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# This file is part of daf_butler. 

# 

# Developed for the LSST Data Management System. 

# This product includes software developed by the LSST Project 

# (http://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 <http://www.gnu.org/licenses/>. 

 

import os 

import unittest 

 

from lsst.daf.butler import (ButlerConfig, DatasetType, Registry, DataId, 

DatasetOriginInfoDef, StorageClass) 

from lsst.daf.butler.sql import DataIdQueryBuilder, SingleDatasetQueryBuilder 

from lsst.sphgeom import Angle, Box, LonLat, NormalizedAngle 

 

 

class QueryBuilderTestCase(unittest.TestCase): 

"""Tests for QueryBuilders. 

""" 

 

def setUp(self): 

self.testDir = os.path.dirname(__file__) 

self.configFile = os.path.join(self.testDir, "config/basic/butler.yaml") 

self.butlerConfig = ButlerConfig(self.configFile) 

self.registry = Registry.fromConfig(self.butlerConfig) 

 

def testDatasetOriginInfoDef(self): 

"""Test for DatasetOriginInfoDef class""" 

 

originInfo = DatasetOriginInfoDef(defaultInputs=["a", "b"], defaultOutput="out") 

self.assertEqual(originInfo.getInputCollections("ds"), ["a", "b"]) 

self.assertEqual(originInfo.getInputCollections("ds2"), ["a", "b"]) 

self.assertEqual(originInfo.getOutputCollection("ds"), "out") 

self.assertEqual(originInfo.getOutputCollection("ds2"), "out") 

 

originInfo = DatasetOriginInfoDef(defaultInputs=["a", "b"], defaultOutput="out", 

inputOverrides=dict(ds2=["c"]), 

outputOverrides=dict(ds2="out2")) 

self.assertEqual(originInfo.getInputCollections("ds"), ["a", "b"]) 

self.assertEqual(originInfo.getInputCollections("ds2"), ["c"]) 

self.assertEqual(originInfo.getOutputCollection("ds"), "out") 

self.assertEqual(originInfo.getOutputCollection("ds2"), "out2") 

 

def testInstrumentDimensions(self): 

"""Test involving only instrument dimensions, no joins to skymap""" 

registry = self.registry 

 

# need a bunch of dimensions and datasets for test 

registry.addDimensionEntry("instrument", dict(instrument="DummyCam", visit_max=25, exposure_max=300, 

detector_max=6)) 

registry.addDimensionEntry("physical_filter", dict(instrument="DummyCam", 

physical_filter="dummy_r", 

abstract_filter="r")) 

registry.addDimensionEntry("physical_filter", dict(instrument="DummyCam", 

physical_filter="dummy_i", 

abstract_filter="i")) 

for detector in (1, 2, 3, 4, 5): 

registry.addDimensionEntry("detector", dict(instrument="DummyCam", detector=detector)) 

registry.addDimensionEntry("visit", dict(instrument="DummyCam", visit=10, physical_filter="dummy_i")) 

registry.addDimensionEntry("visit", dict(instrument="DummyCam", visit=11, physical_filter="dummy_r")) 

registry.addDimensionEntry("visit", dict(instrument="DummyCam", visit=20, physical_filter="dummy_r")) 

registry.addDimensionEntry("exposure", dict(instrument="DummyCam", exposure=100, visit=10, 

physical_filter="dummy_i")) 

registry.addDimensionEntry("exposure", dict(instrument="DummyCam", exposure=101, visit=10, 

physical_filter="dummy_i")) 

registry.addDimensionEntry("exposure", dict(instrument="DummyCam", exposure=110, visit=11, 

physical_filter="dummy_r")) 

registry.addDimensionEntry("exposure", dict(instrument="DummyCam", exposure=111, visit=11, 

physical_filter="dummy_r")) 

registry.addDimensionEntry("exposure", dict(instrument="DummyCam", exposure=200, visit=20, 

physical_filter="dummy_r")) 

registry.addDimensionEntry("exposure", dict(instrument="DummyCam", exposure=201, visit=20, 

physical_filter="dummy_r")) 

 

# dataset types 

collection1 = "test" 

collection2 = "test2" 

run = registry.makeRun(collection=collection1) 

run2 = registry.makeRun(collection=collection2) 

storageClass = StorageClass("testDataset") 

registry.storageClasses.registerStorageClass(storageClass) 

rawType = DatasetType(name="RAW", 

dimensions=registry.dimensions.extract(("instrument", "exposure", "detector")), 

storageClass=storageClass) 

registry.registerDatasetType(rawType) 

calexpType = DatasetType(name="CALEXP", 

dimensions=registry.dimensions.extract(("instrument", "visit", "detector")), 

storageClass=storageClass) 

registry.registerDatasetType(calexpType) 

 

# add pre-existing datasets 

for exposure in (100, 101, 110, 111): 

for detector in (1, 2, 3): 

# note that only 3 of 5 detectors have datasets 

dataId = dict(instrument="DummyCam", exposure=exposure, detector=detector) 

ref = registry.addDataset(rawType, dataId=dataId, run=run) 

# exposures 100 and 101 appear in both collections, 100 has 

# different dataset_id in different collections, for 101 only 

# single dataset_id exists 

if exposure == 100: 

registry.addDataset(rawType, dataId=dataId, run=run2) 

if exposure == 101: 

registry.associate(run2.collection, [ref]) 

# Add pre-existing datasets to second collection. 

for exposure in (200, 201): 

for detector in (3, 4, 5): 

# note that only 3 of 5 detectors have datasets 

dataId = dict(instrument="DummyCam", exposure=exposure, detector=detector) 

registry.addDataset(rawType, dataId=dataId, run=run2) 

 

dimensions = registry.dimensions.empty.union(rawType.dimensions, calexpType.dimensions, 

implied=True) 

 

# with empty expression 

builder = DataIdQueryBuilder.fromDimensions(registry, dimensions) 

builder.requireDataset(rawType, collections=[collection1]) 

rows = list(builder.execute()) 

self.assertEqual(len(rows), 4*3) # 4 exposures times 3 detectors 

for dataId in rows: 

self.assertCountEqual(dataId.keys(), ("instrument", "detector", "exposure", "visit", 

"physical_filter", "abstract_filter")) 

packer1 = registry.makeDataIdPacker("visit_detector", dataId) 

packer2 = registry.makeDataIdPacker("exposure_detector", dataId) 

self.assertEqual(packer1.unpack(packer1.pack(dataId)), 

DataId(dataId, dimensions=packer1.dimensions.required)) 

self.assertEqual(packer2.unpack(packer2.pack(dataId)), 

DataId(dataId, dimensions=packer2.dimensions.required)) 

self.assertNotEqual(packer1.pack(dataId), packer2.pack(dataId)) 

self.assertCountEqual(set(dataId["exposure"] for dataId in rows), 

(100, 101, 110, 111)) 

self.assertCountEqual(set(dataId["visit"] for dataId in rows), (10, 11)) 

self.assertCountEqual(set(dataId["detector"] for dataId in rows), (1, 2, 3)) 

 

# second collection 

builder = DataIdQueryBuilder.fromDimensions(registry, dimensions) 

builder.requireDataset(rawType, collections=[collection2]) 

rows = list(builder.execute()) 

self.assertEqual(len(rows), 4*3) # 4 exposures times 3 detectors 

for dataId in rows: 

self.assertCountEqual(dataId.keys(), ("instrument", "detector", "exposure", "visit", 

"physical_filter", "abstract_filter")) 

self.assertCountEqual(set(dataId["exposure"] for dataId in rows), 

(100, 101, 200, 201)) 

self.assertCountEqual(set(dataId["visit"] for dataId in rows), (10, 20)) 

self.assertCountEqual(set(dataId["detector"] for dataId in rows), (1, 2, 3, 4, 5)) 

 

# with two input datasets 

builder = DataIdQueryBuilder.fromDimensions(registry, dimensions) 

builder.requireDataset(rawType, collections=[collection1, collection2]) 

rows = list(builder.execute()) 

self.assertEqual(len(set(rows)), 6*3) # 6 exposures times 3 detectors; set needed to de-dupe 

for dataId in rows: 

self.assertCountEqual(dataId.keys(), ("instrument", "detector", "exposure", "visit", 

"physical_filter", "abstract_filter")) 

self.assertCountEqual(set(dataId["exposure"] for dataId in rows), 

(100, 101, 110, 111, 200, 201)) 

self.assertCountEqual(set(dataId["visit"] for dataId in rows), (10, 11, 20)) 

self.assertCountEqual(set(dataId["detector"] for dataId in rows), (1, 2, 3, 4, 5)) 

 

# limit to single visit 

builder = DataIdQueryBuilder.fromDimensions(registry, dimensions) 

builder.requireDataset(rawType, collections=[collection1]) 

builder.whereParsedExpression("visit.visit = 10") 

rows = list(builder.execute()) 

self.assertEqual(len(rows), 2*3) # 2 exposures times 3 detectors 

self.assertCountEqual(set(dataId["exposure"] for dataId in rows), (100, 101)) 

self.assertCountEqual(set(dataId["visit"] for dataId in rows), (10,)) 

self.assertCountEqual(set(dataId["detector"] for dataId in rows), (1, 2, 3)) 

 

# more limiting expression, using link names instead of Table.column 

builder = DataIdQueryBuilder.fromDimensions(registry, dimensions) 

builder.requireDataset(rawType, collections=[collection1]) 

builder.whereParsedExpression("visit = 10 and detector > 1") 

rows = list(builder.execute()) 

self.assertEqual(len(rows), 2*2) # 2 exposures times 2 detectors 

self.assertCountEqual(set(dataId["exposure"] for dataId in rows), (100, 101)) 

self.assertCountEqual(set(dataId["visit"] for dataId in rows), (10,)) 

self.assertCountEqual(set(dataId["detector"] for dataId in rows), (2, 3)) 

 

# expression excludes everything 

builder = DataIdQueryBuilder.fromDimensions(registry, dimensions) 

builder.requireDataset(rawType, collections=[collection1]) 

builder.whereParsedExpression("visit.visit > 1000") 

rows = list(builder.execute()) 

self.assertEqual(len(rows), 0) 

 

# Selecting by physical_filter, this is not in the dimensions, but it 

# is a part of the full expression so it should work too. 

builder = DataIdQueryBuilder.fromDimensions(registry, dimensions) 

builder.requireDataset(rawType, collections=[collection1]) 

builder.whereParsedExpression("physical_filter = 'dummy_r'") 

rows = list(builder.execute()) 

self.assertEqual(len(rows), 2*3) # 2 exposures times 3 detectors 

self.assertCountEqual(set(dataId["exposure"] for dataId in rows), (110, 111)) 

self.assertCountEqual(set(dataId["visit"] for dataId in rows), (11,)) 

self.assertCountEqual(set(dataId["detector"] for dataId in rows), (1, 2, 3)) 

 

def testSkyMapDimensions(self): 

"""Test involving only skymap dimensions, no joins to instrument""" 

registry = self.registry 

 

# need a bunch of dimensions and datasets for test, we want 

# "abstract_filter" in the test so also have to add physical_filter 

# dimensions 

registry.addDimensionEntry("instrument", dict(instrument="DummyCam")) 

registry.addDimensionEntry("physical_filter", dict(instrument="DummyCam", 

physical_filter="dummy_r", 

abstract_filter="r")) 

registry.addDimensionEntry("physical_filter", dict(instrument="DummyCam", 

physical_filter="dummy_i", 

abstract_filter="i")) 

registry.addDimensionEntry("skymap", dict(skymap="DummyMap", hash="sha!".encode("utf8"))) 

for tract in range(10): 

registry.addDimensionEntry("tract", dict(skymap="DummyMap", tract=tract)) 

for patch in range(10): 

registry.addDimensionEntry("patch", dict(skymap="DummyMap", tract=tract, patch=patch, 

cell_x=0, cell_y=0, 

region=Box(LonLat(NormalizedAngle(0.), Angle(0.))))) 

 

# dataset types 

collection = "test" 

run = registry.makeRun(collection=collection) 

storageClass = StorageClass("testDataset") 

registry.storageClasses.registerStorageClass(storageClass) 

calexpType = DatasetType(name="deepCoadd_calexp", 

dimensions=registry.dimensions.extract(("skymap", "tract", "patch", 

"abstract_filter")), 

storageClass=storageClass) 

registry.registerDatasetType(calexpType) 

mergeType = DatasetType(name="deepCoadd_mergeDet", 

dimensions=registry.dimensions.extract(("skymap", "tract", "patch")), 

storageClass=storageClass) 

registry.registerDatasetType(mergeType) 

measType = DatasetType(name="deepCoadd_meas", 

dimensions=registry.dimensions.extract(("skymap", "tract", "patch", 

"abstract_filter")), 

storageClass=storageClass) 

registry.registerDatasetType(measType) 

 

dimensions = registry.dimensions.empty.union(calexpType.dimensions, mergeType.dimensions, 

measType.dimensions, implied=True) 

 

# add pre-existing datasets 

for tract in (1, 3, 5): 

for patch in (2, 4, 6, 7): 

dataId = dict(skymap="DummyMap", tract=tract, patch=patch) 

registry.addDataset(mergeType, dataId=dataId, run=run) 

for aFilter in ("i", "r"): 

dataId = dict(skymap="DummyMap", tract=tract, patch=patch, abstract_filter=aFilter) 

registry.addDataset(calexpType, dataId=dataId, run=run) 

 

# with empty expression 

builder = DataIdQueryBuilder.fromDimensions(registry, dimensions) 

builder.requireDataset(calexpType, collections=[collection]) 

builder.requireDataset(mergeType, collections=[collection]) 

rows = list(builder.execute()) 

self.assertEqual(len(rows), 3*4*2) # 4 tracts x 4 patches x 2 filters 

for dataId in rows: 

self.assertCountEqual(dataId.keys(), ("skymap", "tract", "patch", "abstract_filter")) 

self.assertCountEqual(set(dataId["tract"] for dataId in rows), (1, 3, 5)) 

self.assertCountEqual(set(dataId["patch"] for dataId in rows), (2, 4, 6, 7)) 

self.assertCountEqual(set(dataId["abstract_filter"] for dataId in rows), ("i", "r")) 

 

# limit to 2 tracts and 2 patches 

builder = DataIdQueryBuilder.fromDimensions(registry, dimensions) 

builder.requireDataset(calexpType, collections=[collection]) 

builder.requireDataset(mergeType, collections=[collection]) 

builder.whereParsedExpression("tract IN (1, 5) AND patch.patch IN (2, 7)") 

rows = list(builder.execute()) 

self.assertEqual(len(rows), 2*2*2) # 4 tracts x 4 patches x 2 filters 

self.assertCountEqual(set(dataId["tract"] for dataId in rows), (1, 5)) 

self.assertCountEqual(set(dataId["patch"] for dataId in rows), (2, 7)) 

self.assertCountEqual(set(dataId["abstract_filter"] for dataId in rows), ("i", "r")) 

 

# limit to single filter 

builder = DataIdQueryBuilder.fromDimensions(registry, dimensions) 

builder.requireDataset(calexpType, collections=[collection]) 

builder.requireDataset(mergeType, collections=[collection]) 

builder.whereParsedExpression("abstract_filter = 'i'") 

rows = list(builder.execute()) 

self.assertEqual(len(rows), 3*4*1) # 4 tracts x 4 patches x 2 filters 

self.assertCountEqual(set(dataId["tract"] for dataId in rows), (1, 3, 5)) 

self.assertCountEqual(set(dataId["patch"] for dataId in rows), (2, 4, 6, 7)) 

self.assertCountEqual(set(dataId["abstract_filter"] for dataId in rows), ("i",)) 

 

# expression excludes everything, specifying non-existing skymap is 

# not a fatal error, it's operator error 

builder = DataIdQueryBuilder.fromDimensions(registry, dimensions) 

builder.requireDataset(calexpType, collections=[collection]) 

builder.requireDataset(mergeType, collections=[collection]) 

builder.whereParsedExpression("skymap = 'Mars'") 

rows = list(builder.execute()) 

self.assertEqual(len(rows), 0) 

 

def testSpatialMatch(self): 

"""Test involving spatial match using join tables. 

 

Note that realistic test needs a resonably-defined skypix and regions 

in registry tables which is hard to implement in this simple test. 

So we do not actually fill registry with any data and all queries will 

return empty result, but this is still useful for coverage of the code 

that generates query. 

""" 

registry = self.registry 

 

# dataset types 

collection = "test" 

registry.makeRun(collection=collection) 

storageClass = StorageClass("testDataset") 

registry.storageClasses.registerStorageClass(storageClass) 

 

calexpType = DatasetType(name="CALEXP", 

dimensions=registry.dimensions.extract(("instrument", "visit", "detector")), 

storageClass=storageClass) 

registry.registerDatasetType(calexpType) 

 

coaddType = DatasetType(name="deepCoadd_calexp", 

dimensions=registry.dimensions.extract(("skymap", "tract", "patch", 

"abstract_filter")), 

storageClass=storageClass) 

registry.registerDatasetType(coaddType) 

 

dimensions = registry.dimensions.empty.union(calexpType.dimensions, coaddType.dimensions) 

 

# without data this should run OK but return empty set 

builder = DataIdQueryBuilder.fromDimensions(registry, dimensions) 

builder.requireDataset(calexpType, collections=[collection]) 

 

rows = list(builder.execute()) 

self.assertEqual(len(rows), 0) 

 

def testCalibrationLabelIndirection(self): 

"""Test that SingleDatasetQueryBuilder can look up datasets with 

calibration_label dimensions from a data ID with exposure dimensions. 

""" 

# exposure <-> calibration_label lookups for master calibrations 

flat = DatasetType( 

"flat", 

self.registry.dimensions.extract( 

["instrument", "detector", "physical_filter", "calibration_label"] 

), 

"ImageU" 

) 

builder = SingleDatasetQueryBuilder.fromSingleCollection(self.registry, flat, collection="calib") 

newLinks = builder.relateDimensions( 

self.registry.dimensions.extract(["instrument", "exposure", "detector"], implied=True) 

) 

self.assertEqual(newLinks, set(["exposure"])) 

self.assertIsNotNone(builder.findSelectableByName("exposure_calibration_label_join")) 

usedLinks = builder.whereDataId(DataId(instrument="HSC", exposure=12, detector=34, 

physical_filter="HSC-R2", abstract_filter="r", 

universe=self.registry.dimensions)) 

self.assertEqual(usedLinks, set(["instrument", "exposure", "detector", "physical_filter"])) 

 

def testSkyPixIndirection(self): 

"""Test that SingleDatasetQueryBuilder can look up datasets with 

skypix dimensions from a data ID with visit+detector dimensions. 

""" 

# exposure <-> calibration_label lookups for master calibrations 

refcat = DatasetType( 

"refcat", 

self.registry.dimensions.extract(["skypix"]), 

"ImageU" 

) 

builder = SingleDatasetQueryBuilder.fromSingleCollection(self.registry, refcat, collection="refcats") 

newLinks = builder.relateDimensions( 

self.registry.dimensions.extract(["instrument", "visit", "detector"], implied=True) 

) 

self.assertEqual(newLinks, set(["instrument", "visit", "detector"])) 

self.assertIsNotNone(builder.findSelectableByName("visit_detector_skypix_join")) 

usedLinks = builder.whereDataId(DataId(instrument="HSC", visit=12, detector=34, 

physical_filter="HSC-R2", abstract_filter="r", 

universe=self.registry.dimensions)) 

self.assertEqual(usedLinks, set(["instrument", "visit", "detector"])) 

 

 

391 ↛ 392line 391 didn't jump to line 392, because the condition on line 391 was never trueif __name__ == "__main__": 

unittest.main()