Data Reduction Recipe for an LWS01 AOT.

The case of a medium brightness source.

Sergio Molinari


0. About this recipe...

What this recipe is: What this recipe is not: This recipe is a worked example of real LWS data reduction and analysis; it covers many of the peculiar instrumental effects that affect the quality of your data, but certainly not all. In these cases we encourage you to check the LWS and LIA FAQs; should your question remain unanswered, please contact us at if in the U.S, or if in Europe.

Recent changes: Sects 3.2 and 3.4.

1. Definitions & Requirements

2. Inspecting your Data

A preliminary inspection of your data is useful to get a feeling of what you have in your hands, and to spot potential problems you will have to take care of during the data reduction. Let's start by entering ISAP:

3. Reprocessing your Data with LIA

Let's start this Section with a recommendation: it is always advisable to have a go with LIA, also if the preliminary analysis with ISAP did not show any particular problem. It is good to have a look at the dark current and at the raw data to check that everything is all right; a trend of decreasing dark current, e.g., may reflect in an increased scatter of your grating scans (i.e. an increased noise of your averaged spectrum). Besides, the comparison of your data with the Dark Currents will tell you if you are detecting signal or you just reached the sensitivity limit of the instrument.

There are 4 steps in the LIA reprocessing of an LWS01 AOT:

3.1 Dark Currents

The tool to be used is IA_DARK. A full tutorial describing its functionality is accessible at; in the following, it is assumed that you are familiar with that document (or at least have it at hand).

While at the ISAP> prompt, type: IA_DARK, tdt='TDT', where TDT is the eight digit number attached to the filename of all you data files. If you are running ISAP in a directory which is different from the one where your data files are stored, an additional parameter has to be given; the call would then be: IA_DARK,tdt='TDT',dir='your directory'. Once the widget is up, click on detector SW3. You will see this:

Fig. 7

The red crosses are the DC measurements, while the white points are your (uncalibrated) data; everything is plotted as a function of time. If your observations was taken at a revolution number earlier than about 400 you may see DC measurements (red crosses) taken in between the observation; however only the first and the last (before and after your observation) DC measurements can actually be used.

Here the various scans of the grating can be recognized as an oscillating pattern on your data. Remember that this data is still uncalibrated at this stage and the transmission profiles (called RSRF, 1 per detector) of the instrument are still to be divided out. To check where the different scans start and end, go with the mouse on a point and click the middle button of the mouse: the text area at the bottom of the IA_DARK widget will give you all the information regarding the nearest point to the mouse actual position.  Again, it is important to remember that at this stage the instrumental transmission is not yet divided out and, if there is sufficient flux from your source, it will manifest itself as a periodic pattern throughout your dataset; it is not anything you want to model and subtract as a DC or Gain trend.

You will note that the average signal from the source is about a factor 4 higher than the DC values. In a case like this an incorrect DC estimate will not affect your data unless the DC is wrong by a factor 4 of course. It is always an advisable practice to check and possibily refine the DC
estimates also if the refinement is not going to affect your data, because the DCs are also subtracted from your illuminator flash data before estimating the Absolute Responsivity Correction Factors. An increasing trend is clearly visible in the data, but since the DCs are much lower than that, it must be a gain trend; we can correct for this in  IA_DRIFT or in ISAP.

Speaking of instrumental trends, If you have a Raster Map you will be in the uncomfortable situation to have a signal variation during the observation. In a single pointing observation, you are sure that the intrinsic signal from the source is not varying so that you can assign trends either to DC or Gain variations (and remove them). In a raster, unless you have an extended uniform brightness source, the intrinsic signal is varying; it is practically impossible to spot a trend in the instrument behaviour in this conditions.

3.2 Responsivity Drifts

With the possibility of `shifting spectral scans'  which will be available with ISAP version 2.0, the routine IA_DRIFT, used to correct for temporal responsivity drifts, is likely to become obsolete. This routine was needed because the pipeline incorrectly estimate the responsivity drift before subtracting the DC; it will be much easier and less time consuming to do this with the new ISAP functionality.

The only plausible reason to still use IA_DRIFT is when there is evidence for a non-linear responsivity drift: please refer to the tutorial available at However, if a memory effect is spotted for a detector, i.e. there is a  systematic difference between the two scan directions, it is important you remember the following:

If you have a raster map, remeber what we said above, before trying to estimate and remove a suspect gain trend.

3.3 Absolute Responsivity Correction Factors

The absolute responsivity correction factors can revised using the routine IA_ABSCORR, whose tutorial is available at Since the estimate of these factors is based on the Illuminator Flash data, the characteristics of the source observed are not important; the tutorial has all the information you need to proceed.

3.4 Recalibration

The recalibration of your data is independent on the type of source observed. Instructions to recalibrate your data are found in If you did not use IA_DRIFT to remove the relative responsivity drifts, remember to run SHORT_ALL with the `/nodrift` option.

4. Data Analysis with ISAP

At this time, you should have in your directory a file called LSANxxxxxxxx_SHORT.FITS produced by SHORT_AAL; load this file into ISAP. You can do a straight average and compare the result with the averaged spectrum for the original LSAN file produced by the OLP. Once you are done, we can start with the real work to analyse this data.