Source code for graphscope.analytical.app.attribute_assortativity

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# Copyright 2020 Alibaba Group Holding Limited. All Rights Reserved.
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
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# Author: Ning Xin
#


from graphscope.framework.app import AppAssets
from graphscope.framework.app import not_compatible_for
from graphscope.framework.app import project_to_simple

__all__ = ["attribute_assortativity_coefficient", "numeric_assortativity_coefficient"]


@project_to_simple
@not_compatible_for("arrow_property")
def attribute_assortativity_coefficient(graph, attribute):
    """Compute assortativity for node attributes.

    Assortativity measures the similarity of connections in the graph with
    respect to the given attribute.

    Args:
        graph (:class:`graphscope.Graph`): A simple graph.
        attribute (str): Node attribute key.

    Returns:
        r (float): Assortativity of graph for given attribute

    Notes:
        This computes Eq. (2) in Ref. [1]_ , (trace(M)-sum(M^2))/(1-sum(M^2)),
        where M is the joint probability distribution (mixing matrix)
        of the specified attribute.

    References:
        [1] M. E. J. Newman, Mixing patterns in networks, Physical Review E, 67 026126, 2003

    Examples:

    .. code:: python

        >>> import graphscope
        >>> from graphscope.dataset import load_modern_graph
        >>> sess = graphscope.session(cluster_type="hosts", mode="eager")
        >>> g = load_modern_graph(sess)
        >>> g.schema
        >>> c = graphscope.attribute_assortativity_coefficient(g, attribute="name")
        >>> sess.close()
    """
    ctx = AppAssets(algo="attribute_assortativity_coefficient", context="tensor")(
        graph, False
    )
    return ctx.to_numpy("r", axis=0)[0]


@project_to_simple
@not_compatible_for("arrow_property")
def numeric_assortativity_coefficient(graph, attribute):
    """Compute assortativity for numerical node attributes.

    Assortativity measures the similarity of connections
    in the graph with respect to the given numeric attribute.

    Args:
        graph (:class:`graphscope.Graph`): A simple graph.
        attribute (str): Node attribute key.

    Returns:
        r (float): Assortativity of graph for given attribute

    Examples
    --------
    .. code:: python

        >>> import graphscope
        >>> from graphscope.dataset import load_modern_graph
        >>> sess = graphscope.session(cluster_type="hosts", mode="eager")
        >>> g = load_modern_graph(sess)
        >>> g.schema
        >>> c = graphscope.numeric_assortativity_coefficient(g, attribute="name")
        >>> sess.close()

    Notes
    -----
    This computes Eq. (21) in Ref. [1]_ , for the mixing matrix
    of the specified attribute.

    References
    ----------
    .. [1] M. E. J. Newman, Mixing patterns in networks
           Physical Review E, 67 026126, 2003
    """

    ctx = AppAssets(algo="attribute_assortativity_coefficient", context="tensor")(
        graph, True
    )
    return ctx.to_numpy("r", axis=0)[0]