{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "907dfa6a",
   "metadata": {},
   "source": [
    "# Use of CODA on the VRE\n",
    "\n",
    "## Example of CODA Atmospheric Toolbox use (S&T Corp)\n",
    "\n",
    "> Abstract: Using pre-installed and configured CODA software to access data from original Aeolus products"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a14c58e-2252-43b6-bdb9-ddbd6fcc0e09",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Load packages, modules and extensions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a12b9e67-e2d9-49e9-9ac7-47585a5c9c31",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-11T10:18:37.596284Z",
     "iopub.status.busy": "2024-01-11T10:18:37.596116Z",
     "iopub.status.idle": "2024-01-11T10:18:38.614696Z",
     "shell.execute_reply": "2024-01-11T10:18:38.614151Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Python implementation: CPython\n",
      "Python version       : 3.9.7\n",
      "IPython version      : 8.0.1\n",
      "\n",
      "viresclient: 0.11.0\n",
      "pandas     : 1.4.1\n",
      "xarray     : 0.21.1\n",
      "matplotlib : 3.5.1\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# enable following line for interactive visualization backend for matplotlib\n",
    "# %matplotlib widget\n",
    "# print version info\n",
    "%load_ext watermark\n",
    "%watermark -i -v -p viresclient,pandas,xarray,matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1d8abffb-59f9-43a0-88bc-98266f34db52",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-11T10:18:38.616861Z",
     "iopub.status.busy": "2024-01-11T10:18:38.616728Z",
     "iopub.status.idle": "2024-01-11T10:18:39.050847Z",
     "shell.execute_reply": "2024-01-11T10:18:39.050358Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from viresclient import AeolusRequest\n",
    "\n",
    "import os\n",
    "import tarfile\n",
    "import getpass\n",
    "import fnmatch\n",
    "from ftplib import FTP\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "# Configuration of CODA path not needed in VRE, might be required\n",
    "# when using in other environments, example left here as reference\n",
    "# os.putenv('CODA_DEFINITION', '/usr/share/coda/definitions/')\n",
    "\n",
    "# Importing python bindings for coda, they are pre installed and available\n",
    "import coda"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9f8440d-50bd-4250-90a8-714f15c75738",
   "metadata": {},
   "source": [
    "## Atmospheric Toolbox CODA\n",
    "\n",
    "CODA allows direct reading access to local product files, supporting a wide range of products among them support for Aeolus products.\n",
    "\n",
    "\n",
    "Links of interest:\n",
    " - Main site: https://atmospherictoolbox.org/coda/\n",
    " - Documentation: http://stcorp.github.io/coda/doc/html/index.html\n",
    " - Github repository: https://github.com/stcorp/coda\n",
    " - Aeolus CODA definition: https://github.com/stcorp/codadef-aeolus\n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90e1f9c9",
   "metadata": {},
   "source": [
    "## Retrieval of original Aelous product\n",
    "\n",
    "The easiest approach to access Aeolus data is through the use of the VirES service as explained thoroughly in most examples of the documentation.\n",
    "\n",
    "If however you have a special case where you need to access Aeolus data in its original Earth Explorer format the VRE is pre-configured to allow the use of CODA. This means if you generated test files with custom processors you can upload them to your VRE workspace and work with them.\n",
    "\n",
    "In order to show how to access information on products in the Aeolus format we fetch one example file from the ADDF. For your use case you can skip this step and use your own file uploaded to the workspace."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "bbefda20-bcaf-4926-ae9f-a72ce06582a7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-11T10:18:39.053615Z",
     "iopub.status.busy": "2024-01-11T10:18:39.053455Z",
     "iopub.status.idle": "2024-01-11T10:18:39.057791Z",
     "shell.execute_reply": "2024-01-11T10:18:39.057318Z"
    }
   },
   "outputs": [],
   "source": [
    "# Example file to fetch\n",
    "filename = \"AE_OPER_ALD_U_N_1B_20211126T091705022_005400014_018894_0001\"\n",
    "\n",
    "# Get user folder and set/create folder for example files\n",
    "user_folder = os.path.expanduser(\"~\")\n",
    "example_folder = os.path.join(user_folder, \"files/examples\")\n",
    "os.makedirs(example_folder, exist_ok=True)\n",
    "\n",
    "# Check if file is already available\n",
    "example_file_path_exists = False\n",
    "for file in os.listdir(example_folder):\n",
    "    if fnmatch.fnmatch(file, \"*{}*.DBL\".format(filename)):\n",
    "        example_file_path = os.path.join(example_folder, file)\n",
    "        example_file_path_exists = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b534007a-aa16-4230-ad3b-3dfd58bcc9d9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-11T10:18:39.060061Z",
     "iopub.status.busy": "2024-01-11T10:18:39.059766Z",
     "iopub.status.idle": "2024-01-11T10:18:46.928278Z",
     "shell.execute_reply": "2024-01-11T10:18:46.927750Z"
    }
   },
   "outputs": [],
   "source": [
    "if not example_file_path_exists:\n",
    "    # Set user and password from ESA SSO account\n",
    "    USERNAME = os.environ[\"DATAU\"]\n",
    "    PW = os.environ[\"DATAP\"]\n",
    "    # Uncomment following two lines to provide your credentials as input\n",
    "    # USERNAME = input(\"Please enter your SSO user name:\")\n",
    "    # PW = getpass.getpass(\"Please enter your password:\")\n",
    "\n",
    "    # Connect to the ADDF FTP server\n",
    "    ftp = FTP(\"aeolus-ds.eo.esa.int\")\n",
    "    ftp.login(user=USERNAME, passwd=PW)\n",
    "\n",
    "    # change directory\n",
    "    ftp.cwd(\"/ADDF/L1B_preliminary_products/ALD_U_N_1B/1B12/2021-11/26/\")\n",
    "\n",
    "    # get file list of directory\n",
    "    file_list = ftp.nlst()\n",
    "\n",
    "    # check if example file is available and set file name\n",
    "    try:\n",
    "        example_filename = [k for k in file_list if filename in k][0]\n",
    "    except:\n",
    "        print(\"Warning: Example file not found\")\n",
    "        assert False\n",
    "\n",
    "    # Download example file to user space\n",
    "    example_file_packed_path = os.path.join(example_folder, example_filename)\n",
    "    with open(example_file_packed_path, \"wb\") as fp:\n",
    "        ftp.retrbinary(\"RETR \" + example_filename, fp.write)\n",
    "\n",
    "    # close FTP connection\n",
    "    ftp.quit()\n",
    "\n",
    "    # Open received compressed file\n",
    "    tar = tarfile.open(example_file_packed_path, \"r:gz\")\n",
    "    \n",
    "    # Define file name for DBL-File\n",
    "    example_file_name_unpacked = example_filename.split(\".\")[0] + \".DBL\"\n",
    "\n",
    "    # Extract only the .DBL file\n",
    "    tar.extract(example_file_name_unpacked, path=example_folder)\n",
    "    tar.close()\n",
    "    \n",
    "    # Define file path for extracted DBL-File\n",
    "    example_file_path = os.path.join(example_folder, example_file_name_unpacked)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47a9bb44-bc74-47ae-a6e3-2068fac80c6a",
   "metadata": {},
   "source": [
    "## Opening file with CODA\n",
    "Now that we have retrieved (or uploaded the file) we can use the pre-configured CODA python bindings to open the Aeolus product and access the available parameters using their paths.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bfa8185b-7c7c-4572-8dbd-723903a2fe68",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-11T10:18:46.930547Z",
     "iopub.status.busy": "2024-01-11T10:18:46.930401Z",
     "iopub.status.idle": "2024-01-11T10:18:46.940052Z",
     "shell.execute_reply": "2024-01-11T10:18:46.939595Z"
    }
   },
   "outputs": [],
   "source": [
    "# Open coda file\n",
    "pf = coda.open(example_file_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6621bed1-b828-4b3f-a0bf-23cac71c6ed8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-11T10:18:46.941825Z",
     "iopub.status.busy": "2024-01-11T10:18:46.941688Z",
     "iopub.status.idle": "2024-01-11T10:18:46.993769Z",
     "shell.execute_reply": "2024-01-11T10:18:46.993303Z"
    }
   },
   "outputs": [],
   "source": [
    "# Fetch specific parameter specifying the wanted path\n",
    "rayleigh_wind_velocity = coda.fetch(\n",
    "    pf, \"wind_velocity\", -1, \"observation_wind_profile\",\n",
    "    \"rayleigh_altitude_bin_wind_info\", -1, \"wind_velocity\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "86193b98-b08d-4d2a-b72a-58c50060a367",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-11T10:18:46.995938Z",
     "iopub.status.busy": "2024-01-11T10:18:46.995801Z",
     "iopub.status.idle": "2024-01-11T10:18:47.220671Z",
     "shell.execute_reply": "2024-01-11T10:18:47.220167Z"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1152x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Now that we have accessed the parameter data we can do a\n",
    "# quick plot to visualize the content\n",
    "\n",
    "# We transpose the array to better represent the data\n",
    "transposed_data = np.vstack(rayleigh_wind_velocity).T\n",
    "\n",
    "# We use a ver simple matplotlib example to plot the data\n",
    "fig = plt.figure(figsize=(16,4))\n",
    "plt.pcolormesh(\n",
    "    transposed_data,\n",
    "    cmap=\"RdYlBu\",\n",
    "    vmin=-70,\n",
    "    vmax=70\n",
    ")\n",
    "plt.title(\"Example plot\")\n",
    "plt.colorbar()\n",
    "plt.gca().invert_yaxis()\n",
    "plt.show()"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
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  "widgets": {
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