adding read for statistics tendencies

src/anemoi/datasets/create/loaders.py

@@ -550,7 +550,7 @@ def __init__(self, name="", **kwargs):
         super().__init__(**kwargs)
         self.name = name
 
-        storage_path = os.path.join(self.path + ".tmp_data", name)
+        storage_path = f"{self.path}.tmp_storage_{name}"
         self.tmp_storage = build_storage(directory=storage_path, create=True)
 
     def initialise(self):
@@ -725,6 +725,8 @@ class TendenciesStatisticsDeltaNotMultipleOfFrequency(ValueError):
 
 
 class TendenciesStatisticsAddition(GenericAdditions):
+    DATASET_NAME_PATTERN = "statistics_tendencies_{delta}"
+
     def __init__(self, path, delta=None, **kwargs):
         full_ds = open_dataset(path)
         self.variables = full_ds.variables
@@ -739,7 +741,7 @@ def __init__(self, path, delta=None, **kwargs):
             )
         idelta = delta // frequency
 
-        super().__init__(path=path, name=f"tendencies_statistics_{delta}h", **kwargs)
+        super().__init__(path=path, name=self.DATASET_NAME_PATTERN.format(delta=f"{delta}h"), **kwargs)
 
         z = zarr.open(self.path, mode="r")
         start = z.attrs["statistics_start_date"]

src/anemoi/datasets/data/forewards.py

@@ -67,6 +67,11 @@ def variables(self):
     def statistics(self):
         return self.forward.statistics
 
+    def statistics_tendencies(self, delta=None):
+        if delta is None:
+            delta = self.frequency
+        return self.forward.statistics_tendencies(delta)
+
     @property
     def shape(self):
         return self.forward.shape

src/anemoi/datasets/data/join.py

@@ -121,6 +121,14 @@ def statistics(self):
             k: np.concatenate([d.statistics[k] for d in self.datasets], axis=0) for k in self.datasets[0].statistics
         }
 
+    def statistics_tendencies(self, delta=None):
+        if delta is None:
+            delta = self.frequency
+        return {
+            k: np.concatenate([d.statistics_tendencies(delta)[k] for d in self.datasets], axis=0)
+            for k in self.datasets[0].statistics_tendencies(delta)
+        }
+
     def source(self, index):
         i = index
         for dataset in self.datasets:

src/anemoi/datasets/data/select.py

@@ -74,6 +74,11 @@ def name_to_index(self):
     def statistics(self):
         return {k: v[self.indices] for k, v in self.dataset.statistics.items()}
 
+    def statistics_tendencies(self, delta=None):
+        if delta is None:
+            delta = self.frequency
+        return {k: v[self.indices] for k, v in self.dataset.statistics_tendencies(delta).items()}
+
     def metadata_specific(self, **kwargs):
         return super().metadata_specific(indices=self.indices, **kwargs)
 

src/anemoi/datasets/data/statistics.py

@@ -29,6 +29,11 @@ def __init__(self, dataset, statistic):
     def statistics(self):
         return self._statistic.statistics
 
+    def statistics_tendencies(self, delta=None):
+        if delta is None:
+            delta = self.frequency
+        return self._statistic.statistics_tendencies(delta)
+
     def metadata_specific(self, **kwargs):
         return super().metadata_specific(
             statistics=self._statistic.metadata_specific(),

src/anemoi/datasets/data/stores.py

@@ -218,6 +218,21 @@ def statistics(self):
             minimum=self.z.minimum[:],
         )
 
+    def statistics_tendencies(self, delta=None):
+        if delta is None:
+            delta = self.frequency
+        if isinstance(delta, int):
+            delta = f"{delta}h"
+        from anemoi.datasets.create.loaders import TendenciesStatisticsAddition
+
+        prefix = TendenciesStatisticsAddition.DATASET_NAME_PATTERN.format(delta=delta) + "_"
+        return dict(
+            mean=self.z[f"{prefix}mean"][:],
+            stdev=self.z[f"{prefix}stdev"][:],
+            maximum=self.z[f"{prefix}maximum"][:],
+            minimum=self.z[f"{prefix}minimum"][:],
+        )
+
     @property
     def resolution(self):
         return self.z.attrs["resolution"]

src/anemoi/datasets/data/unchecked.py

@@ -101,6 +101,10 @@ def variables(self):
     def statistics(self):
         raise NotImplementedError()
 
+    @check("check_same_variables")
+    def statistics_tendencies(self, delta=None):
+        raise NotImplementedError()
+
     @property
     def shape(self):
         raise NotImplementedError()