Coverage for tests/utils_tests.py: 16%
42 statements
« prev ^ index » next coverage.py v7.3.1, created at 2023-09-21 18:46 +0000
« prev ^ index » next coverage.py v7.3.1, created at 2023-09-21 18:46 +0000
1# This file is part of ap_association.
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/>.
22"""Helper functions for tests of DIA catalogs, including generating mock
23catalogs for simulated APDB access.
24"""
25import datetime
26import pandas as pd
27import numpy as np
29import lsst.daf.base as dafBase
30import lsst.geom
33def makeDiaObjects(nObjects, exposure):
34 """Make a test set of DiaObjects.
36 Parameters
37 ----------
38 nObjects : `int`
39 Number of objects to create.
40 exposure : `lsst.afw.image.Exposure`
41 Exposure to create objects over.
43 Returns
44 -------
45 diaObjects : `pandas.DataFrame`
46 DiaObjects generated across the exposure.
47 """
48 bbox = lsst.geom.Box2D(exposure.getBBox())
49 rand_x = np.random.uniform(bbox.getMinX(), bbox.getMaxX(), size=nObjects)
50 rand_y = np.random.uniform(bbox.getMinY(), bbox.getMaxY(), size=nObjects)
52 midpointMjdTai = exposure.visitInfo.date.get(system=dafBase.DateTime.MJD)
54 data = []
55 for idx, (x, y) in enumerate(zip(rand_x, rand_y)):
56 coord = exposure.wcs.pixelToSky(x, y)
57 newObject = {"ra": coord.getRa().asDegrees(),
58 "dec": coord.getDec().asDegrees(),
59 "radecMjdTai": midpointMjdTai,
60 "diaObjectId": idx + 1,
61 "pmParallaxNdata": 0,
62 "nearbyObj1": 0,
63 "nearbyObj2": 0,
64 "nearbyObj3": 0,
65 "flags": 1,
66 "nDiaSources": 5}
67 for f in ["u", "g", "r", "i", "z", "y"]:
68 newObject["%s_psfFluxNdata" % f] = 0
69 data.append(newObject)
71 return pd.DataFrame(data=data)
74def makeDiaSources(nSources, diaObjectIds, exposure, randomizeObjects=False):
75 """Make a test set of DiaSources.
77 Parameters
78 ----------
79 nSources : `int`
80 Number of sources to create.
81 diaObjectIds : `numpy.ndarray`
82 Integer Ids of diaobjects to "associate" with the DiaSources.
83 exposure : `lsst.afw.image.Exposure`
84 Exposure to create sources over.
85 randomizeObjects : `bool`, optional
86 If True, randomly draw from `diaObjectIds` to generate the ids in the
87 output catalog, otherwise just iterate through them, repeating as
88 necessary to get nSources objectIds.
90 Returns
91 -------
92 diaSources : `pandas.DataFrame`
93 DiaSources generated across the exposure.
94 """
95 bbox = lsst.geom.Box2D(exposure.getBBox())
96 rand_x = np.random.uniform(bbox.getMinX(), bbox.getMaxX(), size=nSources)
97 rand_y = np.random.uniform(bbox.getMinY(), bbox.getMaxY(), size=nSources)
98 if randomizeObjects:
99 objectIds = diaObjectIds[np.random.randint(len(diaObjectIds), size=nSources)]
100 else:
101 objectIds = diaObjectIds[[i % len(diaObjectIds) for i in range(nSources)]]
103 midpointMjdTai = exposure.visitInfo.date.get(system=dafBase.DateTime.MJD)
105 data = []
106 for idx, (x, y, objId) in enumerate(zip(rand_x, rand_y, objectIds)):
107 coord = exposure.wcs.pixelToSky(x, y)
108 # Put together the minimum values for the alert.
109 data.append({"ra": coord.getRa().asDegrees(),
110 "dec": coord.getDec().asDegrees(),
111 "x": x,
112 "y": y,
113 "ccdVisitId": exposure.info.id,
114 "time_processed": datetime.datetime.now(),
115 "diaObjectId": objId,
116 "ssObjectId": 0,
117 "parentDiaSourceId": 0,
118 "diaSourceId": idx + 1,
119 "midpointMjdTai": midpointMjdTai + 1.0 * idx,
120 "band": exposure.getFilter().bandLabel,
121 "psfNdata": 0,
122 "trailNdata": 0,
123 "dipoleNdata": 0,
124 "flags": 1})
126 return pd.DataFrame(data=data)
129def makeDiaForcedSources(nForcedSources, diaObjectIds, exposure, randomizeObjects=False):
130 """Make a test set of DiaSources.
132 Parameters
133 ----------
134 nForcedSources : `int`
135 Number of sources to create.
136 diaObjectIds : `numpy.ndarray`
137 Integer Ids of diaobjects to "associate" with the DiaSources.
138 exposure : `lsst.afw.image.Exposure`
139 Exposure to create sources over.
140 randomizeObjects : `bool`, optional
141 If True, randomly draw from `diaObjectIds` to generate the ids in the
142 output catalog, otherwise just iterate through them.
144 Returns
145 -------
146 diaForcedSources : `pandas.DataFrame`
147 DiaForcedSources generated across the exposure.
148 """
149 midpointMjdTai = exposure.visitInfo.date.get(system=dafBase.DateTime.MJD)
150 ccdVisitId = exposure.info.id
151 if randomizeObjects:
152 objectIds = diaObjectIds[np.random.randint(len(diaObjectIds), size=nForcedSources)]
153 else:
154 objectIds = diaObjectIds[[i % len(diaObjectIds) for i in range(nForcedSources)]]
156 data = []
157 for i, objId in enumerate(objectIds):
158 # Put together the minimum values for the alert.
159 data.append({"diaForcedSourceId": i + 1,
160 "ccdVisitId": ccdVisitId + i,
161 "diaObjectId": objId,
162 "midpointMjdTai": midpointMjdTai + 1.0 * i,
163 "time_processed": datetime.datetime.now(),
164 "band": exposure.getFilter().bandLabel,
165 "flags": 0})
167 return pd.DataFrame(data=data)