{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Getting started with ELA\n",
    "\n",
    "This notebook uses data covering a few kilometres around the township of [Bungendore](https://www.google.com.au/maps/@-35.251235,149.4173155,34159m/data=!3m1!1e3) in NSW, Australia. \n",
    "\n",
    "For convenience compressed data for this notebook is available for download from [this link](https://cloudstor.aarnet.edu.au/plus/s/gTAVfJZ5Dve15ud). This data will be imported in the section 'Importing data' in this notebook. Once you adjust the data path to your liking, this notebook should run fine.\n",
    "\n",
    "Sample data was derived from the Australian Bureau of Meteorology [National Groundwater Information System](http://www.bom.gov.au/water/groundwater/ngis/index.shtml) and from [ELVIS - Elevation and Depth - Foundation Spatial Data](http://elevation.fsdf.org.au/). You can check the licensing for these data; the short version is that use for learning purposes is fine.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Purpose\n",
    "\n",
    "This notebook is a realistic example of one case study the pyela package addresses. What we obtain at the end of the workflow is a 3D gridded model of primary lithologies. A visual outcome (normally interactive) is:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![3D Interpolated overlay primary lithology clay](img/3d_overlay_bungendore_clay_lithology.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing python packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-27T01:54:38.357642Z",
     "start_time": "2018-02-27T01:54:36.460827Z"
    },
    "init_cell": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import rasterio\n",
    "from rasterio.plot import show\n",
    "import geopandas as gpd\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Only set to True for co-dev of ela from this use case:\n",
    "ela_from_source = False\n",
    "# ela_from_source = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "if ela_from_source:\n",
    "    if ('ELA_SRC' in os.environ):\n",
    "        root_src_dir = os.environ['ELA_SRC']\n",
    "    elif sys.platform == 'win32':\n",
    "        root_src_dir = r'C:\\src\\github_jm\\pyela'\n",
    "    else:\n",
    "        username = os.environ['USER']\n",
    "        root_src_dir = os.path.join('/home', username, 'src/github_jm/pyela')\n",
    "    pkg_src_dir = root_src_dir\n",
    "    sys.path.append(pkg_src_dir)\n",
    "\n",
    "from ela.textproc import *\n",
    "from ela.utils import *\n",
    "from ela.classification import *\n",
    "from ela.visual import *\n",
    "from ela.spatial import SliceOperation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing data\n",
    "\n",
    "There are two main sets of information we need: the borehole lithology logs, and the spatial information in the surface elevation (DEM) and geolocation of a subset of bores around Bungendore. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_path = None"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You probably want to explicitly set `data_path` to the location where you put the 'Bungendore' folder e.g:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#data_path = '/home/myusername/data' # On Linux, if you now have the folder /home/myusername/data/Bungendore\n",
    "#data_path = r'C:\\data\\Lithology'  # windows, if you have C:\\data\\Lithology\\Bungendore"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Otherwise a fallback for the pyela developer(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "if data_path is None:\n",
    "    if ('ELA_DATA' in os.environ):\n",
    "        data_path = os.environ['ELA_DATA']\n",
    "    elif sys.platform == 'win32':\n",
    "        data_path = r'C:\\data\\Lithology'\n",
    "    else:\n",
    "        username = os.environ['USER']\n",
    "        data_path = os.path.join('/home', username, 'data/Lithology')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "bungendore_datadir = os.path.join(data_path, 'Bungendore')\n",
    "bidgee_path = os.path.join(bungendore_datadir, 'gw_shp_murrumbidgee_river/shp_murrumbidgee_river')\n",
    "bungendore_bore_locations_fn = os.path.join(bungendore_datadir,'gw_shp_murrumbidgee_river/shp_bungendore.shp')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read the lithology logs from the whole Murrumbidgee catchment - we will subset later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "lithology_logs = pd.read_csv(os.path.join(bidgee_path, 'NGIS_LithologyLog.csv'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The DEM raster and the bore location shapefile do not use the same projection (coordinate reference system) so we reproject one of them. We choose the raster's UTM."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "bungendore_raster = rasterio.open(os.path.join(bungendore_datadir,'CLIP_66949','CLIP_reproj_UTM55.tif'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "bore_locations_raw = gpd.read_file(bungendore_bore_locations_fn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "({'init': 'epsg:3577'}, CRS.from_epsg(32755))"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bore_locations_raw.crs, bungendore_raster.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "bore_locations = bore_locations_raw.to_crs(bungendore_raster.crs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>HydroID</th>\n",
       "      <th>HydroCode</th>\n",
       "      <th>StateBoreI</th>\n",
       "      <th>StatePipeI</th>\n",
       "      <th>StateTerri</th>\n",
       "      <th>Agency</th>\n",
       "      <th>WCode</th>\n",
       "      <th>BoreDepth</th>\n",
       "      <th>DrilledDep</th>\n",
       "      <th>Status</th>\n",
       "      <th>...</th>\n",
       "      <th>Hydrostrat</th>\n",
       "      <th>WaterLevel</th>\n",
       "      <th>Salinity</th>\n",
       "      <th>WaterCount</th>\n",
       "      <th>WaterDateM</th>\n",
       "      <th>WaterDat_1</th>\n",
       "      <th>SalinityCo</th>\n",
       "      <th>SalinityDa</th>\n",
       "      <th>Salinity_1</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10055899</td>\n",
       "      <td>GW061345.1.1</td>\n",
       "      <td>GW061345</td>\n",
       "      <td>1.1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>53.3</td>\n",
       "      <td>53.3</td>\n",
       "      <td>UNK</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>POINT (713783.3445196336 6099618.639519438)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10094010</td>\n",
       "      <td>GW404937.1.1</td>\n",
       "      <td>GW404937</td>\n",
       "      <td>1.1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>96.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>ABN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>POINT (718150.9998919906 6093237.005439439)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10114667</td>\n",
       "      <td>GW414316.1.1</td>\n",
       "      <td>GW414316</td>\n",
       "      <td>1.1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>42.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>USE</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>POINT (713568.9940640796 6106887.001336516)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10114672</td>\n",
       "      <td>GW414581.1.1</td>\n",
       "      <td>GW414581</td>\n",
       "      <td>1.1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>42.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>USE</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>POINT (715642.0000155731 6097858.004591262)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10122533</td>\n",
       "      <td>GW402017.1.1</td>\n",
       "      <td>GW402017</td>\n",
       "      <td>1.1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>90.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>UNK</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>POINT (712620.6561813344 6102894.13739373)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 52 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    HydroID     HydroCode StateBoreI StatePipeI  StateTerri  Agency  WCode  \\\n",
       "0  10055899  GW061345.1.1   GW061345        1.1           1       1      8   \n",
       "1  10094010  GW404937.1.1   GW404937        1.1           1       1      8   \n",
       "2  10114667  GW414316.1.1   GW414316        1.1           1       1      8   \n",
       "3  10114672  GW414581.1.1   GW414581        1.1           1       1      8   \n",
       "4  10122533  GW402017.1.1   GW402017        1.1           1       1      8   \n",
       "\n",
       "   BoreDepth  DrilledDep Status  ... Hydrostrat  WaterLevel  Salinity  \\\n",
       "0       53.3        53.3    UNK  ...          0           0         0   \n",
       "1       96.0        96.0    ABN  ...          0           0         0   \n",
       "2       42.0        42.0    USE  ...          0           0         0   \n",
       "3       42.0         0.0    USE  ...          0           0         0   \n",
       "4       90.0        90.0    UNK  ...          0           0         0   \n",
       "\n",
       "  WaterCount  WaterDateM  WaterDat_1 SalinityCo  SalinityDa  Salinity_1  \\\n",
       "0          0        None        None          0        None        None   \n",
       "1          0        None        None          0        None        None   \n",
       "2          0        None        None          0        None        None   \n",
       "3          0        None        None          0        None        None   \n",
       "4          0        None        None          0        None        None   \n",
       "\n",
       "                                      geometry  \n",
       "0  POINT (713783.3445196336 6099618.639519438)  \n",
       "1  POINT (718150.9998919906 6093237.005439439)  \n",
       "2  POINT (713568.9940640796 6106887.001336516)  \n",
       "3  POINT (715642.0000155731 6097858.004591262)  \n",
       "4   POINT (712620.6561813344 6102894.13739373)  \n",
       "\n",
       "[5 rows x 52 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bore_locations.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# backup, but likely obsolete:\n",
    "# raster_projstring = \"+proj=utm +zone=55 +south +datum=WGS84 +units=m +no_defs\"\n",
    "# bore_locations = bore_locations_raw.to_crs(raster_projstring)\n",
    "# bore_locations.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Geolocation of data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f4cbda66cc0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 12))\n",
    "show(bungendore_raster,title='East of Bungendore, AU', cmap='terrain',  ax=ax)\n",
    "bore_locations.plot(ax=ax, facecolor='black')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>BoreID</th>\n",
       "      <th>HydroCode</th>\n",
       "      <th>RefElev</th>\n",
       "      <th>RefElevDesc</th>\n",
       "      <th>FromDepth</th>\n",
       "      <th>ToDepth</th>\n",
       "      <th>TopElev</th>\n",
       "      <th>BottomElev</th>\n",
       "      <th>MajorLithCode</th>\n",
       "      <th>MinorLithCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Source</th>\n",
       "      <th>LogType</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3295968</td>\n",
       "      <td>10096490</td>\n",
       "      <td>GW403458.1.1</td>\n",
       "      <td>332.05</td>\n",
       "      <td>UNK</td>\n",
       "      <td>29.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>303.05</td>\n",
       "      <td>302.05</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sump</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3295974</td>\n",
       "      <td>10117707</td>\n",
       "      <td>GW400023.1.1</td>\n",
       "      <td>108.41</td>\n",
       "      <td>UNK</td>\n",
       "      <td>69.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>39.41</td>\n",
       "      <td>37.41</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3295982</td>\n",
       "      <td>10094368</td>\n",
       "      <td>GW405126.1.1</td>\n",
       "      <td>223.24</td>\n",
       "      <td>UNK</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>223.24</td>\n",
       "      <td>222.64</td>\n",
       "      <td>TPSL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Topsoil</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3296095</td>\n",
       "      <td>10113483</td>\n",
       "      <td>GW415991.1.1</td>\n",
       "      <td>None</td>\n",
       "      <td>UNK</td>\n",
       "      <td>0.4</td>\n",
       "      <td>10.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>CLAY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clay</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3296209</td>\n",
       "      <td>10144702</td>\n",
       "      <td>GW401440.1.1</td>\n",
       "      <td>76.17</td>\n",
       "      <td>UNK</td>\n",
       "      <td>128.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>-51.83</td>\n",
       "      <td>-62.83</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clay</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3296429</td>\n",
       "      <td>10108243</td>\n",
       "      <td>GW416031.1.1</td>\n",
       "      <td>None</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>CLAY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clay</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>3296436</td>\n",
       "      <td>10130964</td>\n",
       "      <td>GW416560.1.1</td>\n",
       "      <td>None</td>\n",
       "      <td>UNK</td>\n",
       "      <td>5.1</td>\n",
       "      <td>7.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>FSND</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Fine sand, dry</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3296437</td>\n",
       "      <td>10126252</td>\n",
       "      <td>GW415984.1.1</td>\n",
       "      <td>None</td>\n",
       "      <td>UNK</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>FILL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Fill</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>3296441</td>\n",
       "      <td>10106582</td>\n",
       "      <td>GW416266.1.1</td>\n",
       "      <td>None</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>CLAY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clay</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>3296577</td>\n",
       "      <td>10004408</td>\n",
       "      <td>GW030348.1.1</td>\n",
       "      <td>115.9</td>\n",
       "      <td>NGS</td>\n",
       "      <td>4.58</td>\n",
       "      <td>6.1</td>\n",
       "      <td>111.32</td>\n",
       "      <td>109.8</td>\n",
       "      <td>CLAY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clay - grey to yellow brown; quartz grains fin...</td>\n",
       "      <td>WC&amp;IC</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   OBJECTID    BoreID     HydroCode RefElev RefElevDesc FromDepth ToDepth  \\\n",
       "0   3295968  10096490  GW403458.1.1  332.05         UNK      29.0    30.0   \n",
       "1   3295974  10117707  GW400023.1.1  108.41         UNK      69.0    71.0   \n",
       "2   3295982  10094368  GW405126.1.1  223.24         UNK       0.0     0.6   \n",
       "3   3296095  10113483  GW415991.1.1    None         UNK       0.4    10.0   \n",
       "4   3296209  10144702  GW401440.1.1   76.17         UNK     128.0   139.0   \n",
       "5   3296429  10108243  GW416031.1.1    None         UNK       1.0     4.0   \n",
       "6   3296436  10130964  GW416560.1.1    None         UNK       5.1     7.0   \n",
       "7   3296437  10126252  GW415984.1.1    None         UNK       0.0     0.2   \n",
       "8   3296441  10106582  GW416266.1.1    None         UNK       1.0     5.0   \n",
       "9   3296577  10004408  GW030348.1.1   115.9         NGS      4.58     6.1   \n",
       "\n",
       "  TopElev BottomElev MajorLithCode  MinorLithCode  \\\n",
       "0  303.05     302.05          None            NaN   \n",
       "1   39.41      37.41          None            NaN   \n",
       "2  223.24     222.64          TPSL            NaN   \n",
       "3    None       None          CLAY            NaN   \n",
       "4  -51.83     -62.83          None            NaN   \n",
       "5    None       None          CLAY            NaN   \n",
       "6    None       None          FSND            NaN   \n",
       "7    None       None          FILL            NaN   \n",
       "8    None       None          CLAY            NaN   \n",
       "9  111.32      109.8          CLAY            NaN   \n",
       "\n",
       "                                         Description Source  LogType  \n",
       "0                                               Sump    UNK        1  \n",
       "1                                                NaN    UNK        1  \n",
       "2                                            Topsoil    UNK        1  \n",
       "3                                               Clay    UNK        1  \n",
       "4                                               Clay    UNK        1  \n",
       "5                                               Clay    UNK        1  \n",
       "6                                     Fine sand, dry    UNK        1  \n",
       "7                                               Fill    UNK        1  \n",
       "8                                               Clay    UNK        1  \n",
       "9  Clay - grey to yellow brown; quartz grains fin...  WC&IC        2  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lithology_logs.head(n=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that around 2500 data points do not have their AHD height but do have their depth. This will be remediated when we calculate our own AHD heights."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Subset to the location of interest\n",
    "\n",
    "The lithology logs are for all of the Murrumbidgee catchment, which is much larger than the area of interest and for which we have the geolocation of boreholes. We subset to the location of interest "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-06T00:50:36.439052Z",
     "start_time": "2018-02-06T00:50:36.434305Z"
    }
   },
   "outputs": [],
   "source": [
    "df = lithology_logs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's subset the logs based on spatial locations, to keep only those \"nearby\" the DEM we have near the locality of Bungendore in this case study. First define a few constants: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['OBJECTID', 'BoreID', 'HydroCode', 'RefElev', 'RefElevDesc',\n",
       "       'FromDepth', 'ToDepth', 'TopElev', 'BottomElev', 'MajorLithCode',\n",
       "       'MinorLithCode', 'Description', 'Source', 'LogType'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "DEPTH_FROM_COL = 'FromDepth'\n",
    "DEPTH_TO_COL = 'ToDepth'\n",
    "\n",
    "TOP_ELEV_COL = 'TopElev'\n",
    "BOTTOM_ELEV_COL = 'BottomElev'\n",
    "\n",
    "LITHO_DESC_COL = 'Description'\n",
    "HYDRO_CODE_COL = 'HydroCode'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Merging the geolocation from the shapefile and lithology records"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The geopandas data frame has a column geometry listing `POINT` objects. 'ela' includes  `get_coords_from_gpd_shape` to extrace the coordinates to a simpler structure. 'ela' has predefined column names (e.g. EASTING_COL) defined for easting/northing information, that we can use to name our coordinate information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Easting</th>\n",
       "      <th>Northing</th>\n",
       "      <th>HydroCode</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>713783.344520</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>718150.999892</td>\n",
       "      <td>6.093237e+06</td>\n",
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       "    <tr>\n",
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       "      <td>713568.994064</td>\n",
       "      <td>6.106887e+06</td>\n",
       "      <td>GW414316.1.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>715642.000016</td>\n",
       "      <td>6.097858e+06</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>712620.656181</td>\n",
       "      <td>6.102894e+06</td>\n",
       "      <td>GW402017.1.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Easting      Northing     HydroCode\n",
       "0  713783.344520  6.099619e+06  GW061345.1.1\n",
       "1  718150.999892  6.093237e+06  GW404937.1.1\n",
       "2  713568.994064  6.106887e+06  GW414316.1.1\n",
       "3  715642.000016  6.097858e+06  GW414581.1.1\n",
       "4  712620.656181  6.102894e+06  GW402017.1.1"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geoloc = get_coords_from_gpd_shape(bore_locations, colname='geometry', out_colnames=[EASTING_COL, NORTHING_COL])\n",
    "geoloc[HYDRO_CODE_COL] = bore_locations[HYDRO_CODE_COL]\n",
    "geoloc.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With this data frame we can perform two operations in one go: subsetting the lithology records to only the 640 bores of interest, and adding to the result the x/y geolocations to the data frame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(640, 58944)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(geoloc), len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.merge(df, geoloc, how='inner', on=HYDRO_CODE_COL, sort=False, copy=True, indicator=False, validate=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2454"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>BoreID</th>\n",
       "      <th>HydroCode</th>\n",
       "      <th>RefElev</th>\n",
       "      <th>RefElevDesc</th>\n",
       "      <th>FromDepth</th>\n",
       "      <th>ToDepth</th>\n",
       "      <th>TopElev</th>\n",
       "      <th>BottomElev</th>\n",
       "      <th>MajorLithCode</th>\n",
       "      <th>MinorLithCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Source</th>\n",
       "      <th>LogType</th>\n",
       "      <th>Easting</th>\n",
       "      <th>Northing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>3297041</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>8.8</td>\n",
       "      <td>11.0</td>\n",
       "      <td>682.63</td>\n",
       "      <td>680.43</td>\n",
       "      <td>SHLE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Shale broken</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3297109</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>691.43</td>\n",
       "      <td>690.53</td>\n",
       "      <td>TPSL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Topsoil</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3297126</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>0.9</td>\n",
       "      <td>3.3</td>\n",
       "      <td>690.53</td>\n",
       "      <td>688.13</td>\n",
       "      <td>CLAY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clay</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3297127</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>5.2</td>\n",
       "      <td>7.3</td>\n",
       "      <td>686.23</td>\n",
       "      <td>684.13</td>\n",
       "      <td>SAND</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sand clay</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3297180</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>7.3</td>\n",
       "      <td>8.8</td>\n",
       "      <td>684.13</td>\n",
       "      <td>682.63</td>\n",
       "      <td>CLAY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clay</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   OBJECTID    BoreID     HydroCode RefElev RefElevDesc FromDepth ToDepth  \\\n",
       "0   3297041  10037380  GW058949.1.1  691.43         UNK       8.8    11.0   \n",
       "1   3297109  10037380  GW058949.1.1  691.43         UNK       0.0     0.9   \n",
       "2   3297126  10037380  GW058949.1.1  691.43         UNK       0.9     3.3   \n",
       "3   3297127  10037380  GW058949.1.1  691.43         UNK       5.2     7.3   \n",
       "4   3297180  10037380  GW058949.1.1  691.43         UNK       7.3     8.8   \n",
       "\n",
       "  TopElev BottomElev MajorLithCode  MinorLithCode   Description Source  \\\n",
       "0  682.63     680.43          SHLE            NaN  Shale broken    UNK   \n",
       "1  691.43     690.53          TPSL            NaN       Topsoil    UNK   \n",
       "2  690.53     688.13          CLAY            NaN          Clay    UNK   \n",
       "3  686.23     684.13          SAND            NaN     Sand clay    UNK   \n",
       "4  684.13     682.63          CLAY            NaN          Clay    UNK   \n",
       "\n",
       "   LogType        Easting      Northing  \n",
       "0        1  720769.160247  6.095597e+06  \n",
       "1        1  720769.160247  6.095597e+06  \n",
       "2        1  720769.160247  6.095597e+06  \n",
       "3        1  720769.160247  6.095597e+06  \n",
       "4        1  720769.160247  6.095597e+06  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Round up 'depth to' and 'depth from' columns\n",
    "\n",
    "We round the depth related columns to the upper integer value and drop the entries where the resulting depths have degenerated to 0. `ela` has a class `DepthsRounding` to facilitate this operations on lithology records with varying column names.\n",
    "\n",
    "We first clean up height/depths columns to make sure they are numeric."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def as_numeric(x):\n",
    "    if isinstance(x, float):\n",
    "        return x\n",
    "    if x == 'None':\n",
    "        return np.nan\n",
    "    elif x is None:\n",
    "        return np.nan\n",
    "    elif isinstance(x, str):\n",
    "        return float(x)\n",
    "    else:\n",
    "        return float(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[DEPTH_FROM_COL] = df[DEPTH_FROM_COL].apply(as_numeric)\n",
    "df[DEPTH_TO_COL] = df[DEPTH_TO_COL].apply(as_numeric)\n",
    "df[TOP_ELEV_COL] = df[TOP_ELEV_COL].apply(as_numeric)\n",
    "df[BOTTOM_ELEV_COL] = df[BOTTOM_ELEV_COL].apply(as_numeric)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "dr = DepthsRounding(DEPTH_FROM_COL, DEPTH_TO_COL)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Before rounding heights we have 2454 records'"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"Before rounding heights we have \" + str(len(df)) + \" records\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'After removing thin sliced entries of less than a metre, we are left with 2222 records left'"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = dr.round_to_metre_depths(df, np.round, True)\n",
    "\"After removing thin sliced entries of less than a metre, we are left with \" + str(len(df)) + \" records left\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploring the descriptive lithology "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    Shale broken\n",
       "1         Topsoil\n",
       "2            Clay\n",
       "3       Sand clay\n",
       "4            Clay\n",
       "Name: Description, dtype: object"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "descs = df[LITHO_DESC_COL]\n",
    "descs = descs.reset_index()\n",
    "descs = descs[LITHO_DESC_COL]\n",
    "descs.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The description column as read seems to be objects. Other columns seem to be objects when they should be numeric. We define two functions to clean these."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "def clean_desc(x):\n",
    "    if isinstance(x, float):\n",
    "        return u''\n",
    "    elif x is None:\n",
    "        return u''\n",
    "    else:\n",
    "        # python2 return unicode(x)        \n",
    "        return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = [clean_desc(x) for x in descs]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "from striplog import Lexicon\n",
    "lex = Lexicon.default()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = clean_lithology_descriptions(y, lex)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We get a flat list of all the \"tokens\" but remove stop words ('s', 'the' and the like)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = v_lower(y)\n",
    "vt = v_word_tokenize(y)\n",
    "flat = np.concatenate(vt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "import nltk\n",
    "from nltk.corpus import stopwords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "stoplist = stopwords.words('english')\n",
    "exclude = stoplist + ['.',',',';',':','(',')','-']\n",
    "flat = [word for word in flat if word not in exclude]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "271"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(set(flat))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_most_common= token_freq(flat, 50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f4cb8092668>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_freq(df_most_common)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are terms such as 'sandy', 'clayey', 'silty' and so on. Let's define functions to detect terms derived from lithology classes, and their frequency. Given the likely skewness, we use a y log scale. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f4cb3e8a6d8>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_freq_for_root(flat, 'sand')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f4cb3d52080>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_freq_for_root(flat, 'clay')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO: add a section that defines additional clean up e.g. 'sand/clay/soil' or dashed union composite terms\n",
    "# split_composite_term('sand/clay/soil', '/').replace('/', ' / ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>token</th>\n",
       "      <th>frequency</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>shale</td>\n",
       "      <td>833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>clay</td>\n",
       "      <td>711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>grey</td>\n",
       "      <td>345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>gravel</td>\n",
       "      <td>270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>brown</td>\n",
       "      <td>259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>water</td>\n",
       "      <td>250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>supply</td>\n",
       "      <td>218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>yellow</td>\n",
       "      <td>206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>black</td>\n",
       "      <td>187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>soft</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>sand</td>\n",
       "      <td>155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>hard</td>\n",
       "      <td>109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>light</td>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>topsoil</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>white</td>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>slate</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>bands</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>sandy</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>weathered</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>quartz</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>soil</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>granite</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>blue</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>red</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>broken</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>decomposed</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>coarse</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>fractured</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>shales</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>siltstone</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>bearing</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>sandstone</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>fine</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>dark</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>rock</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>plastic</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>basalt</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>pink</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>clayey</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>clays</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>grained</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>interbedded</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>sticky</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>medium</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>orange</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>&amp;</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>large</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>silt</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>loamy</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>top</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          token  frequency\n",
       "0         shale        833\n",
       "1          clay        711\n",
       "2          grey        345\n",
       "3        gravel        270\n",
       "4         brown        259\n",
       "5         water        250\n",
       "6        supply        218\n",
       "7        yellow        206\n",
       "8         black        187\n",
       "9          soft        182\n",
       "10         sand        155\n",
       "11         hard        109\n",
       "12        light        101\n",
       "13      topsoil         93\n",
       "14        white         87\n",
       "15        slate         79\n",
       "16        bands         78\n",
       "17        sandy         75\n",
       "18    weathered         73\n",
       "19       quartz         67\n",
       "20         soil         66\n",
       "21      granite         65\n",
       "22         blue         65\n",
       "23          red         60\n",
       "24       broken         53\n",
       "25   decomposed         52\n",
       "26       coarse         49\n",
       "27    fractured         47\n",
       "28       shales         42\n",
       "29    siltstone         32\n",
       "30      bearing         31\n",
       "31    sandstone         29\n",
       "32         fine         27\n",
       "33         dark         26\n",
       "34         rock         26\n",
       "35      plastic         24\n",
       "36       basalt         22\n",
       "37         pink         19\n",
       "38       clayey         18\n",
       "39        clays         16\n",
       "40      grained         16\n",
       "41  interbedded         16\n",
       "42       sticky         16\n",
       "43       medium         15\n",
       "44       orange         15\n",
       "45            &         15\n",
       "46        large         15\n",
       "47         silt         14\n",
       "48        loamy         13\n",
       "49          top         13"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_most_common"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Defining lithology classes and finding primary/secondary lithologies\n",
    "\n",
    "From the list of most common tokens, we may want to define lithology classes as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[LITHO_DESC_COL] = y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "lithologies = ['clay','sand','gravel','granite','shale','silt','topsoil','loam','soil','slate','sandstone']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And to capture any of these we devise a regular expression:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "any_litho_markers_re = r'sand|clay|ston|shale|silt|granit|soil|gravel|loam|slate'\n",
    "regex = re.compile(any_litho_markers_re)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_lithologies_numclasses = create_numeric_classes(lithologies)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "lithologies_dict = dict([(x,x) for x in lithologies])\n",
    "lithologies_dict['sands'] = 'sand'\n",
    "lithologies_dict['clays'] = 'clay'\n",
    "lithologies_dict['shales'] = 'shale'\n",
    "lithologies_dict['claystone'] = 'clay'\n",
    "lithologies_dict['siltstone'] = 'silt'\n",
    "lithologies_dict['limesand'] = 'sand' # ??\n",
    "lithologies_dict['calcarenite'] = 'limestone' # ??\n",
    "lithologies_dict['calcitareous'] = 'limestone' # ??\n",
    "lithologies_dict['mudstone'] = 'silt' # ??\n",
    "lithologies_dict['capstone'] = 'limestone' # ??\n",
    "lithologies_dict['ironstone'] = 'sandstone' # ??\n",
    "#lithologies_dict['topsoil'] = 'soil' # ??"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "lithologies_adjective_dict = {\n",
    "    'sandy' :  'sand',\n",
    "    'clayey' :  'clay',\n",
    "    'clayish' :  'clay',\n",
    "    'shaley' :  'shale',\n",
    "    'silty' :  'silt',\n",
    "    'gravelly' :  'gravel'\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "v_tokens = v_word_tokenize(y)\n",
    "litho_terms_detected = v_find_litho_markers(v_tokens, regex=regex)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's see if we detect these lithology markers in each bore log entries  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 148 entries with no marker, 2074 entries with at least one, 465 with at least two\n"
     ]
    }
   ],
   "source": [
    "zero_mark = [x for x in litho_terms_detected if len(x) == 0 ]\n",
    "at_least_one_mark = [x for x in litho_terms_detected if len(x) >= 1]\n",
    "at_least_two_mark = [x for x in litho_terms_detected if len(x) >= 2]\n",
    "print('There are %s entries with no marker, %s entries with at least one, %s with at least two'%(len(zero_mark),len(at_least_one_mark),len(at_least_two_mark)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note: probably need to think of precanned facilities in ela to assess the detection rate in such EDA. Maybe wordcloud not such a bad idea too."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "descs_zero_mark = [y[i] for i in range(len(litho_terms_detected)) if len(litho_terms_detected[i]) == 0 ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['quartz water supply',\n",
       " 'humus',\n",
       " 'quartz',\n",
       " 'aquifer water supply',\n",
       " 'none',\n",
       " 'none',\n",
       " 'black rock',\n",
       " 'rock water supply',\n",
       " 'yellow rock',\n",
       " 'basalt',\n",
       " 'coal lignitic',\n",
       " 'driller',\n",
       " 'dacite water supply',\n",
       " 'surface rock',\n",
       " 'dacite, yellowibrown',\n",
       " 'dacite, blue with black',\n",
       " 'quartz feldspar porphry - quartz veins',\n",
       " 'sediment, light browns-white',\n",
       " 'sediment - fine']"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "descs_zero_mark[1:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "primary_litho = v_find_primary_lithology(litho_terms_detected, lithologies_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "secondary_litho = v_find_secondary_lithology(litho_terms_detected, primary_litho, lithologies_adjective_dict, lithologies_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[PRIMARY_LITHO_COL]=primary_litho\n",
    "df[SECONDARY_LITHO_COL]=secondary_litho"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[PRIMARY_LITHO_NUM_COL] = v_to_litho_class_num(primary_litho, my_lithologies_numclasses)\n",
    "df[SECONDARY_LITHO_NUM_COL] = v_to_litho_class_num(secondary_litho, my_lithologies_numclasses)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>BoreID</th>\n",
       "      <th>HydroCode</th>\n",
       "      <th>RefElev</th>\n",
       "      <th>RefElevDesc</th>\n",
       "      <th>FromDepth</th>\n",
       "      <th>ToDepth</th>\n",
       "      <th>TopElev</th>\n",
       "      <th>BottomElev</th>\n",
       "      <th>MajorLithCode</th>\n",
       "      <th>MinorLithCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Source</th>\n",
       "      <th>LogType</th>\n",
       "      <th>Easting</th>\n",
       "      <th>Northing</th>\n",
       "      <th>Lithology_1</th>\n",
       "      <th>Lithology_2</th>\n",
       "      <th>Lithology_1_num</th>\n",
       "      <th>Lithology_2_num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3297041</td>\n",
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       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>9.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>682.63</td>\n",
       "      <td>680.43</td>\n",
       "      <td>SHLE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>shale broken</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>shale</td>\n",
       "      <td></td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3297109</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>691.43</td>\n",
       "      <td>690.53</td>\n",
       "      <td>TPSL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>topsoil</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>topsoil</td>\n",
       "      <td></td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3297126</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>690.53</td>\n",
       "      <td>688.13</td>\n",
       "      <td>CLAY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>clay</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>clay</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3297127</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>686.23</td>\n",
       "      <td>684.13</td>\n",
       "      <td>SAND</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sand clay</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>sand</td>\n",
       "      <td>clay</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3297180</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>684.13</td>\n",
       "      <td>682.63</td>\n",
       "      <td>CLAY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>clay</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>clay</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   OBJECTID    BoreID     HydroCode RefElev RefElevDesc  FromDepth  ToDepth  \\\n",
       "0   3297041  10037380  GW058949.1.1  691.43         UNK        9.0     11.0   \n",
       "1   3297109  10037380  GW058949.1.1  691.43         UNK        0.0      1.0   \n",
       "2   3297126  10037380  GW058949.1.1  691.43         UNK        1.0      3.0   \n",
       "3   3297127  10037380  GW058949.1.1  691.43         UNK        5.0      7.0   \n",
       "4   3297180  10037380  GW058949.1.1  691.43         UNK        7.0      9.0   \n",
       "\n",
       "   TopElev  BottomElev MajorLithCode  MinorLithCode   Description Source  \\\n",
       "0   682.63      680.43          SHLE            NaN  shale broken    UNK   \n",
       "1   691.43      690.53          TPSL            NaN       topsoil    UNK   \n",
       "2   690.53      688.13          CLAY            NaN          clay    UNK   \n",
       "3   686.23      684.13          SAND            NaN     sand clay    UNK   \n",
       "4   684.13      682.63          CLAY            NaN          clay    UNK   \n",
       "\n",
       "   LogType        Easting      Northing Lithology_1 Lithology_2  \\\n",
       "0        1  720769.160247  6.095597e+06       shale               \n",
       "1        1  720769.160247  6.095597e+06     topsoil               \n",
       "2        1  720769.160247  6.095597e+06        clay               \n",
       "3        1  720769.160247  6.095597e+06        sand        clay   \n",
       "4        1  720769.160247  6.095597e+06        clay               \n",
       "\n",
       "   Lithology_1_num  Lithology_2_num  \n",
       "0              4.0              NaN  \n",
       "1              6.0              NaN  \n",
       "2              0.0              NaN  \n",
       "3              1.0              0.0  \n",
       "4              0.0              NaN  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Converting depth below ground to Australian Height Datum elevation\n",
    "\n",
    "While the bore entries have columns for AHD elevations, many appear to be missing data. Since we have a DEM of the region we can correct this."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "cd = HeightDatumConverter(bungendore_raster)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = cd.add_height(df, \n",
    "        depth_from_col=DEPTH_FROM_COL, depth_to_col=DEPTH_TO_COL, \n",
    "        depth_from_ahd_col=DEPTH_FROM_AHD_COL, depth_to_ahd_col=DEPTH_TO_AHD_COL, \n",
    "        easting_col=EASTING_COL, northing_col=NORTHING_COL, drop_na=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>BoreID</th>\n",
       "      <th>HydroCode</th>\n",
       "      <th>RefElev</th>\n",
       "      <th>RefElevDesc</th>\n",
       "      <th>FromDepth</th>\n",
       "      <th>ToDepth</th>\n",
       "      <th>TopElev</th>\n",
       "      <th>BottomElev</th>\n",
       "      <th>MajorLithCode</th>\n",
       "      <th>...</th>\n",
       "      <th>Source</th>\n",
       "      <th>LogType</th>\n",
       "      <th>Easting</th>\n",
       "      <th>Northing</th>\n",
       "      <th>Lithology_1</th>\n",
       "      <th>Lithology_2</th>\n",
       "      <th>Lithology_1_num</th>\n",
       "      <th>Lithology_2_num</th>\n",
       "      <th>Depth From (AHD)</th>\n",
       "      <th>Depth To (AHD)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3297041</td>\n",
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       "      <td>9.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>682.63</td>\n",
       "      <td>680.43</td>\n",
       "      <td>SHLE</td>\n",
       "      <td>...</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>shale</td>\n",
       "      <td></td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>682.26709</td>\n",
       "      <td>680.26709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3297109</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>691.43</td>\n",
       "      <td>690.53</td>\n",
       "      <td>TPSL</td>\n",
       "      <td>...</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>topsoil</td>\n",
       "      <td></td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>691.26709</td>\n",
       "      <td>690.26709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3297126</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>690.53</td>\n",
       "      <td>688.13</td>\n",
       "      <td>CLAY</td>\n",
       "      <td>...</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>clay</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>690.26709</td>\n",
       "      <td>688.26709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3297127</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>686.23</td>\n",
       "      <td>684.13</td>\n",
       "      <td>SAND</td>\n",
       "      <td>...</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>sand</td>\n",
       "      <td>clay</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>686.26709</td>\n",
       "      <td>684.26709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3297180</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>684.13</td>\n",
       "      <td>682.63</td>\n",
       "      <td>CLAY</td>\n",
       "      <td>...</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>clay</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>684.26709</td>\n",
       "      <td>682.26709</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   OBJECTID    BoreID     HydroCode RefElev RefElevDesc  FromDepth  ToDepth  \\\n",
       "0   3297041  10037380  GW058949.1.1  691.43         UNK        9.0     11.0   \n",
       "1   3297109  10037380  GW058949.1.1  691.43         UNK        0.0      1.0   \n",
       "2   3297126  10037380  GW058949.1.1  691.43         UNK        1.0      3.0   \n",
       "3   3297127  10037380  GW058949.1.1  691.43         UNK        5.0      7.0   \n",
       "4   3297180  10037380  GW058949.1.1  691.43         UNK        7.0      9.0   \n",
       "\n",
       "   TopElev  BottomElev MajorLithCode  ...  Source LogType        Easting  \\\n",
       "0   682.63      680.43          SHLE  ...     UNK       1  720769.160247   \n",
       "1   691.43      690.53          TPSL  ...     UNK       1  720769.160247   \n",
       "2   690.53      688.13          CLAY  ...     UNK       1  720769.160247   \n",
       "3   686.23      684.13          SAND  ...     UNK       1  720769.160247   \n",
       "4   684.13      682.63          CLAY  ...     UNK       1  720769.160247   \n",
       "\n",
       "       Northing  Lithology_1  Lithology_2 Lithology_1_num Lithology_2_num  \\\n",
       "0  6.095597e+06        shale                          4.0             NaN   \n",
       "1  6.095597e+06      topsoil                          6.0             NaN   \n",
       "2  6.095597e+06         clay                          0.0             NaN   \n",
       "3  6.095597e+06         sand         clay             1.0             0.0   \n",
       "4  6.095597e+06         clay                          0.0             NaN   \n",
       "\n",
       "   Depth From (AHD)  Depth To (AHD)  \n",
       "0         682.26709       680.26709  \n",
       "1         691.26709       690.26709  \n",
       "2         690.26709       688.26709  \n",
       "3         686.26709       684.26709  \n",
       "4         684.26709       682.26709  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "# to be reused in experimental notebooks:\n",
    "classified_logs_filename = os.path.join(data_path, 'Bungendore','classified_logs.pkl')\n",
    "df.to_pickle(classified_logs_filename)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## Interpolate over a regular grid\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-06T00:50:58.799366Z",
     "start_time": "2018-02-06T00:50:55.503766Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(706394.2929625576, 6089546.817226024, 729010.1694019751, 6109176.439475171)"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# max/min bounds\n",
    "shp_bbox = get_bbox(bore_locations)\n",
    "shp_bbox"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BoundingBox(left=698072.3317566791, bottom=6081052.435896559, right=743160.9813157511, top=6117034.783610981)"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raster_bbox = bungendore_raster.bounds\n",
    "raster_bbox"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_min = max(shp_bbox[0], raster_bbox[0])\n",
    "x_max = min(shp_bbox[2], raster_bbox[2])\n",
    "y_min = max(shp_bbox[1], raster_bbox[1])\n",
    "y_max = min(shp_bbox[3], raster_bbox[3])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "grid_res = 150\n",
    "m = create_meshgrid_cartesian(x_min, x_max, y_min, y_max, grid_res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(151, 131), (151, 131)]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[x.shape for x in m]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-06T00:50:58.799366Z",
     "start_time": "2018-02-06T00:50:55.503766Z"
    }
   },
   "outputs": [],
   "source": [
    "dem_array = surface_array(bungendore_raster, x_min, y_min, x_max, y_max, grid_res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-06T00:50:58.799366Z",
     "start_time": "2018-02-06T00:50:55.503766Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(151, 131)"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dem_array.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f4cb3b4dd30>"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(to_carto(dem_array), cmap='terrain')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-06T00:50:58.799366Z",
     "start_time": "2018-02-06T00:50:55.503766Z"
    }
   },
   "outputs": [],
   "source": [
    "dem_array_data = {'bounds': (x_min, x_max, y_min, y_max), 'grid_res': grid_res, 'mesh_xy': m, 'dem_array': dem_array}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "fp = os.path.join(bungendore_datadir, 'dem_array_data.pkl')\n",
    "if not os.path.exists(fp):\n",
    "    with open(fp, 'wb') as handle:\n",
    "        pickle.dump(dem_array_data, handle, protocol=pickle.HIGHEST_PROTOCOL)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>BoreID</th>\n",
       "      <th>HydroCode</th>\n",
       "      <th>RefElev</th>\n",
       "      <th>RefElevDesc</th>\n",
       "      <th>FromDepth</th>\n",
       "      <th>ToDepth</th>\n",
       "      <th>TopElev</th>\n",
       "      <th>BottomElev</th>\n",
       "      <th>MajorLithCode</th>\n",
       "      <th>...</th>\n",
       "      <th>Source</th>\n",
       "      <th>LogType</th>\n",
       "      <th>Easting</th>\n",
       "      <th>Northing</th>\n",
       "      <th>Lithology_1</th>\n",
       "      <th>Lithology_2</th>\n",
       "      <th>Lithology_1_num</th>\n",
       "      <th>Lithology_2_num</th>\n",
       "      <th>Depth From (AHD)</th>\n",
       "      <th>Depth To (AHD)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3297041</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>9.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>682.63</td>\n",
       "      <td>680.43</td>\n",
       "      <td>SHLE</td>\n",
       "      <td>...</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>shale</td>\n",
       "      <td></td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>682.267090</td>\n",
       "      <td>680.267090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3297109</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>691.43</td>\n",
       "      <td>690.53</td>\n",
       "      <td>TPSL</td>\n",
       "      <td>...</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>topsoil</td>\n",
       "      <td></td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>691.267090</td>\n",
       "      <td>690.267090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3297126</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>690.53</td>\n",
       "      <td>688.13</td>\n",
       "      <td>CLAY</td>\n",
       "      <td>...</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>clay</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>690.267090</td>\n",
       "      <td>688.267090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3297127</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>686.23</td>\n",
       "      <td>684.13</td>\n",
       "      <td>SAND</td>\n",
       "      <td>...</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>sand</td>\n",
       "      <td>clay</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>686.267090</td>\n",
       "      <td>684.267090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3297180</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>684.13</td>\n",
       "      <td>682.63</td>\n",
       "      <td>CLAY</td>\n",
       "      <td>...</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>clay</td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>684.267090</td>\n",
       "      <td>682.267090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3302117</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>11.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>680.43</td>\n",
       "      <td>652.73</td>\n",
       "      <td>CLAY</td>\n",
       "      <td>...</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>clay</td>\n",
       "      <td>shale</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>680.267090</td>\n",
       "      <td>652.267090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>3302166</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>39.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>652.73</td>\n",
       "      <td>635.43</td>\n",
       "      <td>SAND</td>\n",
       "      <td>...</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>sand</td>\n",
       "      <td></td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>652.267090</td>\n",
       "      <td>635.267090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3302167</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>56.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>635.43</td>\n",
       "      <td>634.43</td>\n",
       "      <td>CLAY</td>\n",
       "      <td>...</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>clay</td>\n",
       "      <td>shale</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>635.267090</td>\n",
       "      <td>634.267090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>3302256</td>\n",
       "      <td>10037380</td>\n",
       "      <td>GW058949.1.1</td>\n",
       "      <td>691.43</td>\n",
       "      <td>UNK</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>688.13</td>\n",
       "      <td>686.23</td>\n",
       "      <td>SHLE</td>\n",
       "      <td>...</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>720769.160247</td>\n",
       "      <td>6.095597e+06</td>\n",
       "      <td>shale</td>\n",
       "      <td></td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>688.267090</td>\n",
       "      <td>686.267090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>3297085</td>\n",
       "      <td>10027294</td>\n",
       "      <td>GW058023.1.1</td>\n",
       "      <td>804.98</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>803.98</td>\n",
       "      <td>786.98</td>\n",
       "      <td>SLTE</td>\n",
       "      <td>...</td>\n",
       "      <td>UNK</td>\n",
       "      <td>1</td>\n",
       "      <td>716921.554268</td>\n",
       "      <td>6.100716e+06</td>\n",
       "      <td>slate</td>\n",
       "      <td></td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>807.349976</td>\n",
       "      <td>790.349976</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   OBJECTID    BoreID     HydroCode RefElev RefElevDesc  FromDepth  ToDepth  \\\n",
       "0   3297041  10037380  GW058949.1.1  691.43         UNK        9.0     11.0   \n",
       "1   3297109  10037380  GW058949.1.1  691.43         UNK        0.0      1.0   \n",
       "2   3297126  10037380  GW058949.1.1  691.43         UNK        1.0      3.0   \n",
       "3   3297127  10037380  GW058949.1.1  691.43         UNK        5.0      7.0   \n",
       "4   3297180  10037380  GW058949.1.1  691.43         UNK        7.0      9.0   \n",
       "5   3302117  10037380  GW058949.1.1  691.43         UNK       11.0     39.0   \n",
       "6   3302166  10037380  GW058949.1.1  691.43         UNK       39.0     56.0   \n",
       "7   3302167  10037380  GW058949.1.1  691.43         UNK       56.0     57.0   \n",
       "8   3302256  10037380  GW058949.1.1  691.43         UNK        3.0      5.0   \n",
       "9   3297085  10027294  GW058023.1.1  804.98         UNK        1.0     18.0   \n",
       "\n",
       "   TopElev  BottomElev MajorLithCode  ...  Source LogType        Easting  \\\n",
       "0   682.63      680.43          SHLE  ...     UNK       1  720769.160247   \n",
       "1   691.43      690.53          TPSL  ...     UNK       1  720769.160247   \n",
       "2   690.53      688.13          CLAY  ...     UNK       1  720769.160247   \n",
       "3   686.23      684.13          SAND  ...     UNK       1  720769.160247   \n",
       "4   684.13      682.63          CLAY  ...     UNK       1  720769.160247   \n",
       "5   680.43      652.73          CLAY  ...     UNK       1  720769.160247   \n",
       "6   652.73      635.43          SAND  ...     UNK       1  720769.160247   \n",
       "7   635.43      634.43          CLAY  ...     UNK       1  720769.160247   \n",
       "8   688.13      686.23          SHLE  ...     UNK       1  720769.160247   \n",
       "9   803.98      786.98          SLTE  ...     UNK       1  716921.554268   \n",
       "\n",
       "       Northing  Lithology_1  Lithology_2 Lithology_1_num Lithology_2_num  \\\n",
       "0  6.095597e+06        shale                          4.0             NaN   \n",
       "1  6.095597e+06      topsoil                          6.0             NaN   \n",
       "2  6.095597e+06         clay                          0.0             NaN   \n",
       "3  6.095597e+06         sand         clay             1.0             0.0   \n",
       "4  6.095597e+06         clay                          0.0             NaN   \n",
       "5  6.095597e+06         clay        shale             0.0             4.0   \n",
       "6  6.095597e+06         sand                          1.0             NaN   \n",
       "7  6.095597e+06         clay        shale             0.0             4.0   \n",
       "8  6.095597e+06        shale                          4.0             NaN   \n",
       "9  6.100716e+06        slate                          9.0             NaN   \n",
       "\n",
       "   Depth From (AHD)  Depth To (AHD)  \n",
       "0        682.267090      680.267090  \n",
       "1        691.267090      690.267090  \n",
       "2        690.267090      688.267090  \n",
       "3        686.267090      684.267090  \n",
       "4        684.267090      682.267090  \n",
       "5        680.267090      652.267090  \n",
       "6        652.267090      635.267090  \n",
       "7        635.267090      634.267090  \n",
       "8        688.267090      686.267090  \n",
       "9        807.349976      790.349976  \n",
       "\n",
       "[10 rows x 22 columns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We need to define min and max heights on the Z axis for which we interoplate. We use the KNN algorithm with 10 neighbours. We should use a domain such that there are enough points for each height. Let's find visually heights with at least 10 records"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_bins=100\n",
    "p = df.hist(column=[DEPTH_FROM_AHD_COL,DEPTH_TO_AHD_COL], sharex=True, sharey=True, bins=n_bins, figsize=(15,5))\n",
    "for axes in p:\n",
    "    axes[0].set_yscale(\"log\", nonposy='clip')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_neighbours=10\n",
    "ahd_min=620\n",
    "ahd_max=830\n",
    "\n",
    "z_ahd_coords = np.arange(ahd_min,ahd_max,1)\n",
    "dim_x,dim_y = m[0].shape\n",
    "dim_z = len(z_ahd_coords)\n",
    "dims = (dim_x,dim_y,dim_z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "lithology_3d_array=np.empty(dims)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "gi = GridInterpolation(easting_col=EASTING_COL, northing_col=NORTHING_COL)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "gi.interpolate_volume(lithology_3d_array, df, PRIMARY_LITHO_NUM_COL, z_ahd_coords, n_neighbours, m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(180, 10)"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Burn DEM into grid\n",
    "z_index_for_ahd = z_index_for_ahd_functor(b=-ahd_min)\n",
    "# check that we get the expected indexes for an AHD height\n",
    "z_index_for_ahd(800), z_index_for_ahd(+630)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((151, 131), (151, 131), (151, 131, 210))"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dem_array.shape, m[0].shape, lithology_3d_array.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "burn_volume(lithology_3d_array, dem_array, z_index_for_ahd, below=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2D visualisations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "#lithologies =           ['clay',  'sand',      'gravel',    'granite', 'shale',  'silt',           'topsoil',      'loam',     'soil',    'slate',      'sandstone']\n",
    "lithology_color_names = ['olive', 'yellow', 'lightgrey',      'dimgray', 'teal',  'cornsilk',     'saddlebrown', 'rosybrown', 'chocolate', 'lightslategrey', 'gold']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "lithology_cmap = discrete_classes_colormap(lithology_color_names) # Later for exporting to RGB geotiffs??\n",
    "litho_legend_display_info = [(lithology_cmap[i], lithologies[i], lithology_color_names[i]) for i in range(len(lithologies))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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QuAX4N+CXwDE9qvoi3aO57egWy1zI8nWYxmv3e8Bz6Ea8Hg18Fbg9yQ10b/NdRve9t2Xqye+SpJUw5yaZ7rrrrn3eiJImVVV3JXkG8Drg5cCOdG/KfRn4J+DyoewLV6L+Dyb5Dd0K5Y+m+1u6HPg88M+Mv7jl2DpuTfJl4Pnt0heqatIgrqrOTLIT3ejTQcBDgU3bd/gZ3XYyn28rpEuSZli6RY6ltUuSp9ItJXBVVe0wy92RJK0hfFSntdUbW/rVWe2FJGmNYuCkkZRknSSnJTkwySZD13dJchrdfnZLGWcvO0mSJuKjOo2k9rbZ0qFLt9DNQxpsRXIP8OqqOmF1902StOYycNJIaitx/yXdyNJuwFbAesAfgAuA46rqB7PXQ0nSmsjASZIkqSfnOEmSJPVk4CRJktSTgZMkSVJPBk6SJEk9GThJkiT1NOf2qnvNa17ja34j4vjjj3ffwRmW5Dxgb+DlVXXS7PZGktY+cy5wkrTikmwKHAlQVUfPbm8kaXT5qE5as1wN/AxYNOb6psBR7ZAkrSKOOElrkKp66Wz3QZLWZo44SZIk9WTgpJGVZJ0kRya5NMmSJNcnOSPJE9v9ascOQ2VOateOTrJ+kre08re265u2fAuSHJrk1CSXJVnY2vhlkhOS7DhJv/6n3SQPSvLRJL9NcmeSK5Icm2TjCcqe18oePnwNuGKc+gfH0ePUs0OSDyX5WZLF7ft9P8nfJdloRX9rSVpb+KhOIynJesB/AE9vl+6m++/7M4ADkrxgiirm020G/FhgKbB4zP3DgQ8Nnd9K9w+Rh7TjRUmeXVXnTtLGI4GPA5sPld8BeAOwd5InVNXSKfoJcBNwA3C/dn7tmPu3DZ8kOQQ4le47AiwB5gG7t+PFSZ5WVWPrkaS1niNOGlVvpQualtG9bbZxVW1GF5icBXxsivJ/BewEvABYUFWbtrK3t/s30gVOTwA2raqN6QKRh9EFJRsBn5pi9OYk4IfAbq38AuDPgDuBPYBX9vmiVXUIsOfQ+TZjjmMH95LsCXwGWA94D7B96+uGwF7Ad4DdgJP7tC1JaxsDJ42cJAvoRm0A3l5VH6iqJQBVdRVwCHDVFNUsAA6rqs9W1V2DsoMRoKr6dFW9rqouqqpF7VpV1eXAS4BzgS2B503SxjXAQVV1WSt/Z1V9HPhouz9Z2ZX1frqg6Y1V9aaqurr1e1lVfYcu2PwdsH+SPVZB+5K0RjNw0ig6gG4U5Q7gg2NvtuDnfVPUcWlVnbMyjVdVAV9pp0+cJOv7qurOca6f3tJdV6b9iSR5SOvPEuBfxstTVTcDZ7bTp81k+5I0CpzjpFH06Jb+sKpumyDPhVPUcdFUjSTZDjgC2I9uXtN9ufc/Ru4/SRXfneD6NS3dbKo+rKAntHQecEUy4cLuC1r6wBluX5LWeAZOGkWDSdK/nyTP76ao4/rJbibZGziD5UEGdItS3tE+bwBsTDfyNZFbJ7g+qGOm/z63bek6wNY98m84w+1L0hrPR3UaRX32yJtqT8RlE1bevbF3Cl3QdC7wZGCDqtp0MCEb+JsV6MvqMvh7v7iq0uM4fDY7K0lzkSNOGkWD0aJtJ8kz2SO0qTwe2I5uGYCDq2rsUgXQb0RndRssL7BjknWr6u5Z7Y0krYEccdIourilj2pv2I3nSdOof7uW/nyCoAm6eU+r0z2DD5l48tJg3tYCYP9V3iNJGkEGThpF59CttzSfbj2m/yXJusBfT6P+wQa7OyaZP/Zmkv2BfadR/8q4ZejzpuNlaEslfLudvmeyNaaSbJBk/RnsnySNBAMnjZyqupVuvSKAdyY5IskGAEkeBJwGPHgaTXyTbiXxLYCTk2zb6t4gySuAL9AtkLnaVNVClk94f/kkWY+gW2BzV+DCJPu1QJIk90myS5K3Ar9i8kedkrRWMnDSqHoH3cjTunRrOS1KchPdwpcHAa8YyjveWkoTakHKm9vpocDvkiykG/X5N+CXwDHT6v3KGayG/t4ktyW5sh1HDjJU1feA59CNmj0a+Cpwe5Ib6N7mu4zut9uWqSfQS9JaZ85NDj/++OPn0ltIWkNV1V1JngG8jm4EZke6N+W+DPwTcPlQ9oUrUf8Hk/yGboXyR9P9LV0OfB74Z+CwaX2BlfMPdI8oXww8lG47FRjz6K6qzkyyE93o00Et76Z0v8PP6Lak+XxbZV2SNCTdIsfS2iXJU+mWEriqqnaY5e5IktYQPqrT2uqNLf3qrPZCkrRGMXDSSEqyTpLTkhyYZJOh67skOY1uP7uljLOXnSRJE/FRnUZSe1Ns6dClW+jmIQ22EbkHeHVVnbC6+yZJWnMZOGkktUUg/5JuZGk3YCtgPeAPwAXAcVX1g9nroSRpTWTgJEmS1JNznCRJknoycJIkSerJwEmSJKknAydJkqSeDJwkSZJ6mnN71eWYY3zNb0TUUUetEfsOJjkcOBE4v6r2GfV2JUkrzxEnSZKkngycJEmSejJwkiRJ6snASZIkqScDJ42kJPOSvD7Jt5IsTLI0ybVJLknykSSPn6Tss5J8o5W7Lcm3k7xwkvy7JnlbkguTXJ3kziQ3JjkvyZ8nWWca32PXJB9PckWSO1qfvpnkL5Ost7L1SpJWzpx7q06ariTrAucAe7dLBSwCtqDb7PcR7fNF45R9G/APwD3ArcBGwOOATyXZuqqOG6fJ81p9AMuA24DNW/t7A89JcnBV3b2C3+O1wAdY/g+c24EFwBPacViSZ1TV4hWpV5K08hxx0ih6EV3Ashh4CbBhVW0GrA9sD7wWuGScco8EjgLeBmxRVZsC2wCntfvvSrL5OOUuAF7Z6p7fyi1obf8BOAj46xX5AkkOBj4ELAH+Hti6qhYAGwD7Az8D9gHevyL1SpKmx8BJo2ivlp5cVadU1R0AVbWsqq6uqo9U1bvGKbcpcFRVvbOqFrYy19IFQNcD84Fnji1UVYdU1cda3Xe3a7dX1SnA81u21/TtfHu094F2+pKqeldVXdfqXVpVXwWeTjcC9Yok2/atW5I0PQZOGkW3tHRFA4o7gHs9imuB19ntdNcVqbCqLgQWAjskuX/PYvvQjV5dWVVfnKDeK4Bv0z1u32dF+iRJWnkGThpFZ7b04CRfSnJIki0mLdH5SVXdPsG9a1q62Xg3kzwvyeltcviSJDU46EayAPoGTk8Y5E/yh4kO4Ikt3wN71itJmiYnh2vkVNX5Sd4OvB14VjtIcjnwFeBfq+oX4xS9dZJq72jp/3qTrU1E/xzwnKHLdwI30E0UB9iS7h8pG/X8CoORsnnA1j3yb9izXknSNDnipJFUVe8AdgLeTPeY7RZgZ+ANwE+SvHSGmnolXdC0GHg98MCqml9VW1bVNlW1DfC7lrfv3n2Dv8svVlV6HEfP0HeRJE3BwEkjq6quqKp3V9WBdMsD7Ev3Bty6wPFJtpqBZg5t6Tuq6oNV9dvhm22i9/1WsM5rW/rw6XZOkjSzDJy0Vmhv1J1H91bcUrrHZnvMQNXbtfTiCe4/ke5tvBUxWF/qj5PsslK9kiStEgZOGjlJ5k1y+y6Wzz1afwaaW9TS3cbpx7rAO1eizq8BV7fP759s5fEk405WlyStGgZOGkUnJzkxyQFJ7ju4mGQH4BN0I0BLgAtnoK2vtvRtSQ4eBDlJdga+DDyWbr2l3qpqKXAE3YrnTwPOSfK4JGl1r5vkMUneDfx6Br6DJKkn36rTKJoPHAYcDlSSRXRvqA3ePlsGvKqqbpiBto6lW+TyIcDpwNIkS4CNWzt/DhxN/zfqAKiqLyX5M+BfgKfQrdl0R5Lb6ZY3WOn97yRJK2/OBU511FF93zySJvIm4Jt0AceOdK/3rwP8im5y+HFVdelMNFRVNyXZi25/u2fRLR+wBPg6cGxVfTPJ0StZ94lJvkH3tt7T6BbF3AS4Efgx3dIKp01cgyRppqWqZrsPkiRJawTnOEmSJPVk4CRJktSTgZMkSVJPBk6SJEk9GThJkiT1ZOAkSZLUk4GTJElSTwZOkiRJPRk4SZIk9WTgJEmS1NOc26uOO3/lHjCjYv2HrBH7DibZB/gGcFVV7TDm3knAy4Bjquro1d03SdLcMvcCJ2kNMbR573FVtXA2+yJJWj0MnCRYDPwMuGYFyx3V0pMAAydJWgsYOGmtV1X/Dew82/2QJM19Tg6XJEnqycBJIynJvCSvT/KtJAuTLE1ybZJLknwkyeOH8u6TpJJc2bPuk5IMv8RwRSs/OE6a4a8jSZojfFSnkZNkXeAcYO92qYBFwBbAVsAj2ueLVrKJRcC1wNbt/AZg2Zj7kqQRZOCkUfQiuqBpMfAq4LSquiPJOsADgGcBG69s5VX1euD1Q6NOe1bVldPrsiRpTWDgpFG0V0tPrqpTBherahlwNfCRWemVJGmN5xwnjaJbWrrtrPZCkjRyDJw0is5s6cFJvpTkkCRbzGqPJEkjwcBJI6eqzgfeDtxNN5/pC8ANSX6a5NgkO85qByVJaywDJ42kqnoHsBPwZuBsusd3OwNvAH6S5KWz2D1J0hrKwEkjq6quqKp3V9WBwObAvsAFdC9FHJ9kq1ntoCRpjWPgpLVCVS2rqvOAZwJLgY2APaZbbUszzXokSWsIAyeNnCTzJrl9F8sXq1x/mk0N3t7bdJr1SJLWEAZOGkUnJzkxyQFJ7ju4mGQH4BPAfGAJcOE02/lxS1/aFteUJI04AyeNovnA4cBZwKIkNye5HbgCOIxuxOlVVXXDNNv5WEuPBG5LclWSK5McO816JUlz1NxbOXz9hzhfRNP1JuCbwFOAHekWwlwH+BXd5PDjqurS6TZSVSe2kaZXAg8HHkg33+l+061bkjQ3paqmziVJkiQf1UmSJPVl4CRJktSTgZMkSVJPBk6SJEk9GThJkiT1ZOAkSZLUk4GTJElSTwZOkiRJPRk4SZIk9WTgJEmS1NOc26vu2P3v5x4wI+Jvz7nBfQfngCSDv6kHV9WVQ9cPB04Ezq+qfVZ/zyRpzTPnAidpprTAYAfg9Kr64ez2RpI0CgycNMoOB/YGrgTW5sDpZy1dOqu9kKQRYOAkjbiq2nm2+yBJo8LJ4ZIkST0ZOGnkJDm8TYjeu106MUkNHVeOyb91kvcmuTzJ4iSLkvx3kjckWX+CNk5qdR2dZH6SY1r5JUmuS/LpJDtN0sdHJjk5yZVJ7kxya5JfJzkryZFJNpyg3CEtz/Wt3G+TnJpk90naGnzvHab46SRJU/BRnUbREuBaYHNgPeCWdm3g+sGHJI8Fzmx5AW4F5gF7tuMlSfavqusmaGt94BvAXsBdwB3AlsALgP+T5OlVdcFwgSQHAae3vgHcCdwDPLgdBwBnAZcPlbkP3RtwL22XlrW+PgB4EfCCJK+tqv83xW8jSZoGR5w0cqrqs1W1DfCtdun1VbXN0LEnQJLN6AKYzYEfAY+tqo2BBcChwM3AI4FTJ2nu1cAjgJcBC6pqE+DRwA+ADYHPtXaGfYguaDoD+OOqmt/KbQI8GfgoXQA27P/SBU0FvA3YrKo2A7YDPk/3t/zhJE/u+ztJklacgZPWZq8FtgUWAvtX1XcBqmpZVZ1GN2oEsF+Sp0xQxybAX1TVyVW1tJX/Id2o0Y3A1sBfDTIn2Qr4o3b651X188G9qrqlqi6sqr8Ys97SRsCb2+l7quqdVXVrK3MN8ELgv+j+nt+5cj+FJKkPAyetzZ7X0o9V1R/G3qyqc4CL2unzJ6jjKuBT45S9AfjXMe1A93jtnvZ525793B/YmO5R4P83TlvLgHe00ycl2aZnvZKkFWTgpLVSknnAru30G5Nk/XpLJ5p8fX5VTbTa/fkt3bW1R1UtGbp+dpK3JnlUknUm6cOg7Uuq6uYJ8lwA3D1FXyVJ02TgpLXV5iz/7/81k+T7bUu3nOD+ZGUH99YBhuc5/TnwU2ArupGii4GFSb6S5E+TjH1pY9D2hG1V1R10jwYn66skaZoMnKTuzbhVYdy9+qrq13QTyp8DnEAXRC0ADgI+CXwnyYLV2E9JUk8GTlpb3cTyuUbbT5Jvu5ZeP8H9+09SdjCHaRndG3r/o6rurqrTq+pVVfXwlveNdG/T7Q4cNZR90PaE/UwyH9hiir5KkqbJwEmjbBAY3Wvkp6ruAi5rp/tOUsfgbW0/TUoAABcQSURBVLofTHB/7wmuD9+7rLU3oar6Q1UdCxw3Tr2DtndM8oAJqngyy9dlm6ivkqRpMnDSKLulpZtOcP+0lh6e5F5vuCXZH3h8O/3cBHXskOSF45TdHPiLdvr5oevrJRn3EV4zWKhz+LHcOXTfZT26Uamxba1Dt7YTwIXjvSEoSZoZBk4aZT9u6SFJNhnn/oeB3wMbAGcl2QO6QCTJc4HPtHznVtXXxykPsAj46PCk7iSPAM6mm6R9HXD8UP5dgMvatio7DYKoFlA9F/iblu/sQYGquh34p3b6uiRvGcyBaiNQnwb+hG6E7a1T/iqSpJVm4KRR9km6tY/+BLghyTVtb7j/Amiv9j+bbv7RI4DvJrkFuI1uNGoz4FLgxZO08f/oVh3/JHBbkkXAJcAewGLg0HGWEHg48H7gZ8CSJDfSzW06jW5Bze9x74UsjwVOpnvs+E66t/BuAn5Dt8r5PcARY7d3kSTNrDm3V93fnnPDZI8xpN6q6vIkT6NbdXtPYBvG/GOhqv47ycPptjR5BvAguvWQvgd8Fvhwe9V/InfSzZF6M91K4w+im5z9NeDoqvrZmPw/pVsQcz/gcXSTy7egexR3WWvzhLFzotoily9L8iW6R4CPoVsU8/d060K9t6q+3++XkSStrEy8dp+kiSQ5iW5/umOq6ujZ7Y0kaXXxUZ0kSVJPBk6SJEk9GThJkiT1ZOAkSZLUk5PDJUmSenLESZIkqScDJ0mSpJ4MnCRJknoycJIkSerJwEmSJKmnObdX3deOO87X/EbEU488ctb2HUxyHrA38PKqOmm2+iFJGi2OOEmSJPVk4CRJktSTgZMkSVJPBk6SJEk9GThprZNk4yRHJ7kkyW3tuDTJMUk2maDMOkn2TfKBJN9Pcm2Su5L8LskXkzxlkvbOS1JJDm9t/39JfpVkSZJfJ/mHJPOH8j81ydlJbkhye5ILkjxpVfwWkqQVM+feqpNWpSQPBc4Ftm+XFrd0t3YcnmS/qvrFmKIPA74+dH4ncBewLfBs4NlJ3lJV/zRJ85sB3wF2Bm4H1gEeDLwNeBTwf5K8BvgwUMBtwIbAk4Bzkzylqr654t9akjRTHHHSWiPJPOALdEHTb4D9gQXt2A+4GngQ8MUk648pfhfweeBZwDbABlW1ANiaLvBZBrwzyeMm6cJRQIAntbILgFcCdwPPSvI24Djg3cAWVbUJsANwETAPeP90vr8kafoMnLQ2OQx4BF2gclBVfbWW+xpwELAU2AV48XDBqvp5VT2/qs6oqmurqtr166rqncAxdEHRX07S/kbAM6vqv1rZu6rqY8DJ7f4/AKdU1d9X1cKW5yrghXQjUHsmedBM/BCSpJVj4KS1yfNaenpVXTb2ZlX9GDitnT5/Bev+ckufOEmez1fVL8e5fu7Q53eN06+rgEG5XVewX5KkGWTgpLXJ7i39xiR5BvOYdh97I8kGSf66Tfa+LsnSNum7gItbtvtPUvePJrh+XUvvYHmANNa1Ld1skvolSauYk8O1NtmypddMkue3Ld0iSQaP5JJsC5wH7DSU93bgZuAeuone96N7HDeR309wfVlL/+cR4CR51pukfknSKuaIk9ZGYyd+93EcXdD0a+C5wOZVtaCqtqqqbYC9ZrKDkqS5yREnrU2uB7Zj+VIE49mupTcOjTbNAw5u119cVd8ep9zWM9ZLSdKc5YiT1iY/aOm+k+QZLGT5g6Fr92P5KNXFjG+/afRLkrSGMHDS2mTwxtzTkzx67M0ku7D8zbvPDd26hW45AOgWyRxbblvgiBnspyRpjjJw0trks8Cl7fPpSfZLEui2OQH+k27y9Y+BUweFquo2YPB47uNJHtXK3KeVO59uDSdJ0ogzcNJao6ruopvYfRXdCuFfBW5LcjvdWkoPols9/JCqunNM8b8GltCNOF2c5Da6LVHOBbYA/my1fAlJ0qyac5PDn3rkkf7LXatMVf0yySOBvwEOAf6o3boM+CLw3qpaNE657yR5PHA0sDfdsgO/B84C/pFuOQJJ0ojLxMvGSJIkaZiP6iRJknoycJIkSerJwEmSJKknAydJkqSeDJwkSZJ6MnCSJEnqycBJkiSpJwMnSZKkngycJEmSejJwkiRJ6mnO7VX3o9ds7x4wI2K3468a+X0HkxwNHAV8oqoOH3PvSmB7YN+qOm91902SNPMccZIkSerJwEmanhuAnwG/n+2OSJJWvTn3qE5ak1TVh4EPz3Y/JEmrhyNOkiRJPRk4aSQlmZfk9Um+lWRhkqVJrk1ySZKPJHn8OGW2TvLeJJcnWZxkUZL/TvKGJOtP0M7RSSrJSav8S0mSZp2P6jRykqwLnAPs3S4VsAjYAtgKeET7fNFQmccCZwKbt0u3AvOAPdvxkiT7V9V1q+M7SJLmJkecNIpeRBc0LQZeAmxYVZsB69MtD/Ba4JJB5iSbAafTBU0/Ah5bVRsDC4BDgZuBRwKnrsbvIEmagxxx0ijaq6UnV9Upg4tVtQy4GvjImPyvBbYFFgL7V9UfhvKfluQW4GxgvyRPqaqvr+ovIEmamxxx0ii6paXb9sz/vJZ+bBA0Dauqc1j+WO/50+ybJGkNZuCkUXRmSw9O8qUkhyTZYryMSeYBu7bTb0xS52CUafcZ6qMkaQ1k4KSRU1XnA28H7gaeBXwBuCHJT5Mcm2THoeybs/zv4JpJqv1tS7ec6f5KktYcBk4aSVX1DmAn4M1085NuAXYG3gD8JMlLxyk27pIDkiQNGDhpZFXVFVX17qo6kG5kaV/gArqXIo5PshVwE3BPK7L9JNVt19LrV1V/JUlzn4GT1gpVtayqzgOeCSwFNgL2qKq7gMtatn0nqeIpLf3BKuukJGnOM3DSyGkTvidyF7CsfR48mjutpYcnudebeEn2BwYrjX9uRjopSVojGThpFJ2c5MQkByS57+Bikh2ATwDzgSXAhe3Wh4HfAxsAZyXZo+VfJ8lzgc+0fOe6hpMkrd1cAFOjaD5wGHA4UEkW0W2fsmG7vwx4VVXdAFBVNyd5NnAW3XYs301yK7BeqwvgUuDFq+0bSJLmpDkXOO12/FWZ7T5ojfcm4Jt085J2pFsIcx3gV3STw4+rqkuHC1TVfyd5OPB/gWcAD6JbzuB7wGeBD1fVHavtG0iS5qRU1Wz3QZIkaY3gHCdJkqSeDJwkSZJ6MnCSJEnqycBJkiSpJwMnSZKkngycJEmSejJwkiRJ6snASZIkqScDJ0mSpJ4MnCRJknqac3vVvek9J7gHzIh499/9xRqx72CSfYBvAFdV1Q6z2xtJ0lw25wInaVQkORLYFDipqq6c5e5IkmaAgZO06hwJbA+cB1w5qz2RJM0I5zhJkiT1ZOAkSZLUk4GTRlKSeUlen+RbSRYmWZrk2iSXJPlIksf3rGdBkkOTnJrkslbXkiS/THJCkh3HKXN0kqJ7TAfwjSQ1dJw3QTt/n+S7SRYluSPJL5J8MMkDp/VjSJJmjHOcNHKSrAucA+zdLhWwCNgC2Ap4RPt8UY/qDgc+NHR+K90/OB7SjhcleXZVnTuU5zbgWmDLlvdm4K6h+zeN6e/DgDNZHmjdDdwJPBQ4AvjTJM+qqm/26K8kaRVyxEmj6EV0QdNi4CXAhlW1GbA+XXDyWuCSnnXdSBc4PQHYtKo2BuYDDwNOBTYCPpVko0GBqjq2qrYBftMuHVJV2wwdhwzyJtkE+M/Wr9OB3YENqmoB8GDgk8BmwBeSbLriP4UkaSY54qRRtFdLT66qUwYXq2oZcDXwkb4VVdWngU+PuVbA5UleAmwN7Ac8D/jESvT1jcAOwH/QBVj/s45ZW8LgpUm2AA4C/hw4diXakCTNEEecNIpuaem2q7KRFuR8pZ0+cSWreVlL3z8cNI0xCNyetpJtSJJmiCNOGkVnAn8HHJzkS8BJwPlVdePKVJZkO7q5RvvRzWu6L/f+R8f9V6LeBwLbtdPPJ7lngqzzWuokcUmaZQZOGjlVdX6StwNvB57VDpJcTjdC9K9V9Ys+dSXZGzgDWDB0eRFwR/u8AbAx3VynFTU8IrZlj/wbrkQbkqQZ5KM6jaSqegewE/Bm4Gy6x3c7A28AfpLkpVPVkWQ94BS6oOlc4Ml0E7c3HUz0Bv5mkH0lujn897dJVWWKY4eVaEOSNIMMnDSyquqKqnp3VR0IbA7sC1xAN9J6fJKtpqji8XSP0m4CDq6qC6vqjjF5tp5GF68d+vzwadQjSVpNDJy0VqiqZVV1HvBMYCndo7U9pig2mH/086paPEGe/SYpP5izNO5oVFVdwfLg6ZDx8kiS5hYDJ42cJPMmuX0XsKx9Xn+Kqha1dMck88dpZ3+6UayJDN7um2z9pZNa+pq2EOa40tlkknokSauBgZNG0clJTkxyQJL7Di4m2YFuraX5wBLgwinq+SbdIppbtDq3bfVskOQVwBfoFsicyI9b+sLxAq/m3cCv6UbAzk/ysiT/MxE9yQOTvBL4PvCcKforSVrFDJw0iubTbZVyFrAoyc1JbgeuAA6jG3F6VVXdMFklVbWQbnI5wKHA75IspBtJ+jfgl8Axk1Txb0NlFyX5TZIrk3xmTBsHAD+le7PupJb3xiSL6RbsPAF4NN3WMZKkWZSJ19yT1kxJdqZbguApwI50r/2vA/yWbnL4cVV16VD+fYBvAFeN9+ZakufQvY03CF6uAD4P/DNdIHYi3TpR+4xT9tnAkcCj6JYtyHh5k6wPvIIuyNqN7vHektbW+cBpwH9V1URrPUmSVgMDJ0mSpJ58VCdJktSTgZMkSVJPBk6SJEk9GThJkiT1ZOAkSZLUk4GTJElSTwZOkiRJPRk4SZIk9WTgJEmS1JOBkyRJUk/rznYH7uXyuAfMqNi5MttdWNMlOQl4GXBMVR09u72RJM29wEnSKtE2HH4UcF5VnTfL3ZGkNZKBk7T2eDbd6BXAebPYD0laYznHSZIkqScDJ0mSpJ4MnDSSksxL8vok30qyMMnSJNcmuSTJR5I8fkz+xyV5V5JvJ7kmyV1JrktyVpLnTdLOSUkqydFJ1klyZGtjcZKbkpyRZI8p+vq4JF9u+W9L8sPW90n/PpM8OMn/S/LzJEtam1clOS/Jm5Pcr+XbJ0mx/DHdUa3P/3OMU/fG7Ttd0vp0W5JLkxyTZJMJ+nN0q++kdv6yJN9JcmuSW5J8I8nTpvhO85K8NsmF7fe4s32njyd52GRlJWl1cI6TRk6SdYFzgL3bpQIWAVsAWwGPaJ8vavkXAN8eqmIpcAewJXAAcECSE6rqVZM0uy5wBnBgK38nsBnwDOCpSZ5SVReN09cXAKcA67RLC4FdgOOAJwG3T/Add6ebp3TfoT7fDjyoHXsDFwNnAXcB1wKbAPNbvtsm+iJJHgqcC2zfLi1u6W7tODzJflX1i0nq+BjwZ8Cy1t7GwD7Ak5M8v6q+ME6ZbYEzgUe2S/cMfaeXAy9M8uKq+veJ2pWkVc0RJ42iF9EFDouBlwAbVtVmwPp0wcBrgUuG8t8D/CfwQuABwPyq2pgu8DmCLsj4iySHTtLmXwGPBQ4DFlTVfekCgMvogpUPjC2Q5CHAiXRB0znAQ1o/NwHeQDeZ++AJ2juWLmj6DrB7Vc1rZTcC9qQLvBYBVNW3qmob4LODslW1zfAx1Kd5wBfa7/QbYH9gQTv2A66mC2S+mGT9Cfp2MPBi4NXAxlW1CfBHwAV0/5vzoRbcDv8W6wH/0X6zC4AnAxu0/xy2Ad7bfsdPtt9NkmaFI04aRXu19OSqOmVwsaqW0f0f/0eGM1fVYrqRIcZcXwh8OMki4GTgNcDnJ2hzU+BJVfVfQ+UvTXI48D1gzyTbV9VVQ2X+ni4Y+BlwcFXdMdSf9yXZEHjHFN/x9VV18Zjv8r12rIzD6Ebk7gYOqqrLhu59LclBdCNZu9AFRx8fp45NgT+tqlOH+nVFG127EtgWeAJdgDTwMrqA77vA/lV151DZa4G/bb/Hq4G/pgt+JWm1c8RJo+iWlm47Q/V9uaV7JVlngjwXDgdNA1X1feC37XSXwfUkAQ5pp+8fBE1jHMfyx2RjzfR3HBjM5zp9TNAEQFX9GDitnT5/gjquBj41TtnfA//dTncdc3sw/+ojw0HTGIM6J50nJUmrkoGTRtGZLT04yZeSHJJki8kKJFk3yZ+1yeC/b5OSBxOnb27Z5tM9vhvPdyep/pqWDpf9I7qRGYDzxytUVbcB35+gzv9s6clJ3p1kr/a4a7p2b+k3Jsnz9TF5x/peVU20A8C9fov22O6x7fR9Sf4w3gF8seV54ORfQZJWHQMnjZyqOh94O93jpmfRzdm5IclPkxybZMfh/G1y+PnAx+gmg29DN6n5erpJ1dcOZd9ogmZvnaRLg9Gk4cBmy6HPv5uk7DUTXH8j8C26eU5/RzfR/ZYkX0/y6iQbTFLnZAb9mqhdWD6CtkUbORtrRX+LzYF5Q5+3nuC4X8uzst9NkqbNwEkjqareAewEvBk4m+7R1s50k65/kuSlQ9nfRjfn5ga6R0ZbV9WGVbVVmzj9gKG8q3v/vXHbq6obgT+he2z1Qbp5R/OAfYHjgcuSbDeNdiea+L0qDP/v0COrKlMdq7FvkvS/GDhpZFXVFVX17qo6kG4kY1+6CcnrAscn2aplHbwtd0RVnVxV142pautV0L3rhz7ff5J8E85hqs65VfX6qtqdbkTmVcBNdI8C3z+Nfm0/SZ5BQHbjJI/kVsSNdCN8AA+fgfokaZUxcNJaoaqWtY1tn0m35tFGwGBhykEgcPE4RaF7DX+m/ZpuzSboXr2/lyTDfZxSVd1cVSfQva0Hy9exGrhnUPUk1fygpftOkucpY/JOS1UtZflbgIdMlleSZpuBk0ZOW4toInexfHRj8DhqUUt3G6euBcBbZq53nTZSM1gE8sgJ1kR6HbDhOH26z9h1kMZY0tKxdQ7exNuUiQ3emHt6kkeP0/YuLH/z7nOT1LOiTmrpc5NMFrSRZKIJ+pK0yhk4aRSdnOTEJAckGaysTZIdgE/QvR23BLiw3fpqS9+XZO/BhOckewJfY/mk5Jn2LrrJ0g8DTk/y4NbuBkmOpFvDadE45TYGfpnkLUl2GyyR0AKqpwL/2PKdPabcj1t6YFulezyfBS5tn09Pst/Q7/FUurf51mt1nTp+FSvl3+hWb78PcEa6LWc2H9xMslWSFyY5D3j9DLYrSSvEBTA1iubTLeR4OFBtAct5LB+9WQa8qqpuaOdvpZtk/UC6bUzuSLKM7nHeEroVvMcGIdNWVb9K8nK6LVcOBH6dZCHdKt3rAv9Ot2r5S8cpvj3wznYsTXIr3Yrjg3Wmfg38zZgyXwTeTTdp/rdJrqPbGoaq2qGldyV5Lsu3XPkqsLjFToPf72rgkEnWW1phVbU0ycF03/mJdGtYvb/9HuvR/SYDky2VIEmr1NwLnHb2jRlN25uAb9LNxdmRboL1OsCv6CaHH1dVg1EVqurXSR4L/APdFiOb0U1YPh14V1X9ePy37qevqj6T5Aq6N/ueSBfg/YRuRe4PMf7K3LfQzdXaj+5twO3olhG4nW4V8tOBD1XV/1oWoKpuaI/BjmptbcnyQGs43y+TPJIu8DqEbqI5dNvHfBF4b1WNNxI2LVV1XZK96YLeFwOPoZvUfxdwOd1/pl+gC+okaVZkZl6KkSRJGn3OcZIkSerJwEmSJKknAydJkqSeDJwkSZJ6MnCSJEnqycBJkiSpJwMnSZKkngycJEmSejJwkiRJ6snASZIkqScDJ0mSpJ4MnCRJknoycJIkSerJwEmSJKknAydJkqSeDJwkSZJ6MnCSJEnqycBJkiSpJwMnSZKkngycJEmSejJwkiRJ6snASZIkqScDJ0mSpJ4MnCRJknoycJIkSerJwEmSJKknAydJkqSeDJwkSZJ6MnCSJEnq6f8HKwImfB8TyYYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "litho_legend = legend_fig(litho_legend_display_info)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "cms = cartopy_color_settings(lithology_color_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "imgplot = plt.imshow(to_carto(lithology_3d_array[:, :, z_index_for_ahd(660)]), cmap=cms['cmap'])\n",
    "title = plt.title('Primary litho at +660mAHD')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "imgplot = plt.imshow(to_carto(lithology_3d_array[:, :, z_index_for_ahd(700)]), cmap=cms['cmap'])\n",
    "title = plt.title('Primary litho at +700mAHD')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3D visualisation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ela.visual3d import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "xx, yy = dem_array_data['mesh_xy']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "from mayavi import mlab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "vis_litho = LithologiesClassesVisual3d(lithologies, lithology_color_names, 'black')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO: problematic with this data - investigate\n",
    "# vis_litho.render_classes_planar(lithology_3d_array, 'Primary lithology')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "# vis_litho.render_class(lithology_3d_array, 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ela has facilities to visualise overlaid information: DEM, classified bore logs, and volumes of interpolated lithologies. This is important to convey .\n",
    "\n",
    "First a bit of data filling for visual purposes, as NaN lithology class codes may cause issues."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_infilled = df.fillna({PRIMARY_LITHO_NUM_COL: -1.0})\n",
    "# df_2 = df_1[(df_1[DEPTH_TO_AHD_COL] > (ahd_min-20))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "# A factor to apply to Z coordinates, otherwise things would be squashed visually along the heights.\n",
    "# Would prefer a visual only scaling factor, but could not find a way to do so. \n",
    "Z_SCALING = 20.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "z_coords = np.arange(ahd_min,ahd_max,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "overlay_vis_litho = LithologiesClassesOverlayVisual3d(lithologies, lithology_color_names, 'black', dem_array_data, z_coords, Z_SCALING, df_infilled, PRIMARY_LITHO_NUM_COL)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "def view_class(value):\n",
    "    f = overlay_vis_litho.view_overlay(value, lithology_3d_array)\n",
    "    return f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "# f = view_class(0.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![3D Interpolated overlay primary lithology clay](img/3d_overlay_bungendore_clay_lithology.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "f = view_class(1.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Slicing and exporting as Geotiff\n",
    "\n",
    "The interpolated volume is naturally using AHD coordinates for height. We may want to slice data such that we have maps of lithologies at particular depths below ground level. `SliceOperation` is here for this.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "sops = SliceOperation(dem_array, z_index_for_ahd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "depths = sops.from_ahd_to_depth_below_ground_level(lithology_3d_array, from_depth = 0, to_depth = 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(151, 131, 11)"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "depths.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plt_litho(depth_bgl):\n",
    "    imgplot = plt.imshow(to_carto(depths[:,:,10-depth_bgl]), cmap=cms['cmap'])\n",
    "    title = plt.title('Primary litho at %s m BGL'%depth_bgl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_litho(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Although the DEM had no missing data, there are some areas with no interpolated lithology classification. These correspond to elevations where there were not enough records at a given AHD to interpolate from. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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vXNcgWGdUtnTRpbe8BYA/OP2i3mwymhPC3OXpEGQSZtn0nbvIdz/XAaXf456PoiEzTQbFZtE4TBORQ0TkUyLyvvj5MSLyIRG5M/67urmZhmFMO20oo98DbgeOjJ9vB25S1R0isj1+vq3uwfMWgDNFFD5N1E8fg1gnYaBs+tZvq18n6zhtT7hWtaymkTISkROAM4G3O5tfClwRP74CeFmTNgzDmA2aKqM3A68Hnuhsm1PVRQBVXRSR4xq2sSJ/lDf3shE+VXNGXeZzQlZE0EwFVU1ag//5qLPizug9BfvUdkYichZwr6reKiJn1Hj/BcAFABx1VLX3miMKgm2r1o4eF61S2+THo22HEboDaousYR4uvjNCtkEfw0FOB14iIi8GVgFHisiVwFBE1saqaC1wb9abVfUy4DKIVwcxDGOmaWWpolgZ/b6qniUilwIPOAnsY1T19YXv91yqyJhcQqrGnhR1VCdMKxsoW0ST+qKypPcoTNu1K3epoi4qsHcALxCRO4EXxM8NwzAKaaXoUVVvBm6OHz8AbGrjuJPKpbe8ZaJLD7pMGoeQ75uELv26NFVTUO/6+86eUcRErShrTBZNFuLsk1CdUgfTe3mxsOBfc1TZsQ8GvYZphmEYlTFnZMw8oSqjcTEuRWbOyDCMIAh21P604OZNQsqTJPSRrM7KHYVWRT/NSW1fiqqy+5jZwJzRjNPHly/P6WQNDUlvm4TpPfqmyXJETY6XdtjuCrXpfcq2ZWFhmmEYQWDKqGPKQpG2wrj0r1bbE19NM6EqL3d8WR8RrduGzg+WbctSqFk2NTmXpowMwwgCU0Zjpmx6XV/Sv0iTpIqKPnuoqqUviua0bit35PP+RCm5tK3WzBkFQls9S8mXdzjcErxDKuttc/cxlqh7SsqmFfFtM6+3Lb2tKhamGYYRBKaMpozRr1LYogjwD027qgHqs4amS3yXJ/JVRbfdtm/0ePPmpe27d2/Mba8NTBkZhhEEpowCIfRK7S4o+pzu+ZiGObBd9eXbbhX7fBd2LNrPVURpNpxyGBu23xXtd+cjwJJSgnbOZbDOaNbK82fFAc0Kj6x62/INBxeXthXMF+7SNHxMnEsSarnOw7cnbsMph+Vu25iTtLYEtmEYE41NrmaMDXd1ESheYQT6UcttHDtLJQwYjD5v2eesaleZukkU0oYNG72S3W64tnH37tFj3X4uALLjylyb3G2Zq8fY5GqGYYROsDkjY3KpqgDqKIW2aVNt5SmGR4hyRttWra38mYtUSFkx44YN1brkN2zYOFJHiRqCpcT1kkIqPm9VP6M5ozHiU2czKYntOiFICE4oZHR+ULh8kBsCVr1N3CEl2aFbnOx+9K7RtiRxnTilfZs3A1F2PHF4LCwl3aveExamGYYRBKaMxkjZpGOh4ZtA7krxTHq9UXJe0on7PJosqgjF04/4DMAFWNhxMgCbN+/L7OZPH889l1XvA1NGhmEEgSkjw5s2k5VN7Wg74dyn6mr7XOXZn6WssvZLFNGy/ePHyf7zGzYuyx8lJF3/Gh9j0CDF2cgZicjRwNuBDYAC5wN3ANcA64GvAK9Q1QeLjrOWRS4cndIBMDuV11m0NcfRuGhyDZvU4kwbZQlsl+RcJ/MO5b0vs1fOY0VZWRiwb3OUuHYT2Vnt7R1eDsCpc+d72Z7QNEz7S+B/q+p/AJ4J3A5sB25S1VOAm+LnhmEYhdRWRiJyJPCzwGsAVPV7wPdE5KXAGfFuVwA3A9uKjrXIWgZEFdizrIgmmbYVTWb1boekRWiTioqmYV/WrIq+NE16Q/53cNR9nxGuuSSKqKpCaqKMngrcB7xDRD4lIm8XkcOBOVVdBIj/Hpf1ZhG5QET2iMgeDhxoYIZhGNNA7bFpInIa8DHgdFX9uIj8JfAt4CJVPdrZ70FVXV14rCkbm9b8l7H+lKv6ypXtyjX1bembRBHt2HYBkH8O2swt+iqROmqpjn2uPUVKZ1z5tX3OjGvp7n7ZcWWxIioYm9bEGf0I8DFVXR8//xmi/NDJwBmquigia4GbVfVphceaMmdUl6yEdd0KbH3lYKKcUJoyh9x2R0faIRXN7QPLB5CmbWhqU5lz3H7J21Zs83VIrZ83Z7gILA2ihaUwzeXUXXe3P1BWVb8BfE1EEkezCfgccANwXrztPOD6um0YhjE7NK0zugi4SkQeB3wJ+A0iB3etiLwWuBt4ecM2MtkyHC573tdKGF2tWtFUFaXDs0lWRS46P194HpJf+M2b943UihtGuAomv43Bsmk2fEjaaHu2wzJkYcC2VSu3p0O2rGlM0o+rkNehkCihtEKCvMR1fvuNnJGqfhrIklybmhzXMIzZY2IrsOfmdgH9/Bp1WXzY1rGnSQlB9cLP3bs3sm/zvtFjiNRSXVyFlJU/6lIRJUnrrES2zi+N0F8xtS1LCmZwsJ2qct8kuauQ3LxRFYKa6bHLsvxQKfqyTcr0IWXkXdck1N65c+eK13w/e9H94jqjonDN/YJnXY6iZLZPGNgGRSu65p3fkL5Lox62LhLYhmEYbTKxYdoskyiK0JevThgOt6xYVDJPEbahiBJ27944UkdJwjlPyVRVRAlVk+VVKBubNp8xOLWJGioKybJmp9w7vNy72nppe759QTmjkGRll5TlQaYlPHMZjf6ez08L9PG5s+6xOmvQt5GXKqPK0I6uvjuug0o7K9fxVB0Um4WFaYZhBEFQymja8e0Z6qqWqW/cWrCRMuqx/SzVcvZwHdfN3b1ie/pU512qtCLavXtjLVVS9J6i28RVS1lJ7bIpRLIoCs+qzk7ZBFNGhmEEgSmjCcNVG5OSyB6XfW4CW3eeCYBsvTGatdAhf47o5ftt3rxvmSKC5rmaJmPF3Nqj5HGZIspKNBfVEGXljIpUUl7ye/R6gW1B1RlNO3UKHJNQLT38xSV0Z+Tiew7KQlTfL+/Zw3XLnl83d3fluYvSDqipTVWoE3alqTPzYtWwrMgJLXvNVpQ1DCN0TBmNmTpKYVyDhJtQVRW2pYz6JESbYEkZ7eLMFa/53jtZA2WzBuDmDagdKTzBlJFhGGFjymjM1CmATKZr2Pq6Px9tC10d1R0QXDa5mvs8FGWSZ0fbE5tV7cDYMhyO9i3LQfrmjIq6/l0FNRxuiY69a1f7Mz22yaw6o/QXNGukuk+tUd6NFZKD6toZhUofdmY5mV1zc6PHW7gx2pYRpmVx5EnPqmzDt7766dHjrPtuZFeBM7IwzTCMILA6o0DIUgC+FdghKSAjokwRtdkJ4b63jXthzU1/yP2b/rR0v8MOXjgKv1zSIZurmoowZWQYRhCYMhozTRSRS9fj2crmos57TxdMQr6orNCwDzWbtLGLyIZl1fsFeaQvnfwKSKmZrKR2lirauXPXaPWSHduiPPDWrSv3y8Kc0Rhp6jiyelNCGGTbhhMqm4Q/q2eqayflDrwtq8ZOqFL9XBS61Rn6kz5Hc3O7ls7RMHJCW7jRK7G9ZTjkW6zsKEmS3UkotnXrFnbuXN4ZlUwRXYaFaYZhBIEpownG/ZWsOoF9VzRtv4mia7uOJwtfRZSeAdGHohqgOmFdVi3WiuN6dveX4ZYDJGFZooiWLxyQX8JjysgwjCAwZVSRca1v7ksbuaI6yeo2qNLmOJLYZarIFYXJvNTJRG7ufNFlNEluN1GHSVIb/BRTWXFkkuCem/MraG7kjETkdcBvAgrsI1pR9gnANcB64CvAK1T1wSbthESITsh1Hm0lsLPCrbyK8bz967TpY3fbQz9c04ua37x5n3eYlgwMdY9XZyoPX9JOqGz5osHcYGRT4niSv65Tquqg3JqixFkNv7rFK4ldO0wTkScDvwucpqobgEOAc4DtwE2qegpwU/zcMAyjkKZh2qHAYSLyfSJFdA9wMXBG/PoVwM3AtobtGCWklUmeyhh3grsNyrrzfUOVrFNRdHpuuy17//yZIpfjq4jqKCifZLW7fVQqkDWtCGcuU0R5+2VRZ1xbQm1lpKpfB/4MuBtYBB5W1Q8Cc6q6GO+zCByX9X4RuUBE9ojIHg4cqGuGYRhTQm1lJCKrgZcCTwEeAv5BRM71fb+qXgZcBvGofaM2ebmbPlRQm220uYCjD25zdT9GXVWU/gzz87BvazRFrrt6ydJ6c9HzJtPPVqGtLn+I1dLB8v2ahGm/AHxZVe8DEJHrgOcDQxFZq6qLIrIWuLdBG4YxoswJNXFSiQNxnZLPirJZx0gfByhd9XVhAUgtoaTzgyUbHj0s3nplJZvy8JnXCIqHjeQNlM3iMI8OwiZ1RncDPyUiTxARATYBtwM3AOfF+5wHXN+gDcMwZoTaykhVPy4i7wE+CTwGfIoo7DoCuFZEXkvksF7ehqGGH31UYrvhVBvtdVnT5LP8tNtdn5iS9T7fbn33OC7pkAuc5Ya2OxmOx58c/X30LuAR7zbLyEr8Z41/c3G7+9PqKE8VJd346WR5GY1601R1npWLhD5KpJIMwzC8sQrsClx6y1v4g9MvGrcZhfSliLpob1yV31m4C0C2QXop6iQXpNsPy9i7Oa4aSdSPq4yyygcKx8ZVSGgnimlLPMrfd9S+OSMPLr3lLQBBO6Kuq6PL2mjjuHnHS87/d08vPk5WfVGV0MqliiOa334XAAs7Tvbaf1lifFlItpyFHSePjp2QV1mdnmJk2RzYGY4p6bHzDaGy8J1+xBcbKGsYRhDY6iAzQFehmyws9FpnVNR1P86lirKWv05Oi5sQ37Ahet1VRhtOyQjTCtQSgOzI794vC898u+LbZpTUHtgijoZhBI7ljKaUSau+bkofqihv1H5RXmrpFG10Ciud/bPUT7Lt8SeveD1PFWXlfpJtQ5KE8o34pZKXlEyRkpqb29Wq0rIwrSKTkMyGsBxFGU2Ggfhuq0NRErvIAbntp3vRVpATiuWxsOPkwgR2VbJ6uroM5WwRR8MwgidYZdTVfMYh1bK0ySQpoTyqLGXtc1/43ju+k6b57jc/z/JQK01FNZQmK1RLK6OdO3eufN/CQqOu/DYwZWQYRvAEq4zaJks5+CokfeUg2v+aQYsW1WcaVJBL1ZyRr+JpqqrTOaMqBZSll6iBOipSRkl3ft49snXr1mj/gtH4ZZSNZyt8b4EympnetKwBnb7zRYfihKaVrOvQx7JDZdSt3vaZU3u+xcmY64RebVZOt4WFaYZhBMFMh2mj9n3DtUCT35MattU9l1WqrbP2y6qYbjpliI8dri0/fdRfALBpyy9VOk5Z175bH5QVsiXnvEkiu6swzZSRYRhBMDM5oyLKFE+dPFOfdDFCf9wUrQBSJY+UpYKKqqiz9q9D2aolx33hL+Kt1ZRR2WdPChabLASZRxfHdDFnFNPV9Bh908dMj3Woej6bLEG0/PXNldptKzQrs/XeH3td7eOmj7llOBz1jiXzE3Vx/buuUbIwzTCMIDBlVEDRr0tWUnCaaFthVQ1vXWVRt5t/wKCiLio/Xls1Th95OFJGmyqGafPb72KQUWeUdNWXddRkzuJYc6WQLdw4mqStjfFspowMwwiCqVJGWXmfur/sVd437qR22/mBvNU/+shHNUlWt0nestU+VMppxVPVpqeXzSOa2nb58d0pZrNoozsfVhZK7uJMaDGNFKwzauML3ncSt0nolvXekELBtpYnKruuWSFZnfAsTdVesqKlhroga4jHsuWLCtgyHI5CrZXDY7Pxma8Img0bqYqFaYZhBEFQyijrlzYkddAXvp85hO57H/t8w+UulEdaCflOA5JlT1ky/fBbjo0eeKxi4pOUz1JLWXuXhWludXaihFxFlH6vu+pHn2PYSpWRiFwuIveKyG3OtmNE5EMicmf8d7Xz2sUicpeI3CEiL+zKcMMwpgsfZfRO4K3A3znbtgM3qeoOEdkeP98mIk8HzgGeARwP/LOI/Jiq/qCJkZOmiMrsLVMJ4/q8Vdstne1ggq5bm5O19XWchC3D4SgHJAtL49FGiet4P3e8WmJDVs7IVUNubqnr/JHXQFkRWQ+8T1U3xM/vAM5Q1UURWQvcrKpPE5GLAVT1f8T7fQAYqOpHC4/vDJRtMqDVJxToelXUvDaqtNck+d0G43IiWXU8VWp7so5X9rhoW/q1vH18Qq6yz9FkteK82iGf3iC/mOYAAAuJSURBVLOySfXbdkBdDJSdU9VFgPjvcfH2JwNfc/bbH29bgYhcICJ7RGQPBw7UNMMwjGmhrjJ6SFWPdl5/UFVXi8j/Aj6qqlfG2/8WeL+q7i48fsYUIm11k69oK+dYfS5GmNfmuBVRXTvaokl3fpP2yhSP77Ykge2jcNJtN1GALlmLODapL0rCtLOH61aoo7m5XZw9XAcsLZedtZ9LF8poGIdnxH/vjbfvB0509jsBuKdmG4ZhzBB1ldGlwANOAvsYVX29iDwDeBfwXKIE9k3AKWUJ7JDWTWtDbdSt/E4rkrxj+O7XtP1xEEoFdpN2D7/lWO/8Txtj8GDl5GruMeooI59cUbJP2X4ujebAFpGrgTOANSKyH5gHdgDXishrgbuBlwOo6mdF5Frgc8BjwG837UnrmzaGPHRd/9PV8cc9rCUvBBqXQ+qSJo7H57hZ4dre4eX+TsNjv6x93BqlqpQ6I1V9Vc5Lm3L2fyPwxlrWGIYxswRVgR0Sfc+eGEKIlBDSXN99q6I67a14T0kFdtlxmiTyixLYp86dv2JJozoJ76I5sJuUANjYNMMwgsCUkQfTOMd0ESGooqpd3rr93MyxXHXbTT9uG99jF6kld1vR/NRZOaNE0bg5Hlc1jWMZbHNGAdK3wwvB+dTFd5qNSaSsh803CT5yMpxZu/Yoz9m1UcuUYGGaYRhBYMooIGYhBCyiytiv5LHs6N6eMuVRpwLb53hlbfuGer4JZ3e/orDPLQHJUkRZNUo+yxyZMjIMIwhMGQXCOFVR18WOvuMM3RzJ3uHlAFw3N54q7DptNlVEXZGcy6ycUV6RYtF88mX3SWYx5ChvlY/XcJCuCWk4iC/THFK17ZSyzpXbRlmS1meISFsOq+pxqgz9CBF3/mzfe9q9dlmzRKaXL1o2c2QHA2UNwzBaxcK0moS6jHQTQu3i72ocVxtt9aWKfOuNfGmrjigd9u3iTOZSwZhvVbYpI8MwgsCUUcf0Mc1tU8atiJqMB2tSyTxJtGX3UsdAO8tSFyksVzX5dO2bM2pIF1/kLoefjNvxJOT1sKWdRt5wkK6dS9kwFN9liULj1LnzgeVOJHnsO3d71rUrXCqJG2GYLH2Uj4VphmEEgXXtB0yX4VyfCqlOl7FLUdd+HwNbfdtIQqBEfXRhQ9ufcZlCiiuns6YagfISjeR4RUtnW9e+YRjBYzmjAAktwT1ufMZn9ZGYPvyWYwtzRF0ooiLa+uyuIsqjTBW5CitRRIlC8rXRlNGMIQsLhcs1deEI2w4Jk3CoCmUJ6az90+/97ukPtGJLHara70tWL1dWO6VDQObmRv8ThsMto/9bhsPS2iZzRoZhBIGFaRNCHxXfoXT716FsDFtZqUDWe4q2JZw6d36niesi2lJKabt9a4/y5krPUls+Fd+mjAzDCAJTRgHSZdV2naW/QyNPgTRJ6NadCWDv8PLeFVHX+FRLJ/gs0e47Ds6ckTEV+NYCNQltst4bmiOq45CzaoqyaJIqaGWmRxG5XETuFZHbnG2XisjnRWSviLxXRI52XrtYRO4SkTtE5IWVrTYMYybxyRm9E3hRatuHgA2qeirwBeBiABF5OnAO8Iz4PTtF5JDWrJ1hirrk26Krrv0mZHWx5+3XVfd3wqW3vCVz+97h5b118ZfRxjnIuwfq3h++YV+pM1LV/wN8M7Xtg6r6WPz0Y8AJ8eOXAu9W1UdV9cvAXcBzfY02DGN2aSNndD5wTfz4yUTOKWF/vG0FInIBcAEARx3VghnTTZ+KJaTlrX3pQhWl8y9lE6mVdfGX5XP2bd4MwMbdu6sZ2pAs5eKTmG6bRs5IRN4APAZclWzK2C1zJK6qXgZcBvFAWaOQomlF3MnSx4XvpPtV6XsgbNb2rNe7qC3avXvjqOW+8J0Du4/7q7YzEpHzgLOATbo09H8/cKKz2wnAPfXNMwxjVqjljETkRcA24OdU9YDz0g3Au0TkTcDxwCnAvzW20lhGlvJoozapLUXTp0orqw/yUVNthXhlKqmsCty3rsm3PR+q1BT50CTEL3VGInI1cAawRkT2A/NEvWePBz4kIgAfU9XfUtXPisi1wOeIwrffVtUf1LLMMIyZwiZXm1KaqJMqv2xtqqAmyqxMVVR93VUv7mvpLvy+ih6LSgfq2OB+tq6UbOb1HAxyJ1ezCmxjBT4z+vnQ5VzeValaoZ0XSvVdcd22E3JX6k0IZdktGyhrGEYQmDKaUiZhiaQ2yVIyeaGW+3rRe0MgUT9ZCinZdtVJb+CSg4uVjpf1+bpUssnxZLCy3QRTRoZhBIEpI6N1xl293WQEf51R7+PiqpPeAOCtilzOHq4DYNBuz/4yqqorc0ZGIW05lj6SpL4OJMvhhO6E3GT1tlVrWz1eKFiYZhhGEJgyMgoZJR5LFNK4Q7MqpFVQF4NsuyJLFW1btdY7VPMdUzeO7n5TRoZhBIEpI6MRVRVRKAV2EG5+qIhLDi6uUEdrbvpDKJneJCHEXFGCOaMZoK+hISEc12iXPuvVLEwzDCMIwhgoK3If8F3g/jGbsiYAGyAMO8wGsyFNG3acpKpPynohCGcEICJ78kbzzpINodhhNpgNfdthYZphGEFgzsgwjCAIyRldNm4DCMMGCMMOsyHCbFiiUzuCyRkZhjHbhKSMDMOYYcwZGYYRBEE4IxF5kYjcISJ3icj2nto8UUT+RURuF5HPisjvxduPEZEPicid8d/VPdhyiIh8SkTeNw4bRORoEXmPiHw+Ph/PG4MNr4uvw20icrWIrOrDBhG5XETuFZHbnG257YrIxfF9eoeIvLBDGy6Nr8deEXmviBzdtw3Oa78vIioia7q0AVUd63/gEOCLwFOBxwGfAZ7eQ7trgefEj58IfAF4OvA/ge3x9u3AJT3Y8l+BdwHvi5/3agNwBfCb8ePHAUf3aQPREuhfBg6Ln18LvKYPG4CfBZ4D3OZsy2w3vj8+Q7RM11Pi+/aQjmz4T8Ch8eNLxmFDvP1E4APAV4E1ndrQ1Q1W4SQ8D/iA8/xi4OIx2HE98ALgDmBtvG0tcEfH7Z4A3AT8vOOMerMBODJ2BJLa3qcNTwa+BhxDNF7yffGXsRcbgPUpR5DZbvrejL+kz+vChtRrvwxcNQ4bgPcAzwS+4jijTmwIIUxLbsSE/fG23hCR9cCzgY8Dc6q6CBD/Pa7j5t8MvB74d2dbnzY8FbgPeEccKr5dRA7v0wZV/TrwZ8DdwCLwsKp+sE8bUuS1O6579Xzgn/q2QUReAnxdVT+TeqkTG0JwRpKxrbd6AxE5AtgN/BdV/VZf7cZtnwXcq6q39tluikOJ5PkuVX020RjBXvJ2CXFO5qVEkv944HARObdPGzzp/V4VkTcQrc58VZ82iMgTgDcAf5T1chc2hOCM9hPFpQknAPf00bCI/DCRI7pKVa+LNw9FZG38+lrg3g5NOB14iYh8BXg38PMicmXPNuwH9qvqx+Pn7yFyTn3a8AvAl1X1PlX9PnAd8PyebXDJa7fXe1VEzgPOAn5N43ioRxt+lOjH4TPx/XkC8EkR+ZGubAjBGX0COEVEniIijwPOAW7oulEREeBvgdtV9U3OSzcA58WPzyPKJXWCql6sqieo6nqiz/1hVT23Zxu+AXxNRJ4Wb9oEfK5PG4jCs58SkSfE12UTcHvPNrjktXsDcI6IPF5EngKcAvxbFwaIyIuAbcBLVPVAyrbObVDVfap6nKquj+/P/UQdPt/ozIYuEoI1EmcvJurN+iLwhp7a/GkiabkX+HT8/8XAsUQJ5Tvjv8f0ZM8ZLCWwe7UBeBawJz4X/wisHoMNC8DngduAvyfqqencBuBqojzV9+Mv3GuL2iUKXb5IlOT+xQ5tuIsoL5Pcm3/dtw2p179CnMDuygYbDmIYRhCEEKYZhmGYMzIMIwzMGRmGEQTmjAzDCAJzRoZhBIE5I8MwgsCckWEYQfD/AflISaIAD9JAAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_litho(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "'ela' includes facilities to export slices to the GeoTIFF format. Features are available through the `GeotiffExporter` class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "from rasterio.transform import from_origin\n",
    "transform = from_origin(x_min, y_max, grid_res, grid_res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ela.io import GeotiffExporter\n",
    "ge = GeotiffExporter(bungendore_raster.crs, transform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "litho_depth = to_carto(depths[:,:,0])\n",
    "lithology_cmap = discrete_classes_colormap(lithology_color_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ge.export_rgb_geotiff(litho_depth, '/home/xxxyyy/tmp/test.tif', lithology_cmap)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The resulting file (RGB channels) should be visible from most explorer windows (Windows or Linux). Other functions export the georeference values.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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