def test_chord_length_t_array(fit_points):
t_vector = list(distance_t_vector(fit_points))
assert len(t_vector) == len(fit_points)
assert t_vector[0] == 0.
assert t_vector[-1] == 1.
for t1, t2 in zip(t_vector, t_vector[1:]):
assert t1 <= t2
def test_double_knots(p, fit_points_2):
t_vector = list(distance_t_vector(fit_points_2))
n = len(fit_points_2) - 1
# create knots for each control point and 1st derivative
knots = double_knots(n, p, t_vector)
check_knots((n + 1) * 2, p + 1, knots)
def test_constrained_natural_knots(p, fit_points_2):
t_vector = list(distance_t_vector(fit_points_2))
n = len(fit_points_2) - 1
# add 2 knots for tangents
knots = natural_knots_constrained(n + 2, p, t_vector)
check_knots(n + 3, p + 1, knots)
def test_knot_generation(p, method):
fit_points = Vec3.list([(0, 0), (0, 10), (10, 10), (20, 10), (20, 0),
(30, 0), (30, 10), (40, 10), (40, 0)])
count = len(fit_points)
n = count - 1
order = p + 1
t_vector = distance_t_vector(fit_points)
knots = list(knots_from_parametrization(n, p, t_vector, method))
check_knots(n + 1, p + 1, knots)
def test_unconstrained_averaged_knots(p, fit_points_2):
t_vector = list(distance_t_vector(fit_points_2))
n = len(fit_points_2) - 1
knots = averaged_knots_unconstrained(n, p, t_vector)
check_knots(n + 1, p + 1, knots)
