Add source Metrics and plots

Adding metrics on associated and unassociated sources, as well as pipeline to create a bar graph comparing associated and unassociated sources. 
Rename demoMetric


Lint fix


Typo Fix


Formatting Fix


Add __all__ and updated docstrings


Formatting fixes


Small fix


Removed repeated Unique Action


Updated docstring

pipelines/diaObjectAssociatedSources.yaml

@@ -0,0 +1,13 @@
+description: |
+  Pipeline to create metrics for associated and unassociated sources from diaObject tables
+tasks:
+  analyzeDiaObjectTableSources:
+    class: lsst.analysis.tools.tasks.DiaObjectTableAssociatedSourcesTask
+    config:
+      connections.outputName: sourcesOutput
+      bands: ['g']
+      metrics.sourceMetrics: CountSources
+      plots.analysisPlots: SourcesPlot
+      python: |
+        from lsst.analysis.tools.analysisMetrics import *
+        from lsst.analysis.tools.analysisPlots import *

python/lsst/analysis/tools/actions/scalar/scalarActions.py

@@ -171,47 +171,3 @@ def getInputSchema(self) -> KeyedDataSchema:
     def __call__(self, data: KeyedData, **kwargs) -> Scalar:
         mask = self.getMask(**kwargs)
         return cast(Scalar, float(np.min(cast(Vector, data[self.vectorKey.format(**kwargs)])[mask])))
-
-
-class UniqueAction(ScalarAction):
-    vectorKey = Field[str]("Key of Vector from which to investigate the number of unique entries")
-
-    def getInputSchema(self) -> KeyedDataSchema:
-        return ((self.vectorKey, Vector),)
-
-    def __call__(self, data: KeyedData, **kwargs) -> Scalar:
-        mask = self.getMask(**kwargs)
-        return cast(Scalar, int(len(np.unique(cast(Vector, data[self.vectorKey.format(**kwargs)])[mask]))))
-
-
-class MaxAction(ScalarAction):
-    vectorKey = Field[str]("Key of Vector to find maximum")
-
-    def getInputSchema(self) -> KeyedDataSchema:
-        return ((self.vectorKey, Vector),)
-
-    def __call__(self, data: KeyedData, **kwargs) -> Scalar:
-        mask = self.getMask(**kwargs)
-        return cast(Scalar, float(np.max(cast(Vector, data[self.vectorKey.format(**kwargs)])[mask])))
-
-
-class MinAction(ScalarAction):
-    vectorKey = Field[str]("Key for the vector to perform action on")
-
-    def getInputSchema(self) -> KeyedDataSchema:
-        return ((self.vectorKey, Vector),)
-
-    def __call__(self, data: KeyedData, **kwargs) -> Scalar:
-        mask = self.getMask(**kwargs)
-        return cast(Scalar, float(np.min(cast(Vector, data[self.vectorKey.format(**kwargs)])[mask])))
-
-
-class UniqueAction(ScalarAction):
-    vectorKey = Field[str]("Key of Vector from which to investigate the number of unique entries")
-
-    def getInputSchema(self) -> KeyedDataSchema:
-        return ((self.vectorKey, Vector),)
-
-    def __call__(self, data: KeyedData, **kwargs) -> Scalar:
-        mask = self.getMask(**kwargs)
-        return cast(Scalar, int(len(np.unique(cast(Vector, data[self.vectorKey.format(**kwargs)])[mask]))))

python/lsst/analysis/tools/analysisMetrics/__init__.py

@@ -26,3 +26,4 @@
 from .photometricRepeatabilityMetrics import *
 from .psfResidualMetrics import *
 from .skyFluxStatisticMetrics import *
+from .sourceMetrics import *

python/lsst/analysis/tools/analysisMetrics/seeingMetric.py

@@ -23,6 +23,8 @@
 
 from ..interfaces import AnalysisMetric
 
+__all__ = ("SeeingStatistics",)
+
 
 class SeeingStatistics(AnalysisMetric):
     """Calculate seeing statistics from the ccdVisit table.
@@ -38,6 +40,6 @@ def setDefaults(self):
 
         self.produce.units = {
             "medianSeeing": "arcsec",
-            "minSeeing": "arcsev",
+            "minSeeing": "arcsec",
             "maxSeeing": "arcsec",
         }

python/lsst/analysis/tools/analysisMetrics/sourceMetrics.py

@@ -0,0 +1,53 @@
+# This file is part of analysis_tools.
+#
+# 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/>.
+
+from lsst.analysis.tools.actions.scalar import CountAction, FracThreshold
+
+from ..analysisParts.baseSources import BaseSources
+from ..interfaces import AnalysisMetric
+
+__all__ = ("CountSources",)
+
+
+class CountSources(AnalysisMetric, BaseSources):
+    """Counts associated and unassociated sources as
+    well as their percentage of the total sources."""
+
+    def setDefaults(self):
+        super().setDefaults()
+
+        self.process.calculateActions.associatedPercent = FracThreshold(
+            op="gt", threshold=1.0, vectorKey="nDiaSources"
+        )
+        self.process.calculateActions.unassociatedPercent = FracThreshold(
+            op="le", threshold=1.0, vectorKey="nDiaSources"
+        )
+
+        self.process.calculateActions.associatedCount = CountAction(vectorKey="associatedVector")
+        self.process.calculateActions.unassociatedCount = CountAction(vectorKey="unassociatedVector")
+
+        self.produce.units = {
+            "associatedPercent": "count",
+            "unassociatedPercent": "count",
+            "associatedCount": "count",
+            "unassociatedCount": "count",
+            "uniqueSources": "count",
+        }

python/lsst/analysis/tools/analysisParts/baseSources.py

@@ -1,7 +1,9 @@
-from lsst.analysis.tools.actions.scalar import UniqueAction
+from lsst.analysis.tools.actions.scalar import CountUniqueAction
 from lsst.analysis.tools.actions.vector import DownselectVector, LoadVector, ThresholdSelector, VectorSelector
 from lsst.analysis.tools.interfaces import AnalysisTool
 
+__all__ = ("BaseSources",)
+
 
 class BaseSources(AnalysisTool):
     """Base class for counting associated and unassociated sources."""
@@ -30,4 +32,4 @@ def setDefaults(self):
             vectorKey="nDiaSources", selector=self.process.buildActions.unassociatedVectorSelector
         )
 
-        self.process.buildActions.uniqueSources = UniqueAction(vectorKey="nDiaSources")
+        self.process.buildActions.uniqueSources = CountUniqueAction(vectorKey="nDiaSources")

python/lsst/analysis/tools/analysisPlots/analysisPlots.py

@@ -33,14 +33,17 @@
     "YPerpCModelPlot",
     "TargetRefCatDeltaRAScatterPlot",
     "TargetRefCatDeltaRAScatterPlot",
+    "SourcesPlot",
 )
 
 from lsst.pex.config import Field
 
+from ..actions.plot.barPlots import BarPanel, BarPlot
 from ..actions.plot.colorColorFitPlot import ColorColorFitPlot
 from ..actions.plot.histPlot import HistPanel, HistPlot
 from ..actions.plot.scatterplotWithTwoHists import ScatterPlotStatsAction, ScatterPlotWithTwoHists
 from ..actions.plot.skyPlot import SkyPlot
+from ..actions.scalar import CountAction
 from ..actions.vector import (
     AstromDiff,
     CoaddPlotFlagSelector,
@@ -53,6 +56,7 @@
     VectorSelector,
 )
 from ..analysisParts.baseFluxRatio import BasePsfApRatio
+from ..analysisParts.baseSources import BaseSources
 from ..analysisParts.genericPrep import CoaddPrep, VisitPrep
 from ..analysisParts.shapeSizeFractional import BasePsfResidualMixin
 from ..analysisParts.stellarLocus import WPerpCModel, WPerpPSF, XPerpCModel, XPerpPSF, YPerpCModel, YPerpPSF
@@ -329,3 +333,21 @@ def setDefaults(self):
         self.produce.panels["panel_flux"] = HistPanel()
         self.produce.panels["panel_flux"].label = "Psf/Ap Ratio"
         self.produce.panels["panel_flux"].hists = dict(fluxRatioMetric="Ratio")
+
+
+class SourcesPlot(AnalysisPlot, BaseSources):
+    """Plot a histogram of the associated and unassociated Sources"""
+
+    def setDefaults(self, **kwargs):
+        super().setDefaults()
+
+        self.process.calculateActions.associatedCount = CountAction(vectorKey="associatedVector")
+        self.process.calculateActions.unassociatedCount = CountAction(vectorKey="unassociatedVector")
+
+        self.produce = BarPlot()
+        self.produce.panels["panel_source"] = BarPanel()
+        self.produce.panels["panel_source"].label = "N Assoc and Unassoc Sources"
+        self.produce.panels["panel_source"].bars = dict(
+            associatedVector="Associated Sources",
+            unassociatedVector="Unassociated Sources",
+        )

python/lsst/analysis/tools/tasks/__init__.py

@@ -1,5 +1,6 @@
 from .associatedSourcesTractAnalysis import *
 from .catalogMatch import *
+from .diaObjectTableAssocAnalysis import *
 from .diaSourceTableVisitAnalysis import *
 from .diffMatchedAnalysis import *
 from .objectTableTractAnalysis import *

python/lsst/analysis/tools/tasks/diaObjectTableAssocAnalysis.py

@@ -0,0 +1,35 @@
+from __future__ import annotations
+
+from lsst.pipe.base import connectionTypes as ct
+
+from .base import AnalysisBaseConfig, AnalysisBaseConnections, AnalysisPipelineTask
+
+__all__ = [
+    "DiaObjectTableAnalysisConnections",
+    "DiaObjectTableAnalysisConfig",
+    "DiaObjectTableAssociatedSourcesTask",
+]
+
+
+class DiaObjectTableAnalysisConnections(
+    AnalysisBaseConnections,
+    dimensions=("visit", "band"),
+    defaultTemplates={"coaddName": "deep", "fakesType": ""},
+):
+
+    data = ct.Input(
+        doc="CcdVisit-based DiaObject table to load from the butler",
+        name="{fakesType}{coaddName}Diff_diaObject",
+        storageClass="DataFrame",
+        dimensions=("visit", "band", "detector"),
+        deferLoad=True,
+    )
+
+
+class DiaObjectTableAnalysisConfig(AnalysisBaseConfig, pipelineConnections=DiaObjectTableAnalysisConnections):
+    pass
+
+
+class DiaObjectTableAssociatedSourcesTask(AnalysisPipelineTask):
+    ConfigClass = DiaObjectTableAnalysisConfig
+    _DefaultName = "DiaObjectTableAssociatedSources"