Merge branch 'master' into coverage_upgrade

optim_esm_tools/analyze/region_finding.py

@@ -6,6 +6,7 @@
 from optim_esm_tools.analyze.clustering import build_cluster_mask
 from optim_esm_tools.analyze.clustering import build_weighted_cluster
 from optim_esm_tools.analyze.xarray_tools import mask_xr_ds, mask_to_reduced_dataset
+from optim_esm_tools.analyze.time_statistics import TimeStatistics
 from optim_esm_tools.plotting.plot import setup_map, _show
 
 import numpy as np
@@ -75,6 +76,7 @@ class RegionExtractor:
 
     criteria = (tipping_criteria.StdDetrended, tipping_criteria.MaxJump)
     extra_opt = None
+    save_statistics = True
 
     def __init__(
         self,
@@ -108,6 +110,10 @@ def __init__(
         self.save_kw = save_kw
         self.variable = variable or self.data_set.attrs.get('variable_id', 'NO_VAR_ID!')
 
+    @property
+    def read_ds_kw(self):
+        return self.extra_opt.get('read_ds_kw', {})
+
     @property
     def log(self):
         if self._logger is None:
@@ -202,6 +208,15 @@ def store_mask(self, mask, m_i, store_masks=True):
         store_in_dir = os.path.join(save_in, 'masks')
         os.makedirs(store_in_dir, exist_ok=True)
         ds_masked = mask_to_reduced_dataset(self.data_set, mask)
+        kw = {
+            k: v
+            for k, v in self.read_ds_kw.items()
+            if k not in 'max_time min_time'.split()
+        }
+        statistics = TimeStatistics(
+            ds_masked, calculation_kwargs=dict(max_jump=kw)
+        ).calculate_statistics()
+        ds_masked.attrs.update(statistics)
         ds_masked.to_netcdf(
             os.path.join(
                 store_in_dir,