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#!/usr/bin/env python 

# 

# LSST Data Management System 

# Copyright 2008-2015 AURA/LSST. 

# 

# This product includes software developed by the 

# LSST Project (http://www.lsst.org/). 

# 

# This program is free software: you can redistribute it and/or modify 

# it under the terms of the GNU General Public License as published by 

# the Free Software Foundation, either version 3 of the License, or 

# (at your option) any later version. 

# 

# This program is distributed in the hope that it will be useful, 

# but WITHOUT ANY WARRANTY; without even the implied warranty of 

# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 

# GNU General Public License for more details. 

# 

# You should have received a copy of the LSST License Statement and 

# the GNU General Public License along with this program. If not, 

# see <https://www.lsstcorp.org/LegalNotices/>. 

# 

import numpy 

 

from lsst.coadd.utils.coaddDataIdContainer import ExistingCoaddDataIdContainer 

from lsst.pipe.base import CmdLineTask, Struct, TaskRunner, ArgumentParser, ButlerInitializedTaskRunner 

from lsst.pex.config import Config, Field, ListField, ConfigurableField, RangeField, ConfigField 

from lsst.meas.algorithms import DynamicDetectionTask, SkyObjectsTask 

from lsst.meas.base import SingleFrameMeasurementTask, ApplyApCorrTask, CatalogCalculationTask 

from lsst.meas.deblender import SourceDeblendTask 

from lsst.pipe.tasks.coaddBase import getSkyInfo 

from lsst.pipe.tasks.scaleVariance import ScaleVarianceTask 

from lsst.meas.astrom import DirectMatchTask, denormalizeMatches 

from lsst.pipe.tasks.fakes import BaseFakeSourcesTask 

from lsst.pipe.tasks.setPrimaryFlags import SetPrimaryFlagsTask 

from lsst.pipe.tasks.propagateVisitFlags import PropagateVisitFlagsTask 

import lsst.afw.image as afwImage 

import lsst.afw.table as afwTable 

import lsst.afw.math as afwMath 

import lsst.afw.detection as afwDetect 

from lsst.daf.base import PropertyList 

 

""" 

New dataset types: 

* deepCoadd_det: detections from what used to be processCoadd (tract, patch, filter) 

* deepCoadd_mergeDet: merged detections (tract, patch) 

* deepCoadd_meas: measurements of merged detections (tract, patch, filter) 

* deepCoadd_ref: reference sources (tract, patch) 

All of these have associated *_schema catalogs that require no data ID and hold no records. 

 

In addition, we have a schema-only dataset, which saves the schema for the PeakRecords in 

the mergeDet, meas, and ref dataset Footprints: 

* deepCoadd_peak_schema 

""" 

 

 

def _makeGetSchemaCatalogs(datasetSuffix): 

"""Construct a getSchemaCatalogs instance method 

 

These are identical for most of the classes here, so we'll consolidate 

the code. 

 

datasetSuffix: Suffix of dataset name, e.g., "src" for "deepCoadd_src" 

""" 

 

def getSchemaCatalogs(self): 

"""Return a dict of empty catalogs for each catalog dataset produced by this task.""" 

src = afwTable.SourceCatalog(self.schema) 

if hasattr(self, "algMetadata"): 

src.getTable().setMetadata(self.algMetadata) 

return {self.config.coaddName + "Coadd_" + datasetSuffix: src} 

return getSchemaCatalogs 

 

 

def _makeMakeIdFactory(datasetName): 

"""Construct a makeIdFactory instance method 

 

These are identical for all the classes here, so this consolidates 

the code. 

 

datasetName: Dataset name without the coadd name prefix, e.g., "CoaddId" for "deepCoaddId" 

""" 

 

def makeIdFactory(self, dataRef): 

"""Return an IdFactory for setting the detection identifiers 

 

The actual parameters used in the IdFactory are provided by 

the butler (through the provided data reference. 

""" 

expBits = dataRef.get(self.config.coaddName + datasetName + "_bits") 

expId = int(dataRef.get(self.config.coaddName + datasetName)) 

return afwTable.IdFactory.makeSource(expId, 64 - expBits) 

return makeIdFactory 

 

 

def getShortFilterName(name): 

"""Given a longer, camera-specific filter name (e.g. "HSC-I") return its shorthand name ("i"). 

""" 

# I'm not sure if this is the way this is supposed to be implemented, but it seems to work, 

# and its the only way I could get it to work. 

return afwImage.Filter(name).getFilterProperty().getName() 

 

 

############################################################################################################## 

 

class DetectCoaddSourcesConfig(Config): 

"""! 

@anchor DetectCoaddSourcesConfig_ 

 

@brief Configuration parameters for the DetectCoaddSourcesTask 

""" 

doScaleVariance = Field(dtype=bool, default=True, doc="Scale variance plane using empirical noise?") 

scaleVariance = ConfigurableField(target=ScaleVarianceTask, doc="Variance rescaling") 

detection = ConfigurableField(target=DynamicDetectionTask, doc="Source detection") 

coaddName = Field(dtype=str, default="deep", doc="Name of coadd") 

doInsertFakes = Field(dtype=bool, default=False, 

doc="Run fake sources injection task") 

insertFakes = ConfigurableField(target=BaseFakeSourcesTask, 

doc="Injection of fake sources for testing " 

"purposes (must be retargeted)") 

 

def setDefaults(self): 

Config.setDefaults(self) 

self.detection.thresholdType = "pixel_stdev" 

self.detection.isotropicGrow = True 

# Coadds are made from background-subtracted CCDs, so any background subtraction should be very basic 

self.detection.reEstimateBackground = False 

self.detection.background.useApprox = False 

self.detection.background.binSize = 4096 

self.detection.background.undersampleStyle = 'REDUCE_INTERP_ORDER' 

self.detection.doTempWideBackground = True # Suppress large footprints that overwhelm the deblender 

 

## @addtogroup LSST_task_documentation 

## @{ 

## @page DetectCoaddSourcesTask 

## @ref DetectCoaddSourcesTask_ "DetectCoaddSourcesTask" 

## @copybrief DetectCoaddSourcesTask 

## @} 

 

 

class DetectCoaddSourcesTask(CmdLineTask): 

"""! 

@anchor DetectCoaddSourcesTask_ 

 

@brief Detect sources on a coadd 

 

@section pipe_tasks_multiBand_Contents Contents 

 

- @ref pipe_tasks_multiBand_DetectCoaddSourcesTask_Purpose 

- @ref pipe_tasks_multiBand_DetectCoaddSourcesTask_Initialize 

- @ref pipe_tasks_multiBand_DetectCoaddSourcesTask_Run 

- @ref pipe_tasks_multiBand_DetectCoaddSourcesTask_Config 

- @ref pipe_tasks_multiBand_DetectCoaddSourcesTask_Debug 

- @ref pipe_tasks_multiband_DetectCoaddSourcesTask_Example 

 

@section pipe_tasks_multiBand_DetectCoaddSourcesTask_Purpose Description 

 

Command-line task that detects sources on a coadd of exposures obtained with a single filter. 

 

Coadding individual visits requires each exposure to be warped. This introduces covariance in the noise 

properties across pixels. Before detection, we correct the coadd variance by scaling the variance plane 

in the coadd to match the observed variance. This is an approximate approach -- strictly, we should 

propagate the full covariance matrix -- but it is simple and works well in practice. 

 

After scaling the variance plane, we detect sources and generate footprints by delegating to the @ref 

SourceDetectionTask_ "detection" subtask. 

 

@par Inputs: 

deepCoadd{tract,patch,filter}: ExposureF 

@par Outputs: 

deepCoadd_det{tract,patch,filter}: SourceCatalog (only parent Footprints) 

@n deepCoadd_calexp{tract,patch,filter}: Variance scaled, background-subtracted input 

exposure (ExposureF) 

@n deepCoadd_calexp_background{tract,patch,filter}: BackgroundList 

@par Data Unit: 

tract, patch, filter 

 

DetectCoaddSourcesTask delegates most of its work to the @ref SourceDetectionTask_ "detection" subtask. 

You can retarget this subtask if you wish. 

 

@section pipe_tasks_multiBand_DetectCoaddSourcesTask_Initialize Task initialization 

 

@copydoc \_\_init\_\_ 

 

@section pipe_tasks_multiBand_DetectCoaddSourcesTask_Run Invoking the Task 

 

@copydoc run 

 

@section pipe_tasks_multiBand_DetectCoaddSourcesTask_Config Configuration parameters 

 

See @ref DetectCoaddSourcesConfig_ "DetectSourcesConfig" 

 

@section pipe_tasks_multiBand_DetectCoaddSourcesTask_Debug Debug variables 

 

The @link lsst.pipe.base.cmdLineTask.CmdLineTask command line task@endlink interface supports a 

flag @c -d to import @b debug.py from your @c PYTHONPATH; see @ref baseDebug for more about @b debug.py 

files. 

 

DetectCoaddSourcesTask has no debug variables of its own because it relegates all the work to 

@ref SourceDetectionTask_ "SourceDetectionTask"; see the documetation for 

@ref SourceDetectionTask_ "SourceDetectionTask" for further information. 

 

@section pipe_tasks_multiband_DetectCoaddSourcesTask_Example A complete example 

of using DetectCoaddSourcesTask 

 

DetectCoaddSourcesTask is meant to be run after assembling a coadded image in a given band. The purpose of 

the task is to update the background, detect all sources in a single band and generate a set of parent 

footprints. Subsequent tasks in the multi-band processing procedure will merge sources across bands and, 

eventually, perform forced photometry. Command-line usage of DetectCoaddSourcesTask expects a data 

reference to the coadd to be processed. A list of the available optional arguments can be obtained by 

calling detectCoaddSources.py with the `--help` command line argument: 

@code 

detectCoaddSources.py --help 

@endcode 

 

To demonstrate usage of the DetectCoaddSourcesTask in the larger context of multi-band processing, we 

will process HSC data in the [ci_hsc](https://github.com/lsst/ci_hsc) package. Assuming one has followed 

steps 1 - 4 at @ref pipeTasks_multiBand, one may detect all the sources in each coadd as follows: 

@code 

detectCoaddSources.py $CI_HSC_DIR/DATA --id patch=5,4 tract=0 filter=HSC-I 

@endcode 

that will process the HSC-I band data. The results are written to 

`$CI_HSC_DIR/DATA/deepCoadd-results/HSC-I`. 

 

It is also necessary to run: 

@code 

detectCoaddSources.py $CI_HSC_DIR/DATA --id patch=5,4 tract=0 filter=HSC-R 

@endcode 

to generate the sources catalogs for the HSC-R band required by the next step in the multi-band 

processing procedure: @ref MergeDetectionsTask_ "MergeDetectionsTask". 

""" 

_DefaultName = "detectCoaddSources" 

ConfigClass = DetectCoaddSourcesConfig 

getSchemaCatalogs = _makeGetSchemaCatalogs("det") 

makeIdFactory = _makeMakeIdFactory("CoaddId") 

 

@classmethod 

def _makeArgumentParser(cls): 

parser = ArgumentParser(name=cls._DefaultName) 

parser.add_id_argument("--id", "deepCoadd", help="data ID, e.g. --id tract=12345 patch=1,2 filter=r", 

ContainerClass=ExistingCoaddDataIdContainer) 

return parser 

 

def __init__(self, schema=None, **kwargs): 

"""! 

@brief Initialize the task. Create the @ref SourceDetectionTask_ "detection" subtask. 

 

Keyword arguments (in addition to those forwarded to CmdLineTask.__init__): 

 

@param[in] schema: initial schema for the output catalog, modified-in place to include all 

fields set by this task. If None, the source minimal schema will be used. 

@param[in] **kwargs: keyword arguments to be passed to lsst.pipe.base.task.Task.__init__ 

""" 

CmdLineTask.__init__(self, **kwargs) 

if schema is None: 

schema = afwTable.SourceTable.makeMinimalSchema() 

if self.config.doInsertFakes: 

self.makeSubtask("insertFakes") 

self.schema = schema 

self.makeSubtask("detection", schema=self.schema) 

if self.config.doScaleVariance: 

self.makeSubtask("scaleVariance") 

 

def runDataRef(self, patchRef): 

"""! 

@brief Run detection on a coadd. 

 

Invokes @ref run and then uses @ref write to output the 

results. 

 

@param[in] patchRef: data reference for patch 

""" 

exposure = patchRef.get(self.config.coaddName + "Coadd", immediate=True) 

expId = int(patchRef.get(self.config.coaddName + "CoaddId")) 

results = self.run(exposure, self.makeIdFactory(patchRef), expId=expId) 

self.write(exposure, results, patchRef) 

return results 

 

def run(self, exposure, idFactory, expId): 

"""! 

@brief Run detection on an exposure. 

 

First scale the variance plane to match the observed variance 

using @ref ScaleVarianceTask. Then invoke the @ref SourceDetectionTask_ "detection" subtask to 

detect sources. 

 

@param[in,out] exposure: Exposure on which to detect (may be backround-subtracted and scaled, 

depending on configuration). 

@param[in] idFactory: IdFactory to set source identifiers 

@param[in] expId: Exposure identifier (integer) for RNG seed 

 

@return a pipe.base.Struct with fields 

- sources: catalog of detections 

- backgrounds: list of backgrounds 

""" 

if self.config.doScaleVariance: 

varScale = self.scaleVariance.run(exposure.maskedImage) 

exposure.getMetadata().add("variance_scale", varScale) 

backgrounds = afwMath.BackgroundList() 

if self.config.doInsertFakes: 

self.insertFakes.run(exposure, background=backgrounds) 

table = afwTable.SourceTable.make(self.schema, idFactory) 

detections = self.detection.makeSourceCatalog(table, exposure, expId=expId) 

sources = detections.sources 

fpSets = detections.fpSets 

if hasattr(fpSets, "background") and fpSets.background: 

for bg in fpSets.background: 

backgrounds.append(bg) 

return Struct(sources=sources, backgrounds=backgrounds) 

 

def write(self, exposure, results, patchRef): 

"""! 

@brief Write out results from runDetection. 

 

@param[in] exposure: Exposure to write out 

@param[in] results: Struct returned from runDetection 

@param[in] patchRef: data reference for patch 

""" 

coaddName = self.config.coaddName + "Coadd" 

patchRef.put(results.backgrounds, coaddName + "_calexp_background") 

patchRef.put(results.sources, coaddName + "_det") 

patchRef.put(exposure, coaddName + "_calexp") 

 

############################################################################################################## 

 

 

class MergeSourcesRunner(TaskRunner): 

"""! 

@anchor MergeSourcesRunner_ 

 

@brief Task runner for the @ref MergeSourcesTask_ "MergeSourcesTask". Required because the run method 

requires a list of dataRefs rather than a single dataRef. 

""" 

 

def makeTask(self, parsedCmd=None, args=None): 

"""! 

@brief Provide a butler to the Task constructor. 

 

@param[in] parsedCmd the parsed command 

@param[in] args tuple of a list of data references and kwargs (un-used) 

@throws RuntimeError if both parsedCmd & args are None 

""" 

if parsedCmd is not None: 

butler = parsedCmd.butler 

elif args is not None: 

dataRefList, kwargs = args 

butler = dataRefList[0].getButler() 

else: 

raise RuntimeError("Neither parsedCmd or args specified") 

return self.TaskClass(config=self.config, log=self.log, butler=butler) 

 

@staticmethod 

def getTargetList(parsedCmd, **kwargs): 

"""! 

@brief Provide a list of patch references for each patch. 

 

The patch references within the list will have different filters. 

 

@param[in] parsedCmd the parsed command 

@param **kwargs key word arguments (unused) 

@throws RuntimeError if multiple references are provided for the same combination of tract, patch and 

filter 

""" 

refList = {} # Will index this as refList[tract][patch][filter] = ref 

for ref in parsedCmd.id.refList: 

tract = ref.dataId["tract"] 

patch = ref.dataId["patch"] 

filter = ref.dataId["filter"] 

if tract not in refList: 

refList[tract] = {} 

if patch not in refList[tract]: 

refList[tract][patch] = {} 

if filter in refList[tract][patch]: 

raise RuntimeError("Multiple versions of %s" % (ref.dataId,)) 

refList[tract][patch][filter] = ref 

return [(list(p.values()), kwargs) for t in refList.values() for p in t.values()] 

 

 

class MergeSourcesConfig(Config): 

"""! 

@anchor MergeSourcesConfig_ 

 

@brief Configuration for merging sources. 

""" 

priorityList = ListField(dtype=str, default=[], 

doc="Priority-ordered list of bands for the merge.") 

coaddName = Field(dtype=str, default="deep", doc="Name of coadd") 

 

def validate(self): 

Config.validate(self) 

if len(self.priorityList) == 0: 

raise RuntimeError("No priority list provided") 

 

 

class MergeSourcesTask(CmdLineTask): 

"""! 

@anchor MergeSourcesTask_ 

 

@brief A base class for merging source catalogs. 

 

Merging detections (MergeDetectionsTask) and merging measurements (MergeMeasurementsTask) are 

so similar that it makes sense to re-use the code, in the form of this abstract base class. 

 

NB: Do not use this class directly. Instead use one of the child classes that inherit from 

MergeSourcesTask such as @ref MergeDetectionsTask_ "MergeDetectionsTask" or @ref MergeMeasurementsTask_ 

"MergeMeasurementsTask" 

 

Sub-classes should set the following class variables: 

* `_DefaultName`: name of Task 

* `inputDataset`: name of dataset to read 

* `outputDataset`: name of dataset to write 

* `getSchemaCatalogs` to the result of `_makeGetSchemaCatalogs(outputDataset)` 

 

In addition, sub-classes must implement the run method. 

""" 

_DefaultName = None 

ConfigClass = MergeSourcesConfig 

RunnerClass = MergeSourcesRunner 

inputDataset = None 

outputDataset = None 

getSchemaCatalogs = None 

 

@classmethod 

def _makeArgumentParser(cls): 

"""! 

@brief Create a suitable ArgumentParser. 

 

We will use the ArgumentParser to get a provide a list of data 

references for patches; the RunnerClass will sort them into lists 

of data references for the same patch 

""" 

parser = ArgumentParser(name=cls._DefaultName) 

parser.add_id_argument("--id", "deepCoadd_" + cls.inputDataset, 

ContainerClass=ExistingCoaddDataIdContainer, 

help="data ID, e.g. --id tract=12345 patch=1,2 filter=g^r^i") 

return parser 

 

def getInputSchema(self, butler=None, schema=None): 

"""! 

@brief Obtain the input schema either directly or froma butler reference. 

 

@param[in] butler butler reference to obtain the input schema from 

@param[in] schema the input schema 

""" 

if schema is None: 

assert butler is not None, "Neither butler nor schema specified" 

schema = butler.get(self.config.coaddName + "Coadd_" + self.inputDataset + "_schema", 

immediate=True).schema 

return schema 

 

def __init__(self, butler=None, schema=None, **kwargs): 

"""! 

@brief Initialize the task. 

 

Keyword arguments (in addition to those forwarded to CmdLineTask.__init__): 

@param[in] schema the schema of the detection catalogs used as input to this one 

@param[in] butler a butler used to read the input schema from disk, if schema is None 

 

Derived classes should use the getInputSchema() method to handle the additional 

arguments and retreive the actual input schema. 

""" 

CmdLineTask.__init__(self, **kwargs) 

 

def runDataRef(self, patchRefList): 

"""! 

@brief Merge coadd sources from multiple bands. Calls @ref `run` which must be defined in 

subclasses that inherit from MergeSourcesTask. 

 

@param[in] patchRefList list of data references for each filter 

""" 

catalogs = dict(self.readCatalog(patchRef) for patchRef in patchRefList) 

mergedCatalog = self.run(catalogs, patchRefList[0]) 

self.write(patchRefList[0], mergedCatalog) 

 

def readCatalog(self, patchRef): 

"""! 

@brief Read input catalog. 

 

We read the input dataset provided by the 'inputDataset' 

class variable. 

 

@param[in] patchRef data reference for patch 

@return tuple consisting of the filter name and the catalog 

""" 

filterName = patchRef.dataId["filter"] 

catalog = patchRef.get(self.config.coaddName + "Coadd_" + self.inputDataset, immediate=True) 

self.log.info("Read %d sources for filter %s: %s" % (len(catalog), filterName, patchRef.dataId)) 

return filterName, catalog 

 

def run(self, catalogs, patchRef): 

"""! 

@brief Merge multiple catalogs. This function must be defined in all subclasses that inherit from 

MergeSourcesTask. 

 

@param[in] catalogs dict mapping filter name to source catalog 

 

@return merged catalog 

""" 

raise NotImplementedError() 

 

def write(self, patchRef, catalog): 

"""! 

@brief Write the output. 

 

@param[in] patchRef data reference for patch 

@param[in] catalog catalog 

 

We write as the dataset provided by the 'outputDataset' 

class variable. 

""" 

patchRef.put(catalog, self.config.coaddName + "Coadd_" + self.outputDataset) 

# since the filter isn't actually part of the data ID for the dataset we're saving, 

# it's confusing to see it in the log message, even if the butler simply ignores it. 

mergeDataId = patchRef.dataId.copy() 

del mergeDataId["filter"] 

self.log.info("Wrote merged catalog: %s" % (mergeDataId,)) 

 

def writeMetadata(self, dataRefList): 

"""! 

@brief No metadata to write, and not sure how to write it for a list of dataRefs. 

""" 

pass 

 

 

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 MergeDetectionsConfig(MergeSourcesConfig): 

"""! 

@anchor MergeDetectionsConfig_ 

 

@brief Configuration parameters for the MergeDetectionsTask. 

""" 

minNewPeak = Field(dtype=float, default=1, 

doc="Minimum distance from closest peak to create a new one (in arcsec).") 

 

maxSamePeak = Field(dtype=float, default=0.3, 

doc="When adding new catalogs to the merge, all peaks less than this distance " 

" (in arcsec) to an existing peak will be flagged as detected in that catalog.") 

cullPeaks = ConfigField(dtype=CullPeaksConfig, doc="Configuration for how to cull peaks.") 

 

skyFilterName = Field(dtype=str, default="sky", 

doc="Name of `filter' used to label sky objects (e.g. flag merge_peak_sky is set)\n" 

"(N.b. should be in MergeMeasurementsConfig.pseudoFilterList)") 

skyObjects = ConfigurableField(target=SkyObjectsTask, doc="Generate sky objects") 

 

def setDefaults(self): 

MergeSourcesConfig.setDefaults(self) 

self.skyObjects.avoidMask = ["DETECTED"] # Nothing else is available in our custom mask 

 

 

## @addtogroup LSST_task_documentation 

## @{ 

## @page MergeDetectionsTask 

## @ref MergeDetectionsTask_ "MergeDetectionsTask" 

## @copybrief MergeDetectionsTask 

## @} 

 

 

class MergeDetectionsTask(MergeSourcesTask): 

"""! 

@anchor MergeDetectionsTask_ 

 

@brief Merge coadd detections from multiple bands. 

 

@section pipe_tasks_multiBand_Contents Contents 

 

- @ref pipe_tasks_multiBand_MergeDetectionsTask_Purpose 

- @ref pipe_tasks_multiBand_MergeDetectionsTask_Init 

- @ref pipe_tasks_multiBand_MergeDetectionsTask_Run 

- @ref pipe_tasks_multiBand_MergeDetectionsTask_Config 

- @ref pipe_tasks_multiBand_MergeDetectionsTask_Debug 

- @ref pipe_tasks_multiband_MergeDetectionsTask_Example 

 

@section pipe_tasks_multiBand_MergeDetectionsTask_Purpose Description 

 

Command-line task that merges sources detected in coadds of exposures obtained with different filters. 

 

To perform photometry consistently across coadds in multiple filter bands, we create a master catalog of 

sources from all bands by merging the sources (peaks & footprints) detected in each coadd, while keeping 

track of which band each source originates in. 

 

The catalog merge is performed by @ref getMergedSourceCatalog. Spurious peaks detected around bright 

objects are culled as described in @ref CullPeaksConfig_. 

 

@par Inputs: 

deepCoadd_det{tract,patch,filter}: SourceCatalog (only parent Footprints) 

@par Outputs: 

deepCoadd_mergeDet{tract,patch}: SourceCatalog (only parent Footprints) 

@par Data Unit: 

tract, patch 

 

MergeDetectionsTask subclasses @ref MergeSourcesTask_ "MergeSourcesTask". 

 

@section pipe_tasks_multiBand_MergeDetectionsTask_Init Task initialisation 

 

@copydoc \_\_init\_\_ 

 

@section pipe_tasks_multiBand_MergeDetectionsTask_Run Invoking the Task 

 

@copydoc run 

 

@section pipe_tasks_multiBand_MergeDetectionsTask_Config Configuration parameters 

 

See @ref MergeDetectionsConfig_ 

 

@section pipe_tasks_multiBand_MergeDetectionsTask_Debug Debug variables 

 

The @link lsst.pipe.base.cmdLineTask.CmdLineTask command line task@endlink interface supports a flag @c -d 

to import @b debug.py from your @c PYTHONPATH; see @ref baseDebug for more about @b debug.py files. 

 

MergeDetectionsTask has no debug variables. 

 

@section pipe_tasks_multiband_MergeDetectionsTask_Example A complete example of using MergeDetectionsTask 

 

MergeDetectionsTask is meant to be run after detecting sources in coadds generated for the chosen subset 

of the available bands. 

The purpose of the task is to merge sources (peaks & footprints) detected in the coadds generated from the 

chosen subset of filters. 

Subsequent tasks in the multi-band processing procedure will deblend the generated master list of sources 

and, eventually, perform forced photometry. 

Command-line usage of MergeDetectionsTask expects data references for all the coadds to be processed. 

A list of the available optional arguments can be obtained by calling mergeCoaddDetections.py with the 

`--help` command line argument: 

@code 

mergeCoaddDetections.py --help 

@endcode 

 

To demonstrate usage of the DetectCoaddSourcesTask in the larger context of multi-band processing, we 

will process HSC data in the [ci_hsc](https://github.com/lsst/ci_hsc) package. Assuming one has finished 

step 5 at @ref pipeTasks_multiBand, one may merge the catalogs of sources from each coadd as follows: 

@code 

mergeCoaddDetections.py $CI_HSC_DIR/DATA --id patch=5,4 tract=0 filter=HSC-I^HSC-R 

@endcode 

This will merge the HSC-I & -R band parent source catalogs and write the results to 

`$CI_HSC_DIR/DATA/deepCoadd-results/merged/0/5,4/mergeDet-0-5,4.fits`. 

 

The next step in the multi-band processing procedure is 

@ref MeasureMergedCoaddSourcesTask_ "MeasureMergedCoaddSourcesTask" 

""" 

ConfigClass = MergeDetectionsConfig 

_DefaultName = "mergeCoaddDetections" 

inputDataset = "det" 

outputDataset = "mergeDet" 

makeIdFactory = _makeMakeIdFactory("MergedCoaddId") 

 

def __init__(self, butler=None, schema=None, **kwargs): 

"""! 

@brief Initialize the merge detections task. 

 

A @ref FootprintMergeList_ "FootprintMergeList" will be used to 

merge the source catalogs. 

 

Additional keyword arguments (forwarded to MergeSourcesTask.__init__): 

@param[in] schema the schema of the detection catalogs used as input to this one 

@param[in] butler a butler used to read the input schema from disk, if schema is None 

@param[in] **kwargs keyword arguments to be passed to MergeSourcesTask.__init__ 

 

The task will set its own self.schema attribute to the schema of the output merged catalog. 

""" 

MergeSourcesTask.__init__(self, butler=butler, schema=schema, **kwargs) 

self.makeSubtask("skyObjects") 

self.schema = self.getInputSchema(butler=butler, schema=schema) 

 

filterNames = [getShortFilterName(name) for name in self.config.priorityList] 

filterNames += [self.config.skyFilterName] 

self.merged = afwDetect.FootprintMergeList(self.schema, filterNames) 

 

def run(self, catalogs, patchRef): 

"""! 

@brief Merge multiple catalogs. 

 

After ordering the catalogs and filters in priority order, 

@ref getMergedSourceCatalog of the @ref FootprintMergeList_ "FootprintMergeList" created by 

@ref \_\_init\_\_ is used to perform the actual merging. Finally, @ref cullPeaks is used to remove 

garbage peaks detected around bright objects. 

 

@param[in] catalogs 

@param[in] patchRef 

@param[out] mergedList 

""" 

 

# Convert distance to tract coordinate 

skyInfo = getSkyInfo(coaddName=self.config.coaddName, patchRef=patchRef) 

tractWcs = skyInfo.wcs 

peakDistance = self.config.minNewPeak / tractWcs.getPixelScale().asArcseconds() 

samePeakDistance = self.config.maxSamePeak / tractWcs.getPixelScale().asArcseconds() 

 

# Put catalogs, filters in priority order 

orderedCatalogs = [catalogs[band] for band in self.config.priorityList if band in catalogs.keys()] 

orderedBands = [getShortFilterName(band) for band in self.config.priorityList 

if band in catalogs.keys()] 

 

mergedList = self.merged.getMergedSourceCatalog(orderedCatalogs, orderedBands, peakDistance, 

self.schema, self.makeIdFactory(patchRef), 

samePeakDistance) 

 

# 

# Add extra sources that correspond to blank sky 

# 

skySeed = patchRef.get(self.config.coaddName + "MergedCoaddId") 

skySourceFootprints = self.getSkySourceFootprints(mergedList, skyInfo, skySeed) 

if skySourceFootprints: 

key = mergedList.schema.find("merge_footprint_%s" % self.config.skyFilterName).key 

for foot in skySourceFootprints: 

s = mergedList.addNew() 

s.setFootprint(foot) 

s.set(key, True) 

 

# Sort Peaks from brightest to faintest 

for record in mergedList: 

record.getFootprint().sortPeaks() 

self.log.info("Merged to %d sources" % len(mergedList)) 

# Attempt to remove garbage peaks 

self.cullPeaks(mergedList) 

return mergedList 

 

def cullPeaks(self, catalog): 

"""! 

@brief Attempt to remove garbage peaks (mostly on the outskirts of large blends). 

 

@param[in] catalog Source catalog 

""" 

keys = [item.key for item in self.merged.getPeakSchema().extract("merge_peak_*").values()] 

assert len(keys) > 0, "Error finding flags that associate peaks with their detection bands." 

totalPeaks = 0 

culledPeaks = 0 

for parentSource in catalog: 

# Make a list copy so we can clear the attached PeakCatalog and append the ones we're keeping 

# to it (which is easier than deleting as we iterate). 

keptPeaks = parentSource.getFootprint().getPeaks() 

oldPeaks = list(keptPeaks) 

keptPeaks.clear() 

familySize = len(oldPeaks) 

totalPeaks += familySize 

for rank, peak in enumerate(oldPeaks): 

if ((rank < self.config.cullPeaks.rankSufficient) or 

(sum([peak.get(k) for k in keys]) >= self.config.cullPeaks.nBandsSufficient) or 

(rank < self.config.cullPeaks.rankConsidered and 

rank < self.config.cullPeaks.rankNormalizedConsidered * familySize)): 

keptPeaks.append(peak) 

else: 

culledPeaks += 1 

self.log.info("Culled %d of %d peaks" % (culledPeaks, totalPeaks)) 

 

def getSchemaCatalogs(self): 

"""! 

Return a dict of empty catalogs for each catalog dataset produced by this task. 

 

@param[out] dictionary of empty catalogs 

""" 

mergeDet = afwTable.SourceCatalog(self.schema) 

peak = afwDetect.PeakCatalog(self.merged.getPeakSchema()) 

return {self.config.coaddName + "Coadd_mergeDet": mergeDet, 

self.config.coaddName + "Coadd_peak": peak} 

 

def getSkySourceFootprints(self, mergedList, skyInfo, seed): 

"""! 

@brief Return a list of Footprints of sky objects which don't overlap with anything in mergedList 

 

@param mergedList The merged Footprints from all the input bands 

@param skyInfo A description of the patch 

@param seed Seed for the random number generator 

""" 

mask = afwImage.Mask(skyInfo.patchInfo.getOuterBBox()) 

detected = mask.getPlaneBitMask("DETECTED") 

for s in mergedList: 

s.getFootprint().spans.setMask(mask, detected) 

 

footprints = self.skyObjects.run(mask, seed) 

if not footprints: 

return footprints 

 

# Need to convert the peak catalog's schema so we can set the "merge_peak_<skyFilterName>" flags 

schema = self.merged.getPeakSchema() 

mergeKey = schema.find("merge_peak_%s" % self.config.skyFilterName).key 

converted = [] 

for oldFoot in footprints: 

assert len(oldFoot.getPeaks()) == 1, "Should be a single peak only" 

peak = oldFoot.getPeaks()[0] 

newFoot = afwDetect.Footprint(oldFoot.spans, schema) 

newFoot.addPeak(peak.getFx(), peak.getFy(), peak.getPeakValue()) 

newFoot.getPeaks()[0].set(mergeKey, True) 

converted.append(newFoot) 

 

return converted 

 

 

class MeasureMergedCoaddSourcesConfig(Config): 

"""! 

@anchor MeasureMergedCoaddSourcesConfig_ 

 

@brief Configuration parameters for the MeasureMergedCoaddSourcesTask 

""" 

doDeblend = Field(dtype=bool, default=True, doc="Deblend sources?") 

deblend = ConfigurableField(target=SourceDeblendTask, doc="Deblend sources") 

measurement = ConfigurableField(target=SingleFrameMeasurementTask, doc="Source measurement") 

setPrimaryFlags = ConfigurableField(target=SetPrimaryFlagsTask, doc="Set flags for primary tract/patch") 

doPropagateFlags = Field( 

dtype=bool, default=True, 

doc="Whether to match sources to CCD catalogs to propagate flags (to e.g. identify PSF stars)" 

) 

propagateFlags = ConfigurableField(target=PropagateVisitFlagsTask, doc="Propagate visit flags to coadd") 

doMatchSources = Field(dtype=bool, default=True, doc="Match sources to reference catalog?") 

match = ConfigurableField(target=DirectMatchTask, doc="Matching to reference catalog") 

doWriteMatchesDenormalized = Field( 

dtype=bool, 

default=False, 

doc=("Write reference matches in denormalized format? " 

"This format uses more disk space, but is more convenient to read."), 

) 

coaddName = Field(dtype=str, default="deep", doc="Name of coadd") 

checkUnitsParseStrict = Field( 

doc="Strictness of Astropy unit compatibility check, can be 'raise', 'warn' or 'silent'", 

dtype=str, 

default="raise", 

) 

doApCorr = Field( 

dtype=bool, 

default=True, 

doc="Apply aperture corrections" 

) 

applyApCorr = ConfigurableField( 

target=ApplyApCorrTask, 

doc="Subtask to apply aperture corrections" 

) 

doRunCatalogCalculation = Field( 

dtype=bool, 

default=True, 

doc='Run catalogCalculation task' 

) 

catalogCalculation = ConfigurableField( 

target=CatalogCalculationTask, 

doc="Subtask to run catalogCalculation plugins on catalog" 

) 

 

def setDefaults(self): 

Config.setDefaults(self) 

self.deblend.propagateAllPeaks = True 

self.measurement.plugins.names |= ['base_InputCount', 'base_Variance'] 

self.measurement.plugins['base_PixelFlags'].masksFpAnywhere = ['CLIPPED', 'SENSOR_EDGE', 

'INEXACT_PSF'] 

self.measurement.plugins['base_PixelFlags'].masksFpCenter = ['CLIPPED', 'SENSOR_EDGE', 

'INEXACT_PSF'] 

 

## @addtogroup LSST_task_documentation 

## @{ 

## @page MeasureMergedCoaddSourcesTask 

## @ref MeasureMergedCoaddSourcesTask_ "MeasureMergedCoaddSourcesTask" 

## @copybrief MeasureMergedCoaddSourcesTask 

## @} 

 

 

class MeasureMergedCoaddSourcesRunner(ButlerInitializedTaskRunner): 

"""Get the psfCache setting into MeasureMergedCoaddSourcesTask""" 

@staticmethod 

def getTargetList(parsedCmd, **kwargs): 

return ButlerInitializedTaskRunner.getTargetList(parsedCmd, psfCache=parsedCmd.psfCache) 

 

 

class MeasureMergedCoaddSourcesTask(CmdLineTask): 

"""! 

@anchor MeasureMergedCoaddSourcesTask_ 

 

@brief Deblend sources from master catalog in each coadd seperately and measure. 

 

@section pipe_tasks_multiBand_Contents Contents 

 

- @ref pipe_tasks_multiBand_MeasureMergedCoaddSourcesTask_Purpose 

- @ref pipe_tasks_multiBand_MeasureMergedCoaddSourcesTask_Initialize 

- @ref pipe_tasks_multiBand_MeasureMergedCoaddSourcesTask_Run 

- @ref pipe_tasks_multiBand_MeasureMergedCoaddSourcesTask_Config 

- @ref pipe_tasks_multiBand_MeasureMergedCoaddSourcesTask_Debug 

- @ref pipe_tasks_multiband_MeasureMergedCoaddSourcesTask_Example 

 

@section pipe_tasks_multiBand_MeasureMergedCoaddSourcesTask_Purpose Description 

 

Command-line task that uses peaks and footprints from a master catalog to perform deblending and 

measurement in each coadd. 

 

Given a master input catalog of sources (peaks and footprints), deblend and measure each source on the 

coadd. Repeating this procedure with the same master catalog across multiple coadds will generate a 

consistent set of child sources. 

 

The deblender retains all peaks and deblends any missing peaks (dropouts in that band) as PSFs. Source 

properties are measured and the @c is-primary flag (indicating sources with no children) is set. Visit 

flags are propagated to the coadd sources. 

 

Optionally, we can match the coadd sources to an external reference catalog. 

 

@par Inputs: 

deepCoadd_mergeDet{tract,patch}: SourceCatalog 

@n deepCoadd_calexp{tract,patch,filter}: ExposureF 

@par Outputs: 

deepCoadd_meas{tract,patch,filter}: SourceCatalog 

@par Data Unit: 

tract, patch, filter 

 

MeasureMergedCoaddSourcesTask delegates most of its work to a set of sub-tasks: 

 

<DL> 

<DT> @ref SourceDeblendTask_ "deblend" 

<DD> Deblend all the sources from the master catalog.</DD> 

<DT> @ref SingleFrameMeasurementTask_ "measurement" 

<DD> Measure source properties of deblended sources.</DD> 

<DT> @ref SetPrimaryFlagsTask_ "setPrimaryFlags" 

<DD> Set flag 'is-primary' as well as related flags on sources. 'is-primary' is set for sources that are 

not at the edge of the field and that have either not been deblended or are the children of deblended 

sources</DD> 

<DT> @ref PropagateVisitFlagsTask_ "propagateFlags" 

<DD> Propagate flags set in individual visits to the coadd.</DD> 

<DT> @ref DirectMatchTask_ "match" 

<DD> Match input sources to a reference catalog (optional). 

</DD> 

</DL> 

These subtasks may be retargeted as required. 

 

@section pipe_tasks_multiBand_MeasureMergedCoaddSourcesTask_Initialize Task initialization 

 

@copydoc \_\_init\_\_ 

 

@section pipe_tasks_multiBand_MeasureMergedCoaddSourcesTask_Run Invoking the Task 

 

@copydoc run 

 

@section pipe_tasks_multiBand_MeasureMergedCoaddSourcesTask_Config Configuration parameters 

 

See @ref MeasureMergedCoaddSourcesConfig_ 

 

@section pipe_tasks_multiBand_MeasureMergedCoaddSourcesTask_Debug Debug variables 

 

The @link lsst.pipe.base.cmdLineTask.CmdLineTask command line task@endlink interface supports a 

flag @c -d to import @b debug.py from your @c PYTHONPATH; see @ref baseDebug for more about @b debug.py 

files. 

 

MeasureMergedCoaddSourcesTask has no debug variables of its own because it delegates all the work to 

the various sub-tasks. See the documetation for individual sub-tasks for more information. 

 

@section pipe_tasks_multiband_MeasureMergedCoaddSourcesTask_Example A complete example of using 

MeasureMergedCoaddSourcesTask 

 

After MeasureMergedCoaddSourcesTask has been run on multiple coadds, we have a set of per-band catalogs. 

The next stage in the multi-band processing procedure will merge these measurements into a suitable 

catalog for driving forced photometry. 

 

Command-line usage of MeasureMergedCoaddSourcesTask expects a data reference to the coadds 

to be processed. 

A list of the available optional arguments can be obtained by calling measureCoaddSources.py with the 

`--help` command line argument: 

@code 

measureCoaddSources.py --help 

@endcode 

 

To demonstrate usage of the DetectCoaddSourcesTask in the larger context of multi-band processing, we 

will process HSC data in the [ci_hsc](https://github.com/lsst/ci_hsc) package. Assuming one has finished 

step 6 at @ref pipeTasks_multiBand, one may perform deblending and measure sources in the HSC-I band 

coadd as follows: 

@code 

measureCoaddSources.py $CI_HSC_DIR/DATA --id patch=5,4 tract=0 filter=HSC-I 

@endcode 

This will process the HSC-I band data. The results are written in 

`$CI_HSC_DIR/DATA/deepCoadd-results/HSC-I/0/5,4/meas-HSC-I-0-5,4.fits 

 

It is also necessary to run 

@code 

measureCoaddSources.py $CI_HSC_DIR/DATA --id patch=5,4 tract=0 filter=HSC-R 

@endcode 

to generate the sources catalogs for the HSC-R band required by the next step in the multi-band 

procedure: @ref MergeMeasurementsTask_ "MergeMeasurementsTask". 

""" 

_DefaultName = "measureCoaddSources" 

ConfigClass = MeasureMergedCoaddSourcesConfig 

RunnerClass = MeasureMergedCoaddSourcesRunner 

getSchemaCatalogs = _makeGetSchemaCatalogs("meas") 

makeIdFactory = _makeMakeIdFactory("MergedCoaddId") # The IDs we already have are of this type 

 

@classmethod 

def _makeArgumentParser(cls): 

parser = ArgumentParser(name=cls._DefaultName) 

parser.add_id_argument("--id", "deepCoadd_calexp", 

help="data ID, e.g. --id tract=12345 patch=1,2 filter=r", 

ContainerClass=ExistingCoaddDataIdContainer) 

parser.add_argument("--psfCache", type=int, default=100, help="Size of CoaddPsf cache") 

return parser 

 

def __init__(self, butler=None, schema=None, peakSchema=None, refObjLoader=None, **kwargs): 

"""! 

@brief Initialize the task. 

 

Keyword arguments (in addition to those forwarded to CmdLineTask.__init__): 

@param[in] schema: the schema of the merged detection catalog used as input to this one 

@param[in] peakSchema: the schema of the PeakRecords in the Footprints in the merged detection catalog 

@param[in] refObjLoader: an instance of LoadReferenceObjectsTasks that supplies an external reference 

catalog. May be None if the loader can be constructed from the butler argument or all steps 

requiring a reference catalog are disabled. 

@param[in] butler: a butler used to read the input schemas from disk or construct the reference 

catalog loader, if schema or peakSchema or refObjLoader is None 

 

The task will set its own self.schema attribute to the schema of the output measurement catalog. 

This will include all fields from the input schema, as well as additional fields for all the 

measurements. 

""" 

CmdLineTask.__init__(self, **kwargs) 

if schema is None: 

assert butler is not None, "Neither butler nor schema is defined" 

schema = butler.get(self.config.coaddName + "Coadd_mergeDet_schema", immediate=True).schema 

self.schemaMapper = afwTable.SchemaMapper(schema) 

self.schemaMapper.addMinimalSchema(schema) 

self.schema = self.schemaMapper.getOutputSchema() 

self.algMetadata = PropertyList() 

if self.config.doDeblend: 

if peakSchema is None: 

assert butler is not None, "Neither butler nor peakSchema is defined" 

peakSchema = butler.get(self.config.coaddName + "Coadd_peak_schema", immediate=True).schema 

self.makeSubtask("deblend", schema=self.schema, peakSchema=peakSchema) 

self.makeSubtask("measurement", schema=self.schema, algMetadata=self.algMetadata) 

self.makeSubtask("setPrimaryFlags", schema=self.schema) 

if self.config.doMatchSources: 

if refObjLoader is None: 

assert butler is not None, "Neither butler nor refObjLoader is defined" 

self.makeSubtask("match", butler=butler, refObjLoader=refObjLoader) 

if self.config.doPropagateFlags: 

self.makeSubtask("propagateFlags", schema=self.schema) 

self.schema.checkUnits(parse_strict=self.config.checkUnitsParseStrict) 

if self.config.doApCorr: 

self.makeSubtask("applyApCorr", schema=self.schema) 

if self.config.doRunCatalogCalculation: 

self.makeSubtask("catalogCalculation", schema=self.schema) 

 

def runDataRef(self, patchRef, psfCache=100): 

"""! 

@brief Deblend and measure. 

 

@param[in] patchRef: Patch reference. 

 

Deblend each source in every coadd and measure. Set 'is-primary' and related flags. Propagate flags 

from individual visits. Optionally match the sources to a reference catalog and write the matches. 

Finally, write the deblended sources and measurements out. 

""" 

exposure = patchRef.get(self.config.coaddName + "Coadd_calexp", immediate=True) 

exposure.getPsf().setCacheCapacity(psfCache) 

sources = self.readSources(patchRef) 

if self.config.doDeblend: 

self.deblend.run(exposure, sources) 

 

bigKey = sources.schema["deblend_parentTooBig"].asKey() 

# catalog is non-contiguous so can't extract column 

numBig = sum((s.get(bigKey) for s in sources)) 

if numBig > 0: 

self.log.warn("Patch %s contains %d large footprints that were not deblended" % 

(patchRef.dataId, numBig)) 

 

table = sources.getTable() 

table.setMetadata(self.algMetadata) # Capture algorithm metadata to write out to the source catalog. 

 

self.measurement.run(sources, exposure, exposureId=self.getExposureId(patchRef)) 

 

if self.config.doApCorr: 

self.applyApCorr.run( 

catalog=sources, 

apCorrMap=exposure.getInfo().getApCorrMap() 

) 

 

# TODO DM-11568: this contiguous check-and-copy could go away if we 

# reserve enough space during SourceDetection and/or SourceDeblend. 

# NOTE: sourceSelectors require contiguous catalogs, so ensure 

# contiguity now, so views are preserved from here on. 

if not sources.isContiguous(): 

sources = sources.copy(deep=True) 

 

if self.config.doRunCatalogCalculation: 

self.catalogCalculation.run(sources) 

 

skyInfo = getSkyInfo(coaddName=self.config.coaddName, patchRef=patchRef) 

self.setPrimaryFlags.run(sources, skyInfo.skyMap, skyInfo.tractInfo, skyInfo.patchInfo, 

includeDeblend=self.config.doDeblend) 

if self.config.doPropagateFlags: 

self.propagateFlags.run(patchRef.getButler(), sources, self.propagateFlags.getCcdInputs(exposure), 

exposure.getWcs()) 

if self.config.doMatchSources: 

self.writeMatches(patchRef, exposure, sources) 

self.write(patchRef, sources) 

 

def readSources(self, dataRef): 

"""! 

@brief Read input sources. 

 

@param[in] dataRef: Data reference for catalog of merged detections 

@return List of sources in merged catalog 

 

We also need to add columns to hold the measurements we're about to make 

so we can measure in-place. 

""" 

merged = dataRef.get(self.config.coaddName + "Coadd_mergeDet", immediate=True) 

self.log.info("Read %d detections: %s" % (len(merged), dataRef.dataId)) 

idFactory = self.makeIdFactory(dataRef) 

for s in merged: 

idFactory.notify(s.getId()) 

table = afwTable.SourceTable.make(self.schema, idFactory) 

sources = afwTable.SourceCatalog(table) 

sources.extend(merged, self.schemaMapper) 

return sources 

 

def writeMatches(self, dataRef, exposure, sources): 

"""! 

@brief Write matches of the sources to the astrometric reference catalog. 

 

We use the Wcs in the exposure to match sources. 

 

@param[in] dataRef: data reference 

@param[in] exposure: exposure with Wcs 

@param[in] sources: source catalog 

""" 

result = self.match.run(sources, exposure.getInfo().getFilter().getName()) 

if result.matches: 

matches = afwTable.packMatches(result.matches) 

matches.table.setMetadata(result.matchMeta) 

dataRef.put(matches, self.config.coaddName + "Coadd_measMatch") 

if self.config.doWriteMatchesDenormalized: 

denormMatches = denormalizeMatches(result.matches, result.matchMeta) 

dataRef.put(denormMatches, self.config.coaddName + "Coadd_measMatchFull") 

 

def write(self, dataRef, sources): 

"""! 

@brief Write the source catalog. 

 

@param[in] dataRef: data reference 

@param[in] sources: source catalog 

""" 

dataRef.put(sources, self.config.coaddName + "Coadd_meas") 

self.log.info("Wrote %d sources: %s" % (len(sources), dataRef.dataId)) 

 

def getExposureId(self, dataRef): 

return int(dataRef.get(self.config.coaddName + "CoaddId")) 

 

 

class MergeMeasurementsConfig(MergeSourcesConfig): 

"""! 

@anchor MergeMeasurementsConfig_ 

 

@brief Configuration parameters for the MergeMeasurementsTask 

""" 

pseudoFilterList = ListField(dtype=str, default=["sky"], 

doc="Names of filters which may have no associated detection\n" 

"(N.b. should include MergeDetectionsConfig.skyFilterName)") 

snName = Field(dtype=str, default="base_PsfFlux", 

doc="Name of flux measurement for calculating the S/N when choosing the reference band.") 

minSN = Field(dtype=float, default=10., 

doc="If the S/N from the priority band is below this value (and the S/N " 

"is larger than minSNDiff compared to the priority band), use the band with " 

"the largest S/N as the reference band.") 

minSNDiff = Field(dtype=float, default=3., 

doc="If the difference in S/N between another band and the priority band is larger " 

"than this value (and the S/N in the priority band is less than minSN) " 

"use the band with the largest S/N as the reference band") 

flags = ListField(dtype=str, doc="Require that these flags, if available, are not set", 

default=["base_PixelFlags_flag_interpolatedCenter", "base_PsfFlux_flag", 

"ext_photometryKron_KronFlux_flag", "modelfit_CModel_flag", ]) 

 

## @addtogroup LSST_task_documentation 

## @{ 

## @page MergeMeasurementsTask 

## @ref MergeMeasurementsTask_ "MergeMeasurementsTask" 

## @copybrief MergeMeasurementsTask 

## @} 

 

 

class MergeMeasurementsTask(MergeSourcesTask): 

"""! 

@anchor MergeMeasurementsTask_ 

 

@brief Merge measurements from multiple bands 

 

@section pipe_tasks_multiBand_Contents Contents 

 

- @ref pipe_tasks_multiBand_MergeMeasurementsTask_Purpose 

- @ref pipe_tasks_multiBand_MergeMeasurementsTask_Initialize 

- @ref pipe_tasks_multiBand_MergeMeasurementsTask_Run 

- @ref pipe_tasks_multiBand_MergeMeasurementsTask_Config 

- @ref pipe_tasks_multiBand_MergeMeasurementsTask_Debug 

- @ref pipe_tasks_multiband_MergeMeasurementsTask_Example 

 

@section pipe_tasks_multiBand_MergeMeasurementsTask_Purpose Description 

 

Command-line task that merges measurements from multiple bands. 

 

Combines consistent (i.e. with the same peaks and footprints) catalogs of sources from multiple filter 

bands to construct a unified catalog that is suitable for driving forced photometry. Every source is 

required to have centroid, shape and flux measurements in each band. 

 

@par Inputs: 

deepCoadd_meas{tract,patch,filter}: SourceCatalog 

@par Outputs: 

deepCoadd_ref{tract,patch}: SourceCatalog 

@par Data Unit: 

tract, patch 

 

MergeMeasurementsTask subclasses @ref MergeSourcesTask_ "MergeSourcesTask". 

 

@section pipe_tasks_multiBand_MergeMeasurementsTask_Initialize Task initialization 

 

@copydoc \_\_init\_\_ 

 

@section pipe_tasks_multiBand_MergeMeasurementsTask_Run Invoking the Task 

 

@copydoc run 

 

@section pipe_tasks_multiBand_MergeMeasurementsTask_Config Configuration parameters 

 

See @ref MergeMeasurementsConfig_ 

 

@section pipe_tasks_multiBand_MergeMeasurementsTask_Debug Debug variables 

 

The @link lsst.pipe.base.cmdLineTask.CmdLineTask command line task@endlink interface supports a 

flag @c -d to import @b debug.py from your @c PYTHONPATH; see @ref baseDebug for more about @b debug.py 

files. 

 

MergeMeasurementsTask has no debug variables. 

 

@section pipe_tasks_multiband_MergeMeasurementsTask_Example A complete example 

of using MergeMeasurementsTask 

 

MergeMeasurementsTask is meant to be run after deblending & measuring sources in every band. 

The purpose of the task is to generate a catalog of sources suitable for driving forced photometry in 

coadds and individual exposures. 

Command-line usage of MergeMeasurementsTask expects a data reference to the coadds to be processed. A list 

of the available optional arguments can be obtained by calling mergeCoaddMeasurements.py with the `--help` 

command line argument: 

@code 

mergeCoaddMeasurements.py --help 

@endcode 

 

To demonstrate usage of the DetectCoaddSourcesTask in the larger context of multi-band processing, we 

will process HSC data in the [ci_hsc](https://github.com/lsst/ci_hsc) package. Assuming one has finished 

step 7 at @ref pipeTasks_multiBand, one may merge the catalogs generated after deblending and measuring 

as follows: 

@code 

mergeCoaddMeasurements.py $CI_HSC_DIR/DATA --id patch=5,4 tract=0 filter=HSC-I^HSC-R 

@endcode 

This will merge the HSC-I & HSC-R band catalogs. The results are written in 

`$CI_HSC_DIR/DATA/deepCoadd-results/`. 

""" 

_DefaultName = "mergeCoaddMeasurements" 

ConfigClass = MergeMeasurementsConfig 

inputDataset = "meas" 

outputDataset = "ref" 

getSchemaCatalogs = _makeGetSchemaCatalogs("ref") 

 

def __init__(self, butler=None, schema=None, **kwargs): 

"""! 

Initialize the task. 

 

Additional keyword arguments (forwarded to MergeSourcesTask.__init__): 

@param[in] schema: the schema of the detection catalogs used as input to this one 

@param[in] butler: a butler used to read the input schema from disk, if schema is None 

 

The task will set its own self.schema attribute to the schema of the output merged catalog. 

""" 

MergeSourcesTask.__init__(self, butler=butler, schema=schema, **kwargs) 

inputSchema = self.getInputSchema(butler=butler, schema=schema) 

self.schemaMapper = afwTable.SchemaMapper(inputSchema, True) 

self.schemaMapper.addMinimalSchema(inputSchema, True) 

self.fluxKey = inputSchema.find(self.config.snName + "_flux").getKey() 

self.fluxErrKey = inputSchema.find(self.config.snName + "_fluxSigma").getKey() 

self.fluxFlagKey = inputSchema.find(self.config.snName + "_flag").getKey() 

 

self.flagKeys = {} 

for band in self.config.priorityList: 

short = getShortFilterName(band) 

outputKey = self.schemaMapper.editOutputSchema().addField( 

"merge_measurement_%s" % short, 

type="Flag", 

doc="Flag field set if the measurements here are from the %s filter" % band 

) 

peakKey = inputSchema.find("merge_peak_%s" % short).key 

footprintKey = inputSchema.find("merge_footprint_%s" % short).key 

self.flagKeys[band] = Struct(peak=peakKey, footprint=footprintKey, output=outputKey) 

self.schema = self.schemaMapper.getOutputSchema() 

 

self.pseudoFilterKeys = [] 

for filt in self.config.pseudoFilterList: 

try: 

self.pseudoFilterKeys.append(self.schema.find("merge_peak_%s" % filt).getKey()) 

except Exception as e: 

self.log.warn("merge_peak is not set for pseudo-filter %s: %s" % (filt, e)) 

 

self.badFlags = {} 

for flag in self.config.flags: 

try: 

self.badFlags[flag] = self.schema.find(flag).getKey() 

except KeyError as exc: 

self.log.warn("Can't find flag %s in schema: %s" % (flag, exc,)) 

 

def run(self, catalogs, patchRef): 

"""! 

Merge measurement catalogs to create a single reference catalog for forced photometry 

 

@param[in] catalogs: the catalogs to be merged 

@param[in] patchRef: patch reference for data 

 

For parent sources, we choose the first band in config.priorityList for which the 

merge_footprint flag for that band is is True. 

 

For child sources, the logic is the same, except that we use the merge_peak flags. 

""" 

# Put catalogs, filters in priority order 

orderedCatalogs = [catalogs[band] for band in self.config.priorityList if band in catalogs.keys()] 

orderedKeys = [self.flagKeys[band] for band in self.config.priorityList if band in catalogs.keys()] 

 

mergedCatalog = afwTable.SourceCatalog(self.schema) 

mergedCatalog.reserve(len(orderedCatalogs[0])) 

 

idKey = orderedCatalogs[0].table.getIdKey() 

for catalog in orderedCatalogs[1:]: 

if numpy.any(orderedCatalogs[0].get(idKey) != catalog.get(idKey)): 

raise ValueError("Error in inputs to MergeCoaddMeasurements: source IDs do not match") 

 

# This first zip iterates over all the catalogs simultaneously, yielding a sequence of one 

# record for each band, in priority order. 

for orderedRecords in zip(*orderedCatalogs): 

 

maxSNRecord = None 

maxSNFlagKeys = None 

maxSN = 0. 

priorityRecord = None 

priorityFlagKeys = None 

prioritySN = 0. 

hasPseudoFilter = False 

 

# Now we iterate over those record-band pairs, keeping track of the priority and the 

# largest S/N band. 

for inputRecord, flagKeys in zip(orderedRecords, orderedKeys): 

parent = (inputRecord.getParent() == 0 and inputRecord.get(flagKeys.footprint)) 

child = (inputRecord.getParent() != 0 and inputRecord.get(flagKeys.peak)) 

 

if not (parent or child): 

for pseudoFilterKey in self.pseudoFilterKeys: 

if inputRecord.get(pseudoFilterKey): 

hasPseudoFilter = True 

priorityRecord = inputRecord 

priorityFlagKeys = flagKeys 

break 

if hasPseudoFilter: 

break 

 

isBad = any(inputRecord.get(flag) for flag in self.badFlags) 

if isBad or inputRecord.get(self.fluxFlagKey) or inputRecord.get(self.fluxErrKey) == 0: 

sn = 0. 

else: 

sn = inputRecord.get(self.fluxKey)/inputRecord.get(self.fluxErrKey) 

if numpy.isnan(sn) or sn < 0.: 

sn = 0. 

if (parent or child) and priorityRecord is None: 

priorityRecord = inputRecord 

priorityFlagKeys = flagKeys 

prioritySN = sn 

if sn > maxSN: 

maxSNRecord = inputRecord 

maxSNFlagKeys = flagKeys 

maxSN = sn 

 

# If the priority band has a low S/N we would like to choose the band with the highest S/N as 

# the reference band instead. However, we only want to choose the highest S/N band if it is 

# significantly better than the priority band. Therefore, to choose a band other than the 

# priority, we require that the priority S/N is below the minimum threshold and that the 

# difference between the priority and highest S/N is larger than the difference threshold. 

# 

# For pseudo code objects we always choose the first band in the priority list. 

bestRecord = None 

bestFlagKeys = None 

if hasPseudoFilter: 

bestRecord = priorityRecord 

bestFlagKeys = priorityFlagKeys 

elif (prioritySN < self.config.minSN and (maxSN - prioritySN) > self.config.minSNDiff and 

maxSNRecord is not None): 

bestRecord = maxSNRecord 

bestFlagKeys = maxSNFlagKeys 

elif priorityRecord is not None: 

bestRecord = priorityRecord 

bestFlagKeys = priorityFlagKeys 

 

if bestRecord is not None and bestFlagKeys is not None: 

outputRecord = mergedCatalog.addNew() 

outputRecord.assign(bestRecord, self.schemaMapper) 

outputRecord.set(bestFlagKeys.output, True) 

else: # if we didn't find any records 

raise ValueError("Error in inputs to MergeCoaddMeasurements: no valid reference for %s" % 

inputRecord.getId()) 

 

# more checking for sane inputs, since zip silently iterates over the smallest sequence 

for inputCatalog in orderedCatalogs: 

if len(mergedCatalog) != len(inputCatalog): 

raise ValueError("Mismatch between catalog sizes: %s != %s" % 

(len(mergedCatalog), len(orderedCatalogs))) 

 

return mergedCatalog