Coverage for python/lsst/analysis/tools/analysisPlots/photometricRepeatabilityPlots.py: 39%
18 statements
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« prev ^ index » next coverage.py v6.5.0, created at 2023-02-24 02:02 -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__ = ("StellarPhotometricRepeatabilityHistPlot",)
25from ..actions.plot.histPlot import HistPanel, HistPlot, HistStatsPanel
26from ..analysisParts.photometricRepeatability import StellarPhotometricRepeatabilityMixin
27from ..interfaces import AnalysisPlot
30class StellarPhotometricRepeatabilityHistPlot(AnalysisPlot, StellarPhotometricRepeatabilityMixin):
31 """Compute photometric repeatability from multiple measurements of a set of
32 stars. First, a set of per-source quality criteria are applied. Second,
33 the individual source measurements are grouped together by object index
34 and per-group quantities are computed (e.g., a representative S/N for the
35 group based on the median of associated per-source measurements). Third,
36 additional per-group criteria are applied. Fourth, summary statistics are
37 computed for the filtered groups.
38 """
40 def setDefaults(self):
41 super().setDefaults()
43 self.produce = HistPlot()
45 self.produce.panels["panel_rms"] = HistPanel()
47 self.produce.panels["panel_rms"].statsPanel = HistStatsPanel()
48 self.produce.panels["panel_rms"].statsPanel.statsLabels = ["N", "PA1", "PF1 %"]
49 self.produce.panels["panel_rms"].statsPanel.stat1 = ["photRepeatNsources"]
50 self.produce.panels["panel_rms"].statsPanel.stat2 = ["photRepeatStdev"]
51 self.produce.panels["panel_rms"].statsPanel.stat3 = ["photRepeatOutlier"]
53 self.produce.panels["panel_rms"].referenceValue = self.PA2Value
54 self.produce.panels["panel_rms"].label = "rms (mmag)"
55 self.produce.panels["panel_rms"].hists = dict(perGroupStdevFiltered="Filtered per group rms")