FutureWarnings based on Dataset.dims in stm.py fixed.

stmtools/stm.py

@@ -76,7 +76,7 @@ def regulate_dims(self, space_label=None, time_label=None):
         if (
             (space_label is None)
             and (time_label is None)
-            and all([k not in self._obj.dims.keys() for k in ["space", "time"]])
+            and all([k not in self._obj.sizes.keys() for k in ["space", "time"]])
         ):
             raise ValueError(
                 'No "space" nor "time" dimension found. \
@@ -86,7 +86,7 @@ def regulate_dims(self, space_label=None, time_label=None):
         # Check time dimension
         ds_reg = self._obj
         for key, label in zip(["space", "time"], [space_label, time_label], strict=True):
-            if key not in self._obj.dims.keys():
+            if key not in self._obj.sizes.keys():
                 if label is None:
                     ds_reg = ds_reg.expand_dims({key: 1})
                 elif isinstance(label, str):
@@ -100,7 +100,7 @@ def regulate_dims(self, space_label=None, time_label=None):
         # Squeeze the time dimension for all point attibutes, if exists
         pnt_vars = [var for var in ds_reg.data_vars.keys() if var.startswith("pnt_")]
         for var in pnt_vars:
-            if "time" in ds_reg[var].dims:
+            if "time" in ds_reg[var].sizes:
                 ds_reg[var] = ds_reg[var].squeeze(dim="time")
 
         return ds_reg
@@ -467,12 +467,12 @@ def enrich_from_dataset(self,
                     f'Coordinate label "{coord_label}" was not found in the input dataset.'
                     )
 
-        # check if dataset is point or raster if 'space' in dataset.dims:
-        if "space" in dataset.dims:
+        # check if dataset is point or raster if 'space' in dataset.sizes:
+        if "space" in dataset.sizes:
             approch = "point"
-        elif "lat" in dataset.dims and "lon" in dataset.dims:
+        elif "lat" in dataset.sizes and "lon" in dataset.sizes:
             approch = "raster"
-        elif "y" in dataset.dims and "x" in dataset.dims:
+        elif "y" in dataset.sizes and "x" in dataset.sizes:
             approch = "raster"
         else:
             raise ValueError(
@@ -483,7 +483,7 @@ def enrich_from_dataset(self,
                              )
 
         # check if dataset has time dimensions
-        if "time" not in dataset.dims:
+        if "time" not in dataset.sizes:
             raise ValueError('Missing dimension: "time" in the input dataset.')
 
         # check if dtype of time is the same
@@ -518,7 +518,7 @@ def num_points(self):
             Number of space entry.
 
         """
-        return self._obj.dims["space"]
+        return self._obj.sizes["space"]
 
     @property
     def num_epochs(self):
@@ -530,7 +530,7 @@ def num_epochs(self):
             Number of epochs.
 
         """
-        return self._obj.dims["time"]
+        return self._obj.sizes["time"]
 
 
 def _in_polygon_block(mask, polygon, xlabel, ylabel, type_polygon):
@@ -715,7 +715,7 @@ def _enrich_from_raster_block(ds, dataraster, fields, method):
 
     # Assign these values to the corresponding points in ds
     for field in fields:
-        ds[field] = xr.DataArray(interpolated[field].data, dims=ds.dims, coords=ds.coords)
+        ds[field] = xr.DataArray(interpolated[field].data, dims=ds.sizes, coords=ds.coords)
     return ds
 
 
@@ -747,7 +747,7 @@ def _enrich_from_points_block(ds, datapoints, fields):
     for dim in ["space", "time"]:
         if dim not in datapoints.coords:
             indexer[dim]= [
-                coord for coord in datapoints.coords if dim in datapoints[coord].dims
+                coord for coord in datapoints.coords if dim in datapoints[coord].sizes
                 ]
         else:
             indexer[dim] = [dim]
@@ -778,7 +778,7 @@ def _enrich_from_points_block(ds, datapoints, fields):
     # Assign these values to the corresponding points in ds
     for field in fields:
         ds[field] = xr.DataArray(
-            selections[field].data, dims=ds.dims, coords=ds.coords
+            selections[field].data, dims=ds.sizes, coords=ds.coords
             )
 
     return ds