def cal_topic_quotasystem_count_by_date(topic, start, end):
#确定要查询Weibo的时间段
start_date = ts2datetime(start)
end_date = ts2datetime(end) # 若结束时间戳为2014:09:02 00:00:00,实际上还是算在9.1那一天中
print 'start, end:', start_date, end_date
windowsize = (end - start) / Day
print 'windowsize:', windowsize
datestr_list = []
for i in range(windowsize):
time = start + i * Day
time_date = ts2datetime(time)
datestr_list.append(time_date.replace('-', ''))
print 'datestr_list:', datestr_list
#
topic_xapian_id = weibo_topic2xapian(topic, start, end)
print 'topic_xapian_id:', topic_xapian_id
xapian_search_weibo = getXapianWeiboByTopic(topic_xapian_id)
'''
xapian_search_weibo = getXapianWeiboByDuration(datestr_list) # 这里是根据时间段进行查询的
xapian_search_topic = getXapianWeiboByTopic(topic) # 直接查topic建立的索引
'''
if xapian_search_weibo:
print '******start_compute'
quota_attention(topic, xapian_search_weibo, start_ts=start, end_ts=end)
quota_duration(topic, start_ts=start, end_ts=end)
print 'save duration success'
quota_sensitivity(topic, start_ts=start, end_ts=end)
print 'save sensitivity success'
quota_importance(topic, start_ts=start, end_ts=end)
print 'save importance success'
quota_sentiment(topic, xapian_search_weibo, start_ts=start, end_ts=end)
print 'save sentiment success'
quota_coverage(topic, xapian_search_weibo, start_ts=start, end_ts=end) # 覆盖度计算
print 'save coverage success'
quota_person_sensitivity(topic, xapian_search_weibo, start_ts=start, end_ts=end) # 敏感人物参与度
print 'save person_sensitivity success'
reverse=True)
print 'top_source_user:'******'''
count, top_weibo = xapian_search_weibo.search(query={'_id':top_source_mid}, fields=['timestamp'])
print 'count:', count
for i in top_weibo():
timestamp = i['timestamp']
print 'timestamp:', ts2date(int(timestamp))
'''
return sorted_result
if __name__ == '__main__':
'''
topic = u'高校思想宣传'
date = '2015-02-01'
windowsize = 9
topic_xapian_id = '54ccbfab5a220134d9fc1b37'
'''
topic = TOPIC
date = END
start_ts = datetime2ts(START)
end_ts = datetime2ts(END)
#windowsize = (end_ts - start_ts) / Day
windowsize = (end_ts - start_ts) / Day / 2
topic_xapian_id = weibo_topic2xapian(topic, start_ts, end_ts)
get_interval_count(topic, date, windowsize, topic_xapian_id)
def main(topic, start_ts, end_ts):
'''
topics = _topic_not_calc() # topics=[{id:x,module:x,status:x,topic:x,start:x,end:x,db_date:x}]
'''
topic_status_info = db.session.query(TopicStatus).filter(TopicStatus.topic==topic ,\
TopicStatus.start==start_ts ,\
TopicStatus.end==end_ts ,\
TopicStatus.module=='identify' ,\
TopicStatus.status==-1).first()
if topic_status_info:
#topic = topics[0] # 每次只计算一个----为了做一个缓冲，每个n时间才计算一个
print 'topic_id', topic_status_info.id
start_ts = topic_status_info.start
end_ts = topic_status_info.end
db_date = topic_status_info.db_date
topicname = topic
_update_topic_status2Computing(topicname, start_ts, end_ts, db_date)
print 'update_status'
topic_id = acquire_topic_id(topicname, start_ts, end_ts) # 重新获取id是因为TopicStatus中id是自增加的，进行更新后，id就不是原来的那一个了
windowsize = (end_ts - start_ts) / Day # 确定时间跨度的大小
date = ts2datetime(end_ts)
print 'start topic2xapianid'
topic_xapian_id = weibo_topic2xapian(topicname, start_ts, end_ts)
print 'topic_xapian_id:', topic_xapian_id
print 'start compute first_nodes'
start_date = ts2datetime(start_ts) # used to compute the first user
get_first_node(topicname, start_date, date, windowsize, topic_xapian_id)
print 'end compute first_nodes'
#
print 'start make network'
max_size = MAX_SIZE
attribute_add = True
g, gg, new_attribute_dict, ds_dg, ds_udg, ds_new_attribute_dict = make_network(topicname, date, windowsize, topic_xapian_id, max_size, attribute_add)
print 'write gexf file'
real_topic_id = acquire_real_topic_id(topicname, start_ts, end_ts)
if not real_topic_id:
print 'the topic not exist'
return None
key = str(real_topic_id) + '_' + str(date) + '_' + str(windowsize)
print 'gexf_file:', str(GRAPH_PATH)+str(key)+'_g_graph.gexf'
nx.write_gexf(g, str(GRAPH_PATH) + str(key) + '_g_graph.gexf')
nx.write_gexf(gg, str(GRAPH_PATH) + str(key) + '_gg_graph.gexf')
nx.write_gexf(ds_dg, str(GRAPH_PATH) + str(key) + '_ds_dg_graph.gexf')
nx.write_gexf(ds_udg, str(GRAPH_PATH) + str(key) + '_ds_udg_graph.gexf')
save_attribute_dict(new_attribute_dict, 'g')
save_attribute_dict(ds_new_attribute_dict, 'ds_g')
print 'end make network'
print 'start PageRank'
all_uid_pr, ds_all_uid_pr, data, ds_data = pagerank_rank(TOPK, date, topic_id, windowsize, topicname, real_topic_id)
print 'len(all_uid_pr):', len(all_uid_pr)
print 'end PageRank'
print 'start make network graph'
topic_id = int(topic_id)
windowsize = int(windowsize)
if not topic_id: # 待删
gexf = ''
else:
gexf, ds_gexf = make_network_graph(date, topic_id, topicname, windowsize, all_uid_pr, data, ds_all_uid_pr, ds_data, real_topic_id)
print 'save gexf'
save_gexf_results(topicname, date, windowsize, gexf, gexf_type)
save_gexf_results(topicname, date, windowsize, ds_gexf, ds_gexf_type)
print 'start fu_tr'
get_interval_count(topicname, date, windowsize, topic_xapian_id)
print 'update_topic_end'
_update_topic_status2Completed(topicname, start_ts, end_ts, db_date)
user_info['statuses_count'] = result['statuses_count']
else:
user_info['name'] = u'未知'
user_info['location'] = u'未知'
user_info['friends_count'] = u'未知'
user_info['followers_count'] = u'未知'
user_info['profile_image_url'] = 'no'
user_info['friends_count'] = u'未知'
user_info['followers_count'] = u'未知'
user_info['created_at'] = u'未知'
user_info['statuses_count'] = u'未知'
return user_info
if __name__=='__main__':
'''
topic = u'高校思想宣传'
date = '2015-02-01'
windowsize = 9
topic_xapian_id = '54ccbfab5a220134d9fc1b37'
'''
topic = TOPIC
date = END
start_ts = datetime2ts(START)
end_ts = datetime2ts(END)
windowsize = (end_ts - start_ts) / Day
topic_xapian_id = weibo_topic2xapian(topic, start_ts, end_ts)
get_interval_count(topic, date, windowsize, topic_xapian_id)
def main(topic, start_ts, end_ts):
'''
topics = _topic_not_calc() # topics=[{id:x,module:x,status:x,topic:x,start:x,end:x,db_date:x}]
'''
topic_status_info = db.session.query(TopicStatus).filter(TopicStatus.topic==topic ,\
TopicStatus.start==start_ts ,\
TopicStatus.end==end_ts ,\
TopicStatus.module=='identify' ,\
TopicStatus.status==-1).first()
if topic_status_info:
#topic = topics[0] # 每次只计算一个----为了做一个缓冲，每个n时间才计算一个
print 'topic_id', topic_status_info.id
start_ts = topic_status_info.start
end_ts = topic_status_info.end
db_date = topic_status_info.db_date
topicname = topic
_update_topic_status2Computing(topicname, start_ts, end_ts, db_date)
print 'update_status'
topic_id = acquire_topic_id(
topicname, start_ts,
end_ts) # 重新获取id是因为TopicStatus中id是自增加的，进行更新后，id就不是原来的那一个了
windowsize = (end_ts - start_ts) / Day # 确定时间跨度的大小
date = ts2datetime(end_ts)
print 'start topic2xapianid'
topic_xapian_id = weibo_topic2xapian(topicname, start_ts, end_ts)
print 'topic_xapian_id:', topic_xapian_id
print 'start compute first_nodes'
start_date = ts2datetime(start_ts) # used to compute the first user
get_first_node(topicname, start_date, date, windowsize,
topic_xapian_id)
print 'end compute first_nodes'
#
print 'start make network'
max_size = MAX_SIZE
attribute_add = True
g, gg, new_attribute_dict, ds_dg, ds_udg, ds_new_attribute_dict = make_network(
topicname, date, windowsize, topic_xapian_id, max_size,
attribute_add)
print 'write gexf file'
real_topic_id = acquire_real_topic_id(topicname, start_ts, end_ts)
if not real_topic_id:
print 'the topic not exist'
return None
key = str(real_topic_id) + '_' + str(date) + '_' + str(windowsize)
print 'gexf_file:', str(GRAPH_PATH) + str(key) + '_g_graph.gexf'
nx.write_gexf(g, str(GRAPH_PATH) + str(key) + '_g_graph.gexf')
nx.write_gexf(gg, str(GRAPH_PATH) + str(key) + '_gg_graph.gexf')
nx.write_gexf(ds_dg, str(GRAPH_PATH) + str(key) + '_ds_dg_graph.gexf')
nx.write_gexf(ds_udg,
str(GRAPH_PATH) + str(key) + '_ds_udg_graph.gexf')
save_attribute_dict(new_attribute_dict, 'g')
save_attribute_dict(ds_new_attribute_dict, 'ds_g')
print 'end make network'
print 'start PageRank'
all_uid_pr, ds_all_uid_pr, data, ds_data = pagerank_rank(
TOPK, date, topic_id, windowsize, topicname, real_topic_id)
print 'len(all_uid_pr):', len(all_uid_pr)
print 'end PageRank'
print 'start make network graph'
topic_id = int(topic_id)
windowsize = int(windowsize)
if not topic_id: # 待删
gexf = ''
else:
gexf, ds_gexf = make_network_graph(date, topic_id, topicname,
windowsize, all_uid_pr, data,
ds_all_uid_pr, ds_data,
real_topic_id)
print 'save gexf'
save_gexf_results(topicname, date, windowsize, gexf, gexf_type)
save_gexf_results(topicname, date, windowsize, ds_gexf, ds_gexf_type)
print 'start fu_tr'
get_interval_count(topicname, date, windowsize, topic_xapian_id)
print 'update_topic_end'
_update_topic_status2Completed(topicname, start_ts, end_ts, db_date)