def make_cascades_summary(self, cascade_networks, logweight=True):
new_nodes = {}
new_links = {}
self.cascades_network = Network()
for cascade in cascade_networks:
for node_id in cascade.network.nodes_ids:
if new_nodes.get(node_id) is None:
new_nodes[node_id] = 0
new_nodes[node_id] += 1
for from_id, to_id in cascade.network.links.keys():
if new_links.get((from_id, to_id)) is None:
new_links[(from_id, to_id)] = 0
new_links[(from_id, to_id)] += 1
self.cascades_network.nodes_attributes.append({'id': 'w', 'title': 'LogWeight', 'type': 'float'})
for node_id, quantity in new_nodes.items():
self.cascades_network.add_node(node_id)
if logweight:
w = math.log(quantity) + 1
else:
w = quantity
self.cascades_network.add_meta_for_node(node_id, {'w': w})
for link, quantity in new_links.items():
if logweight:
w = math.log(quantity) + 1
else:
w = quantity
self.cascades_network.add_link(link[0], link[1], mutual=False, weighted=True, weight=w)
def make_test_network_star():
ntw = Network(optimisation=NetworkOptimisation.id_only)
for i in range(31):
ntw.add_node(i + 1)
for i in range(30):
ntw.add_link(1, i + 2)
return ntw
def make_test_network_chain(n=31):
ntw = Network(optimisation=NetworkOptimisation.id_only)
for i in range(n):
ntw.add_node(i + 1)
for i in range(n - 1):
ntw.add_link(i + 1, i + 2)
return ntw
def __init__(self, net=Network(), name='', base_dir=''):
super().__init__(net, name, base_dir)
self.post_meta = {}
self.posters = {}
self.hiddens = set()
self.likers = set()
self.timestamp = datetime.datetime.now()
def make_test_network_traingle():
ntw = Network(optimisation=NetworkOptimisation.id_only)
for i in range(3):
ntw.add_node(i + 1)
ntw.add_link(1, 2)
ntw.add_link(1, 3)
ntw.add_link(2, 3)
return ntw
def make_test_network_connected():
ntw = Network(optimisation=NetworkOptimisation.id_only)
for i in range(31):
ntw.add_node(i + 1)
for i in range(30):
for j in range(i + 1, 31):
ntw.add_link(i + 1, j + 1)
return ntw
def __init__(self,
net=Network(optimisation=NetworkOptimisation.id_only),
name='',
base_dir=''):
super().__init__(net, name, base_dir)
self.nodes_meta = {}
self.crawled_nodes = set()
self.counters_meta = {}
def make_underlying_summary(self, underlyings):
if len(underlyings) == 1:
self.underlying = underlyings[0].network
else:
self.underlying = Network(optimisation=NetworkOptimisation.id_only)
for underlying in underlyings:
for node_id, neighbors in underlying.network.nodes.items():
self.underlying.add_node(node_id)
self.underlying.nodes[node_id].update(neighbors)
def make_test_network():
ntw = Network(optimisation=NetworkOptimisation.id_only)
for i in range(31):
ntw.add_node(i + 1)
ntw.add_link(1, 2)
ntw.add_link(1, 3)
ntw.add_link(2, 3)
ntw.add_link(3, 4)
ntw.add_link(4, 5)
ntw.add_link(4, 6)
ntw.add_link(5, 6)
ntw.add_link(4, 7)
ntw.add_link(7, 8)
ntw.add_link(7, 9)
ntw.add_link(7, 10)
ntw.add_link(8, 10)
ntw.add_link(9, 10)
ntw.add_link(9, 11)
ntw.add_link(11, 12)
ntw.add_link(11, 13)
ntw.add_link(12, 13)
ntw.add_link(13, 14)
ntw.add_link(8, 15)
ntw.add_link(3, 16)
ntw.add_link(16, 17)
ntw.add_link(17, 18)
ntw.add_link(18, 19)
ntw.add_link(19, 20)
ntw.add_link(15, 20)
ntw.add_link(1, 21)
ntw.add_link(1, 22)
ntw.add_link(1, 23)
ntw.add_link(1, 24)
ntw.add_link(1, 25)
ntw.add_link(1, 26)
ntw.add_link(2, 21)
ntw.add_link(2, 22)
ntw.add_link(2, 23)
ntw.add_link(2, 24)
ntw.add_link(2, 25)
ntw.add_link(2, 26)
ntw.add_link(3, 21)
ntw.add_link(3, 22)
ntw.add_link(3, 23)
ntw.add_link(3, 24)
ntw.add_link(3, 25)
ntw.add_link(3, 26)
return ntw
def __init__(self, net=Network(), name='', base_dir=''):
self.network = net
self.name = name
self.base_dir = base_dir
self.source = NetworkSource.vkontakte
self.crawl_plan = []
def __init__(self):
self.cascades_network = Network()
self.underlying = Network()
pass
def remake_network(self,
possible_links: dict,
uselikes=True,
usehiddens=True,
dynamic=True,
logdyn=False,
start_from_zero=False):
# print('This method updates network from post_meta, hiddens, likers etc.')
self.network = Network()
if dynamic:
self.network.nodes_attributes.append({
'id': 'start',
'title': 'start',
'type': 'float'
})
self.network.nodes_attributes.append({
'id': 'n',
'title': 'Underlying_degree',
'type': 'integer'
})
self.network.nodes_attributes.append({
'id': 'g',
'title': 'Is_group',
'type': 'boolean'
})
self.network.links_attributes.append({
'id': 'start',
'title': 'start',
'type': 'float'
})
self.network.links_attributes.append({
'id': 'delay',
'title': 'delay',
'type': 'float'
})
if usehiddens:
for node_id in self.hiddens:
self.network.add_node(node_id)
if uselikes:
for node_id in self.likers:
self.network.add_node(node_id)
nodes = self.posters.keys()
min_date = float("inf")
if start_from_zero:
for node_id in nodes:
date = self.posters[node_id]['date']
if date < min_date:
min_date = date
for node_id in nodes:
self.network.add_node(node_id)
if node_id > 0:
self.network.add_meta_for_node(node_id, {'g': "False"})
else:
self.network.add_meta_for_node(node_id, {'g': "True"})
date = self.posters[node_id]['date']
neighs_set = possible_links.get(node_id)
if neighs_set:
self.network.add_meta_for_node(node_id, {'n': len(neighs_set)})
else:
self.network.add_meta_for_node(node_id, {'n': 0})
if start_from_zero:
date -= min_date
if dynamic:
if logdyn:
self.network.add_meta_for_node(
node_id, {'start': math.log(date + 1)})
else:
self.network.add_meta_for_node(node_id, {'start': date})
for node2_id in nodes:
if node2_id != node_id:
date2 = self.posters[node2_id]['date']
if start_from_zero:
date2 -= min_date
if date < date2:
if neighs_set and node2_id in neighs_set:
self.network.add_link(node_id,
node2_id,
mutual=False)
self.network.add_meta_for_link(
node_id, node2_id, {'delay': date2 - date})
if dynamic:
if logdyn:
self.network.add_meta_for_link(
node_id, node2_id,
{'start': math.log(date2 + 1)})
else:
self.network.add_meta_for_link(
node_id, node2_id, {'start': date2})