class CubicSplineTests(SverchokTestCase):
def setUp(self):
super().setUp()
vertices = [(-1, -1, 0), (0, 0, 0), (1, 2, 0), (2, 3, 0)]
self.spline = CubicSpline(vertices, metric="DISTANCE")
def test_eval(self):
t_in = np.array([0.0, 0.1, 0.4, 0.5, 0.7, 1.0])
result = self.spline.eval(t_in)
#info(result)
expected_result = np.array([[-1.0, -1.0, 0.0],
[-0.60984526, -0.66497986, 0.0],
[0.29660356, 0.5303721, 0.0],
[0.5, 1.0, 0.0],
[0.94256655, 1.91347161, 0.0],
[2.0, 3.0, 0.0]])
self.assert_numpy_arrays_equal(result, expected_result, precision=8)
def test_tangent(self):
t_in = np.array([0.0, 0.1, 0.4, 0.5, 0.7, 1.0])
result = self.spline.tangent(t_in)
expected_result = np.array([[7.89735717, 6.63246233, 0.],
[7.61454151, 6.83630432, 0.],
[4.30643188, 9.22065484, 0.],
[3.94869522, 9.47849683, 0.],
[5.37964186, 8.44712885, 0.],
[7.89735717, 6.63246233, 0.]])
self.assert_numpy_arrays_equal(result, expected_result, precision=8)
class CubicSplineTests(SverchokTestCase):
def setUp(self):
super().setUp()
vertices = [(-1, -1, 0), (0, 0, 0), (1, 2, 0), (2, 3, 0)]
self.spline = CubicSpline(vertices, metric="DISTANCE")
def test_eval(self):
t_in = np.array([0.0, 0.1, 0.4, 0.5, 0.7, 1.0])
result = self.spline.eval(t_in)
#info(result)
expected_result = np.array([[-1.0, -1.0, 0.0],
[-0.60984526, -0.66497986, 0.0],
[0.29660356, 0.5303721, 0.0],
[0.5, 1.0, 0.0],
[0.94256655, 1.91347161, 0.0],
[2.0, 3.0, 0.0]])
self.assert_numpy_arrays_equal(result, expected_result, precision=8)
def test_tangent(self):
t_in = np.array([0.0, 0.1, 0.4, 0.5, 0.7, 1.0])
result = self.spline.tangent(t_in)
#info(result)
expected_result = np.array([[0.00789736, 0.00663246, 0.0],
[0.00761454, 0.0068363, 0.0],
[0.00430643, 0.00922065, 0.0],
[0.0039487, 0.0094785, 0.0],
[0.00537964, 0.00844713, 0.0],
[0.00789736, 0.00663246, 0.0]])
self.assert_numpy_arrays_equal(result, expected_result, precision=8)
class CubicSplineTests(SverchokTestCase):
def setUp(self):
super().setUp()
vertices = [(-1, -1, 0), (0, 0, 0), (1, 2, 0), (2, 3, 0)]
self.spline = CubicSpline(vertices, metric="DISTANCE")
def test_eval(self):
t_in = np.array([0.0, 0.1, 0.4, 0.5, 0.7, 1.0])
result = self.spline.eval(t_in)
#info(result)
expected_result = np.array(
[[-1.0, -1.0, 0.0 ],
[-0.60984526, -0.66497986, 0.0 ],
[ 0.29660356, 0.5303721, 0.0 ],
[ 0.5, 1.0, 0.0 ],
[ 0.94256655, 1.91347161, 0.0 ],
[ 2.0, 3.0, 0.0 ]])
self.assert_numpy_arrays_equal(result, expected_result, precision=8)
def test_tangent(self):
t_in = np.array([0.0, 0.1, 0.4, 0.5, 0.7, 1.0])
result = self.spline.tangent(t_in)
#info(result)
expected_result = np.array(
[[ 0.00789736, 0.00663246, 0.0 ],
[ 0.00761454, 0.0068363, 0.0 ],
[ 0.00430643, 0.00922065, 0.0 ],
[ 0.0039487, 0.0094785, 0.0 ],
[ 0.00537964, 0.00844713, 0.0 ],
[ 0.00789736, 0.00663246, 0.0 ]])
self.assert_numpy_arrays_equal(result, expected_result, precision=8)
class CubicSplineTests(SverchokTestCase):
def setUp(self):
super().setUp()
vertices = [(-1, -1, 0), (0, 0, 0), (1, 2, 0), (2, 3, 0)]
self.control_points = np.array(vertices)
self.spline = CubicSpline(vertices, metric="DISTANCE")
def test_eval(self):
t_in = np.array([0.0, 0.1, 0.4, 0.5, 0.7, 1.0])
result = self.spline.eval(t_in)
#info(result)
expected_result = np.array([[-1.0, -1.0, 0.0],
[-0.60984526, -0.66497986, 0.0],
[0.29660356, 0.5303721, 0.0],
[0.5, 1.0, 0.0],
[0.94256655, 1.91347161, 0.0],
[2.0, 3.0, 0.0]])
self.assert_numpy_arrays_equal(result, expected_result, precision=8)
def test_tangent(self):
t_in = np.array([0.0, 0.1, 0.4, 0.5, 0.7, 1.0])
result = self.spline.tangent(t_in)
expected_result = np.array([[7.89735717, 6.63246233, 0.],
[7.61454151, 6.83630432, 0.],
[4.30643188, 9.22065484, 0.],
[3.94869522, 9.47849683, 0.],
[5.37964186, 8.44712885, 0.],
[7.89735717, 6.63246233, 0.]])
self.assert_numpy_arrays_equal(result, expected_result, precision=8)
def test_control_points_1(self):
#index = np.array([0,1,2])
points = self.spline.get_control_points()
self.assertEquals(points.shape, (3, 4, 3))
#print(points)
for i in range(3):
with self.subTest(segmentNum=i):
p0 = points[i][0]
p3 = points[i][3]
expected_p0 = self.control_points[i]
expected_p3 = self.control_points[i + 1]
self.assert_numpy_arrays_equal(p0, expected_p0, precision=8)
self.assert_numpy_arrays_equal(p3, expected_p3, precision=8)
bezier = SvBezierCurve([points[i][k] for k in range(4)])
t_min_spline = self.spline.tknots[i]
t_max_spline = self.spline.tknots[i + 1]
#print(f"Spline #{i}: {t_min_spline}, {t_max_spline}")
t_spline = np.linspace(t_min_spline, t_max_spline, num=10)
t_bezier = np.linspace(0, 1, num=10)
pts_spline = self.spline.eval(t_spline)
pts_bezier = bezier.evaluate_array(t_bezier)
self.assert_numpy_arrays_equal(pts_bezier,
pts_spline,
precision=6)