def getData(opsDb, sqlconstraint):
# Define columns we want from opsim database (for metrics, slicers and stacker info).
colnames = [
'observationStartMJD', 'filter', 'fieldRA', 'fieldDec',
'observationStartLST', 'moonRA', 'moonDec', 'moonPhase', 'night'
]
# Get data from database.
simdata = opsDb.fetchMetricData(colnames, sqlconstraint)
if len(simdata) == 0:
raise Exception('No simdata found matching constraint %s' %
(sqlconstraint))
# Hack because observationStartLst in HOURS here. :(
simdata[
'observationStartLST'] = simdata['observationStartLST'] / 24.0 * 360.0
# Add stacker columns.
hourangleStacker = stackers.HourAngleStacker()
simdata = hourangleStacker.run(simdata)
filterStacker = stackers.FilterColorStacker()
simdata = filterStacker.run(simdata)
fieldIdStacker = stackers.OpSimFieldStacker()
simdata = fieldIdStacker.run(simdata)
# Fetch field data.
#fields = opsDb.fetchFieldsFromFieldTable(degreesToRadians=True)
fidx = np.unique(simdata['opsimFieldId'], return_index=True)[1]
fields = np.recarray(len(fidx),
dtype=[('opsimFieldId', np.float),
('fieldRA', np.float), ('fieldDec', np.float)])
fields['opsimFieldId'] = simdata['opsimFieldId'][fidx]
fields['fieldRA'] = np.radians(simdata['fieldRA'][fidx])
fields['fieldDec'] = np.radians(simdata['fieldDec'][fidx])
return simdata, fields
def getData(opsDb, sqlconstraint):
# Define columns we want from opsim database (for metrics, slicers and
# stacker info).
colnames = [
'expMJD', 'filter', 'fieldID', 'fieldRA', 'fieldDec', 'lst', 'moonRA',
'moonDec', 'moonPhase', 'night'
]
# Get data from database.
simdata = opsDb.fetchMetricData(colnames, sqlconstraint)
if len(simdata) == 0:
raise Exception('No simdata found matching constraint %s' %
(sqlconstraint))
# Add stacker columns.
hourangleStacker = stackers.HourAngleStacker()
simdata = hourangleStacker.run(simdata)
# ZTF
filterStacker = stackers.FilterColorStacker(filterMap={
'g': 1,
'r': 2,
'i': 3
})
filterStacker.filter_rgb_map = {
'g': (0, 1, 0), # green
'r': (1, 0, 0), # red
'i': (1, 0, 1)
} # red
simdata = filterStacker.run(simdata)
# Fetch field data.
fields = opsDb.fetchFieldsFromFieldTable()
return simdata, fields
def getData(opsDb, sqlconstraint):
# Define columns we want from opsim database (for metrics, slicers and stacker info).
colnames = ['observationStartMJD', 'filter', 'fieldId', 'fieldRA', 'fieldDec', 'observationStartLST',
'moonRA', 'moonDec', 'moonPhase', 'night']
# Get data from database.
simdata = opsDb.fetchMetricData(colnames, sqlconstraint)
if len(simdata) == 0:
raise Exception('No simdata found matching constraint %s' %(sqlconstraint))
# Add stacker columns.
hourangleStacker = stackers.HourAngleStacker()
simdata = hourangleStacker.run(simdata)
filterStacker = stackers.FilterColorStacker()
simdata = filterStacker.run(simdata)
# Fetch field data.
fields = opsDb.fetchFieldsFromFieldTable(degreesToRadians=True)
return simdata, fields
def testFilterColorStacker(self):
"""Test the filter color stacker."""
data = np.zeros(60, dtype=list(zip(['filter'], ['<U1'])))
data['filter'][0:10] = 'u'
data['filter'][10:20] = 'g'
data['filter'][20:30] = 'r'
data['filter'][30:40] = 'i'
data['filter'][40:50] = 'z'
data['filter'][50:60] = 'y'
stacker = stackers.FilterColorStacker()
data = stacker.run(data)
# Check if re-run stacker raises warning (adding column twice).
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
data = stacker.run(data)
assert len(w) > 1
assert "already present in simData" in str(w[-1].message)
# Check if use non-recognized filter raises exception.
data = np.zeros(600, dtype=list(zip(['filter'], ['<U1'])))
data['filter'] = 'q'
self.assertRaises(IndexError, stacker.run, data)
def runSlices(opsimName,
metadata,
simdata,
fields,
bins,
args,
opsDb,
verbose=False):
# Set up the movie slicer.
movieslicer = setupMovieSlicer(simdata, bins)
# Set up formatting for output suffix.
sliceformat = '%s0%dd' % ('%', int(np.log10(len(movieslicer))) + 1)
# Get the telescope latitude info.
lat_tele = Site(name='LSST').latitude_rad
# Run through the movie slicer slicePoints and generate plots at each point.
for i, ms in enumerate(movieslicer):
t = time.time()
slicenumber = sliceformat % (i)
if verbose:
print(slicenumber)
# Set up metrics.
if args.movieStepsize != 0:
tstep = args.movieStepsize
else:
tstep = ms['slicePoint']['binRight'] - bins[i]
if tstep > 1:
tstep = 40. / 24. / 60. / 60.
# Add simple view of time to plot label.
times_from_start = ms['slicePoint']['binRight'] - (int(bins[0]) +
0.16 - 0.5)
# Opsim years are 365 days (not 365.25)
years = int(times_from_start / 365)
days = times_from_start - years * 365
plotlabel = 'Year %d Day %.4f' % (years, days)
# Set up metrics.
metricList, plotDictList = setupMetrics(
opsimName,
metadata,
plotlabel=plotlabel,
t0=ms['slicePoint']['binRight'],
tStep=tstep,
years=years,
verbose=verbose)
# Identify the subset of simdata in the movieslicer 'data slice'
simdatasubset = simdata[ms['idxs']]
# Set up opsim slicer on subset of simdata provided by movieslicer
opslicer = slicers.OpsimFieldSlicer(
simDataFieldIdColName='opsimFieldId',
fieldIdColName='opsimFieldId')
# Set up metricBundles to combine metrics, plotdicts and slicer.
bundles = []
sqlconstraint = ''
for metric, plotDict in zip(metricList, plotDictList):
bundles.append(
metricBundles.MetricBundle(metric,
opslicer,
constraint=sqlconstraint,
metadata=metadata,
runName=opsimName,
plotDict=plotDict))
# Remove (default) stackers from bundles, because we've already run them above on the original data.
for mb in bundles:
mb.stackerList = []
bundledict = metricBundles.makeBundlesDictFromList(bundles)
# Set up metricBundleGroup to handle metrics calculation + plotting
bg = metricBundles.MetricBundleGroup(bundledict,
opsDb,
outDir=args.outDir,
resultsDb=None,
saveEarly=False)
# 'Hack' bundleGroup to just go ahead and run the metrics, without querying the database.
simData = simdatasubset
bg.fieldData = fields
bg.setCurrent(sqlconstraint)
bg.runCurrent(constraint=sqlconstraint, simData=simData)
# Plot data each metric, for this slice of the movie, adding slicenumber as a suffix for output plots.
# Plotting here, rather than automatically via sliceMetric method because we're going to rotate the sky,
# and add extra legend info and figure text (for FilterColors metric).
ph = plots.PlotHandler(outDir=args.outDir,
figformat='png',
dpi=72,
thumbnail=False,
savefig=False)
obsnow = np.where(simdatasubset['observationStartMJD'] ==
simdatasubset['observationStartMJD'].max())[0]
raCen = np.radians(
np.mean(simdatasubset[obsnow]['observationStartLST']))
# Calculate horizon location.
horizonlon, horizonlat = addHorizon(lat_telescope=lat_tele)
# Create the plot for each metric and save it (after some additional manipulation).
for mb in bundles:
ph.setMetricBundles([mb])
fignum = ph.plot(plotFunc=plots.BaseSkyMap(),
plotDicts={'raCen': raCen})
fig = plt.figure(fignum)
ax = plt.gca()
# Add horizon and zenith.
plt.plot(horizonlon, horizonlat, 'k.', alpha=0.3, markersize=1.8)
plt.plot(0, lat_tele, 'k+')
# For the FilterColors metric, add some extra items.
if mb.metric.name == 'FilterColors':
# Add the time stamp info (plotlabel) with a fancybox.
plt.figtext(0.75,
0.9,
'%s' % (plotlabel),
bbox=dict(boxstyle='Round, pad=0.7',
fc='w',
ec='k',
alpha=0.5))
# Add a legend for the filters.
filterstacker = stackers.FilterColorStacker()
for i, f in enumerate(['u', 'g', 'r', 'i', 'z', 'y']):
plt.figtext(0.92,
0.55 - i * 0.035,
f,
color=filterstacker.filter_rgb_map[f])
# Add a moon.
moonRA = np.radians(np.mean(simdatasubset[obsnow]['moonRA']))
lon = -(moonRA - raCen - np.pi) % (np.pi * 2) - np.pi
moonDec = np.radians(np.mean(simdatasubset[obsnow]['moonDec']))
# Note that moonphase is 0-100 (translate to 0-1). 0=new.
moonPhase = np.mean(simdatasubset[obsnow]['moonPhase']) / 100.
alpha = np.max([moonPhase, 0.15])
circle = Circle((lon, moonDec),
radius=0.05,
color='k',
alpha=alpha)
ax.add_patch(circle)
# Add some explanatory text.
ecliptic = Line2D([], [], color='r', label="Ecliptic plane")
galaxy = Line2D([], [], color='b', label="Galactic plane")
horizon = Line2D([], [],
color='k',
alpha=0.3,
label="20 deg elevation limit")
moon = Line2D([], [],
color='k',
linestyle='',
marker='o',
markersize=8,
alpha=alpha,
label="\nMoon (Dark=Full)\n (Light=New)")
zenith = Line2D([], [],
color='k',
linestyle='',
marker='+',
markersize=5,
label="Zenith")
plt.legend(
handles=[horizon, zenith, galaxy, ecliptic, moon],
loc=[0.1, -0.35],
ncol=3,
frameon=False,
title=
'Aitoff plot showing HA/Dec of simulated survey pointings',
numpoints=1,
fontsize='small')
# Save figure.
plt.savefig(os.path.join(
args.outDir,
mb.metric.name + '_' + slicenumber + '_SkyMap.png'),
format='png',
dpi=72)
plt.close('all')
dt, t = dtime(t)
if verbose:
print('Ran and plotted slice %s of movieslicer in %f s' %
(slicenumber, dt))
