dustem_sed_extractor.pro
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FUNCTION dustem_sed_extractor,maps,index_roi,filters, $
comments=comments, $
maps_order=maps_order, $
method=method, $
index_off=index_off, $
reference_filter=reference_filter, $
mask_I_undef=mask_I_undef, $
total_intensity_only=total_intensity_only, $
_extra=_extra
;+
; NAME:
; sed_extractor
; PURPOSE:
; Extract SEDs from a set of maps
; CATEGORY:
; Dustemwrap
; CALLING SEQUENCE:
; sed=sed_extractor(maps,index,filters[,comments=][,maps_order=][,method=][,mask_I_undef=][,/total_intensity_only])
; INPUTS:
; maps : a set of Nmaps maps of same dimension [Nx,Ny,Nmaps,Ndata_sets]
; index_roi : spatial index in Nx,Ny where the SED is to be extracted from (ROI=region of interest)
; filters : dustemwrap filters corresponding to each maps [Nmaps]
; OPTIONAL INPUT PARAMETERS:
; comments = a vector of strings to be attached to the SED. Also an output.
; maps_order = a vector of 9 integers giving the 0-based index for I,Q,U,II,QQ,UU,IQ,IU,QU in that order
; (default [0,1,2,3,4,5,6,7,8]). For total intensity only, use something like [0,-1,-1,1,-1,-1,-1,-1,-1].
; method = extraction method (default = 'MEAN')/ Possible values : 'MEAN','MEAN_ONOFF','QU_CORREL'
; index_off = same as index for the OFF region (needed only for method='MEAN_ONOFF')
; reference_filter = reference filter to be correlated with each map (needed only for method='QU_CORREL')
; OUTPUTS:
; SED : a dustemwrap SED structure containing te extracted SED
; OPTIONAL OUTPUT PARAMETERS:
; mask_I_undef = a map of saturated pixels found in Stokes I
; comments = a vector of strings to be writtena s comments into the SED.
; ACCEPTED KEY-WORDS:
; total_intensity_only = if set, data is assumed to contain only total intensity (no polarization)
; comments = comments to be added to the sed. sed_extractor adds comments to this
; COMMON BLOCKS:
; None
; SIDE EFFECTS:
; None
; RESTRICTIONS:
; None
; PROCEDURE:
; None
; EXAMPLES
; MODIFICATION HISTORY:
; Written by JPB
;-
IF keyword_set(help) THEN BEGIN
doc_library,'dustem_sed_extractor'
sed=0.
goto,the_end
ENDIF
Nfilt=n_elements(filters)
sed=dustem_initialize_sed(Nfilt,comments=comments)
sed.filter=filters
sed.instru=dustem_filter2instru(sed.filter)
sed.wave=dustem_filter2wav(filters)
comments=[comments,'\Computed using sed_extractor on '+systime(0)]
order=sort(sed.wave) ;wavelength order
count_roi=n_elements(index_roi)
use_method='MEAN' ;This is the default extraction method
IF keyword_set(method) THEN BEGIN
use_method=method
ENDIF
comments=[comments,'SED extracted using method '+use_method]
comments=[comments,'ROI has '+strtrim(count_roi,2)+' map pixels']
N1=(size(maps))[1]
N2=(size(maps))[2]
Nplanes=(size(maps))[3]
IF keyword_set(total_intensity_only) THEN BEGIN
indI=0L & indII=1L
IF keyword_set(maps_order) THEN BEGIN
indI=maps_order[0]
indII=maps_order[1]
ENDIF
ENDIF ELSE BEGIN
indI=0L & indQ=1L & indU=2L & indII=3L & indQQ=4L & indUU=5L &indIQ=6L & indIU=7L &indQU=8L
IF keyword_set(maps_order) THEN BEGIN
indI=maps_order[0]
indQ=maps_order[1]
indU=maps_order[2]
indII=maps_order[3]
indQQ=maps_order[4]
indUU=maps_order[5]
indIQ=maps_order[6]
indIU=maps_order[7]
indQU=maps_order[8]
ENDIF
ENDELSE
;===== do a map of saturated stokesI pixels
mask_I_undef=maps[*,*,0,0]
mask_I_undef[*]=0
FOR j=0L,Nfilt-1 DO BEGIN
this_map=maps[*,*,indI,j]
ind=where(this_map EQ la_undef(),count)
IF count NE 0 AND count NE N1*N2 THEN BEGIN
message,'Found '+strtrim(count,2)+' undefined values for map of '+filters[j],/continue
;stop
mask_I_undef[ind]=1
ENDIF
ENDFOR
used_maps=maps
;set saturated stokesI pixels to la_undef in
indbad=where(mask_I_undef EQ 1,count)
IF count NE 0 THEN BEGIN
message,'Setting Stokes I saturated values to undef in the whole cube',/continue
FOR j=0L,Nfilt-1 DO BEGIN
FOR k=0L,Nplanes-1 DO BEGIN
this_map=used_maps[*,*,k,j]
this_map[indbad]=la_undef()
used_maps[*,*,k,j]=this_map
ENDFOR
ENDFOR
ENDIF
CASE use_method OF
'MEAN':BEGIN
FOR j=0L,Nfilt-1 DO BEGIN
this_map=used_maps[*,*,indI,j]
sed[j].stokesI=la_mean(this_map[index_roi])
this_map=used_maps[*,*,indII,j]
sed[j].sigmaII=la_div(la_mean(this_map[index_roi]),count_roi)
IF not keyword_set(total_intensity_only) THEN BEGIN
this_map=used_maps[*,*,indQ,j]
sed[j].stokesQ=la_mean(this_map[index_roi])
this_map=used_maps[*,*,indU,j]
sed[j].stokesU=la_mean(this_map[index_roi])
this_map=used_maps[*,*,indQQ,j]
sed[j].sigmaQQ=la_div(la_mean(this_map[index_roi]),count_roi)
this_map=used_maps[*,*,indUU,j]
sed[j].sigmaUU=la_div(la_mean(this_map[index_roi]),count_roi)
this_map=used_maps[*,*,indIQ,j]
sed[j].sigmaIQ=la_div(la_mean(this_map[index_roi]),count_roi)
this_map=used_maps[*,*,indIU,j]
sed[j].sigmaIU=la_div(la_mean(this_map[index_roi]),count_roi)
this_map=used_maps[*,*,indQU,j]
sed[j].sigmaQU=la_div(la_mean(this_map[index_roi]),count_roi)
ENDIF
ENDFOR
END
'MEAN_ONOFF': BEGIN ;This is mean ON - mean MEAN_ONOFF
IF not keyword_set(index_off) THEN BEGIN
message,'index_off keyword must be set with method '+use_method,/continue
stop
ENDIF
count_off=n_elements(index_off)
comments=[comments,'OFF has '+strtrim(count_off,2)+' map pixels']
FOR j=0L,Nfilt-1 DO BEGIN
this_map=used_maps[*,*,indI,j]
sed[j].stokesI=la_sub(la_mean(this_map[index_roi]),la_mean(this_map[index_off]))
this_map=used_maps[*,*,indII,j]
sig_on=la_div(la_mean(this_map[index_roi]),count_roi)
sig_off=la_div(la_mean(this_map[index_off]),count_off)
sed[j].sigmaII=la_add(sig_on,sig_off)
IF not keyword_set(total_intensity_only) THEN BEGIN
this_map=used_maps[*,*,indQ,j]
sed[j].stokesQ=la_sub(la_mean(this_map[index_roi]),la_mean(this_map[index_off]))
this_map=used_maps[*,*,indU,j]
sed[j].stokesU=la_sub(la_mean(this_map[index_roi]),la_mean(this_map[index_off]))
;variances
this_map=used_maps[*,*,indQQ,j]
sig_on=la_div(la_mean(this_map[index_roi]),count_roi)
sig_off=la_div(la_mean(this_map[index_off]),count_off)
sed[j].sigmaQQ=la_add(sig_on,sig_off)
this_map=used_maps[*,*,indUU,j]
sig_on=la_div(la_mean(this_map[index_roi]),count_roi)
sig_off=la_div(la_mean(this_map[index_off]),count_off)
sed[j].sigmaUU=la_add(sig_on,sig_off)
;co-variances
this_map=used_maps[*,*,indIQ,j]
sig_on=la_div(la_mean(this_map[index_roi]),count_roi)
sig_off=la_div(la_mean(this_map[index_off]),count_off)
sed[j].sigmaIQ=la_add(sig_on,sig_off)
this_map=used_maps[*,*,indIU,j]
sig_on=la_div(la_mean(this_map[index_roi]),count_roi)
sig_off=la_div(la_mean(this_map[index_off]),count_off)
sed[j].sigmaIU=la_add(sig_on,sig_off)
this_map=used_maps[*,*,indQU,j]
sig_on=la_div(la_mean(this_map[index_roi]),count_roi)
sig_off=la_div(la_mean(this_map[index_off]),count_off)
sed[j].sigmaQU=la_add(sig_on,sig_off)
ENDIF
ENDFOR
;stop
END
'QU_CORREL': BEGIN ;This is to compute SED of polarization correlated to a reference
IF keyword_set(total_intensity_only) THEN BEGIN
message,'mode QU_CORREL can only be used with polarization data'
ENDIF
IF not keyword_set(reference_filter) THEN BEGIN
message,'reference_filter keyword must be set with method '+use_method,/continue
stop
ENDIF
indf=where(filters EQ reference_filter,countf)
IF countf EQ 0 THEN BEGIN
message,'reference filter '+reference_filter+' not found in provided filter list',/continue
stop
ENDIF
mapI_ref=used_maps[*,*,indI,indf]
mapQ_ref=used_maps[*,*,indQ,indf]
mapU_ref=used_maps[*,*,indU,indf]
mapII_ref=used_maps[*,*,indII,indf]
mapQQ_ref=used_maps[*,*,indQQ,indf]
mapUU_ref=used_maps[*,*,indUU,indf]
Iref=la_mean(mapI_ref[index_roi])
Qref=la_mean(mapQ_ref[index_roi])
Uref=la_mean(mapU_ref[index_roi])
FOR j=0L,Nfilt-1 DO BEGIN
;==== do the correlation in Stokes I
x=mapI_ref[index_roi]
y=(used_maps[*,*,indI,j])[index_roi]
sx=la_power(mapII_ref[index_roi],0.5)
sy=la_power((used_maps[*,*,indI,j])[index_roi],0.5)
ind_good=where(x NE la_undef() AND y NE la_undef() AND sx NE la_undef() and sy NE la_undef(),count_good)
comments=[comments,'I corelation has '+strtrim(count_good,2)+' map pixels']
IF count_good NE 0 THEN BEGIN
x=x[ind_good]
y=y[ind_good]
sx=sx[ind_good]
sy=sy[ind_good]
start=[1.,1.]
try=linear_mpfit(x,y,sx,sy,start,status=status $
,perror=perror,bestnorm=bestnorm,_extra=_extra)
;stop
ENDIF ELSE BEGIN
status=0
try=[la_undef(),la_undef()]
ENDELSE
IF status NE 0 AND status NE -16 THEN BEGIN
sed[j].stokesI=try[0]*Iref
sed[j].sigmaII=la_power(la_mul(perror[0],Iref),2.)
ENDIF
;Do the correlation between Q maps
x=[mapQ_ref[index_roi],mapU_ref[index_roi]]
y=[(used_maps[*,*,indQ,j])[index_roi],(used_maps[*,*,indU,j])[index_roi]]
sx=la_power([mapQQ_ref[index_roi],mapUU_ref[index_roi]],0.5)
sy=la_power([(used_maps[*,*,indQ,j])[index_roi],(used_maps[*,*,indU,j])[index_roi]],0.5)
ind_good=where(x NE la_undef() AND y NE la_undef() AND sx NE la_undef() and sy NE la_undef(),count_good)
comments=[comments,'QU corelation has '+strtrim(count_good,2)+' map pixels']
IF count_good NE 0 THEN BEGIN
x=x[ind_good]
y=y[ind_good]
sx=sx[ind_good]
sy=sy[ind_good]
start=[1.,1.]
try=linear_mpfit(x,y,sx,sy,start,status=status $
,perror=perror,bestnorm=bestnorm,_extra=_extra)
;stop
ENDIF ELSE BEGIN
status=0
try=[la_undef(),la_undef()]
ENDELSE
IF status NE 0 AND status NE -16 THEN BEGIN
sed[j].stokesQ=la_mul(try[0],Qref)
sed[j].stokesU=la_mul(try[0],Uref)
sed[j].sigmaQQ=la_power(la_mul(perror[0],Qref),2.)
sed[j].sigmaUU=la_power(la_mul(perror[0],Uref),2.)
;for now assume no co-variances. But we could aclculate this, right ?
sed[j].sigmaIQ=0.
sed[j].sigmaIU=0.
sed[j].sigmaQU=0.
;IF filters[j] EQ reference_filter THEN stop
ENDIF
ENDFOR
comments=[comments,'Reference filter for QU correlation '+reference_filter]
END
ELSE: BEGIN
message,'Method '+use_method+' not implemented',/continue
sed=0L
goto,the_end
END
ENDCASE
polar_iqu2ippsi,sed.stokesI,sed.stokesQ,sed.stokesU,p_values,psi_values,/lac,largep=largep
sed.smallp=p_values
sed.psi=psi_values
sed.largep=largep
polar_variance_iqu2ippsi,sed.stokesI,sed.stokesQ,sed.stokesU,sed.sigmaII,sed.sigmaQQ,sed.sigmaUU,sed.sigmaIQ,sed.sigmaIU,sed.sigmaQU,variances_p,variances_psi,variances_largep,/lac
sed.sigma_smallp=variances_p
sed.sigma_largep=variances_largep
sed.sigma_psi=variances_psi
ssed=sed[order]
sed=ssed
;stop
the_end:
RETURN,sed
END