def process(self):
inputs, outputs = self.inputs, self.outputs
if not outputs[0].is_linked:
return
_noise_type = noise_dict[self.noise_type]
_seed = inputs['Seed'].sv_get()[0][0]
wrapped_fractal_function = fractal_f[self.fractal_type]
verts = inputs['Vertices'].sv_get()
m_h_factor = inputs['H Factor'].sv_get()[0]
m_lacunarity = inputs['Lacunarity'].sv_get()[0]
m_octaves = inputs['Octaves'].sv_get()[0]
m_offset = inputs['Offset'].sv_get()[0] if 'Offset' in inputs else [
0.0
]
m_gain = inputs['Gain'].sv_get()[0] if 'Gain' in inputs else [0.0]
param_list = [m_h_factor, m_lacunarity, m_octaves, m_offset, m_gain]
out = []
for idx, vlist in enumerate(verts):
# lazy generation of full parameters.
params = [(param[idx] if idx < len(param) else param[-1])
for param in param_list]
final_vert_list = [seed_adjusted(vlist, _seed)]
out.append(
wrapped_fractal_function(_noise_type, final_vert_list[0],
*params))
outputs[0].sv_set(out)
def process(self):
inputs, outputs = self.inputs, self.outputs
if not outputs[0].is_linked:
return
_noise_type = noise_dict[self.noise_type]
_seed = inputs['Seed'].sv_get()[0][0]
wrapped_fractal_function = fractal_f[self.fractal_type]
verts = inputs['Vertices'].sv_get()
m_h_factor = inputs['H Factor'].sv_get()[0]
m_lacunarity = inputs['Lacunarity'].sv_get()[0]
m_octaves = inputs['Octaves'].sv_get()[0]
m_offset = inputs['Offset'].sv_get()[0] if 'Offset' in inputs else [0.0]
m_gain = inputs['Gain'].sv_get()[0] if 'Gain' in inputs else [0.0]
param_list = [m_h_factor, m_lacunarity, m_octaves, m_offset, m_gain]
out = []
for idx, vlist in enumerate(verts):
# lazy generation of full parameters.
params = [(param[idx] if idx < len(param) else param[-1]) for param in param_list]
final_vert_list = [seed_adjusted(vlist, _seed)]
out.append(wrapped_fractal_function(_noise_type, final_vert_list[0], *params))
outputs[0].sv_set(out)
def process(self):
inputs, outputs = self.inputs, self.outputs
if not outputs[0].is_linked:
return
_noise_type = noise_dict[self.noise_type]
tfunc = turbulence_f[self.out_mode]
verts = inputs['Vertices'].sv_get(deepcopy=False)
maxlen = len(verts)
arguments = [verts]
# gather socket data into arguments
for socket in inputs[1:]:
data = socket.sv_get()[0]
fullList(data, maxlen)
arguments.append(data)
# iterate over vert lists and pass arguments to the turbulence function
out = []
for idx, (vert_list, octaves, hard, amp, freq, seed) in enumerate(zip(*arguments)):
final_vert_list = seed_adjusted(vert_list, seed)
out.append([tfunc(v, octaves, hard, _noise_type, amp, freq) for v in final_vert_list])
if 'Noise V' in outputs:
out = Vector_degenerate(out)
outputs[0].sv_set(out)
def process(self):
inputs, outputs = self.inputs, self.outputs
if not outputs[0].is_linked:
return
_noise_type = noise_dict[self.noise_type]
tfunc = turbulence_f[self.out_mode]
verts = inputs['Vertices'].sv_get(deepcopy=False)
maxlen = len(verts)
arguments = [verts]
# gather socket data into arguments
for socket in inputs[1:]:
data = socket.sv_get()[0]
fullList(data, maxlen)
arguments.append(data)
# iterate over vert lists and pass arguments to the turbulence function
out = []
for idx, (vert_list, octaves, hard, amp, freq,
seed) in enumerate(zip(*arguments)):
final_vert_list = seed_adjusted(vert_list, seed)
out.append([
tfunc(v, octaves, hard, _noise_type, amp, freq)
for v in final_vert_list
])
if 'Noise V' in outputs:
out = Vector_degenerate(out)
outputs[0].sv_set(out)
def process(self):
inputs, outputs = self.inputs, self.outputs
if not outputs[0].is_linked:
return
out = []
verts = inputs['Vertices'].sv_get(deepcopy=False)
_seed = inputs['Seed'].sv_get()[0][0]
_distortion = inputs['Distrortion'].sv_get()[0][0]
_noise_type1 = noise_dict[self.noise_type1]
_noise_type2 = noise_dict[self.noise_type2]
for vert_list in verts:
final_vert_list = seed_adjusted(vert_list, _seed)
out.append([var_func(v, _distortion, _noise_type1, _noise_type2) for v in final_vert_list])
outputs[0].sv_set(out)
def process(self):
inputs, outputs = self.inputs, self.outputs
if not outputs[0].is_linked:
return
out = []
verts = inputs['Vertices'].sv_get(deepcopy=False)
_seed = inputs['Seed'].sv_get()[0][0]
_distortion = inputs['Distrortion'].sv_get()[0][0]
for vert_list in verts:
final_vert_list = seed_adjusted(vert_list, _seed)
out.append([
var_func(v, _distortion, self.noise_type1, self.noise_type2)
for v in final_vert_list
])
outputs[0].sv_set(out)
