Merge pull request #173 from nschloe/clarify-license

Clarify license

.pre-commit-config.yaml

@@ -5,7 +5,7 @@ repos:
       - id: isort
 
   - repo: https://github.com/psf/black
-    rev: 21.10b0
+    rev: 22.1.0
     hooks:
       - id: black
         language_version: python3

README.md

@@ -116,17 +116,14 @@ import numpy as np
 import meshplex
 
 # Generate tetrahedron
-points = (
-    np.array(
-        [
-            [1.0, 0.0, -1.0 / np.sqrt(8)],
-            [-0.5, +np.sqrt(3.0) / 2.0, -1.0 / np.sqrt(8)],
-            [-0.5, -np.sqrt(3.0) / 2.0, -1.0 / np.sqrt(8)],
-            [0.0, 0.0, np.sqrt(2.0) - 1.0 / np.sqrt(8)],
-        ]
-    )
-    / np.sqrt(3.0)
-)
+points = np.array(
+    [
+        [1.0, 0.0, -1.0 / np.sqrt(8)],
+        [-0.5, +np.sqrt(3.0) / 2.0, -1.0 / np.sqrt(8)],
+        [-0.5, -np.sqrt(3.0) / 2.0, -1.0 / np.sqrt(8)],
+        [0.0, 0.0, np.sqrt(2.0) - 1.0 / np.sqrt(8)],
+    ]
+) / np.sqrt(3.0)
 cells = [[0, 1, 2, 3]]
 
 # Create mesh object
@@ -159,5 +156,7 @@ to install.
 
 ### License
 
-This software is published under the [GPLv3
-license](https://www.gnu.org/licenses/gpl-3.0.en.html).
+This software is available under the [GPLv3
+license](https://www.gnu.org/licenses/gpl-3.0.en.html) as well as a commercial
+license. If you'd like to use this software commercially, please contact the
+author.

src/meshplex/__about__.py

@@ -1 +1 @@
-__version__ = "0.17.0"
+__version__ = "0.17.1"

src/meshplex/_mesh_tetra.py

@@ -79,7 +79,7 @@ def q_min_sin_dihedral_angles(self):
         cos_alpha += [(fa[2] ** 2 + fa[3] ** 2 - H2) / (2 * fa[2] * fa[3])]
 
         cos_alpha = np.array(cos_alpha).T
-        sin_alpha = np.sqrt(1 - cos_alpha ** 2)
+        sin_alpha = np.sqrt(1 - cos_alpha**2)
 
         m = np.min(sin_alpha, axis=1) / (np.sqrt(2) * 2 / 3)
         return m
@@ -95,7 +95,7 @@ def q_vol_rms_edgelength3(self):
             (el2[0][0] + el2[1][0] + el2[2][0] + el2[0][2] + el2[1][1] + el2[0][1]) / 6
         )
         alpha = np.sqrt(2) / 12  # normalization factor
-        return self.cell_volumes / rms ** 3 / alpha
+        return self.cell_volumes / rms**3 / alpha
 
     def show(self):
         from matplotlib import pyplot as plt

src/meshplex/_mesh_tri.py

@@ -202,7 +202,7 @@ def compute_ncurl(self, vector_field):
         #
         #    curl = z * sum_edge_dot_A * 0.5 / |A|^2.
         #
-        curl = z * (0.5 * sum_edge_dot_A / self.cell_volumes ** 2)[..., None]
+        curl = z * (0.5 * sum_edge_dot_A / self.cell_volumes**2)[..., None]
         return curl
 
     def show_vertex(self, *args, **kwargs):

tests/helpers.py

@@ -25,7 +25,7 @@ def run(mesh, volume, convol_norms, ce_ratio_norms, cellvol_norms, tol=1.0e-12):
     # self.assertAlmostEqual(volume, total_ce_ratio, delta=tol * volume)
     # ```
     # Check ce_ratio norms.
-    alpha2 = fsum((mesh.ce_ratios ** 2).flat)
+    alpha2 = fsum((mesh.ce_ratios**2).flat)
     alpha_inf = max(abs(mesh.ce_ratios).flat)
     assert is_near_equal(ce_ratio_norms, [alpha2, alpha_inf], tol), [alpha2, alpha_inf]
 

tests/mesh_tri/test_mesh_tri.py

@@ -212,7 +212,7 @@ def test_regular_tri2(a):
     assert is_near_equal(mesh.ce_ratios, [val, val, val], tol)
 
     # control volumes
-    vol = np.sqrt(3.0) / 4 * a ** 2
+    vol = np.sqrt(3.0) / 4 * a**2
     assert is_near_equal(mesh.control_volumes, [vol / 3.0, vol / 3.0, vol / 3.0], tol)
 
     # cell volumes
@@ -300,17 +300,17 @@ def test_degenerate_small0b(h):
     tol = 1.0e-14
 
     # edge lengths
-    el = np.sqrt(0.5 ** 2 + h ** 2)
+    el = np.sqrt(0.5**2 + h**2)
     assert is_near_equal(mesh.edge_lengths.T, [el, el, 1.0], tol)
 
     # ce_ratios
-    ce0 = 0.5 / h * (h ** 2 - 0.25)
+    ce0 = 0.5 / h * (h**2 - 0.25)
     ce12 = 0.25 / h
     assert is_near_equal(mesh.ce_ratios.T, [ce12, ce12, ce0], tol)
 
     # control volumes
-    cv12 = 0.25 * (1.0 ** 2 * ce0 + (0.25 + h ** 2) * ce12)
-    cv0 = 0.5 * (0.25 + h ** 2) * ce12
+    cv12 = 0.25 * (1.0**2 * ce0 + (0.25 + h**2) * ce12)
+    cv0 = 0.5 * (0.25 + h**2) * ce12
     assert is_near_equal(mesh.control_volumes, [cv12, cv12, cv0], tol)
 
     # cell volumes
@@ -374,8 +374,8 @@ def test_degenerate_small1(h, a):
     tol = 1.0e-12
 
     # edge lengths
-    el0 = np.sqrt((1.0 - a) ** 2 + h ** 2)
-    el1 = np.sqrt(a ** 2 + h ** 2)
+    el0 = np.sqrt((1.0 - a) ** 2 + h**2)
+    el1 = np.sqrt(a**2 + h**2)
     el2 = 1.0
     assert is_near_equal(mesh.edge_lengths.T, [[el0, el1, el2]], tol)
 
@@ -648,18 +648,18 @@ def test_flat_boundary():
     mesh = meshplex.MeshTri(X, cells)
 
     # Inspect the covolumes in left cell.
-    edge_length = np.sqrt(x ** 2 + y ** 2)
+    edge_length = np.sqrt(x**2 + y**2)
     ref = np.array([edge_length, edge_length, 1.0])
     assert np.all(np.abs(mesh.edge_lengths[:, 3] - ref) < 1.0e-12)
     #
-    alpha = 0.5 / x * y * np.sqrt(y ** 2 + x ** 2)
-    beta = 0.5 / x * (x ** 2 - y ** 2)
+    alpha = 0.5 / x * y * np.sqrt(y**2 + x**2)
+    beta = 0.5 / x * (x**2 - y**2)
     ref = [alpha, alpha, beta]
     covolumes = mesh.ce_ratios[:, 3] * mesh.edge_lengths[:, 3]
     assert np.all(np.abs(covolumes - ref) < 1.0e-12)
 
     #
-    beta = np.sqrt(alpha ** 2 + 0.2 ** 2 + 0.25 ** 2)
+    beta = np.sqrt(alpha**2 + 0.2**2 + 0.25**2)
     control_volume_corners = np.array(
         [
             mesh.cell_circumcenters[0][:2],

tests/performance.py

@@ -19,8 +19,8 @@ def setup(n):
     # Compute the number of interior points such that all triangles can be somewhat
     # equilateral.
     edge_length = 2 * np.pi * radius / n
-    domain_area = np.pi - n * (radius ** 2 / 2 * (edge_length - np.sin(edge_length)))
-    cell_area = np.sqrt(3) / 4 * edge_length ** 2
+    domain_area = np.pi - n * (radius**2 / 2 * (edge_length - np.sin(edge_length)))
+    cell_area = np.sqrt(3) / 4 * edge_length**2
     target_num_cells = domain_area / cell_area
     # Euler:
     # 2 * num_points - num_boundary_edges - 2 = num_cells
@@ -76,7 +76,7 @@ def flip_new(data):
 perfplot.show(
     setup=setup,
     kernels=[flip_old, flip_new],
-    n_range=[2 ** k for k in range(5, 13)],
+    n_range=[2**k for k in range(5, 13)],
     equality_check=None,
     # set target time to 0 to avoid more than one repetition
     target_time_per_measurement=0.0,

tests/test_mesh_tetra.py

@@ -60,7 +60,7 @@ def test_regular_tet0(a):
     )
 
     # cell volumes
-    vol = a ** 3 / 6.0 / np.sqrt(2)
+    vol = a**3 / 6.0 / np.sqrt(2)
     assert is_near_equal(mesh.cell_volumes, [vol], tol)
 
     # control volumes
@@ -161,12 +161,12 @@ def test_unit_tetrahedron_geometric(a):
     assert is_near_equal(mesh.ce_ratios, ref, tol)
 
     # cell volumes
-    assert is_near_equal(mesh.cell_volumes, [a ** 3 / 6.0], tol)
+    assert is_near_equal(mesh.cell_volumes, [a**3 / 6.0], tol)
 
     # control volumes
     assert is_near_equal(
         mesh.control_volumes,
-        [a ** 3 / 8.0, a ** 3 / 72.0, a ** 3 / 72.0, a ** 3 / 72.0],
+        [a**3 / 8.0, a**3 / 72.0, a**3 / 72.0, a**3 / 72.0],
         tol,
     )
 
@@ -216,12 +216,12 @@ def test_regular_tet1_geometric_order():
     assert is_near_equal(mesh.ce_ratios, ref, tol)
 
     # cell volumes
-    assert is_near_equal(mesh.cell_volumes, [a ** 3 / 6.0], tol)
+    assert is_near_equal(mesh.cell_volumes, [a**3 / 6.0], tol)
 
     # control volumes
     assert is_near_equal(
         mesh.control_volumes,
-        [a ** 3 / 72.0, a ** 3 / 8.0, a ** 3 / 72.0, a ** 3 / 72.0],
+        [a**3 / 72.0, a**3 / 8.0, a**3 / 72.0, a**3 / 72.0],
         tol,
     )
 
@@ -449,17 +449,14 @@ def test_toy_geometric():
 def test_show_cell(render=False):
     pytest.importorskip("vtk")
 
-    points = (
-        np.array(
-            [
-                [1.0, 0.0, -1.0 / np.sqrt(8)],
-                [-0.5, +np.sqrt(3.0) / 2.0, -1.0 / np.sqrt(8)],
-                [-0.5, -np.sqrt(3.0) / 2.0, -1.0 / np.sqrt(8)],
-                [0.0, 0.0, np.sqrt(2.0) - 1.0 / np.sqrt(8)],
-            ]
-        )
-        / np.sqrt(3.0)
-    )
+    points = np.array(
+        [
+            [1.0, 0.0, -1.0 / np.sqrt(8)],
+            [-0.5, +np.sqrt(3.0) / 2.0, -1.0 / np.sqrt(8)],
+            [-0.5, -np.sqrt(3.0) / 2.0, -1.0 / np.sqrt(8)],
+            [0.0, 0.0, np.sqrt(2.0) - 1.0 / np.sqrt(8)],
+        ]
+    ) / np.sqrt(3.0)
 
     # points = np.array(
     #     [