mole_broad_spectrum_parallel/workflow/04.new_predictions.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# New predictions    \n",
    "### Author: Roberto Olayo-Alarcon\n",
    "  \n",
    "In this noteboook we use the models we built in the previous notebook to make predictions on the MedChemExpress library, as well as Halicin and Abaucin\n",
    "  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import re\n",
    "import pickle\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "\n",
    "from scipy.stats.mstats import gmean\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "from xgboost import XGBClassifier\n",
    "\n",
    "from dataset.dataset_representation import process_dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set up directories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "MODEL_DIR = \"../data/03.model_evaluation/\"\n",
    "PROCESSED_DATA_DIR = \"../data/01.prepare_training_data/\"\n",
    "RAW_DATA_DIR = \"../raw_data/\"\n",
    "\n",
    "OUTPUT_DIR = \"../data/04.new_predictions\"\n",
    "os.makedirs(OUTPUT_DIR, exist_ok=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# MolE model\n",
    "with open(os.path.join(MODEL_DIR, \"MolE-XGBoost-08.03.2024_14.20.pkl\"), \"rb\") as file:\n",
    "    mole_model = pickle.load(file)\n",
    "\n",
    "# ECFP4 model\n",
    "with open(os.path.join(MODEL_DIR, \"ecfp4-XGBoost-08.03.2024_14.20.pkl\"), \"rb\") as file:\n",
    "    ecfp4_model = pickle.load(file)\n",
    "\n",
    "# ChemDesc model\n",
    "with open(os.path.join(MODEL_DIR, \"chemDesc-XGBoost-08.03.2024_14.20.pkl\"), \"rb\") as file:\n",
    "    chemDesc_model = pickle.load(file)\n",
    "\n",
    "# Read optimized parameters\n",
    "optimized_parameters = pd.read_csv(os.path.join(MODEL_DIR, \"optimal_thresholds.tsv.gz\"), sep='\\t')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prepare representations for Halicin and Abaucin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the dictionary with SMILES\n",
    "novel_abx = {\"compound\": [\"Halicin\", \"Abaucin\"],\n",
    "            \"pchem_id\": [11837140, 10000456],\n",
    "             \"pchem_canonical_smiles\": [\"C1=C(SC(=N1)SC2=NN=C(S2)N)[N+](=O)[O-]\", \"C1CN(CCC12C3=CC=CC=C3NC(=O)O2)CCC4=CC=C(C=C4)C(F)(F)F\"],\n",
    "             \"pchem_isomeric_smiles\": [\"C1=C(SC(=N1)SC2=NN=C(S2)N)[N+](=O)[O-]\", \"C1CN(CCC12C3=CC=CC=C3NC(=O)O2)CCC4=CC=C(C=C4)C(F)(F)F\"]}\n",
    "\n",
    "pd.DataFrame(novel_abx).to_csv(os.path.join(OUTPUT_DIR, \"novel_abx_smiles.tsv.gz\"), sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Representation dimension (1000) - Embedding dimension (8000)\n",
      "../pretrained_model/model_ginconcat_btwin_100k_d8000_l0.0001/model.pth\n",
      "x_embedding1.weight\n",
      "x_embedding2.weight\n",
      "gnns.0.mlp.0.weight\n",
      "gnns.0.mlp.0.bias\n",
      "gnns.0.mlp.1.weight\n",
      "gnns.0.mlp.1.bias\n",
      "gnns.0.mlp.1.running_mean\n",
      "gnns.0.mlp.1.running_var\n",
      "gnns.0.mlp.1.num_batches_tracked\n",
      "gnns.0.mlp.3.weight\n",
      "gnns.0.mlp.3.bias\n",
      "gnns.0.edge_embedding1.weight\n",
      "gnns.0.edge_embedding2.weight\n",
      "gnns.1.mlp.0.weight\n",
      "gnns.1.mlp.0.bias\n",
      "gnns.1.mlp.1.weight\n",
      "gnns.1.mlp.1.bias\n",
      "gnns.1.mlp.1.running_mean\n",
      "gnns.1.mlp.1.running_var\n",
      "gnns.1.mlp.1.num_batches_tracked\n",
      "gnns.1.mlp.3.weight\n",
      "gnns.1.mlp.3.bias\n",
      "gnns.1.edge_embedding1.weight\n",
      "gnns.1.edge_embedding2.weight\n",
      "gnns.2.mlp.0.weight\n",
      "gnns.2.mlp.0.bias\n",
      "gnns.2.mlp.1.weight\n",
      "gnns.2.mlp.1.bias\n",
      "gnns.2.mlp.1.running_mean\n",
      "gnns.2.mlp.1.running_var\n",
      "gnns.2.mlp.1.num_batches_tracked\n",
      "gnns.2.mlp.3.weight\n",
      "gnns.2.mlp.3.bias\n",
      "gnns.2.edge_embedding1.weight\n",
      "gnns.2.edge_embedding2.weight\n",
      "gnns.3.mlp.0.weight\n",
      "gnns.3.mlp.0.bias\n",
      "gnns.3.mlp.1.weight\n",
      "gnns.3.mlp.1.bias\n",
      "gnns.3.mlp.1.running_mean\n",
      "gnns.3.mlp.1.running_var\n",
      "gnns.3.mlp.1.num_batches_tracked\n",
      "gnns.3.mlp.3.weight\n",
      "gnns.3.mlp.3.bias\n",
      "gnns.3.edge_embedding1.weight\n",
      "gnns.3.edge_embedding2.weight\n",
      "gnns.4.mlp.0.weight\n",
      "gnns.4.mlp.0.bias\n",
      "gnns.4.mlp.1.weight\n",
      "gnns.4.mlp.1.bias\n",
      "gnns.4.mlp.1.running_mean\n",
      "gnns.4.mlp.1.running_var\n",
      "gnns.4.mlp.1.num_batches_tracked\n",
      "gnns.4.mlp.3.weight\n",
      "gnns.4.mlp.3.bias\n",
      "gnns.4.edge_embedding1.weight\n",
      "gnns.4.edge_embedding2.weight\n",
      "batch_norms.0.weight\n",
      "batch_norms.0.bias\n",
      "batch_norms.0.running_mean\n",
      "batch_norms.0.running_var\n",
      "batch_norms.0.num_batches_tracked\n",
      "batch_norms.1.weight\n",
      "batch_norms.1.bias\n",
      "batch_norms.1.running_mean\n",
      "batch_norms.1.running_var\n",
      "batch_norms.1.num_batches_tracked\n",
      "batch_norms.2.weight\n",
      "batch_norms.2.bias\n",
      "batch_norms.2.running_mean\n",
      "batch_norms.2.running_var\n",
      "batch_norms.2.num_batches_tracked\n",
      "batch_norms.3.weight\n",
      "batch_norms.3.bias\n",
      "batch_norms.3.running_mean\n",
      "batch_norms.3.running_var\n",
      "batch_norms.3.num_batches_tracked\n",
      "batch_norms.4.weight\n",
      "batch_norms.4.bias\n",
      "batch_norms.4.running_mean\n",
      "batch_norms.4.running_var\n",
      "batch_norms.4.num_batches_tracked\n",
      "feat_lin.weight\n",
      "feat_lin.bias\n",
      "out_lin.0.weight\n",
      "out_lin.0.bias\n",
      "out_lin.1.weight\n",
      "out_lin.1.bias\n",
      "out_lin.1.running_mean\n",
      "out_lin.1.running_var\n",
      "out_lin.1.num_batches_tracked\n",
      "out_lin.3.weight\n",
      "out_lin.3.bias\n",
      "out_lin.4.weight\n",
      "out_lin.4.bias\n",
      "out_lin.4.running_mean\n",
      "out_lin.4.running_var\n",
      "out_lin.4.num_batches_tracked\n",
      "out_lin.6.weight\n",
      "out_lin.6.bias\n"
     ]
    }
   ],
   "source": [
    "mole_novel = process_dataset(dataset_path = os.path.join(OUTPUT_DIR, \"novel_abx_smiles.tsv.gz\"), \n",
    "                                                  pretrain_architecture = \"gin_concat\", \n",
    "                                                  pretrained_model = \"model_ginconcat_btwin_100k_d8000_l0.0001\", \n",
    "                                                  dataset_split=False,\n",
    "                                                  smile_column_str = \"pchem_canonical_smiles\", \n",
    "                                                  id_column_str = \"compound\")\n",
    "\n",
    "#mole_novel.to_csv(os.path.join(OUTPUT_DIR, \"MolE_novel_abx.tsv.gz\"), sep='\\t')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prepare representations for MedChemExpress"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Representation dimension (1000) - Embedding dimension (8000)\n",
      "../pretrained_model/model_ginconcat_btwin_100k_d8000_l0.0001/model.pth\n",
      "x_embedding1.weight\n",
      "x_embedding2.weight\n",
      "gnns.0.mlp.0.weight\n",
      "gnns.0.mlp.0.bias\n",
      "gnns.0.mlp.1.weight\n",
      "gnns.0.mlp.1.bias\n",
      "gnns.0.mlp.1.running_mean\n",
      "gnns.0.mlp.1.running_var\n",
      "gnns.0.mlp.1.num_batches_tracked\n",
      "gnns.0.mlp.3.weight\n",
      "gnns.0.mlp.3.bias\n",
      "gnns.0.edge_embedding1.weight\n",
      "gnns.0.edge_embedding2.weight\n",
      "gnns.1.mlp.0.weight\n",
      "gnns.1.mlp.0.bias\n",
      "gnns.1.mlp.1.weight\n",
      "gnns.1.mlp.1.bias\n",
      "gnns.1.mlp.1.running_mean\n",
      "gnns.1.mlp.1.running_var\n",
      "gnns.1.mlp.1.num_batches_tracked\n",
      "gnns.1.mlp.3.weight\n",
      "gnns.1.mlp.3.bias\n",
      "gnns.1.edge_embedding1.weight\n",
      "gnns.1.edge_embedding2.weight\n",
      "gnns.2.mlp.0.weight\n",
      "gnns.2.mlp.0.bias\n",
      "gnns.2.mlp.1.weight\n",
      "gnns.2.mlp.1.bias\n",
      "gnns.2.mlp.1.running_mean\n",
      "gnns.2.mlp.1.running_var\n",
      "gnns.2.mlp.1.num_batches_tracked\n",
      "gnns.2.mlp.3.weight\n",
      "gnns.2.mlp.3.bias\n",
      "gnns.2.edge_embedding1.weight\n",
      "gnns.2.edge_embedding2.weight\n",
      "gnns.3.mlp.0.weight\n",
      "gnns.3.mlp.0.bias\n",
      "gnns.3.mlp.1.weight\n",
      "gnns.3.mlp.1.bias\n",
      "gnns.3.mlp.1.running_mean\n",
      "gnns.3.mlp.1.running_var\n",
      "gnns.3.mlp.1.num_batches_tracked\n",
      "gnns.3.mlp.3.weight\n",
      "gnns.3.mlp.3.bias\n",
      "gnns.3.edge_embedding1.weight\n",
      "gnns.3.edge_embedding2.weight\n",
      "gnns.4.mlp.0.weight\n",
      "gnns.4.mlp.0.bias\n",
      "gnns.4.mlp.1.weight\n",
      "gnns.4.mlp.1.bias\n",
      "gnns.4.mlp.1.running_mean\n",
      "gnns.4.mlp.1.running_var\n",
      "gnns.4.mlp.1.num_batches_tracked\n",
      "gnns.4.mlp.3.weight\n",
      "gnns.4.mlp.3.bias\n",
      "gnns.4.edge_embedding1.weight\n",
      "gnns.4.edge_embedding2.weight\n",
      "batch_norms.0.weight\n",
      "batch_norms.0.bias\n",
      "batch_norms.0.running_mean\n",
      "batch_norms.0.running_var\n",
      "batch_norms.0.num_batches_tracked\n",
      "batch_norms.1.weight\n",
      "batch_norms.1.bias\n",
      "batch_norms.1.running_mean\n",
      "batch_norms.1.running_var\n",
      "batch_norms.1.num_batches_tracked\n",
      "batch_norms.2.weight\n",
      "batch_norms.2.bias\n",
      "batch_norms.2.running_mean\n",
      "batch_norms.2.running_var\n",
      "batch_norms.2.num_batches_tracked\n",
      "batch_norms.3.weight\n",
      "batch_norms.3.bias\n",
      "batch_norms.3.running_mean\n",
      "batch_norms.3.running_var\n",
      "batch_norms.3.num_batches_tracked\n",
      "batch_norms.4.weight\n",
      "batch_norms.4.bias\n",
      "batch_norms.4.running_mean\n",
      "batch_norms.4.running_var\n",
      "batch_norms.4.num_batches_tracked\n",
      "feat_lin.weight\n",
      "feat_lin.bias\n",
      "out_lin.0.weight\n",
      "out_lin.0.bias\n",
      "out_lin.1.weight\n",
      "out_lin.1.bias\n",
      "out_lin.1.running_mean\n",
      "out_lin.1.running_var\n",
      "out_lin.1.num_batches_tracked\n",
      "out_lin.3.weight\n",
      "out_lin.3.bias\n",
      "out_lin.4.weight\n",
      "out_lin.4.bias\n",
      "out_lin.4.running_mean\n",
      "out_lin.4.running_var\n",
      "out_lin.4.num_batches_tracked\n",
      "out_lin.6.weight\n",
      "out_lin.6.bias\n"
     ]
    }
   ],
   "source": [
    "mole_mce = process_dataset(dataset_path = os.path.join(RAW_DATA_DIR, \"medchemexpress\", \"chemical_library_cleaned.tsv.gz\"), \n",
    "                                                  pretrain_architecture = \"gin_concat\", \n",
    "                                                  pretrained_model = \"model_ginconcat_btwin_100k_d8000_l0.0001\", \n",
    "                                                  dataset_split=False,\n",
    "                                                  smile_column_str = \"rdkit_no_salt\", \n",
    "                                                  id_column_str = \"Catalog Number\")\n",
    "\n",
    "#mole_mce.to_csv(os.path.join(OUTPUT_DIR, \"MolE_representation_medchemexpress.tsv.gz\"), sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "ecfp4_mce = process_dataset(dataset_path = os.path.join(RAW_DATA_DIR, \"medchemexpress\", \"chemical_library_cleaned.tsv.gz\"), \n",
    "                            pretrained_model = \"ECFP4\", \n",
    "                            \n",
    "                            dataset_split=False,\n",
    "                            smile_column_str = \"rdkit_no_salt\", \n",
    "                            id_column_str = \"Catalog Number\")\n",
    "\n",
    "#ecfp4_mce.to_csv(os.path.join(OUTPUT_DIR, \"ecfp4_representation_medchemexpress.tsv.gz\"), sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Could not compute descriptors for HY-B1831A\n",
      "Could not compute descriptors for HY-N0239\n",
      "Could not compute descriptors for HY-15991\n",
      "Could not compute descriptors for HY-15664\n",
      "Could not compute descriptors for HY-N2031\n",
      "Could not compute descriptors for HY-N1981\n",
      "Could not compute descriptors for HY-P0163\n",
      "Could not compute descriptors for HY-B2136\n",
      "Could not compute descriptors for HY-B2239\n",
      "Could not compute descriptors for HY-13581A\n",
      "Could not compute descriptors for HY-17565\n",
      "Could not compute descriptors for HY-P0009A\n",
      "Could not compute descriptors for HY-113498\n",
      "Could not compute descriptors for HY-17565A\n",
      "Could not compute descriptors for HY-B0108\n",
      "Could not compute descriptors for HY-17586\n",
      "Could not compute descriptors for HY-16168A\n",
      "Could not compute descriptors for HY-107799\n",
      "Could not compute descriptors for HY-P0059\n",
      "Could not compute descriptors for HY-N0062\n",
      "Could not compute descriptors for HY-N0118\n",
      "Could not compute descriptors for HY-B2235\n",
      "Could not compute descriptors for HY-N7075\n"
     ]
    }
   ],
   "source": [
    "chemdesc_mce = process_dataset(dataset_path = os.path.join(RAW_DATA_DIR, \"medchemexpress\", \"chemical_library_cleaned.tsv.gz\"), \n",
    "                            pretrained_model = \"ChemDesc\", \n",
    "                            dataset_split=False,\n",
    "                            smile_column_str = \"pchem_isomeric_smile\", \n",
    "                            id_column_str = \"Catalog Number\")\n",
    "\n",
    "#chemdesc_mce.to_csv(os.path.join(OUTPUT_DIR, \"chemDesc_representation_medchemexpress.tsv.gz\"), sep='\\t')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Predictions for novel antibiotics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/roberto_olayo/miniconda3/envs/mole_test/lib/python3.8/site-packages/openpyxl/worksheet/_reader.py:329: UserWarning: Unknown extension is not supported and will be removed\n",
      "  warn(msg)\n"
     ]
    }
   ],
   "source": [
    "# Results from screening\n",
    "maier_screen = pd.read_csv(os.path.join(PROCESSED_DATA_DIR, \"maier_screening_results.tsv.gz\"), sep='\\t', index_col=0)\n",
    "\n",
    "# Additional information for strains\n",
    "maier_strains = pd.read_excel(os.path.join(RAW_DATA_DIR, \"maier_microbiome\", \"strain_info_SF2.xlsx\"),\n",
    "                             skiprows=[0,1, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54], \n",
    "                             index_col=\"NT data base\")\n",
    "\n",
    "# Additional information on chemical library\n",
    "maier_library = pd.read_excel(os.path.join(RAW_DATA_DIR, \"maier_microbiome\", \"chem_library_info_SF1.xlsx\"))\n",
    "\n",
    "# Prepare the OHE of the strains\n",
    "def prep_ohe(categories):\n",
    "\n",
    "    \"\"\"\n",
    "    Prepare one-hot encoding for strain variables.\n",
    "\n",
    "    This function creates a one-hot encoding representation of the provided categorical variables.\n",
    "    It fits a OneHotEncoder to the categories and transforms them into a pandas DataFrame.\n",
    "\n",
    "    Parameters:\n",
    "    - categories (array-like): Array-like object containing categorical variables.\n",
    "\n",
    "    Returns:\n",
    "    - cat_ohe (pandas.DataFrame): DataFrame representing the one-hot encoded categorical variables.\n",
    "    \"\"\"\n",
    "\n",
    "    # Prepare OHE\n",
    "    ohe = OneHotEncoder(sparse=False)\n",
    "\n",
    "    # Fit OHE\n",
    "    ohe.fit(pd.DataFrame(categories))\n",
    "\n",
    "    # Prepare OHE\n",
    "    cat_ohe = pd.DataFrame(ohe.transform(pd.DataFrame(categories)), columns=categories, index=categories)\n",
    "\n",
    "    return cat_ohe\n",
    "\n",
    "# Prepare the input for the prediction\n",
    "def add_strains(chemfeats_df, ohe_df):\n",
    "\n",
    "    \"\"\"\n",
    "    Add strains to chemical features using Cartesian product merge.\n",
    "\n",
    "    This function adds strains to chemical features using Cartesian product merge\n",
    "    between the chemical features DataFrame and the one-hot encoded strains DataFrame.\n",
    "\n",
    "    Parameters:\n",
    "    - chemfeats_df (pandas.DataFrame): DataFrame containing chemical features.\n",
    "    - ohe_df (pandas.DataFrame): DataFrame containing one-hot encoded strains.\n",
    "\n",
    "    Returns:\n",
    "    - xpred (pandas.DataFrame): DataFrame containing chemical features with added strains.\n",
    "    \"\"\"\n",
    "\n",
    "    # Prepare chemical features\n",
    "    chemfe = chemfeats_df.reset_index().rename(columns={\"index\": \"chem_id\"})\n",
    "    chemfe[\"chem_id\"] = chemfe[\"chem_id\"].astype(str) \n",
    "\n",
    "    # Prepare OHE\n",
    "    sohe = ohe_df.reset_index().rename(columns={\"index\": \"strain_name\"})\n",
    "\n",
    "    # Cartesian product merge\n",
    "    xpred = chemfe.merge(sohe, how=\"cross\")\n",
    "    xpred[\"pred_id\"] = xpred[\"chem_id\"].str.cat(xpred[\"strain_name\"], sep=\":\")\n",
    "\n",
    "    xpred = xpred.set_index(\"pred_id\")\n",
    "    xpred = xpred.drop(columns=[\"chem_id\", \"strain_name\"])\n",
    "\n",
    "    # Make sure correct number of rows\n",
    "    assert xpred.shape[0] == (chemfeats_df.shape[0] * ohe_df.shape[0])\n",
    "\n",
    "    # Make sure correct number of features\n",
    "    assert xpred.shape[1] == (chemfeats_df.shape[1] + ohe_df.shape[1])\n",
    "    \n",
    "    return xpred\n",
    "\n",
    "# Function to make predictions\n",
    "def make_predictions(model, chemrep_df, score_threshold, strain_categories = maier_screen.columns):\n",
    "\n",
    "    \"\"\"\n",
    "    Make predictions using a trained model on chemical representations with added strains.\n",
    "\n",
    "    This function makes predictions using a trained model on chemical representations with added strains.\n",
    "    It applies a score threshold to the predicted probabilities and prepares the predictions for output.\n",
    "\n",
    "    Parameters:\n",
    "    - model: Trained model for making predictions.\n",
    "    - chemrep_df (pandas.DataFrame): DataFrame containing chemical representations.\n",
    "    - score_threshold (float): Threshold applied to scores for classification into growth or no-growth.\n",
    "    - strain_categories (array-like): Array-like object containing strain categories (default is maier_screen.columns).\n",
    "\n",
    "    Returns:\n",
    "    - pred_df (pandas.DataFrame): DataFrame containing predictions with chemical IDs and strain names.\n",
    "    \"\"\"\n",
    "\n",
    "    # Prepare the input for the prediction\n",
    "    strain_ohe = prep_ohe(strain_categories)\n",
    "    x_input = add_strains(chemrep_df, strain_ohe)\n",
    "\n",
    "    # Make the prediction\n",
    "    y_pred = model.predict_proba(x_input)[:,1]\n",
    "\n",
    "    # Prepare the output\n",
    "    pred_df = pd.DataFrame(y_pred, columns=[\"pred_score\"], index=x_input.index)\n",
    "\n",
    "    # Apply the threshold\n",
    "    pred_df[\"pred_label\"] = pred_df[\"pred_score\"].apply(lambda x: 1 if x >= score_threshold else 0)\n",
    "\n",
    "    # Prepare the output\n",
    "    pred_df = pred_df.reset_index()\n",
    "    pred_df[\"chem_id\"] = pred_df[\"pred_id\"].str.split(\":\", expand=True)[0]\n",
    "    pred_df[\"strain_name\"] = pred_df[\"pred_id\"].str.split(\":\", expand=True)[1]\n",
    "    pred_df = pred_df.drop(columns=[\"pred_id\"])\n",
    "\n",
    "    return pred_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "mole_halicin_predictions = make_predictions(mole_model, mole_novel, optimized_parameters.loc[(optimized_parameters[\"representation\"]== \"MolE\") &\n",
    "                                                                                            (optimized_parameters[\"score_type\"]== \"optimized\"), \"threshold\"].values[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='strain_name', ylabel='chem_id'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 3000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mole_halicin_predictions = mole_halicin_predictions.pivot_table(index=\"chem_id\", columns=\"strain_name\", values=\"pred_label\")\n",
    "\n",
    "\n",
    "plt.figure(figsize=(30, 6))\n",
    "\n",
    "sns.heatmap(mole_halicin_predictions, cmap=\"vlag\", robust=False, center=0, \n",
    "            linewidths=0.1, linecolor=\"black\", annot=True,\n",
    "            cbar_kws={\"label\": \"Prediction Score\", \"pad\": 0.02})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Predictions for MedChemExpress"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Catalog Number</th>\n",
       "      <th>Original lib</th>\n",
       "      <th>ProductName</th>\n",
       "      <th>Synonyms</th>\n",
       "      <th>CAS Number</th>\n",
       "      <th>Target</th>\n",
       "      <th>PathWay</th>\n",
       "      <th>Biological Activity</th>\n",
       "      <th>Formula</th>\n",
       "      <th>URL</th>\n",
       "      <th>Research Area</th>\n",
       "      <th>atc_code</th>\n",
       "      <th>rdkit_no_salt</th>\n",
       "      <th>pchem_isomeric_smile</th>\n",
       "      <th>final_abx</th>\n",
       "      <th>atc_description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HY-B1898</td>\n",
       "      <td>1-FDAapproved 2- 3-</td>\n",
       "      <td>Metadoxine</td>\n",
       "      <td>0</td>\n",
       "      <td>74536-44-0</td>\n",
       "      <td>PKA</td>\n",
       "      <td>Protein Tyrosine Kinase/RTK; Stem Cell/Wnt</td>\n",
       "      <td>Metadoxine blocks adipocyte differentiation in...</td>\n",
       "      <td>C13H18N2O6</td>\n",
       "      <td>https://www.medchemexpress.com/Metadoxine.html</td>\n",
       "      <td>Metabolic Disease</td>\n",
       "      <td>A05BA09</td>\n",
       "      <td>Cc1ncc(CO)c(CO)c1O.O=C1CCC(C(=O)O)N1</td>\n",
       "      <td>CC1=NC=C(C(=C1O)CO)CO.C1CC(=O)N[C@@H]1C(=O)O</td>\n",
       "      <td>not_abx</td>\n",
       "      <td>ALIMENTARY TRACT AND METABOLISM - BILE AND LIV...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>HY-B0983</td>\n",
       "      <td>1-FDAapproved 2- 3-</td>\n",
       "      <td>Hydrocortisone 17-butyrate</td>\n",
       "      <td>Cortisol 17-butyrate; Hydrocortisone butyrate</td>\n",
       "      <td>13609-67-1</td>\n",
       "      <td>Adrenergic Receptor</td>\n",
       "      <td>GPCR/G Protein; Neuronal Signaling</td>\n",
       "      <td>Hydrocortisone 17-butyrate is an adrenocortico...</td>\n",
       "      <td>C25H36O6</td>\n",
       "      <td>https://www.medchemexpress.com/Hydrocortisone-...</td>\n",
       "      <td>Inflammation/Immunology; Endocrinology</td>\n",
       "      <td>A01AC03:A07EA02:C05AA01:D07AA02:D07XA01:H02AB0...</td>\n",
       "      <td>CCCC(=O)OC1(C(=O)CO)CCC2C3CCC4=CC(=O)CCC4(C)C3...</td>\n",
       "      <td>CCCC(=O)O[C@@]1(CC[C@@H]2[C@@]1(C[C@@H]([C@H]3...</td>\n",
       "      <td>not_abx</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HY-B1892</td>\n",
       "      <td>1-FDAapproved 2- 3-</td>\n",
       "      <td>Cefazolin</td>\n",
       "      <td>0</td>\n",
       "      <td>25953-19-9</td>\n",
       "      <td>Antibiotic; Bacterial</td>\n",
       "      <td>Anti-infection</td>\n",
       "      <td>Cefazolin is an antibiotic used for the resear...</td>\n",
       "      <td>C14H14N8O4S3</td>\n",
       "      <td>https://www.medchemexpress.com/cefazolin.html</td>\n",
       "      <td>Infection; Inflammation/Immunology; Neurologic...</td>\n",
       "      <td>J01DB04</td>\n",
       "      <td>Cc1nnc(SCC2=C(C(=O)O)N3C(=O)C(NC(=O)Cn4cnnn4)C...</td>\n",
       "      <td>CC1=NN=C(S1)SCC2=C(N3[C@@H]([C@@H](C3=O)NC(=O)...</td>\n",
       "      <td>abx</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>HY-B1900</td>\n",
       "      <td>1-FDAapproved 2- 3-</td>\n",
       "      <td>Methylprednisolone succinate</td>\n",
       "      <td>Methylprednisolone hydrogen succinate</td>\n",
       "      <td>2921-57-5</td>\n",
       "      <td>Glucocorticoid Receptor</td>\n",
       "      <td>GPCR/G Protein</td>\n",
       "      <td>Methylprednisolone succinate is a synthetic gl...</td>\n",
       "      <td>C26H34O8</td>\n",
       "      <td>https://www.medchemexpress.com/Methylprednisol...</td>\n",
       "      <td>Cancer; Inflammation/Immunology; Endocrinology</td>\n",
       "      <td>D07AA01:D10AA02:H02AB04</td>\n",
       "      <td>CC1CC2C(C(O)CC3(C)C2CCC3(O)C(=O)COC(=O)CCC(=O)...</td>\n",
       "      <td>C[C@H]1C[C@H]2[C@@H]3CC[C@@]([C@]3(C[C@@H]([C@...</td>\n",
       "      <td>not_abx</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>HY-A0070A</td>\n",
       "      <td>1-FDAapproved 2-EndoMetabolites 3-</td>\n",
       "      <td>Liothyronine</td>\n",
       "      <td>Triiodothyronine; 3,3',5-Triiodo-L-thyronine; T3</td>\n",
       "      <td>6893-02-3</td>\n",
       "      <td>Endogenous Metabolite; Thyroid Hormone Receptor</td>\n",
       "      <td>Metabolic Enzyme/Protease; Others</td>\n",
       "      <td>Liothyronine is an active form of thyroid horm...</td>\n",
       "      <td>C15H12I3NO4</td>\n",
       "      <td>https://www.medchemexpress.com/3,3_acute_,5-Tr...</td>\n",
       "      <td>Cancer; Endocrinology</td>\n",
       "      <td>not_found</td>\n",
       "      <td>NC(Cc1cc(I)c(Oc2ccc(O)c(I)c2)c(I)c1)C(=O)O</td>\n",
       "      <td>C1=CC(=C(C=C1OC2=C(C=C(C=C2I)C[C@@H](C(=O)O)N)...</td>\n",
       "      <td>not_abx</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Catalog Number                        Original lib  \\\n",
       "0       HY-B1898                 1-FDAapproved 2- 3-   \n",
       "1       HY-B0983                 1-FDAapproved 2- 3-   \n",
       "2       HY-B1892                 1-FDAapproved 2- 3-   \n",
       "3       HY-B1900                 1-FDAapproved 2- 3-   \n",
       "4      HY-A0070A  1-FDAapproved 2-EndoMetabolites 3-   \n",
       "\n",
       "                    ProductName  \\\n",
       "0                    Metadoxine   \n",
       "1    Hydrocortisone 17-butyrate   \n",
       "2                     Cefazolin   \n",
       "3  Methylprednisolone succinate   \n",
       "4                  Liothyronine   \n",
       "\n",
       "                                           Synonyms  CAS Number  \\\n",
       "0                                                 0  74536-44-0   \n",
       "1     Cortisol 17-butyrate; Hydrocortisone butyrate  13609-67-1   \n",
       "2                                                 0  25953-19-9   \n",
       "3             Methylprednisolone hydrogen succinate   2921-57-5   \n",
       "4  Triiodothyronine; 3,3',5-Triiodo-L-thyronine; T3   6893-02-3   \n",
       "\n",
       "                                            Target  \\\n",
       "0                                              PKA   \n",
       "1                              Adrenergic Receptor   \n",
       "2                            Antibiotic; Bacterial   \n",
       "3                          Glucocorticoid Receptor   \n",
       "4  Endogenous Metabolite; Thyroid Hormone Receptor   \n",
       "\n",
       "                                      PathWay  \\\n",
       "0  Protein Tyrosine Kinase/RTK; Stem Cell/Wnt   \n",
       "1          GPCR/G Protein; Neuronal Signaling   \n",
       "2                              Anti-infection   \n",
       "3                              GPCR/G Protein   \n",
       "4           Metabolic Enzyme/Protease; Others   \n",
       "\n",
       "                                 Biological Activity       Formula  \\\n",
       "0  Metadoxine blocks adipocyte differentiation in...    C13H18N2O6   \n",
       "1  Hydrocortisone 17-butyrate is an adrenocortico...      C25H36O6   \n",
       "2  Cefazolin is an antibiotic used for the resear...  C14H14N8O4S3   \n",
       "3  Methylprednisolone succinate is a synthetic gl...      C26H34O8   \n",
       "4  Liothyronine is an active form of thyroid horm...   C15H12I3NO4   \n",
       "\n",
       "                                                 URL  \\\n",
       "0     https://www.medchemexpress.com/Metadoxine.html   \n",
       "1  https://www.medchemexpress.com/Hydrocortisone-...   \n",
       "2      https://www.medchemexpress.com/cefazolin.html   \n",
       "3  https://www.medchemexpress.com/Methylprednisol...   \n",
       "4  https://www.medchemexpress.com/3,3_acute_,5-Tr...   \n",
       "\n",
       "                                       Research Area  \\\n",
       "0                                  Metabolic Disease   \n",
       "1             Inflammation/Immunology; Endocrinology   \n",
       "2  Infection; Inflammation/Immunology; Neurologic...   \n",
       "3     Cancer; Inflammation/Immunology; Endocrinology   \n",
       "4                              Cancer; Endocrinology   \n",
       "\n",
       "                                            atc_code  \\\n",
       "0                                            A05BA09   \n",
       "1  A01AC03:A07EA02:C05AA01:D07AA02:D07XA01:H02AB0...   \n",
       "2                                            J01DB04   \n",
       "3                            D07AA01:D10AA02:H02AB04   \n",
       "4                                          not_found   \n",
       "\n",
       "                                       rdkit_no_salt  \\\n",
       "0               Cc1ncc(CO)c(CO)c1O.O=C1CCC(C(=O)O)N1   \n",
       "1  CCCC(=O)OC1(C(=O)CO)CCC2C3CCC4=CC(=O)CCC4(C)C3...   \n",
       "2  Cc1nnc(SCC2=C(C(=O)O)N3C(=O)C(NC(=O)Cn4cnnn4)C...   \n",
       "3  CC1CC2C(C(O)CC3(C)C2CCC3(O)C(=O)COC(=O)CCC(=O)...   \n",
       "4         NC(Cc1cc(I)c(Oc2ccc(O)c(I)c2)c(I)c1)C(=O)O   \n",
       "\n",
       "                                pchem_isomeric_smile final_abx  \\\n",
       "0       CC1=NC=C(C(=C1O)CO)CO.C1CC(=O)N[C@@H]1C(=O)O   not_abx   \n",
       "1  CCCC(=O)O[C@@]1(CC[C@@H]2[C@@]1(C[C@@H]([C@H]3...   not_abx   \n",
       "2  CC1=NN=C(S1)SCC2=C(N3[C@@H]([C@@H](C3=O)NC(=O)...       abx   \n",
       "3  C[C@H]1C[C@H]2[C@@H]3CC[C@@]([C@]3(C[C@@H]([C@...   not_abx   \n",
       "4  C1=CC(=C(C=C1OC2=C(C=C(C=C2I)C[C@@H](C(=O)O)N)...   not_abx   \n",
       "\n",
       "                                     atc_description  \n",
       "0  ALIMENTARY TRACT AND METABOLISM - BILE AND LIV...  \n",
       "1                                                NaN  \n",
       "2                                                NaN  \n",
       "3                                                NaN  \n",
       "4                                                NaN  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read the chemical library metadata\n",
    "\n",
    "medchemexp_df = pd.read_csv(os.path.join(RAW_DATA_DIR, \"medchemexpress\", \"chemical_library_cleaned.tsv.gz\"), sep='\\t', index_col=0)\n",
    "medchemexp_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3286, 16)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "medchemexp_df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Remove chemicals that are present in the Maier dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2746, 17)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Function to simplify the chemical names\n",
    "def simplified_names_chemlibrary(original_name):\n",
    "    \n",
    "    # Remove additional information from name \n",
    "    name = original_name.split(\" (\")[0]\n",
    "    name = name.split(\" [\")[0]\n",
    "    name = name.rstrip()\n",
    "    \n",
    "    name = name.lower()\n",
    "    \n",
    "    \n",
    "    return name\n",
    "\n",
    "# Simplify the product names\n",
    "medchemexp_df[\"simple_name\"] = medchemexp_df[\"ProductName\"].apply(simplified_names_chemlibrary)\n",
    "\n",
    "# Lowercase the names in the maier data\n",
    "maier_library[\"chem_name_lower\"] = maier_library[\"chemical name\"].apply(lambda x: x.lower())\n",
    "\n",
    "medchemexp_df_filtnames = medchemexp_df.loc[~medchemexp_df[\"simple_name\"].isin(maier_library.chem_name_lower.tolist())]\n",
    "medchemexp_df_filtnames.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Also remove chemicals with overlapping ATC codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2332, 17)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Gather all Maier atc codes\n",
    "maier_atc = [c for a in maier_library[\"ATC codes\"].unique() for c in a.split(\" \")]\n",
    "\n",
    "# Function to detect ATC overlap\n",
    "def atc_in_maier(atc_str, maier_atc_list=maier_atc):\n",
    "    \n",
    "    # check if atc code is in the maier dataset\n",
    "    if any([x for x in atc_str.split(\":\") if x in maier_atc_list]):\n",
    "        return True\n",
    "    else:\n",
    "        return False\n",
    "    \n",
    "# Filter chemicals with overlapping ATC codes\n",
    "medchemexp_df_filtatc = medchemexp_df_filtnames.loc[~medchemexp_df_filtnames[\"atc_code\"].apply(atc_in_maier)]\n",
    "medchemexp_df_filtatc.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2319, 17)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Other chemicals that are in the Maier dataset\n",
    "overlap_catnums = ['HY-B1246', 'HY-30234A', 'HY-B0463', 'HY-W010832', \n",
    "                   'HY-B1320', 'HY-13578', 'HY-14447', 'HY-12857',\n",
    "                   'HY-B0537B', 'HY-16478', 'HY-18341', 'HY-18341A', 'HY-18341B']\n",
    "\n",
    "# Filter the chemicals\n",
    "medchemexp_df_filttotal = medchemexp_df_filtatc.loc[~medchemexp_df_filtatc[\"Catalog Number\"].isin(overlap_catnums)]\n",
    "medchemexp_df_filttotal.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "962 chemicals removed\n"
     ]
    }
   ],
   "source": [
    "print(f\"{medchemexp_df.shape[0] -   medchemexp_df_filttotal.shape[0]} chemicals removed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "medchemexp_df_filttotal.to_csv(os.path.join(OUTPUT_DIR, \"medchemexpress_filtered.tsv.gz\"), sep='\\t', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Make predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read MolE representation\n",
    "mole_mce = pd.read_csv(os.path.join(OUTPUT_DIR, \"MolE_representation_medchemexpress.tsv.gz\"), sep='\\t', index_col=0)\n",
    "\n",
    "# Make predictions\n",
    "mole_mce_predictions = make_predictions(mole_model, \n",
    "                mole_mce.loc[medchemexp_df_filttotal[\"Catalog Number\"]], \n",
    "                optimized_parameters.loc[(optimized_parameters[\"representation\"]== \"MolE\") &\n",
    "                                         (optimized_parameters[\"score_type\"]== \"optimized\"), \"threshold\"].values[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read ECFP4 representation\n",
    "ecfp4_mce = pd.read_csv(os.path.join(OUTPUT_DIR, \"ecfp4_representation_medchemexpress.tsv.gz\"), sep='\\t', index_col=0)\n",
    "\n",
    "# Make predictions\n",
    "ecfp4_mce_predictions = make_predictions(ecfp4_model, \n",
    "                ecfp4_mce.loc[medchemexp_df_filttotal[\"Catalog Number\"]], \n",
    "                optimized_parameters.loc[(optimized_parameters[\"representation\"]== \"ecfp4\") &\n",
    "                                         (optimized_parameters[\"score_type\"]== \"optimized\"), \"threshold\"].values[0])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analyze predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add gram stain information\n",
    "def gram_stain(label_df, strain_info_df=maier_strains):\n",
    "\n",
    "    \"\"\"\n",
    "    Add Gram stain information to strain labels.\n",
    "\n",
    "    This function adds Gram stain information to strain labels based on the NT number in the strain name.\n",
    "\n",
    "    Parameters:\n",
    "    - label_df (pandas.DataFrame): DataFrame containing strain labels.\n",
    "    - strain_info_df (pandas.DataFrame, optional): DataFrame containing strain information (default is maier_strains).\n",
    "\n",
    "    Returns:\n",
    "    - df_label (pandas.DataFrame): DataFrame containing strain labels with Gram stain information.\n",
    "    \"\"\"\n",
    "\n",
    "    # Create copy of the label dataframe\n",
    "    df_label = label_df.copy()\n",
    "    \n",
    "    # Gather NT number\n",
    "    df_label[\"nt_number\"] = df_label[\"strain_name\"].apply(lambda x: re.search(\".*?\\((NT\\d+)\\)\", x).group(1))\n",
    "\n",
    "    # Create Gram strain dict\n",
    "    gram_dict = strain_info_df[[\"Gram stain\"]].to_dict()[\"Gram stain\"]\n",
    "\n",
    "    # Add stain information\n",
    "    df_label[\"gram_stain\"] = df_label[\"nt_number\"].apply(gram_dict.get)\n",
    "\n",
    "    return df_label\n",
    "\n",
    "\n",
    "def aggregate_predictions(pred_df):\n",
    "\n",
    "    \"\"\"\n",
    "    Aggregate predictions to calculate total and gram stain-specific metrics.\n",
    "\n",
    "    This function aggregates predictions to calculate total and Gram stain-specific metrics such as\n",
    "    total number of inhibited strains, antimicrobial score, and antimicrobial score by Gram stain.\n",
    "\n",
    "    Parameters:\n",
    "    - pred_df (pandas.DataFrame): DataFrame containing predictions.\n",
    "\n",
    "    Returns:\n",
    "    - agg_pred (pandas.DataFrame): DataFrame containing aggregated predictions.\n",
    "    \"\"\"\n",
    "\n",
    "    # Total number of inhibited strains\n",
    "    nkill_total = pred_df.groupby(\"chem_id\")[[\"pred_label\"]].sum().rename(columns={\"pred_label\": \"nk_total\"})\n",
    "\n",
    "    # Total number of inhibited strains by gram stain\n",
    "    nkill_gram = pred_df.groupby([\"chem_id\", \"gram_stain\"])[\"pred_label\"].sum().unstack().rename(columns={\"negative\": \"nk_gnegative\",\n",
    "                                                                                                            \"positive\": \"nk_gpositive\"})\n",
    "\n",
    "    # Antimicrobial score\n",
    "    apscore_total = pred_df.groupby(\"chem_id\")[\"pred_score\"].apply(gmean).to_frame().rename(columns={\"pred_score\": \"apscore_total\"})\n",
    "    apscore_total[\"apscore_total\"] = np.log(apscore_total[\"apscore_total\"])\n",
    "\n",
    "    # Antimicrobial score by gram stain\n",
    "    apscore_gram = pred_df.groupby([\"chem_id\", \"gram_stain\"])[\"pred_score\"].apply(gmean).unstack().rename(columns={\"negative\": \"apscore_gnegative\",\n",
    "                                                                                                         \"positive\": \"apscore_gpositive\"})\n",
    "    apscore_gram[\"apscore_gnegative\"] = np.log(apscore_gram[\"apscore_gnegative\"])\n",
    "    apscore_gram[\"apscore_gpositive\"] = np.log(apscore_gram[\"apscore_gpositive\"])\n",
    "\n",
    "\n",
    "    # Merge the results\n",
    "    agg_pred = nkill_total.join(nkill_gram).join(apscore_total).join(apscore_gram)\n",
    "\n",
    "    return agg_pred\n",
    "\n",
    "def inform_predictions(pred_df, metadata_df = medchemexp_df_filttotal, strain_info_df=maier_strains):\n",
    "\n",
    "    \"\"\"\n",
    "    Enrich predictions with antibiotic and Gram stain information.\n",
    "\n",
    "    This function enriches predictions with antibiotic and Gram stain information.\n",
    "    It adds Gram stain information to strain labels, aggregates predictions, and adds antibiotic information.\n",
    "\n",
    "    Parameters:\n",
    "    - pred_df (pandas.DataFrame): DataFrame containing predictions.\n",
    "    - metadata_df (pandas.DataFrame, optional): DataFrame containing metadata (default is medchemexp_df_filttotal).\n",
    "    - strain_info_df (pandas.DataFrame, optional): DataFrame containing strain information (default is maier_strains).\n",
    "\n",
    "    Returns:\n",
    "    - agg_pred (pandas.DataFrame): DataFrame containing enriched predictions.\n",
    "    \"\"\"\n",
    "\n",
    "    # Add gram stain information\n",
    "    pred_df_gram = gram_stain(pred_df, strain_info_df)\n",
    "\n",
    "    # Aggregate prediction information\n",
    "    agg_pred = aggregate_predictions(pred_df_gram)\n",
    "    agg_pred = agg_pred.reset_index()\n",
    "\n",
    "    # Add antibiotic information\n",
    "    abx_dict = metadata_df[[\"Catalog Number\", \"final_abx\"]].set_index(\"Catalog Number\").to_dict()[\"final_abx\"]\n",
    "    agg_pred[\"antibiotic\"] = agg_pred[\"chem_id\"].apply(abx_dict.get)\n",
    "\n",
    "    return agg_pred\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "mole_mce_info = inform_predictions(mole_mce_predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "ecfp4_mce_info = inform_predictions(ecfp4_mce_predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='nk_total', ylabel='apscore_total'>"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "sns.scatterplot(data=mole_mce_info, y=\"apscore_total\", x=\"nk_total\", hue=\"antibiotic\", \n",
    "                palette={\"abx\": \"red\", \"not_abx\": \"#C5C5C5\"}, s=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'ECFP4 results')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "sns.scatterplot(data=ecfp4_mce_info, y=\"apscore_total\", x=\"nk_total\", hue=\"antibiotic\", \n",
    "                palette={\"abx\": \"red\", \"not_abx\": \"#C5C5C5\"}, s=50)\n",
    "\n",
    "plt.title(\"ECFP4 results\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='apscore_gnegative', ylabel='apscore_gpositive'>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "sns.scatterplot(data=mole_mce_info.loc[mole_mce_info[\"nk_total\"] >= 10], y=\"apscore_gpositive\", x=\"apscore_gnegative\", hue=\"antibiotic\", \n",
    "                palette={\"abx\": \"red\", \"not_abx\": \"#C5C5C5\"}, s=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'ECFP4 results')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "sns.scatterplot(data=ecfp4_mce_info.loc[ecfp4_mce_info[\"nk_total\"] >= 10], y=\"apscore_gpositive\", x=\"apscore_gnegative\", hue=\"antibiotic\", \n",
    "                palette={\"abx\": \"red\", \"not_abx\": \"#C5C5C5\"}, s=50)\n",
    "\n",
    "plt.title(\"ECFP4 results\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prepare output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add metadata\n",
    "mole_mce_metadata = mole_mce_info.set_index(\"chem_id\").join(medchemexp_df_filttotal.set_index(\"Catalog Number\")[[\"ProductName\", \"atc_description\", \"Biological Activity\"]])\n",
    "mole_mce_metadata = mole_mce_metadata.reset_index().rename(columns={\"chem_id\": \"Catalog Number\"}).sort_values(\"nk_total\", ascending=False)\n",
    "\n",
    "\n",
    "# Isolate over 10\n",
    "mole_mce_over10 = mole_mce_metadata.loc[mole_mce_metadata[\"nk_total\"] >= 10]\n",
    "\n",
    "# Gather the scores\n",
    "mole_scores_table = mole_mce_predictions.pivot_table(index=\"chem_id\", columns=\"strain_name\", values=\"pred_score\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.ExcelWriter(os.path.join(OUTPUT_DIR, \"mole_mce_predictions.xlsx\")) as writer:\n",
    "    mole_mce_metadata.to_excel(writer, sheet_name=\"mole_prediction_overview\", index=False)\n",
    "    mole_mce_over10.to_excel(writer, sheet_name=\"mole_over10\", index=False)\n",
    "    mole_scores_table.to_excel(writer, sheet_name=\"mole_scores\", index=True)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add metadata\n",
    "ecfp4_mce_metadata = ecfp4_mce_info.set_index(\"chem_id\").join(medchemexp_df_filttotal.set_index(\"Catalog Number\")[[\"ProductName\", \"atc_description\", \"Biological Activity\"]])\n",
    "ecfp4_mce_metadata = ecfp4_mce_metadata.reset_index().rename(columns={\"chem_id\": \"Catalog Number\"}).sort_values(\"nk_total\", ascending=False)\n",
    "\n",
    "\n",
    "# Isolate over 10\n",
    "ecfp4_mce_over10 = ecfp4_mce_metadata.loc[ecfp4_mce_metadata[\"nk_total\"] >= 10]\n",
    "\n",
    "# Gather the scores\n",
    "ecfp4_scores_table = ecfp4_mce_predictions.pivot_table(index=\"chem_id\", columns=\"strain_name\", values=\"pred_score\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.ExcelWriter(os.path.join(OUTPUT_DIR, \"ecfp4_mce_predictions.xlsx\")) as writer:\n",
    "    ecfp4_mce_metadata.to_excel(writer, sheet_name=\"ecfp4_prediction_overview\", index=False)\n",
    "    ecfp4_mce_over10.to_excel(writer, sheet_name=\"ecfp4_over10\", index=False)\n",
    "    ecfp4_scores_table.to_excel(writer, sheet_name=\"ecfp4_scores\", index=True)    "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "mole_test",
   "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": "3.8.20"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}