Source code for openpnm.io._networkx

import logging
import numpy as np
logger = logging.getLogger(__name__)



[docs]
def network_from_networkx(G):
    r"""
    Creates an OpenPNM Network from a undirected NetworkX graph object

    Parameters
    ----------
    G : networkx.classes.graph.Graph Object
        The NetworkX graph. G should be undirected. The numbering of nodes
        should be numeric (int's), zero-based and should not contain any
        gaps, i.e. ``G.nodes() = [0,1,3,4,5]`` is not allowed and should be
        mapped to ``G.nodes() = [0,1,2,3,4]``.

    Returns
    -------
    network : dict
        An OpenPNM network dictionary

    Notes
    -----
    1. Each node in a NetworkX object (i.e. ``G``) can be assigned properties
    using syntax like ``G.node[n]['diameter'] = 0.5`` where ``n`` is the
    node number.  There is no need to precede the property name with any
    indication that it is pore data such as \'pore\_\'.  OpenPNM will prepend
    \'pore.\' to each property name.

    2. Since \'pore.coords\' is so central to OpenPNM it should be specified
    in the NetworkX object as \'coords\', and the [X, Y, Z] coordinates of
    each node should be a 1x3 list.

    3. Edges in a NetworkX object are accessed using the index numbers of the
    two nodes it connects, such as ``G.adj[2][3]['length'] = 0.1``
    indicating the edge that connects nodes 2 and 3.  There is no need to
    precede the property name with any indication that it is throat data such
    as \'throat\_\'.  OpenPNM will prepend \'throat.\' to each property name.

    4. The \'throat.conns\' property is essential to OpenPNM, but this does NOT
    need to be specified explicitly as a property in NetworkX.  The
    connectivity is embedded into the network representation and is extracted
    by OpenPNM.

    """
    import networkx as nx
    from openpnm.network import Network

    net = {}

    # Ensure G is an undirected networkX graph with numerically numbered
    # nodes for which numbering starts at 0 and does not contain any gaps
    if not isinstance(G, nx.Graph):  # pragma: no cover
        raise Exception('Provided object is not a NetworkX graph.')
    if nx.is_directed(G):  # pragma: no cover
        raise Exception('Provided graph is directed. Convert to undirected graph.')
    if not all(isinstance(n, int) for n in G.nodes()):  # pragma: no cover
        raise Exception('Node numbering is not numeric. Convert to int.')
    if min(G.nodes()) != 0:  # pragma: no cover
        raise Exception('Node numbering does not start at zero.')
    if max(G.nodes()) + 1 != len(G.nodes()):  # pragma: no cover
        raise Exception('Node numbering contains gaps. Map nodes to remove gaps.')

    # Parsing node data
    Np = len(G)
    net.update({'pore.all': np.ones((Np,), dtype=bool)})
    for n, props in G.nodes(data=True):
        for item in props.keys():
            val = props[item]
            dtype = type(val)
            # Remove prepended pore. and pore_ if present
            for b in ['pore.', 'pore_']:
                item = item.replace(b, '')
            # Create arrays for subsequent indexing, if not present already
            if 'pore.'+item not in net.keys():
                if dtype == str:  # handle strings of arbitrary length
                    net['pore.'+item] = np.ndarray((Np,), dtype='object')
                elif dtype is list:
                    dtype = type(val[0])
                    if dtype == str:
                        dtype = 'object'
                    cols = len(val)
                    net['pore.'+item] = np.ndarray((Np, cols), dtype=dtype)
                else:
                    net['pore.'+item] = np.ndarray((Np,), dtype=dtype)
            net['pore.'+item][n] = val

    # Parsing edge data
    # Deal with conns explicitly
    try:
        conns = list(G.edges)   # NetworkX V2
    except Exception:  # pragma: no cover
        conns = G.edges()       # NetworkX V1
    conns.sort()

    # Add conns to Network
    Nt = len(conns)
    net.update({'throat.all': np.ones(Nt, dtype=bool)})
    net.update({'throat.conns': np.array(conns)})

    # Scan through each edge and extract all its properties
    i = 0
    for t in conns:
        props = G[t[0]][t[1]]
        for item in props:
            val = props[item]
            dtype = type(val)
            # Remove prepended throat. and throat_ if present
            for b in ['throat.', 'throat_']:
                item = item.replace(b, '')
            # Create arrays for subsequent indexing, if not present already
            if 'throat.'+item not in net.keys():
                if dtype == str:
                    net['throat.'+item] = np.ndarray((Nt,), dtype='object')
                if dtype is list:
                    dtype = type(val[0])
                    if dtype == str:
                        dtype = 'object'
                    cols = len(val)
                    net['throat.'+item] = np.ndarray((Nt, cols),
                                                     dtype=dtype)
                else:
                    net['throat.'+item] = np.ndarray((Nt,), dtype=dtype)
            net['throat.'+item][i] = val
        i += 1

    network = Network()
    network.update(net)
    return network




[docs]
def network_to_networkx(network):
    r"""
    Write OpenPNM Network to a NetworkX object.

    Parameters
    ----------
    network : dict
        The OpenPNM Network to be converted to a NetworkX object

    Returns
    -------
    G : undirected graph object
        A NetworkX object with all pore/throat properties attached to it
    """
    import networkx as nx
    from openpnm.network import Network

    # Ensure network is an Network.
    if not isinstance(network, Network):  # pragma: no cover
        raise Exception('Provided network is not an OpenPNM Network.')

    G = nx.Graph()

    # Extracting node list and connectivity matrix from Network
    nodes = map(int, network.Ps)
    conns = network['throat.conns']

    # Explicitly add nodes and connectivity matrix
    G.add_nodes_from(nodes)
    G.add_edges_from(conns)

    # Attach Network properties to G
    for prop in network.props() + network.labels():
        if 'pore.' in prop:
            if len(network[prop].shape) > 1:
                val = {i: list(network[prop][i]) for i in network.Ps}
            else:
                val = {i: network[prop][i] for i in network.Ps}
            nx.set_node_attributes(G, name=prop[5:], values=val)
        if 'throat.' in prop:
            val = {tuple(conn): network[prop][i] for i, conn
                   in enumerate(conns)}
            nx.set_edge_attributes(G, name=prop[7:], values=val)

    return G