Getting To Know Your Baselines

 If you want to start a little data reduction on your spectrum you can remove some baselines or fit some models. There seems to be some controversy about the names of the commands though. Some people claim that a gaussian is not a baseline, it's a model. The difference lies in whether one is removing an instrumental `baseline' or curve which underlies the line itself, or whether one is fitting the line itself with a `model'.

When fitting baselines or models, or doing a number of other operations on spectra, one or more sections of the spectrum need to be specified. For a linear baseline fit, two regions of the baseline need to be identified for the fit. In the case of polynomial fits, one to several such regions can be specified. And for a gaussian fit, one specifies not the baseline, but the line region to be fit. It all makes sense really. Just try it.

One can specify the fit regions either in interactive mode, in which case the cursor (or crosshair) is used to define sections of the spectrum, or by specifying the same sections by typing in the numbers in non-interactive mode. In my view interactive mode can be a pain to use, but the results are worth it. The procedures outlined next for fitting a linear baseline will apply to all situations where x-value ranges are called for.