pre-commit fixes

LICENSE.txt

@@ -7,4 +7,4 @@ Redistribution and use in source and binary forms, with or without modification,
 
 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
 
-THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

ciso/__init__.py

@@ -1,3 +1,5 @@
+"""Cythonized ISOsurface calculation (CISO)."""
+
 from ciso.ciso import zslice
 
 __all__ = ["zslice"]

ciso/ciso.py

@@ -1,13 +1,15 @@
+"""Compute iso-surface slices on 3D fields."""
+
 import numpy as np
 
 from ciso._ciso import _zslice
 
 
 def zslice(q, p, p0):
     """
-    Returns a 2D slice of the variable `q` from a 3D field defined by `p`,
-    along an iso-surface at `p0` using a linear interpolation.
+    Return a 2D slice of the variable `q` from a 3D field defined by `p`.
 
+    The slice is defined along an iso-surface at `p0` using a linear interpolation.
     The result `q_iso` is a projection of variable at property == iso-value
     in the first non-singleton dimension.
 
@@ -24,16 +26,15 @@ def zslice(q, p, p0):
 
     """
     if q.shape != p.shape:
-        msg = "Arrays q {} and p {} must be of the same shape.".format
-        raise ValueError(msg(q.shape, p.shape))
+        raise ValueError(
+            f"Arrays q {q.shape} and p {p.shape} must be of the same shape.",
+        )
 
     if np.array(p0).squeeze().ndim != 0:
-        msg = "p0 must be a float number or 0-dim array.  Got {!r}.".format
-        raise ValueError(msg(p0))
+        raise ValueError(f"p0 must be a float number or 0-dim array.  Got {p0!r}.")
 
     if p0 < p.min() or p.max() < p0:
-        msg = "p0 {} is outise p bounds ({}, {}).".format
-        raise ValueError(msg(p0, p.min(), p.max()))
+        raise ValueError(f"p0 {p0} is outside p bounds ({p.min}, {p.max}).")
 
     q = np.asfarray(q)
     p = np.asfarray(p)
@@ -45,5 +46,4 @@ def zslice(q, p, p0):
     elif q.ndim == 2:
         return _zslice(q, p, p0)
     else:
-        msg = "Expected 2D (UGRID) or 3D (S/RGRID) arrays.  Got {}D.".format
-        raise ValueError(msg(q.ndim))
+        raise ValueError(f"Expected 2D (UGRID) or 3D (S/RGRID) arrays.  Got {q.ndim}D.")

ciso/tests/test_ciso.py

@@ -1,7 +1,6 @@
-from __future__ import absolute_import, division, print_function
-
 import os
 import sys
+
 import numpy as np
 import pytest
 
@@ -39,13 +38,16 @@ def test_bad_dtypes(data):
         zslice(np.empty_like(data["q"], dtype=np.str_), data["p"], p0=0)
 
 
-@pytest.mark.parametrize("dtype", [int, float, np.int32, np.int64, np.float16, np.float32, np.float64])
+@pytest.mark.parametrize(
+    "dtype",
+    [int, float, np.int32, np.int64, np.float16, np.float32, np.float64],
+)
 def test_good_dtypes(data, dtype):
     zslice(np.empty_like(data["q"], dtype=dtype), data["p"], p0=0)
 
 
 @pytest.mark.skipif(
-    sys.platform in ["win32"],
+    sys.platform == "win32",
     reason="Windows doesn't provide float128",
 )
 def test_good_dtypes_float128(data):

setup.py

@@ -2,11 +2,8 @@
 from Cython.Build import cythonize
 from setuptools import Extension, setup
 
-
 extensions = [
-    Extension(
-        "ciso._ciso", ["ciso/_ciso.pyx"], include_dirs=[numpy.get_include()]
-    )
+    Extension("ciso._ciso", ["ciso/_ciso.pyx"], include_dirs=[numpy.get_include()]),
 ]
 
 setup(