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JP-3551: Exclude overlapping background candidates (spacetelescope#8744)
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Co-authored-by: Tyler Pauly <[email protected]>
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@melanieclarke @tapastro
melanieclarke and tapastro authored Sep 17, 2024
1 parent 05d3c96 commit 5b49c08
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4 changes: 4 additions & 0 deletions CHANGES.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -36,6 +36,10 @@ associations

- Remove ``MultilineLogger`` and no longer set it as the default logger. [#8781]

- Excluded nearby background candidates from NIRSpec fixed slit associations
for S1600A1 with 5 point dithers, to reduce overlap between background nods
and science exposure. [#8744]

badpix_selfcal
--------------

Expand Down
261 changes: 166 additions & 95 deletions jwst/associations/lib/rules_level2_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -26,7 +26,7 @@
IMAGE2_NONSCIENCE_EXP_TYPES,
IMAGE2_SCIENCE_EXP_TYPES,
PRODUCT_NAME_DEFAULT,
SPEC2_SCIENCE_EXP_TYPES,
SPEC2_SCIENCE_EXP_TYPES
)
from jwst.associations.lib.member import Member
from jwst.associations.lib.process_list import ListCategory
Expand Down Expand Up @@ -391,98 +391,6 @@ def validate_candidates(self, member):
# fail.
return False

def make_nod_asns(self):
"""Make background nod Associations
For observing modes, such as NIRSpec MSA, exposures can be
nodded, such that the object is in a different position in the
slitlet. The association creation simply groups these all
together as a single association, all exposures marked as
`science`. When complete, this method will create separate
associations each exposure becoming the single science
exposure, and the other exposures then become `background`.
Returns
-------
associations : [association[, ...]]
List of new associations to be used in place of
the current one.
"""

for product in self['products']:
members = product['members']

# Split out the science vs. non-science
# The non-science exposures will get attached
# to every resulting association.
science_exps = [
member
for member in members
if member['exptype'] == 'science'
]
nonscience_exps = [
member
for member in members
if member['exptype'] != 'science'
]

# Create new associations for each science, using
# the other science as background.
results = []
for science_exp in science_exps:
asn = copy.deepcopy(self)
asn.data['products'] = None

product_name = remove_suffix(
splitext(split(science_exp['expname'])[1])[0]
)[0]
asn.new_product(product_name)
new_members = asn.current_product['members']
new_members.append(science_exp)

for other_science in science_exps:
if other_science['expname'] != science_exp['expname']:
if science_exp.item['exp_type'] in ['nrs_fixedslit', 'nrs_msaspec']:
try:
sci_prim_dithpt = (int(science_exp.item['patt_num']) - 1) // \
int(science_exp.item['subpxpts'])
other_prim_dithpt = (int(other_science.item['patt_num']) - 1) // \
int(other_science.item['subpxpts'])
if sci_prim_dithpt != other_prim_dithpt:
now_background = Member(other_science)
now_background['exptype'] = 'background'
new_members.append(now_background)
# Catch missing values with KeyError, NULL values with ValueError
except (ValueError, KeyError):
try:
sci_prim_dithpt = (int(science_exp.item['patt_num']) - 1) // \
int(science_exp.item['subpxpns'])
other_prim_dithpt = (int(other_science.item['patt_num']) - 1) // \
int(other_science.item['subpxpns'])
if sci_prim_dithpt != other_prim_dithpt:
now_background = Member(other_science)
now_background['exptype'] = 'background'
new_members.append(now_background)
except (ValueError, KeyError, ZeroDivisionError):
if science_exp.item['exp_type'] == 'nrs_msaspec':
now_background = Member(other_science)
now_background['exptype'] = 'background'
new_members.append(now_background)
else:
pass
else:
now_background = Member(other_science)
now_background['exptype'] = 'background'
new_members.append(now_background)

new_members += nonscience_exps

if asn.is_valid:
results.append(asn)

return results

def __repr__(self):
try:
file_name, json_repr = self.ioregistry['json'].dump(self)
Expand Down Expand Up @@ -1060,18 +968,181 @@ def _init_hook(self, item):
class AsnMixin_Lv2Nod:
"""Associations that need to create nodding associations
For some spectragraphic modes, background spectra are taken by
For some spectrographic modes, background spectra are taken by
nodding between different slits, or internal slit positions.
The main associations rules will collect all the exposures of all the nods
into a single association. Then, on finalization, this one association
is split out into many associations, where each nod is, in turn, treated
as science, and the other nods are treated as background.
"""

@staticmethod
def nod_background_overlap(science_item, background_item):
"""
Check that a candidate background nod will not overlap with science.
For NIRSpec fixed slit or MOS data, this returns True if the
background candidate shares a primary dither point with the
science.
In addition, for NIRSpec fixed slit exposures taken with slit
S1600A1 in a 5-point nod pattern, this returns True when the
background candidate is in the next closest primary position
to the science.
For any other data, this function returns False (no overlap).
"""
# Get exp_type, needed for any data:
# if not present, return False
try:
exptype = str(science_item['exp_type']).lower()
except KeyError:
return False

# Return False for any non-FS or MOS data
if exptype not in ['nrs_fixedslit', 'nrs_msaspec']:
return False

# Get pattern number values, needed for FS or MOS
try:
numdthpt = int(science_item['numdthpt'])
patt_num = int(science_item['patt_num'])
bkg_num = int(background_item['patt_num'])
except (KeyError, ValueError):
numdthpt = 0
patt_num = None
bkg_num = None

# Get subpxpts (or old alternate 'subpxpns')
try:
subpx = int(science_item['subpxpts'])
except (KeyError, ValueError):
try:
subpx = int(science_item['subpxpns'])
except (KeyError, ValueError):
subpx = None
try:
bkg_subpx = int(background_item['subpxpts'])
except (KeyError, ValueError):
try:
bkg_subpx = int(background_item['subpxpns'])
except (KeyError, ValueError):
bkg_subpx = None

# If values not found, return False for MOS, True for FS
if (None in [patt_num, bkg_num, subpx, bkg_subpx]
or subpx == 0 or bkg_subpx == 0):
if exptype == 'nrs_fixedslit':
# These values are required for background
# candidates for FS: report an overlap.
return True
else:
# For MOS, it's okay to go ahead and use them.
# Report no overlap.
return False

# Check for primary point overlap
sci_prim_dithpt = (patt_num - 1) // subpx
bkg_prim_dithpt = (bkg_num - 1) // bkg_subpx
if sci_prim_dithpt == bkg_prim_dithpt:
# Primary points are the same - overlap is present
return True

# Primary points are not the same -
# no further check needed for MOS
if exptype == 'nrs_msaspec':
return False

# Get slit name, needed only for FS S1600A1 check
try:
slit = str(science_item['fxd_slit']).lower()
except KeyError:
slit = None

# Background is currently only expected to overlap severely for
# 5 point dithers with fixed slit S1600A1. Only the nearest
# dithers to the science observation need to be excluded.
if (exptype == 'nrs_fixedslit'
and slit == 's1600a1'
and numdthpt // subpx == 5
and abs(sci_prim_dithpt - bkg_prim_dithpt) <= 1):
return True

# For anything else, return False
return False

def make_nod_asns(self):
"""Make background nod Associations
For observing modes, such as NIRSpec MSA, exposures can be
nodded, such that the object is in a different position in the
slitlet. The association creation simply groups these all
together as a single association, all exposures marked as
`science`. When complete, this method will create separate
associations each exposure becoming the single science
exposure, and the other exposures then become `background`.
Returns
-------
associations : [association[, ...]]
List of new associations to be used in place of
the current one.
"""

for product in self['products']:
members = product['members']

# Split out the science vs. non-science
# The non-science exposures will get attached
# to every resulting association.
science_exps = [
member
for member in members
if member['exptype'] == 'science'
]
nonscience_exps = [
member
for member in members
if member['exptype'] != 'science'
]

# Create new associations for each science, using
# the other science as background.
results = []
for science_exp in science_exps:
asn = copy.deepcopy(self)
asn.data['products'] = None

product_name = remove_suffix(
splitext(split(science_exp['expname'])[1])[0]
)[0]
asn.new_product(product_name)
new_members = asn.current_product['members']
new_members.append(science_exp)

for other_science in science_exps:
if other_science['expname'] != science_exp['expname']:
# check for likely overlap between science
# and background candidate
overlap = self.nod_background_overlap(
science_exp.item, other_science.item)
if not overlap:
now_background = Member(other_science)
now_background['exptype'] = 'background'
new_members.append(now_background)

new_members += nonscience_exps

if asn.is_valid:
results.append(asn)

return results

def finalize(self):
"""Finalize association
For some spectragraphic modes, background spectra and taken by
For some spectrographic modes, background spectra are taken by
nodding between different slits, or internal slit positions.
The main associations rules will collect all the exposures of all the nods
into a single association. Then, on finalization, this one association
Expand Down
20 changes: 20 additions & 0 deletions jwst/associations/tests/data/pool_024b_nirspec_fss_nods.csv
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@@ -0,0 +1,20 @@
# NIRSpec Fixed-slit with various nods and dithers
#
# This example contains a 5 point dither for S1600A1, no subpixel dither
#
FILENAME|OBS_ID|PROGRAM|OBS_NUM|VISIT|VISIT_ID|VISITGRP|VISITYPE|SEQ_ID|ACT_ID|EXPOSURE|EXP_TYPE|NEXPOSUR|EXPCOUNT|INSTRUME|DETECTOR|CHANNEL|TARGETID|TARGPROP|TARGNAME|TARGTYPE|TEMPLATE|PNTGTYPE|PNTG_SEQ|TARGORDN|EXPSPCIN|DITHPTIN|MOSTILNO|MODULE|FILTER|PUPIL|DITHERID|PATTTYPE|PATTSTRT|NUMDTHPT|PATTSIZE|SUBPXPNS|PATT_NUM|SUBPXNUM|SUBPIXEL|APERNAME|SDP_VER|SUBARRAY|GRATING|FXD_SLIT|BAND|GWA_XTIL|GWA_YTIL|ASN_CANDIDATE|EXPOSERR|IS_PSF|IS_IMPRT|BKGDTARG|TSOVISIT|MSAMETFL|SPAT_NUM|SPEC_NUM
#
# Initialize ACID. This is done with a dummy exposure that will not match any association
set acid|OBS_ID|PROGRAM|OBS_NUM|VISIT|VISIT_ID|VISITGRP|VISITYPE|SEQ_ID|ACT_ID|EXPOSURE|EXP_TYPE|NEXPOSUR|EXPCOUNT|INSTRUME|DETECTOR|CHANNEL|TARGETID|TARGPROP|TARGNAME|TARGTYPE|TEMPLATE|PNTGTYPE|PNTG_SEQ|TARGORDN|EXPSPCIN|DITHPTIN|MOSTILNO|MODULE|FILTER|PUPIL|DITHERID|PATTTYPE|PATTSTRT|NUMDTHPT|PATTSIZE|SUBPXPNS|PATT_NUM|SUBPXNUM|SUBPIXEL|APERNAME|SDP_VER|SUBARRAY|GRATING|FXD_SLIT|BAND|GWA_XTIL|GWA_YTIL|@!next(acid)|EXPOSERR|IS_PSF|IS_IMPRT|BKGDTARG|TSOVISIT|MSAMETFL|SPAT_NUM|SPEC_NUM
#
# Primary Dither=5, Sub-pixel Pattern=None, F290LP/G395H/S1600A1
@!fmt_fname(next(expnum))|V93125002001P0000000002106|93125|@!next(obsnum)|1|93125002001|2|PRIME_TARGETED_FIXED|1|06|1|NRS_FIXEDSLIT|6|6|NIRSPEC|NRS1|NULL|1|TARGET-OBSERVATION-2|NULL|FIXED|NIRSpec Fixed-slit Spectroscopy|SCIENCE|6|1|1|1|1|NULL|F290LP|NULL|NULL|NULL|NULL|5|NULL|1|1|NULL|NULL|S200A1|2017_1|SUB200A1|G395H|S1600A1|NULL|0.2866025270000001|0.17855911|@!fmt_cand([(obsnum.value, 'OBSERVATION')])|NULL|NULL|F|F|F|F|1|NULL
@!fmt_fname(next(expnum))|V93125002001P0000000002106|93125|@!obsnum.value|1|93125002001|2|PRIME_TARGETED_FIXED|1|06|1|NRS_FIXEDSLIT|6|6|NIRSPEC|NRS2|NULL|1|TARGET-OBSERVATION-2|NULL|FIXED|NIRSpec Fixed-slit Spectroscopy|SCIENCE|6|1|1|1|1|NULL|F290LP|NULL|NULL|NULL|NULL|5|NULL|1|1|NULL|NULL|S200A1|2017_1|SUB200A1|G395H|S1600A1|NULL|0.2866025270000001|0.17855911|@!fmt_cand([(obsnum.value, 'OBSERVATION')])|NULL|NULL|F|F|F|F|1|NULL
@!fmt_fname(next(expnum))|V93125002001P0000000002106|93125|@!obsnum.value|1|93125002001|2|PRIME_TARGETED_FIXED|1|06|1|NRS_FIXEDSLIT|6|6|NIRSPEC|NRS1|NULL|1|TARGET-OBSERVATION-2|NULL|FIXED|NIRSpec Fixed-slit Spectroscopy|SCIENCE|6|1|1|1|1|NULL|F290LP|NULL|NULL|NULL|NULL|5|NULL|1|2|NULL|NULL|S200A1|2017_1|SUB200A1|G395H|S1600A1|NULL|0.2866025270000001|0.17855911|@!fmt_cand([(obsnum.value, 'OBSERVATION')])|NULL|NULL|F|F|F|F|2|NULL
@!fmt_fname(next(expnum))|V93125002001P0000000002106|93125|@!obsnum.value|1|93125002001|2|PRIME_TARGETED_FIXED|1|06|1|NRS_FIXEDSLIT|6|6|NIRSPEC|NRS2|NULL|1|TARGET-OBSERVATION-2|NULL|FIXED|NIRSpec Fixed-slit Spectroscopy|SCIENCE|6|1|1|1|1|NULL|F290LP|NULL|NULL|NULL|NULL|5|NULL|1|2|NULL|NULL|S200A1|2017_1|SUB200A1|G395H|S1600A1|NULL|0.2866025270000001|0.17855911|@!fmt_cand([(obsnum.value, 'OBSERVATION')])|NULL|NULL|F|F|F|F|2|NULL
@!fmt_fname(next(expnum))|V93125002001P0000000002106|93125|@!obsnum.value|1|93125002001|2|PRIME_TARGETED_FIXED|1|06|1|NRS_FIXEDSLIT|6|6|NIRSPEC|NRS1|NULL|1|TARGET-OBSERVATION-2|NULL|FIXED|NIRSpec Fixed-slit Spectroscopy|SCIENCE|6|1|1|1|1|NULL|F290LP|NULL|NULL|NULL|NULL|5|NULL|1|3|NULL|NULL|S200A1|2017_1|SUB200A1|G395H|S1600A1|NULL|0.2866025270000001|0.17855911|@!fmt_cand([(obsnum.value, 'OBSERVATION')])|NULL|NULL|F|F|F|F|2|NULL
@!fmt_fname(next(expnum))|V93125002001P0000000002106|93125|@!obsnum.value|1|93125002001|2|PRIME_TARGETED_FIXED|1|06|1|NRS_FIXEDSLIT|6|6|NIRSPEC|NRS2|NULL|1|TARGET-OBSERVATION-2|NULL|FIXED|NIRSpec Fixed-slit Spectroscopy|SCIENCE|6|1|1|1|1|NULL|F290LP|NULL|NULL|NULL|NULL|5|NULL|1|3|NULL|NULL|S200A1|2017_1|SUB200A1|G395H|S1600A1|NULL|0.2866025270000001|0.17855911|@!fmt_cand([(obsnum.value, 'OBSERVATION')])|NULL|NULL|F|F|F|F|2|NULL
@!fmt_fname(next(expnum))|V93125002001P0000000002106|93125|@!obsnum.value|1|93125002001|2|PRIME_TARGETED_FIXED|1|06|1|NRS_FIXEDSLIT|6|6|NIRSPEC|NRS1|NULL|1|TARGET-OBSERVATION-2|NULL|FIXED|NIRSpec Fixed-slit Spectroscopy|SCIENCE|6|1|1|1|1|NULL|F290LP|NULL|NULL|NULL|NULL|5|NULL|1|4|NULL|NULL|S200A1|2017_1|SUB200A1|G395H|S1600A1|NULL|0.2866025270000001|0.17855911|@!fmt_cand([(obsnum.value, 'OBSERVATION')])|NULL|NULL|F|F|F|F|2|NULL
@!fmt_fname(next(expnum))|V93125002001P0000000002106|93125|@!obsnum.value|1|93125002001|2|PRIME_TARGETED_FIXED|1|06|1|NRS_FIXEDSLIT|6|6|NIRSPEC|NRS2|NULL|1|TARGET-OBSERVATION-2|NULL|FIXED|NIRSpec Fixed-slit Spectroscopy|SCIENCE|6|1|1|1|1|NULL|F290LP|NULL|NULL|NULL|NULL|5|NULL|1|4|NULL|NULL|S200A1|2017_1|SUB200A1|G395H|S1600A1|NULL|0.2866025270000001|0.17855911|@!fmt_cand([(obsnum.value, 'OBSERVATION')])|NULL|NULL|F|F|F|F|2|NULL
@!fmt_fname(next(expnum))|V93125002001P0000000002106|93125|@!obsnum.value|1|93125002001|2|PRIME_TARGETED_FIXED|1|06|1|NRS_FIXEDSLIT|6|6|NIRSPEC|NRS1|NULL|1|TARGET-OBSERVATION-2|NULL|FIXED|NIRSpec Fixed-slit Spectroscopy|SCIENCE|6|1|1|1|1|NULL|F290LP|NULL|NULL|NULL|NULL|5|NULL|1|5|NULL|NULL|S200A1|2017_1|SUB200A1|G395H|S1600A1|NULL|0.2866025270000001|0.17855911|@!fmt_cand([(obsnum.value, 'OBSERVATION')])|NULL|NULL|F|F|F|F|2|NULL
@!fmt_fname(next(expnum))|V93125002001P0000000002106|93125|@!obsnum.value|1|93125002001|2|PRIME_TARGETED_FIXED|1|06|1|NRS_FIXEDSLIT|6|6|NIRSPEC|NRS2|NULL|1|TARGET-OBSERVATION-2|NULL|FIXED|NIRSpec Fixed-slit Spectroscopy|SCIENCE|6|1|1|1|1|NULL|F290LP|NULL|NULL|NULL|NULL|5|NULL|1|5|NULL|NULL|S200A1|2017_1|SUB200A1|G395H|S1600A1|NULL|0.2866025270000001|0.17855911|@!fmt_cand([(obsnum.value, 'OBSERVATION')])|NULL|NULL|F|F|F|F|2|NULL
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