98 lines
3.9 KiB
Python
98 lines
3.9 KiB
Python
import os
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import numpy as np
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import pytest
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from damask import Rotation
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def pytest_addoption(parser):
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parser.addoption("--update",
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action="store_true",
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default=False)
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@pytest.fixture
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def update(request):
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"""Store current results as new reference results."""
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return request.config.getoption("--update")
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@pytest.fixture
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def reference_dir_base():
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"""Directory containing reference results."""
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return os.path.join(os.path.dirname(__file__),'reference')
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@pytest.fixture
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def set_of_rotations():
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"""A set of n random rotations."""
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n = 1100
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scatter=1.e-2
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specials = np.array([
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[1.0, 0.0, 0.0, 0.0],
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#----------------------
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[0.0, 1.0, 0.0, 0.0],
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[0.0, 0.0, 1.0, 0.0],
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[0.0, 0.0, 0.0, 1.0],
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[0.0,-1.0, 0.0, 0.0],
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[0.0, 0.0,-1.0, 0.0],
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[0.0, 0.0, 0.0,-1.0],
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#----------------------
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[1.0, 1.0, 0.0, 0.0],
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[1.0, 0.0, 1.0, 0.0],
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[1.0, 0.0, 0.0, 1.0],
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[0.0, 1.0, 1.0, 0.0],
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[0.0, 1.0, 0.0, 1.0],
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[0.0, 0.0, 1.0, 1.0],
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#----------------------
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[1.0,-1.0, 0.0, 0.0],
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[1.0, 0.0,-1.0, 0.0],
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[1.0, 0.0, 0.0,-1.0],
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[0.0, 1.0,-1.0, 0.0],
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[0.0, 1.0, 0.0,-1.0],
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[0.0, 0.0, 1.0,-1.0],
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#----------------------
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[0.0, 1.0,-1.0, 0.0],
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[0.0, 1.0, 0.0,-1.0],
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[0.0, 0.0, 1.0,-1.0],
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#----------------------
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[0.0,-1.0,-1.0, 0.0],
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[0.0,-1.0, 0.0,-1.0],
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[0.0, 0.0,-1.0,-1.0],
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#----------------------
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[1.0, 1.0, 1.0, 0.0],
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[1.0, 1.0, 0.0, 1.0],
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[1.0, 0.0, 1.0, 1.0],
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[1.0,-1.0, 1.0, 0.0],
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[1.0,-1.0, 0.0, 1.0],
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[1.0, 0.0,-1.0, 1.0],
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[1.0, 1.0,-1.0, 0.0],
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[1.0, 1.0, 0.0,-1.0],
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[1.0, 0.0, 1.0,-1.0],
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[1.0,-1.0,-1.0, 0.0],
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[1.0,-1.0, 0.0,-1.0],
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[1.0, 0.0,-1.0,-1.0],
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#----------------------
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[0.0, 1.0, 1.0, 1.0],
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[0.0, 1.0,-1.0, 1.0],
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[0.0, 1.0, 1.0,-1.0],
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[0.0,-1.0, 1.0, 1.0],
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[0.0,-1.0,-1.0, 1.0],
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[0.0,-1.0, 1.0,-1.0],
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[0.0,-1.0,-1.0,-1.0],
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#----------------------
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[1.0, 1.0, 1.0, 1.0],
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[1.0,-1.0, 1.0, 1.0],
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[1.0, 1.0,-1.0, 1.0],
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[1.0, 1.0, 1.0,-1.0],
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[1.0,-1.0,-1.0, 1.0],
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[1.0,-1.0, 1.0,-1.0],
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[1.0, 1.0,-1.0,-1.0],
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[1.0,-1.0,-1.0,-1.0],
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])
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specials /= np.linalg.norm(specials,axis=1).reshape(-1,1)
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specials_scatter = specials + np.broadcast_to(np.random.rand(4)*scatter,specials.shape)
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specials_scatter /= np.linalg.norm(specials_scatter,axis=1).reshape(-1,1)
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specials_scatter[specials_scatter[:,0]<0]*=-1
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return [Rotation.from_quaternion(s) for s in specials] + \
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[Rotation.from_quaternion(s) for s in specials_scatter] + \
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[Rotation.from_random() for _ in range(n-len(specials)-len(specials_scatter))]
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