Update config and add normalization

Author: sgreenbury

autoemulate/experimental/config_models.py

@@ -152,6 +152,9 @@ class DataConfig(BaseModel):
     # DataLoader configuration
     batch_size: int = Field(default=4, description="Batch size for DataLoader")
     dtype: str = Field(default="float32", description="Data type (float32 or float64)")
+    use_normalization: bool = Field(
+        default=False, description="Whether to use normalization (for Well datasets)"
+    )
 
     def get_source_type(self) -> DataSourceType:
         """Automatically determine data source type from configuration."""
@@ -161,10 +164,9 @@ def get_source_type(self) -> DataSourceType:
         # Auto-detect based on fields
         if self.well_dataset_name is not None:
             return DataSourceType.WELL_NATIVE
-        elif self.data_path is not None:
+        if self.data_path is not None:
             return DataSourceType.FILE
-        else:
-            return DataSourceType.GENERATED
+        return DataSourceType.GENERATED
 
 
 class TeacherForcingConfig(BaseModel):

autoemulate/experimental/configs/turbulent_radiative_layer_2d.yaml

@@ -15,8 +15,9 @@ formatter_type: "default_channels_first"
 model_params:
   modes1: 16
   modes2: 16
-  width: 20
-  n_blocks: 4
+  hidden_channels: 128
+  # width: 20
+  # n_blocks: 4
 
 # Data configuration - The Well native dataset
 # Setting well_dataset_name automatically uses WELL_NATIVE source type
@@ -26,6 +27,7 @@ data:
   n_steps_input: 4
   n_steps_output: 1
   batch_size: 4
+  use_normalization: true
 
 # No simulator section needed for native Well datasets!