round_trip_NDBC.ipynb

{
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   "execution_count": 4,
   "id": "92d15b15-a0f4-4c00-b0c9-4f67213f4060",
   "metadata": {
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     "text": [
      "/vortexfs1/home/csherwood/src/NOPP_Utilities\n"
     ]
    }
   ],
   "source": [
    "# round trip NDBC code\n",
    "import os\n",
    "import pickle\n",
    "from datetime import datetime, timezone\n",
    "from scipy import stats\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.colors\n",
    "import numpy as np\n",
    "\n",
    "import xarray as xr\n",
    "import xroms\n",
    "import matplotlib.pyplot as plt\n",
    "from wavespectra import read_ww3, read_swan, read_ndbc, read_netcdf\n",
    "#from roguewave.wavespectra.estimators.estimate import estimate_directional_distribution\n",
    "#%run -i roguewave_estimators.py\n",
    "os.chdir('/vortexfs1/home/csherwood/src/NOPP_Utilities')\n",
    "print(os.getcwd())\n",
    "%run -i wave_stats.py"
   ]
  },
  {
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   "execution_count": 15,
   "id": "44de9655-9e89-4b2d-8d4d-2199409c51f5",
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     "name": "stdout",
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     "text": [
      "https://dods.ndbc.noaa.gov/thredds/dodsC/data/swden/42039/42039w9999.nc\n"
     ]
    },
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       "Dimensions:  (time: 118, freq: 46, lat: 1, lon: 1, dir: 36)\n",
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       "  * lat      (lat) float32 28.79\n",
       "  * lon      (lon) float32 -86.01\n",
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       "    efth     (time, lat, lon, freq, dir) float64 dask.array&lt;chunksize=(118, 1, 1, 46, 36), meta=np.ndarray&gt;</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e1eabe78-abd4-459d-9fb4-218fffd7081a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e1eabe78-abd4-459d-9fb4-218fffd7081a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 118</li><li><span class='xr-has-index'>freq</span>: 46</li><li><span class='xr-has-index'>lat</span>: 1</li><li><span class='xr-has-index'>lon</span>: 1</li><li><span class='xr-has-index'>dir</span>: 36</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d5c60031-2ab2-436d-bb58-f4b3ea5f3e60' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d5c60031-2ab2-436d-bb58-f4b3ea5f3e60' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-09-26T00:50:00 ... 2022-09-...</div><input id='attrs-fa1230dd-95f1-408f-bc91-dcd711add845' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa1230dd-95f1-408f-bc91-dcd711add845' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e6e80ab-10c5-4a72-9345-18f976919457' class='xr-var-data-in' type='checkbox'><label for='data-8e6e80ab-10c5-4a72-9345-18f976919457' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-09-26T00:50:00.000000000&#x27;, &#x27;2022-09-26T01:50:00.000000000&#x27;,\n",
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       "       &#x27;2022-09-27T00:50:00.000000000&#x27;, &#x27;2022-09-27T01:50:00.000000000&#x27;,\n",
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       "       &#x27;2022-09-27T06:50:00.000000000&#x27;, &#x27;2022-09-27T07:50:00.000000000&#x27;,\n",
       "       &#x27;2022-09-27T08:50:00.000000000&#x27;, &#x27;2022-09-27T09:50:00.000000000&#x27;,\n",
       "       &#x27;2022-09-27T10:50:00.000000000&#x27;, &#x27;2022-09-27T11:50:00.000000000&#x27;,\n",
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       "       &#x27;2022-09-28T16:50:00.000000000&#x27;, &#x27;2022-09-28T17:50:00.000000000&#x27;,\n",
       "       &#x27;2022-09-28T18:50:00.000000000&#x27;, &#x27;2022-09-28T19:50:00.000000000&#x27;,\n",
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       "       &#x27;2022-09-28T22:50:00.000000000&#x27;, &#x27;2022-09-28T23:50:00.000000000&#x27;,\n",
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       "       &#x27;2022-09-30T05:50:00.000000000&#x27;, &#x27;2022-09-30T06:50:00.000000000&#x27;,\n",
       "       &#x27;2022-09-30T07:50:00.000000000&#x27;, &#x27;2022-09-30T08:50:00.000000000&#x27;,\n",
       "       &#x27;2022-09-30T09:50:00.000000000&#x27;, &#x27;2022-09-30T10:50:00.000000000&#x27;,\n",
       "       &#x27;2022-09-30T11:50:00.000000000&#x27;, &#x27;2022-09-30T12:50:00.000000000&#x27;,\n",
       "       &#x27;2022-09-30T13:50:00.000000000&#x27;, &#x27;2022-09-30T15:50:00.000000000&#x27;,\n",
       "       &#x27;2022-09-30T16:50:00.000000000&#x27;, &#x27;2022-09-30T17:50:00.000000000&#x27;,\n",
       "       &#x27;2022-09-30T18:50:00.000000000&#x27;, &#x27;2022-09-30T19:50:00.000000000&#x27;,\n",
       "       &#x27;2022-09-30T20:50:00.000000000&#x27;, &#x27;2022-09-30T21:50:00.000000000&#x27;,\n",
       "       &#x27;2022-09-30T22:50:00.000000000&#x27;, &#x27;2022-09-30T23:50:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>freq</span></div><div class='xr-var-dims'>(freq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.033 0.038 0.043 ... 0.465 0.485</div><input id='attrs-8d502942-75d5-4c6c-bbda-c9341ddad37e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d502942-75d5-4c6c-bbda-c9341ddad37e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93217cfc-6962-4202-9482-d8281d5fdcc7' class='xr-var-data-in' type='checkbox'><label for='data-93217cfc-6962-4202-9482-d8281d5fdcc7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_wave_frequency</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([0.033, 0.038, 0.043, 0.048, 0.053, 0.058, 0.063, 0.068, 0.073, 0.078,\n",
       "       0.083, 0.088, 0.093, 0.1  , 0.11 , 0.12 , 0.13 , 0.14 , 0.15 , 0.16 ,\n",
       "       0.17 , 0.18 , 0.19 , 0.2  , 0.21 , 0.22 , 0.23 , 0.24 , 0.25 , 0.26 ,\n",
       "       0.27 , 0.28 , 0.29 , 0.3  , 0.31 , 0.32 , 0.33 , 0.34 , 0.35 , 0.365,\n",
       "       0.385, 0.405, 0.425, 0.445, 0.465, 0.485], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>28.79</div><input id='attrs-1c4d3821-eaff-4aaa-8d92-8af80ff9098d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c4d3821-eaff-4aaa-8d92-8af80ff9098d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25131cd6-00b9-4325-9f90-ca9a0bb85060' class='xr-var-data-in' type='checkbox'><label for='data-25131cd6-00b9-4325-9f90-ca9a0bb85060' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([28.788], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-86.01</div><input id='attrs-981d626d-a378-4ed9-a760-04522f791a98' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-981d626d-a378-4ed9-a760-04522f791a98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd99fe4e-4cde-4ba8-aa99-52c7f6f92e1a' class='xr-var-data-in' type='checkbox'><label for='data-cd99fe4e-4cde-4ba8-aa99-52c7f6f92e1a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-86.008], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 10.0 20.0 ... 330.0 340.0 350.0</div><input id='attrs-7e1bce70-0fc8-4680-97fe-e64592b2ce78' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e1bce70-0fc8-4680-97fe-e64592b2ce78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7cd28e8d-3b24-4072-8dcd-14b7ccf24876' class='xr-var-data-in' type='checkbox'><label for='data-7cd28e8d-3b24-4072-8dcd-14b7ccf24876' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_wave_from_direction</dd><dt><span>units :</span></dt><dd>degree</dd></dl></div><div class='xr-var-data'><pre>array([  0.,  10.,  20.,  30.,  40.,  50.,  60.,  70.,  80.,  90., 100., 110.,\n",
       "       120., 130., 140., 150., 160., 170., 180., 190., 200., 210., 220., 230.,\n",
       "       240., 250., 260., 270., 280., 290., 300., 310., 320., 330., 340., 350.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4b86c5ec-339c-4e51-8b39-a3f3c55d2ce7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4b86c5ec-339c-4e51-8b39-a3f3c55d2ce7' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>efth</span></div><div class='xr-var-dims'>(time, lat, lon, freq, dir)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(118, 1, 1, 46, 36), meta=np.ndarray&gt;</div><input id='attrs-a87f703c-13c3-4549-9c66-08c7d62f3e9e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a87f703c-13c3-4549-9c66-08c7d62f3e9e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1bed3f9-2ffb-4c36-9a3e-6f451372d6dc' class='xr-var-data-in' type='checkbox'><label for='data-b1bed3f9-2ffb-4c36-9a3e-6f451372d6dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_wave_directional_variance_spectral_density</dd><dt><span>units :</span></dt><dd>m2 s degree-1</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.49 MiB </td>\n",
       "                        <td> 1.49 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (118, 1, 1, 46, 36) </td>\n",
       "                        <td> (118, 1, 1, 46, 36) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 40 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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       "               &#x27;2022-09-26 02:50:00&#x27;, &#x27;2022-09-26 03:50:00&#x27;,\n",
       "               &#x27;2022-09-26 04:50:00&#x27;, &#x27;2022-09-26 05:50:00&#x27;,\n",
       "               &#x27;2022-09-26 06:50:00&#x27;, &#x27;2022-09-26 07:50:00&#x27;,\n",
       "               &#x27;2022-09-26 08:50:00&#x27;, &#x27;2022-09-26 09:50:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2022-09-30 13:50:00&#x27;, &#x27;2022-09-30 15:50:00&#x27;,\n",
       "               &#x27;2022-09-30 16:50:00&#x27;, &#x27;2022-09-30 17:50:00&#x27;,\n",
       "               &#x27;2022-09-30 18:50:00&#x27;, &#x27;2022-09-30 19:50:00&#x27;,\n",
       "               &#x27;2022-09-30 20:50:00&#x27;, &#x27;2022-09-30 21:50:00&#x27;,\n",
       "               &#x27;2022-09-30 22:50:00&#x27;, &#x27;2022-09-30 23:50:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=118, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>freq</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3db31f4e-8640-4af6-8c9a-e34198cfdd72' class='xr-index-data-in' type='checkbox'/><label for='index-3db31f4e-8640-4af6-8c9a-e34198cfdd72' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0.032999999821186066,  0.03799999877810478,   0.0430000014603138,\n",
       "        0.04800000041723251,  0.05299999937415123, 0.057999998331069946,\n",
       "        0.06300000101327896,  0.06800000369548798,   0.0729999989271164,\n",
       "        0.07800000160932541,  0.08299999684095383,  0.08799999952316284,\n",
       "        0.09300000220537186,  0.10000000149011612,  0.10999999940395355,\n",
       "        0.11999999731779099,  0.12999999523162842,  0.14000000059604645,\n",
       "        0.15000000596046448,   0.1599999964237213,  0.17000000178813934,\n",
       "        0.18000000715255737,   0.1899999976158142,  0.20000000298023224,\n",
       "        0.20999999344348907,   0.2199999988079071,  0.23000000417232513,\n",
       "        0.23999999463558197,                 0.25,  0.25999999046325684,\n",
       "        0.27000001072883606,   0.2800000011920929,  0.28999999165534973,\n",
       "        0.30000001192092896,   0.3100000023841858,   0.3199999928474426,\n",
       "        0.33000001311302185,   0.3400000035762787,   0.3499999940395355,\n",
       "        0.36500000953674316,  0.38499999046325684,   0.4050000011920929,\n",
       "        0.42500001192092896,   0.4449999928474426,   0.4650000035762787,\n",
       "        0.48500001430511475],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;freq&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9bbe37f8-10d1-46a9-81e7-ec683e3a6361' class='xr-index-data-in' type='checkbox'/><label for='index-9bbe37f8-10d1-46a9-81e7-ec683e3a6361' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([28.788], dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-aeea8ea7-fcc5-423c-afaf-3d30e640a1ea' class='xr-index-data-in' type='checkbox'/><label for='index-aeea8ea7-fcc5-423c-afaf-3d30e640a1ea' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-86.008], dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dir</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c0f2ca67-4672-4965-a959-5bed96e90f84' class='xr-index-data-in' type='checkbox'/><label for='index-c0f2ca67-4672-4965-a959-5bed96e90f84' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0.0,  10.0,  20.0,  30.0,  40.0,  50.0,  60.0,  70.0,  80.0,  90.0,\n",
       "       100.0, 110.0, 120.0, 130.0, 140.0, 150.0, 160.0, 170.0, 180.0, 190.0,\n",
       "       200.0, 210.0, 220.0, 230.0, 240.0, 250.0, 260.0, 270.0, 280.0, 290.0,\n",
       "       300.0, 310.0, 320.0, 330.0, 340.0, 350.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;dir&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-26af02e8-1e57-4b71-ad8f-b8077dc456ea' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-26af02e8-1e57-4b71-ad8f-b8077dc456ea' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 118, freq: 46, lat: 1, lon: 1, dir: 36)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2022-09-26T00:50:00 ... 2022-09-30T23:50:00\n",
       "  * freq     (freq) float32 0.033 0.038 0.043 0.048 ... 0.425 0.445 0.465 0.485\n",
       "  * lat      (lat) float32 28.79\n",
       "  * lon      (lon) float32 -86.01\n",
       "  * dir      (dir) float64 0.0 10.0 20.0 30.0 40.0 ... 320.0 330.0 340.0 350.0\n",
       "Data variables:\n",
       "    efth     (time, lat, lon, freq, dir) float64 dask.array<chunksize=(118, 1, 1, 46, 36), meta=np.ndarray>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# These are the GOM buoys with data for Ian\n",
    "buoys = ['42039','42098', '42099']\n",
    "# pick one for testing\n",
    "buoy = buoys[0]\n",
    "\n",
    "stime = datetime.strptime('2022-09-26', '%Y-%m-%d')\n",
    "etime = datetime.strptime('2022-10-01', '%Y-%m-%d')\n",
    "\n",
    "url ='https://dods.ndbc.noaa.gov/thredds/dodsC/data/swden/' + str(buoy) + '/' + str(buoy) + 'w9999' + '.nc'\n",
    "print(url)\n",
    "# use wavespectra routine for reading & generating 2dspec\n",
    "dso = read_ndbc(url, dd=10.0, chunks={}).sel(time=slice(stime, etime))\n",
    "dso"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ca8267d7-fcfe-40c2-bfb8-8152e109f507",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "ds = dso.isel(lat=0, lon=0, time=18)\n",
    "ds\n",
    "efth = ds.efth.values\n",
    "dirs = ds.dir.values\n",
    "freqs = ds.freq.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a5608252-cd46-40a8-bee8-76eb36939c93",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x2aac201f2bb0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pcolormesh(dirs, freqs, efth)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}