Update fO plot defaults, use 750 as min nvis for fO_area

rubin_sim/maf/batches/glance_batch.py

@@ -413,8 +413,8 @@ def glanceBatch(
     metric = metrics.CountExplimMetric(metric_name="fO")
     plotDict = {
         "xlabel": "Number of Visits",
-        "Asky": benchmarkArea,
-        "Nvisit": minNvisits,
+        "asky": benchmarkArea,
+        "n_visits": minNvisits,
         "x_min": 0,
         "x_max": 1500,
     }

rubin_sim/maf/batches/info_batch.py

@@ -11,12 +11,12 @@ def info_bundle_dicts(allsky_slicer, wfd_slicer, opsim="opsim", colmap=batches.c
     bdict = {}
 
     for tag, slicer in zip(["All sky", "WFD"], [allsky_slicer, wfd_slicer]):
-        fO = batches.fOBatch(colmap=colmap, runName=opsim, slicer=slicer, extraInfoLabel=tag)
+        fO = batches.fOBatch(colmap=colmap, run_name=opsim, slicer=slicer, extra_info=tag)
         bdict.update(fO)
-        astrometry = batches.astrometryBatch(colmap=colmap, runName=opsim, slicer=slicer, extraInfoLabel=tag)
+        astrometry = batches.astrometryBatch(colmap=colmap, run_name=opsim, slicer=slicer, extra_info=tag)
         bdict.update(astrometry)
         rapidrevisit = batches.rapidRevisitBatch(
-            colmap=colmap, runName=opsim, slicer=slicer, extraInfoLabel=tag
+            colmap=colmap, run_name=opsim, slicer=slicer, extra_info=tag
         )
         bdict.update(rapidrevisit)
 

rubin_sim/maf/batches/radar_limited.py

@@ -80,8 +80,8 @@ def radar_limited(
     metric = metrics.CountExplimMetric(col="observationStartMJD", metric_name="fO")
     plotDict = {
         "xlabel": "Number of Visits",
-        "Asky": benchmarkArea,
-        "Nvisit": benchmarkNvisits,
+        "asky": benchmarkArea,
+        "n_visits": benchmarkNvisits,
         "x_min": 0,
         "x_max": 1500,
     }

rubin_sim/maf/batches/science_radar_batch.py

@@ -84,8 +84,8 @@ def science_radar_batch(
     metric = metrics.CountExplimMetric(metric_name="fO")
     plotDict = {
         "xlabel": "Number of Visits",
-        "Asky": benchmarkArea,
-        "Nvisit": minNvisits,
+        "asky": benchmarkArea,
+        "n_visits": minNvisits,
         "x_min": 0,
         "x_max": 1500,
     }

rubin_sim/maf/batches/srd_batch.py

@@ -21,30 +21,36 @@
 
 def fOBatch(
     colmap=None,
-    runName="run_name",
-    extraSql=None,
-    extraInfoLabel=None,
+    run_name="run_name",
+    extra_sql=None,
+    extra_info=None,
     slicer=None,
-    benchmarkArea=18000,
-    benchmarkn_visits=825,
-    minn_visits=750,
+    benchmark_area=18000,
+    benchmark_n_visits=825,
+    min_n_visits=750,
 ):
     """Metrics for calculating fO.
 
     Parameters
     ----------
-    colmap : `dict` or None, optional
+    colmap : `dict` or None, opt
         A dictionary with a mapping of column names.
-    runName : `str`, optional
+    run_name : `str`, opt
         The name of the simulated survey.
-    extraSql : `str` or None, optional
+    extra_sql : `str` or None, opt
         Additional sql constraint to apply to all metrics.
-    extraInfoLabel : `str` or None, optional
+    extra_Info : `str` or None, opt
         Additional info_label to apply to all results.
-    slicer : `rubin_sim.maf.slicer.HealpixSlicer` or None, optional
+    slicer : `rubin_sim.maf.slicer.HealpixSlicer` or None, opt
          This must be a HealpixSlicer or some kind,
          although could be a HealpixSubsetSlicer.
          None will default to HealpixSlicer with nside=64.
+    benchmark_area : `float`, opt
+        Area to use when calculating fO_Nvis, for design.
+    benchmark_n_visits : `float`, opt
+        Nvisits minimum to use when calculating fO_Area, for design.
+    min_n_visits : `float`, opt
+        Nvisits minimum to use when calculating fO_Area, for minimum.
 
     Returns
     -------
@@ -58,13 +64,13 @@ def fOBatch(
     sql = ""
     info_label = "All visits"
     # Add additional sql constraint (such as wfdWhere) and info_label
-    if (extraSql is not None) and (len(extraSql) > 0):
-        sql = extraSql
-        if extraInfoLabel is None:
-            info_label = extraSql.replace("filter =", "").replace("filter=", "")
+    if (extra_sql is not None) and (len(extra_sql) > 0):
+        sql = extra_sql
+        if extra_info is None:
+            info_label = extra_sql.replace("filter =", "").replace("filter=", "")
             info_label = info_label.replace('"', "").replace("'", "")
-    if extraInfoLabel is not None:
-        info_label = extraInfoLabel
+    if extra_info is not None:
+        info_label = extra_info
 
     subgroup = info_label
 
@@ -89,8 +95,8 @@ def fOBatch(
     metric = metrics.CountExplimMetric(metric_name="fO", exp_col=colmap["exptime"])
     plotDict = {
         "xlabel": "Number of Visits",
-        "asky": benchmarkArea,
-        "n_visit": minn_visits,
+        "asky": benchmark_area,
+        "n_visits": min_n_visits,
         "x_min": 0,
         "x_max": 1500,
     }
@@ -99,46 +105,46 @@ def fOBatch(
             nside=nside,
             norm=False,
             metric_name="fOArea",
-            asky=benchmarkArea,
-            n_visit=benchmarkn_visits,
+            asky=benchmark_area,
+            n_visit=benchmark_n_visits,
         ),
         metrics.FOArea(
             nside=nside,
             norm=True,
             metric_name="fOArea/benchmark",
-            asky=benchmarkArea,
-            n_visit=benchmarkn_visits,
+            asky=benchmark_area,
+            n_visit=benchmark_n_visits,
         ),
         metrics.FONv(
             nside=nside,
             norm=False,
             metric_name="fONv",
-            asky=benchmarkArea,
-            n_visit=benchmarkn_visits,
+            asky=benchmark_area,
+            n_visit=benchmark_n_visits,
         ),
         metrics.FONv(
             nside=nside,
             norm=True,
             metric_name="fONv/benchmark",
-            asky=benchmarkArea,
-            n_visit=benchmarkn_visits,
+            asky=benchmark_area,
+            n_visit=benchmark_n_visits,
         ),
         metrics.FOArea(
             nside=nside,
             norm=False,
-            metric_name=f"fOArea_{minn_visits}",
-            asky=benchmarkArea,
-            n_visit=minn_visits,
+            metric_name=f"fOArea_{min_n_visits}",
+            asky=benchmark_area,
+            n_visit=min_n_visits,
         ),
     ]
     caption = "The FO metric evaluates the overall efficiency of observing. "
     caption += (
         "foNv: out of %.2f sq degrees, the area receives at least X and a median of Y visits "
-        "(out of %d, if compared to benchmark). " % (benchmarkArea, benchmarkn_visits)
+        "(out of %d, if compared to benchmark). " % (benchmark_area, benchmark_n_visits)
     )
     caption += (
         "fOArea: this many sq deg (out of %.2f sq deg if compared "
-        "to benchmark) receives at least %d visits. " % (benchmarkArea, benchmarkn_visits)
+        "to benchmark) receives at least %d visits. " % (benchmark_area, benchmark_n_visits)
     )
     displayDict["caption"] = caption
     bundle = mb.MetricBundle(
@@ -154,15 +160,15 @@ def fOBatch(
     bundleList.append(bundle)
     # 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)
 
 
 def astrometryBatch(
     colmap=None,
-    runName="opsim",
-    extraSql=None,
-    extraInfoLabel=None,
+    run_name="opsim",
+    extra_sql=None,
+    extra_info=None,
     slicer=None,
 ):
     """Metrics for evaluating proper motion and parallax.
@@ -171,11 +177,11 @@ def astrometryBatch(
     ----------
     colmap : `dict` or None, optional
         A dictionary with a mapping of column names.
-    runName : `str`, optional
+    run_name : `str`, optional
         The name of the simulated survey.
-    extraSql : `str` or None, optional
+    extra_sql : `str` or None, optional
         Additional sql constraint to apply to all metrics.
-    extraInfoLabel : `str` or None, optional
+    extra_info : `str` or None, optional
         Additional info_label to apply to all results.
     slicer : `rubin_sim.maf.slicer` or None, optional
         Optionally, specify something other than an nside=64 healpix slicer.
@@ -191,13 +197,13 @@ def astrometryBatch(
     sql = ""
     info_label = "All visits"
     # Add additional sql constraint (such as wfdWhere) and info_label
-    if (extraSql is not None) and (len(extraSql) > 0):
-        sql = extraSql
-        if extraInfoLabel is None:
-            info_label = extraSql.replace("filter =", "").replace("filter=", "")
+    if (extra_sql is not None) and (len(extra_sql) > 0):
+        sql = extra_sql
+        if extra_info is None:
+            info_label = extra_sql.replace("filter =", "").replace("filter=", "")
             info_label = info_label.replace('"', "").replace("'", "")
-    if extraInfoLabel is not None:
-        info_label = extraInfoLabel
+    if extra_info is not None:
+        info_label = extra_info
 
     subgroup = info_label
 
@@ -466,15 +472,15 @@ def astrometryBatch(
 
     # 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)
 
 
 def rapidRevisitBatch(
     colmap=None,
-    runName="opsim",
-    extraSql=None,
-    extraInfoLabel=None,
+    run_name="opsim",
+    extra_sql=None,
+    extra_info=None,
     slicer=None,
 ):
     """Metrics for evaluating proper motion and parallax.
@@ -483,11 +489,11 @@ def rapidRevisitBatch(
     ----------
     colmap : `dict` or None, optional
         A dictionary with a mapping of column names.
-    runName : `str`, optional
+    run_name : `str`, optional
         The name of the simulated survey.
-    extraSql : `str` or None, optional
+    extra_sql : `str` or None, optional
         Additional sql constraint to apply to all metrics.
-    extraInfoLabel : `str` or None, optional
+    extra_info : `str` or None, optional
         Additional info_label to apply to all results.
     slicer : `rubin_sim_maf.slicers.HealpixSlicer` or None, optional
         Optionally, specify something other than an nside=64 healpix slicer.
@@ -504,13 +510,13 @@ def rapidRevisitBatch(
     sql = ""
     info_label = "All visits"
     # Add additional sql constraint (such as wfdWhere) and info_label.
-    if (extraSql is not None) and (len(extraSql) > 0):
-        sql = extraSql
-        if extraInfoLabel is None:
-            info_label = extraSql.replace("filter =", "").replace("filter=", "")
+    if (extra_sql is not None) and (len(extra_sql) > 0):
+        sql = extra_sql
+        if extra_info is None:
+            info_label = extra_sql.replace("filter =", "").replace("filter=", "")
             info_label = info_label.replace('"', "").replace("'", "")
-    if extraInfoLabel is not None:
-        info_label = extraInfoLabel
+    if extra_info is not None:
+        info_label = extra_info
 
     subgroup = info_label
 
@@ -623,5 +629,5 @@ def rapidRevisitBatch(
 
     # 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/plots/special_plotters.py

@@ -75,34 +75,37 @@ def __call__(self, metric_value, slicer, user_plot_dict, fignum=None):
         )
         # This results in calculating the summary stats in two places ..
         # not the ideal choice but easiest for most uses in this case.
+        asky = plot_dict["asky"]
+        n_visits = plot_dict["n_visits"]
         rarr = np.array(list(zip(metric_value.compressed())), dtype=[("fO", metric_value.dtype)])
         f_o_area = metrics.FOArea(
-            col="fO", n_visit=plot_dict["n_visits"], norm=False, nside=slicer.nside
+            col="fO", n_visit=n_visits, norm=False, nside=slicer.nside
         ).run(rarr)
-        f_o_nv = metrics.FONv(col="fO", asky=plot_dict["asky"], norm=False, nside=slicer.nside).run(rarr)
+        f_o_nv = metrics.FONv(col="fO", asky=asky, norm=False, nside=slicer.nside).run(rarr)
 
-        plt.axvline(x=plot_dict["n_visits"], linewidth=plot_dict["reflinewidth"], color="b")
-        plt.axhline(y=plot_dict["asky"] / 1000.0, linewidth=plot_dict["reflinewidth"], color="r")
+        plt.axvline(x=n_visits, linewidth=plot_dict["reflinewidth"], color="b", linestyle=':')
+        plt.axhline(y=asky / 1000.0, linewidth=plot_dict["reflinewidth"], color="r", linestyle=':')
         # Add lines for nvis_median and f_o_area:
         # note if these are -666 (badval), they will 'disappear'
-        nvis_median = f_o_nv["value"][np.where(f_o_nv["name"] == "MedianNvis")]
+        nvis_median = f_o_nv["value"][np.where(f_o_nv["name"] == "MedianNvis")][0]
+
         plt.axvline(
             x=nvis_median,
             linewidth=plot_dict["reflinewidth"],
             color="b",
             alpha=0.5,
-            linestyle=":",
-            label=r"f$_0$ Median n_visits=%.0f" % nvis_median,
+            linestyle="-",
+            label=f"f$_0$ Med. Nvis. (@ {asky/1000 :.0f}K sq deg) = {nvis_median :.0f} visits",
         )
         plt.axhline(
             y=f_o_area / 1000.0,
             linewidth=plot_dict["reflinewidth"],
             color="r",
             alpha=0.5,
-            linestyle=":",
-            label="f$_0$ Area=%.0f" % f_o_area,
+            linestyle="-",
+            label=f"f$_0$ Area (@ {n_visits :.0f} visits) = {f_o_area/1000 :.01f}K sq deg",
         )
-        plt.legend(loc="lower left", fontsize="small", numpoints=1)
+        plt.legend(loc="upper right", fontsize="small", numpoints=1, framealpha=1.0)
 
         plt.xlabel(plot_dict["xlabel"])
         plt.ylabel(plot_dict["ylabel"])