def graph(config, user_id, depth, max_follow, username_file, graph_file):
'''
Get follower/following graph.
Starting with the seed user identified by USER_ID, construct a directed
follower/following graph by traversing up to --depth hops (default: 1).
For each user, fetch only --max-follow followers and followees.
'''
# Get username for this user_id.
endpoint = '/users/{}'.format(user_id)
response = _get_instagram(config, endpoint)
if response.status_code != 200:
raise click.ClickException(
'Unable to fetch user information: {} {}'
.format(response.status_code, response.payload['meta']['error_message'])
)
user_info = json.loads(response.text)
username = user_info['data']['username']
# Get graph.
node_fn = functools.partial(_get_graph, config, max_follow)
users, graph = get_graph(node_fn, {user_id: username}, depth)
write_users(users, username_file)
write_graph(graph, graph_file)
click.secho('Finished: {} nodes'.format(len(users)))
def graph(config, depth, max_follow, username, username_file, graph_file):
''' Get a twitter user's friends/follower graph. '''
session = _login_twitter(config)
# Get user ID.
home_url = '{}/{}'.format(config.twitter_url, username)
response = session.get(home_url)
if response.status_code != 200:
raise click.ClickException('Not able to get home page for {}. ({})'
.format(username, response.status_code))
html = bs4.BeautifulSoup(response.text, 'html.parser')
profile_el = html.select('.ProfileNav-item--userActions .user-actions')[0]
user_id = profile_el['data-user-id']
# Get graph.
node_fn = functools.partial(_get_graph, session, config, max_follow)
users, graph = get_graph(node_fn, {user_id: username}, depth)
write_users(users, username_file)
write_graph(graph, graph_file)
click.secho('Finished: {} nodes'.format(len(users)))
def algorithm_basic( g, n ):
threshold = 10
h = None
current_density = -1
while( g.number_of_nodes() > 1 ):
deg = g.degree( weight = 'weight' )
g.remove_node( min(deg, key=deg.get) )
temp_density = density(g)
if ( temp_density > current_density ) & ( g.number_of_nodes() <= threshold ) & ( g.number_of_nodes() >= 2 ) :
h = nx.Graph(g)
current_density = temp_density
u.write_graph(h, n)
return h
termsfile = args.filename
relationfile = args.relationfile
relationtype = args.relationtype
outdir = args.outdir
minscore = args.minscore
p_lambda = args.p_lambda
logdir = args.logdir
noise = args.noise
wn = args.wn
entities = util.read_terms(termsfile)
pruned, stats = mtg(entities,
relationfile,
reltype=relationtype,
minscore=minscore,
lmda=p_lambda,
noise=noise,
wn=wn)
bn = os.path.basename(termsfile)
util.write_taxo(pruned,
fname=os.path.join(outdir, bn.replace('.terms', '.taxo')))
util.write_graph(pruned,
fname=os.path.join(outdir, bn.replace('.terms',
'.graph')))
util.write_log(pruned,
stats,
fname=os.path.join(
logdir, 'mtg.terms-%s.rel-%s.minsc%0.1f.lambda-%0.1f' %
(bn, relationtype, minscore, p_lambda)))
