def analysis_2(work_a, work_b):
""""""
members_a = books.find_all_members(work_a)
print len(remove_duplicate(members_a))
members_b = books.find_all_members(work_b)
adj_list = friends_list(members_a)
adj_list = make_cleand_adjacancy_list(adj_list, members_a)
#G1 = create_graph(remove_not_book_member(adj_list, members_a))
#plot_graph(G1, members_a, members_b)
adj_list_b = friends_list(members_b)
adj_list_b = make_cleand_adjacancy_list(adj_list_b, members_b)
#G2 = create_graph(remove_not_book_member(adj_list_b, members_b))
#plot_graph(G2, members_a, members_b)
adj_list.update(adj_list_b)
all_members = remove_duplicate(members_a + members_b)
adj_list = remove_not_book_member(adj_list, all_members)
print len(adj_list)
G = create_graph(adj_list)
#plot_graph(G, members_a, members_b)
#save_edges(G)
GC = connected_component_subgraphs(G)[0] # Giant Component
center = sort_dict(closeness_centrality(GC))[0]
#center = sort_dict(eigenvector_centrality(GC))[0]
#center = sort_dict(betweenness_centrality(GC))[0]
#pos = graphviz_layout(G, prog="twopi", root=center) # draw and save
#plot_graph(GC, members_a, members_b)
#plot_hist(GC)
return G
def analysis_1(work_a, work_b):
""""""
members_a = books.find_all_members(work_a)
adj_list = find_adjacancy_list(work_a)
adj_list = make_cleand_adjacancy_list(adj_list, members_a)
# make sure every member of work is in adjacancy list
for member in members_a:
if member not in adj_list:
log('%s removed from adjacancy list of %s' % (member, work_a),
'Error')
members_b = books.find_all_members(work_b)
adj_list_b = find_adjacancy_list(work_b)
adj_list_b = make_cleand_adjacancy_list(adj_list_b, members_b)
# make sure every member of work is in adjacancy list
for member in members_b:
if member not in adj_list_b:
log('%s removed from adjacancy list of %s' % (member, work_b),
'Error')
# create the big adjacanvy list for mambers of both books
adj_list.update(adj_list_b)
G = create_graph(adj_list)
save_edges(G, True, 'all_friends')
#print betweenness_centrality(G,normalized=False)
print '%s has %d members' % (work_a, len(remove_duplicate(members_a)))
print '%s has %d members' % (work_b, len(remove_duplicate(members_b)))
same = same_users_between(members_a, members_b)
print 'and %s of them are in both works' % len(same)
#avg = average_shortest_path_between(G, members_a, members_b)
#print 'average shortest path between %s and %s %f' % (work_a, work_b, avg)
#avg = average_shortest_path_between(G, members_a, members_a)
#print 'average shortest path between members of %s is %f' % (work_a, avg)
#avg = average_shortest_path_between(G, members_b, members_b)
#print 'average shortest path between members of %s is %f' % (work_b, avg)
return G
def find_adjacancy_list(work):
"""(str)->dict
dsc: loads all members of a work and save user name with all friends of her
to a json file
"""
file_path = './data/%s_members.json' % work
try: # if we have information alredy
with open(file_path):
adj_list = load_local_friends(file_path)
except IOError: # otherwise calc it and save it for further use
# Note: this algorithm is very ineficient thats why we save the result
members = books.find_all_members(work)
print len(members)
print len(remove_duplicate(members))
adj_list = get_adjacancy_list(members)
print len(adj_list)
for k, v in adj_list.items():
record = json.dumps({k: v})
write_to_file(record, file_path)
return adj_list
"""
finds book catalogs for all members of a given work id and saves them in html
files: "./data/profile/catalog/*.html"
"""
import users
import books
import json
import sys
from helpers import *
try:
work = sys.argv[1]
except:
work = '306947'
members = books.find_all_members(work) # all members of given work
members = remove_duplicate(members)
print len(members)
i = 0
for member in members:
i += 1
print '%d of %d, %s' % (i, len(members), member)
users.find_books(member)
#center = sort_dict(betweenness_centrality(GC))[0]
#pos = graphviz_layout(G, prog="twopi", root=center) # draw and save
#plot_graph(GC, members_a, members_b)
#plot_hist(GC)
return G
def analysis_3(work_a, work_b):
""""""
adj_list = friends_list(members_a)
adj_list = make_cleand_adjacancy_list(adj_list, members_a)
adj_list_b = friends_list(members_b)
adj_list_b = make_cleand_adjacancy_list(adj_list_b, members_b)
adj_list.update(adj_list_b)
all_members = remove_duplicate(members_a + members_b)
adj_list = remove_not_book_member(adj_list, all_members)
G = create_weighted_graph(adj_list)
C = connected_component_subgraphs(G)[0] # Giant Component
plot_graph(G, members_a, members_b, node_lable='True')
if __name__ == '__main__':
work_a = '306947' # The Holy Bible: King James Version (KJV)
work_b = '1576656' # The Blind Watchmaker
members_a = books.find_all_members(work_a)
members_b = books.find_all_members(work_b)
#G = analysis_1(work_a, work_b)
#G = analysis_2(work_a, work_b)
#G = analysis_3(work_a, work_b)
