lsst.validate.drp

The lsst.validate.drp module provides utilities for measuring and plotting Key Performance Metrics (KPMs) on processed LSST data.

Contributing

lsst.validate.drp is developed at https://github.com/lsst/validate_drp. You can find Jira issues for this module under the validate_drp component.

Python API reference

lsst.validate.drp Package

lsst.validate.drp.validate Module

Functions

plot_metrics(job, filterName[, outputPrefix])

Plot AM1, AM2, AM3, PA1 plus related informational plots.

print_metrics(job[, levels])

print_pass_fail_summary(jobs[, levels, …])

run(repo_or_json[, metrics, outputPrefix, …])

Main entrypoint from validateDrp.py.

runOneFilter(repo, visitDataIds, metrics[, …])

Main executable for the case where there is just one filter.

lsst.validate.drp.util Module

Functions

averageDecFromCat(cat)

Compute the average declination from a catalog of measurements.

averageRaDec(ra, dec)

Calculate average RA, Dec from input lists using spherical geometry.

averageRaDecFromCat(cat)

Calculate the average right ascension and declination from a catalog.

averageRaFromCat(cat)

Compute the average right ascension from a catalog of measurements.

constructDataIds(filters, visits, ccds[, …])

Returns a list of dataIds consisting of every combination of visit & ccd for each filter.

constructRunList(visits, ccds[, ccdKeyName])

Construct a comprehensive runList for processCcd.py.

discoverDataIds(repo, **kwargs)

Retrieve a list of all dataIds in a repo.

ellipticity(i_xx, i_xy, i_yy)

Calculate ellipticity from second moments.

ellipticity_from_cat(cat[, slot_shape])

Calculate the ellipticity of the Shapes in a catalog from the 2nd moments.

ellipticity_from_shape(shape)

Calculate the ellipticty of shape from its moments.

getCcdKeyName(dataId)

Return the key in a dataId that’s referring to the CCD or moral equivalent.

loadDataIdsAndParameters(configFile)

Load data IDs, magnitude range, and expected metrics from a yaml file.

loadParameters(configFile)

Load configuration parameters from a yaml file.

loadRunList(configFile)

Load run list from a YAML file.

medianEllipticity1ResidualsFromCat(cat)

Compute the median real ellipticty residuals from a catalog of measurements.

medianEllipticity2ResidualsFromCat(cat)

Compute the median imaginary ellipticty residuals from a catalog of measurements.

medianEllipticityResidualsFromCat(cat)

Compute the median ellipticty residuals from a catalog of measurements.

positionRms(ra_mean, dec_mean, ra, dec)

Calculate the RMS between an array of coordinates and a reference (mean) position.

positionRmsFromCat(cat)

Calculate the RMS for RA, Dec for a set of observations an object.

raftSensorToInt(visitId)

Construct an int that encodes raft, sensor coordinates.

repoNameToPrefix(repo)

Generate a base prefix for plots based on the repo name.

sphDist(ra_mean, dec_mean, ra, dec)

Calculate distance on the surface of a unit sphere.

lsst.validate.drp.matchedVisitMetricsTask Module

Classes

MatchedVisitMetricsRunner(TaskClass, parsedCmd)

Subclass of TaskRunner for MatchedVisitMetrics

MatchedVisitMetricsConfig

MatchedVisitMetricsTask([config, name, …])

An alternate command-line driver for the validate_drp metrics.

Class Inheritance Diagram

Inheritance diagram of lsst.validate.drp.matchedVisitMetricsTask.MatchedVisitMetricsRunner, lsst.validate.drp.matchedVisitMetricsTask.MatchedVisitMetricsConfig, lsst.validate.drp.matchedVisitMetricsTask.MatchedVisitMetricsTask

lsst.validate.drp.photerrmodel Module

Functions

photErrModel(mag, sigmaSys, gamma, m5, **kwargs)

Model of photometric error for a single visit.

fitPhotErrModel(mag, mag_err)

Fit photometric error model from the LSST Overview paper:

build_photometric_error_model(…[, …])

Returns a serializable analytic photometry error model for a single visit.

lsst.validate.drp.astromerrmodel Module

Functions

astromErrModel(snr[, theta, sigmaSys, C])

Calculate expected astrometric uncertainty based on SNR.

fitAstromErrModel(snr, dist)

Fit model of astrometric error from the LSST Overview paper:

build_astrometric_error_model(…[, …])

Serializable model of astrometry errors across multiple visits.