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small tweaks
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@bhilbert4
bhilbert4 committed Sep 21, 2023
1 parent 85acbcf commit 1e8f27c
Showing 1 changed file with 65 additions and 11 deletions.
76 changes: 65 additions & 11 deletions jwql/instrument_monitors/common_monitors/ta_monitor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -267,6 +267,7 @@ def calc_target_xy(self):
self.attitude = define_attitude(self.V2_ref, self.V3_ref, self.RA_ref, self.DEC_ref, self.roll_ref)
self.v2_targ, self.v3_targ = rotations.getv2v3(self.attitude, self.RA_targ, self.DEC_targ)
self.x_targ, self.y_targ = self.ap_siaf.tel_to_sci(self.v2_targ, self.v3_targ)
self.idl_x_targ, self.idl_y_targ = self.ap.tel_to_idl(self.v2_targ, self.v3_targ)

def manual_centroid(self, use_ref_loc=True, use_targ_loc=False, half_width=None):
"""Calculate the centroid of the source in the data. This will be compared to the
Expand Down Expand Up @@ -800,20 +801,24 @@ def flip_coords_to_DMS(self):

if self.instrument == 'nircam':
self.dms_aperture_centroid = self.ap_siaf.det_to_sci(self.event.ta_info['detector_centroid'][0], self.event.ta_info['detector_centroid'][1])
self.dms_aperture_centroid_v2v3 = self.ap_siaf.det_to_tel(self.event.ta_info['detector_centroid'][0], self.event.ta_info['detector_centroid'][1])
self.full_siaf = self.inst_siaf[f'{self.aperture.split("_")[0]}_FULL'] #-- but what about coronagraphic ta?
self.dms_det_centroid = self.full_siaf.det_to_sci(self.event.ta_info['detector_centroid'][0], self.event.ta_info['detector_centroid'][1])
elif self.instrument == 'niriss':
self.dms_aperture_centroid = self.ap_siaf.det_to_sci(self.event.ta_info['detector_centroid'][1], self.event.ta_info['detector_centroid'][0])
self.dms_aperture_centroid_v2v3 = self.ap_siaf.det_to_tel(self.event.ta_info['detector_centroid'][0], self.event.ta_info['detector_centroid'][1])
self.full_siaf = self.inst_siaf['NIS_CEN']
self.dms_det_centroid = self.full_siaf.raw_to_sci(self.event.ta_info['detector_centroid'][0], self.event.ta_info['detector_centroid'][1])
elif self.instrument == 'miri':
self.full_siaf = Siaf('miri')['MIRIM_FULL'] #-- but what about e.g. coronagraphic ta?
if self.subarray != 'FULL':
sub_siaf = self.inst_siaf['MIRIM_' + self.subarray]
self.dms_aperture_centroid = sub_siaf.det_to_sci(self.event.ta_info['detector_centroid'][0], self.event.ta_info['detector_centroid'][1])
self.dms_aperture_centroid_v2v3 = sub_siaf.det_to_tel(self.event.ta_info['detector_centroid'][0], self.event.ta_info['detector_centroid'][1])
self.dms_det_centroid = self.full_siaf.det_to_sci(self.event.ta_info['detector_centroid'][0], self.event.ta_info['detector_centroid'][1])
else:
self.dms_aperture_centroid = self.event.ta_info['aperture_centroid']
self.dms_aperture_centroid_v2v3 = ???
self.dms_det_centroid = self.event.ta_info['detector_centroid']


Expand Down Expand Up @@ -1187,12 +1192,10 @@ def process(self, ta_file, taconfirm_file, science_file):


# Calculate offset of target from ref point, in arcseconds
# This is the offset between the refernnce location and the CALCULATED RA, Dec of the target.
# Keep in mind that this will be wrong if the calcuated RA, Dec is wrong.
offset_RA = (self.ta_data.RA_ref - self.ta_data.RA_targ) * 3600
offset_DEC = (self.ta_data.DEC_ref - self.ta_data.DEC_targ) * 3600

# Maybe better here: look at offset between target x,y (from gentalocate) and ref pos x,y


self.offset = np.sqrt(offset_RA**2 + offset_DEC**2)

logging.info('Target RA: {}, Target DEC: {}'.format(self.ta_data.RA_targ, self.ta_data.DEC_targ))
Expand Down Expand Up @@ -1278,8 +1281,12 @@ def process(self, ta_file, taconfirm_file, science_file):
delta_xy_targ_ref = np.sqrt(delta_x_targ_ref**2 + delta_y_targ_ref**2)
delta_arcsec_targ_ref = np.sqrt((delta_x_targ_ref * self.pixel_scale_x)**2 + (delta_y_targ_ref * self.pixel_scale_y)**2)

request to have this delta in ideal pixels and V2,V3
delta_v2_targ_ref = self.ta_data.V2_ref - self.dms_aperture_centroid_v2v3[0]
delta_v3_targ_ref = self.ta_data.V3_ref - self.dms_aperture_centroid_v2v3[1]
#delta_idlx_targ_ref = self.ta_data.idl_x_targ -
#delta_idly_targ_ref = self.ta_data.idl_y_targ -

request to have the delta above in ideal pixels and V2,V3

# Now we need an independenly measured centroid value to compare to. e.g. photutils
# For now let's use a simple call to photutils' centroid_com(). Note that we are supplying
Expand All @@ -1289,6 +1296,8 @@ def process(self, ta_file, taconfirm_file, science_file):
# 1st quantity to track in requirements page
# x, y offsets between the source and the reference location of the aperture (blind pointing accuracy)
# but this case uses the independently-measured location of the source. Do we really want this?
# This is a repeat of delta_x_targ_ref above, but using the manually calculated centroid rather than the
# GENTALOCATE results
print('Do we really want this?')
ref_dx = x_photutil_centroid - self.x_ref
ref_dy = y_photutil_centroid - self.y_ref
Expand Down Expand Up @@ -1547,7 +1556,7 @@ def run(self):

# Loop through TA apertures and process new data
#for exp_type in exp_type_list:
for instrument in ['nircam', 'niriss', 'miri']:
for instrument in ['nircam']: #['nircam', 'niriss', 'miri']:
logging.info(f'Working on {instrument}')

self.instrument = instrument
Expand All @@ -1559,12 +1568,53 @@ def run(self):
self.identify_tables()

# We start by querying for new data
self.query_start = self.most_recent_search()
self.query_end = Time.now().mjd
#Skip during development at the moment
#self.query_start = self.most_recent_search()
#self.query_end = Time.now().mjd

# Query via django model rather than mast. Leave the aperture value as an empty
# string so that the query will look for all apertures. This will query for TACQ
# and TACONFIRM data

######!!!!!FOR DEVELOPMENT ######
# NIRCam
# 59714 - will get the TA image for NIRCam PID 1068 obs 7 - 2022-05-15 16:23:43
# jw01068007001_02102_00001-seg001_nrcalong_rate.fits
# 59714.5 - 59714.8
#
# NIRISS
# AMI
# JW01093002001_02101_00001_NIS_rate.fits
# 59722.33 - 59722.375
# 2022-05-23 08:24
#
# SOSS
# JW01541001001_02101_00001-SEG001_NIS_RATE.fits
# 2022-06-08T06:16:09.084
# 59738.25 - 59738.3
#
# MIRI
# LRS - fixed slit
# JW01033001001_02101_00001_MIRIMAGE_RATE.fits
# 2022-05-26T10:27:51.288
# 59725.4 - 59725.5
#
# LRS slitless
# JW01353005001_02101_00001-SEG001_MIRIMAGE_RATE.fits
# 2023-03-12T23:25:06.923
# 60015.95 - 60016.
if instrument == 'nircam':
self.query_start = 59714.5
self.query_end = 59714.8
elif instrument == 'niriss':
self.query_start = 59722.33
self.query_end = 59722.375
elif instrument == 'miri':
self.query_start = 60015.95
self.query_end = 60016.0
######!!!!!FOR DEVELOPMENT ######


self.ta_entries = monitor_utils.model_query_ta(self.instrument, '', self.query_start, self.query_end)

# Organize the query results. Remove entries for coron observations and TACQ files we
Expand Down Expand Up @@ -1636,6 +1686,9 @@ def run(self):
else:
monitor_run = False




new_entry = {'instrument': self.instrument,
'exp_type': self.exp_type[0],
'start_time_mjd': self.query_start,
Expand All @@ -1644,10 +1697,11 @@ def run(self):
'files_run': len(ta_files_processed)
'run_monitor': monitor_run,
'entry_date': datetime.datetime.now()}
self.query_table.__table__.insert().execute(new_entry)
# Skip making a database entry for the moment
#self.query_table.__table__.insert().execute(new_entry)

logging.info(f'\tUpdated the query history table with {sef.instrument} results.')
logging.info(f'\t{new_entry}')
#logging.info(f'\tUpdated the query history table with {sef.instrument} results.')
#logging.info(f'\t{new_entry}')



Expand Down

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