2025-03-07_09:12:11 [INFO] : __main__ : Starting main()
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua : Control Experiment: 2025-02-16
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua : ('Non-control Experiment(s): ', ['crtm2.4.1'])
2025-03-07_09:12:11 [INFO] : __main__ : 
2025-03-07_09:12:11 [INFO] : __main__ : Analyzing StatsDB for amsua_aqua
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua : =====================================================
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua : Construct pandas dataframe from static database files
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua : =====================================================
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua : Reading intermediate statistics files
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua : with 128 out of 256 processors
Generating CY-type figures
control: 2025-02-16
experiments: ['2025-02-16:jwittig_3denvar-60-iter_O120km_VarBC.2025-02-16_cron', 'crtm2.4.1:jwittig_3denvar-60-iter_O120km_VarBC.crtm2.4.1']
obs omb/oma None 2018-04-21 18:00:00
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-15 00:00:00
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-15 06:00:00
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-15 12:00:00
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-15 18:00:00
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-16 00:00:00
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-16 06:00:00
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-16 12:00:00
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-16 18:00:00
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-17 00:00:00
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-17 06:00:00
2025-03-07_09:12:11 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-17 12:00:00
2025-03-07_09:12:12 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-17 18:00:00
2025-03-07_09:12:12 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-18 00:00:00
2025-03-07_09:12:12 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-18 06:00:00
2025-03-07_09:12:12 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-18 12:00:00
2025-03-07_09:12:12 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-18 18:00:00
2025-03-07_09:12:12 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-19 00:00:00
2025-03-07_09:12:12 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-19 06:00:00
2025-03-07_09:12:12 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-19 12:00:00
2025-03-07_09:12:12 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-19 18:00:00
2025-03-07_09:12:12 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-20 00:00:00
2025-03-07_09:12:12 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-20 06:00:00
2025-03-07_09:12:12 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-20 12:00:00
2025-03-07_09:12:12 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-20 18:00:00
2025-03-07_09:12:12 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-21 00:00:00
2025-03-07_09:12:12 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-21 06:00:00
2025-03-07_09:12:12 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-21 12:00:00
2025-03-07_09:12:12 [INFO] : analysis.StatisticsDatabase.amsua_aqua :   Working on cycle time 2018-04-21 18:00:00
2025-03-07_09:12:31 [INFO] : analysis.StatisticsDatabase.amsua_aqua : Concatenating statistics sub-dictionaries from multiple processors
2025-03-07_09:12:32 [INFO] : analysis.StatisticsDatabase.amsua_aqua : Constructing a dataframe from statistics dictionary
2025-03-07_09:12:38 [INFO] : analysis.StatisticsDatabase.amsua_aqua : Sorting the dataframe index
2025-03-07_09:12:40 [INFO] : analysis.StatisticsDatabase.amsua_aqua : Extracting index values
2025-03-07_09:12:49 [INFO] : analysis.StatisticsDatabase.amsua_aqua : availableDiagnostics: ['omb', 'omb_nobc', 'sigmaob']
2025-03-07_09:12:49 [INFO] : analysis.Analyses.amsua_aqua : Analyses Constructed
2025-03-07_09:12:49 [INFO] : analysis.Analyses.amsua_aqua : Entering Analyses.analyze()
2025-03-07_09:12:49 [INFO] : analysis.AnalysisBase.amsua_aqua.BinValAxisProfileDiffCI : analyze()
2025-03-07_09:12:49 [INFO] : analysis.AnalysisBase.amsua_aqua.BinValAxisProfileDiffCI : 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/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, :]
2025-03-07_09:12:51 [INFO] : analysis.AnalysisBase.amsua_aqua.BinValAxisProfileDiffCI : omb_nobc, 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/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, :]
2025-03-07_09:12:53 [INFO] : analysis.AnalysisBase.amsua_aqua.BinValAxisProfileDiffCI : 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/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, :]
2025-03-07_09:12:55 [INFO] : analysis.Analyses.amsua_aqua : Exiting Analyses.analyze()
2025-03-07_09:12:55 [INFO] : __main__ : Finished main() successfully