Coverage for python/lsst/analysis/tools/tasks/objectTableSurveyAnalysis.py: 47%
33 statements
« prev ^ index » next coverage.py v6.5.0, created at 2023-02-14 03:39 -0800
« prev ^ index » next coverage.py v6.5.0, created at 2023-02-14 03:39 -0800
1# Developed for the LSST Data Management System.
2# This product includes software developed by the LSST Project
3# (https://www.lsst.org).
4# See the COPYRIGHT file at the top-level directory of this distribution
5# for details of code ownership.
6#
7# This program is free software: you can redistribute it and/or modify
8# it under the terms of the GNU General Public License as published by
9# the Free Software Foundation, either version 3 of the License, or
10# (at your option) any later version.
11#
12# This program is distributed in the hope that it will be useful,
13# but WITHOUT ANY WARRANTY; without even the implied warranty of
14# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
15# GNU General Public License for more details.
16#
17# You should have received a copy of the GNU General Public License
18# along with this program. If not, see <https://www.gnu.org/licenses/>.
20from __future__ import annotations
22__all__ = ("ObjectTableSurveyAnalysisTask",)
25from typing import TYPE_CHECKING, Any, Iterable, Mapping, cast
27import pandas as pd
29if TYPE_CHECKING: 29 ↛ 30line 29 didn't jump to line 30, because the condition on line 29 was never true
30 from lsst.daf.butler import DataCoordinate, DeferredDatasetHandle
32from lsst.pipe.base import connectionTypes as ct
34from ..actions.plot.plotUtils import shorten_list
35from ..interfaces import KeyedData
36from .base import AnalysisBaseConfig, AnalysisBaseConnections, AnalysisPipelineTask
39class ObjectTableSurveyAnalysisConnections(
40 AnalysisBaseConnections,
41 dimensions=("skymap",),
42 defaultTemplates={"input": "deepCoadd"},
43):
44 skymap = ct.Input(
45 doc="Input definition of geometry/bbox and projection/wcs for warped exposures",
46 name="skyMap",
47 storageClass="SkyMap",
48 dimensions=("skymap",),
49 )
51 data = ct.Input(
52 doc="Input catalog of objects",
53 name="objectTable_tract",
54 storageClass="DataFrame",
55 deferLoad=True,
56 multiple=True,
57 dimensions=("tract", "skymap"),
58 )
61class ObjectTableSurveyAnalysisConfig(
62 AnalysisBaseConfig, pipelineConnections=ObjectTableSurveyAnalysisConnections
63):
64 pass
67class ObjectTableSurveyAnalysisTask(AnalysisPipelineTask):
68 ConfigClass = ObjectTableSurveyAnalysisConfig
69 _DefaultName = "objectTableSurveyAnalysis"
71 def parsePlotInfo(
72 self, inputs: Mapping[str, Any] | None, dataId: DataCoordinate | None, connectionName: str = "data"
73 ) -> Mapping[str, str]:
74 # Docstring inherited
76 if inputs is None:
77 tableName = ""
78 run = ""
79 tracts = []
80 else:
81 tableName = inputs[connectionName][0].ref.datasetType.name
82 run = inputs[connectionName][0].ref.run
83 tracts = [data.ref.dataId["tract"] for data in inputs[connectionName]]
85 # Initialize the plot info dictionary
86 plotInfo = {
87 "tableName": tableName,
88 "run": run,
89 "tract": shorten_list(tracts),
90 }
92 self._populatePlotInfoWithDataId(plotInfo, dataId)
93 return plotInfo
95 def loadData( # type: ignore[override]
96 self,
97 handle: Iterable[DeferredDatasetHandle],
98 names: Iterable[str] | None = None,
99 ) -> KeyedData:
100 """Load the minimal set of keyed data from the input dataset.
102 Parameters
103 ----------
104 handle : `Iterable` of `DeferredDatasetHandle`
105 Handle to load the dataset with only the specified columns.
106 names : `Iterable` of `str`
107 The names of keys to extract from the dataset.
108 If `names` is `None` then the `collectInputNames` method
109 is called to generate the names.
110 For most purposes these are the names of columns to load from
111 a catalog or data frame.
113 Returns
114 -------
115 result: `KeyedData`
116 The dataset with only the specified keys loaded.
117 """
118 # Except associatedSourceTractAnalysis, all other tasks trivially
119 # subclass this, so names don't get utilized.
120 if names is None:
121 names = self.collectInputNames()
123 return cast(KeyedData, pd.concat(h.get(parameters={"columns": names}) for h in handle))