def _processScienceIm(self, input, masterdir):
"""Takes in science images to be reduced, checks that they are in fact science images,
then calls to the iraf task ccdproc to reduce the science images. Input can be a file location
or a directory.
@param input: file or directory location of science images to be reduced
@type input: str
@param masterdir: directory location of master calibration images
@type masterdir: str
"""
sciencelist = []
reducedlist = None
if os.path.isfile(input):
if os.path.splitext(os.path.split(input)[-1])[-1]=='.fits':
iraf.images.imutil.imgets(image=input, param='imagetyp')
imagetyp = iraf.images.imutil.imgets.value
if imagetyp=='object':
sciencelist.append(input)
sciencelist = reduction_tools.copyNewFits(sciencelist, os.path.split(input)[0]+'/ReducedImages/')
for im in sciencelist:
iraf.noao.imred.ccdred.ccdproc(images=im, fixpix='no', oversca='no', trim='no', zero=masterdir+'Zero', dark=masterdir+'Dark', flat=masterdir+'Flat*')
os.remove(input)
reducedlist = sciencelist
elif os.path.isdir(input):
for im in glob(input+'/*'):
if os.path.splitext(os.path.split(im)[-1])[-1]=='.fits':
iraf.images.imutil.imgets(image=im, param='imagetyp')
imagetyp = iraf.images.imutil.imgets.value
if imagetyp=='object':
sciencelist.append(im)
sciencelist = reduction_tools.copyNewFits(sciencelist, input+'ReducedImages/')
for im in sciencelist:
iraf.noao.imred.ccdred.ccdproc(images=im, fixpix='no', oversca='no', trim='no', zero=masterdir+'Zero',dark=masterdir+'Dark', flat=masterdir+'Flat*')
os.remove(input+os.path.split(im)[-1])
reducedlist = sciencelist
return reducedlist
def _processScienceIm(self, input, masterdir):
"""Takes in science images to be reduced, checks that they are in fact science images,
then calls to the iraf task ccdproc to reduce the science images. Input can be a file location
or a directory.
@param input: file or directory location of science images to be reduced
@type input: str
@param masterdir: directory location of master calibration images
@type masterdir: str
"""
sciencelist = []
reducedlist = None
if os.path.isfile(input):
if os.path.splitext(os.path.split(input)[-1])[-1] == '.fits':
iraf.images.imutil.imgets(image=input, param='imagetyp')
imagetyp = iraf.images.imutil.imgets.value
if imagetyp == 'object':
sciencelist.append(input)
sciencelist = reduction_tools.copyNewFits(
sciencelist,
os.path.split(input)[0] + '/ReducedImages/')
for im in sciencelist:
iraf.noao.imred.ccdred.ccdproc(images=im,
fixpix='no',
oversca='no',
trim='no',
zero=masterdir + 'Zero',
dark=masterdir + 'Dark',
flat=masterdir + 'Flat*')
os.remove(input)
reducedlist = sciencelist
elif os.path.isdir(input):
for im in glob(input + '/*'):
if os.path.splitext(os.path.split(im)[-1])[-1] == '.fits':
iraf.images.imutil.imgets(image=im, param='imagetyp')
imagetyp = iraf.images.imutil.imgets.value
if imagetyp == 'object':
sciencelist.append(im)
sciencelist = reduction_tools.copyNewFits(sciencelist,
input + 'ReducedImages/')
for im in sciencelist:
iraf.noao.imred.ccdred.ccdproc(images=im,
fixpix='no',
oversca='no',
trim='no',
zero=masterdir + 'Zero',
dark=masterdir + 'Dark',
flat=masterdir + 'Flat*')
os.remove(input + os.path.split(im)[-1])
reducedlist = sciencelist
return reducedlist
def reduce(self, input, coordsList=None, subset='filter'):
"""The method in the pipeline that performs the complete reduction. Input
should first be a directory containing at least the calibration images. Science
images to be reduced can also be included. Can also pass just a filename as input, however
single images passed in can only be science images. Nothing will be done if just a single
calibration images is passed.
@param input: directory where calibration and science images are stored or filename of an image to be reduced.
@type input: str
@param coordsList: future work: will give a set of coordinates for photometry
@type coordsList: list
@param subset: subset by which to reduce science images. Default is filter. If this is changed, it must be present in the headers to take effect.
@type subset: str
@return: images that have been reduced. the images are given as the location in the 'ReducedImages/' directory, which is automatically created.
@rtype: list
"""
self.imagedate = os.path.split(os.path.split(input)[0])[-1]
print os.path.split(input)[0]
print self.imagedate
self.reduction_dir = self["calibration_dir"] + self.imagedate + '/'
masterdir = self.reduction_dir + 'Masters/'
if os.path.isfile(input):
imagelist = []
filename = os.path.split(input)[-1]
imagelist.append(input)
reduction_tools.copyNewFits(imagelist, self.reduction_dir)
if not self._haveMasters(self.reduction_dir):
print "No master calibration images found for this date."
return None
else:
subset_file = open(self.reduction_dir + 'instruments', 'w')
print >> subset_file, "subset %s" % subset
subset_file.close()
reduced_images = self._processScienceIm(
self.reduction_dir + filename, masterdir)
return reduced_images
elif os.path.isdir(input):
print input
copylist = glob(input + '*')
reduction_tools.copyNewFits(copylist, self.reduction_dir)
subset_file = open(self.reduction_dir + 'instruments', 'w')
print >> subset_file, "subset %s" % subset
subset_file.close()
if not self._haveMasters(self.reduction_dir):
self._createMasters()
reduced_images = self._processScienceIm(self.reduction_dir,
masterdir)
self.reductionComplete(imageRequest)
return reduced_images
else:
self.err.info("Input is not a valid input type")
return None
def reduce(self, input, coordsList=None, subset='filter'):
"""The method in the pipeline that performs the complete reduction. Input
should first be a directory containing at least the calibration images. Science
images to be reduced can also be included. Can also pass just a filename as input, however
single images passed in can only be science images. Nothing will be done if just a single
calibration images is passed.
@param input: directory where calibration and science images are stored or filename of an image to be reduced.
@type input: str
@param coordsList: future work: will give a set of coordinates for photometry
@type coordsList: list
@param subset: subset by which to reduce science images. Default is filter. If this is changed, it must be present in the headers to take effect.
@type subset: str
@return: images that have been reduced. the images are given as the location in the 'ReducedImages/' directory, which is automatically created.
@rtype: list
"""
self.imagedate = os.path.split(os.path.split(input)[0])[-1]
print os.path.split(input)[0]
print self.imagedate
self.reduction_dir = self["calibration_dir"]+self.imagedate+'/'
masterdir = self.reduction_dir+'Masters/'
if os.path.isfile(input):
imagelist = []
filename = os.path.split(input)[-1]
imagelist.append(input)
reduction_tools.copyNewFits(imagelist, self.reduction_dir)
if not self._haveMasters(self.reduction_dir):
print "No master calibration images found for this date."
return None
else:
subset_file = open(self.reduction_dir+'instruments', 'w')
print >> subset_file, "subset %s" % subset
subset_file.close()
reduced_images = self._processScienceIm(self.reduction_dir+filename, masterdir)
return reduced_images
elif os.path.isdir(input):
print input
copylist = glob(input+'*')
reduction_tools.copyNewFits(copylist, self.reduction_dir)
subset_file = open(self.reduction_dir+'instruments', 'w')
print >> subset_file, "subset %s" % subset
subset_file.close()
if not self._haveMasters(self.reduction_dir):
self._createMasters()
reduced_images = self._processScienceIm(self.reduction_dir, masterdir)
self.reductionComplete(imageRequest)
return reduced_images
else:
self.err.info("Input is not a valid input type")
return None
