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adding plots

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mozoezomoe 2024-05-10 22:10:09 +02:00
parent 23516b2054
commit 1f02f3c80b
32 changed files with 89 additions and 35 deletions
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scripts/__pycache__/main_retrain.cpython-311.pyc
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scripts/__pycache__/utils.cpython-311.pyc
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12,27.271827597402602,24.9,113.27344877344883,102.0,75.98878138528136,74.0,0.0737763656977943,0.225,0.2681974468184146,0.193548387096774,0.31602654340304914,0.36144578313253,7.696000360750361,6.0,0.1847064463314464,0.173717948717949,0.18351823445828547,0.168367346938776,0.22453513261365157,0.236344537815126,0.18464610480251184,0.241206030150754,0.36078138144841276,0.5,35.5036623015873,34.7,67.67452633477633,70.0,WOMAN,ST,0.05089872067343238,0.0074135090609555,0.038507845808280504,0.0329429855689614,0.2041315555868399,0.319783197831978,0.3465823217646926,0.452887537993921,0.04086231739755383,0.0286075703026175,0.2819806119649606,0.176884029675908,0.2329997758679896,0.13665815825643,0.3429588547815819,0.231334622823985,0.253456981348106,0.192576258728409,0.1647965095582527,0.178844815588031,0.20343005512534784,0.11704834605598,74.76649134199133,71.9
86,28.498510606060606,27.9,130.941170995671,151.0,89.32027308802311,104.0,0.10720908962069671,0.0357142857142857,0.29651907322068616,0.193548387096774,0.38112421982301503,1.0,10.518943722943721,12.0,0.20267039973914971,0.126923076923077,0.20919494967900573,0.270408163265306,0.23680921307917113,0.121848739495798,0.180809442232809,0.0,0.4122495289953101,0.2675,27.915842063492065,26.3,67.79791233766232,86.0,MAN,SU,0.07008326597741757,0.0024711696869851,0.06296272041445924,0.0272651999053702,0.25100921624295586,0.319783197831978,0.3965301267459321,0.225157820902502,0.06439328922188704,0.0230612046317019,0.2974679671710128,0.285001518504057,0.2337376812039215,0.167435696053407,0.39356091601285004,0.514119922630561,0.2628236158773644,0.468945240720323,0.2057288240542416,0.294711203897008,0.2500046337603588,0.158608990670059,89.3390294733045,94.5
65,27.715285606060593,26.6,117.99189754689752,125.0,77.78756096681097,82.0,0.1070339195526695,0.117857142857143,0.2802254806125774,0.17741935483871,0.3630761748291869,0.72289156626506,8.250544733044736,8.0,0.19618404812779805,0.0461538461538462,0.19769888204199426,0.038265306122449,0.22025961179926518,0.112394957983193,0.18642484699833947,0.226130653266332,0.3993587620625902,0.1575,33.096955591630596,35.8,60.347909812409796,68.0,WOMAN,SU,0.057503762818425085,0.0529928610653487,0.042493882733857895,0.0440619824934942,0.24359126984126975,0.317073170731707,0.38013185362425506,0.109188683656769,0.045316038623351054,0.0458304952807239,0.29172889833422827,0.226560805241008,0.23978196327528745,0.0780973885725506,0.360930126772003,0.266537717601547,0.2443618810035569,0.549797868430724,0.18565546382404421,0.532707028531663,0.20667854389037602,0.33587786259542,79.15016327561328,77.9
136,28.91784188311688,31.4,125.01580375180373,125.0,82.51338961038962,82.0,0.1311627396413111,0.142857142857143,0.33815357491970394,0.241935483870968,0.3782638258662358,0.566265060240964,10.605613275613273,14.0,0.1908734129296629,0.0903846153846154,0.2089871501089614,0.122448979591837,0.26605044972534464,0.359243697478992,0.20905964345537217,0.0,0.4142151247970775,0.2978125,27.427843037518056,29.6,62.70592676767679,92.0,MAN,SA,0.09841763718617097,0.042833607907743,0.08724970251110242,0.039981074047788,0.27580104275429457,0.311653116531165,0.4027341301892974,0.273790039747487,0.08938644000226907,0.0406733482533813,0.3168836289517339,0.536162089461582,0.2402893406839141,0.441782839191047,0.43381642998093684,0.735396518375242,0.29660456695903226,0.177875780962881,0.2454875055355223,0.326026443980515,0.2508340380051575,0.438507209499576,88.42199599567098,103.9
1,28.0542908008658,27.9,118.89352669552667,120.0,79.42954689754693,85.0,0.10065080266955269,0.0464285714285714,0.3009155960526929,0.629032258064516,0.3416553530137867,0.602409638554217,8.171947691197692,7.0,0.1855390972453472,0.0634615384615385,0.1938414327311012,0.165816326530612,0.22144989018334596,0.105042016806723,0.19091438251865386,0.0,0.36154985930735933,0.1059375,35.442314213564195,41.0,68.09911652236654,98.0,WOMAN,ST,0.060497250392843496,0.0340472267984624,0.043166906036095146,0.0079843860894251,0.23672041162691548,0.311653116531165,0.3482462271770782,0.0678045358896423,0.04639559030862429,0.0127955629074633,0.2892307368792142,0.1157967807714,0.23331817902029475,0.0796681720007854,0.37119736868547315,0.0882011605415861,0.25178911708569923,0.256155825064315,0.18795385031345366,0.0,0.21899447400210761,0.626802374893978,78.7594479437229,75.0
27,28.633624819624835,29.7,125.12254401154397,111.0,84.33075396825397,77.0,0.11550686842918985,0.0571428571428571,0.33898644858725513,0.129032258064516,0.344094620907874,0.228915662650602,10.39781746031746,10.0,0.17324374190624187,0.0115384615384615,0.19136777578996966,0.0280612244897959,0.2496042398019813,0.0987394957983193,0.20800417128934723,0.120603015075377,0.4167630800189393,0.3684375,27.309780699855697,21.4,63.61248340548344,55.0,MAN,ST,0.08896761349273706,0.0639758374519495,0.07925807414695807,0.0295718003312042,0.2565434689520054,0.151761517615176,0.39289390430575843,0.240589198036007,0.08114216300468367,0.0358567675391651,0.29585339525737153,0.147555208468914,0.22990142198895633,0.0626349892008639,0.38953254666030285,0.499032882011605,0.29254583173574356,0.127894156560088,0.20523437275629353,0.203201113430759,0.22992556089184593,0.325699745547074,88.69147070707074,101.6
53,27.588980122655126,28.0,116.35157070707074,109.0,76.80541486291487,70.0,0.09237265254586688,0.0142857142857143,0.2822265628636596,0.467741935483871,0.35929197308715394,0.120481927710843,8.023979437229437,7.0,0.1883873644873646,0.0897435897435898,0.19977727530406109,0.209183673469388,0.21613821210302311,0.0483193277310924,0.17337324972626486,0.0678391959798995,0.40225922201930026,0.27875,33.744931024531034,37.8,62.74108621933622,79.0,WOMAN,SU,0.06339893680667975,0.0,0.04924375659498087,0.0003548616039744,0.23205173590336162,0.151761517615176,0.3775008804940416,0.202478372691139,0.05190494886169695,0.000389218643573,0.26361592565484276,0.149203870016053,0.21047504382057947,0.0972413116041626,0.343497616396069,0.417408123791103,0.2481056563694381,0.027930907754502,0.17923426894956124,0.121433542101601,0.2067894414274822,0.368956743002545,77.86226911976912,71.8
76,27.753418506493507,25.6,126.08652489177483,133.0,84.025382034632,88.0,0.1359727105236034,0.075,0.3239822708653354,0.451612903225806,0.38126844607868693,0.265060240963855,9.62759018759019,9.0,0.18563506447256448,0.125641025641026,0.2044143309921371,0.102040816326531,0.2552269873858636,0.032563025210084,0.20527962141153094,0.293969849246231,0.42823890771554846,0.5496875,27.362795382395376,25.9,61.54605627705628,59.0,MAN,SU,0.08947323622591333,0.0820977484898407,0.08209950932147522,0.0068015140761769,0.27767224509907423,0.227642276422764,0.40805604594662365,0.425999532382511,0.08356719980283517,0.0203366741266907,0.2982047018595242,0.287084038353074,0.23123725514591642,0.299234243078736,0.4141430126074227,0.0963249516441006,0.25012720474021477,0.205071664829107,0.22216694670635173,0.0,0.2511030109039016,0.281594571670908,83.68287958152955,73.0
117,29.505141017316024,33.6,121.46919877344871,120.0,80.63337085137088,83.0,0.08853982426303852,0.0392857142857143,0.275288734115347,0.0,0.342712677550027,0.204819277108434,8.885298340548339,9.0,0.1675886747511747,0.0487179487179487,0.19072368639014045,0.26530612244898,0.23517504767058328,0.0399159663865546,0.16886411585343747,0.376884422110553,0.3952797743055556,0.6221875,36.203470851370845,43.0,55.13406890331891,61.0,WOMAN,SA,0.0448524912377878,0.0,0.04829011333637841,0.0055594984622663,0.22513038925843795,0.0921409214092141,0.36775784237714304,0.476502221183072,0.047833403117484054,0.0046706237228763,0.30395832758142416,0.263829233372381,0.24670686160927668,0.243716866287061,0.3841662602817341,0.373694390715667,0.24156482489089984,0.332598309445057,0.20364091908246407,0.0,0.22425210391813447,0.0,84.20416565656569,93.6
25,27.147951154401156,25.0,118.43159235209232,117.0,79.2832878787879,75.0,0.1274373260667903,0.0714285714285714,0.3024815610017223,0.387096774193548,0.35605710721674577,0.180722891566265,9.131540764790765,7.0,0.19715915681540686,0.0333333333333333,0.22667399118738404,0.150510204081633,0.22964822482023112,0.186974789915966,0.23918934046132542,0.0,0.4202202932224025,0.355625,27.38655999278499,17.2,65.66359054834057,53.0,MAN,ST,0.06222380221371162,0.0886875343218012,0.0597541569928901,0.0332387035722735,0.2610660603323205,0.195121951219512,0.40570548203906887,0.260462941314005,0.06035335055541584,0.0432519217670526,0.2847275383793996,0.158358280185691,0.22802953281447047,0.11314549381504,0.3772421433176751,0.397292069632495,0.23021210556767333,0.0893054024255788,0.1991890126034177,0.148921363952679,0.23082002810119862,0.108566581849025,81.09617972582971,72.5
1 numVol BMI_pred BMI_test Bpmax_pred Bpmax_test Bpmin_pred Bpmin_test CA.G_pred CA.G_test CA.S_pred CA.S_test CA_pred CA_test CVRI_pred CVRI_test DHPAA.GG_pred DHPAA.GG_test DHPAA.GS_pred DHPAA.GS_test DHPAA.G_pred DHPAA.G_test DHPAA.SS_pred DHPAA.SS_test DHPAA_pred DHPAA_test Fat_pred Fat_test Frec_pred Frec_test Sex Sweetener TFA.G_pred TFA.G_test TFA.S_pred TFA.S_test Total.CA_pred Total.CA_test Total.DHPAA_pred Total.DHPAA_test Total.TFA_pred Total.TFA_test Total.VA_pred Total.VA_test VA.GG_pred VA.GG_test VA.GS_pred VA.GS_test VA.SS_pred VA.SS_test VA.S_pred VA.S_test VA_pred VA_test Weight_pred Weight_test
2 19 27.259431313131298 23.0 117.40495454545453 114.0 77.31301443001443 76.0 0.09069635255617398 0.0714285714285714 0.2687425464320627 0.241935483870968 0.33048892539856406 0.530120481927711 8.109095598845599 6.0 0.1931308943371444 0.007051282051282 0.1878788430956799 0.219387755102041 0.22120383191155246 0.127100840336134 0.19392405570420645 0.158291457286432 0.39660669654130587 0.126875 32.8474931818182 29.2 64.24228499278497 70.0 WOMAN ST 0.06628083147708351 0.261120263591433 0.04861523010445116 0.0173290749940856 0.22111371164216675 0.249322493224932 0.37692643602597997 0.0855740004676175 0.05190876933333389 0.0607181083973922 0.3108484195819222 0.11072063863942 0.2644544492816017 0.082367956018064 0.3516933395854091 0.222050290135397 0.2353538524850542 0.0121278941565601 0.17797849706931132 0.173973556019485 0.21892796222249156 0.210347752332485 76.90381172438669 61.9
3 54 27.166870165945152 28.2 114.00775216450211 114.0 75.76315331890332 82.0 0.0836367359822717 0.0107142857142857 0.2735151166038263 0.274193548387097 0.3423652141031659 0.253012048192771 7.834620851370853 8.0 0.20052186748436757 0.122435897435897 0.190762179926083 0.275510204081633 0.21592165654140444 0.158613445378151 0.18522758090597286 0.14572864321608 0.4014397137671356 0.2784375 33.31554520202021 37.0 62.926591269841246 67.0 WOMAN SU 0.06714920593318449 0.103239978034047 0.05241656826468749 0.0274426307073575 0.21962343430432846 0.146341463414634 0.3815321917191218 0.252045826513912 0.055184006957493856 0.0410625668969544 0.2843511677424538 0.221397891448653 0.24192981710813785 0.231788729628902 0.32834107348701175 0.381044487427466 0.229480909531075 0.0554943035648659 0.16047991358560254 0.0 0.19982484789736696 0.0 75.76926760461761 71.2
4 56 28.404448268398255 30.1 116.90409271284275 125.0 77.61984884559884 85.0 0.0872696531642961 0.0392857142857143 0.27049981380626537 0.193548387096774 0.3471091900067805 0.168674698795181 8.325168109668107 8.0 0.18517968836718843 0.136538461538462 0.18959978428600888 0.0331632653061225 0.22230206438636071 0.0514705882352941 0.17252495975548743 0.253768844221106 0.3982738914817821 0.1484375 36.41349585137088 39.8 60.16928354978356 0.0 WOMAN SU 0.06616176880200765 0.0 0.047939867813625824 0.0301632363378283 0.22336356206274882 0.13550135501355 0.37377077169706346 0.123918634556932 0.05132863418867359 0.0249099931886737 0.27222395641896485 0.146123476072715 0.22234347372635227 0.148439033968192 0.3411195101051969 0.19458413926499 0.24118652039903427 0.0922454979786843 0.17483562084710313 0.0723729993041058 0.20421664543165824 0.0 79.01676818181818 82.0
5 108 27.534900757575752 26.6 116.65768506493505 102.0 78.1257427849928 70.0 0.09003050273139562 0.0678571428571429 0.3150515349345994 0.225806451612903 0.34831146664580404 0.614457831325301 7.910566738816741 6.0 0.1885584644522145 0.0666666666666667 0.1974614714933592 0.183673469387755 0.22498938893739315 0.18172268907563 0.1820270671539516 0.278894472361809 0.3798521834415584 0.128125 34.02786962481962 33.1 66.5766818181818 56.0 WOMAN SA 0.059655805029981294 0.0186710598572213 0.04558038575453408 0.0293943695292169 0.23336905152962042 0.262872628726287 0.36330778551067305 0.128361000701426 0.048225289126828975 0.0276831760241316 0.29629552372488077 0.224651828712742 0.248051017878428 0.149371686628706 0.3170788219302726 0.741972920696325 0.26217171200109457 0.0863653068724733 0.17403293560417776 0.0 0.2372330306579672 0.508905852417303 76.8563952020202 65.6
6 5 27.060256565656555 24.9 113.31228643578645 121.0 76.72052705627705 62.0 0.0819956928983715 0.0821428571428571 0.2826003002373969 0.274193548387097 0.3324180531650411 0.216867469879518 7.477949134199132 5.0 0.1881931008806009 0.104487179487179 0.19275288600288598 0.262755102040816 0.20406920609152757 0.0672268907563025 0.17958559482114755 0.0 0.3814207457386363 0.0634375 34.08787561327562 31.1 70.40289538239539 69.0 WOMAN ST 0.047233140715224754 0.0032948929159802 0.04529645987998543 0.0458362905133665 0.21664822049374868 0.192411924119241 0.3590505564175776 0.0514379237783493 0.04578933962148905 0.0384839933832831 0.2701191398061112 0.100655126035837 0.2252886179790387 0.0595915963086589 0.3107858588649691 0.102514506769826 0.24228170824642706 0.191106210951856 0.16425506242964494 0.279053583855254 0.20451035344355964 0.0 74.80806410533911 70.3
7 41 28.479690981240992 28.2 123.78951479076477 138.0 82.80328679653681 80.0 0.11178889404246549 0.0214285714285714 0.3265207024158637 0.225806451612903 0.34771594168883335 0.0 10.387335137085138 13.0 0.19520318061568054 0.0320512820512821 0.19766895908796414 0.107142857142857 0.2585539291474165 0.107142857142857 0.21659817666978473 0.261306532663317 0.41428748004599564 0.350625 27.96736471861472 26.5 60.647917748917756 74.0 MAN ST 0.0875960571629847 0.0804503020318506 0.08667284986128136 0.0065649396735273 0.2518685646632799 0.0542005420054201 0.4023246140890518 0.2569558101473 0.0869940182731975 0.0198501508222244 0.2961511169002709 0.183825762505966 0.22914164077027316 0.152316905556646 0.4009619392320554 0.174854932301741 0.268828544673914 0.10327085630283 0.2214821009327795 0.203897007654836 0.23333599994859547 0.251060220525869 87.5183505050505 94.4
8 72 28.653897005772006 28.9 126.14300432900427 116.0 84.98726082251082 93.0 0.12114557436611012 0.0321428571428571 0.31758919261741847 0.129032258064516 0.3741161963872808 0.27710843373494 10.498818181818184 8.0 0.20547464109964111 0.0 0.21291458498984003 0.10969387755102 0.2765974848272643 0.369747899159664 0.2022336230213115 0.0 0.43739371020472584 0.45375 28.11971655844156 17.6 59.839006854256866 91.0 MAN SU 0.07918943504631316 0.0019220208676551 0.08406437514231162 0.0424651052756092 0.263917441937767 0.143631436314363 0.4275455257339756 0.359597848959551 0.08336379544903431 0.0354675488955921 0.3178783232497276 0.198620330600026 0.2501582300275481 0.169104653445906 0.41616145860372167 0.347388781431335 0.2621670214509245 0.104373392135244 0.234993562099773 0.0807237299930411 0.2425996111606799 0.169635284139101 87.37903055555553 86.5
9 128 27.693098701298705 26.3 124.71812842712842 107.0 84.47551334776335 77.0 0.12234599438260153 0.128571428571429 0.32312494181445794 0.387096774193548 0.38203823084545957 0.156626506024096 9.470935425685425 8.0 0.17545602684352699 0.733974358974359 0.1921816129590364 0.397959183673469 0.22953228109425583 0.092436974789916 0.18479637001747548 0.0879396984924623 0.4229438381583693 0.5925 26.440846176046165 22.6 67.64444624819625 60.0 MAN SA 0.08716688032359367 0.0 0.06990128438052498 0.0997752543174829 0.2674112358583902 0.233062330623306 0.39173838530601446 0.70119242459668 0.07312342139685966 0.0821737861243554 0.2871145109199253 0.488958306217189 0.22424768563379152 0.369919497349303 0.3915958037127282 0.44100580270793 0.25360555680180824 0.239985299522234 0.1983904862824487 0.778357689631176 0.25977118237996094 0.156912637828668 83.60604199134197 76.8
10 32 29.123759271284275 31.0 132.0701277056277 146.0 88.58315512265513 101.0 0.13425279839208412 0.0464285714285714 0.3216678827444957 0.370967741935484 0.3631262061231943 0.253012048192771 11.130281385281386 13.0 0.23948333980833972 0.0717948717948718 0.20376748166799186 0.0586734693877551 0.29046547065796013 0.0420168067226891 0.17760735858223292 0.0 0.4287875654987374 0.3921875 28.646952020202022 26.1 58.94234523809525 80.0 MAN ST 0.07529005933659973 0.152663371773751 0.07769768042297316 0.09356517624793 0.27196468948094954 0.18970189701897 0.43348536401119964 0.261164367547346 0.0774407458669038 0.104213291816678 0.3100423104344423 0.170766627619419 0.23711695968690852 0.0706361672884351 0.4189108059037459 0.679690522243714 0.2865749632885796 0.0826901874310915 0.2437908157527157 0.103340292275574 0.2281430792843007 0.592875318066158 90.6098095238095 100.5
11 64 28.528021500721508 27.8 122.0076803751803 130.0 80.75978391053394 86.0 0.09522812950937957 0.0464285714285714 0.28146821323837456 0.0967741935483871 0.354657491437612 0.228915662650602 8.412451298701301 7.0 0.18654406126281128 0.0743589743589744 0.18326346187825784 0.0688775510204082 0.23796131748153815 0.141806722689076 0.15864415874466123 0.0 0.3746693362193362 0.46375 35.950727705627685 42.4 57.40877922077922 69.0 WOMAN SU 0.05261235650218354 0.0 0.041441493259848465 0.0 0.23306184473460867 0.138211382113821 0.3581903255474684 0.338788870703764 0.04358309758365708 0.0 0.311323974687342 0.210464662241312 0.258420607012596 0.176614961712154 0.3768257846494791 0.349709864603482 0.2402426298741073 0.148107313487688 0.18922231749345528 0.0706332637439109 0.2186174901811034 0.189991518235793 80.64081064213563 85.2
12 62 27.532571464646463 26.2 116.03012301587303 120.0 77.92345707070709 80.0 0.09517017882910742 0.0714285714285714 0.2860997765675186 0.306451612903226 0.35025897529511985 0.240963855421687 7.955121933621934 4.0 0.19688982036482044 0.0935897435897436 0.2127432147642607 0.278061224489796 0.22876504616998308 0.148109243697479 0.19259135776284012 0.351758793969849 0.38451884774080086 0.4165625 34.22554707792208 31.6 69.94619552669555 80.0 WOMAN SU 0.06431048145216188 0.128775398132894 0.04957750879814398 0.0256091790868228 0.2329275761877385 0.195121951219512 0.37307561663260735 0.361935936404021 0.05234414057448501 0.0440790113846453 0.2977593349340389 0.188207731354939 0.24758871956713352 0.164294129196937 0.3481718392825742 0.234429400386847 0.26061085854608457 0.099595736861448 0.16652546691690734 0.155880306193459 0.22955083948659016 0.124681933842239 77.18486587301591 71.5
13 140 27.937193398268395 27.0 122.03180122655127 118.0 80.46716414141413 82.0 0.11192602298495151 0.0607142857142857 0.2939971372713309 0.354838709677419 0.34760041899198524 0.289156626506024 9.5625386002886 6.0 0.18724868210493217 0.3 0.21495353682598595 0.673469387755102 0.23586068897255874 0.504201680672269 0.20560585213223398 0.241206030150754 0.4006705421401516 0.099375 27.875008946608958 20.3 64.46738347763348 71.0 MAN SA 0.061540285969445746 0.0134541460735859 0.0607418890696481 0.0854625029571801 0.24691820449950513 0.205962059620596 0.3846970629842971 0.30512041150339 0.06103692166034043 0.0728811910090493 0.29610912749279933 0.30582671699423 0.2333390668061785 0.270125662674259 0.37941769337475334 0.392263056092843 0.26463752782192695 0.118706357956634 0.21492628768046307 0.191718858733473 0.23649960192008532 0.117896522476675 84.41657384559886 102.9
14 11 29.109383477633486 30.3 118.82082431457424 100.0 78.11894480519486 65.0 0.08024169758812615 0.0571428571428571 0.27106299748638457 0.258064516129032 0.3245196674142457 0.313253012048193 8.592966089466087 9.0 0.1723224419099418 0.544871794871795 0.18287609513502368 0.0739795918367347 0.2168898517740428 0.226890756302521 0.1534320891977927 0.243718592964824 0.4176980120400431 0.3725 37.26525378787878 45.4 49.859772005772 0.0 WOMAN ST 0.055077559445557804 0.14168039538715 0.044600004894495664 0.0192808138159451 0.21373836800056295 0.192411924119241 0.380075455446276 0.482347439794248 0.04661093050776323 0.0411598715578476 0.28610885143245546 0.347260184823637 0.23345829628789092 0.237041036717063 0.3656560331136734 0.36247582205029 0.2180993399899133 0.799705990444689 0.19920313195078335 0.130828114126653 0.21363264230821483 0.141645462256149 81.48783474025974 82.4
15 109 28.630759920634915 29.3 120.20572041847039 136.0 79.1326305916306 79.0 0.09294212791177077 0.0321428571428571 0.28476608248382446 0.0645161290322581 0.34966449347172224 0.204819277108434 8.548655122655124 8.0 0.18989065471565464 0.0891025641025641 0.19866968519009337 0.326530612244898 0.23663954180156918 0.199579831932773 0.17769743830987555 0.0 0.37757689484126994 0.476875 35.64917983405483 38.9 59.53673953823954 80.0 WOMAN SA 0.05420364407390766 0.0057660626029654 0.03987649962738678 0.0130707357463922 0.2311023553381275 0.116531165311653 0.3644674801726472 0.390460603226561 0.04257058052550413 0.0119684732898706 0.29455938524720265 0.442448696255803 0.23976053381490994 0.366139799725113 0.3608249055908631 0.663829787234043 0.2533532056269102 0.0323410510841602 0.18976070640292977 0.447112038970077 0.22392220031405785 0.111111111111111 81.01107766955269 80.7
16 130 27.519382178932197 24.4 118.96275793650788 130.0 79.36695274170273 90.0 0.11216517985982272 0.0714285714285714 0.3331175813433878 0.161290322580645 0.39887924859611606 0.36144578313253 8.989510822510825 13.0 0.21069430291930286 0.184615384615385 0.20181075974762203 0.229591836734694 0.2651884856215213 0.137605042016807 0.19144391057016677 0.673366834170854 0.45770837448142154 0.43 28.07253351370852 19.5 56.2872950937951 88.0 MAN SA 0.08473613012925205 0.0 0.07894413906119899 0.052578660988881 0.26544130229902574 0.197831978319783 0.4399084156303003 0.428337619826981 0.08012427167180497 0.0433492264279459 0.2983301747290752 0.330860341012625 0.24402765865507622 0.299479677989397 0.35645502133800017 0.186460348162476 0.2535494513041372 0.35023888276369 0.19312241889016415 0.132567849686848 0.22994111415867152 0.161153519932146 81.19962059884563 78.2
17 12 27.271827597402602 24.9 113.27344877344883 102.0 75.98878138528136 74.0 0.0737763656977943 0.225 0.2681974468184146 0.193548387096774 0.31602654340304914 0.36144578313253 7.696000360750361 6.0 0.1847064463314464 0.173717948717949 0.18351823445828547 0.168367346938776 0.22453513261365157 0.236344537815126 0.18464610480251184 0.241206030150754 0.36078138144841276 0.5 35.5036623015873 34.7 67.67452633477633 70.0 WOMAN ST 0.05089872067343238 0.0074135090609555 0.038507845808280504 0.0329429855689614 0.2041315555868399 0.319783197831978 0.3465823217646926 0.452887537993921 0.04086231739755383 0.0286075703026175 0.2819806119649606 0.176884029675908 0.2329997758679896 0.13665815825643 0.3429588547815819 0.231334622823985 0.253456981348106 0.192576258728409 0.1647965095582527 0.178844815588031 0.20343005512534784 0.11704834605598 74.76649134199133 71.9
18 86 28.498510606060606 27.9 130.941170995671 151.0 89.32027308802311 104.0 0.10720908962069671 0.0357142857142857 0.29651907322068616 0.193548387096774 0.38112421982301503 1.0 10.518943722943721 12.0 0.20267039973914971 0.126923076923077 0.20919494967900573 0.270408163265306 0.23680921307917113 0.121848739495798 0.180809442232809 0.0 0.4122495289953101 0.2675 27.915842063492065 26.3 67.79791233766232 86.0 MAN SU 0.07008326597741757 0.0024711696869851 0.06296272041445924 0.0272651999053702 0.25100921624295586 0.319783197831978 0.3965301267459321 0.225157820902502 0.06439328922188704 0.0230612046317019 0.2974679671710128 0.285001518504057 0.2337376812039215 0.167435696053407 0.39356091601285004 0.514119922630561 0.2628236158773644 0.468945240720323 0.2057288240542416 0.294711203897008 0.2500046337603588 0.158608990670059 89.3390294733045 94.5
19 65 27.715285606060593 26.6 117.99189754689752 125.0 77.78756096681097 82.0 0.1070339195526695 0.117857142857143 0.2802254806125774 0.17741935483871 0.3630761748291869 0.72289156626506 8.250544733044736 8.0 0.19618404812779805 0.0461538461538462 0.19769888204199426 0.038265306122449 0.22025961179926518 0.112394957983193 0.18642484699833947 0.226130653266332 0.3993587620625902 0.1575 33.096955591630596 35.8 60.347909812409796 68.0 WOMAN SU 0.057503762818425085 0.0529928610653487 0.042493882733857895 0.0440619824934942 0.24359126984126975 0.317073170731707 0.38013185362425506 0.109188683656769 0.045316038623351054 0.0458304952807239 0.29172889833422827 0.226560805241008 0.23978196327528745 0.0780973885725506 0.360930126772003 0.266537717601547 0.2443618810035569 0.549797868430724 0.18565546382404421 0.532707028531663 0.20667854389037602 0.33587786259542 79.15016327561328 77.9
20 136 28.91784188311688 31.4 125.01580375180373 125.0 82.51338961038962 82.0 0.1311627396413111 0.142857142857143 0.33815357491970394 0.241935483870968 0.3782638258662358 0.566265060240964 10.605613275613273 14.0 0.1908734129296629 0.0903846153846154 0.2089871501089614 0.122448979591837 0.26605044972534464 0.359243697478992 0.20905964345537217 0.0 0.4142151247970775 0.2978125 27.427843037518056 29.6 62.70592676767679 92.0 MAN SA 0.09841763718617097 0.042833607907743 0.08724970251110242 0.039981074047788 0.27580104275429457 0.311653116531165 0.4027341301892974 0.273790039747487 0.08938644000226907 0.0406733482533813 0.3168836289517339 0.536162089461582 0.2402893406839141 0.441782839191047 0.43381642998093684 0.735396518375242 0.29660456695903226 0.177875780962881 0.2454875055355223 0.326026443980515 0.2508340380051575 0.438507209499576 88.42199599567098 103.9
21 1 28.0542908008658 27.9 118.89352669552667 120.0 79.42954689754693 85.0 0.10065080266955269 0.0464285714285714 0.3009155960526929 0.629032258064516 0.3416553530137867 0.602409638554217 8.171947691197692 7.0 0.1855390972453472 0.0634615384615385 0.1938414327311012 0.165816326530612 0.22144989018334596 0.105042016806723 0.19091438251865386 0.0 0.36154985930735933 0.1059375 35.442314213564195 41.0 68.09911652236654 98.0 WOMAN ST 0.060497250392843496 0.0340472267984624 0.043166906036095146 0.0079843860894251 0.23672041162691548 0.311653116531165 0.3482462271770782 0.0678045358896423 0.04639559030862429 0.0127955629074633 0.2892307368792142 0.1157967807714 0.23331817902029475 0.0796681720007854 0.37119736868547315 0.0882011605415861 0.25178911708569923 0.256155825064315 0.18795385031345366 0.0 0.21899447400210761 0.626802374893978 78.7594479437229 75.0
22 27 28.633624819624835 29.7 125.12254401154397 111.0 84.33075396825397 77.0 0.11550686842918985 0.0571428571428571 0.33898644858725513 0.129032258064516 0.344094620907874 0.228915662650602 10.39781746031746 10.0 0.17324374190624187 0.0115384615384615 0.19136777578996966 0.0280612244897959 0.2496042398019813 0.0987394957983193 0.20800417128934723 0.120603015075377 0.4167630800189393 0.3684375 27.309780699855697 21.4 63.61248340548344 55.0 MAN ST 0.08896761349273706 0.0639758374519495 0.07925807414695807 0.0295718003312042 0.2565434689520054 0.151761517615176 0.39289390430575843 0.240589198036007 0.08114216300468367 0.0358567675391651 0.29585339525737153 0.147555208468914 0.22990142198895633 0.0626349892008639 0.38953254666030285 0.499032882011605 0.29254583173574356 0.127894156560088 0.20523437275629353 0.203201113430759 0.22992556089184593 0.325699745547074 88.69147070707074 101.6
23 53 27.588980122655126 28.0 116.35157070707074 109.0 76.80541486291487 70.0 0.09237265254586688 0.0142857142857143 0.2822265628636596 0.467741935483871 0.35929197308715394 0.120481927710843 8.023979437229437 7.0 0.1883873644873646 0.0897435897435898 0.19977727530406109 0.209183673469388 0.21613821210302311 0.0483193277310924 0.17337324972626486 0.0678391959798995 0.40225922201930026 0.27875 33.744931024531034 37.8 62.74108621933622 79.0 WOMAN SU 0.06339893680667975 0.0 0.04924375659498087 0.0003548616039744 0.23205173590336162 0.151761517615176 0.3775008804940416 0.202478372691139 0.05190494886169695 0.000389218643573 0.26361592565484276 0.149203870016053 0.21047504382057947 0.0972413116041626 0.343497616396069 0.417408123791103 0.2481056563694381 0.027930907754502 0.17923426894956124 0.121433542101601 0.2067894414274822 0.368956743002545 77.86226911976912 71.8
24 76 27.753418506493507 25.6 126.08652489177483 133.0 84.025382034632 88.0 0.1359727105236034 0.075 0.3239822708653354 0.451612903225806 0.38126844607868693 0.265060240963855 9.62759018759019 9.0 0.18563506447256448 0.125641025641026 0.2044143309921371 0.102040816326531 0.2552269873858636 0.032563025210084 0.20527962141153094 0.293969849246231 0.42823890771554846 0.5496875 27.362795382395376 25.9 61.54605627705628 59.0 MAN SU 0.08947323622591333 0.0820977484898407 0.08209950932147522 0.0068015140761769 0.27767224509907423 0.227642276422764 0.40805604594662365 0.425999532382511 0.08356719980283517 0.0203366741266907 0.2982047018595242 0.287084038353074 0.23123725514591642 0.299234243078736 0.4141430126074227 0.0963249516441006 0.25012720474021477 0.205071664829107 0.22216694670635173 0.0 0.2511030109039016 0.281594571670908 83.68287958152955 73.0
25 117 29.505141017316024 33.6 121.46919877344871 120.0 80.63337085137088 83.0 0.08853982426303852 0.0392857142857143 0.275288734115347 0.0 0.342712677550027 0.204819277108434 8.885298340548339 9.0 0.1675886747511747 0.0487179487179487 0.19072368639014045 0.26530612244898 0.23517504767058328 0.0399159663865546 0.16886411585343747 0.376884422110553 0.3952797743055556 0.6221875 36.203470851370845 43.0 55.13406890331891 61.0 WOMAN SA 0.0448524912377878 0.0 0.04829011333637841 0.0055594984622663 0.22513038925843795 0.0921409214092141 0.36775784237714304 0.476502221183072 0.047833403117484054 0.0046706237228763 0.30395832758142416 0.263829233372381 0.24670686160927668 0.243716866287061 0.3841662602817341 0.373694390715667 0.24156482489089984 0.332598309445057 0.20364091908246407 0.0 0.22425210391813447 0.0 84.20416565656569 93.6
26 25 27.147951154401156 25.0 118.43159235209232 117.0 79.2832878787879 75.0 0.1274373260667903 0.0714285714285714 0.3024815610017223 0.387096774193548 0.35605710721674577 0.180722891566265 9.131540764790765 7.0 0.19715915681540686 0.0333333333333333 0.22667399118738404 0.150510204081633 0.22964822482023112 0.186974789915966 0.23918934046132542 0.0 0.4202202932224025 0.355625 27.38655999278499 17.2 65.66359054834057 53.0 MAN ST 0.06222380221371162 0.0886875343218012 0.0597541569928901 0.0332387035722735 0.2610660603323205 0.195121951219512 0.40570548203906887 0.260462941314005 0.06035335055541584 0.0432519217670526 0.2847275383793996 0.158358280185691 0.22802953281447047 0.11314549381504 0.3772421433176751 0.397292069632495 0.23021210556767333 0.0893054024255788 0.1991890126034177 0.148921363952679 0.23082002810119862 0.108566581849025 81.09617972582971 72.5

55
scripts/main_retrain.py
View file

@ -15,6 +15,7 @@ from sklearn.ensemble import RandomForestRegressor
sns.set_theme()
def evaluateNPlot(modelPath, df, df_name, y_test ='' , X_test='', full = True, pipeline = True, plot = True):
# extract model name
@ -51,26 +52,26 @@ def evaluateNPlot(modelPath, df, df_name, y_test ='' , X_test='', full = True,
#X_test.to_csv("X_test_"+modelname+".csv")
scores = []
for n in y_test.columns:
scores = pd.Series()
metabs = pd.Series(y_test.columns)
for n in metabs:
print(" ----------------- " + n + " MODEL EVALUATION ----------------- ")
n_scores = cross_val_score(model, X_test, y_test[n], scoring='neg_mean_absolute_error', cv=cv, n_jobs=-1)
n_scores = np.absolute(n_scores)
scores.append(n_scores)
print('Full model ' + modelname + ' for metabolite '+n+ ' MAE: %.3f (%.3f)' % (np.mean(n_scores), np.std(n_scores)))
scores._append(pd.Series(n_scores))
print('Full model ' + df_name + ' for metabolite '+n+ ' MAE: %.3f (%.3f)' % (np.mean(n_scores), np.std(n_scores)))
# full model evaluation
print(" ----------------- MEAN PERFORMANCE EVALUATION ----------------- ")
n_scores = cross_val_score(model, X_test, y_test, scoring='neg_mean_absolute_error', cv=cv, n_jobs=-1)
n_scores = np.absolute(n_scores)
scores.append = n_scores
metabs = y_test.columns.append("Mean Performance")
scores._append(pd.Series(n_scores))
metabs._append(pd.Series(["Mean Performance"]))
df_scores = pd.concat([metabs, scores])
df_scores.columns = ["Metabolite modeled", "MAE score"]
df_scores.to_csv("scores_" + modelname +".csv", sep = ",")
df_scores.to_csv("scores_" + df_name +".csv", sep = ",")
print("Mean performance of all model" + modelname + " MAE: %.3f (%.3f)" % (np.mean(n_scores), np.std(n_scores)))
@ -93,13 +94,14 @@ def evaluateNPlot(modelPath, df, df_name, y_test ='' , X_test='', full = True,
df_predTest = pd.DataFrame([i for i in y_pred], index = y_test.index, columns= y_test.columns).add_suffix("_pred").join(y_test.add_suffix('_test')).fillna(0)
df_predTest["Sex"] = dummies_sex
df_predTest["Sweetener"] = dummies_sweetener
df_predTest.reindex(sorted(df_predTest.columns), axis=1).to_csv("df_pred-test_"+modelname+".csv", sep = ",")
df_predTest.reindex(sorted(df_predTest.columns), axis=1).to_csv("df_pred-test_"+df_name+".csv", sep = ",")
# print plots
metabs = y_test.columns.drop(list(y_test.filter(regex='Sex|Sweetener')))
print(" ----------------- STARTING PLOTTING ----------------- ")
for metab in metabs:
#sns.regplot(data = pred_prueba_DF, x=metab+"_pred", y=metab+"_test", )
@ -117,25 +119,24 @@ def evaluateNPlot(modelPath, df, df_name, y_test ='' , X_test='', full = True,
sns.lmplot(data = df_predTest, x=metab+"_pred", y=metab+"_test")
plt.title("TEST VS PREDICTED lmplot " + metab + " " + modelname)
plt.savefig("testVsPredicted_lmplot_"+ metab+"_"+modelname+".png")
plt.savefig("testVsPredicted_lmplot_"+ metab+"_"+df_name+".png")
plt.close()
print(" ----------------- PREDICTED VS RESIDUALS " + metab + " ----------------- ")
plt.figure()
y_pred_metab = y_pred[metab]
residuals = y_test[metab]-y_pred[metab]
df_all = pd.concat([y_pred_metab, residuals], axis=1)
df_all.columns = ["Predicted", "Residuals"]
sns.scatterplot(data = df_all, x="Predicted", y="Residuals")
plt.title("RESIDUALS VS PREDICTED " + metab + " " + modelname)
plt.savefig("residualsVsPredicted_"+ metab+"_"+modelname+".png")
plt.axhline(y=0)
plt.close()
'''
if (residPlot):
print(" ----------------- PREDICTED VS RESIDUALS " + metab + " ----------------- ")
plt.figure()
y_pred_metab = y_pred[metab]
residuals = y_test[metab]-y_pred[metab]
df_all = pd.concat([y_pred_metab, residuals], axis=1)
df_all.columns = ["Predicted", "Residuals"]
sns.scatterplot(data = df_all, x="Predicted", y="Residuals")
plt.title("RESIDUALS VS PREDICTED " + metab + " " + modelname)
plt.savefig("residualsVsPredicted_"+ metab+"_"+df_name+".png")
plt.axhline(y=0)
plt.close()
'''
def RF_Fit(df, df_name, full = True, eval = True, plot = True):

16
scripts/modelSanoApp.py
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@ -18,19 +18,19 @@ paths = ["../data/" + s for s in paths]
# execution
test = False
exec = False
test = True
execution = False
if (test):
df, df_name = fullRead(paths[0], sep = ",", full = True)
df, df_name = fullRead(paths[1], sep = ",", full = True)
df_name = re.sub("../", "", df_name)
df[['Weight', 'BMI']] = df[['Weight', 'BMI']].apply(pd.to_numeric)
y_metTest = pd.read_csv("/home/die/Documents/repositories/mSApp/doc/scripts/X_metTest_RF_Met_lightTrainplasmFlav.csv")
X_metTest = pd.read_csv("/home/die/Documents/repositories/mSApp/doc/scripts/y_metTest_RF_Met_lightTrainplasmFlav.csv")
evaluateNPlot(modelPath = "RF_Met_lightTrainplasmFlav.pkl", df = df, df_name = df_name, y_metTest =y_metTest, X_metTest=X_metTest, pipeline = False)
#y_test = pd.read_csv("/home/die/Documents/repositories/mSApp/doc/scripts/X_metTest_RF_Met_lightTrainplasmFlav.csv")
#X_test = pd.read_csv("/home/die/Documents/repositories/mSApp/doc/scripts/y_metTest_RF_Met_lightTrainplasmFlav.csv")
residPlot = False
evaluateNPlot(modelPath = "../models/RF_Full_lightTrainplasmAnt.pkl", df = df, df_name = df_name, pipeline = False)
elif (exec):
elif (execution):
for path in paths:
df, df_name = fullRead(path, sep = ",", full = True)
df_name = re.sub("../", "", df_name)

27
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@ -0,0 +1,27 @@
,0
0,CA
1,CA.G
2,CA.S
3,Total.CA
4,DHPAA
5,DHPAA.G
6,DHPAA.GG
7,DHPAA.GS
8,DHPAA.SS
9,Total.DHPAA
10,TFA.G
11,TFA.S
12,Total.TFA
13,VA
14,VA.GG
15,VA.S
16,VA.GS
17,VA.SS
18,Total.VA
19,Weight
20,BMI
21,Fat
22,CVRI
23,Bpmin
24,Bpmax
25,Frec
1 0
2 0 CA
3 1 CA.G
4 2 CA.S
5 3 Total.CA
6 4 DHPAA
7 5 DHPAA.G
8 6 DHPAA.GG
9 7 DHPAA.GS
10 8 DHPAA.SS
11 9 Total.DHPAA
12 10 TFA.G
13 11 TFA.S
14 12 Total.TFA
15 13 VA
16 14 VA.GG
17 15 VA.S
18 16 VA.GS
19 17 VA.SS
20 18 Total.VA
21 19 Weight
22 20 BMI
23 21 Fat
24 22 CVRI
25 23 Bpmin
26 24 Bpmax
27 25 Frec

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