def standardizeInstrumentHeaders(self, rc):
"""
This primitive is used to make the changes and additions to the
keywords in the headers of NIRI data, specifically.
"""
# Instantiate the log
log = logutils.get_logger(__name__)
# Log the standard "starting primitive" debug message
log.debug(gt.log_message("primitive", "standardizeInstrumentHeaders",
"starting"))
# Define the keyword to be used for the time stamp for this primitive
timestamp_key = self.timestamp_keys["standardizeInstrumentHeaders"]
# Initialize the list of output AstroData objects
adoutput_list = []
# Loop over each input AstroData object in the input list
for ad in rc.get_inputs_as_astrodata():
# Check whether the standardizeInstrumentHeaders primitive has been
# run previously
if ad.phu_get_key_value(timestamp_key):
log.warning("No changes will be made to %s, since it has "
"already been processed by "
"standardizeInstrumentHeaders" % ad.filename)
# Append the input AstroData object to the list of output
# AstroData objects without further processing
adoutput_list.append(ad)
continue
# Standardize the headers of the input AstroData object. Update the
# keywords in the headers that are specific to NIRI
log.status("Updating keywords that are specific to NIRI")
# Filter name (required for IRAF?)
gt.update_key_from_descriptor(
adinput=ad, descriptor="filter_name(stripID=True, pretty=True)",
keyword="FILTER", extname="PHU")
# Pixel scale
gt.update_key_from_descriptor(
adinput=ad, descriptor="pixel_scale()", extname="PHU")
# Read noise (new keyword, should it be written?)
gt.update_key_from_descriptor(
adinput=ad, descriptor="read_noise()", extname="SCI")
# Gain (new keyword, should it be written?)
gt.update_key_from_descriptor(
adinput=ad, descriptor="gain()", extname="SCI")
# Non linear level
gt.update_key_from_descriptor(
adinput=ad, descriptor="non_linear_level()", extname="SCI")
# Saturation level
gt.update_key_from_descriptor(
adinput=ad, descriptor="saturation_level()", extname="SCI")
# Dispersion axis (new keyword, should it be written?)
if "SPECT" in ad.types:
gt.update_key_from_descriptor(
adinput=ad, descriptor="dispersion_axis()", extname="SCI")
# Convention seems to be to multiply the exposure time by coadds in prepared data
gt.update_key_from_descriptor(
adinput=ad, descriptor="exposure_time()", extname="PHU")
# Add the appropriate time stamps to the PHU
gt.mark_history(adinput=ad, keyword=timestamp_key)
# Change the filename
ad.filename = gt.filename_updater(adinput=ad, suffix=rc["suffix"],
strip=True)
# Append the output AstroData object to the list of output
# AstroData objects
adoutput_list.append(ad)
# Report the list of output AstroData objects to the reduction context
rc.report_output(adoutput_list)
yield rc
