02_ATL07_processing.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Check available ATL03 files over Ross Sea"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Check available ATL03 files in ICESat-2 server (Ross Sea)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "READY TO GO\n"
     ]
    }
   ],
   "source": [
    "## Check available ATL03 data over Ross Sea and convert to csv files\n",
    "\n",
    "import os, sys\n",
    "import h5py\n",
    "from glob import glob\n",
    "import numpy as np\n",
    "import shutil\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.signal\n",
    "import datetime as dt\n",
    "import pandas as pd\n",
    "import netCDF4\n",
    "import time\n",
    "\n",
    "module_path = os.path.abspath(os.path.join('.'))\n",
    "if module_path not in sys.path:\n",
    "    sys.path.append(module_path)\n",
    "\n",
    "# make sure we're dealing with the most recent version of any code we're using\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "from readers.get_ATL10 import get_ATL10data\n",
    "from readers.getATL07 import getATL07\n",
    "\n",
    "data_dir='F:\\\\ATL03\\\\ATL07\\\\RossSea\\\\h5'\n",
    "lst = os.listdir(data_dir)\n",
    "lst = sorted(lst)\n",
    "\n",
    "first = True\n",
    "print(\"READY TO GO\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ATL07-02_20190201190211_05400201_004_01.h5',\n",
       " 'ATL07-02_20190216185428_07690201_004_01.h5',\n",
       " 'ATL07-02_20190301180351_09670201_004_01.h5',\n",
       " 'ATL07-02_20190309192128_10900201_004_01.h5',\n",
       " 'ATL07-02_20190313173850_11500201_004_01.h5',\n",
       " 'ATL07-02_20191005204240_01370501_004_01.h5',\n",
       " 'ATL07-02_20191006201700_01520501_004_01.h5',\n",
       " 'ATL07-02_20191008192541_01820501_004_01.h5',\n",
       " 'ATL07-02_20191009190002_01970501_004_01.h5',\n",
       " 'ATL07-02_20191014182603_02730501_004_01.h5',\n",
       " 'ATL07-02_20191017184322_03190501_004_01.h5',\n",
       " 'ATL07-02_20191018181743_03340501_004_01.h5',\n",
       " 'ATL07-02_20191019175205_03490501_004_01.h5',\n",
       " 'ATL07-02_20191021200922_03810501_004_01.h5',\n",
       " 'ATL07-02_20191024185224_04260501_004_01.h5',\n",
       " 'ATL07-02_20191025200102_04420501_004_01.h5',\n",
       " 'ATL07-02_20191026193522_04570501_004_01.h5',\n",
       " 'ATL07-02_20191027190943_04720501_004_01.h5',\n",
       " 'ATL07-02_20191028184403_04870501_004_01.h5',\n",
       " 'ATL07-02_20191031190122_05330501_004_01.h5',\n",
       " 'ATL07-02_20191103174424_05780501_004_01.h5',\n",
       " 'ATL07-02_20191103191842_05790501_004_01.h5',\n",
       " 'ATL07-02_20191104185303_05940501_004_01.h5',\n",
       " 'ATL07-02_20191106180144_06240501_004_01.h5',\n",
       " 'ATL07-02_20191107191022_06400501_004_01.h5',\n",
       " 'ATL07-02_20191111190203_07010501_004_01.h5',\n",
       " 'ATL07-02_20191113181045_07310501_004_01.h5',\n",
       " 'ATL07-02_20191115185345_07620501_004_01.h5',\n",
       " 'ATL07-02_20191116182805_07770501_004_01.h5',\n",
       " 'ATL07-02_20191117180226_07920501_004_01.h5',\n",
       " 'ATL07-02_20191118173646_08070501_004_01.h5',\n",
       " 'ATL07-02_20191123183704_08840501_004_01.h5',\n",
       " 'ATL07-02_20191206174623_10820501_004_01.h5',\n",
       " 'ATL07-02_20210209185529_07301001_004_01.h5',\n",
       " 'ATL07-02_20210215193007_08221001_004_01.h5',\n",
       " 'ATL07-02_20210216203845_08381001_004_01.h5',\n",
       " 'ATL07-02_20210218194727_08681001_004_01.h5',\n",
       " 'ATL07-02_20210219192149_08831001_004_01.h5',\n",
       " 'ATL07-02_20210224202206_09601001_004_01.h5',\n",
       " 'ATL07-02_20210304200528_10821001_004_01.h5',\n",
       " 'ATL07-02_20210305193948_10971001_004_01.h5',\n",
       " 'ATL07-02_20210306191409_11121001_004_01.h5',\n",
       " 'ATL07-02_20210307184829_11271001_004_01.h5',\n",
       " 'ATL07-02_20210308195707_11431001_004_01.h5',\n",
       " 'ATL07-02_20210309193128_11581001_004_01.h5',\n",
       " 'ATL07-02_20210310190548_11731001_004_01.h5',\n",
       " 'ATL07-02_20210318184907_12951001_004_01.h5',\n",
       " 'ATL07-02_20210322170632_13551001_004_01.h5',\n",
       " 'ATL07-02_20210324192348_13871001_004_01.h5']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191005204240_01370501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191006201700_01520501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191008192541_01820501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191009190002_01970501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191014182603_02730501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191017184322_03190501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191018181743_03340501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191019175205_03490501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191021200922_03810501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191024185224_04260501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191025200102_04420501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191026193522_04570501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191027190943_04720501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191028184403_04870501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191031190122_05330501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191103174424_05780501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191103191842_05790501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191104185303_05940501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191106180144_06240501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191107191022_06400501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191111190203_07010501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191113181045_07310501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191115185345_07620501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191116182805_07770501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191117180226_07920501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191118173646_08070501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191123183704_08840501_004_01.h5\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07_ATL07-02_20191206174623_10820501_004_01.h5\n"
     ]
    }
   ],
   "source": [
    "year = 2019\n",
    "csvlist = sorted(glob(\"F:\\\\ATL03\\\\ATL07\\\\RossSea\\\\ATL07_S2_{0}*.csv\".format(year)))\n",
    "df = pd.read_csv(csvlist[0])\n",
    "files = df['IS2_file'].unique()\n",
    "\n",
    "for file in files[:]:\n",
    "    filename = data_dir + \"\\\\ATL07_\" + file    \n",
    "    print(filename)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas\n",
    "from shapely.geometry import Point\n",
    "import time\n",
    "\n",
    "# Function to convert pandas dataframe to ESRI shapefile\n",
    "def convertshp(df, outfile):\n",
    "    '''\n",
    "    === input\n",
    "        - df: input pandas dataframe\n",
    "        - outfile: the nampe of the output shapefile\n",
    "    '''   \n",
    "\n",
    "    df=df.reset_index(drop=True)\n",
    "\n",
    "    if len(df) > 0:\n",
    "        df['geometry'] = df.apply(lambda x: Point((float(x.lon), float(x.lat))), axis=1)\n",
    "        collist = list(df.columns)\n",
    "        if 'time' in collist:\n",
    "            collist.remove('time')\n",
    "        df2 = df[collist]\n",
    "\n",
    "        df2 = geopandas.GeoDataFrame(df2, geometry='geometry')\n",
    "\n",
    "        # proj WGS84\n",
    "        df2.crs= \"+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs\"\n",
    "\n",
    "        df2.to_file(outfile, driver='ESRI Shapefile')\n",
    "\n",
    "    print('... converted to ' + outfile)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20190201190211_05400201_004_01.h5\n",
      "... ATL07 file was read (0.150 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20190201190211_05400201.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20190216185428_07690201_004_01.h5\n",
      "... ATL07 file was read (0.239 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20190216185428_07690201.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20190301180351_09670201_004_01.h5\n",
      "... ATL07 file was read (0.161 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20190301180351_09670201.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20190309192128_10900201_004_01.h5\n",
      "... ATL07 file was read (0.107 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20190309192128_10900201.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20190313173850_11500201_004_01.h5\n",
      "... ATL07 file was read (0.237 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20190313173850_11500201.shp\n",
      "==================================================================\n",
      "======================= FINISH ===================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191005204240_01370501_004_01.h5\n",
      "... ATL07 file was read (0.089 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191005204240_01370501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191006201700_01520501_004_01.h5\n",
      "... ATL07 file was read (0.213 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191006201700_01520501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191008192541_01820501_004_01.h5\n",
      "... ATL07 file was read (0.607 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191008192541_01820501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191009190002_01970501_004_01.h5\n",
      "... ATL07 file was read (0.563 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191009190002_01970501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191014182603_02730501_004_01.h5\n",
      "... ATL07 file was read (0.608 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191014182603_02730501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191017184322_03190501_004_01.h5\n",
      "... ATL07 file was read (0.834 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191017184322_03190501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191018181743_03340501_004_01.h5\n",
      "... ATL07 file was read (0.331 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191018181743_03340501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191019175205_03490501_004_01.h5\n",
      "... ATL07 file was read (0.605 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191019175205_03490501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191021200922_03810501_004_01.h5\n",
      "... ATL07 file was read (0.319 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191021200922_03810501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191024185224_04260501_004_01.h5\n",
      "... ATL07 file was read (0.040 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191024185224_04260501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191025200102_04420501_004_01.h5\n",
      "... ATL07 file was read (0.550 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191025200102_04420501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191026193522_04570501_004_01.h5\n",
      "... ATL07 file was read (0.673 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191026193522_04570501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191027190943_04720501_004_01.h5\n",
      "... ATL07 file was read (1.085 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191027190943_04720501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191028184403_04870501_004_01.h5\n",
      "... ATL07 file was read (0.310 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191028184403_04870501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191031190122_05330501_004_01.h5\n",
      "... ATL07 file was read (0.285 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191031190122_05330501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191103174424_05780501_004_01.h5\n",
      "... ATL07 file was read (0.643 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191103174424_05780501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191103191842_05790501_004_01.h5\n",
      "... ATL07 file was read (0.164 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191103191842_05790501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191104185303_05940501_004_01.h5\n",
      "... ATL07 file was read (0.570 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191104185303_05940501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191106180144_06240501_004_01.h5\n",
      "... ATL07 file was read (0.403 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191106180144_06240501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191107191022_06400501_004_01.h5\n",
      "... ATL07 file was read (0.855 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191107191022_06400501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191111190203_07010501_004_01.h5\n",
      "... ATL07 file was read (0.104 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191111190203_07010501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191113181045_07310501_004_01.h5\n",
      "... ATL07 file was read (0.769 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191113181045_07310501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191115185345_07620501_004_01.h5\n",
      "... ATL07 file was read (0.132 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191115185345_07620501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191116182805_07770501_004_01.h5\n",
      "... ATL07 file was read (0.211 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191116182805_07770501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191117180226_07920501_004_01.h5\n",
      "... ATL07 file was read (0.801 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191117180226_07920501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191118173646_08070501_004_01.h5\n",
      "... ATL07 file was read (0.504 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191118173646_08070501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191123183704_08840501_004_01.h5\n",
      "... ATL07 file was read (0.050 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191123183704_08840501.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20191206174623_10820501_004_01.h5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "... ATL07 file was read (0.747 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20191206174623_10820501.shp\n",
      "==================================================================\n",
      "======================= FINISH ===================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20210209185529_07301001_004_01.h5\n",
      "... ATL07 file was read (0.082 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20210209185529_07301001.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20210215193007_08221001_004_01.h5\n",
      "... ATL07 file was read (0.130 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20210215193007_08221001.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20210216203845_08381001_004_01.h5\n",
      "... ATL07 file was read (0.287 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20210216203845_08381001.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20210218194727_08681001_004_01.h5\n",
      "... ATL07 file was read (0.110 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20210218194727_08681001.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20210219192149_08831001_004_01.h5\n",
      "... ATL07 file was read (0.118 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20210219192149_08831001.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20210224202206_09601001_004_01.h5\n",
      "... ATL07 file was read (0.252 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20210224202206_09601001.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20210304200528_10821001_004_01.h5\n",
      "... ATL07 file was read (0.541 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20210304200528_10821001.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20210305193948_10971001_004_01.h5\n",
      "... ATL07 file was read (0.489 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20210305193948_10971001.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20210306191409_11121001_004_01.h5\n",
      "... ATL07 file was read (0.348 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20210306191409_11121001.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20210307184829_11271001_004_01.h5\n",
      "... ATL07 file was read (0.506 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20210307184829_11271001.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20210308195707_11431001_004_01.h5\n",
      "... ATL07 file was read (0.149 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20210308195707_11431001.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20210309193128_11581001_004_01.h5\n",
      "... ATL07 file was read (0.397 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20210309193128_11581001.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20210310190548_11731001_004_01.h5\n",
      "... ATL07 file was read (0.580 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20210310190548_11731001.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20210318184907_12951001_004_01.h5\n",
      "... ATL07 file was read (0.388 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20210318184907_12951001.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20210322170632_13551001_004_01.h5\n",
      "... ATL07 file was read (0.444 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20210322170632_13551001.shp\n",
      "==================================================================\n",
      "F:\\ATL03\\ATL07\\RossSea\\h5\\ATL07-02_20210324192348_13871001_004_01.h5\n",
      "... ATL07 file was read (0.565 s)\n",
      "... converted to F:\\ATL03\\ATL07\\RossSea\\shpfile\\ATL07-02_20210324192348_13871001.shp\n",
      "==================================================================\n",
      "======================= FINISH ===================================\n"
     ]
    }
   ],
   "source": [
    "# Read ATL03 file and convert for every valid files ============================\n",
    "\n",
    "for year in [2018, 2019, 2020]:\n",
    "    csvlist = sorted(glob(\"F:\\\\ATL03\\\\ATL07\\\\RossSea\\\\ATL07_S2_{0}*.csv\".format(year)))\n",
    "    df = pd.read_csv(csvlist[0])\n",
    "    files = df['IS2_file'].unique()\n",
    "\n",
    "    bbox = [170, -78, -140, -70] # Ross Sea\n",
    "    # bounding_box = [ll_lon, ll_lat, ur_lon, ur_lat]\n",
    "\n",
    "    for file in files[:]:\n",
    "        \n",
    "        filename = data_dir + \"\\\\\" + file\n",
    "        \n",
    "        if os.path.exists(filename):\n",
    "            print(filename)\n",
    "            first = True\n",
    "            \n",
    "            for beam_number in [0, 2, 4]:\n",
    "                t1 = time.time()\n",
    "                df07 = getATL07(filename, beam_number, bbox)\n",
    "                t2 = time.time()                              \n",
    "\n",
    "                if len(df07) > 100:\n",
    "                    beam = df07['beam'][0]\n",
    "                    \n",
    "                    if first:\n",
    "                        df = df07\n",
    "                        first = False\n",
    "                    else:\n",
    "                        df = df.append(df07).reset_index(drop=True)\n",
    "                        \n",
    "            print(\"... ATL07 file was read (%.3f s)\"%(t2-t1))\n",
    "            \n",
    "            # convert ATL03 dataframe to shpfile\n",
    "            shppath = \"F:\\\\ATL03\\\\ATL07\\\\RossSea\\\\shpfile\\\\\"\n",
    "            shpfile = shppath + file.replace('processed_', '').replace('_004_01.h5', '.shp')\n",
    "            convertshp(df, shpfile)\n",
    "\n",
    "            # save ATL03 dataframe as csvfile\n",
    "            csvpath = \"F:\\\\ATL03\\\\ATL07\\\\RossSea\\\\csv\\\\\"\n",
    "            csvfile = csvpath + file.replace('processed_', '').replace('_004_01.h5', '.csv')\n",
    "            df.to_csv(csvfile)\n",
    "                        \n",
    "        else:\n",
    "            print(\"No file: {0}\".format(file))\n",
    "\n",
    "        print(\"==================================================================\")\n",
    "    print(\"======================= FINISH ===================================\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>beam</th>\n",
       "      <th>lat</th>\n",
       "      <th>lon</th>\n",
       "      <th>x</th>\n",
       "      <th>deltatime</th>\n",
       "      <th>height</th>\n",
       "      <th>h_mean</th>\n",
       "      <th>h_median</th>\n",
       "      <th>h_diff</th>\n",
       "      <th>width</th>\n",
       "      <th>...</th>\n",
       "      <th>sic</th>\n",
       "      <th>stype</th>\n",
       "      <th>seg_len</th>\n",
       "      <th>time</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>hour</th>\n",
       "      <th>minute</th>\n",
       "      <th>second</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gt1l</td>\n",
       "      <td>-74.912118</td>\n",
       "      <td>-142.346222</td>\n",
       "      <td>3.178181e+07</td>\n",
       "      <td>3.428741e+07</td>\n",
       "      <td>0.756001</td>\n",
       "      <td>0.780208</td>\n",
       "      <td>0.728021</td>\n",
       "      <td>0.052187</td>\n",
       "      <td>0.433</td>\n",
       "      <td>...</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>11.359826</td>\n",
       "      <td>2019-02-01 20:17:07.045916</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>17</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gt1l</td>\n",
       "      <td>-74.912118</td>\n",
       "      <td>-142.346222</td>\n",
       "      <td>3.178181e+07</td>\n",
       "      <td>3.428741e+07</td>\n",
       "      <td>0.754282</td>\n",
       "      <td>0.780208</td>\n",
       "      <td>0.728021</td>\n",
       "      <td>0.052187</td>\n",
       "      <td>0.433</td>\n",
       "      <td>...</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>11.359826</td>\n",
       "      <td>2019-02-01 20:17:07.045916</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>17</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>gt1l</td>\n",
       "      <td>-74.912118</td>\n",
       "      <td>-142.346222</td>\n",
       "      <td>3.178181e+07</td>\n",
       "      <td>3.428741e+07</td>\n",
       "      <td>0.750790</td>\n",
       "      <td>0.780208</td>\n",
       "      <td>0.728021</td>\n",
       "      <td>0.052187</td>\n",
       "      <td>0.433</td>\n",
       "      <td>...</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>11.359826</td>\n",
       "      <td>2019-02-01 20:17:07.045916</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>17</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>gt1l</td>\n",
       "      <td>-74.912118</td>\n",
       "      <td>-142.346222</td>\n",
       "      <td>3.178181e+07</td>\n",
       "      <td>3.428741e+07</td>\n",
       "      <td>0.742948</td>\n",
       "      <td>0.780208</td>\n",
       "      <td>0.728021</td>\n",
       "      <td>0.052187</td>\n",
       "      <td>0.433</td>\n",
       "      <td>...</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>11.359826</td>\n",
       "      <td>2019-02-01 20:17:07.045916</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>17</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>gt1l</td>\n",
       "      <td>-74.912075</td>\n",
       "      <td>-142.346246</td>\n",
       "      <td>3.178181e+07</td>\n",
       "      <td>3.428741e+07</td>\n",
       "      <td>1.132964</td>\n",
       "      <td>1.182259</td>\n",
       "      <td>1.193998</td>\n",
       "      <td>-0.011739</td>\n",
       "      <td>0.922</td>\n",
       "      <td>...</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>12.080376</td>\n",
       "      <td>2019-02-01 20:17:07.046597</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>17</td>\n",
       "      <td>7</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",
       "      <td>...</td>\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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26169</th>\n",
       "      <td>gt1l</td>\n",
       "      <td>-73.540749</td>\n",
       "      <td>-143.077753</td>\n",
       "      <td>3.193647e+07</td>\n",
       "      <td>3.428743e+07</td>\n",
       "      <td>-0.014055</td>\n",
       "      <td>-0.034628</td>\n",
       "      <td>-0.018766</td>\n",
       "      <td>-0.015863</td>\n",
       "      <td>0.138</td>\n",
       "      <td>...</td>\n",
       "      <td>15.217178</td>\n",
       "      <td>8</td>\n",
       "      <td>52.485138</td>\n",
       "      <td>2019-02-01 20:17:28.950058</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>17</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26170</th>\n",
       "      <td>gt1l</td>\n",
       "      <td>-73.540531</td>\n",
       "      <td>-143.077865</td>\n",
       "      <td>3.193650e+07</td>\n",
       "      <td>3.428743e+07</td>\n",
       "      <td>-0.016704</td>\n",
       "      <td>-0.038302</td>\n",
       "      <td>-0.023945</td>\n",
       "      <td>-0.014356</td>\n",
       "      <td>0.116</td>\n",
       "      <td>...</td>\n",
       "      <td>15.173039</td>\n",
       "      <td>6</td>\n",
       "      <td>48.213905</td>\n",
       "      <td>2019-02-01 20:17:28.953516</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>17</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26171</th>\n",
       "      <td>gt1l</td>\n",
       "      <td>-73.540334</td>\n",
       "      <td>-143.077966</td>\n",
       "      <td>3.193652e+07</td>\n",
       "      <td>3.428743e+07</td>\n",
       "      <td>0.010272</td>\n",
       "      <td>-0.006134</td>\n",
       "      <td>0.001110</td>\n",
       "      <td>-0.007244</td>\n",
       "      <td>0.118</td>\n",
       "      <td>...</td>\n",
       "      <td>15.131452</td>\n",
       "      <td>6</td>\n",
       "      <td>45.298958</td>\n",
       "      <td>2019-02-01 20:17:28.956657</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>17</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26172</th>\n",
       "      <td>gt1l</td>\n",
       "      <td>-73.540132</td>\n",
       "      <td>-143.078070</td>\n",
       "      <td>3.193654e+07</td>\n",
       "      <td>3.428743e+07</td>\n",
       "      <td>-0.026252</td>\n",
       "      <td>-0.017687</td>\n",
       "      <td>-0.015570</td>\n",
       "      <td>-0.002117</td>\n",
       "      <td>0.129</td>\n",
       "      <td>...</td>\n",
       "      <td>15.093468</td>\n",
       "      <td>6</td>\n",
       "      <td>45.916336</td>\n",
       "      <td>2019-02-01 20:17:28.959872</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>17</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26173</th>\n",
       "      <td>gt1l</td>\n",
       "      <td>-73.539919</td>\n",
       "      <td>-143.078180</td>\n",
       "      <td>3.193657e+07</td>\n",
       "      <td>3.428743e+07</td>\n",
       "      <td>-0.074012</td>\n",
       "      <td>-0.094465</td>\n",
       "      <td>-0.084787</td>\n",
       "      <td>-0.009678</td>\n",
       "      <td>0.104</td>\n",
       "      <td>...</td>\n",
       "      <td>15.051645</td>\n",
       "      <td>1</td>\n",
       "      <td>48.724514</td>\n",
       "      <td>2019-02-01 20:17:28.963288</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>17</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>26174 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       beam        lat         lon             x     deltatime    height  \\\n",
       "0      gt1l -74.912118 -142.346222  3.178181e+07  3.428741e+07  0.756001   \n",
       "1      gt1l -74.912118 -142.346222  3.178181e+07  3.428741e+07  0.754282   \n",
       "2      gt1l -74.912118 -142.346222  3.178181e+07  3.428741e+07  0.750790   \n",
       "3      gt1l -74.912118 -142.346222  3.178181e+07  3.428741e+07  0.742948   \n",
       "4      gt1l -74.912075 -142.346246  3.178181e+07  3.428741e+07  1.132964   \n",
       "...     ...        ...         ...           ...           ...       ...   \n",
       "26169  gt1l -73.540749 -143.077753  3.193647e+07  3.428743e+07 -0.014055   \n",
       "26170  gt1l -73.540531 -143.077865  3.193650e+07  3.428743e+07 -0.016704   \n",
       "26171  gt1l -73.540334 -143.077966  3.193652e+07  3.428743e+07  0.010272   \n",
       "26172  gt1l -73.540132 -143.078070  3.193654e+07  3.428743e+07 -0.026252   \n",
       "26173  gt1l -73.539919 -143.078180  3.193657e+07  3.428743e+07 -0.074012   \n",
       "\n",
       "         h_mean  h_median    h_diff  width  ...         sic  stype    seg_len  \\\n",
       "0      0.780208  0.728021  0.052187  0.433  ...  100.000000      1  11.359826   \n",
       "1      0.780208  0.728021  0.052187  0.433  ...  100.000000      1  11.359826   \n",
       "2      0.780208  0.728021  0.052187  0.433  ...  100.000000      1  11.359826   \n",
       "3      0.780208  0.728021  0.052187  0.433  ...  100.000000      1  11.359826   \n",
       "4      1.182259  1.193998 -0.011739  0.922  ...  100.000000      1  12.080376   \n",
       "...         ...       ...       ...    ...  ...         ...    ...        ...   \n",
       "26169 -0.034628 -0.018766 -0.015863  0.138  ...   15.217178      8  52.485138   \n",
       "26170 -0.038302 -0.023945 -0.014356  0.116  ...   15.173039      6  48.213905   \n",
       "26171 -0.006134  0.001110 -0.007244  0.118  ...   15.131452      6  45.298958   \n",
       "26172 -0.017687 -0.015570 -0.002117  0.129  ...   15.093468      6  45.916336   \n",
       "26173 -0.094465 -0.084787 -0.009678  0.104  ...   15.051645      1  48.724514   \n",
       "\n",
       "                            time  year  month  day  hour  minute  second  \n",
       "0     2019-02-01 20:17:07.045916  2019      2    1    20      17       7  \n",
       "1     2019-02-01 20:17:07.045916  2019      2    1    20      17       7  \n",
       "2     2019-02-01 20:17:07.045916  2019      2    1    20      17       7  \n",
       "3     2019-02-01 20:17:07.045916  2019      2    1    20      17       7  \n",
       "4     2019-02-01 20:17:07.046597  2019      2    1    20      17       7  \n",
       "...                          ...   ...    ...  ...   ...     ...     ...  \n",
       "26169 2019-02-01 20:17:28.950058  2019      2    1    20      17      28  \n",
       "26170 2019-02-01 20:17:28.953516  2019      2    1    20      17      28  \n",
       "26171 2019-02-01 20:17:28.956657  2019      2    1    20      17      28  \n",
       "26172 2019-02-01 20:17:28.959872  2019      2    1    20      17      28  \n",
       "26173 2019-02-01 20:17:28.963288  2019      2    1    20      17      28  \n",
       "\n",
       "[26174 rows x 28 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F:\\ATL03\\ATL03\\RossSea\\h5\\ATL03_20191014192611_02730510_004_01.h5\n",
      "... ATL03 file was read (2214.758 s)\n",
      "... ATL03 file was resampled (2227.519 s)\n",
      "... First photon bias correction (2229.750 s)\n",
      "... MSS was added (3178.510 s)\n",
      "... converted to F:\\ATL03\\ATL03\\RossSea\\shpfile\\ATL03_20191014192611_02730510_gt3r.shp\n",
      "... ATL03 file was read (2195.052 s)\n",
      "... ATL03 file was resampled (2216.734 s)\n",
      "... First photon bias correction (2219.835 s)\n",
      "... MSS was added (3170.387 s)\n",
      "... converted to F:\\ATL03\\ATL03\\RossSea\\shpfile\\ATL03_20191014192611_02730510_gt2r.shp\n"
     ]
    }
   ],
   "source": [
    "# Read ATL03 file and convert for every valid files ============================\n",
    "\n",
    "for year in [2019]:\n",
    "    csvlist = sorted(glob(\"F:\\\\ATL03\\\\ATL03\\\\RossSea\\\\ATL03_S2_{0}*.csv\".format(year)))\n",
    "    df = pd.read_csv(csvlist[0])\n",
    "    files = df['ATL03_file'].unique()\n",
    "\n",
    "    bbox = [170, -78, -140, -70] # Ross Sea\n",
    "    # bounding_box = [ll_lon, ll_lat, ur_lon, ur_lat]\n",
    "\n",
    "    for file in files[:]:\n",
    "        \n",
    "        filename = data_dir + \"\\\\\" + file\n",
    "\n",
    "        if os.path.exists(filename):\n",
    "            print(filename)\n",
    "\n",
    "            for beam_number in [0, 2, 4]:\n",
    "                t1 = time.time()\n",
    "                df03 = getATL03(filename, beam_number, bbox)\n",
    "                t2 = time.time()\n",
    "                print(\"... ATL03 file was read (%.3f s)\"%(t2-t1))\n",
    "\n",
    "                if len(df03) > 100:\n",
    "                    beam = df03['beam'][0]\n",
    "\n",
    "                    stats = ['mean', 'sd', 'med'] # calculated statistical parameters\n",
    "                    variables = ['height', 'pcnt', 'pcnth', 'bcnt', 'brate'] # calculated variables\n",
    "                    df_sam1 = sampling_ATL03(df03, stats, variables)\n",
    "                    t2 = time.time()\n",
    "                    print(\"... ATL03 file was resampled (%.3f s)\"%(t2-t1))\n",
    "\n",
    "                    if len(df_sam1) > 100:\n",
    "                        # the sampling process is done based on high-confidence photons (conf >= 3)\n",
    "\n",
    "                        # First photon bias correction\n",
    "                        correction = fpb_correction(filename, beam, df_sam1['pcnt_mean'])\n",
    "                        df_sam1['fpb_corr'] = correction\n",
    "                        t2 = time.time()\n",
    "                        print(\"... First photon bias correction (%.3f s)\"%(t2-t1))\n",
    "\n",
    "                        # Add MSS\n",
    "                        if df_sam1['lat'][0] < 0:\n",
    "                            ncfile = r\"F:\\\\ATL03\\\\ATL03\\\\MSS\\\\mss_antarc.nc\"\n",
    "                        else:\n",
    "                            ncfile = r\"F:\\\\ATL03\\\\ATL03\\\\MSS\\\\mss_arctic.nc\"\n",
    "                        # MSS boundary\n",
    "                        maxlat = df_sam1['lat'].max()\n",
    "                        minlat = df_sam1['lat'].min()\n",
    "                        maxlon = df_sam1['lon'].max()\n",
    "                        minlon = df_sam1['lon'].min()\n",
    "                        df_sam = add_MSS(df_sam1, ncfile, maxlat, minlat, maxlon, minlon)\n",
    "                        t2 = time.time()\n",
    "                        print(\"... MSS was added (%.3f s)\"%(t2-t1))\n",
    "\n",
    "                        df_sam['h_cor_mean'] = df_sam['height_mean'] - df_sam['tide'] - df_sam['mss'] - df_sam['fpb_corr']\n",
    "                        df_sam['h_cor_med'] = df_sam['height_med'] - df_sam['tide'] - df_sam['mss'] - df_sam['fpb_corr']\n",
    "\n",
    "                        # convert ATL03 dataframe to shpfile\n",
    "                        shppath = \"F:\\\\ATL03\\\\ATL03\\\\RossSea\\\\shpfile\\\\\"\n",
    "                        shpfile = shppath + os.path.basename(filename).replace('processed_', '')\\\n",
    "                        .replace('004_01.h5', '{0}.shp'.format(beam))\n",
    "                        convertshp(df_sam, shpfile)\n",
    "\n",
    "                        # save ATL03 dataframe as csvfile\n",
    "                        csvpath = \"F:\\\\ATL03\\\\ATL03\\\\RossSea\\\\csv\\\\\"\n",
    "                        csvfile = csvpath + os.path.basename(filename).replace('processed_', '')\\\n",
    "                        .replace('004_01.h5', '{0}.csv'.format(beam))\n",
    "                        df_sam.to_csv(csvfile)\n",
    "                        \n",
    "                        del df_sam1, df03, correction\n",
    "\n",
    "            print(\"==================================================================\")\n",
    "    print(\"======================= FINISH ===================================\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x25183229880>"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(df_sam['h_cor_med'], df_sam['h_cor_mean'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x251812c1fd0>]"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(df_sam['x'], df_sam['height_mean'], '.')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}