import MultiTensor as mt

import numpy as np

import networkx as nx

from argparse import ArgumentParser

import sys

import tools as tl

import time

def main():

inf=10000000000000

err_max=0.0000001

p = ArgumentParser()

p.add_argument('-f', '--folder', type=str, default='')

p.add_argument('-a', '--adj', type=str, default='adjacency.dat')

p.add_argument('-E', '--end_file', type=str, default='.dat')

p.add_argument('-w', '--w_file', type=str, default='w.dat')

p.add_argument('-l', '--L', type=int, default=4)

p.add_argument('-i', '--initialization', type=int, default=0)

p.add_argument('-k', '--K', type=int, default=5)

p.add_argument('-r', '--N_real', type=int, default=1)

p.add_argument('-t', '--maxit', type=int, default=500)

p.add_argument('-e', '--tolerance', type=float,default=0.1)

p.add_argument('-g', '--err', type=float,default=0.1)

p.add_argument('-o','--out_adjacency',type=int,default=0)

p.add_argument('-A','--assortative',type=int,default=0)

p.add_argument('-u','--undirected',type=int,default=0)

p.add_argument('-z', '--rseed', type=int, default=0)

p.add_argument('-y','--decision',type=int,default=2)

args = p.parse_args()

folder="../data/"+args.folder

if(args.undirected==True):A=[ nx.MultiGraph() for l in range(args.L) ] # list of graphs

else:A=[ nx.MultiDiGraph() for l in range(args.L) ] # list of graphs

tl.read_graph(folder,args.adj,A)

print "Undirected=",bool(args.undirected)

print "Assortative=",bool(args.assortative)

tl.print_graph_stat(A,args.undirected)

if(args.out_adjacency):tl.out_graph(folder,A)

if(args.undirected==True):

u_list=v_list=tl.remove_zero_entries_undirected(A)

else:

u_list=tl.remove_zero_entries_u(A) # list of INT INDECES of nodes with zero out degree

v_list=tl.remove_zero_entries_v(A) # list of INT INDECES of nodes with zero in degree

MT=mt.MultiTensor( N=A[0].number_of_nodes(),

L=args.L,K=args.K,

N_real=args.N_real,

tolerance=args.tolerance,

decision=args.decision,

maxit=args.maxit,

rseed=args.rseed,

out_adjacency=bool(args.out_adjacency),

inf=inf,

err_max=err_max,

err=args.err,

initialization=args.initialization,

undirected=bool(args.undirected),

folder=folder,

end_file=args.end_file,

adj=args.adj,

w_file=args.w_file,

assortative=bool(args.assortative)

)

tic = time.clock()

N=A[0].number_of_nodes()

B=np.empty(shape=[args.L,N,N])

for l in range(args.L):B[l,:,:]=nx.to_numpy_matrix(A[l],weight='weight')

MT.cycle_over_realizations(A,B,u_list,v_list)

#tl.print_graph_stat(A)

toc = time.clock()

print "It took ",toc-tic," seconds.";

if __name__ == '__main__':

main()