;xy_offsets ; ;PURPOSE: ; This script will return the difference in coordinates between a ; ShackHartman image centroid and the corresponding point on the ; reference grid ; ; Since the center of the grid seems to be drifting pro new_xy_offsets_10_cn_depth_ind_letter,Date=Date,stats_directory=stats_directory,$ x_center_file=x_center_file,y_center_file=y_center_file,$ depth=depth If (not keyword_set(Date)) then Date='10' If (not keyword_set(stats_directory)) then stats_directory='stats_temp' If (not keyword_set(x_center_file)) then x_center_file='x_centers.txt' If (not keyword_set(y_center_file)) then y_center_file='y_centers.txt' If (not keyword_set(depth)) then depth=2 If (not keyword_set(postscript_dir)) then postscript_dir='postscripts' letter=['hr5132a','hr5132b','hr5132c','hr5132d','hr5132e','hr5132f','hr5132g','hr5132h','hr5132i'] stats_directory='/a/pippin01/Volumes/u08/lsst/CPanalysis/2005-05-'+Date+$ '/ShackHartman/'+stats_directory+'/' postscript_dir='/a/pippin01/Volumes/u08/lsst/CPanalysis/2005-05-'+Date+$ '/ShackHartman/'+postscript_dir+'/' ;RUN THIS SCRIPT FOR EACH 100 FILES for j=0, N_elements(letter)-1 do begin offset_files=file_search(stats_directory+letter(j)+'*offsets.txt',count=num_stats_files) ;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' not_fitted=where(x_offset eq -1,complement=fitted) ;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 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 -1) and $ (x_offset_hor(file_number+time,spot_index+spacing) ne -1) then begin Cxl_arr(spot_index)=x_offset_hor(file_number,spot_index)*$ x_offset_hor(file_number+time,spot_index+spacing) Cxt_arr(spot_index)=y_offset_hor(file_number,spot_index)*$ y_offset_hor(file_number+time,spot_index+spacing) ;print,FORMAT='(%"%i\t%i\t")',spot_index,spot_index+spacing ; C_num=C_num+1 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)=0 Cxt(spacing,time)=0 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 -1) and $ (y_offset_ver(file_number+time,spot_index+spacing) ne -1) then begin Cyl_arr(spot_index)=y_offset_ver(file_number,spot_index)*$ y_offset_ver(file_number+time,spot_index+spacing) Cyt_arr(spot_index)=x_offset_ver(file_number,spot_index)*$ x_offset_ver(file_number+time,spot_index+spacing) ;print,FORMAT='(%"%i\t%i\t")',spot_index,spot_index+spacing ; C_num=C_num+1 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)=0 Cyt(spacing,time)=0 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 Cxt_means=fltarr(num,depth) Cxl_means=fltarr(num,depth) Cyt_means=fltarr(num,depth) Cyl_means=fltarr(num,depth) for n=0, num-1 do begin for m=0, depth-1 do begin Cxt_means(n,m)=mean(Cxt_full(*,n,m)) Cxl_means(n,m)=mean(Cxl_full(*,n,m)) Cyl_means(n,m)=mean(Cyl_full(*,n,m)) Cyt_means(n,m)=mean(Cyt_full(*,n,m)) endfor endfor set_plot,'ps' device,filename=Postscript_dir+letter(j)+'cn_time'+string(strtrim(depth,2))+'.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=1.2 !P.THICK=4. !p.multi=[0,1,1] 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 plot,Cxt_means(*,0),psym=1,title="Transverse correlation along X direction",$ xtitle="n",ytitle="Covariance",$ background=white,color=black,$ yrange=[min(Cxt_means(*,0))-.5,max(Cxt_means(*,0))+.5],$ POSITION=[0.10,0.10,0.9,0.9] ;Over Plot the various separations in time and also generate legends for i=1,depth-1 do begin oplot,Cxt_means(*,i),psym=(((i+1) mod 5)+1),color=20*((i+1)/5) sym_time=[sym_time,((i+1) mod 5)+1] items_time=[items_time,string(strtrim(i*7,2))+' seconds'] colors_time=[colors_time,(20*((i+1)/5))] endfor legend,items_time,psym=sym_time,position=[.7,.8],colors=colors_time,/normal ;*************SECOND PLOT plot,(Cxt_means(*,0)-Cxt_means(*,depth-1)),psym=1,$ title="Transverse correlation along X direction for t=0-t="+$ strtrim(string(depth*7),2)+' seconds',$ xtitle="n",ytitle="Covariance",$ background=white,color=black,$ yrange=[0,2],$ POSITION=[0.10,0.10,0.9,0.9] oplot,findgen(num-1)+1,(findgen(num-1)+1)^(-7./32.),psym=0,color=black,$ linestyle=1 oplot,findgen(num-1)+1,(findgen(num-1)+1)^(-13./64.),psym=0,color=black,$ linestyle=2 oplot,findgen(num-1)+1,(findgen(num-1)+1)^(-27./128.),psym=0,color=black,$ linestyle=3 legend,items_k_tran,linestyle=line_k_tran,position=[.6,.8],/normal ;**************THIRD PLOT !p.multi=[0,5,5] for n=0, num-1 do begin Cxt_max=floor(max(Cxt_full(*,n,0)-Cxt_full(*,n,depth-1)))+.5 Cxt_min=floor(min(Cxt_full(*,n,0)-Cxt_full(*,n,depth-1)))-.5 n_bins=40 Cxt_hist=histogram((Cxt_full(*,n,0)-Cxt_means(n,depth-1)),nbins=n_bins,$ max=Cxt_max,min=Cxt_min,locations=Cxt_locations) plot,Cxt_locations,Cxt_hist,psym=10,title='Spacing= '+string(strtrim(n,2)),$ xrange=[Cxt_min,Cxt_max],xtitle="Correlation",ytitle="Number",$ background=white,color=black endfor !p.multi=[0,1,1] ;***************FOURTH PLOT plot,Cxl_means(*,0),psym=1,title="Longitudinal correlation along X direction",$ xtitle="n",ytitle="Covariance (Pixels Squared)",$ background=white,color=black,$ yrange=[min(Cxl_means(*,0))-.5,max(Cxl_means(*,0))+.5],$ POSITION=[0.10,0.10,0.9,0.9] for i=1,depth-1 do begin oplot,Cxl_means(*,i),psym=(((i+1) mod 5)+1),color=20*((i+1)/5) endfor legend,items_time,psym=sym_time,position=[.2,.4],/normal,colors=colors_time ;**************FIFTH PLOT plot,(Cxl_means(*,0)-Cxl_means(*,depth-1)),psym=1,$ title="Longitudinal correlation along X direction for t=0-t="+$ strtrim(string(depth*7),2)+' seconds',$ xtitle="n",ytitle="Covariance",$ background=white,color=black,$ yrange=[0,max(Cxl_means(*,0)-Cxl_means(*,depth-1))+.5],$ POSITION=[0.10,0.10,0.9,0.9] oplot,findgen(num-1)+1,(findgen(num-1)+1)^(-1./3.),psym=0,color=black legend,items_k_lon,linestyle=line_k_lon,position=[.6,.8],/normal ;**************SIXTH PLOT !p.multi=[0,5,5] for n=0, num-1 do begin Cxl_max=floor(max(Cxl_full(*,n,0)-Cxl_full(*,n,depth-1)))+.5 Cxl_min=floor(min(Cxl_full(*,n,0)-Cxl_full(*,n,depth-1)))-.5 n_bins=40 Cxl_hist=histogram((Cxl_full(*,n,0)-Cxl_full(*,n,depth-1)),nbins=n_bins,$ max=Cxl_max,min=Cxl_min,locations=Cxl_locations) plot,Cxl_locations,Cxl_hist,psym=10,title='Spacing= '+string(strtrim(n,2)),$ xrange=[Cxl_min,Cxl_max],xtitle="Correlation",ytitle="Number",$ background=white,color=black endfor !P.multi=[0,1,1] ;**************SEVENTH PLOT plot,Cyt_means(*,0),psym=1,title="Transverse correlation along Y direction",$ xtitle="n",ytitle="Covariance (Pixels Squared)",$ background=white,color=black,$ yrange=[min(Cyt_means(*,0))-.5,max(Cyt_means(*,0))+.5],$ POSITION=[0.10,0.10,0.9,0.9] for i=1,depth-1 do begin oplot,Cyt_means(*,i),psym=(((i+1) mod 5)+1),color=20*((i+1)/5) endfor legend,items_time,psym=sym_time,position=[.6,.8],/normal,colors=colors_time ;***************EIGHT PLOT plot,(Cyt_means(*,0)-Cyt_means(*,depth-1)),psym=1,$ title="Transverse correlation along Y direction for t=0-t="+$ strtrim(string(depth*7),2)+' seconds',$ xtitle="n",ytitle="Covariance",$ background=white,color=black,$ yrange=[min(Cyt_means(*,0)-Cyt_means(*,depth-1))-.5,$ max(Cyt_means(*,0)-Cyt_means(*,depth-1))+.5],$ POSITION=[0.10,0.10,0.9,0.9] oplot,findgen(num-1)+1,(findgen(num-1)+1)^(-7./32.),psym=0,color=black,$ linestyle=1 oplot,findgen(num-1)+1,(findgen(num-1)+1)^(-13./64.),psym=0,color=black,$ linestyle=2 oplot,findgen(num-1)+1,(findgen(num-1)+1)^(-27./128.),psym=0,color=black,$ linestyle=3 legend,items_k_tran,linestyle=line_k_tran,position=[.6,.8],/normal ;***************NINTH PLOT !p.multi=[0,5,5] for n=0, num-1 do begin Cyt_max=floor(max(Cyt_full(*,n,0)-Cyt_full(*,n,depth-1)))+.5 Cyt_min=floor(min(Cyt_full(*,n,0)-Cyt_full(*,n,depth-1)))-.5 n_bins=40 Cyt_hist=histogram((Cyt_full(*,n,0)-Cyt_full(*,n,depth-1)),nbins=n_bins,$ max=Cyt_max,min=Cyt_min,locations=Cyt_locations) plot,Cyt_locations,Cyt_hist,psym=10,title='Spacing= '+string(strtrim(n,2)),$ xrange=[Cyt_min,Cyt_max],xtitle="Correlation",ytitle="Number",$ background=white,color=black endfor ;***************TENTH PLOT !p.multi=[0,1,1] plot,Cyl_means(*,0),psym=1,title="Longitudinal correlation along Y direction",$ xtitle="n",ytitle="Covariance (Pixels Squared)",$ background=white,color=black,$ yrange=[min(Cyl_means(*,0))-.5,max(Cyl_means(*,0))+.5],$ POSITION=[0.10,0.10,0.9,0.9] for i=1,depth-1 do begin oplot,Cyl_means(*,i),psym=(((i+1) mod 5)+1),color=20*((i+1)/5) endfor legend,items_time,psym=sym_time,position=[.6,.8],/normal,colors=colors_time ;***************ELEVENTH PLOT plot,(Cyl_means(*,0)-Cyl_means(*,depth-1)),psym=1,$ title="Longitudinal correlation along Y direction for t=0-t="+$ strtrim(string(depth*7),2)+' seconds',$ xtitle="n",ytitle="Covariance",$ background=white,color=black,$ yrange=[0,max(Cyl_means(*,0)-Cyl_means(*,depth-1))+.5],$ POSITION=[0.10,0.10,0.9,0.9] oplot,findgen(num-1)+1,(findgen(num-1)+1)^(-1./3.),psym=0,color=black legend,items_k_lon,linestyle=line_k_lon,position=[.6,.8],/normal ;***************TWELTH PLOT !p.multi=[0,5,5] for n=0, num-1 do begin Cyl_max=floor(max(Cyl_full(*,n,0)-Cyl_full(*,n,depth-1)))+.5 Cyl_min=floor(min(Cyl_full(*,n,0)-Cyl_full(*,n,depth-1)))-.5 n_bins=40 Cyl_hist=histogram((Cyl_full(*,n,0)-Cyl_full(*,n,depth-1)),nbins=n_bins,$ max=Cyl_max,min=Cyl_min,locations=Cyl_locations) plot,Cyl_locations,Cyl_hist,psym=10,title='Spacing= '+string(strtrim(n,2)),$ xrange=[Cyl_min,Cyl_max],xtitle="Correlation",ytitle="Number",$ background=white,color=black endfor device,/close set_plot,'X' endfor end