3dgrid_downsample.py

from collections import defaultdict


def downsample(verts, n=(20,20,20)):

    grid_3d = defaultdict(list)
    bbox = getBBox(verts)
    xdiv, ydiv, zdiv = get_divs(bbox)

    def getBBox(verts):
        rotated = list(zip(*verts[0][::-1]))
        return [[min(dim), max(dim)] for dim in rotated]

    def get_divs(bbox):
        # refactor later.
        x_span = bbox[0][1] - bbox[0][0] 
        y_span = bbox[1][1] - bbox[1][0] 
        z_span = bbox[2][1] - bbox[2][0]
        x_seg = x_span / n[0]
        y_seg = y_span / n[1]
        z_seg = z_span / n[2]
        xdiv = [bbox[0][0]+(x_seg*i) for i in range(n[0])]
        ydiv = [bbox[1][0]+(y_seg*i) for i in range(n[1])]
        zdiv = [bbox[2][0]+(z_seg*i) for i in range(n[2])]
        return xdiv, ydiv, zdiv

    def avg_vert(verts):
        n_verts = len(verts)
        if n_verts == 1:
            return verts[0]
        else:
            s = verts[0]
            [s += v for v in verts[1:]]
            return s

    def find_slot(dim, dimdivs):
        for idx, div in reversed(list(enumerate(dimdivs))):
            if not dim >= div:
                continue
            else:
                return idx
        return 0

    def get_bucket_tuple(vec):
        x_idx = find_slot(vec.x, xdiv)
        y_idx = find_slot(vec.y, ydiv)
        z_idx = find_slot(vec.z, zdiv)
        return x_idx, y_idx, z_idx


    for v in verts:
        bucket = get_bucket_tuple(vec)
        grid_3d[bucket].append(Vector(v))

    return [avg_vert(v) for v in grid_3d.values()]

Is this for SN? I'll be patient and waited for the working script.

For find_slot I think python bisect or numpy.searchsorted is the right answer.
http://docs.scipy.org/doc/numpy/reference/generated/numpy.searchsorted.html
https://docs.python.org/3.4/library/bisect.html

Also return s*1/n_verts on line 34.