#!//anaconda/bin/python

# python bib-graph.py input_file.bib min_year max_year

# Example: python bib-graph.py "../data/Biblio-perso-globale-fr.bib" 2005 2015

import sys

import yapbib.biblist as biblist

import networkx as nx

import matplotlib.pyplot as plt

from networkx.readwrite import json_graph

import os

bibfile_input=sys.argv[1]

min_year_input=int(sys.argv[2])

max_year_input=int(sys.argv[3])

bib_handle=biblist.BibList()

bib_handle.import_bibtex(bibfile_input, normalize=False)

items= bib_handle.List() # Shows the keys of all entries

for year_iter in range(max_year_input, min_year_input-1, -1):

bib_graph=nx.Graph()

pos=dict()

for item_index in items:

item_handle = bib_handle.get_item(item_index)

item_year = int(item_handle.get('year'))

if item_year > year_iter:

continue

for author_index, author_handle in enumerate(item_handle.get_authorsList()[:len(item_handle.get_authorsList())-1]):

clean_author_handle = str(author_handle)

for next_author_index, next_author_handle in enumerate(item_handle.get_authorsList()[author_index+1:]):

clean_next_author_handle = str(next_author_handle)

if bib_graph.get_edge_data(clean_author_handle, clean_next_author_handle, default=0):

bib_graph[clean_author_handle][clean_next_author_handle]['weight'] = bib_graph[clean_author_handle][clean_next_author_handle]['weight'] + 1

else:

bib_graph.add_edge(clean_author_handle, clean_next_author_handle, weight = 1)

# bib_graph is bidirectional but edge list of a node gives only one of the incident edges

for n in bib_graph:

temp_node_weight = 0

for e in bib_graph.edges_iter(n):

if e in bib_graph.edges():

temp_node_weight = temp_node_weight + nx.get_edge_attributes(bib_graph,'weight')[e]

else:

temp_node_weight = temp_node_weight + nx.get_edge_attributes(bib_graph,'weight')[e[1],e[0]]

bib_graph.node[n]['weight'] = temp_node_weight

node_weight=[data.values()[0]*2.5 for n,data in bib_graph.nodes(data=True)]

edge_weight = [data.values()[0] for a,b,data in bib_graph.edges(data=True)]

data = json_graph.node_link_data(bib_graph)

json_output_file = open("../output/json-graph%s.json" %year_iter, 'w')

json_output_file.write(str(data))

fig = plt.figure(1, figsize=(8, 8))

if year_iter == max_year_input:

init_pos=nx.pydot_layout(bib_graph)

for node in bib_graph:

pos[node] = init_pos[node]

nx.draw_networkx(bib_graph, pos, node_size=node_weight, node_color=node_weight, edge_color=edge_weight, cmap=plt.cm.OrRd, font_size=9)

if year_iter == max_year_input:

xmax=max(xx for xx,yy in pos.values())

xmin=min(xx for xx,yy in pos.values())

ymax=max(yy for xx,yy in pos.values())

ymin=min(yy for xx,yy in pos.values())

dx = xmax - xmin

ddx=0.1*dx

dy = ymax - ymin

ddy=0.1*dy

plt.hold(False)

plt.xlim(xmin-ddx,xmax+ddx)

plt.ylim(ymin-ddy,ymax+ddy)

plt.title('Bibliography Graph %s' %year_iter)

plt.axis('off')

plt.savefig("../output/bib-graph%s.png" %year_iter) # save as png

# Uncomment for more output formats

#nx.write_graphml(bib_graph, './output/biblio-perso-globale%s.graphml' %year_iter)

#nx.write_gml(bib_graph, './output/biblio-perso-globale.gml')

#nx.write_graphml(bib_graph, './output/biblio-perso-globale.graphml')

#plt.show() # display

input = "../output/bib-graph????.png"

output = "../output/bib-animation.gif"

os.system("convert -delay 100 -loop 0 %s %s" % (input, output))