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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text

mol_moe/data/moleculenet/bbbp/test.csv

@@ -0,0 +1,195 @@
+num,name,p_np,smiles
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mol_moe/data/moleculenet/bbbp/valid.csv

@@ -0,0 +1,206 @@
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mol_moe/data/moleculenet/clintox/train.csv

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+CC(C)COCC(CN(Cc1ccccc1)c2ccccc2)[NH+]3CCCC3,1,0
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+CC(C)NC(=O)c1ccc(cc1)CNNC,1,0
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+CC(C)NCC(COC1=CC=CC2=CC=CC=C21)O,0,1
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+CC(Cc1ccc2c(c1)OCO2)[NH2+]CC(c3ccc(c(c3)O)O)O,1,0
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+CC(Cc1ccccc1)[NH3+],1,0
+CC(CCc1ccc(cc1)O)[NH2+]CCc2ccc(c(c2)O)O,1,0
+CC(CCc1ccccc1)[NH2+]CC(c2ccc(c(c2)C(=O)N)O)O,1,0
+CC(CCC[NH3+])Nc1cc(cc2c1nccc2)OC,1,0
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+CC(CN1c2ccccc2Sc3c1cccc3)[NH+](C)C,1,0
+CC(CN1CC[NH+](CCN(CCN(CC1)CC(=O)[O-])CC(=O)[O-])CC(=O)[O-])O,1,0
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mol_moe/data/moleculenet/clintox/valid.csv

@@ -0,0 +1,149 @@
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+C[C@@H]1[C@H]([C@H](C[C@@H](O1)OC2[C@H](O[C@H](C[C@@H]2O)O[C@@H]3[C@H](O[C@H](C[C@@H]3O)OC4CC[C@]5([C@@H](C4)CC[C@@H]6[C@@H]5CC[C@]7([C@@]6(CC[C@@H]7C8=CC(=O)OC8)O)C)C)C)C)OC(=O)C)O,1,0
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+C[C@@H]1C[C@H]2[C@@H]3C[C@@H](C4=CC(=O)C=C[C@@]4([C@]3([C@H](C[C@@]2([C@]1(C(=O)SCF)OC(=O)c5ccco5)C)O)F)C)F,1,0
+C[C@@H]1C[C@H]2[C@@H]3C[C@@H](C4=CC(=O)C=C[C@@]4([C@]3([C@H](C[C@@]2([C@H]1C(=O)COC(=O)C(C)(C)C)C)O)Cl)C)F,1,0
+C[C@@H]1C[C@H]2[C@@H]3CCC4=CC(=O)C=C[C@@]4([C@]3([C@H](C[C@@]2([C@]1(C(=O)CCl)OC(=O)c5ccco5)C)O)Cl)C,1,0
+C[C@@H]1C[C@H]2[C@@H]3CCC4=CC(=O)C=C[C@@]4([C@]3([C@H](C[C@@]2([C@]1(C(=O)CO)O)C)O)F)C,1,1
+C[C@@H]1C[C@H]2[C@@H]3CCC4=CC(=O)C=C[C@@]4([C@]3([C@H](C[C@@]2([C@]1(C(=O)COP(=O)([O-])[O-])O)C)O)F)C,1,0
+C[C@]12C[C@@H]([C@]3([C@H]([C@@H]1C[C@@H]4[C@]2(OC(O4)(C)C)C(=O)COC(=O)CC(C)(C)C)CCC5=CC(=O)C=C[C@@]53C)F)O,1,0
+C[C@]12C[C@@H]([C@H]3[C@H]([C@@H]1C[C@@H]4[C@]2(OC(O4)(C)C)C(=O)CO)CCC5=CC(=O)C=C[C@]35C)O,1,0
+C[C@]12C[C@@H]([C@H]3[C@H]([C@@H]1CC[C@@]2(C(=O)CO)O)C[C@@H](C4=CC(=O)C=C[C@]34C)F)O,1,0
+C[C@]12C[C@@H]([C@H]3[C@H]([C@@H]1CC[C@@]2(C(=O)CO)O)CCC4=CC(=O)C=C[C@]34C)O,1,1
+C[C@]12C[C@@H]([C@H]3[C@H]([C@@H]1CC[C@@]2(C(=O)COC(=O)CC(C)(C)C)O)CCC4=CC(=O)C=C[C@]34C)O,1,0
+C[C@]12CC[C@H]3[C@H]([C@@H]1CC[C@]2(C#C)O)CCC4=CC(=O)CC[C@H]34,1,0
+C[C@]12CC[C@H]3[C@H]([C@@H]1CC[C@]2(C)O)CC[C@@H]4[C@@]3(C/C(=C/[O-])/C(=O)C4)C,1,0
+C[C@]12CCC(=O)C=C1CC[C@@H]3[C@@H]2CC[C@]4([C@H]3CC[C@]4(C)O)C,1,0
+C[C@H]([C@@H](C(=O)NCC(=O)N[C@@H](Cc1c[nH]c2c1cccc2)C(=O)N[C@@H](CCSC)C(=O)N[C@@H](CC(=O)[O-])C(=O)N[C@@H](Cc3ccccc3)C(=O)N)NC(=O)[C@H](Cc4ccc(cc4)OS(=O)(=O)[O-])NC(=O)[C@H](CC(=O)[O-])NC(=O)[C@H](CCC(=O)N)NC(=O)[C@@H]5CCC(=O)N5)O,1,0
+C[C@H](C(=O)N)NC(=O)[C@@H]1CCCN1C(=O)[C@H](CCCC[NH2+]C(C)C)NC(=O)[C@H](CC(C)C)NC(=O)[C@@H](CC(=O)N)NC(=O)[C@H](Cc2ccc(cc2)O)N(C)C(=O)[C@H](CO)NC(=O)[C@@H](Cc3cccnc3)NC(=O)[C@@H](Cc4ccc(cc4)Cl)NC(=O)[C@@H](Cc5ccc6ccccc6c5)NC(=O)C,1,0
+C[C@H]1C[C@@H]2[C@H](CC[C@]3([C@H]2CC[C@@]3(C(=O)C)OC(=O)C)C)[C@@]4(C1=CC(=O)CC4)C,1,0
+C[C@H]1C[C@H]2[C@@H]3C[C@@H](C4=CC(=O)C=C[C@@]4([C@]3([C@H](C[C@@]2([C@]1(C(=O)COC(=O)C)OC(=O)C)C)O)F)C)F,1,0
+C[C@H]1C[C@H]2[C@@H]3CC[C@@]([C@]3(C[C@@H]([C@@]2([C@@]4(C1=CC(=O)C=C4)C)F)O)C)(C(=O)C)O,1,0
+C[C@H]1C[C@H]2[C@@H]3CC[C@@]([C@]3(C[C@@H]([C@@]2([C@@]4(C1=CC(=O)C=C4)C)F)O)C)(C(=O)C)OC(=O)C,1,0
+C[C@H]1C[C@H]2[C@@H]3CC[C@@]([C@]3(C[C@@H]([C@@H]2[C@@]4(C1=CC(=O)C=C4)C)O)C)(C(=O)CO)O,1,0
+C[C@H]1C[C@H]2[C@@H]3CC[C@@H]([C@]3(C[C@@H]([C@@H]2[C@@]4(C1=CC(=O)CC4)C)O)C)C(=O)C,1,0
+C[C@H]1C[C@H]2[C@@H]3CCC4=CC(=O)C=C[C@@]4([C@]3([C@H](C[C@@]2([C@]1(C(=O)CO)O)C)O)F)C,1,0
+C[C@H]1C[C@H]2[C@@H]3CCC4=CC(=O)C=C[C@@]4([C@]3([C@H](C[C@@]2([C@]1(C(=O)CO)OC(=O)c5ccccc5)C)O)F)C,1,0
+C[C@H]1C[C@H]2[C@@H]3CCC4=CC(=O)C=C[C@@]4([C@]3([C@H](C[C@@]2([C@]1(C(=O)COC(=O)C)O)C)O)F)C,1,0
+C[N+]1(CCc2cc(c(c(c2[C@H]1Cc3cc(c(c(c3)OC)OC)OC)OC)OC)OC)CCCOC(=O)CCC(=O)OCCC[N+]4(CCc5cc(c(c(c5[C@@H]4Cc6cc(c(c(c6)OC)OC)OC)OC)OC)OC)C,1,0
+C[N@@+]1(CCc2cc(c(cc2[C@H]1Cc3ccc(c(c3)OC)OC)OC)OC)CCC(=O)OCCCCCOC(=O)CC[N@+]4(CCc5cc(c(cc5[C@H]4Cc6ccc(c(c6)OC)OC)OC)OC)C,1,0
+C[NH+](C)CCOc1ccc(cc1)/C(=C(/CCCl)\c2ccccc2)/c3ccccc3,1,0
+C[NH+]1C[C@@H]2c3ccccc3Oc4ccc(cc4[C@H]2C1)Cl,1,0
+C[NH+]1CCC(C1)CN2c3ccccc3Sc4c2cccc4,1,0
+C[NH+]1CCC(=C2c3ccccc3C=Cc4c2cccc4)CC1,1,0
+C[NH+]1CCN(CC1)CC/C=C\2/c3ccccc3Sc4c2cc(cc4)S(=O)(=O)N(C)C,1,0
+C[NH+]1CCN(CC1)CCCN2c3ccccc3Sc4c2cc(cc4)C(F)(F)F,1,0
+CC#CCn1c2c(nc1N3CCC[C@H](C3)[NH3+])n(c(=O)n(c2=O)Cc4nc(c5ccccc5n4)C)C,1,0
+CC(C(=O)NCC(=O)[O-])S,1,0
+CC(C)(C)[NH2+]CC(c1ccc(c(c1)CO)O)O,1,0
+CC(C)(C)[NH2+]CC(COc1cccc2c1C[C@@H]([C@@H](C2)O)O)O,1,0
+CC(C)CN(C[C@H]([C@H](Cc1ccccc1)NC(=O)O[C@H]2CCOC2)OP(=O)([O-])[O-])S(=O)(=O)c3ccc(cc3)N,1,0
+CC(C)OC(=O)CCC/C=C\C[C@H]1[C@H](C[C@H]([C@@H]1CC[C@H](CCc2ccccc2)O)O)O,1,0
+CC(CN1c2ccccc2Sc3c1cccc3)C[NH+](C)C,1,0
+CC(=O)c1ccc2c(c1)N(c3ccccc3S2)CCC[NH+]4CCC(CC4)CCO,1,0
+CC(=O)Nc1c(c(c(c(c1I)N(C)C(=O)C)I)C(=O)[O-])I,1,0
+CC(=O)O[C@]1(CC[C@@H]2[C@@]1(CC[C@H]3[C@H]2CCC4=CC(=O)CC[C@H]34)C)C#C,1,0
+CC(=O)O[C@H]1CC[C@@H]2[C@H]3CC[C@]4([C@H]([C@@H]3CCC2=C1)CC[C@]4(C#C)OC(=O)C)C,1,0
+CC(=O)OCC(=O)[C@@]12[C@@H](C[C@@H]3[C@@]1(C[C@@H]([C@]4([C@H]3C[C@@H](C5=CC(=O)C=C[C@@]54C)F)F)O)C)OC(O2)(C)C,1,0
+CC(=O)OCC(=O)[C@]1(CC[C@@H]2[C@@]1(C[C@@H]([C@H]3[C@H]2CCC4=CC(=O)CC[C@]34C)O)C)O,1,0
+CC(=O)OCC(=O)[C@H]1CC[C@@H]2[C@@]1(CC[C@H]3[C@H]2CCC4=CC(=O)CC[C@]34C)C,1,0
+CC(=O)OCC1=C(N2[C@@H]([C@@H](C2=O)NC(=O)/C(=N\OC)/c3csc(n3)N)SC1)C(=O)[O-],1,0
+CC(=O)OCC1=C(N2[C@@H]([C@@H](C2=O)NC(=O)[C@@H](c3ccccc3)[NH3+])SC1)C(=O)[O-],1,0
+CC/C(=C(\c1ccccc1)/c2ccc(cc2)OCC[NH+](C)C)/c3ccccc3,1,0
+CC1([C@@H](N2[C@H](S1)[C@@H](C2=O)NC(=O)[C@@H](c3ccccc3)[NH3+])C(=O)[O-])C,1,0
+CC1([C@@H](N2[C@H](S1)[C@@H](C2=O)NC(=O)COc3ccccc3)C(=O)[O-])C,1,0
+CC1(C(=O)N(C(=O)O1)C)C,1,0
+C=C1[C@H](C[C@@H]([C@H]1CO)O)n2cnc3c2nc([nH]c3=O)N,1,0
+Cc1c(c(c(c2c1OC(CC2)(C)CCCC(C)CCCC(C)CCCC(C)C)C)OC(=O)C)C,1,0
+Cc1cc(c(c(c1/C=C/C(=C/C=C/C(=C/C(=O)[O-])/C)/C)C)C)OC,1,0
+Cc1cc(cc(c1Nc2ccnc(n2)Nc3ccc(cc3)C#N)C)/C=C/C#N,1,0
+Cc1cc2=C(Nc3ccccc3N=c2s1)N4CC[NH+](CC4)C,1,0
+Cc1ccc(cc1Nc2nccc(n2)c3cccnc3)NC(=O)c4ccc(cc4)CN5CC[NH+](CC5)C,1,0
+Cc1nccn1CC2CCc3c(c4ccccc4n3C)C2=O,1,0
+CC[NH2+][C@H]1C[C@@H](S(=O)(=O)c2c1cc(s2)S(=O)(=O)N)C,1,0
+CCC(C)CCCC(=O)N[C@@H](CC[NH3+])C(=O)N[C@@H]([C@@H](C)O)C(=O)N[C@@H](CC[NH3+])C(=O)N[C@H]1CCNC(=O)[C@@H](NC(=O)[C@@H](NC(=O)[C@@H](NC(=O)[C@@H](NC(=O)[C@H](NC(=O)[C@@H](NC1=O)CC[NH3+])CC(C)C)CC(C)C)CC[NH3+])CC[NH3+])[C@@H](C)O,1,0
+C=CC(CCC(=O)[O-])[NH3+],1,0
+CCC(=O)O[C@@](Cc1ccccc1)(c2ccccc2)[C@@H](C)C[NH+](C)C,1,0
+CCC(=O)O[C@@]1([C@@H](C[C@@H]2[C@@]1(C[C@@H]([C@]3([C@H]2C[C@@H](C4=CC(=O)C=C[C@@]43C)F)F)O)C)C)C(=O)SCF,1,0
+CCC(=O)O[C@@]1([C@H](C[C@@H]2[C@@]1(C[C@@H]([C@]3([C@H]2CCC4=CC(=O)C=C[C@@]43C)F)O)C)C)C(=O)CCl,1,0
+CCC(=O)OC(C(C)C)OP(=O)(CCCCc1ccccc1)CC(=O)N2C[C@@H](C[C@H]2C(=O)[O-])C3CCCCC3,1,0
+CCC(=O)OCC(=O)[C@]1([C@@H](C[C@@H]2[C@@]1(C[C@@H]([C@H]3[C@H]2[C@@H](CC4=CC(=O)C=C[C@]34C)Cl)O)C)C)OC(=O)CC,1,0
+CCC(=O)OCC(=O)[C@]1([C@H](C[C@@H]2[C@@]1(C[C@@H]([C@]3([C@H]2CCC4=CC(=O)C=C[C@@]43C)Cl)O)C)C)OC(=O)CC,1,0
+CCC1(CCC(=O)NC1=O)c2ccccc2,1,0
+CCc1c([nH]c2c1C(=O)C(CC2)C[NH+]3CCOCC3)C,1,0
+CCC1=C(CN(C1=O)C(=O)NCCc2ccc(cc2)S(=O)(=O)[N-]C(=O)NC3CCC(CC3)C)C,1,0
+C=CC1=C(N2[C@@H]([C@@H](C2=O)NC(=O)/C(=N\O)/c3csc(n3)N)SC1)C(=O)[O-],1,0
+CCC1=C[C@H]2C[C@@](C3=C(CN(C2)C1)C4=CC=CC=C4N3)(C5=C(C=C6C(=C5)[C@]78CCN9[C@H]7[C@@](C=CC9)([C@H]([C@@]([C@@H]8N6C)(C(=O)OC)O)OC(=O)C)CC)OC)C(=O)OC,0,1
+CCC1Nc2cc(c(cc2C(=O)N1)S(=O)(=O)N)Cl,1,0
+CCC[C@@H]1C[C@H]([NH+](C1)C)C(=O)NC([C@@H]2[C@@H]([C@@H]([C@H]([C@H](O2)SC)O)O)O)C(C)Cl,1,0
+CCC[NH2+]C(C)C(=O)Nc1ccccc1C,1,0
+CCCC(CCC)C(=O)[O-],1,0
+CCCC(=O)Nc1ccc(c(c1)C(=O)C)OCC(C[NH2+]C(C)C)O,1,0
+CCCC(=O)OCOC(=O)C1=C(NC(=C(C1c2cccc(c2Cl)Cl)C(=O)OC)C)C,1,0
+CCCc1cc(=O)[nH]c(=S)[nH]1,1,0
+CCCCC([C@]1(CC[C@H]2[C@H](O1)CC(=O)[C@H]2CCCCCCC(=O)[O-])O)(F)F,1,0
+CCCCC(=O)N(Cc1ccc(cc1)c2ccccc2c3[n-]nnn3)[C@@H](C(C)C)C(=O)[O-],1,0
+CCCCC[C@@H](/C=C/[C@H]1[C@@H](C[C@@H]([C@@H]1C/C=C\CCCC(=O)[O-])O)O)O,1,0
+CCCCC[C@@H](/C=C/[C@H]1[C@@H](CC(=O)[C@@H]1C/C=C\CCCC(=O)[O-])O)O,1,0
+CCCCCCCCCCCCCCCC(=O)OCC(COP(=O)([O-])OCC[N+](C)(C)C)OC(=O)CCCCCCCCCCCCCCC,1,0
+CCCCOCCOCCOCc1cc2c(cc1CCC)OCO2,1,0
+CCCNC(=O)[N-]S(=O)(=O)c1ccc(cc1)Cl,1,0
+CCOC(=O)Nc1ccc2c(c1)N(c3ccccc3S2)C(=O)CC[NH+]4CCOCC4,1,0
+CCOc1cc(ccc1C(=O)[O-])CC(=O)N[C@@H](CC(C)C)c2ccccc2N3CCCCC3,1,0
+CCOc1ccc2c(c1)sc(n2)S(=O)(=O)N,1,0
+CCOc1ccccc1OCC[NH2+][C@H](C)Cc2ccc(c(c2)S(=O)(=O)N)OC,1,0
+CCS(=O)(=O)CCn1c(ncc1[N+](=O)[O-])C,1,0
+CN1CCC[NH+]=C1COC(=O)C(c2ccccc2)(C3CCCCC3)O,1,0
+Cn1cnc2c1c(=O)n(c(=O)n2C)C,1,0
+CO/N=C(/c1ccco1)\C(=O)N[C@H]2[C@@H]3N(C2=O)C(=C(CS3)COC(=O)N)C(=O)[O-],1,0
+CO/N=C/1\CN(CC1C[NH3+])c2c(cc3c(=O)c(cn(c3n2)C4CC4)C(=O)[O-])F,1,0
+COc1c(ncnc1OC)[N-]S(=O)(=O)c2ccc(cc2)N,1,0
+COc1c2c(ccc(=O)o2)cc3c1occ3,1,0
+COc1cc(cc(c1O)OC)[C@@H]2c3cc4c(cc3[C@H]([C@@H]5[C@@H]2C(=O)OC5)O[C@H]6[C@@H]([C@H]([C@H]7[C@H](O6)COC(O7)c8cccs8)O)O)OCO4,1,0
+COc1cc(cc(c1OC)OC)C(=O)O[C@@H]2C[C@@H]3C[NH+]4CCc5c6ccccc6[nH]c5[C@H]4C[C@@H]3[C@@H]([C@H]2OC)C(=O)OC,1,0

mol_moe/data/moleculenet/esol/test.csv

@@ -0,0 +1,114 @@
+Compound ID,ESOL predicted log solubility in mols per litre,Minimum Degree,Molecular Weight,Number of H-Bond Donors,Number of Rings,Number of Rotatable Bonds,Polar Surface Area,measured log solubility in mols per litre,smiles
+Dieldrin,-4.533,1,380.913,0,5,0,12.53,-6.29,ClC4=C(Cl)C5(Cl)C3C1CC(C2OC12)C3C4(Cl)C5(Cl)Cl
+Valeraldehyde,-1.103,1,86.13399999999999,0,0,3,17.07,-0.85,CCCCC=O
+4-Pentene-1-ol,-0.7909999999999999,1,86.134,1,0,3,20.23,-0.15,OCCCC=C
+brompyrazone,-3.005,1,266.098,1,2,1,60.910000000000004,-3.127,c1ccccc1n2ncc(N)c(Br)c2(=O)
+p-Aminophenol,-1.2309999999999999,1,109.12799999999999,2,1,0,46.25,-0.8,Nc1ccc(O)cc1
+nitrofurantoin,-1.2429999999999999,1,238.15899999999996,1,2,3,118.04999999999998,-3.38,O=C2CN(N=Cc1ccc(o1)N(=O)=O)C(=O)N2 
+Isopentyl acetate,-1.817,1,130.18699999999998,0,0,3,26.3,-1.92,CC(C)CCOC(=O)C
+Formothion,-2.0869999999999997,1,257.27299999999997,0,0,6,55.84,-1.995,COP(=S)(OC)SCC(=O)N(C)C=O
+"2,3',4',5-PCB",-6.312,1,291.992,0,2,1,0.0,-7.25,Clc1ccc(Cl)c(c1)c2ccc(Cl)c(Cl)c2
+chlorquinox,-4.438,1,267.93,0,2,0,25.78,-5.43,c2(Cl)c(Cl)c(Cl)c1nccnc1c2(Cl) 
+dimethirimol,-3.57,1,209.29299999999998,1,1,4,49.25000000000001,-2.24,CCCCc1c(C)nc(nc1O)N(C)C 
+Malonic acid diethylester,-1.413,1,160.16899999999998,0,0,4,52.60000000000001,-0.82,CCOC(=O)CC(=O)OCC
+p-t-Butylphenol,-3.1919999999999997,1,150.22099999999998,1,1,0,20.23,-2.41,CC(C)(C)c1ccc(O)cc1
+m-Xylene ,-3.035,1,106.16799999999999,0,1,0,0.0,-2.82,Cc1cccc(C)c1
+Propyl acetate,-1.125,1,102.13299999999998,0,0,2,26.3,-0.72,CCCOC(=O)C
+Metribuzin,-2.324,1,214.29399999999998,1,1,1,73.8,-2.253,CSc1nnc(c(=O)n1N)C(C)(C)C
+"2,4'-PCB",-5.142,1,223.102,0,2,1,0.0,-5.28,Clc1ccc(cc1)c2ccccc2Cl 
+cycloheximide,-1.5319999999999998,1,281.35200000000003,2,2,3,83.47,-1.13,CC1CC(C)C(=O)C(C1)C(O)CC2CC(=O)NC(=O)C2 
+Formetanate,-1.8459999999999999,1,221.26,1,1,3,53.93,-2.34,CNC(=O)Oc1cccc(N=CN(C)C)c1
+nevirapine,-3.397,1,266.30400000000003,1,4,1,58.120000000000005,-3.19,Cc3ccnc4N(C1CC1)c2ncccc2C(=O)Nc34 
+N-Ethylaniline,-2.3890000000000002,1,121.18299999999995,1,1,2,12.03,-1.7,CCNc1ccccc1
+"7,12-Dimethylbenz(a)anthracene",-6.297000000000001,1,256.348,0,4,0,0.0,-7.02,Cc1c2ccccc2c(C)c3ccc4ccccc4c13
+TEFLUBENZURON,-5.462000000000001,1,381.1120000000001,2,2,2,58.2,-7.28,Fc1cccc(F)c1C(=O)NC(=O)Nc2cc(Cl)c(F)c(Cl)c2F 
+4-Chloroanisole,-3.057,1,142.585,0,1,1,9.23,-2.78,COc1ccc(Cl)cc1
+"3,4-Dichloronitrobenzene",-3.448,1,192.001,0,1,1,43.14,-3.2,O=N(=O)c1cc(Cl)c(Cl)cc1
+Dibenzofurane,-4.2010000000000005,2,168.195,0,3,0,13.14,-4.6,o1c2ccccc2c3ccccc13
+Acridine,-3.846,2,179.22199999999998,0,3,0,12.89,-3.67,c3ccc2nc1ccccc1cc2c3
+Cortisone,-2.8930000000000002,1,360.45000000000016,2,4,2,91.67,-3.11,CC12CC(=O)C3C(CCC4=CC(=O)CCC34C)C2CCC1(O)C(=O)CO
+alachlor,-3.319,1,269.77199999999993,0,1,6,29.54,-3.26,CCc1cccc(CC)c1N(COC)C(=O)CCl 
+Neburon,-4.157,1,275.179,1,1,4,32.34,-4.77,CCCCN(C)C(=O)Nc1ccc(Cl)c(Cl)c1
+p-Nitrophenol,-2.318,1,139.10999999999999,1,1,1,63.37,-0.74,Oc1ccc(cc1)N(=O)=O
+rhodanine,-0.396,1,133.197,1,1,0,29.1,-1.77,C1SC(=S)NC1(=O)
+Morin,-2.7310000000000003,1,302.23800000000006,5,3,1,131.35999999999999,-3.083,Oc1ccc(c(O)c1)c3oc2cc(O)cc(O)c2c(=O)c3O 
+chlordimeform,-3.1639999999999997,1,196.68099999999998,0,1,2,15.6,-2.86,CN(C)C=Nc1ccc(Cl)cc1C
+allantoin,0.652,1,158.117,4,1,1,113.32,-1.6,NC(=O)NC1NC(=O)NC1=O 
+1-Chloronapthalene,-4.063,1,162.61899999999997,0,2,0,0.0,-3.93,Clc1cccc2ccccc12
+"3,4-Dichlorophenol",-3.352,1,163.00300000000001,1,1,0,20.23,-1.25,Oc1ccc(Cl)c(Cl)c1
+Cypermethrin,-6.775,1,416.30400000000014,0,3,6,59.32000000000001,-8.017000000000001,CC1(C)C(C=C(Cl)Cl)C1C(=O)OC(C#N)c2cccc(Oc3ccccc3)c2
+Benzotriazole,-2.21,2,119.127,1,2,0,41.57,-0.78,c2ccc1[nH]nnc1c2
+Fluvalinate,-8.057,1,502.9200000000002,1,3,8,71.35,-8.003,CC(C)C(Nc1ccc(cc1Cl)C(F)(F)F)C(=O)OC(C#N)c2cccc(Oc3ccccc3)c2
+Propane,-1.5530000000000002,1,44.096999999999994,0,0,0,0.0,-1.94,CCC
+Acenapthene,-3.792,2,154.21199999999996,0,3,0,0.0,-4.63,C1Cc2cccc3cccc1c23
+1-Butyne,-1.092,1,54.09199999999999,0,0,0,0.0,-1.24,CCC#C
+"1,4-Dichlorobenzene",-3.5580000000000003,1,147.00400000000002,0,1,0,0.0,-3.27,Clc1ccc(Cl)cc1
+3-methylindole,-2.9810000000000003,1,131.17799999999997,1,2,0,15.79,-2.42,Cc1c[nH]c2ccccc12 
+Acetonitrile,0.152,1,41.053,0,0,0,23.79,0.26,CC#N
+1-Butanol,-0.688,1,74.12299999999999,1,0,2,20.23,0.0,CCCCO
+"2,3-Dimethyl-1,3-Butadiene",-2.052,1,82.146,0,0,1,0.0,-2.4,CC(=C)C(=C)C
+m-Chloronitrobenzene ,-2.9010000000000002,1,157.55599999999998,0,1,1,43.14,-2.77,Clc1cccc(c1)N(=O)=O
+3-Methyl-2-pentanol,-1.308,1,102.17699999999999,1,0,3,20.23,-0.71,CCC(C)CCO
+"2,2',3,3',4,4'-PCB",-7.192,1,360.88200000000006,0,2,1,0.0,-8.01,Clc1ccc(c(Cl)c1Cl)c2ccc(Cl)c(Cl)c2Cl 
+Perfluidone,-4.945,1,379.38100000000003,1,2,4,80.31,-3.8,Cc1cc(ccc1NS(=O)(=O)C(F)(F)F)S(=O)(=O)c2ccccc2
+"2,4-Dichlorophenol ",-3.22,1,163.003,1,1,0,20.23,-1.55,Oc1ccc(Cl)cc1Cl
+piroxicam,-3.4730000000000003,1,331.353,2,3,2,99.60000000000001,-4.16,CN2C(=C(O)c1ccccc1S2(=O)=O)C(=O)Nc3ccccn3 
+Estrone,-3.872,1,270.372,1,4,0,37.3,-3.955,CC12CCC3C(CCc4cc(O)ccc34)C2CCC1=O
+"1,5-Dimethlnapthalene",-4.147,1,156.228,0,2,0,0.0,-4.678999999999999,Cc1cccc2c(C)cccc12
+hydrochlorothiazide,-1.72,1,297.745,3,2,1,118.35999999999999,-2.63,NS(=O)(=O)c2cc1c(NCNS1(=O)=O)cc2Cl 
+8-quinolinol,-2.725,1,145.16099999999997,1,2,0,33.120000000000005,-2.42,Oc1cccc2cccnc12 
+"1,2,3,4-Tetrahydronapthalene",-3.447,2,132.20599999999996,0,2,0,0.0,-4.37,C1CCc2ccccc2C1
+"1,1-Diethoxyethane ",-0.899,1,118.176,0,0,4,18.46,-0.43,CCOC(C)OCC
+Procymidone,-3.464,1,284.142,0,3,1,37.38,-4.8,CC12CC2(C)C(=O)N(C1=O)c3cc(Cl)cc(Cl)c3
+Dinoseb,-3.715,1,240.21499999999995,1,1,4,106.51000000000002,-3.38,CCC(C)c1cc(cc(N(=O)=O)c1O)N(=O)=O 
+9-Methylanthracene,-4.87,1,192.261,0,3,0,0.0,-5.89,Cc1c2ccccc2cc3ccccc13
+Methyl butyl ether ,-1.072,1,88.14999999999999,0,0,3,9.23,-0.99,CCCCOC
+aldosterone,-3.0660000000000003,1,360.45000000000005,2,4,3,91.67000000000002,-3.85,CC13CCC(=O)C=C1CCC4C2CCC(C(=O)CO)C2(CC(O)C34)C=O 
+probarbital,-1.6030000000000002,1,198.22199999999998,2,1,2,75.27000000000001,-2.21,CCC1(C(C)C)C(=O)NC(=O)NC1=O 
+Ethyl-p-hydroxybenzoate ,-2.761,1,166.176,1,1,2,46.53,-2.35,CCOC(=O)c1ccc(O)cc1
+Coronene,-6.885,2,300.36000000000007,0,7,0,0.0,-9.332,c1cc2ccc3ccc4ccc5ccc6ccc1c7c2c3c4c5c67
+RTI 22,-4.408,1,296.374,1,3,2,48.47,-4.871,CCN2c1cc(N(C)C)cc(C)c1NC(=O)c3cccnc23 
+Diuron,-3.301,1,233.09799999999998,1,1,1,32.34,-3.8,CN(C)C(=O)Nc1ccc(Cl)c(Cl)c1
+2-Methylheptane,-3.3080000000000003,1,114.23199999999999,0,0,4,0.0,-5.08,CCCCCC(C)C
+Trimazosin,-3.958,1,435.48100000000034,2,3,6,132.5,-3.638,COc2cc1c(N)nc(nc1c(OC)c2OC)N3CCN(CC3)C(=O)OCC(C)(C)O 
+phthalamide,-0.636,1,149.149,1,2,0,46.17,-2.932,c1cC2C(=O)NC(=O)C2cc1
+Propionaldehyde,-0.39399999999999996,1,58.08,0,0,1,17.07,0.58,CCC=O
+Pencycuron,-5.126,1,328.84299999999996,1,3,4,32.34,-5.915,Clc1ccc(CN(C2CCCC2)C(=O)Nc3ccccc3)cc1
+2-Ethylhexanal,-2.2319999999999998,1,128.21499999999997,0,0,5,17.07,-2.13,CCCCC(CC)C=O
+5-Ethyl-5-(3-methylbutyl)barbital,-2.312,1,226.27599999999995,2,1,4,75.27000000000001,-2.658,O=C1NC(=O)NC(=O)C1(CC)CCC(C)C
+Acetanilide,-1.857,1,135.16599999999997,1,1,1,29.1,-1.33,CC(=O)Nc1ccccc1
+Isonazid,-0.7170000000000001,1,137.14200000000002,2,1,1,68.01,0.009000000000000001,c1nccc(C(=O)NN)c1
+D-fenchone,-2.158,1,152.237,0,2,0,17.07,-1.85,CC2(C)C1CCC(C)(C1)C2=O
+7-methoxypteridine,-1.589,1,162.152,0,2,1,60.790000000000006,-0.91,COc2cnc1cncnc1n2
+Azodrin,-0.9490000000000001,1,223.16499999999996,1,0,5,73.86,0.6509999999999999,CNC(=O)C=C(C)OP(=O)(OC)OC
+RTI 9,-3.784,1,239.274,0,3,1,29.54,-3.68,O2c1ccccc1N(CC)C(=O)c3ccccc23 
+osthole,-4.0760000000000005,1,244.28999999999994,0,2,3,39.44,-4.314,c1cc2ccc(OC)c(CC=C(C)(C))c2oc1=O 
+Di-n-propylsulfide,-2.307,1,118.24499999999999,0,0,4,0.0,-2.58,CCCSCCC
+Monolinuron,-2.948,1,214.652,1,1,2,41.57,-2.57,CON(C)C(=O)Nc1ccc(Cl)cc1
+Diethyl ether ,-0.718,1,74.123,0,0,2,9.23,-0.09,CCOCC
+estriol,-3.858,1,288.387,3,4,0,60.69,-4.955,CC34CCC1C(CCc2cc(O)ccc12)C3CC(O)C4O 
+Cyanazine,-2.49,1,240.698,2,1,4,86.52,-3.15,CCNc1nc(Cl)nc(NC(C)(C)C#N)n1
+"2,4-Dimethyl-2-pentanol ",-1.6469999999999998,1,116.20399999999998,1,0,2,20.23,-0.92,CC(C)CC(C)(C)O
+m-Chlorobromobenzene,-3.928,1,191.45499999999998,0,1,0,0.0,-3.21,Clc1cccc(Br)c1
+3-Octanol,-2.033,1,130.23099999999997,1,0,5,20.23,-1.98,CCCCCC(O)CC
+5-(3-Methyl-2-butenyl)-5-ethylbarbital,-2.126,1,224.25999999999996,2,1,3,75.27000000000001,-2.253,O=C1NC(=O)NC(=O)C1(CC)CC=C(C)C
+butallylonal,-2.766,1,303.156,2,1,4,75.27000000000001,-2.647,CCC(C)C1(CC(Br)=C)C(=O)NC(=O)NC1=O 
+Methyl acetate,-0.41600000000000004,1,74.07900000000001,0,0,0,26.3,0.46,COC(=O)C
+Thymol,-3.1289999999999996,1,150.22099999999998,1,1,1,20.23,-2.22,CC(C)c1ccc(C)cc1O
+Methane,-0.636,0,16.043,0,0,0,0.0,-0.9,C
+isoguanine,-1.74,1,151.129,3,2,0,100.71000000000001,-3.4010000000000002,Nc1nc(O)nc2nc[nH]c12 
+difluron,-4.692,1,310.687,2,2,2,58.2,-6.02,Fc1cccc(F)c1C(=O)NC(=O)Nc2ccc(Cl)cc2
+"1,8-Cineole",-2.5789999999999997,1,154.253,0,3,0,9.23,-1.74,CC12CCC(CC1)C(C)(C)O2
+Ethanol,0.02,1,46.069,1,0,0,20.23,1.1,CCO
+Carbetamide,-2.29,1,236.271,2,1,4,67.42999999999999,-1.83,c1c(NC(=O)OC(C)C(=O)NCC)cccc1
+phenothrin,-6.763,1,350.4580000000001,0,3,6,35.53,-5.24,CC(C)=CC3C(C(=O)OCc2cccc(Oc1ccccc1)c2)C3(C)C 
+Benomyl,-2.9019999999999997,1,290.323,2,2,4,85.25,-4.883,CCCCNC(=O)n1c(NC(=O)OC)nc2ccccc12
+"N,N-Dimethylaniline",-2.542,1,121.18299999999995,0,1,1,3.24,-1.92,CN(C)c1ccccc1
+Methyl acrylate,-0.878,1,86.09,0,0,1,26.3,-0.22,COC(=O)C=C
+Chloroxuron,-4.477,1,290.75,1,2,3,41.57000000000001,-4.89,CN(C)C(=O)Nc2ccc(Oc1ccc(Cl)cc1)cc2
+5-(3-Methyl-2-butenyl)-5-isoPrbarbital,-2.465,1,238.28699999999998,2,1,3,75.27000000000001,-2.593,O=C1NC(=O)NC(=O)C1(C(C)C)CC=C(C)C
+"3,4-Dimethylphenol",-2.6210000000000004,1,122.16699999999999,1,1,0,20.23,-1.38,Cc1ccc(O)cc1C
+Nitrapyrin,-3.833,1,230.909,0,1,0,12.89,-3.76,Clc1cccc(n1)C(Cl)(Cl)Cl
+norethindrone acetate,-4.2410000000000005,1,340.4630000000001,0,4,1,43.370000000000005,-4.8,CC(=O)OC3(CCC4C2CCC1=CC(=O)CCC1C2CCC34C)C#C
+thiofanox,-2.7,1,218.32199999999997,1,0,3,50.69,-1.62,CNC(=O)ON=C(CSC)C(C)(C)C 
+2-Octanol,-2.033,1,130.231,1,0,5,20.23,-2.09,CCCCCCC(C)O

mol_moe/data/moleculenet/esol/train.csv

@@ -0,0 +1,902 @@
+Compound ID,ESOL predicted log solubility in mols per litre,Minimum Degree,Molecular Weight,Number of H-Bond Donors,Number of Rings,Number of Rotatable Bonds,Polar Surface Area,measured log solubility in mols per litre,smiles
+Amigdalin,-0.9740000000000001,1,457.4320000000001,7,3,7,202.31999999999996,-0.77,OCC3OC(OCC2OC(OC(C#N)c1ccccc1)C(O)C(O)C2O)C(O)C(O)C3O 
+Fenfuram,-2.885,1,201.22500000000002,1,2,2,42.24,-3.3,Cc1occc1C(=O)Nc2ccccc2
+citral,-2.5789999999999997,1,152.237,0,0,4,17.07,-2.06,CC(C)=CCCC(C)=CC(=O)
+Picene,-6.617999999999999,2,278.354,0,5,0,0.0,-7.87,c1ccc2c(c1)ccc3c2ccc4c5ccccc5ccc43
+Thiophene,-2.2319999999999998,2,84.14299999999999,0,1,0,0.0,-1.33,c1ccsc1
+benzothiazole,-2.733,2,135.191,0,2,0,12.89,-1.5,c2ccc1scnc1c2 
+"2,2,4,6,6'-PCB",-6.545,1,326.437,0,2,1,0.0,-7.32,Clc1cc(Cl)c(c(Cl)c1)c2c(Cl)cccc2Cl
+Estradiol,-4.138,1,272.388,2,4,0,40.46,-5.03,CC12CCC3C(CCc4cc(O)ccc34)C2CCC1O
+Rotenone,-5.246,1,394.42300000000023,0,5,3,63.22,-4.42,COc5cc4OCC3Oc2c1CC(Oc1ccc2C(=O)C3c4cc5OC)C(C)=C 
+2-pyrrolidone,0.243,1,85.10600000000001,1,1,0,29.1,1.07,O=C1CCCN1
+2-Chloronapthalene,-4.063,1,162.61899999999997,0,2,0,0.0,-4.14,Clc1ccc2ccccc2c1
+1-Pentene ,-2.01,1,70.135,0,0,2,0.0,-2.68,CCCC=C
+Primidone,-1.8969999999999998,1,218.256,2,2,2,58.2,-2.64,CCC1(C(=O)NCNC1=O)c2ccccc2
+Tetradecane,-5.45,1,198.39399999999995,0,0,11,0.0,-7.96,CCCCCCCCCCCCCC
+2-Chloropropane,-1.585,1,78.542,0,0,0,0.0,-1.41,CC(C)Cl
+2-Methylbutanol,-1.0270000000000001,1,88.14999999999999,1,0,2,20.23,-0.47,CCC(C)CO
+Diazinon,-3.989,1,304.35200000000003,0,1,7,53.47,-3.64,CCOP(=S)(OCC)Oc1cc(C)nc(n1)C(C)C
+2-Undecanol,-3.096,1,172.312,1,0,8,20.23,-2.94,CCCCCCCCCC(C)O
+"2,2',3,4,6-PCB",-6.627000000000001,1,326.437,0,2,1,0.0,-7.43,Clc1ccc(c(Cl)c1)c2c(Cl)ccc(Cl)c2Cl 
+Lenacil,-3.355,1,234.29899999999995,1,3,1,54.86,-4.593999999999999,O=c2[nH]c1CCCc1c(=O)n2C3CCCCC3
+Phorate,-3.747,1,260.38599999999997,0,0,8,18.46,-4.11,CCOP(=S)(OCC)SCSCC
+Phenacetin,-2.342,1,179.219,1,1,3,38.33,-2.35,CCOc1ccc(NC(=O)C)cc1
+Dinitramine,-4.479,1,322.243,1,1,5,115.54000000000002,-5.47,CCN(CC)c1c(cc(c(N)c1N(=O)=O)C(F)(F)F)N(=O)=O
+1-Heptanol,-1.751,1,116.204,1,0,5,20.23,-1.81,CCCCCCCO
+Theophylline,-1.452,1,180.16699999999997,1,2,0,72.68,-1.39,Cn1c(=O)n(C)c2nc[nH]c2c1=O
+"P,P'-DDE",-6.553,1,318.0300000000001,0,2,2,0.0,-6.9,ClC(Cl)=C(c1ccc(Cl)cc1)c2ccc(Cl)cc2
+Methyl octanoate,-2.608,1,158.24099999999999,0,0,6,26.3,-3.17,CCCCCCCC(=O)OC
+"1,4-Diethylbenzene ",-3.633,1,134.22199999999998,0,1,2,0.0,-3.75,CCc1ccc(CC)cc1
+Terbufos,-4.367,1,288.44,0,0,7,18.46,-4.755,CCOP(=S)(OCC)SCSC(C)(C)C
+Phenmedipham,-4.229,1,300.314,2,2,3,76.66,-4.805,COC(=O)Nc1cccc(OC(=O)Nc2cccc(C)c2)c1
+"1,1-Dichloroethylene",-1.939,1,96.94399999999999,0,0,0,0.0,-1.64,ClC(=C)Cl
+1-Methylfluorene,-4.478,1,180.25000000000003,0,3,0,0.0,-5.22,Cc1cccc2c1Cc3ccccc32
+Diphenylamine,-3.8569999999999998,2,169.227,1,2,2,12.03,-3.5039999999999996,N(c1ccccc1)c2ccccc2
+Fenothiocarb,-3.2969999999999997,1,253.367,0,1,6,29.540000000000003,-3.927,CN(C)C(=O)SCCCCOc1ccccc1
+Piperophos,-4.637,1,353.4900000000001,0,1,9,38.77,-4.15,CCCOP(=S)(OCCC)SCC(=O)N1CCCCC1C
+1-Iodoheptane,-3.904,1,226.101,0,0,5,0.0,-4.81,CCCCCCCI
+3-Chlorobiphenyl,-4.685,1,188.657,0,2,1,0.0,-4.88,c1c(Cl)cccc1c2ccccc2
+Cyclobutyl-5-spirobarbituric acid,-0.527,1,168.15200000000002,2,2,0,75.27,-1.655,O=C2NC(=O)C1(CCC1)C(=O)N2
+menthol,-2.782,1,156.269,1,1,1,20.23,-2.53,CC(C)C1CCC(C)CC1O 
+Isopropyl formate,-0.684,1,88.106,0,0,2,26.3,-0.63,CC(C)OC=O
+2-Heptanol ,-1.6780000000000002,1,116.20399999999998,1,0,4,20.23,-1.55,CCCCCC(C)O
+p-Bromoacetanilide,-3.012,1,214.06199999999998,1,1,1,29.1,-3.083,CC(=O)Nc1ccc(Br)cc1
+nifedipine,-4.248,1,346.33900000000017,1,2,4,107.77,-4.76,COC(=O)C1=C(C)NC(=C(C1c2ccccc2N(=O)=O)C(=O)OC)C 
+"2,7-dimethylquinoline",-3.342,1,157.216,0,2,0,12.89,-1.94,c2c(C)cc1nc(C)ccc1c2 
+1-Octyne ,-2.509,1,110.19999999999999,0,0,4,0.0,-3.66,CCCCCCC#C
+Chrysene,-5.568,2,228.29399999999998,0,4,0,0.0,-8.057,c1ccc2c(c1)ccc3c4ccccc4ccc23
+Bromacil,-3.4189999999999996,1,261.11899999999997,1,1,2,54.86,-2.523,CCC(C)n1c(=O)[nH]c(C)c(Br)c1=O 
+"2,2',3,3',5,6-PCB",-7.185,1,360.88200000000006,0,2,1,0.0,-8.6,Clc1cccc(c1Cl)c2c(Cl)c(Cl)cc(Cl)c2Cl 
+2-Methylphenol,-2.281,1,108.13999999999999,1,1,0,20.23,-0.62,Cc1ccccc1O
+"2,2,5-Trimethylhexane",-3.6310000000000002,1,128.259,0,0,2,0.0,-5.05,CC(C)CCC(C)(C)C
+6-Methylchrysene,-5.931,1,242.321,0,4,0,0.0,-6.57,Cc1cc2c3ccccc3ccc2c4ccccc14
+2-Pentanone,-0.846,1,86.13399999999999,0,0,2,17.07,-0.19,CCCC(=O)C
+"2,2',3,3',5,5',6,6'-PCB",-8.304,1,429.77200000000016,0,2,1,0.0,-9.15,Clc1cc(Cl)c(Cl)c(c1Cl)c2c(Cl)c(Cl)cc(Cl)c2Cl 
+Methyl butyrate,-1.545,1,116.15999999999998,0,0,3,26.3,-0.82,CCCOC(=O)CC
+Triamcinolone,-2.734,1,394.43900000000014,4,4,2,115.06000000000002,-3.68,CC34CC(O)C1(F)C(CCC2=CC(=O)C=CC12C)C3CC(O)C4(O)C(=O)CO
+Benznidazole,-2.3209999999999997,1,260.253,1,2,5,90.06,-2.81,O=C(Cn1ccnc1N(=O)=O)NCc2ccccc2
+Trietazine,-3.233,1,229.71499999999997,1,1,5,53.940000000000005,-4.06,CCNc1nc(Cl)nc(n1)N(CC)CC
+Pyrazinamide,-0.674,1,123.11499999999998,1,1,1,68.87,-0.667,NC(=O)c1cnccn1
+Carbromal,-2.198,1,237.09699999999998,2,0,3,72.19,-2.68,CCC(Br)(CC)C(=O)NC(N)=O
+"2,2'-PCB",-4.984,1,223.102,0,2,1,0.0,-5.27,Clc1ccccc1c2ccccc2Cl 
+Nitrofen,-5.361000000000001,1,284.09799999999996,0,2,3,52.37,-5.46,Clc2ccc(Oc1ccc(cc1)N(=O)=O)c(Cl)c2
+5-Allyl-5-phenylbarbital,-2.36,1,244.25,2,2,3,75.27000000000001,-2.369,O=C1NC(=O)NC(=O)C1(CC=C)c1ccccc1
+Pentyl propanoate,-1.899,1,130.18699999999998,0,0,4,26.3,-2.25,CCCCC(=O)OCC
+3-Hexanoyloxymethylphenyltoin,-4.1530000000000005,1,380.444,1,3,8,75.71,-5.886,O=C1N(COC(=O)CCCCC)C(=O)C(N1)(c2ccccc2)c3ccccc3
+"2,3',5-PCB",-5.7620000000000005,1,257.547,0,2,1,0.0,-6.01,Clc1cccc(c1)c2cc(Cl)ccc2Cl 
+1-Bromopropane,-1.949,1,122.993,0,0,1,0.0,-1.73,CCCBr
+Propiconazole,-4.603,1,342.2260000000001,0,3,5,49.17,-3.4930000000000003,CCCC1COC(Cn2cncn2)(O1)c3ccc(Cl)cc3Cl
+4-methylpteridine,-1.24,1,146.15299999999996,0,2,0,51.56,-0.466,Cc1ncnc2nccnc12
+Thiourea,0.32899999999999996,1,76.12400000000001,2,0,0,52.04,0.32,NC(=S)N
+p-Xylene ,-3.035,1,106.16799999999999,0,1,0,0.0,-2.77,Cc1ccc(C)cc1
+"1,2-Diethylbenzene",-3.6010000000000004,1,134.22199999999998,0,1,2,0.0,-3.28,CCc1ccccc1CC
+Hexachloroethane,-4.215,1,236.74,0,0,0,0.0,-3.67,ClC(Cl)(Cl)C(Cl)(Cl)Cl
+Flucythrinate,-6.877999999999999,1,451.46900000000005,0,3,9,68.55000000000001,-6.876,CC(C)C(C(=O)OC(C#N)c1cccc(Oc2ccccc2)c1)c3ccc(OC(F)F)cc3
+1-Nitropropane,-0.816,1,89.09399999999998,0,0,2,43.14,-0.8,CCCN(=O)=O
+RTI 24,-4.423,1,273.723,1,3,1,45.230000000000004,-5.36,CCN2c1cc(Cl)ccc1NC(=O)c3cccnc23 
+"2,3-Dichloronitrobenzene",-3.322,1,192.00100000000003,0,1,1,43.14,-3.48,O=N(=O)c1c(Cl)c(Cl)ccc1
+thiamylal,-3.063,1,254.35500000000002,2,1,5,58.2,-3.46,CCCC(C)C1(CC=C)C(=O)NC(=S)NC1=O 
+Fluoranthene,-4.957,2,202.25599999999997,0,4,0,0.0,-6.0,c1ccc2c(c1)c3cccc4cccc2c34
+Propylisopropylether,-1.354,1,102.17699999999998,0,0,3,9.23,-1.34,CCCOC(C)C
+"1,3-Dimethylnaphthalene",-4.147,1,156.22799999999998,0,2,0,0.0,-4.29,Cc1cc(C)c2ccccc2c1
+diethylstilbestrol,-5.074,1,268.356,2,2,4,40.46,-4.07,CCC(=C(CC)c1ccc(O)cc1)c2ccc(O)cc2 
+Chlorothalonil,-3.995,1,265.914,0,1,0,47.58,-5.64,c1(C#N)c(Cl)c(C#N)c(Cl)c(Cl)c(Cl)1
+styrene oxide,-1.8259999999999998,2,120.15099999999995,0,2,1,12.53,-1.6,C1OC1c2ccccc2 
+Deoxycorticosterone,-3.9389999999999996,1,330.4680000000001,1,4,2,54.370000000000005,-3.45,CC12CCC3C(CCC4=CC(=O)CCC34C)C2CCC1C(=O)CO
+L-arabinose,0.601,1,150.13,4,1,0,90.15,0.39,C1OC(O)C(O)C(O)C1O
+Dichloromethane,-1.156,1,84.93299999999999,0,0,0,0.0,-0.63,ClCCl
+1-Ethylnaphthalene ,-4.1,1,156.22799999999998,0,2,1,0.0,-4.17,CCc1cccc2ccccc12
+Methyl formate,-0.048,1,60.05200000000001,0,0,1,26.3,0.58,COC=O
+o-Nitrophenol,-2.318,1,139.10999999999999,1,1,1,63.37,-1.74,Oc1ccccc1N(=O)=O
+thymine,-0.78,1,126.115,2,1,0,65.72,-1.506,Cc1c[nH]c(=O)[nH]c1=O 
+2-Methylpropane,-1.891,1,58.123999999999995,0,0,0,0.0,-2.55,CC(C)C
+Inosine,-0.8340000000000001,1,268.22900000000004,4,3,2,133.75,-1.23,OCC1OC(C(O)C1O)n2cnc3c(O)ncnc23
+Niclosamide,-5.032,1,327.1230000000001,2,2,3,92.47,-4.7,Oc1ccc(Cl)cc1C(=O)Nc2ccc(cc2Cl)N(=O)=O
+Pentane,-2.261,1,72.151,0,0,2,0.0,-3.18,CCCCC
+Phenol,-1.9909999999999999,1,94.11299999999999,1,1,0,20.23,0.0,c1ccccc1O
+2-aminoanthracene,-3.7889999999999997,1,193.249,1,3,0,26.02,-5.17,Nc3ccc2cc1ccccc1cc2c3 
+Isoquinoline,-2.531,2,129.16199999999998,0,2,0,12.89,-1.45,c1ccc2cnccc2c1
+Anilofos,-5.106,1,367.86,0,1,7,38.77,-4.4319999999999995,COP(=S)(OC)SCC(=O)N(C(C)C)c1ccc(Cl)cc1
+Hexylbenzene ,-4.22,1,162.276,0,1,5,0.0,-5.21,CCCCCCc1ccccc1
+2-Chlorobiphenyl,-4.5280000000000005,1,188.657,0,2,1,0.0,-4.54,Clc1ccccc1c2ccccc2
+2-Methyl-1-Pentene,-2.3480000000000003,1,84.16199999999999,0,0,2,0.0,-3.03,CCCC(=C)C
+"2,3,4-Trimethylpentane",-3.2760000000000002,1,114.23199999999999,0,0,2,0.0,-4.8,CC(C)C(C)C(C)C
+Pentachlorobenzene,-5.167999999999999,1,250.339,0,1,0,0.0,-5.65,Clc1cc(Cl)c(Cl)c(Cl)c1Cl
+m-Nitrophenol,-2.318,1,139.10999999999999,1,1,1,63.37,-1.01,Oc1cccc(c1)N(=O)=O
+1-Decene,-3.781,1,140.26999999999998,0,0,7,0.0,-5.51,CCCCCCCCC=C
+Cyfluthrin,-6.84,1,434.29400000000015,0,3,6,59.32000000000001,-7.337000000000001,CC1(C)C(C=C(Cl)Cl)C1C(=O)OC(C#N)c2ccc(F)c(Oc3ccccc3)c2
+Pyridine,-1.4809999999999999,2,79.10199999999998,0,1,0,12.89,0.76,c1ccncc1
+1-Bromoheptane,-3.366,1,179.101,0,0,5,0.0,-4.43,CCCCCCCBr
+Fludrocortisone,-3.1719999999999997,1,380.45600000000013,3,4,2,94.83,-3.43,CC34CC(O)C1(F)C(CCC2=CC(=O)CCC12C)C3CCC4(O)C(=O)CO 
+ethiofencarb,-2.855,1,225.313,1,1,4,38.33,-2.09,CCSCc1ccccc1OC(=O)NC 
+d-Limonene,-3.429,1,136.238,0,1,1,0.0,-4.26,CC1=CCC(CC1)C(C)=C
+Indan,-3.057,2,118.17899999999997,0,2,0,0.0,-3.04,C1Cc2ccccc2C1
+Cyclopropyl-5-spirobarbituric acid,-0.08800000000000001,1,154.125,2,2,0,75.27,-1.886,O=C2NC(=O)C1(CC1)C(=O)N2 
+m-Chloroiodobenzene,-4.3839999999999995,1,238.45499999999998,0,1,0,0.0,-3.55,Clc1cccc(I)c1
+1-Bromonapthalene,-4.434,1,207.07,0,2,0,0.0,-4.35,Brc1cccc2ccccc12
+trans-2-Pentene ,-2.076,1,70.135,0,0,1,0.0,-2.54,CC/C=C/C
+"2,6-Dimethylpyridine",-2.0980000000000003,1,107.156,0,1,0,12.89,0.45,Cc1cccc(C)n1
+Trichloroethylene,-2.312,1,131.389,0,0,0,0.0,-1.96,ClC=C(Cl)Cl
+1-Napthylamine,-2.721,1,143.189,1,2,0,26.02,-1.92,Nc1cccc2ccccc12
+2-hydroxypteridine,-1.4040000000000001,1,148.125,1,2,0,71.79,-1.9469999999999998,Oc2ncc1nccnc1n2
+Methanol,0.441,1,32.042,1,0,0,20.23,1.57,CO
+Amobarbital,-2.312,1,226.27599999999998,2,1,4,75.27000000000001,-2.468,CCC1(CCC(C)C)C(=O)NC(=O)NC1=O
+2-Butanone,-0.491,1,72.107,0,0,1,17.07,0.52,CCC(=O)C
+5-fluorouracil,-0.792,1,130.078,2,1,0,65.72,-1.077,Fc1c[nH]c(=O)[nH]c1=O 
+tubercidin,-0.892,1,266.257,4,3,2,126.65,-1.95,Nc1ncnc2n(ccc12)C3OC(CO)C(O)C3O 
+"1,3-Benzenediol",-1.59,1,110.11199999999998,2,1,0,40.46,0.81,Oc1cccc(O)c1
+1-Hexanol,-1.3969999999999998,1,102.17699999999999,1,0,4,20.23,-1.24,CCCCCCO
+1-Chloropentane,-2.294,1,106.596,0,0,3,0.0,-2.73,CCCCCCl
+"1,3-Butadiene",-1.376,1,54.09199999999999,0,0,1,0.0,-1.87,C=CC=C
+"5,6,7,8-tetrahydro-2-naphthol",-3.0860000000000003,1,148.205,1,2,0,20.23,-1.99,Oc2ccc1CCCCc1c2 
+chloroacetamide,-0.106,1,93.513,1,0,1,43.09,-0.02,NC(=O)CCl 
+Iodofenphos,-6.148,1,413.0,0,1,4,27.69,-6.62,COP(=S)(OC)Oc1cc(Cl)c(I)cc1Cl
+4-Chlorotoluene,-3.2969999999999997,1,126.586,0,1,0,0.0,-3.08,Cc1ccc(Cl)cc1
+Tricresyl phosphate,-6.39,1,368.3690000000001,0,3,6,44.760000000000005,-6.01,Cc1ccc(OP(=O)(Oc2cccc(C)c2)Oc3ccccc3C)cc1
+Caproaldehyde,-1.4569999999999999,1,100.16099999999999,0,0,4,17.07,-1.3,CCCCCC=O
+Butamben,-3.0389999999999997,1,193.24599999999998,1,1,4,52.32,-3.082,CCCCOC(=O)c1ccc(N)cc1
+RTI 3,-3.049,1,255.277,1,3,0,68.45,-3.043,O2c1cc(C)ccc1N(C)C(=O)c3cc(N)cnc23 
+Nerol,-2.603,1,154.253,1,0,4,20.23,-2.46,CC(C)=CCC/C(C)=C\CO
+3-Octanoyloxymethylphenytoin,-4.84,1,408.498,1,3,10,75.71,-6.523,O=C1N(COC(=O)CCCCCCC)C(=O)C(N1)(c2ccccc2)c3ccccc3
+Nitroethane,-0.462,1,75.067,0,0,1,43.14,-0.22,CCN(=O)=O
+Ethalfluralin,-5.063,1,333.266,0,1,6,89.51999999999998,-6.124,CCN(CC(C)=C)c1c(cc(cc1N(=O)=O)C(F)(F)F)N(=O)=O
+"1,2,3,4-Tetrachlorobenzene",-4.546,1,215.894,0,1,0,0.0,-4.57,Clc1ccc(Cl)c(Cl)c1Cl
+Meprobamate,-1.376,1,218.25299999999996,2,0,6,104.63999999999999,-1.807,CCCC(C)(COC(N)=O)COC(N)=O 
+pregnenolone,-4.342,1,316.48500000000007,1,4,1,37.3,-4.65,CC(=O)C3CCC4C2CC=C1CC(O)CCC1(C)C2CCC34C 
+3-Heptanoyloxymethylphenytoin,-4.496,1,394.471,1,3,9,75.71,-6.301,O=C1N(COC(=O)CCCCCC)C(=O)C(N1)(c2ccccc2)c3ccccc3
+isophorone,-2.015,1,138.20999999999998,0,1,0,17.07,-1.06,CC1=CC(=O)CC(C)(C)C1 
+Butabarbital,-1.9580000000000002,1,212.24899999999997,2,1,3,75.27000000000001,-2.39,O=C1NC(=O)NC(=O)C1(CC)C(C)CC
+5-Nonanone,-2.329,1,142.242,0,0,6,17.07,-2.58,CCCCC(=O)CCCC
+Glutethimide,-2.591,1,217.268,1,2,2,46.17,-2.3369999999999997,CCC1(CCC(=O)NC1=O)c2ccccc2 
+3-Methylpentane,-2.6,1,86.178,0,0,2,0.0,-3.68,CCC(C)CC
+Etofenprox,-6.896,1,376.49600000000004,0,3,9,27.69,-8.6,CCOc1ccc(cc1)C(C)(C)COCc3cccc(Oc2ccccc2)c3
+Methaqualone,-3.8810000000000002,1,250.30100000000002,0,3,1,34.89,-2.925,Cc1ccccc1n3c(C)nc2ccccc2c3=O
+Chloroacetonitrile,-0.44799999999999995,1,75.498,0,0,0,23.79,-0.092,ClCC#N
+Ethisterone,-3.858,1,312.45300000000003,1,4,0,37.3,-5.66,CC12CCC(=O)C=C1CCC3C2CCC4(C)C3CCC4(O)C#C 
+Pyridazine,-0.619,2,80.08999999999999,0,1,0,25.78,1.1,c1ccnnc1
+"1,2,3,5-Tetrachlorobenzene",-4.621,1,215.894,0,1,0,0.0,-4.63,Clc1cc(Cl)c(Cl)c(Cl)c1
+Diosgenin,-5.681,1,414.63000000000017,1,6,0,38.69,-7.32,C1C(O)CCC2(C)CC3CCC4(C)C5(C)CC6OCC(C)CC6OC5CC4C3C=C21
+o-Aminophenol,-1.465,1,109.12799999999999,2,1,0,46.25,-0.72,Nc1ccccc1O
+Ethyl nonanoate,-3.3160000000000003,1,186.295,0,0,8,26.3,-3.8,CCCCCCCCC(=O)OCC
+metalaxyl,-2.87,1,279.336,0,1,5,55.84,-1.601,COCC(=O)N(C(C)C(=O)OC)c1c(C)cccc1C 
+Propoxur,-2.4090000000000003,1,209.24499999999998,1,1,3,47.56,-2.05,CNC(=O)Oc1ccccc1OC(C)C
+2-Chlorobutane,-1.94,1,92.569,0,0,1,0.0,-1.96,CCC(C)Cl
+2-Napthol,-3.08,1,144.17299999999997,1,2,0,20.23,-2.28,Oc1ccc2ccccc2c1
+Oxadiazon,-5.265,1,345.22600000000017,0,2,3,57.26,-5.696000000000001,CC(C)Oc1cc(c(Cl)cc1Cl)n2nc(oc2=O)C(C)(C)C
+1-Hexyne ,-1.801,1,82.14599999999999,0,0,2,0.0,-2.36,CCCCC#C
+1-Nonyne ,-2.864,1,124.22699999999999,0,0,5,0.0,-4.24,CCCCCCCC#C
+2-Chlorotoluene,-3.2969999999999997,1,126.586,0,1,0,0.0,-3.52,Cc1ccccc1Cl
+Diisopropyl ether ,-1.281,1,102.17699999999999,0,0,2,9.23,-1.1,CC(C)OC(C)C
+Dapsone,-2.464,1,248.307,2,2,2,86.18,-3.094,Nc1ccc(cc1)S(=O)(=O)c2ccc(N)cc2
+Methyl hydrazine,0.5429999999999999,1,46.073,2,0,0,38.05,1.34,CNN
+Propyne,-0.672,1,40.065000000000005,0,0,0,0.0,-0.41,CC#C
+Phoxim,-4.5569999999999995,1,298.304,0,1,7,63.839999999999996,-4.862,CCOP(=S)(OCC)ON=C(C#N)c1ccccc1
+Propetamphos,-2.826,1,281.314,1,0,7,56.790000000000006,-3.408,CCNP(=S)(OC)OC(=CC(=O)OC(C)C)C
+Acrolein,-0.184,1,56.064,0,0,1,17.07,0.57,C=CC=O
+Hypoxanthine,-0.6559999999999999,1,136.114,2,2,0,74.43,-2.296,O=c1[nH]cnc2nc[nH]c12 
+6-hydroxyquinoline,-2.725,1,145.161,1,2,0,33.120000000000005,-2.16,Oc2ccc1ncccc1c2 
+Fluorobenzene,-2.5140000000000002,1,96.10399999999998,0,1,0,0.0,-1.8,Fc1ccccc1
+1-Chloropropane,-1.585,1,78.542,0,0,1,0.0,-1.47,CCCCl
+Ethyl acetate,-0.77,1,88.106,0,0,1,26.3,-0.04,CCOC(=O)C
+"2,2-Dimethylpentane",-2.938,1,100.20499999999998,0,0,1,0.0,-4.36,CCCC(C)(C)C
+eucalyptol,-2.5789999999999997,1,154.253,0,3,0,9.23,-1.64,CC12CCC(CC1)C(C)(C)O2 
+dibutyl sebacate,-4.726,1,314.46600000000007,0,0,15,52.60000000000001,-3.8960000000000004,CCCCOC(=O)CCCCCCCCC(=O)OCCCC
+"4,4'-PCB",-5.2989999999999995,1,223.102,0,2,1,0.0,-6.56,Clc1ccc(cc1)c2ccc(Cl)cc2 
+"2,3-Dimethylpyridine",-2.0669999999999997,1,107.156,0,1,0,12.89,0.38,Cc1cccnc1C
+Carvone,-2.042,1,150.22099999999998,0,1,1,17.07,-2.06,CC(=C)C1CC=C(C)C(=O)C1
+Carbophenthion,-5.827999999999999,1,342.875,0,1,8,18.46,-5.736000000000001,CCOP(=S)(OCC)SCSc1ccc(Cl)cc1
+"Etoposide (148-167,25mg/ml)",-3.292,1,588.5620000000001,3,7,5,160.83,-3.571,COc1cc(cc(OC)c1O)C6C2C(COC2=O)C(OC4OC3COC(C)OC3C(O)C4O)c7cc5OCOc5cc67
+Perylene,-6.007000000000001,2,252.31599999999997,0,5,0,0.0,-8.804,c1cc2cccc3c4cccc5cccc(c(c1)c23)c54
+"2,4-Dinitrotoluene",-2.6039999999999996,1,182.135,0,1,2,86.28,-2.82,Cc1ccc(cc1N(=O)=O)N(=O)=O
+2-bromonaphthalene,-4.434,1,207.07000000000002,0,2,0,0.0,-4.4,c1c(Br)ccc2ccccc12 
+Isazofos,-3.76,1,313.747,0,1,7,58.4,-3.658,CCOP(=S)(OCC)Oc1nc(Cl)n(n1)C(C)C
+"2-Methyl-1,3-Butadiene ",-1.714,1,68.11900000000001,0,0,1,0.0,-2.03,CC(=C)C=C
+linalool,-2.399,1,154.253,1,0,4,20.23,-1.99,CC(C)=CCCC(O)(C)C=C
+Fenthion,-4.265,1,278.335,0,1,5,27.69,-4.57,COP(=S)(OC)Oc1ccc(SC)c(C)c1
+Cyclohexanol ,-1.261,1,100.161,1,1,0,20.23,-0.44,OC1CCCCC1
+5-Allyl-5-methylbarbital,-1.013,1,182.17899999999997,2,1,2,75.27000000000001,-1.16,O=C1NC(=O)NC(=O)C1(C)CC=C
+Epiandrosterone,-3.8819999999999997,1,290.447,1,4,0,37.3,-4.16,CC34CCC1C(CCC2CC(O)CCC12C)C3CCC4=O
+mannitol,0.647,1,182.172,6,0,5,121.38000000000001,0.06,OCC(O)C(O)C(O)C(O)CO 
+Atrazine,-3.069,1,215.68800000000002,2,1,4,62.730000000000004,-3.85,CCNc1nc(Cl)nc(NC(C)C)n1
+Phenylthiourea,-1.7009999999999998,1,152.22199999999998,2,1,1,38.05,-1.77,NC(=S)Nc1ccccc1
+4-Heptanone,-1.62,1,114.18799999999999,0,0,4,17.07,-1.3,CCCC(=O)CCC
+"3,3-Dimethyl-2-butanone",-1.25,1,100.16099999999999,0,0,0,17.07,-0.72,CC(=O)C(C)(C)C
+4-Chlorophenol ,-2.761,1,128.558,1,1,0,20.23,-0.7,Oc1ccc(Cl)cc1
+Cyclohexanone,-0.996,1,98.14500000000001,0,1,0,17.07,-0.6,O=C1CCCCC1
+m-Methylaniline,-1.954,1,107.156,1,1,0,26.02,-0.85,Cc1cccc(N)c1
+Trichloroacetonitrile,-2.019,1,144.388,0,0,0,23.79,-2.168,ClC(Cl)(Cl)C#N
+norflurazon,-4.029,1,303.67100000000005,1,2,2,46.92,-4.046,CNc2cnn(c1cccc(c1)C(F)(F)F)c(=O)c2Cl
+Ipazine,-3.497,1,243.74200000000002,1,1,5,53.940000000000005,-3.785,CCN(CC)c1nc(Cl)nc(NC(C)C)n1
+Benzocaine,-2.383,1,165.19199999999998,1,1,2,52.32,-2.616,CCOC(=O)c1ccc(N)cc1
+"1,2,4-Trichlorobenzene",-4.083,1,181.449,0,1,0,0.0,-3.59,Clc1ccc(Cl)c(Cl)c1
+Triazolam,-3.948,1,343.2170000000001,0,4,1,43.07,-4.09,Cc3nnc4CN=C(c1ccccc1Cl)c2cc(Cl)ccc2n34
+Reverse Transcriptase inhibitor 1,-2.7939999999999996,1,254.29299999999998,0,3,1,49.330000000000005,-2.62,CCN2c1ncccc1N(C)C(=O)c3cccnc23 
+Dimethyl sulfide,-0.758,1,62.137,0,0,0,0.0,-0.45,CSC
+2-Bromotoluene,-3.667,1,171.03699999999998,0,1,0,0.0,-2.23,Cc1ccccc1Br
+O-Ethyl carbamate,-0.218,1,89.09400000000001,1,0,1,52.32,0.85,CCOC(=O)N
+megestrol acetate,-4.417,1,384.5160000000002,0,4,2,60.440000000000005,-5.35,CC(=O)OC3(CCC4C2C=C(C)C1=CC(=O)CCC1(C)C2CCC34C)C(C)=O 
+"2,4-Dimethyl-3-pentanol",-1.6469999999999998,1,116.20399999999998,1,0,2,20.23,-1.22,CC(C)C(O)C(C)C
+Napthalene,-3.468,2,128.17399999999995,0,2,0,0.0,-3.6,c1ccc2ccccc2c1
+Phenytoin,-3.057,1,252.27300000000002,2,3,2,58.2,-4.0969999999999995,O=C1NC(=O)C(N1)(c2ccccc2)c3ccccc3
+Methoxychlor,-5.537999999999999,1,345.6529999999999,0,2,4,18.46,-6.89,COc1ccc(cc1)C(c2ccc(OC)cc2)C(Cl)(Cl)Cl
+3-Pentanoyloxymethylphenytoin,-3.81,1,366.41700000000003,1,3,7,75.71,-4.678,O=C1N(COC(=O)CCCC)C(=O)C(N1)(c2ccccc2)c3ccccc3
+Flutriafol,-3.569,1,301.296,1,3,4,50.94,-3.37,OC(Cn1cncn1)(c2ccc(F)cc2)c3ccccc3F
+triamcinolone diacetate,-3.8760000000000003,1,478.51300000000026,2,4,4,127.20000000000002,-4.13,CC(=O)OCC(=O)C3(O)C(CC4C2CCC1=CC(=O)C=CC1(C)C2(F)C(O)CC34C)OC(C)=O 
+1-Bromobutane,-2.303,1,137.01999999999998,0,0,2,0.0,-2.37,CCCCBr
+"1,2,4,5-Tetrabromobenzene",-6.001,1,393.69800000000004,0,1,0,0.0,-6.98,Brc1cc(Br)c(Br)cc1Br
+4-Methyl-2-pentanone,-1.1840000000000002,1,100.16099999999999,0,0,2,17.07,-0.74,CC(C)CC(=O)C
+cycloate,-3.35,1,215.36199999999994,0,1,3,20.310000000000002,-3.4,CCSC(=O)N(CC)C1CCCCC1 
+Deltamethrin,-7.44,1,505.20600000000024,0,3,6,59.32000000000001,-8.402000000000001,CC1(C)C(C=C(Br)Br)C1C(=O)OC(C#N)c2cccc(Oc3ccccc3)c2
+Talbutal,-2.06,1,224.26,2,1,4,75.27000000000001,-2.016,CCC(C)C1(CC=C)C(=O)NC(=O)NC1=O
+Fenitrothion,-3.845,1,277.238,0,1,5,70.83000000000001,-4.04,COP(=S)(OC)Oc1ccc(N(=O)=O)c(C)c1
+1-Iodonapthalene,-4.888999999999999,1,254.07000000000002,0,2,0,0.0,-4.55,Ic1cccc2ccccc12
+Sorbitol,0.647,1,182.172,6,0,5,121.38000000000001,1.09,OCC(O)C(O)C(O)C(O)CO
+Ethanethiol,-0.968,1,62.137,1,0,0,0.0,-0.6,CCS
+"1,1,2-Trichloroethane",-1.9609999999999999,1,133.405,0,0,1,0.0,-1.48,ClCC(Cl)Cl
+Pyrolan,-3.141,1,245.282,0,2,2,47.36000000000001,-2.09,CN(C)C(=O)Oc1cc(C)nn1c2ccccc2
+o-Hydroxybenzamide,-1.942,1,137.13799999999998,2,1,1,63.32000000000001,-1.82,NC(=O)c1ccccc1O
+o-Nitrotoluene,-2.589,1,137.138,0,1,1,43.14,-2.33,Cc1ccccc1N(=O)=O
+"5,5-Diisopropylbarbital",-1.942,1,212.249,2,1,2,75.27000000000001,-2.766,O=C1NC(=O)NC(=O)C1(C(C)C)C(C)C
+2-Ethyltoluene,-3.2960000000000003,1,120.19499999999996,0,1,1,0.0,-3.21,CCc1ccccc1C
+1-Chloroheptane,-3.003,1,134.65,0,0,5,0.0,-4.0,CCCCCCCCl
+Barbital,-1.265,1,184.19499999999996,2,1,2,75.27000000000001,-2.4,O=C1NC(=O)NC(=O)C1(CC)CC
+Bibenzyl ,-4.301,2,182.266,0,2,3,0.0,-4.62,C(Cc1ccccc1)c2ccccc2
+RTI 23,-4.228,1,283.331,1,3,2,54.46,-5.153,CCN2c1cc(OC)cc(C)c1NC(=O)c3cccnc23 
+2-Methylphenanthrene,-4.87,1,192.261,0,3,0,0.0,-5.84,Cc1ccc2c(ccc3ccccc32)c1
+dibutylphthalate,-4.378,1,278.348,0,1,8,52.60000000000001,-4.4,CCCCOC(=O)c1ccccc1C(=O)OCCCC 
+tetrachloroguaiacol,-4.2989999999999995,1,261.919,1,1,1,29.46,-4.02,COc1c(O)c(Cl)c(Cl)c(Cl)c1Cl 
+Equilin,-3.555,1,268.356,1,4,0,37.3,-5.282,CC34CCC1C(=CCc2cc(O)ccc12)C3CCC4=O
+Chlorimuron-ethyl (ph 7),-3.719,1,414.82700000000017,1,2,8,127.79,-4.5760000000000005,CCOC(=O)c1ccccc1S(=O)(=O)NN(C=O)c2nc(Cl)cc(OC)n2
+p-Nitroanisole,-2.522,1,153.13699999999997,0,1,2,52.37,-2.41,COc1ccc(cc1)N(=O)=O
+1-Chlorohexane,-2.648,1,120.623,0,0,4,0.0,-3.12,CCCCCCCl
+"2,2',3,3',4,4',5,5'-PCB",-8.468,1,429.77200000000016,0,2,1,0.0,-9.16,Clc1cc(c(Cl)c(Cl)c1Cl)c2cc(Cl)c(Cl)c(Cl)c2Cl
+Raffinose,0.496,1,504.43800000000005,11,3,8,268.67999999999995,-0.41,OCC1OC(CO)(OC2OC(COC3OC(CO)C(O)C(O)C3O)C(O)C(O)C2O)C(O)C1O
+RTI 5,-3.471,1,253.30499999999995,0,3,1,36.44,-3.324,CCN2c1ccccc1N(C)C(=O)c3cccnc23 
+"1,1-Dichloroethane",-1.5759999999999998,1,98.96000000000001,0,0,0,0.0,-1.29,CC(Cl)Cl
+Sulfanilamide,-0.9540000000000001,1,172.20899999999997,2,1,1,86.18,-1.34,Nc1ccc(cc1)S(N)(=O)=O
+Isopropalin,-5.306,1,309.36600000000004,0,1,8,89.51999999999998,-6.49,CCCN(CCC)c1c(cc(cc1N(=O)=O)C(C)C)N(=O)=O
+Lindane,-4.0089999999999995,1,290.832,0,1,0,0.0,-4.64,ClC1C(Cl)C(Cl)C(Cl)C(Cl)C1Cl
+Isofenphos,-4.538,1,345.4010000000002,1,1,8,56.790000000000006,-4.194,CCOP(=S)(NC(C)C)Oc1ccccc1C(=O)OC(C)C
+"1,2,3-Trichlorobenzene",-4.008,1,181.44899999999998,0,1,0,0.0,-4.0,Clc1cccc(Cl)c1Cl
+Tetrachloromethane,-2.6069999999999998,1,153.823,0,0,0,0.0,-2.31,ClC(Cl)(Cl)Cl
+17a-Methyltestosterone,-4.073,1,302.4580000000001,1,4,0,37.3,-3.9989999999999997,CC1(O)CCC2C3CCC4=CC(=O)CCC4(C)C3CCC21C
+Dulcin,-2.167,1,180.20699999999997,2,1,3,64.35,-2.17,CCOc1ccc(NC(N)=O)cc1
+"trans-1,4-Dimethylcyclohexane",-3.305,1,112.216,0,1,0,0.0,-4.47,C/C1CCC(\C)CC1
+"1,7-phenantroline",-2.9939999999999998,2,180.20999999999998,0,3,0,25.78,-2.68,c1cnc2c(c1)ccc3ncccc23
+Methyl t-butyl ether ,-0.9840000000000001,1,88.14999999999999,0,0,0,9.23,-0.24,COC(C)(C)C
+Anethole,-3.2539999999999996,1,148.20499999999998,0,1,2,9.23,-3.13,COc1ccc(C=CC)cc1
+1-Hexadecanol,-4.94,1,242.44699999999992,1,0,14,20.23,-7.0,CCCCCCCCCCCCCCCCO
+uracil,-0.441,1,112.088,2,1,0,65.72,-1.4880000000000002,O=c1cc[nH]c(=O)[nH]1 
+adenine,-1.255,1,135.13,2,2,0,80.47999999999999,-2.12,Nc1ncnc2nc[nH]c12 
+Ancymidol,-2.181,1,256.30499999999995,1,3,4,55.24,-2.596,COc1ccc(cc1)C(O)(C2CC2)c3cncnc3 
+phenobarbital,-2.272,1,232.239,2,2,2,75.27000000000001,-2.322,CCC1(C(=O)NC(=O)NC1=O)c2ccccc2 
+"2',3,4-PCB",-5.686,1,257.547,0,2,1,0.0,-6.29,Clc1ccc(cc1)c2cccc(Cl)c2Cl 
+Isoproturon,-2.867,1,206.289,1,1,2,32.34,-3.536,CC(C)c1ccc(NC(=O)N(C)C)cc1
+Azintamide,-2.231,1,259.762,0,1,5,46.09,-1.716,CCN(CC)C(=O)CSc1ccc(Cl)nn1
+"2,2-Dimethyl-1-butanol",-1.365,1,102.17699999999998,1,0,2,20.23,-1.04,CCC(C)(C)CO
+Ethyl pentanoate,-1.899,1,130.18699999999998,0,0,4,26.3,-1.75,CCCOC(=O)CCC
+"2,4,6-Trinitrotoluene",-2.6060000000000003,1,227.13199999999998,0,1,3,129.42000000000002,-3.22,Cc1c(cc(cc1N(=O)=O)N(=O)=O)N(=O)=O
+Bensulide,-4.99,1,397.52400000000006,1,1,10,64.63,-4.2,CC(C)OP(=S)(OC(C)C)SCCNS(=O)(=O)c1ccccc1
+Cycloheptane,-2.9160000000000004,2,98.18900000000001,0,1,0,0.0,-3.51,C1CCCCCC1
+Propyl formate,-0.757,1,88.10599999999998,0,0,3,26.3,-0.49,CCCOC=O
+2-Isopropyltoluene,-3.585,1,134.22199999999995,0,1,1,0.0,-3.76,CC(C)c1ccccc1C
+m-Chloroaniline,-2.392,1,127.574,1,1,0,26.02,-1.37,Nc1cccc(Cl)c1
+"2,4-Dimethylpentane",-2.938,1,100.20499999999998,0,0,2,0.0,-4.26,CC(C)CC(C)C
+ethofumesate,-3.1839999999999997,1,286.34900000000005,0,2,4,61.830000000000005,-3.42,CCOC2Oc1ccc(OS(C)(=O)=O)cc1C2(C)C
+Fluometuron,-3.065,1,232.20499999999996,1,1,1,32.34,-3.43,CN(C)C(=O)Nc1cccc(c1)C(F)(F)F
+glucose,0.501,1,180.156,5,1,1,110.38000000000001,0.74,OCC1OC(O)C(O)C(O)C1O
+3-Methylphenol,-2.313,1,108.13999999999999,1,1,0,20.23,-0.68,Cc1cccc(O)c1
+Indapamide,-4.345,1,365.84200000000004,2,3,3,92.5,-3.5860000000000003,CC2Cc1ccccc1N2NC(=O)c3ccc(Cl)c(c3)S(N)(=O)=O 
+Lovastatin,-4.731,1,404.54700000000025,1,3,6,72.83,-6.005,CCC(C)C(=O)OC2CC(C)C=C3C=CC(C)C(CCC1CC(O)CC(=O)O1)C23 
+Reposal,-2.781,1,262.30899999999997,2,3,2,75.27000000000001,-2.696,CCC1(C(=O)NC(=O)NC1=O)C2=CCC3CCC2C3
+Ethyl decanoate,-3.6710000000000003,1,200.32199999999997,0,0,9,26.3,-4.1,CCCCCCCCCC(=O)OCC
+Fenuron,-1.847,1,164.208,1,1,1,32.34,-1.6,CN(C)C(=O)Nc1ccccc1
+Ethyl propyl ether,-1.072,1,88.14999999999999,0,0,3,9.23,-0.66,CCCOCC
+2-Propanol,-0.261,1,60.096000000000004,1,0,0,20.23,0.43,CC(C)O
+2-Methylnapthalene,-3.802,1,142.201,0,2,0,0.0,-3.77,Cc1ccc2ccccc2c1
+Chlorodibromethane,-2.54,1,208.28,0,0,0,0.0,-1.9,ClC(Br)Br
+Hexestrol,-4.854,1,270.372,2,2,5,40.46,-4.43,CCC(C(CC)c1ccc(O)cc1)c2ccc(O)cc2
+Malathion,-3.391,1,330.3640000000001,0,0,9,71.06,-3.37,CCOC(=O)CC(SP(=S)(OC)OC)C(=O)OCC
+Benzylchloride,-2.887,1,126.58599999999996,0,1,1,0.0,-2.39,ClCc1ccccc1
+t-Crotonaldehyde,-0.604,1,70.09100000000001,0,0,1,17.07,0.32,C/C=C/C=O
+Chlorbromuron,-3.938,1,293.548,1,1,2,41.57,-3.924,CON(C)C(=O)Nc1ccc(Br)c(Cl)c1
+"9,10-Dimethylanthracene",-5.228,1,206.28799999999998,0,3,0,0.0,-6.57,Cc1c2ccccc2c(C)c3ccccc13
+Methyl hexanoate,-1.899,1,130.18699999999998,0,0,4,26.3,-1.87,CCCCCC(=O)OC
+Dimefuron,-3.8310000000000004,1,338.79500000000013,1,2,2,80.37,-4.328,CN(C)C(=O)Nc1ccc(c(Cl)c1)n2nc(oc2=O)C(C)(C)C
+p-Fluoroacetanilide,-2.181,1,153.156,1,1,1,29.1,-1.78,CC(=O)Nc1ccc(F)cc1
+Pyrimidine,-0.884,2,80.08999999999999,0,1,0,25.78,1.1,c1cncnc1
+p-Chloronitrobenzene,-2.9010000000000002,1,157.55599999999998,0,1,1,43.14,-2.92,Clc1ccc(cc1)N(=O)=O
+Methyl propionate,-0.836,1,88.106,0,0,1,26.3,-0.14,CCC(=O)OC
+o-Chloronitrobenzene,-2.775,1,157.55599999999998,0,1,1,43.14,-2.55,Clc1ccccc1N(=O)=O
+Buthidazole,-2.398,1,256.33099999999996,1,2,1,69.56,-1.8769999999999998,CN1CC(O)N(C1=O)c2nnc(s2)C(C)(C)C
+Nitrobenzene,-2.2880000000000003,1,123.11099999999996,0,1,1,43.14,-1.8,O=N(=O)c1ccccc1
+Iodobenzene,-3.8,1,204.01000000000002,0,1,0,0.0,-3.01,Ic1ccccc1
+Metolazone,-3.7769999999999997,1,365.8420000000001,2,3,2,92.5,-3.78,CC2Nc1cc(Cl)c(cc1C(=O)N2c3ccccc3C)S(N)(=O)=O 
+Methocarbamol,-1.4280000000000002,1,241.24299999999994,2,1,6,91.00999999999999,-0.985,COc1ccccc1OCC(O)COC(N)=O
+butachlor,-4.3469999999999995,1,311.85300000000007,0,1,9,29.54,-4.19,CCCCOCN(C(=O)CCl)c1c(CC)cccc1CC 
+"2,3-Dichlorophenol",-3.1439999999999997,1,163.003,1,1,0,20.23,-1.3,Oc1cccc(Cl)c1Cl
+Propyl butyrate,-1.1909999999999998,1,102.13299999999998,0,0,2,26.3,-1.92,CCCC(=O)OC
+Propanil,-3.6439999999999997,1,218.08299999999997,1,1,2,29.1,-3.0,CCC(=O)Nc1ccc(Cl)c(Cl)c1
+Triamterene,-3.051,1,253.26900000000003,3,3,1,129.62,-2.404,Nc3nc(N)c2nc(c1ccccc1)c(N)nc2n3
+Ethyl hexanoate,-2.254,1,144.21399999999997,0,0,5,26.3,-2.35,CCCCCC(=O)OCC
+chloralose,-1.8869999999999998,1,309.529,3,2,2,88.38000000000001,-1.84,OCC(O)C2OC1OC(OC1C2O)C(Cl)(Cl)Cl 
+Prometon,-3.448,1,225.296,2,1,5,71.96000000000001,-2.478,COc1nc(NC(C)C)nc(NC(C)C)n1
+1-Octene ,-3.073,1,112.216,0,0,5,0.0,-4.44,CCCCCCC=C
+p-Methylaniline ,-1.954,1,107.156,1,1,0,26.02,-1.21,Cc1ccc(N)cc1
+aminothiazole,-1.226,1,100.14599999999999,1,1,0,38.91,-0.36,Nc1nccs1 
+Metolcarb,-1.9469999999999998,1,151.165,1,1,1,38.33,-1.8030000000000002,c1ccccc1(OC(=O)NC)
+3-Hexanol,-1.324,1,102.17699999999999,1,0,3,20.23,-0.8,CCCC(O)CC
+9-anthrol,-4.148,1,194.23299999999998,1,3,0,20.23,-4.73,c3ccc2c(O)c1ccccc1cc2c3 
+2-Methylanthracene,-4.87,1,192.261,0,3,0,0.0,-6.96,Cc1ccc2cc3ccccc3cc2c1
+"1,2,3-Trimethylbenzene ",-3.312,1,120.195,0,1,0,0.0,-3.2,Cc1cccc(C)c1C
+Aminocarb,-2.677,1,208.26099999999997,1,1,2,41.57,-2.36,CNC(=O)Oc1ccc(N(C)C)c(C)c1
+2-Nonanol,-2.387,1,144.258,1,0,6,20.23,-2.74,CCCCCCCC(C)O
+Methyldymron,-3.863,1,268.36,1,2,3,32.34,-3.35,CN(C(=O)NC(C)(C)c1ccccc1)c2ccccc2
+3-Hexanone,-1.266,1,100.16099999999999,0,0,3,17.07,-0.83,CCCC(=O)CC
+bromoxynil,-3.793,1,276.91499999999996,1,1,0,44.019999999999996,-3.33,Oc1c(Br)cc(C#N)cc1Br 
+"3,4-PCB",-5.223,1,223.102,0,2,1,0.0,-6.39,Clc1ccc(cc1Cl)c2ccccc2 
+Mefenacet,-4.504,1,298.367,0,3,4,42.43000000000001,-4.873,CN(C(=O)COc1nc2ccccc2s1)c3ccccc3
+5-hydroxyquinoline,-2.725,1,145.161,1,2,0,33.120000000000005,-2.54,Oc1cccc2ncccc12 
+Carboxin,-2.927,1,235.30800000000002,1,2,2,38.33,-3.14,CC1=C(SCCO1)C(=O)Nc2ccccc2
+Ethoxyzolamide,-3.085,1,258.324,1,2,3,82.28,-3.81,CCOc2ccc1nc(sc1c2)S(N)(=O)=O 
+Pentachlorophenol,-4.835,1,266.33799999999997,1,1,0,20.23,-4.28,Oc1c(Cl)c(Cl)c(Cl)c(Cl)c1Cl
+Bromochloromethane,-1.5190000000000001,1,129.384,0,0,0,0.0,-0.89,ClCBr
+deoxycorticosterone acetate,-4.4719999999999995,1,372.5050000000002,0,4,3,60.440000000000005,-4.63,CC(=O)OCC(=O)C3CCC4C2CCC1=CC(=O)CCC1(C)C2CCC34C 
+benzylurea,-1.5090000000000001,1,150.18099999999998,2,1,2,55.120000000000005,-0.95,NC(=O)NCc1ccccc1 
+Chlortoluron,-3.048,1,212.67999999999998,1,1,1,32.34,-3.483,CN(C)C(=O)Nc1ccc(C)c(Cl)c1
+Linuron,-3.5810000000000004,1,249.09699999999998,1,1,2,41.57,-3.592,CON(C)C(=O)Nc1ccc(Cl)c(Cl)c1
+Cycloheptanol,-1.7,1,114.188,1,1,0,20.23,-0.88,OC1CCCCCC1
+Thiamphenicol,-1.936,1,356.2270000000001,3,1,6,103.70000000000002,-2.154,CS(=O)(=O)c1ccc(cc1)C(O)C(CO)NC(=O)C(Cl)Cl 
+thiopental,-2.96,1,242.34400000000002,2,1,4,58.2,-3.36,CCCC(C)C1(CC)C(=O)NC(=S)NC1=O 
+acetazolamide,-0.7929999999999999,1,222.251,2,1,2,115.03999999999999,-2.36,CC(=O)Nc1nnc(s1)S(N)(=O)=O 
+Aldrin,-5.511,1,364.914,0,4,0,0.0,-6.307,ClC1=C(Cl)C2(Cl)C3C4CC(C=C4)C3C1(Cl)C2(Cl)Cl
+Tetrahydrofurane ,-0.62,2,72.107,0,1,0,9.23,0.49,C1CCOC1
+o-Nitroaniline,-2.2769999999999997,1,138.126,1,1,1,69.16,-1.96,Nc1ccccc1N(=O)=O
+"2,2',3,3'-PCB",-6.079,1,291.99199999999996,0,2,1,0.0,-7.28,Clc1cccc(c1Cl)c2cccc(Cl)c2Cl
+phenylbutazone,-4.0760000000000005,1,308.38100000000003,0,3,5,40.620000000000005,-3.81,CCCCC1C(=O)N(N(C1=O)c2ccccc2)c3ccccc3 
+Chlorazine,-3.6630000000000003,1,257.76899999999995,0,1,6,45.150000000000006,-4.4110000000000005,CCN(CC)c1nc(Cl)nc(n1)N(CC)CC
+captafol,-4.365,1,349.06600000000014,0,2,3,37.38,-5.4,ClC(Cl)C(Cl)(Cl)SN2C(=O)C1CC=CCC1C2=O 
+Oxazepam,-3.517,1,286.718,2,3,1,61.690000000000005,-3.952,OC3N=C(c1ccccc1)c2cc(Cl)ccc2NC3=O 
+Secobarbital,-2.415,1,238.28699999999995,2,1,5,75.27000000000001,-2.356,O=C1NC(=O)NC(=O)C1(C(C)CCC)CC=C
+Carvacrol,-3.2239999999999998,1,150.22099999999998,1,1,1,20.23,-2.08,c1(O)c(C)ccc(C(C)C)c1
+Kepone,-5.112,1,490.6390000000001,0,6,0,17.07,-5.2589999999999995,ClC1(C(=O)C2(Cl)C3(Cl)C14Cl)C5(Cl)C2(Cl)C3(Cl)C(Cl)(Cl)C45Cl
+Disulfiram,-3.862,1,296.5520000000001,0,0,4,6.48,-4.86,CCN(CC)C(=S)SSC(=S)N(CC)CC
+Cyclohexane,-2.477,2,84.162,0,1,0,0.0,-3.1,C1CCCCC1
+Dienochlor,-7.848,1,474.64,0,2,1,0.0,-7.278,ClC1=C(Cl)C(Cl)(C(=C1Cl)Cl)C2(Cl)C(=C(Cl)C(=C2Cl)Cl)Cl
+Equilenin,-3.927,1,266.34,1,4,0,37.3,-5.24,CC34CCc1c(ccc2cc(O)ccc12)C3CCC4=O
+1-Octanol,-2.105,1,130.23100000000002,1,0,6,20.23,-2.39,CCCCCCCCO
+Diethyl sulfide,-1.598,1,90.191,0,0,2,0.0,-1.34,CCSCC
+"1,2-Dichloroethane",-1.374,1,98.96000000000001,0,0,1,0.0,-1.06,ClCCCl
+2-Chloro-2-methylbutane,-2.278,1,106.59599999999999,0,0,1,0.0,-2.51,CCC(C)(C)Cl
+1-Chloro-2-bromoethane,-1.7380000000000002,1,143.411,0,0,1,0.0,-1.32,ClCCBr
+RTI 2,-3.125,1,268.32,0,3,2,49.330000000000005,-2.86,CCN2c1ncccc1N(CC)C(=O)c3cccnc23 
+Chlorobenzene,-2.975,1,112.55899999999997,0,1,0,0.0,-2.38,Clc1ccccc1
+1-Nonene ,-3.427,1,126.243,0,0,6,0.0,-5.05,CCCCCCCC=C
+p-Bromoiodobenzene,-4.754,1,282.90599999999995,0,1,0,0.0,-4.56,Brc1ccc(I)cc1
+3-Methyl-3-pentanol,-1.308,1,102.17699999999998,1,0,2,20.23,-0.36,CCC(C)(O)CC
+Pentylbenzene,-3.8989999999999996,1,148.249,0,1,4,0.0,-4.64,CCCCCc1ccccc1
+testosterone acetate,-4.449,1,330.4680000000001,0,4,1,43.370000000000005,-5.184,CC(=O)OC3CCC4C2CCC1=CC(=O)CCC1(C)C2CCC34C 
+RTI 19,-4.007,1,252.31699999999995,0,3,1,23.55,-4.749,CCN2c1ccccc1N(C)C(=O)c3ccccc23 
+2-Hexanol,-1.324,1,102.17699999999998,1,0,3,20.23,-0.89,CCCCC(C)O
+Propylcyclopentane,-3.16,1,112.21600000000001,0,1,2,0.0,-4.74,CCCC1CCCC1
+Etomidate,-3.359,1,244.294,0,2,4,44.12,-4.735,CCOC(=O)c1cncn1C(C)c2ccccc2
+Benzoxazole,-2.214,2,119.12299999999998,0,2,0,26.03,-1.16,c2ccc1ocnc1c2
+1-Pentanol,-1.042,1,88.14999999999999,1,0,3,20.23,-0.6,CCCCCO
+"N,N-Diethylaniline",-3.16,1,149.237,0,1,3,3.24,-3.03,CCN(CC)c1ccccc1
+"1,3-Difluorobenzene",-2.636,1,114.094,0,1,0,0.0,-2.0,Fc1cccc(F)c1
+3-chloropropionitrile,-0.522,1,89.525,0,0,1,23.79,-0.29,ClCCC#N 
+5-Ethyl-5-phenylbarbital,-2.272,1,232.239,2,2,2,75.27000000000001,-2.322,O=C1NC(=O)NC(=O)C1(CC)c1ccccc1
+Carbofuran,-3.05,1,221.25599999999994,1,2,1,47.56,-2.8,CNC(=O)Oc1cccc2CC(C)(C)Oc12
+"2,6-Dimethylphenol",-2.589,1,122.16699999999999,1,1,0,20.23,-1.29,Cc1cccc(C)c1O
+benzhydrol,-3.033,1,184.238,1,2,2,20.23,-2.55,c1ccccc1C(O)c2ccccc2
+Methyl decanoate,-3.3160000000000003,1,186.295,0,0,8,26.3,-4.69,CCCCCCCCCC(=O)OC
+Dicapthon,-4.188,1,297.656,0,1,5,70.83000000000001,-4.31,COP(=S)(OC)Oc1ccc(cc1Cl)N(=O)=O
+1-Bromo-2-methylpropane,-2.2880000000000003,1,137.01999999999998,0,0,1,0.0,-2.43,CC(C)CBr
+Pirimicarb,-2.34,1,238.29099999999997,0,1,2,58.56000000000001,-1.95,CN(C)C(=O)Oc1nc(nc(C)c1C)N(C)C
+1-Bromohexane,-3.012,1,165.074,0,0,4,0.0,-3.81,CCCCCCBr
+2-Methylpentane,-2.6,1,86.178,0,0,2,0.0,-3.74,CCCC(C)C
+Tetrafluthrin,-6.3389999999999995,1,418.7360000000001,0,2,4,26.3,-7.321000000000001,Cc1c(F)c(F)c(COC(=O)C2C(C=C(Cl)C(F)(F)F)C2(C)C)c(F)c1F
+Metolachlor,-3.431,1,283.7989999999999,0,1,6,29.54,-2.73,CCc1cccc(C)c1N(C(C)COC)C(=O)CCl 
+nifuroxime,-1.8430000000000002,1,156.09699999999998,1,1,2,88.87,-2.19,ON=Cc1ccc(o1)N(=O)=O 
+Amitrole,-0.674,1,84.082,2,1,0,67.59,0.522,Nc1nc[nH]n1
+Tribromomethane,-2.904,1,252.731,0,0,0,0.0,-1.91,BrC(Br)Br
+Trichlorfon,-1.8659999999999999,1,257.437,1,0,3,55.760000000000005,-0.22,COP(=O)(OC)C(O)C(Cl)(Cl)Cl
+Phosalone,-5.024,1,367.8160000000001,0,2,7,53.6,-5.233,CCOP(=S)(OCC)SCn1c(=O)oc2cc(Cl)ccc12
+Phenylmethanol,-1.699,1,108.13999999999997,1,1,1,20.23,-0.4,OCc1ccccc1
+Coumatetralyl,-5.194,1,292.33400000000006,1,4,1,50.44,-2.84,O=c2c(C3CCCc4ccccc43)c(O)c1ccccc1o2 
+4-Bromophenol,-3.1319999999999997,1,173.00900000000001,1,1,0,20.23,-1.09,Oc1ccc(Br)cc1
+2-Bromopropane,-1.949,1,122.993,0,0,0,0.0,-1.59,CC(C)Br
+"2,2,4-Trimethylpentane",-3.2760000000000002,1,114.23199999999999,0,0,1,0.0,-4.74,CC(C)CC(C)(C)C
+Nimetazepam,-3.557,1,295.29800000000006,0,3,2,75.81,-3.7960000000000003,CN2C(=O)CN=C(c1ccccc1)c3cc(ccc23)N(=O)=O
+Minoxidil,-1.8090000000000002,1,209.25299999999996,2,2,1,95.10999999999999,-1.989,Nc1cc(nc(N)n1=O)N2CCCCC2 
+Dicofol,-6.268,1,370.49,1,2,2,20.23,-5.666,OC(c1ccc(Cl)cc1)(c2ccc(Cl)cc2)C(Cl)(Cl)Cl
+Dialifos,-5.026,1,393.85400000000016,0,2,8,55.84,-6.34,CCOP(=S)(OCC)SC(CCl)N2C(=O)c1ccccc1C2=O
+"1,4-Dibromobenzene",-4.298,1,235.90599999999998,0,1,0,0.0,-4.07,Brc1ccc(Br)cc1
+Methazole,-3.6010000000000004,1,261.064,0,2,1,57.14,-2.82,Cn2c(=O)on(c1ccc(Cl)c(Cl)c1)c2=O
+p-Phenylphenol,-3.701,1,170.211,1,2,1,20.23,-3.48,Oc1ccc(cc1)c2ccccc2
+pyracarbolid,-2.83,1,217.26800000000003,1,2,2,38.33,-2.56,CC1=C(CCCO1)C(=O)Nc2ccccc2 
+Ethyl vinyl ether,-0.857,1,72.10700000000001,0,0,2,9.23,-0.85,CCOC=C
+4-methoxypteridine,-1.589,1,162.15200000000002,0,2,1,60.790000000000006,-1.11,COc1ncnc2nccnc12 
+3-Methyl-3-heptanol,-2.017,1,130.23099999999997,1,0,4,20.23,-1.6,CCCCC(C)(O)CC
+3-Ethanoyloxymethylphenytoin,-2.7230000000000003,1,324.33600000000007,1,3,4,75.71,-4.47,O=C1N(COC(=O)C)C(=O)C(N1)(c2ccccc2)c3ccccc3
+2-methoxypteridine,-1.589,1,162.152,0,2,1,60.790000000000006,-1.11,COc2ncc1nccnc1n2
+Dioxacarb,-1.614,1,223.22799999999995,1,2,2,56.790000000000006,-1.57,CNC(=O)Oc1ccccc1C2OCCO2
+isocarbamid,-1.508,1,185.22699999999998,2,1,2,61.440000000000005,-2.15,C1N(C(=O)NCC(C)C)C(=O)NC1
+Fenoxycarb,-4.662,1,301.34200000000004,1,2,7,56.790000000000006,-4.7,CCOC(=O)NCCOc2ccc(Oc1ccccc1)cc2
+acetyl sulfisoxazole,-2.024,1,293.34800000000007,1,2,3,89.43,-3.59,CC(=O)N(S(=O)c1ccc(N)cc1)c2onc(C)c2C 
+"1,1,1,2-Tetrachloroethane",-2.7939999999999996,1,167.85,0,0,0,0.0,-2.18,ClCC(Cl)(Cl)Cl
+Siduron,-3.779,1,232.32700000000003,2,2,2,41.13,-4.11,CC1CCCCC1NC(=O)Nc2ccccc2
+"1,3,5-Trichlorobenzene",-4.159,1,181.449,0,1,0,0.0,-4.48,Clc1cc(Cl)cc(Cl)c1
+Furfural,-1.391,1,96.08499999999998,0,1,1,30.21,-0.1,O=Cc1ccco1
+3-Methylbutan-1-ol,-1.0270000000000001,1,88.14999999999999,1,0,2,20.23,-0.51,CC(C)CCO
+piperonal,-2.033,1,150.13299999999998,0,2,1,35.53,-1.63,O=Cc2ccc1OCOc1c2 
+2-Methylpropene,-1.5730000000000002,1,56.108000000000004,0,0,0,0.0,-2.33,CC(=C)C
+Benzaldehyde,-1.999,1,106.12399999999997,0,1,1,17.07,-1.19,O=Cc1ccccc1
+Benfuracarb,-5.132999999999999,1,410.53600000000023,0,2,8,68.31,-4.71,CCOC(=O)CCN(SN(C)C(=O)Oc1cccc2CC(C)(C)Oc21)C(C)C
+RTI 10,-2.7710000000000004,1,226.235,0,3,0,42.43,-3.6719999999999997,O2c1ccccc1N(C)C(=O)c3cccnc23 
+Fluorene ,-4.125,2,166.22299999999998,0,3,0,0.0,-5.0,C1c2ccccc2c3ccccc13
+Methylcyclohexane ,-2.891,1,98.18900000000001,0,1,0,0.0,-3.85,CC1CCCCC1
+sulfaguanidine,-0.706,1,214.25,4,1,2,122.05999999999999,-1.99,NC(=N)NS(=O)(=O)c1ccc(N)cc1 
+Methylparaben,-2.441,1,152.149,1,1,1,46.53,-1.827,COC(=O)c1ccc(O)cc1
+2-Methyltetrahydrofurane,-1.034,1,86.134,0,1,0,9.23,0.11,CC1CCCO1
+Santonin,-2.43,1,246.30599999999995,0,3,0,43.370000000000005,-3.09,CC3C2CCC1(C)C=CC(=O)C(=C1C2OC3=O)C
+Salicin,-0.975,1,286.28,5,2,4,119.61000000000001,-0.85,OCC2OC(Oc1ccccc1CO)C(O)C(O)C2O
+Ametryn,-3.43,1,227.337,2,1,5,62.730000000000004,-3.04,CCNc1nc(NC(C)C)nc(SC)n1
+Hydroxyprogesterone-17a,-3.8760000000000003,1,330.4680000000001,1,4,1,54.37,-3.8169999999999997,CC(=O)C1(O)CCC2C3CCC4=CC(=O)CCC4(C)C3CCC21C
+2-Pentanol,-0.97,1,88.14999999999999,1,0,2,20.23,-0.29,CCCC(C)O
+benzoin,-3.148,1,212.248,1,2,3,37.3,-2.85,OC(C(=O)c1ccccc1)c2ccccc2
+"2,4-Dimethylphenol",-2.6210000000000004,1,122.16699999999999,1,1,0,20.23,-1.19,Cc1ccc(O)c(C)c1
+ampyrone,-1.192,1,203.245,1,2,1,52.95,-0.624,Cc2c(N)c(=O)n(c1ccccc1)n2C
+"2,2',4,5'-PCB",-6.23,1,291.99199999999996,0,2,1,0.0,-6.57,Clc1ccc(c(Cl)c1)c2cc(Cl)ccc2Cl 
+Terbutryn,-3.75,1,241.364,2,1,4,62.730000000000004,-4.0,CCNc1nc(NC(C)(C)C)nc(SC)n1
+2-methylpteridine,-1.24,1,146.153,0,2,0,51.56,-0.12,Cc2ncc1nccnc1n2
+Danazol,-4.5569999999999995,1,337.4630000000001,1,5,0,46.260000000000005,-5.507000000000001,CC23Cc1cnoc1C=C2CCC4C3CCC5(C)C4CCC5(O)C#C
+1-Iodobutane,-2.841,1,184.01999999999998,0,0,2,0.0,-2.96,CCCCI
+2-Bromonapthalene,-4.434,1,207.07,0,2,0,0.0,-4.4,Brc1ccc2ccccc2c1
+"Digoxin (L1=41,8mg/mL, L2=68,2mg/mL, Z=40,1mg/mL)",-5.312,1,780.9490000000001,6,8,7,203.05999999999997,-4.081,CC1OC(CC(O)C1O)OC2C(O)CC(OC2C)OC8C(O)CC(OC7CCC3(C)C(CCC4C3CC(O)C5(C)C(CCC45O)C6=CC(=O)OC6)C7)OC8C 
+Benzyltrifluoride,-3.0989999999999998,1,146.111,0,1,0,0.0,-2.51,FC(F)(F)c1ccccc1
+Dihexyl phthalate,-5.757999999999999,1,334.45600000000024,0,1,12,52.60000000000001,-6.144,CCCCCCOC(=O)c1ccccc1C(=O)OCCCCCC
+Dibenzothiophene,-4.5969999999999995,2,184.263,0,3,0,0.0,-4.38,c1ccc2c(c1)sc3ccccc23
+"2,3',4,4'-PCB",-6.709,1,326.437,0,2,1,0.0,-7.8,Clc1ccc(c(Cl)c1)c2ccc(Cl)c(Cl)c2Cl 
+Warfarin,-3.9130000000000003,1,308.3330000000001,1,3,4,67.50999999999999,-3.8930000000000002,CC(=O)CC(c1ccccc1)c3c(O)c2ccccc2oc3=O 
+hydrobenzoin,-2.645,1,214.264,2,2,3,40.46,-1.93,c1ccccc1C(O)C(O)c2ccccc2
+Dimethyl phthalate,-2.347,1,194.18599999999995,0,1,2,52.60000000000001,-1.66,COC(=O)c1ccccc1C(=O)OC
+Ethyl octanoate,-2.9619999999999997,1,172.26799999999997,0,0,7,26.3,-3.39,CCCCCCCC(=O)OCC
+Diethyldisulfide,-2.364,1,122.258,0,0,3,0.0,-2.42,CCSSCC
+"1,2-Diethoxyethane ",-0.833,1,118.176,0,0,5,18.46,-0.77,CCOCCOCC
+"1,2,4,5-Tetrachlorobenzene",-4.621,1,215.894,0,1,0,0.0,-5.56,Clc1cc(Cl)c(Cl)cc1Cl
+p-benzidine,-2.613,1,184.242,2,2,1,52.04,-2.7,Nc1ccc(cc1)c2ccc(N)cc2
+1-Heptene,-2.718,1,98.189,0,0,4,0.0,-3.73,CCCCCC=C
+Ethirimol,-2.7319999999999998,1,209.29299999999998,2,1,5,57.78,-3.028,CCCCc1c(C)nc(NCC)[nH]c1=O
+Pentobarbital,-2.312,1,226.27599999999995,2,1,4,75.27000000000001,-2.39,O=C1NC(=O)NC(=O)C1(CC)C(C)CCC
+o-Chloroaniline,-2.392,1,127.574,1,1,0,26.02,-1.52,Nc1ccccc1Cl
+3-Chloroanisole,-3.057,1,142.58499999999998,0,1,1,9.23,-2.78,COc1cccc(Cl)c1
+Pebulate,-3.1310000000000002,1,203.35099999999997,0,0,6,20.310000000000002,-3.53,CCCCN(CC)C(=O)SCCC
+Butyl acetate,-1.111,1,102.13299999999998,0,0,4,26.3,-1.37,CCCCOC=O
+Prednisolone,-2.9739999999999998,1,360.4500000000002,3,4,2,94.83,-3.18,CC12CC(O)C3C(CCC4=CC(=O)C=CC34C)C2CCC1(O)C(=O)CO
+p-terphenyl,-5.7410000000000005,2,230.31,0,3,2,0.0,-7.11,c1ccc(cc1)c2ccc(cc2)c3ccccc3
+p-Hydroxybenzaldehyde ,-2.003,1,122.12299999999998,1,1,1,37.3,-0.96,Oc1ccc(C=O)cc1
+Bromomethane,-1.109,1,94.939,0,0,0,0.0,-0.79,CBr
+Coumachlor,-4.553999999999999,1,342.7780000000001,1,3,4,67.50999999999999,-5.8389999999999995,CC(=O)CC(c1ccc(Cl)cc1)c2c(O)c3ccccc3oc2=O
+5-methylcytosine,-0.257,1,125.13099999999999,2,1,0,71.77000000000001,-1.4580000000000002,Nc1c(C)c[nH]c(=O)n1 
+benodanil,-4.245,1,323.133,1,2,2,29.1,-4.21,c1c(NC(=O)c2ccccc2(I))cccc1
+Riboflavin,-1.865,1,376.36900000000014,5,3,5,161.56,-3.685,Cc3cc2nc1c(=O)[nH]c(=O)nc1n(CC(O)C(O)C(O)CO)c2cc3C
+o-Fluorobromobenzene,-3.467,1,175.0,0,1,0,0.0,-2.7,Fc1ccccc1Br
+Permethrin,-7.129,1,391.2940000000001,0,3,6,35.53,-6.291,CC1(C)C(C=C(Cl)Cl)C1C(=O)OCc2cccc(Oc3ccccc3)c2
+3-Propanoyloxymethylphenytoin,-3.128,1,338.36300000000006,1,3,5,75.71,-4.907,O=C1N(COC(=O)CC)C(=O)C(N1)(c2ccccc2)c3ccccc3
+Cyclopentane ,-2.0380000000000003,2,70.135,0,1,0,0.0,-2.64,C1CCCC1
+o-Toluidine,-1.922,1,107.156,1,1,0,26.02,-2.21,Cc1ccccc1N
+Estragole,-3.074,1,148.205,0,1,3,9.23,-2.92,c1(OC)ccc(CC=C)cc1
+karbutilate,-2.655,1,279.34,2,1,2,70.67,-2.93,CN(C)C(=O)Nc1cccc(OC(=O)NC(C)(C)C)c1 
+3-Methyl-1-Butene,-1.994,1,70.135,0,0,1,0.0,-2.73,CC(C)C=C
+2-Hydroxypyridine,-1.655,1,95.101,1,1,0,33.120000000000005,1.02,Oc1ccccn1
+Ethane,-1.1320000000000001,1,30.07,0,0,0,0.0,-1.36,CC
+"1,2-Dichlorobenzene",-3.4819999999999998,1,147.00399999999996,0,1,0,0.0,-3.05,Clc1ccccc1Cl
+mercaptobenzothiazole,-3.411,1,167.25799999999998,1,2,0,12.89,-3.18,Sc2nc1ccccc1s2 
+"2,2',3,3',4,4',5,5',6,6'-PCB",-9.589,1,498.66200000000026,0,2,1,0.0,-11.6,Clc1c(Cl)c(Cl)c(c(Cl)c1Cl)c2c(Cl)c(Cl)c(Cl)c(Cl)c2Cl 
+Methoxsalen,-3.25,1,216.19199999999995,0,3,1,52.58,-3.6639999999999997,COc2c1occc1cc3ccc(=O)oc23 
+Acetamide,0.494,1,59.068,1,0,0,43.09,1.58,CC(=O)N
+1-Methylnaphthalene,-3.802,1,142.201,0,2,0,0.0,-3.7,Cc1cccc2ccccc12
+Napropamide,-4.088,1,271.36,0,2,5,29.540000000000003,-3.57,CCN(CC)C(=O)C(C)Oc1cccc2ccccc12 
+"3,3-Dimethyl-2-butanol",-1.2919999999999998,1,102.17699999999999,1,0,0,20.23,-0.62,CC(O)C(C)(C)C
+Methyl pentanoate,-1.545,1,116.15999999999998,0,0,3,26.3,-1.36,CCCC(=O)OCC
+Menadione,-2.667,1,172.18299999999996,0,2,0,34.14,-3.03,CC2=CC(=O)c1ccccc1C2=O 
+Phenanthrene,-4.518,2,178.23399999999998,0,3,0,0.0,-5.26,c1ccc2c(c1)ccc3ccccc32
+"2,4-Dimethylpyridine",-2.0980000000000003,1,107.15599999999999,0,1,0,12.89,0.38,Cc1ccnc(C)c1
+1-Nonanol,-2.46,1,144.258,1,0,7,20.23,-3.01,CCCCCCCCCO
+Dibromomethane,-1.883,1,173.83499999999998,0,0,0,0.0,-1.17,BrCBr
+Dexamethasone,-3.4,1,392.4670000000002,3,4,2,94.83,-3.59,CC1CC2C3CCC4=CC(=O)C=CC4(C)C3(F)C(O)CC2(C)C1(O)C(=O)CO
+"2,6-Dimethylnaphthalene ",-4.147,1,156.228,0,2,0,0.0,-4.89,Cc1ccc2cc(C)ccc2c1
+Butylate,-3.4530000000000003,1,217.378,0,0,5,20.310000000000002,-3.68,CCSC(=O)N(CC(C)C)CC(C)C
+nitroglycerin,-2.029,1,227.08499999999998,0,0,8,157.11,-2.22,O=N(=O)OCC(CON(=O)=O)ON(=O)=O 
+m-Nitroaniline,-1.936,1,138.126,1,1,1,69.16,-2.19,Nc1cccc(c1)N(=O)=O
+1-Chlorobutane,-1.94,1,92.56899999999999,0,0,2,0.0,-2.03,CCCCCl
+triforine,-3.715,1,430.9340000000001,2,1,6,64.68,-4.19,ClC(Cl)(Cl)C(NC=O)N1C=CN(C=C1)C(NC=O)C(Cl)(Cl)Cl 
+6-aminochrysene,-4.849,1,243.309,1,4,0,26.02,-6.2,Nc3cc2c1ccccc1ccc2c4ccccc34 
+RTI 17,-4.227,1,269.373,0,3,1,19.37,-4.706,CCN2c1ccccc1N(C)C(=S)c3cccnc23 
+Nitrazepam,-3.4730000000000003,1,281.271,1,3,2,84.6,-3.7960000000000003,O=C3CN=C(c1ccccc1)c2cc(ccc2N3)N(=O)=O
+"1,3-diethylthiourea",-1.028,1,132.232,2,0,2,24.06,-1.46,CCNC(=S)NCC
+"2,3,5-Trichlorophenol",-3.78,1,197.44799999999998,1,1,0,20.23,-2.67,Oc1cc(Cl)cc(Cl)c1Cl
+Propyl propanoate,-1.545,1,116.15999999999998,0,0,3,26.3,-1.34,CCCCC(=O)OC
+Aniline ,-1.632,1,93.12899999999999,1,1,0,26.02,-0.41,Nc1ccccc1
+Acenapthylene,-3.682,2,152.19599999999994,0,3,0,0.0,-3.96,C1=Cc2cccc3cccc1c23
+Atratone,-3.185,1,211.26899999999998,2,1,5,71.96000000000001,-2.084,CCNc1nc(NC(C)C)nc(OC)n1
+Benzo(a)pyrene,-6.007000000000001,2,252.31599999999997,0,5,0,0.0,-8.699,c1ccc2c(c1)cc3ccc4cccc5ccc2c3c45
+Bromoethane,-1.5290000000000001,1,108.966,0,0,0,0.0,-1.09,CCBr
+3-Hexyne,-1.933,1,82.14599999999999,0,0,0,0.0,-1.99,CCC#CCC
+Digitoxin,-6.114,1,764.9499999999999,5,8,7,182.82999999999998,-5.292999999999999,CC1OC(CC(O)C1O)OC2C(O)CC(OC2C)OC8C(O)CC(OC7CCC3(C)C(CCC4C3CCC5(C)C(CCC45O)C6=CC(=O)OC6)C7)OC8C 
+2-Methyl-1-Butene,-1.994,1,70.13499999999999,0,0,1,0.0,-2.73,CCC(=C)C
+phenolphthalein,-4.59,1,318.32800000000003,2,4,2,66.76,-2.9,Oc1ccc(cc1)C2(OC(=O)c3ccccc23)c4ccc(O)cc4 
+"1,3,5-Tribromobenzene",-5.27,1,314.802,0,1,0,0.0,-5.6,Brc1cc(Br)cc(Br)c1
+Ronnel,-5.247000000000001,1,321.549,0,1,4,27.69,-5.72,COP(=S)(OC)Oc1cc(Cl)c(Cl)cc1Cl
+methylthiouracil,-0.547,1,142.18300000000002,2,1,0,48.65,-2.436,Cc1cc(=O)[nH]c(=S)[nH]1
+Eugenol,-2.675,1,164.204,1,1,3,29.46,-1.56,COc1cc(CC=C)ccc1O
+Pyrene,-4.957,2,202.25599999999997,0,4,0,0.0,-6.176,c1cc2ccc3cccc4ccc(c1)c2c34
+Clomazone,-3.077,1,239.702,0,2,2,29.54,-2.338,CC1(C)CON(Cc2ccccc2Cl)C1=O
+2-Butoxyethanol,-0.775,1,118.17599999999999,1,0,5,29.46,-0.42,CCCCOCCO
+Quintozene,-5.098,1,295.336,0,1,1,43.14,-5.82,Clc1c(Cl)c(Cl)c(N(=O)=O)c(Cl)c1Cl
+Androsterone,-3.8819999999999997,1,290.447,1,4,0,37.3,-4.402,CC12CCC(O)CC1CCC3C2CCC4(C)C3CCC4=O
+Flurochloridone,-4.749,1,312.118,0,2,2,20.310000000000002,-4.047,FC(F)(F)c1cccc(c1)N2CC(CCl)C(Cl)C2=O
+Quinoline,-2.6630000000000003,2,129.16199999999998,0,2,0,12.89,-1.3,c1ccc2ncccc2c1
+methyl gallate,-1.913,1,184.147,3,1,1,86.99000000000001,-1.24,COC(=O)c1cc(O)c(O)c(O)c1 
+fluconazole,-2.418,1,306.276,1,3,5,81.64999999999999,-1.8,OC(Cn1cncn1)(Cn2cncn2)c3ccc(F)cc3F 
+Chlorzoxazone,-2.679,1,169.567,1,2,0,46.0,-2.8310000000000004,Clc2ccc1oc(=O)[nH]c1c2
+"2,2',3,4,4',5',6-PCB",-7.898,1,395.3270000000001,0,2,1,0.0,-7.92,Clc1ccc(c(Cl)c1)c2c(Cl)c(Cl)c(Cl)c(Cl)c2Cl
+alloxan,0.436,1,142.07,2,1,0,92.34,-1.25,O=C1NC(=O)C(=O)C(=O)N1 
+"1,3-Dichloropropane",-1.618,1,112.98700000000001,0,0,2,0.0,-1.62,ClCCCCl
+m-Fluorobromobenzene,-3.467,1,175.0,0,1,0,0.0,-2.67,Fc1cccc(Br)c1
+p-Chlorobromobenzene,-3.928,1,191.45499999999998,0,1,0,0.0,-3.63,Clc1ccc(Br)cc1
+"2,3-Dimethylbutane",-2.5839999999999996,1,86.178,0,0,1,0.0,-3.65,CC(C)C(C)C
+1-Butene,-1.655,1,56.108,0,0,1,0.0,-1.94,CCC=C
+cytosine,0.051,1,111.104,2,1,0,71.77000000000001,-1.155,Nc1cc[nH]c(=O)n1 
+"1,1,2-Trichlorotrifluoroethane",-3.077,1,187.37500000000003,0,0,1,0.0,-3.04,FC(F)(Cl)C(F)(Cl)Cl
+"O,P'-DDD",-6.007999999999999,1,320.04600000000005,0,2,3,0.0,-6.51,ClC(Cl)C(c1ccc(Cl)cc1)c2ccccc2Cl 
+o-Nitroanisole,-2.346,1,153.13699999999997,0,1,2,52.37,-1.96,COc1ccccc1N(=O)=O
+Prasterone,-3.5639999999999996,1,288.43100000000004,1,4,0,37.3,-4.12,CC34CCC1C(CC=C2CC(O)CCC12C)C3CCC4=O
+Benzo[ghi]perylene,-6.446000000000001,2,276.338,0,6,0,0.0,-9.017999999999999,c1cc2ccc3ccc4ccc5cccc6c(c1)c2c3c4c56
+meconin,-0.825,1,196.20199999999997,0,2,2,44.760000000000005,-1.899,c1c(OC)c(OC)C2C(=O)OCC2c1
+Glycerol,0.688,1,92.09400000000001,3,0,2,60.69,1.12,OCC(O)CO
+Guaiacol,-1.9409999999999998,1,124.13899999999997,1,1,1,29.46,-1.96,COc1ccccc1O 
+chlorpyrifos,-4.9719999999999995,1,350.591,0,1,6,40.58,-5.67,CCOP(=S)(OCC)Oc1nc(Cl)c(Cl)cc1Cl 
+Antipyrene,-1.733,1,188.23000000000002,0,2,1,26.93,0.715,Cc1cc(=O)n(c2ccccc2)n1C
+simazine,-2.8110000000000004,1,201.661,2,1,4,62.730000000000004,-4.55,CCNc1nc(Cl)nc(NCC)n1 
+Simetryn,-2.6889999999999996,1,213.31,0,1,3,45.150000000000006,-2.676,CSc1nc(nc(n1)N(C)C)N(C)C
+Ethylene,-0.815,1,28.053999999999995,0,0,0,0.0,-0.4,C=C
+"3,3-Dimethyl-1-butanol",-1.365,1,102.17699999999999,1,0,1,20.23,-0.5,CC(C)(C)CCO
+5-Allyl-5-ethylbarbital,-1.368,1,196.20599999999996,2,1,3,75.27000000000001,-1.614,O=C1NC(=O)NC(=O)C1(CC)CC=C
+"2,3,4-Trichlorophenol",-3.705,1,197.448,1,1,0,20.23,-2.67,Oc1ccc(Cl)c(Cl)c1Cl
+Difenoxuron,-3.928,1,286.331,1,2,4,50.800000000000004,-4.16,COc2ccc(Oc1ccc(NC(=O)N(C)C)cc1)cc2
+4-Ethyltoluene,-3.3280000000000003,1,120.19499999999996,0,1,1,0.0,-3.11,CCc1ccc(C)cc1
+Diisopropylsulfide,-2.162,1,118.24499999999999,0,0,2,0.0,-2.24,CC(C)SC(C)C
+"1,3-Dinitrobenzene",-2.281,1,168.10799999999995,0,1,2,86.28,-2.29,O=N(=O)c1cccc(c1)N(=O)=O
+Ethion,-5.471,1,384.4870000000002,0,0,12,36.92,-5.54,CCOP(=S)(OCC)SCSP(=S)(OCC)OCC
+cortisone acetate,-3.426,1,402.48700000000025,1,4,3,97.74000000000001,-4.21,CC(=O)OCC(=O)C3(O)CCC4C2CCC1=CC(=O)CCC1(C)C2C(=O)CC34C 
+Metronidazole,-0.8590000000000001,1,171.15599999999998,1,1,3,81.19,-1.22,Cc1ncc(N(=O)=O)n1CCO
+p-Chloroaniline,-2.392,1,127.574,1,1,0,26.02,-1.66,Nc1ccc(Cl)cc1
+"2,2-Dimethylpentanol",-1.719,1,116.20399999999998,1,0,3,20.23,-1.52,CCCC(C)(C)CO
+Methoproptryne,-3.259,1,271.39,2,1,8,71.96000000000001,-2.928,COCCCNc1nc(NC(C)C)nc(SC)n1
+Norea,-2.47,1,222.33199999999994,1,3,1,32.34,-3.1710000000000003,CN(C)C(=O)NC1CC2CC1C3CCCC23
+t-Butylbenzene ,-3.554,1,134.22199999999998,0,1,0,0.0,-3.66,CC(C)(C)c1ccccc1
+kebuzone,-2.645,1,322.36400000000003,0,3,5,57.690000000000005,-3.27,CC(=O)CCC1C(=O)N(N(C1=O)c2ccccc2)c3ccccc3
+prednisolone acetate,-3.5069999999999997,1,402.48700000000014,2,4,3,100.90000000000002,-4.37,CC(=O)OCC(=O)C3(O)CCC4C2CCC1=CC(=O)C=CC1(C)C2C(O)CC34C 
+Methyl propyl ether ,-0.718,1,74.12299999999999,0,0,2,9.23,-0.39,CCCOC
+Isopropyl acetate,-1.1909999999999998,1,102.133,0,0,1,26.3,-0.55,CC(C)OC(=O)C
+Bromobenzene,-3.345,1,157.01,0,1,0,0.0,-2.55,Brc1ccccc1
+testosterone propionate,-4.87,1,344.4950000000001,0,4,2,43.370000000000005,-5.37,CCC(=O)OC3CCC4C2CCC1=CC(=O)CCC1(C)C2CCC34C 
+allopurinol,-0.84,1,136.114,2,2,0,74.43,-2.266,O=c1[nH]cnc2[nH]ncc12 
+diphenamid,-3.147,1,239.318,0,2,3,20.310000000000002,-2.98,CN(C)C(=O)C(c1ccccc1)c2ccccc2 
+phthalimide,-1.882,1,147.13299999999998,1,2,0,46.17,-2.61,O=C1NC(=O)c2ccccc12 
+Fenarimol,-4.1080000000000005,1,331.202,1,3,3,46.010000000000005,-4.38,OC(c1ccc(Cl)cc1)(c2cncnc2)c3ccccc3Cl
+Methyl benzoate ,-2.4619999999999997,1,136.14999999999998,0,1,1,26.3,-1.85,COC(=O)c1ccccc1
+1-methyluracil,-0.375,1,126.115,1,1,0,54.86,-0.807,Cn1ccc(=O)[nH]c1=O
+oxyphenbutazone,-3.739,1,324.38000000000005,1,3,5,60.85000000000001,-3.73,CCCCC1C(=O)N(N(C1=O)c2ccc(O)cc2)c3ccccc3 
+"2,2',3,5'-PCB",-6.155,1,291.9920000000001,0,2,1,0.0,-6.47,Clc1ccc(Cl)c(c1)c2cccc(Cl)c2Cl 
+Quinethazone,-2.184,1,289.7440000000001,3,2,2,101.28999999999999,-3.29,CCC2NC(=O)c1cc(c(Cl)cc1N2)S(N)(=O)=O
+Cyclopentene ,-1.72,2,68.11900000000001,0,1,0,0.0,-2.1,C1CC=CC1
+alloxantin,0.919,1,286.156,6,2,1,191.0,-1.99,C1(=O)NC(=O)NC(=O)C1(O)C2(O)C(=O)NC(=O)NC2(=O)
+Nonane,-3.678,1,128.259,0,0,6,0.0,-5.88,CCCCCCCCC
+5-Methylchrysene,-5.931,1,242.321,0,4,0,0.0,-6.59,c1cccc2c3c(C)cc4ccccc4c3ccc12
+Phenetole,-2.66,1,122.16699999999996,0,1,2,9.23,-2.33,CCOc1ccccc1
+ethyl cinnamate,-3.0980000000000003,1,176.215,0,1,3,26.3,-3.0,CCOC(=O)C=Cc1ccccc1
+Clonazepam,-3.707,1,315.716,1,3,2,84.6,-3.4989999999999997,Clc1ccccc1C2=NCC(=O)Nc3ccc(cc23)N(=O)=O
+p-Toluenesulfonamide ,-1.815,1,171.22099999999998,1,1,1,60.16,-1.74,Cc1ccc(cc1)S(=O)(=O)N
+Chlorbufam,-3.6289999999999996,1,223.659,1,1,2,38.33,-2.617,CC(OC(=O)Nc1cccc(Cl)c1)C#C
+Diazepam,-4.05,1,284.74600000000004,0,3,1,32.67,-3.7539999999999996,CN2C(=O)CN=C(c1ccccc1)c3cc(Cl)ccc23
+2-Methyl-3-pentanol,-1.308,1,102.17699999999999,1,0,2,20.23,-0.7,CCC(O)C(C)C
+fensulfothion,-3.283,1,308.36100000000005,0,1,7,44.760000000000005,-2.3,CCOP(=S)(OCC)Oc1ccc(cc1)S(C)=O 
+Testosterone,-3.659,1,288.431,1,4,0,37.3,-4.02,CC12CCC3C(CCC4=CC(=O)CCC34C)C2CCC1O
+Heptane,-2.97,1,100.205,0,0,4,0.0,-4.53,CCCCCCC
+1-Napthol,-3.08,1,144.17299999999997,1,2,0,20.23,-2.22,Oc1cccc2ccccc12
+"cis-1,2-Dimethylcyclohexane",-3.305,1,112.216,0,1,0,0.0,-4.3,C/C1CCCCC1\C
+Cholanthrene,-5.942,2,254.33199999999997,0,5,0,0.0,-7.85,C1Cc2c3c1cccc3cc4c2ccc5ccccc54
+Medrogestone,-4.593,1,340.5070000000001,0,4,1,34.14,-5.27,CC(=O)C3(C)CCC4C2C=C(C)C1=CC(=O)CCC1(C)C2CCC34C
+2-Heptanone,-1.554,1,114.18799999999999,0,0,4,17.07,-1.45,CCCCCC(=O)C
+Acephate,-0.41600000000000004,1,183.16899999999998,1,0,3,55.4,0.54,COP(=O)(NC(C)=O)SC 
+DEF,-4.074,1,314.5220000000001,0,0,12,17.07,-5.14,CCCCSP(=O)(SCCCC)SCCCC
+Trichlomethiazide,-2.98,1,380.66200000000003,3,2,2,118.35999999999999,-2.68,NS(=O)(=O)c2cc1c(NC(NS1(=O)=O)C(Cl)Cl)cc2Cl 
+2-Methy-2-Butene,-1.994,1,70.13499999999999,0,0,0,0.0,-2.56,CC=C(C)C
+"1,2,4-Trimethylbenzene",-3.343,1,120.195,0,1,0,0.0,-3.31,Cc1ccc(C)c(C)c1
+"2,4,5-Trichlorophenol ",-3.78,1,197.448,1,1,0,20.23,-2.21,Oc1cc(Cl)c(Cl)cc1Cl
+phenanthridine,-3.713,2,179.22199999999998,0,3,0,12.89,-2.78,c1ccc2c(c1)cnc3ccccc23 
+3-Methyl-3-hexanol,-1.663,1,116.20399999999998,1,0,3,20.23,-0.98,CCCC(C)(O)CC
+Octane,-3.324,1,114.232,0,0,5,0.0,-5.24,CCCCCCCC
+Anthracene,-4.518,2,178.23399999999995,0,3,0,0.0,-6.35,c1ccc2cc3ccccc3cc2c1
+Phenylhydrazine,-1.8659999999999999,1,108.14399999999998,2,1,1,38.05,0.07,NNc1ccccc1
+Cyclooctane,-3.355,2,112.21600000000001,0,1,0,0.0,-4.15,C1CCCCCCC1
+"5,5-Diallylbarbital",-1.4709999999999999,1,208.21699999999996,2,1,4,75.27000000000001,-2.077,O=C1NC(=O)NC(=O)C1(CC=C)CC=C
+Trichloromethane,-1.8119999999999998,1,119.37800000000001,0,0,0,0.0,-1.17,ClC(Cl)Cl
+1-Methylcyclohexene ,-2.574,1,96.17300000000002,0,1,0,0.0,-3.27,CC1=CCCCC1
+Khellin,-3.603,1,260.24499999999995,0,3,2,61.81,-3.0210000000000004,COc2c1occc1c(OC)c3c(=O)cc(C)oc23 
+Benzo(j)fluoranthene,-6.007000000000001,2,252.31599999999997,0,5,0,0.0,-8.0,c1ccc2c3c(ccc2c1)c4cccc5cccc3c45
+2-Ethylbutanal,-1.5230000000000001,1,100.16099999999999,0,0,3,17.07,-1.52,CCC(CC)C=O
+Dipropyl ether,-1.426,1,102.17699999999999,0,0,4,9.23,-1.62,CCCOCCC
+1-Tetradecanol,-4.231,1,214.39299999999994,1,0,12,20.23,-5.84,CCCCCCCCCCCCCCO
+"2,3,6-Trichlorophenol",-3.572,1,197.44799999999998,1,1,0,20.23,-2.64,Oc1c(Cl)ccc(Cl)c1Cl
+Urea,0.8320000000000001,1,60.056,2,0,0,69.11,0.96,NC(=O)N
+1-Pentyne,-1.446,1,68.11899999999999,0,0,1,0.0,-1.64,CCCC#C
+"1,3-Dibromobenzene",-4.298,1,235.90599999999998,0,1,0,0.0,-3.54,Brc1cccc(Br)c1
+1-Octadecanol,-5.649,1,270.50099999999986,1,0,16,20.23,-8.4,CCCCCCCCCCCCCCCCCCO
+hematein,-1.795,1,300.266,4,4,0,107.22000000000001,-2.7,c1cc(O)c(O)c2OCC3(O)CC4=CC(=O)C(O)=CC4=C3c21
+hydroxychlordene,-4.156000000000001,1,354.8749999999999,1,3,0,20.23,-5.46,OC1C=CC2C1C3(Cl)C(=C(Cl)C2(Cl)C3(Cl)Cl)Cl 
+Isopentyl formate,-1.449,1,116.15999999999998,0,0,4,26.3,-1.52,CC(C)CCOC=O
+biquinoline,-4.9030000000000005,2,256.308,0,4,1,25.78,-5.4,c2ccc1nc(ccc1c2)c4ccc3ccccc3n4 
+Triethyl phosphate,-0.953,1,182.15599999999998,0,0,6,44.760000000000005,0.43,CCOP(=O)(OCC)OCC
+Chlordene,-5.152,1,338.876,0,3,0,0.0,-5.64,ClC2=C(Cl)C3(Cl)C1C=CCC1C2(Cl)C3(Cl)Cl 
+2-Nitropropane,-0.743,1,89.094,0,0,1,43.14,-0.62,CC(C)N(=O)=O
+Carbazole,-3.8360000000000003,2,167.21099999999998,1,3,0,15.79,-5.27,c1ccc2c(c1)[nH]c3ccccc32
+Erythritol,0.675,1,122.11999999999999,4,0,3,80.92,0.7,OCC(O)C(O)CO
+Risocaine,-2.7089999999999996,1,179.21899999999997,1,1,3,52.32,-2.452,CCCOC(=O)c1ccc(N)cc1
+Succinimide,0.282,1,99.089,1,1,0,46.17,0.3,O=C1CCC(=O)N1
+bupirimate,-3.4930000000000003,1,316.4270000000001,1,1,8,84.42,-4.16,CCCCc1c(C)nc(NCC)nc1OS(=O)(=O)N(C)C 
+RTI 16,-3.411,1,270.361,0,3,1,32.260000000000005,-4.6339999999999995,CCN2c1ncccc1N(C)C(=S)c3cccnc23 
+Tetrahydropyran ,-0.978,2,86.134,0,1,0,9.23,-0.03,C1CCOCC1
+1-Heptyne,-2.155,1,96.17299999999999,0,0,3,0.0,-3.01,CCCCCC#C
+3-Methylcholanthrene,-6.311,1,268.3589999999999,0,5,0,0.0,-7.92,c1cc(C)cc2c1c3cc4cccc5CCc(c45)c3cc2
+Ethyl benzoate ,-2.775,1,150.177,0,1,2,26.3,-2.32,CCOC(=O)c1ccccc1
+1-Chloro-2-methylpropane,-1.9240000000000002,1,92.569,0,0,1,0.0,-2.0,ClCC(C)C
+Ethinyl estradiol,-4.317,1,296.41,2,4,0,40.46,-4.3,CC34CCC1C(CCc2cc(O)ccc12)C3CCC4(O)C#C 
+methyl laurate,-4.025,1,214.34899999999996,0,0,10,26.3,-4.69,CCCCCCCCCCCC(=O)OC
+Napthacene,-5.568,2,228.29399999999998,0,4,0,0.0,-8.6,c1ccc2cc3cc4ccccc4cc3cc2c1
+1-Bromopentane,-2.658,1,151.047,0,0,3,0.0,-3.08,CCCCCBr
+trans-2-Heptene ,-2.784,1,98.18899999999998,0,0,3,0.0,-3.82,CCCC/C=C/C
+Metranidazole,-0.8590000000000001,1,171.15599999999998,1,1,3,81.19,-1.26,Cc1ncc(N(=O)=O)n1CCO 
+Pentylcyclopentane,-3.8689999999999998,1,140.26999999999998,0,1,4,0.0,-6.08,CCCCCC1CCCC1
+"2,2',3,5,5',6-PCB",-7.261,1,360.88200000000006,0,2,1,0.0,-7.42,Clc1ccc(Cl)c(c1)c2c(Cl)c(Cl)cc(Cl)c2Cl 
+5-Ethyl-5-isopropylbarbituric acid,-1.6030000000000002,1,198.22199999999998,2,1,2,75.27000000000001,-2.148,O=C1NC(=O)NC(=O)C1(CC)C(C)C
+"1,1,1-Trichloroethane",-2.2319999999999998,1,133.405,0,0,0,0.0,-2.0,CC(Cl)(Cl)Cl
+Cyclohexyl-5-spirobarbituric acid,-1.405,1,196.206,2,2,0,75.27,-3.06,O=C2NC(=O)C1(CCCCC1)C(=O)N2
+dimetan,-2.3040000000000003,1,211.26099999999994,0,1,1,46.61,-0.85,CN(C)C(=O)OC1=CC(=O)CC(C)(C)C1 
+4-Bromotoluene,-3.667,1,171.03700000000003,0,1,0,0.0,-3.19,Cc1ccc(Br)cc1
+Rovral,-4.004,1,330.17100000000005,1,2,2,69.72,-4.376,CC(C)NC(=O)N1CC(=O)N(C1=O)c2cc(Cl)cc(Cl)c2
+Benfluralin,-5.205,1,335.28200000000004,0,1,7,89.51999999999998,-5.53,CCCCN(CC)c1c(cc(cc1N(=O)=O)C(F)(F)F)N(=O)=O
+"2,4,6-Trimethylphenol",-2.9410000000000003,1,136.194,1,1,0,20.23,-2.05,Cc1cc(C)c(O)c(C)c1
+Benzene ,-2.418,2,78.11399999999999,0,1,0,0.0,-1.64,c1ccccc1
+p-Chloroiodobenzene,-4.3839999999999995,1,238.45499999999998,0,1,0,0.0,-4.03,Clc1ccc(I)cc1
+Metoxuron,-2.6830000000000003,1,228.67899999999997,1,1,2,41.57,-2.5639999999999996,COc1ccc(NC(=O)N(C)C)cc1Cl
+propachlor,-3.0180000000000002,1,211.69200000000004,0,1,3,20.310000000000002,-2.48,CC(C)N(C(=O)CCl)c1ccccc1 
+Styrene,-2.85,1,104.15199999999997,0,1,1,0.0,-2.82,C=Cc1ccccc1
+Dimethoxymethane,0.092,1,76.095,0,0,2,18.46,0.48,COCOC
+o-Xylene ,-3.0039999999999996,1,106.16799999999999,0,1,0,0.0,-2.8,Cc1ccccc1C
+Butan-2-ol,-0.616,1,74.12299999999999,1,0,1,20.23,0.47,CCC(C)O
+"1,4-Benzenediol",-1.59,1,110.11199999999998,2,1,0,40.46,-0.17,Oc1ccc(O)cc1
+Benzo(b)fluorene,-5.189,2,216.283,0,4,0,0.0,-8.04,C1c2ccccc2c3cc4ccccc4cc13
+hydantoin,0.603,1,100.077,2,1,0,58.2,-0.4,O=C1CNC(=O)N1 
+4-hexylresorcinol,-3.4930000000000003,1,194.27399999999992,2,1,5,40.46,-2.59,c1(O)cc(O)ccc1CCCCCC
+allicin,-2.045,1,162.27899999999997,0,0,5,17.07,-0.83,C=CCS(=O)SCC=C
+"5,6-Dimethylchrysene",-6.265,1,256.348,0,4,0,0.0,-7.01,Cc1c(C)c2c3ccccc3ccc2c4ccccc14
+Betamethasone-17-valerate,-5.062,1,476.5850000000002,2,4,6,100.90000000000002,-4.71,CCCCC(=O)OC3(C(C)CC4C2CCC1=CC(=O)C=CC1(C)C2(F)C(O)CC34C)C(=O)CO
+uric acid,-0.541,1,168.112,4,2,0,114.36999999999998,-3.93,O=c2[nH]c(=O)c1[nH]c(=O)[nH]c1[nH]2 
+"2,3,4,6-Tetrachlorophenol",-4.203,1,231.89299999999997,1,1,0,20.23,-3.1,Oc1c(Cl)cc(Cl)c(Cl)c1Cl
+DDT,-6.638,1,354.491,0,2,2,0.0,-7.15,Clc1ccc(cc1)C(c2ccc(Cl)cc2)C(Cl)(Cl)Cl
+Isobutyl formate,-1.095,1,102.13299999999998,0,0,3,26.3,-1.01,CC(C)COC=O
+RTI 13,-4.45,1,322.29,1,3,1,58.120000000000005,-4.207,CCN2c1nc(C)cc(C(F)(F)F)c1NC(=O)c3cccnc23 
+Hexane ,-2.615,1,86.178,0,0,3,0.0,-3.84,CCCCCC
+methyl nicotinate,-1.621,1,137.138,0,1,1,39.19,-0.46,COC(=O)c1cccnc1 
+Bendroflumethiazide,-3.741,1,421.4220000000001,3,3,3,118.35999999999999,-3.59,NS(=O)(=O)c3cc2c(NC(Cc1ccccc1)NS2(=O)=O)cc3C(F)(F)F
+"2,3,3',4,4',5-PCB",-7.425,1,360.88200000000006,0,2,1,0.0,-7.82,Clc1ccc(cc1Cl)c2cc(Cl)c(Cl)c(Cl)c2Cl 
+Triphenylene,-5.568,2,228.29399999999998,0,4,0,0.0,-6.726,c1ccc2c(c1)c3ccccc3c4ccccc24
+Dienestrol,-4.775,1,266.34,2,2,3,40.46,-4.95,CC=C(C(=CC)c1ccc(O)cc1)c2ccc(O)cc2
+Di(2-ethylhexyl)-phthalate,-7.117000000000001,1,390.5640000000003,0,1,14,52.60000000000001,-6.96,CCCCC(CC)COC(=O)c1ccccc1C(=O)OCC(CC)CCCC
+2-Ethyl pyridine,-2.051,1,107.15599999999998,0,1,1,12.89,0.51,CCc1ccccn1
+Naled,-3.548,1,380.784,0,0,5,44.760000000000005,-2.28,COP(=O)(OC)OC(Br)C(Cl)(Cl)Br
+Biphenyl,-4.079,2,154.21199999999996,0,2,1,0.0,-4.345,c1ccc(cc1)c2ccccc2
+Altretamine,-2.492,1,210.285,0,1,3,48.39000000000001,-3.364,CN(C)c1nc(nc(n1)N(C)C)N(C)C
+Cycloheptyl-5-spirobarbituric acid,-1.844,1,210.23299999999998,2,2,0,75.27,-3.168,O=C2NC(=O)C1(CCCCCC1)C(=O)N2 
+Fructose,0.47100000000000003,1,180.156,5,1,2,110.38000000000001,0.64,OCC1OC(O)(CO)C(O)C1O
+"3,5-Dimethylphenol",-2.6519999999999997,1,122.16699999999997,1,1,0,20.23,-1.4,Cc1cc(C)cc(O)c1
+Barban,-4.16,1,258.104,1,1,2,38.33,-4.37,ClCC#CCOC(=O)Nc1cccc(Cl)c1
+p-Chloroacetanilide,-2.642,1,169.611,1,1,1,29.1,-2.843,CC(=O)Nc1ccc(Cl)cc1
+"2,2',3,4,5,5',6-PCB",-7.898,1,395.3270000000001,0,2,1,0.0,-8.94,Clc1ccc(Cl)c(c1)c2c(Cl)c(Cl)c(Cl)c(Cl)c2Cl
+"2,2-Dimethylbutane",-2.5839999999999996,1,86.17799999999998,0,0,0,0.0,-3.55,CCC(C)(C)C
+N-Methylaniline ,-2.097,1,107.15599999999998,1,1,1,12.03,-1.28,CNc1ccccc1
+Hydrocortisone 21-acetate,-3.6919999999999997,1,404.5030000000002,2,4,3,100.90000000000002,-4.88,CC(=O)OCC(=O)C1(O)CCC2C3CCC4=CC(=O)CCC4(C)C3C(O)CC21C
+Lorazepam,-3.75,1,321.163,2,3,1,61.690000000000005,-3.6039999999999996,OC3N=C(c1ccccc1Cl)c2cc(Cl)ccc2NC3=O
+3-Chlorophenol,-2.761,1,128.558,1,1,0,20.23,-0.7,Oc1cccc(Cl)c1
+chlorothiazide,-1.7519999999999998,1,295.72900000000004,2,2,1,118.69,-3.05,NS(=O)(=O)c2cc1c(N=CNS1(=O)=O)cc2Cl 
+5-Methyl-5-ethylbarbituric acid,-0.9109999999999999,1,170.16799999999998,2,1,1,75.27000000000001,-1.228,O=C1NC(=O)NC(=O)C1(C)CC
+Diphenylmethane,-4.09,2,168.239,0,2,2,0.0,-4.08,C(c1ccccc1)c2ccccc2
+Propazine,-3.3289999999999997,1,229.71500000000003,2,1,4,62.730000000000004,-4.43,CC(C)Nc1nc(Cl)nc(NC(C)C)n1
+2-Methylpentanol,-1.381,1,102.17699999999999,1,0,3,20.23,-1.11,CCCC(C)CO
+2-Methyl-2-hexanol,-1.663,1,116.20399999999998,1,0,3,20.23,-1.08,CCCCC(C)(C)O
+Ethylbenzene,-2.988,1,106.16799999999996,0,1,1,0.0,-2.77,CCc1ccccc1
+Heptachlor,-5.26,1,373.3209999999999,0,3,0,0.0,-6.317,ClC1C=CC2C1C3(Cl)C(=C(Cl)C2(Cl)C3(Cl)Cl)Cl
+Fenpropathrin,-6.15,1,349.43000000000006,0,3,5,59.32000000000001,-6.025,CC1(C)C(C(=O)OC(C#N)c2cccc(Oc3ccccc3)c2)C1(C)C
+Methoprene,-4.795,1,310.47800000000007,0,0,10,35.53,-5.19,COC(C)(C)CCCC(C)CC=CC(C)=CC(=O)OC(C)C
+Prometryn,-3.693,1,241.364,2,1,5,62.730000000000004,-4.1,CSc1nc(NC(C)C)nc(NC(C)C)n1
+Buturon,-3.199,1,236.702,1,1,2,32.34,-3.9,CC(C#C)N(C)C(=O)Nc1ccc(Cl)cc1
+"2,3-Dimethylnaphthalene",-4.1160000000000005,1,156.22799999999998,0,2,0,0.0,-4.72,Cc1cc2ccccc2cc1C
+"2,4',5-PCB",-5.7620000000000005,1,257.547,0,2,1,0.0,-6.25,Clc1ccc(cc1)c2cc(Cl)ccc2Cl 
+"2,3',4,4',5-PCB",-7.343,1,360.88200000000006,0,2,1,0.0,-7.39,Clc1ccc(c(Cl)c1)c2cc(Cl)c(Cl)c(Cl)c2Cl 
+2-cyanoguanidine,0.361,1,84.082,2,0,0,88.19,-0.31,NC(N)=NC#N 
+Chloropicrin,-1.8659999999999999,1,164.375,0,0,0,43.14,-2.0,ClC(Cl)(Cl)N(=O)=O
+"2,6-PCB",-4.984,1,223.102,0,2,1,0.0,-5.21,Clc1cccc(Cl)c1c2ccccc2 
+p-Methoxybenzaldehyde,-2.252,1,136.14999999999998,0,1,2,26.3,-1.49,COc1ccc(C=O)cc1
+4-Nitroacetanilide,-2.219,1,180.16299999999998,1,1,2,72.24000000000001,-2.6919999999999997,CC(=O)Nc1ccc(cc1)N(=O)=O
+Ethyl heptanoate,-2.608,1,158.24099999999999,0,0,6,26.3,-2.74,CCCCCCC(=O)OCC
+indazole,-2.34,2,118.13899999999998,1,2,0,28.68,-2.16,c2ccc1[nH]ncc1c2 
+triamcinolone acetonide,-3.928,1,434.50400000000025,2,5,2,93.06000000000002,-4.31,CC5(C)OC4CC3C2CCC1=CC(=O)C=CC1(C)C2(F)C(O)CC3(C)C4(O5)C(=O)CO 
+guanine,-0.67,1,151.129,3,2,0,100.44999999999999,-3.583,Nc2nc1[nH]cnc1c(=O)[nH]2 
+Stanolone,-3.8819999999999997,1,290.44699999999995,1,4,0,37.3,-4.743,CC34CCC1C(CCC2CC(=O)CCC12C)C3CCC4O 
+1-Hexene-3-ol,-1.199,1,100.16099999999999,1,0,3,20.23,-0.59,CCCC(O)C=C
+norbormide,-4.238,1,511.5810000000002,2,7,5,92.18,-3.931,OC(C1=CC2C5C(C1C2=C(c3ccccc3)c4ccccn4)C(=O)NC5=O)(c6ccccc6)c7ccccn7 
+Dibutyl ether ,-2.135,1,130.231,0,0,6,9.23,-1.85,CCCCOCCCC
+RTI 6,-3.335,1,313.36100000000005,2,3,4,81.59000000000002,-3.36,CCN2c1nc(N(C)(CCO))ccc1NC(=O)c3cccnc23 
+Flucytosine,-0.132,1,129.09399999999997,2,1,0,71.77,-0.972,Nc1nc(=O)[nH]cc1F
+stadacaine,-5.127999999999999,1,293.40700000000004,0,1,9,38.77,-3.84,CCCCOc1ccc(C(=O)OCC)c(c1)N(CC)CC 
+2-Methyl-2-heptanol,-2.017,1,130.231,1,0,4,20.23,-1.72,CCCCCC(C)(C)O
+Hexamethylbenzene,-4.361000000000001,1,162.27599999999998,0,1,0,0.0,-5.23,Cc1c(C)c(C)c(C)c(C)c1C
+Pteridine,-0.9059999999999999,2,132.12599999999998,0,2,0,51.56,0.02,c2cnc1ncncc1n2
+Parathion,-3.949,1,291.26500000000004,0,1,7,70.83000000000001,-4.66,CCOP(=S)(OCC)Oc1ccc(cc1)N(=O)=O
+indoline,-2.195,2,119.16699999999999,1,2,0,12.03,-1.04,c2ccc1NCCc1c2 
+1-Nitronapthalene,-3.4139999999999997,1,173.171,0,2,1,43.14,-3.54,O=N(=O)c1cccc2ccccc12
+3-Methyl-2-pentanone,-1.266,1,100.16099999999999,0,0,2,17.07,-0.67,CCC(C)C(=O)C
+bromadiolone,-7.877000000000001,1,527.4140000000002,2,5,6,70.67,-4.445,OC(CC(c1ccccc1)c3c(O)c2ccccc2oc3=O)c4ccc(cc4)c5ccc(Br)cc5 
+Nitromethane,-0.042,1,61.040000000000006,0,0,0,43.14,0.26,CN(=O)=O
+Triallate,-4.578,1,304.66999999999996,0,0,4,20.310000000000002,-4.88,CC(C)N(C(C)C)C(=O)SCC(Cl)=C(Cl)Cl
+Indole,-2.654,2,117.15099999999997,1,2,0,15.79,-1.52,c2ccc1[nH]ccc1c2
+Androstenedione,-3.3930000000000002,1,286.415,0,4,0,34.14,-3.69,CC34CCC1C(CCC2=CC(=O)CCC12C)C3CCC4=O
+Xipamide,-3.642,1,354.8150000000001,3,2,3,109.48999999999998,-3.79,Cc1cccc(C)c1NC(=O)c2cc(c(Cl)cc2O)S(N)(=O)=O
+Ethylcyclohexane,-3.245,1,112.21600000000001,0,1,1,0.0,-4.25,CCC1CCCCC1
+Mebendazole,-4.118,1,295.298,2,3,3,84.07999999999998,-3.88,COC(=O)Nc2nc1ccc(cc1[nH]2)C(=O)c3ccccc3
+RTI 12,-3.446,1,288.73800000000006,0,3,1,49.330000000000005,-4.114,CCN2c1nc(Cl)ccc1N(C)C(=O)c3cccnc23 
+Carbaryl,-3.0869999999999997,1,201.225,1,2,1,38.33,-3.2239999999999998,CNC(=O)Oc1cccc2ccccc12
+Ethyne,-0.252,1,26.037999999999997,0,0,0,0.0,0.29,C#C
+"3,5-Dimethylpyridine",-2.0980000000000003,1,107.15599999999998,0,1,0,12.89,0.38,Cc1cncc(C)c1
+"1,4-Cyclohexadiene",-1.8419999999999999,2,80.12999999999998,0,1,0,0.0,-2.06,C1C=CCC=C1
+Mecarbam,-3.738,1,329.3800000000001,0,0,8,65.07000000000001,-2.5180000000000002,CCOC(=O)N(C)C(=O)CSP(=S)(OCC)OCC
+1-Phenylethanol,-1.919,1,122.16699999999996,1,1,1,20.23,-0.92,CC(O)c1ccccc1
+"1,2-Dichloropropane",-1.794,1,112.98700000000001,0,0,1,0.0,-1.6,CC(Cl)CCl
+2-Ethyl-2-hexanal,-2.081,1,126.19899999999998,0,0,4,17.07,-2.46,CCCC=C(CC)C=O
+methyltestosterone acetate,-4.863,1,344.4950000000001,0,4,1,43.370000000000005,-5.284,CC(=O)OC3(C)CCC4C2CCC1=CC(=O)CCC1(C)C2CCC34C 
+"2,4,6-PCB",-5.604,1,257.547,0,2,1,0.0,-6.14,Clc1ccc(cc1)c2c(Cl)cccc2Cl 
+Triclosan,-5.645,1,289.54499999999996,1,2,2,29.46,-4.46,Oc1cc(Cl)ccc1Oc2ccc(Cl)cc2Cl
+Corticosterone,-3.4539999999999997,1,346.46700000000016,2,4,2,74.6,-3.24,CC12CC(O)C3C(CCC4=CC(=O)CCC34C)C2CCC1C(=O)CO
+"1,3,5-Trimethylbenzene ",-3.375,1,120.19499999999998,0,1,0,0.0,-3.4,Cc1cc(C)cc(C)c1
+dioctyl phthalate,-7.148,1,390.56400000000036,0,1,16,52.60000000000001,-5.115,CCCCCCCCOC(=O)c1ccccc1C(=O)OCCCCCCCC 
+1-Pentadecanol,-4.586,1,228.41999999999993,1,0,13,20.23,-6.35,CCCCCCCCCCCCCCCO
+"2,2',6,6'-PCB",-5.915,1,291.99199999999996,0,2,1,0.0,-7.39,Clc1cccc(Cl)c1c2c(Cl)cccc2Cl 
+"5,5-Dimethylbarbituric acid",-0.556,1,156.141,2,1,0,75.27000000000001,-1.742,O=C1NC(=O)NC(=O)C1(C)C
+2-Iodopropane,-2.4859999999999998,1,169.993,0,0,0,0.0,-2.09,CC(C)I
+"1,2-Dinitrobenzene",-2.281,1,168.10799999999995,0,1,2,86.28,-3.1,O=N(=O)c1ccccc1N(=O)=O
+3-Methyl-2-butanone,-0.912,1,86.13399999999999,0,0,1,17.07,-0.12,CC(C)C(=O)C
+Tricyclazole,-2.8680000000000003,1,189.24300000000002,0,3,0,30.19,-2.07,Cc2cccc3sc1nncn1c23 
+2-Octanone,-1.909,1,128.21499999999997,0,0,5,17.07,-2.05,CCCCCCC(=O)C
+Methyl nonanoate,-2.9619999999999997,1,172.268,0,0,7,26.3,-3.38,CCCCCCCCC(=O)OC
+Thalidomide,-1.944,1,258.233,1,3,1,83.55000000000001,-2.676,O=C1N(C2CCC(=O)NC2=O)C(=O)c3ccccc13
+Trifluralin,-5.205,1,335.28200000000004,0,1,7,89.51999999999998,-5.68,CCCN(CCC)c1c(cc(cc1N(=O)=O)C(F)(F)F)N(=O)=O
+Cyclopentyl-5-spirobarbituric acid,-0.966,1,182.179,2,2,0,75.27,-2.349,O=C2NC(=O)C1(CCCC1)C(=O)N2
+Cycluron,-2.6289999999999996,1,198.30999999999992,1,1,1,32.34,-2.218,CN(C)C(=O)NC1CCCCCCC1
+Mirex,-6.155,1,545.5460000000002,0,6,0,0.0,-6.8,ClC1(C2(Cl)C3(Cl)C4(Cl)C5(Cl)C1(Cl)C3(Cl)Cl)C5(Cl)C(Cl)(Cl)C24Cl
+aminopyrine,-2.129,1,231.299,0,2,2,30.17,-0.364,CN(C)c2c(C)n(C)n(c1ccccc1)c2=O 
+3-Pentanol,-0.97,1,88.15,1,0,2,20.23,-0.24,CCC(O)CC
+p-Nitrotoluene,-2.64,1,137.138,0,1,1,43.14,-2.49,Cc1ccc(cc1)N(=O)=O
+bromopropylate,-5.832999999999999,1,428.12000000000006,1,2,4,46.53,-4.93,CC(C)OC(=O)C(O)(c1ccc(Br)cc1)c2ccc(Br)cc2 
+Pyrazon,-2.603,1,221.647,1,2,1,60.91,-2.878,Nc2cnn(c1ccccc1)c(=O)c2Cl
+2-Methylbutan-2-ol,-0.9540000000000001,1,88.14999999999998,1,0,1,20.23,0.15,CCC(C)(C)O
+p-Cresol,-2.313,1,108.13999999999999,1,1,0,20.23,-0.73,Cc1ccc(O)cc1
+Ethyl formate,-0.402,1,74.07900000000001,0,0,2,26.3,0.15,CCOC=O
+Decalin,-3.715,2,138.254,0,2,0,0.0,-5.19,C1CCC2CCCCC2C1
+Butanethiol ,-1.676,1,90.19099999999999,1,0,2,0.0,-2.18,CCCCS
+Benzo(e)pyrene,-6.007000000000001,2,252.31599999999997,0,5,0,0.0,-7.8,c1ccc2c(c1)c3cccc4ccc5cccc2c5c43
+Tetrachloroethylene,-3.063,1,165.834,0,0,0,0.0,-2.54,ClC(=C(Cl)Cl)Cl
+3-Pentanone,-0.912,1,86.134,0,0,2,17.07,-0.28,CCC(=O)CC
+Acrylonitrile,-0.354,1,53.06399999999999,0,0,0,23.79,0.15,C=CC#N
+Flumethasone,-3.5389999999999997,1,410.4570000000002,3,4,2,94.83,-5.6129999999999995,CC1CC2C3CC(F)C4=CC(=O)C=CC4(C)C3(F)C(O)CC2(C)C1(O)C(=O)CO
+Terbumeton,-3.505,1,225.296,2,1,4,71.96000000000001,-3.239,CCNc1nc(NC(C)(C)C)nc(OC)n1
+3-Methylheptane,-3.3080000000000003,1,114.23199999999999,0,0,4,0.0,-5.16,CCCCC(C)CC
+"1,2-Dibromoethane",-2.102,1,187.862,0,0,1,0.0,-1.68,BrCCBr
+Isoprocarb,-2.734,1,193.24599999999998,1,1,2,38.33,-2.863,CNC(=O)Oc1ccccc1C(C)C
+Niridazole,-1.9480000000000002,1,214.20600000000002,1,2,2,88.37,-3.22,O=C1NCCN1c2ncc(s2)N(=O)=O
+Benzo(a)fluorene,-5.189,2,216.283,0,4,0,0.0,-6.68,C1c2ccccc2c3ccc4ccccc4c13
+2-Chloroanisole,-2.912,1,142.58499999999998,0,1,1,9.23,-2.46,COc1ccccc1Cl
+Bromophos,-5.604,1,366.0,0,1,4,27.69,-6.09,COP(=S)(OC)Oc1cc(Cl)c(Br)cc1Cl
+"P,P'-DDD",-6.007999999999999,1,320.04600000000005,0,2,3,0.0,-7.2,ClC(Cl)C(c1ccc(Cl)cc1)c2ccc(Cl)cc2 
+Azobenzene,-4.034,2,182.226,0,2,2,24.72,-4.45,N(=Nc1ccccc1)c2ccccc2
+4-Isopropyltoluene,-3.617,1,134.22199999999998,0,1,1,0.0,-3.77,CC(C)c1ccc(C)cc1
+"2,6-Dichlorophenol",-3.012,1,163.003,1,1,0,20.23,-1.79,Oc1c(Cl)cccc1Cl
+Sucrose,0.31,1,342.297,8,2,5,189.52999999999997,0.79,OCC2OC(OC1(CO)OC(CO)C(O)C1O)C(O)C(O)C2O 
+d-inositol,-0.887,1,180.156,6,1,0,121.38000000000001,0.35,OC1C(O)C(O)C(O)C(O)C1O
+Dyphylline,-0.847,1,254.24599999999995,2,2,3,102.28,-0.17,Cn2c(=O)n(C)c1ncn(CC(O)CO)c1c2=O
+Chloramphenicol,-2.613,1,323.13200000000006,3,1,6,112.70000000000002,-2.1109999999999998,OCC(NC(=O)C(Cl)Cl)C(O)c1ccc(cc1)N(=O)=O
+Epitostanol,-4.545,1,306.51500000000004,1,5,0,20.23,-5.41,CC45CCC2C(CCC3CC1SC1CC23C)C4CCC5O
+"1,2-Dibromobenzene",-4.172,1,235.90599999999998,0,1,0,0.0,-3.5,Brc1ccccc1Br
+"2,4,6-Trichlorophenol",-3.648,1,197.44799999999998,1,1,0,20.23,-2.34,Oc1c(Cl)cc(Cl)cc1Cl
+RTI 20,-3.6630000000000003,1,255.29199999999997,0,3,2,20.310000000000002,-4.7989999999999995,C2c1ccccc1N(CCF)C(=O)c3ccccc23 
+"2,4-Dimethyl-3-pentanone",-1.7519999999999998,1,114.18799999999997,0,0,2,17.07,-1.3,CC(C)C(=O)C(C)C
+gentisin,-1.2919999999999998,1,262.261,2,3,1,75.99000000000001,-2.943,c1c(O)C2C(=O)C3cc(O)ccC3OC2cc1(OC)
+Caffeine,-1.4980000000000002,1,194.19399999999996,0,2,0,61.82,-0.8759999999999999,Cn1cnc2n(C)c(=O)n(C)c(=O)c12
+Spironolactone,-3.842,1,416.58300000000025,0,5,1,60.44,-4.173,CC(=O)SC4CC1=CC(=O)CCC1(C)C5CCC2(C)C(CCC23CCC(=O)O3)C45
+Diphenyl ether ,-4.254,2,170.211,0,2,2,9.23,-3.96,O(c1ccccc1)c2ccccc2
+"2,2',4,4',5,5'-PCB",-7.343,1,360.88200000000006,0,2,1,0.0,-8.56,Clc1cc(Cl)c(cc1Cl)c2cc(Cl)c(Cl)cc2Cl 
+nicotinamide,-0.9640000000000001,1,122.12699999999997,1,1,1,55.980000000000004,0.61,NC(=O)c1cccnc1 
+Thiophenol ,-2.758,1,110.18099999999997,1,1,0,0.0,-2.12,Sc1ccccc1
+XMC,-2.688,1,179.219,1,1,1,38.33,-2.5810000000000004,CNC(=O)Oc1cc(C)cc(C)c1
+Chlordane,-6.039,1,409.7819999999999,0,3,0,0.0,-6.86,ClC1CC2C(C1Cl)C3(Cl)C(=C(Cl)C2(Cl)C3(Cl)Cl)Cl
+Dimethyldisulfide,-1.524,1,94.20400000000001,0,0,1,0.0,-1.44,CSSC
+Benzamide,-1.501,1,121.13899999999995,1,1,1,43.09,-0.96,NC(=O)c1ccccc1
+o-Chlorobromobenzene,-3.84,1,191.45499999999998,0,1,0,0.0,-3.19,Clc1ccccc1Br
+Monotropitoside,-1.493,1,446.40500000000003,6,3,6,184.6,-0.742,COC(=O)c1ccccc1OC2OC(COC3OCC(O)C(O)C3O)C(O)C(O)C2O
+RTI 15,-3.891,1,268.32,1,3,1,58.120000000000005,-4.553999999999999,CCN2c1nc(C)cc(C)c1NC(=O)c3cccnc23 
+"3,5-Dichlorophenol",-3.428,1,163.003,1,1,0,20.23,-1.34,Oc1cc(Cl)cc(Cl)c1
+1-Methylphenanthrene,-4.87,1,192.261,0,3,0,0.0,-5.85,Cc1cccc2c1ccc3ccccc32
+2-Ethyl-1-hexanol,-2.089,1,130.231,1,0,5,20.23,-2.11,CCCCC(CC)CO
+Diallate,-3.827,1,270.225,0,0,4,20.310000000000002,-4.2860000000000005,CC(C)N(C(C)C)C(=O)SCC(=CCl)Cl
+Toluene ,-2.713,1,92.14099999999999,0,1,0,0.0,-2.21,Cc1ccccc1
+Cycloheptene,-2.5989999999999998,2,96.173,0,1,0,0.0,-3.18,C1CCC=CCC1
+Griseofulvin,-3.3280000000000003,1,352.7700000000001,0,3,3,71.06,-3.2460000000000004,COC1=CC(=O)CC(C)C13Oc2c(Cl)c(OC)cc(OC)c2C3=O
+1-Decanol,-2.8139999999999996,1,158.285,1,0,8,20.23,-3.63,CCCCCCCCCCO
+"3,3-Dimethylpentane",-2.938,1,100.20499999999998,0,0,2,0.0,-4.23,CCC(C)(C)CC
+vamidothion,-1.446,1,287.34299999999996,1,0,8,64.63000000000001,1.1440000000000001,CNC(=O)C(C)SCCSP(=O)(OC)(OC)
+"2,3,4,5-Tetrachlorophenol",-4.335,1,231.893,1,1,0,20.23,-3.15,Oc1cc(Cl)c(Cl)c(Cl)c1Cl
+Butyraldehyde,-0.7490000000000001,1,72.107,0,0,2,17.07,-0.01,CCCC=O
+dexamethasone acetate,-3.9330000000000003,1,434.5040000000003,2,4,3,100.9,-4.9,CC4CC3C2CCC1=CC(=O)C=CC1(C)C2(F)C(O)CC3(C)C4(O)C(=O)COC(C)=O 
+Butane,-1.9069999999999998,1,58.123999999999995,0,0,1,0.0,-2.57,CCCC
+o-Methoxyphenol,-1.9409999999999998,1,124.13899999999997,1,1,1,29.46,-1.96,COc1ccccc1O
+Fluoromethalone,-3.5069999999999997,1,376.46800000000013,2,4,1,74.6,-4.099,CC1CC2C3CCC(O)(C(=O)C)C3(C)CC(O)C2(F)C4(C)C=CC(=O)C=C14
+Pentachloroethane,-3.3819999999999997,1,202.29500000000002,0,0,0,0.0,-2.6,ClC(Cl)C(Cl)(Cl)Cl
+Diethyl phthalate ,-3.016,1,222.23999999999995,0,1,4,52.60000000000001,-2.35,CCOC(=O)c1ccccc1C(=O)OCC
+2-Methylpropan-1-ol,-0.672,1,74.12299999999999,1,0,1,20.23,0.1,CC(C)CO
+Isobutylbenzene,-3.57,1,134.22199999999998,0,1,2,0.0,-4.12,CC(C)Cc1ccccc1
+Diiodomethane,-2.958,1,267.835,0,0,0,0.0,-2.34,ICI
+4-Heptanol,-1.6780000000000002,1,116.204,1,0,4,20.23,-1.4,CCCC(O)CCC
+Pentyl acetate,-1.8330000000000002,1,130.18699999999998,0,0,4,26.3,-1.89,CCCCCOC(=O)C
+"2,3,5,6-Tetrachlorophenol",-4.203,1,231.893,1,1,0,20.23,-3.37,Oc1c(Cl)c(Cl)cc(Cl)c1Cl
+Propylbenzene ,-3.281,1,120.19499999999995,0,1,2,0.0,-3.37,CCCc1ccccc1
+"1,2-Dichlorotetrafluoroethane",-2.697,1,170.92000000000002,0,0,1,0.0,-2.74,FC(F)(Cl)C(F)(F)Cl
+2-butenal,-0.604,1,70.09100000000001,0,0,1,17.07,0.32,CC=CC=O
+tetramethylurea,-0.495,1,116.16399999999999,0,0,0,23.550000000000004,0.94,CN(C)C(=O)N(C)C 
+salicylanilide,-3.782,1,213.23600000000002,2,2,2,49.33,-3.59,c1ccccc1NC(=O)c2c(O)cccc2
+Sulfallate,-3.2539999999999996,1,223.79399999999998,0,0,4,3.24,-3.39,CCN(CC)C(=S)SCC(Cl)=C
+Chloroethane,-1.165,1,64.515,0,0,0,0.0,-1.06,ClCC
+Mefluidide,-3.165,1,310.297,2,1,3,75.27000000000001,-3.24,CC(=O)Nc1cc(NS(=O)(=O)C(F)(F)F)c(C)cc1C
+Piperine,-3.659,1,285.343,0,3,3,38.77,-3.46,O=C(C=CC=Cc2ccc1OCOc1c2)N3CCCCC3
+cis-2-Pentene,-2.076,1,70.135,0,0,1,0.0,-2.54,CC/C=C\C
+Cyclooctyl-5-spirobarbituric acid,-2.2840000000000003,1,224.25999999999996,2,2,0,75.27,-2.9819999999999998,O=C2NC(=O)C1(CCCCCCC1)C(=O)N2
+butacarb,-4.6419999999999995,1,263.381,1,1,1,38.33,-4.24,c1(C(C)(C)C)cc(C(C)(C)C)cc(OC(=O)NC)c1
+Eriodictyol,-3.1519999999999997,1,288.255,4,3,1,107.22000000000001,-3.62,Oc2cc(O)c1C(=O)CC(Oc1c2)c3ccc(O)c(O)c3
+Benzophenone,-3.612,1,182.222,0,2,2,17.07,-3.12,O=C(c1ccccc1)c2ccccc2
+Eicosane,-7.5760000000000005,1,282.5559999999999,0,0,17,0.0,-8.172,CCCCCCCCCCCCCCCCCCCC
+hydrazobenzene,-3.492,2,184.242,2,2,3,24.06,-2.92,N(Nc1ccccc1)c2ccccc2 
+2-Ethyl-1-butanol,-1.381,1,102.17699999999999,1,0,3,20.23,-1.17,CCC(CC)CO
+4-hydroxypyridine,-1.655,1,95.10099999999998,1,1,0,33.120000000000005,1.02,Oc1ccncc1
+"cis 1,2-Dichloroethylene",-1.561,1,96.94400000000002,0,0,0,0.0,-1.3,Cl\C=C/Cl
+Methylcyclopentane,-2.452,1,84.162,0,1,0,0.0,-3.3,CC1CCCC1
+4-Methyl-2-pentanol,-1.308,1,102.17699999999998,1,0,2,20.23,-0.8,CC(C)CC(C)O
+RTI 11,-3.125,1,254.28900000000002,1,3,0,55.56,-3.928,O2c1ccc(N)cc1N(C)C(=O)c3cc(C)ccc23 
+Triadimefon,-4.132,1,293.754,0,2,4,57.010000000000005,-3.61,CC(C)(C)C(=O)C(Oc1ccc(Cl)cc1)n2cncn2
+Isocarboxazid,-2.251,1,231.25500000000002,2,2,4,67.16,-2.461,Cc1cc(no1)C(=O)NNCc2ccccc2
+Dichlorophen,-4.9239999999999995,1,269.127,2,2,2,40.46,-3.9530000000000003,Oc1ccc(Cl)cc1Cc2cc(Cl)ccc2O
+Anthraquinone,-3.34,1,208.21599999999998,0,3,0,34.14,-5.19,O=C1c2ccccc2C(=O)c3ccccc13
+Oxycarboxin,-2.169,1,267.306,1,2,2,72.47,-2.281,CC1=C(C(=O)Nc2ccccc2)S(=O)(=O)CCO1
+parabanic acid,1.091,1,114.05999999999999,2,1,0,75.27,-0.4,O=C1NC(=O)C(=O)N1 
+Abate,-6.678,1,466.47900000000016,0,2,10,55.38000000000001,-6.237,COP(=S)(OC)Oc1ccc(Sc2ccc(OP(=S)(OC)OC)cc2)cc1
+Chlorthalidone,-2.5639999999999996,1,338.7720000000001,3,3,2,109.49000000000001,-3.451,NS(=O)(=O)c1cc(ccc1Cl)C2(O)NC(=O)c3ccccc23
+Isobutyl acetate,-1.463,1,116.15999999999998,0,0,2,26.3,-1.21,CC(C)COC(=O)C
+"2,2,3-Trimethylbutane",-2.9219999999999997,1,100.20499999999998,0,0,0,0.0,-4.36,CC(C)C(C)(C)C
+"2,3,3',4,4'6-PCB",-7.746,1,395.3270000000001,0,2,1,0.0,-7.66,Clc1ccc(c(Cl)c1Cl)c2c(Cl)cc(Cl)c(Cl)c2Cl 
+Phthalonitrile,-1.7169999999999999,1,128.13399999999996,0,1,0,47.58,-2.38,N#Cc1ccccc1C#N
+m-Nitrotoluene,-2.64,1,137.138,0,1,1,43.14,-2.44,Cc1cccc(c1)N(=O)=O
+halothane,-2.608,1,197.381,0,0,0,0.0,-1.71,FC(F)(F)C(Cl)Br 
+Oxamyl,-0.9079999999999999,1,219.266,1,0,1,70.99999999999999,0.106,CNC(=O)ON=C(SC)C(=O)N(C)C
+Thiometon,-3.323,1,246.35899999999998,0,0,7,18.46,-3.091,CCSCCSP(=S)(OC)OC
+2-Methylbutane,-2.245,1,72.151,0,0,1,0.0,-3.18,CCC(C)C

mol_moe/data/moleculenet/esol/valid.csv

@@ -0,0 +1,114 @@
+Compound ID,ESOL predicted log solubility in mols per litre,Minimum Degree,Molecular Weight,Number of H-Bond Donors,Number of Rings,Number of Rotatable Bonds,Polar Surface Area,measured log solubility in mols per litre,smiles
+Benzonitrile,-2.03,1,103.12399999999997,0,1,0,23.79,-1.0,N#Cc1ccccc1
+Butethal,-1.974,1,212.249,2,1,4,75.27000000000001,-1.661,CCCCC1(CC)C(=O)NC(=O)NC1=O
+cyclobarbital,-2.421,1,236.27099999999993,2,2,2,75.27000000000001,-2.17,CCC1(C(=O)NC(=O)NC1=O)C2=CCCCC2 
+"1,4-Dimethylnaphthalene ",-4.147,1,156.228,0,2,0,0.0,-4.14,Cc1ccc(C)c2ccccc12
+"Atovaquone(0,430mg/ml) - neutral",-6.269,1,366.84400000000016,1,4,2,54.37,-5.931,OC4=C(C1CCC(CC1)c2ccc(Cl)cc2)C(=O)c3ccccc3C4=O
+Camphor,-2.158,1,152.237,0,2,0,17.07,-1.96,CC1(C)C2CCC1(C)C(=O)C2
+Menthone,-2.516,1,154.253,0,1,1,17.07,-2.35,CC(C)C1CCC(C)CC1=O
+Isopropylbenzene ,-3.265,1,120.19499999999995,0,1,1,0.0,-3.27,CC(C)c1ccccc1
+Ioxynil,-4.615,1,370.91499999999996,1,1,0,44.019999999999996,-3.61,Oc1c(I)cc(C#N)cc1I
+theobromine,-1.05,1,180.16699999999997,1,2,0,72.68,-2.523,Cn1cnc2n(C)c(=O)[nH]c(=O)c12 
+Glyceryl triacetate,-1.285,1,218.20499999999998,0,0,5,78.9,-0.6,CC(=O)OCC(COC(=O)C)OC(=O)C
+"3,4-Dimethylpyridine",-2.0669999999999997,1,107.15599999999999,0,1,0,12.89,0.36,Cc1ccncc1C
+Iodomethane,-1.646,1,141.939,0,0,0,0.0,-1.0,CI
+Trichloronate,-5.225,1,333.60400000000004,0,1,5,18.46,-5.752000000000001,CCOP(=S)(CC)Oc1cc(Cl)c(Cl)cc1Cl
+Pentamethylbenzene,-3.9930000000000003,1,148.249,0,1,0,0.0,-4.0,Cc1cc(C)c(C)c(C)c1C
+6-methoxypteridine,-1.589,1,162.15200000000002,0,2,1,60.790000000000006,-1.139,COc2cnc1ncncc1n2
+4-Methylbiphenyl,-4.4239999999999995,1,168.239,0,2,1,0.0,-4.62,Cc1ccc(cc1)c2ccccc2
+2-Decanone,-2.617,1,156.269,0,0,7,17.07,-3.3,CCCCCCCCC(=O)C
+"1,2-Benzenediol",-1.635,1,110.11199999999998,2,1,0,40.46,0.62,Oc1ccccc1O
+Dialifor,-5.026,1,393.85400000000016,0,2,8,55.84,-6.34,CCOP(=S)(OCC)SC(CCl)N1C(=O)c2ccccc2C1=O
+Monuron,-2.6710000000000003,1,198.653,1,1,1,32.34,-2.89,CN(C)C(=O)Nc1ccc(Cl)cc1
+"1,1,2,2-Tetrachloroethane",-2.549,1,167.85,0,0,1,0.0,-1.74,ClC(Cl)C(Cl)Cl
+Dimecron,-2.426,1,299.6909999999999,0,0,8,65.07000000000001,0.523,CCN(CC)C(=O)C(=CCOP(=O)(OC)OC)Cl
+hexacosane,-9.702,1,366.7180000000002,0,0,23,0.0,-8.334,CCCCCCCCCCCCCCCCCCCCCCCCCC
+Cyclooctanol,-2.14,1,128.215,1,1,0,20.23,-1.29,OC1CCCCCCC1
+"2,2',3,4,5-PCB",-6.709,1,326.437,0,2,1,0.0,-7.21,Clc1cc(Cl)c(cc1Cl)c2cccc(Cl)c2Cl 
+Benzo(b)fluoranthene,-6.007000000000001,2,252.31599999999997,0,5,0,0.0,-8.23,c1ccc2c(c1)c3cccc4c3c2cc5ccccc54
+Carbanilide,-3.611,1,212.25199999999998,2,2,2,41.13,-3.15,O=C(Nc1ccccc1)Nc2ccccc2
+"1,4-Dinitrobenzene",-2.281,1,168.10799999999995,0,1,2,86.28,-3.39,O=N(=O)c1ccc(cc1)N(=O)=O
+Cyclohexene,-2.16,2,82.146,0,1,0,0.0,-2.59,C1CCC=CC1
+Hydrocortisone ,-3.159,1,362.4660000000002,3,4,2,94.83,-3.09,CC12CC(O)C3C(CCC4=CC(=O)CCC34C)C2CCC1(O)C(=O)CO
+Amitraz,-5.5329999999999995,1,293.41400000000004,0,2,4,27.96,-5.47,CN(C=Nc1ccc(C)cc1C)C=Nc2ccc(C)cc2C
+metharbital,-1.6580000000000001,1,198.22199999999998,1,1,2,66.48,-2.23,CCC1(CC)C(=O)NC(=O)N(C)C1=O 
+"2,6-Dinitrotoluene",-2.553,1,182.135,0,1,2,86.28,-3.0,Cc1c(cccc1N(=O)=O)N(=O)=O
+Progesterone,-4.17,1,314.46900000000005,0,4,1,34.14,-4.42,CC(=O)C1CCC2C3CCC4=CC(=O)CCC4(C)C3CCC12C
+"1,2,4-tribromobenzene",-5.144,1,314.802,0,1,0,0.0,-4.5,c1(Br)c(Br)cc(Br)cc1
+p-Nitroaniline,-1.936,1,138.126,1,1,1,69.16,-2.37,Nc1ccc(cc1)N(=O)=O
+Lactose,1.071,1,342.297,8,2,4,189.52999999999997,-0.244,OCC1OC(OC2C(O)C(O)C(O)OC2CO)C(O)C(O)C1O
+Glafenine,-5.052,1,372.80800000000016,3,3,6,91.67999999999999,-4.571000000000001,OCC(O)COC(=O)c1ccccc1Nc2ccnc3cc(Cl)ccc23
+DDD,-6.007999999999999,1,320.04600000000005,0,2,3,0.0,-7.2,ClC(Cl)C(c1ccc(Cl)cc1)c2ccc(Cl)cc2
+t-Pentylbenzene,-3.867,1,148.249,0,1,1,0.0,-4.15,CC(C)(C)Cc1ccccc1
+o-Chloroiodobenzene,-4.3839999999999995,1,238.45499999999998,0,1,0,0.0,-3.54,Clc1ccccc1I
+3-Methyl-2-butanol,-0.9540000000000001,1,88.14999999999999,1,0,1,20.23,-0.18,CC(C)C(C)O
+Iodoethane,-2.066,1,155.966,0,0,0,0.0,-1.6,CCI
+"1,3,5-Trinitrobenzene",-2.324,1,213.10499999999996,0,1,3,129.42000000000002,-2.89,O=N(=O)c1cc(cc(c1)N(=O)=O)N(=O)=O
+1-aminoacridine,-3.542,1,194.23700000000002,1,3,0,38.91,-4.22,Nc2cccc3nc1ccccc1cc23 
+Benzo(k)fluoranthene,-6.007000000000001,2,252.31599999999997,0,5,0,0.0,-8.49,c1ccc2cc3c4cccc5cccc(c3cc2c1)c45
+"Sparsomycin (3,8mg/ml)",-1.57,1,361.4450000000001,4,1,8,132.11999999999998,-1.9809999999999999,CSCS(=O)CC(CO)NC(=O)C=Cc1c(C)[nH]c(=O)[nH]c1=O
+1-Iodopropane,-2.4859999999999998,1,169.993,0,0,1,0.0,-2.29,CCCI
+1-Propanol,-0.33399999999999996,1,60.096,1,0,1,20.23,0.62,CCCO
+"Hexachloro-1,3-butadiene",-4.546,1,260.762,0,0,1,0.0,-4.92,ClC(=C(Cl)C(=C(Cl)Cl)Cl)Cl
+Bromodichloromethane,-2.176,1,163.82899999999998,0,0,0,0.0,-1.54,BrC(Cl)Cl
+adrenosterone,-2.99,1,300.3980000000001,0,4,0,51.21,-3.48,CC34CC(=O)C1C(CCC2=CC(=O)CCC12C)C3CCC4(=O) 
+2-Ethylnaphthalene,-4.1,1,156.22799999999998,0,2,1,0.0,-4.29,CCc1ccc2ccccc2c1
+"2,3,4,5,6-PCB",-6.785,1,326.437,0,2,1,0.0,-7.92,Clc2c(Cl)c(Cl)c(c1ccccc1)c(Cl)c2Cl 
+Fluridone,-4.249,1,329.32099999999997,0,3,2,22.0,-4.445,Cn2cc(c1ccccc1)c(=O)c(c2)c3cccc(c3)C(F)(F)F
+"1,2-Propylene oxide",-0.358,1,58.08,0,1,0,12.53,-0.59,CC1CO1
+Ethyl butyrate,-2.254,1,144.21399999999997,0,0,5,26.3,-1.28,CCCCCOC(=O)CC
+5-Allyl-5-isopropylbarbital,-1.706,1,210.23299999999998,2,1,3,75.27000000000001,-1.7080000000000002,O=C1NC(=O)NC(=O)C1(C(C)C)CC=C
+"2,2',3,4,5,5'-PCB",-7.343,1,360.88200000000006,0,2,1,0.0,-7.68,Clc1ccc(Cl)c(c1)c2cc(Cl)c(Cl)c(Cl)c2Cl
+Propionitrile,-0.26899999999999996,1,55.07999999999999,0,0,0,23.79,0.28,CCC#N
+7-methylpteridine,-1.24,1,146.153,0,2,0,51.56,-0.8540000000000001,Cc2cnc1cncnc1n2
+"N,N-Dimethylacetamide",0.12300000000000001,1,87.12199999999999,0,0,0,20.310000000000002,1.11,CN(C)C(=O)C
+Anisole,-2.3680000000000003,1,108.13999999999997,0,1,1,9.23,-1.85,COc1ccccc1
+chloropropylate,-5.093,1,339.21800000000013,1,2,4,46.53,-4.53,c1ccc(Cl)cc1C(c2ccc(Cl)cc2)(O)C(=O)OC(C)C
+Furane,-1.837,2,68.07499999999999,0,1,0,13.14,-0.82,c1ccoc1
+3-Butanoyloxymethylphenytoin,-3.469,1,352.39000000000004,1,3,6,75.71,-5.071000000000001,O=C1N(COC(=O)CCC)C(=O)C(N1)(c2ccccc2)c3ccccc3
+Chloroethylene,-1.188,1,62.499,0,0,0,0.0,-1.75,ClC=C
+Tetrabromomethane,-4.063,1,331.62699999999995,0,0,0,0.0,-3.14,BrC(Br)(Br)Br
+2-Chlorophenol,-2.553,1,128.558,1,1,0,20.23,-1.06,Oc1ccccc1Cl
+Terbacil,-3.033,1,216.66799999999998,1,1,0,54.86,-2.484,Cc1[nH]c(=O)n(c(=O)c1Cl)C(C)(C)C
+Cyhalothrin,-6.905,1,449.8560000000001,0,3,6,59.32000000000001,-8.176,CC1(C)C(C=C(Cl)C(F)(F)F)C1C(=O)OC(C#N)c2cccc(Oc3ccccc3)c2
+Apazone,-2.9,1,300.3620000000001,0,3,2,56.220000000000006,-3.5380000000000003,CCCC1C(=O)N3N(C1=O)c2cc(C)ccc2N=C3N(C)C 
+borneol,-2.423,1,154.253,1,2,0,20.23,-2.32,CC1(C)C2CCC1(C)C(O)C2
+thiouracil,-0.992,1,128.15599999999998,2,1,0,45.75,-2.273,Sc1nccc(=O)[nH]1 
+Acetophenone,-2.0780000000000003,1,120.15099999999995,0,1,1,17.07,-1.28,CC(=O)c1ccccc1
+"2,3-Dimethylpentane",-2.938,1,100.20499999999998,0,0,2,0.0,-4.28,CCC(C)C(C)C
+Coumaphos,-5.04,1,362.77100000000013,0,2,6,57.9,-5.382000000000001,CCOP(=S)(OCC)Oc2ccc1oc(=O)c(Cl)c(C)c1c2
+"1,3-Dichlorobenzene",-3.5580000000000003,1,147.004,0,1,0,0.0,-3.04,Clc1cccc(Cl)c1
+thioanisole,-2.87,1,124.208,0,1,1,0.0,-2.39,c1ccccc1SC
+Vinclozolin,-4.377,1,286.11400000000003,0,2,2,46.61,-4.925,CC1(OC(=O)N(C1=O)c2cc(Cl)cc(Cl)c2)C=C
+"2,2',4,4',6,6'-PCB",-7.178999999999999,1,360.88200000000006,0,2,1,0.0,-8.71,Clc1cc(Cl)c(c(Cl)c1)c2c(Cl)cc(Cl)cc2Cl 
+"1,4-Pentadiene ",-1.758,1,68.119,0,0,2,0.0,-2.09,C=CCC=C
+DNOC,-2.818,1,198.134,1,1,2,106.51000000000002,-1.456,Cc1cc(cc(N(=O)=O)c1O)N(=O)=O
+2-Phenoxyethanol,-1.761,1,138.16599999999997,1,1,3,29.46,-0.7,OCCOc1ccccc1
+Flumetralin,-6.584,1,421.7340000000001,0,2,6,89.51999999999998,-6.78,CCN(Cc1c(F)cccc1Cl)c2c(cc(cc2N(=O)=O)C(F)(F)F)N(=O)=O
+Ethyl propionate,-1.1909999999999998,1,102.133,0,0,2,26.3,-0.66,CCOC(=O)CC
+p-Hydroxyacetanilide,-1.495,1,151.165,2,1,1,49.33,-1.03,CC(=O)Nc1ccc(O)cc1
+1-Dodecanol,-3.523,1,186.33899999999997,1,0,10,20.23,-4.8,CCCCCCCCCCCCO
+2-Methyl-2-pentanol,-1.308,1,102.17699999999998,1,0,2,20.23,-0.49,CCCC(C)(C)O
+"1,5-Hexadiene ",-2.112,1,82.14599999999999,0,0,3,0.0,-2.68,C=CCCC=C
+1-Hexene,-2.364,1,84.16199999999999,0,0,3,0.0,-3.23,CCCCC=C
+2-Nonanone,-2.263,1,142.242,0,0,6,17.07,-2.58,CCCCCCCC(=O)C
+Chloropham,-3.5439999999999996,1,213.66400000000002,1,1,2,38.33,-3.38,CC(C)OC(=O)Nc1cccc(Cl)c1
+Disulfoton,-3.975,1,274.413,0,0,9,18.46,-4.23,CCOP(=S)(OCC)SCCSCC
+diisooctyl phthalate,-7.117000000000001,1,390.5640000000002,0,1,14,52.60000000000001,-6.6370000000000005,c1(C(=O)OCCCCCC(C)(C))c(C(=O)OCCCCCC(C)(C))cccc1
+Hexadecane,-6.159,1,226.44799999999992,0,0,13,0.0,-8.4,CCCCCCCCCCCCCCCC
+"1,4-Difluorobenzene",-2.636,1,114.094,0,1,0,0.0,-1.97,Fc1ccc(F)cc1
+1-Bromooctane,-3.721,1,193.128,0,0,6,0.0,-5.06,CCCCCCCCBr
+4-Methylpentanol,-1.381,1,102.17699999999999,1,0,3,20.23,-1.14,CC(C)CCCO
+Norethisterone,-2.6689999999999996,1,314.42500000000007,2,4,0,57.53,-4.57,CC34CCC1C(CCC2=CC(=O)CCC12O)C3CCC4(O)C#C
+2-Hexanone,-1.2,1,100.16099999999999,0,0,3,17.07,-0.8,CCCCC(=O)C
+Quinonamid,-3.988,1,332.57000000000005,1,2,3,63.24,-5.03,ClC(Cl)CC(=O)NC2=C(Cl)C(=O)c1ccccc1C2=O
+3-Ethyl-3-pentanol,-1.663,1,116.204,1,0,3,20.23,-0.85,CCC(O)(CC)CC
+oryzalin,-3.784,1,346.3650000000001,1,1,8,149.67999999999998,-5.16,CCCN(CCC)c1c(cc(cc1N(=O)=O)S(N)(=O)=O)N(=O)=O
+3-Heptanol ,-1.6780000000000002,1,116.20399999999998,1,0,4,20.23,-1.47,CCCCC(O)CC
+Thiram,-2.444,1,240.44400000000002,0,0,0,6.48,-3.9,CN(C)C(=S)SSC(=S)N(C)C 
+"1,2,4,5-Tetramethylbenzene",-3.6639999999999997,1,134.22199999999998,0,1,0,0.0,-4.59,Cc1cc(C)c(C)cc1C
+Ditalimfos,-3.992,1,299.28800000000007,0,2,5,55.84,-3.35,CCOP(=S)(OCC)N2C(=O)c1ccccc1C2=O
+"2,2-Dimethylpropanol",-1.011,1,88.14999999999999,1,0,0,20.23,-0.4,CC(C)(C)CO
+Propylene,-1.235,1,42.080999999999996,0,0,0,0.0,-1.08,CC=C
+Desmedipham,-4.1819999999999995,1,300.314,2,2,4,76.66,-4.632,CCOC(=O)Nc2cccc(OC(=O)Nc1ccccc1)c2 
+Butylbenzene,-3.585,1,134.22199999999998,0,1,3,0.0,-4.06,CCCCc1ccccc1

mol_moe/data/moleculenet/freesolv/test.csv

@@ -0,0 +1,66 @@
+iupac,smiles,expt,calc
+2-methylpentan-2-ol,CCCC(C)(C)O,-3.92,-2.779
+ethion,CCOP(=S)(OCC)SCSP(=S)(OCC)OCC,-6.1,-10.644
+"penta-1,4-diene",C=CCC=C,0.93,2.357
+2-hydroxybenzaldehyde,c1ccc(c(c1)C=O)O,-4.68,-8.809
+simazine,CCNc1nc(nc(n1)Cl)NCC,-10.22,-10.914
+"1,1-difluoroethane",CC(F)F,-0.11,0.226
+ethanamine,CCN,-4.5,-3.156
+3-methoxyphenol,COc1cccc(c1)O,-7.66,-6.969
+imidazole,c1cnc[nH]1,-9.63,-7.972
+3-hydroxybenzonitrile,c1cc(cc(c1)O)C#N,-9.65,-7.739
+4-chlorophenol,c1cc(ccc1O)Cl,-7.03,-5.373
+[(2S)-butan-2-yl] nitrate,CC[C@H](C)O[N+](=O)[O-],-1.82,-1.864
+"1,4-dichloro-2-phenyl-benzene",c1ccc(cc1)c2cc(ccc2Cl)Cl,-2.46,-1.903
+cyclopropane,C1CC1,0.75,2.485
+propyl formate,CCCOC=O,-2.48,-3.699
+"1,4-dimethylpiperazine",CN1CCN(CC1)C,-7.58,-7.874
+"N,N-diethylethanamine",CCN(CC)CC,-3.22,-1.955
+"3,4-dimethylpyridine",Cc1ccncc1C,-5.22,-3.201
+2-methoxypropane,CC(C)OC,-2.01,-0.657
+"1,2,3,4,6,7,8,9-octachlorodibenzo-p-dioxin",c12c(c(c(c(c1Cl)Cl)Cl)Cl)Oc3c(c(c(c(c3Cl)Cl)Cl)Cl)O2,-4.53,-1.147
+4-chlorophenyl)sulfanylmethylsulfanyl-diethoxy-thioxo-$l^{5}-phosphane,CCOP(=S)(OCC)SCSc1ccc(cc1)Cl,-6.5,-7.024
+"3-(dimethoxyphosphinothioylsulfanylmethyl)-1,2,3-benzotriazin-4-one",COP(=S)(OC)SCn1c(=O)c2ccccc2nn1,-10.03,-14.106
+hexan-1-ol,CCCCCCO,-4.4,-3.0
+naphthalene,c1ccc2ccccc2c1,-2.4,-3.213
+N-isopropylpropan-2-amine,CC(C)NC(C)C,-3.22,-1.985
+heptan-1-amine,CCCCCCCN,-3.79,-2.554
+"(1R)-2,2,2-trichloro-1-dimethoxyphosphoryl-ethanol",COP(=O)([C@H](C(Cl)(Cl)Cl)O)OC,-12.74,-13.424
+butane-1-thiol,CCCCS,-0.99,-0.174
+"2,6-dichlorosyringaldehyde",COc1c(c(c(c(c1Cl)C=O)Cl)OC)O,-8.68,-9.846
+benzyl chloride,c1ccc(cc1)CCl,-1.93,-1.742
+methylcyclohexane,CC1CCCCC1,1.7,1.679
+alachlor,CCc1cccc(c1N(COC)C(=O)CCl)CC,-8.21,-6.851
+iodobenzene,c1ccc(cc1)I,-1.74,-1.057
+chlorobenzene,c1ccc(cc1)Cl,-1.12,-0.475
+heptanal,CCCCCCC=O,-2.67,-2.704
+2-nitroaniline,c1ccc(c(c1)N)[N+](=O)[O-],-7.37,-7.66
+methylsulfinylmethane,CS(=O)C,-9.280000000000001,-8.243
+"1,1,2,2-tetrachloroethane",C(C(Cl)Cl)(Cl)Cl,-2.37,-0.534
+1-bromoheptane,CCCCCCCBr,0.34,1.223
+1-cyclopropylethanone,CC(=O)C1CC1,-4.61,-3.043
+pyrrole,c1cc[nH]c1,-4.78,-4.014
+diflunisal,c1cc(c(cc1c2ccc(cc2F)F)C(=O)O)O,-9.4,-6.613
+"1,4-dimethylcyclohexane",CC1CCC(CC1)C,2.11,1.918
+"(2R,5R)-2-methyl-5-(1-methylethenyl)-cyclohexanone",C[C@@H]1CC[C@H](CC1=O)C(=C)C,-3.75,-3.344
+ketoprofen,C[C@@H](c1cccc(c1)C(=O)c2ccccc2)C(=O)O,-10.78,-17.242
+2-methylpent-1-ene,CCCC(=C)C,1.47,2.486
+"1,4-dimethylnaphthalene",Cc1ccc(c2c1cccc2)C,-2.82,-3.081
+methyldisulfanylmethane,CSSC,-1.83,-0.093
+propyl acetate,CCCOC(=O)C,-2.79,-3.486
+ethyldisulfanylethane,CCSSCC,-1.64,-0.979
+pentan-2-one,CCCC(=O)C,-3.52,-3.166
+diethoxy-(ethylsulfanylmethylsulfanyl)-thioxo-$l^{5}-phosphane,CCOP(=S)(OCC)SCSCC,-4.37,-6.427
+1-(4-pyridyl)ethanone,CC(=O)c1ccncc1,-7.62,-7.566
+2-methylprop-1-ene,CC(=C)C,1.16,2.327
+1-butoxybutane,CCCCOCCCC,-0.83,0.139
+3-methylhexane,CCC[C@H](C)CC,2.71,2.81
+naproxen,C[C@@H](c1ccc2cc(ccc2c1)OC)C(=O)O,-10.21,-12.199
+methanethiol,CS,-1.2,-0.273
+chloroethane,CCCl,-0.63,0.775
+methyl propanoate,CCC(=O)OC,-2.93,-3.652
+oct-1-ene,CCCCCCC=C,1.92,2.895
+1-propoxypropane,CCCOCCC,-1.16,-0.004
+isobutylbenzene,CC(C)Cc1ccccc1,0.16,-0.257
+2-methoxyphenol,COc1ccccc1O,-5.94,-4.746
+1-chloroheptane,CCCCCCCCl,0.29,1.467

mol_moe/data/moleculenet/freesolv/train.csv

@@ -0,0 +1,513 @@
+iupac,smiles,expt,calc
+"4-methoxy-N,N-dimethyl-benzamide",CN(C)C(=O)c1ccc(cc1)OC,-11.01,-9.625
+methanesulfonyl chloride,CS(=O)(=O)Cl,-4.87,-6.219
+2-ethylpyrazine,CCc1cnccn1,-5.45,-5.809
+heptan-1-ol,CCCCCCCO,-4.21,-2.917
+"3,5-dimethylphenol",Cc1cc(cc(c1)O)C,-6.27,-5.444
+"2,3-dimethylbutane",CC(C)C(C)C,2.34,2.468
+"1,2-dimethylcyclohexane",C[C@@H]1CCCC[C@@H]1C,1.58,1.685
+butan-2-ol,CC[C@H](C)O,-4.62,-3.145
+dibromomethane,C(Br)Br,-1.96,-0.405
+2-ethylpyridine,CCc1ccccn1,-4.33,-3.31
+ethyl pentanoate,CCCCC(=O)OCC,-2.49,-3.11
+benzenethiol,c1ccc(cc1)S,-2.55,-1.501
+indane,c1ccc2c(c1)CCC2,-1.46,-1.752
+ethoxybenzene,CCOc1ccccc1,-2.22,-2.254
+4-bromophenol,c1cc(ccc1O)Br,-5.85,-5.833
+"2,2-dimethylpentane",CCCC(C)(C)C,2.88,2.686
+2-acetoxyethyl acetate,CC(=O)OCCOC(=O)C,-6.34,-8.292
+methyl cyclopropanecarboxylate,COC(=O)C1CC1,-4.1,-3.604
+benzonitrile,c1ccc(cc1)C#N,-4.1,-3.238
+pentanenitrile,CCCCC#N,-3.52,-2.147
+2-methylpropan-2-ol,CC(C)(C)O,-4.47,-3.288
+"2,4-dimethylpentan-3-one",CC(C)C(=O)C(C)C,-2.74,-2.629
+propanal,CCC=O,-3.43,-3.148
+"N,N-dimethylformamide",CN(C)C=O,-7.81,-6.932
+p-xylene,Cc1ccc(cc1)C,-0.8,-0.658
+"2-(2,3-dimethylphenyl)aminobenzoic acid",Cc1cccc(c1C)Nc2ccccc2C(=O)O,-6.78,-7.665
+"N,N-dimethylbenzamide",CN(C)C(=O)c1ccccc1,-9.29,-8.113
+N-ethylethanamine,CCNCC,-4.07,-2.986
+4-tert-butylphenol,CC(C)(C)c1ccc(cc1)O,-5.91,-5.543
+isopentyl formate,CC(C)CCOC=O,-2.13,-3.414
+decan-1-ol,CCCCCCCCCCO,-3.64,-2.446
+ethyl propanoate,CCC(=O)OCC,-2.68,-3.221
+nonane,CCCCCCCCC,3.13,3.221
+N-methylacetamide,CC(=O)NC,-10.0,-8.276
+non-1-ene,CCCCCCCC=C,2.06,2.995
+naphthalen-2-ol,c1ccc2cc(ccc2c1)O,-8.11,-7.849
+"1,2,4-trichlorobenzene",c1cc(c(cc1Cl)Cl)Cl,-1.12,-0.117
+"(2R,3R,4R,5R)-Hexan-1,2,3,4,5,6-hexol",C([C@H]([C@H]([C@@H]([C@@H](CO)O)O)O)O)O,-23.62,-18.162
+methyl butanoate,CCCC(=O)OC,-2.83,-3.552
+azetidine,C1CNC1,-5.56,-3.861
+N-propylpropan-1-amine,CCCNCCC,-3.65,-2.233
+aniline,c1ccc(cc1)N,-5.49,-5.543
+tetrafluoromethane,C(F)(F)(F)F,3.12,2.489
+2-methylbutan-1-ol,CC[C@@H](C)CO,-4.42,-2.995
+2-iodophenol,c1ccc(c(c1)O)I,-6.2,-3.221
+"2,6-dimethoxyphenol",COc1cccc(c1O)OC,-6.96,-7.393
+but-1-yne,CCC#C,-0.16,0.284
+trifluoromethylbenzene,c1ccc(cc1)C(F)(F)F,-0.25,-0.57
+"2,3-dichlorodibenzo-p-dioxin",c1ccc2c(c1)Oc3cc(c(cc3O2)Cl)Cl,-3.56,-3.59
+octan-1-amine,CCCCCCCCN,-3.65,-2.589
+ammonia,N,-4.29,-4.018
+"1,2-bis(trifluoromethyl)benzene",c1ccc(c(c1)C(F)(F)F)C(F)(F)F,1.07,-1.441
+methyl paraben,COC(=O)c1ccc(cc1)O,-9.51,-9.785
+pentylbenzene,CCCCCc1ccccc1,-0.23,-0.094
+5-Amino-4-chloro-2-phenylpyridazin-3(2H)-one,c1ccc(cc1)n2c(=O)c(c(cn2)N)Cl,-16.43,-16.039
+butadiene,C=CC=C,0.56,1.955
+"N,N-dimethylmethanamine",CN(C)C,-3.2,-2.636
+hexanamide,CCCCCC(=O)N,-9.31,-8.103
+"1-(2-hydroxyethylamino)-9,10-anthraquinone",c1ccc2c(c1)C(=O)c3cccc(c3C2=O)NCCO,-14.21,-13.599
+2-(nitrooxy)ethan-1-ol,C(CO[N+](=O)[O-])O,-8.18,-6.676
+octan-2-one,CCCCCCC(=O)C,-2.88,-2.758
+1-methylpiperazine,CN1CCNCC1,-7.77,-8.173
+"9,10-dihydroanthracene",c1ccc2c(c1)Cc3ccccc3C2,-3.78,-4.304
+"1,1-dichloroethane",CC(Cl)Cl,-0.84,0.187
+acenaphthene,c1cc2cccc3c2c(c1)CC3,-3.15,-4.198
+1-bromooctane,CCCCCCCCBr,0.52,1.352
+5-bromouracil,c1c(c(=O)[nH]c(=O)[nH]1)Br,-18.17,-17.298
+n-butane,CCCC,2.1,2.588
+chloromethane,CCl,-0.55,0.764
+1-bromo-2-methyl-propane,CC(C)CBr,-0.03,0.756
+2-isopropylsulfanylpropane,CC(C)SC(C)C,-1.21,0.14
+heptane,CCCCCCC,2.67,2.925
+bromacil,CC[C@H](C)n1c(=O)c(c([nH]c1=O)C)Br,-9.73,-14.496
+diiodomethane,C(I)I,-2.49,-1.882
+"N,N-dipropyl(propylsulfanyl)formamide",CCCN(CCC)C(=O)SCCC,-4.13,-4.569
+nitromethane,C[N+](=O)[O-],-4.02,-2.075
+methoxyethane,CCOC,-2.1,-0.71
+"2-chloro-1,1,1-trimethoxy-ethane",COC(CCl)(OC)OC,-4.59,-3.638
+isobutane,CC(C)C,2.3,2.535
+3-methylbutanoic acid,CC(C)CC(=O)O,-6.09,-8.844
+"2-chloro-1-(2,4-dichlorophenyl)ethenyl diethyl phosphate",CCOP(=O)(OCC)O/C(=C/Cl)/c1ccc(cc1Cl)Cl,-7.07,-9.029
+1-chloropropane,CCCCl,-0.33,0.973
+1-propylsulfanylpropane,CCCSCCC,-1.28,0.64
+hexan-3-ol,CCC[C@H](CC)O,-4.06,-2.585
+acetonitrile,CC#N,-3.88,-2.789
+"N-methyl-N-(2,2,2-trifluoroethyl)aniline",CN(CC(F)(F)F)c1ccccc1,-1.92,-3.964
+"2-chloro-2-(difluoromethoxy)-1,1,1-trifluoro-ethane",[C@@H](C(F)(F)F)(OC(F)F)Cl,0.1,-1.156
+"hexa-1,5-diene",C=CCCC=C,1.01,2.487
+m-xylene,Cc1cccc(c1)C,-0.83,-0.697
+methyl acetate,CC(=O)OC,-3.13,-3.83
+trimethoxymethylbenzene,COC(c1ccccc1)(OC)OC,-4.04,-5.559
+ethyl benzoate,CCOC(=O)c1ccccc1,-3.64,-4.597
+propanethiol,CCCS,-1.1,-0.182
+heptan-2-one,CCCCCC(=O)C,-3.04,-2.945
+carbofuran,CC1(Cc2cccc(c2O1)OC(=O)NC)C,-9.61,-11.126
+benzyl bromide,c1ccc(cc1)CBr,-2.38,-1.853
+ethyl hexanoate,CCCCCC(=O)OCC,-2.23,-2.929
+4-methylmorpholine,CN1CCOCC1,-6.32,-5.774
+"1,2,4,5-tetrachloro-3-(3,4-dichlorophenyl)benzene",c1cc(c(cc1c2c(c(cc(c2Cl)Cl)Cl)Cl)Cl)Cl,-4.38,-0.705
+caffeine,Cn1cnc2c1c(=O)n(c(=O)n2C)C,-12.64,-17.621
+N-methylmethanamine,CNC,-4.29,-2.991
+"1,1,2,3,3,3-hexafluoroprop-1-ene",C(=C(F)F)(C(F)(F)F)F,2.93,2.305
+piperidine,C1CCNCC1,-5.11,-3.873
+phenanthrene,c1ccc2c(c1)ccc3c2cccc3,-3.88,-5.264
+iodomethane,CI,-0.89,-0.641
+"3,5-dichloro-2,6-dimethoxyphenol",COc1c(cc(c(c1O)OC)Cl)Cl,-6.44,-5.98
+"(E)-1,2-dichloroethylene",C(=C/Cl)\Cl,-0.78,1.024
+n-pentane,CCCCC,2.3,2.673
+butanenitrile,CCCC#N,-3.64,-2.287
+2-isobutylpyrazine,CC(C)Cc1cnccn1,-5.04,-5.495
+"1,2,3,4-tetrachloro-5-phenyl-benzene",c1ccc(cc1)c2cc(c(c(c2Cl)Cl)Cl)Cl,-3.48,-1.31
+"2,3-dimethylpentane",CC[C@@H](C)C(C)C,2.52,2.625
+4-methylpentan-2-ol,C[C@H](CC(C)C)O,-3.73,-2.907
+"1,2,3,4-tetrachloro-5-(3,4,5-trichlorophenyl)benzene",c1c(cc(c(c1Cl)Cl)Cl)c2cc(c(c(c2Cl)Cl)Cl)Cl,-3.17,-0.822
+"1,1-dichloroethylene",C=C(Cl)Cl,0.25,1.108
+2-methylpropan-1-ol,CC(C)CO,-4.5,-3.13
+propyl propanoate,CCCOC(=O)CC,-2.44,-2.453
+hexachloroethane,C(C(Cl)(Cl)Cl)(Cl)(Cl)Cl,-0.64,0.885
+methylsulfanylbenzene,CSc1ccccc1,-2.73,-1.325
+2-ethylphenol,CCc1ccccc1O,-5.66,-4.768
+2-chloro-2-methyl-propane,CC(C)(C)Cl,1.09,0.826
+isoprene,CC(=C)C=C,0.68,1.824
+1-isopropyl-4-methyl-benzene,Cc1ccc(cc1)C(C)C,-0.68,-0.456
+1-methylimidazole,Cn1ccnc1,-8.41,-6.282
+ethylene glycol,C(CO)O,-9.3,-7.266
+6-chlorouracil,c1c(=O)[nH]c(=O)[nH]c1Cl,-15.83,-15.128
+2-chlorodibenzo-p-dioxin,c1ccc2c(c1)Oc3ccc(cc3O2)Cl,-3.1,-4.054
+hexanoic acid,CCCCCC(=O)O,-6.21,-7.878
+"2,4-dimethylpyridine",Cc1ccnc(c1)C,-4.86,-3.282
+cyclohexene,C1CCC=CC1,0.14,1.175
+"1,2,3,4-tetrachloro-5-(3,4-dichlorophenyl)benzene",c1cc(c(cc1c2cc(c(c(c2Cl)Cl)Cl)Cl)Cl)Cl,-3.04,-1.083
+quinone,C1=CC(=O)C=CC1=O,-6.5,-6.96
+methyl 2-chloroacetate,COC(=O)CCl,-4.0,-3.816
+butanal,CCCC=O,-3.18,-3.044
+ethylbenzene,CCc1ccccc1,-0.79,-0.606
+"1,1,2-trichloroethylene",C(=C(Cl)Cl)Cl,-0.44,0.818
+cyanuric acid,c1(=O)[nH]c(=O)[nH]c(=O)[nH]1,-18.06,-21.762
+2-chloropyridine,c1ccnc(c1)Cl,-4.39,-3.873
+3-chloroprop-1-ene,C=CCCl,-0.57,0.944
+1-(p-tolyl)ethanone,Cc1ccc(cc1)C(=O)C,-4.7,-4.91
+formaldehyde,C=O,-2.75,-3.155
+1-pyrrolidin-1-ylethanone,CC(=O)N1CCCC1,-9.8,-7.831
+"1,1,1-trimethoxyethane",CC(OC)(OC)OC,-4.42,-3.7
+butylbenzene,CCCCc1ccccc1,-0.4,-0.227
+"N,N-dimethylaniline",CN(C)c1ccccc1,-3.45,-4.426
+"1,2,3,4,5-pentachloro-6-(2,3,4,5,6-pentachlorophenyl)benzene",c1(c(c(c(c(c1Cl)Cl)Cl)Cl)Cl)c2c(c(c(c(c2Cl)Cl)Cl)Cl)Cl,-2.98,0.76
+"1,1,2-trichloroethane",C(C(Cl)Cl)Cl,-1.99,-0.384
+N-methylaniline,CNc1ccccc1,-4.69,-5.719
+isopropyl acetate,CC(C)OC(=O)C,-2.64,-3.371
+benzene,c1ccccc1,-0.9,-0.806
+"1,2,3-trichlorobenzene",c1cc(c(c(c1)Cl)Cl)Cl,-1.24,-0.51
+"1,2,4-trichlorodibenzo-p-dioxin",c1ccc2c(c1)Oc3c(cc(c(c3O2)Cl)Cl)Cl,-4.05,-3.16
+"2,3-dimethylbuta-1,3-diene",CC(=C)C(=C)C,0.4,1.862
+hex-1-ene,CCCCC=C,1.58,2.628
+hydrogen sulfide,S,-0.7,-1.135
+"2-N-ethyl-6-(methylsulfanyl)-4-N-(propan-2-yl)-1,3,5-triazine-2,4-diamine",CCNc1nc(nc(n1)SC)NC(C)C,-7.65,-10.552
+butyl paraben,CCCCOC(=O)c1ccc(cc1)O,-8.72,-8.771
+hexyl acetate,CCCCCCOC(=O)C,-2.26,-2.219
+cyclopentanone,C1CCC(=O)C1,-4.7,-3.889
+pentanoic acid,CCCCC(=O)O,-6.16,-9.053
+bromoethane,CCBr,-0.74,0.487
+"2,6-dimethylnaphthalene",Cc1ccc2cc(ccc2c1)C,-2.63,-2.848
+1-chloro-2-phenyl-benzene,c1ccc(cc1)c2ccccc2Cl,-2.69,-2.508
+1-methylcyclohexene,CC1=CCCCC1,0.67,1.338
+hexyl nitrate,CCCCCCO[N+](=O)[O-],-1.66,-1.596
+bromoform,C(Br)(Br)Br,-2.13,-0.531
+4-ethylphenol,CCc1ccc(cc1)O,-6.13,-5.453
+2-propoxyethanol,CCCOCCO,-6.4,-3.94
+5-iodouracil,c1c(c(=O)[nH]c(=O)[nH]1)I,-18.72,-17.742
+butyric acid,CCCC(=O)O,-6.35,-9.434
+"1,1,1-trifluoro-2,2,2-trimethoxyethane",COC(C(F)(F)F)(OC)OC,-0.8,-2.319
+"(2S,3R,4S,5R)-oxane-2,3,4,5-tetrol",C1[C@H]([C@@H]([C@H]([C@H](O1)O)O)O)O,-20.52,-14.148
+bromo-trifluoro-methane,C(F)(F)(F)Br,1.79,1.564
+butan-1-ol,CCCCO,-4.72,-3.232
+fluorobenzene,c1ccc(cc1)F,-0.8,-0.041
+ethyl acetate,CCOC(=O)C,-2.94,-3.745
+isobutyl 2-methylpropanoate,CC(C)COC(=O)C(C)C,-1.69,-2.58
+heptachlor,C1=C[C@@H]([C@@H]2[C@H]1[C@@]3(C(=C([C@]2(C3(Cl)Cl)Cl)Cl)Cl)Cl)Cl,-2.55,-0.974
+pentan-3-one,CCC(=O)CC,-3.41,-3.05
+"methyl 2,2,2-trifluoroacetate",COC(=O)C(F)(F)F,-1.1,-1.353
+"1,2,3,4-tetrachloro-5-(2,3,4-trichlorophenyl)benzene",c1cc(c(c(c1c2cc(c(c(c2Cl)Cl)Cl)Cl)Cl)Cl)Cl,-4.4,-0.805
+acetylsalicylic acid,CC(=O)Oc1ccccc1C(=O)O,-9.94,-9.399
+"3,3-dimethylbutan-2-one",CC(=O)C(C)(C)C,-3.11,-3.234
+4-ethylpyridine,CCc1ccncc1,-4.73,-3.19
+"2,7-dichlorodibenzo-p-dioxin",c1cc2c(cc1Cl)Oc3ccc(cc3O2)Cl,-3.67,-3.321
+methylcyclopentane,CC1CCCC1,1.59,1.785
+2-methyltetrahydrofuran,C[C@H]1CCCO1,-3.3,-1.984
+naphthalen-1-yl N-methylcarbamate,CNC(=O)Oc1cccc2c1cccc2,-9.45,-10.436
+anthracene,c1ccc2cc3ccccc3cc2c1,-3.95,-5.187
+dichloromethane,C(Cl)Cl,-1.31,0.038
+"methyl 2,2-dimethylpropanoate",CC(C)(C)C(=O)OC,-2.4,-3.304
+trichloro(nitro)methane,C([N+](=O)[O-])(Cl)(Cl)Cl,-1.45,-0.379
+sulfolane,C1CC[S+2](C1)([O-])[O-],-8.61,-9.624
+"2,6-dimethylphenol",Cc1cccc(c1O)C,-5.26,-4.308
+"1,4-diamino-9,10-anthracenedione",c1ccc2c(c1)C(=O)c3c(ccc(c3C2=O)N)N,-11.85,-15.252
+nonan-2-one,CCCCCCCC(=O)C,-2.49,-2.563
+butan-1-amine,CCCCN,-4.24,-2.961
+ethyl butanoate,CCCC(=O)OCC,-2.49,-3.381
+4-methylaniline,Cc1ccc(cc1)N,-5.57,-5.494
+1-iodohexane,CCCCCCI,0.08,0.043
+"1,1,2-trichloro-1,2,2-trifluoro-ethane",C(C(F)(Cl)Cl)(F)(F)Cl,1.77,1.691
+trimethyl phosphate,COP(=O)(OC)OC,-8.7,-10.642
+"1,3-dichlorobenzene",c1cc(cc(c1)Cl)Cl,-0.98,-0.11
+"1,3-dimethylnaphthalene",Cc1cc(c2ccccc2c1)C,-2.47,-2.995
+chlorpyrifos,CCOP(=S)(OCC)Oc1c(cc(c(n1)Cl)Cl)Cl,-5.04,-9.625
+"2-chloro-1,1,1-trifluoro-ethane",C(C(F)(F)F)Cl,0.06,0.233
+ethylene,C=C,1.28,2.328
+1-iodopentane,CCCCCI,-0.14,-0.111
+trimethoxymethane,COC(OC)OC,-4.42,-4.625
+decane,CCCCCCCCCC,3.16,3.335
+"1,2-dinitroxypropane",C[C@@H](CO[N+](=O)[O-])O[N+](=O)[O-],-4.95,-5.646
+3-methyl-1H-indole,Cc1c[nH]c2c1cccc2,-5.88,-8.161
+cyclohexane,C1CCCCC1,1.23,1.503
+"(2E)-3,7-dimethylocta-2,6-dien-1-ol",CC(=CCC/C(=C/CO)/C)C,-4.45,-2.518
+cumene,CC(C)c1ccccc1,-0.3,-0.674
+"2,3,4-trimethylpentane",CC(C)C(C)C(C)C,2.56,2.674
+3-methylbutan-2-one,CC(C)C(=O)C,-3.24,-3.078
+N-butylbutan-1-amine,CCCCNCCCC,-3.24,-2.076
+"1,2,3,4-tetrachlorodibenzo-p-dioxin",c1ccc2c(c1)Oc3c(c(c(c(c3Cl)Cl)Cl)Cl)O2,-3.81,-2.775
+cyclohexanamine,C1CCC(CC1)N,-4.59,-3.953
+chloro-difluoro-methane,C(F)(F)Cl,-0.5,-0.067
+1-(3-pyridyl)ethanone,CC(=O)c1cccnc1,-8.26,-7.844
+prop-1-yne,CC#C,-0.48,0.065
+nonanal,CCCCCCCCC=O,-2.07,-2.336
+propionic acid,CCC(=O)O,-6.46,-9.088
+chloroform,C(Cl)(Cl)Cl,-1.08,0.285
+"1,2,3-trimethylbenzene",Cc1cccc(c1C)C,-1.21,-0.883
+methane,C,2.0,2.446
+pyridine,c1ccncc1,-4.69,-3.508
+"2,5-dimethyltetrahydrofuran",C[C@H]1CC[C@@H](O1)C,-2.92,-1.787
+4-methyl-2-methoxyphenol,Cc1ccc(c(c1)OC)O,-5.8,-4.547
+chlordane,C1[C@H]([C@@H]2[C@H]([C@H]1Cl)[C@]3(C(=C([C@@]2(C3(Cl)Cl)Cl)Cl)Cl)Cl)Cl,-3.44,-3.23
+toluene,Cc1ccccc1,-0.9,-0.79
+isobutyl formate,CC(C)COC=O,-2.22,-3.458
+ethyl paraben,CCOC(=O)c1ccc(cc1)O,-9.2,-9.535
+"1,2-diethoxyethane",CCOCCOCC,-3.54,-3.42
+pentyl propanoate,CCCCCOC(=O)CC,-2.11,-2.176
+4-propylphenol,CCCc1ccc(cc1)O,-5.21,-5.211
+2-methylbut-2-ene,CC=C(C)C,1.31,2.272
+"1,2-dichloroethane",C(CCl)Cl,-1.79,-0.363
+"3,3-dimethylpentane",CCC(C)(C)CC,2.56,2.593
+"2,6-dimethylpyridine",Cc1cccc(n1)C,-4.59,-3.443
+"2,2-dichloro-1,1-difluoro-1-methoxy-ethane",COC(C(Cl)Cl)(F)F,-1.12,-0.685
+2-ethoxyethyl acetate,CCOCCOC(=O)C,-5.31,-5.751
+pyridine-3-carbaldehyde,c1cc(cnc1)C=O,-7.1,-7.425
+2-methylbutan-2-ol,CCC(C)(C)O,-4.43,-2.933
+1-methylpyrrole,Cn1cccc1,-2.89,-2.374
+dimethoxymethane,COCOC,-2.93,-3.221
+pentan-3-ol,CCC(CC)O,-4.35,-2.786
+undecan-2-one,CCCCCCCCCC(=O)C,-2.15,-2.201
+1-bromo-2-chloro-ethane,C(CBr)Cl,-1.95,-0.8
+"3,5,5-trimethylcyclohex-2-en-1-one",CC1=CC(=O)CC(C1)(C)C,-5.18,-4.088
+iodoethane,CCI,-0.74,-0.609
+4-propylguaiacol,CCCc1ccc(c(c1)OC)O,-5.26,-4.127
+2-bromopropane,CC(C)Br,-0.48,0.448
+1-bromo-4-methyl-benzene,Cc1ccc(cc1)Br,-1.39,-0.894
+4-hydroxybenzonitrile,c1cc(ccc1C#N)O,-10.17,-8.39
+methylsulfonylmethane,CS(=O)(=O)C,-10.08,-10.559
+3-ethylphenol,CCc1cccc(c1)O,-6.25,-5.272
+"(1S,5R)-2-methyl-5-(1-methylethenyl)-2-cyclohexen-1-ol",CC1=CC[C@H](C[C@@H]1O)C(=C)C,-4.44,-3.257
+"1,4-dibromobenzene",c1cc(ccc1Br)Br,-2.3,-1.091
+dicamba,COc1c(ccc(c1C(=O)O)Cl)Cl,-9.86,-8.658
+pent-2-ene,CC/C=C\C,1.31,2.374
+ethane,CC,1.83,2.465
+"1,2-dimethoxybenzene",COc1ccccc1OC,-5.33,-4.055
+pyridine-3-carbonitrile,c1cc(cnc1)C#N,-6.75,-5.582
+"3,4-dichlorophenol",c1cc(c(cc1O)Cl)Cl,-7.29,-5.139
+anisole,COc1ccccc1,-2.45,-2.318
+"2,5-dimethylphenol",Cc1ccc(c(c1)O)C,-5.91,-5.014
+"1,4-dichlorobenzene",c1cc(ccc1Cl)Cl,-1.01,-0.19
+chloro-fluoro-methane,C(F)Cl,-0.77,-0.171
+pent-1-ene,CCCC=C,1.68,2.532
+"1,2,3,4-tetrachlorobenzene",c1cc(c(c(c1Cl)Cl)Cl)Cl,-1.34,-0.304
+hept-1-yne,CCCCCC#C,0.6,0.639
+decan-2-one,CCCCCCCCC(=O)C,-2.34,-2.573
+[2-benzhydryloxyethyl]-dimethyl-amine,CN(C)CCOC(c1ccccc1)c2ccccc2,-9.34,-7.873
+cyclohexanone,C1CCC(=O)CC1,-4.91,-4.18
+pyridine-4-carbaldehyde,c1cnccc1C=O,-7.0,-7.338
+1-chloro-2-(2-chloroethoxy)ethane,C(CCl)OCCCl,-4.23,-2.248
+3-chloropyridine,c1cc(cnc1)Cl,-4.01,-2.767
+bromomethane,CBr,-0.82,0.46
+methanol,CO,-5.1,-3.491
+"1,3-dichloro-2-(2,6-dichlorophenyl)benzene",c1cc(c(c(c1)Cl)c2c(cccc2Cl)Cl)Cl,-2.28,-1.226
+1-methylpiperidine,CN1CCCCC1,-3.88,-3.467
+octanal,CCCCCCCC=O,-2.29,-2.57
+"(2S,5R)-2-isopropyl-5-methylcyclohexanone",C[C@@H]1CC[C@H](C(=O)C1)C(C)C,-2.53,-3.523
+"(2R,3R,4S,5S,6R)-6-(hydroxymethyl)tetrahydropyran-2,3,4,5-tetrol",C([C@@H]1[C@H]([C@@H]([C@H]([C@@H](O1)O)O)O)O)O,-25.47,-18.095
+fluoromethane,CF,-0.22,0.881
+dibenzo-p-dioxin,c1ccc2c(c1)Oc3ccccc3O2,-3.15,-4.9
+2-methylaniline,Cc1ccccc1N,-5.53,-5.325
+1-bromobutane,CCCCBr,-0.4,0.705
+4-methylpyridine,Cc1ccncc1,-4.93,-3.343
+"1,1,2,2-tetrachloroethylene",C(=C(Cl)Cl)(Cl)Cl,0.1,1.328
+2-bromo-2-methyl-propane,CC(C)(C)Br,0.84,0.438
+"1,1-diphenylethene",C=C(c1ccccc1)c2ccccc2,-2.78,-2.47
+3-methylpyridine,Cc1cccnc1,-4.77,-3.221
+"1,1,1,2-tetramethoxyethane",COCC(OC)(OC)OC,-5.73,-5.436
+9H-fluorene,c1ccc-2c(c1)Cc3c2cccc3,-3.35,-4.269
+acetamide,CC(=O)N,-9.71,-8.82
+dimethyl sulfate,COS(=O)(=O)OC,-5.1,-8.411
+methyl cyclohexanecarboxylate,COC(=O)C1CCCCC1,-3.3,-4.376
+1-bromohexane,CCCCCCBr,0.18,1.076
+1-chlorodibenzo-p-dioxin,c1ccc2c(c1)Oc3cccc(c3O2)Cl,-3.52,-4.473
+"3,3,3-trimethoxypropanenitrile",COC(CC#N)(OC)OC,-6.4,-5.859
+2-chlorobutane,CC[C@H](C)Cl,0.0,0.927
+hexylbenzene,CCCCCCc1ccccc1,-0.04,-0.1
+2-chlorosyringaldehyde,COc1cc(c(c(c1O)OC)Cl)C=O,-7.78,-8.292
+m-bis(trifluoromethyl)benzene,c1cc(cc(c1)C(F)(F)F)C(F)(F)F,1.07,-0.34
+1-benzylimidazole,c1ccc(cc1)Cn2ccnc2,-7.63,-7.997
+naphthalen-1-amine,c1ccc2c(c1)cccc2N,-7.28,-7.777
+cyclohexanol,C1CCC(CC1)O,-5.46,-4.178
+Amitriptyline,CN(C)CCC=C1c2ccccc2CCc3c1cccc3,-7.43,-7.349
+4-fluorophenol,c1cc(ccc1O)F,-6.19,-4.955
+2-chloroaniline,c1ccc(c(c1)N)Cl,-4.91,-4.847
+"1,2,4-trimethylbenzene",Cc1ccc(c(c1)C)C,-0.86,-0.795
+biphenyl,c1ccc(cc1)c2ccccc2,-2.7,-3.143
+"2,3-dimethylphenol",Cc1cccc(c1C)O,-6.16,-5.148
+methylparathion,COP(=S)(OC)Oc1ccc(cc1)[N+](=O)[O-],-7.19,-10.466
+diethoxy-(4-nitrophenoxy)-thioxo-$l^{5}-phosphane,CCOP(=S)(OCC)Oc1ccc(cc1)[N+](=O)[O-],-6.74,-9.211
+"1-N,1-N-diethyl-2,6-dinitro-4-(trifluoromethyl)benzene-1,3-diamine",CCN(CC)c1c(cc(c(c1[N+](=O)[O-])N)C(F)(F)F)[N+](=O)[O-],-5.66,-7.503
+cyclopentanol,C1CCC(C1)O,-5.49,-4.29
+methyl pentanoate,CCCCC(=O)OC,-2.56,-3.492
+flurbiprofen,C[C@@H](c1ccc(c(c1)F)c2ccccc2)C(=O)O,-8.42,-13.953
+nitralin,CCCN(CCC)c1c(cc(cc1[N+](=O)[O-])S(=O)(=O)C)[N+](=O)[O-],-7.98,-11.246
+chloroethylene,C=CCl,-0.59,1.162
+"N,N-4-trimethylbenzamide",Cc1ccc(cc1)C(=O)N(C)C,-9.76,-8.081
+heptan-4-one,CCCC(=O)CCC,-2.92,-2.704
+methyl benzoate,COC(=O)c1ccccc1,-3.92,-4.921
+4-methylbenzaldehyde,Cc1ccc(cc1)C=O,-4.27,-5.014
+propyl butanoate,CCCC(=O)OCCC,-2.28,-2.754
+piperazine,C1CNCCN1,-7.4,-8.481
+dialifor,CCOP(=S)(OCC)S[C@@H](CCl)N1C(=O)c2ccccc2C1=O,-5.74,-16.515
+2-ethoxyethanol,CCOCCO,-6.69,-4.407
+2-methylpyrazine,Cc1cnccn1,-5.51,-6.161
+1-nitropropane,CCC[N+](=O)[O-],-3.34,-1.632
+5-fluorouracil,c1c(c(=O)[nH]c(=O)[nH]1)F,-16.92,-16.371
+ethanol,CCO,-5.0,-3.394
+"2,3,7,8-tetrachlorodibenzo-p-dioxin",c1c2c(cc(c1Cl)Cl)Oc3cc(c(cc3O2)Cl)Cl,-3.37,-2.54
+dichlobenil,c1cc(c(c(c1)Cl)C#N)Cl,-4.71,-3.32
+ethyl formate,CCOC=O,-2.56,-3.867
+"1,2,4,5-tetrachlorobenzene",c1c(c(cc(c1Cl)Cl)Cl)Cl,-1.34,0.035
+diethoxymethoxybenzene,CCOC(OCC)Oc1ccccc1,-5.23,-5.203
+3-nitrophenol,c1cc(cc(c1)O)[N+](=O)[O-],-9.62,-7.889
+octan-1-ol,CCCCCCCCO,-4.09,-2.69
+but-1-ene,CCC=C,1.38,2.367
+carbon tetrachloride,C(Cl)(Cl)(Cl)Cl,0.08,1.185
+2-phenylethanol,c1ccc(cc1)CCO,-6.79,-5.28
+fenuron,CN(C)C(=O)Nc1ccccc1,-9.13,-11.81
+captan,C1C=CC[C@@H]2[C@@H]1C(=O)N(C2=O)SC(Cl)(Cl)Cl,-9.01,-8.718
+"2,3-diacetoxypropyl acetate",CC(=O)OCC(COC(=O)C)OC(=O)C,-8.84,-12.333
+methoxymethane,COC,-1.91,-0.853
+hexane,CCCCCC,2.48,2.851
+"1,2-dibromoethane",C(CBr)Br,-2.33,-1.275
+5-trifluoromethyluracil,c1c(c(=O)[nH]c(=O)[nH]1)C(F)(F)F,-15.46,-17.349
+"2,6-dimethylaniline",Cc1cccc(c1N)C,-5.21,-5.57
+quinoline,c1ccc2c(c1)cccn2,-5.72,-4.989
+ethanethiol,CCS,-1.14,-0.395
+thiophene,c1ccsc1,-1.4,-0.359
+1-ethylnaphthalene,CCc1cccc2c1cccc2,-2.4,-2.961
+profluralin,CCC[N@@](CC1CC1)c2c(cc(cc2[N+](=O)[O-])C(F)(F)F)[N+](=O)[O-],-2.45,-1.956
+acetic acid,CC(=O)O,-6.69,-7.281
+acetaldehyde,CC=O,-3.5,-3.372
+3-nitroaniline,c1cc(cc(c1)[N+](=O)[O-])N,-8.84,-8.204
+hex-1-yne,CCCCC#C,0.29,0.553
+2-methoxyaniline,COc1ccccc1N,-6.12,-6.771
+phenol,c1ccc(cc1)O,-6.6,-5.707
+propanenitrile,CCC#N,-3.84,-2.491
+naphthalen-1-ol,c1ccc2c(c1)cccc2O,-7.67,-7.137
+butyl acetate,CCCCOC(=O)C,-2.64,-3.406
+aldicarb,CC(C)(/C=N\OC(=O)NC)SC,-9.84,-9.679
+o-cresol,Cc1ccccc1O,-5.9,-5.076
+2-methylpropanal,CC(C)C=O,-2.86,-2.968
+propionamide,CCC(=O)N,-9.4,-8.31
+1-bromopropane,CCCBr,-0.56,0.579
+2-chloropropane,CC(C)Cl,-0.25,0.833
+"1,3-dichloropropane",C(CCl)CCl,-1.89,-0.416
+4-nitrophenol,c1cc(ccc1[N+](=O)[O-])O,-10.64,-8.472
+"1,2-dichloropropane",C[C@@H](CCl)Cl,-1.27,-0.265
+pyridine-4-carbonitrile,c1cnccc1C#N,-6.02,-5.765
+1-cyclohexylethanone,CC(=O)C1CCCCC1,-3.9,-4.003
+"1,2,3,4,7,8-hexachlorodibenzo-p-dioxin",c1c2c(cc(c1Cl)Cl)Oc3c(c(c(c(c3Cl)Cl)Cl)Cl)O2,-3.71,-1.878
+acetone,CC(=O)C,-3.8,-3.506
+"1,2,3-trichloro-5-(2,5-dichlorophenyl)benzene",c1cc(c(cc1Cl)c2cc(c(c(c2)Cl)Cl)Cl)Cl,-3.61,-0.922
+1-nitropentane,CCCCC[N+](=O)[O-],-2.82,-1.325
+(2E)-hex-2-enal,CCC/C=C/C=O,-3.68,-3.123
+tetrahydrofuran,C1CCOC1,-3.47,-2.201
+octane,CCCCCCCC,2.88,3.088
+trifluralin,CCCN(CCC)c1c(cc(cc1[N+](=O)[O-])C(F)(F)F)[N+](=O)[O-],-3.25,-2.023
+"(3R)-3,7-Dimethylocta-1,6-dien-3-yl acetate",CC(=CCC[C@](C)(C=C)OC(=O)C)C,-2.49,-2.964
+"1,3-bis-(nitrooxy)butane",C[C@@H](CCO[N+](=O)[O-])O[N+](=O)[O-],-4.29,-4.944
+2-isopropoxypropane,CC(C)OC(C)C,-0.53,-0.178
+2-methylhexane,CCCCC(C)C,2.93,2.894
+pentachloronitrobenzene,c1(c(c(c(c(c1Cl)Cl)Cl)Cl)Cl)N(=O)=O,-5.22,-1.284
+"2-bromo-2-chloro-1,1,1-trifluoro-ethane",[C@@H](C(F)(F)F)(Cl)Br,-0.11,0.206
+pentylcyclopentane,CCCCCC1CCCC1,2.55,2.381
+"2,5-dimethylpyridine",Cc1ccc(nc1)C,-4.72,-3.165
+but-2-enal,C/C=C/C=O,-4.22,-3.341
+"1,3,5-trichloro-2-(2,6-dichlorophenyl)benzene",c1cc(c(c(c1)Cl)c2c(cc(cc2Cl)Cl)Cl)Cl,-1.96,-0.477
+"1,2,2-trifluoroethoxybenzene",c1ccc(cc1)O[C@@H](C(F)F)F,-1.29,-3.043
+"1,2-dimethoxyethane",COCCOC,-4.84,-3.103
+sec-butylbenzene,CC[C@H](C)c1ccccc1,-0.45,-0.22
+3-phenylpropan-1-ol,c1ccc(cc1)CCCO,-6.92,-5.771
+"2-[(1R)-1-methylpropyl]-4,6-dinitro-phenolate",CC[C@@H](C)c1cc(cc(c1O)[N+](=O)[O-])[N+](=O)[O-],-6.23,-5.378
+methyl 4-methoxybenzoate,COc1ccc(cc1)C(=O)OC,-5.33,-6.462
+"N-(3,4-dichlorophenyl)propanimidic acid",CCC(=O)Nc1ccc(c(c1)Cl)Cl,-7.78,-9.409
+octafluorocyclobutane,C1(C(C(C1(F)F)(F)F)(F)F)(F)F,3.43,3.077
+isopentyl acetate,CC(C)CCOC(=O)C,-2.21,-3.067
+1-chlorohexane,CCCCCCCl,0.0,1.261
+4-methylpentan-2-one,CC(C)CC(=O)C,-3.05,-3.116
+hexanal,CCCCCC=O,-2.81,-2.86
+morpholine,C1COCCN1,-7.17,-6.116
+"1,1-diethoxyethane",CCOC(C)OCC,-3.28,-1.795
+"N-butyl-N-ethyl-2,6-dinitro-4-(trifluoromethyl)aniline",CCCC[N@](CC)c1c(cc(cc1[N+](=O)[O-])C(F)(F)F)[N+](=O)[O-],-3.51,-2.303
+endosulfan alpha,C1[C@@H]2[C@H](COS(=O)O1)[C@@]3(C(=C([C@]2(C3(Cl)Cl)Cl)Cl)Cl)Cl,-4.23,-9.785
+1-(4-methoxyphenyl)ethanone,CC(=O)c1ccc(cc1)OC,-4.4,-6.575
+prop-2-en-1-ol,C=CCO,-5.03,-3.286
+methylsulfanylethane,CCSC,-1.5,0.386
+pentyl acetate,CCCCCOC(=O)C,-2.51,-2.565
+"1,2,3,5-tetrachlorobenzene",c1c(cc(c(c1Cl)Cl)Cl)Cl,-1.62,0.136
+1-phenylethanone,CC(=O)c1ccccc1,-4.58,-5.078
+propylcyclopentane,CCCC1CCCC1,2.13,2.102
+"1,3,5-trichlorobenzene",c1c(cc(cc1Cl)Cl)Cl,-0.78,0.326
+propyl paraben,CCCOC(=O)c1ccc(cc1)O,-9.37,-8.945
+3-chlorophenol,c1cc(cc(c1)Cl)O,-6.62,-5.018
+3-methylbutan-1-ol,CC(C)CCO,-4.42,-3.237
+terbacil,Cc1c(c(=O)n(c(=O)[nH]1)C(C)(C)C)Cl,-11.14,-13.769
+"2,2,5-trimethylhexane",CC(C)CCC(C)(C)C,2.93,2.97
+endrin,C1[C@@H]2[C@H]3[C@@H]([C@H]1[C@H]4[C@@H]2O4)[C@@]5(C(=C([C@]3(C5(Cl)Cl)Cl)Cl)Cl)Cl,-4.82,-5.179
+benzamide,c1ccc(cc1)C(=O)N,-11.0,-10.412
+2-nitropropane,CC(C)[N+](=O)[O-],-3.13,-1.741
+glycerol,C(C(CO)O)O,-13.43,-10.14
+1-iodopropane,CCCI,-0.53,-0.443
+2-methoxyethanamine,COCCN,-6.55,-5.027
+"1,1,1,2-tetrachloroethane",C(C(Cl)(Cl)Cl)Cl,-1.43,-0.091
+"3,5-dimethylpyridine",Cc1cc(cnc1)C,-4.84,-2.869
+2-methoxyethanol,COCCO,-6.619999999999999,-4.686
+methyl formate,COC=O,-2.78,-4.028
+naphthalen-2-amine,c1ccc2cc(ccc2c1)N,-7.47,-8.003
+4-methyl-1H-imidazole,Cc1c[nH]cn1,-10.27,-8.205
+1-methyl-3-nitro-benzene,Cc1cccc(c1)[N+](=O)[O-],-3.45,-3.278
+"1,4-dichlorobutane",C(CCCl)CCl,-2.32,-0.404
+nitroxyacetone,CC(=O)CO[N+](=O)[O-],-5.99,-5.362
+tert-butylbenzene,CC(C)(C)c1ccccc1,-0.44,-0.803
+methyl hexanoate,CCCCCC(=O)OC,-2.49,-3.299
+"1,1,1-trifluoropropan-2-ol",C[C@@H](C(F)(F)F)O,-4.16,-3.518
+1-bromo-pentane,CCCCCBr,-0.1,0.824
+6-isopropyl-3-methyl-1-cyclohex-2-enone,CC1=CC(=O)[C@@H](CC1)C(C)C,-4.51,-3.825
+propan-2-ol,CC(C)O,-4.74,-3.427
+hexan-1-amine,CCCCCCN,-3.95,-2.772
+3-nitrooxypropyl nitrate,C(CO[N+](=O)[O-])CO[N+](=O)[O-],-4.8,-5.322
+"2,4-dimethylphenol",Cc1ccc(c(c1)C)O,-6.01,-4.98
+pentan-1-ol,CCCCCO,-4.57,-3.054
+pentan-2-ol,CCC[C@@H](C)O,-4.39,-2.945
+3-methylheptane,CCCC[C@@H](C)CC,2.97,3.03
+ibuprofen,C[C@@H](c1ccc(cc1)CC(C)C)C(=O)O,-7.0,-10.857
+diethyl (2R)-2-dimethoxyphosphinothioylsulfanylbutanedioate,CCOC(=O)C[C@H](C(=O)OCC)SP(=S)(OC)OC,-8.15,-11.194
+"3,4-dimethylphenol",Cc1ccc(cc1C)O,-6.5,-5.471
+4-chloro-3-methyl-phenol,Cc1cc(ccc1Cl)O,-6.79,-5.14
+hept-2-ene,CCCC/C=C/C,1.68,2.78
+terbutryn,CCNc1nc(nc(n1)SC)NC(C)(C)C,-6.68,-9.271
+"2,2,4-trimethylpentane",CC(C)CC(C)(C)C,2.89,2.542
+nonan-5-one,CCCCC(=O)CCCC,-2.64,-2.364
+pebulate,CCCCN(CC)C(=O)SCCC,-3.64,-4.573
+hept-1-ene,CCCCCC=C,1.66,2.761
+isopropyl formate,CC(C)OC=O,-2.02,-3.591
+5-chlorouracil,c1c(c(=O)[nH]c(=O)[nH]1)Cl,-17.74,-16.612
+isopropenylbenzene,CC(=C)c1ccccc1,-1.24,-0.651
+isopentane,CCC(C)C,2.38,2.59
+butyl nitrate,CCCCO[N+](=O)[O-],-2.09,-1.938
+bromobenzene,c1ccc(cc1)Br,-1.46,-0.947
+"1,1,1-trichloroethane",CC(Cl)(Cl)Cl,-0.19,0.505
+4-(1-Methylethenyl)-1-cyclohexene-1-carboxaldehyde,CC(=C)[C@H]1CCC(=CC1)C=O,-4.09,-3.591
+1-methyl-2-nitro-benzene,Cc1ccccc1[N+](=O)[O-],-3.58,-3.133
+1-iodoheptane,CCCCCCCI,0.27,0.228
+pyrene,c1cc2ccc3cccc4c3c2c(c1)cc4,-4.52,-6.79
+1-chloro-pentane,CCCCCCl,-0.1,1.084
+isobutyl acetate,CC(C)COC(=O)C,-2.36,-2.896
+"2,2-dimethylbutane",CCC(C)(C)C,2.51,2.495
+4-nitroaniline,c1cc(ccc1N)N(=O)=O,-9.82,-9.416
+methyl 2-cyanoacetate,COC(=O)CC#N,-6.72,-6.36
+4-methoxyaniline,COc1ccc(cc1)N,-7.48,-7.016
+"1,3,5-trichloro-2-phenyl-benzene",c1ccc(cc1)c2c(cc(cc2Cl)Cl)Cl,-2.16,-1.151
+methanamine,CN,-4.55,-3.583
+"2-amino-9,10-anthraquinone",c1ccc2c(c1)C(=O)c3ccc(cc3C2=O)N,-11.53,-13.895
+"(Z)-1,2-dichloroethylene",C(=C\Cl)\Cl,-1.17,1.156
+hexan-2-one,CCCCC(=O)C,-3.28,-3.006
+"1,2-dinitroxyethane",C(CO[N+](=O)[O-])O[N+](=O)[O-],-5.73,-6.227
+2-fluorophenol,c1ccc(c(c1)O)F,-5.29,-3.346
+pirimor,Cc1c(nc(nc1OC(=O)N(C)C)N(C)C)C,-9.41,-13.87
+styrene,C=Cc1ccccc1,-1.24,-1.078
+triethylphosphate,CCOP(=O)(OCC)OCC,-7.5,-10.251
+"2,2,2-trifluoroethanol",C(C(F)(F)F)O,-4.31,-3.809
+1-butoxy-2-propanol,CCCCOC[C@H](C)O,-5.73,-3.891
+propan-1-ol,CCCO,-4.85,-3.33
+o-xylene,Cc1ccccc1C,-0.9,-0.851
+neopentane,CC(C)(C)C,2.51,2.506
+pent-1-yne,CCCC#C,0.01,0.47
+phthalimide,c1ccc2c(c1)C(=O)NC2=O,-9.61,-11.825
+1-iodobutane,CCCCI,-0.25,-0.223
+p-cresol,Cc1ccc(cc1)O,-6.13,-5.579
+2-iodopropane,CC(C)I,-0.46,-0.492
+cyclopentene,C1CC=CC1,0.56,1.23
+111-trifluoropropan-2-ol,C[C@H](C(F)(F)F)O,-4.2,-3.486
+propan-1-amine,CCCN,-4.39,-3.053
+2-nitrophenol,c1ccc(c(c1)[N+](=O)[O-])O,-4.58,-5.667
+1-methylnaphthalene,Cc1cccc2c1cccc2,-2.44,-3.212
+hexachlorobenzene,c1(c(c(c(c(c1Cl)Cl)Cl)Cl)Cl)Cl,-2.33,0.379
+oct-2-enal,CCCCC/C=C/C=O,-3.43,-2.706
+oct-1-yne,CCCCCCC#C,0.71,0.832
+diazinon,CCOP(=S)(OCC)Oc1cc(nc(n1)C(C)C)C,-6.48,-10.753
+pyrrolidine,C1CCNC1,-5.48,-4.278
+4-hydroxybenzaldehyde,c1cc(ccc1C=O)O,-8.83,-10.05

mol_moe/data/moleculenet/freesolv/valid.csv

@@ -0,0 +1,65 @@
+iupac,smiles,expt,calc
+3-methylbut-1-ene,CC(C)C=C,1.83,2.452
+2-methylpentan-3-ol,CC[C@H](C(C)C)O,-3.88,-2.416
+"(2Z)-3,7-dimethylocta-2,6-dien-1-ol",CC(=CCC/C(=C\CO)/C)C,-4.78,-2.597
+cycloheptanol,C1CCCC(CC1)O,-5.48,-4.345
+hydrazine,NN,-9.3,-6.508
+2-methylpyridine,Cc1ccccn1,-4.63,-3.501
+isobutyl nitrate,CC(C)CO[N+](=O)[O-],-1.88,-1.835
+"cyclohepta-1,3,5-triene",C1C=CC=CC=C1,-0.99,-0.098
+phenylmethanol,c1ccc(cc1)CO,-6.62,-5.133
+"1,2,3,7-tetrachlorodibenzo-p-dioxin",c1cc2c(cc1Cl)Oc3cc(c(c(c3O2)Cl)Cl)Cl,-3.84,-2.66
+1-methoxypropane,CCCOC,-1.66,-0.598
+propylbenzene,CCCc1ccccc1,-0.53,-0.511
+"2-bromo-1,1,1,2-tetrafluoro-ethane",[C@@H](C(F)(F)F)(F)Br,0.5,0.234
+tetrahydropyran,C1CCOCC1,-3.12,-1.809
+"1,2-dichlorobenzene",c1ccc(c(c1)Cl)Cl,-1.36,-0.553
+diethyl butanedioate,CCOC(=O)CCC(=O)OCC,-5.71,-8.683
+"1,2,3,4,7-pentachlorodibenzo-p-dioxin",c1cc2c(cc1Cl)Oc3c(c(c(c(c3Cl)Cl)Cl)Cl)O2,-4.15,-2.31
+benzaldehyde,c1ccc(cc1)C=O,-4.02,-5.058
+1-chloro-2-methyl-benzene,Cc1ccccc1Cl,-1.14,-0.473
+ethoxyethane,CCOCC,-1.59,-0.617
+phenyl formate,c1ccc(cc1)OC=O,-3.82,-5.442
+2-methoxy-2-methyl-propane,CC(C)(C)OC,-2.21,-0.691
+methyl methanesulfonate,COS(=O)(=O)C,-4.87,-8.824
+propane,CCC,2.0,2.495
+3-hydroxybenzaldehyde,c1cc(cc(c1)O)C=O,-9.52,-9.369
+m-cresol,Cc1cccc(c1)O,-5.49,-5.378
+"1-amino-4-hydroxy-9,10-anthracenedione",c1ccc2c(c1)C(=O)c3c(ccc(c3C2=O)O)N,-9.53,-10.984
+isohexane,CCCC(C)C,2.51,2.808
+prop-1-ene,CC=C,1.32,2.328
+methyl 4-nitrobenzoate,COC(=O)c1ccc(cc1)[N+](=O)[O-],-6.88,-6.588
+2-methylthiophene,Cc1cccs1,-1.38,-0.3
+1-chlorobutane,CCCCCl,-0.16,0.993
+"2,3-dimethylnaphthalene",Cc1cc2ccccc2cc1C,-2.78,-2.953
+3-methoxyaniline,COc1cccc(c1)N,-7.29,-7.201
+ethylsulfanylethane,CCSCC,-1.46,0.299
+pentanal,CCCCC=O,-3.03,-2.927
+diphenyl ether,c1ccc(cc1)Oc2ccccc2,-2.87,-2.81
+1-nitrobutane,CCCC[N+](=O)[O-],-3.09,-1.449
+1-nitroethane,CC[N+](=O)[O-],-3.71,-1.839
+nitrobenzene,c1ccc(cc1)[N+](=O)[O-],-4.12,-3.46
+nonan-1-ol,CCCCCCCCCO,-3.88,-2.564
+1-ethyl-4-methyl-benzene,CCc1ccc(cc1)C,-0.95,-0.575
+diethyl propanedioate,CCOC(=O)CC(=O)OCC,-6.0,-6.716
+1-ethyl-2-methylbenzene,CCc1ccccc1C,-0.85,-0.761
+methylsulfanylmethane,CSC,-1.61,0.44
+3-methylpentane,CCC(C)CC,2.51,2.613
+mesitylene,Cc1cc(cc(c1)C)C,-0.9,-0.553
+"1,1,1,2,2-pentachloroethane",C(C(Cl)(Cl)Cl)(Cl)Cl,-1.23,0.059
+"1,2,3,4-tetrachloro-5-(2,3,4,6-tetrachlorophenyl)benzene",c1c(c(c(c(c1Cl)Cl)Cl)Cl)c2c(cc(c(c2Cl)Cl)Cl)Cl,-4.61,-0.039
+4-chloroaniline,c1cc(ccc1N)Cl,-5.9,-5.281
+"1-amino-9,10-anthracenedione",c1ccc2c(c1)C(=O)c3cccc(c3C2=O)N,-9.44,-12.214
+"2,3-dimethylpyridine",Cc1cccnc1C,-4.82,-3.367
+2-methylbenzaldehyde,Cc1ccccc1C=O,-3.93,-4.554
+"N,N-dimethyl-4-nitro-benzamide",CN(C)C(=O)c1ccc(cc1)[N+](=O)[O-],-11.95,-10.036
+"2,4-dimethylpentane",CC(C)CC(C)C,2.83,2.756
+3-chloroaniline,c1cc(cc(c1)Cl)N,-5.82,-5.138
+pentan-1-amine,CCCCCN,-4.09,-2.835
+2-butoxyethanol,CCCCOCCO,-6.25,-3.85
+cyclopentane,C1CCCC1,1.2,1.648
+3-ethylpyridine,CCc1cccnc1,-4.59,-2.965
+"(1R,2S,5R)-2-isopropyl-5-methylcyclohexanol",C[C@@H]1CC[C@H]([C@@H](C1)O)C(C)C,-3.2,-3.35
+1-acetoxyethyl acetate,CC(OC(=O)C)OC(=O)C,-4.97,-8.006
+2-chlorophenol,c1ccc(c(c1)O)Cl,-4.55,-3.317
+methyl octanoate,CCCCCCCC(=O)OC,-2.04,-3.035

mol_moe/data/moleculenet/lipophilicity/test.csv

@@ -0,0 +1,421 @@
+smiles,y
+N(c1ccccc1)c2ccnc3ccccc23,0.4881605584346015
+Clc1ccc2Oc3ccccc3N=C(N4CCNCC4)c2c1,0.07001669633726465
+NC1(CCC1)c2ccc(cc2)c3ncc4cccnc4c3c5ccccc5,-0.4150301836956459
+OC[C@H](O)CN1C(=O)[C@@H](Cc2ccccc12)NC(=O)c3cc4cc(Cl)sc4[nH]3,0.8979415432899918
+NS(=O)(=O)c1nc2ccccc2s1,-0.7077308871637816
+COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1OC4CCN(CC(=O)N)CC4,0.7557726301768973
+CN(c1ccnc(Nc2cccc(c2)S(=O)(=O)C)n1)c3cccc4[nH]ncc34,0.8477642798383113
+OC(=O)COc1ccc(cc1c2ccccc2)c3nccs3,-1.970525350697739
+NC(=O)c1ccccc1OCc2ccccc2,0.253999995660093
+CCN1CCC[C@H]1CNC(=O)c2c(O)c(Cl)cc(Cl)c2OC,-0.9251656954543968
+O=C(CCc1ccncc1)Nc2ccc(cc2)C(=O)c3ccccc3,1.0066589474352992
+COc1cc(Nc2cc(nc(N[C@@H](C)c3ncc(F)cn3)n2)N4CCOCC4)n[nH]1,-0.013612076082202416
+FC(F)(F)c1nnc2ccc(NCn3nnc4ccccc34)nn12,0.12019395978894512
+NC(=O)C(NC(=O)C1(N)CCN(CC1)c2ncnc3[nH]ccc23)c4ccc(Cl)cc4,0.0031136784016910723
+NC(=O)c1cccc(O[C@@H]2C[C@H]3CC[C@@H](C2)N3Cc4ccccc4)c1,-0.3648529202439655
+O[C@H](CNC(=O)C1=CNC(=O)c2ccccc12)CN3CCC(CC3)Oc4ccc(Cl)c(Cl)c4,1.0233847019191928
+CC(C)[N+](C)(CCOC(=O)C1c2ccccc2Oc3ccccc13)C(C)C,-1.6694617699876564
+COc1cc2c(Nc3c(Cl)ccc4OCOc34)ncnc2cc1OCC5CCN(C)CC5,-0.30631277955033825
+COc1ccc(c(OC)n1)c2c(F)ccc3c(N)c(nnc23)C(=O)NC4CC4,0.9815703157094592
+OC(=O)c1ccc(cc1)n2ncc(C(=O)NC3C4CC5CC(CC3C5)C4)c2C6CCC6,-0.7244566416476751
+Cc1ccc(CN2[C@@H]3CC[C@H]2C[C@H](C3)Oc4cccc(c4)C(=O)N)s1,0.16200834599867903
+Oc1ccc(cc1)c2nc3ccccc3s2,1.5920603543715706
+CCCSc1ncccc1C(=O)N(C)C2CCOCC2,-0.47357032438927316
+COc1ccc2c(C)cc(N[C@H]3CCC[C@@H](C3)NCc4cccc(OC(F)(F)F)c4)nc2c1,1.1822793695161806
+COc1cnc(nc1N2CCOCC2)c3ccccn3,-0.5655619740506872
+CC(C)(C)OC(=O)N1CCN(CC1)c2ncc(OCc3ccc(cc3)S(=O)(=O)C)nn2,0.6136037170638028
+N[C@@H]1CCCN(C1)c2c(Cl)cccc2\C=C\3/SC(=O)NC3=O,-0.18923249816308405
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mol_moe/data/moleculenet/sider/test.csv

@@ -0,0 +1,144 @@
+smiles,Hepatobiliary disorders,Metabolism and nutrition disorders,Product issues,Eye disorders,Investigations,Musculoskeletal and connective tissue disorders,Gastrointestinal disorders,Social circumstances,Immune system disorders,Reproductive system and breast disorders,"Neoplasms benign, malignant and unspecified (incl cysts and polyps)",General disorders and administration site conditions,Endocrine disorders,Surgical and medical procedures,Vascular disorders,Blood and lymphatic system disorders,Skin and subcutaneous tissue disorders,"Congenital, familial and genetic disorders",Infections and infestations,"Respiratory, thoracic and mediastinal disorders",Psychiatric disorders,Renal and urinary disorders,"Pregnancy, puerperium and perinatal conditions",Ear and labyrinth disorders,Cardiac disorders,Nervous system disorders,"Injury, poisoning and procedural complications"
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mol_moe/data/moleculenet/sider/valid.csv

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+smiles,Hepatobiliary disorders,Metabolism and nutrition disorders,Product issues,Eye disorders,Investigations,Musculoskeletal and connective tissue disorders,Gastrointestinal disorders,Social circumstances,Immune system disorders,Reproductive system and breast disorders,"Neoplasms benign, malignant and unspecified (incl cysts and polyps)",General disorders and administration site conditions,Endocrine disorders,Surgical and medical procedures,Vascular disorders,Blood and lymphatic system disorders,Skin and subcutaneous tissue disorders,"Congenital, familial and genetic disorders",Infections and infestations,"Respiratory, thoracic and mediastinal disorders",Psychiatric disorders,Renal and urinary disorders,"Pregnancy, puerperium and perinatal conditions",Ear and labyrinth disorders,Cardiac disorders,Nervous system disorders,"Injury, poisoning and procedural complications"
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mol_moe/data/moleculenet/tox21/valid.csv

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+,,,,,,,0,,0,,,TOX31421,CC(=O)OC[C@H]1O[C@@H](OC(C)=O)[C@H](OC(C)=O)[C@@H]1OC(C)=O
+0,0,0,0,0,0,,,0,,,0,TOX5548,CN1CCC(CN2c3ccccc3Sc3ccccc32)C1
+0,0,0,0,0,0,0,0,0,0,0,0,TOX21659,N#Cc1ccc(C(=O)O)cc1
+0,0,0,0,0,0,0,0,0,0,0,0,TOX27767,COc1cc(N)c(Cl)cc1C(=O)NC1CCN(Cc2ccccc2)CC1
+0,0,0,0,0,0,0,0,0,0,,0,TOX27761,N[C@@H]1C[C@H]1c1ccccc1
+0,0,0,0,0,0,0,0,0,0,0,0,TOX27760,CNC(C)(C)Cc1ccccc1.CNC(C)(C)Cc1ccccc1
+0,0,0,0,0,0,0,0,0,0,0,0,TOX20236,O=c1cc(CO)occ1O
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+0,0,0,0,1,0,0,,0,,0,0,TOX25950,CC(C)C[C@H](CN)CC(=O)O
+0,0,0,,,0,,,0,0,1,1,TOX25953,CCc1c2c(nc3ccc(OC(=O)N4CCC(N5CCCCC5)CC4)cc13)-c1cc3c(c(=O)n1C2)COC(=O)[C@]3(O)CC
+,,0,0,,0,0,0,0,0,0,0,TOX5053,CCCCC(CC)CNCC(CC)CCCC
+0,0,0,0,1,0,0,0,0,0,0,0,TOX1028,CCN(CC)N=O
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+0,,,1,,,,1,,,1,,TOX29109,CCCCCCCCCCCCn1cc[n+](C)c1.F[B-](F)(F)F
+0,0,0,0,,0,0,1,0,0,0,0,TOX29108,CCCCCCn1cc[n+](C)c1.F[B-](F)(F)F
+0,0,0,0,0,0,0,0,0,0,0,0,TOX29107,CCCn1cc[n+](C)c1.F[B-](F)(F)F
+0,0,0,0,0,0,0,0,0,0,,0,TOX29103,CCCn1cc[n+](C)c1C
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+0,0,0,0,0,0,0,0,0,0,,0,TOX25547,CCCc1ncc(C[n+]2ccccc2C)c(N)n1
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+0,0,0,0,0,,0,0,0,0,0,0,TOX3205,C=CCN1CC[C@]23CCCC[C@H]2[C@H]1Cc1ccc(O)cc13
+0,0,0,0,0,0,0,1,0,0,0,0,TOX27110,CC(=O)OC/C=C(\C)CC/C=C(\C)CCC=C(C)C
+0,0,,1,,1,0,,,0,,0,TOX24519,Cc1c([N+](=O)[O-])cc2c(c1[N+](=O)[O-])C(C)(C)CC2(C)C
+,,,,,,,,,0,,,TOX26422,N[C@H](C(=O)O)[C@@H](O)c1ccc(O)c(O)c1
+0,0,0,0,,0,0,,0,,0,0,TOX26169,CCCCCCCCCCCCCCCC(=O)OCC(COC(=O)CCCCCCCCCCCCCCC)OC(=O)CCCCCCCCCCCCCCC
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+0,0,0,0,0,0,0,0,0,0,0,0,TOX26163,CCNC(=O)NCc1cccc(Cl)c1
+0,0,0,0,0,0,0,0,0,0,0,0,TOX5567,COC(=O)c1ccccc1N
+0,0,0,0,0,0,0,0,0,0,0,0,TOX27780,CCC[C@@H]1C[C@@H](C(=O)N[C@H]([C@@H](C)O)[C@H]2O[C@H](SC)[C@H](O)[C@@H](O)[C@H]2O)N(C)C1
+,,,,,,,0,,0,,,TOX27788,CCN(CCO)CCCC(C)Nc1ccnc2cc(Cl)ccc12
+0,0,0,0,,0,0,1,0,0,0,0,TOX14165,CC1(C)NC(=O)N(c2ccc([N+](=O)[O-])c(C(F)(F)F)c2)C1=O
+0,0,0,1,,0,,,0,,,1,TOX28698,O=[N+]([O-])c1ccc(Oc2ccc(N=C=S)cc2)cc1
+0,0,0,0,0,0,1,,0,0,0,0,TOX28699,CCO[C@H](Cc1ccc(OCCc2ccc(OS(C)(=O)=O)cc2)cc1)C(=O)O
+0,0,0,,0,0,0,,0,,0,0,TOX28692,CCCCCCCCCC(=O)N[O-]
+0,,,,0,0,,,1,,,0,TOX3693,COc1ccc(/C=C/C(=O)Nc2ccccc2C(=O)O)cc1OC
+0,0,0,0,0,0,,0,0,0,0,0,TOX3690,Cc1cccc(Nc2ccncc2S(=O)(=O)NC(=O)NC(C)C)c1
+0,0,0,0,0,0,0,0,0,0,,0,TOX21075,CN(C)C(=O)Oc1cccc([N+](C)(C)C)c1
+0,0,0,0,1,0,0,0,0,0,0,0,TOX24552,CC(=O)O[AlH3](O)OC(C)=O
+0,,,,,,,,0,0,,1,TOX21070,COc1c(C)c2c(c(O)c1C/C=C(\C)CCC(=O)O)C(=O)OC2
+0,0,0,0,0,0,0,1,0,0,,0,TOX25975,COc1ccc(-c2cc(C(F)F)nn2-c2ccc(S(N)(=O)=O)cc2)cc1F
+0,0,0,,,0,0,1,0,1,1,1,TOX243,O=C1C2CC=CCC2C(=O)N1SC(Cl)(Cl)Cl
+0,0,0,0,0,0,0,0,0,0,0,0,TOX244,NNC(N)=O
+0,0,0,,1,0,,,0,0,,0,TOX29121,O=Cc1cc(O)ccc1Br
+0,0,0,,0,0,0,0,0,1,,0,TOX29128,COS(=O)(=O)C(F)(F)F
+0,0,0,,,0,0,1,0,0,1,0,TOX25205,O=C(CCCN1CCC2(CC1)C(=O)NCN2c1ccccc1)c1ccc(F)cc1
+0,0,0,,0,0,,,0,0,0,0,TOX12832,O=C(O)C(Br)CBr
+0,0,0,0,0,0,0,0,0,0,0,0,TOX7595,CCCCCCCCS(=O)(=O)[O-]
+0,0,0,0,0,0,0,0,0,0,0,0,TOX7598,CC(C)OB(OC(C)C)OC(C)C
+0,0,,,0,0,0,,0,0,0,0,TOX7841,CC(C)CCCCCOC(=O)CS
+0,0,0,,0,0,,,0,1,,,TOX12649,CC(C)=CC1C(C(=O)OCN2C(=O)C3=C(CCCC3)C2=O)C1(C)C
+0,0,,0,0,0,0,0,0,0,0,0,TOX1193,CC(C)NCC(O)c1ccc2ccccc2c1
+0,0,0,0,0,0,0,0,0,0,0,0,TOX27040,CCC(C)(CCC(C)C)C(=O)[O-].CCC(C)(CCC(C)C)C(=O)[O-].[Zn+2]
+0,0,,0,0,0,0,,0,,0,0,TOX25789,CNC(=O)OCC[N+](C)(C)C
+0,0,0,0,0,0,0,,0,,0,0,TOX25568,CCN(CC)Cc1cc(Nc2ccnc3cc(Cl)ccc23)ccc1O
+1,0,0,0,0,0,0,0,0,0,0,0,TOX3590,C[C@H]1CN(c2c(F)c(N)c3c(=O)c(C(=O)O)cn(C4CC4)c3c2F)C[C@@H](C)N1
+0,0,0,0,0,0,0,0,0,0,0,0,TOX21847,CCCCOC(=O)CCCCCCCCC(=O)OCCCC
+0,0,0,0,0,0,0,0,0,0,0,0,TOX28648,O=C(OCC1(COC(=O)c2cccnc2)CCCC(COC(=O)c2cccnc2)(COC(=O)c2cccnc2)C1O)c1cccnc1
+0,0,0,,0,0,,1,0,1,0,0,TOX4902,CN1CSC(=S)N(C)C1
+0,0,0,0,0,0,0,0,0,0,0,0,TOX7454,CC(=O)CC(=O)N(C)C
+0,0,0,0,1,0,0,,0,,0,0,TOX26146,C[C@@H](Cc1ccccc1)N(C)C
+0,0,0,0,0,0,0,0,0,0,0,0,TOX27547,COC(CC(C)CCCC(C)(C)O)OC
+0,0,0,0,,0,0,0,0,0,0,0,TOX4431,CSC(C)(C)/C=N\O
+0,0,,0,,,0,,0,0,,0,TOX27846,CCCC[P+](C)(CCCC)CCCC.COS(=O)(=O)[O-]
+0,0,0,0,,0,0,1,0,0,,0,TOX27847,CCCCCCn1cc[n+](C)c1.O=S(=O)([O-])C(F)(F)F
+0,0,,0,0,0,0,,0,0,0,0,TOX27848,C[n+]1ccn(CCO)c1
+0,0,0,0,0,0,0,0,0,0,0,0,TOX25195,CCCN(CCC)CCc1cccc2c1CC(=O)N2
+0,0,0,0,0,0,0,0,0,0,0,0,TOX25196,COc1ccccc1OCC(O)CN1CCN(CC(=O)Nc2c(C)cccc2C)CC1
+0,0,0,0,0,0,0,0,0,0,0,0,TOX3011,CCN(CC)S(=O)(=O)c1ccc(C(=O)O)cc1
+0,0,0,0,0,0,0,0,0,0,0,0,TOX22503,CCCCOC(CC)OC(C)COC(O)CC
+0,0,0,0,0,0,0,0,0,0,0,0,TOX2927,O=c1[nH]cnc2c1ncn2[C@H]1CC[C@@H](CO)O1
+0,0,0,0,1,1,0,,0,0,,0,TOX26553,C#C[C@]1(O)CC[C@H]2[C@@H]3CCc4cc(OC5CCCC5)ccc4[C@H]3CC[C@@]21C
+0,0,0,0,1,1,0,,0,,0,0,TOX26552,CC[C@H](C)[C@@H]1NC(=O)[C@H](Cc2ccc(O)cc2)NC(=O)[C@@H](N)CSSC[C@@H](C(=O)N2CCC[C@H]2C(=O)N[C@@H](CC(C)C)C(=O)NCC(N)=O)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CCC(N)=O)NC1=O
+0,0,0,0,0,0,0,,0,,0,0,TOX26084,C=CC1=C(C(=O)O)N2C(=O)[C@@H](NC(=O)/C(=N/O)c3csc(N)n3)[C@H]2SC1
+0,0,1,0,0,0,0,1,0,0,0,0,TOX985,O=[N+]([O-])c1cccc2cccnc12
+0,0,0,0,0,0,0,0,1,0,0,1,TOX634,O=c1[nH]cc(F)c(=O)[nH]1
+,,,,,,,0,,0,,,TOX26882,CCC(C)C(N)C(=O)O
+0,0,1,0,0,0,0,,0,0,0,0,TOX4102,CCOP(=O)(NC(C)C)Oc1ccc(SC)c(C)c1
+0,0,0,0,0,0,0,0,0,0,0,0,TOX4107,Cn1cc(-c2ccccc2)c(=O)c(-c2cccc(C(F)(F)F)c2)c1
+0,0,,,0,,0,0,0,0,,,TOX25863,CN1CCC(=C2c3ccccc3Sc3ccccc32)CC1
+0,0,0,0,0,0,0,,0,,0,0,TOX25344,CN(C)[C@@H]1C(O)=C(C(=O)NCN[C@@H](CCCCN)C(=O)O)C(=O)[C@@]2(O)C(O)=C3C(=O)c4c(O)cccc4[C@@](C)(O)C3C[C@@H]12
+0,0,0,0,1,0,0,,0,,0,0,TOX2624,CO[C@H]1[C@@H](O)[C@H](N)[C@@H](O[C@H]2O[C@H]([C@H](C)N)CC[C@H]2N)[C@H](O)[C@@H]1N(C)C(=O)CN
+1,1,0,0,1,1,0,0,0,,1,0,TOX2999,C[C@]12CC[C@@H]3c4ccc(O)cc4CC[C@H]3[C@@H]1CC[C@@H]2OC(=O)CCC1CCCC1
+0,0,1,,,0,0,1,0,0,1,1,TOX1716,Oc1c(Cl)cc(Cl)c(Cl)c1Cl
+0,0,0,1,,0,0,,0,0,1,,TOX12344,CCOP(=S)(OCC)OC(Cl)C(Cl)(Cl)Cl
+0,0,0,0,0,0,0,0,0,0,0,0,TOX25506,O=C(O)/C=C/c1ccc(Cn2ccnc2)cc1
+0,0,0,0,1,0,0,0,0,0,0,0,TOX3572,O=C(Oc1ccccc1C(=O)O)c1ccccc1O
+0,0,0,0,0,0,0,,0,0,0,0,TOX7007,CCC(=O)OC(=O)CC
+,,,,,,,0,,0,,,TOX4926,Nc1ccc(C=Cc2ccc(N)cc2S(=O)(=O)O)c(S(=O)(=O)O)c1
+0,0,0,0,0,0,0,0,0,0,0,0,TOX164,OCC(CO)(CBr)CBr
+0,0,0,0,0,0,0,1,0,0,0,0,TOX5570,CNC(=O)c1ccccc1
+0,0,0,0,0,0,0,0,0,0,0,0,TOX6872,CCCCN=C=O
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+0,0,0,0,0,0,0,0,0,0,0,0,TOX24591,CCCCN1C(=O)c2ccccc2C1=O
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+0,0,1,,1,1,0,,1,0,1,,TOX27863,CCCCCOC(=O)c1ccc(O)cc1
+1,1,0,0,1,1,0,1,0,0,0,0,TOX3380,C#C[C@]1(O)CC[C@H]2[C@@H]3CCC4=CC(=O)CC[C@@H]4[C@H]3CC[C@@]21C
+0,0,,0,0,0,0,0,0,0,,0,TOX6606,Cc1ccccc1NC(=N)Nc1ccccc1C
+,,,,,,,1,,0,,,TOX26531,OCc1ccccn1
+0,0,1,,1,,0,0,1,0,,0,TOX22622,Cn1ccc2cc3c(cc21)CCN3C(=O)Nc1cccnc1
+0,0,0,0,0,0,0,0,0,0,,0,TOX22190,CCCCCCCCCC[N+](C)(C)[O-]
+0,0,0,0,,0,0,0,0,0,0,0,TOX4123,COC(=O)C(C)Oc1ccc(Oc2ncc(C(F)(F)F)cc2Cl)cc1
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+0,0,0,,0,0,0,,0,0,,,TOX2810,CN(C)CC/C=C1\c2ccccc2Sc2ccc(Cl)cc21
+0,0,,0,0,0,0,,0,,1,0,TOX26637,O=C([O-])c1cc(O)c2c3nc4ccccc4oc-3cc(=O)c2n1
+0,0,0,,0,0,0,,0,0,0,0,TOX6049,C(=C\c1ccccc1)\c1ccccc1
+0,0,0,0,0,0,0,0,0,0,0,0,TOX5659,COC(=O)c1ccccc1O
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+0,0,0,0,0,0,0,0,0,0,0,0,TOX24929,CCCCCCCCCCCCSC
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+0,0,0,0,0,0,0,0,0,0,,0,TOX24925,O=C(C(=O)c1ccc(Br)cc1)c1ccc(Br)cc1
+0,0,0,0,0,0,0,0,0,0,0,0,TOX7397,CCCCCCCC/C=C\CCCCCCCC(=O)OC[C@@H](O)[C@H]1OC[C@H](O)[C@H]1O
+0,0,0,1,0,0,0,1,0,1,1,0,TOX3556,CC1=C(/C=C/C(C)=C/C=C/C(C)=C/CO)C(C)(C)CCC1
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+0,0,0,1,,,,1,0,0,0,0,TOX27272,Cc1nccn1-c1ccc(Sc2cccc(C3(C(N)=O)CCOCC3)c2)cc1
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+0,0,0,0,0,0,,,0,0,0,0,TOX21097,CCC(C)N(C)C(=O)c1cc2ccccc2c(-c2ccccc2Cl)n1
+0,0,1,,,0,0,1,0,0,,0,TOX28727,Cc1ccc(/C=N/n2c(-c3ccccc3)csc2=S)cc1
+0,0,1,,0,0,0,0,0,0,0,0,TOX8967,Clc1ccc(C(Cl)(Cl)Cl)cn1
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+0,0,0,0,0,0,0,0,0,0,0,0,TOX802,Nc1nc(N)nc(N)n1
+0,0,0,0,0,0,0,0,0,0,0,0,TOX809,O=S(=O)([O-])CCS
+0,0,0,0,0,0,0,,0,0,0,0,TOX26042,CCCCCCCCCCCCSCCOCCO
+0,0,0,0,0,0,0,0,0,0,,0,TOX1234,Cc1cc(C)c(S(=O)(=O)[O-])cc1N=Nc1cc(S(=O)(=O)[O-])c2ccccc2c1O
+0,0,0,,0,0,,,0,0,1,,TOX21778,CC(C)OC(=O)C(O)(c1ccc(Cl)cc1)c1ccc(Cl)cc1
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+0,0,1,0,,0,0,1,0,1,1,,TOX2837,Oc1c(I)cc(Cl)c2cccnc12
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+0,0,0,0,0,0,0,0,0,0,0,0,TOX3745,OC1OC[C@@H](O)[C@H](O)[C@H]1O
+,,0,0,,0,0,0,0,0,0,0,TOX4977,O=C(O)c1ccc(Cl)cc1Cl
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mol_moe/experts/mhg_model/__init__.py

@@ -0,0 +1,5 @@
+# -*- coding:utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#

mol_moe/experts/mhg_model/graph_grammar/__init__.py

@@ -0,0 +1,19 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES THE ORIGINAL SOURCE CODE (AND SOME ADAPTATIONS)
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE. 
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""
+
+""" Title """
+
+__author__ = "Hiroshi Kajino <[email protected]>"
+__copyright__ = "(c) Copyright IBM Corp. 2018"
+__version__ = "0.1"
+__date__ = "Jan 1 2018"
+

mol_moe/experts/mhg_model/graph_grammar/algo/__init__.py

@@ -0,0 +1,20 @@
+#!/usr/bin/env python
+# -*- coding:utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES THE ORIGINAL SOURCE CODE (AND SOME ADAPTATIONS)
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE. 
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""
+
+""" Title """
+
+__author__ = "Hiroshi Kajino <[email protected]>"
+__copyright__ = "(c) Copyright IBM Corp. 2018"
+__version__ = "0.1"
+__date__ = "Jan 1 2018"
+

mol_moe/experts/mhg_model/graph_grammar/algo/tree_decomposition.py

@@ -0,0 +1,821 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES THE ORIGINAL SOURCE CODE (AND SOME ADAPTATIONS)
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE. 
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""
+
+""" Title """
+
+__author__ = "Hiroshi Kajino <[email protected]>"
+__copyright__ = "(c) Copyright IBM Corp. 2017"
+__version__ = "0.1"
+__date__ = "Dec 11 2017"
+
+from copy import deepcopy
+from itertools import combinations
+from ..hypergraph import Hypergraph
+import networkx as nx
+import numpy as np
+
+
+class CliqueTree(nx.Graph):
+    ''' clique tree object
+
+    Attributes
+    ----------
+    hg : Hypergraph
+        This hypergraph will be decomposed.
+    root_hg : Hypergraph
+        Hypergraph on the root node.
+    ident_node_dict : dict
+        ident_node_dict[key_node] gives a list of nodes that are identical (i.e., the adjacent hyperedges are common)
+    '''
+    def __init__(self, hg=None, **kwargs):
+        self.hg = deepcopy(hg)
+        if self.hg is not None:
+            self.ident_node_dict = self.hg.get_identical_node_dict()
+        else:
+            self.ident_node_dict = {}
+        super().__init__(**kwargs)
+
+    @property
+    def root_hg(self):
+        ''' return the hypergraph on the root node
+        '''
+        return self.nodes[0]['subhg']
+
+    @root_hg.setter
+    def root_hg(self, hypergraph):
+        ''' set the hypergraph on the root node
+        '''
+        self.nodes[0]['subhg'] = hypergraph
+
+    def insert_subhg(self, subhypergraph: Hypergraph) -> None:
+        ''' insert a subhypergraph, which is extracted from a root hypergraph, into the tree.
+
+        Parameters
+        ----------
+        subhg : Hypergraph
+        '''
+        num_nodes = self.number_of_nodes()
+        self.add_node(num_nodes, subhg=subhypergraph)
+        self.add_edge(num_nodes, 0)
+        adj_nodes = deepcopy(list(self.adj[0].keys()))
+        for each_node in adj_nodes:
+            if len(self.nodes[each_node]["subhg"].nodes.intersection(
+                    self.nodes[num_nodes]["subhg"].nodes)\
+                   - self.root_hg.nodes) != 0 and each_node != num_nodes:
+                self.remove_edge(0, each_node)
+                self.add_edge(each_node, num_nodes)
+
+    def to_irredundant(self) -> None:
+        ''' convert the clique tree to be irredundant
+        '''
+        for each_node in self.hg.nodes:
+            subtree = self.subgraph([
+                each_tree_node for each_tree_node in self.nodes()\
+                if each_node in self.nodes[each_tree_node]["subhg"].nodes]).copy()
+            leaf_node_list = [x for x in subtree.nodes() if subtree.degree(x)==1]
+            redundant_leaf_node_list = []
+            for each_leaf_node in leaf_node_list:
+                if len(self.nodes[each_leaf_node]["subhg"].adj_edges(each_node)) == 0:
+                    redundant_leaf_node_list.append(each_leaf_node)
+            for each_red_leaf_node in redundant_leaf_node_list:
+                current_node = each_red_leaf_node
+                while subtree.degree(current_node) == 1 \
+                      and len(subtree.nodes[current_node]["subhg"].adj_edges(each_node)) == 0:
+                    self.nodes[current_node]["subhg"].remove_node(each_node)
+                    remove_node = current_node
+                    current_node = list(dict(subtree[remove_node]).keys())[0]
+                    subtree.remove_node(remove_node)
+
+        fixed_node_set = deepcopy(self.nodes)
+        for each_node in fixed_node_set:
+            if self.nodes[each_node]["subhg"].num_edges == 0:
+                if len(self[each_node]) == 1:
+                    self.remove_node(each_node)
+                elif len(self[each_node]) == 2:
+                    self.add_edge(*self[each_node])
+                    self.remove_node(each_node)
+                else:
+                    pass
+            else:
+                pass
+
+        redundant = True
+        while redundant:
+            redundant = False
+            fixed_edge_set = deepcopy(self.edges)
+            remove_node_set = set()
+            for node_1, node_2 in fixed_edge_set:
+                if node_1 in remove_node_set or node_2 in remove_node_set:
+                    pass
+                else:
+                    if self.nodes[node_1]['subhg'].is_subhg(self.nodes[node_2]['subhg']):
+                        redundant = True
+                        adj_node_list = set(self.adj[node_1]) - {node_2}
+                        self.remove_node(node_1)
+                        remove_node_set.add(node_1)
+                        for each_node in adj_node_list:
+                            self.add_edge(node_2, each_node)
+
+                    elif self.nodes[node_2]['subhg'].is_subhg(self.nodes[node_1]['subhg']):
+                        redundant = True
+                        adj_node_list = set(self.adj[node_2]) - {node_1}
+                        self.remove_node(node_2)
+                        remove_node_set.add(node_2)
+                        for each_node in adj_node_list:
+                            self.add_edge(node_1, each_node)
+
+    def node_update(self, key_node: str, subhg) -> None:
+        """ given a pair of a hypergraph, H, and its subhypergraph, sH, return a hypergraph H\sH.
+
+        Parameters
+        ----------
+        key_node : str
+            key node that must be removed.
+        subhg : Hypegraph
+        """
+        for each_edge in subhg.edges:
+            self.root_hg.remove_edge(each_edge)
+        self.root_hg.remove_nodes(self.ident_node_dict[key_node])
+
+        adj_node_list = list(subhg.nodes)
+        for each_node in subhg.nodes:
+            if each_node not in self.ident_node_dict[key_node]:
+                if set(self.root_hg.adj_edges(each_node)).issubset(subhg.edges):
+                    self.root_hg.remove_node(each_node)
+                    adj_node_list.remove(each_node)
+            else:
+                adj_node_list.remove(each_node)
+
+        for each_node_1, each_node_2 in combinations(adj_node_list, 2):
+            if not self.root_hg.is_adj(each_node_1, each_node_2):
+                self.root_hg.add_edge(set([each_node_1, each_node_2]), attr_dict=dict(tmp=True))
+        
+        subhg.remove_edges_with_attr({'tmp' : True})
+        self.insert_subhg(subhg)
+
+    def update(self, subhg, remove_nodes=False):
+        """ given a pair of a hypergraph, H, and its subhypergraph, sH, return a hypergraph H\sH.
+
+        Parameters
+        ----------
+        subhg : Hypegraph
+        """
+        for each_edge in subhg.edges:
+            self.root_hg.remove_edge(each_edge)
+        if remove_nodes:
+            remove_edge_list = []
+            for each_edge in self.root_hg.edges:
+                if set(self.root_hg.nodes_in_edge(each_edge)).issubset(subhg.nodes)\
+                   and self.root_hg.edge_attr(each_edge).get('tmp', False):
+                    remove_edge_list.append(each_edge)
+            self.root_hg.remove_edges(remove_edge_list)
+
+        adj_node_list = list(subhg.nodes)
+        for each_node in subhg.nodes:
+            if self.root_hg.degree(each_node) == 0:
+                self.root_hg.remove_node(each_node)
+                adj_node_list.remove(each_node)
+
+        if len(adj_node_list) != 1 and not remove_nodes:
+            self.root_hg.add_edge(set(adj_node_list), attr_dict=dict(tmp=True))
+        '''
+        else:
+            for each_node_1, each_node_2 in combinations(adj_node_list, 2):
+                if not self.root_hg.is_adj(each_node_1, each_node_2):
+                    self.root_hg.add_edge(
+                        [each_node_1, each_node_2], attr_dict=dict(tmp=True))
+        '''
+        subhg.remove_edges_with_attr({'tmp':True})
+        self.insert_subhg(subhg)
+
+
+def _get_min_deg_node(hg, ident_node_dict: dict, mode='mol'):
+    if mode == 'standard':
+        degree_dict = hg.degrees()
+        min_deg_node = min(degree_dict, key=degree_dict.get)
+        min_deg_subhg = hg.adj_subhg(min_deg_node, ident_node_dict)
+        return min_deg_node, min_deg_subhg
+    elif mode == 'mol':
+        degree_dict = hg.degrees()
+        min_deg = min(degree_dict.values())
+        min_deg_node_list = [each_node for each_node in hg.nodes if degree_dict[each_node]==min_deg]
+        min_deg_subhg_list = [hg.adj_subhg(each_min_deg_node, ident_node_dict)
+                              for each_min_deg_node in min_deg_node_list]
+        best_score = np.inf
+        best_idx = -1
+        for each_idx in range(len(min_deg_subhg_list)):
+            if min_deg_subhg_list[each_idx].num_nodes < best_score:
+                best_idx = each_idx
+        return min_deg_node_list[each_idx], min_deg_subhg_list[each_idx]
+    else:
+        raise ValueError
+
+
+def tree_decomposition(hg, irredundant=True):
+    """ compute a tree decomposition of the input hypergraph
+
+    Parameters
+    ----------
+    hg : Hypergraph
+        hypergraph to be decomposed
+    irredundant : bool
+        if True, irredundant tree decomposition will be computed.
+
+    Returns
+    -------
+    clique_tree : nx.Graph
+        each node contains a subhypergraph of `hg`
+    """
+    org_hg = hg.copy()
+    ident_node_dict = hg.get_identical_node_dict()
+    clique_tree = CliqueTree(org_hg)
+    clique_tree.add_node(0, subhg=org_hg)
+    while True:
+        degree_dict = org_hg.degrees()
+        min_deg_node = min(degree_dict, key=degree_dict.get)
+        min_deg_subhg = org_hg.adj_subhg(min_deg_node, ident_node_dict)
+        if org_hg.nodes == min_deg_subhg.nodes:
+            break
+
+        # org_hg and min_deg_subhg are divided
+        clique_tree.node_update(min_deg_node, min_deg_subhg)
+
+    clique_tree.root_hg.remove_edges_with_attr({'tmp' : True})
+
+    if irredundant:
+        clique_tree.to_irredundant()
+    return clique_tree
+
+
+def tree_decomposition_with_hrg(hg, hrg, irredundant=True, return_root=False):
+    ''' compute a tree decomposition given a hyperedge replacement grammar.
+    the resultant clique tree should induce a less compact HRG.
+    
+    Parameters
+    ----------
+    hg : Hypergraph
+        hypergraph to be decomposed
+    hrg : HyperedgeReplacementGrammar
+        current HRG
+    irredundant : bool
+        if True, irredundant tree decomposition will be computed.
+
+    Returns
+    -------
+    clique_tree : nx.Graph
+        each node contains a subhypergraph of `hg`
+    '''
+    org_hg = hg.copy()
+    ident_node_dict = hg.get_identical_node_dict()
+    clique_tree = CliqueTree(org_hg)
+    clique_tree.add_node(0, subhg=org_hg)
+    root_node = 0
+    
+    # construct a clique tree using HRG
+    success_any = True
+    while success_any:
+        success_any = False
+        for each_prod_rule in hrg.prod_rule_list:
+            org_hg, success, subhg = each_prod_rule.revert(org_hg, True)
+            if success:
+                if each_prod_rule.is_start_rule: root_node = clique_tree.number_of_nodes()
+                success_any = True
+                subhg.remove_edges_with_attr({'terminal' : False})
+                clique_tree.root_hg = org_hg
+                clique_tree.insert_subhg(subhg)
+    
+    clique_tree.root_hg = org_hg
+    
+    for each_edge in deepcopy(org_hg.edges):
+        if not org_hg.edge_attr(each_edge)['terminal']:
+            node_list = org_hg.nodes_in_edge(each_edge)
+            org_hg.remove_edge(each_edge)
+            
+            for each_node_1, each_node_2 in combinations(node_list, 2):
+                if not org_hg.is_adj(each_node_1, each_node_2):
+                    org_hg.add_edge([each_node_1, each_node_2], attr_dict=dict(tmp=True))
+
+    # construct a clique tree using the existing algorithm
+    degree_dict = org_hg.degrees()
+    if degree_dict:
+        while True:
+            min_deg_node, min_deg_subhg = _get_min_deg_node(org_hg, ident_node_dict)
+            if org_hg.nodes == min_deg_subhg.nodes: break
+
+            # org_hg and min_deg_subhg are divided
+            clique_tree.node_update(min_deg_node, min_deg_subhg)
+
+    clique_tree.root_hg.remove_edges_with_attr({'tmp' : True})
+    if irredundant:
+        clique_tree.to_irredundant()
+
+    if return_root:
+        if root_node == 0 and 0 not in clique_tree.nodes:
+            root_node = clique_tree.number_of_nodes()
+            while root_node not in clique_tree.nodes:
+                root_node -= 1
+        elif root_node not in clique_tree.nodes:
+            while root_node not in clique_tree.nodes:
+                root_node -= 1
+        else:
+            pass
+        return clique_tree, root_node
+    else:
+        return clique_tree
+
+
+def tree_decomposition_from_leaf(hg, irredundant=True):
+    """ compute a tree decomposition of the input hypergraph
+
+    Parameters
+    ----------
+    hg : Hypergraph
+        hypergraph to be decomposed
+    irredundant : bool
+        if True, irredundant tree decomposition will be computed.
+
+    Returns
+    -------
+    clique_tree : nx.Graph
+        each node contains a subhypergraph of `hg`
+    """
+    def apply_normal_decomposition(clique_tree):
+        degree_dict = clique_tree.root_hg.degrees()
+        min_deg_node = min(degree_dict, key=degree_dict.get)
+        min_deg_subhg = clique_tree.root_hg.adj_subhg(min_deg_node, clique_tree.ident_node_dict)
+        if clique_tree.root_hg.nodes == min_deg_subhg.nodes:
+            return clique_tree, False
+        clique_tree.node_update(min_deg_node, min_deg_subhg)
+        return clique_tree, True
+
+    def apply_min_edge_deg_decomposition(clique_tree):
+        edge_degree_dict = clique_tree.root_hg.edge_degrees()
+        non_tmp_edge_list = [each_edge for each_edge in clique_tree.root_hg.edges \
+                             if not clique_tree.root_hg.edge_attr(each_edge).get('tmp')]
+        if not non_tmp_edge_list:
+            return clique_tree, False
+        min_deg_edge = None
+        min_deg = np.inf
+        for each_edge in non_tmp_edge_list:
+            if min_deg > edge_degree_dict[each_edge]:
+                min_deg_edge = each_edge
+                min_deg = edge_degree_dict[each_edge]
+        node_list = clique_tree.root_hg.nodes_in_edge(min_deg_edge)
+        min_deg_subhg = clique_tree.root_hg.get_subhg(
+            node_list, [min_deg_edge], clique_tree.ident_node_dict)
+        if clique_tree.root_hg.nodes == min_deg_subhg.nodes:
+            return clique_tree, False
+        clique_tree.update(min_deg_subhg)
+        return clique_tree, True
+
+    org_hg = hg.copy()
+    clique_tree = CliqueTree(org_hg)
+    clique_tree.add_node(0, subhg=org_hg)
+
+    success = True
+    while success:
+        clique_tree, success = apply_min_edge_deg_decomposition(clique_tree)
+        if not success:
+            clique_tree, success = apply_normal_decomposition(clique_tree)
+
+    clique_tree.root_hg.remove_edges_with_attr({'tmp' : True})
+    if irredundant:
+        clique_tree.to_irredundant()
+    return clique_tree
+
+def topological_tree_decomposition(
+        hg, irredundant=True, rip_labels=True, shrink_cycle=False, contract_cycles=False):
+    ''' compute a tree decomposition of the input hypergraph
+
+    Parameters
+    ----------
+    hg : Hypergraph
+        hypergraph to be decomposed
+    irredundant : bool
+        if True, irredundant tree decomposition will be computed.
+
+    Returns
+    -------
+    clique_tree : CliqueTree
+        each node contains a subhypergraph of `hg`
+    '''
+    def _contract_tree(clique_tree):
+        ''' contract a single leaf
+
+        Parameters
+        ----------
+        clique_tree : CliqueTree
+
+        Returns
+        -------
+        CliqueTree, bool
+            bool represents whether this operation succeeds or not.
+        '''
+        edge_degree_dict = clique_tree.root_hg.edge_degrees()
+        leaf_edge_list = [each_edge for each_edge in clique_tree.root_hg.edges \
+                          if (not clique_tree.root_hg.edge_attr(each_edge).get('tmp'))\
+                          and edge_degree_dict[each_edge] == 1]
+        if not leaf_edge_list:
+            return clique_tree, False
+        min_deg_edge = leaf_edge_list[0]
+        node_list = clique_tree.root_hg.nodes_in_edge(min_deg_edge)
+        min_deg_subhg = clique_tree.root_hg.get_subhg(
+            node_list, [min_deg_edge], clique_tree.ident_node_dict)
+        if clique_tree.root_hg.nodes == min_deg_subhg.nodes:
+            return clique_tree, False
+        clique_tree.update(min_deg_subhg)
+        return clique_tree, True
+
+    def _rip_labels_from_cycles(clique_tree, org_hg):
+        ''' rip hyperedge-labels off
+
+        Parameters
+        ----------
+        clique_tree : CliqueTree
+        org_hg : Hypergraph
+
+        Returns
+        -------
+        CliqueTree, bool
+            bool represents whether this operation succeeds or not.
+        '''
+        ident_node_dict = clique_tree.ident_node_dict #hg.get_identical_node_dict()
+        for each_edge in clique_tree.root_hg.edges:
+            if each_edge in org_hg.edges:
+                if org_hg.in_cycle(each_edge):
+                    node_list = clique_tree.root_hg.nodes_in_edge(each_edge)
+                    subhg = clique_tree.root_hg.get_subhg(
+                        node_list, [each_edge], ident_node_dict)
+                    if clique_tree.root_hg.nodes == subhg.nodes:
+                        return clique_tree, False
+                    clique_tree.update(subhg)
+                    '''
+                    in_cycle_dict = {each_node: org_hg.node_attr(each_node)['is_in_ring'] for each_node in node_list}
+                    if not all(in_cycle_dict.values()):
+                        node_not_in_cycle = [each_node for each_node in in_cycle_dict.keys() if not in_cycle_dict[each_node]][0]
+                        node_list = [node_not_in_cycle]
+                        node_list.extend(clique_tree.root_hg.adj_nodes(node_not_in_cycle))
+                        edge_list = clique_tree.root_hg.adj_edges(node_not_in_cycle)
+                        import pdb; pdb.set_trace()
+                        subhg = clique_tree.root_hg.get_subhg(
+                            node_list, edge_list, ident_node_dict)
+                        
+                        clique_tree.update(subhg)
+                    '''
+                    return clique_tree, True
+        return clique_tree, False
+
+    def _shrink_cycle(clique_tree):
+        ''' shrink a cycle
+
+        Parameters
+        ----------
+        clique_tree : CliqueTree
+
+        Returns
+        -------
+        CliqueTree, bool
+            bool represents whether this operation succeeds or not.
+        '''
+        def filter_subhg(subhg, hg, key_node):
+            num_nodes_cycle = 0
+            nodes_in_cycle_list = []
+            for each_node in subhg.nodes:
+                if hg.in_cycle(each_node):
+                    num_nodes_cycle += 1
+                    if each_node != key_node:
+                        nodes_in_cycle_list.append(each_node)
+                if num_nodes_cycle > 3:
+                    break
+            if num_nodes_cycle != 3:
+                return False
+            else:
+                for each_edge in hg.edges:
+                    if set(nodes_in_cycle_list).issubset(hg.nodes_in_edge(each_edge)):
+                        return False
+                return True
+
+        #ident_node_dict = hg.get_identical_node_dict()
+        ident_node_dict = clique_tree.ident_node_dict
+        for each_node in clique_tree.root_hg.nodes:
+            if clique_tree.root_hg.in_cycle(each_node)\
+               and filter_subhg(clique_tree.root_hg.adj_subhg(each_node, ident_node_dict),
+                                clique_tree.root_hg,
+                                each_node):
+                target_node = each_node
+                target_subhg = clique_tree.root_hg.adj_subhg(target_node, ident_node_dict)
+                if clique_tree.root_hg.nodes == target_subhg.nodes:
+                    return clique_tree, False
+                clique_tree.update(target_subhg)
+                return clique_tree, True
+        return clique_tree, False
+
+    def _contract_cycles(clique_tree):
+        '''
+        remove a subhypergraph that looks like a cycle on a leaf.
+
+        Parameters
+        ----------
+        clique_tree : CliqueTree
+
+        Returns
+        -------
+        CliqueTree, bool
+            bool represents whether this operation succeeds or not.
+        '''
+        def _divide_hg(hg):
+            ''' divide a hypergraph into subhypergraphs such that
+            each subhypergraph is connected to each other in a tree-like way.
+
+            Parameters
+            ----------
+            hg : Hypergraph
+
+            Returns
+            -------
+            list of Hypergraphs
+                each element corresponds to a subhypergraph of `hg`
+            '''
+            for each_node in hg.nodes:
+                if hg.is_dividable(each_node):
+                    adj_edges_dict = {each_edge: hg.in_cycle(each_edge) for each_edge in hg.adj_edges(each_node)}
+                    '''
+                    if any(adj_edges_dict.values()):
+                        import pdb; pdb.set_trace()
+                        edge_in_cycle = [each_key for each_key, each_val in adj_edges_dict.items() if each_val][0]
+                        subhg1, subhg2, subhg3 = hg.divide(each_node, edge_in_cycle)
+                        return _divide_hg(subhg1) + _divide_hg(subhg2) + _divide_hg(subhg3)
+                    else:
+                    '''
+                    subhg1, subhg2 = hg.divide(each_node)
+                    return _divide_hg(subhg1) + _divide_hg(subhg2)
+            return [hg]
+
+        def _is_leaf(hg, divided_subhg) -> bool:
+            ''' judge whether subhg is a leaf-like in the original hypergraph
+
+            Parameters
+            ----------
+            hg : Hypergraph
+            divided_subhg : Hypergraph
+                `divided_subhg` is a subhypergraph of `hg`
+
+            Returns
+            -------
+            bool
+            '''
+            '''
+            adj_edges_set = set([])
+            for each_node in divided_subhg.nodes:
+                adj_edges_set.update(set(hg.adj_edges(each_node)))
+
+
+            _hg = deepcopy(hg)
+            _hg.remove_subhg(divided_subhg)
+            if nx.is_connected(_hg.hg) != (len(adj_edges_set - divided_subhg.edges) == 1):
+                import pdb; pdb.set_trace()
+            return len(adj_edges_set - divided_subhg.edges) == 1
+            '''
+            _hg = deepcopy(hg)
+            _hg.remove_subhg(divided_subhg)
+            return nx.is_connected(_hg.hg)
+        
+        subhg_list = _divide_hg(clique_tree.root_hg)
+        if len(subhg_list) == 1:
+            return clique_tree, False
+        else:
+            while len(subhg_list) > 1:
+                max_leaf_subhg = None
+                for each_subhg in subhg_list:
+                    if _is_leaf(clique_tree.root_hg, each_subhg):
+                        if max_leaf_subhg is None:
+                            max_leaf_subhg = each_subhg
+                        elif max_leaf_subhg.num_nodes < each_subhg.num_nodes:
+                            max_leaf_subhg = each_subhg
+                clique_tree.update(max_leaf_subhg)
+                subhg_list.remove(max_leaf_subhg)
+            return clique_tree, True
+
+    org_hg = hg.copy()
+    clique_tree = CliqueTree(org_hg)
+    clique_tree.add_node(0, subhg=org_hg)
+
+    success = True
+    while success:
+        '''
+        clique_tree, success = _rip_labels_from_cycles(clique_tree, hg)
+        if not success:
+            clique_tree, success = _contract_cycles(clique_tree)
+        '''
+        clique_tree, success = _contract_tree(clique_tree)
+        if not success:
+            if rip_labels:
+                clique_tree, success = _rip_labels_from_cycles(clique_tree, hg)
+            if not success:
+                if shrink_cycle:
+                    clique_tree, success = _shrink_cycle(clique_tree)
+                if not success:
+                    if contract_cycles:
+                        clique_tree, success = _contract_cycles(clique_tree)
+    clique_tree.root_hg.remove_edges_with_attr({'tmp' : True})
+    if irredundant:
+        clique_tree.to_irredundant()
+    return clique_tree
+
+def molecular_tree_decomposition(hg, irredundant=True):
+    """ compute a tree decomposition of the input molecular hypergraph
+
+    Parameters
+    ----------
+    hg : Hypergraph
+        molecular hypergraph to be decomposed
+    irredundant : bool
+        if True, irredundant tree decomposition will be computed.
+
+    Returns
+    -------
+    clique_tree : CliqueTree
+        each node contains a subhypergraph of `hg`
+    """
+    def _divide_hg(hg):
+        ''' divide a hypergraph into subhypergraphs such that
+        each subhypergraph is connected to each other in a tree-like way.
+
+        Parameters
+        ----------
+        hg : Hypergraph
+
+        Returns
+        -------
+        list of Hypergraphs
+            each element corresponds to a subhypergraph of `hg`
+        '''
+        is_ring = False
+        for each_node in hg.nodes:
+            if hg.node_attr(each_node)['is_in_ring']:
+                is_ring = True
+            if not hg.node_attr(each_node)['is_in_ring'] \
+               and hg.degree(each_node) == 2:
+                subhg1, subhg2 = hg.divide(each_node)
+                return _divide_hg(subhg1) + _divide_hg(subhg2)
+
+        if is_ring:
+            subhg_list = []
+            remove_edge_list = []
+            remove_node_list = []
+            for each_edge in hg.edges:
+                node_list = hg.nodes_in_edge(each_edge)
+                subhg = hg.get_subhg(node_list, [each_edge], hg.get_identical_node_dict())
+                subhg_list.append(subhg)
+                remove_edge_list.append(each_edge)
+                for each_node in node_list:
+                    if not hg.node_attr(each_node)['is_in_ring']:
+                        remove_node_list.append(each_node)
+            hg.remove_edges(remove_edge_list)
+            hg.remove_nodes(remove_node_list, False)
+            return subhg_list + [hg]
+        else:
+            return [hg]
+
+    org_hg = hg.copy()
+    clique_tree = CliqueTree(org_hg)
+    clique_tree.add_node(0, subhg=org_hg)
+
+    subhg_list = _divide_hg(deepcopy(clique_tree.root_hg))
+    #_subhg_list = deepcopy(subhg_list)
+    if len(subhg_list) == 1:
+        pass
+    else:
+        while len(subhg_list) > 1:
+            max_leaf_subhg = None
+            for each_subhg in subhg_list:
+                if _is_leaf(clique_tree.root_hg, each_subhg) and not _is_ring(each_subhg):
+                    if max_leaf_subhg is None:
+                        max_leaf_subhg = each_subhg
+                    elif max_leaf_subhg.num_nodes < each_subhg.num_nodes:
+                        max_leaf_subhg = each_subhg
+
+            if max_leaf_subhg is None:
+                for each_subhg in subhg_list:
+                    if _is_ring_label(clique_tree.root_hg, each_subhg):
+                        if max_leaf_subhg is None:
+                            max_leaf_subhg = each_subhg
+                        elif max_leaf_subhg.num_nodes < each_subhg.num_nodes:
+                            max_leaf_subhg = each_subhg
+            if max_leaf_subhg is not None:
+                clique_tree.update(max_leaf_subhg)
+                subhg_list.remove(max_leaf_subhg)
+            else:
+                for each_subhg in subhg_list:
+                    if _is_leaf(clique_tree.root_hg, each_subhg):
+                        if max_leaf_subhg is None:
+                            max_leaf_subhg = each_subhg
+                        elif max_leaf_subhg.num_nodes < each_subhg.num_nodes:
+                            max_leaf_subhg = each_subhg
+                if max_leaf_subhg is not None:
+                    clique_tree.update(max_leaf_subhg, True)
+                    subhg_list.remove(max_leaf_subhg)
+                else:
+                    break
+    if len(subhg_list) > 1:
+        '''
+        for each_idx, each_subhg in enumerate(subhg_list):
+            each_subhg.draw(f'{each_idx}', True)
+        clique_tree.root_hg.draw('root', True)
+        import pickle
+        with open('buggy_hg.pkl', 'wb') as f:
+            pickle.dump(hg, f)
+        return clique_tree, subhg_list, _subhg_list
+        '''
+        raise RuntimeError('bug in tree decomposition algorithm')
+    clique_tree.root_hg.remove_edges_with_attr({'tmp' : True})
+
+    '''
+    for each_tree_node in clique_tree.adj[0]:
+        subhg = clique_tree.nodes[each_tree_node]['subhg']
+        for each_edge in subhg.edges:
+            if set(subhg.nodes_in_edge(each_edge)).issubset(clique_tree.root_hg.nodes):
+                clique_tree.root_hg.add_edge(set(subhg.nodes_in_edge(each_edge)), attr_dict=dict(tmp=True))
+    '''
+    if irredundant:
+        clique_tree.to_irredundant()
+    return clique_tree #, _subhg_list
+
+def _is_leaf(hg, subhg) -> bool:
+    ''' judge whether subhg is a leaf-like in the original hypergraph
+
+    Parameters
+    ----------
+    hg : Hypergraph
+    subhg : Hypergraph
+        `subhg` is a subhypergraph of `hg`
+
+    Returns
+    -------
+    bool
+    '''
+    if len(subhg.edges) == 0:
+        adj_edge_set = set([])
+        subhg_edge_set = set([])
+        for each_edge in hg.edges:
+            if set(hg.nodes_in_edge(each_edge)).issubset(subhg.nodes) and hg.edge_attr(each_edge).get('tmp', False):
+                subhg_edge_set.add(each_edge)
+        for each_node in subhg.nodes:
+            adj_edge_set.update(set(hg.adj_edges(each_node)))
+        if subhg_edge_set.issubset(adj_edge_set) and len(adj_edge_set.difference(subhg_edge_set)) == 1:
+            return True
+        else:
+            return False
+    elif len(subhg.edges) == 1:
+        adj_edge_set = set([])
+        subhg_edge_set = subhg.edges
+        for each_node in subhg.nodes:
+            for each_adj_edge in hg.adj_edges(each_node):
+                adj_edge_set.add(each_adj_edge)
+        if subhg_edge_set.issubset(adj_edge_set) and len(adj_edge_set.difference(subhg_edge_set)) == 1:
+            return True
+        else:
+            return False
+    else:
+        raise ValueError('subhg should be nodes only or one-edge hypergraph.')
+
+def _is_ring_label(hg, subhg):
+    if len(subhg.edges) != 1:
+        return False
+    edge_name = list(subhg.edges)[0]
+    #assert edge_name in hg.edges, f'{edge_name}'
+    is_in_ring = False
+    for each_node in subhg.nodes:
+        if subhg.node_attr(each_node)['is_in_ring']:
+            is_in_ring = True
+        else:
+            adj_edge_list = list(hg.adj_edges(each_node))
+            adj_edge_list.remove(edge_name)
+            if len(adj_edge_list) == 1:
+                if not hg.edge_attr(adj_edge_list[0]).get('tmp', False):
+                    return False
+            elif len(adj_edge_list) == 0:
+                pass
+            else:
+                raise ValueError
+    if is_in_ring:
+        return True
+    else:
+        return False
+
+def _is_ring(hg):
+    for each_node in hg.nodes:
+        if not hg.node_attr(each_node)['is_in_ring']:
+            return False
+    return True        
+

mol_moe/experts/mhg_model/graph_grammar/graph_grammar/__init__.py

@@ -0,0 +1,20 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES THE ORIGINAL SOURCE CODE (AND SOME ADAPTATIONS)
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE. 
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""
+
+""" Title """
+
+__author__ = "Hiroshi Kajino <[email protected]>"
+__copyright__ = "(c) Copyright IBM Corp. 2018"
+__version__ = "0.1"
+__date__ = "Jan 1 2018"
+

mol_moe/experts/mhg_model/graph_grammar/graph_grammar/base.py

@@ -0,0 +1,30 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES THE ORIGINAL SOURCE CODE (AND SOME ADAPTATIONS)
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE. 
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""
+
+""" Title """
+
+__author__ = "Hiroshi Kajino <[email protected]>"
+__copyright__ = "(c) Copyright IBM Corp. 2017"
+__version__ = "0.1"
+__date__ = "Dec 11 2017"
+
+from abc import ABCMeta, abstractmethod
+
+class GraphGrammarBase(metaclass=ABCMeta):
+    @abstractmethod
+    def learn(self):
+        pass
+    
+    @abstractmethod
+    def sample(self):
+        pass

mol_moe/experts/mhg_model/graph_grammar/graph_grammar/corpus.py

@@ -0,0 +1,152 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES THE ORIGINAL SOURCE CODE (AND SOME ADAPTATIONS)
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE. 
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""
+
+""" Title """
+
+__author__ = "Hiroshi Kajino <[email protected]>"
+__copyright__ = "(c) Copyright IBM Corp. 2018"
+__version__ = "0.1"
+__date__ = "Jun 4 2018"
+
+from collections import Counter
+from functools import partial
+from .utils import _easy_node_match, _edge_match, _node_match, common_node_list, _node_match_prod_rule
+from networkx.algorithms.isomorphism import GraphMatcher
+import os
+
+
+class CliqueTreeCorpus(object):
+
+    ''' clique tree corpus
+
+    Attributes
+    ----------
+    clique_tree_list : list of CliqueTree
+    subhg_list : list of Hypergraph
+    '''
+
+    def __init__(self):
+        self.clique_tree_list = []
+        self.subhg_list = []
+
+    @property
+    def size(self):
+        return len(self.subhg_list)
+
+    def add_clique_tree(self, clique_tree):
+        for each_node in clique_tree.nodes:
+            subhg = clique_tree.nodes[each_node]['subhg']
+            subhg_idx = self.add_subhg(subhg)
+            clique_tree.nodes[each_node]['subhg_idx'] = subhg_idx
+        self.clique_tree_list.append(clique_tree)
+
+    def add_to_subhg_list(self, clique_tree, root_node):
+        parent_node_dict = {}
+        current_node = None
+        parent_node_dict[root_node] = None
+        stack = [root_node]
+        while stack:
+            current_node = stack.pop()
+            current_subhg = clique_tree.nodes[current_node]['subhg']
+            for each_child in clique_tree.adj[current_node]:
+                if each_child != parent_node_dict[current_node]:
+                    stack.append(each_child)
+                    parent_node_dict[each_child] = current_node
+            if parent_node_dict[current_node] is not None:
+                parent_subhg = clique_tree.nodes[parent_node_dict[current_node]]['subhg']
+                common, _ = common_node_list(parent_subhg, current_subhg)
+                parent_subhg.add_edge(set(common), attr_dict={'tmp': True})
+
+        parent_node_dict = {}
+        current_node = None
+        parent_node_dict[root_node] = None
+        stack = [root_node]
+        while stack:
+            current_node = stack.pop()
+            current_subhg = clique_tree.nodes[current_node]['subhg']
+            for each_child in clique_tree.adj[current_node]:
+                if each_child != parent_node_dict[current_node]:
+                    stack.append(each_child)
+                    parent_node_dict[each_child] = current_node
+            if parent_node_dict[current_node] is not None:
+                parent_subhg = clique_tree.nodes[parent_node_dict[current_node]]['subhg']
+                common, _ = common_node_list(parent_subhg, current_subhg)
+                for each_idx, each_node in enumerate(common):
+                    current_subhg.set_node_attr(each_node, {'ext_id': each_idx})
+
+            subhg_idx, is_new = self.add_subhg(current_subhg)
+            clique_tree.nodes[current_node]['subhg_idx'] = subhg_idx
+        return clique_tree
+
+    def add_subhg(self, subhg):
+        if len(self.subhg_list) == 0:
+            node_dict = {}
+            for each_node in subhg.nodes:
+                node_dict[each_node] = subhg.node_attr(each_node)['symbol'].__hash__()
+            node_list = []
+            for each_key, _ in sorted(node_dict.items(), key=lambda x:x[1]):
+                node_list.append(each_key)
+            for each_idx, each_node in enumerate(node_list):
+                subhg.node_attr(each_node)['order4hrg'] = each_idx
+            self.subhg_list.append(subhg)
+            return 0, True
+        else:
+            match = False
+            subhg_bond_symbol_counter \
+                = Counter([subhg.node_attr(each_node)['symbol'] \
+                           for each_node in subhg.nodes])
+            subhg_atom_symbol_counter \
+                = Counter([subhg.edge_attr(each_edge).get('symbol', None) \
+                           for each_edge in subhg.edges])
+            for each_idx, each_subhg in enumerate(self.subhg_list):
+                each_bond_symbol_counter \
+                    = Counter([each_subhg.node_attr(each_node)['symbol'] \
+                               for each_node in each_subhg.nodes])
+                each_atom_symbol_counter \
+                    = Counter([each_subhg.edge_attr(each_edge).get('symbol', None) \
+                               for each_edge in each_subhg.edges])
+                if not match \
+                   and (subhg.num_nodes == each_subhg.num_nodes
+                        and subhg.num_edges == each_subhg.num_edges
+                        and subhg_bond_symbol_counter == each_bond_symbol_counter
+                        and subhg_atom_symbol_counter == each_atom_symbol_counter):
+                    gm = GraphMatcher(each_subhg.hg,
+                                      subhg.hg,
+                                      node_match=_easy_node_match,
+                                      edge_match=_edge_match)
+                    try:
+                        isomap = next(gm.isomorphisms_iter())
+                        match = True
+                        for each_node in each_subhg.nodes:
+                            subhg.node_attr(isomap[each_node])['order4hrg'] \
+                                = each_subhg.node_attr(each_node)['order4hrg']
+                            if 'ext_id' in each_subhg.node_attr(each_node):
+                                subhg.node_attr(isomap[each_node])['ext_id'] \
+                                    = each_subhg.node_attr(each_node)['ext_id']
+                        return each_idx, False
+                    except StopIteration:
+                        match = False    
+            if not match:
+                node_dict = {}
+                for each_node in subhg.nodes:
+                    node_dict[each_node] = subhg.node_attr(each_node)['symbol'].__hash__()
+                node_list = []
+                for each_key, _ in sorted(node_dict.items(), key=lambda x:x[1]):
+                    node_list.append(each_key)
+                for each_idx, each_node in enumerate(node_list):
+                    subhg.node_attr(each_node)['order4hrg'] = each_idx
+
+                #for each_idx, each_node in enumerate(subhg.nodes):
+                #    subhg.node_attr(each_node)['order4hrg'] = each_idx
+                self.subhg_list.append(subhg)
+                return len(self.subhg_list) - 1, True

mol_moe/experts/mhg_model/graph_grammar/graph_grammar/hrg.py

@@ -0,0 +1,1065 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES THE ORIGINAL SOURCE CODE (AND SOME ADAPTATIONS)
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE. 
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""
+
+""" Title """
+
+__author__ = "Hiroshi Kajino <[email protected]>"
+__copyright__ = "(c) Copyright IBM Corp. 2017"
+__version__ = "0.1"
+__date__ = "Dec 11 2017"
+
+from .corpus import CliqueTreeCorpus
+from .base import GraphGrammarBase
+from .symbols import TSymbol, NTSymbol, BondSymbol
+from .utils import _node_match, _node_match_prod_rule, _edge_match, masked_softmax, common_node_list
+from ..hypergraph import Hypergraph
+from collections import Counter
+from copy import deepcopy
+from ..algo.tree_decomposition import (
+    tree_decomposition,
+    tree_decomposition_with_hrg,
+    tree_decomposition_from_leaf,
+    topological_tree_decomposition,
+    molecular_tree_decomposition)
+from functools import partial
+from networkx.algorithms.isomorphism import GraphMatcher
+from typing import List, Dict, Tuple
+import networkx as nx
+import numpy as np
+import torch
+import os
+import random
+
+DEBUG = False
+
+
+class ProductionRule(object):
+    """ A class of a production rule
+
+    Attributes
+    ----------
+    lhs : Hypergraph or None
+        the left hand side of the production rule.
+        if None, the rule is a starting rule.
+    rhs : Hypergraph
+        the right hand side of the production rule.
+    """
+    def __init__(self, lhs, rhs):
+        self.lhs = lhs
+        self.rhs = rhs
+
+    @property
+    def is_start_rule(self) -> bool:
+        return self.lhs.num_nodes == 0
+
+    @property
+    def ext_node(self) -> Dict[int, str]:
+        """ return a dict of external nodes
+        """
+        if self.is_start_rule:
+            return {}
+        else:
+            ext_node_dict = {}
+            for each_node in self.lhs.nodes:
+                ext_node_dict[self.lhs.node_attr(each_node)["ext_id"]] = each_node
+            return ext_node_dict
+
+    @property
+    def lhs_nt_symbol(self) -> NTSymbol:
+        if self.is_start_rule:
+            return NTSymbol(degree=0, is_aromatic=False, bond_symbol_list=[])
+        else:
+            return self.lhs.edge_attr(list(self.lhs.edges)[0])['symbol']
+
+    def rhs_adj_mat(self, node_edge_list):
+        ''' return the adjacency matrix of rhs of the production rule
+        '''
+        return nx.adjacency_matrix(self.rhs.hg, node_edge_list)
+        
+    def draw(self, file_path=None):
+        return self.rhs.draw(file_path)
+
+    def is_same(self, prod_rule, ignore_order=False):
+        """ judge whether this production rule is
+        the same as the input one, `prod_rule`
+
+        Parameters
+        ----------
+        prod_rule : ProductionRule
+            production rule to be compared
+
+        Returns
+        -------
+        is_same : bool
+        isomap : dict
+            isomorphism of nodes and hyperedges.
+            ex) {'bond_42': 'bond_37', 'bond_2': 'bond_1',
+                 'e36': 'e11', 'e16': 'e12', 'e25': 'e18',
+                 'bond_40': 'bond_38', 'e26': 'e21', 'bond_41': 'bond_39'}.
+            key comes from `prod_rule`, value comes from `self`.
+        """
+        if self.is_start_rule:
+            if not prod_rule.is_start_rule:
+                return False, {}
+        else:
+            if prod_rule.is_start_rule:
+                return False, {}
+            else:
+                if prod_rule.lhs.num_nodes != self.lhs.num_nodes:
+                    return False, {}
+
+        if prod_rule.rhs.num_nodes != self.rhs.num_nodes:
+            return False, {}
+        if prod_rule.rhs.num_edges != self.rhs.num_edges:
+            return False, {}
+
+        subhg_bond_symbol_counter \
+            = Counter([prod_rule.rhs.node_attr(each_node)['symbol'] \
+                       for each_node in prod_rule.rhs.nodes])
+        each_bond_symbol_counter \
+            = Counter([self.rhs.node_attr(each_node)['symbol'] \
+                       for each_node in self.rhs.nodes])
+        if subhg_bond_symbol_counter != each_bond_symbol_counter:
+            return False, {}
+
+        subhg_atom_symbol_counter \
+            = Counter([prod_rule.rhs.edge_attr(each_edge)['symbol'] \
+                       for each_edge in prod_rule.rhs.edges])
+        each_atom_symbol_counter \
+            = Counter([self.rhs.edge_attr(each_edge)['symbol'] \
+                       for each_edge in self.rhs.edges])
+        if subhg_atom_symbol_counter != each_atom_symbol_counter:
+            return False, {}
+
+        gm = GraphMatcher(prod_rule.rhs.hg,
+                          self.rhs.hg,
+                          partial(_node_match_prod_rule,
+                                  ignore_order=ignore_order),
+                          partial(_edge_match,
+                                  ignore_order=ignore_order))
+        try:
+            return True, next(gm.isomorphisms_iter())
+        except StopIteration:
+            return False, {}
+
+    def applied_to(self,
+                   hg: Hypergraph,
+                   edge: str) -> Tuple[Hypergraph, List[str]]:
+        """ augment `hg` by replacing `edge` with `self.rhs`.
+
+        Parameters
+        ----------
+        hg : Hypergraph
+        edge : str
+            `edge` must belong to `hg`
+
+        Returns
+        -------
+        hg : Hypergraph
+            resultant hypergraph
+        nt_edge_list : list
+            list of non-terminal edges
+        """
+        nt_edge_dict = {}
+        if self.is_start_rule:
+            if (edge is not None) or (hg is not None):
+                ValueError("edge and hg must be None for this prod rule.")
+            hg = Hypergraph()
+            node_map_rhs = {} # node id in rhs -> node id in hg, where rhs is augmented.
+            for num_idx, each_node in enumerate(self.rhs.nodes):
+                hg.add_node(f"bond_{num_idx}",
+                            #attr_dict=deepcopy(self.rhs.node_attr(each_node)))
+                            attr_dict=self.rhs.node_attr(each_node))
+                node_map_rhs[each_node] = f"bond_{num_idx}"
+            for each_edge in self.rhs.edges:
+                node_list = []
+                for each_node in self.rhs.nodes_in_edge(each_edge):
+                    node_list.append(node_map_rhs[each_node])
+                if isinstance(self.rhs.nodes_in_edge(each_edge), set):
+                    node_list = set(node_list)
+                edge_id = hg.add_edge(
+                    node_list,
+                    #attr_dict=deepcopy(self.rhs.edge_attr(each_edge)))
+                    attr_dict=self.rhs.edge_attr(each_edge))
+                if "nt_idx" in hg.edge_attr(edge_id):
+                    nt_edge_dict[hg.edge_attr(edge_id)["nt_idx"]] = edge_id
+            nt_edge_list = [nt_edge_dict[key] for key in range(len(nt_edge_dict))]
+            return hg, nt_edge_list
+        else:
+            if edge not in hg.edges:
+                raise ValueError("the input hyperedge does not exist.")
+            if hg.edge_attr(edge)["terminal"]:
+                raise ValueError("the input hyperedge is terminal.")
+            if hg.edge_attr(edge)['symbol'] != self.lhs_nt_symbol:
+                print(hg.edge_attr(edge)['symbol'], self.lhs_nt_symbol)
+                raise ValueError("the input hyperedge and lhs have inconsistent number of nodes.")
+            if DEBUG:
+                for node_idx, each_node in enumerate(hg.nodes_in_edge(edge)):
+                    other_node = self.lhs.nodes_in_edge(list(self.lhs.edges)[0])[node_idx]
+                    attr = deepcopy(self.lhs.node_attr(other_node))
+                    attr.pop('ext_id')
+                    if hg.node_attr(each_node) != attr:
+                        raise ValueError('node attributes are inconsistent.')
+
+            # order of nodes that belong to the non-terminal edge in hg
+            nt_order_dict = {}  # hg_node -> order ("bond_17" : 1)
+            nt_order_dict_inv = {} # order -> hg_node
+            for each_idx, each_node in enumerate(hg.nodes_in_edge(edge)):
+                nt_order_dict[each_node] = each_idx
+                nt_order_dict_inv[each_idx] = each_node
+
+            # construct a node_map_rhs: rhs -> new hg
+            node_map_rhs = {} # node id in rhs -> node id in hg, where rhs is augmented.
+            node_idx = hg.num_nodes
+            for each_node in self.rhs.nodes:
+                if "ext_id" in self.rhs.node_attr(each_node):
+                    node_map_rhs[each_node] \
+                        = nt_order_dict_inv[
+                            self.rhs.node_attr(each_node)["ext_id"]]
+                else:
+                    node_map_rhs[each_node] = f"bond_{node_idx}"
+                    node_idx += 1
+
+            # delete non-terminal
+            hg.remove_edge(edge)
+
+            # add nodes to hg
+            for each_node in self.rhs.nodes:
+                hg.add_node(node_map_rhs[each_node],
+                            attr_dict=self.rhs.node_attr(each_node))
+
+            # add hyperedges to hg
+            for each_edge in self.rhs.edges:
+                node_list_hg = []
+                for each_node in self.rhs.nodes_in_edge(each_edge):
+                    node_list_hg.append(node_map_rhs[each_node])
+                edge_id = hg.add_edge(
+                    node_list_hg,
+                    attr_dict=self.rhs.edge_attr(each_edge))#deepcopy(self.rhs.edge_attr(each_edge)))
+                if "nt_idx" in hg.edge_attr(edge_id):
+                    nt_edge_dict[hg.edge_attr(edge_id)["nt_idx"]] = edge_id
+            nt_edge_list = [nt_edge_dict[key] for key in range(len(nt_edge_dict))]
+            return hg, nt_edge_list
+
+    def revert(self, hg: Hypergraph, return_subhg=False):
+        ''' revert applying this production rule.
+        i.e., if there exists a subhypergraph that matches the r.h.s. of this production rule,
+        this method replaces the subhypergraph with a non-terminal hyperedge.
+
+        Parameters
+        ----------
+        hg : Hypergraph
+            hypergraph to be reverted
+        return_subhg : bool
+            if True, the removed subhypergraph will be returned.
+
+        Returns
+        -------
+        hg : Hypergraph
+            the resultant hypergraph. if it cannot be reverted, the original one is returned without any replacement.
+        success : bool
+            this indicates whether reverting is successed or not.
+        '''
+        gm = GraphMatcher(hg.hg, self.rhs.hg, node_match=_node_match_prod_rule,
+                          edge_match=_edge_match)
+        try:
+            # in case when the matched subhg is connected to the other part via external nodes and more.
+            not_iso = True
+            while not_iso:
+                isomap = next(gm.subgraph_isomorphisms_iter())
+                adj_node_set = set([]) # reachable nodes from the internal nodes
+                subhg_node_set = set(isomap.keys()) # nodes in subhg
+                for each_node in subhg_node_set:
+                    adj_node_set.add(each_node)
+                    if isomap[each_node] not in self.ext_node.values():
+                        adj_node_set.update(hg.hg.adj[each_node])
+                if adj_node_set == subhg_node_set:
+                    not_iso = False
+                else:
+                    if return_subhg:
+                        return hg, False, Hypergraph()
+                    else:
+                        return hg, False
+            inv_isomap = {v: k for k, v in isomap.items()}
+            '''
+            isomap = {'e35': 'e8', 'bond_13': 'bond_18', 'bond_14': 'bond_19',
+                      'bond_15': 'bond_17', 'e29': 'e23', 'bond_12': 'bond_20'}
+            where keys come from `hg` and values come from `self.rhs`
+            '''
+        except StopIteration:
+            if return_subhg:
+                return hg, False, Hypergraph()
+            else:
+                return hg, False
+
+        if return_subhg:
+            subhg = Hypergraph()
+            for each_node in hg.nodes:
+                if each_node in isomap:
+                    subhg.add_node(each_node, attr_dict=hg.node_attr(each_node))
+            for each_edge in hg.edges:
+                if each_edge in isomap:
+                    subhg.add_edge(hg.nodes_in_edge(each_edge),
+                                   attr_dict=hg.edge_attr(each_edge),
+                                   edge_name=each_edge)
+            subhg.edge_idx = hg.edge_idx
+
+        # remove subhg except for the externael nodes
+        for each_key, each_val in isomap.items():
+            if each_key.startswith('e'):
+                hg.remove_edge(each_key)
+        for each_key, each_val in isomap.items():
+            if each_key.startswith('bond_'):
+                if each_val not in self.ext_node.values():
+                    hg.remove_node(each_key)
+
+        # add non-terminal hyperedge
+        nt_node_list = []
+        for each_ext_id in self.ext_node.keys():
+            nt_node_list.append(inv_isomap[self.ext_node[each_ext_id]])
+
+        hg.add_edge(nt_node_list,
+                    attr_dict=dict(
+                        terminal=False,
+                        symbol=self.lhs_nt_symbol))
+        if return_subhg:
+            return hg, True, subhg
+        else:
+            return hg, True
+
+
+class ProductionRuleCorpus(object):
+
+    '''
+    A corpus of production rules.
+    This class maintains 
+        (i) list of unique production rules,
+        (ii) list of unique edge symbols (both terminal and non-terminal), and
+        (iii) list of unique node symbols.
+
+    Attributes
+    ----------
+    prod_rule_list : list
+        list of unique production rules
+    edge_symbol_list : list
+        list of unique symbols (including both terminal and non-terminal)
+    node_symbol_list : list
+        list of node symbols
+    nt_symbol_list : list
+        list of unique lhs symbols
+    ext_id_list : list
+        list of ext_ids
+    lhs_in_prod_rule : array
+        a matrix of lhs vs prod_rule (= lhs_in_prod_rule)
+    '''
+
+    def __init__(self):
+        self.prod_rule_list = []
+        self.edge_symbol_list = []
+        self.edge_symbol_dict = {}
+        self.node_symbol_list = []
+        self.node_symbol_dict = {}
+        self.nt_symbol_list = []
+        self.ext_id_list = []
+        self._lhs_in_prod_rule = None
+        self.lhs_in_prod_rule_row_list = []
+        self.lhs_in_prod_rule_col_list = []
+
+    @property
+    def lhs_in_prod_rule(self):
+        if self._lhs_in_prod_rule is None:
+            self._lhs_in_prod_rule = torch.sparse.FloatTensor(
+                torch.LongTensor(list(zip(self.lhs_in_prod_rule_row_list, self.lhs_in_prod_rule_col_list))).t(),
+                torch.FloatTensor([1.0]*len(self.lhs_in_prod_rule_col_list)),
+                torch.Size([len(self.nt_symbol_list), len(self.prod_rule_list)])
+            ).to_dense()
+        return self._lhs_in_prod_rule
+        
+    @property
+    def num_prod_rule(self):
+        ''' return the number of production rules
+
+        Returns
+        -------
+        int : the number of unique production rules
+        '''
+        return len(self.prod_rule_list)
+
+    @property
+    def start_rule_list(self):
+        ''' return a list of start rules
+
+        Returns
+        -------
+        list : list of start rules
+        '''
+        start_rule_list = []
+        for each_prod_rule in self.prod_rule_list:
+            if each_prod_rule.is_start_rule:
+                start_rule_list.append(each_prod_rule)
+        return start_rule_list
+
+    @property
+    def num_edge_symbol(self):
+        return len(self.edge_symbol_list)
+
+    @property
+    def num_node_symbol(self):
+        return len(self.node_symbol_list)
+
+    @property
+    def num_ext_id(self):
+        return len(self.ext_id_list)
+
+    def construct_feature_vectors(self):
+        ''' this method constructs feature vectors for the production rules collected so far.
+        currently, NTSymbol and TSymbol are treated in the same manner.
+        '''
+        feature_id_dict = {}
+        feature_id_dict['TSymbol'] = 0
+        feature_id_dict['NTSymbol'] = 1
+        feature_id_dict['BondSymbol'] = 2
+        for each_edge_symbol in self.edge_symbol_list:
+            for each_attr in each_edge_symbol.__dict__.keys():
+                each_val = each_edge_symbol.__dict__[each_attr]
+                if isinstance(each_val, list):
+                    each_val = tuple(each_val)
+                if (each_attr, each_val) not in feature_id_dict:
+                    feature_id_dict[(each_attr, each_val)] = len(feature_id_dict)
+
+        for each_node_symbol in self.node_symbol_list:
+            for each_attr in each_node_symbol.__dict__.keys():
+                each_val = each_node_symbol.__dict__[each_attr]
+                if isinstance(each_val, list):
+                    each_val = tuple(each_val)
+                if (each_attr, each_val) not in feature_id_dict:
+                    feature_id_dict[(each_attr, each_val)] = len(feature_id_dict)
+        for each_ext_id in self.ext_id_list:
+            feature_id_dict[('ext_id', each_ext_id)] = len(feature_id_dict)
+        dim = len(feature_id_dict)
+
+        feature_dict = {}
+        for each_edge_symbol in self.edge_symbol_list:
+            idx_list = []
+            idx_list.append(feature_id_dict[each_edge_symbol.__class__.__name__])
+            for each_attr in each_edge_symbol.__dict__.keys():
+                each_val = each_edge_symbol.__dict__[each_attr]
+                if isinstance(each_val, list):
+                    each_val = tuple(each_val)
+                idx_list.append(feature_id_dict[(each_attr, each_val)])
+            feature = torch.sparse.LongTensor(
+                torch.LongTensor([idx_list]),
+                torch.ones(len(idx_list)),
+                torch.Size([len(feature_id_dict)])
+            )
+            feature_dict[each_edge_symbol] = feature
+
+        for each_node_symbol in self.node_symbol_list:
+            idx_list = []
+            idx_list.append(feature_id_dict[each_node_symbol.__class__.__name__])
+            for each_attr in each_node_symbol.__dict__.keys():
+                each_val = each_node_symbol.__dict__[each_attr]
+                if isinstance(each_val, list):
+                    each_val = tuple(each_val)
+                idx_list.append(feature_id_dict[(each_attr, each_val)])
+            feature = torch.sparse.LongTensor(
+                torch.LongTensor([idx_list]),
+                torch.ones(len(idx_list)),
+                torch.Size([len(feature_id_dict)])
+            )
+            feature_dict[each_node_symbol] = feature
+        for each_ext_id in self.ext_id_list:
+            idx_list = [feature_id_dict[('ext_id', each_ext_id)]]
+            feature_dict[('ext_id', each_ext_id)] \
+                = torch.sparse.LongTensor(
+                    torch.LongTensor([idx_list]),
+                    torch.ones(len(idx_list)),
+                    torch.Size([len(feature_id_dict)])
+                )
+        return feature_dict, dim
+
+    def edge_symbol_idx(self, symbol):
+        return self.edge_symbol_dict[symbol]
+
+    def node_symbol_idx(self, symbol):
+        return self.node_symbol_dict[symbol]
+
+    def append(self, prod_rule: ProductionRule) -> Tuple[int, ProductionRule]:
+        """ return whether the input production rule is new or not, and its production rule id.
+        Production rules are regarded as the same if 
+            i) there exists a one-to-one mapping of nodes and edges, and
+            ii) all the attributes associated with nodes and hyperedges are the same.
+
+        Parameters
+        ----------
+        prod_rule : ProductionRule
+
+        Returns
+        -------
+        prod_rule_id : int
+            production rule index. if new, a new index will be assigned.
+        prod_rule : ProductionRule
+        """
+        num_lhs = len(self.nt_symbol_list)
+        for each_idx, each_prod_rule in enumerate(self.prod_rule_list):
+            is_same, isomap = prod_rule.is_same(each_prod_rule)
+            if is_same:
+                # we do not care about edge and node names, but care about the order of non-terminal edges.
+                for key, val in isomap.items(): # key : edges & nodes in each_prod_rule.rhs , val : those in prod_rule.rhs
+                    if key.startswith("bond_"):
+                        continue
+
+                    # rewrite `nt_idx` in `prod_rule` for further processing
+                    if "nt_idx" in prod_rule.rhs.edge_attr(val).keys():
+                        if "nt_idx" not in each_prod_rule.rhs.edge_attr(key).keys():
+                            raise ValueError
+                        prod_rule.rhs.set_edge_attr(
+                            val,
+                            {'nt_idx': each_prod_rule.rhs.edge_attr(key)["nt_idx"]})
+                return each_idx, prod_rule
+        self.prod_rule_list.append(prod_rule)
+        self._update_edge_symbol_list(prod_rule)
+        self._update_node_symbol_list(prod_rule)
+        self._update_ext_id_list(prod_rule)
+
+        lhs_idx = self.nt_symbol_list.index(prod_rule.lhs_nt_symbol)
+        self.lhs_in_prod_rule_row_list.append(lhs_idx)
+        self.lhs_in_prod_rule_col_list.append(len(self.prod_rule_list)-1)
+        self._lhs_in_prod_rule = None
+        return len(self.prod_rule_list)-1, prod_rule
+
+    def get_prod_rule(self, prod_rule_idx: int) -> ProductionRule:
+        return self.prod_rule_list[prod_rule_idx]
+
+    def sample(self, unmasked_logit_array, nt_symbol, deterministic=False):
+        ''' sample a production rule whose lhs is `nt_symbol`, followihng `unmasked_logit_array`.
+
+        Parameters
+        ----------
+        unmasked_logit_array : array-like, length `num_prod_rule`
+        nt_symbol : NTSymbol
+        '''
+        if not isinstance(unmasked_logit_array, np.ndarray):
+            unmasked_logit_array = unmasked_logit_array.numpy().astype(np.float64)
+        if deterministic:
+            prob = masked_softmax(unmasked_logit_array,
+                                  self.lhs_in_prod_rule[self.nt_symbol_list.index(nt_symbol)].numpy().astype(np.float64))
+            return self.prod_rule_list[np.argmax(prob)]
+        else:
+            return np.random.choice(
+                self.prod_rule_list, 1,
+                p=masked_softmax(unmasked_logit_array,
+                                 self.lhs_in_prod_rule[self.nt_symbol_list.index(nt_symbol)].numpy().astype(np.float64)))[0]
+
+    def masked_logprob(self, unmasked_logit_array, nt_symbol):
+        if not isinstance(unmasked_logit_array, np.ndarray):
+            unmasked_logit_array = unmasked_logit_array.numpy().astype(np.float64)
+        prob = masked_softmax(unmasked_logit_array,
+                              self.lhs_in_prod_rule[self.nt_symbol_list.index(nt_symbol)].numpy().astype(np.float64))
+        return np.log(prob)
+
+    def _update_edge_symbol_list(self, prod_rule: ProductionRule):
+        ''' update edge symbol list
+
+        Parameters
+        ----------
+        prod_rule : ProductionRule
+        '''
+        if prod_rule.lhs_nt_symbol not in self.nt_symbol_list:
+            self.nt_symbol_list.append(prod_rule.lhs_nt_symbol)
+
+        for each_edge in prod_rule.rhs.edges:
+            if prod_rule.rhs.edge_attr(each_edge)['symbol'] not in self.edge_symbol_dict:
+                edge_symbol_idx = len(self.edge_symbol_list)
+                self.edge_symbol_list.append(prod_rule.rhs.edge_attr(each_edge)['symbol'])
+                self.edge_symbol_dict[prod_rule.rhs.edge_attr(each_edge)['symbol']] = edge_symbol_idx
+            else:
+                edge_symbol_idx = self.edge_symbol_dict[prod_rule.rhs.edge_attr(each_edge)['symbol']]
+            prod_rule.rhs.edge_attr(each_edge)['symbol_idx'] = edge_symbol_idx
+        pass
+
+    def _update_node_symbol_list(self, prod_rule: ProductionRule):
+        ''' update node symbol list
+
+        Parameters
+        ----------
+        prod_rule : ProductionRule
+        '''
+        for each_node in prod_rule.rhs.nodes:
+            if prod_rule.rhs.node_attr(each_node)['symbol'] not in self.node_symbol_dict:
+                node_symbol_idx = len(self.node_symbol_list)
+                self.node_symbol_list.append(prod_rule.rhs.node_attr(each_node)['symbol'])
+                self.node_symbol_dict[prod_rule.rhs.node_attr(each_node)['symbol']] = node_symbol_idx
+            else:
+                node_symbol_idx = self.node_symbol_dict[prod_rule.rhs.node_attr(each_node)['symbol']]
+            prod_rule.rhs.node_attr(each_node)['symbol_idx'] = node_symbol_idx
+
+    def _update_ext_id_list(self, prod_rule: ProductionRule):
+        for each_node in prod_rule.rhs.nodes:
+            if 'ext_id' in prod_rule.rhs.node_attr(each_node):
+                if prod_rule.rhs.node_attr(each_node)['ext_id'] not in self.ext_id_list:
+                    self.ext_id_list.append(prod_rule.rhs.node_attr(each_node)['ext_id'])
+
+
+class HyperedgeReplacementGrammar(GraphGrammarBase):
+    """
+    Learn a hyperedge replacement grammar from a set of hypergraphs.
+
+    Attributes
+    ----------
+    prod_rule_list : list of ProductionRule
+        production rules learned from the input hypergraphs
+    """
+    def __init__(self,
+                 tree_decomposition=molecular_tree_decomposition,
+                 ignore_order=False, **kwargs):
+        from functools import partial
+        self.prod_rule_corpus = ProductionRuleCorpus()
+        self.clique_tree_corpus = CliqueTreeCorpus()
+        self.ignore_order = ignore_order
+        self.tree_decomposition = partial(tree_decomposition, **kwargs)
+
+    @property
+    def num_prod_rule(self):
+        ''' return the number of production rules
+
+        Returns
+        -------
+        int : the number of unique production rules
+        '''
+        return self.prod_rule_corpus.num_prod_rule
+
+    @property
+    def start_rule_list(self):
+        ''' return a list of start rules
+
+        Returns
+        -------
+        list : list of start rules
+        '''
+        return self.prod_rule_corpus.start_rule_list
+
+    @property
+    def prod_rule_list(self):
+        return self.prod_rule_corpus.prod_rule_list
+
+    def learn(self, hg_list, logger=print, max_mol=np.inf, print_freq=500):
+        """ learn from a list of hypergraphs
+
+        Parameters
+        ----------
+        hg_list : list of Hypergraph
+
+        Returns
+        -------
+        prod_rule_seq_list : list of integers
+            each element corresponds to a sequence of production rules to generate each hypergraph.
+        """
+        prod_rule_seq_list = []
+        idx = 0
+        for each_idx, each_hg in enumerate(hg_list):
+            clique_tree = self.tree_decomposition(each_hg)
+
+            # get a pair of myself and children
+            root_node = _find_root(clique_tree)
+            clique_tree = self.clique_tree_corpus.add_to_subhg_list(clique_tree, root_node)
+            prod_rule_seq = []
+            stack = []
+
+            children = sorted(list(clique_tree[root_node].keys()))
+
+            # extract a temporary production rule
+            prod_rule = extract_prod_rule(
+                None,
+                clique_tree.nodes[root_node]["subhg"],
+                [clique_tree.nodes[each_child]["subhg"]
+                 for each_child in children],
+                clique_tree.nodes[root_node].get('subhg_idx', None))
+
+            # update the production rule list
+            prod_rule_id, prod_rule = self.update_prod_rule_list(prod_rule)
+            children = reorder_children(root_node,
+                                        children,
+                                        prod_rule,
+                                        clique_tree)
+            stack.extend([(root_node, each_child) for each_child in children[::-1]])
+            prod_rule_seq.append(prod_rule_id)
+
+            while len(stack) != 0:
+                # get a triple of parent, myself, and children
+                parent, myself = stack.pop()
+                children = sorted(list(dict(clique_tree[myself]).keys()))
+                children.remove(parent)
+
+                # extract a temp prod rule
+                prod_rule = extract_prod_rule(
+                    clique_tree.nodes[parent]["subhg"],
+                    clique_tree.nodes[myself]["subhg"],
+                    [clique_tree.nodes[each_child]["subhg"]
+                     for each_child in children],
+                    clique_tree.nodes[myself].get('subhg_idx', None))
+
+                # update the prod rule list
+                prod_rule_id, prod_rule = self.update_prod_rule_list(prod_rule)
+                children = reorder_children(myself,
+                                            children,
+                                            prod_rule,
+                                            clique_tree)
+                stack.extend([(myself, each_child)
+                              for each_child in children[::-1]])
+                prod_rule_seq.append(prod_rule_id)
+            prod_rule_seq_list.append(prod_rule_seq)
+            if (each_idx+1) % print_freq == 0:
+                msg = f'#(molecules processed)={each_idx+1}\t'\
+                        f'#(production rules)={self.prod_rule_corpus.num_prod_rule}\t#(subhg in corpus)={self.clique_tree_corpus.size}'
+                logger(msg)
+            if each_idx > max_mol:
+                break
+
+        print(f'corpus_size = {self.clique_tree_corpus.size}')
+        return prod_rule_seq_list
+
+    def sample(self, z, deterministic=False):
+        """ sample a new hypergraph from HRG.
+
+        Parameters
+        ----------
+        z : array-like, shape (len, num_prod_rule)
+            logit
+        deterministic : bool
+            if True, deterministic sampling
+
+        Returns
+        -------
+        Hypergraph
+        """
+        seq_idx = 0
+        stack = []
+        z = z[:, :-1]
+        init_prod_rule = self.prod_rule_corpus.sample(z[0], NTSymbol(degree=0,
+                                                                     is_aromatic=False,
+                                                                     bond_symbol_list=[]),
+                                                      deterministic=deterministic)
+        hg, nt_edge_list = init_prod_rule.applied_to(None, None)
+        stack = deepcopy(nt_edge_list[::-1])
+        while len(stack) != 0 and seq_idx < z.shape[0]-1:
+            seq_idx += 1
+            nt_edge = stack.pop()
+            nt_symbol = hg.edge_attr(nt_edge)['symbol']
+            prod_rule = self.prod_rule_corpus.sample(z[seq_idx], nt_symbol, deterministic=deterministic)
+            hg, nt_edge_list = prod_rule.applied_to(hg, nt_edge)
+            stack.extend(nt_edge_list[::-1])
+        if len(stack) != 0:
+            raise RuntimeError(f'{len(stack)} non-terminals are left.')
+        return hg
+
+    def construct(self, prod_rule_seq):
+        """ construct a hypergraph following `prod_rule_seq`
+
+        Parameters
+        ----------
+        prod_rule_seq : list of integers
+            a sequence of production rules.
+
+        Returns
+        -------
+        UndirectedHypergraph
+        """
+        seq_idx = 0
+        init_prod_rule = self.prod_rule_corpus.get_prod_rule(prod_rule_seq[seq_idx])
+        hg, nt_edge_list = init_prod_rule.applied_to(None, None)
+        stack = deepcopy(nt_edge_list[::-1])
+        while len(stack) != 0:
+            seq_idx += 1
+            nt_edge = stack.pop()
+            hg, nt_edge_list = self.prod_rule_corpus.get_prod_rule(prod_rule_seq[seq_idx]).applied_to(hg, nt_edge)
+            stack.extend(nt_edge_list[::-1])            
+        return hg
+
+    def update_prod_rule_list(self, prod_rule):
+        """ return whether the input production rule is new or not, and its production rule id.
+        Production rules are regarded as the same if 
+            i) there exists a one-to-one mapping of nodes and edges, and
+            ii) all the attributes associated with nodes and hyperedges are the same.
+
+        Parameters
+        ----------
+        prod_rule : ProductionRule
+
+        Returns
+        -------
+        is_new : bool
+            if True, this production rule is new
+        prod_rule_id : int
+            production rule index. if new, a new index will be assigned.
+        """
+        return self.prod_rule_corpus.append(prod_rule)
+
+
+class IncrementalHyperedgeReplacementGrammar(HyperedgeReplacementGrammar):
+    '''
+    This class learns HRG incrementally leveraging the previously obtained production rules.
+    '''
+    def __init__(self, tree_decomposition=tree_decomposition_with_hrg, ignore_order=False):
+        self.prod_rule_list = []
+        self.tree_decomposition = tree_decomposition
+        self.ignore_order = ignore_order
+
+    def learn(self, hg_list):
+        """ learn from a list of hypergraphs
+
+        Parameters
+        ----------
+        hg_list : list of UndirectedHypergraph
+
+        Returns
+        -------
+        prod_rule_seq_list : list of integers
+            each element corresponds to a sequence of production rules to generate each hypergraph.
+        """
+        prod_rule_seq_list = []
+        for each_hg in hg_list:
+            clique_tree, root_node = tree_decomposition_with_hrg(each_hg, self, return_root=True)
+
+            prod_rule_seq = []
+            stack = []
+
+            # get a pair of myself and children
+            children = sorted(list(clique_tree[root_node].keys()))
+            
+            # extract a temporary production rule
+            prod_rule = extract_prod_rule(None, clique_tree.nodes[root_node]["subhg"],
+                                          [clique_tree.nodes[each_child]["subhg"] for each_child in children])
+            
+            # update the production rule list
+            prod_rule_id, prod_rule = self.update_prod_rule_list(prod_rule)
+            children = reorder_children(root_node, children, prod_rule, clique_tree)
+            stack.extend([(root_node, each_child) for each_child in children[::-1]])
+            prod_rule_seq.append(prod_rule_id)
+            
+            while len(stack) != 0:
+                # get a triple of parent, myself, and children
+                parent, myself = stack.pop()
+                children = sorted(list(dict(clique_tree[myself]).keys()))
+                children.remove(parent)
+
+                # extract a temp prod rule
+                prod_rule = extract_prod_rule(
+                    clique_tree.nodes[parent]["subhg"], clique_tree.nodes[myself]["subhg"],
+                    [clique_tree.nodes[each_child]["subhg"] for each_child in children])
+
+                # update the prod rule list
+                prod_rule_id, prod_rule = self.update_prod_rule_list(prod_rule)
+                children = reorder_children(myself, children, prod_rule, clique_tree)
+                stack.extend([(myself, each_child) for each_child in children[::-1]])
+                prod_rule_seq.append(prod_rule_id)
+            prod_rule_seq_list.append(prod_rule_seq)
+        self._compute_stats()
+        return prod_rule_seq_list
+
+
+def reorder_children(myself, children, prod_rule, clique_tree):
+    """ reorder children so that they match the order in `prod_rule`.
+
+    Parameters
+    ----------
+    myself : int
+    children : list of int
+    prod_rule : ProductionRule
+    clique_tree : nx.Graph
+
+    Returns
+    -------
+    new_children : list of str
+        reordered children
+    """
+    perm = {} # key : `nt_idx`, val : child
+    for each_edge in prod_rule.rhs.edges:
+        if "nt_idx" in prod_rule.rhs.edge_attr(each_edge).keys():
+            for each_child in children:
+                common_node_set = set(
+                    common_node_list(clique_tree.nodes[myself]["subhg"],
+                                     clique_tree.nodes[each_child]["subhg"])[0])
+                if set(prod_rule.rhs.nodes_in_edge(each_edge)) == common_node_set:
+                    assert prod_rule.rhs.edge_attr(each_edge)["nt_idx"] not in perm
+                    perm[prod_rule.rhs.edge_attr(each_edge)["nt_idx"]] = each_child
+    new_children = []
+    assert len(perm) == len(children)
+    for i in range(len(perm)):
+        new_children.append(perm[i])
+    return new_children
+
+
+def extract_prod_rule(parent_hg, myself_hg, children_hg_list, subhg_idx=None):
+    """ extract a production rule from a triple of `parent_hg`, `myself_hg`, and `children_hg_list`.
+
+    Parameters
+    ----------
+    parent_hg : Hypergraph
+    myself_hg : Hypergraph
+    children_hg_list : list of Hypergraph
+
+    Returns
+    -------
+    ProductionRule, consisting of
+        lhs : Hypergraph or None
+        rhs : Hypergraph
+    """
+    def _add_ext_node(hg, ext_nodes):
+        """ mark nodes to be external (ordered ids are assigned)
+
+        Parameters
+        ----------
+        hg : UndirectedHypergraph
+        ext_nodes : list of str
+            list of external nodes
+
+        Returns
+        -------
+        hg : Hypergraph
+            nodes in `ext_nodes` are marked to be external
+        """
+        ext_id = 0
+        ext_id_exists = []
+        for each_node in ext_nodes:
+            ext_id_exists.append('ext_id' in hg.node_attr(each_node))
+        if ext_id_exists and any(ext_id_exists) != all(ext_id_exists):
+            raise ValueError
+        if not all(ext_id_exists):
+            for each_node in ext_nodes:
+                hg.node_attr(each_node)['ext_id'] = ext_id
+                ext_id += 1
+        return hg
+
+    def _check_aromatic(hg, node_list):
+        is_aromatic = False
+        node_aromatic_list = []
+        for each_node in node_list:
+            if hg.node_attr(each_node)['symbol'].is_aromatic:
+                is_aromatic = True
+                node_aromatic_list.append(True)
+            else:
+                node_aromatic_list.append(False)
+        return is_aromatic, node_aromatic_list
+
+    def _check_ring(hg):
+        for each_edge in hg.edges:
+            if not ('tmp' in hg.edge_attr(each_edge) or (not hg.edge_attr(each_edge)['terminal'])):
+                return False
+        return True
+
+    if parent_hg is None:
+        lhs = Hypergraph()
+        node_list = []
+    else:
+        lhs = Hypergraph()
+        node_list, edge_exists = common_node_list(parent_hg, myself_hg)
+        for each_node in node_list:
+            lhs.add_node(each_node,
+                         deepcopy(myself_hg.node_attr(each_node)))
+        is_aromatic, _ = _check_aromatic(parent_hg, node_list)
+        for_ring = _check_ring(myself_hg)
+        bond_symbol_list = []
+        for each_node in node_list:
+            bond_symbol_list.append(parent_hg.node_attr(each_node)['symbol'])
+        lhs.add_edge(
+            node_list,
+            attr_dict=dict(
+                terminal=False,
+                edge_exists=edge_exists,
+                symbol=NTSymbol(
+                    degree=len(node_list),
+                    is_aromatic=is_aromatic,
+                    bond_symbol_list=bond_symbol_list,
+                    for_ring=for_ring)))
+        try:
+            lhs = _add_ext_node(lhs, node_list)
+        except ValueError:
+            import pdb; pdb.set_trace()
+
+    rhs = remove_tmp_edge(deepcopy(myself_hg))
+    #rhs = remove_ext_node(rhs)
+    #rhs = remove_nt_edge(rhs)
+    try:
+        rhs = _add_ext_node(rhs, node_list)
+    except ValueError:
+        import pdb; pdb.set_trace()
+
+    nt_idx = 0
+    if children_hg_list is not None:
+        for each_child_hg in children_hg_list:
+            node_list, edge_exists = common_node_list(myself_hg, each_child_hg)
+            is_aromatic, _ = _check_aromatic(myself_hg, node_list)
+            for_ring = _check_ring(each_child_hg)
+            bond_symbol_list = []
+            for each_node in node_list:
+                bond_symbol_list.append(myself_hg.node_attr(each_node)['symbol'])
+            rhs.add_edge(
+                node_list,
+                attr_dict=dict(
+                    terminal=False,
+                    nt_idx=nt_idx,
+                    edge_exists=edge_exists,
+                    symbol=NTSymbol(degree=len(node_list),
+                                    is_aromatic=is_aromatic,
+                                    bond_symbol_list=bond_symbol_list,
+                                    for_ring=for_ring)))
+            nt_idx += 1
+    prod_rule = ProductionRule(lhs, rhs)
+    prod_rule.subhg_idx = subhg_idx
+    if DEBUG:
+        if sorted(list(prod_rule.ext_node.keys())) \
+           != list(np.arange(len(prod_rule.ext_node))):
+            raise RuntimeError('ext_id is not continuous')
+    return prod_rule
+
+
+def _find_root(clique_tree):
+    max_node = None
+    num_nodes_max = -np.inf
+    for each_node in clique_tree.nodes:
+        if clique_tree.nodes[each_node]['subhg'].num_nodes > num_nodes_max:
+            max_node = each_node
+            num_nodes_max = clique_tree.nodes[each_node]['subhg'].num_nodes
+        '''
+        children = sorted(list(clique_tree[each_node].keys()))
+        prod_rule = extract_prod_rule(None,
+                                      clique_tree.nodes[each_node]["subhg"],
+                                      [clique_tree.nodes[each_child]["subhg"]
+                                       for each_child in children])
+        for each_start_rule in start_rule_list:
+            if prod_rule.is_same(each_start_rule):
+                return each_node
+        '''
+    return max_node
+
+def remove_ext_node(hg):
+    for each_node in hg.nodes:
+        hg.node_attr(each_node).pop('ext_id', None)
+    return hg
+
+def remove_nt_edge(hg):
+    remove_edge_list = []
+    for each_edge in hg.edges:
+        if not hg.edge_attr(each_edge)['terminal']:
+            remove_edge_list.append(each_edge)
+    hg.remove_edges(remove_edge_list)
+    return hg
+
+def remove_tmp_edge(hg):
+    remove_edge_list = []
+    for each_edge in hg.edges:
+        if hg.edge_attr(each_edge).get('tmp', False):
+            remove_edge_list.append(each_edge)
+    hg.remove_edges(remove_edge_list)
+    return hg

mol_moe/experts/mhg_model/graph_grammar/graph_grammar/symbols.py

@@ -0,0 +1,180 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES THE ORIGINAL SOURCE CODE (AND SOME ADAPTATIONS)
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE. 
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""
+
+
+""" Title """
+
+__author__ = "Hiroshi Kajino <[email protected]>"
+__copyright__ = "(c) Copyright IBM Corp. 2018"
+__version__ = "0.1"
+__date__ = "Jan 1 2018"
+
+from typing import List
+
+class TSymbol(object):
+
+    ''' terminal symbol
+
+    Attributes
+    ----------
+    degree : int
+        the number of nodes in a hyperedge
+    is_aromatic : bool
+        whether or not the hyperedge is in an aromatic ring
+    symbol : str
+        atomic symbol
+    num_explicit_Hs : int
+        the number of hydrogens associated to this hyperedge
+    formal_charge : int
+        charge
+    chirality : int
+        chirality
+    '''
+
+    def __init__(self, degree, is_aromatic,
+                 symbol, num_explicit_Hs, formal_charge, chirality):
+        self.degree = degree
+        self.is_aromatic = is_aromatic
+        self.symbol = symbol
+        self.num_explicit_Hs = num_explicit_Hs
+        self.formal_charge = formal_charge
+        self.chirality = chirality
+
+    @property
+    def terminal(self):
+        return True
+
+    def __eq__(self, other):
+        if not isinstance(other, TSymbol):
+            return False
+        if self.degree != other.degree:
+            return False
+        if self.is_aromatic != other.is_aromatic:
+            return False
+        if self.symbol != other.symbol:
+            return False
+        if self.num_explicit_Hs != other.num_explicit_Hs:
+            return False
+        if self.formal_charge != other.formal_charge:
+            return False
+        if self.chirality != other.chirality:
+            return False
+        return True
+
+    def __hash__(self):
+        return self.__str__().__hash__()
+
+    def __str__(self):
+        return f'degree={self.degree}, is_aromatic={self.is_aromatic}, '\
+            f'symbol={self.symbol}, '\
+            f'num_explicit_Hs={self.num_explicit_Hs}, '\
+            f'formal_charge={self.formal_charge}, chirality={self.chirality}'
+
+
+class NTSymbol(object):
+
+    ''' non-terminal symbol
+
+    Attributes
+    ----------
+    degree : int
+        degree of the hyperedge
+    is_aromatic : bool
+        if True, at least one of the associated bonds must be aromatic.
+    node_aromatic_list : list of bool
+        indicate whether each of the nodes is aromatic or not.
+    bond_type_list : list of int
+        bond type of each node"
+    '''
+
+    def __init__(self, degree: int, is_aromatic: bool,
+                 bond_symbol_list: list,
+                 for_ring=False):
+        self.degree = degree
+        self.is_aromatic = is_aromatic
+        self.for_ring = for_ring
+        self.bond_symbol_list = bond_symbol_list
+
+    @property
+    def terminal(self) -> bool:
+        return False
+
+    @property
+    def symbol(self):
+        return f'NT{self.degree}'
+
+    def __eq__(self, other) -> bool:
+        if not isinstance(other, NTSymbol):
+            return False
+
+        if self.degree != other.degree:
+            return False
+        if self.is_aromatic != other.is_aromatic:
+            return False
+        if self.for_ring != other.for_ring:
+            return False
+        if len(self.bond_symbol_list) != len(other.bond_symbol_list):
+            return False
+        for each_idx in range(len(self.bond_symbol_list)):
+            if self.bond_symbol_list[each_idx] != other.bond_symbol_list[each_idx]:
+                return False
+        return True
+
+    def __hash__(self):
+        return self.__str__().__hash__()
+
+    def __str__(self) -> str:
+        return f'degree={self.degree}, is_aromatic={self.is_aromatic}, '\
+            f'bond_symbol_list={[str(each_symbol) for each_symbol in self.bond_symbol_list]}'\
+            f'for_ring={self.for_ring}'
+
+
+class BondSymbol(object):
+    
+
+    ''' Bond symbol
+
+    Attributes
+    ----------
+    is_aromatic : bool
+        if True, at least one of the associated bonds must be aromatic.
+    bond_type : int
+        bond type of each node"
+    '''
+
+    def __init__(self, is_aromatic: bool,
+                 bond_type: int,
+                 stereo: int):
+        self.is_aromatic = is_aromatic
+        self.bond_type = bond_type
+        self.stereo = stereo
+
+    def __eq__(self, other) -> bool:
+        if not isinstance(other, BondSymbol):
+            return False
+
+        if self.is_aromatic != other.is_aromatic:
+            return False
+        if self.bond_type != other.bond_type:
+            return False
+        if self.stereo != other.stereo:
+            return False
+        return True
+
+    def __hash__(self):
+        return self.__str__().__hash__()
+
+    def __str__(self) -> str:
+        return f'is_aromatic={self.is_aromatic}, '\
+            f'bond_type={self.bond_type}, '\
+            f'stereo={self.stereo}, '

mol_moe/experts/mhg_model/graph_grammar/graph_grammar/utils.py

@@ -0,0 +1,130 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES THE ORIGINAL SOURCE CODE (AND SOME ADAPTATIONS)
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE. 
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""
+
+""" Title """
+
+__author__ = "Hiroshi Kajino <[email protected]>"
+__copyright__ = "(c) Copyright IBM Corp. 2018"
+__version__ = "0.1"
+__date__ = "Jun 4 2018"
+
+from ..hypergraph import Hypergraph
+from copy import deepcopy
+from typing import List
+import numpy as np
+
+
+def common_node_list(hg1: Hypergraph, hg2: Hypergraph) -> List[str]:
+    """ return a list of common nodes
+
+    Parameters
+    ----------
+    hg1, hg2 : Hypergraph
+
+    Returns
+    -------
+    list of str
+        list of common nodes
+    """
+    if hg1 is None or hg2 is None:
+        return [], False
+    else:
+        node_set = hg1.nodes.intersection(hg2.nodes)
+        node_dict = {}
+        if 'order4hrg' in hg1.node_attr(list(hg1.nodes)[0]):
+            for each_node in node_set:
+                node_dict[each_node] = hg1.node_attr(each_node)['order4hrg']
+        else:
+            for each_node in node_set:
+                node_dict[each_node] = hg1.node_attr(each_node)['symbol'].__hash__()
+        node_list = []
+        for each_key, _ in sorted(node_dict.items(), key=lambda x:x[1]):
+            node_list.append(each_key)
+        edge_name = hg1.has_edge(node_list, ignore_order=True)
+        if edge_name:
+            if not hg1.edge_attr(edge_name).get('terminal', True):
+                node_list = hg1.nodes_in_edge(edge_name)
+            return node_list, True
+        else:
+            return node_list, False
+
+
+def _node_match(node1, node2):
+    # if the nodes are hyperedges, `atom_attr` determines the match
+    if node1['bipartite'] == 'edge' and node2['bipartite'] == 'edge':
+        return node1["attr_dict"]['symbol'] == node2["attr_dict"]['symbol']
+    elif node1['bipartite'] == 'node' and node2['bipartite'] == 'node':
+        # bond_symbol
+        return node1['attr_dict']['symbol'] == node2['attr_dict']['symbol']
+    else:
+        return False
+
+def _easy_node_match(node1, node2):
+    # if the nodes are hyperedges, `atom_attr` determines the match
+    if node1['bipartite'] == 'edge' and node2['bipartite'] == 'edge':
+        return node1["attr_dict"].get('symbol', None) == node2["attr_dict"].get('symbol', None)
+    elif node1['bipartite'] == 'node' and node2['bipartite'] == 'node':
+        # bond_symbol
+        return node1['attr_dict'].get('ext_id', -1) == node2['attr_dict'].get('ext_id', -1)\
+            and node1['attr_dict']['symbol'] == node2['attr_dict']['symbol']
+    else:
+        return False
+
+
+def _node_match_prod_rule(node1, node2, ignore_order=False):
+    # if the nodes are hyperedges, `atom_attr` determines the match
+    if node1['bipartite'] == 'edge' and node2['bipartite'] == 'edge':
+        return node1["attr_dict"]['symbol'] == node2["attr_dict"]['symbol']
+    elif node1['bipartite'] == 'node' and node2['bipartite'] == 'node':
+        # ext_id, order4hrg, bond_symbol
+        if ignore_order:
+            return node1['attr_dict']['symbol'] == node2['attr_dict']['symbol']
+        else:
+            return node1['attr_dict']['symbol'] == node2['attr_dict']['symbol']\
+                and node1['attr_dict'].get('ext_id', -1) == node2['attr_dict'].get('ext_id', -1)
+    else:
+        return False
+
+
+def _edge_match(edge1, edge2, ignore_order=False):
+    #return True
+    if ignore_order:
+        return True
+    else:
+        return edge1["order"] == edge2["order"]
+
+def masked_softmax(logit, mask):
+    ''' compute a probability distribution from logit
+
+    Parameters
+    ----------
+    logit : array-like, length D
+        each element indicates how each dimension is likely to be chosen
+        (the larger, the more likely)
+    mask : array-like, length D
+        each element is either 0 or 1.
+        if 0, the dimension is ignored
+        when computing the probability distribution.
+
+    Returns
+    -------
+    prob_dist : array, length D
+        probability distribution computed from logit.
+        if `mask[d] = 0`, `prob_dist[d] = 0`.
+    '''
+    if logit.shape != mask.shape:
+        raise ValueError('logit and mask must have the same shape')
+    c = np.max(logit)
+    exp_logit = np.exp(logit - c) * mask
+    sum_exp_logit = exp_logit @ mask
+    return exp_logit / sum_exp_logit

mol_moe/experts/mhg_model/graph_grammar/hypergraph.py

@@ -0,0 +1,544 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES THE ORIGINAL SOURCE CODE (AND SOME ADAPTATIONS)
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE. 
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""
+
+""" Title """
+
+__author__ = "Hiroshi Kajino <[email protected]>"
+__copyright__ = "(c) Copyright IBM Corp. 2018"
+__version__ = "0.1"
+__date__ = "Jan 31 2018"
+
+from copy import deepcopy
+from typing import List, Dict, Tuple
+import networkx as nx
+import numpy as np
+import os
+
+
+class Hypergraph(object):
+    '''
+    A class of a hypergraph.
+    Each hyperedge can be ordered. For the ordered case,
+    edges adjacent to the hyperedge node are labeled by their orders.
+
+    Attributes
+    ----------
+    hg : nx.Graph
+        a bipartite graph representation of a hypergraph
+    edge_idx : int
+        total number of hyperedges that exist so far
+    '''
+    def __init__(self):
+        self.hg = nx.Graph()
+        self.edge_idx = 0
+        self.nodes = set([])
+        self.num_nodes = 0
+        self.edges = set([])
+        self.num_edges = 0
+        self.nodes_in_edge_dict = {}
+
+    def add_node(self, node: str, attr_dict=None):
+        ''' add a node to hypergraph
+
+        Parameters
+        ----------
+        node : str
+            node name
+        attr_dict : dict
+            dictionary of node attributes
+        '''
+        self.hg.add_node(node, bipartite='node', attr_dict=attr_dict)
+        if node not in self.nodes:
+            self.num_nodes += 1
+        self.nodes.add(node)
+
+    def add_edge(self, node_list: List[str], attr_dict=None, edge_name=None):
+        ''' add an edge consisting of nodes `node_list`
+
+        Parameters
+        ----------
+        node_list : list 
+            ordered list of nodes that consist the edge
+        attr_dict : dict
+            dictionary of edge attributes
+        '''
+        if edge_name is None:
+            edge = 'e{}'.format(self.edge_idx)
+        else:
+            assert edge_name not in self.edges
+            edge = edge_name
+        self.hg.add_node(edge, bipartite='edge', attr_dict=attr_dict)
+        if edge not in self.edges:
+            self.num_edges += 1
+        self.edges.add(edge)
+        self.nodes_in_edge_dict[edge] = node_list
+        if type(node_list) == list:
+            for node_idx, each_node in enumerate(node_list):
+                self.hg.add_edge(edge, each_node, order=node_idx)
+                if each_node not in self.nodes:
+                    self.num_nodes += 1
+                self.nodes.add(each_node)
+
+        elif type(node_list) == set:
+            for each_node in node_list:
+                self.hg.add_edge(edge, each_node, order=-1)
+                if each_node not in self.nodes:
+                    self.num_nodes += 1
+                self.nodes.add(each_node)
+        else:
+            raise ValueError
+        self.edge_idx += 1
+        return edge
+
+    def remove_node(self, node: str, remove_connected_edges=True):
+        ''' remove a node
+
+        Parameters
+        ----------
+        node : str
+            node name
+        remove_connected_edges : bool
+            if True, remove edges that are adjacent to the node
+        '''
+        if remove_connected_edges:
+            connected_edges = deepcopy(self.adj_edges(node))
+            for each_edge in connected_edges:
+                self.remove_edge(each_edge)
+        self.hg.remove_node(node)
+        self.num_nodes -= 1
+        self.nodes.remove(node)
+
+    def remove_nodes(self, node_iter, remove_connected_edges=True):
+        ''' remove a set of nodes
+
+        Parameters
+        ----------
+        node_iter : iterator of strings
+            nodes to be removed
+        remove_connected_edges : bool
+            if True, remove edges that are adjacent to the node        
+        '''
+        for each_node in node_iter:
+            self.remove_node(each_node, remove_connected_edges)
+
+    def remove_edge(self, edge: str):
+        ''' remove an edge
+
+        Parameters
+        ----------
+        edge : str
+            edge to be removed
+        '''
+        self.hg.remove_node(edge)
+        self.edges.remove(edge)
+        self.num_edges -= 1
+        self.nodes_in_edge_dict.pop(edge)
+
+    def remove_edges(self, edge_iter):
+        ''' remove a set of edges
+
+        Parameters
+        ----------
+        edge_iter : iterator of strings
+            edges to be removed
+        '''
+        for each_edge in edge_iter:
+            self.remove_edge(each_edge)
+
+    def remove_edges_with_attr(self, edge_attr_dict):
+        remove_edge_list = []
+        for each_edge in self.edges:
+            satisfy = True
+            for each_key, each_val in edge_attr_dict.items():
+                if not satisfy:
+                    break
+                try:
+                    if self.edge_attr(each_edge)[each_key] != each_val:
+                        satisfy = False
+                except KeyError:
+                    satisfy = False
+            if satisfy:
+                remove_edge_list.append(each_edge)
+        self.remove_edges(remove_edge_list)
+
+    def remove_subhg(self, subhg):
+        ''' remove subhypergraph.
+        all of the hyperedges are removed.
+        each node of subhg is removed if its degree becomes 0 after removing hyperedges.
+
+        Parameters
+        ----------
+        subhg : Hypergraph
+        '''
+        for each_edge in subhg.edges:
+            self.remove_edge(each_edge)
+        for each_node in subhg.nodes:
+            if self.degree(each_node) == 0:
+                self.remove_node(each_node)
+
+    def nodes_in_edge(self, edge):
+        ''' return an ordered list of nodes in a given edge.
+
+        Parameters
+        ----------
+        edge : str
+            edge whose nodes are returned
+
+        Returns
+        -------
+        list or set
+            ordered list or set of nodes that belong to the edge
+        '''
+        if edge.startswith('e'):
+            return self.nodes_in_edge_dict[edge]
+        else:
+            adj_node_list = self.hg.adj[edge]
+            adj_node_order_list = []
+            adj_node_name_list = []
+            for each_node in adj_node_list:
+                adj_node_order_list.append(adj_node_list[each_node]['order'])
+                adj_node_name_list.append(each_node)
+            if adj_node_order_list == [-1] * len(adj_node_order_list):
+                return set(adj_node_name_list)
+            else:
+                return [adj_node_name_list[each_idx] for each_idx
+                        in np.argsort(adj_node_order_list)]
+
+    def adj_edges(self, node):
+        ''' return a dict of adjacent hyperedges
+
+        Parameters
+        ----------
+        node : str
+
+        Returns
+        -------
+        set
+            set of edges that are adjacent to `node`
+        '''
+        return self.hg.adj[node]
+
+    def adj_nodes(self, node):
+        ''' return a set of adjacent nodes
+
+        Parameters
+        ----------
+        node : str
+
+        Returns
+        -------
+        set
+            set of nodes that are adjacent to `node`
+        '''
+        node_set = set([])
+        for each_adj_edge in self.adj_edges(node):
+            node_set.update(set(self.nodes_in_edge(each_adj_edge)))
+        node_set.discard(node)
+        return node_set
+
+    def has_edge(self, node_list, ignore_order=False):
+        for each_edge in self.edges:
+            if ignore_order:
+                if set(self.nodes_in_edge(each_edge)) == set(node_list):
+                    return each_edge
+            else:
+                if self.nodes_in_edge(each_edge) == node_list:
+                    return each_edge
+        return False
+
+    def degree(self, node):
+        return len(self.hg.adj[node])
+
+    def degrees(self):
+        return {each_node: self.degree(each_node) for each_node in self.nodes}
+
+    def edge_degree(self, edge):
+        return len(self.nodes_in_edge(edge))
+
+    def edge_degrees(self):
+        return {each_edge: self.edge_degree(each_edge) for each_edge in self.edges}
+
+    def is_adj(self, node1, node2):
+        return node1 in self.adj_nodes(node2)
+
+    def adj_subhg(self, node, ident_node_dict=None):
+        """ return a subhypergraph consisting of a set of nodes and hyperedges adjacent to `node`.
+        if an adjacent node has a self-loop hyperedge, it will be also added to the subhypergraph.
+
+        Parameters
+        ----------
+        node : str
+        ident_node_dict : dict
+            dict containing identical nodes. see `get_identical_node_dict` for more details
+
+        Returns
+        -------
+        subhg : Hypergraph
+        """
+        if ident_node_dict is None:
+            ident_node_dict = self.get_identical_node_dict()
+        adj_node_set = set(ident_node_dict[node])
+        adj_edge_set = set([])
+        for each_node in ident_node_dict[node]:
+            adj_edge_set.update(set(self.adj_edges(each_node)))
+        fixed_adj_edge_set = deepcopy(adj_edge_set)
+        for each_edge in fixed_adj_edge_set:
+            other_nodes = self.nodes_in_edge(each_edge)
+            adj_node_set.update(other_nodes)
+
+            # if the adjacent node has self-loop edge, it will be appended to adj_edge_list.
+            for each_node in other_nodes:
+                for other_edge in set(self.adj_edges(each_node)) - set([each_edge]):
+                    if len(set(self.nodes_in_edge(other_edge)) \
+                           - set(self.nodes_in_edge(each_edge))) == 0:
+                        adj_edge_set.update(set([other_edge]))
+        subhg = Hypergraph()
+        for each_node in adj_node_set:
+            subhg.add_node(each_node, attr_dict=self.node_attr(each_node))
+        for each_edge in adj_edge_set:
+            subhg.add_edge(self.nodes_in_edge(each_edge),
+                           attr_dict=self.edge_attr(each_edge),
+                           edge_name=each_edge)
+        subhg.edge_idx = self.edge_idx
+        return subhg
+
+    def get_subhg(self, node_list, edge_list, ident_node_dict=None):
+        """ return a subhypergraph consisting of a set of nodes and hyperedges adjacent to `node`.
+        if an adjacent node has a self-loop hyperedge, it will be also added to the subhypergraph.
+
+        Parameters
+        ----------
+        node : str
+        ident_node_dict : dict
+            dict containing identical nodes. see `get_identical_node_dict` for more details
+
+        Returns
+        -------
+        subhg : Hypergraph
+        """
+        if ident_node_dict is None:
+            ident_node_dict = self.get_identical_node_dict()
+        adj_node_set = set([])
+        for each_node in node_list:
+            adj_node_set.update(set(ident_node_dict[each_node]))
+        adj_edge_set = set(edge_list)
+
+        subhg = Hypergraph()
+        for each_node in adj_node_set:
+            subhg.add_node(each_node,
+                           attr_dict=deepcopy(self.node_attr(each_node)))
+        for each_edge in adj_edge_set:
+            subhg.add_edge(self.nodes_in_edge(each_edge),
+                           attr_dict=deepcopy(self.edge_attr(each_edge)),
+                           edge_name=each_edge)
+        subhg.edge_idx = self.edge_idx
+        return subhg
+
+    def copy(self):
+        ''' return a copy of the object
+        
+        Returns
+        -------
+        Hypergraph
+        '''
+        return deepcopy(self)
+
+    def node_attr(self, node):
+        return self.hg.nodes[node]['attr_dict']
+
+    def edge_attr(self, edge):
+        return self.hg.nodes[edge]['attr_dict']
+
+    def set_node_attr(self, node, attr_dict):
+        for each_key, each_val in attr_dict.items():
+            self.hg.nodes[node]['attr_dict'][each_key] = each_val
+
+    def set_edge_attr(self, edge, attr_dict):
+        for each_key, each_val in attr_dict.items():
+            self.hg.nodes[edge]['attr_dict'][each_key] = each_val
+
+    def get_identical_node_dict(self):
+        ''' get identical nodes
+        nodes are identical if they share the same set of adjacent edges.
+        
+        Returns
+        -------
+        ident_node_dict : dict
+            ident_node_dict[node] returns a list of nodes that are identical to `node`.
+        '''
+        ident_node_dict = {}
+        for each_node in self.nodes:
+            ident_node_list = []
+            for each_other_node in self.nodes:
+                if each_other_node == each_node:
+                    ident_node_list.append(each_other_node)
+                elif self.adj_edges(each_node) == self.adj_edges(each_other_node) \
+                   and len(self.adj_edges(each_node)) != 0:
+                    ident_node_list.append(each_other_node)
+            ident_node_dict[each_node] = ident_node_list
+        return ident_node_dict
+    '''
+        ident_node_dict = {}
+        for each_node in self.nodes:
+            ident_node_dict[each_node] = [each_node]
+        return ident_node_dict
+    '''
+
+    def get_leaf_edge(self):
+        ''' get an edge that is incident only to one edge
+
+        Returns
+        -------
+        if exists, return a leaf edge. otherwise, return None.
+        '''
+        for each_edge in self.edges:
+            if len(self.adj_nodes(each_edge)) == 1:
+                if 'tmp' not in self.edge_attr(each_edge):
+                    return each_edge
+        return None
+
+    def get_nontmp_edge(self):
+        for each_edge in self.edges:
+            if 'tmp' not in self.edge_attr(each_edge):
+                return each_edge
+        return None
+
+    def is_subhg(self, hg):
+        ''' return whether this hypergraph is a subhypergraph of `hg`
+
+        Returns
+        -------
+        True if self \in hg,
+        False otherwise.
+        '''
+        for each_node in self.nodes:
+            if each_node not in hg.nodes:
+                return False
+        for each_edge in self.edges:
+            if each_edge not in hg.edges:
+                return False
+        return True
+
+    def in_cycle(self, node, visited=None, parent='', root_node='') -> bool:
+        ''' if `node` is in a cycle, then return True. otherwise, False.
+
+        Parameters
+        ----------
+        node : str
+            node in a hypergraph
+        visited : list
+            list of visited nodes, used for recursion
+        parent : str
+            parent node, used to eliminate a cycle consisting of two nodes and one edge.
+
+        Returns
+        -------
+        bool
+        '''
+        if visited is None:
+            visited = []
+        if parent == '':
+            visited = []
+        if root_node == '':
+            root_node = node
+        visited.append(node)
+        for each_adj_node in self.adj_nodes(node):
+            if each_adj_node not in visited:
+                if self.in_cycle(each_adj_node, visited, node, root_node):
+                    return True
+            elif each_adj_node != parent and each_adj_node == root_node:
+                return True
+        return False
+
+    
+    def draw(self, file_path=None, with_node=False, with_edge_name=False):
+        ''' draw hypergraph
+        '''
+        import graphviz
+        G = graphviz.Graph(format='png')
+        for each_node in self.nodes:
+            if 'ext_id' in self.node_attr(each_node):
+                G.node(each_node, label='',
+                       shape='circle', width='0.1', height='0.1', style='filled',
+                       fillcolor='black')
+            else:
+                if with_node:
+                    G.node(each_node, label='',
+                           shape='circle', width='0.1', height='0.1', style='filled',
+                           fillcolor='gray')
+        edge_list = []
+        for each_edge in self.edges:
+            if self.edge_attr(each_edge).get('terminal', False):
+                G.node(each_edge,
+                       label=self.edge_attr(each_edge)['symbol'].symbol if not with_edge_name \
+                       else self.edge_attr(each_edge)['symbol'].symbol + ', ' + each_edge,
+                       fontcolor='black', shape='square')
+            elif self.edge_attr(each_edge).get('tmp', False):
+                G.node(each_edge, label='tmp' if not with_edge_name else 'tmp, ' + each_edge,
+                       fontcolor='black', shape='square')
+            else:
+                G.node(each_edge,
+                       label=self.edge_attr(each_edge)['symbol'].symbol if not with_edge_name \
+                       else self.edge_attr(each_edge)['symbol'].symbol + ', ' + each_edge,
+                       fontcolor='black', shape='square', style='filled')
+            if with_node:
+                for each_node in self.nodes_in_edge(each_edge):
+                    G.edge(each_edge, each_node)
+            else:
+                for each_node in self.nodes_in_edge(each_edge):
+                    if 'ext_id' in self.node_attr(each_node)\
+                       and set([each_node, each_edge]) not in edge_list:
+                        G.edge(each_edge, each_node)
+                        edge_list.append(set([each_node, each_edge]))
+                for each_other_edge in self.adj_nodes(each_edge):
+                    if set([each_edge, each_other_edge]) not in edge_list:
+                        num_bond = 0
+                        common_node_set = set(self.nodes_in_edge(each_edge))\
+                                          .intersection(set(self.nodes_in_edge(each_other_edge)))
+                        for each_node in common_node_set:
+                            if self.node_attr(each_node)['symbol'].bond_type in [1, 2, 3]:
+                                num_bond += self.node_attr(each_node)['symbol'].bond_type
+                            elif self.node_attr(each_node)['symbol'].bond_type in [12]:
+                                num_bond += 1
+                            else:
+                                raise NotImplementedError('unsupported bond type')
+                        for _ in range(num_bond):
+                            G.edge(each_edge, each_other_edge)
+                        edge_list.append(set([each_edge, each_other_edge]))
+        if file_path is not None:
+            G.render(file_path, cleanup=True)
+            #os.remove(file_path)
+        return G
+
+    def is_dividable(self, node):
+        _hg = deepcopy(self.hg)
+        _hg.remove_node(node)
+        return (not nx.is_connected(_hg))
+
+    def divide(self, node):
+        subhg_list = []
+
+        hg_wo_node = deepcopy(self)
+        hg_wo_node.remove_node(node, remove_connected_edges=False)
+        connected_components = nx.connected_components(hg_wo_node.hg)
+        for each_component in connected_components:
+            node_list = [node]
+            edge_list = []
+            node_list.extend([each_node for each_node in each_component
+                              if each_node.startswith('bond_')])
+            edge_list.extend([each_edge for each_edge in each_component
+                              if each_edge.startswith('e')])
+            subhg_list.append(self.get_subhg(node_list, edge_list))
+            #subhg_list[-1].set_node_attr(node, {'divided': True})
+        return subhg_list
+

mol_moe/experts/mhg_model/graph_grammar/io/__init__.py

@@ -0,0 +1,20 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES THE ORIGINAL SOURCE CODE (AND SOME ADAPTATIONS)
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE. 
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""
+
+""" Title """
+
+__author__ = "Hiroshi Kajino <[email protected]>"
+__copyright__ = "(c) Copyright IBM Corp. 2018"
+__version__ = "0.1"
+__date__ = "Jan 1 2018"
+

mol_moe/experts/mhg_model/graph_grammar/io/smi.py

@@ -0,0 +1,559 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES THE ORIGINAL SOURCE CODE (AND SOME ADAPTATIONS)
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE. 
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""
+
+""" Title """
+
+__author__ = "Hiroshi Kajino <[email protected]>"
+__copyright__ = "(c) Copyright IBM Corp. 2018"
+__version__ = "0.1"
+__date__ = "Jan 12 2018"
+
+from copy import deepcopy
+from rdkit import Chem
+from rdkit import RDLogger
+import networkx as nx
+import numpy as np
+from ..hypergraph import Hypergraph
+from ..graph_grammar.symbols import TSymbol, BondSymbol
+
+# supress warnings
+lg = RDLogger.logger()
+lg.setLevel(RDLogger.CRITICAL)
+
+
+class HGGen(object):
+    """
+    load .smi file and yield a hypergraph.
+
+    Attributes
+    ----------
+    path_to_file : str
+        path to .smi file
+    kekulize : bool
+        kekulize or not
+    add_Hs : bool
+        add implicit hydrogens to the molecule or not.
+    all_single : bool
+        if True, all multiple bonds are summarized into a single bond with some attributes
+
+    Yields
+    ------
+    Hypergraph
+    """
+    def __init__(self, path_to_file, kekulize=True, add_Hs=False, all_single=True):
+        self.num_line = 1
+        self.mol_gen = Chem.SmilesMolSupplier(path_to_file, titleLine=False)
+        self.kekulize = kekulize
+        self.add_Hs = add_Hs
+        self.all_single = all_single
+
+    def __iter__(self):
+        return self
+
+    def __next__(self):
+        '''
+        each_mol = None
+        while each_mol is None:
+            each_mol = next(self.mol_gen)
+        '''
+        # not ignoring parse errors
+        each_mol = next(self.mol_gen)
+        if each_mol is None:
+            raise ValueError(f'incorrect smiles in line {self.num_line}')
+        else:
+            self.num_line += 1
+        return mol_to_hg(each_mol, self.kekulize, self.add_Hs)
+
+
+def mol_to_bipartite(mol, kekulize):
+    """
+    get a bipartite representation of a molecule.
+
+    Parameters
+    ----------
+    mol : rdkit.Chem.rdchem.Mol
+        molecule object
+
+    Returns
+    -------
+    nx.Graph
+        a bipartite graph representing which bond is connected to which atoms.
+    """
+    try:
+        mol = standardize_stereo(mol)
+    except KeyError:
+        print(Chem.MolToSmiles(mol))
+        raise KeyError
+        
+    if kekulize:
+        Chem.Kekulize(mol)
+
+    bipartite_g = nx.Graph()
+    for each_atom in mol.GetAtoms():
+        bipartite_g.add_node(f"atom_{each_atom.GetIdx()}",
+                             atom_attr=atom_attr(each_atom, kekulize))
+
+    for each_bond in mol.GetBonds():
+        bond_idx = each_bond.GetIdx()
+        bipartite_g.add_node(
+            f"bond_{bond_idx}",
+            bond_attr=bond_attr(each_bond, kekulize))
+        bipartite_g.add_edge(
+            f"atom_{each_bond.GetBeginAtomIdx()}",
+            f"bond_{bond_idx}")
+        bipartite_g.add_edge(
+            f"atom_{each_bond.GetEndAtomIdx()}",
+            f"bond_{bond_idx}")
+    return bipartite_g
+
+
+def mol_to_hg(mol, kekulize, add_Hs):
+    """
+    get a bipartite representation of a molecule.
+
+    Parameters
+    ----------
+    mol : rdkit.Chem.rdchem.Mol
+        molecule object
+    kekulize : bool
+        kekulize or not
+    add_Hs : bool
+        add implicit hydrogens to the molecule or not.
+
+    Returns
+    -------
+    Hypergraph
+    """
+    if add_Hs:
+        mol = Chem.AddHs(mol)
+
+    if kekulize:
+        Chem.Kekulize(mol)
+
+    bipartite_g = mol_to_bipartite(mol, kekulize)
+    hg = Hypergraph()
+    for each_atom in [each_node for each_node in bipartite_g.nodes()
+                      if each_node.startswith('atom_')]:
+        node_set = set([])
+        for each_bond in bipartite_g.adj[each_atom]:
+            hg.add_node(each_bond,
+                        attr_dict=bipartite_g.nodes[each_bond]['bond_attr'])
+            node_set.add(each_bond)
+        hg.add_edge(node_set,
+                    attr_dict=bipartite_g.nodes[each_atom]['atom_attr'])
+    return hg
+
+
+def hg_to_mol(hg, verbose=False):
+    """ convert a hypergraph into Mol object
+
+    Parameters
+    ----------
+    hg : Hypergraph
+
+    Returns
+    -------
+    mol : Chem.RWMol
+    """
+    mol = Chem.RWMol()
+    atom_dict = {}
+    bond_set = set([])
+    for each_edge in hg.edges:
+        atom = Chem.Atom(hg.edge_attr(each_edge)['symbol'].symbol)
+        atom.SetNumExplicitHs(hg.edge_attr(each_edge)['symbol'].num_explicit_Hs)
+        atom.SetFormalCharge(hg.edge_attr(each_edge)['symbol'].formal_charge)
+        atom.SetChiralTag(
+            Chem.rdchem.ChiralType.values[
+                hg.edge_attr(each_edge)['symbol'].chirality])
+        atom_idx = mol.AddAtom(atom)
+        atom_dict[each_edge] = atom_idx
+
+    for each_node in hg.nodes:
+        edge_1, edge_2 = hg.adj_edges(each_node)
+        if edge_1+edge_2 not in bond_set:
+            if hg.node_attr(each_node)['symbol'].bond_type <= 3:
+                num_bond = hg.node_attr(each_node)['symbol'].bond_type
+            elif hg.node_attr(each_node)['symbol'].bond_type == 12:
+                num_bond = 1
+            else:
+                raise ValueError(f'too many bonds; {hg.node_attr(each_node)["bond_symbol"].bond_type}')
+            _ = mol.AddBond(atom_dict[edge_1],
+                            atom_dict[edge_2],
+                            order=Chem.rdchem.BondType.values[num_bond])
+            bond_idx = mol.GetBondBetweenAtoms(atom_dict[edge_1], atom_dict[edge_2]).GetIdx()
+
+            # stereo
+            mol.GetBondWithIdx(bond_idx).SetStereo(
+                Chem.rdchem.BondStereo.values[hg.node_attr(each_node)['symbol'].stereo])
+            bond_set.update([edge_1+edge_2])
+            bond_set.update([edge_2+edge_1])
+    mol.UpdatePropertyCache()
+    mol = mol.GetMol()
+    not_stereo_mol = deepcopy(mol)
+    if Chem.MolFromSmiles(Chem.MolToSmiles(not_stereo_mol)) is None:
+        raise RuntimeError('no valid molecule was obtained.')
+    try:
+        mol = set_stereo(mol)
+        is_stereo = True
+    except:
+        import traceback
+        traceback.print_exc()
+        is_stereo = False
+    mol_tmp = deepcopy(mol)
+    Chem.SetAromaticity(mol_tmp)
+    if Chem.MolFromSmiles(Chem.MolToSmiles(mol_tmp)) is not None:
+        mol = mol_tmp
+    else:
+        if Chem.MolFromSmiles(Chem.MolToSmiles(mol)) is None:
+            mol = not_stereo_mol
+    mol.UpdatePropertyCache()
+    Chem.GetSymmSSSR(mol)
+    mol = Chem.MolFromSmiles(Chem.MolToSmiles(mol))
+    if verbose:
+        return mol, is_stereo
+    else:
+        return mol
+
+def hgs_to_mols(hg_list, ignore_error=False):
+    if ignore_error:
+        mol_list = []
+        for each_hg in hg_list:
+            try:
+                mol = hg_to_mol(each_hg)
+            except:
+                mol = None
+            mol_list.append(mol)
+    else:
+        mol_list = [hg_to_mol(each_hg) for each_hg in hg_list]
+    return mol_list
+
+def hgs_to_smiles(hg_list, ignore_error=False):
+    mol_list = hgs_to_mols(hg_list, ignore_error)
+    smiles_list = []
+    for each_mol in mol_list:
+        try:
+            smiles_list.append(
+                Chem.MolToSmiles(
+                    Chem.MolFromSmiles(
+                        Chem.MolToSmiles(
+                            each_mol))))
+        except:
+            smiles_list.append(None)
+    return smiles_list
+
+def atom_attr(atom, kekulize):
+    """
+    get atom's attributes
+
+    Parameters
+    ----------
+    atom : rdkit.Chem.rdchem.Atom
+    kekulize : bool
+        kekulize or not
+
+    Returns
+    -------
+    atom_attr : dict
+        "is_aromatic" : bool
+            the atom is aromatic or not.
+        "smarts" : str
+            SMARTS representation of the atom.
+    """
+    if kekulize:
+        return {'terminal': True,
+                'is_in_ring': atom.IsInRing(),
+                'symbol': TSymbol(degree=0,
+                                  #degree=atom.GetTotalDegree(),
+                                  is_aromatic=False,
+                                  symbol=atom.GetSymbol(),
+                                  num_explicit_Hs=atom.GetNumExplicitHs(),
+                                  formal_charge=atom.GetFormalCharge(),
+                                  chirality=atom.GetChiralTag().real
+                )}
+    else:
+        return {'terminal': True,
+                'is_in_ring': atom.IsInRing(),
+                'symbol': TSymbol(degree=0,
+                                  #degree=atom.GetTotalDegree(),
+                                  is_aromatic=atom.GetIsAromatic(),
+                                  symbol=atom.GetSymbol(),
+                                  num_explicit_Hs=atom.GetNumExplicitHs(),
+                                  formal_charge=atom.GetFormalCharge(),
+                                  chirality=atom.GetChiralTag().real
+                )}
+
+def bond_attr(bond, kekulize):
+    """
+    get atom's attributes
+
+    Parameters
+    ----------
+    bond : rdkit.Chem.rdchem.Bond
+    kekulize : bool
+        kekulize or not
+
+    Returns
+    -------
+    bond_attr : dict
+        "bond_type" : int
+        {0: rdkit.Chem.rdchem.BondType.UNSPECIFIED,
+         1: rdkit.Chem.rdchem.BondType.SINGLE,
+         2: rdkit.Chem.rdchem.BondType.DOUBLE,
+         3: rdkit.Chem.rdchem.BondType.TRIPLE,
+         4: rdkit.Chem.rdchem.BondType.QUADRUPLE,
+         5: rdkit.Chem.rdchem.BondType.QUINTUPLE,
+         6: rdkit.Chem.rdchem.BondType.HEXTUPLE,
+         7: rdkit.Chem.rdchem.BondType.ONEANDAHALF,
+         8: rdkit.Chem.rdchem.BondType.TWOANDAHALF,
+         9: rdkit.Chem.rdchem.BondType.THREEANDAHALF,
+         10: rdkit.Chem.rdchem.BondType.FOURANDAHALF,
+         11: rdkit.Chem.rdchem.BondType.FIVEANDAHALF,
+         12: rdkit.Chem.rdchem.BondType.AROMATIC,
+         13: rdkit.Chem.rdchem.BondType.IONIC,
+         14: rdkit.Chem.rdchem.BondType.HYDROGEN,
+         15: rdkit.Chem.rdchem.BondType.THREECENTER,
+         16: rdkit.Chem.rdchem.BondType.DATIVEONE,
+         17: rdkit.Chem.rdchem.BondType.DATIVE,
+         18: rdkit.Chem.rdchem.BondType.DATIVEL,
+         19: rdkit.Chem.rdchem.BondType.DATIVER,
+         20: rdkit.Chem.rdchem.BondType.OTHER,
+         21: rdkit.Chem.rdchem.BondType.ZERO}
+    """
+    if kekulize:
+        is_aromatic = False
+        if bond.GetBondType().real == 12:
+            bond_type = 1
+        else:
+            bond_type = bond.GetBondType().real
+    else:
+        is_aromatic = bond.GetIsAromatic()
+        bond_type = bond.GetBondType().real
+    return {'symbol': BondSymbol(is_aromatic=is_aromatic,
+                                 bond_type=bond_type,
+                                 stereo=int(bond.GetStereo())),
+            'is_in_ring': bond.IsInRing()}
+
+
+def standardize_stereo(mol):
+    '''
+ 0: rdkit.Chem.rdchem.BondDir.NONE,
+ 1: rdkit.Chem.rdchem.BondDir.BEGINWEDGE,
+ 2: rdkit.Chem.rdchem.BondDir.BEGINDASH,
+ 3: rdkit.Chem.rdchem.BondDir.ENDDOWNRIGHT,
+ 4: rdkit.Chem.rdchem.BondDir.ENDUPRIGHT,
+
+    '''
+    # mol = Chem.AddHs(mol) # this removes CIPRank !!!
+    for each_bond in mol.GetBonds():
+        if int(each_bond.GetStereo()) in [2, 3]: #2=Z (same side), 3=E
+            begin_stereo_atom_idx = each_bond.GetBeginAtomIdx()
+            end_stereo_atom_idx = each_bond.GetEndAtomIdx()
+            atom_idx_1 = each_bond.GetStereoAtoms()[0]
+            atom_idx_2 = each_bond.GetStereoAtoms()[1]
+            if mol.GetBondBetweenAtoms(atom_idx_1, begin_stereo_atom_idx):
+                begin_atom_idx = atom_idx_1
+                end_atom_idx = atom_idx_2
+            else:
+                begin_atom_idx = atom_idx_2
+                end_atom_idx = atom_idx_1
+
+            begin_another_atom_idx = None
+            assert len(mol.GetAtomWithIdx(begin_stereo_atom_idx).GetNeighbors()) <= 3
+            for each_neighbor in mol.GetAtomWithIdx(begin_stereo_atom_idx).GetNeighbors():
+                each_neighbor_idx = each_neighbor.GetIdx()
+                if each_neighbor_idx not in [end_stereo_atom_idx, begin_atom_idx]:
+                    begin_another_atom_idx = each_neighbor_idx
+
+            end_another_atom_idx = None
+            assert len(mol.GetAtomWithIdx(end_stereo_atom_idx).GetNeighbors()) <= 3
+            for each_neighbor in mol.GetAtomWithIdx(end_stereo_atom_idx).GetNeighbors():
+                each_neighbor_idx = each_neighbor.GetIdx()
+                if each_neighbor_idx not in [begin_stereo_atom_idx, end_atom_idx]:
+                    end_another_atom_idx = each_neighbor_idx
+
+            ''' 
+            relationship between begin_atom_idx and end_atom_idx is encoded in GetStereo
+            '''
+            begin_atom_rank = int(mol.GetAtomWithIdx(begin_atom_idx).GetProp('_CIPRank'))
+            end_atom_rank = int(mol.GetAtomWithIdx(end_atom_idx).GetProp('_CIPRank'))
+            try:
+                begin_another_atom_rank = int(mol.GetAtomWithIdx(begin_another_atom_idx).GetProp('_CIPRank'))
+            except:
+                begin_another_atom_rank = np.inf
+            try:
+                end_another_atom_rank = int(mol.GetAtomWithIdx(end_another_atom_idx).GetProp('_CIPRank'))
+            except:
+                end_another_atom_rank = np.inf
+            if begin_atom_rank < begin_another_atom_rank\
+               and end_atom_rank < end_another_atom_rank:
+                pass
+            elif begin_atom_rank < begin_another_atom_rank\
+                 and end_atom_rank > end_another_atom_rank:
+                # (begin_atom_idx +) end_another_atom_idx should be in StereoAtoms
+                if each_bond.GetStereo() == 2:
+                    # set stereo
+                    each_bond.SetStereo(Chem.rdchem.BondStereo.values[3])
+                    # set bond dir
+                    mol = safe_set_bond_dir(mol, begin_atom_idx, begin_stereo_atom_idx, 3)
+                    mol = safe_set_bond_dir(mol, begin_another_atom_idx, begin_stereo_atom_idx, 0)
+                    mol = safe_set_bond_dir(mol, end_atom_idx, end_stereo_atom_idx, 0)
+                    mol = safe_set_bond_dir(mol, end_another_atom_idx, end_stereo_atom_idx, 3)
+                elif each_bond.GetStereo() == 3:
+                    # set stereo
+                    each_bond.SetStereo(Chem.rdchem.BondStereo.values[2])
+                    # set bond dir
+                    mol = safe_set_bond_dir(mol, begin_atom_idx, begin_stereo_atom_idx, 3)
+                    mol = safe_set_bond_dir(mol, begin_another_atom_idx, begin_stereo_atom_idx, 0)
+                    mol = safe_set_bond_dir(mol, end_atom_idx, end_stereo_atom_idx, 0)
+                    mol = safe_set_bond_dir(mol, end_another_atom_idx, end_stereo_atom_idx, 4)
+                else:
+                    raise ValueError
+                each_bond.SetStereoAtoms(begin_atom_idx, end_another_atom_idx)
+            elif begin_atom_rank > begin_another_atom_rank\
+                 and end_atom_rank < end_another_atom_rank:
+                # (end_atom_idx +) begin_another_atom_idx should be in StereoAtoms
+                if each_bond.GetStereo() == 2:
+                    # set stereo
+                    each_bond.SetStereo(Chem.rdchem.BondStereo.values[3])
+                    # set bond dir
+                    mol = safe_set_bond_dir(mol, begin_atom_idx, begin_stereo_atom_idx, 0)
+                    mol = safe_set_bond_dir(mol, begin_another_atom_idx, begin_stereo_atom_idx, 4)
+                    mol = safe_set_bond_dir(mol, end_atom_idx, end_stereo_atom_idx, 4)
+                    mol = safe_set_bond_dir(mol, end_another_atom_idx, end_stereo_atom_idx, 0)
+                elif each_bond.GetStereo() == 3:
+                    # set stereo
+                    each_bond.SetStereo(Chem.rdchem.BondStereo.values[2])
+                    # set bond dir
+                    mol = safe_set_bond_dir(mol, begin_atom_idx, begin_stereo_atom_idx, 0)
+                    mol = safe_set_bond_dir(mol, begin_another_atom_idx, begin_stereo_atom_idx, 4)
+                    mol = safe_set_bond_dir(mol, end_atom_idx, end_stereo_atom_idx, 3)
+                    mol = safe_set_bond_dir(mol, end_another_atom_idx, end_stereo_atom_idx, 0)
+                else:
+                    raise ValueError
+                each_bond.SetStereoAtoms(begin_another_atom_idx, end_atom_idx)
+            elif begin_atom_rank > begin_another_atom_rank\
+                 and end_atom_rank > end_another_atom_rank:
+                # begin_another_atom_idx + end_another_atom_idx should be in StereoAtoms
+                if each_bond.GetStereo() == 2:
+                    # set bond dir
+                    mol = safe_set_bond_dir(mol, begin_atom_idx, begin_stereo_atom_idx, 0)
+                    mol = safe_set_bond_dir(mol, begin_another_atom_idx, begin_stereo_atom_idx, 4)
+                    mol = safe_set_bond_dir(mol, end_atom_idx, end_stereo_atom_idx, 0)
+                    mol = safe_set_bond_dir(mol, end_another_atom_idx, end_stereo_atom_idx, 3)
+                elif each_bond.GetStereo() == 3:
+                    # set bond dir
+                    mol = safe_set_bond_dir(mol, begin_atom_idx, begin_stereo_atom_idx, 0)
+                    mol = safe_set_bond_dir(mol, begin_another_atom_idx, begin_stereo_atom_idx, 4)
+                    mol = safe_set_bond_dir(mol, end_atom_idx, end_stereo_atom_idx, 0)
+                    mol = safe_set_bond_dir(mol, end_another_atom_idx, end_stereo_atom_idx, 4)
+                else:
+                    raise ValueError
+                each_bond.SetStereoAtoms(begin_another_atom_idx, end_another_atom_idx)
+            else:
+                raise RuntimeError
+    return mol
+
+
+def set_stereo(mol):
+    '''
+ 0: rdkit.Chem.rdchem.BondDir.NONE,
+ 1: rdkit.Chem.rdchem.BondDir.BEGINWEDGE,
+ 2: rdkit.Chem.rdchem.BondDir.BEGINDASH,
+ 3: rdkit.Chem.rdchem.BondDir.ENDDOWNRIGHT,
+ 4: rdkit.Chem.rdchem.BondDir.ENDUPRIGHT,
+    '''
+    _mol = Chem.MolFromSmiles(Chem.MolToSmiles(mol))
+    Chem.Kekulize(_mol, True)
+    substruct_match = mol.GetSubstructMatch(_mol)
+    if not substruct_match:
+        ''' mol and _mol are kekulized.
+        sometimes, the order of '=' and '-' changes, which causes mol and _mol not matched.
+        '''
+        Chem.SetAromaticity(mol)
+        Chem.SetAromaticity(_mol)
+        substruct_match = mol.GetSubstructMatch(_mol)
+    try:
+        atom_match = {substruct_match[_mol_atom_idx]: _mol_atom_idx for _mol_atom_idx in range(_mol.GetNumAtoms())} # mol to _mol
+    except:
+        raise ValueError('two molecules obtained from the same data do not match.')
+        
+    for each_bond in mol.GetBonds():
+        begin_atom_idx = each_bond.GetBeginAtomIdx()
+        end_atom_idx = each_bond.GetEndAtomIdx()
+        _bond = _mol.GetBondBetweenAtoms(atom_match[begin_atom_idx], atom_match[end_atom_idx])
+        _bond.SetStereo(each_bond.GetStereo())
+
+    mol = _mol
+    for each_bond in mol.GetBonds():
+        if int(each_bond.GetStereo()) in [2, 3]: #2=Z (same side), 3=E
+            begin_stereo_atom_idx = each_bond.GetBeginAtomIdx()
+            end_stereo_atom_idx = each_bond.GetEndAtomIdx()
+            begin_atom_idx_set = set([each_neighbor.GetIdx()
+                                      for each_neighbor
+                                      in mol.GetAtomWithIdx(begin_stereo_atom_idx).GetNeighbors()
+                                      if each_neighbor.GetIdx() != end_stereo_atom_idx])
+            end_atom_idx_set = set([each_neighbor.GetIdx()
+                                    for each_neighbor
+                                    in mol.GetAtomWithIdx(end_stereo_atom_idx).GetNeighbors()
+                                    if each_neighbor.GetIdx() != begin_stereo_atom_idx])
+            if not begin_atom_idx_set:
+                each_bond.SetStereo(Chem.rdchem.BondStereo(0))
+                continue
+            if not end_atom_idx_set:
+                each_bond.SetStereo(Chem.rdchem.BondStereo(0))
+                continue
+            if len(begin_atom_idx_set) == 1:
+                begin_atom_idx = begin_atom_idx_set.pop()
+                begin_another_atom_idx = None
+            if len(end_atom_idx_set) == 1:
+                end_atom_idx = end_atom_idx_set.pop()
+                end_another_atom_idx = None
+            if len(begin_atom_idx_set) == 2:
+                atom_idx_1 = begin_atom_idx_set.pop()
+                atom_idx_2 = begin_atom_idx_set.pop()
+                if int(mol.GetAtomWithIdx(atom_idx_1).GetProp('_CIPRank')) < int(mol.GetAtomWithIdx(atom_idx_2).GetProp('_CIPRank')):
+                    begin_atom_idx = atom_idx_1
+                    begin_another_atom_idx = atom_idx_2
+                else:
+                    begin_atom_idx = atom_idx_2
+                    begin_another_atom_idx = atom_idx_1
+            if len(end_atom_idx_set) == 2:
+                atom_idx_1 = end_atom_idx_set.pop()
+                atom_idx_2 = end_atom_idx_set.pop()
+                if int(mol.GetAtomWithIdx(atom_idx_1).GetProp('_CIPRank')) < int(mol.GetAtomWithIdx(atom_idx_2).GetProp('_CIPRank')):
+                    end_atom_idx = atom_idx_1
+                    end_another_atom_idx = atom_idx_2
+                else:
+                    end_atom_idx = atom_idx_2
+                    end_another_atom_idx = atom_idx_1
+
+            if each_bond.GetStereo() == 2: # same side
+                mol = safe_set_bond_dir(mol, begin_atom_idx, begin_stereo_atom_idx, 3)
+                mol = safe_set_bond_dir(mol, end_atom_idx, end_stereo_atom_idx, 4)
+                each_bond.SetStereoAtoms(begin_atom_idx, end_atom_idx)
+            elif each_bond.GetStereo() == 3: # opposite side
+                mol = safe_set_bond_dir(mol, begin_atom_idx, begin_stereo_atom_idx, 3)
+                mol = safe_set_bond_dir(mol, end_atom_idx, end_stereo_atom_idx, 3)
+                each_bond.SetStereoAtoms(begin_atom_idx, end_atom_idx)
+            else:
+                raise ValueError
+    return mol
+
+
+def safe_set_bond_dir(mol, atom_idx_1, atom_idx_2, bond_dir_val):
+    if atom_idx_1 is None or atom_idx_2 is None:
+        return mol
+    else:
+        mol.GetBondBetweenAtoms(atom_idx_1, atom_idx_2).SetBondDir(Chem.rdchem.BondDir.values[bond_dir_val])
+        return mol
+        

mol_moe/experts/mhg_model/graph_grammar/nn/__init__.py

@@ -0,0 +1,11 @@
+# -*- coding:utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES THE ORIGINAL SOURCE CODE (AND SOME ADAPTATIONS)
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE. 
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""

mol_moe/experts/mhg_model/graph_grammar/nn/dataset.py

@@ -0,0 +1,121 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES THE ORIGINAL SOURCE CODE (AND SOME ADAPTATIONS)
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE. 
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""
+
+""" Title """
+
+__author__ = "Hiroshi Kajino <[email protected]>"
+__copyright__ = "(c) Copyright IBM Corp. 2018"
+__version__ = "0.1"
+__date__ = "Apr 18 2018"
+
+from torch.utils.data import Dataset, DataLoader
+import torch
+import numpy as np
+
+
+def left_padding(sentence_list, max_len, pad_idx=-1, inverse=False):
+    ''' pad left
+
+    Parameters
+    ----------
+    sentence_list : list of sequences of integers
+    max_len : int
+        maximum length of sentences.
+        if a sentence is shorter than `max_len`, its left part is padded.
+    pad_idx : int
+        integer for padding
+    inverse : bool
+        if True, the sequence is inversed.
+
+    Returns
+    -------
+    List of torch.LongTensor
+        each sentence is left-padded.
+    '''
+    max_in_list = max([len(each_sen) for each_sen in sentence_list])
+        
+    if max_in_list > max_len:
+        raise ValueError('`max_len` should be larger than the maximum length of input sequences, {}.'.format(max_in_list))
+
+    if inverse:
+        return [torch.LongTensor([pad_idx] * (max_len - len(each_sen)) + each_sen[::-1]) for each_sen in sentence_list]
+    else:
+        return [torch.LongTensor([pad_idx] * (max_len - len(each_sen)) + each_sen) for each_sen in sentence_list]
+
+
+def right_padding(sentence_list, max_len, pad_idx=-1):
+    ''' pad right
+
+    Parameters
+    ----------
+    sentence_list : list of sequences of integers
+    max_len : int
+        maximum length of sentences.
+        if a sentence is shorter than `max_len`, its right part is padded.
+    pad_idx : int
+        integer for padding
+
+    Returns
+    -------
+    List of torch.LongTensor
+        each sentence is right-padded.
+    '''
+    max_in_list = max([len(each_sen) for each_sen in sentence_list])
+    if max_in_list > max_len:
+        raise ValueError('`max_len` should be larger than the maximum length of input sequences, {}.'.format(max_in_list))
+
+    return [torch.LongTensor(each_sen + [pad_idx] * (max_len - len(each_sen))) for each_sen in sentence_list]
+
+
+class HRGDataset(Dataset):
+
+    '''
+    A class of HRG data
+    '''
+
+    def __init__(self, hrg, prod_rule_seq_list, max_len, target_val_list=None, inversed_input=False):
+        self.hrg = hrg
+        self.left_prod_rule_seq_list = left_padding(prod_rule_seq_list,
+                                                    max_len,
+                                                    inverse=inversed_input)
+            
+        self.right_prod_rule_seq_list = right_padding(prod_rule_seq_list, max_len)
+        self.inserved_input = inversed_input
+        self.target_val_list = target_val_list
+        if target_val_list is not None:
+            if len(prod_rule_seq_list) != len(target_val_list):
+                raise ValueError(f'prod_rule_seq_list and target_val_list have inconsistent lengths: {len(prod_rule_seq_list)}, {len(target_val_list)}')
+
+    def __len__(self):
+        return len(self.left_prod_rule_seq_list)
+
+    def __getitem__(self, idx):
+        if self.target_val_list is not None:
+            return self.left_prod_rule_seq_list[idx], self.right_prod_rule_seq_list[idx], np.float32(self.target_val_list[idx])
+        else:
+            return self.left_prod_rule_seq_list[idx], self.right_prod_rule_seq_list[idx]
+
+    @property
+    def vocab_size(self):
+        return self.hrg.num_prod_rule
+
+def batch_padding(each_batch, batch_size, padding_idx):
+    num_pad = batch_size - len(each_batch[0])
+    if num_pad:
+        each_batch[0] = torch.cat([each_batch[0],
+                                   padding_idx * torch.ones((batch_size - len(each_batch[0]),
+                                                             len(each_batch[0][0])), dtype=torch.int64)], dim=0)
+        each_batch[1] = torch.cat([each_batch[1],
+                                   padding_idx * torch.ones((batch_size - len(each_batch[1]),
+                                                             len(each_batch[1][0])), dtype=torch.int64)], dim=0)
+    return each_batch, num_pad

mol_moe/experts/mhg_model/graph_grammar/nn/decoder.py

@@ -0,0 +1,158 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES THE ORIGINAL SOURCE CODE (AND SOME ADAPTATIONS)
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE. 
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""
+
+""" Title """
+
+__author__ = "Hiroshi Kajino <[email protected]>"
+__copyright__ = "(c) Copyright IBM Corp. 2018"
+__version__ = "0.1"
+__date__ = "Aug 9 2018"
+
+
+import abc
+import numpy as np
+import torch
+from torch import nn
+
+
+class DecoderBase(nn.Module):
+
+    def __init__(self):
+        super().__init__()
+        self.hidden_dict = {}
+
+    @abc.abstractmethod
+    def forward_one_step(self, tgt_emb_in):
+        ''' one-step forward model
+
+        Parameters
+        ----------
+        tgt_emb_in : Tensor, shape (batch_size, input_dim)
+
+        Returns
+        -------
+        Tensor, shape (batch_size, hidden_dim)
+        '''
+        tgt_emb_out = None
+        return tgt_emb_out
+
+    @abc.abstractmethod
+    def init_hidden(self):
+        ''' initialize the hidden states
+        '''
+        pass
+
+    @abc.abstractmethod
+    def feed_hidden(self, hidden_dict_0):
+        for each_hidden in self.hidden_dict.keys():
+            self.hidden_dict[each_hidden][0] = hidden_dict_0[each_hidden]
+
+
+class GRUDecoder(DecoderBase):
+
+    def __init__(self, input_dim: int, hidden_dim: int, num_layers: int,
+                 dropout: float, batch_size: int, use_gpu: bool,
+                 no_dropout=False):
+        super().__init__()
+        self.input_dim = input_dim
+        self.hidden_dim = hidden_dim
+        self.num_layers = num_layers
+        self.dropout = dropout
+        self.batch_size = batch_size
+        self.use_gpu = use_gpu
+        self.model = nn.GRU(input_size=self.input_dim,
+                            hidden_size=self.hidden_dim,
+                            num_layers=self.num_layers,
+                            batch_first=True,
+                            bidirectional=False,
+                            dropout=self.dropout if not no_dropout else 0
+        )
+        if self.use_gpu:
+            self.model.cuda()
+        self.init_hidden()
+
+    def init_hidden(self):
+        self.hidden_dict['h'] = torch.zeros((self.num_layers,
+                                             self.batch_size,
+                                             self.hidden_dim),
+                                            requires_grad=False)
+        if self.use_gpu:
+            self.hidden_dict['h'] = self.hidden_dict['h'].cuda()
+
+    def forward_one_step(self, tgt_emb_in):
+        ''' one-step forward model
+
+        Parameters
+        ----------
+        tgt_emb_in : Tensor, shape (batch_size, input_dim)
+
+        Returns
+        -------
+        Tensor, shape (batch_size, hidden_dim)
+        '''
+        tgt_emb_out, self.hidden_dict['h'] \
+            = self.model(tgt_emb_in.view(self.batch_size, 1, -1),
+                         self.hidden_dict['h'])
+        return tgt_emb_out
+
+
+class LSTMDecoder(DecoderBase):
+
+    def __init__(self, input_dim: int, hidden_dim: int, num_layers: int,
+                 dropout: float, batch_size: int, use_gpu: bool,
+                 no_dropout=False):
+        super().__init__()
+        self.input_dim = input_dim
+        self.hidden_dim = hidden_dim
+        self.num_layers = num_layers
+        self.dropout = dropout
+        self.batch_size = batch_size
+        self.use_gpu = use_gpu
+        self.model = nn.LSTM(input_size=self.input_dim,
+                             hidden_size=self.hidden_dim,
+                             num_layers=self.num_layers,
+                             batch_first=True,
+                             bidirectional=False,
+                             dropout=self.dropout if not no_dropout else 0)
+        if self.use_gpu:
+            self.model.cuda()
+        self.init_hidden()
+
+    def init_hidden(self):
+        self.hidden_dict['h'] = torch.zeros((self.num_layers,
+                                             self.batch_size,
+                                             self.hidden_dim),
+                                            requires_grad=False)
+        self.hidden_dict['c'] = torch.zeros((self.num_layers,
+                                             self.batch_size,
+                                             self.hidden_dim),
+                                            requires_grad=False)
+        if self.use_gpu:
+            for each_hidden in self.hidden_dict.keys():
+                self.hidden_dict[each_hidden] = self.hidden_dict[each_hidden].cuda()
+
+    def forward_one_step(self, tgt_emb_in):
+        ''' one-step forward model
+
+        Parameters
+        ----------
+        tgt_emb_in : Tensor, shape (batch_size, input_dim)
+
+        Returns
+        -------
+        Tensor, shape (batch_size, hidden_dim)
+        '''
+        tgt_hidden_out, self.hidden_dict['h'], self.hidden_dict['c'] \
+            = self.model(tgt_emb_in.view(self.batch_size, 1, -1),
+                         self.hidden_dict['h'], self.hidden_dict['c'])
+        return tgt_hidden_out

mol_moe/experts/mhg_model/graph_grammar/nn/encoder.py

@@ -0,0 +1,199 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES THE ORIGINAL SOURCE CODE (AND SOME ADAPTATIONS)
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE. 
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""
+
+""" Title """
+
+__author__ = "Hiroshi Kajino <[email protected]>"
+__copyright__ = "(c) Copyright IBM Corp. 2018"
+__version__ = "0.1"
+__date__ = "Aug 9 2018"
+
+
+import abc
+import numpy as np
+import torch
+import torch.nn.functional as F
+from torch import nn
+from typing import List
+
+
+class EncoderBase(nn.Module):
+
+    def __init__(self):
+        super().__init__()
+
+    @abc.abstractmethod
+    def forward(self, in_seq):
+        ''' forward model
+
+        Parameters
+        ----------
+        in_seq_emb : Variable, shape (batch_size, max_len, input_dim)
+
+        Returns
+        -------
+        hidden_seq_emb : Tensor, shape (batch_size, max_len, 1 + bidirectional, hidden_dim)
+        '''
+        pass
+
+    @abc.abstractmethod
+    def init_hidden(self):
+        ''' initialize the hidden states
+        '''
+        pass
+
+
+class GRUEncoder(EncoderBase):
+
+    def __init__(self, input_dim: int, hidden_dim: int, num_layers: int,
+                 bidirectional: bool, dropout: float, batch_size: int, use_gpu: bool,
+                 no_dropout=False):
+        super().__init__()
+        self.input_dim = input_dim
+        self.hidden_dim = hidden_dim
+        self.num_layers = num_layers
+        self.bidirectional = bidirectional
+        self.dropout = dropout
+        self.batch_size = batch_size
+        self.use_gpu = use_gpu
+        self.model = nn.GRU(input_size=self.input_dim,
+                            hidden_size=self.hidden_dim,
+                            num_layers=self.num_layers,
+                            batch_first=True,
+                            bidirectional=self.bidirectional,
+                            dropout=self.dropout if not no_dropout else 0)
+        if self.use_gpu:
+            self.model.cuda()
+        self.init_hidden()
+
+
+    def init_hidden(self):
+        self.h0 = torch.zeros(((self.bidirectional + 1) * self.num_layers,
+                               self.batch_size,
+                               self.hidden_dim),
+                              requires_grad=False)
+        if self.use_gpu:        
+            self.h0 = self.h0.cuda()
+
+    def forward(self, in_seq_emb):
+        ''' forward model
+
+        Parameters
+        ----------
+        in_seq_emb : Tensor, shape (batch_size, max_len, input_dim)
+
+        Returns
+        -------
+        hidden_seq_emb : Tensor, shape (batch_size, max_len, 1 + bidirectional, hidden_dim)
+        '''
+        max_len = in_seq_emb.size(1)
+        hidden_seq_emb, self.h0 = self.model(
+            in_seq_emb, self.h0)
+        hidden_seq_emb = hidden_seq_emb.view(self.batch_size,
+                                             max_len,
+                                             1 + self.bidirectional,
+                                             self.hidden_dim)
+        return hidden_seq_emb
+
+
+class LSTMEncoder(EncoderBase):
+
+    def __init__(self, input_dim: int, hidden_dim: int, num_layers: int,
+                 bidirectional: bool, dropout: float, batch_size: int, use_gpu: bool,
+                 no_dropout=False):
+        super().__init__()
+        self.input_dim = input_dim
+        self.hidden_dim = hidden_dim
+        self.num_layers = num_layers
+        self.bidirectional = bidirectional
+        self.dropout = dropout
+        self.batch_size = batch_size
+        self.use_gpu = use_gpu
+        self.model = nn.LSTM(input_size=self.input_dim,
+                             hidden_size=self.hidden_dim,
+                             num_layers=self.num_layers,
+                             batch_first=True,
+                             bidirectional=self.bidirectional,
+                             dropout=self.dropout if not no_dropout else 0)
+        if self.use_gpu:
+            self.model.cuda()
+        self.init_hidden()
+
+    def init_hidden(self):
+        self.h0 = torch.zeros(((self.bidirectional + 1) * self.num_layers,
+                               self.batch_size,
+                               self.hidden_dim),
+                              requires_grad=False)
+        self.c0 = torch.zeros(((self.bidirectional + 1) * self.num_layers,
+                               self.batch_size,
+                               self.hidden_dim),
+                              requires_grad=False)
+        if self.use_gpu:        
+            self.h0 = self.h0.cuda()
+            self.c0 = self.c0.cuda()
+
+    def forward(self, in_seq_emb):
+        ''' forward model
+
+        Parameters
+        ----------
+        in_seq_emb : Tensor, shape (batch_size, max_len, input_dim)
+
+        Returns
+        -------
+        hidden_seq_emb : Tensor, shape (batch_size, max_len, 1 + bidirectional, hidden_dim)
+        '''
+        max_len = in_seq_emb.size(1)
+        hidden_seq_emb, (self.h0, self.c0) = self.model(
+            in_seq_emb, (self.h0, self.c0))
+        hidden_seq_emb = hidden_seq_emb.view(self.batch_size,
+                                             max_len,
+                                             1 + self.bidirectional,
+                                             self.hidden_dim)
+        return hidden_seq_emb
+
+
+class FullConnectedEncoder(EncoderBase):
+
+    def __init__(self, input_dim: int, hidden_dim: int, max_len: int, hidden_dim_list: List[int],
+                 batch_size: int, use_gpu: bool):
+        super().__init__()
+        self.input_dim = input_dim
+        self.hidden_dim = hidden_dim
+        self.max_len = max_len
+        self.hidden_dim_list = hidden_dim_list
+        self.use_gpu = use_gpu
+        in_out_dim_list = [input_dim * max_len] + list(hidden_dim_list) + [hidden_dim]
+        self.linear_list = nn.ModuleList(
+            [nn.Linear(in_out_dim_list[each_idx], in_out_dim_list[each_idx + 1])\
+             for each_idx in range(len(in_out_dim_list) - 1)])
+
+    def forward(self, in_seq_emb):
+        ''' forward model
+
+        Parameters
+        ----------
+        in_seq_emb : Tensor, shape (batch_size, max_len, input_dim)
+
+        Returns
+        -------
+        hidden_seq_emb : Tensor, shape (batch_size, max_len, 1 + bidirectional, hidden_dim)
+        '''
+        batch_size = in_seq_emb.size(0)
+        x = in_seq_emb.view(batch_size, -1)
+        for each_linear in self.linear_list:
+            x = F.relu(each_linear(x))
+        return x.view(batch_size, 1, -1)
+
+    def init_hidden(self):
+        pass

mol_moe/experts/mhg_model/graph_grammar/nn/graph.py

@@ -0,0 +1,313 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES THE ORIGINAL SOURCE CODE (AND SOME ADAPTATIONS)
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE. 
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""
+
+""" Title """
+
+__author__ = "Hiroshi Kajino <[email protected]>"
+__copyright__ = "(c) Copyright IBM Corp. 2018"
+__version__ = "0.1"
+__date__ = "Jan 1 2018"
+
+import numpy as np
+import torch
+import torch.nn.functional as F
+from graph_grammar.graph_grammar.hrg import ProductionRuleCorpus
+from torch import nn
+from torch.autograd import Variable
+
+class MolecularProdRuleEmbedding(nn.Module):
+    
+    ''' molecular fingerprint layer
+    '''
+
+    def __init__(self, prod_rule_corpus, layer2layer_activation, layer2out_activation,
+                 out_dim=32, element_embed_dim=32,
+                 num_layers=3, padding_idx=None, use_gpu=False):
+        super().__init__()
+        if padding_idx is not None:
+            assert padding_idx == -1, 'padding_idx must be -1.'
+        self.prod_rule_corpus = prod_rule_corpus
+        self.layer2layer_activation = layer2layer_activation
+        self.layer2out_activation = layer2out_activation
+        self.out_dim = out_dim
+        self.element_embed_dim = element_embed_dim
+        self.num_layers = num_layers
+        self.padding_idx = padding_idx
+        self.use_gpu = use_gpu
+
+        self.layer2layer_list = []
+        self.layer2out_list = []
+
+        if self.use_gpu:
+            self.atom_embed = torch.randn(self.prod_rule_corpus.num_edge_symbol,
+                                          self.element_embed_dim, requires_grad=True).cuda()
+            self.bond_embed = torch.randn(self.prod_rule_corpus.num_node_symbol,
+                                          self.element_embed_dim, requires_grad=True).cuda()
+            self.ext_id_embed = torch.randn(self.prod_rule_corpus.num_ext_id,
+                                            self.element_embed_dim, requires_grad=True).cuda()
+            for _ in range(num_layers):
+                self.layer2layer_list.append(nn.Linear(self.element_embed_dim, self.element_embed_dim).cuda())
+                self.layer2out_list.append(nn.Linear(self.element_embed_dim, self.out_dim).cuda())
+        else:
+            self.atom_embed = torch.randn(self.prod_rule_corpus.num_edge_symbol,
+                                          self.element_embed_dim, requires_grad=True)
+            self.bond_embed = torch.randn(self.prod_rule_corpus.num_node_symbol,
+                                          self.element_embed_dim, requires_grad=True)
+            self.ext_id_embed = torch.randn(self.prod_rule_corpus.num_ext_id,
+                                            self.element_embed_dim, requires_grad=True)
+            for _ in range(num_layers):
+                self.layer2layer_list.append(nn.Linear(self.element_embed_dim, self.element_embed_dim))
+                self.layer2out_list.append(nn.Linear(self.element_embed_dim, self.out_dim))
+
+
+    def forward(self, prod_rule_idx_seq):
+        ''' forward model for mini-batch
+
+        Parameters
+        ----------
+        prod_rule_idx_seq : (batch_size, length)
+
+        Returns
+        -------
+        Variable, shape (batch_size, length, out_dim)
+        '''
+        batch_size, length = prod_rule_idx_seq.shape
+        if self.use_gpu:
+            out = Variable(torch.zeros((batch_size, length, self.out_dim))).cuda()
+        else:
+            out = Variable(torch.zeros((batch_size, length, self.out_dim)))
+        for each_batch_idx in range(batch_size):
+            for each_idx in range(length):
+                if int(prod_rule_idx_seq[each_batch_idx, each_idx]) == len(self.prod_rule_corpus.prod_rule_list):
+                    continue
+                else:
+                    each_prod_rule = self.prod_rule_corpus.prod_rule_list[int(prod_rule_idx_seq[each_batch_idx, each_idx])]
+                    layer_wise_embed_dict = {each_edge: self.atom_embed[
+                        each_prod_rule.rhs.edge_attr(each_edge)['symbol_idx']]
+                                             for each_edge in each_prod_rule.rhs.edges}
+                    layer_wise_embed_dict.update({each_node: self.bond_embed[
+                        each_prod_rule.rhs.node_attr(each_node)['symbol_idx']]
+                                                  for each_node in each_prod_rule.rhs.nodes})
+                    for each_node in each_prod_rule.rhs.nodes:
+                        if 'ext_id' in each_prod_rule.rhs.node_attr(each_node):
+                            layer_wise_embed_dict[each_node] \
+                                = layer_wise_embed_dict[each_node] \
+                                + self.ext_id_embed[each_prod_rule.rhs.node_attr(each_node)['ext_id']]
+
+                    for each_layer in range(self.num_layers):
+                        next_layer_embed_dict = {}
+                        for each_edge in each_prod_rule.rhs.edges:
+                            v = layer_wise_embed_dict[each_edge]
+                            for each_node in each_prod_rule.rhs.nodes_in_edge(each_edge):
+                                v = v + layer_wise_embed_dict[each_node]
+                            next_layer_embed_dict[each_edge] = self.layer2layer_activation(self.layer2layer_list[each_layer](v))
+                            out[each_batch_idx, each_idx, :] \
+                                = out[each_batch_idx, each_idx, :] + self.layer2out_activation(self.layer2out_list[each_layer](v))
+                        for each_node in each_prod_rule.rhs.nodes:
+                            v = layer_wise_embed_dict[each_node]
+                            for each_edge in each_prod_rule.rhs.adj_edges(each_node):
+                                v = v + layer_wise_embed_dict[each_edge]
+                            next_layer_embed_dict[each_node] = self.layer2layer_activation(self.layer2layer_list[each_layer](v))
+                            out[each_batch_idx, each_idx, :]\
+                                = out[each_batch_idx, each_idx, :] + self.layer2out_activation(self.layer2out_list[each_layer](v))
+                        layer_wise_embed_dict = next_layer_embed_dict
+                        
+        return out
+
+
+class MolecularProdRuleEmbeddingLastLayer(nn.Module):
+    
+    ''' molecular fingerprint layer
+    '''
+
+    def __init__(self, prod_rule_corpus, layer2layer_activation, layer2out_activation,
+                 out_dim=32, element_embed_dim=32,
+                 num_layers=3, padding_idx=None, use_gpu=False):
+        super().__init__()
+        if padding_idx is not None:
+            assert padding_idx == -1, 'padding_idx must be -1.'
+        self.prod_rule_corpus = prod_rule_corpus
+        self.layer2layer_activation = layer2layer_activation
+        self.layer2out_activation = layer2out_activation
+        self.out_dim = out_dim
+        self.element_embed_dim = element_embed_dim
+        self.num_layers = num_layers
+        self.padding_idx = padding_idx
+        self.use_gpu = use_gpu
+
+        self.layer2layer_list = []
+        self.layer2out_list = []
+
+        if self.use_gpu:
+            self.atom_embed = nn.Embedding(self.prod_rule_corpus.num_edge_symbol, self.element_embed_dim).cuda()
+            self.bond_embed = nn.Embedding(self.prod_rule_corpus.num_node_symbol, self.element_embed_dim).cuda()
+            for _ in range(num_layers+1):
+                self.layer2layer_list.append(nn.Linear(self.element_embed_dim, self.element_embed_dim).cuda())
+                self.layer2out_list.append(nn.Linear(self.element_embed_dim, self.out_dim).cuda())
+        else:
+            self.atom_embed = nn.Embedding(self.prod_rule_corpus.num_edge_symbol, self.element_embed_dim)
+            self.bond_embed = nn.Embedding(self.prod_rule_corpus.num_node_symbol, self.element_embed_dim)
+            for _ in range(num_layers+1):
+                self.layer2layer_list.append(nn.Linear(self.element_embed_dim, self.element_embed_dim))
+                self.layer2out_list.append(nn.Linear(self.element_embed_dim, self.out_dim))
+
+
+    def forward(self, prod_rule_idx_seq):
+        ''' forward model for mini-batch
+
+        Parameters
+        ----------
+        prod_rule_idx_seq : (batch_size, length)
+
+        Returns
+        -------
+        Variable, shape (batch_size, length, out_dim)
+        '''
+        batch_size, length = prod_rule_idx_seq.shape
+        if self.use_gpu:
+            out = Variable(torch.zeros((batch_size, length, self.out_dim))).cuda()
+        else:
+            out = Variable(torch.zeros((batch_size, length, self.out_dim)))
+        for each_batch_idx in range(batch_size):
+            for each_idx in range(length):
+                if int(prod_rule_idx_seq[each_batch_idx, each_idx]) == len(self.prod_rule_corpus.prod_rule_list):
+                    continue
+                else:
+                    each_prod_rule = self.prod_rule_corpus.prod_rule_list[int(prod_rule_idx_seq[each_batch_idx, each_idx])]
+
+                    if self.use_gpu:
+                        layer_wise_embed_dict = {each_edge: self.atom_embed(
+                            Variable(torch.LongTensor(
+                                [each_prod_rule.rhs.edge_attr(each_edge)['symbol_idx']]
+                            ), requires_grad=False).cuda())
+                                                 for each_edge in each_prod_rule.rhs.edges}
+                        layer_wise_embed_dict.update({each_node: self.bond_embed(
+                                                         Variable(
+                                                             torch.LongTensor([
+                                                                     each_prod_rule.rhs.node_attr(each_node)['symbol_idx']]),
+                                                             requires_grad=False).cuda()
+                                                     ) for each_node in each_prod_rule.rhs.nodes})
+                    else:
+                        layer_wise_embed_dict = {each_edge: self.atom_embed(
+                            Variable(torch.LongTensor(
+                                [each_prod_rule.rhs.edge_attr(each_edge)['symbol_idx']]
+                            ), requires_grad=False))
+                                                 for each_edge in each_prod_rule.rhs.edges}
+                        layer_wise_embed_dict.update({each_node: self.bond_embed(
+                                                         Variable(
+                                                             torch.LongTensor([
+                                                                     each_prod_rule.rhs.node_attr(each_node)['symbol_idx']]), 
+                                                             requires_grad=False)
+                                                     ) for each_node in each_prod_rule.rhs.nodes})
+
+                    for each_layer in range(self.num_layers):
+                        next_layer_embed_dict = {}
+                        for each_edge in each_prod_rule.rhs.edges:
+                            v = layer_wise_embed_dict[each_edge]
+                            for each_node in each_prod_rule.rhs.nodes_in_edge(each_edge):
+                                v += layer_wise_embed_dict[each_node]
+                            next_layer_embed_dict[each_edge] = self.layer2layer_activation(self.layer2layer_list[each_layer](v))
+                        for each_node in each_prod_rule.rhs.nodes:
+                            v = layer_wise_embed_dict[each_node]
+                            for each_edge in each_prod_rule.rhs.adj_edges(each_node):
+                                v += layer_wise_embed_dict[each_edge]
+                            next_layer_embed_dict[each_node] = self.layer2layer_activation(self.layer2layer_list[each_layer](v))
+                        layer_wise_embed_dict = next_layer_embed_dict
+                    for each_edge in each_prod_rule.rhs.edges:
+                        out[each_batch_idx, each_idx, :] = self.layer2out_activation(self.layer2out_list[self.num_layers](v))
+                    for each_edge in each_prod_rule.rhs.edges:
+                        out[each_batch_idx, each_idx, :] = self.layer2out_activation(self.layer2out_list[self.num_layers](v))
+                        
+        return out
+
+
+class MolecularProdRuleEmbeddingUsingFeatures(nn.Module):
+    
+    ''' molecular fingerprint layer
+    '''
+
+    def __init__(self, prod_rule_corpus, layer2layer_activation, layer2out_activation,
+                 out_dim=32, num_layers=3, padding_idx=None, use_gpu=False):
+        super().__init__()
+        if padding_idx is not None:
+            assert padding_idx == -1, 'padding_idx must be -1.'
+        self.feature_dict, self.feature_dim = prod_rule_corpus.construct_feature_vectors()
+        self.prod_rule_corpus = prod_rule_corpus
+        self.layer2layer_activation = layer2layer_activation
+        self.layer2out_activation = layer2out_activation
+        self.out_dim = out_dim
+        self.num_layers = num_layers
+        self.padding_idx = padding_idx
+        self.use_gpu = use_gpu
+
+        self.layer2layer_list = []
+        self.layer2out_list = []
+
+        if self.use_gpu:
+            for each_key in self.feature_dict:
+                self.feature_dict[each_key] = self.feature_dict[each_key].to_dense().cuda()
+            for _ in range(num_layers):
+                self.layer2layer_list.append(nn.Linear(self.feature_dim, self.feature_dim).cuda())
+                self.layer2out_list.append(nn.Linear(self.feature_dim, self.out_dim).cuda())
+        else:
+            for _ in range(num_layers):
+                self.layer2layer_list.append(nn.Linear(self.feature_dim, self.feature_dim))
+                self.layer2out_list.append(nn.Linear(self.feature_dim, self.out_dim))
+
+
+    def forward(self, prod_rule_idx_seq):
+        ''' forward model for mini-batch
+
+        Parameters
+        ----------
+        prod_rule_idx_seq : (batch_size, length)
+
+        Returns
+        -------
+        Variable, shape (batch_size, length, out_dim)
+        '''
+        batch_size, length = prod_rule_idx_seq.shape
+        if self.use_gpu:
+            out = Variable(torch.zeros((batch_size, length, self.out_dim))).cuda()
+        else:
+            out = Variable(torch.zeros((batch_size, length, self.out_dim)))
+        for each_batch_idx in range(batch_size):
+            for each_idx in range(length):
+                if int(prod_rule_idx_seq[each_batch_idx, each_idx]) == len(self.prod_rule_corpus.prod_rule_list):
+                    continue
+                else:
+                    each_prod_rule = self.prod_rule_corpus.prod_rule_list[int(prod_rule_idx_seq[each_batch_idx, each_idx])]
+                    edge_list = sorted(list(each_prod_rule.rhs.edges))
+                    node_list = sorted(list(each_prod_rule.rhs.nodes))
+                    adj_mat = torch.FloatTensor(each_prod_rule.rhs_adj_mat(edge_list + node_list).todense() + np.identity(len(edge_list)+len(node_list)))
+                    if self.use_gpu:
+                        adj_mat = adj_mat.cuda()
+                    layer_wise_embed = [
+                        self.feature_dict[each_prod_rule.rhs.edge_attr(each_edge)['symbol']]
+                        for each_edge in edge_list]\
+                            + [self.feature_dict[each_prod_rule.rhs.node_attr(each_node)['symbol']]
+                               for each_node in node_list]
+                    for each_node in each_prod_rule.ext_node.values():
+                        layer_wise_embed[each_prod_rule.rhs.num_edges + node_list.index(each_node)] \
+                                = layer_wise_embed[each_prod_rule.rhs.num_edges + node_list.index(each_node)] \
+                                + self.feature_dict[('ext_id', each_prod_rule.rhs.node_attr(each_node)['ext_id'])]
+                    layer_wise_embed = torch.stack(layer_wise_embed)
+
+                    for each_layer in range(self.num_layers):
+                        message = adj_mat @ layer_wise_embed
+                        next_layer_embed = self.layer2layer_activation(self.layer2layer_list[each_layer](message))
+                        out[each_batch_idx, each_idx, :] \
+                                = out[each_batch_idx, each_idx, :] \
+                                + self.layer2out_activation(self.layer2out_list[each_layer](message)).sum(dim=0)
+                        layer_wise_embed = next_layer_embed
+        return out

mol_moe/experts/mhg_model/load.py

@@ -0,0 +1,104 @@
+# -*- coding:utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+import os
+import pickle
+import sys
+sys.path.insert(1, '../')
+
+from rdkit import Chem
+import torch
+from torch_geometric.utils.smiles import from_smiles
+
+from typing import Any, Dict, List, Optional, Union
+from typing_extensions import Self
+
+from .graph_grammar.io.smi import hg_to_mol
+from .models.mhgvae import GrammarGINVAE
+
+from huggingface_hub import hf_hub_download
+
+
+class PretrainedModelWrapper:
+    model: GrammarGINVAE
+
+    def __init__(self, model_dict: Dict[str, Any]) -> None:
+        json_params = model_dict['gnn_params']
+        encoder_params = json_params['encoder_params']
+        encoder_params['node_feature_size'] = model_dict['num_features']
+        encoder_params['edge_feature_size'] = model_dict['num_edge_features']
+        self.model = GrammarGINVAE(model_dict['hrg'], rank=-1, encoder_params=encoder_params,
+                                   decoder_params=json_params['decoder_params'],
+                                   prod_rule_embed_params=json_params["prod_rule_embed_params"],
+                                   batch_size=512, max_len=model_dict['max_length'])
+        self.model.load_state_dict(model_dict['model_state_dict'])
+
+        self.model.eval()
+
+    def to(self, device: Union[str, int, torch.device]) -> Self:
+        dev_type = type(device)
+        if dev_type != torch.device:
+            if dev_type == str or torch.cuda.is_available():
+                device = torch.device(device)
+            else:
+                device = torch.device("mps", device)
+
+        self.model = self.model.to(device)
+        return self
+
+    def encode(self, data: List[str]) -> List[torch.tensor]:
+        # Need to encode them into a graph nn
+        output = []
+        for d in data:
+            params = next(self.model.parameters())
+            g = from_smiles(d)
+            if (g.cpu() and params != 'cpu') or (not g.cpu() and params == 'cpu'):
+                g.to(params.device)
+            ltvec = self.model.graph_embed(g.x, g.edge_index, g.edge_attr, g.batch)
+            output.append(ltvec[0])
+        return output
+
+    def decode(self, data: List[torch.tensor]) -> List[str]:
+        output = []
+        for d in data:
+            mu, logvar = self.model.get_mean_var(d.unsqueeze(0))
+            z = self.model.reparameterize(mu, logvar)
+            flags, _, hgs = self.model.decode(z)
+            if flags[0]:
+                reconstructed_mol, _ = hg_to_mol(hgs[0], True)
+                output.append(Chem.MolToSmiles(reconstructed_mol))
+            else:
+                output.append(None)
+        return output
+
+
+def load(model_name: str = "mhg_model/pickles/mhggnn_pretrained_model_0724_2023.pickle") -> Optional[
+    PretrainedModelWrapper]:
+
+    repo_id = "ibm/materials.mhg-ged"
+    filename = "pytorch_model.bin" #"mhggnn_pretrained_model_0724_2023.pickle"
+    file_path = hf_hub_download(repo_id=repo_id, filename=filename)
+    with open(file_path, "rb") as f:
+        model_dict = torch.load(f, weights_only=False)
+        return PretrainedModelWrapper(model_dict)
+
+
+    """try:
+        if os.path.isfile(model_name):
+            with open(model_name, "rb") as f:
+                model_dict = pickle.load(f)
+                print("MHG Model Loaded")
+                return PretrainedModelWrapper(model_dict)
+
+    except:
+
+        for p in sys.path:
+            file = p + "/" + model_name
+            if os.path.isfile(file):
+                with open(file, "rb") as f:
+                    model_dict = pickle.load(f)
+                    return PretrainedModelWrapper(model_dict)"""
+    return None

mol_moe/experts/mhg_model/models/__init__.py

@@ -0,0 +1,5 @@
+# -*- coding:utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#

mol_moe/experts/mhg_model/models/mhgvae.py

@@ -0,0 +1,956 @@
+# -*- coding:utf-8 -*-
+# Rhizome
+# Version beta 0.0, August 2023
+# Property of IBM Research, Accelerated Discovery
+#
+
+"""
+PLEASE NOTE THIS IMPLEMENTATION INCLUDES ADAPTED SOURCE CODE
+OF THE MHG IMPLEMENTATION OF HIROSHI KAJINO AT IBM TRL ALREADY PUBLICLY AVAILABLE, 
+E.G., GRUEncoder/GRUDecoder, GrammarSeq2SeqVAE AND EVEN SOME METHODS OF GrammarGINVAE.
+THIS MIGHT INFLUENCE THE DECISION OF THE FINAL LICENSE SO CAREFUL CHECK NEEDS BE DONE. 
+"""
+
+import numpy as np
+import logging
+
+import torch
+from torch.autograd import Variable
+import torch.nn as nn
+import torch.nn.functional as F
+from torch.nn.modules.loss import _Loss
+
+from torch_geometric.nn import MessagePassing
+from torch_geometric.nn import global_add_pool
+
+
+from ..graph_grammar.graph_grammar.symbols import NTSymbol
+from ..graph_grammar.nn.encoder import EncoderBase
+from ..graph_grammar.nn.decoder import DecoderBase
+
+def get_atom_edge_feature_dims():
+    from torch_geometric.utils.smiles import x_map, e_map
+    func = lambda x: len(x[1])
+    return list(map(func, x_map.items())), list(map(func, e_map.items()))
+
+
+class FeatureEmbedding(nn.Module):
+    def __init__(self, input_dims, embedded_dim):
+        super().__init__()
+        self.embedding_list = nn.ModuleList()
+        for dim in input_dims:
+            embedding = nn.Embedding(dim, embedded_dim)
+            self.embedding_list.append(embedding)
+    
+    def forward(self, x):
+        output = 0
+        for i in range(x.shape[1]):
+            input = x[:, i].to(torch.int)
+            device = next(self.parameters()).device
+            if device != input.device:
+                input = input.to(device)
+            emb = self.embedding_list[i](input)
+            output += emb
+        return output
+    
+
+class GRUEncoder(EncoderBase):
+
+    def __init__(self, input_dim: int, hidden_dim: int, num_layers: int,
+                 bidirectional: bool, dropout: float, batch_size: int, rank: int=-1,
+                 no_dropout: bool=False):
+        super().__init__()
+        self.input_dim = input_dim
+        self.hidden_dim = hidden_dim
+        self.num_layers = num_layers
+        self.bidirectional = bidirectional
+        self.dropout = dropout
+        self.batch_size = batch_size
+        self.rank = rank
+        self.model = nn.GRU(input_size=self.input_dim,
+                            hidden_size=self.hidden_dim,
+                            num_layers=self.num_layers,
+                            batch_first=True,
+                            bidirectional=self.bidirectional,
+                            dropout=self.dropout if not no_dropout else 0)
+        if self.rank >= 0:
+            if torch.cuda.is_available():
+                self.model = self.model.to(rank)
+            else:
+                # support mac mps
+                self.model = self.model.to(torch.device("mps", rank))
+        self.init_hidden(self.batch_size)
+        
+    def init_hidden(self, bsize):
+        self.h0 = torch.zeros(((self.bidirectional + 1) * self.num_layers,
+                               min(self.batch_size, bsize),
+                               self.hidden_dim),
+                              requires_grad=False)
+        if self.rank >= 0:        
+            if torch.cuda.is_available():
+                self.h0 = self.h0.to(self.rank)
+            else:
+                # support mac mps
+                self.h0 = self.h0.to(torch.device("mps", self.rank))
+
+    def to(self, device):
+        newself = super().to(device)
+        newself.model = newself.model.to(device)
+        newself.h0 = newself.h0.to(device)
+        newself.rank = next(newself.parameters()).get_device()
+        return newself
+
+    def forward(self, in_seq_emb):
+        ''' forward model
+
+        Parameters
+        ----------
+        in_seq_emb : Tensor, shape (batch_size, max_len, input_dim)
+
+        Returns
+        -------
+        hidden_seq_emb : Tensor, shape (batch_size, max_len, 1 + bidirectional, hidden_dim)
+        '''
+        # Kishi: I think original MHG had this init_hidden()
+        self.init_hidden(in_seq_emb.size(0))
+        max_len = in_seq_emb.size(1)
+        hidden_seq_emb, self.h0 = self.model(
+            in_seq_emb, self.h0)
+        # As shown as returns, convert hidden_seq_emb: (batch_size, seq_len, (1 or 2) * hidden_size) -->
+        # (batch_size, seq_len, 1 or 2, hidden_size)
+        # In the original input the original GRU/LSTM with bidirectional encoding 
+        # has contactinated tensors 
+        # (first half for forward RNN, latter half for backward RNN)
+        # so convert them in a more friendly format packed for each RNN
+        hidden_seq_emb = hidden_seq_emb.view(-1,
+                                             max_len,
+                                             1 + self.bidirectional,
+                                             self.hidden_dim)
+        return hidden_seq_emb
+
+
+class GRUDecoder(DecoderBase):
+
+    def __init__(self, input_dim: int, hidden_dim: int, num_layers: int,
+                 dropout: float, batch_size: int, rank: int=-1,
+                 no_dropout: bool=False):
+        super().__init__()
+        self.input_dim = input_dim
+        self.hidden_dim = hidden_dim
+        self.num_layers = num_layers
+        self.dropout = dropout
+        self.batch_size = batch_size
+        self.rank = rank
+        self.model = nn.GRU(input_size=self.input_dim,
+                            hidden_size=self.hidden_dim,
+                            num_layers=self.num_layers,
+                            batch_first=True,
+                            bidirectional=False,
+                            dropout=self.dropout if not no_dropout else 0
+        )
+        if self.rank >= 0:
+            if torch.cuda.is_available():
+                self.model = self.model.to(self.rank)
+            else:
+                # support mac mps
+                self.model = self.model.to(torch.device("mps", self.rank))
+        self.init_hidden(self.batch_size)
+
+    def init_hidden(self, bsize):
+        self.hidden_dict['h'] = torch.zeros((self.num_layers,
+                                             min(self.batch_size, bsize),
+                                             self.hidden_dim),
+                                            requires_grad=False)
+        if self.rank >= 0:
+            if torch.cuda.is_available():
+                self.hidden_dict['h'] = self.hidden_dict['h'].to(self.rank)
+            else:
+                self.hidden_dict['h'] = self.hidden_dict['h'].to(torch.device("mps", self.rank))
+
+    def to(self, device):
+        newself = super().to(device)
+        newself.model = newself.model.to(device)
+        for k in self.hidden_dict.keys():
+            newself.hidden_dict[k] = newself.hidden_dict[k].to(device)
+        newself.rank = next(newself.parameters()).get_device()
+        return newself
+
+    def forward_one_step(self, tgt_emb_in):
+        ''' one-step forward model
+
+        Parameters
+        ----------
+        tgt_emb_in : Tensor, shape (batch_size, input_dim)
+
+        Returns
+        -------
+        Tensor, shape (batch_size, hidden_dim)
+        '''
+        bsize = tgt_emb_in.size(0)
+        tgt_emb_out, self.hidden_dict['h'] \
+            = self.model(tgt_emb_in.view(bsize, 1, -1),
+                         self.hidden_dict['h'])
+        return tgt_emb_out
+
+
+class NodeMLP(nn.Module):
+    def __init__(self, input_size, output_size, hidden_size):
+        super().__init__()
+        self.lin1 = nn.Linear(input_size, hidden_size)
+        self.nbat = nn.BatchNorm1d(hidden_size)
+        self.lin2 = nn.Linear(hidden_size, output_size)
+        
+    def forward(self, x):
+        x = self.lin1(x)
+        x = self.nbat(x)
+        x = x.relu()
+        x = self.lin2(x)
+        return x
+    
+    
+class GINLayer(MessagePassing):
+    def __init__(self, node_input_size, node_output_size, node_hidden_size, edge_input_size):
+        super().__init__()
+        self.node_mlp = NodeMLP(node_input_size, node_output_size, node_hidden_size)
+        self.edge_mlp = FeatureEmbedding(edge_input_size, node_output_size)
+        self.eps = nn.Parameter(torch.tensor([0.0]))
+        
+    def forward(self, x, edge_index, edge_attr):
+        msg = self.propagate(edge_index, x=x ,edge_attr=edge_attr)
+        x = (1.0 + self.eps) * x + msg
+        x = x.relu()
+        x = self.node_mlp(x)
+        return x
+    
+    def message(self, x_j, edge_attr):
+        edge_attr = self.edge_mlp(edge_attr)
+        x_j = x_j + edge_attr
+        x_j = x_j.relu()
+        return x_j
+    
+    def update(self, aggr_out):
+        return aggr_out
+
+#TODO implement the case where features of atoms and edges are considered
+# Check GraphMVP and ogb (open graph benchmark) to realize this
+class GIN(torch.nn.Module):
+    def __init__(self, node_feature_size, edge_feature_size, hidden_channels=64, 
+                 proximity_size=3, dropout=0.1):
+        super().__init__()
+        #print("(num node features, num edge features)=", (node_feature_size, edge_feature_size))
+        hsize = hidden_channels * 2
+        atom_dim, edge_dim = get_atom_edge_feature_dims()
+        self.trans = FeatureEmbedding(atom_dim, hidden_channels)
+        ml = []
+        for _ in range(proximity_size):
+            ml.append(GINLayer(hidden_channels, hidden_channels, hsize, edge_dim))
+        self.mlist = nn.ModuleList(ml)
+        #It is possible to calculate relu with x.relu() where x is an output
+        #self.activations = nn.ModuleList(actl)
+        self.dropout = dropout
+        self.proximity_size = proximity_size
+        
+    def forward(self, x, edge_index, edge_attr, batch_size):
+        x = x.to(torch.float)
+        #print("before: edge_weight.shape=", edge_attr.shape)
+        edge_attr = edge_attr.to(torch.float)
+        #print("after: edge_weight.shape=", edge_attr.shape)
+        x = self.trans(x)
+        # TODO Check if this x is consistent with global_add_pool
+        hlist = [global_add_pool(x, batch_size)]
+        for id, m in enumerate(self.mlist):
+            x = m(x, edge_index=edge_index, edge_attr=edge_attr)
+            #print("Done with one layer") 
+            ###if id != self.proximity_size - 1:
+            x = x.relu()
+            x = F.dropout(x, p=self.dropout, training=self.training)
+            #h = global_mean_pool(x, batch_size)
+            h = global_add_pool(x, batch_size)
+            hlist.append(h)
+            #print("Done with one relu call: x.shape=", x.shape)
+        #print("calling golbal mean pool")
+        #print("calling dropout x.shape=", x.shape)
+        #print("x=", x)
+        #print("hlist[0].shape=", hlist[0].shape)
+        x = torch.cat(hlist, dim=1)
+        #print("x.shape=", x.shape)
+        x = F.dropout(x, p=self.dropout, training=self.training)
+
+        return x
+
+
+# TODO copied from MHG implementation and adapted here. 
+class GrammarSeq2SeqVAE(nn.Module):
+
+    '''
+    Variational seq2seq with grammar.
+    TODO: rewrite this class using mixin
+    '''
+
+    def __init__(self, hrg, rank=-1, latent_dim=64, max_len=80,
+                 batch_size=64, padding_idx=-1, 
+                 encoder_params={'hidden_dim': 384, 'num_layers': 3, 'bidirectional': True,
+                                 'dropout': 0.1},
+                 decoder_params={'hidden_dim': 384, #'num_layers': 2,
+                                 'num_layers': 3,
+                                 'dropout': 0.1},
+                 prod_rule_embed_params={'out_dim': 128},
+                 no_dropout=False):
+
+        super().__init__()
+        # TODO USE GRU FOR ENCODING AND DECODING
+        self.hrg = hrg
+        self.rank = rank
+        self.prod_rule_corpus = hrg.prod_rule_corpus
+        self.prod_rule_embed_params = prod_rule_embed_params
+
+        self.vocab_size = hrg.num_prod_rule + 1
+        self.batch_size = batch_size
+        self.padding_idx = np.mod(padding_idx, self.vocab_size)
+        self.no_dropout = no_dropout
+
+        self.latent_dim = latent_dim
+        self.max_len = max_len
+        self.encoder_params = encoder_params
+        self.decoder_params = decoder_params
+        
+        # TODO Simple embedding is used. Check if a domain-dependent embedding works or not. 
+        embed_out_dim = self.prod_rule_embed_params['out_dim']        
+        #use MolecularProdRuleEmbedding later on
+        self.src_embedding = nn.Embedding(self.vocab_size, embed_out_dim,
+                                          padding_idx=self.padding_idx)
+        self.tgt_embedding = nn.Embedding(self.vocab_size, embed_out_dim,
+                                          padding_idx=self.padding_idx)
+
+        # USE a GRU-based encoder in MHG
+        self.encoder = GRUEncoder(input_dim=embed_out_dim, batch_size=self.batch_size,
+                                      rank=self.rank, no_dropout=self.no_dropout,
+                                  **self.encoder_params)
+
+        lin_dim = (self.encoder_params.get('bidirectional', False) + 1) * self.encoder_params['hidden_dim']
+        lin_out_dim = self.latent_dim
+        self.hidden2mean = nn.Linear(lin_dim, lin_out_dim, bias=False)
+        self.hidden2logvar = nn.Linear(lin_dim, lin_out_dim)
+   
+        # USE a GRU-based decoder in MHG
+        self.decoder = GRUDecoder(input_dim=embed_out_dim, batch_size=self.batch_size,
+                                  rank=self.rank, no_dropout=self.no_dropout, **self.decoder_params)
+        self.latent2tgt_emb = nn.Linear(self.latent_dim, embed_out_dim)
+        self.latent2hidden_dict = nn.ModuleDict()
+        dec_lin_out_dim = self.decoder_params['hidden_dim']
+        for each_hidden in self.decoder.hidden_dict.keys():
+            self.latent2hidden_dict[each_hidden] = nn.Linear(self.latent_dim, dec_lin_out_dim)
+            if self.rank >= 0:
+                if torch.cuda.is_available():
+                    self.latent2hidden_dict[each_hidden] = self.latent2hidden_dict[each_hidden].to(self.rank)
+                else:
+                    # support mac mps
+                    self.latent2hidden_dict[each_hidden] = self.latent2hidden_dict[each_hidden].to(torch.device("mps", self.rank))
+
+        self.dec2vocab = nn.Linear(dec_lin_out_dim, self.vocab_size)
+        self.encoder.init_hidden(self.batch_size)
+        self.decoder.init_hidden(self.batch_size)
+
+        # TODO Do we need this?
+        if hasattr(self.src_embedding, 'weight'):
+            self.src_embedding.weight.data.uniform_(-0.1, 0.1)
+        if hasattr(self.tgt_embedding, 'weight'):
+            self.tgt_embedding.weight.data.uniform_(-0.1, 0.1)
+            
+        self.encoder.init_hidden(self.batch_size)
+        self.decoder.init_hidden(self.batch_size)
+    
+    def to(self, device):
+        newself = super().to(device)
+        newself.src_embedding = newself.src_embedding.to(device)
+        newself.tgt_embedding = newself.tgt_embedding.to(device)
+        newself.encoder = newself.encoder.to(device)
+        newself.decoder = newself.decoder.to(device)
+        newself.dec2vocab = newself.dec2vocab.to(device)
+        newself.hidden2mean = newself.hidden2mean.to(device)
+        newself.hidden2logvar = newself.hidden2logvar.to(device)
+        newself.latent2tgt_emb = newself.latent2tgt_emb.to(device)
+        newself.latent2hidden_dict = newself.latent2hidden_dict.to(device)
+        return newself
+    
+    def forward(self, in_seq, out_seq):
+        ''' forward model
+
+        Parameters
+        ----------
+        in_seq : Variable, shape (batch_size, length)
+            each element corresponds to word index.
+            where the index should be less than `vocab_size`
+
+        Returns
+        -------
+        Variable, shape (batch_size, length, vocab_size)
+            logit of each word (applying softmax yields the probability)
+        '''
+        mu, logvar = self.encode(in_seq)
+        z = self.reparameterize(mu, logvar)
+        return self.decode(z, out_seq), mu, logvar
+
+    def encode(self, in_seq):
+        src_emb = self.src_embedding(in_seq)
+        src_h = self.encoder.forward(src_emb)
+        if self.encoder_params.get('bidirectional', False):
+            concat_src_h = torch.cat((src_h[:, -1, 0, :], src_h[:, 0, 1, :]), dim=1)
+            return self.hidden2mean(concat_src_h), self.hidden2logvar(concat_src_h)
+        else:
+            return self.hidden2mean(src_h[:, -1, :]), self.hidden2logvar(src_h[:, -1, :])
+
+    def reparameterize(self, mu, logvar, training=True):
+        if training:
+            std = logvar.mul(0.5).exp_()
+            device = next(self.parameters()).device
+            eps = Variable(std.data.new(std.size()).normal_())
+            if device != eps.get_device():
+                eps.to(device)
+            return eps.mul(std).add_(mu)
+        else:
+            return mu
+
+    #TODO Not tested. Need to implement this in case of molecular structure generation
+    def sample(self, sample_size=-1, deterministic=True, return_z=False):
+        self.eval()
+        self.init_hidden()
+        if sample_size == -1:
+            sample_size = self.batch_size
+
+        num_iter = int(np.ceil(sample_size / self.batch_size))
+        hg_list = []
+        z_list = []
+        for _ in range(num_iter):
+            z = Variable(torch.normal(
+                torch.zeros(self.batch_size, self.latent_dim),
+                torch.ones(self.batch_size * self.latent_dim))).cuda()
+            _, each_hg_list = self.decode(z, deterministic=deterministic)
+            z_list.append(z)
+            hg_list += each_hg_list
+        z = torch.cat(z_list)[:sample_size]
+        hg_list = hg_list[:sample_size]
+        if return_z:
+            return hg_list, z.cpu().detach().numpy()
+        else:
+            return hg_list
+
+    def decode(self, z=None, out_seq=None, deterministic=True):
+        if z is None:
+            z = Variable(torch.normal(
+                torch.zeros(self.batch_size, self.latent_dim),
+                torch.ones(self.batch_size * self.latent_dim)))
+        if self.rank >= 0:
+            z = z.to(next(self.parameters()).device)
+
+        hidden_dict_0 = {}
+        for each_hidden in self.latent2hidden_dict.keys():
+            hidden_dict_0[each_hidden] = self.latent2hidden_dict[each_hidden](z)
+        bsize = z.size(0)
+        self.decoder.init_hidden(bsize) 
+        self.decoder.feed_hidden(hidden_dict_0)
+
+        if out_seq is not None:
+            tgt_emb0 = self.latent2tgt_emb(z)
+            tgt_emb0 = tgt_emb0.view(tgt_emb0.shape[0], 1, tgt_emb0.shape[1])
+            out_seq_emb = self.tgt_embedding(out_seq)
+            tgt_emb = torch.cat((tgt_emb0, out_seq_emb), dim=1)[:, :-1, :]
+            tgt_emb_pred_list = []
+            for each_idx in range(self.max_len):
+                tgt_emb_pred = self.decoder.forward_one_step(tgt_emb[:, each_idx, :].view(bsize, 1, -1))
+                tgt_emb_pred_list.append(tgt_emb_pred)
+            vocab_logit = self.dec2vocab(torch.cat(tgt_emb_pred_list, dim=1))
+            return vocab_logit
+        else:
+            with torch.no_grad():
+                tgt_emb = self.latent2tgt_emb(z)
+                tgt_emb = tgt_emb.view(tgt_emb.shape[0], 1, tgt_emb.shape[1])
+                tgt_emb_pred_list = []
+                stack_list = []
+                hg_list = []
+                nt_symbol_list = []
+                nt_edge_list = []
+                gen_finish_list = []
+                for _ in range(bsize):
+                    stack_list.append([])
+                    hg_list.append(None)
+                    nt_symbol_list.append(NTSymbol(degree=0,
+                                                   is_aromatic=False,
+                                                   bond_symbol_list=[]))
+                    nt_edge_list.append(None)
+                    gen_finish_list.append(False)
+
+                for idx in range(self.max_len):
+                    tgt_emb_pred = self.decoder.forward_one_step(tgt_emb)
+                    tgt_emb_pred_list.append(tgt_emb_pred)
+                    vocab_logit = self.dec2vocab(tgt_emb_pred)
+                    for each_batch_idx in range(bsize):
+                        if not gen_finish_list[each_batch_idx]: # if generation has not finished
+                            # get production rule greedily
+                            prod_rule = self.hrg.prod_rule_corpus.sample(vocab_logit[each_batch_idx, :, :-1].squeeze().cpu().numpy(),
+                                                                         nt_symbol_list[each_batch_idx],
+                                                                         deterministic=deterministic)
+                            # convert production rule into an index
+                            tgt_id = self.hrg.prod_rule_list.index(prod_rule)
+                            # apply the production rule
+                            hg_list[each_batch_idx], nt_edges = prod_rule.applied_to(hg_list[each_batch_idx], nt_edge_list[each_batch_idx])
+                            # add non-terminals to the stack
+                            stack_list[each_batch_idx].extend(nt_edges[::-1])
+                            # if the stack size is 0, generation has finished!
+                            if len(stack_list[each_batch_idx]) == 0:
+                                gen_finish_list[each_batch_idx] = True
+                            else:
+                                nt_edge_list[each_batch_idx] = stack_list[each_batch_idx].pop()
+                                nt_symbol_list[each_batch_idx] = hg_list[each_batch_idx].edge_attr(nt_edge_list[each_batch_idx])['symbol']
+                        else:
+                            tgt_id = np.mod(self.padding_idx, self.vocab_size)
+                        indice_tensor = torch.LongTensor([tgt_id])
+                        device = next(self.parameters()).device
+                        if indice_tensor.device != device: 
+                            indice_tensor = indice_tensor.to(device)
+                        tgt_emb[each_batch_idx, :] = self.tgt_embedding(indice_tensor)
+                vocab_logit = self.dec2vocab(torch.cat(tgt_emb_pred_list, dim=1))
+                #for id, v in enumerate(gen_finish_list):
+                #if not v:
+                #    print("bacth id={} not finished generating a sequence: ".format(id))
+                return gen_finish_list, vocab_logit, hg_list
+
+
+# TODO A lot of duplicates with GrammarVAE. Clean up it if necessary
+class GrammarGINVAE(nn.Module):
+
+    '''
+    Variational autoencoder based on GIN and grammar
+    '''
+
+    def __init__(self, hrg, rank=-1, max_len=80,
+                 batch_size=64, padding_idx=-1, 
+                 encoder_params={'node_feature_size': 4, 'edge_feature_size': 3, 
+                                 'hidden_channels': 64, 'proximity_size': 3,
+                                 'dropout': 0.1},
+                 decoder_params={'hidden_dim': 384, 'num_layers': 3,
+                                 'dropout': 0.1},
+                 prod_rule_embed_params={'out_dim': 128},
+                 no_dropout=False):
+
+        super().__init__()
+        # TODO USE GRU FOR ENCODING AND DECODING
+        self.hrg = hrg
+        self.rank = rank
+        self.prod_rule_corpus = hrg.prod_rule_corpus
+        self.prod_rule_embed_params = prod_rule_embed_params
+
+        self.vocab_size = hrg.num_prod_rule + 1
+        self.batch_size = batch_size
+        self.padding_idx = np.mod(padding_idx, self.vocab_size)
+        self.no_dropout = no_dropout
+        self.max_len = max_len
+        self.encoder_params = encoder_params
+        self.decoder_params = decoder_params
+        
+        # TODO Simple embedding is used. Check if a domain-dependent embedding works or not. 
+        embed_out_dim = self.prod_rule_embed_params['out_dim']        
+        #use MolecularProdRuleEmbedding later on
+        self.tgt_embedding = nn.Embedding(self.vocab_size, embed_out_dim,
+                                          padding_idx=self.padding_idx)
+
+        self.encoder = GIN(**self.encoder_params)
+        self.latent_dim = self.encoder_params['hidden_channels']
+        self.proximity_size = self.encoder_params['proximity_size']
+        hidden_dim = self.decoder_params['hidden_dim']
+        self.hidden2mean = nn.Linear(self.latent_dim * (1 + self.proximity_size), self.latent_dim, bias=False)
+        self.hidden2logvar = nn.Linear(self.latent_dim * (1 + self.proximity_size), self.latent_dim)
+   
+        self.decoder = GRUDecoder(input_dim=embed_out_dim, batch_size=self.batch_size,
+                                  rank=self.rank, no_dropout=self.no_dropout, **self.decoder_params)
+        self.latent2tgt_emb = nn.Linear(self.latent_dim, embed_out_dim)
+        self.latent2hidden_dict = nn.ModuleDict()
+        for each_hidden in self.decoder.hidden_dict.keys():
+            self.latent2hidden_dict[each_hidden] = nn.Linear(self.latent_dim, hidden_dim)
+            if self.rank >= 0:
+                if torch.cuda.is_available():
+                    self.latent2hidden_dict[each_hidden] = self.latent2hidden_dict[each_hidden].to(self.rank)
+                else:
+                    # support mac mps
+                    self.latent2hidden_dict[each_hidden] = self.latent2hidden_dict[each_hidden].to(torch.device("mps", self.rank))
+
+        self.dec2vocab = nn.Linear(hidden_dim, self.vocab_size)
+        self.decoder.init_hidden(self.batch_size)
+
+        # TODO Do we need this?
+        if hasattr(self.tgt_embedding, 'weight'):
+            self.tgt_embedding.weight.data.uniform_(-0.1, 0.1)
+        self.decoder.init_hidden(self.batch_size)
+    
+    def to(self, device):
+        newself = super().to(device)
+        newself.encoder = newself.encoder.to(device)
+        newself.decoder = newself.decoder.to(device)
+        newself.rank = next(newself.encoder.parameters()).get_device()
+        return newself
+    
+    def forward(self, x, edge_index, edge_attr, batch_size, out_seq=None, sched_prob = None):
+        mu, logvar = self.encode(x, edge_index, edge_attr, batch_size)
+        z = self.reparameterize(mu, logvar)
+        return self.decode(z, out_seq, sched_prob=sched_prob), mu, logvar
+
+    #TODO Not tested. Need to implement this in case of molecular structure generation
+    def sample(self, sample_size=-1, deterministic=True, return_z=False):
+        self.eval()
+        self.init_hidden()
+        if sample_size == -1:
+            sample_size = self.batch_size
+
+        num_iter = int(np.ceil(sample_size / self.batch_size))
+        hg_list = []
+        z_list = []
+        for _ in range(num_iter):
+            z = Variable(torch.normal(
+                torch.zeros(self.batch_size, self.latent_dim),
+                torch.ones(self.batch_size * self.latent_dim))).cuda()
+            _, each_hg_list = self.decode(z, deterministic=deterministic)
+            z_list.append(z)
+            hg_list += each_hg_list
+        z = torch.cat(z_list)[:sample_size]
+        hg_list = hg_list[:sample_size]
+        if return_z:
+            return hg_list, z.cpu().detach().numpy()
+        else:
+            return hg_list
+
+    def decode(self, z=None, out_seq=None, deterministic=True, sched_prob=None):
+        if z is None:
+            z = Variable(torch.normal(
+                torch.zeros(self.batch_size, self.latent_dim),
+                torch.ones(self.batch_size * self.latent_dim)))
+        if self.rank >= 0:
+            z = z.to(next(self.parameters()).device)
+
+        hidden_dict_0 = {}
+        for each_hidden in self.latent2hidden_dict.keys():
+            hidden_dict_0[each_hidden] = self.latent2hidden_dict[each_hidden](z)
+        bsize = z.size(0)
+        self.decoder.init_hidden(bsize) 
+        self.decoder.feed_hidden(hidden_dict_0)
+
+        if out_seq is not None:
+            tgt_emb0 = self.latent2tgt_emb(z)
+            tgt_emb0 = tgt_emb0.view(tgt_emb0.shape[0], 1, tgt_emb0.shape[1])
+            out_seq_emb = self.tgt_embedding(out_seq)
+            tgt_emb = torch.cat((tgt_emb0, out_seq_emb), dim=1)[:, :-1, :]
+            tgt_emb_pred_list = []
+            tgt_emb_pred = None
+            for each_idx in range(self.max_len):
+                if tgt_emb_pred is None or sched_prob is None or torch.rand(1)[0] <= sched_prob:
+                    inp = tgt_emb[:, each_idx, :].view(bsize, 1, -1)
+                else:
+                    cur_logit = self.dec2vocab(tgt_emb_pred)
+                    yi = torch.argmax(cur_logit, dim=2)
+                    inp = self.tgt_embedding(yi)
+                tgt_emb_pred = self.decoder.forward_one_step(inp)
+                tgt_emb_pred_list.append(tgt_emb_pred)
+            vocab_logit = self.dec2vocab(torch.cat(tgt_emb_pred_list, dim=1))
+            return vocab_logit
+        else:
+            with torch.no_grad():
+                tgt_emb = self.latent2tgt_emb(z)
+                tgt_emb = tgt_emb.view(tgt_emb.shape[0], 1, tgt_emb.shape[1])
+                tgt_emb_pred_list = []
+                stack_list = []
+                hg_list = []
+                nt_symbol_list = []
+                nt_edge_list = []
+                gen_finish_list = []
+                for _ in range(bsize):
+                    stack_list.append([])
+                    hg_list.append(None)
+                    nt_symbol_list.append(NTSymbol(degree=0,
+                                                   is_aromatic=False,
+                                                   bond_symbol_list=[]))
+                    nt_edge_list.append(None)
+                    gen_finish_list.append(False)
+
+                for _ in range(self.max_len):
+                    tgt_emb_pred = self.decoder.forward_one_step(tgt_emb)
+                    tgt_emb_pred_list.append(tgt_emb_pred)
+                    vocab_logit = self.dec2vocab(tgt_emb_pred)
+                    for each_batch_idx in range(bsize):
+                        if not gen_finish_list[each_batch_idx]: # if generation has not finished
+                            # get production rule greedily
+                            prod_rule = self.hrg.prod_rule_corpus.sample(vocab_logit[each_batch_idx, :, :-1].squeeze().cpu().numpy(),
+                                                                         nt_symbol_list[each_batch_idx],
+                                                                         deterministic=deterministic)
+                            # convert production rule into an index
+                            tgt_id = self.hrg.prod_rule_list.index(prod_rule)
+                            # apply the production rule
+                            hg_list[each_batch_idx], nt_edges = prod_rule.applied_to(hg_list[each_batch_idx], nt_edge_list[each_batch_idx])
+                            # add non-terminals to the stack
+                            stack_list[each_batch_idx].extend(nt_edges[::-1])
+                            # if the stack size is 0, generation has finished!
+                            if len(stack_list[each_batch_idx]) == 0:
+                                gen_finish_list[each_batch_idx] = True
+                            else:
+                                nt_edge_list[each_batch_idx] = stack_list[each_batch_idx].pop()
+                                nt_symbol_list[each_batch_idx] = hg_list[each_batch_idx].edge_attr(nt_edge_list[each_batch_idx])['symbol']
+                        else:
+                            tgt_id = np.mod(self.padding_idx, self.vocab_size)
+                        indice_tensor = torch.LongTensor([tgt_id])
+                        if self.rank >= 0:
+                            indice_tensor = indice_tensor.to(next(self.parameters()).device)
+                        tgt_emb[each_batch_idx, :] = self.tgt_embedding(indice_tensor)
+                vocab_logit = self.dec2vocab(torch.cat(tgt_emb_pred_list, dim=1))
+                return gen_finish_list, vocab_logit, hg_list
+
+    #TODO Not tested. Need to implement this in case of molecular structure generation
+    def conditional_distribution(self, z, tgt_id_list):
+        self.eval()
+        self.init_hidden()
+        z = z.cuda()
+
+        hidden_dict_0 = {}
+        for each_hidden in self.latent2hidden_dict.keys():
+            hidden_dict_0[each_hidden] = self.latent2hidden_dict[each_hidden](z)
+        self.decoder.feed_hidden(hidden_dict_0)
+
+        with torch.no_grad():
+            tgt_emb = self.latent2tgt_emb(z)
+            tgt_emb = tgt_emb.view(tgt_emb.shape[0], 1, tgt_emb.shape[1])
+            nt_symbol_list = []
+            stack_list = []
+            hg_list = []
+            nt_edge_list = []
+            gen_finish_list = []
+            for _ in range(self.batch_size):
+                nt_symbol_list.append(NTSymbol(degree=0,
+                                               is_aromatic=False,
+                                               bond_symbol_list=[]))
+                stack_list.append([])
+                hg_list.append(None)
+                nt_edge_list.append(None)
+                gen_finish_list.append(False)
+
+            for each_position in range(len(tgt_id_list[0])):
+                tgt_emb_pred = self.decoder.forward_one_step(tgt_emb)
+                for each_batch_idx in range(self.batch_size):
+                    if not gen_finish_list[each_batch_idx]: # if generation has not finished
+                        # use the prespecified target ids
+                        tgt_id = tgt_id_list[each_batch_idx][each_position]
+                        prod_rule = self.hrg.prod_rule_list[tgt_id]
+                        # apply the production rule
+                        hg_list[each_batch_idx], nt_edges = prod_rule.applied_to(hg_list[each_batch_idx], nt_edge_list[each_batch_idx])
+                        # add non-terminals to the stack
+                        stack_list[each_batch_idx].extend(nt_edges[::-1])
+                        # if the stack size is 0, generation has finished!
+                        if len(stack_list[each_batch_idx]) == 0:
+                            gen_finish_list[each_batch_idx] = True
+                        else:
+                            nt_edge_list[each_batch_idx] = stack_list[each_batch_idx].pop()
+                            nt_symbol_list[each_batch_idx] = hg_list[each_batch_idx].edge_attr(nt_edge_list[each_batch_idx])['symbol']
+                    else:
+                        tgt_id = np.mod(self.padding_idx, self.vocab_size)
+                    indice_tensor = torch.LongTensor([tgt_id])
+                    indice_tensor = indice_tensor.cuda()
+                    tgt_emb[each_batch_idx, :] = self.tgt_embedding(indice_tensor)
+
+            # last one step
+            conditional_logprob_list = []
+            tgt_emb_pred = self.decoder.forward_one_step(tgt_emb)
+            vocab_logit = self.dec2vocab(tgt_emb_pred)
+            for each_batch_idx in range(self.batch_size):
+                if not gen_finish_list[each_batch_idx]: # if generation has not finished
+                    # get production rule greedily
+                    masked_logprob = self.hrg.prod_rule_corpus.masked_logprob(
+                        vocab_logit[each_batch_idx, :, :-1].squeeze().cpu().numpy(),
+                        nt_symbol_list[each_batch_idx])
+                    conditional_logprob_list.append(masked_logprob)
+                else:
+                    conditional_logprob_list.append(None)
+        return conditional_logprob_list
+
+    #TODO Not tested. Need to implement this in case of molecular structure generation
+    def decode_with_beam_search(self, z, beam_width=1):
+        ''' Decode a latent vector using beam search.
+
+        Parameters
+        ----------
+        z
+            latent vector
+        beam_width : int
+            parameter for beam search
+
+        Returns
+        -------
+        List of Hypergraphs
+        '''
+        if self.batch_size != 1:
+            raise ValueError('this method works only under batch_size=1')
+        if self.padding_idx != -1:
+            raise ValueError('this method works only under padding_idx=-1')
+        top_k_tgt_id_list = [[]] * beam_width
+        logprob_list = [0.] * beam_width
+
+        for each_len in range(self.max_len):
+            expanded_logprob_list = np.repeat(logprob_list, self.vocab_size) # including padding_idx
+            expanded_length_list = np.array([0] * (beam_width * self.vocab_size))
+            for each_beam_idx, each_candidate in enumerate(top_k_tgt_id_list):
+                conditional_logprob = self.conditional_distribution(z, [each_candidate])[0]
+                if conditional_logprob is None:
+                    expanded_logprob_list[(each_beam_idx + 1) * self.vocab_size - 1]\
+                        = logprob_list[each_beam_idx]
+                    expanded_logprob_list[each_beam_idx * self.vocab_size : (each_beam_idx + 1) * self.vocab_size - 1]\
+                        = -np.inf
+                    expanded_length_list[each_beam_idx * self.vocab_size : (each_beam_idx + 1) * self.vocab_size]\
+                        = len(each_candidate)
+                else:
+                    expanded_logprob_list[each_beam_idx * self.vocab_size : (each_beam_idx + 1) * self.vocab_size - 1]\
+                        = logprob_list[each_beam_idx] + conditional_logprob
+                    expanded_logprob_list[(each_beam_idx + 1) * self.vocab_size - 1]\
+                        = -np.inf
+                    expanded_length_list[each_beam_idx * self.vocab_size : (each_beam_idx + 1) * self.vocab_size]\
+                        = len(each_candidate) + 1
+            score_list = np.array(expanded_logprob_list) / np.array(expanded_length_list)
+            if each_len == 0:
+                top_k_list = np.argsort(score_list[:self.vocab_size])[::-1][:beam_width]
+            else:
+                top_k_list = np.argsort(score_list)[::-1][:beam_width]
+            next_top_k_tgt_id_list = []
+            next_logprob_list = []
+            for each_top_k in top_k_list:
+                beam_idx = each_top_k // self.vocab_size
+                vocab_idx = each_top_k % self.vocab_size
+                if vocab_idx == self.vocab_size - 1:
+                    next_top_k_tgt_id_list.append(top_k_tgt_id_list[beam_idx])
+                    next_logprob_list.append(expanded_logprob_list[each_top_k])
+                else:
+                    next_top_k_tgt_id_list.append(top_k_tgt_id_list[beam_idx] + [vocab_idx])
+                    next_logprob_list.append(expanded_logprob_list[each_top_k])
+            top_k_tgt_id_list = next_top_k_tgt_id_list
+            logprob_list = next_logprob_list
+
+        # construct hypergraphs
+        hg_list = []
+        for each_tgt_id_list in top_k_tgt_id_list:
+            hg = None
+            stack = []
+            nt_edge = None
+            for each_idx, each_prod_rule_id in enumerate(each_tgt_id_list):
+                prod_rule = self.hrg.prod_rule_list[each_prod_rule_id]
+                hg, nt_edges = prod_rule.applied_to(hg, nt_edge)
+                stack.extend(nt_edges[::-1])
+                try:
+                    nt_edge = stack.pop()
+                except IndexError:
+                    if each_idx == len(each_tgt_id_list) - 1:
+                        break
+                    else:
+                        raise ValueError('some bugs')
+            hg_list.append(hg)
+        return hg_list
+
+    def graph_embed(self, x, edge_index, edge_attr, batch_size):
+        src_h = self.encoder.forward(x, edge_index, edge_attr, batch_size)
+        return src_h        
+
+    def encode(self, x, edge_index, edge_attr, batch_size):
+        #print("device for src_emb=", src_emb.get_device())
+        #print("device for self.encoder=", next(self.encoder.parameters()).get_device())
+        src_h = self.graph_embed(x, edge_index, edge_attr, batch_size)
+        mu, lv = self.get_mean_var(src_h)
+        return mu, lv
+    
+    def get_mean_var(self, src_h):
+        #src_h = torch.tanh(src_h)
+        mu = self.hidden2mean(src_h)
+        lv = self.hidden2logvar(src_h)
+        mu = torch.tanh(mu)
+        lv = torch.tanh(lv)
+        return mu, lv
+
+    def reparameterize(self, mu, logvar, training=True):
+        if training:
+            std = logvar.mul(0.5).exp_()
+            eps = Variable(std.data.new(std.size()).normal_())
+            if self.rank >= 0:
+                eps = eps.to(next(self.parameters()).device)
+            return eps.mul(std).add_(mu)
+        else:
+            return mu
+
+# Copied from the MHG implementation and adapted
+class GrammarVAELoss(_Loss):
+
+    '''
+    a loss function for Grammar VAE
+
+    Attributes
+    ----------
+    hrg : HyperedgeReplacementGrammar
+    beta : float
+        coefficient of KL divergence
+    '''
+
+    def __init__(self, rank, hrg, beta=1.0, **kwargs):
+        super().__init__(**kwargs)
+        self.hrg = hrg
+        self.beta = beta
+        self.rank = rank
+
+    def forward(self, mu, logvar, in_seq_pred, in_seq):
+        ''' compute VAE loss
+
+        Parameters
+        ----------
+        in_seq_pred : torch.Tensor, shape (batch_size, max_len, vocab_size)
+            logit
+        in_seq : torch.Tensor, shape (batch_size, max_len)
+            each element corresponds to a word id in vocabulary.
+        mu : torch.Tensor, shape (batch_size, hidden_dim)
+        logvar : torch.Tensor, shape (batch_size, hidden_dim)
+            mean and log variance of the normal distribution
+        '''
+        batch_size = in_seq_pred.shape[0]
+        max_len = in_seq_pred.shape[1]
+        vocab_size = in_seq_pred.shape[2]
+        mask = torch.zeros(in_seq_pred.shape)
+        
+        for each_batch in range(batch_size):
+            flag = True
+            for each_idx in range(max_len):
+                prod_rule_idx = in_seq[each_batch, each_idx]
+                if prod_rule_idx == vocab_size - 1:
+                    #### DETERMINE WHETHER THIS SHOULD BE SKIPPED OR NOT
+                    mask[each_batch, each_idx, prod_rule_idx] = 1
+                    #break
+                    continue
+                lhs = self.hrg.prod_rule_corpus.prod_rule_list[prod_rule_idx].lhs_nt_symbol
+                lhs_idx = self.hrg.prod_rule_corpus.nt_symbol_list.index(lhs)
+                mask[each_batch, each_idx, :-1] = torch.FloatTensor(self.hrg.prod_rule_corpus.lhs_in_prod_rule[lhs_idx])
+            if self.rank >= 0:
+                mask = mask.to(next(self.parameters()).device)
+        in_seq_pred = mask * in_seq_pred
+
+        cross_entropy = F.cross_entropy(
+            in_seq_pred.view(-1, vocab_size),
+            in_seq.view(-1),
+            reduction='sum',
+            #ignore_index=self.ignore_index if self.ignore_index is not None else -100
+            )
+        kl_div = -0.5 * torch.sum(1 + logvar - mu.pow(2) - logvar.exp())
+        return cross_entropy + self.beta * kl_div
+
+
+class VAELoss(_Loss):
+    def __init__(self, beta=0.01):
+        super().__init__()
+        self.beta = beta
+
+    def forward(self, mean, log_var, dec_outputs, targets):
+
+        device = mean.get_device()
+        if device >= 0:
+            targets = targets.to(mean.get_device())
+        reconstruction = F.cross_entropy(dec_outputs.view(-1, dec_outputs.size(2)), targets.view(-1), reduction='sum')
+        
+        KL = 0.5 * torch.sum(1 + log_var - mean ** 2 - torch.exp(log_var))
+        loss = - self.beta * KL + reconstruction
+        return loss