Commit ae959234 authored by Roberto Susino's avatar Roberto Susino
Browse files

Fix bugs in dark file selection

parent 4e3758f8

metis_dark_uvda.pro

+18 −9
Original line number Diff line number Diff line
@@ -10,12 +10,16 @@ function metis_dark_uvda, data, header, cal_pack, history = history 
	obj_cnt = header.obj_cnt

	obt_beg = header.obt_beg



	; WARN - temporary patch to handle local l1 fits files

	; if tsensor eq 0. then tsensor = -25.



	for i = 0, n_elements(dark) - 1 do begin

		if (dark[i].dit eq dit) and (dark[i].nbin eq nbin) and (dark[i].ndit1 eq ndit1) and (dark[i].ndit2 eq ndit2) and (abs(dark[i].tsensor - tsensor) lt 5) and (abs(obt_beg - dark[i].obt_beg) lt (3600 * 24 * 10)) then begin

		if (dark[i].dit eq dit) and (dark[i].ndit1 eq ndit1) and (dark[i].ndit2 eq ndit2) and (abs(dark[i].tsensor - tsensor) lt 5.) and (abs(obt_beg - dark[i].obt_beg) lt (3600. * 24. * 10.)) then begin

			if obj_cnt eq 1 then begin

				dark_file = dark[i].file_name.cnt_1

				dark_image = float(readfits(cal_pack.path + dark[i].file_name.cnt_1, /silent))

				dark_image = float(readfits(cal_pack.path + dark_file, /silent))

				dark_image = rebin(dark_image, header.naxis1, header.naxis2) * nbin^2



				mask = where(data eq 0., count)

				data = data - dark_image * ndit1 * ndit2

				data[mask] = 0.
@@ -23,8 +27,9 @@ function metis_dark_uvda, data, header, cal_pack, history = history 
				goto, jump

			endif else begin

				dark_file = dark[i].file_name.cnt_2

				dark_image = float(readfits(cal_pack.path + dark[i].file_name.cnt_2, /silent))

				dark_image = float(readfits(cal_pack.path + dark_file, /silent))

				dark_image = rebin(dark_image, header.naxis1, header.naxis2) * nbin^2



				mask = where(data eq 0., count)

				data = data - dark_image * ndit1 * ndit2

				data[mask] = 0.
@@ -36,28 +41,32 @@ function metis_dark_uvda, data, header, cal_pack, history = history 


	obt_available = !null

	for i = 0, n_elements(dark) - 1 do begin

		if (dark[i].dit eq dit) and (abs(dark[i].tsensor - tsensor) lt 5) then begin

			obt_available = [obt_available, dark[i].obt_beg]

		endif

		if (dark[i].dit eq dit) and (abs(dark[i].tsensor - tsensor) lt 5.) then obt_available = [obt_available, dark[i].obt_beg]

	endfor



	if not isa(obt_available) then begin

		dark_file = 'applicable file not found - correction not applied'



		goto, jump

	endif



	delta_obt = min(abs(obt_beg - obt_available), j)

	i = where(dark.obt_beg eq obt_available[j])



	if obj_cnt eq 1 then begin

		if (ndit1 eq dark[i].ndit1) and (ndit2 eq dark[i].ndit2) then begin

			dark_image = float(readfits(cal_pack.path + dark[i].file_name.cnt_1, /silent))

			dark_file = dark[i].file_name.cnt_1

			dark_image = float(readfits(cal_pack.path + dark_file, /silent))

		endif else begin

			q = ndit2/dark[i].ndit2

			dark_file = dark[i].file_name.cnt_1 + ' - ' + dark[i].file_name.cnt_2

			dark_1 = float(readfits(cal_pack.path + dark[i].file_name.cnt_1, /silent))

			dark_2 = float(readfits(cal_pack.path + dark[i].file_name.cnt_2, /silent))

			dark_image = (dark_1 + (q - 1) * dark_2)/q

			dark_file = dark[i].file_name.cnt_1 + ' - ' + dark[i].file_name.cnt_2

		endelse

	endif else begin

		dark_image = float(readfits(cal_pack.path + dark[i].file_name.cnt_2, /silent))

		dark_file = dark[i].file_name.cnt_2

		dark_image = float(readfits(cal_pack.path + dark_file, /silent))

	endelse



	dark_image = rebin(dark_image, header.naxis1, header.naxis2) * nbin^2

metis_dark_vlda.pro

+28 −17
Original line number Diff line number Diff line
@@ -8,15 +8,18 @@ function metis_dark_vlda, data, header, cal_pack, history = history 
	ndit = header.ndit

	nbin = sqrt(header.nbin)

	tsensor = header.tsensor

	obt_beg = header.obt_beg/1000.D0

	obt_beg = header.obt_beg/1000.D0 ; check why obt_beg must be divided by 1000.



	; WARN - temporary patch to handle local l1 fits files

	; if tsensor eq 0. then tsensor = -30.



	for i = 0, n_elements(bias_dark) - 1 do begin

		if bias_dark[i].dit eq dit and bias_dark[i].nbin eq nbin and abs(bias_dark[i].tsensor - tsensor) lt 5 then begin

			dark_image = float(readfits(cal_pack.path + bias_dark[i].file_name, /silent))

		if bias_dark[i].dit eq dit and bias_dark[i].nbin eq nbin and abs(bias_dark[i].tsensor - tsensor) lt 5. then begin

			dark_file = bias_dark[i].file_name

			dark_image = float(readfits(cal_pack.path + dark_file, /silent))

			dark_image = rebin(dark_image, header.naxis1, header.naxis2) * nbin^2 * ndit

			

			mask = where(data eq 0.)

			dark_image = rebin(dark_image, header.naxis1, header.naxis2) * nbin^2 * ndit

			data = data - dark_image

			data[mask] = 0.
@@ -26,25 +29,33 @@ function metis_dark_vlda, data, header, cal_pack, history = history 


	bias_obt_available = !null

	for i = 0, n_elements(bias) - 1 do begin

		if abs(bias[i].tsensor - tsensor) lt 5 then $

		bias_obt_available = [bias_obt_available, bias[i].obt_beg]

		if abs(bias[i].tsensor - tsensor) lt 5. then bias_obt_available = [bias_obt_available, bias[i].obt_beg]

	endfor



	if isa(bias_obt_available) then begin

		delta_obt = min(abs(obt_beg - bias_obt_available), j)

		i = where(bias.obt_beg eq bias_obt_available[j])

		bias_image = float(readfits(cal_pack.path + bias[i].file_name, /silent))

		dark_file = bias[i].file_name

	endif else begin

		bias_image = fltarr(header.naxis1, header.naxis2)

		dark_file = 'applicable bias file not found - correction not applied'

	endelse



	dark_obt_available = !null

	for i = 0, n_elements(dark) - 1 do begin

		if abs(dark[i].tsensor - tsensor) lt 5 then $

		dark_obt_available = [dark_obt_available, dark[i].obt_beg]

		if abs(dark[i].tsensor - tsensor) lt 5. then dark_obt_available = [dark_obt_available, dark[i].obt_beg]

	endfor



	if isa(dark_obt_available) then begin

		delta_obt = min(abs(obt_beg - dark_obt_available), j)

		i = where(dark.obt_beg eq dark_obt_available[j])

		dark_image = float(readfits(cal_pack.path + dark[i].file_name, /silent))

		dark_file = [dark_file, dark[i].file_name]

	endif else begin

		dark_image = fltarr(header.naxis1, header.naxis2)

		dark_file =  [dark_file, 'applicable dark file not found - correction not applied']

	endelse



	bias_image = rebin(bias_image, header.naxis1, header.naxis2) * nbin^2

	dark_image = rebin(dark_image, header.naxis1, header.naxis2) * nbin^2