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# 

# This file is part of ap_verify. 

# 

# Developed for the LSST Data Management System. 

# This product includes software developed by the LSST Project 

# (http://www.lsst.org). 

# See the COPYRIGHT file at the top-level directory of this distribution 

# for details of code ownership. 

# 

# 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 GNU General Public License 

# along with this program. If not, see <http://www.gnu.org/licenses/>. 

# 

 

"""Code for measuring software performance metrics. 

""" 

 

__all__ = ["measureNumberNewDiaObjects", 

"measureNumberUnassociatedDiaObjects", 

"measureFractionUpdatedDiaObjects", 

"measureNumberSciSources", 

"measureFractionDiaSourcesToSciSources", 

"measureTotalUnassociatedDiaObjects"] 

 

import astropy.units as u 

import lsst.verify 

 

 

def measureNumberNewDiaObjects(metadata, taskName, metricName): 

"""Compute the number of newly created DIAObjects from metadata. 

 

Parameters 

---------- 

metadata : `lsst.daf.base.PropertySet` 

The metadata to search for object count information. 

taskName : `str` 

The name of the Task, e.g., "processCcd". SubTask names must be the 

ones assigned by the parent Task and may be disambiguated using the 

parent Task name, as in "processCcd:calibrate". 

If `taskName` matches multiple runs of a subTask in different 

contexts, the information for only one run will be provided. 

metricName : `str` 

The fully qualified name of the metric being measured, e.g., 

"association.numNewDiaObjects" 

 

Returns 

------- 

measurement : `lsst.verify.Measurement` 

a value of `metricName`, or `None` if the object counts for 

`taskName` are not present in `metadata` 

""" 

if not metadata.exists("%s.numNewDiaObjects" % taskName): 

return None 

 

nNew = metadata.getAsInt("%s.numNewDiaObjects" % taskName) 

meas = lsst.verify.Measurement(metricName, nNew * u.count) 

return meas 

 

 

def measureNumberUnassociatedDiaObjects(metadata, taskName, metricName): 

"""Compute the number of previously created DIAObjects that were loaded 

but did not have a new association in this visit, ccd. 

 

Parameters 

---------- 

metadata : `lsst.daf.base.PropertySet` 

The metadata to search for object count information. 

taskName : `str` 

The name of the Task, e.g., "processCcd". SubTask names must be the 

ones assigned by the parent Task and may be disambiguated using the 

parent Task name, as in "processCcd:calibrate". 

If `taskName` matches multiple runs of a subTask in different 

contexts, the information for only one run will be provided. 

metricName : `str` 

The fully qualified name of the metric being measured, e.g., 

"association.numUnassociatedDiaObjects" 

 

Returns 

------- 

measurement : `lsst.verify.Measurement` 

a value for `metricName`, or `None` if the object counts for 

`taskName` are not present in `metadata` 

""" 

if not metadata.exists("%s.numUnassociatedDiaObjects" % taskName): 

return None 

 

nUnassociated = metadata.getAsInt("%s.numUnassociatedDiaObjects" % taskName) 

meas = lsst.verify.Measurement(metricName, nUnassociated * u.count) 

return meas 

 

 

def measureFractionUpdatedDiaObjects(metadata, taskName, metricName): 

"""Compute the fraction of previously created DIAObjects that have a new 

association in this visit, ccd. 

 

Parameters 

---------- 

metadata : `lsst.daf.base.PropertySet` 

The metadata to search for object count information. 

taskName : `str` 

The name of the Task, e.g., "processCcd". SubTask names must be the 

ones assigned by the parent Task and may be disambiguated using the 

parent Task name, as in "processCcd:calibrate". 

If `taskName` matches multiple runs of a subTask in different 

contexts, the information for only one run will be provided. 

metricName : `str` 

The fully qualified name of the metric being measured, e.g., 

"association.fracUpdatedDiaObjects" 

 

Returns 

------- 

measurement : `lsst.verify.Measurement` 

a value for `metricName`, or `None` if the object counts for 

`taskName` are not present in `metadata` 

""" 

if not metadata.exists("%s.numUpdatedDiaObjects" % taskName) or \ 

not metadata.exists("%s.numUnassociatedDiaObjects" % taskName): 

return None 

 

nUpdated = metadata.getAsDouble("%s.numUpdatedDiaObjects" % taskName) 

nUnassociated = metadata.getAsDouble("%s.numUnassociatedDiaObjects" % taskName) 

if nUpdated <= 0. or nUnassociated <= 0.: 

return lsst.verify.Measurement(metricName, 0. * u.dimensionless_unscaled) 

meas = lsst.verify.Measurement( 

metricName, 

nUpdated / (nUpdated + nUnassociated) * u.dimensionless_unscaled) 

return meas 

 

 

def measureNumberSciSources(butler, dataIdDict, metricName): 

"""Compute the number of cataloged science sources. 

 

Parameters 

---------- 

butler : `lsst.daf.persistence.Butler` 

The output repository location to read from disk. 

dataIdDict : `dict` 

Butler identifier naming the data to be processed (e.g., visit and 

ccdnum) formatted in the usual way (e.g., 'visit=54321 ccdnum=7'). 

metricName : `str` 

The fully qualified name of the metric being measured, e.g., 

"ip_diffim.numSciSources" 

 

Returns 

------- 

measurement : `lsst.verify.Measurement` 

a value for `metricName`, or `None` 

""" 

 

# Parse the input dataId string and convert to a dictionary of values. 

# Hard coded assuming the same input formate as in ap_pipe. 

 

nSciSources = len(butler.get('src', dataId=dataIdDict)) 

meas = lsst.verify.Measurement( 

metricName, nSciSources * u.count) 

return meas 

 

 

def measureFractionDiaSourcesToSciSources(butler, 

dataIdDict, 

metricName): 

"""Compute the ratio of cataloged science sources to different image 

sources per ccd per visit. 

 

Parameters 

---------- 

butler : `lsst.daf.percistence.Butler` 

The output repository location to read from disk. 

dataIdDict : `dict` 

Butler identifier naming the data to be processed (e.g., visit and 

ccdnum) formatted in the usual way (e.g., 'visit=54321 ccdnum=7'). 

metricName : `str` 

The fully qualified name of the metric being measured, e.g., 

"ip_diffim.fracDiaSourcesToSciSources" 

 

Returns 

------- 

measurement : `lsst.verify.Measurement` 

a value for `metricName`, or `None` 

""" 

 

# Parse the input dataId string and convert to a dictionary of values. 

# Hard coded assuming the same input formate as in ap_pipe. 

 

nSciSources = len(butler.get('src', dataId=dataIdDict)) 

nDiaSources = len(butler.get('deepDiff_diaSrc', dataId=dataIdDict)) 

meas = lsst.verify.Measurement( 

metricName, 

nDiaSources / nSciSources * u.dimensionless_unscaled) 

return meas 

 

 

def measureTotalUnassociatedDiaObjects(dbCursor, metricName): 

""" Compute number of DIAObjects with only one association DIASource. 

 

Parameters 

---------- 

dbCursor : `sqlite3.Cursor` 

Cursor to the sqlite data base created from a previous run of 

AssociationDBSqlite task to load. 

metricName : `str` 

The fully qualified name of the metric being measured, e.g., 

"association.totalUnassociatedDiaObjects" 

 

Returns 

------- 

measurement : `lsst.verify.Measurement` 

a value for `metricName`, or `None` 

""" 

 

dbCursor.execute("SELECT count(*) FROM dia_objects " 

"WHERE nDiaSources = 1") 

(nUnassociatedDiaObjects,) = dbCursor.fetchall()[0] 

 

meas = lsst.verify.Measurement( 

metricName, 

nUnassociatedDiaObjects * u.count) 

return meas