removed already imported method, add dependency

Author: lfischerr

graphconstructor/operators/metric_distance.py

@@ -3,85 +3,9 @@
 from .base import GraphOperator
 from distanceclosure.dijkstra import single_source_dijkstra_path_length
 from networkx.algorithms.shortest_paths.weighted import _weight_function
-from heapq import heappush, heappop
-from itertools import count
 import networkx as nx
 from typing import Literal
 
-def single_source_dijkstra_path_length(G, source, weight_function, paths=None, disjunction=sum):
-    """Uses (a custom) Dijkstra's algorithm to find shortest weighted paths
-
-    Parameters
-    ----------
-    G : NetworkX graph
-
-    source : node
-        Starting node for path.
-
-    weight_function: function
-        Function with (u, v, data) input that returns that edges weight
-
-    paths: dict, optional (default=None)
-        dict to store the path list from source to each node, keyed by node.
-        If None, paths are not stored.
-
-    disjunction: function (default=sum)
-        Whether to sum paths or use the max value.
-        Use `sum` for metric and `max` for ultrametric.
-
-    Returns
-    -------
-    distance : dictionary
-        A mapping from node to shortest distance to that node from one
-        of the source nodes.
-
-    Raises
-    ------
-    NodeNotFound
-        If `source` is not in `G`.
-
-    Note
-    -----
-    The optional predecessor and path dictionaries can be accessed by
-    the caller through the original paths objects passed
-    as arguments. No need to explicitly return paths.
-
-    """
-    G_succ = G._succ if G.is_directed() else G._adj
-
-    push = heappush
-    pop = heappop
-    dist = {}  # dictionary of final distances
-    seen = {}
-    # fringe is heapq with 3-tuples (distance,c,node)
-    # use the count c to avoid comparing nodes (may not be able to)
-    c = count()
-    fringe = []
-    if source not in G:
-        raise nx.NodeNotFound(f"Source {source} not in G")
-    seen[source] = 0
-    push(fringe, (0, next(c), source))
-    while fringe:
-        (d, _, v) = pop(fringe)
-        if v in dist:
-            continue  # already searched this node.
-        dist[v] = d
-        for u, e in G_succ[v].items():
-            cost = weight_function(v, u, e)
-            if cost is None:
-                continue
-            vu_dist = disjunction([dist[v], cost])
-            if u in dist:
-                u_dist = dist[u]
-                if vu_dist < u_dist:
-                    raise ValueError("Contradictory paths found:", "negative weights?")
-            elif u not in seen or vu_dist < seen[u]:
-                seen[u] = vu_dist
-                push(fringe, (vu_dist, next(c), u))
-                if paths is not None:
-                    paths[u] = paths[v] + [u]
-    return dist
-
 Mode = Literal["distance", "similarity"]
 
 @dataclass(slots=True)

pyproject.toml

@@ -28,6 +28,7 @@ networkx = ">3.4.0"
 pandas = ">=2.1.1"
 scipy= ">=1.14.0"
 matplotlib= ">=3.8.0"
+distanceclosure = ">=0.5.0"
 
 [tool.poetry.group.dev.dependencies]
 decorator = "^5.1.1"