{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a92dcf7d-66b1-4c7e-af33-1e667c541cd2",
   "metadata": {},
   "source": [
    "# Example 4 a-  Fitting H2O:Silicate areas in glasses\n",
    "- This notebook shows how to quantify the relative area of the silicate peak and H2O peak in glasses\n",
    "- Please see example 4b if you want to quantify H2O/silicate areas in unexposed olivine-hosted melt inclusions\n",
    "- This folder lets you fit one spectra at a time - this is best if you need to adjust the fits for each spectra. It saves each fit to a CSV, then you go to the end of the notebook and stitch these all together into 1 file. \n",
    "- There is also an example coming soon for looping through all spectra using the same fit parameters"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d915c98f",
   "metadata": {},
   "source": [
    "### Install DiadFit if you havent already- uncomment this!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "744d04b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install --upgrade DiadFit"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "131d8b64-4d04-46f7-b72b-4d3db8f6560e",
   "metadata": {},
   "source": [
    "## Import necessary python things"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "94f748f3-b42b-4ec3-b03a-d826d67e6ae1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.0.3'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import DiadFit as pf\n",
    "pf.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f7818105-ce38-47e4-a2dc-d193b38fad0e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set your ptah here - this assumes the txt files are in the same folder as the notebook, but you can easily add a different directory here. Chat GPT can help you with that!\n",
    "import os\n",
    "DayFolder=os.getcwd()\n",
    "spectra_path=DayFolder\n",
    "file_ext='.txt'\n",
    "filetype='headless_txt'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "061b0f3a-0c69-46f5-a73c-a8c616f1037f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ETFS_OL39_MI7_50X_GLASS.txt', 'test_H2O.txt']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "H2O_Files=pf.get_files(path=spectra_path,\n",
    "file_ext=file_ext, sort=False)\n",
    "H2O_Files"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63d820c9-50ea-4cd9-a93c-2dd365349f7c",
   "metadata": {},
   "source": [
    "### Select file\n",
    "-----------------------------------------------------------------------------------------------\n",
    "-----------------------------------------------------------------------------------------------\n",
    "-----------------------------------------------------------------------------------------------\n",
    "- Come back to here and change the i value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "016d740f-8541-4611-8acf-d7009d6b6c36",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "max i value=1\n"
     ]
    }
   ],
   "source": [
    "print('max i value='+str(len(H2O_Files)-1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "128b81b0-b6b0-460d-b21c-24f49e69ee97",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ETFS_OL39_MI7_50X_GLASS.txt\n"
     ]
    }
   ],
   "source": [
    "i=0\n",
    "filename_H2O=H2O_Files[i]\n",
    "print(filename_H2O)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "71d8c68e-eed2-4acb-8905-eb1b0d723bcb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Intensity')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the spectra from the glass sample collected by Raman\n",
    "spectra_H2O=pf.get_data(path=spectra_path, filename=filename_H2O,\n",
    "            Diad_files=None, filetype=filetype)\n",
    "plt.plot(spectra_H2O[:, 0], spectra_H2O[:,1], ':b')\n",
    "plt.xlabel('Wavenumber')\n",
    "plt.ylabel('Intensity')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cac5d6c3-0a20-4236-ba9a-9399d4b8a0a8",
   "metadata": {},
   "source": [
    "## Now lets quantify the area under the silicate region"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fb875bbd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sil_bck_pos_Schiavi_basalt(lower_range_sil=(300, 340), mid_range1_sil=(630, 640), mid_range2_sil=(800, 830), upper_range_sil=(1200, 1250), LW=(400, 600), HW=(800, 1200), N_poly_sil=3, sigma_sil=5)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We have stored default fit parameters, you can see them here\n",
    "pf.sil_bck_pos_Schiavi_basalt()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1ccabb01-af48-4f14-9271-bf1f6e8161b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sil_bck_pos_Schiavi_basalt(lower_range_sil=(300, 340), mid_range1_sil=(630, 640), mid_range2_sil=(770, 810), upper_range_sil=(1200, 1250), LW=(400, 600), HW=(800, 1200), N_poly_sil=4, sigma_sil=5)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# You can edit any of them by writing the variable name between these brackets, and entering new numbers that might work better for your system\n",
    "config_silicate=pf.sil_bck_pos_Schiavi_basalt(mid_range2_sil=(770, 810),\n",
    "     N_poly_sil=4, LW=(400, 600), HW=(800, 1200))\n",
    "config_silicate\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "bad8a847-b301-4ab1-aa45-484e3efb700e",
   "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>Silicate_LHS_Back1</th>\n",
       "      <th>Silicate_LHS_Back2</th>\n",
       "      <th>Silicate_RHS_Back1</th>\n",
       "      <th>Silicate_RHS_Back2</th>\n",
       "      <th>Silicate_N_Poly</th>\n",
       "      <th>Silicate_Trapezoid_Area</th>\n",
       "      <th>Silicate_Simpson_Area</th>\n",
       "      <th>LW_Silicate_Trapezoid_Area</th>\n",
       "      <th>LW_Silicate_Simpson_Area</th>\n",
       "      <th>HW_Silicate_Trapezoid_Area</th>\n",
       "      <th>HW_Silicate_Simpson_Area</th>\n",
       "      <th>MW_Silicate_Trapezoid_Area</th>\n",
       "      <th>MW_Silicate_Simpson_Area</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>300</td>\n",
       "      <td>340</td>\n",
       "      <td>1200</td>\n",
       "      <td>1250</td>\n",
       "      <td>4</td>\n",
       "      <td>362558.10011</td>\n",
       "      <td>362437.552216</td>\n",
       "      <td>69943.66401</td>\n",
       "      <td>69904.770625</td>\n",
       "      <td>265265.242676</td>\n",
       "      <td>265018.00209</td>\n",
       "      <td>11333.332933</td>\n",
       "      <td>11224.5619</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Silicate_LHS_Back1  Silicate_LHS_Back2  Silicate_RHS_Back1  \\\n",
       "0                 300                 340                1200   \n",
       "\n",
       "   Silicate_RHS_Back2  Silicate_N_Poly  Silicate_Trapezoid_Area  \\\n",
       "0                1250                4             362558.10011   \n",
       "\n",
       "   Silicate_Simpson_Area  LW_Silicate_Trapezoid_Area  \\\n",
       "0          362437.552216                 69943.66401   \n",
       "\n",
       "   LW_Silicate_Simpson_Area  HW_Silicate_Trapezoid_Area  \\\n",
       "0              69904.770625               265265.242676   \n",
       "\n",
       "   HW_Silicate_Simpson_Area  MW_Silicate_Trapezoid_Area  \\\n",
       "0              265018.00209                11333.332933   \n",
       "\n",
       "   MW_Silicate_Simpson_Area  \n",
       "0                11224.5619  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# This cell calculates the area under the 3 different silicate regions\n",
    "df_sil=pf.fit_area_for_silicate_region(Spectra=spectra_H2O, \n",
    "path=spectra_path, filename=filename_H2O, config1=config_silicate,\n",
    "exclude_range1_sil=None, exclude_range2_sil=None,  plot_figure=True,\n",
    "fit_sil='poly')\n",
    "df_sil"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab74105e-2919-40f0-a2ac-5fa46fca494c",
   "metadata": {},
   "source": [
    "## Now quantify the area under the water region"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "13312cce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "water_bck_pos(fit_water='poly', N_poly_water=3, lower_bck_water=(2750, 3100), upper_bck_water=(3750, 4100))"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Again, there is a default set of variables\n",
    "pf.water_bck_pos()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0afc7b71-c12f-4686-b5b7-16076629ad52",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "water_bck_pos(fit_water='poly', N_poly_water=3, lower_bck_water=(2500, 2750), upper_bck_water=(3750, 4100))\n"
     ]
    },
    {
     "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>Water Filename</th>\n",
       "      <th>Water_LHS_Back1</th>\n",
       "      <th>Water_LHS_Back2</th>\n",
       "      <th>Water_RHS_Back1</th>\n",
       "      <th>Water_RHS_Back2</th>\n",
       "      <th>Water_N_Poly</th>\n",
       "      <th>Water_Trapezoid_Area</th>\n",
       "      <th>Water_Simpson_Area</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ETFS_OL39_MI7_50X_GLASS.txt</td>\n",
       "      <td>2500</td>\n",
       "      <td>2750</td>\n",
       "      <td>3750</td>\n",
       "      <td>4100</td>\n",
       "      <td>3</td>\n",
       "      <td>274807.39519</td>\n",
       "      <td>274611.003728</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Water Filename  Water_LHS_Back1  Water_LHS_Back2  \\\n",
       "0  ETFS_OL39_MI7_50X_GLASS.txt             2500             2750   \n",
       "\n",
       "   Water_RHS_Back1  Water_RHS_Back2  Water_N_Poly  Water_Trapezoid_Area  \\\n",
       "0             3750             4100             3          274807.39519   \n",
       "\n",
       "   Water_Simpson_Area  \n",
       "0       274611.003728  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# And you can edit any of these values here - we are tweaking the lower background\n",
    "config_H2O=pf.water_bck_pos(lower_bck_water=(2500, 2750))\n",
    "print(config_H2O)\n",
    "\n",
    "df_H2O=pf.fit_area_for_water_region(\n",
    "path=spectra_path, filename=filename_H2O,\n",
    "Spectra=spectra_H2O,\n",
    "config1=config_H2O)\n",
    "df_H2O"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f8e6c2d9-05ca-4f28-babb-69ed2f576fcf",
   "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>MI filename</th>\n",
       "      <th>Water_to_HW_ratio_Trapezoid</th>\n",
       "      <th>Water_to_HW_ratio_Simpson</th>\n",
       "      <th>Water_to_Total_Silicate_ratio_Trapezoid</th>\n",
       "      <th>Water_to_Total_Silicate_ratio_Simpson</th>\n",
       "      <th>Water_Trapezoid_Area</th>\n",
       "      <th>Water_Simpson_Area</th>\n",
       "      <th>Silicate_Trapezoid_Area</th>\n",
       "      <th>Silicate_Simpson_Area</th>\n",
       "      <th>Silicate_LHS_Back1</th>\n",
       "      <th>...</th>\n",
       "      <th>HW_Silicate_Trapezoid_Area</th>\n",
       "      <th>HW_Silicate_Simpson_Area</th>\n",
       "      <th>MW_Silicate_Trapezoid_Area</th>\n",
       "      <th>MW_Silicate_Simpson_Area</th>\n",
       "      <th>Water Filename</th>\n",
       "      <th>Water_LHS_Back1</th>\n",
       "      <th>Water_LHS_Back2</th>\n",
       "      <th>Water_RHS_Back1</th>\n",
       "      <th>Water_RHS_Back2</th>\n",
       "      <th>Water_N_Poly</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ETFS_OL39_MI7_50X_GLASS.txt</td>\n",
       "      <td>1.035972</td>\n",
       "      <td>1.036198</td>\n",
       "      <td>0.757968</td>\n",
       "      <td>0.757678</td>\n",
       "      <td>274807.39519</td>\n",
       "      <td>274611.003728</td>\n",
       "      <td>362558.10011</td>\n",
       "      <td>362437.552216</td>\n",
       "      <td>300</td>\n",
       "      <td>...</td>\n",
       "      <td>265265.242676</td>\n",
       "      <td>265018.00209</td>\n",
       "      <td>11333.332933</td>\n",
       "      <td>11224.5619</td>\n",
       "      <td>ETFS_OL39_MI7_50X_GLASS.txt</td>\n",
       "      <td>2500</td>\n",
       "      <td>2750</td>\n",
       "      <td>3750</td>\n",
       "      <td>4100</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   MI filename  Water_to_HW_ratio_Trapezoid  \\\n",
       "0  ETFS_OL39_MI7_50X_GLASS.txt                     1.035972   \n",
       "\n",
       "   Water_to_HW_ratio_Simpson  Water_to_Total_Silicate_ratio_Trapezoid  \\\n",
       "0                   1.036198                                 0.757968   \n",
       "\n",
       "   Water_to_Total_Silicate_ratio_Simpson  Water_Trapezoid_Area  \\\n",
       "0                               0.757678          274807.39519   \n",
       "\n",
       "   Water_Simpson_Area  Silicate_Trapezoid_Area  Silicate_Simpson_Area  \\\n",
       "0       274611.003728             362558.10011          362437.552216   \n",
       "\n",
       "   Silicate_LHS_Back1  ...  HW_Silicate_Trapezoid_Area  \\\n",
       "0                 300  ...               265265.242676   \n",
       "\n",
       "   HW_Silicate_Simpson_Area  MW_Silicate_Trapezoid_Area  \\\n",
       "0              265018.00209                11333.332933   \n",
       "\n",
       "   MW_Silicate_Simpson_Area               Water Filename  Water_LHS_Back1  \\\n",
       "0                11224.5619  ETFS_OL39_MI7_50X_GLASS.txt             2500   \n",
       "\n",
       "   Water_LHS_Back2  Water_RHS_Back1  Water_RHS_Back2  Water_N_Poly  \n",
       "0             2750             3750             4100             3  \n",
       "\n",
       "[1 rows x 26 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This combines the outputs you got from silicate fitting and H2O fitting.\n",
    "combo_out=pf.stitch_dataframes_together(df_sil=df_sil, df_water=df_H2O, \n",
    "MI_file=filename_H2O, save_csv=True, path=DayFolder)\n",
    "combo_out"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "956eb550-698f-496c-bc78-29341a835744",
   "metadata": {},
   "source": [
    "### You have fitted one file - Now click this to go back to the top and do the next file and so on by changing i"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b805b25c-adef-4353-8664-025c18957f9a",
   "metadata": {},
   "source": [
    "[Select file](#Select-file)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32aada47-007b-4010-878d-05989eac7534",
   "metadata": {},
   "source": [
    "## Once you've fitted all your files...\n",
    "- Now stitch them, this code works by finding Stitching all the files together once you have them"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4de002f4-3564-40fe-b872-1d8d568cf945",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ETFS_OL39_MI7_50X_GLASS_combo_fit.csv', 'test_H2O_combo_fit.csv']"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv_files2=pf.get_files(path=DayFolder, ID_str='combo_fit',\n",
    "    sort=True, file_ext='csv')\n",
    "csv_files2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58ebc31d-9033-4271-87bf-f05949809f0b",
   "metadata": {},
   "source": [
    "### Stitch data from all these CSVs together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d4d32b40-d291-4c75-8ab4-9fc51279b1d8",
   "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>Unnamed: 0</th>\n",
       "      <th>MI filename</th>\n",
       "      <th>Water_to_HW_ratio_Trapezoid</th>\n",
       "      <th>Water_to_HW_ratio_Simpson</th>\n",
       "      <th>Water_to_Total_Silicate_ratio_Trapezoid</th>\n",
       "      <th>Water_to_Total_Silicate_ratio_Simpson</th>\n",
       "      <th>Water_Trapezoid_Area</th>\n",
       "      <th>Water_Simpson_Area</th>\n",
       "      <th>Silicate_Trapezoid_Area</th>\n",
       "      <th>Silicate_Simpson_Area</th>\n",
       "      <th>...</th>\n",
       "      <th>MW_Silicate_Trapezoid_Area</th>\n",
       "      <th>MW_Silicate_Simpson_Area</th>\n",
       "      <th>Water Filename</th>\n",
       "      <th>Water_LHS_Back1</th>\n",
       "      <th>Water_LHS_Back2</th>\n",
       "      <th>Water_RHS_Back1</th>\n",
       "      <th>Water_RHS_Back2</th>\n",
       "      <th>Water_N_Poly</th>\n",
       "      <th>HW:LW_Trapezoid</th>\n",
       "      <th>HW:LW_Simpson</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>ETFS_OL39_MI7_50X_GLASS.txt</td>\n",
       "      <td>1.035972</td>\n",
       "      <td>1.036198</td>\n",
       "      <td>0.757968</td>\n",
       "      <td>0.757678</td>\n",
       "      <td>274807.39519</td>\n",
       "      <td>274611.003728</td>\n",
       "      <td>362558.10011</td>\n",
       "      <td>362437.552216</td>\n",
       "      <td>...</td>\n",
       "      <td>11333.332933</td>\n",
       "      <td>11224.5619</td>\n",
       "      <td>ETFS_OL39_MI7_50X_GLASS.txt</td>\n",
       "      <td>2500</td>\n",
       "      <td>2750</td>\n",
       "      <td>3750</td>\n",
       "      <td>4100</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>test_H2O.txt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>274807.39519</td>\n",
       "      <td>274611.003728</td>\n",
       "      <td>362558.10011</td>\n",
       "      <td>362437.552216</td>\n",
       "      <td>...</td>\n",
       "      <td>11333.332933</td>\n",
       "      <td>11224.5619</td>\n",
       "      <td>test_H2O.txt</td>\n",
       "      <td>2500</td>\n",
       "      <td>2750</td>\n",
       "      <td>3750</td>\n",
       "      <td>4100</td>\n",
       "      <td>3</td>\n",
       "      <td>3.928982</td>\n",
       "      <td>3.928359</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0                  MI filename  Water_to_HW_ratio_Trapezoid  \\\n",
       "0           0  ETFS_OL39_MI7_50X_GLASS.txt                     1.035972   \n",
       "1           0                 test_H2O.txt                          NaN   \n",
       "\n",
       "   Water_to_HW_ratio_Simpson  Water_to_Total_Silicate_ratio_Trapezoid  \\\n",
       "0                   1.036198                                 0.757968   \n",
       "1                        NaN                                      NaN   \n",
       "\n",
       "   Water_to_Total_Silicate_ratio_Simpson  Water_Trapezoid_Area  \\\n",
       "0                               0.757678          274807.39519   \n",
       "1                                    NaN          274807.39519   \n",
       "\n",
       "   Water_Simpson_Area  Silicate_Trapezoid_Area  Silicate_Simpson_Area  ...  \\\n",
       "0       274611.003728             362558.10011          362437.552216  ...   \n",
       "1       274611.003728             362558.10011          362437.552216  ...   \n",
       "\n",
       "   MW_Silicate_Trapezoid_Area  MW_Silicate_Simpson_Area  \\\n",
       "0                11333.332933                11224.5619   \n",
       "1                11333.332933                11224.5619   \n",
       "\n",
       "                Water Filename  Water_LHS_Back1  Water_LHS_Back2  \\\n",
       "0  ETFS_OL39_MI7_50X_GLASS.txt             2500             2750   \n",
       "1                 test_H2O.txt             2500             2750   \n",
       "\n",
       "   Water_RHS_Back1  Water_RHS_Back2  Water_N_Poly  HW:LW_Trapezoid  \\\n",
       "0             3750             4100             3              NaN   \n",
       "1             3750             4100             3         3.928982   \n",
       "\n",
       "   HW:LW_Simpson  \n",
       "0            NaN  \n",
       "1       3.928359  \n",
       "\n",
       "[2 rows x 29 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.concat(\n",
    "    map(pd.read_csv, csv_files2), ignore_index=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a0da79e-1b2b-4b16-9d7e-c419a64a6700",
   "metadata": {},
   "source": [
    "### Now save to Excel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a2178c44-7718-4ac9-ac6b-b4fb4317bf6c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_excel('H2O_Silicate_areas.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f652b2df",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d5822ed8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b8b48879",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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