style: updated pre-commit hook versions

.github/workflows/release.yml

@@ -71,7 +71,7 @@ jobs:
           tag: ${{ github.ref_name }}
 
       - name: create Release
-        uses: ncipollo/release-action@v1.12.0
+        uses: ncipollo/release-action@v1.14.0
         with:
           allowUpdates: true
           draft: false

.pre-commit-config.yaml

@@ -11,17 +11,10 @@ repos:
       - id: check-yaml
 
   - repo: https://github.com/commitizen-tools/commitizen
-    rev: v3.15.0
+    rev: v4.0.0
     hooks:
       - id: commitizen
 
-  - repo: https://github.com/pre-commit/mirrors-prettier
-    rev: v3.1.0
-    hooks:
-      - id: prettier
-        additional_dependencies: [prettier, prettier-plugin-toml, prettier-plugin-ini]
-        types: ["ini", "toml", "yaml"]
-
   - repo: https://github.com/executablebooks/mdformat
     rev: 0.7.17 # Use the ref you want to point at
     hooks:
@@ -38,7 +31,7 @@ repos:
         args: ["-d relaxed"]
 
   - repo: https://github.com/python-jsonschema/check-jsonschema
-    rev: 0.28.0
+    rev: 0.30.0
     hooks:
       - id: check-github-workflows
 
@@ -60,7 +53,7 @@ repos:
           - tomli
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.2.2
+    rev: v0.8.2
     hooks:
       - id: ruff
         args: [ --fix ]

detectree/__init__.py

@@ -1,4 +1,5 @@
 """detectree init."""
+
 from .classifier import Classifier, ClassifierTrainer
 from .lidar import LidarToCanopy, rasterize_lidar
 from .train_test_split import TrainingSelector

detectree/lidar.py

@@ -1,4 +1,5 @@
 """Utilities to get canopy information from LiDAR data."""
+
 import laspy
 import numpy as np
 import pandas as pd

detectree/pixel_features.py

@@ -185,9 +185,9 @@ def build_features_from_arr(self, img_rgb):
                     img_lab_l, ddepth=-1, kernel=oriented_kernel_arr
                 )
                 img_filtered_vec = img_filtered.flatten()
-                X[
-                    :, self.num_color_features + i * self.num_orientations + j
-                ] = img_filtered_vec
+                X[:, self.num_color_features + i * self.num_orientations + j] = (
+                    img_filtered_vec
+                )
 
         # entropy features
         # tpf.compute_entropy_features(X_img[:, self.entropy_slice],