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# Source code for fnss.topologies.simplemodels

    """
    Generate canonical deterministic topologies
    """
    import networkx as nx
    from fnss.topologies.topology import Topology, DirectedTopology

    __all__ = [
        'ring_topology',
        'line_topology',
        'star_topology',
        'full_mesh_topology',
        'k_ary_tree_topology',
        'dumbbell_topology',
        'chord_topology',
               ]

    def ring_topology(n):
        """
        Return a ring topology of n nodes

        Parameters
        ----------
        n : int
            The number of nodes

        Returns
        -------
        topology : A Topology object
        """
        if not isinstance(n, int):
            raise TypeError('n argument must be of int type')
        if n < 1:
            raise ValueError('n argument must be a positive integer')
        G = Topology(nx.path_graph(n))
        G.add_edge(n-1, 0)
        G.name = "ring_topology(%d)" % (n)
        G.graph['type'] = 'ring'
        return G

    def line_topology(n):
        """
        Return a line topology of n nodes

        Parameters
        ----------
        n : int
            The number of nodes

        Returns
        -------
        topology : A Topology object

        """
        if not isinstance(n, int):
            raise TypeError('n argument must be of int type')
        if n < 1:
            raise ValueError('n argument must be a positive integer')
        G = Topology(nx.path_graph(n))
        G.name = "line_topology(%d)" % (n)
        G.graph['type'] = 'line'
        return G

    def star_topology(n):
        """
        Return a star (a.k.a hub-and-spoke) topology of :math:`n+1` nodes

        The root (hub) node has id 0 while all leaf (spoke) nodes have id
        :math:`(1, n+1)`.

        Each node has the attribute type which can either be *root* (for node 0) or
        *leaf* for all other nodes

        Parameters
        ----------
        n : int
            The number of leaf nodes

        Returns
        -------
        topology : A Topology object
        """
        if not isinstance(n, int):
            raise TypeError('n argument must be of int type')
        if n < 1:
            raise ValueError('n argument must be a positive integer')
        G = Topology(nx.star_graph(n))
        G.name = "star_topology(%d)" % (n)
        G.graph['type'] = 'star'
        G.node[0]['type'] = 'root'
        for v in range(1, n + 1):
            G.node[v]['type'] = 'leaf'
        return G

    def full_mesh_topology(n):
        """
        Return a fully connected mesh topology of n nodes

        Parameters
        ----------
        n : int
            The number of nodes

        Returns
        -------
        topology : A Topology object
        """
        if not isinstance(n, int):
            raise TypeError('n argument must be of int type')
        if n < 1:
            raise ValueError('n argument must be a positive integer')
        G = Topology(nx.complete_graph(n))
        G.name = "full_mesh_topology(%d)" % (n)
        G.graph['type'] = 'full_mesh'
        return G

    def k_ary_tree_topology(k, h):
        """
        Return a balanced k-ary tree topology of with depth h

        Each node has two attributes:
         * type: which can either be *root*, *intermediate* or *leaf*
         * depth:math:`(0, h)` the height of the node in the tree, where 0 is the
           root and h are leaves.

        Parameters
        ----------
        k : int
            The branching factor of the tree
        h : int
            The height or depth of the tree

        Returns
        -------
        topology : A Topology object
        """
        if not isinstance(k, int) or not isinstance(h, int):
            raise TypeError('k and h arguments must be of int type')
        if k <= 1:
            raise ValueError("Invalid k parameter. It should be > 1")
        if h < 1:
            raise ValueError("Invalid h parameter. It should be >=1")
        G = Topology(nx.balanced_tree(k, h))
        G.name = "k_ary_tree_topology(%d,%d)" % (k, h)
        G.graph['type'] = 'tree'
        G.graph['k'] = k
        G.graph['h'] = h
        G.node[0]['type'] = 'root'
        G.node[0]['depth'] = 0
        # Iterate through the tree to assign labels to nodes
        v = 1
        for depth in range(1, h + 1):
            for _ in range(k**depth):
                G.node[v]['depth'] = depth
                if depth == h:
                    G.node[v]['type'] = 'leaf'
                else:
                    G.node[v]['type'] = 'intermediate'
                v += 1
        return G

    def dumbbell_topology(m1, m2):
        """
        Return a dumbbell topology consisting of two star topologies
        connected by a path.

        More precisely, two star graphs :math:`K_{m1}` form the left and right
        bells, and are connected by a path :math:`P_{m2}`.

        The :math:`2*m1+m2`  nodes are numbered as follows.
         * :math:`0,...,m1-1` for the left barbell,
         * :math:`m1,...,m1+m2-1` for the path,
         * :math:`m1+m2,...,2*m1+m2-1` for the right barbell.

        The 3 subgraphs are joined via the edges :math:`(m1-1,m1)` and
        :math:`(m1+m2-1,m1+m2)`. If m2 = 0, this is merely two star topologies
        joined together.

        Please notice that this dumbbell topology is different from the barbell
        graph generated by networkx's barbell_graph function. That barbell graph
        consists of two complete graphs connected by a path. This consists of two
        stars whose roots are connected by a path. This dumbbell topology is
        particularly useful for simulating transport layer protocols.

        All nodes and edges of this topology have an attribute *type* which can be
        either *right bell*, *core* or *left_bell*

        Parameters
        ----------
        m1 : int
            The number of nodes in each bell
        m2 : int
            The number of nodes in the path

        Returns
        -------
        topology : A Topology object
        """
        if not isinstance(m1, int) or not isinstance(m2, int):
            raise TypeError('m1 and m2 arguments must be of int type')
        if m1 < 2:
            raise ValueError("Invalid graph description, m1 should be >= 2")
        if m2 < 1:
            raise ValueError("Invalid graph description, m2 should be >= 1")

        G = Topology(type='dumbbell')
        G.name = "dumbbell_topology(%d,%d)" % (m1, m2)

        # left bell
        G.add_node(m1)
        for v in range(m1):
            G.add_node(v, type='left_bell')
            G.add_edge(v, m1, type='left_bell')

        # right bell
        for v in range(m1):
            G.add_node(v + m1 + m2, type='right_bell')
            G.add_edge(v + m1 + m2, m1 + m2 - 1, type='right_bell')

        # connecting path
        for v in range(m1, m1 + m2 - 1):
            G.node[v]['type'] = 'core'
            G.add_edge(v, v + 1, type='core')
        G.node[m1 + m2 - 1]['type'] = 'core'

        return G

    def chord_topology(m, r=1):
        """Return a Chord topology, as described in [1]_:

        Chord is a Distributed Hash Table (DHT) providing guaranteed correctness.
        In Chord, both nodes and keys are identified by sequences of :math:`m`
        bits. Keys can be resolved in at most :math:`log(n)` steps (with :math:`n`
        being the number of nodes) as long as each node maintains a routing table
        o :math:`n` entries.

        In this implementation, it is possible only to generate topologies with a
        number of nodes :math:`n = 2^m`. where :math:`m` is the length (in bits) of
        the keys used by Chord and also corresponds the the size of the finger
        table kept by each node.

        The :math:`r` argument is the number of nearest successors which can be
        optionally kept at each node to guarantee correctness in case of node
        failures.

        Parameters
        ----------
        m : int
            The length of keys (in bits), which also corresponds to the length of
            the finger table of each node
        r : int, optional
            The length of the nearest successors table

        Returns
        -------
        G : DirectedTopology
            A Chord topology

        References
        ----------
        .. [1] I. Stoica, R. Morris, D. Karger, M. Frans Kaashoek, H. Balakrishnan,
               Chord: A Scalable Peer-to-peer Lookup Service for Internet
               Applications. Proceedings of the ACM SIGCOMM 2001 conference on Data
               communication (SIGCOMM '09). ACM, New York, NY, USA.
        """
        if not isinstance(m, int) or not isinstance(r, int):
            raise TypeError("m and r must be integers")
        if m < 2:
            raise ValueError("m must be an integer >= 2")
        if  r < 1 or r > 2**m - 1:
            raise ValueError("r must be an integer and 1 <= r <= 2^m")
        # n is the number of nodes
        n = 2**m
        G = DirectedTopology()
        for v in range(n):
            for u in range(m):
                G.add_edge(v, (v + 2**u) % n)
        if r > 2:
            for v in range(n):
                for u in range(v + 3, v + r + 1):
                    G.add_edge(v, u % n)
        return G

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