[pre-commit.ci] pre-commit autoupdate (#406)

* [pre-commit.ci] pre-commit autoupdate

updates:
- [github.com/astral-sh/ruff-pre-commit: v0.8.6 → v0.9.4](astral-sh/ruff-pre-commit@v0.8.6...v0.9.4)
- [github.com/psf/black: 24.10.0 → 25.1.0](psf/black@24.10.0...25.1.0)

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: pre-commit-ci[bot]

.pre-commit-config.yaml

@@ -16,10 +16,10 @@ repos:
           - id: requirements-txt-fixer
           - id: trailing-whitespace
     - repo: https://github.com/astral-sh/ruff-pre-commit
-      rev: v0.8.6
+      rev: v0.9.4
       hooks:
         - id: ruff
     - repo: https://github.com/psf/black
-      rev: 24.10.0
+      rev: 25.1.0
       hooks:
           - id: black

examples/add_cylinder.py

@@ -1,6 +1,6 @@
 """
-    This example shows how to add a cylinder actor to a scene (e.g.
-    to represent the location of an implanted optic canula)
+This example shows how to add a cylinder actor to a scene (e.g.
+to represent the location of an implanted optic canula)
 """
 
 from brainrender import Scene, settings

examples/add_labels.py

@@ -1,5 +1,5 @@
 """
-    This example shows how to add a label to a renderend actor
+This example shows how to add a label to a renderend actor
 """
 
 from pathlib import Path

examples/cell_density.py

@@ -1,6 +1,6 @@
 """
-    This example shows how to use a PointsDensity
-    actor to show the density of labelled cells
+This example shows how to use a PointsDensity
+actor to show the density of labelled cells
 """
 
 import random

examples/custom_camera.py

@@ -1,12 +1,12 @@
 """
-    This example shows how to create a scene and render it with a custom camera.
-    This is done by specifying a dictionary of camera parameters, to get the
-    parameters you need for your camera:
-    - render an interactive scene with any camera
-    - move the camera to where you need it to be
-    - press 'c'
-    - this will print the current camera parameters to your console. Copy paste the
-        parameters in your script
+This example shows how to create a scene and render it with a custom camera.
+This is done by specifying a dictionary of camera parameters, to get the
+parameters you need for your camera:
+- render an interactive scene with any camera
+- move the camera to where you need it to be
+- press 'c'
+- this will print the current camera parameters to your console. Copy paste the
+    parameters in your script
 """
 
 from pathlib import Path

examples/user_volumetric_data.py

@@ -1,17 +1,17 @@
 """
 
-    This example shows how to render VOLUMETRIC data in brainrender.
-    It uses data downloaded from: https://fishatlas.neuro.mpg.de/lines/
-    showing gene expression for this transgenic line (brn3c:GPF): https://zfin.org/ZDB-ALT-050728-2
-
-    These data are a 3D image with orientation different from the axes system used by
-    brainrender, so it has to be loaded and transposed to the correct orientation
-
-    This examples shows how to:
-        - load volumetric data from a TIFF file
-        - transpose the data with BrainGlobe Space to re-orient it
-        - extract a mesh from the volumetric data using vedo
-        - render the data
+This example shows how to render VOLUMETRIC data in brainrender.
+It uses data downloaded from: https://fishatlas.neuro.mpg.de/lines/
+showing gene expression for this transgenic line (brn3c:GPF): https://zfin.org/ZDB-ALT-050728-2
+
+These data are a 3D image with orientation different from the axes system used by
+brainrender, so it has to be loaded and transposed to the correct orientation
+
+This examples shows how to:
+    - load volumetric data from a TIFF file
+    - transpose the data with BrainGlobe Space to re-orient it
+    - extract a mesh from the volumetric data using vedo
+    - render the data
 
 """
 

examples/volumetric_data.py

@@ -1,8 +1,8 @@
 """
-    This example shows how to render volumetric (i.e. organized in voxel)
-    data in brainrender. The data used are is the localized expression of
-    'Gpr161' from the Allen Atlas database, downloaded with brainrender
-    and saved to a numpy file
+This example shows how to render volumetric (i.e. organized in voxel)
+data in brainrender. The data used are is the localized expression of
+'Gpr161' from the Allen Atlas database, downloaded with brainrender
+and saved to a numpy file
 """
 
 import numpy as np