Python configuration to run odi-tools

The function odi_config.py imports all of the modules needed to run odi-tools as well as sets up the needed dictionaries and directories. It is imported in the following way in the main odi-tool scripts (odi_process, odi_scalestack_process, odi_phot_process).

>>> import odi_config as odi

Once it is imported, the dictionaries are directories created in odi_config.py can be referenced throughout the odi-tools pipeline in the following manner

>>> example_dict = odi.dictionary
>>> example_directory = odi.directory

Similarly, we can also reference all of the modules and functions imported in odi_config.py.

>>> gaps = odi.get_gaps(img, ota)

The OTA dictionaries

There are two dictionaries defined by this function that correspond to different versions of ODI.

  1. podi_dictionary
  2. odi5_dictionary

As an example, here are the contents of podi_dictionary:

podi_dictionary = {1: 'OTA33.SCI',
                   2: 'OTA34.SCI',
                   3: 'OTA44.SCI',
                   4: 'OTA43.SCI',
                   5: 'OTA42.SCI',
                   6: 'OTA32.SCI',
                   7: 'OTA22.SCI',
                   8: 'OTA23.SCI',
                   9: 'OTA24.SCI'
                   }

For those that are not familiar with Python, a dictionary is made up of pairs of keys and values. The keys are to the left of the colon, and the values are to the right. In our case, the keys are the numbers 1-9, and the values are the names of the different OTAs, (e.g. OTA33.SCI). The dictionaries provide a clean way to work through a multi-extension fits image like those produced by ODI. The simpled code example below provides an illustration of how this is done in odi-tools.

>>> images = ['img1.fits','img2.fits']
>>> for img in images:
>>>     for key in podi_dictionary:
>>>         print img, key

This would produce the following output:

'img1.fits' 'OTA33.SCI'
'img1.fits' 'OTA34.SCI'
'img1.fits' 'OTA44.SCI'
'img1.fits' 'OTA43.SCI'
'img1.fits' 'OTA42.SCI'
'img1.fits' 'OTA32.SCI'
'img1.fits' 'OTA22.SCI'
'img1.fits' 'OTA23.SCI'
'img1.fits' 'OTA24.SCI'
'img2.fits' 'OTA33.SCI'
'img2.fits' 'OTA34.SCI'
'img2.fits' 'OTA44.SCI'
'img2.fits' 'OTA43.SCI'
'img2.fits' 'OTA42.SCI'
'img2.fits' 'OTA32.SCI'
'img2.fits' 'OTA22.SCI'
'img2.fits' 'OTA23.SCI'
'img2.fits' 'OTA24.SCI'

Although this is a simple example it illustrates the overall workflow of odi-tools.

The odi5_dictionary works the same way, but simply has more OTAs. The correct dictionary is selected by odi_helpers.instrument(). If the instrument used was 5odi, odi5_dictionary is used for odi-tools, if it was podi, podi_dictionary is used.

Processing directories

odi_config.py also sets up a number of directories to hold the intermediate data products during the data processing. Here is an example of how one of those directories is created

>>> bpmdirectory = 'bpmasks'
>>> if not os.path.exists(bpmdirectory):
>>>    print 'Creating directory for bad pixel masks...'
>>>    os.makedirs(bpmdirectory)

>>> bppath = bpmdirectory+'/'

The directory in this case is given the name bpmasks. Then, we check if the directory already exists. If is does not, the directory is created. Once this directory is created it can be accessed by other odi-tools modules and scripts using the following

>>> odi.bppath

Here is a full list of the directories created

  • bpmasks - directory for bad pixel masks
  • illcor - directory for illumination corrected ota images
  • reproj - directory for reprojected ota images
  • bgsub - directory for background subtracted ota images
  • scaled - directory for scaled ota images
  • otastack - directory for stacked ota images
  • skyflat - directory for sky flats
  • coords - directory for coordinate files
  • match - directory for match files
  • sdssoffline- directory for sdss catalogs
  • twomassoffline - directory for 2mass catalogs
  • gaiaoffline - directory for gaia catalogs
  • sources - directory for detected sources