U/yoachim/fo plot fix

rubin_sim/maf/batches/col_map_dict.py

@@ -26,8 +26,6 @@ def col_map_dict(dict_name=None):
         col_map["seeingGeom"] = "seeingFwhmGeom"
         col_map["skyBrightness"] = "skyBrightness"
         col_map["moonDistance"] = "moonDistance"
-        col_map["fieldId"] = "fieldId"
-        col_map["proposalId"] = "proposalId"
         col_map["slewactivities"] = {}
         col_map["metadataList"] = [
             "airmass",
@@ -41,7 +39,7 @@ def col_map_dict(dict_name=None):
             "saturation_mag",
         ]
         col_map["metadataAngleList"] = ["rotSkyPos"]
-        col_map["note"] = "note"
+        col_map["scheduler_note"] = "scheduler_note"
 
     elif dict_name == "opsimv4":
         col_map = {}

rubin_sim/maf/batches/ddf_batch.py

@@ -2,7 +2,13 @@
 
 import healpy as hp
 import numpy as np
-from rubin_scheduler.utils import angular_separation, ddf_locations, hpid2_ra_dec, sample_patch_on_sphere
+from rubin_scheduler.utils import (
+    angular_separation,
+    ddf_locations,
+    ddf_locations_pre3_5,
+    hpid2_ra_dec,
+    sample_patch_on_sphere,
+)
 
 import rubin_sim.maf as maf
 
@@ -16,6 +22,7 @@ def ddfBatch(
     nside_sne=128,
     extra_sql=None,
     extra_info_label=None,
+    old_coords=False,
 ):
     """
     A set of metrics to evaluate DDF fields.
@@ -42,6 +49,8 @@ def ddfBatch(
         necessary sql constraints for each metric.
     extra_info_label : `str`, optional
         Additional description information to add (alongside the extra_sql)
+    old_coords : `bool`
+        Use the default locations for the DDFs from pre-July 2024. Default False.
 
     Returns
     -------
@@ -53,7 +62,10 @@ def ddfBatch(
     # Define the slicer to use for each DDF
     # Get standard DDF locations and reformat information as a dictionary
     ddfs = {}
-    ddfs_rough = ddf_locations()
+    if old_coords:
+        ddfs_rough = ddf_locations_pre3_5()
+    else:
+        ddfs_rough = ddf_locations()
     for ddf in ddfs_rough:
         ddfs[ddf] = {"ra": ddfs_rough[ddf][0], "dec": ddfs_rough[ddf][1]}
     # Combine the Euclid double-field into one - but with two ra/dec values
@@ -474,7 +486,7 @@ def ddfBatch(
             for f in filterlist:
                 fieldsqls[f] = sqls[f]
         else:
-            fieldsql = f"note like '%{fieldname}%'"
+            fieldsql = f"scheduler_note like '%{fieldname}%'"
             for f in filterlist:
                 if len(sqls[f]) > 0:
                     fieldsqls[f] = fieldsql + " and " + sqls[f]

rubin_sim/maf/batches/glance_batch.py

@@ -144,7 +144,7 @@ def glanceBatch(
         bundle_list.append(bundle)
 
     # alt az of long gaps
-    sql = "note = 'long'"
+    sql = "scheduler_note = 'long'"
     metric = metrics.CountMetric(colmap["mjd"], metric_name="Nvisits long")
     bundle = metric_bundles.MetricBundle(
         metric,
@@ -156,7 +156,7 @@ def glanceBatch(
     )
     bundle_list.append(bundle)
 
-    sql = "note like 'blob_long%'"
+    sql = "scheduler_note like 'blob_long%'"
     metric = metrics.CountMetric(colmap["mjd"], metric_name="Nvisits blob long")
     bundle = metric_bundles.MetricBundle(
         metric,
@@ -168,7 +168,7 @@ def glanceBatch(
     )
     bundle_list.append(bundle)
 
-    sql = "note like '%neo%' or note like '%near_sun%'"
+    sql = "scheduler_note like '%neo%' or scheduler_note like '%near_sun%'"
     metric = metrics.CountMetric(colmap["mjd"], metric_name="Nvisits twilight near sun")
     bundle = metric_bundles.MetricBundle(
         metric,
@@ -182,7 +182,7 @@ def glanceBatch(
 
     # alt,az pf ToO
 
-    sql = "note like 'ToO%'"
+    sql = "scheduler_note like 'ToO%'"
     metric = metrics.CountMetric(colmap["mjd"], metric_name="Nvisits long")
     bundle = metric_bundles.MetricBundle(
         metric,
@@ -277,7 +277,7 @@ def glanceBatch(
         bundle_list.append(bundle)
 
     # Make a cumulative plot of a WFD spot
-    sql = "note not like '%NEO%' and note not like '%near_sun%'"
+    sql = "scheduler_note not like '%NEO%' and scheduler_note not like '%near_sun%'"
     uslicer = slicers.UserPointsSlicer(ra=0, dec=-20)
     metric = metrics.CumulativeMetric()
     metricb = metric_bundles.MetricBundle(
@@ -362,16 +362,16 @@ def glanceBatch(
     )
     bundle_list.append(bundle)
 
-    # stats from the note column
-    if "note" in colmap.keys():
+    # stats from the scheduler_note column
+    if "scheduler_note" in colmap.keys():
         displayDict = {"group": "Basic Stats", "subgroup": "Percent stats"}
-        metric = metrics.StringCountMetric(col=colmap["note"], percent=True, metric_name="Percents")
+        metric = metrics.StringCountMetric(col=colmap["scheduler_note"], percent=True, metric_name="Percents")
         sql = ""
         slicer = slicers.UniSlicer()
         bundle = metric_bundles.MetricBundle(metric, slicer, sql, display_dict=displayDict)
         bundle_list.append(bundle)
         displayDict["subgroup"] = "Count Stats"
-        metric = metrics.StringCountMetric(col=colmap["note"], metric_name="Counts")
+        metric = metrics.StringCountMetric(col=colmap["scheduler_note"], metric_name="Counts")
         bundle = metric_bundles.MetricBundle(metric, slicer, sql, display_dict=displayDict)
         bundle_list.append(bundle)
 
@@ -381,7 +381,7 @@ def glanceBatch(
     displayDict["subgroup"] = ""
     for ddf in ddf_surveys:
         label = ddf.replace("DD:", "")
-        sql = 'note like "%s%%"' % ("DD:" + label)
+        sql = 'scheduler_note like "%s%%"' % ("DD:" + label)
         slicer = slicers.UniSlicer()
         metric = metrics.CumulativeMetric()
         metricb = metric_bundles.MetricBundle(
@@ -515,7 +515,7 @@ def glanceBatch(
         lat_lon_deg=colmap["raDecDeg"],
     )
     for filtername in filternames:
-        sql = "filter='%s' and note like 'ToO%%'" % filtername
+        sql = "filter='%s' and scheduler_note like 'ToO%%'" % filtername
         metric = metrics.CountMetric(col=colmap["mjd"], metric_name="N ToO")
         bundle = metric_bundles.MetricBundle(
             metric,
@@ -528,7 +528,9 @@ def glanceBatch(
         )
         bundle_list.append(bundle)
 
-    too_sqls = ["note like 'ToO, %" + "t%i'" % hour for hour in [0, 1, 2, 4, 24, 48]] + ["note like 'ToO, %'"]
+    too_sqls = ["scheduler_note like 'ToO, %" + "t%i'" % hour for hour in [0, 1, 2, 4, 24, 48]] + [
+        "scheduler_note like 'ToO, %'"
+    ]
     slicer = slicers.UniSlicer()
     for sql in too_sqls:
         metric = metrics.CountMetric(col="night")

rubin_sim/maf/batches/info_batch.py

@@ -61,7 +61,7 @@ def info_bundle_dicts(allsky_slicer, wfd_slicer, opsim="opsim", colmap=batches.c
             colmap,
             opsim,
             slicer=allsky_slicer,
-            extraSql='night > 365*3.5 and night < 365*4.5 and note not like "%DD%"',
+            extraSql='night > 365*3.5 and night < 365*4.5 and scheduler_note not like "%DD%"',
             extraInfoLabel="Yr 3-4",
             runLength=1,
         )
@@ -87,7 +87,7 @@ def info_bundle_dicts(allsky_slicer, wfd_slicer, opsim="opsim", colmap=batches.c
             extraInfoLabel="WFD",
         )
     )
-    dd_constraint = "note like '%DD%'"
+    dd_constraint = "scheduler_note like '%DD%'"
     bdict.update(
         batches.nvisitsPerSubset(
             colmap,

rubin_sim/maf/batches/radar_limited.py

@@ -529,7 +529,7 @@ def radar_limited(
     for yr_cut in yrs:
         ptsrc_lim_mag_i_band = mag_cuts[yr_cut]
         sqlconstraint = "night <= %s" % (yr_cut * 365.25 + 0.5)
-        sqlconstraint += ' and note not like "DD%"'
+        sqlconstraint += ' and scheduler_note not like "DD%"'
         info_label = f"{bandpass} band non-DD year {yr_cut}"
         ThreebyTwoSummary_simple = metrics.StaticProbesFoMEmulatorMetricSimple(
             nside=nside, year=yr_cut, metric_name="3x2ptFoM_simple"
@@ -581,7 +581,7 @@ def radar_limited(
     subgroupCount += 1
     displayDict["subgroup"] = f"{subgroupCount}: WL"
     displayDict["order"] = 0
-    sqlconstraint = 'note not like "DD%" and (filter="g" or filter="r" or filter="i")'
+    sqlconstraint = 'scheduler_note not like "DD%" and (filter="g" or filter="r" or filter="i")'
     info_label = "gri band non-DD"
     minExpTime = 15
     m = metrics.WeakLensingNvisits(
@@ -612,7 +612,7 @@ def radar_limited(
     # Do the weak lensing per year
     for year in [10]:
         sqlconstraint = (
-            'note not like "DD%"'
+            'scheduler_note not like "DD%"'
             + ' and (filter="g" or filter="r" or filter="i") and night < %i' % (year * 365.25)
         )
         m = metrics.WeakLensingNvisits(
@@ -648,7 +648,7 @@ def radar_limited(
         bundleList.append(bundle)
 
         sqlconstraint = (
-            'note not like "DD%"'
+            'scheduler_note not like "DD%"'
             + ' and (filter="r" or filter="i" or filter="z") and night < %i' % (year * 365.25)
         )
         m = metrics.WeakLensingNvisits(
@@ -741,7 +741,7 @@ def radar_limited(
     bundle = mb.MetricBundle(
         metric,
         snslicer,
-        "note not like '%DD%'",
+        "scheduler_note not like '%DD%'",
         plot_dict=plotDict,
         display_dict=displayDict,
         info_label="DDF excluded",
@@ -925,7 +925,7 @@ def radar_limited(
     bundle = mb.MetricBundle(
         metric,
         kneslicer,
-        "note not like 'DD%'",
+        "scheduler_note not like 'DD%'",
         run_name=runName,
         info_label="single model",
         summary_metrics=lightcurve_summary(),
@@ -947,7 +947,7 @@ def radar_limited(
     bundle = mb.MetricBundle(
         metric_allkne,
         kneslicer_allkne,
-        "note not like 'DD%'",
+        "scheduler_note not like 'DD%'",
         run_name=runName,
         info_label="all models",
         summary_metrics=lightcurve_summary(),

rubin_sim/maf/batches/science_radar_batch.py

@@ -568,7 +568,7 @@ def science_radar_batch(
     for yr_cut in yrs:
         ptsrc_lim_mag_i_band = mag_cuts[yr_cut]
         sqlconstraint = "night <= %s" % (yr_cut * 365.25 + 0.5)
-        sqlconstraint += ' and note not like "DD%"'
+        sqlconstraint += ' and scheduler_note not like "DD%"'
         info_label = f"{bandpass} band non-DD year {yr_cut}"
         ThreebyTwoSummary_simple = metrics.StaticProbesFoMEmulatorMetricSimple(
             nside=nside, year=yr_cut, metric_name="3x2ptFoM_simple"
@@ -614,7 +614,7 @@ def science_radar_batch(
     plotDict = {"n_ticks": 5}
     # Have to include all filters in query to check for filter coverage.
     # Galaxy numbers calculated using 'bandpass' images only though.
-    sqlconstraint = 'note not like "DD%"'
+    sqlconstraint = 'scheduler_note not like "DD%"'
     info_label = f"{bandpass} band galaxies non-DD"
     metric = maf.DepthLimitedNumGalMetric(
         nside=nside,
@@ -654,7 +654,7 @@ def science_radar_batch(
     subgroupCount += 1
     displayDict["subgroup"] = f"{subgroupCount}: WL"
     displayDict["order"] = 0
-    sqlconstraint = 'note not like "DD%" and (filter="g" or filter="r" or filter="i")'
+    sqlconstraint = 'scheduler_note not like "DD%" and (filter="g" or filter="r" or filter="i")'
     info_label = "gri band non-DD"
     minExpTime = 15
     m = metrics.WeakLensingNvisits(
@@ -686,7 +686,7 @@ def science_radar_batch(
     for year in np.arange(1, 10):
         displayDict["order"] = year
         sqlconstraint = (
-            'note not like "DD%"'
+            'scheduler_note not like "DD%"'
             + ' and (filter="g" or filter="r" or filter="i") and night < %i' % (year * 365.25)
         )
         m = metrics.WeakLensingNvisits(
@@ -722,7 +722,7 @@ def science_radar_batch(
         bundleList.append(bundle)
 
         sqlconstraint = (
-            'note not like "DD%"'
+            'scheduler_note not like "DD%"'
             + ' and (filter="r" or filter="i" or filter="z") and night < %i' % (year * 365.25)
         )
         m = metrics.WeakLensingNvisits(
@@ -781,7 +781,7 @@ def science_radar_batch(
     # Kuiper per year in gri and riz
     for year in np.arange(1, 10):
         sqlconstraint = (
-            'note not like "DD%"'
+            'scheduler_note not like "DD%"'
             + ' and (filter="g" or filter="r" or filter="i") and night < %i' % (year * 365.25)
         )
         metric1 = metrics.KuiperMetric("rotSkyPos", metric_name="Kuiper_rotSkyPos_gri_year%i" % year)
@@ -835,7 +835,7 @@ def science_radar_batch(
     bundle = mb.MetricBundle(
         metric,
         snslicer,
-        "note not like '%DD%'",
+        "scheduler_note not like '%DD%'",
         plot_dict=plotDict,
         display_dict=displayDict,
         info_label="DDF excluded",
@@ -858,7 +858,7 @@ def science_radar_batch(
 
     # Calculate the number of expected QSOs, in each band
     for f in filterlist:
-        sql = filtersqls[f] + ' and note not like "%DD%"'
+        sql = filtersqls[f] + ' and scheduler_note not like "%DD%"'
         md = filterinfo_label[f] + " and non-DD"
         summaryMetrics = [metrics.SumMetric(metric_name="Total QSO")]
         zmin = 0.3
@@ -1359,7 +1359,7 @@ def science_radar_batch(
     bundle = mb.MetricBundle(
         metric,
         kneslicer,
-        "note not like 'DD%'",
+        "scheduler_note not like 'DD%'",
         run_name=runName,
         info_label="single model",
         summary_metrics=lightcurve_summary(),
@@ -1381,7 +1381,7 @@ def science_radar_batch(
     bundle = mb.MetricBundle(
         metric_allkne,
         kneslicer_allkne,
-        "note not like 'DD%'",
+        "scheduler_note not like 'DD%'",
         run_name=runName,
         info_label="all models",
         summary_metrics=lightcurve_summary(),

rubin_sim/maf/ddf_dir.py

@@ -21,6 +21,9 @@ def ddf_dir():
     parser = argparse.ArgumentParser()
     parser.add_argument("--db", type=str, default=None)
     parser.add_argument("--nside", type=int, default=512)
+    parser.add_argument("--old_coords", dest="old_coords", action="store_true")
+    parser.set_defaults(verbose=False)
+
     args = parser.parse_args()
 
     if args.db is None:
@@ -35,7 +38,7 @@ def ddf_dir():
             shutil.rmtree(name + "_ddf")
 
         bdict = {}
-        bdict.update(batches.ddfBatch(run_name=name, nside=args.nside))
+        bdict.update(batches.ddfBatch(run_name=name, nside=args.nside, old_coords=args.old_coords))
         results_db = db.ResultsDb(out_dir=name + "_ddf")
         group = mb.MetricBundleGroup(
             bdict,

rubin_sim/maf/metrics/sn_n_sn_metric.py

@@ -86,7 +86,7 @@ def __init__(
         nexp_col="numExposures",
         vistime_col="visitTime",
         seeing_col="seeingFwhmEff",
-        note_col="note",
+        note_col="scheduler_note",
         season=[-1],
         coadd_night=True,
         zmin=0.1,

rubin_sim/maf/metrics/use_metrics.py

@@ -8,7 +8,7 @@
 class UseMetric(BaseMetric):  # pylint: disable=too-few-public-methods
     """Metric to classify visits by type of visits"""
 
-    def __init__(self, note_col="note", **kwargs):
+    def __init__(self, note_col="scheduler_note", **kwargs):
         self.note_col = note_col
         super().__init__(col=[note_col], metric_dtype="object", **kwargs)