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      "source": [
        "\n# Calculate and plot daily daytime temperature averages\n\nExample of how to read in MET data and plot up daytime\ntemperature averages using the add_solar_variable function\n\nAuthor: Adam Theisen\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
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      "source": [
        "import matplotlib.pyplot as plt\nfrom arm_test_data import DATASETS\n\nimport act\n\n# Read in the sample MET data\nmet_wildcard_list = [\n    'sgpmetE13.b1.20190101.000000.cdf',\n    'sgpmetE13.b1.20190102.000000.cdf',\n    'sgpmetE13.b1.20190103.000000.cdf',\n    'sgpmetE13.b1.20190104.000000.cdf',\n    'sgpmetE13.b1.20190105.000000.cdf',\n    'sgpmetE13.b1.20190106.000000.cdf',\n    'sgpmetE13.b1.20190107.000000.cdf',\n]\nmet_filenames = [DATASETS.fetch(file) for file in met_wildcard_list]\nds = act.io.arm.read_arm_netcdf(met_filenames)\n\n# Add the solar variable, including dawn/dusk to variable\nds = act.utils.geo_utils.add_solar_variable(ds)\n\n# Using the sun variable, only analyze daytime data\nds = ds.where(ds['sun_variable'] == 1)\n\n# Take daily mean using xarray features\nds = ds.resample(time='1d', skipna=True).mean()\n\n# Creat Plot Display\ndisplay = act.plotting.TimeSeriesDisplay(ds, figsize=(15, 10))\ndisplay.plot('temp_mean', linestyle='solid')\ndisplay.day_night_background()\nplt.show()\n\nds.close()"
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