class CullPeaksConfig(Config):
"""!
@anchor CullPeaksConfig_
@brief Configuration for culling garbage peaks after merging footprints.
Peaks may also be culled after detection or during deblending; this configuration object
only deals with culling after merging Footprints.
These cuts are based on three quantities:
- nBands: the number of bands in which the peak was detected
- peakRank: the position of the peak within its family, sorted from brightest to faintest.
- peakRankNormalized: the peak rank divided by the total number of peaks in the family.
The formula that identifie peaks to cull is:
nBands < nBandsSufficient
AND (rank >= rankSufficient)
AND (rank >= rankConsider OR rank >= rankNormalizedConsider)
To disable peak culling, simply set nBandsSufficient=1.
"""
nBandsSufficient = RangeField(dtype=int, default=2, min=1,
doc="Always keep peaks detected in this many bands")
rankSufficient = RangeField(dtype=int, default=20, min=1,
doc="Always keep this many peaks in each family")
rankConsidered = RangeField(dtype=int, default=30, min=1,
doc=("Keep peaks with less than this rank that also match the "
"rankNormalizedConsidered condition."))
rankNormalizedConsidered = RangeField(dtype=float, default=0.7, min=0.0,
doc=("Keep peaks with less than this normalized rank that"
" also match the rankConsidered condition."))
class BackgroundConfig(Config):
"""Configuration for background measurement"""
statistic = ChoiceField(dtype=str, default="MEANCLIP", doc="type of statistic to use for grid points",
allowed={"MEANCLIP": "clipped mean",
"MEAN": "unclipped mean",
"MEDIAN": "median",})
xBinSize = RangeField(dtype=int, default=32, min=1, doc="Superpixel size in x")
yBinSize = RangeField(dtype=int, default=32, min=1, doc="Superpixel size in y")
algorithm = ChoiceField(dtype=str, default="NATURAL_SPLINE", optional=True,
doc="How to interpolate the background values. "
"This maps to an enum; see afw::math::Background",
allowed={
"CONSTANT": "Use a single constant value",
"LINEAR": "Use linear interpolation",
"NATURAL_SPLINE": "cubic spline with zero second derivative at endpoints",
"AKIMA_SPLINE": "higher-level nonlinear spline that is more robust to outliers",
"NONE": "No background estimation is to be attempted",
})
mask = ListField(dtype=str, default=["SAT", "BAD", "EDGE", "DETECTED", "DETECTED_NEGATIVE", "NO_DATA",],
doc="Names of mask planes to ignore while estimating the background")
class ANetBasicAstrometryConfig(LoadAstrometryNetObjectsTask.ConfigClass):
maxCpuTime = RangeField(
doc="Maximum CPU time to spend solving, in seconds",
dtype=float,
default=0.,
min=0.,
)
matchThreshold = RangeField(
doc="Matching threshold for Astrometry.net solver (log-odds)",
dtype=float,
default=math.log(1e12),
min=math.log(1e6),
)
maxStars = RangeField(
doc="Maximum number of stars to use in Astrometry.net solving",
dtype=int,
default=50,
min=10,
)
useWcsPixelScale = Field(
doc="Use the pixel scale from the input exposure\'s WCS headers?",
dtype=bool,
default=True,
)
useWcsRaDecCenter = Field(
doc=
"Use the RA,Dec center information from the input exposure\'s WCS headers?",
dtype=bool,
default=True,
)
useWcsParity = Field(
doc=
"Use the parity (flip / handedness) of the image from the input exposure\'s WCS headers?",
dtype=bool,
default=True,
)
raDecSearchRadius = RangeField(
doc=
"When useWcsRaDecCenter=True, this is the radius, in degrees, around the RA,Dec center "
+ "specified in the input exposure\'s WCS to search for a solution.",
dtype=float,
default=1.0,
min=0.0,
)
pixelScaleUncertainty = RangeField(
doc=
"Range of pixel scales, around the value in the WCS header, to search. "
+ "If the value of this field is X and the nominal scale is S, " +
"the range searched will be S/X to S*X",
dtype=float,
default=1.1,
min=1.001,
)
catalogMatchDist = RangeField(
doc=
"Matching radius (arcsec) for matching sources to reference objects",
dtype=float,
default=1.0,
min=0.0,
)
cleaningParameter = RangeField(
doc="Sigma-clipping parameter in sip/cleanBadPoints.py",
dtype=float,
default=3.0,
min=0.0,
)
calculateSip = Field(
doc="Compute polynomial SIP distortion terms?",
dtype=bool,
default=True,
)
sipOrder = RangeField(
doc="Polynomial order of SIP distortion terms",
dtype=int,
default=4,
min=2,
)
badFlags = ListField(
doc="List of flags which cause a source to be rejected as bad",
dtype=str,
default=[
"slot_Centroid_flag", # bad centroids
"base_PixelFlags_flag_edge",
"base_PixelFlags_flag_saturated",
"base_PixelFlags_flag_crCenter", # cosmic rays
],
)
allFluxes = Field(
doc="Retrieve all available fluxes (and errors) from catalog?",
dtype=bool,
default=True,
)
maxIter = RangeField(
doc="maximum number of iterations of match sources and fit WCS" +
"ignored if not fitting a WCS",
dtype=int,
default=5,
min=1,
)
matchDistanceSigma = RangeField(
doc="The match and fit loop stops when maxMatchDist minimized: "
" maxMatchDist = meanMatchDist + matchDistanceSigma*stdDevMatchDistance "
+
" (where the mean and std dev are computed using outlier rejection);" +
" ignored if not fitting a WCS",
dtype=float,
default=2,
min=0,
)