changes for PR (a65d0290) · Commits · 钟慕尧 / deepchem

datasets/core_smiles_labels.csv

deleted100644 → 0

+0 −169

Original line number	Diff line number	Diff line
		smiles,id,-logKd/Ki
		Cn1nc(-c2ccc3c(c2)OCO3)cc1N,3ao4,2.0699999999999998
		[NH3+]CCc1ccccc1,1uto,2.27
		O=C1NC2C(O)C(O)C(O)C(CO)N2C1=O,1ps3,2.2799999999999998
		OCC1OC(OC2C(CO)OC(O)C(O)C2O)C(O)C(O)C1O,1qi0,2.3500000000000001
		O=C1C=C(Nc2nnn[nH]2)CCC1,3g2z,2.3599999999999999
		N=c1ccn(C2OC(CO)C(O)C(F)C2O)c(=O)[nH]1,3l7b,2.3999999999999999
		Nc1ncc(CCC([NH3+])C(=O)[O-])[nH]1,3mfv,2.52
		CC(C)CC([NH3+])C(=O)[O-],3b3s,2.5499999999999998
		[NH3+]Cc1ccc(C(=O)[O-])cc1,3kgp,2.5699999999999998
		CC(=O)Oc1c(C)cccc1C(=O)[O-],3fcq,2.77
		COc1ccc(S(N)(=O)=O)cc1,3lka,2.8199999999999998
		O=C1Nc2ccccc2C12CC[NH2+]C2,3udh,2.8500000000000001
		CCOC(=O)C=Cc1ccc(O)c(O)c1,4gqq,2.8900000000000001
		COc1ccc2[nH]ccc2c1,3imc,2.96
		CCN(CC)C(=O)c1ccc(O)c(OC)c1,2xdl,3.1000000000000001
		[NH3+]CCc1c[nH]c2ccc(O)cc12,2ymd,3.1600000000000001
		[NH3+]C(CCC(=O)NC(CS)C(=O)NCC(=O)[O-])C(=O)[O-],1lbk,3.1800000000000002
		Nc1ccc2cc3ccc(N)cc3nc2c1,1bcu,3.2799999999999998
		C=CC[NH+](Cc1ccccc1C(=O)NCc1ccccc1)Cc1ccc2c(c1C(=O)[O-])OCO2,3zsx,3.2799999999999998
		CC(=O)NC1C(O)C=C(C(=O)[O-])OC1C(O)C(O)C[NH3+],1f8d,3.3999999999999999
		Nc1nc(CCc2ccccc2)cc(=O)[nH]1,2v00,3.6600000000000001
		O=C([O-])C1(O)C=CC(O)C(O)C1,3n7a,3.7000000000000002
		C=CCOC1(C(=O)[O-])CC(OC2(C(=O)[O-])OC(C(O)CO)C(O)C(O)C2O)C(O)C(C(O)CO)O1,2r23,3.7200000000000002
		CCCCCCCCCC(=O)[O-],3nq3,3.7799999999999998
		O=C([O-])COc1c(Br)csc1C(=O)[O-],2hb1,3.7999999999999998
		CC(=O)NC1C(O)C[NH2+]C(CO)C(O)C1O,2w66,4.0499999999999998
		CCCCc1nc2c(=O)[nH][nH]c(=O)c2[nH]1,1n2v,4.0800000000000001
		[NH3+]CCC[NH2+]CCCC[NH2+]CCC[NH3+],3kwa,4.0800000000000001
		O=C(NC1OC(CO)C(O)C(O)C1O)c1ccccc1,3g2n,4.0899999999999999
		C[NH+](C)Cc1cccc(C(=O)Nc2cccc(-c3nn[nH]n3)c2)c1,4de2,4.1200000000000001
		O=C(NCC=CC1OC(n2ccc(=O)cc2)C(O)C1O)c1cc([N+](=O)[O-])cc(O)c1O,3ozt,4.1299999999999999
		CC(C)CC([NH3+])C(=O)[O-],3b3w,4.1900000000000004
		Nc1cccc2c(S(=O)(=O)[O-])cccc12,3cft,4.1900000000000004
		[NH3+]C(Cc1c[nH]c2ccccc12)C(=O)[O-],3f3a,4.1900000000000004
		CC1OC(OC2C(CO)OC(OC3C(CO)OC(O)C(O)C3O)C(O)C2O)C(O)C(O)C1[NH2+]C1C=C(CO)C(O)C(O)C1O,2qmj,4.21
		[NH3+]C(CCCC[N+](=O)[O-])C(=O)[O-],3f80,4.2199999999999998
		CC(C)CC(NC(=O)C(CC(=O)[O-])NC(=O)C([NH3+])CCC(=O)[O-])C(=O)[O-],1a30,4.2999999999999998
		OCC1OC(OC2C(O)C[NH2+]OC2CO)C(O)C(O)C1O,1w3k,4.2999999999999998
		COc1ccc2c(c1)cc(CNS(=O)(=O)c1cc3ccccc3o1)n2CC(=O)[O-],3ivg,4.2999999999999998
		COC1OC(CO)C(O)C(O)C1O,2jdy,4.3700000000000001
		CCCCCCCCCC(=O)[O-],3u9q,4.3799999999999999
		O=S(=O)([O-])c1cccc2cccc(Nc3ccccc3)c12,3pxf,4.4299999999999997
		CCCCCCCCN=C1OCC2C(O)C(O)C(O)C(O)N12,2wbg,4.4500000000000002
		COC1C(CO)OC(OC2C(CO)OC(OC3C(CO)NC(=NO)C(O)C3O)C(O)C2O)C(O)C1O,1u33,4.5999999999999996
		Cn1c(=O)c2c(ncn2CC(O)CO)n(C)c1=O,2x0y,4.5999999999999996
		CNC(=O)C([NH3+])Cc1ccc(OCc2ccccc2)cc1,3mss,4.6600000000000001
		CC([NH3+])C1CCC(C(=O)Nc2ccncc2)CC1,1q8t,4.7599999999999998
		OC1(c2ccc(-c3ccccc3)cc2)C[NH+]2CCC1CC2,3acw,4.7599999999999998
		CC=COC1(C(=O)[O-])CC(O)C(O)C(C(O)COC2(C(=O)[O-])C=CCC(C(O)CO)O2)O1,3bpc,4.7999999999999998
		CC1CC(C)CN(C(=O)c2cc(Br)ccc2N)C1,3cj2,4.8499999999999996
		OCCNc1ncnc2oc(-c3ccccc3)c(-c3ccccc3)c12,2brb,4.8600000000000003
		Cc1o[nH]c(=O)c1CC([NH3+])C(=O)[O-],1p1q,4.8899999999999997
		OCC1CC2C(O)C(O)C1(O)C[NH+]2Cc1ccccc1,2vo5,4.8899999999999997
		OCC1C(O)C(O)C(O)c2nccn21,3d4z,4.8899999999999997
		C=C(CC)C(=O)c1ccc(OCC(=O)[O-])c(Cl)c1Cl,2gss,4.9400000000000004
		COC1=C2CC(C)CC(OC)C(O)C(C)C=C(C)C(OC(N)=O)C(OC)C=CC=C(C)C(=O)NC(=CC1=O)C2=O,2yge,5.0599999999999996
		NC(=[NH2+])c1ccc(N)cc1,3gy4,5.0999999999999996
		C=CC[NH+](Cc1ccccc1C(=O)NC(c1ccc(OC)cc1)c1ccc(OC)cc1)Cc1ccc2c(c1C(=O)[O-])OCO2,3zso,5.1200000000000001
		CC(C)C([NH3+])C(=O)N1CCCC1C(=O)NCC(=O)NC(CO)C(=O)NC(CCC(N)=O)C(=O)NC(Cc1c[nH]cn1)C(=O)NC(Cc1ccc(O)cc1)C(=O)NC(CC(=O)[O-])C(=O)NC(CO)C(=O)[O-],1zea,5.2199999999999998
		CC(C)C1[NH2+]CC(O)C(O)C1O,2zxd,5.2199999999999998
		CCCCCCCCCCCC(=O)[O-],3ueu,5.2400000000000002
		CC=C1C2C=C(C)CC1([NH3+])c1ccc(=O)[nH]c1C2,1gpk,5.3700000000000001
		CC(=O)NC1C(O)C=C(C(=O)[O-])OC1C(O)C(O)CO,1f8b,5.4000000000000004
		COC1OC(C)C(O)C(O)C1O,2jdm,5.4000000000000004
		CCC1CC1(NC(=O)C1CC2CN1C(=O)C(C(C)(C)C)NC(=O)OCC(C)(C)CCCCc1cccc3cn(cc13)C(=O)O2)C(=O)NS(=O)(=O)C1CC1,3su5,5.5800000000000001
		CCCC(=O)NC1C(=NOC(=O)Nc2ccccc2)OC(CO)C(O)C1O,2wca,5.5999999999999996
		O=C(CCC1=CC(O)(C(=O)[O-])CC(O)C1O)Nc1ccccc1,3n86,5.6399999999999997
		CC(C)C([NH3+])C(=O)N1CCCC1,1n1m,5.7000000000000002
		NC(=[NH2+])c1cc2c(I)cccc2s1,1o5b,5.7699999999999996
		C[N+](C)(C)CCCN1C(=O)C2C(C1=O)C(c1coc(-c3ccc(Cl)s3)n1)[NH+]1CCCC21,2y5h,5.79
		COc1ccc(S(=O)(=O)NC(C)C(=O)[O-])cc1,3ehy,5.8499999999999996
		O=c1cc(-c2ccccc2)oc2cc(O)cc(O)c12,4des,5.8499999999999996
		C[NH+]1CCC(c2c(O)cc(O)c3c(=O)cc(-c4ccccc4Cl)oc23)C(O)C1,3ebp,5.9100000000000001
		Cc1cncc2cccc(S(=O)(=O)N3CCC[NH2+]CC3C)c12,1q8u,5.96
		O=C(Nc1cccc(-c2nnn[nH]2)c1)c1ccc2n[nH]cc2c1,4de1,5.96
		C=CC(=O)Nc1ccc2c(Nc3ccn[nH]3)nc(-c3ccccc3)nc2c1,3huc,5.9900000000000002
		OCC[NH+]1CC(O)C(O)C(O)C1CO,3l4w,6.0
		OCC1C[NH2+]C(O)C(O)C1O,2vl4,6.0099999999999998
		CC(C)(C)C([NH3+])C(=O)NS(=O)(=O)OCC1OC(n2cnc3c(N)ncnc32)C(O)C1O,3coy,6.0199999999999996
		[NH3+]C(Cc1ccc(F)cc1)C(=O)[O-],3f3c,6.0199999999999996
		Cc1c2cc[nH]c(=O)c2c(C)c2c1[nH]c1ccc(O)cc12,3owj,6.0700000000000003
		O=C(CCC(O)(O)C(Cc1ccccc1)NC(=O)c1ccccc1)NC(Cc1ccccc1)C(=O)[O-],3bkk,6.0800000000000001
		CCc1cc(-c2n[nH]c(C(=O)[O-])c2-c2ccc3c(c2)OCO3)c(O)cc1O,1yc1,6.1699999999999999
		NS(=O)(=O)c1ccc2c(c1)C[NH2+]CC2,1hnn,6.2400000000000002
		Oc1cccc2cccnc12,3vh9,6.2400000000000002
		[NH3+]C(Cc1ns[nH]c1=O)C(=O)[O-],3bfu,6.2699999999999996
		OCC1OC(OC2C(CO)OC(OC3C(O)C[NH2+]OC3CO)C(O)C2O)C(O)C(O)C1O,1w3l,6.2800000000000002
		NC(=O)c1cccc(-c2cc(Nc3ccc(OC(F)(F)F)cc3)ncn2)c1,3k5v,6.2999999999999998
		O=C([O-])COc1c(C(=O)[O-])sc(-c2cccc(NCc3ccccc3)c2)c1Br,2qbr,6.3300000000000001
		[NH3+]C(CCC(=O)NC(CSCc1ccccc1)C(=O)NC(C(=O)[O-])c1ccccc1)C(=O)[O-],10gs,6.4000000000000004
		OCC1NC(=NO)C(O)C(O)C1O,2j78,6.4199999999999999
		Nc1ccc2nc(N)[nH]c(=O)c2c1,1r5y,6.46
		NS(=O)(=O)c1ccccc1F,2weg,6.5
		O=C([O-])c1ccc(Nc2nccc(Nc3ccccc3-c3ccccc3)n2)cc1,3uo4,6.5199999999999996
		CC(C)(C)c1ccc(C(=O)NNC(=O)Nc2cccc3ccccc23)cc1[N+](=O)[O-],3jvs,6.54
		COc1cc(CCc2ccccc2)c(C(=O)[O-])c(O)c1CC=C(C)C,2yfe,6.6299999999999999
		CC([NH2+]C(CCc1ccccc1)C(=O)NC(CCCNC(N)=[NH2+])C(=O)Nc1ccccc1)C(=O)[O-],1sln,6.6399999999999997
		O=C1CCCCCC=CCCOC(=O)c2c(O)cc(O)c(Cl)c2C1,2iwx,6.6799999999999997
		COC1OC(C)C(O)C(O)C1O,2jdu,6.7199999999999998
		COc1cccc(-c2cccc(C3(c4ccccc4)NC(=[NH2+])N(C)C3=O)c2)c1,4djv,6.7199999999999998
		Cc1c(-c2ccnc(Nc3ccc(N4CC[NH2+]CC4)cc3)n2)sc(=O)n1C,2xnb,6.8300000000000001
		O=C(NCC=CC1OC(Sc2ccncc2)C(O)C1O)c1cc([N+](=O)[O-])cc(O)c1O,3oe5,6.8799999999999999
		[NH3+]C(CC1(C(=O)[O-])CC2OCCCC2O1)C(=O)[O-],3gbb,6.9000000000000004
		Cc1ccccc1S(=O)(=O)Nc1cc(-c2ccc(C#N)cc2)sc1C(=O)[O-],2d3u,6.9199999999999999
		CCCCCCCCCCCCCCCCCC(=O)[O-],3uex,6.9199999999999999
		O=c1cc(-c2ccc(O)c(O)c2)oc2cc(O)cc(O)c12,4dew,7.0
		CC1OC(OC2C(CO)OC(O)C(O)C2O)C(O)C(O)C1[NH2+]C1CC(CO)C(OC2OC(CO)C(OC3OC(CO)C(O)C(O)C3O)C(O)C2O)C(O)C1O,1xd0,7.1200000000000001
		CC(O)(CS(=O)(=O)c1ccc(F)cc1)C(=O)Nc1ccc(C#N)c(C(F)(F)F)c1,1z95,7.1200000000000001
		OCC1C(O)C(O)C(O)c2nc(CNc3ccccc3)cn21,2vot,7.1399999999999997
		NC(=[NH2+])c1ccc(C2C3C(=O)N(Cc4ccc(F)cc4)C(=O)C3C3CCC[NH+]32)cc1,1oyt,7.2400000000000002
		[NH3+]C(CC(=O)N1CCCCCN1C(=O)c1ccccc1)Cc1cc(F)c(F)cc1F,2ole,7.25
		CNC(=O)c1cc(Oc2ccc(NC(=O)Nc3ccc(Cl)c(C(F)(F)F)c3)cc2)ccn1,3gcs,7.25
		CCNC1=NC2C(OC(CO)C(O)C2O)S1,2vvn,7.2999999999999998
		NC(=NO)NCCC([NH3+])C(=O)[O-],3kv2,7.3200000000000003
		CC(C)(C)NC(=O)C1CC2CCCCC2C[NH+]1CC(O)C(Cc1ccccc1)NC(=O)C(CC(N)=O)NC(=O)c1ccc2ccccc2n1,3pww,7.3200000000000003
		CC(C)(C)OC(=O)NC1CCCCCC=CC2CC2(C(=O)NS(=O)(=O)C2CC2)NC(=O)C2CC(OC(=O)n3cc4cccc(F)c4c3)CN2C1=O,3su2,7.3499999999999996
		CC(=O)NC1C([NH3+])C=C(C(=O)[O-])OC1C(O)C(O)CO,1f8c,7.4000000000000004
		OC1CC2OCC=C3C[NH+]4CCC56c7ccccc7N1C5C2C3CC46,2xys,7.4199999999999999
		OCC(O)C(O)C(O)C(O)C(O)C[S+]1CC(O)C(O)C1CO,3l4u,7.5199999999999996
		COc1ccc(CC2C(=O)C(O)C(O)CC2(O)C(=O)[O-])cc1,2xb8,7.5899999999999999
		NC(=[NH2+])NCc1ccccc1CCCCCCCCCC(=O)NC(CCCC[NH3+])C(=O)NO,2d1o,7.7000000000000002
		O=c1oc2c(O)c(O)cc3c(=O)oc4c(O)c(O)cc1c4c23,2zjw,7.7000000000000002
		CC(C)CC([NH3+])C(=O)[O-],3f3e,7.7000000000000002
		O=[N+]([O-])c1ccc2c(c1)C[NH2+]C(CO)C2,2g70,7.7699999999999996
		CC1[NH2+]C(C[NH3+])C(O)C(O)C1O,2zwz,7.79
		[NH3+]C(C(=O)[O-])C1CCC1C(=O)[O-],4g8m,7.8899999999999997
		NC(=[NH2+])c1ccc2[nH]c(-c3cccc(-c4ccccc4)c3O)cc2c1,1o3f,7.96
		CC(CS)C(=O)N1CCCC1C(=O)[O-],2x8z,7.96
		CC(C)(C)NC(=O)C1CC2CCCCC2C[NH+]1CC(O)C(Cc1ccccc1)NC(=O)C(CC(N)=O)NC(=O)c1ccc2ccccc2n1,3cyx,8.0
		OCC1C(O)C(O)C(O)c2nc(CCc3ccccc3)cn21,2cet,8.0199999999999996
		NC(=[NH2+])NCCCC(NC(=O)C(CCCNC(N)=[NH2+])NC(=O)CCCCCNC(=O)C(CCCC[NH3+])NC(=O)CCCCCNC(=O)C1OC(n2cnc3c(N)ncnc32)C(O)C1O)C(N)=O,3ag9,8.0500000000000007
		[NH3+]CCCCC([NH2+]C(CCc1ccccc1)C(=O)[O-])C(=O)NC(Cc1c[nH]c2ccccc12)C(=O)[O-],3l3n,8.1799999999999997
		C[NH2+]C1CC2OC(C)(C1OC)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)C(=O)NC4O,1nvq,8.25
		CC(=O)NC1C(=NOC(=O)Nc2ccccc2)OC(CO)C(O)C1O,2cbj,8.2699999999999996
		COC(C(=O)N1Cc2[nH]nc(NC(=O)c3ccc(N4CC[NH+](C)CC4)cc3)c2C1)c1ccccc1,2v7a,8.3000000000000007
		O=c1ccc2c([nH]1)CCCC2[NH2+]CCCCCCCCCCCC[NH2+]C1CCCc2[nH]c(=O)ccc21,1h23,8.3499999999999996
		O=C([O-])COc1c(C(=O)[O-])sc(-c2cccc(NC3CCN(S(=O)(=O)Cc4ccccc4)CC3)c2)c1Br,2qbp,8.4000000000000004
		CC(=O)Nc1ccc(OCC(C)(O)C(=O)Nc2ccc([N+](=O)[O-])c(C(F)(F)F)c2)cc1,3b68,8.4000000000000004
		O=C(Nc1ccc(Cl)cn1)C1C[NH+](CC(F)F)CC1C(=O)Nc1ccc(-n2ccccc2=O)cc1F,2xbv,8.4299999999999997
		COc1ccc(F)c(F)c1C(=O)c1cnc(NC2CCN(S(C)(=O)=O)CC2)nc1N,2fvd,8.5199999999999996
		COC1CC(C)Cc2cc(O)cc(c2)NC(=O)C(C)=CCCC(C)C(OC(N)=O)C(C)=CC(C)C1O,2vw5,8.5199999999999996
		CC(C)(C)c1ccc(C(=O)CC2CCC(O)C3C(O)C(O)C[NH+]23)cc1,3ejr,8.5700000000000003
		O=NC(=O)CNS(=O)(=O)c1ccc(-c2ccccc2)cc1,3f17,8.6300000000000008
		Cc1nc2nc(C(=O)N3CCOCC3)cn2c(-c2ccc(Cl)cc2Cl)c1C[NH3+],3nox,8.6600000000000001
		CC(C)CC(NC(=O)C(CCc1ccc(-c2ccc(F)cc2)cc1)CC(CCCCN1Cc2ccccc2C1=O)C(=O)[O-])C(=O)Nc1ccccc1,1hfs,8.6999999999999993
		c1ccc(C2([NH+]3CCCCC3)CCCCC2)cc1,2pcp,8.6999999999999993
		CNc1nc2c(CC[NH2+]CC3CCCC3)c3[nH]c(=[NH2+])[nH]c(=O)c3cc2[nH]1,3ge7,8.6999999999999993
		O=C([O-])c1ccc(Nc2ncc3c(n2)-c2ccc(Cl)cc2C(c2c(F)cccc2F)=NC3)cc1,2wtv,8.7400000000000002
		O=S(=O)(Nc1ccc(Cl)cc1)c1ccc2c(c1)C[NH2+]C(CO)C2,2obf,8.8499999999999996
		Cc1ccc(C(=O)Nc2cccc(N3CCOCC3)c2)cc1-c1ccc2c(C3CC[NH2+]CC3)noc2c1,3e93,8.8499999999999996
		COc1ccc2c(-c3c(C)n(Cc4cc(OC(C)C(=O)[O-])ccc4Cl)c4cc(OC(F)(F)F)ccc34)noc2c1,2p4y,9.0
		CCOc1ccc2nc(S(N)(=O)=O)sc2c1,3dd0,9.0
		Cc1ncnc2c1ncn2C1OC(C=CCNC(=O)c2cc(-c3ccc(F)cc3)cc(O)c2O)C(O)C1O,3nw9,9.0
		CSCCC([NH2+]CC(Cc1ccccc1)NC(=O)C(CO)NC(=O)C(CC(C)C)NC(=O)C(Cc1cnc[nH]1)NC(=O)C1CCC[NH2+]1)C(=O)NC(C)C(=O)NC(Cc1cnc[nH]1)C(=O)[O-],3uri,9.0
		Cc1cccc(C(=O)N2c3cccc(O)c3NC3=C(C2c2ccc(OCc4ccccc4)cc2F)S(=O)(=O)CC(C)(C)C3)n1,3gnw,9.0999999999999996
		CCC1CC1(NC(=O)C1CC2CN1C(=O)C(C(C)(C)C)NC(=O)OCC(C)(C)CCCCc1cccc3cn(cc13)C(=O)O2)C(=O)NS(=O)(=O)C1CC1,3su3,9.1300000000000008
		NC(=[NH2+])c1ccc2cc(C(=O)Nc3ccc(C[NH3+])cc3)cc(Nc3ncccn3)c2c1,1sqa,9.2100000000000009
		C[NH2+]C1C(O)COC2CC(CC([NH3+])C(=O)[O-])(C(=O)[O-])OC21,3fv1,9.3000000000000007
		O=C(NC1c2ccccc2-c2c(-c3nc4ccncc4[nH]3)cccc21)c1ccnc2[nH]ccc12,2yki,9.4600000000000009
		Cc1c(N=C2OC(C(F)(F)F)C3C(O)CCN23)ccc(C#N)c1Cl,3g0w,9.5199999999999996
		C#Cc1cccc(Nc2nc3cc(C(=O)[O-])ccc3c3cncnc23)c1,3pe2,9.7599999999999998
		CCC1=CC2Cc3nc4cc(Cl)ccc4c(N)c3C(C1)C2,1e66,9.8900000000000006
		CC1OC(OC2CCC3(C)C(CCC4C3CC(O)C3(C)C(C5=CC(=O)OC5)CCC43O)C2)CC(O)C1O,1igj,10.0
		CC1[NH2+]C(CNC(=O)Cc2c[nH]c3ccccc23)C(O)C(O)C1O,2zx6,10.6
		CC[NH+](Cc1cc(Nc2nc(C)cn3c(-c4cn[nH]c4)cnc23)sn1)C(C)(C)CO,3myg,10.699999999999999
		CC(C)CNC(=O)C([NH2+]CC(Cc1ccccc1)NC(=O)c1cc(C(=O)NC(C)c2ccccc2)cc(N(C)S(C)(=O)=O)c1)C(C)O,4gid,10.77
		COc1ccc(S(=O)(=O)NC(CC(=O)NCc2ccc(C#N)cc2)C(=O)N2CCCC2C(=O)NCc2ccc(C(N)=[NH2+])cc2)cc1Cl,3utu,10.92
		COc1cc(Cl)cc(C(=O)Nc2ccc(Cl)cn2)c1NC(=O)c1scc(CN(C)C2=NCCO2)c1Cl,1mq6,11.15

datasets/full_smiles_labels.csv

deleted100644 → 0

+0 −9881

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datasets/pdbbind_year.csv

deleted100644 → 0

+0 −11965

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datasets/refined_smiles_labels.csv

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+0 −3041

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deepchem/hyper/gaussian_process.py

+13 −5

Original line number	Diff line number	Diff line
		@@ -34,9 +34,8 @@ class GaussianProcessHyperparamOpt(HyperparamOpt):
		'bypass_dropouts', 'n_pair_feat', 'fit_transformers',
		'min_child_weight', 'max_delta_step','subsample',
		'colsample_bylevel', 'colsample_bytree', 'reg_alpha',
		'reg_lambda', 'scale_pos_weight', 'base_score', 'T', 'M'
		'reg_lambda', 'scale_pos_weight', 'base_score'
		],
		logdir=None,
		log_file='GPhypersearch.log'):
		"""Perform hyperparams search using a gaussian process assumption

		@@ -73,7 +72,9 @@ class GaussianProcessHyperparamOpt(HyperparamOpt):
		optimization on [initial values / search_range,
		initial values * search_range]
		hp_invalid_list: list
		names of parameters that should not be optimized
		names of parameters that should not be optimize
		logfile: string
		name of log file, hyperparameters and results for each trial will be recorded

		Returns
		-------
		@@ -190,6 +191,7 @@ class GaussianProcessHyperparamOpt(HyperparamOpt):
		print(hyper_parameters)
		# Run benchmark
		with open(log_file, 'a') as f:
		# Record hyperparameters
		f.write(str(hyper_parameters))
		f.write('\n')
		if isinstance(self.model_class, str) or isinstance(
		@@ -225,8 +227,10 @@ class GaussianProcessHyperparamOpt(HyperparamOpt):
		score = multitask_scores[metric.name]

		with open(log_file, 'a') as f:
		# Record performances
		f.write(str(score))
		f.write('\n')
		# GPGO maximize performance by default, set performance to its negative value for minimization
		if direction:
		return score
		else:
		@@ -260,8 +264,9 @@ class GaussianProcessHyperparamOpt(HyperparamOpt):
		hyper_parameters[hp[0]] = map(int, hyper_parameters[hp[0]])
		i = i + hp[1]


		# Compare best model to default hyperparameters
		with open(log_file, 'a') as f:
		# Record hyperparameters
		f.write(str(params_dict))
		f.write('\n')
		if isinstance(self.model_class, str) or isinstance(
		@@ -288,11 +293,14 @@ class GaussianProcessHyperparamOpt(HyperparamOpt):
		hyper_parameters=params_dict)
		score = valid_scores[self.model_class][metric[0].name]
		with open(log_file, 'a') as f:
		# Record performances
		f.write(str(score))
		f.write('\n')
		if not direction:
		score = -score
		if score > valid_performance_opt:
		# Optimized model is better, return hyperparameters
		return params_dict, score

		# Return default hyperparameters
		return hyper_parameters, valid_performance_opt

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