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# Copyright CNRS/Inria/UNS
# Contributor(s): Eric Debreuve (since 2018)
#
# eric.debreuve@cnrs.fr
#
# This software is governed by the CeCILL license under French law and
# abiding by the rules of distribution of free software. You can use,
# modify and/ or redistribute the software under the terms of the CeCILL
# license as circulated by CEA, CNRS and INRIA at the following URL
# "http://www.cecill.info".
#
# As a counterpart to the access to the source code and rights to copy,
# modify and redistribute granted by the license, users are provided only
# with a limited warranty and the software's author, the holder of the
# economic rights, and the successive licensors have only limited
# liability.
#
# In this respect, the user's attention is drawn to the risks associated
# with loading, using, modifying and/or developing or reproducing the
# software by the user in light of its specific status of free software,
# that may mean that it is complicated to manipulate, and that also
# therefore means that it is reserved for developers and experienced
# professionals having in-depth computer knowledge. Users are therefore
# encouraged to load and test the software's suitability as regards their
# requirements in conditions enabling the security of their systems and/or
# data to be ensured and, more generally, to use and operate it in the
# same conditions as regards security.
#
# The fact that you are presently reading this means that you have had
# knowledge of the CeCILL license and that you accept its terms.
import sklgraph.brick.edge as dg_
import sklgraph.brick.node as nd_
import sklgraph.skl_map as sm_
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from typing import List, Tuple
import numpy as np_
array_t = np_.ndarray
def AssignNodeIDsToEdges(
e_nodes: List[nd_.end_node_t],
e_node_lmap: array_t,
b_nodes: List[nd_.branch_node_t],
b_node_lmap: array_t,
edges: List[dg_.edge_t],
edge_lmap: array_t,
) -> None:
#
# Not uint to allow for subtraction
edge_parts = sm_.SkeletonPartMap(
(edge_lmap > 0).astype(np_.int8), check_validity=None
)
# ep=edge end point; Leave < 2 since ==0 (length-1 edges) and ==1 (other edges) are needed
for ep_coords in zip(*(edge_parts < 2).nonzero()):
edge_label = edge_lmap[ep_coords]
edge = edges[edge_label - 1]
e_node_label = e_node_lmap[ep_coords]
if e_node_label > 0:
# End node-to-X edge (i.e., edge end point is also an end node)
_AppendNodeIDToEdge(
edge,
np_.zeros(ep_coords.__len__(), dtype=np_.int64),
e_nodes[e_node_label - 1],
)
if edge.sites[0].__len__() == 1:
# End node-to-branch node edge (and there is a unique non-zero value in b_neighborhood)
nh_slices_starts, b_neighborhood = _LMapNeighborhood(
b_node_lmap, ep_coords
)
b_node_label = b_neighborhood.max()
b_coords = np_.transpose((b_neighborhood == b_node_label).nonzero())[0]
_AppendNodeIDToEdge(
edge, nh_slices_starts.__add__(b_coords), b_nodes[b_node_label - 1]
)
else:
nh_slices_starts, b_neighborhood = _LMapNeighborhood(b_node_lmap, ep_coords)
force_after = False
# Looping only for length-1, b-to-b edges
for b_coords in zip(*b_neighborhood.nonzero()):
b_node_label = b_neighborhood[b_coords]
_AppendNodeIDToEdge(
edge,
nh_slices_starts.__add__(b_coords),
b_nodes[b_node_label - 1],
force_after=force_after,
)
force_after = not force_after
def _AppendNodeIDToEdge(
edge: dg_.edge_t, b_coords: array_t, node: nd_.node_t, force_after: bool = False
) -> None:
#
edge.node_uids.append(node.uid)
space_dim = b_coords.size
first_site = tuple(edge.sites[idx_][0] for idx_ in range(space_dim))
if isinstance(node, nd_.branch_node_t):
sq_distance = (b_coords.__sub__(first_site) ** 2).sum()
if sq_distance <= space_dim:
edge.origin_node = node.uid
if edge.sites[0].__len__() > 1:
if sq_distance <= space_dim:
edge.sites = tuple(
np_.hstack((b_coords[idx_], edge.sites[idx_]))
for idx_ in range(space_dim)
)
else:
edge.sites = tuple(
np_.hstack((edge.sites[idx_], b_coords[idx_]))
for idx_ in range(space_dim)
)
elif force_after:
edge.sites = tuple(
np_.hstack((edge.sites[idx_], b_coords[idx_]))
for idx_ in range(space_dim)
)
else:
edge.sites = tuple(
np_.hstack((b_coords[idx_], edge.sites[idx_]))
for idx_ in range(space_dim)
)
#
elif np_.array_equal(first_site, node.position):
edge.origin_node = node.uid
def _LMapNeighborhood(lmsk: array_t, site: Tuple[int, ...]) -> Tuple[array_t, array_t]:
#
slices_starts = tuple(max(site[idx_] - 1, 0) for idx_ in range(site.__len__()))
slices = tuple(
slice(slices_starts[idx_], min(site[idx_] + 2, lmsk.shape[idx_]))
for idx_ in range(site.__len__())
)
neighborhood = lmsk[slices]
return np_.array(slices_starts, dtype=np_.int64), neighborhood