2025-04-01_14:25:02 [INFO] : __main__ : Starting main() 2025-04-01_14:25:02 [INFO] : analysis.StatisticsDatabase.mpas : Control Experiment: 2025-03-30 2025-04-01_14:25:02 [INFO] : analysis.StatisticsDatabase.mpas : ('Non-control Experiment(s): ', ['2025-03-28']) 2025-04-01_14:25:02 [INFO] : __main__ :  2025-04-01_14:25:02 [INFO] : __main__ : Analyzing StatsDB for mpas 2025-04-01_14:25:02 [INFO] : analysis.StatisticsDatabase.mpas : ===================================================== 2025-04-01_14:25:02 [INFO] : analysis.StatisticsDatabase.mpas : Construct pandas dataframe from static database files 2025-04-01_14:25:02 [INFO] : analysis.StatisticsDatabase.mpas : ===================================================== 2025-04-01_14:25:02 [INFO] : analysis.StatisticsDatabase.mpas : Reading intermediate statistics files 2025-04-01_14:25:02 [INFO] : analysis.StatisticsDatabase.mpas : with 128 out of 128 processors Generating CY-type figures control: 2025-03-30 experiments: ['2025-03-30:jwittig_3denvar-60-iter_O120km_VarBC.2025-03-30_cron', '2025-03-28:jwittig_3denvar-60-iter_O120km_VarBC.2025-03-28_cron'] model forecast None 2018-04-21 18:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-15 00:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-15 06:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-15 12:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-15 18:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-16 00:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-16 06:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-16 12:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-16 18:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-17 00:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-17 06:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-17 12:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-17 18:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-18 00:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-18 06:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-18 12:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-18 18:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-19 00:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-19 06:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-19 12:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-19 18:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-20 00:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-20 06:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-20 12:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-20 18:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-21 00:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-21 06:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-21 12:00:00 2025-04-01_14:25:03 [INFO] : analysis.StatisticsDatabase.mpas : Working on cycle time 2018-04-21 18:00:00 2025-04-01_14:25:20 [INFO] : analysis.StatisticsDatabase.mpas : Concatenating statistics sub-dictionaries from multiple processors 2025-04-01_14:25:20 [INFO] : analysis.StatisticsDatabase.mpas : Constructing a dataframe from statistics dictionary 2025-04-01_14:25:21 [INFO] : analysis.StatisticsDatabase.mpas : Sorting the dataframe index 2025-04-01_14:25:21 [INFO] : analysis.StatisticsDatabase.mpas : Extracting index values 2025-04-01_14:25:25 [INFO] : analysis.StatisticsDatabase.mpas : availableDiagnostics: ['mmgfsan'] 2025-04-01_14:25:25 [INFO] : analysis.Analyses.mpas : Analyses Constructed 2025-04-01_14:25:25 [INFO] : analysis.Analyses.mpas : Entering Analyses.analyze() 2025-04-01_14:25:25 [INFO] : analysis.AnalysisBase.mpas.CYandBinValAxes2D : analyze() 2025-04-01_14:25:25 [INFO] : analysis.AnalysisBase.mpas.CYandBinValAxes2D : mmgfsan, 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]) /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]) /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]) /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]) /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]) /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]) /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]) /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]) 2025-04-01_14:25:39 [INFO] : analysis.AnalysisBase.mpas.CYandBinValAxes2D : mmgfsan, ModLev, ITCZ /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:461: 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, var] /glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:461: 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, var] /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]) /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]) /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]) 2025-04-01_14:25:44 [INFO] : analysis.AnalysisBase.mpas.CYandBinValAxes2D : mmgfsan, ModLev, NTro /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:461: 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, var] /glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:461: 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, var] /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]) /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]) /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]) 2025-04-01_14:25:49 [INFO] : analysis.AnalysisBase.mpas.CYandBinValAxes2D : mmgfsan, ModLev, NXTro /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:461: 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, var] /glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:461: 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, var] /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]) /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]) /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]) 2025-04-01_14:25:54 [INFO] : analysis.AnalysisBase.mpas.CYandBinValAxes2D : mmgfsan, ModLev, STro /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:461: 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, var] /glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:461: 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, var] /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]) /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]) /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]) 2025-04-01_14:25:59 [INFO] : analysis.AnalysisBase.mpas.CYandBinValAxes2D : mmgfsan, ModLev, SXTro /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:461: 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, var] /glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:461: 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, var] /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]) /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]) /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]) 2025-04-01_14:26:04 [INFO] : analysis.AnalysisBase.mpas.CYandBinValAxes2D : mmgfsan, ModLev, 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/StatisticsDatabase.py:461: 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, var] /glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:461: 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, var] /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]) /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]) /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]) 2025-04-01_14:26:09 [INFO] : analysis.AnalysisBase.mpas.CYandBinValAxes2D : mmgfsan, ModLev, abi_g16 /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:461: 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, var] /glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:461: 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, var] /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]) /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]) /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]) 2025-04-01_14:26:14 [INFO] : analysis.AnalysisBase.mpas.CYandBinValAxes2D : mmgfsan, ModLev, ahi_himawari8 /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:461: 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, var] /glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:461: 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, var] /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]) /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]) /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]) 2025-04-01_14:26:19 [INFO] : analysis.AnalysisBase.mpas.CYandBinValAxes2D : mmgfsan, ModLev, 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:461: 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, var] /glade/derecho/scratch/jwittig/repos-s/mpas-jedi-cron/graphics/analysis/StatisticsDatabase.py:461: 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, var] /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]) /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]) /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/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, :] 2025-04-01_14:26:24 [INFO] : analysis.Analyses.mpas : Exiting Analyses.analyze() 2025-04-01_14:26:24 [INFO] : __main__ : Finished main() successfully