TABLE OF CONTENTS


TEMANEJO_GRAPHBASECLASS

[ Top ] [ TEMANEJO ] [ Modules ]

NAME

temanejo_graphBaseclass - provides the base class for *Ss' task graph class

DESCRIPTION

temanejo_graphBaseclass.py implements the base class for the graph data structure implemented in temanejo_graph.py

PORTABILITY

The following modules are imported:

AUTHOR

Steffen Brinkmann, HLRS <brinkmann@hlrs.de>

COPYRIGHT

(C) HLRS, University of Stuttgart temanejo_graphBaseclass.py is published under the terms of the BSD license. temanejo_graphBaseclass.py is based on NetworkX with the following copyright statement:

     Copyright (C) 2004-2009 by
     Aric Hagberg <hagberg@lanl.gov>
     Dan Schult <dschult@colgate.edu>
     Pieter Swart <swart@lanl.gov>
     All rights reserved.
     BSD license.


Graph

[ Top ] [ TEMANEJO_GRAPHBASECLASS ] [ Classes ]

NAME

Graph - base class for undirected graphs

DESCRIPTION

Base class for undirected graphs.

A Graph stores nodes and edges with optional data, or attributes.

Graphs hold undirected edges. Self loops are allowed but multiple (parallel) edges are not.

Nodes can be arbitrary (hashable) Python objects with optional key/value attributes.

Edges are represented as links between nodes with optional key/value attributes.

DERIVED FROM

   object

INPUTS

data : input graph

        Data to initialize graph.  If data=None (default) an empty
        graph is created.  The data can be an edge list, or any
        NetworkX graph object.  If the corresponding optional Python
        packages are installed the data can also be a NumPy matrix
        or 2d ndarray, a SciPy sparse matrix, or a PyGraphviz graph.
    name : string, optional (default='')
        An optional name for the graph.
    attr : keyword arguments, optional (default= no attributes)
        Attributes to add to graph as key=value pairs.

SEE ALSO

DiGraph MultiGraph MultiDiGraph (of module NetworkX)

EXAMPLE

    Create an empty graph structure (a "null graph") with no nodes and
    no edges.

    >>> G = nx.Graph()

    G can be grown in several ways.

    **Nodes:**

    Add one node at a time:

    >>> G.add_node(1)

    Add the nodes from any container (a list, dict, set or
    even the lines from a file or the nodes from another graph).

    >>> G.add_nodes_from([2,3])
    >>> G.add_nodes_from(range(100,110))
    >>> H=nx.Graph()
    >>> H.add_path([0,1,2,3,4,5,6,7,8,9])
    >>> G.add_nodes_from(H)

    In addition to strings and integers any hashable Python object
    (except None) can represent a node, e.g. a customized node object,
    or even another Graph.

    >>> G.add_node(H)

    **Edges:**

    G can also be grown by adding edges.

    Add one edge,

    >>> G.add_edge(1, 2)

    a list of edges,

    >>> G.add_edges_from([(1,2),(1,3)])

    or a collection of edges,

    >>> G.add_edges_from(H.edges())

    If some edges connect nodes not yet in the graph, the nodes
    are added automatically.  There are no errors when adding
    nodes or edges that already exist.

    **Attributes:**

    Each graph, node, and edge can hold key/value attribute pairs
    in an associated attribute dictionary (the keys must be hashable).
    By default these are empty, but can be added or changed using
    add_edge, add_node or direct manipulation of the attribute
    dictionaries named graph, node and edge respectively.

    >>> G = nx.Graph(day="Friday")
    >>> G.graph
    {'day': 'Friday'}

    Add node attributes using add_node(), add_nodes_from() or G.node

    >>> G.add_node(1, time='5pm')
    >>> G.add_nodes_from([3], time='2pm')
    >>> G.node[1]
    {'time': '5pm'}
    >>> G.node[1]['room'] = 714
    >>> G.nodes(data=True)
    [(1, {'room': 714, 'time': '5pm'}), (3, {'time': '2pm'})]

    Warning: adding a node to G.node does not add it to the graph.

    Add edge attributes using add_edge(), add_edges_from(), subscript
    notation, or G.edge.

    >>> G.add_edge(1, 2, weight=4.7 )
    >>> G.add_edges_from([(3,4),(4,5)], color='red')
    >>> G.add_edges_from([(1,2,{'color':'blue'}), (2,3,{'weight':8})])
    >>> G[1][2]['weight'] = 4.7
    >>> G.edge[1][2]['weight'] = 4

    **Shortcuts:**

    Many common graph features allow python syntax to speed reporting.

    >>> 1 in G     # check if node in graph
    True
    >>> [n for n in G if n<3]   # iterate through nodes
    [1, 2]
    >>> len(G)  # number of nodes in graph
    5
    >>> G[1] # adjacency dict keyed by neighbor to edge attributes
    ...            # Note: you should not change this dict manually!
    {2: {'color': 'blue', 'weight': 4}}

    The fastest way to traverse all edges of a graph is via
    adjacency_iter(), but the edges() method is often more convenient.

    >>> for n,nbrsdict in G.adjacency_iter():
    ...     for nbr,eattr in nbrsdict.items():
    ...        if 'weight' in eattr:
    ...            (n,nbr,eattr['weight'])
    (1, 2, 4)
    (2, 1, 4)
    (2, 3, 8)
    (3, 2, 8)
    >>> [ (u,v,edata['weight']) for u,v,edata in G.edges(data=True) if 'weight' in edata ]
    [(1, 2, 4), (2, 3, 8)]

    **Reporting:**

    Simple graph information is obtained using methods.
    Iterator versions of many reporting methods exist for efficiency.
    Methods exist for reporting nodes(), edges(), neighbors() and degree()
    as well as the number of nodes and edges.

METHODS

   __init__

NetworkXError

[ Top ] [ TEMANEJO_GRAPHBASECLASS ] [ Classes ]

NAME

NetworkXError - generic error exception for NetworkX

DESCRIPTION

Error exception class for NetworkX

DERIVED FROM

   NetworkXException

NetworkXException

[ Top ] [ TEMANEJO_GRAPHBASECLASS ] [ Classes ]

NAME

NetworkXException - Exception base class for NetworkX

DESCRIPTION

Exception base class fro NetworkX

DERIVED FROM

   Exception

pygraphviz_layout

[ Top ] [ TEMANEJO_GRAPHBASECLASS ] [ Functions ]

NAME

pygraphviz_layout - layout the graph

DESCRIPTION

This creates node positions for G using Graphviz.

INPUTS

G : NetworkX graph

     A graph created with NetworkX

prog : string

     Name of Graphviz layout program

root : string, optional

     Root node for twopi layout

args : string, optional

     Extra arguments to Graphviz layout program

OUTPUT

   Dictionary of x,y, positions keyed by node.

EXAMPLE

   >>> G=nx.petersen_graph()
   >>> pos=nx.graphviz_layout(G)
   >>> pos=nx.graphviz_layout(G,prog='dot')

to_agraph

[ Top ] [ TEMANEJO_GRAPHBASECLASS ] [ Functions ]

NAME

to_agraph - Return a pygraphviz graph from a NetworkX graph N

DESCRIPTION

This function returns a pygraphviz graph from a NetworkX graph N. It is needed in pygraphviz_layout

INPUTS

N : NetworkX graph

       A graph created with NetworkX

EXAMPLE

   >>> K5=nx.complete_graph(5)
   >>> A=nx.to_agraph(K5)

NOTES

   If N has an dict N.graph_attr an attempt will be made first
   to copy properties attached to the graph (see from_agraph)
   and then updated with the calling arguments if any.

write_dot

[ Top ] [ TEMANEJO_GRAPHBASECLASS ] [ Functions ]

NAME

write_dot - Return a pygraphviz graph from a NetworkX graph N

DESCRIPTION

This function returns a pygraphviz graph from a NetworkX graph N. It is needed in pygraphviz_layout

INPUTS

N : NetworkX graph

       A graph created with NetworkX

EXAMPLE

   >>> K5=nx.complete_graph(5)
   >>> A=nx.to_agraph(K5)

NOTES

   If N has an dict N.graph_attr an attempt will be made first
   to copy properties attached to the graph (see from_agraph)
   and then updated with the calling arguments if any.