diff --git a/demo/APO Sample Existing Demo.ipynb b/demo/APO Sample Existing Demo.ipynb
index 8e8e2b0..8e9df98 100644
--- a/demo/APO Sample Existing Demo.ipynb	
+++ b/demo/APO Sample Existing Demo.ipynb	
@@ -2,18 +2,10 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "75f106cc",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "['../', '/opt/homebrew/Cellar/python@3.13/3.13.5/Frameworks/Python.framework/Versions/3.13/lib/python313.zip', '/opt/homebrew/Cellar/python@3.13/3.13.5/Frameworks/Python.framework/Versions/3.13/lib/python3.13', '/opt/homebrew/Cellar/python@3.13/3.13.5/Frameworks/Python.framework/Versions/3.13/lib/python3.13/lib-dynload', '', '/Users/margovsk/Desktop/source-code/obsidian/.venv/lib/python3.13/site-packages']\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import sys\n",
     "sys.path.insert(0, '../')\n",
@@ -23,26 +15,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "117a382f",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/margovsk/Desktop/source-code/obsidian/.venv/lib/python3.13/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
-      "  from .autonotebook import tqdm as notebook_tqdm\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "obsidian version: 0.8.6-test\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import obsidian\n",
     "import pandas as pd\n",
@@ -55,229 +31,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "1cd0a6b0",
    "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>reagent_conc</th>\n",
-       "      <th>ionic_strength</th>\n",
-       "      <th>surfactant_conc</th>\n",
-       "      <th>compound_A</th>\n",
-       "      <th>compound_B</th>\n",
-       "      <th>sugar</th>\n",
-       "      <th>surfactant</th>\n",
-       "      <th>buffer</th>\n",
-       "      <th>pH</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>FormulationID</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>0.44</td>\n",
-       "      <td>26.66</td>\n",
-       "      <td>0.060</td>\n",
-       "      <td>33.64</td>\n",
-       "      <td>28.60</td>\n",
-       "      <td>sucrose</td>\n",
-       "      <td>Tween20</td>\n",
-       "      <td>Tris</td>\n",
-       "      <td>7.11</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>0.96</td>\n",
-       "      <td>58.77</td>\n",
-       "      <td>0.057</td>\n",
-       "      <td>39.83</td>\n",
-       "      <td>40.27</td>\n",
-       "      <td>sucrose</td>\n",
-       "      <td>Tween20</td>\n",
-       "      <td>PBS</td>\n",
-       "      <td>8.30</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>0.76</td>\n",
-       "      <td>88.57</td>\n",
-       "      <td>0.182</td>\n",
-       "      <td>12.52</td>\n",
-       "      <td>38.01</td>\n",
-       "      <td>sucrose</td>\n",
-       "      <td>SDS</td>\n",
-       "      <td>PBS</td>\n",
-       "      <td>8.00</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>0.64</td>\n",
-       "      <td>75.90</td>\n",
-       "      <td>0.057</td>\n",
-       "      <td>31.24</td>\n",
-       "      <td>7.69</td>\n",
-       "      <td>fructose</td>\n",
-       "      <td>Tween20</td>\n",
-       "      <td>Tris</td>\n",
-       "      <td>8.03</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>0.24</td>\n",
-       "      <td>82.59</td>\n",
-       "      <td>0.062</td>\n",
-       "      <td>28.59</td>\n",
-       "      <td>7.46</td>\n",
-       "      <td>sucrose</td>\n",
-       "      <td>SDS</td>\n",
-       "      <td>Tris</td>\n",
-       "      <td>6.41</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>995</th>\n",
-       "      <td>0.18</td>\n",
-       "      <td>69.13</td>\n",
-       "      <td>0.174</td>\n",
-       "      <td>22.11</td>\n",
-       "      <td>44.87</td>\n",
-       "      <td>glucose</td>\n",
-       "      <td>SDS</td>\n",
-       "      <td>Tris</td>\n",
-       "      <td>8.27</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>996</th>\n",
-       "      <td>0.93</td>\n",
-       "      <td>96.10</td>\n",
-       "      <td>0.040</td>\n",
-       "      <td>16.72</td>\n",
-       "      <td>5.97</td>\n",
-       "      <td>glucose</td>\n",
-       "      <td>SDS</td>\n",
-       "      <td>PBS</td>\n",
-       "      <td>7.77</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>997</th>\n",
-       "      <td>0.22</td>\n",
-       "      <td>16.21</td>\n",
-       "      <td>0.069</td>\n",
-       "      <td>19.73</td>\n",
-       "      <td>16.39</td>\n",
-       "      <td>sucrose</td>\n",
-       "      <td>SDS</td>\n",
-       "      <td>HEPES</td>\n",
-       "      <td>7.70</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>998</th>\n",
-       "      <td>0.96</td>\n",
-       "      <td>15.13</td>\n",
-       "      <td>0.065</td>\n",
-       "      <td>26.50</td>\n",
-       "      <td>40.79</td>\n",
-       "      <td>glucose</td>\n",
-       "      <td>SDS</td>\n",
-       "      <td>Tris</td>\n",
-       "      <td>7.63</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>999</th>\n",
-       "      <td>0.50</td>\n",
-       "      <td>35.40</td>\n",
-       "      <td>0.176</td>\n",
-       "      <td>8.07</td>\n",
-       "      <td>29.87</td>\n",
-       "      <td>sucrose</td>\n",
-       "      <td>SDS</td>\n",
-       "      <td>Tris</td>\n",
-       "      <td>6.10</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>1000 rows × 9 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "               reagent_conc  ionic_strength  surfactant_conc  compound_A  \\\n",
-       "FormulationID                                                              \n",
-       "0                      0.44           26.66            0.060       33.64   \n",
-       "1                      0.96           58.77            0.057       39.83   \n",
-       "2                      0.76           88.57            0.182       12.52   \n",
-       "3                      0.64           75.90            0.057       31.24   \n",
-       "4                      0.24           82.59            0.062       28.59   \n",
-       "...                     ...             ...              ...         ...   \n",
-       "995                    0.18           69.13            0.174       22.11   \n",
-       "996                    0.93           96.10            0.040       16.72   \n",
-       "997                    0.22           16.21            0.069       19.73   \n",
-       "998                    0.96           15.13            0.065       26.50   \n",
-       "999                    0.50           35.40            0.176        8.07   \n",
-       "\n",
-       "               compound_B     sugar surfactant buffer    pH  \n",
-       "FormulationID                                                \n",
-       "0                   28.60   sucrose    Tween20   Tris  7.11  \n",
-       "1                   40.27   sucrose    Tween20    PBS  8.30  \n",
-       "2                   38.01   sucrose        SDS    PBS  8.00  \n",
-       "3                    7.69  fructose    Tween20   Tris  8.03  \n",
-       "4                    7.46   sucrose        SDS   Tris  6.41  \n",
-       "...                   ...       ...        ...    ...   ...  \n",
-       "995                 44.87   glucose        SDS   Tris  8.27  \n",
-       "996                  5.97   glucose        SDS    PBS  7.77  \n",
-       "997                 16.39   sucrose        SDS  HEPES  7.70  \n",
-       "998                 40.79   glucose        SDS   Tris  7.63  \n",
-       "999                 29.87   sucrose        SDS   Tris  6.10  \n",
-       "\n",
-       "[1000 rows x 9 columns]"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "#generate random data for this demo\n",
     "np.random.seed(42)\n",
@@ -301,7 +58,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "57ed0226",
    "metadata": {},
    "outputs": [],
@@ -312,247 +69,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "9feae24b",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Random seed for reproducibility: 220\n",
-      "Weights min: 0.000819672131147541 max: 0.002459016393442623\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 800x400 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "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>reagent_conc</th>\n",
-       "      <th>ionic_strength</th>\n",
-       "      <th>surfactant_conc</th>\n",
-       "      <th>compound_A</th>\n",
-       "      <th>compound_B</th>\n",
-       "      <th>sugar</th>\n",
-       "      <th>surfactant</th>\n",
-       "      <th>buffer</th>\n",
-       "      <th>pH</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>FormulationID</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>369</th>\n",
-       "      <td>0.16</td>\n",
-       "      <td>31.38</td>\n",
-       "      <td>0.149</td>\n",
-       "      <td>34.73</td>\n",
-       "      <td>9.22</td>\n",
-       "      <td>sucrose</td>\n",
-       "      <td>Tween20</td>\n",
-       "      <td>Tris</td>\n",
-       "      <td>6.49</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>379</th>\n",
-       "      <td>0.35</td>\n",
-       "      <td>63.37</td>\n",
-       "      <td>0.162</td>\n",
-       "      <td>34.95</td>\n",
-       "      <td>25.28</td>\n",
-       "      <td>fructose</td>\n",
-       "      <td>SDS</td>\n",
-       "      <td>PBS</td>\n",
-       "      <td>7.61</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>642</th>\n",
-       "      <td>0.29</td>\n",
-       "      <td>56.89</td>\n",
-       "      <td>0.159</td>\n",
-       "      <td>23.40</td>\n",
-       "      <td>42.93</td>\n",
-       "      <td>sucrose</td>\n",
-       "      <td>TritonX</td>\n",
-       "      <td>PBS</td>\n",
-       "      <td>7.57</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>241</th>\n",
-       "      <td>0.96</td>\n",
-       "      <td>79.89</td>\n",
-       "      <td>0.017</td>\n",
-       "      <td>21.45</td>\n",
-       "      <td>19.80</td>\n",
-       "      <td>glucose</td>\n",
-       "      <td>TritonX</td>\n",
-       "      <td>HEPES</td>\n",
-       "      <td>5.89</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>339</th>\n",
-       "      <td>0.19</td>\n",
-       "      <td>12.76</td>\n",
-       "      <td>0.090</td>\n",
-       "      <td>32.71</td>\n",
-       "      <td>10.82</td>\n",
-       "      <td>fructose</td>\n",
-       "      <td>SDS</td>\n",
-       "      <td>PBS</td>\n",
-       "      <td>6.24</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>343</th>\n",
-       "      <td>0.49</td>\n",
-       "      <td>75.45</td>\n",
-       "      <td>0.077</td>\n",
-       "      <td>7.82</td>\n",
-       "      <td>41.32</td>\n",
-       "      <td>fructose</td>\n",
-       "      <td>TritonX</td>\n",
-       "      <td>Tris</td>\n",
-       "      <td>5.70</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>634</th>\n",
-       "      <td>0.20</td>\n",
-       "      <td>93.45</td>\n",
-       "      <td>0.145</td>\n",
-       "      <td>4.69</td>\n",
-       "      <td>6.87</td>\n",
-       "      <td>fructose</td>\n",
-       "      <td>TritonX</td>\n",
-       "      <td>Tris</td>\n",
-       "      <td>6.85</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>906</th>\n",
-       "      <td>0.84</td>\n",
-       "      <td>96.23</td>\n",
-       "      <td>0.195</td>\n",
-       "      <td>25.70</td>\n",
-       "      <td>48.29</td>\n",
-       "      <td>glucose</td>\n",
-       "      <td>TritonX</td>\n",
-       "      <td>HEPES</td>\n",
-       "      <td>6.68</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>170</th>\n",
-       "      <td>0.71</td>\n",
-       "      <td>65.52</td>\n",
-       "      <td>0.140</td>\n",
-       "      <td>32.76</td>\n",
-       "      <td>8.84</td>\n",
-       "      <td>sucrose</td>\n",
-       "      <td>TritonX</td>\n",
-       "      <td>HEPES</td>\n",
-       "      <td>5.81</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>808</th>\n",
-       "      <td>0.51</td>\n",
-       "      <td>25.67</td>\n",
-       "      <td>0.101</td>\n",
-       "      <td>2.52</td>\n",
-       "      <td>12.35</td>\n",
-       "      <td>fructose</td>\n",
-       "      <td>TritonX</td>\n",
-       "      <td>HEPES</td>\n",
-       "      <td>7.24</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>1000 rows × 9 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "               reagent_conc  ionic_strength  surfactant_conc  compound_A  \\\n",
-       "FormulationID                                                              \n",
-       "369                    0.16           31.38            0.149       34.73   \n",
-       "379                    0.35           63.37            0.162       34.95   \n",
-       "642                    0.29           56.89            0.159       23.40   \n",
-       "241                    0.96           79.89            0.017       21.45   \n",
-       "339                    0.19           12.76            0.090       32.71   \n",
-       "...                     ...             ...              ...         ...   \n",
-       "343                    0.49           75.45            0.077        7.82   \n",
-       "634                    0.20           93.45            0.145        4.69   \n",
-       "906                    0.84           96.23            0.195       25.70   \n",
-       "170                    0.71           65.52            0.140       32.76   \n",
-       "808                    0.51           25.67            0.101        2.52   \n",
-       "\n",
-       "               compound_B     sugar surfactant buffer    pH  \n",
-       "FormulationID                                                \n",
-       "369                  9.22   sucrose    Tween20   Tris  6.49  \n",
-       "379                 25.28  fructose        SDS    PBS  7.61  \n",
-       "642                 42.93   sucrose    TritonX    PBS  7.57  \n",
-       "241                 19.80   glucose    TritonX  HEPES  5.89  \n",
-       "339                 10.82  fructose        SDS    PBS  6.24  \n",
-       "...                   ...       ...        ...    ...   ...  \n",
-       "343                 41.32  fructose    TritonX   Tris  5.70  \n",
-       "634                  6.87  fructose    TritonX   Tris  6.85  \n",
-       "906                 48.29   glucose    TritonX  HEPES  6.68  \n",
-       "170                  8.84   sucrose    TritonX  HEPES  5.81  \n",
-       "808                 12.35  fructose    TritonX  HEPES  7.24  \n",
-       "\n",
-       "[1000 rows x 9 columns]"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "\"\"\"\n",
     "You can sample an existing dataset with or without bias: \n",
@@ -579,7 +99,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "ab457ed8",
    "metadata": {},
    "outputs": [],
@@ -590,335 +110,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "9a46bcd0",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Random seed for reproducibility: 994\n",
-      "Weights min: 0.000819672131147541 max: 0.002459016393442623\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 800x400 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'score': 4.498930450581275, 'metric': 'hybrid', 'n_trials': 1000}\n"
-     ]
-    },
-    {
-     "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>reagent_conc</th>\n",
-       "      <th>ionic_strength</th>\n",
-       "      <th>surfactant_conc</th>\n",
-       "      <th>compound_A</th>\n",
-       "      <th>compound_B</th>\n",
-       "      <th>pH</th>\n",
-       "      <th>sugar_fructose</th>\n",
-       "      <th>sugar_glucose</th>\n",
-       "      <th>sugar_sucrose</th>\n",
-       "      <th>surfactant_SDS</th>\n",
-       "      <th>surfactant_TritonX</th>\n",
-       "      <th>surfactant_Tween20</th>\n",
-       "      <th>buffer_HEPES</th>\n",
-       "      <th>buffer_PBS</th>\n",
-       "      <th>buffer_Tris</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>FormulationID</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>326</th>\n",
-       "      <td>0.60</td>\n",
-       "      <td>26.39</td>\n",
-       "      <td>0.166</td>\n",
-       "      <td>40.15</td>\n",
-       "      <td>1.10</td>\n",
-       "      <td>6.39</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>251</th>\n",
-       "      <td>0.45</td>\n",
-       "      <td>53.34</td>\n",
-       "      <td>0.183</td>\n",
-       "      <td>5.77</td>\n",
-       "      <td>3.10</td>\n",
-       "      <td>5.64</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>81</th>\n",
-       "      <td>0.66</td>\n",
-       "      <td>18.05</td>\n",
-       "      <td>0.022</td>\n",
-       "      <td>44.15</td>\n",
-       "      <td>11.67</td>\n",
-       "      <td>7.53</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>83</th>\n",
-       "      <td>0.16</td>\n",
-       "      <td>89.12</td>\n",
-       "      <td>0.183</td>\n",
-       "      <td>29.38</td>\n",
-       "      <td>37.35</td>\n",
-       "      <td>5.89</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>687</th>\n",
-       "      <td>0.35</td>\n",
-       "      <td>53.84</td>\n",
-       "      <td>0.089</td>\n",
-       "      <td>19.37</td>\n",
-       "      <td>0.54</td>\n",
-       "      <td>8.11</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>603</th>\n",
-       "      <td>0.18</td>\n",
-       "      <td>41.95</td>\n",
-       "      <td>0.070</td>\n",
-       "      <td>13.93</td>\n",
-       "      <td>18.51</td>\n",
-       "      <td>7.10</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>963</th>\n",
-       "      <td>0.45</td>\n",
-       "      <td>44.54</td>\n",
-       "      <td>0.196</td>\n",
-       "      <td>29.16</td>\n",
-       "      <td>37.43</td>\n",
-       "      <td>6.64</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>756</th>\n",
-       "      <td>0.66</td>\n",
-       "      <td>96.36</td>\n",
-       "      <td>0.099</td>\n",
-       "      <td>9.23</td>\n",
-       "      <td>0.50</td>\n",
-       "      <td>6.13</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>534</th>\n",
-       "      <td>0.79</td>\n",
-       "      <td>47.22</td>\n",
-       "      <td>0.150</td>\n",
-       "      <td>11.63</td>\n",
-       "      <td>27.76</td>\n",
-       "      <td>7.96</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>279</th>\n",
-       "      <td>0.82</td>\n",
-       "      <td>54.90</td>\n",
-       "      <td>0.023</td>\n",
-       "      <td>39.58</td>\n",
-       "      <td>19.59</td>\n",
-       "      <td>6.27</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "               reagent_conc  ionic_strength  surfactant_conc  compound_A  \\\n",
-       "FormulationID                                                              \n",
-       "326                    0.60           26.39            0.166       40.15   \n",
-       "251                    0.45           53.34            0.183        5.77   \n",
-       "81                     0.66           18.05            0.022       44.15   \n",
-       "83                     0.16           89.12            0.183       29.38   \n",
-       "687                    0.35           53.84            0.089       19.37   \n",
-       "603                    0.18           41.95            0.070       13.93   \n",
-       "963                    0.45           44.54            0.196       29.16   \n",
-       "756                    0.66           96.36            0.099        9.23   \n",
-       "534                    0.79           47.22            0.150       11.63   \n",
-       "279                    0.82           54.90            0.023       39.58   \n",
-       "\n",
-       "               compound_B    pH  sugar_fructose  sugar_glucose  sugar_sucrose  \\\n",
-       "FormulationID                                                                   \n",
-       "326                  1.10  6.39               1              0              0   \n",
-       "251                  3.10  5.64               0              0              1   \n",
-       "81                  11.67  7.53               0              1              0   \n",
-       "83                  37.35  5.89               1              0              0   \n",
-       "687                  0.54  8.11               0              1              0   \n",
-       "603                 18.51  7.10               0              0              1   \n",
-       "963                 37.43  6.64               0              0              1   \n",
-       "756                  0.50  6.13               0              1              0   \n",
-       "534                 27.76  7.96               0              0              1   \n",
-       "279                 19.59  6.27               1              0              0   \n",
-       "\n",
-       "               surfactant_SDS  surfactant_TritonX  surfactant_Tween20  \\\n",
-       "FormulationID                                                           \n",
-       "326                         1                   0                   0   \n",
-       "251                         0                   1                   0   \n",
-       "81                          0                   1                   0   \n",
-       "83                          1                   0                   0   \n",
-       "687                         1                   0                   0   \n",
-       "603                         0                   0                   1   \n",
-       "963                         0                   1                   0   \n",
-       "756                         0                   1                   0   \n",
-       "534                         1                   0                   0   \n",
-       "279                         0                   0                   1   \n",
-       "\n",
-       "               buffer_HEPES  buffer_PBS  buffer_Tris  \n",
-       "FormulationID                                         \n",
-       "326                       1           0            0  \n",
-       "251                       1           0            0  \n",
-       "81                        1           0            0  \n",
-       "83                        0           1            0  \n",
-       "687                       0           0            1  \n",
-       "603                       0           1            0  \n",
-       "963                       0           0            1  \n",
-       "756                       0           1            0  \n",
-       "534                       1           0            0  \n",
-       "279                       0           1            0  "
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "\"\"\"\n",
     "perform random sampling n_trial times, select the best one via criteria metric:\n",
@@ -941,212 +136,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "3ea1bcd8",
    "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>reagent_conc</th>\n",
-       "      <th>ionic_strength</th>\n",
-       "      <th>surfactant_conc</th>\n",
-       "      <th>compound_A</th>\n",
-       "      <th>compound_B</th>\n",
-       "      <th>pH</th>\n",
-       "      <th>sugar</th>\n",
-       "      <th>surfactant</th>\n",
-       "      <th>buffer</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>FormulationID</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>326</th>\n",
-       "      <td>0.60</td>\n",
-       "      <td>26.39</td>\n",
-       "      <td>0.166</td>\n",
-       "      <td>40.15</td>\n",
-       "      <td>1.10</td>\n",
-       "      <td>6.39</td>\n",
-       "      <td>fructose</td>\n",
-       "      <td>SDS</td>\n",
-       "      <td>HEPES</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>251</th>\n",
-       "      <td>0.45</td>\n",
-       "      <td>53.34</td>\n",
-       "      <td>0.183</td>\n",
-       "      <td>5.77</td>\n",
-       "      <td>3.10</td>\n",
-       "      <td>5.64</td>\n",
-       "      <td>sucrose</td>\n",
-       "      <td>TritonX</td>\n",
-       "      <td>HEPES</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>81</th>\n",
-       "      <td>0.66</td>\n",
-       "      <td>18.05</td>\n",
-       "      <td>0.022</td>\n",
-       "      <td>44.15</td>\n",
-       "      <td>11.67</td>\n",
-       "      <td>7.53</td>\n",
-       "      <td>glucose</td>\n",
-       "      <td>TritonX</td>\n",
-       "      <td>HEPES</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>83</th>\n",
-       "      <td>0.16</td>\n",
-       "      <td>89.12</td>\n",
-       "      <td>0.183</td>\n",
-       "      <td>29.38</td>\n",
-       "      <td>37.35</td>\n",
-       "      <td>5.89</td>\n",
-       "      <td>fructose</td>\n",
-       "      <td>SDS</td>\n",
-       "      <td>PBS</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>687</th>\n",
-       "      <td>0.35</td>\n",
-       "      <td>53.84</td>\n",
-       "      <td>0.089</td>\n",
-       "      <td>19.37</td>\n",
-       "      <td>0.54</td>\n",
-       "      <td>8.11</td>\n",
-       "      <td>glucose</td>\n",
-       "      <td>SDS</td>\n",
-       "      <td>Tris</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>603</th>\n",
-       "      <td>0.18</td>\n",
-       "      <td>41.95</td>\n",
-       "      <td>0.070</td>\n",
-       "      <td>13.93</td>\n",
-       "      <td>18.51</td>\n",
-       "      <td>7.10</td>\n",
-       "      <td>sucrose</td>\n",
-       "      <td>Tween20</td>\n",
-       "      <td>PBS</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>963</th>\n",
-       "      <td>0.45</td>\n",
-       "      <td>44.54</td>\n",
-       "      <td>0.196</td>\n",
-       "      <td>29.16</td>\n",
-       "      <td>37.43</td>\n",
-       "      <td>6.64</td>\n",
-       "      <td>sucrose</td>\n",
-       "      <td>TritonX</td>\n",
-       "      <td>Tris</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>756</th>\n",
-       "      <td>0.66</td>\n",
-       "      <td>96.36</td>\n",
-       "      <td>0.099</td>\n",
-       "      <td>9.23</td>\n",
-       "      <td>0.50</td>\n",
-       "      <td>6.13</td>\n",
-       "      <td>glucose</td>\n",
-       "      <td>TritonX</td>\n",
-       "      <td>PBS</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>534</th>\n",
-       "      <td>0.79</td>\n",
-       "      <td>47.22</td>\n",
-       "      <td>0.150</td>\n",
-       "      <td>11.63</td>\n",
-       "      <td>27.76</td>\n",
-       "      <td>7.96</td>\n",
-       "      <td>sucrose</td>\n",
-       "      <td>SDS</td>\n",
-       "      <td>HEPES</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>279</th>\n",
-       "      <td>0.82</td>\n",
-       "      <td>54.90</td>\n",
-       "      <td>0.023</td>\n",
-       "      <td>39.58</td>\n",
-       "      <td>19.59</td>\n",
-       "      <td>6.27</td>\n",
-       "      <td>fructose</td>\n",
-       "      <td>Tween20</td>\n",
-       "      <td>PBS</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "               reagent_conc  ionic_strength  surfactant_conc  compound_A  \\\n",
-       "FormulationID                                                              \n",
-       "326                    0.60           26.39            0.166       40.15   \n",
-       "251                    0.45           53.34            0.183        5.77   \n",
-       "81                     0.66           18.05            0.022       44.15   \n",
-       "83                     0.16           89.12            0.183       29.38   \n",
-       "687                    0.35           53.84            0.089       19.37   \n",
-       "603                    0.18           41.95            0.070       13.93   \n",
-       "963                    0.45           44.54            0.196       29.16   \n",
-       "756                    0.66           96.36            0.099        9.23   \n",
-       "534                    0.79           47.22            0.150       11.63   \n",
-       "279                    0.82           54.90            0.023       39.58   \n",
-       "\n",
-       "               compound_B    pH     sugar surfactant buffer  \n",
-       "FormulationID                                                \n",
-       "326                  1.10  6.39  fructose        SDS  HEPES  \n",
-       "251                  3.10  5.64   sucrose    TritonX  HEPES  \n",
-       "81                  11.67  7.53   glucose    TritonX  HEPES  \n",
-       "83                  37.35  5.89  fructose        SDS    PBS  \n",
-       "687                  0.54  8.11   glucose        SDS   Tris  \n",
-       "603                 18.51  7.10   sucrose    Tween20    PBS  \n",
-       "963                 37.43  6.64   sucrose    TritonX   Tris  \n",
-       "756                  0.50  6.13   glucose    TritonX    PBS  \n",
-       "534                 27.76  7.96   sucrose        SDS  HEPES  \n",
-       "279                 19.59  6.27  fructose    Tween20    PBS  "
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "#decode from one-hot encoding\n",
     "normal_cols = list(optimal_sample.columns)[0:6]\n",
@@ -1158,28 +151,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "2137e315",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1800x1000 with 9 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "None\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "print(designer.plot_histograms(optimal_design_decoded))"
    ]