/***********************************************************************//**
* @brief Read response table from FITS table HDU
*
* @param[in] table Response table.
*
* Reads CTA response table information from a FITS table. The FITS table
* is expected to have a single row, and axes and parameter information are
* found in vector columns. Axes information is expected to be placed
* before parameter information.
*
* Each axis is defined by two vector columns of equal width, describing the
* lower and upper limits for each bin. The column names for this boundary
* information terminates by "_LO" and "HI", respectively (upper case). It
* is expected that the "_LO" column preceeds the "_HI" column.
*
* Following the axes columns are parameter columns of equal width. The width
* of each parameter column is given by the product of the lengths of all
* axes. It is furthermore expected that the first axis is the most rapidely
* varying index of the vector.
*
* In case that the HDU table pointer is not valid (i.e. NULL), this method
* clears the objects and does nothing else.
***************************************************************************/
void GCTAResponseTable::read(const GFitsTable& table)
{
// Clear instance
clear();
// Read column names
read_colnames(table);
// Read axes
read_axes(table);
// Read parameter cubes
read_pars(table);
// Return
return;
}
int main()
{
read_pars("analysis_pars");
read_ensemble_pars(base_path,T,TSEP,ibeta,nmass,mass,iml_un,nlight,ntheta,theta,ist_th,njack,data_list_file);
TH=L=T/2;
//we stick to the light-heavy
int im_spec=0;
//load the 2 points and fits M and Z
jack M[nmass];
jack Z[nmass];
for(int im_S0=0;im_S0<nmass;im_S0++)
{
int ith_S0=ist_th;
fit_ZM_2pts(M[im_S0],Z[im_S0],im_spec,im_S0,ith_S0);
}
ofstream FT_file("FT.dat");
ofstream FP_file("FP.dat");
ofstream FM_file("FM.dat");
ofstream F0_file("F0.dat");
FILE *Q2_file=open_file("Q2_combo","w");
//loop over all the theta combination
for(int ith_S1=0;ith_S1<ntheta;ith_S1++)
for(int ith_S0=ith_S1;ith_S0<ntheta;ith_S0++)
{
//compute energy
jack E_source=Eth(M[gen_im_S0],ith_S0);
jack E_sink=Eth(M[gen_im_S1],ith_S1);
//construct time dependance
jvec time_dep(T,njack);
for(int t=0;t<T;t++)
{
jack coef=Z[gen_im_S0]*Z[gen_im_S1]/sqrt(2*E_source*2*E_sink);
jack forw,back;
if(t<TSEP)
{
forw=exp(-E_source*t-E_sink*(TSEP-t));
back=exp(-E_source*(T-t)-E_sink*(T-(TSEP-t)));
}
else
{
forw=exp(-E_source*(T-t)-E_sink*(t-TSEP));
back=exp(-E_source*t-E_sink*(T-(t-TSEP)));
}
time_dep[t]=coef*(forw+back);
}
//loop over matrix element
int iV0=0,iVK=1,iTK=2;
char MEL_name[3][4]={"V0","VK","TK"};
jack MEL[3];
jvec MEL_corr[3];
for(int iMEL=0;iMEL<3;iMEL++)
{
//load 3pts
jvec P5MELP5;
switch(iMEL)
{
case 0:P5MELP5=load_P5V0P5(gen_im_S0,ith_S0,gen_im_S1,ith_S1);break;
case 1:P5MELP5=load_P5VKP5(gen_im_S0,ith_S0,gen_im_S1,ith_S1);break;
case 2:P5MELP5=load_P5TKP5(gen_im_S0,ith_S0,gen_im_S1,ith_S1);break;
}
P5MELP5.subset(1,TSEP).print_to_file(combine("P5%sP5/%02d_%d_%02d_%d.xmg",MEL_name[iMEL],gen_im_S0,ith_S0,gen_im_S1,ith_S1).c_str());
time_dep.subset(1,TSEP).print_to_file(combine("time_dep/%02d_%d_%02d_%d.xmg",gen_im_S0,ith_S0,gen_im_S1,ith_S1).c_str());
//compute remotion of time dependance
MEL_corr[iMEL]=P5MELP5/time_dep;
MEL[iMEL]=constant_fit(MEL_corr[iMEL].subset(1,TSEP),tmin_MEL,tmax_MEL,combine("%s/%02d_%d_%02d_%d.xmg",MEL_name[iMEL],gen_im_S0,ith_S0,gen_im_S1,ith_S1).c_str());
}
//ratios
jvec VK_fr_TK_corr=MEL_corr[iVK]/MEL_corr[iTK];
jack VK_fr_TK=constant_fit(VK_fr_TK_corr.subset(1,TSEP),tmin_MEL,tmax_MEL,combine("VK_fr_TK/%02d_%d_%02d_%d.xmg",gen_im_S0,ith_S0,gen_im_S1,ith_S1).c_str());
jvec V0_fr_TK_corr=MEL_corr[iV0]/MEL_corr[iTK];
jack V0_fr_TK=constant_fit(V0_fr_TK_corr.subset(1,TSEP),tmin_MEL,tmax_MEL,combine("V0_fr_TK/%02d_%d_%02d_%d.xmg",gen_im_S0,ith_S0,gen_im_S1,ith_S1).c_str());
//////////////////////////// compute_form_factors ///////////////////////
//2*Zv
MEL[iVK]/=-2*1.69;
MEL[iV0]/=-2*1.69;
//impulses
jack M_source=M[gen_im_S0],M_sink=M[gen_im_S1];
double p_source=M_PI*theta[ith_S0]/L,p_sink=M_PI*theta[ith_S1]/L;
jack P0=E_source+E_sink,Q0=E_source-E_sink;
double Pi=p_source+p_sink,Qi=p_source-p_sink;
jack Q2=Q0*Q0-3*Qi*Qi;
jack P2=P0*P0-3*Pi*Pi;
jack DM2=M_source*M_source-M_sink*M_sink;
//TK=(E_source*p_sink-p_source*E_sink)*2FT/(M_source+M_sink)
jack FT=MEL[iTK]*0.5*(M_source+M_sink)/(E_source*p_sink-p_source*E_sink);
//FP,F0
jack FM,FP,F0;
if(ith_S0!=iopp[ith_S1])
{
jack DET=P0*Qi-Q0*Pi;
//calculate (f+) and (f-)*Q2/(M_K^2-M_Pi^2)
FP=(MEL[iV0]*Qi-Q0*MEL[iVK])/DET;
FM=(P0*MEL[iVK]-MEL[iV0]*Pi)/DET;
F0=FP+Q2/DM2*FM;
}
else
{
//calculate (f+) and (f-)*Q2/(M_K^2-M_Pi^2)
FM=MEL[iVK]/Qi;
FP=(MEL[iV0]-Q0*FM)/P0;
F0=FP+Q2/DM2*FM;
}
FT_file<<Q2<<" "<<FT<<" "<<Pi<<endl;
FP_file<<Q2<<" "<<FP<<" "<<Pi<<endl;
FM_file<<Q2<<" "<<FM<<" "<<Pi<<endl;
F0_file<<Q2<<" "<<F0<<" "<<Pi<<endl;
fprintf(Q2_file,"th0=%f\t" "th1=%f\t" "Q2=%f\n",theta[ith_S0],theta[ith_S1],Q2.med());
}
fclose(Q2_file);
return 0;
}
int main()
{
read_pars("input");
read_ensemble_pars(base_path,T,ibeta,nmass,mass,iml_un,nlights,data_list_file);
TH=L=T/2;
int ncombo=nmass*nmass;
//load all the corrs
double *buf=new double[4*ncombo*T*(njack+1)];
FILE *fin=open_file(combine("%s/%s",base_path,corr_name).c_str(),"r");
int stat=fread(buf,sizeof(double),4*ncombo*(njack+1)*T,fin);
if(stat!=4*ncombo*(njack+1)*T)
{
cerr<<"Error loading data!"<<endl;
exit(1);
}
jvec M(ncombo,njack);
jvec Z2(ncombo,njack);
//define minuit staff
TMinuit minu(2);
minu.SetPrintLevel(-1);
minu.SetFCN(chi2);
corr_fit=new double[TH+1];
corr_err=new double[TH+1];
int ic=0;
//fit each combo
for(int ims=0;ims<nmass;ims++)
for(int imc=0;imc<nmass;imc++)
{
int ic1=0+2*(imc+nmass*(0+2*ims));
int ic2=1+2*(imc+nmass*(1+2*ims));
printf("%d %d\n",ic1,ic2);
//take into account corr
jvec corr(T,njack);
jvec corr1(T,njack);
jvec corr2(T,njack);
corr1.put(buf+ic1*T*(njack+1));
corr2.put(buf+ic2*T*(njack+1));
corr=(corr1+corr2)/2;
//choose the index of the fitting interval
if(ims>=nlights) ifit_int=2;
else
if(imc>=nlights) ifit_int=1;
else ifit_int=0;
//simmetrize
corr=corr.simmetrized(parity);
int ttmin=tmin[ifit_int];
int ttmax=tmax[ifit_int];
jvec Mcor=effective_mass(corr),Z2cor(TH+1,njack);
jack Meff=constant_fit(Mcor,ttmin,ttmax);
for(int t=0;t<=TH;t++)
for(int ijack=0;ijack<=njack;ijack++)
Z2cor[t].data[ijack]=corr[t].data[ijack]/fun_fit(1,Meff[ijack],t);
jack Z2eff=constant_fit(Z2cor,ttmin,ttmax);
if(!isnan(Z2eff[0])) minu.DefineParameter(0,"Z2",Z2eff[0],Z2eff.err(),0,2*Z2eff[0]);
if(!isnan(Meff[0])) minu.DefineParameter(1,"M",Meff[0],Meff.err(),0,2*Meff[0]);
for(int t=tmin[ifit_int];t<=tmax[ifit_int];t++) corr_err[t]=corr.data[t].err();
//jacknife analysis
for(int ijack=0;ijack<njack+1;ijack++)
{
//copy data so that glob function may access it
for(int t=tmin[ifit_int];t<=tmax[ifit_int];t++) corr_fit[t]=corr.data[t].data[ijack];
//fit
double dum;
minu.Migrad();
minu.GetParameter(0,Z2.data[ic].data[ijack],dum);
minu.GetParameter(1,M.data[ic].data[ijack],dum);
}
//if((ims==iml_un||ims==nlights-1||ims==nlights||ims==nmass-1)&&
//(imc==iml_un||imc==nlights-1||imc==nlights||imc==nmass-1))
{
//plot eff mass
{
ofstream out(combine("eff_mass_plot_%02d_%02d.xmg",ims,imc).c_str());
out<<"@type xydy"<<endl;
out<<"@s0 line type 0"<<endl;
out<<Mcor<<endl;
out<<"&"<<endl;
out<<"@type xy"<<endl;
double av_mass=M[ic].med();
double er_mass=M[ic].err();
out<<tmin[ifit_int]<<" "<<av_mass-er_mass<<endl;
out<<tmax[ifit_int]<<" "<<av_mass-er_mass<<endl;
out<<tmax[ifit_int]<<" "<<av_mass+er_mass<<endl;
out<<tmin[ifit_int]<<" "<<av_mass+er_mass<<endl;
out<<tmin[ifit_int]<<" "<<av_mass-er_mass<<endl;
}
//plot fun
{
ofstream out(combine("fun_plot_%02d_%02d.xmg",ims,imc).c_str());
out<<"@type xydy"<<endl;
out<<"@s0 line type 0"<<endl;
out<<corr<<endl;
out<<"&"<<endl;
out<<"@type xy"<<endl;
for(int t=tmin[ifit_int];t<tmax[ifit_int];t++)
out<<t<<" "<<fun_fit(Z2[ic][njack],M[ic][njack],t)<<endl;
}
}
cout<<mass[ims]<<" "<<mass[imc]<<" "<<M[ic]<<" "<<Z2[ic]<<" "<<sqrt(Z2[ic])/(sinh(M[ic])*M[ic])*(mass[ims]+mass[imc])<<endl;
ic++;
}
ofstream out("fitted_mass.xmg");
out<<"@type xydy"<<endl;
for(int ims=0;ims<nmass;ims++)
{
//out<<"s0 line type 0"<<endl;
for(int imc=0;imc<nmass;imc++)
{
int ic=imc+nmass*ims;
out<<mass[imc]<<" "<<M[ic]<<endl;
}
out<<"&"<<endl;
}
M.write_to_binfile(out_file);
Z2.append_to_binfile(out_file);
return 0;
}
main (int argc, char *argv[]) {
int i, j, **seqs, **nall, ord=1, ns, **pij, lkf=0, npt=0, pnew=0, anc=0;
int tcat=1, rcat=0, verb=1, miss=0, *flocs;
int sw_flag=0, moment_flag=0, rmin_flag=0, sim_flag=0, test_flag=0;
char fname[MAXNAME+1], **seqnames;
long seed=-setseed();
extern int sizeofpset;
double *locs;
double **lkmat, *lkres;
FILE *ifp=NULL, *ifp2=NULL, *ifp3=NULL, *tfp;
struct site_type **pset;
struct data_sum *data;
int ask_questions = 1;
char *in_str;
print_help(argc, argv);
idum = &seed;
data = malloc((size_t) sizeof(struct data_sum));
data->exact = 0;
strcpy(data->prefix, "");
for(i = 0; i < argc; i++)
{
if(*argv[i] == '-')
{
in_str = argv[i];
ask_questions = 0;
if(strcmp(in_str, "-seq") == 0) ifp = fopen(argv[i+1], "r");
if(strcmp(in_str, "-loc") == 0) ifp2 = fopen(argv[i+1], "r");
if(strcmp(in_str, "-lk") == 0)
{
lkf = 1;
ifp3 = fopen(argv[i+1], "r");
}
if(strcmp(in_str, "-exact") == 0) data->exact = 1;
if(strcmp(in_str, "-concise") == 0) verb=0;
if(strcmp(in_str, "-window") == 0) sw_flag=1;
if(strcmp(in_str, "-moment") == 0) moment_flag=1;
if(strcmp(in_str, "-simulate") == 0) sim_flag=1;
if(strcmp(in_str, "-rmin_flag") == 0) rmin_flag=2;
if(strcmp(in_str, "-test") == 0) test_flag=1;
if(strcmp(in_str, "-prefix") == 0) strcpy(data->prefix, argv[i+1]);
}
}
if (ifp == NULL)
{
printf("\nCould not find seqs file in command line.\n");
printf("\nInput filename for seqs:\n");
scanf("%s", &fname);
ifp = fopen(fname, "r");
}
if (ifp == NULL) nrerror("Error in opening sequence file");
fscanf(ifp,"%i%i%i", &data->nseq, &data->lseq, &data->hd);
if ((data->nseq < 2) || (data->lseq < 2)) {printf("\n\nInsufficient data for analysis (n > 1, L > 1) \n\n"); exit(1);}
if (data->nseq > SEQ_MAX) {printf("\n\nMore than max no. sequences: Using first %i for analysis\n\n", SEQ_MAX); data->nseq=SEQ_MAX;}
printf("\nAnalysing %i (n=%i) sequences of length %i seg sites\n", data->nseq, data->hd, data->lseq);
seqs = imatrix(1, data->nseq, 1, data->lseq);
seqnames = cmatrix(1, data->nseq+11, 1, MAXNAME+11);
if (read_fasta(seqs, ifp, data->nseq, data->lseq, seqnames)) printf("\nSequences read succesfully\n");
fclose(ifp);
nall = imatrix(1, data->lseq, 1, 6);
allele_count(seqs, data->nseq, data->lseq, nall,1, data->hd, data->prefix);
/*Store lnfac values in array for speed of computation*/
lnfac_array = (double *) malloc((size_t) ((int) (data->nseq+2)*(data->hd))*sizeof(double));
lnfac_array[0]=lnfac_array[1]=0;
for (j=2;j<=((int) data->nseq*(data->hd));j++) lnfac_array[j]=(double) lnfac_array[j-1]+log(j);
/*Open file with location of seg sites and read in data*/
if (ifp2 == NULL)
{
printf("\nCould not find locs file in command line.\n");
printf("\nInput name of file containing location of seg sites\n\n");
scanf("%s", &fname);
ifp2 = fopen(fname, "r");
}
if (ifp2 == NULL) nrerror("Cannot open loc file");
fscanf(ifp2, "%i %lf %c", &ns, &data->tlseq, &data->lc);
if (ns != data->lseq) nrerror("Lseq and Locs disagree");
if ((data->lc != 'C')&&(data->lc != 'L')) nrerror("Must input linear(L)/conversion(C)");
if (data->lc == 'C') {
data->avc=0;
while (data->avc <= 0) {
printf("\n\nInput average tract length for conversion model: ");scanf("%lf", &(data->avc));
}
}
locs = dvector(1, data->lseq);
flocs = ivector(1, data->lseq); /*Array to use when simulating data*/
for (i=1; i<=data->lseq; i++) {
fscanf(ifp2, "%lf", &locs[i]);
if ((locs[i]==0)||(locs[i]>data->tlseq)) {printf("\n\nError in Loc file\n\n%lf\n", data->tlseq); exit(1);}
if (i>1 && locs[i]<=locs[i-1]) nrerror("Error in locs file: SNPs must be montonically increasing");
}
printf("\nLocation of seg sites\n\n");
for (i=1; i<=data->lseq; i++) printf("%3i %4.2lf\n", i, locs[i]);
fclose(ifp2);
/*Read in likelihood file where needed*/
if (ask_questions)
{
printf("\n\nUse existing likelihood file? (yes=1, no=0):");
scanf("%i", &lkf); /*lkf is a flag: 1 means use existing likelihood file as starting point*/
if (lkf)
{
printf("\n\nInput name of likelihood file: ");
scanf("%s", &fname);
ifp3 = fopen(fname, "r");
}
else
data->exact=0;
if (lkf == 1)
{
printf("\n\nIs likelihood file an exact match to data?(no=0/yes=1): ");
scanf("%i", &data->exact);
}
}
if (lkf && !ifp3) nrerror("Cannot open likelihood file");
if (!lkf && data->hd==2) nrerror("For diploid data need complete lookup table for sequences");
/*Store pair-types in pij matrix - classify in pair_spectrum routine*/
data->w = data->lseq; /*Note for this program use all data - pair_int restricts to a smaller window*/
pij = imatrix((int) 1,(int) data->lseq,(int) 1,(int) data->w);
for (i=1;i<=data->lseq;i++) for (j=1;j<=data->w;j++) pij[i][j]=0;
pset = init_pset(pset, lkf, ifp3, &npt, data); /*Reads in type configurations from likelihood file*/
printf("\n\n*** Calculating distribution of pair types ***\n\n");
pset = pair_spectrum(seqs, data, nall, pset, &npt, &pnew, &miss, anc, pij);
printf("\n\n *** Completed classification of pair types ***\n\n");
if (data->exact && (pnew || miss)) nrerror("Lookup table is not exact for sequences\n(possibly generated by interval)");
printf("\n\nOld = %i: New = %i: Missing = %i\n\n", npt,pnew,miss);
data->ptt = (int) npt+pnew+miss; /*npt is number from likelihood file, pnew is number new with no missing data, miss is # new with missing data*/
if (verb) {
strcpy(fname, data->prefix);
tfp = fopen(strcat(fname, "type_table.txt"), "w");
if (!tfp) nrerror("Cannot open type file");
type_print(pij, data->lseq, data->w,tfp);
fclose(tfp);
}
if (verb) print_pairs(stdout, pset, npt+pnew, data->hd, data->nseq);
/*Need a complete set for missing data or diploid data - check this*/
if (!data->exact && (data->hd ==2 || miss)) {
printf("\n\nMissing data or diploid: checking that likelihood table is exhaustive\n\n");
check_exhaustive(pset,npt,(data->nseq)*((int) data->hd));
}
/*Read parameters and likelihoods from likelihood file - where appropriate*/
if (lkf) {
read_pars(ifp3, &tcat, &data->th, &data->rcat, &data->rmax);
lkmat = dmatrix(1,npt+pnew+miss,1,data->rcat);
if (lkf) read_lk(ifp3, lkmat, npt, tcat, data->rcat);
}
/*If haploid, but novel types, need to calculate new likelihoods and input parameter values*/
if (data->hd ==1 && pnew) { /*Note can have pnew for diploid data, but this has been checked for already*/
if (!lkf) {
data->th=data->rmax=-1.0; data->rcat=0;
printf("\n\nInput theta per site (suggest Watterson estimate of %.5lf):",(double) data->lseq/(watterson(data->nseq*data->hd)*data->tlseq));
while (data->th<0.0) scanf("%lf", &data->th);
printf("\n\nMax 4Ner for grid (suggest 100):");
while(data->rmax<0.0) scanf("%lf", &data->rmax);
printf("\n\nNumber of points on grid (suggest 101, min=2):");
while(data->rcat<2) scanf("%i", &data->rcat);
lkmat = dmatrix(1,npt+pnew+miss,1,data->rcat);
}
lk_est(pset,npt,pnew,lkmat,data->th,data->rcat,data->rmax);
data->exact=1;
}
/*Sum over missing data or resolve genotypes and sum over missing data+configurations*/
else if (miss && data->hd==1) {
printf("\n\n*** Calculating likelihoods for missing data ***\n\n");
for (i=1;i<=miss;i++) {
lk_miss(pset[npt+i],lkmat[npt+i],lkmat,data);
printf("\rType %i", i);
}
printf(" ...Done!\n\n");
}
/*Sum over resolutions for diploid data*/
else if (data->hd==2 && !data->exact) {
printf("\n\n*** Resolving diploid data: %i ***\n\n",pnew+miss);
lkres = dvector(1,data->rcat);
for (i=1;i<=pnew+miss;i++) {
lk_resolve(lkres,pset[npt+i],lkmat[npt+i],lkmat,data);
printf("\rType %i", i);
}
free_dvector(lkres,1,data->rcat);
printf(" ...Done!\n\n");
}
/*If new likelihood generated can output likelihood file for future analyses*/
if (verb) print_lks(pset, data, npt+pnew+miss, lkmat);
/*Basic analysis - estimation of 4Ner asuming constant rate*/
data->rme=data->rmax; data->rce=data->rcat;
if (1) {
printf("\n\nDo you wish to change grid over which to estimate likelihoods for (default = %i points, 4Ner 0 - %.1lf) (1/0) :",data->rcat,data->rmax);
scanf("%i", &lkf);
if (lkf) {
data->rme=-10; data->rce=0;
printf("\n\nMax 4Ner for estimation : ");
while (data->rme < 0.0) scanf("%lf", &data->rme);
printf("\n\nNumber of classes to estimate for: ");
while (data->rce < 1) scanf("%i", &data->rce);
}
}
data->lksurf = dmatrix(1,data->rce,1,2);
lk_surf(pset, pij, data, lkmat, data->th, locs, 1);
/*Print marginal likelihood ratio test statistics for each pair of sites*/
printf("\n\nCalculating fits\n\n");
fit_pwlk(data,pij,locs,lkmat,verb);
/*Sliding windows version*/
if (1) {
printf("\n\nDo you wish to carry out a sliding windows analysis? (yes=1/no=0):");
scanf("%i", &sw_flag);
}
if (sw_flag) lk_win(pset,pij,data,lkmat,locs,nall);
/*Nonparametric estimation of recombination rate*/
if (1) {
printf("\n\nPrint out table of Rmin values?\n(0=No, 1=Total only, 2=Full table):");
scanf("%i", &rmin_flag);
}
if (rmin_flag) {
rmin(data, pset, pij, locs, lkf-1);
printf("\n\nLower bound on Rmin = %i\n\n",data->rmin);
}
/*Estimate 4Ner by Wakeley 1997 method*/
if (1) {
printf("\n\nEstimate 4Ner by moment method? (yes=1, no=0)");
scanf("%i", &moment_flag);
}
if (moment_flag) wakeley_est(data, seqs, locs);
/*Recombination tests - only available for haploid data!*/
if (data->hd==1) {
if (1) {
printf("\n\nDo you wish to test for recombination? (yes=1, no=0): ");
scanf("%i", &test_flag);
}
if (test_flag) {
rec_test(data, pij, locs, lkmat, pset, npt+pnew+miss);
}
}
/*Conditional simulation - only available for haploid data with a complete lk file*/
if (data->hd==1 && !(data->exact)) {
if (1) {
printf("\n\nDo you wish to test constant-rate model and estimate sampling distribution by simulation? (yes=1/no=0): ");
scanf("%i", &test_flag);
}
if (test_flag) {
freq_min(locs, flocs, nall, data);
printf("\n\nHow many simulations? ");
scanf("%i", &lkf);
snp_sim(locs, flocs, pset, lkmat, lkf, data);
}
}
free_imatrix(pij,1,data->lseq,1,data->w);
free_imatrix(seqs,1,data->nseq,1,data->lseq);
free_imatrix(nall,1,data->lseq,1,5);
for (i=1;i<sizeofpset;i++) free(pset[i]);
free(pset);
free(data);
free_dvector(locs, 1, data->lseq);
free_ivector(flocs, 1, data->lseq);
/* system("PAUSE"); */
}
void create_model_ratio_hist1( const char* model_pars_file = "outputfiles/model-pars-qcdmc3.txt",
const char* qcd_ratio_file = "outputfiles/qcdmc-ratio-v3.root" ) {
setup_bins();
gDirectory -> Delete( "h*" ) ;
loadHist( qcd_ratio_file, "qcdmc" ) ;
read_pars( model_pars_file ) ;
TH1F* h_ratio_all = new TH1F( "h_ratio_all", "QCD model H/L ratio", nb_global_after_exclusion, 0.5, nb_global_after_exclusion + 0.5 ) ;
TH1F* h_max_ldp_weight_search_bins = get_hist( "h_max_ldp_weight_search_bins_qcdmc" ) ;
TH1F* h_ldp_search_bins = get_hist( "h_ldp_search_bins_qcdmc" ) ;
TH1F* h_hdp_search_bins = get_hist( "h_hdp_search_bins_qcdmc" ) ;
TH1F* h_ratio_qcdmc = get_hist( "h_ratio_qcdmc" ) ;
int bi_hist_with_exclusion(0) ;
for ( int bi_nj=1; bi_nj<=nb_nj; bi_nj++ ) {
for ( int bi_nb=1; bi_nb<=nb_nb; bi_nb++ ) {
for ( int bi_htmht=4; bi_htmht<=nb_htmht; bi_htmht++ ) {
if ( is_this_bin_excluded(bi_nj-1, bi_nb-1, bi_htmht-1) ) continue;
bi_hist_with_exclusion++; // these few lines should be changed when we update the code that produces qcdmc-ratio-v3.root
int bi_ht, bi_mht ;
htmht_bin_to_ht_and_mht_bins( bi_htmht, bi_ht, bi_mht ) ;
char label[100] ;
sprintf( label, " %3d Nj%d-Nb%d-MHT%d-HT%d (%d)", bi_hist_with_exclusion, bi_nj, bi_nb-1, bi_mht-1, bi_ht, bi_htmht-3 ) ;
double model_ratio_val = 0;
double model_ratio_err = 0;
model_ratio_val = par_val_ht[bi_ht] * par_val_njet[bi_nj] * par_val_ht_mht[bi_ht][bi_mht] * par_val_nb[bi_nb] ;
model_ratio_err = model_ratio_val * sqrt(
pow( par_err_ht_fit[bi_ht]/par_val_ht[bi_ht], 2. )
+ pow( par_err_ht_syst[bi_ht]/par_val_ht[bi_ht], 2. )
+ pow( par_err_njet_fit[bi_nj]/par_val_njet[bi_nj], 2. )
+ pow( par_err_njet_syst[bi_nj]/par_val_njet[bi_nj], 2. )
+ pow( par_err_ht_mht[bi_ht][bi_mht]/par_val_ht_mht[bi_ht][bi_mht], 2. )
+ pow( par_err_nb[bi_nb]/par_val_nb[bi_nb], 2. )
) ;
printf(" %s : Nj %6.4f Nb %6.4f MHT %6.4f HT %6.4f model ratio = %6.4f +/- %6.4f\n", label,
par_val_njet[bi_nj], par_val_nb[bi_nb], par_val_ht_mht[bi_ht][bi_mht], par_val_ht[bi_ht], model_ratio_val, model_ratio_err ) ;
h_ratio_all -> GetXaxis() -> SetBinLabel( bi_hist_with_exclusion, label ) ;
h_ratio_all -> SetBinContent( bi_hist_with_exclusion, model_ratio_val ) ;
h_ratio_all -> SetBinError( bi_hist_with_exclusion, model_ratio_err ) ;
} // bi_htmht
} // bi_nb
} // bi_nj
gStyle -> SetOptStat(0) ;
gStyle -> SetPadBottomMargin(0.30) ;
h_ratio_all -> SetMarkerStyle( 22 ) ;
h_ratio_all -> SetMarkerColor( 2 ) ;
h_ratio_all -> GetXaxis() -> LabelsOption("v") ;
h_ratio_all -> Draw() ;
gPad -> SetGridy(1) ;
//---------------
TH1F* h_ratio_qcdmc_minus_model = new TH1F( "h_ratio_qcdmc_minus_model", "QCD H/L ratio difference (QCD MC - model)", nb_global_after_exclusion, 0.5, nb_global_after_exclusion + 0.5 ) ;
printf("\n\n") ;
bi_hist_with_exclusion = 0;
for ( int bi_nj=1; bi_nj<=nb_nj; bi_nj++ ) {
for ( int bi_nb=1; bi_nb<=nb_nb; bi_nb++ ) {
for ( int bi_htmht=4; bi_htmht<=nb_htmht; bi_htmht++ ) {
if ( is_this_bin_excluded(bi_nj-1, bi_nb-1, bi_htmht-1) ) continue;
bi_hist_with_exclusion++; // these few lines should be changed when we update the code that produces qcdmc-ratio-v3.root
float model_val = h_ratio_all -> GetBinContent( bi_hist_with_exclusion ) ;
float qcdmc_val = h_ratio_qcdmc -> GetBinContent( bi_hist_with_exclusion ) ;
float ldp_val = h_ldp_search_bins -> GetBinContent( bi_hist_with_exclusion ) ;
float hdp_val = h_hdp_search_bins -> GetBinContent( bi_hist_with_exclusion ) ;
float max_ldp_weight = h_max_ldp_weight_search_bins -> GetBinContent( bi_hist_with_exclusion ) ;
char label[100] ;
sprintf( label, "%s", h_ratio_all -> GetXaxis() -> GetBinLabel( bi_hist_with_exclusion ) ) ;
float diff_val(0.) ;
float diff_err(0.) ;
printf(" debug1 : model bin label = %s , qcdmc bin label = %s\n", h_ratio_all -> GetXaxis() -> GetBinLabel( bi_hist_with_exclusion ), h_ratio_qcdmc -> GetXaxis() -> GetBinLabel( bi_hist_with_exclusion ) ) ;
if ( hdp_val > 0 ) {
diff_val = qcdmc_val - model_val ;
std::cout << qcdmc_val << " " << model_val << " " << diff_val << std::endl;
diff_err = diff_val ;
printf(" %40s : LDP %7.1f HDP %7.1f max LDP weight %5.3f, diff err = %5.3f\n", label, ldp_val, hdp_val, max_ldp_weight, diff_err ) ;
} else {
diff_val = 0. ;
if ( ldp_val > 0 ) {
diff_err = max_ldp_weight / ldp_val ;
printf(" %40s : LDP %7.1f HDP %7.1f max LDP weight %5.3f, zero HDP H/L err = %5.3f\n", label, ldp_val, hdp_val, max_ldp_weight, diff_err ) ;
} else {
//diff_err = 0.5 ;
//diff_err = 0.2;
diff_err = 0.0;
printf(" %40s : LDP %7.1f HDP %7.1f max LDP weight %5.3f, *** both zero\n", label, ldp_val, hdp_val, max_ldp_weight ) ;
}
}
h_ratio_qcdmc_minus_model -> SetBinContent( bi_hist_with_exclusion, diff_val ) ;
h_ratio_qcdmc_minus_model -> SetBinError( bi_hist_with_exclusion, diff_err ) ;
h_ratio_qcdmc_minus_model -> GetXaxis() -> SetBinLabel( bi_hist_with_exclusion, label ) ;
} // bi_htmht
}//bi_nb
}//bi_nj
printf("\n\n") ;
h_ratio_qcdmc_minus_model -> GetXaxis() -> LabelsOption( "v" ) ;
saveHist("outputfiles/model-ratio-hist1.root", "h*" ) ;
} // create_model_ratio_hist1
