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updated functions in core.py #7027

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Nov 17, 2023
Merged

updated functions in core.py #7027

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7e42a78
added examples in core.py
Schefflera-Arboricola Oct 18, 2023
b0a1184
updated core.py docs
Schefflera-Arboricola Nov 5, 2023
b93b236
added test_k_truss_self_loop
Schefflera-Arboricola Nov 5, 2023
1cad9d7
small bug fix in test_k_truss_self_loop
Schefflera-Arboricola Nov 5, 2023
2666982
updated core.py
Schefflera-Arboricola Nov 6, 2023
195a5ae
updated core.py file
Schefflera-Arboricola Nov 8, 2023
ffd7ab1
inline implementation for decorators and exceptions and modified sec…
Schefflera-Arboricola Nov 9, 2023
b5a4fb9
changed .nodes() to .nodes
Schefflera-Arboricola Nov 12, 2023
018453c
Replace parallel edges with multigraph in docstrings.
rossbar Nov 14, 2023
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138 changes: 94 additions & 44 deletions networkx/algorithms/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,7 @@

"""
import networkx as nx
from networkx.exception import NetworkXError
from networkx.exception import NetworkXNotImplemented
from networkx.utils import not_implemented_for

__all__ = [
Expand All @@ -46,7 +46,7 @@
@not_implemented_for("multigraph")
@nx._dispatch
def core_number(G):
"""Returns the core number for each vertex.
"""Returns the core number for each node.

A k-core is a maximal subgraph that contains nodes of degree k or more.

Expand All @@ -65,17 +65,27 @@ def core_number(G):

Raises
------
NetworkXError
The k-core is not implemented for graphs with self loops
or parallel edges.
NetworkXNotImplemented
The k-core is not implemented for graphs with self loops.
NetworkXNotImplemented
If `G` is a Multigraph.

Notes
-----
Not implemented for graphs with parallel edges or self loops.

For directed graphs the node degree is defined to be the
in-degree + out-degree.

Examples
--------
>>> degrees = [0, 1, 2, 2, 2, 2, 3]
>>> H = nx.havel_hakimi_graph(degrees)
>>> nx.core_number(H)
{0: 1, 1: 2, 2: 2, 3: 2, 4: 1, 5: 2, 6: 0}
>>> G = nx.DiGraph()
>>> G.add_edges_from([(1, 2), (2, 1), (2, 3), (2, 4), (3, 4), (4, 3)])
>>> nx.core_number(G)
{1: 2, 2: 2, 3: 2, 4: 2}

References
----------
.. [1] An O(m) Algorithm for Cores Decomposition of Networks
Expand All @@ -87,7 +97,7 @@ def core_number(G):
"Input graph has self loops which is not permitted; "
"Consider using G.remove_edges_from(nx.selfloop_edges(G))."
)
raise NetworkXError(msg)
raise NetworkXNotImplemented(msg)
degrees = dict(G.degree())
# Sort nodes by degree.
nodes = sorted(degrees, key=degrees.get)
Expand Down Expand Up @@ -153,7 +163,7 @@ def k_core(G, k=None, core_number=None):
G : NetworkX graph
A graph or directed graph
k : int, optional
The order of the core. If not specified return the main core.
The order of the core. If not specified return the main core.
core_number : dictionary, optional
Precomputed core numbers for the graph G.

Expand All @@ -164,20 +174,28 @@ def k_core(G, k=None, core_number=None):

Raises
------
NetworkXError
The k-core is not defined for graphs with self loops or parallel edges.
NetworkXNotImplemented
The k-core is not defined for graphs with self loops
or parallel edges.

Notes
-----
The main core is the core with the largest degree.

Not implemented for graphs with parallel edges or self loops.
The main core is the core with `k` as the largest core_number.

For directed graphs the node degree is defined to be the
in-degree + out-degree.

Graph, node, and edge attributes are copied to the subgraph.

Examples
--------
>>> degrees = [0, 1, 2, 2, 2, 2, 3]
>>> H = nx.havel_hakimi_graph(degrees)
>>> H.degree
DegreeView({0: 1, 1: 2, 2: 2, 3: 2, 4: 2, 5: 3, 6: 0})
>>> nx.k_core(H).nodes()
NodeView((1, 2, 3, 5))

See Also
--------
core_number
Expand Down Expand Up @@ -219,7 +237,7 @@ def k_shell(G, k=None, core_number=None):

Raises
------
NetworkXError
NetworkXNotImplemented
The k-shell is not implemented for graphs with self loops
or parallel edges.

Expand All @@ -228,13 +246,20 @@ def k_shell(G, k=None, core_number=None):
This is similar to k_corona but in that case only neighbors in the
k-core are considered.

Not implemented for graphs with parallel edges or self loops.

For directed graphs the node degree is defined to be the
in-degree + out-degree.

Graph, node, and edge attributes are copied to the subgraph.

Examples
--------
>>> degrees = [0, 1, 2, 2, 2, 2, 3]
>>> H = nx.havel_hakimi_graph(degrees)
>>> H.degree
DegreeView({0: 1, 1: 2, 2: 2, 3: 2, 4: 2, 5: 3, 6: 0})
>>> nx.k_shell(H, k=1).nodes()
NodeView((0, 4))

See Also
--------
core_number
Expand Down Expand Up @@ -267,7 +292,7 @@ def k_crust(G, k=None, core_number=None):
G : NetworkX graph
A graph or directed graph.
k : int, optional
The order of the shell. If not specified return the main crust.
The order of the shell. If not specified return the main crust.
core_number : dictionary, optional
Precomputed core numbers for the graph G.

Expand All @@ -278,7 +303,7 @@ def k_crust(G, k=None, core_number=None):

Raises
------
NetworkXError
NetworkXNotImplemented
The k-crust is not implemented for graphs with self loops
or parallel edges.

Expand All @@ -287,13 +312,20 @@ def k_crust(G, k=None, core_number=None):
This definition of k-crust is different than the definition in [1]_.
The k-crust in [1]_ is equivalent to the k+1 crust of this algorithm.

Not implemented for graphs with parallel edges or self loops.

For directed graphs the node degree is defined to be the
in-degree + out-degree.

Graph, node, and edge attributes are copied to the subgraph.

Examples
--------
>>> degrees = [0, 1, 2, 2, 2, 2, 3]
>>> H = nx.havel_hakimi_graph(degrees)
>>> H.degree
DegreeView({0: 1, 1: 2, 2: 2, 3: 2, 4: 2, 5: 3, 6: 0})
>>> nx.k_crust(H, k=1).nodes()
NodeView((0, 4, 6))

See Also
--------
core_number
Expand Down Expand Up @@ -338,19 +370,26 @@ def k_corona(G, k, core_number=None):

Raises
------
NetworkXError
The k-corona is not defined for graphs with self loops or
parallel edges.
NetworkXNotImplemented
The k-corona is not defined for graphs with self loops
or parallel edges.

Notes
-----
Not implemented for graphs with parallel edges or self loops.

For directed graphs the node degree is defined to be the
in-degree + out-degree.

Graph, node, and edge attributes are copied to the subgraph.

Examples
--------
>>> degrees = [0, 1, 2, 2, 2, 2, 3]
>>> H = nx.havel_hakimi_graph(degrees)
>>> H.degree
DegreeView({0: 1, 1: 2, 2: 2, 3: 2, 4: 2, 5: 3, 6: 0})
>>> nx.k_corona(H, k=2).nodes()
NodeView((1, 2, 3, 5))

See Also
--------
core_number
Expand Down Expand Up @@ -393,17 +432,15 @@ def k_truss(G, k):

Raises
------
NetworkXError

The k-truss is not defined for graphs with self loops, directed graphs
and multigraphs.
NetworkXNotImplemented
The k-truss is not defined for graphs with self loops.
NetworkXNotImplemented
If `G` is a Multigraph or Directed graph.

Notes
-----
A k-clique is a (k-2)-truss and a k-truss is a (k+1)-core.

Not implemented for digraphs or graphs with parallel edges or self loops.

Graph, node, and edge attributes are copied to the subgraph.

K-trusses were originally defined in [2] which states that the k-truss
Expand All @@ -412,6 +449,15 @@ def k_truss(G, k):
definition requiring that each edge belong to at least `k` triangles.
This implementation uses the original definition of `k-2` triangles.

Examples
--------
>>> degrees = [0, 1, 2, 2, 2, 2, 3]
>>> H = nx.havel_hakimi_graph(degrees)
>>> H.degree
DegreeView({0: 1, 1: 2, 2: 2, 3: 2, 4: 2, 5: 3, 6: 0})
>>> nx.k_truss(H, k=2).nodes()
NodeView((0, 1, 2, 3, 4, 5))

References
----------
.. [1] Bounds and Algorithms for k-truss. Paul Burkhardt, Vance Faber,
Expand All @@ -424,7 +470,7 @@ def k_truss(G, k):
"Input graph has self loops which is not permitted; "
"Consider using G.remove_edges_from(nx.selfloop_edges(G))."
)
raise NetworkXError(msg)
raise NetworkXNotImplemented(msg)

H = G.copy()

Expand Down Expand Up @@ -460,25 +506,29 @@ def onion_layers(G):
Parameters
----------
G : NetworkX graph
A simple graph without self loops or parallel edges
An undirected graph without self loops.

Returns
-------
od_layers : dictionary
A dictionary keyed by vertex to the onion layer. The layers are
A dictionary keyed by node to the onion layer. The layers are
contiguous integers starting at 1.

Raises
------
NetworkXError
The onion decomposition is not implemented for graphs with self loops
or parallel edges or for directed graphs.

Notes
-----
Not implemented for graphs with parallel edges or self loops.
NetworkXNotImplemented
The onion decomposition is not implemented for graphs with self loops.
NetworkXNotImplemented
If `G` is a Multigraph or Directed graph.

Not implemented for directed graphs.
Examples
--------
>>> degrees = [0, 1, 2, 2, 2, 2, 3]
>>> H = nx.havel_hakimi_graph(degrees)
>>> H.degree
DegreeView({0: 1, 1: 2, 2: 2, 3: 2, 4: 2, 5: 3, 6: 0})
>>> nx.onion_layers(H)
{6: 1, 0: 2, 4: 3, 1: 4, 2: 4, 3: 4, 5: 4}

See Also
--------
Expand All @@ -501,7 +551,7 @@ def onion_layers(G):
"Input graph contains self loops which is not permitted; "
"Consider using G.remove_edges_from(nx.selfloop_edges(G))."
)
raise NetworkXError(msg)
raise NetworkXNotImplemented(msg)
# Dictionaries to register the k-core/onion decompositions.
od_layers = {}
# Adjacency list
Expand Down
16 changes: 14 additions & 2 deletions networkx/algorithms/tests/test_core.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -72,7 +72,9 @@ def test_core_number2(self):
def test_core_number_self_loop(self):
G = nx.cycle_graph(3)
G.add_edge(0, 0)
with pytest.raises(nx.NetworkXError, match="Input graph has self loops"):
with pytest.raises(
nx.NetworkXNotImplemented, match="Input graph has self loops"
):
nx.core_number(G)

def test_directed_core_number(self):
Expand Down Expand Up @@ -166,6 +168,14 @@ def test_k_truss(self):
k_truss_subgraph = nx.k_truss(self.G, 5)
assert sorted(k_truss_subgraph.nodes()) == []

def test_k_truss_self_loop(self):
G = nx.cycle_graph(3)
G.add_edge(0, 0)
with pytest.raises(
nx.NetworkXNotImplemented, match="Input graph has self loops"
):
nx.k_truss(G, k=1)

def test_onion_layers(self):
layers = nx.onion_layers(self.G)
nodes_by_layer = [
Expand All @@ -181,5 +191,7 @@ def test_onion_layers(self):
def test_onion_self_loop(self):
G = nx.cycle_graph(3)
G.add_edge(0, 0)
with pytest.raises(nx.NetworkXError, match="Input graph contains self loops"):
with pytest.raises(
nx.NetworkXNotImplemented, match="Input graph contains self loops"
):
nx.onion_layers(G)