DFN_mesh_node_prep_3-1b.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=pd.read_csv('large_well_3-1b_node.csv', skiprows = 10, float_precision='round_trip')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Z</th>\n",
       "      <th>dX</th>\n",
       "      <th>dY</th>\n",
       "      <th>dZ</th>\n",
       "      <th>pressure_MPa</th>\n",
       "      <th>sigma_h_max_MPa</th>\n",
       "      <th>sigma_h_min_MPa</th>\n",
       "      <th>Sigma_V_MPa</th>\n",
       "      <th>temperature_C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3.996081e+06</td>\n",
       "      <td>3.996081e+06</td>\n",
       "      <td>3.996081e+06</td>\n",
       "      <td>3.996081e+06</td>\n",
       "      <td>3996081.0</td>\n",
       "      <td>3996081.0</td>\n",
       "      <td>3996081.0</td>\n",
       "      <td>3.996081e+06</td>\n",
       "      <td>3.996081e+06</td>\n",
       "      <td>3.996081e+06</td>\n",
       "      <td>3.996081e+06</td>\n",
       "      <td>3.996081e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.998040e+06</td>\n",
       "      <td>7.500000e+02</td>\n",
       "      <td>1.120000e+03</td>\n",
       "      <td>-4.750000e+02</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.902218e+01</td>\n",
       "      <td>3.699827e+01</td>\n",
       "      <td>3.217816e+01</td>\n",
       "      <td>5.277819e+01</td>\n",
       "      <td>1.833050e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.153569e+06</td>\n",
       "      <td>4.070218e+02</td>\n",
       "      <td>4.070218e+02</td>\n",
       "      <td>5.802299e+02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.084631e+00</td>\n",
       "      <td>1.035117e+01</td>\n",
       "      <td>8.908026e+00</td>\n",
       "      <td>1.570728e+01</td>\n",
       "      <td>3.502214e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>5.000000e+01</td>\n",
       "      <td>4.200000e+02</td>\n",
       "      <td>-1.475000e+03</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.002488e+01</td>\n",
       "      <td>1.864353e+01</td>\n",
       "      <td>1.617470e+01</td>\n",
       "      <td>2.544605e+01</td>\n",
       "      <td>1.106922e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>9.990200e+05</td>\n",
       "      <td>4.000000e+02</td>\n",
       "      <td>7.700000e+02</td>\n",
       "      <td>-9.750000e+02</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.464307e+01</td>\n",
       "      <td>2.821518e+01</td>\n",
       "      <td>2.474237e+01</td>\n",
       "      <td>3.904700e+01</td>\n",
       "      <td>1.541820e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.998040e+06</td>\n",
       "      <td>7.500000e+02</td>\n",
       "      <td>1.120000e+03</td>\n",
       "      <td>-4.750000e+02</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.912009e+01</td>\n",
       "      <td>3.710544e+01</td>\n",
       "      <td>3.241430e+01</td>\n",
       "      <td>5.275623e+01</td>\n",
       "      <td>1.842313e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2.997060e+06</td>\n",
       "      <td>1.100000e+03</td>\n",
       "      <td>1.470000e+03</td>\n",
       "      <td>2.500000e+01</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2.343801e+01</td>\n",
       "      <td>4.591633e+01</td>\n",
       "      <td>3.983032e+01</td>\n",
       "      <td>6.641029e+01</td>\n",
       "      <td>2.131155e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>3.996080e+06</td>\n",
       "      <td>1.450000e+03</td>\n",
       "      <td>1.820000e+03</td>\n",
       "      <td>5.250000e+02</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2.766735e+01</td>\n",
       "      <td>5.518527e+01</td>\n",
       "      <td>4.743421e+01</td>\n",
       "      <td>8.065098e+01</td>\n",
       "      <td>2.555467e+02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Id             X             Y             Z         dX  \\\n",
       "count  3.996081e+06  3.996081e+06  3.996081e+06  3.996081e+06  3996081.0   \n",
       "mean   1.998040e+06  7.500000e+02  1.120000e+03 -4.750000e+02       10.0   \n",
       "std    1.153569e+06  4.070218e+02  4.070218e+02  5.802299e+02        0.0   \n",
       "min    0.000000e+00  5.000000e+01  4.200000e+02 -1.475000e+03       10.0   \n",
       "25%    9.990200e+05  4.000000e+02  7.700000e+02 -9.750000e+02       10.0   \n",
       "50%    1.998040e+06  7.500000e+02  1.120000e+03 -4.750000e+02       10.0   \n",
       "75%    2.997060e+06  1.100000e+03  1.470000e+03  2.500000e+01       10.0   \n",
       "max    3.996080e+06  1.450000e+03  1.820000e+03  5.250000e+02       10.0   \n",
       "\n",
       "              dY         dZ  pressure_MPa  sigma_h_max_MPa  sigma_h_min_MPa  \\\n",
       "count  3996081.0  3996081.0  3.996081e+06     3.996081e+06     3.996081e+06   \n",
       "mean        10.0       10.0  1.902218e+01     3.699827e+01     3.217816e+01   \n",
       "std          0.0        0.0  5.084631e+00     1.035117e+01     8.908026e+00   \n",
       "min         10.0       10.0  1.002488e+01     1.864353e+01     1.617470e+01   \n",
       "25%         10.0       10.0  1.464307e+01     2.821518e+01     2.474237e+01   \n",
       "50%         10.0       10.0  1.912009e+01     3.710544e+01     3.241430e+01   \n",
       "75%         10.0       10.0  2.343801e+01     4.591633e+01     3.983032e+01   \n",
       "max         10.0       10.0  2.766735e+01     5.518527e+01     4.743421e+01   \n",
       "\n",
       "        Sigma_V_MPa  temperature_C  \n",
       "count  3.996081e+06   3.996081e+06  \n",
       "mean   5.277819e+01   1.833050e+02  \n",
       "std    1.570728e+01   3.502214e+01  \n",
       "min    2.544605e+01   1.106922e+02  \n",
       "25%    3.904700e+01   1.541820e+02  \n",
       "50%    5.275623e+01   1.842313e+02  \n",
       "75%    6.641029e+01   2.131155e+02  \n",
       "max    8.065098e+01   2.555467e+02  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All is good.  BUT...because the file is so big, it can't be edited in Excel, so need to add some additional columns to the file now, and then later add the 10 row header that is usually written by Leapfrog"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Add the disp_k_bc\tdisp_j_bc\tdisp_i_bc\tvertical\th_max\th_min columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.insert(loc=8, column='disp_k_bc', value=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.insert(loc=9, column='disp_j_bc', value=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.insert(loc=10, column='disp_i_bc', value=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.insert(loc=11, column='vertical', value=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.insert(loc=12, column='h_max', value=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.insert(loc=13, column='h_min', value=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.rename(columns={'temperature_C': 'temperature'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.rename(columns={'pressure_MPa': 'pressure'}, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "now check the file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Id</th>\n",
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       "      <th>dX</th>\n",
       "      <th>dY</th>\n",
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       "      <th>disp_i_bc</th>\n",
       "      <th>vertical</th>\n",
       "      <th>h_max</th>\n",
       "      <th>h_min</th>\n",
       "      <th>sigma_h_max_MPa</th>\n",
       "      <th>sigma_h_min_MPa</th>\n",
       "      <th>Sigma_V_MPa</th>\n",
       "      <th>temperature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>420</td>\n",
       "      <td>-1475</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>54.383797</td>\n",
       "      <td>47.417642</td>\n",
       "      <td>78.659853</td>\n",
       "      <td>226.074346</td>\n",
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       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>420</td>\n",
       "      <td>-1475</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>27.666658</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>54.381446</td>\n",
       "      <td>47.412370</td>\n",
       "      <td>78.656734</td>\n",
       "      <td>226.210827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>70</td>\n",
       "      <td>420</td>\n",
       "      <td>-1475</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
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       "      <td>78.656918</td>\n",
       "      <td>226.350794</td>\n",
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       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>80</td>\n",
       "      <td>420</td>\n",
       "      <td>-1475</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>27.665727</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>54.383207</td>\n",
       "      <td>47.405856</td>\n",
       "      <td>78.660337</td>\n",
       "      <td>226.494008</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>90</td>\n",
       "      <td>420</td>\n",
       "      <td>-1475</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>27.665387</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>54.386726</td>\n",
       "      <td>47.404308</td>\n",
       "      <td>78.666232</td>\n",
       "      <td>226.640055</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id   X    Y     Z  dX  dY  dZ   pressure  disp_k_bc  disp_j_bc  disp_i_bc  \\\n",
       "0   0  50  420 -1475  10  10  10  27.667349          1          1          1   \n",
       "1   1  60  420 -1475  10  10  10  27.666658          1          1          1   \n",
       "2   2  70  420 -1475  10  10  10  27.666128          1          1          1   \n",
       "3   3  80  420 -1475  10  10  10  27.665727          1          1          1   \n",
       "4   4  90  420 -1475  10  10  10  27.665387          1          1          1   \n",
       "\n",
       "   vertical  h_max  h_min  sigma_h_max_MPa  sigma_h_min_MPa  Sigma_V_MPa  \\\n",
       "0         1      1      1        54.383797        47.417642    78.659853   \n",
       "1         1      1      1        54.381446        47.412370    78.656734   \n",
       "2         1      1      1        54.381283        47.408446    78.656918   \n",
       "3         1      1      1        54.383207        47.405856    78.660337   \n",
       "4         1      1      1        54.386726        47.404308    78.666232   \n",
       "\n",
       "   temperature  \n",
       "0   226.074346  \n",
       "1   226.210827  \n",
       "2   226.350794  \n",
       "3   226.494008  \n",
       "4   226.640055  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "now sort so values are in correct order for em2ex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = data.sort_values([\"Z\",\"Y\",\"X\"], ascending = [True, True, True])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Id</th>\n",
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       "      <th>dY</th>\n",
       "      <th>dZ</th>\n",
       "      <th>pressure</th>\n",
       "      <th>disp_k_bc</th>\n",
       "      <th>disp_j_bc</th>\n",
       "      <th>disp_i_bc</th>\n",
       "      <th>vertical</th>\n",
       "      <th>h_max</th>\n",
       "      <th>h_min</th>\n",
       "      <th>sigma_h_max_MPa</th>\n",
       "      <th>sigma_h_min_MPa</th>\n",
       "      <th>Sigma_V_MPa</th>\n",
       "      <th>temperature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>420</td>\n",
       "      <td>-1475</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>27.667349</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>54.383797</td>\n",
       "      <td>47.417642</td>\n",
       "      <td>78.659853</td>\n",
       "      <td>226.074346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>420</td>\n",
       "      <td>-1475</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>27.666658</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>54.381446</td>\n",
       "      <td>47.412370</td>\n",
       "      <td>78.656734</td>\n",
       "      <td>226.210827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>70</td>\n",
       "      <td>420</td>\n",
       "      <td>-1475</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>27.666128</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>54.381283</td>\n",
       "      <td>47.408446</td>\n",
       "      <td>78.656918</td>\n",
       "      <td>226.350794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>80</td>\n",
       "      <td>420</td>\n",
       "      <td>-1475</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>27.665727</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>54.383207</td>\n",
       "      <td>47.405856</td>\n",
       "      <td>78.660337</td>\n",
       "      <td>226.494008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>90</td>\n",
       "      <td>420</td>\n",
       "      <td>-1475</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>27.665387</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>54.386726</td>\n",
       "      <td>47.404308</td>\n",
       "      <td>78.666232</td>\n",
       "      <td>226.640055</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id   X    Y     Z  dX  dY  dZ   pressure  disp_k_bc  disp_j_bc  disp_i_bc  \\\n",
       "0   0  50  420 -1475  10  10  10  27.667349          1          1          1   \n",
       "1   1  60  420 -1475  10  10  10  27.666658          1          1          1   \n",
       "2   2  70  420 -1475  10  10  10  27.666128          1          1          1   \n",
       "3   3  80  420 -1475  10  10  10  27.665727          1          1          1   \n",
       "4   4  90  420 -1475  10  10  10  27.665387          1          1          1   \n",
       "\n",
       "   vertical  h_max  h_min  sigma_h_max_MPa  sigma_h_min_MPa  Sigma_V_MPa  \\\n",
       "0         1      1      1        54.383797        47.417642    78.659853   \n",
       "1         1      1      1        54.381446        47.412370    78.656734   \n",
       "2         1      1      1        54.381283        47.408446    78.656918   \n",
       "3         1      1      1        54.383207        47.405856    78.660337   \n",
       "4         1      1      1        54.386726        47.404308    78.666232   \n",
       "\n",
       "   temperature  \n",
       "0   226.074346  \n",
       "1   226.210827  \n",
       "2   226.350794  \n",
       "3   226.494008  \n",
       "4   226.640055  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "now we have all the needed columns in the dataframe.  Now can populate the new columns with data, and also fix the pressure and temperature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "a['temperature'] =+ a['temperature'] + 273.15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "a['pressure'] = a['pressure']* 1e6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "a['disp_k_bc'] = (a['Sigma_V_MPa'] * -1e6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "a['disp_j_bc'] = (a['sigma_h_max_MPa'] * -1e6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "a['disp_i_bc'] = (a['sigma_h_min_MPa'] * -1e6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "to get IC for effective stress, must convert total to negtive and Pa, the add pressure.  Note that alpha (0.6) was already factored into the calculation of total stress, so we don't need to worry about it converting back into MOOSE conventions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "a['vertical'] = (a['Sigma_V_MPa'] * -1e6) + (a['pressure'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "a['h_max'] = (a['sigma_h_max_MPa'] * -1e6) + (a['pressure'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "a['h_min'] = (a['sigma_h_min_MPa'] * -1e6) + (a['pressure'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "   Id   X    Y     Z  dX  dY  dZ    pressure   disp_k_bc   disp_j_bc  \\\n",
       "0   0  50  420 -1475  10  10  10  27667348.9 -78659853.2 -54383797.3   \n",
       "1   1  60  420 -1475  10  10  10  27666657.9 -78656733.8 -54381446.3   \n",
       "2   2  70  420 -1475  10  10  10  27666128.4 -78656918.4 -54381283.4   \n",
       "3   3  80  420 -1475  10  10  10  27665726.5 -78660336.9 -54383207.2   \n",
       "4   4  90  420 -1475  10  10  10  27665386.7 -78666231.6 -54386726.3   \n",
       "\n",
       "    disp_i_bc    vertical       h_max       h_min  sigma_h_max_MPa  \\\n",
       "0 -47417642.2 -50992504.3 -26716448.4 -19750293.3        54.383797   \n",
       "1 -47412369.6 -50990075.9 -26714788.4 -19745711.7        54.381446   \n",
       "2 -47408446.2 -50990790.0 -26715155.0 -19742317.8        54.381283   \n",
       "3 -47405856.2 -50994610.4 -26717480.7 -19740129.7        54.383207   \n",
       "4 -47404308.1 -51000844.9 -26721339.6 -19738921.4        54.386726   \n",
       "\n",
       "   sigma_h_min_MPa  Sigma_V_MPa  temperature  \n",
       "0        47.417642    78.659853   499.224346  \n",
       "1        47.412370    78.656734   499.360827  \n",
       "2        47.408446    78.656918   499.500794  \n",
       "3        47.405856    78.660337   499.644008  \n",
       "4        47.404308    78.666232   499.790055  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "now we can delete some columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "del a['sigma_h_max_MPa']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "del a['sigma_h_min_MPa']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "del a['Sigma_V_MPa']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and now the dataframe should be ready for em2ex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
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       "      <td>10</td>\n",
       "      <td>27665386.7</td>\n",
       "      <td>-78666231.6</td>\n",
       "      <td>-54386726.3</td>\n",
       "      <td>-47404308.1</td>\n",
       "      <td>-51000844.9</td>\n",
       "      <td>-26721339.6</td>\n",
       "      <td>-19738921.4</td>\n",
       "      <td>499.790055</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id   X    Y     Z  dX  dY  dZ    pressure   disp_k_bc   disp_j_bc  \\\n",
       "0   0  50  420 -1475  10  10  10  27667348.9 -78659853.2 -54383797.3   \n",
       "1   1  60  420 -1475  10  10  10  27666657.9 -78656733.8 -54381446.3   \n",
       "2   2  70  420 -1475  10  10  10  27666128.4 -78656918.4 -54381283.4   \n",
       "3   3  80  420 -1475  10  10  10  27665726.5 -78660336.9 -54383207.2   \n",
       "4   4  90  420 -1475  10  10  10  27665386.7 -78666231.6 -54386726.3   \n",
       "\n",
       "    disp_i_bc    vertical       h_max       h_min  temperature  \n",
       "0 -47417642.2 -50992504.3 -26716448.4 -19750293.3   499.224346  \n",
       "1 -47412369.6 -50990075.9 -26714788.4 -19745711.7   499.360827  \n",
       "2 -47408446.2 -50990790.0 -26715155.0 -19742317.8   499.500794  \n",
       "3 -47405856.2 -50994610.4 -26717480.7 -19740129.7   499.644008  \n",
       "4 -47404308.1 -51000844.9 -26721339.6 -19738921.4   499.790055  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "now can write the data to a CSV file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "a.to_csv(\"processed_local_large_well_3_1b_node.csv\", encoding='utf-8', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "a.describe().to_csv(\"processed_local_large_well_3_1b_node_Summary.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "now need to read into leapfrog and verify all the mpaaings"
   ]
  }
 ],
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