Precommit updated configuration

.pre-commit-config.yaml

@@ -2,20 +2,20 @@
 # See https://pre-commit.com/hooks.html for more hooks
 repos:
   - repo: https://github.com/timothycrosley/isort
-    rev: 5.10.1
+    rev: 5.12.0
     hooks:
       - id: isort
         args: [--settings-path, "pyproject.toml"]
   - repo: https://github.com/psf/black
-    rev: 22.3.0
+    rev: 23.1.0
     hooks:
       - id: black
-  - repo: https://gitlab.com/pycqa/flake8
-    rev: 3.9.2
+  - repo: https://github.com/pycqa/flake8
+    rev: 6.0.0
     hooks:
       - id: flake8
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.2.0
+    rev: v4.4.0
     hooks:
       - id: check-ast
       - id: check-case-conflict

src/bob/fusion/base/script/fuse.py

@@ -33,7 +33,7 @@ def write_info(
     model_file,
     skip_check,
     force,
-    **kwargs
+    **kwargs,
 ):
     info = """
 scores: %s
@@ -95,7 +95,6 @@ def routine_fusion(
     min_file_size=1000,
     do_training=True,
 ):
-
     # load the model if model_file exists and no training data was provided
     if os.path.exists(model_file) and not do_training:
         logger.info("Loading the algorithm from %s", model_file)
@@ -240,7 +239,7 @@ def fuse(
     model_file,
     skip_check,
     force,
-    **kwargs
+    **kwargs,
 ):
     """Score fusion
 
@@ -288,7 +287,7 @@ def fuse(
         model_file,
         skip_check,
         force,
-        **kwargs
+        **kwargs,
     )
 
     """Do the actual fusion."""

src/bob/fusion/base/tools/plotting.py

@@ -8,7 +8,6 @@ from bob.learn.em import KMeansMachine
 
 
 def grouping(scores, gformat="random", npoints=500, seed=None, **kwargs):
-
     scores = np.asarray(scores)
     if scores.size == 0:
         return scores