Coverage for python/lsst/ap/association/mapApData.py : 23%

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1#
2# Developed for the LSST Data Management System.
3# This product includes software developed by the LSST Project
4# (http://www.lsst.org).
5# See the COPYRIGHT file at the top-level directory of this distribution
6# for details of code ownership.
7#
8# This program is free software: you can redistribute it and/or modify
9# it under the terms of the GNU General Public License as published by
10# the Free Software Foundation, either version 3 of the License, or
11# (at your option) any later version.
12#
13# This program is distributed in the hope that it will be useful,
14# but WITHOUT ANY WARRANTY; without even the implied warranty of
15# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
16# GNU General Public License for more details.
17#
18# You should have received a copy of the GNU General Public License
19# along with this program. If not, see <http://www.gnu.org/licenses/>.
20#
22"""Classes for taking science pipeline outputs and creating data products for
23use in ap_association and the alert production database (APDB).
24"""
26__all__ = ["MapApDataConfig", "MapApDataTask",
27 "MapDiaSourceConfig", "MapDiaSourceTask",
28 "UnpackApdbFlags"]
30import numpy as np
31import os
32import yaml
34import lsst.afw.table as afwTable
35from lsst.daf.base import DateTime
36import lsst.pipe.base as pipeBase
37import lsst.pex.config as pexConfig
38from lsst.pex.exceptions import RuntimeError
39from lsst.utils import getPackageDir
40from .afwUtils import make_dia_source_schema
43class MapApDataConfig(pexConfig.Config):
44 """Configuration for the generic MapApDataTask class.
45 """
46 copyColumns = pexConfig.DictField(
47 keytype=str,
48 itemtype=str,
49 doc="Mapping of input SciencePipelines columns to output DPDD "
50 "columns.",
51 default={"id": "id",
52 "parent": "parent",
53 "coord_ra": "coord_ra",
54 "coord_dec": "coord_dec"}
55 )
58class MapApDataTask(pipeBase.Task):
59 """Generic mapper class for copying values from a science pipelines catalog
60 into a product for use in ap_association or the APDB.
61 """
62 ConfigClass = MapApDataConfig
63 _DefaultName = "mapApDataTask"
65 def __init__(self, inputSchema, outputSchema, **kwargs):
66 pipeBase.Task.__init__(self, **kwargs)
67 self.inputSchema = inputSchema
68 self.outputSchema = outputSchema
70 self.mapper = afwTable.SchemaMapper(inputSchema, outputSchema)
72 for inputName, outputName in self.config.copyColumns.items():
73 self.mapper.addMapping(
74 self.inputSchema.find(inputName).key,
75 outputName,
76 True)
78 def run(self, inputCatalog, exposure=None):
79 """Copy data from the inputCatalog into an output catalog with
80 requested columns.
82 Parameters
83 ----------
84 inputCatalog: `lsst.afw.table.SourceCatalog`
85 Input catalog with data to be copied into new output catalog.
87 Returns
88 -------
89 outputCatalog: `lsst.afw.table.SourceCatalog`
90 Output catalog with data copied from input and new column names.
91 """
92 outputCatalog = afwTable.SourceCatalog(self.outputSchema)
93 outputCatalog.extend(inputCatalog, self.mapper)
95 if not outputCatalog.isContiguous():
96 raise RuntimeError("Output catalogs must be contiguous.")
98 return outputCatalog
101class MapDiaSourceConfig(pexConfig.Config):
102 """Config for the DiaSourceMapperTask
103 """
104 copyColumns = pexConfig.DictField(
105 keytype=str,
106 itemtype=str,
107 doc="Mapping of input SciencePipelines columns to output DPDD "
108 "columns.",
109 default={"id": "id",
110 "parent": "parent",
111 "coord_ra": "coord_ra",
112 "coord_dec": "coord_dec",
113 "slot_Centroid_x": "x",
114 "slot_Centroid_xErr": "xErr",
115 "slot_Centroid_y": "y",
116 "slot_Centroid_yErr": "yErr",
117 "slot_ApFlux_instFlux": "apFlux",
118 "slot_ApFlux_instFluxErr": "apFluxErr",
119 "slot_PsfFlux_instFlux": "psFlux",
120 "slot_PsfFlux_instFluxErr": "psFluxErr",
121 "ip_diffim_DipoleFit_orientation": "dipAngle",
122 "ip_diffim_DipoleFit_chi2dof": "dipChi2",
123 "ip_diffim_forced_PsfFlux_instFlux": "totFlux",
124 "ip_diffim_forced_PsfFlux_instFluxErr": "totFluxErr",
125 "ip_diffim_DipoleFit_flag_classification": "isDipole",
126 "slot_Shape_xx": "ixx",
127 "slot_Shape_xxErr": "ixxErr",
128 "slot_Shape_yy": "iyy",
129 "slot_Shape_yyErr": "iyyErr",
130 "slot_Shape_xy": "ixy",
131 "slot_Shape_xyErr": "ixyErr",
132 "slot_PsfShape_xx": "ixxPSF",
133 "slot_PsfShape_yy": "iyyPSF",
134 "slot_PsfShape_xy": "ixyPSF"}
135 )
136 calibrateColumns = pexConfig.ListField(
137 dtype=str,
138 doc="Flux columns in the input catalog to calibrate.",
139 default=["slot_ApFlux", "slot_PsfFlux", "ip_diffim_forced_PsfFlux"]
140 )
141 flagMap = pexConfig.Field(
142 dtype=str,
143 doc="Yaml file specifying SciencePipelines flag fields to bit packs.",
144 default=os.path.join(getPackageDir("ap_association"),
145 "data",
146 "association-flag-map.yaml"),
147 )
148 dipFluxPrefix = pexConfig.Field(
149 dtype=str,
150 doc="Prefix of the Dipole measurement column containing negative and "
151 "positive flux lobes.",
152 default="ip_diffim_DipoleFit",
153 )
154 dipSepColumn = pexConfig.Field(
155 dtype=str,
156 doc="Column of the separation of the negative and positive poles of "
157 "the dipole.",
158 default="ip_diffim_DipoleFit_separation"
159 )
162class MapDiaSourceTask(MapApDataTask):
163 """Task specific for copying columns from science pipelines catalogs,
164 calibrating them, for use in ap_association and the APDB.
166 This task also copies information from the exposure such as the ExpsoureId
167 and the exposure date as specified in the DPDD.
168 """
170 ConfigClass = MapDiaSourceConfig
171 _DefaultName = "mapDiaSourceTask"
173 def __init__(self, inputSchema, **kwargs):
174 MapApDataTask.__init__(self,
175 inputSchema=inputSchema,
176 outputSchema=make_dia_source_schema(),
177 **kwargs)
178 self._create_bit_pack_mappings()
180 def _create_bit_pack_mappings(self):
181 """Setup all flag bit packings.
182 """
183 self.bit_pack_columns = []
184 with open(self.config.flagMap) as yaml_stream:
185 table_list = list(yaml.safe_load_all(yaml_stream))
186 for table in table_list:
187 if table['tableName'] == 'DiaSource':
188 self.bit_pack_columns = table['columns']
189 break
191 # Test that all flags requested are present in both the input and
192 # output schemas.
193 for outputFlag in self.bit_pack_columns:
194 try:
195 self.outputSchema.find(outputFlag['columnName'])
196 except KeyError:
197 raise KeyError(
198 "Requested column %s not found in MapDiaSourceTask output "
199 "schema. Please check that the requested output column "
200 "exists." % outputFlag['columnName'])
201 bitList = outputFlag['bitList']
202 for bit in bitList:
203 try:
204 self.inputSchema.find(bit['name'])
205 except KeyError:
206 raise KeyError(
207 "Requested column %s not found in MapDiaSourceTask input "
208 "schema. Please check that the requested input column "
209 "exists." % outputFlag['columnName'])
211 def run(self, inputCatalog, exposure, return_pandas=False):
212 """Copy data from the inputCatalog into an output catalog with
213 requested columns.
215 Parameters
216 ----------
217 inputCatalog : `lsst.afw.table.SourceCatalog`
218 Input catalog with data to be copied into new output catalog.
219 exposure: `lsst.afw.image.Exposure`
220 Exposure with containing the PhotoCalib object relevant to this
221 catalog.
222 return_pandas : `bool`
223 Return `pandas.DataFrame` instead of `lsst.afw.table.SourceCatalog`
225 Returns
226 -------
227 outputCatalog: `lsst.afw.table.SourceCatalog` or `pandas.DataFrame`
228 Output catalog with data copied from input and new column names.
229 """
230 visit_info = exposure.getInfo().getVisitInfo()
231 ccdVisitId = visit_info.getExposureId()
232 midPointTaiMJD = visit_info.getDate().get(system=DateTime.MJD)
233 filterId = exposure.getFilter().getId()
234 # canonical name should always be the abstract filter (in Gen 3 sense)
235 filterName = exposure.getFilter().getCanonicalName()
236 wcs = exposure.getWcs()
238 photoCalib = exposure.getPhotoCalib()
240 outputCatalog = afwTable.SourceCatalog(self.outputSchema)
241 outputCatalog.reserve(len(inputCatalog))
243 for inputRecord in inputCatalog:
244 outputRecord = outputCatalog.addNew()
245 outputRecord.assign(inputRecord, self.mapper)
246 self.calibrateFluxes(inputRecord, outputRecord, photoCalib)
247 self.computeDipoleFluxes(inputRecord, outputRecord, photoCalib)
248 self.computeDipoleSep(inputRecord, outputRecord, wcs)
249 self.bitPackFlags(inputRecord, outputRecord)
250 outputRecord.set("ccdVisitId", ccdVisitId)
251 outputRecord.set("midPointTai", midPointTaiMJD)
252 outputRecord.set("filterId", filterId)
253 outputRecord.set("filterName", filterName)
255 if not outputCatalog.isContiguous():
256 raise RuntimeError("Output catalogs must be contiguous.")
258 if return_pandas:
259 return self._convert_to_pandas(outputCatalog)
260 return outputCatalog
262 def calibrateFluxes(self, inputRecord, outputRecord, photoCalib):
263 """Copy flux values into an output record and calibrate them.
265 Parameters
266 ----------
267 inputRecord : `lsst.afw.table.SourceRecord`
268 Record to copy flux values from.
269 outputRecord : `lsst.afw.table.SourceRecord`
270 Record to copy and calibrate values into.
271 photoCalib : `lsst.afw.image.PhotoCalib`
272 Calibration object from the difference exposure.
273 """
274 for col_name in self.config.calibrateColumns:
275 meas = photoCalib.instFluxToNanojansky(inputRecord, col_name)
276 outputRecord.set(self.config.copyColumns[col_name + "_instFlux"],
277 meas.value)
278 outputRecord.set(
279 self.config.copyColumns[col_name + "_instFluxErr"],
280 meas.error)
282 def computeDipoleFluxes(self, inputRecord, outputRecord, photoCalib):
283 """Calibrate and compute dipole mean flux and diff flux.
285 Parameters
286 ----------
287 inputRecord : `lsst.afw.table.SourceRecord`
288 Record to copy flux values from.
289 outputRecord : `lsst.afw.table.SourceRecord`
290 Record to copy and calibrate values into.
291 photoCalib `lsst.afw.image.PhotoCalib`
292 Calibration object from the difference exposure.
293 """
295 neg_meas = photoCalib.instFluxToNanojansky(
296 inputRecord, self.config.dipFluxPrefix + "_neg")
297 pos_meas = photoCalib.instFluxToNanojansky(
298 inputRecord, self.config.dipFluxPrefix + "_pos")
299 outputRecord.set(
300 "dipMeanFlux",
301 0.5 * (np.abs(neg_meas.value) + np.abs(pos_meas.value)))
302 outputRecord.set(
303 "dipMeanFluxErr",
304 0.5 * np.sqrt(neg_meas.error ** 2 + pos_meas.error ** 2))
305 outputRecord.set(
306 "dipFluxDiff",
307 np.abs(pos_meas.value) - np.abs(neg_meas.value))
308 outputRecord.set(
309 "dipFluxDiffErr",
310 np.sqrt(neg_meas.error ** 2 + pos_meas.error ** 2))
312 def computeDipoleSep(self, inputRecord, outputRecord, wcs):
313 """Convert the dipole separation from pixels to arcseconds.
315 Parameters
316 ----------
317 inputRecord : `lsst.afw.table.SourceRecord`
318 Record to copy flux values from.
319 outputRecord : `lsst.afw.table.SourceRecord`
320 Record to copy and calibrate values into.
321 wcs : `lsst.afw.geom.SkyWcs`
322 Wcs of image inputRecords was observed.
323 """
324 pixScale = wcs.getPixelScale(inputRecord.getCentroid())
325 dipSep = pixScale * inputRecord.get(self.config.dipSepColumn)
326 outputRecord.set("dipLength", dipSep.asArcseconds())
328 def bitPackFlags(self, inputRecord, outputRecord):
329 """Pack requested flag columns in inputRecord into single columns in
330 outputRecord.
332 Parameters
333 ----------
334 inputRecord : `lsst.afw.table.SourceRecord`
335 Record to copy flux values from.
336 outputRecord : `lsst.afw.table.SourceRecord`
337 Record to copy and calibrate values into.
338 """
339 for outputFlag in self.bit_pack_columns:
340 bitList = outputFlag['bitList']
341 value = 0
342 for bit in bitList:
343 value += inputRecord[bit['name']] * 2 ** bit['bit']
344 outputRecord.set(outputFlag['columnName'], value)
346 def _convert_to_pandas(self, inputCatalog):
347 """Convert input afw table to pandas.
349 Using afwTable.toAstropy().to_pandas() alone is not sufficient to
350 properly store data in the Apdb. We must also convert the RA/DEC values
351 from radians to degrees and rename several columns.
353 Parameters
354 ----------
355 inputCatalog : `lsst.afw.table.SourceCatalog`
356 Catalog to convert to panads and rename columns.
358 Returns
359 -------
360 catalog : `pandas.DataFrame`
361 """
362 catalog = inputCatalog.asAstropy().to_pandas()
363 catalog.rename(columns={"coord_ra": "ra",
364 "coord_dec": "decl",
365 "id": "diaSourceId",
366 "parent": "parentDiaSourceId"},
367 inplace=True)
368 catalog["ra"] = np.degrees(catalog["ra"])
369 catalog["decl"] = np.degrees(catalog["decl"])
371 return catalog
374class UnpackApdbFlags:
375 """Class for unpacking bits from integer flag fields stored in the Apdb.
377 Attributes
378 ----------
379 flag_map_file : `str`
380 Absolute or relative path to a yaml file specifiying mappings of flags
381 to integer bits.
382 table_name : `str`
383 Name of the Apdb table the integer bit data are coming from.
384 """
386 def __init__(self, flag_map_file, table_name):
387 self.bit_pack_columns = []
388 with open(flag_map_file) as yaml_stream:
389 table_list = list(yaml.safe_load_all(yaml_stream))
390 for table in table_list:
391 if table['tableName'] == table_name:
392 self.bit_pack_columns = table['columns']
393 break
395 self.output_flag_columns = {}
397 for column in self.bit_pack_columns:
398 names = []
399 for bit in column["bitList"]:
400 names.append((bit["name"], np.bool))
401 self.output_flag_columns[column["columnName"]] = names
403 def unpack(self, input_flag_values, flag_name):
404 """Determine individual boolean flags from an input array of unsigned
405 ints.
407 Parameters
408 ----------
409 input_flag_values : array-like of type uint
410 Input integer flags to unpack.
411 flag_name : `str`
412 Apdb column name of integer flags to unpack. Names of packed int
413 flags are given by the flag_map_file.
415 Returns
416 -------
417 output_flags : `numpy.ndarray`
418 Numpy named tuple of booleans.
419 """
420 bit_names_types = self.output_flag_columns[flag_name]
421 output_flags = np.zeros(len(input_flag_values), dtype=bit_names_types)
423 for bit_idx, (bit_name, dtypes) in enumerate(bit_names_types):
424 masked_bits = np.bitwise_and(input_flag_values, 2 ** bit_idx)
425 output_flags[bit_name] = masked_bits
427 return output_flags