Coverage for python/lsst/ap/association/diaForcedSource.py: 33%
71 statements
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1# This file is part of ap_association.
2#
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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
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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.
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22"""Methods for force photometering direct and difference images at DiaObject
23locations.
24"""
26__all__ = ["DiaForcedSourceTask", "DiaForcedSourcedConfig"]
28import numpy as np
30import lsst.afw.table as afwTable
31from lsst.daf.base import DateTime
32import lsst.geom as geom
33from lsst.meas.base import ForcedMeasurementTask
34import lsst.pex.config as pexConfig
35import lsst.pipe.base as pipeBase
36from lsst.utils.timer import timeMethod
39class DiaForcedSourcedConfig(pexConfig.Config):
40 """Configuration for the generic DiaForcedSourcedTask class.
41 """
42 forcedMeasurement = pexConfig.ConfigurableField(
43 target=ForcedMeasurementTask,
44 doc="Subtask to force photometer DiaObjects in the direct and "
45 "difference images.",
46 )
47 dropColumns = pexConfig.ListField(
48 dtype=str,
49 doc="Columns produced in forced measurement that can be dropped upon "
50 "creation and storage of the final pandas data.",
51 )
53 def setDefaults(self):
54 self.forcedMeasurement.plugins = ["base_TransformedCentroidFromCoord",
55 "base_PsfFlux"]
56 self.forcedMeasurement.doReplaceWithNoise = False
57 self.forcedMeasurement.copyColumns = {
58 "id": "diaObjectId",
59 "coord_ra": "coord_ra",
60 "coord_dec": "coord_dec"}
61 self.forcedMeasurement.slots.centroid = "base_TransformedCentroidFromCoord"
62 self.forcedMeasurement.slots.psfFlux = "base_PsfFlux"
63 self.forcedMeasurement.slots.shape = None
64 self.dropColumns = ['coord_ra', 'coord_dec', 'parent',
65 'base_TransformedCentroidFromCoord_x',
66 'base_TransformedCentroidFromCoord_y',
67 'base_PsfFlux_instFlux',
68 'base_PsfFlux_instFluxErr', 'base_PsfFlux_area',
69 'slot_PsfFlux_area', 'base_PsfFlux_flag',
70 'slot_PsfFlux_flag',
71 'base_PsfFlux_flag_noGoodPixels',
72 'slot_PsfFlux_flag_noGoodPixels',
73 'base_PsfFlux_flag_edge', 'slot_PsfFlux_flag_edge',
74 'base_PsfFlux_chi2', 'slot_PsfFlux_chi2',
75 'base_PsfFlux_npixels', 'slot_PsfFlux_npixels',
76 'base_InvalidPsf_flag',
77 ]
80class DiaForcedSourceTask(pipeBase.Task):
81 """Task for measuring and storing forced sources at DiaObject locations
82 in both difference and direct images.
83 """
84 ConfigClass = DiaForcedSourcedConfig
85 _DefaultName = "diaForcedSource"
87 def __init__(self, **kwargs):
88 pipeBase.Task.__init__(self, **kwargs)
89 self.makeSubtask("forcedMeasurement",
90 refSchema=afwTable.SourceTable.makeMinimalSchema())
92 @timeMethod
93 def run(self,
94 dia_objects,
95 updatedDiaObjectIds,
96 exposure,
97 diffim,
98 idGenerator):
99 """Measure forced sources on the direct and difference images.
101 Parameters
102 ----------
103 dia_objects : `pandas.DataFrame`
104 Catalog of previously observed and newly created DiaObjects
105 contained within the difference and direct images. DiaObjects
106 must be indexed on the ``diaObjectId`` column.
107 updatedDiaObjectIds : `numpy.ndarray`
108 Array of diaObjectIds that were updated during this dia processing.
109 Used to assure that the pipeline includes all diaObjects that were
110 updated in case one falls on the edge of the CCD.
111 exposure : `lsst.afw.image.Exposure`
112 Direct image exposure.
113 diffim : `lsst.afw.image.Exposure`
114 Difference image.
115 idGenerator : `lsst.meas.base.IdGenerator`
116 Object that generates source IDs and random number generator seeds.
118 Returns
119 -------
120 output_forced_sources : `pandas.DataFrame`
121 Catalog of calibrated forced photometered fluxes on both the
122 difference and direct images at DiaObject locations.
123 """
125 afw_dia_objects = self._convert_from_pandas(dia_objects)
127 idFactoryDiff = idGenerator.make_table_id_factory()
129 diffForcedSources = self.forcedMeasurement.generateMeasCat(
130 diffim,
131 afw_dia_objects,
132 diffim.getWcs(),
133 idFactory=idFactoryDiff)
134 self.forcedMeasurement.run(
135 diffForcedSources, diffim, afw_dia_objects, diffim.getWcs())
137 directForcedSources = self.forcedMeasurement.generateMeasCat(
138 exposure,
139 afw_dia_objects,
140 exposure.getWcs(),
141 idFactory=idFactoryDiff)
142 self.forcedMeasurement.run(
143 directForcedSources, exposure, afw_dia_objects, exposure.getWcs())
145 output_forced_sources = self._calibrate_and_merge(diffForcedSources,
146 directForcedSources,
147 diffim,
148 exposure)
150 output_forced_sources = self._trim_to_exposure(output_forced_sources,
151 updatedDiaObjectIds,
152 exposure)
153 return output_forced_sources.set_index(
154 ["diaObjectId", "diaForcedSourceId"],
155 drop=False)
157 def _convert_from_pandas(self, input_objects):
158 """Create minimal schema SourceCatalog from a pandas DataFrame.
160 We need a catalog of this type to run within the forced measurement
161 subtask.
163 Parameters
164 ----------
165 input_objects : `pandas.DataFrame`
166 DiaObjects with locations and ids. ``
168 Returns
169 -------
170 outputCatalog : `lsst.afw.table.SourceTable`
171 Output catalog with minimal schema.
172 """
173 schema = afwTable.SourceTable.makeMinimalSchema()
175 outputCatalog = afwTable.SourceCatalog(schema)
176 outputCatalog.reserve(len(input_objects))
178 for obj_id, df_row in input_objects.iterrows():
179 outputRecord = outputCatalog.addNew()
180 outputRecord.setId(obj_id)
181 outputRecord.setCoord(
182 geom.SpherePoint(df_row["ra"],
183 df_row["dec"],
184 geom.degrees))
185 return outputCatalog
187 def _calibrate_and_merge(self,
188 diff_sources,
189 direct_sources,
190 diff_exp,
191 direct_exp):
192 """Take the two output catalogs from the ForcedMeasurementTasks and
193 calibrate, combine, and convert them to Pandas.
195 Parameters
196 ----------
197 diff_sources : `lsst.afw.table.SourceTable`
198 Catalog with PsFluxes measured on the difference image.
199 direct_sources : `lsst.afw.table.SourceTable`
200 Catalog with PsfFluxes measured on the direct (calexp) image.
201 diff_exp : `lsst.afw.image.Exposure`
202 Difference exposure ``diff_sources`` were measured on.
203 direct_exp : `lsst.afw.image.Exposure`
204 Direct (calexp) exposure ``direct_sources`` were measured on.
206 Returns
207 -------
208 output_catalog : `pandas.DataFrame`
209 Catalog calibrated diaForcedSources.
210 """
211 diff_calib = diff_exp.getPhotoCalib()
212 direct_calib = direct_exp.getPhotoCalib()
214 diff_fluxes = diff_calib.instFluxToNanojansky(diff_sources,
215 "slot_PsfFlux")
216 direct_fluxes = direct_calib.instFluxToNanojansky(direct_sources,
217 "slot_PsfFlux")
219 output_catalog = diff_sources.asAstropy().to_pandas()
220 output_catalog.rename(columns={"id": "diaForcedSourceId",
221 "slot_PsfFlux_instFlux": "psfFlux",
222 "slot_PsfFlux_instFluxErr": "psfFluxErr",
223 "slot_Centroid_x": "x",
224 "slot_Centroid_y": "y"},
225 inplace=True)
226 output_catalog.loc[:, "psfFlux"] = diff_fluxes[:, 0]
227 output_catalog.loc[:, "psfFluxErr"] = diff_fluxes[:, 1]
229 output_catalog["scienceFlux"] = direct_fluxes[:, 0]
230 output_catalog["scienceFluxErr"] = direct_fluxes[:, 1]
232 midpointMjdTai = direct_exp.visitInfo.date.get(system=DateTime.MJD)
233 output_catalog["visit"] = direct_exp.visitInfo.id
234 output_catalog["detector"] = direct_exp.detector.getId()
235 output_catalog["midpointMjdTai"] = midpointMjdTai
236 output_catalog["band"] = diff_exp.getFilter().bandLabel
237 output_catalog["time_processed"] = DateTime.now().toPython()
238 # TODO: propagate actual flags (DM-42355)
240 # Drop superfluous columns from output DataFrame.
241 output_catalog.drop(columns=self.config.dropColumns, inplace=True)
243 return output_catalog
245 def _trim_to_exposure(self, catalog, updatedDiaObjectIds, exposure):
246 """Remove DiaForcedSources that are outside of the bounding box region.
248 Paramters
249 ---------
250 catalog : `pandas.DataFrame`
251 DiaForcedSources to check against the exposure bounding box.
252 updatedDiaObjectIds : `numpy.ndarray`
253 Array of diaObjectIds that were updated during this dia processing.
254 Used to assure that the pipeline includes all diaObjects that were
255 updated in case one falls on the edge of the CCD.
256 exposure : `lsst.afw.image.Exposure`
257 Exposure to check against.
259 Returns
260 -------
261 output : `pandas.DataFrame`
262 DataFrame trimmed to only the objects within the exposure bounding
263 box.
264 """
265 bbox = geom.Box2D(exposure.getBBox())
267 xS = catalog.loc[:, "x"]
268 yS = catalog.loc[:, "y"]
270 return catalog[
271 np.logical_or(bbox.contains(xS, yS),
272 np.isin(catalog.loc[:, "diaObjectId"],
273 updatedDiaObjectIds))]