docs/Examples/Liquid_Ol_Liq_Themometry/Olivine_Liquid_thermometry.ipynb

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  {
   "cell_type": "markdown",
   "id": "a73c4346-37c0-48a6-a496-6a3c9086a52d",
   "metadata": {},
   "source": [
    "# Olivine-Liquid thermometry\n",
    "- This script shows how to use the various options for olivine-liquid thermometry, including tests for equilibrium\n",
    "- It also shows how to calculate equilibrium olivine compositions from a measured liquid composition\n",
    "- we recomend you first got through the \"Liquid_only thermometry.ipynb\" example, as this demonstrates the various options for H2O and P which are also relevant here. \n",
    "- You can download the excel spreadsheet here for Liq-ol (paired up): https://github.com/PennyWieser/Thermobar/blob/main/docs/Examples/Liquid_Ol_Liq_Themometry/Liquid_only_Thermometry.xlsx\n",
    "- And the spreadsheet for individual Ol and Liquid here: \n",
    "https://github.com/PennyWieser/Thermobar/blob/main/docs/Examples/Liquid_Ol_Liq_Themometry/2018_Olivines_Glasses.xlsx\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "44cbd85d-dca1-4d6d-adf2-ab1aee51a60f",
   "metadata": {},
   "source": [
    "### You need to install Thermobar once on your machine, if you haven't done this yet, uncomment the line below (remove the #)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7770de98-ac0b-48a3-bda3-65cc5d896508",
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install Thermobar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "81a1a82f-2075-44fb-b2b3-1da72c1778e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Loading various python things\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import Thermobar as pt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "74460991-41ed-4705-af80-e58d058a5575",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.0.12'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pt.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e84c94fd-5554-4570-b03d-09b2eeb06b51",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Setting plotting parameters\n",
    "plt.rcParams[\"font.family\"] = 'arial'\n",
    "plt.rcParams[\"font.size\"] =12\n",
    "plt.rcParams[\"mathtext.default\"] = \"regular\"\n",
    "plt.rcParams[\"mathtext.fontset\"] = \"dejavusans\"\n",
    "plt.rcParams['patch.linewidth'] = 1\n",
    "plt.rcParams['axes.linewidth'] = 1 \n",
    "plt.rcParams[\"xtick.direction\"] = \"in\"\n",
    "plt.rcParams[\"ytick.direction\"] = \"in\"\n",
    "plt.rcParams[\"ytick.direction\"] = \"in\"\n",
    "plt.rcParams[\"xtick.major.size\"] = 6 # Sets length of ticks\n",
    "plt.rcParams[\"ytick.major.size\"] = 4 # Sets length of ticks\n",
    "plt.rcParams[\"ytick.labelsize\"] = 12 # Sets size of numbers on tick marks\n",
    "plt.rcParams[\"xtick.labelsize\"] = 12 # Sets size of numbers on tick marks\n",
    "plt.rcParams[\"axes.titlesize\"] = 14 # Overall title\n",
    "plt.rcParams[\"axes.labelsize\"] = 14 # Axes labels"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aba9a301-d3b9-46dd-ba2e-2f9bfdd6d72c",
   "metadata": {},
   "source": [
    "## Step 1 - load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "31b100b6-c286-4776-a531-3fa17d85f30d",
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SiO2_Ol</th>\n",
       "      <th>TiO2_Ol</th>\n",
       "      <th>Al2O3_Ol</th>\n",
       "      <th>FeOt_Ol</th>\n",
       "      <th>MnO_Ol</th>\n",
       "      <th>MgO_Ol</th>\n",
       "      <th>CaO_Ol</th>\n",
       "      <th>Na2O_Ol</th>\n",
       "      <th>K2O_Ol</th>\n",
       "      <th>Cr2O3_Ol</th>\n",
       "      <th>NiO_Ol</th>\n",
       "      <th>Sample_ID_Ol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>40.5</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.08</td>\n",
       "      <td>12.40</td>\n",
       "      <td>0.17</td>\n",
       "      <td>47.4</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.03</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>41.3</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.11</td>\n",
       "      <td>9.59</td>\n",
       "      <td>0.14</td>\n",
       "      <td>50.2</td>\n",
       "      <td>0.31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>39.7</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.11</td>\n",
       "      <td>15.60</td>\n",
       "      <td>0.18</td>\n",
       "      <td>44.5</td>\n",
       "      <td>0.31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40.5</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.10</td>\n",
       "      <td>13.20</td>\n",
       "      <td>0.18</td>\n",
       "      <td>46.8</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>40.5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.10</td>\n",
       "      <td>9.41</td>\n",
       "      <td>0.10</td>\n",
       "      <td>49.3</td>\n",
       "      <td>0.31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SiO2_Ol  TiO2_Ol  Al2O3_Ol  FeOt_Ol  MnO_Ol  MgO_Ol  CaO_Ol  Na2O_Ol  \\\n",
       "0     40.5     0.02      0.08    12.40    0.17    47.4    0.30      0.0   \n",
       "1     41.3     0.03      0.11     9.59    0.14    50.2    0.31      0.0   \n",
       "2     39.7     0.05      0.11    15.60    0.18    44.5    0.31      0.0   \n",
       "3     40.5     0.05      0.10    13.20    0.18    46.8    0.29      0.0   \n",
       "4     40.5     0.00      0.10     9.41    0.10    49.3    0.31      0.0   \n",
       "\n",
       "   K2O_Ol  Cr2O3_Ol  NiO_Ol  Sample_ID_Ol  \n",
       "0       0      0.03     0.0             0  \n",
       "1       0      0.00     0.0             1  \n",
       "2       0      0.03     0.0             2  \n",
       "3       0      0.02     0.0             3  \n",
       "4       0      0.00     0.0             4  "
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SiO2_Liq</th>\n",
       "      <th>TiO2_Liq</th>\n",
       "      <th>Al2O3_Liq</th>\n",
       "      <th>FeOt_Liq</th>\n",
       "      <th>MnO_Liq</th>\n",
       "      <th>MgO_Liq</th>\n",
       "      <th>CaO_Liq</th>\n",
       "      <th>Na2O_Liq</th>\n",
       "      <th>K2O_Liq</th>\n",
       "      <th>Cr2O3_Liq</th>\n",
       "      <th>P2O5_Liq</th>\n",
       "      <th>H2O_Liq</th>\n",
       "      <th>Fe3Fet_Liq</th>\n",
       "      <th>NiO_Liq</th>\n",
       "      <th>CoO_Liq</th>\n",
       "      <th>CO2_Liq</th>\n",
       "      <th>Sample_ID_Liq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>57.023602</td>\n",
       "      <td>0.623106</td>\n",
       "      <td>16.332899</td>\n",
       "      <td>4.36174</td>\n",
       "      <td>0.103851</td>\n",
       "      <td>4.19180</td>\n",
       "      <td>6.94858</td>\n",
       "      <td>3.59702</td>\n",
       "      <td>0.896895</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.226584</td>\n",
       "      <td>5.59</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>57.658600</td>\n",
       "      <td>0.654150</td>\n",
       "      <td>17.194799</td>\n",
       "      <td>3.90621</td>\n",
       "      <td>0.084105</td>\n",
       "      <td>2.86892</td>\n",
       "      <td>5.91538</td>\n",
       "      <td>3.85948</td>\n",
       "      <td>1.018600</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.214935</td>\n",
       "      <td>6.55</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>60.731201</td>\n",
       "      <td>0.862054</td>\n",
       "      <td>17.144199</td>\n",
       "      <td>4.07781</td>\n",
       "      <td>0.077488</td>\n",
       "      <td>2.50867</td>\n",
       "      <td>5.22075</td>\n",
       "      <td>4.45556</td>\n",
       "      <td>1.414160</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.319638</td>\n",
       "      <td>3.14</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>61.532799</td>\n",
       "      <td>0.440860</td>\n",
       "      <td>16.508801</td>\n",
       "      <td>3.32990</td>\n",
       "      <td>0.037520</td>\n",
       "      <td>1.64150</td>\n",
       "      <td>4.34294</td>\n",
       "      <td>4.40860</td>\n",
       "      <td>1.407000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.215740</td>\n",
       "      <td>6.20</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>52.969101</td>\n",
       "      <td>0.803412</td>\n",
       "      <td>17.563000</td>\n",
       "      <td>5.93217</td>\n",
       "      <td>0.149472</td>\n",
       "      <td>3.78351</td>\n",
       "      <td>7.65110</td>\n",
       "      <td>3.80219</td>\n",
       "      <td>0.551178</td>\n",
       "      <td>0.037368</td>\n",
       "      <td>0.196182</td>\n",
       "      <td>6.58</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
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      "text/plain": [
       "    SiO2_Liq  TiO2_Liq  Al2O3_Liq  FeOt_Liq   MnO_Liq  MgO_Liq  CaO_Liq  \\\n",
       "0  57.023602  0.623106  16.332899   4.36174  0.103851  4.19180  6.94858   \n",
       "1  57.658600  0.654150  17.194799   3.90621  0.084105  2.86892  5.91538   \n",
       "2  60.731201  0.862054  17.144199   4.07781  0.077488  2.50867  5.22075   \n",
       "3  61.532799  0.440860  16.508801   3.32990  0.037520  1.64150  4.34294   \n",
       "4  52.969101  0.803412  17.563000   5.93217  0.149472  3.78351  7.65110   \n",
       "\n",
       "   Na2O_Liq   K2O_Liq  Cr2O3_Liq  P2O5_Liq  H2O_Liq  Fe3Fet_Liq  NiO_Liq  \\\n",
       "0   3.59702  0.896895   0.000000  0.226584     5.59         0.2      0.0   \n",
       "1   3.85948  1.018600   0.000000  0.214935     6.55         0.2      0.0   \n",
       "2   4.45556  1.414160   0.000000  0.319638     3.14         0.2      0.0   \n",
       "3   4.40860  1.407000   0.000000  0.215740     6.20         0.2      0.0   \n",
       "4   3.80219  0.551178   0.037368  0.196182     6.58         0.2      0.0   \n",
       "\n",
       "   CoO_Liq  CO2_Liq  Sample_ID_Liq  \n",
       "0      0.0      0.0              0  \n",
       "1      0.0      0.0              1  \n",
       "2      0.0      0.0              2  \n",
       "3      0.0      0.0              3  \n",
       "4      0.0      0.0              4  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "out=pt.import_excel('Liquid_only_Thermometry.xlsx', sheet_name=\"Ol-Liq\")\n",
    "my_input=out['my_input']\n",
    "myLiquids1=out['Liqs']\n",
    "myOls1=out['Ols']\n",
    "display(myOls1.head())\n",
    "display(myLiquids1.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c915a94c-057a-4abf-851e-0476b18a5335",
   "metadata": {},
   "source": [
    "## Example 1 - Olivine-Liquid temperatures\n",
    "- It has been shown many times that olivines are not in equilirium with their co-erupted carrier melts. Thus, it is difficult to know what a meaningful Ol-Liq match is. Because of this, by default we return the value of Kd calculated for olivine-liquid as well as the calculated temperature in the \"calculate_ol_liq_temp\" function.\n",
    "- The function uses the Fe3Fet_Liq column in the user-entered spreadsheet, and calculates Fe/Mg in the liquid using only Fe2+ by default. \n",
    "- You can also specify a Fe3Fet_Liq ratio in the function itself (see later examples) to overwrite this value.\n",
    "- If the user doesn't specify a column for Fe3Fet in the input, this value is set to zero. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b11c5884-7137-43ba-a744-6fe3f09c1169",
   "metadata": {},
   "source": [
    "### 1a - Putirka eq 22"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c96fe4a3-cc6d-49bf-b88a-a5d4034fe8b8",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>T_K_calc</th>\n",
       "      <th>Kd (Fe-Mg) Meas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1289.947705</td>\n",
       "      <td>0.314264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1229.813416</td>\n",
       "      <td>0.175383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1285.857491</td>\n",
       "      <td>0.269582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1198.240159</td>\n",
       "      <td>0.173799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1259.174284</td>\n",
       "      <td>0.152172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1244.931462</td>\n",
       "      <td>0.159554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1241.300118</td>\n",
       "      <td>0.215915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1199.601831</td>\n",
       "      <td>0.404699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1162.693468</td>\n",
       "      <td>0.314115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1339.466029</td>\n",
       "      <td>0.429135</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "      T_K_calc  Kd (Fe-Mg) Meas\n",
       "0  1289.947705         0.314264\n",
       "1  1229.813416         0.175383\n",
       "2  1285.857491         0.269582\n",
       "3  1198.240159         0.173799\n",
       "4  1259.174284         0.152172\n",
       "5  1244.931462         0.159554\n",
       "6  1241.300118         0.215915\n",
       "7  1199.601831         0.404699\n",
       "8  1162.693468         0.314115\n",
       "9  1339.466029         0.429135"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eq22_PHinput=pt.calculate_ol_liq_temp(liq_comps=myLiquids1, ol_comps=myOls1,  equationT=\"T_Put2008_eq22\", \n",
    "                                      P=my_input['P_kbar'])\n",
    "eq22_PHinput"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77dcf483-5ffa-41ba-822d-29b33ee58b87",
   "metadata": {},
   "source": [
    "### 1b - Specify eq_tests=True\n",
    "- FIf you specify eq_tests=True, the function also returns calculated Kd values for olivine-Liquid pairs so you can assess if olivine-liquids are in equilibrium. \n",
    "- A number of different equilibrium tests are returned, using Toplis, Matzen and Roeder and Emslie (preferred value=0.3 for Roeder and Emslie, 1970, =0.34 for Matzen, function of melt comp, temp and press for Toplis). \n",
    "- As before, here the Fe3Fet_Liq ratio in the spreadsheet is being used for calculations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "75d205d0-7d85-4080-bd91-f6427ca9fd09",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>T_K_calc</th>\n",
       "      <th>Kd Meas</th>\n",
       "      <th>Kd calc (Toplis)</th>\n",
       "      <th>ΔKd, Toplis (M-P)</th>\n",
       "      <th>ΔKd, Roeder (M-P)</th>\n",
       "      <th>ΔKd, Matzen (M-P)</th>\n",
       "      <th>ΔKd, Shea (M-P)</th>\n",
       "      <th>SiO2_Liq</th>\n",
       "      <th>TiO2_Liq</th>\n",
       "      <th>Al2O3_Liq</th>\n",
       "      <th>...</th>\n",
       "      <th>K2O_Ol</th>\n",
       "      <th>Cr2O3_Ol</th>\n",
       "      <th>NiO_Ol</th>\n",
       "      <th>Sample_ID_Ol</th>\n",
       "      <th>P2O5_Ol</th>\n",
       "      <th>DMg_Meas</th>\n",
       "      <th>CNML</th>\n",
       "      <th>CSiO2L</th>\n",
       "      <th>NF</th>\n",
       "      <th>Den_Beat93</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1289.947705</td>\n",
       "      <td>0.314264</td>\n",
       "      <td>0.325040</td>\n",
       "      <td>-0.010776</td>\n",
       "      <td>0.014264</td>\n",
       "      <td>-0.025736</td>\n",
       "      <td>-0.020736</td>\n",
       "      <td>57.023602</td>\n",
       "      <td>0.623106</td>\n",
       "      <td>16.332899</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9.472619</td>\n",
       "      <td>0.170395</td>\n",
       "      <td>0.557471</td>\n",
       "      <td>-0.761843</td>\n",
       "      <td>9.819071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1229.813416</td>\n",
       "      <td>0.175383</td>\n",
       "      <td>0.308684</td>\n",
       "      <td>-0.133301</td>\n",
       "      <td>-0.124617</td>\n",
       "      <td>-0.164617</td>\n",
       "      <td>-0.159617</td>\n",
       "      <td>57.658600</td>\n",
       "      <td>0.654150</td>\n",
       "      <td>17.194799</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>14.186789</td>\n",
       "      <td>0.137941</td>\n",
       "      <td>0.570023</td>\n",
       "      <td>-0.816654</td>\n",
       "      <td>10.303635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1285.857491</td>\n",
       "      <td>0.269582</td>\n",
       "      <td>0.315891</td>\n",
       "      <td>-0.046309</td>\n",
       "      <td>-0.030418</td>\n",
       "      <td>-0.070418</td>\n",
       "      <td>-0.065418</td>\n",
       "      <td>60.731201</td>\n",
       "      <td>0.862054</td>\n",
       "      <td>17.144199</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>15.531216</td>\n",
       "      <td>0.122184</td>\n",
       "      <td>0.579288</td>\n",
       "      <td>-0.792785</td>\n",
       "      <td>10.250501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1198.240159</td>\n",
       "      <td>0.173799</td>\n",
       "      <td>0.296719</td>\n",
       "      <td>-0.122920</td>\n",
       "      <td>-0.126201</td>\n",
       "      <td>-0.166201</td>\n",
       "      <td>-0.161201</td>\n",
       "      <td>61.532799</td>\n",
       "      <td>0.440860</td>\n",
       "      <td>16.508801</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>23.753206</td>\n",
       "      <td>0.097626</td>\n",
       "      <td>0.605753</td>\n",
       "      <td>-0.767076</td>\n",
       "      <td>10.715090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1259.174284</td>\n",
       "      <td>0.152172</td>\n",
       "      <td>0.323766</td>\n",
       "      <td>-0.171594</td>\n",
       "      <td>-0.147828</td>\n",
       "      <td>-0.187828</td>\n",
       "      <td>-0.182828</td>\n",
       "      <td>52.969101</td>\n",
       "      <td>0.803412</td>\n",
       "      <td>17.563000</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>10.781292</td>\n",
       "      <td>0.186877</td>\n",
       "      <td>0.523030</td>\n",
       "      <td>-0.842157</td>\n",
       "      <td>10.215321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1244.931462</td>\n",
       "      <td>0.159554</td>\n",
       "      <td>0.324986</td>\n",
       "      <td>-0.165432</td>\n",
       "      <td>-0.140446</td>\n",
       "      <td>-0.180446</td>\n",
       "      <td>-0.175446</td>\n",
       "      <td>54.050201</td>\n",
       "      <td>0.857348</td>\n",
       "      <td>17.333300</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>12.276130</td>\n",
       "      <td>0.168070</td>\n",
       "      <td>0.533835</td>\n",
       "      <td>-0.833465</td>\n",
       "      <td>10.295063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1241.300118</td>\n",
       "      <td>0.215915</td>\n",
       "      <td>0.333878</td>\n",
       "      <td>-0.117963</td>\n",
       "      <td>-0.084085</td>\n",
       "      <td>-0.124085</td>\n",
       "      <td>-0.119085</td>\n",
       "      <td>55.656300</td>\n",
       "      <td>0.897984</td>\n",
       "      <td>17.117800</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>14.083460</td>\n",
       "      <td>0.145845</td>\n",
       "      <td>0.547483</td>\n",
       "      <td>-0.820914</td>\n",
       "      <td>10.324021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1199.601831</td>\n",
       "      <td>0.404699</td>\n",
       "      <td>0.391378</td>\n",
       "      <td>0.013321</td>\n",
       "      <td>0.104699</td>\n",
       "      <td>0.064699</td>\n",
       "      <td>0.069699</td>\n",
       "      <td>49.054699</td>\n",
       "      <td>0.488832</td>\n",
       "      <td>14.665000</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>7.372298</td>\n",
       "      <td>0.220053</td>\n",
       "      <td>0.554209</td>\n",
       "      <td>-0.789502</td>\n",
       "      <td>9.845140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1162.693468</td>\n",
       "      <td>0.314115</td>\n",
       "      <td>0.361834</td>\n",
       "      <td>-0.047718</td>\n",
       "      <td>0.014115</td>\n",
       "      <td>-0.025885</td>\n",
       "      <td>-0.020885</td>\n",
       "      <td>50.625099</td>\n",
       "      <td>0.334074</td>\n",
       "      <td>16.875000</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>10.509878</td>\n",
       "      <td>0.180293</td>\n",
       "      <td>0.551305</td>\n",
       "      <td>-0.873502</td>\n",
       "      <td>10.229233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1339.466029</td>\n",
       "      <td>0.429135</td>\n",
       "      <td>0.299720</td>\n",
       "      <td>0.129416</td>\n",
       "      <td>0.129135</td>\n",
       "      <td>0.089135</td>\n",
       "      <td>0.094135</td>\n",
       "      <td>51.403301</td>\n",
       "      <td>0.663880</td>\n",
       "      <td>18.019600</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>7.070601</td>\n",
       "      <td>0.228386</td>\n",
       "      <td>0.498172</td>\n",
       "      <td>-0.840523</td>\n",
       "      <td>9.673734</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 75 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      T_K_calc   Kd Meas  Kd calc (Toplis)  ΔKd, Toplis (M-P)  \\\n",
       "0  1289.947705  0.314264          0.325040          -0.010776   \n",
       "1  1229.813416  0.175383          0.308684          -0.133301   \n",
       "2  1285.857491  0.269582          0.315891          -0.046309   \n",
       "3  1198.240159  0.173799          0.296719          -0.122920   \n",
       "4  1259.174284  0.152172          0.323766          -0.171594   \n",
       "5  1244.931462  0.159554          0.324986          -0.165432   \n",
       "6  1241.300118  0.215915          0.333878          -0.117963   \n",
       "7  1199.601831  0.404699          0.391378           0.013321   \n",
       "8  1162.693468  0.314115          0.361834          -0.047718   \n",
       "9  1339.466029  0.429135          0.299720           0.129416   \n",
       "\n",
       "   ΔKd, Roeder (M-P)  ΔKd, Matzen (M-P)  ΔKd, Shea (M-P)   SiO2_Liq  TiO2_Liq  \\\n",
       "0           0.014264          -0.025736        -0.020736  57.023602  0.623106   \n",
       "1          -0.124617          -0.164617        -0.159617  57.658600  0.654150   \n",
       "2          -0.030418          -0.070418        -0.065418  60.731201  0.862054   \n",
       "3          -0.126201          -0.166201        -0.161201  61.532799  0.440860   \n",
       "4          -0.147828          -0.187828        -0.182828  52.969101  0.803412   \n",
       "5          -0.140446          -0.180446        -0.175446  54.050201  0.857348   \n",
       "6          -0.084085          -0.124085        -0.119085  55.656300  0.897984   \n",
       "7           0.104699           0.064699         0.069699  49.054699  0.488832   \n",
       "8           0.014115          -0.025885        -0.020885  50.625099  0.334074   \n",
       "9           0.129135           0.089135         0.094135  51.403301  0.663880   \n",
       "\n",
       "   Al2O3_Liq  ...  K2O_Ol  Cr2O3_Ol  NiO_Ol  Sample_ID_Ol  P2O5_Ol   DMg_Meas  \\\n",
       "0  16.332899  ...       0         0     0.0             0        0   9.472619   \n",
       "1  17.194799  ...       0         0     0.0             1        0  14.186789   \n",
       "2  17.144199  ...       0         0     0.0             2        0  15.531216   \n",
       "3  16.508801  ...       0         0     0.0             3        0  23.753206   \n",
       "4  17.563000  ...       0         0     0.0             4        0  10.781292   \n",
       "5  17.333300  ...       0         0     0.0             5        0  12.276130   \n",
       "6  17.117800  ...       0         0     0.0             6        0  14.083460   \n",
       "7  14.665000  ...       0         0     0.0             7        0   7.372298   \n",
       "8  16.875000  ...       0         0     0.0             8        0  10.509878   \n",
       "9  18.019600  ...       0         0     0.0             9        0   7.070601   \n",
       "\n",
       "       CNML    CSiO2L        NF  Den_Beat93  \n",
       "0  0.170395  0.557471 -0.761843    9.819071  \n",
       "1  0.137941  0.570023 -0.816654   10.303635  \n",
       "2  0.122184  0.579288 -0.792785   10.250501  \n",
       "3  0.097626  0.605753 -0.767076   10.715090  \n",
       "4  0.186877  0.523030 -0.842157   10.215321  \n",
       "5  0.168070  0.533835 -0.833465   10.295063  \n",
       "6  0.145845  0.547483 -0.820914   10.324021  \n",
       "7  0.220053  0.554209 -0.789502    9.845140  \n",
       "8  0.180293  0.551305 -0.873502   10.229233  \n",
       "9  0.228386  0.498172 -0.840523    9.673734  \n",
       "\n",
       "[10 rows x 75 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eq22_PHinput=pt.calculate_ol_liq_temp(liq_comps=myLiquids1, ol_comps=myOls1,  \n",
    "                                      equationT=\"T_Put2008_eq22\", P=my_input['P_kbar'], eq_tests=True)\n",
    "eq22_PHinput"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13674293-b1ab-4c61-b98e-7b39a36a8dda",
   "metadata": {},
   "source": [
    "- If you want to access just the temperature from this panda dataframe, you do name['column heading']\n",
    "- To get the output in Celcius, subtract -273.15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5ae9da4d-4d05-4d09-92f2-d7ebd2bd0348",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1016.797705\n",
       "1     956.663416\n",
       "2    1012.707491\n",
       "3     925.090159\n",
       "4     986.024284\n",
       "5     971.781462\n",
       "6     968.150118\n",
       "7     926.451831\n",
       "8     889.543468\n",
       "9    1066.316029\n",
       "Name: T_K_calc, dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Teq22_PHinput=eq22_PHinput['T_K_calc']-273.15 #converting temp to C\n",
    "Teq22_PHinput"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04ceef31-43c2-4fd8-9228-7580a102f97a",
   "metadata": {},
   "source": [
    "- Can also filter outputs, to only look at temps for pairs with delta K<=0.03 using the pandas loc function.\n",
    "- This basically says \"give me the rows of eq22_PHinput where the column \"ΔKd, Roeder\" is less than or equal to 0.03 (e.g., in equilibrium)\n",
    "- Only 2 Ol-Liq pairs are in equilibrium here!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "33129e01-ec9e-496f-b918-34c6d1caaa2c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>T_K_calc</th>\n",
       "      <th>Kd Meas</th>\n",
       "      <th>Kd calc (Toplis)</th>\n",
       "      <th>ΔKd, Toplis (M-P)</th>\n",
       "      <th>ΔKd, Roeder (M-P)</th>\n",
       "      <th>ΔKd, Matzen (M-P)</th>\n",
       "      <th>ΔKd, Shea (M-P)</th>\n",
       "      <th>SiO2_Liq</th>\n",
       "      <th>TiO2_Liq</th>\n",
       "      <th>Al2O3_Liq</th>\n",
       "      <th>...</th>\n",
       "      <th>K2O_Ol</th>\n",
       "      <th>Cr2O3_Ol</th>\n",
       "      <th>NiO_Ol</th>\n",
       "      <th>Sample_ID_Ol</th>\n",
       "      <th>P2O5_Ol</th>\n",
       "      <th>DMg_Meas</th>\n",
       "      <th>CNML</th>\n",
       "      <th>CSiO2L</th>\n",
       "      <th>NF</th>\n",
       "      <th>Den_Beat93</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1289.947705</td>\n",
       "      <td>0.314264</td>\n",
       "      <td>0.325040</td>\n",
       "      <td>-0.010776</td>\n",
       "      <td>0.014264</td>\n",
       "      <td>-0.025736</td>\n",
       "      <td>-0.020736</td>\n",
       "      <td>57.023602</td>\n",
       "      <td>0.623106</td>\n",
       "      <td>16.332899</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9.472619</td>\n",
       "      <td>0.170395</td>\n",
       "      <td>0.557471</td>\n",
       "      <td>-0.761843</td>\n",
       "      <td>9.819071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1229.813416</td>\n",
       "      <td>0.175383</td>\n",
       "      <td>0.308684</td>\n",
       "      <td>-0.133301</td>\n",
       "      <td>-0.124617</td>\n",
       "      <td>-0.164617</td>\n",
       "      <td>-0.159617</td>\n",
       "      <td>57.658600</td>\n",
       "      <td>0.654150</td>\n",
       "      <td>17.194799</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>14.186789</td>\n",
       "      <td>0.137941</td>\n",
       "      <td>0.570023</td>\n",
       "      <td>-0.816654</td>\n",
       "      <td>10.303635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1285.857491</td>\n",
       "      <td>0.269582</td>\n",
       "      <td>0.315891</td>\n",
       "      <td>-0.046309</td>\n",
       "      <td>-0.030418</td>\n",
       "      <td>-0.070418</td>\n",
       "      <td>-0.065418</td>\n",
       "      <td>60.731201</td>\n",
       "      <td>0.862054</td>\n",
       "      <td>17.144199</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>15.531216</td>\n",
       "      <td>0.122184</td>\n",
       "      <td>0.579288</td>\n",
       "      <td>-0.792785</td>\n",
       "      <td>10.250501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1198.240159</td>\n",
       "      <td>0.173799</td>\n",
       "      <td>0.296719</td>\n",
       "      <td>-0.122920</td>\n",
       "      <td>-0.126201</td>\n",
       "      <td>-0.166201</td>\n",
       "      <td>-0.161201</td>\n",
       "      <td>61.532799</td>\n",
       "      <td>0.440860</td>\n",
       "      <td>16.508801</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>23.753206</td>\n",
       "      <td>0.097626</td>\n",
       "      <td>0.605753</td>\n",
       "      <td>-0.767076</td>\n",
       "      <td>10.715090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1259.174284</td>\n",
       "      <td>0.152172</td>\n",
       "      <td>0.323766</td>\n",
       "      <td>-0.171594</td>\n",
       "      <td>-0.147828</td>\n",
       "      <td>-0.187828</td>\n",
       "      <td>-0.182828</td>\n",
       "      <td>52.969101</td>\n",
       "      <td>0.803412</td>\n",
       "      <td>17.563000</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>10.781292</td>\n",
       "      <td>0.186877</td>\n",
       "      <td>0.523030</td>\n",
       "      <td>-0.842157</td>\n",
       "      <td>10.215321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1244.931462</td>\n",
       "      <td>0.159554</td>\n",
       "      <td>0.324986</td>\n",
       "      <td>-0.165432</td>\n",
       "      <td>-0.140446</td>\n",
       "      <td>-0.180446</td>\n",
       "      <td>-0.175446</td>\n",
       "      <td>54.050201</td>\n",
       "      <td>0.857348</td>\n",
       "      <td>17.333300</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>12.276130</td>\n",
       "      <td>0.168070</td>\n",
       "      <td>0.533835</td>\n",
       "      <td>-0.833465</td>\n",
       "      <td>10.295063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1241.300118</td>\n",
       "      <td>0.215915</td>\n",
       "      <td>0.333878</td>\n",
       "      <td>-0.117963</td>\n",
       "      <td>-0.084085</td>\n",
       "      <td>-0.124085</td>\n",
       "      <td>-0.119085</td>\n",
       "      <td>55.656300</td>\n",
       "      <td>0.897984</td>\n",
       "      <td>17.117800</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>14.083460</td>\n",
       "      <td>0.145845</td>\n",
       "      <td>0.547483</td>\n",
       "      <td>-0.820914</td>\n",
       "      <td>10.324021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1162.693468</td>\n",
       "      <td>0.314115</td>\n",
       "      <td>0.361834</td>\n",
       "      <td>-0.047718</td>\n",
       "      <td>0.014115</td>\n",
       "      <td>-0.025885</td>\n",
       "      <td>-0.020885</td>\n",
       "      <td>50.625099</td>\n",
       "      <td>0.334074</td>\n",
       "      <td>16.875000</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>10.509878</td>\n",
       "      <td>0.180293</td>\n",
       "      <td>0.551305</td>\n",
       "      <td>-0.873502</td>\n",
       "      <td>10.229233</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 75 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      T_K_calc   Kd Meas  Kd calc (Toplis)  ΔKd, Toplis (M-P)  \\\n",
       "0  1289.947705  0.314264          0.325040          -0.010776   \n",
       "1  1229.813416  0.175383          0.308684          -0.133301   \n",
       "2  1285.857491  0.269582          0.315891          -0.046309   \n",
       "3  1198.240159  0.173799          0.296719          -0.122920   \n",
       "4  1259.174284  0.152172          0.323766          -0.171594   \n",
       "5  1244.931462  0.159554          0.324986          -0.165432   \n",
       "6  1241.300118  0.215915          0.333878          -0.117963   \n",
       "8  1162.693468  0.314115          0.361834          -0.047718   \n",
       "\n",
       "   ΔKd, Roeder (M-P)  ΔKd, Matzen (M-P)  ΔKd, Shea (M-P)   SiO2_Liq  TiO2_Liq  \\\n",
       "0           0.014264          -0.025736        -0.020736  57.023602  0.623106   \n",
       "1          -0.124617          -0.164617        -0.159617  57.658600  0.654150   \n",
       "2          -0.030418          -0.070418        -0.065418  60.731201  0.862054   \n",
       "3          -0.126201          -0.166201        -0.161201  61.532799  0.440860   \n",
       "4          -0.147828          -0.187828        -0.182828  52.969101  0.803412   \n",
       "5          -0.140446          -0.180446        -0.175446  54.050201  0.857348   \n",
       "6          -0.084085          -0.124085        -0.119085  55.656300  0.897984   \n",
       "8           0.014115          -0.025885        -0.020885  50.625099  0.334074   \n",
       "\n",
       "   Al2O3_Liq  ...  K2O_Ol  Cr2O3_Ol  NiO_Ol  Sample_ID_Ol  P2O5_Ol   DMg_Meas  \\\n",
       "0  16.332899  ...       0         0     0.0             0        0   9.472619   \n",
       "1  17.194799  ...       0         0     0.0             1        0  14.186789   \n",
       "2  17.144199  ...       0         0     0.0             2        0  15.531216   \n",
       "3  16.508801  ...       0         0     0.0             3        0  23.753206   \n",
       "4  17.563000  ...       0         0     0.0             4        0  10.781292   \n",
       "5  17.333300  ...       0         0     0.0             5        0  12.276130   \n",
       "6  17.117800  ...       0         0     0.0             6        0  14.083460   \n",
       "8  16.875000  ...       0         0     0.0             8        0  10.509878   \n",
       "\n",
       "       CNML    CSiO2L        NF  Den_Beat93  \n",
       "0  0.170395  0.557471 -0.761843    9.819071  \n",
       "1  0.137941  0.570023 -0.816654   10.303635  \n",
       "2  0.122184  0.579288 -0.792785   10.250501  \n",
       "3  0.097626  0.605753 -0.767076   10.715090  \n",
       "4  0.186877  0.523030 -0.842157   10.215321  \n",
       "5  0.168070  0.533835 -0.833465   10.295063  \n",
       "6  0.145845  0.547483 -0.820914   10.324021  \n",
       "8  0.180293  0.551305 -0.873502   10.229233  \n",
       "\n",
       "[8 rows x 75 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T_in_eq=eq22_PHinput.loc[eq22_PHinput['ΔKd, Roeder (M-P)']<=0.03]\n",
    "T_in_eq"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b273d943-7c13-42ee-98ca-cd6a0064ffdd",
   "metadata": {},
   "source": [
    "### 1c - You can also overwrite the spreadsheet Fe3Fet_Liq in the function itself\n",
    "- Here, we peform calculations using 30% Fe3+"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9fda5c18-48b5-47d3-a879-d1aaa6a088b2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>T_K_calc</th>\n",
       "      <th>Kd (Fe-Mg) Meas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1289.947705</td>\n",
       "      <td>0.359158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1229.813416</td>\n",
       "      <td>0.200438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1285.857491</td>\n",
       "      <td>0.308094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1198.240159</td>\n",
       "      <td>0.198628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1259.174284</td>\n",
       "      <td>0.173911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1244.931462</td>\n",
       "      <td>0.182347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1241.300118</td>\n",
       "      <td>0.246761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1199.601831</td>\n",
       "      <td>0.462513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1162.693468</td>\n",
       "      <td>0.358989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1339.466029</td>\n",
       "      <td>0.490441</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      T_K_calc  Kd (Fe-Mg) Meas\n",
       "0  1289.947705         0.359158\n",
       "1  1229.813416         0.200438\n",
       "2  1285.857491         0.308094\n",
       "3  1198.240159         0.198628\n",
       "4  1259.174284         0.173911\n",
       "5  1244.931462         0.182347\n",
       "6  1241.300118         0.246761\n",
       "7  1199.601831         0.462513\n",
       "8  1162.693468         0.358989\n",
       "9  1339.466029         0.490441"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eq22_PHinput_30Fe3=pt.calculate_ol_liq_temp(liq_comps=myLiquids1, ol_comps=myOls1,  \n",
    "                                      equationT=\"T_Put2008_eq22\", P=my_input['P_kbar'], \n",
    "                                        Fe3Fet_Liq=0.3)\n",
    "eq22_PHinput_30Fe3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a21026f-414b-42a9-84b8-593937ed6684",
   "metadata": {},
   "source": [
    "## Example 2 - Considering all liquid-olivine matches\n",
    "- In reality, you have probably measured a load of glasses, and a load of olivines, but you dont know which ones match with which.\n",
    "- So, we have a matching algorithm, that returns all possible olivine-liquid pairs, which you can then filter. \n",
    "- Lets load the olivines and liquids separatly, as they will likely be different lenghts (and if you put them in one spreasdheet, you'll end up with a load of NaNs which will cause issues!)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "98cf596b-72b7-4980-bfde-b3a3d824266a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Loading in matrix glasses\n",
    "out2018MG=pt.import_excel('2018_Olivines_Glasses.xlsx', sheet_name=\"LL4_MGs\", suffix='_Liq')\n",
    "my_input_MGs2018=out2018MG['my_input']\n",
    "MGs2018=out2018MG['Liqs']\n",
    "\n",
    "out2018Ols=pt.import_excel('2018_Olivines_Glasses.xlsx', sheet_name=\"LL4_Ols\")\n",
    "my_input_Ols2018=out2018Ols['my_input']\n",
    "Ols2018=out2018Ols['Ols']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "30d9214c-ea49-47a2-99fc-d6902df23bdf",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SiO2_Liq</th>\n",
       "      <th>TiO2_Liq</th>\n",
       "      <th>Al2O3_Liq</th>\n",
       "      <th>FeOt_Liq</th>\n",
       "      <th>MnO_Liq</th>\n",
       "      <th>MgO_Liq</th>\n",
       "      <th>CaO_Liq</th>\n",
       "      <th>Na2O_Liq</th>\n",
       "      <th>K2O_Liq</th>\n",
       "      <th>Cr2O3_Liq</th>\n",
       "      <th>P2O5_Liq</th>\n",
       "      <th>H2O_Liq</th>\n",
       "      <th>Fe3Fet_Liq</th>\n",
       "      <th>NiO_Liq</th>\n",
       "      <th>CoO_Liq</th>\n",
       "      <th>CO2_Liq</th>\n",
       "      <th>Sample_ID_Liq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>50.6243</td>\n",
       "      <td>2.8773</td>\n",
       "      <td>13.0360</td>\n",
       "      <td>11.8288</td>\n",
       "      <td>0.1830</td>\n",
       "      <td>5.8471</td>\n",
       "      <td>10.2471</td>\n",
       "      <td>2.5120</td>\n",
       "      <td>0.5234</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.2689</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>50.0975</td>\n",
       "      <td>2.8840</td>\n",
       "      <td>12.8885</td>\n",
       "      <td>11.2897</td>\n",
       "      <td>0.1769</td>\n",
       "      <td>5.8521</td>\n",
       "      <td>9.9658</td>\n",
       "      <td>2.4681</td>\n",
       "      <td>0.5305</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.2652</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>50.1346</td>\n",
       "      <td>2.8741</td>\n",
       "      <td>12.8953</td>\n",
       "      <td>11.8696</td>\n",
       "      <td>0.1814</td>\n",
       "      <td>5.8682</td>\n",
       "      <td>10.2012</td>\n",
       "      <td>2.4618</td>\n",
       "      <td>0.5778</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.2875</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>50.5233</td>\n",
       "      <td>2.8765</td>\n",
       "      <td>12.9818</td>\n",
       "      <td>11.3536</td>\n",
       "      <td>0.1454</td>\n",
       "      <td>5.8673</td>\n",
       "      <td>10.1806</td>\n",
       "      <td>2.6206</td>\n",
       "      <td>0.5206</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.2759</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>51.5840</td>\n",
       "      <td>2.9055</td>\n",
       "      <td>13.3290</td>\n",
       "      <td>11.5014</td>\n",
       "      <td>0.2286</td>\n",
       "      <td>5.8450</td>\n",
       "      <td>10.0408</td>\n",
       "      <td>2.1722</td>\n",
       "      <td>0.5565</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.2693</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SiO2_Liq  TiO2_Liq  Al2O3_Liq  FeOt_Liq  MnO_Liq  MgO_Liq  CaO_Liq  \\\n",
       "0   50.6243    2.8773    13.0360   11.8288   0.1830   5.8471  10.2471   \n",
       "1   50.0975    2.8840    12.8885   11.2897   0.1769   5.8521   9.9658   \n",
       "2   50.1346    2.8741    12.8953   11.8696   0.1814   5.8682  10.2012   \n",
       "3   50.5233    2.8765    12.9818   11.3536   0.1454   5.8673  10.1806   \n",
       "4   51.5840    2.9055    13.3290   11.5014   0.2286   5.8450  10.0408   \n",
       "\n",
       "   Na2O_Liq  K2O_Liq  Cr2O3_Liq  P2O5_Liq  H2O_Liq  Fe3Fet_Liq  NiO_Liq  \\\n",
       "0    2.5120   0.5234        0.0    0.2689      0.0         0.0      0.0   \n",
       "1    2.4681   0.5305        0.0    0.2652      0.0         0.0      0.0   \n",
       "2    2.4618   0.5778        0.0    0.2875      0.0         0.0      0.0   \n",
       "3    2.6206   0.5206        0.0    0.2759      0.0         0.0      0.0   \n",
       "4    2.1722   0.5565        0.0    0.2693      0.0         0.0      0.0   \n",
       "\n",
       "   CoO_Liq  CO2_Liq  Sample_ID_Liq  \n",
       "0      0.0      0.0              0  \n",
       "1      0.0      0.0              1  \n",
       "2      0.0      0.0              2  \n",
       "3      0.0      0.0              3  \n",
       "4      0.0      0.0              4  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SiO2_Ol</th>\n",
       "      <th>TiO2_Ol</th>\n",
       "      <th>Al2O3_Ol</th>\n",
       "      <th>FeOt_Ol</th>\n",
       "      <th>MnO_Ol</th>\n",
       "      <th>MgO_Ol</th>\n",
       "      <th>CaO_Ol</th>\n",
       "      <th>Na2O_Ol</th>\n",
       "      <th>K2O_Ol</th>\n",
       "      <th>Cr2O3_Ol</th>\n",
       "      <th>NiO_Ol</th>\n",
       "      <th>Sample_ID_Ol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>39.65300</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.04025</td>\n",
       "      <td>15.12365</td>\n",
       "      <td>0.20515</td>\n",
       "      <td>44.36500</td>\n",
       "      <td>0.25190</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.30635</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>39.79465</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.04405</td>\n",
       "      <td>12.84395</td>\n",
       "      <td>0.16570</td>\n",
       "      <td>45.94980</td>\n",
       "      <td>0.23245</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.37605</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>40.14520</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.04705</td>\n",
       "      <td>11.68440</td>\n",
       "      <td>0.14900</td>\n",
       "      <td>46.74595</td>\n",
       "      <td>0.23320</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.38705</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>39.53345</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.05060</td>\n",
       "      <td>16.92675</td>\n",
       "      <td>0.22125</td>\n",
       "      <td>43.10860</td>\n",
       "      <td>0.23345</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.26300</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>40.02325</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.05610</td>\n",
       "      <td>11.42200</td>\n",
       "      <td>0.15300</td>\n",
       "      <td>47.16475</td>\n",
       "      <td>0.22890</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.38110</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    SiO2_Ol  TiO2_Ol  Al2O3_Ol   FeOt_Ol   MnO_Ol    MgO_Ol   CaO_Ol  Na2O_Ol  \\\n",
       "0  39.65300      0.0   0.04025  15.12365  0.20515  44.36500  0.25190      0.0   \n",
       "1  39.79465      0.0   0.04405  12.84395  0.16570  45.94980  0.23245      0.0   \n",
       "2  40.14520      0.0   0.04705  11.68440  0.14900  46.74595  0.23320      0.0   \n",
       "3  39.53345      0.0   0.05060  16.92675  0.22125  43.10860  0.23345      0.0   \n",
       "4  40.02325      0.0   0.05610  11.42200  0.15300  47.16475  0.22890      0.0   \n",
       "\n",
       "   K2O_Ol  Cr2O3_Ol   NiO_Ol  Sample_ID_Ol  \n",
       "0     0.0       0.0  0.30635             0  \n",
       "1     0.0       0.0  0.37605             1  \n",
       "2     0.0       0.0  0.38705             2  \n",
       "3     0.0       0.0  0.26300             3  \n",
       "4     0.0       0.0  0.38110             4  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(MGs2018.head())\n",
    "display(Ols2018.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3ef8fb04-3152-4675-8976-43caa2d4256c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Considering N=23 Ol & N=19 Liqs, which is a total of N=437 Liq-Ol pairs, be patient if this is >>1 million!\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>T_K_calc</th>\n",
       "      <th>Ol_Fo_Meas</th>\n",
       "      <th>Kd Meas</th>\n",
       "      <th>Kd calc (Toplis)</th>\n",
       "      <th>ΔKd, Toplis (M-P)</th>\n",
       "      <th>ΔKd, Roeder (M-P)</th>\n",
       "      <th>ΔKd, Matzen (M-P)</th>\n",
       "      <th>ΔKd, Shea (M-P)</th>\n",
       "      <th>SiO2_Liq</th>\n",
       "      <th>TiO2_Liq</th>\n",
       "      <th>...</th>\n",
       "      <th>Al_Ol_cat_frac</th>\n",
       "      <th>Na_Ol_cat_frac</th>\n",
       "      <th>K_Ol_cat_frac</th>\n",
       "      <th>Mn_Ol_cat_frac</th>\n",
       "      <th>Ti_Ol_cat_frac</th>\n",
       "      <th>DMg_Meas</th>\n",
       "      <th>CNML</th>\n",
       "      <th>CSiO2L</th>\n",
       "      <th>NF</th>\n",
       "      <th>Den_Beat93</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1423.494959</td>\n",
       "      <td>0.839462</td>\n",
       "      <td>0.168506</td>\n",
       "      <td>0.287209</td>\n",
       "      <td>-0.118703</td>\n",
       "      <td>-0.131494</td>\n",
       "      <td>-0.171494</td>\n",
       "      <td>-0.166494</td>\n",
       "      <td>50.6243</td>\n",
       "      <td>2.87730</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000399</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001461</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.613445</td>\n",
       "      <td>0.286926</td>\n",
       "      <td>0.488362</td>\n",
       "      <td>-0.709158</td>\n",
       "      <td>9.825288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1427.581425</td>\n",
       "      <td>0.864445</td>\n",
       "      <td>0.176704</td>\n",
       "      <td>0.288398</td>\n",
       "      <td>-0.111695</td>\n",
       "      <td>-0.123296</td>\n",
       "      <td>-0.163296</td>\n",
       "      <td>-0.158296</td>\n",
       "      <td>50.0975</td>\n",
       "      <td>2.88400</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000399</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001461</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.510601</td>\n",
       "      <td>0.283867</td>\n",
       "      <td>0.490494</td>\n",
       "      <td>-0.713838</td>\n",
       "      <td>9.785899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1425.597182</td>\n",
       "      <td>0.877020</td>\n",
       "      <td>0.168533</td>\n",
       "      <td>0.287756</td>\n",
       "      <td>-0.119223</td>\n",
       "      <td>-0.131467</td>\n",
       "      <td>-0.171467</td>\n",
       "      <td>-0.166467</td>\n",
       "      <td>50.1346</td>\n",
       "      <td>2.87410</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000399</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001461</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.548023</td>\n",
       "      <td>0.288897</td>\n",
       "      <td>0.486713</td>\n",
       "      <td>-0.707200</td>\n",
       "      <td>9.810375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1426.830801</td>\n",
       "      <td>0.819485</td>\n",
       "      <td>0.176165</td>\n",
       "      <td>0.285916</td>\n",
       "      <td>-0.109751</td>\n",
       "      <td>-0.123835</td>\n",
       "      <td>-0.163835</td>\n",
       "      <td>-0.158835</td>\n",
       "      <td>50.5233</td>\n",
       "      <td>2.87650</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000399</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001461</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.563785</td>\n",
       "      <td>0.283546</td>\n",
       "      <td>0.489384</td>\n",
       "      <td>-0.709681</td>\n",
       "      <td>9.791213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1420.924109</td>\n",
       "      <td>0.880391</td>\n",
       "      <td>0.173241</td>\n",
       "      <td>0.294867</td>\n",
       "      <td>-0.121626</td>\n",
       "      <td>-0.126759</td>\n",
       "      <td>-0.166759</td>\n",
       "      <td>-0.161759</td>\n",
       "      <td>51.5840</td>\n",
       "      <td>2.90550</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000399</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001461</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.631816</td>\n",
       "      <td>0.281814</td>\n",
       "      <td>0.496419</td>\n",
       "      <td>-0.722465</td>\n",
       "      <td>9.840915</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",
       "      <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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>432</th>\n",
       "      <td>1447.022100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.253368</td>\n",
       "      <td>0.297809</td>\n",
       "      <td>-0.044441</td>\n",
       "      <td>-0.046632</td>\n",
       "      <td>-0.086632</td>\n",
       "      <td>-0.081632</td>\n",
       "      <td>49.4837</td>\n",
       "      <td>2.87040</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000443</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001810</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.977917</td>\n",
       "      <td>0.289633</td>\n",
       "      <td>0.484568</td>\n",
       "      <td>-0.715446</td>\n",
       "      <td>9.632690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>1446.896632</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.252072</td>\n",
       "      <td>0.297970</td>\n",
       "      <td>-0.045898</td>\n",
       "      <td>-0.047928</td>\n",
       "      <td>-0.087928</td>\n",
       "      <td>-0.082928</td>\n",
       "      <td>49.6879</td>\n",
       "      <td>2.88715</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000443</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001810</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.985175</td>\n",
       "      <td>0.289672</td>\n",
       "      <td>0.485115</td>\n",
       "      <td>-0.711773</td>\n",
       "      <td>9.633974</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>1441.532415</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.240536</td>\n",
       "      <td>0.296134</td>\n",
       "      <td>-0.055598</td>\n",
       "      <td>-0.059464</td>\n",
       "      <td>-0.099464</td>\n",
       "      <td>-0.094464</td>\n",
       "      <td>50.6177</td>\n",
       "      <td>2.82230</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000443</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001810</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.159819</td>\n",
       "      <td>0.285566</td>\n",
       "      <td>0.486791</td>\n",
       "      <td>-0.713133</td>\n",
       "      <td>9.671203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>435</th>\n",
       "      <td>1445.556449</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.247346</td>\n",
       "      <td>0.298063</td>\n",
       "      <td>-0.050717</td>\n",
       "      <td>-0.052654</td>\n",
       "      <td>-0.092654</td>\n",
       "      <td>-0.087654</td>\n",
       "      <td>50.9821</td>\n",
       "      <td>2.81450</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000443</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001810</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.040965</td>\n",
       "      <td>0.286894</td>\n",
       "      <td>0.489008</td>\n",
       "      <td>-0.703872</td>\n",
       "      <td>9.641341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>1443.554425</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.243931</td>\n",
       "      <td>0.297099</td>\n",
       "      <td>-0.053168</td>\n",
       "      <td>-0.056069</td>\n",
       "      <td>-0.096069</td>\n",
       "      <td>-0.091069</td>\n",
       "      <td>50.7999</td>\n",
       "      <td>2.81840</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000443</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001810</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.099735</td>\n",
       "      <td>0.286231</td>\n",
       "      <td>0.487901</td>\n",
       "      <td>-0.708494</td>\n",
       "      <td>9.656165</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>437 rows × 78 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        T_K_calc  Ol_Fo_Meas   Kd Meas  Kd calc (Toplis)  ΔKd, Toplis (M-P)  \\\n",
       "0    1423.494959    0.839462  0.168506          0.287209          -0.118703   \n",
       "1    1427.581425    0.864445  0.176704          0.288398          -0.111695   \n",
       "2    1425.597182    0.877020  0.168533          0.287756          -0.119223   \n",
       "3    1426.830801    0.819485  0.176165          0.285916          -0.109751   \n",
       "4    1420.924109    0.880391  0.173241          0.294867          -0.121626   \n",
       "..           ...         ...       ...               ...                ...   \n",
       "432  1447.022100         NaN  0.253368          0.297809          -0.044441   \n",
       "433  1446.896632         NaN  0.252072          0.297970          -0.045898   \n",
       "434  1441.532415         NaN  0.240536          0.296134          -0.055598   \n",
       "435  1445.556449         NaN  0.247346          0.298063          -0.050717   \n",
       "436  1443.554425         NaN  0.243931          0.297099          -0.053168   \n",
       "\n",
       "     ΔKd, Roeder (M-P)  ΔKd, Matzen (M-P)  ΔKd, Shea (M-P)  SiO2_Liq  \\\n",
       "0            -0.131494          -0.171494        -0.166494   50.6243   \n",
       "1            -0.123296          -0.163296        -0.158296   50.0975   \n",
       "2            -0.131467          -0.171467        -0.166467   50.1346   \n",
       "3            -0.123835          -0.163835        -0.158835   50.5233   \n",
       "4            -0.126759          -0.166759        -0.161759   51.5840   \n",
       "..                 ...                ...              ...       ...   \n",
       "432          -0.046632          -0.086632        -0.081632   49.4837   \n",
       "433          -0.047928          -0.087928        -0.082928   49.6879   \n",
       "434          -0.059464          -0.099464        -0.094464   50.6177   \n",
       "435          -0.052654          -0.092654        -0.087654   50.9821   \n",
       "436          -0.056069          -0.096069        -0.091069   50.7999   \n",
       "\n",
       "     TiO2_Liq  ...  Al_Ol_cat_frac  Na_Ol_cat_frac  K_Ol_cat_frac  \\\n",
       "0     2.87730  ...        0.000399             0.0            0.0   \n",
       "1     2.88400  ...        0.000399             0.0            0.0   \n",
       "2     2.87410  ...        0.000399             0.0            0.0   \n",
       "3     2.87650  ...        0.000399             0.0            0.0   \n",
       "4     2.90550  ...        0.000399             0.0            0.0   \n",
       "..        ...  ...             ...             ...            ...   \n",
       "432   2.87040  ...        0.000443             0.0            0.0   \n",
       "433   2.88715  ...        0.000443             0.0            0.0   \n",
       "434   2.82230  ...        0.000443             0.0            0.0   \n",
       "435   2.81450  ...        0.000443             0.0            0.0   \n",
       "436   2.81840  ...        0.000443             0.0            0.0   \n",
       "\n",
       "     Mn_Ol_cat_frac  Ti_Ol_cat_frac  DMg_Meas      CNML    CSiO2L        NF  \\\n",
       "0          0.001461             0.0  6.613445  0.286926  0.488362 -0.709158   \n",
       "1          0.001461             0.0  6.510601  0.283867  0.490494 -0.713838   \n",
       "2          0.001461             0.0  6.548023  0.288897  0.486713 -0.707200   \n",
       "3          0.001461             0.0  6.563785  0.283546  0.489384 -0.709681   \n",
       "4          0.001461             0.0  6.631816  0.281814  0.496419 -0.722465   \n",
       "..              ...             ...       ...       ...       ...       ...   \n",
       "432        0.001810             0.0  5.977917  0.289633  0.484568 -0.715446   \n",
       "433        0.001810             0.0  5.985175  0.289672  0.485115 -0.711773   \n",
       "434        0.001810             0.0  6.159819  0.285566  0.486791 -0.713133   \n",
       "435        0.001810             0.0  6.040965  0.286894  0.489008 -0.703872   \n",
       "436        0.001810             0.0  6.099735  0.286231  0.487901 -0.708494   \n",
       "\n",
       "     Den_Beat93  \n",
       "0      9.825288  \n",
       "1      9.785899  \n",
       "2      9.810375  \n",
       "3      9.791213  \n",
       "4      9.840915  \n",
       "..          ...  \n",
       "432    9.632690  \n",
       "433    9.633974  \n",
       "434    9.671203  \n",
       "435    9.641341  \n",
       "436    9.656165  \n",
       "\n",
       "[437 rows x 78 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eq22_PHinput_30Fe3_Matching=pt.calculate_ol_liq_temp_matching(liq_comps=MGs2018,\n",
    "                                        ol_comps=Ols2018,  \n",
    "                                      equationT=\"T_Put2008_eq22\", P=5, \n",
    "                                        Fe3Fet_Liq=0.3, eq_tests=True)\n",
    "eq22_PHinput_30Fe3_Matching"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "85f7762b-4b01-4f53-ab0f-4825df31a56b",
   "metadata": {},
   "source": [
    "## Example 3 - Calculating equilibrium olivine Fo contents based on the liquid composition"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d949b5b5-8482-4b26-af67-4dc869eba574",
   "metadata": {},
   "source": [
    "### 3a - Roeder and Emslie, 1970\n",
    "- Here, using the Kd model of Roeder and Emslie, 1970, Kd=0.03+-0.03, for 20% Fe3\n",
    "- The function returns the Mg# of the liquid using Fe2+ based on the Fe3Fet ratio from the input spreadsheet, or specified by the user in the function (as in this example)\n",
    "- The Fet assumes that all Fe in the olivine and liquid is Fe2+\n",
    "- The Eq Fo contents are calculated using the Mg# with just Fe2, based on the Kd model shown in brackets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bff1b647-0b4e-47c1-9671-82bbb74ba844",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mg#_Liq_Fe2</th>\n",
       "      <th>Mg#_Liq_Fet</th>\n",
       "      <th>Eq Fo (Roeder, Kd=0.3)</th>\n",
       "      <th>Eq Fo (Roeder, Kd=0.33)</th>\n",
       "      <th>Eq Fo (Roeder, Kd=0.27)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.681666</td>\n",
       "      <td>0.631416</td>\n",
       "      <td>0.877117</td>\n",
       "      <td>0.866470</td>\n",
       "      <td>0.888030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.620707</td>\n",
       "      <td>0.566947</td>\n",
       "      <td>0.845080</td>\n",
       "      <td>0.832188</td>\n",
       "      <td>0.858378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.578196</td>\n",
       "      <td>0.523041</td>\n",
       "      <td>0.820442</td>\n",
       "      <td>0.805970</td>\n",
       "      <td>0.835443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.523445</td>\n",
       "      <td>0.467721</td>\n",
       "      <td>0.785468</td>\n",
       "      <td>0.768971</td>\n",
       "      <td>0.802688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.586967</td>\n",
       "      <td>0.532031</td>\n",
       "      <td>0.825694</td>\n",
       "      <td>0.811549</td>\n",
       "      <td>0.840342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.565465</td>\n",
       "      <td>0.510056</td>\n",
       "      <td>0.812653</td>\n",
       "      <td>0.797709</td>\n",
       "      <td>0.828169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.528731</td>\n",
       "      <td>0.473003</td>\n",
       "      <td>0.789019</td>\n",
       "      <td>0.772716</td>\n",
       "      <td>0.806025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.620033</td>\n",
       "      <td>0.566244</td>\n",
       "      <td>0.844705</td>\n",
       "      <td>0.831788</td>\n",
       "      <td>0.858030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.583864</td>\n",
       "      <td>0.528846</td>\n",
       "      <td>0.823846</td>\n",
       "      <td>0.809585</td>\n",
       "      <td>0.838619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.665729</td>\n",
       "      <td>0.614386</td>\n",
       "      <td>0.869086</td>\n",
       "      <td>0.857856</td>\n",
       "      <td>0.880615</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Mg#_Liq_Fe2  Mg#_Liq_Fet  Eq Fo (Roeder, Kd=0.3)  Eq Fo (Roeder, Kd=0.33)  \\\n",
       "0     0.681666     0.631416                0.877117                 0.866470   \n",
       "1     0.620707     0.566947                0.845080                 0.832188   \n",
       "2     0.578196     0.523041                0.820442                 0.805970   \n",
       "3     0.523445     0.467721                0.785468                 0.768971   \n",
       "4     0.586967     0.532031                0.825694                 0.811549   \n",
       "5     0.565465     0.510056                0.812653                 0.797709   \n",
       "6     0.528731     0.473003                0.789019                 0.772716   \n",
       "7     0.620033     0.566244                0.844705                 0.831788   \n",
       "8     0.583864     0.528846                0.823846                 0.809585   \n",
       "9     0.665729     0.614386                0.869086                 0.857856   \n",
       "\n",
       "   Eq Fo (Roeder, Kd=0.27)  \n",
       "0                 0.888030  \n",
       "1                 0.858378  \n",
       "2                 0.835443  \n",
       "3                 0.802688  \n",
       "4                 0.840342  \n",
       "5                 0.828169  \n",
       "6                 0.806025  \n",
       "7                 0.858030  \n",
       "8                 0.838619  \n",
       "9                 0.880615  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Eq_Ol_Roeder=pt.calculate_eq_ol_content(liq_comps=myLiquids1, Kd_model=\"Roeder1970\")\n",
    "Eq_Ol_Roeder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "98ec73fb-af2e-4f58-ab40-2c3ed9ad0479",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mg#_Liq_Fe2</th>\n",
       "      <th>Mg#_Liq_Fet</th>\n",
       "      <th>Eq Fo (Roeder, Kd=0.3)</th>\n",
       "      <th>Eq Fo (Roeder, Kd=0.33)</th>\n",
       "      <th>Eq Fo (Roeder, Kd=0.27)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.681666</td>\n",
       "      <td>0.631416</td>\n",
       "      <td>0.877117</td>\n",
       "      <td>0.866470</td>\n",
       "      <td>0.888030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.620707</td>\n",
       "      <td>0.566947</td>\n",
       "      <td>0.845080</td>\n",
       "      <td>0.832188</td>\n",
       "      <td>0.858378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.578196</td>\n",
       "      <td>0.523041</td>\n",
       "      <td>0.820442</td>\n",
       "      <td>0.805970</td>\n",
       "      <td>0.835443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.523445</td>\n",
       "      <td>0.467721</td>\n",
       "      <td>0.785468</td>\n",
       "      <td>0.768971</td>\n",
       "      <td>0.802688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.586967</td>\n",
       "      <td>0.532031</td>\n",
       "      <td>0.825694</td>\n",
       "      <td>0.811549</td>\n",
       "      <td>0.840342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.565465</td>\n",
       "      <td>0.510056</td>\n",
       "      <td>0.812653</td>\n",
       "      <td>0.797709</td>\n",
       "      <td>0.828169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.528731</td>\n",
       "      <td>0.473003</td>\n",
       "      <td>0.789019</td>\n",
       "      <td>0.772716</td>\n",
       "      <td>0.806025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.620033</td>\n",
       "      <td>0.566244</td>\n",
       "      <td>0.844705</td>\n",
       "      <td>0.831788</td>\n",
       "      <td>0.858030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.583864</td>\n",
       "      <td>0.528846</td>\n",
       "      <td>0.823846</td>\n",
       "      <td>0.809585</td>\n",
       "      <td>0.838619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.665729</td>\n",
       "      <td>0.614386</td>\n",
       "      <td>0.869086</td>\n",
       "      <td>0.857856</td>\n",
       "      <td>0.880615</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Mg#_Liq_Fe2  Mg#_Liq_Fet  Eq Fo (Roeder, Kd=0.3)  Eq Fo (Roeder, Kd=0.33)  \\\n",
       "0     0.681666     0.631416                0.877117                 0.866470   \n",
       "1     0.620707     0.566947                0.845080                 0.832188   \n",
       "2     0.578196     0.523041                0.820442                 0.805970   \n",
       "3     0.523445     0.467721                0.785468                 0.768971   \n",
       "4     0.586967     0.532031                0.825694                 0.811549   \n",
       "5     0.565465     0.510056                0.812653                 0.797709   \n",
       "6     0.528731     0.473003                0.789019                 0.772716   \n",
       "7     0.620033     0.566244                0.844705                 0.831788   \n",
       "8     0.583864     0.528846                0.823846                 0.809585   \n",
       "9     0.665729     0.614386                0.869086                 0.857856   \n",
       "\n",
       "   Eq Fo (Roeder, Kd=0.27)  \n",
       "0                 0.888030  \n",
       "1                 0.858378  \n",
       "2                 0.835443  \n",
       "3                 0.802688  \n",
       "4                 0.840342  \n",
       "5                 0.828169  \n",
       "6                 0.806025  \n",
       "7                 0.858030  \n",
       "8                 0.838619  \n",
       "9                 0.880615  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Eq_Ol_Roeder=pt.calculate_eq_ol_content(liq_comps=myLiquids1, Kd_model=\"Roeder1970\", Fe3Fet_Liq=0.2)\n",
    "Eq_Ol_Roeder"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e041c6e-fe3f-4b0a-96ec-52a9a5f2d0a1",
   "metadata": {},
   "source": [
    "- If you also specify the olivine compositions, it will add the measured Fo content as a column for comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f64f1720-ade3-499b-bcbb-e7364de22fe5",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mg#_Liq_Fe2</th>\n",
       "      <th>Mg#_Liq_Fet</th>\n",
       "      <th>Eq Fo (Roeder, Kd=0.3)</th>\n",
       "      <th>Eq Fo (Roeder, Kd=0.33)</th>\n",
       "      <th>Eq Fo (Roeder, Kd=0.27)</th>\n",
       "      <th>Fo_meas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.681666</td>\n",
       "      <td>0.631416</td>\n",
       "      <td>0.877117</td>\n",
       "      <td>0.866470</td>\n",
       "      <td>0.888030</td>\n",
       "      <td>0.872023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.620707</td>\n",
       "      <td>0.566947</td>\n",
       "      <td>0.845080</td>\n",
       "      <td>0.832188</td>\n",
       "      <td>0.858378</td>\n",
       "      <td>0.903203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.578196</td>\n",
       "      <td>0.523041</td>\n",
       "      <td>0.820442</td>\n",
       "      <td>0.805970</td>\n",
       "      <td>0.835443</td>\n",
       "      <td>0.835656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.523445</td>\n",
       "      <td>0.467721</td>\n",
       "      <td>0.785468</td>\n",
       "      <td>0.768971</td>\n",
       "      <td>0.802688</td>\n",
       "      <td>0.863386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.586967</td>\n",
       "      <td>0.532031</td>\n",
       "      <td>0.825694</td>\n",
       "      <td>0.811549</td>\n",
       "      <td>0.840342</td>\n",
       "      <td>0.903278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.565465</td>\n",
       "      <td>0.510056</td>\n",
       "      <td>0.812653</td>\n",
       "      <td>0.797709</td>\n",
       "      <td>0.828169</td>\n",
       "      <td>0.890781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.528731</td>\n",
       "      <td>0.473003</td>\n",
       "      <td>0.789019</td>\n",
       "      <td>0.772716</td>\n",
       "      <td>0.806025</td>\n",
       "      <td>0.838609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.620033</td>\n",
       "      <td>0.566244</td>\n",
       "      <td>0.844705</td>\n",
       "      <td>0.831788</td>\n",
       "      <td>0.858030</td>\n",
       "      <td>0.801278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.583864</td>\n",
       "      <td>0.528846</td>\n",
       "      <td>0.823846</td>\n",
       "      <td>0.809585</td>\n",
       "      <td>0.838619</td>\n",
       "      <td>0.817074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.665729</td>\n",
       "      <td>0.614386</td>\n",
       "      <td>0.869086</td>\n",
       "      <td>0.857856</td>\n",
       "      <td>0.880615</td>\n",
       "      <td>0.822724</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Mg#_Liq_Fe2  Mg#_Liq_Fet  Eq Fo (Roeder, Kd=0.3)  Eq Fo (Roeder, Kd=0.33)  \\\n",
       "0     0.681666     0.631416                0.877117                 0.866470   \n",
       "1     0.620707     0.566947                0.845080                 0.832188   \n",
       "2     0.578196     0.523041                0.820442                 0.805970   \n",
       "3     0.523445     0.467721                0.785468                 0.768971   \n",
       "4     0.586967     0.532031                0.825694                 0.811549   \n",
       "5     0.565465     0.510056                0.812653                 0.797709   \n",
       "6     0.528731     0.473003                0.789019                 0.772716   \n",
       "7     0.620033     0.566244                0.844705                 0.831788   \n",
       "8     0.583864     0.528846                0.823846                 0.809585   \n",
       "9     0.665729     0.614386                0.869086                 0.857856   \n",
       "\n",
       "   Eq Fo (Roeder, Kd=0.27)   Fo_meas  \n",
       "0                 0.888030  0.872023  \n",
       "1                 0.858378  0.903203  \n",
       "2                 0.835443  0.835656  \n",
       "3                 0.802688  0.863386  \n",
       "4                 0.840342  0.903278  \n",
       "5                 0.828169  0.890781  \n",
       "6                 0.806025  0.838609  \n",
       "7                 0.858030  0.801278  \n",
       "8                 0.838619  0.817074  \n",
       "9                 0.880615  0.822724  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Eq_Ol_Roeder=pt.calculate_eq_ol_content(liq_comps=myLiquids1, ol_comps=myOls1,\n",
    "                                     Kd_model=\"Roeder1970\", Fe3Fet_Liq=0.2)\n",
    "Eq_Ol_Roeder"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a3d2c74-a66e-4aae-9fcc-6a8e1d13a991",
   "metadata": {},
   "source": [
    "- We can also specify to use the Kd model of Matzen (2011), where Kd=0.34 +-0.012"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d2f4128e-4da5-4d6f-ab9d-d0ab316f0a78",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mg#_Liq_Fe2</th>\n",
       "      <th>Mg#_Liq_Fet</th>\n",
       "      <th>Eq Fo (Matzen, Kd=0.34)</th>\n",
       "      <th>Eq Fo (Matzen, Kd=0.352)</th>\n",
       "      <th>Eq Fo (Matzen, Kd=0.328)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.681666</td>\n",
       "      <td>0.631416</td>\n",
       "      <td>0.862978</td>\n",
       "      <td>0.858825</td>\n",
       "      <td>0.867172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.620707</td>\n",
       "      <td>0.566947</td>\n",
       "      <td>0.827977</td>\n",
       "      <td>0.822980</td>\n",
       "      <td>0.833035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.578196</td>\n",
       "      <td>0.523041</td>\n",
       "      <td>0.801259</td>\n",
       "      <td>0.795678</td>\n",
       "      <td>0.806919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.523445</td>\n",
       "      <td>0.467721</td>\n",
       "      <td>0.763625</td>\n",
       "      <td>0.757307</td>\n",
       "      <td>0.770049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.586967</td>\n",
       "      <td>0.532031</td>\n",
       "      <td>0.806941</td>\n",
       "      <td>0.801479</td>\n",
       "      <td>0.812477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.565465</td>\n",
       "      <td>0.510056</td>\n",
       "      <td>0.792848</td>\n",
       "      <td>0.787094</td>\n",
       "      <td>0.798688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.528731</td>\n",
       "      <td>0.473003</td>\n",
       "      <td>0.767431</td>\n",
       "      <td>0.761182</td>\n",
       "      <td>0.773782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.620033</td>\n",
       "      <td>0.566244</td>\n",
       "      <td>0.827569</td>\n",
       "      <td>0.822563</td>\n",
       "      <td>0.832637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.583864</td>\n",
       "      <td>0.528846</td>\n",
       "      <td>0.804941</td>\n",
       "      <td>0.799437</td>\n",
       "      <td>0.810521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.665729</td>\n",
       "      <td>0.614386</td>\n",
       "      <td>0.854176</td>\n",
       "      <td>0.849803</td>\n",
       "      <td>0.858595</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Mg#_Liq_Fe2  Mg#_Liq_Fet  Eq Fo (Matzen, Kd=0.34)  \\\n",
       "0     0.681666     0.631416                 0.862978   \n",
       "1     0.620707     0.566947                 0.827977   \n",
       "2     0.578196     0.523041                 0.801259   \n",
       "3     0.523445     0.467721                 0.763625   \n",
       "4     0.586967     0.532031                 0.806941   \n",
       "5     0.565465     0.510056                 0.792848   \n",
       "6     0.528731     0.473003                 0.767431   \n",
       "7     0.620033     0.566244                 0.827569   \n",
       "8     0.583864     0.528846                 0.804941   \n",
       "9     0.665729     0.614386                 0.854176   \n",
       "\n",
       "   Eq Fo (Matzen, Kd=0.352)  Eq Fo (Matzen, Kd=0.328)  \n",
       "0                  0.858825                  0.867172  \n",
       "1                  0.822980                  0.833035  \n",
       "2                  0.795678                  0.806919  \n",
       "3                  0.757307                  0.770049  \n",
       "4                  0.801479                  0.812477  \n",
       "5                  0.787094                  0.798688  \n",
       "6                  0.761182                  0.773782  \n",
       "7                  0.822563                  0.832637  \n",
       "8                  0.799437                  0.810521  \n",
       "9                  0.849803                  0.858595  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Eq_Ol_Matzen=pt.calculate_eq_ol_content(liq_comps=myLiquids1,\n",
    "                                        Kd_model=\"Matzen2011\", Fe3Fet_Liq=0.2)\n",
    "Eq_Ol_Matzen"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "139e3d1c-b285-4d20-ad6d-74b44b8b6377",
   "metadata": {},
   "source": [
    "### 3b - Toplis, 2005\n",
    "- This Kd expression is a bit more complicated, because the Toplis model is dependent on melt composition, as well as pressure, temperature, water content, and the olivine forsterite content \n",
    "- There are a number of options, firstly, you can specify a fixed olivine Fo content, P and T from input spreadsheet to perform calculations at "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "07621521-2d2d-4df9-970e-3a7ce9c2ffc5",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mg#_Liq_Fe2</th>\n",
       "      <th>Mg#_Liq_Fet</th>\n",
       "      <th>Kd (Toplis, input Fo)</th>\n",
       "      <th>Eq Fo (Toplis, input Fo)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.681666</td>\n",
       "      <td>0.631416</td>\n",
       "      <td>0.343939</td>\n",
       "      <td>0.861610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.620707</td>\n",
       "      <td>0.566947</td>\n",
       "      <td>0.354888</td>\n",
       "      <td>0.821787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.578196</td>\n",
       "      <td>0.523041</td>\n",
       "      <td>0.339995</td>\n",
       "      <td>0.801262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.523445</td>\n",
       "      <td>0.467721</td>\n",
       "      <td>0.343036</td>\n",
       "      <td>0.762017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.586967</td>\n",
       "      <td>0.532031</td>\n",
       "      <td>0.373208</td>\n",
       "      <td>0.792006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.565465</td>\n",
       "      <td>0.510056</td>\n",
       "      <td>0.372049</td>\n",
       "      <td>0.777663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.528731</td>\n",
       "      <td>0.473003</td>\n",
       "      <td>0.365932</td>\n",
       "      <td>0.754055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.620033</td>\n",
       "      <td>0.566244</td>\n",
       "      <td>0.451357</td>\n",
       "      <td>0.783331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.583864</td>\n",
       "      <td>0.528846</td>\n",
       "      <td>0.434877</td>\n",
       "      <td>0.763388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.665729</td>\n",
       "      <td>0.614386</td>\n",
       "      <td>0.336976</td>\n",
       "      <td>0.855286</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Mg#_Liq_Fe2  Mg#_Liq_Fet  Kd (Toplis, input Fo)  Eq Fo (Toplis, input Fo)\n",
       "0     0.681666     0.631416               0.343939                  0.861610\n",
       "1     0.620707     0.566947               0.354888                  0.821787\n",
       "2     0.578196     0.523041               0.339995                  0.801262\n",
       "3     0.523445     0.467721               0.343036                  0.762017\n",
       "4     0.586967     0.532031               0.373208                  0.792006\n",
       "5     0.565465     0.510056               0.372049                  0.777663\n",
       "6     0.528731     0.473003               0.365932                  0.754055\n",
       "7     0.620033     0.566244               0.451357                  0.783331\n",
       "8     0.583864     0.528846               0.434877                  0.763388\n",
       "9     0.665729     0.614386               0.336976                  0.855286"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Eq_Ol_Toplis_FixedFo=pt.calculate_eq_ol_content(liq_comps=myLiquids1, Kd_model=\"Toplis2005\", Fe3Fet_Liq=0.2, \n",
    "                     P=my_input['P_kbar'], T=my_input['Temperature_C']+273.15, ol_fo=0.8)\n",
    "Eq_Ol_Toplis_FixedFo"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b477c24-7b9c-4e7f-8344-d80c3c8b644c",
   "metadata": {},
   "source": [
    "- Can do the same, but input olivine compositions, so the function uses the Fo content of each row to perform calculations (rather than a fixed Fo content)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "22df8a19-f5ab-4dbf-979c-e00a65a57a3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mg#_Liq_Fe2</th>\n",
       "      <th>Mg#_Liq_Fet</th>\n",
       "      <th>Kd (Toplis, input Fo)</th>\n",
       "      <th>Eq Fo (Toplis, input Fo)</th>\n",
       "      <th>Fo_meas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.681666</td>\n",
       "      <td>0.631416</td>\n",
       "      <td>0.262240</td>\n",
       "      <td>0.890897</td>\n",
       "      <td>0.872023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.620707</td>\n",
       "      <td>0.566947</td>\n",
       "      <td>0.270643</td>\n",
       "      <td>0.858089</td>\n",
       "      <td>0.903203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.578196</td>\n",
       "      <td>0.523041</td>\n",
       "      <td>0.276728</td>\n",
       "      <td>0.832031</td>\n",
       "      <td>0.835656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.523445</td>\n",
       "      <td>0.467721</td>\n",
       "      <td>0.274170</td>\n",
       "      <td>0.800249</td>\n",
       "      <td>0.863386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.586967</td>\n",
       "      <td>0.532031</td>\n",
       "      <td>0.290580</td>\n",
       "      <td>0.830239</td>\n",
       "      <td>0.903278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.565465</td>\n",
       "      <td>0.510056</td>\n",
       "      <td>0.292062</td>\n",
       "      <td>0.816702</td>\n",
       "      <td>0.890781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.528731</td>\n",
       "      <td>0.473003</td>\n",
       "      <td>0.297262</td>\n",
       "      <td>0.790541</td>\n",
       "      <td>0.838609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.620033</td>\n",
       "      <td>0.566244</td>\n",
       "      <td>0.375747</td>\n",
       "      <td>0.812833</td>\n",
       "      <td>0.801278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.583864</td>\n",
       "      <td>0.528846</td>\n",
       "      <td>0.358296</td>\n",
       "      <td>0.796579</td>\n",
       "      <td>0.817074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.665729</td>\n",
       "      <td>0.614386</td>\n",
       "      <td>0.276607</td>\n",
       "      <td>0.878049</td>\n",
       "      <td>0.822724</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Mg#_Liq_Fe2  Mg#_Liq_Fet  Kd (Toplis, input Fo)  Eq Fo (Toplis, input Fo)  \\\n",
       "0     0.681666     0.631416               0.262240                  0.890897   \n",
       "1     0.620707     0.566947               0.270643                  0.858089   \n",
       "2     0.578196     0.523041               0.276728                  0.832031   \n",
       "3     0.523445     0.467721               0.274170                  0.800249   \n",
       "4     0.586967     0.532031               0.290580                  0.830239   \n",
       "5     0.565465     0.510056               0.292062                  0.816702   \n",
       "6     0.528731     0.473003               0.297262                  0.790541   \n",
       "7     0.620033     0.566244               0.375747                  0.812833   \n",
       "8     0.583864     0.528846               0.358296                  0.796579   \n",
       "9     0.665729     0.614386               0.276607                  0.878049   \n",
       "\n",
       "    Fo_meas  \n",
       "0  0.872023  \n",
       "1  0.903203  \n",
       "2  0.835656  \n",
       "3  0.863386  \n",
       "4  0.903278  \n",
       "5  0.890781  \n",
       "6  0.838609  \n",
       "7  0.801278  \n",
       "8  0.817074  \n",
       "9  0.822724  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Eq_Ol_Toplis_FixedFo2=pt.calculate_eq_ol_content(liq_comps=myLiquids1, ol_comps=myOls1,\n",
    "        Kd_model=\"Toplis2005\", Fe3Fet_Liq=0.2, P=my_input['P_kbar'], T=my_input['Temperature_C'])\n",
    "Eq_Ol_Toplis_FixedFo2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a99e8c29-ba07-4b37-8f0d-3264dc4f1217",
   "metadata": {},
   "source": [
    "- However, this is clearly a bit of a backwards arguement if olivines and liquids aren't in equilibrium, because that Fo content isn't relevant, and you are having to use a Fo content to calculate a Fo content...\n",
    "- Instead, if you don't specify Fo or an olivine content, the function will iterate Kd and olivine Fo content, starting from an olivine Fo content of 0.95 to reach an olivine content in equilibrium with your liquid for the toplis model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "76084416-85a3-43f2-8157-a559326f3b29",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mg#_Liq_Fe2</th>\n",
       "      <th>Mg#_Liq_Fet</th>\n",
       "      <th>Kd (Toplis, Iter)</th>\n",
       "      <th>Eq Fo (Toplis, Iter)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.681666</td>\n",
       "      <td>0.631416</td>\n",
       "      <td>0.340829</td>\n",
       "      <td>0.862690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.620707</td>\n",
       "      <td>0.566947</td>\n",
       "      <td>0.358919</td>\n",
       "      <td>0.820127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.578196</td>\n",
       "      <td>0.523041</td>\n",
       "      <td>0.345482</td>\n",
       "      <td>0.798700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.523445</td>\n",
       "      <td>0.467721</td>\n",
       "      <td>0.356696</td>\n",
       "      <td>0.754863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.586967</td>\n",
       "      <td>0.532031</td>\n",
       "      <td>0.381278</td>\n",
       "      <td>0.788460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.565465</td>\n",
       "      <td>0.510056</td>\n",
       "      <td>0.383301</td>\n",
       "      <td>0.772469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.528731</td>\n",
       "      <td>0.473003</td>\n",
       "      <td>0.382311</td>\n",
       "      <td>0.745844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.620033</td>\n",
       "      <td>0.566244</td>\n",
       "      <td>0.463462</td>\n",
       "      <td>0.778805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.583864</td>\n",
       "      <td>0.528846</td>\n",
       "      <td>0.451827</td>\n",
       "      <td>0.756413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.665729</td>\n",
       "      <td>0.614386</td>\n",
       "      <td>0.332066</td>\n",
       "      <td>0.857093</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Mg#_Liq_Fe2  Mg#_Liq_Fet  Kd (Toplis, Iter)  Eq Fo (Toplis, Iter)\n",
       "0     0.681666     0.631416           0.340829              0.862690\n",
       "1     0.620707     0.566947           0.358919              0.820127\n",
       "2     0.578196     0.523041           0.345482              0.798700\n",
       "3     0.523445     0.467721           0.356696              0.754863\n",
       "4     0.586967     0.532031           0.381278              0.788460\n",
       "5     0.565465     0.510056           0.383301              0.772469\n",
       "6     0.528731     0.473003           0.382311              0.745844\n",
       "7     0.620033     0.566244           0.463462              0.778805\n",
       "8     0.583864     0.528846           0.451827              0.756413\n",
       "9     0.665729     0.614386           0.332066              0.857093"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Eq_Ol_Toplis_IterFo=pt.calculate_eq_ol_content(liq_comps=myLiquids1, Kd_model=\"Toplis2005\", Fe3Fet_Liq=0.2, \n",
    "                                                P=10, T=my_input['Temperature_C']+273.15)\n",
    "Eq_Ol_Toplis_IterFo"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1b6fa85-3e70-470d-85e3-1164b6317dba",
   "metadata": {},
   "source": [
    "- You might not know temperature, which is needed for Toplis.\n",
    "- But, you have olivine-only thermometers at your fingertips, which can be input into the Eq ol content function.\n",
    "- Here we use one of the adapted olivine-liquid thermometers which use calulated DMg from the liquid rather than measured DMg."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "491784cb-0777-4b26-8659-32e9d2de5ab3",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mg#_Liq_Fe2</th>\n",
       "      <th>Mg#_Liq_Fet</th>\n",
       "      <th>Kd (Toplis, Iter)</th>\n",
       "      <th>Eq Fo (Toplis, Iter)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.681666</td>\n",
       "      <td>0.631416</td>\n",
       "      <td>0.336288</td>\n",
       "      <td>0.864271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.620707</td>\n",
       "      <td>0.566947</td>\n",
       "      <td>0.332721</td>\n",
       "      <td>0.831037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.578196</td>\n",
       "      <td>0.523041</td>\n",
       "      <td>0.324101</td>\n",
       "      <td>0.808775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.523445</td>\n",
       "      <td>0.467721</td>\n",
       "      <td>0.317484</td>\n",
       "      <td>0.775769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.586967</td>\n",
       "      <td>0.532031</td>\n",
       "      <td>0.354413</td>\n",
       "      <td>0.800390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.565465</td>\n",
       "      <td>0.510056</td>\n",
       "      <td>0.353012</td>\n",
       "      <td>0.786612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.528731</td>\n",
       "      <td>0.473003</td>\n",
       "      <td>0.349961</td>\n",
       "      <td>0.762237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.620033</td>\n",
       "      <td>0.566244</td>\n",
       "      <td>0.404831</td>\n",
       "      <td>0.801226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.583864</td>\n",
       "      <td>0.528846</td>\n",
       "      <td>0.385667</td>\n",
       "      <td>0.784390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.665729</td>\n",
       "      <td>0.614386</td>\n",
       "      <td>0.319173</td>\n",
       "      <td>0.861875</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Mg#_Liq_Fe2  Mg#_Liq_Fet  Kd (Toplis, Iter)  Eq Fo (Toplis, Iter)\n",
       "0     0.681666     0.631416           0.336288              0.864271\n",
       "1     0.620707     0.566947           0.332721              0.831037\n",
       "2     0.578196     0.523041           0.324101              0.808775\n",
       "3     0.523445     0.467721           0.317484              0.775769\n",
       "4     0.586967     0.532031           0.354413              0.800390\n",
       "5     0.565465     0.510056           0.353012              0.786612\n",
       "6     0.528731     0.473003           0.349961              0.762237\n",
       "7     0.620033     0.566244           0.404831              0.801226\n",
       "8     0.583864     0.528846           0.385667              0.784390\n",
       "9     0.665729     0.614386           0.319173              0.861875"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T_Calc_22=pt.calculate_liq_only_temp(liq_comps=myLiquids1, equationT=\"T_Put2008_eq22_BeattDMg\", \n",
    "                                     P=my_input['P_kbar'])\n",
    "\n",
    "Eq_Ol_Toplis_IterFo_calcT=pt.calculate_eq_ol_content(liq_comps=myLiquids1, Kd_model=\"Toplis2005\",\n",
    "                          Fe3Fet_Liq=0.2, P=my_input['P_kbar'], T=T_Calc_22)\n",
    "\n",
    "Eq_Ol_Toplis_IterFo_calcT"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b95b947f-42e8-4752-a334-945095a8cd44",
   "metadata": {},
   "source": [
    "### 3c - Putirka (2016)\n",
    "- Equations 8a-8c are for when the proportion of Fe3 is known\n",
    "- Equations 9a-c are for when Fe is entered as Fet\n",
    "- Equation 8b and 9b require pressure, so if a presure isn't entered, you dont get these outputs\n",
    "- Similarly, equation 9b requires an estimate of fo2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "a74acfd4-3c5c-4059-ba32-193adc15700d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "g:\\my drive\\postdoc\\pymme\\mybarometers\\thermobar_outer\\src\\Thermobar\\mineral_equilibrium.py:214: UserWarning: Putirka (2016) Kd models equation 8b and 9b are P-dependent you need to enter a P in kbar to get these outputs\n",
      "  w.warn(\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mg#_Liq_Fe2</th>\n",
       "      <th>Mg#_Liq_Fet</th>\n",
       "      <th>Eq Fo (Putirka 8a Fe2, Kd=0.33)</th>\n",
       "      <th>Eq Fo (Putirka 8a Fe2, Kd=0.33-0.044)</th>\n",
       "      <th>Eq Fo (Putirka 8a Fe2, Kd=0.33+0.044)</th>\n",
       "      <th>Calc Kd (Putirka 8c, Fe2)</th>\n",
       "      <th>Eq Fo (Putirka 8c Fe2)</th>\n",
       "      <th>Eq Fo (Putirka 9a Fet, Kd=0.29)</th>\n",
       "      <th>Eq Fo (Putirka 9a Fet, Kd=0.29-0.051)</th>\n",
       "      <th>Eq Fo (Putirka 9a Fet, Kd=0.29+0.051)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.681666</td>\n",
       "      <td>0.631416</td>\n",
       "      <td>0.866470</td>\n",
       "      <td>0.882176</td>\n",
       "      <td>0.851313</td>\n",
       "      <td>0.346039</td>\n",
       "      <td>0.860883</td>\n",
       "      <td>0.855223</td>\n",
       "      <td>0.877567</td>\n",
       "      <td>0.877567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.620707</td>\n",
       "      <td>0.566947</td>\n",
       "      <td>0.832188</td>\n",
       "      <td>0.851234</td>\n",
       "      <td>0.813975</td>\n",
       "      <td>0.346004</td>\n",
       "      <td>0.825469</td>\n",
       "      <td>0.818658</td>\n",
       "      <td>0.845626</td>\n",
       "      <td>0.845626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.578196</td>\n",
       "      <td>0.523041</td>\n",
       "      <td>0.805970</td>\n",
       "      <td>0.827375</td>\n",
       "      <td>0.785645</td>\n",
       "      <td>0.348050</td>\n",
       "      <td>0.797507</td>\n",
       "      <td>0.790858</td>\n",
       "      <td>0.821056</td>\n",
       "      <td>0.821056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.523445</td>\n",
       "      <td>0.467721</td>\n",
       "      <td>0.768971</td>\n",
       "      <td>0.793411</td>\n",
       "      <td>0.745992</td>\n",
       "      <td>0.349700</td>\n",
       "      <td>0.758510</td>\n",
       "      <td>0.751864</td>\n",
       "      <td>0.786171</td>\n",
       "      <td>0.786171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.586967</td>\n",
       "      <td>0.532031</td>\n",
       "      <td>0.811549</td>\n",
       "      <td>0.832466</td>\n",
       "      <td>0.791657</td>\n",
       "      <td>0.339147</td>\n",
       "      <td>0.807332</td>\n",
       "      <td>0.796761</td>\n",
       "      <td>0.826295</td>\n",
       "      <td>0.826295</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Mg#_Liq_Fe2  Mg#_Liq_Fet  Eq Fo (Putirka 8a Fe2, Kd=0.33)  \\\n",
       "0     0.681666     0.631416                         0.866470   \n",
       "1     0.620707     0.566947                         0.832188   \n",
       "2     0.578196     0.523041                         0.805970   \n",
       "3     0.523445     0.467721                         0.768971   \n",
       "4     0.586967     0.532031                         0.811549   \n",
       "\n",
       "   Eq Fo (Putirka 8a Fe2, Kd=0.33-0.044)  \\\n",
       "0                               0.882176   \n",
       "1                               0.851234   \n",
       "2                               0.827375   \n",
       "3                               0.793411   \n",
       "4                               0.832466   \n",
       "\n",
       "   Eq Fo (Putirka 8a Fe2, Kd=0.33+0.044)  Calc Kd (Putirka 8c, Fe2)  \\\n",
       "0                               0.851313                   0.346039   \n",
       "1                               0.813975                   0.346004   \n",
       "2                               0.785645                   0.348050   \n",
       "3                               0.745992                   0.349700   \n",
       "4                               0.791657                   0.339147   \n",
       "\n",
       "   Eq Fo (Putirka 8c Fe2)  Eq Fo (Putirka 9a Fet, Kd=0.29)  \\\n",
       "0                0.860883                         0.855223   \n",
       "1                0.825469                         0.818658   \n",
       "2                0.797507                         0.790858   \n",
       "3                0.758510                         0.751864   \n",
       "4                0.807332                         0.796761   \n",
       "\n",
       "   Eq Fo (Putirka 9a Fet, Kd=0.29-0.051)  \\\n",
       "0                               0.877567   \n",
       "1                               0.845626   \n",
       "2                               0.821056   \n",
       "3                               0.786171   \n",
       "4                               0.826295   \n",
       "\n",
       "   Eq Fo (Putirka 9a Fet, Kd=0.29+0.051)  \n",
       "0                               0.877567  \n",
       "1                               0.845626  \n",
       "2                               0.821056  \n",
       "3                               0.786171  \n",
       "4                               0.826295  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Here, we dont specify fo2 or P, so only get 8a, 8c, 9a +- errors back\n",
    "Eq_Ol_Put_noP_fo2=pt.calculate_eq_ol_content(liq_comps=myLiquids1, Kd_model=\"Putirka2016\", \n",
    "                  Fe3Fet_Liq=0.2)\n",
    "Eq_Ol_Put_noP_fo2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b26b681d-d66a-4c5b-93be-0f5752f1315d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mg#_Liq_Fe2</th>\n",
       "      <th>Mg#_Liq_Fet</th>\n",
       "      <th>Eq Fo (Putirka 8a Fe2, Kd=0.33)</th>\n",
       "      <th>Eq Fo (Putirka 8a Fe2, Kd=0.33-0.044)</th>\n",
       "      <th>Eq Fo (Putirka 8a Fe2, Kd=0.33+0.044)</th>\n",
       "      <th>Calc Kd (Putirka 8c, Fe2)</th>\n",
       "      <th>Eq Fo (Putirka 8c Fe2)</th>\n",
       "      <th>Eq Fo (Putirka 9a Fet, Kd=0.29)</th>\n",
       "      <th>Eq Fo (Putirka 9a Fet, Kd=0.29-0.051)</th>\n",
       "      <th>Eq Fo (Putirka 9a Fet, Kd=0.29+0.051)</th>\n",
       "      <th>Calc Kd (Putirka 8b, Fe2)</th>\n",
       "      <th>Eq Fo (Putirka 8b Fe2)</th>\n",
       "      <th>Calc Kd (Putirka 9b, Fet)</th>\n",
       "      <th>Eq Fo (Putirka 9b Fet)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.681666</td>\n",
       "      <td>0.631416</td>\n",
       "      <td>0.866470</td>\n",
       "      <td>0.882176</td>\n",
       "      <td>0.851313</td>\n",
       "      <td>0.346039</td>\n",
       "      <td>0.860883</td>\n",
       "      <td>0.855223</td>\n",
       "      <td>0.877567</td>\n",
       "      <td>0.877567</td>\n",
       "      <td>0.349228</td>\n",
       "      <td>0.859781</td>\n",
       "      <td>0.308935</td>\n",
       "      <td>0.873919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.620707</td>\n",
       "      <td>0.566947</td>\n",
       "      <td>0.832188</td>\n",
       "      <td>0.851234</td>\n",
       "      <td>0.813975</td>\n",
       "      <td>0.346004</td>\n",
       "      <td>0.825469</td>\n",
       "      <td>0.818658</td>\n",
       "      <td>0.845626</td>\n",
       "      <td>0.845626</td>\n",
       "      <td>0.349509</td>\n",
       "      <td>0.824013</td>\n",
       "      <td>0.307039</td>\n",
       "      <td>0.842019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.578196</td>\n",
       "      <td>0.523041</td>\n",
       "      <td>0.805970</td>\n",
       "      <td>0.827375</td>\n",
       "      <td>0.785645</td>\n",
       "      <td>0.348050</td>\n",
       "      <td>0.797507</td>\n",
       "      <td>0.790858</td>\n",
       "      <td>0.821056</td>\n",
       "      <td>0.821056</td>\n",
       "      <td>0.353321</td>\n",
       "      <td>0.795068</td>\n",
       "      <td>0.305758</td>\n",
       "      <td>0.817624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.523445</td>\n",
       "      <td>0.467721</td>\n",
       "      <td>0.768971</td>\n",
       "      <td>0.793411</td>\n",
       "      <td>0.745992</td>\n",
       "      <td>0.349700</td>\n",
       "      <td>0.758510</td>\n",
       "      <td>0.751864</td>\n",
       "      <td>0.786171</td>\n",
       "      <td>0.786171</td>\n",
       "      <td>0.355555</td>\n",
       "      <td>0.755456</td>\n",
       "      <td>0.308271</td>\n",
       "      <td>0.780850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.586967</td>\n",
       "      <td>0.532031</td>\n",
       "      <td>0.811549</td>\n",
       "      <td>0.832466</td>\n",
       "      <td>0.791657</td>\n",
       "      <td>0.339147</td>\n",
       "      <td>0.807332</td>\n",
       "      <td>0.796761</td>\n",
       "      <td>0.826295</td>\n",
       "      <td>0.826295</td>\n",
       "      <td>0.339543</td>\n",
       "      <td>0.807150</td>\n",
       "      <td>0.299996</td>\n",
       "      <td>0.825696</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Mg#_Liq_Fe2  Mg#_Liq_Fet  Eq Fo (Putirka 8a Fe2, Kd=0.33)  \\\n",
       "0     0.681666     0.631416                         0.866470   \n",
       "1     0.620707     0.566947                         0.832188   \n",
       "2     0.578196     0.523041                         0.805970   \n",
       "3     0.523445     0.467721                         0.768971   \n",
       "4     0.586967     0.532031                         0.811549   \n",
       "\n",
       "   Eq Fo (Putirka 8a Fe2, Kd=0.33-0.044)  \\\n",
       "0                               0.882176   \n",
       "1                               0.851234   \n",
       "2                               0.827375   \n",
       "3                               0.793411   \n",
       "4                               0.832466   \n",
       "\n",
       "   Eq Fo (Putirka 8a Fe2, Kd=0.33+0.044)  Calc Kd (Putirka 8c, Fe2)  \\\n",
       "0                               0.851313                   0.346039   \n",
       "1                               0.813975                   0.346004   \n",
       "2                               0.785645                   0.348050   \n",
       "3                               0.745992                   0.349700   \n",
       "4                               0.791657                   0.339147   \n",
       "\n",
       "   Eq Fo (Putirka 8c Fe2)  Eq Fo (Putirka 9a Fet, Kd=0.29)  \\\n",
       "0                0.860883                         0.855223   \n",
       "1                0.825469                         0.818658   \n",
       "2                0.797507                         0.790858   \n",
       "3                0.758510                         0.751864   \n",
       "4                0.807332                         0.796761   \n",
       "\n",
       "   Eq Fo (Putirka 9a Fet, Kd=0.29-0.051)  \\\n",
       "0                               0.877567   \n",
       "1                               0.845626   \n",
       "2                               0.821056   \n",
       "3                               0.786171   \n",
       "4                               0.826295   \n",
       "\n",
       "   Eq Fo (Putirka 9a Fet, Kd=0.29+0.051)  Calc Kd (Putirka 8b, Fe2)  \\\n",
       "0                               0.877567                   0.349228   \n",
       "1                               0.845626                   0.349509   \n",
       "2                               0.821056                   0.353321   \n",
       "3                               0.786171                   0.355555   \n",
       "4                               0.826295                   0.339543   \n",
       "\n",
       "   Eq Fo (Putirka 8b Fe2)  Calc Kd (Putirka 9b, Fet)  Eq Fo (Putirka 9b Fet)  \n",
       "0                0.859781                   0.308935                0.873919  \n",
       "1                0.824013                   0.307039                0.842019  \n",
       "2                0.795068                   0.305758                0.817624  \n",
       "3                0.755456                   0.308271                0.780850  \n",
       "4                0.807150                   0.299996                0.825696  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Here, we specify fo2 andd P, so only get 8b and 9b outputs as well.\n",
    "Eq_Ol_Put_P_fo2=pt.calculate_eq_ol_content(liq_comps=myLiquids1, Kd_model=\"Putirka2016\", \n",
    "                                           Fe3Fet_Liq=0.2, logfo2=-10, P=5)\n",
    "Eq_Ol_Put_P_fo2.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f539d4b0-bae0-4fbb-8295-223d7fef3059",
   "metadata": {},
   "source": [
    "### 3d - All Models\n",
    "- We can also specify Kd_model=\"All\" to get results from all of these models\n",
    "- Here we are using the temperature from the adapted ol-liq thermometer applied to just liquid compositions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f90cd5d6-ffe6-4a21-b9a2-53e6be28251f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>Mg#_Liq_Fe2</th>\n",
       "      <th>Mg#_Liq_Fet</th>\n",
       "      <th>Eq Fo (Shea, Kd=0.335)</th>\n",
       "      <th>Eq Fo (Shea, Kd=0.325)</th>\n",
       "      <th>Eq Fo (Shea, Kd=0.345)</th>\n",
       "      <th>Eq Fo (Roeder, Kd=0.3)</th>\n",
       "      <th>Eq Fo (Roeder, Kd=0.33)</th>\n",
       "      <th>Eq Fo (Roeder, Kd=0.27)</th>\n",
       "      <th>Eq Fo (Matzen, Kd=0.34)</th>\n",
       "      <th>Eq Fo (Matzen, Kd=0.352)</th>\n",
       "      <th>...</th>\n",
       "      <th>Eq Fo (Putirka 8a Fe2, Kd=0.33)</th>\n",
       "      <th>Eq Fo (Putirka 8a Fe2, Kd=0.33-0.044)</th>\n",
       "      <th>Eq Fo (Putirka 8a Fe2, Kd=0.33+0.044)</th>\n",
       "      <th>Calc Kd (Putirka 8c, Fe2)</th>\n",
       "      <th>Eq Fo (Putirka 8c Fe2)</th>\n",
       "      <th>Eq Fo (Putirka 9a Fet, Kd=0.29)</th>\n",
       "      <th>Eq Fo (Putirka 9a Fet, Kd=0.29-0.051)</th>\n",
       "      <th>Eq Fo (Putirka 9a Fet, Kd=0.29+0.051)</th>\n",
       "      <th>Calc Kd (Putirka 8b, Fe2)</th>\n",
       "      <th>Eq Fo (Putirka 8b Fe2)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.681666</td>\n",
       "      <td>0.631416</td>\n",
       "      <td>0.864721</td>\n",
       "      <td>0.861243</td>\n",
       "      <td>0.868227</td>\n",
       "      <td>0.877117</td>\n",
       "      <td>0.866470</td>\n",
       "      <td>0.888030</td>\n",
       "      <td>0.862978</td>\n",
       "      <td>0.858825</td>\n",
       "      <td>...</td>\n",
       "      <td>0.866470</td>\n",
       "      <td>0.882176</td>\n",
       "      <td>0.851313</td>\n",
       "      <td>0.346039</td>\n",
       "      <td>0.860883</td>\n",
       "      <td>0.855223</td>\n",
       "      <td>0.877567</td>\n",
       "      <td>0.877567</td>\n",
       "      <td>0.346828</td>\n",
       "      <td>0.860610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.620707</td>\n",
       "      <td>0.566947</td>\n",
       "      <td>0.830077</td>\n",
       "      <td>0.825888</td>\n",
       "      <td>0.834309</td>\n",
       "      <td>0.845080</td>\n",
       "      <td>0.832188</td>\n",
       "      <td>0.858378</td>\n",
       "      <td>0.827977</td>\n",
       "      <td>0.822980</td>\n",
       "      <td>...</td>\n",
       "      <td>0.832188</td>\n",
       "      <td>0.851234</td>\n",
       "      <td>0.813975</td>\n",
       "      <td>0.346004</td>\n",
       "      <td>0.825469</td>\n",
       "      <td>0.818658</td>\n",
       "      <td>0.845626</td>\n",
       "      <td>0.845626</td>\n",
       "      <td>0.347909</td>\n",
       "      <td>0.824677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.578196</td>\n",
       "      <td>0.523041</td>\n",
       "      <td>0.803608</td>\n",
       "      <td>0.798924</td>\n",
       "      <td>0.808347</td>\n",
       "      <td>0.820442</td>\n",
       "      <td>0.805970</td>\n",
       "      <td>0.835443</td>\n",
       "      <td>0.801259</td>\n",
       "      <td>0.795678</td>\n",
       "      <td>...</td>\n",
       "      <td>0.805970</td>\n",
       "      <td>0.827375</td>\n",
       "      <td>0.785645</td>\n",
       "      <td>0.348050</td>\n",
       "      <td>0.797507</td>\n",
       "      <td>0.790858</td>\n",
       "      <td>0.821056</td>\n",
       "      <td>0.821056</td>\n",
       "      <td>0.353321</td>\n",
       "      <td>0.795068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.523445</td>\n",
       "      <td>0.467721</td>\n",
       "      <td>0.766289</td>\n",
       "      <td>0.760980</td>\n",
       "      <td>0.771672</td>\n",
       "      <td>0.785468</td>\n",
       "      <td>0.768971</td>\n",
       "      <td>0.802688</td>\n",
       "      <td>0.763625</td>\n",
       "      <td>0.757307</td>\n",
       "      <td>...</td>\n",
       "      <td>0.768971</td>\n",
       "      <td>0.793411</td>\n",
       "      <td>0.745992</td>\n",
       "      <td>0.349700</td>\n",
       "      <td>0.758510</td>\n",
       "      <td>0.751864</td>\n",
       "      <td>0.786171</td>\n",
       "      <td>0.786171</td>\n",
       "      <td>0.355555</td>\n",
       "      <td>0.755456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.586967</td>\n",
       "      <td>0.532031</td>\n",
       "      <td>0.809238</td>\n",
       "      <td>0.804656</td>\n",
       "      <td>0.813873</td>\n",
       "      <td>0.825694</td>\n",
       "      <td>0.811549</td>\n",
       "      <td>0.840342</td>\n",
       "      <td>0.806941</td>\n",
       "      <td>0.801479</td>\n",
       "      <td>...</td>\n",
       "      <td>0.811549</td>\n",
       "      <td>0.832466</td>\n",
       "      <td>0.791657</td>\n",
       "      <td>0.339147</td>\n",
       "      <td>0.807332</td>\n",
       "      <td>0.796761</td>\n",
       "      <td>0.826295</td>\n",
       "      <td>0.826295</td>\n",
       "      <td>0.339543</td>\n",
       "      <td>0.807150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.565465</td>\n",
       "      <td>0.510056</td>\n",
       "      <td>0.795271</td>\n",
       "      <td>0.790440</td>\n",
       "      <td>0.800161</td>\n",
       "      <td>0.812653</td>\n",
       "      <td>0.797709</td>\n",
       "      <td>0.828169</td>\n",
       "      <td>0.792848</td>\n",
       "      <td>0.787094</td>\n",
       "      <td>...</td>\n",
       "      <td>0.797709</td>\n",
       "      <td>0.819821</td>\n",
       "      <td>0.776758</td>\n",
       "      <td>0.339433</td>\n",
       "      <td>0.793122</td>\n",
       "      <td>0.782127</td>\n",
       "      <td>0.813288</td>\n",
       "      <td>0.813288</td>\n",
       "      <td>0.340403</td>\n",
       "      <td>0.792654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.528731</td>\n",
       "      <td>0.473003</td>\n",
       "      <td>0.770064</td>\n",
       "      <td>0.764815</td>\n",
       "      <td>0.775386</td>\n",
       "      <td>0.789019</td>\n",
       "      <td>0.772716</td>\n",
       "      <td>0.806025</td>\n",
       "      <td>0.767431</td>\n",
       "      <td>0.761182</td>\n",
       "      <td>...</td>\n",
       "      <td>0.772716</td>\n",
       "      <td>0.796865</td>\n",
       "      <td>0.749988</td>\n",
       "      <td>0.340052</td>\n",
       "      <td>0.767403</td>\n",
       "      <td>0.755798</td>\n",
       "      <td>0.789713</td>\n",
       "      <td>0.789713</td>\n",
       "      <td>0.341896</td>\n",
       "      <td>0.766436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.620033</td>\n",
       "      <td>0.566244</td>\n",
       "      <td>0.829673</td>\n",
       "      <td>0.825476</td>\n",
       "      <td>0.833913</td>\n",
       "      <td>0.844705</td>\n",
       "      <td>0.831788</td>\n",
       "      <td>0.858030</td>\n",
       "      <td>0.827569</td>\n",
       "      <td>0.822563</td>\n",
       "      <td>...</td>\n",
       "      <td>0.831788</td>\n",
       "      <td>0.850871</td>\n",
       "      <td>0.813541</td>\n",
       "      <td>0.337757</td>\n",
       "      <td>0.828512</td>\n",
       "      <td>0.818233</td>\n",
       "      <td>0.845252</td>\n",
       "      <td>0.845252</td>\n",
       "      <td>0.336036</td>\n",
       "      <td>0.829236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.583864</td>\n",
       "      <td>0.528846</td>\n",
       "      <td>0.807256</td>\n",
       "      <td>0.802638</td>\n",
       "      <td>0.811928</td>\n",
       "      <td>0.823846</td>\n",
       "      <td>0.809585</td>\n",
       "      <td>0.838619</td>\n",
       "      <td>0.804941</td>\n",
       "      <td>0.799437</td>\n",
       "      <td>...</td>\n",
       "      <td>0.809585</td>\n",
       "      <td>0.830675</td>\n",
       "      <td>0.789540</td>\n",
       "      <td>0.339023</td>\n",
       "      <td>0.805392</td>\n",
       "      <td>0.794683</td>\n",
       "      <td>0.824452</td>\n",
       "      <td>0.824452</td>\n",
       "      <td>0.338229</td>\n",
       "      <td>0.805759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.665729</td>\n",
       "      <td>0.614386</td>\n",
       "      <td>0.856012</td>\n",
       "      <td>0.852348</td>\n",
       "      <td>0.859707</td>\n",
       "      <td>0.869086</td>\n",
       "      <td>0.857856</td>\n",
       "      <td>0.880615</td>\n",
       "      <td>0.854176</td>\n",
       "      <td>0.849803</td>\n",
       "      <td>...</td>\n",
       "      <td>0.857856</td>\n",
       "      <td>0.874428</td>\n",
       "      <td>0.841899</td>\n",
       "      <td>0.338564</td>\n",
       "      <td>0.854703</td>\n",
       "      <td>0.846012</td>\n",
       "      <td>0.869560</td>\n",
       "      <td>0.869560</td>\n",
       "      <td>0.338111</td>\n",
       "      <td>0.854869</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Mg#_Liq_Fe2  Mg#_Liq_Fet  Eq Fo (Shea, Kd=0.335)  Eq Fo (Shea, Kd=0.325)  \\\n",
       "0     0.681666     0.631416                0.864721                0.861243   \n",
       "1     0.620707     0.566947                0.830077                0.825888   \n",
       "2     0.578196     0.523041                0.803608                0.798924   \n",
       "3     0.523445     0.467721                0.766289                0.760980   \n",
       "4     0.586967     0.532031                0.809238                0.804656   \n",
       "5     0.565465     0.510056                0.795271                0.790440   \n",
       "6     0.528731     0.473003                0.770064                0.764815   \n",
       "7     0.620033     0.566244                0.829673                0.825476   \n",
       "8     0.583864     0.528846                0.807256                0.802638   \n",
       "9     0.665729     0.614386                0.856012                0.852348   \n",
       "\n",
       "   Eq Fo (Shea, Kd=0.345)  Eq Fo (Roeder, Kd=0.3)  Eq Fo (Roeder, Kd=0.33)  \\\n",
       "0                0.868227                0.877117                 0.866470   \n",
       "1                0.834309                0.845080                 0.832188   \n",
       "2                0.808347                0.820442                 0.805970   \n",
       "3                0.771672                0.785468                 0.768971   \n",
       "4                0.813873                0.825694                 0.811549   \n",
       "5                0.800161                0.812653                 0.797709   \n",
       "6                0.775386                0.789019                 0.772716   \n",
       "7                0.833913                0.844705                 0.831788   \n",
       "8                0.811928                0.823846                 0.809585   \n",
       "9                0.859707                0.869086                 0.857856   \n",
       "\n",
       "   Eq Fo (Roeder, Kd=0.27)  Eq Fo (Matzen, Kd=0.34)  Eq Fo (Matzen, Kd=0.352)  \\\n",
       "0                 0.888030                 0.862978                  0.858825   \n",
       "1                 0.858378                 0.827977                  0.822980   \n",
       "2                 0.835443                 0.801259                  0.795678   \n",
       "3                 0.802688                 0.763625                  0.757307   \n",
       "4                 0.840342                 0.806941                  0.801479   \n",
       "5                 0.828169                 0.792848                  0.787094   \n",
       "6                 0.806025                 0.767431                  0.761182   \n",
       "7                 0.858030                 0.827569                  0.822563   \n",
       "8                 0.838619                 0.804941                  0.799437   \n",
       "9                 0.880615                 0.854176                  0.849803   \n",
       "\n",
       "   ...  Eq Fo (Putirka 8a Fe2, Kd=0.33)  \\\n",
       "0  ...                         0.866470   \n",
       "1  ...                         0.832188   \n",
       "2  ...                         0.805970   \n",
       "3  ...                         0.768971   \n",
       "4  ...                         0.811549   \n",
       "5  ...                         0.797709   \n",
       "6  ...                         0.772716   \n",
       "7  ...                         0.831788   \n",
       "8  ...                         0.809585   \n",
       "9  ...                         0.857856   \n",
       "\n",
       "   Eq Fo (Putirka 8a Fe2, Kd=0.33-0.044)  \\\n",
       "0                               0.882176   \n",
       "1                               0.851234   \n",
       "2                               0.827375   \n",
       "3                               0.793411   \n",
       "4                               0.832466   \n",
       "5                               0.819821   \n",
       "6                               0.796865   \n",
       "7                               0.850871   \n",
       "8                               0.830675   \n",
       "9                               0.874428   \n",
       "\n",
       "   Eq Fo (Putirka 8a Fe2, Kd=0.33+0.044)  Calc Kd (Putirka 8c, Fe2)  \\\n",
       "0                               0.851313                   0.346039   \n",
       "1                               0.813975                   0.346004   \n",
       "2                               0.785645                   0.348050   \n",
       "3                               0.745992                   0.349700   \n",
       "4                               0.791657                   0.339147   \n",
       "5                               0.776758                   0.339433   \n",
       "6                               0.749988                   0.340052   \n",
       "7                               0.813541                   0.337757   \n",
       "8                               0.789540                   0.339023   \n",
       "9                               0.841899                   0.338564   \n",
       "\n",
       "   Eq Fo (Putirka 8c Fe2)  Eq Fo (Putirka 9a Fet, Kd=0.29)  \\\n",
       "0                0.860883                         0.855223   \n",
       "1                0.825469                         0.818658   \n",
       "2                0.797507                         0.790858   \n",
       "3                0.758510                         0.751864   \n",
       "4                0.807332                         0.796761   \n",
       "5                0.793122                         0.782127   \n",
       "6                0.767403                         0.755798   \n",
       "7                0.828512                         0.818233   \n",
       "8                0.805392                         0.794683   \n",
       "9                0.854703                         0.846012   \n",
       "\n",
       "   Eq Fo (Putirka 9a Fet, Kd=0.29-0.051)  \\\n",
       "0                               0.877567   \n",
       "1                               0.845626   \n",
       "2                               0.821056   \n",
       "3                               0.786171   \n",
       "4                               0.826295   \n",
       "5                               0.813288   \n",
       "6                               0.789713   \n",
       "7                               0.845252   \n",
       "8                               0.824452   \n",
       "9                               0.869560   \n",
       "\n",
       "   Eq Fo (Putirka 9a Fet, Kd=0.29+0.051)  Calc Kd (Putirka 8b, Fe2)  \\\n",
       "0                               0.877567                   0.346828   \n",
       "1                               0.845626                   0.347909   \n",
       "2                               0.821056                   0.353321   \n",
       "3                               0.786171                   0.355555   \n",
       "4                               0.826295                   0.339543   \n",
       "5                               0.813288                   0.340403   \n",
       "6                               0.789713                   0.341896   \n",
       "7                               0.845252                   0.336036   \n",
       "8                               0.824452                   0.338229   \n",
       "9                               0.869560                   0.338111   \n",
       "\n",
       "   Eq Fo (Putirka 8b Fe2)  \n",
       "0                0.860610  \n",
       "1                0.824677  \n",
       "2                0.795068  \n",
       "3                0.755456  \n",
       "4                0.807150  \n",
       "5                0.792654  \n",
       "6                0.766436  \n",
       "7                0.829236  \n",
       "8                0.805759  \n",
       "9                0.854869  \n",
       "\n",
       "[10 rows x 23 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Eq_Ol_IterFo_calcT=pt.calculate_eq_ol_content(liq_comps=myLiquids1, Kd_model=\"All\", Fe3Fet_Liq=0.2, \n",
    "                                                P=my_input['P_kbar'], T=T_Calc_22)\n",
    "Eq_Ol_IterFo_calcT"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7ae7f93-c18f-4fc1-9846-d6f1676e9d4d",
   "metadata": {},
   "source": [
    "## Example 4 - Rhodes Diagrams\n",
    "- We can also calculate equilibrium lines to draw on a Rhodes diagram to assess olivine-liquid equilibrium\n",
    "- We don't have the Toplis model built in, because it depends on liquid composition, so you can't use it to draw lines for multiple liquid compositions. \n",
    "- By default, the user just specifies the max and min liquid Mgno they want to calculate lines for"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "078e499e-e80e-4bf2-985e-5413d82d4368",
   "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>Mg#_Liq</th>\n",
       "      <th>Eq_Ol_Fo_Roeder (Kd=0.3)</th>\n",
       "      <th>Eq_Ol_Fo_Roeder (Kd=0.27)</th>\n",
       "      <th>Eq_Ol_Fo_Roeder (Kd=0.33)</th>\n",
       "      <th>Eq_Ol_Fo_Matzen (Kd=0.34)</th>\n",
       "      <th>Eq_Ol_Fo_Matzen (Kd=0.328)</th>\n",
       "      <th>Eq_Ol_Fo_Matzen (Kd=0.352)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.769231</td>\n",
       "      <td>0.787402</td>\n",
       "      <td>0.751880</td>\n",
       "      <td>0.746269</td>\n",
       "      <td>0.753012</td>\n",
       "      <td>0.739645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.502020</td>\n",
       "      <td>0.770662</td>\n",
       "      <td>0.788751</td>\n",
       "      <td>0.753384</td>\n",
       "      <td>0.747796</td>\n",
       "      <td>0.754512</td>\n",
       "      <td>0.741198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.504040</td>\n",
       "      <td>0.772087</td>\n",
       "      <td>0.790095</td>\n",
       "      <td>0.754883</td>\n",
       "      <td>0.749317</td>\n",
       "      <td>0.756006</td>\n",
       "      <td>0.742745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.506061</td>\n",
       "      <td>0.773506</td>\n",
       "      <td>0.791432</td>\n",
       "      <td>0.756375</td>\n",
       "      <td>0.750832</td>\n",
       "      <td>0.757493</td>\n",
       "      <td>0.744286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.508081</td>\n",
       "      <td>0.774919</td>\n",
       "      <td>0.792763</td>\n",
       "      <td>0.757861</td>\n",
       "      <td>0.752341</td>\n",
       "      <td>0.758975</td>\n",
       "      <td>0.745822</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Mg#_Liq  Eq_Ol_Fo_Roeder (Kd=0.3)  Eq_Ol_Fo_Roeder (Kd=0.27)  \\\n",
       "0  0.500000                  0.769231                   0.787402   \n",
       "1  0.502020                  0.770662                   0.788751   \n",
       "2  0.504040                  0.772087                   0.790095   \n",
       "3  0.506061                  0.773506                   0.791432   \n",
       "4  0.508081                  0.774919                   0.792763   \n",
       "\n",
       "   Eq_Ol_Fo_Roeder (Kd=0.33)  Eq_Ol_Fo_Matzen (Kd=0.34)  \\\n",
       "0                   0.751880                   0.746269   \n",
       "1                   0.753384                   0.747796   \n",
       "2                   0.754883                   0.749317   \n",
       "3                   0.756375                   0.750832   \n",
       "4                   0.757861                   0.752341   \n",
       "\n",
       "   Eq_Ol_Fo_Matzen (Kd=0.328)  Eq_Ol_Fo_Matzen (Kd=0.352)  \n",
       "0                    0.753012                    0.739645  \n",
       "1                    0.754512                    0.741198  \n",
       "2                    0.756006                    0.742745  \n",
       "3                    0.757493                    0.744286  \n",
       "4                    0.758975                    0.745822  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Rhodes=pt.calculate_ol_rhodes_diagram_lines(Min_Mgno=0.5, Max_Mgno=0.7)\n",
    "Rhodes.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be05d410-795e-4b9d-a0fa-cc5a1655578b",
   "metadata": {},
   "source": [
    "- We also need to calculate olivine forsterite contents for our measured olivine compositions: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "6fb6e9fb-bd29-47c6-95c4-9e01186bd05e",
   "metadata": {},
   "outputs": [],
   "source": [
    "Ol_Fo_Calc=pt.calculate_ol_fo(ol_comps=myOls1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "215833fb-66e0-4dd8-b9bb-3211c1c1314f",
   "metadata": {},
   "source": [
    "- And the Mg#s of the matrix glass using the ratio inputted in the spreadsheet (as here, 0.2), or you could also enter Fe3Fet_Liq=value here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "98fa9fbf-9f6e-4d08-aff3-f16eff637a72",
   "metadata": {},
   "outputs": [],
   "source": [
    "Liq_Mgno_calc=pt.calculate_liq_mgno(liq_comps=myLiquids1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f682320-f3e9-4086-9632-065baf8c535b",
   "metadata": {},
   "source": [
    "- Here, we use these calculated lines, Mg#s and Ol conetnts to draw min and max equilibrium fields for Roeder and Emslie on the LH axis, and Matzen on the RH axis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "45ae3c6c-d3da-425b-adbd-2ddf18197215",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.5, 0.7)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12,5))\n",
    "# Plotting for Roeder and Emslie\n",
    "ax1.set_title('Roeder and Emslie, 1970')\n",
    "# Plotting equilibrium lines\n",
    "ax1.plot(Rhodes['Mg#_Liq'], Rhodes['Eq_Ol_Fo_Roeder (Kd=0.27)'], ':k')\n",
    "ax1.plot(Rhodes['Mg#_Liq'], Rhodes['Eq_Ol_Fo_Roeder (Kd=0.33)'], ':k')\n",
    "ax1.plot(Rhodes['Mg#_Liq'], Rhodes['Eq_Ol_Fo_Roeder (Kd=0.3)'], '-k')\n",
    "\n",
    "# Plotting data\n",
    "ax1.plot(Liq_Mgno_calc, Ol_Fo_Calc, 'ok', mfc='red')\n",
    "\n",
    "ax2.set_title('Matzen (2011)')\n",
    "# Plotting equilibrium lines\n",
    "ax2.plot(Rhodes['Mg#_Liq'], Rhodes['Eq_Ol_Fo_Matzen (Kd=0.328)'], ':k')\n",
    "ax2.plot(Rhodes['Mg#_Liq'], Rhodes['Eq_Ol_Fo_Matzen (Kd=0.352)'], ':k')\n",
    "ax2.plot(Rhodes['Mg#_Liq'], Rhodes['Eq_Ol_Fo_Matzen (Kd=0.34)'], '-k')\n",
    "# Plotting data\n",
    "ax2.plot(Liq_Mgno_calc, Ol_Fo_Calc, 'ok', mfc='red')\n",
    "ax1.set_ylabel('Ol Fo content')\n",
    "ax1.set_xlabel('Glass Mg#')\n",
    "ax2.set_xlabel('Glass Mg#')\n",
    "# Adjust axis limits here\n",
    "ax1.set_ylim([0.74, 0.92])\n",
    "ax2.set_ylim([0.74, 0.92])\n",
    "ax1.set_xlim([0.5, 0.7])\n",
    "ax2.set_xlim([0.5, 0.7])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "315c072d-f677-43b8-84ed-659b8eae6ddf",
   "metadata": {},
   "source": [
    " - We can also use the fill_between function to show the equilibrium field or you could show the min and max to provide the full range using the fill between function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "c23c1248-33d0-4409-9c85-678b06875b2d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate Ol Fo contents to plot\n",
    "Ol_Fo_Calc=pt.calculate_ol_fo(ol_comps=myOls1)\n",
    "Liq_Mgno_calc=pt.calculate_liq_mgno(liq_comps=myLiquids1, Fe3Fet_Liq=0.2)\n",
    "## Here we plot these results\n",
    "fig, (ax1) = plt.subplots(1, 1, figsize=(6,5))\n",
    "\n",
    "# This section of code fills between the two lines, where xfill_pap is the sorted x co-ordinate, \n",
    "# and the y1fill and y2fill are the two y coordinates. You have to have a shared x axis (here, same\n",
    "# generated set of Mg#s)\n",
    "xfill_pap = np.sort(Rhodes['Mg#_Liq'])\n",
    "y1fill_pap = Rhodes['Eq_Ol_Fo_Roeder (Kd=0.27)']\n",
    "y2fill_pap = Rhodes['Eq_Ol_Fo_Matzen (Kd=0.352)']\n",
    "ax1.fill_between(xfill_pap, y1fill_pap, y2fill_pap, where=y1fill_pap < y2fill_pap,\n",
    "                 interpolate=True, color='grey',  alpha=0.3)\n",
    "ax1.fill_between(xfill_pap, y1fill_pap, y2fill_pap, where=y1fill_pap > y2fill_pap, \n",
    "                 interpolate=True, color='grey', linewidth=0.5, alpha=0.3)\n",
    "\n",
    "\n",
    "# # Plotting equilibrium lines\n",
    "ax1.plot(Rhodes['Mg#_Liq'], Rhodes['Eq_Ol_Fo_Roeder (Kd=0.27)'], '-k', linewidth=1)\n",
    "\n",
    "ax1.plot(Rhodes['Mg#_Liq'], Rhodes['Eq_Ol_Fo_Matzen (Kd=0.352)'], '-k', linewidth=1)\n",
    "# Plotting data\n",
    "ax1.plot(Liq_Mgno_calc, Ol_Fo_Calc, 'ok', mfc='red')\n",
    "ax1.set_ylabel('Ol Fo content')\n",
    "ax1.set_xlabel('Glass Mg#')\n",
    "ax1.set_ylim([0.74, 0.92]);\n",
    "ax1.set_xlim([0.5, 0.7]);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "270cc725-fec4-4ade-83f2-8a36cd01d9a7",
   "metadata": {},
   "source": [
    "## Example 5 - Calculating Fe3Fet_Liq using a buffer position to assess equilibrium\n",
    "- Say we don't know the Fe3FeT_Liq we want to perform equilibrium calculations at, but we have reason to believe our system is buffered at NNO+1\n",
    "- As liquid-olivine temperatures aren't sensitive to fo2, first we calculate temperature (as buffers are highly temperature-sensitive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "f806d0b2-73ea-4264-833f-7e3d61e354c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "eq22_PHinput=pt.calculate_ol_liq_temp(liq_comps=myLiquids1, ol_comps=myOls1,  \n",
    "                                      equationT=\"T_Put2008_eq22\", P=my_input['P_kbar'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4dd3264-8b06-40b6-b6a7-cfe05174067a",
   "metadata": {},
   "source": [
    "- Then we use this function to convert NNO+1 to a Fe3/FeT ratio (the function returns a dataframe, and the variable we care about is Fe3Fet_Liq)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "65c86cb7-2b0f-4196-b38a-23747cf704a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.286549\n",
       "1    0.294522\n",
       "2    0.290725\n",
       "3    0.304642\n",
       "4    0.288451\n",
       "5    0.293145\n",
       "6    0.296381\n",
       "7    0.276202\n",
       "8    0.290563\n",
       "9    0.278905\n",
       "Name: Fe3Fet_Liq, dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "myLiquids_Fe3_Kress_no_norm_Fe3=pt.convert_fo2_to_fe_partition(liq_comps=myLiquids1, \n",
    "                                T_K=eq22_PHinput['T_K_calc'], P_kbar=3, fo2=\"NNO\", fo2_offset=1, \n",
    "                                model=\"Kress1991\", renorm=False).Fe3Fet_Liq\n",
    "myLiquids_Fe3_Kress_no_norm_Fe3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2cf05673-0b7f-4d88-a504-5dd9bde15f46",
   "metadata": {},
   "source": [
    "- We then input this into the calculate_ol_liq_temp function as Fe3Fet_Liq=...."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "17068b1a-8657-4a0e-9c08-f4937a41bcdd",
   "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>T_K_calc</th>\n",
       "      <th>Kd Meas</th>\n",
       "      <th>Kd calc (Toplis)</th>\n",
       "      <th>ΔKd, Toplis (M-P)</th>\n",
       "      <th>ΔKd, Roeder (M-P)</th>\n",
       "      <th>ΔKd, Matzen (M-P)</th>\n",
       "      <th>SiO2_Liq</th>\n",
       "      <th>TiO2_Liq</th>\n",
       "      <th>Al2O3_Liq</th>\n",
       "      <th>FeOt_Liq</th>\n",
       "      <th>...</th>\n",
       "      <th>Cr2O3_Ol</th>\n",
       "      <th>NiO_Ol</th>\n",
       "      <th>Sample_ID_Ol</th>\n",
       "      <th>Fo_meas</th>\n",
       "      <th>P2O5_Ol</th>\n",
       "      <th>DMg_Meas</th>\n",
       "      <th>CNML</th>\n",
       "      <th>CSiO2L</th>\n",
       "      <th>NF</th>\n",
       "      <th>Den_Beat93</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1289.947705</td>\n",
       "      <td>0.352387</td>\n",
       "      <td>0.325040</td>\n",
       "      <td>0.027347</td>\n",
       "      <td>0.052387</td>\n",
       "      <td>0.012387</td>\n",
       "      <td>57.023602</td>\n",
       "      <td>0.623106</td>\n",
       "      <td>16.332899</td>\n",
       "      <td>4.36174</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.872023</td>\n",
       "      <td>0</td>\n",
       "      <td>9.472619</td>\n",
       "      <td>0.170395</td>\n",
       "      <td>0.557471</td>\n",
       "      <td>-0.761843</td>\n",
       "      <td>9.819071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1229.813416</td>\n",
       "      <td>0.198881</td>\n",
       "      <td>0.308684</td>\n",
       "      <td>-0.109802</td>\n",
       "      <td>-0.101119</td>\n",
       "      <td>-0.141119</td>\n",
       "      <td>57.658600</td>\n",
       "      <td>0.654150</td>\n",
       "      <td>17.194799</td>\n",
       "      <td>3.90621</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.903203</td>\n",
       "      <td>0</td>\n",
       "      <td>14.186789</td>\n",
       "      <td>0.137941</td>\n",
       "      <td>0.570023</td>\n",
       "      <td>-0.816654</td>\n",
       "      <td>10.303635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1285.857491</td>\n",
       "      <td>0.304065</td>\n",
       "      <td>0.315891</td>\n",
       "      <td>-0.011826</td>\n",
       "      <td>0.004065</td>\n",
       "      <td>-0.035935</td>\n",
       "      <td>60.731201</td>\n",
       "      <td>0.862054</td>\n",
       "      <td>17.144199</td>\n",
       "      <td>4.07781</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.835656</td>\n",
       "      <td>0</td>\n",
       "      <td>15.531216</td>\n",
       "      <td>0.122184</td>\n",
       "      <td>0.579288</td>\n",
       "      <td>-0.792785</td>\n",
       "      <td>10.250501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1198.240159</td>\n",
       "      <td>0.199954</td>\n",
       "      <td>0.296719</td>\n",
       "      <td>-0.096765</td>\n",
       "      <td>-0.100046</td>\n",
       "      <td>-0.140046</td>\n",
       "      <td>61.532799</td>\n",
       "      <td>0.440860</td>\n",
       "      <td>16.508801</td>\n",
       "      <td>3.32990</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.863386</td>\n",
       "      <td>0</td>\n",
       "      <td>23.753206</td>\n",
       "      <td>0.097626</td>\n",
       "      <td>0.605753</td>\n",
       "      <td>-0.767076</td>\n",
       "      <td>10.715090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1259.174284</td>\n",
       "      <td>0.171088</td>\n",
       "      <td>0.323766</td>\n",
       "      <td>-0.152678</td>\n",
       "      <td>-0.128912</td>\n",
       "      <td>-0.168912</td>\n",
       "      <td>52.969101</td>\n",
       "      <td>0.803412</td>\n",
       "      <td>17.563000</td>\n",
       "      <td>5.93217</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.903278</td>\n",
       "      <td>0</td>\n",
       "      <td>10.781292</td>\n",
       "      <td>0.186877</td>\n",
       "      <td>0.523030</td>\n",
       "      <td>-0.842157</td>\n",
       "      <td>10.215321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1244.931462</td>\n",
       "      <td>0.180579</td>\n",
       "      <td>0.324986</td>\n",
       "      <td>-0.144407</td>\n",
       "      <td>-0.119421</td>\n",
       "      <td>-0.159421</td>\n",
       "      <td>54.050201</td>\n",
       "      <td>0.857348</td>\n",
       "      <td>17.333300</td>\n",
       "      <td>5.60072</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>0.890781</td>\n",
       "      <td>0</td>\n",
       "      <td>12.276130</td>\n",
       "      <td>0.168070</td>\n",
       "      <td>0.533835</td>\n",
       "      <td>-0.833465</td>\n",
       "      <td>10.295063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1241.300118</td>\n",
       "      <td>0.245491</td>\n",
       "      <td>0.333878</td>\n",
       "      <td>-0.088387</td>\n",
       "      <td>-0.054509</td>\n",
       "      <td>-0.094509</td>\n",
       "      <td>55.656300</td>\n",
       "      <td>0.897984</td>\n",
       "      <td>17.117800</td>\n",
       "      <td>5.31307</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0.838609</td>\n",
       "      <td>0</td>\n",
       "      <td>14.083460</td>\n",
       "      <td>0.145845</td>\n",
       "      <td>0.547483</td>\n",
       "      <td>-0.820914</td>\n",
       "      <td>10.324021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1199.601831</td>\n",
       "      <td>0.447306</td>\n",
       "      <td>0.391378</td>\n",
       "      <td>0.055928</td>\n",
       "      <td>0.147306</td>\n",
       "      <td>0.107306</td>\n",
       "      <td>49.054699</td>\n",
       "      <td>0.488832</td>\n",
       "      <td>14.665000</td>\n",
       "      <td>5.83168</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7</td>\n",
       "      <td>0.801278</td>\n",
       "      <td>0</td>\n",
       "      <td>7.372298</td>\n",
       "      <td>0.220053</td>\n",
       "      <td>0.554209</td>\n",
       "      <td>-0.789502</td>\n",
       "      <td>9.845140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1162.693468</td>\n",
       "      <td>0.354214</td>\n",
       "      <td>0.361834</td>\n",
       "      <td>-0.007620</td>\n",
       "      <td>0.054214</td>\n",
       "      <td>0.014214</td>\n",
       "      <td>50.625099</td>\n",
       "      <td>0.334074</td>\n",
       "      <td>16.875000</td>\n",
       "      <td>5.01968</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>0.817074</td>\n",
       "      <td>0</td>\n",
       "      <td>10.509878</td>\n",
       "      <td>0.180293</td>\n",
       "      <td>0.551305</td>\n",
       "      <td>-0.873502</td>\n",
       "      <td>10.229233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1339.466029</td>\n",
       "      <td>0.476093</td>\n",
       "      <td>0.299720</td>\n",
       "      <td>0.176373</td>\n",
       "      <td>0.176093</td>\n",
       "      <td>0.136093</td>\n",
       "      <td>51.403301</td>\n",
       "      <td>0.663880</td>\n",
       "      <td>18.019600</td>\n",
       "      <td>5.98440</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9</td>\n",
       "      <td>0.822724</td>\n",
       "      <td>0</td>\n",
       "      <td>7.070601</td>\n",
       "      <td>0.228386</td>\n",
       "      <td>0.498172</td>\n",
       "      <td>-0.840523</td>\n",
       "      <td>9.673734</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 75 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      T_K_calc   Kd Meas  Kd calc (Toplis)  ΔKd, Toplis (M-P)  \\\n",
       "0  1289.947705  0.352387          0.325040           0.027347   \n",
       "1  1229.813416  0.198881          0.308684          -0.109802   \n",
       "2  1285.857491  0.304065          0.315891          -0.011826   \n",
       "3  1198.240159  0.199954          0.296719          -0.096765   \n",
       "4  1259.174284  0.171088          0.323766          -0.152678   \n",
       "5  1244.931462  0.180579          0.324986          -0.144407   \n",
       "6  1241.300118  0.245491          0.333878          -0.088387   \n",
       "7  1199.601831  0.447306          0.391378           0.055928   \n",
       "8  1162.693468  0.354214          0.361834          -0.007620   \n",
       "9  1339.466029  0.476093          0.299720           0.176373   \n",
       "\n",
       "   ΔKd, Roeder (M-P)  ΔKd, Matzen (M-P)   SiO2_Liq  TiO2_Liq  Al2O3_Liq  \\\n",
       "0           0.052387           0.012387  57.023602  0.623106  16.332899   \n",
       "1          -0.101119          -0.141119  57.658600  0.654150  17.194799   \n",
       "2           0.004065          -0.035935  60.731201  0.862054  17.144199   \n",
       "3          -0.100046          -0.140046  61.532799  0.440860  16.508801   \n",
       "4          -0.128912          -0.168912  52.969101  0.803412  17.563000   \n",
       "5          -0.119421          -0.159421  54.050201  0.857348  17.333300   \n",
       "6          -0.054509          -0.094509  55.656300  0.897984  17.117800   \n",
       "7           0.147306           0.107306  49.054699  0.488832  14.665000   \n",
       "8           0.054214           0.014214  50.625099  0.334074  16.875000   \n",
       "9           0.176093           0.136093  51.403301  0.663880  18.019600   \n",
       "\n",
       "   FeOt_Liq  ...  Cr2O3_Ol  NiO_Ol  Sample_ID_Ol   Fo_meas  P2O5_Ol  \\\n",
       "0   4.36174  ...         0     0.0             0  0.872023        0   \n",
       "1   3.90621  ...         0     0.0             1  0.903203        0   \n",
       "2   4.07781  ...         0     0.0             2  0.835656        0   \n",
       "3   3.32990  ...         0     0.0             3  0.863386        0   \n",
       "4   5.93217  ...         0     0.0             4  0.903278        0   \n",
       "5   5.60072  ...         0     0.0             5  0.890781        0   \n",
       "6   5.31307  ...         0     0.0             6  0.838609        0   \n",
       "7   5.83168  ...         0     0.0             7  0.801278        0   \n",
       "8   5.01968  ...         0     0.0             8  0.817074        0   \n",
       "9   5.98440  ...         0     0.0             9  0.822724        0   \n",
       "\n",
       "    DMg_Meas      CNML    CSiO2L        NF  Den_Beat93  \n",
       "0   9.472619  0.170395  0.557471 -0.761843    9.819071  \n",
       "1  14.186789  0.137941  0.570023 -0.816654   10.303635  \n",
       "2  15.531216  0.122184  0.579288 -0.792785   10.250501  \n",
       "3  23.753206  0.097626  0.605753 -0.767076   10.715090  \n",
       "4  10.781292  0.186877  0.523030 -0.842157   10.215321  \n",
       "5  12.276130  0.168070  0.533835 -0.833465   10.295063  \n",
       "6  14.083460  0.145845  0.547483 -0.820914   10.324021  \n",
       "7   7.372298  0.220053  0.554209 -0.789502    9.845140  \n",
       "8  10.509878  0.180293  0.551305 -0.873502   10.229233  \n",
       "9   7.070601  0.228386  0.498172 -0.840523    9.673734  \n",
       "\n",
       "[10 rows x 75 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eq22_PHinput_EqTests=pt.calculate_ol_liq_temp(liq_comps=myLiquids1, ol_comps=myOls1,  \n",
    "                                      equationT=\"T_Put2008_eq22\", P=my_input['P_kbar'], eq_tests=True, \n",
    "                                    Fe3Fet_Liq=myLiquids_Fe3_Kress_no_norm_Fe3)\n",
    "eq22_PHinput_EqTests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4e4f5ea7-dcba-49af-a810-d65bacc57202",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b6478d3e-6342-442d-8248-f1cde14493a2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "420d1321-cf4b-4227-857e-d2284b8b2c1f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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