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runtarget.pro
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runtarget.pro
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pro runtarget, pickpath=pickpath, skypath=skypath, sub=sub, linear=linear, cubic=cubic, plot=plot, skipgc=skipgc
; This procedure is devoted to the reduction of cross scans acquired on the observed target sources and
; apply the previously-measured conversion factors (cnt->Jy).
; It plots and analyses the data obtained by stacking all the subscans contained in any scan
; (i.e. subfolder) present inside the working folder.
; If users want to graphically choose the data folder, they must use:
;
; IDL> runtarget, /pickpath in order to select the path to the data parent folders (otherwise the chosen paths are ./CALIBRATORS and ./TARGETS)
; IDL> runtarget, /skypath in order to select the path to the folder containing skydips (otherwise the chosen path is ./SKYDIPS)
;
; Measurements for all the single subscans can be obtained by explicitly choosing this option:
;
; IDL> runtarget, /sub
;
; The gaussian fitting performed on the (sub)scans can be run using three different baseline-fitting options,
; in particular:
;
; IDL> runtarget, /linear performs, and outputs, only the linear fitting of baselines
; IDL> runtarget, /cubic performs, and outputs, only the cubic fitting of baselines
; IDL> runtarget, /both performs, and outputs, both the cubic and linear fitting of baselines
;
; By default, the choice is 'both'.
;
; Plot output in PDF is exceedingly slow, in particular for single subscans (if the /sub option is selected).
; So it is disabled by default.
; To enable it, explicitly set the option:
;
; IDL> runtarget, /plot
;
;
; The option
;
; IDL> runcalib, /skipgc
;
; overrides the use of the standard gain curves; it poses Gain=1 for all the elevations,
; thus practically avoiding the elevation-dependent gain compensation.
;
; COMPATIBILITY WITH CONVERTED FILES
; FITS files achieved with older versions of DISCOS (dating back to years 2008-2015)
; need to be converted into the proper FITS format (ask for procedure named updatefits.pro).
; The program automatically handles the TP-like files resulting from the
; conversion of SARDARA acquisitions, which have raw counts levels in the
; orders of magnitude of 10E+06..10E+07, producing properly-formatted output tables.
;
; Authors: Marcello Giroletti, Simona Righini
; Last edited: November 24, 2020 by Simona
;
common logistics, workpath, calpath, sep, skydippath, myextlist, fitchoice, dosingle, doplot
close, /all ; to close possible pending text files
sep=path_sep()
if keyword_set (sub) then dosingle='y' else dosingle='n'
if keyword_set(pickpath) then begin
workpath=dialog_pickfile(/DIRECTORY, TITLE='Pick the DATA parent folder')
endif else begin
CD, CURRENT=curr
workpath=curr+sep+'TARGETS'+sep
endelse
if keyword_set(pickpath) then begin
calpath=dialog_pickfile(/DIRECTORY, TITLE='Pick the CALIBRATION FILES parent folder')
endif else begin
calpath=curr+sep+'CALIBRATORS'+sep ; assuming a rigidly-defined folder hierarchy and naming!
endelse
if keyword_set(skypath) then begin
skydippath=dialog_pickfile(/DIRECTORY, TITLE='Please pick folder containing the Tau.txt file')
endif else begin
CD, CURRENT=curr
skydippath=curr+sep+'SKYDIP'+sep ; assuming a rigidly-defined folder hierarchy and naming!
endelse
if keyword_set(linear) then begin
fitchoice='linear'
endif else begin
if keyword_set(cubic) then fitchoice='cubic' else fitchoice='both'
endelse
if keyword_set (plot) then doplot='y' else doplot='n'
tar_stack, freq=freq
return
end
PRO tar_gfunct, X, A, F, pder
EX2 = A[0]*EXP(-(X-A[1])^2/(2*A[2]^2))
F = EX2 + A[3] + A[4]*X +A[5]*X^2 +A[6]*X^3
IF N_PARAMS() GE 4 THEN $
pder = [[EX2/A[0]], [EX2*(X-A[1])/(A[2]^2)], [EX2*((X-A[1])^2)/(A[2]^3)], [replicate(1.0, N_ELEMENTS(X))], [X], [X^2], [X^3]]
END
function tar_wmean, val, dval, nan = nan, error = error
COMPILE_OPT idl2
on_error, 2
;- check inputs
if n_params() ne 2 then begin
return, !values.f_nan
endif
sz = n_elements(val)
if n_elements(dval) ne sz then $
message, 'val and dval must contain the same number of elements'
;- the calculation
;- requires at least one finite value
if keyword_set(nan) then begin
hit = where(finite(val) and finite(dval), ct)
if ct eq 0 then begin
error = !values.f_nan
return, !values.f_nan
endif
endif
dw = total(1D / dval^2, nan = keyword_set(nan))
sum = total(1D * val / dval^2, nan = keyword_set(nan)) / dw
error = sqrt(1D / dw)
return, sum
end
pro tar_stack, path=path, out=out, plot=plot, beam=beam, speed=speed, dt=dt, source=source, flux=flux, freq=freq
common logistics
; !EXCEPT=2 ; enabling the indications of location/line numbers in exception messages
!EXCEPT=0 ; silencing the printout of exception messages
fw_tol=0.3 ; we accept measurements where FWHM is within 30% of the nominal HPBW
; reads first file from first scan to set basic info in output files
list = FILE_SEARCH(workpath+'20*', COUNT=number, /TEST_DIRECTORY)
timings=dblarr(number+1)
gap=dblarr(number+1)
timings[0]=systime(1)
gap[0]=0
sublist = FILE_SEARCH(list[0]+sep+'20*.fits', COUNT=subnumber)
; XXX ripetere la lettura per un file di ogni sub-folder e verificare che siano omogenei
data=MRDFITS(sublist[0],4,/SILENT)
RFinfo=MRDFITS(sublist[0],2,/SILENT)
Sectinfo=MRDFITS(sublist[0],1,/SILENT)
gaintime=data[0].time ; associated MJD (first sample of first subscan)
firstscanname=strsplit(sublist[0],sep,/extract)
firstscandate=strsplit(firstscanname[-1],'-',/extract)
datesplit=strsplit(firstscandate[0],path_sep(),/extract)
yyyymmdd=datesplit[-1]
if double(yyyymmdd) lt double(20120101) then begin
ksectchoice='mf' ; K-band receiver in MED was multi-feed
endif else begin
ksectchoice='df' ; K-band receiver in MED was dual-feed
endelse
; read frequency and bandwidth from RF table
bw=RFinfo[0].bandWidth
freq=RFinfo[0].frequency+bw/2.0
dt=1.0/(Sectinfo[0].sampleRate*1e6)
; which telescope was used? Let's get to a 3-char code to be used afterwards
firstmainh=mrdfits(sublist[0],0,firsthead0,/silent)
findh0key, firsthead0, '*ANTENNA =*', keylab, sitename, infolab, siteflag
splitsitename=strsplit(sitename,"'",/extract)
cleansite=strupcase(strcompress(splitsitename[1],/remove_all))
site=strmid(cleansite,0,3) ; this way, possible cases will be MED, SRT and NOT
case site of
'MED': begin
beam=38.7/(freq/1000.0) ; beam in arcmin
; frequency-dependent normalized gain polynomials
; http://www.med.ira.inaf.it/ManualeMedicina/English/5.%20Efficiency.htm
; taken on 2015 September 17
if (freq gt 4000 and freq lt 6000) then begin
; this is C band
A_0=[7.9212981E-1,6.2403816E-3,-4.6834953E-5,0]
A_1=[7.9212981E-1,6.2403816E-3,-4.6834953E-5,0]
endif
if (freq gt 8000 and freq lt 10000) then begin
; this is X band
A_0=[0.730487,0.00773332,-5.54743e-05,0] ; updated 2015, but it is not opacity-corrected
A_1=[0.730487,0.00773332,-5.54743e-05,0] ; updated 2015, but it is not opacity-corrected
; A_0=[6.1059261E-01,1.0623634E-02,-7.2457279E-05,0] ; origin???
; A_1=[6.1059261E-01,1.0623634E-02,-7.2457279E-05,0] ; origin???
endif
if (freq gt 18000 and freq le 18500) then begin
if gaintime gt 55926.0 then begin
; this is K-low band
A_0=[0.8373589,0.005140111,-4.058370E-5,0] ; as of Sept.30, 2015
A_1=[0.8373589,0.005140111,-4.058370E-5,0] ; as of Sept.30, 2015
endif else begin
; multi-feed gain curve for feed0
A_0=[0.59778067,0.013571075,-0.00011447367,0]
A_1=[0.59778067,0.013571075,-0.00011447367,0]
print, 'BEWARE: Using gain curve for multi-feed K-band receiver'
endelse
endif
if (freq gt 18500 and freq le 26500) then begin
; this is K-high band
if gaintime gt 55926.0 then begin
A_0=[0.7929185,0.005900533,-4.203179E-5,0] ; as of Sept.30, 2015
A_1=[0.7929185,0.005900533,-4.203179E-5,0] ; as of Sept.30, 2015
endif else begin
; multi-feed gain curve for feed0
A_0=[0.59778067,0.013571075,-0.00011447367,0]
A_1=[0.59778067,0.013571075,-0.00011447367,0]
print, 'BEWARE: Using gain curve for multi-feed K-band receiver'
endelse
endif
end
'SRT': begin
; frequency dependent normalized gain polynomials
; as provided by Andrea Orlati (commissioning)
if (freq gt 4000 and freq lt 8000) then begin
; this is C band
beam=18.937/(freq/1000.0) ; beam in arcmin
A_0=[0.939813,0.00139,-0.000009,0] ; XXX To be updated
A_1=[0.939813,0.00139,-0.000009,0] ; XXX To be updated
endif
if (freq ge 18000 and freq lt 27000) then begin
; this is K band
beam=18.264/(freq/1000.0) ; beam in arcmin
if freq lt 21000 then begin
A_0=[0.508145,0.014839,-0.000111,0] ; from official SRT page
A_1=[0.508145,0.014839,-0.000111,0] ; from official SRT page
endif
if freq ge 21000 and freq le 23000 then begin
A_0=[0.606733,0.01132,-0.000081,0] ; from official SRT page
A_1=[0.606733,0.01132,-0.000081,0] ; from official SRT page
endif
if freq gt 23000 then begin
A_0=[0.533025,0.015561,-0.000129,0] ; from official SRT page
A_1=[0.533025,0.015561,-0.000129,0] ; from official SRT page
endif
endif
end
'NOT': begin
;beam=38.7/(freq/1000.0) ; beam in arcmin - CLONED FROM MEDICINA XXX
if (freq gt 4000 and freq lt 6000) then begin
; this is C band
beam=7.5 ; fixed value
; A_0=[0.98463659,0.00017053038,1.9348601e-09,0] ; old
; A_1=[0.98463659,0.00017053038,1.9348601e-09,0] ; old
A_0=[0.95227062926,0.00198726460815,-2.0685473288e-05,0] ; Cassaro, Oct 16th 2017
A_1=[0.95227062926,0.00198726460815,-2.0685473288e-05,0] ; Cassaro, Oct 16th 2017
endif
if (freq gt 8000 and freq lt 10000) then begin
; this is X band
print, 'X Curve for Noto is not available, yet. Returning.'
return
endif
if (freq gt 18000 and freq le 26500) then begin
; this is K band
print, 'K Curve for Noto is not available, yet. Returning.'
return
endif
end
else: begin
print, 'UNKNOWN SITE: cannot apply gain curves. Returning.'
return
end
endcase
beamd=beam/60.
sd=beamd/(2*SQRT(2*ALOG(2)))
; open the main output files
if fitchoice eq 'linear' or fitchoice eq 'both' then begin
openw, Unit0, workpath+'tar_stack_lin_final.txt', /GET_LUN
openw, Unit1, workpath+'tar_stack_lin_sep.txt', /GET_LUN
printf, Unit0, FORMAT = '(A7,1X,A3)', "Site =",site
endif
if fitchoice eq 'cubic' or fitchoice eq 'both' then begin
openw, Unit10, workpath+'tar_stack_cub_final.txt', /GET_LUN
openw, Unit11, workpath+'tar_stack_cub_sep.txt', /GET_LUN
endif
if strmatch(sublist[0],'*TPlike*.*',/FOLD_CASE) then begin
TPlike=1 ; this is a SARDARA file converted/integrated in TotalPower-like format
if fitchoice eq 'linear' or fitchoice eq 'both' then begin
printf, Unit0, ' Name HHMMSS # MJD Freq Elev Amp_0 Amp_1 e_Amp_0 e_Amp_1 flux_0 flux_1 e_flux_0 e_flux_1'
printf, Unit0, ' MHz deg count count count count Jy Jy Jy Jy'
printf, Unit1, ' Name HHMMSS # MJD Freq Elev Amp_0 Amp_1 e_Amp_0 e_Amp_1 flux_0 flux_1 e_flux_0 e_flux_1 SNR_0 SNR_1 Offset FW/HP Type'
printf, Unit1, ' MHz deg count count count count Jy Jy Jy Jy deg '
endif
if fitchoice eq 'cubic' or fitchoice eq 'both' then begin
printf, Unit10, ' Name HHMMSS # MJD Freq Elev Amp_0 Amp_1 e_Amp_0 e_Amp_1 flux_0 flux_1 e_flux_0 e_flux_1'
printf, Unit10, ' MHz deg count count count count Jy Jy Jy Jy'
printf, Unit11, ' Name HHMMSS # MJD Freq Elev Amp_0 Amp_1 e_Amp_0 e_Amp_1 flux_0 flux_1 e_flux_0 e_flux_1 SNR_0 SNR_1 Offset FW/HP Type'
printf, Unit11, ' MHz deg count count count count Jy Jy Jy Jy deg '
endif
endif else begin
TPlike=2 ; this is an original TotalPower FITS
if fitchoice eq 'linear' or fitchoice eq 'both' then begin
printf, Unit0, ' Name HHMMSS # MJD Freq Elev Amp_0 Amp_1 e_Amp_0 e_Amp_1 flux_0 flux_1 e_flux_0 e_flux_1'
printf, Unit0, ' MHz deg count count count count Jy Jy Jy Jy'
printf, Unit1, ' Name HHMMSS # MJD Freq Elev Amp_0 Amp_1 e_Amp_0 e_Amp_1 flux_0 flux_1 e_flux_0 e_flux_1 SNR_0 SNR_1 Offset FW/HP Type'
printf, Unit1, ' MHz deg count count count count Jy Jy Jy Jy deg '
endif
if fitchoice eq 'cubic' or fitchoice eq 'both' then begin
printf, Unit10, ' Name HHMMSS # MJD Freq Elev Amp_0 Amp_1 e_Amp_0 e_Amp_1 flux_0 flux_1 e_flux_0 e_flux_1'
printf, Unit10, ' MHz deg count count count count Jy Jy Jy Jy'
printf, Unit11, ' Name HHMMSS # MJD Freq Elev Amp_0 Amp_1 e_Amp_0 e_Amp_1 flux_0 flux_1 e_flux_0 e_flux_1 SNR_0 SNR_1 Offset FW/HP Type'
printf, Unit11, ' MHz deg count count count count Jy Jy Jy Jy deg '
endif
endelse
openw, Unit2, workpath+'tar_prints.txt', /GET_LUN
; reads skydip information
ans=file_test(skydippath+'Tau.txt')
if ans eq 1 then begin
readcol, skydippath+'Tau.txt', tau_mjd, tau_freq, t30l, t90l, t30r, t90r, tau_empL, tau_empR, tau0L, tau0R, format='(d,d,d,d,d,d,d,d,d,d)', /SILENT
for t=0,n_elements(tau_mjd)-1 do begin
; if for any reason tau_emp is considered more reliable than tau0, uncomment the following two lines
; tau0L[t]=tau_empL[t]
; tau0R[t]=tau_empR[t]
endfor
caltau = 1
print, '++++++++++++++++++++++++++++++++'
print, 'Reading tau0 values from Tau.txt
print, '++++++++++++++++++++++++++++++++'
endif else begin
print, ' '
print, '+++++++++++++++++++++++++++++++++++++++++++++'
print, 'Beware: no Tau.txt available, assuming tau0=0
print, '+++++++++++++++++++++++++++++++++++++++++++++'
wait, 0.5
tau0L=[0,0]
tau0R=[0,0]
caltau = 0
endelse
; definition of arrays
p0=fltArr(2)
p1=fltArr(2)
e0=fltArr(2)
e1=fltArr(2)
c0=fltArr(2) ; count to jansky array
c1=fltArr(2)
d0=fltArr(2) ; error on count to jansky array
d1=fltArr(2)
SNR0=fltArr(2)
SNR1=fltArr(2)
offset=dblArr(2)
p0c=fltArr(2)
p1c=fltArr(2)
e0c=fltArr(2)
e1c=fltArr(2)
c0c=fltArr(2) ; count to jansky array
c1c=fltArr(2)
d0c=fltArr(2) ; error on count to jansky array
d1c=fltArr(2)
SNR0c=fltArr(2)
SNR1c=fltArr(2)
offsetc=dblArr(2)
fw_ratio0=fltarr(2)
fw_ratio1=fltarr(2)
fw_ratio0c=fltarr(2)
fw_ratio1c=fltarr(2)
; scan-based analysis
for i =0,number-1 do begin
print, ' '
print, '========================================='
print, 'Now analysing scan ', list[i]
print, '========================================='
sommaL=0
sommaR=0
sommaLA = 0
sommaRA = 0
numLA = 0
numRA = 0
iiA = 0
ffA = 0
sommaLB = 0
sommaRB = 0
numLB = 0
numRB = 0
iiB = 0
ffB = 0
splitfoldname1=strsplit(list[i],sep,/extract)
foldname=splitfoldname1[-1]
splitfoldname2=strsplit(foldname,'-',/extract)
hhmmss = splitfoldname2[1]
; splitfoldname=strsplit(list[i],'-',/extract)
; hhmmss = splitfoldname[1]
sublist = FILE_SEARCH(list[i]+sep+'2*.fits', COUNT=subnumber)
scanname=file_basename(list[i])
; reads flagging info
err=0
checkfile = list[i]+sep+'checkfile_'+scanname+'.txt'
openr, Unit9, checkfile, ERROR=err, /GET_LUN
subscan=file_basename(sublist)
flagcode=strarr(subnumber)
flagcode[*]='+1cx'
if (err lt 0) then begin
print, "No valid flagging information for this scan"
print, "Temporarily assuming all scans are good"
endif else begin
readcol, checkfile, F='a,a,a', subscan_t, flagcode_t, who, /SILENT
if (n_elements(subscan_t) lt subnumber) then begin
print, "Some subscans miss flagging information"
print, "Temporarily assuming those subscans are good"
endif
for n_flag = 0, n_elements(subscan_t)-1 do begin
for j_flag = 0, subnumber-1 do begin
if (subscan_t[n_flag] eq subscan[j_flag]) then begin
flagcode[j_flag]=flagcode_t[n_flag]
endif
endfor
endfor
close, Unit9
free_lun, Unit9
endelse
if dosingle eq 'y' then begin
; creating output files for single-subscan analysis
if fitchoice eq 'linear' or fitchoice eq 'both' then begin
openw, Unit3, list[i]+sep+scanname+'_single_linear.txt', /GET_LUN
printf, Unit3,' Name # MJD El(r) El(d) cnt_0 cnt_1 e_c_0 e_c_1 offL(d) offR(d) FW/HP scantype'
endif
if fitchoice eq 'cubic' or fitchoice eq 'both' then begin
openw, Unit4, list[i]+sep+scanname+'_single_cubic.txt', /GET_LUN
printf, Unit4,' Name # MJD El(r) El(d) cnt_0 cnt_1 e_c_0 e_c_1 offL(d) offR(d) FW/HP scantype'
endif
openw, Unit5, list[i]+sep+'tar_prints.txt', /GET_LUN
endif
; Dynamic arrays (for amplitudes and errors, for each section)
Lampl=[ ]
Rampl=[ ]
Lerrs=[ ]
Rerrs=[ ]
offset_sub=[ ]
type=[ ]
mean_lat=[ ]
; readout of the previously produced files, containing the list of counts-to-Jy factors achieved on calibrators
if fitchoice eq 'linear' or fitchoice eq 'both' then begin
lincal=file_search(calpath+sep+'cnt2jy_exlin.txt', count=lincalnum)
if lincalnum eq 0 then begin
print, '++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++'
print, 'cnt2Jy_lin factors not found. Assuming cnt2Jy=1 and returning all amplitudes in raw counts
print, '++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++'
endif else begin
readcol, calpath+sep+'cnt2jy_exlin.txt', lincalname, linfre, lintime_i, lintime_f, linm_0, linc2j_0, err_linm_0, err_linc2j_0, linm_1, linc2j_1, err_linm_1, err_linc2j_1, format='(A,D,D,D,D,D,D,D,D,D,D,D)', /SILENT
endelse
endif
if fitchoice eq 'cubic' or fitchoice eq 'both' then begin
cubcal=file_search(calpath+sep+'cnt2jy_excub.txt', count=cubcalnum)
if cubcalnum eq 0 then begin
print, '++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++'
print, 'cnt2Jy_cub factors not found. Assuming cnt2Jy=1 and returning all amplitudes in raw counts
print, '++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++'
endif else begin
readcol, calpath+sep+'cnt2jy_excub.txt', cubcalname, cubfre, cubtime_i, cubtime_f, cubm_0, cubc2j_0, err_cubm_0, err_cubc2j_0, cubm_1, cubc2j_1, err_cubm_1, err_cubc2j_1, format='(A,D,D,D,D,D,D,D,D,D,D,D)', /SILENT
endelse
endif
; subscan-based measurements
for j=0,subnumber-1 do begin
; READ DATA TABLE (binary data tables)
data=MRDFITS(sublist[j],4,/SILENT)
RFinfo=MRDFITS(sublist[j],2,/SILENT)
Sectinfo=MRDFITS(sublist[j],1,/SILENT)
; read frequency and bandwith from RF table
bw=RFinfo[0].bandWidth
freq=RFinfo[0].frequency+bw/2.0
dt=1.0/(Sectinfo[0].sampleRate*1e6)
ndat = (size(data.time))
;assigning an MJD value to this subscan (first sample)
mymjd=data[0].time
if fitchoice eq 'linear' or fitchoice eq 'both' then begin
if lincalnum eq 0 then begin
; forcing cnt2Jy values to 1.0 --> final "fluxes" will be expressed in raw counts
mylinc2j_0=1.0
mylinc2j_1=1.0
err_mylinc2j_0=1.0
err_mylinc2j_1=1.0
endif else begin
; find which cnt2Jy interval contains such MJD - LINEAR-FIT-BASED data
my_lin_interval=where(((mymjd-lintime_i) ge 0) and ((mymjd-lintime_f) le 0))
if my_lin_interval eq -1 then begin
; the target observation time does not belong to any of the available intervals
; thus some degree of approximation is needed
if mymjd le lintime_i[0] then begin
; my target was observed before the first available cnt2Jy interval: I'll use the first cnt2Jy value
my_lin_interval=0
endif else begin
if mymjd ge lintime_f[-1] then begin
; my target was observed after the last available cnt2Jy interval: I'll use the last cnt2Jy value
my_lin_interval=-1
endif else begin
; my target was observed in between calibrators, but outside any of the intervals available:
; going to the nearest value/interval as a compromise!
min_dist_to_init=min(abs(mymjd-lintime_i))
min_dist_to_final=min(abs(mymjd-lintime_f))
if min_dist_to_final lt min_dist_to_init then begin
my_lin_interval=where(abs(mymjd-lintime_f) eq min(abs(mymjd-lintime_f)))
endif else begin
my_lin_interval=where(abs(mymjd-lintime_i) eq min(abs(mymjd-lintime_i)))
endelse
endelse
endelse
endif
if j eq 0 then printf, Unit2, 'EXLIN calib interval: ', my_lin_interval, ' for scan ', scanname, format='(A,1X,I3,1X,A,1X,A)'
; assigning the identified best-matching cnt2Jy values to the final attributes, for the subsequent analysis
mylinc2j_0=linc2j_0[my_lin_interval]+mymjd*linm_0[my_lin_interval]
mylinc2j_1=linc2j_1[my_lin_interval]+mymjd*linm_1[my_lin_interval]
; err_mylinc2j_0=mylinc2j_0*sqrt(err_linc2j_0[my_lin_interval]^2+mymjd*err_linm_0[my_lin_interval]^2) ; originale errato
; err_mylinc2j_1=mylinc2j_1*sqrt(err_linc2j_1[my_lin_interval]^2+mymjd*err_linm_1[my_lin_interval]^2)
err_mylinc2j_0=sqrt(err_linc2j_0[my_lin_interval]^2+mymjd*err_linm_0[my_lin_interval]^2)
err_mylinc2j_1=sqrt(err_linc2j_1[my_lin_interval]^2+mymjd*err_linm_1[my_lin_interval]^2)
endelse
endif
if fitchoice eq 'cubic' or fitchoice eq 'both' then begin
if cubcalnum eq 0 then begin
; forcing cnt2Jy values to 1.0 --> final "fluxes" will be expressed in raw counts
mycubc2j_0=1.0
mycubc2j_1=1.0
err_mycubc2j_0=1.0
err_mycubc2j_1=1.0
endif else begin
; find which cnt2Jy interval contains such MJD - CUBIC-FIT-BASED data
my_cub_interval=where(((mymjd-cubtime_i) ge 0) and ((mymjd-cubtime_f) le 0))
if my_cub_interval eq -1 then begin
; the target observation time does not belong to any of the available intervals
; thus some degree of approximation is needed
if mymjd le cubtime_i[0] then begin
; my target was observed before the first available cnt2Jy interval: I'll use the first cnt2Jy value
my_cub_interval=0
endif else begin
if mymjd ge cubtime_f[-1] then begin
; my target was observed after the last available cnt2Jy interval: I'll use the last cnt2Jy value
my_cub_interval=-1
endif else begin
; my target was observed in between calibrators, but outside any of the intervals available:
; going to the nearest value/interval as a compromise!
min_dist_to_init=min(abs(mymjd-cubtime_i))
min_dist_to_final=min(abs(mymjd-cubtime_f))
if min_dist_to_final lt min_dist_to_init then begin
my_cub_interval=where(abs(mymjd-cubtime_f) eq min(abs(mymjd-cubtime_f)))
endif else begin
my_cub_interval=where(abs(mymjd-cubtime_i) eq min(abs(mymjd-cubtime_i)))
endelse
endelse
endelse
endif
if j eq 0 then printf, Unit2, 'EXCUB calib interval: ', my_cub_interval, ' for scan ', scanname, format='(A,1X,I3,1X,A,1X,A)'
; assigning the identified best-matching cnt2Jy values to the final attributes, for the subsequent analysis
mycubc2j_0=cubc2j_0[my_cub_interval]+mymjd*cubm_0[my_cub_interval]
mycubc2j_1=cubc2j_1[my_cub_interval]+mymjd*cubm_1[my_cub_interval]
; err_mycubc2j_0=mycubc2j_0*sqrt(err_cubc2j_0[my_cub_interval]^2+mymjd*err_cubm_0[my_cub_interval]^2) ; originale errato
; err_mycubc2j_1=mycubc2j_1*sqrt(err_cubc2j_1[my_cub_interval]^2+mymjd*err_cubm_1[my_cub_interval]^2)
err_mycubc2j_0=sqrt(err_cubc2j_0[my_cub_interval]^2+mymjd*err_cubm_0[my_cub_interval]^2)
err_mycubc2j_1=sqrt(err_cubc2j_1[my_cub_interval]^2+mymjd*err_cubm_1[my_cub_interval]^2)
; check per la revisione del sistema di calcolo/utilizzo dei cnt2Jy
; print, 'c2j0 medio - c2j1 medio - err orig0 - err orig1 - err c2j0 medio - err c2j1 medio
; print, mycubc2j_0, mycubc2j_1, err_cubc2j_0[my_cub_interval], err_cubc2j_1[my_cub_interval], err_mycubc2j_0, err_mycubc2j_1, format='(D6.4,1X,D6.4,1X,D6.4,1X,D6.4,1X,D6.4,1X,D6.4)'
; print, ' '
; stop
endelse
endif
; UNCOMMENT IF WANTING TO PRINT THE cnt2Jy choice at runtime
; print, '***********************************************'
; if fitchoice eq 'linear' or fitchoice eq 'both' then begin
; print, '** Chosen cnt2Jy values for LIN (pos, v0, v1): ', my_lin_interval+1, mylinc2j_0, mylinc2j_1
; endif
; if fitchoice eq 'cubic' or fitchoice eq 'both' then begin
; print, '** Chosen cnt2Jy values for CUB (pos, v0, v1): ', my_cub_interval+1, mycubc2j_0, mycubc2j_1
; endif
; print, '***********************************************'
; takes source name and subscantype from header
mainh=mrdfits(sublist[j],0,head0,/silent)
; assessing whether this is an old converted FITS
findh0key, head0, '*Converted FITS*', keylab, converted, infolab, convertedflag
findh0key, head0, '*Obtained from ESCS 0.1 TP FITS*', keylab, version, infolab, oldestflag
if convertedflag eq 0 then begin ; this IS NOT a converted file: ESCS 0.3 keyword names hold
findh0key, head0, '*SOURCE*', keylab, target, infolab, tarflag
findh0key, head0, '*SubScanType =*', keylab, orscantype, infolab, tarflag
findh0key, head0, '*Azimuth Offset =*', keylab, hAZoff, infolab, typeflag ; offset utente e di sistema
findh0key, head0, '*Elevation Offset =*', keylab, hELoff, infolab, typeflag ; offset utente e di sistema
findh0key, head0, '*RightAscension Offset =*', keylab, hRAoff, infolab, typeflag ; offset utente e di sistema
findh0key, head0, '*Declination Offset =*', keylab, hDECoff, infolab, typeflag ; offset utente e di sistema
findh0key, head0, '*RightAscension =*', keylab, ras, infolab, typeflag ; RA nominale del target, radianti
findh0key, head0, '*Declination =*', keylab, decs, infolab, typeflag ; DEC nominale del target, radianti
endif else begin ; this IS a converted file: custom 8-char keyword names hold according to original FITS date, and offsets are not present
findh0key, head0, '*SOURCE*', keylab, target, infolab, tarflag
findh0key, head0, '*SUBSCANT=*', keylab, orscantype, infolab, tarflag
hAZoff=0.0d
hELoff=0.0d
hRAoff=0.0d
hDECoff=0.0d
if oldestflag eq 0 then begin
findh0key, head0, '*RightAscension =*', keylab, ras, infolab, typeflag ; RA nominale del target, radianti
findh0key, head0, '*Declination =*', keylab, decs, infolab, typeflag ; DEC nominale del target, radianti
endif else begin ; these are the oldest FITS, where several more keywords have converted names
findh0key, head0, '*RIGHTASC=*', keylab, ras, infolab, typeflag ; RA nominale del target, radianti
findh0key, head0, '*DECLINAT=*', keylab, decs, infolab, typeflag ; DEC nominale del target, radianti
endelse
endelse
target=strcompress(target, /remove_all)
cleantarget=strsplit(target,"'",/extract)
target=cleantarget[0]
sourcename=target
; nominal target coordinates, converted in degrees
rasd=ras*180.0d/!dpi
decsd=decs*180.0d/!dpi
elapsed=(double(data.time)-double(data[0].time))*24.0*3600.0 ; elapsed time from first sample
duration=dt*ndat[1]/60.0 ; duration of the whole subscan (approx)
; RA and DEC span of the subscan
deltaDec=abs(data[0].decj2000-data[-1].decj2000)/!dpi*180.0
deltaRA=abs(data[0].raj2000-data[-1].raj2000)*cos(mean(data.decj2000))/!dpi*180.0
; determine speed (deg/min) along scan direction
; if type is AZ or EL, treats is as DEC or RA depending on which quantity spans a larger range
splitscantype=strsplit(orscantype,"'",/extract)
cleanscantype=strcompress(splitscantype[1], /remove_all) ; cleaning the string so that it become more manageable
case cleanscantype of
'DEC': begin
if (data[0].decj2000 lt data[-1].decj2000) then scantype = 1 else scantype = 2
speed=deltaDec/duration
end
'RA': begin
if (data[0].raj2000 lt data[-1].raj2000) then scantype = 3 else scantype = 4
speed=deltaRA/duration
end
'AZ': begin
if (deltaDec gt deltaRA) then begin
if (data[0].decj2000 lt data[-1].decj2000) then scantype = 1 else scantype = 2
speed=deltaDec/duration
endif
if (deltaDec lt deltaRA) then begin
if (data[0].raj2000 lt data[-1].raj2000) then scantype = 3 else scantype = 4
speed=deltaRA/duration
endif
end
'EL': begin
if (deltaDec gt deltaRA) then begin
if (data[0].decj2000 lt data[-1].decj2000) then scantype = 1 else scantype = 2
speed=deltaDec/duration
endif
if (deltaDec lt deltaRA) then begin
if (data[0].raj2000 lt data[-1].raj2000) then scantype = 3 else scantype = 4
speed=deltaRA/duration
endif
end
'UNKNOWN': begin
if (deltaDec gt deltaRA) then begin
if (data[0].decj2000 lt data[-1].decj2000) then scantype = 1 else scantype = 2
speed=deltaDec/duration
endif
if (deltaDec lt deltaRA) then begin
if (data[0].raj2000 lt data[-1].raj2000) then scantype = 3 else scantype = 4
speed=deltaRA/duration
endif
end
endcase
; check for spikes in X-band wide bandwidth data XXX Perché farlo solo per la banda X?
if (bw gt 500 and freq lt 10000) then begin
for k=3, ndat[1]-4 do begin
temp0=[data[k-3].ch0,data[k-2].ch0,data[k-1].ch0,data[k+1].ch0,data[k+2].ch0,data[k+3].ch0]
temp1=[data[k-3].ch1,data[k-2].ch1,data[k-1].ch1,data[k+1].ch1,data[k+2].ch1,data[k+3].ch1]
avech0=mean(temp0)
avech1=mean(temp1)
stdch0=stddev(temp0)
stdch1=stddev(temp1)
if ((data[k].ch0-avech0) gt 7*stdch0) then begin
data[k].ch0=avech0
endif
if ((data[k].ch1-avech1) gt 7*stdch1) then begin
data[k].ch1=avech1
endif
endfor
endif
; reverse arrays for scans in decreasing RA or Dec
if (scantype eq 2 or scantype eq 4) then begin
; data=reverse(data)
data.raj2000=reverse(data.raj2000)
data.decj2000=reverse(data.decj2000)
if freq ge 18000 and site eq 'MED' and ksectchoice eq 'mf' then begin
data.ch10=reverse(data.ch10)
data.ch11=reverse(data.ch11)
endif else begin
data.ch0=reverse(data.ch0)
data.ch1=reverse(data.ch1)
endelse
endif
; computing the sample offset with respect to the source position
xdec=(data.decj2000-decs)/!dpi*180.0
xra=(data.raj2000-ras)*cos(mean(data.decj2000))/!dpi*180.0
; scanname = sublist[j]
case flagcode[j] of
'-1c0': begin
k0=1
k1=0
end
'-1c1': begin
k0=0
k1=1
end
'+0cx': begin
k0=1
k1=1
end
'+1cx': begin
k0=1
k1=1
end
'-1cx': begin
k0=0
k1=0
end
endcase
; shift scans of type 'Dec' so they align with first one; sets start and end value of array with data from every scan
if (scantype eq 1 or scantype eq 2) then begin
if ((numLA+numRA) eq 0) then begin
dataA=data
ndatA=ndat
xdecA=xdec
iiA=0
if (k0+k1 gt 0) then ffA=ndatA[1]-1
decoffA = min(xdecA,xdec0A,/ABSOLUTE) ; xdec0A is the number of sample at the source declination for scan A
endif else begin
decoff = min(xdec,xdec0,/ABSOLUTE)
; shift data by (xdec0-xdec0B) samples
ndelta=xdec0-xdec0A
if (ndelta gt 0) then begin
iiA=iiA
if (k0+k1 gt 0) then ffA=min([ffA,ndat[1]-1-ndelta])
for k=iiA,ffA do begin
if (k0+k1 gt 0) then data[k]=data[k+ndelta]
endfor
endif
if (ndelta lt 0) then begin
if (k0+k1 gt 0) then iiA=max([iiA,0-ndelta])
; here we have a problem: we would like to start from ffA and go down to iiA, since ffA can be filled by shifting "data" right. but data only has dimension ndat, not ndat-ndelta (ndelta is <0)
; ffA=min([ffA,ndat[1]-1-ndelta])
if (k0+k1 gt 0) then ffA=min([ffA,ndat[1]-1])
for k=ffA,iiA,-1 do begin
if (k0+k1 gt 0) then data[k]=data[k+ndelta]
endfor
endif
if (ndelta eq 0) then begin
if (k0+k1 gt 0) then ffA=min([ffA,ndat[1]-1])
endif
endelse
endif
; shifts scans of type 'RA' so they align with first one; sets start and end value of array with data from every scan
if (scantype eq 3 or scantype eq 4) then begin
if ((numLB+numRB) eq 0) then begin
dataB=data
ndatB=ndat
xraB=xra
iiB=0
if (k0+k1 gt 0) then ffB=ndatB[1]-1
raoffB = min(xraB,xra0B,/ABSOLUTE) ; xra0B is the number of sample at the source right ascension for scan B
endif else begin
raoff = min(xra,xra0,/ABSOLUTE)
; shift data by (xra0-xra0B) samples
ndelta=xra0-xra0B
if (ndelta gt 0) then begin
iiB=iiB
if (k0+k1 gt 0) then ffB=min([ffB,ndat[1]-1-ndelta])
for k=iiB,ffB do begin
if (k0+k1 gt 0) then data[k]=data[k+ndelta]
endfor
endif
if (ndelta lt 0) then begin
if (k0+k1 gt 0) then iiB=max([iiB,0-ndelta])
; here we have a problem: we would like to start from ffB and go down to iiB, since ffB can be filled by shifting "data" right. but data only has dimension ndat, not ndat-ndelta (ndelta is <0)
; ffB=min([ffB,ndat[1]-1-ndelta])
if (k0+k1 gt 0) then ffB=min([ffB,ndat[1]-1])
for k=ffB,iiB,-1 do begin
if (k0+k1 gt 0) then data[k]=data[k+ndelta]
endfor
endif
if (ndelta eq 0) then begin
if (k0+k1 gt 0) then ffB=min([ffB,ndat[1]-1])
endif
endelse
endif
time_s = (data.time-data[round(ndat[1]/2)].time)*24.d0*3600.d0
midscan=FIX(ndat[1]/2)
beamspan= beam/speed ; duration of acquisition for one beamwidth
Nsamples=ROUND(beamspan/dt) ; number of samples in one beamwidth
el_d=data[midscan].el*180.0/!dpi
g_0=A_0[0]+A_0[1]*el_d+A_0[2]*el_d^2+A_0[3]*el_d^3
g_1=A_1[0]+A_1[1]*el_d+A_1[2]*el_d^2+A_1[3]*el_d^3
if keyword_set(skipgc) then begin
; Overriding the gain computation and applying a flat gain curve (constant value = 1.0)
g_0=1.0
g_1=1.0
endif
; actually sums counts only for scans flagged as good and sets inputs for single scan fit
if ( scantype eq 1 or scantype eq 2) then begin
if freq ge 18000 and site eq 'MED' and ksectchoice eq 'mf' then begin
if (k0 ne 0) then sommaLA = sommaLA + k0*data.ch10/g_0
if (k1 ne 0) then sommaRA = sommaRA + k1*data.ch11/g_1
endif else begin
if (k0 ne 0) then sommaLA = sommaLA + k0*data.ch0/g_0
if (k1 ne 0) then sommaRA = sommaRA + k1*data.ch1/g_1
endelse
numLA = numLA + k0*1
numRA = numRA + k1*1
ascissa=(data.decj2000-hDECoff)*180d/!dpi
gpos=decsd
endif else begin
if freq ge 18000 and site eq 'MED' and ksectchoice eq 'mf' then begin
if (k0 ne 0) then sommaLB = sommaLB + k0*data.ch10/g_0
if (k1 ne 0) then sommaRB = sommaRB + k1*data.ch11/g_1
endif else begin
if (k0 ne 0) then sommaLB = sommaLB + k0*data.ch0/g_0
if (k1 ne 0) then sommaRB = sommaRB + k1*data.ch1/g_1
endelse
numLB = numLB + k0*1
numRB = numRB + k1*1
ascissa=(data.raj2000-hRAoff/cos(mean(data.decj2000)))*180d/!dpi
gpos=rasd
endelse
if dosingle eq 'y' then begin
if (fitchoice eq 'linear') or (fitchoice eq 'both') then begin
; fit single subscans with linear + gaussian
Lfwhm=0
Rfwhm=0
if freq ge 18000 and site eq 'MED' and ksectchoice eq 'mf' then begin
yy0=data.ch10/g_0
yy1=data.ch11/g_1
endif else begin
yy0=data.ch0/g_0
yy1=data.ch1/g_1
endelse
if (scantype eq 1 or scantype eq 2) then tipo=0 else tipo=1
; pro targetfit, scanflag,stacflag,polyflag,section,tipo,namefile,Out3,cnt2Jy,err_cnt2Jy,datael,tau0, xx,yy,ii,ff,x_mid,Nsamples,sd_sub,gpos,decsd,rasd, fwhm, n_off, off, p, e, c, d, SNR, plo, doplot
targetfit, k0,'single','linear','Ch_0',tipo,list[i],subscan[j],Unit5,mylinc2j_0,err_mylinc2j_0,data[0].el,tau0L,ascissa,yy0,0,ndat[1]-1,midscan,Nsamples,sd*(1.+tipo*(1./cos(decs)-1.)),gpos,decsd,rasd, Lfwhm, nL, offL, peak_cnt_0, err_cnt_0, dum3, dum4, dum5, psingle, doplot
targetfit, k1,'single','linear','Ch_1',tipo,list[i],subscan[j],Unit5,mylinc2j_1,err_mylinc2j_1,data[0].el,tau0R,ascissa,yy1,0,ndat[1]-1,midscan,Nsamples,sd*(1.+tipo*(1./cos(decs)-1.)),gpos,decsd,rasd, Rfwhm, nR, offR, peak_cnt_1, err_cnt_1, dum3, dum4, dum5, psingle, doplot
; NOTA: modificata la gestione del caso /sub; ora il salvataggio del PDF avviene direttamente dentro alla procedura dataplot,
; che salva un file per ogni chiamata.
if TPlike eq 2 then begin
printf, Unit3, FORMAT = '(a15,D12.5,9(" ",D08.4),i)', sourcename, data[midscan].time,$
data[midscan].el, el_d, peak_cnt_0, peak_cnt_1, err_cnt_0, err_cnt_1, offL, offR, Lfwhm/beam, scantype
endif else begin
printf, Unit3, FORMAT = '(a15,1X,D12.5,1X,D08.4,1X,D08.4,1X,E12.6,1X,E12.6,1X,E12.6,1X,E12.6,1X,D08.4,1X,D08.4,1X,D08.4,1X,i)', sourcename, data[midscan].time,$
data[midscan].el, el_d, peak_cnt_0, peak_cnt_1, err_cnt_0, err_cnt_1, offL, offR, Lfwhm/beam, scantype
endelse
endif
if (fitchoice eq 'cubic') or (fitchoice eq 'both') then begin
; fit single subscans with cubic + gaussian
Lfwhm=0
Rfwhm=0
if freq ge 18000 and site eq 'MED' and ksectchoice eq 'mf' then begin
yy0=data.ch10/g_0
yy1=data.ch11/g_1
endif else begin
yy0=data.ch0/g_0
yy1=data.ch1/g_1
endelse
if (scantype eq 1 or scantype eq 2) then tipo=0 else tipo=1
targetfit, k0,'single','cubic','Ch_0',tipo,list[i],subscan[j],Unit5,mycubc2j_0,err_mycubc2j_0,data[0].el,tau0L,ascissa,yy0,0,ndat[1]-1,midscan,Nsamples,sd*(1.+tipo*(1./cos(decs)-1.)),gpos,decsd,rasd, Lfwhm, nL, offL, peak_cnt_0, err_cnt_0, dum3, dum4, dum5, psingle, doplot
targetfit, k1,'single','cubic','Ch_1',tipo,list[i],subscan[j],Unit5,mycubc2j_1,err_mycubc2j_1,data[0].el,tau0R,ascissa,yy1,0,ndat[1]-1,midscan,Nsamples,sd*(1.+tipo*(1./cos(decs)-1.)),gpos,decsd,rasd, Rfwhm, nR, offR, peak_cnt_1, err_cnt_1, dum3, dum4, dum5, psingle, doplot
; NOTA: modificata la gestione del caso /sub; ora il salvataggio del PDF avviene direttamente dentro alla procedura dataplot,
; che salva un file per ogni chiamata.
if TPlike eq 2 then begin
printf, Unit4, FORMAT = '(a15,D12.5,9(" ",D08.4),i)', sourcename, data[midscan].time,$
data[midscan].el, el_d, peak_cnt_0, peak_cnt_1, err_cnt_0, err_cnt_1, offL, offR, Lfwhm/beam, scantype
endif else begin
printf, Unit4, FORMAT = '(a15,1X,D12.5,1X,D08.4,1X,D08.4,1X,E12.6,1X,E12.6,1X,E12.6,1X,E12.6,1X,D08.4,1X,D08.4,1X,D08.4,1X,i)', sourcename, data[midscan].time,$
data[midscan].el, el_d, peak_cnt_0, peak_cnt_1, err_cnt_0, err_cnt_1, offL, offR, Lfwhm/beam, scantype
endelse
endif
if (nL+nR gt 0) then offset_sub = [offset_sub,(offL+offR)/(nL+nR)]
endif
endfor
if dosingle eq 'y' then begin
; closing the output files and freeing memory
if fitchoice eq 'linear' or fitchoice eq 'both' then begin
close, Unit3
FREE_LUN, Unit3
endif
if fitchoice eq 'cubic' or fitchoice eq 'both' then begin
close, Unit4
FREE_LUN, Unit4
endif
close, Unit5
free_lun, Unit5, /force
endif
; stacked analysis begins
for tipo = 0,1 do begin
ascissa=time_s ; default if all subscans are void
; set some inputs
case tipo of
0: begin
if (numLA+numRA gt 0) then begin
if (numLA gt 0) then sommaL = sommaLA/numLA else sommaL = sommaLA
if (numRA gt 0) then sommaR = sommaRA/numRA else sommaR = sommaRA
numL = numLA
numR = numRA
ii=iiA
ff=ffA
; tipo=0 means scan declination, ie scantype Dec, ie constant RA
ascissa=(dataA.decj2000-hDECoff)*180d/!dpi
xdiffA = min(ascissa-decsd,x_mid,/ABSOLUTE) ; x_mid contains the sample number nearest to the source nominal position
gpos=decsd
endif else begin
numL=0
numR=0
endelse
end
1: begin
if (numLB+numRB gt 0) then begin
if (numLB gt 0) then sommaL = sommaLB/numLB else sommaL = sommaLB
if (numRB gt 0) then sommaR = sommaRB/numRB else sommaR = sommaRB
numL = numLB
numR = numRB
ii=iiA
ff=ffB
; tipo=1 means scan right asc., ie scantype RA, ie constant Dec
ascissa=(dataB.raj2000-hRAoff/cos(mean(dataB.decj2000)))*180d/!dpi
xdiffB = min(ascissa-rasd,x_mid,/ABSOLUTE) ; x_mid contains the sample number nearest to the source nominal position
gpos=rasd
endif else begin
numL=0
numR=0
endelse
end
endcase
PRINTF, Unit2, " "
; PRINTF, Unit2, "****** "+scanname+" ******"
PRINTF, Unit2, FORMAT = '("* MJD = ", D014.8)', data[midscan].time
PRINTF, Unit2, "* nsamples = ", ndat[1]
PRINTF, Unit2, "* Beamspan = ", beamspan, " [s]"
PRINTF, Unit2, "* Beam samples = ", Nsamples
if fitchoice eq 'linear' or fitchoice eq 'both' then begin