-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathupdate_MR_Inv.py
209 lines (178 loc) · 7.92 KB
/
update_MR_Inv.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
# -*- coding: utf-8 -*-
"""
Created on Sun Aug 06 15:48:01 2017
@author: Kun
"""
#v_bar is v_bar_e_star
import primal
import api
import numpy as np
def update_MR_inv(Case, MR_inv, V, newV, E_B, newE_B, e_prime, e_star, fbar_T, fbar_X):
#essentially, we are just returning a cbinded matrix, a column for each e_X
# print "case is ", Case
if newV is None:
newV = V
newR = newV[0]
R = V[0]
N = V[1]
len_newR = len(newR)
# temp_matrix = np.zeros([len_newR,len_newR])
if Case == '1a':
temp_matrix = np.zeros([len_newR,len_newR])
#in the first iteration here
#e_star is e_bar
#e_prime is e_star
if e_star in fbar_X:
fbar_X_e_star = fbar_X[e_star]
else:
fbar_X_e_star = fbar_T[e_star]
for v in newR:
for e in newE_B[1]:
if e == e_prime:
temp_val = -1*((MR_inv[E_B[1].index(e_star)][newR.index(v)])/fbar_X_e_star)
temp_matrix[newE_B[1].index(e)][newR.index(v)] = temp_val
else:
#all the e is in existing E_X but v not be in existing R
temp_val = MR_inv[E_B[1].index(e)][V[0].index(v)] - (((MR_inv[E_B[1].index(e_star)][newR.index(v)])/fbar_X_e_star)*fbar_X[e])
temp_matrix[newE_B[1].index(e)][newR.index(v)] = temp_val
return temp_matrix
elif Case == '1b':
temp_matrix = np.zeros([len_newR,len_newR])
if e_star in fbar_X:
fbar_X_e_star = fbar_X[e_star]
else:
fbar_X_e_star = fbar_T[e_star]
for v in newR:
for e in newE_B[1]:
#all the e is in existing E_X but v not be in existing R
temp_val = MR_inv[E_B[1].index(e)][V[0].index(v)] - (((MR_inv[E_B[1].index(e_star)][newR.index(v)])/fbar_X_e_star)*fbar_X[e])
temp_matrix[newE_B[1].index(e)][newR.index(v)] = temp_val
return temp_matrix
elif Case == '2a':
temp_matrix = np.zeros([len_newR,len_newR])
#in the first iteration here
#e_star is e_bar
#e_prime is e_star
fbar_e_star = None
if e_star in fbar_X:
fbar_e_star = fbar_X[e_star]
elif e_star in fbar_T:
fbar_e_star = fbar_T[e_star]
if fbar_e_star != 0:
for v in newR:
for e in newE_B[1]:
if e == e_prime:
temp_val = -1*((MR_inv[E_B[1].index(e_star)][newR.index(v)])/fbar_e_star)
temp_matrix[newE_B[1].index(e)][newR.index(v)] = temp_val
else:
#all the e is in existing E_X but v not be in existing R
temp_val = MR_inv[E_B[1].index(e)][V[0].index(v)] - (((MR_inv[E_B[1].index(e_star)][newR.index(v)])/fbar_e_star)*fbar_X[e])
temp_matrix[newE_B[1].index(e)][newR.index(v)] = temp_val
else:
temp_matrix = api.test_MR_inv(newE_B,V)
return temp_matrix
# elif Case == '2a-1st':
# temp_matrix = np.zeros([len_newR,len_newR])
# #in the first iteration here
# #e_star is e_bar
# #e_prime is e_star
# fbar_e_star = None
# if e_prime in fbar_X:
# fbar_e_star = fbar_X[e_prime]
# elif e_prime in fbar_T:
# fbar_e_star = fbar_T[e_prime]
#
# for v in newR:
# temp_R = dict.fromkeys(V[0], 0)
# temp_N = dict.fromkeys(V[1], 0)
# if v in R:
# temp_R[v] = 1
# elif v in N:
# temp_N[v] = 1
# temp_bar = [temp_R, temp_N]
# phi_T, phi_X = primal.Primal(V, E_B, MR_inv, temp_bar)
#
#
# for e in newE_B[1]:
# if e == e_prime:
# temp_val = -1*((phi_T[e_prime])/fbar_e_star)
# temp_matrix[newE_B[1].index(e)][newR.index(v)] = temp_val
# else:
# #all the e is in existing E_X but v not be in existing R
# temp_val = MR_inv[E_B[1].index(e)][V[0].index(v)] - (((phi_T[e_prime])/fbar_e_star)*fbar_X[e])
# temp_matrix[newE_B[1].index(e)][newR.index(v)] = temp_val
#
#
#
# return temp_matrix
#
# elif Case == '2a-2nd':
# temp_matrix = np.zeros([len_newR,len_newR])
# #in the first iteration here
# #e_star is e_bar
# #e_prime is e_star
# fbar_e_star = None
# if e_star in fbar_X:
# fbar_e_star = fbar_X[e_star]
# elif e_star in fbar_T:
# fbar_e_star = fbar_T[e_star]
#
# for v in newR:
# for e in newE_B[1]:
# if e == e_prime:
# temp_val = -1*((MR_inv[E_B[1].index(e_star)][newR.index(v)])/fbar_e_star)
# temp_matrix[newE_B[1].index(e)][newR.index(v)] = temp_val
# else:
# #all the e is in existing E_X but v not be in existing R
# temp_val = MR_inv[E_B[1].index(e)][V[0].index(v)] - (((MR_inv[E_B[1].index(e_star)][newR.index(v)])/fbar_e_star)*fbar_X[e])
# temp_matrix[newE_B[1].index(e)][newR.index(v)] = temp_val
#
#
# return temp_matrix
elif Case == '2b1':
#thing e_prime replace e_star as tree arc, E_X does not change
#MR_inv does not change
temp_matrix = np.zeros([len_newR,len_newR])
for v in newR:
temp_R = dict.fromkeys(V[0], 0)
temp_N = dict.fromkeys(V[1], 0)
if v in R:
temp_R[v] = 1
elif v in N:
temp_N[v] = 1
temp_bar = [temp_R, temp_N]
phi_T, phi_X = primal.Primal(V, E_B, MR_inv, temp_bar)
for e in newE_B[1]:
#all the e is in existing E_X but v not be in existing R
temp_val = MR_inv[E_B[1].index(e)][V[0].index(v)] - (((phi_T[e_star])/fbar_T[e_star])*fbar_X[e])
temp_matrix[newE_B[1].index(e)][newR.index(v)] = temp_val
return temp_matrix
elif Case == '2b2':
#v_bar is the node that gets added to R
# col_num = E_X_list.index(e_star)
#v_bar should have already been added to R
#i thin kthat e_prime is already added to E_X_list
# E_X_list.append(e_prime)
temp_matrix = np.zeros([len_newR,len_newR])
for v in newR:
temp_R = dict.fromkeys(V[0], 0)
temp_N = dict.fromkeys(V[1], 0)
if v in R:
temp_R[v] = 1
elif v in N:
temp_N[v] = 1
temp_bar = [temp_R, temp_N]
phi_T, phi_X = primal.Primal(V, E_B, MR_inv, temp_bar)
for e in newE_B[1]:
if e == e_prime:
temp_val = -1*((phi_T[e_star])/fbar_T[e_star])
temp_matrix[newE_B[1].index(e)][newR.index(v)] = temp_val
else:
#all the e is in existing E_X but v not be in existing R
if v in R:
temp_val = MR_inv[E_B[1].index(e)][V[0].index(v)] - (((phi_T[e_star])/fbar_T[e_star])*fbar_X[e])
temp_matrix[newE_B[1].index(e)][newR.index(v)] = temp_val
else:
temp_val = (phi_X[e]) - (((phi_T[e_star])/fbar_T[e_star])*fbar_X[e])
temp_matrix[newE_B[1].index(e)][newR.index(v)] = temp_val
return temp_matrix