def test_point(self, p, error=None, interpolation=None, error_norm_order=2, update_improvement_map=False):
# Calculate old error
error_old = norm(self.interpolation_map() - self.dem, error_norm_order)
# Append the new coordinates
p = np.round(p).astype(int)
points = np.vstack([self.points, [p]])
values = np.append(self.point_elevations, self.dem_elevation(p[0], p[1]))
# Retriangulate
tri_new = triangle.delaunay(points)
tri_new = mpltri.Triangulation(*points.T, triangles=tri_new)
# Reinterpolate
interpolator = mpltri.LinearTriInterpolator(tri_new, values)
interpolation_new = interpolator(self.yy, self.xx)
# Calculate new error
error_new = norm(interpolation_new - self.dem, error_norm_order)
improvement = error_new - error_old
if update_improvement_map:
self.improvement_map[p[1], p[0]] = improvement
return improvement
def set_triangles(self):
points = []
for ver in self.vertexes:
points.append(ver.pos[0:2])
triangles = delaunay(points)
for tri in triangles:
self.triangles.extend(self.vertexes[tri[i]].pos for i in xrange(3))
def terrainLOD0(fname, npoints, lowerbound, upperbound, cityModel):
i = 0
points = []
ptdir = {}
while i < npoints:
randomx = random.uniform(lowerbound[0], upperbound[0])
randomy = random.uniform(lowerbound[1], upperbound[1])
randomz = random.uniform(lowerbound[2], upperbound[2])
points.append([randomx, randomy, randomz])
ptdir[i] = [randomx, randomy, randomz]
i = i + 1
x, y, origin, n = getxy(points)
local_coords = []
sep = []
for p in points:
S = np.dot(n, p - origin)
sep.append(S)
local_coords.append((np.dot(p - origin, x), np.dot(p - origin, y)))
tri = triangle.delaunay(local_coords)
get_TINRelief(cityModel, tri, ptdir, "lod0")
def triangulation(self, recalculate=False):
if recalculate or self.triangulation_dirty:
self._triangulation = triangle.delaunay(self.points)
self._triangulation = mpltri.Triangulation(*self.points.T,
triangles=self._triangulation)
self.triangulation_dirty = False
return self._triangulation
def heuristic_reconstruction(points: list, filename = None):
points = np.array(points)
ax = plt.axes()
#drawing.plot_and_save(os.path.join(images_folder, filename+"_original.png"), False, ax, vertices=points, vertices_color="g")
lim = ax.axis()
deltriangles = triangle.delaunay(points)
delaunay_edges = []
for t in deltriangles:
delaunay_edges.extend(edges_from_triangle(t))
#try:
drawing.plot(ax, vertices=points, segments=delaunay_edges)
drawing.plot_and_save(os.path.join(images_folder, os.path.join("delaunay",filename+"delaunay.eps")),
True, ax, vertices=points, vertices_color="b")
ax.axis(lim)
triangles_length = [perimeter(points, t) for t in deltriangles]
mean_length = sum(triangles_length)/len(triangles_length)
std_length = np.std(triangles_length)
filtered_triangles = [deltriangles[i] for i in range(len(deltriangles)) if triangles_length[i] < (mean_length + 1*std_length)]
ax = plt.axes()
drawing.plot_and_save(os.path.join(images_folder, os.path.join("boundary", filename+"_region1std.eps")),
True, ax, triangles = filtered_triangles, vertices=points, draw_vertices=False)
#graph initialization
num_of_triangles = len(filtered_triangles)
graph = [Node(i) for i in range(num_of_triangles)]
for node in graph:
vertices = filtered_triangles[node.id]
node.neighbors = [index for index in range(num_of_triangles) if len(set(vertices).intersection(filtered_triangles[index])) == 2]
node.costs = [1.0 for i in node.neighbors]
connected_one = []
def append_to(node, connected_one:list):
connected_one.append(node)
BFS(graph, 1, append_to, connected_one)
boundary_triangles = [filtered_triangles[node.id] for node in connected_one if len(node.neighbors) < 3]
filtered_segments = []
for t in filtered_triangles:
filtered_segments.extend(edges_from_triangle(t))
boundary_segments = [edge for edge in filtered_segments if filtered_segments.count(edge) == 1]
# print(boundary_segments)
ax = plt.axes()
drawing.plot_and_save(os.path.join(images_folder, os.path.join("boundary", filename+"_boundary_triangles1std.eps")),
True, ax, triangles = boundary_triangles, vertices=points, segments=boundary_segments)
ax = plt.axes()
drawing.plot_and_save(os.path.join(images_folder, os.path.join("boundary", filename+"_boundary_triangles1stdstd.eps")),
True, ax, vertices=points, segments=boundary_segments)
def true_deulunay(points):
G = nx.Graph()
for p in points.keys():
G.add_node(p)
triangles = triangle.delaunay([locs[x] for x in sorted(locs.keys())])
for t in triangles:
G.add_edge(t[0], t[1])
G.add_edge(t[1], t[2])
G.add_edge(t[2], t[0])
return G
def test_easy():
points = [[1.0, 2.0, 2.0, 5.0, 9.0, 10.0, -1.0],
[1.0, 1.0, 2.0, 7.0, 11.0, 11.0, 8.0]]
d = triangle.delaunay([(points[0][i], points[1][i])
for i in range(len(points[0]))])
diagram = get_persistence([[points[0][i], points[1][i]]
for i in range(len(points[0]))]).get_diagram()
print(diagram)
pyplot.scatter(points[0], points[1], marker='o')
pyplot.triplot(points[0], points[1], d)
pyplot.show()
def test_hard():
points = generators.poisson.poisson_homogeneous_point_process(1, 50)
d = triangle.delaunay(points)
diagram = get_persistence(points).get_diagram()
pyplot.figure(1)
pyplot.triplot([points[i][0] for i in range(len(points))],
[points[i][1] for i in range(len(points))], d)
pyplot.figure(2)
pyplot.scatter([diagram[i][0] for i in range(len(diagram))],
[diagram[i][1] for i in range(len(diagram))],
marker='o')
pyplot.show()
def test_delaunay():
pts = [[0, 0], [0, 1], [0.5, 0.5], [1, 1], [1, 0]]
tri = delaunay(pts)
assert np.allclose(
tri,
[
[1, 0, 2],
[2, 4, 3],
[4, 2, 0],
[2, 3, 1],
],
)
def auto_plane(self):
indices_split = self.indices_split[np.nonzero(self.all_con)]
data_gnd = self.ptCLoudData[np.nonzero(self.all_con)]
plane_split = self.plane_split
for i in range(1, len(plane_split)):
sel = data_gnd[np.nonzero(indices_split == i)]
if len(sel) < 3:
continue
pca = PCA(n_components=2)
data_transfer = pca.fit_transform(sel['a_position'])
tri = np.array(triangle.delaunay(data_transfer), dtype=np.uint32)
self.all_plane.append({'data': sel, 'tri': tri})
def delaunayMap(points, imageSize = (0, 0)):
"""Return a GeoMap containing a Delaunay Triangulation of the given
points."""
if len(points) < 3:
raise ValueError, \
"cannot compute Delaunay Triangulation of less than three points"
if triangle:
nodePositions, edges = triangle.delaunay(points)
sigma = None
else:
nodePositions, edges, sigma = geomap.delaunay(points)
return _delaunayMapFromData(nodePositions, edges, imageSize,
sigma)
def delaunayMap(points, imageSize = (0, 0)):
"""Return a GeoMap containing a Delaunay Triangulation of the given
points."""
if len(points) < 3:
raise ValueError, \
"cannot compute Delaunay Triangulation of less than three points"
if triangle:
nodePositions, edges = triangle.delaunay(points)
sigma = None
else:
nodePositions, edges, sigma = geomap.delaunay(points)
return _delaunayMapFromData(nodePositions, edges, imageSize,
sigma)
def NNcrust(points: list, filename = None)-> list:
points = np.array(points)
ax = plt.axes()
drawing.plot_and_save(os.path.join(images_folder, filename+"_original.png"), False, ax, vertices=points, vertices_color="g")
lim = ax.axis()
triangles = triangle.delaunay(points)
delaunay_edges = []
for t in triangles:
delaunay_edges.extend(edges_from_triangle(t))
rec_edges = set([])
for i in range(len(points)):
edges_with_p = [edge for edge in delaunay_edges if i in edge]
if edges_with_p:
costs = [distance(points, edge) for edge in edges_with_p]
min_index = costs.index(min(costs))
pq = edges_with_p[min_index]
rec_edges.add(pq)
ps_candidates = [edge for edge in edges_with_p if
cos_angle(points[i], points[pq[0] if pq[0] != i else pq[1]], points[edge[0] if edge[0] != i else edge[1]]) < 0]
if ps_candidates:
costs = [distance(points, edge) for edge in ps_candidates]
min_index = costs.index(min(costs))
ps = ps_candidates[min_index]
rec_edges.add(ps)
# rec_edges = [e for e in delaunay_edges if ((e[0] < len(points)) and (e[1] < len(points)))]
try:
drawing.plot(ax, vertices=points, edges=delaunay_edges, segments=rec_edges)
drawing.plot_and_save(os.path.join(images_folder, os.path.join("delaunay",filename+"delaunay.png")),
True, ax, vertices=points, vertices_color="b")
ax.axis(lim)
except Exception as e:
print("Could not draw delaunay diagram. Please, check if you have the correct directory")
#final reconstruction
ax = plt.axes()
drawing.plot_and_save(os.path.join(images_folder, filename+"_reconstruction.png"),
True, ax, vertices=points, segments=rec_edges, draw_vertices=False)
# print(points)
# print(rec_edges)
ordered_points = []
return ordered_points
def convert_point(point_set, point_on_plane, axis):
tmp = []
u = []
v = []
z = []
for i in point_set:
z.append(i[2])
tmp = [i[x] - point_on_plane[x] for x in range(3)]
tmp_u = np.dot(tmp, axis[0])
tmp_v = np.dot(tmp, axis[1])
u.append(tmp_u)
v.append(tmp_v)
points = np.column_stack((u, v))
tri = triangle.delaunay(points)
return tri
def auto_plane_gnd(self):
# TODO the condition is no need
indices_split_gnd = self.indices_split[np.nonzero(self.gnd_con)]
data_gnd = self.ptCLoudData[np.nonzero(self.gnd_con)]
plane_split = self.plane_split
for i in range(1, len(plane_split)):
plane = plane_split[i]
vec = (plane['nx'], plane['ny'], plane['nz'])
angle_diff = base_process.angle_between(vec, (0, 0, -1))
if angle_diff < 0.3 or True:
sel = data_gnd[np.nonzero(indices_split_gnd == i)]
if len(sel) < 3:
continue
pca = PCA(n_components=2)
data_transfer = pca.fit_transform(sel['a_position'])
tri = np.array(triangle.delaunay(data_transfer), dtype=np.uint32)
self.gnd_plane.append({'data': sel, 'tri': tri})
def crust(points: list, filename = None)-> list:
points = np.array(points)
ax = plt.axes()
drawing.plot_and_save(os.path.join(images_folder, filename+"_original.png"), False, ax, vertices=points, vertices_color="g")
lim = ax.axis()
vertices, edges, ray_origins, ray_directions = triangle.voronoi(points)
try:
drawing.plot_and_save(os.path.join(images_folder, os.path.join("voronoi", filename+"_voronoi.png")),
False, ax, vertices=vertices, edges=edges, ray_origins=ray_origins, ray_directions=ray_directions)
ax.axis(lim)
except Exception as e:
print("Could not draw voronoi diagram. Please, check if you have the correct directory")
extended_points = np.concatenate((points, vertices))
triangles = triangle.delaunay(extended_points)
delaunay_edges = []
for t in triangles:
delaunay_edges.extend(edges_from_triangle(t))
rec_edges = [e for e in delaunay_edges if ((e[0] < len(points)) and (e[1] < len(points)))]
try:
drawing.plot(ax, vertices=extended_points, edges=delaunay_edges, segments=rec_edges)
drawing.plot_and_save(os.path.join(images_folder, os.path.join("delaunay",filename+"delaunay.png")),
True, ax, vertices=points, vertices_color="b")
ax.axis(lim)
except Exception as e:
print("Could not draw delaunay diagram. Please, check if you have the correct directory")
#final reconstruction
ax = plt.axes()
drawing.plot_and_save(os.path.join(images_folder, filename+"_reconstruction.png"),
True, ax, vertices=points, segments=rec_edges, draw_vertices=False)
# print(points)
# print(rec_edges)
ordered_points = []
return ordered_points
def gen_ground_triangles(ground, origin, x, y):
faces = []
localGround = []
for p in ground:
localGround.append((np.dot(p - origin, x), np.dot(p - origin, y)))
tr = triangle.delaunay(localGround)
for t in tr:
s = [ground[t[0]], ground[t[1]], ground[t[2]]]
sp = Polygon(s)
sp = geometry.polygon.orient(sp, 1)
faces.append(sp)
# ground1 = [ground[0],ground[1],ground[2],ground[0]]
# ground2 =[ground[2],ground[3],ground[0],ground[2]]
# g1 = Polygon(ground1)
# g1 = geometry.polygon.orient(g1, 1)
# g2 = Polygon(ground2)
# g2 = geometry.polygon.orient(g2, 1)
# faces.append(g1)
# faces.append(g2)
return faces
def setup(POLYGON_COUNT=4096,
SCREEN_WIDTH=1152,
SCREEN_HEIGHT=900,
HUD_SIZE=32 * 9,
main_island_shape_seed=800,
small_island_shape_seed=300,
improve_points=False,
triangles=False):
OFFSETX = int(0.04 * SCREEN_WIDTH)
OFFSETY = int(0.05 * SCREEN_HEIGHT)
polygons = []
SECTION_SIZE = POLYGON_COUNT // 80
# this is for game use
display_size = (SCREEN_WIDTH + HUD_SIZE, SCREEN_HEIGHT)
# centre of the effective screen for map generation/display
centre = tuple(
map(int, ((SCREEN_WIDTH + 0.4 * OFFSETX) / 2,
(SCREEN_HEIGHT + 0.5 * OFFSETY) / 2)))
# euclidean distance from diagonal map corner with a slight offset
# larger max_dist will affect the size of the main island
max_dist = int((centre[0]**2 + centre[1]**2)**.5) - int(6.6 * OFFSETX)
# these are the polygon centres
generator_sites = []
for i in range(POLYGON_COUNT):
while True:
p = Point(random.randrange(-OFFSETX, SCREEN_WIDTH + OFFSETX),
random.randrange(-OFFSETY, SCREEN_HEIGHT + OFFSETY), i)
if not [i for i in generator_sites if i.x == p.x and i.y == p.y]:
break
generator_sites.append(p)
# delaunay triangles provide co-ordinates of polygon vertices
print("Generating delaunay triangles...")
tris = triangle.delaunay(
[poly_centre.get_cords() for poly_centre in generator_sites])
Triangles = [
Triangle(generator_sites[i[0]], generator_sites[i[1]],
generator_sites[i[2]]) for i in tris
]
# these are class based functions to retain a random seed. Useful for map generation
# look at the Island Class for more information
print("Generating island shapes...")
island_shape = Island(main_island_shape_seed)
smaller_island = Island(small_island_shape_seed)
# polygons are the polygon objects, poly_sites is a useful look-up dict
# for x,y co-ordinates matching a polygon
print("Generating polygons...")
if triangles:
polygons, poly_sites = __alt_polygon_generator(Triangles, centre,
max_dist, island_shape,
smaller_island)
else:
polygons, poly_sites = __polygon_generator(generator_sites, Triangles,
centre, max_dist,
island_shape,
smaller_island)
if improve_points:
generator_sites = []
print("Improving points...")
for counter, p in enumerate(polygons):
x, y = p.centroid()
generator_sites.append(Point(x, y, counter))
tris = triangle.delaunay(
[poly_centre.get_cords() for poly_centre in generator_sites])
Triangles = [
Triangle(generator_sites[i[0]], generator_sites[i[1]],
generator_sites[i[2]]) for i in tris
]
if triangles:
polygons, poly_sites = __alt_polygon_generator(
Triangles, centre, max_dist, island_shape, smaller_island)
else:
polygons, poly_sites = __polygon_generator(generator_sites,
Triangles, centre,
max_dist, island_shape,
smaller_island)
## this is arbitrary and can be changed however it appeared to work reasonably well
# I've tried higher and lower.
mount_count = POLYGON_COUNT // 200
# this is the main generator function and will determine most of the map terrain
# see relevant function for more details
print("Generating mountains, rivers and city locations...")
river_list, city_sites, regions = _determine_terrain(
mount_count, poly_sites, polygons, centre, max_dist)
print("Generating roads...")
road_list = _make_roads(city_sites)
print("")
print("Map created...")
print("Key data:")
print("mountains = ", mount_count)
print("rivers = ", len(river_list))
print("cities = ", len(city_sites))
print("roads = ", len(road_list))
# return data and render objects
return display_size, polygons, poly_sites, river_list, city_sites, road_list, regions
continue
texture_data = np.zeros(
(texture_len),
dtype=[('a_position', np.float32, 3),
('a_color', np.float32, 3)])
texture_data['a_color'] = np.array(texture_color)
texture_data['a_position'] = np.array(texture_xyz)
# pca = PCA(n_components=2)
# data_transfer = pca.fit_transform(texture_data['a_position'])
#data_transfer = texture_data['a_position'][:, 0:2]
#texture_tri = np.array(triangle.delaunay(data_transfer), dtype=np.uint32)
pca = PCA(n_components=2)
data_transfer = pca.fit_transform(
np.array(texture_xyz_3d))
tri = np.array(triangle.delaunay(data_transfer),
dtype=np.uint32)
texture_data['a_position'][:, 0] = texture_data[
'a_position'][:, 0] / 256.0 - 1.0
texture_data['a_position'][:, 1] = -(
texture_data['a_position'][:, 1] / 128.0 - 1.0)
programTexture = glumpy_setting.ProgramTexture(
data=texture_data, name='ProgramTexture', tri=tri)
programTexture_set.append(programTexture)
#break
print(rrr)
#scipy.misc.imshow(syn_pano)
if needVisual:
programSV3DRegion = glumpy_setting.ProgramSV3DRegion(
data = np.concatenate((data, sv3D.ptCLoudData), axis=0)
index += 1
if index > 0:
break
#break
gpyWindow = glumpy_setting.GpyWindow()
programSV3DRegion = glumpy_setting.ProgramSV3DRegion(
data=data, name=None, point_size=1, anchor_matrix=anchor_matrix_whole)
programSV3DRegion.apply_anchor()
#gpyWindow.add_program(programSV3DRegion)
data = programSV3DRegion.data
tri = np.array(triangle.delaunay(data['a_position'][:, 0:2]), dtype=np.uint32)
programGround = glumpy_setting.ProgramPlane(data=data,
name=str(index),
face=tri)
gpyWindow.add_program(programGround)
"""
ALL PLY EXPORT IN HERE
"""
data = programSV3DRegion.data
data['a_color'] *= 255
data['a_color'].astype(int)
xyzzz = np.zeros(len(data),
dtype=[('x', 'f4'), ('y', 'f4'), ('z', 'f4'), ('red', 'u1'),
('green', 'u1'), ('blue', 'u1')])
def triangulate_triangle(nodes, randstream):
import triangle
data = triangle.delaunay(nodes)
return data
d = triangle.delaunay(points)
diagram = get_persistence(points).get_diagram()
pyplot.figure(1)
pyplot.triplot([points[i][0] for i in range(len(points))],
[points[i][1] for i in range(len(points))], d)
pyplot.figure(2)
pyplot.scatter([diagram[i][0] for i in range(len(diagram))],
[diagram[i][1] for i in range(len(diagram))],
marker='o')
pyplot.show()
tim = []
for i in range(2):
points = generators.poisson.poisson_homogeneous_point_process(1, 5000)
d = triangle.delaunay(points)
pers = get_persistence(points)
#pyplot.figure(1)
pyplot.plot(
range(len(pers.numOfComponents)),
pers.numOfComponents,
'-b',
range(len(pers.numOfBigComponents)),
pers.numOfBigComponents,
'-r',
range(len(pers.numOfCycles)),
pers.numOfCycles,
'-g',
)
#pyplot.show()
b_1 = max(pers.numOfCycles)
def from_points(cls, x, y):
"""
Построение фильтрации Чеха по набору точек из R^2.
:param points:
:return:
"""
if len(x) != len(y):
raise RuntimeError('Длины x и y должны совпадать!')
f = Filtration()
f.vertNum = len(x)
# Индексирование вершин, рёбер и треугольников
f.vertices = [
triangulation.vert.Vert(idx, x[idx], y[idx])
for idx in range(f.vertNum)
]
f.incidEdgesToVertices = [[] for i in range(f.vertNum)]
f.incidTrianglesToVertices = [[] for i in range(f.vertNum)]
tr = triangle.delaunay(np.transpose([x, y]))
f.trNum = len(tr)
f.triangles = [
triangulation.triang.Triang(idx, tr[idx][0], tr[idx][1],
tr[idx][2]) for idx in range(f.trNum)
]
f.incidEdgesToTriangles = [[] for i in range(f.trNum)]
# Индексируем рёбра для быстрого поиска
edges_idx = dict()
idx = 0
# внешность не учитываем
for triIdx in range(f.trNum):
tr = f.triangles[triIdx]
if not edges_idx.get((tr.v(0), tr.v(1))):
f.edges.append(triangulation.edge.Edge(idx, tr.v(0), tr.v(1)))
edges_idx[(tr.v(0), tr.v(1))] = True
edges_idx[(tr.v(1), tr.v(0))] = True
idx += 1
if not edges_idx.get((tr.v(0), tr.v(2))):
f.edges.append(triangulation.edge.Edge(idx, tr.v(0), tr.v(2)))
edges_idx[(tr.v(0), tr.v(2))] = True
edges_idx[(tr.v(2), tr.v(0))] = True
idx += 1
if not edges_idx.get((tr.v(1), tr.v(2))):
f.edges.append(triangulation.edge.Edge(idx, tr.v(1), tr.v(2)))
edges_idx[(tr.v(1), tr.v(2))] = True
edges_idx[(tr.v(2), tr.v(1))] = True
idx += 1
f.edgeNum = len(f.edges)
f.incidTrianglesToEdges = [[] for i in range(f.edgeNum)]
# Инициализация списков инцидентных рёбер для вершин
# Пробегаем все ребра, каждое приписываем двум его вершинам.
# Результат: массив, индексы которого - глоальные номера точек,
# в i-ой ячейке - список индексов ребер, инцедентных i-ой вершине.
for idx in range(f.edgeNum):
v0 = f.edges[idx].v(0)
v1 = f.edges[idx].v(1)
f.incidEdgesToVertices[v0].append(idx)
f.incidEdgesToVertices[v1].append(idx)
# Инициализация списков инцидентных треугольников для вершин
# Пробегаем все треугольники, каждый записываем в 3 списка,
# соответствующих вершинам этого треугольника.
# Результат: массив, индексы которого - глоальные номера точек,
# в i-й ячейке - список индексов треугольников, содержащих i-ую вершину.
for idx in range(f.trNum):
f.incidTrianglesToVertices[f.triangles[idx].v(0)].append(idx)
f.incidTrianglesToVertices[f.triangles[idx].v(1)].append(idx)
f.incidTrianglesToVertices[f.triangles[idx].v(2)].append(idx)
# Инициализация списков инцидентных рёбер для треугольников
# Пробегаем все треугольники
for i in range(f.trNum):
# Количество ребер, инцидентных вершине A треугольника i.
iAEdgesCount = len(f.incidEdgesToVertices[f.triangles[i].v(0)])
# Для i-ого треугольника просматриваем список инцедентных ребер вершины A.
# Если текущее (j-ое) ребро равно ребру AB или AC i-ого треугольника,
# добавляем это ребро в список ребер, инцедентных i-ому треугольнику.
for j in range(iAEdgesCount):
# Глобальный индекс j-ого ребра инцидентного вершине A i-ого треугольника.
iAj = f.incidEdgesToVertices[f.triangles[i].v(0)][j]
if (f.edges[iAj].equals(f.triangles[i].v(0),
f.triangles[i].v(1))
or f.edges[iAj].equals(f.triangles[i].v(0),
f.triangles[i].v(2))):
f.incidEdgesToTriangles[i].append(iAj)
# Количество ребер, инцидентных вершине B треугольника i.
iBEdgesCount = len(f.incidEdgesToVertices[f.triangles[i].v(1)])
# Для i-ого треугольника просматриваем список инцедентных ребер вершины B.
# Если текущее (j-ое) ребро равно ребру BC i-ого треугольника,
# добавляем это ребро в список ребер, инцедентных i-ому треугольнику.
for j in range(iBEdgesCount):
# Глобальный индекс j-ого ребра инцидентного вершине B i-ого треугольника.
iBj = f.incidEdgesToVertices[f.triangles[i].v(1)][j]
if f.edges[iBj].equals(f.triangles[i].v(1),
f.triangles[i].v(2)):
f.incidEdgesToTriangles[i].append(iBj)
# Инициализация списка инцидентных треугольников для рёбер
# Пробегаем все треугольники, каждый записываем в 3 списка,
# соответствующих ребрам этого треугольника.
# Результат: массив, индексы которого - глобальные номера ребер,
# в i-ой ячейке - список индексов треугольников, инцедентных i-ому ребру.
for i in range(f.trNum):
f.incidTrianglesToEdges[f.incidEdgesToTriangles[i][0]].append(i)
f.incidTrianglesToEdges[f.incidEdgesToTriangles[i][1]].append(i)
f.incidTrianglesToEdges[f.incidEdgesToTriangles[i][2]].append(i)
# Инициализация списка граничных рёбер
for edge_idx in range(f.edgeNum):
if len(f.incidTrianglesToEdges[edge_idx]) == 1:
f.boardEdges.append(edge_idx)
# Инициализация списка граничных вершин
for edge_idx in f.boardEdges:
v0 = f.edges[edge_idx].v(0)
v1 = f.edges[edge_idx].v(1)
if v0 not in f.boardVertices:
f.boardVertices.append(v0)
if v1 not in f.boardVertices:
f.boardVertices.append(v1)
# Add outer face to the triangulation
outIdx = f.trNum
out = triangulation.triang.Out(outIdx, f.boardVertices)
f.triangles.append(out)
f.incidEdgesToTriangles.append(f.boardEdges)
for vert_idx in f.boardVertices:
f.incidTrianglesToVertices[vert_idx].append(outIdx)
for edge_idx in f.boardEdges:
f.incidTrianglesToEdges[edge_idx].append(outIdx)
f.trNum += 1 # учитываем внешность
f.simpNum = f.vertNum + f.edgeNum + f.trNum
# Добавление вершин, ребер, треугольников, внешности
for i in range(f.vertNum):
f.simplexes.append(f.vertices[i])
for i in range(f.edgeNum):
f.simplexes.append(f.edges[i])
for i in range(f.trNum):
f.simplexes.append(f.triangles[i])
# Инициализация времен появления
for s in f.simplexes:
if s.dim == 0:
s.appTime = 0
elif s.dim == 1:
length = triangulation.util.dist(f.vertices[s.v(0)],
f.vertices[s.v(1)])
s.appTime = length / 2
elif s.dim == 2:
len_a = triangulation.util.dist(f.vertices[s.v(0)],
f.vertices[s.v(1)])
len_b = triangulation.util.dist(f.vertices[s.v(0)],
f.vertices[s.v(2)])
len_c = triangulation.util.dist(f.vertices[s.v(1)],
f.vertices[s.v(2)])
if triangulation.util.is_obtuse(len_a, len_b, len_c):
s.appTime = max([len_a, len_b, len_c]) / 2
else:
s.appTime = triangulation.util.outer_radius(
f.vertices[s.v(0)], f.vertices[s.v(1)],
f.vertices[s.v(2)])
f.simplexes[-1].appTime = max(
[f.triangles[i].appTime for i in range(f.trNum - 1)]) + 1
# Сортировка списка симплексов по времени появления
f.sort_simplexes()
# Инициализация индексов фильтрации симплексов
for i in range(f.simpNum):
f.simplexes[i].filtInd = i
return f
if crossPhase:
if len(texture_xyz_3d_back_right) >= 3:
texture_data = np.zeros(
(texture_len_back_right),
dtype=[('a_position', np.float32, 3),
('a_color', np.float32, 3)])
texture_data['a_color'] = np.array(
texture_color_back_right)
texture_data['a_position'] = np.array(
texture_xyz_back_right)
pca = PCA(n_components=2)
data_transfer = pca.fit_transform(
np.array(texture_xyz_3d_back_right))
tri = np.array(
triangle.delaunay(data_transfer),
dtype=np.uint32)
texture_data[
'a_position'][:, 0] = texture_data[
'a_position'][:, 0] / float(
texture_height) - 1.0
texture_data['a_position'][:, 1] = -(
texture_data['a_position'][:, 1] /
float(texture_height) * 2.0 - 1.0)
programTexture = glumpy_setting.ProgramTexture(
data=texture_data,
name='ProgramTexture',
tri=tri)
programTexture_set.append(programTexture)
gpyWindow = glumpy_setting.GpyWindow()
#programSV3DRegion = glumpy_setting.ProgramSV3DRegion(data=data, name=None, point_size=1, anchor_matrix=anchor_matrix_whole)
#programSV3DRegion.apply_anchor()
#gpyWindow.add_program(programSV3DRegion)
programSV3DRegion = glumpy_setting.ProgramSV3DRegion(
data=data_gnd, name=None, point_size=1, anchor_matrix=anchor_matrix_whole)
programSV3DRegion.apply_anchor()
gpyWindow.add_program(programSV3DRegion)
#programSV3DRegion = glumpy_setting.ProgramSV3DRegion(data=data_gnd_grid, name=None, point_size=1, anchor_matrix=anchor_matrix_whole, alpha=0)
#programSV3DRegion.apply_anchor()
#gpyWindow.add_program(programSV3DRegion)
"""
Triangle
"""
tri = np.array(triangle.delaunay(data_gnd['a_position'][:, 0:2]),
dtype=np.uint32)
#data_gnd_grid['a_position'] = base_process.sv3d_apply_m4(data=data_gnd_grid['a_position'], m4=np.linalg.inv(anchor_matrix_whole))
#data_gnd['a_position'][:, 2] = 0
programGround = glumpy_setting.ProgramPlane(data=data_gnd,
name=str(index),
face=tri)
gpyWindow.add_program(programGround)
#programAxis = glumpy_setting.ProgramAxis(line_length=5)
#gpyWindow.add_program(programAxis)
gpyWindow.run()
def triangulate_triangle(nodes, randstream): import triangle data = triangle.delaunay(nodes) return data
import matplotlib.pyplot as plt import numpy as np import triangle as tr pts = np.array([[0, 0], [0, 1], [.5, .5], [1, 1], [1, 0]]) tri = tr.delaunay(pts) A = dict(vertices=pts) B = dict(vertices=pts, triangles=tri) tr.compare(plt, A, B) plt.show()
def main():
buildings_path = "by_get_shp/by_get" ##read points from datahandler
propertys_path = "ay_get_shp/ay_get"
las_path = "datafromndr/norrkoping.las"
#points = readPointsFromFile("PolygonPoints.txt") # read strykjarnet from file
#points = removeOutliers(points, mode='sor', max=2)
#points = [points]
data_handler = DataHandler(buildings_path, propertys_path, las_path)
bfps, points, solids, property_area, mbb, top_dogs = data_handler.get_slice_from_property(
1592
) #Djupet 1593 #Diket 1592 1375 1343 1588 taet data: 1015 843 tre nivaer: 1594
points = [points[i] for i in range(len(points)) if bfps[i].id in top_dogs]
points = [points[0]]
offset = np.mean(property_area.points, 0)
for p in points:
p[:, 0:2] -= offset
rg = SunRegionGrowing()
regions = rg.getMultiRegions(points)
planes = []
#fig = plt.figure()
#ax = fig.add_subplot(111)
f = open('myfile.csv', 'w')
cs_fe = CarlosSantosFeatureExtraction()
ax = a3.Axes3D(pl.figure())
for region in regions[0]: # project points to planes
planeq = getPlaneLSQ(points[0][region])
csr = cs_fe.extractFeature(points[0][region], planeq)
planes.append(planeq)
hull = np.array(csh.concaveHull(points[0][region][:, 0:2], 100))
#for p in hull:
# p += offset
hull0 = hull
hull = np.hstack((hull, hull[:, 0:1]))
hull = elevatePointsToPlane(hull, planeq)
for point in hull:
x, y, z = point
f.write(str(x) + ",")
f.write(str(y) + ",")
f.write(str(z) + "\n")
f.write("\n")
tri = a3.art3d.Poly3DCollection([hull])
vtx = sp.rand(4, 3)
#tri = a3.art3d.Poly3DCollection([vtx])
tri.set_color(colors.rgb2hex(sp.rand(3)))
tri.set_edgecolor('k')
#ax.add_collection3d(tri)
#gör tianglelist av 2d hullet -> använd sedan 3d hullet!
trianglelist = triangle.delaunay(hull0)
for tri_ids in trianglelist:
tri = a3.art3d.Poly3DCollection([hull[tri_ids]]) #3d hull
tri.set_color(colors.rgb2hex(sp.rand(3)))
tri.set_edgecolor('k')
ax.add_collection3d(tri)
for i in range(len(hull)):
p0 = hull[i]
p0down = np.array([p0[0], p0[1], 0])
next = i + 1
if next == len(hull):
next = 0
p1 = hull[next]
p1down = np.array([p1[0], p1[1], 0])
tri = a3.art3d.Poly3DCollection([[p0, p0down, p1down]])
tri.set_color('b')
tri.set_edgecolor('k')
ax.add_collection3d(tri)
tri = a3.art3d.Poly3DCollection([[p0, p1down, p1]])
tri.set_color('b')
tri.set_edgecolor('k')
ax.add_collection3d(tri)
x = 10
f.close()
ax.view_init(elev=39, azim=-55)
ax.set_xlim3d(-30, 30)
ax.set_ylim3d(-30, 30)
ax.set_zlim3d(0, 60)
pl.show()
data = np.concatenate((data, sv3D.ptCLoudData), axis=0)
index += 1
if index > 0:
break
#break
gpyWindow = glumpy_setting.GpyWindow()
programSV3DRegion = glumpy_setting.ProgramSV3DRegion(data=data, name=None, point_size=1, anchor_matrix=anchor_matrix_whole)
programSV3DRegion.apply_anchor()
#gpyWindow.add_program(programSV3DRegion)
data = programSV3DRegion.data
tri = np.array(triangle.delaunay(data['a_position'][:, 0:2]), dtype=np.uint32)
programGround = glumpy_setting.ProgramPlane(data=data, name=str(index), face=tri)
gpyWindow.add_program(programGround)
"""
ALL PLY EXPORT IN HERE
"""
data = programSV3DRegion.data
data['a_color'] *= 255
data['a_color'].astype(int)
xyzzz = np.zeros(len(data), dtype=[('x', 'f4'), ('y', 'f4'), ('z', 'f4'), ('red', 'u1'), ('green', 'u1'), ('blue', 'u1')])
xyzzz['x'] = data['a_position'][:, 0]
xyzzz['y'] = data['a_position'][:, 1]
xyzzz['z'] = data['a_position'][:, 2]
gm = geomap.GeoMap(points, [], Size2D(11, 11))
showMapStats(gm)
# import mapdisplay
# d = mapdisplay.MapDisplay(gm)
for i in range(1, len(points)):
assert gm.node(i).position() == points[i]
for node in gm.nodeIter():
if not node.degree():
gm.removeIsolatedNode(node) # check MapDisplay callbacks
import triangle
points, edgeData = triangle.delaunay(points[1:])
edgeTuples = [
startEnd and (
startEnd[0],
startEnd[1],
#([points[startEnd[0]], points[startEnd[1]]]))
geomap.Vector2Array([points[startEnd[0]], points[startEnd[1]]]))
for startEnd in edgeData
]
print "\n- creating Map from delaunay data (%d edges)..." % (len(edgeTuples) -
1, )
gm = geomap.GeoMap(points, edgeTuples, Size2D(11, 11))
showMapStats(gm)
def gen_vertical_walls(ground, origin, x, y):
faces = []
randomh = random.uniform(15.0, upperBound[2])
side1 = [
ground[0], ground[1],
(ground[0][0], ground[0][1], ground[0][2] + randomh),
(ground[1][0], ground[1][1], ground[1][2] + randomh)
]
localside11 = []
for p in side1:
localside11.append((np.dot(p - origin, x), np.dot(p - origin, y)))
tr = triangle.delaunay(localside11)
for t in tr:
s = [side1[t[0]], side1[t[1]], side1[t[2]]]
sp = Polygon(s)
sp = geometry.polygon.orient(sp, 1)
faces.append(sp)
side2 = [
ground[1], ground[2],
(ground[1][0], ground[1][1], ground[1][2] + randomh),
(ground[2][0], ground[2][1], ground[2][2] + randomh)
]
localside22 = []
for p in side2:
localside22.append((np.dot(p - origin, x), np.dot(p - origin, y)))
tr = triangle.delaunay(localside22)
for t in tr:
s = [side2[t[0]], side2[t[1]], side2[t[2]]]
sp = Polygon(s)
sp = geometry.polygon.orient(sp, 1)
faces.append(sp)
side3 = [
ground[2], ground[3],
(ground[2][0], ground[2][1], ground[2][2] + randomh),
(ground[3][0], ground[3][1], ground[3][2] + randomh)
]
localside33 = []
for p in side3:
localside33.append((np.dot(p - origin, x), np.dot(p - origin, y)))
tr = triangle.delaunay(localside33)
for t in tr:
s = [side3[t[0]], side3[t[1]], side3[t[2]]]
sp = Polygon(s)
sp = geometry.polygon.orient(sp, 1)
faces.append(sp)
side4 = [
ground[3], ground[0],
(ground[3][0], ground[3][1], ground[3][2] + randomh),
(ground[0][0], ground[0][1], ground[0][2] + randomh)
]
localside44 = []
for p in side4:
localside44.append((np.dot(p - origin, x), np.dot(p - origin, y)))
tr = triangle.delaunay(localside44)
for t in tr:
s = [side4[t[0]], side4[t[1]], side4[t[2]]]
sp = Polygon(s)
sp = geometry.polygon.orient(sp, 1)
faces.append(sp)
roof = [(ground[0][0], ground[0][1], ground[0][2] + randomh),
(ground[1][0], ground[1][1], ground[1][2] + randomh),
(ground[2][0], ground[2][1], ground[2][2] + randomh),
(ground[3][0], ground[3][1], ground[3][2] + randomh)]
localroof = []
for p in roof:
localroof.append((np.dot(p - origin, x), np.dot(p - origin, y)))
tr = triangle.delaunay(localroof)
for t in tr:
s = [roof[t[0]], roof[t[1]], roof[t[2]]]
sp = Polygon(s)
sp = geometry.polygon.orient(sp, 1)
faces.append(sp)
return faces
if needTexture:
if len(texture_xyz_3d) < 3:
rrr.append(plane_idx)
continue
texture_data = np.zeros((texture_len),
dtype=[('a_position', np.float32, 3), ('a_color', np.float32, 3)])
texture_data['a_color'] = np.array(texture_color)
texture_data['a_position'] = np.array(texture_xyz)
# pca = PCA(n_components=2)
# data_transfer = pca.fit_transform(texture_data['a_position'])
#data_transfer = texture_data['a_position'][:, 0:2]
#texture_tri = np.array(triangle.delaunay(data_transfer), dtype=np.uint32)
pca = PCA(n_components=2)
data_transfer = pca.fit_transform(np.array(texture_xyz_3d))
tri = np.array(triangle.delaunay(data_transfer), dtype=np.uint32)
texture_data['a_position'][:, 0] = texture_data['a_position'][:, 0] / 256.0 - 1.0
texture_data['a_position'][:, 1] = -(texture_data['a_position'][:, 1] / 128.0 - 1.0)
programTexture = glumpy_setting.ProgramTexture(data=texture_data, name='ProgramTexture', tri=tri)
programTexture_set.append(programTexture)
#break
#scipy.misc.imshow(syn_pano)
if needVisual:
if needPerspective:
ori_pano = sv3D.panorama / 255.0
pano_height, pano_width = ori_pano.shape[0], ori_pano.shape[1] # Actually, this must be 1:2
perspective_height, perspective_width = int(pano_height / 4), int(pano_width / 4)
perspective_data = np.zeros((pano_height*pano_width),
dtype=[('a_position', np.float32, 3), ('a_color', np.float32, 3)])
programSV3D.info_3d_offs()
sv3D.matrix_offs = programSV3D.u_model
#gpyWindow.add_program(programSV3D)
vec3 = np.reshape(sv3D.ptCLoudData['a_position'], (256 * 512, 3))
vec4 = np.hstack([vec3, np.ones((len(vec3), 1))])
vec4_mul = np.dot(vec4, sv3D.matrix_offs)
vec4_out = np.reshape(vec4_mul[:, 0:3], (256, 512, 3))
#groundPoint_cur = (sv3D.ptCLoudData[vec4_out[:, :, 2] < -2])
groundPoint_cur['a_position'] = (vec4_out[(sv3D.ptCLoudData['a_position'][:, :, 2] > 2) * (sv3D.ptCLoudData['a_position'][:, :, 0] > 0)])
if index == 0:
matrix_offs_whole = sv3D.matrix_offs
groundPoint = groundPoint_cur
else:
groundPoint = np.concatenate((groundPoint, groundPoint_cur), axis=0)
index += 1
tri = np.array(triangle.delaunay(groundPoint['a_position'][:, 0:2]), dtype=np.uint32)
programGround = glumpy_setting.ProgramPlane(data=groundPoint, name=str(index), face=tri)
#programGround.u_model = matrix_offs_whole
gpyWindow.add_program(programGround)
programAxis = glumpy_setting.ProgramAxis(line_length=5)
gpyWindow.add_program(programAxis)
gpyWindow.run()
img_x = int(lng / 360.0 * 512.0)
img_y = int(-(lat - 90) / 180.0 * 256.0)
syn_pano[img_y, img_x, :] = point['a_color']
index_pano[img_y, img_x] = True
yo_xyz.append([img_x, img_y, 0])
yo_color.append(point['a_color'])
yo_len += 1
show_pano = np.concatenate((ori_pano, syn_pano), axis=1)
#scipy.misc.imsave('yo.png', syn_pano)
scipy.misc.imshow(show_pano)
data = np.zeros((yo_len),
dtype=[('a_position', np.float32, 3),
('a_color', np.float32, 3)])
data['a_color'] = np.array(yo_color)
data['a_position'] = np.array(yo_xyz)
pca = PCA(n_components=2)
data_transfer = pca.fit_transform(data['a_position'])
tri = np.array(triangle.delaunay(data_transfer), dtype=np.uint32)
programImage = glumpy_setting.ProgramPlane(data=data,
name='test',
face=tri)
data['a_position'][:, 0] = data['a_position'][:, 0] / 256.0 - 1.0
data['a_position'][:, 1] = data['a_position'][:, 1] / 128.0 - 1.0
gpyViewWindow = glumpy_setting.GpyViewWindow(data, tri)
gpyViewWindow.run()
gm = geomap.GeoMap(points, [], Size2D(11, 11))
showMapStats(gm)
# import mapdisplay
# d = mapdisplay.MapDisplay(gm)
for i in range(1, len(points)):
assert gm.node(i).position() == points[i]
for node in gm.nodeIter():
if not node.degree():
gm.removeIsolatedNode(node) # check MapDisplay callbacks
import triangle
points, edgeData = triangle.delaunay(points[1:])
edgeTuples = [startEnd and
(startEnd[0], startEnd[1],
#([points[startEnd[0]], points[startEnd[1]]]))
geomap.Vector2Array([points[startEnd[0]], points[startEnd[1]]]))
for startEnd in edgeData]
print "\n- creating Map from delaunay data (%d edges)..." % (len(edgeTuples)-1, )
gm = geomap.GeoMap(points, edgeTuples, Size2D(11, 11))
showMapStats(gm)
# addPathFromHere("../subpixelWatersheds")
# import mapdisplay
# d = mapdisplay.MapDisplay(gm)
