Merge pull request #984 from PMEAL/style/apply-ruff-throghout

pyproject.toml

@@ -158,11 +158,3 @@ exclude_lines = [
     "raise NotImplementedError",
     "if __name__ == .__main__.:",
 ]
-
-[tool.ruff]
-exclude = [".git", ".github", ".venv", "build", "docs", "examples", "test"]
-line-length = 92
-[tool.ruff.lint.per-file-ignores]
-"__init__.py" = ["E402", "F401", "F403"]
-[tool.ruff.lint]
-extend-ignore = ["F401"]

ruff.toml

@@ -29,7 +29,7 @@ exclude = [
 ]
 
 # Same as Black.
-line-length = 95
+line-length = 92
 indent-width = 4
 
 # Assume Python 3.10
@@ -40,6 +40,7 @@ target-version = "py310"
 # Unlike Flake8, Ruff doesn't enable pycodestyle warnings (`W`) or
 # McCabe complexity (`C901`) by default.
 select = ["E4", "E7", "E9", "F", "W"]
+extend-select = ["I"]
 ignore = ["E731"]
 
 # Allow fix for all enabled rules (when `--fix`) is provided.
@@ -75,3 +76,7 @@ docstring-code-format = true
 # This only has an effect when the `docstring-code-format` setting is
 # enabled.
 docstring-code-line-length = "dynamic"
+
+[lint.per-file-ignores]
+"__init__.py" = ["E402", "F401", "F403", "I001"]
+"test/**" = ["F841"]

src/porespy/beta/_drainage2.py

@@ -1,9 +1,11 @@
 import numpy as np
 from edt import edt
 from numba import njit, prange
-from porespy.filters import trim_disconnected_blobs, pc_to_satn
+
 from porespy import settings
-from porespy.tools import get_tqdm, Results
+from porespy.filters import pc_to_satn, trim_disconnected_blobs
+from porespy.tools import Results, get_tqdm
+
 tqdm = get_tqdm()
 
 
@@ -180,11 +182,12 @@ def _insert_disks_npoints_nradii_1value_parallel(
 
 
 if __name__ == "__main__":
-    import numpy as np
-    import porespy as ps
     import matplotlib.pyplot as plt
+    import numpy as np
     from edt import edt
 
+    import porespy as ps
+
     # %%
     im = ps.generators.blobs(shape=[200, 200, 200], porosity=0.7, blobiness=1.5, seed=0)
     inlets = np.zeros_like(im)

src/porespy/beta/_gdd.py

@@ -1,12 +1,14 @@
 import time
-from porespy import simulations, settings
-from porespy.tools import Results
+
+import dask
+import dask.delayed
+import edt
 import numpy as np
 import openpnm as op
 from pandas import DataFrame
-import dask.delayed
-import dask
-import edt
+
+from porespy import settings, simulations
+from porespy.tools import Results
 
 __all__ = ['tortuosity_gdd', 'chunks_to_dataframe']
 settings.loglevel = 50
@@ -345,8 +347,9 @@ def chunks_to_dataframe(im, scale_factor=3, use_dask=True):
 
 
 if __name__ =="__main__":
-    import porespy as ps
     import numpy as np
+
+    import porespy as ps
     np.random.seed(1)
     im = ps.generators.blobs(shape=[100, 100, 100], porosity=0.7)
     res = ps.simulations.tortuosity_gdd(im=im, scale_factor=3, use_dask=True)

src/porespy/beta/_generators.py

@@ -1,7 +1,6 @@
-import numpy as np
 from scipy.signal import convolve
-from porespy.tools import ps_rect
 
+from porespy.tools import ps_rect
 
 __all__ = [
     "local_diff",

src/porespy/beta/_poly_cylinders.py

@@ -1,8 +1,8 @@
 import numpy as np
+
 from porespy import settings
 from porespy.tools import get_tqdm
 
-
 tqdm = get_tqdm()
 
 
@@ -145,8 +145,9 @@ def polydisperse_cylinders(
 
 
 if __name__ == "__main__":
-    import scipy.stats as spst
     import matplotlib.pyplot as plt
+    import scipy.stats as spst
+
     import porespy as ps
 
     params = (5.65832732e+00, 1.54364793e-05, 7.37705832e+00)

src/porespy/dns/_funcs.py

@@ -1,6 +1,6 @@
 from deprecated import deprecated
-from porespy.simulations import tortuosity_fd as _tortuosity
 
+from porespy.simulations import tortuosity_fd as _tortuosity
 
 __all__ = [
     'tortuosity',

src/porespy/filters/_fftmorphology.py

@@ -1,7 +1,6 @@
 import numpy as np
 from scipy.signal import fftconvolve
 
-
 __all__ = [
     "fftmorphology",
 ]

src/porespy/filters/_funcs.py

@@ -1,20 +1,30 @@
 import inspect as insp
 import logging
+import operator as op
+from typing import Literal
+
 import dask
 import numpy as np
-import operator as op
 import scipy.ndimage as spim
 from deprecated import deprecated
-from skimage.morphology import reconstruction
+from skimage.morphology import ball, cube, diamond, disk, octahedron, reconstruction, square
 from skimage.segmentation import clear_border
-from skimage.morphology import ball, disk, square, cube, diamond, octahedron
-from porespy.tools import _check_for_singleton_axes
-from porespy.tools import get_border, subdivide, recombine, make_contiguous
-from porespy.tools import unpad, extract_subsection
-from porespy.tools import ps_disk, ps_ball, ps_round
+
 from porespy import settings
-from porespy.tools import get_tqdm
-from typing import Literal
+from porespy.tools import (
+    _check_for_singleton_axes,
+    extract_subsection,
+    get_border,
+    get_tqdm,
+    make_contiguous,
+    ps_ball,
+    ps_disk,
+    ps_round,
+    recombine,
+    subdivide,
+    unpad,
+)
+
 try:
     from pyedt import edt
 except ModuleNotFoundError:

src/porespy/filters/_nlmeans.py

@@ -1,8 +1,9 @@
+import dask
 import numpy as np
-from skimage.restoration.non_local_means import denoise_nl_means
+from skimage.exposure import match_histograms, rescale_intensity
 from skimage.restoration import estimate_sigma
-from skimage.exposure import rescale_intensity, match_histograms
-import dask
+from skimage.restoration.non_local_means import denoise_nl_means
+
 dask.config.set(scheduler="threads")
 # from dask.diagnostics import ProgressBar
 

src/porespy/filters/_size_seq_satn.py

@@ -1,7 +1,7 @@
 import numpy as np
-from porespy.tools import make_contiguous
 from scipy.stats import rankdata
 
+from porespy.tools import make_contiguous
 
 __all__ = [
     'size_to_seq',

src/porespy/filters/_snows.py

@@ -1,18 +1,25 @@
-import dask.array as da
 import inspect as insp
 import logging
+
+import dask.array as da
 import numpy as np
-from numba import njit, prange
 import scipy.ndimage as spim
 import scipy.spatial as sptl
+from numba import njit, prange
+from skimage.morphology import cube, square
 from skimage.segmentation import watershed
-from skimage.morphology import square, cube
-from porespy.tools import _check_for_singleton_axes
-from porespy.tools import extend_slice, ps_rect, ps_round
-from porespy.tools import Results
-from porespy.tools import get_tqdm
-from porespy.filters import chunked_func
+
 from porespy import settings
+from porespy.filters import chunked_func
+from porespy.tools import (
+    Results,
+    _check_for_singleton_axes,
+    extend_slice,
+    get_tqdm,
+    ps_rect,
+    ps_round,
+)
+
 try:
     from pyedt import edt
 except ModuleNotFoundError:
@@ -359,7 +366,7 @@ def reduce_peaks(peaks):
     else:
         strel = cube
     markers, N = spim.label(input=peaks, structure=strel(3))
-    inds = spim.measurements.center_of_mass(
+    inds = spim.center_of_mass(
         input=peaks, labels=markers, index=np.arange(1, N + 1)
     )
     inds = np.floor(inds).astype(int)
@@ -567,8 +574,7 @@ def trim_nearby_peaks(peaks, dt, f=1):
         from skimage.morphology import cube
 
     labels, N = spim.label(peaks > 0, structure=cube(3))
-    crds = spim.measurements.center_of_mass(peaks > 0, labels=labels,
-                                            index=np.arange(1, N + 1))
+    crds = spim.center_of_mass(peaks > 0, labels=labels, index=np.arange(1, N + 1))
     try:
         crds = np.vstack(crds).astype(int)  # Convert to numpy array of ints
     except ValueError:

src/porespy/filters/imagej/_funcs.py

@@ -1,6 +1,6 @@
 import logging
-import numpy as np
 
+import numpy as np
 
 logger = logging.getLogger(__name__)
 

src/porespy/generators/_borders.py

@@ -1,6 +1,6 @@
-import numpy as np
 from typing import Literal
 
+import numpy as np
 
 __all__ = ['faces', 'borders']
 

src/porespy/generators/_fractals.py

@@ -1,9 +1,10 @@
 import logging
+
 import numpy as np
 import scipy.ndimage as spim
-from porespy.tools import get_tqdm
-from porespy import settings
 
+from porespy import settings
+from porespy.tools import get_tqdm
 
 tqdm = get_tqdm()
 logger = logging.getLogger(__name__)

src/porespy/generators/_imgen.py

@@ -1,26 +1,28 @@
+import inspect as insp
 import logging
+from typing import List, Literal
+
 import numpy as np
-import inspect as insp
-from numba import njit
-import scipy.spatial as sptl
+import numpy.typing as npt
 import scipy.ndimage as spim
+import scipy.spatial as sptl
 import scipy.stats as spst
-from porespy import metrics
-from porespy import settings
-from typing import List, Literal
+from numba import njit
+
+from porespy import metrics, settings
 from porespy.filters import chunked_func
 from porespy.tools import (
+    _insert_disk_at_points,
+    _insert_disk_at_points_parallel,
     all_to_uniform,
-    ps_ball,
-    ps_disk,
-    get_border,
     extract_subsection,
-    insert_sphere,
+    get_border,
     get_tqdm,
-    _insert_disk_at_points,
-    _insert_disk_at_points_parallel,
+    insert_sphere,
+    ps_ball,
+    ps_disk,
 )
-import numpy.typing as npt
+
 try:
     from pyedt import edt
 except ModuleNotFoundError:

src/porespy/generators/_noise.py

@@ -1,7 +1,9 @@
+from typing import Literal
+
 import numpy as np
-from porespy.tools import all_to_uniform
 import psutil
-from typing import Literal
+
+from porespy.tools import all_to_uniform
 
 
 def fractal_noise(
@@ -10,7 +12,7 @@ def fractal_noise(
     frequency: float = 0.05,
     octaves: int = 4,
     gain: float = 0.5,
-    mode: Literal['simplex', 'perlin', 'value', 'cubic'] = 'simplex',
+    mode: Literal["simplex", "perlin", "value", "cubic"] = "simplex",
     seed: int = None,
     cores: int = 1,
     uniform: bool = True,
@@ -23,9 +25,9 @@ def fractal_noise(
     shape : array_like
         The size of the image to generate, can be 2D or 3D.
     porosity : float
-        If specified, this will convert the noise distribution to uniform 
-        (no need to set uniform to ``True``), and then threshold the image 
-        to the specified value prior to returning. 
+        If specified, this will convert the noise distribution to uniform
+        (no need to set uniform to ``True``), and then threshold the image
+        to the specified value prior to returning.
     frequency : scalar, default=0.05
         Controls the overall scale of the generated noise, with larger
         values giving smaller structures.
@@ -87,14 +89,15 @@ def fractal_noise(
     try:
         from pyfastnoisesimd import Noise, NoiseType, PerturbType
     except ModuleNotFoundError:
-        raise ModuleNotFoundError("You need to install `pyfastnoisesimd` using"
-                                  " `pip install pyfastnoisesimd`")
+        raise ModuleNotFoundError(
+            "You need to install `pyfastnoisesimd` using" " `pip install pyfastnoisesimd`"
+        )
     if cores is None:
         cores = psutil.cpu_count(logical=False)
     if seed is None:
         seed = np.random.randint(2**31)
     perlin = Noise(numWorkers=cores)
-    perlin.noiseType = getattr(NoiseType, f'{mode.capitalize()}Fractal')
+    perlin.noiseType = getattr(NoiseType, f"{mode.capitalize()}Fractal")
     perlin.frequency = frequency
     perlin.fractal.octaves = octaves
     perlin.fractal.gain = gain