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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/results/meanInRadar/tables/ed_category_table_top.csv b/results/meanInRadar/tables/ed_category_table_top.csv new file mode 100644 index 00000000..1eeda15b --- /dev/null +++ b/results/meanInRadar/tables/ed_category_table_top.csv @@ -0,0 +1,7 @@ +ED score,latex category,number of model replicas,$d_{\mathrm{OO}}$,$d_{\mathrm{OH}}$,$\theta_{\mathrm{HOH}}$,$\theta_{\mathrm{ZOH}}$,"$(d_{\mathrm{O_d}\mathrm{O_a}}, \theta_{\mathrm{O_d}\mathrm{H}\mathrm{O_a}})$","$(S_k, S_g)$" +Pure,$F_{\mathcal{U}}(\mathcal{V})$,11,0.275599 +/- 0.031741,0.576532 +/- 0.066782,0.359159 +/- 0.058150,0.561244 +/- 0.039572,0.289474 +/- 0.066207,0.637434 +/- 0.066332 +Handcrafted,$F_{\overline{\mathcal{V}}}(\mathcal{V})$,11,0.250668 +/- 0.044479,0.600431 +/- 0.042217,0.498077 +/- 0.044695,0.582750 +/- 0.043586,0.362176 +/- 0.050520,0.589816 +/- 0.032142 +Style translated (L20L1),$F_{\widetilde{\mathcal{V}}}(\mathcal{V})$,11,0.501403 +/- 0.044059,0.739899 +/- 0.026731,0.456786 +/- 0.039028,0.726704 +/- 0.037023,0.771469 +/- 0.037032,0.647663 +/- 0.062463 +Style translated (L10L10),$F_{\widetilde{\mathcal{V}}}(\mathcal{V})$,11,0.433481 +/- 0.052406,0.703684 +/- 0.036449,0.575560 +/- 0.059645,0.564036 +/- 0.066593,0.735751 +/- 0.039150,0.595637 +/- 0.068111 +Hybrid (L20L1),$F_{\mathcal{V}^{\dagger}}(\mathcal{V})$,10,0.569767 +/- 0.019648,0.801374 +/- 0.033699,0.643962 +/- 0.053991,0.613493 +/- 0.041923,0.880770 +/- 0.023119,0.673267 +/- 0.058428 +Hybrid (L10L10),$F_{\mathcal{V}^{\dagger}}(\mathcal{V})$,11,0.512158 +/- 0.033083,0.796943 +/- 0.032596,0.690493 +/- 0.045397,0.641599 +/- 0.029290,0.866532 +/- 0.027714,0.695373 +/- 0.056797 diff --git a/results/meanInRadar/tables/ed_category_table_top_detailed.csv b/results/meanInRadar/tables/ed_category_table_top_detailed.csv new file mode 100644 index 00000000..65bf00a1 --- /dev/null +++ b/results/meanInRadar/tables/ed_category_table_top_detailed.csv @@ -0,0 +1,7 @@ +ED score,latex category,number of model replicas,$d_{\mathrm{OO}}$,$d_{\mathrm{OH}}$,$\theta_{\mathrm{HOH}}$,$\theta_{\mathrm{ZOH}}$,"$(d_{\mathrm{O_d}\mathrm{O_a}}, \theta_{\mathrm{O_d}\mathrm{H}\mathrm{O_a}})$","$(S_k, S_g)$" +Pure,$F_{\mathcal{U}}(\mathcal{V})$,11,"(0.014862 +/- 0.000592), (0.275599 +/- 0.031741)","(0.022186 +/- 0.001060), (0.576532 +/- 0.066782)","(0.026211 +/- 0.000796), (0.359159 +/- 0.058150)","(0.041248 +/- 0.003119), (0.561244 +/- 0.039572)","(0.106086 +/- 0.008836), (0.289474 +/- 0.066207)","(0.251196 +/- 0.010884), (0.637434 +/- 0.066332)" +Handcrafted,$F_{\overline{\mathcal{V}}}(\mathcal{V})$,11,"(0.015327 +/- 0.000830), (0.250668 +/- 0.044479)","(0.021806 +/- 0.000670), (0.600431 +/- 0.042217)","(0.024309 +/- 0.000612), (0.498077 +/- 0.044695)","(0.039553 +/- 0.003436), (0.582750 +/- 0.043586)","(0.096383 +/- 0.006742), (0.362176 +/- 0.050520)","(0.259010 +/- 0.005274), (0.589816 +/- 0.032142)" +Style translated (L20L1),$F_{\widetilde{\mathcal{V}}}(\mathcal{V})$,11,"(0.010650 +/- 0.000822), (0.501403 +/- 0.044059)","(0.019592 +/- 0.000424), (0.739899 +/- 0.026731)","(0.024874 +/- 0.000534), (0.456786 +/- 0.039028)","(0.028206 +/- 0.002918), (0.726704 +/- 0.037023)","(0.041762 +/- 0.004942), (0.771469 +/- 0.037032)","(0.249518 +/- 0.010249), (0.647663 +/- 0.062463)" +Style translated (L10L10),$F_{\widetilde{\mathcal{V}}}(\mathcal{V})$,11,"(0.011917 +/- 0.000977), (0.433481 +/- 0.052406)","(0.020167 +/- 0.000579), (0.703684 +/- 0.036449)","(0.023248 +/- 0.000816), (0.575560 +/- 0.059645)","(0.041028 +/- 0.005249), (0.564036 +/- 0.066593)","(0.046529 +/- 0.005225), (0.735751 +/- 0.039150)","(0.258055 +/- 0.011176), (0.595637 +/- 0.068111)" +Hybrid (L20L1),$F_{\mathcal{V}^{\dagger}}(\mathcal{V})$,10,"(0.009375 +/- 0.000366), (0.569767 +/- 0.019648)","(0.018616 +/- 0.000535), (0.801374 +/- 0.033699)","(0.022312 +/- 0.000739), (0.643962 +/- 0.053991)","(0.037130 +/- 0.003305), (0.613493 +/- 0.041923)","(0.027176 +/- 0.003085), (0.880770 +/- 0.023119)","(0.245317 +/- 0.009587), (0.673267 +/- 0.058428)" +Hybrid (L10L10),$F_{\mathcal{V}^{\dagger}}(\mathcal{V})$,11,"(0.010450 +/- 0.000617), (0.512158 +/- 0.033083)","(0.018686 +/- 0.000518), (0.796943 +/- 0.032596)","(0.021675 +/- 0.000621), (0.690493 +/- 0.045397)","(0.034914 +/- 0.002309), (0.641599 +/- 0.029290)","(0.029076 +/- 0.003699), (0.866532 +/- 0.027714)","(0.241690 +/- 0.009320), (0.695373 +/- 0.056797)" diff --git a/results/meanInRadar/tables/group_membership_top.json b/results/meanInRadar/tables/group_membership_top.json new file mode 100644 index 00000000..3e4ee09b --- /dev/null +++ b/results/meanInRadar/tables/group_membership_top.json @@ -0,0 +1,86 @@ +{ + "Ref": { + "pattern": "^Ref(_C\\d+)?$", + "matched_structures": [ + "Ref_C0", + "Ref", + "Ref_C2", + "Ref_C6", + "Ref_C8", + "Ref_C1", + "Ref_C4", + "Ref_C7", + "Ref_C5", + "Ref_C3", + "Ref_C9" + ], + "n_structures": 11 + }, + "PPAFM2Exp_CoAll_L20_L1_Elatest_Only": { + "pattern": "^PPAFM2Exp_CoAll_L20_L1_Elatest_Only(_C\\d+)?$", + "matched_structures": [ + "PPAFM2Exp_CoAll_L20_L1_Elatest_Only_C6", + "PPAFM2Exp_CoAll_L20_L1_Elatest_Only_C8", + "PPAFM2Exp_CoAll_L20_L1_Elatest_Only_C4", + "PPAFM2Exp_CoAll_L20_L1_Elatest_Only_C7", + "PPAFM2Exp_CoAll_L20_L1_Elatest_Only_C1", + "PPAFM2Exp_CoAll_L20_L1_Elatest_Only_C9", + "PPAFM2Exp_CoAll_L20_L1_Elatest_Only_C5", + "PPAFM2Exp_CoAll_L20_L1_Elatest_Only_C0", + "PPAFM2Exp_CoAll_L20_L1_Elatest_Only_C3", + "PPAFM2Exp_CoAll_L20_L1_Elatest_Only_C10", + "PPAFM2Exp_CoAll_L20_L1_Elatest_Only_C2" + ], + "n_structures": 11 + }, + "PPAFM2Exp_CoAll_L20_L1_Elatest": { + "pattern": "^PPAFM2Exp_CoAll_L20_L1_Elatest(_C\\d+)?$", + "matched_structures": [ + "PPAFM2Exp_CoAll_L20_L1_Elatest_C3", + "PPAFM2Exp_CoAll_L20_L1_Elatest_C9", + "PPAFM2Exp_CoAll_L20_L1_Elatest", + "PPAFM2Exp_CoAll_L20_L1_Elatest_C2", + "PPAFM2Exp_CoAll_L20_L1_Elatest_C4", + "PPAFM2Exp_CoAll_L20_L1_Elatest_C8", + "PPAFM2Exp_CoAll_L20_L1_Elatest_C0", + "PPAFM2Exp_CoAll_L20_L1_Elatest_C7", + "PPAFM2Exp_CoAll_L20_L1_Elatest_C1", + "PPAFM2Exp_CoAll_L20_L1_Elatest_C5" + ], + "n_structures": 10 + }, + "PPAFM2Exp_CoAll_L10_L10_Elatest_Only": { + "pattern": "^PPAFM2Exp_CoAll_L10_L10_Elatest_Only(_C\\d+)?$", + "matched_structures": [ + "PPAFM2Exp_CoAll_L10_L10_Elatest_Only_C9", + "PPAFM2Exp_CoAll_L10_L10_Elatest_Only_C7", + "PPAFM2Exp_CoAll_L10_L10_Elatest_Only_C5", + "PPAFM2Exp_CoAll_L10_L10_Elatest_Only_C3", + "PPAFM2Exp_CoAll_L10_L10_Elatest_Only_C4", + "PPAFM2Exp_CoAll_L10_L10_Elatest_Only_C8", + "PPAFM2Exp_CoAll_L10_L10_Elatest_Only_C2", + "PPAFM2Exp_CoAll_L10_L10_Elatest_Only_C1", + "PPAFM2Exp_CoAll_L10_L10_Elatest_Only_C10", + "PPAFM2Exp_CoAll_L10_L10_Elatest_Only_C0", + "PPAFM2Exp_CoAll_L10_L10_Elatest_Only_C6" + ], + "n_structures": 11 + }, + "PPAFM2Exp_CoAll_L10_L10_Elatest": { + "pattern": "^PPAFM2Exp_CoAll_L10_L10_Elatest(_C\\d+)?$", + "matched_structures": [ + "PPAFM2Exp_CoAll_L10_L10_Elatest_C1", + "PPAFM2Exp_CoAll_L10_L10_Elatest_C5", + "PPAFM2Exp_CoAll_L10_L10_Elatest_C6", + "PPAFM2Exp_CoAll_L10_L10_Elatest_C2", + "PPAFM2Exp_CoAll_L10_L10_Elatest_C3", + "PPAFM2Exp_CoAll_L10_L10_Elatest_C7", + "PPAFM2Exp_CoAll_L10_L10_Elatest", + "PPAFM2Exp_CoAll_L10_L10_Elatest_C4", + "PPAFM2Exp_CoAll_L10_L10_Elatest_C8", + "PPAFM2Exp_CoAll_L10_L10_Elatest_C0", + "PPAFM2Exp_CoAll_L10_L10_Elatest_C9" + ], + "n_structures": 11 + } +} \ No newline at end of file diff --git a/results/meanInRadar/tables/mmd_category_table_top.csv b/results/meanInRadar/tables/mmd_category_table_top.csv new file mode 100644 index 00000000..fb8833c0 --- /dev/null +++ b/results/meanInRadar/tables/mmd_category_table_top.csv @@ -0,0 +1,7 @@ +MMD score,latex category,number of model replicas,$d_{\mathrm{OO}}$,$d_{\mathrm{OH}}$,$\theta_{\mathrm{HOH}}$,$\theta_{\mathrm{ZOH}}$,"$(d_{\mathrm{O_d}\mathrm{O_a}}, \theta_{\mathrm{O_d}\mathrm{H}\mathrm{O_a}})$","$(S_k, S_g)$" +Pure,$F_{\mathcal{U}}(\mathcal{V})$,11,0.134016 +/- 0.018592,0.693685 +/- 0.061712,0.299984 +/- 0.065944,0.446540 +/- 0.035260,0.196940 +/- 0.052068,0.480083 +/- 0.079647 +Handcrafted,$F_{\overline{\mathcal{V}}}(\mathcal{V})$,11,0.149388 +/- 0.027545,0.760671 +/- 0.036710,0.615092 +/- 0.072449,0.471537 +/- 0.039159,0.289909 +/- 0.031952,0.384053 +/- 0.038761 +Style translated (L20L1),$F_{\widetilde{\mathcal{V}}}(\mathcal{V})$,11,0.331504 +/- 0.036543,0.727202 +/- 0.038545,0.424245 +/- 0.060947,0.589496 +/- 0.043429,0.704940 +/- 0.040222,0.437882 +/- 0.050752 +Style translated (L10L10),$F_{\widetilde{\mathcal{V}}}(\mathcal{V})$,11,0.300993 +/- 0.040128,0.719908 +/- 0.031362,0.495177 +/- 0.063986,0.454049 +/- 0.068748,0.640641 +/- 0.045170,0.425757 +/- 0.078091 +Hybrid (L20L1),$F_{\mathcal{V}^{\dagger}}(\mathcal{V})$,10,0.397052 +/- 0.013552,0.826062 +/- 0.035707,0.608789 +/- 0.060362,0.493610 +/- 0.042111,0.837969 +/- 0.025832,0.403592 +/- 0.054114 +Hybrid (L10L10),$F_{\mathcal{V}^{\dagger}}(\mathcal{V})$,11,0.377345 +/- 0.024576,0.825804 +/- 0.035850,0.672892 +/- 0.063560,0.515562 +/- 0.029586,0.799642 +/- 0.033428,0.472028 +/- 0.057574 diff --git a/results/meanInRadar/tables/mmd_category_table_top_detailed.csv b/results/meanInRadar/tables/mmd_category_table_top_detailed.csv new file mode 100644 index 00000000..5718b170 --- /dev/null +++ b/results/meanInRadar/tables/mmd_category_table_top_detailed.csv @@ -0,0 +1,7 @@ +MMD score,latex category,number of model replicas,$d_{\mathrm{OO}}$,$d_{\mathrm{OH}}$,$\theta_{\mathrm{HOH}}$,$\theta_{\mathrm{ZOH}}$,"$(d_{\mathrm{O_d}\mathrm{O_a}}, \theta_{\mathrm{O_d}\mathrm{H}\mathrm{O_a}})$","$(S_k, S_g)$" +Pure,$F_{\mathcal{U}}(\mathcal{V})$,11,"(0.381706 +/- 0.004799), (0.134016 +/- 0.018592)","(0.636832 +/- 0.007012), (0.693685 +/- 0.061712)","(0.709318 +/- 0.005983), (0.299984 +/- 0.065944)","(0.224151 +/- 0.008761), (0.446540 +/- 0.035260)","(0.483717 +/- 0.019009), (0.196940 +/- 0.052068)","(0.631027 +/- 0.014678), (0.480083 +/- 0.079647)" +Handcrafted,$F_{\overline{\mathcal{V}}}(\mathcal{V})$,11,"(0.377738 +/- 0.007110), (0.149388 +/- 0.027545)","(0.629221 +/- 0.004171), (0.760671 +/- 0.036710)","(0.680731 +/- 0.006573), (0.615092 +/- 0.072449)","(0.217940 +/- 0.009730), (0.471537 +/- 0.039159)","(0.449777 +/- 0.011665), (0.289909 +/- 0.031952)","(0.648725 +/- 0.007143), (0.384053 +/- 0.038761)" +Style translated (L20L1),$F_{\widetilde{\mathcal{V}}}(\mathcal{V})$,11,"(0.330730 +/- 0.009433), (0.331504 +/- 0.036543)","(0.633024 +/- 0.004380), (0.727202 +/- 0.038545)","(0.698045 +/- 0.005529), (0.424245 +/- 0.060947)","(0.188631 +/- 0.010791), (0.589496 +/- 0.043429)","(0.298260 +/- 0.014684), (0.704940 +/- 0.040222)","(0.638805 +/- 0.009353), (0.437882 +/- 0.050752)" +Style translated (L10L10),$F_{\widetilde{\mathcal{V}}}(\mathcal{V})$,11,"(0.338605 +/- 0.010358), (0.300993 +/- 0.040128)","(0.633852 +/- 0.003563), (0.719908 +/- 0.031362)","(0.691610 +/- 0.005805), (0.495177 +/- 0.063986)","(0.222285 +/- 0.017082), (0.454049 +/- 0.068748)","(0.321734 +/- 0.016490), (0.640641 +/- 0.045170)","(0.641039 +/- 0.014392), (0.425757 +/- 0.078091)" +Hybrid (L20L1),$F_{\mathcal{V}^{\dagger}}(\mathcal{V})$,10,"(0.313810 +/- 0.003498), (0.397052 +/- 0.013552)","(0.621791 +/- 0.004057), (0.826062 +/- 0.035707)","(0.681303 +/- 0.005476), (0.608789 +/- 0.060362)","(0.212456 +/- 0.010463), (0.493610 +/- 0.042111)","(0.249695 +/- 0.009430), (0.837969 +/- 0.025832)","(0.645124 +/- 0.009973), (0.403592 +/- 0.054114)" +Hybrid (L10L10),$F_{\mathcal{V}^{\dagger}}(\mathcal{V})$,11,"(0.318897 +/- 0.006344), (0.377345 +/- 0.024576)","(0.621820 +/- 0.004073), (0.825804 +/- 0.035850)","(0.675487 +/- 0.005766), (0.672892 +/- 0.063560)","(0.207001 +/- 0.007351), (0.515562 +/- 0.029586)","(0.263687 +/- 0.012204), (0.799642 +/- 0.033428)","(0.632512 +/- 0.010611), (0.472028 +/- 0.057574)" diff --git a/results/meanInRadar/tables/radar_stats_top_condensed.csv b/results/meanInRadar/tables/radar_stats_top_condensed.csv new file mode 100644 index 00000000..89603ad4 --- /dev/null +++ b/results/meanInRadar/tables/radar_stats_top_condensed.csv @@ -0,0 +1,16 @@ +group,metric,HOH,Hbond,OH,OO,OrderP,ZOH,n_HOH,n_Hbond,n_OH,n_OO,n_OrderP,n_ZOH +PPAFM2Exp_CoAll_L10_L10_Elatest,ED,0.021675 +/- 0.000621,0.029076 +/- 0.003699,0.018686 +/- 0.000518,0.010450 +/- 0.000617,0.241690 +/- 0.009320,0.034914 +/- 0.002309,11,11,11,11,11,11 +PPAFM2Exp_CoAll_L10_L10_Elatest,MMD,0.675487 +/- 0.005766,0.263687 +/- 0.012204,0.621820 +/- 0.004073,0.318897 +/- 0.006344,0.632512 +/- 0.010611,0.207001 +/- 0.007351,11,11,11,11,11,11 +PPAFM2Exp_CoAll_L10_L10_Elatest,WD,0.051522 +/- 0.001139,0.048406 +/- 0.004120,0.040573 +/- 0.000645,0.032041 +/- 0.001239,0.245997 +/- 0.007683,0.118144 +/- 0.003839,11,11,11,11,11,11 +PPAFM2Exp_CoAll_L10_L10_Elatest_Only,ED,0.023248 +/- 0.000816,0.046529 +/- 0.005225,0.020167 +/- 0.000579,0.011917 +/- 0.000977,0.258055 +/- 0.011176,0.041028 +/- 0.005249,11,11,11,11,11,11 +PPAFM2Exp_CoAll_L10_L10_Elatest_Only,MMD,0.691610 +/- 0.005805,0.321734 +/- 0.016490,0.633852 +/- 0.003563,0.338605 +/- 0.010358,0.641039 +/- 0.014392,0.222285 +/- 0.017082,11,11,11,11,11,11 +PPAFM2Exp_CoAll_L10_L10_Elatest_Only,WD,0.053425 +/- 0.001647,0.066208 +/- 0.005341,0.042898 +/- 0.000655,0.035385 +/- 0.001791,0.262284 +/- 0.009313,0.125227 +/- 0.008753,11,11,11,11,11,11 +PPAFM2Exp_CoAll_L20_L1_Elatest,ED,0.022312 +/- 0.000739,0.027176 +/- 0.003085,0.018616 +/- 0.000535,0.009375 +/- 0.000366,0.245317 +/- 0.009587,0.037130 +/- 0.003305,10,10,10,10,10,10 +PPAFM2Exp_CoAll_L20_L1_Elatest,MMD,0.681303 +/- 0.005476,0.249695 +/- 0.009430,0.621791 +/- 0.004057,0.313810 +/- 0.003498,0.645124 +/- 0.009973,0.212456 +/- 0.010463,10,10,10,10,10,10 +PPAFM2Exp_CoAll_L20_L1_Elatest,WD,0.052702 +/- 0.001289,0.048966 +/- 0.003328,0.040957 +/- 0.000574,0.031550 +/- 0.001542,0.247171 +/- 0.010070,0.121231 +/- 0.006147,10,10,10,10,10,10 +PPAFM2Exp_CoAll_L20_L1_Elatest_Only,ED,0.024874 +/- 0.000534,0.041762 +/- 0.004942,0.019592 +/- 0.000424,0.010650 +/- 0.000822,0.249518 +/- 0.010249,0.028206 +/- 0.002918,11,11,11,11,11,11 +PPAFM2Exp_CoAll_L20_L1_Elatest_Only,MMD,0.698045 +/- 0.005529,0.298260 +/- 0.014684,0.633024 +/- 0.004380,0.330730 +/- 0.009433,0.638805 +/- 0.009353,0.188631 +/- 0.010791,11,11,11,11,11,11 +PPAFM2Exp_CoAll_L20_L1_Elatest_Only,WD,0.057524 +/- 0.001173,0.064006 +/- 0.005201,0.043411 +/- 0.000550,0.034263 +/- 0.001712,0.253320 +/- 0.010350,0.104814 +/- 0.005701,11,11,11,11,11,11 +Ref,ED,0.024309 +/- 0.000612,0.096383 +/- 0.006742,0.021806 +/- 0.000670,0.015327 +/- 0.000830,0.259010 +/- 0.005274,0.039553 +/- 0.003436,11,11,11,11,11,11 +Ref,MMD,0.680731 +/- 0.006573,0.449777 +/- 0.011665,0.629221 +/- 0.004171,0.377738 +/- 0.007110,0.648725 +/- 0.007143,0.217940 +/- 0.009730,11,11,11,11,11,11 +Ref,WD,0.057553 +/- 0.001144,0.114462 +/- 0.006263,0.044694 +/- 0.000667,0.042481 +/- 0.001066,0.257413 +/- 0.003867,0.120964 +/- 0.006215,11,11,11,11,11,11 diff --git a/results/meanInRadar/tables/radar_stats_top_long.csv b/results/meanInRadar/tables/radar_stats_top_long.csv new file mode 100644 index 00000000..88d98058 --- /dev/null +++ b/results/meanInRadar/tables/radar_stats_top_long.csv @@ -0,0 +1,91 @@ +layer,group,distance_key,metric,property,n,mean,std,sem +Top,Ref,wdistancec_nor,WD,OO,11,0.042481241659697445,0.0035360156633612414,0.0010661488371080806 +Top,Ref,wdistancec_nor,WD,OH,11,0.04469414125018884,0.0022134578632017903,0.0006673826565001954 +Top,Ref,wdistancec_nor,WD,HOH,11,0.05755268589979994,0.0037957247935201835,0.0011444540861414248 +Top,Ref,wdistancec_nor,WD,ZOH,11,0.12096354147219766,0.02061330657048898,0.006215145780261782 +Top,Ref,wdistancec_nor,WD,Hbond,11,0.11446212773973291,0.020771613418908527,0.006262877090984628 +Top,Ref,wdistancec_nor,WD,OrderP,11,0.2574126408858733,0.012824408901192038,0.0038667047712134515 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest_Only,wdistancec_nor,WD,OO,11,0.03426253401562478,0.005677121164364217,0.0017117164355983342 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest_Only,wdistancec_nor,WD,OH,11,0.043410848767097894,0.001824039888798885,0.0005499687194352262 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest_Only,wdistancec_nor,WD,HOH,11,0.05752402791011428,0.003889281543891055,0.0011726625077400725 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest_Only,wdistancec_nor,WD,ZOH,11,0.10481442589446856,0.018907318342372168,0.005700770975768445 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest_Only,wdistancec_nor,WD,Hbond,11,0.06400576538660309,0.017248345477159636,0.00520057183656019 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest_Only,wdistancec_nor,WD,OrderP,11,0.2533200830221176,0.03432772796012159,0.01035019941355595 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,wdistancec_nor,WD,OO,10,0.031550152394393856,0.004877511565484328,0.001542404586074399 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,wdistancec_nor,WD,OH,10,0.04095724178820863,0.00181486830855186,0.000573911750828112 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,wdistancec_nor,WD,HOH,10,0.05270242752880476,0.004074949176570743,0.0012886120747391192 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,wdistancec_nor,WD,ZOH,10,0.12123111534691162,0.01943964441236637,0.006147355324684323 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,wdistancec_nor,WD,Hbond,10,0.048966304212808606,0.010523783922257094,0.003327912679779277 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,wdistancec_nor,WD,OrderP,10,0.2471708297729492,0.03184474798206013,0.010070193513736081 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest_Only,wdistancec_nor,WD,OO,11,0.035384589338614394,0.005940696754461505,0.001791187466166445 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest_Only,wdistancec_nor,WD,OH,11,0.04289795750883473,0.0021732261297047893,0.0006552523324388203 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest_Only,wdistancec_nor,WD,HOH,11,0.05342514690095794,0.005463024367970988,0.00164716382264802 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest_Only,wdistancec_nor,WD,ZOH,11,0.12522666799377252,0.02902990626834422,0.008752846071934915 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest_Only,wdistancec_nor,WD,Hbond,11,0.06620849872177298,0.017714212347864838,0.00534103598314075 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest_Only,wdistancec_nor,WD,OrderP,11,0.26228382370688696,0.030889342131899825,0.00931348707931168 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest,wdistancec_nor,WD,OO,11,0.03204091387235946,0.004110895383278439,0.0012394815944308032 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest,wdistancec_nor,WD,OH,11,0.04057337632354672,0.002139227036898834,0.0006450012202524726 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest,wdistancec_nor,WD,HOH,11,0.05152165980326306,0.0037792592533227305,0.0011394895389772914 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest,wdistancec_nor,WD,ZOH,11,0.11814423346789392,0.012733898111384971,0.0038394147412799274 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest,wdistancec_nor,WD,Hbond,11,0.04840597713535482,0.013665750434245637,0.004120378788093559 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest,wdistancec_nor,WD,OrderP,11,0.2459973625161431,0.025481739879380752,0.0076830336532129105 +Top,Ref,edistancec_nor,ED,OO,11,0.015326649493213142,0.0027512532933498157,0.0008295340797519033 +Top,Ref,edistancec_nor,ED,OH,11,0.021806109463587617,0.002223080755324552,0.0006702840676428561 +Top,Ref,edistancec_nor,ED,HOH,11,0.024308996743274004,0.0020292361979814353,0.0006118377345192515 +Top,Ref,edistancec_nor,ED,ZOH,11,0.03955300861877487,0.011395104969853543,0.0034357534210652982 +Top,Ref,edistancec_nor,ED,Hbond,11,0.0963833882432794,0.022360975915651747,0.0067420879143991475 +Top,Ref,edistancec_nor,ED,OrderP,11,0.2590098852381029,0.017491861054529795,0.0052739945457186965 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest_Only,edistancec_nor,ED,OO,11,0.010650441045892821,0.0027253055426715556,0.0008217105385561325 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest_Only,edistancec_nor,ED,OH,11,0.019591751811166427,0.0014076416910505786,0.0004244199389523769 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest_Only,edistancec_nor,ED,HOH,11,0.024874235321097508,0.0017719321891396121,0.0005342576568481047 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest_Only,edistancec_nor,ED,ZOH,11,0.02820563919214444,0.009679327712028023,0.0029184271130623775 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest_Only,edistancec_nor,ED,Hbond,11,0.04176203619768944,0.01639083114083033,0.004942021536018832 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest_Only,edistancec_nor,ED,OrderP,11,0.24951792314305,0.03399292613306611,0.010249252864513362 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,edistancec_nor,ED,OO,10,0.009375440083210774,0.0011587810100694446,0.0003664387301169954 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,edistancec_nor,ED,OH,10,0.018615708881767657,0.0016919506748193799,0.0005350417821088139 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,edistancec_nor,ED,HOH,10,0.022311952704815684,0.0023371969977798103,0.0007390865853491699 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,edistancec_nor,ED,ZOH,10,0.037129703839061,0.01045011868261961,0.0033046176856156204 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,edistancec_nor,ED,Hbond,10,0.027175587643926025,0.009756376102384163,0.003085237019277008 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,edistancec_nor,ED,OrderP,10,0.24531680856426266,0.030317027804200397,0.009587085974792653 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+Top,PPAFM2Exp_CoAll_L10_L10_Elatest,edistancec_nor,ED,OH,11,0.018686050653612254,0.001716437734360728,0.0005175254491711134 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest,edistancec_nor,ED,HOH,11,0.02167498460948311,0.0020610860795827577,0.0006214408351455088 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest,edistancec_nor,ED,ZOH,11,0.03491415662763565,0.007657586604150243,0.002308849233238011 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest,edistancec_nor,ED,Hbond,11,0.02907567175856405,0.012266656770738486,0.003698536176419289 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest,edistancec_nor,ED,OrderP,11,0.2416895081981292,0.030909589052794888,0.00931959175565431 +Top,Ref,mdistancec_nor,MMD,OO,11,0.3777380371048389,0.023580884911130362,0.007109904315888414 +Top,Ref,mdistancec_nor,MMD,OH,11,0.6292207091627587,0.013833970877818713,0.004171099160220745 +Top,Ref,mdistancec_nor,MMD,HOH,11,0.6807306902414686,0.0217997238354004,0.006572864045035497 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+Top,PPAFM2Exp_CoAll_L20_L1_Elatest_Only,mdistancec_nor,MMD,OrderP,11,0.6388046388943809,0.03102094753267159,0.00935316760065207 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,mdistancec_nor,MMD,OO,10,0.3138101552486602,0.011061592287495807,0.003497982617663883 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,mdistancec_nor,MMD,OH,10,0.6217908751391874,0.012829659788009175,0.004057094653518199 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,mdistancec_nor,MMD,HOH,10,0.6813025396115694,0.017317485419973265,0.005476269727387308 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,mdistancec_nor,MMD,ZOH,10,0.2124556465297356,0.03308782774580087,0.010463289850404556 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,mdistancec_nor,MMD,Hbond,10,0.2496954683472022,0.029821752620516364,0.009430466209892671 +Top,PPAFM2Exp_CoAll_L20_L1_Elatest,mdistancec_nor,MMD,OrderP,10,0.6451239296551358,0.03153700492477996,0.009972876614225183 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest_Only,mdistancec_nor,MMD,OO,11,0.3386053293716922,0.0343532101093027,0.010357882570618279 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest_Only,mdistancec_nor,MMD,OH,11,0.6338523198138382,0.011818481763528899,0.003563406327389377 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest_Only,mdistancec_nor,MMD,HOH,11,0.6916098096534088,0.019252980109710358,0.00580499192000771 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest_Only,mdistancec_nor,MMD,ZOH,11,0.22228535951663472,0.056653538028540625,0.017081684426072746 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest_Only,mdistancec_nor,MMD,Hbond,11,0.32173448368003577,0.05469212695615404,0.016490296736367756 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest_Only,mdistancec_nor,MMD,OrderP,11,0.6410392194577275,0.04773169962725165,0.014391648933594584 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest,mdistancec_nor,MMD,OO,11,0.318897095283908,0.021039742897548393,0.006343721170610268 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest,mdistancec_nor,MMD,OH,11,0.6218201662526878,0.013509704890098884,0.004073329286262503 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest,mdistancec_nor,MMD,HOH,11,0.6754869481043662,0.019124958753617482,0.005766392028797477 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest,mdistancec_nor,MMD,ZOH,11,0.20700136014457413,0.024380964130608487,0.007351137277121991 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest,mdistancec_nor,MMD,Hbond,11,0.2636874880292344,0.04047520321499406,0.01220373294341108 +Top,PPAFM2Exp_CoAll_L10_L10_Elatest,mdistancec_nor,MMD,OrderP,11,0.6325118236056245,0.03519105709718465,0.010610502942484994 diff --git a/results/meanInRadar/tables/radar_stats_top_long.md b/results/meanInRadar/tables/radar_stats_top_long.md new file mode 100644 index 00000000..e1ed4da8 --- /dev/null +++ b/results/meanInRadar/tables/radar_stats_top_long.md @@ -0,0 +1,92 @@ +| group | metric | property | n | mean_pm_sem | std | mean | sem | +| --- | --- | --- | --- | --- | --- | --- | --- | +| Ref | WD | OO | 11 | 0.042481 +/- 0.001066 | 0.003536 | 0.042481 | 0.001066 | +| Ref | WD | OH | 11 | 0.044694 +/- 0.000667 | 0.002213 | 0.044694 | 0.000667 | +| Ref | WD | HOH | 11 | 0.057553 +/- 0.001144 | 0.003796 | 0.057553 | 0.001144 | +| Ref | WD | ZOH | 11 | 0.120964 +/- 0.006215 | 0.020613 | 0.120964 | 0.006215 | +| Ref | WD | Hbond | 11 | 0.114462 +/- 0.006263 | 0.020772 | 0.114462 | 0.006263 | +| Ref | WD | OrderP | 11 | 0.257413 +/- 0.003867 | 0.012824 | 0.257413 | 0.003867 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | WD | OO | 11 | 0.034263 +/- 0.001712 | 0.005677 | 0.034263 | 0.001712 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | WD | OH | 11 | 0.043411 +/- 0.000550 | 0.001824 | 0.043411 | 0.000550 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | WD | HOH | 11 | 0.057524 +/- 0.001173 | 0.003889 | 0.057524 | 0.001173 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | WD | ZOH | 11 | 0.104814 +/- 0.005701 | 0.018907 | 0.104814 | 0.005701 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | WD | Hbond | 11 | 0.064006 +/- 0.005201 | 0.017248 | 0.064006 | 0.005201 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | WD | OrderP | 11 | 0.253320 +/- 0.010350 | 0.034328 | 0.253320 | 0.010350 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | WD | OO | 10 | 0.031550 +/- 0.001542 | 0.004878 | 0.031550 | 0.001542 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | WD | OH | 10 | 0.040957 +/- 0.000574 | 0.001815 | 0.040957 | 0.000574 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | WD | HOH | 10 | 0.052702 +/- 0.001289 | 0.004075 | 0.052702 | 0.001289 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | WD | ZOH | 10 | 0.121231 +/- 0.006147 | 0.019440 | 0.121231 | 0.006147 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | WD | Hbond | 10 | 0.048966 +/- 0.003328 | 0.010524 | 0.048966 | 0.003328 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | WD | OrderP | 10 | 0.247171 +/- 0.010070 | 0.031845 | 0.247171 | 0.010070 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | WD | OO | 11 | 0.035385 +/- 0.001791 | 0.005941 | 0.035385 | 0.001791 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | WD | OH | 11 | 0.042898 +/- 0.000655 | 0.002173 | 0.042898 | 0.000655 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | WD | HOH | 11 | 0.053425 +/- 0.001647 | 0.005463 | 0.053425 | 0.001647 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | WD | ZOH | 11 | 0.125227 +/- 0.008753 | 0.029030 | 0.125227 | 0.008753 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | WD | Hbond | 11 | 0.066208 +/- 0.005341 | 0.017714 | 0.066208 | 0.005341 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | WD | OrderP | 11 | 0.262284 +/- 0.009313 | 0.030889 | 0.262284 | 0.009313 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | WD | OO | 11 | 0.032041 +/- 0.001239 | 0.004111 | 0.032041 | 0.001239 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | WD | OH | 11 | 0.040573 +/- 0.000645 | 0.002139 | 0.040573 | 0.000645 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | WD | HOH | 11 | 0.051522 +/- 0.001139 | 0.003779 | 0.051522 | 0.001139 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | WD | ZOH | 11 | 0.118144 +/- 0.003839 | 0.012734 | 0.118144 | 0.003839 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | WD | Hbond | 11 | 0.048406 +/- 0.004120 | 0.013666 | 0.048406 | 0.004120 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | WD | OrderP | 11 | 0.245997 +/- 0.007683 | 0.025482 | 0.245997 | 0.007683 | +| Ref | ED | OO | 11 | 0.015327 +/- 0.000830 | 0.002751 | 0.015327 | 0.000830 | +| Ref | ED | OH | 11 | 0.021806 +/- 0.000670 | 0.002223 | 0.021806 | 0.000670 | +| Ref | ED | HOH | 11 | 0.024309 +/- 0.000612 | 0.002029 | 0.024309 | 0.000612 | +| Ref | ED | ZOH | 11 | 0.039553 +/- 0.003436 | 0.011395 | 0.039553 | 0.003436 | +| Ref | ED | Hbond | 11 | 0.096383 +/- 0.006742 | 0.022361 | 0.096383 | 0.006742 | +| Ref | ED | OrderP | 11 | 0.259010 +/- 0.005274 | 0.017492 | 0.259010 | 0.005274 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | ED | OO | 11 | 0.010650 +/- 0.000822 | 0.002725 | 0.010650 | 0.000822 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | ED | OH | 11 | 0.019592 +/- 0.000424 | 0.001408 | 0.019592 | 0.000424 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | ED | HOH | 11 | 0.024874 +/- 0.000534 | 0.001772 | 0.024874 | 0.000534 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | ED | ZOH | 11 | 0.028206 +/- 0.002918 | 0.009679 | 0.028206 | 0.002918 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | ED | Hbond | 11 | 0.041762 +/- 0.004942 | 0.016391 | 0.041762 | 0.004942 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | ED | OrderP | 11 | 0.249518 +/- 0.010249 | 0.033993 | 0.249518 | 0.010249 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | ED | OO | 10 | 0.009375 +/- 0.000366 | 0.001159 | 0.009375 | 0.000366 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | ED | OH | 10 | 0.018616 +/- 0.000535 | 0.001692 | 0.018616 | 0.000535 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | ED | HOH | 10 | 0.022312 +/- 0.000739 | 0.002337 | 0.022312 | 0.000739 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | ED | ZOH | 10 | 0.037130 +/- 0.003305 | 0.010450 | 0.037130 | 0.003305 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | ED | Hbond | 10 | 0.027176 +/- 0.003085 | 0.009756 | 0.027176 | 0.003085 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | ED | OrderP | 10 | 0.245317 +/- 0.009587 | 0.030317 | 0.245317 | 0.009587 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | ED | OO | 11 | 0.011917 +/- 0.000977 | 0.003242 | 0.011917 | 0.000977 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | ED | OH | 11 | 0.020167 +/- 0.000579 | 0.001919 | 0.020167 | 0.000579 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | ED | HOH | 11 | 0.023248 +/- 0.000816 | 0.002708 | 0.023248 | 0.000816 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | ED | ZOH | 11 | 0.041028 +/- 0.005249 | 0.017410 | 0.041028 | 0.005249 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | ED | Hbond | 11 | 0.046529 +/- 0.005225 | 0.017329 | 0.046529 | 0.005225 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | ED | OrderP | 11 | 0.258055 +/- 0.011176 | 0.037067 | 0.258055 | 0.011176 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | ED | OO | 11 | 0.010450 +/- 0.000617 | 0.002046 | 0.010450 | 0.000617 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | ED | OH | 11 | 0.018686 +/- 0.000518 | 0.001716 | 0.018686 | 0.000518 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | ED | HOH | 11 | 0.021675 +/- 0.000621 | 0.002061 | 0.021675 | 0.000621 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | ED | ZOH | 11 | 0.034914 +/- 0.002309 | 0.007658 | 0.034914 | 0.002309 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | ED | Hbond | 11 | 0.029076 +/- 0.003699 | 0.012267 | 0.029076 | 0.003699 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | ED | OrderP | 11 | 0.241690 +/- 0.009320 | 0.030910 | 0.241690 | 0.009320 | +| Ref | MMD | OO | 11 | 0.377738 +/- 0.007110 | 0.023581 | 0.377738 | 0.007110 | +| Ref | MMD | OH | 11 | 0.629221 +/- 0.004171 | 0.013834 | 0.629221 | 0.004171 | +| Ref | MMD | HOH | 11 | 0.680731 +/- 0.006573 | 0.021800 | 0.680731 | 0.006573 | +| Ref | MMD | ZOH | 11 | 0.217940 +/- 0.009730 | 0.032270 | 0.217940 | 0.009730 | +| Ref | MMD | Hbond | 11 | 0.449777 +/- 0.011665 | 0.038688 | 0.449777 | 0.011665 | +| Ref | MMD | OrderP | 11 | 0.648725 +/- 0.007143 | 0.023692 | 0.648725 | 0.007143 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | MMD | OO | 11 | 0.330730 +/- 0.009433 | 0.031284 | 0.330730 | 0.009433 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | MMD | OH | 11 | 0.633024 +/- 0.004380 | 0.014525 | 0.633024 | 0.004380 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | MMD | HOH | 11 | 0.698045 +/- 0.005529 | 0.018339 | 0.698045 | 0.005529 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | MMD | ZOH | 11 | 0.188631 +/- 0.010791 | 0.035789 | 0.188631 | 0.010791 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | MMD | Hbond | 11 | 0.298260 +/- 0.014684 | 0.048701 | 0.298260 | 0.014684 | +| PPAFM2Exp_CoAll_L20_L1_Elatest_Only | MMD | OrderP | 11 | 0.638805 +/- 0.009353 | 0.031021 | 0.638805 | 0.009353 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | MMD | OO | 10 | 0.313810 +/- 0.003498 | 0.011062 | 0.313810 | 0.003498 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | MMD | OH | 10 | 0.621791 +/- 0.004057 | 0.012830 | 0.621791 | 0.004057 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | MMD | HOH | 10 | 0.681303 +/- 0.005476 | 0.017317 | 0.681303 | 0.005476 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | MMD | ZOH | 10 | 0.212456 +/- 0.010463 | 0.033088 | 0.212456 | 0.010463 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | MMD | Hbond | 10 | 0.249695 +/- 0.009430 | 0.029822 | 0.249695 | 0.009430 | +| PPAFM2Exp_CoAll_L20_L1_Elatest | MMD | OrderP | 10 | 0.645124 +/- 0.009973 | 0.031537 | 0.645124 | 0.009973 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | MMD | OO | 11 | 0.338605 +/- 0.010358 | 0.034353 | 0.338605 | 0.010358 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | MMD | OH | 11 | 0.633852 +/- 0.003563 | 0.011818 | 0.633852 | 0.003563 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | MMD | HOH | 11 | 0.691610 +/- 0.005805 | 0.019253 | 0.691610 | 0.005805 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | MMD | ZOH | 11 | 0.222285 +/- 0.017082 | 0.056654 | 0.222285 | 0.017082 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | MMD | Hbond | 11 | 0.321734 +/- 0.016490 | 0.054692 | 0.321734 | 0.016490 | +| PPAFM2Exp_CoAll_L10_L10_Elatest_Only | MMD | OrderP | 11 | 0.641039 +/- 0.014392 | 0.047732 | 0.641039 | 0.014392 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | MMD | OO | 11 | 0.318897 +/- 0.006344 | 0.021040 | 0.318897 | 0.006344 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | MMD | OH | 11 | 0.621820 +/- 0.004073 | 0.013510 | 0.621820 | 0.004073 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | MMD | HOH | 11 | 0.675487 +/- 0.005766 | 0.019125 | 0.675487 | 0.005766 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | MMD | ZOH | 11 | 0.207001 +/- 0.007351 | 0.024381 | 0.207001 | 0.007351 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | MMD | Hbond | 11 | 0.263687 +/- 0.012204 | 0.040475 | 0.263687 | 0.012204 | +| PPAFM2Exp_CoAll_L10_L10_Elatest | MMD | OrderP | 11 | 0.632512 +/- 0.010611 | 0.035191 | 0.632512 | 0.010611 | diff --git a/results/meanInRadar/tables/radar_stats_top_wide.csv b/results/meanInRadar/tables/radar_stats_top_wide.csv new file mode 100644 index 00000000..8f2bbcaf --- /dev/null +++ b/results/meanInRadar/tables/radar_stats_top_wide.csv @@ -0,0 +1,16 @@ +group,metric,mean_HOH,mean_Hbond,mean_OH,mean_OO,mean_OrderP,mean_ZOH,n_HOH,n_Hbond,n_OH,n_OO,n_OrderP,n_ZOH,sem_HOH,sem_Hbond,sem_OH,sem_OO,sem_OrderP,sem_ZOH +PPAFM2Exp_CoAll_L10_L10_Elatest,ED,0.02167498460948311,0.02907567175856405,0.018686050653612254,0.010449867680614094,0.2416895081981292,0.03491415662763565,11,11,11,11,11,11,0.0006214408351455088,0.003698536176419289,0.0005175254491711134,0.0006169949846514367,0.00931959175565431,0.002308849233238011 +PPAFM2Exp_CoAll_L10_L10_Elatest,MMD,0.6754869481043662,0.2636874880292344,0.6218201662526878,0.318897095283908,0.6325118236056245,0.20700136014457413,11,11,11,11,11,11,0.005766392028797477,0.01220373294341108,0.004073329286262503,0.006343721170610268,0.010610502942484994,0.007351137277121991 +PPAFM2Exp_CoAll_L10_L10_Elatest,WD,0.05152165980326306,0.04840597713535482,0.04057337632354672,0.03204091387235946,0.2459973625161431,0.11814423346789392,11,11,11,11,11,11,0.0011394895389772914,0.004120378788093559,0.0006450012202524726,0.0012394815944308032,0.0076830336532129105,0.0038394147412799274 +PPAFM2Exp_CoAll_L10_L10_Elatest_Only,ED,0.02324831273989542,0.046528787297849705,0.0201667397415644,0.0119171867256867,0.2580547052177222,0.041028207743320874,11,11,11,11,11,11,0.0008164849024293039,0.005224741767566058,0.0005787014877767485,0.0009773826243085584,0.011176045929896985,0.00524927761046104 +PPAFM2Exp_CoAll_L10_L10_Elatest_Only,MMD,0.6916098096534088,0.32173448368003577,0.6338523198138382,0.3386053293716922,0.6410392194577275,0.22228535951663472,11,11,11,11,11,11,0.00580499192000771,0.016490296736367756,0.003563406327389377,0.010357882570618279,0.014391648933594584,0.017081684426072746 +PPAFM2Exp_CoAll_L10_L10_Elatest_Only,WD,0.05342514690095794,0.06620849872177298,0.04289795750883473,0.035384589338614394,0.26228382370688696,0.12522666799377252,11,11,11,11,11,11,0.00164716382264802,0.00534103598314075,0.0006552523324388203,0.001791187466166445,0.00931348707931168,0.008752846071934915 +PPAFM2Exp_CoAll_L20_L1_Elatest,ED,0.022311952704815684,0.027175587643926025,0.018615708881767657,0.009375440083210774,0.24531680856426266,0.037129703839061,10,10,10,10,10,10,0.0007390865853491699,0.003085237019277008,0.0005350417821088139,0.0003664387301169954,0.009587085974792653,0.0033046176856156204 +PPAFM2Exp_CoAll_L20_L1_Elatest,MMD,0.6813025396115694,0.2496954683472022,0.6217908751391874,0.3138101552486602,0.6451239296551358,0.2124556465297356,10,10,10,10,10,10,0.005476269727387308,0.009430466209892671,0.004057094653518199,0.003497982617663883,0.009972876614225183,0.010463289850404556 +PPAFM2Exp_CoAll_L20_L1_Elatest,WD,0.05270242752880476,0.048966304212808606,0.04095724178820863,0.031550152394393856,0.2471708297729492,0.12123111534691162,10,10,10,10,10,10,0.0012886120747391192,0.003327912679779277,0.000573911750828112,0.001542404586074399,0.010070193513736081,0.006147355324684323 +PPAFM2Exp_CoAll_L20_L1_Elatest_Only,ED,0.024874235321097508,0.04176203619768944,0.019591751811166427,0.010650441045892821,0.24951792314305,0.02820563919214444,11,11,11,11,11,11,0.0005342576568481047,0.004942021536018832,0.0004244199389523769,0.0008217105385561325,0.010249252864513362,0.0029184271130623775 +PPAFM2Exp_CoAll_L20_L1_Elatest_Only,MMD,0.6980450300529001,0.2982604117216889,0.6330235378658642,0.3307297047834266,0.6388046388943809,0.18863093822383795,11,11,11,11,11,11,0.005529283666497941,0.014683859315514155,0.004379567845058767,0.009432617967299094,0.00935316760065207,0.010790775133651053 +PPAFM2Exp_CoAll_L20_L1_Elatest_Only,WD,0.05752402791011428,0.06400576538660309,0.043410848767097894,0.03426253401562478,0.2533200830221176,0.10481442589446856,11,11,11,11,11,11,0.0011726625077400725,0.00520057183656019,0.0005499687194352262,0.0017117164355983342,0.01035019941355595,0.005700770975768445 +Ref,ED,0.024308996743274004,0.0963833882432794,0.021806109463587617,0.015326649493213142,0.2590098852381029,0.03955300861877487,11,11,11,11,11,11,0.0006118377345192515,0.0067420879143991475,0.0006702840676428561,0.0008295340797519033,0.0052739945457186965,0.0034357534210652982 +Ref,MMD,0.6807306902414686,0.44977681612878123,0.6292207091627587,0.3777380371048389,0.6487248559815245,0.21794010225112215,11,11,11,11,11,11,0.006572864045035497,0.011664882581824874,0.004171099160220745,0.007109904315888414,0.0071433079220963895,0.009729873190677852 +Ref,WD,0.05755268589979994,0.11446212773973291,0.04469414125018884,0.042481241659697445,0.2574126408858733,0.12096354147219766,11,11,11,11,11,11,0.0011444540861414248,0.006262877090984628,0.0006673826565001954,0.0010661488371080806,0.0038667047712134515,0.006215145780261782 diff --git a/results/meanInRadar/tables/wd_category_table_top.csv b/results/meanInRadar/tables/wd_category_table_top.csv new file mode 100644 index 00000000..edd86938 --- /dev/null +++ b/results/meanInRadar/tables/wd_category_table_top.csv @@ -0,0 +1,7 @@ +WD score,latex category,number of model replicas,$d_{\mathrm{OO}}$,$d_{\mathrm{OH}}$,$\theta_{\mathrm{HOH}}$,$\theta_{\mathrm{ZOH}}$,"$(d_{\mathrm{O_d}\mathrm{O_a}}, \theta_{\mathrm{O_d}\mathrm{H}\mathrm{O_a}})$","$(S_k, S_g)$" +Pure,$F_{\mathcal{U}}(\mathcal{V})$,11,0.253171 +/- 0.034706,0.662503 +/- 0.040391,0.321435 +/- 0.039361,0.434786 +/- 0.038833,0.279645 +/- 0.061220,0.597136 +/- 0.063515 +Handcrafted,$F_{\overline{\mathcal{V}}}(\mathcal{V})$,11,0.208591 +/- 0.027849,0.666324 +/- 0.025474,0.350691 +/- 0.035986,0.464916 +/- 0.046306,0.339818 +/- 0.047413,0.634877 +/- 0.025700 +Style translated (L20L1),$F_{\widetilde{\mathcal{V}}}(\mathcal{V})$,11,0.423275 +/- 0.044712,0.715308 +/- 0.020992,0.351592 +/- 0.036873,0.585236 +/- 0.042474,0.721796 +/- 0.039371,0.662078 +/- 0.068793 +Style translated (L10L10),$F_{\widetilde{\mathcal{V}}}(\mathcal{V})$,11,0.393965 +/- 0.046788,0.734885 +/- 0.025011,0.480477 +/- 0.051794,0.433153 +/- 0.065214,0.705120 +/- 0.040434,0.602500 +/- 0.061902 +Hybrid (L20L1),$F_{\mathcal{V}^{\dagger}}(\mathcal{V})$,10,0.494126 +/- 0.040290,0.808963 +/- 0.021906,0.503203 +/- 0.040519,0.462922 +/- 0.045801,0.835652 +/- 0.025194,0.702949 +/- 0.066932 +Hybrid (L10L10),$F_{\mathcal{V}^{\dagger}}(\mathcal{V})$,11,0.481307 +/- 0.032377,0.823615 +/- 0.024620,0.540331 +/- 0.035830,0.485921 +/- 0.028606,0.839894 +/- 0.031193,0.710749 +/- 0.051066 diff --git a/results/meanInRadar/tables/wd_category_table_top_detailed.csv b/results/meanInRadar/tables/wd_category_table_top_detailed.csv new file mode 100644 index 00000000..62eafe6f --- /dev/null +++ b/results/meanInRadar/tables/wd_category_table_top_detailed.csv @@ -0,0 +1,7 @@ +WD score,latex category,number of model replicas,$d_{\mathrm{OO}}$,$d_{\mathrm{OH}}$,$\theta_{\mathrm{HOH}}$,$\theta_{\mathrm{ZOH}}$,"$(d_{\mathrm{O_d}\mathrm{O_a}}, \theta_{\mathrm{O_d}\mathrm{H}\mathrm{O_a}})$","$(S_k, S_g)$" +Pure,$F_{\mathcal{U}}(\mathcal{V})$,11,"(0.040775 +/- 0.001329), (0.253171 +/- 0.034706)","(0.044794 +/- 0.001058), (0.662503 +/- 0.040391)","(0.058483 +/- 0.001252), (0.321435 +/- 0.039361)","(0.125007 +/- 0.005212), (0.434786 +/- 0.038833)","(0.122411 +/- 0.008087), (0.279645 +/- 0.061220)","(0.263091 +/- 0.009556), (0.597136 +/- 0.063515)" +Handcrafted,$F_{\overline{\mathcal{V}}}(\mathcal{V})$,11,"(0.042481 +/- 0.001066), (0.208591 +/- 0.027849)","(0.044694 +/- 0.000667), (0.666324 +/- 0.025474)","(0.057553 +/- 0.001144), (0.350691 +/- 0.035986)","(0.120964 +/- 0.006215), (0.464916 +/- 0.046306)","(0.114462 +/- 0.006263), (0.339818 +/- 0.047413)","(0.257413 +/- 0.003867), (0.634877 +/- 0.025700)" +Style translated (L20L1),$F_{\widetilde{\mathcal{V}}}(\mathcal{V})$,11,"(0.034263 +/- 0.001712), (0.423275 +/- 0.044712)","(0.043411 +/- 0.000550), (0.715308 +/- 0.020992)","(0.057524 +/- 0.001173), (0.351592 +/- 0.036873)","(0.104814 +/- 0.005701), (0.585236 +/- 0.042474)","(0.064006 +/- 0.005201), (0.721796 +/- 0.039371)","(0.253320 +/- 0.010350), (0.662078 +/- 0.068793)" +Style translated (L10L10),$F_{\widetilde{\mathcal{V}}}(\mathcal{V})$,11,"(0.035385 +/- 0.001791), (0.393965 +/- 0.046788)","(0.042898 +/- 0.000655), (0.734885 +/- 0.025011)","(0.053425 +/- 0.001647), (0.480477 +/- 0.051794)","(0.125227 +/- 0.008753), (0.433153 +/- 0.065214)","(0.066208 +/- 0.005341), (0.705120 +/- 0.040434)","(0.262284 +/- 0.009313), (0.602500 +/- 0.061902)" +Hybrid (L20L1),$F_{\mathcal{V}^{\dagger}}(\mathcal{V})$,10,"(0.031550 +/- 0.001542), (0.494126 +/- 0.040290)","(0.040957 +/- 0.000574), (0.808963 +/- 0.021906)","(0.052702 +/- 0.001289), (0.503203 +/- 0.040519)","(0.121231 +/- 0.006147), (0.462922 +/- 0.045801)","(0.048966 +/- 0.003328), (0.835652 +/- 0.025194)","(0.247171 +/- 0.010070), (0.702949 +/- 0.066932)" +Hybrid (L10L10),$F_{\mathcal{V}^{\dagger}}(\mathcal{V})$,11,"(0.032041 +/- 0.001239), (0.481307 +/- 0.032377)","(0.040573 +/- 0.000645), (0.823615 +/- 0.024620)","(0.051522 +/- 0.001139), (0.540331 +/- 0.035830)","(0.118144 +/- 0.003839), (0.485921 +/- 0.028606)","(0.048406 +/- 0.004120), (0.839894 +/- 0.031193)","(0.245997 +/- 0.007683), (0.710749 +/- 0.051066)" diff --git a/src/performanceEvaluation/exportRadarStatsTable.py b/src/performanceEvaluation/exportRadarStatsTable.py new file mode 100644 index 00000000..a8f2cae8 --- /dev/null +++ b/src/performanceEvaluation/exportRadarStatsTable.py @@ -0,0 +1,343 @@ +#!/usr/bin/env python +import argparse +import json +import os +import re +from math import sqrt + +import numpy as np +import pandas as pd + + +DISTANCE_MAP = { + "wdistancec_nor": "WD", + "edistancec_nor": "ED", + "mdistancec_nor": "MMD", +} + +PROPERTY_MAP = { + "OO": "OO_dist", + "OH": "OH_dist", + "HOH": "HOH_dist", + "ZOH": "ThetaOH_dist", + "Hbond": "Hbonds", + "OrderP": "OrderP", +} + +# These 5 groups mirror visualiseEvaluateMeanInRadar.py intent. +GROUP_PATTERNS = { + "Ref": r"^Ref(_C\d+)?$", + "PPAFM2Exp_CoAll_L20_L1_Elatest_Only": r"^PPAFM2Exp_CoAll_L20_L1_Elatest_Only(_C\d+)?$", + "PPAFM2Exp_CoAll_L20_L1_Elatest": r"^PPAFM2Exp_CoAll_L20_L1_Elatest(_C\d+)?$", + "PPAFM2Exp_CoAll_L10_L10_Elatest_Only": r"^PPAFM2Exp_CoAll_L10_L10_Elatest_Only(_C\d+)?$", + "PPAFM2Exp_CoAll_L10_L10_Elatest": r"^PPAFM2Exp_CoAll_L10_L10_Elatest(_C\d+)?$", +} + +REFERENCE_PATTERN = {"Ref_Pure": r"^Ref_Pure(_C\d+)?$"} + +CATEGORY_GROUPS = { + "Pure": ["Ref_Pure"], + "Handcrafted": ["Ref"], + "Style translated (L20L1)": ["PPAFM2Exp_CoAll_L20_L1_Elatest_Only"], + "Style translated (L10L10)": ["PPAFM2Exp_CoAll_L10_L10_Elatest_Only"], + "Hybrid (L20L1)": ["PPAFM2Exp_CoAll_L20_L1_Elatest"], + "Hybrid (L10L10)": ["PPAFM2Exp_CoAll_L10_L10_Elatest"], +} + +CATEGORY_LATEX = { + "Pure": r"$F_{\mathcal{U}}(\mathcal{V})$", + "Handcrafted": r"$F_{\overline{\mathcal{V}}}(\mathcal{V})$", + "Style translated (L20L1)": r"$F_{\widetilde{\mathcal{V}}}(\mathcal{V})$", + "Style translated (L10L10)": r"$F_{\widetilde{\mathcal{V}}}(\mathcal{V})$", + "Hybrid (L20L1)": r"$F_{\mathcal{V}^{\dagger}}(\mathcal{V})$", + "Hybrid (L10L10)": r"$F_{\mathcal{V}^{\dagger}}(\mathcal{V})$", +} + + +def parse_args(): + parser = argparse.ArgumentParser( + description="Export mean/error tables for WD/ED/MMD radar metrics." + ) + parser.add_argument( + "--input-json", + default="../../processed_data/distribution_distances/similarities_Label_Top.json", + help="Path to similarities JSON file.", + ) + parser.add_argument( + "--output-dir", + default="../../results/meanInRadar/tables", + help="Directory for table and diagnostics outputs.", + ) + parser.add_argument( + "--include-reference-pure", + action="store_true", + help="Also include Ref_Pure summary rows in the outputs.", + ) + return parser.parse_args() + + +def build_distance_dataframe(similarities, distance_key): + rows = [] + for structure, values in similarities.items(): + row = {"Structure": structure} + for property_name, json_key in PROPERTY_MAP.items(): + row[property_name] = values[json_key][distance_key] + rows.append(row) + return pd.DataFrame(rows) + + +def calculate_stats(df, group_name, group_regex, distance_key): + mask = df["Structure"].str.match(group_regex) + selected = df.loc[mask].copy() + + records = [] + matched_structures = selected["Structure"].tolist() + for property_name in PROPERTY_MAP: + values = selected[property_name].dropna() + n = int(values.count()) + mean = float(values.mean()) if n > 0 else np.nan + std = float(values.std(ddof=1)) if n > 1 else np.nan + sem = float(std / sqrt(n)) if n > 1 else np.nan + + records.append( + { + "group": group_name, + "distance_key": distance_key, + "metric": DISTANCE_MAP[distance_key], + "property": property_name, + "n": n, + "mean": mean, + "std": std, + "sem": sem, + } + ) + + return records, matched_structures + + +def save_markdown_table(df, output_path): + md_df = df.copy() + md_df["mean"] = md_df["mean"].map(lambda x: f"{x:.6f}" if pd.notna(x) else "nan") + md_df["sem"] = md_df["sem"].map(lambda x: f"{x:.6f}" if pd.notna(x) else "nan") + md_df["std"] = md_df["std"].map(lambda x: f"{x:.6f}" if pd.notna(x) else "nan") + md_df["mean_pm_sem"] = md_df.apply( + lambda row: f"{row['mean']} +/- {row['sem']}", axis=1 + ) + md_df = md_df[ + ["group", "metric", "property", "n", "mean_pm_sem", "std", "mean", "sem"] + ] + + headers = list(md_df.columns) + lines = [] + lines.append("| " + " | ".join(headers) + " |") + lines.append("| " + " | ".join(["---"] * len(headers)) + " |") + for _, row in md_df.iterrows(): + cells = [str(row[h]) for h in headers] + lines.append("| " + " | ".join(cells) + " |") + + with open(output_path, "w") as f: + f.write("\n".join(lines) + "\n") + + +def build_condensed_table(stats_df): + rows = [] + for _, row in stats_df.iterrows(): + mean = row["mean"] + sem = row["sem"] + n = int(row["n"]) + if pd.notna(mean) and pd.notna(sem): + value = f"{mean:.6f} +/- {sem:.6f}" + elif pd.notna(mean): + value = f"{mean:.6f}" + else: + value = "nan" + rows.append( + { + "group": row["group"], + "metric": row["metric"], + "property": row["property"], + "n": n, + "mean_pm_sem": value, + } + ) + + condensed = pd.DataFrame(rows) + wide = condensed.pivot_table( + index=["group", "metric"], + columns="property", + values="mean_pm_sem", + aggfunc="first", + ).reset_index() + n_wide = condensed.pivot_table( + index=["group", "metric"], + columns="property", + values="n", + aggfunc="first", + ).reset_index() + + n_columns = [col for col in n_wide.columns if col not in ["group", "metric"]] + for col in n_columns: + wide[f"n_{col}"] = n_wide[col] + + return wide + + +def _category_regex(group_names): + regexes = [] + for name in group_names: + if name in GROUP_PATTERNS: + regexes.append(GROUP_PATTERNS[name]) + elif name in REFERENCE_PATTERN: + regexes.append(REFERENCE_PATTERN[name]) + else: + raise KeyError(f"Unknown group name in category mapping: {name}") + return "(?:" + "|".join(regexes) + ")" + + +def _format_pm(mean, sem): + if pd.notna(mean) and pd.notna(sem): + return f"{mean:.6f} +/- {sem:.6f}" + if pd.notna(mean): + return f"{mean:.6f}" + return "nan" + + +def build_category_tables(similarities, distance_key, score_label): + df = build_distance_dataframe(similarities, distance_key) + mins = df[list(PROPERTY_MAP.keys())].min() + maxs = df[list(PROPERTY_MAP.keys())].max() + + display_map = { + "OO": r"$d_{\mathrm{OO}}$", + "OH": r"$d_{\mathrm{OH}}$", + "HOH": r"$\theta_{\mathrm{HOH}}$", + "ZOH": r"$\theta_{\mathrm{ZOH}}$", + "Hbond": r"$(d_{\mathrm{O_d}\mathrm{O_a}}, \theta_{\mathrm{O_d}\mathrm{H}\mathrm{O_a}})$", + "OrderP": r"$(S_k, S_g)$", + } + + rows_normalized = [] + rows_detailed = [] + for category, groups in CATEGORY_GROUPS.items(): + regex = _category_regex(groups) + subset = df[df["Structure"].str.match(regex)] + row_normalized = { + score_label: category, + "latex category": CATEGORY_LATEX[category], + "number of model replicas": int(subset["Structure"].nunique()), + } + row_detailed = { + score_label: category, + "latex category": CATEGORY_LATEX[category], + "number of model replicas": int(subset["Structure"].nunique()), + } + for prop in PROPERTY_MAP.keys(): + values = subset[prop].dropna() + n = int(values.count()) + mean = float(values.mean()) if n > 0 else np.nan + std = float(values.std(ddof=1)) if n > 1 else np.nan + sem = float(std / sqrt(n)) if n > 1 else np.nan + + denom = float(maxs[prop] - mins[prop]) + norm_mean = 1.0 - ((mean - float(mins[prop])) / denom) if n > 0 and denom != 0 else np.nan + norm_sem = (sem / denom) if pd.notna(sem) and denom != 0 else np.nan + + raw_text = _format_pm(mean, sem) + norm_text = _format_pm(norm_mean, norm_sem) + row_normalized[display_map[prop]] = norm_text + row_detailed[display_map[prop]] = f"({raw_text}), ({norm_text})" + rows_normalized.append(row_normalized) + rows_detailed.append(row_detailed) + + return pd.DataFrame(rows_normalized), pd.DataFrame(rows_detailed) + + +def main(): + args = parse_args() + os.makedirs(args.output_dir, exist_ok=True) + + with open(args.input_json, "r") as f: + similarities = json.load(f) + + group_patterns = dict(GROUP_PATTERNS) + if args.include_reference_pure: + group_patterns.update(REFERENCE_PATTERN) + + all_records = [] + membership = {} + + for distance_key in DISTANCE_MAP: + df = build_distance_dataframe(similarities, distance_key) + for group_name, group_regex in group_patterns.items(): + records, matched_structures = calculate_stats( + df=df, + group_name=group_name, + group_regex=group_regex, + distance_key=distance_key, + ) + all_records.extend(records) + membership.setdefault(group_name, { + "pattern": group_regex, + "matched_structures": matched_structures, + "n_structures": len(matched_structures), + }) + + stats_df = pd.DataFrame(all_records) + stats_df.insert(0, "layer", "Top") + + long_csv = os.path.join(args.output_dir, "radar_stats_top_long.csv") + stats_df.to_csv(long_csv, index=False) + + wide_df = stats_df.pivot_table( + index=["group", "metric"], + columns="property", + values=["mean", "sem", "n"], + aggfunc="first", + ) + wide_df.columns = [f"{stat}_{prop}" for stat, prop in wide_df.columns] + wide_df = wide_df.reset_index() + + wide_csv = os.path.join(args.output_dir, "radar_stats_top_wide.csv") + wide_df.to_csv(wide_csv, index=False) + + markdown_out = os.path.join(args.output_dir, "radar_stats_top_long.md") + save_markdown_table(stats_df, markdown_out) + + condensed_df = build_condensed_table(stats_df) + condensed_csv = os.path.join(args.output_dir, "radar_stats_top_condensed.csv") + condensed_df.to_csv(condensed_csv, index=False) + + category_table_specs = [ + ("wdistancec_nor", "WD score", "wd_category_table_top.csv", "wd_category_table_top_detailed.csv"), + ("edistancec_nor", "ED score", "ed_category_table_top.csv", "ed_category_table_top_detailed.csv"), + ("mdistancec_nor", "MMD score", "mmd_category_table_top.csv", "mmd_category_table_top_detailed.csv"), + ] + saved_category_tables = [] + for distance_key, score_label, normalized_name, detailed_name in category_table_specs: + normalized_df, detailed_df = build_category_tables( + similarities=similarities, + distance_key=distance_key, + score_label=score_label, + ) + normalized_out = os.path.join(args.output_dir, normalized_name) + detailed_out = os.path.join(args.output_dir, detailed_name) + normalized_df.to_csv(normalized_out, index=False) + detailed_df.to_csv(detailed_out, index=False) + saved_category_tables.append(normalized_out) + saved_category_tables.append(detailed_out) + + membership_out = os.path.join(args.output_dir, "group_membership_top.json") + with open(membership_out, "w") as f: + json.dump(membership, f, indent=2) + + print(f"Saved long table: {long_csv}") + print(f"Saved wide table: {wide_csv}") + print(f"Saved markdown table: {markdown_out}") + print(f"Saved condensed table: {condensed_csv}") + for category_table in saved_category_tables: + print(f"Saved category table: {category_table}") + print(f"Saved group membership: {membership_out}") + + +if __name__ == "__main__": + main() diff --git a/src/performanceEvaluation/visualiseEvaluateMeanInRadar.py b/src/performanceEvaluation/visualiseEvaluateMeanInRadar.py index 86147528..62e90d3a 100755 --- a/src/performanceEvaluation/visualiseEvaluateMeanInRadar.py +++ b/src/performanceEvaluation/visualiseEvaluateMeanInRadar.py @@ -78,11 +78,11 @@ std_values = compare_data[numeric_columns].std() / np.sqrt(compare_data[numeric_columns].count()) if 'Only' in comp_key: # Style translation only - legend = rf'$F_{{\tilde{{\mathcal{{V}}}}}}(\mathcal{{V}})$: Style Translated' + legend = rf'$F_{{\widetilde{{\mathcal{{V}}}}}}(\mathcal{{V}})$: Style Translated' else: if comp_key == 'Ref': # Handcrafted - legend = rf'$F_{{\bar{{\mathcal{{V}}}}}}(\mathcal{{V}})$: Handcrafted' + legend = rf'$F_{{\overline{{\mathcal{{V}}}}}}(\mathcal{{V}})$: Handcrafted' else: # Hybrid legend = rf'$F_{{\mathcal{{V}}^{{\dagger}}}}(\mathcal{{V}})$: Hybrid'