LINT

Longitudinal Investigation of Non-Transparency (LINT): using flats from CCDs to find the amount of dust, debris, or other contamination present on a sensor's surface. This program uses flats from CCDs to find the amount of dust, debris, or other contamination present on a sensor's surface.

The code will:

• Load flats (fits).
• Subtract overscan and mask overscan regions (if overscanSubtractBOOL is "True").
• Scale the flats to a common mean.
• Stack the flats using a median.
• Subtract the average sky value.
• Multiply the values by -1 to make to make attenuation spots appear positive to photometry code.
• Run Source Extractor on the image to detect the debris.
• Print a detailed map of the debris locations.
• Analyze and plot histograms showing the amount of contamination.
• Batch process data to show the accumulation of debris over time.

Programs, packages, and wrappers:

• Interpreter: python 3
• PyDev: 4.5.5.201603221110
• Numpy: 1.11.0
• Astropy: 1.3
• Python-dev: python-dev 2.7.5-5ubuntu3
• Eclipse: eclipse-platform 3.8.1-5.1
• SExtractor: 2.19.5-2
• Matplotlib: 1.5.1-1ubuntu1

Modules:

testAstro:

• Test for issues with your astropy installation.

loadFits:

• Load fits files image data into a 3D array.
• Saves data to a fits file.
• Makes a directory for output products and move output products into it.
• Scans the images to insure that they are all the same size dimensionally.

loadConfig:

• Load LINT.config.

overscan:

• Subtract and remove overscan (if overscanSubtractBOOL bool is true).

scaleAndStack:

• Scales the images using a common mean (find the mean of all of the data and scale the data so that every image has that same baseline mean).
• Stack the images, using a median, into a single flat field image (median the images: meaning that the resulting value in a pixel in the final image is the median of the values in that same pixel in the input images).

skyValue:

• Subtracts the average sky value from the median stacked image.

callSExtractor:

• Call SExtractor and send commands to process the stacked and inverted image.
• Record the output from SExtractor.

analyzeSExOutput:

• Performs cuts to remove objects that are not debris.
  • Flags: no gremlins in photometry.
  • Flux: only want divots in original image.
  • SNR: signal to noise ratio. Calculate the signal-to-noise ratio as FLUX_ISO / FLUXERR_ISO, that is, the isophotal flux (photometry derived from the counts above the threshold minus the background) divided by the RMS error for the isophotal flux; in other words, the signal divided by the noise.
  • FWHM: Full Width at Half Maximum. Very small values may be anomalous and not represent debris.
• Make histograms of:
  • Area of debris.
  • Debris versus clean area.

batch:

• Create a list that groups the fits files by date.
• Run LINT on pre-grouped (by date) fits files.
• Plot the debris accumulation over time as: scatter plot.

To do:

• Add logger.
• Add help command in optional arguments.
• Check to see if dependencies are installed.
• Mask bad pixel columns.
• Test installation code.

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This research makes use of:

• Astropy, a community-developed core Python package for Astronomy (Astropy Collaboration, 2013).
• Bertin, E. & Arnouts, S. 1996: SExtractor: Software for source extraction, Astronomy & Astrophysics Supplement 317, 393
• PyDev for Eclipse 4.5.5.201603221110 org.python.pydev.feature.feature.group Fabio Zadrozny
• Hunter, J. D. Matplotlib: A 2D graphics environment. 2007