run_impute.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import scanpy as sc\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import multiprocessing\n",
    "from tool import train_impute\n",
    "from tool.data import mapping_adj2pyg,impute_preprocessing,mapping_adj2matrix,adata_to_cluster_expression\n",
    "from tool.calculate_adj import impute_cal_adj,impute_another_cal_adj\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AnnData object with n_obs × n_vars = 14249 × 34041\n",
      "    obs: 'celltype'\n"
     ]
    }
   ],
   "source": [
    "DataDir=\"data/DataUpload/Dataset2/\"\n",
    "Spatial_file = DataDir + 'Insitu_count.txt'\n",
    "location_file = DataDir + 'Locations.txt'\n",
    "\n",
    "RNA_data_adata = sc.read_h5ad(DataDir+'starmap_sc_rna.h5ad')\n",
    "Spatial_data_adata = sc.read(Spatial_file, sep = '\\t')\n",
    "spatial_loc = pd.read_csv(location_file,sep='\\t')\n",
    "train_gene = np.load(DataDir + 'train_list.npy', allow_pickle = True).tolist()\n",
    "predict_gene = np.load(DataDir + 'test_list.npy', allow_pickle = True).tolist()\n",
    "Spatial_data_adata.obs=spatial_loc\n",
    "\n",
    "RNA_ret_adata=RNA_data_adata.copy()\n",
    "sc.pp.normalize_total(RNA_ret_adata)\n",
    "RNA_ret_adata=adata_to_cluster_expression(RNA_ret_adata)\n",
    "print(RNA_data_adata)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data exists, load it\n",
      "load adj dataframe\n"
     ]
    }
   ],
   "source": [
    "adj_df=impute_another_cal_adj(RNA_ret_adata,Spatial_data_adata,DataDir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "View of AnnData object with n_obs × n_vars = 2376 × 225\n",
      "    obs: 'x', 'y'\n",
      "AnnData object with n_obs × n_vars = 15 × 26\n",
      "    obs: 'celltype', 'cluster_density'\n",
      "(2376, 26)\n"
     ]
    }
   ],
   "source": [
    "test_list = np.unique(predict_gene[0])\n",
    "train_list = np.unique(train_gene[0])\n",
    "spatial_data_partial = Spatial_data_adata[:, train_list]\n",
    "gd_results=Spatial_data_adata[:, test_list].copy()\n",
    "RNA_data_test=RNA_ret_adata[:, test_list].copy()\n",
    "print(spatial_data_partial)\n",
    "print(RNA_data_test)\n",
    "print(gd_results.X.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "concat_st_sc=impute_preprocessing(RNA_data_adata,spatial_data_partial)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "View of AnnData object with n_obs × n_vars = 539 × 900\n",
      "    obs: 'celltype', 'cluster_density', 'X', 'Y', 'n_genes', 'rna_count_based_density', 'batch'\n",
      "    var: 'n_cells-0', 'n_cells-1'\n"
     ]
    }
   ],
   "source": [
    "print(concat_st_sc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 000: Loss 2.2458858489990234\n",
      "(-0.01850981645313526, 0.01016352066061731, 0.5971334723085404)\n",
      "max_pcc:0\n",
      "Epoch 010: Loss 1.8140517473220825\n",
      "(0.2934524973592634, 0.22749764802715397, 0.4162823818043456)\n",
      "max_pcc:0.30496783337585176\n",
      "Epoch 020: Loss 1.770567536354065\n",
      "(0.30667689572920454, 0.23680187130736224, 0.43768850187452757)\n",
      "max_pcc:0.3134788655250351\n",
      "Epoch 030: Loss 1.7223010063171387\n",
      "(0.3437718307465477, 0.27294801297156335, 0.4090330214919088)\n",
      "max_pcc:0.3437718307465477\n",
      "Epoch 040: Loss 1.7137024402618408\n",
      "(0.3451442815242102, 0.26726277127578607, 0.4066333068349733)\n",
      "max_pcc:0.3451442815242102\n",
      "Epoch 050: Loss 1.710174798965454\n",
      "(0.34743835895641817, 0.25850084353304914, 0.4053546117641881)\n",
      "max_pcc:0.34842667331036326\n",
      "Epoch 060: Loss 1.7109708786010742\n",
      "(0.34831099207190724, 0.25021023526407676, 0.4046270897827381)\n",
      "max_pcc:0.3535894612565005\n",
      "Epoch 070: Loss 1.7035236358642578\n",
      "(0.3661048996745398, 0.27215274496453107, 0.3999484978170757)\n",
      "max_pcc:0.3661048996745398\n",
      "Epoch 080: Loss 1.696592092514038\n",
      "(0.3929094795497336, 0.30264097443133453, 0.3949973352074407)\n",
      "max_pcc:0.3929094795497336\n",
      "Epoch 090: Loss 1.8539185523986816\n",
      "(0.12208004649969656, 0.09912464953844223, 0.46453800232686243)\n",
      "max_pcc:0.4101176540320159\n",
      "Epoch 100: Loss 1.7178313732147217\n",
      "(0.32812070085913253, 0.2554588770595706, 0.40554517247159416)\n",
      "max_pcc:0.4101176540320159\n",
      "Epoch 110: Loss 1.7208043336868286\n",
      "(0.3293534027169773, 0.24374276435853684, 0.41010125342270215)\n",
      "max_pcc:0.4101176540320159\n",
      "Epoch 120: Loss 1.7118210792541504\n",
      "(0.34001973817566056, 0.2583349612876638, 0.40303250284704456)\n",
      "max_pcc:0.4101176540320159\n",
      "Epoch 130: Loss 1.7106666564941406\n",
      "(0.3434735310399508, 0.26777086516793647, 0.40096991618171285)\n",
      "max_pcc:0.4101176540320159\n",
      "Epoch 140: Loss 1.696159839630127\n",
      "(0.3821617959451874, 0.3077881175245145, 0.39081529933687414)\n",
      "max_pcc:0.4101176540320159\n",
      "Epoch 150: Loss 1.7312898635864258\n",
      "(0.3207154515119622, 0.2457760170851007, 0.40723200923037695)\n",
      "max_pcc:0.4101176540320159\n",
      "Epoch 160: Loss 1.7118620872497559\n",
      "(0.3448464445932924, 0.25753044846843154, 0.3977085767760407)\n",
      "max_pcc:0.4101176540320159\n",
      "Epoch 170: Loss 1.7042078971862793\n",
      "(0.3613850294817705, 0.2552964855283363, 0.3936686706722564)\n",
      "max_pcc:0.4101176540320159\n",
      "Epoch 180: Loss 1.6963586807250977\n",
      "(0.3916407134575018, 0.2927104042278682, 0.39122779399781643)\n",
      "max_pcc:0.4101176540320159\n",
      "Epoch 190: Loss 1.6891579627990723\n",
      "(0.43203915771880913, 0.38110454352706524, 0.39434095231425803)\n",
      "max_pcc:0.4409445327348912\n",
      "Epoch 200: Loss 1.7031962871551514\n",
      "(0.36552948661826806, 0.27237117462013777, 0.39362014213613716)\n",
      "max_pcc:0.4409445327348912\n",
      "Epoch 210: Loss 1.6889140605926514\n",
      "(0.4116130633355549, 0.3260333717919589, 0.39151195950461165)\n",
      "max_pcc:0.4409445327348912\n",
      "Epoch 220: Loss 1.6754398345947266\n",
      "(0.4485647383315377, 0.3434405679129824, 0.3859654243220023)\n",
      "max_pcc:0.449374217381906\n",
      "Epoch 230: Loss 1.6892881393432617\n",
      "(0.40285845783756424, 0.28969930025525037, 0.38935481317277726)\n",
      "max_pcc:0.449374217381906\n",
      "Epoch 240: Loss 1.6811565160751343\n",
      "(0.43568975912473207, 0.32219939676070053, 0.3890952840911506)\n",
      "max_pcc:0.449374217381906\n",
      "Epoch 250: Loss 1.6733253002166748\n",
      "(0.4639700660232219, 0.38020776167129205, 0.3854389388467848)\n",
      "max_pcc:0.4639700660232219\n",
      "Epoch 260: Loss 1.6685237884521484\n",
      "(0.4604775709995947, 0.37232944554520747, 0.3802226633432405)\n",
      "max_pcc:0.4639700660232219\n",
      "Epoch 270: Loss 1.6862813234329224\n",
      "(0.4059745797110665, 0.2942363849858166, 0.38387736827908375)\n",
      "max_pcc:0.4639700660232219\n",
      "Epoch 280: Loss 1.687497854232788\n",
      "(0.4286634703507605, 0.3856195219652775, 0.3942209433323769)\n",
      "max_pcc:0.4639700660232219\n",
      "Epoch 290: Loss 1.697190523147583\n",
      "(0.3756356462600731, 0.27925263861381056, 0.3911018590081115)\n",
      "max_pcc:0.4639700660232219\n",
      "Epoch 300: Loss 1.6785590648651123\n",
      "(0.4339100866402368, 0.36597394092408364, 0.38515205060227187)\n",
      "max_pcc:0.4639700660232219\n",
      "Epoch 310: Loss 1.6805927753448486\n",
      "(0.4241536173896807, 0.3176062567346787, 0.3839769927705715)\n",
      "max_pcc:0.4639700660232219\n",
      "Epoch 320: Loss 1.6755366325378418\n",
      "(0.43324492668315834, 0.31980470256256016, 0.3818644382230852)\n",
      "max_pcc:0.4639700660232219\n",
      "Epoch 330: Loss 1.680108904838562\n",
      "(0.44408204872354096, 0.40790705357944673, 0.38644642554303876)\n",
      "max_pcc:0.4639700660232219\n",
      "Epoch 340: Loss 1.6749088764190674\n",
      "(0.428666560243115, 0.3173546459889073, 0.38037106653830266)\n",
      "max_pcc:0.4639700660232219\n"
     ]
    }
   ],
   "source": [
    "adj_matrix=mapping_adj2pyg(adj_df,concat_st_sc)\n",
    "ad_map=train_impute.start(concat_st_sc,adj_matrix,RNA_data_test,gd_results,GCN_method=\"pygGCN\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 000: Loss 0.3258594274520874\n",
      "(0.019853500271007317, 0.05230147355851713, 0.6796400743905551)\n",
      "max_pcc:0.019853500271007317\n",
      "Epoch 010: Loss 0.2313256859779358\n",
      "(0.22006708419756316, 0.20717973714785548, 0.6177730803011189)\n",
      "max_pcc:0.22006708419756316\n",
      "Epoch 020: Loss 0.22322505712509155\n",
      "(0.22918632930851984, 0.22556398314980833, 0.6151711501575142)\n",
      "max_pcc:0.22918632930851984\n",
      "Epoch 030: Loss 0.2165069580078125\n",
      "(0.2331012795682356, 0.2217236681694401, 0.6199093082878869)\n",
      "max_pcc:0.23651977031614643\n"
     ]
    }
   ],
   "source": [
    "adj_matrix=mapping_adj2matrix(adj_df,concat_st_sc)\n",
    "ad_map=train_impute.start(concat_st_sc,adj_matrix,RNA_data_test,gd_results,GCN_method=\"coGCN\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# multiprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data exists, load it\n",
      "load adj dataframe\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "import scanpy as sc\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from functools import partial\n",
    "import random\n",
    "import multiprocessing\n",
    "from tool import train_impute\n",
    "from tool.data import mapping_adj2pyg,impute_preprocessing,mapping_adj2matrix,adata_to_cluster_expression\n",
    "from tool.calculate_adj import impute_cal_adj,impute_another_cal_adj\n",
    "from tool.impute_metric import CalDataMetric\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "DataDir=\"data/DataUpload/Dataset2(9)/\"\n",
    "Spatial_file = DataDir + 'Insitu_count.txt'\n",
    "location_file = DataDir + 'Locations.txt'\n",
    "\n",
    "RNA_data_adata = sc.read_h5ad(DataDir+'starmap_sc_rna.h5ad')\n",
    "Spatial_data_adata = sc.read(Spatial_file, sep = '\\t')\n",
    "spatial_loc = pd.read_csv(location_file,sep='\\t')\n",
    "train_gene = np.load(DataDir + 'train_list.npy', allow_pickle = True).tolist()\n",
    "predict_gene = np.load(DataDir + 'test_list.npy', allow_pickle = True).tolist()\n",
    "Spatial_data_adata.obs=spatial_loc\n",
    "\n",
    "RNA_ret_adata=RNA_data_adata.copy()\n",
    "sc.pp.normalize_total(RNA_ret_adata)\n",
    "RNA_ret_adata=adata_to_cluster_expression(RNA_ret_adata)\n",
    "\n",
    "adj_df=impute_another_cal_adj(RNA_ret_adata,Spatial_data_adata,DataDir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def coGCN_impute(seed,K):\n",
    "    global RNA_data_adata, Spatial_data_adata, train_gene, predict_gene,RNA_ret_adata,adj_df\n",
    "    test_list = np.unique(predict_gene[K])\n",
    "    train_list = np.unique(train_gene[K])\n",
    "    spatial_data_partial = Spatial_data_adata[:, train_list]\n",
    "    gd_results=Spatial_data_adata[:, test_list].copy()\n",
    "    RNA_data_test=RNA_ret_adata[:, test_list].copy()\n",
    "    concat_st_sc=impute_preprocessing(RNA_data_adata,spatial_data_partial)\n",
    "\n",
    "    adj_matrix=mapping_adj2pyg(adj_df,concat_st_sc)\n",
    "    ad_map=train_impute.start(concat_st_sc,adj_matrix,RNA_data_test,gd_results,GCN_method=\"pygGCN\",seed=seed)\n",
    "\n",
    "    X_space = ad_map.X @ RNA_ret_adata.X\n",
    "    adata_ge = sc.AnnData(X=X_space, obs=ad_map.obs, var=RNA_ret_adata.var)\n",
    "    test_list = list(set(adata_ge.var_names) & set(test_list))\n",
    "    test_list = np.array(test_list)\n",
    "    pre_gene = pd.DataFrame(adata_ge[:,test_list].X, index=adata_ge[:,test_list].obs_names, columns=adata_ge[:,test_list].var_names)\n",
    "    return pre_gene"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 000: Loss 1.8012272119522095\n",
      "(0.0577642591013786, 0.08788042852436045, 0.7188081679567389)\n",
      "max_pcc:0.0577642591013786\n",
      "Epoch 000: Loss 1.8172457218170166\n",
      "(0.04615174475441803, 0.095103372562278, 0.7182789996130128)\n",
      "max_pcc:0.04615174475441803\n",
      "Epoch 000: Loss 1.8200151920318604\n",
      "(0.04464778360349975, 0.09559331968380555, 0.7349550051466736)\n",
      "max_pcc:0.04464778360349975\n",
      "Epoch 000: Loss 1.7758255004882812\n",
      "(0.07112142825609871, 0.10255829953643522, 0.7150187631233795)\n",
      "max_pcc:0.07112142825609871\n",
      "Epoch 000: Loss 1.8255367279052734\n",
      "(0.057070395668373075, 0.09199542846523415, 0.7364742465989431)\n",
      "max_pcc:0.057070395668373075\n",
      "Epoch 010: Loss 1.6055625677108765\n",
      "(0.10838406004318717, 0.11850870033687405, 0.6619669541141612)\n",
      "max_pcc:0.11502222700412171\n",
      "Epoch 010: Loss 1.6148114204406738\n",
      "(0.1500889318353002, 0.152035539874945, 0.6524447609002326)\n",
      "max_pcc:0.15108988367293158\n",
      "Epoch 010: Loss 1.6247773170471191\n",
      "(0.090659028731778, 0.09975838247933266, 0.6953006705861385)\n",
      "max_pcc:0.090659028731778\n",
      "Epoch 010: Loss 1.7514533996582031\n",
      "(0.05528792204271792, 0.08036717575006516, 0.7018552218480071)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 010: Loss 1.5969401597976685\n",
      "(0.10169204001519919, 0.10113426948623402, 0.6750470304056709)\n",
      "max_pcc:0.11860684012649429\n",
      "Epoch 020: Loss 1.5735112428665161\n",
      "(0.12017669099987899, 0.1275485652994528, 0.6577462233627209)\n",
      "max_pcc:0.1392206113126249\n",
      "Epoch 020: Loss 1.572811245918274\n",
      "(0.15616668116643315, 0.14975848932674182, 0.6450002543470135)\n",
      "max_pcc:0.15895184322691364\n",
      "Epoch 020: Loss 1.6080865859985352\n",
      "(0.09940776427470294, 0.10203699380093469, 0.6907176568781062)\n",
      "max_pcc:0.09940776427470294\n",
      "Epoch 020: Loss 1.7408080101013184\n",
      "(0.06064093119469263, 0.08567283342847543, 0.6991954615925596)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 020: Loss 1.5700535774230957\n",
      "(0.11580383601888108, 0.1028498660971276, 0.6698367545843218)\n",
      "max_pcc:0.1194369027514237\n",
      "Epoch 030: Loss 1.5647192001342773\n",
      "(0.11682977251762587, 0.11311123513913544, 0.6575422753784396)\n",
      "max_pcc:0.1392206113126249\n",
      "Epoch 030: Loss 1.5592942237854004\n",
      "(0.16140565855033373, 0.15217328054344118, 0.6413849202730664)\n",
      "max_pcc:0.1621455960384423\n",
      "Epoch 030: Loss 1.5899345874786377\n",
      "(0.1070225910153186, 0.10482512983217994, 0.6880415058925)\n",
      "max_pcc:0.1070225910153186\n",
      "Epoch 030: Loss 1.703381061553955\n",
      "(0.08164174562059832, 0.09143342107096078, 0.6928161903322868)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 030: Loss 1.5563198328018188\n",
      "(0.12108949698744566, 0.10950785078299223, 0.6673398025253208)\n",
      "max_pcc:0.1234953746995515\n",
      "Epoch 040: Loss 1.5456501245498657\n",
      "(0.12580271572299828, 0.11493286611626587, 0.653192108732241)\n",
      "max_pcc:0.1392206113126249\n",
      "Epoch 040: Loss 1.554417610168457\n",
      "(0.1551754094643845, 0.14381773723881097, 0.6405829504753062)\n",
      "max_pcc:0.16316221540693177\n",
      "Epoch 040: Loss 1.5669490098953247\n",
      "(0.11349051001305029, 0.11912078647330775, 0.6845379128167421)\n",
      "max_pcc:0.11349051001305029\n",
      "Epoch 040: Loss 1.692425012588501\n",
      "(0.08220725456603234, 0.08599199326757949, 0.6907112938501794)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 040: Loss 1.5318310260772705\n",
      "(0.13782191579754655, 0.12730468591825322, 0.6627804387161546)\n",
      "max_pcc:0.13782191579754655\n",
      "Epoch 050: Loss 1.5284265279769897\n",
      "(0.13360081290036374, 0.12661596216163915, 0.647653851805838)\n",
      "max_pcc:0.1392206113126249\n",
      "Epoch 050: Loss 1.5308892726898193\n",
      "(0.16446183405406914, 0.14275006936567924, 0.6354555662130443)\n",
      "max_pcc:0.16446183405406914\n",
      "Epoch 050: Loss 1.594120979309082\n",
      "(0.10781605905185002, 0.10739327591914147, 0.6834945090290931)\n",
      "max_pcc:0.11903547171974319\n",
      "Epoch 050: Loss 1.6904889345169067\n",
      "(0.08756214004927482, 0.09354489490824552, 0.6888981926229344)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 050: Loss 1.5069644451141357\n",
      "(0.1464426924007537, 0.11866499348751751, 0.6571064861012731)\n",
      "max_pcc:0.1464426924007537\n",
      "Epoch 060: Loss 1.4781519174575806\n",
      "(0.15136816707172984, 0.13532062364445568, 0.6420319431448717)\n",
      "max_pcc:0.15338411879148792\n",
      "Epoch 060: Loss 1.5184236764907837\n",
      "(0.17419052614520605, 0.14756689078037713, 0.6315317791825126)\n",
      "max_pcc:0.17419052614520605\n",
      "Epoch 060: Loss 1.567828893661499\n",
      "(0.12292216947325811, 0.10451383228318382, 0.6771874388293415)\n",
      "max_pcc:0.12292216947325811\n",
      "Epoch 060: Loss 1.6815953254699707\n",
      "(0.08741297364580948, 0.09742939447319192, 0.6877946248402634)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 060: Loss 1.5147887468338013\n",
      "(0.1347223007146985, 0.1263531276950946, 0.6619791662794028)\n",
      "max_pcc:0.1536810292964398\n",
      "Epoch 070: Loss 1.4550851583480835\n",
      "(0.18089495369952677, 0.1440204132966807, 0.6357925765891248)\n",
      "max_pcc:0.1810508375275452\n",
      "Epoch 070: Loss 1.5060510635375977\n",
      "(0.1628683628464197, 0.1260109317961745, 0.6335067583577013)\n",
      "max_pcc:0.1828414260223409\n",
      "Epoch 070: Loss 1.548067331314087\n",
      "(0.1296324657068312, 0.1075502077616794, 0.675704356637684)\n",
      "max_pcc:0.1296324657068312\n",
      "Epoch 070: Loss 1.674708604812622\n",
      "(0.08403159658060591, 0.0866743280006789, 0.6884351647630622)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 070: Loss 1.494678020477295\n",
      "(0.13471203703263965, 0.12051092784267724, 0.6597030352805079)\n",
      "max_pcc:0.1536810292964398\n",
      "Epoch 080: Loss 1.4415693283081055\n",
      "(0.1829029800073657, 0.13983460567437458, 0.6343457940128117)\n",
      "max_pcc:0.1920019353199959\n",
      "Epoch 080: Loss 1.4846417903900146\n",
      "(0.18513600623976498, 0.13572739533655753, 0.6267075708775054)\n",
      "max_pcc:0.18513600623976498\n",
      "Epoch 080: Loss 1.5420715808868408\n",
      "(0.13069447741706028, 0.09813491332375439, 0.672566455283854)\n",
      "max_pcc:0.13188862939851625\n",
      "Epoch 080: Loss 1.674058198928833\n",
      "(0.08900538663280555, 0.0916968888776482, 0.6866115994745924)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 080: Loss 1.4757812023162842\n",
      "(0.14074692512479825, 0.12092910638992363, 0.6570331783190596)\n",
      "max_pcc:0.1536810292964398\n",
      "Epoch 090: Loss 1.468737244606018\n",
      "(0.1623102545687633, 0.12334012443017416, 0.6403386504523932)\n",
      "max_pcc:0.1920019353199959\n",
      "Epoch 090: Loss 1.4715402126312256\n",
      "(0.1913882406735238, 0.12456638076903695, 0.6247643200433312)\n",
      "max_pcc:0.20732191250293858\n",
      "Epoch 090: Loss 1.5283812284469604\n",
      "(0.13147514835893748, 0.09791879147121378, 0.6720864561299723)\n",
      "max_pcc:0.13691048292761582\n",
      "Epoch 090: Loss 1.6623554229736328\n",
      "(0.07977211591466127, 0.08002206508124829, 0.6879421898964974)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 090: Loss 1.4737440347671509\n",
      "(0.1481981676937928, 0.1263955708186902, 0.654501359839053)\n",
      "max_pcc:0.1536810292964398\n",
      "Epoch 100: Loss 1.448315143585205\n",
      "(0.16962842854941992, 0.1425314240450237, 0.6344881736585815)\n",
      "max_pcc:0.1920019353199959\n",
      "Epoch 100: Loss 1.4590433835983276\n",
      "(0.2065200100154547, 0.14324316689116418, 0.6206968004059404)\n",
      "max_pcc:0.20732191250293858\n",
      "Epoch 100: Loss 1.5026562213897705\n",
      "(0.13761503548797918, 0.10618265750108331, 0.6707051939680656)\n",
      "max_pcc:0.14058580330905907\n",
      "Epoch 100: Loss 1.6504185199737549\n",
      "(0.08217558532940133, 0.08840238715937235, 0.6854225351828934)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 100: Loss 1.432997226715088\n",
      "(0.16717673622618853, 0.13931010559807816, 0.6494705095462779)\n",
      "max_pcc:0.1676757280264817\n",
      "Epoch 110: Loss 1.4384230375289917\n",
      "(0.17030376061293523, 0.11786965313077948, 0.6337886255410363)\n",
      "max_pcc:0.1920019353199959\n",
      "Epoch 110: Loss 1.4997024536132812\n",
      "(0.1441933990059479, 0.11049087405689258, 0.6675334321362366)\n",
      "max_pcc:0.1441933990059479\n",
      "Epoch 110: Loss 1.4518895149230957\n",
      "(0.20398174981070383, 0.12858898815578626, 0.6212318381100291)\n",
      "max_pcc:0.20817556217575997\n",
      "Epoch 110: Loss 1.6457860469818115\n",
      "(0.0799478582740525, 0.07717212423676621, 0.6858405995069287)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 110: Loss 1.4386380910873413\n",
      "(0.17053602537745255, 0.13694113507920835, 0.6489324282654642)\n",
      "max_pcc:0.17215512250580203\n",
      "Epoch 120: Loss 1.429107666015625\n",
      "(0.17787928951956367, 0.1190483634923217, 0.6336382140705371)\n",
      "max_pcc:0.1920019353199959\n",
      "Epoch 120: Loss 1.497711420059204\n",
      "(0.13505780889106814, 0.1015968904857457, 0.6692777413358083)\n",
      "max_pcc:0.1468935379796211\n",
      "Epoch 120: Loss 1.4554922580718994\n",
      "(0.20514045449370372, 0.13213412766275162, 0.6204811075943895)\n",
      "max_pcc:0.20817556217575997\n",
      "Epoch 120: Loss 1.4200193881988525\n",
      "(0.18112719488037524, 0.14048671267482107, 0.6464017249430996)\n",
      "max_pcc:0.18112719488037524\n",
      "Epoch 120: Loss 1.6386560201644897\n",
      "(0.08357541493436399, 0.07854062489070611, 0.685414270514509)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 130: Loss 1.4139958620071411\n",
      "(0.19219969483901217, 0.129635989869742, 0.6298306644469678)\n",
      "max_pcc:0.19219969483901217\n",
      "Epoch 130: Loss 1.477477788925171\n",
      "(0.14867821696136702, 0.09821505117650925, 0.6669456841325182)\n",
      "max_pcc:0.15179151283649697\n",
      "Epoch 130: Loss 1.45106840133667\n",
      "(0.21001315570836093, 0.1422303850200103, 0.6188113178449121)\n",
      "max_pcc:0.21001315570836093\n",
      "Epoch 130: Loss 1.6358622312545776\n",
      "(0.08052306394039757, 0.08330238522068503, 0.6865673331215331)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 130: Loss 1.409280776977539\n",
      "(0.18082871337043266, 0.1332380401118875, 0.6458767504895188)\n",
      "max_pcc:0.18112719488037524\n",
      "Epoch 140: Loss 1.426693081855774\n",
      "(0.1955034136167994, 0.14972948250324752, 0.6306999780784175)\n",
      "max_pcc:0.19631540323877975\n",
      "Epoch 140: Loss 1.4715805053710938\n",
      "(0.14850967189776504, 0.09505014689470626, 0.6687750071377618)\n",
      "max_pcc:0.15179151283649697\n",
      "Epoch 140: Loss 1.642629861831665\n",
      "(0.07706644351901934, 0.08057598856634036, 0.68436281808173)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 140: Loss 1.4557665586471558\n",
      "(0.2056792170777084, 0.1403917893447661, 0.6201311437267161)\n",
      "max_pcc:0.21586531538525625\n",
      "Epoch 140: Loss 1.4200539588928223\n",
      "(0.17517787838997084, 0.12691985020179575, 0.6469391717286288)\n",
      "max_pcc:0.18242502956931797\n",
      "Epoch 150: Loss 1.4181774854660034\n",
      "(0.19863638391725366, 0.14374503839011077, 0.6276211538306923)\n",
      "max_pcc:0.20244967235568584\n",
      "Epoch 150: Loss 1.4563708305358887\n",
      "(0.15442005309392706, 0.09563162540943937, 0.6667018672564592)\n",
      "max_pcc:0.15487367109654593\n",
      "Epoch 150: Loss 1.628894567489624\n",
      "(0.09552530342072052, 0.08102301280477685, 0.6807550630662246)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 150: Loss 1.447631597518921\n",
      "(0.20758596818462005, 0.1463081569079235, 0.6186516681282671)\n",
      "max_pcc:0.21586531538525625\n",
      "Epoch 150: Loss 1.4022815227508545\n",
      "(0.18113991102506477, 0.12494923038834141, 0.6459272711412873)\n",
      "max_pcc:0.18721641567674638\n",
      "Epoch 160: Loss 1.4047529697418213\n",
      "(0.20303330802556388, 0.1443227024730461, 0.6257860155541048)\n",
      "max_pcc:0.208294605540846\n",
      "Epoch 160: Loss 1.4456002712249756\n",
      "(0.16371622829230895, 0.11343055533505, 0.6626301572824735)\n",
      "max_pcc:0.16544641445527894\n",
      "Epoch 160: Loss 1.6136560440063477\n",
      "(0.09986816867432086, 0.09000947854711085, 0.6801182423136949)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 160: Loss 1.443047046661377\n",
      "(0.20515327549864054, 0.14680048755081995, 0.6183873846166771)\n",
      "max_pcc:0.21840643264963105\n",
      "Epoch 160: Loss 1.4210150241851807\n",
      "(0.1765763684055016, 0.12311233229383095, 0.646210644359285)\n",
      "max_pcc:0.18953559305010226\n",
      "Epoch 170: Loss 1.4265332221984863\n",
      "(0.1961181351768203, 0.1426158871215377, 0.6313870560274665)\n",
      "max_pcc:0.208294605540846\n",
      "Epoch 170: Loss 1.4331879615783691\n",
      "(0.17001471975444837, 0.10069541382958525, 0.6619987597477285)\n",
      "max_pcc:0.17001471975444837\n",
      "Epoch 170: Loss 1.5982706546783447\n",
      "(0.10543918931224554, 0.08640869314407025, 0.6779726002077225)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 170: Loss 1.3936278820037842\n",
      "(0.18432666141281773, 0.1221965564173807, 0.6444055605389079)\n",
      "max_pcc:0.19141552118025815\n",
      "Epoch 170: Loss 1.4240516424179077\n",
      "(0.2208367621276601, 0.14625357109609968, 0.6145952603222107)\n",
      "max_pcc:0.22347878101181287\n",
      "Epoch 180: Loss 1.4086658954620361\n",
      "(0.20236888579730203, 0.14358561233496417, 0.6304109983646223)\n",
      "max_pcc:0.208294605540846\n",
      "Epoch 180: Loss 1.4356958866119385\n",
      "(0.16579999241699273, 0.11852193503786905, 0.6612487823137226)\n",
      "max_pcc:0.1802503434679203\n",
      "Epoch 180: Loss 1.614129662513733\n",
      "(0.10574694505201286, 0.08914841563150686, 0.6778817955603411)\n",
      "max_pcc:0.10762126095034606\n",
      "Epoch 180: Loss 1.3884739875793457\n",
      "(0.19406787089408578, 0.12612817032978743, 0.6424810755945884)\n",
      "max_pcc:0.19617797038036894\n",
      "Epoch 180: Loss 1.4162954092025757\n",
      "(0.22195810294553223, 0.13659691948521344, 0.6136160641719323)\n",
      "max_pcc:0.22347878101181287\n",
      "Epoch 190: Loss 1.4234201908111572\n",
      "(0.19909917225034995, 0.16055145311943253, 0.6276375345018959)\n",
      "max_pcc:0.21074479602072177\n",
      "Epoch 190: Loss 1.4648849964141846\n",
      "(0.14165423448123446, 0.1333607903833942, 0.6650905540290346)\n",
      "max_pcc:0.18135315375422084\n",
      "Epoch 190: Loss 1.4212960004806519\n",
      "(0.17174712973606646, 0.11047324132779873, 0.6636355738969448)\n",
      "max_pcc:0.17174712973606646\n",
      "Epoch 190: Loss 1.380030870437622\n",
      "(0.19644935005346315, 0.127544832924671, 0.6413322502168732)\n",
      "max_pcc:0.19922975343597824\n",
      "Epoch 190: Loss 1.4081681966781616\n",
      "(0.23238056988886927, 0.1524796134904568, 0.6127633051946411)\n",
      "max_pcc:0.23238056988886927\n",
      "Epoch 200: Loss 1.4163224697113037\n",
      "(0.19808805900739895, 0.15119719101286422, 0.6292666941741871)\n",
      "max_pcc:0.21074479602072177\n",
      "Epoch 200: Loss 1.4625285863876343\n",
      "(0.14714177260791358, 0.11999179685522593, 0.6647816259165666)\n",
      "max_pcc:0.18135315375422084\n",
      "Epoch 200: Loss 1.4330735206604004\n",
      "(0.1639135132729935, 0.1113727757582953, 0.6664720079613552)\n",
      "max_pcc:0.17174712973606646\n",
      "Epoch 200: Loss 1.3707703351974487\n",
      "(0.2024546391124899, 0.11875768899762053, 0.6413514917182449)\n",
      "max_pcc:0.2024546391124899\n",
      "Epoch 200: Loss 1.4526634216308594\n",
      "(0.21095541023632008, 0.1406498075073211, 0.616641405495892)\n",
      "max_pcc:0.23238056988886927\n",
      "Epoch 210: Loss 1.4006985425949097\n",
      "(0.20792086901176127, 0.14685294439976943, 0.6263408368896394)\n",
      "max_pcc:0.21074479602072177\n",
      "Epoch 210: Loss 1.4515743255615234\n",
      "(0.15494805018601254, 0.11551953078574949, 0.6636003767463298)\n",
      "max_pcc:0.18135315375422084\n",
      "Epoch 210: Loss 1.40664803981781\n",
      "(0.1563636528060598, 0.10368674366843798, 0.6675930385655771)\n",
      "max_pcc:0.17174712973606646\n",
      "Epoch 210: Loss 1.3689930438995361\n",
      "(0.1981647903400151, 0.12754078438590521, 0.6409725384917877)\n",
      "max_pcc:0.2070449870627158\n",
      "Epoch 210: Loss 1.447955846786499\n",
      "(0.21651081683884485, 0.1739620623927453, 0.6164262215998735)\n",
      "max_pcc:0.23391538233749903\n",
      "Epoch 220: Loss 1.387970209121704\n",
      "(0.20819882339937812, 0.14282936795103388, 0.6231358357653022)\n",
      "max_pcc:0.21631641052739561\n",
      "Epoch 220: Loss 1.4497371912002563\n",
      "(0.15898263216050518, 0.12089027446089268, 0.6626930214628559)\n",
      "max_pcc:0.18135315375422084\n",
      "Epoch 220: Loss 1.4227029085159302\n",
      "(0.171059913543454, 0.11413417623527973, 0.6660600034990555)\n",
      "max_pcc:0.18024750695102376\n",
      "Epoch 220: Loss 1.3519113063812256\n",
      "(0.20147021080108285, 0.11585123334695148, 0.6405679262672609)\n",
      "max_pcc:0.2088871623407367\n",
      "Epoch 220: Loss 1.4148402214050293\n",
      "(0.23737077436729484, 0.153790275758267, 0.611811436802365)\n",
      "max_pcc:0.23737077436729484\n",
      "Epoch 230: Loss 1.4111440181732178\n",
      "(0.2004981817586608, 0.15705386089373155, 0.6252596475817493)\n",
      "max_pcc:0.22539535059068197\n",
      "Epoch 230: Loss 1.432837724685669\n",
      "(0.16599298998813483, 0.11223598886450042, 0.661046466723481)\n",
      "max_pcc:0.18135315375422084\n",
      "Epoch 230: Loss 1.3893897533416748\n",
      "(0.1824611683997029, 0.11475690112677561, 0.663621517520675)\n",
      "max_pcc:0.18276825162553592\n",
      "Epoch 230: Loss 1.3616743087768555\n",
      "(0.20142889015764065, 0.11639351785762911, 0.6400586303219116)\n",
      "max_pcc:0.21258685109381759\n",
      "Epoch 230: Loss 1.4145357608795166\n",
      "(0.24065638269259904, 0.16944462227109225, 0.6081105009153522)\n",
      "max_pcc:0.24729537388238565\n",
      "Epoch 240: Loss 1.3628746271133423\n",
      "(0.22564302256126098, 0.14734797112142262, 0.6198717107913877)\n",
      "max_pcc:0.22792143801128564\n",
      "Epoch 240: Loss 1.424666166305542\n",
      "(0.17467400763340354, 0.1178360973000479, 0.6593564761039994)\n",
      "max_pcc:0.18135315375422084\n",
      "Epoch 240: Loss 1.3875046968460083\n",
      "(0.18156612087229818, 0.09969162233333309, 0.661665438725827)\n",
      "max_pcc:0.18276825162553592\n",
      "Epoch 240: Loss 1.4172546863555908\n",
      "(0.17827909447608867, 0.1324312785196049, 0.6427298712937304)\n",
      "max_pcc:0.21618779785698894\n",
      "Epoch 240: Loss 1.3994463682174683\n",
      "(0.24320876294072707, 0.15358844656278944, 0.6099991623593856)\n",
      "max_pcc:0.25012555734159975\n",
      "Epoch 250: Loss 1.3992104530334473\n",
      "(0.21834580207882948, 0.17201292520089137, 0.6242157594683476)\n",
      "max_pcc:0.23293949865703387\n",
      "Epoch 250: Loss 1.4352784156799316\n",
      "(0.16679666885355193, 0.12772775670800082, 0.6599791868304824)\n",
      "max_pcc:0.18135315375422084\n",
      "Epoch 250: Loss 1.4067484140396118\n",
      "(0.17000680360201856, 0.10439465451650061, 0.6638460615423214)\n",
      "max_pcc:0.18520363757110608\n",
      "Epoch 250: Loss 1.3795337677001953\n",
      "(0.20288459620980187, 0.13805633059200673, 0.6388941302708221)\n",
      "max_pcc:0.21618779785698894\n",
      "Epoch 250: Loss 1.391508936882019\n",
      "(0.24637539940688358, 0.14938570088503497, 0.609741902135215)\n",
      "max_pcc:0.25012555734159975\n",
      "Epoch 260: Loss 1.3792893886566162\n",
      "(0.22387167045805698, 0.1597093581296345, 0.6242623137288652)\n",
      "max_pcc:0.23293949865703387\n",
      "Epoch 260: Loss 1.4245071411132812\n",
      "(0.1769985949620919, 0.1380443752563891, 0.656894624751927)\n",
      "max_pcc:0.1817328022455237\n",
      "Epoch 260: Loss 1.3789293766021729\n",
      "(0.1857854737360468, 0.11032921076158896, 0.6610491946819488)\n",
      "max_pcc:0.19255936127094864\n",
      "Epoch 260: Loss 1.3527132272720337\n",
      "(0.21725399678395896, 0.12539725071748564, 0.6377862308608608)\n",
      "max_pcc:0.21725399678395896\n",
      "Epoch 260: Loss 1.390405297279358\n",
      "(0.24741325857185467, 0.16284196625984157, 0.6089122969719789)\n",
      "max_pcc:0.2555014534188187\n",
      "Epoch 270: Loss 1.3690485954284668\n",
      "(0.23155965212286098, 0.16652670959069574, 0.6217505384571919)\n",
      "max_pcc:0.23293949865703387\n",
      "Epoch 270: Loss 1.4240676164627075\n",
      "(0.17537038986921394, 0.11875332136049618, 0.6604773872324056)\n",
      "max_pcc:0.1817328022455237\n",
      "Epoch 270: Loss 1.4146885871887207\n",
      "(0.1785115187379324, 0.1181038816988707, 0.6617960738411703)\n",
      "max_pcc:0.19255936127094864\n",
      "Epoch 270: Loss 1.3596241474151611\n",
      "(0.21028983640651525, 0.11793585142933692, 0.6387051021119652)\n",
      "max_pcc:0.22131428831451794\n",
      "Epoch 270: Loss 1.3709485530853271\n",
      "(0.25688787838072713, 0.1457935770133313, 0.6064259674845386)\n",
      "max_pcc:0.26099893156395026\n",
      "Epoch 280: Loss 1.365490198135376\n",
      "(0.23177939158669617, 0.16308168319455857, 0.6221550595371472)\n",
      "max_pcc:0.23293949865703387\n",
      "Epoch 280: Loss 1.4116220474243164\n",
      "(0.1784232665353555, 0.13427297599174207, 0.6577673313958903)\n",
      "max_pcc:0.18333097551057834\n",
      "Epoch 280: Loss 1.3770596981048584\n",
      "(0.185952667847166, 0.1108225233162785, 0.660107502600069)\n",
      "max_pcc:0.19255936127094864\n",
      "Epoch 280: Loss 1.3380544185638428\n",
      "(0.22313639137747515, 0.12497535261980232, 0.6367212133926426)\n",
      "max_pcc:0.22509309823779414\n",
      "Epoch 280: Loss 1.3810007572174072\n",
      "(0.24839646191245868, 0.15573167647619907, 0.609192104195337)\n",
      "max_pcc:0.26099893156395026\n",
      "Epoch 290: Loss 1.3718211650848389\n",
      "(0.21962867462260008, 0.15141491633560225, 0.6248500969167128)\n",
      "max_pcc:0.2346825034186154\n",
      "Epoch 290: Loss 1.388791799545288\n",
      "(0.18382894264137298, 0.12034337147589629, 0.6576968376777746)\n",
      "max_pcc:0.18742759115591476\n",
      "Epoch 290: Loss 1.3660978078842163\n",
      "(0.18866566722303815, 0.11758468163590736, 0.6588938610315604)\n",
      "max_pcc:0.19938836386980935\n",
      "Epoch 290: Loss 1.330718755722046\n",
      "(0.22692739382007726, 0.12210722116459316, 0.6368713595720097)\n",
      "max_pcc:0.23051168877035966\n",
      "Epoch 290: Loss 1.3689892292022705\n",
      "(0.2574477387046939, 0.14930981466069537, 0.6062530147479812)\n",
      "max_pcc:0.26130482608828676\n",
      "Epoch 300: Loss 1.375354290008545\n",
      "(0.2183039137940845, 0.1560218271742535, 0.6240416497399942)\n",
      "max_pcc:0.2346825034186154\n",
      "Epoch 300: Loss 1.3752304315567017\n",
      "(0.18800738052012883, 0.12400122388541751, 0.6560512628821189)\n",
      "max_pcc:0.18800738052012883\n",
      "Epoch 300: Loss 1.3829816579818726\n",
      "(0.1889479815703242, 0.11674085207225764, 0.6593169351988086)\n",
      "max_pcc:0.19938836386980935\n",
      "Epoch 300: Loss 1.3378599882125854\n",
      "(0.22640906921460321, 0.12476475384524992, 0.6354485718989353)\n",
      "max_pcc:0.23385453580904678\n",
      "Epoch 300: Loss 1.3583579063415527\n",
      "(0.2665523657713273, 0.13140543458726922, 0.6048737283365131)\n",
      "max_pcc:0.2665523657713273\n",
      "Epoch 310: Loss 1.3509747982025146\n",
      "(0.23484505169015168, 0.15621717756390688, 0.6213430460039511)\n",
      "max_pcc:0.2392255987831512\n",
      "Epoch 310: Loss 1.38176691532135\n",
      "(0.18417054654692108, 0.11153216876282487, 0.6575855386623997)\n",
      "max_pcc:0.19148270003990117\n",
      "Epoch 310: Loss 1.3593536615371704\n",
      "(0.1821070024333944, 0.10533787641045615, 0.6595946332917049)\n",
      "max_pcc:0.19938836386980935\n",
      "Epoch 310: Loss 1.3169422149658203\n",
      "(0.23978915052087005, 0.11609099496054703, 0.6341040516681773)\n",
      "max_pcc:0.24017909470803048\n",
      "Epoch 310: Loss 1.3409175872802734\n",
      "(0.2779982018957878, 0.14772528930889056, 0.6023293831800824)\n",
      "max_pcc:0.2779982018957878\n",
      "Epoch 320: Loss 1.3496334552764893\n",
      "(0.23536140602609032, 0.1543202330667741, 0.6216840153326165)\n",
      "max_pcc:0.2392255987831512\n",
      "Epoch 320: Loss 1.3718522787094116\n",
      "(0.18524681933087792, 0.12253192822328592, 0.6562255966092692)\n",
      "max_pcc:0.1987030469168344\n",
      "Epoch 320: Loss 1.3642222881317139\n",
      "(0.18710318569550727, 0.10659719598913028, 0.6601823224275326)\n",
      "max_pcc:0.2007570302903319\n",
      "Epoch 320: Loss 1.31253981590271\n",
      "(0.2435935368466249, 0.11392109206970825, 0.6337498991619521)\n",
      "max_pcc:0.24674903001716675\n",
      "Epoch 320: Loss 1.3396459817886353\n",
      "(0.2742825301166759, 0.14516747394166093, 0.6034351958214953)\n",
      "max_pcc:0.2779982018957878\n",
      "Epoch 330: Loss 1.3402289152145386\n",
      "(0.24188641439978492, 0.16092965598423223, 0.6187405905696798)\n",
      "max_pcc:0.24188641439978492\n",
      "Epoch 330: Loss 1.3771260976791382\n",
      "(0.1834147898946694, 0.12580307488333792, 0.6551887127328929)\n",
      "max_pcc:0.1987030469168344\n",
      "Epoch 330: Loss 1.347414493560791\n",
      "(0.19865021018539647, 0.10890047698047647, 0.6586864948629867)\n",
      "max_pcc:0.2007570302903319\n",
      "Epoch 330: Loss 1.325935959815979\n",
      "(0.2315485738584388, 0.12930215892748356, 0.6338226178737104)\n",
      "max_pcc:0.25392885361510975\n",
      "Epoch 330: Loss 1.3461389541625977\n",
      "(0.27091326609337885, 0.14247791706300134, 0.603729968374035)\n",
      "max_pcc:0.28067985599305234\n",
      "Epoch 340: Loss 1.3404163122177124\n",
      "(0.24031451126147124, 0.15765495121392253, 0.61943114791743)\n",
      "max_pcc:0.24188641439978492\n",
      "Epoch 340: Loss 1.3499473333358765\n",
      "(0.1947954265219542, 0.11697882598475845, 0.6555136924653895)\n",
      "max_pcc:0.1987030469168344\n",
      "Epoch 340: Loss 1.3404210805892944\n",
      "(0.19385266651040237, 0.1086474005249452, 0.658057029928462)\n",
      "max_pcc:0.2007570302903319\n",
      "Epoch 340: Loss 1.3053141832351685\n",
      "(0.24328539815326627, 0.11716239910715831, 0.6332670379780124)\n",
      "max_pcc:0.25439332929809466\n",
      "Epoch 340: Loss 1.339601993560791\n",
      "(0.2745182943330283, 0.15339323408504177, 0.6034939192581141)\n",
      "max_pcc:0.28067985599305234\n",
      "Epoch 000: Loss 1.8220691680908203\n",
      "(0.025169761416776897, 0.042507132587687325, 0.7153402604839765)\n",
      "max_pcc:0.025169761416776897\n",
      "Epoch 000: Loss 1.8291877508163452\n",
      "(0.04247263677881727, 0.07943165911298537, 0.7096313423806581)\n",
      "max_pcc:0.04247263677881727\n",
      "Epoch 000: Loss 1.781368613243103\n",
      "(0.060392974224334164, 0.08344855574212008, 0.7181289539616693)\n",
      "max_pcc:0.060392974224334164\n",
      "Epoch 000: Loss 1.7681331634521484\n",
      "(0.05799079575206655, 0.08432429133228089, 0.7152781484910213)\n",
      "max_pcc:0.05799079575206655\n",
      "Epoch 000: Loss 1.7795475721359253\n",
      "(0.0659143221187756, 0.09857815850708587, 0.7115566070195287)\n",
      "max_pcc:0.0659143221187756\n",
      "Epoch 010: Loss 1.6138365268707275\n",
      "(0.148067112957318, 0.15320413269788333, 0.665301235135013)\n",
      "max_pcc:0.148067112957318\n",
      "Epoch 010: Loss 1.6319841146469116\n",
      "(0.0784295896650893, 0.09893010594674614, 0.6511909717944697)\n",
      "max_pcc:0.08729504244835976\n",
      "Epoch 010: Loss 1.6327335834503174\n",
      "(0.10657448348005856, 0.12009322788597605, 0.6601908097009122)\n",
      "max_pcc:0.10657448348005856\n",
      "Epoch 010: Loss 1.607163906097412\n",
      "(0.11017176490148821, 0.09637141077412081, 0.6626444041033193)\n",
      "max_pcc:0.11017176490148821\n",
      "Epoch 010: Loss 1.617822527885437\n",
      "(0.10678554825938905, 0.09858391325787735, 0.669831639338973)\n",
      "max_pcc:0.11584085521422073\n",
      "Epoch 020: Loss 1.601196527481079\n",
      "(0.15581945199595204, 0.15459513746705764, 0.6511208310392802)\n",
      "max_pcc:0.15581945199595204\n",
      "Epoch 020: Loss 1.6130390167236328\n",
      "(0.0711735076682418, 0.09140859879233297, 0.6468448444819088)\n",
      "max_pcc:0.0893704461125606\n",
      "Epoch 020: Loss 1.6020921468734741\n",
      "(0.11438626620384015, 0.11967445690725714, 0.6530250435229635)\n",
      "max_pcc:0.11780537998465129\n",
      "Epoch 020: Loss 1.5751633644104004\n",
      "(0.12987976588546427, 0.12343787395840052, 0.653573093748873)\n",
      "max_pcc:0.12987976588546427\n",
      "Epoch 020: Loss 1.6004642248153687\n",
      "(0.10603422069456334, 0.08412550104435537, 0.6596123691209475)\n",
      "max_pcc:0.11584085521422073\n",
      "Epoch 030: Loss 1.5570907592773438\n",
      "(0.1656157145524936, 0.16075972988520779, 0.6436680010658824)\n",
      "max_pcc:0.16621491356605808\n",
      "Epoch 030: Loss 1.5923833847045898\n",
      "(0.08981578067156872, 0.10611509682949524, 0.637923087583195)\n",
      "max_pcc:0.09547082241807413\n",
      "Epoch 030: Loss 1.589128017425537\n",
      "(0.10858936937423395, 0.10887985192563276, 0.652432985202103)\n",
      "max_pcc:0.11983721874570159\n",
      "Epoch 030: Loss 1.5887963771820068\n",
      "(0.12022252464964928, 0.10157471462169591, 0.6537652061355114)\n",
      "max_pcc:0.12022252464964928\n",
      "Epoch 030: Loss 1.568781852722168\n",
      "(0.14161077932041435, 0.12526416518628336, 0.6462494182145491)\n",
      "max_pcc:0.14177046008716482\n",
      "Epoch 040: Loss 1.5363291501998901\n",
      "(0.1789360895893727, 0.17254400631975048, 0.6408212592098254)\n",
      "max_pcc:0.1789360895893727\n",
      "Epoch 040: Loss 1.5711209774017334\n",
      "(0.0961820133356432, 0.10476040711050906, 0.6330973406875859)\n",
      "max_pcc:0.09859030690488771\n",
      "Epoch 040: Loss 1.5464035272598267\n",
      "(0.132064552081376, 0.13186765040750145, 0.6465639450755919)\n",
      "max_pcc:0.132064552081376\n",
      "Epoch 040: Loss 1.5377577543258667\n",
      "(0.13473297394018222, 0.11095323659786512, 0.6475365246560288)\n",
      "max_pcc:0.1615007942691922\n",
      "Epoch 040: Loss 1.5488847494125366\n",
      "(0.13456874896986945, 0.10490675810035417, 0.6466964096547884)\n",
      "max_pcc:0.13505243393500554\n",
      "Epoch 050: Loss 1.5342235565185547\n",
      "(0.18688399159972427, 0.18112740662711002, 0.6368254428046989)\n",
      "max_pcc:0.19091125544656262\n",
      "Epoch 050: Loss 1.544459342956543\n",
      "(0.10972745477131939, 0.11271104902877827, 0.6253517603705212)\n",
      "max_pcc:0.10972745477131939\n",
      "Epoch 050: Loss 1.5512089729309082\n",
      "(0.13413655956725123, 0.13696417142613418, 0.6446454065781971)\n",
      "max_pcc:0.14210523003306624\n",
      "Epoch 050: Loss 1.5063128471374512\n",
      "(0.15456431404113377, 0.10758566555525054, 0.6425651274537827)\n",
      "max_pcc:0.16169545225383342\n",
      "Epoch 050: Loss 1.5398902893066406\n",
      "(0.13971283047937955, 0.11460817873935492, 0.6448150823434382)\n",
      "max_pcc:0.14144006030521547\n",
      "Epoch 060: Loss 1.5042603015899658\n",
      "(0.19734143833827825, 0.1866885434559496, 0.6295615304856956)\n",
      "max_pcc:0.19808432433746145\n",
      "Epoch 060: Loss 1.5169439315795898\n",
      "(0.12216502223146904, 0.12069859710309158, 0.6199644849181225)\n",
      "max_pcc:0.12219263299917703\n",
      "Epoch 060: Loss 1.534000277519226\n",
      "(0.14017892336610532, 0.1392555934435827, 0.6419589466406727)\n",
      "max_pcc:0.14210523003306624\n",
      "Epoch 060: Loss 1.5234308242797852\n",
      "(0.1271368330701001, 0.10660165244746611, 0.6451934212908825)\n",
      "max_pcc:0.1654939559873328\n",
      "Epoch 060: Loss 1.5280423164367676\n",
      "(0.1418954347778171, 0.11163393570044775, 0.6401727262144825)\n",
      "max_pcc:0.14413139347876783\n",
      "Epoch 070: Loss 1.4944664239883423\n",
      "(0.18683928567944108, 0.1786168172879779, 0.627060820229271)\n",
      "max_pcc:0.21146273026519985\n",
      "Epoch 070: Loss 1.5193016529083252\n",
      "(0.15116990260510146, 0.14830633939610274, 0.6373212317036401)\n",
      "max_pcc:0.15116990260510146\n",
      "Epoch 070: Loss 1.499287724494934\n",
      "(0.13043994448185195, 0.11924245640071465, 0.6172398198395146)\n",
      "max_pcc:0.13099093217001728\n",
      "Epoch 070: Loss 1.474825143814087\n",
      "(0.16856397748504837, 0.10715545508985592, 0.6358694489441945)\n",
      "max_pcc:0.17307709400350454\n",
      "Epoch 070: Loss 1.5279910564422607\n",
      "(0.14881416614861792, 0.1295111016773506, 0.6380937223392521)\n",
      "max_pcc:0.15283491736969443\n",
      "Epoch 080: Loss 1.5296692848205566\n",
      "(0.14303156143162674, 0.148015490160767, 0.6391003301223208)\n",
      "max_pcc:0.15139349961683912\n",
      "Epoch 080: Loss 1.477632999420166\n",
      "(0.1998402102522742, 0.17201742556219501, 0.6257011347952669)\n",
      "max_pcc:0.21146273026519985\n",
      "Epoch 080: Loss 1.4993243217468262\n",
      "(0.1378897512150461, 0.11826312760811802, 0.6143939319293756)\n",
      "max_pcc:0.1378897512150461\n",
      "Epoch 080: Loss 1.4647345542907715\n",
      "(0.17521271348740705, 0.11873912951666264, 0.6331486861505748)\n",
      "max_pcc:0.1765801312096495\n",
      "Epoch 080: Loss 1.5086560249328613\n",
      "(0.1518173122923586, 0.1286099487819686, 0.637986773344172)\n",
      "max_pcc:0.15283491736969443\n",
      "Epoch 090: Loss 1.5193943977355957\n",
      "(0.14856654795837432, 0.15289464350184184, 0.6373849228027582)\n",
      "max_pcc:0.15139349961683912\n",
      "Epoch 090: Loss 1.4666903018951416\n",
      "(0.20419323449421195, 0.18032273079608596, 0.6224951653554036)\n",
      "max_pcc:0.21155512807869084\n",
      "Epoch 090: Loss 1.4806230068206787\n",
      "(0.1518357311300298, 0.12457242912493721, 0.6122562771399744)\n",
      "max_pcc:0.1528921145305216\n",
      "Epoch 090: Loss 1.4888412952423096\n",
      "(0.17036637098247984, 0.12874630738301543, 0.6343673059711741)\n",
      "max_pcc:0.19037985959514217\n",
      "Epoch 090: Loss 1.514241337776184\n",
      "(0.14806392757926218, 0.13351708318454386, 0.6399783358014414)\n",
      "max_pcc:0.15799017630451642\n",
      "Epoch 100: Loss 1.5015774965286255\n",
      "(0.1634004014977687, 0.1575715500708031, 0.632616233847152)\n",
      "max_pcc:0.1634004014977687\n",
      "Epoch 100: Loss 1.4671266078948975\n",
      "(0.19671194805348896, 0.18144285776952837, 0.6221784921614593)\n",
      "max_pcc:0.21879581499968162\n",
      "Epoch 100: Loss 1.4979047775268555\n",
      "(0.14730172701084807, 0.12563972842354948, 0.6135982564317685)\n",
      "max_pcc:0.15765363514028632\n",
      "Epoch 100: Loss 1.477315068244934\n",
      "(0.16549516862639865, 0.11766208628008284, 0.6335235127296847)\n",
      "max_pcc:0.19037985959514217\n",
      "Epoch 100: Loss 1.5030463933944702\n",
      "(0.15684771784752738, 0.13383185158466843, 0.6349466372850755)\n",
      "max_pcc:0.16305483868038387\n",
      "Epoch 110: Loss 1.522827386856079\n",
      "(0.16108716352622857, 0.1656255469963196, 0.6352897264526486)\n",
      "max_pcc:0.1700732311566098\n",
      "Epoch 110: Loss 1.5035580396652222\n",
      "(0.15101299871515506, 0.12740588716911327, 0.6110973519634596)\n",
      "max_pcc:0.15765363514028632\n",
      "Epoch 110: Loss 1.4468588829040527\n",
      "(0.2193764053744048, 0.19028146789869815, 0.6175234216701666)\n",
      "max_pcc:0.21976569311197053\n",
      "Epoch 110: Loss 1.5051054954528809\n",
      "(0.14600730836470419, 0.12786869463339065, 0.6350238223475941)\n",
      "max_pcc:0.16305483868038387\n",
      "Epoch 110: Loss 1.4372968673706055\n",
      "(0.18426442184392255, 0.11671573077136185, 0.6299410247883254)\n",
      "max_pcc:0.19037985959514217\n",
      "Epoch 120: Loss 1.500459909439087\n",
      "(0.1595656989667658, 0.16296363072792944, 0.6327522540613026)\n",
      "max_pcc:0.17533433647052343\n",
      "Epoch 120: Loss 1.4631657600402832\n",
      "(0.17087001273549407, 0.13025494917351857, 0.6090793201550447)\n",
      "max_pcc:0.17358357625694612\n",
      "Epoch 120: Loss 1.432236671447754\n",
      "(0.22586390526991906, 0.18344777905057896, 0.6133078371273128)\n",
      "max_pcc:0.22586390526991906\n",
      "Epoch 120: Loss 1.4716246128082275\n",
      "(0.16575372008856007, 0.14287304288843056, 0.6284311402104928)\n",
      "max_pcc:0.16984019603349754\n",
      "Epoch 120: Loss 1.430816650390625\n",
      "(0.18263334655000343, 0.11001346530234411, 0.6307268881684592)\n",
      "max_pcc:0.19037985959514217\n",
      "Epoch 130: Loss 1.4493861198425293\n",
      "(0.18259725217341732, 0.16814818873293563, 0.6274664484772905)\n",
      "max_pcc:0.1870357743971596\n",
      "Epoch 130: Loss 1.4672026634216309\n",
      "(0.17018649938451313, 0.13233866640121492, 0.6086198868511697)\n",
      "max_pcc:0.176699713197481\n",
      "Epoch 130: Loss 1.5029950141906738\n",
      "(0.14838688201391087, 0.13645956736325768, 0.6368462074404904)\n",
      "max_pcc:0.16984019603349754\n",
      "Epoch 130: Loss 1.4780805110931396\n",
      "(0.19825385850991242, 0.18587637933462564, 0.6189654294879565)\n",
      "max_pcc:0.24198536569029297\n",
      "Epoch 130: Loss 1.431544542312622\n",
      "(0.19389554577429, 0.10736553158051425, 0.6285628895695454)\n",
      "max_pcc:0.19389554577429\n",
      "Epoch 140: Loss 1.448319435119629\n",
      "(0.19013559505409638, 0.1650783128950237, 0.6265505074242576)\n",
      "max_pcc:0.19665781829019674\n",
      "Epoch 140: Loss 1.4410240650177002\n",
      "(0.1816278293153963, 0.1325605474407563, 0.6047475698817768)\n",
      "max_pcc:0.1836192519245233\n",
      "Epoch 140: Loss 1.4774036407470703\n",
      "(0.14640935121472923, 0.12752517468899657, 0.6316585863440928)\n",
      "max_pcc:0.17800529135532933\n",
      "Epoch 140: Loss 1.4679975509643555\n",
      "(0.19635320425178598, 0.1812479297239968, 0.6200625318798716)\n",
      "max_pcc:0.24198536569029297\n",
      "Epoch 140: Loss 1.4081203937530518\n",
      "(0.18634788286898651, 0.11011582396910193, 0.6310037779864374)\n",
      "max_pcc:0.19389554577429\n",
      "Epoch 150: Loss 1.4230823516845703\n",
      "(0.1938478251108406, 0.15727465867213197, 0.6245783191811877)\n",
      "max_pcc:0.20197760043239374\n",
      "Epoch 150: Loss 1.460355520248413\n",
      "(0.17555922537821422, 0.14170350611850713, 0.6042966658165345)\n",
      "max_pcc:0.18569700715057053\n",
      "Epoch 150: Loss 1.4443531036376953\n",
      "(0.1620124437470294, 0.14366749896483946, 0.6367626314339442)\n",
      "max_pcc:0.19229633455512127\n",
      "Epoch 150: Loss 1.4429121017456055\n",
      "(0.2131397607144298, 0.17217625859542562, 0.614259953360677)\n",
      "max_pcc:0.24198536569029297\n",
      "Epoch 150: Loss 1.409010410308838\n",
      "(0.18859107395261304, 0.12564814349864287, 0.6288774798324027)\n",
      "max_pcc:0.19427800080798668\n",
      "Epoch 160: Loss 1.4184865951538086\n",
      "(0.20299230435121532, 0.16979716037141376, 0.6217724603131786)\n",
      "max_pcc:0.2100054784492928\n",
      "Epoch 160: Loss 1.4152576923370361\n",
      "(0.19365389803867258, 0.13121818986688671, 0.6049196527577033)\n",
      "max_pcc:0.19868054650112676\n",
      "Epoch 160: Loss 1.4404217004776\n",
      "(0.18802188794258792, 0.14761671922622882, 0.6255230164709809)\n",
      "max_pcc:0.19976486375642885\n",
      "Epoch 160: Loss 1.4857112169265747\n",
      "(0.18733442400460956, 0.1502148891620561, 0.6186157392391877)\n",
      "max_pcc:0.24198536569029297\n",
      "Epoch 160: Loss 1.4076294898986816\n",
      "(0.18946657818507404, 0.11519895892384001, 0.6300293193780309)\n",
      "max_pcc:0.19757230785254684\n",
      "Epoch 170: Loss 1.4473663568496704\n",
      "(0.18834636998666687, 0.16532553388756044, 0.6246989562107328)\n",
      "max_pcc:0.21735785477017835\n",
      "Epoch 170: Loss 1.4099061489105225\n",
      "(0.20023018645566965, 0.1404088201967411, 0.6028939367002156)\n",
      "max_pcc:0.20023018645566965\n",
      "Epoch 170: Loss 1.4264616966247559\n",
      "(0.16085422366788799, 0.13339532594704692, 0.6312092894618161)\n",
      "max_pcc:0.19976486375642885\n",
      "Epoch 170: Loss 1.4429206848144531\n",
      "(0.20396827316056731, 0.17541493027173183, 0.61498671029469)\n",
      "max_pcc:0.24198536569029297\n",
      "Epoch 170: Loss 1.3938038349151611\n",
      "(0.20386227010278823, 0.10986370631700762, 0.6266419315034943)\n",
      "max_pcc:0.20386227010278823\n",
      "Epoch 180: Loss 1.4192990064620972\n",
      "(0.19625589629360557, 0.16601696831387847, 0.6219724485884645)\n",
      "max_pcc:0.21846608009743704\n",
      "Epoch 180: Loss 1.416921854019165\n",
      "(0.19557766119168057, 0.14876568244664198, 0.6006939291802534)\n",
      "max_pcc:0.20023018645566965\n",
      "Epoch 180: Loss 1.4151026010513306\n",
      "(0.17323159867875845, 0.1374637452211259, 0.6233930388505441)\n",
      "max_pcc:0.19976486375642885\n",
      "Epoch 180: Loss 1.4699561595916748\n",
      "(0.21289047518595733, 0.18769367040263585, 0.6144149682305236)\n",
      "max_pcc:0.24198536569029297\n",
      "Epoch 180: Loss 1.3812777996063232\n",
      "(0.20763623741853227, 0.10577742063346397, 0.6260694435534226)\n",
      "max_pcc:0.2101511030777406\n",
      "Epoch 190: Loss 1.3861522674560547\n",
      "(0.21739523968624952, 0.1610883440739875, 0.6177747987973128)\n",
      "max_pcc:0.22302519607800464\n",
      "Epoch 190: Loss 1.4051697254180908\n",
      "(0.20461294188957838, 0.13974120619048094, 0.6002941582032671)\n",
      "max_pcc:0.20461294188957838\n",
      "Epoch 190: Loss 1.4115753173828125\n",
      "(0.19877374051682714, 0.15797236546785656, 0.6155312813931348)\n",
      "max_pcc:0.2227029744361687\n",
      "Epoch 190: Loss 1.442516803741455\n",
      "(0.2221102247168052, 0.17121423838605335, 0.6122040280843111)\n",
      "max_pcc:0.24198536569029297\n",
      "Epoch 190: Loss 1.3733559846878052\n",
      "(0.2104259629605814, 0.10803794931214857, 0.6246391822012438)\n",
      "max_pcc:0.21390110701743367\n",
      "Epoch 200: Loss 1.3902480602264404\n",
      "(0.22599139689665787, 0.17915101899184926, 0.6162764972554731)\n",
      "max_pcc:0.2303878102243157\n",
      "Epoch 200: Loss 1.3948402404785156\n",
      "(0.20495996052060433, 0.1332983704800723, 0.601338499866572)\n",
      "max_pcc:0.21084661543322836\n",
      "Epoch 200: Loss 1.3922011852264404\n",
      "(0.18495837517848643, 0.14182030935809342, 0.6204501232747919)\n",
      "max_pcc:0.2227029744361687\n",
      "Epoch 200: Loss 1.4246528148651123\n",
      "(0.2355908113083903, 0.17603360230895024, 0.6083747550171623)\n",
      "max_pcc:0.24198536569029297\n",
      "Epoch 200: Loss 1.390596866607666\n",
      "(0.20326794662618664, 0.13190807046828212, 0.623589772218423)\n",
      "max_pcc:0.21507767204704797\n",
      "Epoch 210: Loss 1.4021015167236328\n",
      "(0.21916688991947605, 0.17725731982680373, 0.616113016420302)\n",
      "max_pcc:0.2330583500878986\n",
      "Epoch 210: Loss 1.392442226409912\n",
      "(0.20821389678237678, 0.15137405458800246, 0.5974510133631936)\n",
      "max_pcc:0.21239468574422504\n",
      "Epoch 210: Loss 1.3792202472686768\n",
      "(0.21994072160357, 0.16991016271529916, 0.6124900258332111)\n",
      "max_pcc:0.2227029744361687\n",
      "Epoch 210: Loss 1.4142613410949707\n",
      "(0.24525682935951615, 0.1811314753421544, 0.607047690299218)\n",
      "max_pcc:0.24668553000599666\n",
      "Epoch 210: Loss 1.399709939956665\n",
      "(0.20642187633859688, 0.13632673549537253, 0.6207380110784748)\n",
      "max_pcc:0.21507767204704797\n",
      "Epoch 220: Loss 1.3836150169372559\n",
      "(0.23049150800919446, 0.17302200187743305, 0.6147702642964153)\n",
      "max_pcc:0.2330583500878986\n",
      "Epoch 220: Loss 1.3693695068359375\n",
      "(0.2181640161242794, 0.150019367408788, 0.5980319452559738)\n",
      "max_pcc:0.2181640161242794\n",
      "Epoch 220: Loss 1.3564592599868774\n",
      "(0.2277846153685592, 0.161880364526798, 0.6099075196392316)\n",
      "max_pcc:0.2277846153685592\n",
      "Epoch 220: Loss 1.4079418182373047\n",
      "(0.24427582322279684, 0.17397305138236382, 0.6063004288066091)\n",
      "max_pcc:0.24709893989252035\n",
      "Epoch 220: Loss 1.378077745437622\n",
      "(0.20792213796310668, 0.12403669994961077, 0.6248030161348241)\n",
      "max_pcc:0.21507767204704797\n",
      "Epoch 230: Loss 1.3829174041748047\n",
      "(0.22692751806285433, 0.1795368491761967, 0.6151637784495119)\n",
      "max_pcc:0.2330583500878986\n",
      "Epoch 230: Loss 1.412231683731079\n",
      "(0.19323719584198848, 0.14455961667723904, 0.6159683311761701)\n",
      "max_pcc:0.23656563636519512\n",
      "Epoch 230: Loss 1.3581931591033936\n",
      "(0.22117123926755947, 0.14574868007038735, 0.5967948644872249)\n",
      "max_pcc:0.22117123926755947\n",
      "Epoch 230: Loss 1.3976486921310425\n",
      "(0.2549277186735663, 0.18255216432189983, 0.6043983302200903)\n",
      "max_pcc:0.2564084130361764\n",
      "Epoch 230: Loss 1.3651044368743896\n",
      "(0.22308188626585526, 0.12536692141989178, 0.6207024247486104)\n",
      "max_pcc:0.22308188626585526\n",
      "Epoch 240: Loss 1.4309550523757935\n",
      "(0.1954674968082453, 0.16368634499670695, 0.6201259917878452)\n",
      "max_pcc:0.2330583500878986\n",
      "Epoch 240: Loss 1.3694727420806885\n",
      "(0.20924255967622557, 0.1414960887095317, 0.6141204770802017)\n",
      "max_pcc:0.23656563636519512\n",
      "Epoch 240: Loss 1.3656835556030273\n",
      "(0.2217610439428656, 0.14774261408304695, 0.5958417023836271)\n",
      "max_pcc:0.2233419596685463\n",
      "Epoch 240: Loss 1.3804880380630493\n",
      "(0.26234410923185497, 0.1832361228167425, 0.6043452484176983)\n",
      "max_pcc:0.26234410923185497\n",
      "Epoch 240: Loss 1.3563849925994873\n",
      "(0.22717258238580004, 0.1321999791010469, 0.6189161614243032)\n",
      "max_pcc:0.22835793011785252\n",
      "Epoch 250: Loss 1.369598627090454\n",
      "(0.22967647392281484, 0.16487190943522737, 0.615304200651084)\n",
      "max_pcc:0.2330583500878986\n",
      "Epoch 250: Loss 1.357240080833435\n",
      "(0.2155493064953535, 0.15425602589100212, 0.6092056387179288)\n",
      "max_pcc:0.23656563636519512\n",
      "Epoch 250: Loss 1.3646211624145508\n",
      "(0.2187158602550468, 0.15152705989628187, 0.5961257100887061)\n",
      "max_pcc:0.22830001367303143\n",
      "Epoch 250: Loss 1.4007645845413208\n",
      "(0.2527212155966199, 0.18724952864075586, 0.6065678535401448)\n",
      "max_pcc:0.26234410923185497\n",
      "Epoch 250: Loss 1.3488258123397827\n",
      "(0.2289338511622615, 0.1143790437177053, 0.6197741930484318)\n",
      "max_pcc:0.23048494201166636\n",
      "Epoch 260: Loss 1.3716199398040771\n",
      "(0.22771854318187096, 0.15621270118068747, 0.6157954154451343)\n",
      "max_pcc:0.2330583500878986\n",
      "Epoch 260: Loss 1.359452486038208\n",
      "(0.22556859206903135, 0.15473691795094097, 0.6074371629155)\n",
      "max_pcc:0.23656563636519512\n",
      "Epoch 260: Loss 1.3450729846954346\n",
      "(0.22853489064673313, 0.1486768117439664, 0.5945449037029039)\n",
      "max_pcc:0.22853489064673313\n",
      "Epoch 260: Loss 1.3979315757751465\n",
      "(0.2584543047003208, 0.18469857910612375, 0.6069620703553129)\n",
      "max_pcc:0.26234410923185497\n",
      "Epoch 260: Loss 1.3420331478118896\n",
      "(0.2311106573487152, 0.1134891307255559, 0.6189422616367337)\n",
      "max_pcc:0.2311106573487152\n",
      "Epoch 270: Loss 1.3787012100219727\n",
      "(0.2105038633664243, 0.15704739579965193, 0.61808826435615)\n",
      "max_pcc:0.2330583500878986\n",
      "Epoch 270: Loss 1.3537639379501343\n",
      "(0.20488066673248867, 0.1371577315369326, 0.6129410119280498)\n",
      "max_pcc:0.23877427177756608\n",
      "Epoch 270: Loss 1.3438299894332886\n",
      "(0.23252901244621604, 0.1549802251277279, 0.5933577323598433)\n",
      "max_pcc:0.237837843143589\n",
      "Epoch 270: Loss 1.3868873119354248\n",
      "(0.2678275227699214, 0.18427146090132443, 0.6068901658452271)\n",
      "max_pcc:0.2693724089581133\n",
      "Epoch 270: Loss 1.332504153251648\n",
      "(0.23734041007785453, 0.11198506820946179, 0.6188522478943287)\n",
      "max_pcc:0.24035588102283306\n",
      "Epoch 280: Loss 1.3744388818740845\n",
      "(0.23060337627327762, 0.16882428635543634, 0.613486751106113)\n",
      "max_pcc:0.2330583500878986\n",
      "Epoch 280: Loss 1.3492927551269531\n",
      "(0.24230572413673687, 0.17593151361242834, 0.6042442144472167)\n",
      "max_pcc:0.24514953629924385\n",
      "Epoch 280: Loss 1.3372714519500732\n",
      "(0.23721263105383839, 0.1608438841785999, 0.592105941038868)\n",
      "max_pcc:0.237837843143589\n",
      "Epoch 280: Loss 1.3772921562194824\n",
      "(0.26932695000714574, 0.1770749356148325, 0.6048608895277883)\n",
      "max_pcc:0.27200232679663067\n",
      "Epoch 280: Loss 1.3321770429611206\n",
      "(0.2413841008975592, 0.1293811528349854, 0.6173926771494496)\n",
      "max_pcc:0.2413841008975592\n",
      "Epoch 290: Loss 1.3773410320281982\n",
      "(0.21396471503884928, 0.15973939879026208, 0.6171901007887745)\n",
      "max_pcc:0.2339134647562888\n",
      "Epoch 290: Loss 1.3371446132659912\n",
      "(0.24269156092960972, 0.15177209241915057, 0.6071286673808542)\n",
      "max_pcc:0.24514953629924385\n",
      "Epoch 290: Loss 1.3386707305908203\n",
      "(0.23520020149472284, 0.16076326634964042, 0.5929874120169987)\n",
      "max_pcc:0.2407446994767564\n",
      "Epoch 290: Loss 1.386948823928833\n",
      "(0.2648787064125203, 0.1980356722728861, 0.6050369053529224)\n",
      "max_pcc:0.27200232679663067\n",
      "Epoch 290: Loss 1.320672869682312\n",
      "(0.2481827534531032, 0.12353090834388368, 0.6160874616754896)\n",
      "max_pcc:0.25194535554641845\n",
      "Epoch 300: Loss 1.3453484773635864\n",
      "(0.24340817309021112, 0.15487143154448973, 0.6123439730050411)\n",
      "max_pcc:0.24340817309021112\n",
      "Epoch 300: Loss 1.337266445159912\n",
      "(0.23284152534260147, 0.14577986185102207, 0.6089621267910065)\n",
      "max_pcc:0.24922784104917503\n",
      "Epoch 300: Loss 1.387763261795044\n",
      "(0.252387284245102, 0.16782079597979088, 0.6067699396150329)\n",
      "max_pcc:0.27200232679663067\n",
      "Epoch 300: Loss 1.3219941854476929\n",
      "(0.24950875670985626, 0.15288702987179403, 0.5900398510122884)\n",
      "max_pcc:0.24950875670985626\n",
      "Epoch 300: Loss 1.3168628215789795\n",
      "(0.249008639036683, 0.11730480149731466, 0.615784235097889)\n",
      "max_pcc:0.25531366828271335\n",
      "Epoch 310: Loss 1.3429656028747559\n",
      "(0.24377599065825237, 0.15419879169636583, 0.6129892722707075)\n",
      "max_pcc:0.24583410047504156\n",
      "Epoch 310: Loss 1.3368393182754517\n",
      "(0.24480021701849605, 0.17158586352262653, 0.6047197473685594)\n",
      "max_pcc:0.24922784104917503\n",
      "Epoch 310: Loss 1.3664538860321045\n",
      "(0.27411434824216596, 0.1875627110867768, 0.6019293396966541)\n",
      "max_pcc:0.27884392763517296\n",
      "Epoch 310: Loss 1.3192722797393799\n",
      "(0.24717229679925987, 0.156908452615979, 0.5900897119946605)\n",
      "max_pcc:0.24990348300526918\n",
      "Epoch 310: Loss 1.3052455186843872\n",
      "(0.25585499556928415, 0.12000959737658974, 0.6155618495686471)\n",
      "max_pcc:0.25585499556928415\n",
      "Epoch 320: Loss 1.3509422540664673\n",
      "(0.23359549943986097, 0.14542248027273247, 0.615050915540617)\n",
      "max_pcc:0.24583410047504156\n",
      "Epoch 320: Loss 1.3276833295822144\n",
      "(0.24697232071995553, 0.15769798207859897, 0.6016899866791839)\n",
      "max_pcc:0.2565297725735831\n",
      "Epoch 320: Loss 1.3591926097869873\n",
      "(0.2772472968139096, 0.1929041132661878, 0.5995633515305842)\n",
      "max_pcc:0.27884392763517296\n",
      "Epoch 320: Loss 1.3086743354797363\n",
      "(0.25677947801563333, 0.15366785913525904, 0.5882166355531344)\n",
      "max_pcc:0.25677947801563333\n",
      "Epoch 320: Loss 1.3040199279785156\n",
      "(0.2579613861907596, 0.11906695048269204, 0.6138310619327481)\n",
      "max_pcc:0.25918787614637095\n",
      "Epoch 330: Loss 1.34036123752594\n",
      "(0.2377950255832736, 0.15182215979105185, 0.6129420502645261)\n",
      "max_pcc:0.24583410047504156\n",
      "Epoch 330: Loss 1.3159897327423096\n",
      "(0.254964862677983, 0.16846583699154447, 0.6031631108559121)\n",
      "max_pcc:0.2605165385952395\n",
      "Epoch 330: Loss 1.3585546016693115\n",
      "(0.27741330112972706, 0.20008906320717235, 0.600299717203115)\n",
      "max_pcc:0.28388545298776663\n",
      "Epoch 330: Loss 1.340308427810669\n",
      "(0.24010458794495412, 0.15728792460152805, 0.5908090736625935)\n",
      "max_pcc:0.25705206112125284\n",
      "Epoch 330: Loss 1.29987370967865\n",
      "(0.2597622935889531, 0.11820172692713546, 0.6149870411070959)\n",
      "max_pcc:0.2600951093720736\n",
      "Epoch 340: Loss 1.3494362831115723\n",
      "(0.23315275154689477, 0.1548626870499662, 0.6125782148658149)\n",
      "max_pcc:0.2464063295659646\n",
      "Epoch 340: Loss 1.3001459836959839\n",
      "(0.2632211327270617, 0.1626605055874936, 0.5993809106310036)\n",
      "max_pcc:0.2688793857649716\n",
      "Epoch 340: Loss 1.3485747575759888\n",
      "(0.27553700077156534, 0.1903100682534927, 0.6000780751647937)\n",
      "max_pcc:0.28388545298776663\n",
      "Epoch 340: Loss 1.3286772966384888\n",
      "(0.24439579506896156, 0.16951707924997128, 0.5901205857915506)\n",
      "max_pcc:0.25705206112125284\n",
      "Epoch 340: Loss 1.298013687133789\n",
      "(0.2638084277954648, 0.12377009382226609, 0.6125008936266355)\n",
      "max_pcc:0.2638084277954648\n",
      "We are calculating the : impute matrix\n",
      "\n"
     ]
    }
   ],
   "source": [
    "seed=2022\n",
    "KFOLD1 = list(range(len(train_gene)-5))\n",
    "with multiprocessing.Pool(5) as pool:\n",
    "    impute_count1 = pd.concat(pool.map(partial(coGCN_impute,seed), KFOLD1), axis = 1)\n",
    "\n",
    "\n",
    "KFOLD2 = list(range(5,len(train_gene)))\n",
    "with multiprocessing.Pool(5) as pool:\n",
    "    impute_count2 = pd.concat(pool.map(partial(coGCN_impute,seed), KFOLD2), axis = 1)\n",
    "\n",
    "impute_count = pd.concat([impute_count1,impute_count2], axis = 1)\n",
    "impute_count = impute_count.loc[:,np.unique(impute_count.columns)]\n",
    "\n",
    "raw_count=pd.DataFrame(Spatial_data_adata.X, \n",
    "                index=Spatial_data_adata.obs_names, \n",
    "                columns=Spatial_data_adata.var_names)\n",
    "raw_count = raw_count.loc[:,np.unique(raw_count.columns)]\n",
    "result_metric=CalDataMetric(raw_count,impute_count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We are calculating the : impute matrix\n",
      "\n",
      "We are calculating the : impute matrix\n",
      "\n",
      "We are calculating the : impute matrix\n",
      "\n",
      "We are calculating the : impute matrix\n",
      "\n",
      "We are calculating the : impute matrix\n",
      "\n",
      "We are calculating the : impute matrix\n",
      "\n",
      "We are calculating the : impute matrix\n",
      "\n",
      "We are calculating the : impute matrix\n",
      "\n",
      "We are calculating the : impute matrix\n",
      "\n",
      "We are calculating the : impute matrix\n",
      "\n",
      "2872\n",
      "PCC     0.226725\n",
      "SSIM    0.139050\n",
      "RMSE    1.238718\n",
      "JS      0.400856\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "best_result=0\n",
    "for i in random.sample(range(1000, 3000), 10):\n",
    "    seed=i\n",
    "    KFOLD1 = list(range(len(train_gene)-5))\n",
    "    with multiprocessing.Pool(5) as pool:\n",
    "        impute_count1 = pd.concat(pool.map(partial(coGCN_impute,seed), KFOLD1), axis = 1)\n",
    "\n",
    "    KFOLD2 = list(range(5,len(train_gene)))\n",
    "    with multiprocessing.Pool(5) as pool:\n",
    "        impute_count2 = pd.concat(pool.map(partial(coGCN_impute,seed), KFOLD2), axis = 1)\n",
    "\n",
    "    impute_count = pd.concat([impute_count1,impute_count2], axis = 1)\n",
    "    impute_count = impute_count.loc[:,np.unique(impute_count.columns)]\n",
    "\n",
    "    raw_count=pd.DataFrame(Spatial_data_adata.X, \n",
    "                    index=Spatial_data_adata.obs_names, \n",
    "                    columns=Spatial_data_adata.var_names)\n",
    "    raw_count = raw_count.loc[:,np.unique(raw_count.columns)]\n",
    "    result_metric=CalDataMetric(raw_count,impute_count)\n",
    "\n",
    "    if (result_metric.mean(1)[0]+result_metric.mean(1)[1])/2 > best_result:\n",
    "        best_seed=i\n",
    "        best_result_metric=result_metric\n",
    "\n",
    "print(best_seed)\n",
    "print(best_result_metric.mean(1))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         ACTA2   ADAMTS2   ADAMTS4    ADRA1B       ALK    ANKFN1      ANO4  \\\n",
      "PCC   0.215621  0.139919  0.369790  0.169702  0.408535  0.118463  0.161307   \n",
      "SSIM  0.165630  0.036011  0.081341  0.086854  0.113111  0.024994  0.087582   \n",
      "RMSE  1.252501  1.311550  1.122684  1.288641  1.087625  1.327808  1.295139   \n",
      "JS    0.345343  0.543283  0.315941  0.500355  0.394346  0.621286  0.473748   \n",
      "\n",
      "          AQP4     ASIC4  B4GALNT2  ...     UNC5B     UNC5D       UST  \\\n",
      "PCC   0.142046  0.158273  0.317447  ...  0.251240  0.232762  0.374480   \n",
      "SSIM  0.086178  0.021963  0.070251  ...  0.070539  0.117640  0.167615   \n",
      "RMSE  1.309927  1.297480  1.168377  ...  1.223732  1.238740  1.118499   \n",
      "JS    0.506479  0.559854  0.428528  ...  0.384596  0.367862  0.283758   \n",
      "\n",
      "           VIP     VIPR2       VTN      VWC2     WIPF3     WNT7B   ZFP804B  \n",
      "PCC   0.495709  0.315406  0.395359  0.480728  0.442475  0.076855  0.232585  \n",
      "SSIM  0.148870  0.212453  0.288235  0.470772  0.411483  0.015598  0.085589  \n",
      "RMSE  1.004282  1.170123  1.099674  1.019090  1.055959  1.358783  1.238882  \n",
      "JS    0.240332  0.338420  0.545285  0.131856  0.142878  0.584805  0.401982  \n",
      "\n",
      "[4 rows x 251 columns]\n",
      "PCC     0.251596\n",
      "SSIM    0.141581\n",
      "RMSE    1.218022\n",
      "JS      0.396017\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(result_metric)\n",
    "print(result_metric.mean(1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# impute_count.to_csv(DataDir + \"results/coGCN_impute.csv\", header = 1, index = 1)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9.13 ('yw')",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "ebbdff288f15729aecf796ae30123e3e6c6398eceb1e4a6b8963c1ec326e4375"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}