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import numpy
import pypathlib
def test_show():
path = pypathlib.ClosedPath([[0.0, 0.0], [1.0, 0.0], [1.1, 1.1], [0.1, 1.0]])
path.show()
return
def test_convex():
path = pypathlib.ClosedPath([[0.0, 0.0], [1.0, 0.0], [1.1, 1.1], [0.1, 1.0]])
ref = 1.045
assert abs(path.area - ref) < 1.0e-12 * ref
assert path.positive_orientation
assert all(path.is_convex_node)
return
def test_orientation():
path = pypathlib.ClosedPath([[0.1, 1.0], [1.1, 1.1], [1.0, 0.0], [0.0, 0.0]])
ref = 1.045
assert abs(path.area - ref) < 1.0e-12 * ref
assert not path.positive_orientation
assert all(path.is_convex_node)
return
def test_concave():
path = pypathlib.ClosedPath(
[[0.0, 0.0], [1.0, 0.0], [0.9, 0.5], [1.1, 1.1], [0.1, 1.0]]
)
ref = 0.965
assert abs(path.area - ref) < 1.0e-12 * ref
assert path.positive_orientation
assert numpy.array_equal(path.is_convex_node, [True, True, False, True, True])
return
def test_concave_counterclock():
path = pypathlib.ClosedPath(
[[0.1, 1.0], [1.1, 1.1], [0.9, 0.5], [1.0, 0.0], [0.0, 0.0]]
)
ref = 0.965
assert abs(path.area - ref) < 1.0e-12 * ref
assert not path.positive_orientation
assert numpy.array_equal(path.is_convex_node, [True, True, False, True, True])
return
def test_squared_distance():
path = pypathlib.ClosedPath(
[[0.0, 0.0], [1.0, 0.0], [0.9, 0.5], [1.0, 1.0], [0.0, 1.0]]
)
dist = path.squared_distance(
[[0.2, 0.1], [0.5, 0.5], [1.0, 0.5], [0.0, 1.1], [-0.1, 1.1], [1.0, 1.0]]
)
ref = numpy.array([0.01, 0.16, 1.0 / 104.0, 0.01, 0.02, 0.0])
assert numpy.all(numpy.abs(dist - ref) < 1.0e-12)
return
def test_distance():
path = pypathlib.ClosedPath(
[[0.0, 0.0], [1.0, 0.0], [0.9, 0.5], [1.0, 1.0], [0.0, 1.0]]
)
dist = path.distance(
[[0.2, 0.1], [0.5, 0.5], [1.0, 0.5], [0.0, 1.1], [-0.1, 1.1], [1.0, 1.0]]
)
ref = numpy.array([0.1, 0.4, numpy.sqrt(1.0 / 104.0), 0.1, numpy.sqrt(2) / 10, 0.0])
assert numpy.all(numpy.abs(dist - ref) < 1.0e-12)
return
def test_signed_distance():
path = pypathlib.ClosedPath(
[[0.0, 0.0], [1.0, 0.0], [0.9, 0.5], [1.0, 1.0], [0.0, 1.0]]
)
dist = path.signed_distance(
[[0.2, 0.1], [0.5, 0.5], [1.0, 0.5], [0.0, 1.1], [-0.1, 1.1], [1.0, 1.0]]
)
print(dist)
ref = numpy.array(
[-0.1, -0.4, numpy.sqrt(1.0 / 104.0), 0.1, numpy.sqrt(2) / 10, 0.0]
)
assert numpy.all(numpy.abs(dist - ref) < 1.0e-12)
return
def test_inside():
path = pypathlib.ClosedPath(
[[0.0, 0.0], [1.0, 0.0], [0.9, 0.5], [1.0, 1.0], [0.0, 1.0]]
)
contains_points = path.contains_points(
[[0.2, 0.1], [0.5, 0.5], [1.0, 0.5], [0.0, 1.1], [-0.1, 1.1], [1.0, 1.0]]
)
assert numpy.array_equal(contains_points, [True, True, False, False, False, True])
return
def test_closest_points():
path = pypathlib.ClosedPath(
[[0.0, 0.0], [1.0, 0.0], [0.9, 0.5], [1.0, 1.0], [0.0, 1.0]]
)
closest_points = path.closest_points(
[[0.2, 0.1], [0.5, 0.5], [1.0, 0.5], [0.0, 1.1], [-0.1, 1.1], [1.0, 1.0]]
)
ref = numpy.array(
[
[0.2, 0.0],
[0.9, 0.5],
[9.0384615384615385e-01, 5.1923076923076927e-01],
[0.0, 1.0],
[0.0, 1.0],
[1.0, 1.0],
]
)
assert numpy.all(numpy.abs(closest_points - ref) < 1.0e-12)
return
def test_signed_squared_distance():
path = pypathlib.ClosedPath(
[[0.0, 0.0], [1.0, 0.0], [0.9, 0.5], [1.0, 1.0], [0.0, 1.0]]
)
dist = path.signed_squared_distance(
[[0.2, 0.1], [0.5, 0.5], [1.0, 0.5], [0.0, 1.1], [-0.1, 1.1], [1.0, 1.0]]
)
ref = numpy.array([-0.01, -0.16, 1.0 / 104.0, 0.01, 0.02, 0.0])
assert numpy.all(numpy.abs(dist - ref) < 1.0e-12)
return
def test_sharp_angle():
path = pypathlib.ClosedPath(
[
[0.0, 0.0],
[1.0, 0.0],
[1.0, 0.45],
[0.6, 0.5],
[1.0, 0.55],
[1.0, 1.0],
[0.0, 1.0],
]
)
contains_points = path.contains_points([[0.5, 0.4], [0.5, 0.6]])
assert numpy.all(contains_points)
dist = path.signed_squared_distance([[0.5, 0.4], [0.5, 0.6]])
ref = numpy.array([-0.02, -0.02])
assert numpy.all(numpy.abs(dist - ref) < 1.0e-12)
return
# def test_two_points():
# path = pypathlib.ClosedPath([[-0.5, 1.0], [+0.5, 1.0]])
# contains_points = path.contains_points([[0.0, 0.0], [0.0, 2.0]])
# assert numpy.array_equal(contains_points, [False, False])
# return
if __name__ == "__main__":
test_sharp_angle()
|
