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Merged
dbrnz merged 2 commits into from
Aug 7, 2025
Merged

Align rendered connectivity extraction with highlighted nodes #153

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0981b09
Reorganise rendered connectivity extraction: move from Pathways to Re…
napakalas Aug 5, 2025
51c250a
Enable identification of proxy anatomical nodes in rendered connectiv…
napakalas Aug 5, 2025
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2 changes: 2 additions & 0 deletions mapmaker/flatmap/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -252,6 +252,8 @@ def features_for_anatomical_node(self, anatomical_node: AnatomicalNode, warn: bo
if len(fts:=set(feature for feature in self.__features_with_id.values()
if feature.models in [features[0][0]]+list(features[0][1])
and feature.get_property('kind')=='proxy')) > 0:
for f in fts:
f.add_anatomical_node(anatomical_node)
return (features[0], fts)
return features

Expand Down
132 changes: 68 additions & 64 deletions mapmaker/properties/pathways.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,7 @@

from collections import defaultdict
from typing import Any, Iterable, Optional, TYPE_CHECKING
import json

#===============================================================================

Expand Down Expand Up @@ -310,11 +311,62 @@ def __resolve_nodes_for_path(self, path_id, node_feature_ids):
log.warning(f'Cannot find feature for node: {id}')
return node_geojson_ids

def __resolve_rendered_connectivity(self, path_id: str,
#======================================================
connectivity_graph: nx.Graph,
rendered_route_graphs: list):

def list_to_tuple(obj):
if isinstance(obj, list):
return tuple(list_to_tuple(x) for x in obj)
return obj

available_nodes = {
list_to_tuple(json.loads(an))
for geojson_id in self.__paths[path_id].as_dict['nodes'] + self.__paths[path_id].as_dict['nerves']
for an in self.__flatmap.get_feature_by_geojson_id(geojson_id).anatomical_nodes
}

# remove the missing nodes:
removed_nodes = []
for node in connectivity_graph.nodes:
if node not in available_nodes:
removed_nodes += [node]
neighbors = list(connectivity_graph.neighbors(node))
predecessors = [n for n in neighbors if n == connectivity_graph.edges[(node, n)]['predecessor']]
successors = [n for n in neighbors if n == connectivity_graph.edges[(node, n)]['successor']]
predecessors, successors = (predecessors or neighbors), (successors or neighbors)
connectivity_graph.add_edges_from([(e_0, e_1, {'predecessor': e_0, 'successor': e_1})
for e_0 in predecessors for e_1 in successors if e_0 != e_1])
connectivity_graph.remove_nodes_from(removed_nodes)

# extract and filter rendered edges and node_phenotypes
rendered_data = {
'connectivity': [
(connectivity_graph.nodes[ed['predecessor']]['node'], connectivity_graph.nodes[ed['successor']]['node'])
for _, _, ed in connectivity_graph.edges(data=True)
],
'node_phenotypes': {
phenotype: [connectivity_graph.nodes[node]['node'] for node in nodes if node in connectivity_graph.nodes]
for phenotype, nodes in connectivity_graph.graph.get('node-phenotypes').items()
},
'forward_connections': [
conn_id for conn_id in connectivity_graph.graph.get('forward-connections', [])
if conn_id in rendered_route_graphs
],
'node_nerves': [
list_to_tuple(n) for n in connectivity_graph.graph.get('nerves', [])
if list_to_tuple(n) in available_nodes
]
}
return rendered_data

def add_connectivity(self, path_id: str, line_geojson_ids: list[int],
#====================================================================
model: str, path_type: PATH_TYPE,
node_feature_ids: set[str], nerve_features: list[Feature],
rendered_data: dict,
connectivity_graph: nx.Graph,
rendered_route_graphs: list,
centrelines: Optional[list[str]]=None):
resolved_path = self.__paths[path_id]
if model is not None:
Expand All @@ -323,6 +375,7 @@ def add_connectivity(self, path_id: str, line_geojson_ids: list[int],
resolved_path.extend_nodes(self.__resolve_nodes_for_path(path_id, node_feature_ids))
resolved_path.extend_lines(line_geojson_ids)
resolved_path.extend_nerves([f.geojson_id for f in nerve_features])
rendered_data = self.__resolve_rendered_connectivity(path_id, connectivity_graph, rendered_route_graphs)
resolved_path.extend_connectivity(rendered_data['connectivity'])
resolved_path.extend_node_phenotypes(rendered_data['node_phenotypes'])
resolved_path.extend_forward_connections(rendered_data['forward_connections'])
Expand Down Expand Up @@ -723,67 +776,6 @@ def add_connectivity(self, connectivity):
for nerve_id in nerves:
self.__paths_by_nerve_id[nerve_id].append(path_id)

def __extract_rendered_connectivity(self, route_graphs, path_id):
#===============================================================================
connectivity_graph = route_graphs[path_id].graph['connectivity']

# restructure connectivity graph so it aligns to self.__resolved_pathways
available_features = {
x for layer in self.__flatmap.layers if layer.exported
for feature in layer.features
if 'error' not in feature.properties
and not feature.get_property('exclude', False)
and (model := feature.get_property('models', False))
for x in (feature.id, model)
}
removed_nodes = [
node for node, node_dict in connectivity_graph.nodes(data=True)
if (
(node_dict.get('type') == 'feature' and not {f.id for f in node_dict.get('features', [])} & available_features) or
(node_dict.get('type') != 'feature' and not set(node_dict['node'].normalised()) & available_features)
)
]
for node in removed_nodes:
neighbors = list(connectivity_graph.neighbors(node))
predecessors = [n for n in neighbors if n == connectivity_graph.edges[(node, n)]['predecessor']]
successors = [n for n in neighbors if n == connectivity_graph.edges[(node, n)]['successor']]
predecessors, successors = (predecessors or neighbors), (successors or neighbors)
connectivity_graph.add_edges_from([(e_0, e_1, {'predecessor': e_0, 'successor': e_1})
for e_0 in predecessors for e_1 in successors if e_0 != e_1])
connectivity_graph.remove_nodes_from(removed_nodes)

# extract hierarchy
for node_dict in connectivity_graph.nodes.values():
self.__node_hierarchy['nodes'].add(source := node_dict['node'])
while len(target := source[1]) > 0:
target = (target[0], target[1:])
self.__node_hierarchy['links'].add((source, target))
self.__node_hierarchy['nodes'].add(source := target)

# extract and filter rendered edges and node_phenotypes
rendered_data = {
'connectivity': [
(connectivity_graph.nodes[ed['predecessor']]['node'], connectivity_graph.nodes[ed['successor']]['node'])
for _, _, ed in connectivity_graph.edges(data=True)
],
'node_phenotypes': {
phenotype: [connectivity_graph.nodes[node]['node'] for node in nodes if node in connectivity_graph.nodes]
for phenotype, nodes in connectivity_graph.graph.get('node-phenotypes').items()
},
'forward_connections': [
conn_id for conn_id in connectivity_graph.graph.get('forward-connections', [])
if conn_id in route_graphs and route_graphs[conn_id].nodes
],
'node_nerves': [
rn for n in connectivity_graph.graph.get('nerves', [])
if n in connectivity_graph and
((rn := connectivity_graph.nodes[n]['node']) == n or any(get_knowledge(t).get('type') == NERVE_TYPE for t in [rn[0], *rn[1]]))
]
}

return rendered_data


def __route_network_connectivity(self, network: Network):
#========================================================
if self.__resolved_pathways is None:
Expand All @@ -809,6 +801,7 @@ def __route_network_connectivity(self, network: Network):
# Add features to the map for the geometric objects that make up each path
layer = FeatureLayer(f'{network.id}-routes', self.__flatmap, exported=True)
self.__flatmap.add_layer(layer)
rendered_route_graphs = [id for id, route_graph in route_graphs.items() if route_graph.nodes]
for route_number, routed_path in routed_paths.items():
for path_id, geometric_shapes in routed_path.path_geometry().items():
path = paths_by_id[path_id]
Expand Down Expand Up @@ -866,15 +859,26 @@ def __route_network_connectivity(self, network: Network):
nerve_feature_ids = routed_path.nerve_feature_ids
nerve_features = [self.__flatmap.get_feature(nerve_id) for nerve_id in nerve_feature_ids]
active_nerve_features.update(nerve_features)
rendered_data = self.__extract_rendered_connectivity(route_graphs, path_id)
connectivity_graph = route_graphs[path_id].graph['connectivity']
self.__resolved_pathways.add_connectivity(path_id,
path_geojson_ids,
path.models,
path.path_type,
routed_path.node_feature_ids,
nerve_features,
rendered_data,
connectivity_graph,
rendered_route_graphs,
centrelines=routed_path.centrelines)

# extract hierarchy
for node_dict in connectivity_graph.nodes.values():
self.__node_hierarchy['nodes'].add(source := node_dict['node'])
while len(target := source[1]) > 0:
target = (target[0], target[1:])
self.__node_hierarchy['links'].add((source, target))
self.__node_hierarchy['nodes'].add(source := target)


for feature in active_nerve_features:
if feature.get_property('type') == 'nerve' and feature.geom_type == 'LineString':
feature.pop_property('exclude')
Expand Down