{
  "cells": [
    {
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      "source": [
        "\n# NEON Data\n\nThis example shows how to download data from\nNEON and ARM 2m surface meteorology stations\non the North Slope and plot them\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
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      "source": [
        "import glob\nimport os\n\nimport matplotlib.pyplot as plt\n\nimport act\n\n# Place your username and token here\nusername = os.getenv('ARM_USERNAME')\ntoken = os.getenv('ARM_PASSWORD')\n\nif token is not None and len(token) > 0:\n    # Download ARM data if a username/token are set\n    files = act.discovery.download_arm_data(\n        username, token, 'nsametC1.b1', '2022-10-01', '2022-10-07'\n    )\n    ds = act.io.arm.read_arm_netcdf(files)\n\n    # Download NEON Data\n    # NEON sites can be found through the NEON website\n    # https://www.neonscience.org/field-sites/explore-field-sites\n    site_code = 'BARR'\n    product_code = 'DP1.00002.001'\n    result = act.discovery.neon.download_neon_data(site_code, product_code, '2022-10')\n\n    # A number of files are downloaded and further explained in the readme file that's downloaded.\n    # These are the files we will need for reading 1 minute NEON data\n    file = glob.glob(\n        os.path.join(\n            '.',\n            'BARR_DP1.00002.001',\n            'NEON.D18.BARR.DP1.00002.001.000.010.001.SAAT_1min.2022-10.expanded.*.csv',\n        )\n    )\n    variable_file = glob.glob(\n        os.path.join('.', 'BARR_DP1.00002.001', 'NEON.D18.BARR.DP1.00002.001.variables.*.csv')\n    )\n    position_file = glob.glob(\n        os.path.join(\n            '.',\n            'BARR_DP1.00002.001',\n            'NEON.D18.BARR.DP1.00002.001.sensor_positions.*.csv',\n        )\n    )\n    # Read in the data using the ACT reader, passing with it the variable and position files\n    # for added information in the dataset\n    ds2 = act.io.read_neon_csv(file, variable_files=variable_file, position_files=position_file)\n\n    # Plot up the two datasets\n    display = act.plotting.TimeSeriesDisplay({'ARM': ds, 'NEON': ds2})\n    display.plot('temp_mean', 'ARM', marker=None, label='ARM')\n    display.plot('tempSingleMean', 'NEON', marker=None, label='NEON')\n    display.day_night_background('ARM')\n    plt.show()"
      ]
    }
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