support for data with scalar time

enstools/feature/identification/identification.py

@@ -153,6 +153,11 @@ class IdentificationTechnique(ABC):
         time_dim_in_input = (time_dim is not None)
         if time_dim_in_input and time_dim in dataset.dims:
             split_dimensions.append(time_dim)
+        time_var_value = None
+        if not time_dim_in_input and 'time' in dataset.variables:
+            # time dimension as scalar in dataset, also remember it
+            time_var_value = dataset.variables['time'].data
+            time_var_value = str(np.datetime_as_string(time_var_value, unit='s'))
         time_dim_len = len(dataset.coords[time_dim].values) if time_dim_in_input else 1
 
         # search init_time
@@ -210,8 +215,10 @@ class IdentificationTechnique(ABC):
                             valid_time = dataset.coords[time_dim].data[t]
                             timestep.valid_time = str(np.datetime_as_string(valid_time, unit='s'))
                             cur_indices[time_dim] = valid_time
+                        elif time_var_value is not None:
+                            timestep.valid_time = time_var_value
 
-                        # ID to access this object block in protobuf set
+                            # ID to access this object block in protobuf set
                         sets_id = len(self.pb_dataset.sets) - 1
                         tl_id = len(s_i.timesteps) - 1
                         index_field.loc[cur_indices] = (sets_id, tl_id)