Merge pull request #30 from BrainLesion/27-broken-docs

27 broken docs

brats/core/brats_algorithm.py

@@ -64,7 +64,13 @@ def _standardize_batch_inputs(
     def _process_single_output(
         self, tmp_output_folder: Path | str, subject_id: str, output_file: Path
     ) -> None:
-        # TODO add docstring
+        """Process the output of a single inference run and save it in the specified file.
+
+        Args:
+            tmp_output_folder (Path | str): Folder with the algorithm output
+            subject_id (str): Subject ID of the output
+            output_file (Path): Path to the desired output file
+        """
         # rename output
         algorithm_output = Path(tmp_output_folder) / OUTPUT_NAME_SCHEMA[
             self.task
@@ -81,7 +87,13 @@ def _process_batch_output(
         output_folder: Path,
         mapping: dict[str, str],
     ) -> None:
-        # TODO add docstring
+        """Process the outputs of a batch inference run and save them in the specified folder.
+
+        Args:
+            tmp_output_folder (Path | str): Folder with the algorithm outputs
+            output_folder (Path): Folder to save the outputs
+            mapping (dict[str, str]): Mapping from internal to external subject names
+        """
         # move outputs and change name back to initially provided one
         output_folder = Path(output_folder)
         output_folder.mkdir(parents=True, exist_ok=True)
@@ -97,7 +109,14 @@ def _infer_single(
         inputs: dict[str, Path | str],
         output_file: Path | str,
         log_file: Optional[Path | str] = None,
-    ):
+    ) -> None:
+        """Perform a single inference run with the provided inputs and save the output in the specified file.
+
+        Args:
+            inputs (dict[str, Path  |  str]): Input Images for the task
+            output_file (Path | str): File to save the output
+            log_file (Optional[Path  |  str], optional): Log file with extra information. Defaults to None.
+        """
         with InferenceSetup(log_file=log_file) as (tmp_data_folder, tmp_output_folder):
             logger.info(f"Performing single inference")
 
@@ -130,7 +149,13 @@ def _infer_batch(
         output_folder: Path | str,
         log_file: Optional[Path | str] = None,
     ):
+        """Perform a batch inference run with the provided inputs and save the outputs in the specified folder.
 
+        Args:
+            data_folder (Path | str): Folder with the input data
+            output_folder (Path | str): Folder to save the outputs
+            log_file (Optional[Path  |  str], optional): Log file with extra information. Defaults to None.
+        """
         with InferenceSetup(log_file=log_file) as (tmp_data_folder, tmp_output_folder):
 
             # find subjects

brats/core/inpainting_algorithms.py

@@ -93,7 +93,7 @@ def infer_single(
         """Perform inpainting task on a single subject with the provided images and save the result to the output file.
 
         Args:
-            t1n (Path | str): Path to the T1n image
+            t1n (Path | str): Path to the voided T1n image
             mask (Path | str): Path to the mask image
             output_file (Path | str): Path to save the segmentation
             log_file (Path | str, optional): Save logs to this file

docs/source/algorithms.rst

@@ -5,30 +5,26 @@ The following classes provide the top performing algorithms from several BraTS c
 All algorithms can be used for a single subject inference (one set of MRI scans) or for a batch of multiple subjects with the respective methods inherited from the base class (BraTSAlgorithm).
 
 
-Challenge Algorithms
+Segmentation Algorithms
 --------------------------------------
 
 
-.. autoclass:: brats.AdultGliomaSegmenter
+.. automodule:: brats.core.segmentation_algorithms
 
 
-.. autoclass:: brats.AfricaSegmenter
-
-
-.. autoclass:: brats.MeningiomaSegmenter
-
+Inpainting Algorithms
+--------------------------------------
 
-.. autoclass:: brats.MetastasesSegmenter
 
+.. automodule:: brats.core.inpainting_algorithms
 
-.. autoclass:: brats.PediatricSegmenter
 
 
 
 Abstract Base Class
 --------------------------------------
 
-.. autoclass:: brats.algorithms.BraTSAlgorithm
+.. automodule:: brats.core.brats_algorithm
 
 
 

docs/source/constants.rst

@@ -4,5 +4,5 @@ Constants
 Constants used in the package
 ------------------------------
 
-.. automodule:: brats.constants 
+.. automodule:: brats.utils.constants 
     :members:

pyproject.toml

@@ -39,11 +39,11 @@ docker = ">=7.0.0"
 rich = ">=13.0.0"
 PyYAML = ">=6.0.1"
 dacite = ">=1.8.0"
-loguru = ">=0.6.0"
+loguru = ">=0.7.0"
 nibabel = ">=5.0.0"
 
 [tool.poetry.dev-dependencies]
-pytest = "^6.2.5"
+pytest = ">=8.0.0"
 
 [tool.poetry.group.docs]
 optional = true