{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1496df86-801f-4984-80dd-eccf9ba5ab90",
   "metadata": {},
   "outputs": [],
   "source": [
    "from oggm import cfg, tasks, utils, workflow\n",
    "from oggm.shop import millan22, bedtopo\n",
    "from fiona.errors import DriverError\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "from oggm.global_tasks import compile_task_log"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "83caf340-98d9-4b3f-b7eb-ac94811a129d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-10-26 16:40:13: oggm.cfg: Reading default parameters from the OGGM `params.cfg` configuration file.\n",
      "2022-10-26 16:40:13: oggm.cfg: Multiprocessing switched OFF according to the parameter file.\n",
      "2022-10-26 16:40:13: oggm.cfg: Multiprocessing: using all available processors (N=32)\n",
      "2022-10-26 16:40:13: oggm.cfg: Multiprocessing switched ON after user settings.\n",
      "2022-10-26 16:40:13: oggm.cfg: Multiprocessing: using the requested number of processors (N=4)\n",
      "2022-10-26 16:40:13: oggm.cfg: PARAMS['continue_on_error'] changed from `False` to `True`.\n"
     ]
    }
   ],
   "source": [
    "# Initialize OGGM and set up the default run parameters\n",
    "cfg.initialize(logging_level='WORKFLOW', future=True)\n",
    "\n",
    "# Local working directory (where OGGM will write its output)\n",
    "cfg.PATHS['working_dir'] = 'working_dir'\n",
    "\n",
    "cfg.PARAMS['use_multiprocessing'] = True\n",
    "cfg.PARAMS['mp_processes'] = 4\n",
    "cfg.PARAMS['continue_on_error'] = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9855c075-bfb0-4467-92d3-cd53f0fc495b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2785\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "2782"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rgi_ids = pd.concat([pd.read_csv('glathida_rgi_ids.csv', index_col=0), pd.read_csv('toy_rgi_ids.csv', index_col=0)])\n",
    "print(len(rgi_ids))\n",
    "rgi_ids = rgi_ids.RGI_ID.unique()\n",
    "len(rgi_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1dfe1f28-abc4-41f0-814c-4f5f5a238fb0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "You have some level 2 glaciers... Removing...\n",
      "2592\n"
     ]
    }
   ],
   "source": [
    "# Check which glaciers we can actually process\n",
    "rgi_stats = pd.read_csv(utils.file_downloader('https://cluster.klima.uni-bremen.de/~oggm/rgi/rgi62_stats.csv'), index_col=0)\n",
    "rgi_stats = rgi_stats.loc[rgi_ids]\n",
    "\n",
    "if np.any(rgi_stats.Connect == 2):\n",
    "    print('You have some level 2 glaciers... Removing...')\n",
    "    rgi_ids = list(rgi_stats.loc[rgi_stats.Connect != 2].index)\n",
    "    print(len(rgi_ids))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "de337664-d627-463f-9bfa-49c73f814cd6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# rgi_ids = rgi_ids[:8]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b5abf5af-c946-41a0-8537-8c8608953692",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-10-26 16:40:13: oggm.workflow: init_glacier_directories from prepro level 2 on 2592 glaciers.\n",
      "2022-10-26 16:40:13: oggm.workflow: Execute entity tasks [gdir_from_prepro] on 2592 glaciers\n"
     ]
    }
   ],
   "source": [
    "utils.mkdir(cfg.PATHS['working_dir'])\n",
    "\n",
    "# Check if some of the gdirs is missing files\n",
    "base_url = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.6/L1-L2_files/elev_bands/'\n",
    "gdirs = workflow.init_glacier_directories(rgi_ids, prepro_base_url=base_url, from_prepro_level=2, prepro_border=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cb643336-1b6d-4583-a5d9-dd26815987ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "workflow.execute_entity_task(tasks.gridded_attributes, gdirs); # this does some stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "29a0ee93-cb80-457c-af3b-919d7dbb749a",
   "metadata": {},
   "outputs": [],
   "source": [
    "workflow.execute_entity_task(bedtopo.add_consensus_thickness, gdirs);  # Use consensus ice thicknesses from Farinotti et al. (2019)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ee61b346-232c-4554-9deb-1bc658a8bee9",
   "metadata": {},
   "outputs": [],
   "source": [
    "workflow.execute_entity_task(millan22.thickness_to_gdir, gdirs);  # millan thickness"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b4f95d94-28cd-4ec3-b9c0-e54b24025324",
   "metadata": {},
   "outputs": [],
   "source": [
    "workflow.execute_entity_task(millan22.velocity_to_gdir, gdirs);  # millan velocity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "46f5651c-0603-4f29-8f95-66a0007a966e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_millan = millan22.compile_millan_statistics(gdirs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8008a498-0879-4ce4-a503-38fedec774f5",
   "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>rgi_region</th>\n",
       "      <th>rgi_subregion</th>\n",
       "      <th>rgi_area_km2</th>\n",
       "      <th>millan_vol_km3</th>\n",
       "      <th>millan_area_km2</th>\n",
       "      <th>millan_perc_cov</th>\n",
       "      <th>millan_avg_vel</th>\n",
       "      <th>millan_max_vel</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rgi_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RGI60-01.00570</th>\n",
       "      <td>01</td>\n",
       "      <td>01-02</td>\n",
       "      <td>17.567</td>\n",
       "      <td>1.380018</td>\n",
       "      <td>17.549046</td>\n",
       "      <td>0.998978</td>\n",
       "      <td>7.857373</td>\n",
       "      <td>50.500019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-01.08989</th>\n",
       "      <td>01</td>\n",
       "      <td>01-04</td>\n",
       "      <td>29.395</td>\n",
       "      <td>5.070058</td>\n",
       "      <td>29.147636</td>\n",
       "      <td>0.991585</td>\n",
       "      <td>16.232468</td>\n",
       "      <td>153.300903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-01.10006</th>\n",
       "      <td>01</td>\n",
       "      <td>01-04</td>\n",
       "      <td>219.444</td>\n",
       "      <td>48.965865</td>\n",
       "      <td>218.960000</td>\n",
       "      <td>0.997794</td>\n",
       "      <td>157.288147</td>\n",
       "      <td>2696.096924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-01.10196</th>\n",
       "      <td>01</td>\n",
       "      <td>01-04</td>\n",
       "      <td>427.281</td>\n",
       "      <td>125.213590</td>\n",
       "      <td>427.360000</td>\n",
       "      <td>1.000185</td>\n",
       "      <td>197.699814</td>\n",
       "      <td>1434.918701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-01.10557</th>\n",
       "      <td>01</td>\n",
       "      <td>01-04</td>\n",
       "      <td>307.521</td>\n",
       "      <td>66.722425</td>\n",
       "      <td>307.360000</td>\n",
       "      <td>0.999476</td>\n",
       "      <td>92.037796</td>\n",
       "      <td>627.021362</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               rgi_region rgi_subregion  rgi_area_km2  millan_vol_km3  \\\n",
       "rgi_id                                                                  \n",
       "RGI60-01.00570         01         01-02        17.567        1.380018   \n",
       "RGI60-01.08989         01         01-04        29.395        5.070058   \n",
       "RGI60-01.10006         01         01-04       219.444       48.965865   \n",
       "RGI60-01.10196         01         01-04       427.281      125.213590   \n",
       "RGI60-01.10557         01         01-04       307.521       66.722425   \n",
       "\n",
       "                millan_area_km2  millan_perc_cov  millan_avg_vel  \\\n",
       "rgi_id                                                             \n",
       "RGI60-01.00570        17.549046         0.998978        7.857373   \n",
       "RGI60-01.08989        29.147636         0.991585       16.232468   \n",
       "RGI60-01.10006       218.960000         0.997794      157.288147   \n",
       "RGI60-01.10196       427.360000         1.000185      197.699814   \n",
       "RGI60-01.10557       307.360000         0.999476       92.037796   \n",
       "\n",
       "                millan_max_vel  \n",
       "rgi_id                          \n",
       "RGI60-01.00570       50.500019  \n",
       "RGI60-01.08989      153.300903  \n",
       "RGI60-01.10006     2696.096924  \n",
       "RGI60-01.10196     1434.918701  \n",
       "RGI60-01.10557      627.021362  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_millan.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d15bd422-d2fa-46ba-95d6-e15f886da89f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-10-26 16:58:21: oggm.utils: Applying global task compile_task_log on 2592 glaciers\n"
     ]
    }
   ],
   "source": [
    "task_log = compile_task_log(gdirs, task_names=[\"gridded_attributes\", \"add_consensus_thickness\", \"velocity_to_gdir\", \"thickness_to_gdir\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4ed496c5-a0b1-42ea-93dc-b4b90fe00ff2",
   "metadata": {},
   "outputs": [],
   "source": [
    "with xr.open_dataset(gdirs[0].get_filepath('gridded_data')) as ds:\n",
    "    ds = ds.load()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "345c110c-479f-4660-8e94-0f2d9fffaab6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds.millan_ice_thickness.plot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "7c1d9bff-6c6c-4de5-bd3b-4bcd458d0a7a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds.consensus_ice_thickness.plot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3eb773e1-81e9-46ed-9b10-98d81a9af326",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds.millan_v.plot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "15758986-caaf-4f2b-8547-f460608af220",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os, shutil\n",
    "\n",
    "# Where to put the compressed dirs\n",
    "PREPRO_DIR = 'prepro_dir'\n",
    "if os.path.exists(PREPRO_DIR):\n",
    "    shutil.rmtree(PREPRO_DIR)\n",
    "\n",
    "# Then tar the gdirs and bundle\n",
    "workflow.execute_entity_task(utils.gdir_to_tar, gdirs, delete=True)\n",
    "utils.base_dir_to_tar(delete=True)\n",
    "\n",
    "# Copy the outcome in a new directory: scratch folder, new machine, etc.\n",
    "shutil.copytree(os.path.join(cfg.PATHS['working_dir'], 'per_glacier'), PREPRO_DIR);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "69a61301-992e-4afa-806d-ce9d04d36b7e",
   "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>gridded_attributes</th>\n",
       "      <th>add_consensus_thickness</th>\n",
       "      <th>velocity_to_gdir</th>\n",
       "      <th>thickness_to_gdir</th>\n",
       "      <th>gridded_attributes_n</th>\n",
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       "      <th>velocity_to_gdir_n</th>\n",
       "      <th>thickness_to_gdir_n</th>\n",
       "      <th>gridded_attributes_n.1</th>\n",
       "      <th>add_consensus_thickness_n.1</th>\n",
       "      <th>velocity_to_gdir_n.1</th>\n",
       "      <th>thickness_to_gdir_n.1</th>\n",
       "      <th>gridded_attributes_n.2</th>\n",
       "      <th>add_consensus_thickness_n.2</th>\n",
       "      <th>velocity_to_gdir_n.2</th>\n",
       "      <th>thickness_to_gdir_n.2</th>\n",
       "      <th>gridded_attributes_n</th>\n",
       "      <th>add_consensus_thickness_n</th>\n",
       "      <th>velocity_to_gdir_n</th>\n",
       "      <th>thickness_to_gdir_n</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rgi_id</th>\n",
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       "      <th></th>\n",
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       "  <tbody>\n",
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       "      <th>RGI60-01.00570</th>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
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       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
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       "    <tr>\n",
       "      <th>RGI60-01.08989</th>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
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       "      <td>SUCCESS</td>\n",
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       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
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       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-01.10006</th>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
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       "      <td>SUCCESS</td>\n",
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       "      <td>SUCCESS</td>\n",
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       "      <td></td>\n",
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       "    <tr>\n",
       "      <th>RGI60-01.10196</th>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
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       "      <td>SUCCESS</td>\n",
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       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
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       "    <tr>\n",
       "      <th>RGI60-01.10557</th>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
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       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-01.10612</th>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-01.10621</th>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td>SUCCESS</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               gridded_attributes add_consensus_thickness velocity_to_gdir  \\\n",
       "rgi_id                                                                       \n",
       "RGI60-01.00570            SUCCESS                 SUCCESS          SUCCESS   \n",
       "RGI60-01.08989            SUCCESS                 SUCCESS          SUCCESS   \n",
       "RGI60-01.10006            SUCCESS                 SUCCESS          SUCCESS   \n",
       "RGI60-01.10196            SUCCESS                 SUCCESS          SUCCESS   \n",
       "RGI60-01.10557            SUCCESS                 SUCCESS          SUCCESS   \n",
       "RGI60-01.10575            SUCCESS                 SUCCESS          SUCCESS   \n",
       "RGI60-01.10612            SUCCESS                 SUCCESS          SUCCESS   \n",
       "RGI60-01.10621            SUCCESS                 SUCCESS          SUCCESS   \n",
       "\n",
       "               thickness_to_gdir gridded_attributes_n  \\\n",
       "rgi_id                                                  \n",
       "RGI60-01.00570           SUCCESS              SUCCESS   \n",
       "RGI60-01.08989           SUCCESS              SUCCESS   \n",
       "RGI60-01.10006           SUCCESS              SUCCESS   \n",
       "RGI60-01.10196           SUCCESS              SUCCESS   \n",
       "RGI60-01.10557           SUCCESS              SUCCESS   \n",
       "RGI60-01.10575           SUCCESS              SUCCESS   \n",
       "RGI60-01.10612           SUCCESS              SUCCESS   \n",
       "RGI60-01.10621           SUCCESS              SUCCESS   \n",
       "\n",
       "               add_consensus_thickness_n velocity_to_gdir_n  \\\n",
       "rgi_id                                                        \n",
       "RGI60-01.00570                   SUCCESS            SUCCESS   \n",
       "RGI60-01.08989                   SUCCESS            SUCCESS   \n",
       "RGI60-01.10006                   SUCCESS            SUCCESS   \n",
       "RGI60-01.10196                   SUCCESS            SUCCESS   \n",
       "RGI60-01.10557                   SUCCESS            SUCCESS   \n",
       "RGI60-01.10575                   SUCCESS            SUCCESS   \n",
       "RGI60-01.10612                   SUCCESS            SUCCESS   \n",
       "RGI60-01.10621                   SUCCESS            SUCCESS   \n",
       "\n",
       "               thickness_to_gdir_n gridded_attributes_n.1  \\\n",
       "rgi_id                                                      \n",
       "RGI60-01.00570             SUCCESS                SUCCESS   \n",
       "RGI60-01.08989             SUCCESS                SUCCESS   \n",
       "RGI60-01.10006             SUCCESS                SUCCESS   \n",
       "RGI60-01.10196             SUCCESS                SUCCESS   \n",
       "RGI60-01.10557             SUCCESS                SUCCESS   \n",
       "RGI60-01.10575             SUCCESS                SUCCESS   \n",
       "RGI60-01.10612             SUCCESS                SUCCESS   \n",
       "RGI60-01.10621             SUCCESS                SUCCESS   \n",
       "\n",
       "               add_consensus_thickness_n.1 velocity_to_gdir_n.1  \\\n",
       "rgi_id                                                            \n",
       "RGI60-01.00570                     SUCCESS              SUCCESS   \n",
       "RGI60-01.08989                     SUCCESS              SUCCESS   \n",
       "RGI60-01.10006                     SUCCESS              SUCCESS   \n",
       "RGI60-01.10196                     SUCCESS              SUCCESS   \n",
       "RGI60-01.10557                     SUCCESS              SUCCESS   \n",
       "RGI60-01.10575                     SUCCESS              SUCCESS   \n",
       "RGI60-01.10612                     SUCCESS              SUCCESS   \n",
       "RGI60-01.10621                     SUCCESS              SUCCESS   \n",
       "\n",
       "               thickness_to_gdir_n.1 gridded_attributes_n.2  \\\n",
       "rgi_id                                                        \n",
       "RGI60-01.00570               SUCCESS                SUCCESS   \n",
       "RGI60-01.08989               SUCCESS                SUCCESS   \n",
       "RGI60-01.10006               SUCCESS                SUCCESS   \n",
       "RGI60-01.10196               SUCCESS                SUCCESS   \n",
       "RGI60-01.10557               SUCCESS                SUCCESS   \n",
       "RGI60-01.10575               SUCCESS                SUCCESS   \n",
       "RGI60-01.10612               SUCCESS                SUCCESS   \n",
       "RGI60-01.10621               SUCCESS                SUCCESS   \n",
       "\n",
       "               add_consensus_thickness_n.2 velocity_to_gdir_n.2  \\\n",
       "rgi_id                                                            \n",
       "RGI60-01.00570                     SUCCESS              SUCCESS   \n",
       "RGI60-01.08989                     SUCCESS              SUCCESS   \n",
       "RGI60-01.10006                     SUCCESS              SUCCESS   \n",
       "RGI60-01.10196                     SUCCESS              SUCCESS   \n",
       "RGI60-01.10557                     SUCCESS              SUCCESS   \n",
       "RGI60-01.10575                     SUCCESS              SUCCESS   \n",
       "RGI60-01.10612                     SUCCESS              SUCCESS   \n",
       "RGI60-01.10621                     SUCCESS              SUCCESS   \n",
       "\n",
       "               thickness_to_gdir_n.2 gridded_attributes_n  \\\n",
       "rgi_id                                                      \n",
       "RGI60-01.00570               SUCCESS                        \n",
       "RGI60-01.08989               SUCCESS                        \n",
       "RGI60-01.10006               SUCCESS                        \n",
       "RGI60-01.10196               SUCCESS                        \n",
       "RGI60-01.10557               SUCCESS                        \n",
       "RGI60-01.10575               SUCCESS                        \n",
       "RGI60-01.10612               SUCCESS                        \n",
       "RGI60-01.10621               SUCCESS                        \n",
       "\n",
       "               add_consensus_thickness_n velocity_to_gdir_n  \\\n",
       "rgi_id                                                        \n",
       "RGI60-01.00570                                                \n",
       "RGI60-01.08989                                                \n",
       "RGI60-01.10006                                                \n",
       "RGI60-01.10196                                                \n",
       "RGI60-01.10557                                                \n",
       "RGI60-01.10575                                                \n",
       "RGI60-01.10612                                                \n",
       "RGI60-01.10621                                                \n",
       "\n",
       "               thickness_to_gdir_n  \n",
       "rgi_id                              \n",
       "RGI60-01.00570                      \n",
       "RGI60-01.08989                      \n",
       "RGI60-01.10006                      \n",
       "RGI60-01.10196                      \n",
       "RGI60-01.10557                      \n",
       "RGI60-01.10575                      \n",
       "RGI60-01.10612                      \n",
       "RGI60-01.10621                      "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "task_log"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "fb4a315d-56b0-47d8-8bed-6b4870569aca",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_millan.to_csv('millan_statistics.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "a34301c9-8218-4e7c-8359-16dc3493994a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "rgi_region         2592\n",
       "rgi_subregion      2592\n",
       "rgi_area_km2       2592\n",
       "millan_vol_km3     2592\n",
       "millan_area_km2    2592\n",
       "millan_perc_cov    2592\n",
       "millan_avg_vel     1235\n",
       "millan_max_vel     1235\n",
       "dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(~ df_millan.isnull()).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "09748328-2efa-43f7-a8c3-76ad5c5bf45b",
   "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>rgi_region</th>\n",
       "      <th>rgi_subregion</th>\n",
       "      <th>rgi_area_km2</th>\n",
       "      <th>millan_vol_km3</th>\n",
       "      <th>millan_area_km2</th>\n",
       "      <th>millan_perc_cov</th>\n",
       "      <th>millan_avg_vel</th>\n",
       "      <th>millan_max_vel</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rgi_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RGI60-01.00570</th>\n",
       "      <td>01</td>\n",
       "      <td>01-02</td>\n",
       "      <td>17.567</td>\n",
       "      <td>1.380018</td>\n",
       "      <td>17.549046</td>\n",
       "      <td>0.998978</td>\n",
       "      <td>7.857373</td>\n",
       "      <td>50.500019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-01.08989</th>\n",
       "      <td>01</td>\n",
       "      <td>01-04</td>\n",
       "      <td>29.395</td>\n",
       "      <td>5.070058</td>\n",
       "      <td>29.147636</td>\n",
       "      <td>0.991585</td>\n",
       "      <td>16.232468</td>\n",
       "      <td>153.300903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-01.10006</th>\n",
       "      <td>01</td>\n",
       "      <td>01-04</td>\n",
       "      <td>219.444</td>\n",
       "      <td>48.965865</td>\n",
       "      <td>218.960000</td>\n",
       "      <td>0.997794</td>\n",
       "      <td>157.288147</td>\n",
       "      <td>2696.096924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-01.10196</th>\n",
       "      <td>01</td>\n",
       "      <td>01-04</td>\n",
       "      <td>427.281</td>\n",
       "      <td>125.213590</td>\n",
       "      <td>427.360000</td>\n",
       "      <td>1.000185</td>\n",
       "      <td>197.699814</td>\n",
       "      <td>1434.918701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-01.10557</th>\n",
       "      <td>01</td>\n",
       "      <td>01-04</td>\n",
       "      <td>307.521</td>\n",
       "      <td>66.722425</td>\n",
       "      <td>307.360000</td>\n",
       "      <td>0.999476</td>\n",
       "      <td>92.037796</td>\n",
       "      <td>627.021362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-04.07051</th>\n",
       "      <td>04</td>\n",
       "      <td>04-01</td>\n",
       "      <td>58.211</td>\n",
       "      <td>7.096113</td>\n",
       "      <td>55.988010</td>\n",
       "      <td>0.961812</td>\n",
       "      <td>9.595749</td>\n",
       "      <td>176.839325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-07.01323</th>\n",
       "      <td>07</td>\n",
       "      <td>07-01</td>\n",
       "      <td>12.723</td>\n",
       "      <td>0.697274</td>\n",
       "      <td>12.690000</td>\n",
       "      <td>0.997406</td>\n",
       "      <td>6.297728</td>\n",
       "      <td>35.770042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-03.04207</th>\n",
       "      <td>03</td>\n",
       "      <td>03-01</td>\n",
       "      <td>3.591</td>\n",
       "      <td>0.063339</td>\n",
       "      <td>3.278755</td>\n",
       "      <td>0.913048</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-03.03533</th>\n",
       "      <td>03</td>\n",
       "      <td>03-01</td>\n",
       "      <td>2.693</td>\n",
       "      <td>0.015570</td>\n",
       "      <td>1.723887</td>\n",
       "      <td>0.640136</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-01.17316</th>\n",
       "      <td>01</td>\n",
       "      <td>01-05</td>\n",
       "      <td>54.668</td>\n",
       "      <td>7.267350</td>\n",
       "      <td>54.375264</td>\n",
       "      <td>0.994645</td>\n",
       "      <td>34.153572</td>\n",
       "      <td>369.054230</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2592 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               rgi_region rgi_subregion  rgi_area_km2  millan_vol_km3  \\\n",
       "rgi_id                                                                  \n",
       "RGI60-01.00570         01         01-02        17.567        1.380018   \n",
       "RGI60-01.08989         01         01-04        29.395        5.070058   \n",
       "RGI60-01.10006         01         01-04       219.444       48.965865   \n",
       "RGI60-01.10196         01         01-04       427.281      125.213590   \n",
       "RGI60-01.10557         01         01-04       307.521       66.722425   \n",
       "...                   ...           ...           ...             ...   \n",
       "RGI60-04.07051         04         04-01        58.211        7.096113   \n",
       "RGI60-07.01323         07         07-01        12.723        0.697274   \n",
       "RGI60-03.04207         03         03-01         3.591        0.063339   \n",
       "RGI60-03.03533         03         03-01         2.693        0.015570   \n",
       "RGI60-01.17316         01         01-05        54.668        7.267350   \n",
       "\n",
       "                millan_area_km2  millan_perc_cov  millan_avg_vel  \\\n",
       "rgi_id                                                             \n",
       "RGI60-01.00570        17.549046         0.998978        7.857373   \n",
       "RGI60-01.08989        29.147636         0.991585       16.232468   \n",
       "RGI60-01.10006       218.960000         0.997794      157.288147   \n",
       "RGI60-01.10196       427.360000         1.000185      197.699814   \n",
       "RGI60-01.10557       307.360000         0.999476       92.037796   \n",
       "...                         ...              ...             ...   \n",
       "RGI60-04.07051        55.988010         0.961812        9.595749   \n",
       "RGI60-07.01323        12.690000         0.997406        6.297728   \n",
       "RGI60-03.04207         3.278755         0.913048             NaN   \n",
       "RGI60-03.03533         1.723887         0.640136             NaN   \n",
       "RGI60-01.17316        54.375264         0.994645       34.153572   \n",
       "\n",
       "                millan_max_vel  \n",
       "rgi_id                          \n",
       "RGI60-01.00570       50.500019  \n",
       "RGI60-01.08989      153.300903  \n",
       "RGI60-01.10006     2696.096924  \n",
       "RGI60-01.10196     1434.918701  \n",
       "RGI60-01.10557      627.021362  \n",
       "...                        ...  \n",
       "RGI60-04.07051      176.839325  \n",
       "RGI60-07.01323       35.770042  \n",
       "RGI60-03.04207             NaN  \n",
       "RGI60-03.03533             NaN  \n",
       "RGI60-01.17316      369.054230  \n",
       "\n",
       "[2592 rows x 8 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_millan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "0bc34340-c6bb-43af-8da8-39047c84d8d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2592"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(rgi_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "0664f973-d926-480f-88ce-ff0c0aec3c6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "rgi_df = utils.get_rgi_glacier_entities(rgi_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "07196a3c-b369-4fb1-8e46-581f5b3239bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "rgi_df.to_file('rgi_entities')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a004a5a4-805b-41d2-993b-1c12611c61ea",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
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