The hawki_step_refine_offsets recipe



(OBSOLETE) Jitter recipe


(OBSOLETE) hawki_step_refine_offsets – utility to refine the nominal offsets.

This utility will take the offsets in the header as a first approach and tries to refine them correlating the input images at the points given by the detected objects.

The input of the recipe files listed in the Set Of Frames (sof-file) must be tagged as: images.fits DIST_CORRECTED or images.fits BKG_SUBTRACTED and det_obj_stats.fits OBJ_PARAM The recipe creates as an output: hawki_step_refine_offsets.fits (OFFSETS_REFINED): Table with refined offsets Return code: esorex exits with an error code of 0 if the recipe completes successfully or 1 otherwise



Create an object for the recipe hawki_step_refine_offsets.

import cpl
hawki_step_refine_offsets = cpl.Recipe("hawki_step_refine_offsets")



Cross correlation search and measure sizes (str; default: ‘20,20,25,25’) [default=”20,20,25,25”].


Number of brightest objects to use (int; default: 3) [default=3].

The following code snippet shows the default settings for the available parameters.

import cpl
hawki_step_refine_offsets = cpl.Recipe("hawki_step_refine_offsets")

hawki_step_refine_offsets.param.xcorr = "20,20,25,25"
hawki_step_refine_offsets.param.nbrightest = 3

You may also set or overwrite some or all parameters by the recipe parameter param, as shown in the following example:

import cpl
hawki_step_refine_offsets = cpl.Recipe("hawki_step_refine_offsets")
res = hawki_step_refine_offsets( ..., param = {"xcorr":"20,20,25,25", "nbrightest":3})

See also

cpl.Recipe for more information about the recipe object.

Bug reports

Please report any problems to ESO Pipeline Group. Alternatively, you may send a report to the ESO User Support Department.