NpyFilesDatastore -> NpyFilesDatastoreMEPS

neural_lam/datastore/__init__.py

@@ -1,10 +1,10 @@
 # Local
 from .mdp import MDPDatastore  # noqa
-from .npyfiles import NpyFilesDatastore  # noqa
+from .npyfilesmeps import NpyFilesDatastoreMEPS  # noqa
 
 DATASTORES = dict(
     mdp=MDPDatastore,
-    npyfiles=NpyFilesDatastore,
+    npyfilesmeps=NpyFilesDatastoreMEPS,
 )
 
 

neural_lam/datastore/npyfilesmeps/__init__.py

@@ -0,0 +1,2 @@
+# Local
+from .store import NpyFilesDatastoreMEPS  # noqa

neural_lam/datastore/npyfiles/create_parameter_weights.py → neural_lam/datastore/npyfilesmeps/create_parameter_weights.py

@@ -163,7 +163,7 @@ def main():
     rank = get_rank()
     world_size = get_world_size()
     datastore = init_datastore(
-        datastore_kind="npyfiles", config_path=args.datastore_config
+        datastore_kind="npyfilesmeps", config_path=args.datastore_config
     )
 
     if distributed:

neural_lam/datastore/npyfiles/store.py → neural_lam/datastore/npyfilesmeps/store.py

@@ -37,7 +37,7 @@ def _load_np(fp, add_feature_dim):
     return arr
 
 
-class NpyFilesDatastore(BaseCartesianDatastore):
+class NpyFilesDatastoreMEPS(BaseCartesianDatastore):
     __doc__ = f"""
     Represents a dataset stored as numpy files on disk. The dataset is assumed
     to be stored in a directory structure where each sample is stored in a

neural_lam/weather_dataset.py

@@ -117,7 +117,8 @@ def _sample_time(self, da, idx, n_steps: int, n_timesteps_offset: int = 0):
         n_steps : int
             The number of time steps to include in the sample.
         n_timestep_offset : int
-            A number of timesteps to use as offset from the start time of the slice
+            A number of timesteps to use as offset from the start time of the
+            slice
         """
         # selecting the time slice
         if self.datastore.is_forecast:
@@ -455,7 +456,7 @@ def __init__(
         self.test_dataset = None
         if num_workers > 0:
             # default to spawn for now, as the default on linux "fork" hangs
-            # when using dask (which the npyfiles datastore uses)
+            # when using dask (which the npyfilesmeps datastore uses)
             self.multiprocessing_context = "spawn"
         else:
             self.multiprocessing_context = None

tests/conftest.py

@@ -60,7 +60,7 @@ def download_meps_example_reduced_dataset():
 
 DATASTORES_EXAMPLES = dict(
     mdp=(DATASTORE_EXAMPLES_ROOT_PATH / "mdp" / "danra.example.yaml"),
-    npyfiles=download_meps_example_reduced_dataset(),
+    npyfilesmeps=download_meps_example_reduced_dataset(),
 )