2025-04-15_02:05:41 [INFO] : __main__ : Starting main()
2025-04-15_02:05:41 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d : Control Experiment: 2025-04-13
2025-04-15_02:05:41 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d : ('Non-control Experiment(s): ', ['2025-04-14'])
2025-04-15_02:05:41 [INFO] : __main__ : 
2025-04-15_02:05:41 [INFO] : __main__ : Analyzing StatsDB for gnssrobndropp1d
2025-04-15_02:05:41 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d : =====================================================
2025-04-15_02:05:41 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d : Construct pandas dataframe from static database files
2025-04-15_02:05:41 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d : =====================================================
2025-04-15_02:05:41 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d : Reading intermediate statistics files
2025-04-15_02:05:41 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d : with 128 out of 128 processors
Generating CY-type figures
control: 2025-04-13
experiments: ['2025-04-13:jwittig_3denvar-60-iter_O120km_VarBC.2025-04-13_cron', '2025-04-14:jwittig_3denvar-60-iter_O120km_VarBC.2025-04-14_cron']
obs omb/oma None 2018-04-21 18:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-15 00:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-15 06:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-15 12:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-15 18:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-16 00:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-16 06:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-16 12:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-16 18:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-17 00:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-17 06:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-17 12:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-17 18:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-18 00:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-18 06:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-18 12:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-18 18:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-19 00:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-19 06:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-19 12:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-19 18:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-20 00:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-20 06:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-20 12:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-20 18:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-21 00:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-21 06:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-21 12:00:00
2025-04-15_02:05:42 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d :   Working on cycle time 2018-04-21 18:00:00
2025-04-15_02:05:47 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d : Concatenating statistics sub-dictionaries from multiple processors
2025-04-15_02:05:47 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d : Constructing a dataframe from statistics dictionary
2025-04-15_02:05:48 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d : Sorting the dataframe index
2025-04-15_02:05:49 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d : Extracting index values
2025-04-15_02:05:50 [INFO] : analysis.StatisticsDatabase.gnssrobndropp1d : availableDiagnostics: ['sigmaob', 'rltv_omb', 'omb']
2025-04-15_02:05:50 [INFO] : analysis.Analyses.gnssrobndropp1d : Analyses Constructed
2025-04-15_02:05:50 [INFO] : analysis.Analyses.gnssrobndropp1d : Entering Analyses.analyze()
2025-04-15_02:05:50 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : analyze()
2025-04-15_02:05:50 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : sigmaob, impact_height, NMid
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:05:51 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : sigmaob, impact_height, NPol
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:05:51 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : sigmaob, impact_height, SMid
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:05:51 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : sigmaob, impact_height, SPol
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:05:52 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : sigmaob, impact_height, Tro
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:05:52 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : sigmaob, impact_height, identity
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:05:53 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : sigmaob, impact_height, alt=10000m
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
2025-04-15_02:05:53 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : sigmaob, lat, alt=10000m
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:05:53 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : sigmaob, lat, identity
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:05:53 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : omb, impact_height, NMid
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:05:55 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : omb, impact_height, NPol
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:05:56 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : omb, impact_height, SMid
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:05:58 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : omb, impact_height, SPol
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:05:59 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : omb, impact_height, Tro
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:06:00 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : omb, impact_height, identity
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:06:02 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : omb, impact_height, alt=10000m
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
2025-04-15_02:06:02 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : omb, lat, alt=10000m
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:06:03 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : omb, lat, identity
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:06:05 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : rltv_omb, impact_height, NMid
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:06:06 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : rltv_omb, impact_height, NPol
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:06:07 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : rltv_omb, impact_height, SMid
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:06:09 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : rltv_omb, impact_height, SPol
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:06:10 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : rltv_omb, impact_height, Tro
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:06:12 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : rltv_omb, impact_height, identity
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:06:13 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : rltv_omb, impact_height, alt=10000m
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
2025-04-15_02:06:13 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : rltv_omb, lat, alt=10000m
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:06:15 [INFO] : analysis.AnalysisBase.gnssrobndropp1d.CYandBinValAxes2D : rltv_omb, lat, identity
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:459: FutureWarning: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version. `series.loc[label, sequence]` will raise if any members of 'sequence' or not present in the index's second level. To retain the old behavior, use `series.index.isin(sequence, level=1)`
  return self.df.loc[Loc, :]
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
/glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/AnalysisBase.py:296: RuntimeWarning: divide by zero encountered in double_scalars
  dmax = np.nanmax([dmax, 1.0/dmin])
2025-04-15_02:06:16 [INFO] : analysis.Analyses.gnssrobndropp1d : Exiting Analyses.analyze()
2025-04-15_02:06:16 [INFO] : __main__ : Finished main() successfully