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Dateien nach "ILP/butadien" hochladen

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kilian
2026-09-02 13:05:54 +02:00
parent f55799c1cd
commit 935f9276a9
1 changed files with 54 additions and 174 deletions
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ILP/butadien/butadiensynthesis.py
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@@ -3,31 +3,19 @@ from gurobipy import GRB, Model, quicksum
HYPERGRAPH = {
0: (['Butadien'], []),
1: (['Butadien'], ['Butadien']),
2: (['p_{0,0}'], []),
3: (['p_{0,1}'], []),
4: (['Butadien', 'Butadien'], ['p_{0,0}', 'p_{0,1}']),
5: (['Butadien', 'Butadien'], ['Butadien', 'Butadien']),
6: (['p_{0,2}'], []),
7: (['Butadien', 'Butadien'], ['p_{0,2}']),
8: (['p_{0,1}'], ['p_{0,1}']),
9: (['p_{0,0}', 'p_{0,0}'], ['p_{0,0}', 'p_{0,0}']),
10: (['p_{0,0}', 'p_{0,1}'], ['Butadien', 'Butadien']),
11: (['p_{0,0}', 'p_{0,1}'], ['p_{0,0}', 'p_{0,1}']),
12: (['p_{0,3}'], []),
13: (['p_{0,0}', 'p_{0,2}'], ['p_{0,3}']),
14: (['p_{0,0}', 'p_{0,2}'], ['p_{0,0}', 'p_{0,2}']),
15: (['Butadien', 'p_{0,0}'], ['Butadien', 'p_{0,0}']),
16: (['p_{0,1}', 'p_{0,1}'], ['p_{0,1}', 'p_{0,1}']),
17: (['p_{0,4}'], []),
18: (['p_{0,1}', 'p_{0,1}'], ['Butadien', 'p_{0,4}']),
19: (['p_{0,5}'], []),
20: (['p_{0,1}', 'p_{0,2}'], ['Butadien', 'p_{0,5}']),
21: (['Butadien', 'p_{0,1}'], ['Butadien', 'p_{0,1}']),
22: (['p_{0,1}', 'p_{0,2}'], ['p_{0,1}', 'p_{0,2}']),
23: (['Butadien', 'p_{0,1}'], ['p_{0,0}', 'p_{0,4}']),
24: (['p_{0,2}', 'p_{0,2}'], ['p_{0,2}', 'p_{0,2}']),
25: (['Butadien', 'p_{0,2}'], ['Butadien', 'p_{0,2}']),
26: (['Butadien', 'p_{0,2}'], ['p_{0,0}', 'p_{0,5}']),
27: (['p_{0,6}'], []),
28: (['p_{0,0}', 'p_{0,1}'], ['p_{0,6}']),
@@ -41,183 +29,42 @@ HYPERGRAPH = {
36: (['p_{0,10}'], []),
37: (['Butadien', 'p_{0,1}'], ['p_{0,10}']),
38: (['p_{0,3}'], ['p_{0,0}', 'p_{0,2}']),
39: (['p_{0,3}'], ['p_{0,3}']),
40: (['p_{0,4}'], ['p_{0,4}']),
41: (['p_{0,11}'], []),
42: (['p_{0,4}'], ['p_{0,0}', 'p_{0,11}']),
43: (['p_{0,12}'], []),
44: (['p_{0,5}'], ['p_{0,12}']),
45: (['p_{0,5}'], ['p_{0,5}']),
46: (['p_{0,6}'], ['p_{0,6}']),
47: (['p_{0,8}'], ['p_{0,8}']),
48: (['p_{0,9}'], ['p_{0,9}']),
49: (['p_{0,10}'], ['p_{0,10}']),
50: (['p_{0,3}', 'p_{0,3}'], ['p_{0,3}', 'p_{0,3}']),
51: (['p_{0,3}', 'p_{0,4}'], ['p_{0,3}', 'p_{0,4}']),
52: (['p_{0,3}', 'p_{0,5}'], ['p_{0,3}', 'p_{0,5}']),
53: (['p_{0,3}', 'p_{0,6}'], ['p_{0,3}', 'p_{0,6}']),
54: (['p_{0,3}', 'p_{0,8}'], ['p_{0,3}', 'p_{0,8}']),
55: (['p_{0,3}', 'p_{0,9}'], ['p_{0,3}', 'p_{0,9}']),
56: (['p_{0,3}', 'p_{0,10}'], ['p_{0,3}', 'p_{0,10}']),
57: (['p_{0,2}', 'p_{0,3}'], ['p_{0,2}', 'p_{0,3}']),
58: (['p_{0,0}', 'p_{0,3}'], ['p_{0,0}', 'p_{0,3}']),
59: (['Butadien', 'p_{0,3}'], ['Butadien', 'p_{0,3}']),
60: (['p_{0,1}', 'p_{0,3}'], ['p_{0,1}', 'p_{0,3}']),
61: (['p_{0,4}', 'p_{0,4}'], ['p_{0,4}', 'p_{0,4}']),
62: (['p_{0,4}', 'p_{0,5}'], ['p_{0,4}', 'p_{0,5}']),
63: (['p_{0,13}'], []),
64: (['p_{0,4}', 'p_{0,6}'], ['p_{0,1}', 'p_{0,13}']),
65: (['p_{0,2}', 'p_{0,4}'], ['p_{0,1}', 'p_{0,5}']),
66: (['p_{0,0}', 'p_{0,4}'], ['Butadien', 'p_{0,1}']),
67: (['Butadien', 'p_{0,4}'], ['p_{0,1}', 'p_{0,1}']),
68: (['Butadien', 'p_{0,4}'], ['Butadien', 'p_{0,4}']),
69: (['p_{0,1}', 'p_{0,4}'], ['p_{0,1}', 'p_{0,4}']),
70: (['p_{0,4}', 'p_{0,6}'], ['p_{0,4}', 'p_{0,6}']),
71: (['p_{0,4}', 'p_{0,8}'], ['p_{0,4}', 'p_{0,8}']),
72: (['p_{0,4}', 'p_{0,9}'], ['p_{0,4}', 'p_{0,9}']),
73: (['p_{0,4}', 'p_{0,10}'], ['p_{0,4}', 'p_{0,10}']),
74: (['p_{0,2}', 'p_{0,4}'], ['p_{0,2}', 'p_{0,4}']),
75: (['p_{0,0}', 'p_{0,4}'], ['p_{0,0}', 'p_{0,4}']),
76: (['p_{0,5}', 'p_{0,5}'], ['p_{0,5}', 'p_{0,5}']),
77: (['p_{0,5}', 'p_{0,6}'], ['p_{0,2}', 'p_{0,13}']),
78: (['p_{0,2}', 'p_{0,5}'], ['p_{0,2}', 'p_{0,5}']),
79: (['p_{0,0}', 'p_{0,5}'], ['Butadien', 'p_{0,2}']),
80: (['Butadien', 'p_{0,5}'], ['p_{0,1}', 'p_{0,2}']),
81: (['Butadien', 'p_{0,5}'], ['Butadien', 'p_{0,5}']),
82: (['p_{0,1}', 'p_{0,5}'], ['p_{0,1}', 'p_{0,5}']),
83: (['p_{0,1}', 'p_{0,5}'], ['p_{0,2}', 'p_{0,4}']),
84: (['p_{0,5}', 'p_{0,6}'], ['p_{0,5}', 'p_{0,6}']),
85: (['p_{0,5}', 'p_{0,8}'], ['p_{0,5}', 'p_{0,8}']),
86: (['p_{0,5}', 'p_{0,9}'], ['p_{0,5}', 'p_{0,9}']),
87: (['p_{0,5}', 'p_{0,10}'], ['p_{0,5}', 'p_{0,10}']),
88: (['p_{0,0}', 'p_{0,5}'], ['p_{0,0}', 'p_{0,5}']),
89: (['p_{0,6}', 'p_{0,6}'], ['p_{0,6}', 'p_{0,6}']),
90: (['p_{0,6}', 'p_{0,8}'], ['p_{0,6}', 'p_{0,8}']),
91: (['p_{0,6}', 'p_{0,9}'], ['p_{0,6}', 'p_{0,9}']),
92: (['p_{0,6}', 'p_{0,10}'], ['p_{0,6}', 'p_{0,10}']),
93: (['p_{0,2}', 'p_{0,6}'], ['p_{0,2}', 'p_{0,6}']),
94: (['p_{0,0}', 'p_{0,6}'], ['p_{0,0}', 'p_{0,6}']),
95: (['Butadien', 'p_{0,6}'], ['Butadien', 'p_{0,6}']),
96: (['Butadien', 'p_{0,6}'], ['p_{0,0}', 'p_{0,13}']),
97: (['p_{0,1}', 'p_{0,6}'], ['Butadien', 'p_{0,13}']),
98: (['p_{0,1}', 'p_{0,6}'], ['p_{0,1}', 'p_{0,6}']),
99: (['p_{0,14}'], []),
100: (['p_{0,0}', 'p_{0,6}'], ['p_{0,14}']),
101: (['p_{0,15}'], []),
102: (['p_{0,0}', 'p_{0,7}'], ['p_{0,15}']),
103: (['p_{0,8}', 'p_{0,8}'], ['p_{0,8}', 'p_{0,8}']),
104: (['p_{0,8}', 'p_{0,9}'], ['p_{0,8}', 'p_{0,9}']),
105: (['p_{0,8}', 'p_{0,10}'], ['p_{0,8}', 'p_{0,10}']),
106: (['p_{0,2}', 'p_{0,8}'], ['p_{0,2}', 'p_{0,8}']),
107: (['p_{0,0}', 'p_{0,8}'], ['p_{0,0}', 'p_{0,8}']),
108: (['Butadien', 'p_{0,8}'], ['Butadien', 'p_{0,8}']),
109: (['p_{0,1}', 'p_{0,8}'], ['p_{0,1}', 'p_{0,8}']),
110: (['p_{0,9}', 'p_{0,9}'], ['p_{0,9}', 'p_{0,9}']),
111: (['p_{0,9}', 'p_{0,10}'], ['p_{0,9}', 'p_{0,10}']),
112: (['p_{0,2}', 'p_{0,9}'], ['p_{0,2}', 'p_{0,9}']),
113: (['p_{0,0}', 'p_{0,9}'], ['p_{0,0}', 'p_{0,9}']),
114: (['Butadien', 'p_{0,9}'], ['Butadien', 'p_{0,9}']),
115: (['p_{0,1}', 'p_{0,9}'], ['p_{0,1}', 'p_{0,9}']),
116: (['p_{0,10}', 'p_{0,10}'], ['p_{0,10}', 'p_{0,10}']),
117: (['p_{0,2}', 'p_{0,10}'], ['p_{0,2}', 'p_{0,10}']),
118: (['p_{0,0}', 'p_{0,10}'], ['p_{0,0}', 'p_{0,10}']),
119: (['Butadien', 'p_{0,10}'], ['Butadien', 'p_{0,10}']),
120: (['p_{0,1}', 'p_{0,10}'], ['p_{0,1}', 'p_{0,10}']),
121: (['p_{0,0}', 'p_{0,4}'], ['p_{0,13}']),
122: (['p_{0,16}'], []),
123: (['p_{0,0}', 'p_{0,4}'], ['p_{0,16}']),
124: (['p_{0,17}'], []),
125: (['Butadien', 'p_{0,7}'], ['p_{0,17}']),
126: (['p_{0,11}'], ['p_{0,11}']),
127: (['p_{0,12}'], ['p_{0,5}']),
128: (['p_{0,12}'], ['p_{0,12}']),
129: (['p_{0,13}'], ['p_{0,13}']),
130: (['p_{0,14}'], ['p_{0,0}', 'p_{0,6}']),
131: (['p_{0,14}'], ['p_{0,14}']),
132: (['p_{0,15}'], ['p_{0,0}', 'p_{0,7}']),
133: (['p_{0,15}'], ['p_{0,15}']),
134: (['p_{0,16}'], ['p_{0,16}']),
135: (['p_{0,0}', 'p_{0,11}'], ['p_{0,4}']),
136: (['p_{0,12}', 'p_{0,12}'], ['p_{0,12}', 'p_{0,12}']),
137: (['p_{0,12}', 'p_{0,13}'], ['p_{0,12}', 'p_{0,13}']),
138: (['p_{0,12}', 'p_{0,14}'], ['p_{0,12}', 'p_{0,14}']),
139: (['p_{0,12}', 'p_{0,15}'], ['p_{0,12}', 'p_{0,15}']),
140: (['p_{0,12}', 'p_{0,16}'], ['p_{0,12}', 'p_{0,16}']),
141: (['p_{0,8}', 'p_{0,12}'], ['p_{0,8}', 'p_{0,12}']),
142: (['p_{0,9}', 'p_{0,12}'], ['p_{0,9}', 'p_{0,12}']),
143: (['Butadien', 'p_{0,12}'], ['Butadien', 'p_{0,12}']),
144: (['p_{0,10}', 'p_{0,12}'], ['p_{0,10}', 'p_{0,12}']),
145: (['p_{0,0}', 'p_{0,12}'], ['p_{0,0}', 'p_{0,12}']),
146: (['p_{0,1}', 'p_{0,12}'], ['p_{0,1}', 'p_{0,12}']),
147: (['p_{0,2}', 'p_{0,12}'], ['p_{0,2}', 'p_{0,12}']),
148: (['p_{0,3}', 'p_{0,12}'], ['p_{0,3}', 'p_{0,12}']),
149: (['p_{0,4}', 'p_{0,12}'], ['p_{0,4}', 'p_{0,12}']),
150: (['p_{0,5}', 'p_{0,12}'], ['p_{0,5}', 'p_{0,12}']),
151: (['p_{0,6}', 'p_{0,12}'], ['p_{0,6}', 'p_{0,12}']),
152: (['p_{0,13}', 'p_{0,13}'], ['p_{0,13}', 'p_{0,13}']),
153: (['Butadien', 'p_{0,13}'], ['p_{0,1}', 'p_{0,6}']),
154: (['Butadien', 'p_{0,13}'], ['Butadien', 'p_{0,13}']),
155: (['p_{0,0}', 'p_{0,13}'], ['Butadien', 'p_{0,6}']),
156: (['p_{0,1}', 'p_{0,13}'], ['p_{0,1}', 'p_{0,13}']),
157: (['p_{0,1}', 'p_{0,13}'], ['p_{0,4}', 'p_{0,6}']),
158: (['p_{0,2}', 'p_{0,13}'], ['p_{0,5}', 'p_{0,6}']),
159: (['p_{0,4}', 'p_{0,13}'], ['p_{0,4}', 'p_{0,13}']),
160: (['p_{0,5}', 'p_{0,13}'], ['p_{0,5}', 'p_{0,13}']),
161: (['p_{0,6}', 'p_{0,13}'], ['p_{0,6}', 'p_{0,13}']),
162: (['p_{0,13}', 'p_{0,14}'], ['p_{0,13}', 'p_{0,14}']),
163: (['p_{0,13}', 'p_{0,15}'], ['p_{0,13}', 'p_{0,15}']),
164: (['p_{0,13}', 'p_{0,16}'], ['p_{0,13}', 'p_{0,16}']),
165: (['p_{0,8}', 'p_{0,13}'], ['p_{0,8}', 'p_{0,13}']),
166: (['p_{0,9}', 'p_{0,13}'], ['p_{0,9}', 'p_{0,13}']),
167: (['p_{0,10}', 'p_{0,13}'], ['p_{0,10}', 'p_{0,13}']),
168: (['p_{0,0}', 'p_{0,13}'], ['p_{0,0}', 'p_{0,13}']),
169: (['p_{0,2}', 'p_{0,13}'], ['p_{0,2}', 'p_{0,13}']),
170: (['p_{0,3}', 'p_{0,13}'], ['p_{0,3}', 'p_{0,13}']),
171: (['p_{0,14}', 'p_{0,14}'], ['p_{0,14}', 'p_{0,14}']),
172: (['p_{0,14}', 'p_{0,15}'], ['p_{0,14}', 'p_{0,15}']),
173: (['p_{0,14}', 'p_{0,16}'], ['p_{0,14}', 'p_{0,16}']),
174: (['p_{0,8}', 'p_{0,14}'], ['p_{0,8}', 'p_{0,14}']),
175: (['p_{0,9}', 'p_{0,14}'], ['p_{0,9}', 'p_{0,14}']),
176: (['Butadien', 'p_{0,14}'], ['Butadien', 'p_{0,14}']),
177: (['p_{0,10}', 'p_{0,14}'], ['p_{0,10}', 'p_{0,14}']),
178: (['p_{0,0}', 'p_{0,14}'], ['p_{0,0}', 'p_{0,14}']),
179: (['p_{0,1}', 'p_{0,14}'], ['p_{0,1}', 'p_{0,14}']),
180: (['p_{0,2}', 'p_{0,14}'], ['p_{0,2}', 'p_{0,14}']),
181: (['p_{0,3}', 'p_{0,14}'], ['p_{0,3}', 'p_{0,14}']),
182: (['p_{0,4}', 'p_{0,14}'], ['p_{0,4}', 'p_{0,14}']),
183: (['p_{0,5}', 'p_{0,14}'], ['p_{0,5}', 'p_{0,14}']),
184: (['p_{0,6}', 'p_{0,14}'], ['p_{0,6}', 'p_{0,14}']),
185: (['p_{0,15}', 'p_{0,15}'], ['p_{0,15}', 'p_{0,15}']),
186: (['p_{0,15}', 'p_{0,16}'], ['p_{0,15}', 'p_{0,16}']),
187: (['p_{0,8}', 'p_{0,15}'], ['p_{0,8}', 'p_{0,15}']),
188: (['p_{0,9}', 'p_{0,15}'], ['p_{0,9}', 'p_{0,15}']),
189: (['Butadien', 'p_{0,15}'], ['Butadien', 'p_{0,15}']),
190: (['p_{0,10}', 'p_{0,15}'], ['p_{0,10}', 'p_{0,15}']),
191: (['p_{0,0}', 'p_{0,15}'], ['p_{0,0}', 'p_{0,15}']),
192: (['p_{0,1}', 'p_{0,15}'], ['p_{0,1}', 'p_{0,15}']),
193: (['p_{0,2}', 'p_{0,15}'], ['p_{0,2}', 'p_{0,15}']),
194: (['p_{0,3}', 'p_{0,15}'], ['p_{0,3}', 'p_{0,15}']),
195: (['p_{0,4}', 'p_{0,15}'], ['p_{0,4}', 'p_{0,15}']),
196: (['p_{0,5}', 'p_{0,15}'], ['p_{0,5}', 'p_{0,15}']),
197: (['p_{0,6}', 'p_{0,15}'], ['p_{0,6}', 'p_{0,15}']),
198: (['p_{0,16}', 'p_{0,16}'], ['p_{0,16}', 'p_{0,16}']),
199: (['p_{0,8}', 'p_{0,16}'], ['p_{0,8}', 'p_{0,16}']),
200: (['p_{0,9}', 'p_{0,16}'], ['p_{0,9}', 'p_{0,16}']),
201: (['Butadien', 'p_{0,16}'], ['Butadien', 'p_{0,16}']),
202: (['p_{0,10}', 'p_{0,16}'], ['p_{0,10}', 'p_{0,16}']),
203: (['p_{0,0}', 'p_{0,16}'], ['p_{0,0}', 'p_{0,16}']),
204: (['p_{0,1}', 'p_{0,16}'], ['p_{0,1}', 'p_{0,16}']),
205: (['p_{0,2}', 'p_{0,16}'], ['p_{0,2}', 'p_{0,16}']),
206: (['p_{0,3}', 'p_{0,16}'], ['p_{0,3}', 'p_{0,16}']),
207: (['p_{0,4}', 'p_{0,16}'], ['p_{0,4}', 'p_{0,16}']),
208: (['p_{0,5}', 'p_{0,16}'], ['p_{0,5}', 'p_{0,16}']),
209: (['p_{0,6}', 'p_{0,16}'], ['p_{0,6}', 'p_{0,16}']),
210: (['p_{0,18}'], []),
211: (['Butadien', 'p_{0,11}'], ['p_{0,18}']),
212: (['p_{0,18}'], ['p_{0,18}']),
213: ([], ['Butadien']),
}
VERTICES = ['Butadien', 'p_{0,0}', 'p_{0,1}', 'p_{0,2}', 'p_{0,3}', 'p_{0,4}', 'p_{0,5}', 'p_{0,6}', 'p_{0,7}', 'p_{0,8}', 'p_{0,9}', 'p_{0,10}', 'p_{0,11}', 'p_{0,12}', 'p_{0,13}', 'p_{0,14}', 'p_{0,15}', 'p_{0,16}', 'p_{0,17}', 'p_{0,18}']
#Vergleich mit dem NMR von Ethylen und Hexatrien
NMR1 = [0.32, 0.5, 0.87, 0.0, 0.11, 0.58, 0.06, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.09, 0.0, 0.0, 0.17, 0.0, 0.09]
@@ -226,37 +73,53 @@ NMR2 = [0.33, 0.43, 0.6, 0.0, 0.13, 0.9, 0.07, 0.01, 0.0, 0.0, 0.01, 0.0, 0.0, 0
#Vergleich mit dem NMR von Ethylen und Benzol
NMR3 = [0.0, 0.32, 0.0, 0.0, 0.0, 0.0, 0.05, 0.0, 0.0, 0.02, 0.0, 0.29, 0.95, 0.17, 0.0, 0.0, 0.0, 0.0, 0.0, 0.05]
VERTICESSMILES = ['C=CC=C', 'C=C', 'C=CC=CC=C', 'C1CCC(C=C)CC=1', 'C(CCC(C=C)CC=C)=C', 'C=CC=CC=CC=C', 'C1CCC(C=CC=C)CC=1', 'C=CC1C=CCCC1', 'C1CCCCC=1', 'C=CC1CC=CCC1C=C', 'C1CCC(C=C)C(C=C)C=1', 'C(C1CC(C=C)C=CC1)=C', 'C1C=CC=CC=1', 'C(CCC1C=CC=CC1)=C', 'C1C(C=CC=C)CCCC=1', 'C=CC(C=C)CCCC=C', 'C=CCCCCC=C', 'C=CC1C=CC(C=C)CC1', 'C1CC2CCCCC2CC=1', 'C1CC2C=CC=CC2CC=1']
NMRMAX = [max(n1,n2,n3) for n1,n2,n3 in zip(NMR1,NMR2,NMR3)]
FIXED_FLOWS = {
213: 3,
41: 1,
#2: 3,
#4: 1,
#23: 1,
#41: 1,
#42: 1,
}
def build_model(name, hyperedges, vertices, nmrlikelihoods1, nmrlikelihoods2, nmrlikelihoods3, excluded_support=None):
def build_model(name, hyperedges, vertices, nmrlikelihoodsmax, nmrlikelihoods1, nmrlikelihoods2, nmrlikelihoods3, excluded_support=None):
model = Model(name)
x = {e_id: model.addVar(vtype=GRB.INTEGER, lb = 0, name = f"x_{e_id}") for e_id in hyperedges}
b = {e_id: model.addVar(vtype=GRB.BINARY, name = f"b_{e_id}") for e_id in hyperedges}
nmax = model.addVars(vertices, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 1.0, name = "nmrmax")
n1 = model.addVars(vertices, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 1.0, name = "nmr1")
n2 = model.addVars(vertices, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 1.0, name = "nmr2")
n3 = model.addVars(vertices, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 1.0, name = "nmr3")
en1 = model.addVars(vertices, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 2.0, name = "edgenmr1")
en2 = model.addVars(vertices, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 2.0, name = "edgenmr2")
en3 = model.addVars(vertices, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 2.0, name = "edgenmr3")
enmax = model.addVars(vertices, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 1.0, name = "edgenmrmax")
en1 = model.addVars(vertices, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 1.0, name = "edgenmr1")
en2 = model.addVars(vertices, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 1.0, name = "edgenmr2")
en3 = model.addVars(vertices, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 1.0, name = "edgenmr3")
#Assigns every Molecule the likelihood compared to the three different reference spectra
for v, nmr1, nmr2, nmr3 in zip(vertices, nmrlikelihoods1, nmrlikelihoods2, nmrlikelihoods3):
for v, nmrmax, nmr1, nmr2, nmr3 in zip(vertices, nmrlikelihoodsmax, nmrlikelihoods1, nmrlikelihoods2, nmrlikelihoods3):
nmax[v] = nmrmax
n1[v] = nmr1
n2[v] = nmr2
n3[v] = nmr3
#Assigns the edges a likelihood based on the products
for e, (_, heads) in hyperedges.items():
en1[e] = quicksum(n1[head] for head in heads)
en2[e] = quicksum(n2[head] for head in heads)
en3[e] = quicksum(n3[head] for head in heads)
for e, (tails, heads) in hyperedges.items():
if heads != [] and tails != []:
enmax[e] = quicksum(nmax[head] for head in heads)/len(heads)
en1[e] = quicksum(n1[head] for head in heads)/len(heads)
en2[e] = quicksum(n2[head] for head in heads)/len(heads)
en3[e] = quicksum(n3[head] for head in heads)/len(heads)
else:
enmax[e] = 0.0
en1[e] = 0.0
en2[e] = 0.0
en3[e] = 0.0
print(en1[203])
print(enmax[123])
print(enmax[42])
vertices = set(v for tails, heads in hyperedges.values() for v in tails + heads)
@@ -281,22 +144,39 @@ def build_model(name, hyperedges, vertices, nmrlikelihoods1, nmrlikelihoods2, nm
#Multiplizier den node Wert mit infow + outflow
model.ModelSense = GRB.MAXIMIZE
#Multiply node value with infow or outflow
model.setObjectiveN(
quicksum((en1[e_id] + en2[e_id] + en3[e_id]) * x[e_id] for e_id, (_, _) in hyperedges.items()),
quicksum(enmax[e_id] * x[e_id] for e_id, (_, _) in hyperedges.items()),
index = 0,
priority = 2,
name = "maximize_nmr_similarity",
)
model.setObjectiveN(
quicksum(-1 * x[e_id] for e_id in hyperedges),
index=3,
priority=1,
quicksum(x[e_id] for e_id in hyperedges),
index=1,
priority= - 1,
name="minimize_used_hyperedges",
)
#Excluding creation and destruction only three reactions for three nmr
model.addConstr(quicksum(b[e_id] for e_id, (heads, tails) in hyperedges.items() if tails != [] and heads != []) == 3)
#Restrict number of used edges to prevent using all available
#model.addConstr(quicksum(x[e_id] for e_id in hyperedges) <= 10)
#2 Butadien create first different molecule:
model.addConstr(b[4] + b[7] == 1)
#Every item created has to be consumed:
#No cyclic reaction pairs:
for e_id1, (heads1, tails1) in hyperedges.items():
for e_id2, (heads2, tails2) in hyperedges.items():
if (heads1, tails1) == (tails2, heads2):
#print(e_id1, e_id2)
model.addConstr((b[e_id1] + b[e_id2]) <= 1)
return model, x, b
@@ -317,7 +197,7 @@ def print_solution(title, flow_solution, binary_solution, hyperedges):
print(f"Number of used hyperedges: {len(binary_solution)}")
def main():
model, x, b = build_model("HypergraphFlow", HYPERGRAPH, VERTICES, NMR1, NMR2, NMR3)
model, x, b = build_model("HypergraphFlow", HYPERGRAPH, VERTICES, NMRMAX, NMR1, NMR2, NMR3)
model.optimize()
if model.status != GRB.Status.OPTIMAL:
print("No optimal solution found for the first model.")
@@ -326,16 +206,16 @@ def main():
optimal_binary_solution = positive_entries(b)
print_solution("Optimal Solution", optimal_solution, optimal_binary_solution, HYPERGRAPH)
""" excluded_support = list(optimal_binary_solution.keys())
second_model, x2, b2 = build_model("SecondBestHypergraphFlow", HYPEREDGES, excluded_support=excluded_support,)
excluded_support = list(optimal_binary_solution.keys())
second_model, x2, b2 = build_model("SecondBestHypergraphFlow", HYPERGRAPH, VERTICES, NMRMAX, NMR1, NMR2, NMR3, excluded_support=excluded_support,)
second_model.optimize()
if second_model.status == GRB.Status.OPTIMAL:
second_solution = positive_entries(x2)
second_binary_solution = positive_entries(b2)
print_solution("Second Best Solution", second_solution, second_binary_solution, HYPEREDGES, VERTICES)
print_solution("Second Best Solution", second_solution, second_binary_solution, HYPERGRAPH)
else:
print("No optimal solution found for the second best model.")
"""
if __name__ == "__main__":
main()