lc_sigma_clip

Description

The lc_sigma_clip() routine - which used to be called analyze_ltcrv() prior to CIAO 4.1 - uses a simple iterative sigma-clipping routine to detect and remove flares from a lightcurve. For more information see the Filtering Lightcurves thread.

Loading the routine

The routine can be loaded into a Python interpreter - such as chips, sherpa, or ipython - by saying:

from lightcurves import *

See "ahelp lightcurves" for more information on the lightcurves module.

Common arguments

The lc_sigma_clip() and lc_clean() routines share a number of common arguments and options. The filename argument - which is the only required argument for either call - is used to specify the name of the light curve to analyze. The required columns for this file are discussed in the "FORMAT OF LIGHT CURVES" section below.

Common options between the two routines (i.e. those with the same meaning)

Although both routines contain an optional sigma argument, the meaning of this parameter is not exactly the same for the two routines.

Using lc_sigma_clip

The lc_sigma_clip routine performs an iterative sigma-clipping algorithm, removing those points that fall outside the range

mean - n * sigma

to

mean + n * sigma

at each iteration until all data points are within this range. The default value for n is 3.0 but this can be changed using the sigma parameter as described below. This algorithm is robust but not perfect; it can easily "overclean" a noisy lightcurve, or fail to reject any points, and so should not be used blindly.

The two options for lc_sigma_clip are "sigma" and "minlength". The sigma argument determines the value used to clip the count rate data at each iteration, and defaults to 3.0. The minlength option, which defaults to 3, is the minimum number of consecutive bins that must all lie within the final rate limits for that range to be considered good.

How do we use the output GTI file?

If the outfile argument is set, then a GTI file will be created listing those time periods which are considered to be "good" by the algorithm. This file can be used to filter an event file using the following syntax (we assume here that the event file to be filtered is evt2.fits and the output of the routine is called evt.gti):

unix% dmcopy "evt2.fits[@evt.gti]" evt2_filt.fits

A warning about low count-rate lightcurves

The lc_sigma_clip algorithm excludes bins which have a zero count rate, whether it is because the exposure time of the bin is zero or because no counts were detected in this bin. This is because the algorithm is not designed for use with low count-rate data. Therefore the routines should be used with extreme care when applied to data for which zero-rate bins are expected (for example a very-faint source).

A note on times

When run with verbose set to 1, durations are displayed alongside time filters. These values are instructive, but should not be taken as the actual exposure-length of each interval because they may not account for

• the dead-time correction of the observation (DTCOR header keyword);
• exposure variations within the bin due to existing time filters (i.e. the time filters already applied to the observation).

The best way to find out what the final exposure time will be is to create a GTI file, use it to filter the event file, and then look at the EXPOSURE value of the filtered file.