Commit dc77a722 authored by Roberto Susino's avatar Roberto Susino
Browse files

Add error calculation in VLDA dark corr. procedure

parent 1dc2c61e

metis_dark_vlda.pro

+32 −7
Original line number Diff line number Diff line 
function metis_dark_vlda, data, header, cal_pack, history = history

function metis_dark_vlda, data, header, cal_pack, error = error, quality_matrix = quality_matrix, history = history



	bias = cal_pack.vl_channel.bias

	dark = cal_pack.vl_channel.dark
@@ -6,24 +6,36 @@ function metis_dark_vlda, data, header, cal_pack, history = history 


	dit = header.dit/1000.D0

	ndit = header.ndit

	nbin = header.nbin

	xposure = dit * ndit

	nbin = sqrt(header.nbin)

	tsensor = header.tsensor

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



	gain = cal_pack.vl_channel.radiometry.gain.value



	; WARN - temporary patch to handle local l1 fits files

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

	if tsensor eq 0. then tsensor = -30.



	; check if one or more bias+dark matrices with same dit, binning, and tsensor exist

	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

		if $

			bias_dark[i].dit eq dit and $

			bias_dark[i].nbin^2 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

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

			dark_image = dark_image * ndit

			

			mask = where(data eq 0.)

			data = data - dark_image

			data[mask] = 0.



			; WARN - for this case the error matrix is not provided so the error is not computed



			if isa(error) then error += 0.



			goto, jump

		endif

	endfor
@@ -37,6 +49,7 @@ function metis_dark_vlda, data, header, cal_pack, history = history 
		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))

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

		dark_file = bias[i].file_name

	endif else begin

		journal, 'Error 02: VL applicable bias file not found.'
@@ -53,6 +66,7 @@ function metis_dark_vlda, data, header, cal_pack, history = history 
		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_error = float(readfits(cal_pack.path + dark[i].error, /silent))

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

	endif else begin

		journal, 'Error 03: VL applicable dark file not found.'
@@ -60,14 +74,25 @@ function metis_dark_vlda, data, header, cal_pack, history = history 
		exit, status = 3

	endelse



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

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

	; WARN - error for binning must be checked



	bias_nobin = bias_image

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

	bias_error = bias_image * sqrt(rebin((bias_error/bias_nobin)^2, header.naxis1, header.naxis2)/nbin)

	

	dark_nobin = dark_image

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

	dark_error = dark_image * sqrt(rebin((dark_error/dark_nobin)^2, header.naxis1, header.naxis2)/nbin)



	mask = where(data eq 0.)

	data = data - (bias_image * ndit + dark_image * xposure)

	data[mask] = 0.



	if isa(error) then error += (data * gain + 2. * (bias_error * ndit)^2 + 2. * (dark_error * xposure)^2)/data^2



	jump:

	s = where(data le 0., count)

	if isa(quality_matrix) then quality_matrix[s] = 0



	if ~ isa(history) then history = !null

	history = [history, 'Bias and dark-current corrections: ', '  ' + dark_file]