lsst.validate.drp — Science Requirements Monitoring¶
Introduction to the Measurement API¶
Python API Reference¶
lsst.validate.drp.base Module¶
lsst.validate.drp’s Measurement API that handles JSON persistence.
Classes¶
BlobBase() |
Base class for Blob classes. |
Datum(value, units[, label, description]) |
A value annotated with units, a plot label and description. |
DatumAttributeMixin |
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Job([measurements, blobs]) |
A Job is a wrapper around all measurements and blob metadata associated with a validate_drp run. |
JsonSerializationMixin |
Mixin that provides serialization support |
MeasurementBase() |
Baseclass for Measurement classes. |
Metric(name, description, operatorStr[, ...]) |
Container for the definition of a Metric and specification levels. |
Specification(name, value, units[, ...]) |
A specification level or threshold associated with a Metric. |
ValidateError |
Base classes for exceptions in validate_drp. |
ValidateErrorNoStars |
To be raised by tests that find no stars satisfying a set of criteria. |
ValidateErrorSpecification |
Indicates an error with accessing or using requirement specifications. |
ValidateErrorUnknownSpecificationLevel |
Indicates the requested level of requirements is unknown. |
Class Inheritance Diagram¶
lsst.validate.drp.calcsrd Package¶
Metric measurement classes that implement LPM-17, the Science Requirements Document.
Classes¶
ADxMeasurement(x, matchedDataset, amx, ...) |
Measurement of AFx (x=1,2,3): The maximum fraction of astrometric distances which deviate by more than ADx milliarcsec (see AMx) (%). |
AFxMeasurement(x, matchedDataset, amx, ...) |
Measurement of AFx (x=1,2,3): The maximum fraction of astrometric distances which deviate by more than ADx milliarcsec (see AMx) (%). |
AMxMeasurement(x, matchedDataset, bandpass) |
Measurement of AMx (x=1,2,3): The maximum rms of the astrometric distance distribution for stellar pairs with separations of D arcmin (repeatability). |
PA1Measurement(matchedDataset, bandpass[, ...]) |
Measurement of the PA1 metric: photometric repeatability of measurements across a set of observations. |
PA2Measurement(matchedDataset, pa1, ...[, ...]) |
Measurement of PA2: millimag from median RMS (see PA1) of which PF1 of the samples can be found. |
PF1Measurement(matchedDataset, pa1, ...[, ...]) |
Measurement of PF1: fraction of samples between median RMS (PA1) and PA2 specification. |
Class Inheritance Diagram¶
lsst.validate.drp.matchreduce Module¶
Blob classes that reduce a multi-visit dataset and encapsulate data for measurement classes, plotting functions, and JSON persistence.
Functions¶
isExtended(source, extendedKey[, ...]) |
Is the source extended attribute above the threshold. |
magNormDiff(cat) |
Calculate the normalized mag/mag_err difference from the mean for a set of observations of an objection. |
fitExp(x, y, y_err[, deg]) |
Fit an exponential quadratic to x, y, y_err. |
fitAstromErrModel(snr, dist) |
Fit model of astrometric error from LSST Overview paper |
fitPhotErrModel(mag, mmag_err) |
Fit model of photometric error from LSST Overview paper |
positionRms(cat) |
Calculate the RMS for RA, Dec for a set of observations an object. |
astromErrModel(snr[, theta, sigmaSys, C]) |
Calculate expected astrometric uncertainty based on SNR. |
photErrModel(mag, sigmaSys, gamma, m5, **kwargs) |
Fit model of photometric error from LSST Overview paper |
Classes¶
MatchedMultiVisitDataset(repo, dataIds[, ...]) |
Container for matched star catalogs from multple visits, with filtering, summary statistics, and modelling. |
AnalyticAstrometryModel(matchedMultiVisitDataset) |
Serializable model of astronometry errors across multiple visits. |
AnalyticPhotometryModel(matchedMultiVisitDataset) |
Serializable analytic photometry error model for multi-visit catalogs. |
Class Inheritance Diagram¶
lsst.validate.drp.plot Module¶
Matplotlib plots describing lsst.validate.drp metric measurements, as well as analytic models of photometric and astrometric repeatability.
Functions¶
plotOutlinedLinesHorizontal(ax, *args, **kwargs) |
Plot horizontal lines outlined in white. |
plotOutlinedLinesVertical(ax, *args, **kwargs) |
Plot vertical lines outlined in white. |
plotOutlinedLines(ax_plot, x1, x2[, ...]) |
Plot horizontal lines outlined in white. |
plotOutlinedAxline(axMethod, x, **kwargs) |
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plotAnalyticAstrometryModel(dataset, astromModel) |
Plot angular distance between matched sources from different exposures. |
plotExpFit(x, y, y_err[, fit_params, deg, ...]) |
Plot an exponential quadratic fit to x, y, y_err. |
plotAstromErrModelFit(snr, dist, model[, ...]) |
Plot model of photometric error from LSST Overview paper |
plotPhotErrModelFit(mag, mmag_err, photomModel) |
Plot model of photometric error from LSST Overview paper (Eq. |
plotAnalyticPhotometryModel(dataset, photomModel) |
Plot photometric RMS for matched sources. |
plotPA1(pa1[, outputPrefix]) |
Plot the results of calculating the LSST SRC requirement PA1. |
plotAMx(amx, afx, bandpass[, amxSpecName, ...]) |
Plot a histogram of the RMS in relative distance between pairs of stars. |
lsst.validate.drp.util Module¶
Miscellaneous functions to support lsst.validate.drp.
Functions¶
arcminToRadians(arcmin) |
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averageDecFromCat(cat) |
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averageRaDec(ra, dec) |
Calculate average RA, Dec from input lists using spherical geometry. |
averageRaDecFromCat(cat) |
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averageRaFromCat(cat) |
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calcOrNone(func, x, ErrorClass, **kwargs) |
Calculate the func and return result. |
calcRmsDistances(groupView, annulus[, ...]) |
Calculate the RMS distance of a set of matched objects over visits. |
computeWidths(array) |
Compute the RMS and the scaled inter-quartile range of an array. |
constructDataIds(filters, visits, ccds[, ...]) |
Returns a list of dataIds consisting of every combination of visit & ccd for each filter. |
constructRunList(filter, visits, ccds[, ...]) |
Construct a comprehensive runList for processCcd.py. |
discoverDataIds(repo, **kwargs) |
Retrieve a list of all dataIds in a repo. |
getCcdKeyName(dataid) |
Return the key in a dataId that’s referring to the CCD or moral equivalent. |
getRandomDiff(array) |
Get the difference between two randomly selected elements of an array. |
getRandomDiffRmsInMas(array) |
Calculate the RMS difference in mmag between a random pairs of magnitudes. |
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. |
matchVisitComputeDistance(visit_obj1, ...) |
Calculate obj1-obj2 distance for each visit in which both objects are seen. |
radiansToMilliarcsec(rad) |
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repoNameToPrefix(repo) |
Generate a base prefix for plots based on the repo name. |
sphDist(ra1, dec1, ra2, dec2) |
Calculate distance on the surface of a unit sphere. |
lsst.validate.drp.validate Module¶
Main driver functions for metric measurements, plotting, specification grading, and persistence.
Functions¶
run(repo, dataIds[, outputPrefix, level, ...]) |
Main executable. |
runOneFilter(repo, visitDataIds[, ...]) |
Main executable for the case where there is just one filter. |