notebooks/analysis/Glacier_description_table.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "09547d46-4f44-425e-972c-c7868a320406",
   "metadata": {},
   "source": [
    "## Notebook Purpose\n",
    "This notebook is used to pull out statistics for glacier description in the study site table (Table 1).  \n",
    "\n",
    "#### Last updated: May 23, 2023\n",
    "\n",
    "## TODO:\n",
    "- Update imports when new library has been built up with all updates\n",
    "-Generalise path to data products during revisions, after the data distribution plan is finalized\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4840694b-ea9f-465c-807b-3ab2477fb495",
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "%config InlineBackend.figure_format='retina'\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a26bc9e8-58ac-49db-9027-e9ce6f58d9a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np \n",
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "from imview import pltlib\n",
    "import pandas as pd\n",
    "from pygeotools.lib import warplib,geolib,iolib,malib,filtlib,timelib\n",
    "import os,sys,glob,shutil\n",
    "from debris_cover_smb import glac_dyn, constants, geospatial"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd79cdba-06aa-4eea-b0ff-faa33f26a366",
   "metadata": {},
   "source": [
    "## Ngozumpa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d168acba-e9e4-481f-8f2f-ed5132da2fbf",
   "metadata": {},
   "outputs": [],
   "source": [
    "glac_name = 'ngozumpa'\n",
    "shp = gpd.read_file(constants.fetch_glac_shp(constants.rgi_dicts[glac_name])).to_crs('EPSG:32645')\n",
    "glac_thick_ds = iolib.fn_getds(constants.fetch_farinotti_thickness(glac_name))\n",
    "res = geolib.get_res(glac_thick_ds)[0]\n",
    "glac_thick = iolib.ds_getma(glac_thick_ds)\n",
    "deb_thick_ds = iolib.fn_getds(constants.fetch_rounce_debris_thickness(glac_name))\n",
    "res_deb = geolib.get_res(deb_thick_ds)[0]\n",
    "deb_thick = iolib.ds_getma(deb_thick_ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c311c8c1-f157-4515-acb6-06c4d06c4ba0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    5815\n",
       "Name: Zmed, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shp.Zmed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ca1f56bc-ed4a-44d0-9f85-c1b68f72af11",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.999331\n",
       "dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shp.area/(glac_thick.count()*res*res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bde2deef-b6ff-4369-8dad-6e1461a21e96",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "61.0475"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glac_thick.count()*res*res*1e-6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c8341d71-15bf-4555-8988-975cdba91943",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19.088549999999998"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deb_thick.count()*res_deb*res_deb*1e-6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7b214f04-fbd4-4146-8959-c685955e61ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    31.289294\n",
       "dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((deb_thick.count()*res_deb*res_deb)/shp.area)*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "63aa6397-225a-445a-9bbd-67e2195880f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.02812129, 0.13449664, 0.47741808, 1.78103662, 3.        ])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.nanpercentile(deb_thick.compressed(),(5,16,50,84,95))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12e9c77a-b4a7-4300-8a23-068026b4d851",
   "metadata": {},
   "source": [
    "# Khumbu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7aa579e5-7637-48e6-86cb-1a9e5a5051bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "glac_name = 'khumbu'\n",
    "shp = gpd.read_file(constants.fetch_glac_shp(constants.rgi_dicts[glac_name])).to_crs('EPSG:32645')\n",
    "glac_thick_ds = iolib.fn_getds(constants.fetch_farinotti_thickness(glac_name))\n",
    "res = geolib.get_res(glac_thick_ds)[0]\n",
    "glac_thick = iolib.ds_getma(glac_thick_ds)\n",
    "deb_thick_ds = iolib.fn_getds(constants.fetch_rounce_debris_thickness(glac_name))\n",
    "res_deb = geolib.get_res(deb_thick_ds)[0]\n",
    "deb_thick = iolib.ds_getma(deb_thick_ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e53b17bd-d34d-4e4e-8b77-f4dc68d2fcd0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    5568\n",
       "Name: Zmed, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shp.Zmed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6480520a-d14b-454d-9b57-1a409ca23b2d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19.0825"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glac_thick.count()*res*res*1e-6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "44801e12-2341-485c-8b07-51de07c36449",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    19.081582\n",
       "dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shp.area*1e-6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "732f7a51-f831-4c83-85b9-1a0dc5b72db9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.352694"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deb_thick.count()*res_deb*res_deb*1e-6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5a6b902b-2ed4-4b67-856c-dff9f2645fcb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    38.532937\n",
       "dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((deb_thick.count()*res_deb*res_deb)/shp.area)*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "cf032e07-0bfe-482d-8de8-ad0216a47480",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.0162879 , 0.06124099, 0.29475071, 1.7283973 , 3.        ])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.nanpercentile(deb_thick.compressed(),(5,16,50,84,95))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "143bb71a-77a9-4dbd-aeff-3b871d81baf9",
   "metadata": {},
   "source": [
    "# Imja"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b8de8146-4103-40a3-9b6c-feb05cee98e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "glac_name = 'imja'\n",
    "shp = gpd.read_file(constants.fetch_glac_shp(constants.rgi_dicts[glac_name])).to_crs('EPSG:32645')\n",
    "glac_thick_ds = iolib.fn_getds(constants.fetch_farinotti_thickness(glac_name))\n",
    "res = geolib.get_res(glac_thick_ds)[0]\n",
    "glac_thick = iolib.ds_getma(glac_thick_ds)\n",
    "deb_thick_ds = iolib.fn_getds(constants.fetch_rounce_debris_thickness(glac_name))\n",
    "res_deb = geolib.get_res(deb_thick_ds)[0]\n",
    "deb_thick = iolib.ds_getma(deb_thick_ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "572e73f0-e141-45da-95b9-5b4516fb9b1f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    5366\n",
       "Name: Zmed, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shp.Zmed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7fc92bbd-1816-4c0e-8372-86de06d35ea2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    14.254544\n",
       "dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shp.area*1e-6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "85ec227e-dc89-478e-8260-8d75ec9c3fcb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14.259374999999999"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glac_thick.count()*res*res*1e-6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "79dcd5eb-7214-4a54-9779-b4a650122eeb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    40.749617\n",
       "dtype: float64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((deb_thick.count()*res_deb*res_deb)/shp.area)*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d317db99-fa3d-4810-b68c-ec53856c441f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.0326701 , 0.09261377, 0.31181386, 0.53447376, 0.83649198])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.nanpercentile(deb_thick.compressed(),(5,16,50,84,95))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d03e8a5a-c9ab-4596-a49b-26d3e258051f",
   "metadata": {},
   "source": [
    "# Langtang"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "65204c69-abdc-4e16-a6b6-4cf66105226b",
   "metadata": {},
   "outputs": [],
   "source": [
    "glac_name = 'langtang'\n",
    "shp = gpd.read_file(constants.fetch_glac_shp(constants.rgi_dicts[glac_name])).to_crs('EPSG:32645')\n",
    "glac_thick_ds = iolib.fn_getds(constants.fetch_farinotti_thickness(glac_name))\n",
    "res = geolib.get_res(glac_thick_ds)[0]\n",
    "glac_thick = iolib.ds_getma(glac_thick_ds)\n",
    "deb_thick_ds = iolib.fn_getds(constants.fetch_rounce_debris_thickness(glac_name))\n",
    "res_deb = geolib.get_res(deb_thick_ds)[0]\n",
    "deb_thick = iolib.ds_getma(deb_thick_ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "09e05a58-34e2-4394-a0f6-891003e2abe4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    5343\n",
       "Name: Zmed, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shp.Zmed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f0ec7a80-c75c-4295-a5e2-a6f8e9fcd32a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    37.776506\n",
       "dtype: float64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shp.area*1e-6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "18a00c75-afd7-42b2-b05c-d936b46375fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    44.748876\n",
       "dtype: float64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((deb_thick.count()*res_deb*res_deb)/shp.area)*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7f43dcbb-78c0-44a2-bce4-2596743426ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.04004339, 0.20279822, 0.67204264, 1.49267059, 3.        ])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.nanpercentile(deb_thick.compressed(),(5,16,50,84,95))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "945e1edc-5f92-4ca2-b066-f8e9d58c50ae",
   "metadata": {},
   "source": [
    "# Lirung"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "28242640-5040-457a-86e3-6ac538d3bc05",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "debris thickness not found, will return extrap product\n"
     ]
    }
   ],
   "source": [
    "glac_name = 'lirung'\n",
    "shp = gpd.read_file(constants.fetch_glac_shp(constants.rgi_dicts[glac_name])).to_crs('EPSG:32645')\n",
    "glac_thick_ds = iolib.fn_getds(constants.fetch_farinotti_thickness(glac_name))\n",
    "res = geolib.get_res(glac_thick_ds)[0]\n",
    "glac_thick = iolib.ds_getma(glac_thick_ds)\n",
    "deb_thick_ds = iolib.fn_getds(constants.fetch_rounce_debris_thickness(glac_name))\n",
    "res_deb = geolib.get_res(deb_thick_ds)[0]\n",
    "deb_thick = iolib.ds_getma(deb_thick_ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "94420184-1820-4cb9-a1db-2ec8df316fa0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    4255\n",
       "Name: Zmed, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shp.Zmed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d669ca14-97c6-4d94-b3b0-ab3ec14225ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1.459637\n",
       "dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shp.area*1e-6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "8d2f7de9-b0b0-4db5-800b-57b1f150ae41",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.415232"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deb_thick.count()*res_deb*res_deb*1e-6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bcb638ba-c27c-4e63-9f5c-07545a83791a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "445bb91a-179e-4ba2-b784-d34a936ec006",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "97.09996569468268"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((deb_thick.count()*res_deb*res_deb)/(glac_thick.count()*res*res))*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "44b8b4de-9784-4947-9381-493b6e052b36",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.15286841, 0.21394299, 0.3619173 , 0.53262957, 0.6263999 ])"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.nanpercentile(deb_thick.compressed(),(5,16,50,84,95))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb4f5d94-33b7-4c40-88c2-7ab101e875cd",
   "metadata": {},
   "source": [
    "# Changri Nup (Black Changri Nup)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ba7a1791-f65c-4dc4-b072-8e358eec4b46",
   "metadata": {},
   "outputs": [],
   "source": [
    "glac_name = 'changri_nup'\n",
    "dem1_fn = '/nobackup/sbhusha1/chapter2/HighresDebrisCover_SMB_Data/BlackChangriNup/dem/20151102_0517_10400100125E8E00_10400100130D8500_align.tif'\n",
    "shp = gpd.read_file(constants.fetch_glac_shp(constants.rgi_dicts[glac_name])).to_crs('EPSG:32645')\n",
    "dem1_ds = iolib.fn_getds(dem1_fn)\n",
    "glac_thick_ds = iolib.fn_getds(constants.fetch_farinotti_thickness(glac_name))\n",
    "res = geolib.get_res(glac_thick_ds)[0]\n",
    "glac_thick = iolib.ds_getma(glac_thick_ds)\n",
    "deb_thick_ds = iolib.fn_getds(constants.fetch_rounce_debris_thickness(glac_name))\n",
    "res_deb = geolib.get_res(deb_thick_ds)[0]\n",
    "deb_thick = iolib.ds_getma(deb_thick_ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "0716abf5-fab3-4d8b-add7-cf7ac246b936",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Warping all inputs to the following:\n",
      "Resolution: 25.0\n",
      "Extent: [476612.5, 3094162.5, 482987.5, 3099437.5]\n",
      "Projection: '+proj=utm +zone=45 +datum=WGS84 +units=m +no_defs'\n",
      "Resampling alg: cubic\n",
      "\n",
      "1 of 3: /nobackupp11/sbhusha1/reference_data/farinotti_2019_ice_thickness/RGI60-15/RGI60-15.03734_thickness.tif\n",
      "2 of 3: /nobackupp11/sbhusha1/reference_data/debris_thickness/HMA_DTE_15.03734_hdts_m.tif\n",
      "nl: 211 ns: 255 res: 25.000\n",
      "0...10...20...30...40...50...60...70...80...90...3 of 3: /nobackup/sbhusha1/chapter2/HighresDebrisCover_SMB_Data/BlackChangriNup/dem/20151102_0517_10400100125E8E00_10400100130D8500_align.tif\n",
      "nl: 211 ns: 255 res: 25.000\n",
      "100 - done.\n",
      "0...10...20...30...40...50...60...70...80...90..."
     ]
    }
   ],
   "source": [
    "ds_list = warplib.memwarp_multi([glac_thick_ds,deb_thick_ds,dem1_ds])\n",
    "res,res_deb = geolib.get_res(ds_list[0])\n",
    "glac_thick,deb_thick,dem1 = [iolib.ds_getma(ds) for ds in ds_list]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "264d3f15-7feb-40c5-825b-c412ede769a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "glac_shp = gpd.read_file('/nobackup/sbhusha1/hma/agu22_scratch/Black_changri_with_accumulation_area2.shp')\n",
    "glac_thick_ma = geospatial.mask_by_shp(glac_shp.geometry,glac_thick,ds_list[0])\n",
    "deb_thick_ma = geospatial.mask_by_shp(glac_shp.geometry,deb_thick,ds_list[1])\n",
    "dem1_ma = geospatial.mask_by_shp(glac_shp.geometry,dem1,ds=ds_list[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b5e5b837-20da-4561-a1cc-704d7513e5c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f05f1b54-bf26-4a93-9544-d0e591afd8a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 470,
       "width": 625
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pltlib.iv(dem1_ma)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "5b2092dd-e3dc-469e-a88c-eb5c2bc82758",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5467.727"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.ma.median(dem1_ma)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "1815ad2d-357e-46f0-a1d4-4a801a1f8b55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.26125"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deb_thick_ma.count()*res_deb*res_deb*1e-6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "52046d43-d02f-4016-aef2-1bbfc9dd3957",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25.0"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res_deb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "42333a6a-4817-459a-9891-c81642a10703",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25.0"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "d0a4a867-de6e-4fbf-9d5c-1389b704f7e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "53.358011634056055"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((deb_thick_ma.count()*res_deb*res_deb)/(glac_thick_ma.count()*res*res))*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "438e5753-cc94-44ef-a03b-c0ed22f612d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.09340205, 0.29517524, 0.92171839, 3.        , 3.        ])"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.nanpercentile(deb_thick.compressed(),(5,16,50,84,95))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "b555c1bb-ed16-47c9-951d-265e5909a8aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'count': 11724,\n",
       " 'min': 0.0032886057160794735,\n",
       " 'max': 3.1680309772491455,\n",
       " 'ptp': 3.1647424697875977,\n",
       " 'mean': 1.343993825297558,\n",
       " 'std': 1.081438807939735,\n",
       " 'nmad': 0.9556243604063988,\n",
       " 'med': 0.9217183887958527,\n",
       " 'median': 0.9217183887958527,\n",
       " 'p16': 0.295175244808197,\n",
       " 'p84': 3.0,\n",
       " 'spread': 1.3524123775959014,\n",
       " 'mode': 3.0}"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "malib.get_stats_dict(deb_thick.compressed())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bcc190c4-6180-4045-93ca-559d343f6245",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "655d0d0e-6015-4ac9-a819-548c75f8c830",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "46579b13-1ad0-4b86-9092-6472c80fbdab",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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