Coverage for python/lsst/analysis/tools/tasks/photometricCatalogMatch.py: 25%
88 statements
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« prev ^ index » next coverage.py v7.4.0, created at 2024-01-10 14:08 +0000
1# This file is part of analysis_tools.
2#
3# Developed for the LSST Data Management System.
4# This product includes software developed by the LSST Project
5# (https://www.lsst.org).
6# See the COPYRIGHT file at the top-level directory of this distribution
7# for details of code ownership.
8#
9# This program is free software: you can redistribute it and/or modify
10# it under the terms of the GNU General Public License as published by
11# the Free Software Foundation, either version 3 of the License, or
12# (at your option) any later version.
13#
14# This program is distributed in the hope that it will be useful,
15# but WITHOUT ANY WARRANTY; without even the implied warranty of
16# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
17# GNU General Public License for more details.
18#
19# You should have received a copy of the GNU General Public License
20# along with this program. If not, see <https://www.gnu.org/licenses/>.
22__all__ = ("PhotometricCatalogMatchConfig", "PhotometricCatalogMatchTask")
25import lsst.geom
26import lsst.pipe.base as pipeBase
27import numpy as np
28from astropy.table import Table
29from astropy.time import Time
30from lsst.pipe.tasks.loadReferenceCatalog import LoadReferenceCatalogTask
32from ..actions.vector import VisitPlotFlagSelector
33from ..tasks.catalogMatch import CatalogMatchConfig, CatalogMatchConnections, CatalogMatchTask
36class PhotometricCatalogMatchConnections(CatalogMatchConnections):
37 pass
40class PhotometricCatalogMatchConfig(
41 CatalogMatchConfig, pipelineConnections=PhotometricCatalogMatchConnections
42):
43 def setDefaults(self):
44 super().setDefaults()
45 self.referenceCatalogLoader.doReferenceSelection = False
46 self.referenceCatalogLoader.doApplyColorTerms = True
49class PhotometricCatalogMatchTask(CatalogMatchTask):
50 """A wrapper task to provide the information that
51 is specific to the photometric reference catalog.
52 """
54 ConfigClass = PhotometricCatalogMatchConfig
55 _DefaultName = "analysisToolsPhotometricCatalogMatch"
57 def runQuantum(self, butlerQC, inputRefs, outputRefs):
58 """Run the matching to the photometric reference catalog.
60 Parameters
61 ----------
62 butlerQC : `lsst.pipe.base.QuantumContext`
63 inputRefs : `lsst.pipe.base.InputQuantizedConnection`
64 outputRefs : `lsst.pipe.base.OutputQuantizedConnection`
65 """
67 inputs = butlerQC.get(inputRefs)
68 bands = []
69 for filterName in self.config.filterNames:
70 bands.append(self.config.referenceCatalogLoader.refObjLoader.filterMap[filterName])
72 # For some reason the imsim filterMaps don't work the same way as
73 # the HSC ones do, this is a bit hacky but fixes this
74 if "sim" in bands[0] or "smeared" in bands[0]:
75 bands = self.config.filterNames
77 columns = self.prepColumns(bands)
78 table = inputs["catalog"].get(parameters={"columns": columns})
80 tract = butlerQC.quantum.dataId["tract"]
82 loaderTask = LoadReferenceCatalogTask(
83 config=self.config.referenceCatalogLoader,
84 dataIds=[ref.dataId for ref in inputRefs.refCat],
85 name=inputs["refCat"][0].ref.datasetType.name,
86 refCats=inputs["refCat"],
87 )
89 skymap = inputs.pop("skymap")
90 loadedRefCat = self._loadRefCat(loaderTask, skymap[tract])
91 outputs = self.run(catalog=table, loadedRefCat=loadedRefCat, bands=bands)
93 butlerQC.put(outputs, outputRefs)
96class PhotometricCatalogMatchVisitConnections(
97 pipeBase.PipelineTaskConnections,
98 dimensions=("visit",),
99 defaultTemplates={"targetCatalog": "sourceTable_visit", "refCatalog": "ps1_pv3_3pi_20170110"},
100):
101 catalog = pipeBase.connectionTypes.Input(
102 doc="The visit-wide catalog to make plots from.",
103 storageClass="ArrowAstropy",
104 name="{targetCatalog}",
105 dimensions=("visit",),
106 deferLoad=True,
107 )
109 refCat = pipeBase.connectionTypes.PrerequisiteInput(
110 doc="The photometric reference catalog to match to.",
111 name="{refCatalog}",
112 storageClass="SimpleCatalog",
113 dimensions=("skypix",),
114 deferLoad=True,
115 multiple=True,
116 )
118 visitSummaryTable = pipeBase.connectionTypes.Input(
119 doc="A summary table of the ccds in the visit",
120 storageClass="ExposureCatalog",
121 name="visitSummary",
122 dimensions=("visit",),
123 )
125 matchedCatalog = pipeBase.connectionTypes.Output(
126 doc="Catalog with matched target and reference objects with separations",
127 name="{targetCatalog}_{refCatalog}_match",
128 storageClass="ArrowAstropy",
129 dimensions=("visit",),
130 )
133class PhotometricCatalogMatchVisitConfig(
134 PhotometricCatalogMatchConfig, pipelineConnections=PhotometricCatalogMatchVisitConnections
135):
136 def setDefaults(self):
137 self.filterNames = []
138 self.extraPerBandColumns = []
139 self.patchColumn = ""
140 self.selectorBands = []
141 self.selectorActions.flagSelector = VisitPlotFlagSelector
142 self.sourceSelectorActions.sourceSelector.vectorKey = "extendedness"
143 self.extraColumnSelectors.selector1.fluxType = "psfFlux"
144 self.extraColumnSelectors.selector2.vectorKey = "extendedness"
147class PhotometricCatalogMatchVisitTask(PhotometricCatalogMatchTask):
148 """A wrapper task to provide the information that
149 is specific to the photometric reference catalog.
150 """
152 ConfigClass = PhotometricCatalogMatchVisitConfig
153 _DefaultName = "analysisToolsPhotometricCatalogMatchVisit"
155 def runQuantum(self, butlerQC, inputRefs, outputRefs):
156 """Run the matching to the photometric reference catalog.
158 Parameters
159 ----------
160 butlerQC : `lsst.pipe.base.QuantumContext`
161 inputRefs : `lsst.pipe.base.InputQuantizedConnection`
162 outputRefs : `lsst.pipe.base.OutputQuantizedConnection`
163 """
165 inputs = butlerQC.get(inputRefs)
166 physicalFilter = inputs["catalog"].dataId["physical_filter"]
168 # For some reason the imsim filterMaps don't work the same way as
169 # the HSC ones do, this is a bit hacky but fixes this
170 if "sim" in physicalFilter:
171 physicalFilter = physicalFilter[0]
172 bands = [physicalFilter]
173 else:
174 bands = [self.config.referenceCatalogLoader.refObjLoader.filterMap[physicalFilter]]
175 # No bands needed for visit tables
176 # but we do need them later for the matching
177 columns = ["coord_ra", "coord_dec", "detector"] + self.config.extraColumns.list()
178 for selectorAction in [
179 self.config.selectorActions,
180 self.config.sourceSelectorActions,
181 self.config.extraColumnSelectors,
182 ]:
183 for selector in selectorAction:
184 selectorSchema = selector.getFormattedInputSchema()
185 columns += [s[0] for s in selectorSchema]
187 table = inputs["catalog"].get(parameters={"columns": columns})
189 loaderTask = LoadReferenceCatalogTask(
190 config=self.config.referenceCatalogLoader,
191 dataIds=[ref.dataId for ref in inputRefs.refCat],
192 name=inputs["refCat"][0].ref.datasetType.name,
193 refCats=inputs["refCat"],
194 )
196 visitSummaryTable = inputs.pop("visitSummaryTable")
197 loadedRefCat = self._loadRefCat(loaderTask, visitSummaryTable, physicalFilter)
198 outputs = self.run(catalog=table, loadedRefCat=loadedRefCat, bands=bands)
200 # The matcher adds the band to the front of the columns
201 # but the visit plots aren't expecting it
202 cols = list(outputs.matchedCatalog.columns)
203 for col in cols:
204 if col[:2] == bands[0] + "_":
205 outputs.matchedCatalog.rename_column(col, col[2:])
207 butlerQC.put(outputs, outputRefs)
209 def _loadRefCat(self, loaderTask, visitSummaryTable, physicalFilter):
210 """Make a reference catalog with coordinates in degrees
212 Parameters
213 ----------
214 visitSummaryTable : `lsst.afw.table.ExposureCatalog`
215 The table of visit information
216 """
217 # Get convex hull around the detectors, then get its center and radius
218 corners = []
219 for visSum in visitSummaryTable:
220 for ra, dec in zip(visSum["raCorners"], visSum["decCorners"]):
221 # If the coordinates are nan then don't keep going
222 # because it crashes later
223 if not np.isfinite(ra) or not np.isfinite(dec):
224 raise pipeBase.NoWorkFound("Visit summary corners not finite")
225 corners.append(lsst.geom.SpherePoint(ra, dec, units=lsst.geom.degrees).getVector())
226 visitBoundingCircle = lsst.sphgeom.ConvexPolygon.convexHull(corners).getBoundingCircle()
227 center = lsst.geom.SpherePoint(visitBoundingCircle.getCenter())
228 radius = visitBoundingCircle.getOpeningAngle()
230 # Get the observation date of the visit
231 obsDate = visSum.getVisitInfo().getDate()
232 epoch = Time(obsDate.toPython())
234 # Load the reference catalog in the skyCircle of the detectors, then
235 # convert the coordinates to degrees and convert the catalog to a
236 # dataframe
238 loadedRefCat = loaderTask.getSkyCircleCatalog(center, radius, [physicalFilter], epoch=epoch)
240 return Table(loadedRefCat)