example/thermodynamics/VLE/methane-water.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "%pip install neqsim\n",
    "\n",
    "#To check for methods in a Java object \n",
    "#from neqsim import methods"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Experimental data\n",
    "Experimental data from a number of sources was collected for the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>ID</th>\n",
       "      <th>ComponentSolute</th>\n",
       "      <th>ComponentSolvent</th>\n",
       "      <th>x1</th>\n",
       "      <th>StandardDeviation</th>\n",
       "      <th>x2</th>\n",
       "      <th>Pressure</th>\n",
       "      <th>VapourPressure2</th>\n",
       "      <th>Type</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>Reference</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>134</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.001560</td>\n",
       "      <td>1.000000e-01</td>\n",
       "      <td>0.998440</td>\n",
       "      <td>73.6</td>\n",
       "      <td>0</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Addicks2001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>135</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.002010</td>\n",
       "      <td>1.000000e-01</td>\n",
       "      <td>0.997990</td>\n",
       "      <td>102.2</td>\n",
       "      <td>0</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Addicks2001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>136</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.002400</td>\n",
       "      <td>1.000000e-01</td>\n",
       "      <td>0.997600</td>\n",
       "      <td>139.2</td>\n",
       "      <td>0</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Addicks2001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>137</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.002740</td>\n",
       "      <td>1.000000e-01</td>\n",
       "      <td>0.997260</td>\n",
       "      <td>178.2</td>\n",
       "      <td>0</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Addicks2001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>150</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000033</td>\n",
       "      <td>3.320000e-07</td>\n",
       "      <td>0.999967</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>VLE</td>\n",
       "      <td>283.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>151</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000026</td>\n",
       "      <td>2.620000e-07</td>\n",
       "      <td>0.999974</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>152</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000022</td>\n",
       "      <td>2.200000e-07</td>\n",
       "      <td>0.999978</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>VLE</td>\n",
       "      <td>303.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>153</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000019</td>\n",
       "      <td>1.900000e-07</td>\n",
       "      <td>0.999981</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>VLE</td>\n",
       "      <td>313.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>154</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000017</td>\n",
       "      <td>1.710000e-07</td>\n",
       "      <td>0.999983</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>VLE</td>\n",
       "      <td>323.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>155</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>1.580000e-07</td>\n",
       "      <td>0.999984</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>VLE</td>\n",
       "      <td>333.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>156</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>1.480000e-07</td>\n",
       "      <td>0.999985</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>VLE</td>\n",
       "      <td>343.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>157</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000066</td>\n",
       "      <td>6.650000e-07</td>\n",
       "      <td>0.999934</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>VLE</td>\n",
       "      <td>283.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>158</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000052</td>\n",
       "      <td>5.250000e-07</td>\n",
       "      <td>0.999948</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>159</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000044</td>\n",
       "      <td>4.400000e-07</td>\n",
       "      <td>0.999956</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>VLE</td>\n",
       "      <td>303.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>160</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000038</td>\n",
       "      <td>3.800000e-07</td>\n",
       "      <td>0.999962</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>VLE</td>\n",
       "      <td>313.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>161</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000034</td>\n",
       "      <td>3.420000e-07</td>\n",
       "      <td>0.999966</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>VLE</td>\n",
       "      <td>323.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>162</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000032</td>\n",
       "      <td>3.150000e-07</td>\n",
       "      <td>0.999968</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>VLE</td>\n",
       "      <td>333.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>163</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>2.960000e-07</td>\n",
       "      <td>0.999970</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>VLE</td>\n",
       "      <td>343.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>164</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000166</td>\n",
       "      <td>1.661000e-06</td>\n",
       "      <td>0.999834</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>VLE</td>\n",
       "      <td>283.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>165</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000131</td>\n",
       "      <td>1.312000e-06</td>\n",
       "      <td>0.999869</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>166</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000110</td>\n",
       "      <td>1.099000e-06</td>\n",
       "      <td>0.999890</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>VLE</td>\n",
       "      <td>303.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>167</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>9.490000e-07</td>\n",
       "      <td>0.999905</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>VLE</td>\n",
       "      <td>313.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>168</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000086</td>\n",
       "      <td>8.550000e-07</td>\n",
       "      <td>0.999914</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>VLE</td>\n",
       "      <td>323.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>169</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000079</td>\n",
       "      <td>7.880000e-07</td>\n",
       "      <td>0.999921</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>VLE</td>\n",
       "      <td>333.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>170</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000074</td>\n",
       "      <td>7.410000e-07</td>\n",
       "      <td>0.999926</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>VLE</td>\n",
       "      <td>343.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>171</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000332</td>\n",
       "      <td>3.323000e-06</td>\n",
       "      <td>0.999668</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>VLE</td>\n",
       "      <td>283.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>172</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000262</td>\n",
       "      <td>2.625000e-06</td>\n",
       "      <td>0.999738</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>173</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000220</td>\n",
       "      <td>2.198000e-06</td>\n",
       "      <td>0.999780</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>VLE</td>\n",
       "      <td>303.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>174</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000190</td>\n",
       "      <td>1.898000e-06</td>\n",
       "      <td>0.999810</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>VLE</td>\n",
       "      <td>313.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>175</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000171</td>\n",
       "      <td>1.710000e-06</td>\n",
       "      <td>0.999829</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>VLE</td>\n",
       "      <td>323.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>176</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000158</td>\n",
       "      <td>1.577000e-06</td>\n",
       "      <td>0.999842</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>VLE</td>\n",
       "      <td>333.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>177</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000148</td>\n",
       "      <td>1.482000e-06</td>\n",
       "      <td>0.999852</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>VLE</td>\n",
       "      <td>343.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>178</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000665</td>\n",
       "      <td>6.646000e-06</td>\n",
       "      <td>0.999335</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20</td>\n",
       "      <td>VLE</td>\n",
       "      <td>283.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>179</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000525</td>\n",
       "      <td>5.250000e-06</td>\n",
       "      <td>0.999475</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>180</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000440</td>\n",
       "      <td>4.396000e-06</td>\n",
       "      <td>0.999560</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20</td>\n",
       "      <td>VLE</td>\n",
       "      <td>303.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>181</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000380</td>\n",
       "      <td>3.796000e-06</td>\n",
       "      <td>0.999620</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20</td>\n",
       "      <td>VLE</td>\n",
       "      <td>313.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>182</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000342</td>\n",
       "      <td>3.421000e-06</td>\n",
       "      <td>0.999658</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20</td>\n",
       "      <td>VLE</td>\n",
       "      <td>323.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>183</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000315</td>\n",
       "      <td>3.153000e-06</td>\n",
       "      <td>0.999685</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20</td>\n",
       "      <td>VLE</td>\n",
       "      <td>333.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>184</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000296</td>\n",
       "      <td>2.964000e-06</td>\n",
       "      <td>0.999704</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20</td>\n",
       "      <td>VLE</td>\n",
       "      <td>343.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>185</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.001661</td>\n",
       "      <td>1.661500e-05</td>\n",
       "      <td>0.998339</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50</td>\n",
       "      <td>VLE</td>\n",
       "      <td>283.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>186</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.001312</td>\n",
       "      <td>1.312400e-05</td>\n",
       "      <td>0.998688</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>187</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.001099</td>\n",
       "      <td>1.099000e-05</td>\n",
       "      <td>0.998901</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50</td>\n",
       "      <td>VLE</td>\n",
       "      <td>303.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>188</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000949</td>\n",
       "      <td>9.490000e-06</td>\n",
       "      <td>0.999051</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50</td>\n",
       "      <td>VLE</td>\n",
       "      <td>313.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>189</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000855</td>\n",
       "      <td>8.552000e-06</td>\n",
       "      <td>0.999145</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50</td>\n",
       "      <td>VLE</td>\n",
       "      <td>323.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>190</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000788</td>\n",
       "      <td>7.883000e-06</td>\n",
       "      <td>0.999212</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50</td>\n",
       "      <td>VLE</td>\n",
       "      <td>333.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>191</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000741</td>\n",
       "      <td>7.409000e-06</td>\n",
       "      <td>0.999259</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50</td>\n",
       "      <td>VLE</td>\n",
       "      <td>343.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>192</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.003323</td>\n",
       "      <td>3.323000e-05</td>\n",
       "      <td>0.996677</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100</td>\n",
       "      <td>VLE</td>\n",
       "      <td>283.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>193</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.002625</td>\n",
       "      <td>2.624800e-05</td>\n",
       "      <td>0.997375</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>194</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.002198</td>\n",
       "      <td>2.198000e-05</td>\n",
       "      <td>0.997802</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100</td>\n",
       "      <td>VLE</td>\n",
       "      <td>303.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>195</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.001898</td>\n",
       "      <td>1.897900e-05</td>\n",
       "      <td>0.998102</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100</td>\n",
       "      <td>VLE</td>\n",
       "      <td>313.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>196</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.001710</td>\n",
       "      <td>1.710400e-05</td>\n",
       "      <td>0.998290</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100</td>\n",
       "      <td>VLE</td>\n",
       "      <td>323.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>197</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.001577</td>\n",
       "      <td>1.576600e-05</td>\n",
       "      <td>0.998423</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100</td>\n",
       "      <td>VLE</td>\n",
       "      <td>333.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>198</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.001482</td>\n",
       "      <td>1.481900e-05</td>\n",
       "      <td>0.998518</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100</td>\n",
       "      <td>VLE</td>\n",
       "      <td>343.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     ID ComponentSolute ComponentSolvent        x1  StandardDeviation  \\\n",
       "0   134         methane            water  0.001560       1.000000e-01   \n",
       "1   135         methane            water  0.002010       1.000000e-01   \n",
       "2   136         methane            water  0.002400       1.000000e-01   \n",
       "3   137         methane            water  0.002740       1.000000e-01   \n",
       "4   150         methane            water  0.000033       3.320000e-07   \n",
       "5   151         methane            water  0.000026       2.620000e-07   \n",
       "6   152         methane            water  0.000022       2.200000e-07   \n",
       "7   153         methane            water  0.000019       1.900000e-07   \n",
       "8   154         methane            water  0.000017       1.710000e-07   \n",
       "9   155         methane            water  0.000016       1.580000e-07   \n",
       "10  156         methane            water  0.000015       1.480000e-07   \n",
       "11  157         methane            water  0.000066       6.650000e-07   \n",
       "12  158         methane            water  0.000052       5.250000e-07   \n",
       "13  159         methane            water  0.000044       4.400000e-07   \n",
       "14  160         methane            water  0.000038       3.800000e-07   \n",
       "15  161         methane            water  0.000034       3.420000e-07   \n",
       "16  162         methane            water  0.000032       3.150000e-07   \n",
       "17  163         methane            water  0.000030       2.960000e-07   \n",
       "18  164         methane            water  0.000166       1.661000e-06   \n",
       "19  165         methane            water  0.000131       1.312000e-06   \n",
       "20  166         methane            water  0.000110       1.099000e-06   \n",
       "21  167         methane            water  0.000095       9.490000e-07   \n",
       "22  168         methane            water  0.000086       8.550000e-07   \n",
       "23  169         methane            water  0.000079       7.880000e-07   \n",
       "24  170         methane            water  0.000074       7.410000e-07   \n",
       "25  171         methane            water  0.000332       3.323000e-06   \n",
       "26  172         methane            water  0.000262       2.625000e-06   \n",
       "27  173         methane            water  0.000220       2.198000e-06   \n",
       "28  174         methane            water  0.000190       1.898000e-06   \n",
       "29  175         methane            water  0.000171       1.710000e-06   \n",
       "30  176         methane            water  0.000158       1.577000e-06   \n",
       "31  177         methane            water  0.000148       1.482000e-06   \n",
       "32  178         methane            water  0.000665       6.646000e-06   \n",
       "33  179         methane            water  0.000525       5.250000e-06   \n",
       "34  180         methane            water  0.000440       4.396000e-06   \n",
       "35  181         methane            water  0.000380       3.796000e-06   \n",
       "36  182         methane            water  0.000342       3.421000e-06   \n",
       "37  183         methane            water  0.000315       3.153000e-06   \n",
       "38  184         methane            water  0.000296       2.964000e-06   \n",
       "39  185         methane            water  0.001661       1.661500e-05   \n",
       "40  186         methane            water  0.001312       1.312400e-05   \n",
       "41  187         methane            water  0.001099       1.099000e-05   \n",
       "42  188         methane            water  0.000949       9.490000e-06   \n",
       "43  189         methane            water  0.000855       8.552000e-06   \n",
       "44  190         methane            water  0.000788       7.883000e-06   \n",
       "45  191         methane            water  0.000741       7.409000e-06   \n",
       "46  192         methane            water  0.003323       3.323000e-05   \n",
       "47  193         methane            water  0.002625       2.624800e-05   \n",
       "48  194         methane            water  0.002198       2.198000e-05   \n",
       "49  195         methane            water  0.001898       1.897900e-05   \n",
       "50  196         methane            water  0.001710       1.710400e-05   \n",
       "51  197         methane            water  0.001577       1.576600e-05   \n",
       "52  198         methane            water  0.001482       1.481900e-05   \n",
       "\n",
       "          x2  Pressure  VapourPressure2 Type  Temperature    Reference  \n",
       "0   0.998440      73.6                0  VLE       293.15  Addicks2001  \n",
       "1   0.997990     102.2                0  VLE       293.15  Addicks2001  \n",
       "2   0.997600     139.2                0  VLE       293.15  Addicks2001  \n",
       "3   0.997260     178.2                0  VLE       293.15  Addicks2001  \n",
       "4   0.999967       1.0                1  VLE       283.15    Perry1998  \n",
       "5   0.999974       1.0                1  VLE       293.15    Perry1998  \n",
       "6   0.999978       1.0                1  VLE       303.15    Perry1998  \n",
       "7   0.999981       1.0                1  VLE       313.15    Perry1998  \n",
       "8   0.999983       1.0                1  VLE       323.15    Perry1998  \n",
       "9   0.999984       1.0                1  VLE       333.15    Perry1998  \n",
       "10  0.999985       1.0                1  VLE       343.15    Perry1998  \n",
       "11  0.999934       2.0                2  VLE       283.15    Perry1998  \n",
       "12  0.999948       2.0                2  VLE       293.15    Perry1998  \n",
       "13  0.999956       2.0                2  VLE       303.15    Perry1998  \n",
       "14  0.999962       2.0                2  VLE       313.15    Perry1998  \n",
       "15  0.999966       2.0                2  VLE       323.15    Perry1998  \n",
       "16  0.999968       2.0                2  VLE       333.15    Perry1998  \n",
       "17  0.999970       2.0                2  VLE       343.15    Perry1998  \n",
       "18  0.999834       5.0                5  VLE       283.15    Perry1998  \n",
       "19  0.999869       5.0                5  VLE       293.15    Perry1998  \n",
       "20  0.999890       5.0                5  VLE       303.15    Perry1998  \n",
       "21  0.999905       5.0                5  VLE       313.15    Perry1998  \n",
       "22  0.999914       5.0                5  VLE       323.15    Perry1998  \n",
       "23  0.999921       5.0                5  VLE       333.15    Perry1998  \n",
       "24  0.999926       5.0                5  VLE       343.15    Perry1998  \n",
       "25  0.999668      10.0               10  VLE       283.15    Perry1998  \n",
       "26  0.999738      10.0               10  VLE       293.15    Perry1998  \n",
       "27  0.999780      10.0               10  VLE       303.15    Perry1998  \n",
       "28  0.999810      10.0               10  VLE       313.15    Perry1998  \n",
       "29  0.999829      10.0               10  VLE       323.15    Perry1998  \n",
       "30  0.999842      10.0               10  VLE       333.15    Perry1998  \n",
       "31  0.999852      10.0               10  VLE       343.15    Perry1998  \n",
       "32  0.999335      20.0               20  VLE       283.15    Perry1998  \n",
       "33  0.999475      20.0               20  VLE       293.15    Perry1998  \n",
       "34  0.999560      20.0               20  VLE       303.15    Perry1998  \n",
       "35  0.999620      20.0               20  VLE       313.15    Perry1998  \n",
       "36  0.999658      20.0               20  VLE       323.15    Perry1998  \n",
       "37  0.999685      20.0               20  VLE       333.15    Perry1998  \n",
       "38  0.999704      20.0               20  VLE       343.15    Perry1998  \n",
       "39  0.998339      50.0               50  VLE       283.15    Perry1998  \n",
       "40  0.998688      50.0               50  VLE       293.15    Perry1998  \n",
       "41  0.998901      50.0               50  VLE       303.15    Perry1998  \n",
       "42  0.999051      50.0               50  VLE       313.15    Perry1998  \n",
       "43  0.999145      50.0               50  VLE       323.15    Perry1998  \n",
       "44  0.999212      50.0               50  VLE       333.15    Perry1998  \n",
       "45  0.999259      50.0               50  VLE       343.15    Perry1998  \n",
       "46  0.996677     100.0              100  VLE       283.15    Perry1998  \n",
       "47  0.997375     100.0              100  VLE       293.15    Perry1998  \n",
       "48  0.997802     100.0              100  VLE       303.15    Perry1998  \n",
       "49  0.998102     100.0              100  VLE       313.15    Perry1998  \n",
       "50  0.998290     100.0              100  VLE       323.15    Perry1998  \n",
       "51  0.998423     100.0              100  VLE       333.15    Perry1998  \n",
       "52  0.998518     100.0              100  VLE       343.15    Perry1998  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "expdata_df = pd.read_csv('../../../data/thermodynamics/VLE/methane-water.csv')\n",
    "expdata_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "references  ['Addicks2001', 'Perry1998']\n",
      "temperature  [293.15, 283.15, 303.15, 313.15, 323.15, 333.15, 343.15]\n",
      "numer of data points for each temperature:\n",
      "Temperature\n",
      "283.15     7\n",
      "293.15    11\n",
      "303.15     7\n",
      "313.15     7\n",
      "323.15     7\n",
      "333.15     7\n",
      "343.15     7\n",
      "Name: Pressure, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "referenceList = expdata_df['Reference'].unique().tolist()\n",
    "temperatureList = expdata_df['Temperature'].unique().tolist()\n",
    "data = expdata_df.groupby(['Temperature'])['Pressure'].count()\n",
    "print('references ', referenceList)\n",
    "print('temperature ', temperatureList)\n",
    "print('numer of data points for each temperature:')\n",
    "print(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "fig = plt.figure()\n",
    "\n",
    "data283 = expdata_df.loc[expdata_df['Temperature'] == 283.15]\n",
    "plot1 = data283.plot(x='x1', y='Pressure', kind='scatter',ylabel='Pressure(bara)', xlabel='x_CO2[mol/mol]',color='red')\n",
    "\n",
    "data288 = expdata_df.loc[expdata_df['Temperature'] == 293.15]\n",
    "data288.plot(ax=plot1, x='x1', y='Pressure', kind='scatter',ylabel='Pressure(bara)', xlabel='x_CO2[mol/mol]',color='blue')\n",
    "\n",
    "data323 = expdata_df.loc[expdata_df['Temperature'] == 303.15]\n",
    "data323.plot(ax=plot1, x='x1', y='Pressure', kind='scatter',ylabel='Pressure(bara)', xlabel='x_CO2[mol/mol]',color='yellow')\n",
    "\n",
    "data373 = expdata_df.loc[expdata_df['Temperature'] == 343.15]\n",
    "data373.plot(ax=plot1, x='x1', y='Pressure', kind='scatter',ylabel='Pressure(bara)', xlabel='x_CO2[mol/mol]',color='black')\t\t\t\n",
    "\n",
    "plt.legend(['283.15', '288.15', '303.15', '343.15'])\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Evaluation of experimental data\n",
    "\n",
    "In this section the experimental data will be evaluated and eventual some data sets will be removed from the set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>ID</th>\n",
       "      <th>ComponentSolute</th>\n",
       "      <th>ComponentSolvent</th>\n",
       "      <th>x1</th>\n",
       "      <th>StandardDeviation</th>\n",
       "      <th>x2</th>\n",
       "      <th>Pressure</th>\n",
       "      <th>VapourPressure2</th>\n",
       "      <th>Type</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>Reference</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>134</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.001560</td>\n",
       "      <td>1.000000e-01</td>\n",
       "      <td>0.998440</td>\n",
       "      <td>73.6</td>\n",
       "      <td>0</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Addicks2001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>135</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.002010</td>\n",
       "      <td>1.000000e-01</td>\n",
       "      <td>0.997990</td>\n",
       "      <td>102.2</td>\n",
       "      <td>0</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Addicks2001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>136</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.002400</td>\n",
       "      <td>1.000000e-01</td>\n",
       "      <td>0.997600</td>\n",
       "      <td>139.2</td>\n",
       "      <td>0</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Addicks2001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>137</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.002740</td>\n",
       "      <td>1.000000e-01</td>\n",
       "      <td>0.997260</td>\n",
       "      <td>178.2</td>\n",
       "      <td>0</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Addicks2001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>150</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000033</td>\n",
       "      <td>3.320000e-07</td>\n",
       "      <td>0.999967</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>VLE</td>\n",
       "      <td>283.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>151</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000026</td>\n",
       "      <td>2.620000e-07</td>\n",
       "      <td>0.999974</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>152</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000022</td>\n",
       "      <td>2.200000e-07</td>\n",
       "      <td>0.999978</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>VLE</td>\n",
       "      <td>303.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>153</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000019</td>\n",
       "      <td>1.900000e-07</td>\n",
       "      <td>0.999981</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>VLE</td>\n",
       "      <td>313.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>154</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000017</td>\n",
       "      <td>1.710000e-07</td>\n",
       "      <td>0.999983</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>VLE</td>\n",
       "      <td>323.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>155</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>1.580000e-07</td>\n",
       "      <td>0.999984</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>VLE</td>\n",
       "      <td>333.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>156</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>1.480000e-07</td>\n",
       "      <td>0.999985</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>VLE</td>\n",
       "      <td>343.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>157</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000066</td>\n",
       "      <td>6.650000e-07</td>\n",
       "      <td>0.999934</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>VLE</td>\n",
       "      <td>283.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>158</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000052</td>\n",
       "      <td>5.250000e-07</td>\n",
       "      <td>0.999948</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>159</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000044</td>\n",
       "      <td>4.400000e-07</td>\n",
       "      <td>0.999956</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>VLE</td>\n",
       "      <td>303.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>160</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000038</td>\n",
       "      <td>3.800000e-07</td>\n",
       "      <td>0.999962</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>VLE</td>\n",
       "      <td>313.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>161</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000034</td>\n",
       "      <td>3.420000e-07</td>\n",
       "      <td>0.999966</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>VLE</td>\n",
       "      <td>323.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>162</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000032</td>\n",
       "      <td>3.150000e-07</td>\n",
       "      <td>0.999968</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>VLE</td>\n",
       "      <td>333.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>163</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>2.960000e-07</td>\n",
       "      <td>0.999970</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>VLE</td>\n",
       "      <td>343.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>164</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000166</td>\n",
       "      <td>1.661000e-06</td>\n",
       "      <td>0.999834</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>VLE</td>\n",
       "      <td>283.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>165</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000131</td>\n",
       "      <td>1.312000e-06</td>\n",
       "      <td>0.999869</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>166</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000110</td>\n",
       "      <td>1.099000e-06</td>\n",
       "      <td>0.999890</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>VLE</td>\n",
       "      <td>303.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>167</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>9.490000e-07</td>\n",
       "      <td>0.999905</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>VLE</td>\n",
       "      <td>313.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>168</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000086</td>\n",
       "      <td>8.550000e-07</td>\n",
       "      <td>0.999914</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>VLE</td>\n",
       "      <td>323.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>169</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000079</td>\n",
       "      <td>7.880000e-07</td>\n",
       "      <td>0.999921</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>VLE</td>\n",
       "      <td>333.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>170</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000074</td>\n",
       "      <td>7.410000e-07</td>\n",
       "      <td>0.999926</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>VLE</td>\n",
       "      <td>343.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>171</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000332</td>\n",
       "      <td>3.323000e-06</td>\n",
       "      <td>0.999668</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>VLE</td>\n",
       "      <td>283.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>172</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000262</td>\n",
       "      <td>2.625000e-06</td>\n",
       "      <td>0.999738</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>173</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000220</td>\n",
       "      <td>2.198000e-06</td>\n",
       "      <td>0.999780</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>VLE</td>\n",
       "      <td>303.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>174</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000190</td>\n",
       "      <td>1.898000e-06</td>\n",
       "      <td>0.999810</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>VLE</td>\n",
       "      <td>313.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>175</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000171</td>\n",
       "      <td>1.710000e-06</td>\n",
       "      <td>0.999829</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>VLE</td>\n",
       "      <td>323.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>176</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000158</td>\n",
       "      <td>1.577000e-06</td>\n",
       "      <td>0.999842</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>VLE</td>\n",
       "      <td>333.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>177</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000148</td>\n",
       "      <td>1.482000e-06</td>\n",
       "      <td>0.999852</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>VLE</td>\n",
       "      <td>343.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>178</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000665</td>\n",
       "      <td>6.646000e-06</td>\n",
       "      <td>0.999335</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20</td>\n",
       "      <td>VLE</td>\n",
       "      <td>283.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>179</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000525</td>\n",
       "      <td>5.250000e-06</td>\n",
       "      <td>0.999475</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>180</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000440</td>\n",
       "      <td>4.396000e-06</td>\n",
       "      <td>0.999560</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20</td>\n",
       "      <td>VLE</td>\n",
       "      <td>303.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>181</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000380</td>\n",
       "      <td>3.796000e-06</td>\n",
       "      <td>0.999620</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20</td>\n",
       "      <td>VLE</td>\n",
       "      <td>313.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>182</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000342</td>\n",
       "      <td>3.421000e-06</td>\n",
       "      <td>0.999658</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20</td>\n",
       "      <td>VLE</td>\n",
       "      <td>323.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>183</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000315</td>\n",
       "      <td>3.153000e-06</td>\n",
       "      <td>0.999685</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20</td>\n",
       "      <td>VLE</td>\n",
       "      <td>333.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>184</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000296</td>\n",
       "      <td>2.964000e-06</td>\n",
       "      <td>0.999704</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20</td>\n",
       "      <td>VLE</td>\n",
       "      <td>343.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>185</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.001661</td>\n",
       "      <td>1.661500e-05</td>\n",
       "      <td>0.998339</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50</td>\n",
       "      <td>VLE</td>\n",
       "      <td>283.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>186</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.001312</td>\n",
       "      <td>1.312400e-05</td>\n",
       "      <td>0.998688</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>187</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.001099</td>\n",
       "      <td>1.099000e-05</td>\n",
       "      <td>0.998901</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50</td>\n",
       "      <td>VLE</td>\n",
       "      <td>303.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>188</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000949</td>\n",
       "      <td>9.490000e-06</td>\n",
       "      <td>0.999051</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50</td>\n",
       "      <td>VLE</td>\n",
       "      <td>313.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>189</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000855</td>\n",
       "      <td>8.552000e-06</td>\n",
       "      <td>0.999145</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50</td>\n",
       "      <td>VLE</td>\n",
       "      <td>323.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>190</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000788</td>\n",
       "      <td>7.883000e-06</td>\n",
       "      <td>0.999212</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50</td>\n",
       "      <td>VLE</td>\n",
       "      <td>333.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>191</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.000741</td>\n",
       "      <td>7.409000e-06</td>\n",
       "      <td>0.999259</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50</td>\n",
       "      <td>VLE</td>\n",
       "      <td>343.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>192</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.003323</td>\n",
       "      <td>3.323000e-05</td>\n",
       "      <td>0.996677</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100</td>\n",
       "      <td>VLE</td>\n",
       "      <td>283.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>193</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.002625</td>\n",
       "      <td>2.624800e-05</td>\n",
       "      <td>0.997375</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100</td>\n",
       "      <td>VLE</td>\n",
       "      <td>293.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>194</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.002198</td>\n",
       "      <td>2.198000e-05</td>\n",
       "      <td>0.997802</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100</td>\n",
       "      <td>VLE</td>\n",
       "      <td>303.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>195</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.001898</td>\n",
       "      <td>1.897900e-05</td>\n",
       "      <td>0.998102</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100</td>\n",
       "      <td>VLE</td>\n",
       "      <td>313.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>196</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.001710</td>\n",
       "      <td>1.710400e-05</td>\n",
       "      <td>0.998290</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100</td>\n",
       "      <td>VLE</td>\n",
       "      <td>323.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>197</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.001577</td>\n",
       "      <td>1.576600e-05</td>\n",
       "      <td>0.998423</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100</td>\n",
       "      <td>VLE</td>\n",
       "      <td>333.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>198</td>\n",
       "      <td>methane</td>\n",
       "      <td>water</td>\n",
       "      <td>0.001482</td>\n",
       "      <td>1.481900e-05</td>\n",
       "      <td>0.998518</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100</td>\n",
       "      <td>VLE</td>\n",
       "      <td>343.15</td>\n",
       "      <td>Perry1998</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     ID ComponentSolute ComponentSolvent        x1  StandardDeviation  \\\n",
       "0   134         methane            water  0.001560       1.000000e-01   \n",
       "1   135         methane            water  0.002010       1.000000e-01   \n",
       "2   136         methane            water  0.002400       1.000000e-01   \n",
       "3   137         methane            water  0.002740       1.000000e-01   \n",
       "4   150         methane            water  0.000033       3.320000e-07   \n",
       "5   151         methane            water  0.000026       2.620000e-07   \n",
       "6   152         methane            water  0.000022       2.200000e-07   \n",
       "7   153         methane            water  0.000019       1.900000e-07   \n",
       "8   154         methane            water  0.000017       1.710000e-07   \n",
       "9   155         methane            water  0.000016       1.580000e-07   \n",
       "10  156         methane            water  0.000015       1.480000e-07   \n",
       "11  157         methane            water  0.000066       6.650000e-07   \n",
       "12  158         methane            water  0.000052       5.250000e-07   \n",
       "13  159         methane            water  0.000044       4.400000e-07   \n",
       "14  160         methane            water  0.000038       3.800000e-07   \n",
       "15  161         methane            water  0.000034       3.420000e-07   \n",
       "16  162         methane            water  0.000032       3.150000e-07   \n",
       "17  163         methane            water  0.000030       2.960000e-07   \n",
       "18  164         methane            water  0.000166       1.661000e-06   \n",
       "19  165         methane            water  0.000131       1.312000e-06   \n",
       "20  166         methane            water  0.000110       1.099000e-06   \n",
       "21  167         methane            water  0.000095       9.490000e-07   \n",
       "22  168         methane            water  0.000086       8.550000e-07   \n",
       "23  169         methane            water  0.000079       7.880000e-07   \n",
       "24  170         methane            water  0.000074       7.410000e-07   \n",
       "25  171         methane            water  0.000332       3.323000e-06   \n",
       "26  172         methane            water  0.000262       2.625000e-06   \n",
       "27  173         methane            water  0.000220       2.198000e-06   \n",
       "28  174         methane            water  0.000190       1.898000e-06   \n",
       "29  175         methane            water  0.000171       1.710000e-06   \n",
       "30  176         methane            water  0.000158       1.577000e-06   \n",
       "31  177         methane            water  0.000148       1.482000e-06   \n",
       "32  178         methane            water  0.000665       6.646000e-06   \n",
       "33  179         methane            water  0.000525       5.250000e-06   \n",
       "34  180         methane            water  0.000440       4.396000e-06   \n",
       "35  181         methane            water  0.000380       3.796000e-06   \n",
       "36  182         methane            water  0.000342       3.421000e-06   \n",
       "37  183         methane            water  0.000315       3.153000e-06   \n",
       "38  184         methane            water  0.000296       2.964000e-06   \n",
       "39  185         methane            water  0.001661       1.661500e-05   \n",
       "40  186         methane            water  0.001312       1.312400e-05   \n",
       "41  187         methane            water  0.001099       1.099000e-05   \n",
       "42  188         methane            water  0.000949       9.490000e-06   \n",
       "43  189         methane            water  0.000855       8.552000e-06   \n",
       "44  190         methane            water  0.000788       7.883000e-06   \n",
       "45  191         methane            water  0.000741       7.409000e-06   \n",
       "46  192         methane            water  0.003323       3.323000e-05   \n",
       "47  193         methane            water  0.002625       2.624800e-05   \n",
       "48  194         methane            water  0.002198       2.198000e-05   \n",
       "49  195         methane            water  0.001898       1.897900e-05   \n",
       "50  196         methane            water  0.001710       1.710400e-05   \n",
       "51  197         methane            water  0.001577       1.576600e-05   \n",
       "52  198         methane            water  0.001482       1.481900e-05   \n",
       "\n",
       "          x2  Pressure  VapourPressure2 Type  Temperature    Reference  \n",
       "0   0.998440      73.6                0  VLE       293.15  Addicks2001  \n",
       "1   0.997990     102.2                0  VLE       293.15  Addicks2001  \n",
       "2   0.997600     139.2                0  VLE       293.15  Addicks2001  \n",
       "3   0.997260     178.2                0  VLE       293.15  Addicks2001  \n",
       "4   0.999967       1.0                1  VLE       283.15    Perry1998  \n",
       "5   0.999974       1.0                1  VLE       293.15    Perry1998  \n",
       "6   0.999978       1.0                1  VLE       303.15    Perry1998  \n",
       "7   0.999981       1.0                1  VLE       313.15    Perry1998  \n",
       "8   0.999983       1.0                1  VLE       323.15    Perry1998  \n",
       "9   0.999984       1.0                1  VLE       333.15    Perry1998  \n",
       "10  0.999985       1.0                1  VLE       343.15    Perry1998  \n",
       "11  0.999934       2.0                2  VLE       283.15    Perry1998  \n",
       "12  0.999948       2.0                2  VLE       293.15    Perry1998  \n",
       "13  0.999956       2.0                2  VLE       303.15    Perry1998  \n",
       "14  0.999962       2.0                2  VLE       313.15    Perry1998  \n",
       "15  0.999966       2.0                2  VLE       323.15    Perry1998  \n",
       "16  0.999968       2.0                2  VLE       333.15    Perry1998  \n",
       "17  0.999970       2.0                2  VLE       343.15    Perry1998  \n",
       "18  0.999834       5.0                5  VLE       283.15    Perry1998  \n",
       "19  0.999869       5.0                5  VLE       293.15    Perry1998  \n",
       "20  0.999890       5.0                5  VLE       303.15    Perry1998  \n",
       "21  0.999905       5.0                5  VLE       313.15    Perry1998  \n",
       "22  0.999914       5.0                5  VLE       323.15    Perry1998  \n",
       "23  0.999921       5.0                5  VLE       333.15    Perry1998  \n",
       "24  0.999926       5.0                5  VLE       343.15    Perry1998  \n",
       "25  0.999668      10.0               10  VLE       283.15    Perry1998  \n",
       "26  0.999738      10.0               10  VLE       293.15    Perry1998  \n",
       "27  0.999780      10.0               10  VLE       303.15    Perry1998  \n",
       "28  0.999810      10.0               10  VLE       313.15    Perry1998  \n",
       "29  0.999829      10.0               10  VLE       323.15    Perry1998  \n",
       "30  0.999842      10.0               10  VLE       333.15    Perry1998  \n",
       "31  0.999852      10.0               10  VLE       343.15    Perry1998  \n",
       "32  0.999335      20.0               20  VLE       283.15    Perry1998  \n",
       "33  0.999475      20.0               20  VLE       293.15    Perry1998  \n",
       "34  0.999560      20.0               20  VLE       303.15    Perry1998  \n",
       "35  0.999620      20.0               20  VLE       313.15    Perry1998  \n",
       "36  0.999658      20.0               20  VLE       323.15    Perry1998  \n",
       "37  0.999685      20.0               20  VLE       333.15    Perry1998  \n",
       "38  0.999704      20.0               20  VLE       343.15    Perry1998  \n",
       "39  0.998339      50.0               50  VLE       283.15    Perry1998  \n",
       "40  0.998688      50.0               50  VLE       293.15    Perry1998  \n",
       "41  0.998901      50.0               50  VLE       303.15    Perry1998  \n",
       "42  0.999051      50.0               50  VLE       313.15    Perry1998  \n",
       "43  0.999145      50.0               50  VLE       323.15    Perry1998  \n",
       "44  0.999212      50.0               50  VLE       333.15    Perry1998  \n",
       "45  0.999259      50.0               50  VLE       343.15    Perry1998  \n",
       "46  0.996677     100.0              100  VLE       283.15    Perry1998  \n",
       "47  0.997375     100.0              100  VLE       293.15    Perry1998  \n",
       "48  0.997802     100.0              100  VLE       303.15    Perry1998  \n",
       "49  0.998102     100.0              100  VLE       313.15    Perry1998  \n",
       "50  0.998290     100.0              100  VLE       323.15    Perry1998  \n",
       "51  0.998423     100.0              100  VLE       333.15    Perry1998  \n",
       "52  0.998518     100.0              100  VLE       343.15    Perry1998  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The data set of Nighswander1989 will be removed\n",
    "expdata_df_update = expdata_df.loc[expdata_df['Reference'] != 'Nighswander1989']\n",
    "expdata_df_update"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Compare to NeqSim Calculations"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## NeqSim calculations at 288.15 K"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import neqsim\n",
    "from neqsim.thermo.thermoTools import fluid, TPflash, fluidComposition,bubp\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# Creating a fluid in neqsim\n",
    "fluid1 = fluid('cpa') #create a fluid using the SRK-EoS\n",
    "fluid1.addComponent('methane', 1.0)\n",
    "fluid1.addComponent(\"water\", 1.0) \n",
    "fluid1.autoSelectMixingRule()\n",
    "fluid1.setTemperature(15.0, 'C')\n",
    "\n",
    "def solubility(pres):\n",
    "    fluid1.setPressure(pres, 'bara')\n",
    "    TPflash(fluid1)\n",
    "    return fluid1.getPhase('aqueous').getComponent('methane').getx()\n",
    "\n",
    "pressures = data283['Pressure'].values.tolist()\n",
    "x_res = [solubility(P) for P in pressures]\n",
    "\n",
    "dataWithExperiment = data283.assign(x_CPA = x_res)\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "fig = plt.figure()\t\n",
    "plot1 = data283.plot(x='x1', y='Pressure', kind='scatter',ylabel='Pressure(bara)', xlabel='x_methane[mol/mol]',color='black')\t\n",
    "dataWithExperiment.plot(ax=plot1, x='x_CPA', y='Pressure', kind='scatter',ylabel='Pressure(bara)', xlabel='x_methane[mol/mol]',color='blue')\t\n",
    "plt.legend(['10C', 'CPA'])\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Check to all data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "median average deviation  7.246513870606801\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_2035/200205163.py:29: FutureWarning: The 'mad' method is deprecated and will be removed in a future version. To compute the same result, you may do `(df - df.mean()).abs().mean()`.\n",
      "  print('median average deviation ', devdf.mad(axis=0))\n"
     ]
    }
   ],
   "source": [
    "import neqsim\n",
    "from neqsim.thermo.thermoTools import fluid, TPflash, fluidComposition,bubp\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "fluid1 = fluid('cpa')\n",
    "fluid1.addComponent('methane', 1.0)\n",
    "fluid1.addComponent(\"water\", 1.0) \n",
    "fluid1.autoSelectMixingRule()\n",
    "fluid1.setTemperature(15.0, 'C')\n",
    "\n",
    "def solubility(inp):\n",
    "    fluid1.setPressure(inp[2], 'bara')\n",
    "    fluid1.setTemperature(inp[1], 'K')\n",
    "    try:\n",
    "        TPflash(fluid1)\n",
    "        return fluid1.getPhase('aqueous').getComponent('methane').getx()\n",
    "    except:\n",
    "        return float('nan')\n",
    "    \n",
    "inpdata = expdata_df[['x1', 'Temperature', 'Pressure']].values.tolist()\n",
    "solres = [solubility(inp) for inp in inpdata]\n",
    "dataWithExperiment = expdata_df.assign(x_CPA = solres)\n",
    "\n",
    "devdf = (dataWithExperiment['x_CPA'] - dataWithExperiment['x1']) / dataWithExperiment['x1']*100.0\n",
    "\n",
    "dataWithExperimentAndDev = dataWithExperiment.assign(dev = devdf.values)\n",
    "\n",
    "print('median average deviation ', devdf.mad(axis=0))\n",
    "\n",
    "dataWithExperimentAndDev.to_csv('./water-methane-exp.csv')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Parameter fitting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "model  CPAs-SRK-EOS-statoil\n",
      "mixing rule  classic-CPA_T\n",
      "kij  -0.827413423\n",
      "kijT  0.0026055\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# return intparam[i][j] + intparamT[i][j] * temperature\n",
    "print('model ', fluid1.getModelName())\n",
    "print('mixing rule ', fluid1.getMixingRuleName())\n",
    "print('kij ', fluid1.getPhase(1).getMixingRule().getBinaryInteractionParameter(0,1))\n",
    "print('kijT ', fluid1.getPhase(1).getMixingRule().getBinaryInteractionParameterT1(0,1))\n",
    "\n",
    "kij = fluid1.getPhase(1).getMixingRule().getBinaryInteractionParameter(0,1)\n",
    "kijT = fluid1.getPhase(1).getMixingRule().getBinaryInteractionParameterT1(0,1)\n",
    "\n",
    "def calcKIJ(temp):\n",
    "    return kij+kijT*temp\n",
    "\n",
    "temperatures = np.arange(273.15, 373.15, 10.0)#range(273.0, 373.15, 10.0)\n",
    "kijcalc = [calcKIJ(T) for T in temperatures]\n",
    "\n",
    "plt.plot(temperatures, kijcalc)\n",
    "plt.xlabel('Temperature[K]')\n",
    "plt.ylabel('k_ij')\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Manual fiting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "average deviation  -17.22395541033987\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#set datafram for testing model\n",
    "inpdata = data373\n",
    "\n",
    "import neqsim\n",
    "from neqsim.thermo.thermoTools import fluid, TPflash, fluidComposition,bubp\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "fluid1 = fluid('cpa')\n",
    "fluid1.addComponent('methane', 1.0)\n",
    "fluid1.addComponent(\"water\", 1.0) \n",
    "fluid1.autoSelectMixingRule()\n",
    "fluid1.setTemperature(15.0, 'C')\n",
    "\n",
    "fluid1.getPhase(0).getMixingRule().setBinaryInteractionParameter(0,1, 0.0950001306904282)\n",
    "fluid1.getPhase(1).getMixingRule().setBinaryInteractionParameter(0,1, 0.0950011306904282)\n",
    "fluid1.getPhase(1).getMixingRule().setBinaryInteractionParameterT1(0,1, 0)\n",
    "fluid1.getPhase(1).getMixingRule().setBinaryInteractionParameterT1(0,1, 0)\n",
    "\n",
    "def solubility(inp):\n",
    "    fluid1.setPressure(inp[2], 'bara')\n",
    "    fluid1.setTemperature(inp[1], 'K')\n",
    "    try:\n",
    "        TPflash(fluid1)\n",
    "        return fluid1.getPhase('aqueous').getComponent('methane').getx()\n",
    "    except:\n",
    "        return float('nan')\n",
    "    \n",
    "inpdataList = inpdata[['x1', 'Temperature', 'Pressure']].values.tolist()\n",
    "solres = [solubility(inp) for inp in inpdataList]\n",
    "dataWithExperiment = inpdata.assign(x_CPA_fitted = solres)\n",
    "\n",
    "devdf = (dataWithExperiment['x_CPA_fitted'] - dataWithExperiment['x1']) / dataWithExperiment['x1']*100.0\n",
    "\n",
    "dataWithExperimentAndDev = dataWithExperiment.assign(dev_fitted = devdf.values)\n",
    "\n",
    "print('average deviation ', devdf.mean(axis=0))\n",
    "\n",
    "dataWithExperimentAndDev.to_csv('./water-CO2-exp-fitted.csv')\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "fig = plt.figure()\t\n",
    "plot1 = inpdata.plot(x='x1', y='Pressure', kind='scatter',ylabel='Pressure(bara)', xlabel='x_methane[mol/mol]',color='black')\t\n",
    "dataWithExperimentAndDev.plot(ax=plot1, x='x_CPA_fitted', y='Pressure', kind='scatter',ylabel='Pressure(bara)', xlabel='x_methane[mol/mol]',color='blue')\t\n",
    "plt.legend(['experiment', 'CPA'])\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# optimized results\n",
    "\n",
    "288.15K : kij =  0.0282  (neqsim 0.038)\n",
    "323.15K : kij =  0.069   (neqsim 0.08)\n",
    "373.15 : kij = 0.095  (neqsim 0.13)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "kij: -0.1878446484018264\n",
      "kijT: [0.00076767]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "\n",
    "x = np.array([288.15, 323.15, 373.15]).reshape((-1, 1))\n",
    "y = np.array([0.0282, 0.069, 0.095])\n",
    "model = LinearRegression()\n",
    "model.fit(x, y)\n",
    "print(f\"kij: {model.intercept_}\")\n",
    "print(f\"kijT: {model.coef_}\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test new parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "median average deviation  14.400706869367884\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_2035/1520280405.py:34: FutureWarning: The 'mad' method is deprecated and will be removed in a future version. To compute the same result, you may do `(df - df.mean()).abs().mean()`.\n",
      "  print('median average deviation ', devdf.mad(axis=0))\n"
     ]
    }
   ],
   "source": [
    "import neqsim\n",
    "from neqsim.thermo.thermoTools import fluid, TPflash, fluidComposition,bubp\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "fluid1 = fluid('cpa')\n",
    "fluid1.addComponent('methane', 1.0)\n",
    "fluid1.addComponent(\"water\", 1.0) \n",
    "fluid1.autoSelectMixingRule()\n",
    "fluid1.setTemperature(15.0, 'C')\n",
    "\n",
    "fluid1.getPhase(0).getMixingRule().setBinaryInteractionParameter(0,1, -0.187844648401)\n",
    "fluid1.getPhase(1).getMixingRule().setBinaryInteractionParameter(0,1, -0.187844648401)\n",
    "fluid1.getPhase(1).getMixingRule().setBinaryInteractionParameterT1(0,1, 0.00076767)\n",
    "fluid1.getPhase(1).getMixingRule().setBinaryInteractionParameterT1(0,1, 0.00076767)\n",
    "\n",
    "def solubility(inp):\n",
    "    fluid1.setPressure(inp[2], 'bara')\n",
    "    fluid1.setTemperature(inp[1], 'K')\n",
    "    try:\n",
    "        TPflash(fluid1)\n",
    "        return fluid1.getPhase('aqueous').getComponent('methane').getx()\n",
    "    except:\n",
    "        return float('nan')\n",
    "    \n",
    "inpdata = expdata_df[['x1', 'Temperature', 'Pressure']].values.tolist()\n",
    "solres = [solubility(inp) for inp in inpdata]\n",
    "dataWithExperiment = expdata_df.assign(x_CPA = solres)\n",
    "\n",
    "devdf = (dataWithExperiment['x_CPA'] - dataWithExperiment['x1']) / dataWithExperiment['x1']*100.0\n",
    "\n",
    "dataWithExperimentAndDev = dataWithExperiment.assign(dev = devdf.values)\n",
    "\n",
    "print('median average deviation ', devdf.mad(axis=0))\n",
    "\n",
    "dataWithExperimentAndDev.to_csv('./water-methane-exp-fitted2.csv')"
   ]
  },
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   "source": [
    "## Automatic fitting"
   ]
  }
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