def test_draco_two_layers():
n_points = 12
img = sphere_tissue_image(size=100, n_points=n_points)
draco = DracoMesh(img)
draco.construct_adjacency_complex()
triangular = ['star', 'remeshed', 'projected', 'regular', 'flat']
image_dual_topomesh = draco.dual_reconstruction(
reconstruction_triangulation=triangular, adjacency_complex_degree=3)
def test_draco():
n_points = 12
img = sphere_tissue_image(size=100, n_points=n_points)
draco = DracoMesh(img)
assert draco.point_topomesh.nb_wisps(0) == n_points + 1
draco.delaunay_adjacency_complex(surface_cleaning_criteria=[])
image_tetrahedra = np.sort(draco.image_cell_vertex.keys())
image_tetrahedra = image_tetrahedra[image_tetrahedra[:, 0] != 1]
draco_tetrahedra = np.sort([
list(draco.triangulation_topomesh.borders(3, t, 3))
for t in draco.triangulation_topomesh.wisps(3)
])
delaunay_consistency = jaccard_index(image_tetrahedra, draco_tetrahedra)
draco.adjacency_complex_optimization(n_iterations=2)
assert draco.triangulation_topomesh.nb_region_neighbors(0, 2) == n_points
image_tetrahedra = np.sort(draco.image_cell_vertex.keys())
image_tetrahedra = image_tetrahedra[image_tetrahedra[:, 0] != 1]
draco_tetrahedra = np.sort([
list(draco.triangulation_topomesh.borders(3, t, 3))
for t in draco.triangulation_topomesh.wisps(3)
])
draco_consistency = jaccard_index(image_tetrahedra, draco_tetrahedra)
# print delaunay_consistency,' -> ',draco_consistency
assert draco_consistency == 1 or (draco_consistency >= 0.9 and
draco_consistency > delaunay_consistency)
triangular = ['star', 'remeshed', 'projected', 'regular', 'flat']
image_dual_topomesh = draco.dual_reconstruction(
reconstruction_triangulation=triangular, adjacency_complex_degree=3)
image_volumes = array_dict(
nd.sum(np.ones_like(img), img, index=np.unique(img)[1:]) *
np.prod(img.voxelsize),
np.unique(img)[1:])
compute_topomesh_property(image_dual_topomesh, 'volume', 3)
draco_volumes = image_dual_topomesh.wisp_property('volume', 3)
for c in image_dual_topomesh.wisps(3):
assert np.isclose(image_volumes[c], draco_volumes[c], 0.33)
def test_draco():
n_points = 12
img = sphere_tissue_image(size=100,n_points=n_points)
draco = DracoMesh(img)
assert draco.point_topomesh.nb_wisps(0) == n_points+1
draco.delaunay_adjacency_complex(surface_cleaning_criteria = [])
image_tetrahedra = np.sort(draco.image_cell_vertex.keys())
image_tetrahedra = image_tetrahedra[image_tetrahedra[:,0] != 1]
draco_tetrahedra = np.sort([list(draco.triangulation_topomesh.borders(3,t,3)) for t in draco.triangulation_topomesh.wisps(3)])
delaunay_consistency = jaccard_index(image_tetrahedra, draco_tetrahedra)
draco.adjacency_complex_optimization(n_iterations=2)
assert draco.triangulation_topomesh.nb_region_neighbors(0,2) == n_points
image_tetrahedra = np.sort(draco.image_cell_vertex.keys())
image_tetrahedra = image_tetrahedra[image_tetrahedra[:,0] != 1]
draco_tetrahedra = np.sort([list(draco.triangulation_topomesh.borders(3,t,3)) for t in draco.triangulation_topomesh.wisps(3)])
draco_consistency = jaccard_index(image_tetrahedra, draco_tetrahedra)
# print delaunay_consistency,' -> ',draco_consistency
assert draco_consistency == 1 or (draco_consistency >= 0.9 and draco_consistency > delaunay_consistency)
triangular = ['star','remeshed','projected','regular','flat']
image_dual_topomesh = draco.dual_reconstruction(reconstruction_triangulation = triangular, adjacency_complex_degree=3)
image_volumes = array_dict(nd.sum(np.ones_like(img),img,index=np.unique(img)[1:])*np.prod(img.resolution),np.unique(img)[1:])
compute_topomesh_property(image_dual_topomesh,'volume',3)
draco_volumes = image_dual_topomesh.wisp_property('volume',3)
for c in image_dual_topomesh.wisps(3):
assert np.isclose(image_volumes[c],draco_volumes[c],0.33)
from openalea.draco_stem.draco.draco import DracoMesh from openalea.draco_stem.example_image import sphere_tissue_image from openalea.oalab.colormap.colormap_def import load_colormaps world.clear() size = 100. n_points = 11 n_layers = 2 img = sphere_tissue_image(size=size, n_points=n_points, n_layers=n_layers) world.add(img,"segmented_image",colormap='glasbey',alphamap='constant',bg_id=1,alpha=0.25) draco = DracoMesh(image=img) draco.delaunay_adjacency_complex(surface_cleaning_criteria=[]) world.add(draco.triangulation_topomesh,'adjacency_complex') world['adjacency_complex']['display_3'] = False world['adjacency_complex']['display_0'] = True world['adjacency_complex_vertices']['display_colorbar'] = False world['adjacency_complex_vertices']['polydata_colormap'] = load_colormaps()['glasbey'] world['adjacency_complex_vertices']['point_radius'] = 1.5 draco.adjacency_complex_optimization(n_iterations=3) world['adjacency_complex']['coef_3'] = 0.9 world['adjacency_complex']['display_3'] = True world['adjacency_complex_cells']['display_colorbar'] = False world['adjacency_complex_cells']['polydata_colormap'] = load_colormaps()['grey']
img = imread(inputfile)
#img[img==0]=1
#img = SpatialImage(np.concatenate([img[:,:,35:],np.ones((img.shape[0],img.shape[1],5))],axis=2).astype(np.uint16),resolution=img.resolution)
cell_vertex_file = dirname+"/output_meshes/"+filename+"/image_cell_vertex.dict"
triangulation_file = dirname+"/output_meshes/"+filename+"/"+filename+"_draco_adjacency_complex.pkl"
from openalea.container import array_dict
world.add(img,"segmented_image",colormap='glasbey',alphamap='constant',bg_id=1,alpha=1.0)
#draco = DracoMesh(image=img, image_cell_vertex_file=cell_vertex_file, triangulation_file=triangulation_file)
#draco = DracoMesh(image_file=inputfile, image_cell_vertex_file=cell_vertex_file)
draco = DracoMesh(image=img)
#world.add(draco.segmented_image-(draco.segmented_image==1),'segmented_image',colormap='glasbey',alphamap='constant',bg_id=0)
world.add(draco.point_topomesh,'image_cells')
world['image_cells_vertices'].set_attribute('point_radius',img.max())
world.add(draco.layer_edge_topomesh['L1'],'L1_adjacency')
#world.add(draco.image_cell_vertex_topomesh,'image_cell_vertex')
draco.delaunay_adjacency_complex(surface_cleaning_criteria = [])
#draco.delaunay_adjacency_complex(surface_cleaning_criteria = ['surface','sliver','distance'])
draco.adjacency_complex_optimization(n_iterations=2)
from copy import deepcopy
triangulation_topomesh = deepcopy(draco.triangulation_topomesh)
world.add(triangulation_topomesh,'cell_adjacency_complex')
alphamap='constant',
bg_id=1,
alpha=1.0)
#from openalea.cgal_meshing.idra import IdraMesh
#topomesh = IdraMesh(img,mesh_fineness=1.0).idra_topomesh()
#world.add(topomesh,'IDRA_mesh')
#idra_file = dirname+"/output_meshes/"+filename+"/"+filename+"_IDRA_mesh.ply"
#save_ply_property_topomesh(topomesh,idra_file,color_faces=True,colormap=load_colormaps()['glasbey'])
#from openalea.draco_stem.stem.tissue_mesh_optimization import optimize_topomesh
#draco = DracoMesh(image=img, image_cell_vertex_file=cell_vertex_file, triangulation_file=triangulation_file)
draco = DracoMesh(image_file=inputfile,
image_cell_vertex_file=cell_vertex_file,
triangulation_file=triangulation_file)
#draco = DracoMesh(image=img)
image_cell_vertex = draco.image_cell_vertex
#optimized_topomesh = optimize_topomesh(topomesh,omega_forces={'regularization':0.00,'neighborhood':0.0,'laplacian':1.0,'planarization':0.27,'epidermis_planarization':0.07,'convexity':0.02},omega_regularization_max=0.01,edge_flip=True,cell_vertex_motion=True,image_cell_vertex=image_cell_vertex)
#optimized_topomesh = optimize_topomesh(optimized_topomesh,omega_forces={'taubin_smoothing':0.65},cell_vertex_motion=True,image_cell_vertex=image_cell_vertex)
#world.add(optimized_topomesh,'IDRA_STEM_mesh')
#idra_stem_file = dirname+"/output_meshes/"+filename+"/"+filename+"_IDRA_STEM_mesh.ply"
#save_ply_property_topomesh(optimized_topomesh,idra_stem_file,color_faces=True,colormap=load_colormaps()['glasbey'])
#world.add(draco.segmented_image-(draco.segmented_image==1),'segmented_image',colormap='glasbey',alphamap='constant',bg_id=0)
#world.add(draco.point_topomesh,'image_cells')
#world['image_cells_vertices'].set_attribute('point_radius',img.max())
#world.add(draco.layer_edge_topomesh['L1'],'L1_adjacency')
