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skyObjects.py
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1# This file is part of meas_algorithms.
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/>.
21
22__all__ = ["SkyObjectsConfig", "SkyObjectsTask", "generateSkyObjects"]
23
24from scipy.stats import qmc
25
26from lsst.pex.config import Config, Field, ListField
27from lsst.pipe.base import Task
28
30import lsst.afw.geom
31import lsst.afw.math
32
33
35 """Configuration for generating sky objects"""
36 avoidMask = ListField(
37 dtype=str,
38 default=["DETECTED", "DETECTED_NEGATIVE", "BAD", "NO_DATA"],
39 doc="Avoid pixels masked with these mask planes."
40 )
41 growMask = Field(
42 dtype=int,
43 default=0,
44 doc="Number of pixels to grow the masked pixels when adding sky sources."
45 )
46 sourceRadius = Field(
47 dtype=float,
48 default=8,
49 doc="Radius, in pixels, of sky sources."
50 )
51 nSources = Field(
52 dtype=int,
53 default=100,
54 doc="Try to add this many sky sources."
55 )
56 nTrialSources = Field(
57 dtype=int,
58 default=None,
59 optional=True,
60 doc="Maximum number of trial sky object positions "
61 "(default: nSkySources*nTrialSkySourcesMultiplier)."
62 )
63 nTrialSourcesMultiplier = Field(
64 dtype=int,
65 default=5,
66 doc="Set nTrialSkySources to nSkySources*nTrialSkySourcesMultiplier "
67 "if nTrialSkySources is None."
68 )
69
70
71def generateSkyObjects(mask, seed, config):
72 """Generate a list of Footprints of sky objects
73
74 Sky objects don't overlap with other objects. This is determined
75 through the provided `mask` (in which objects are typically flagged
76 as `DETECTED`).
77
78 Sky objects are positioned using a quasi-random Halton sequence number
79 generator. This is a deterministic sequence that mimics a random trial and
80 error approach whilst acting to minimize clustering of points for a given
81 field of view. Up to `nTrialSources` points are generated, returning the
82 first `nSources` that do not overlap with the mask.
83
84 Parameters
85 ----------
86 mask : `lsst.afw.image.Mask`
87 Input mask plane, which identifies pixels to avoid for the sky
88 objects.
89 seed : `int`
90 Random number generator seed.
91 config : `SkyObjectsConfig`
92 Configuration for finding sky objects.
93
94 Returns
95 -------
96 skyFootprints : `list` of `lsst.afw.detection.Footprint`
97 Footprints of sky objects. Each will have a peak at the center
98 of the sky object.
99 """
100 if config.nSources <= 0:
101 return []
102
103 skySourceRadius = config.sourceRadius
104 nSkySources = config.nSources
105 nTrialSkySources = config.nTrialSources
106 if nTrialSkySources is None:
107 nTrialSkySources = config.nTrialSourcesMultiplier*nSkySources
108
109 box = mask.getBBox()
110 box.grow(-(int(skySourceRadius) + 1)) # Avoid objects partially off the image
111 xMin, yMin = box.getMin()
112 xMax, yMax = box.getMax()
113
114 avoid = lsst.afw.geom.SpanSet.fromMask(mask, mask.getPlaneBitMask(config.avoidMask))
115 if config.growMask > 0:
116 avoid = avoid.dilated(config.growMask)
117
118 sampler = qmc.Halton(d=2, seed=seed).random(nTrialSkySources)
119 sample = qmc.scale(sampler, [xMin, yMin], [xMax, yMax])
120
121 skyFootprints = []
122 for x, y in zip(sample[:, 0].astype(int), sample[:, 1].astype(int)):
123 if len(skyFootprints) == nSkySources:
124 break
125
126 spans = lsst.afw.geom.SpanSet.fromShape(int(skySourceRadius), offset=(x, y))
127 if spans.overlaps(avoid):
128 continue
129
130 fp = lsst.afw.detection.Footprint(spans, mask.getBBox())
131 fp.addPeak(x, y, 0)
132 skyFootprints.append(fp)
133
134 # Add doubled-in-size sky object spanSet to the avoid mask.
135 avoid = avoid.union(spans.dilated(int(skySourceRadius)))
136
137 return skyFootprints
138
139
140class SkyObjectsTask(Task):
141 """Generate a list of Footprints of sky sources/objects (regions on the
142 sky that do not otherwise have detections).
143
144 Parameters
145 ----------
146 schema : `lsst.afw.table.Schema`
147 Schema used to create the output `~lsst.afw.table.SourceCatalog`,
148 updated with fields that will be written by this task.
149
150 """
151 ConfigClass = SkyObjectsConfig
152
153 def __init__(self, schema=None, **kwargs):
154 super().__init__(**kwargs)
155 if schema is not None:
156 self.skySourceKey = schema.addField("sky_source", type="Flag",
157 doc="Region on image with no detections.")
158 else:
159 self.skySourceKey = None
160
161 def run(self, mask, seed, catalog=None):
162 """Generate a list of Footprints of sky sources/objects.
163
164 Sky objects don't overlap with other objects. This is determined
165 through the provided `mask` (in which objects are typically flagged
166 as `DETECTED`).
167
168 Sky objects are positioned using a quasi-random Halton sequence
169 number generator. This is a deterministic sequence that mimics a random
170 trial and error approach whilst acting to minimize clustering of points
171 for a given field of view. Up to `nTrialSources` points are generated,
172 returning the first `nSources` that do not overlap with the mask.
173
174 Parameters
175 ----------
176 mask : `lsst.afw.image.Mask`
177 Input mask plane, which identifies pixels to avoid for the sky
178 objects.
179 seed : `int`
180 Random number generator seed.
181 catalog : `lsst.afw.table.SourceCatalog`, optional
182 Catalog to add detected footprints to; modified in-place if any
183 sky source/object footprints are created.
184
185 Returns
186 -------
187 skyFootprints : `list` of `lsst.afw.detection.Footprint`
188 Footprints of sky objects. Each will have a peak at the center
189 of the sky object.
190 """
191 skyFootprints = generateSkyObjects(mask, seed, self.config)
192 self.log.info("Added %d of %d requested sky sources (%.0f%%)", len(skyFootprints),
193 self.config.nSources, 100*len(skyFootprints)/self.config.nSources)
194 self.metadata["sky_footprint_count"] = len(skyFootprints)
195
196 if skyFootprints and self.skySourceKey is not None and catalog is not None:
197 for footprint in skyFootprints:
198 record = catalog.addNew()
199 record.setFootprint(footprint)
200 record.set(self.skySourceKey, True)
201
202 return skyFootprints
Class to describe the properties of a detected object from an image.
Definition Footprint.h:63
static std::shared_ptr< geom::SpanSet > fromMask(image::Mask< T > const &mask, UnaryPredicate comparator=details::AnyBitSetFunctor< T >())
Create a SpanSet from a mask.
Definition SpanSet.h:644
static std::shared_ptr< geom::SpanSet > fromShape(int r, Stencil s=Stencil::CIRCLE, lsst::geom::Point2I offset=lsst::geom::Point2I())
Factory function for creating SpanSets from a Stencil.
Definition SpanSet.cc:688
run(self, mask, seed, catalog=None)
generateSkyObjects(mask, seed, config)
Definition skyObjects.py:71