wehub/easy-graph--easy-graph
1
0
Fork 0
Code Issues Pull Requests Actions 1 Deployments Models Agent Notes Packages Projects Releases Wiki Activity

chore: import upstream snapshot with attribution

Browse Source
This commit is contained in:
wehub-resource-sync
2026-07-13 12:36:30 +08:00
commit 55ab4e4a73
473 changed files with 72932 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files
easygraph/classes/multigraph.py
+729
View File
@@ -0,0 +1,729 @@
"""Base class for MultiGraph."""
from copy import deepcopy
from typing import Dict
from typing import List
import easygraph as eg
import easygraph.convert as convert
from easygraph.classes.graph import Graph
from easygraph.utils.exception import EasyGraphError
__all__ = ["MultiGraph"]
class MultiGraph(Graph):
edge_key_dict_factory = dict
def __init__(self, incoming_graph_data=None, multigraph_input=None, **attr):
"""Initialize a graph with edges, name, or graph attributes.
Parameters
----------
incoming_graph_data : input graph
Data to initialize graph. If incoming_graph_data=None (default)
an empty graph is created. The data can be an edge list, or any
EasyGraph graph object. If the corresponding optional Python
packages are installed the data can also be a NumPy matrix
or 2d ndarray, a SciPy sparse matrix, or a PyGraphviz graph.
multigraph_input : bool or None (default None)
Note: Only used when `incoming_graph_data` is a dict.
If True, `incoming_graph_data` is assumed to be a
dict-of-dict-of-dict-of-dict structure keyed by
node to neighbor to edge keys to edge data for multi-edges.
A EasyGraphError is raised if this is not the case.
If False, :func:`to_easygraph_graph` is used to try to determine
the dict's graph data structure as either a dict-of-dict-of-dict
keyed by node to neighbor to edge data, or a dict-of-iterable
keyed by node to neighbors.
If None, the treatment for True is tried, but if it fails,
the treatment for False is tried.
attr : keyword arguments, optional (default= no attributes)
Attributes to add to graph as key=value pairs.
See Also
--------
convert
Examples
--------
>>> G = eg.Graph() # or DiGraph, MultiGraph, MultiDiGraph, etc
>>> G = eg.Graph(name="my graph")
>>> e = [(1, 2), (2, 3), (3, 4)] # list of edges
>>> G = eg.Graph(e)
Arbitrary graph attribute pairs (key=value) may be assigned
>>> G = eg.Graph(e, day="Friday")
>>> G.graph
{'day': 'Friday'}
"""
self.edge_key_dict_factory = self.edge_key_dict_factory
if isinstance(incoming_graph_data, dict) and multigraph_input is not False:
Graph.__init__(self)
try:
convert.from_dict_of_dicts(
incoming_graph_data, create_using=self, multigraph_input=True
)
self.graph.update(attr)
except Exception as err:
if multigraph_input is True:
raise eg.EasyGraphError(
f"converting multigraph_input raised:\n{type(err)}: {err}"
)
Graph.__init__(self, incoming_graph_data, **attr)
else:
Graph.__init__(self, incoming_graph_data, **attr)
def new_edge_key(self, u, v):
"""Returns an unused key for edges between nodes `u` and `v`.
The nodes `u` and `v` do not need to be already in the graph.
Notes
-----
In the standard MultiGraph class the new key is the number of existing
edges between `u` and `v` (increased if necessary to ensure unused).
The first edge will have key 0, then 1, etc. If an edge is removed
further new_edge_keys may not be in this order.
Parameters
----------
u, v : nodes
Returns
-------
key : int
"""
try:
keydict = self._adj[u][v]
except KeyError:
return 0
key = len(keydict)
while key in keydict:
key += 1
return key
def add_edge(self, u_for_edge, v_for_edge, key=None, **attr):
"""Add an edge between u and v.
The nodes u and v will be automatically added if they are
not already in the graph.
Edge attributes can be specified with keywords or by directly
accessing the edge's attribute dictionary. See examples below.
Parameters
----------
u_for_edge, v_for_edge : nodes
Nodes can be, for example, strings or numbers.
Nodes must be hashable (and not None) Python objects.
key : hashable identifier, optional (default=lowest unused integer)
Used to distinguish multiedges between a pair of nodes.
attr : keyword arguments, optional
Edge data (or labels or objects) can be assigned using
keyword arguments.
Returns
-------
The edge key assigned to the edge.
See Also
--------
add_edges_from : add a collection of edges
Notes
-----
To replace/update edge data, use the optional key argument
to identify a unique edge. Otherwise a new edge will be created.
EasyGraph algorithms designed for weighted graphs cannot use
multigraphs directly because it is not clear how to handle
multiedge weights. Convert to Graph using edge attribute
'weight' to enable weighted graph algorithms.
Default keys are generated using the method `new_edge_key()`.
This method can be overridden by subclassing the base class and
providing a custom `new_edge_key()` method.
Examples
--------
The following all add the edge e=(1, 2) to graph G:
>>> G = eg.MultiGraph()
>>> e = (1, 2)
>>> ekey = G.add_edge(1, 2) # explicit two-node form
>>> G.add_edge(*e) # single edge as tuple of two nodes
1
>>> G.add_edges_from([(1, 2)]) # add edges from iterable container
[2]
Associate data to edges using keywords:
>>> ekey = G.add_edge(1, 2, weight=3)
>>> ekey = G.add_edge(1, 2, key=0, weight=4) # update data for key=0
>>> ekey = G.add_edge(1, 3, weight=7, capacity=15, length=342.7)
For non-string attribute keys, use subscript notation.
>>> ekey = G.add_edge(1, 2)
>>> G[1][2][0].update({0: 5})
>>> G.edges[1, 2, 0].update({0: 5})
"""
u, v = u_for_edge, v_for_edge
# add nodes
if u not in self._adj:
if u is None:
raise ValueError("None cannot be a node")
self._adj[u] = self.adjlist_inner_dict_factory()
self._node[u] = self.node_attr_dict_factory()
if v not in self._adj:
if v is None:
raise ValueError("None cannot be a node")
self._adj[v] = self.adjlist_inner_dict_factory()
self._node[v] = self.node_attr_dict_factory()
if key is None:
key = self.new_edge_key(u, v)
if v in self._adj[u]:
keydict = self._adj[u][v]
datadict = keydict.get(key, self.edge_attr_dict_factory())
datadict.update(attr)
keydict[key] = datadict
else:
# selfloops work this way without special treatment
datadict = self.edge_attr_dict_factory()
datadict.update(attr)
keydict = self.edge_key_dict_factory()
keydict[key] = datadict
self._adj[u][v] = keydict
self._adj[v][u] = keydict
return key
def add_edges_from(self, ebunch_to_add, **attr):
"""Add all the edges in ebunch_to_add.
Parameters
----------
ebunch_to_add : container of edges
Each edge given in the container will be added to the
graph. The edges can be:
- 2-tuples (u, v) or
- 3-tuples (u, v, d) for an edge data dict d, or
- 3-tuples (u, v, k) for not iterable key k, or
- 4-tuples (u, v, k, d) for an edge with data and key k
attr : keyword arguments, optional
Edge data (or labels or objects) can be assigned using
keyword arguments.
Returns
-------
A list of edge keys assigned to the edges in `ebunch`.
See Also
--------
add_edge : add a single edge
add_weighted_edges_from : convenient way to add weighted edges
Notes
-----
Adding the same edge twice has no effect but any edge data
will be updated when each duplicate edge is added.
Edge attributes specified in an ebunch take precedence over
attributes specified via keyword arguments.
Default keys are generated using the method ``new_edge_key()``.
This method can be overridden by subclassing the base class and
providing a custom ``new_edge_key()`` method.
Examples
--------
>>> G = eg.Graph() # or DiGraph, MultiGraph, MultiDiGraph, etc
>>> G.add_edges_from([(0, 1), (1, 2)]) # using a list of edge tuples
>>> e = zip(range(0, 3), range(1, 4))
>>> G.add_edges_from(e) # Add the path graph 0-1-2-3
Associate data to edges
>>> G.add_edges_from([(1, 2), (2, 3)], weight=3)
>>> G.add_edges_from([(3, 4), (1, 4)], label="WN2898")
"""
keylist = []
for e in ebunch_to_add:
ne = len(e)
if ne == 4:
u, v, key, dd = e
elif ne == 3:
u, v, dd = e
key = None
elif ne == 2:
u, v = e
dd = {}
key = None
else:
msg = f"Edge tuple {e} must be a 2-tuple, 3-tuple or 4-tuple."
raise EasyGraphError(msg)
ddd = {}
ddd.update(attr)
try:
ddd.update(dd)
except (TypeError, ValueError):
if ne != 3:
raise
key = dd # ne == 3 with 3rd value not dict, must be a key
key = self.add_edge(u, v, key)
self[u][v][key].update(ddd)
keylist.append(key)
return keylist
def remove_edge(self, u, v, key=None):
"""Remove an edge between u and v.
Parameters
----------
u, v : nodes
Remove an edge between nodes u and v.
key : hashable identifier, optional (default=None)
Used to distinguish multiple edges between a pair of nodes.
If None remove a single (arbitrary) edge between u and v.
Raises
------
EasyGraphError
If there is not an edge between u and v, or
if there is no edge with the specified key.
See Also
--------
remove_edges_from : remove a collection of edges
Examples
--------
For multiple edges
>>> G = eg.MultiGraph() # or MultiDiGraph, etc
>>> G.add_edges_from([(1, 2), (1, 2), (1, 2)]) # key_list returned
[0, 1, 2]
>>> G.remove_edge(1, 2) # remove a single (arbitrary) edge
For edges with keys
>>> G = eg.MultiGraph() # or MultiDiGraph, etc
>>> G.add_edge(1, 2, key="first")
'first'
>>> G.add_edge(1, 2, key="second")
'second'
>>> G.remove_edge(1, 2, key="second")
"""
try:
d = self._adj[u][v]
except KeyError as err:
raise EasyGraphError(f"The edge {u}-{v} is not in the graph.") from err
# remove the edge with specified data
if key is None:
d.popitem()
else:
try:
del d[key]
except KeyError as err:
msg = f"The edge {u}-{v} with key {key} is not in the graph."
raise EasyGraphError(msg) from err
if len(d) == 0:
# remove the key entries if last edge
del self._adj[u][v]
if u != v: # check for selfloop
del self._adj[v][u]
def remove_edges_from(self, ebunch):
"""Remove all edges specified in ebunch.
Parameters
----------
ebunch: list or container of edge tuples
Each edge given in the list or container will be removed
from the graph. The edges can be:
- 2-tuples (u, v) All edges between u and v are removed.
- 3-tuples (u, v, key) The edge identified by key is removed.
- 4-tuples (u, v, key, data) where data is ignored.
See Also
--------
remove_edge : remove a single edge
Notes
-----
Will fail silently if an edge in ebunch is not in the graph.
Examples
--------
Removing multiple copies of edges
>>> G = eg.MultiGraph()
>>> keys = G.add_edges_from([(1, 2), (1, 2), (1, 2)])
>>> G.remove_edges_from([(1, 2), (1, 2)])
>>> list(G.edges())
[(1, 2)]
>>> G.remove_edges_from([(1, 2), (1, 2)]) # silently ignore extra copy
>>> list(G.edges) # now empty graph
[]
"""
for e in ebunch:
try:
self.remove_edge(*e[:3])
except EasyGraphError:
pass
def has_edge(self, u, v, key=None):
"""Returns True if the graph has an edge between nodes u and v.
This is the same as `v in G[u] or key in G[u][v]`
without KeyError exceptions.
Parameters
----------
u, v : nodes
Nodes can be, for example, strings or numbers.
key : hashable identifier, optional (default=None)
If specified return True only if the edge with
key is found.
Returns
-------
edge_ind : bool
True if edge is in the graph, False otherwise.
Examples
--------
Can be called either using two nodes u, v, an edge tuple (u, v),
or an edge tuple (u, v, key).
>>> G = eg.MultiGraph() # or MultiDiGraph
>>> G = eg.complete_graph(4, create_using=eg.MultiDiGraph)
>>> G.has_edge(0, 1) # using two nodes
True
>>> e = (0, 1)
>>> G.has_edge(*e) # e is a 2-tuple (u, v)
True
>>> G.add_edge(0, 1, key="a")
'a'
>>> G.has_edge(0, 1, key="a") # specify key
True
>>> e = (0, 1, "a")
>>> G.has_edge(*e) # e is a 3-tuple (u, v, 'a')
True
The following syntax are equivalent:
>>> G.has_edge(0, 1)
True
>>> 1 in G[0] # though this gives :exc:`KeyError` if 0 not in G
True
"""
try:
if key is None:
return v in self._adj[u]
else:
return key in self._adj[u][v]
except KeyError:
return False
@property
def edges(self):
edges = list()
seen = {}
for n, nbrs in self._adj.items():
for nbr, kd in nbrs.items():
if nbr not in seen:
for k, dd in kd.items():
edges.append((n, nbr, k, dd))
seen[n] = 1
del seen
return edges
def get_edge_data(self, u, v, key=None, default=None):
"""Returns the attribute dictionary associated with edge (u, v).
This is identical to `G[u][v][key]` except the default is returned
instead of an exception is the edge doesn't exist.
Parameters
----------
u, v : nodes
default : any Python object (default=None)
Value to return if the edge (u, v) is not found.
key : hashable identifier, optional (default=None)
Return data only for the edge with specified key.
Returns
-------
edge_dict : dictionary
The edge attribute dictionary.
Examples
--------
>>> G = eg.MultiGraph() # or MultiDiGraph
>>> key = G.add_edge(0, 1, key="a", weight=7)
>>> G[0][1]["a"] # key='a'
{'weight': 7}
>>> G.edges[0, 1, "a"] # key='a'
{'weight': 7}
Warning: we protect the graph data structure by making
`G.edges` and `G[1][2]` read-only dict-like structures.
However, you can assign values to attributes in e.g.
`G.edges[1, 2, 'a']` or `G[1][2]['a']` using an additional
bracket as shown next. You need to specify all edge info
to assign to the edge data associated with an edge.
>>> G[0][1]["a"]["weight"] = 10
>>> G.edges[0, 1, "a"]["weight"] = 10
>>> G[0][1]["a"]["weight"]
10
>>> G.edges[1, 0, "a"]["weight"]
10
>>> G = eg.MultiGraph() # or MultiDiGraph
>>> G = eg.complete_graph(4, create_using=eg.MultiDiGraph)
>>> G.get_edge_data(0, 1)
{0: {}}
>>> e = (0, 1)
>>> G.get_edge_data(*e) # tuple form
{0: {}}
>>> G.get_edge_data("a", "b", default=0) # edge not in graph, return 0
0
"""
try:
if key is None:
return self._adj[u][v]
else:
return self._adj[u][v][key]
except KeyError:
return default
@property
def degree(self, weight="weight"):
degree = dict()
if weight is None:
for n in self._nodes:
nbrs = self._succ[n]
deg = sum(len(keys) for keys in nbrs.values()) + (
n in nbrs and len(nbrs[n])
)
degree[n] = deg
else:
for n in self._nodes:
nbrs = self._succ[n]
deg = sum(
d.get(weight, 1)
for key_dict in nbrs.values()
for d in key_dict.values()
)
if n in nbrs:
deg += sum(d.get(weight, 1) for d in nbrs[n].values())
degree[n] = deg
def is_multigraph(self):
"""Returns True if graph is a multigraph, False otherwise."""
return True
def is_directed(self):
"""Returns True if graph is directed, False otherwise."""
return False
def copy(self):
"""Returns a copy of the graph.
The copy method by default returns an independent shallow copy
of the graph and attributes. That is, if an attribute is a
container, that container is shared by the original an the copy.
Use Python's `copy.deepcopy` for new containers.
Notes
-----
All copies reproduce the graph structure, but data attributes
may be handled in different ways. There are four types of copies
of a graph that people might want.
Deepcopy -- A "deepcopy" copies the graph structure as well as
all data attributes and any objects they might contain.
The entire graph object is new so that changes in the copy
do not affect the original object. (see Python's copy.deepcopy)
Data Reference (Shallow) -- For a shallow copy the graph structure
is copied but the edge, node and graph attribute dicts are
references to those in the original graph. This saves
time and memory but could cause confusion if you change an attribute
in one graph and it changes the attribute in the other.
EasyGraph does not provide this level of shallow copy.
Independent Shallow -- This copy creates new independent attribute
dicts and then does a shallow copy of the attributes. That is, any
attributes that are containers are shared between the new graph
and the original. This is exactly what `dict.copy()` provides.
You can obtain this style copy using:
>>> G = eg.path_graph(5)
>>> H = G.copy()
>>> H = eg.Graph(G)
>>> H = G.__class__(G)
Fresh Data -- For fresh data, the graph structure is copied while
new empty data attribute dicts are created. The resulting graph
is independent of the original and it has no edge, node or graph
attributes. Fresh copies are not enabled. Instead use:
>>> H = G.__class__()
>>> H.add_nodes_from(G)
>>> H.add_edges_from(G.edges)
See the Python copy module for more information on shallow
and deep copies, https://docs.python.org/3/library/copy.html.
Returns
-------
G : Graph
A copy of the graph.
See Also
--------
to_directed: return a directed copy of the graph.
Examples
--------
>>> G = eg.path_graph(4) # or DiGraph, MultiGraph, MultiDiGraph, etc
>>> H = G.copy()
"""
G = self.__class__()
G.graph.update(self.graph)
G.add_nodes_from((n, d.copy()) for n, d in self._node.items())
G.add_edges_from(
(u, v, key, datadict.copy())
for u, nbrs in self._adj.items()
for v, keydict in nbrs.items()
for key, datadict in keydict.items()
)
return G
def to_directed(self):
"""Returns a directed representation of the graph.
Returns
-------
G : MultiDiGraph
A directed graph with the same name, same nodes, and with
each edge (u, v, data) replaced by two directed edges
(u, v, data) and (v, u, data).
Notes
-----
This returns a "deepcopy" of the edge, node, and
graph attributes which attempts to completely copy
all of the data and references.
This is in contrast to the similar D=DiGraph(G) which returns a
shallow copy of the data.
See the Python copy module for more information on shallow
and deep copies, https://docs.python.org/3/library/copy.html.
Warning: If you have subclassed MultiGraph to use dict-like objects
in the data structure, those changes do not transfer to the
MultiDiGraph created by this method.
Examples
--------
>>> G = eg.Graph() # or MultiGraph, etc
>>> G.add_edge(0, 1)
>>> H = G.to_directed()
>>> list(H.edges)
[(0, 1), (1, 0)]
If already directed, return a (deep) copy
>>> G = eg.DiGraph() # or MultiDiGraph, etc
>>> G.add_edge(0, 1)
>>> H = G.to_directed()
>>> list(H.edges)
[(0, 1)]
"""
G = eg.MultiDiGraph()
G.graph.update(deepcopy(self.graph))
G.add_nodes_from((n, deepcopy(d)) for n, d in self._node.items())
G.add_edges_from(
(u, v, key, deepcopy(datadict))
for u, nbrs in self.adj.items()
for v, keydict in nbrs.items()
for key, datadict in keydict.items()
)
return G
def number_of_edges(self, u=None, v=None):
"""Returns the number of edges between two nodes.
Parameters
----------
u, v : nodes, optional (Gefault=all edges)
If u and v are specified, return the number of edges between
u and v. Otherwise return the total number of all edges.
Returns
-------
nedges : int
The number of edges in the graph. If nodes `u` and `v` are
specified return the number of edges between those nodes. If
the graph is directed, this only returns the number of edges
from `u` to `v`.
See Also
--------
size
Examples
--------
For undirected multigraphs, this method counts the total number
of edges in the graph::
>>> G = eg.MultiGraph()
>>> G.add_edges_from([(0, 1), (0, 1), (1, 2)])
[0, 1, 0]
>>> G.number_of_edges()
3
If you specify two nodes, this counts the total number of edges
joining the two nodes::
>>> G.number_of_edges(0, 1)
2
For directed multigraphs, this method can count the total number
of directed edges from `u` to `v`::
>>> G = eg.MultiDiGraph()
>>> G.add_edges_from([(0, 1), (0, 1), (1, 0)])
[0, 1, 0]
>>> G.number_of_edges(0, 1)
2
>>> G.number_of_edges(1, 0)
1
"""
if u is None:
return self.size()
try:
edgedata = self._adj[u][v]
except KeyError:
return 0 # no such edge
return len(edgedata)