Results up to 180

Author: niklases

scripts/ProteinGym_runs/results/dca_esm_and_hybrid_opt_results.csv

@@ -157,3 +157,14 @@ No.,Dataset,N_Variants,N_Max_Muts,Untrained_Performance_DCA,Untrained_Performanc
 167,GFP_AEQVI_Sarkisyan_2016,51714,15,0.6406366653494072,0.1336688728267403,0.6860965519817945,0.6422492276272843,0.6495590297325259,nan,0.6486786880849276,0.6360629034990605,nan,0.7463828216993244,0.7711781697848346,nan,51714,51614,51514,50714,8310
 168,GRB2_HUMAN_Faure_2021,63366,2,0.5258434005381363,0.5367412810228084,0.7216670654700138,0.5839763004949682,0.6852622116666458,0.697364904206813,0.6746840807821936,0.7103753714289707,0.7316071269759475,0.708765178129165,0.7742172713240596,0.7938850307943259,63366,63266,63166,62366,13344
 169,HECD1_HUMAN_Tsuboyama_2023_3DKM,5586,2,0.28623326119763287,0.2150000228393089,0.2406307470397028,0.5991137006846494,0.6520916880669738,0.7123845116845012,0.671240119874008,0.6713008248409833,0.715769538708621,0.6959516975099861,0.7840773924211748,0.7706682813598381,5586,5486,5386,4586,986
+170,X
+171,ISDH_STAAW_Tsuboyama_2023_2LHR,1944,2,0.20133105028259743,0.4099797311289111,0.6170821214186833,0.20801835436717128,0.5463153858513373,0.7901066784963037,0.27927295081872605,0.6608119258589598,0.8602977148353521,0.3815799941028187,0.8616768816914405,0.8570970243337553,1944,1844,1744,944,465
+172,MAFG_MOUSE_Tsuboyama_2023_1K1V,1429,2,0.3772754724604933,0.2867701014285044,0.7883997038650642,0.5667968813528276,0.7212985249027445,0.8518818361413882,0.5870433889556854,0.805020022074178,0.8660043558185719,0.6537497661951548,0.9156898969137485,0.9121471008886789,1429,1329,1229,429,385
+173,MBD11_ARATH_Tsuboyama_2023_6ACV,2116,2,0.7329834422357441,0.27532090639771084,0.7881088186243161,0.7839860922931414,0.792328599906371,0.8356866331913111,0.8077768572836533,0.8161648125358435,0.8760480892176334,0.8367560823060701,0.9079456651452383,0.8812386007566525,2116,2016,1916,1116,547
+174,MYO3_YEAST_Tsuboyama_2023_2BTT,3297,2,0.22736027288974528,0.39038676871890193,0.655911044328377,0.5293937331055336,0.6012770298659345,0.7467316039573004,0.502079452467581,0.6801520002381222,0.7899160469479081,0.5706408172217424,0.8152869780272132,0.7444738342715336,3297,3197,3097,2297,635
+175,NKX31_HUMAN_Tsuboyama_2023_2L9R,2482,2,0.5196042879352247,0.5522653235349196,0.6723568827321114,0.5237224856829698,0.6334523075196178,0.7854217747657275,0.5859761902998967,0.669134199661453,0.8185506698606887,0.626925034108479,0.8429564399261074,0.8636033602875912,2482,2382,2282,1482,544
+176,NUSA_ECOLI_Tsuboyama_2023_1WCL,2028,2,0.6014145743469108,0.39213099588495737,0.829129913783728,0.6686314477896026,0.6983392057013559,0.8570870095474957,0.6853797626050436,0.816717565342857,0.8440539539328691,0.7662356414959274,0.9255284813365755,0.8856793894101138,2028,1928,1828,1028,541
+177,NUSG_MYCTU_Tsuboyama_2023_2MI6,1380,2,0.3185563959299844,0.2650521655606262,0.6835605718997004,0.3404721732075912,0.4558591358775928,0.8713252426606706,0.3235636303747638,0.6424823794937596,0.8674173793039379,0.4194035805811384,0.8575977220627845,0.9002750055493168,1380,1280,1180,380,417
+178,OBSCN_HUMAN_Tsuboyama_2023_1V1C,3197,2,0.7049347544997513,0.5640843767042256,0.8046058299987234,0.7294521912125891,0.7331462357273572,0.8695220703317328,0.7605979822734487,0.8278244858240499,0.8694298657950439,0.7996494573669364,0.9074278259681756,0.9075736567483621,3197,3097,2997,2197,679
+179,ODP2_GEOSE_Tsuboyama_2023_1W4G,1134,2,0.12554037717520414,-0.06007588981415863,0.2347909925259055,0.256965178026339,0.46200581622369263,0.5963034456602403,0.32498630193680217,0.46800164167292563,0.7732094387197265,0.45782583926520193,0.6956350462427737,0.8596541104003791,1134,1034,934,134,371
+180,PABP_YEAST_Melamed_2013,37708,2,0.6282349395615039,0.6187616937806348,0.726758973687955,0.705030508811938,0.7401796671480408,0.7491737079223693,0.7217315324275344,0.7778647633866328,0.7720861996641367,0.7640660118093641,0.8346626364747024,0.8343864537497722,37708,37608,37508,36708,14995

scripts/ProteinGym_runs/run_performance_tests_proteingym_hybrid_dca_llm.py

@@ -562,11 +562,11 @@ def plot_csv_data(csv, plot_name):
             start_i = 0
             already_tested_is = []
 
-    #compute_performances(
-    #    mut_data=combined_mut_data, 
-    #    start_i=start_i, 
-    #    already_tested_is=already_tested_is
-    #)
+    compute_performances(
+        mut_data=combined_mut_data, 
+        start_i=start_i, 
+        already_tested_is=already_tested_is
+    )
 
     with open(out_results_csv, 'r') as fh:
         lines = fh.readlines()