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from math import sqrt
import torch
from torch_geometric.data import Data
from torch_geometric.transforms import NormalizeRotation
def test_normalize_rotation():
assert str(NormalizeRotation()) == 'NormalizeRotation()'
pos = torch.tensor([
[-2.0, -2.0],
[-1.0, -1.0],
[0.0, 0.0],
[1.0, 1.0],
[2.0, 2.0],
])
normal = torch.tensor([
[-1.0, 1.0],
[-1.0, 1.0],
[-1.0, 1.0],
[-1.0, 1.0],
[-1.0, 1.0],
])
data = Data(pos=pos)
data.normal = normal
data = NormalizeRotation()(data)
assert len(data) == 2
expected_pos = torch.tensor([
[-2 * sqrt(2), 0.0],
[-sqrt(2), 0.0],
[0.0, 0.0],
[sqrt(2), 0.0],
[2 * sqrt(2), 0.0],
])
expected_normal = [[0, 1], [0, 1], [0, 1], [0, 1], [0, 1]]
assert torch.allclose(data.pos, expected_pos, atol=1e-04)
assert data.normal.tolist() == expected_normal
data = Data(pos=pos)
data.normal = normal
data = NormalizeRotation(max_points=3)(data)
assert len(data) == 2
assert torch.allclose(data.pos, expected_pos, atol=1e-04)
assert data.normal.tolist() == expected_normal
data = Data(pos=pos)
data.normal = normal
data = NormalizeRotation(sort=True)(data)
assert len(data) == 2
assert torch.allclose(data.pos, expected_pos, atol=1e-04)
assert data.normal.tolist() == expected_normal
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