def testOpsim2dSlicer(self):
metric = metrics.AccumulateCountMetric(bins=[0.5, 1.5, 2.5])
slicer = slicers.OpsimFieldSlicer()
sql = ''
mb = metricBundle.MetricBundle(metric, slicer, sql)
mbg = metricBundle.MetricBundleGroup({0: mb}, None, saveEarly=False)
mbg.setCurrent('')
mbg.fieldData = self.fieldData
mbg.runCurrent('', simData=self.simData)
expected = np.array([[self.n1, self.n1], [-666., self.n2]])
assert (np.array_equal(mb.metricValues.data, expected))
def testHealpix2dSlicer(self):
metric = metrics.AccumulateCountMetric(bins=[0.5, 1.5, 2.5])
slicer = slicers.HealpixSlicer(nside=16)
sql = ''
mb = metricBundle.MetricBundle(metric, slicer, sql)
mbg = metricBundle.MetricBundleGroup({0: mb}, None, saveEarly=False)
mbg.setCurrent('')
mbg.runCurrent('', simData=self.simData)
good = np.where(mb.metricValues.mask[:, -1] == False)[0]
expected = np.array([[self.n1, self.n1], [-666., self.n2]])
assert (np.array_equal(mb.metricValues.data[good, :], expected))
nside = 128
# Connect to an opsim database, bleeding-edge sims here:
# https://lsst-web.ncsa.illinois.edu/sim-data/sims_featureScheduler_runs/
opsdb = db.OpsimDatabase('baseline_1exp_pairsmix_10yrs.db')
outDir = 'maf_out'
resultsDb = db.ResultsDb(outDir=outDir)
plotFuncs = [plots.TwoDMap()]
filters = ['u', 'g', 'r', 'i', 'z', 'y']
day_max = np.round(365.25 * 2)
bins = np.arange(day_max)
nval = 3
for filtername in filters:
metric = metrics.AccumulateCountMetric(bins=bins)
slicer = slicers.HealpixSlicer(nside=nside)
plotDict = {'xlabel': 'Night (days)', 'cbarTitle': 'N obs', 'colorMax': 75}
# only use i-band
sql = 'filter = "%s" and night < %i' % (filtername, day_max)
bundle = metricBundles.MetricBundle(metric,
slicer,
sql,
plotDict=plotDict,
plotFuncs=plotFuncs)
group = metricBundles.MetricBundleGroup({0: bundle},
opsdb,
outDir=outDir,
resultsDb=resultsDb)
group.runAll()
latCol = 'fieldDec'
lonCol = 'fieldRA'
if extra == 'rotation':
rotSkyPosColName = 'rotatedRotSkyPos'
md += ' Rotated 2nd visit,'
else:
rotSkyPosColName = 'rotSkyPos'
for filterName in filters:
bundleList=[]
mdf = md+' %s, %s' % (filterName,raftConfig)
sql = 'filter="%s" and night < %i' % (filterName,year*365.25)
metric = metrics.AccumulateCountMetric()
bins = np.arange(0,np.ceil(year*365.25)+1,1)
slicer = slicers.Healpix2dSlicer(nside=nside, bins=bins, useCamera=True,
latCol=latCol, lonCol=lonCol,
rotSkyPosColName=rotSkyPosColName)
bundle = metricBundles.MetricBundle(metric,slicer,sql, metadata=mdf+'Single Vendor')
bundle.Single=True
bundleList.append(bundle)
slicer = slicers.Healpix2dSlicer(nside=nside, bins=bins, useCamera=True, chipNames=chips1,
latCol=latCol, lonCol=lonCol,
rotSkyPosColName=rotSkyPosColName)
bundle = metricBundles.MetricBundle(metric,slicer,sql, metadata=mdf+'Vendor 1')
bundleList.append(bundle)
def plot_progress_by_band():
"""Plot LSST progress by band.
Parameters
----------
Returns
-------
fig : the `matplotlib.figure.Figure`
the figure with the plot
axes : `list(matplotlib.axes.Axes)`
the axes in the plot
"""
ops_db = lsst.sims.maf.db.OpsimDatabase(SIM_DATABASE_FNAME)
vector_bins = np.arange(365 * 10 + 2)
metric = metrics.AccumulateCountMetric(col="observationStartMJD",
bins=vector_bins,
binCol="night")
slicer = slicers.UniSlicer()
bundles = {}
for band in plotprep.BANDS:
sql = f"filter = '{band}'"
bundles[band] = metricBundles.MetricBundle(metric,
slicer,
sql,
plotDict={},
plotFuncs=[],
summaryMetrics=[])
sql = ""
slicer = slicers.OneDSlicer(sliceColName="night", bins=vector_bins)
metric = metrics.MeanMetric(col="moonPhase")
bundles["moon"] = metricBundles.MetricBundle(metric, slicer, sql)
sql = ""
slicer = slicers.OneDSlicer(sliceColName="night", bins=vector_bins)
#metric = metrics.MeanMetric(col="observationStartMJD")
metric = metrics.MeanMetric(col="observationStartMJD")
bundles["mjd"] = metricBundles.MetricBundle(metric, slicer, sql)
metric_group = metricBundles.MetricBundleGroup(bundles, ops_db)
metric_group.runAll()
fig, ax = plt.subplots()
num_nights = NUM_NIGHTS
mjd = bundles["mjd"].metricValues[:num_nights]
for band in plotprep.BANDS:
bundle = bundles[band]
ax.plot(
mjd,
bundle.metricValues[0, :num_nights],
c=plotprep.BAND_COLOR[band],
label=band,
)
ax.scatter(
mjd,
np.zeros(num_nights),
c=bundles["moon"].metricValues[:num_nights],
cmap="cividis",
s=5,
)
ax.legend()
start_date = pd.to_datetime(mjd.min() - 15 + 2400000.5,
unit="D",
origin="julian")
end_date = pd.to_datetime(mjd.max() + 15 + 2400000.5,
unit="D",
origin="julian")
date_seq = pd.date_range(start=start_date, end=end_date, freq="MS")
ax.set_xticks(date_seq.to_julian_date() - 2400000.5)
ax.set_xticklabels(str(d)[:10] for d in date_seq)
ax.set_ylabel("Number of visits")
return fig, ax
def plot_progress_by_quadrant():
"""Plot LSST progress by quadrant of the sky.
Parameters
----------
Returns
-------
fig : the `matplotlib.figure.Figure`
the figure with the plot
axes : `list(matplotlib.axes.Axes)`
the axes in the plot
"""
ops_db = lsst.sims.maf.db.OpsimDatabase(SIM_DATABASE_FNAME)
vector_bins = np.arange(366 * 10)
metric = metrics.AccumulateCountMetric(col="observationStartMJD",
bins=vector_bins,
binCol="night")
slicer = slicers.UniSlicer()
bundles = {}
quads = np.arange(0, 360, 90)
for quad in quads:
sql = f"fieldRA >= {quad} and fieldRA < {quad+90}"
bundles[quad] = metricBundles.MetricBundle(metric,
slicer,
sql,
plotDict={},
plotFuncs=[],
summaryMetrics=[])
sql = ""
slicer = slicers.OneDSlicer(sliceColName="night", bins=vector_bins)
metric = metrics.MeanMetric(col="observationStartMJD")
bundles["mjd"] = metricBundles.MetricBundle(metric, slicer, sql)
metric_group = metricBundles.MetricBundleGroup(bundles, ops_db)
metric_group.runAll()
fig, ax = plt.subplots()
num_nights = NUM_NIGHTS
mjd = bundles["mjd"].metricValues[:num_nights]
for quad in quads:
bundle = bundles[quad]
ax.plot(
mjd,
bundle.metricValues[0, :num_nights],
label=f"{quad}$^\circ$ $\leq$ R.A. < {quad+90}$^\circ$",
)
ax.legend()
start_date = pd.to_datetime(mjd.min() - 15 + 2400000.5,
unit="D",
origin="julian")
end_date = pd.to_datetime(mjd.max() + 15 + 2400000.5,
unit="D",
origin="julian")
date_seq = pd.date_range(start=start_date, end=end_date, freq="Q")
ax.set_xticks(date_seq.to_julian_date() - 2400000.5)
ax.set_xticklabels([str(d)[:10] for d in date_seq], rotation=15)
ax.set_ylabel("Number of visits")
return fig, ax