Ruff update

.github/workflows/code-style.yml

@@ -25,13 +25,6 @@ jobs:
           python -m pip install --progress-bar off .[style]
       - name: Run Ruff
         run: ruff check .
-      - name: Run isort
-        uses: isort/isort-action@master
-      - name: Run black
-        uses: psf/black@stable
-        with:
-          options: "--check --verbose"
-          version: "23.10.1"
       - name: Run codespell
         uses: codespell-project/actions-codespell@master
         with:

brainprint/asymmetry.py

@@ -1,15 +1,13 @@
 """
 Contains asymmetry estimation functionality.
 """
-from typing import Dict
-
 import numpy as np
 from lapy import shapedna
 
 
 def compute_asymmetry(
     eigenvalues, distance: str = "euc", skip_cortex: bool = False
-) -> Dict[str, float]:
+) -> dict[str, float]:
     """
     Compute lateral shape distances from BrainPrint analysis results.
 
@@ -24,7 +22,7 @@ def compute_asymmetry(
 
     Returns
     -------
-    Dict[str, float]
+    dict[str, float]
         {left_label}_{right_label}, distance.
     """
     # Define structures
@@ -75,10 +73,8 @@ def compute_asymmetry(
         key = f"{left_label}_{right_label}"
         if has_nan:
             message = (
-                "NaNs found for {left_label} or {right_label}, "
-                "skipping asymmetry computation...".format(
-                    left_label=left_label, right_label=right_label
-                )
+                f"NaNs found for {left_label} or {right_label}, "
+                "skipping asymmetry computation..."
             )
             print(message)
             distances[key] = np.nan

brainprint/brainprint.py

@@ -5,7 +5,7 @@
 import shutil
 import warnings
 from pathlib import Path
-from typing import Dict, Tuple, Union
+from typing import Union
 
 import numpy as np
 from lapy import TriaMesh, shapedna
@@ -69,7 +69,7 @@ def compute_surface_brainprint(
     norm: str = "none",
     reweight: bool = False,
     use_cholmod: bool = False,
-) -> Tuple[np.ndarray, Union[np.ndarray, None]]:
+) -> tuple[np.ndarray, Union[np.ndarray, None]]:
     """
     Compute BrainPrint eigenvalues and eigenvectors for the given surface.
 
@@ -94,7 +94,7 @@ def compute_surface_brainprint(
 
     Returns
     -------
-    Tuple[np.ndarray, Union[np.ndarray, None]]
+    tuple[np.ndarray, Union[np.ndarray, None]]
         Eigenvalues, eigenvectors (if returned).
     """
     triangular_mesh = read_vtk(path)
@@ -126,19 +126,19 @@ def compute_surface_brainprint(
 
 
 def compute_brainprint(
-    surfaces: Dict[str, Path],
+    surfaces: dict[str, Path],
     keep_eigenvectors: bool = False,
     num: int = 50,
     norm: str = "none",
     reweight: bool = False,
     use_cholmod: bool = False,
-) -> Tuple[Dict[str, np.ndarray], Union[Dict[str, np.ndarray], None]]:
+) -> tuple[dict[str, np.ndarray], Union[dict[str, np.ndarray], None]]:
     """
     Compute ShapeDNA descriptors over several surfaces.
 
     Parameters
     ----------
-    surfaces : Dict[str, Path]
+    surfaces : dict[str, Path]
         Dictionary mapping from labels to *.vtk* paths.
     keep_eigenvectors : bool, optional
         Whether to also return eigenvectors or not, by default False.
@@ -155,7 +155,7 @@ def compute_brainprint(
 
     Returns
     -------
-    Tuple[Dict[str, np.ndarray], Union[Dict[str, np.ndarray], None]]
+    tuple[dict[str, np.ndarray], Union[dict[str, np.ndarray], None]]
         Surface label to eigenvalues, surface label to eigenvectors (if
         *keep_eigenvectors* is True).
     """
@@ -177,9 +177,9 @@ def compute_brainprint(
         except Exception as e:
             message = (
                 "BrainPrint analysis raised the following exception:\n"
-                "{exception}".format(exception=e)
+                f"{e}"
             )
-            warnings.warn(message)
+            warnings.warn(message, stacklevel = 2)
             eigenvalues[surface_label] = ["NaN"] * (num + 2)
         else:
             if len(surface_eigenvalues) == 0:
@@ -275,7 +275,7 @@ def run_brainprint(
             skip_cortex=skip_cortex,
         )
 
-    csv_name = "{subject_id}.brainprint.csv".format(subject_id=subject_id)
+    csv_name = f"{subject_id}.brainprint.csv"
     csv_path = destination / csv_name
     export_brainprint_results(csv_path, eigenvalues, eigenvectors, distances)
     if not keep_temp:
@@ -358,7 +358,7 @@ def __init__(
         if freesurfer_validation:
             test_freesurfer()
 
-    def run(self, subject_id: str, destination: Path = None) -> Dict[str, Path]:
+    def run(self, subject_id: str, destination: Path = None) -> dict[str, Path]:
         """
         Run Brainprint analysis for a specified subject.
 
@@ -371,7 +371,7 @@ def run(self, subject_id: str, destination: Path = None) -> Dict[str, Path]:
 
         Returns
         -------
-        Dict[str, Path]
+        dict[str, Path]
             A dictionary containing paths to the generated analysis results.
         """
         self._eigenvalues = self._eigenvectors = self._distances = None
@@ -418,7 +418,7 @@ def export_results(self, destination: Path, subject_id: str) -> None:
         -------
         None
         """
-        csv_name = "{subject_id}.brainprint.csv".format(subject_id=subject_id)
+        csv_name = f"{subject_id}.brainprint.csv"
         csv_path = destination / csv_name
         return export_brainprint_results(
             csv_path, self._eigenvalues, self._eigenvectors, self._distances

brainprint/surfaces.py

@@ -3,15 +3,14 @@
 """
 import uuid
 from pathlib import Path
-from typing import Dict, List
 
 from lapy import TriaMesh
 
 from .utils.utils import run_shell_command
 
 
 def create_aseg_surface(
-    subject_dir: Path, destination: Path, indices: List[int]
+    subject_dir: Path, destination: Path, indices: list[int]
 ) -> Path:
     """
     Generate a surface from the aseg and label files.
@@ -22,7 +21,7 @@ def create_aseg_surface(
         Path to the subject's directory.
     destination : Path
         Path to the destination directory where the surface will be saved.
-    indices : List[int]
+    indices : list[int]
         List of label indices to include in the surface generation.
 
     Returns
@@ -32,7 +31,7 @@ def create_aseg_surface(
     """
     aseg_path = subject_dir / "mri/aseg.mgz"
     norm_path = subject_dir / "mri/norm.mgz"
-    temp_name = "temp/aseg.{uid}".format(uid=uuid.uuid4())
+    temp_name = f"temp/aseg.{uuid.uuid4()}"
     indices_mask = destination / f"{temp_name}.mgz"
     # binarize on selected labels (creates temp indices_mask)
     # always binarize first, otherwise pretess may scale aseg if labels are
@@ -58,7 +57,7 @@ def create_aseg_surface(
         run_shell_command(pretess_command)
 
     # runs marching cube to extract surface
-    surface_name = "{name}.surf".format(name=temp_name)
+    surface_name = f"{temp_name}.surf"
     surface_path = destination / surface_name
     extraction_template = "mri_mc {source} {label_value} {destination}"
     extraction_command = extraction_template.format(
@@ -80,7 +79,7 @@ def create_aseg_surface(
     return conversion_destination
 
 
-def create_aseg_surfaces(subject_dir: Path, destination: Path) -> Dict[str, Path]:
+def create_aseg_surfaces(subject_dir: Path, destination: Path) -> dict[str, Path]:
     """
     Create surfaces from FreeSurfer aseg labels.
 
@@ -93,7 +92,7 @@ def create_aseg_surfaces(subject_dir: Path, destination: Path) -> Dict[str, Path
 
     Returns
     -------
-    Dict[str, Path]
+    dict[str, Path]
         Dictionary of label names mapped to corresponding surface Path objects.
     """
     # Define aseg labels
@@ -145,7 +144,7 @@ def create_aseg_surfaces(subject_dir: Path, destination: Path) -> Dict[str, Path
     }
 
 
-def create_cortical_surfaces(subject_dir: Path, destination: Path) -> Dict[str, Path]:
+def create_cortical_surfaces(subject_dir: Path, destination: Path) -> dict[str, Path]:
     """
     Create cortical surfaces from FreeSurfer labels.
 
@@ -158,7 +157,7 @@ def create_cortical_surfaces(subject_dir: Path, destination: Path) -> Dict[str,
 
     Returns
     -------
-    Dict[str, Path]
+    dict[str, Path]
         Dictionary mapping label names to associated surface Paths.
     """
     cortical_labels = {
@@ -178,7 +177,7 @@ def create_cortical_surfaces(subject_dir: Path, destination: Path) -> Dict[str,
 
 def create_surfaces(
     subject_dir: Path, destination: Path, skip_cortex: bool = False
-) -> Dict[str, Path]:
+) -> dict[str, Path]:
     """
     Create surfaces based on FreeSurfer labels.
 
@@ -193,7 +192,7 @@ def create_surfaces(
 
     Returns
     -------
-    Dict[str, Path]
+    dict[str, Path]
         Dict mapping label names to the corresponding Path objects of created surfaces.
     """
     surfaces = create_aseg_surfaces(subject_dir, destination)
@@ -225,15 +224,11 @@ def read_vtk(path: Path):
     try:
         triangular_mesh = TriaMesh.read_vtk(path)
     except Exception:
-        message = "Failed to read VTK from the following path: {path}!".format(
-            path=path
-        )
-        raise RuntimeError(message)
+        message = f"Failed to read VTK from the following path: {path}!"
+        raise RuntimeError(message) from None
     else:
         if triangular_mesh is None:
-            message = "Failed to read VTK from the following path: {path}!".format(
-                path=path
-            )
+            message = f"Failed to read VTK from the following path: {path}!"
             raise RuntimeError(message)
         return triangular_mesh
 

brainprint/utils/_config.py

@@ -3,7 +3,7 @@
 import sys
 from functools import partial
 from importlib.metadata import requires, version
-from typing import IO, Callable, List, Optional
+from typing import IO, Callable, Optional
 
 import psutil
 
@@ -67,7 +67,7 @@ def sys_info(fid: Optional[IO] = None, developer: bool = False):
             _list_dependencies_info(out, ljust, dependencies)
 
 
-def _list_dependencies_info(out: Callable, ljust: int, dependencies: List[str]):
+def _list_dependencies_info(out: Callable, ljust: int, dependencies: list[str]):
     """List dependencies names and versions.
 
     Parameters
@@ -76,7 +76,7 @@ def _list_dependencies_info(out: Callable, ljust: int, dependencies: List[str]):
         output function
     ljust : int
          length of returned string
-    dependencies : List[str]
+    dependencies : list[str]
         list of dependencies
 
     """

brainprint/utils/utils.py

@@ -5,7 +5,6 @@
 import shlex
 import subprocess
 from pathlib import Path
-from typing import Dict
 
 import numpy as np
 import pandas as pd
@@ -34,11 +33,11 @@ def test_freesurfer() -> None:
     command = "mri_binarize -version"
     try:
         run_shell_command(command)
-    except FileNotFoundError:
+    except FileNotFoundError as err:
         raise RuntimeError(
             "Failed to run FreeSurfer command, please check the required binaries "
             "are included in your $PATH."
-        )
+        ) from err
 
 
 def run_shell_command(command: str, verbose: bool = False):
@@ -62,17 +61,15 @@ def run_shell_command(command: str, verbose: bool = False):
         return_code = subprocess.call(args)
     except Exception as e:
         message = (
-            "Failed to execute the following command:\n{command}\n"
-            "The following exception was raised:\n{exception}".format(
-                command=command, exception=e
-            )
+            f"Failed to execute the following command:\n{command}\n"
+            f"The following exception was raised:\n{e}"
         )
         print(message)
         raise
     if return_code != 0:
         message = (
-            "Execution of the following command:\n{command}\n"
-            "Returned non-zero exit code!".format(command=command)
+            f"Execution of the following command:\n{command}\n"
+            "Returned non-zero exit code!"
         )
         raise RuntimeError(message)
 
@@ -96,9 +93,7 @@ def validate_subject_dir(subjects_dir: Path, subject_id: str) -> Path:
     """
     subject_dir = Path(subjects_dir) / subject_id
     if not subject_dir.is_dir():
-        message = "FreeSurfer results directory at {path} does not exist!".format(
-            path=subject_dir
-        )
+        message = f"FreeSurfer results directory at {subject_dir} does not exist!"
         raise FileNotFoundError(message)
     return subject_dir
 
@@ -141,7 +136,7 @@ def export_brainprint_results(
     eigenvalues: np.ndarray,
     eigenvectors: np.ndarray = None,
     distances: np.ndarray = None,
-) -> Dict[str, Path]:
+) -> dict[str, Path]:
     """
     Writes the BrainPrint analysis results to CSV files.
 
@@ -167,7 +162,7 @@ def export_brainprint_results(
         eigenvectors_dir = destination.parent / "eigenvectors"
         eigenvectors_dir.mkdir(parents=True, exist_ok=True)
         for key, value in eigenvectors.items():
-            suffix = ".evecs-{key}.csv".format(key=key)
+            suffix = f".evecs-{key}.csv"
             name = destination.with_suffix(suffix).name
             vectors_destination = eigenvectors_dir / name
             pd.DataFrame(value).to_csv(