Use mmag units for photometric repeatability

lsst · Aug 2, 2022 · 7792b13 · 7792b13
1 parent bec1a03
commit 7792b13
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Showing 3 changed files with 39 additions and 29 deletions.
diff --git a/python/lsst/analysis/tools/actions/vector/selectors.py b/python/lsst/analysis/tools/actions/vector/selectors.py
@@ -30,7 +30,7 @@
     "GalaxySelector",
     "UnknownSelector",
     "VectorSelector",
-    "AndSelector",
+    # "AndSelector",
     "ThresholdSelector",
     "BandSelector",
 )
@@ -332,26 +332,26 @@ def __call__(self, data: KeyedData, **kwargs) -> Vector:
         return cast(Vector, data[self.vectorKey.format(**kwargs)])
 
 
-class AndSelector(VectorAction):
-    """Apply multiple selection criteria with logical AND."""
-
-    selectors = ConfigurableActionStructField[VectorAction](
-        doc="Selectors for selecting rows, will be AND together",
-    )
-
-    def getInputSchema(self) -> KeyedDataSchema:
-        for action in self.selectors:
-            yield from action.getInputSchema()
-
-    def __call__(self, data: KeyedData, **kwargs) -> KeyedData:
-        mask: Optional[Vector] = None
-        for selector in self.selectors:
-            subMask = selector(data, **kwargs)
-            if mask is None:
-                mask = subMask
-            else:
-                mask *= subMask  # type: ignore
-        return cast(Vector, mask)
+# class AndSelector(VectorAction):
+#    """Apply multiple selection criteria with logical AND."""
+#
+#    selectors = ConfigurableActionStructField[VectorAction](
+#        doc="Selectors for selecting rows, will be AND together",
+#    )
+#
+#    def getInputSchema(self) -> KeyedDataSchema:
+#        for action in self.selectors:
+#            yield from action.getInputSchema()
+#
+#    def __call__(self, data: KeyedData, **kwargs) -> KeyedData:
+#        mask: Optional[Vector] = None
+#        for selector in self.selectors:
+#            subMask = selector(data, **kwargs)
+#            if mask is None:
+#                mask = subMask
+#            else:
+#                mask *= subMask  # type: ignore
+#        return cast(Vector, mask)
 
 
 class ThresholdSelector(VectorAction):

diff --git a/python/lsst/analysis/tools/actions/vector/vectorActions.py b/python/lsst/analysis/tools/actions/vector/vectorActions.py
@@ -21,7 +21,7 @@
 from __future__ import annotations
 
 import logging
-from typing import cast
+from typing import Optional, cast
 
 import numpy as np
 import pandas as pd
@@ -82,6 +82,7 @@ def __call__(self, data: KeyedData, **kwargs) -> Vector:
 
 class MagColumnNanoJansky(VectorAction):
     vectorKey = Field[str](doc="column key to use for this transformation")
+    returnMillimags = Field[bool](doc="Use millimags or not?", default=False)
 
     def getInputSchema(self) -> KeyedDataSchema:
         return ((self.vectorKey, Vector),)
@@ -91,7 +92,11 @@ def __call__(self, data: KeyedData, **kwargs) -> Vector:
             np.warnings.filterwarnings("ignore", r"invalid value encountered")  # type: ignore
             np.warnings.filterwarnings("ignore", r"divide by zero")  # type: ignore
             vec = cast(Vector, data[self.vectorKey.format(**kwargs)])
-            return np.array(-2.5 * np.log10((vec * 1e-9) / 3631.0))  # type: ignore
+            mag = np.array(-2.5 * np.log10((vec * 1e-9) / 3631.0))  # type: ignore
+            if self.returnMillimags:
+                return mag * u.mag.to(u.mmag)
+            else:
+                return mag
 
 
 class FractionalDifference(VectorAction):
@@ -281,9 +286,10 @@ def __call__(self, data: KeyedData, **kwargs) -> Vector:
 
 
 class PerGroupStatistic(VectorAction):
-    """Compute per-group statistic values and return result as a vector with one element per group. The
-    computed statistic can be any function accepted by pandas DataFrameGroupBy.aggregate passed in as a string
-    function name."""
+    """Compute per-group statistic values and return result as a vector with
+    one element per group. The computed statistic can be any function accepted
+    by pandas DataFrameGroupBy.aggregate passed in as a string function name.
+    """
 
     groupKey = Field[str](doc="Column key to use for forming groups", default="obj_index")
     buildAction = ConfigurableActionField(doc="Action to build vector", default=LoadVector)

diff --git a/python/lsst/analysis/tools/analysisMetrics/photometricRepeatabilityMetrics.py b/python/lsst/analysis/tools/analysisMetrics/photometricRepeatabilityMetrics.py
@@ -22,6 +22,8 @@
 
 __all__ = ("StellarPhotometricRepeatabilityMetric",)
 
+from astropy import units as u
+
 from ..actions.scalar.scalarActions import FracThreshold, MedianAction
 from ..actions.vector import (
     BandSelector,
@@ -62,9 +64,11 @@ def setDefaults(self):
         self.process.buildActions.perGroupCount = PerGroupStatistic()
         self.process.buildActions.perGroupCount.buildAction.vectorKey = f"{self.fluxType}"
         self.process.buildActions.perGroupCount.func = "count"
+        # Use mmag units
         self.process.buildActions.perGroupStdev = PerGroupStatistic()
         self.process.buildActions.perGroupStdev.buildAction = MagColumnNanoJansky(
-            vectorKey=f"{self.fluxType}"
+            vectorKey=f"{self.fluxType}",
+            returnMillimags=True,
         )
         self.process.buildActions.perGroupStdev.func = "std"
 
@@ -93,12 +97,12 @@ def setDefaults(self):
         self.process.calculateActions.photRepeatOutlier = FracThreshold(
             vectorKey="perGroupStdevFiltered",
             op="ge",
-            threshold=0.015,
+            threshold=15.0,
             percent=True,
         )
 
         self.produce.units = {  # type: ignore
-            "photRepeatStdev": "mag",
+            "photRepeatStdev": "mmag",
             "photRepeatOutlier": "percent",
         }
         self.produce.newNames = {