{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-09-22 14:46:09: oggm.cfg: Reading default parameters from the OGGM `params.cfg` configuration file.\n",
      "2021-09-22 14:46:09: oggm.cfg: Multiprocessing switched OFF according to the parameter file.\n",
      "2021-09-22 14:46:09: oggm.cfg: Multiprocessing: using all available processors (N=32)\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "import matplotlib.pyplot as plt\n",
    "from oggm import utils, cfg\n",
    "cfg.initialize()\n",
    "\n",
    "import matplotlib\n",
    "matplotlib.rcParams['figure.figsize'] = (14, 8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "sns.set_context('talk')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "period = '2000-01-01_2020-01-01'\n",
    "\n",
    "dfz = pd.read_csv(utils.get_demo_file('zemp_ref_2006_2016.csv'), index_col=0)\n",
    "dfh = pd.read_csv(utils.get_demo_file('table_hugonnet_regions_10yr_20yr_ar6period.csv'), index_col=0)\n",
    "dfh = dfh.loc[dfh.period == period]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfz['SMB_ZEMP'] = dfz['SMB']\n",
    "dfz['SMB_HUGUONNET'] = dfh['dmdtda'] * 1e-3\n",
    "dfz['SMB_HUGUONNET_err'] = dfh['err_dmdtda'] * 1e-3\n",
    "dfz.index = ['{:02d}'.format(rgi_reg) for rgi_reg in dfz.index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots()\n",
    "dfz.plot(ax=ax, y='SMB_ZEMP', yerr='SMB_err', marker='o', linestyle='none');\n",
    "dfz.plot(ax=ax, y='SMB_HUGUONNET', yerr='SMB_HUGUONNET_err', marker='o', linestyle='none');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfh['dmdt_zemp'] = dfz.SMB.values * 1000\n",
    "dfh['dmdt_zemp_err'] = dfz.SMB_err.values * 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfh.index = ['{:02d}'.format(int(rgi_reg)) for rgi_reg in dfh.index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "odirs = ['../L3-L5_files/ERA5/elev_bands/qc3/pcp1.6/no_match/RGI62/b_160/L3/summary/',\n",
    "         '../L3-L5_files/ERA5/elev_bands/qc3/pcp1.6/match_geod/RGI62/b_160/L3/summary/',\n",
    "         '../L3-L5_files/ERA5/elev_bands/qc3/pcp1.6/match_geod_pergla/RGI62/b_160/L3/summary/',\n",
    "        ]\n",
    "names = ['old', 'regio', 'pergla'\n",
    "        ]         \n",
    "\n",
    "for odir, name in zip(odirs, names):\n",
    "    for rgi_reg in np.arange(1, 20):\n",
    "        rgi_reg = '{:02d}'.format(rgi_reg)\n",
    "\n",
    "        try:\n",
    "            df = pd.read_csv(odir + f'fixed_geometry_mass_balance_{rgi_reg}.csv'.format(rgi_reg), index_col=0, low_memory=False)\n",
    "            dfs = pd.read_csv(odir + f'glacier_statistics_{rgi_reg}.csv'.format(rgi_reg), index_col=0, low_memory=False)\n",
    "        except FileNotFoundError:\n",
    "            print('Not here:', odir, rgi_reg)\n",
    "            continue\n",
    "        df = df.dropna(axis=0, how='all')\n",
    "        df = df.dropna(axis=1, how='all')\n",
    "\n",
    "#         odf = pd.DataFrame(df.loc[2006:2016].mean(), columns=['SMB'])\n",
    "#         odf['AREA'] = dfs.rgi_area_km2\n",
    "\n",
    "#         dfh.loc[rgi_reg, 'AREA_OGGM'] = odf['AREA'].sum()\n",
    "#         dfh.loc[rgi_reg, 'SMB_OGGM'] = np.average(odf['SMB'], weights=odf['AREA']) / 1000\n",
    "\n",
    "        odf = pd.DataFrame(df.loc[2000:].mean(), columns=['SMB'])\n",
    "        odf['AREA'] = dfs.rgi_area_km2\n",
    "        dfh.loc[rgi_reg, f'dmdtda_OGGM_{name}'] = np.average(odf['SMB'], weights=odf['AREA'])\n",
    "        \n",
    "        \n",
    "        odir_5 = odir.replace('L3/', 'L5/')\n",
    "        \n",
    "        with xr.open_dataset(odir_5 + f'historical_run_output_extended_{rgi_reg}.nc') as ds:\n",
    "            ds = ds[['volume', 'area']].sum(dim='rgi_id')\n",
    "        vol_ts = ds.volume.to_series()\n",
    "        area_ts = ds.area.to_series()\n",
    "        dfh.loc[rgi_reg, f'dmdt_OGGM_{name}'] = (vol_ts.loc[2019] - vol_ts.loc[2000]) * cfg.PARAMS['ice_density'] * 1e-12 / 20\n",
    "        dfh.loc[rgi_reg, f'dmdtda_dyna_OGGM_{name}'] = (vol_ts.loc[2019] - vol_ts.loc[2000]) / area_ts.loc[2000] * cfg.PARAMS['ice_density'] / 20 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots()\n",
    "dfh.plot(ax=ax, y='dmdtda_OGGM_old', marker='o', linestyle='none', markersize=8);\n",
    "dfh.plot(ax=ax, y='dmdt_zemp', yerr='dmdt_zemp_err', marker='o', linestyle='none');\n",
    "dfh.plot(ax=ax, y='dmdtda', yerr='err_dmdtda', marker='o', linestyle='none');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dmdtda            -495.951579\n",
       "dmdt_zemp         -581.578947\n",
       "dmdtda_OGGM_old   -608.398797\n",
       "dtype: float64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfh[['dmdtda', 'dmdt_zemp', 'dmdtda_OGGM_old']].mean()Assoc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots()\n",
    "dfh.plot(ax=ax, y='dmdtda_OGGM_regio', marker='o', linestyle='none', markersize=8);\n",
    "dfh.plot(ax=ax, y='dmdtda_OGGM_pergla', marker='o', linestyle='none', markersize=8);\n",
    "dfh.plot(ax=ax, y='dmdtda', yerr='err_dmdtda', marker='o', linestyle='none');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots()\n",
    "dfh.plot(ax=ax, y='dmdtda_dyna_OGGM_regio', marker='o', linestyle='none', markersize=8);\n",
    "dfh.plot(ax=ax, y='dmdtda_dyna_OGGM_pergla', marker='o', linestyle='none', markersize=8);\n",
    "dfh.plot(ax=ax, y='dmdtda', yerr='err_dmdtda', marker='o', linestyle='none');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots()\n",
    "dfh.plot(ax=ax, y='dmdt_OGGM_regio', marker='o', linestyle='none', markersize=8);\n",
    "dfh.plot(ax=ax, y='dmdt_OGGM_pergla', marker='o', linestyle='none', markersize=8);\n",
    "dfh.plot(ax=ax, y='dmdt', yerr='err_dmdt', marker='o', linestyle='none');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['period', 'dmdt', 'err_dmdt', 'dmdtda', 'err_dmdtda', 'dmdtda_OGGM_old',\n",
       "       'dmdt_OGGM_old', 'dmdtda_dyna_OGGM_old', 'dmdtda_OGGM_regio',\n",
       "       'dmdt_OGGM_regio', 'dmdtda_dyna_OGGM_regio', 'dmdtda_OGGM_pergla',\n",
       "       'dmdt_OGGM_pergla', 'dmdtda_dyna_OGGM_pergla'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfh.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>dmdtda</th>\n",
       "      <th>dmdtda_OGGM_old</th>\n",
       "      <th>dmdtda_OGGM_regio</th>\n",
       "      <th>dmdtda_OGGM_pergla</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>dmdtda</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.334927</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.986900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dmdtda_OGGM_old</th>\n",
       "      <td>0.334927</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.334927</td>\n",
       "      <td>0.338504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dmdtda_OGGM_regio</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.334927</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.986900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dmdtda_OGGM_pergla</th>\n",
       "      <td>0.986900</td>\n",
       "      <td>0.338504</td>\n",
       "      <td>0.986900</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      dmdtda  dmdtda_OGGM_old  dmdtda_OGGM_regio  \\\n",
       "dmdtda              1.000000         0.334927           1.000000   \n",
       "dmdtda_OGGM_old     0.334927         1.000000           0.334927   \n",
       "dmdtda_OGGM_regio   1.000000         0.334927           1.000000   \n",
       "dmdtda_OGGM_pergla  0.986900         0.338504           0.986900   \n",
       "\n",
       "                    dmdtda_OGGM_pergla  \n",
       "dmdtda                        0.986900  \n",
       "dmdtda_OGGM_old               0.338504  \n",
       "dmdtda_OGGM_regio             0.986900  \n",
       "dmdtda_OGGM_pergla            1.000000  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfh[['dmdtda', 'dmdtda_OGGM_old', 'dmdtda_OGGM_regio', 'dmdtda_OGGM_pergla']].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dmdt               -266.380000\n",
       "dmdt_OGGM_old      -361.180263\n",
       "dmdt_OGGM_regio    -266.220926\n",
       "dmdt_OGGM_pergla   -264.189416\n",
       "dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfh[['dmdt', 'dmdt_OGGM_old', 'dmdt_OGGM_regio', 'dmdt_OGGM_pergla']].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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