Constructing Quotient Graphs

Collapse
This topic is closed.
X
X
 
  • Time
  • Show
Clear All
new posts
  • BigBaz

    Constructing Quotient Graphs

    If we have a graph G=(N,E), where N is the set of nodes, and E is the
    set of edges. If we partition N into k parts (partition 1, 2,3...k).
    And this partition is given by an array, with the node number as the
    index. For example, C[x]=a means node x is belongs to partition a.

    We define the "Quotient graph" with respect to the above partition as:

    A simple graph with no multiple edges. With the set of nodes 1 to K,
    and the set of edges (i,j) such that for each each edge (u,v) in E
    (the original set of edges in G), there is C[u]=i and C[v]=j.

    In English, the quotient graph is a graph with all the K partition
    numbers as the edges.

    How can I give an algorithm to construct a Quotient Graph from G, with
    running time O(size(N)+size( E)).







  • Kai-Uwe Bux

    #2
    Re: Constructing Quotient Graphs

    BigBaz wrote:
    If we have a graph G=(N,E), where N is the set of nodes, and E is the
    set of edges. If we partition N into k parts (partition 1, 2,3...k).
    And this partition is given by an array, with the node number as the
    index. For example, C[x]=a means node x is belongs to partition a.
    >
    We define the "Quotient graph" with respect to the above partition as:
    >
    A simple graph with no multiple edges. With the set of nodes 1 to K,
    and the set of edges (i,j) such that for each each edge (u,v) in E
    (the original set of edges in G), there is C[u]=i and C[v]=j.
    >
    In English, the quotient graph is a graph with all the K partition
    numbers as the edges.
    >
    How can I give an algorithm to construct a Quotient Graph from G, with
    running time O(size(N)+size( E)).
    a) This is off-topic since it is unrelated to C++.

    b) It also smells like homework.

    c) When posting to a more topical group, you also might want to specify the
    data structure for the graph. If the edges are described as an incidence
    matrix, then the input is a size(N) x size(N) matrix and the result is a
    size(K) x size(K) matrix. So input and output alone will be worse than
    O(size(N)+size( E)).

    d) A book on graph algorithms might be a good start.


    Best

    Kai-Uwe Bux

    Comment

    Working...