def extraction_algorithm(fine_data, resolutions, dimensions):
print "### Dual Contouring ###"
[verts_out_dc, quads_out_dc, manifolds, datasets] = tworesolution_dual_contour(fine_data, resolutions, dimensions)
print "### Dual Contouring DONE ###"
N_quads = {'coarse': quads_out_dc['coarse'].__len__(), 'fine': quads_out_dc['fine'].__len__()}
N_verts = {'coarse': verts_out_dc['coarse'].__len__(), 'fine': verts_out_dc['fine'].__len__()}
quads = {'coarse': [None] * N_quads['coarse'], 'fine': quads_out_dc['fine']}
verts = {'coarse': verts_out_dc['coarse'], 'fine': verts_out_dc['fine']} # todo substitute with vertex objects
for i in range(N_quads['coarse']):
quads['coarse'][i]=Quad(i,quads_out_dc['coarse'],verts_out_dc['coarse'])
assert quads['coarse'].__len__() > 0
print "### Projecting Datapoints onto coarse quads ###"
# do projection of fine verts on coarse quads
param = create_parameters(verts, quads)
export_results.export_as_csv(param,'param')
print "### Projecting Datapoints onto coarse quads DONE ###"
return verts_out_dc, quads_out_dc, quads, param, datasets
def tworesolution_dual_contour(data, resolutions, dims):
# fine_dataset = VoxelDataset.from_filename('GE_white_big.vtk') # use for GE bracket
fine_dataset = VoxelDataset(dims, resolutions['fine'], data) # use for topy files
print "++ Aligning Dataset ++"
fine_dataset.align()
fine_dataset.surround()
pre_coarsening_steps = 0
if pre_coarsening_steps > 0:
print "PRESMOOTHING OF DATASET APPLIED!"
print "++ Precoarsening of dataset ++"
print "coarsening steps: %d" % (pre_coarsening_steps)
fine_dataset = coarsen_dataset(pre_coarsening_steps, fine_dataset)
print "++ Fine Resolution DC ++"
print "resolution: %d" % (fine_dataset._resolution)
[dc_verts_fine, dc_quads_fine, dc_manifold_edges_fine, not_resolved_edges_fine] = dual_contour(fine_dataset,
resolutions['fine'],
is_coarse_level=False,
do_manifold_treatment=False)
# compute necessary coarsening steps from given coarse resolution.
print "fine quads produced: %d" % (dc_quads_fine.__len__())
coarsening_steps = int(np.log(resolutions['coarse']) / np.log(2)) - pre_coarsening_steps
if coarsening_steps > 0:
print "++ Coarsening Dataset ++"
assert type(coarsening_steps) is int # coarsening steps have to be integer!
coarse_dataset = coarsen_dataset(coarsening_steps, fine_dataset)
else:
coarse_dataset = fine_dataset
print "++ Coarse Resolution DC ++"
print "resolution: %d" % (coarse_dataset._resolution)
[dc_verts_coarse, dc_quads_coarse, dc_manifold_edges_coarse, not_resolved_edges_coarse] = dual_contour(
coarse_dataset,
resolutions['fine'],
is_coarse_level=True,
do_manifold_treatment=True)
print "coarse quads produced: %d" % (dc_quads_coarse.__len__())
dc_verts = {'fine': dc_verts_fine, 'coarse': dc_verts_coarse}
dc_quads = {'fine': dc_quads_fine, 'coarse': dc_quads_coarse}
dc_manifolds = {'fine': dc_manifold_edges_fine, 'coarse': dc_manifold_edges_coarse}
print "checking for remaining non-manifold edges on coarse level:"
nonmanifold = []
edge_usage = generate_edge_usage_dict(dc_quads_coarse)
for edge_identifier, used_by_quads in edge_usage.items():
if used_by_quads.__len__() != 2:
nonmanifold.append(np.array(edge_identifier))
try:
assert nonmanifold.__len__() == 0 and not_resolved_edges_coarse.__len__() == 0
except AssertionError as e:
import traceback, os.path
top = traceback.extract_stack()[-1]
print '\n'
print ', '.join([os.path.basename(top[0]), str(top[1])])
print "ERROR found. exporting intermediate results."
export_results.export_as_csv(dc_verts_fine, './PYTHON/NURBSReconstruction/DualContouring/plotting/dc_verts_fine')
export_results.export_as_csv(dc_quads_fine, './PYTHON/NURBSReconstruction/DualContouring/plotting/dc_quads_fine')
export_results.export_as_csv(dc_verts_coarse, './PYTHON/NURBSReconstruction/DualContouring/plotting/dc_verts_coarse')
export_results.export_as_csv(dc_quads_coarse, './PYTHON/NURBSReconstruction/DualContouring/plotting/dc_quads_coarse')
export_results.export_as_csv(np.array(nonmanifold), './PYTHON/NURBSReconstruction/DualContouring/plotting/dc_non_manifold_edges')
export_results.export_as_csv([coarse_dataset._dimensions['min'], coarse_dataset._dimensions['max']],
'./PYTHON/NURBSReconstruction/DualContouring/plotting/dc_dimensions')
print "dc_non_manifold_edges references all the vertices connected by a non-manifold edge."
print PColors.FAIL + "ERROR: Not all manifold edges have been successfully resolved! Aborting." + PColors.ENDC
quit()
datasets = {'fine': fine_dataset, 'coarse': coarse_dataset}
return dc_verts, dc_quads, dc_manifolds, datasets