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DM-53634: change metric connections to run in AP daytime pipeline #448

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Merged
isullivan merged 2 commits into from
Jan 15, 2026
Merged

DM-53634: change metric connections to run in AP daytime pipeline #448

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78500d4
Remove matchedTemplate from spatially sampled metrics
isullivan Dec 16, 2025
d817f60
Switch spatial metrics to use final filtered diaSource catalog
isullivan Dec 17, 2025
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31 changes: 10 additions & 21 deletions python/lsst/ip/diffim/computeSpatiallySampledMetrics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -48,12 +48,6 @@ class SpatiallySampledMetricsConnections(pipeBase.PipelineTaskConnections,
storageClass="ExposureF",
name="{fakesType}calexp"
)
matchedTemplate = pipeBase.connectionTypes.Input(
doc="Warped and PSF-matched template used to create the difference image.",
dimensions=("instrument", "visit", "detector"),
storageClass="ExposureF",
name="{fakesType}{coaddName}Diff_matchedExp",
)
template = pipeBase.connectionTypes.Input(
doc="Warped and not PSF-matched template used to create the difference image.",
dimensions=("instrument", "visit", "detector"),
Expand All @@ -69,8 +63,8 @@ class SpatiallySampledMetricsConnections(pipeBase.PipelineTaskConnections,
diaSources = pipeBase.connectionTypes.Input(
doc="Filtered diaSources on the difference image.",
dimensions=("instrument", "visit", "detector"),
storageClass="SourceCatalog",
name="{fakesType}{coaddName}Diff_candidateDiaSrc",
storageClass="ArrowAstropy",
name="{fakesType}dia_source_detector",
)
psfMatchingKernel = pipeBase.connectionTypes.Input(
doc="Kernel used to PSF match the science and template images.",
Expand Down Expand Up @@ -195,16 +189,13 @@ def __init__(self, **kwargs):
units="radian")

@timeMethod
def run(self, science, matchedTemplate, template, difference, diaSources, psfMatchingKernel):
def run(self, science, template, difference, diaSources, psfMatchingKernel):
"""Calculate difference image metrics on specific locations across the images

Parameters
----------
science : `lsst.afw.image.ExposureF`
Science exposure that the template was subtracted from.
matchedTemplate : `lsst.afw.image.ExposureF`
Warped and PSF-matched template that was used produce the
difference image.
template : `lsst.afw.image.ExposureF`
Warped and non PSF-matched template that was used produce
the difference image.
Expand Down Expand Up @@ -237,13 +228,13 @@ def run(self, science, matchedTemplate, template, difference, diaSources, psfMat
self.log.info("Unable to calculate metrics for mask plane %s: not in image"%maskPlane)

for src in spatiallySampledMetrics:
self._evaluateLocalMetric(src, science, matchedTemplate, template, difference, diaSources,
self._evaluateLocalMetric(src, science, template, difference, diaSources,
metricsMaskPlanes=metricsMaskPlanes,
psfMatchingKernel=psfMatchingKernel)

return pipeBase.Struct(spatiallySampledMetrics=spatiallySampledMetrics.asAstropy())

def _evaluateLocalMetric(self, src, science, matchedTemplate, template, difference, diaSources,
def _evaluateLocalMetric(self, src, science, template, difference, diaSources,
metricsMaskPlanes, psfMatchingKernel):
"""Calculate image quality metrics at spatially sampled locations.

Expand All @@ -255,8 +246,6 @@ def _evaluateLocalMetric(self, src, science, matchedTemplate, template, differen
The catalog of detected sources.
science : `lsst.afw.image.Exposure`
The science image.
matchedTemplate : `lsst.afw.image.Exposure`
The reference image, warped and psf-matched to the science image.
difference : `lsst.afw.image.Exposure`
Result of subtracting template from the science image.
metricsMaskPlanes : `list` of `str`
Expand All @@ -282,18 +271,18 @@ def _evaluateLocalMetric(self, src, science, matchedTemplate, template, differen
src.set('x', peak['i_x'])
src.set('y', peak['i_y'])
src.setCoord(science.wcs.pixelToSky(peak['i_x'], peak['i_y']))
selectSources = diaSources[bbox.contains(diaSources.getX(), diaSources.getY())]
selectSources = diaSources[bbox.contains(diaSources['x'], diaSources['y'])]
sourceDensity = len(selectSources)/area
dipoleSources = selectSources[selectSources["ip_diffim_DipoleFit_classification"]]
dipoleSources = selectSources[selectSources["isDipole"]]
dipoleDensity = len(dipoleSources)/area

if dipoleSources:
meanDipoleOrientation = angleMean(dipoleSources["ip_diffim_DipoleFit_orientation"])
meanDipoleOrientation = angleMean(dipoleSources["dipoleAngle"])
src.set('dipole_direction', meanDipoleOrientation)
meanDipoleSeparation = np.mean(dipoleSources["ip_diffim_DipoleFit_separation"])
meanDipoleSeparation = np.mean(dipoleSources["dipoleLength"])
src.set('dipole_separation', meanDipoleSeparation)

templateVal = np.median(matchedTemplate[bbox].image.array)
templateVal = np.median(template[bbox].image.array)
scienceVal = np.median(science[bbox].image.array)
diffimVal = np.median(difference[bbox].image.array)
src.set('source_density', sourceDensity)
Expand Down