diff --git a/evaluation.ipynb b/evaluation.ipynb
index adcab4a..ee9fc31 100644
--- a/evaluation.ipynb
+++ b/evaluation.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 95,
    "id": "cleared-jacob",
    "metadata": {},
    "outputs": [
@@ -11,7 +11,11 @@
      "output_type": "stream",
      "text": [
       "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 24 concurrent workers.\n",
-      "[Parallel(n_jobs=-1)]: Done   1 out of   1 | elapsed:   11.9s finished\n"
+      "[Parallel(n_jobs=-1)]: Done  29 out of  50 | elapsed:  1.2min remaining:   51.2s\n",
+      "[Parallel(n_jobs=-1)]: Done  50 out of  50 | elapsed:  1.9min finished\n",
+      "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 24 concurrent workers.\n",
+      "[Parallel(n_jobs=-1)]: Done  29 out of  50 | elapsed:  1.2min remaining:   50.9s\n",
+      "[Parallel(n_jobs=-1)]: Done  50 out of  50 | elapsed:  1.9min finished\n"
      ]
     }
    ],
@@ -89,53 +93,11 @@
     "    return [list(a)+[name,iteration] for a in np.array(list(zip(x,y_recall,y_gap)))]\n",
     "    \n",
     "\n",
-    "# bias=f1Bias_scorer_CV(y_pred,y_test)[1]\n",
     "# # bias = .1\n",
-    "time_gap_delta = 20\n",
-    "gap_th = 70\n",
-    "\n",
-    "inc = ['3002', '3004', '3005', '3006', '3007', '3009', '3013', '3014', '3015', '3022', '3024', '3025', '3029', '3031', '3033',\n",
-    " '3036', '3038', '3041', '3045', '3048', '3050', '3053', '3076', '3077', '3079', '3086', '3088', '3091', '3095', '3099',\n",
-    " '3101', '3102', '3122', '3125', '3126', '3128', '3133', '3135', '3137', '3138', '3139', '3143', '3145', '3148', '3152',\n",
-    " '3153', '3158', '3160', '3164', '3165', '3166', '3168']\n",
-    "\n",
-    "n_lag = 15\n",
-    "\n",
-    "data_eval = pickle.load(open('./data/output/episode_encoded_lag_15_episode_model_v9_new_validation_set_include_smoking_focal_loss_static_coeff_phenotype_lower_model_v2.p','rb'))\n",
-    "\n",
-    "data_feature_label = pickle.load(open('./data/episode_encoded_lagged_data/episode_encoded_lagged_15_windows_standardized_phenotype.p','rb'))\n",
-    "\n",
-    "data_cluster = pickle.load(open('./data/episode_encoded_lagged_data/episode_encoded_lagged_'+str(n_lag)+'_windows_standardized_phenotype.p','rb'))\n",
-    "\n",
-    "temp = data_cluster.groupby(['user','cluster_label']).count().index.values\n",
-    "users = np.array([a[0] for a in temp])\n",
-    "labels = np.array([a[1] for a in temp])\n",
-    "cluster_dict = {}\n",
-    "for i,a in enumerate(users):\n",
-    "    cluster_dict[a] = labels[i]\n",
-    "\n",
-    "result_phenotypes_final = {}\n",
-    "for label in cluster_dict.values():\n",
-    "    result_phenotypes_final[label] = [0,0,0,len(users[labels==label]),[],[],[],[]]\n",
-    "y_time = data_eval[0]\n",
-    "y_pred = np.array(data_eval[1])\n",
-    "y_test = data_eval[2]\n",
-    "y_pid = data_eval[3]\n",
-    "bias_dict = data_eval[4]\n",
-    "val_results = data_eval[5]\n",
-    "y_time = np.array(y_time)\n",
-    "y_pred = np.array(y_pred)\n",
-    "y_test = np.array(y_test)\n",
-    "y_pid = np.array(y_pid)\n",
-    "pars = np.unique(y_pid)\n",
-    "total_lapsers = len(pars)\n",
-    "indexes_pred = np.arange(y_pred.shape[1])\n",
-    "n_iters = 1\n",
-    "\n",
     "# for iteration in np.arange(n_iters):\n",
     "def get_results(iteration):\n",
-    "    n_sample = 50\n",
-    "    x = np.arange(3.5,12.5,1)\n",
+    "    n_sample = 30\n",
+    "    x = np.array([3.5]+list(np.arange(4,12,1)))\n",
     "    all_data = []\n",
     "    pred_index = np.random.choice(indexes_pred,n_sample,replace=False)\n",
     "    final_intpday = []\n",
@@ -153,15 +115,16 @@
     "            result_phenotypes[key][2] = 0\n",
     "            result_phenotypes[key][4] = []\n",
     "        for i,par in enumerate(pars):\n",
-    "            val_pred = val_results[bias_dict[par]][1]\n",
-    "            val_y = val_results[bias_dict[par]][2]\n",
-    "            val_time = val_results[bias_dict[par]][0]\n",
-    "            val_pred = val_pred[val_time.argsort()]\n",
-    "            val_pred = val_pred[:,pred_index].mean(axis=1)\n",
-    "            val_y = val_y[val_time.argsort()]\n",
-    "            val_time = np.array(sorted(val_time))\n",
-    "            df = pd.DataFrame({'time':val_time,'prob':val_pred})\n",
-    "            val_pred = df['prob'].rolling(window=10).mean().fillna(0).values\n",
+    "            \n",
+    "            # val_pred = val_results[bias_dict[par]][1]\n",
+    "            # val_y = val_results[bias_dict[par]][2]\n",
+    "            # val_time = val_results[bias_dict[par]][0]\n",
+    "            # val_pred = val_pred[val_time.argsort()]\n",
+    "            # val_pred = val_pred[:,pred_index].mean(axis=1)\n",
+    "            # val_y = val_y[val_time.argsort()]\n",
+    "            # val_time = np.array(sorted(val_time))\n",
+    "            # df = pd.DataFrame({'time':val_time,'prob':val_pred})\n",
+    "            # val_pred = df['prob'].rolling(window=10).mean().fillna(0).values\n",
     "            # bias = f1Bias_scorer_CV(val_pred,val_y)[1]\n",
     "            # bias = bias_col[int(bias_dict[par])]\n",
     "            # bias = .1\n",
@@ -180,12 +143,11 @@
     "            df = pd.DataFrame({'time':y_time_pid,'prob':y_pred_pid})\n",
     "            y_pred_pid = df['prob'].rolling(window=10).mean().fillna(0).values\n",
     "            f1,bias=f1Bias_scorer_CV(y_pred_pid,y_test_pid)\n",
-    "            # bias = np.percentile(y_pred_pid,75)\n",
+    "            # bias = np.percentile(y_pred_pid,80)\n",
     "            # print(f1,bias)\n",
     "            b = (np.where(y_test_pid>0))\n",
     "            y_time_lapses = y_time_pid[b]\n",
     "            udays = len(np.unique(data_feature_label[data_feature_label['user']==par]['day'].values))\n",
-    "\n",
     "            part_days+=udays\n",
     "            # print(result_phenotypes[cluster_dict[par]][0])\n",
     "            result_phenotypes[cluster_dict[par]][0]+=udays\n",
@@ -205,7 +167,7 @@
     "                    else:\n",
     "                        timedelta = y_time_pid[p] - prev_time\n",
     "                        mins = timedelta.astype('timedelta64[m]').astype(np.int32)\n",
-    "                        if mins>timescap and ys>=bias:\n",
+    "                        if mins>=timescap and ys>=bias:\n",
     "                            ipd+=1\n",
     "                            int_time= y_time_pid[p]\n",
     "                            int_times.append(int_time)\n",
@@ -258,224 +220,754 @@
     "        all_data.extend(result_final_cluster)\n",
     "    return all_data\n",
     "    # print('-'*20)\n",
-    "from joblib import Parallel,delayed\n",
-    "all_data_v1 = Parallel(n_jobs=-1,verbose=2)(delayed(get_results)(iteration) for iteration in np.arange(n_iters))\n",
-    "all_data = []\n",
-    "for a in all_data_v1:\n",
-    "    all_data.extend(a)\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df_predictions = pd.DataFrame({'risk':y_pred.mean(axis=1),'cluster':[cluster_dict[a] for a in y_pid],'time':y_time}) "
+    "\n",
+    "from collections import Counter\n",
+    "time_gap_delta = 20\n",
+    "gap_th = 30\n",
+    "\n",
+    "inc = ['3002', '3004', '3005', '3006', '3007', '3009', '3013', '3014', '3015', '3022', '3024', '3025', '3029', '3031', '3033',\n",
+    " '3036', '3038', '3041', '3045', '3048', '3050', '3053', '3076', '3077', '3079', '3086', '3088', '3091', '3095', '3099',\n",
+    " '3101', '3102', '3122', '3125', '3126', '3128', '3133', '3135', '3137', '3138', '3139', '3143', '3145', '3148', '3152',\n",
+    " '3153', '3158', '3160', '3164', '3165', '3166', '3168']\n",
+    "\n",
+    "n_lag = 15\n",
+    "data_directory = './data/output/episode_encoded_lag_'\n",
+    "\n",
+    "# episode_presence = False\n",
+    "df_all = []\n",
+    "for episode_presence in [True,False]:\n",
+    "\n",
+    "    if episode_presence:\n",
+    "        data_eval = pickle.load(open(data_directory+str(n_lag)+\n",
+    "        '_episode_model_v9_new_validation_set_include_smoking_focal_loss_static_coeff_phenotype_lower_model_v2.p','rb'))\n",
+    "    else:\n",
+    "        data_eval = pickle.load(open(data_directory+str(n_lag)+\n",
+    "        '_episode_model_v9_new_validation_set_include_smoking_focal_loss_static_coeff_phenotype_lower_model_no_episode_v2.p','rb'))\n",
+    "\n",
+    "    data_feature_label = pickle.load(open('./data/episode_encoded_lagged_data/episode_encoded_lagged_15_windows_standardized_phenotype1.p','rb'))\n",
+    "\n",
+    "    data_cluster = pickle.load(open('./data/episode_encoded_lagged_data/episode_encoded_lagged_'+str(n_lag)+'_windows_standardized_phenotype1.p','rb'))\n",
+    "\n",
+    "    temp = data_cluster.groupby(['user','cluster_label']).count().index.values\n",
+    "    users = np.array([a[0] for a in temp])\n",
+    "    labels = np.array([a[1] for a in temp])\n",
+    "    cluster_dict = {}\n",
+    "    for i,a in enumerate(users):\n",
+    "        cluster_dict[a] = labels[i]\n",
+    "\n",
+    "    result_phenotypes_final = {}\n",
+    "    for label in cluster_dict.values():\n",
+    "        result_phenotypes_final[label] = [0,0,0,len(users[labels==label]),[],[],[],[]]\n",
+    "    \n",
+    "    y_time = data_eval[0]\n",
+    "    y_pred = np.array(data_eval[1])\n",
+    "    y_test = data_eval[2]\n",
+    "    y_pid = data_eval[3]\n",
+    "    bias_dict = data_eval[4]\n",
+    "    val_results = data_eval[5]\n",
+    "    \n",
+    "    y_time = np.array(y_time)\n",
+    "    y_pred = np.array(y_pred)\n",
+    "    y_test = np.array(y_test)\n",
+    "    y_pid = np.array(y_pid)\n",
+    "    pars = np.unique(y_pid)\n",
+    "    y_time_day = np.array([str(a)[:10] for a in y_time])\n",
+    "    y_time_hour = np.array(pd.to_datetime(y_time).hour)\n",
+    "    intervention_dict={}\n",
+    "    for a in pars:\n",
+    "        intervention_dict[a]={}\n",
+    "        index = np.where(y_pid==a)[0]\n",
+    "        days = y_time_day[index]\n",
+    "        for day in np.unique(days):\n",
+    "            intervention_dict[a][day]= {}\n",
+    "            index_hour = np.where((y_pid==a)&(y_time_day==day))[0]\n",
+    "            hours = y_time_hour[index_hour]\n",
+    "            for hour in np.unique(hours):\n",
+    "                intervention_dict[a][day][hour]=0\n",
+    "\n",
+    "    from collections import Counter\n",
+    "    # users = [a[0] for a in Counter(y_pid)]\n",
+    "    # pars=np.array([a for a in pars if a in users])\n",
+    "    total_lapsers = len(pars)\n",
+    "    indexes_pred = np.arange(y_pred.shape[1])\n",
+    "    n_iters = 50\n",
+    "    # bias=f1Bias_scorer_CV(y_pred.mean(axis=1),y_test)[1]\n",
+    "    from joblib import Parallel,delayed\n",
+    "    all_data_v1 = Parallel(n_jobs=-1,verbose=2)(delayed(get_results)(iteration) for iteration in np.arange(n_iters))\n",
+    "    all_data = []\n",
+    "    for a in all_data_v1:\n",
+    "        all_data.extend(a)\n",
+    "    df2 = pd.DataFrame(all_data,columns=['Interventions per day','IHR','TPI','Subtype','Iteration'])\n",
+    "    if episode_presence:\n",
+    "        df2['Encoding'] = ['Proposed Episode Encoding']*df2.shape[0]\n",
+    "    else:\n",
+    "        df2['Encoding'] = ['Use LSTM on Features']*df2.shape[0]\n",
+    "    df_all.append(df2)\n",
+    "df=pd.concat(df_all)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 94,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
-       "<Figure size 720x360 with 1 Axes>"
+       "{'3002': {'2017-06-09': {11: 0,\n",
+       "   12: 0,\n",
+       "   13: 0,\n",
+       "   14: 0,\n",
+       "   15: 0,\n",
+       "   16: 0,\n",
+       "   17: 0,\n",
+       "   18: 0}},\n",
+       " '3004': {'2017-06-23': {10: 0, 11: 0, 12: 0, 13: 0, 14: 0},\n",
+       "  '2017-06-26': {8: 0,\n",
+       "   9: 0,\n",
+       "   10: 0,\n",
+       "   11: 0,\n",
+       "   12: 0,\n",
+       "   13: 0,\n",
+       "   14: 0,\n",
+       "   15: 0,\n",
+       "   16: 0,\n",
+       "   17: 0}},\n",
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+       "   10: 0,\n",
+       "   11: 0,\n",
+       "   12: 0,\n",
+       "   13: 0,\n",
+       "   14: 0,\n",
+       "   15: 0,\n",
+       "   16: 0,\n",
+       "   17: 0,\n",
+       "   18: 0,\n",
+       "   19: 0},\n",
+       "  '2019-03-18': {4: 0, 5: 0, 6: 0, 7: 0, 8: 0, 9: 0}},\n",
+       " '3165': {'2019-03-19': {13: 0,\n",
+       "   14: 0,\n",
+       "   15: 0,\n",
+       "   16: 0,\n",
+       "   17: 0,\n",
+       "   18: 0,\n",
+       "   19: 0,\n",
+       "   20: 0},\n",
+       "  '2019-03-21': {9: 0,\n",
+       "   10: 0,\n",
+       "   11: 0,\n",
+       "   12: 0,\n",
+       "   13: 0,\n",
+       "   14: 0,\n",
+       "   15: 0,\n",
+       "   16: 0,\n",
+       "   17: 0,\n",
+       "   18: 0}},\n",
+       " '3166': {'2019-03-22': {11: 0, 12: 0, 13: 0, 14: 0, 15: 0, 16: 0, 17: 0},\n",
+       "  '2019-03-23': {7: 0,\n",
+       "   8: 0,\n",
+       "   9: 0,\n",
+       "   10: 0,\n",
+       "   11: 0,\n",
+       "   12: 0,\n",
+       "   13: 0,\n",
+       "   14: 0,\n",
+       "   15: 0,\n",
+       "   16: 0,\n",
+       "   17: 0,\n",
+       "   18: 0,\n",
+       "   19: 0,\n",
+       "   20: 0,\n",
+       "   21: 0,\n",
+       "   22: 0,\n",
+       "   23: 0},\n",
+       "  '2019-03-24': {7: 0, 8: 0, 9: 0, 10: 0, 11: 0, 12: 0, 13: 0, 14: 0, 15: 0}},\n",
+       " '3168': {'2019-03-25': {12: 0, 13: 0, 14: 0, 15: 0, 16: 0, 17: 0, 18: 0}}}"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
+     "execution_count": 94,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
-    "# plt.close('all')\n",
-    "# %matplotlib inline\n",
-    "plt.figure(figsize=(10,5))\n",
-    "# sns.kdeplot(x='risk',hue='cluster',data=df_predictions,common_norm=True)\n",
-    "# plt.hist(df_predictions[df_predictions.cluster==0]['risk'],300)\n",
-    "# plt.hist(df_predictions[df_predictions.cluster==1]['risk'],300)\n",
-    "# plt.hist(df_predictions[df_predictions.cluster==2]['risk'],300)\n",
-    "# plt.hist(df_predictions[df_predictions.cluster==3]['risk'],300)\n",
-    "plt.plot(df_predictions[df_predictions.cluster==0]['time'],df_predictions[df_predictions.cluster==0]['risk'])\n",
-    "plt.show()"
+    "intervention_dict"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 231,
+   "execution_count": 88,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
    "metadata": {},
    "outputs": [],
    "source": [
-    "df = pd.DataFrame(all_data,columns=['Interventions per day','IHR','TPI','Subtype','Iteration'])\n",
-    "df['Encoding'] = ['Proposed Episode Encoding']*df.shape[0]"
+    "# from collections import Counter\n",
+    "# data=[a[0]+a[1] for a in np.array(list(zip(y_pid,y_time_day)))]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 232,
+   "execution_count": 82,
    "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>Subtype</th>\n",
-       "      <th>Interventions per day</th>\n",
-       "      <th>Encoding</th>\n",
-       "      <th>IHR</th>\n",
-       "      <th>TPI</th>\n",
-       "      <th>Iteration</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>Overall</td>\n",
-       "      <td>3.5</td>\n",
-       "      <td>Proposed Episode Encoding</td>\n",
-       "      <td>0.181139</td>\n",
-       "      <td>38.253968</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Overall</td>\n",
-       "      <td>4.5</td>\n",
-       "      <td>Proposed Episode Encoding</td>\n",
-       "      <td>0.366607</td>\n",
-       "      <td>31.156693</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>Overall</td>\n",
-       "      <td>5.5</td>\n",
-       "      <td>Proposed Episode Encoding</td>\n",
-       "      <td>0.639333</td>\n",
-       "      <td>27.151444</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>Overall</td>\n",
-       "      <td>6.5</td>\n",
-       "      <td>Proposed Episode Encoding</td>\n",
-       "      <td>0.798801</td>\n",
-       "      <td>23.394958</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>Overall</td>\n",
-       "      <td>7.5</td>\n",
-       "      <td>Proposed Episode Encoding</td>\n",
-       "      <td>0.869790</td>\n",
-       "      <td>21.231474</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>Overall</td>\n",
-       "      <td>8.5</td>\n",
-       "      <td>Proposed Episode Encoding</td>\n",
-       "      <td>0.901850</td>\n",
-       "      <td>19.721510</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>Overall</td>\n",
-       "      <td>9.5</td>\n",
-       "      <td>Proposed Episode Encoding</td>\n",
-       "      <td>0.914566</td>\n",
-       "      <td>18.761905</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>Overall</td>\n",
-       "      <td>10.5</td>\n",
-       "      <td>Proposed Episode Encoding</td>\n",
-       "      <td>0.914566</td>\n",
-       "      <td>18.761905</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>Overall</td>\n",
-       "      <td>11.5</td>\n",
-       "      <td>Proposed Episode Encoding</td>\n",
-       "      <td>0.914566</td>\n",
-       "      <td>18.761905</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   Subtype  Interventions per day                   Encoding       IHR  \\\n",
-       "0  Overall                    3.5  Proposed Episode Encoding  0.181139   \n",
-       "1  Overall                    4.5  Proposed Episode Encoding  0.366607   \n",
-       "2  Overall                    5.5  Proposed Episode Encoding  0.639333   \n",
-       "3  Overall                    6.5  Proposed Episode Encoding  0.798801   \n",
-       "4  Overall                    7.5  Proposed Episode Encoding  0.869790   \n",
-       "5  Overall                    8.5  Proposed Episode Encoding  0.901850   \n",
-       "6  Overall                    9.5  Proposed Episode Encoding  0.914566   \n",
-       "7  Overall                   10.5  Proposed Episode Encoding  0.914566   \n",
-       "8  Overall                   11.5  Proposed Episode Encoding  0.914566   \n",
-       "\n",
-       "         TPI  Iteration  \n",
-       "0  38.253968          0  \n",
-       "1  31.156693          0  \n",
-       "2  27.151444          0  \n",
-       "3  23.394958          0  \n",
-       "4  21.231474          0  \n",
-       "5  19.721510          0  \n",
-       "6  18.761905          0  \n",
-       "7  18.761905          0  \n",
-       "8  18.761905          0  "
-      ]
-     },
-     "execution_count": 232,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "df[df.Subtype=='Overall'].groupby(['Subtype','Interventions per day','Encoding'],as_index=False).mean()"
+    "\n",
+    "# len(y_time_day)*2/(len(np.unique(y_time_day))*60)\n",
+    "# plt.hist(Counter(y_pid).values())"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1440x720 with 4 Axes>"
       ]
@@ -490,11 +982,11 @@
     "import matplotlib.pyplot as plt\n",
     "import seaborn as sns\n",
     "import pickle\n",
-    "df  = pickle.load(open('./data/saved_result/ihr_tpi_dataframe.p','rb'))\n",
+    "# df  = pickle.load(open('./data/saved_result/ihr_tpi_dataframe.p','rb'))\n",
     "plt.rcParams.update({'font.size':15})\n",
     "fig,ax = plt.subplots(2,2,figsize=(20,10),sharex=True)\n",
     "sns.pointplot(x='Interventions per day',y='IHR',hue='Encoding',data=df[df.Subtype.isin(['Cluster 0'])],ci='sd',ax=ax[0,0])\n",
-    "ax[0,0].set_ylim([0,1])\n",
+    "# ax[0,0].set_ylim([0,1])\n",
     "ax[0,0].set_title('Cluster 0')\n",
     "sns.pointplot(x='Interventions per day',y='IHR',hue='Encoding',data=df[df.Subtype.isin(['Cluster 1'])],ci='sd',ax=ax[0,1])\n",
     "ax[0,1].set_ylim([0,1])\n",
@@ -516,26 +1008,56 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 97,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "final_recall = [0.75, 0.7307692307692307, 0.7307692307692307, 0.6923076923076923, 0.7115384615384616, 0.6153846153846154, 0.5961538461538461, 0.4230769230769231, 0.25, 0.2692307692307692, 0.21153846153846154, 0.11538461538461539, 0.11538461538461539]\n",
+    "0.6923076923076923\n",
+    "final_intpday = [11.761467889908257, 8.81651376146789, 7.110091743119266, 5.972477064220183, 5.284403669724771, 4.706422018348624, 4.275229357798165, 3.926605504587156, 3.614678899082569, 3.4128440366972477, 3.1743119266055047, 3.055045871559633, 2.963302752293578]\n",
+    "final_gap = [23.96153846153846, 25.346153846153847, 27.346153846153847, 29.807692307692307, 30.076923076923077, 32.69230769230769, 36.26923076923077, 36.69230769230769, 38.92307692307692, 39.34615384615385, 42.80769230769231, 43.46153846153846, 45.15384615384615]\n",
+    "result =  get_smoothed_result(final_intpday,final_recall,final_gap)\n",
+    "x = np.array([3.5]+list(np.arange(4,12,1)))\n",
+    "result= get_interpolated_data(result,x,name='Overall',iteration=1)\n",
+    "result\n",
+    "temp_data = []\n",
+    "for a in result:\n",
+    "    temp_data.append([a[0],a[1],a[2],'Overall','Random Forest on Features',0])\n",
+    "df4 = pd.DataFrame(temp_data,columns=['Interventions per day','IHR','TPI','Subtype','Encoding','Iteration'])\n",
+    "df_final = pd.concat([df,df4])\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "image/png": 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",
       "text/plain": [
-       "array(['Overall', 'Cluster 3', 'Cluster 1', 'Cluster 2', 'Cluster 0'],\n",
-       "      dtype=object)"
+       "<Figure size 1440x720 with 2 Axes>"
       ]
      },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "# df1 = df.copy()\n",
-    "# from collections import Counter\n",
-    "# Counter(cluster_dict.values())\n",
-    "df.Subtype.unique()"
+    "plt.rcParams.update({'font.size':25})\n",
+    "fig,ax = plt.subplots(1,1,figsize=(20,10))\n",
+    "sns.pointplot(x='Interventions per day',y='IHR',hue='Encoding',data=df_final[df_final.Subtype.isin(['Overall'])],ci=None,ax=ax)\n",
+    "plt.legend(loc='center right')\n",
+    "ax.set_ylabel('IHR\\n(Solid line)')\n",
+    "ax1=ax.twinx()\n",
+    "sns.pointplot(x='Interventions per day',y='TPI',hue='Encoding',data=df_final[df_final.Subtype.isin(['Overall'])],ci=None,ax=ax1,linestyles='-.')\n",
+    "ax1.set_ylabel('TPI\\n(Dashed line)')\n",
+    "plt.legend([],[], frameon=False)\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n",
+    "\n"
    ]
   },
   {
diff --git a/preprocess_event_encoded_data.ipynb b/preprocess_event_encoded_data.ipynb
index 92a4eeb..e81c39b 100644
--- a/preprocess_event_encoded_data.ipynb
+++ b/preprocess_event_encoded_data.ipynb
@@ -26,21 +26,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
    "id": "ultimate-linux",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/azim/miniconda3/envs/test1/lib/python3.8/site-packages/tensorflow_addons/utils/ensure_tf_install.py:38: UserWarning: You are currently using a nightly version of TensorFlow (2.5.0-dev20210310). \n",
-      "TensorFlow Addons offers no support for the nightly versions of TensorFlow. Some things might work, some other might not. \n",
-      "If you encounter a bug, do not file an issue on GitHub.\n",
-      "  warnings.warn(\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from datetime import datetime,timedelta\n",
     "from scipy.stats import iqr,skew,kurtosis,mode\n",
@@ -93,7 +89,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 94,
+   "execution_count": 102,
    "id": "thousand-volume",
    "metadata": {},
    "outputs": [
@@ -109,8 +105,8 @@
      "output_type": "stream",
      "text": [
       "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 24 concurrent workers.\n",
-      "[Parallel(n_jobs=-1)]: Done  32 out of  52 | elapsed:    5.8s remaining:    3.6s\n",
-      "[Parallel(n_jobs=-1)]: Done  52 out of  52 | elapsed:    8.8s finished\n"
+      "[Parallel(n_jobs=-1)]: Done  32 out of  52 | elapsed:    4.0s remaining:    2.5s\n",
+      "[Parallel(n_jobs=-1)]: Done  52 out of  52 | elapsed:    6.9s finished\n"
      ]
     },
     {
@@ -144,12 +140,12 @@
      "output_type": "stream",
      "text": [
       "[0 2 4 5 6 7 8]\n",
-      "Counter({1: 20, 0: 13, 3: 9, 2: 9})\n"
+      "Counter({2: 20, 3: 13, 1: 9, 0: 9})\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -158,6 +154,13 @@
       "needs_background": "light"
      },
      "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(1, 14)\n"
+     ]
     }
    ],
    "source": [
@@ -402,8 +405,9 @@
     "    cluster_features = {a:list(xxx[y==y[i],:].mean(axis=0)) for i,a in enumerate(users)}\n",
     "    df_seq['cluster_label'] = df_seq['user'].apply(lambda a:cluster_dict[a])\n",
     "    df_seq['static_features'] = df_seq.apply(lambda a:\n",
-    "                                             np.array(cluster_features[a['user']]).reshape(1,-1),\n",
+    "                                             np.array(list(cluster_features[a['user']])+list(a['weekday_encoded'])).reshape(1,-1),\n",
     "                                             axis=1)\n",
+    "    print(df_seq.static_features.iloc[0].shape)\n",
     "    feature_names = ['visit_freq',\n",
     "                'visit_duration_mean',\n",
     "                'stress_avg_density_per_day',\n",
@@ -420,13 +424,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 101,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0., 0., 0., 0., 1., 0., 0.])"
+      ]
+     },
+     "execution_count": 101,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# xxx.shape,len(index_of_features_kept),\n",
     "\n",
-    "df = pd.DataFrame(xxx,columns=[feature_names[i] for i in index_of_features_kept])"
+    "# df = pd.DataFrame(xxx,columns=[feature_names[i] for i in index_of_features_kept])\n",
+    "df_seq.weekday_encoded.iloc[0]"
    ]
   },
   {
diff --git a/v1_train_lstm_with_event_encoded.ipynb b/v1_train_lstm_with_event_encoded.ipynb
index ce2a69d..cd25162 100644
--- a/v1_train_lstm_with_event_encoded.ipynb
+++ b/v1_train_lstm_with_event_encoded.ipynb
@@ -2610,7 +2610,158 @@
       "Epoch 00170: early stopping\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
       "Epoch 00080: early stopping\n",
-      "(None, 1, 1) coeff (None, 10, 30) amplitude\n"
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00074: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00056: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00118: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00105: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00091: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00083: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00077: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00098: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00184: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00066: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00068: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00065: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00090: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00077: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00128: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00071: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00056: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00062: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00070: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00265: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00109: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00111: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00117: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00078: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00080: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00132: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00116: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00104: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00056: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00089: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00142: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00062: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00084: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00149: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00083: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00113: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00079: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00084: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00074: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00075: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00092: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00083: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00099: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00049: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00085: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00076: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00060: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00057: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00103: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00066: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00072: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00151: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00091: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00110: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00061: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00102: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00075: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00071: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00105: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00049: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00103: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00058: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00080: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00062: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00075: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00099: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00064: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00059: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00074: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00094: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00065: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00070: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00080: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00084: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00085: early stopping\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00066: early stopping\n"
      ]
     }
    ],
diff --git a/v2_train_lstm_with_event_encoded.ipynb b/v2_train_lstm_with_event_encoded.ipynb
index 76ed8cc..a6bee89 100644
--- a/v2_train_lstm_with_event_encoded.ipynb
+++ b/v2_train_lstm_with_event_encoded.ipynb
@@ -2,19 +2,9 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/azim/miniconda3/envs/test1/lib/python3.8/site-packages/tensorflow_addons/utils/ensure_tf_install.py:38: UserWarning: You are currently using a nightly version of TensorFlow (2.5.0-dev20210310). \n",
-      "TensorFlow Addons offers no support for the nightly versions of TensorFlow. Some things might work, some other might not. \n",
-      "If you encounter a bug, do not file an issue on GitHub.\n",
-      "  warnings.warn(\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -81,7 +71,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -218,7 +215,7 @@
     "    smoking_alpha_time_exp = tf.math.exp(smoking_alpha_time)\n",
     "    \n",
     "    x_smoking_amplitude = x_smoking[:,:,:,1]\n",
-    "    smoking_amplitude_coeff = Dense(1,activation='sigmoid',name='amplitude_smoking')(x_static)\n",
+    "    smoking_amplitude_coeff = Dense(1,activation='relu',name='amplitude_smoking')(x_static)\n",
     "    smoking_amplitude_coeff = Lambda(lambda x: expand_dims(x, axis=2))(smoking_amplitude_coeff)\n",
     "    x_smoking_amplitude = tf.math.multiply(x_smoking_amplitude,smoking_amplitude_coeff)\n",
     "    \n",
@@ -314,73 +311,163 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 84,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00063: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00072: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
       "Epoch 00085: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
-      "Epoch 00098: early stopping\n",
+      "Epoch 00086: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
-      "Epoch 00081: early stopping\n",
+      "Epoch 00123: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
-      "Epoch 00070: early stopping\n",
+      "Epoch 00056: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
-      "Epoch 00074: early stopping\n",
+      "Epoch 00054: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
-      "Epoch 00086: early stopping\n",
+      "Epoch 00101: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
-      "Epoch 00095: early stopping\n",
+      "Epoch 00058: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
-      "Epoch 00079: early stopping\n",
+      "Epoch 00115: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
-      "Epoch 00066: early stopping\n",
+      "Epoch 00068: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00073: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00060: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00089: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00060: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00065: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00094: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00085: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00109: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
       "Epoch 00066: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
-      "Epoch 00064: early stopping\n",
+      "Epoch 00074: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00068: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00071: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00053: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00085: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00069: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00070: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00094: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00069: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00084: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00069: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
       "Epoch 00063: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
-      "Epoch 00146: early stopping\n",
+      "Epoch 00124: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
-      "Epoch 00092: early stopping\n",
+      "Epoch 00084: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
       "Epoch 00068: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
-      "Epoch 00117: early stopping\n",
+      "Epoch 00097: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
-      "Epoch 00102: early stopping\n",
+      "Epoch 00115: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00071: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00190: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00068: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00053: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00085: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00052: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00114: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
       "Epoch 00066: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
-      "Epoch 00125: early stopping\n",
+      "Epoch 00075: early stopping\n",
       "15 67\n",
       "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
-      "Epoch 00082: early stopping\n"
+      "Epoch 00119: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00093: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00063: early stopping\n",
+      "15 67\n",
+      "(None, 1, 1) coeff (None, 10, 30) amplitude\n",
+      "Epoch 00089: early stopping\n"
      ]
     }
    ],
@@ -428,7 +515,7 @@
     "        positive_train_index = np.where(y_train==1)[0]\n",
     "        negative_train_index = np.where(y_train==0)[0]\n",
     "        len_positive = len(positive_train_index)\n",
-    "        n_iters = 2\n",
+    "        n_iters = 5\n",
     "        test_preds = []\n",
     "        bias_pred = []\n",
     "        for i,n_iter in enumerate(range(n_iters)):\n",
@@ -462,25 +549,42 @@
     "            validation_data=([val_feature,val_static,val_stress,val_activity,val_smoking,val_quit],val_y), epochs=200, batch_size=100,\n",
     "                        verbose=0,callbacks=callbacks_list,shuffle=True)\n",
     "            model.load_weights(filepath)\n",
-    "            for c_name in columns:\n",
-    "                temp_model = tf.keras.Model(model.input,model.get_layer(c_name).output)\n",
-    "                alpha_stress = temp_model.predict([X_feature_test,X_static_test,X_stress_episode_test,\n",
-    "                                                    X_activity_episode_test,X_smoking_episode_test,X_quit_episode_test])\n",
-    "                cluster_done = [False]*len(cluster_dict)\n",
-    "                for ii,a in enumerate(groups_test):\n",
-    "                    if cluster_done[int(cluster_dict[a])]:\n",
-    "                        continue\n",
-    "                    all_data.append([alpha_stress[i][0]*-1,c_name,cluster_dict[a],n_lag,kk,i])\n",
-    "                    cluster_done[int(cluster_dict[a])] = True\n",
-    "            temp_model = tf.keras.Model(model.input,[model.get_layer(amplitude_duration_columns[0]).output,model.get_layer(amplitude_duration_columns[1]).output])\n",
-    "            alpha_stress = temp_model.predict([X_feature_test,X_static_test,X_stress_episode_test,\n",
-    "                                        X_activity_episode_test,X_smoking_episode_test,X_quit_episode_test])\n",
-    "            cluster_done = [False]*len(cluster_dict)\n",
-    "            for ii,a in enumerate(groups_test):\n",
-    "                if cluster_done[int(cluster_dict[a])]:\n",
-    "                    continue\n",
-    "                amplitude_duration_data.append([alpha_stress[0][i][0]*-1,alpha_stress[1][i][0]*-1,cluster_dict[a],n_lag,kk,i])\n",
-    "                cluster_done[int(cluster_dict[a])] = True\n",
+    "            temp_model = Model(model.input[1],[model.get_layer(c).output for c in columns+amplitude_duration_columns])\n",
+    "            X_static_test_new = np.hstack((X_static_test, np.zeros((X_static_test.shape[0], 3), dtype=X_static_test.dtype)))\n",
+    "            X_static_test_new[:,-3] = np.mean(X_stress_episode_test[:,:,0,1],axis=1)\n",
+    "            X_static_test_new[:,-2] = np.mean(X_stress_episode_test[:,:,0,2],axis=1)\n",
+    "            X_static_test_new[:,-1] = [cluster_dict[a] for a in groups_test]\n",
+    "            X_static_test_new = np.unique(X_static_test_new,axis=0)\n",
+    "            pred_list = list(zip(*[list(a.reshape(-1)) for a in temp_model.predict(X_static_test_new[:,:-3])]))\n",
+    "            for ii,a in enumerate(pred_list):\n",
+    "                for jj,c_name in enumerate(columns+amplitude_duration_columns):\n",
+    "                    all_data.append([a[jj],\n",
+    "                                    c_name,\n",
+    "                                    X_static_test_new[ii][-1],\n",
+    "                                    a[-2]*X_static_test_new[ii][-3],\n",
+    "                                    a[-1]*X_static_test_new[ii][-2],\n",
+    "                                    n_lag,\n",
+    "                                    kk,\n",
+    "                                    i])\n",
+    "    #         for c_name in columns:\n",
+    "    #             temp_model = tf.keras.Model(model.input,model.get_layer(c_name).output)\n",
+    "    #             alpha_stress = temp_model.predict([X_feature_test,X_static_test,X_stress_episode_test,\n",
+    "    #                                                 X_activity_episode_test,X_smoking_episode_test,X_quit_episode_test])\n",
+    "    #             cluster_done = [False]*len(cluster_dict)\n",
+    "    #             for ii,a in enumerate(groups_test):\n",
+    "    #                 if cluster_done[int(cluster_dict[a])]:\n",
+    "    #                     continue\n",
+    "    #                 all_data.append([alpha_stress[i][0]*-1,c_name,cluster_dict[a],n_lag,kk,i])\n",
+    "    #                 cluster_done[int(cluster_dict[a])] = True\n",
+    "    #         temp_model = tf.keras.Model(model.input,[model.get_layer(amplitude_duration_columns[0]).output,model.get_layer(amplitude_duration_columns[1]).output])\n",
+    "    #         alpha_stress = temp_model.predict([X_feature_test,X_static_test,X_stress_episode_test,\n",
+    "    #                                     X_activity_episode_test,X_smoking_episode_test,X_quit_episode_test])\n",
+    "    #         cluster_done = [False]*len(cluster_dict)\n",
+    "    #         for ii,a in enumerate(groups_test):\n",
+    "    #             if cluster_done[int(cluster_dict[a])]:\n",
+    "    #                 continue\n",
+    "    #             amplitude_duration_data.append([alpha_stress[0][i][0]*-1,alpha_stress[1][i][0]*-1,cluster_dict[a],n_lag,kk,i])\n",
+    "    #             cluster_done[int(cluster_dict[a])] = True\n",
     "\n",
     "            test_preds.append(model.predict([X_feature_test,X_static_test,X_stress_episode_test,\n",
     "                                        X_activity_episode_test,X_smoking_episode_test,X_quit_episode_test]))\n",
@@ -506,7 +610,215 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pickle.dump(all_data,open('./data/saved_result/coeffs3.p','wb'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "df = pd.DataFrame(all_data,columns=['value','name','cluster','amplitude','duration','lag','split','iteration'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "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>value</th>\n",
+       "      <th>name</th>\n",
+       "      <th>cluster</th>\n",
+       "      <th>amplitude</th>\n",
+       "      <th>duration</th>\n",
+       "      <th>lag</th>\n",
+       "      <th>split</th>\n",
+       "      <th>iteration</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.999459</td>\n",
+       "      <td>alpha_stress</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.000478</td>\n",
+       "      <td>4.329489</td>\n",
+       "      <td>15</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.228008</td>\n",
+       "      <td>alpha_smoking</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.000478</td>\n",
+       "      <td>4.329489</td>\n",
+       "      <td>15</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.097826</td>\n",
+       "      <td>alpha_activity</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.000478</td>\n",
+       "      <td>4.329489</td>\n",
+       "      <td>15</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.002337</td>\n",
+       "      <td>amplitude_stress</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.000478</td>\n",
+       "      <td>4.329489</td>\n",
+       "      <td>15</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.994825</td>\n",
+       "      <td>duration_stress</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.000478</td>\n",
+       "      <td>4.329489</td>\n",
+       "      <td>15</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      value              name  cluster  amplitude  duration  lag  split  \\\n",
+       "0  0.999459      alpha_stress      1.0   0.000478  4.329489   15      0   \n",
+       "1  0.228008     alpha_smoking      1.0   0.000478  4.329489   15      0   \n",
+       "2  0.097826    alpha_activity      1.0   0.000478  4.329489   15      0   \n",
+       "3  0.002337  amplitude_stress      1.0   0.000478  4.329489   15      0   \n",
+       "4  0.994825   duration_stress      1.0   0.000478  4.329489   15      0   \n",
+       "\n",
+       "   iteration  \n",
+       "0          0  \n",
+       "1          0  \n",
+       "2          0  \n",
+       "3          0  \n",
+       "4          0  "
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='name', ylabel='value'>"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1440x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(20,10))\n",
+    "sns.barplot(x='name',y='value',data=df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7f26b8079e20>"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# plt.scatter(df['duration'],df['amplitude'])\n",
+    "# plt.hist(df['duration'])\n",
+    "# sns.jointplot(x='amplitude',y='duration',data=df,kind='hex')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 184,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -515,7 +827,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 89,
+   "execution_count": 185,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -524,21 +836,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 90,
+   "execution_count": 186,
    "metadata": {},
    "outputs": [],
    "source": [
-    "pickle.dump([df,df_amplitude_duration],open('./data/saved_result/coeffs.p','wb'))"
+    "pickle.dump([df,df_amplitude_duration],open('./data/saved_result/coeffs1.p','wb'))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 148,
+   "execution_count": 188,
    "metadata": {},
    "outputs": [],
    "source": [
     "import seaborn as sns\n",
-    "df,df_amplitude_duration = pickle.load(open('./data/saved_result/coeffs.p','rb'))\n",
+    "df,df_amplitude_duration = pickle.load(open('./data/saved_result/coeffs1.p','rb'))\n",
     "df['value'] = df['value']*-1\n",
     "df_amplitude_duration['amplitude'] = df_amplitude_duration['amplitude']*-1\n",
     "df_amplitude_duration['duration'] = df_amplitude_duration['duration']*-1\n"
@@ -546,7 +858,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 178,
+   "execution_count": 189,
    "metadata": {},
    "outputs": [
     {
@@ -560,7 +872,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 432x432 with 3 Axes>"
       ]
@@ -728,12 +1040,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 139,
+   "execution_count": 191,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1440x720 with 1 Axes>"
       ]
@@ -747,7 +1059,7 @@
    "source": [
     "plt.rcParams.update({'font.size':25})\n",
     "plt.figure(figsize=(20,10))\n",
-    "sns.barplot(x='name',y='value',hue='cluster',data=df)\n",
+    "sns.boxplot(x='name',y='value',hue='cluster',data=df)\n",
     "plt.xticks([0,1,2],[r'$\\alpha_{stress}$',r'$\\alpha_{smoking}$',r'$\\alpha_{activity}$'])\n",
     "plt.xlabel('Decay Parameters')\n",
     "plt.ylabel('Value')\n",
@@ -1064,15 +1376,6 @@
     "import shutil"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 180,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "shutil.rmtree('./catboost_info/')"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,