138 lines
4.2 KiB
Python
138 lines
4.2 KiB
Python
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import numpy as np
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import heapq
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def _revalidate_node_edges(rag, node, heap_list):
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"""Handles validation and invalidation of edges incident to a node.
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This function invalidates all existing edges incident on `node` and inserts
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new items in `heap_list` updated with the valid weights.
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rag : RAG
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The Region Adjacency Graph.
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node : int
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The id of the node whose incident edges are to be validated/invalidated
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.
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heap_list : list
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The list containing the existing heap of edges.
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"""
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# networkx updates data dictionary if edge exists
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# this would mean we have to reposition these edges in
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# heap if their weight is updated.
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# instead we invalidate them
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for nbr in rag.neighbors(node):
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data = rag[node][nbr]
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try:
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# invalidate edges incident on `dst`, they have new weights
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data['heap item'][3] = False
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_invalidate_edge(rag, node, nbr)
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except KeyError:
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# will handle the case where the edge did not exist in the existing
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# graph
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pass
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wt = data['weight']
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heap_item = [wt, node, nbr, True]
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data['heap item'] = heap_item
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heapq.heappush(heap_list, heap_item)
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def _rename_node(graph, node_id, copy_id):
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""" Rename `node_id` in `graph` to `copy_id`. """
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graph._add_node_silent(copy_id)
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graph.nodes[copy_id].update(graph.nodes[node_id])
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for nbr in graph.neighbors(node_id):
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wt = graph[node_id][nbr]['weight']
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graph.add_edge(nbr, copy_id, {'weight': wt})
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graph.remove_node(node_id)
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def _invalidate_edge(graph, n1, n2):
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""" Invalidates the edge (n1, n2) in the heap. """
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graph[n1][n2]['heap item'][3] = False
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def merge_hierarchical(labels, rag, thresh, rag_copy, in_place_merge,
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merge_func, weight_func):
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"""Perform hierarchical merging of a RAG.
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Greedily merges the most similar pair of nodes until no edges lower than
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`thresh` remain.
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Parameters
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----------
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labels : ndarray
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The array of labels.
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rag : RAG
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The Region Adjacency Graph.
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thresh : float
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Regions connected by an edge with weight smaller than `thresh` are
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merged.
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rag_copy : bool
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If set, the RAG copied before modifying.
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in_place_merge : bool
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If set, the nodes are merged in place. Otherwise, a new node is
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created for each merge..
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merge_func : callable
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This function is called before merging two nodes. For the RAG `graph`
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while merging `src` and `dst`, it is called as follows
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``merge_func(graph, src, dst)``.
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weight_func : callable
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The function to compute the new weights of the nodes adjacent to the
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merged node. This is directly supplied as the argument `weight_func`
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to `merge_nodes`.
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Returns
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-------
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out : ndarray
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The new labeled array.
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"""
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if rag_copy:
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rag = rag.copy()
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edge_heap = []
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for n1, n2, data in rag.edges(data=True):
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# Push a valid edge in the heap
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wt = data['weight']
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heap_item = [wt, n1, n2, True]
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heapq.heappush(edge_heap, heap_item)
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# Reference to the heap item in the graph
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data['heap item'] = heap_item
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while len(edge_heap) > 0 and edge_heap[0][0] < thresh:
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_, n1, n2, valid = heapq.heappop(edge_heap)
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# Ensure popped edge is valid, if not, the edge is discarded
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if valid:
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# Invalidate all neigbors of `src` before its deleted
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for nbr in rag.neighbors(n1):
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_invalidate_edge(rag, n1, nbr)
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for nbr in rag.neighbors(n2):
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_invalidate_edge(rag, n2, nbr)
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if not in_place_merge:
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next_id = rag.next_id()
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_rename_node(rag, n2, next_id)
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src, dst = n1, next_id
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else:
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src, dst = n1, n2
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merge_func(rag, src, dst)
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new_id = rag.merge_nodes(src, dst, weight_func)
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_revalidate_node_edges(rag, new_id, edge_heap)
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label_map = np.arange(labels.max() + 1)
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for ix, (n, d) in enumerate(rag.nodes(data=True)):
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for label in d['labels']:
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label_map[label] = ix
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return label_map[labels]
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