#sample code

#import _2_time_based_data_network_feature

#cite_year_divider_in_path = "../2.processed_data/"

#cite_year_divider_out_path = "../3.time_based_data/1.cite_relation_devide/"

#_2_time_based_data_network_feature.cite_year_divider(cite_year_divider_in_path, cite_year_divider_out_path)

#연도별로 인용 링크를 나누어준다.

#363초 걸림

start_time = time.time()

temp_start_time = time.time()

print "============= cite_year_divider start =============="

print "============= from 1951 to 2015 =============="

f_in_1 = open(in_path + "all_cite.txt","r")

f_in_2 = open(in_path + "all_id_year_title.txt", "r")

t_year = f_in_2.readlines()

t_cite = f_in_1.readlines()

f_in_1.close()

f_in_2.close()

item_id = {}

for i in t_year:

t = i.split("|")

item = t[0].strip()

year = int(t[1])

item_id[item] = year

f_error = open("cite_year_divider_error.txt","w")

for i in range(1951, 2016):

print i

f_out = open(out_path +str(i) + "_cite.csv","w")

f_out.write("Source,Target\n")

for j in t_cite:

tt = j.split(",")

source = tt[0].strip()

target = tt[1].strip()

if (source in item_id and target in item_id):

if (item_id[source] <= i and item_id[target] <=i):

f_out.write(str(source) + ","+ str(target) + "\n")

else:

print "error"

f_error.write(str(target) + "," +str(target)+"\n")

f_out.close()

print "============= cite_year_divider end =============="

print("takes %s seconds" % (time.time() - temp_start_time))

#연도별 중심성을 저장하는 Dump를 초기화해주는 코드라 한다.

global Dump

f_in = open(in_path + "2015_cite.csv", "r")

lines = f_in.readlines()

for line in lines:

data = line.split(",")

Dump[data[0].strip()] = {}

#sample code

#import _2_time_based_data_network_feature

#make_net_in_path = "../3.time_based_data/1.cite_relation_devide/"

#make_net_out_path = "../3.time_based_data/2.centrality_data/"

#_2_time_based_data.make_net( "in_degree", make_net_in_path, make_net_out_path)

#네트워크를 만들고 Centurality를 계산하고 저장할 것이다.

import networkx as nx

global Dump

Dump = {}

make_net_initialize(in_path)

start_time = time.time()

temp_start_time = time.time()

print "============= make_net start:" + centrality_name + " =============="

print "============= from 1951 to 2015 =============="

for year in range(1951, 2016):

print year

f_in = open(in_path + str(year) + "_cite.csv","r")

lines = f_in.readlines()

f_in.close()

edge_list = []

for line in lines:

data = line.split(",")

data_tuple = (data[0].strip(), data[1].strip())

edge_list.append(data_tuple)

Net = nx.DiGraph(edge_list)

Cen_in = {}

if (centrality_name == "in_degree"):

Cen_in = nx.in_degree_centrality(Net)

elif (centrality_name == "degree"):

Cen_in = nx.degree_centrality(Net)

elif (centrality_name == "eigenvector"):

Cen_in = nx.eigenvector_centrality_numpy(Net)

elif (centrality_name == "katz"):

Cen_in = nx.katz_centrality(Net)

elif (centrality_name == "pagerank"):

Cen_in = nx.pagerank(Net)

elif (centrality_name == "communicability"):

Net = nx.Graph(edge_list)

Cen_in = nx.communicability_centrality(Net)

elif (centrality_name == "load"):

Cen_in = nx.load_centrality(Net)

for j in Cen_in:

key = j

val = Cen_in[j]

Dump[key][year] = val

#저장하는 코드

f_out = open(out_path + centrality_name +"_centrality.csv", "w")

for key in Dump:

line = str(key)

for year in range(1951, 2016):

data = Dump[key].get(year, 0)

line = line + ","+ str(data)

line = line + "\n"

f_out.write(line)

f_out.close()

print "============= make_net end =============="

print(centrality_name + "takes %s seconds" % (time.time() - temp_start_time))

#아직 안돌림 나중에 계산 다 되면 돌려야 함

#load centrality, communicatability계산되면 돌릴 것

#해당 연도까지의 max, slope, sum 값을 모아서 저장한다.

#sample code

#import _2_time_based_data_network_feature

#centrality_maker_in_path = "../3.time_based_data/2.centrality_data/"

#centrality_maker_out_path = "../3.time_based_data/3.centrality_feature_data/"

#_2_time_based_data.make_cited_count_sheet(centrality_maker_in_path,centrality_maker_out_path)

start_time = time.time()

year = year - 1936 + 1

#id 공간 때문에 + 1

file_name = ["in_degree_centrality",

"degree_centrality",

"load_centrality",

"communicability_centrality",

"pagerank_centrality"]

for name in file_name:

list_id = []

list_max = []

list_sum = []

list_slope = []

f = open("./4.centrality_data/"+name+".csv", "r")

lines = csv.reader(f)

for line in lines:

val = map(float, line)

val_slope = val[1]

for v in val[2:year]:

val_slope = max(val_slope,v-val_slope)

val_id = int(val[0])

val_max = max(val[1:year])

val_sum = sum(val[1:year])

list_id.append(val_id)

list_max.append(0-val_max)

list_sum.append(0-val_sum)

list_slope.append(0-val_slope)

rank_max = rankdata(list_max)

rank_sum = rankdata(list_sum)

rank_slope = rankdata(list_slope)

#print str(len(rank_max)) +" " + str(len(rank_sum)) +" " + str(len(rank_slope))

f_out_1 = open(out_path+name+"_max.csv","w")

f_out_2 = open(out_path+name+"_sum.csv","w")

f_out_3 = open(out_path+name+"_slope.csv", "w")

cnt = 0

for i in rank_max:

f_out_1.write(str(list_id[cnt]) +","+ str(i) + "\n")

cnt = cnt + 1

cnt =0

for i in rank_sum:

f_out_2.write(str(list_id[cnt]) +","+ str(i) + "\n")

cnt = cnt + 1

cnt =0

for i in rank_slope:

f_out_3.write(str(list_id[cnt]) +","+ str(i) + "\n")

cnt = cnt + 1

cnt =0

print("centrality_maker takes %s seconds" % (time.time() - start_time))