if objects[i] in dz.observation_dict['Standard_stars']:
sigclip = 10.0
else:
if colors_arm[i] == 'Blue arm':
sigclip = 10.0
elif colors_arm[i] == 'Red arm':
sigclip = 10.0
print '\n-Treating:', Files_Name[i],' ', i, '/', len(Files_Name), objects[i] + '_lacosmic', sigclip, '\n'
gain = pyfits.getval(Files_Folder[i] + Files_Name[i], 'GAIN' ,0)
readnoise = pyfits.getval(Files_Folder[i] + Files_Name[i], 'READNOIS' ,0)
lacosmic_param = [gain, readnoise, sigclip]
#Frame cosmic object
c = cosmics.cosmicsimage(fitsdata, gain=lacosmic_param[0], readnoise=lacosmic_param[1], sigclip = lacosmic_param[2])
#Run the fitting
c.run(maxiter = 4)
#Write the cleaned image into a new FITS file, conserving the original header :
output_clean = Files_Folder[i] + Files_Name[i][0:Files_Name[i].rfind('.')] + '_cr.fits'
output_mask = Files_Folder[i] + Files_Name[i][0:Files_Name[i].rfind('.')] + '_mask.fits'
#Delete the file if it already exists
if os.path.isfile(output_clean):
os.remove(output_clean)
if os.path.isfile(output_mask):
os.remove(output_mask)
#Store the frames
