Coverage for python/lsst/analysis/tools/analysisMetrics/photometricRepeatabilityMetrics.py: 27%
30 statements
« prev ^ index » next coverage.py v6.5.0, created at 2022-12-06 02:44 -0800
« prev ^ index » next coverage.py v6.5.0, created at 2022-12-06 02:44 -0800
1# This file is part of analysis_tools.
2#
3# Developed for the LSST Data Management System.
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
10# it under the terms of the GNU General Public License as published by
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.
18#
19# You should have received a copy of the GNU General Public License
20# along with this program. If not, see <https://www.gnu.org/licenses/>.
21from __future__ import annotations
23__all__ = ("StellarPhotometricRepeatabilityMetric",)
25from ..actions.scalar.scalarActions import FracThreshold, MedianAction
26from ..actions.vector import (
27 BandSelector,
28 MagColumnNanoJansky,
29 MultiCriteriaDownselectVector,
30 PerGroupStatistic,
31 Sn,
32 ThresholdSelector,
33)
34from ..interfaces import AnalysisMetric
37class StellarPhotometricRepeatabilityMetric(AnalysisMetric):
38 """Compute photometric repeatability from multiple measurements of a set of
39 stars. First, a set of per-source quality criteria are applied. Second,
40 the individual source measurements are grouped together by object index
41 and per-group quantities are computed (e.g., a representative S/N for the
42 group based on the median of associated per-source measurements). Third,
43 additional per-group criteria are applied. Fourth, summary statistics are
44 computed for the filtered groups.
45 """
47 fluxType: str = "psfFlux"
49 def setDefaults(self):
50 super().setDefaults()
52 # Apply per-source selection criteria
53 self.prep.selectors.bandSelector = BandSelector()
55 # Compute per-group quantities
56 self.process.buildActions.perGroupSn = PerGroupStatistic()
57 self.process.buildActions.perGroupSn.buildAction = Sn(fluxType=f"{self.fluxType}")
58 self.process.buildActions.perGroupSn.func = "median"
59 self.process.buildActions.perGroupExtendedness = PerGroupStatistic()
60 self.process.buildActions.perGroupExtendedness.buildAction.vectorKey = "extendedness"
61 self.process.buildActions.perGroupExtendedness.func = "median"
62 self.process.buildActions.perGroupCount = PerGroupStatistic()
63 self.process.buildActions.perGroupCount.buildAction.vectorKey = f"{self.fluxType}"
64 self.process.buildActions.perGroupCount.func = "count"
65 # Use mmag units
66 self.process.buildActions.perGroupStdev = PerGroupStatistic()
67 self.process.buildActions.perGroupStdev.buildAction = MagColumnNanoJansky(
68 vectorKey=f"{self.fluxType}",
69 returnMillimags=True,
70 )
71 self.process.buildActions.perGroupStdev.func = "std"
73 # Filter on per-group quantities
74 self.process.filterActions.perGroupStdevFiltered = MultiCriteriaDownselectVector(
75 vectorKey="perGroupStdev"
76 )
77 self.process.filterActions.perGroupStdevFiltered.selectors.count = ThresholdSelector(
78 vectorKey="perGroupCount",
79 op="ge",
80 threshold=3,
81 )
82 self.process.filterActions.perGroupStdevFiltered.selectors.sn = ThresholdSelector(
83 vectorKey="perGroupSn",
84 op="ge",
85 threshold=200,
86 )
87 self.process.filterActions.perGroupStdevFiltered.selectors.extendedness = ThresholdSelector(
88 vectorKey="perGroupExtendedness",
89 op="le",
90 threshold=0.5,
91 )
93 # Compute summary statistics on filtered groups
94 self.process.calculateActions.photRepeatStdev = MedianAction(vectorKey="perGroupStdevFiltered")
95 self.process.calculateActions.photRepeatOutlier = FracThreshold(
96 vectorKey="perGroupStdevFiltered",
97 op="ge",
98 threshold=15.0,
99 percent=True,
100 )
102 self.produce.units = { # type: ignore
103 "photRepeatStdev": "mmag",
104 "photRepeatOutlier": "percent",
105 }
106 self.produce.newNames = {
107 "photRepeatStdev": "{band}_stellarPhotRepeatStdev",
108 "photRepeatOutlier": "{band}_stellarPhotRepeatOutlierFraction",
109 }