Run unittets and cleaning

.github/workflows/lint.yaml

@@ -2,9 +2,9 @@ name: 'Lint codebase'
 
 on:
   pull_request:
-    branches: [ dev ]
+    branches: [ "dev", "refactoring" ]
   push:
-    branches: [ dev ]
+    branches: [ "dev", "refactoring" ]
 
 permissions:
   contents: read

.github/workflows/test.yml

@@ -2,9 +2,9 @@ name: Test
 
 on:
   push:
-    branches: [dev]
+    branches: ["dev", "refactoring"]
   pull_request:
-    branches: [dev]
+    branches: ["dev", "refactoring"]
 
 permissions:
   contents: read

.github/workflows/test_cli.yml

@@ -5,6 +5,7 @@ on:
     branches: ["dev", "refactoring"]
   pull_request:
     branches: ["dev", "refactoring"]
+    types: [opened, synchronize, reopened, ready_for_review]
 
 permissions:
   contents: read

.github/workflows/test_generate.yml

@@ -5,6 +5,7 @@ on:
     branches: ["dev", "refactoring"]
   pull_request:
     branches: ["dev", "refactoring"]
+    types: [opened, synchronize, reopened, ready_for_review]
 
 permissions:
   contents: read

.github/workflows/test_interpret.yml

@@ -5,6 +5,7 @@ on:
     branches: ["dev", "refactoring"]
   pull_request:
     branches: ["dev", "refactoring"]
+    types: [opened, synchronize, reopened, ready_for_review]
 
 permissions:
   contents: read

.github/workflows/test_predict.yml

@@ -5,6 +5,7 @@ on:
     branches: ["dev", "refactoring"]
   pull_request:
     branches: ["dev", "refactoring"]
+    types: [opened, synchronize, reopened, ready_for_review]
 
 permissions:
   contents: read

.github/workflows/test_prepare_data.yml

@@ -5,6 +5,7 @@ on:
     branches: ["dev", "refactoring"]
   pull_request:
     branches: ["dev", "refactoring"]
+    types: [opened, synchronize, reopened, ready_for_review]
 
 permissions:
   contents: read

.github/workflows/test_quality_checks.yml

@@ -5,6 +5,7 @@ on:
     branches: ["dev", "refactoring"]
   pull_request:
     branches: ["dev", "refactoring"]
+    types: [opened, synchronize, reopened, ready_for_review]
 
 permissions:
   contents: read

.github/workflows/test_random_search.yml

@@ -5,6 +5,7 @@ on:
     branches: ["dev", "refactoring"]
   pull_request:
     branches: ["dev", "refactoring"]
+    types: [opened, synchronize, reopened, ready_for_review]
 
 permissions:
   contents: read

.github/workflows/test_resume.yml

@@ -5,6 +5,7 @@ on:
     branches: ["dev", "refactoring"]
   pull_request:
     branches: ["dev", "refactoring"]
+    types: [opened, synchronize, reopened, ready_for_review]
 
 permissions:
   contents: read

.github/workflows/test_train.yml

@@ -5,6 +5,7 @@ on:
     branches: ["dev", "refactoring"]
   pull_request:
     branches: ["dev", "refactoring"]
+    types: [opened, synchronize, reopened, ready_for_review]
 
 permissions:
   contents: read

.github/workflows/test_transfer_learning.yml

@@ -5,6 +5,7 @@ on:
     branches: ["dev", "refactoring"]
   pull_request:
     branches: ["dev", "refactoring"]
+    types: [opened, synchronize, reopened, ready_for_review]
 
 permissions:
   contents: read

.github/workflows/test_tsvtools.yml

@@ -5,6 +5,7 @@ on:
     branches: ["dev", "refactoring"]
   pull_request:
     branches: ["dev", "refactoring"]
+    types: [opened, synchronize, reopened, ready_for_review]
 
 permissions:
   contents: read

Makefile

@@ -10,7 +10,7 @@ help: Makefile
 
 .PHONY: check.lock
 check.lock:
-	@$(POETRY) lock --check
+	@$(POETRY) check --lock
 
 ## build			: Build the package.
 .PHONY: build

clinicadl/callbacks/config.py

@@ -1,13 +1,8 @@
-from abc import ABC, abstractmethod
-from enum import Enum
 from logging import getLogger
-from pathlib import Path
-from typing import Any, Dict, Optional, Tuple
+from typing import Optional
 
-from pydantic import BaseModel, ConfigDict, computed_field, field_validator
-from pydantic.types import NonNegativeFloat, NonNegativeInt, PositiveFloat, PositiveInt
+from pydantic import BaseModel, ConfigDict
 
-from clinicadl.preprocessing.preprocessing import read_preprocessing
 from clinicadl.utils.enum import ExperimentTracking
 
 logger = getLogger("clinicadl.callbacks_config")

clinicadl/caps_dataset/data_config.py

@@ -28,7 +28,7 @@ class DataConfig(BaseModel):  # TODO : put in data module
     diagnoses: Tuple[str, ...] = ("AD", "CN")
     data_df: Optional[pd.DataFrame] = None
     label: Optional[str] = None
-    label_code: Union[str, dict[str, int], None] = {}
+    label_code: Union[str, Dict[str, int], None] = {}
     multi_cohort: bool = False
     mask_path: Optional[Path] = None
     preprocessing_json: Optional[Path] = None

clinicadl/caps_dataset/data_utils.py

@@ -1,6 +1,5 @@
 # coding: utf8
 # TODO: create a folder for generate/ prepare_data/ data to deal with capsDataset objects ?
-import abc
 from logging import getLogger
 from pathlib import Path
 from typing import Any, Callable, Dict, Optional

clinicadl/commandline/modules_options/__init__.py

@@ -1 +0,0 @@
-# from .task import classification, reconstruction, regression

clinicadl/commandline/modules_options/computational.py

@@ -2,7 +2,6 @@
 
 from clinicadl.config.config.computational import ComputationalConfig
 from clinicadl.config.config_utils import get_default_from_config_class as get_default
-from clinicadl.config.config_utils import get_type_from_config_class as get_type
 
 # Computational
 amp = click.option(

clinicadl/commandline/pipelines/generate/shepplogan/options.py

@@ -1,5 +1,3 @@
-from typing import get_args
-
 import click
 
 from clinicadl.config.config_utils import get_default_from_config_class as get_default

clinicadl/commandline/pipelines/generate/trivial/cli.py

@@ -1,4 +1,3 @@
-import tarfile
 from logging import getLogger
 from pathlib import Path
 

clinicadl/commandline/pipelines/predict/options.py

@@ -1,7 +1,6 @@
 import click
 
 from clinicadl.config.config_utils import get_default_from_config_class as get_default
-from clinicadl.config.config_utils import get_type_from_config_class as get_type
 from clinicadl.predict.config import PredictConfig
 
 # predict specific

clinicadl/commandline/pipelines/prepare_data/prepare_data_cli.py

@@ -1,5 +1,4 @@
 from pathlib import Path
-from typing import Optional
 
 import click
 

clinicadl/commandline/pipelines/prepare_data/prepare_data_from_bids_cli.py

@@ -1,5 +1,5 @@
-
 import click
+
 from clinicadl.caps_dataset.caps_dataset_config import CapsDatasetConfig
 from clinicadl.commandline import arguments
 from clinicadl.commandline.modules_options import (
@@ -10,9 +10,6 @@
 )
 from clinicadl.prepare_data.prepare_data import DeepLearningPrepareData
 from clinicadl.utils.enum import ExtractionMethod
-from clinicadl.commandline import arguments
-from clinicadl.commandline.modules_options import data, dataloader, modality, preprocessing
-from clinicadl.utils.enum import ExtractionMethod
 
 
 @click.command(name="image", no_args_is_help=True)
@@ -27,7 +24,6 @@
 @modality.custom_suffix
 @data.participants_tsv
 def image_bids_cli(kwargs):
-
     image_config = CapsDatasetConfig.from_preprocessing_and_extraction_method(
         extraction=ExtractionMethod.IMAGE,
         preprocessing_type=kwargs["preprocessing"],

clinicadl/config/config/maps_manager.py

@@ -1,12 +1,10 @@
-from enum import Enum
 from logging import getLogger
 from pathlib import Path
 from typing import Optional
 
 from pydantic import BaseModel, ConfigDict
 
 from clinicadl.utils.exceptions import ClinicaDLArgumentError  # type: ignore
-from clinicadl.utils.maps_manager.maps_manager import MapsManager  # type: ignore
 
 logger = getLogger("clinicadl.predict_config")
 

clinicadl/config/config_utils.py

@@ -1,6 +1,6 @@
 import typing
 from enum import Enum
-from typing import Any, get_args, get_origin
+from typing import Any, get_args
 
 import click
 from pydantic import BaseModel

clinicadl/generate/generate_config.py

@@ -1,4 +1,3 @@
-import tarfile
 from logging import getLogger
 from pathlib import Path
 from time import time
@@ -14,22 +13,8 @@
     field_validator,
 )
 
-from clinicadl.utils.clinica_utils import (
-    RemoteFileStructure,
-    clinicadl_file_reader,
-    fetch_file,
-)
-from clinicadl.utils.enum import (
-    Pathology,
-    Preprocessing,
-    SUVRReferenceRegions,
-    Tracer,
-)
-from clinicadl.utils.exceptions import (
-    ClinicaDLArgumentError,
-    ClinicaDLTSVError,
-    DownloadError,
-)
+from clinicadl.utils.enum import Pathology
+from clinicadl.utils.exceptions import ClinicaDLArgumentError
 
 logger = getLogger("clinicadl.predict_config")
 
@@ -52,6 +37,8 @@ class GenerateArtifactsConfig(BaseModel):
     noise_std: Tuple[NonNegativeFloat, NonNegativeFloat] = (5.0, 15.0)
     rotation: Tuple[NonNegativeFloat, NonNegativeFloat] = (2.0, 4.0)  # float o int ???
     translation: Tuple[NonNegativeFloat, NonNegativeFloat] = (2.0, 4.0)
+    # pydantic config
+    model_config = ConfigDict(validate_assignment=True)
 
     @field_validator("gamma", "noise_std", "rotation", "translation", mode="before")
     def list_to_tuples(cls, v):
@@ -85,16 +72,22 @@ class GenerateHypometabolicConfig(BaseModel):
     anomaly_degree: NonNegativeFloat = 30.0
     pathology: Pathology = Pathology.AD
     sigma: NonNegativeFloat = 5
+    # pydantic config
+    model_config = ConfigDict(validate_assignment=True)
 
 
 class GenerateRandomConfig(BaseModel):
     mean: NonNegativeFloat = 0.0
     sigma: NonNegativeFloat = 0.5
+    # pydantic config
+    model_config = ConfigDict(validate_assignment=True)
 
 
 class GenerateTrivialConfig(BaseModel):
     atrophy_percent: PositiveFloat = 60.0
     mask_path: Optional[Path] = None
+    # pydantic config
+    model_config = ConfigDict(validate_assignment=True)
 
 
 class GenerateSheppLoganConfig(BaseModel):
@@ -107,6 +100,8 @@ class GenerateSheppLoganConfig(BaseModel):
     extract_json: Optional[str] = None
     image_size: PositiveInt = 128
     smoothing: bool = False
+    # pydantic config
+    model_config = ConfigDict(validate_assignment=True)
 
     @field_validator("extract_json", mode="before")
     def compute_extract_json(cls, v: str):

clinicadl/generate/generate_utils.py

@@ -3,11 +3,10 @@
 import random
 from copy import copy
 from pathlib import Path
-from typing import Dict, Optional, Union
+from typing import Dict, Optional
 
 import numpy as np
 import pandas as pd
-from pydantic import BaseModel
 from scipy.ndimage import gaussian_filter
 from skimage.draw import ellipse
 
@@ -22,15 +21,12 @@
 from clinicadl.utils.enum import (
     LinearModality,
     Preprocessing,
-    SUVRReferenceRegions,
-    Tracer,
 )
 
 # from clinicadl.caps_dataset.caps_dataset_config import CapsDatasetConfig
 from clinicadl.utils.exceptions import (
     ClinicaDLArgumentError,
     ClinicaDLTSVError,
-    DownloadError,
 )
 
 

clinicadl/hugging_face/pull_cli.py

@@ -1,9 +1,6 @@
-from pathlib import Path
-
 import click
 
 from clinicadl.utils import cli_param
-from clinicadl.utils.maps_manager import MapsManager
 
 
 @click.command(name="pull", no_args_is_help=True)

clinicadl/interpret/config.py

@@ -1,14 +1,10 @@
-from enum import Enum
 from logging import getLogger
 from pathlib import Path
-from typing import Dict, Optional, Union
+from typing import Optional
 
 from pydantic import BaseModel, field_validator
 
 from clinicadl.caps_dataset.data_config import DataConfig as DataBaseConfig
-from clinicadl.caps_dataset.data_utils import (
-    load_data_test,
-)
 from clinicadl.caps_dataset.dataloader_config import DataLoaderConfig
 from clinicadl.config.config.computational import ComputationalConfig
 from clinicadl.config.config.cross_validation import CrossValidationConfig

clinicadl/mlflow_test.py

@@ -1,5 +1,4 @@
 import logging
-import os
 import sys
 import warnings
 from urllib.parse import urlparse

clinicadl/network/autoencoder/models.py

@@ -1,7 +1,7 @@
 from torch import nn
 
 from clinicadl.network.autoencoder.cnn_transformer import CNN_Transformer
-from clinicadl.network.cnn.models import Conv4_FC3, Conv5_FC3, resnet18
+from clinicadl.network.cnn.models import Conv4_FC3, Conv5_FC3
 from clinicadl.network.sub_network import AutoEncoder
 from clinicadl.network.vae.vae_layers import (
     DecoderLayer3D,

clinicadl/network/cnn/random.py

@@ -2,7 +2,6 @@
 
 from clinicadl.network.network_utils import *
 from clinicadl.network.sub_network import CNN
-from clinicadl.utils.enum import Normalization
 from clinicadl.utils.exceptions import ClinicaDLNetworksError
 
 

clinicadl/predict/config.py

@@ -1,7 +1,5 @@
 from logging import getLogger
 
-from pydantic import BaseModel
-
 from clinicadl.caps_dataset.data_config import DataConfig as DataBaseConfig
 from clinicadl.caps_dataset.dataloader_config import DataLoaderConfig
 from clinicadl.config.config.maps_manager import (