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LSST Data Management Base Package
skyObjects.py
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2__all__ = ["SkyObjectsConfig", "SkyObjectsTask", "generateSkyObjects"]
3
4from lsst.pex.config import Config, Field, ListField
5from lsst.pipe.base import Task
6
8import lsst.afw.geom
9import lsst.afw.math
10
11
13 """Configuration for generating sky objects"""
14 avoidMask = ListField(dtype=str, default=["DETECTED", "DETECTED_NEGATIVE", "BAD", "NO_DATA"],
15 doc="Avoid pixels masked with these mask planes")
16 growMask = Field(dtype=int, default=0,
17 doc="Number of pixels to grow the masked pixels when adding sky objects")
18 sourceRadius = Field(dtype=float, default=8, doc="Radius, in pixels, of sky objects")
19 nSources = Field(dtype=int, default=100, doc="Try to add this many sky objects")
20 nTrialSources = Field(dtype=int, default=None, optional=True,
21 doc="Maximum number of trial sky object positions\n"
22 "(default: nSkySources*nTrialSkySourcesMultiplier)")
23 nTrialSourcesMultiplier = Field(dtype=int, default=5,
24 doc="Set nTrialSkySources to\n"
25 " nSkySources*nTrialSkySourcesMultiplier\n"
26 "if nTrialSkySources is None")
27
28
29def generateSkyObjects(mask, seed, config):
30 """Generate a list of Footprints of sky objects
31
32 Sky objects don't overlap with other objects. This is determined
33 through the provided `mask` (in which objects are typically flagged
34 as `DETECTED`).
35
36 The algorithm for determining sky objects is random trial and error:
37 we try up to `nTrialSkySources` random positions to find `nSources`
38 sky objects.
39
40 Parameters
41 ----------
42 mask : `lsst.afw.image.Mask`
43 Input mask plane, which identifies pixels to avoid for the sky
44 objects.
45 seed : `int`
46 Random number generator seed.
47 config : `SkyObjectsConfig`
48 Configuration for finding sky objects.
49
50 Returns
51 -------
52 skyFootprints : `list` of `lsst.afw.detection.Footprint`
53 Footprints of sky objects. Each will have a peak at the center
54 of the sky object.
55 """
56 if config.nSources <= 0:
57 return []
58
59 skySourceRadius = config.sourceRadius
60 nSkySources = config.nSources
61 nTrialSkySources = config.nTrialSources
62 if nTrialSkySources is None:
63 nTrialSkySources = config.nTrialSourcesMultiplier*nSkySources
64
65 box = mask.getBBox()
66 box.grow(-(int(skySourceRadius) + 1)) # Avoid objects partially off the image
67 xMin, yMin = box.getMin()
68 xMax, yMax = box.getMax()
69
70 avoid = lsst.afw.geom.SpanSet.fromMask(mask, mask.getPlaneBitMask(config.avoidMask))
71 if config.growMask > 0:
72 avoid = avoid.dilated(config.growMask)
73
74 rng = lsst.afw.math.Random(seed=seed)
75
76 skyFootprints = []
77 for _ in range(nTrialSkySources):
78 if len(skyFootprints) == nSkySources:
79 break
80
81 x = int(rng.flat(xMin, xMax))
82 y = int(rng.flat(yMin, yMax))
83 spans = lsst.afw.geom.SpanSet.fromShape(int(skySourceRadius), offset=(x, y))
84 if spans.overlaps(avoid):
85 continue
86
87 fp = lsst.afw.detection.Footprint(spans, mask.getBBox())
88 fp.addPeak(x, y, 0)
89 skyFootprints.append(fp)
90
91 return skyFootprints
92
93
94class SkyObjectsTask(Task):
95 """Generate a list of Footprints of sky objects.
96 """
97 ConfigClass = SkyObjectsConfig
98
99 def run(self, mask, seed):
100 """Generate a list of Footprints of sky objects
101
102 Sky objects don't overlap with other objects. This is determined
103 through the provided `mask` (in which objects are typically flagged
104 as `DETECTED`).
105
106 The algorithm for determining sky objects is random trial and error:
107 we try up to `nTrialSkySources` random positions to find `nSources`
108 sky objects.
109
110 Parameters
111 ----------
112 mask : `lsst.afw.image.Mask`
113 Input mask plane, which identifies pixels to avoid for the sky
114 objects.
115 seed : `int`
116 Random number generator seed.
117
118 Returns
119 -------
120 skyFootprints : `list` of `lsst.afw.detection.Footprint`
121 Footprints of sky objects. Each will have a peak at the center
122 of the sky object.
123 """
124 skyFootprints = generateSkyObjects(mask, seed, self.config)
125 self.log.info("Added %d of %d requested sky sources (%.0f%%)", len(skyFootprints),
126 self.config.nSources, 100*len(skyFootprints)/self.config.nSources)
127 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
Represent a 2-dimensional array of bitmask pixels.
Definition: Mask.h:77
A class that can be used to generate sequences of random numbers according to a number of different a...
Definition: Random.h:57
def generateSkyObjects(mask, seed, config)
Definition: skyObjects.py:29