def parseHeader(self, header):
'''parse a FITS header, and if the image is an
object frame add the information to the summary
return true if an object, false otherwise'''
if fitsHeader.getFrameType(header) == 'object':
targetName = fitsHeader.getObjectName(header)
filterName = fitsHeader.getFilter(header)
self.addObservation(targetName, filterName)
return True
else:
return False
def parseHeader(self, header):
'''parse a FITS header, and if the image is an
object frame add the information to the summary
return true if an object, false otherwise'''
if fitsHeader.getFrameType(header) == 'object':
targetName = fitsHeader.getObjectName(header)
filterName = fitsHeader.getFilter(header)
self.addObservation(targetName, filterName)
return True
else:
return False
def getFrameLists(fileList):
'''given an iterator of filenames, go through each one,
get the the type of the frame and add it to the appropriate list
return a dictionary containing lists of files for 'zero', 'dark',
'object', and 'none'. The 'none' category will contain fits files
that we can't determine the type for and files that we are unable to
open'''
results = {'zero': [], 'dark': [], 'flat': [], 'object': [], 'unknown': []}
for f in iter(fileList):
try:
imType = getFrameType(pyfits.getheader(f))
except:
imType = 'unknown'
if imType is None:
imType = 'unknown'
results[imType].append(f)
return results
def getFrameLists(fileList):
'''given an iterator of filenames, go through each one,
get the the type of the frame and add it to the appropriate list
return a dictionary containing lists of files for 'zero', 'dark',
'object', and 'none'. The 'none' category will contain fits files
that we can't determine the type for and files that we are unable to
open'''
results = {'zero':[],'dark':[],'flat':[],'object':[],'unknown':[]}
for f in iter(fileList):
try:
imType = getFrameType(pyfits.getheader(f))
except:
imType = 'unknown'
if imType is None:
imType = 'unknown'
results[imType].append(f)
return results
