cell-painting/2.train/0.cell-painting-vaeLEVEL4-leave_out.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Train a VAE on Cell Painting LINCS Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import pathlib\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "sys.path.insert(0, \"../../scripts\")\n",
    "from utils import load_data\n",
    "\n",
    "\n",
    "from pycytominer.cyto_utils import infer_cp_features\n",
    "\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.pyplot import figure\n",
    "\n",
    "from sklearn.decomposition import PCA\n",
    "from tensorflow import keras\n",
    "\n",
    "from vae import VAE\n",
    "\n",
    "from tensorflow.keras.models import Model, Sequential\n",
    "import seaborn\n",
    "import random as python_random\n",
    "import tensorflow as tf\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def remove_moa(df):\n",
    "    pipes = ['cytochrome P450 inhibitor|protein synthesis inhibitor',\n",
    "            'thromboxane receptor antagonist|thromboxane synthase inhibitor',\n",
    "            'serotonin receptor antagonist|sodium channel blocker',\n",
    "            'antiviral|RNA synthesis inhibitor',\n",
    "            'adenosine receptor antagonist|phosphodiesterase inhibitor']    \n",
    "    moas =  []\n",
    "    for pipe in pipes:\n",
    "        moas.append(pipe)\n",
    "        moas.append(pipe.split('|')[0])\n",
    "        moas.append(pipe.split('|')[1])\n",
    "    return df[~df.moa.isin(moas)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ubuntu/miniconda3/envs/cell-painting-vae/lib/python3.7/site-packages/IPython/core/interactiveshell.py:3361: DtypeWarning: Columns (18,19) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  if (await self.run_code(code, result,  async_=asy)):\n"
     ]
    }
   ],
   "source": [
    "data_splits = [\"train\", \"test\", \"valid\",\"complete\"]\n",
    "data_dict = load_data(data_splits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Prepare data for training\n",
    "meta_features = infer_cp_features(data_dict[\"train\"], metadata=True)\n",
    "cp_features = infer_cp_features(data_dict[\"train\"])\n",
    "\n",
    "moa_df_train = pd.read_csv(\"../3.application/repurposing_info_external_moa_map_resolved.tsv\",sep='\\t').set_index('broad_sample').reindex(index=data_dict['train']['Metadata_broad_sample']).reset_index().drop('Metadata_broad_sample',axis = 1)\n",
    "data_dict['train'] = pd.concat([moa_df_train,data_dict['train']], axis=1)\n",
    "\n",
    "moa_df_valid = pd.read_csv(\"../3.application/repurposing_info_external_moa_map_resolved.tsv\",sep='\\t').set_index('broad_sample').reindex(index=data_dict['valid']['Metadata_broad_sample']).reset_index().drop('Metadata_broad_sample',axis = 1)\n",
    "data_dict['valid'] = pd.concat([moa_df_valid,data_dict['valid']], axis=1)\n",
    "\n",
    "data_dict['train'] = remove_moa(data_dict['train'])\n",
    "data_dict['valid'] = remove_moa(data_dict['valid'])\n",
    "\n",
    "train_features_df = data_dict[\"train\"].reindex(cp_features, axis=\"columns\")\n",
    "train_meta_df = data_dict[\"train\"].reindex(meta_features, axis=\"columns\")\n",
    "\n",
    "test_features_df = data_dict[\"test\"].reindex(cp_features, axis=\"columns\")\n",
    "test_meta_df = data_dict[\"test\"].reindex(meta_features, axis=\"columns\")\n",
    "\n",
    "valid_features_df = data_dict[\"valid\"].reindex(cp_features, axis=\"columns\")\n",
    "valid_meta_df = data_dict[\"valid\"].reindex(meta_features, axis=\"columns\")\n",
    "\n",
    "complete_features_df = data_dict[\"complete\"].reindex(cp_features, axis=\"columns\")\n",
    "complete_meta_df = data_dict[\"complete\"].reindex(meta_features, axis=\"columns\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(38170, 685)\n"
     ]
    },
    {
     "data": {
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       "\n",
       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Cells_AreaShape_Compactness</th>\n",
       "      <th>Cells_AreaShape_Eccentricity</th>\n",
       "      <th>Cells_AreaShape_Extent</th>\n",
       "      <th>Cells_AreaShape_FormFactor</th>\n",
       "      <th>Cells_AreaShape_MedianRadius</th>\n",
       "      <th>Cells_AreaShape_Orientation</th>\n",
       "      <th>Cells_AreaShape_Solidity</th>\n",
       "      <th>Cells_AreaShape_Zernike_0_0</th>\n",
       "      <th>Cells_AreaShape_Zernike_1_1</th>\n",
       "      <th>Cells_AreaShape_Zernike_2_0</th>\n",
       "      <th>...</th>\n",
       "      <th>Nuclei_Texture_SumEntropy_DNA_5_0</th>\n",
       "      <th>Nuclei_Texture_SumEntropy_Mito_5_0</th>\n",
       "      <th>Nuclei_Texture_SumEntropy_RNA_20_0</th>\n",
       "      <th>Nuclei_Texture_SumEntropy_RNA_5_0</th>\n",
       "      <th>Nuclei_Texture_SumVariance_DNA_20_0</th>\n",
       "      <th>Nuclei_Texture_SumVariance_RNA_20_0</th>\n",
       "      <th>Nuclei_Texture_Variance_DNA_20_0</th>\n",
       "      <th>Nuclei_Texture_Variance_ER_20_0</th>\n",
       "      <th>Nuclei_Texture_Variance_RNA_10_0</th>\n",
       "      <th>Nuclei_Texture_Variance_RNA_20_0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.18605</td>\n",
       "      <td>0.68873</td>\n",
       "      <td>0.41051</td>\n",
       "      <td>0.31982</td>\n",
       "      <td>0.19885</td>\n",
       "      <td>0.72510</td>\n",
       "      <td>0.39552</td>\n",
       "      <td>0.38362</td>\n",
       "      <td>0.65094</td>\n",
       "      <td>0.89679</td>\n",
       "      <td>...</td>\n",
       "      <td>0.61393</td>\n",
       "      <td>0.38269</td>\n",
       "      <td>0.63814</td>\n",
       "      <td>0.68204</td>\n",
       "      <td>0.23700</td>\n",
       "      <td>0.32808</td>\n",
       "      <td>0.27981</td>\n",
       "      <td>0.26893</td>\n",
       "      <td>0.34938</td>\n",
       "      <td>0.33179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.19083</td>\n",
       "      <td>0.66276</td>\n",
       "      <td>0.38585</td>\n",
       "      <td>0.31437</td>\n",
       "      <td>0.20415</td>\n",
       "      <td>0.71380</td>\n",
       "      <td>0.38701</td>\n",
       "      <td>0.36699</td>\n",
       "      <td>0.60932</td>\n",
       "      <td>0.88492</td>\n",
       "      <td>...</td>\n",
       "      <td>0.60850</td>\n",
       "      <td>0.41850</td>\n",
       "      <td>0.63529</td>\n",
       "      <td>0.65208</td>\n",
       "      <td>0.22852</td>\n",
       "      <td>0.32710</td>\n",
       "      <td>0.29371</td>\n",
       "      <td>0.27159</td>\n",
       "      <td>0.33871</td>\n",
       "      <td>0.31965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.17934</td>\n",
       "      <td>0.67469</td>\n",
       "      <td>0.38835</td>\n",
       "      <td>0.31453</td>\n",
       "      <td>0.20468</td>\n",
       "      <td>0.72474</td>\n",
       "      <td>0.39699</td>\n",
       "      <td>0.37328</td>\n",
       "      <td>0.64139</td>\n",
       "      <td>0.89582</td>\n",
       "      <td>...</td>\n",
       "      <td>0.60439</td>\n",
       "      <td>0.38586</td>\n",
       "      <td>0.65320</td>\n",
       "      <td>0.66223</td>\n",
       "      <td>0.22899</td>\n",
       "      <td>0.31620</td>\n",
       "      <td>0.29548</td>\n",
       "      <td>0.26682</td>\n",
       "      <td>0.35609</td>\n",
       "      <td>0.34152</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 685 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Cells_AreaShape_Compactness  Cells_AreaShape_Eccentricity  \\\n",
       "1                      0.18605                       0.68873   \n",
       "2                      0.19083                       0.66276   \n",
       "3                      0.17934                       0.67469   \n",
       "\n",
       "   Cells_AreaShape_Extent  Cells_AreaShape_FormFactor  \\\n",
       "1                 0.41051                     0.31982   \n",
       "2                 0.38585                     0.31437   \n",
       "3                 0.38835                     0.31453   \n",
       "\n",
       "   Cells_AreaShape_MedianRadius  Cells_AreaShape_Orientation  \\\n",
       "1                       0.19885                      0.72510   \n",
       "2                       0.20415                      0.71380   \n",
       "3                       0.20468                      0.72474   \n",
       "\n",
       "   Cells_AreaShape_Solidity  Cells_AreaShape_Zernike_0_0  \\\n",
       "1                   0.39552                      0.38362   \n",
       "2                   0.38701                      0.36699   \n",
       "3                   0.39699                      0.37328   \n",
       "\n",
       "   Cells_AreaShape_Zernike_1_1  Cells_AreaShape_Zernike_2_0  ...  \\\n",
       "1                      0.65094                      0.89679  ...   \n",
       "2                      0.60932                      0.88492  ...   \n",
       "3                      0.64139                      0.89582  ...   \n",
       "\n",
       "   Nuclei_Texture_SumEntropy_DNA_5_0  Nuclei_Texture_SumEntropy_Mito_5_0  \\\n",
       "1                            0.61393                             0.38269   \n",
       "2                            0.60850                             0.41850   \n",
       "3                            0.60439                             0.38586   \n",
       "\n",
       "   Nuclei_Texture_SumEntropy_RNA_20_0  Nuclei_Texture_SumEntropy_RNA_5_0  \\\n",
       "1                             0.63814                            0.68204   \n",
       "2                             0.63529                            0.65208   \n",
       "3                             0.65320                            0.66223   \n",
       "\n",
       "   Nuclei_Texture_SumVariance_DNA_20_0  Nuclei_Texture_SumVariance_RNA_20_0  \\\n",
       "1                              0.23700                              0.32808   \n",
       "2                              0.22852                              0.32710   \n",
       "3                              0.22899                              0.31620   \n",
       "\n",
       "   Nuclei_Texture_Variance_DNA_20_0  Nuclei_Texture_Variance_ER_20_0  \\\n",
       "1                           0.27981                          0.26893   \n",
       "2                           0.29371                          0.27159   \n",
       "3                           0.29548                          0.26682   \n",
       "\n",
       "   Nuclei_Texture_Variance_RNA_10_0  Nuclei_Texture_Variance_RNA_20_0  \n",
       "1                           0.34938                           0.33179  \n",
       "2                           0.33871                           0.31965  \n",
       "3                           0.35609                           0.34152  \n",
       "\n",
       "[3 rows x 685 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(train_features_df.shape)\n",
    "train_features_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(5030, 685)\n"
     ]
    },
    {
     "data": {
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Cells_AreaShape_Compactness</th>\n",
       "      <th>Cells_AreaShape_Eccentricity</th>\n",
       "      <th>Cells_AreaShape_Extent</th>\n",
       "      <th>Cells_AreaShape_FormFactor</th>\n",
       "      <th>Cells_AreaShape_MedianRadius</th>\n",
       "      <th>Cells_AreaShape_Orientation</th>\n",
       "      <th>Cells_AreaShape_Solidity</th>\n",
       "      <th>Cells_AreaShape_Zernike_0_0</th>\n",
       "      <th>Cells_AreaShape_Zernike_1_1</th>\n",
       "      <th>Cells_AreaShape_Zernike_2_0</th>\n",
       "      <th>...</th>\n",
       "      <th>Nuclei_Texture_SumEntropy_DNA_5_0</th>\n",
       "      <th>Nuclei_Texture_SumEntropy_Mito_5_0</th>\n",
       "      <th>Nuclei_Texture_SumEntropy_RNA_20_0</th>\n",
       "      <th>Nuclei_Texture_SumEntropy_RNA_5_0</th>\n",
       "      <th>Nuclei_Texture_SumVariance_DNA_20_0</th>\n",
       "      <th>Nuclei_Texture_SumVariance_RNA_20_0</th>\n",
       "      <th>Nuclei_Texture_Variance_DNA_20_0</th>\n",
       "      <th>Nuclei_Texture_Variance_ER_20_0</th>\n",
       "      <th>Nuclei_Texture_Variance_RNA_10_0</th>\n",
       "      <th>Nuclei_Texture_Variance_RNA_20_0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.19050</td>\n",
       "      <td>0.68937</td>\n",
       "      <td>0.39383</td>\n",
       "      <td>0.33072</td>\n",
       "      <td>0.20185</td>\n",
       "      <td>0.72292</td>\n",
       "      <td>0.38085</td>\n",
       "      <td>0.37504</td>\n",
       "      <td>0.61905</td>\n",
       "      <td>0.88361</td>\n",
       "      <td>...</td>\n",
       "      <td>0.60356</td>\n",
       "      <td>0.39345</td>\n",
       "      <td>0.63470</td>\n",
       "      <td>0.63406</td>\n",
       "      <td>0.23588</td>\n",
       "      <td>0.36061</td>\n",
       "      <td>0.30092</td>\n",
       "      <td>0.23638</td>\n",
       "      <td>0.36015</td>\n",
       "      <td>0.32779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.18661</td>\n",
       "      <td>0.67731</td>\n",
       "      <td>0.39621</td>\n",
       "      <td>0.32318</td>\n",
       "      <td>0.20716</td>\n",
       "      <td>0.70964</td>\n",
       "      <td>0.39401</td>\n",
       "      <td>0.37779</td>\n",
       "      <td>0.60275</td>\n",
       "      <td>0.88912</td>\n",
       "      <td>...</td>\n",
       "      <td>0.60936</td>\n",
       "      <td>0.40380</td>\n",
       "      <td>0.64406</td>\n",
       "      <td>0.64859</td>\n",
       "      <td>0.22752</td>\n",
       "      <td>0.29811</td>\n",
       "      <td>0.29430</td>\n",
       "      <td>0.25475</td>\n",
       "      <td>0.34154</td>\n",
       "      <td>0.32013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.18626</td>\n",
       "      <td>0.67036</td>\n",
       "      <td>0.41101</td>\n",
       "      <td>0.31863</td>\n",
       "      <td>0.20182</td>\n",
       "      <td>0.71139</td>\n",
       "      <td>0.40302</td>\n",
       "      <td>0.38979</td>\n",
       "      <td>0.59188</td>\n",
       "      <td>0.86857</td>\n",
       "      <td>...</td>\n",
       "      <td>0.61009</td>\n",
       "      <td>0.40904</td>\n",
       "      <td>0.64250</td>\n",
       "      <td>0.63285</td>\n",
       "      <td>0.23931</td>\n",
       "      <td>0.33179</td>\n",
       "      <td>0.28571</td>\n",
       "      <td>0.24980</td>\n",
       "      <td>0.34516</td>\n",
       "      <td>0.32968</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 685 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Cells_AreaShape_Compactness  Cells_AreaShape_Eccentricity  \\\n",
       "0                      0.19050                       0.68937   \n",
       "1                      0.18661                       0.67731   \n",
       "2                      0.18626                       0.67036   \n",
       "\n",
       "   Cells_AreaShape_Extent  Cells_AreaShape_FormFactor  \\\n",
       "0                 0.39383                     0.33072   \n",
       "1                 0.39621                     0.32318   \n",
       "2                 0.41101                     0.31863   \n",
       "\n",
       "   Cells_AreaShape_MedianRadius  Cells_AreaShape_Orientation  \\\n",
       "0                       0.20185                      0.72292   \n",
       "1                       0.20716                      0.70964   \n",
       "2                       0.20182                      0.71139   \n",
       "\n",
       "   Cells_AreaShape_Solidity  Cells_AreaShape_Zernike_0_0  \\\n",
       "0                   0.38085                      0.37504   \n",
       "1                   0.39401                      0.37779   \n",
       "2                   0.40302                      0.38979   \n",
       "\n",
       "   Cells_AreaShape_Zernike_1_1  Cells_AreaShape_Zernike_2_0  ...  \\\n",
       "0                      0.61905                      0.88361  ...   \n",
       "1                      0.60275                      0.88912  ...   \n",
       "2                      0.59188                      0.86857  ...   \n",
       "\n",
       "   Nuclei_Texture_SumEntropy_DNA_5_0  Nuclei_Texture_SumEntropy_Mito_5_0  \\\n",
       "0                            0.60356                             0.39345   \n",
       "1                            0.60936                             0.40380   \n",
       "2                            0.61009                             0.40904   \n",
       "\n",
       "   Nuclei_Texture_SumEntropy_RNA_20_0  Nuclei_Texture_SumEntropy_RNA_5_0  \\\n",
       "0                             0.63470                            0.63406   \n",
       "1                             0.64406                            0.64859   \n",
       "2                             0.64250                            0.63285   \n",
       "\n",
       "   Nuclei_Texture_SumVariance_DNA_20_0  Nuclei_Texture_SumVariance_RNA_20_0  \\\n",
       "0                              0.23588                              0.36061   \n",
       "1                              0.22752                              0.29811   \n",
       "2                              0.23931                              0.33179   \n",
       "\n",
       "   Nuclei_Texture_Variance_DNA_20_0  Nuclei_Texture_Variance_ER_20_0  \\\n",
       "0                           0.30092                          0.23638   \n",
       "1                           0.29430                          0.25475   \n",
       "2                           0.28571                          0.24980   \n",
       "\n",
       "   Nuclei_Texture_Variance_RNA_10_0  Nuclei_Texture_Variance_RNA_20_0  \n",
       "0                           0.36015                           0.32779  \n",
       "1                           0.34154                           0.32013  \n",
       "2                           0.34516                           0.32968  \n",
       "\n",
       "[3 rows x 685 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(test_features_df.shape)\n",
    "test_features_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(50303, 685)\n"
     ]
    },
    {
     "data": {
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       "<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>Cells_AreaShape_Compactness</th>\n",
       "      <th>Cells_AreaShape_Eccentricity</th>\n",
       "      <th>Cells_AreaShape_Extent</th>\n",
       "      <th>Cells_AreaShape_FormFactor</th>\n",
       "      <th>Cells_AreaShape_MedianRadius</th>\n",
       "      <th>Cells_AreaShape_Orientation</th>\n",
       "      <th>Cells_AreaShape_Solidity</th>\n",
       "      <th>Cells_AreaShape_Zernike_0_0</th>\n",
       "      <th>Cells_AreaShape_Zernike_1_1</th>\n",
       "      <th>Cells_AreaShape_Zernike_2_0</th>\n",
       "      <th>...</th>\n",
       "      <th>Nuclei_Texture_SumEntropy_DNA_5_0</th>\n",
       "      <th>Nuclei_Texture_SumEntropy_Mito_5_0</th>\n",
       "      <th>Nuclei_Texture_SumEntropy_RNA_20_0</th>\n",
       "      <th>Nuclei_Texture_SumEntropy_RNA_5_0</th>\n",
       "      <th>Nuclei_Texture_SumVariance_DNA_20_0</th>\n",
       "      <th>Nuclei_Texture_SumVariance_RNA_20_0</th>\n",
       "      <th>Nuclei_Texture_Variance_DNA_20_0</th>\n",
       "      <th>Nuclei_Texture_Variance_ER_20_0</th>\n",
       "      <th>Nuclei_Texture_Variance_RNA_10_0</th>\n",
       "      <th>Nuclei_Texture_Variance_RNA_20_0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.19575</td>\n",
       "      <td>0.67566</td>\n",
       "      <td>0.40288</td>\n",
       "      <td>0.32633</td>\n",
       "      <td>0.20267</td>\n",
       "      <td>0.71477</td>\n",
       "      <td>0.39122</td>\n",
       "      <td>0.38048</td>\n",
       "      <td>0.61184</td>\n",
       "      <td>0.88375</td>\n",
       "      <td>...</td>\n",
       "      <td>0.60865</td>\n",
       "      <td>0.38869</td>\n",
       "      <td>0.65364</td>\n",
       "      <td>0.65716</td>\n",
       "      <td>0.24912</td>\n",
       "      <td>0.33129</td>\n",
       "      <td>0.28864</td>\n",
       "      <td>0.27106</td>\n",
       "      <td>0.35254</td>\n",
       "      <td>0.32675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.18472</td>\n",
       "      <td>0.66556</td>\n",
       "      <td>0.39721</td>\n",
       "      <td>0.30968</td>\n",
       "      <td>0.20009</td>\n",
       "      <td>0.71345</td>\n",
       "      <td>0.39953</td>\n",
       "      <td>0.37314</td>\n",
       "      <td>0.61074</td>\n",
       "      <td>0.87695</td>\n",
       "      <td>...</td>\n",
       "      <td>0.60682</td>\n",
       "      <td>0.39779</td>\n",
       "      <td>0.64013</td>\n",
       "      <td>0.63120</td>\n",
       "      <td>0.24380</td>\n",
       "      <td>0.30471</td>\n",
       "      <td>0.28554</td>\n",
       "      <td>0.27852</td>\n",
       "      <td>0.35157</td>\n",
       "      <td>0.31637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.18254</td>\n",
       "      <td>0.69650</td>\n",
       "      <td>0.39596</td>\n",
       "      <td>0.33502</td>\n",
       "      <td>0.20420</td>\n",
       "      <td>0.72770</td>\n",
       "      <td>0.39590</td>\n",
       "      <td>0.37023</td>\n",
       "      <td>0.60264</td>\n",
       "      <td>0.88038</td>\n",
       "      <td>...</td>\n",
       "      <td>0.60665</td>\n",
       "      <td>0.39705</td>\n",
       "      <td>0.66616</td>\n",
       "      <td>0.62889</td>\n",
       "      <td>0.25125</td>\n",
       "      <td>0.33549</td>\n",
       "      <td>0.29656</td>\n",
       "      <td>0.25706</td>\n",
       "      <td>0.33868</td>\n",
       "      <td>0.31901</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 685 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Cells_AreaShape_Compactness  Cells_AreaShape_Eccentricity  \\\n",
       "0                      0.19575                       0.67566   \n",
       "1                      0.18472                       0.66556   \n",
       "2                      0.18254                       0.69650   \n",
       "\n",
       "   Cells_AreaShape_Extent  Cells_AreaShape_FormFactor  \\\n",
       "0                 0.40288                     0.32633   \n",
       "1                 0.39721                     0.30968   \n",
       "2                 0.39596                     0.33502   \n",
       "\n",
       "   Cells_AreaShape_MedianRadius  Cells_AreaShape_Orientation  \\\n",
       "0                       0.20267                      0.71477   \n",
       "1                       0.20009                      0.71345   \n",
       "2                       0.20420                      0.72770   \n",
       "\n",
       "   Cells_AreaShape_Solidity  Cells_AreaShape_Zernike_0_0  \\\n",
       "0                   0.39122                      0.38048   \n",
       "1                   0.39953                      0.37314   \n",
       "2                   0.39590                      0.37023   \n",
       "\n",
       "   Cells_AreaShape_Zernike_1_1  Cells_AreaShape_Zernike_2_0  ...  \\\n",
       "0                      0.61184                      0.88375  ...   \n",
       "1                      0.61074                      0.87695  ...   \n",
       "2                      0.60264                      0.88038  ...   \n",
       "\n",
       "   Nuclei_Texture_SumEntropy_DNA_5_0  Nuclei_Texture_SumEntropy_Mito_5_0  \\\n",
       "0                            0.60865                             0.38869   \n",
       "1                            0.60682                             0.39779   \n",
       "2                            0.60665                             0.39705   \n",
       "\n",
       "   Nuclei_Texture_SumEntropy_RNA_20_0  Nuclei_Texture_SumEntropy_RNA_5_0  \\\n",
       "0                             0.65364                            0.65716   \n",
       "1                             0.64013                            0.63120   \n",
       "2                             0.66616                            0.62889   \n",
       "\n",
       "   Nuclei_Texture_SumVariance_DNA_20_0  Nuclei_Texture_SumVariance_RNA_20_0  \\\n",
       "0                              0.24912                              0.33129   \n",
       "1                              0.24380                              0.30471   \n",
       "2                              0.25125                              0.33549   \n",
       "\n",
       "   Nuclei_Texture_Variance_DNA_20_0  Nuclei_Texture_Variance_ER_20_0  \\\n",
       "0                           0.28864                          0.27106   \n",
       "1                           0.28554                          0.27852   \n",
       "2                           0.29656                          0.25706   \n",
       "\n",
       "   Nuclei_Texture_Variance_RNA_10_0  Nuclei_Texture_Variance_RNA_20_0  \n",
       "0                           0.35254                           0.32675  \n",
       "1                           0.35157                           0.31637  \n",
       "2                           0.33868                           0.31901  \n",
       "\n",
       "[3 rows x 685 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(complete_features_df.shape)\n",
    "complete_features_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# VAE of one layer\n",
    "\n",
    "encoder_architecture = [250]\n",
    "decoder_architecture = [250]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "cp_vae = VAE(\n",
    "    input_dim=train_features_df.shape[1],\n",
    "    latent_dim=90,\n",
    "    batch_size=32,\n",
    "    encoder_batch_norm=True,\n",
    "    epochs=58,\n",
    "    learning_rate=0.0001,\n",
    "    encoder_architecture=encoder_architecture,\n",
    "    decoder_architecture=decoder_architecture,\n",
    "    beta=0.06,\n",
    "    verbose=True,\n",
    ")\n",
    "\n",
    "cp_vae.compile_vae()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/58\n",
      "1193/1193 [==============================] - 24s 14ms/step - loss: 122.0518 - recon: 57.4903 - kl: 0.8025 - mmd: 0.0000e+00 - val_loss: 13.1307 - val_recon: 12.2870 - val_kl: 0.8437 - val_mmd: 0.0000e+00\n",
      "Epoch 2/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 9.9690 - recon: 7.7723 - kl: 0.5619 - mmd: 0.0000e+00 - val_loss: 6.1224 - val_recon: 5.5543 - val_kl: 0.5681 - val_mmd: 0.0000e+00\n",
      "Epoch 3/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 5.5351 - recon: 4.6046 - kl: 0.4446 - mmd: 0.0000e+00 - val_loss: 4.1262 - val_recon: 3.7050 - val_kl: 0.4212 - val_mmd: 0.0000e+00\n",
      "Epoch 4/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 3.8641 - recon: 3.1947 - kl: 0.3671 - mmd: 0.0000e+00 - val_loss: 3.1317 - val_recon: 2.7148 - val_kl: 0.4168 - val_mmd: 0.0000e+00\n",
      "Epoch 5/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 2.7834 - recon: 2.2949 - kl: 0.2974 - mmd: 0.0000e+00 - val_loss: 2.3166 - val_recon: 1.9774 - val_kl: 0.3392 - val_mmd: 0.0000e+00\n",
      "Epoch 6/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 2.0759 - recon: 1.7303 - kl: 0.2324 - mmd: 0.0000e+00 - val_loss: 1.7581 - val_recon: 1.4955 - val_kl: 0.2626 - val_mmd: 0.0000e+00\n",
      "Epoch 7/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 1.6471 - recon: 1.3868 - kl: 0.1824 - mmd: 0.0000e+00 - val_loss: 1.4071 - val_recon: 1.2003 - val_kl: 0.2068 - val_mmd: 0.0000e+00\n",
      "Epoch 8/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 1.3614 - recon: 1.1789 - kl: 0.1453 - mmd: 0.0000e+00 - val_loss: 1.2702 - val_recon: 1.0723 - val_kl: 0.1980 - val_mmd: 0.0000e+00\n",
      "Epoch 9/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 1.1888 - recon: 1.0484 - kl: 0.1222 - mmd: 0.0000e+00 - val_loss: 1.1871 - val_recon: 0.9688 - val_kl: 0.2182 - val_mmd: 0.0000e+00\n",
      "Epoch 10/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 1.0809 - recon: 0.9657 - kl: 0.1053 - mmd: 0.0000e+00 - val_loss: 0.9919 - val_recon: 0.8690 - val_kl: 0.1229 - val_mmd: 0.0000e+00\n",
      "Epoch 11/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 1.0219 - recon: 0.9123 - kl: 0.0959 - mmd: 0.0000e+00 - val_loss: 0.9609 - val_recon: 0.8266 - val_kl: 0.1343 - val_mmd: 0.0000e+00\n",
      "Epoch 12/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.9615 - recon: 0.8776 - kl: 0.0887 - mmd: 0.0000e+00 - val_loss: 0.9477 - val_recon: 0.8107 - val_kl: 0.1370 - val_mmd: 0.0000e+00\n",
      "Epoch 13/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.9539 - recon: 0.8542 - kl: 0.0844 - mmd: 0.0000e+00 - val_loss: 0.9092 - val_recon: 0.7753 - val_kl: 0.1339 - val_mmd: 0.0000e+00\n",
      "Epoch 14/58\n",
      "1193/1193 [==============================] - 15s 12ms/step - loss: 0.9141 - recon: 0.8356 - kl: 0.0804 - mmd: 0.0000e+00 - val_loss: 0.8857 - val_recon: 0.7732 - val_kl: 0.1125 - val_mmd: 0.0000e+00\n",
      "Epoch 15/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8945 - recon: 0.8252 - kl: 0.0779 - mmd: 0.0000e+00 - val_loss: 0.8829 - val_recon: 0.7636 - val_kl: 0.1193 - val_mmd: 0.0000e+00\n",
      "Epoch 16/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8989 - recon: 0.8184 - kl: 0.0780 - mmd: 0.0000e+00 - val_loss: 0.8912 - val_recon: 0.7377 - val_kl: 0.1536 - val_mmd: 0.0000e+00\n",
      "Epoch 17/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8889 - recon: 0.8048 - kl: 0.0780 - mmd: 0.0000e+00 - val_loss: 0.9217 - val_recon: 0.7304 - val_kl: 0.1913 - val_mmd: 0.0000e+00\n",
      "Epoch 18/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8931 - recon: 0.7982 - kl: 0.0799 - mmd: 0.0000e+00 - val_loss: 0.8599 - val_recon: 0.7526 - val_kl: 0.1073 - val_mmd: 0.0000e+00\n",
      "Epoch 19/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8650 - recon: 0.7884 - kl: 0.0795 - mmd: 0.0000e+00 - val_loss: 0.8634 - val_recon: 0.7145 - val_kl: 0.1489 - val_mmd: 0.0000e+00\n",
      "Epoch 20/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8593 - recon: 0.7854 - kl: 0.0801 - mmd: 0.0000e+00 - val_loss: 0.8426 - val_recon: 0.7162 - val_kl: 0.1264 - val_mmd: 0.0000e+00\n",
      "Epoch 21/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8775 - recon: 0.7783 - kl: 0.0797 - mmd: 0.0000e+00 - val_loss: 0.8255 - val_recon: 0.7129 - val_kl: 0.1126 - val_mmd: 0.0000e+00\n",
      "Epoch 22/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8590 - recon: 0.7751 - kl: 0.0809 - mmd: 0.0000e+00 - val_loss: 0.8149 - val_recon: 0.7077 - val_kl: 0.1072 - val_mmd: 0.0000e+00\n",
      "Epoch 23/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8618 - recon: 0.7709 - kl: 0.0812 - mmd: 0.0000e+00 - val_loss: 0.8670 - val_recon: 0.6922 - val_kl: 0.1749 - val_mmd: 0.0000e+00\n",
      "Epoch 24/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8364 - recon: 0.7625 - kl: 0.0810 - mmd: 0.0000e+00 - val_loss: 0.8079 - val_recon: 0.7015 - val_kl: 0.1065 - val_mmd: 0.0000e+00\n",
      "Epoch 25/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8257 - recon: 0.7607 - kl: 0.0811 - mmd: 0.0000e+00 - val_loss: 0.9018 - val_recon: 0.6860 - val_kl: 0.2158 - val_mmd: 0.0000e+00\n",
      "Epoch 26/58\n",
      "1193/1193 [==============================] - 16s 13ms/step - loss: 0.8250 - recon: 0.7556 - kl: 0.0829 - mmd: 0.0000e+00 - val_loss: 0.8321 - val_recon: 0.7148 - val_kl: 0.1172 - val_mmd: 0.0000e+00\n",
      "Epoch 27/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8374 - recon: 0.7485 - kl: 0.0831 - mmd: 0.0000e+00 - val_loss: 0.8068 - val_recon: 0.6934 - val_kl: 0.1134 - val_mmd: 0.0000e+00\n",
      "Epoch 28/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8419 - recon: 0.7445 - kl: 0.0830 - mmd: 0.0000e+00 - val_loss: 0.8116 - val_recon: 0.6785 - val_kl: 0.1331 - val_mmd: 0.0000e+00\n",
      "Epoch 29/58\n",
      "1193/1193 [==============================] - 15s 12ms/step - loss: 0.8296 - recon: 0.7455 - kl: 0.0833 - mmd: 0.0000e+00 - val_loss: 0.8063 - val_recon: 0.6738 - val_kl: 0.1325 - val_mmd: 0.0000e+00\n",
      "Epoch 30/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8295 - recon: 0.7398 - kl: 0.0840 - mmd: 0.0000e+00 - val_loss: 0.8255 - val_recon: 0.6768 - val_kl: 0.1486 - val_mmd: 0.0000e+00\n",
      "Epoch 31/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8230 - recon: 0.7344 - kl: 0.0847 - mmd: 0.0000e+00 - val_loss: 0.7938 - val_recon: 0.6912 - val_kl: 0.1026 - val_mmd: 0.0000e+00\n",
      "Epoch 32/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8124 - recon: 0.7312 - kl: 0.0841 - mmd: 0.0000e+00 - val_loss: 0.8136 - val_recon: 0.6860 - val_kl: 0.1276 - val_mmd: 0.0000e+00\n",
      "Epoch 33/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8257 - recon: 0.7265 - kl: 0.0850 - mmd: 0.0000e+00 - val_loss: 0.8271 - val_recon: 0.6828 - val_kl: 0.1443 - val_mmd: 0.0000e+00\n",
      "Epoch 34/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8147 - recon: 0.7226 - kl: 0.0861 - mmd: 0.0000e+00 - val_loss: 0.8507 - val_recon: 0.6922 - val_kl: 0.1585 - val_mmd: 0.0000e+00\n",
      "Epoch 35/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8032 - recon: 0.7172 - kl: 0.0861 - mmd: 0.0000e+00 - val_loss: 0.7794 - val_recon: 0.6675 - val_kl: 0.1119 - val_mmd: 0.0000e+00\n",
      "Epoch 36/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.7961 - recon: 0.7174 - kl: 0.0868 - mmd: 0.0000e+00 - val_loss: 0.7957 - val_recon: 0.6531 - val_kl: 0.1426 - val_mmd: 0.0000e+00\n",
      "Epoch 37/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8001 - recon: 0.7127 - kl: 0.0883 - mmd: 0.0000e+00 - val_loss: 0.7616 - val_recon: 0.6514 - val_kl: 0.1102 - val_mmd: 0.0000e+00\n",
      "Epoch 38/58\n",
      "1193/1193 [==============================] - 15s 13ms/step - loss: 0.8076 - recon: 0.7088 - kl: 0.0875 - mmd: 0.0000e+00 - val_loss: 0.8140 - val_recon: 0.6610 - val_kl: 0.1531 - val_mmd: 0.0000e+00\n",
      "Epoch 39/58\n",
      "1193/1193 [==============================] - 16s 13ms/step - loss: 0.7769 - recon: 0.7061 - kl: 0.0869 - mmd: 0.0000e+00 - val_loss: 0.8017 - val_recon: 0.6455 - val_kl: 0.1562 - val_mmd: 0.0000e+00\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 40/58\n",
      "1193/1193 [==============================] - 16s 13ms/step - loss: 0.7782 - recon: 0.7039 - kl: 0.0875 - mmd: 0.0000e+00 - val_loss: 0.8067 - val_recon: 0.6524 - val_kl: 0.1542 - val_mmd: 0.0000e+00\n",
      "Epoch 41/58\n",
      "1193/1193 [==============================] - 21s 18ms/step - loss: 0.8114 - recon: 0.7011 - kl: 0.0875 - mmd: 0.0000e+00 - val_loss: 0.7506 - val_recon: 0.6414 - val_kl: 0.1091 - val_mmd: 0.0000e+00\n",
      "Epoch 42/58\n",
      "1193/1193 [==============================] - 26s 22ms/step - loss: 0.7806 - recon: 0.6999 - kl: 0.0869 - mmd: 0.0000e+00 - val_loss: 0.7728 - val_recon: 0.6575 - val_kl: 0.1153 - val_mmd: 0.0000e+00\n",
      "Epoch 43/58\n",
      "1193/1193 [==============================] - 18s 15ms/step - loss: 0.7794 - recon: 0.6963 - kl: 0.0875 - mmd: 0.0000e+00 - val_loss: 0.7716 - val_recon: 0.6526 - val_kl: 0.1190 - val_mmd: 0.0000e+00\n",
      "Epoch 44/58\n",
      "1193/1193 [==============================] - 16s 14ms/step - loss: 0.7960 - recon: 0.6974 - kl: 0.0867 - mmd: 0.0000e+00 - val_loss: 0.8057 - val_recon: 0.6478 - val_kl: 0.1579 - val_mmd: 0.0000e+00\n",
      "Epoch 45/58\n",
      "1193/1193 [==============================] - 17s 14ms/step - loss: 0.7572 - recon: 0.6936 - kl: 0.0867 - mmd: 0.0000e+00 - val_loss: 0.7657 - val_recon: 0.6390 - val_kl: 0.1267 - val_mmd: 0.0000e+00\n",
      "Epoch 46/58\n",
      "1193/1193 [==============================] - 17s 14ms/step - loss: 0.7731 - recon: 0.6930 - kl: 0.0871 - mmd: 0.0000e+00 - val_loss: 0.7587 - val_recon: 0.6346 - val_kl: 0.1241 - val_mmd: 0.0000e+00\n",
      "Epoch 47/58\n",
      "1193/1193 [==============================] - 16s 14ms/step - loss: 0.7669 - recon: 0.6918 - kl: 0.0865 - mmd: 0.0000e+00 - val_loss: 0.7665 - val_recon: 0.6425 - val_kl: 0.1240 - val_mmd: 0.0000e+00\n",
      "Epoch 48/58\n",
      "1193/1193 [==============================] - 16s 14ms/step - loss: 0.7993 - recon: 0.6878 - kl: 0.0865 - mmd: 0.0000e+00 - val_loss: 0.7503 - val_recon: 0.6362 - val_kl: 0.1141 - val_mmd: 0.0000e+00\n",
      "Epoch 49/58\n",
      "1193/1193 [==============================] - 16s 14ms/step - loss: 0.7873 - recon: 0.6892 - kl: 0.0870 - mmd: 0.0000e+00 - val_loss: 0.7606 - val_recon: 0.6382 - val_kl: 0.1224 - val_mmd: 0.0000e+00\n",
      "Epoch 50/58\n",
      "1193/1193 [==============================] - 16s 14ms/step - loss: 0.7701 - recon: 0.6849 - kl: 0.0875 - mmd: 0.0000e+00 - val_loss: 0.7632 - val_recon: 0.6440 - val_kl: 0.1192 - val_mmd: 0.0000e+00\n",
      "Epoch 51/58\n",
      "1193/1193 [==============================] - 16s 13ms/step - loss: 0.7857 - recon: 0.6856 - kl: 0.0867 - mmd: 0.0000e+00 - val_loss: 0.7418 - val_recon: 0.6336 - val_kl: 0.1082 - val_mmd: 0.0000e+00\n",
      "Epoch 52/58\n",
      "1193/1193 [==============================] - 16s 13ms/step - loss: 0.7580 - recon: 0.6835 - kl: 0.0860 - mmd: 0.0000e+00 - val_loss: 0.7614 - val_recon: 0.6439 - val_kl: 0.1174 - val_mmd: 0.0000e+00\n",
      "Epoch 53/58\n",
      "1193/1193 [==============================] - 16s 13ms/step - loss: 0.7694 - recon: 0.6804 - kl: 0.0864 - mmd: 0.0000e+00 - val_loss: 0.7443 - val_recon: 0.6284 - val_kl: 0.1160 - val_mmd: 0.0000e+00\n",
      "Epoch 54/58\n",
      "1193/1193 [==============================] - 16s 13ms/step - loss: 0.7720 - recon: 0.6785 - kl: 0.0862 - mmd: 0.0000e+00 - val_loss: 0.7432 - val_recon: 0.6372 - val_kl: 0.1061 - val_mmd: 0.0000e+00\n",
      "Epoch 55/58\n",
      "1193/1193 [==============================] - 16s 13ms/step - loss: 0.7515 - recon: 0.6760 - kl: 0.0861 - mmd: 0.0000e+00 - val_loss: 0.7393 - val_recon: 0.6286 - val_kl: 0.1106 - val_mmd: 0.0000e+00\n",
      "Epoch 56/58\n",
      "1193/1193 [==============================] - 16s 13ms/step - loss: 0.7481 - recon: 0.6773 - kl: 0.0860 - mmd: 0.0000e+00 - val_loss: 0.7686 - val_recon: 0.6279 - val_kl: 0.1406 - val_mmd: 0.0000e+00\n",
      "Epoch 57/58\n",
      "1193/1193 [==============================] - 16s 13ms/step - loss: 0.7760 - recon: 0.6759 - kl: 0.0858 - mmd: 0.0000e+00 - val_loss: 0.7301 - val_recon: 0.6223 - val_kl: 0.1078 - val_mmd: 0.0000e+00\n",
      "Epoch 58/58\n",
      "1193/1193 [==============================] - 16s 13ms/step - loss: 0.7491 - recon: 0.6746 - kl: 0.0859 - mmd: 0.0000e+00 - val_loss: 0.7633 - val_recon: 0.6399 - val_kl: 0.1234 - val_mmd: 0.0000e+00\n"
     ]
    }
   ],
   "source": [
    "cp_vae.train(x_train=train_features_df, x_test=valid_features_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tensorflow.python.keras.engine.functional.Functional at 0x7fda0c472450>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cp_vae.vae"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
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       "        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>loss</th>\n",
       "      <th>recon</th>\n",
       "      <th>kl</th>\n",
       "      <th>mmd</th>\n",
       "      <th>val_loss</th>\n",
       "      <th>val_recon</th>\n",
       "      <th>val_kl</th>\n",
       "      <th>val_mmd</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>58.292843</td>\n",
       "      <td>57.490314</td>\n",
       "      <td>0.802487</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.130677</td>\n",
       "      <td>12.287017</td>\n",
       "      <td>0.843660</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8.334225</td>\n",
       "      <td>7.772343</td>\n",
       "      <td>0.561887</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.122387</td>\n",
       "      <td>5.554319</td>\n",
       "      <td>0.568067</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5.049180</td>\n",
       "      <td>4.604609</td>\n",
       "      <td>0.444574</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.126220</td>\n",
       "      <td>3.705049</td>\n",
       "      <td>0.421171</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.561778</td>\n",
       "      <td>3.194679</td>\n",
       "      <td>0.367099</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.131655</td>\n",
       "      <td>2.714819</td>\n",
       "      <td>0.416835</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.592312</td>\n",
       "      <td>2.294902</td>\n",
       "      <td>0.297410</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.316570</td>\n",
       "      <td>1.977379</td>\n",
       "      <td>0.339189</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1.962671</td>\n",
       "      <td>1.730283</td>\n",
       "      <td>0.232389</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.758110</td>\n",
       "      <td>1.495534</td>\n",
       "      <td>0.262575</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1.569218</td>\n",
       "      <td>1.386809</td>\n",
       "      <td>0.182410</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.407089</td>\n",
       "      <td>1.200291</td>\n",
       "      <td>0.206797</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1.324177</td>\n",
       "      <td>1.178900</td>\n",
       "      <td>0.145277</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.270231</td>\n",
       "      <td>1.072258</td>\n",
       "      <td>0.197974</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.170606</td>\n",
       "      <td>1.048365</td>\n",
       "      <td>0.122242</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.187065</td>\n",
       "      <td>0.968830</td>\n",
       "      <td>0.218234</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1.070993</td>\n",
       "      <td>0.965696</td>\n",
       "      <td>0.105298</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.991869</td>\n",
       "      <td>0.869011</td>\n",
       "      <td>0.122858</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1.008211</td>\n",
       "      <td>0.912270</td>\n",
       "      <td>0.095941</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.960935</td>\n",
       "      <td>0.826620</td>\n",
       "      <td>0.134315</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.966302</td>\n",
       "      <td>0.877577</td>\n",
       "      <td>0.088725</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.947689</td>\n",
       "      <td>0.810731</td>\n",
       "      <td>0.136958</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.938624</td>\n",
       "      <td>0.854178</td>\n",
       "      <td>0.084446</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.909216</td>\n",
       "      <td>0.775311</td>\n",
       "      <td>0.133905</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.916012</td>\n",
       "      <td>0.835567</td>\n",
       "      <td>0.080446</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.885708</td>\n",
       "      <td>0.773219</td>\n",
       "      <td>0.112489</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.903076</td>\n",
       "      <td>0.825194</td>\n",
       "      <td>0.077883</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.882914</td>\n",
       "      <td>0.763579</td>\n",
       "      <td>0.119335</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.896349</td>\n",
       "      <td>0.818392</td>\n",
       "      <td>0.077956</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.891246</td>\n",
       "      <td>0.737655</td>\n",
       "      <td>0.153590</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.882826</td>\n",
       "      <td>0.804777</td>\n",
       "      <td>0.078049</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.921716</td>\n",
       "      <td>0.730382</td>\n",
       "      <td>0.191333</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.878034</td>\n",
       "      <td>0.798163</td>\n",
       "      <td>0.079870</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.859941</td>\n",
       "      <td>0.752609</td>\n",
       "      <td>0.107332</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.867889</td>\n",
       "      <td>0.788359</td>\n",
       "      <td>0.079529</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.863400</td>\n",
       "      <td>0.714460</td>\n",
       "      <td>0.148939</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.865541</td>\n",
       "      <td>0.785436</td>\n",
       "      <td>0.080105</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.842635</td>\n",
       "      <td>0.716212</td>\n",
       "      <td>0.126423</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.858017</td>\n",
       "      <td>0.778286</td>\n",
       "      <td>0.079730</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.825457</td>\n",
       "      <td>0.712887</td>\n",
       "      <td>0.112570</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.855983</td>\n",
       "      <td>0.775057</td>\n",
       "      <td>0.080927</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.814915</td>\n",
       "      <td>0.707745</td>\n",
       "      <td>0.107170</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.852087</td>\n",
       "      <td>0.770850</td>\n",
       "      <td>0.081236</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.867035</td>\n",
       "      <td>0.692162</td>\n",
       "      <td>0.174874</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.843430</td>\n",
       "      <td>0.762468</td>\n",
       "      <td>0.080962</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.807947</td>\n",
       "      <td>0.701491</td>\n",
       "      <td>0.106457</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.841811</td>\n",
       "      <td>0.760694</td>\n",
       "      <td>0.081116</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.901783</td>\n",
       "      <td>0.686007</td>\n",
       "      <td>0.215777</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.838494</td>\n",
       "      <td>0.755561</td>\n",
       "      <td>0.082933</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.832076</td>\n",
       "      <td>0.714846</td>\n",
       "      <td>0.117230</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.831580</td>\n",
       "      <td>0.748502</td>\n",
       "      <td>0.083078</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.806778</td>\n",
       "      <td>0.693396</td>\n",
       "      <td>0.113382</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.827480</td>\n",
       "      <td>0.744469</td>\n",
       "      <td>0.083010</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.811622</td>\n",
       "      <td>0.678549</td>\n",
       "      <td>0.133072</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.828759</td>\n",
       "      <td>0.745463</td>\n",
       "      <td>0.083295</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.806330</td>\n",
       "      <td>0.673810</td>\n",
       "      <td>0.132520</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.823791</td>\n",
       "      <td>0.739808</td>\n",
       "      <td>0.083983</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.825452</td>\n",
       "      <td>0.676825</td>\n",
       "      <td>0.148627</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.819088</td>\n",
       "      <td>0.734386</td>\n",
       "      <td>0.084701</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.793795</td>\n",
       "      <td>0.691203</td>\n",
       "      <td>0.102592</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0.815331</td>\n",
       "      <td>0.731194</td>\n",
       "      <td>0.084137</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.813607</td>\n",
       "      <td>0.685977</td>\n",
       "      <td>0.127630</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>0.811477</td>\n",
       "      <td>0.726475</td>\n",
       "      <td>0.085002</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.827063</td>\n",
       "      <td>0.682795</td>\n",
       "      <td>0.144268</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>0.808707</td>\n",
       "      <td>0.722607</td>\n",
       "      <td>0.086100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.850694</td>\n",
       "      <td>0.692196</td>\n",
       "      <td>0.158498</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>0.803319</td>\n",
       "      <td>0.717189</td>\n",
       "      <td>0.086130</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.779375</td>\n",
       "      <td>0.667457</td>\n",
       "      <td>0.111919</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.804148</td>\n",
       "      <td>0.717393</td>\n",
       "      <td>0.086756</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.795716</td>\n",
       "      <td>0.653084</td>\n",
       "      <td>0.142632</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>0.801090</td>\n",
       "      <td>0.712749</td>\n",
       "      <td>0.088341</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.761575</td>\n",
       "      <td>0.651352</td>\n",
       "      <td>0.110223</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>0.796346</td>\n",
       "      <td>0.708847</td>\n",
       "      <td>0.087499</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.814031</td>\n",
       "      <td>0.660967</td>\n",
       "      <td>0.153064</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>0.793020</td>\n",
       "      <td>0.706086</td>\n",
       "      <td>0.086934</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.801730</td>\n",
       "      <td>0.645492</td>\n",
       "      <td>0.156238</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>0.791431</td>\n",
       "      <td>0.703941</td>\n",
       "      <td>0.087489</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.806681</td>\n",
       "      <td>0.652435</td>\n",
       "      <td>0.154246</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.788677</td>\n",
       "      <td>0.701146</td>\n",
       "      <td>0.087531</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.750568</td>\n",
       "      <td>0.641441</td>\n",
       "      <td>0.109127</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>0.786748</td>\n",
       "      <td>0.699854</td>\n",
       "      <td>0.086893</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.772837</td>\n",
       "      <td>0.657501</td>\n",
       "      <td>0.115336</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>0.783791</td>\n",
       "      <td>0.696254</td>\n",
       "      <td>0.087538</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.771642</td>\n",
       "      <td>0.652626</td>\n",
       "      <td>0.119016</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>0.784080</td>\n",
       "      <td>0.697353</td>\n",
       "      <td>0.086728</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.805721</td>\n",
       "      <td>0.647818</td>\n",
       "      <td>0.157903</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>0.780279</td>\n",
       "      <td>0.693559</td>\n",
       "      <td>0.086719</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.765681</td>\n",
       "      <td>0.638958</td>\n",
       "      <td>0.126722</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0.780051</td>\n",
       "      <td>0.692993</td>\n",
       "      <td>0.087060</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.758702</td>\n",
       "      <td>0.634586</td>\n",
       "      <td>0.124116</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>0.778321</td>\n",
       "      <td>0.691821</td>\n",
       "      <td>0.086501</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.766496</td>\n",
       "      <td>0.642500</td>\n",
       "      <td>0.123996</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>0.774285</td>\n",
       "      <td>0.687783</td>\n",
       "      <td>0.086503</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.750320</td>\n",
       "      <td>0.636175</td>\n",
       "      <td>0.114145</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>0.776202</td>\n",
       "      <td>0.689197</td>\n",
       "      <td>0.087006</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.760580</td>\n",
       "      <td>0.638161</td>\n",
       "      <td>0.122418</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>0.772384</td>\n",
       "      <td>0.684881</td>\n",
       "      <td>0.087502</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.763206</td>\n",
       "      <td>0.644045</td>\n",
       "      <td>0.119161</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>0.772319</td>\n",
       "      <td>0.685643</td>\n",
       "      <td>0.086675</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.741828</td>\n",
       "      <td>0.633631</td>\n",
       "      <td>0.108198</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>0.769450</td>\n",
       "      <td>0.683497</td>\n",
       "      <td>0.085953</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.761362</td>\n",
       "      <td>0.643923</td>\n",
       "      <td>0.117439</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>0.766765</td>\n",
       "      <td>0.680400</td>\n",
       "      <td>0.086364</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.744317</td>\n",
       "      <td>0.628353</td>\n",
       "      <td>0.115964</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>0.764705</td>\n",
       "      <td>0.678529</td>\n",
       "      <td>0.086175</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.743250</td>\n",
       "      <td>0.637181</td>\n",
       "      <td>0.106069</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>0.762114</td>\n",
       "      <td>0.675966</td>\n",
       "      <td>0.086148</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.739259</td>\n",
       "      <td>0.628611</td>\n",
       "      <td>0.110648</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>0.763310</td>\n",
       "      <td>0.677322</td>\n",
       "      <td>0.085989</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.768596</td>\n",
       "      <td>0.627949</td>\n",
       "      <td>0.140647</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>0.761681</td>\n",
       "      <td>0.675862</td>\n",
       "      <td>0.085818</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.730082</td>\n",
       "      <td>0.622329</td>\n",
       "      <td>0.107753</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>0.760481</td>\n",
       "      <td>0.674554</td>\n",
       "      <td>0.085928</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.763306</td>\n",
       "      <td>0.639920</td>\n",
       "      <td>0.123387</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         loss      recon        kl  mmd   val_loss  val_recon    val_kl  \\\n",
       "0   58.292843  57.490314  0.802487  0.0  13.130677  12.287017  0.843660   \n",
       "1    8.334225   7.772343  0.561887  0.0   6.122387   5.554319  0.568067   \n",
       "2    5.049180   4.604609  0.444574  0.0   4.126220   3.705049  0.421171   \n",
       "3    3.561778   3.194679  0.367099  0.0   3.131655   2.714819  0.416835   \n",
       "4    2.592312   2.294902  0.297410  0.0   2.316570   1.977379  0.339189   \n",
       "5    1.962671   1.730283  0.232389  0.0   1.758110   1.495534  0.262575   \n",
       "6    1.569218   1.386809  0.182410  0.0   1.407089   1.200291  0.206797   \n",
       "7    1.324177   1.178900  0.145277  0.0   1.270231   1.072258  0.197974   \n",
       "8    1.170606   1.048365  0.122242  0.0   1.187065   0.968830  0.218234   \n",
       "9    1.070993   0.965696  0.105298  0.0   0.991869   0.869011  0.122858   \n",
       "10   1.008211   0.912270  0.095941  0.0   0.960935   0.826620  0.134315   \n",
       "11   0.966302   0.877577  0.088725  0.0   0.947689   0.810731  0.136958   \n",
       "12   0.938624   0.854178  0.084446  0.0   0.909216   0.775311  0.133905   \n",
       "13   0.916012   0.835567  0.080446  0.0   0.885708   0.773219  0.112489   \n",
       "14   0.903076   0.825194  0.077883  0.0   0.882914   0.763579  0.119335   \n",
       "15   0.896349   0.818392  0.077956  0.0   0.891246   0.737655  0.153590   \n",
       "16   0.882826   0.804777  0.078049  0.0   0.921716   0.730382  0.191333   \n",
       "17   0.878034   0.798163  0.079870  0.0   0.859941   0.752609  0.107332   \n",
       "18   0.867889   0.788359  0.079529  0.0   0.863400   0.714460  0.148939   \n",
       "19   0.865541   0.785436  0.080105  0.0   0.842635   0.716212  0.126423   \n",
       "20   0.858017   0.778286  0.079730  0.0   0.825457   0.712887  0.112570   \n",
       "21   0.855983   0.775057  0.080927  0.0   0.814915   0.707745  0.107170   \n",
       "22   0.852087   0.770850  0.081236  0.0   0.867035   0.692162  0.174874   \n",
       "23   0.843430   0.762468  0.080962  0.0   0.807947   0.701491  0.106457   \n",
       "24   0.841811   0.760694  0.081116  0.0   0.901783   0.686007  0.215777   \n",
       "25   0.838494   0.755561  0.082933  0.0   0.832076   0.714846  0.117230   \n",
       "26   0.831580   0.748502  0.083078  0.0   0.806778   0.693396  0.113382   \n",
       "27   0.827480   0.744469  0.083010  0.0   0.811622   0.678549  0.133072   \n",
       "28   0.828759   0.745463  0.083295  0.0   0.806330   0.673810  0.132520   \n",
       "29   0.823791   0.739808  0.083983  0.0   0.825452   0.676825  0.148627   \n",
       "30   0.819088   0.734386  0.084701  0.0   0.793795   0.691203  0.102592   \n",
       "31   0.815331   0.731194  0.084137  0.0   0.813607   0.685977  0.127630   \n",
       "32   0.811477   0.726475  0.085002  0.0   0.827063   0.682795  0.144268   \n",
       "33   0.808707   0.722607  0.086100  0.0   0.850694   0.692196  0.158498   \n",
       "34   0.803319   0.717189  0.086130  0.0   0.779375   0.667457  0.111919   \n",
       "35   0.804148   0.717393  0.086756  0.0   0.795716   0.653084  0.142632   \n",
       "36   0.801090   0.712749  0.088341  0.0   0.761575   0.651352  0.110223   \n",
       "37   0.796346   0.708847  0.087499  0.0   0.814031   0.660967  0.153064   \n",
       "38   0.793020   0.706086  0.086934  0.0   0.801730   0.645492  0.156238   \n",
       "39   0.791431   0.703941  0.087489  0.0   0.806681   0.652435  0.154246   \n",
       "40   0.788677   0.701146  0.087531  0.0   0.750568   0.641441  0.109127   \n",
       "41   0.786748   0.699854  0.086893  0.0   0.772837   0.657501  0.115336   \n",
       "42   0.783791   0.696254  0.087538  0.0   0.771642   0.652626  0.119016   \n",
       "43   0.784080   0.697353  0.086728  0.0   0.805721   0.647818  0.157903   \n",
       "44   0.780279   0.693559  0.086719  0.0   0.765681   0.638958  0.126722   \n",
       "45   0.780051   0.692993  0.087060  0.0   0.758702   0.634586  0.124116   \n",
       "46   0.778321   0.691821  0.086501  0.0   0.766496   0.642500  0.123996   \n",
       "47   0.774285   0.687783  0.086503  0.0   0.750320   0.636175  0.114145   \n",
       "48   0.776202   0.689197  0.087006  0.0   0.760580   0.638161  0.122418   \n",
       "49   0.772384   0.684881  0.087502  0.0   0.763206   0.644045  0.119161   \n",
       "50   0.772319   0.685643  0.086675  0.0   0.741828   0.633631  0.108198   \n",
       "51   0.769450   0.683497  0.085953  0.0   0.761362   0.643923  0.117439   \n",
       "52   0.766765   0.680400  0.086364  0.0   0.744317   0.628353  0.115964   \n",
       "53   0.764705   0.678529  0.086175  0.0   0.743250   0.637181  0.106069   \n",
       "54   0.762114   0.675966  0.086148  0.0   0.739259   0.628611  0.110648   \n",
       "55   0.763310   0.677322  0.085989  0.0   0.768596   0.627949  0.140647   \n",
       "56   0.761681   0.675862  0.085818  0.0   0.730082   0.622329  0.107753   \n",
       "57   0.760481   0.674554  0.085928  0.0   0.763306   0.639920  0.123387   \n",
       "\n",
       "    val_mmd  \n",
       "0       0.0  \n",
       "1       0.0  \n",
       "2       0.0  \n",
       "3       0.0  \n",
       "4       0.0  \n",
       "5       0.0  \n",
       "6       0.0  \n",
       "7       0.0  \n",
       "8       0.0  \n",
       "9       0.0  \n",
       "10      0.0  \n",
       "11      0.0  \n",
       "12      0.0  \n",
       "13      0.0  \n",
       "14      0.0  \n",
       "15      0.0  \n",
       "16      0.0  \n",
       "17      0.0  \n",
       "18      0.0  \n",
       "19      0.0  \n",
       "20      0.0  \n",
       "21      0.0  \n",
       "22      0.0  \n",
       "23      0.0  \n",
       "24      0.0  \n",
       "25      0.0  \n",
       "26      0.0  \n",
       "27      0.0  \n",
       "28      0.0  \n",
       "29      0.0  \n",
       "30      0.0  \n",
       "31      0.0  \n",
       "32      0.0  \n",
       "33      0.0  \n",
       "34      0.0  \n",
       "35      0.0  \n",
       "36      0.0  \n",
       "37      0.0  \n",
       "38      0.0  \n",
       "39      0.0  \n",
       "40      0.0  \n",
       "41      0.0  \n",
       "42      0.0  \n",
       "43      0.0  \n",
       "44      0.0  \n",
       "45      0.0  \n",
       "46      0.0  \n",
       "47      0.0  \n",
       "48      0.0  \n",
       "49      0.0  \n",
       "50      0.0  \n",
       "51      0.0  \n",
       "52      0.0  \n",
       "53      0.0  \n",
       "54      0.0  \n",
       "55      0.0  \n",
       "56      0.0  \n",
       "57      0.0  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Save training performance\n",
    "history_df = pd.DataFrame(cp_vae.vae.history.history)\n",
    "history_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 5))\n",
    "plt.plot(history_df[\"loss\"], label=\"Training data\")\n",
    "plt.plot(history_df[\"val_loss\"], label=\"Validation data\")\n",
    "plt.title(\"Loss for VAE training on Cell Painting Level 4 data\")\n",
    "plt.ylabel(\"MSE + KL Divergence\")\n",
    "plt.xlabel(\"No. Epoch\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "158/158 [==============================] - 1s 6ms/step - loss: 0.7348 - recon: 0.6182 - kl: 0.1166 - mmd: 0.0000e+00\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[0.7348112463951111, 0.6181932687759399, 0.1166178360581398, 0.0]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cp_vae.vae.evaluate(test_features_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "55.54928503745787"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reconstruction = pd.DataFrame(cp_vae.vae.predict(test_features_df), columns=cp_features)\n",
    "(sum(sum((np.array(test_features_df) - np.array(reconstruction)) ** 2))) ** 0.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#latent space heatmap\n",
    "fig, ax = plt.subplots(figsize=(10, 10))\n",
    "encoder = cp_vae.encoder_block[\"encoder\"]\n",
    "latent = np.array(encoder.predict(test_features_df)[2])\n",
    "seaborn.heatmap(latent, ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "reconstruction = pd.DataFrame(cp_vae.vae.predict(test_features_df), columns=cp_features)\n",
    "pca = PCA(n_components=2).fit(test_features_df)\n",
    "pca_reconstructed_latent_df = pd.DataFrame(pca.transform(reconstruction))\n",
    "pca_test_latent_df = pd.DataFrame(pca.transform(test_features_df))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fd9c408b190>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure(figsize=(10, 10), dpi=80)\n",
    "plt.scatter(pca_test_latent_df[0],pca_test_latent_df[1], marker = \".\", alpha = 0.5)\n",
    "plt.scatter(pca_reconstructed_latent_df[0],pca_reconstructed_latent_df[1], marker = \".\", alpha = 0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "decoder = cp_vae.decoder_block[\"decoder\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fd92b932b50>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pca_training = PCA(n_components=2).fit(train_features_df)\n",
    "\n",
    "simulated_df = pd.DataFrame(np.random.normal(size=(40242, 90)), columns=np.arange(0,90))\n",
    "reconstruction_of_simulated = decoder.predict(simulated_df)\n",
    "pca_reconstruction_of_simulated = pd.DataFrame(pca_training.transform(reconstruction_of_simulated))\n",
    "pca_train_latent_df = pd.DataFrame(pca_training.transform(train_features_df))\n",
    "\n",
    "fig, (ax1,ax2) = plt.subplots(1, 2, figsize=(16,8), sharey = True, sharex = True)\n",
    "ax1.scatter(pca_train_latent_df[0],pca_train_latent_df[1], marker = \".\", alpha = 0.5)\n",
    "ax2.scatter(pca_reconstruction_of_simulated[0],pca_reconstruction_of_simulated[1], marker = \".\", alpha = 0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.706190140019404"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.spatial.distance import directed_hausdorff\n",
    "max(directed_hausdorff(reconstruction_of_simulated, train_features_df)[0],directed_hausdorff(train_features_df,reconstruction_of_simulated)[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "#NOTE: IF YOU RUN THIS, YOU WILL NOT BE ABLE TO REPRODUCE THE EXACT RESULTS IN THE EXPERIMENT\n",
    "latent_complete = np.array(encoder.predict(complete_features_df)[2])\n",
    "latent_df = pd.DataFrame(latent_complete)\n",
    "latent_df.to_csv(\"../3.application/level4Latent_leaveOut.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: level4Decoder_leaveOut/assets\n"
     ]
    }
   ],
   "source": [
    "#NOTE: IF YOU RUN THIS, YOU WILL NOT BE ABLE TO REPRODUCE THE EXACT RESULTS IN THE EXPERIMENT\n",
    "decoder.save(\"models/level4Decoder_leaveOut\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: level4Encoder_leaveOut/assets\n"
     ]
    }
   ],
   "source": [
    "encoder.save(\"models/level4Encoder_leaveOut\")"
   ]
  }
 ],
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