def global_skysub(self, sciimg, sciivar, tilts, std=False, skymask=None, update_crmask=True, maskslits=None, show_fit=False,
show=False, show_objs=False):
"""
Perform global sky subtraction, slit by slit
Wrapper to skysub.global_skysub
Parameters
----------
tslits_dict: dict
Dictionary containing information on the slits traced for this image
Optional Parameters
-------------------
bspline_spaceing: (float):
Break-point spacing for bspline
use_skymask: (bool, optional):
Mask objects using self.skymask if object finding has been run
(This requires they were found previously, i.e. that find_objects was already run)
Returns:
global_sky: (numpy.ndarray) image of the the global sky model
"""
# Prep
self.global_sky = np.zeros_like(sciimg)
if (std and not self.redux_par['global_sky_std']):
msgs.info('Skipping global sky-subtraction for standard star.')
return self.global_sky
if std:
sigrej = 7.0
update_crmask = False
else:
sigrej = 3.0
self.sciimg = sciimg
self.sciivar = sciivar
self.tilts = tilts
self.maskslits = self.maskslits if maskslits is None else maskslits
gdslits = np.where(np.invert(self.maskslits))[0]
# Mask objects using the skymask? If skymask has been set by objfinding, and masking is requested, then do so
skymask_now = skymask if (skymask is not None) else np.ones_like(self.sciimg, dtype=bool)
# Loop on slits
for slit in gdslits:
msgs.info("Global sky subtraction for slit: {:d}".format(slit))
thismask = (self.slitmask == slit)
inmask = (self.mask == 0) & thismask & skymask_now
# Find sky
self.global_sky[thismask] = skysub.global_skysub(self.sciimg, self.sciivar,
self.tilts, thismask,
self.tslits_dict['slit_left'][:,slit],
self.tslits_dict['slit_righ'][:,slit],
inmask=inmask,
sigrej=sigrej,
bsp=self.redux_par['bspline_spacing'],
no_poly=self.redux_par['no_poly'],
pos_mask = (not self.ir_redux),
show_fit=show_fit)
# Mask if something went wrong
if np.sum(self.global_sky[thismask]) == 0.:
self.maskslits[slit] = True
if update_crmask:
self.crmask = processimages.ProcessImages.build_crmask(self.sciimg - self.global_sky, self.proc_par,
self.det, self.spectrograph, ivar = self.sciivar,
binning=self.binning)
# Rebuild the mask with this new crmask
self.mask = processimages.ProcessImages.update_mask_cr(self.mask, self.crmask)
# Step
self.steps.append(inspect.stack()[0][3])
if show:
sobjs_show = None if show_objs else self.sobjs_obj
# Global skysub is the first step in a new extraction so clear the channels here
self.show('global', slits=True, sobjs =sobjs_show, clear=False)
# Return
return self.global_sky
def global_skysub(self,
skymask=None,
update_crmask=True,
show_fit=False,
show=False,
show_objs=False):
"""
Perform global sky subtraction, slit by slit
Wrapper to skysub.global_skysub
Args:
skymask (np.ndarray):
update_crmask (bool, optional):
show_fit (bool, optional):
show (bool, optional):
show_objs (bool, optional):
Returns:
numpy.ndarray: image of the the global sky model
"""
# Prep
self.global_sky = np.zeros_like(self.sciImg.image)
# Parameters for a standard star
if self.std_redux:
sigrej = 7.0
update_crmask = False
if not self.par['reduce']['skysub']['global_sky_std']:
msgs.info('Skipping global sky-subtraction for standard star.')
return self.global_sky
else:
sigrej = 3.0
gdslits = np.where(np.invert(self.reduce_bpm))[0]
# Mask objects using the skymask? If skymask has been set by objfinding, and masking is requested, then do so
skymask_now = skymask if (skymask is not None) else np.ones_like(
self.sciImg.image, dtype=bool)
# Loop on slits
for slit_idx in gdslits:
slit_spat = self.slits.spat_id[slit_idx]
msgs.info(
"Global sky subtraction for slit: {:d}".format(slit_spat))
thismask = self.slitmask == slit_spat
inmask = (self.sciImg.fullmask == 0) & thismask & skymask_now
# Find sky
self.global_sky[thismask] \
= skysub.global_skysub(self.sciImg.image, self.sciImg.ivar, self.tilts,
thismask, self.slits_left[:,slit_idx],
self.slits_right[:,slit_idx],
inmask=inmask, sigrej=sigrej,
bsp=self.par['reduce']['skysub']['bspline_spacing'],
no_poly=self.par['reduce']['skysub']['no_poly'],
pos_mask=(not self.ir_redux), show_fit=show_fit)
# Mask if something went wrong
if np.sum(self.global_sky[thismask]) == 0.:
self.reduce_bpm[slit_idx] = True
if update_crmask:
# Find CRs with sky subtraction
self.sciImg.build_crmask(self.par['scienceframe']['process'],
subtract_img=self.global_sky)
# Update the fullmask
self.sciImg.update_mask_cr(self.sciImg.crmask)
# Step
self.steps.append(inspect.stack()[0][3])
if show:
sobjs_show = None if show_objs else self.sobjs_obj
# Global skysub is the first step in a new extraction so clear the channels here
self.show('global', slits=True, sobjs=sobjs_show, clear=False)
# Return
return self.global_sky
rcen = tslits_dict['rcen']
ximg = tslits_dict['ximg']
edgmask = tslits_dict['edge_mask']
FWHM = 5.0
bsp = 0.8
residual_img = np.zeros_like(sciframe_A)
specobjs_pos = specobjs.SpecObjs()
specobjs_neg = specobjs.SpecObjs()
skymask = (slitpix > 0)
for islit in range(1, nslits + 1):
thismask = (slitpix == islit)
residual_img[thismask] = skysub.global_skysub(diff_AB,
ivar_AB,
mstilts,
thismask,
lcen[:,islit-1],
rcen[:,islit-1],
inmask=((edgmask == False) & (mask_AB == True)),
bsp=bsp,
pos_mask=False,
show_fit=False)
image = diff_AB - residual_img
# Extract negative trace
specobj_slit_neg, skymask_neg, objmask_neg = extract.objfind(-image,
#ivar_AB,
thismask,
lcen[:,islit-1],
rcen[:,islit-1],
sig_thresh=3.0,
inmask=mask_AB,
FWHM=FWHM,
nperslit=1,
