;xy_offsets ; ;PURPOSE: ; This script will calculate the covariances of the ShackHartman images ; using the distorted grid obtained by averaging all of the positions. pro newest_cn_depth_w_offsets,Date=Date,stats_directory=stats_directory,$ x_center_file=x_center_file,y_center_file=y_center_file,$ depth=depth,x_off=x_off,y_off=y_off If (not keyword_set(Date)) then Date='10' If (not keyword_set(stats_directory)) then stats_directory='stats_1_31' If (not keyword_set(x_center_file)) then x_center_file='newest_x_centers.txt' If (not keyword_set(y_center_file)) then y_center_file='newest_y_centers.txt' If (not keyword_set(depth)) then depth=0 If (not keyword_set(postscript_dir)) then postscript_dir='distorted_postscripts' If (not keyword_set(x_off)) then x_off=[0,.2,.4] If (not keyword_set(y_off)) then y_off=[0,0,0] stats_directory='/nfs/slac/g/ki/ki08/lsst/CPanalysis/2005-05-'+Date+$ '/ShackHartman/'+stats_directory+'/' postscript_dir='/nfs/slac/g/ki/ki08/lsst/CPanalysis/2005-05-'+Date+$ '/ShackHartman/'+postscript_dir+'/' ;ARRAYS OF FILES offset_files=file_search(stats_directory+'*5132*newest_offsets.txt',count=num_stats_files) readcol,stats_directory+'newest_x_centers.txt',x_center,x_fit_center,$ format='X,f,f' readcol,stats_directory+'newest_y_centers.txt',y_center,y_fit_center,$ format='X,f,f' x_off_cen=x_center-x_fit_center y_off_cen=y_center-y_fit_center stop ;CONSTANTS num=25 grid_spots=625 index=findgen(625) ;ARRAY REFERENCE 25x25=625 FOR GRID subx=2*indgen(num)-25 ;The x-reference numbers suby=indgen(num)-12 ;The y-reference numbers ;HUGE DATA CUBE x_offset_hor=fltarr(num_stats_files,grid_spots) y_offset_hor=fltarr(num_stats_files,grid_spots) x_offset_ver=fltarr(num_stats_files,grid_spots) y_offset_ver=fltarr(num_stats_files,grid_spots) ;Correlations Cxt_full=fltarr(num_stats_files,num,depth) Cxl_full=fltarr(num_stats_files,num,depth) Cyt_full=fltarr(num_stats_files,num,depth) Cyl_full=fltarr(num_stats_files,num,depth) ;FILL THE DATA CUBES for file_number=0,num_stats_files-1 do begin ;Take the results from the offset.txt files and fill the cube readcol,offset_files(file_number),x_offset,y_offset,format='X,X,f,X,f' if center_sub eq 1 then begin ;Obtain the difference ordered in COLUMN, ROW between centroid and grid point x_offset=x_offset-x_off_cen(file_number) y_offset=y_offset-y_off_cen(file_number) endif ;Obtain the difference ordered in COLUMN, ROW between centroid and grid point x_offset_hor(file_number,*)=x_offset y_offset_hor(file_number,*)=y_offset ;Obtain the difference ordered in ROW, COLUMN x_offset_ver(file_number,*)=x_offset((index mod 25)*25+index/25) y_offset_ver(file_number,*)=y_offset((index mod 25)*25+index/25) endfor ;DATA CUBEs are now in place. Begin the covariance ;Loop through all of the files in the offsets=n_elements(x_off) Cxt_means=fltarr(offsets,num,depth) Cxl_means=fltarr(offsets,num,depth) Cyt_means=fltarr(offsets,num,depth) Cyl_means=fltarr(offsets,num,depth) for off=0, offsets-1 do begin for file_number=0,num_stats_files-depth do begin ;CORRELATIONS Cxl=fltarr(num,depth) Cxt=fltarr(num,depth) Cyl=fltarr(num,depth) Cyt=fltarr(num,depth) for time=0, depth-1 do begin for spacing=0, num-1 do begin Cxl_arr=fltarr(num*num) Cxt_arr=fltarr(num*num) Cyl_arr=fltarr(num*num) Cyt_arr=fltarr(num*num) ;SCAN FIRST ALONG THE ROWS for column_index=0, num-1 do begin for row_index=0, num -1 do begin spot_index=column_index*num+row_index ;If we have reached the edge, start on the next row If (row_index+spacing) ge num then break ;Check to see if both have valid values If (x_offset_hor(file_number,spot_index) ne -10) and $ (x_offset_hor(file_number+time,spot_index+spacing) ne -10) $ then begin ;add offset in to tweek the plots Cxl_arr(spot_index)=(x_offset_hor(file_number,spot_index)+$ x_off(off))*$ (x_offset_hor(file_number+time,spot_index+spacing)+$ x_off(off)) Cxt_arr(spot_index)=(y_offset_hor(file_number,spot_index)+$ y_off(off))*$ (y_offset_hor(file_number+time,spot_index+spacing)+$ y_off(off)) ;print,FORMAT='(%"%i\t%i\t")',spot_index,spot_index+spacing endif endfor endfor correlated=where(Cxl_arr ne 0) If correlated(0) ne -1 then begin Cxl(spacing,time)=mean(Cxl_arr(correlated)) Cxt(spacing,time)=mean(Cxt_arr(correlated)) endif else begin Cxl(spacing,time)=-10 Cxt(spacing,time)=-10 endelse ;printf,xcor,FORMAT='(%"%f\t%f\t%i")',Cxl(spacing-1),Cxt(spacing-1),N_elements(correlated) ;SCAN SECOND ALONG Y for column_index=0, num-1 do begin for row_index=0, num -1 do begin spot_index=column_index*num+row_index ;If we have reached the edge, start on the next row If (row_index+spacing) ge num then break ;Check to see if both have valid values If (y_offset_ver(file_number,spot_index) ne -10) and $ (y_offset_ver(file_number+time,spot_index+spacing) ne -10) $ then begin Cyl_arr(spot_index)=(y_offset_ver(file_number,spot_index)+$ y_off(off))*$ (y_offset_ver(file_number+time,spot_index+spacing)+$ y_off(off)) Cyt_arr(spot_index)=(x_offset_ver(file_number,spot_index)+$ x_off(off))*$ (x_offset_ver(file_number+time,spot_index+spacing)+$ x_off(off)) ;print,FORMAT='(%"%i\t%i\t")',spot_index,spot_index+spacing endif endfor endfor correlated=where(Cyl_arr ne 0) If correlated(0) ne -1 then begin Cyl(spacing,time)=mean(Cyl_arr(correlated)) Cyt(spacing,time)=mean(Cyt_arr(correlated)) endif else begin Cyl(spacing,time)=-10 Cyt(spacing,time)=-10 endelse ;printf,ycor,FORMAT='(%"%f\t%f\t%i")',Cyl(spacing-1),Cyt(spacing-1),N_elements(correlated) endfor endfor ;partvelvec,x_offset(fitted),y_offset(fitted),gridx(fitted),$ ; gridy(fitted),yrange=[150,800],xrange=[200,850] ;close,xcor ;free_lun,xcor ;close,ycor ;free_lun,ycor Cxt_full(file_number,*,*)=Cxt Cxl_full(file_number,*,*)=Cxl Cyt_full(file_number,*,*)=Cyt Cyl_full(file_number,*,*)=Cyl endfor for n=0, num-1 do begin for m=0, depth-1 do begin Cxt_means(off,n,m)=mean(Cxt_full(*,n,m)) Cxl_means(off,n,m)=mean(Cxl_full(*,n,m)) Cyl_means(off,n,m)=mean(Cyl_full(*,n,m)) Cyt_means(off,n,m)=mean(Cyt_full(*,n,m)) endfor endfor endfor set_plot,'ps' device,filename=Postscript_dir+'Cns_mean_offsets.ps' loadct,39 ;load color table 39 device,/color ;allow color on the postscript device,ysize=8.5,/inches ;Height of plot in y device,xsize=10.0,/inches ;Width of plot in x device,yoffset=1.0,/inches ;Y position of lower left corner white='FFFFFF'x black='000000'x !P.CHARSIZE=.7 !P.THICK=4. items_time=['t=0'] sym_time=[1] items_k_tran=['Data Points','n!e-7/32!n','n!e-13/64!n','n!e-27/128!n'] sym_k_tran=[1,0,0,0] line_k_tran=[0,1,2,3] items_k_lon=['Data Points','n!e-1/3!n'] sym_k_long=[0,1] colors_time=[0] ;*************FIRST PLOT !P.multi=[0,1,1] plot,Cxt_means(0,*,0),psym=1,title="Transverse correlation along X direction",$ xtitle="n",ytitle="Covariance",$ background=white,color=black,$ yrange=[min(Cxt_means(0,*,0))-3,max(Cxt_means(0,*,0))+.5],$ POSITION=[0.10,0.10,0.9,0.9] ;Over Plot the various separations in time and also generate legends for k=1,offsets-1 do begin oplot,Cxt_means(k,*,0)-Cxt_means(0,*,0),psym=(((k+1) mod 5)+1),color=20*((k+1)/5) sym_time=[sym_time,((k+1) mod 5)+1] items_time=[items_time,string(strtrim(x_off(k)))+' pixel offset'] colors_time=[colors_time,(20*((k+1)/5))] endfor legend,items_time,psym=sym_time,position=[.7,.8],colors=colors_time,/normal !p.multi=[0,1,1] ;***************FIFTH PLOT plot,Cxl_means(0,*,0),psym=1,title="Longitudinal correlation along X direction",$ xtitle="n",ytitle="Covariance (Pixels Squared)",$ background=white,color=black,$ yrange=[min(Cxl_means(0,*,0))-3,max(Cxl_means(0,*,0))+.5],$ POSITION=[0.10,0.10,0.9,0.9] for k=1,offsets-1 do begin oplot,Cxl_means(0,*,0)-Cxl_means(k,*,0),psym=(((k+1) mod 5)+1),color=20*((k+1)/5) endfor legend,items_time,psym=sym_time,position=[.2,.4],/normal,colors=colors_time !P.multi=[0,1,1] ;**************NINTH PLOT plot,Cyt_means(0,*,0),psym=1,title="Transverse correlation along Y direction",$ xtitle="n",ytitle="Covariance (Pixels Squared)",$ background=white,color=black,$ yrange=[min(Cyt_means(0,*,0))-3,max(Cyt_means(0,*,0))+.5],$ POSITION=[0.10,0.10,0.9,0.9] for k=1,offsets-1 do begin oplot,Cyt_means(0,*,0)-Cyt_means(k,*,0),psym=(((k+1) mod 5)+1),$ color=20*((k+1)/5) endfor legend,items_time,psym=sym_time,position=[.6,.8],/normal,colors=colors_time ;***************THIRTEENTH PLOT !p.multi=[0,1,1] plot,Cyl_means(0,*,0),psym=1,title="Longitudinal correlation along Y direction",$ xtitle="n",ytitle="Covariance (Pixels Squared)",$ background=white,color=black,$ yrange=[min(Cyl_means(0,*,0))-3,max(Cyl_means(0,*,0))+.5],$ POSITION=[0.10,0.10,0.9,0.9] for k=1,offsets-1 do begin oplot,Cyl_means(0,*,0)-Cyl_means(k,*,0),psym=(((k+1) mod 5)+1),$ color=20*((k+1)/5) endfor legend,items_time,psym=sym_time,position=[.6,.8],/normal,colors=colors_time device,/close set_plot,'X' end