This section should be read thoroughly.
It may often happen that the presence of ``contaminating'' sources scattered all over the field of view makes it difficult to define in an easy way a ``background'' region in the sky.
In this situation the best way to proceed is to take the coordinates of all of the sky sources which were identified by means of the source detection routines (see the Spatial Analysis package chapter for that). With this information, it is possible to prepare an ASCII command file which produces a photon list containing all but the contaminating photons.
Such a command file would consist simply in a sequence of SELECT/RING commands. Each select command would define an annulus centered on a contaminating source, with the internal radius large enough to contain all of the source photons, and the external radius very large (i.e. infinity -- actually it would be enough to take the external radius just large enough to include all the other photons in the dataset).
The result of one of such SELECT commands is to exclude from the data the circle containing the centered contaminating source. In the following command file three contaminating sources are excluded from the data:
INPUT events ! ! Three holes: ! SELECT/RING center = ( 10, 1234) radii = 400 to 99999999 SELECT/RING center = (5647, 634) radii = 400 to 99999999 SELECT/RING center = ( 453, 4521) radii = 400 to 99999999 ! ! Output to a Photon Event Table ! OUTPUT to cleanevents END
The command file in the example performs the complex spatial selection and writes the resulting photon list into the Photon Event Table cleanevents.tbl. In order to execute the command file, one must use the command
Midas 001> MAKE/PROJECTION hole_itwhere it is assumed that the commands are written in the ASCII file hole_it.cmd.
All the next work of Data Preparation will be performed taking as input the Photon Event Table which has been cleaned from the contaminating sources. Any further spatial selection can be performed being sure that no contaminating photons are included in any of the results. The data correction procedures would automatically take care of the effect of the holes on the data (e.g., keeping into account that the area of any selected region that includes any hole, is reduced accordingly).