There are two stages to echmenu wavelength calibration; the first stage is simple; the second stage may be more complex. The first step is to run Option 9 Locate arc line candidates. This searches the arc spectrum for features which look like arc lines. The result is a small list of potential features which can be used in the second stage, wavelength calibration.
echmenu Option 10 Identify features performs wavelength calibration. There are a number of prompts:
ECH_FTRDB - Reference line list database /'$ARCDIRS/THAR'/ > $ARCDIRS/CUAR ARC_TYPE - Type of arc lamp used /'$ARCDIRS/THAR.ARC'/ > $ARCDIRS/CUAR.ARC WAVFIT - Function for wavelength fitting /'POLY'/ > AUTO_ID - YES for fully automatic identification /FALSE/ > HI_WAVE - Longest wavelength to search for arc lines /0/ > LOW_WAVE - Shortest wavelength to search for arc lines /0/ > MAX_DISPERSION - Max dispersion (Units per pixel) allowed /1/ > MIN_DISPERSION - Min dispersion (Units per pixel) allowed /0.01/ > W_NPOLY - Number of coeffs of wavelength fitting function /7/ >
Arc lamp database information for CuAr and ThAr lamps is available,
if you use some other lamp you will need a list of wavelengths for
features in the spectrum of the lamp. Often a ThAr lamp is used,
however, in the example data the lamp used is CuAr,
so you can should set
Note that the names of these files are case-sensitive.
wavfit is the type of fit to use,
poly should be fine.
If you select
echmenu will attempt a fully automatic wavelength calibration.
This will often work; however, it is better to
inspect the fit manually, rather than just accepting it automatically;
so we accept the default
hi_wave and low_wave are limits on the wavelength range that might be covered by the spectrum; setting the limits both to zero (the default) indicates we have no idea of the wavelength range. However, if you do have a rough idea of either or both limits then enter them here. Constraining the wavelength range speeds up the process of feature identification. The units are Angstroms for the ThAr and CuAr databases.
min_dispersion are the limits on the
dispersion of the spectrum. Again, if you know the dispersion, set these
values close to the value to help constrain automatic feature identification.
Inspection of FITS headers may reveal the dispersion used in your data,
you might otherwise look in the instrument handbook for the spectrograph
The units here are Angstroms per detector pixel. The default values are
set for common échelle spectrographs and so may be too small for your
data. If in doubt, set
max_dispersion to a large value and leave
the default for
min_dispersion as it is.
w_npoly is the number of coefficients of fit to use for the wavelength polynomial. The default value of 7 is fine. The fitter will adjust the order automatically the first time a fit is made if the value is unusable.
I(identify features manually). Accept the default by pressing return and (yet) another menu appears. The graphics display will also update showing the arc spectrum. Each potential feature identified in the arc spectrum will be marked by a short vertical dash above the feature. This will be similar-looking to the figure above, except the features will not yet be labelled with wavelengths.
All these sub-menus may appear confusing, however, you can just accept the default to get to the interactive wavelength calibration. The other options are used when the dataset is multi-spectrum or multi-order. You should now have a menu like this one:
Option [Info,Del,Set,Thresh,Auto,New,Plot,Re-interp,Worst,BClip,Fit,+-=, XClip,Clear,Keep,List,Move,Zoom,Ozoom,>,<,Exit,Quit,Help,?]
As you can see, there are rather a large number of options. To apply an
option, type its first letter with the graphics cursor on the displayed plot.
A, which will attempt automatic calibration. You will see
some details of the fit displayed and then a plot with the wavelengths of the
identified features overlaid. For the example dataset this is all you
need to do - you now have a wavelength scale.
If the display zooms on to only a small part of the spectrum hit
R to get a full-spectrum plot.
At this point you may want to have one of the atlases mentioned earlier to hand to check the identifications manually. You can inspect the line-wavelength lists on-line, for example, the ThAr list by:
% more $ARCDIRS/THAR.ARC
The important point in deciding whether the fit is good is the RMS error of the fit. Below is an example of a good fit:
Line Wavelength Calculated Discrepancy RMS if Wavelength omitted 1 297.366 4561.347 4561.349 0.001 0.00232 2 451.861 4567.240 4567.238 -0.002 0.00243 ... other lines ... 9 1300.145 4598.763 4598.759 -0.004 0.00212 10 1599.801 4609.567 4609.568 0.001 0.00207 RMS error: 0.00250. Selected degree for fits: 4. Number of features identified: 10.
You can see that the RMS error is quite small, also the `RMS if omitted
values' are all of similar values. If a mis-identified or badly recorded
feature is included, then this will be indicated by a much lower
`RMS if omitted' than the other features. To remove such a feature:
position the graphics cursor on the feature; hit
D to delete the
feature from the list of features to be fitted; hit
F to apply the
It is important not to over-fit the feature list. In the above example
ten points are fitted with a fourth-order curve; this is fine,
seventh-order would be too high as the errors would then be fitted away.
The plus and minus (
-) keys change the order of fit.
E key when you are happy with the fit.
Simple Spectroscopy Reductions