DeppTrianglePython.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "tf.compat.v1.disable_eager_execution()\n",
    "\n",
    "from tensorflow import keras\n",
    "from tensorflow.keras import layers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"data_wit_features.csv\", sep=\";\", decimal=\",\")\n",
    "df.drop(\"Unnamed: 0\", axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "scrolled": true
   },
   "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>lob</th>\n",
       "      <th>group_code</th>\n",
       "      <th>group_name</th>\n",
       "      <th>accident_year</th>\n",
       "      <th>development_year</th>\n",
       "      <th>development_lag</th>\n",
       "      <th>incurred_loss</th>\n",
       "      <th>cumulative_paid_loss</th>\n",
       "      <th>bulk_loss</th>\n",
       "      <th>earned_premium_direct</th>\n",
       "      <th>...</th>\n",
       "      <th>posted_reserve_97</th>\n",
       "      <th>calendar_year</th>\n",
       "      <th>incremental_paid_loss</th>\n",
       "      <th>case_reserves</th>\n",
       "      <th>incremental_paid_actual</th>\n",
       "      <th>incremental_paid</th>\n",
       "      <th>cumulative_paid_actual</th>\n",
       "      <th>cumulative_paid</th>\n",
       "      <th>case_reserves_actual</th>\n",
       "      <th>bucket</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>commercial_auto</td>\n",
       "      <td>10022</td>\n",
       "      <td>Agway Ins Co</td>\n",
       "      <td>1988</td>\n",
       "      <td>1988</td>\n",
       "      <td>1</td>\n",
       "      <td>179</td>\n",
       "      <td>72</td>\n",
       "      <td>71</td>\n",
       "      <td>1070</td>\n",
       "      <td>...</td>\n",
       "      <td>1400</td>\n",
       "      <td>1988</td>\n",
       "      <td>72</td>\n",
       "      <td>0.108850</td>\n",
       "      <td>0.073245</td>\n",
       "      <td>0.073245</td>\n",
       "      <td>0.073245</td>\n",
       "      <td>0.073245</td>\n",
       "      <td>0.108850</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>commercial_auto</td>\n",
       "      <td>10022</td>\n",
       "      <td>Agway Ins Co</td>\n",
       "      <td>1988</td>\n",
       "      <td>1989</td>\n",
       "      <td>2</td>\n",
       "      <td>151</td>\n",
       "      <td>122</td>\n",
       "      <td>17</td>\n",
       "      <td>1070</td>\n",
       "      <td>...</td>\n",
       "      <td>1400</td>\n",
       "      <td>1989</td>\n",
       "      <td>50</td>\n",
       "      <td>0.029502</td>\n",
       "      <td>0.050865</td>\n",
       "      <td>0.050865</td>\n",
       "      <td>0.124110</td>\n",
       "      <td>0.124110</td>\n",
       "      <td>0.029502</td>\n",
       "      <td>train</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>commercial_auto</td>\n",
       "      <td>10022</td>\n",
       "      <td>Agway Ins Co</td>\n",
       "      <td>1988</td>\n",
       "      <td>1990</td>\n",
       "      <td>3</td>\n",
       "      <td>163</td>\n",
       "      <td>142</td>\n",
       "      <td>0</td>\n",
       "      <td>1070</td>\n",
       "      <td>...</td>\n",
       "      <td>1400</td>\n",
       "      <td>1990</td>\n",
       "      <td>20</td>\n",
       "      <td>0.021363</td>\n",
       "      <td>0.020346</td>\n",
       "      <td>0.020346</td>\n",
       "      <td>0.144456</td>\n",
       "      <td>0.144456</td>\n",
       "      <td>0.021363</td>\n",
       "      <td>train</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>commercial_auto</td>\n",
       "      <td>10022</td>\n",
       "      <td>Agway Ins Co</td>\n",
       "      <td>1988</td>\n",
       "      <td>1991</td>\n",
       "      <td>4</td>\n",
       "      <td>172</td>\n",
       "      <td>156</td>\n",
       "      <td>0</td>\n",
       "      <td>1070</td>\n",
       "      <td>...</td>\n",
       "      <td>1400</td>\n",
       "      <td>1991</td>\n",
       "      <td>14</td>\n",
       "      <td>0.016277</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>0.158698</td>\n",
       "      <td>0.158698</td>\n",
       "      <td>0.016277</td>\n",
       "      <td>train</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>commercial_auto</td>\n",
       "      <td>10022</td>\n",
       "      <td>Agway Ins Co</td>\n",
       "      <td>1988</td>\n",
       "      <td>1992</td>\n",
       "      <td>5</td>\n",
       "      <td>181</td>\n",
       "      <td>167</td>\n",
       "      <td>0</td>\n",
       "      <td>1070</td>\n",
       "      <td>...</td>\n",
       "      <td>1400</td>\n",
       "      <td>1992</td>\n",
       "      <td>11</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>0.011190</td>\n",
       "      <td>0.011190</td>\n",
       "      <td>0.169888</td>\n",
       "      <td>0.169888</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>train</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               lob  group_code    group_name  accident_year  development_year  \\\n",
       "0  commercial_auto       10022  Agway Ins Co           1988              1988   \n",
       "1  commercial_auto       10022  Agway Ins Co           1988              1989   \n",
       "2  commercial_auto       10022  Agway Ins Co           1988              1990   \n",
       "3  commercial_auto       10022  Agway Ins Co           1988              1991   \n",
       "4  commercial_auto       10022  Agway Ins Co           1988              1992   \n",
       "\n",
       "   development_lag  incurred_loss  cumulative_paid_loss  bulk_loss  \\\n",
       "0                1            179                    72         71   \n",
       "1                2            151                   122         17   \n",
       "2                3            163                   142          0   \n",
       "3                4            172                   156          0   \n",
       "4                5            181                   167          0   \n",
       "\n",
       "   earned_premium_direct  ...  posted_reserve_97  calendar_year  \\\n",
       "0                   1070  ...               1400           1988   \n",
       "1                   1070  ...               1400           1989   \n",
       "2                   1070  ...               1400           1990   \n",
       "3                   1070  ...               1400           1991   \n",
       "4                   1070  ...               1400           1992   \n",
       "\n",
       "   incremental_paid_loss  case_reserves  incremental_paid_actual  \\\n",
       "0                     72       0.108850                 0.073245   \n",
       "1                     50       0.029502                 0.050865   \n",
       "2                     20       0.021363                 0.020346   \n",
       "3                     14       0.016277                 0.014242   \n",
       "4                     11       0.014242                 0.011190   \n",
       "\n",
       "   incremental_paid  cumulative_paid_actual  cumulative_paid  \\\n",
       "0          0.073245                0.073245         0.073245   \n",
       "1          0.050865                0.124110         0.124110   \n",
       "2          0.020346                0.144456         0.144456   \n",
       "3          0.014242                0.158698         0.158698   \n",
       "4          0.011190                0.169888         0.169888   \n",
       "\n",
       "   case_reserves_actual  bucket  \n",
       "0              0.108850     NaN  \n",
       "1              0.029502   train  \n",
       "2              0.021363   train  \n",
       "3              0.016277   train  \n",
       "4              0.014242   train  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Datafit "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "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>lob</th>\n",
       "      <th>group_code</th>\n",
       "      <th>group_name</th>\n",
       "      <th>accident_year</th>\n",
       "      <th>development_year</th>\n",
       "      <th>development_lag</th>\n",
       "      <th>incurred_loss</th>\n",
       "      <th>cumulative_paid_loss</th>\n",
       "      <th>bulk_loss</th>\n",
       "      <th>earned_premium_direct</th>\n",
       "      <th>...</th>\n",
       "      <th>posted_reserve_97</th>\n",
       "      <th>calendar_year</th>\n",
       "      <th>incremental_paid_loss</th>\n",
       "      <th>case_reserves</th>\n",
       "      <th>incremental_paid_actual</th>\n",
       "      <th>incremental_paid</th>\n",
       "      <th>cumulative_paid_actual</th>\n",
       "      <th>cumulative_paid</th>\n",
       "      <th>case_reserves_actual</th>\n",
       "      <th>bucket</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>commercial_auto</td>\n",
       "      <td>10022</td>\n",
       "      <td>Agway Ins Co</td>\n",
       "      <td>1988</td>\n",
       "      <td>1988</td>\n",
       "      <td>1</td>\n",
       "      <td>179</td>\n",
       "      <td>72</td>\n",
       "      <td>71</td>\n",
       "      <td>1070</td>\n",
       "      <td>...</td>\n",
       "      <td>1400</td>\n",
       "      <td>1988</td>\n",
       "      <td>72</td>\n",
       "      <td>0.108850</td>\n",
       "      <td>0.073245</td>\n",
       "      <td>0.073245</td>\n",
       "      <td>0.073245</td>\n",
       "      <td>0.073245</td>\n",
       "      <td>0.108850</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>commercial_auto</td>\n",
       "      <td>10022</td>\n",
       "      <td>Agway Ins Co</td>\n",
       "      <td>1988</td>\n",
       "      <td>1989</td>\n",
       "      <td>2</td>\n",
       "      <td>151</td>\n",
       "      <td>122</td>\n",
       "      <td>17</td>\n",
       "      <td>1070</td>\n",
       "      <td>...</td>\n",
       "      <td>1400</td>\n",
       "      <td>1989</td>\n",
       "      <td>50</td>\n",
       "      <td>0.029502</td>\n",
       "      <td>0.050865</td>\n",
       "      <td>0.050865</td>\n",
       "      <td>0.124110</td>\n",
       "      <td>0.124110</td>\n",
       "      <td>0.029502</td>\n",
       "      <td>train</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>commercial_auto</td>\n",
       "      <td>10022</td>\n",
       "      <td>Agway Ins Co</td>\n",
       "      <td>1988</td>\n",
       "      <td>1990</td>\n",
       "      <td>3</td>\n",
       "      <td>163</td>\n",
       "      <td>142</td>\n",
       "      <td>0</td>\n",
       "      <td>1070</td>\n",
       "      <td>...</td>\n",
       "      <td>1400</td>\n",
       "      <td>1990</td>\n",
       "      <td>20</td>\n",
       "      <td>0.021363</td>\n",
       "      <td>0.020346</td>\n",
       "      <td>0.020346</td>\n",
       "      <td>0.144456</td>\n",
       "      <td>0.144456</td>\n",
       "      <td>0.021363</td>\n",
       "      <td>train</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>commercial_auto</td>\n",
       "      <td>10022</td>\n",
       "      <td>Agway Ins Co</td>\n",
       "      <td>1988</td>\n",
       "      <td>1991</td>\n",
       "      <td>4</td>\n",
       "      <td>172</td>\n",
       "      <td>156</td>\n",
       "      <td>0</td>\n",
       "      <td>1070</td>\n",
       "      <td>...</td>\n",
       "      <td>1400</td>\n",
       "      <td>1991</td>\n",
       "      <td>14</td>\n",
       "      <td>0.016277</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>0.158698</td>\n",
       "      <td>0.158698</td>\n",
       "      <td>0.016277</td>\n",
       "      <td>train</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>commercial_auto</td>\n",
       "      <td>10022</td>\n",
       "      <td>Agway Ins Co</td>\n",
       "      <td>1988</td>\n",
       "      <td>1992</td>\n",
       "      <td>5</td>\n",
       "      <td>181</td>\n",
       "      <td>167</td>\n",
       "      <td>0</td>\n",
       "      <td>1070</td>\n",
       "      <td>...</td>\n",
       "      <td>1400</td>\n",
       "      <td>1992</td>\n",
       "      <td>11</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>0.011190</td>\n",
       "      <td>0.011190</td>\n",
       "      <td>0.169888</td>\n",
       "      <td>0.169888</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>train</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               lob  group_code    group_name  accident_year  development_year  \\\n",
       "0  commercial_auto       10022  Agway Ins Co           1988              1988   \n",
       "1  commercial_auto       10022  Agway Ins Co           1988              1989   \n",
       "2  commercial_auto       10022  Agway Ins Co           1988              1990   \n",
       "3  commercial_auto       10022  Agway Ins Co           1988              1991   \n",
       "4  commercial_auto       10022  Agway Ins Co           1988              1992   \n",
       "\n",
       "   development_lag  incurred_loss  cumulative_paid_loss  bulk_loss  \\\n",
       "0                1            179                    72         71   \n",
       "1                2            151                   122         17   \n",
       "2                3            163                   142          0   \n",
       "3                4            172                   156          0   \n",
       "4                5            181                   167          0   \n",
       "\n",
       "   earned_premium_direct  ...  posted_reserve_97  calendar_year  \\\n",
       "0                   1070  ...               1400           1988   \n",
       "1                   1070  ...               1400           1989   \n",
       "2                   1070  ...               1400           1990   \n",
       "3                   1070  ...               1400           1991   \n",
       "4                   1070  ...               1400           1992   \n",
       "\n",
       "   incremental_paid_loss  case_reserves  incremental_paid_actual  \\\n",
       "0                     72       0.108850                 0.073245   \n",
       "1                     50       0.029502                 0.050865   \n",
       "2                     20       0.021363                 0.020346   \n",
       "3                     14       0.016277                 0.014242   \n",
       "4                     11       0.014242                 0.011190   \n",
       "\n",
       "   incremental_paid  cumulative_paid_actual  cumulative_paid  \\\n",
       "0          0.073245                0.073245         0.073245   \n",
       "1          0.050865                0.124110         0.124110   \n",
       "2          0.020346                0.144456         0.144456   \n",
       "3          0.014242                0.158698         0.158698   \n",
       "4          0.011190                0.169888         0.169888   \n",
       "\n",
       "   case_reserves_actual  bucket  \n",
       "0              0.108850     NaN  \n",
       "1              0.029502   train  \n",
       "2              0.021363   train  \n",
       "3              0.016277   train  \n",
       "4              0.014242   train  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "def df_to_model_input(df):\n",
    "    paid = df.pivot_table(index=['lob','group_code','accident_year'], columns='development_lag', values=['incremental_paid'], aggfunc=np.sum)\n",
    "    reserves = df.pivot_table(index=['group_code','lob','accident_year'], columns='development_lag', values=['case_reserves'], aggfunc=np.sum)\n",
    "\n",
    "    #triangles = np.append(paid.to_numpy()[:,np.newaxis],reserves.to_numpy()[:,np.newaxis], axis=2)\n",
    "\n",
    "    triangles=np.stack([paid.to_numpy(),reserves.to_numpy()])\n",
    "\n",
    "    print(triangles.shape)\n",
    "\n",
    "    company_code = paid.index.get_level_values(0)\n",
    "\n",
    "    return [triangles, company_code]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.set_index('lob',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "filter_validation = (df[\"bucket\"].isin([\"train\", \"validation\"])) & (df[\"development_lag\"] ==1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 2,  3,  4,  5,  6,  7,  8,  9, 10])"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(df[(df[\"bucket\"].isin([\"train\", \"validation\"]))][\"development_lag\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2, 450, 9)\n",
      "(2, 450, 9)\n",
      "(2, 450, 9)\n"
     ]
    }
   ],
   "source": [
    "lob='commercial_auto'\n",
    "filter_validation = (df[\"bucket\"].isin([\"validation\"])) \n",
    "filter_train = (df[\"bucket\"].isin([\"train\", \"validation\"])) \n",
    "filter_test = (df[\"bucket\"].isin([\"test\"])) | (df[\"calendar_year\"] ==1998)\n",
    "training_data = df_to_model_input(df[filter_train].loc[lob])\n",
    "test_data = df_to_model_input(df[filter_test].loc[lob])\n",
    "validaiton_data = df_to_model_input(df[filter_validation].loc[lob])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_df = pd.read_csv(\"x.csv\", sep=\";\", decimal=\",\")\n",
    "x_df.drop(\"Unnamed: 0\", axis=1, inplace=True)\n",
    "\n",
    "y_df = pd.read_csv(\"y.csv\", sep=\";\", decimal=\",\")\n",
    "y_df.drop(\"Unnamed: 0\", axis=1, inplace=True)\n",
    "\n",
    "validation = pd.read_csv(\"validation.csv\", sep=\";\", decimal=\",\")\n",
    "validation.drop(\"Unnamed: 0\", axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>ay_seq_input.1</th>\n",
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       "      <th>ay_seq_input.6</th>\n",
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       "      <th>ay_seq_input.8</th>\n",
       "      <th>ay_seq_input.9</th>\n",
       "      <th>ay_seq_input.10</th>\n",
       "      <th>ay_seq_input.11</th>\n",
       "      <th>ay_seq_input.12</th>\n",
       "      <th>ay_seq_input.13</th>\n",
       "      <th>ay_seq_input.14</th>\n",
       "      <th>ay_seq_input.15</th>\n",
       "      <th>ay_seq_input.16</th>\n",
       "      <th>ay_seq_input.17</th>\n",
       "      <th>ay_seq_input.18</th>\n",
       "      <th>group_code</th>\n",
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       "  </thead>\n",
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      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [ay_seq_input.1, ay_seq_input.2, ay_seq_input.3, ay_seq_input.4, ay_seq_input.5, ay_seq_input.6, ay_seq_input.7, ay_seq_input.8, ay_seq_input.9, ay_seq_input.10, ay_seq_input.11, ay_seq_input.12, ay_seq_input.13, ay_seq_input.14, ay_seq_input.15, ay_seq_input.16, ay_seq_input.17, ay_seq_input.18, group_code]\n",
       "Index: []"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_df[x_df[\"ay_seq_input.9\"] == 0.124110]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ay_seq_input.1</th>\n",
       "      <th>ay_seq_input.2</th>\n",
       "      <th>ay_seq_input.3</th>\n",
       "      <th>ay_seq_input.4</th>\n",
       "      <th>ay_seq_input.5</th>\n",
       "      <th>ay_seq_input.6</th>\n",
       "      <th>ay_seq_input.7</th>\n",
       "      <th>ay_seq_input.8</th>\n",
       "      <th>ay_seq_input.9</th>\n",
       "      <th>ay_seq_input.10</th>\n",
       "      <th>ay_seq_input.11</th>\n",
       "      <th>ay_seq_input.12</th>\n",
       "      <th>ay_seq_input.13</th>\n",
       "      <th>ay_seq_input.14</th>\n",
       "      <th>ay_seq_input.15</th>\n",
       "      <th>ay_seq_input.16</th>\n",
       "      <th>ay_seq_input.17</th>\n",
       "      <th>ay_seq_input.18</th>\n",
       "      <th>group_code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.073245</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.108850</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.073245</td>\n",
       "      <td>0.050865</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.108850</td>\n",
       "      <td>0.029502</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.073245</td>\n",
       "      <td>0.050865</td>\n",
       "      <td>0.020346</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.108850</td>\n",
       "      <td>0.029502</td>\n",
       "      <td>0.021363</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.073245</td>\n",
       "      <td>0.050865</td>\n",
       "      <td>0.020346</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.108850</td>\n",
       "      <td>0.029502</td>\n",
       "      <td>0.021363</td>\n",
       "      <td>0.016277</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.073245</td>\n",
       "      <td>0.050865</td>\n",
       "      <td>0.020346</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>0.011190</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.108850</td>\n",
       "      <td>0.029502</td>\n",
       "      <td>0.021363</td>\n",
       "      <td>0.016277</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.073245</td>\n",
       "      <td>0.050865</td>\n",
       "      <td>0.020346</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>0.011190</td>\n",
       "      <td>0.008138</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.108850</td>\n",
       "      <td>0.029502</td>\n",
       "      <td>0.021363</td>\n",
       "      <td>0.016277</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>0.037640</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.073245</td>\n",
       "      <td>0.050865</td>\n",
       "      <td>0.020346</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>0.011190</td>\n",
       "      <td>0.008138</td>\n",
       "      <td>0.005086</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.108850</td>\n",
       "      <td>0.029502</td>\n",
       "      <td>0.021363</td>\n",
       "      <td>0.016277</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>0.037640</td>\n",
       "      <td>0.033571</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.073245</td>\n",
       "      <td>0.050865</td>\n",
       "      <td>0.020346</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>0.011190</td>\n",
       "      <td>0.008138</td>\n",
       "      <td>0.005086</td>\n",
       "      <td>0.001017</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>0.108850</td>\n",
       "      <td>0.029502</td>\n",
       "      <td>0.021363</td>\n",
       "      <td>0.016277</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>0.037640</td>\n",
       "      <td>0.033571</td>\n",
       "      <td>0.029502</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.073245</td>\n",
       "      <td>0.050865</td>\n",
       "      <td>0.020346</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>0.011190</td>\n",
       "      <td>0.008138</td>\n",
       "      <td>0.005086</td>\n",
       "      <td>0.001017</td>\n",
       "      <td>0.003052</td>\n",
       "      <td>0.10885</td>\n",
       "      <td>0.029502</td>\n",
       "      <td>0.021363</td>\n",
       "      <td>0.016277</td>\n",
       "      <td>0.014242</td>\n",
       "      <td>0.037640</td>\n",
       "      <td>0.033571</td>\n",
       "      <td>0.029502</td>\n",
       "      <td>0.030519</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.118467</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.123693</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.118467</td>\n",
       "      <td>0.108014</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.123693</td>\n",
       "      <td>0.069686</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.118467</td>\n",
       "      <td>0.108014</td>\n",
       "      <td>0.033101</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.123693</td>\n",
       "      <td>0.069686</td>\n",
       "      <td>0.083624</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.118467</td>\n",
       "      <td>0.108014</td>\n",
       "      <td>0.033101</td>\n",
       "      <td>0.040070</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.123693</td>\n",
       "      <td>0.069686</td>\n",
       "      <td>0.083624</td>\n",
       "      <td>0.059233</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.118467</td>\n",
       "      <td>0.108014</td>\n",
       "      <td>0.033101</td>\n",
       "      <td>0.040070</td>\n",
       "      <td>0.081882</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.123693</td>\n",
       "      <td>0.069686</td>\n",
       "      <td>0.083624</td>\n",
       "      <td>0.059233</td>\n",
       "      <td>0.026132</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.118467</td>\n",
       "      <td>0.108014</td>\n",
       "      <td>0.033101</td>\n",
       "      <td>0.040070</td>\n",
       "      <td>0.081882</td>\n",
       "      <td>0.013937</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.123693</td>\n",
       "      <td>0.069686</td>\n",
       "      <td>0.083624</td>\n",
       "      <td>0.059233</td>\n",
       "      <td>0.026132</td>\n",
       "      <td>0.013937</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.118467</td>\n",
       "      <td>0.108014</td>\n",
       "      <td>0.033101</td>\n",
       "      <td>0.040070</td>\n",
       "      <td>0.081882</td>\n",
       "      <td>0.013937</td>\n",
       "      <td>0.005226</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.123693</td>\n",
       "      <td>0.069686</td>\n",
       "      <td>0.083624</td>\n",
       "      <td>0.059233</td>\n",
       "      <td>0.026132</td>\n",
       "      <td>0.013937</td>\n",
       "      <td>0.006969</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.118467</td>\n",
       "      <td>0.108014</td>\n",
       "      <td>0.033101</td>\n",
       "      <td>0.040070</td>\n",
       "      <td>0.081882</td>\n",
       "      <td>0.013937</td>\n",
       "      <td>0.005226</td>\n",
       "      <td>0.003484</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>0.123693</td>\n",
       "      <td>0.069686</td>\n",
       "      <td>0.083624</td>\n",
       "      <td>0.059233</td>\n",
       "      <td>0.026132</td>\n",
       "      <td>0.013937</td>\n",
       "      <td>0.006969</td>\n",
       "      <td>0.003484</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.178423</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.221300</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.178423</td>\n",
       "      <td>0.123098</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.221300</td>\n",
       "      <td>0.118949</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.178423</td>\n",
       "      <td>0.123098</td>\n",
       "      <td>0.149378</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.221300</td>\n",
       "      <td>0.118949</td>\n",
       "      <td>0.071923</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.178423</td>\n",
       "      <td>0.123098</td>\n",
       "      <td>0.149378</td>\n",
       "      <td>0.087137</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.221300</td>\n",
       "      <td>0.118949</td>\n",
       "      <td>0.071923</td>\n",
       "      <td>0.033195</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.178423</td>\n",
       "      <td>0.123098</td>\n",
       "      <td>0.149378</td>\n",
       "      <td>0.087137</td>\n",
       "      <td>0.008299</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.221300</td>\n",
       "      <td>0.118949</td>\n",
       "      <td>0.071923</td>\n",
       "      <td>0.033195</td>\n",
       "      <td>0.016598</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.178423</td>\n",
       "      <td>0.123098</td>\n",
       "      <td>0.149378</td>\n",
       "      <td>0.087137</td>\n",
       "      <td>0.008299</td>\n",
       "      <td>0.006916</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.221300</td>\n",
       "      <td>0.118949</td>\n",
       "      <td>0.071923</td>\n",
       "      <td>0.033195</td>\n",
       "      <td>0.016598</td>\n",
       "      <td>0.008299</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.178423</td>\n",
       "      <td>0.123098</td>\n",
       "      <td>0.149378</td>\n",
       "      <td>0.087137</td>\n",
       "      <td>0.008299</td>\n",
       "      <td>0.006916</td>\n",
       "      <td>0.004149</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.221300</td>\n",
       "      <td>0.118949</td>\n",
       "      <td>0.071923</td>\n",
       "      <td>0.033195</td>\n",
       "      <td>0.016598</td>\n",
       "      <td>0.008299</td>\n",
       "      <td>0.002766</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.344015</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.341188</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.344015</td>\n",
       "      <td>0.161169</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.341188</td>\n",
       "      <td>0.090481</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.344015</td>\n",
       "      <td>0.161169</td>\n",
       "      <td>0.035815</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.341188</td>\n",
       "      <td>0.090481</td>\n",
       "      <td>0.209237</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.344015</td>\n",
       "      <td>0.161169</td>\n",
       "      <td>0.035815</td>\n",
       "      <td>0.096136</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.341188</td>\n",
       "      <td>0.090481</td>\n",
       "      <td>0.209237</td>\n",
       "      <td>0.107446</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.344015</td>\n",
       "      <td>0.161169</td>\n",
       "      <td>0.035815</td>\n",
       "      <td>0.096136</td>\n",
       "      <td>0.015080</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.341188</td>\n",
       "      <td>0.090481</td>\n",
       "      <td>0.209237</td>\n",
       "      <td>0.107446</td>\n",
       "      <td>0.095193</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.344015</td>\n",
       "      <td>0.161169</td>\n",
       "      <td>0.035815</td>\n",
       "      <td>0.096136</td>\n",
       "      <td>0.015080</td>\n",
       "      <td>0.066918</td>\n",
       "      <td>-99.00000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.341188</td>\n",
       "      <td>0.090481</td>\n",
       "      <td>0.209237</td>\n",
       "      <td>0.107446</td>\n",
       "      <td>0.095193</td>\n",
       "      <td>0.049010</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ay_seq_input.1  ay_seq_input.2  ay_seq_input.3  ay_seq_input.4  \\\n",
       "0       -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "1       -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "2       -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "3       -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "4       -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "5       -99.000000      -99.000000      -99.000000        0.073245   \n",
       "6       -99.000000      -99.000000        0.073245        0.050865   \n",
       "7       -99.000000        0.073245        0.050865        0.020346   \n",
       "8         0.073245        0.050865        0.020346        0.014242   \n",
       "9       -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "10      -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "11      -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "12      -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "13      -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "14      -99.000000      -99.000000      -99.000000        0.118467   \n",
       "15      -99.000000      -99.000000        0.118467        0.108014   \n",
       "16      -99.000000        0.118467        0.108014        0.033101   \n",
       "17      -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "18      -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "19      -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "20      -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "21      -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "22      -99.000000      -99.000000      -99.000000        0.178423   \n",
       "23      -99.000000      -99.000000        0.178423        0.123098   \n",
       "24      -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "25      -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "26      -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "27      -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "28      -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "29      -99.000000      -99.000000      -99.000000        0.344015   \n",
       "\n",
       "    ay_seq_input.5  ay_seq_input.6  ay_seq_input.7  ay_seq_input.8  \\\n",
       "0       -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "1       -99.000000      -99.000000      -99.000000        0.073245   \n",
       "2       -99.000000      -99.000000        0.073245        0.050865   \n",
       "3       -99.000000        0.073245        0.050865        0.020346   \n",
       "4         0.073245        0.050865        0.020346        0.014242   \n",
       "5         0.050865        0.020346        0.014242        0.011190   \n",
       "6         0.020346        0.014242        0.011190        0.008138   \n",
       "7         0.014242        0.011190        0.008138        0.005086   \n",
       "8         0.011190        0.008138        0.005086        0.001017   \n",
       "9       -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "10      -99.000000      -99.000000      -99.000000        0.118467   \n",
       "11      -99.000000      -99.000000        0.118467        0.108014   \n",
       "12      -99.000000        0.118467        0.108014        0.033101   \n",
       "13        0.118467        0.108014        0.033101        0.040070   \n",
       "14        0.108014        0.033101        0.040070        0.081882   \n",
       "15        0.033101        0.040070        0.081882        0.013937   \n",
       "16        0.040070        0.081882        0.013937        0.005226   \n",
       "17      -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "18      -99.000000      -99.000000      -99.000000        0.178423   \n",
       "19      -99.000000      -99.000000        0.178423        0.123098   \n",
       "20      -99.000000        0.178423        0.123098        0.149378   \n",
       "21        0.178423        0.123098        0.149378        0.087137   \n",
       "22        0.123098        0.149378        0.087137        0.008299   \n",
       "23        0.149378        0.087137        0.008299        0.006916   \n",
       "24      -99.000000      -99.000000      -99.000000      -99.000000   \n",
       "25      -99.000000      -99.000000      -99.000000        0.344015   \n",
       "26      -99.000000      -99.000000        0.344015        0.161169   \n",
       "27      -99.000000        0.344015        0.161169        0.035815   \n",
       "28        0.344015        0.161169        0.035815        0.096136   \n",
       "29        0.161169        0.035815        0.096136        0.015080   \n",
       "\n",
       "    ay_seq_input.9  ay_seq_input.10  ay_seq_input.11  ay_seq_input.12  \\\n",
       "0         0.073245        -99.00000       -99.000000       -99.000000   \n",
       "1         0.050865        -99.00000       -99.000000       -99.000000   \n",
       "2         0.020346        -99.00000       -99.000000       -99.000000   \n",
       "3         0.014242        -99.00000       -99.000000       -99.000000   \n",
       "4         0.011190        -99.00000       -99.000000       -99.000000   \n",
       "5         0.008138        -99.00000       -99.000000       -99.000000   \n",
       "6         0.005086        -99.00000       -99.000000         0.108850   \n",
       "7         0.001017        -99.00000         0.108850         0.029502   \n",
       "8         0.003052          0.10885         0.029502         0.021363   \n",
       "9         0.118467        -99.00000       -99.000000       -99.000000   \n",
       "10        0.108014        -99.00000       -99.000000       -99.000000   \n",
       "11        0.033101        -99.00000       -99.000000       -99.000000   \n",
       "12        0.040070        -99.00000       -99.000000       -99.000000   \n",
       "13        0.081882        -99.00000       -99.000000       -99.000000   \n",
       "14        0.013937        -99.00000       -99.000000       -99.000000   \n",
       "15        0.005226        -99.00000       -99.000000         0.123693   \n",
       "16        0.003484        -99.00000         0.123693         0.069686   \n",
       "17        0.178423        -99.00000       -99.000000       -99.000000   \n",
       "18        0.123098        -99.00000       -99.000000       -99.000000   \n",
       "19        0.149378        -99.00000       -99.000000       -99.000000   \n",
       "20        0.087137        -99.00000       -99.000000       -99.000000   \n",
       "21        0.008299        -99.00000       -99.000000       -99.000000   \n",
       "22        0.006916        -99.00000       -99.000000       -99.000000   \n",
       "23        0.004149        -99.00000       -99.000000         0.221300   \n",
       "24        0.344015        -99.00000       -99.000000       -99.000000   \n",
       "25        0.161169        -99.00000       -99.000000       -99.000000   \n",
       "26        0.035815        -99.00000       -99.000000       -99.000000   \n",
       "27        0.096136        -99.00000       -99.000000       -99.000000   \n",
       "28        0.015080        -99.00000       -99.000000       -99.000000   \n",
       "29        0.066918        -99.00000       -99.000000       -99.000000   \n",
       "\n",
       "    ay_seq_input.13  ay_seq_input.14  ay_seq_input.15  ay_seq_input.16  \\\n",
       "0        -99.000000       -99.000000       -99.000000       -99.000000   \n",
       "1        -99.000000       -99.000000       -99.000000       -99.000000   \n",
       "2        -99.000000       -99.000000       -99.000000         0.108850   \n",
       "3        -99.000000       -99.000000         0.108850         0.029502   \n",
       "4        -99.000000         0.108850         0.029502         0.021363   \n",
       "5          0.108850         0.029502         0.021363         0.016277   \n",
       "6          0.029502         0.021363         0.016277         0.014242   \n",
       "7          0.021363         0.016277         0.014242         0.037640   \n",
       "8          0.016277         0.014242         0.037640         0.033571   \n",
       "9        -99.000000       -99.000000       -99.000000       -99.000000   \n",
       "10       -99.000000       -99.000000       -99.000000       -99.000000   \n",
       "11       -99.000000       -99.000000       -99.000000         0.123693   \n",
       "12       -99.000000       -99.000000         0.123693         0.069686   \n",
       "13       -99.000000         0.123693         0.069686         0.083624   \n",
       "14         0.123693         0.069686         0.083624         0.059233   \n",
       "15         0.069686         0.083624         0.059233         0.026132   \n",
       "16         0.083624         0.059233         0.026132         0.013937   \n",
       "17       -99.000000       -99.000000       -99.000000       -99.000000   \n",
       "18       -99.000000       -99.000000       -99.000000       -99.000000   \n",
       "19       -99.000000       -99.000000       -99.000000         0.221300   \n",
       "20       -99.000000       -99.000000         0.221300         0.118949   \n",
       "21       -99.000000         0.221300         0.118949         0.071923   \n",
       "22         0.221300         0.118949         0.071923         0.033195   \n",
       "23         0.118949         0.071923         0.033195         0.016598   \n",
       "24       -99.000000       -99.000000       -99.000000       -99.000000   \n",
       "25       -99.000000       -99.000000       -99.000000       -99.000000   \n",
       "26       -99.000000       -99.000000       -99.000000         0.341188   \n",
       "27       -99.000000       -99.000000         0.341188         0.090481   \n",
       "28       -99.000000         0.341188         0.090481         0.209237   \n",
       "29         0.341188         0.090481         0.209237         0.107446   \n",
       "\n",
       "    ay_seq_input.17  ay_seq_input.18  group_code  \n",
       "0        -99.000000         0.108850           0  \n",
       "1          0.108850         0.029502           0  \n",
       "2          0.029502         0.021363           0  \n",
       "3          0.021363         0.016277           0  \n",
       "4          0.016277         0.014242           0  \n",
       "5          0.014242         0.037640           0  \n",
       "6          0.037640         0.033571           0  \n",
       "7          0.033571         0.029502           0  \n",
       "8          0.029502         0.030519           0  \n",
       "9        -99.000000         0.123693           0  \n",
       "10         0.123693         0.069686           0  \n",
       "11         0.069686         0.083624           0  \n",
       "12         0.083624         0.059233           0  \n",
       "13         0.059233         0.026132           0  \n",
       "14         0.026132         0.013937           0  \n",
       "15         0.013937         0.006969           0  \n",
       "16         0.006969         0.003484           0  \n",
       "17       -99.000000         0.221300           0  \n",
       "18         0.221300         0.118949           0  \n",
       "19         0.118949         0.071923           0  \n",
       "20         0.071923         0.033195           0  \n",
       "21         0.033195         0.016598           0  \n",
       "22         0.016598         0.008299           0  \n",
       "23         0.008299         0.002766           0  \n",
       "24       -99.000000         0.341188           0  \n",
       "25         0.341188         0.090481           0  \n",
       "26         0.090481         0.209237           0  \n",
       "27         0.209237         0.107446           0  \n",
       "28         0.107446         0.095193           0  \n",
       "29         0.095193         0.049010           0  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_df.head(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "company_input = x_df[\"group_code\"].to_numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2250, 19)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = y_df.to_numpy()\n",
    "x = x_df.to_numpy()\n",
    "x.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = y[:,:, np.newaxis]\n",
    "x = x[:,:-1,np.newaxis]\n",
    "\n",
    "val_single = validation\n",
    "validation_x_tri = val_single[validation.columns[:18]].to_numpy()\n",
    "validation_x_comp =val_single[\"x.group_code\"].to_numpy()\n",
    "validation_x_tri = validation_x_tri[:,:,np.newaxis]\n",
    "validation_x_comp = validation_x_comp[:,np.newaxis]\n",
    "\n",
    "validation_y = val_single[val_single.columns[val_single.columns.str.startswith(\"y\")]].to_numpy()\n",
    "validation_y_paid = validation_y[:,:9,np.newaxis]\n",
    "validation_y_reserve = validation_y[:,9:,np.newaxis]\n",
    "\n",
    "x_input = np.concatenate([x[:,:9], x[:,9:]], axis=2)\n",
    "y_input = np.concatenate([y[:,:9], y[:,9:]], axis=2)\n",
    "validation_x_tri = np.concatenate([validation_x_tri[:,:9], validation_x_tri[:,9:]], axis=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x shape: (2250, 18, 1), y shape : (2250, 18, 1),  validation x shape : (850, 9, 2),  validation y shape : (850, 18)\n"
     ]
    }
   ],
   "source": [
    "print(f\"x shape: {x.shape}, y shape : {y.shape},  validation x shape : {validation_x_tri.shape},  validation y shape : {validation_y.shape}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(45, 9, 2) (45, 9, 2)\n"
     ]
    }
   ],
   "source": [
    "print(x_input.shape, y_input.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tensorflow.keras.layers import TimeDistributed, GRU, Dense, RepeatVector, LSTM\n",
    "from tensorflow.keras.models import Sequential\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "tf.compat.v1.disable_eager_execution()\n",
    "\n",
    "from tensorflow import keras\n",
    "from tensorflow.keras import layers\n",
    "\n",
    "from tensorflow.keras.callbacks import EarlyStopping\n",
    "from tensorflow.keras.optimizers import Adam\n",
    "import tensorflow.keras.backend as tfk\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"DeepTriangle\"\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "ay_seq_input (InputLayer)       [(None, 9, 2)]       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "masking (Masking)               (None, 9, 2)         0           ay_seq_input[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "gru (GRU)                       (None, 128)          50688       masking[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "repeat_vector_1 (RepeatVector)  (None, 9, 128)       0           gru[0][0]                        \n",
      "__________________________________________________________________________________________________\n",
      "gru_1 (GRU)                     (None, 9, 128)       99072       repeat_vector_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "lambda (Lambda)                 (None, 9, 177)       0           gru_1[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "time_distributed_2 (TimeDistrib (None, 9, 64)        11392       lambda[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "time_distributed (TimeDistribut (None, 9, 64)        11392       lambda[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "time_distributed_3 (TimeDistrib (None, 9, 64)        0           time_distributed_2[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "time_distributed_1 (TimeDistrib (None, 9, 64)        0           time_distributed[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "company_input (InputLayer)      [(None, 1)]          0                                            \n",
      "__________________________________________________________________________________________________\n",
      "paid_output (TimeDistributed)   (None, 9, 1)         65          time_distributed_3[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "case_reserves_output (TimeDistr (None, 9, 1)         65          time_distributed_1[0][0]         \n",
      "==================================================================================================\n",
      "Total params: 172,674\n",
      "Trainable params: 172,674\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "\n",
    "tfk.clear_session()\n",
    "\n",
    "ay_seq_input  = layers.Input(shape = (9,2), name = 'ay_seq_input' )\n",
    "company_code_input = layers.Input(shape = 1, name = \"company_input\")\n",
    "company_code_embedding = layers.Embedding(200,49)(company_code_input)\n",
    "company_code_embedding = layers.Flatten()(company_code_embedding)\n",
    "company_code_embedding = layers.RepeatVector(9)(company_code_embedding)\n",
    "   \n",
    "\n",
    "encoded = layers.Masking(mask_value = -99)(ay_seq_input)\n",
    "encoded = layers.GRU(128, dropout = 0.2, recurrent_dropout = 0.2)(encoded)\n",
    "\n",
    "concat_layer = lambda x: layers.Concatenate()([x, company_code_embedding])\n",
    "decoded = layers.RepeatVector(9)(encoded)\n",
    "decoded = layers.GRU(128, return_sequences = True, dropout = 0.2, recurrent_dropout = 0.2)(decoded)\n",
    "decoded = layers.Lambda(concat_layer)(decoded)\n",
    "\n",
    "case_reserves_output = layers.TimeDistributed(layers.Dense(units = 64, activation = \"relu\"))(decoded)\n",
    "case_reserves_output = layers.TimeDistributed(layers.Dropout(rate = 0.2))(case_reserves_output)\n",
    "case_reserves_output = layers.TimeDistributed(layers.Dense(units = 1, activation = \"relu\"), name = \"case_reserves_output\")(case_reserves_output)\n",
    "\n",
    "paid_output = layers.TimeDistributed(layers.Dense(units = 64, activation = \"relu\"))(decoded)\n",
    "paid_output = layers.TimeDistributed(layers.Dropout(rate = 0.2))(paid_output)\n",
    "paid_output = layers.TimeDistributed(layers.Dense(units = 1, activation = \"relu\"), name = \"paid_output\")(paid_output)\n",
    "\n",
    "\n",
    "\n",
    "model = keras.Model(\n",
    "inputs = [ay_seq_input, company_code_input],\n",
    "outputs = [paid_output, case_reserves_output],\n",
    "    name = \"DeepTriangle\"\n",
    ")\n",
    "\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#%%\n",
    "''' 9. Fit og Predict model\n",
    "'''\n",
    "# fit model - stopper efter 200 ved lille udvikling og gemmer bedste resultat - vigtigt pga. ML modeller svinger meget\n",
    "callback = EarlyStopping(min_delta = 0.001, patience = 200, mode = \"min\", restore_best_weights = True)\n",
    "missing_value = -99\n",
    "\n",
    "# masked funktion benyttet af Kuo i Deep Triangle\n",
    "def masked_mse(missing_value):\n",
    "    \n",
    "    def custom_mse(y_true, y_pred):\n",
    "    # assume 1st dimension is the number of samples\n",
    "        keep= tfk.cast(tfk.not_equal(y_true, missing_value), tfk.floatx())\n",
    "        mse = tfk.mean(tfk.square((y_pred-y_true)*keep), axis=2)\n",
    "\n",
    "        return mse\n",
    "\n",
    "    return custom_mse\n",
    "\n",
    "\n",
    "model.compile(optimizer = Adam(learning_rate=0.0005, amsgrad = True),\n",
    "            loss         = [masked_mse(missing_value),masked_mse(missing_value)],\n",
    "            loss_weights = [0.5,0.5])\n",
    "\n",
    "### beregner model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "paid_y = y_input[:,:,0,np.newaxis]\n",
    "rbns_y = y_input[:,:,1,np.newaxis]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:2371: UserWarning: `Model.state_updates` will be removed in a future version. This property should not be used in TensorFlow 2.0, as `updates` are applied automatically.\n",
      "  warnings.warn('`Model.state_updates` will be removed in a future version. '\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 9min 45s, sys: 1min 10s, total: 10min 55s\n",
      "Wall time: 1min 47s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "#beregn_model.fit(x= X_train,y= y_train, batch_size = X_dim1, epochs = 99, callbacks = (callback), verbose = 0) KRÆVER valideringsdata\n",
    "history = model.fit(x= [x_input, company_input],\n",
    "                 y=  [paid_y, rbns_y],\n",
    "                 batch_size = 2250,\n",
    "                 epochs = 200,\n",
    "                 callbacks = [callback],\n",
    "                  \n",
    "                 validation_data=[[validation_x_tri,validation_x_comp],[validation_y_paid,validation_y_reserve]],\n",
    "                 verbose = 0)\n",
    "\n",
    "#Y_ibnr = model.predict(X_ibnr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tensorflow.python.keras.callbacks.History at 0x7f8224351cf8>"
      ]
     },
     "execution_count": 259,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.predict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_data = pd.read_csv(\"test_data.csv\", sep=\";\", decimal=\",\")\n",
    "test_data.drop(\"Unnamed: 0\", axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "test_data_x_tri = test_data[test_data.columns[:18]].to_numpy()\n",
    "test_data_x_comp =test_data[\"x.group_code\"].to_numpy()\n",
    "test_data_x_tri = test_data_x_tri[:,:,np.newaxis]\n",
    "test_data_x_comp = test_data_x_comp[:,np.newaxis]\n",
    "\n",
    "test_data_y = test_data[test_data.columns[test_data.columns.str.startswith(\"y\")]].to_numpy()\n",
    "test_data_y_paid = test_data_y[:,:9,np.newaxis]\n",
    "test_data_y_reserve = test_data_y[:,9:,np.newaxis]\n",
    "\n",
    "test_data_x_tri = np.concatenate([test_data_x_tri[:,:9], test_data_x_tri[:,9:]], axis=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(450, 9, 2)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data_x_tri.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "preds = model.predict([test_data_x_tri, test_data_x_comp])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.118467</td>\n",
       "      <td>0.108014</td>\n",
       "      <td>0.033101</td>\n",
       "      <td>0.040070</td>\n",
       "      <td>0.081882</td>\n",
       "      <td>0.013937</td>\n",
       "      <td>0.005226</td>\n",
       "      <td>0.003484</td>\n",
       "      <td>0.001742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.178423</td>\n",
       "      <td>0.123098</td>\n",
       "      <td>0.149378</td>\n",
       "      <td>0.087137</td>\n",
       "      <td>0.008299</td>\n",
       "      <td>0.006916</td>\n",
       "      <td>0.004149</td>\n",
       "      <td>0.002766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.344015</td>\n",
       "      <td>0.161169</td>\n",
       "      <td>0.035815</td>\n",
       "      <td>0.096136</td>\n",
       "      <td>0.015080</td>\n",
       "      <td>0.066918</td>\n",
       "      <td>0.025448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.120999</td>\n",
       "      <td>0.055425</td>\n",
       "      <td>0.065574</td>\n",
       "      <td>0.187354</td>\n",
       "      <td>0.030445</td>\n",
       "      <td>0.026542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.130653</td>\n",
       "      <td>0.109835</td>\n",
       "      <td>0.194544</td>\n",
       "      <td>0.142139</td>\n",
       "      <td>0.034458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.145390</td>\n",
       "      <td>0.109338</td>\n",
       "      <td>0.156028</td>\n",
       "      <td>0.065603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.164843</td>\n",
       "      <td>0.099198</td>\n",
       "      <td>0.017505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.127941</td>\n",
       "      <td>0.057353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>-99.000000</td>\n",
       "      <td>0.167070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.333952</td>\n",
       "      <td>0.499072</td>\n",
       "      <td>0.083488</td>\n",
       "      <td>0.096475</td>\n",
       "      <td>0.089054</td>\n",
       "      <td>-0.053803</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           0          1          2          3          4          5  \\\n",
       "0   0.118467   0.108014   0.033101   0.040070   0.081882   0.013937   \n",
       "1 -99.000000   0.178423   0.123098   0.149378   0.087137   0.008299   \n",
       "2 -99.000000 -99.000000   0.344015   0.161169   0.035815   0.096136   \n",
       "3 -99.000000 -99.000000 -99.000000   0.120999   0.055425   0.065574   \n",
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     "execution_count": 34,
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    "pd.DataFrame(test_data_x_tri[:,:,0]).head(10)"
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  {
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     "execution_count": 32,
     "metadata": {},
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   "source": [
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  {
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       "3  0.016990  0.004205  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "4  0.029840  0.022628  0.016448  0.009404  0.003893  0.000000  0.000000   \n",
       "5  0.059718  0.037979  0.026397  0.015073  0.004811  0.000000  0.000000   \n",
       "6  0.055931  0.035235  0.025435  0.017339  0.011624  0.006484  0.002133   \n",
       "7  0.145582  0.069670  0.039415  0.026184  0.017314  0.010967  0.005478   \n",
       "8  0.213367  0.122692  0.056259  0.032188  0.023113  0.016824  0.011122   \n",
       "9  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "\n",
       "          7        8  \n",
       "0  0.000000  0.00000  \n",
       "1  0.000000  0.00000  \n",
       "2  0.000000  0.00000  \n",
       "3  0.000000  0.00000  \n",
       "4  0.000000  0.00000  \n",
       "5  0.000000  0.00000  \n",
       "6  0.000000  0.00000  \n",
       "7  0.000700  0.00000  \n",
       "8  0.007329  0.00432  \n",
       "9  0.000000  0.00000  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(preds[1].reshape(450,9)).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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