OPSIM:1050 Update m52snr and add y-band parallax metric

rubin_sim/maf/batches/common.py

@@ -13,7 +13,6 @@
     "microlensing_summary",
 )
 
-import inspect
 
 import rubin_sim.maf.metrics as metrics
 

rubin_sim/maf/batches/glance_batch.py

@@ -473,7 +473,7 @@ def glanceBatch(
     for filtername in filternames:
         sql = "filter='%s' and night < 365" % filtername
         metric = metrics.CountMetric(col="night", metric_name="N year 1")
-        summary_stat = metrics.FootprintFraction(
+        summary_stat = metrics.FootprintFractionMetric(
             footprint=footprints_hp_array[filtername],
             n_min=3,
         )
@@ -499,7 +499,7 @@ def glanceBatch(
 
     # Add basic slew stats.
     try:
-        slewDict = slewBasics(colmap=colmap, runName=run_name)
+        slewDict = slewBasics(colmap=colmap, run_name=run_name)
         bd.update(slewDict)
     except KeyError as e:
         warnings.warn("Could not add slew stats: missing required key %s from colmap" % (e))

rubin_sim/maf/batches/moving_objects_batch.py

@@ -183,14 +183,14 @@ def _setup_child_metrics(parentMetric):
     def _configure_child_bundles(parentBundle):
         dispDict = {
             "group": f"{objtype}",
-            "subgroup": f"Completeness Over Time",
+            "subgroup": "Completeness Over Time",
             "caption": "Time of discovery of objects",
             "order": 0,
         }
         parentBundle.child_bundles["Time"].set_display_dict(dispDict)
         dispDict = {
             "group": f"{objtype}",
-            "subgroup": f"N Chances",
+            "subgroup": "N Chances",
             "caption": "Number of chances for discovery of objects",
             "order": 0,
         }
@@ -326,14 +326,14 @@ def _setup_child_metrics(parentMetric):
     def _configure_child_bundles(parentBundle):
         dispDict = {
             "group": f"{objtype}",
-            "subgroup": f"Completeness Over Time",
+            "subgroup": "Completeness Over Time",
             "caption": "Time of discovery of objects",
             "order": 0,
         }
         parentBundle.child_bundles["Time"].set_display_dict(dispDict)
         dispDict = {
             "group": f"{objtype}",
-            "subgroup": f"N Chances",
+            "subgroup": "N Chances",
             "caption": "Number of chances for discovery of objects",
             "order": 0,
         }
@@ -734,7 +734,7 @@ def _compbundles(b, bundle, h_mark, results_db):
     # Write the completeness bundles to disk, so we can re-read them later.
     # (also set the display dict properties, for the results_db output).
     for b, bundle in completeness.items():
-        bundle.display_dict["subgroup"] = f"Completeness"
+        bundle.display_dict["subgroup"] = "Completeness"
         bundle.write(out_dir=out_dir, results_db=results_db)
 
     # Calculate total number of objects - currently for NEOs and PHAs only
@@ -825,7 +825,7 @@ def _codePlot(key):
     plt.grid(True, alpha=0.3)
     # Make a PlotHandler to deal with savings/results_db, etc.
     ph = plots.PlotHandler(fig_format=fig_format, results_db=results_db, out_dir=out_dir)
-    display_dict["subgroup"] = f"Completeness over time"
+    display_dict["subgroup"] = "Completeness over time"
     display_dict["caption"] = "Completeness over time, for H values indicated in legend."
     ph.save_fig(
         fig.number,
@@ -881,7 +881,7 @@ def _codePlot(key):
         "legendloc": (1.01, 0.1),
         "color": None,
     }
-    display_dict["subgroup"] = f"Completeness all criteria"
+    display_dict["subgroup"] = "Completeness all criteria"
     display_dict["caption"] = "Plotting all of the cumulative completeness curves together."
     ph.plot(
         plot_func=plots.MetricVsH(),
@@ -949,7 +949,7 @@ def characterization_inner_batch(
 
     # Number of observations.
     md = info_label
-    display_dict["subgroup"] = f"N Obs"
+    display_dict["subgroup"] = "N Obs"
     plotDict = {
         "ylabel": "Number of observations (#)",
         "title": "%s: Number of observations %s" % (run_name, md),
@@ -971,7 +971,7 @@ def characterization_inner_batch(
 
     # Observational arc.
     md = info_label
-    display_dict["subgroup"] = f"Obs Arc"
+    display_dict["subgroup"] = "Obs Arc"
     plotDict = {
         "ylabel": "Observational Arc (days)",
         "title": "%s: Observational Arc Length %s" % (run_name, md),
@@ -992,7 +992,7 @@ def characterization_inner_batch(
     bundleList.append(bundle)
 
     # Activity detection.
-    display_dict["subgroup"] = f"Activity"
+    display_dict["subgroup"] = "Activity"
     for w in windows:
         md = info_label + " activity lasting %.0f days" % w
         plotDict = {
@@ -1037,7 +1037,7 @@ def characterization_inner_batch(
 
     # Lightcurve inversion.
     md = info_label
-    display_dict["subgroup"] = f"Color/Inversion"
+    display_dict["subgroup"] = "Color/Inversion"
     plotDict = {
         "y_min": 0,
         "y_max": 1,
@@ -1146,7 +1146,7 @@ def characterization_outer_batch(
 
     # Number of observations.
     md = info_label
-    display_dict["subgroup"] = f"N Obs"
+    display_dict["subgroup"] = "N Obs"
     plotDict = {
         "ylabel": "Number of observations (#)",
         "title": "%s: Number of observations %s" % (run_name, md),
@@ -1168,7 +1168,7 @@ def characterization_outer_batch(
 
     # Observational arc.
     md = info_label
-    display_dict["subgroup"] = f"Obs Arc"
+    display_dict["subgroup"] = "Obs Arc"
     plotDict = {
         "ylabel": "Observational Arc (days)",
         "title": "%s: Observational Arc Length %s" % (run_name, md),
@@ -1189,7 +1189,7 @@ def characterization_outer_batch(
     bundleList.append(bundle)
 
     # Activity detection.
-    display_dict["subgroup"] = f"Activity"
+    display_dict["subgroup"] = "Activity"
     for w in windows:
         md = info_label + " activity lasting %.0f days" % w
         plotDict = {
@@ -1234,7 +1234,7 @@ def characterization_outer_batch(
 
     # Color determination.
     md = info_label
-    display_dict["subgroup"] = f"Color/Inversion"
+    display_dict["subgroup"] = "Color/Inversion"
     plotDict = {
         "y_min": 0,
         "y_max": 1,
@@ -1375,7 +1375,7 @@ def plot_fractions(
     if figroot is None:
         figroot = run_name
     display_dict = deepcopy(first.display_dict)
-    display_dict["subgroup"] = f"Characterization Fraction"
+    display_dict["subgroup"] = "Characterization Fraction"
 
     ph = plots.PlotHandler(fig_format=fig_format, results_db=results_db, out_dir=out_dir)
     ph.set_metric_bundles(bdictFractions)

rubin_sim/maf/batches/radar_limited.py

@@ -568,8 +568,8 @@ def radar_limited(
     subgroupCount += 1
     displayDict["subgroup"] = f"{subgroupCount}: WL"
     displayDict["order"] = 0
-    sqlconstraint = f'note not like "DD%" and (filter="g" or filter="r" or filter="i")'
-    info_label = f"gri band non-DD"
+    sqlconstraint = 'note not like "DD%" and (filter="g" or filter="r" or filter="i")'
+    info_label = "gri band non-DD"
     minExpTime = 15
     m = metrics.WeakLensingNvisits(
         lsst_filter=bandpass,

rubin_sim/maf/batches/science_radar_batch.py

@@ -589,7 +589,7 @@ def science_radar_batch(
     plotDict = {"n_ticks": 5}
     # Have to include all filters in query, so that we check for all-band coverage.
     # Galaxy numbers calculated using 'bandpass' images only though.
-    sqlconstraint = f'note not like "DD%"'
+    sqlconstraint = 'note not like "DD%"'
     info_label = f"{bandpass} band galaxies non-DD"
     metric = maf.DepthLimitedNumGalMetric(
         nside=nside,
@@ -628,8 +628,8 @@ def science_radar_batch(
     subgroupCount += 1
     displayDict["subgroup"] = f"{subgroupCount}: WL"
     displayDict["order"] = 0
-    sqlconstraint = f'note not like "DD%" and (filter="g" or filter="r" or filter="i")'
-    info_label = f"gri band non-DD"
+    sqlconstraint = 'note not like "DD%" and (filter="g" or filter="r" or filter="i")'
+    info_label = "gri band non-DD"
     minExpTime = 15
     m = metrics.WeakLensingNvisits(
         lsst_filter=bandpass,
@@ -1457,9 +1457,9 @@ def science_radar_batch(
     plotDict = {"color_min": 0, "color_max": 1500, "x_min": 0, "x_max": 2000}
     displayDict["order"] = 0
     displayDict["caption"] = (
-        f"Evaluate the distribution of filter pairs and time gaps at each point in "
-        f"the sky. The time gaps are evaluated on a logarithmic spacing "
-        f"from 0-100 days for pairs of filters, and 0-3650 days for same filters."
+        "Evaluate the distribution of filter pairs and time gaps at each point in "
+        "the sky. The time gaps are evaluated on a logarithmic spacing "
+        "from 0-100 days for pairs of filters, and 0-3650 days for same filters."
     )
     summarystats = [
         metrics.MedianMetric(),
@@ -1881,8 +1881,8 @@ def science_radar_batch(
     # galaxy counting uses dustmap
     slicer = slicers.HealpixSlicer(nside=nside, use_cache=False)
     displayDict["caption"] = (
-        f"Approximate number of resolvable galaxies in i band, scaled by the "
-        f"coadded depth and median seeing. A dust and magnitude cut has been applied."
+        "Approximate number of resolvable galaxies in i band, scaled by the "
+        "coadded depth and median seeing. A dust and magnitude cut has been applied."
     )
     bundle = mb.MetricBundle(
         metric,
@@ -1901,9 +1901,9 @@ def science_radar_batch(
     # NlcPoints metric uses star density maps
     slicer = slicers.HealpixSlicer(nside=nside, use_cache=False)
     displayDict["caption"] = (
-        f"Approximate number of expected stellar measurements (nstars * nobs) "
-        f"in all filters, where the limiting magnitude for at least 10 visits "
-        f"is fainter than 21st magnitude, using a TRILEGAL stellar density map."
+        "Approximate number of expected stellar measurements (nstars * nobs) "
+        "in all filters, where the limiting magnitude for at least 10 visits "
+        "is fainter than 21st magnitude, using a TRILEGAL stellar density map."
     )
     bundle = mb.MetricBundle(
         metric,

rubin_sim/maf/batches/slew_batch.py

@@ -12,7 +12,7 @@
 from .common import standard_metrics
 
 
-def slewBasics(colmap=None, runName="opsim", sqlConstraint=None):
+def slewBasics(colmap=None, run_name="opsim", sql_constraint=None):
     """Generate a simple set of statistics about the slew times and distances.
     These slew statistics can be run on the summary or default tables.
 
@@ -39,8 +39,8 @@ def slewBasics(colmap=None, runName="opsim", sqlConstraint=None):
     slicer = slicers.UniSlicer()
 
     info_label = "All visits"
-    if sqlConstraint is not None and len(sqlConstraint) > 0:
-        info_label = "%s" % (sqlConstraint)
+    if sql_constraint is not None and len(sql_constraint) > 0:
+        info_label = "%s" % (sql_constraint)
     displayDict = {
         "group": "Slew",
         "subgroup": "Slew Basics",
@@ -51,15 +51,15 @@ def slewBasics(colmap=None, runName="opsim", sqlConstraint=None):
     metric = metrics.CountMetric(colmap["slewtime"], metric_name="Slew Count")
     displayDict["caption"] = "Total number of slews recorded in summary table."
     displayDict["order"] += 1
-    bundle = mb.MetricBundle(metric, slicer, sqlConstraint, info_label=info_label, display_dict=displayDict)
+    bundle = mb.MetricBundle(metric, slicer, sql_constraint, info_label=info_label, display_dict=displayDict)
     bundleList.append(bundle)
     for metric in standard_metrics(colmap["slewtime"]):
         displayDict["caption"] = "%s in seconds." % (metric.name)
         displayDict["order"] += 1
         bundle = mb.MetricBundle(
             metric,
             slicer,
-            sqlConstraint,
+            sql_constraint,
             info_label=info_label,
             display_dict=displayDict,
         )
@@ -75,7 +75,7 @@ def slewBasics(colmap=None, runName="opsim", sqlConstraint=None):
     bundle = mb.MetricBundle(
         metric,
         slicer,
-        sqlConstraint,
+        sql_constraint,
         info_label=info_label,
         plot_dict=plotDict,
         display_dict=displayDict,
@@ -91,7 +91,7 @@ def slewBasics(colmap=None, runName="opsim", sqlConstraint=None):
     bundle = mb.MetricBundle(
         metric,
         slicer,
-        sqlConstraint,
+        sql_constraint,
         info_label=info_label,
         plot_dict=plotDict,
         display_dict=displayDict,
@@ -111,7 +111,7 @@ def slewBasics(colmap=None, runName="opsim", sqlConstraint=None):
         bundle = mb.MetricBundle(
             metric,
             slicer,
-            sqlConstraint,
+            sql_constraint,
             info_label=info_label,
             plot_dict=plotDict,
             display_dict=displayDict,
@@ -134,7 +134,7 @@ def slewBasics(colmap=None, runName="opsim", sqlConstraint=None):
         bundle = mb.MetricBundle(
             metric,
             slicer,
-            sqlConstraint,
+            sql_constraint,
             info_label=info_label,
             plot_dict=plotDict,
             display_dict=displayDict,
@@ -143,5 +143,5 @@ def slewBasics(colmap=None, runName="opsim", sqlConstraint=None):
 
     # Set the run_name for all bundles and return the bundleDict.
     for b in bundleList:
-        b.set_run_name(runName)
+        b.set_run_name(run_name)
     return mb.make_bundles_dict_from_list(bundleList)

rubin_sim/maf/batches/srd_batch.py

@@ -233,7 +233,7 @@ def astrometryBatch(
         "caption": None,
     }
     # Expected error on parallax at 10 AU.
-    plotmaxVals = (2.0, 15.0)
+    plotmaxVals = (5.0, 18.0)
     good_parallax_limit = 11.5
     summary = [
         metrics.AreaSummaryMetric(
@@ -342,6 +342,60 @@ def astrometryBatch(
         bundleList.append(bundle)
         displayDict["order"] += 1
 
+    # Evaluate y-band-only parallax uncertainty
+    # Approximate "10sigma sources" as y=21.33
+    ymag = 21.33
+    if info_label == "All visits":
+        yinfo = "y band visits"
+    else:
+        yinfo = f"{info_label} y band only"
+    if len(sql) == 0:
+        ysql = "filter == 'y'"
+    else:
+        ysql = f"{sql} and filter == 'y'"
+    plotDict = {"x_min": 0, "x_max": 15, "color_min": 0, "color_max": 15}
+    metric = metrics.ParallaxMetric(
+        metric_name="Parallax Uncert @ %.1f" % (ymag),
+        rmag=ymag,
+        seeing_col=colmap["seeingGeom"],
+        filter_col=colmap["filter"],
+        m5_col=colmap["fiveSigmaDepth"],
+        normalize=False,
+    )
+    bundle = mb.MetricBundle(
+        metric,
+        slicer,
+        ysql,
+        info_label=yinfo,
+        stacker_list=[parallaxStacker],
+        display_dict=displayDict,
+        plot_dict=plotDict,
+        summary_metrics=summary,
+        plot_funcs=subsetPlots,
+    )
+    bundleList.append(bundle)
+    displayDict["order"] += 1
+    metric = metrics.ParallaxMetric(
+        metric_name="Normalized Parallax Uncert @ %.1f" % (ymag),
+        rmag=ymag,
+        seeing_col=colmap["seeingGeom"],
+        filter_col=colmap["filter"],
+        m5_col=colmap["fiveSigmaDepth"],
+        normalize=True,
+    )
+    bundle = mb.MetricBundle(
+        metric,
+        slicer,
+        ysql,
+        info_label=yinfo,
+        stacker_list=[parallaxStacker],
+        display_dict=displayDict,
+        summary_metrics=summary,
+        plot_funcs=subsetPlots,
+    )
+    bundleList.append(bundle)
+    displayDict["order"] += 1
+
     # Proper Motion metrics.
     displayDict = {
         "group": "SRD Proper Motion",