def get_injector_from_file(path: str):
config = parse_from_file(path)
injector = Injector(config)
log_config = config.get("Logging", {})
LoggerFactory.init_root_logger("snaces2.log")
return injector
from src.activity.download_user_tweets_activity import DownloadUserTweetsActivity
import argparse
import time
from src.dependencies.injector import Injector
from src.shared.utils import get_project_root
from src.shared.logger_factory import LoggerFactory
import numpy as np
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
from src.model.local_neighbourhood import LocalNeighbourhood
import json
import logging
import random
import gc
log = LoggerFactory.logger(__name__, logging.ERROR)
DEFAULT_PATH = str(
get_project_root()) + "/src/scripts/config/default_config.yaml"
def produce_plots(user_name: str, thresh, i, path=DEFAULT_PATH):
injector = Injector.get_injector_from_file(path)
process_module = injector.get_process_module()
dao_module = injector.get_dao_module()
user_friend_getter = dao_module.get_user_friend_getter()
friends_cleaner = process_module.get_extended_friends_cleaner()
social_graph_constructor = process_module.get_social_graph_constructor()
clusterer = process_module.get_clusterer()
from src.activity.download_user_tweets_activity import DownloadUserTweetsActivity
import argparse
import time
from src.dependencies.injector import Injector
from src.shared.utils import get_project_root
from src.shared.logger_factory import LoggerFactory
import numpy as np
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
from src.model.local_neighbourhood import LocalNeighbourhood
import json
log = LoggerFactory.logger(__name__)
DEFAULT_PATH = str(get_project_root()) + "/src/scripts/config/default_config.yaml"
def produce_plots(seed_id: str, user_name: str, path=DEFAULT_PATH):
threshold = 60
injector = Injector.get_injector_from_file(path)
process_module = injector.get_process_module()
dao_module = injector.get_dao_module()
user_friend_getter = dao_module.get_user_friend_getter()
friends_cleaner = process_module.get_friends_cleaner()
social_graph_constructor = process_module.get_social_graph_constructor()
clusterer = process_module.get_clusterer()
cluster_word_frequency_processor = process_module.get_cluster_word_frequency_processor()
tweet_processor = process_module.get_tweet_processor()
import networkx as nx
from copy import deepcopy
from src.model.social_graph.social_graph import SocialGraph
from src.model.local_neighbourhood import LocalNeighbourhood
from src.shared.logger_factory import LoggerFactory
import logging
log = LoggerFactory.logger(__name__, logging.INFO)
class IntersectionSocialGraph(SocialGraph):
def fromLocalNeighbourhood(local_neighbourhood: LocalNeighbourhood,
params=None,
remove_unconnected_nodes=True):
graph = nx.DiGraph()
user_list = local_neighbourhood.get_user_id_list()
user_list.remove(str(local_neighbourhood.seed_id))
log.info("Length of list " + str(len(user_list)))
if remove_unconnected_nodes:
user_list = SocialGraph.remove_unconnected_nodes(
local_neighbourhood)
log.info("Length of list after removing unconnected nodes " +
str(len(user_list)))
user_list.remove(str(local_neighbourhood.seed_id))
for user in user_list:
graph.add_node(user)
for user in user_list:
friends = local_neighbourhood.get_user_friends(user)
from typing import Union, List, Dict
from src.model.word_frequency_vector import WordFrequencyVector
from src.model.user_word_frequency_vector import UserWordFrequencyVector
from copy import deepcopy
from src.shared.logger_factory import LoggerFactory
import logging
log = LoggerFactory.logger(__name__, logging.DEBUG)
class UserWordFrequencyProcessor():
"""
Process and store a users word frequency
"""
def __init__(self, processed_tweet_getter,
user_word_frequency_vector_getter,
user_word_frequency_vector_setter,
global_word_frequency_vector_getter,
user_relative_word_frequency_vector_setter):
self.processed_tweet_getter = processed_tweet_getter
self.user_word_frequency_vector_getter = user_word_frequency_vector_getter
self.user_word_frequency_vector_setter = user_word_frequency_vector_setter
self.global_word_frequency_vector_getter = global_word_frequency_vector_getter
self.user_relative_word_frequency_vector_setter = user_relative_word_frequency_vector_setter
def process_user_word_frequency_vector(self, id: str):
user_processed_tweets = self.processed_tweet_getter.get_user_processed_tweets(
id)
log.info("Number of processed tweets " +
str(len(user_processed_tweets)))
user_word_freq_vc = self.user_word_frequency_vector_getter.get_user_word_frequency_by_id(
