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November 19, 2021 07:19
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Download the Bluelink Reanalysis 2020 surface currents and animate
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| { | |
| "cell_type": "markdown", | |
| "id": "b1a3e8a9", | |
| "metadata": {}, | |
| "source": [ | |
| "# Download and animate the BRAN 2020 model data\n", | |
| "\n", | |
| "Use xarray to access a group of netcdf files on an opendap server, subset the data and plot\n", | |
| "\n", | |
| "Uses [XMovie](https://github.com/jbusecke/xmovie) to save an mp4 animation.\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "Matt Rayson\n", | |
| "\n", | |
| "University of Western Australia\n", | |
| "\n", | |
| "November 2021" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 1, | |
| "id": "6e39220d", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "import xarray as xr\n", | |
| "import numpy as np\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "from cmocean import cm # pip install cmocean\n", | |
| "from xmovie import Movie # pip install xmovie\n", | |
| "\n", | |
| "# Cartopy makes nice maps but can be a pain to install...\n", | |
| "# import cartopy.crs as ccrs\n", | |
| "# import cartopy.feature as cfeature" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 13, | |
| "id": "92d53b57", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "plt.rcParams['font.size']=14\n", | |
| "plt.rcParams['axes.labelsize'] = 'medium'" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 8, | |
| "id": "af9ceb4c", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "%matplotlib inline" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 2, | |
| "id": "f8117edf", | |
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| "</style><pre class='xr-text-repr-fallback'><xarray.Dataset>\n", | |
| "Dimensions: (xu_ocean: 3600, yu_ocean: 1500, st_ocean: 51, Time: 61, nv: 2, st_edges_ocean: 52)\n", | |
| "Coordinates:\n", | |
| " * xu_ocean (xu_ocean) float64 0.1 0.2 0.3 0.4 ... 359.8 359.9 360.0\n", | |
| " * yu_ocean (yu_ocean) float64 -74.9 -74.8 -74.7 ... 74.8 74.9 75.0\n", | |
| " * st_ocean (st_ocean) float64 2.5 7.5 12.5 ... 3.603e+03 4.509e+03\n", | |
| " * Time (Time) datetime64[ns] 2017-03-01T12:00:00 ... 2017-04-30T...\n", | |
| " * nv (nv) float64 1.0 2.0\n", | |
| " * st_edges_ocean (st_edges_ocean) float64 0.0 5.0 10.0 ... 4.056e+03 5e+03\n", | |
| "Data variables:\n", | |
| " average_T1 (Time) datetime64[ns] dask.array<chunksize=(31,), meta=np.ndarray>\n", | |
| " average_T2 (Time) datetime64[ns] dask.array<chunksize=(31,), meta=np.ndarray>\n", | |
| " average_DT (Time) timedelta64[ns] dask.array<chunksize=(31,), meta=np.ndarray>\n", | |
| " Time_bounds (Time, nv) timedelta64[ns] dask.array<chunksize=(31, 2), meta=np.ndarray>\n", | |
| " u (Time, st_ocean, yu_ocean, xu_ocean) float32 dask.array<chunksize=(31, 51, 1500, 3600), meta=np.ndarray>\n", | |
| "Attributes:\n", | |
| " filename: TMP/ocean_ofam_2017_03_01.nc.0000\n", | |
| " NumFilesInSet: 20\n", | |
| " grid_type: regular\n", | |
| " grid_tile: N/A\n", | |
| " history: Tue Nov 3 11:18:33 2020: ncrcat -4 --df...\n", | |
| " NCO: netCDF Operators version 4.9.2 (Homepage...\n", | |
| " title: BRAN2020\n", | |
| " catalogue_doi_url: http://dx.doi.org/10.25914/6009627c7af03\n", | |
| " acknowledgement: BRAN is made freely available by CSIRO B...\n", | |
| " DODS_EXTRA.Unlimited_Dimension: Time</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-445e7c9f-44ca-4917-96e0-b856396c6269' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-445e7c9f-44ca-4917-96e0-b856396c6269' 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'>xu_ocean</span>: 3600</li><li><span class='xr-has-index'>yu_ocean</span>: 1500</li><li><span class='xr-has-index'>st_ocean</span>: 51</li><li><span class='xr-has-index'>Time</span>: 61</li><li><span class='xr-has-index'>nv</span>: 2</li><li><span class='xr-has-index'>st_edges_ocean</span>: 52</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-bb6c5c44-209c-4050-b0cd-8ac554099b2c' class='xr-section-summary-in' type='checkbox' checked><label for='section-bb6c5c44-209c-4050-b0cd-8ac554099b2c' class='xr-section-summary' >Coordinates: <span>(6)</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'>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'>0.1 0.2 0.3 ... 359.8 359.9 360.0</div><input id='attrs-55591206-edb6-443d-8dda-b77bbf350063' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-55591206-edb6-443d-8dda-b77bbf350063' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f705225d-9a32-49c4-8c21-09d30f563115' class='xr-var-data-in' type='checkbox'><label for='data-f705225d-9a32-49c4-8c21-09d30f563115' 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>long_name :</span></dt><dd>ucell longitude</dd><dt><span>units :</span></dt><dd>degrees_E</dd><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>domain_decomposition :</span></dt><dd>[ 1 3600 1 1800]</dd><dt><span>_ChunkSizes :</span></dt><dd>300</dd></dl></div><div class='xr-var-data'><pre>array([1.000e-01, 2.000e-01, 3.000e-01, ..., 3.598e+02, 3.599e+02, 3.600e+02])</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'>-74.9 -74.8 -74.7 ... 74.9 75.0</div><input id='attrs-9bff7007-1210-47c3-897c-40027e747613' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9bff7007-1210-47c3-897c-40027e747613' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2954f7b7-3ca2-4e42-bc1b-5c8119b6040e' class='xr-var-data-in' type='checkbox'><label for='data-2954f7b7-3ca2-4e42-bc1b-5c8119b6040e' 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>long_name :</span></dt><dd>ucell latitude</dd><dt><span>units :</span></dt><dd>degrees_N</dd><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>domain_decomposition :</span></dt><dd>[ 1 1500 1 150]</dd><dt><span>_ChunkSizes :</span></dt><dd>300</dd></dl></div><div class='xr-var-data'><pre>array([-74.900002, -74.800003, -74.699997, ..., 74.800003, 74.900002,\n", | |
| " 75. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>st_ocean</span></div><div class='xr-var-dims'>(st_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.5 7.5 ... 3.603e+03 4.509e+03</div><input id='attrs-0a694a47-82e9-454c-a777-f51fda63c973' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a694a47-82e9-454c-a777-f51fda63c973' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0121244b-52d5-4f8d-86ab-0bf87914040e' class='xr-var-data-in' type='checkbox'><label for='data-0121244b-52d5-4f8d-86ab-0bf87914040e' 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>long_name :</span></dt><dd>tcell zstar depth</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>edges :</span></dt><dd>st_edges_ocean</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([2.500000e+00, 7.500000e+00, 1.250000e+01, 1.751539e+01, 2.266702e+01,\n", | |
| " 2.816938e+01, 3.421801e+01, 4.095498e+01, 4.845498e+01, 5.671801e+01,\n", | |
| " 6.566938e+01, 7.516702e+01, 8.501539e+01, 9.500000e+01, 1.050000e+02,\n", | |
| " 1.150000e+02, 1.250000e+02, 1.350000e+02, 1.450000e+02, 1.550000e+02,\n", | |
| " 1.650000e+02, 1.750000e+02, 1.850000e+02, 1.950000e+02, 2.051899e+02,\n", | |
| " 2.170545e+02, 2.331943e+02, 2.558842e+02, 2.866090e+02, 3.258842e+02,\n", | |
| " 3.731943e+02, 4.270545e+02, 4.851899e+02, 5.455111e+02, 6.104156e+02,\n", | |
| " 6.859268e+02, 7.759268e+02, 8.804156e+02, 9.955111e+02, 1.115313e+03,\n", | |
| " 1.238354e+03, 1.368157e+03, 1.507734e+03, 1.658157e+03, 1.818354e+03,\n", | |
| " 1.985313e+03, 2.165180e+03, 2.431101e+03, 2.894842e+03, 3.603101e+03,\n", | |
| " 4.509180e+03])</pre></div></li><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'>2017-03-01T12:00:00 ... 2017-04-...</div><input id='attrs-0476b025-ed75-4e12-b427-7dc2253dec5b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0476b025-ed75-4e12-b427-7dc2253dec5b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cba31c44-199d-4028-8516-1b3fdd57d2fa' class='xr-var-data-in' type='checkbox'><label for='data-cba31c44-199d-4028-8516-1b3fdd57d2fa' 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>long_name :</span></dt><dd>Time</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>GREGORIAN</dd><dt><span>bounds :</span></dt><dd>Time_bounds</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array(['2017-03-01T12:00:00.000000000', '2017-03-02T12:00:00.000000000',\n", | |
| " '2017-03-03T12:00:00.000000000', '2017-03-04T12:00:00.000000000',\n", | |
| " '2017-03-05T12:00:00.000000000', '2017-03-06T12:00:00.000000000',\n", | |
| " '2017-03-07T12:00:00.000000000', '2017-03-08T12:00:00.000000000',\n", | |
| " '2017-03-09T12:00:00.000000000', '2017-03-10T12:00:00.000000000',\n", | |
| " '2017-03-11T12:00:00.000000000', '2017-03-12T12:00:00.000000000',\n", | |
| " '2017-03-13T12:00:00.000000000', '2017-03-14T12:00:00.000000000',\n", | |
| " '2017-03-15T12:00:00.000000000', '2017-03-16T12:00:00.000000000',\n", | |
| " '2017-03-17T12:00:00.000000000', '2017-03-18T12:00:00.000000000',\n", | |
| " '2017-03-19T12:00:00.000000000', '2017-03-20T12:00:00.000000000',\n", | |
| " '2017-03-21T12:00:00.000000000', '2017-03-22T12:00:00.000000000',\n", | |
| " '2017-03-23T12:00:00.000000000', '2017-03-24T12:00:00.000000000',\n", | |
| " '2017-03-25T12:00:00.000000000', '2017-03-26T12:00:00.000000000',\n", | |
| " '2017-03-27T12:00:00.000000000', '2017-03-28T12:00:00.000000000',\n", | |
| " '2017-03-29T12:00:00.000000000', '2017-03-30T12:00:00.000000000',\n", | |
| " '2017-03-31T12:00:00.000000000', '2017-04-01T12:00:00.000000000',\n", | |
| " '2017-04-02T12:00:00.000000000', '2017-04-03T12:00:00.000000000',\n", | |
| " '2017-04-04T12:00:00.000000000', '2017-04-05T12:00:00.000000000',\n", | |
| " '2017-04-06T12:00:00.000000000', '2017-04-07T12:00:00.000000000',\n", | |
| " '2017-04-08T12:00:00.000000000', '2017-04-09T12:00:00.000000000',\n", | |
| " '2017-04-10T12:00:00.000000000', '2017-04-11T12:00:00.000000000',\n", | |
| " '2017-04-12T12:00:00.000000000', '2017-04-13T12:00:00.000000000',\n", | |
| " '2017-04-14T12:00:00.000000000', '2017-04-15T12:00:00.000000000',\n", | |
| " '2017-04-16T12:00:00.000000000', '2017-04-17T12:00:00.000000000',\n", | |
| " '2017-04-18T12:00:00.000000000', '2017-04-19T12:00:00.000000000',\n", | |
| " '2017-04-20T12:00:00.000000000', '2017-04-21T12:00:00.000000000',\n", | |
| " '2017-04-22T12:00:00.000000000', '2017-04-23T12:00:00.000000000',\n", | |
| " '2017-04-24T12:00:00.000000000', '2017-04-25T12:00:00.000000000',\n", | |
| " '2017-04-26T12:00:00.000000000', '2017-04-27T12:00:00.000000000',\n", | |
| " '2017-04-28T12:00:00.000000000', '2017-04-29T12:00:00.000000000',\n", | |
| " '2017-04-30T12:00:00.000000000'], dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nv</span></div><div class='xr-var-dims'>(nv)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0</div><input id='attrs-fff88bab-9ddf-4811-9dd8-417c5a9d746d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fff88bab-9ddf-4811-9dd8-417c5a9d746d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-897ed707-3c99-42e3-9d16-7774c8288b00' class='xr-var-data-in' type='checkbox'><label for='data-897ed707-3c99-42e3-9d16-7774c8288b00' 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>_ChunkSizes :</span></dt><dd>2</dd></dl></div><div class='xr-var-data'><pre>array([1., 2.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>st_edges_ocean</span></div><div class='xr-var-dims'>(st_edges_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 5.0 10.0 ... 4.056e+03 5e+03</div><input id='attrs-ff2f68f0-8e8e-4808-ae18-59b96755e205' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff2f68f0-8e8e-4808-ae18-59b96755e205' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea520da0-0d34-493f-9056-12bec83bfbd8' class='xr-var-data-in' type='checkbox'><label for='data-ea520da0-0d34-493f-9056-12bec83bfbd8' 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>long_name :</span></dt><dd>tcell zstar depth edges</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>_ChunkSizes :</span></dt><dd>52</dd></dl></div><div class='xr-var-data'><pre>array([ 0. , 5. , 10. , 15.007695, 20.091206,\n", | |
| " 25.4182 , 31.193693, 37.586491, 44.704975, 52.586491,\n", | |
| " 61.193695, 70.418198, 80.091202, 90.007698, 100. ,\n", | |
| " 110. , 120. , 130. , 140. , 150. ,\n", | |
| " 160. , 170. , 180. , 190. , 200.094955,\n", | |
| " 211.122192, 225.124405, 244.539276, 271.246613, 306.246613,\n", | |
| " 349.539276, 400.12442 , 456.122192, 515.350525, 577.963379,\n", | |
| " 648.171204, 730.926758, 828.171204, 937.963379, 1055.412231,\n", | |
| " 1176.833618, 1303.255737, 1437.945679, 1582.945679, 1738.255737,\n", | |
| " 1901.833618, 2075.246826, 2298.140625, 2662.971436, 3248.971436,\n", | |
| " 4056.140625, 5000. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d4877fe4-6704-438f-b88f-a1013dd98e9d' class='xr-section-summary-in' type='checkbox' checked><label for='section-d4877fe4-6704-438f-b88f-a1013dd98e9d' 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>average_T1</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(31,), meta=np.ndarray></div><input id='attrs-f883fdb2-719b-449f-958a-8cff18423c17' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f883fdb2-719b-449f-958a-8cff18423c17' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb1e5fb2-4d39-4fb4-9120-97b256c91c9c' class='xr-var-data-in' type='checkbox'><label for='data-cb1e5fb2-4d39-4fb4-9120-97b256c91c9c' 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>long_name :</span></dt><dd>Start time for average period</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n", | |
| "<tr>\n", | |
| "<td>\n", | |
| "<table>\n", | |
| " <thead>\n", | |
| " <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr><th> Bytes </th><td> 488 B </td> <td> 248 B </td></tr>\n", | |
| " <tr><th> Shape </th><td> (61,) </td> <td> (31,) </td></tr>\n", | |
| " <tr><th> Count </th><td> 6 Tasks </td><td> 2 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> datetime64[ns] </td><td> numpy.ndarray </td></tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "</td>\n", | |
| "<td>\n", | |
| "<svg width=\"170\" height=\"77\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"27\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"27\" />\n", | |
| " <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"27\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"0.0,0.0 120.0,0.0 120.0,27.933455479739106 0.0,27.933455479739106\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Text -->\n", | |
| " <text x=\"60.000000\" y=\"47.933455\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >61</text>\n", | |
| " <text x=\"140.000000\" y=\"13.966728\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,13.966728)\">1</text>\n", | |
| "</svg>\n", | |
| "</td>\n", | |
| "</tr>\n", | |
| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_T2</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(31,), meta=np.ndarray></div><input id='attrs-6f011d49-e849-4211-ae71-39d9db9c7d40' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f011d49-e849-4211-ae71-39d9db9c7d40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc396a2b-43b4-4838-9637-c8f8d710c33b' class='xr-var-data-in' type='checkbox'><label for='data-cc396a2b-43b4-4838-9637-c8f8d710c33b' 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>long_name :</span></dt><dd>End time for average period</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n", | |
| "<tr>\n", | |
| "<td>\n", | |
| "<table>\n", | |
| " <thead>\n", | |
| " <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr><th> Bytes </th><td> 488 B </td> <td> 248 B </td></tr>\n", | |
| " <tr><th> Shape </th><td> (61,) </td> <td> (31,) </td></tr>\n", | |
| " <tr><th> Count </th><td> 6 Tasks </td><td> 2 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> datetime64[ns] </td><td> numpy.ndarray </td></tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "</td>\n", | |
| "<td>\n", | |
| "<svg width=\"170\" height=\"77\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"27\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"27\" />\n", | |
| " <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"27\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"0.0,0.0 120.0,0.0 120.0,27.933455479739106 0.0,27.933455479739106\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Text -->\n", | |
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| "<tr>\n", | |
| "<td>\n", | |
| "<table>\n", | |
| " <thead>\n", | |
| " <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr><th> Bytes </th><td> 488 B </td> <td> 248 B </td></tr>\n", | |
| " <tr><th> Shape </th><td> (61,) </td> <td> (31,) </td></tr>\n", | |
| " <tr><th> Count </th><td> 6 Tasks </td><td> 2 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> timedelta64[ns] </td><td> numpy.ndarray </td></tr>\n", | |
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| " <tr><th> Bytes </th><td> 0.95 kiB </td> <td> 496 B </td></tr>\n", | |
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| " <tr><th> Count </th><td> 6 Tasks </td><td> 2 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> timedelta64[ns] </td><td> numpy.ndarray </td></tr>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(Time, st_ocean, yu_ocean, xu_ocean)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(31, 51, 1500, 3600), meta=np.ndarray></div><input id='attrs-671534c5-9f96-4bce-8a4c-0bf45223a916' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-671534c5-9f96-4bce-8a4c-0bf45223a916' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b940bf2a-15f5-4f92-af68-612aa8fd908c' class='xr-var-data-in' type='checkbox'><label for='data-b940bf2a-15f5-4f92-af68-612aa8fd908c' 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>long_name :</span></dt><dd>i-current</dd><dt><span>units :</span></dt><dd>m/sec</dd><dt><span>valid_range :</span></dt><dd>[-32767 32767]</dd><dt><span>packing :</span></dt><dd>4</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>coordinates :</span></dt><dd>geolon_c geolat_c</dd><dt><span>standard_name :</span></dt><dd>sea_water_x_velocity</dd><dt><span>_ChunkSizes :</span></dt><dd>[ 1 1 300 300]</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-c82ad039-aa37-46e4-a651-d7b2a5d2014a' class='xr-section-summary-in' type='checkbox' ><label for='section-c82ad039-aa37-46e4-a651-d7b2a5d2014a' class='xr-section-summary' >Attributes: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filename :</span></dt><dd>TMP/ocean_ofam_2017_03_01.nc.0000</dd><dt><span>NumFilesInSet :</span></dt><dd>20</dd><dt><span>grid_type :</span></dt><dd>regular</dd><dt><span>grid_tile :</span></dt><dd>N/A</dd><dt><span>history :</span></dt><dd>Tue Nov 3 11:18:33 2020: ncrcat -4 --dfl_lvl 1 --cnk_dmn Time,1 --cnk_dmn xu_ocean,300 --cnk_dmn yu_ocean,300 --cnk_dmn st_ocean,1 ocean_u_2017_03_01.nc ocean_u_2017_03_02.nc ocean_u_2017_03_03.nc ocean_u_2017_03_04.nc ocean_u_2017_03_05.nc ocean_u_2017_03_06.nc ocean_u_2017_03_07.nc ocean_u_2017_03_08.nc ocean_u_2017_03_09.nc ocean_u_2017_03_10.nc ocean_u_2017_03_11.nc ocean_u_2017_03_12.nc ocean_u_2017_03_13.nc ocean_u_2017_03_14.nc ocean_u_2017_03_15.nc ocean_u_2017_03_16.nc ocean_u_2017_03_17.nc ocean_u_2017_03_18.nc ocean_u_2017_03_19.nc ocean_u_2017_03_20.nc ocean_u_2017_03_21.nc ocean_u_2017_03_22.nc ocean_u_2017_03_23.nc ocean_u_2017_03_24.nc ocean_u_2017_03_25.nc ocean_u_2017_03_26.nc ocean_u_2017_03_27.nc ocean_u_2017_03_28.nc ocean_u_2017_03_29.nc ocean_u_2017_03_30.nc ocean_u_2017_03_31.nc /g/data/gb6/BRAN/BRAN_junk/OFAM/ocean_u_2017_03.nc</dd><dt><span>NCO :</span></dt><dd>netCDF Operators version 4.9.2 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)</dd><dt><span>title :</span></dt><dd>BRAN2020</dd><dt><span>catalogue_doi_url :</span></dt><dd>http://dx.doi.org/10.25914/6009627c7af03</dd><dt><span>acknowledgement :</span></dt><dd>BRAN is made freely available by CSIRO Bluelink and is supported by the Bluelink Partnership: a collaboration between the Australian Department of Defence, Bureau of Meteorology and CSIRO.</dd><dt><span>DODS_EXTRA.Unlimited_Dimension :</span></dt><dd>Time</dd></dl></div></li></ul></div></div>" | |
| ], | |
| "text/plain": [ | |
| "<xarray.Dataset>\n", | |
| "Dimensions: (xu_ocean: 3600, yu_ocean: 1500, st_ocean: 51, Time: 61, nv: 2, st_edges_ocean: 52)\n", | |
| "Coordinates:\n", | |
| " * xu_ocean (xu_ocean) float64 0.1 0.2 0.3 0.4 ... 359.8 359.9 360.0\n", | |
| " * yu_ocean (yu_ocean) float64 -74.9 -74.8 -74.7 ... 74.8 74.9 75.0\n", | |
| " * st_ocean (st_ocean) float64 2.5 7.5 12.5 ... 3.603e+03 4.509e+03\n", | |
| " * Time (Time) datetime64[ns] 2017-03-01T12:00:00 ... 2017-04-30T...\n", | |
| " * nv (nv) float64 1.0 2.0\n", | |
| " * st_edges_ocean (st_edges_ocean) float64 0.0 5.0 10.0 ... 4.056e+03 5e+03\n", | |
| "Data variables:\n", | |
| " average_T1 (Time) datetime64[ns] dask.array<chunksize=(31,), meta=np.ndarray>\n", | |
| " average_T2 (Time) datetime64[ns] dask.array<chunksize=(31,), meta=np.ndarray>\n", | |
| " average_DT (Time) timedelta64[ns] dask.array<chunksize=(31,), meta=np.ndarray>\n", | |
| " Time_bounds (Time, nv) timedelta64[ns] dask.array<chunksize=(31, 2), meta=np.ndarray>\n", | |
| " u (Time, st_ocean, yu_ocean, xu_ocean) float32 dask.array<chunksize=(31, 51, 1500, 3600), meta=np.ndarray>\n", | |
| "Attributes:\n", | |
| " filename: TMP/ocean_ofam_2017_03_01.nc.0000\n", | |
| " NumFilesInSet: 20\n", | |
| " grid_type: regular\n", | |
| " grid_tile: N/A\n", | |
| " history: Tue Nov 3 11:18:33 2020: ncrcat -4 --df...\n", | |
| " NCO: netCDF Operators version 4.9.2 (Homepage...\n", | |
| " title: BRAN2020\n", | |
| " catalogue_doi_url: http://dx.doi.org/10.25914/6009627c7af03\n", | |
| " acknowledgement: BRAN is made freely available by CSIRO B...\n", | |
| " DODS_EXTRA.Unlimited_Dimension: Time" | |
| ] | |
| }, | |
| "execution_count": 2, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "# Open a collection of files\n", | |
| "u_files = ['https://dapds00.nci.org.au/thredds/dodsC/gb6/BRAN/BRAN2020/daily/ocean_u_2017_03.nc',\n", | |
| " 'https://dapds00.nci.org.au/thredds/dodsC/gb6/BRAN/BRAN2020/daily/ocean_u_2017_04.nc'\n", | |
| " ]\n", | |
| "\n", | |
| "v_files = ['https://dapds00.nci.org.au/thredds/dodsC/gb6/BRAN/BRAN2020/daily/ocean_v_2017_03.nc',\n", | |
| " 'https://dapds00.nci.org.au/thredds/dodsC/gb6/BRAN/BRAN2020/daily/ocean_v_2017_04.nc'\n", | |
| " ]\n", | |
| "\n", | |
| "ds_u = xr.open_mfdataset(u_files)\n", | |
| "ds_v = xr.open_mfdataset(v_files)\n", | |
| "\n", | |
| "ds_u" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 3, | |
| "id": "b2ecdfee", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
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| "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n", | |
| "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n", | |
| "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n", | |
| "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n", | |
| "</symbol>\n", | |
| "</defs>\n", | |
| "</svg>\n", | |
| "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n", | |
| " *\n", | |
| " */\n", | |
| "\n", | |
| ":root {\n", | |
| " --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n", | |
| " --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n", | |
| " --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n", | |
| " --xr-border-color: var(--jp-border-color2, #e0e0e0);\n", | |
| " --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n", | |
| " --xr-background-color: var(--jp-layout-color0, white);\n", | |
| " --xr-background-color-row-even: var(--jp-layout-color1, white);\n", | |
| " --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n", | |
| "}\n", | |
| "\n", | |
| "html[theme=dark],\n", | |
| "body.vscode-dark {\n", | |
| " --xr-font-color0: rgba(255, 255, 255, 1);\n", | |
| " --xr-font-color2: rgba(255, 255, 255, 0.54);\n", | |
| " --xr-font-color3: rgba(255, 255, 255, 0.38);\n", | |
| " --xr-border-color: #1F1F1F;\n", | |
| " --xr-disabled-color: #515151;\n", | |
| " --xr-background-color: #111111;\n", | |
| " --xr-background-color-row-even: #111111;\n", | |
| " --xr-background-color-row-odd: #313131;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-wrap {\n", | |
| " display: block;\n", | |
| " min-width: 300px;\n", | |
| " max-width: 700px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-text-repr-fallback {\n", | |
| " /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n", | |
| " display: none;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-header {\n", | |
| " padding-top: 6px;\n", | |
| " padding-bottom: 6px;\n", | |
| " margin-bottom: 4px;\n", | |
| " border-bottom: solid 1px var(--xr-border-color);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-header > div,\n", | |
| ".xr-header > ul {\n", | |
| " display: inline;\n", | |
| " margin-top: 0;\n", | |
| " margin-bottom: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-obj-type,\n", | |
| ".xr-array-name {\n", | |
| " margin-left: 2px;\n", | |
| " margin-right: 10px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-obj-type {\n", | |
| " color: var(--xr-font-color2);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-sections {\n", | |
| " padding-left: 0 !important;\n", | |
| " display: grid;\n", | |
| " grid-template-columns: 150px auto auto 1fr 20px 20px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item {\n", | |
| " display: contents;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item input {\n", | |
| " display: none;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item input + label {\n", | |
| " color: var(--xr-disabled-color);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item input:enabled + label {\n", | |
| " cursor: pointer;\n", | |
| " color: var(--xr-font-color2);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item input:enabled + label:hover {\n", | |
| " color: var(--xr-font-color0);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary {\n", | |
| " grid-column: 1;\n", | |
| " color: var(--xr-font-color2);\n", | |
| " font-weight: 500;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary > span {\n", | |
| " display: inline-block;\n", | |
| " padding-left: 0.5em;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in:disabled + label {\n", | |
| " color: var(--xr-font-color2);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in + label:before {\n", | |
| " display: inline-block;\n", | |
| " content: '►';\n", | |
| " font-size: 11px;\n", | |
| " width: 15px;\n", | |
| " text-align: center;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in:disabled + label:before {\n", | |
| " color: var(--xr-disabled-color);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in:checked + label:before {\n", | |
| " content: '▼';\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in:checked + label > span {\n", | |
| " display: none;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary,\n", | |
| ".xr-section-inline-details {\n", | |
| " padding-top: 4px;\n", | |
| " padding-bottom: 4px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-inline-details {\n", | |
| " grid-column: 2 / -1;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-details {\n", | |
| " display: none;\n", | |
| " grid-column: 1 / -1;\n", | |
| " margin-bottom: 5px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in:checked ~ .xr-section-details {\n", | |
| " display: contents;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-array-wrap {\n", | |
| " grid-column: 1 / -1;\n", | |
| " display: grid;\n", | |
| " grid-template-columns: 20px auto;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-array-wrap > label {\n", | |
| " grid-column: 1;\n", | |
| " vertical-align: top;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-preview {\n", | |
| " color: var(--xr-font-color3);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-array-preview,\n", | |
| ".xr-array-data {\n", | |
| " padding: 0 5px !important;\n", | |
| " grid-column: 2;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-array-data,\n", | |
| ".xr-array-in:checked ~ .xr-array-preview {\n", | |
| " display: none;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-array-in:checked ~ .xr-array-data,\n", | |
| ".xr-array-preview {\n", | |
| " display: inline-block;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list {\n", | |
| " display: inline-block !important;\n", | |
| " list-style: none;\n", | |
| " padding: 0 !important;\n", | |
| " margin: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list li {\n", | |
| " display: inline-block;\n", | |
| " padding: 0;\n", | |
| " margin: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list:before {\n", | |
| " content: '(';\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list:after {\n", | |
| " content: ')';\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list li:not(:last-child):after {\n", | |
| " content: ',';\n", | |
| " padding-right: 5px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-has-index {\n", | |
| " font-weight: bold;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-list,\n", | |
| ".xr-var-item {\n", | |
| " display: contents;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-item > div,\n", | |
| ".xr-var-item label,\n", | |
| ".xr-var-item > .xr-var-name span {\n", | |
| " background-color: var(--xr-background-color-row-even);\n", | |
| " margin-bottom: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-item > .xr-var-name:hover span {\n", | |
| " padding-right: 5px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-list > li:nth-child(odd) > div,\n", | |
| ".xr-var-list > li:nth-child(odd) > label,\n", | |
| ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n", | |
| " background-color: var(--xr-background-color-row-odd);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-name {\n", | |
| " grid-column: 1;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-dims {\n", | |
| " grid-column: 2;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-dtype {\n", | |
| " grid-column: 3;\n", | |
| " text-align: right;\n", | |
| " color: var(--xr-font-color2);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-preview {\n", | |
| " grid-column: 4;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-name,\n", | |
| ".xr-var-dims,\n", | |
| ".xr-var-dtype,\n", | |
| ".xr-preview,\n", | |
| ".xr-attrs dt {\n", | |
| " white-space: nowrap;\n", | |
| " overflow: hidden;\n", | |
| " text-overflow: ellipsis;\n", | |
| " padding-right: 10px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-name:hover,\n", | |
| ".xr-var-dims:hover,\n", | |
| ".xr-var-dtype:hover,\n", | |
| ".xr-attrs dt:hover {\n", | |
| " overflow: visible;\n", | |
| " width: auto;\n", | |
| " z-index: 1;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-attrs,\n", | |
| ".xr-var-data {\n", | |
| " display: none;\n", | |
| " background-color: var(--xr-background-color) !important;\n", | |
| " padding-bottom: 5px !important;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n", | |
| ".xr-var-data-in:checked ~ .xr-var-data {\n", | |
| " display: block;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-data > table {\n", | |
| " float: right;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-name span,\n", | |
| ".xr-var-data,\n", | |
| ".xr-attrs {\n", | |
| " padding-left: 25px !important;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs,\n", | |
| ".xr-var-attrs,\n", | |
| ".xr-var-data {\n", | |
| " grid-column: 1 / -1;\n", | |
| "}\n", | |
| "\n", | |
| "dl.xr-attrs {\n", | |
| " padding: 0;\n", | |
| " margin: 0;\n", | |
| " display: grid;\n", | |
| " grid-template-columns: 125px auto;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt,\n", | |
| ".xr-attrs dd {\n", | |
| " padding: 0;\n", | |
| " margin: 0;\n", | |
| " float: left;\n", | |
| " padding-right: 10px;\n", | |
| " width: auto;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt {\n", | |
| " font-weight: normal;\n", | |
| " grid-column: 1;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt:hover span {\n", | |
| " display: inline-block;\n", | |
| " background: var(--xr-background-color);\n", | |
| " padding-right: 10px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dd {\n", | |
| " grid-column: 2;\n", | |
| " white-space: pre-wrap;\n", | |
| " word-break: break-all;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-icon-database,\n", | |
| ".xr-icon-file-text2 {\n", | |
| " display: inline-block;\n", | |
| " vertical-align: middle;\n", | |
| " width: 1em;\n", | |
| " height: 1.5em !important;\n", | |
| " stroke-width: 0;\n", | |
| " stroke: currentColor;\n", | |
| " fill: currentColor;\n", | |
| "}\n", | |
| "</style><pre class='xr-text-repr-fallback'><xarray.Dataset>\n", | |
| "Dimensions: (xu_ocean: 3600, yu_ocean: 1500, st_ocean: 51, Time: 61, nv: 2, st_edges_ocean: 52)\n", | |
| "Coordinates:\n", | |
| " * xu_ocean (xu_ocean) float64 0.1 0.2 0.3 0.4 ... 359.8 359.9 360.0\n", | |
| " * yu_ocean (yu_ocean) float64 -74.9 -74.8 -74.7 ... 74.8 74.9 75.0\n", | |
| " * st_ocean (st_ocean) float64 2.5 7.5 12.5 ... 3.603e+03 4.509e+03\n", | |
| " * Time (Time) datetime64[ns] 2017-03-01T12:00:00 ... 2017-04-30T...\n", | |
| " * nv (nv) float64 1.0 2.0\n", | |
| " * st_edges_ocean (st_edges_ocean) float64 0.0 5.0 10.0 ... 4.056e+03 5e+03\n", | |
| "Data variables:\n", | |
| " average_T1 (Time) datetime64[ns] dask.array<chunksize=(31,), meta=np.ndarray>\n", | |
| " average_T2 (Time) datetime64[ns] dask.array<chunksize=(31,), meta=np.ndarray>\n", | |
| " average_DT (Time) timedelta64[ns] dask.array<chunksize=(31,), meta=np.ndarray>\n", | |
| " Time_bounds (Time, nv) timedelta64[ns] dask.array<chunksize=(31, 2), meta=np.ndarray>\n", | |
| " v (Time, st_ocean, yu_ocean, xu_ocean) float32 dask.array<chunksize=(31, 51, 1500, 3600), meta=np.ndarray>\n", | |
| "Attributes:\n", | |
| " filename: TMP/ocean_ofam_2017_03_01.nc.0000\n", | |
| " NumFilesInSet: 20\n", | |
| " grid_type: regular\n", | |
| " grid_tile: N/A\n", | |
| " history: Tue Nov 3 11:23:09 2020: ncrcat -4 --df...\n", | |
| " NCO: netCDF Operators version 4.9.2 (Homepage...\n", | |
| " title: BRAN2020\n", | |
| " catalogue_doi_url: http://dx.doi.org/10.25914/6009627c7af03\n", | |
| " acknowledgement: BRAN is made freely available by CSIRO B...\n", | |
| " DODS_EXTRA.Unlimited_Dimension: Time</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-f59b1760-ea5e-43c5-a4f7-357627e781dd' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f59b1760-ea5e-43c5-a4f7-357627e781dd' 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'>xu_ocean</span>: 3600</li><li><span class='xr-has-index'>yu_ocean</span>: 1500</li><li><span class='xr-has-index'>st_ocean</span>: 51</li><li><span class='xr-has-index'>Time</span>: 61</li><li><span class='xr-has-index'>nv</span>: 2</li><li><span class='xr-has-index'>st_edges_ocean</span>: 52</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-0e0e17e6-c4ca-44b4-aa9d-bd7fbd1a3d11' class='xr-section-summary-in' type='checkbox' checked><label for='section-0e0e17e6-c4ca-44b4-aa9d-bd7fbd1a3d11' class='xr-section-summary' >Coordinates: <span>(6)</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'>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'>0.1 0.2 0.3 ... 359.8 359.9 360.0</div><input id='attrs-ab59dabd-36b6-433b-8ee7-4053dd887512' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ab59dabd-36b6-433b-8ee7-4053dd887512' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ef8b30c-db89-4126-9e82-b4e8229c0287' class='xr-var-data-in' type='checkbox'><label for='data-3ef8b30c-db89-4126-9e82-b4e8229c0287' 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>long_name :</span></dt><dd>ucell longitude</dd><dt><span>units :</span></dt><dd>degrees_E</dd><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>domain_decomposition :</span></dt><dd>[ 1 3600 1 1800]</dd><dt><span>_ChunkSizes :</span></dt><dd>300</dd></dl></div><div class='xr-var-data'><pre>array([1.000e-01, 2.000e-01, 3.000e-01, ..., 3.598e+02, 3.599e+02, 3.600e+02])</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'>-74.9 -74.8 -74.7 ... 74.9 75.0</div><input id='attrs-3ed7bcc3-9c5d-44a3-bd1b-12a3551bf2f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ed7bcc3-9c5d-44a3-bd1b-12a3551bf2f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b99460cd-43bd-44cc-9c7e-6d45c00e9be1' class='xr-var-data-in' type='checkbox'><label for='data-b99460cd-43bd-44cc-9c7e-6d45c00e9be1' 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>long_name :</span></dt><dd>ucell latitude</dd><dt><span>units :</span></dt><dd>degrees_N</dd><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>domain_decomposition :</span></dt><dd>[ 1 1500 1 150]</dd><dt><span>_ChunkSizes :</span></dt><dd>300</dd></dl></div><div class='xr-var-data'><pre>array([-74.900002, -74.800003, -74.699997, ..., 74.800003, 74.900002,\n", | |
| " 75. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>st_ocean</span></div><div class='xr-var-dims'>(st_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.5 7.5 ... 3.603e+03 4.509e+03</div><input id='attrs-c5b50a9f-cf2e-45a9-ae7a-b75e3b44a189' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c5b50a9f-cf2e-45a9-ae7a-b75e3b44a189' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3ee28d7-8bb6-467d-879c-d1c926ea3866' class='xr-var-data-in' type='checkbox'><label for='data-d3ee28d7-8bb6-467d-879c-d1c926ea3866' 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>long_name :</span></dt><dd>tcell zstar depth</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>edges :</span></dt><dd>st_edges_ocean</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([2.500000e+00, 7.500000e+00, 1.250000e+01, 1.751539e+01, 2.266702e+01,\n", | |
| " 2.816938e+01, 3.421801e+01, 4.095498e+01, 4.845498e+01, 5.671801e+01,\n", | |
| " 6.566938e+01, 7.516702e+01, 8.501539e+01, 9.500000e+01, 1.050000e+02,\n", | |
| " 1.150000e+02, 1.250000e+02, 1.350000e+02, 1.450000e+02, 1.550000e+02,\n", | |
| " 1.650000e+02, 1.750000e+02, 1.850000e+02, 1.950000e+02, 2.051899e+02,\n", | |
| " 2.170545e+02, 2.331943e+02, 2.558842e+02, 2.866090e+02, 3.258842e+02,\n", | |
| " 3.731943e+02, 4.270545e+02, 4.851899e+02, 5.455111e+02, 6.104156e+02,\n", | |
| " 6.859268e+02, 7.759268e+02, 8.804156e+02, 9.955111e+02, 1.115313e+03,\n", | |
| " 1.238354e+03, 1.368157e+03, 1.507734e+03, 1.658157e+03, 1.818354e+03,\n", | |
| " 1.985313e+03, 2.165180e+03, 2.431101e+03, 2.894842e+03, 3.603101e+03,\n", | |
| " 4.509180e+03])</pre></div></li><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'>2017-03-01T12:00:00 ... 2017-04-...</div><input id='attrs-181adf03-0f29-4984-88f9-04689de18553' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-181adf03-0f29-4984-88f9-04689de18553' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-998f5e2f-9cd0-4993-b2fd-ce0bbef320b9' class='xr-var-data-in' type='checkbox'><label for='data-998f5e2f-9cd0-4993-b2fd-ce0bbef320b9' 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>long_name :</span></dt><dd>Time</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>GREGORIAN</dd><dt><span>bounds :</span></dt><dd>Time_bounds</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array(['2017-03-01T12:00:00.000000000', '2017-03-02T12:00:00.000000000',\n", | |
| " '2017-03-03T12:00:00.000000000', '2017-03-04T12:00:00.000000000',\n", | |
| " '2017-03-05T12:00:00.000000000', '2017-03-06T12:00:00.000000000',\n", | |
| " '2017-03-07T12:00:00.000000000', '2017-03-08T12:00:00.000000000',\n", | |
| " '2017-03-09T12:00:00.000000000', '2017-03-10T12:00:00.000000000',\n", | |
| " '2017-03-11T12:00:00.000000000', '2017-03-12T12:00:00.000000000',\n", | |
| " '2017-03-13T12:00:00.000000000', '2017-03-14T12:00:00.000000000',\n", | |
| " '2017-03-15T12:00:00.000000000', '2017-03-16T12:00:00.000000000',\n", | |
| " '2017-03-17T12:00:00.000000000', '2017-03-18T12:00:00.000000000',\n", | |
| " '2017-03-19T12:00:00.000000000', '2017-03-20T12:00:00.000000000',\n", | |
| " '2017-03-21T12:00:00.000000000', '2017-03-22T12:00:00.000000000',\n", | |
| " '2017-03-23T12:00:00.000000000', '2017-03-24T12:00:00.000000000',\n", | |
| " '2017-03-25T12:00:00.000000000', '2017-03-26T12:00:00.000000000',\n", | |
| " '2017-03-27T12:00:00.000000000', '2017-03-28T12:00:00.000000000',\n", | |
| " '2017-03-29T12:00:00.000000000', '2017-03-30T12:00:00.000000000',\n", | |
| " '2017-03-31T12:00:00.000000000', '2017-04-01T12:00:00.000000000',\n", | |
| " '2017-04-02T12:00:00.000000000', '2017-04-03T12:00:00.000000000',\n", | |
| " '2017-04-04T12:00:00.000000000', '2017-04-05T12:00:00.000000000',\n", | |
| " '2017-04-06T12:00:00.000000000', '2017-04-07T12:00:00.000000000',\n", | |
| " '2017-04-08T12:00:00.000000000', '2017-04-09T12:00:00.000000000',\n", | |
| " '2017-04-10T12:00:00.000000000', '2017-04-11T12:00:00.000000000',\n", | |
| " '2017-04-12T12:00:00.000000000', '2017-04-13T12:00:00.000000000',\n", | |
| " '2017-04-14T12:00:00.000000000', '2017-04-15T12:00:00.000000000',\n", | |
| " '2017-04-16T12:00:00.000000000', '2017-04-17T12:00:00.000000000',\n", | |
| " '2017-04-18T12:00:00.000000000', '2017-04-19T12:00:00.000000000',\n", | |
| " '2017-04-20T12:00:00.000000000', '2017-04-21T12:00:00.000000000',\n", | |
| " '2017-04-22T12:00:00.000000000', '2017-04-23T12:00:00.000000000',\n", | |
| " '2017-04-24T12:00:00.000000000', '2017-04-25T12:00:00.000000000',\n", | |
| " '2017-04-26T12:00:00.000000000', '2017-04-27T12:00:00.000000000',\n", | |
| " '2017-04-28T12:00:00.000000000', '2017-04-29T12:00:00.000000000',\n", | |
| " '2017-04-30T12:00:00.000000000'], dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nv</span></div><div class='xr-var-dims'>(nv)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0</div><input id='attrs-03e83582-81a5-4f53-bbab-6a41e9a23134' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-03e83582-81a5-4f53-bbab-6a41e9a23134' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8db1a879-e5fd-40c1-887c-029c23e1db5a' class='xr-var-data-in' type='checkbox'><label for='data-8db1a879-e5fd-40c1-887c-029c23e1db5a' 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>_ChunkSizes :</span></dt><dd>2</dd></dl></div><div class='xr-var-data'><pre>array([1., 2.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>st_edges_ocean</span></div><div class='xr-var-dims'>(st_edges_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 5.0 10.0 ... 4.056e+03 5e+03</div><input id='attrs-8e3aaf28-1c88-462d-bb71-4304c5c2ea4a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e3aaf28-1c88-462d-bb71-4304c5c2ea4a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53d54f7e-19f6-4737-bbeb-a844de56450e' class='xr-var-data-in' type='checkbox'><label for='data-53d54f7e-19f6-4737-bbeb-a844de56450e' 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>long_name :</span></dt><dd>tcell zstar depth edges</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>_ChunkSizes :</span></dt><dd>52</dd></dl></div><div class='xr-var-data'><pre>array([ 0. , 5. , 10. , 15.007695, 20.091206,\n", | |
| " 25.4182 , 31.193693, 37.586491, 44.704975, 52.586491,\n", | |
| " 61.193695, 70.418198, 80.091202, 90.007698, 100. ,\n", | |
| " 110. , 120. , 130. , 140. , 150. ,\n", | |
| " 160. , 170. , 180. , 190. , 200.094955,\n", | |
| " 211.122192, 225.124405, 244.539276, 271.246613, 306.246613,\n", | |
| " 349.539276, 400.12442 , 456.122192, 515.350525, 577.963379,\n", | |
| " 648.171204, 730.926758, 828.171204, 937.963379, 1055.412231,\n", | |
| " 1176.833618, 1303.255737, 1437.945679, 1582.945679, 1738.255737,\n", | |
| " 1901.833618, 2075.246826, 2298.140625, 2662.971436, 3248.971436,\n", | |
| " 4056.140625, 5000. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-422723cd-c9aa-44f4-b73e-01aea0019787' class='xr-section-summary-in' type='checkbox' checked><label for='section-422723cd-c9aa-44f4-b73e-01aea0019787' 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>average_T1</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(31,), meta=np.ndarray></div><input id='attrs-6a9fef1c-bb4e-44a6-ad3b-688ef1bea906' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a9fef1c-bb4e-44a6-ad3b-688ef1bea906' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-770e3a24-3c35-4886-b7e1-e9ed77a096bf' class='xr-var-data-in' type='checkbox'><label for='data-770e3a24-3c35-4886-b7e1-e9ed77a096bf' 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>long_name :</span></dt><dd>Start time for average period</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n", | |
| "<tr>\n", | |
| "<td>\n", | |
| "<table>\n", | |
| " <thead>\n", | |
| " <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr><th> Bytes </th><td> 488 B </td> <td> 248 B </td></tr>\n", | |
| " <tr><th> Shape </th><td> (61,) </td> <td> (31,) </td></tr>\n", | |
| " <tr><th> Count </th><td> 6 Tasks </td><td> 2 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> datetime64[ns] </td><td> numpy.ndarray </td></tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "</td>\n", | |
| "<td>\n", | |
| "<svg width=\"170\" height=\"77\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"27\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"27\" />\n", | |
| " <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"27\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"0.0,0.0 120.0,0.0 120.0,27.933455479739106 0.0,27.933455479739106\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Text -->\n", | |
| " <text x=\"60.000000\" y=\"47.933455\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >61</text>\n", | |
| " <text x=\"140.000000\" y=\"13.966728\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,13.966728)\">1</text>\n", | |
| "</svg>\n", | |
| "</td>\n", | |
| "</tr>\n", | |
| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_T2</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(31,), meta=np.ndarray></div><input id='attrs-bf50b039-ec86-4f7f-b929-ba16b6ea90c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf50b039-ec86-4f7f-b929-ba16b6ea90c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98959ca3-c49d-431f-bb20-b8f7541016ee' class='xr-var-data-in' type='checkbox'><label for='data-98959ca3-c49d-431f-bb20-b8f7541016ee' 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>long_name :</span></dt><dd>End time for average period</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n", | |
| "<tr>\n", | |
| "<td>\n", | |
| "<table>\n", | |
| " <thead>\n", | |
| " <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr><th> Bytes </th><td> 488 B </td> <td> 248 B </td></tr>\n", | |
| " <tr><th> Shape </th><td> (61,) </td> <td> (31,) </td></tr>\n", | |
| " <tr><th> Count </th><td> 6 Tasks </td><td> 2 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> datetime64[ns] </td><td> numpy.ndarray </td></tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "</td>\n", | |
| "<td>\n", | |
| "<svg width=\"170\" height=\"77\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"27\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"27\" />\n", | |
| " <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"27\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"0.0,0.0 120.0,0.0 120.0,27.933455479739106 0.0,27.933455479739106\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
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| "text/plain": [ | |
| "<xarray.Dataset>\n", | |
| "Dimensions: (xu_ocean: 3600, yu_ocean: 1500, st_ocean: 51, Time: 61, nv: 2, st_edges_ocean: 52)\n", | |
| "Coordinates:\n", | |
| " * xu_ocean (xu_ocean) float64 0.1 0.2 0.3 0.4 ... 359.8 359.9 360.0\n", | |
| " * yu_ocean (yu_ocean) float64 -74.9 -74.8 -74.7 ... 74.8 74.9 75.0\n", | |
| " * st_ocean (st_ocean) float64 2.5 7.5 12.5 ... 3.603e+03 4.509e+03\n", | |
| " * Time (Time) datetime64[ns] 2017-03-01T12:00:00 ... 2017-04-30T...\n", | |
| " * nv (nv) float64 1.0 2.0\n", | |
| " * st_edges_ocean (st_edges_ocean) float64 0.0 5.0 10.0 ... 4.056e+03 5e+03\n", | |
| "Data variables:\n", | |
| " average_T1 (Time) datetime64[ns] dask.array<chunksize=(31,), meta=np.ndarray>\n", | |
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| " average_DT (Time) timedelta64[ns] dask.array<chunksize=(31,), meta=np.ndarray>\n", | |
| " Time_bounds (Time, nv) timedelta64[ns] dask.array<chunksize=(31, 2), meta=np.ndarray>\n", | |
| " v (Time, st_ocean, yu_ocean, xu_ocean) float32 dask.array<chunksize=(31, 51, 1500, 3600), meta=np.ndarray>\n", | |
| "Attributes:\n", | |
| " filename: TMP/ocean_ofam_2017_03_01.nc.0000\n", | |
| " NumFilesInSet: 20\n", | |
| " grid_type: regular\n", | |
| " grid_tile: N/A\n", | |
| " history: Tue Nov 3 11:23:09 2020: ncrcat -4 --df...\n", | |
| " NCO: netCDF Operators version 4.9.2 (Homepage...\n", | |
| " title: BRAN2020\n", | |
| " catalogue_doi_url: http://dx.doi.org/10.25914/6009627c7af03\n", | |
| " acknowledgement: BRAN is made freely available by CSIRO B...\n", | |
| " DODS_EXTRA.Unlimited_Dimension: Time" | |
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| " --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n", | |
| " --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n", | |
| " --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n", | |
| " --xr-border-color: var(--jp-border-color2, #e0e0e0);\n", | |
| " --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n", | |
| " --xr-background-color: var(--jp-layout-color0, white);\n", | |
| " --xr-background-color-row-even: var(--jp-layout-color1, white);\n", | |
| " --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n", | |
| "}\n", | |
| "\n", | |
| "html[theme=dark],\n", | |
| "body.vscode-dark {\n", | |
| " --xr-font-color0: rgba(255, 255, 255, 1);\n", | |
| " --xr-font-color2: rgba(255, 255, 255, 0.54);\n", | |
| " --xr-font-color3: rgba(255, 255, 255, 0.38);\n", | |
| " --xr-border-color: #1F1F1F;\n", | |
| " --xr-disabled-color: #515151;\n", | |
| " --xr-background-color: #111111;\n", | |
| " --xr-background-color-row-even: #111111;\n", | |
| " --xr-background-color-row-odd: #313131;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-wrap {\n", | |
| " display: block;\n", | |
| " min-width: 300px;\n", | |
| " max-width: 700px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-text-repr-fallback {\n", | |
| " /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n", | |
| " display: none;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-header {\n", | |
| " padding-top: 6px;\n", | |
| " padding-bottom: 6px;\n", | |
| " margin-bottom: 4px;\n", | |
| " border-bottom: solid 1px var(--xr-border-color);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-header > div,\n", | |
| ".xr-header > ul {\n", | |
| " display: inline;\n", | |
| " margin-top: 0;\n", | |
| " margin-bottom: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-obj-type,\n", | |
| ".xr-array-name {\n", | |
| " margin-left: 2px;\n", | |
| " margin-right: 10px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-obj-type {\n", | |
| " color: var(--xr-font-color2);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-sections {\n", | |
| " padding-left: 0 !important;\n", | |
| " display: grid;\n", | |
| " grid-template-columns: 150px auto auto 1fr 20px 20px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item {\n", | |
| " display: contents;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item input {\n", | |
| " display: none;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item input + label {\n", | |
| " color: var(--xr-disabled-color);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item input:enabled + label {\n", | |
| " cursor: pointer;\n", | |
| " color: var(--xr-font-color2);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item input:enabled + label:hover {\n", | |
| " color: var(--xr-font-color0);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary {\n", | |
| " grid-column: 1;\n", | |
| " color: var(--xr-font-color2);\n", | |
| " font-weight: 500;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary > span {\n", | |
| " display: inline-block;\n", | |
| " padding-left: 0.5em;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in:disabled + label {\n", | |
| " color: var(--xr-font-color2);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in + label:before {\n", | |
| " display: inline-block;\n", | |
| " content: '►';\n", | |
| " font-size: 11px;\n", | |
| " width: 15px;\n", | |
| " text-align: center;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in:disabled + label:before {\n", | |
| " color: var(--xr-disabled-color);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in:checked + label:before {\n", | |
| " content: '▼';\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in:checked + label > span {\n", | |
| " display: none;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary,\n", | |
| ".xr-section-inline-details {\n", | |
| " padding-top: 4px;\n", | |
| " padding-bottom: 4px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-inline-details {\n", | |
| " grid-column: 2 / -1;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-details {\n", | |
| " display: none;\n", | |
| " grid-column: 1 / -1;\n", | |
| " margin-bottom: 5px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in:checked ~ .xr-section-details {\n", | |
| " display: contents;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-array-wrap {\n", | |
| " grid-column: 1 / -1;\n", | |
| " display: grid;\n", | |
| " grid-template-columns: 20px auto;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-array-wrap > label {\n", | |
| " grid-column: 1;\n", | |
| " vertical-align: top;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-preview {\n", | |
| " color: var(--xr-font-color3);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-array-preview,\n", | |
| ".xr-array-data {\n", | |
| " padding: 0 5px !important;\n", | |
| " grid-column: 2;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-array-data,\n", | |
| ".xr-array-in:checked ~ .xr-array-preview {\n", | |
| " display: none;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-array-in:checked ~ .xr-array-data,\n", | |
| ".xr-array-preview {\n", | |
| " display: inline-block;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list {\n", | |
| " display: inline-block !important;\n", | |
| " list-style: none;\n", | |
| " padding: 0 !important;\n", | |
| " margin: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list li {\n", | |
| " display: inline-block;\n", | |
| " padding: 0;\n", | |
| " margin: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list:before {\n", | |
| " content: '(';\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list:after {\n", | |
| " content: ')';\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list li:not(:last-child):after {\n", | |
| " content: ',';\n", | |
| " padding-right: 5px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-has-index {\n", | |
| " font-weight: bold;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-list,\n", | |
| ".xr-var-item {\n", | |
| " display: contents;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-item > div,\n", | |
| ".xr-var-item label,\n", | |
| ".xr-var-item > .xr-var-name span {\n", | |
| " background-color: var(--xr-background-color-row-even);\n", | |
| " margin-bottom: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-item > .xr-var-name:hover span {\n", | |
| " padding-right: 5px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-list > li:nth-child(odd) > div,\n", | |
| ".xr-var-list > li:nth-child(odd) > label,\n", | |
| ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n", | |
| " background-color: var(--xr-background-color-row-odd);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-name {\n", | |
| " grid-column: 1;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-dims {\n", | |
| " grid-column: 2;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-dtype {\n", | |
| " grid-column: 3;\n", | |
| " text-align: right;\n", | |
| " color: var(--xr-font-color2);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-preview {\n", | |
| " grid-column: 4;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-name,\n", | |
| ".xr-var-dims,\n", | |
| ".xr-var-dtype,\n", | |
| ".xr-preview,\n", | |
| ".xr-attrs dt {\n", | |
| " white-space: nowrap;\n", | |
| " overflow: hidden;\n", | |
| " text-overflow: ellipsis;\n", | |
| " padding-right: 10px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-name:hover,\n", | |
| ".xr-var-dims:hover,\n", | |
| ".xr-var-dtype:hover,\n", | |
| ".xr-attrs dt:hover {\n", | |
| " overflow: visible;\n", | |
| " width: auto;\n", | |
| " z-index: 1;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-attrs,\n", | |
| ".xr-var-data {\n", | |
| " display: none;\n", | |
| " background-color: var(--xr-background-color) !important;\n", | |
| " padding-bottom: 5px !important;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n", | |
| ".xr-var-data-in:checked ~ .xr-var-data {\n", | |
| " display: block;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-data > table {\n", | |
| " float: right;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-name span,\n", | |
| ".xr-var-data,\n", | |
| ".xr-attrs {\n", | |
| " padding-left: 25px !important;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs,\n", | |
| ".xr-var-attrs,\n", | |
| ".xr-var-data {\n", | |
| " grid-column: 1 / -1;\n", | |
| "}\n", | |
| "\n", | |
| "dl.xr-attrs {\n", | |
| " padding: 0;\n", | |
| " margin: 0;\n", | |
| " display: grid;\n", | |
| " grid-template-columns: 125px auto;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt,\n", | |
| ".xr-attrs dd {\n", | |
| " padding: 0;\n", | |
| " margin: 0;\n", | |
| " float: left;\n", | |
| " padding-right: 10px;\n", | |
| " width: auto;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt {\n", | |
| " font-weight: normal;\n", | |
| " grid-column: 1;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt:hover span {\n", | |
| " display: inline-block;\n", | |
| " background: var(--xr-background-color);\n", | |
| " padding-right: 10px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dd {\n", | |
| " grid-column: 2;\n", | |
| " white-space: pre-wrap;\n", | |
| " word-break: break-all;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-icon-database,\n", | |
| ".xr-icon-file-text2 {\n", | |
| " display: inline-block;\n", | |
| " vertical-align: middle;\n", | |
| " width: 1em;\n", | |
| " height: 1.5em !important;\n", | |
| " stroke-width: 0;\n", | |
| " stroke: currentColor;\n", | |
| " fill: currentColor;\n", | |
| "}\n", | |
| "</style><pre class='xr-text-repr-fallback'><xarray.DataArray 'u' (Time: 61, yu_ocean: 551, xu_ocean: 651)>\n", | |
| "dask.array<getitem, shape=(61, 551, 651), dtype=float32, chunksize=(31, 551, 651), chunktype=numpy.ndarray>\n", | |
| "Coordinates:\n", | |
| " * xu_ocean (xu_ocean) float64 100.0 100.1 100.2 100.3 ... 164.8 164.9 165.0\n", | |
| " * yu_ocean (yu_ocean) float64 -60.0 -59.9 -59.8 -59.7 ... -5.3 -5.2 -5.1 -5.0\n", | |
| " st_ocean float64 2.5\n", | |
| " * Time (Time) datetime64[ns] 2017-03-01T12:00:00 ... 2017-04-30T12:00:00\n", | |
| "Attributes:\n", | |
| " long_name: i-current\n", | |
| " units: m/sec\n", | |
| " valid_range: [-32767 32767]\n", | |
| " packing: 4\n", | |
| " cell_methods: time: mean\n", | |
| " time_avg_info: average_T1,average_T2,average_DT\n", | |
| " coordinates: geolon_c geolat_c\n", | |
| " standard_name: sea_water_x_velocity\n", | |
| " _ChunkSizes: [ 1 1 300 300]</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'u'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>Time</span>: 61</li><li><span class='xr-has-index'>yu_ocean</span>: 551</li><li><span class='xr-has-index'>xu_ocean</span>: 651</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-365fe858-86ae-4fae-a4fb-f7801fee83ea' class='xr-array-in' type='checkbox' checked><label for='section-365fe858-86ae-4fae-a4fb-f7801fee83ea' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array<chunksize=(31, 551, 651), meta=np.ndarray></span></div><div class='xr-array-data'><table>\n", | |
| "<tr>\n", | |
| "<td>\n", | |
| "<table>\n", | |
| " <thead>\n", | |
| " <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr><th> Bytes </th><td> 83.47 MiB </td> <td> 42.42 MiB </td></tr>\n", | |
| " <tr><th> Shape </th><td> (61, 551, 651) </td> <td> (31, 551, 651) </td></tr>\n", | |
| " <tr><th> Count </th><td> 8 Tasks </td><td> 2 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "</td>\n", | |
| "<td>\n", | |
| "<svg width=\"202\" height=\"174\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"32\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"10\" y1=\"101\" x2=\"32\" y2=\"124\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"101\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"112\" />\n", | |
| " <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"124\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"10.0,0.0 32.490174926253616,22.490174926253612 32.490174926253616,124.05699520275131 10.0,101.5668202764977\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"21\" y1=\"11\" x2=\"141\" y2=\"11\" />\n", | |
| " <line x1=\"32\" y1=\"22\" x2=\"152\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"32\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"130\" y1=\"0\" x2=\"152\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"10.0,0.0 130.0,0.0 152.49017492625362,22.490174926253612 32.490174926253616,22.490174926253612\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"32\" y1=\"22\" x2=\"152\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"32\" y1=\"124\" x2=\"152\" y2=\"124\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"124\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"152\" y1=\"22\" x2=\"152\" y2=\"124\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"32.490174926253616,22.490174926253612 152.49017492625362,22.490174926253612 152.49017492625362,124.05699520275131 32.490174926253616,124.05699520275131\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Text -->\n", | |
| " <text x=\"92.490175\" y=\"144.056995\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >651</text>\n", | |
| " <text x=\"172.490175\" y=\"73.273585\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,172.490175,73.273585)\">551</text>\n", | |
| " <text x=\"11.245087\" y=\"132.811908\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,11.245087,132.811908)\">61</text>\n", | |
| "</svg>\n", | |
| "</td>\n", | |
| "</tr>\n", | |
| "</table></div></div></li><li class='xr-section-item'><input id='section-ab0123d1-aeea-4844-aa64-57d4cc57815d' class='xr-section-summary-in' type='checkbox' checked><label for='section-ab0123d1-aeea-4844-aa64-57d4cc57815d' class='xr-section-summary' >Coordinates: <span>(4)</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'>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'>100.0 100.1 100.2 ... 164.9 165.0</div><input id='attrs-3cca5d72-8be9-4d2f-a529-ad5453a03810' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3cca5d72-8be9-4d2f-a529-ad5453a03810' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f87bc55a-8d07-4e11-8ab5-784fc6c6fceb' class='xr-var-data-in' type='checkbox'><label for='data-f87bc55a-8d07-4e11-8ab5-784fc6c6fceb' 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>long_name :</span></dt><dd>ucell longitude</dd><dt><span>units :</span></dt><dd>degrees_E</dd><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>domain_decomposition :</span></dt><dd>[ 1 3600 1 1800]</dd><dt><span>_ChunkSizes :</span></dt><dd>300</dd></dl></div><div class='xr-var-data'><pre>array([100. , 100.099998, 100.199997, ..., 164.800003, 164.899994,\n", | |
| " 165. ])</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'>-60.0 -59.9 -59.8 ... -5.1 -5.0</div><input id='attrs-0274559f-592a-48fc-b660-62fa74abe0cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0274559f-592a-48fc-b660-62fa74abe0cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41b821f8-c01b-4a77-8a20-aec73df4d548' class='xr-var-data-in' type='checkbox'><label for='data-41b821f8-c01b-4a77-8a20-aec73df4d548' 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>long_name :</span></dt><dd>ucell latitude</dd><dt><span>units :</span></dt><dd>degrees_N</dd><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>domain_decomposition :</span></dt><dd>[ 1 1500 1 150]</dd><dt><span>_ChunkSizes :</span></dt><dd>300</dd></dl></div><div class='xr-var-data'><pre>array([-60. , -59.900002, -59.799999, ..., -5.2 , -5.1 ,\n", | |
| " -5. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>st_ocean</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.5</div><input id='attrs-773b6826-f8e1-4501-a8aa-b9ff0ef414de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-773b6826-f8e1-4501-a8aa-b9ff0ef414de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86ddd019-dec9-4628-b2ca-9f1351ab1ab6' class='xr-var-data-in' type='checkbox'><label for='data-86ddd019-dec9-4628-b2ca-9f1351ab1ab6' 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>long_name :</span></dt><dd>tcell zstar depth</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>edges :</span></dt><dd>st_edges_ocean</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array(2.5)</pre></div></li><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'>2017-03-01T12:00:00 ... 2017-04-...</div><input id='attrs-4ce5269a-3aa6-4fde-b80f-23dd38cd5d35' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ce5269a-3aa6-4fde-b80f-23dd38cd5d35' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c0aebd9-d3d4-46bb-bf99-3387f67addf2' class='xr-var-data-in' type='checkbox'><label for='data-8c0aebd9-d3d4-46bb-bf99-3387f67addf2' 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>long_name :</span></dt><dd>Time</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>GREGORIAN</dd><dt><span>bounds :</span></dt><dd>Time_bounds</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array(['2017-03-01T12:00:00.000000000', '2017-03-02T12:00:00.000000000',\n", | |
| " '2017-03-03T12:00:00.000000000', '2017-03-04T12:00:00.000000000',\n", | |
| " '2017-03-05T12:00:00.000000000', '2017-03-06T12:00:00.000000000',\n", | |
| " '2017-03-07T12:00:00.000000000', '2017-03-08T12:00:00.000000000',\n", | |
| " '2017-03-09T12:00:00.000000000', '2017-03-10T12:00:00.000000000',\n", | |
| " '2017-03-11T12:00:00.000000000', '2017-03-12T12:00:00.000000000',\n", | |
| " '2017-03-13T12:00:00.000000000', '2017-03-14T12:00:00.000000000',\n", | |
| " '2017-03-15T12:00:00.000000000', '2017-03-16T12:00:00.000000000',\n", | |
| " '2017-03-17T12:00:00.000000000', '2017-03-18T12:00:00.000000000',\n", | |
| " '2017-03-19T12:00:00.000000000', '2017-03-20T12:00:00.000000000',\n", | |
| " '2017-03-21T12:00:00.000000000', '2017-03-22T12:00:00.000000000',\n", | |
| " '2017-03-23T12:00:00.000000000', '2017-03-24T12:00:00.000000000',\n", | |
| " '2017-03-25T12:00:00.000000000', '2017-03-26T12:00:00.000000000',\n", | |
| " '2017-03-27T12:00:00.000000000', '2017-03-28T12:00:00.000000000',\n", | |
| " '2017-03-29T12:00:00.000000000', '2017-03-30T12:00:00.000000000',\n", | |
| " '2017-03-31T12:00:00.000000000', '2017-04-01T12:00:00.000000000',\n", | |
| " '2017-04-02T12:00:00.000000000', '2017-04-03T12:00:00.000000000',\n", | |
| " '2017-04-04T12:00:00.000000000', '2017-04-05T12:00:00.000000000',\n", | |
| " '2017-04-06T12:00:00.000000000', '2017-04-07T12:00:00.000000000',\n", | |
| " '2017-04-08T12:00:00.000000000', '2017-04-09T12:00:00.000000000',\n", | |
| " '2017-04-10T12:00:00.000000000', '2017-04-11T12:00:00.000000000',\n", | |
| " '2017-04-12T12:00:00.000000000', '2017-04-13T12:00:00.000000000',\n", | |
| " '2017-04-14T12:00:00.000000000', '2017-04-15T12:00:00.000000000',\n", | |
| " '2017-04-16T12:00:00.000000000', '2017-04-17T12:00:00.000000000',\n", | |
| " '2017-04-18T12:00:00.000000000', '2017-04-19T12:00:00.000000000',\n", | |
| " '2017-04-20T12:00:00.000000000', '2017-04-21T12:00:00.000000000',\n", | |
| " '2017-04-22T12:00:00.000000000', '2017-04-23T12:00:00.000000000',\n", | |
| " '2017-04-24T12:00:00.000000000', '2017-04-25T12:00:00.000000000',\n", | |
| " '2017-04-26T12:00:00.000000000', '2017-04-27T12:00:00.000000000',\n", | |
| " '2017-04-28T12:00:00.000000000', '2017-04-29T12:00:00.000000000',\n", | |
| " '2017-04-30T12:00:00.000000000'], dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7a60f2e1-8018-4c0d-92f4-1c0a7343f189' class='xr-section-summary-in' type='checkbox' checked><label for='section-7a60f2e1-8018-4c0d-92f4-1c0a7343f189' class='xr-section-summary' >Attributes: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>i-current</dd><dt><span>units :</span></dt><dd>m/sec</dd><dt><span>valid_range :</span></dt><dd>[-32767 32767]</dd><dt><span>packing :</span></dt><dd>4</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>coordinates :</span></dt><dd>geolon_c geolat_c</dd><dt><span>standard_name :</span></dt><dd>sea_water_x_velocity</dd><dt><span>_ChunkSizes :</span></dt><dd>[ 1 1 300 300]</dd></dl></div></li></ul></div></div>" | |
| ], | |
| "text/plain": [ | |
| "<xarray.DataArray 'u' (Time: 61, yu_ocean: 551, xu_ocean: 651)>\n", | |
| "dask.array<getitem, shape=(61, 551, 651), dtype=float32, chunksize=(31, 551, 651), chunktype=numpy.ndarray>\n", | |
| "Coordinates:\n", | |
| " * xu_ocean (xu_ocean) float64 100.0 100.1 100.2 100.3 ... 164.8 164.9 165.0\n", | |
| " * yu_ocean (yu_ocean) float64 -60.0 -59.9 -59.8 -59.7 ... -5.3 -5.2 -5.1 -5.0\n", | |
| " st_ocean float64 2.5\n", | |
| " * Time (Time) datetime64[ns] 2017-03-01T12:00:00 ... 2017-04-30T12:00:00\n", | |
| "Attributes:\n", | |
| " long_name: i-current\n", | |
| " units: m/sec\n", | |
| " valid_range: [-32767 32767]\n", | |
| " packing: 4\n", | |
| " cell_methods: time: mean\n", | |
| " time_avg_info: average_T1,average_T2,average_DT\n", | |
| " coordinates: geolon_c geolat_c\n", | |
| " standard_name: sea_water_x_velocity\n", | |
| " _ChunkSizes: [ 1 1 300 300]" | |
| ] | |
| }, | |
| "execution_count": 4, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "# Domain\n", | |
| "x0,x1 = 100,165\n", | |
| "y0,y1 = -60, -5\n", | |
| "\n", | |
| "# Subset an xarray.DataArray\n", | |
| "my_u = ds_u['u'].sel(xu_ocean=slice(x0,x1), yu_ocean=slice(y0,y1), st_ocean=2.5)\n", | |
| "my_v = ds_v['v'].sel(xu_ocean=slice(x0,x1), yu_ocean=slice(y0,y1), st_ocean=2.5)\n", | |
| "\n", | |
| "my_u\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 18, | |
| "id": "56eda975", | |
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| ".xr-dim-list {\n", | |
| " display: inline-block !important;\n", | |
| " list-style: none;\n", | |
| " padding: 0 !important;\n", | |
| " margin: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list li {\n", | |
| " display: inline-block;\n", | |
| " padding: 0;\n", | |
| " margin: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list:before {\n", | |
| " content: '(';\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list:after {\n", | |
| " content: ')';\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list li:not(:last-child):after {\n", | |
| " content: ',';\n", | |
| " padding-right: 5px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-has-index {\n", | |
| " font-weight: bold;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-list,\n", | |
| ".xr-var-item {\n", | |
| " display: contents;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-item > div,\n", | |
| ".xr-var-item label,\n", | |
| ".xr-var-item > .xr-var-name span {\n", | |
| " background-color: var(--xr-background-color-row-even);\n", | |
| " margin-bottom: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-item > .xr-var-name:hover span {\n", | |
| " padding-right: 5px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-list > li:nth-child(odd) > div,\n", | |
| ".xr-var-list > li:nth-child(odd) > label,\n", | |
| ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n", | |
| " background-color: var(--xr-background-color-row-odd);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-name {\n", | |
| " grid-column: 1;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-dims {\n", | |
| " grid-column: 2;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-dtype {\n", | |
| " grid-column: 3;\n", | |
| " text-align: right;\n", | |
| " color: var(--xr-font-color2);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-preview {\n", | |
| " grid-column: 4;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-name,\n", | |
| ".xr-var-dims,\n", | |
| ".xr-var-dtype,\n", | |
| ".xr-preview,\n", | |
| ".xr-attrs dt {\n", | |
| " white-space: nowrap;\n", | |
| " overflow: hidden;\n", | |
| " text-overflow: ellipsis;\n", | |
| " padding-right: 10px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-name:hover,\n", | |
| ".xr-var-dims:hover,\n", | |
| ".xr-var-dtype:hover,\n", | |
| ".xr-attrs dt:hover {\n", | |
| " overflow: visible;\n", | |
| " width: auto;\n", | |
| " z-index: 1;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-attrs,\n", | |
| ".xr-var-data {\n", | |
| " display: none;\n", | |
| " background-color: var(--xr-background-color) !important;\n", | |
| " padding-bottom: 5px !important;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n", | |
| ".xr-var-data-in:checked ~ .xr-var-data {\n", | |
| " display: block;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-data > table {\n", | |
| " float: right;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-name span,\n", | |
| ".xr-var-data,\n", | |
| ".xr-attrs {\n", | |
| " padding-left: 25px !important;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs,\n", | |
| ".xr-var-attrs,\n", | |
| ".xr-var-data {\n", | |
| " grid-column: 1 / -1;\n", | |
| "}\n", | |
| "\n", | |
| "dl.xr-attrs {\n", | |
| " padding: 0;\n", | |
| " margin: 0;\n", | |
| " display: grid;\n", | |
| " grid-template-columns: 125px auto;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt,\n", | |
| ".xr-attrs dd {\n", | |
| " padding: 0;\n", | |
| " margin: 0;\n", | |
| " float: left;\n", | |
| " padding-right: 10px;\n", | |
| " width: auto;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt {\n", | |
| " font-weight: normal;\n", | |
| " grid-column: 1;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt:hover span {\n", | |
| " display: inline-block;\n", | |
| " background: var(--xr-background-color);\n", | |
| " padding-right: 10px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dd {\n", | |
| " grid-column: 2;\n", | |
| " white-space: pre-wrap;\n", | |
| " word-break: break-all;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-icon-database,\n", | |
| ".xr-icon-file-text2 {\n", | |
| " display: inline-block;\n", | |
| " vertical-align: middle;\n", | |
| " width: 1em;\n", | |
| " height: 1.5em !important;\n", | |
| " stroke-width: 0;\n", | |
| " stroke: currentColor;\n", | |
| " fill: currentColor;\n", | |
| "}\n", | |
| "</style><pre class='xr-text-repr-fallback'><xarray.DataArray (Time: 61, yu_ocean: 551, xu_ocean: 651)>\n", | |
| "dask.array<absolute, shape=(61, 551, 651), dtype=float32, chunksize=(31, 551, 651), chunktype=numpy.ndarray>\n", | |
| "Coordinates:\n", | |
| " * xu_ocean (xu_ocean) float64 100.0 100.1 100.2 100.3 ... 164.8 164.9 165.0\n", | |
| " * yu_ocean (yu_ocean) float64 -60.0 -59.9 -59.8 -59.7 ... -5.3 -5.2 -5.1 -5.0\n", | |
| " st_ocean float64 2.5\n", | |
| " * Time (Time) datetime64[ns] 2017-03-01T12:00:00 ... 2017-04-30T12:00:00</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>Time</span>: 61</li><li><span class='xr-has-index'>yu_ocean</span>: 551</li><li><span class='xr-has-index'>xu_ocean</span>: 651</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-a1a50fc4-a8a1-4723-900b-54c14c491b99' class='xr-array-in' type='checkbox' checked><label for='section-a1a50fc4-a8a1-4723-900b-54c14c491b99' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array<chunksize=(31, 551, 651), meta=np.ndarray></span></div><div class='xr-array-data'><table>\n", | |
| "<tr>\n", | |
| "<td>\n", | |
| "<table>\n", | |
| " <thead>\n", | |
| " <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr><th> Bytes </th><td> 83.47 MiB </td> <td> 42.42 MiB </td></tr>\n", | |
| " <tr><th> Shape </th><td> (61, 551, 651) </td> <td> (31, 551, 651) </td></tr>\n", | |
| " <tr><th> Count </th><td> 22 Tasks </td><td> 2 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "</td>\n", | |
| "<td>\n", | |
| "<svg width=\"202\" height=\"174\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"32\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"10\" y1=\"101\" x2=\"32\" y2=\"124\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"101\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"112\" />\n", | |
| " <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"124\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"10.0,0.0 32.490174926253616,22.490174926253612 32.490174926253616,124.05699520275131 10.0,101.5668202764977\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"21\" y1=\"11\" x2=\"141\" y2=\"11\" />\n", | |
| " <line x1=\"32\" y1=\"22\" x2=\"152\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"32\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"130\" y1=\"0\" x2=\"152\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"10.0,0.0 130.0,0.0 152.49017492625362,22.490174926253612 32.490174926253616,22.490174926253612\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"32\" y1=\"22\" x2=\"152\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"32\" y1=\"124\" x2=\"152\" y2=\"124\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"124\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"152\" y1=\"22\" x2=\"152\" y2=\"124\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"32.490174926253616,22.490174926253612 152.49017492625362,22.490174926253612 152.49017492625362,124.05699520275131 32.490174926253616,124.05699520275131\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Text -->\n", | |
| " <text x=\"92.490175\" y=\"144.056995\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >651</text>\n", | |
| " <text x=\"172.490175\" y=\"73.273585\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,172.490175,73.273585)\">551</text>\n", | |
| " <text x=\"11.245087\" y=\"132.811908\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,11.245087,132.811908)\">61</text>\n", | |
| "</svg>\n", | |
| "</td>\n", | |
| "</tr>\n", | |
| "</table></div></div></li><li class='xr-section-item'><input id='section-4f1c269f-abe9-4cf6-ba7b-64545eb0da6e' class='xr-section-summary-in' type='checkbox' checked><label for='section-4f1c269f-abe9-4cf6-ba7b-64545eb0da6e' class='xr-section-summary' >Coordinates: <span>(4)</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'>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'>100.0 100.1 100.2 ... 164.9 165.0</div><input id='attrs-2157430a-9164-458c-84c5-5fbf87d91a24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2157430a-9164-458c-84c5-5fbf87d91a24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53c7340a-3d9b-48d6-9ab3-b3eb0e82d1ac' class='xr-var-data-in' type='checkbox'><label for='data-53c7340a-3d9b-48d6-9ab3-b3eb0e82d1ac' 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>long_name :</span></dt><dd>ucell longitude</dd><dt><span>units :</span></dt><dd>degrees_E</dd><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>domain_decomposition :</span></dt><dd>[ 1 3600 1 1800]</dd><dt><span>_ChunkSizes :</span></dt><dd>300</dd></dl></div><div class='xr-var-data'><pre>array([100. , 100.099998, 100.199997, ..., 164.800003, 164.899994,\n", | |
| " 165. ])</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'>-60.0 -59.9 -59.8 ... -5.1 -5.0</div><input id='attrs-512616fc-6c39-4d12-8b13-61d25e414e48' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-512616fc-6c39-4d12-8b13-61d25e414e48' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3460e3f9-c4fd-4d33-a8dd-e47f98eb6da8' class='xr-var-data-in' type='checkbox'><label for='data-3460e3f9-c4fd-4d33-a8dd-e47f98eb6da8' 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>long_name :</span></dt><dd>ucell latitude</dd><dt><span>units :</span></dt><dd>degrees_N</dd><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>domain_decomposition :</span></dt><dd>[ 1 1500 1 150]</dd><dt><span>_ChunkSizes :</span></dt><dd>300</dd></dl></div><div class='xr-var-data'><pre>array([-60. , -59.900002, -59.799999, ..., -5.2 , -5.1 ,\n", | |
| " -5. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>st_ocean</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.5</div><input id='attrs-17df24e7-43dc-4107-a456-b716a0bdb378' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17df24e7-43dc-4107-a456-b716a0bdb378' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d069755c-f51d-4e8c-bd67-78f5850f0c9f' class='xr-var-data-in' type='checkbox'><label for='data-d069755c-f51d-4e8c-bd67-78f5850f0c9f' 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>long_name :</span></dt><dd>tcell zstar depth</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>edges :</span></dt><dd>st_edges_ocean</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array(2.5)</pre></div></li><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'>2017-03-01T12:00:00 ... 2017-04-...</div><input id='attrs-f7c2a8cf-5f64-4bb5-ad57-263ead91f4a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7c2a8cf-5f64-4bb5-ad57-263ead91f4a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1dff2f72-b9fe-44cb-893e-8cf80352a2a7' class='xr-var-data-in' type='checkbox'><label for='data-1dff2f72-b9fe-44cb-893e-8cf80352a2a7' 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>long_name :</span></dt><dd>Time</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>GREGORIAN</dd><dt><span>bounds :</span></dt><dd>Time_bounds</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array(['2017-03-01T12:00:00.000000000', '2017-03-02T12:00:00.000000000',\n", | |
| " '2017-03-03T12:00:00.000000000', '2017-03-04T12:00:00.000000000',\n", | |
| " '2017-03-05T12:00:00.000000000', '2017-03-06T12:00:00.000000000',\n", | |
| " '2017-03-07T12:00:00.000000000', '2017-03-08T12:00:00.000000000',\n", | |
| " '2017-03-09T12:00:00.000000000', '2017-03-10T12:00:00.000000000',\n", | |
| " '2017-03-11T12:00:00.000000000', '2017-03-12T12:00:00.000000000',\n", | |
| " '2017-03-13T12:00:00.000000000', '2017-03-14T12:00:00.000000000',\n", | |
| " '2017-03-15T12:00:00.000000000', '2017-03-16T12:00:00.000000000',\n", | |
| " '2017-03-17T12:00:00.000000000', '2017-03-18T12:00:00.000000000',\n", | |
| " '2017-03-19T12:00:00.000000000', '2017-03-20T12:00:00.000000000',\n", | |
| " '2017-03-21T12:00:00.000000000', '2017-03-22T12:00:00.000000000',\n", | |
| " '2017-03-23T12:00:00.000000000', '2017-03-24T12:00:00.000000000',\n", | |
| " '2017-03-25T12:00:00.000000000', '2017-03-26T12:00:00.000000000',\n", | |
| " '2017-03-27T12:00:00.000000000', '2017-03-28T12:00:00.000000000',\n", | |
| " '2017-03-29T12:00:00.000000000', '2017-03-30T12:00:00.000000000',\n", | |
| " '2017-03-31T12:00:00.000000000', '2017-04-01T12:00:00.000000000',\n", | |
| " '2017-04-02T12:00:00.000000000', '2017-04-03T12:00:00.000000000',\n", | |
| " '2017-04-04T12:00:00.000000000', '2017-04-05T12:00:00.000000000',\n", | |
| " '2017-04-06T12:00:00.000000000', '2017-04-07T12:00:00.000000000',\n", | |
| " '2017-04-08T12:00:00.000000000', '2017-04-09T12:00:00.000000000',\n", | |
| " '2017-04-10T12:00:00.000000000', '2017-04-11T12:00:00.000000000',\n", | |
| " '2017-04-12T12:00:00.000000000', '2017-04-13T12:00:00.000000000',\n", | |
| " '2017-04-14T12:00:00.000000000', '2017-04-15T12:00:00.000000000',\n", | |
| " '2017-04-16T12:00:00.000000000', '2017-04-17T12:00:00.000000000',\n", | |
| " '2017-04-18T12:00:00.000000000', '2017-04-19T12:00:00.000000000',\n", | |
| " '2017-04-20T12:00:00.000000000', '2017-04-21T12:00:00.000000000',\n", | |
| " '2017-04-22T12:00:00.000000000', '2017-04-23T12:00:00.000000000',\n", | |
| " '2017-04-24T12:00:00.000000000', '2017-04-25T12:00:00.000000000',\n", | |
| " '2017-04-26T12:00:00.000000000', '2017-04-27T12:00:00.000000000',\n", | |
| " '2017-04-28T12:00:00.000000000', '2017-04-29T12:00:00.000000000',\n", | |
| " '2017-04-30T12:00:00.000000000'], dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4432fef1-05e5-4c85-8162-ec38852f6f7a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4432fef1-05e5-4c85-8162-ec38852f6f7a' 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.DataArray (Time: 61, yu_ocean: 551, xu_ocean: 651)>\n", | |
| "dask.array<absolute, shape=(61, 551, 651), dtype=float32, chunksize=(31, 551, 651), chunktype=numpy.ndarray>\n", | |
| "Coordinates:\n", | |
| " * xu_ocean (xu_ocean) float64 100.0 100.1 100.2 100.3 ... 164.8 164.9 165.0\n", | |
| " * yu_ocean (yu_ocean) float64 -60.0 -59.9 -59.8 -59.7 ... -5.3 -5.2 -5.1 -5.0\n", | |
| " st_ocean float64 2.5\n", | |
| " * Time (Time) datetime64[ns] 2017-03-01T12:00:00 ... 2017-04-30T12:00:00" | |
| ] | |
| }, | |
| "execution_count": 18, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "speed = np.abs(my_u + 1j*my_v)\n", | |
| "speed" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 19, | |
| "id": "7efd87b2", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "CPU times: user 3.25 s, sys: 708 ms, total: 3.96 s\n", | |
| "Wall time: 1min 3s\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "%%time\n", | |
| "# (this will actually download the data)\n", | |
| "speed = speed.compute()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 37, | |
| "id": "04a88032", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/html": [ | |
| "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n", | |
| "<defs>\n", | |
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| "</defs>\n", | |
| "</svg>\n", | |
| "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n", | |
| " *\n", | |
| " */\n", | |
| "\n", | |
| ":root {\n", | |
| " --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n", | |
| " --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n", | |
| " --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n", | |
| " --xr-border-color: var(--jp-border-color2, #e0e0e0);\n", | |
| " --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n", | |
| " --xr-background-color: var(--jp-layout-color0, white);\n", | |
| " --xr-background-color-row-even: var(--jp-layout-color1, white);\n", | |
| " --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n", | |
| "}\n", | |
| "\n", | |
| "html[theme=dark],\n", | |
| "body.vscode-dark {\n", | |
| " --xr-font-color0: rgba(255, 255, 255, 1);\n", | |
| " --xr-font-color2: rgba(255, 255, 255, 0.54);\n", | |
| " --xr-font-color3: rgba(255, 255, 255, 0.38);\n", | |
| " --xr-border-color: #1F1F1F;\n", | |
| " --xr-disabled-color: #515151;\n", | |
| " --xr-background-color: #111111;\n", | |
| " --xr-background-color-row-even: #111111;\n", | |
| " --xr-background-color-row-odd: #313131;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-wrap {\n", | |
| " display: block;\n", | |
| " min-width: 300px;\n", | |
| " max-width: 700px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-text-repr-fallback {\n", | |
| " /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n", | |
| " display: none;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-header {\n", | |
| " padding-top: 6px;\n", | |
| " padding-bottom: 6px;\n", | |
| " margin-bottom: 4px;\n", | |
| " border-bottom: solid 1px var(--xr-border-color);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-header > div,\n", | |
| ".xr-header > ul {\n", | |
| " display: inline;\n", | |
| " margin-top: 0;\n", | |
| " margin-bottom: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-obj-type,\n", | |
| ".xr-array-name {\n", | |
| " margin-left: 2px;\n", | |
| " margin-right: 10px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-obj-type {\n", | |
| " color: var(--xr-font-color2);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-sections {\n", | |
| " padding-left: 0 !important;\n", | |
| " display: grid;\n", | |
| " grid-template-columns: 150px auto auto 1fr 20px 20px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item {\n", | |
| " display: contents;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item input {\n", | |
| " display: none;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item input + label {\n", | |
| " color: var(--xr-disabled-color);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item input:enabled + label {\n", | |
| " cursor: pointer;\n", | |
| " color: var(--xr-font-color2);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item input:enabled + label:hover {\n", | |
| " color: var(--xr-font-color0);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary {\n", | |
| " grid-column: 1;\n", | |
| " color: var(--xr-font-color2);\n", | |
| " font-weight: 500;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary > span {\n", | |
| " display: inline-block;\n", | |
| " padding-left: 0.5em;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in:disabled + label {\n", | |
| " color: var(--xr-font-color2);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in + label:before {\n", | |
| " display: inline-block;\n", | |
| " content: '►';\n", | |
| " font-size: 11px;\n", | |
| " width: 15px;\n", | |
| " text-align: center;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in:disabled + label:before {\n", | |
| " color: var(--xr-disabled-color);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in:checked + label:before {\n", | |
| " content: '▼';\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in:checked + label > span {\n", | |
| " display: none;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary,\n", | |
| ".xr-section-inline-details {\n", | |
| " padding-top: 4px;\n", | |
| " padding-bottom: 4px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-inline-details {\n", | |
| " grid-column: 2 / -1;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-details {\n", | |
| " display: none;\n", | |
| " grid-column: 1 / -1;\n", | |
| " margin-bottom: 5px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in:checked ~ .xr-section-details {\n", | |
| " display: contents;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-array-wrap {\n", | |
| " grid-column: 1 / -1;\n", | |
| " display: grid;\n", | |
| " grid-template-columns: 20px auto;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-array-wrap > label {\n", | |
| " grid-column: 1;\n", | |
| " vertical-align: top;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-preview {\n", | |
| " color: var(--xr-font-color3);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-array-preview,\n", | |
| ".xr-array-data {\n", | |
| " padding: 0 5px !important;\n", | |
| " grid-column: 2;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-array-data,\n", | |
| ".xr-array-in:checked ~ .xr-array-preview {\n", | |
| " display: none;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-array-in:checked ~ .xr-array-data,\n", | |
| ".xr-array-preview {\n", | |
| " display: inline-block;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list {\n", | |
| " display: inline-block !important;\n", | |
| " list-style: none;\n", | |
| " padding: 0 !important;\n", | |
| " margin: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list li {\n", | |
| " display: inline-block;\n", | |
| " padding: 0;\n", | |
| " margin: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list:before {\n", | |
| " content: '(';\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list:after {\n", | |
| " content: ')';\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list li:not(:last-child):after {\n", | |
| " content: ',';\n", | |
| " padding-right: 5px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-has-index {\n", | |
| " font-weight: bold;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-list,\n", | |
| ".xr-var-item {\n", | |
| " display: contents;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-item > div,\n", | |
| ".xr-var-item label,\n", | |
| ".xr-var-item > .xr-var-name span {\n", | |
| " background-color: var(--xr-background-color-row-even);\n", | |
| " margin-bottom: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-item > .xr-var-name:hover span {\n", | |
| " padding-right: 5px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-list > li:nth-child(odd) > div,\n", | |
| ".xr-var-list > li:nth-child(odd) > label,\n", | |
| ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n", | |
| " background-color: var(--xr-background-color-row-odd);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-name {\n", | |
| " grid-column: 1;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-dims {\n", | |
| " grid-column: 2;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-dtype {\n", | |
| " grid-column: 3;\n", | |
| " text-align: right;\n", | |
| " color: var(--xr-font-color2);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-preview {\n", | |
| " grid-column: 4;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-name,\n", | |
| ".xr-var-dims,\n", | |
| ".xr-var-dtype,\n", | |
| ".xr-preview,\n", | |
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| " white-space: nowrap;\n", | |
| " overflow: hidden;\n", | |
| " text-overflow: ellipsis;\n", | |
| " padding-right: 10px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-name:hover,\n", | |
| ".xr-var-dims:hover,\n", | |
| ".xr-var-dtype:hover,\n", | |
| ".xr-attrs dt:hover {\n", | |
| " overflow: visible;\n", | |
| " width: auto;\n", | |
| " z-index: 1;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-attrs,\n", | |
| ".xr-var-data {\n", | |
| " display: none;\n", | |
| " background-color: var(--xr-background-color) !important;\n", | |
| " padding-bottom: 5px !important;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n", | |
| ".xr-var-data-in:checked ~ .xr-var-data {\n", | |
| " display: block;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-data > table {\n", | |
| " float: right;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-name span,\n", | |
| ".xr-var-data,\n", | |
| ".xr-attrs {\n", | |
| " padding-left: 25px !important;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs,\n", | |
| ".xr-var-attrs,\n", | |
| ".xr-var-data {\n", | |
| " grid-column: 1 / -1;\n", | |
| "}\n", | |
| "\n", | |
| "dl.xr-attrs {\n", | |
| " padding: 0;\n", | |
| " margin: 0;\n", | |
| " display: grid;\n", | |
| " grid-template-columns: 125px auto;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt,\n", | |
| ".xr-attrs dd {\n", | |
| " padding: 0;\n", | |
| " margin: 0;\n", | |
| " float: left;\n", | |
| " padding-right: 10px;\n", | |
| " width: auto;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt {\n", | |
| " font-weight: normal;\n", | |
| " grid-column: 1;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt:hover span {\n", | |
| " display: inline-block;\n", | |
| " background: var(--xr-background-color);\n", | |
| " padding-right: 10px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dd {\n", | |
| " grid-column: 2;\n", | |
| " white-space: pre-wrap;\n", | |
| " word-break: break-all;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-icon-database,\n", | |
| ".xr-icon-file-text2 {\n", | |
| " display: inline-block;\n", | |
| " vertical-align: middle;\n", | |
| " width: 1em;\n", | |
| " height: 1.5em !important;\n", | |
| " stroke-width: 0;\n", | |
| " stroke: currentColor;\n", | |
| " fill: currentColor;\n", | |
| "}\n", | |
| "</style><pre class='xr-text-repr-fallback'><xarray.Dataset>\n", | |
| "Dimensions: (xu_ocean: 651, yu_ocean: 551, Time: 61)\n", | |
| "Coordinates:\n", | |
| " * xu_ocean (xu_ocean) float64 100.0 100.1 100.2 100.3 ... 164.8 164.9 165.0\n", | |
| " * yu_ocean (yu_ocean) float64 -60.0 -59.9 -59.8 -59.7 ... -5.3 -5.2 -5.1 -5.0\n", | |
| " st_ocean float64 2.5\n", | |
| " * Time (Time) datetime64[ns] 2017-03-01T12:00:00 ... 2017-04-30T12:00:00\n", | |
| "Data variables:\n", | |
| " u (Time, yu_ocean, xu_ocean) float32 dask.array<chunksize=(31, 551, 651), meta=np.ndarray>\n", | |
| " v (Time, yu_ocean, xu_ocean) float32 dask.array<chunksize=(31, 551, 651), meta=np.ndarray>\n", | |
| " speed (Time, yu_ocean, xu_ocean) float32 0.07966 0.07961 ... 0.2713</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-d8485127-3e9a-407d-8fd3-ca498d08128b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d8485127-3e9a-407d-8fd3-ca498d08128b' 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'>xu_ocean</span>: 651</li><li><span class='xr-has-index'>yu_ocean</span>: 551</li><li><span class='xr-has-index'>Time</span>: 61</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8eb09b62-1d1b-42ac-8819-1f15de3732fe' class='xr-section-summary-in' type='checkbox' checked><label for='section-8eb09b62-1d1b-42ac-8819-1f15de3732fe' class='xr-section-summary' >Coordinates: <span>(4)</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'>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'>100.0 100.1 100.2 ... 164.9 165.0</div><input id='attrs-c265eb8e-3c8c-4e72-ad0a-5ddea1934fe6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c265eb8e-3c8c-4e72-ad0a-5ddea1934fe6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3d571bc-3b40-4497-abce-2ad5ee07c2d2' class='xr-var-data-in' type='checkbox'><label for='data-f3d571bc-3b40-4497-abce-2ad5ee07c2d2' 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>long_name :</span></dt><dd>ucell longitude</dd><dt><span>units :</span></dt><dd>degrees_E</dd><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>domain_decomposition :</span></dt><dd>[ 1 3600 1 1800]</dd><dt><span>_ChunkSizes :</span></dt><dd>300</dd></dl></div><div class='xr-var-data'><pre>array([100. , 100.099998, 100.199997, ..., 164.800003, 164.899994,\n", | |
| " 165. ])</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'>-60.0 -59.9 -59.8 ... -5.1 -5.0</div><input id='attrs-809375af-ef9c-4a8d-8736-acea0b77cc29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-809375af-ef9c-4a8d-8736-acea0b77cc29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4cd1038b-8a1f-4a06-9550-5a716cd85aa3' class='xr-var-data-in' type='checkbox'><label for='data-4cd1038b-8a1f-4a06-9550-5a716cd85aa3' 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>long_name :</span></dt><dd>ucell latitude</dd><dt><span>units :</span></dt><dd>degrees_N</dd><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>domain_decomposition :</span></dt><dd>[ 1 1500 1 150]</dd><dt><span>_ChunkSizes :</span></dt><dd>300</dd></dl></div><div class='xr-var-data'><pre>array([-60. , -59.900002, -59.799999, ..., -5.2 , -5.1 ,\n", | |
| " -5. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>st_ocean</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.5</div><input id='attrs-cbb99263-5d43-418d-b80b-e2209d3d8262' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cbb99263-5d43-418d-b80b-e2209d3d8262' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f790af1-9cb1-40e8-8ce6-3b9bae80a34e' class='xr-var-data-in' type='checkbox'><label for='data-9f790af1-9cb1-40e8-8ce6-3b9bae80a34e' 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>long_name :</span></dt><dd>tcell zstar depth</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>edges :</span></dt><dd>st_edges_ocean</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array(2.5)</pre></div></li><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'>2017-03-01T12:00:00 ... 2017-04-...</div><input id='attrs-1a43a41f-a057-4f02-ade9-0022fed0980f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a43a41f-a057-4f02-ade9-0022fed0980f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c76ec5a-216f-4178-b767-45bd8cf687b6' class='xr-var-data-in' type='checkbox'><label for='data-0c76ec5a-216f-4178-b767-45bd8cf687b6' 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>long_name :</span></dt><dd>Time</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>GREGORIAN</dd><dt><span>bounds :</span></dt><dd>Time_bounds</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array(['2017-03-01T12:00:00.000000000', '2017-03-02T12:00:00.000000000',\n", | |
| " '2017-03-03T12:00:00.000000000', '2017-03-04T12:00:00.000000000',\n", | |
| " '2017-03-05T12:00:00.000000000', '2017-03-06T12:00:00.000000000',\n", | |
| " '2017-03-07T12:00:00.000000000', '2017-03-08T12:00:00.000000000',\n", | |
| " '2017-03-09T12:00:00.000000000', '2017-03-10T12:00:00.000000000',\n", | |
| " '2017-03-11T12:00:00.000000000', '2017-03-12T12:00:00.000000000',\n", | |
| " '2017-03-13T12:00:00.000000000', '2017-03-14T12:00:00.000000000',\n", | |
| " '2017-03-15T12:00:00.000000000', '2017-03-16T12:00:00.000000000',\n", | |
| " '2017-03-17T12:00:00.000000000', '2017-03-18T12:00:00.000000000',\n", | |
| " '2017-03-19T12:00:00.000000000', '2017-03-20T12:00:00.000000000',\n", | |
| " '2017-03-21T12:00:00.000000000', '2017-03-22T12:00:00.000000000',\n", | |
| " '2017-03-23T12:00:00.000000000', '2017-03-24T12:00:00.000000000',\n", | |
| " '2017-03-25T12:00:00.000000000', '2017-03-26T12:00:00.000000000',\n", | |
| " '2017-03-27T12:00:00.000000000', '2017-03-28T12:00:00.000000000',\n", | |
| " '2017-03-29T12:00:00.000000000', '2017-03-30T12:00:00.000000000',\n", | |
| " '2017-03-31T12:00:00.000000000', '2017-04-01T12:00:00.000000000',\n", | |
| " '2017-04-02T12:00:00.000000000', '2017-04-03T12:00:00.000000000',\n", | |
| " '2017-04-04T12:00:00.000000000', '2017-04-05T12:00:00.000000000',\n", | |
| " '2017-04-06T12:00:00.000000000', '2017-04-07T12:00:00.000000000',\n", | |
| " '2017-04-08T12:00:00.000000000', '2017-04-09T12:00:00.000000000',\n", | |
| " '2017-04-10T12:00:00.000000000', '2017-04-11T12:00:00.000000000',\n", | |
| " '2017-04-12T12:00:00.000000000', '2017-04-13T12:00:00.000000000',\n", | |
| " '2017-04-14T12:00:00.000000000', '2017-04-15T12:00:00.000000000',\n", | |
| " '2017-04-16T12:00:00.000000000', '2017-04-17T12:00:00.000000000',\n", | |
| " '2017-04-18T12:00:00.000000000', '2017-04-19T12:00:00.000000000',\n", | |
| " '2017-04-20T12:00:00.000000000', '2017-04-21T12:00:00.000000000',\n", | |
| " '2017-04-22T12:00:00.000000000', '2017-04-23T12:00:00.000000000',\n", | |
| " '2017-04-24T12:00:00.000000000', '2017-04-25T12:00:00.000000000',\n", | |
| " '2017-04-26T12:00:00.000000000', '2017-04-27T12:00:00.000000000',\n", | |
| " '2017-04-28T12:00:00.000000000', '2017-04-29T12:00:00.000000000',\n", | |
| " '2017-04-30T12:00:00.000000000'], dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5ae52d0c-b016-42dc-a229-4cb44b090e04' class='xr-section-summary-in' type='checkbox' checked><label for='section-5ae52d0c-b016-42dc-a229-4cb44b090e04' class='xr-section-summary' >Data variables: <span>(3)</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>u</span></div><div class='xr-var-dims'>(Time, yu_ocean, xu_ocean)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(31, 551, 651), meta=np.ndarray></div><input id='attrs-65ed2b12-e09c-4da3-8ffc-fd9e8b0a621d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65ed2b12-e09c-4da3-8ffc-fd9e8b0a621d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d772bea-91cc-4ecf-9ed1-e63aa197d2c2' class='xr-var-data-in' type='checkbox'><label for='data-3d772bea-91cc-4ecf-9ed1-e63aa197d2c2' 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>long_name :</span></dt><dd>i-current</dd><dt><span>units :</span></dt><dd>m/sec</dd><dt><span>valid_range :</span></dt><dd>[-32767 32767]</dd><dt><span>packing :</span></dt><dd>4</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>coordinates :</span></dt><dd>geolon_c geolat_c</dd><dt><span>standard_name :</span></dt><dd>sea_water_x_velocity</dd><dt><span>_ChunkSizes :</span></dt><dd>[ 1 1 300 300]</dd></dl></div><div class='xr-var-data'><table>\n", | |
| "<tr>\n", | |
| "<td>\n", | |
| "<table>\n", | |
| " <thead>\n", | |
| " <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr><th> Bytes </th><td> 83.47 MiB </td> <td> 42.42 MiB </td></tr>\n", | |
| " <tr><th> Shape </th><td> (61, 551, 651) </td> <td> (31, 551, 651) </td></tr>\n", | |
| " <tr><th> Count </th><td> 8 Tasks </td><td> 2 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "</td>\n", | |
| "<td>\n", | |
| "<svg width=\"202\" height=\"174\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", | |
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| " <text x=\"92.490175\" y=\"144.056995\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >651</text>\n", | |
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| "</tr>\n", | |
| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(Time, yu_ocean, xu_ocean)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(31, 551, 651), meta=np.ndarray></div><input id='attrs-65646ba8-4539-42cc-b713-d0d669c18cdc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65646ba8-4539-42cc-b713-d0d669c18cdc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27a56fcd-a614-4be2-870d-eda3e99279bd' class='xr-var-data-in' type='checkbox'><label for='data-27a56fcd-a614-4be2-870d-eda3e99279bd' 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>long_name :</span></dt><dd>j-current</dd><dt><span>units :</span></dt><dd>m/sec</dd><dt><span>valid_range :</span></dt><dd>[-32767 32767]</dd><dt><span>packing :</span></dt><dd>4</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>coordinates :</span></dt><dd>geolon_c geolat_c</dd><dt><span>standard_name :</span></dt><dd>sea_water_y_velocity</dd><dt><span>_ChunkSizes :</span></dt><dd>[ 1 1 300 300]</dd></dl></div><div class='xr-var-data'><table>\n", | |
| "<tr>\n", | |
| "<td>\n", | |
| "<table>\n", | |
| " <thead>\n", | |
| " <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr><th> Bytes </th><td> 83.47 MiB </td> <td> 42.42 MiB </td></tr>\n", | |
| " <tr><th> Shape </th><td> (61, 551, 651) </td> <td> (31, 551, 651) </td></tr>\n", | |
| " <tr><th> Count </th><td> 8 Tasks </td><td> 2 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n", | |
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| "</table>\n", | |
| "</td>\n", | |
| "<td>\n", | |
| "<svg width=\"202\" height=\"174\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
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| " <text x=\"92.490175\" y=\"144.056995\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >651</text>\n", | |
| " <text x=\"172.490175\" y=\"73.273585\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,172.490175,73.273585)\">551</text>\n", | |
| " <text x=\"11.245087\" y=\"132.811908\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,11.245087,132.811908)\">61</text>\n", | |
| "</svg>\n", | |
| "</td>\n", | |
| "</tr>\n", | |
| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>speed</span></div><div class='xr-var-dims'>(Time, yu_ocean, xu_ocean)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.07966 0.07961 ... 0.2685 0.2713</div><input id='attrs-731f8a67-4023-4b64-96ed-a13d8427eb44' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-731f8a67-4023-4b64-96ed-a13d8427eb44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d07b317-efbe-4a1c-86f1-f33e43cc7811' class='xr-var-data-in' type='checkbox'><label for='data-5d07b317-efbe-4a1c-86f1-f33e43cc7811' 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'></dl></div><div class='xr-var-data'><pre>array([[[0.07965565, 0.07961179, 0.09294678, ..., 0.22735061,\n", | |
| " 0.19117598, 0.10559404],\n", | |
| " [0.09001926, 0.07767066, 0.07142439, ..., 0.24725115,\n", | |
| " 0.22588027, 0.15304904],\n", | |
| " [0.10835274, 0.07763948, 0.05603534, ..., 0.22853719,\n", | |
| " 0.23399816, 0.2150533 ],\n", | |
| " ...,\n", | |
| " [0.26346827, 0.26222077, 0.23642156, ..., 0.5612967 ,\n", | |
| " 0.5365946 , 0.51855904],\n", | |
| " [0.26416567, 0.2666993 , 0.24689192, ..., 0.7019412 ,\n", | |
| " 0.6928431 , 0.68514967],\n", | |
| " [0.2538854 , 0.25483248, 0.24556042, ..., 0.85726947,\n", | |
| " 0.8574561 , 0.84905773]],\n", | |
| "\n", | |
| " [[0.23255125, 0.2214948 , 0.22308195, ..., 0.14247994,\n", | |
| " 0.12381078, 0.08280589],\n", | |
| " [0.22067563, 0.19543406, 0.18412173, ..., 0.16313735,\n", | |
| " 0.16810824, 0.15402174],\n", | |
| " [0.20393148, 0.15680486, 0.13298123, ..., 0.15443994,\n", | |
| " 0.17572832, 0.19736227],\n", | |
| "...\n", | |
| " [0.40023637, 0.41888475, 0.41167027, ..., 0.14464904,\n", | |
| " 0.11601852, 0.10995349],\n", | |
| " [0.36335295, 0.3772074 , 0.36845398, ..., 0.16012797,\n", | |
| " 0.15861553, 0.17510845],\n", | |
| " [0.33083218, 0.32237023, 0.31240013, ..., 0.1999766 ,\n", | |
| " 0.2185528 , 0.24590647]],\n", | |
| "\n", | |
| " [[0.1323156 , 0.14085044, 0.14901066, ..., 0.3345359 ,\n", | |
| " 0.33811548, 0.34788114],\n", | |
| " [0.1588986 , 0.1715922 , 0.17499776, ..., 0.3130161 ,\n", | |
| " 0.31088054, 0.31659448],\n", | |
| " [0.14601919, 0.15428366, 0.16216244, ..., 0.2523218 ,\n", | |
| " 0.24678381, 0.24901327],\n", | |
| " ...,\n", | |
| " [0.1596471 , 0.1883081 , 0.224862 , ..., 0.18726656,\n", | |
| " 0.15518805, 0.14441156],\n", | |
| " [0.14015938, 0.16672158, 0.20723574, ..., 0.22123478,\n", | |
| " 0.20641887, 0.20339939],\n", | |
| " [0.14407355, 0.15565667, 0.193522 , ..., 0.26578116,\n", | |
| " 0.26847026, 0.27130732]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7ea719d2-4a00-48a0-9f41-48e78d8f9bd0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7ea719d2-4a00-48a0-9f41-48e78d8f9bd0' 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: (xu_ocean: 651, yu_ocean: 551, Time: 61)\n", | |
| "Coordinates:\n", | |
| " * xu_ocean (xu_ocean) float64 100.0 100.1 100.2 100.3 ... 164.8 164.9 165.0\n", | |
| " * yu_ocean (yu_ocean) float64 -60.0 -59.9 -59.8 -59.7 ... -5.3 -5.2 -5.1 -5.0\n", | |
| " st_ocean float64 2.5\n", | |
| " * Time (Time) datetime64[ns] 2017-03-01T12:00:00 ... 2017-04-30T12:00:00\n", | |
| "Data variables:\n", | |
| " u (Time, yu_ocean, xu_ocean) float32 dask.array<chunksize=(31, 551, 651), meta=np.ndarray>\n", | |
| " v (Time, yu_ocean, xu_ocean) float32 dask.array<chunksize=(31, 551, 651), meta=np.ndarray>\n", | |
| " speed (Time, yu_ocean, xu_ocean) float32 0.07966 0.07961 ... 0.2713" | |
| ] | |
| }, | |
| "execution_count": 37, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "out_ds = xr.Dataset({'u':my_u,'v':my_v,'speed':speed})\n", | |
| "out_ds" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 61, | |
| "id": "ccfd6516", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "def plotbox(ax,xylims, **kwargs):\n", | |
| " x0,x1,y0,y1 = xylims\n", | |
| " return ax.plot([x0, x1, x1, x0, x0],\n", | |
| " [y0, y0, y1, y1, y0], **kwargs)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 65, | |
| "id": "9ceac475", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 576x432 with 2 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| }, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "# Plot a time step \n", | |
| "\n", | |
| "x0,x1 = 122.75, 123.75\n", | |
| "y0,y1 = -14.4, -13.5\n", | |
| "\n", | |
| "fig=plt.figure(figsize=(8,6))\n", | |
| "ax = fig.add_subplot(1, 1, 1, facecolor='k')\n", | |
| "out_ds['speed'][0,...].plot(cmap=cm.speed, vmin=0, vmax=1.0, ax=ax)\n", | |
| "out_ds['v'][0,...].plot(cmap='Greys_r', alpha=0.2, vmin=-1, vmax=1, ax=ax,add_colorbar=False)\n", | |
| "\n", | |
| "plotbox(ax, (x0,x1,y0,y1),c='r',ls='-')\n", | |
| "ax.set_aspect('equal')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 66, | |
| "id": "a1d5a8eb", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "def custom_plotfunc(ds, fig, tt, framedim=\"Time\", **kwargs):\n", | |
| " ax = fig.add_subplot(1, 1, 1, facecolor='k')\n", | |
| " ax.set_aspect('equal')\n", | |
| " ds['speed'].isel({framedim:tt}).plot(cmap=cm.speed, **kwargs)\n", | |
| " ds['v'].isel({framedim:tt})\\\n", | |
| " .plot(cmap='Greys_r', alpha=0.2, vmin=-1, vmax=1, ax=ax,add_colorbar=False)\n", | |
| " \n", | |
| " plotbox(ax, (x0,x1,y0,y1),c='r',ls='-')\n", | |
| "\n", | |
| " " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 67, | |
| "id": "2c9d0f8a", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "application/vnd.jupyter.widget-view+json": { | |
| "model_id": "70634db25ce4404d8a34ef5f887ae84c", | |
| "version_major": 2, | |
| "version_minor": 0 | |
| }, | |
| "text/plain": [ | |
| " 0%| | 0/61 [00:00<?, ?it/s]" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| }, | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "Movie created at BRAN2020_SurfaceSpeed.mp4\n" | |
| ] | |
| }, | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 576x432 with 0 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "fig=plt.figure(figsize=(8,6))\n", | |
| "\n", | |
| "mov_custom = Movie(out_ds, plotfunc=custom_plotfunc, framedim=\"Time\",\n", | |
| " vmin=0, vmax=1.,extend='max', input_check=False)\n", | |
| "mov_custom.save('../FIGURES/BRAN2020_SurfaceSpeed.mp4', progress=True, overwrite_existing=True)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "id": "e8ab9de3", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| } | |
| ], | |
| "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": "3.7.3" | |
| } | |
| }, | |
| "nbformat": 4, | |
| "nbformat_minor": 5 | |
| } |
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