OTFRM.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 一、OTFRM计算"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 318,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "xxx xxx xxx xxx xxx xxx xxx xxx xxx xxx  tape  xxx xxx xxx xxx xxx xxx xxx xxx xxx xxx\n",
      "=== === === === ===  random  === === === === ===\n",
      "Inter OT-cosine similarity between PDBBind and Kinase: 0.9593\n",
      "Inter OT-cosine similarity between PDBBind and DUDE: 0.9658\n",
      "Inter OT-cosine similarity between Kinase and DUDE: 0.9894\n",
      " -> Task-PDBBind intra-sim: 0.913883, inter-sim: 0.9625, OTFRM: 0.9495\n",
      " -> Task-Kinase intra-sim: 0.978111, inter-sim: 0.9743, OTFRM: 1.0039\n",
      " -> Task-DUDE intra-sim: 0.972389, inter-sim: 0.9776, OTFRM: 0.9947\n",
      ">> Scheme-random spends time: 0.602219 secs, otfrm: {'PDBBind': 0.9494771329531567, 'Kinase': 1.00390259098607, 'DUDE': 0.9947172294212846}\n",
      "=== === === === ===  pretrained  === === === === ===\n",
      "Inter OT-cosine similarity between PDBBind and Kinase: 0.0516\n",
      "Inter OT-cosine similarity between PDBBind and DUDE: 0.0531\n",
      "Inter OT-cosine similarity between Kinase and DUDE: 0.9903\n",
      " -> Task-PDBBind intra-sim: 0.936596, inter-sim: 0.0523, OTFRM: 17.9042\n",
      " -> Task-Kinase intra-sim: 0.982967, inter-sim: 0.5209, OTFRM: 1.8870\n",
      " -> Task-DUDE intra-sim: 0.974436, inter-sim: 0.5217, OTFRM: 1.8680\n",
      ">> Scheme-pretrained spends time: 0.604732 secs, otfrm: {'PDBBind': 17.904170836612288, 'Kinase': 1.8870015076628481, 'DUDE': 1.8679504464173213}\n",
      "=== === === === ===  finetuned  === === === === ===\n",
      "Inter OT-cosine similarity between PDBBind and Kinase: 0.0503\n",
      "Inter OT-cosine similarity between PDBBind and DUDE: 0.0283\n",
      "Inter OT-cosine similarity between Kinase and DUDE: 0.0673\n",
      " -> Task-PDBBind intra-sim: 0.870318, inter-sim: 0.0393, OTFRM: 22.1431\n",
      " -> Task-Kinase intra-sim: 0.866058, inter-sim: 0.0588, OTFRM: 14.7289\n",
      " -> Task-DUDE intra-sim: 0.291449, inter-sim: 0.0478, OTFRM: 6.0936\n",
      ">> Scheme-finetuned spends time: 0.598938 secs, otfrm: {'PDBBind': 22.143063204091607, 'Kinase': 14.72891222214122, 'DUDE': 6.093582342613152}\n",
      "     PDBBind     Kinase      DUDE scheme_type\n",
      "0   0.949477   1.003903  0.994717      random\n",
      "0  17.904171   1.887002  1.867950  pretrained\n",
      "0  22.143063  14.728912  6.093582   finetuned\n",
      "xxx xxx xxx xxx xxx xxx xxx xxx xxx xxx  esm1b  xxx xxx xxx xxx xxx xxx xxx xxx xxx xxx\n",
      "=== === === === ===  random  === === === === ===\n",
      "Inter OT-cosine similarity between PDBBind and Kinase: 0.9631\n",
      "Inter OT-cosine similarity between PDBBind and DUDE: 0.9729\n",
      "Inter OT-cosine similarity between Kinase and DUDE: 0.9900\n",
      " -> Task-PDBBind intra-sim: 0.930761, inter-sim: 0.9680, OTFRM: 0.9615\n",
      " -> Task-Kinase intra-sim: 0.982573, inter-sim: 0.9766, OTFRM: 1.0062\n",
      " -> Task-DUDE intra-sim: 0.976619, inter-sim: 0.9815, OTFRM: 0.9951\n",
      ">> Scheme-random spends time: 0.598786 secs, otfrm: {'PDBBind': 0.9615446732661408, 'Kinase': 1.0061604998796287, 'DUDE': 0.99505705146464}\n",
      "=== === === === ===  pretrained  === === === === ===\n",
      "Inter OT-cosine similarity between PDBBind and Kinase: 0.0392\n",
      "Inter OT-cosine similarity between PDBBind and DUDE: 0.9728\n",
      "Inter OT-cosine similarity between Kinase and DUDE: 0.0367\n",
      " -> Task-PDBBind intra-sim: 0.924703, inter-sim: 0.5060, OTFRM: 1.8275\n",
      " -> Task-Kinase intra-sim: 0.979198, inter-sim: 0.0379, OTFRM: 25.8043\n",
      " -> Task-DUDE intra-sim: 0.971383, inter-sim: 0.5047, OTFRM: 1.9246\n",
      ">> Scheme-pretrained spends time: 0.605699 secs, otfrm: {'PDBBind': 1.8275133982299963, 'Kinase': 25.804269449674454, 'DUDE': 1.9245514223766949}\n",
      "=== === === === ===  finetuned  === === === === ===\n",
      "Inter OT-cosine similarity between PDBBind and Kinase: 0.0449\n",
      "Inter OT-cosine similarity between PDBBind and DUDE: 0.0110\n",
      "Inter OT-cosine similarity between Kinase and DUDE: 0.0252\n",
      " -> Task-PDBBind intra-sim: 0.981639, inter-sim: 0.0279, OTFRM: 35.1474\n",
      " -> Task-Kinase intra-sim: 0.899645, inter-sim: 0.0350, OTFRM: 25.6692\n",
      " -> Task-DUDE intra-sim: 0.322430, inter-sim: 0.0181, OTFRM: 17.8032\n",
      ">> Scheme-finetuned spends time: 0.597768 secs, otfrm: {'PDBBind': 35.14736259591198, 'Kinase': 25.669210739061374, 'DUDE': 17.803249433003682}\n",
      "     PDBBind     Kinase       DUDE scheme_type\n",
      "0   0.961545   1.006160   0.995057      random\n",
      "0   1.827513  25.804269   1.924551  pretrained\n",
      "0  35.147363  25.669211  17.803249   finetuned\n",
      "xxx xxx xxx xxx xxx xxx xxx xxx xxx xxx  prottrans  xxx xxx xxx xxx xxx xxx xxx xxx xxx xxx\n",
      "=== === === === ===  random  === === === === ===\n",
      "Inter OT-cosine similarity between PDBBind and Kinase: 0.9627\n",
      "Inter OT-cosine similarity between PDBBind and DUDE: 0.0437\n",
      "Inter OT-cosine similarity between Kinase and DUDE: 0.0443\n",
      " -> Task-PDBBind intra-sim: 0.928874, inter-sim: 0.5032, OTFRM: 1.8458\n",
      " -> Task-Kinase intra-sim: 0.981050, inter-sim: 0.5035, OTFRM: 1.9483\n",
      " -> Task-DUDE intra-sim: 0.968924, inter-sim: 0.0440, OTFRM: 21.9995\n",
      ">> Scheme-random spends time: 0.788013 secs, otfrm: {'PDBBind': 1.8458179368381191, 'Kinase': 1.9483458092462518, 'DUDE': 21.999513768463498}\n",
      "=== === === === ===  pretrained  === === === === ===\n",
      "Inter OT-cosine similarity between PDBBind and Kinase: 0.9572\n",
      "Inter OT-cosine similarity between PDBBind and DUDE: 0.0225\n",
      "Inter OT-cosine similarity between Kinase and DUDE: 0.0228\n",
      " -> Task-PDBBind intra-sim: 0.910659, inter-sim: 0.4898, OTFRM: 1.8592\n",
      " -> Task-Kinase intra-sim: 0.978831, inter-sim: 0.4900, OTFRM: 1.9977\n",
      " -> Task-DUDE intra-sim: 0.973351, inter-sim: 0.0226, OTFRM: 43.0452\n",
      ">> Scheme-pretrained spends time: 0.786327 secs, otfrm: {'PDBBind': 1.8591872653011383, 'Kinase': 1.9977094536891054, 'DUDE': 43.04515063537842}\n",
      "=== === === === ===  finetuned  === === === === ===\n",
      "Inter OT-cosine similarity between PDBBind and Kinase: 0.1450\n",
      "Inter OT-cosine similarity between PDBBind and DUDE: 0.0821\n",
      "Inter OT-cosine similarity between Kinase and DUDE: 0.1054\n",
      " -> Task-PDBBind intra-sim: 0.792211, inter-sim: 0.1135, OTFRM: 6.9784\n",
      " -> Task-Kinase intra-sim: 0.663760, inter-sim: 0.1252, OTFRM: 5.3020\n",
      " -> Task-DUDE intra-sim: 0.243250, inter-sim: 0.0937, OTFRM: 2.5951\n",
      ">> Scheme-finetuned spends time: 0.782928 secs, otfrm: {'PDBBind': 6.978408283572715, 'Kinase': 5.302008445783826, 'DUDE': 2.5950744153890652}\n",
      "    PDBBind    Kinase       DUDE scheme_type\n",
      "0  1.845818  1.948346  21.999514      random\n",
      "0  1.859187  1.997709  43.045151  pretrained\n",
      "0  6.978408  5.302008   2.595074   finetuned\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import time\n",
    "import os\n",
    "import re\n",
    "from ot_metric import OTFRM\n",
    "\n",
    "pro_embs_base_pth = \"/data1/brian/PLM-PLI/empirical_results/embeddings\"\n",
    "models = ['tape', 'esm1b', 'prottrans']\n",
    "tasks_list = ['PDBBind', 'Kinase', 'DUDE']\n",
    "scheme_types = ['random',  'pretrained', 'finetuned']\n",
    "\n",
    "seed = 42\n",
    "num_samples = 1000\n",
    "p = 2\n",
    "cost_metric = 'cosine'\n",
    "np.random.seed(seed)\n",
    "OT_FRM = OTFRM(method='exact', p=p, cost_metric=cost_metric, numItermax=1000000, entreg=.1)\n",
    "\n",
    "all_models_otfrm = pd.DataFrame(columns=[*tasks_list, 'scheme_type', 'model'])\n",
    "for model in models:\n",
    "    all_schemes_otfrm_df = pd.DataFrame(columns=[*tasks_list, 'scheme_type'])\n",
    "    print(\"xxx \" * 10, model, \" xxx\"* 10)\n",
    "    for scheme_type in scheme_types:\n",
    "        print(\"=== \" * 5, scheme_type, \" ===\" * 5)\n",
    "        spec_scheme_all_tasks_embs_dict = {}\n",
    "        for task_name in tasks_list:\n",
    "            # matching file\n",
    "            for pkl in os.listdir(os.path.join(pro_embs_base_pth, model)):\n",
    "                desc = pkl.split('_')\n",
    "                task_name_, scheme_type_, model_ = desc[0], desc[2], desc[4]\n",
    "                if model_==model and scheme_type_==scheme_type and task_name_==task_name:\n",
    "                    # print(pkl)\n",
    "                    pro_embs_pkl = pkl\n",
    "                \n",
    "            # loading\n",
    "            pro_embs_pth = os.path.join(pro_embs_base_pth, model, pro_embs_pkl)\n",
    "            pro_embs = pd.read_pickle(pro_embs_pth)[['pro_id', 'pro_emb']]\n",
    "            pro_embs = pro_embs.sample(frac=1).reset_index(drop=True)[:num_samples]\n",
    "            pro_embs = np.stack(pro_embs['pro_emb'].tolist(), axis=0) # list of scalar -> 2d array\n",
    "            spec_scheme_all_tasks_embs_dict[task_name]= pro_embs\n",
    "\n",
    "        t0 = time.time()\n",
    "        spec_scheme_all_tasks_otfrm_dict = OT_FRM.otfrm(spec_scheme_all_tasks_embs_dict)\n",
    "        print(\">> Scheme-{} spends time: {:1f} secs, otfrm: {}\".format(scheme_type, time.time()-t0, spec_scheme_all_tasks_otfrm_dict))\n",
    "        spec_scheme_all_tasks_otfrm_dict['scheme_type'] = scheme_type\n",
    "        spec_scheme_all_tasks_otfrm_df = pd.DataFrame({k: [v] for k,v in spec_scheme_all_tasks_otfrm_dict.items()})\n",
    "        all_schemes_otfrm_df = pd.concat([all_schemes_otfrm_df, spec_scheme_all_tasks_otfrm_df], axis=0)\n",
    "\n",
    "    # check and save\n",
    "    print(all_schemes_otfrm_df)\n",
    "    # all_schemes_otfrm_df.to_csv(f\"/data1/brian/PLM-PLI/empirical_results/{model}_all_tasks_otfrm.csv\", index=False)\n",
    "    all_schemes_otfrm_df['model'] = model\n",
    "    all_models_otfrm = pd.concat([all_models_otfrm, all_schemes_otfrm_df], axis=0)\n",
    "all_models_otfrm = all_models_otfrm.reset_index(drop=True)\n",
    "all_models_otfrm.to_csv(\"/data1/brian/PLM-PLI/empirical_results/otfrms.csv\", index=False)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 二、作图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 322,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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1dnKw5wRXYlOmztb8RStUvFgRzZ/5swoVLCBJeqJNc1WtUlFvvv+ZXvnvB1oy7w+VLF40hd6SenfCl/HBqUV//arChQvFb+vdvZOeeelN7d1/WK+8MV4zf/vWZP+Tp89p7JsfKiIiUm/853k9O2JQ/LYn2jRXy6YNNWrMm/rgk69VvFiRdAXR8qIt+85o/I9LFBcXp2/eGaQuLWvFb+vQrLpqVS6pD35YrP98/pcWfveyypdKfZbkmcu3FRgUpspli2ju1y/KyTFf/LaOzWuoRb2KeumTWVq+6bDcCjjrnWe7W+yrc8uaeu+5Hsker3BBl1SPDchL5ixao4+//l2SVKViGY0c3Eslinoq8EGI9hw8rhXrtmn95j3q2qGFvvrwP2meNJZWtrY2ci9s+nsMWScoOETDx7ynk2cuyM7WVn17tNeQJ7vLrVABXb56U7P+XqFPJ/+qGfOW6ddvPlT5sqXSfawZ85Zp8k/TVaFsKfXr0UGlSxRTWHi49h06roXL12vH3kOKjo7RK889nYl/IdJi/CeTNH/hUpUpVVKvvDhaXl4eOnDwiGbNWaClK9fqx8mfq2nj9AWsb92+oxHPjdXVazfUuWM7vfT8SEVGRunvRcv08cTJWrFmvf74+Ru5ulj+zL7j46uXX3tX5y9eUp+eXdWja0e5uDjrxs3bmr9omRYsXqEFi1cQoEKeRIAqk2S0zF1mCA4O1saNG+Xk5JRixld6FClSRB988IFefvllBQQE6LffftPQoUMz/Tg5VZ8enTXi6f7G7IRbdzK9//Fvm8+UeHpAb81ftFLnL17RlKl/acjA3rKxSX55uS+/m6LIyCiNe+tlde4zPNPHmpc45LOXZ+ECFrfvP3ZBV2/dVY92DeTuZn7mtDlR0TFauemgJKlNkxpJglOPPPtUB63cfFChYRFatfmgRvVvZ9KmT4fGGt6vrVycHHTjzr1UHx8pG/vc02azKfr37Khvf56le/6BWr1hR5oDVI+8/Z9RSYJTj7Rr1VitmtbXtt0HNWfBKr30zEAVyO9q0m7S93/q6vVb+n7iOybBKUlydHTQhLde1PFT59M1PuBx0rtuCQ1vWk4uDna66R+a6v1m77msa/eN7d/qXC0+OPWIdwEnPduyvCauOaXft19Qv3olVaSgU5rH17VGsaTBqYcKONnrtQ5V9Prfh3Q7MFxLj9zQ043LmO2jRQUvk+CUJDnls9XQpmX1ycoT8guO0IGr99W8gmeax5hb+fje1ZQ/ZkuSxr44Kj449UjPrh005+9lOnz0hL754Td9++WHqe770JETWrN+syTpxWeHJglOSZK9vZ3e++9L6vXUaO3df1hr/9mizh3aJGkz+YffFBERqaJFvDRq6ACTYzRr0kBPtGmuDZt36LNJP2jlwumpHl9e9uUfqxQXF6e6VUsnCU490r9TQ81ZuVunL93WV9NWa8qEEWk+xlvPdEsSnHqkXZNqatmgkrYfOKc5K/dozKAnVMDV/PuGYz57eRZO/fdDAAniJ401q68pX7/3r0ljbdWwTjWNm/izVv+zQ3WqV9KwgZaDxcn5YeJbqlvTcqblyTMX9cIbn6tt8wby8jCfxTxyUE+NerpXsscheyrtQkLCdPLMBdna2ujPnz5To3oJVUXatJD69eygvsP+o+s37+iZseO1av4vcnFO+/e4mfOX6/NvftPIwX309n+eSfJc69qhlerWqqq3PjStkJRYl/Yt9f7ryVe8KexGgDO9pvwxQ/MXLlXxYkU1f/bviSYjtVTVKpX05nsf6ZX/vqcl86arZIm0ZalFRkXp+Zff0NVrNzR08JMa9/Zr8du6dnpCz7/yprbv3KM33/tIv3w/yWwf/gGBGj76FYWEhmrxvD9VvmyZJNv79+mhJ4eM1rnzF9P2hyMVyKDKCZI/i41U+/PPP/Xnn39KkqZNm6bXXnsthT3Me+211zRt2rR07bt27VqFh4erY8eOcnZ2TlcfKalfv3789QMHDsjb21srVqxIMcPMkoz8Xz1uXnp2aLq+7KSkeDFvtWjSQKXNpIpLko2NjWrVqCpJunffX9du3Eq2vwOHjmnlmo0aPrifypYumenjzUteerqTuretn2ybuSt2SJIG9WiRpr7vBwYrLCJSkiyuO1CqaML9V2+aLxsxZkhnuTixJklm6ti2qaZM/kDVKpez2KZEMeNaJgGBQWnu38ujsGpVr6T6tatZbFPn4Y/kqOhoswGmazdua+nqTfIoXEgd2jSx2E+92tU0fFDyP5aBnGBMm0pmM49Ssv6UcUJJCTdnlfUwDfRKxkwqSYqIjk1T6UBJsre1UfViBdW+quWSInVKJmThH7lufl3D7wbW15udqlrso6Rbwve+gNDINI0xt1u0bI3CwsOVL5+9Oj3Rymyb7p2NEzzWbdyq+/cDUt33+o3b4q+3aGp+3cEqlSvI28v4eb1gyaok2x4EBWnP/kOSpKaN61uc3d+mhfF9/PzFKzp89GSqx5dXnbtyR1du+kmSmteraLFdq4ZVJEnbD56Tj19gqvv3KlxAtSqVUP3qpS22qVPFOEs/KjpGx8/fSHXfANJu7HNPWZg01l7uD0/4r96wM939FyzgKk93N4uX9Zv3SJIG9+tisQ9nZ8dk+/B0d7O4L1LWtUOrJMGpRwrkd9XrY0ZIkm773NXSVRvT3Pflqzf11Y/TVLlCWb01dpTZ51q3Dq313uvPqWVTy+cGHB3yydOjcLKXrM7yy618fO5qyu8zJEljx4w2nYzUrZPq1qmpoKBgffPDL2nuf868RTp34ZJcXV30+isvJNlma2ur9996VZKxvOC2nXvM9jFp8o+6cu26Pnj3dZPglPRw8uj7b+rdN/+T5vEBuQEBqgzYsmWLDAaDtmzZkuT+du3aqXbt1C1e/2+1a9dWu3amWRCpsWzZMkmpL++XHk5OCQGYqKgoOTk5qXv37ipRwnR2fmpk5P8qrxgzeqim/mx+FsYjiT+Ao6OjLbaLiYnRx1/+IG8vD415luy3jOrXualaNLB8wvDu/Qf6Z+dRVS1fXPWqWw5mmFMov7PsH5Zounv/gYX+E06mEISynpLFi6hNi4bJrkXj62c8yVyhbNqDwP16dtDf076Wg4PprOxHkr7mY0y2L1uz2ThzvFbVJBmVsbGxaR4PkJtduRcsSSpa0HLJ4RKJgj/bzvumqX93VwctfKGlOla3XDaukFPCaz06Js5sm5YVvSwG0CTJ50F4/PXyXmRjJLZhs3GiSJVKFeTkZP5xrlfHeFIrJiZWG7em/iTmlWvXJUkGg0FFi1guEVfiYdnAPfsPKTIyIYB47fotxcQY35eLpWJ/Sdq2c2+qx5dXPQpOSVIxz0IW25XwNp4Qjo2N045Dqc8m7texgeZ/+5Ic8tlbbFMof8L7hrnPaUv4nAZSr2ObJpry9XuqVim5SWPG99aAB2mfNFa6RBG9+5+RKl3C8iSTwAfBWr1hh8qUKqamDU2zNZG17O3tVL1KBXVo08xim7q1qsRfP3TsdJqP8cu0eYqMjNLAvp0tVqqxs7PV8Kd6qU7NKma3I2stWrby4WSkfOrUvq3ZNt07d5AkrduwRffv+6ep/7/mL5JkzMZyNjMpvWyZUqpezfjYz5m/2GT7tes3tGTFGnm4F1aHdq0tHqd+3VoaMWRgmsYG5BaU+MsloqOjtWrVKtna2qp79/SlrqdG4nWnqla1fGIe1nXHx3jCzNHRQaVLWg4WzlmwTGfPX9Lkz9/PkmwvJLVg9S5FRcdocM+Wad7XIZ+9uraur2Ub9mnrvlMKeBCiQgWS1jNevvFA/PXWjatneLzIHGs27NBtHz/Z29np2WHJr0+WXrd9EjLmKlUwncG979AJSVLpkkXlH/BAv81YqA1b9+jWHV/ZGGxUskQRPdGqsUY93UduhSyXqARyu+hYY0DINpmAs62NQbY2BsXExumcj/kJAxlx50FY/PVK3ml/PUZExWjOviuSpHZVvFWlCK/pR6Kjo3XuwmVJUpnSlr8fJc5SP3029YGKqIeTgmxsDMlOWshnb/9wPDG6cOmqqlWpGD++R2xsLM+atk8UCDlzjtIvKYlKFBCysU3ucUn4KXz28u1MHcOdRBlZlcpYPrkdEBSq72et1z87T+qWr78ioqJVuKCrGlQvo0HdmqhRrbRNcALykpLFi6hkccuvL0ny9TOeiK5gptx1Sop4eWj4U8mvEbdo5UaFR0RqcN/OyX4OJBYXZ/zukdr2sMy9cCEtnvl9sm0KFUyYuJPcZF5zQsPC9c+WXZKkBnVqJNkWGxub4tIKycno/kiwYfN2SamdjBSjjVt26Mm+yb+2Hzl3/qKuXTdWUKhTu4bFdvXq1NTJU2e0c/c+hYWFJxnHspVrFRcXp3p1aplMHuU5YAW81+YIBKhSISoqSuHh4Sb3J54Bmd22bt0qf39/tWrVSh4e5suBZVRMTIwmTTJm8tja2mrkyJFZchykTXR0jPYdPCpJ6tujs+ztzb+s7/sH6IdfpqthvVrq3vkJaw4xT4qJidX81TtVwNVJ3dumbyHOD17ur6joaK3eckij3vlJb4zuparliysgKFQrNx3Qb/P+kSQ9O7C9Gte2XMIGWSsyKkrh4RG6duOO1m3aqRnzlqtYEU9NHP+qatewXK8+I3btM77mWzdroKLepmvNnDlnPCF79fptdX/qJRV2K6gXRjypUiWL6o6Pn2b/vVK/z1ykpas36/dvP1SVStm/jiKQHTxdHXQzIEx+IZa/0wWGRSrmYSArKDxaIRHR6SonaMmui8aAs72tjfrWS/kEWmxsnCKiYxUQFqmj1/31x46LOn37gQY2KKW3OzNZIbGbt+4oKipKkuTpYboG2CMuzs5ydnZSaGiYrlxNfTk2r4d9xsTE6r5/gAq7FTLb7r5/QrDCx/dufIAq8Zju3Tdf3lGS/P+1P5KXeE2ne/7BFtvdDwyJv+5zL3ODz7sOX5AktWpQWUWTyeLasu+Mrt66p8HdmqhiaW9FREVr56Hzmrd6r9buOK6nuzfV+y/04EQ2kA5rNuxMNGmsb6b3HxcXp/lL1svZyVF9upnP2njk9h0/ffbtVG3bfUi3ffwUGxMrL083NapXU8MGdEu2dDgy5rZPQlZt5Qpp+81z/NQ5hYYZzwWWLlFUm7bv1ey/V+jIiTMKCQlTwQKuqlOzip7u312tm5sv9ftIQGCQvpsyS+s379St276KiIySu1tB1a9TXYP7d1Pj+mTgpUd0dHT8uk1lklnConSibafPnEt1/6cStS1bupTFdmVKGfuPjIzUhUuXVbN6woT+fQcOS5JKlSyu+/4B+n3aLP2zaatu3faRjcGgkiWLq33bVho5bJDF75JAbkeAKhWee+45Pfdc8osZZrelS5dKypzyfrGxsUkCcgEBATpx4oQmTJigQ4cOyWAw6Pvvv1eNGpZnD8B6Nm7dqbt+91Ugv6ueHzXYYruvf/hdIaGh+uDtsVYcXd61cfdx+fgFanifNmYX0E4NV2dHffPeCPXp0EhfT12uUe/8FL/N3t5W7ZvX0pNdmqlZvawJgiB1Bo1+WyfPGE9E2dvZqX+vDnr1haEqWMByOa6MOHH6gk6euSB7OzuNff5pk+1h4REKCjaedPtny25VLFdK86Z+lSRrstMTzTXypQ908OgpjXnrMy3/6we5umTN2oXA46xxWQ8tPnxdl/2C5R8SKTcX0/frI9eTlgEJicy8AFVcXJwWHLgmSRrSuIy8C6Sc3bz1vK/G/LU//nZ5T1f98nRDtansnSljyk0evRdKkrOFGbWPODk6KjQ0TA+CLAc0/q1xg7pavHytJOnQkeNq39Y0Y/pBUJAuXb4afzskJCFjrnixIipRvKhu3Lytg4ePWzzO4WMJ606FhIZZbAejWpVKysnBXmERUTp06qpGWUhmPnrmWvz1kLCITDv+yfM3dfLCTdnb2Wrs0A4W2+V3dlSbRlX03buDk5QLbNWgsto0qqLRH0zTXyt3y93NVS8+lb4S8EBeYpw0FqlrN+9o3aZdmjF/pYoV8dDED8aqdvVKmX68HXsO6+qN23qyVwfld3VJtu3iVZtUo2p5jR7SW6VLFFNwSIg2bN2npWu2aPnarXrthcF6dmjmB9Eg7dprDA7Y29upX4+0rZ1++twlScZ1vz//9jctWv6PnurbRSMH95Gdra127T+i6XOXauvOAxrcv5s+fGuMxb4279inK9dv6en+3VSxfGlFREZp555Dmrt4tdZu3KEhT3bXuDdeYEJCGiWZjORpebK+cTKSs0JDQ3Xl6jWL7f7tcqK2yU128vRM2Hbl6vUkAapH2fnXrt9U975Pq7BbIb0weoRKlyqu23d8NXvuQv02bZaWrFijP36arCqVmXyMvIcAVSqMGzdO3bp1M7n/0KFDeumll7JhRKYyc/2p7du3J1lr6hE7Ozs98cQTGj9+vFq1Mr/INKwrOCRUX33/qyTpo/dfVxEzmRSSdPT4aS1evlZDBvZW5YrMzrKGOcu3y2AwaFDPFunuIzg0XJ/+tFArNh5QqWIemjB2oMqX8lZwaLg27zmh3YfPyr1QftWoVFIFXAkuZJeJ4/+j4OAQ+d0P0K59R7RoxQYtW71ZL4wcoGeH9cvUHxkxMTH65Gvja/4/Lzyt6lXKm7QJDglNcvul0YNMSnrms7fXm6+M0FOj39Kt276av2SdnhnSJ9PGCeQUQ5uW1bKjNxQTG6c/dlzQm52qJdkeGxunaTsuJbnPJhNf03P2XdVZnyBVLVJAr7ZP3boF9UsV1txnmys8KkYXfIO08OA1vfjXftUt6aZPe9dWOc+sCY7nROHhCUEHezvL6wVJUr6HAQJzVRMs6dKxjb796Q/d8bmrP6bPU5uWTWVnl/Tn1fTZC+NLAUrGcoCJjRo6QB9/8b3OnLuordv3qHXLJkm2378foEXLVlvcH6YcHew1qFsTTVu8XVv3n9GZS7dVpVzSdeAuXffVxj2n4m9n1us6JiZWn0wx/i4bO7SDqlcobrHtT+OHWdzWtE4F9WhbR8s2HtZvf2/RwC6NVLggr20gOYOee08nzxgzKezt7NS/5xN69fmns2zS2JzFxgkKT/frnGy7QgVc1bxRbX309gtJynm1a9lIDepW03uf/k+Tf54tb0939exseX0apF1cXJz+XrpOkjR0QA95e6Wt2pDvXWN2c2xsrOYvWavPP3hV/XokTDxo2qiOGtSprudem6A5C1epbOkSGjawp0k/rq7Oatuikb6f+G6SdYZbN2ugti0aadTYDzR7wUq5F3bTmGeeSs+fmmcFBSdMLEp5MpKDQkND0zQZKTgoYbKTpfKBkuTomLDtQVDCmndhYeEKeni89Ru3qGL5spo/+3e5OCecv+ncsZ1GPDtWBw8f1ZhX39byhbPk6pJ80BtpQRnFnIBHKRXKly+vJk2amFyqVauW8s5WcOjQIV2/fl21atVS2bIZL9NUt25d7d69O/6yZ88enTx5UoGBgdqwYQPBqcdEXFyc3vtokq7fuK2Xnxumrh3bmG0XGxurj7/8QYXdCmnsi5RltIZL13y058g5Na1bSWWKW170PDnRMTF69r1ftPSffSpZzEMLf3pTT3Vvroa1Kqhtkxr6+NWnNLJfO81etk29nv9Sl2/4ZvJfgdSqVL606tWupo5tm2nC22M0e8pExcXF6ZufZ+qL76dl6rG+/t8MHT1xVn27P6FnhpifZZl4gXWDwaAWTeqabVenZpX49ac2bdubqeMEcooqRQro3S7VZTBI03Ze0qS1p3TlXrCCw6N08laAXpl3QMdvBqiSd0LJsPyZlD11/GaAvlp3SkULOuqnpxsqn13qvpYXcLJXnZJualLOQ0OalNXCF1qqa81iOnzdX4P/2Kkb/qEpd5JHJD4JFBUdlWzbyEjj9sQnGFLu30HfT5ogV1cXHT52Ui+++r6OnTyj4OAQXbt+U9/8+Lt+/n2matdMmEXr+q9Z9oMH9FbXjsbSUK+9+7Hm/L1Mvnfv6UFQkLbt3Kuhz76qAvld5VaooCSlOEsfRmOHdlD96mUUHROrZ8f/qVVbjsg/MET+gSFas/2Ynhk3TVXKFY0P+Lm6pP5xT87kP9fq6Jnr6tuhvp7pl7HfTB2bGatVhEdEadv+s5kxPCBXmzjuZc2Z8pl+mPiW+vV4QotWblLb3s/pt5mL49d9yiw3b/tq665DqleriqpUTP4czOIZk/XJu2PMrjXTt1s7NahjPK/09U+zFBmV/GcV0mbOwlU6e+GyqlYqp9fGDE/z/okn/lUqXzpJcOqR1s0bqkWTepKkn6fOVUSEadnoX74erynffJjke8kjTRvVUc/Oxu8Bv07/O0lZYKQs8cQie/uUJiPlM9knJWGp7D9fom2JJ0gFh4Qkaffyi88kCU492vet143JDzdv3dH8hctSPT4gtyBAlQFt2rRRXFyc2rRpk63jeFTer1evXpnSX4ECBZIE4ho3bqxq1arJ2ZkMjcfJZ1//pHUbtmnooL565YURFtstWLJaJ06d1esvj1aB/My8tIY5K4yLdD7d07TUT2qt2nxQh08Z1xF6dUQ3uTg5mLR5qntzVShdRLfv+uuDb+am+1jIXLWqV9LQgcZFV2fOW64Ll1JfQiA50+cu059zlqpDmyb65L2XLWZmJc6WcitUINnSfaVLFpMkXbh8PVPGCORETzcuo9+HNlbdkm6avvuSuny/RQ0/X6eBv+1UVHSs5j3XXJW9jcHcAo72crC3zfAxL/sF68XZ++TiYKepw5uoaMGUS/tZYmdro/Hda8jJ3laBYVH65p8zGR5fbpH4e8+jNSQseXQCIq0BoDq1qmvR7F/VuUMb7T1wWE8OeUH1W3ZTh55Pa/P23frf5I/1ZO+ESgxe/yoPYzAY9M0X4zX+3VflXriQPpr4rVp27KeGrXroP29NUP26NTV/xs/xGV7JlZdBAod89pr22TMaO7SDbGwMeuOr+Wo2+FM1G/ypPvppqbq1rq2pnz6j2Ifry3m65U+hx5RNX7JDfy7ZrvZNq+vjV/pmOIO6bImEygjnrvhkdHhArmecNFZVHds00YS3ntfsnz81Thr7Zba++GF6ph5r3pL1io2N1aC+yWdPpUbHtk0lSb5+93XkeOrXxkHyjp06py9/mKqi3p76ZfL4JAGE1IqLS5j416JpfYvt2rVsLEnyD3igQ0dPWWxnScd2zSRJ4RER2rpzfwqtkZiDQ8J5kqgUAryRkcbgYVomIzmmsv/EwWVHx4R9TCaPNmtsdv86tWrI7eH6Uxs3b0/1+IDcghJ/uUBmrj+FnGHi5J81a+5ijRzypN55/UWL7QIfBOnbn6aqepWK6t65ndnZPI9Ex8Qk2Z4vnz31j9MhNCxCyzbsVzEvN7VpnP512rbtPx1/vV5182UZbWxsVLdaWV24ekcHTlyUj1+AvD0KpfuYyDytmtbXbzMWKi4uTpt37FeFcpYXVE2NGXOX6YvvpqpL+xb66qP/ytbW8glyVxdnubo4KzgkNMUfYs4PA5+hrGmCPK55BU81r+CpB2FRuh0YJoNBKlbQSa6OxtfQ/RDj52PVogUyfKxLd4M1Yvpu2doY9OeIpirrkfHJIwWd8ql2iULac/metp7zUWxsHKXgZFzjyd7eXlFRUbrrd89iu5DQ0Pj3weQW2LakTOkS+n7SBEVEROjGzTuKiIyUl6e7PNwLS5J+nfqXJOPM2/LlypjsbzAY9PSA3np6QG/5+Prp3n1/OTjkU8kSxZTP3l6xsbEKCHwgSarKugSpls/eTi8+1U4vPtVON339FfAgVK7ODirhXVi2tjbyvf8gvm3V8sUydKwZS3foyz9WqXPLmvrqzYGytc34PNDEa5gGh6Z+tjcAo1rVK2rogG76beZizZy/Uk/2bK8KZdP+Hv9vkZFRWrRyg9zdCqpTu6YZ7q9sqYT3n3MXr6pRveoZ7jOvu3T1hl54/SO5ODtp2v8+VVELSyGkJHGmS4liltf6fDTpT5IuXL6mpo3qpOk4ZUuXiL9+7uKVNO2b1xXInzDBJOXJSMbMpvxpmLidP1GJ0LBk+k+clZXfNWEfl0STRd0KFUy2dF+ZUiXk7x+gi5cup3p8SAXOa+YIBKhyuEuXLun48eMqVaqU6tWrl93DgRV88uUPmj1/qZ4d8ZTeGPtcsm3PnLso/4BA+QcEqnazLsm2nTL1L015eAJFkjaunKMSxYpkypjzkuUbDygoJEzPDHgiQycn/AONdYoNBoM8kpnV6+leMP76LV9/AlSPCQ93t/jrj2qXp9fU2Uv01Y9/qnun1vryw1eTDU49UrlCGR08espkPap/C3l4wit/fkpGAZKxfF4BJ9PA7iU/43tywzIZy1457xukUdP3yM7GoD9HNlEZ98zLbPbI/zDgHBmjoIgoFXQyLSOT19jZ2alShbI6efqcrly9YbFd4m3VqqQ/AOTg4KDy5Uqb3H/pijGTtl6dGrK3T/7nl7eXh8kaGTdv+8RPImrcoE66x5eXFfdyU3EvtyT3Xb5+V5Lxu1bDGukvkz5t0TZ9NW2NureprS9eH5Cq739BIeGKio5Odl2pkNCEEkH5M6kEIZDXtGpaL77E3+Yd+zMlQLV20y7d93+gF0b0T1dWzr8lXjcnpe/uSNnFK9c1fMx7srW11fSfPlO5RMGftPL2TPjel9xjnXhtopB0TPxzduQ5kF5JJiPd9bPYzjgZyfh/m5bJSGVLJ0w0vet3TxXKm/++cPduwkSoxP27urjI1dVFwcEh8SUGLXFyMlZUCOE5gDyIAFUOl9nl/fD4iouL04SJ32newhV6cfQQvTpmlEmbBUtWqVqViqpetZIkqXqVipo//X/J9jtwxMuSpP69u+rJ3l3j7/fyKJyJo8875q7cLnt7Wz3ZOWOz6Qo9DBjExcXp7v0HFgNPPncD4q+7OnPywhpadx+pQf276IURAyy2Sbzwan7X9JdH/XX6An37yyz16tpWEz/4j0nt+tX/bJenh5sa1k2ardeyab34AJXP3XtJflw9EhcXpyvXbkmSqlYyn6UHQLpyLzg+q6pn7eLp7ufsnQcaNWOPHOxsNWNkE5UsnDQwfPJWoE7dDtST9ZNmXE7feUnTd1/Suv+0Tba8YGCYsbSIjUFyycdX/Efat22hk6fP6cy5CwoLCze7wPXhoyckSba2NmrXulmmj2H3voOSpN7dO6Zv/73G/YsXK6IG9Wpl2rjyut1HLkiSGtQoo+Lebim0Nu+3v7fo2xnr1OuJuvr81f6mn9PbjsmzcH6TANjnv67Q1v1ntWvuOIt9X7iWUNavctmi6RofkNd5uBeKv+7r558pff61aI1sbW00sHfK7+kBgUGSpEIFLU84TBzQYJ3BjDl/8apGvPSe7OzsNOPnz1WmVPq/t0lKsr5YckGDxNUo/j3xLyg4RFFR0SrsVvDfuyX0HZrQ97/XqkTy7OzsVKlieZ08dUZXrlouW594W7UqlVPdf7UqleKvX756TU0bN7DQv3Eykr29vSqWT/rbunLFCjp4+KjJelT/9iiAlpYML6QGGVQ5AWtQ5XCU98sbYmNjNe6TyZq3cIVeeX642eCUJI37ZLI2bd0Vf9vV1UV1alVL9vJIES+PJPenNLsDpg6euKizl26pc8u6cs/gWgYNapaPv77v6HmzbWJiYnXw5CVJUsH8zipb0itDx0Tq+Ny9p70HjifbZuuuA/HX69aumq7j/PTHPH37yyz179nBbHBKkr7+aYYWrdhgcn/PLm3j1yvZuHWv2f4PHjmlwAfGH83dOmZsIXcgJ+vxv636bdsFi9vn7rsqSepTt6RJUCm1Tt0O1Ijpu+Wcz06znmlqtp/NZ+5o/LJjJvcHR0TJ50G4TtyyvGh2cHiUDl8znnirWbyQ7DKhvFhu0a9XFzk6OigyMkrrNm4z22bl2k2SpE5PtJZ74bQFKt798Au9/N8PLG7fsHmHfHz9VK5sKXXv0t5k+7GTZ9S9/wjt2nPAzN7GyQRzFxgXyx774ijKL6fSxt2n1GPMd0mCPImFR0Rp8QZj4O+VIaaL3qfGT3M26tsZ69SvYwOzwSlJmvznGi1eb/6x9X8Qoqu3LM/2XrX1qCTJ2TGfWjaoZLEdkFe17jlaU6YvTLbNgwcJJ4TzJ7Mua2qdOntJR0+cU9vmDVTU2yPF9q+8O0mjX/s42TbnE61XW6VimYwOMc86c/6yho15V/ny2Wv2r1+YBKdOnrmgBUvXpanPerWrycXFmNVy8Yrl4Mflazfjr1erVD7Jts8m/6quA19I9jhJnwPpz+jNq9q3Na79/WgykjmHjxh/v9va2qpd6+ap7rtSxfIqVbJ4kj7MOfRwslOLpo1MJkO1bG5cdyo4OEQ+vnfN7h8XFxcfREscFAPyCn695mB+fn7atWuX3Nzc1KoVJxdzqqioaL342jjVbd5VEyZ+Z7I9NjZW7330lRYuXa3BT/ZS/95ddcfnrtkLstecFTskSYN6tEixbVR0jMZ8+Jvq9XxDH/3wt8n2Xh0aydvDOMvq+xmrFRhkOmNrxpItunLDV5I0om9b2aWi9Bsyx+79R7Vmww6z246fOq8//1oqSapZraKam6lBPn7iT6rb+km98vbnioqONtn+w69/6cff5+iJVo310uin5Hv3vu74+JlcYmNiTfaVpGJFPPXssH6SpCnT/5avX9IygxERkfryh2mSpNo1Kqtn5zap/MuB3OeCb5D+2ntZ/iGm6zRuPuujOXuvqLS7i97oaD7YvO2cr1pO+kcdv92kk2aCSCduBmjU9D2yNRg0qV9d2RoMuhMYZnIJjjB9L0jsq3WnFBxuujhzdEysPlp5PH7/51uxRlFi3l6eenH0UEnSj1P+jF/L6ZEVazbo8NETyu/qotfNlE4e/+lk1WnaWS//9wNFRZk+Rjdu3taGzTt00MxJi+s3bmnC59/KydFREye8bbY8UFhYmM5fvKKps+YrLi7OZPs3P/6uU2fOq2O7VunOwMqLHgSH6cJVH81cutNkW3RMjMb/sFh37wdpeO/mZsv7ffjjEtXrO16vfDpbUdExJtt/mPWP/vfXBj3RpJpeGvyEfO8H6Y5foMklNtb0MU1s0h+rFWnmebV+5wn9s+ukJOnFQe3kVoAZ9cC/+dy9r70HTyTbZuvug/HX69aqkuFjzlm0RpI0uF/y5fMTO3/xuoJDLJd9W73B+D5V1NtDtarzGZ4ep85e1PAx78nZyVGzf52kksVNs043bdurcZ//kKZ+HRzyqWfntpKMExDN/W6TpI1b90iSSpUoqlrVTYML/gEPdPX6LYvHWbV+qyRjucdWTc1n6MCyfr26P5yMFKl1GzabbbNy7T+SpE7t28jdPW3VggYP6CtJ2rR1h9m1my9fuaaTp84Y2z7Vz2R7r+6d4yeAb9hsfrLUwcNH47+jduuSvokzQE5G/Y9/OXXqlG7duqWjR48muW/DBuMM9erVq6to0bSVWAgPD9eOHcYTmf7+/vH/Puqzfv36cnNLe1mJFStWKCYmRt26dZOdXfoeSn9/fx08eDB+nP8eW7FixVStWjWL+5tz+/ZtnTx5Msl9ly5diu+zfXvT2aO5ge/de7pw6Yokye9eQvmAC5euatfD0iwF8udXjWpJv7CcPX8pPutp7oLlenXMKBUqmLAI++df/6QlK4wzfeYsWKY5D2fRpldERKT5kyg3b8ePs2TxoipZImOLRec1fv4PtH7HEVUtX1z1qqdcLu3spZvatNv4g2ruyh36z4huKpTo5IOLk4N+/eQFvTj+N924c099xkzSkF6tVL6Ut0JCI7Rp93Gt2nJIktS/cxM9P8j8lxjfe4G6cPWOJOmef8JJuYtX72jXobOSpAKuTqpRqZTZ/WHK29NdPnfv6bX3J2nxyg1q07yhihX1UkREhPYcOKbFKzcqMjJKNapW0M9fjzOZUe0f+EB/P5y998+WPTp34aqqV0mYaffnnKX6edp8SdLGbXu1cZv5DKiUvDx6kHzv3teCZev15Ij/asTgXipXuoR87t7TXwtW6eyFK6pVvZJ+mvSe7OwIbiJn8w0K1wVfY0bgveCEdVsu+AZp10XjBI6CTvaqXqyQhf0jNPC3HXq6cRmVdndRUHiUtp7z1eoTt1S9aEH9OKiB3JzNZxbP3XdFfg+PufTwdVUvllDC5YZ/qEbN2KOgcOMJjcF/mJ4sT4lnfkfZGKSjNwLU4btNGtigtCp45Vd+Rztdux+qxYeu68ydB8pnZ6O3OlVT2yqWF/HOq54f9bRu3fbR/EUrNHDYGI0cOkCeHu46cOioZs1drPyuLvpx8icmJ7T8AwI1f9EKSdI/m7br3IVL8WWUE4uLi9Nzr7yjIQP7qGb1yoqJidWRYyc1f/FKOTs5acoPE1WnVvKL3u/YtV9DR7+qPj07y6Owm27d8dHy1f/o0JET6tWtoz798M3M+w/JQxas26/7gSHq2LyGCrg66drte1r8zwGdv+qjUf1a6Y2RnU328X8Qor/X7pMkbdh9Uueu3FH1Cgkz8acv2a5f5hmz7jbuOaWNe06leVze7sbv+pv2nlaPMd9pQOdGKlPMQ5HR0dp+4JyWbTJ+x3umXyuN7t86zf0DecXuA8e0ZsNOdWlvmhFx/NR5/TlnuSSpZtUKat6otkmb8V/8ohXrtqlF4zr65tP/yj6Z8yoPgkK06p8dKlOqmJo2TH251YjISE3+eaY++O+zJr8L/py7XCfPXJQkvfnysGSPD/OOnzqvZ8aOk52dnb7++E3Z2tjojo9pdqqltZ3GT/xRy9dsVosm9fTt5++YPAZjnxuidZt2ysf3nn6d/rdeHj04yfb1m3dqz4GjMhgMeve1Zy2uF/zF93/o+8/fja9y8ci6TTu1frPxfNCYZwbJrVABc7sjGd7ennrx2RH69sdf9eMvU9WmVfMk59RWrF6vw0eOK39+V70+9kWT/cd//KWWr1qnFs0a69tJn5isF/r0oP5avGyVzl24pG//96vef+vV+G0xMTH6/KvvJUnt2rRQq+ZNTPovVrSInhs1RP+bMk1Tfp+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      "text/plain": [
       "<Figure size 1568x1008 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from matplotlib import gridspec\n",
    "\n",
    "titles_dict = {'tape': '(a) TAPE', 'esm1b': '(b) ESM1b', 'prottrans': '(c) ProtTrans'}\n",
    "# plot heatmap\n",
    "plt.rcParams['font.family'] = 'DeJavu Serif'\n",
    "plt.rcParams['font.serif'] = ['Times New Roman']\n",
    "plt.rcParams['figure.figsize'] = (7, 4.5)\n",
    "\n",
    "Fig = plt.figure(dpi=224)\n",
    "Fig_spec = gridspec.GridSpec(ncols=3, nrows=1, width_ratios=[1, 1.0, 1.2], wspace=0.2, hspace=0.0)\n",
    "# for i, (model, all_schemes_otfrm_df) in enumerate(all_models_otfrm.groupby(all_models_otfrm.model)):\n",
    "for i, model in enumerate(titles_dict.keys()):\n",
    "    all_schemes_otfrm_df = all_models_otfrm[all_models_otfrm['model']==model].reset_index(drop=True)\n",
    "    all_schemes_otfrm_df.drop(columns=['scheme_type', 'model'], inplace=True)\n",
    "    # all_schemes_otfrm_df = all_schemes_otfrm_df.astype(np.float32)\n",
    "    fig = Fig.add_subfigure(Fig_spec[i])\n",
    "    fig.suptitle(titles_dict[model])\n",
    "    # calculate ratio\n",
    "    otfrm_ratio_df = pd.DataFrame(columns=['PT / RI', 'FT / PT'])\n",
    "    otfrm_ratio_df['PT / RI'] = (all_schemes_otfrm_df.iloc[1] / all_schemes_otfrm_df.iloc[0]).tolist()\n",
    "    otfrm_ratio_df['FT / PT'] = (all_schemes_otfrm_df.iloc[2] / all_schemes_otfrm_df.iloc[1]).tolist()\n",
    "\n",
    "    # the given number of width/height ratios have to match the number of columns/rows of the grid\n",
    "    spec = gridspec.GridSpec(ncols=1, nrows=2, height_ratios=[1, 1], wspace=0.5, hspace=-0.15)\n",
    "\n",
    "    ax1 = fig.add_subplot(spec[0])\n",
    "    mappable_obj = ax1.imshow(all_schemes_otfrm_df[tasks_list], cmap='OrRd') # get mappable object for fig.colorbar()\n",
    "    plt.cla()\n",
    "    ax1 = sns.heatmap(all_schemes_otfrm_df[tasks_list], cmap='OrRd', annot=True, fmt='.2f', annot_kws={'size': 'small'}, cbar=False, linewidths=1, vmin=0, vmax=45)\n",
    "    ax1.set_xticklabels(['PDBbind', 'Kinase', 'DUD-E'],#  \n",
    "                        rotation=0, fontsize='small', ha='center')\n",
    "    ax1.xaxis.tick_top()\n",
    "    ax1.tick_params(axis=u'both', which=u'both', length=0)\n",
    "    fig.add_subplot(spec[1], aspect=4/4)\n",
    "    ax2 = sns.heatmap(otfrm_ratio_df.T, cmap='OrRd', annot=True, fmt='.2f', annot_kws={'size': 'small'}, cbar=False, linewidths=1, vmin=0, vmax=45)\n",
    "    ax2.get_xaxis().set_visible(False)\n",
    "    ax2.tick_params(axis=u'both', which=u'both', length=0)\n",
    "\n",
    "    if i == 0:\n",
    "        ax1.set_yticklabels(['Random', 'Pretrained', 'Finetuned'], fontsize='small', rotation='horizontal')\n",
    "        ax2.set_yticklabels(otfrm_ratio_df.columns, rotation='horizontal', size='small')\n",
    "    else:\n",
    "        ax1.set_yticklabels(\"\")\n",
    "        ax2.set_yticklabels(\"\")\n",
    "\n",
    "cb = fig.colorbar(mappable_obj, ax=[ax1, ax2], location='right', fraction=0.05, pad=0.1, aspect=30, anchor=(0.0, 0.8))\n",
    "cb.outline.set_visible(False) # hide outline of colorbar\n",
    "plt.suptitle('OTFRM of different PLMs on downstream PLI tasks', size='x-large', y=1.05)\n",
    "plt.savefig('./paper_figs/Fig3a.OTFRM.jpg', dpi=2048, bbox_inches='tight')"
   ]
  }
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