FUNCTION dustem_brute_force_fit,sed $ ,table_name $ ,filters $ ,fixed_parameters_description=fixed_parameters_description $ ,fixed_parameters_values=fixed_parameters_values $ ,normalize=normalize $ ,params_hit=params_hit $ ,params_uncertainties=params_uncertainties $ ,params_min=params_min $ ,params_max=params_max $ ,fact=fact $ ,chi2=chi2 $ ,rchi2=rchi2 $ ,best_sed=best_sed $ ,best_grid_sed=best_grid_sed $ ,show_sed=show_sed $ ,nostop=nostop $ ,reset=reset ;+ ; NAME: ; dustem_brute_force_fit ; PURPOSE: ; does brut force fit from a pre-computed model grid ; CATEGORY: ; DustEM ; CALLING SEQUENCE: ; res=dustem_brute_force_fit(sed,table_name,filters[,/normalize][,fact=][,chi2=][,rchi2=][rchi2][best_sed=][,/show_sed][,/nostop][,/reset]) ; INPUTS: ; sed = sed to be fit. Should contain all filters provided to the routine trhough input variable filter ; table_name = name of the fits file to be used as a grid (see dustem_make_sed_table.pro for creation) ; filters = filters to be used in the grid table (only used if !dustem_grid does not exist or if /reset) ; OPTIONAL INPUT PARAMETERS: ; fixed_parameters_description = if set, describes parameters of the table that should be considered fixed. ; fixed_parameters_values = values of parameters of the table that should be considered fixed. ; OUTPUTS: ; res = best values of the free parameters. Not that linear parameters to the sed should be multiplied by fact. ; OPTIONAL OUTPUT PARAMETERS: ; fact = best scaling factor. Such that best_sed*fact is for NH=1.e20 H/cm2 (as in the grid). IF sed is already normalized to NH=1e20 H/cm2, no need to set /normalize ; chi2 = chi2 of the best fit ; rchi2 = reduced chi2 of the best fit ; best_grid_sed = best SED found in the grid ; best_sed = best fit SED matching input SED (such that best_sed=best_grid_sed*fact) ; params_hit= 1 if parameter hits the top, -1 if hits the bottom, 0 otherwise ; params_uncertainties = 90% confidence level uncertainty on parameters ; params_min = 90% lower limit of parameters ; params_max = 90% upper limit of parameters ; ACCEPTED KEY-WORDS: ; help = if set, print this help ; normalize = if set, the best match is done based on the shape of the SEDs only, instead of their absolute values. fact will be computed. ; show_sed = if set, plot the seds ; nostop = if set, do not stop ; COMMON BLOCKS: ; None ; SIDE EFFECTS: ; None ; RESTRICTIONS: ; The DustEMWrap IDL code must be installed ; PROCEDURE: ; Scans the grid SEDs to find the best fit (lowest chi2) ; EXAMPLES ; ; MODIFICATION HISTORY: ; Written by JPB Jan 2024 ; Evolution details on the DustEMWrap gitlab. ; See http://dustemwrap.irap.omp.eu/ for FAQ and help. ;- IF keyword_set(help) THEN BEGIN doc_library,'dustem_brute_force_fit' params=0. goto,the_end ENDIF ;stop ;sed must be normalized to NH=1e20 H/cm2 ;==== test for the existence of a loaded grid and initialize if needed. ;==== only filters contained in the filters variable are kept in the grid, and the sum of grid seds are recomputed accordingly defsysv,'!dustem_grid',0,exist=exist IF exist EQ 0 or keyword_set(reset)THEN BEGIN dustem_define_grid,table_name,filters ENDIF ;=== Should marginalize table for fixed parameters, if any seds=!dustem_grid.seds Nseds=!dustem_grid.Nsed Nfilters=!dustem_grid.Nfilters Nparams=!dustem_grid.Nparams table_params=!dustem_grid.params table_pmins=!dustem_grid.pmin_values table_pmaxs=!dustem_grid.pmax_values IF keyword_set(fixed_parameters_description) THEN BEGIN dustem_marginalize_grid,fixed_parameters_description,fixed_parameters_values,seds,Nseds,Nfilters,Nparams,table_params,table_pmins,table_pmaxs ENDIF ;=== These are the full arrays needed for calculations chi2s=dblarr(Nseds) grid_seds=dblarr(Nseds,Nfilters) total_seds=dblarr(Nseds) grid_param_values=dblarr(Nseds,Nparams) ;=== compute sed grid Array FOR i=0L,Nseds-1 DO BEGIN FOR j=0L,Nfilters-1 DO BEGIN grid_seds[i,j]=seds[i].(j+Nparams) ENDFOR total_seds[i]=seds[i].total ENDFOR ;=== compute the parameter values Array FOR i=0L,Nseds-1 DO BEGIN FOR j=0L,Nparams-1 DO BEGIN grid_param_values[i,j]=seds[i].(j) ENDFOR ENDFOR ;stop ;=== loop over grid lines to compute chi2s ;we do actually store the total of grid sed for each grid sed into the grid fits file ;we could also store the total of observed seds in the observed sed save fits file (!) facts=dblarr(Nseds) facts[*]=1.d0 IF keyword_set(normalize) THEN BEGIN FOR i=0L,Nseds-1 DO BEGIN ;facts[i]=total(sed.stokesI)/total(grid_seds[i,*]) facts[i]=total(sed.stokesI)/total_seds[i] this_sed=sed.stokesI/facts[i] this_var=sed.sigmaII/facts[i]^2 ;chi2s[i]=total((sed.stokesI-grid_seds[i,*])^2/sed.sigmaII) chi2s[i]=total((this_sed-grid_seds[i,*])^2/this_var) ENDFOR ENDIF ELSE BEGIN FOR i=0L,Nseds-1 DO BEGIN chi2s[i]=total((sed.stokesI-grid_seds[i,*])^2/sed.sigmaII) ENDFOR ENDELSE ;stop chi2=min(chi2s) ind=where(chi2s EQ chi2,count) params=grid_param_values[ind[0],*] ;these are the best fit parameters fact=facts[ind[0]] ; This is the corresponding scaling factor Nfreedom=Nfilters-Nparams-1 ;This is the degree of freedom rchi2=chi2/Nfreedom ;This is the reduced chi2 best_grid_sed=reform(grid_seds[ind[0],*]) ;This is the best SED fround in the grid. best_sed=best_grid_sed*fact ;This is the best scaled grid SED matching the input SED. ;==== Check bumping to table edges. params_hit=intarr(Nparams) FOR i=0L,Nparams-1 DO BEGIN IF params[i] EQ table_pmins[i] THEN params_hit[i]=-1 IF params[i] EQ table_pmaxs[i] THEN params_hit[i]=1 ENDFOR ;==== Compute parameter uncertainties ;stop conf_level=90./100. ;print,Nfreedom,conf_level IF Nfreedom NE 0. THEN BEGIN dchi2=delta_chi2(Nfreedom,conf_level) ENDIF ELSE BEGIN message,'Nfreedom = 0. Beware of meaningless fit',/continue stop message,'seting Nfreedom = 1. Beware of meaningless fit',/continue dchi2=delta_chi2(1.,conf_level) ENDELSE ind=where(chi2s LE chi2+dchi2,count) params_min=fltarr(Nparams) params_max=fltarr(Nparams) FOR i=0L,Nparams-1 DO BEGIN params_min[i]=min(params[ind,i]) params_max[i]=max(params[ind,i]) ENDFOR params_uncertainties=params_max-params_min IF keyword_set(show_sed) THEN BEGIN xtit='Wavelength [mic]' ytit='SED (model=red,data=blue)' ;should also plot uncertainties minv=la_min([sed.stokesI,best_sed]) maxv=la_max([sed.stokesI,best_sed]) cgplot,sed.wave,sed.stokesI,psym='Filled Circle',color='blue',/ylog,/ysty,xtit=xtit,ytit=ytit,/xlog,yrange=[minv,maxv] cgoplot,sed.wave,best_sed,psym='Filled Square',color='red' if not keyword_set(nostop) THEN stop ENDIF the_end: RETURN,params END