Coverage for python/lsst/analysis/tools/tasks/associatedSourcesTractAnalysis.py: 46%
59 statements
« prev ^ index » next coverage.py v7.4.4, created at 2024-04-13 11:45 +0000
« prev ^ index » next coverage.py v7.4.4, created at 2024-04-13 11:45 +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/>.
21from __future__ import annotations
23__all__ = ("AssociatedSourcesTractAnalysisConfig", "AssociatedSourcesTractAnalysisTask")
25import numpy as np
26from astropy.table import join, vstack
27from lsst.geom import Box2D
28from lsst.pipe.base import NoWorkFound
29from lsst.pipe.base import connectionTypes as ct
30from lsst.skymap import BaseSkyMap
32from ..interfaces import AnalysisBaseConfig, AnalysisBaseConnections, AnalysisPipelineTask
35class AssociatedSourcesTractAnalysisConnections(
36 AnalysisBaseConnections,
37 dimensions=("skymap", "tract", "instrument"),
38 defaultTemplates={
39 "outputName": "isolated_star_sources",
40 "associatedSourcesInputName": "isolated_star_sources",
41 },
42):
43 sourceCatalogs = ct.Input(
44 doc="Visit based source table to load from the butler",
45 name="sourceTable_visit",
46 storageClass="ArrowAstropy",
47 deferLoad=True,
48 dimensions=("visit", "band"),
49 multiple=True,
50 )
52 associatedSources = ct.Input(
53 doc="Table of associated sources",
54 name="{associatedSourcesInputName}",
55 storageClass="ArrowAstropy",
56 deferLoad=True,
57 dimensions=("instrument", "skymap", "tract"),
58 )
60 skyMap = ct.Input(
61 doc="Input definition of geometry/bbox and projection/wcs for warped exposures",
62 name=BaseSkyMap.SKYMAP_DATASET_TYPE_NAME,
63 storageClass="SkyMap",
64 dimensions=("skymap",),
65 )
66 camera = ct.PrerequisiteInput(
67 doc="Input camera to use for focal plane geometry.",
68 name="camera",
69 storageClass="Camera",
70 dimensions=("instrument",),
71 isCalibration=True,
72 )
75class AssociatedSourcesTractAnalysisConfig(
76 AnalysisBaseConfig, pipelineConnections=AssociatedSourcesTractAnalysisConnections
77):
78 def setDefaults(self):
79 super().setDefaults()
82class AssociatedSourcesTractAnalysisTask(AnalysisPipelineTask):
83 ConfigClass = AssociatedSourcesTractAnalysisConfig
84 _DefaultName = "associatedSourcesTractAnalysis"
86 @staticmethod
87 def getBoxWcs(skymap, tract):
88 """Get box that defines tract boundaries."""
89 tractInfo = skymap.generateTract(tract)
90 wcs = tractInfo.getWcs()
91 tractBox = tractInfo.getBBox()
92 return tractBox, wcs
94 @classmethod
95 def callback(cls, inputs, dataId):
96 """Callback function to be used with reconstructor."""
97 return cls.prepareAssociatedSources(
98 inputs["skyMap"],
99 dataId["tract"],
100 inputs["sourceCatalogs"],
101 inputs["associatedSources"],
102 )
104 @classmethod
105 def prepareAssociatedSources(cls, skymap, tract, sourceCatalogs, associatedSources):
106 """Concatenate source catalogs and join on associated object index."""
108 # Keep only sources with associations
109 sourceCatalogStack = vstack(sourceCatalogs)
110 dataJoined = join(sourceCatalogStack, associatedSources, keys="sourceId", join_type="inner")
112 # Determine which sources are contained in tract
113 ra = np.radians(dataJoined["coord_ra"])
114 dec = np.radians(dataJoined["coord_dec"])
115 box, wcs = cls.getBoxWcs(skymap, tract)
116 box = Box2D(box)
117 x, y = wcs.skyToPixelArray(ra, dec)
118 boxSelection = box.contains(x, y)
120 # Keep only the sources in groups that are fully contained within the
121 # tract
122 dataFiltered = dataJoined[boxSelection]
124 return dataFiltered
126 def runQuantum(self, butlerQC, inputRefs, outputRefs):
127 inputs = butlerQC.get(inputRefs)
129 # Load specified columns from source catalogs
130 names = self.collectInputNames()
131 names |= {"sourceId", "coord_ra", "coord_dec"}
132 names.remove("obj_index")
133 sourceCatalogs = []
134 for handle in inputs["sourceCatalogs"]:
135 sourceCatalogs.append(self.loadData(handle, names))
136 inputs["sourceCatalogs"] = sourceCatalogs
138 dataId = butlerQC.quantum.dataId
139 plotInfo = self.parsePlotInfo(inputs, dataId, connectionName="associatedSources")
141 # TODO: make key used for object index configurable
142 inputs["associatedSources"] = self.loadData(inputs["associatedSources"], ["obj_index", "sourceId"])
144 if len(inputs["associatedSources"]) == 0:
145 raise NoWorkFound(f"No associated sources in tract {dataId.tract.id}")
147 data = self.callback(inputs, dataId)
149 kwargs = {"data": data, "plotInfo": plotInfo, "skymap": inputs["skyMap"], "camera": inputs["camera"]}
150 outputs = self.run(**kwargs)
151 butlerQC.put(outputs, outputRefs)