def to_point(self, centers, falloff):
n = len(centers)
if n == 1:
sfield = SvScalarFieldPointDistance(centers[0], falloff=falloff)
vfield = SvVectorFieldPointDistance(centers[0], falloff=falloff)
elif self.point_mode == 'AVG':
sfields = [
SvScalarFieldPointDistance(center, falloff=falloff)
for center in centers
]
sfield = SvMergedScalarField('AVG', sfields)
vfields = [
SvVectorFieldPointDistance(center, falloff=falloff)
for center in centers
]
vfield = SvAverageVectorField(vfields)
elif self.point_mode == 'MIN':
kdt = kdtree.KDTree(len(centers))
for i, v in enumerate(centers):
kdt.insert(v, i)
kdt.balance()
vfield = SvKdtVectorField(kdt=kdt, falloff=falloff)
sfield = SvKdtScalarField(kdt=kdt, falloff=falloff)
else: # SEP
sfield = [
SvScalarFieldPointDistance(center, falloff=falloff)
for center in centers
]
vfield = [
SvVectorFieldPointDistance(center, falloff=falloff)
for center in centers
]
return vfield, sfield
def to_point(self, centers, falloff):
if self.metric == 'DISTANCE':
metric_single = 'EUCLIDEAN'
else:
metric_single = self.metric
n = len(centers)
if n == 1:
sfield = SvScalarFieldPointDistance(centers[0],
falloff=falloff,
metric=metric_single,
power=self.get_power())
vfield = SvVectorFieldPointDistance(centers[0],
falloff=falloff,
metric=metric_single,
power=self.get_power())
elif self.merge_mode == 'AVG':
sfields = [
SvScalarFieldPointDistance(center,
falloff=falloff,
metric=metric_single,
power=self.get_power())
for center in centers
]
sfield = SvMergedScalarField('AVG', sfields)
vfields = [
SvVectorFieldPointDistance(center,
falloff=falloff,
metric=metric_single,
power=self.get_power())
for center in centers
]
vfield = SvAverageVectorField(vfields)
elif self.merge_mode == 'MIN':
kdt = SvKdTree.new(SvKdTree.best_available_implementation(),
centers,
power=self.get_power())
vfield = SvKdtVectorField(kdt=kdt, falloff=falloff)
sfield = SvKdtScalarField(kdt=kdt, falloff=falloff)
else: # SEP
sfield = [
SvScalarFieldPointDistance(center,
falloff=falloff,
metric=metric_single,
power=self.get_power())
for center in centers
]
vfield = [
SvVectorFieldPointDistance(center,
falloff=falloff,
metric=metric_single,
power=self.get_power())
for center in centers
]
return vfield, sfield
def process(self):
if not any(socket.is_linked for socket in self.outputs):
return
center_s = self.inputs['Center'].sv_get()
amplitudes_s = self.inputs['Amplitude'].sv_get(default=[0.5])
coefficients_s = self.inputs['Coefficient'].sv_get(default=[0.5])
fields_out = []
for centers, amplitudes, coefficients in zip_long_repeat(
center_s, amplitudes_s, coefficients_s):
for center, amplitude, coefficient in zip_long_repeat(
centers, amplitudes, coefficients):
if self.falloff_type == 'NONE':
falloff_func = None
else:
falloff_func = falloff_array(self.falloff_type, amplitude,
coefficient, self.clamp)
field = SvScalarFieldPointDistance(np.array(center),
metric=self.metric,
power=self.power,
falloff=falloff_func)
fields_out.append(field)
self.outputs['Field'].sv_set(fields_out)