CHange extract/preprocessing/modality names (#626)

* change preprocessing to extraction and modality to preprocessing

clinicadl/caps_dataset/caps_dataset_config.py

@@ -4,62 +4,60 @@
 
 from clinicadl.caps_dataset.data_config import DataConfig
 from clinicadl.caps_dataset.dataloader_config import DataLoaderConfig
-from clinicadl.config.config.modality import (
-    CustomModalityConfig,
-    DTIModalityConfig,
-    FlairModalityConfig,
-    ModalityConfig,
-    PETModalityConfig,
-    T1ModalityConfig,
-)
-from clinicadl.preprocessing import config as preprocessing
+from clinicadl.caps_dataset.extraction import config as extraction
+from clinicadl.caps_dataset.preprocessing import config as preprocessing
 from clinicadl.transforms.config import TransformsConfig
 from clinicadl.utils.enum import ExtractionMethod, Preprocessing
 
 
-def get_preprocessing(extract_method: ExtractionMethod):
+def get_extraction(extract_method: ExtractionMethod):
     if extract_method == ExtractionMethod.ROI:
-        return preprocessing.PreprocessingROIConfig
+        return extraction.ExtractionROIConfig
     elif extract_method == ExtractionMethod.SLICE:
-        return preprocessing.PreprocessingSliceConfig
+        return extraction.ExtractionSliceConfig
     elif extract_method == ExtractionMethod.IMAGE:
-        return preprocessing.PreprocessingImageConfig
+        return extraction.ExtractionImageConfig
     elif extract_method == ExtractionMethod.PATCH:
-        return preprocessing.PreprocessingPatchConfig
+        return extraction.ExtractionPatchConfig
     else:
-        raise ValueError(f"Modality {extract_method.value} is not implemented.")
+        raise ValueError(f"Preprocessing {extract_method.value} is not implemented.")
 
 
-def get_modality(preprocessing: Preprocessing):
-    if (
-        preprocessing == Preprocessing.T1_EXTENSIVE
-        or preprocessing == Preprocessing.T1_LINEAR
-    ):
-        return T1ModalityConfig
-    elif preprocessing == Preprocessing.PET_LINEAR:
-        return PETModalityConfig
-    elif preprocessing == Preprocessing.FLAIR_LINEAR:
-        return FlairModalityConfig
-    elif preprocessing == Preprocessing.CUSTOM:
-        return CustomModalityConfig
-    elif preprocessing == Preprocessing.DWI_DTI:
-        return DTIModalityConfig
+def get_preprocessing(preprocessing_type: Preprocessing):
+    if preprocessing_type == Preprocessing.T1_LINEAR:
+        return preprocessing.T1PreprocessingConfig
+    elif preprocessing_type == Preprocessing.PET_LINEAR:
+        return preprocessing.PETPreprocessingConfig
+    elif preprocessing_type == Preprocessing.FLAIR_LINEAR:
+        return preprocessing.FlairPreprocessingConfig
+    elif preprocessing_type == Preprocessing.CUSTOM:
+        return preprocessing.CustomPreprocessingConfig
+    elif preprocessing_type == Preprocessing.DWI_DTI:
+        return preprocessing.DTIPreprocessingConfig
     else:
-        raise ValueError(f"Preprocessing {preprocessing.value} is not implemented.")
+        raise ValueError(
+            f"Preprocessing {preprocessing_type.value} is not implemented."
+        )
+
 
+class CapsDatasetConfig(BaseModel):
+    """Config class for CapsDataset object.
+
+    caps_directory, preprocessing_json, extract_method, preprocessing
+    are arguments that must be passed by the user.
+
+    transforms isn't optional because there is always at least one transform (NanRemoval)
+    """
 
-class CapsDatasetBase(BaseModel):
     data: DataConfig
     dataloader: DataLoaderConfig
-    modality: ModalityConfig
+    extraction: extraction.ExtractionConfig
     preprocessing: preprocessing.PreprocessingConfig
-    transforms: Optional[TransformsConfig]
+    transforms: TransformsConfig
 
     # pydantic config
     model_config = ConfigDict(validate_assignment=True, arbitrary_types_allowed=True)
 
-
-class CapsDatasetConfig(CapsDatasetBase):
     @classmethod
     def from_preprocessing_and_extraction_method(
         cls,
@@ -70,7 +68,9 @@ def from_preprocessing_and_extraction_method(
         return cls(
             data=DataConfig(**kwargs),
             dataloader=DataLoaderConfig(**kwargs),
-            modality=get_modality(Preprocessing(preprocessing_type))(**kwargs),
-            preprocessing=get_preprocessing(ExtractionMethod(extraction))(**kwargs),
+            preprocessing=get_preprocessing(Preprocessing(preprocessing_type))(
+                **kwargs
+            ),
+            extraction=get_extraction(ExtractionMethod(extraction))(**kwargs),
             transforms=TransformsConfig(**kwargs),
         )

clinicadl/caps_dataset/caps_dataset_utils.py

@@ -1,9 +1,14 @@
 from pathlib import Path
-from typing import Dict, Optional, Tuple, Union
-
-from pydantic import BaseModel, ConfigDict
+from typing import Dict, Optional, Tuple
 
 from clinicadl.caps_dataset.caps_dataset_config import CapsDatasetConfig
+from clinicadl.caps_dataset.preprocessing.config import (
+    CustomPreprocessingConfig,
+    DTIPreprocessingConfig,
+    FlairPreprocessingConfig,
+    PETPreprocessingConfig,
+    T1PreprocessingConfig,
+)
 from clinicadl.utils.enum import LinearModality, Preprocessing
 
 
@@ -17,14 +22,12 @@ def compute_folder_and_file_type(
         pet_linear_nii,
     )
 
-    preprocessing = Preprocessing(
-        config.preprocessing.preprocessing
-    )  # replace("-", "_")
+    preprocessing = config.preprocessing.preprocessing
     if from_bids is not None:
-        if preprocessing == Preprocessing.CUSTOM:
+        if isinstance(config.preprocessing, CustomPreprocessingConfig):
             mod_subfolder = Preprocessing.CUSTOM.value
             file_type = {
-                "pattern": f"*{config.modality.custom_suffix}",
+                "pattern": f"*{config.preprocessing.custom_suffix}",
                 "description": "Custom suffix",
             }
         else:
@@ -33,34 +36,34 @@ def compute_folder_and_file_type(
 
     elif preprocessing not in Preprocessing:
         raise NotImplementedError(
-            f"Extraction of preprocessing {config.preprocessing.preprocessing.value} is not implemented from CAPS directory."
+            f"Extraction of preprocessing {preprocessing} is not implemented from CAPS directory."
         )
     else:
         mod_subfolder = preprocessing.value.replace("-", "_")
-        if preprocessing == Preprocessing.T1_LINEAR:
+        if isinstance(config.preprocessing, T1PreprocessingConfig):
             file_type = linear_nii(
-                LinearModality.T1W, config.preprocessing.use_uncropped_image
+                LinearModality.T1W, config.extraction.use_uncropped_image
             )
 
-        elif preprocessing == Preprocessing.FLAIR_LINEAR:
+        elif isinstance(config.preprocessing, FlairPreprocessingConfig):
             file_type = linear_nii(
-                LinearModality.FLAIR, config.preprocessing.use_uncropped_image
+                LinearModality.FLAIR, config.extraction.use_uncropped_image
             )
 
-        elif preprocessing == Preprocessing.PET_LINEAR:
+        elif isinstance(config.preprocessing, PETPreprocessingConfig):
             file_type = pet_linear_nii(
-                config.modality.tracer,
-                config.modality.suvr_reference_region,
-                config.preprocessing.use_uncropped_image,
+                config.preprocessing.tracer,
+                config.preprocessing.suvr_reference_region,
+                config.extraction.use_uncropped_image,
             )
-        elif preprocessing == Preprocessing.DWI_DTI:
+        elif isinstance(config.preprocessing, DTIPreprocessingConfig):
             file_type = dwi_dti(
-                config.modality.dti_measure,
-                config.modality.dti_space,
+                config.preprocessing.dti_measure,
+                config.preprocessing.dti_space,
             )
-        elif preprocessing == Preprocessing.CUSTOM:
+        elif isinstance(config.preprocessing, CustomPreprocessingConfig):
             file_type = {
-                "pattern": f"*{config.modality.custom_suffix}",
+                "pattern": f"*{config.preprocessing.custom_suffix}",
                 "description": "Custom suffix",
             }
             # custom_suffix["use_uncropped_image"] = None