From 6832d1ae224b256ee39ed7bdca43cee3853fa477 Mon Sep 17 00:00:00 2001 From: Krzysztof Findeisen Date: Wed, 9 Oct 2024 11:49:56 -0700 Subject: [PATCH 1/6] Modernize ephemerides script. This commit copies innovations from the dataset template, including canonical paths and automated management of the `sso` chained collection. These changes make it easier to apply new improvements. --- scripts/generate_ephemerides_gen3.py | 22 ++++++++++++++-------- 1 file changed, 14 insertions(+), 8 deletions(-) diff --git a/scripts/generate_ephemerides_gen3.py b/scripts/generate_ephemerides_gen3.py index 59f8850..b9b36d9 100644 --- a/scripts/generate_ephemerides_gen3.py +++ b/scripts/generate_ephemerides_gen3.py @@ -25,6 +25,9 @@ Running this script allows for updates to the ephemerides to be incorporated into the dataset. + +This script takes no command-line arguments; it infers everything it needs from +the `preloaded/` repository. """ import glob @@ -36,7 +39,7 @@ import lsst.log import lsst.sphgeom -from lsst.daf.butler import Butler, FileDataset +from lsst.daf.butler import Butler, CollectionType import lsst.obs.base @@ -46,11 +49,12 @@ # Avoid explicit references to dataset package to maximize portability. SCRIPT_DIR = os.path.abspath(os.path.dirname(__file__)) -PIPE_DIR = os.path.join(SCRIPT_DIR, "..", "pipelines") -RAW_DIR = os.path.join(SCRIPT_DIR, "..", "raw") +PIPE_DIR = os.path.normpath(os.path.join(SCRIPT_DIR, "..", "pipelines")) +RAW_DIR = os.path.normpath(os.path.join(SCRIPT_DIR, "..", "raw")) RAW_RUN = "raw" EPHEM_DATASET = "visitSsObjects" -DEST_DIR = os.path.join(SCRIPT_DIR, "..", "preloaded") +DEST_DIR = os.path.normpath(os.path.join(SCRIPT_DIR, "..", "preloaded")) +DEST_COLLECTION = "sso" DEST_RUN = "sso/cached" @@ -92,6 +96,7 @@ def _make_repo_with_instruments(repo_dir, instruments): """ config = Butler.makeRepo(repo_dir) repo = Butler(config, writeable=True) + logging.debug("Temporary repo has universe version %d.", repo.dimensions.version) for instrument in instruments: instrument.register(repo.registry) return repo @@ -112,12 +117,10 @@ def _ingest_raws(repo, raw_dir, run): run : `str` The name of the run into which to import the raws. """ - raws = glob.glob(os.path.join(raw_dir, '**', '*.fits.fz'), recursive=True) - # explicit config workaround for DM-971 + raws = glob.glob(os.path.join(raw_dir, '**', '*.fits*'), recursive=True) ingester = lsst.obs.base.RawIngestTask(butler=repo, config=lsst.obs.base.RawIngestConfig()) ingester.run(raws, run=run) exposures = set(repo.registry.queryDataIds(["exposure"])) - # explicit config workaround for DM-971 definer = lsst.obs.base.DefineVisitsTask(butler=repo, config=lsst.obs.base.DefineVisitsConfig()) definer.run(exposures) @@ -211,7 +214,10 @@ def _transfer_ephems(ephem_type, src_repo, src_dir, run, dest_repo): _get_ephem(workspace, RAW_RUN, DEST_RUN) temp_repo.registry.refresh() # Pipeline added dataset types preloaded = Butler(DEST_DIR, writeable=True) + logging.debug("Preloaded repo has universe version %d.", preloaded.dimensions.version) logging.info("Transferring ephemerides to dataset...") _transfer_ephems(EPHEM_DATASET, temp_repo, workspace, DEST_RUN, preloaded) +preloaded.registry.registerCollection(DEST_COLLECTION, CollectionType.CHAINED) +preloaded.registry.setCollectionChain(DEST_COLLECTION, [DEST_RUN]) -logging.info("Solar system catalogs copied to %s:%s", DEST_DIR, DEST_RUN) +logging.info("Solar system catalogs copied to %s:%s", DEST_DIR, DEST_COLLECTION) From 773ce98f75f8ce74d8144b023f4f192184dec841 Mon Sep 17 00:00:00 2001 From: Krzysztof Findeisen Date: Wed, 9 Oct 2024 12:04:47 -0700 Subject: [PATCH 2/6] Run MPSkyEphemerisQueryTask in generate_ephemerides_gen3.py. The changes to this script are **untested**, because at present the MPSky service can't handle DECam. --- pipelines/Ephemerides.yaml | 6 +++- scripts/generate_ephemerides_gen3.py | 53 +++++++++++++++++----------- 2 files changed, 38 insertions(+), 21 deletions(-) diff --git a/pipelines/Ephemerides.yaml b/pipelines/Ephemerides.yaml index 8ce232d..a3e6985 100644 --- a/pipelines/Ephemerides.yaml +++ b/pipelines/Ephemerides.yaml @@ -1,4 +1,8 @@ description: Pipeline for downloading solar system ephemerides given raw images instrument: lsst.obs.decam.DarkEnergyCamera tasks: - SkyBotEphemerisQuery: lsst.ap.association.skyBotEphemerisQuery.SkyBotEphemerisQueryTask + getRegionTimeFromVisit: + class: lsst.pipe.tasks.getRegionTimeFromVisit.GetRegionTimeFromVisitTask + config: + connections.dummy_visit = visit_dummy + mpSkyEphemerisQuery: lsst.ap.association.MPSkyEphemerisQueryTask diff --git a/scripts/generate_ephemerides_gen3.py b/scripts/generate_ephemerides_gen3.py index b9b36d9..9ede766 100644 --- a/scripts/generate_ephemerides_gen3.py +++ b/scripts/generate_ephemerides_gen3.py @@ -37,9 +37,11 @@ import sys import tempfile +import pandas + import lsst.log import lsst.sphgeom -from lsst.daf.butler import Butler, CollectionType +from lsst.daf.butler import Butler, CollectionType, DatasetType import lsst.obs.base @@ -52,10 +54,11 @@ PIPE_DIR = os.path.normpath(os.path.join(SCRIPT_DIR, "..", "pipelines")) RAW_DIR = os.path.normpath(os.path.join(SCRIPT_DIR, "..", "raw")) RAW_RUN = "raw" -EPHEM_DATASET = "visitSsObjects" +VISIT_DATASET = "visit_dummy" +EPHEM_DATASET = "preloaded_SsObjects" DEST_DIR = os.path.normpath(os.path.join(SCRIPT_DIR, "..", "preloaded")) DEST_COLLECTION = "sso" -DEST_RUN = "sso/cached" +DEST_RUN = DEST_COLLECTION + "/mpsky" ######################################## @@ -103,7 +106,7 @@ def _make_repo_with_instruments(repo_dir, instruments): ######################################## -# Ingest raws (needed for visitinfo) +# Ingest raws (needed for visit records) def _ingest_raws(repo, raw_dir, run): """Ingest this dataset's raws into a specific repo. @@ -125,11 +128,33 @@ def _ingest_raws(repo, raw_dir, run): definer.run(exposures) +######################################## +# Dummy pipeline inputs + +def _make_visit_datasets(repo, run): + """Create stub datasets for running GetRegionTimeFromVisitTask. + + Parameters + --------- + repo : `lsst.daf.butler.Butler` + A writeable Butler in which to create datasets. + run : `str` + The name of the run into which to create datasets. + """ + dummy_type = DatasetType(VISIT_DATASET, {"instrument", "visit", "detector"}, "DataFrame") + repo.registry.registerDatasetType(dummy_type) + # Exclude unused detectors + data_ids = {ref.dataId for ref in repo.query_datasets("raw", collections="*", find_first=False)} + exp_table = pandas.DataFrame() + for id in data_ids: + repo.put(exp_table, dummy_type, id, run=run) + + ######################################## # Download ephemerides def _get_ephem(repo_dir, raw_collection, ephem_collection): - """Run the task for downloading ephemerides. + """Run the tasks for downloading ephemerides. Parameters ---------- @@ -179,25 +204,12 @@ def _transfer_ephems(ephem_type, src_repo, src_dir, run, dest_repo): dest_repo : `lsst.daf.butler.Butler` The repository to which to copy the datasets. """ - # Need to transfer visit definitions as well; Butler.export is the easiest + # Need to transfer group definitions as well; Butler.export is the easiest # way to do this. with tempfile.NamedTemporaryFile(suffix=".yaml") as export_file: with src_repo.export(filename=export_file.name, transfer=None) as contents: contents.saveDatasets(src_repo.registry.queryDatasets(ephem_type, collections=run), - elements=["visit"]) - # Because of how the temp repo was constructed, there should not be - # any visit/exposure records other than those needed to support the - # ephemerides datasets. - contents.saveDimensionData("visit_system", - src_repo.registry.queryDimensionRecords("visit_system")) - contents.saveDimensionData("visit", - src_repo.registry.queryDimensionRecords("visit")) - contents.saveDimensionData("exposure", - src_repo.registry.queryDimensionRecords("exposure")) - contents.saveDimensionData("visit_definition", - src_repo.registry.queryDimensionRecords("visit_definition")) - contents.saveDimensionData("visit_detector_region", - src_repo.registry.queryDimensionRecords("visit_detector_region")) + elements=["group"]) # runs included automatically by saveDatasets dest_repo.import_(directory=src_dir, filename=export_file.name, transfer="copy") @@ -210,6 +222,7 @@ def _transfer_ephems(ephem_type, src_repo, src_dir, run, dest_repo): temp_repo = _make_repo_with_instruments(workspace, _get_instruments(DEST_DIR)) logging.info("Ingesting raws...") _ingest_raws(temp_repo, RAW_DIR, RAW_RUN) + _make_visit_datasets(temp_repo, RAW_RUN) logging.info("Downloading ephemerides...") _get_ephem(workspace, RAW_RUN, DEST_RUN) temp_repo.registry.refresh() # Pipeline added dataset types From 482c0932e8f99cb88b71c4fbf6b16fbbdbfc9449 Mon Sep 17 00:00:00 2001 From: Krzysztof Findeisen Date: Wed, 9 Oct 2024 13:46:33 -0700 Subject: [PATCH 3/6] Convert visitSsObjects catalogs into preloaded_SsObjects. The catalogs have the same format, differing only in dimensionality. This is less efficient than creating a per-detector catalog from scratch, but should let ap_verify data sets keep working until MPSky supports general observatories. --- config/export.yaml | 146 +++++++----------- preloaded/gen3.sqlite3 | 2 +- ...sObjects_DECam_411371_N25_sso_cached.parq} | Bin 27113 -> 27111 bytes ...SsObjects_DECam_411371_N29_sso_cached.parq | Bin 0 -> 27111 bytes ...sObjects_DECam_411371_S26_sso_cached.parq} | Bin 25397 -> 25426 bytes ...SsObjects_DECam_411420_S22_sso_cached.parq | Bin 0 -> 25426 bytes ...SsObjects_DECam_411420_S26_sso_cached.parq | Bin 0 -> 25426 bytes ...sObjects_DECam_419802_S22_sso_cached.parq} | Bin 24634 -> 24622 bytes ...SsObjects_DECam_419802_S26_sso_cached.parq | Bin 0 -> 24622 bytes 9 files changed, 61 insertions(+), 87 deletions(-) rename preloaded/sso/cached/{visitSsObjects/20150217/g/g_DECam_SDSS_c0001_4720.0_1520.0/411371/visitSsObjects_DECam_g_g_DECam_SDSS_c0001_4720_0_1520_0_411371_sso_cached.parq => preloaded_SsObjects/411371/preloaded_SsObjects_DECam_411371_N25_sso_cached.parq} (61%) create mode 100644 preloaded/sso/cached/preloaded_SsObjects/411371/preloaded_SsObjects_DECam_411371_N29_sso_cached.parq rename preloaded/sso/cached/{visitSsObjects/20150217/g/g_DECam_SDSS_c0001_4720.0_1520.0/411420/visitSsObjects_DECam_g_g_DECam_SDSS_c0001_4720_0_1520_0_411420_sso_cached.parq => preloaded_SsObjects/411371/preloaded_SsObjects_DECam_411371_S26_sso_cached.parq} (64%) create mode 100644 preloaded/sso/cached/preloaded_SsObjects/411420/preloaded_SsObjects_DECam_411420_S22_sso_cached.parq create mode 100644 preloaded/sso/cached/preloaded_SsObjects/411420/preloaded_SsObjects_DECam_411420_S26_sso_cached.parq rename preloaded/sso/cached/{visitSsObjects/20150308/g/g_DECam_SDSS_c0001_4720.0_1520.0/419802/visitSsObjects_DECam_g_g_DECam_SDSS_c0001_4720_0_1520_0_419802_sso_cached.parq => preloaded_SsObjects/419802/preloaded_SsObjects_DECam_419802_S22_sso_cached.parq} (63%) create mode 100644 preloaded/sso/cached/preloaded_SsObjects/419802/preloaded_SsObjects_DECam_419802_S26_sso_cached.parq diff --git a/config/export.yaml b/config/export.yaml index 98a9154..430c343 100644 --- a/config/export.yaml +++ b/config/export.yaml @@ -585,57 +585,6 @@ data: cell_y: 1 region: ! encoded: 7046b96efeaeedecbf4af672fa0396da3f9a4b911b91d9b9bf4b1d85fc62ffecbf1e9af7236748da3faeaca89700dab9bf6316771d5103edbf1b0e4797e04bda3f48a011bf1b7eb8bfebacf8dd9cf1ecbf8fed532c7e99da3f64d6111db27db8bf -- type: dimension - element: visit - records: - - instrument: DECam - id: 411371 - day_obs: 20150217 - physical_filter: g DECam SDSS c0001 4720.0 1520.0 - name: ct4m20150218t052637 - seq_num: 411371 - exposure_time: 86.0 - target_name: Blind15A_42 - observation_reason: science - science_program: 2015A-0608 - azimuth: 353.1027 - zenith_angle: 25.289999999999992 - region: ! - encoded: 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 - datetime_begin: !butler_time/tai/iso '2015-02-18 05:27:12.433035000' - datetime_end: !butler_time/tai/iso '2015-02-18 05:29:25.000000000' - - instrument: DECam - id: 411420 - day_obs: 20150217 - physical_filter: g DECam SDSS c0001 4720.0 1520.0 - name: ct4m20150218t070355 - seq_num: 411420 - exposure_time: 86.0 - target_name: Blind15A_40 - observation_reason: science - science_program: 2015A-0608 - azimuth: 306.579 - zenith_angle: 35.09 - region: ! - encoded: 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 - datetime_begin: !butler_time/tai/iso '2015-02-18 07:04:30.532568000' - datetime_end: !butler_time/tai/iso '2015-02-18 07:06:54.000000000' - - instrument: DECam - id: 419802 - day_obs: 20150308 - physical_filter: g DECam SDSS c0001 4720.0 1520.0 - name: ct4m20150309t055516 - seq_num: 419802 - exposure_time: 102.0 - target_name: Blind15A_40 - observation_reason: science - science_program: 2015A-0608 - azimuth: 304.7488 - zenith_angle: 36.15 - region: ! - encoded: 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 - datetime_begin: !butler_time/tai/iso '2015-03-09 05:55:51.522985000' - datetime_end: !butler_time/tai/iso '2015-03-09 05:58:23.000000000' - type: dimension element: visit_definition records: @@ -8314,6 +8263,66 @@ data: detector: 20 path: DECam/calib/curated/19700101T000000Z/linearizer/linearizer_DECam_S9_DECam_calib_curated_19700101T000000Z.fits formatter: lsst.obs.base.formatters.fitsGeneric.FitsGenericFormatter +- type: dataset_type + name: preloaded_SsObjects + dimensions: + - instrument + - detector + - group + storage_class: DataFrame + is_calibration: false +- type: dataset + dataset_type: preloaded_SsObjects + run: sso/cached + records: + - dataset_id: + - !uuid 'ca995f91-40f8-4dc2-9fb5-fdcb37c436d9' + data_id: + - instrument: DECam + detector: 56 + group: '411371' + path: sso/cached/preloaded_SsObjects/411371/preloaded_SsObjects_DECam_411371_N25_sso_cached.parq + formatter: lsst.daf.butler.formatters.parquet.ParquetFormatter + - dataset_id: + - !uuid 'ff0b1579-3018-41b5-832f-de7951caa8b5' + data_id: + - instrument: DECam + detector: 60 + group: '411371' + path: sso/cached/preloaded_SsObjects/411371/preloaded_SsObjects_DECam_411371_N29_sso_cached.parq + formatter: lsst.daf.butler.formatters.parquet.ParquetFormatter + - dataset_id: + - !uuid '692d3282-5fde-45a7-aebb-3b50f10cbe1d' + data_id: + - instrument: DECam + detector: 10 + group: '411420' + path: sso/cached/preloaded_SsObjects/411420/preloaded_SsObjects_DECam_411420_S22_sso_cached.parq + formatter: lsst.daf.butler.formatters.parquet.ParquetFormatter + - dataset_id: + - !uuid '7003813f-c6a8-4157-beb1-6faab95a4988' + data_id: + - instrument: DECam + detector: 5 + group: '411420' + path: sso/cached/preloaded_SsObjects/411420/preloaded_SsObjects_DECam_411420_S26_sso_cached.parq + formatter: lsst.daf.butler.formatters.parquet.ParquetFormatter + - dataset_id: + - !uuid 'be1df728-6f1e-4859-9869-09698aa30a4f' + data_id: + - instrument: DECam + detector: 10 + group: '419802' + path: sso/cached/preloaded_SsObjects/419802/preloaded_SsObjects_DECam_419802_S22_sso_cached.parq + formatter: lsst.daf.butler.formatters.parquet.ParquetFormatter + - dataset_id: + - !uuid '1fa81cef-9ae5-46f9-8fae-c90fe1db32e8' + data_id: + - instrument: DECam + detector: 5 + group: '419802' + path: sso/cached/preloaded_SsObjects/419802/preloaded_SsObjects_DECam_419802_S26_sso_cached.parq + formatter: lsst.daf.butler.formatters.parquet.ParquetFormatter - type: dataset_type name: pretrainedModelPackage dimensions: [] @@ -9297,41 +9306,6 @@ data: - skymap: decam_rings_v1 path: skymaps/skyMap/skyMap_decam_rings_v1_skymaps.pickle formatter: lsst.daf.butler.formatters.pickle.PickleFormatter -- type: dataset_type - name: visitSsObjects - dimensions: - - band - - instrument - - day_obs - - physical_filter - - visit - storage_class: DataFrame - is_calibration: false -- type: dataset - dataset_type: visitSsObjects - run: sso/cached - records: - - dataset_id: - - !uuid 'f559ba2e-371b-4d5f-846e-babedfa458bd' - data_id: - - instrument: DECam - visit: 411371 - path: sso/cached/visitSsObjects/20150217/g/g_DECam_SDSS_c0001_4720.0_1520.0/411371/visitSsObjects_DECam_g_g_DECam_SDSS_c0001_4720_0_1520_0_411371_sso_cached.parq - formatter: lsst.daf.butler.formatters.parquet.ParquetFormatter - - dataset_id: - - !uuid '8ed21fb1-ad38-4077-8fe5-4a8091e3c9e5' - data_id: - - instrument: DECam - visit: 411420 - path: sso/cached/visitSsObjects/20150217/g/g_DECam_SDSS_c0001_4720.0_1520.0/411420/visitSsObjects_DECam_g_g_DECam_SDSS_c0001_4720_0_1520_0_411420_sso_cached.parq - formatter: lsst.daf.butler.formatters.parquet.ParquetFormatter - - dataset_id: - - !uuid 'cfdc5734-fe7b-4d6e-a2a7-833b89aa970c' - data_id: - - instrument: DECam - visit: 419802 - path: sso/cached/visitSsObjects/20150308/g/g_DECam_SDSS_c0001_4720.0_1520.0/419802/visitSsObjects_DECam_g_g_DECam_SDSS_c0001_4720_0_1520_0_419802_sso_cached.parq - formatter: 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zQ;M@|->+QtG4gG;3(Ex@18)8m9B|l<0<1<=6u$EBm;_59$FHex_aVr)`gKWmMJ^ek zPAIDP+opb9k{f9(u!Lnbi^;dh5@9Zl?hA3J$V{de#lF>c>9yva5IUGQsNC5F6k0`!{s_-^7NJl+@(Zm%6EL zz+H1Pvbb!}bsU-h-u0Lgo*wo}m&U$twRcHMcuHFQ|4&)Nvug{8tW;~PXhxT>^}jb; z_etp+8Ki`#U&Y?ENboDs9Za8M}6c+!O(E4C;o0KG_-O_l=QS$Z>2gXd0VKV+!7P+=E#Aw!8(p zvG%<;-!DxV(6zqiOUQqV zLbgVZu1P4=*2EQ=3fcOzQ7uVkXT}W3$uL%NG>W3D;tRF4(WPp3E0W57<*?h8(EefU zwF&kw1iNjC&4+DEh??CSCUe`E{%{|b#_m5$*==cLe|AS>VDCfO`vi7!Xdm`FkNpZ` zH*MDat08Fs><8g4Ihx%`SvNuK#QG1ni;a3|1JeL*|HXE~b{Rg=Nt)N@$8fE$=5zaL z*yA?xFBp+;f(5}s%=KGgc9NA|=1Y3<91&~lD|)OBOi*iP^*8ln_tS6}YKrb^?9|Bs zm*HX7O*uE7yM#vguv@*5+AL^JtJYiP%@3{U)SH_hVyfW=aZ0gn1-W}pYiY2DOv$LJ z&Mh&&+D}L4cC_+~Hfi6GH;SA3N?vaL5wFE(lPT`i{P3iDd6KQ`_0LKbUZ0zQ ztoEh+CPV%D8|2SoSvQiOBb5>fkB>6KVGnOgWX})aZ>TAJ0sNCe=bXRfhjQl`?7;t|zw8M1456XMgSv!OO;j!rVeJ(S`}x<`-$Z}x_{ij! z^$IsX_SJk-gFn{mugQGYU&3FnaZL%Y=EwgJ^SSevaDqG5F`2She+9jAs^;X+dO1Ih zm9!~-*w*lb3dqlJrU3rOj@K5|uRlD(>aVPk8|&W;w;|yvsn$Gciekri> Date: Thu, 10 Oct 2024 11:19:48 -0700 Subject: [PATCH 4/6] Add script for generating APDB catalogs from internal data. This script takes a long time to run, because it simulates ApPipe execution visit by visit. --- scripts/generate_all_gen3.sh | 9 +- scripts/generate_self_preload.py | 254 +++++++++++++++++++++++++++++++ 2 files changed, 261 insertions(+), 2 deletions(-) create mode 100644 scripts/generate_self_preload.py diff --git a/scripts/generate_all_gen3.sh b/scripts/generate_all_gen3.sh index 09f9ba2..cb4b846 100755 --- a/scripts/generate_all_gen3.sh +++ b/scripts/generate_all_gen3.sh @@ -117,12 +117,17 @@ python "${SCRIPT_DIR}/generate_ephemerides_gen3.py" "${SCRIPT_DIR}/generate_fake_injection_catalog.sh" -b ${DATASET_REPO} -o ${INJECTION_CATALOG_COLLECTION} +######################################## +# Generate self-consistent APDB data + +python "${SCRIPT_DIR}/generate_self_preload.py" # Must be run after all other ApPipe inputs available + ######################################## # Final clean-up butler collection-chain "${DATASET_REPO}" sso sso/cached -butler collection-chain "${DATASET_REPO}" DECam/defaults templates/goodSeeing skymaps DECam/calib refcats sso \ - models ${INJECTION_CATALOG_COLLECTION} +butler collection-chain "${DATASET_REPO}" DECam/defaults templates/goodSeeing skymaps DECam/calib \ + refcats sso dia_catalogs models ${INJECTION_CATALOG_COLLECTION} python "${SCRIPT_DIR}/make_preloaded_export.py" echo "Gen 3 preloaded repository complete." diff --git a/scripts/generate_self_preload.py b/scripts/generate_self_preload.py new file mode 100644 index 0000000..df7c8da --- /dev/null +++ b/scripts/generate_self_preload.py @@ -0,0 +1,254 @@ +#!/usr/bin/env python +# This file is part of ap_verify_ci_hits2015. +# +# Developed for the LSST Data Management System. +# This product includes software developed by the LSST Project +# (https://www.lsst.org). +# See the COPYRIGHT file at the top-level directory of this distribution +# for details of code ownership. +# +# This program is free software: you can redistribute it and/or modify +# it under the terms of the GNU General Public License as published by +# the Free Software Foundation, either version 3 of the License, or +# (at your option) any later version. +# +# This program is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +# GNU General Public License for more details. +# +# You should have received a copy of the GNU General Public License +# along with this program. If not, see . + +"""Script for simulating the APDB preloads generated by associating this +dataset's observations. + +This script assumes visits are processed in ascending numerical order, with no +prior history. Prior sources must be provided through a different script. + +This script requires that all other input datasets are already in preloaded/, +but does not require that export.yaml be up to date. It (or rather, the +pipeline configs) require that the repository be set up. + +This script takes roughly 14 minutes to run on rubin-devl. +""" + +import glob +import logging +import os +import subprocess +import sys +import tempfile + +import lsst.log +from lsst.daf.butler import Butler, CollectionType, MissingCollectionError +import lsst.obs.base +import lsst.dax.apdb + + +logging.basicConfig(level=logging.INFO, stream=sys.stdout) +lsst.log.configure_pylog_MDC("DEBUG", MDC_class=None) + + +# Avoid explicit references to dataset package to maximize portability. +SCRIPT_DIR = os.path.abspath(os.path.dirname(__file__)) +PIPE_DIR = os.path.join(SCRIPT_DIR, "..", "pipelines") +RAW_DIR = os.path.join(SCRIPT_DIR, "..", "raw") +RAW_RUN = "raw" +PRELOAD_TYPES = ["preloaded_*"] +DEST_DIR = os.path.join(SCRIPT_DIR, "..", "preloaded") +DEST_COLLECTION = "dia_catalogs" +DEST_RUN = DEST_COLLECTION + "/apdb" + + +######################################## +# Processing steps + +def _clear_preloaded(butler): + """Remove preloaded datasets from the collection's chain. + + If it exists, ``DEST_RUN`` is removed entirely to keep it from interfering + with the rest of this script. Other runs are merely unlinked in case they + would still be useful. + + Parameters + ---------- + butler : `lsst.daf.butler.Butler` + A writeable Butler pointing to this repository. + """ + try: + butler.collections.redefine_chain(DEST_COLLECTION, []) + except MissingCollectionError: + # No preloaded datasets to begin with + return + butler.removeRuns([DEST_RUN], unstore=True) + + +def _copy_repo_to(src_butler, repo_dir): + """Create a repository that's a copy of this one. + + Parameters + ---------- + src_butler : `lsst.daf.butler.Butler` + A Butler pointing to this repository. + repo_dir : `str` + The directory in which to create the new repository. + + Returns + ------- + butler : `lsst.daf.butler.Butler` + A writeable Butler to the new repo. + """ + # Don't use ap_verify code, to avoid dependency on potentially out-of-date export.yaml + repo_config = Butler.makeRepo(repo_dir) + dest_butler = Butler(repo_config, writeable=True) + logging.debug("Temporary repo has universe version %d.", dest_butler.dimensions.version) + # Use export/import to preserve chained and calibration collections + with tempfile.NamedTemporaryFile(suffix=".yaml") as export_file: + with src_butler.export(filename=export_file.name, transfer=None) as contents: + for t in src_butler.registry.queryDatasetTypes(): + contents.saveDatasets( + src_butler.query_datasets(t, collections="*", find_first=False, explain=False)) + # runs and dimensions included automatically + for coll in src_butler.collections.query("*", include_chains=True): + contents.saveCollection(coll) + dest_butler.import_(directory=DEST_DIR, filename=export_file.name, transfer="auto") + return dest_butler + + +def _ingest_raws(repo, raw_dir, run): + """Ingest this dataset's raws into a specific repo. + + Parameters + --------- + repo : `lsst.daf.butler.Butler` + A writeable Butler for the repository to ingest into. + raw_dir : `str` + The directory containing raw files. + run : `str` + The name of the run into which to import the raws. + """ + raws = glob.glob(os.path.join(raw_dir, '**', '*.fits*'), recursive=True) + ingester = lsst.obs.base.RawIngestTask(butler=repo, config=lsst.obs.base.RawIngestConfig()) + ingester.run(raws, run=run) + exposures = set(repo.registry.queryDataIds(["exposure"])) + definer = lsst.obs.base.DefineVisitsTask(butler=repo, config=lsst.obs.base.DefineVisitsConfig()) + definer.run(exposures) + + +def _check_pipeline(butler): + """Confirm that the pipeline is correctly configured. + + Parameters + ---------- + butler : `lsst.daf.butler.Butler` + A Butler pointing to this repository. + """ + pipeline_file = os.path.join(PIPE_DIR, "ApPipe.yaml") + pipeline = lsst.pipe.base.Pipeline.fromFile(pipeline_file) + pipeline.addConfigOverride("parameters", "apdb_config", "foo") + # Check that the configs load correctly; raises if there's a setup missing + pipeline.to_graph() + + +def _build_catalogs(repo_dir, input_collections, output_collection): + """Simulate an AP pipeline run. + + Parameters + ---------- + repo_dir : `str` + The repository on which to run the task. + input_collections : iterable [`str`] + The collection containing inputs. + output_collection : `str` + The collection into which to generate preloaded catalogs. + + Raises + ------ + RuntimeError + Raised on any pipeline failure. + """ + # Should be only one instrument + butler = Butler(repo_dir) + instrument = butler.query_data_ids("instrument")[0]["instrument"] + visits = [coord["visit"] for coord in butler.query_data_ids("visit")] + pipeline_file = os.path.join(PIPE_DIR, "ApPipe.yaml") + + # Create temporary APDB + apdb_location = f"sqlite:///{repo_dir}/apdb.db" + logging.debug("Creating apdb at %s...", apdb_location) + apdb_config = lsst.dax.apdb.ApdbSql.init_database(db_url=apdb_location) + + with tempfile.NamedTemporaryFile(suffix=".py") as config_file: + apdb_config.save(config_file.name) + + # Guarantee execution in observation order + run_exists = False + for visit in sorted(visits): + logging.info("Generating catalogs for visit %d...", visit) + pipeline_args = ["pipetask", "run", + "--butler-config", repo_dir, + "--pipeline", pipeline_file, + "--config", f"parameters:apdb_config='{config_file.name}'", + "--input", ",".join(input_collections), + # Can reuse collection as long as data IDs don't overlap + "--output-run", output_collection, + "--data-query", f"instrument='{instrument}' and visit={visit}", + "--processes", "6", + "--register-dataset-types", + ] + if run_exists: + pipeline_args.append("--extend-run") + results = subprocess.run(pipeline_args, capture_output=False, shell=False, check=False) + run_exists = True + if results.returncode: + raise RuntimeError("Pipeline failed to run; see log for details.") + + +def _transfer_catalogs(catalog_types, src_repo, run, dest_repo): + """Copy preloaded catalogs between two repositories. + + Parameters + ---------- + catalog_types : iterable [`str`] + A query expression for dataset types for preloaded catalogs. + src_repo : `lsst.daf.butler.Butler` + The repository from which to copy the datasets. + run : `str` + The name of the run containing the catalogs in both ``src_repo`` + and ``dest_repo``. + dest_repo : `lsst.daf.butler.Butler` + The repository to which to copy the datasets. + """ + expanded_types = src_repo.registry.queryDatasetTypes(catalog_types) + datasets = set() + for t in expanded_types: + datasets.update(src_repo.query_datasets(t, collections=run, explain=False)) + dest_repo.transfer_from(src_repo, datasets, transfer="copy", + register_dataset_types=True, transfer_dimensions=True) + + +######################################## +# Put everything together + +preloaded = Butler(DEST_DIR, writeable=True) +_check_pipeline(preloaded) +logging.info("Removing old catalogs...") +_clear_preloaded(preloaded) +logging.info("Creating temporary repository...") +with tempfile.TemporaryDirectory() as workspace: + temp_repo = _copy_repo_to(preloaded, workspace) + logging.info("Ingesting raws...") + _ingest_raws(temp_repo, RAW_DIR, RAW_RUN) + logging.info("Simulating DIA analysis...") + inst_name = temp_repo.query_data_ids("instrument")[0]["instrument"] + instrument = lsst.obs.base.Instrument.fromName(inst_name, temp_repo.registry) + _build_catalogs(workspace, [RAW_RUN, instrument.makeUmbrellaCollectionName()], DEST_RUN) + temp_repo.registry.refresh() # Pipeline added dataset types + logging.debug("Preloaded repo has universe version %d.", preloaded.dimensions.version) + logging.info("Transferring catalogs to data set...") + _transfer_catalogs(PRELOAD_TYPES, temp_repo, DEST_RUN, preloaded) +preloaded.collections.register(DEST_COLLECTION, CollectionType.CHAINED) +preloaded.collections.prepend_chain(DEST_COLLECTION, DEST_RUN) + +logging.info("Preloaded APDB catalogs copied to %s:%s", DEST_DIR, DEST_COLLECTION) From 49f3a3f176f32dfa6ef37f190caeb08d3b47aad3 Mon Sep 17 00:00:00 2001 From: Krzysztof Findeisen Date: Thu, 10 Oct 2024 11:20:58 -0700 Subject: [PATCH 5/6] Add preloaded APDB catalogs. These catalogs are generated visit-by-visit from scratch, so the visit 411371 catalogs are empty. --- README.md | 2 +- config/export.yaml | 1137 +++-------------- doc/ap_verify_ci_hits2015/index.rst | 1 + ...es_DECam_411371_N25_dia_catalogs_apdb.parq | Bin 0 -> 8885 bytes ...es_DECam_411371_N29_dia_catalogs_apdb.parq | Bin 0 -> 8885 bytes ...es_DECam_411420_S22_dia_catalogs_apdb.parq | Bin 0 -> 23021 bytes ...es_DECam_411420_S26_dia_catalogs_apdb.parq | Bin 0 -> 24187 bytes ...es_DECam_419802_S22_dia_catalogs_apdb.parq | Bin 0 -> 31762 bytes ...es_DECam_419802_S26_dia_catalogs_apdb.parq | Bin 0 -> 36542 bytes ...ts_DECam_411371_N25_dia_catalogs_apdb.parq | Bin 0 -> 103268 bytes ...ts_DECam_411371_N29_dia_catalogs_apdb.parq | Bin 0 -> 103268 bytes ...ts_DECam_411420_S22_dia_catalogs_apdb.parq | Bin 0 -> 138006 bytes ...ts_DECam_411420_S26_dia_catalogs_apdb.parq | Bin 0 -> 140623 bytes ...ts_DECam_419802_S22_dia_catalogs_apdb.parq | Bin 0 -> 147955 bytes ...ts_DECam_419802_S26_dia_catalogs_apdb.parq | Bin 0 -> 155214 bytes ...es_DECam_411371_N25_dia_catalogs_apdb.parq | Bin 0 -> 76155 bytes ...es_DECam_411371_N29_dia_catalogs_apdb.parq | Bin 0 -> 76155 bytes ...es_DECam_411420_S22_dia_catalogs_apdb.parq | Bin 0 -> 122791 bytes ...es_DECam_411420_S26_dia_catalogs_apdb.parq | Bin 0 -> 124431 bytes ...es_DECam_419802_S22_dia_catalogs_apdb.parq | Bin 0 -> 138958 bytes ...es_DECam_419802_S26_dia_catalogs_apdb.parq | Bin 0 -> 152093 bytes preloaded/gen3.sqlite3 | 2 +- 22 files changed, 195 insertions(+), 947 deletions(-) create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaForcedSources/411371/preloaded_diaForcedSources_DECam_411371_N25_dia_catalogs_apdb.parq create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaForcedSources/411371/preloaded_diaForcedSources_DECam_411371_N29_dia_catalogs_apdb.parq create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaForcedSources/411420/preloaded_diaForcedSources_DECam_411420_S22_dia_catalogs_apdb.parq create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaForcedSources/411420/preloaded_diaForcedSources_DECam_411420_S26_dia_catalogs_apdb.parq create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaForcedSources/419802/preloaded_diaForcedSources_DECam_419802_S22_dia_catalogs_apdb.parq create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaForcedSources/419802/preloaded_diaForcedSources_DECam_419802_S26_dia_catalogs_apdb.parq create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaObjects/411371/preloaded_diaObjects_DECam_411371_N25_dia_catalogs_apdb.parq create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaObjects/411371/preloaded_diaObjects_DECam_411371_N29_dia_catalogs_apdb.parq create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaObjects/411420/preloaded_diaObjects_DECam_411420_S22_dia_catalogs_apdb.parq create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaObjects/411420/preloaded_diaObjects_DECam_411420_S26_dia_catalogs_apdb.parq create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaObjects/419802/preloaded_diaObjects_DECam_419802_S22_dia_catalogs_apdb.parq create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaObjects/419802/preloaded_diaObjects_DECam_419802_S26_dia_catalogs_apdb.parq create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaSources/411371/preloaded_diaSources_DECam_411371_N25_dia_catalogs_apdb.parq create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaSources/411371/preloaded_diaSources_DECam_411371_N29_dia_catalogs_apdb.parq create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaSources/411420/preloaded_diaSources_DECam_411420_S22_dia_catalogs_apdb.parq create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaSources/411420/preloaded_diaSources_DECam_411420_S26_dia_catalogs_apdb.parq create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaSources/419802/preloaded_diaSources_DECam_419802_S22_dia_catalogs_apdb.parq create mode 100644 preloaded/dia_catalogs/apdb/preloaded_diaSources/419802/preloaded_diaSources_DECam_419802_S26_dia_catalogs_apdb.parq diff --git a/README.md b/README.md index 0cef01c..beb3ff8 100644 --- a/README.md +++ b/README.md @@ -18,7 +18,7 @@ path | description `config` | Dataset-specific configs to help the Science Pipelines work with this dataset. `pipelines` | Dataset-specific pipelines to run on this dataset. `dataIds.list` | List of dataIds for use in running Tasks. Currently set to run all Ids. -`preloaded` | Starter Gen3 Butler repo containing a skymap, DECam Community Pipeline MasterCalibs from the 2015 HiTS campaign, deep g-band coadds for use as differencing templates, Gaia and PS1 reference catalogs in HTM format for regions overlapping any visit in the dataset, and a pretrained machine learning model for real/bogus classification. +`preloaded` | Starter Gen3 Butler repo containing a skymap, DECam Community Pipeline MasterCalibs from the 2015 HiTS campaign, deep g-band coadds for use as differencing templates, Gaia and PS1 reference catalogs in HTM format for regions overlapping any visit in the dataset, mock APDB outputs based on the raw images, and a pretrained machine learning model for real/bogus classification. `scripts` | Scripts and data for generating this dataset. Git LFS diff --git a/config/export.yaml b/config/export.yaml index 430c343..07c553e 100644 --- a/config/export.yaml +++ b/config/export.yaml @@ -585,951 +585,6 @@ data: cell_y: 1 region: ! encoded: 7046b96efeaeedecbf4af672fa0396da3f9a4b911b91d9b9bf4b1d85fc62ffecbf1e9af7236748da3faeaca89700dab9bf6316771d5103edbf1b0e4797e04bda3f48a011bf1b7eb8bfebacf8dd9cf1ecbf8fed532c7e99da3f64d6111db27db8bf -- type: dimension - element: visit_definition - records: - - instrument: DECam - exposure: 411371 - visit: 411371 - - instrument: DECam - exposure: 411420 - visit: 411420 - - instrument: DECam - exposure: 419802 - visit: 419802 -- type: dimension - element: visit_detector_region - records: - - instrument: DECam - detector: 1 - visit: 411371 - region: ! - encoded: 706d6767f746eeecbf5e0bfb47f3fdda3fc0d67a55e4a6b1bfa05d2d098dececbf8d28806981fcda3ff4c83448587ab2bf2f06743fb600edbf71af46e769a5da3f05a11a94217ab2bf34e18d296c02edbf8ce2bbc5eda6da3f6a7e7a8292a6b1bf - - instrument: DECam - detector: 1 - visit: 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'11f1535a-a4b6-4a71-b92f-299966879980' + data_id: + - instrument: DECam + detector: 5 + group: '411420' + path: dia_catalogs/apdb/preloaded_diaSources/411420/preloaded_diaSources_DECam_411420_S26_dia_catalogs_apdb.parq + formatter: lsst.daf.butler.formatters.parquet.ParquetFormatter + - dataset_id: + - !uuid '792b8c69-ee8d-469f-a9cf-a6fb5c2fc68c' + data_id: + - instrument: DECam + detector: 10 + group: '419802' + path: dia_catalogs/apdb/preloaded_diaSources/419802/preloaded_diaSources_DECam_419802_S22_dia_catalogs_apdb.parq + formatter: lsst.daf.butler.formatters.parquet.ParquetFormatter + - dataset_id: + - !uuid 'fbf13a2a-12b9-46ab-b745-882a25984eeb' + data_id: + - instrument: DECam + detector: 5 + group: '419802' + path: dia_catalogs/apdb/preloaded_diaSources/419802/preloaded_diaSources_DECam_419802_S26_dia_catalogs_apdb.parq + formatter: lsst.daf.butler.formatters.parquet.ParquetFormatter - type: dataset_type name: pretrainedModelPackage dimensions: [] diff --git a/doc/ap_verify_ci_hits2015/index.rst b/doc/ap_verify_ci_hits2015/index.rst index 9e099c9..e68a2a3 100644 --- a/doc/ap_verify_ci_hits2015/index.rst +++ b/doc/ap_verify_ci_hits2015/index.rst @@ -30,6 +30,7 @@ It contains: * biases (``zci``) and g-band flats (``fci``) * reference catalogs for Gaia and Pan-STARRS1, covering the raw images' footprint. * image differencing templates coadded from HiTS 2014 data, covering the raw images' footprint. +* mock APDB catalogs based on processing the raw images in order. * the rbResnet50-DC2 pretrained machine learning model for real/bogus classification .. _ap_verify_ci_hits2015-contributing: diff --git a/preloaded/dia_catalogs/apdb/preloaded_diaForcedSources/411371/preloaded_diaForcedSources_DECam_411371_N25_dia_catalogs_apdb.parq b/preloaded/dia_catalogs/apdb/preloaded_diaForcedSources/411371/preloaded_diaForcedSources_DECam_411371_N25_dia_catalogs_apdb.parq new file mode 100644 index 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sha256:b3a347c2105fc2931016aa97075bee401fd0d6f99b19cdd24cf5ab34210a5bdd +oid sha256:00a0291d867e8159df4efa28d3dd47ab6684d79572a95b469b08b064ed8653d9 size 5574656 From 76a2d5ac9445811fa225c887d4c3d0e7e9c09bcc Mon Sep 17 00:00:00 2001 From: Krzysztof Findeisen Date: Thu, 10 Oct 2024 13:25:38 -0700 Subject: [PATCH 6/6] Remove unused Butler metadata. This removes the exposure, visit, and day_obs dimensions, as well as the visitSsObjects dataset type and the old deepCoadd_skyMap dimension records. --- config/export.yaml | 86 ------------------------------------------ preloaded/gen3.sqlite3 | 2 +- 2 files changed, 1 insertion(+), 87 deletions(-) diff --git a/config/export.yaml b/config/export.yaml index 07c553e..5ba5ae0 100644 --- a/config/export.yaml +++ b/config/export.yaml @@ -21,17 +21,6 @@ data: tract_max: 18938 patch_nx_max: 6 patch_ny_max: 6 -- type: dimension - element: day_obs - records: - - instrument: DECam - id: 20150217 - datetime_begin: !butler_time/tai/iso '2015-02-17 12:00:00.000000000' - datetime_end: !butler_time/tai/iso '2015-02-18 12:00:00.000000000' - - instrument: DECam - id: 20150308 - datetime_begin: !butler_time/tai/iso '2015-03-08 12:00:00.000000000' - datetime_end: !butler_time/tai/iso '2015-03-09 12:00:00.000000000' - type: dimension element: detector records: @@ -437,81 +426,6 @@ data: id: 8605 region: ! encoded: 7034c5a3c6d8e9ecbf074d37139d92da3feaeedb4a631cbbbfe5c660e89b4eedbf3c3ab4a0bbc9d83f8751a953631cbbbf088ef2d95663edbf5692e44605dcd83f9e26fd0a3957b3bf68884fb893feecbf645ecdb8e6a4da3f419ab5043957b3bf -- type: dimension - element: exposure - records: - - instrument: DECam - id: 411371 - day_obs: 20150217 - group: '411371' - physical_filter: g DECam SDSS c0001 4720.0 1520.0 - obs_id: ct4m20150218t052637 - exposure_time: 86.0 - dark_time: 87.1173 - observation_type: science - observation_reason: science - seq_num: 411371 - seq_start: 411371 - seq_end: 411371 - target_name: Blind15A_42 - science_program: 2015A-0608 - tracking_ra: 155.47028496089578 - tracking_dec: -4.9500504054240375 - sky_angle: 90.0 - azimuth: 353.1027 - zenith_angle: 25.289999999999992 - has_simulated: false - can_see_sky: true - datetime_begin: !butler_time/tai/iso '2015-02-18 05:27:12.433035000' - datetime_end: !butler_time/tai/iso '2015-02-18 05:29:25.000000000' - - instrument: DECam - id: 411420 - day_obs: 20150217 - group: '411420' - physical_filter: g DECam SDSS c0001 4720.0 1520.0 - obs_id: ct4m20150218t070355 - exposure_time: 86.0 - dark_time: 87.3794801 - observation_type: science - observation_reason: science - seq_num: 411420 - seq_start: 411420 - seq_end: 411420 - target_name: Blind15A_40 - science_program: 2015A-0608 - tracking_ra: 155.12027235395627 - tracking_dec: -6.5201342700889855 - sky_angle: 90.0 - azimuth: 306.579 - zenith_angle: 35.09 - has_simulated: false - can_see_sky: true - datetime_begin: !butler_time/tai/iso '2015-02-18 07:04:30.532568000' - datetime_end: !butler_time/tai/iso '2015-02-18 07:06:54.000000000' - - instrument: DECam - id: 419802 - day_obs: 20150308 - group: '419802' - physical_filter: g DECam SDSS c0001 4720.0 1520.0 - obs_id: ct4m20150309t055516 - exposure_time: 102.0 - dark_time: 103.1057501 - observation_type: science - observation_reason: science - seq_num: 419802 - seq_start: 419802 - seq_end: 419802 - target_name: Blind15A_40 - science_program: 2015A-0608 - tracking_ra: 155.12015152062799 - tracking_dec: -6.52007843674732 - sky_angle: 90.0 - azimuth: 304.7488 - zenith_angle: 36.15 - has_simulated: false - can_see_sky: true - datetime_begin: !butler_time/tai/iso '2015-03-09 05:55:51.522985000' - datetime_end: !butler_time/tai/iso '2015-03-09 05:58:23.000000000' - type: dimension element: patch records: diff --git a/preloaded/gen3.sqlite3 b/preloaded/gen3.sqlite3 index 59f7506..af5145d 100644 --- a/preloaded/gen3.sqlite3 +++ b/preloaded/gen3.sqlite3 @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:00a0291d867e8159df4efa28d3dd47ab6684d79572a95b469b08b064ed8653d9 +oid sha256:6843d78a5bf239ab102a75f310ec4356ea626fac521a15429083cf1be93705d4 size 5574656

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