4.19. cosmic_clean

Clears cosmic rays from the fits file

Fits.cosmic_clean(output=None, override=False, sigclip=4.5, sigfrac=0.3, objlim=5, gain=1.0, readnoise=6.5, satlevel=65535.0, niter=4, sepmed=True, cleantype='meanmask', fsmode='median', psfmodel='gauss', psffwhm=2.5, psfsize=7, psfk=None, psfbeta=4.765, gain_apply=True) → Self

Clears cosmic rays from the fits file.

[1]: https://ccdproc.readthedocs.io/en/latest/api/ccdproc.cosmicray_lacosmic.html

Parameters

outputstr, optional

Path of the new FITS file.

overridebool, default=False

If True, will overwrite the output path if a file already exists.

sigclipfloat, default=4.5

Laplacian-to-noise limit for cosmic ray detection. Lower values will flag more pixels as cosmic rays.

sigfracfloat, default=0.3

Fractional detection limit for neighboring pixels. For cosmic ray neighbor pixels, a Laplacian-to-noise detection limit of sigfrac * sigclip will be used.

objlimint, default=5

Minimum contrast between Laplacian image and the fine structure image. Increase this value if cores of bright stars are flagged as cosmic rays.

gainfloat, default=1.0

Gain of the image (electrons / ADU). We always need to work in electrons for cosmic ray detection.

readnoisefloat, default=6.5

Read noise of the image (electrons). Used to generate the noise model of the image.

satlevelfloat, default=65535.0

Saturation level of the image (electrons). Pixels at or above this level are added to the mask.

niterint, default=4

Number of iterations of the LA Cosmic algorithm to perform.

sepmedbool, default=True

Use the separable median filter instead of the full median filter. The separable median is significantly faster and still detects cosmic rays well.

cleantypestr, default=’meanmask’

Set which clean algorithm is used: - “median”: An unmasked 5x5 median filter. - “medmask”: A masked 5x5 median filter. - “meanmask”: A masked 5x5 mean filter. - “idw”: A masked 5x5 inverse distance weighted interpolation.

fsmodestr, default=’median’

Method to build the fine structure image: - “median”: Use the median filter in the standard LA Cosmic algorithm. - “convolve”: Convolve the image with the PSF kernel to calculate the fine structure image.

psfmodelstr, default=’gauss’

Model to use to generate the PSF kernel if fsmode == ‘convolve’ and psfk is None.

psffwhmfloat, default=2.5

Full Width Half Maximum of the PSF to use to generate the kernel.

psfsizeint, default=7

Size of the kernel to calculate. Returned kernel will have size psfsize x psfsize.

psfkAny, optional

PSF kernel array to use for the fine structure image if fsmode == ‘convolve’.

psfbetafloat, default=4.765

Moffat beta parameter. Only used if fsmode`==’convolve’ and `psfmodel==’moffat’.

gain_applybool, default=True

If True, return gain-corrected data with correct units; otherwise, do not gain-correct the data.

Returns

Fits

Cleaned FITS file.

4.19.1. Example:

from myraflib import Fits

fits = Fits.sample()
cleaned_fits = fits.cosmic_clean()