darkframes.py 5.35 KB
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"""
Last modified: 2017-03-07

Reduction of the flat-fields:
- check the exposure time
- check the mean flux in the four quadrants
- create the masterdark
"""

from astropy import units as u
from astropy.io import fits
import warnings
from astropy.utils.exceptions import AstropyWarning

from ccdproc import CCDData, Combiner
from drslib.config import CONFIG
from drslib import db
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from drslib import metadata
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import numpy as np
import os, shutil


class GBDarks():
    def __init__(self, darks, dbconn):
        self.darks = darks
        self.dbconn = dbconn
        self.quality = []
        self.messages = []
        self.darklists = CONFIG['DARKLIST']
        self.masterdarks = {}


    def qualitycheck(self):
        for frame in self.darks:
            dark = CCDData.read(frame, unit=u.adu)
            exptime = int(dark.header[CONFIG['KEYS']['EXPTIME']])
            if exptime not in self.darklists.keys():
                self.messages.append('Dark frame %s has exposure time %s sec: skipped.' % (str(os.path.basename(frame)),str(dark.header[CONFIG['KEYS']['EXPTIME']]),))
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                self.quality.append('FAILED')
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                continue

# check the four dark quadrants, compute mean and std
            x = CONFIG['XCCD']
            y = CONFIG['YCCD']

            mean = []
            std = []

            quadrant1 = dark.data[0:x/2,0:y/2]
            mean.append(np.mean(quadrant1))
            #std.append(np.std(quadrant1))

            quadrant2 = dark.data[x/2+1:x,0:y/2]
            mean.append(np.mean(quadrant2))
            #std.append(np.std(quadrant2))

            quadrant3 = dark.data[0:x/2,y/2+1:y]
            mean.append(np.mean(quadrant3))
            #std.append(np.std(quadrant3))

            quadrant4 = dark.data[x/2+1:x,y/2+1:y]
            mean.append(np.mean(quadrant4))
            #std.append(np.std(quadrant4))

            if exptime in CONFIG['DARK_MEAN']:
                qcheck = np.asarray(CONFIG['DARK_MEAN'][exptime]) 
            else:
                qcheck = np.asarray(CONFIG['DARK_MEAN'][min(CONFIG['DARK_MEAN'].keys(), key=lambda k: abs(k-exptime))])

            if (np.asarray(mean) > qcheck).any():
                self.messages.append('Dark frame %s failed quality check' % (str(os.path.basename(frame))),)
                dark = None
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                self.quality.append('FAILED')
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            else:
                self.darklists[exptime].append(dark)
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                self.quality.append('OK')
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            #print frame
            #print 'Quadrant 1: mean ' + str(mean[0])
            #print 'Quadrant 2: mean ' + str(mean[1])
            #print 'Quadrant 3: mean ' + str(mean[2])
            #print 'Quadrant 4: mean ' + str(mean[3])
            #print 'Global: mean ' + str(np.mean(dark.data)) + ' - std ' + str(np.std(dark.data))
        return


    def masterdark(self):
        for exptime in self.darklists:
            calname = 'dark' + str(int(exptime))
            if self.darklists[exptime]:
                hea = self.darklists[exptime][0].header
                darkname = hea[CONFIG['KEYS']['IMANAME']].replace('.fts','_DARK.fits')

                nome = os.path.join(CONFIG['CALIB_DIR'],darkname)
                red_name = os.path.join(CONFIG['RED_CALIB'],darkname)

                combinedark = Combiner(self.darklists[exptime])
                combinedark.sigma_clipping(func=np.ma.mean)

                self.masterdarks[exptime] = combinedark.average_combine()
                self.masterdarks[exptime].data = np.asarray(self.masterdarks[exptime].data, dtype='float32')
                self.masterdarks[exptime].header = hea
                self.masterdarks[exptime].header[CONFIG['KEYS']['FILENAME']] = darkname
                self.masterdarks[exptime].header[CONFIG['KEYS']['NCOMBINE']] = len(self.darklists[exptime])

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                self.masterdarks[exptime].header[CONFIG['DRS_VERSION'][0]] = (CONFIG['VERSION'], CONFIG['DRS_VERSION'][1])

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                # Add metadata to header
                self.masterdarks[exptime].header = metadata.add_metadata(self.masterdarks[exptime].header)


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                hdu = fits.PrimaryHDU(data=self.masterdarks[exptime].data,header=self.masterdarks[exptime].header)
                mdark = fits.HDUList([hdu])

                darkmean = '%.3f' % np.mean(self.masterdarks[exptime].data)

                mdark.writeto(nome,clobber=True)

                shutil.copyfile(nome,red_name)

                self.darklists[exptime][:] = [] # empty the lists
                self.masterdarks[exptime] = None

                self.messages.append('Created masterdark with exposure time = %s seconds.' % (str(exptime)))
                self.messages.append('Mean value of dark current: %s ' % (str(darkmean),))

                db.insert_dbfile(self.dbconn,calname,nome)

            else:
                self.messages.append('Not enough dark frame to create %s sec masterdark. The masterdark will be taken from the calibration database.' % (exptime),)
                if db.check_dbfile(self.dbconn,calname):
                    try:
                        db.copy_dbfile(self.dbconn,calname)
                    except:
                        self.messages.append('There are no masterdarks of %s sec in the database. If needed, observe them now.' % (exptime),)
        return

    def process(self):
        warnings.simplefilter('ignore', category=AstropyWarning)
        self.qualitycheck()
        self.masterdark()
        return