def process(self):
inputs, outputs = self.inputs, self.outputs
if not outputs[0].is_linked:
return
result = []
params = [si.sv_get(default=[[]], deepcopy=False) for si in inputs[:4]]
params.append(inputs[4].sv_get(default=[Matrix()], deepcopy=False))
matching_f = list_match_func[self.list_match]
desired_levels = [3, 3, 2, 3, 2]
if self.noise_type in noise_numpy_types.keys():
main_func = noise_displace_numpy
noise_function = noise_func_numpy[self.out_mode]
else:
main_func = noise_displace
noise_function = noise_func[self.out_mode]
ops = [
noise_function, self.noise_type, self.smooth, self.interpolate,
self.list_match, self.output_numpy
]
result = recurse_f_level_control(params, ops, main_func, matching_f,
desired_levels)
self.outputs[0].sv_set(result)
def draw_buttons(self, context, layout):
layout.prop(self, 'out_mode', expand=True)
layout.prop(self, 'noise_type', text="Type")
if self.noise_type in noise_numpy_types.keys():
row = layout.row(align=True)
row.prop(self, 'smooth', toggle=True)
row.prop(self, 'interpolate', toggle=True)
def rclick_menu(self, context, layout):
layout.prop_menu_enum(self, "out_mode")
layout.prop_menu_enum(self, "noise_type")
if self.noise_type in noise_numpy_types.keys():
layout.prop(self, 'smooth', toggle=True)
layout.prop(self, 'interpolate', toggle=True)
layout.prop(self, "output_numpy", toggle=True)
def process(self):
inputs, outputs = self.inputs, self.outputs
if not (outputs[0].is_linked and inputs[0].is_linked):
return
out = []
verts = inputs['Vertices'].sv_get(deepcopy=False)
noise_matrix = inputs['Noise Matrix'].sv_get(deepcopy=False,
default=[])
seeds = inputs['Seed'].sv_get()[0]
noise_type = self.noise_type
numpy_mode = noise_type in noise_numpy_types.keys()
if noise_matrix:
verts = preprocess_verts(noise_matrix, verts, numpy_mode)
max_len = max(map(len, (seeds, verts)))
out_mode = self.out_mode
output_numpy = self.output_numpy
if numpy_mode:
noise_function = noise_numpy_types[noise_type][self.interpolate]
smooth = self.smooth
for i in range(max_len):
seed = seeds[min(i, len(seeds) - 1)]
obj_id = min(i, len(verts) - 1)
numpy_noise(verts[obj_id], out, out_mode, seed, noise_function,
smooth, output_numpy)
else:
noise_function = noise.noise_vector
for i in range(max_len):
seed = seeds[min(i, len(seeds) - 1)]
obj_id = min(i, len(verts) - 1)
# 0 unsets the seed and generates unreproducable output based on system time
seed_val = int(round(seed)) or 140230
noise.seed_set(seed_val)
mathulis_noise(verts[obj_id], out, out_mode, noise_type,
noise_function, output_numpy)
outputs[0].sv_set(out)
def rclick_menu(self, context, layout):
if self.noise_type in noise_numpy_types.keys():
layout.prop(self, 'smooth', toggle=True)
layout.prop(self, 'interpolate', toggle=True)
layout.prop_menu_enum(self, "list_match", text="List Match")
layout.prop(self, "output_numpy", toggle=True)
np_scale = local_match(np.array(scale_out), len(verts))
if type(matrix) == list:
matrix = matrix[0].inverted()
else:
matrix = matrix.inverted()
n_props = [np_scale, seed_val[0], matrix, smooth, interpolate]
noise_function(verts, pols, noise_type, n_props, result, output_numpy)
return result
avail_noise = [(t[0], t[0].title(), t[0].title(), '', t[1])
for t in noise_options]
for idx, new_type in enumerate(noise_numpy_types.keys()):
avail_noise.append((new_type, new_type.title().replace('_', ' '),
new_type.title(), '', 100 + idx))
noise_func = {'NORMAL': v_normal, 'VECTOR': v_noise}
noise_func_numpy = {'NORMAL': v_normal_numpy, 'VECTOR': v_noise_numpy}
class SvNoiseDisplaceNode(bpy.types.Node, SverchCustomTreeNode):
"""
Triggers: Add Noise to verts
Tooltip: Move input verts/mesh with a noise values.
"""
bl_idname = 'SvNoiseDisplaceNode'
