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This section gives a quick summary of how photometric calibration can be done in Astro-WISE.
Photometric calibration in Astro-WISE is done by comparing the counts in standard stars on images to their magnitudes as listed in a reference catalog of standard stars. The final result is a PhotometricParameters object which stores the zeropoint and extinction. This object can then be used to photometrically calibrate your ReducedScienceFrames.
Lets again consider the OmegaCAM data used in previous exercises. It was observed the night of 31 May 2012, using the r filter. A Landolt standard star field, SA113, was observed that night. ReducedScienceFrames already exist in the database for that standard field exposure:
awe> q = ReducedScienceFrame.template.start == dateutil.parser.parse('2012-06-01T09:38:56') awe> len(q) 32Lets again only look at CCD#65:
awe> q = q & (ReducedScienceFrame.chip.name == 'ESO_CCD_#65')
awe> filenames = [red.filename for red in q] awe> task = PhotcatTask(instrument='OMEGACAM', red_filenames=filenames, ... transform=1, inspect=1, commit=1) awe> task.execute()red_filenames is a list of the filenames of the ReducedScienceFrames of the standard star observations. transform=1 ensures that differences between the passbands of the instrument and the standard photometric system are accounted for. inspect=1 means a plot will be created to inspect the resulting crossmatch (default inspect=0). commit=1 ensures the result is saved in the database (default commit=0). The above command uses default settings for process parameters such as the standard stars to use and the configuration of the source extraction algorithm.
awe> task = PhotomTask(instrument='OMEGACAM', red_filenames=filenames, ... pars={'PhotometricParameters.process_params.SIGCLIP_LEVEL': 3.5}, ... inspect=1, commit=1) awe> task.execute()where red_filenames, inspect and commit have the same meaning as for the Photometric Source Catalog. The process parameter for sigma clipping was increased; it removed individual standard star measurements which differ by more than 3.5 standard deviations from the median from the calculation of the zeropoint. The above command uses a default atmospheric extinction correction.
After following these steps ReducedScienceFrames which contain your scientific targets can be photometrically calibrated using the PhotometricParameters object.
awe> refcat = PhotRefCatalog.get() awe> refcat.retrieve()To explore its content, see the possibilities by typing:
awe> dir(refcat)For example:
awe> mag_dict = refcat.get_dict_of_magnitudes('SloanR')
awe> q[0].retrieve()Display it in skycat:
awe> q[0].display()Retrieve the standard star catalog in skycat format to local disk:
awe> refcat.make_skycat()To find its filename:
awe> os.system('ls *scat')Use the ``File'' menu in skycat to load and display the image and the ``Data-servers>
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