def subtract_images_subroutine(name, dark):
imA = pyfits.getdata(name)
imAh = pyfits.getheader(name)
imAh['SUBBED'] = 1
imB = np.subtract(imA, dark)
sub_name = name.split(".")[0]
new_name = "{0}_subDARK.fits".format(sub_name)
pyfits.writeto(new_name, imB, imAh, overwrite=True)
print "{0}, OK".format(new_name)
#---------------------------------------
# Write to database
cwd = os.getcwd()
mysqlio_lib.save2sql_images(new_name, cwd)
return new_name
def divide_images(image_list, flat_name):
flat = pyfits.getdata(flat_name)
new_image_list = []
for name in image_list:
imA = pyfits.getdata(name)
imAh = pyfits.getheader(name)
imAh['FLATDIVED'] = 1
imB = np.divide(imA, flat)
sub_name = name.split(".")[0]
new_name = "{0}_divFLAT.fits".format(sub_name)
new_image_list.append(new_name)
pyfits.writeto(new_name, imB, imAh, overwrite=True)
print "{0}, OK ".format(new_name)
#---------------------------------------
# Write to database
cwd = os.getcwd()
mysqlio_lib.save2sql_images(new_name, cwd)
return new_image_list
def subtract_images(image_list, dark_name):
dark = pyfits.getdata(dark_name)
new_image_list = []
print(len(image_list))
for name in image_list:
try:
imA = pyfits.getdata(name)
imAh = pyfits.getheader(name)
imAh['SUBBED'] = 1
imB = np.subtract(imA, dark)
sub_name = name.split(".")[0]
new_name = "{0}_subDARK.fits".format(sub_name)
new_image_list.append(new_name)
pyfits.writeto(new_name, imB, imAh, overwrite=True)
print "{0}, OK".format(new_name)
#---------------------------------------
# Write to database
cwd = os.getcwd()
mysqlio_lib.save2sql_images(new_name, cwd)
except:
print "{0} cannot be subtracted by dark".format(name)
pass
return new_image_list
#----------------------------------------
# Load arguments
if len(argv) != 2:
print 'The number of arguments is wrong.'
print 'Usage: mask_image.py [a list of image name]'
exit()
list_name = argv[1]
image_name_list = np.loadtxt(list_name, dtype=str)
#---------------------------------------
for image_name in image_name_list:
# Load data
data = pyfits.getdata(image_name)
header = pyfits.getheader(image_name)
# Mask
data[:200] = np.nan
# Save data
new_name = '{0}_mask.fits'.format(image_name[:-5])
pyfits.writeto(new_name, data, header, overwrite=True)
print "{0}, done".format(new_name)
#---------------------------------------
# Write to database
cwd = os.getcwd()
mysqlio_lib.save2sql_images(new_name, cwd)
# Save the result as a list
temp = "ls *_mask.fits > masked_image_list.txt"
os.system(temp)
#---------------------------------------
# Measure time
elapsed_time = time.time() - start_time
print "Exiting Main Program, spending ", elapsed_time, "seconds."