Source code for lsst.sims.maf.batches.glanceBatch

from __future__ import print_function
import warnings
import lsst.sims.maf.metrics as metrics
import lsst.sims.maf.slicers as slicers
import lsst.sims.maf.stackers as stackers
import lsst.sims.maf.plots as plots
import lsst.sims.maf.metricBundles as metricBundles
from .colMapDict import ColMapDict
from .common import standardSummary
from .slewBatch import slewBasics
from .hourglassBatch import hourglassPlots

__all__ = ['glanceBatch']


[docs]def glanceBatch(colmap=None, runName='opsim', nside=64, filternames=('u', 'g', 'r', 'i', 'z', 'y'), nyears=10, pairnside=32, sqlConstraint=None, slicer_camera='LSST'): """Generate a handy set of metrics that give a quick overview of how well a survey performed. This is a meta-set of other batches, to some extent. Parameters ---------- colmap : dict, opt A dictionary with a mapping of column names. Default will use OpsimV4 column names. run_name : str, opt The name of the simulated survey. Default is "opsim". nside : int, opt The nside for the healpix slicers. Default 64. filternames : list of str, opt The list of individual filters to use when running metrics. Default is ('u', 'g', 'r', 'i', 'z', 'y'). There is always an all-visits version of the metrics run as well. nyears : int (10) How many years to attempt to make hourglass plots for pairnside : int (32) nside to use for the pair fraction metric (it's slow, so nice to use lower resolution) sqlConstraint : str or None, opt Additional SQL constraint to apply to all metrics. slicer_camera : str ('LSST') Sets which spatial slicer to use. options are 'LSST' and 'ComCam' Returns ------- metricBundleDict """ if isinstance(colmap, str): raise ValueError('colmap must be a dictionary, not a string') if colmap is None: colmap = ColMapDict('opsimV4') bundleList = [] if sqlConstraint is None: sqlC = '' else: sqlC = '(%s) and' % sqlConstraint if slicer_camera == 'LSST': spatial_slicer = slicers.HealpixSlicer elif slicer_camera == 'ComCam': spatial_slicer = slicers.HealpixComCamSlicer else: raise ValueError('Camera must be LSST or Comcam') sql_per_filt = ['%s %s="%s"' % (sqlC, colmap['filter'], filtername) for filtername in filternames] sql_per_and_all_filters = [sqlConstraint] + sql_per_filt standardStats = standardSummary() subsetPlots = [plots.HealpixSkyMap(), plots.HealpixHistogram()] # Super basic things displayDict = {'group': 'Basic Stats', 'order': 1} sql = sqlConstraint slicer = slicers.UniSlicer() # Length of Survey metric = metrics.FullRangeMetric(col=colmap['mjd'], metricName='Length of Survey (days)') bundle = metricBundles.MetricBundle(metric, slicer, sql, displayDict=displayDict) bundleList.append(bundle) # Total number of filter changes metric = metrics.NChangesMetric(col=colmap['filter'], orderBy=colmap['mjd']) bundle = metricBundles.MetricBundle(metric, slicer, sql, displayDict=displayDict) bundleList.append(bundle) # Total open shutter fraction metric = metrics.OpenShutterFractionMetric(slewTimeCol=colmap['slewtime'], expTimeCol=colmap['exptime'], visitTimeCol=colmap['visittime']) bundle = metricBundles.MetricBundle(metric, slicer, sql, displayDict=displayDict) bundleList.append(bundle) # Total effective exposure time metric = metrics.TeffMetric(m5Col=colmap['fiveSigmaDepth'], filterCol=colmap['filter'], normed=True) for sql in sql_per_and_all_filters: bundle = metricBundles.MetricBundle(metric, slicer, sql, displayDict=displayDict) bundleList.append(bundle) # Number of observations, all and each filter metric = metrics.CountMetric(col=colmap['mjd'], metricName='Number of Exposures') for sql in sql_per_and_all_filters: bundle = metricBundles.MetricBundle(metric, slicer, sql, displayDict=displayDict) bundleList.append(bundle) # The alt/az plots of all the pointings slicer = spatial_slicer(nside=nside, latCol=colmap['alt'], lonCol=colmap['az'], latLonDeg=colmap['raDecDeg'], useCache=False) metric = metrics.CountMetric(colmap['mjd'], metricName='Nvisits as function of Alt/Az') plotFuncs = [plots.LambertSkyMap()] plotDict = {'norm': 'log'} for sql in sql_per_and_all_filters: bundle = metricBundles.MetricBundle(metric, slicer, sql, plotFuncs=plotFuncs, displayDict=displayDict, plotDict=plotDict) bundleList.append(bundle) # Things to check per night # Open Shutter per night displayDict = {'group': 'Pointing Efficency', 'order': 2} slicer = slicers.OneDSlicer(sliceColName=colmap['night'], binsize=1) metric = metrics.OpenShutterFractionMetric(slewTimeCol=colmap['slewtime'], expTimeCol=colmap['exptime'], visitTimeCol=colmap['visittime']) sql = sqlConstraint bundle = metricBundles.MetricBundle(metric, slicer, sql, summaryMetrics=standardStats, displayDict=displayDict) bundleList.append(bundle) # Number of filter changes per night slicer = slicers.OneDSlicer(sliceColName=colmap['night'], binsize=1) metric = metrics.NChangesMetric(col=colmap['filter'], orderBy=colmap['mjd'], metricName='Filter Changes') bundle = metricBundles.MetricBundle(metric, slicer, sql, summaryMetrics=standardStats, displayDict=displayDict) bundleList.append(bundle) # A few basic maps # Number of observations, coadded depths extended_stats = standardStats.copy() extended_stats.append(metrics.AreaSummaryMetric(decreasing=True, metricName='top18k')) extended_stats.append(metrics.PercentileMetric(col='metricdata', percentile=10)) displayDict = {'group': 'Basic Maps', 'order': 3} slicer = spatial_slicer(nside=nside, latCol=colmap['dec'], lonCol=colmap['ra'], latLonDeg=colmap['raDecDeg']) metric = metrics.CountMetric(col=colmap['mjd']) plotDict = {'percentileClip': 95.} for sql in sql_per_and_all_filters: bundle = metricBundles.MetricBundle(metric, slicer, sql, summaryMetrics=extended_stats, displayDict=displayDict, plotDict=plotDict) bundleList.append(bundle) metric = metrics.Coaddm5Metric(m5Col=colmap['fiveSigmaDepth']) for sql in sql_per_and_all_filters: bundle = metricBundles.MetricBundle(metric, slicer, sql, summaryMetrics=extended_stats, displayDict=displayDict) bundleList.append(bundle) # Checking a few basic science things # Maybe check astrometry, observation pairs, SN plotDict = {'percentileClip': 95.} displayDict = {'group': 'Science', 'subgroup': 'Astrometry', 'order': 4} stackerList = [] stacker = stackers.ParallaxFactorStacker(raCol=colmap['ra'], decCol=colmap['dec'], degrees=colmap['raDecDeg'], dateCol=colmap['mjd']) stackerList.append(stacker) astrom_stats = [metrics.AreaSummaryMetric(decreasing=False, metricName='best18k'), metrics.PercentileMetric(col='metricdata', percentile=90)] # Maybe parallax and proper motion, fraction of visits in a good pair for SS displayDict['caption'] = r'Parallax precision of an $r=20$ flat SED star' metric = metrics.ParallaxMetric(m5Col=colmap['fiveSigmaDepth'], filterCol=colmap['filter'], seeingCol=colmap['seeingGeom']) sql = sqlConstraint bundle = metricBundles.MetricBundle(metric, slicer, sql, plotFuncs=subsetPlots, displayDict=displayDict, stackerList=stackerList, plotDict=plotDict, summaryMetrics=astrom_stats) bundleList.append(bundle) displayDict['caption'] = r'Proper motion precision of an $r=20$ flat SED star' metric = metrics.ProperMotionMetric(m5Col=colmap['fiveSigmaDepth'], mjdCol=colmap['mjd'], filterCol=colmap['filter'], seeingCol=colmap['seeingGeom']) bundle = metricBundles.MetricBundle(metric, slicer, sql, plotFuncs=subsetPlots, displayDict=displayDict, plotDict=plotDict, summaryMetrics=astrom_stats) bundleList.append(bundle) # Solar system stuff displayDict['caption'] = 'Fraction of observations that are in pairs' displayDict['subgroup'] = 'Solar System' sql = '%s (filter="g" or filter="r" or filter="i")' % sqlC pairSlicer = slicers.HealpixSlicer(nside=pairnside, latCol=colmap['dec'], lonCol=colmap['ra'], latLonDeg=colmap['raDecDeg']) metric = metrics.PairFractionMetric(mjdCol=colmap['mjd']) bundle = metricBundles.MetricBundle(metric, pairSlicer, sql, plotFuncs=subsetPlots, displayDict=displayDict) bundleList.append(bundle) # stats from the note column if 'note' in colmap.keys(): displayDict = {'group': 'Basic Stats', 'subgroup': 'Percent stats'} metric = metrics.StringCountMetric(col=colmap['note'], percent=True, metricName='Percents') sql = '' slicer = slicers.UniSlicer() bundle = metricBundles.MetricBundle(metric, slicer, sql, displayDict=displayDict) bundleList.append(bundle) displayDict['subgroup'] = 'Count Stats' metric = metrics.StringCountMetric(col=colmap['note'], metricName='Counts') bundle = metricBundles.MetricBundle(metric, slicer, sql, displayDict=displayDict) bundleList.append(bundle) for b in bundleList: b.setRunName(runName) bd = metricBundles.makeBundlesDictFromList(bundleList) # Add hourglass plots. hrDict = hourglassPlots(colmap=colmap, runName=runName, nyears=nyears, extraSql=sqlConstraint) bd.update(hrDict) # Add basic slew stats. try: slewDict = slewBasics(colmap=colmap, runName=runName) bd.update(slewDict) except KeyError as e: warnings.warn('Could not add slew stats: missing required key %s from colmap' % (e)) return bd