def conditional_marginal2(condition_list, clique, bit_list, bit_cand_list,
row_list, bitsum_list, f, dt):
####################################################################################
# To generate conditional probability and acceptable items for sampling
pro = []
some_list = []
rest_list = list(set(clique) - set(condition_list))
rest_list.sort()
if len(condition_list) == 1:
att_indexs1 = condition_list[0]
att_rappor_list_combine1 = bit_list[att_indexs1]
att_signal_list_combine1 = bit_cand_list[att_indexs1]
att_row_list_combine1 = row_list[att_indexs1]
else:
att_indexs1 = condition_list
att_rappor_list_combine1, att_signal_list_combine1, att_row_list_combine1 = att_combin(
bit_list, bit_cand_list, row_list, att_indexs1)
if len(rest_list) == 1:
att_indexs2 = rest_list[0]
att_rappor_list_combine2 = bit_list[att_indexs2]
att_signal_list_combine2 = bit_cand_list[att_indexs2]
att_row_list_combine2 = [row_list[att_indexs2]]
else:
att_indexs2 = rest_list
att_rappor_list_combine2, att_signal_list_combine2, att_row_list_combine2 = att_combin(
bit_list, bit_cand_list, row_list, att_indexs2)
proe = estimate_2d2(att_signal_list_combine1, att_signal_list_combine2,
bitsum_list, clique)
#print(proe)
protemp = proe
#lenpro=len(protemp)
leng1 = len(att_signal_list_combine1)
leng2 = len(att_signal_list_combine2)
ptemp = [[] for i in range(leng1)]
for i in range(leng1):
for j in range(leng2):
ptemp[i].append(protemp[i][j])
condition_some_list = att_row_list_combine1
#some_list=att_row_list_combine2
some_list = row_list_product(row_list, rest_list)
#print(condition_some_list)
#print(some_list)
#print('true:',true_joint_distribution(bit_list,row_list,clique))
#print('estimate:',ptemp)
return condition_some_list, some_list, ptemp
def independent_marginal2(clique, bit_list, bit_cand_list, row_list,
bitsum_list, f, dt):
##################################################################
# To generate independent probability and possible list for sampling
#print(row_list)
leng = len(clique)
#print(leng)
pro = []
some_list = []
if leng == 1:
att_index1 = clique[0]
ptemp = Get_Rappor.lasso_regression([bit_cand_list[att_index1]],
[bitsum_list[att_index1]])
pro = ptemp[0]
some_list = row_list[clique[0]]
if leng == 2:
att_index1 = clique[0]
att_index2 = clique[leng - 1]
ptemp = estimate_2d2(bit_cand_list[att_index1],
bit_cand_list[att_index2], bitsum_list, clique)
#Get_Rappor.lasso_regression([bit_cand_list[att_index1]], [bitsum_list[att_index1]])
proe = ptemp
proleng = len(proe)
for i in range(proleng):
pro.extend(proe[i])
#print('lasso estimate:',pro)
#some_list=list_product([row_list[clique[0]]],[row_list[clique[1]]])
some_list = row_product(row_list[clique[0]], row_list[clique[1]])
if leng > 2:
att_index1 = clique[0]
att_indexs = clique[1:(leng)]
#print(att_index1)
#print(att_indexs)
att_rappor_list_combine, att_signal_list_combine, att_row_list_combine = att_combin(
bit_list, bit_cand_list, row_list, att_indexs)
#print('rowlist combine',att_row_list_combine)
#print(att_row_list_combine)
proe = estimate_2d2(bit_cand_list[att_index1], att_signal_list_combine,
bitsum_list, clique)
#print(proe)
#pro=proe[0]
#proe=estimate_2d(bit_list[att_index1],att_rappor_list_combine,bit_cand_list[att_index1],att_signal_list_combine,f,dt)
proleng = len(proe)
for i in range(proleng):
pro.extend(proe[i])
#some_list=list_product(row_list[clique[0]],att_row_list_combine)
some_list = row_product(row_list[clique[0]], att_row_list_combine)
#print('lasso estimate:',pro)
some_list = row_list_product(row_list, clique)
#print(some_list)
#print(pro)
return some_list, pro
def conditional_marginal(condition_list, clique, bit_list, bit_cand_list,
row_list, bitsum_list, f, dt):
####################################################################################
# To generate conditional probability and acceptable items for sampling
pro = []
some_list = []
rest_list = list(set(clique) - set(condition_list))
rest_list.sort()
if len(condition_list) == 1:
att_indexs1 = condition_list[0]
att_rappor_list_combine1 = bit_list[att_indexs1]
att_signal_list_combine1 = bit_cand_list[att_indexs1]
att_row_list_combine1 = row_list[att_indexs1]
else:
att_indexs1 = condition_list
att_rappor_list_combine1, att_signal_list_combine1, att_row_list_combine1 = att_combin(
bit_list, bit_cand_list, row_list, att_indexs1)
if len(rest_list) == 1:
att_indexs2 = rest_list[0]
att_rappor_list_combine2 = bit_list[att_indexs2]
att_signal_list_combine2 = bit_cand_list[att_indexs2]
att_row_list_combine2 = row_list[att_indexs2]
else:
att_indexs2 = rest_list
att_rappor_list_combine2, att_signal_list_combine2, att_row_list_combine2 = att_combin(
bit_list, bit_cand_list, row_list, att_indexs2)
pro = estimate_2d(att_rappor_list_combine1, att_rappor_list_combine2,
att_signal_list_combine1, att_signal_list_combine2,
bitsum_list, clique, f, dt)
condition_some_list = att_row_list_combine1
some_list = att_row_list_combine2
#print(condition_some_list)
#print(some_list)
#print('true:',true_joint_distribution(bit_list,row_list,clique))
#print('estimate:',pro)
return condition_some_list, some_list, pro
def getProb(clique, bit_list, bit_cand_list, row_list, bitsum_list, f, dt):
leng = len(clique)
pro = []
att_index1 = clique[0]
att_indexs = clique[1:(leng)]
att_rappor_list_combine, att_signal_list_combine, att_row_list_combine = att_combin(
bit_list, bit_cand_list, row_list, att_indexs)
proe = estimate_2d(bit_list[att_index1], att_rappor_list_combine,
bit_cand_list[att_index1], att_signal_list_combine,
bitsum_list, clique, f, dt)
proleng = len(proe)
for i in range(proleng):
pro.extend(proe[i])
some_list = list_product(row_list[clique[0]], att_row_list_combine)
return [some_list, pro], proe
def independent_marginal3(clique, bit_list, bit_cand_list, row_list,
bitsum_list, f, dt):
##################################################################
# To generate independent probability and possible list for sampling
leng = len(clique)
pro = []
some_list = []
if leng <= 2:
att_index1 = clique[0]
att_index2 = clique[leng - 1]
#proe=estimate_2d(bit_list[att_index1], bit_list[att_index2], bit_cand_list[att_index1], bit_cand_list[att_index2], f, dt)
proe = estimate_2d6(bit_list[att_index1], bit_list[att_index2],
bit_cand_list[att_index1],
bit_cand_list[att_index2], bitsum_list, clique, f,
dt)
proleng = len(proe)
for i in range(proleng):
pro.extend(proe[i])
some_list = row_list[clique[0]]
else:
att_index1 = clique[0]
att_indexs = clique[1:(leng)]
#print(att_index1)
#print(att_indexs)
att_rappor_list_combine, att_signal_list_combine, att_row_list_combine = att_combin(
bit_list, bit_cand_list, row_list, att_indexs)
#print('rowlist combine',att_row_list_combine) att_combin(bit_list,bit_cand_list,row_list,att_indexs)
#print(att_row_list_combine)
#proe=estimate_2d2(bit_cand_list[att_index1],att_signal_list_combine,bitsum_list,clique)
proe = estimate_2d6(bit_list[att_index1], att_rappor_list_combine,
bit_cand_list[att_index1], att_signal_list_combine,
bitsum_list, clique, f, dt)
proleng = len(proe)
for i in range(proleng):
pro.extend(proe[i])
some_list = list_product(row_list[clique[0]], att_row_list_combine)
#print('estimate:',proe)
return some_list, pro