import pyfits

# generovani flatu
bias = pyfits.open('dark_V_0115.fits')
bias_data = bias[0].data
bias.close()

dark = pyfits.open('noise_B_0052.fits')
dark_data = dark[0].data
dark.close()

flat = pyfits.open('flat_V_0007.fits')
flat_data = flat[0].data
flat.close()

xdark_data = (13.0/5.0)*(dark_data - bias_data)
flat_data = flat_data - xdark_data - bias_data
xflat = flat_data.mean()

flat = pyfits.open('flat_V_0007.fits')
flat[0].data = flat_data / xflat
del flat[0].header['BSCALE']
del flat[0].header['BZERO']
flat.writeto('flat.fits',clobber=True)
flat.close()

# fotometricke korekce
bias = pyfits.open('dark_V_0115.fits')
bias_data = bias[0].data
bias.close()

dark = pyfits.open('dark_Clear_0120.fits')
print(dark[0].header['EXPTIME'])
dark_data = dark[0].data
dark.close()

flat = pyfits.open('flat.fits')
flat_data = flat[0].data
flat.close()

obr = pyfits.open('bllac_V_0001.fits')
obr_data = obr[0].data

xdark_data = (300.0/90.0)*(dark_data - bias_data)
obr_data = (obr_data - xdark_data - bias_data) \
             / flat_data

obr[0].data = obr_data
del obr[0].header['BSCALE']
del obr[0].header['BZERO']
obr.writeto('bl.fits',clobber=True)
obr.close()