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pandora-fits

Tools to work with fits files from Pandora.

pandora-fits wraps astropy.io.fits.HDUList classes to ensure that files conform to Pandora FITS standards.

The standards are defined using excel files in the src/pandorasat/formats/ folder. Changing these files will change the standards that this tool checks against.

Pandora Detectors

Pandora has two detectors, VISDA and NIRDA. You can read more about each of these in pandora-sat.

Pandora File Levels

Pandora will have the following levels of files for each detector

Level Description
0 Raw data from spacecraft
1 Reorganized raw data, with potential for additional keywords
2 Calibrated image data products
3 Spectral time-series data, ready for science.

Exceptions

pandora-fits will throw exceptions if files are not in the correct format. This includes

  • Files do not have the right number of extensions
  • Extensions are not the correct type
  • Header keywords have the wrong values when compared with the template

Warnings

pandora-fits will log warnings if files are missing keyword headers, but those headers aren't valued in the excel spreadsheet.

Usage

You should treat the pandora-fits objects as though they were astropy.io.fits.HDUList objects. There is one per detector, per file level.

First you can import the correct HDUList object. Note that I am using the logger and setting the logger to the level "ERROR".

from pandorafits.nirda import NIRDALevel0HDUList
from pandorafits import logger
logger.setLevel("ERROR")

We can create a dummy file by passing nothing to the object

hdulist = NIRDALevel0HDUList()
hdulist.info()
Filename: (No file associated with this HDUList)
No.    Name      Ver    Type      Cards   Dimensions   Format
  0  PRIMARY       1 PrimaryHDU      35   ()      
  1  SCIENCE       1 ImageHDU        12   (80, 400, 10)   int16   

This initializes an "empty" file that is compliant with the Pandora scheme. There are several logger "warning" messages that will state that many of the header keywords are not set.

We can write to a file

hdulist.writeto("test.fits", overwrite=True)

We can also read in a file

hdulist = NIRDALevel0HDUList("test.fits")

Finally we can read in an existing HDUList, e.g.

hdulist = fits.HDUList("test.fits")
NIRDALevel0HDUList(hdulist)

Installation

You can install with a git clone, or via PyPI using the command below. Make sure to update to the most recent version.

pip install pandorafits --upgrade

If you need to run the pipeline and use the databasing features you will need to add the optional extras.

pip install "pandorafits[database]" --upgrade

Note if you're working on a windows machine this install might be harder and you should open an issue if you encounter any problems.

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