def get_master_calibration_image(image, calibration_type, group_by_keywords,
db_address=_DEFAULT_DB):
calibration_criteria = CalibrationImage.type == calibration_type.upper()
calibration_criteria &= CalibrationImage.telescope_id == image.telescope_id
for criterion in group_by_keywords:
if criterion == 'filter':
calibration_criteria &= CalibrationImage.filter_name == getattr(image, criterion)
else:
calibration_criteria &= getattr(CalibrationImage, criterion) == getattr(image, criterion)
# Only grab the last year. In principle we could go farther back, but this limits the number
# of files we get back. And if we are using calibrations that are more than a year old
# it is probably a bad idea anyway.
epoch_datetime = date_utils.epoch_string_to_date(image.epoch)
calibration_criteria &= CalibrationImage.dayobs < (epoch_datetime + datetime.timedelta(days=365))
calibration_criteria &= CalibrationImage.dayobs > (epoch_datetime - datetime.timedelta(days=365))
db_session = get_session(db_address=db_address)
calibration_images = db_session.query(CalibrationImage).filter(calibration_criteria).all()
# Find the closest date
if len(calibration_images) == 0:
calibration_file = None
else:
date_deltas = np.abs(np.array([i.dayobs - epoch_datetime for i in calibration_images]))
closest_calibration_image = calibration_images[np.argmin(date_deltas)]
calibration_file = os.path.join(closest_calibration_image.filepath,
closest_calibration_image.filename)
db_session.close()
return calibration_file
def save_calibration_info(cal_type, output_file, image_config, db_address=_DEFAULT_DB):
# Store the information into the calibration table
# Check and see if the bias file is already in the database
db_session = get_session(db_address=db_address)
image_query = db_session.query(CalibrationImage)
output_filename = os.path.basename(output_file)
image_query = image_query.filter(CalibrationImage.filename == output_filename)
image_query = image_query.all()
if len(image_query) == 0:
# Create a new row
calibration_image = CalibrationImage()
else:
# Otherwise update the existing data
# In principle we could just skip this, but this should be fast
calibration_image = image_query[0]
calibration_image.dayobs = date_utils.epoch_string_to_date(image_config.epoch)
calibration_image.ccdsum = image_config.ccdsum
calibration_image.filter_name = image_config.filter
calibration_image.telescope_id = image_config.telescope_id
calibration_image.type = cal_type.upper()
calibration_image.filename = output_filename
calibration_image.filepath = os.path.dirname(output_file)
db_session.add(calibration_image)
db_session.commit()
db_session.close()
def get_calibration_filename(self, image):
calibration_criteria = dbs.CalibrationImage.type == self.calibration_type.upper()
calibration_criteria &= dbs.CalibrationImage.telescope_id == image.telescope_id
for criterion in self.group_by_keywords:
if criterion == 'filter':
calibration_criteria &= dbs.CalibrationImage.filter_name == getattr(image, criterion)
else:
calibration_criteria &= getattr(dbs.CalibrationImage, criterion) == getattr(image, criterion)
db_session = dbs.get_session(db_address=self.pipeline_context.db_address)
calibration_query = db_session.query(dbs.CalibrationImage).filter(calibration_criteria)
epoch_datetime = date_utils.epoch_string_to_date(image.epoch)
find_closest = func.DATEDIFF(epoch_datetime, dbs.CalibrationImage.dayobs)
find_closest = func.ABS(find_closest)
calibration_query = calibration_query.order_by(find_closest.asc())
calibration_image = calibration_query.first()
if calibration_image is None:
calibration_file = None
else:
calibration_file = os.path.join(calibration_image.filepath, calibration_image.filename)
db_session.close()
return calibration_file
def save_calibration_info(cal_type, output_file, image_config, db_address=_DEFAULT_DB):
# Store the information into the calibration table
# Check and see if the bias file is already in the database
db_session = get_session(db_address=db_address)
output_filename = os.path.basename(output_file)
add_or_update_record(db_session, CalibrationImage, {'filename': output_filename},
{'dayobs': date_utils.epoch_string_to_date(image_config.epoch),
'ccdsum': image_config.ccdsum, 'filter_name': image_config.filter,
'telescope_id': image_config.telescope_id, 'type': cal_type.upper(),
'filename': output_filename, 'filepath': os.path.dirname(output_file)})
db_session.commit()
db_session.close()
def populate_bpm_table(directory, db_address=_DEFAULT_DB):
db_session = get_session(db_address=db_address)
bpm_filenames = glob(os.path.join(directory, 'bpm*.fits*'))
for bpm_filename in bpm_filenames:
if bpm_filename[-3:] == '.fz':
extension_number = 1
else:
extension_number = 0
site = fits.getval(bpm_filename, 'SITEID', extension_number).lower()
instrument = fits.getval(bpm_filename, 'INSTRUME', extension_number).lower()
ccdsum = fits.getval(bpm_filename, 'CCDSUM', extension_number)
creation_date = date_utils.epoch_string_to_date(fits.getval(bpm_filename, 'DAY-OBS',
extension_number))
telescope_id = get_telescope_id(site=site, instrument=instrument, db_address=db_address)
bpm_attributes = {'telescope_id': telescope_id, 'filepath': os.path.abspath(directory),
'filename': os.path.basename(bpm_filename), 'ccdsum': ccdsum,
'creation_date': creation_date}
add_or_update_record(db_session, BadPixelMask, bpm_attributes, bpm_attributes)
db_session.commit()
db_session.close()