util.py 文件源码

def downsample(voxels, step, method='max'):
    """
    downsample a voxels matrix by a factor of step. 
    downsample method options: max/mean 
    same as a pooling
    """
    assert step > 0
    assert voxels.ndim == 3 or voxels.ndim == 4
    assert method in ('max', 'mean')
    if step == 1:
        return voxels

    if voxels.ndim == 3:
        sx, sy, sz = voxels.shape[-3:]
        X, Y, Z = np.ogrid[0:sx, 0:sy, 0:sz]
        regions = sz/step * sy/step * (X/step) + sz/step * (Y/step) + Z/step
        if method == 'max':
            res = ndimage.maximum(voxels, labels=regions, index=np.arange(regions.max() + 1))
        elif method == 'mean':
            res = ndimage.mean(voxels, labels=regions, index=np.arange(regions.max() + 1))
        res.shape = (sx/step, sy/step, sz/step)
        return res
    else:
        res0 = downsample(voxels[0], step, method)
        res = np.zeros((voxels.shape[0],) + res0.shape)
        res[0] = res0
        for ind in xrange(1, voxels.shape[0]):
            res[ind] = downsample(voxels[ind], step, method)
        return res