def process(self):
if not any(socket.is_linked for socket in self.outputs):
return
vertices_s = self.inputs['Vertices'].sv_get()
degree_s = self.inputs['Degree'].sv_get()
curves_out = []
points_out = []
knots_out = []
for vertices, degree in zip_long_repeat(vertices_s, degree_s):
if isinstance(degree, (tuple, list)):
degree = degree[0]
curve = fitting.interpolate_curve(vertices,
degree,
centripetal=self.centripetal)
points_out.append(curve.ctrlpts)
knots_out.append(curve.knotvector)
curve = SvGeomdlCurve(curve)
curves_out.append(curve)
self.outputs['Curve'].sv_set(curves_out)
self.outputs['ControlPoints'].sv_set(points_out)
self.outputs['Knots'].sv_set(knots_out)
def process(self):
if not any(socket.is_linked for socket in self.outputs):
return
vertices_s = self.inputs['Vertices'].sv_get()
degree_s = self.inputs['Degree'].sv_get()
points_cnt_s = self.inputs['PointsCnt'].sv_get()
curves_out = []
points_out = []
knots_out = []
for vertices, degree, points_cnt in zip_long_repeat(
vertices_s, degree_s, points_cnt_s):
if isinstance(degree, (tuple, list)):
degree = degree[0]
if isinstance(points_cnt, (tuple, list)):
points_cnt = points_cnt[0]
kwargs = dict(centripetal=self.centripetal)
if self.has_points_cnt:
kwargs['ctrlpts_size'] = points_cnt
curve = fitting.approximate_curve(vertices, degree, **kwargs)
points_out.append(curve.ctrlpts)
knots_out.append(curve.knotvector)
curve = SvGeomdlCurve(curve)
curves_out.append(curve)
self.outputs['Curve'].sv_set(curves_out)
self.outputs['ControlPoints'].sv_set(points_out)
self.outputs['Knots'].sv_set(knots_out)
def process(self):
if not any(socket.is_linked for socket in self.outputs):
return
vertices_s = self.inputs['Vertices'].sv_get()
degree_s = self.inputs['Degree'].sv_get()
points_cnt_s = self.inputs['PointsCnt'].sv_get()
input_level = get_data_nesting_level(vertices_s)
vertices_s = ensure_nesting_level(vertices_s, 4)
degree_s = ensure_nesting_level(degree_s, 2)
points_cnt_s = ensure_nesting_level(points_cnt_s, 2)
nested_output = input_level > 3
curves_out = []
points_out = []
knots_out = []
for params in zip_long_repeat(vertices_s, degree_s, points_cnt_s):
new_curves = []
new_points = []
new_knots = []
for vertices, degree, points_cnt in zip_long_repeat(*params):
kwargs = dict(centripetal=self.centripetal)
if self.has_points_cnt:
kwargs['ctrlpts_size'] = points_cnt
curve = fitting.approximate_curve(vertices, degree,
**kwargs)
new_points.append(curve.ctrlpts)
new_knots.append(curve.knotvector)
curve = SvGeomdlCurve(curve)
new_curves.append(curve)
if nested_output:
curves_out.append(new_curves)
points_out.append(new_points)
knots_out.append(new_knots)
else:
curves_out.extend(new_curves)
points_out.extend(new_points)
knots_out.extend(new_knots)
self.outputs['Curve'].sv_set(curves_out)
self.outputs['ControlPoints'].sv_set(points_out)
self.outputs['Knots'].sv_set(knots_out)
def process(self):
if not any(socket.is_linked for socket in self.outputs):
return
if not self.text_block:
return
curves_out = []
surfaces_out = []
items = self.load_json()
for i, item in enumerate(items):
if isinstance(item, BSpline.Curve):
curve = SvGeomdlCurve(item)
curves_out.append(curve)
elif isinstance(item, BSpline.Surface):
surface = SvGeomdlSurface(item)
surfaces_out.append(surface)
else:
self.warning("JSON data item #%s contains unsupported data type: %s", i, type(item))
self.outputs['Curves'].sv_set(curves_out)
self.outputs['Surfaces'].sv_set(surfaces_out)
def process(self):
if not any(socket.is_linked for socket in self.outputs):
return
vertices_s = self.inputs['Vertices'].sv_get()
weights_s = self.inputs['Weights'].sv_get(default=[[[None]]])
degree_s = self.inputs['Degree'].sv_get()
points_cnt_s = self.inputs['PointsCnt'].sv_get()
smoothing_s = self.inputs['Smoothing'].sv_get()
input_level = get_data_nesting_level(vertices_s)
vertices_s = ensure_nesting_level(vertices_s, 4)
degree_s = ensure_nesting_level(degree_s, 2)
points_cnt_s = ensure_nesting_level(points_cnt_s, 2)
smoothing_s = ensure_nesting_level(smoothing_s, 2)
has_weights = self.inputs['Weights'].is_linked
if has_weights:
weights_s = ensure_nesting_level(weights_s, 3)
nested_output = input_level > 3
curves_out = []
points_out = []
knots_out = []
for params in zip_long_repeat(vertices_s, weights_s, degree_s,
points_cnt_s, smoothing_s):
new_curves = []
new_points = []
new_knots = []
for vertices, weights, degree, points_cnt, smoothing in zip_long_repeat(
*params):
if self.implementation == 'GEOMDL':
kwargs = dict(centripetal=self.centripetal)
if self.has_points_cnt:
kwargs['ctrlpts_size'] = points_cnt
curve = fitting.approximate_curve(vertices, degree,
**kwargs)
control_points = curve.ctrlpts
knotvector = curve.knotvector
curve = SvGeomdlCurve(curve)
else: # SCIPY:
points = np.array(vertices)
if has_weights:
weights = repeat_last_for_length(
weights, len(vertices))
else:
weights = None
if not self.has_smoothing:
smoothing = None
if self.is_cyclic:
if self.auto_cyclic:
dv = np.linalg.norm(points[0] - points[-1])
is_cyclic = dv <= self.cyclic_threshold
self.info("Dv %s, threshold %s => is_cyclic %s",
dv, self.cyclic_threshold, is_cyclic)
else:
is_cyclic = True
else:
is_cyclic = False
curve = scipy_nurbs_approximate(
points,
weights=weights,
metric=self.metric,
degree=degree,
filter_doubles=None
if not self.remove_doubles else self.threshold,
smoothing=smoothing,
is_cyclic=is_cyclic)
control_points = curve.get_control_points().tolist()
knotvector = curve.get_knotvector().tolist()
new_curves.append(curve)
new_points.append(control_points)
new_knots.append(knotvector)
if nested_output:
curves_out.append(new_curves)
points_out.append(new_points)
knots_out.append(new_knots)
else:
curves_out.extend(new_curves)
points_out.extend(new_points)
knots_out.extend(new_knots)
self.outputs['Curve'].sv_set(curves_out)
self.outputs['ControlPoints'].sv_set(points_out)
self.outputs['Knots'].sv_set(knots_out)
def make(vertices):
curve = fitting.interpolate_curve(vertices,
degree,
centripetal=self.centripetal)
return SvGeomdlCurve(curve)