noao.imred.crutil¶
The noao.imred.crutil package contains various algorithms for finding and replacing cosmic rays in single images or image sets.
Notes¶
For questions or comments please see our github page. We encourage and appreciate user feedback.
Most of these notebooks rely on basic knowledge of the Astropy FITS I/O module. If you are unfamiliar with this module please see the Astropy FITS I/O user documentation before using this documentation.
crgrow¶
Please review the Notes section above before running any examples in this notebook
The crgrow replacement uses the skimage.morphology package to grow
the values in any numpy array. The dilation task is a wrapper around
scipy.ndimage.grey_dilation. You can insert any kernal type where
disk is called in this example. See the
skimage.morphology.dilation
for more information. More kernel shapes are also listed on this page.
# Standard Imports
from skimage.morphology import disk,dilation
# Astronomy Specific Imports
from astropy.io import fits
from astroquery.mast import Observations
# Download test file using astroquery, this only needs to be run once
# and can be skipped if using your own data.
# Astroquery will only download file if not already present.
obsid = '2004615006'
Observations.download_products(obsid,productFilename="iczgs3ygq_flt.fits")
INFO: Found cached file ./mastDownload/HST/ICZGS3YGQ/iczgs3ygq_flt.fits with expected size 16534080. [astroquery.query]
| Local Path | Status | Message | URL |
|---|---|---|---|
| str47 | str5 | str87 | str93 |
| ./mastDownload/HST/ICZGS3YGQ/iczgs3ygq_flt.fits | ERROR | Downloaded filesize is 16531200,but should be 16534080, file may be partial or corrupt. | https://mast.stsci.edu/api/v0/download/file?uri=mast:HST/product/iczgs3ygq/iczgs3ygq_flt.fits |
# Change this value to your desired data file
test_data = './mastDownload/HST/ICZGS3YGQ/iczgs3ygq_flt.fits'
out_file = 'crgrow.fits'
# Read in your fits file, when using some fits file, the byteswap call is required to
# make sure your array data type is correct when the dilation function is used. This
# may be due to a bug in the dilation funciton.
# For this example we will work with the 3rd extensions, the DQ array
hdu = fits.open(test_data,mode='update')
hdu.info()
dq1 = hdu[3].data.byteswap().newbyteorder('=')
# Dilation used to grow the CR flags, here we use the disk radius 2 shape kernel
grownDQ = dilation(dq1, disk(2))
# Re-assign the changed array to our original fits file and close save the updated FITS to a new file.
hdu[3].data = grownDQ
hdu.writeto(out_file, overwrite=True)
Filename: ./mastDownload/HST/ICZGS3YGQ/iczgs3ygq_flt.fits
No. Name Ver Type Cards Dimensions Format
0 PRIMARY 1 PrimaryHDU 266 ()
1 SCI 1 ImageHDU 140 (1014, 1014) float32
2 ERR 1 ImageHDU 51 (1014, 1014) float32
3 DQ 1 ImageHDU 43 (1014, 1014) int16
4 SAMP 1 ImageHDU 37 (1014, 1014) int16
5 TIME 1 ImageHDU 37 (1014, 1014) float32
6 WCSCORR 1 BinTableHDU 59 7R x 24C [40A, I, A, 24A, 24A, 24A, 24A, D, D, D, D, D, D, D, D, 24A, 24A, D, D, D, D, J, 40A, 128A]
crmedian¶
Please review the Notes section above before running any examples in this notebook
The crmedian task is a way to identify and replace cosmic rays in a
single image by detecting pixels that deviate a statistically
significant amount from the median by comparing to a median filtered
version of the image. The identified cosmic rays can then be replaced by
the median filtered value. A similar algorithm has been used in
ccdproc.cosmicray_median.
In ccdproc.cosmicray_median you also have the option of using an
error array. If none is provided the standard deviation of the data is
used. Ccdproc is an evolving package, please see their
documentation for more
information on usage.
# Astronomy Specific Imports
from astropy.io import fits
from astropy import units
from ccdproc import cosmicray_median, fits_ccddata_reader
from astroquery.mast import Observations
# Download test file using astroquery, this only needs to be run once
# and can be skipped if using your own data.
# Astroquery will only download file if not already present.
obsid = '2004615003'
Observations.download_products(obsid,productFilename="iczgs3y5q_flt.fits")
INFO: Found cached file ./mastDownload/HST/ICZGS3Y5Q/iczgs3y5q_flt.fits with expected size 16534080. [astroquery.query]
| Local Path | Status | Message | URL |
|---|---|---|---|
| str47 | str5 | str87 | str93 |
| ./mastDownload/HST/ICZGS3Y5Q/iczgs3y5q_flt.fits | ERROR | Downloaded filesize is 16531200,but should be 16534080, file may be partial or corrupt. | https://mast.stsci.edu/api/v0/download/file?uri=mast:HST/product/iczgs3y5q/iczgs3y5q_flt.fits |
# Change these values to your desired data files
test_data = './mastDownload/HST/ICZGS3Y5Q/iczgs3y5q_flt.fits'
# First we need to pull out the science and error(uncertainty) array to
# create CCDData objects. Our acutal unit is electrons/sec, this is not
# accepted by the current set of units
image_data = fits_ccddata_reader(test_data, hdu=1, unit=units.electron/units.s, hdu_uncertainty=2)
error_data = image_data.uncertainty.array
# Now we run cosmicray_median, since we input a CCDData type, a CCDData type is returned
# If a numpy.ndarray if the input data type, it will return a numpy.ndarray
newdata = cosmicray_median(image_data, error_image=error_data, thresh=5, mbox=11, rbox=11, gbox=3)
INFO: using the unit electron / s passed to the FITS reader instead of the unit ELECTRONS/S in the FITS file. [astropy.nddata.ccddata]
/Users/ogaz/miniconda3/envs/irafdev/lib/python3.5/site-packages/ccdproc/core.py:1565: RuntimeWarning: divide by zero encountered in true_divide
rarr = (data - marr) / error_image
Not Replacing¶
cosmicrays - Remove cosmic rays using flux ratio algorithm.
craverage - Detect CRs against average and avoid objects.
crcombine - Combine multiple exposures to eliminate cosmic rays.
credit - Interactively edit cosmic rays using an image display.
crfix - Fix cosmic rays in images using cosmic ray masks.
crnebula - Detect and replace cosmic rays in nebular data.