def standardAngleMetrics(colname, replace_colname=None):
"""A set of standard simple metrics for some quantity which is a wrap-around angle.
Parameters
----------
colname : str
The column name to apply the metrics to.
replace_colname: str or None, opt
Value to replace colname with in the metricName.
i.e. if replace_colname='' then metric name is Mean, instead of Mean Airmass, or
if replace_colname='seeingGeom', then metric name is Mean seeingGeom instead of Mean seeingFwhmGeom.
Default is None, which does not alter the metric name.
Returns
-------
List of configured metrics.
"""
standardAngleMetrics = [
metrics.MeanAngleMetric(colname),
metrics.RmsAngleMetric(colname),
metrics.FullRangeAngleMetric(colname),
metrics.MinMetric(colname),
metrics.MaxMetric(colname)
]
if replace_colname is not None:
for m in standardAngleMetrics:
if len(replace_colname) > 0:
m.name = m.name.replace('%s' % colname, '%s' % replace_colname)
else:
m.name = m.name.rstrip(' %s' % colname)
return standardAngleMetrics
def meanRADec(colmap=None, runName='opsim', extraSql=None, extraMetadata=None):
"""Plot the range of RA/Dec as a function of night.
Parameters
----------
colmap : dict, opt
A dictionary with a mapping of column names. Default will use OpsimV4 column names.
runName : str, opt
The name of the simulated survey. Default is "opsim".
extraSql : str, opt
Additional constraint to add to any sql constraints (e.g. 'night<365')
Default None, for no additional constraints.
extraMetadata : str, opt
Additional metadata to add before any below (i.e. "WFD"). Default is None.
"""
if colmap is None:
colmap = ColMapDict('opsimV4')
bundleList = []
plotBundles = []
group = 'RA Dec coverage'
subgroup = 'All visits'
if extraMetadata is not None:
subgroup = extraMetadata
displayDict = {'group': group, 'subgroup': subgroup, 'order': 0}
ra_metrics = [metrics.MeanAngleMetric(colmap['ra']), metrics.FullRangeAngleMetric(colmap['ra'])]
dec_metrics = [metrics.MeanMetric(colmap['dec']), metrics.MinMetric(colmap['dec']),
metrics.MaxMetric(colmap['dec'])]
for m in ra_metrics:
slicer = slicers.OneDSlicer(sliceColName=colmap['night'], binsize=1)
if not colmap['raDecDeg']:
plotDict = {'yMin': np.radians(-5), 'yMax': np.radians(365)}
else:
plotDict = {'yMin': -5, 'yMax': 365}
bundle = mb.MetricBundle(m, slicer, extraSql, metadata=extraMetadata,
displayDict=displayDict, plotDict=plotDict)
bundleList.append(bundle)
for m in dec_metrics:
slicer = slicers.OneDSlicer(sliceColName=colmap['night'], binsize=1)
bundle = mb.MetricBundle(m, slicer, extraSql, metadata=extraMetadata,
displayDict=displayDict)
bundleList.append(bundle)
# Set the runName for all bundles and return the bundleDict.
for b in bundleList:
b.setRunName(runName)
return mb.makeBundlesDictFromList(bundleList), plotBundles
def testMeanAngleMetric(self):
"""Test mean angle metric."""
dv1 = np.arange(0, 32, 2.5)
dv2 = (dv1 - 20.0) % 360.
dv1 = np.array(list(zip(dv1)), dtype=[('testdata', 'float')])
dv2 = np.array(list(zip(dv2)), dtype=[('testdata', 'float')])
testmetric = metrics.MeanAngleMetric('testdata')
result1 = testmetric.run(dv1)
result2 = testmetric.run(dv2)
self.assertAlmostEqual(result1, (result2+20)%360.)
dv = np.random.rand(10000)*360.0
dv = dv
dv = np.array(list(zip(dv)), dtype=[('testdata', 'float')])
result = testmetric.run(dv)
result = result
self.assertAlmostEqual(result, 180)
def metadataBasicsAngle(value,
colmap=None,
runName='opsim',
valueName=None,
groupName=None,
extraSql=None,
extraMetadata=None,
nside=64,
ditherStacker=None,
ditherkwargs=None):
"""Calculate basic metrics on visit metadata 'value', where value is a wrap-around angle.
Calculates extended standard metrics (with unislicer) on the quantity (all visits and per filter),
makes histogram of the value (all visits and per filter),
Parameters
----------
value : str
The column name for the quantity to evaluate. (column name in the database or created by a stacker).
colmap : dict or None, opt
A dictionary with a mapping of column names. Default will use OpsimV4 column names.
runName : str, opt
The name of the simulated survey. Default is "opsim".
valueName : str, opt
The name of the value to be reported in the resultsDb and added to the metric.
This is intended to help standardize metric comparison between sim versions.
value = name as it is in the database (seeingFwhmGeom, etc).
valueName = name to be recorded ('seeingGeom', etc.). Default is None, which will match 'value'.
groupName : str, opt
The group name for this quantity in the displayDict. Default is the same as 'valueName', capitalized.
extraSql : str, opt
Additional constraint to add to any sql constraints (e.g. 'propId=1' or 'fieldID=522').
Default None, for no additional constraints.
extraMetadata : str, opt
Additional metadata to add before any below (i.e. "WFD"). Default is None.
nside : int, opt
Nside value for healpix slicer. Default 64.
If "None" is passed, the healpixslicer-based metrics will be skipped.
ditherStacker: str or lsst.sims.maf.stackers.BaseDitherStacker
Optional dither stacker to use to define ra/dec columns.
ditherkwargs: dict, opt
Optional dictionary of kwargs for the dither stacker.
Returns
-------
metricBundleDict
"""
if colmap is None:
colmap = ColMapDict('opsimV4')
bundleList = []
if valueName is None:
valueName = value
if groupName is None:
groupName = valueName.capitalize()
subgroup = extraMetadata
else:
groupName = groupName.capitalize()
subgroup = valueName.capitalize()
if subgroup is None:
subgroup = 'All visits'
displayDict = {'group': groupName, 'subgroup': subgroup}
raCol, decCol, degrees, ditherStacker, ditherMeta = radecCols(
ditherStacker, colmap, ditherkwargs)
extraMetadata = combineMetadata(extraMetadata, ditherMeta)
# Set up basic all and per filter sql constraints.
filterlist, colors, orders, sqls, metadata = filterList(
all=True, extraSql=extraSql, extraMetadata=extraMetadata)
stackerList = [ditherStacker]
# Summarize values over all and per filter.
slicer = slicers.UniSlicer()
for f in filterlist:
for m in standardAngleMetrics(value, replace_colname=valueName):
displayDict['caption'] = '%s for %s.' % (m.name, metadata[f])
displayDict['order'] = orders[f]
bundle = mb.MetricBundle(m,
slicer,
sqls[f],
stackerList=stackerList,
metadata=metadata[f],
displayDict=displayDict)
bundleList.append(bundle)
# Histogram values over all and per filter.
for f in filterlist:
displayDict['caption'] = 'Histogram of %s' % (value)
if valueName != value:
displayDict['caption'] += ' (%s)' % (valueName)
displayDict['caption'] += ' for %s.' % (metadata[f])
displayDict['order'] = orders[f]
m = metrics.CountMetric(value, metricName='%s Histogram' % (valueName))
slicer = slicers.OneDSlicer(sliceColName=value)
bundle = mb.MetricBundle(m,
slicer,
sqls[f],
stackerList=stackerList,
metadata=metadata[f],
displayDict=displayDict)
bundleList.append(bundle)
# Make maps of min/median/max for all and per filter, per RA/Dec, with standard summary stats.
mList = []
mList.append(
metrics.MeanAngleMetric(value,
metricName='AngleMean %s' % (valueName)))
mList.append(
metrics.FullRangeAngleMetric(value,
metricName='AngleRange %s' % (valueName)))
mList.append(
metrics.RmsAngleMetric(value, metricName='AngleRms %s' % (valueName)))
slicer = slicers.HealpixSlicer(nside=nside,
latCol=decCol,
lonCol=raCol,
latLonDeg=degrees)
subsetPlots = [plots.HealpixSkyMap(), plots.HealpixHistogram()]
for f in filterlist:
for m in mList:
displayDict['caption'] = 'Map of %s' % m.name
if valueName != value:
displayDict['caption'] += ' (%s)' % value
displayDict['caption'] += ' for %s.' % metadata[f]
displayDict['order'] = orders[f]
bundle = mb.MetricBundle(m,
slicer,
sqls[f],
stackerList=stackerList,
metadata=metadata[f],
plotFuncs=subsetPlots,
displayDict=displayDict,
summaryMetrics=standardSummary())
bundleList.append(bundle)
# Set the runName for all bundles and return the bundleDict.
for b in bundleList:
b.setRunName(runName)
return mb.makeBundlesDictFromList(bundleList)