def unif_resample(x, n, tol=1, deg=3): x = np.atleast_2d(x) x = mu.remove_duplicate_rows(x) dl = mu.norms(x[1:] - x[:-1], 1) l = np.cumsum(np.r_[0, dl]) (tck, _) = si.splprep(x.T, k=deg, s=tol ** 2 * len(x), u=l) newu = np.linspace(0, l[-1], n) return np.array(si.splev(newu, tck)).T
def unif_resample(x, n, tol=0, deg=None): if deg is None: deg = min(3, len(x) - 1) x = np.atleast_2d(x) x = math_utils.remove_duplicate_rows(x) dl = math_utils.norms(x[1:] - x[:-1], 1) l = np.cumsum(np.r_[0, dl]) (tck, _) = si.splprep(x.T, k=deg, s=tol**2 * len(x), u=l) newu = np.linspace(0, l[-1], n) return np.array(si.splev(newu, tck)).T
def unif_resample(x,n,tol=0,deg=None): if deg is None: deg = min(3, len(x) - 1) x = np.atleast_2d(x) x = math_utils.remove_duplicate_rows(x) dl = math_utils.norms(x[1:] - x[:-1],1) l = np.cumsum(np.r_[0,dl]) (tck,_) = si.splprep(x.T,k=deg,s = tol**2*len(x),u=l) newu = np.linspace(0,l[-1],n) return np.array(si.splev(newu,tck)).T
def find_path_through_point_cloud(xyzs, plotting=False): xyzs = np.asarray(xyzs).reshape(-1, 3) S = skeletonize_point_cloud(xyzs) segs = get_segments(S) if plotting: from mayavi import mlab mlab.figure(1) mlab.clf() plot_graph_3d(S) S, segs = prune_skeleton(S, segs) if plotting: from mayavi import mlab mlab.figure(3) mlab.clf() plot_graph_3d(S) segs3d = [np.array([S.node[i]["xyz"] for i in seg]) for seg in segs] if plotting: plot_paths_2d(segs3d) C = make_cost_matrix(segs3d) PG = make_path_graph(C, [len(path) for path in segs3d]) (score, nodes) = longest_path_through_segment_graph(PG) print nodes total_path = [] for node in nodes[::2]: if node % 2 == 0: total_path.extend(segs[node // 2]) else: total_path.extend(segs[node // 2][::-1]) total_path_3d = math_utils.remove_duplicate_rows( np.array([S.node[i]["xyz"] for i in total_path])) total_path_3d = unif_resample(total_path_3d, n=100, tol=.01) # tolerance of 1mm if plotting: mlab.figure(2) mlab.clf() for seg in segs3d: x, y, z = np.array(seg).T mlab.plot3d(x, y, z, color=(0, 1, 0), tube_radius=.001) x, y, z = np.array(total_path_3d).T mlab.plot3d(x, y, z, color=(1, 0, 0), tube_radius=.01, opacity=.2) x, y, z = np.array(xyzs).reshape(-1, 3).T mlab.points3d(x, y, z, scale_factor=.01, opacity=.1, color=(0, 0, 1)) return total_path_3d
def unif_resample(x, n, weights, tol=.001, deg=3): x = np.atleast_2d(x) weights = np.atleast_2d(weights) x = mu.remove_duplicate_rows(x) x_scaled = x * weights dl = mu.norms(x_scaled[1:] - x_scaled[:-1], 1) l = np.cumsum(np.r_[0, dl]) (tck, _) = si.splprep(x_scaled.T, k=deg, s=tol**2 * len(x), u=l) newu = np.linspace(0, l[-1], n) out_scaled = np.array(si.splev(newu, tck)).T out = out_scaled / weights return out
def unif_resample(x,n,weights,tol=.001,deg=3): x = np.atleast_2d(x) weights = np.atleast_2d(weights) x = mu.remove_duplicate_rows(x) x_scaled = x * weights dl = mu.norms(x_scaled[1:] - x_scaled[:-1],1) l = np.cumsum(np.r_[0,dl]) (tck,_) = si.splprep(x_scaled.T,k=deg,s = tol**2*len(x),u=l) newu = np.linspace(0,l[-1],n) out_scaled = np.array(si.splev(newu,tck)).T out = out_scaled/weights return out
def find_path_through_point_cloud(xyzs, plotting = False): xyzs = np.asarray(xyzs).reshape(-1,3) S = skeletonize_point_cloud(xyzs) segs = get_segments(S) if plotting: from mayavi import mlab mlab.figure(1); mlab.clf() plot_graph_3d(S) S,segs = prune_skeleton(S, segs) if plotting: from mayavi import mlab mlab.figure(3); mlab.clf() plot_graph_3d(S) segs3d = [np.array([S.node[i]["xyz"] for i in seg]) for seg in segs] if plotting: plot_paths_2d(segs3d) C = make_cost_matrix(segs3d) PG = make_path_graph(C, [len(path) for path in segs3d]) (score, nodes) = longest_path_through_segment_graph(PG) print nodes total_path = [] for node in nodes[::2]: if node%2 == 0: total_path.extend(segs[node//2]) else: total_path.extend(segs[node//2][::-1]) total_path_3d = math_utils.remove_duplicate_rows(np.array([S.node[i]["xyz"] for i in total_path])) total_path_3d = unif_resample(total_path_3d, n = 100, tol=.01) # tolerance of 1mm if plotting: mlab.figure(2); mlab.clf() for seg in segs3d: x,y,z = np.array(seg).T mlab.plot3d(x,y,z,color=(0,1,0),tube_radius=.001) x,y,z = np.array(total_path_3d).T mlab.plot3d(x,y,z,color=(1,0,0),tube_radius=.01,opacity=.2) x,y,z = np.array(xyzs).reshape(-1,3).T mlab.points3d(x,y,z,scale_factor=.01,opacity=.1,color=(0,0,1)) return total_path_3d