# -*- coding: utf-8 -*-
"""
Created on Sun Nov 20 20:46:26 2016
@author: ZJun
"""
from twitter_function import Import_Obj, GenerateDate, hinton
df_flu_related_twitter_in_place_loc = Import_Obj(
'./DF_Result/df_flu_related_twitter_in_place_loc')
df_twitter_in_place_loc = Import_Obj('./DF_Result/df_twitter_in_place_loc')
df_move_destination_in_place_loc = Import_Obj(
'./DF_Result/df_move_destination_in_place_loc')
df_flu_related_move_destination_in_place_loc = Import_Obj(
'./DF_Result/df_flu_related_move_destination_in_place_loc')
df_real_flu = Import_Obj('./DF_Result/df_real_flu')
df_where_to_where = Import_Obj('./DF_Result/df_where_to_where')
df_flu_where_to_where = Import_Obj('./DF_Result/df_flu_where_to_where')
def GetTransferProbability(df_where_to_where, df_twitter_in_place_loc):
all_where_to_where = df_where_to_where.values[0] * 0
for w2w in df_where_to_where.values:
all_where_to_where += w2w
# all_where_to_where i to j [i,j]
num_all = df_twitter_in_place_loc.sum(0)
# -*- coding: utf-8 -*-
"""
Created on Wed Nov 23 19:24:30 2016
@author: ZJun
"""
from twitter_function import Import_Obj, GenerateDate, hinton, GetPartOfTimeSeries
population_2015 = dict(
zip([
'Cairns', 'Townsville', 'Mackay', 'Sunshine Coast', 'Brisbane',
'Gold Coast'
], [147993, 180333, 85455, 302122, 2209453, 624918]))
df_flu_related_twitter_in_place_loc = Import_Obj(
'./DF_Result/df_flu_related_twitter_in_place_loc')[population_2015.keys()]
df_twitter_in_place_loc = Import_Obj('./DF_Result/df_twitter_in_place_loc')[
population_2015.keys()]
df_move_destination_in_place_loc = Import_Obj(
'./DF_Result/df_move_destination_in_place_loc')[population_2015.keys()]
df_flu_related_move_destination_in_place_loc = Import_Obj(
'./DF_Result/df_flu_related_move_destination_in_place_loc')[
population_2015.keys()]
df_real_flu = Import_Obj('./DF_Result/df_real_flu')[population_2015.keys()]
df_where_to_where = Import_Obj('./DF_Result/df_where_to_where')
df_flu_where_to_where = Import_Obj('./DF_Result/df_flu_where_to_where')
actual_days_in_week = Import_Obj('./Data/actual_days_in_week')
#a = df_where_to_where[GenerateDate(2015,1,12)]
#a.loc[population_2015.keys(),population_2015.keys()]
# -*- coding: utf-8 -*-
"""
Created on Mon Nov 14 22:01:06 2016
@author: ZJun
"""
from GetData import LoadData
from twitter_function import Import_Obj, GetPartOfTimeSeries, Sort_Dict_key
import pandas as pd
from GetFactors import GetTwitterInPlaceLoc, GetFluRelatedTwitterInPlaceLoc
from GetFactors import GetMoveDestinationInPlaceLoc, GetFluRelatedMoveDestinationInPlaceLoc, GetActuallDayInWeek
import matplotlib.pyplot as plt
from collections import Counter
week_move = Import_Obj('./Data/week_move')
week_user_flu_state = Import_Obj('./Data/week_user_flu_state')
Queensland_Flu = pd.read_csv('./Data/Queensland2015.csv')
from datetime import timedelta
def GetRealFlu(Queensland_Flu, location=None):
first_week = pd.datetime(2015, 1, 5).date()
t = [first_week]
if location != None:
x = Queensland_Flu[location].values
else:
x = Queensland_Flu.ix[:, 1:].sum(1).values
for i in range(1, len(x)):
t.append(first_week + timedelta(i * 7))
ts = pd.Series(x, index=t[:len(x)])
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from twitter_function import Import_Obj,GenerateDate,hinton,GetPartOfTimeSeries,Sort_Dict
n=6
population_2015 = dict(zip(['Cairns','Townsville','Mackay','Sunshine Coast','Brisbane','Gold Coast'],
[147993,180333,85455,302122,2209453,624918]))
P = Sort_Dict(population_2015)
Places = [i[0] for i in P][:n]
df_where_to_where = Import_Obj('./DF_Result/df_where_to_where')
actual_days_in_week = Import_Obj('./Data/actual_days_in_week')
df_real_flu = Import_Obj('./DF_Result/df_real_flu')[Places]
df_twitter_in_place_loc = Import_Obj('./DF_Result/df_twitter_in_place_loc')[Places]
TimeRange = [pd.datetime(2015,3,9).date(),pd.datetime(2015,10,12).date()]
real_flu_ = GetPartOfTimeSeries(df_real_flu,TimeRange)[Places]
Times = real_flu_.index
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from twitter_function import Import_Obj, GenerateDate, hinton, GetPartOfTimeSeries, Sort_Dict
population_2015 = dict(
zip([
'Cairns', 'Townsville', 'Mackay', 'Sunshine Coast', 'Brisbane',
'Gold Coast'
], [147993, 180333, 85455, 302122, 2209453, 624918]))
P = Sort_Dict(population_2015)
Places = [i[0] for i in P]
df_where_to_where = Import_Obj('./DF_Result/df_where_to_where')
actual_days_in_week = Import_Obj('./Data/actual_days_in_week')
df_real_flu = Import_Obj('./DF_Result/df_real_flu')[population_2015.keys()]
df_twitter_in_place_loc = Import_Obj('./DF_Result/df_twitter_in_place_loc')[
population_2015.keys()]
'''
Queensland_Flu = pd.read_csv('./Data/Queensland2015.csv')
from datetime import timedelta
def GetRealFlu(Queensland_Flu,location=None):
first_week = pd.datetime(2015,1,5).date()
t = [first_week]
if location != None:
x = Queensland_Flu[location].values
else:
x = Queensland_Flu.ix[:,1:].sum(1).values
for i in range(1,len(x)):