intake_demo.ipynb

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   "source": [
    "# Uncomment below to install `intake-xarray` if not already installed\n",
    "# !pip install intake intake-xarray"
   ]
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    "## Import catalog and parameters\n",
    "\n",
    "All of the available datasets for the `swot_adac_ogcms` project are cataloged in a parameterized `intake` catalog. The catalog itself and all valid parameterizations for each entry can be imported as follows:"
   ]
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   "source": [
    "from validate_catalog import all_params\n",
    "params_dict, cat = all_params()"
   ]
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    "## Inspect available models\n",
    "\n",
    "Each of the following model names is an item in our catalog.\n",
    "\n",
    "> **NOTE**: INALT60 data in not currently cataloged, pending provisioning of the private cloud bucket requested by the data provider."
   ]
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     "data": {
      "text/plain": [
       "dict_keys(['GIGATL', 'HYCOM25', 'HYCOM50', 'eNATL60', 'FESOM', 'ORCA36', 'FIO-COM32'])"
      ]
     },
     "execution_count": 3,
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   "source": [
    "params_dict.keys()"
   ]
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   "source": [
    "## Choose a model, inspect available parametrizations"
   ]
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      "text/plain": [
       "[{'region': '1', 'datatype': 'surface_hourly', 'season': 'fma'},\n",
       " {'region': '1', 'datatype': 'surface_hourly', 'season': 'aso'},\n",
       " {'region': '1', 'datatype': 'surface_flux_hourly', 'season': 'fma'},\n",
       " {'region': '1', 'datatype': 'surface_flux_hourly', 'season': 'aso'},\n",
       " {'region': '1', 'datatype': 'interior_daily', 'season': 'fma'},\n",
       " {'region': '1', 'datatype': 'interior_daily', 'season': 'aso'},\n",
       " {'region': '2', 'datatype': 'surface_hourly', 'season': 'fma'},\n",
       " {'region': '2', 'datatype': 'surface_hourly', 'season': 'aso'},\n",
       " {'region': '2', 'datatype': 'surface_flux_hourly', 'season': 'fma'},\n",
       " {'region': '2', 'datatype': 'surface_flux_hourly', 'season': 'aso'},\n",
       " {'region': '2', 'datatype': 'interior_daily', 'season': 'fma'},\n",
       " {'region': '2', 'datatype': 'interior_daily', 'season': 'aso'},\n",
       " {'region': '3', 'datatype': 'surface_hourly', 'season': 'fma'},\n",
       " {'region': '3', 'datatype': 'surface_hourly', 'season': 'aso'},\n",
       " {'region': '3', 'datatype': 'surface_flux_hourly', 'season': 'fma'},\n",
       " {'region': '3', 'datatype': 'surface_flux_hourly', 'season': 'aso'},\n",
       " {'region': '3', 'datatype': 'interior_daily', 'season': 'fma'},\n",
       " {'region': '3', 'datatype': 'interior_daily', 'season': 'aso'},\n",
       " {'region': '4', 'datatype': 'surface_hourly', 'season': 'fma'},\n",
       " {'region': '4', 'datatype': 'surface_hourly', 'season': 'aso'},\n",
       " {'region': '4', 'datatype': 'surface_flux_hourly', 'season': 'fma'},\n",
       " {'region': '4', 'datatype': 'surface_flux_hourly', 'season': 'aso'},\n",
       " {'region': '4', 'datatype': 'interior_daily', 'season': 'fma'},\n",
       " {'region': '4', 'datatype': 'interior_daily', 'season': 'aso'}]"
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     "execution_count": 4,
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   "source": [
    "item = \"FIO-COM32\"\n",
    "params_dict[item]"
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   "source": [
    "## Select params from available options"
   ]
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     "text": [
      "FIO-COM32 {'region': '1', 'datatype': 'surface_hourly', 'season': 'fma'}\n"
     ]
    }
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   "source": [
    "params = params_dict[item][0]\n",
    "print(item, params)"
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   "source": [
    "## Load data\n"
   ]
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   "execution_count": 6,
   "id": "732a86aa-9829-4c9d-bf98-0d8c768b0380",
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     "text": [
      "FIO-COM32 {'region': '1', 'datatype': 'surface_hourly', 'season': 'fma'}\n"
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:       (time: 2136, yt_ocean: 320, xt_ocean: 320, yu_ocean: 321, xu_ocean: 321)\n",
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       "    vsurf         (time, yu_ocean, xu_ocean) float32 dask.array&lt;chunksize=(275, 321, 321), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6</pre><div class='xr-wrap' hidden><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-b50971c0-2a03-4508-aab8-6fc8624c740a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b50971c0-2a03-4508-aab8-6fc8624c740a' 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>: 2136</li><li><span class='xr-has-index'>yt_ocean</span>: 320</li><li><span class='xr-has-index'>xt_ocean</span>: 320</li><li><span class='xr-has-index'>yu_ocean</span>: 321</li><li><span class='xr-has-index'>xu_ocean</span>: 321</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f3e8daa2-2b8a-4d79-8c2c-07e934efa90e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f3e8daa2-2b8a-4d79-8c2c-07e934efa90e' 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'>2018-02-01T13:00:00 ... 2018-05-...</div><input id='attrs-b10728ba-bb88-4883-bee5-fb1c6255f77b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b10728ba-bb88-4883-bee5-fb1c6255f77b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05a88c9b-420e-4026-af0e-814b9e55a3ff' class='xr-var-data-in' type='checkbox'><label for='data-05a88c9b-420e-4026-af0e-814b9e55a3ff' 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>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2018-02-01T13:00:00.000000000&#x27;, &#x27;2018-02-01T14:00:00.000000000&#x27;,\n",
       "       &#x27;2018-02-01T15:00:00.000000000&#x27;, ..., &#x27;2018-05-01T10:00:00.000000000&#x27;,\n",
       "       &#x27;2018-05-01T11:00:00.000000000&#x27;, &#x27;2018-05-01T12:00:00.000000000&#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'>xt_ocean</span></div><div class='xr-var-dims'>(xt_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-77.98 -77.95 ... -68.05 -68.02</div><input id='attrs-dd1c46b8-c848-47c8-a10e-d64ed2512c99' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd1c46b8-c848-47c8-a10e-d64ed2512c99' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b65c506c-19de-4db5-8adb-b90778fcda67' class='xr-var-data-in' type='checkbox'><label for='data-b65c506c-19de-4db5-8adb-b90778fcda67' 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>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>tcell longitude</dd><dt><span>modulo :</span></dt><dd> </dd><dt><span>point_spacing :</span></dt><dd>even</dd><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([-77.984375, -77.953125, -77.921875, ..., -68.078125, -68.046875,\n",
       "       -68.015625])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xu_ocean</span></div><div class='xr-var-dims'>(xu_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-78.0 -77.97 ... -68.03 -68.0</div><input id='attrs-81e666e1-d90d-4579-af16-bc041e220c3b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81e666e1-d90d-4579-af16-bc041e220c3b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8f6e04f-5b10-40ce-ab16-e051faffe975' class='xr-var-data-in' type='checkbox'><label for='data-f8f6e04f-5b10-40ce-ab16-e051faffe975' 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>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>ucell longitude</dd><dt><span>modulo :</span></dt><dd> </dd><dt><span>point_spacing :</span></dt><dd>even</dd><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([-78.     , -77.96875, -77.9375 , ..., -68.0625 , -68.03125, -68.     ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yt_ocean</span></div><div class='xr-var-dims'>(yt_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>30.02 30.05 30.08 ... 39.95 39.98</div><input id='attrs-54828d53-da3e-4086-b070-85c9e1e22eba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-54828d53-da3e-4086-b070-85c9e1e22eba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb03d3d7-1245-43a2-976d-fa94e2fc1f1c' class='xr-var-data-in' type='checkbox'><label for='data-fb03d3d7-1245-43a2-976d-fa94e2fc1f1c' 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>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>tcell latitude</dd><dt><span>point_spacing :</span></dt><dd>even</dd><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([30.015625, 30.046875, 30.078125, ..., 39.921875, 39.953125, 39.984375])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yu_ocean</span></div><div class='xr-var-dims'>(yu_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>30.0 30.03 30.06 ... 39.97 40.0</div><input id='attrs-cc5aad86-554e-48b4-bc9f-c7a4d8f64e75' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc5aad86-554e-48b4-bc9f-c7a4d8f64e75' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-002d9dbf-532a-469e-a4f4-6af8061a6e27' class='xr-var-data-in' type='checkbox'><label for='data-002d9dbf-532a-469e-a4f4-6af8061a6e27' 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>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>ucell latitude</dd><dt><span>point_spacing :</span></dt><dd>even</dd><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([30.     , 30.03125, 30.0625 , ..., 39.9375 , 39.96875, 40.     ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e320e304-8a19-4cd5-b900-083226ed5640' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e320e304-8a19-4cd5-b900-083226ed5640' class='xr-section-summary' >Data variables: <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>eta_t</span></div><div class='xr-var-dims'>(time, yt_ocean, xt_ocean)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(275, 320, 320), meta=np.ndarray&gt;</div><input id='attrs-e5a17b2d-4b92-448b-b31d-f37877ec2887' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5a17b2d-4b92-448b-b31d-f37877ec2887' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1ef463f-b4e1-4680-ac61-e8329320d439' class='xr-var-data-in' type='checkbox'><label for='data-d1ef463f-b4e1-4680-ac61-e8329320d439' 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>history :</span></dt><dd>From ../../ocean_snap_eta_t_2018_02_01.nc</dd><dt><span>long_name :</span></dt><dd>IF ( ETA_T0 LT VMAX AND ETA_T0 GT VMIN ) THEN ETA_T0 ELSE (-32768*1.+0.)</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 834.38 MiB </td>\n",
       "                        <td> 107.42 MiB </td>\n",
       "                    </tr>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (275, 320, 320) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 9 Tasks </td>\n",
       "                        <td> 8 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>surface_salt</span></div><div class='xr-var-dims'>(time, yt_ocean, xt_ocean)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(275, 320, 320), meta=np.ndarray&gt;</div><input id='attrs-544b701a-5455-4872-a403-e7a3077adc1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-544b701a-5455-4872-a403-e7a3077adc1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59a04571-0b42-4ff7-8a1d-22672c80d979' class='xr-var-data-in' type='checkbox'><label for='data-59a04571-0b42-4ff7-8a1d-22672c80d979' 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>history :</span></dt><dd>From ../../SFC_snap_tsb_2018_02_01.nc</dd><dt><span>long_name :</span></dt><dd>IF ( SURFACE_SALT0 LT VMAX AND SURFACE_SALT0 GT VMIN ) THEN SURFACE_SALT0 ELSE (-32768*1.+0.)</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <td> 9 Tasks </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-b4dce8e8-8dbf-4a9f-b51a-866a070ddbf0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b4dce8e8-8dbf-4a9f-b51a-866a070ddbf0' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:       (time: 2136, yt_ocean: 320, xt_ocean: 320, yu_ocean: 321, xu_ocean: 321)\n",
       "Coordinates:\n",
       "  * time          (time) datetime64[ns] 2018-02-01T13:00:00 ... 2018-05-01T12...\n",
       "  * xt_ocean      (xt_ocean) float64 -77.98 -77.95 -77.92 ... -68.05 -68.02\n",
       "  * xu_ocean      (xu_ocean) float64 -78.0 -77.97 -77.94 ... -68.06 -68.03 -68.0\n",
       "  * yt_ocean      (yt_ocean) float64 30.02 30.05 30.08 ... 39.92 39.95 39.98\n",
       "  * yu_ocean      (yu_ocean) float64 30.0 30.03 30.06 30.09 ... 39.94 39.97 40.0\n",
       "Data variables:\n",
       "    eta_t         (time, yt_ocean, xt_ocean) float32 dask.array<chunksize=(275, 320, 320), meta=np.ndarray>\n",
       "    surface_salt  (time, yt_ocean, xt_ocean) float32 dask.array<chunksize=(275, 320, 320), meta=np.ndarray>\n",
       "    surface_temp  (time, yt_ocean, xt_ocean) float32 dask.array<chunksize=(275, 320, 320), meta=np.ndarray>\n",
       "    usurf         (time, yu_ocean, xu_ocean) float32 dask.array<chunksize=(275, 321, 321), meta=np.ndarray>\n",
       "    vsurf         (time, yu_ocean, xu_ocean) float32 dask.array<chunksize=(275, 321, 321), meta=np.ndarray>\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(item, params)\n",
    "ds = cat[item](**params).to_dask()\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf00fb4f-8e85-4aeb-8e90-4320b6345aec",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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