"""Test Python 3 compatibility of the vertices module.
.. warning::
These are tests of a mixed Python 2/3 compatible module. When updating, be sure to update the Abaqus Python tests to
match.
"""
import math
from unittest.mock import patch
import numpy
import pytest
from turbo_turtle._abaqus_python.turbo_turtle_abaqus import vertices
compare_xy_values = {
"horizontal": (numpy.array([[0, 0], [1, 0]]), [False, True], None, None),
"vertical": (numpy.array([[0, 0], [0, 1]]), [False, True], None, None),
"x=y": (numpy.array([[0, 0], [1, 1]]), [False, False], None, None),
"inside default rtol": (numpy.array([[100, 0], [100 + 100 * 5e-6, 1]]), [False, True], None, None),
"adjust rtol": (numpy.array([[100, 0], [100 + 100 * 5e-6, 1]]), [False, False], 1e-6, None),
}
[docs]
@pytest.mark.parametrize(
"coordinates, expected, rtol, atol",
compare_xy_values.values(),
ids=compare_xy_values.keys(),
)
def test_compare_xy_values(
coordinates: numpy.ndarray, expected: list[bool], rtol: float | None, atol: float | None
) -> None:
"""Test :meth:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices._compare_xy_values`."""
bools = vertices._compare_xy_values(coordinates, rtol=rtol, atol=atol)
assert bools == expected
compare_euclidean_distance = {
"longer": (numpy.array([[0, 0], [1, 0]]), 0.1, [False, True]),
"shorter": (numpy.array([[0, 0], [1, 0]]), 10.0, [False, False]),
"equal": (numpy.array([[0, 0], [1, 0]]), 1.0, [False, False]),
}
[docs]
@pytest.mark.parametrize(
"coordinates, euclidean_distance, expected",
compare_euclidean_distance.values(),
ids=compare_euclidean_distance.keys(),
)
def test_compare_euclidean_distance(
coordinates: numpy.ndarray, euclidean_distance: float, expected: list[bool]
) -> None:
"""Test :meth:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices._compare_euclidean_distance`."""
bools = vertices._compare_euclidean_distance(coordinates, euclidean_distance)
assert bools == expected
bool_via_or = {
"all true vs all false": ([True, True], [False, False], [True, True]),
"all false": (
[False, False],
[False, False],
[False, False],
),
"all true": (
[True, True],
[True, True],
[True, True],
),
"true/false mirror": ([True, False], [False, True], [True, True]),
"true/false mirror 2": ([False, True], [True, False], [True, True]),
}
[docs]
@pytest.mark.parametrize(
"bool_list_1, bool_list_2, expected",
bool_via_or.values(),
ids=bool_via_or.keys(),
)
def test_bool_via_or(bool_list_1: list[bool], bool_list_2: list[bool], expected: list[bool]) -> None:
"""Test :meth:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices._bool_via_or`."""
bools = vertices._bool_via_or(bool_list_1, bool_list_2)
assert bools == expected
break_coordinates = {
"washer": (
numpy.array([[1.0, -0.5], [2.0, -0.5], [2.0, 0.5], [1.0, 0.5]]),
4,
[numpy.array([[1.0, -0.5]]), numpy.array([[2.0, -0.5]]), numpy.array([[2.0, 0.5]]), numpy.array([[1.0, 0.5]])],
),
"vase": (
numpy.array(
[
[5.1, -5.0],
[5.0, -4.8],
[4.5, -4.0],
[4.1, -3.0],
[4.0, -2.5],
[4.0, 2.5],
[4.1, 3.0],
[4.5, 4.0],
[5.0, 4.8],
[5.1, 5.0],
[3.0, 5.0],
[3.0, -4.0],
[0.0, -4.0],
[0.0, -5.0],
]
),
4,
[
numpy.array(
[
[5.1, -5.0],
[5.0, -4.8],
[4.5, -4.0],
[4.1, -3.0],
[4.0, -2.5],
]
),
numpy.array(
[
[4.0, 2.5],
[4.1, 3.0],
[4.5, 4.0],
[5.0, 4.8],
[5.1, 5.0],
]
),
numpy.array([[3.0, 5.0]]),
numpy.array([[3.0, -4.0]]),
numpy.array([[0.0, -4.0]]),
numpy.array([[0.0, -5.0]]),
],
),
}
[docs]
@pytest.mark.parametrize(
"coordinates, euclidean_distance, expected",
break_coordinates.values(),
ids=break_coordinates.keys(),
)
def test_break_coordinates(
coordinates: numpy.ndarray, euclidean_distance: float, expected: list[numpy.ndarray]
) -> None:
"""Test :meth:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices._break_coordinates`."""
all_splines = vertices._break_coordinates(coordinates, euclidean_distance)
for spline, expectation in zip(all_splines, expected, strict=True):
assert numpy.allclose(spline, expectation)
line_pairs = {
"washer": (
[numpy.array([[1.0, -0.5]]), numpy.array([[2.0, -0.5]]), numpy.array([[2.0, 0.5]]), numpy.array([[1.0, 0.5]])],
[
(numpy.array([1.0, -0.5]), numpy.array([2.0, -0.5])),
(numpy.array([2.0, -0.5]), numpy.array([2.0, 0.5])),
(numpy.array([2.0, 0.5]), numpy.array([1.0, 0.5])),
(numpy.array([1.0, 0.5]), numpy.array([1.0, -0.5])),
],
),
"vase": (
[
numpy.array(
[
[5.1, -5.0],
[5.0, -4.8],
[4.5, -4.0],
[4.1, -3.0],
[4.0, -2.5],
]
),
numpy.array(
[
[4.0, 2.5],
[4.1, 3.0],
[4.5, 4.0],
[5.0, 4.8],
[5.1, 5.0],
]
),
numpy.array([[3.0, 5.0]]),
numpy.array([[3.0, -4.0]]),
numpy.array([[0.0, -4.0]]),
numpy.array([[0.0, -5.0]]),
],
[
(numpy.array([4.0, -2.5]), numpy.array([4.0, 2.5])),
(numpy.array([5.1, 5.0]), numpy.array([3.0, 5.0])),
(numpy.array([3.0, 5.0]), numpy.array([3.0, -4.0])),
(numpy.array([3.0, -4.0]), numpy.array([0.0, -4.0])),
(numpy.array([0.0, -4.0]), numpy.array([0.0, -5.0])),
(numpy.array([0.0, -5.0]), numpy.array([5.1, -5.0])),
],
),
}
[docs]
@pytest.mark.parametrize(
"all_splines, expected",
line_pairs.values(),
ids=line_pairs.keys(),
)
def test_line_pairs(all_splines: list[numpy.ndarray], expected: list[tuple[numpy.ndarray, numpy.ndarray]]) -> None:
"""Test :meth:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices._line_pairs`."""
line_pairs = vertices._line_pairs(all_splines)
for pair, expectation in zip(line_pairs, expected, strict=True):
assert len(pair) == len(expectation)
assert numpy.allclose(pair[0], expectation[0])
assert numpy.allclose(pair[1], expectation[1])
scale_and_offset_coordinates = {
"no modifications": (
numpy.array(
[
[
0.0,
0.0,
],
[1.0, 1.0],
]
),
1.0,
0.0,
numpy.array(
[
[
0.0,
0.0,
],
[1.0, 1.0],
]
),
),
"scale": (
numpy.array(
[
[
0.0,
0.0,
],
[1.0, 1.0],
]
),
2.0,
0.0,
numpy.array(
[
[
0.0,
0.0,
],
[2.0, 2.0],
]
),
),
"offset": (
numpy.array(
[
[
0.0,
0.0,
],
[1.0, 1.0],
]
),
1.0,
1.0,
numpy.array(
[
[
0.0,
1.0,
],
[1.0, 2.0],
]
),
),
"both": (
numpy.array(
[
[
0.0,
0.0,
],
[1.0, 1.0],
]
),
2.0,
1.0,
numpy.array(
[
[
0.0,
1.0,
],
[2.0, 3.0],
]
),
),
}
[docs]
@pytest.mark.parametrize(
"coordinates, unit_conversion, y_offset, expected",
scale_and_offset_coordinates.values(),
ids=scale_and_offset_coordinates.keys(),
)
def test_scale_and_offset_coordinates(
coordinates: numpy.ndarray, unit_conversion: float, y_offset: float, expected: numpy.ndarray
) -> None:
"""Test :meth:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices.scale_and_offset_coordinates`."""
new_coordinates = vertices.scale_and_offset_coordinates(coordinates, unit_conversion, y_offset)
assert numpy.allclose(new_coordinates, expected)
the_real_mccoy = {
"washer": (
numpy.array([[1.0, -0.5], [2.0, -0.5], [2.0, 0.5], [1.0, 0.5]]),
4,
[
numpy.array([[1.0, -0.5], [2.0, -0.5]]),
numpy.array([[2.0, -0.5], [2.0, 0.5]]),
numpy.array([[2.0, 0.5], [1.0, 0.5]]),
numpy.array([[1.0, 0.5], [1.0, -0.5]]),
],
[],
),
"vase": (
numpy.array(
[
[5.1, -5.0],
[5.0, -4.8],
[4.5, -4.0],
[4.1, -3.0],
[4.0, -2.5],
[4.0, 2.5],
[4.1, 3.0],
[4.5, 4.0],
[5.0, 4.8],
[5.1, 5.0],
[3.0, 5.0],
[3.0, -4.0],
[0.0, -4.0],
[0.0, -5.0],
]
),
4,
[
numpy.array([[4.0, -2.5], [4.0, 2.5]]),
numpy.array([[5.1, 5.0], [3.0, 5.0]]),
numpy.array([[3.0, 5.0], [3.0, -4.0]]),
numpy.array([[3.0, -4.0], [0.0, -4.0]]),
numpy.array([[0.0, -4.0], [0.0, -5.0]]),
numpy.array([[0.0, -5.0], [5.1, -5.0]]),
],
[
numpy.array(
[
[5.1, -5.0],
[5.0, -4.8],
[4.5, -4.0],
[4.1, -3.0],
[4.0, -2.5],
]
),
numpy.array(
[
[4.0, 2.5],
[4.1, 3.0],
[4.5, 4.0],
[5.0, 4.8],
[5.1, 5.0],
]
),
],
),
}
[docs]
@pytest.mark.parametrize(
"coordinates, euclidean_distance, expected_lines, expected_splines",
the_real_mccoy.values(),
ids=the_real_mccoy.keys(),
)
def test_lines_and_splines(
coordinates: numpy.ndarray,
euclidean_distance: float,
expected_lines: list[numpy.ndarray],
expected_splines: list[numpy.ndarray],
) -> None:
"""Test :meth:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices.lines_and_splines`."""
lines, splines = vertices.lines_and_splines(coordinates, euclidean_distance)
assert len(lines) == len(expected_lines)
for line, expectation in zip(lines, expected_lines, strict=True):
assert numpy.allclose(line, expectation)
assert len(splines) == len(expected_splines)
for spline, expectation in zip(splines, expected_splines, strict=True):
assert numpy.allclose(spline, expectation)
ordered_lines_and_splines = {
"washer": (
numpy.array([[1.0, -0.5], [2.0, -0.5], [2.0, 0.5], [1.0, 0.5]]),
4,
[
numpy.array([[1.0, -0.5], [2.0, -0.5]]),
numpy.array([[2.0, -0.5], [2.0, 0.5]]),
numpy.array([[2.0, 0.5], [1.0, 0.5]]),
numpy.array([[1.0, 0.5], [1.0, -0.5]]),
],
),
"vase": (
numpy.array(
[
[5.1, -5.0],
[5.0, -4.8],
[4.5, -4.0],
[4.1, -3.0],
[4.0, -2.5],
[4.0, 2.5],
[4.1, 3.0],
[4.5, 4.0],
[5.0, 4.8],
[5.1, 5.0],
[3.0, 5.0],
[3.0, -4.0],
[0.0, -4.0],
[0.0, -5.0],
]
),
4,
[
numpy.array(
[
[5.1, -5.0],
[5.0, -4.8],
[4.5, -4.0],
[4.1, -3.0],
[4.0, -2.5],
]
),
numpy.array([[4.0, -2.5], [4.0, 2.5]]),
numpy.array(
[
[4.0, 2.5],
[4.1, 3.0],
[4.5, 4.0],
[5.0, 4.8],
[5.1, 5.0],
]
),
numpy.array([[5.1, 5.0], [3.0, 5.0]]),
numpy.array([[3.0, 5.0], [3.0, -4.0]]),
numpy.array([[3.0, -4.0], [0.0, -4.0]]),
numpy.array([[0.0, -4.0], [0.0, -5.0]]),
numpy.array([[0.0, -5.0], [5.1, -5.0]]),
],
),
}
[docs]
@pytest.mark.parametrize(
"coordinates, euclidean_distance, expected_lines_and_splines",
ordered_lines_and_splines.values(),
ids=ordered_lines_and_splines.keys(),
)
def test_ordered_lines_and_splines(
coordinates: numpy.ndarray, euclidean_distance: float, expected_lines_and_splines: list[numpy.ndarray]
) -> None:
"""Test :meth:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices.ordered_lines_and_splines`."""
lines_and_splines = vertices.ordered_lines_and_splines(coordinates, euclidean_distance)
assert len(lines_and_splines) == len(expected_lines_and_splines)
for curve, expectation in zip(lines_and_splines, expected_lines_and_splines, strict=True):
assert numpy.allclose(curve, expectation)
[docs]
def test_lines_and_splines_passthrough() -> None:
"""Test :meth:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices.lines_and_splines`."""
with (
patch(
"turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices._break_coordinates", return_value=[]
) as mock_break_coordinates,
patch("turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices._line_pairs", return_value=[]),
):
all_splines = vertices.lines_and_splines([], 4.0, rtol=1e-5, atol=1e-9)
assert all_splines == ([], [])
mock_break_coordinates.assert_called_once_with([], 4.0, rtol=1e-5, atol=1e-9)
[docs]
def test_break_coordinates_passthrough() -> None:
"""Test :meth:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices._break_coordinates`."""
with (
patch("turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices._compare_xy_values") as mock_xy_values,
patch("turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices._compare_euclidean_distance"),
patch("turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices._bool_via_or"),
patch("numpy.where"),
patch("numpy.split"),
):
vertices._break_coordinates([], 4.0, rtol=1e-5, atol=1e-9)
mock_xy_values.assert_called_once_with([], rtol=1e-5, atol=1e-9)
cylinder = {
"no offset": (1.0, 2.0, 1.0, None, numpy.array([[1.0, 0.5], [2.0, 0.5], [2.0, -0.5], [1.0, -0.5]])),
"offset half height": (1.0, 2.0, 1.0, 0.5, numpy.array([[1.0, 1.0], [2.0, 1.0], [2.0, 0.0], [1.0, 0.0]])),
}
[docs]
@pytest.mark.parametrize(
"inner_radius, outer_radius, height, y_offset, expected",
cylinder.values(),
ids=cylinder.keys(),
)
def test_cylinder(
inner_radius: float, outer_radius: float, height: float, y_offset: float | None, expected: numpy.ndarray
) -> None:
"""Test :meth:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices.cylinder`."""
kwargs = {}
if y_offset is not None:
kwargs = {"y_offset": y_offset}
coordinates = vertices.cylinder(inner_radius, outer_radius, height, **kwargs)
assert numpy.allclose(coordinates, expected)
cylinder_lines = {
"no offset": (
1.0,
2.0,
1.0,
None,
[
(numpy.array([1.0, 0.5]), numpy.array([2.0, 0.5])),
(numpy.array([2.0, 0.5]), numpy.array([2.0, -0.5])),
(numpy.array([2.0, -0.5]), numpy.array([1.0, -0.5])),
(numpy.array([1.0, -0.5]), numpy.array([1.0, 0.5])),
],
),
"offset half height": (
1.0,
2.0,
1.0,
0.5,
[
(numpy.array([1.0, 1.0]), numpy.array([2.0, 1.0])),
(numpy.array([2.0, 1.0]), numpy.array([2.0, 0.0])),
(numpy.array([2.0, 0.0]), numpy.array([1.0, 0.0])),
(numpy.array([1.0, 0.0]), numpy.array([1.0, 1.0])),
],
),
}
[docs]
@pytest.mark.parametrize(
"inner_radius, outer_radius, height, y_offset, expected",
cylinder_lines.values(),
ids=cylinder_lines.keys(),
)
def test_cylinder_lines(
inner_radius: float,
outer_radius: float,
height: float,
y_offset: float,
expected: list[tuple[numpy.ndarray, numpy.ndarray]],
) -> None:
"""Test :meth:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices.cylinder_lines`."""
kwargs = {}
if y_offset is not None:
kwargs = {"y_offset": y_offset}
lines = vertices.cylinder_lines(inner_radius, outer_radius, height, **kwargs)
for line, expected_line in zip(lines, expected, strict=True):
assert numpy.allclose(line, expected_line)
number = math.sqrt(2.0**2 / 2.0)
rectalinear_coordinates = {
"unit circle": ((1, 1, 1, 1), (0, math.pi / 2, math.pi, 2 * math.pi), ((1, 0), (0, 1), (-1, 0), (1, 0))),
"forty-fives": (
(2, 2, 2, 2),
(math.pi / 4, math.pi * 3 / 4, math.pi * 5 / 4, math.pi * 7 / 4),
((number, number), (-number, number), (-number, -number), (number, -number)),
),
}
[docs]
@pytest.mark.parametrize(
"radius_list, angle_list, expected",
rectalinear_coordinates.values(),
ids=rectalinear_coordinates.keys(),
)
def test_rectalinear_coordinates(
radius_list: tuple[float, ...], angle_list: tuple[float, ...], expected: tuple[tuple[float, ...]]
) -> None:
"""Test :meth:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices.rectalinear_coordinates`."""
coordinates = vertices.rectalinear_coordinates(radius_list, angle_list)
assert numpy.allclose(coordinates, expected)
one_over_root_three = 1.0 / math.sqrt(3.0)
normalize_vector = {
"zero": ((0.0, 0.0, 0.0), numpy.array([0.0, 0.0, 0.0])),
"unit x-axis": ((1.0, 0.0, 0.0), numpy.array([1.0, 0.0, 0.0])),
"unit y-axis": ((0.0, 1.0, 0.0), numpy.array([0.0, 1.0, 0.0])),
"unit z-axis": ((0.0, 0.0, 1.0), numpy.array([0.0, 0.0, 1.0])),
"unit equal": ((1.0, 1.0, 1.0), numpy.array([one_over_root_three, one_over_root_three, one_over_root_three])),
"twice unit equal": ((2.0, 2.0, 2.0), numpy.array([one_over_root_three, one_over_root_three, one_over_root_three])),
}
[docs]
@pytest.mark.parametrize(
"vector, expected",
normalize_vector.values(),
ids=normalize_vector.keys(),
)
def test_normalize_vector(vector: tuple[float, ...], expected: numpy.ndarray) -> None:
"""Test :func:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices.normalize_vector`."""
normalized = vertices.normalize_vector(vector)
assert numpy.allclose(normalized, expected)
midpoint_vector = {
"+x+y": ([1.0, 0, 0], [0, 1.0, 0], numpy.array([0.5, 0.5, 0.0])),
"+x-y": ([1.0, 0, 0], [0, -1.0, 0], numpy.array([0.5, -0.5, 0.0])),
"+y+z": ([0, 1.0, 0], [0, 0, 1.0], numpy.array([0, 0.5, 0.5])),
"+y-z": ([0, 1.0, 0], [0, 0, -1.0], numpy.array([0, 0.5, -0.5])),
"111,-111": ([1.0, 1.0, 1.0], [-1.0, 1.0, 1.0], numpy.array([0, 1.0, 1.0])),
}
[docs]
@pytest.mark.parametrize(
"first, second, expected",
midpoint_vector.values(),
ids=midpoint_vector.keys(),
)
def test_midpoint_vector(first: list[float], second: list[float], expected: numpy.ndarray) -> None:
"""Test :func:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices.midpoint_vector`."""
midpoint = vertices.midpoint_vector(first, second)
assert numpy.allclose(midpoint, expected)
is_parallel = {
"identical": ((1.0, 1.0, 1.0), (1.0, 1.0, 1.0), True),
"orthogonal": ((1.0, 0.0, 0.0), (0.0, 0.0, 1.0), False),
"multiple": ((0.0, 1.0, 0.0), (0.0, 2.0, 0.0), True),
}
[docs]
@pytest.mark.parametrize(
"first, second, expected",
is_parallel.values(),
ids=is_parallel.keys(),
)
def test_is_parallel(first: tuple[float, ...], second: tuple[float, ...], expected: bool) -> None:
"""Test :func:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices.is_parallel`."""
boolean = vertices.is_parallel(first, second)
assert boolean == expected
any_parallel = {
"identical": ((1.0, 1.0, 1.0), [(1.0, 1.0, 1.0), (1.0, 0.0, 0.0)], True),
"orthogonal": ((1.0, 0.0, 0.0), [(0.0, 0.0, 1.0), (0.0, 1.0, 0.0)], False),
"multiple": ((0.0, 1.0, 0.0), [(2.0, 0.0, 0.0), (0.0, 2.0, 0.0)], True),
}
[docs]
@pytest.mark.parametrize(
"first, options, expected",
any_parallel.values(),
ids=any_parallel.keys(),
)
def test_any_parallel(first: tuple[float, ...], options: list[tuple[float, ...]], expected: bool) -> None:
"""Test :func:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices.any_parallel`."""
boolean = vertices.any_parallel(first, options)
assert boolean == expected
norm = math.sqrt(0.5)
datum_planes = {
"globally aligned 45-degrees": (
(1.0, 0.0, 0.0),
(0.0, 0.0, 1.0),
[
numpy.array([0.0, 0.0, 1.0]), # XY plane
numpy.array([1.0, 0.0, 0.0]), # YZ plane
numpy.array([0.0, 1.0, 0.0]), # ZX plane
numpy.array([norm, norm, 0.0]),
numpy.array([norm, -norm, 0.0]),
numpy.array([0.0, norm, norm]),
numpy.array([0.0, norm, -norm]),
numpy.array([norm, 0.0, norm]),
numpy.array([-norm, 0.0, norm]),
],
),
}
[docs]
@pytest.mark.parametrize(
"xvector, zvector, expected",
datum_planes.values(),
ids=datum_planes.keys(),
)
def test_datum_planes(xvector: numpy.ndarray, zvector: numpy.ndarray, expected: numpy.ndarray) -> None:
"""Test :func:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices.datum_planes`."""
planes = vertices.datum_planes(xvector, zvector)
for plane, expectation in zip(planes, expected, strict=True):
assert numpy.allclose(plane, expectation)
over_root_three = 1.0 / math.sqrt(3.0)
fortyfive_vectors = {
"cartesian aligned": (
numpy.array([1.0, 0.0, 0.0]),
numpy.array([0.0, 0.0, 1.0]),
[
numpy.array([over_root_three, over_root_three, over_root_three]),
numpy.array([-over_root_three, over_root_three, over_root_three]),
numpy.array([-over_root_three, over_root_three, -over_root_three]),
numpy.array([over_root_three, over_root_three, -over_root_three]),
numpy.array([over_root_three, -over_root_three, over_root_three]),
numpy.array([-over_root_three, -over_root_three, over_root_three]),
numpy.array([-over_root_three, -over_root_three, -over_root_three]),
numpy.array([over_root_three, -over_root_three, -over_root_three]),
],
),
}
[docs]
@pytest.mark.parametrize(
"xvector, zvector, expected",
fortyfive_vectors.values(),
ids=fortyfive_vectors.keys(),
)
def test_fortyfive_vectors(xvector: numpy.ndarray, zvector: numpy.ndarray, expected: numpy.ndarray) -> None:
"""Test :func:`turbo_turtle._abaqus_python.turbo_turtle_abaqus.vertices.fortyfive_vectors`."""
fortyfive_vectors = vertices.fortyfive_vectors(xvector, zvector)
for vector, expectation in zip(fortyfive_vectors, expected, strict=True):
assert numpy.allclose(vector, expectation)
