import os
import sys
import time
import numpy as np
import pandas as pd
import networkx as nx
import frovedis.graph as fnx
from collections import OrderedDict

input_graph_files = {
    'preferentialAttachment' : './preferentialAttachment.mtx',
    'caidaRouterLevel'       : './caidaRouterLevel.mtx',
    'coAuthorsDBLP'          : './coAuthorsDBLP.mtx',
    'dblp'                   : './dblp-2010.mtx',
    'citationCiteseer'       : './citationCiteseer.mtx',
    'coPapersDBLP'           : './coPapersDBLP.mtx',
    'coPapersCiteseer'       : './coPapersCiteseer.mtx',
    'as-Skitter'             : './as-Skitter.mtx'
}

# -------- Graph loading demo --------
frov_data_loading_time = []
nx_data_loading_time = []
frov_graph = []
frov_graph_dir = []
nx_graph = []
nx_graph_dir = []
nnodes = []
nedges = []

for dataset, path in input_graph_files.items():    
    dl_start_time = time.time()
    fgraph = fnx.read_edgelist(path, nodetype=np.int32, delimiter=' ')
    # pagerank等において良好なランキング結果を得るため有方向グラフを使用
    fgraph_dir = fnx.read_edgelist(path, nodetype=np.int32, delimiter=' ', \
                                   create_using=nx.DiGraph())
    frov_data_loading_time.append(round(time.time() - dl_start_time, 4))
    frov_graph.append(fgraph)
    frov_graph_dir.append(fgraph_dir)

    dl_start_time = time.time()
    ngraph = nx.read_edgelist(path, nodetype=np.int32, delimiter=' ')
    # pagerank等において良好なランキング結果を得るため有方向グラフを使用
    ngraph_dir = nx.read_edgelist(path, nodetype=np.int32, delimiter=' ', \
                                  create_using=nx.DiGraph())
    nx_data_loading_time.append(round(time.time() - dl_start_time, 4))
    nx_graph.append(ngraph)
    nx_graph_dir.append(ngraph_dir)

    nnodes.append(ngraph.number_of_nodes())
    nedges.append(ngraph.number_of_edges())

src = 5
frov_sssp_time = []
nx_sssp_time = []
dist_matched = []

for i in range(len(frov_graph)):
    start_time = time.time()
    fpath, fdist = fnx.single_source_shortest_path(frov_graph[i], \
                   src, return_distance=True)
    frov_sssp_time.append(round(time.time() - start_time, 4))

    start_time = time.time()
    npath = nx.single_source_shortest_path(nx_graph[i], src)
    nx_sssp_time.append(round(time.time() - start_time, 4))

    ndist = {k: float(len(v)-1) for k, v in npath.items()}

    dist_matched.append("Yes" if fdist == ndist else "No")

frov_pr_time = []
nx_pr_time = []
order_matched = []

#pagerankにおいて良好なランキング結果を得るため有方向グラフを使用
for i in range(len(frov_graph_dir)):
    start_time = time.time()
    frov_ranks = fnx.pagerank(frov_graph_dir[i])
    frov_pr_time.append(round(time.time() - start_time, 4))
    df1 = pd.DataFrame({ "node": list(frov_ranks.keys()),
                         "rank": list(frov_ranks.values())
                       }) \
            .sort_values(by = ["rank", "node"]) \
            .head(10)

    start_time = time.time()
    nx_ranks = nx.pagerank(nx_graph_dir[i])
    nx_pr_time.append(round(time.time() - start_time, 4))
    df2 = pd.DataFrame({ "node": list(nx_ranks.keys()),
                         "rank": list(nx_ranks.values())
                       }) \
            .sort_values(by = ["rank", "node"]) \
            .head(10)
    order_matched.append("Yes" if list(df1.node.values) == list(df2.node.values) else "No")

source = 1
distance = 4 
frov_bfs_time = []
nx_bfs_time = []
result_matched = []

for i in range(len(frov_graph)):
    start_time = time.time()
    frov_res = fnx.descendants_at_distance(frov_graph[i], source, distance)
    frov_bfs_time.append(round(time.time() - start_time, 4))

    start_time = time.time()
    nx_res = nx.descendants_at_distance(nx_graph[i], source, distance)
    nx_bfs_time.append(round(time.time() - start_time, 4))

    result_matched.append("Yes" if len(frov_res - nx_res) == 0 else "No")

frov_cc_time = []
nx_cc_time = []
frov_ncomponents = []
nx_ncomponents = []
result_matched = []

for i in range(len(frov_graph)):
    start_time = time.time()
    tmp = fnx.connected_components(frov_graph[i])
    set_cc_frov = set()
    for elem in tmp:
        set_cc_frov.add(frozenset(elem))
    frov_cc_time.append(round(time.time() - start_time, 4))
    frov_ncomponents.append(len(set_cc_frov))

    start_time = time.time()
    tmp = nx.connected_components(nx_graph[i])
    set_cc_nx = set()
    for elem in tmp:
        set_cc_nx.add(frozenset(elem))
    nx_cc_time.append(round(time.time() - start_time, 4))
    nx_ncomponents.append(len(set_cc_nx))

    result_matched.append("Yes" if set_cc_frov == set_cc_nx else "No")

FrovedisServer.shut_down()