def test_lacosmic():
spec = load_spectrograph('keck_deimos')
file = os.path.join(os.environ['PYPEIT_DEV'], 'RAW_DATA', 'keck_deimos',
'1200G_M_5500', 'd0315_45929.fits')
par = ProcessImagesPar(use_biasimage=False,
use_pixelflat=False,
use_illumflat=False)
img = RawImage(file, spec, 1)
pimg = img.process(par)
test_img = pimg.image[:500, :500]
test_var = utils.inverse(pimg.ivar[:500, :500])
crmask = procimg.lacosmic(test_img, varframe=test_var, maxiter=1)
assert np.sum(crmask) == 1240, 'L.A.Cosmic changed'
_crmask = procimg.lacosmic(test_img, varframe=test_var, maxiter=2)
assert np.sum(_crmask) > np.sum(
crmask), '2nd iteration should find more cosmics'
_crmask = procimg.lacosmic(test_img,
saturation=6000.,
varframe=test_var,
maxiter=1)
assert np.sum(_crmask) < np.sum(
crmask), 'Should have flagged some pixels as saturated'
__crmask = procimg.lacosmic(test_img,
saturation=np.full(test_img.shape, 6000.),
varframe=test_var,
maxiter=1)
assert np.array_equal(__crmask, _crmask), 'Saturation array failed.'
def build_crmask(stack, proc_par, det, spectrograph, ivar=None, binning=None):
"""
Generate the CR mask frame
Wrapper to procimg.lacosmic
Parameters
----------
varframe : ndarray, optional
Returns
-------
self.crmask : ndarray
1. = Masked CR
"""
# Run LA Cosmic to get the cosmic ray mask
varframe = utils.calc_ivar(ivar)
saturation = spectrograph.detector[det-1]['saturation']
nonlinear = spectrograph.detector[det-1]['nonlinear']
#sigclip, objlim = spectrograph.get_lacosmics_par(proc_par,binning=binning)
crmask = procimg.lacosmic(det, stack, saturation, nonlinear,
varframe=varframe, maxiter=proc_par['lamaxiter'],
grow=proc_par['grow'],
remove_compact_obj=proc_par['rmcompact'],
sigclip=proc_par['sigclip'],
sigfrac=proc_par['sigfrac'],
objlim=proc_par['objlim'])
# Return
return crmask
def build_crmask(self, par, subtract_img=None):
"""
Generate the CR mask frame
Mainly a wrapper to :func:`pypeit.core.procimg.lacosmic`
Args:
par (:class:`pypeit.par.pypeitpar.ProcessImagesPar`):
Parameters that dictate the processing of the images. See
:class:`pypeit.par.pypeitpar.ProcessImagesPar` for the
defaults.
subtract_img (`numpy.ndarray`_, optional):
If provided, subtract this from the image prior to CR detection
Returns:
`numpy.ndarray`_: Copy of self.crmask (boolean)
"""
var = utils.inverse(self.ivar)
use_img = self.image if subtract_img is None else self.image - subtract_img
# Run LA Cosmic to get the cosmic ray mask
self.crmask = procimg.lacosmic(use_img,
self.detector['saturation'],
self.detector['nonlinear'],
varframe=var,
maxiter=par['lamaxiter'],
grow=par['grow'],
remove_compact_obj=par['rmcompact'],
sigclip=par['sigclip'],
sigfrac=par['sigfrac'],
objlim=par['objlim'])
# Return
return self.crmask.copy()
def build_crmask(self,
spectrograph,
det,
par,
image,
rawvarframe,
subtract_img=None):
"""
Generate the CR mask frame
Mainly a wrapper to procimg.lacosmic
Args:
spectrograph (:class:`pypeit.spectrographs.spectrograph.Spectrograph`):
Spectrograph used to take the data.
det (:obj:`int`, optional):
The 1-indexed detector number to process.
par (:class:`pypeit.par.pypeitpar.ProcessImagesPar`):
Parameters that dictate the processing of the images. See
:class:`pypeit.par.pypeitpar.ProcessImagesPar` for the
defaults.
image (np.ndarray):
Image to identify CR's in
rawvarframe (np.ndarray):
Variance image
subtract_img (np.ndarray, optional):
If provided, subtract this from the image prior to CR detection
Returns:
np.ndarray: Copy of self.crmask (boolean)
"""
use_img = image if subtract_img is None else image - subtract_img
# Run LA Cosmic to get the cosmic ray mask
self.crmask = procimg.lacosmic(
det,
use_img,
spectrograph.detector[det - 1]['saturation'],
spectrograph.detector[det - 1]['nonlinear'],
varframe=rawvarframe,
maxiter=par['lamaxiter'],
grow=par['grow'],
remove_compact_obj=par['rmcompact'],
sigclip=par['sigclip'],
sigfrac=par['sigfrac'],
objlim=par['objlim'])
# Return
return self.crmask.copy()