2025-09-10_16:41:58 [INFO] : __main__ : Starting main() 2025-09-10_16:41:58 [INFO] : analysis.StatisticsDatabase.sfc : Control Experiment: 2025-06-22-4wks 2025-09-10_16:41:58 [INFO] : analysis.StatisticsDatabase.sfc : ('Non-control Experiment(s): ', ['2025-06-29-4wks']) 2025-09-10_16:41:58 [INFO] : __main__ :  2025-09-10_16:41:58 [INFO] : __main__ : Analyzing StatsDB for sfc 2025-09-10_16:41:58 [INFO] : analysis.StatisticsDatabase.sfc : ===================================================== 2025-09-10_16:41:58 [INFO] : analysis.StatisticsDatabase.sfc : Construct pandas dataframe from static database files 2025-09-10_16:41:58 [INFO] : analysis.StatisticsDatabase.sfc : ===================================================== 2025-09-10_16:41:58 [INFO] : analysis.StatisticsDatabase.sfc : Reading intermediate statistics files 2025-09-10_16:41:58 [INFO] : analysis.StatisticsDatabase.sfc : with 128 out of 128 processors Generating CY-type figures control: 2025-06-22-4wks experiments: ['2025-06-22-4wks:jwittig_3denvar-60-iter_O120km_VarBC.2025-06-22-4wks_cron', '2025-06-29-4wks:jwittig_3denvar-60-iter_O120km_VarBC.2025-06-29-4wks_cron'] obs omb/oma None 2018-05-12 18:00:00 2025-09-10_16:41:59 [INFO] : analysis.StatisticsDatabase.sfc : Working on cycle time 2018-04-15 00:00:00 2025-09-10_16:41:59 [INFO] : analysis.StatisticsDatabase.sfc : Working on cycle time 2018-04-15 06:00:00 2025-09-10_16:41:59 [INFO] : analysis.StatisticsDatabase.sfc : Working on cycle time 2018-04-15 12:00:00 2025-09-10_16:41:59 [INFO] : analysis.StatisticsDatabase.sfc : Working on cycle time 2018-04-15 18:00:00 2025-09-10_16:41:59 [INFO] : analysis.StatisticsDatabase.sfc : Working on cycle time 2018-04-16 00:00:00 2025-09-10_16:41:59 [INFO] : analysis.StatisticsDatabase.sfc : Working on cycle time 2018-04-16 06:00:00 2025-09-10_16:41:59 [INFO] : analysis.StatisticsDatabase.sfc : Working on cycle time 2018-04-16 12:00:00 2025-09-10_16:41:59 [INFO] : analysis.StatisticsDatabase.sfc : Working on 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[INFO] : analysis.StatisticsDatabase.sfc : Concatenating statistics sub-dictionaries from multiple processors 2025-09-10_16:42:14 [INFO] : analysis.StatisticsDatabase.sfc : Constructing a dataframe from statistics dictionary 2025-09-10_16:42:15 [INFO] : analysis.StatisticsDatabase.sfc : Sorting the dataframe index 2025-09-10_16:42:15 [INFO] : analysis.StatisticsDatabase.sfc : Extracting index values 2025-09-10_16:42:17 [INFO] : analysis.StatisticsDatabase.sfc : availableDiagnostics: ['omb', 'sigmaob'] 2025-09-10_16:42:17 [INFO] : analysis.Analyses.sfc : Analyses Constructed 2025-09-10_16:42:17 [INFO] : analysis.Analyses.sfc : Entering Analyses.analyze() 2025-09-10_16:42:17 [INFO] : analysis.AnalysisBase.sfc.CYandBinValAxes2D : analyze() 2025-09-10_16:42:17 [INFO] : analysis.AnalysisBase.sfc.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, :] 2025-09-10_16:42:18 [INFO] : analysis.AnalysisBase.sfc.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, :] 2025-09-10_16:42:20 [INFO] : analysis.Analyses.sfc : Exiting Analyses.analyze() 2025-09-10_16:42:20 [INFO] : __main__ : Finished main() successfully