def from_spline(
cls,
spline: BSpline,
start_width: float,
end_width: float,
segments: int,
) -> "CurvedTrace":
"""
Create curved trace from a B-spline.
Args:
spline: :class:`~ezdxf.math.BSpline` object
start_width: start width
end_width: end width
segments: count of segments for approximation
"""
curve_trace = cls()
count = segments + 1
t = linspace(0, spline.max_t, count)
for ((point, derivative),
width) in zip(spline.derivatives(t, n=1),
linspace(start_width, end_width, count)):
normal = Vec2(derivative).orthogonal(True)
curve_trace._append(Vec2(point), normal, width)
return curve_trace
def test_bspline_point_calculation_against_derivative_calculation():
# point calculation and derivative calculation are not the same functions
# for optimization reasons. The derivatives() function returns the curve
# point and n derivatives, check if both functions return the
# same curve point:
spline = BSpline(DEFPOINTS, order=4)
curve_points = [p[0] for p in spline.derivatives(PARAMS, n=1)]
for p, expected in zip(curve_points, spline.points(PARAMS)):
assert p.isclose(expected)
def test_bspline_derivative_calculation_to_pre_calculated_results():
spline = BSpline(DEFPOINTS, order=4)
for points, expected in zip(spline.derivatives(PARAMS, n=2),
DERIVATIVES_ORDER_4):
for p, e in zip(points, expected):
assert p.isclose(e)
def test_derivative_calculation_is_correct(self):
spline = BSpline(DEFPOINTS, order=4).to_nurbs_python_curve()
for t, expected in zip(PARAMS, DERIVATIVES_ORDER_4):
results = spline.derivatives(t, order=2)
for e, p in zip(expected, results):
assert e.isclose(p)