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Fix Codacy Warnings (#477)

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Co-authored-by: Dario Coscia <dariocos99@gmail.com>
This commit is contained in:
Filippo Olivo
2025-03-10 15:38:45 +01:00
committed by Nicola Demo
parent e3790e049a
commit 4177bfbb50
157 changed files with 3473 additions and 3839 deletions
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76
tests/test_geometry/test_simplex.py
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@@ -6,11 +6,13 @@ from pina.domain import SimplexDomain
def test_constructor():
SimplexDomain([
LabelTensor(torch.tensor([[0, 0]]), labels=["x", "y"]),
LabelTensor(torch.tensor([[1, 1]]), labels=["x", "y"]),
LabelTensor(torch.tensor([[0, 2]]), labels=["x", "y"]),
])
SimplexDomain(
[
LabelTensor(torch.tensor([[0, 0]]), labels=["x", "y"]),
LabelTensor(torch.tensor([[1, 1]]), labels=["x", "y"]),
LabelTensor(torch.tensor([[0, 2]]), labels=["x", "y"]),
]
)
SimplexDomain(
[
LabelTensor(torch.tensor([[0, 0]]), labels=["x", "y"]),
@@ -21,32 +23,41 @@ def test_constructor():
)
with pytest.raises(ValueError):
# different labels
SimplexDomain([
LabelTensor(torch.tensor([[0, 0]]), labels=["x", "y"]),
LabelTensor(torch.tensor([[1, 1]]), labels=["x", "z"]),
LabelTensor(torch.tensor([[0, 2]]), labels=["x", "a"]),
])
SimplexDomain(
[
LabelTensor(torch.tensor([[0, 0]]), labels=["x", "y"]),
LabelTensor(torch.tensor([[1, 1]]), labels=["x", "z"]),
LabelTensor(torch.tensor([[0, 2]]), labels=["x", "a"]),
]
)
# not LabelTensor
SimplexDomain([
LabelTensor(torch.tensor([[0, 0]]), labels=["x", "y"]),
[1, 1],
LabelTensor(torch.tensor([[0, 2]]), labels=["x", "y"]),
])
SimplexDomain(
[
LabelTensor(torch.tensor([[0, 0]]), labels=["x", "y"]),
[1, 1],
LabelTensor(torch.tensor([[0, 2]]), labels=["x", "y"]),
]
)
# different number of vertices
SimplexDomain([
LabelTensor(torch.tensor([[0., -2.]]), labels=["x", "y"]),
LabelTensor(torch.tensor([[-.5, -.5]]), labels=["x", "y"]),
LabelTensor(torch.tensor([[-2., 0.]]), labels=["x", "y"]),
LabelTensor(torch.tensor([[-.5, .5]]), labels=["x", "y"]),
])
SimplexDomain(
[
LabelTensor(torch.tensor([[0.0, -2.0]]), labels=["x", "y"]),
LabelTensor(torch.tensor([[-0.5, -0.5]]), labels=["x", "y"]),
LabelTensor(torch.tensor([[-2.0, 0.0]]), labels=["x", "y"]),
LabelTensor(torch.tensor([[-0.5, 0.5]]), labels=["x", "y"]),
]
)
def test_sample():
# sampling inside
simplex = SimplexDomain([
LabelTensor(torch.tensor([[0, 0]]), labels=["x", "y"]),
LabelTensor(torch.tensor([[1, 1]]), labels=["x", "y"]),
LabelTensor(torch.tensor([[0, 2]]), labels=["x", "y"]),
])
simplex = SimplexDomain(
[
LabelTensor(torch.tensor([[0, 0]]), labels=["x", "y"]),
LabelTensor(torch.tensor([[1, 1]]), labels=["x", "y"]),
LabelTensor(torch.tensor([[0, 2]]), labels=["x", "y"]),
]
)
pts = simplex.sample(10)
assert isinstance(pts, LabelTensor)
assert pts.size() == torch.Size([10, 2])
@@ -117,8 +128,9 @@ def test_is_inside_2D_check_border_false():
pt6 = LabelTensor(torch.tensor([[2.5, 1]]), ["x", "y"])
pt7 = LabelTensor(torch.tensor([[100, 100]]), ["x", "y"])
pts = [pt1, pt2, pt3, pt4, pt5, pt6, pt7]
for pt, exp_result in zip(pts,
[False, False, False, False, True, True, False]):
for pt, exp_result in zip(
pts, [False, False, False, False, True, True, False]
):
assert domain.is_inside(point=pt, check_border=False) == exp_result
@@ -143,7 +155,8 @@ def test_is_inside_3D_check_border_true():
pt9 = LabelTensor(torch.tensor([[2, 1, 1]]), ["x", "y", "z"])
pts = [pt1, pt2, pt3, pt4, pt5, pt6, pt7, pt8, pt9]
for pt, exp_result in zip(
pts, [True, True, True, True, True, False, True, True, False]):
pts, [True, True, True, True, True, False, True, True, False]
):
assert domain.is_inside(point=pt, check_border=True) == exp_result
@@ -165,6 +178,7 @@ def test_is_inside_3D_check_border_false():
pt6 = LabelTensor(torch.tensor([[0, 0, 20]]), ["x", "y", "z"])
pt7 = LabelTensor(torch.tensor([[2, 1, 1]]), ["x", "y", "z"])
pts = [pt1, pt2, pt3, pt4, pt5, pt6, pt7]
for pt, exp_result in zip(pts,
[False, False, False, False, False, False, True]):
for pt, exp_result in zip(
pts, [False, False, False, False, False, False, True]
):
assert domain.is_inside(point=pt, check_border=False) == exp_result