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Documentation for v0.1 version (#199)

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* Adding Equations, solving typos
* improve _code.rst
* the team rst and restuctore index.rst
* fixing errors

---------

Co-authored-by: Dario Coscia <dariocoscia@dhcp-015.eduroam.sissa.it>
This commit is contained in:
Dario Coscia
2023-11-08 14:39:00 +01:00
committed by Nicola Demo
parent 3f9305d475
commit 8b7b61b3bd
144 changed files with 2741 additions and 1766 deletions
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72
tests/test_geometry/test_simplex.py
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@@ -6,13 +6,11 @@ from pina.geometry 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"]),
@@ -23,40 +21,33 @@ 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., -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"]),
])
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])
@@ -127,7 +118,8 @@ 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
@@ -152,8 +144,7 @@ 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
@@ -175,5 +166,6 @@ 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