def test_graph_from_image(visual=False):
im = imread("segmentation.inr.gz")
graph = graph_from_image(im)
if visual:
Viewer.display(
graph2pglscene(graph, graph.vertex_property('barycenter'),
graph.vertex_property('L1')))
def test_graph_from_simple_image(visual=False):
im = np.array([[1, 2, 7, 7, 1, 1], [1, 6, 5, 7, 3, 3], [2, 2, 1, 7, 3, 3],
[1, 1, 1, 4, 1, 1]])
borders = SpatialImageAnalysis(im).cells_in_image_margins()
print '**', SpatialImageAnalysis(im).boundingbox(real=False)
#~ print borders
#~ print np.unique(im)
graph = graph_from_image(im)
#~ print list(graph.vertices())
#~ print map(graph.edge_vertices,graph.edges())
#~ print list(graph.vertex_property_names())
#~ print list(graph.edge_property_names())
for propname in graph.vertex_property_names():
print propname
print graph.vertex_property(propname)
#~ for propname in graph.edge_property_names():
#~ print propname
#~ print [(i,graph.edge_vertices(i),j) for i,j in graph.edge_property(propname).iteritems()]
if visual:
Viewer.display(
graph2pglscene(graph, graph.vertex_property('barycenter'),
graph.vertex_property('border')))
def test_graph_from_simple_image(visual = False):
im = np.array([[1, 2, 7, 7, 1, 1],
[1, 6, 5, 7, 3, 3],
[2, 2, 1, 7, 3, 3],
[1, 1, 1, 4, 1, 1]])
borders = SpatialImageAnalysis(im).cells_in_image_margins()
print '**', SpatialImageAnalysis(im).boundingbox(real=False)
#~ print borders
#~ print np.unique(im)
graph = graph_from_image(im)
#~ print list(graph.vertices())
#~ print map(graph.edge_vertices,graph.edges())
#~ print list(graph.vertex_property_names())
#~ print list(graph.edge_property_names())
for propname in graph.vertex_property_names():
print propname
print graph.vertex_property(propname)
#~ for propname in graph.edge_property_names():
#~ print propname
#~ print [(i,graph.edge_vertices(i),j) for i,j in graph.edge_property(propname).iteritems()]
if visual :
Viewer.display(graph2pglscene(graph,graph.vertex_property('barycenter'),graph.vertex_property('border')))
def link_polydata_triangle_cells(polydata,img,img_graph=None):
if img_graph is None:
from openalea.image.algo.graph_from_image import graph_from_image
img_graph = graph_from_image(img,spatio_temporal_properties=['barycenter','volume'],ignore_cells_at_stack_margins = False,property_as_real=True)
polydata_cell_data = polydata.GetCellData().GetArray(0)
start_time = time()
print " --> Listing points"
polydata_points = np.array([polydata.GetPoints().GetPoint(i) for i in xrange(polydata.GetPoints().GetNumberOfPoints())])
end_time = time()
print " <-- Listing points [",end_time - start_time,"s]"
start_time = time()
print " --> Merging points"
point_ids = {}
for p in xrange(polydata.GetPoints().GetNumberOfPoints()):
point_ids[tuple(polydata_points[p])] = []
for p in xrange(polydata.GetPoints().GetNumberOfPoints()):
point_ids[tuple(polydata_points[p])] += [p]
unique_points = array_unique(polydata_points)
n_points = unique_points.shape[0]
point_unique_id = {}
for p in xrange(n_points):
for i in point_ids[tuple(unique_points[p])]:
point_unique_id[i] = p
end_time = time()
print " <-- Merging points [",end_time - start_time,"s]"
triangle_cell_start_time = time()
print " --> Listing triangles"
print " - ",polydata.GetNumberOfCells()," triangles"
polydata_triangles = np.sort([[polydata.GetCell(t).GetPointIds().GetId(i) for i in xrange(3)] for t in xrange(polydata.GetNumberOfCells())])
print " - ",array_unique(polydata_triangles).shape[0]," unique triangles"
# polydata_triangle_points = [polydata.GetCell(t).GetPointIds() for t in xrange(polydata.GetNumberOfCells())]
# polydata_triangles = np.sort([[triangle_points.GetId(i) for i in xrange(3)] for triangle_points in polydata_triangle_points])
polydata_triangles = np.sort(array_dict(point_unique_id).values(polydata_triangles))
print " - ",array_unique(polydata_triangles).shape[0]," unique triangles (merged vertices)"
triangle_cell_end_time = time()
print " <-- Listing triangles [",triangle_cell_end_time - triangle_cell_start_time,"s]"
raw_input()
triangle_cell_start_time = time()
print " --> Initializing triangle cells"
triangle_cells = {}
for t in xrange(polydata.GetNumberOfCells()):
triangle_cells[tuple(polydata_triangles[t])] = []
for i in xrange(10):
if t == (i*polydata.GetNumberOfCells())/10:
print " --> Initializing triangle cells (",10*i,"%)"
triangle_cell_end_time = time()
print " <-- Initializing triangle cells [",triangle_cell_end_time - triangle_cell_start_time,"s]"
triangle_cell_start_time = time()
for t in xrange(polydata.GetNumberOfCells()):
triangle_cells[tuple(polydata_triangles[t])] += list(polydata_cell_data.GetTuple(t))
for i in xrange(100):
if t == (i*polydata.GetNumberOfCells())/100:
triangle_cell_end_time = time()
print " --> Listing triangle cells (",i,"%) [",(triangle_cell_end_time-triangle_cell_start_time)/(polydata.GetNumberOfCells()/100.),"s]"
triangle_cell_start_time = time()
triangle_cell_start_time = time()
print " --> Cleaning triangle cells"
for t in xrange(polydata.GetNumberOfCells()):
triangle_cells[tuple(polydata_triangles[t])] = np.unique(triangle_cells[tuple(polydata_triangles[t])])
for i in xrange(10):
if t == (i*polydata.GetNumberOfCells())/10:
print " --> Cleaning triangle cells (",10*i,"%)"
triangle_cell_end_time = time()
print " <-- Cleaning triangle cells [",triangle_cell_end_time - triangle_cell_start_time,"s]"
# triangle_cell_start_time = time()
# print " --> Listing triangle cells"
# triangle_cell = np.array([polydata_cell_data.GetTuple(t)[0] for t in xrange(polydata.GetNumberOfCells())],np.uint16)
# triangle_cell_end_time = time()
# print " <-- Listing triangle cells [",triangle_cell_end_time - triangle_cell_start_time,"s]"
# triangle_cells = {}
# for t in xrange(polydata.GetNumberOfCells()):
# triangle_cells[t] = []
# for c in considered_cells:
# cell_triangles = np.where(triangle_cell == c)[0]
# for t in cell_triangles:
# triangle_cells[t] += [c]
# print " Cell ",c," : ",cell_triangles.shape[0]," triangles"
# neighbor_triangles = where_list(triangle_cell,list(img_graph.neighbors(c)))[0]
# neighbor_triangle_matching = vq(polydata_triangles[cell_triangles],polydata_triangles[neighbor_triangles])
# cell_double_triangles = neighbor_triangles[neighbor_triangle_matching[0][np.where(neighbor_triangle_matching[1]==0)[0]]]
# for t in cell_double_triangles:
# triangle_cells[t] += [c]
# print triangle_cells.values()
# raw_input()
# unique_triangles,unique_triangle_rows = array_unique(polydata_triangles,return_index=True)
# n_triangles = unique_triangles.shape[0]
# triangle_unique = array_dict(np.arange(n_triangles),unique_triangle_rows)
# triangle_id = (polydata_triangles * np.array([contour.GetOutput().GetPoints().GetNumberOfPoints(),1,1./contour.GetOutput().GetPoints().GetNumberOfPoints()])).sum(axis=1)
# unique_triangle_id = (unique_triangles * np.array([contour.GetOutput().GetPoints().GetNumberOfPoints(),1,1./contour.GetOutput().GetPoints().GetNumberOfPoints()])).sum(axis=1)
# triangle_number = nd.sum(np.ones_like(triangle_id),triangle_id,index=triangle_id)
# double_triangle_rows = np.where(triangle_number==2)[0]
# print " ",double_triangle_rows.shape[0]," double triangles / ",contour.GetOutput().GetNumberOfCells()
# double_triangles = polydata_triangles[double_triangle_rows]
# unique_triangle_number = nd.sum(np.ones_like(triangle_id),triangle_id,index=unique_triangle_id)
# double_unique_triangle_rows = np.where(unique_triangle_number==2)[0]
# double_unique_triangles = unique_triangles[double_unique_triangle_rows]
# triangle_triangle_matching = (vq(double_triangles,double_unique_triangles)[0])
# triangle_triangle_matching = array_dict(double_unique_triangle_rows[triangle_triangle_matching],double_triangle_rows)
# unique_triangle_cells = {}
# for t in xrange(n_triangles):
# unique_triangle_cells[t] = []
# for t in xrange(polydata.GetNumberOfCells()):
# if triangle_number[t] == 1:
# unique_triangle_cells[triangle_unique[t]] += list(polydata_cell_data.GetTuple(t))
# elif triangle_number[t] == 2:
# unique_triangle_cells[triangle_triangle_matching[t]] += list(polydata_cell_data.GetTuple(t))
# triangle_cells = {}
# for t in xrange(polydata.GetNumberOfCells()):
# if triangle_number[t] == 1:
# triangle_cells[t] = np.array(unique_triangle_cells[triangle_unique[t]],np.uint16)
# elif triangle_number[t] == 2:
# triangle_cells[t] = np.array(unique_triangle_cells[triangle_triangle_matching[t]],np.uint16)
cell_data = vtk.vtkFloatArray()
cell_data.SetNumberOfComponents(2)
cell_data.SetNumberOfTuples(polydata.GetNumberOfCells())
for t in xrange(polydata.GetNumberOfCells()):
triangle_key = tuple(polydata_triangles[t])
if len(triangle_cells[triangle_key]) == 2:
cell_data.SetTuple(t,np.sort(triangle_cells[triangle_key]))
else:
cell_data.SetTuple(t,np.concatenate([triangle_cells[triangle_key],[1]]))
polydata.GetCellData().SetScalars(cell_data)
return triangle_cells
def test_graph_from_image(visual = False):
im = imread("segmentation.inr.gz")
graph = graph_from_image(im)
if visual :
Viewer.display(graph2pglscene(graph,graph.vertex_property('barycenter'),graph.vertex_property('L1')))