Merge pull request #60 from nipype/pre-commit-ci-update-config

[pre-commit.ci] pre-commit autoupdate
nipype · Feb 24, 2024 · c201340 · c201340
2 parents b58ad3d + 39f9e93
commit c201340
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Showing 2 changed files with 11 additions and 11 deletions.
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -5,29 +5,29 @@ ci:
 
 repos:
 -   repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.4.0
+    rev: v4.5.0
     hooks:
     -   id: check-added-large-files
     -   id: check-yaml
     -   id: end-of-file-fixer
     -   id: trailing-whitespace
 -   repo: https://github.com/psf/black
-    rev: 23.1.0
+    rev: 24.2.0
     hooks:
     -   id: black
 -   repo: https://github.com/PyCQA/flake8
-    rev: 6.0.0
+    rev: 7.0.0
     hooks:
     - id: flake8
       exclude: ^(pydra_ml/_version\.py|versioneer\.py)$
 -   repo: https://github.com/PyCQA/isort
-    rev: 5.12.0
+    rev: 5.13.2
     hooks:
     -   id: isort
         args: ["--profile", "black"]
         exclude: ^(pydra_ml/_version\.py|versioneer\.py)$
 -   repo: https://github.com/codespell-project/codespell
-    rev: v2.2.2
+    rev: v2.2.6
     hooks:
     -   id: codespell
         exclude: ^(pydra_ml/_version\.py|versioneer\.py)$
diff --git a/pydra_ml/report.py b/pydra_ml/report.py
@@ -37,9 +37,9 @@ def performance_table(df, output_dir, round_decimals=2):
             df_clf = df_clf.reset_index(drop=True)
             df_metric_data_clean[clf] = df_clf
         df_metric_data_clean_median = df_metric_data_clean.median().T
-        df_metric_data_clean.loc[
-            len(df_metric_data_clean)
-        ] = df_metric_data_clean_median
+        df_metric_data_clean.loc[len(df_metric_data_clean)] = (
+            df_metric_data_clean_median
+        )
         df_metric_data_clean.index = list(df_metric_data_clean.index[:-1]) + ["median"]
         df_metric_data_clean.to_csv(
             os.path.join(
@@ -77,9 +77,9 @@ def performance_table(df, output_dir, round_decimals=2):
             )
             if "null" in df_metric.type.unique():
                 null_median = round(df_metric_null_clean_median[clf], 2)
-                df_summary.loc[
-                    0, clf
-                ] = f"{data_median} [{ci_lower}–{ci_upper}; {null_median}]"
+                df_summary.loc[0, clf] = (
+                    f"{data_median} [{ci_lower}–{ci_upper}; {null_median}]"
+                )
             else:
                 df_summary.loc[0, clf] = f"{data_median} [{ci_lower}–{ci_upper}]"