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July 6, 2022 20:36
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zarr_example
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| { | |
| "cells": [ | |
| { | |
| "metadata": { | |
| "trusted": true | |
| }, | |
| "cell_type": "code", | |
| "source": "import xarray as xr\n\n\nurl = \"https://tds.marine.rutgers.edu/thredds/dodsC/roms/doppio/2017_da/avg/Averages_Best\"\nds = xr.open_dataset(url)", | |
| "execution_count": 1, | |
| "outputs": [] | |
| }, | |
| { | |
| "metadata": { | |
| "trusted": true | |
| }, | |
| "cell_type": "code", | |
| "source": "time_slice = {\"time\": \"2022-06-06\"}\nsurface = {\"s_rho\": -1}\n\nds = ds[[\"temp\", \"salt\"]].sel(time_slice).isel(surface)", | |
| "execution_count": 2, | |
| "outputs": [] | |
| }, | |
| { | |
| "metadata": { | |
| "trusted": true | |
| }, | |
| "cell_type": "code", | |
| "source": "import zarr\n\n\ncompressor = zarr.Blosc(clevel=2, shuffle=-1)\n\n\nfname = \"doppio/doppio_compressed.zarr\"\n\nds.to_zarr(\n fname,\n mode=\"w\",\n safe_chunks=True,\n consolidated=True,\n encoding={\n var: {\"compressor\": compressor} for var in ds.variables\n },\n);", | |
| "execution_count": 3, | |
| "outputs": [] | |
| }, | |
| { | |
| "metadata": { | |
| "trusted": true | |
| }, | |
| "cell_type": "code", | |
| "source": "!ls doppio/*zarr\n!du -h doppio/*zarr", | |
| "execution_count": 4, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": "lat_rho lon_rho salt\ts_rho temp time time_run\n144K\tdoppio/doppio_compressed.zarr/salt\n156K\tdoppio/doppio_compressed.zarr/lat_rho\n148K\tdoppio/doppio_compressed.zarr/temp\n16K\tdoppio/doppio_compressed.zarr/time\n16K\tdoppio/doppio_compressed.zarr/s_rho\n16K\tdoppio/doppio_compressed.zarr/time_run\n156K\tdoppio/doppio_compressed.zarr/lon_rho\n676K\tdoppio/doppio_compressed.zarr\n", | |
| "name": "stdout" | |
| } | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "trusted": true | |
| }, | |
| "cell_type": "code", | |
| "source": "subset = xr.open_zarr(fname)\n\nsubset", | |
| "execution_count": 5, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "execution_count": 5, | |
| "data": { | |
| "text/plain": "<xarray.Dataset>\nDimensions: (eta_rho: 106, xi_rho: 242, time: 1)\nCoordinates:\n lat_rho (eta_rho, xi_rho) float64 dask.array<chunksize=(106, 242), meta=np.ndarray>\n lon_rho (eta_rho, xi_rho) float64 dask.array<chunksize=(106, 242), meta=np.ndarray>\n s_rho float64 ...\n * time (time) datetime64[ns] 2022-06-06T12:00:00\n time_run (time) datetime64[ns] dask.array<chunksize=(1,), meta=np.ndarray>\nDimensions without coordinates: eta_rho, xi_rho\nData variables:\n salt (time, eta_rho, xi_rho) float64 dask.array<chunksize=(1, 106, 242), meta=np.ndarray>\n temp (time, eta_rho, xi_rho) float64 dask.array<chunksize=(1, 106, 242), meta=np.ndarray>\nAttributes: (12/46)\n CPP_options: DOPPIO, ADD_FSOBC, ADD_M2OBC, ANA_BSFLUX...\n Conventions: CF-1.4, SGRID-0.3\n DODS_EXTRA.Unlimited_Dimension: ocean_time\n NLM_LBC: \\nEDGE: WEST SOUTH EAST NORTH \\nz...\n NLM_TADV: \\nADVECTION: HORIZONTAL VERTICAL ...\n _CoordSysBuilder: ucar.nc2.dataset.conv.CF1Convention\n ... ...\n svn_url: https://www.myroms.org/svn/src/trunk\n tide_file: /home/om/roms/doppio/7km/doppio_tide_7km.nc\n tiling: 004x004\n title: ROMS doppio Real-Time Operational PSAS F...\n type: ROMS/TOMS nonlinear model averages file\n var_info: ../Data/varinfo1040t_daily.dat", | |
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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>\nDimensions: (eta_rho: 106, xi_rho: 242, time: 1)\nCoordinates:\n lat_rho (eta_rho, xi_rho) float64 dask.array<chunksize=(106, 242), meta=np.ndarray>\n lon_rho (eta_rho, xi_rho) float64 dask.array<chunksize=(106, 242), meta=np.ndarray>\n s_rho float64 ...\n * time (time) datetime64[ns] 2022-06-06T12:00:00\n time_run (time) datetime64[ns] dask.array<chunksize=(1,), meta=np.ndarray>\nDimensions without coordinates: eta_rho, xi_rho\nData variables:\n salt (time, eta_rho, xi_rho) float64 dask.array<chunksize=(1, 106, 242), meta=np.ndarray>\n temp (time, eta_rho, xi_rho) float64 dask.array<chunksize=(1, 106, 242), meta=np.ndarray>\nAttributes: (12/46)\n CPP_options: DOPPIO, ADD_FSOBC, ADD_M2OBC, ANA_BSFLUX...\n Conventions: CF-1.4, SGRID-0.3\n DODS_EXTRA.Unlimited_Dimension: ocean_time\n NLM_LBC: \\nEDGE: WEST SOUTH EAST NORTH \\nz...\n NLM_TADV: \\nADVECTION: HORIZONTAL VERTICAL ...\n _CoordSysBuilder: ucar.nc2.dataset.conv.CF1Convention\n ... ...\n svn_url: https://www.myroms.org/svn/src/trunk\n tide_file: /home/om/roms/doppio/7km/doppio_tide_7km.nc\n tiling: 004x004\n title: ROMS doppio Real-Time Operational PSAS F...\n type: ROMS/TOMS nonlinear model averages file\n var_info: ../Data/varinfo1040t_daily.dat</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-735c154b-c368-444b-9629-5c4940d79bdd' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-735c154b-c368-444b-9629-5c4940d79bdd' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>eta_rho</span>: 106</li><li><span>xi_rho</span>: 242</li><li><span class='xr-has-index'>time</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-0ae34ef8-2827-4d0d-b6a2-1a3537841bad' class='xr-section-summary-in' type='checkbox' checked><label for='section-0ae34ef8-2827-4d0d-b6a2-1a3537841bad' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat_rho</span></div><div class='xr-var-dims'>(eta_rho, xi_rho)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(106, 242), meta=np.ndarray></div><input id='attrs-d346e8d7-ef84-4057-b494-8b29b83f0ab3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d346e8d7-ef84-4057-b494-8b29b83f0ab3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23333ba5-8b3d-41f0-b7a9-e1a5c5350ad2' class='xr-var-data-in' type='checkbox'><label for='data-23333ba5-8b3d-41f0-b7a9-e1a5c5350ad2' 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>[106, 242]</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>field :</span></dt><dd>lat_rho, scalar</dd><dt><span>long_name :</span></dt><dd>latitude of RHO-points</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n <tr>\n <td>\n <table>\n <thead>\n <tr>\n <td> </td>\n <th> Array </th>\n <th> Chunk </th>\n </tr>\n </thead>\n <tbody>\n \n <tr>\n <th> Bytes </th>\n <td> 200.41 kiB </td>\n <td> 200.41 kiB </td>\n </tr>\n \n <tr>\n <th> Shape </th>\n <td> (106, 242) </td>\n <td> (106, 242) </td>\n </tr>\n <tr>\n <th> Count </th>\n <td> 2 Tasks </td>\n <td> 1 Chunks </td>\n </tr>\n <tr>\n <th> Type </th>\n <td> float64 </td>\n <td> numpy.ndarray </td>\n </tr>\n </tbody>\n </table>\n </td>\n <td>\n <svg width=\"170\" height=\"102\" 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=\"52\" x2=\"120\" y2=\"52\" style=\"stroke-width:2\" />\n\n <!-- Vertical lines -->\n <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"52\" style=\"stroke-width:2\" />\n <line x1=\"120\" y1=\"0\" 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class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-001cd879-cbe5-4024-bce5-e9d33bf692b9' class='xr-var-data-in' type='checkbox'><label for='data-001cd879-cbe5-4024-bce5-e9d33bf692b9' 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>[106, 242]</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>field :</span></dt><dd>lon_rho, scalar</dd><dt><span>long_name :</span></dt><dd>longitude of RHO-points</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n <tr>\n <td>\n <table>\n <thead>\n <tr>\n <td> </td>\n <th> Array </th>\n <th> Chunk </th>\n </tr>\n </thead>\n <tbody>\n \n <tr>\n <th> Bytes </th>\n <td> 200.41 kiB </td>\n <td> 200.41 kiB </td>\n </tr>\n \n <tr>\n <th> Shape </th>\n <td> (106, 242) </td>\n <td> (106, 242) </td>\n </tr>\n <tr>\n <th> Count </th>\n <td> 2 Tasks </td>\n <td> 1 Chunks </td>\n </tr>\n <tr>\n <th> Type </th>\n <td> float64 </td>\n <td> numpy.ndarray </td>\n </tr>\n </tbody>\n </table>\n </td>\n <td>\n <svg width=\"170\" height=\"102\" 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=\"52\" x2=\"120\" y2=\"52\" style=\"stroke-width:2\" />\n\n <!-- Vertical lines -->\n <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"52\" style=\"stroke-width:2\" />\n <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"52\" style=\"stroke-width:2\" />\n\n <!-- Colored Rectangle -->\n <polygon points=\"0.0,0.0 120.0,0.0 120.0,52.56198347107438 0.0,52.56198347107438\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n\n <!-- Text -->\n <text x=\"60.000000\" y=\"72.561983\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >242</text>\n <text x=\"140.000000\" y=\"26.280992\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,26.280992)\">106</text>\n</svg>\n </td>\n </tr>\n</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>s_rho</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a1b89c86-0c45-45b5-9c4f-f5e075cc2f05' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a1b89c86-0c45-45b5-9c4f-f5e075cc2f05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d9b5ee7-6a2f-4628-a422-e2ac9a10f07b' class='xr-var-data-in' type='checkbox'><label for='data-5d9b5ee7-6a2f-4628-a422-e2ac9a10f07b' 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>_CoordinateAxes :</span></dt><dd>s_rho</dd><dt><span>_CoordinateAxisType :</span></dt><dd>GeoZ</dd><dt><span>_CoordinateTransformType :</span></dt><dd>Vertical</dd><dt><span>_CoordinateZisPositive :</span></dt><dd>up</dd><dt><span>field :</span></dt><dd>s_rho, scalar</dd><dt><span>formula_terms :</span></dt><dd>s: s_rho C: Cs_r eta: zeta depth: h depth_c: hc</dd><dt><span>long_name :</span></dt><dd>S-coordinate at RHO-points</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>ocean_s_coordinate_g2</dd><dt><span>units :</span></dt><dd></dd><dt><span>valid_max :</span></dt><dd>0.0</dd><dt><span>valid_min :</span></dt><dd>-1.0</dd></dl></div><div class='xr-var-data'><pre>array(-0.0125)</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'>2022-06-06T12:00:00</div><input id='attrs-6bb6f258-78d3-46a2-ad59-38599afc075f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6bb6f258-78d3-46a2-ad59-38599afc075f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0436be9b-e8f3-4d31-84eb-1876ec440aaf' class='xr-var-data-in' type='checkbox'><label for='data-0436be9b-e8f3-4d31-84eb-1876ec440aaf' 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>_CoordinateAxisType :</span></dt><dd>Time</dd><dt><span>long_name :</span></dt><dd>Forecast time for ForecastModelRunCollection</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(['2022-06-06T12:00:00.000000000'], dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_run</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=(1,), meta=np.ndarray></div><input id='attrs-9a27cceb-3e68-4582-902c-280255d2734e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a27cceb-3e68-4582-902c-280255d2734e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a66f8ba-2b3a-4037-87c9-d097b5f22d4c' class='xr-var-data-in' type='checkbox'><label for='data-7a66f8ba-2b3a-4037-87c9-d097b5f22d4c' 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>_CoordinateAxisType :</span></dt><dd>RunTime</dd><dt><span>long_name :</span></dt><dd>run times for coordinate = time</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><table>\n <tr>\n <td>\n <table>\n <thead>\n <tr>\n <td> </td>\n <th> Array </th>\n <th> Chunk </th>\n </tr>\n </thead>\n <tbody>\n \n <tr>\n <th> Bytes </th>\n <td> 8 B </td>\n <td> 8 B </td>\n </tr>\n \n <tr>\n <th> Shape </th>\n <td> (1,) </td>\n <td> (1,) </td>\n </tr>\n <tr>\n <th> Count </th>\n <td> 2 Tasks </td>\n <td> 1 Chunks </td>\n </tr>\n <tr>\n <th> Type </th>\n <td> datetime64[ns] </td>\n <td> numpy.ndarray </td>\n </tr>\n </tbody>\n </table>\n </td>\n <td>\n <svg width=\"170\" height=\"170\" 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=\"120\" x2=\"120\" y2=\"120\" style=\"stroke-width:2\" />\n\n <!-- Vertical lines -->\n <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"120\" style=\"stroke-width:2\" />\n\n <!-- Colored Rectangle -->\n <polygon points=\"0.0,0.0 120.0,0.0 120.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n\n <!-- Text -->\n <text x=\"60.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1</text>\n <text x=\"140.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,60.000000)\">1</text>\n</svg>\n </td>\n </tr>\n</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-200d4982-0d06-489e-a0cd-93a7da664c38' class='xr-section-summary-in' type='checkbox' checked><label for='section-200d4982-0d06-489e-a0cd-93a7da664c38' class='xr-section-summary' >Data variables: <span>(2)</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>salt</span></div><div class='xr-var-dims'>(time, eta_rho, xi_rho)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 106, 242), meta=np.ndarray></div><input id='attrs-736824a1-6983-4273-9535-c01210097d55' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-736824a1-6983-4273-9535-c01210097d55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2f006fb-9cc3-45ba-9ca4-2a673c4b8384' class='xr-var-data-in' type='checkbox'><label for='data-e2f006fb-9cc3-45ba-9ca4-2a673c4b8384' 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>[1, 20, 53, 121]</dd><dt><span>field :</span></dt><dd>salinity, scalar, series</dd><dt><span>grid :</span></dt><dd>grid</dd><dt><span>location :</span></dt><dd>face</dd><dt><span>long_name :</span></dt><dd>time-averaged salinity</dd><dt><span>standard_name :</span></dt><dd>sea_water_salinity</dd><dt><span>time :</span></dt><dd>ocean_time</dd></dl></div><div class='xr-var-data'><table>\n <tr>\n <td>\n <table>\n <thead>\n <tr>\n <td> </td>\n <th> Array </th>\n <th> Chunk </th>\n </tr>\n </thead>\n <tbody>\n \n <tr>\n <th> Bytes </th>\n <td> 200.41 kiB </td>\n <td> 200.41 kiB </td>\n </tr>\n \n <tr>\n <th> Shape </th>\n <td> (1, 106, 242) </td>\n <td> (1, 106, 242) </td>\n </tr>\n <tr>\n <th> Count </th>\n <td> 2 Tasks </td>\n <td> 1 Chunks </td>\n </tr>\n <tr>\n <th> Type </th>\n <td> float64 </td>\n <td> numpy.ndarray </td>\n </tr>\n </tbody>\n </table>\n </td>\n <td>\n <svg width=\"194\" height=\"117\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n\n <!-- Horizontal lines -->\n <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n <line x1=\"10\" y1=\"52\" x2=\"24\" y2=\"67\" style=\"stroke-width:2\" />\n\n <!-- Vertical lines -->\n <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"52\" 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class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time, eta_rho, xi_rho)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 106, 242), meta=np.ndarray></div><input id='attrs-6cb99c93-dc2d-4555-b2ec-c9856c8a4bde' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6cb99c93-dc2d-4555-b2ec-c9856c8a4bde' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e049b84d-dc50-4760-8322-d8a76a04c9a8' class='xr-var-data-in' type='checkbox'><label for='data-e049b84d-dc50-4760-8322-d8a76a04c9a8' 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>[1, 20, 53, 121]</dd><dt><span>field :</span></dt><dd>temperature, scalar, series</dd><dt><span>grid :</span></dt><dd>grid</dd><dt><span>location :</span></dt><dd>face</dd><dt><span>long_name :</span></dt><dd>time-averaged potential temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_potential_temperature</dd><dt><span>time :</span></dt><dd>ocean_time</dd><dt><span>units :</span></dt><dd>Celsius</dd></dl></div><div class='xr-var-data'><table>\n <tr>\n <td>\n <table>\n <thead>\n <tr>\n <td> </td>\n <th> Array </th>\n <th> Chunk </th>\n </tr>\n </thead>\n <tbody>\n \n <tr>\n <th> Bytes </th>\n <td> 200.41 kiB </td>\n <td> 200.41 kiB </td>\n </tr>\n \n <tr>\n <th> Shape </th>\n <td> (1, 106, 242) </td>\n <td> (1, 106, 242) </td>\n </tr>\n <tr>\n <th> Count </th>\n <td> 2 Tasks </td>\n <td> 1 Chunks </td>\n </tr>\n <tr>\n <th> Type </th>\n <td> float64 </td>\n <td> numpy.ndarray </td>\n </tr>\n </tbody>\n </table>\n </td>\n <td>\n <svg width=\"194\" height=\"117\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n\n <!-- Horizontal lines -->\n <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n <line x1=\"10\" y1=\"52\" x2=\"24\" y2=\"67\" style=\"stroke-width:2\" />\n\n <!-- Vertical lines -->\n <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"52\" style=\"stroke-width:2\" />\n <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"67\" style=\"stroke-width:2\" />\n\n <!-- Colored Rectangle -->\n <polygon points=\"10.0,0.0 24.9485979497544,14.948597949754403 24.9485979497544,67.51058142082879 10.0,52.56198347107438\" 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=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n\n <!-- Vertical lines -->\n <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n <line x1=\"130\" y1=\"0\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n\n <!-- Colored Rectangle -->\n <polygon points=\"10.0,0.0 130.0,0.0 144.9485979497544,14.948597949754403 24.9485979497544,14.948597949754403\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n\n <!-- Horizontal lines -->\n <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n <line x1=\"24\" y1=\"67\" x2=\"144\" y2=\"67\" style=\"stroke-width:2\" />\n\n <!-- Vertical lines -->\n <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"67\" style=\"stroke-width:2\" />\n <line x1=\"144\" y1=\"14\" x2=\"144\" y2=\"67\" style=\"stroke-width:2\" />\n\n <!-- Colored Rectangle -->\n <polygon points=\"24.9485979497544,14.948597949754403 144.9485979497544,14.948597949754403 144.9485979497544,67.51058142082879 24.9485979497544,67.51058142082879\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n\n <!-- Text -->\n <text x=\"84.948598\" y=\"87.510581\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >242</text>\n <text x=\"164.948598\" y=\"41.229590\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,164.948598,41.229590)\">106</text>\n <text x=\"7.474299\" y=\"80.036282\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,80.036282)\">1</text>\n</svg>\n </td>\n </tr>\n</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-262dad26-802a-4fb1-a233-6ff24aa95d0c' class='xr-section-summary-in' type='checkbox' ><label for='section-262dad26-802a-4fb1-a233-6ff24aa95d0c' class='xr-section-summary' >Attributes: <span>(46)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CPP_options :</span></dt><dd>DOPPIO, ADD_FSOBC, ADD_M2OBC, ANA_BSFLUX, ANA_BTFLUX, ASSUMED_SHAPE, ATM_PRESS, AVERAGES, !BOUNDARY_A BULK_FLUXES, !COLLECT_ALL..., CHARNOK, CRAIG_BANNER, CURVGRID, DEFLATE, DIURNAL_SRFLUX, DJ_GRADPS, DOUBLE_PRECISION, EMINUSP, FLOATS, FORWARD_WRITE, GLS_MIXING, HDF5, KANTHA_CLAYSON, LONGWAVE_OUT, MASKING, MIX_GEO_TS, MIX_S_UV, MPI, NONLINEAR, NONLIN_EOS, NO_LBC_ATT, N2S2_HORAVG, OUT_DOUBLE, POWER_LAW, PROFILE, K_GSCHEME, REDUCE_ALLREDUCE, !RST_SINGLE, SALINITY, SOLAR_SOURCE, SOLVE3D, SSH_TIDES, TS_DIF2, UV_ADV, UV_COR, UV_U3HADVECTION, UV_C4VADVECTION, UV_QDRAG, UV_TIDES, UV_VIS2, VAR_RHO_2D, WIND_MINUS_CURRENT</dd><dt><span>Conventions :</span></dt><dd>CF-1.4, SGRID-0.3</dd><dt><span>DODS_EXTRA.Unlimited_Dimension :</span></dt><dd>ocean_time</dd><dt><span>NLM_LBC :</span></dt><dd>\nEDGE: WEST SOUTH EAST NORTH \nzeta: Cha Cha Cha Clo \nubar: Fla Fla Fla Clo \nvbar: Fla Fla Fla Clo \nu: RadNud RadNud RadNud Clo \nv: RadNud RadNud RadNud Clo \ntemp: Rad Rad Rad Clo \nsalt: Rad Rad Rad Clo \ntke: Gra Gra Gra Clo</dd><dt><span>NLM_TADV :</span></dt><dd>\nADVECTION: HORIZONTAL VERTICAL \ntemp: Akima4 Akima4 \nsalt: Akima4 Akima4</dd><dt><span>_CoordSysBuilder :</span></dt><dd>ucar.nc2.dataset.conv.CF1Convention</dd><dt><span>ana_file :</span></dt><dd>ROMS/Functionals/ana_btflux.h, ROMS/Functionals/ana_srflux.h</dd><dt><span>avg_base :</span></dt><dd>doppio_avg_6019</dd><dt><span>cdm_data_type :</span></dt><dd>GRID</dd><dt><span>clm_file_01 :</span></dt><dd>../Data/doppio_clm.nc</dd><dt><span>code_dir :</span></dt><dd>/home/julia/ROMS/doppio/svn1040t</dd><dt><span>compiler_command :</span></dt><dd>/opt/sw/apps/intel-18.0.1/openmpi/3.1.2/bin/mpif90</dd><dt><span>compiler_flags :</span></dt><dd>-fp-model precise -heap-arrays -ip -O3 -traceback -check uninit</dd><dt><span>compiler_system :</span></dt><dd>ifort</dd><dt><span>cpu :</span></dt><dd>x86_64</dd><dt><span>featureType :</span></dt><dd>GRID</dd><dt><span>file :</span></dt><dd>doppio_avg_6019_0004.nc</dd><dt><span>flt_file :</span></dt><dd>doppio_flt_6019.nc</dd><dt><span>format :</span></dt><dd>netCDF-4/HDF5 file</dd><dt><span>fpos_file :</span></dt><dd>floats.in</dd><dt><span>frc_file_01 :</span></dt><dd>../Data/lwrad_down_ncepnam_3hourly_MAB_and_GoM.nc</dd><dt><span>frc_file_02 :</span></dt><dd>../Data/Pair_ncepnam_3hourly_MAB_and_GoM.nc</dd><dt><span>frc_file_03 :</span></dt><dd>../Data/Qair_ncepnam_3hourly_MAB_and_GoM.nc</dd><dt><span>frc_file_04 :</span></dt><dd>../Data/rain_ncepnam_3hourly_MAB_and_GoM.nc</dd><dt><span>frc_file_05 :</span></dt><dd>../Data/swrad_daily_ncepnam_3hourly_MAB_and_GoM.nc</dd><dt><span>frc_file_06 :</span></dt><dd>../Data/Tair_ncepnam_3hourly_MAB_and_GoM.nc</dd><dt><span>frc_file_07 :</span></dt><dd>../Data/Winds_ncepnam_3hourly_MAB_and_GoM.nc</dd><dt><span>grd_file :</span></dt><dd>/home/om/roms/doppio/7km/grid_doppio_JJA_v13.nc</dd><dt><span>header_dir :</span></dt><dd>/home/julia/ROMS/doppio/Compile/fwd</dd><dt><span>header_file :</span></dt><dd>doppio.h</dd><dt><span>his_base :</span></dt><dd>doppio_his_6019</dd><dt><span>history :</span></dt><dd>ROMS/TOMS, Version 3.9, Tuesday - June 28, 2022 - 4:34:57 AM ;\nFMRC Best Dataset</dd><dt><span>ini_file :</span></dt><dd>doppio_rst_6019.nc</dd><dt><span>location :</span></dt><dd>Proto fmrc:doppio_2017_da_avg</dd><dt><span>nud_file :</span></dt><dd>/home/om/roms/doppio/7km/doppio_nudgcoef_7km_1500-2000_GS.nc</dd><dt><span>os :</span></dt><dd>Linux</dd><dt><span>rst_file :</span></dt><dd>tmp_doppio_rst_6019.nc</dd><dt><span>script_file :</span></dt><dd>nl_ocean_doppio.in</dd><dt><span>summary :</span></dt><dd>doppio</dd><dt><span>svn_rev :</span></dt><dd>1040</dd><dt><span>svn_url :</span></dt><dd>https://www.myroms.org/svn/src/trunk</dd><dt><span>tide_file :</span></dt><dd>/home/om/roms/doppio/7km/doppio_tide_7km.nc</dd><dt><span>tiling :</span></dt><dd>004x004</dd><dt><span>title :</span></dt><dd>ROMS doppio Real-Time Operational PSAS Forecast System Version 1 FMRC Averages</dd><dt><span>type :</span></dt><dd>ROMS/TOMS nonlinear model averages file</dd><dt><span>var_info :</span></dt><dd>../Data/varinfo1040t_daily.dat</dd></dl></div></li></ul></div></div>" | |
| }, | |
| "metadata": {} | |
| } | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "trusted": true | |
| }, | |
| "cell_type": "code", | |
| "source": "from pathlib import Path\n\npath = Path(\"doppio\").absolute()\nfname = f\"file://{path}#mode=nczarr,file\"\nprint(fname)", | |
| "execution_count": 6, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": "file:///home/filipe/nwm_dask/doppio#mode=nczarr,file\n", | |
| "name": "stdout" | |
| } | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "trusted": true | |
| }, | |
| "cell_type": "code", | |
| "source": "!ncdump -h \"$fname\" # Crashed the kernel with a segfault! Same happens if I change to nczarr to zarr mode.", | |
| "execution_count": 7, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": "netcdf doppio {\r\ndimensions:\r\n\t.zdim_106 = 106 ;\r\n\t.zdim_242 = 242 ;\r\n\t.zdim_1 = 1 ;\r\n\r\ngroup: doppio_compressed.zarr {\r\n variables:\r\n", | |
| "name": "stdout" | |
| } | |
| ] | |
| } | |
| ], | |
| "metadata": { | |
| "kernelspec": { | |
| "name": "python3", | |
| "display_name": "Python 3 (ipykernel)", | |
| "language": "python" | |
| }, | |
| "language_info": { | |
| "name": "python", | |
| "version": "3.10.5", | |
| "mimetype": "text/x-python", | |
| "codemirror_mode": { | |
| "name": "ipython", | |
| "version": 3 | |
| }, | |
| "pygments_lexer": "ipython3", | |
| "nbconvert_exporter": "python", | |
| "file_extension": ".py" | |
| }, | |
| "gist": { | |
| "id": "", | |
| "data": { | |
| "description": "zarr_example", | |
| "public": true | |
| } | |
| } | |
| }, | |
| "nbformat": 4, | |
| "nbformat_minor": 2 | |
| } |
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