Make trailedAssociatorTask

Make trailedAssociatorTask which filters out trails whose lengths are above 0.416 arcseconds/second in length.
Updated unit test and added test_trailedSourceFilter.py. Refactored doLongTrailFilter to doTrailedSourceFilter. 


Update comments

python/lsst/ap/association/__init__.py

@@ -20,6 +20,7 @@
 # along with this program. If not, see <https://www.gnu.org/licenses/>.
 
 from .version import *
+from .trailedSourceFilter import *
 from .association import *
 from .diaForcedSource import *
 from .loadDiaCatalogs import *

python/lsst/ap/association/association.py

@@ -32,6 +32,7 @@
 import lsst.pex.config as pexConfig
 import lsst.pipe.base as pipeBase
 from lsst.utils.timer import timeMethod
+from .trailedSourceFilter import TrailedSourceFilterTask
 
 # Enforce an error for unsafe column/array value setting in pandas.
 pd.options.mode.chained_assignment = 'raise'
@@ -47,6 +48,18 @@ class AssociationConfig(pexConfig.Config):
  default=1.0,
  )
 
+ trailedSourceFilter = pexConfig.ConfigurableField(
+ target=TrailedSourceFilterTask,
+ doc="Subtask to filter artifact candidates based on morphological "
+ "criteria, i.g. those that appear to be streaks.",
+ )
+
+ doTrailedSourceFilter = pexConfig.Field(
+ doc="Set flag for trailed source filter subtask to run.",
+ dtype=bool,
+ default=True,
+ )
+
 
 class AssociationTask(pipeBase.Task):
  """Associate DIAOSources into existing DIAObjects.
@@ -60,10 +73,16 @@ class AssociationTask(pipeBase.Task):
  ConfigClass = AssociationConfig
  _DefaultName = "association"
 
+ def __init__(self, *args, **kwargs):
+ super().__init__(*args, **kwargs)
+ if self.config.doTrailedSourceFilter:
+ self.makeSubtask("trailedSourceFilter")
+
  @timeMethod
  def run(self,
  diaSources,
- diaObjects):
+ diaObjects,
+ exposure=None):
  """Associate the new DiaSources with existing DiaObjects.
 
  Parameters
@@ -72,6 +91,9 @@ def run(self,
  New DIASources to be associated with existing DIAObjects.
  diaObjects : `pandas.DataFrame`
  Existing diaObjects from the Apdb.
+ exposure : `pandas.DataFrame` optional
+ Calibrated exposure differenced with a template image during
+ image differencing.
 
  Returns
  -------
@@ -98,7 +120,13 @@ def run(self,
  nUpdatedDiaObjects=0,
  nUnassociatedDiaObjects=0)
 
- matchResult = self.associate_sources(diaObjects, diaSources)
+ if self.config.doTrailedSourceFilter:
+ diaTrailedResult = self.trailedSourceFilter.run(diaSources, exposure)
+
+ matchResult = self.associate_sources(diaObjects, diaTrailedResult.diaSources)
+
+ else:
+ matchResult = self.associate_sources(diaObjects, diaSources)
 
  mask = matchResult.diaSources["diaObjectId"] != 0
 

python/lsst/ap/association/diaPipe.py

@@ -28,6 +28,10 @@
 Currently loads directly from the Apdb rather than pre-loading.
 """
 
+__all__ = ("DiaPipelineConfig",
+ "DiaPipelineTask",
+ "DiaPipelineConnections")
+
 import pandas as pd
 
 import lsst.dax.apdb as daxApdb
@@ -41,13 +45,10 @@
  AssociationTask,
  DiaForcedSourceTask,
  LoadDiaCatalogsTask,
- PackageAlertsTask)
+ PackageAlertsTask,
+ TrailedSourceFilterTask)
 from lsst.ap.association.ssoAssociation import SolarSystemAssociationTask
 
-__all__ = ("DiaPipelineConfig",
- "DiaPipelineTask",
- "DiaPipelineConnections")
-
 
 class DiaPipelineConnections(
  pipeBase.PipelineTaskConnections,
@@ -221,6 +222,10 @@ class DiaPipelineConfig(pipeBase.PipelineTaskConfig,
  target=AssociationTask,
  doc="Task used to associate DiaSources with DiaObjects.",
  )
+ trailedFilter = pexConfig.ConfigurableField(
+ target=TrailedSourceFilterTask,
+ doc="Task used to find trailed DiaSources.",
+ )
  doSolarSystemAssociation = pexConfig.Field(
  dtype=bool,
  default=False,
@@ -368,7 +373,7 @@ def run(self,
 
  # Associate new DiaSources with existing DiaObjects.
  assocResults = self.associator.run(diaSourceTable,
- loaderResult.diaObjects)
+ loaderResult.diaObjects, exposure=exposure)
  if self.config.doSolarSystemAssociation:
  ssoAssocResult = self.solarSystemAssociator.run(
  assocResults.unAssocDiaSources,

python/lsst/ap/association/trailedSourceFilter.py

@@ -0,0 +1,114 @@
+# This file is part of ap_association.
+#
+# Developed for the LSST Data Management System.
+# This product includes software developed by the LSST Project
+# (https://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 <https://www.gnu.org/licenses/>.
+
+"""A simple implementation of trailed source filtering for the association
+ task.
+"""
+
+__all__ = ["TrailedSourceFilterTask", "TrailedSourceFilterConfig"]
+
+import lsst.pex.config as pexConfig
+import lsst.pipe.base as pipeBase
+from lsst.utils.timer import timeMethod
+
+# import numpy as np
+import pandas as pd
+
+# Enforce an error for unsafe column/array value setting in pandas.
+pd.options.mode.chained_assignment = 'raise'
+
+
+class TrailedSourceFilterConfig(pexConfig.Config):
+ """Config class for TrailedSourceFilterTask.
+ """
+ maxTrailLength = pexConfig.Field(
+ dtype=float,
+ doc='Maximum trail length permitted is less than 10 degrees/day. '
+ 'This is a rate of 0.416 arcseconds per second. As trail length'
+ ' is measured in arcseconds, it is dependant on the length of '
+ 'the exposure.',
+ default=0.416,
+ )
+
+
+class TrailedSourceFilterTask(pipeBase.Task):
+ """Find trailed sources in DIAObjects.
+
+ """
+
+ ConfigClass = TrailedSourceFilterConfig
+ _DefaultName = "trailedAssociation"
+
+ @timeMethod
+ def run(self,
+ dia_sources, exposure):
+ """Find trailed sources which have not been filtered out and will
+ not be included in the diaSource catalog.
+
+ Parameters
+ ----------
+ dia_sources : `pandas.DataFrame`
+ New DIASources to be checked for trailed sources.
+ exposure : `pandas.DataFrame`
+ Calibrated exposure differenced with a template image during
+ image differencing.
+
+ Returns
+ -------
+ result : `lsst.pipe.base.Struct`
+ Results struct with components.
+
+ - ``"dia_sources"`` : DiaSource table that is free from unwanted
+ trailed sources (`pandas.DataFrame`)
+
+ - ``"trailed_dia_sources"`` : DiaSources that have trailed more
+ than 0.416 arcseconds/second*exposure_time(`pandas.DataFrame`)
+ """
+ trail_mask = self.check_dia_source_trail(dia_sources, exposure)
+
+ return pipeBase.Struct(
+ diaSources=dia_sources[~trail_mask].reset_index(drop=True),
+ trailedDiaSources=dia_sources[trail_mask].reset_index(drop=True))
+
+ def check_dia_source_trail(self, dia_sources, exposure):
+ """Check that all DiaSources have trails.
+
+ Creates a mask for sources with lengths greater than 0.416
+ arcseconds/second times the exposure time.
+
+ Parameters
+ ----------
+ dia_sources : `pandas.DataFrame`
+ Input DiaSources to check for trail lengths.
+ exposure : `pandas.DataFrame`
+ Calibrated exposure differenced with a template image during
+ image differencing.
+
+ Returns
+ -------
+ trail_mask : `pandas.DataFrame`
+ Boolean mask for dia_sources which are greater than the
+ cuttoff length.
+ """
+ exposure_time = exposure.getInfo().getVisitInfo().getExposureTime()
+ trail_mask = (dia_sources.loc[:, "trailLength"].values[:] >= self.config.maxTrailLength*exposure_time)
+
+ return trail_mask

tests/test_association_task.py

@@ -22,7 +22,8 @@
 import numpy as np
 import pandas as pd
 import unittest
-
+import lsst.afw.image as afwImage
+from lsst.afw.coord import Weather
 import lsst.geom as geom
 import lsst.utils.tests
 
@@ -46,20 +47,38 @@ def setUp(self):
  self.diaSources = pd.DataFrame(data=[
  {"ra": 0.04*idx + scatter*rng.uniform(-1, 1),
  "dec": 0.04*idx + scatter*rng.uniform(-1, 1),
- "diaSourceId": idx + 1 + self.nObjects, "diaObjectId": 0}
+ "diaSourceId": idx + 1 + self.nObjects, "diaObjectId": 0, "trailLength": 5.5*idx}
  for idx in range(self.nSources)])
  self.diaSourceZeroScatter = pd.DataFrame(data=[
  {"ra": 0.04*idx,
  "dec": 0.04*idx,
- "diaSourceId": idx + 1 + self.nObjects, "diaObjectId": 0}
+ "diaSourceId": idx + 1 + self.nObjects, "diaObjectId": 0, "trailLength": 5.5*idx}
  for idx in range(self.nSources)])
+ exposureId = 5
+ exposureTime = 30
+ boresightRotAngle = 45.6 * lsst.geom.degrees
+ weather = Weather(1.1, 2.2, 0.3)
+ visitInfo = afwImage.VisitInfo(
+ exposureId=exposureId,
+ exposureTime=exposureTime,
+ boresightRotAngle=boresightRotAngle,
+ weather=weather,
+ )
+ exposureInfo = afwImage.ExposureInfo()
+ exposureInfo.setVisitInfo(visitInfo)
+ maskedImage = afwImage.MaskedImageF(lsst.geom.Extent2I(64, 64))
+ self.exposure = afwImage.ExposureF(maskedImage, exposureInfo)
 
  def test_run(self):
  """Test the full task by associating a set of diaSources to
  existing diaObjects.
  """
- assocTask = AssociationTask()
- results = assocTask.run(self.diaSources, self.diaObjects)
+
+ config = AssociationTask.ConfigClass()
+ config.doTrailedSourceFilter = False
+ assocTask = AssociationTask(config=config)
+
+ results = assocTask.run(self.diaSources, self.diaObjects, self.exposure)
 
  self.assertEqual(results.nUpdatedDiaObjects, len(self.diaObjects) - 1)
  self.assertEqual(results.nUnassociatedDiaObjects, 1)
@@ -75,13 +94,36 @@ def test_run(self):
  [0]):
  self.assertEqual(test_obj_id, expected_obj_id)
 
+ def test_run_trailed_sources(self):
+ """Test the full task by associating a set of diaSources to
+ existing diaObjects when trailed sources are filtered.
+ """
+
+ assocTask = AssociationTask()
+
+ results = assocTask.run(self.diaSources, self.diaObjects, self.exposure)
+
+ self.assertEqual(results.nUpdatedDiaObjects, len(self.diaObjects) - 3)
+ self.assertEqual(results.nUnassociatedDiaObjects, 3)
+ self.assertEqual(len(results.matchedDiaSources),
+ len(self.diaObjects) - 3)
+ self.assertEqual(len(results.unAssocDiaSources), 1)
+ for test_obj_id, expected_obj_id in zip(
+ results.matchedDiaSources["diaObjectId"].to_numpy(),
+ [1, 2, 3, 4]):
+ self.assertEqual(test_obj_id, expected_obj_id)
+ for test_obj_id, expected_obj_id in zip(
+ results.unAssocDiaSources["diaObjectId"].to_numpy(),
+ [0]):
+ self.assertEqual(test_obj_id, expected_obj_id)
+
  def test_run_no_existing_objects(self):
  """Test the run method with a completely empty database.
  """
  assocTask = AssociationTask()
  results = assocTask.run(
  self.diaSources,
- pd.DataFrame(columns=["ra", "dec", "diaObjectId"]))
+ pd.DataFrame(columns=["ra", "dec", "diaObjectId", "trailLength"]), self.exposure)
  self.assertEqual(results.nUpdatedDiaObjects, 0)
  self.assertEqual(results.nUnassociatedDiaObjects, 0)
  self.assertEqual(len(results.matchedDiaSources), 0)

tests/test_diaPipe.py

@@ -121,7 +121,7 @@ def solarSystemAssociator_run(self, unAssocDiaSources, solarSystemObjectTable, d
  unAssocDiaSources=MagicMock(spec=pd.DataFrame()))
 
  @lsst.utils.timer.timeMethod
- def associator_run(self, table, diaObjects):
+ def associator_run(self, table, diaObjects, exposure):
  return lsst.pipe.base.Struct(nUpdatedDiaObjects=2, nUnassociatedDiaObjects=3,
  matchedDiaSources=MagicMock(spec=pd.DataFrame()),
  unAssocDiaSources=MagicMock(spec=pd.DataFrame()))