#T=0.05
#R_star=3
#
#data_list=get_data.list_of_static_networks()+get_data.list_of_temporal_networks()
#
#data=data_list[8]
#R0=get_R0_prediction(data,R_star,T)
#
#print(R0)
R_star_range=[2,3,4]
# get list of networks
temporal_networks=get_data.list_of_temporal_networks(bats=False)
static_networks=get_data.list_of_static_networks()
data_list=static_networks+temporal_networks
phi_values=pk.load(open('pickles/phi.p','rb'))
epsilon=pk.load(open('pickles/epsilon.p','rb'))
for R_star in R_star_range:
R0_het={}
R0_hom={}
for data in data_list:
e=epsilon[data]
import get_data
import pandas as pd
import pickle
import numpy as np
mean_weight_values={}
weight_heterogeneity_values={}
data_list=get_data.list_of_static_networks()+get_data.list_of_temporal_networks(bats=True)
for data in data_list:
df,t_0,delta_t,species,interaction,phi_zero=get_data.dataframe(data)
############################################################
if data=='bats':
ID_list=list(set(df['ID1']))
else:
ID_list=list(set(pd.concat([df['ID1'],df['ID2']])))
N=len(ID_list)
####################################################################
K=[len(set(pd.concat([df[df['ID1']==ID]['ID2'],df[df['ID2']==ID]['ID1']]))) for ID in ID_list]
S=[len(pd.concat([df[df['ID1']==ID]['ID2'],df[df['ID2']==ID]['ID1']])) for ID in ID_list]
W=[]
edge_list=[]
for i,row in df.iterrows():
edge=tuple(sorted([row['ID1'],row['ID2']]))
if edge not in edge_list:
edge_list.append(edge)
import get_data
import heterogeneity_MSE as mse
import pandas as pd
import pickle
phi_values = {}
epsilon_values = {}
fidelity_values = {}
data_list = get_data.list_of_static_networks(
) + get_data.list_of_temporal_networks(bats=True) #+get_data.twitter()
for data in data_list:
df, t_0, delta_t, species, interaction, phi_zero = get_data.dataframe(data)
############################################################
if data == 'bats_0':
ID_list = list(set(df['ID1']))
else:
ID_list = list(set(pd.concat([df['ID1'], df['ID2']])))
N = len(ID_list)
####################################################################
K = [
len(
set(
pd.concat(
[df[df['ID1'] == ID]['ID2'], df[df['ID2'] == ID]['ID1']])))