benchmark_art3d.py

import time
import numpy as np

segments = np.ones((100000, 12, 3))
M = np.ones((4, 4))

def _proj_transform_vectors(vecs, M):
    is_masked = isinstance(vecs, np.ma.MaskedArray)
    if is_masked:
        mask = vecs.mask
    vecs_pad = np.empty((vecs.shape[0] + 1,) + vecs.shape[1:])
    vecs_pad[:-1] = vecs
    vecs_pad[-1] = 1
    product = np.dot(M, vecs_pad)
    result = product[:3] / product[3]
    if is_masked:
        return np.ma.array(result, mask=mask)
    else:
        return result

def baseline():
    num_faces, num_face_vertices, _ = segments.shape
    vecs = segments.reshape(-1, 3).T
    _, _, pzs = pvecs = _proj_transform_vectors(vecs, M)
    del vecs  # To avoid typos with pvecs
    psegments = pvecs.T.reshape(segments.shape)
    assert psegments.shape == (num_faces, num_face_vertices, 3)
    epilogue(psegments)

def _proj_transform_vectors_new(vecs, M):
    is_masked = isinstance(vecs, np.ma.MaskedArray)
    if is_masked:
        mask = vecs.mask
    vecs_pad = np.empty(vecs.shape[:-1] + (vecs.shape[-1] + 1,))
    vecs_pad[..., :-1] = vecs
    vecs_pad[..., -1] = 1
    product = vecs_pad @ M.T
    result = product[..., :3] / product[..., 3:]
    if is_masked:
        return np.ma.array(result, mask=mask)
    else:
        return result

def new():
    psegments = _proj_transform_vectors_new(segments, M)
    epilogue(psegments)

def epilogue(psegments):
    face_z = np.mean(psegments[..., 2], axis=-1)
    if isinstance(face_z, np.ma.MaskedArray):
        # NOTE: Unpacking .data is safe here, because every face has to contain
        #       a valid vertex.
        face_z = face_z.data
    face_order = np.argsort(face_z, axis=-1)[::-1]
    np.min(psegments[..., 2])


from timeit import timeit

N = 25

new_t = timeit(new, number=N) / N * 1000
baseline_t = timeit(baseline, number=N) / N * 1000

print('New:\t\t{: .2f}ms'.format(new_t))
print('Baseline:\t{: .2f}ms'.format(baseline_t))
print('Diff:\t\t{: .2f}ms'.format(baseline_t - new_t))