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DFCADSegmentator component

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DFCADSegmentator component#

Cluster a point cloud based on normals.

Inputs:

i_clouds (pointcloud ,list)

The point cloud clusters already segmented by normals.

i_assembly (ghdoc ,item)

The DFAssembly object.

i_angle_threshold (float ,item)

From 0 to 1, it’s the sin value. By default 0.1. The closer to 0 the less permissive and viceversa to 1.

i_association_threshold (float ,item)

From 0 to infinite. By default 0.1. The closer to 0 the less permissive your point.

Outputs:

o_clusters

The clouds associated to each beam.

Code:

#! python3

import System

import Rhino
from ghpythonlib.componentbase import executingcomponent as component
from Grasshopper.Kernel import GH_RuntimeMessageLevel as RML


from diffCheck.diffcheck_bindings import dfb_segmentation
from diffCheck.diffcheck_bindings import dfb_geometry

from diffCheck import df_cvt_bindings



class DFCADSegmentator(component):
    def RunScript(self,
        i_clouds: System.Collections.Generic.IList[Rhino.Geometry.PointCloud],
        i_assembly,
        i_angle_threshold: float = 0.1,
        i_association_threshold: float = 0.1) -> Rhino.Geometry.PointCloud:

        if i_clouds is None or i_assembly is None:
            self.AddRuntimeMessage(RML.Warning, "Please provide a cloud and an assembly to segment.")
            return None
        if i_angle_threshold is None:
            i_angle_threshold = 0.1
        if i_association_threshold is None:
            i_association_threshold = 0.1

        o_clusters = []
        df_clusters = []
        # we make a deepcopy of the input clouds
        df_clouds = [df_cvt_bindings.cvt_rhcloud_2_dfcloud(cloud.Duplicate()) for cloud in i_clouds]

        df_beams = i_assembly.beams
        df_beams_meshes = []
        rh_beams_meshes = []

        for df_b in df_beams:
            rh_b_mesh_faces = [df_b_f.to_mesh() for df_b_f in df_b.side_faces]
            df_b_mesh_faces = [df_cvt_bindings.cvt_rhmesh_2_dfmesh(rh_b_mesh_face) for rh_b_mesh_face in rh_b_mesh_faces]
            df_beams_meshes.append(df_b_mesh_faces)
            rh_beams_meshes.append(rh_b_mesh_faces)

            df_asssociated_cluster_faces = dfb_segmentation.DFSegmentation.associate_clusters(
                reference_mesh=df_b_mesh_faces,
                unassociated_clusters=df_clouds,
                angle_threshold=i_angle_threshold,
                association_threshold=i_association_threshold
            )

            df_asssociated_cluster = dfb_geometry.DFPointCloud()
            for df_associated_face in df_asssociated_cluster_faces:
                df_asssociated_cluster.add_points(df_associated_face)
            df_clusters.append(df_asssociated_cluster)

        dfb_segmentation.DFSegmentation.clean_unassociated_clusters(
                unassociated_clusters=df_clouds,
                associated_clusters=df_clusters,
                reference_mesh=df_beams_meshes,
                angle_threshold=i_angle_threshold,
                association_threshold=i_association_threshold
            )

        o_clusters = [df_cvt_bindings.cvt_dfcloud_2_rhcloud(cluster) for cluster in df_clusters]

        return o_clusters
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