2 __all__ = [
"SkyObjectsConfig",
"SkyObjectsTask",
"generateSkyObjects"]
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")
30 """Generate a list of Footprints of sky objects 32 Sky objects don't overlap with other objects. This is determined 33 through the provided `mask` (in which objects are typically flagged 36 The algorithm for determining sky objects is random trial and error: 37 we try up to `nTrialSkySources` random positions to find `nSources` 42 mask : `lsst.afw.image.Mask` 43 Input mask plane, which identifies pixels to avoid for the sky 46 Random number generator seed. 47 config : `SkyObjectsConfig` 48 Configuration for finding sky objects. 52 skyFootprints : `list` of `lsst.afw.detection.Footprint` 53 Footprints of sky objects. Each will have a peak at the center 56 if config.nSources <= 0:
59 skySourceRadius = config.sourceRadius
60 nSkySources = config.nSources
61 nTrialSkySources = config.nTrialSources
62 if nTrialSkySources
is None:
63 nTrialSkySources = config.nTrialSourcesMultiplier*nSkySources
66 box.grow(-(
int(skySourceRadius) + 1))
67 xMin, yMin = box.getMin()
68 xMax, yMax = box.getMax()
71 if config.growMask > 0:
72 avoid = avoid.dilated(config.growMask)
77 for _
in range(nTrialSkySources):
78 if len(skyFootprints) == nSkySources:
81 x =
int(rng.flat(xMin, xMax))
82 y =
int(rng.flat(yMin, yMax))
84 if spans.overlaps(avoid):
89 skyFootprints.append(fp)
95 ConfigClass = SkyObjectsConfig
97 def run(self, mask, seed):
98 """Generate a list of Footprints of sky objects 100 Sky objects don't overlap with other objects. This is determined 101 through the provided `mask` (in which objects are typically flagged 104 The algorithm for determining sky objects is random trial and error: 105 we try up to `nTrialSkySources` random positions to find `nSources` 110 mask : `lsst.afw.image.Mask` 111 Input mask plane, which identifies pixels to avoid for the sky 114 Random number generator seed. 118 skyFootprints : `list` of `lsst.afw.detection.Footprint` 119 Footprints of sky objects. Each will have a peak at the center 123 self.
log.
info(
"Added %d of %d requested sky sources (%.0f%%)", len(skyFootprints),
124 self.
config.nSources, 100*len(skyFootprints)/self.
config.nSources)
static std::shared_ptr< geom::SpanSet > fromMask(image::Mask< T > const &mask, UnaryPredicate comparator=details::AnyBitSetFunctor< T >())
Create a SpanSet from a mask.
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.
def run(self, mask, seed)
def generateSkyObjects(mask, seed, config)
A class that can be used to generate sequences of random numbers according to a number of different a...