMean(), hpool2127->GetMean());
		347	fprintf(fp1,"%s , %f , %f , %f , %f , %f , %f , %f , %f , %f , %f\n",b31,hpool3->GetMean(),hpool31->GetMean(), hpool3130->GetMean(), hpool3131->GetMean(), hpool3132->GetMean(), hpool3133->GetMean(), hpool3134->GetMean(), hpool3135->GetMean(), hpool3136->GetMean(), hpool3137->GetMean());
		348	}
		349	fclose(fp1);
		350	/*********************************vsi nakloni iz vseh kanalov***********************************************/
		351	/*for(int ch=0;ch<144;ch++){
		352	FILE *fp2 = fopen("proba tocke.txt","at");
		353	if (fp2!=NULL) {
		354	//fprintf(fp2,"%s , %f , %f\n",b01,hfito10->GetBinContent(ch+1),hfito101->GetBinContent(ch+1));
		355	//fprintf(fp2,"%s , %f , %f\n",b11,hfito11->GetBinContent(ch+1),hfito111->GetBinContent(ch+1));
		356	//fprintf(fp2,"%s , %f , %f\n",b21,hfito12->GetBinContent(ch+1),hfito121->GetBinContent(ch+1));
		357	fprintf(fp2,"%s , %f , %f\n",b31,hfito13->GetBinContent(ch+1),hfito131->GetBinContent(ch+1)));
		358	}
		359	}
		360	/****************************************************************************************************/
		361	return 0;
		362	}

Subversion Repositories f9daq

(root)/cvi/apps/sa02_daq/macros/febana.cxx – Rev 326