xgi.stats.diedgestats#

Directed edge statistics.

This module is part of the stats package, and it defines edge-level statistics. That is, each function defined in this module is assumed to define an edge-quantity mapping. Each callable defined here is accessible via a Network object, or a DiEdgeView object. For more details, see the tutorial.

Examples

>>> import xgi
>>> H = xgi.DiHypergraph([[{1, 2}, {5, 6}], [{4}, {1, 3}]])
>>> H.order()
{0: 3, 1: 2}
>>> H.edges.order.asdict()
{0: 3, 1: 2}

Functions

attrs(net, bunch, attr=None, missing=None)[source]#

Access edge attributes.

Parameters:

  • net (xgi.Hypergraph) – The network.

  • bunch (Iterable) – Nodes in net.

  • attr (str | None (default)) – If None, return all attributes. Otherwise, return a single attribute with name attr.

  • missing (Any) – Value to impute in case an edge does not have an attribute with name attr. Default is None.

Returns:

If attr is None, return a nested dict of the form {edge: {“attr”: val}}. Otherwise, return a simple dict of the form {edge: val}.

Return type:

dict

Notes

When requesting all attributes (i.e. when attr is None), no value is imputed.

Examples

>>> import xgi
>>> H = xgi.DiHypergraph()
>>> edges = [
...     ([{0, 1}, {2, 4}], 'one', {'color': 'red'}),
...     ([{1, 2}, {2, 0}], 'two', {'color': 'black', 'age': 30}),
...     ([{2, 3, 4}, {1}], 'three', {'color': 'blue', 'age': 40}),
... ]
>>> H.add_edges_from(edges)

Access all attributes as different types.

>>> H.edges.attrs.asdict() 
{'one': {'color': 'red'},
 'two': {'color': 'black', 'age': 30},
 'three': {'color': 'blue', 'age': 40}}
>>> H.edges.attrs.asnumpy() 
array([{'color': 'red'},
       {'color': 'black', 'age': 30},
       {'color': 'blue', 'age': 40}],
       dtype=object)

Access a single attribute as different types.

>>> H.edges.attrs('color').asdict()
{'one': 'red', 'two': 'black', 'three': 'blue'}
>>> H.edges.attrs('color').aslist()
['red', 'black', 'blue']

By default, None is imputed when a node does not have the requested attribute.

>>> H.edges.attrs('age').asdict()
{'one': None, 'two': 30, 'three': 40}

Use missing to change the imputed value.

>>> H.edges.attrs('age', missing=100).asdict()
{'one': 100, 'two': 30, 'three': 40}
order(net, bunch, degree=None)[source]#

Edge order.

The order of a directed edge is the number of nodes contained in the union of the head and the tail minus 1.

Parameters:

  • net (xgi.Hypergraph) – The network.

  • bunch (Iterable) – Edges in net.

  • degree (int | None) – If not None (default), count only those member nodes with the specified degree.

Return type:

dict

See also

size

Examples

>>> import xgi
>>> H = xgi.DiHypergraph([[{1, 2}, {5, 6}], [{4}, {1, 3}]])
>>> H.edges.order.asdict()
{0: 3, 1: 2}
size(net, bunch, degree=None)[source]#

Edge size.

The size of a directed edge is the number of nodes contained in the union of the head and the tail.

Parameters:

  • net (xgi.Hypergraph) – The network.

  • bunch (Iterable) – Edges in net.

Return type:

dict

See also

order

Examples

>>> import xgi
>>> H = xgi.DiHypergraph([[{1, 2}, {5, 6}], [{4}, {1, 3}]])
>>> H.edges.size.asdict()
{0: 4, 1: 3}
head_order(net, bunch, degree=None)[source]#

Head order.

The order of the head is the number of nodes it contains minus 1.

Parameters:

  • net (xgi.Hypergraph) – The network.

  • bunch (Iterable) – Edges in net.

Return type:

dict

See also

order

Examples

>>> import xgi
>>> H = xgi.DiHypergraph([[{1, 2}, {5, 6}], [{4}, {1, 3}]])
>>> H.edges.head_order.asdict()
{0: 1, 1: 1}
head_size(net, bunch, degree=None)[source]#

Head size.

The size of the head is the number of nodes it contains.

Parameters:

  • net (xgi.Hypergraph) – The network.

  • bunch (Iterable) – Edges in net.

Return type:

dict

See also

order

Examples

>>> import xgi
>>> H = xgi.DiHypergraph([[{1, 2}, {5, 6}], [{4}, {1, 3}]])
>>> H.edges.head_size.asdict()
{0: 2, 1: 2}
tail_order(net, bunch, degree=None)[source]#

Tail order.

The order of the tail is the number of nodes it contains minus 1.

Parameters:

  • net (xgi.Hypergraph) – The network.

  • bunch (Iterable) – Edges in net.

Return type:

dict

See also

order

Examples

Examples

>>> import xgi
>>> H = xgi.DiHypergraph([[{1, 2}, {5, 6}], [{4}, {1, 3}]])
>>> H.edges.tail_order.asdict()
{0: 1, 1: 0}
tail_size(net, bunch, degree=None)[source]#

Tail size.

The size of the tail is the number of nodes it contains.

Parameters:

  • net (xgi.Hypergraph) – The network.

  • bunch (Iterable) – Edges in net.

Return type:

dict

See also

order

Examples

>>> import xgi
>>> H = xgi.DiHypergraph([[{1, 2}, {5, 6}], [{4}, {1, 3}]])
>>> H.edges.tail_size.asdict()
{0: 2, 1: 1}