Part_1.Data_Processing.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Inversion of a Transect of MT Tipper data. Part I\n",
    "\n",
    "This dataset consists of 29 Magnetotelluric stations arranged on a 2D transect. Our objective is to invert the tipper data on line 5000 using MtPy to (hopefully) reveal a conductive structure known to exist under the array. While the task is straightforward, there are a number of smaller tasks we'll have to complete in sequence:\n",
    "\n",
    "1) Loading and cleaning the data\n",
    "\n",
    "2) Parsing data into MtPy compatible formats\n",
    "\n",
    "3) Visualizing the data\n",
    "\n",
    "4) Set up Occam2D Inversion\n",
    "\n",
    "5) Explore Inversion Parameters\n",
    "\n",
    "6) Analyze Results\n",
    "\n",
    "Before following this jupyter notebook tutorial, ensure you have the latest version of miniconda3 installed. Create an ```mtpy_inversion``` environment by installing the following packages in series\n",
    "```\n",
    "conda create --name mtpy_inversion\n",
    "source activate mtpy_inversion\n",
    "conda install python=3.6.8\n",
    "conda install numpy scipy matplotlib pandas cartopy\n",
    "pip install mtpy\n",
    "```\n",
    "\n",
    "#### How to use this notebook\n",
    "\n",
    "Cells in this notebook are divided into two types:\n",
    "\n",
    "- Helper Cells\n",
    "\n",
    "- Data Manipulation/Exploration Cells\n",
    "\n",
    "Only the \"Helper cells\" are labeled for convenience. You may, of course, edit any cell you wish, or copy bits of code to use in your own analysis. There is one external module you need called ```cartopy_mapping.py```. Make sure this python file is in the same directory you run this notebook from.\n",
    "\n",
    "This notebook performs steps 1) and 2) as described above. It is meant to be used prior to executing Part_2.Data_Analysis. The first cell you execute will shoot out some warnings. Don't worry, this won't affect anything.\n",
    "\n",
    "After you're done with this notebook move on to Part II.\n",
    "\n",
    "## Step 1. load the data. \n",
    "\n",
    "The data are provided in a .csv file. Since pandas is well-suited for loading csv's, I'll load it into a pandas dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GDAL_DATA environment variable is not set  Please see https://trac.osgeo.org/gdal/wiki/FAQInstallationAndBuilding#HowtosetGDAL_DATAvariable \n",
      "WARNING:mtpy.utils.decorator:GDAL_DATA environment variable is not set  Please see https://trac.osgeo.org/gdal/wiki/FAQInstallationAndBuilding#HowtosetGDAL_DATAvariable \n",
      "WARNING:mtpy.utils.decorator:GDAL_DATA environment variable is not set  Please see https://trac.osgeo.org/gdal/wiki/FAQInstallationAndBuilding#HowtosetGDAL_DATAvariable \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ignore GDAL as it is not working. Will use pyproj\n",
      "Ignore GDAL as it is not working. Will use pyproj\n",
      "Ignore GDAL as it is not working. Will use pyproj\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "HELPER CELL\n",
    "\n",
    "for importing relevant modules\n",
    "\n",
    "\"\"\"\n",
    "\n",
    "import matplotlib.cm as cm\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from scipy import ndimage as nd\n",
    "import cartopy_mapping\n",
    "import numpy as np\n",
    "from mtpy.core.z import Tipper, Z\n",
    "from mtpy.core.mt import MT\n",
    "import os\n",
    "import glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('original_data/YGS-20200107-ELF_with_repeat_readings.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's Look at the data dimensions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Line</th>\n",
       "      <th>Station</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long</th>\n",
       "      <th>E_WGS84_Z7</th>\n",
       "      <th>N_WGS84_Z7</th>\n",
       "      <th>ALT</th>\n",
       "      <th>Az</th>\n",
       "      <th>Dur</th>\n",
       "      <th>Noise</th>\n",
       "      <th>...</th>\n",
       "      <th>iN_0720</th>\n",
       "      <th>iN_1440</th>\n",
       "      <th>SNI_0011</th>\n",
       "      <th>SNI_0022</th>\n",
       "      <th>SNI_0045</th>\n",
       "      <th>SNI_0090</th>\n",
       "      <th>SNI_0180</th>\n",
       "      <th>SNI_0360</th>\n",
       "      <th>SNI_0720</th>\n",
       "      <th>SNI_1440</th>\n",
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       "  </thead>\n",
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       "      <td>592876.0</td>\n",
       "      <td>6804421.0</td>\n",
       "      <td>1271.7</td>\n",
       "      <td>9.4</td>\n",
       "      <td>164</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.070</td>\n",
       "      <td>0.159</td>\n",
       "      <td>27.3</td>\n",
       "      <td>132.4</td>\n",
       "      <td>330.9</td>\n",
       "      <td>606.8</td>\n",
       "      <td>759.6</td>\n",
       "      <td>765.9</td>\n",
       "      <td>243.9</td>\n",
       "      <td>72.5</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>61.362678</td>\n",
       "      <td>-139.262820</td>\n",
       "      <td>592876.0</td>\n",
       "      <td>6804421.0</td>\n",
       "      <td>1271.7</td>\n",
       "      <td>79.9</td>\n",
       "      <td>226</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.038</td>\n",
       "      <td>0.048</td>\n",
       "      <td>48.5</td>\n",
       "      <td>65.3</td>\n",
       "      <td>510.1</td>\n",
       "      <td>1254.6</td>\n",
       "      <td>2970.4</td>\n",
       "      <td>5078.0</td>\n",
       "      <td>5034.9</td>\n",
       "      <td>2071.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>250</td>\n",
       "      <td>61.364319</td>\n",
       "      <td>-139.259848</td>\n",
       "      <td>593030.0</td>\n",
       "      <td>6804608.0</td>\n",
       "      <td>1257.7</td>\n",
       "      <td>130.6</td>\n",
       "      <td>251</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.007</td>\n",
       "      <td>-0.003</td>\n",
       "      <td>30.8</td>\n",
       "      <td>152.1</td>\n",
       "      <td>389.2</td>\n",
       "      <td>713.9</td>\n",
       "      <td>812.3</td>\n",
       "      <td>913.9</td>\n",
       "      <td>399.7</td>\n",
       "      <td>110.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>500</td>\n",
       "      <td>61.365838</td>\n",
       "      <td>-139.256965</td>\n",
       "      <td>593179.6</td>\n",
       "      <td>6804781.3</td>\n",
       "      <td>1268.5</td>\n",
       "      <td>145.8</td>\n",
       "      <td>180</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.014</td>\n",
       "      <td>0.050</td>\n",
       "      <td>68.4</td>\n",
       "      <td>123.8</td>\n",
       "      <td>288.8</td>\n",
       "      <td>544.9</td>\n",
       "      <td>650.4</td>\n",
       "      <td>477.9</td>\n",
       "      <td>197.1</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>750</td>\n",
       "      <td>61.367767</td>\n",
       "      <td>-139.253557</td>\n",
       "      <td>593356.0</td>\n",
       "      <td>6805001.0</td>\n",
       "      <td>1233.2</td>\n",
       "      <td>238.9</td>\n",
       "      <td>160</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.031</td>\n",
       "      <td>0.026</td>\n",
       "      <td>36.1</td>\n",
       "      <td>122.3</td>\n",
       "      <td>370.8</td>\n",
       "      <td>770.2</td>\n",
       "      <td>1274.0</td>\n",
       "      <td>1790.1</td>\n",
       "      <td>1565.3</td>\n",
       "      <td>498.5</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <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",
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       "    <tr>\n",
       "      <th>417</th>\n",
       "      <td>11000</td>\n",
       "      <td>6250</td>\n",
       "      <td>61.339016</td>\n",
       "      <td>-139.031672</td>\n",
       "      <td>605311.0</td>\n",
       "      <td>6802137.0</td>\n",
       "      <td>846.5</td>\n",
       "      <td>349.9</td>\n",
       "      <td>188</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001</td>\n",
       "      <td>-0.030</td>\n",
       "      <td>28.4</td>\n",
       "      <td>152.8</td>\n",
       "      <td>437.3</td>\n",
       "      <td>800.6</td>\n",
       "      <td>512.8</td>\n",
       "      <td>412.7</td>\n",
       "      <td>127.9</td>\n",
       "      <td>20.5</td>\n",
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       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>11000</td>\n",
       "      <td>6500</td>\n",
       "      <td>61.340766</td>\n",
       "      <td>-139.028496</td>\n",
       "      <td>605475.0</td>\n",
       "      <td>6802337.0</td>\n",
       "      <td>838.2</td>\n",
       "      <td>253.4</td>\n",
       "      <td>164</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.014</td>\n",
       "      <td>-0.022</td>\n",
       "      <td>108.3</td>\n",
       "      <td>126.6</td>\n",
       "      <td>325.2</td>\n",
       "      <td>675.6</td>\n",
       "      <td>864.5</td>\n",
       "      <td>913.2</td>\n",
       "      <td>468.9</td>\n",
       "      <td>105.8</td>\n",
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       "    <tr>\n",
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       "      <td>-139.025425</td>\n",
       "      <td>605634.0</td>\n",
       "      <td>6802517.0</td>\n",
       "      <td>833.4</td>\n",
       "      <td>286.7</td>\n",
       "      <td>165</td>\n",
       "      <td>0.1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.034</td>\n",
       "      <td>-0.067</td>\n",
       "      <td>149.3</td>\n",
       "      <td>212.9</td>\n",
       "      <td>578.6</td>\n",
       "      <td>963.7</td>\n",
       "      <td>763.2</td>\n",
       "      <td>506.8</td>\n",
       "      <td>110.0</td>\n",
       "      <td>11.0</td>\n",
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       "    <tr>\n",
       "      <th>420</th>\n",
       "      <td>11000</td>\n",
       "      <td>7000</td>\n",
       "      <td>61.343953</td>\n",
       "      <td>-139.022219</td>\n",
       "      <td>605800.0</td>\n",
       "      <td>6802702.0</td>\n",
       "      <td>827.6</td>\n",
       "      <td>199.1</td>\n",
       "      <td>197</td>\n",
       "      <td>0.1</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.011</td>\n",
       "      <td>NaN</td>\n",
       "      <td>137.9</td>\n",
       "      <td>221.2</td>\n",
       "      <td>555.7</td>\n",
       "      <td>948.2</td>\n",
       "      <td>893.5</td>\n",
       "      <td>293.1</td>\n",
       "      <td>64.3</td>\n",
       "      <td>4.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>421</th>\n",
       "      <td>11000</td>\n",
       "      <td>7000</td>\n",
       "      <td>61.343953</td>\n",
       "      <td>-139.022219</td>\n",
       "      <td>605800.0</td>\n",
       "      <td>6802702.0</td>\n",
       "      <td>827.6</td>\n",
       "      <td>165.0</td>\n",
       "      <td>198</td>\n",
       "      <td>0.1</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.001</td>\n",
       "      <td>-0.207</td>\n",
       "      <td>105.6</td>\n",
       "      <td>151.4</td>\n",
       "      <td>450.5</td>\n",
       "      <td>1075.3</td>\n",
       "      <td>2026.8</td>\n",
       "      <td>2710.3</td>\n",
       "      <td>1262.4</td>\n",
       "      <td>72.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>422 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Line  Station        Lat        Long  E_WGS84_Z7  N_WGS84_Z7     ALT  \\\n",
       "0        0        0  61.362678 -139.262820    592876.0   6804421.0  1271.7   \n",
       "1        0        0  61.362678 -139.262820    592876.0   6804421.0  1271.7   \n",
       "2        0      250  61.364319 -139.259848    593030.0   6804608.0  1257.7   \n",
       "3        0      500  61.365838 -139.256965    593179.6   6804781.3  1268.5   \n",
       "4        0      750  61.367767 -139.253557    593356.0   6805001.0  1233.2   \n",
       "..     ...      ...        ...         ...         ...         ...     ...   \n",
       "417  11000     6250  61.339016 -139.031672    605311.0   6802137.0   846.5   \n",
       "418  11000     6500  61.340766 -139.028496    605475.0   6802337.0   838.2   \n",
       "419  11000     6750  61.342338 -139.025425    605634.0   6802517.0   833.4   \n",
       "420  11000     7000  61.343953 -139.022219    605800.0   6802702.0   827.6   \n",
       "421  11000     7000  61.343953 -139.022219    605800.0   6802702.0   827.6   \n",
       "\n",
       "        Az  Dur  Noise  ...  iN_0720  iN_1440  SNI_0011  SNI_0022  SNI_0045  \\\n",
       "0      9.4  164    0.0  ...    0.070    0.159      27.3     132.4     330.9   \n",
       "1     79.9  226    0.0  ...    0.038    0.048      48.5      65.3     510.1   \n",
       "2    130.6  251    0.0  ...   -0.007   -0.003      30.8     152.1     389.2   \n",
       "3    145.8  180    0.0  ...    0.014    0.050      68.4     123.8     288.8   \n",
       "4    238.9  160    0.0  ...    0.031    0.026      36.1     122.3     370.8   \n",
       "..     ...  ...    ...  ...      ...      ...       ...       ...       ...   \n",
       "417  349.9  188    0.0  ...    0.001   -0.030      28.4     152.8     437.3   \n",
       "418  253.4  164    0.0  ...    0.014   -0.022     108.3     126.6     325.2   \n",
       "419  286.7  165    0.1  ...    0.034   -0.067     149.3     212.9     578.6   \n",
       "420  199.1  197    0.1  ...   -0.011      NaN     137.9     221.2     555.7   \n",
       "421  165.0  198    0.1  ...   -0.001   -0.207     105.6     151.4     450.5   \n",
       "\n",
       "     SNI_0090  SNI_0180  SNI_0360  SNI_0720  SNI_1440  \n",
       "0       606.8     759.6     765.9     243.9      72.5  \n",
       "1      1254.6    2970.4    5078.0    5034.9    2071.3  \n",
       "2       713.9     812.3     913.9     399.7     110.1  \n",
       "3       544.9     650.4     477.9     197.1      16.0  \n",
       "4       770.2    1274.0    1790.1    1565.3     498.5  \n",
       "..        ...       ...       ...       ...       ...  \n",
       "417     800.6     512.8     412.7     127.9      20.5  \n",
       "418     675.6     864.5     913.2     468.9     105.8  \n",
       "419     963.7     763.2     506.8     110.0      11.0  \n",
       "420     948.2     893.5     293.1      64.3       4.6  \n",
       "421    1075.3    2026.8    2710.3    1262.4      72.3  \n",
       "\n",
       "[422 rows x 50 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I know the .csv data is structured Like so:\n",
    "\n",
    "* **Line**: Local grid's line value\n",
    "* **Station**: Local grid's station value\n",
    "* **Lat**: Latitude\n",
    "* **Longitude**: Longitude\n",
    "* **E_WGS84_Z7**: Easting\n",
    "* **N_WGS84_Z7z**: Northing\n",
    "* **ALT**: Station Altitude (m)\n",
    "* **DUR**: Duration of the reading (s)\n",
    "* **Noise**: Level of Industrial Noise\n",
    "* **nE_M**: East Tipper measurement of frequency M. if ```n=='r'```, data is the real component. If ```n=='i'```, data is the imaginary component.\n",
    "* **nN_M**: North Tipper measurement of frequency M. if ```n=='r'```, data is the real component. If ```n=='i'```, data is the imaginary component.\n",
    "* **SNI_M**: Signal-to-noise index of component M.\n",
    "\n",
    "**M** takes on the values of 11, 22, 45, 90, 180, 360, 720, and 1440 Hz.\n",
    "\n",
    "I will further assume the tipper is defined as:\n",
    "\n",
    "$$H_z(\\omega) = \\bf{[}T_n(\\omega), T_e(\\omega)\\bf{]}\\begin{bmatrix}\n",
    "           H_n(\\omega) \\\\\n",
    "           H_e(\\omega) \\\\\n",
    "         \\end{bmatrix}$$\n",
    "         \n",
    "And individual components can be expressed as\n",
    "$$\\frac{H_z(\\omega)}{H_n(\\omega)} = T_n(\\omega)$$\n",
    "\n",
    "\n",
    "$$\\frac{H_z(\\omega)}{H_e(\\omega)} = T_e(\\omega)$$\n",
    "\n",
    "It appears as if each row represents the $T_x(\\omega)$ data and metadata relevant to a single station. Lets check how many stations exist in line 5000."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "29"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_line_5000=data[data['Line']==5000]\n",
    "len(data_line_5000.Station.unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How many repeat measurements can we find in this line?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.axis.YTick at 0x7fdc5555ae48>,\n",
       " <matplotlib.axis.YTick at 0x7fdc5555a710>,\n",
       " <matplotlib.axis.YTick at 0x7fdc556496a0>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = data_line_5000['Station'].value_counts().plot(kind='bar',\n",
    "                                    figsize=(14,8),\n",
    "                                    title=\"Number of measurements per station\")\n",
    "ax.set_xlabel(\"Station\")\n",
    "ax.set_ylabel(\"Count\")\n",
    "ax.set_yticks([0,1,2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Stations 0, 3000,5000,6000,2000,1000,7000, and 4000 have 2 repeat occupations. All the other lines appear to only have one occupation. For now lets drop the first ocurrence of each repeat occupation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_1            = data_line_5000.sort_values(by=['Station'],ascending = [True])\n",
    "df_1['cumcount']= df_1.groupby('Station').cumcount()\n",
    "data_line_5000  = data_line_5000[df_1['cumcount'] ==0]\n",
    "data_line_5000  = data_line_5000.sort_values(by=['Station'],ascending = [True])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.axis.YTick at 0x7fdc55449550>,\n",
       " <matplotlib.axis.YTick at 0x7fdc55442da0>,\n",
       " <matplotlib.axis.YTick at 0x7fdc552275f8>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = data_line_5000['Station'].value_counts().plot(kind='bar',\n",
    "                                    figsize=(14,8),\n",
    "                                    title=\"Number of measurements per station\")\n",
    "ax.set_xlabel(\"Station\")\n",
    "ax.set_ylabel(\"Count\")\n",
    "ax.set_yticks([0,1,2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I'm not sure why the stations aren't sorted in ascending order, but our station-pruning operation has been successful.\n",
    "\n",
    "\n",
    "While we have the metadata nicely packed away in a dataframe, lets see how the stations are distributed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<cartopy.mpl.geoaxes.GeoAxes at 0x7fdc554c50f0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cartopy_mapping.plot_map(data_line_5000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data are arranged on a nice NE-SW transect. How about the data itself?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "HELPER CELL\n",
    "\n",
    "for plotting the data, separating by both direction and real/imaginary component.\n",
    "\n",
    "\"\"\"\n",
    "def sort_data_into_columns(df,direction='N',part='real'):\n",
    "    data_columns = ['rE_0011', 'rE_0022', 'rE_0045', 'rE_0090',\n",
    "       'rE_0180', 'rE_0360', 'rE_0720', 'rE_1440', 'rN_0011', 'rN_0022',\n",
    "       'rN_0045', 'rN_0090', 'rN_0180', 'rN_0360', 'rN_0720', 'rN_1440','iE_0011', 'iE_0022', 'iE_0045', 'iE_0090', 'iE_0180', 'iE_0360',\n",
    "       'iE_0720', 'iE_1440', 'iN_0011', 'iN_0022', 'iN_0045', 'iN_0090',\n",
    "       'iN_0180', 'iN_0360', 'iN_0720', 'iN_1440']\n",
    "    cols_to_use =[]\n",
    "    for col in data_columns:\n",
    "        if direction in col:\n",
    "            if part=='real':\n",
    "                if 'r' in col:\n",
    "                    cols_to_use.append(col)\n",
    "            else:\n",
    "                if 'i' in col:\n",
    "                    cols_to_use.append(col)\n",
    "                    \n",
    "    d_subset = df.loc[:,cols_to_use]\n",
    "    d_subset = d_subset.reindex(sorted(d_subset.columns), axis=1)\n",
    "    return d_subset\n",
    "\n",
    "def plot_data(df,direction='N',part='real'):\n",
    "    d_subset     = sort_data_into_columns(df,direction=direction,part=part)\n",
    "    frequencies  = [int(x.split('_')[1]) for x in d_subset.columns]\n",
    "    stations     = df['Station'].values\n",
    "    data         = d_subset.values\n",
    "\n",
    "    fig,ax = plt.subplots(figsize=(10,10))\n",
    "    current_cmap = cm.get_cmap()\n",
    "    current_cmap.set_bad(color='red')\n",
    "    im = ax.imshow(data.T)\n",
    "    cbar = ax.figure.colorbar(im, ax=ax,fraction=0.012, pad=0.04)\n",
    "    cbar.ax.set_ylabel('value', rotation=-90, va=\"bottom\")\n",
    "    ax.set_xticks(np.arange(len(stations)))\n",
    "    ax.set_yticks(np.arange(len(frequencies)))\n",
    "    ax.set_xticklabels(stations)\n",
    "    ax.set_yticklabels(frequencies)\n",
    "    plt.setp(ax.get_xticklabels(), rotation=45, ha=\"right\",\n",
    "         rotation_mode=\"anchor\")\n",
    "    ax.set_title(\"{} Value of component {}\".format(part,direction))\n",
    "    fig.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1OuKbmZmZ2egKxPKBKQ2XiaauK/oCcBxPnkPqLZKuk3S6pNWHO1jSkZIWSFrQ/+jDNSXRzMzMzFoWk6eJRfErkrQXcHdE/HbIU6cAzwC2BO4E/nu4GBExPyK2iYht+laaUTqJZmZmZtamwSYWjZaJpo42yC8A9s6d8FYEVpH07Yh4/eAOkr4GXFjDuc3MzMysBoNNLCaD4lcZEcdHxJyI2ADYH/h5RLxe0uzKbq8Eri99bjMzMzOrT39MabhMNKM5DvJnJG1JqqG/FThqFM9tZmZmZl2IgP5JUoNcawE5Ii4DLsuPD6rzXGZmZmZWp4nZ3rgRz6RnZmZmZk0Fk6cGeXJcpZmZmZl1J6A/1HBphaTdJd0s6RZJ72vw/DMlXS5piaR3F09/G1yDbGZmZmZNBRAdNrGQ1Ad8BXgpsAi4WtL5EXFDZbf7gLcB+3aZ1K65BtnMzMzMWiD6BxovLdgWuCUi/hIRS4FzgH2qO0TE3RFxNbCsfNrb4xpkMzMzM2sqAgaGb4M8S9KCyvr8iJhfWV8XuL2yvgjYrnASi+n5AnKsAEvWjGLxHn1q+UuOKWV7dA70FQ1Xixl3DZ1FvDtTlpV7jQGWzZhaNN6MO8qmD2Da4rJ5OP3+5UXjDfSV76n82Jplb+5lTyn8I5jKv84DZW9Flq9U9nVRf/nXOVbuLxywbDgKX7MeLv+h3fdI4del7McNAzWUHqYUrjMcmFY23vIVa3ivlMzHUWoTMEJt8T0Rsc0IhzY6sPyHbiE9X0A2MzMzs97QaRtkUo3x3Mr6HOCOrhNUE7dBNjMzM7OmIo+D3GhpwdXAPEkbSppGmm35/FoT3AXXIJuZmZlZcwHRWoe8Jx8asVzSW4BLgD7g9IhYKOno/PypktYGFgCrAAOS3gFsFhEPlrmA1rmAbGZmZmYtGeiwgAwQERcBFw3Zdmrl8V2kphdjzgVkMzMzM2uqm3GQx5va2iBLeruk6yUtzFXkSFpD0qWS/pT/rl7X+c3MzMysoNzEotEy0dRSQJa0OXAEaVDo5wB7SZoHvA/4WUTMA36W183MzMys5zUuHLuA3LpNgSsi4pGIWA78AnglacaUM/I+Z9ADUwmamZmZWYtimGUckbSlpBNH2qeuAvL1wIskrSlpZWBP0th3T4uIOwHy37VqOr+ZmZmZlTSOm1hI2kzSRyUtBL4A3DbS/rV00ouIGyV9GrgUWAz8Hmh5mi9JRwJHAqywqpspm5mZmfWEcdhJT9J1wEPAOcAuebSMEdXWSS8iTouI50bEi4D7gD8B/5A0Oyd2NnD3MMfOj4htImKbvhkz6kqimZmZmbUqgAE1Xnrb3cCawNq02HqhzlEs1sp/1wNeBZxNmjHlkLzLIcCP6jq/mZmZmZUV0XjpZRGxK7ATaWrrr+QR1j480jF1joP8A0lrAsuAYyLiX7lB9LmSDgP+BrymxvObmZmZWUm9X1v8JLk8+lrgAWBnYDbwxpGOqa2AHBE7Nth2L7BLXec0MzMzs5oEaGCsE9GRC4CrSc0rnkcaZvhFIx3gmfTMzMzMrAUal530gBUi4u2SpgC/i4jFklYb6YDa2iCbmZmZ2QQzMMzS266V9OKIGAAGcpOLqSMd4BpkMzMzM2tucBSL8ecFwOGSbiM1s7gCeNdIB7iAbGZmZmYtGadtkPeoPH4sIhoOM1zlArKZmZmZTVgR8bd2j+n5AnKsECyZ1V8s3sMPlr/k/hXLxpv6UNl4dUySPvWhcq8JwNTFLU+02JJpD6xUNN5TFi0rGg+g75Gy17zC/Y8Vjbd8tcI3NvDYGn1F4w1MLXtvR9nkATAwvWwapywt+/Nm39Ki4VLMFcve2/0PTisaT4XzcMV/lr9xphR+XVT438BADaWH0jWTU5aUjUcNLQtK9ncbraGINQ6bWEh6kPQKNsomRcRThm7s+QKymZmZmfWAYDx0yHuSiFil3WNcQDYzMzOzlpT+NWK0SJoDrE+l7BsRvxhufxeQzczMzKw147AGOc/kvB9wA49fgQAXkM3MzMysc4rx2QYZ2AfYJCJa7lDkiULMzMzMrCUaaLz0uD8BK7dzQFcFZEmnS7pb0vWVbVtKukLStZIWSNq28tzxkm6RdLOk3bo5t5mZmZmNshhm6W1Lgd9J+pqkkwaXkQ7otonFN4EvA2dWtn0G+GhEXCxpz7y+s6TNgP2BZwHrAD+VtHFElB0vzMzMzMzKi3FRW9zI+XlpWVcF5Ij4paQNhm4GBofTWBW4Iz/eBzgnIpYAf5V0C7AtcHk3aTAzMzOz0TEeC8gRcaakqcAmpHLqzREx4oDtdXTSewdwiaT/IjXh2CFvX5c09/WgRXmbmZmZmVktJG0BfB/4J7A5cL2kt0bENcMdU0cnvTcB74yIucA7gdMG09dg34atViQdmdsvL+hf/HANSTQzMzOztsS47aR3EnBwRLwA+DOwN/C5kQ6oo4B8CPDD/Ph7pGYUkGqM51b2m8PjzS+eICLmR8Q2EbFN38wZNSTRzMzMzNo2MMzS21aNiMFWDIqIe4ERC5h1FJDvAHbKj19CGloDUuPo/SVNl7QhMA+4qobzm5mZmVlhYtzWIPdJGmxWPEXSfsA9Ix3QVRtkSWcDOwOzJC0CPgwcAXwxJ+Qx4EiAiFgo6VzSLCbLgWM8goWZmZnZOBHjdqrpLwAbk8qgdwC7AW8Y6YBuR7E4YJinth5m/xOAE7o5p5mZmZmNkd6vLX6SiDit8niPVo7xVNNmZmZm1pJx0JyiCE81bWZmZmbNdTmKhaTd82zKt0h6X4PnJelL+fnrJD239CW0ygVkMzMzM2tNh1NNS+oDvgLsAWwGHJBnWa7agzSIwzxSH7ZTSiW7XS4gm5mZmVlLuqhB3ha4JSL+EhFLgXNIsyxX7QOcGckVwGqSZhe9gBa5gGxmZmZmTSmGX1qwLnB7Zb3RjMqt7DMqer+TnoDp5VqEP/q08uOTxNqPFY2nG1cqGq/v0UaTGPaYKPu6TF1cNt60fz5aNB5A/yrTisZT4TzsX7n8x8PACmXvxSj8FT9WKP/5MFDw8wugf6Wyedj/WPnPh9IRp97fVzReX+Frnn5v0XBJ4Xt7oGwWtvSTertUeODX0p3JSn/eAGVf59H6Vz/8az9L0oLK+vyImF9Zb2VG5ZZnXa5b7xeQzczMzKwnjPDF456I2GaEQ1uZUbnlWZfr5iYWZmZmZtZcd6NYXA3Mk7ShpGnA/qRZlqvOBw7Oo1lsDzwQEXcWvYYWuQbZzMzMzFrSadOViFgu6S3AJUAfcHqeZfno/PypwEXAnsAtwCPAoSXS3AkXkM3MzMysNV20CI6Ii0iF4Oq2UyuPAzim8zOU4wKymZmZmTUXk2cmPReQzczMzKwpMXkKyB130pO0oqSrJP1e0kJJH60899Y8leBCSZ+pbD8+Tx94s6Tduk28mZmZmY2iDmfSG2+6qUFeArwkIhZLmgr8StLFwEqkmVC2iIglktYCyNMJ7g88C1gH+KmkjSOi8MiHZmZmZlZcgAYmYGm4gY5rkPM0gIvz6tS8BPAm4MSIWJL3uzvvsw9wTkQsiYi/knoobttxys3MzMxsVHUxzNu40tU4yJL6JF0L3A1cGhFXAhsDO0q6UtIvJD0v797y9IGSjpS0QNKC/sUPd5NEMzMzMyvEBeQWRER/RGxJmulkW0mbk5ptrA5sD7wHOFeSaGP6wIiYHxHbRMQ2fTNndJNEMzMzMyshQMMsE02RUSwi4n5JlwG7k2qGf5jHsrtK0gAwix6aPtDMzMzM2uNRLFog6amSVsuPVwJ2BW4C/gd4Sd6+MTANuIc0feD+kqZL2hCYB1zVXfLNzMzMbLRoIBouE003NcizgTMk9ZEK2udGxIV5fu3TJV0PLAUOybXJCyWdC9wALAeO8QgWZmZmZuPEBB3SrZGOC8gRcR2wVYPtS4HXD3PMCcAJnZ7TzMzMzMaOJknVpmfSMzMzM7PmJtE4yC4gm5mZmVlLJksnPReQzczMzKwpMTGHdGvEBWQzMzMzay4m5ogVjbiAbGZmZmYtcROLXhHA0q4m/HuCOl7Yjda9u2i8v966XtF4K97XaBLD7jyw4dSi8Va/pew30oc2LBqONb6xsGxA4M737lA03uzfFA3HI08t//FQ+v23wqNl7+0lK5f/gHjJVjcUjffzazcrGk/L+4rGAxgYKPu6zLyzbLwofMlTHy5fo7Z85bLxphR+TZauWjQcANMeKBtvhUfLvi5LViv/v3SFx8rFGpWmDwG4BtnMzMzM7HGuQTYzMzMzq3AbZDMzMzOzTB4H2czMzMxsCDexMDMzMzPLJlENcsfDQ0jaRNK1leVBSe+Q9FlJN0m6TtJ5klarHHO8pFsk3SxptzKXYGZmZmb1S+MgN1ommo4LyBFxc0RsGRFbAlsDjwDnAZcCm0fEFsAfgeMBJG0G7A88C9gdOFlS+fGFzMzMzKy8APVHw2WiKTXA8C7AnyPitoj4SUQsz9uvAObkx/sA50TEkoj4K3ALsG2h85uZmZlZ3SIaLxNMqQLy/sDZDba/Ebg4P14XuL3y3KK87UkkHSlpgaQF/YsfLpREMzMzM+uGm1i0SNI0YG/ge0O2fwBYDnxncFODwxvmaETMj4htImKbvpkzuk2imZmZmXUrgP5ovEwwJUax2AO4JiL+MbhB0iHAXsAuEf+ud18EzK0cNwe4o8D5zczMzKxmItAEbE7RSIkmFgdQaV4haXfgvcDeEfFIZb/zgf0lTZe0ITAPuKrA+c3MzMxsNAwMNF4mmK5qkCWtDLwUOKqy+cvAdOBSSQBXRMTREbFQ0rnADaSmF8dERH835zczMzOzUZJHsZgMuiog5xriNYds22iE/U8ATujmnGZmZmY2FmJC1hY34pn0zMzMzKy5YEIO6dZIqWHezMzMzGyCq2OiEElrSLpU0p/y39WH2e90SXdLur6rE7bABWQzMzMzay6A/oHGS3feB/wsIuYBP8vrjXyTNBtz7VxANjMzM7MWDDOLXvfNLvYBzsiPzwD2bXj2iF8C93V7sla4DbKZmZmZtWb4TnqzJC2orM+PiPktRn1aRNwJEBF3SlqrmySW0PMFZC0TK91RLpkr3lO+cfmsHctOh/3XwvX6Wl42HsBTf1f2mqcsKzvi3yp/mVo03qXx/aLxADixbMyd9vh00XgPzy7/A9PCzx5bNN68T/x30Xi3vvU9ReNZb3rWcZ8rGq9vafn/K/3TG00+27mlDVt0dm7Fe8rGA4i+svEGCpdw+paWjQcwUPBfVZS9ZYY5SUD/sP+v74mIbYZ7UtJPgbUbPPWBEkkrrecLyGZmZmbWAwbbIHdyaMSuwz0n6R+SZufa49nA3R2msBi3QTYzMzOz1tTTBvl84JD8+BDgR90G7JYLyGZmZmbWgqhrqukTgZdK+hNphuYTASStI+miwZ0knQ1cDmwiaZGkw7o98XDcxMLMzMzMmgtGaoPcediIe4FdGmy/A9izsn5A8ZMPwwVkMzMzM2uNZ9JLRpq1RNK7JYWkWUO2rydpsaR3V7ZtLekPkm6R9CVJo9Hf0szMzMxKiCD6+xsuE00rbZC/SYNZSyTNJbUT+VuDYz4PXDxk2ynAkcC8vIzKTChmZmZmVkg9M+n1nKYF5BFmLfk8cBypRcq/SdoX+AuwsLJtNrBKRFweEQGcyTCzpJiZmZlZDxocB7nRMsF0NIqFpL2Bv0fE74dsnwG8F/jokEPWBRZV1hflbWZmZmY2TsTAQMNlomm7k56klUmznryswdMfBT4fEYuHNDFu1N542Fbeko4kNccAWHzzx469uYWkzQJKzu3Tcrzfn1w2XhvG7JrHKF7rMa8uG6+NBvNjl4cXv7dszKGNpLqNR8v52Po1f/BdrUWcSK/z2MSrI+bYxftMyzM6TpxrHpt4dcTs9Xh1xGw13voFz9lYxIRsTtFIJ6NYPAPYEPh9LgTPAa6RtC2wHfAfkj4DrAYMSHoM+EHeb9Ac4I7hTpDn7m51/m4AJC0YaYrDdvV6vDpi9nq8OmJOtnh1xOz1eHXEnGzx6ojZ6/HqiDnZ4tURs9fj1RGzjjR2KmBCdshrpO0CckT8AVhrcF3SrcA2EXEPsGNl+0eAxRHx5bz+kKTtgSuBg4GTukq5mSXiLSYAABUESURBVJmZmY2ePIrFZNC0gJxnLdkZmCVpEfDhiDitg3O9iTQixkqkH29b/wHXzMzMzMbUQ/zrkp8OnDtrmKdLN1UZU00LyM1mLYmIDYbZ/pEh6wuAzdtIW7vaapIxAeLVEbPX49URc7LFqyNmr8erI+Zki1dHzF6PV0fMyRavjpi9Hq+OmHWksSMRMWmG6FVMkhlRzMzMzMxa0dEwb2ZmZmZmE5ULyGZmZmZmFeO+gCxpE0nPlzRVUt9Yp8cmLw0Z/LsXY/Z6vDpiOl7vxez1eHXEnIxp7PV4dcTs9XjWuk7GQe4Zkl4FfBL4e14WSPpmRDzYYbyXAhsDUyLiJEmKLhppl45XV8wh8SdVvBIxJc0FFgMPAcsLpalozF6PV0dMx+ter6dxMl5zHTEnW7w6YvZ6PGvfuO2kJ2kq8G3gSxHxa0mvBrYHlgCfabeQLOmFwHnA+4BDgd8B3wWuiIi2b87S8WqM+VxgLnAt8M+IeETSlIjoaKqcXo9XOqakfUnTqz8IXAFcHREXdpq2OmL2erzxkMbJFm88pHEyXvN4SGOvxxsPaazjmq0DETEuF2AqaSzlN+T1KcBOwGeAo8mF/zbiHUsa4xlgReATwBeA53eYvqLxakrj3sAfgXNJY1SfBMwezM+JFq90TNL0n38gfTF7NnAI8CPggC5e46Ixez3eeEjjZIs3HtI4Ga95PKSx1+ONhzTWcc1eOlvGbROLiFgm6XPAWyX9OSL+T9KvgHWBPYGvthKn8vP674F3S9o4Iv4o6ePAh4EDgcs7SOIfgHeViFdjGvcA3hMRP8q1qvsCX5D09oi4awLGKx1zOXAzcG1EPCbpb8D9wBsk/SsiftxB+voLxyydxtLpGw9pnGzpGw9pnIz34XhIY6+nbzyksY73s3VgvHfS+z/gJ8BBkl4UEf0RcRawDvCcZgdL2g7YQZKAG/LyQkmzI2IJ8DFgW0lvaCUxkuZKmi5pJnAZ6SbfsdN4daSxEncK0AdsChAR1wBfA24C3iNppTbj9RWOVzR9daQxIu4HHgW+k9cfAH4JXARsnc/ZUgcLSbNzjH8BDwPf6jZmyTTWlb7xkMbJkr7xkMbJfB+OhzT2evrGQxpLvp+tO+O6gBwRj5Fuot8Dx0s6UtIhwNOAO0c6VtJuwBnAY5HcCfwKeAGwp6Rn5vgXAE3bpkp6OanJx0nA14G1SW+YHYGXtxuvjjTmmNMkTY/U3vZk4LWS9stPL8rXsBawaovxtpK0bkT0A18G9pf0mi7iFU1f6TRKeqmkYyS9I296C3CPpC/Bvz8sFwAvkDQz1/w3i7kbcMrgB26O+bCkL3QSs3QaS6dvPKRxsqVvPKRxMt6H4yGNvZ6+8ZDGOt7P1r1xXUCGf984XyO1PX4J8GLg9RHxj+GOUersdjrwpoj4raRVcqzzgG8AmwFflfRF0o169QixpNTb9MS874eAa4DfAHeTCmSbthqvEnd7UhvZrtNYiflq4CzgAkl7k2q4PwAcLOm1uRB+BbAaqe1Ts3i7Aafk/YmI64CPAIdK2q+DeEXTVzqN+b45C3gMeI2kk4AtSAX5lST9j6TVSK/NyqR28s3S9/Kcni/mL0BExEOk0VlWbzdm6TSWTt94SONkS994SONkvA/HQxp7PX3jIY11vJ+tkOiBhtClFtLP5007WgFvJnXS2gJYn3Rzfg04B1g377MjcDiwUYvnnk9q2jE4Msg7gb8Bc9qNB2wAvBs4m1Ro6zqNpKHhbgSeDxwAnA+8NefBHsB1wAeBd+T95jaJt1c+5rl5fUrluX3zcx9qI17R9NWUxqGdJE8A/juneWXSF5pvk77pb9lC+p5Kalv2qby+Tr7W1wICViJ9GWonZpE05vOvBTxQMn2l83Ey5qHvw8lxH46HfHQe9lYeeim7jHkCRvViYSPSt7C1SYWiU0g/sb8N2JZUALsEWKXFeK8gFYSnkgqu7x/y/Pvym2WlNtK4G/Az4Lmk0ThO7yaNlbjbAZdV1ncgFerfQvpi8Wzg08B/Ac9pEmsKqRPkH/P6zHzsacBeedvmrcbL+29fKn2VGKcVTuNLgR8DG+f16aRag69U9lkRmNHG6/Ia4NfAMcDPgc+Smgyd0k5MHv9itgupyUhXaQRWzH/3K5G+OvNxsuWh78OJfR+Op3x0HvZeHnopt4x5AkbtQh+vTfwlqSb2BaQayiMr+8whFUintxDvZaRxdHfL6xuQaozfW9lnA1Ihr6Uh5yox/wackLe9DTiikzQ2iH9mfnOvkNd3yB8ce3YQayqp+cgVwJXAe3J+Xga8to04K+e/U0hfJrpOHzCvEvNL3aSRNF7ydFIBeyrwReAwHh8abkXgKuCwNtK3DjANmJnXX036ee09lZiXA29rMd52+X4WMJtU+/DGTtNI+pL2c+Bpef2V3aSvjnycbHno+3By3IfjIR+dh72Xh17qWcbtMG/tkLQDqZbwgIj4naRTgf0j4q2Spld23Ql4OulnkiVN4n0LeEVEXCVpFqmWd1/g/0laBlxIKuA9l9S+9V9N0rgrqc3RPsCfgIskbU2q5a5Ood1SGnPM7UhvtEcj4ipSwXAH4G5Jv46I30g6hzR8zE+iyWQjSsOirQwsi4grJb2V9PPPnyPis3mfe4EDJf0wIpY1ibcbsIWkL+dr+S2plryj9OWYLwXOlvTeiDhN0nGkPPxru2nMbc0+TWpPvgqpgP0tUq22JP0qIm6SdAEw4rVWYu5OGprvZmCJpI9ExA8k3RARNypNWPJYjtl0spuch18EDoz0yXqn0nCHe+U0/rqdNFbi/Z3Udv4fEXGepC1znLbSl2MWzcfJloe+DyfHfTjkunsyH52HvZeHVqOxLqGPxkIqFL6hsv5UUhvXaZVth5F+JnlWC/E2IRWI9wHWBP4XuJQ0acfHSSNrnELqOPfsFtO4G7BDfrwaaTSMN+f1wZ+KjiDVMLeSxj1IBe35pEHGv5S3vy+n86C8fjCpZrmvSby9SDP3nQl8Dzgqb582ZL83kGqCm8XbI+f3zpVtM0mdHz7fbvryvrvn/DmTSnMXhtS2N0sjqdZhLmks651Jo6IcB9wOrAdsQ6qR+AXpg/MfwKYtpO/FpElKXphjfJrUoRRyrXnlmq8FNmkS74WkD+0X5/VVhjzXVhrzPXgNqW37e4ALKs9N6SB9xfNxHOTh7qXycBLfh8XycLzch+MkH9cFri+YhzuR/keVzMMdgDsK5uHLSP/3SuXhbGBhqTz0Uu8y5gkYlYtMNbCrVB7PyTf9U/O2pwOfA57ZRsznAH8hFZSPIP2cfyTwFXJnL2D1DtI6Jf/dHbiLXMAGZpBG6mjlH2AfqU30YCFzFdLPP6fn9deTGv1fRvqnsVWTeFuRmqc8J6+/BvhCfqzKfoeSOhJs3iTeZsBfyc1bSF8yNgM26CR9+Zid82u6NekL0F3Ayxrs12oa+0hfLtaF7jte5v3fM/ia5PXjgPmV9WmkkViubpa+vH+xzqb5/v0isFNen0r6oH5jZZ+ppIJBS+mr5OOppfKR1Hn1wIJ5+KacX0U67OY83LFUHpIKd1+nUAfgvP+7gEMK5uFRwA8o0KE434efB15S8j7Mx5XsSH0sBd/LlXw8t0Q+5n0/R6H3M+kXy+mkip+u85A0pObxwOsK3oerkJokFuncDqxB+n/+wkJ5uA7wlFJ56KX+ZcwTMOoXDCuQaip/ltdfT/rm2lant3zsZsAxQ7ZdwuOjJrQ13XWD+B/LHyJ9eb3lqZBJ87gfNGTbb4DPV9afDazVQqwdgKMr6xuR2kfNrbzJ55HaRjetMScVYk/OHwK7Az8Fvktq4/XpdtOX990T2K6y/pacnlUr256ZPyyHTWO+tueRCu3fBY4b8nwnHS83yudeC1i/sn074Jwh9+aq5HZuTeKV7Gw6Ly+DXyIHv6S9GfjEkH3ntHjPPIv0j2PDnI/v6yYfSR0qt8nXXiIPN8+v88Y5D7/aZR5uDmzJ4//kBtvRd5SHpNqug/PjM4EPFbgPdwRemR+vXUljp3m4I/Cq/PhNpA6w3eThjsDelfWVCtyHRTtSk6aqP5zUdG09Hv/86ygPKzGPIDVfezvpM6qbfNybJ/5iOq3Le3EfUkFx8L38gS7zcF/SsKgbkQqxJfJwX1IF0uD7uds83Jc0msTg+7nbPNyN1Bfm2aS5Dbp+P3upfxnzBIzZhae2s58itXvdolDMV+d4Td/QbcT7FZWfm5rsv3Hl8etJP4etV9k2i1TT02qNRjXeYG17X/4gv4DHC1Qb5r8jvrmHxHsBqaboz6TROgZ/Bv0Z8KI28miTIeuDhbttSc1o1q8+R+4UOEyswY6cvyB1QNwbuBU4vrLPBrTX8bIa81tUmseQCmhX5scHk5rnjPgliPKdTQfjXUb657d55bktSD9X7t7mfTs4LN/5pMLdjsBtVArJ7eTjkHg/AtapPLdtB3lYjXcO6cvG2+mwM2yO94ectovINVX5uee0k4f5Hp1J+hn2JtKvNWuSfnH5YIf5NzTm4UOeb+s+HBLvZh7/WfwtpHHb28rDIfFuJDct6zQPK8cV7Ug9NN6Q59q+D4fE3D2vzyQV8A6v7NNJ5/FGv561nY+kZhA3VfJwPdJ7+dgO8/AJ8YY8t32HeTgYczAPZ5AKxod0mIeD8Rrl4VYd5GG18/1/AqvnPOy4Q7+X0VnGPAGjfsGpIDaNVDD7G3nEgwIx30iaBrpp++A2Y59LbnrQZL+9gEd44jfwj5PbN1W2nUOlprXNeIOFzymkgsAqwEGkDomrdRBvW3KNVmXbN4HtW8ybwZhnV7ZV266dRqXNWJNYO+QPxa3y+nzgE6Sfwv5GqoHYiNR+eQEtNJ9pEPNkcjOXvL4R6SfA15C+WDVrDzc03qnASfnx9Mp+B5IKvM1ek2HTx+O1OoeRCvZrtpiPO5PaZm6b1y8gFUCfQfrHciyplqelfGwQ7zxg18rz6+R7utU8HBrvfNJ4oytQ+fLURh4Omz4er6E9op08zMccR2oKcRZpZJc+0nv57aTa/pbvwwYxzwTeWdn+NNLP0i3lYYN43+bx5lJt34fDpO8dQ+7Dw9u8D3cgteEcfF1m5df4uaRZVtu9D4fGW5VU+zmT9HnY1n04TMw1cjrXpDKkVxv34khpnNrJvZjz6d358Xqk9/JBwEOk2tRN2rkXh8RbhzTE2fakpgdrkL6kt3sfVmPOyfmwE5WKqnbuxWHSuN3g9ZGaUraUh8CuwC2kX9SmkX4lfQbps38RHfxf8TJ6y6QYxaIq0l27VNLHgasj4k+FQv+F9HPjTSWCSVIk+7Ww7wxS7c07gB0knR0RB0TEh5SmbL9A0smkD9/nkGb4ayfetyPi9RExIKmP9IXgYVIbty1JPwXf30a8syLidZFGAFmpst+rSR8kI04T3iSNy5Wmql5CamYyX9ILI+JXzWICJ0bE7/LjDwDfjIg7JO1M+iA7llSoPzTSDI6tqMb8MPA1SStGmiL8n6QP301IeXhjm/E+BJwmaVq+XiQdRqo9ed1Ir0mT9E0n9Z4OHu9Es7SFWJD+QR+VX9u1Sc0iPktqkvN1UvOaeXl7K/k4NN526TK1H+nXlR+T/gltRGt5ODTe80jNmO4ArpB0NqkA8BZSW+dmeThc+l4DXCnpW6QC9Pa0nocAy0kFktNIv7DMJTWR2or0Hn427d2H1ZhnAIdL+hzwKGmEn5eTXpdW78NqvG8AR0jahPTZ+oGc5iNpLQ9HSt9S0s/Pt5HuyVbz8N68/2xJa5I6Fi8n1VJ3ch8Ojfd9Ut49TPoSeDHt3YfDxVxCmojix5K+Q6pJbfVeHC6Ni3O8Tu7F5aSCHaQvAHeQKpf+QKoZ3YRUIG31XqzG+z7pde0HBkifPzuSCpDt3oeDMc8lVWgsBaZIehupIuVYWr8XG6VxOdAn6c2ka281D/vytSxUmg1vIWnY0pMk7UT6v/Ju0v3Y7vvZ6jbWJfSxWphgP2WQvunOJBWCv88Ta1VfSWoj+HVab14xNN63hzz/P6Qa86Y9i4eJ950hzx9C+51umqVxZVL78rVbiDVcR87BcSnXJ7eJayN9zTqHziM1vWipc2gL8drqbNpCvDXz345qNUhfMj6YHx9Baiu9Qacxh8Q7lFTbtAnwE2CzAvHOIf1z/hQd9B4fJn2z8voabcZ6BrlJCqlWdRnw8crzneTf0JiPkCcjIH3RaCsPm8Q7od08HCbeyZXn283Doh2ph4n3RlLt+0ad3IcjxDyL1Oa3rXtxhHjn8HgNaMv5SGpbf3M+/tC8beOcrn06yMNG8Z5O+jVsvw7zcKSYr8ppbTnmCPG+CuzS4b04tPP94K92g5OPtPQri5fRXcY8AV5qeFHTT3Q/IBeSSbWy6xeI9+28Po8000/bhZJh4m1K+rnu6QXTuA2pI1LLHRsrsRp15PwqXXSgaBBzsI1dRx+Mw6Sxo86mw8Q7kNTMpFinEVIt2zb5cddfUEmdbtYvnL5iPcdJzZCe1+Gx65BrZkm1+B8mNWV6U6f51yDmf+Y0vpoWhlFsMd6FpKniS6XvAoa0SW4zZtGO1MPE+wmVDssF09jR5+Ew8X4MbN1hvFeQ2sB/rLLtNB7vRNpuHjaKdzpttjFvMY17F4z3NSrtmrtI68eA95MqJVrqX+RlbJYxT4CXml7YVKv6DdI34VvIvXELxPtjXrrqiDgkfX8k19QWinlToWv+Jo935GxpPOs2Y3bdObTmeB1f89B/mjzegbVpbX6b8Tq6b0YxXkfXm2N8jPRz8Svy+ovJNZ8FY76km5il01jHNQ/zupTsSH1NN69z3TG7vWbSl+eDSTXTh+VlAfCMgvF+SxdfTkdIY0cxS19zg9fjV3TwpdTL6C5jngAvNb64aXijf4+lPNHjlYpJfR05i8Xs9XiVuNPzP5eFtNF8xvECUq3k1pX1tn8NqTtmr8erxCnakbp0vPGQRlIHx0+SJrPo+jO7dLzxksYct6XO917GdhnsIWwTjKTVSW/Cd0XEdRM9Xh0xJb2B1JFzYbex6oo5DuJNJXVE/HNE3Ox4HcVUFP6gLh1zPMQjjWxwVxToSF06Xh0x60ijdaeO97LVxwXkCawyWsKkiFc6pgsmZmZmk5MLyGZmZmZmFVPGOgFmZmZmZr3EBWQzMzMzswoXkM3MzMzMKlxANjMzMzOrcAHZzMzMzKzCBWQzMzMzs4r/DzH8MP1jeJzDAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_data(data_line_5000,direction='N',part='real')\n",
    "plot_data(data_line_5000,direction='N',part='imag')\n",
    "plot_data(data_line_5000,direction='E',part='real')\n",
    "plot_data(data_line_5000,direction='E',part='imag')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Oops, looks like there are some ```NAN``` fields which show up as red. Strangely, there are specific frequencies which are ```NAN``` in the real component, but exist in the imaginary component (and vice versa). I'll have to make non-```NAN``` values ```NAN``` if the corresponding component is ```NAN```."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "HELPER CELL\n",
    "\n",
    "for assigning NAN values to the appropriate cell.\n",
    "\n",
    "\"\"\"\n",
    "def assign_NAN_values(df,direction='N',part='real'):\n",
    "    frequencies = ['0011','0022','0045','0090','0180','0360','0720','1440']\n",
    "    for freq in frequencies:\n",
    "        for direction in ['N','E']:\n",
    "            real_key = 'r'+direction+'_'+freq\n",
    "            imag_key = 'i'+direction+'_'+freq\n",
    "            df.loc[pd.isna(df[real_key]) | pd.isna(df[imag_key]), real_key] = np.nan\n",
    "            df.loc[pd.isna(df[real_key]) | pd.isna(df[imag_key]), imag_key] = np.nan\n",
    "                    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_line_5000=assign_NAN_values(data_line_5000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_data(data_line_5000,direction='N',part='real')\n",
    "plot_data(data_line_5000,direction='N',part='imag')\n",
    "plot_data(data_line_5000,direction='E',part='real')\n",
    "plot_data(data_line_5000,direction='E',part='imag')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ahh much better. At least the data gaps make sense now. \n",
    "\n",
    "We now have a choice to make. I can either:\n",
    "\n",
    "* Ensure my inversion scheme can handle ```nan``` values.\n",
    "\n",
    "* Drop stations with ```nan``` values.\n",
    "\n",
    "* Restrict my frequency space to only contain non ```nan``` numbers.\n",
    "\n",
    "* Interpolate values within reason.\n",
    "\n",
    "There are drawbacks to each approach. Ensuring your inversion scheme can handle NaN's requires an intimate understanding of the program. My intended approach uses Occam2D, which does not handle nan values well. Dropping all stations with NaN values leaves us with a really sparse dataset. Restricting frequency space to non nan values means we now can only invert 3 of 8 frequencies. Interpolating values is like creating 'fake' data and will bias the inversion results.\n",
    "\n",
    "How about a compromise?\n",
    "\n",
    "First, I'll drop stations 1250, 1750, 4250, 5250, and 6500. These stations have the most nan values, and based on discussions with the team that acquired this data, nan values mean high uncertainty."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bad_stations = [1250,1750,4250,5250,6500]\n",
    "new_data  = data_line_5000[~data_line_5000.Station.isin(bad_stations)]\n",
    "new_data  = new_data.reset_index()\n",
    "plot_data(new_data,direction='N',part='real')\n",
    "plot_data(new_data,direction='N',part='imag')\n",
    "plot_data(new_data,direction='E',part='real')\n",
    "plot_data(new_data,direction='E',part='imag')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We still have NaN values on some of the channels. One approach to deal with this is to locally interpolate from the nearest value on each station. We could do this here OR we could do this when we convert to MtPy. I prefer the second option as it will allow us to use pandas ```fillna``` methods."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 2. Prepare Data for MtPy\n",
    "\n",
    "Every row in this pandas dataframe represents spectral Tipper data collected from a station. Before we can do any inversion, it's prudent to convert these to xml files on disk. While this isn't necessary, it will allow us to separate data cleaning from data analysis.\n",
    "\n",
    "MtPy uses an object called ```MT``` contained in ```mtpy.core.mt```. An easy way to do the conversion is to use a function to assign every row's ```MT``` Object into an ```mt_obj``` column.\n",
    "\n",
    "Documentation for ```MtPy's``` ```MT```object is lacking, but from reading the git repository I can tell the following items should be incorporated into our object:\n",
    "\n",
    "* **Metadata**: Stuff like lat, lon, elevation, station. These are simple float/string attributes. Note that we can either provide MtPy with lat,lon or easting-northing information. I prefer using lat-lons in WGS84 format. It's a universal format used by most WMS, google maps, google earth, navigation software, and smartphone GPS apps. While it might be hard to convert lat-lon into meaningful distance measurements in the field, with the availability of packages like ```pyproj```, I find sending UTM coordinates are at best redundant and at worst, add unneeded complexity to data processing.\n",
    "* **Tipper Data**: This is a bit more complex. It requires an array of frequencies, complex numbers, and needs to be shaped appropriatey. There is an option for incorporating error into the Tipper array, but for now we'll just set those to zero. **THIS IS WHERE THE FILL_NA COMES IN**. I'll use a fillna operation that relies on a succinct stackoverflow solution using a scipy image processing routine.\n",
    "\n",
    "For ease of understanding, I'll make these separate functions which are then called by ```parse_row_into_mt_obj```."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "HELPER CELL\n",
    "\n",
    "for parsing pandas dataframe row data into an MT object\n",
    "\n",
    "\"\"\"\n",
    "\n",
    "def fill(data, invalid=None):\n",
    "    \"\"\"\n",
    "    FROM STACKOVERFLOW: \n",
    "    https://stackoverflow.com/questions/3662361/fill-in-missing-values-with-nearest-neighbour-in-python-numpy-masked-arrays\n",
    "    Replace the value of invalid 'data' cells (indicated by 'invalid') \n",
    "    by the value of the nearest valid data cell\n",
    "\n",
    "    Input:\n",
    "        data:    numpy array of any dimension\n",
    "        invalid: a binary array of same shape as 'data'. True cells set where data\n",
    "                 value should be replaced.\n",
    "                 If None (default), use: invalid  = np.isnan(data)\n",
    "\n",
    "    Output: \n",
    "        Return a filled array. \n",
    "    \"\"\"\n",
    "\n",
    "    if invalid is None: invalid = np.isnan(data)\n",
    "\n",
    "    ind = nd.distance_transform_edt(invalid, return_distances=False, return_indices=True)\n",
    "    return data[tuple(ind)]\n",
    "\n",
    "def create_simple_metadata(row):\n",
    "    \"\"\"\n",
    "    extracts metadata from the pandas dataframe row, specifically:\n",
    "    site (lat, lon, elevation, station, line)\n",
    "    acquisition (azimuth, recording time)\n",
    "    \"\"\"\n",
    "    lat     = row['Lat']\n",
    "    lon     = row['Long']\n",
    "    elev    = row['ALT']\n",
    "    station = row['Station']\n",
    "    \n",
    "    return lat, lon, elev, station\n",
    "\n",
    "def generate_tipper_arrays(row):\n",
    "    \"\"\"\n",
    "    function to populate numpy arrays from pandas dataframe\n",
    "    \"\"\"\n",
    "    frequencies = np.asarray([11, 22, 45, 90, 180, 360, 720, 1440])\n",
    "    t_n=[]\n",
    "    t_e=[]\n",
    "    for freq in frequencies:\n",
    "        real_east_key = f\"rE_{freq:04}\"\n",
    "        imag_east_key = f\"iE_{freq:04}\"\n",
    "        real_north_key= f\"rN_{freq:04}\"\n",
    "        imag_north_key= f\"iN_{freq:04}\"\n",
    "        t_e.append( row[real_east_key]+row[imag_east_key]*1j)\n",
    "        t_n.append( row[real_north_key]+row[imag_north_key]*1j)\n",
    "        \n",
    "    t_n = fill(np.asarray(t_n,dtype=np.complex64))\n",
    "    t_e = fill(np.asarray(t_e,dtype=np.complex64))\n",
    "    return frequencies, t_n, t_e\n",
    "\n",
    "def create_tipper(row):\n",
    "    \"\"\"\n",
    "    creates an MtPy Tipper array from source numpy arrays and relevant metadata\n",
    "    \n",
    "    ############################# BIG WARNING #################################\n",
    "    Notice Ive done something funny with the error array. This is purely for MtPy compatibility.\n",
    "    To incorporate error please assign other values.\n",
    "    \"\"\"\n",
    "    frequencies, t_n, t_e = generate_tipper_arrays(row)\n",
    "    \n",
    "    array            = np.ones((len(frequencies),1,2),dtype=np.complex64)\n",
    "    tipper_err_array = np.ones((len(frequencies),1,2)) #<- change this to include error\n",
    "    array[:,0,0]=t_n\n",
    "    array[:,0,1]=t_e\n",
    "    \n",
    "    tipper = Tipper(tipper_array=array, tipper_err_array=tipper_err_array,\n",
    "                    freq=frequencies)\n",
    "    return tipper\n",
    "\n",
    "def create_dummy_impedanc_tensor():\n",
    "    \"\"\"\n",
    "    creates an MtPy Impedance Tensor object from dummy data\n",
    "    \n",
    "    ############################# BIG WARNING #################################\n",
    "    Both the values and the error are made up here because the data is only made up of tipper data.\n",
    "    This is done to maintain compatibility with MtPY\n",
    "    \"\"\"\n",
    "    frequencies = np.asarray([11, 22, 45, 90, 180, 360, 720, 1440])\n",
    "    z_array     = np.ones((len(frequencies),2,2),dtype=np.complex64)\n",
    "    impedance_tensor = Z(z_array=z_array, z_err_array=z_array, freq=frequencies)\n",
    "    return impedance_tensor\n",
    "\n",
    "def parse_row_into_mt_obj(row):\n",
    "    lat, lon, elev, station = create_simple_metadata(row)\n",
    "    tipper   = create_tipper(row)\n",
    "    impedance_tensor  = create_dummy_impedanc_tensor()\n",
    "    mt_obj   = MT(station=station,lat=lat,lon=lon,elev=elev,Tipper=tipper,Z=impedance_tensor)\n",
    "    return mt_obj"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/kevin/anaconda3/envs/mtpy_inv/lib/python3.6/site-packages/mtpy/core/z.py:125: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  self._resistivity[idx_f, ii, jj] * r_err\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>Line</th>\n",
       "      <th>Station</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long</th>\n",
       "      <th>E_WGS84_Z7</th>\n",
       "      <th>N_WGS84_Z7</th>\n",
       "      <th>ALT</th>\n",
       "      <th>Az</th>\n",
       "      <th>Dur</th>\n",
       "      <th>...</th>\n",
       "      <th>iN_1440</th>\n",
       "      <th>SNI_0011</th>\n",
       "      <th>SNI_0022</th>\n",
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       "      <th>SNI_1440</th>\n",
       "      <th>mt_obj</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>6801212.0</td>\n",
       "      <td>1015.0</td>\n",
       "      <td>294.3</td>\n",
       "      <td>144</td>\n",
       "      <td>...</td>\n",
       "      <td>0.023</td>\n",
       "      <td>38.6</td>\n",
       "      <td>160.2</td>\n",
       "      <td>385.1</td>\n",
       "      <td>603.8</td>\n",
       "      <td>484.1</td>\n",
       "      <td>455.3</td>\n",
       "      <td>704.7</td>\n",
       "      <td>477.2</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b9f4198&gt;</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>184</td>\n",
       "      <td>5000</td>\n",
       "      <td>250</td>\n",
       "      <td>61.334589</td>\n",
       "      <td>-139.189912</td>\n",
       "      <td>596860.0</td>\n",
       "      <td>6801399.0</td>\n",
       "      <td>977.8</td>\n",
       "      <td>151.3</td>\n",
       "      <td>188</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.007</td>\n",
       "      <td>67.6</td>\n",
       "      <td>207.4</td>\n",
       "      <td>491.3</td>\n",
       "      <td>742.5</td>\n",
       "      <td>544.4</td>\n",
       "      <td>155.9</td>\n",
       "      <td>165.1</td>\n",
       "      <td>145.6</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b9fc160&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>185</td>\n",
       "      <td>5000</td>\n",
       "      <td>500</td>\n",
       "      <td>61.336235</td>\n",
       "      <td>-139.186733</td>\n",
       "      <td>597025.0</td>\n",
       "      <td>6801587.0</td>\n",
       "      <td>1002.1</td>\n",
       "      <td>40.4</td>\n",
       "      <td>147</td>\n",
       "      <td>...</td>\n",
       "      <td>0.139</td>\n",
       "      <td>41.0</td>\n",
       "      <td>150.2</td>\n",
       "      <td>324.8</td>\n",
       "      <td>585.7</td>\n",
       "      <td>542.6</td>\n",
       "      <td>482.1</td>\n",
       "      <td>418.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b9fccf8&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>186</td>\n",
       "      <td>5000</td>\n",
       "      <td>750</td>\n",
       "      <td>61.338026</td>\n",
       "      <td>-139.183675</td>\n",
       "      <td>597183.0</td>\n",
       "      <td>6801791.0</td>\n",
       "      <td>990.7</td>\n",
       "      <td>40.7</td>\n",
       "      <td>263</td>\n",
       "      <td>...</td>\n",
       "      <td>0.035</td>\n",
       "      <td>50.5</td>\n",
       "      <td>206.8</td>\n",
       "      <td>510.2</td>\n",
       "      <td>736.4</td>\n",
       "      <td>538.5</td>\n",
       "      <td>342.3</td>\n",
       "      <td>178.1</td>\n",
       "      <td>16.6</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b9fc5f8&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>187</td>\n",
       "      <td>5000</td>\n",
       "      <td>1000</td>\n",
       "      <td>61.339457</td>\n",
       "      <td>-139.181200</td>\n",
       "      <td>597311.0</td>\n",
       "      <td>6801954.0</td>\n",
       "      <td>966.2</td>\n",
       "      <td>265.1</td>\n",
       "      <td>273</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.001</td>\n",
       "      <td>34.6</td>\n",
       "      <td>179.6</td>\n",
       "      <td>521.7</td>\n",
       "      <td>830.8</td>\n",
       "      <td>708.4</td>\n",
       "      <td>253.2</td>\n",
       "      <td>147.5</td>\n",
       "      <td>45.8</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b9b7438&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>190</td>\n",
       "      <td>5000</td>\n",
       "      <td>1500</td>\n",
       "      <td>61.342927</td>\n",
       "      <td>-139.174137</td>\n",
       "      <td>597678.0</td>\n",
       "      <td>6802351.0</td>\n",
       "      <td>909.5</td>\n",
       "      <td>194.6</td>\n",
       "      <td>274</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.077</td>\n",
       "      <td>31.1</td>\n",
       "      <td>190.8</td>\n",
       "      <td>615.9</td>\n",
       "      <td>1029.6</td>\n",
       "      <td>828.2</td>\n",
       "      <td>194.7</td>\n",
       "      <td>48.5</td>\n",
       "      <td>9.2</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b9b7b00&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>192</td>\n",
       "      <td>5000</td>\n",
       "      <td>2000</td>\n",
       "      <td>61.346186</td>\n",
       "      <td>-139.168076</td>\n",
       "      <td>597992.0</td>\n",
       "      <td>6802723.0</td>\n",
       "      <td>891.1</td>\n",
       "      <td>285.6</td>\n",
       "      <td>215</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.8</td>\n",
       "      <td>139.5</td>\n",
       "      <td>376.9</td>\n",
       "      <td>592.0</td>\n",
       "      <td>387.6</td>\n",
       "      <td>83.0</td>\n",
       "      <td>25.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b952048&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>194</td>\n",
       "      <td>5000</td>\n",
       "      <td>2250</td>\n",
       "      <td>61.347940</td>\n",
       "      <td>-139.164963</td>\n",
       "      <td>598153.0</td>\n",
       "      <td>6802923.0</td>\n",
       "      <td>916.7</td>\n",
       "      <td>236.7</td>\n",
       "      <td>258</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.8</td>\n",
       "      <td>112.3</td>\n",
       "      <td>413.1</td>\n",
       "      <td>684.7</td>\n",
       "      <td>469.5</td>\n",
       "      <td>292.3</td>\n",
       "      <td>221.9</td>\n",
       "      <td>76.2</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b952668&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>195</td>\n",
       "      <td>5000</td>\n",
       "      <td>2500</td>\n",
       "      <td>61.349670</td>\n",
       "      <td>-139.162075</td>\n",
       "      <td>598302.0</td>\n",
       "      <td>6803120.0</td>\n",
       "      <td>935.2</td>\n",
       "      <td>130.2</td>\n",
       "      <td>123</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.053</td>\n",
       "      <td>42.5</td>\n",
       "      <td>147.8</td>\n",
       "      <td>363.0</td>\n",
       "      <td>486.8</td>\n",
       "      <td>418.0</td>\n",
       "      <td>418.4</td>\n",
       "      <td>218.8</td>\n",
       "      <td>20.1</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b952c18&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>196</td>\n",
       "      <td>5000</td>\n",
       "      <td>2750</td>\n",
       "      <td>61.351332</td>\n",
       "      <td>-139.158817</td>\n",
       "      <td>598471.0</td>\n",
       "      <td>6803310.0</td>\n",
       "      <td>989.7</td>\n",
       "      <td>336.6</td>\n",
       "      <td>180</td>\n",
       "      <td>...</td>\n",
       "      <td>0.008</td>\n",
       "      <td>33.0</td>\n",
       "      <td>145.0</td>\n",
       "      <td>406.5</td>\n",
       "      <td>771.5</td>\n",
       "      <td>1317.7</td>\n",
       "      <td>1987.1</td>\n",
       "      <td>1204.5</td>\n",
       "      <td>178.7</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b956208&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>197</td>\n",
       "      <td>5000</td>\n",
       "      <td>3000</td>\n",
       "      <td>61.353160</td>\n",
       "      <td>-139.155886</td>\n",
       "      <td>598622.0</td>\n",
       "      <td>6803518.0</td>\n",
       "      <td>982.9</td>\n",
       "      <td>267.7</td>\n",
       "      <td>180</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.2</td>\n",
       "      <td>171.1</td>\n",
       "      <td>425.0</td>\n",
       "      <td>684.0</td>\n",
       "      <td>518.7</td>\n",
       "      <td>277.4</td>\n",
       "      <td>167.0</td>\n",
       "      <td>52.6</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b9567b8&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>199</td>\n",
       "      <td>5000</td>\n",
       "      <td>3250</td>\n",
       "      <td>61.354696</td>\n",
       "      <td>-139.152579</td>\n",
       "      <td>598794.0</td>\n",
       "      <td>6803694.0</td>\n",
       "      <td>975.4</td>\n",
       "      <td>89.2</td>\n",
       "      <td>309</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.3</td>\n",
       "      <td>75.2</td>\n",
       "      <td>360.0</td>\n",
       "      <td>721.0</td>\n",
       "      <td>547.2</td>\n",
       "      <td>457.2</td>\n",
       "      <td>242.9</td>\n",
       "      <td>43.9</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b956d68&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>200</td>\n",
       "      <td>5000</td>\n",
       "      <td>3500</td>\n",
       "      <td>61.356432</td>\n",
       "      <td>-139.149502</td>\n",
       "      <td>598953.0</td>\n",
       "      <td>6803892.0</td>\n",
       "      <td>955.9</td>\n",
       "      <td>282.2</td>\n",
       "      <td>180</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.4</td>\n",
       "      <td>129.4</td>\n",
       "      <td>345.9</td>\n",
       "      <td>529.9</td>\n",
       "      <td>382.1</td>\n",
       "      <td>206.2</td>\n",
       "      <td>125.8</td>\n",
       "      <td>13.5</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b95b358&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>201</td>\n",
       "      <td>5000</td>\n",
       "      <td>3750</td>\n",
       "      <td>61.358015</td>\n",
       "      <td>-139.146378</td>\n",
       "      <td>599115.0</td>\n",
       "      <td>6804073.0</td>\n",
       "      <td>958.0</td>\n",
       "      <td>68.3</td>\n",
       "      <td>215</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.6</td>\n",
       "      <td>121.0</td>\n",
       "      <td>309.2</td>\n",
       "      <td>517.4</td>\n",
       "      <td>333.6</td>\n",
       "      <td>109.0</td>\n",
       "      <td>47.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b95b908&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>202</td>\n",
       "      <td>5000</td>\n",
       "      <td>4000</td>\n",
       "      <td>61.359823</td>\n",
       "      <td>-139.143297</td>\n",
       "      <td>599274.0</td>\n",
       "      <td>6804279.0</td>\n",
       "      <td>934.2</td>\n",
       "      <td>160.9</td>\n",
       "      <td>179</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.3</td>\n",
       "      <td>165.6</td>\n",
       "      <td>412.6</td>\n",
       "      <td>660.0</td>\n",
       "      <td>434.2</td>\n",
       "      <td>117.1</td>\n",
       "      <td>98.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b95beb8&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>205</td>\n",
       "      <td>5000</td>\n",
       "      <td>4500</td>\n",
       "      <td>61.363124</td>\n",
       "      <td>-139.137171</td>\n",
       "      <td>599591.0</td>\n",
       "      <td>6804656.0</td>\n",
       "      <td>898.3</td>\n",
       "      <td>211.4</td>\n",
       "      <td>128</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.9</td>\n",
       "      <td>154.7</td>\n",
       "      <td>339.9</td>\n",
       "      <td>505.1</td>\n",
       "      <td>319.4</td>\n",
       "      <td>241.6</td>\n",
       "      <td>221.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b95f4a8&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>206</td>\n",
       "      <td>5000</td>\n",
       "      <td>4750</td>\n",
       "      <td>61.364832</td>\n",
       "      <td>-139.133982</td>\n",
       "      <td>599756.0</td>\n",
       "      <td>6804851.0</td>\n",
       "      <td>880.6</td>\n",
       "      <td>191.6</td>\n",
       "      <td>159</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.4</td>\n",
       "      <td>169.9</td>\n",
       "      <td>388.2</td>\n",
       "      <td>596.7</td>\n",
       "      <td>453.6</td>\n",
       "      <td>312.3</td>\n",
       "      <td>140.1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b95fa58&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>207</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "      <td>61.366495</td>\n",
       "      <td>-139.130890</td>\n",
       "      <td>599916.0</td>\n",
       "      <td>6805041.0</td>\n",
       "      <td>855.0</td>\n",
       "      <td>218.7</td>\n",
       "      <td>121</td>\n",
       "      <td>...</td>\n",
       "      <td>0.010</td>\n",
       "      <td>166.7</td>\n",
       "      <td>307.3</td>\n",
       "      <td>476.8</td>\n",
       "      <td>631.7</td>\n",
       "      <td>1005.5</td>\n",
       "      <td>1857.5</td>\n",
       "      <td>4405.7</td>\n",
       "      <td>5544.0</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b95ff98&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>210</td>\n",
       "      <td>5000</td>\n",
       "      <td>5500</td>\n",
       "      <td>61.369670</td>\n",
       "      <td>-139.124712</td>\n",
       "      <td>600236.0</td>\n",
       "      <td>6805404.0</td>\n",
       "      <td>849.9</td>\n",
       "      <td>242.4</td>\n",
       "      <td>128</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.012</td>\n",
       "      <td>32.3</td>\n",
       "      <td>134.5</td>\n",
       "      <td>298.1</td>\n",
       "      <td>589.7</td>\n",
       "      <td>682.2</td>\n",
       "      <td>467.2</td>\n",
       "      <td>216.5</td>\n",
       "      <td>315.9</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b9645f8&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>211</td>\n",
       "      <td>5000</td>\n",
       "      <td>5750</td>\n",
       "      <td>61.371493</td>\n",
       "      <td>-139.121478</td>\n",
       "      <td>600403.0</td>\n",
       "      <td>6805612.0</td>\n",
       "      <td>844.8</td>\n",
       "      <td>244.8</td>\n",
       "      <td>163</td>\n",
       "      <td>...</td>\n",
       "      <td>0.013</td>\n",
       "      <td>20.6</td>\n",
       "      <td>140.4</td>\n",
       "      <td>387.4</td>\n",
       "      <td>541.2</td>\n",
       "      <td>837.5</td>\n",
       "      <td>1175.4</td>\n",
       "      <td>2005.4</td>\n",
       "      <td>3583.0</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b964ba8&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>212</td>\n",
       "      <td>5000</td>\n",
       "      <td>6000</td>\n",
       "      <td>61.373185</td>\n",
       "      <td>-139.118457</td>\n",
       "      <td>600559.0</td>\n",
       "      <td>6805805.0</td>\n",
       "      <td>843.5</td>\n",
       "      <td>320.3</td>\n",
       "      <td>121</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.005</td>\n",
       "      <td>41.5</td>\n",
       "      <td>116.8</td>\n",
       "      <td>264.9</td>\n",
       "      <td>352.1</td>\n",
       "      <td>310.5</td>\n",
       "      <td>224.4</td>\n",
       "      <td>149.9</td>\n",
       "      <td>106.0</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b96a198&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>214</td>\n",
       "      <td>5000</td>\n",
       "      <td>6250</td>\n",
       "      <td>61.374786</td>\n",
       "      <td>-139.115441</td>\n",
       "      <td>600715.0</td>\n",
       "      <td>6805988.0</td>\n",
       "      <td>839.1</td>\n",
       "      <td>281.8</td>\n",
       "      <td>222</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.002</td>\n",
       "      <td>25.2</td>\n",
       "      <td>122.5</td>\n",
       "      <td>361.2</td>\n",
       "      <td>681.5</td>\n",
       "      <td>770.7</td>\n",
       "      <td>788.5</td>\n",
       "      <td>634.9</td>\n",
       "      <td>446.7</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b96a748&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>216</td>\n",
       "      <td>5000</td>\n",
       "      <td>6750</td>\n",
       "      <td>61.378147</td>\n",
       "      <td>-139.109155</td>\n",
       "      <td>601040.0</td>\n",
       "      <td>6806372.0</td>\n",
       "      <td>833.7</td>\n",
       "      <td>181.3</td>\n",
       "      <td>121</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000</td>\n",
       "      <td>58.8</td>\n",
       "      <td>147.5</td>\n",
       "      <td>416.7</td>\n",
       "      <td>731.0</td>\n",
       "      <td>730.8</td>\n",
       "      <td>365.3</td>\n",
       "      <td>121.4</td>\n",
       "      <td>64.5</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b96acf8&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>217</td>\n",
       "      <td>5000</td>\n",
       "      <td>7000</td>\n",
       "      <td>61.379803</td>\n",
       "      <td>-139.106173</td>\n",
       "      <td>601194.0</td>\n",
       "      <td>6806561.0</td>\n",
       "      <td>830.9</td>\n",
       "      <td>357.8</td>\n",
       "      <td>178</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004</td>\n",
       "      <td>24.5</td>\n",
       "      <td>109.7</td>\n",
       "      <td>323.5</td>\n",
       "      <td>838.2</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>400.5</td>\n",
       "      <td>58.8</td>\n",
       "      <td>11.5</td>\n",
       "      <td>&lt;mtpy.core.mt.MT object at 0x7fdc4b9712e8&gt;</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>24 rows × 52 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    index  Line  Station        Lat        Long  E_WGS84_Z7  N_WGS84_Z7  \\\n",
       "0     182  5000        0  61.332953 -139.193146    596692.0   6801212.0   \n",
       "1     184  5000      250  61.334589 -139.189912    596860.0   6801399.0   \n",
       "2     185  5000      500  61.336235 -139.186733    597025.0   6801587.0   \n",
       "3     186  5000      750  61.338026 -139.183675    597183.0   6801791.0   \n",
       "4     187  5000     1000  61.339457 -139.181200    597311.0   6801954.0   \n",
       "5     190  5000     1500  61.342927 -139.174137    597678.0   6802351.0   \n",
       "6     192  5000     2000  61.346186 -139.168076    597992.0   6802723.0   \n",
       "7     194  5000     2250  61.347940 -139.164963    598153.0   6802923.0   \n",
       "8     195  5000     2500  61.349670 -139.162075    598302.0   6803120.0   \n",
       "9     196  5000     2750  61.351332 -139.158817    598471.0   6803310.0   \n",
       "10    197  5000     3000  61.353160 -139.155886    598622.0   6803518.0   \n",
       "11    199  5000     3250  61.354696 -139.152579    598794.0   6803694.0   \n",
       "12    200  5000     3500  61.356432 -139.149502    598953.0   6803892.0   \n",
       "13    201  5000     3750  61.358015 -139.146378    599115.0   6804073.0   \n",
       "14    202  5000     4000  61.359823 -139.143297    599274.0   6804279.0   \n",
       "15    205  5000     4500  61.363124 -139.137171    599591.0   6804656.0   \n",
       "16    206  5000     4750  61.364832 -139.133982    599756.0   6804851.0   \n",
       "17    207  5000     5000  61.366495 -139.130890    599916.0   6805041.0   \n",
       "18    210  5000     5500  61.369670 -139.124712    600236.0   6805404.0   \n",
       "19    211  5000     5750  61.371493 -139.121478    600403.0   6805612.0   \n",
       "20    212  5000     6000  61.373185 -139.118457    600559.0   6805805.0   \n",
       "21    214  5000     6250  61.374786 -139.115441    600715.0   6805988.0   \n",
       "22    216  5000     6750  61.378147 -139.109155    601040.0   6806372.0   \n",
       "23    217  5000     7000  61.379803 -139.106173    601194.0   6806561.0   \n",
       "\n",
       "       ALT     Az  Dur  ...  iN_1440  SNI_0011  SNI_0022  SNI_0045  SNI_0090  \\\n",
       "0   1015.0  294.3  144  ...    0.023      38.6     160.2     385.1     603.8   \n",
       "1    977.8  151.3  188  ...   -0.007      67.6     207.4     491.3     742.5   \n",
       "2   1002.1   40.4  147  ...    0.139      41.0     150.2     324.8     585.7   \n",
       "3    990.7   40.7  263  ...    0.035      50.5     206.8     510.2     736.4   \n",
       "4    966.2  265.1  273  ...   -0.001      34.6     179.6     521.7     830.8   \n",
       "5    909.5  194.6  274  ...   -0.077      31.1     190.8     615.9    1029.6   \n",
       "6    891.1  285.6  215  ...      NaN      12.8     139.5     376.9     592.0   \n",
       "7    916.7  236.7  258  ...      NaN      24.8     112.3     413.1     684.7   \n",
       "8    935.2  130.2  123  ...   -0.053      42.5     147.8     363.0     486.8   \n",
       "9    989.7  336.6  180  ...    0.008      33.0     145.0     406.5     771.5   \n",
       "10   982.9  267.7  180  ...      NaN      39.2     171.1     425.0     684.0   \n",
       "11   975.4   89.2  309  ...      NaN      29.3      75.2     360.0     721.0   \n",
       "12   955.9  282.2  180  ...      NaN      27.4     129.4     345.9     529.9   \n",
       "13   958.0   68.3  215  ...      NaN      26.6     121.0     309.2     517.4   \n",
       "14   934.2  160.9  179  ...      NaN      39.3     165.6     412.6     660.0   \n",
       "15   898.3  211.4  128  ...      NaN      29.9     154.7     339.9     505.1   \n",
       "16   880.6  191.6  159  ...      NaN      37.4     169.9     388.2     596.7   \n",
       "17   855.0  218.7  121  ...    0.010     166.7     307.3     476.8     631.7   \n",
       "18   849.9  242.4  128  ...   -0.012      32.3     134.5     298.1     589.7   \n",
       "19   844.8  244.8  163  ...    0.013      20.6     140.4     387.4     541.2   \n",
       "20   843.5  320.3  121  ...   -0.005      41.5     116.8     264.9     352.1   \n",
       "21   839.1  281.8  222  ...   -0.002      25.2     122.5     361.2     681.5   \n",
       "22   833.7  181.3  121  ...    0.000      58.8     147.5     416.7     731.0   \n",
       "23   830.9  357.8  178  ...    0.004      24.5     109.7     323.5     838.2   \n",
       "\n",
       "    SNI_0180  SNI_0360  SNI_0720  SNI_1440  \\\n",
       "0      484.1     455.3     704.7     477.2   \n",
       "1      544.4     155.9     165.1     145.6   \n",
       "2      542.6     482.1     418.0     128.0   \n",
       "3      538.5     342.3     178.1      16.6   \n",
       "4      708.4     253.2     147.5      45.8   \n",
       "5      828.2     194.7      48.5       9.2   \n",
       "6      387.6      83.0      25.6       0.0   \n",
       "7      469.5     292.3     221.9      76.2   \n",
       "8      418.0     418.4     218.8      20.1   \n",
       "9     1317.7    1987.1    1204.5     178.7   \n",
       "10     518.7     277.4     167.0      52.6   \n",
       "11     547.2     457.2     242.9      43.9   \n",
       "12     382.1     206.2     125.8      13.5   \n",
       "13     333.6     109.0      47.1       0.0   \n",
       "14     434.2     117.1      98.8       0.0   \n",
       "15     319.4     241.6     221.3       0.0   \n",
       "16     453.6     312.3     140.1       0.6   \n",
       "17    1005.5    1857.5    4405.7    5544.0   \n",
       "18     682.2     467.2     216.5     315.9   \n",
       "19     837.5    1175.4    2005.4    3583.0   \n",
       "20     310.5     224.4     149.9     106.0   \n",
       "21     770.7     788.5     634.9     446.7   \n",
       "22     730.8     365.3     121.4      64.5   \n",
       "23    1000.0     400.5      58.8      11.5   \n",
       "\n",
       "                                        mt_obj  \n",
       "0   <mtpy.core.mt.MT object at 0x7fdc4b9f4198>  \n",
       "1   <mtpy.core.mt.MT object at 0x7fdc4b9fc160>  \n",
       "2   <mtpy.core.mt.MT object at 0x7fdc4b9fccf8>  \n",
       "3   <mtpy.core.mt.MT object at 0x7fdc4b9fc5f8>  \n",
       "4   <mtpy.core.mt.MT object at 0x7fdc4b9b7438>  \n",
       "5   <mtpy.core.mt.MT object at 0x7fdc4b9b7b00>  \n",
       "6   <mtpy.core.mt.MT object at 0x7fdc4b952048>  \n",
       "7   <mtpy.core.mt.MT object at 0x7fdc4b952668>  \n",
       "8   <mtpy.core.mt.MT object at 0x7fdc4b952c18>  \n",
       "9   <mtpy.core.mt.MT object at 0x7fdc4b956208>  \n",
       "10  <mtpy.core.mt.MT object at 0x7fdc4b9567b8>  \n",
       "11  <mtpy.core.mt.MT object at 0x7fdc4b956d68>  \n",
       "12  <mtpy.core.mt.MT object at 0x7fdc4b95b358>  \n",
       "13  <mtpy.core.mt.MT object at 0x7fdc4b95b908>  \n",
       "14  <mtpy.core.mt.MT object at 0x7fdc4b95beb8>  \n",
       "15  <mtpy.core.mt.MT object at 0x7fdc4b95f4a8>  \n",
       "16  <mtpy.core.mt.MT object at 0x7fdc4b95fa58>  \n",
       "17  <mtpy.core.mt.MT object at 0x7fdc4b95ff98>  \n",
       "18  <mtpy.core.mt.MT object at 0x7fdc4b9645f8>  \n",
       "19  <mtpy.core.mt.MT object at 0x7fdc4b964ba8>  \n",
       "20  <mtpy.core.mt.MT object at 0x7fdc4b96a198>  \n",
       "21  <mtpy.core.mt.MT object at 0x7fdc4b96a748>  \n",
       "22  <mtpy.core.mt.MT object at 0x7fdc4b96acf8>  \n",
       "23  <mtpy.core.mt.MT object at 0x7fdc4b9712e8>  \n",
       "\n",
       "[24 rows x 52 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data['mt_obj']=new_data.apply(parse_row_into_mt_obj, axis=1)\n",
    "new_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One of the under appreciated aspects of pandas is that the live memory version of dataframes can store and index arbitrarily defined objects. I would not reccomend saving this again as a .csv to file, but it allows us to efficiently query, plot, and examine objects. \n",
    "\n",
    "Now that we seem to have created indexed ```MTPy``` objects, we need to verify that the attributes contained in the live objects match those from the dataframe. Trust, but verify. Another benefit of this approach is that I now have  a separate code section specifically dedicated to testin. If errors in the data cleaning are discovered at a later date, I can add additional checks here to prevent the same error from ocurring again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "HELPER CELL\n",
    "\n",
    "for assuring the created MT object is equivalent to its dataframe source data\n",
    "\n",
    "\"\"\"\n",
    "def metadata_assertions(row):\n",
    "    mt_obj = row['mt_obj']\n",
    "    lat     = row['Lat']\n",
    "    lon     = row['Long']\n",
    "    elev    = row['ALT']\n",
    "    station = row['Station']\n",
    "    \n",
    "    assert mt_obj.elev ==elev,\"elevations don't match\"\n",
    "    assert mt_obj.station==station,\"stations don't match\"\n",
    "    assert mt_obj.lon==lon,\"longitudes don't match\"\n",
    "    assert mt_obj.lat==lat,\"latitudes don't match\"\n",
    "\n",
    "def tipper_assertions(row):\n",
    "    mt_obj = row['mt_obj']\n",
    "    frequencies, t_n, t_e=generate_tipper_arrays(row)\n",
    "    source_tipper = mt_obj.Tipper\n",
    "    target_tipper = create_tipper(row)\n",
    "    np.testing.assert_array_equal(source_tipper.tipper,target_tipper.tipper,'tipper arrays not equal')\n",
    "    \n",
    "def verify_row_corresponds_to_mt_obj(row):\n",
    "    tipper_assertions(row)\n",
    "    metadata_assertions(row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data is verified\n"
     ]
    }
   ],
   "source": [
    "for index, row in new_data.iterrows():\n",
    "    verify_row_corresponds_to_mt_obj(row)\n",
    "print('data is verified')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "MtPy supports three main file types often used in MT: .xml, .edi, and .Jfile. While the .edi format is probably the most popular at the moment, a wide variety of perspectives on where and how to store metadata within the format has motivated the community to explore other ways of storing data. My favorite candidate file format is the netcdf4-5 datatype widely used by the meteorological community to describe multidimensional datasets. The .xml format is also an attractive candidate due to its self-describing structure. For now, I'll stick to saving the data in an intermediate .edi format.\n",
    "\n",
    "I'll add some machinery to create and delete any intermediate files in the .edi directory. This is a best practice to ensure that any modification to data preprocessing is both reproducible and robust.\n",
    "\n",
    "The last thing we need to do here is save the ```MT_obj```'s to file and ensure their integrity by loading them up and verifying the data much like we did before. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "directory='edi_files'\n",
    "# create temporary data directory\n",
    "if not os.path.exists(directory):\n",
    "    os.makedirs(directory)\n",
    "    \n",
    "# clear existing edi files in directory\n",
    "files = glob.glob('edi_files/*.edi')\n",
    "for f in files:\n",
    "    os.remove(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/kevin/anaconda3/envs/mtpy_inv/lib/python3.6/site-packages/mtpy/core/z.py:125: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  self._resistivity[idx_f, ii, jj] * r_err\n"
     ]
    }
   ],
   "source": [
    "# save every station as an .edi file into directory  \n",
    "for index, row in new_data.iterrows():\n",
    "    row['mt_obj'].write_mt_file(save_dir=directory, fn_basename=str(row['Station']), file_type='edi',\n",
    "                      longitude_format='LON',latlon_format='dd')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "HELPER CELL\n",
    "\n",
    "loads .edi files into a dataframe, then compares it to the previously loaded file\n",
    "\n",
    "\"\"\"\n",
    "\n",
    "def check_one_edi_per_station():\n",
    "    files = glob.glob('edi_files/*.edi')\n",
    "    assert len(files)==24,\"differing number of .edi files and stations\"\n",
    "    \n",
    "def convert_tipper_to_csv_columns(mt_obj):\n",
    "    new_row      = {}\n",
    "    frequencies  = mt_obj.Tipper.freq\n",
    "    tipper_array = mt_obj.Tipper.tipper\n",
    "    t_n=[]\n",
    "    t_e=[]\n",
    "    for index,freq in enumerate(frequencies):\n",
    "        int_freq = int(freq)\n",
    "        real_east_key = f\"rE_{int_freq:04}\"\n",
    "        imag_east_key = f\"iE_{int_freq:04}\"\n",
    "        real_north_key= f\"rN_{int_freq:04}\"\n",
    "        imag_north_key= f\"iN_{int_freq:04}\"\n",
    "        \n",
    "        new_row[real_east_key]  = tipper_array[index,0,1].real\n",
    "        new_row[imag_east_key]  = tipper_array[index,0,1].imag\n",
    "        new_row[real_north_key] = tipper_array[index,0,0].real\n",
    "        new_row[imag_north_key] = tipper_array[index,0,0].imag\n",
    "    return new_row\n",
    "    \n",
    "def extract_edi_to_dataframe_row(row):\n",
    "    mt_obj  = MT(row['filepath'])\n",
    "    new_row = convert_tipper_to_csv_columns(mt_obj)\n",
    "    new_row['Lat']    = mt_obj.lat\n",
    "    new_row['Long']   = mt_obj.lon\n",
    "    new_row['ALT']    = mt_obj.elev\n",
    "    new_row['Station']= int(float(mt_obj.station))\n",
    "    new_row['mt_obj'] = mt_obj\n",
    "    return new_row\n",
    "    \n",
    "    \n",
    "def convert_edi_files_into_dataframe():\n",
    "    files = glob.glob('edi_files/*.edi')\n",
    "    df    = pd.DataFrame(files,columns=['filepath'])\n",
    "    new_rows = []\n",
    "    for index,row in df.iterrows():\n",
    "        new_rows.append(extract_edi_to_dataframe_row(row))\n",
    "    df    = pd.DataFrame(new_rows)\n",
    "    df  = df.sort_values(by=['Station'],ascending = [True])\n",
    "    return df\n",
    "\n",
    "def check_both_dataframes_are_equivalent(source_df,target_df):\n",
    "    columns = ['Station', 'Lat', 'Long', 'ALT','rE_0011', 'rE_0022', 'rE_0045', 'rE_0090',\n",
    "       'rE_0180', 'rE_0360', 'rE_0720', 'rE_1440', 'rN_0011', 'rN_0022',\n",
    "       'rN_0045', 'rN_0090', 'rN_0180', 'rN_0360', 'rN_0720', 'rN_1440',\n",
    "       'iE_0011', 'iE_0022', 'iE_0045', 'iE_0090', 'iE_0180', 'iE_0360',\n",
    "       'iE_0720', 'iE_1440', 'iN_0011', 'iN_0022', 'iN_0045', 'iN_0090',\n",
    "       'iN_0180', 'iN_0360', 'iN_0720', 'iN_1440']\n",
    "    for col in columns:\n",
    "        target_series = target_df[col]\n",
    "        source_series = source_df[col]\n",
    "        try:\n",
    "            np.testing.assert_array_equal(target_series.values,\n",
    "                                          source_series.values,'{} columns not equal'.format(col))\n",
    "        except:\n",
    "            print('******************************')\n",
    "            print(col)\n",
    "            print('******************************')\n",
    "            for s,t in zip(target_series.values,source_series.values):\n",
    "                print('source:{} target:{} diff:{}'.format(s,t,s-t))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "******************************\n",
      "Lat\n",
      "******************************\n",
      "source:61.33295316 target:61.332953 diff:1.5999999902760464e-07\n",
      "source:61.33458935 target:61.334589 diff:3.500000005374204e-07\n",
      "source:61.33623517 target:61.336235 diff:1.6999999985500835e-07\n",
      "source:61.33802624 target:61.338026 diff:2.3999999854140697e-07\n",
      "source:61.33945685 target:61.339457 diff:-1.500000053056283e-07\n",
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      "source:61.34794011 target:61.34794 diff:1.1000000199601345e-07\n",
      "source:61.34967013 target:61.34967 diff:1.2999999654539351e-07\n",
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      "source:61.35316032 target:61.35316 diff:3.199999980552093e-07\n",
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      "source:61.35801488 target:61.358015 diff:-1.2000000282341716e-07\n",
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      "source:61.36649544 target:61.366495 diff:4.4000000087862645e-07\n",
      "source:61.36967012 target:61.36967 diff:1.2000000282341716e-07\n",
      "source:61.37149332 target:61.371493 diff:3.199999980552093e-07\n",
      "source:61.37318470000001 target:61.373185 diff:-2.999999892949745e-07\n",
      "source:61.37478629 target:61.374786 diff:2.900000026784255e-07\n",
      "source:61.37814738 target:61.378147 diff:3.8000000301963155e-07\n",
      "source:61.3798031 target:61.379803 diff:9.999999406318238e-08\n",
      "******************************\n",
      "Long\n",
      "******************************\n",
      "source:-139.19314609999998 target:-139.193146 diff:-9.999996564147295e-08\n",
      "source:-139.1899118 target:-139.189912 diff:1.9999998812636477e-07\n",
      "source:-139.1867326 target:-139.186733 diff:4.0000000467443897e-07\n",
      "source:-139.1836755 target:-139.183675 diff:-4.999999987376214e-07\n",
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      "source:-139.1649629 target:-139.164963 diff:9.999999406318238e-08\n",
      "source:-139.1620753 target:-139.162075 diff:-3.000000106112566e-07\n",
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      "source:-139.15588590000002 target:-139.155886 diff:9.999999406318238e-08\n",
      "source:-139.1525786 target:-139.152579 diff:4.0000000467443897e-07\n",
      "source:-139.1495022 target:-139.149502 diff:-1.9999998812636477e-07\n",
      "source:-139.1463785 target:-139.146378 diff:-4.999999987376214e-07\n",
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      "source:-139.1308896 target:-139.13089 diff:4.0000000467443897e-07\n",
      "source:-139.1247122 target:-139.124712 diff:-2.000000165480742e-07\n",
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      "source:-139.10617290000002 target:-139.106173 diff:9.999999406318238e-08\n",
      "******************************\n",
      "rE_0011\n",
      "******************************\n",
      "source:-0.107 target:-0.107 diff:0.0\n",
      "source:-0.009000000000000001 target:-0.009 diff:-1.734723475976807e-18\n",
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      "source:nan target:0.077 diff:nan\n",
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      "source:-0.081 target:-0.081 diff:0.0\n",
      "source:-0.018000000000000002 target:-0.018 diff:-3.469446951953614e-18\n",
      "source:nan target:-0.166 diff:nan\n",
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      "source:nan target:-0.08 diff:nan\n",
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      "source:nan target:0.0 diff:nan\n",
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      "source:-0.036000000000000004 target:-0.036 diff:-6.938893903907228e-18\n",
      "source:nan target:-0.098 diff:nan\n",
      "source:nan target:-0.023 diff:nan\n",
      "source:nan target:-0.04 diff:nan\n",
      "******************************\n",
      "rE_0022\n",
      "******************************\n",
      "source:-0.042 target:-0.042 diff:0.0\n",
      "source:-0.046 target:-0.046 diff:0.0\n",
      "source:-0.053 target:-0.053 diff:0.0\n",
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      "source:-0.023 target:-0.023 diff:0.0\n",
      "source:-0.04 target:-0.04 diff:0.0\n",
      "******************************\n",
      "rE_0045\n",
      "******************************\n",
      "source:-0.033 target:-0.033 diff:0.0\n",
      "source:-0.047 target:-0.047 diff:0.0\n",
      "source:-0.042 target:-0.042 diff:0.0\n",
      "source:-0.018000000000000002 target:-0.018 diff:-3.469446951953614e-18\n",
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      "source:-0.025 target:-0.025 diff:0.0\n",
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      "source:0.022000000000000002 target:0.022 diff:3.469446951953614e-18\n",
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      "source:0.026000000000000002 target:0.026 diff:3.469446951953614e-18\n",
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      "source:-0.016 target:-0.016 diff:0.0\n",
      "source:-0.022000000000000002 target:-0.022 diff:-3.469446951953614e-18\n",
      "******************************\n",
      "rE_0090\n",
      "******************************\n",
      "source:0.002 target:0.002 diff:0.0\n",
      "source:-0.024 target:-0.024 diff:0.0\n",
      "source:0.0 target:0.0 diff:0.0\n",
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      "source:0.002 target:0.002 diff:0.0\n",
      "source:-0.008 target:-0.008 diff:0.0\n",
      "******************************\n",
      "rE_0180\n",
      "******************************\n",
      "source:0.037000000000000005 target:0.037 diff:6.938893903907228e-18\n",
      "source:0.018000000000000002 target:0.018 diff:3.469446951953614e-18\n",
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      "source:-0.017 target:-0.017 diff:0.0\n",
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      "source:0.107 target:0.107 diff:0.0\n",
      "source:0.037000000000000005 target:0.037 diff:6.938893903907228e-18\n",
      "source:-0.067 target:-0.067 diff:0.0\n",
      "source:-0.061 target:-0.061 diff:0.0\n",
      "source:-0.02 target:-0.02 diff:0.0\n",
      "source:0.022000000000000002 target:0.022 diff:3.469446951953614e-18\n",
      "source:0.076 target:0.076 diff:0.0\n",
      "source:0.057999999999999996 target:0.058 diff:-6.938893903907228e-18\n",
      "source:-0.02 target:-0.02 diff:0.0\n",
      "source:-0.006 target:-0.006 diff:0.0\n",
      "source:0.052000000000000005 target:0.052 diff:6.938893903907228e-18\n",
      "source:0.087 target:0.087 diff:0.0\n",
      "source:0.043 target:0.043 diff:0.0\n",
      "source:0.027000000000000003 target:0.027 diff:3.469446951953614e-18\n",
      "source:0.004 target:0.004 diff:0.0\n",
      "source:0.006999999999999999 target:0.007 diff:-8.673617379884035e-19\n",
      "source:0.002 target:0.002 diff:0.0\n",
      "source:0.005 target:0.005 diff:0.0\n",
      "******************************\n",
      "rE_0360\n",
      "******************************\n",
      "source:0.06 target:0.06 diff:0.0\n",
      "source:0.105 target:0.105 diff:0.0\n",
      "source:0.09300000000000001 target:0.093 diff:1.3877787807814457e-17\n",
      "source:0.09300000000000001 target:0.093 diff:1.3877787807814457e-17\n",
      "source:-0.013999999999999999 target:-0.014 diff:1.734723475976807e-18\n",
      "source:0.145 target:0.145 diff:0.0\n",
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      "source:-0.032 target:-0.032 diff:0.0\n",
      "source:-0.14 target:-0.14 diff:0.0\n",
      "source:-0.078 target:-0.078 diff:0.0\n",
      "source:-0.028999999999999998 target:-0.029 diff:3.469446951953614e-18\n",
      "source:0.055 target:0.055 diff:0.0\n",
      "source:0.14 target:0.14 diff:0.0\n",
      "source:0.08800000000000001 target:0.088 diff:1.3877787807814457e-17\n",
      "source:-0.025 target:-0.025 diff:0.0\n",
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      "source:0.073 target:0.073 diff:0.0\n",
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      "source:0.016 target:0.016 diff:0.0\n",
      "source:0.016 target:0.016 diff:0.0\n",
      "******************************\n",
      "rE_0720\n",
      "******************************\n",
      "source:0.071 target:0.071 diff:0.0\n",
      "source:0.245 target:0.245 diff:0.0\n",
      "source:0.11699999999999999 target:0.117 diff:-1.3877787807814457e-17\n",
      "source:0.299 target:0.299 diff:0.0\n",
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      "source:0.46799999999999997 target:0.468 diff:-5.551115123125783e-17\n",
      "source:-0.009000000000000001 target:-0.009 diff:-1.734723475976807e-18\n",
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      "source:0.23199999999999998 target:0.232 diff:-2.7755575615628914e-17\n",
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      "source:0.040999999999999995 target:0.041 diff:-6.938893903907228e-18\n",
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      "source:0.026000000000000002 target:0.026 diff:3.469446951953614e-18\n",
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      "source:0.064 target:0.064 diff:0.0\n",
      "source:0.051 target:0.051 diff:0.0\n",
      "******************************\n",
      "rE_1440\n",
      "******************************\n",
      "source:0.01 target:0.01 diff:0.0\n",
      "source:0.39899999999999997 target:0.399 diff:-5.551115123125783e-17\n",
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      "source:-0.24600000000000002 target:-0.246 diff:-2.7755575615628914e-17\n",
      "source:0.614 target:0.614 diff:0.0\n",
      "source:nan target:-0.009 diff:nan\n",
      "source:nan target:-0.048 diff:nan\n",
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      "source:-0.122 target:-0.122 diff:0.0\n",
      "source:nan target:-0.042 diff:nan\n",
      "source:nan target:0.078 diff:nan\n",
      "source:nan target:0.232 diff:nan\n",
      "source:nan target:0.144 diff:nan\n",
      "source:nan target:-0.031 diff:nan\n",
      "source:nan target:0.041 diff:nan\n",
      "source:nan target:0.081 diff:nan\n",
      "source:0.09 target:0.09 diff:0.0\n",
      "source:-0.024 target:-0.024 diff:0.0\n",
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      "source:0.085 target:0.085 diff:0.0\n",
      "source:-0.025 target:-0.025 diff:0.0\n",
      "******************************\n",
      "rN_0011\n",
      "******************************\n",
      "source:-0.239 target:-0.239 diff:0.0\n",
      "source:-0.138 target:-0.138 diff:0.0\n",
      "source:-0.11800000000000001 target:-0.118 diff:-1.3877787807814457e-17\n",
      "source:-0.048 target:-0.048 diff:0.0\n",
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      "source:-0.086 target:-0.086 diff:0.0\n",
      "source:-0.019 target:-0.019 diff:0.0\n",
      "source:nan target:0.144 diff:nan\n",
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      "source:-0.006 target:-0.006 diff:0.0\n",
      "source:-0.053 target:-0.053 diff:0.0\n",
      "source:nan target:0.009 diff:nan\n",
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      "source:nan target:-0.043 diff:nan\n",
      "source:-0.111 target:-0.111 diff:0.0\n",
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      "source:-0.113 target:-0.113 diff:0.0\n",
      "source:-0.106 target:-0.106 diff:0.0\n",
      "source:nan target:-0.054 diff:nan\n",
      "source:nan target:-0.014 diff:nan\n",
      "source:-0.073 target:-0.073 diff:0.0\n",
      "source:nan target:-0.076 diff:nan\n",
      "source:nan target:-0.019 diff:nan\n",
      "source:nan target:-0.034 diff:nan\n",
      "******************************\n",
      "rN_0022\n",
      "******************************\n",
      "source:-0.154 target:-0.154 diff:0.0\n",
      "source:-0.16699999999999998 target:-0.167 diff:2.7755575615628914e-17\n",
      "source:-0.17800000000000002 target:-0.178 diff:-2.7755575615628914e-17\n",
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    }
   ],
   "source": [
    "check_one_edi_per_station()\n",
    "df = convert_edi_files_into_dataframe()\n",
    "check_both_dataframes_are_equivalent(df,new_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The utility of doing these kinds of checks is immediately demonstrated. Every column value test failed except for station. However, the tipper data appears to be identical within floating point precision ($\\approx$1e-16). Lat-Lon data appears to have dropped off a decimal place ($\\approx$1e-7), perhaps as part of MtPy's internal handling of decimal degrees. Still, the data are close enough to be trusted.\n",
    "\n",
    "\n",
    "**WAIT**. Remember when I said we needed to fill those nan values? lets check really quick to see if that happened."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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357XAfvkivMnAypJ+FBHv63uBpO8Dlw4UICLmAnMBpqw1Owpso5mZmZkNQwDd7oPcmIg4PiJmRcQGwIHAbyLifZJmVl72NuC2Vuc2MzMzs3J6Y1zNaaxp5zjIX5W0DekLyD3AB9qY28zMzMyaEKEVpgW5aAU5Iq4CrsqPDy6Zy8zMzMzKCaC71xVkMzMzMzOg7yI9V5DNzMzMzF7Qy9gb0q0WV5DNzMzMbEgR7mJhZmZmZvYCd7EwMzMzM+unx6NYmJmZmZklEdA7Bm8rXYsryGZmZmZWB9HjLhadIcbDkull7zb9/Bpld0OMK/9tayzcBn3le3qKxp/4VPmTeuKzvUXjT3qyu2h8gN6usu/XxdPLv1mXvaTwsVbZzySA3gnFU9A9peyxjqllz+mUpHD8nvKf3+MXFc5R9mMppShcmxi3rGx8gO7Jhc+H0jWuNtRbA5qqIEvaGzgV6ALOjIiT+z3/cuAHwCuBEyLi641vbXM6voJsZmZmZh0gUjeLRkjqAr4L7AEsBG6QdHFE3F552RPAPwNvbXJLm7ZitJObmZmZWVOCdJFerakOOwALIuIvEbEUmAfs/6L4EY9ExA1AG34zGJxbkM3MzMysDqKnt+GuKOsC91fmFwI7Nr1JhbiCbGZmZmZDioDegfsgz5B0Y2V+bkTMrczXqlmXv6CjQa4gm5mZmVldBhnm7bGI2H6QVRcCsyvzs4AHWrVdreY+yGZmZmZWl95e1ZzqcAOwsaQNJU0EDgQuLrqxTXALspmZmZkNKVDDNwqJiG5JxwCXk4Z5Ozsi5kv6YH7+DElrAzcCKwO9kj4KbB4RT7emBPVzBdnMzMzMhhYQTdxJLyIuAy7rt+yMyuOHSF0vRlyxLhaSPiLpNknz8zcAJK0u6QpJf85/VyuV38zMzMxaK3pVcxprilSQJW0JHEUa825rYF9JGwOfAq6MiI2BK/O8mZmZmXW4oKk+yKNKqRbkzYDrImJRRHQDvwXeRhoQ+tz8mnPpgDulmJmZmVkdwi3IzboNeJ2k6ZKmAm8iDe2xVkQ8CJD/rlkov5mZmZm1WgwwjSKStpF08mCvKXKRXkTcIekrwBXAs8AtQHe960uaA8wBGL+KuymbmZmZjbzR21osaXPg3cA7gUeBnwz2+mKjWETEWcBZeaO+TBog+mFJMyPiQUkzgUcGWHcuMBdg8rqzR9n3EjMzM7MxKHexGG0k3Qo8A8wDdsujZQyq5CgWa+a/6wFvBy4gDQh9aH7JocDPS+U3MzMzs1bTAFNHewSYDqxNnd17S46D/DNJ04FlwNER8ffc3+NCSUcA9wHvKpjfzMzMzFqpd6Q3YPgiYndJa5G6V3xX0urAhRHxhYHWKdnFYpcayx4HdiuV08zMzMwKGb1dLKaT+h8/BewKzATeP9g6vpOemZmZmdVnFFaQgUuAG0jdK15Fug/H6wZbwRVkMzMzM6uLRufQCeMj4iOSxgF/jIhnJa062ArFLtIzMzMzszEklFqQa02d7WZJb4iIXqA3d7mYMNgKbkE2MzMzs/qMwov0gNcCR0q6l9TN4jrgXwZbwRVkMzMzMxtaMBpai2vZp/J4cUTUvA9HlSvIZmZmZlaX0dgHOSLuG+46riCbmZmZWX1GYQVZ0tOku5nU2npFxEv6L+z4CnKMD5bM6Cma47mny+6GnslFwwMw4ZnSGcqfEZMfW1o0/oTnuorGB+ha1F00/vgnFxeND9C9atk37OLVyx+H3gll369Rvgj0Tip/zo1bWvan0q7JZc8HgJ6nJxaNr8L7CGDiU2VztKPFr7dwbULt6Pda+FBH6fhlw79Ao7CLRUSsPNx1Or6CbGZmZmYdIBiVLcgAkmYB61Op+0bEbwd6vSvIZmZmZlaXtrTmt5ikk4EDgNtZPg6HAFeQzczMzKxJo7CCDOwPbBoRy+pdwRVkMzMzMxuSYnT2QQb+DEwFnqp3BVeQzczMzKw+o7MP8lLgj5KuBF642j0i/mmgFVxBNjMzM7O6jMY+yMDFeaqbK8hmZmZmNrQYnRXkiDhP0gRgU1Ib+F0RMeg4lOOaSSjpbEmPSLqtsmwbSddJulnSjZJ2qDx3vKQFku6StFczuc3MzMyszWKAqYNJ2gqYD3wPuAb4raRXDrZOUxVk4Bxg737Lvgp8ISK2AT6b55G0OXAgsEVe5zRJbRhu38zMzMxaQVF76nDfBg6JiNcCdwP7Ad8YbIWmKsgR8Tvgif6Lgb47lqwCPJAf7w/Mi4glEfFXYAGwA2ZmZmbW+XIXi1pTh1slIq7LjxURjwMrDbZCiT7IHwUul/R1UgX8NXn5usB1ldctzMvMzMzMbDTo/MpwLV2Sxud+x+MkHQA8NtgKzXaxqOVDwMciYjbwMeCsvLzWwHk1G+Ulzcn9l2/sefa5AptoZmZmZsMhRm0Xi28Cm+THDwB7AYcNtkKJFuRDgY/kxz8FzsyPFwKzK6+bxfLuFy8SEXOBuQCT1p/V+bvdzMzMbKwbvaNYnFV5vE8965RoQX4AeH1+/EbS3UsgjT93oKRJkjYENgauL5DfzMzMzEroHWAaY5pqQZZ0AbArMEPSQuBzwFHAqZLGk+5WMgcgIuZLuhC4HegGjo6Inmbym5mZmVn7jILuFC3RVAU5Ig4a4KntBnj9icCJzeQ0MzMzsxEQNNVaLGlv4FSgCzgzIk7u97zy828CFgGHRcRNjWdsXIkuFmZmZmY2BjU6zFu+98V3gX2AzYGD8j0yqvYhdcHdmNQD4fSWbvwwuIJsZmZmZnVpYhzkHYAFEfGXiFgKzCPdI6Nqf+C8SK4DVpU0s6UFqJMryGZmZmY2tIFuM11fv+R1gfsr87Xuh1HPa9qixDBvZmZmZjbG9I2DPIAZkm6szM/Nw/ZWV++vf7S675lRmivIZmZmZlaXQbpTPBYR2w+yaj33w6j7nhmluYuFmZmZmdWn8S4WNwAbS9pQ0kTgQNI9MqouBg5RshPwVEQ82KpNHw63IJuZmZnZ0Jq4k15EdEs6BricNMzb2fkeGR/Mz58BXEYa4m0BaZi3w1ux2Y1wBdnMzMzM6tLMraYj4jJSJbi67IzK4wCObjxD63R+BVnApLL3MHx+rbL9v2PtxUXjA+iOKUXjdz1fq998i0XZ4zDx0eeLxgfoWXli0fgqvI8AeqaW/VjoHV/+vRSFO4/F+PLHobfw5x5Az5Syx6INnxpMeLKraPyuxeVLMeG5svF7y+6ipPApoTbcd7f050bxTq3tOOGaaEEebTq/gmxmZmZmncG3mjYzMzMzS4RbkM3MzMzMlgtQ74rRhOwKspmZmZnVxS3IZmZmZmYVg9xJb0xxBdnMzMzMhuZRLMzMzMzMlluRLtJreFQ+SZMlXS/pFknzJX2h8tw/SborL/9qZfnxkhbk5/ZqduPNzMzMrI0iak9jTDMtyEuAN0bEs5ImAFdL+gUwBdgf2CoilkhaE0DS5qT7bm8BrAP8WtImEdGG4b/NzMzMrCkrUBeLhluQI3k2z07IUwAfAk6OiCX5dY/k1+wPzIuIJRHxV9J9tndoeMvNzMzMrK3UU3saa5q68aGkLkk3A48AV0TE74FNgF0k/V7SbyW9Kr98XeD+yuoL8zIzMzMz63R5HORa01jT1EV6uXvENpJWBS6StGWOuRqwE/Aq4EJJL6X2XcJr7lFJc4A5AF3TV21mE83MzMysRVaUYd6aakHuExFPAlcBe5Nahv8zd8G4HugFZuTlsyurzQIeGCDe3IjYPiK275q2Uis20czMzMya0DeKRa1prGlmFIs1cssxkqYAuwN3Av8FvDEv3wSYCDwGXAwcKGmSpA2BjYHrm9t8MzMzM2uLqN29wl0sXmwmcK6kLlJF+8KIuFTSROBsSbcBS4FDIyKA+ZIuBG4HuoGjPYKFmZmZ2Sgy9urCNTVcQY6IW4FtayxfCrxvgHVOBE5sNKeZmZmZjZAA9awYNWTfSc/MzMzM6jIW+xvX4gqymZmZmdVlLPY3rsUVZDMzMzMbWuA+yGZmZmZmfYT7IJuZmZmZLRfuYmFmZmZmVhEQriCbmZmZmb3ALcidIoClLbkj9oBKD1my0bqPlE0A/PWe9YrGn/yEisYH6Jla9u047uqbi8YHePCTrykaf+Y1RcMDsGiNssehHUMEjX++7Pt1ydTyhXjjtrcXz/GbmzcvGn9cb/nPjWkPls0RXUXDA+X7dLbjOCxdpWz8iU+VjQ/QM6ls/PGLy8ZXO+qtHgfZzMzMzOzF3IJsZmZmZlblPshmZmZmZoki3MXCzMzMzOxFeleMe027gmxmZmZmQwtgxagfu4JsZmZmZvWRW5DNzMzMzLKIFaaLRcMDDEvaVNLNlelpSR+V9DVJd0q6VdJFklatrHO8pAWS7pK0V2uKYGZmZmbtoJ6oOTUVU1pd0hWS/pz/rjbA686W9Iik25pKWIeGK8gRcVdEbBMR2wDbAYuAi4ArgC0jYivg/4DjASRtDhwIbAHsDZwmqQ1DsJuZmZlZS0TUnprzKeDKiNgYuDLP13IOqQ5ZXKtuUbcbcHdE3BsRv4qI7rz8OmBWfrw/MC8ilkTEX4EFwA4tym9mZmZmJUVAT2/tqTn7A+fmx+cCb62dPn4HPNFssnq0qoJ8IHBBjeXvB36RH68L3F95bmFeZmZmZmajQW9v7ak5a0XEgwD575pNb2eTmr5IT9JEYD9yV4rK8hOAbuD8vkU1Vq/ZJi9pDjAHoGv1VWu9xMzMzMzaKQJ6egZ6doakGyvzcyNibt+MpF8Da9dY74QWbmHLtGIUi32AmyLi4b4Fkg4F9gV2i3ihY8pCYHZlvVnAA7UC5h06F2DS+rNWjFu2mJmZmXW6gfsbPxYR2w+8Wuw+0HOSHpY0MyIelDQTeKTJrWxaK7pYHESle4WkvYFPAvtFxKLK6y4GDpQ0SdKGwMbA9S3Ib2ZmZmalBaX6IF8MHJofHwr8vNmAzWqqgixpKrAH8J+Vxd8BXgJckYd/OwMgIuYDFwK3A78Ejo6IAdvpzczMzKyTRKk+yCcDe0j6M6leeTKApHUkXdb3IkkXANcCm0paKOmIZhMPpKkuFrmFeHq/ZRsN8voTgRObyWlmZmZmIyAocqOQiHicNCJa/+UPAG+qzB/U8uQD8J30zMzMzKw+K8id9FxBNjMzM7OhRRADj2IxpriCbGZmZmb1af6CvFHBFWQzMzMzG1qEu1iYmZmZmVW5i4WZmZmZWZ8Id7EwMzMzM3uRcAXZzMzMzAyA8CgWnUPLxJQHym7m5McGvK94S8zY5bmi8QH+2oqbhg9C3WXjA0x8YnHR+GWPcnt0r1T+lH1uZtk309SHx8KRsBVFdJXPocL1jaWrlY0PMPmxsvHbcRy6lpaN3zuhbPxQ2fgAz/D3y6/o/smMAZ4u/C5or46vIJuZmZnZyIuIvUd6G9qlcLujmZmZmdno4gqymZmZmVmFK8hmZmZmZhWuIJuZmZmZVbiCbGZmZmZW4QqymZmZmVnFkBVkSWdLekTSbTWeO1ZSSJrRb/l6kp6VdGxl2XaS/iRpgaRvSWrDiH1mZmZmZsNTTwvyOcA/jHsnaTawB3BfjXVOAX7Rb9npwBxg4zytMGPpmZmZmdnoMWQFOSJ+BzxR46lTgOPod4MySW8F/gLMryybCawcEddGRADnAW9tYrvNzMzMzIpoqA+ypP2Av0XELf2WrwR8EvhCv1XWBRZW5hfmZWZmZmZmHWXYt5qWNBU4AdizxtNfAE6JiGf7dTGu1d84aizryzGH1B0D4Nm7vvjxu4axiTMoez/wYce/5bTyOTosfkM5/tSGHMXjn/wfRXPcMdzojZShf+eoEjk6K347cgw7/jltyNFh8duRw2XojBwuQ5kc65fakBXRsCvIwMuADYFbciV4FnCTpB2AHYF3SvoqsCrQK2kx8LP8uj6zgAcGShARc4G5DWwbkm6MiO0bWbcT4rcjx1goQztyuAydkcNl6IwcLkNn5HAZOiPHWCiDDW7YFeSI+BOwZt+8pHuA7SPiMWCXyvLPA89GxHfy/DOSdgJ+DxwCfLupLTczMzMzK6CeYd4uAK4FNpW0UNIRDeb6EHAmsAC4m0Z+yDUzMzMzK2zIFuSIOGiI5zcYYPnn+83fCGw5jG1rVENdMzoofk0MFlkAABHmSURBVDtyjIUytCOHy9AZOVyGzsjhMnRGDpehM3KMhTLYIJRGXTMzMzMzM/Ctps3MzMzMXsQVZLMa2nEr9NI5XIbOyOEydEaOsVCGduRwGTojRzvKYIMbMxVkSZtKerWkCZK6Rnp7bHR+gEiaLWk1oNh7qHQOl6EzcrgMnZFjLJShHTlchs7I0Y4yWH3GRB9kSW8Hvgz8LU83AudExNMtir8HsAkwLiK+LUnR4h1XOkebyvBKYDZwM/BoRCySNC4iekdJ/LeS7gT5NHAdcENEXNqK2O3K4TJ0Rg6XoTNyjIUytCOHy9AZOdpRBhuGiBjVEzAB+Anw2jz/DuBrwL8BK7cg/s7Ao8ARwNWk8Zt3Bsa3sAxFc7SpDPsB/wdcSLoJ2LeBmfm5caMg/gzSzfx2Al4BHAr8HDiohfuoaA6XoTNyuAydkWMslMH7qTPij5UyeBre1Mid9DrRysDGwP8CF5Fuzfhm4D2Svhf53degHYDvRMRZks4HPgO8E+ghjQ/dCqVztKMM+wCfiIif55betwLflPSRiHhoFMTvBu4Cbo6IxZLuA54EDpP094j4ZQty9BTO4TLUx2UYWjvKUDpH6X0E3k/1GgtlGAvnnA3DqO+DHBHLgG8Ab5e0S6Sf268m/Qy/c6NxK/1bbwF2krRJRCwGvgQsAt7b3Ja/yJ+AV7c6R7vKIGkcqb/UZgARcRPwfeBO4BOSpnRy/BzzSeB54Pw8/xTwO+AyYLu8HQ31eZY0M8f8O/Ac8MNW53AZXIbRUobSOdq1j0qWoR05xsJ+akcZxtI5Z8Mz6ivI2f8AvwIOlvS6iOiJiB8D6wBbDzeYpB2B1+Q34+152lnSzIhYAnwR2EHSYY1usFJH/EmSpgFXkb457tKqHG0qw0RJk/KXktOAd0s6ID+9kHS3xDWBVTo0/h6Sjpb00bzoGOAxSd+CFz4QbwReK2laI79ESNoLOL3vQzbneE7SN1uRw2VwGUZZGYrmKL2P2lGGduQYC/upTWUY9eecNW5MVJBzq+j5pJbS4yXNkXQosBbw4HBi5RPiXGBxJA+SWqRfC7xJ0stzvkuAhi4Ok/RmUuXu26Tbb69N+la6C/DmZnO0qQzvAH4MXCJpP1IF/wTgEEnvznmvA1Yl9afqtPg75/iLgXdJ+jawFakiPkXSf0laFdgcmErq6z7cHG8GPg+cmo8BEfEM6YLS1ZrN4TK4DKOsDEVzlN5H7ShDO3KMhf3UpjKM+nPOmhQd0BG6VRMwEXgDMI90Ide2w1x/Z9IoGG/I8yv3e+7fgd8CpwIPA5sNM75IozD8CdiVVIE/DrgfWA/YvgU5diJ9KShShhxnE+AO4NXAQcDFwD+RTu59gFtJ/Zw/ml83u5Pi5xwfBz6XH08GTsz75tWkD6NzgB+Rvr1v00D8NUj9x07K8+vkbX93fh9MAX7QZI5iZcjbuCbw1Ggtg49DZ5ShdI527SPvp5EvQ7ThnG7XfmrHe8lTc9OIb0CRQqX+qsMe2QD4MGmUhK2A9Unf7r5PqnCvm1+zC3AksFET2zc3n3B9w+x9DLgPmNVMDmAD4FjgAlKrapEyADsCV1XmX5PLdEze968AvgJ8Hdi6gfg7lYyfY+4B/BLYJM9PIrUMfLfymsnASk0c53eRLhw9GvgNaXSVW4DTm8lRed/sRvolouVlACbnvweUKIOPw4pzHErvp3btI++nzthPed0i53Q791PpfeSp+WnEN6ATJmAj0s8Ya5NaJU8n9XH9Z9IIEJ8BLqeJYeOAt5AqwhNIldVP93v+U6RvpFMajL8XcCXwSuCDwNmtLkO/fOflD5Dxef41+UP9TU3EnJr/jsv7otXxZ+cPoWn5OJxKGvqub7i4ycD1wBFN5FiH9EvGtDz/DtJPaJ+o5LgW+OcG4+9I6iojYCapxeH9LS7DXvkfwlp5/m0tLoOPw4pzHIrup9L7yPupc/ZT6XO6HfupHe8lT62bxsowbw2TtC/pW9uTpH6u55CGc/ljRMzNr3kAeCmwpMEce5JGjvhkRCyT9Cngd5J6IuIr+WXzgE+TTsZG4n8FWB14R0ScIGkicG1EfL9FZdiRdPI+HxHXky4sfA3wiKT/jYhrJM0jDUnzq4joHmb8vYCtJH0nb+MfSBX7VsV/M2kfXUMaFvATpH7fx6SndXVE3CnpEmDZcGJXcuwNfI70Ploi6fMR8TNJt0fEHUo3NVmccwz7JjZ5H50KvDfSp+mDkq4G9s1l+N8WlKEvx99Io4Y8HBEXSdomx262DD4Ow8sxmo9D0f1Ueh/lHN5P9eUoup9Kn9M5x6g/56zFRrqGPpITqYJ3J7mvMnAG8O38eFLlde8lVQhXbTDHw8AOeX4GMJ7U0vsgqR/SJsBhpL5Gqw0z/u7AAmAL0rfrX5OGhJlA/qmoBWXYB/gzqZvDz4Fv5eWfAr4JHJznDyG1LHc1EP8WYNfKsmmkCyROaSY+bej3nfO8gXQjk51zzK8A78vPja+87hDSEISbDjN+0f7xOc5ewE2kLjifAC6pPDeumTL4OAwrx95j4DiUvp6j2D7yfhp2GdYFbiu1n4DXk/7/FDmn87p7An8s+H6aCcwv+V7y1PppxDdgRAufKq+HVebXIF0QNrGy7AhS5W2LBnNsSurqsD8wHfhv4ApSxfJLpNE3TgduAF7RQPy9gNfkx6uSRsb4cJ7v69N2VD6ph10GUp/feSyvpK5M+onp7Dz/PtKFBFeR/pkM98LIzYG/AnPy/PS8bINWxK+UYW7+IG9pv+9Kjk/07aM8fxwwtzI/EXhjPs5bNhC/aP94UreWU4HX5/kJ+QP7/ZXXTCBVQBstQxfpS2jJ43AsqSWu1HH4UN7nxa5TyMdhl4LHQaTRc1p+HUQlxweAn1HgWoj8Xj0FeGOpfVSJU+R6kX776cIS+ymv+43C5/QUUpeB00vsJ9IQnscD76ksa/U5vTrwXWDnEvsp75eXlNpHnspNI74BI1r49A975crjWaRvkWvkZS/NHzAvbzLP1sBfSBXlo/IH/Jx8Us7OrxlWy3GNHOPy372Bh8iVbWAl4Ks08Y2UdG/4g/stuwY4pTL/CmDNBmJvRxrW5si87b8m3Tr8N8BXmolP6lv+KlKl+yfAcf2eb6rfdyXHy0lXPa9fWb4jMK8yPz5/2K/VQPzS/eM3zlPfudD3Xvow8G/9XjurgeOwRf7nsmE+Dp8qcBy2JLXEbFToOGyZ30ub5OPwvQLHYUtgG5b/w+zrf9+q47AzcEh+fB7wrwWOwy7A2/PjDwFntXI/5fj7VeantHIf5fWKXi+SY+xH+l8wFfgIqVLcyv20Hy9u/JlYYD/tT/of1nden9DK/US6W+rJfec0yyuWLTmnKzlOrJxzLd1PpAas60j/v84tcc55KjeN+AZ0ypRPsmnAlXn+faSfclp1UdvmwNH9ll0OvDI/VgvL8kXSt+6uPN/IiB6bVB6/j/QT2nqVZTNILUQNtc70i/9aUovQ3aQLDPt+3rwSeF2D8fclDQf3W+A7+R/GPcDxlddsQGohamjf98vxQyot9KTK1O/z40NIvxYM6zhU4v+O9A/0taTh7uZUXjOLdEHmpCbLcFX+J7dl5bmtgAeAvZt4L/YNy3cxqVK2C3AvlUpyC45DNcfPgXUqz+3QguNQjT8vn8sfAY5q4XHYh/QLyc9Jd85at/Lc1s0cB9IX8mmkn3jvJI0AMJ30y81nWnEc+uW4i+U/gR8DfKjZ/dQv/h3kX8latY8qcfYk/dq2V2Wf3Ee6fqRV79e+HHvn+WmkL11HtuL9VIm/Z43nWrWfXp/fS337ab18Xn+8Re+nF8Xv99xOzZ7T/XLU2k/bNrufKsfhPuCzwGp5H7XsveSp7DTiG9BpE+kivZNIF4ltVTDPO3KOYX/rrTP21VT6Zw1z/X1Jt6Kufkv/ErnPVGXZPGDHFsXfAXhbjWOxUwPx+/ctnwv8G+nnrftIrTMb0WC/7wFynEbudpLnNyL9XPqufJyH2++uXf3ja5aB5a01R5Aq/9MbiL8rqT9wX//7S0iVy5flfz5N9b8fIMdFwO6V59fJ79NGj0P/+BeTxikdTx51pQXHYcAysLwV+ahGj0Mlz3HAv+T35QGkX83uJ1X2N27mONTI8SOWd5tqyfu1X/zzgI/2e68e2cw+ovD1IgPkWD3nmU5lOK9G91ON+KuQWl+nARNa+F76OHBsfrwe6bw+GHiG1Pq6aZP7qRp/HdKQaDuRuiqsTvoy39A5PUSOHfu2l/Qrb6Offf2vDfoN6XNvI9IvBU3/D/JUflrhR7HoI0mkn9R2yX93i4g/F8pzOKmv5Lsi4uFW54h0de+7Sa0Q9wxz+1Yitfp8lHSr6gsi4qCI+Ne06Vwi6TTSh/rWwCNNxv9xRLwnIq6XNKXyuneQPlyGdSfEipMj4o/58QnAORHxgKRdSR9OHydVyg+PdDvPZnN8Dvi+pMmR7lL4KOkDd1PSz9p3NBn/X4GzJE2MdKtwJB1B+kn2PRHxZAvLMIl0FXWw/OKYpQ3Efhj4QD62a5O6QHyNNIzRmaTuNRvn5Y0eh/45diSdZgeQviT+kvTPaiMaOw7947+K9OvMA8B1ki4gVQyOIfV9buQ4DFSGdwG/l/RDUgV6Jxo7Dn26SZWZs0i/1MwmdZXalnQuv4Lmzodqjh8AR0naFFgq6YSccw6N76dq/HOBIyV9g7RPPkVqnVtG4/vo8bz+TEnTgZ/mfPNp3fu1f47/II3a8xTwS0nnk1pFG30/1Yr/PPBsjt/K99LE/Hge6Xy4m/QryJ6kz73X0Ph+qsb/D9Kx7SHd+fVzpP/TL6Pxz9aBcnQDXZI+TCpLo/upK2/bfKW74c0nDVH6bUmvJ/0POpb0nmr2nLNSRrqG3mkT6RtdQxfk1RlfpBajpvo1Dxa/BTHWIbU4zCB9cFxQee5tpL6FZ9J494r+8c/v9/yhNHFxDQP3Le8ba3J9cr+1JvbRUP3XNyZ1vWjoONcRv+n+8XXkmJ7/Nt26QfqS8pn8+ChSX+oNWhW/Ro7DSa1MmwK/AjYvEH8e6Z/0SbToqvMByjAjz6/eZOyXkbu2kFphlwFfqjzfiuPcP8ci8o0PSH09m9pPA8Q/rfJ8s/uoHdeL1MrxflLL/obNvp8GiT+P5a2jze6nLUldaeaRKniQWtdPAvZvdj8NEP+lpF/SDmjFOT1Iju+RGshasZ/6XxvU92td381IGvolxVN7phHfgE6bcF+g/vtjOqmv8QV5fgsqF0G1MP6P8vxmpJ/oXtqi+LX6ln+PFl4UUSNHX7+4lnz4DVCGlvWPHyDHe0ldU4pcPEK66cv2+XGRc47Ux3/9ErErZSh6xTmpP/KrWhRrHXLLLumXgc8Bl5L7CLfiONTI8dmc46CC8S+hX5/kJnMUv15kkByt+tyrFf+XwHYt3E9vIfVj/2Jl2VksvxC0qf00QPyzabL/dB05vg8c2qoclbhfJN3roIsGuz96au/kLhb9RH4nWxIRj0v6APA1SXeRTu5dC8YXaViiRrtW9I/fDTwr6X5JJ5F+/jssIp5vRfxBchwejf+MXG/8hgbEH0aOluwnSaqeV7n7zJqkFq6WnHMD5JhBcz8jDxV/TeC5VsQfJMdapH7CTYvUxeh+UnedoyPiEklvIPWVbMlxGCxH6fjNxq7kuB24vW++8l76W36+FeWolWMNUot40waJv7AV8bNfkL5kfV7SvXnZ1qQbb7ViPw0av0Vq5diWNHpGq91CGh3lKzHMG13ZyFALznVbAUj6GGm4tz0i4k+jJX6lb/kdFOpbXjrHWChDzjGJ1Pr9ceDdEXFbK+O3I8doL4Ok2aShqv6Q58dFRG+r4rcjRzvKkOP2v15k/mjL0aYyvBJ4J2k85HNa/f+hdPx25ch5LiQNN3pPifjWWq4g25AkrUYazP5fIuLW0RY/5zgMuKHEP4h25RjtZZA0gXTh4t0RcVer47cjx1goQ87xotbq0ZijHfFJQ4E9FBF3jsYc7SiDDa0d55u1nivIVpfK6AyjNb4rBB2Sw8zMrNO5gmxmZmZmVjFupDfAzMzMzKyTuIJsZmZmZlbhCrKZmZmZWYUryGZmZmZmFa4gm5mZmZlVuIJsZmZmZlbhCrKZmZmZWcX/B1DNMS8KS4/vAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "new_data  = new_data.reset_index()\n",
    "plot_data(df,direction='N',part='real')\n",
    "plot_data(df,direction='N',part='imag')\n",
    "plot_data(df,direction='E',part='real')\n",
    "plot_data(df,direction='E',part='imag')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Perfect! As long as we keep in mind the surface and deepest layers may be biased towards a smooth halfspace.\n",
    "\n",
    "Thats it for this notebook. In the next notebook I'll examine the data directly and see what can be interpreted working towards a 2d inversion."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:mtpy_inv] *",
   "language": "python",
   "name": "conda-env-mtpy_inv-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}