Graph annotate_weighted_degrees

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annotate_weighted_degrees(self, output_property_name, degree_option=None, input_edge_labels=None, edge_weight_property=None, edge_weight_default=None)

Calculates the weighted degree of each vertex with respect to an (optional) set of labels.

Parameters:

output_property_name : unicode

property name of where to store output

degree_option : unicode (default=None)

choose from ‘out’, ‘in’, ‘undirected’

input_edge_labels : list (default=None)

labels of edge types that should be included

edge_weight_property : unicode (default=None)

property name of edge weight, if not provided all edges are weighted equally

edge_weight_default : float64 (default=None)

default edge weight

Returns:

: dict

Pulls graph from underlying store, calculates weighted degrees and writes them into the property specified, and then writes the output graph to the underlying store.

Degree Calculation

A fundamental quantity in graph analysis is the degree of a vertex: The degree of a vertex is the number of edges adjacent to it.

For a directed edge relation, a vertex has both an out-degree (the number of edges leaving the vertex) and an in-degree (the number of edges entering the vertex).

The toolkit provides a routine annotate_degrees for calculating the degrees of vertices. The Trusted Analytics Platform routine annotate_degrees can be executed at distributed scale.

In the presence of edge weights, vertices can have weighted degrees: The weighted degree of a vertex is the sum of weights of edges adjacent to it. Analogously, the weighted in-degree of a vertex is the sum of the weights of the edges entering it, and the weighted out-degree is the sum of the weights of the edges leaving the vertex.

The toolkit provides this routine for the distributed calculation of weighted vertex degrees.

Examples

>>> graph = ta.Graph()

>>> graph.define_vertex_type('source')
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>>> graph.vertices['source'].add_vertices(vertex_frame, 'source', 'label')
[===Job Progress===]
>>> graph.define_edge_type('edges','source', 'source', directed=False)
[===Job Progress===]
>>> graph.edges['edges'].add_edges(edge_frame, 'source', 'dest', ['weight'])
[===Job Progress===]
>>> result = graph.annotate_weighted_degrees("outEdgesCount",edge_weight_property="weight", degree_option="out")
[===Job Progress===]
>>> result['source'].inspect()
[#]  _vid  _label  source  label  outEdgesCount
===============================================
[0]     1  source       1    1.0            3.0
[1]     2  source       2    1.0            2.0
[2]     3  source       3    5.0            2.0
[3]     4  source       4    5.0            2.0
[4]     5  source       5    5.0            1.0
>>> result = graph.annotate_weighted_degrees("inEdgesCount",edge_weight_property="weight", degree_option="in")
[===Job Progress===]
>>> result['source'].inspect()
[#]  _vid  _label  source  label  inEdgesCount
==============================================
[0]     1  source       1    1.0           3.0
[1]     2  source       2    1.0           2.0
[2]     3  source       3    5.0           2.0
[3]     4  source       4    5.0           2.0
[4]     5  source       5    5.0           1.0