import networkx as nx
import numpy as np

class InfluenceGraph(nx.Graph):
    """
    Inherits from the graph class
    with new init function and other attributes
    """
    def __init__(self, max_proba, *args, **kwargs):
        self.max_proba = max_proba
        super(InfluenceGraph, self).__init__(*args, **kwargs)

    def erdos_init(self, n, p):
        G = nx.erdos_renyi_graph(n, p, directed=True)
        self.add_nodes_from(G.nodes())
        self.add_edges_from(G.edges())

    @property
    def mat(self):
        if not hasattr(self, '_mat'):
            self._mat = (self.max_proba * np.random.rand(len(self), len(self))
                         * nx.adjacency_matrix(self))
        return self._mat

    @property
    def logmat(self):
        if not hasattr(self, '_logmat'):
            self._logmat = np.log(1 - self.mat)
        return self._logmat


def icc_cascade(G, p_init):
    """
    input: graph with prob as edge attr
    returns: 2D boolean matrix with indep. casc.
        where True means node was active at that time step
    p_init: proba that node in seed set
    """
    susceptible = np.ones(G.number_of_nodes(), dtype=bool)
    active = np.random.rand(G.number_of_nodes()) < p_init
    susceptible = susceptible - active
    cascade = []
    while active.any() and susceptible.any():
        cascade.append(active)
        active = np.exp(np.dot(G.logmat, active)) \
                    < np.random.rand(G.number_of_nodes())
        active = active & susceptible
        susceptible = susceptible - active
    return cascade


def concat_cascades(cascades):
    """
    Concatenate list of cascades into matrix
    """


def test():
    """
    unit test
    """
    G = nx.erdos_renyi_graph(1000, 1, directed=True)
    G.logmat = np.zeros((G.number_of_nodes(), G.number_of_nodes()))
    G.mat = G.logmat
    for edge in G.edges(data=True):
        edge[2]['weight'] = .3*np.random.rand()
        G.logmat[edge[0],edge[1]] = np.log(1 - edge[2]["weight"])
        G.mat[edge[0], edge[1]] = edge[2]["weight"]
    import time
    t0 = time.time()
    print len(icc_cascade(G, p_init=.1))
    t1 = time.time()
    print t1 - t0

if __name__ == "__main__":
    test()