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| { | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "## Accessing zarr-formatted Daymet data on Azure\n", | |
| "\n", | |
| "The Daymet dataset contains daily minimum temperature, maximum temperature, precipitation, shortwave radiation, vapor pressure, snow water equivalent, and day length at 1km resolution for North America. The dataset covers the period from January 1, 1980 to December 31, 2019.\n", | |
| "\n", | |
| "The Daymet dataset is maintained at [daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1328](daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1328) and mirrored on Azure Open Datasets at [aka.ms/ai4edata-daymet](aka.ms/ai4edata-daymet). Azure also provides a cloud-optimized version of the data in [Zarr](https://zarr.readthedocs.io/en/stable/) format, which can be read into an [xarray](http://xarray.pydata.org/en/stable/) [Dataset](http://xarray.pydata.org/en/stable/data-structures.html#dataset). If you just need a subset of the data, we recommend using xarray and Zarr to avoid downloading the full dataset unnecessarily.\n", | |
| "\n", | |
| "The datasets are available in the `daymeteuwest` storage account, in the `daymet-zarr` container. Files are named according to `daymet-zarr/{frequency}/{region}.zarr`, where frequency is one of `{daily, monthly, annual}` and region is one of `{hi, na, pr}` (for Hawaii, CONUS, and Puerto Rico, respectively). For example, `daymet-zarr/daily/hi.zarr`." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 1, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "# Standard or standard-ish imports\n", | |
| "import warnings\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "# Less standard, but still pip- or conda-installable\n", | |
| "import xarray as xr\n", | |
| "import fsspec\n", | |
| "from dask.distributed import Client\n", | |
| "\n", | |
| "# Neither of these are accessed directly, but both need to be installed; they're used\n", | |
| "# via fsspec\n", | |
| "import adlfs\n", | |
| "import zarr" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 2, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "account_name = 'daymeteuwest'\n", | |
| "container_name = 'daymet-zarr'" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Load data into an xarray Dataset\n", | |
| "\n", | |
| "We can lazily load the data into an `xarray.Dataset` by creating a zarr store with [fsspec](https://filesystem-spec.readthedocs.io/en/latest/) and then reading it in with xarray. This only reads the metadata, so it's safe to call on a dataset that's larger than memory." | |
| ] | |
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| "</style><pre class='xr-text-repr-fallback'><xarray.Dataset>\n", | |
| "Dimensions: (nv: 2, time: 480, x: 7814, y: 8075)\n", | |
| "Coordinates:\n", | |
| " lat (y, x) float32 dask.array<chunksize=(505, 977), meta=np.ndarray>\n", | |
| " lon (y, x) float32 dask.array<chunksize=(505, 977), meta=np.ndarray>\n", | |
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| " * y (y) float32 4.984e+06 4.983e+06 ... -3.09e+06\n", | |
| "Dimensions without coordinates: nv\n", | |
| "Data variables:\n", | |
| " lambert_conformal_conic int16 ...\n", | |
| " prcp (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| " swe (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| " time_bnds (time, nv) datetime64[ns] dask.array<chunksize=(480, 2), meta=np.ndarray>\n", | |
| " tmax (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| " tmin (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
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| "Attributes:\n", | |
| " Conventions: CF-1.6\n", | |
| " NCO: netCDF Operators version 4.9.3 (Homepage = http://nco....\n", | |
| " Version_data: Daymet Data Version 4.0\n", | |
| " Version_software: Daymet Software Version 4.0\n", | |
| " citation: Please see http://daymet.ornl.gov/ for current Daymet ...\n", | |
| " references: Please see http://daymet.ornl.gov/ for current informa...\n", | |
| " source: Daymet Software Version 4.0\n", | |
| " start_year: [1980]</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-8268b71f-1542-4b14-a6ae-32e652e059f0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8268b71f-1542-4b14-a6ae-32e652e059f0' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>nv</span>: 2</li><li><span class='xr-has-index'>time</span>: 480</li><li><span class='xr-has-index'>x</span>: 7814</li><li><span class='xr-has-index'>y</span>: 8075</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-29f67236-737e-46e8-a582-a1128d5f8bb3' class='xr-section-summary-in' type='checkbox' checked><label for='section-29f67236-737e-46e8-a582-a1128d5f8bb3' 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</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(505, 977), meta=np.ndarray></div><input id='attrs-37bdfabc-4e7b-4f07-a93a-2579abbc6a2e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-37bdfabc-4e7b-4f07-a93a-2579abbc6a2e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01f8f3ec-9fb6-48de-966d-379b7237de85' class='xr-var-data-in' type='checkbox'><label for='data-01f8f3ec-9fb6-48de-966d-379b7237de85' 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>latitude coordinate</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><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr><th> Bytes </th><td> 252.39 MB </td> <td> 1.97 MB </td></tr>\n", | |
| " <tr><th> Shape </th><td> (8075, 7814) </td> <td> (505, 977) </td></tr>\n", | |
| " <tr><th> Count </th><td> 129 Tasks </td><td> 128 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "</td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(505, 977), meta=np.ndarray></div><input id='attrs-0be0309f-c8b9-4160-b4fb-bba09f8a52a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0be0309f-c8b9-4160-b4fb-bba09f8a52a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c722fe4-e6db-4521-9b53-69562b891c3d' class='xr-var-data-in' type='checkbox'><label for='data-1c722fe4-e6db-4521-9b53-69562b891c3d' 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>longitude coordinate</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><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr><th> Bytes </th><td> 252.39 MB </td> <td> 1.97 MB </td></tr>\n", | |
| " <tr><th> Shape </th><td> (8075, 7814) </td> <td> (505, 977) </td></tr>\n", | |
| " <tr><th> Count </th><td> 129 Tasks </td><td> 128 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n", | |
| " </tbody>\n", | |
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| "<td>\n", | |
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| "</table></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'>1980-01-16T12:00:00 ... 2019-12-...</div><input id='attrs-7dbf4f44-40d6-4e29-9341-66c8616d2827' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7dbf4f44-40d6-4e29-9341-66c8616d2827' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8c4b955-490a-4da7-a622-98b5e7e0f369' class='xr-var-data-in' type='checkbox'><label for='data-b8c4b955-490a-4da7-a622-98b5e7e0f369' 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>bounds :</span></dt><dd>time_bnds</dd><dt><span>long_name :</span></dt><dd>24-hour day based on local time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(['1980-01-16T12:00:00.000000000', '1980-02-15T12:00:00.000000000',\n", | |
| " '1980-03-16T12:00:00.000000000', ..., '2019-10-16T12:00:00.000000000',\n", | |
| " '2019-11-16T00:00:00.000000000', '2019-12-16T12:00:00.000000000'],\n", | |
| " dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-4.56e+06 -4.559e+06 ... 3.253e+06</div><input id='attrs-d37c702b-a6c1-4d44-ac8b-273b8258c960' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d37c702b-a6c1-4d44-ac8b-273b8258c960' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe6205b7-fe9a-43e9-ba9e-c2c3f6ccdeef' class='xr-var-data-in' type='checkbox'><label for='data-fe6205b7-fe9a-43e9-ba9e-c2c3f6ccdeef' 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>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([-4560250., -4559250., -4558250., ..., 3250750., 3251750., 3252750.],\n", | |
| " dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>4.984e+06 4.983e+06 ... -3.09e+06</div><input id='attrs-e6aeec54-5bce-4f47-a17a-5645fa54ea06' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e6aeec54-5bce-4f47-a17a-5645fa54ea06' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f28ed3e-e405-4023-8945-0251a6337dc7' class='xr-var-data-in' type='checkbox'><label for='data-5f28ed3e-e405-4023-8945-0251a6337dc7' 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>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ 4984000., 4983000., 4982000., ..., -3088000., -3089000., -3090000.],\n", | |
| " dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-416f691f-33ba-4fd3-82bf-eb0c38742c0e' class='xr-section-summary-in' type='checkbox' checked><label for='section-416f691f-33ba-4fd3-82bf-eb0c38742c0e' class='xr-section-summary' >Data variables: <span>(7)</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>lambert_conformal_conic</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9217f97b-3330-4bb9-8dc5-3a92fee26136' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9217f97b-3330-4bb9-8dc5-3a92fee26136' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c008ace-2c60-4d76-ba54-16c60d4ab05e' class='xr-var-data-in' type='checkbox'><label for='data-0c008ace-2c60-4d76-ba54-16c60d4ab05e' 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>false_easting :</span></dt><dd>[0.0]</dd><dt><span>false_northing :</span></dt><dd>[0.0]</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>inverse_flattening :</span></dt><dd>[298.257223563]</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>[42.5]</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>[-100.0]</dd><dt><span>semi_major_axis :</span></dt><dd>[6378137.0]</dd><dt><span>standard_parallel :</span></dt><dd>[25.0, 60.0]</dd></dl></div><div class='xr-var-data'><pre>array(-32767, dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prcp</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray></div><input id='attrs-d85043df-0915-4508-b2bc-750208b9827f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d85043df-0915-4508-b2bc-750208b9827f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03001dbb-b6b4-4bb7-89b7-f4745ba345c8' class='xr-var-data-in' type='checkbox'><label for='data-03001dbb-b6b4-4bb7-89b7-f4745ba345c8' 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>cell_methods :</span></dt><dd>area: mean time: sum within days time: sum over days</dd><dt><span>grid_mapping :</span></dt><dd>lambert_conformal_conic</dd><dt><span>long_name :</span></dt><dd>monthly total precipitation</dd><dt><span>units :</span></dt><dd>mm</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", | |
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| " <tbody>\n", | |
| " <tr><th> Bytes </th><td> 121.15 GB </td> <td> 75.00 MB </td></tr>\n", | |
| " <tr><th> Shape </th><td> (480, 8075, 7814) </td> <td> (12, 1250, 1250) </td></tr>\n", | |
| " <tr><th> Count </th><td> 1961 Tasks </td><td> 1960 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> float32 </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>swe</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray></div><input id='attrs-796b88e1-64c3-4518-b1f0-c37c92b435ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-796b88e1-64c3-4518-b1f0-c37c92b435ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83948373-91f6-44e1-9efb-4dcc16d8f81c' class='xr-var-data-in' type='checkbox'><label for='data-83948373-91f6-44e1-9efb-4dcc16d8f81c' 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>cell_methods :</span></dt><dd>area: mean time: sum within days time: sum over days</dd><dt><span>grid_mapping :</span></dt><dd>lambert_conformal_conic</dd><dt><span>long_name :</span></dt><dd>monthly total snow water equivalent</dd><dt><span>units :</span></dt><dd>mm</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| "<table>\n", | |
| " <thead>\n", | |
| " <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr><th> Bytes </th><td> 121.15 GB </td> <td> 75.00 MB </td></tr>\n", | |
| " <tr><th> Shape </th><td> (480, 8075, 7814) </td> <td> (12, 1250, 1250) </td></tr>\n", | |
| " <tr><th> Count </th><td> 1961 Tasks </td><td> 1960 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n", | |
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| " <tbody>\n", | |
| " <tr><th> Bytes </th><td> 7.68 kB </td> <td> 7.68 kB </td></tr>\n", | |
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| " <tr><th> Count </th><td> 2 Tasks </td><td> 1 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> datetime64[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>tmax</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray></div><input id='attrs-52435a88-dce6-4ef9-b9cb-9a80dfeda4c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52435a88-dce6-4ef9-b9cb-9a80dfeda4c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f90963df-cd48-4137-ac71-a8d506b6e70f' class='xr-var-data-in' type='checkbox'><label for='data-f90963df-cd48-4137-ac71-a8d506b6e70f' 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>cell_methods :</span></dt><dd>area: mean time: maximum within days time: mean over days</dd><dt><span>grid_mapping :</span></dt><dd>lambert_conformal_conic</dd><dt><span>long_name :</span></dt><dd>monthly average of daily maximum temperature</dd><dt><span>units :</span></dt><dd>degrees C</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <tr><th> Bytes </th><td> 121.15 GB </td> <td> 75.00 MB </td></tr>\n", | |
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| " <tr><th> Count </th><td> 1961 Tasks </td><td> 1960 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> float32 </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>tmin</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray></div><input id='attrs-faf91c5a-0acb-4fcf-bd50-461cc7691e44' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-faf91c5a-0acb-4fcf-bd50-461cc7691e44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-112b2946-bade-48aa-86f9-466605bea2c8' class='xr-var-data-in' type='checkbox'><label for='data-112b2946-bade-48aa-86f9-466605bea2c8' 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>cell_methods :</span></dt><dd>area: mean time: minimum within days time: mean over days</dd><dt><span>grid_mapping :</span></dt><dd>lambert_conformal_conic</dd><dt><span>long_name :</span></dt><dd>monthly average of daily minimum temperature</dd><dt><span>units :</span></dt><dd>degrees C</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <tr><th> Count </th><td> 1961 Tasks </td><td> 1960 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> float32 </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>vp</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray></div><input id='attrs-9d1bc236-0099-454a-82c9-2038bd06b8df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9d1bc236-0099-454a-82c9-2038bd06b8df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42e3db67-545b-448a-84c7-75c3bcff56e2' class='xr-var-data-in' type='checkbox'><label for='data-42e3db67-545b-448a-84c7-75c3bcff56e2' 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>cell_methods :</span></dt><dd>area: mean time: mean within days time: mean over days</dd><dt><span>grid_mapping :</span></dt><dd>lambert_conformal_conic</dd><dt><span>long_name :</span></dt><dd>monthly average of daily average vapor pressure</dd><dt><span>units :</span></dt><dd>Pa</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> 121.15 GB </td> <td> 75.00 MB </td></tr>\n", | |
| " <tr><th> Shape </th><td> (480, 8075, 7814) </td> <td> (12, 1250, 1250) </td></tr>\n", | |
| " <tr><th> Count </th><td> 1961 Tasks </td><td> 1960 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n", | |
| " </tbody>\n", | |
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| " <text x=\"10.457661\" y=\"150.457661\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,10.457661,150.457661)\">480</text>\n", | |
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| "</td>\n", | |
| "</tr>\n", | |
| "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-4030f64e-5b8b-4db4-8643-1e9e6432892f' class='xr-section-summary-in' type='checkbox' checked><label for='section-4030f64e-5b8b-4db4-8643-1e9e6432892f' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>NCO :</span></dt><dd>netCDF Operators version 4.9.3 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)</dd><dt><span>Version_data :</span></dt><dd>Daymet Data Version 4.0</dd><dt><span>Version_software :</span></dt><dd>Daymet Software Version 4.0</dd><dt><span>citation :</span></dt><dd>Please see http://daymet.ornl.gov/ for current Daymet data citation information</dd><dt><span>references :</span></dt><dd>Please see http://daymet.ornl.gov/ for current information on Daymet references</dd><dt><span>source :</span></dt><dd>Daymet Software Version 4.0</dd><dt><span>start_year :</span></dt><dd>[1980]</dd></dl></div></li></ul></div></div>" | |
| ], | |
| "text/plain": [ | |
| "<xarray.Dataset>\n", | |
| "Dimensions: (nv: 2, time: 480, x: 7814, y: 8075)\n", | |
| "Coordinates:\n", | |
| " lat (y, x) float32 dask.array<chunksize=(505, 977), meta=np.ndarray>\n", | |
| " lon (y, x) float32 dask.array<chunksize=(505, 977), meta=np.ndarray>\n", | |
| " * time (time) datetime64[ns] 1980-01-16T12:00:00 ... 20...\n", | |
| " * x (x) float32 -4.56e+06 -4.559e+06 ... 3.253e+06\n", | |
| " * y (y) float32 4.984e+06 4.983e+06 ... -3.09e+06\n", | |
| "Dimensions without coordinates: nv\n", | |
| "Data variables:\n", | |
| " lambert_conformal_conic int16 ...\n", | |
| " prcp (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| " swe (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| " time_bnds (time, nv) datetime64[ns] dask.array<chunksize=(480, 2), meta=np.ndarray>\n", | |
| " tmax (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| " tmin (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| " vp (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| "Attributes:\n", | |
| " Conventions: CF-1.6\n", | |
| " NCO: netCDF Operators version 4.9.3 (Homepage = http://nco....\n", | |
| " Version_data: Daymet Data Version 4.0\n", | |
| " Version_software: Daymet Software Version 4.0\n", | |
| " citation: Please see http://daymet.ornl.gov/ for current Daymet ...\n", | |
| " references: Please see http://daymet.ornl.gov/ for current informa...\n", | |
| " source: Daymet Software Version 4.0\n", | |
| " start_year: [1980]" | |
| ] | |
| }, | |
| "execution_count": 3, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "store = fsspec.get_mapper('az://' + container_name + '/monthly/na.zarr', account_name=account_name)\n", | |
| "# consolidated=True speeds of reading the metadata\n", | |
| "ds = xr.open_zarr(store, consolidated=True)\n", | |
| "ds" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "#### Compute the average monthly tmin, tmax and precip for the period 1990-2019" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 4, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
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| "\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: (nv: 2, time: 360, x: 7814, y: 8075)\n", | |
| "Coordinates:\n", | |
| " lat (y, x) float32 dask.array<chunksize=(505, 977), meta=np.ndarray>\n", | |
| " lon (y, x) float32 dask.array<chunksize=(505, 977), meta=np.ndarray>\n", | |
| " * time (time) datetime64[ns] 1990-01-16T12:00:00 ... 20...\n", | |
| " * x (x) float32 -4.56e+06 -4.559e+06 ... 3.253e+06\n", | |
| " * y (y) float32 4.984e+06 4.983e+06 ... -3.09e+06\n", | |
| "Dimensions without coordinates: nv\n", | |
| "Data variables:\n", | |
| " lambert_conformal_conic int16 ...\n", | |
| " prcp (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| " swe (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| " time_bnds (time, nv) datetime64[ns] dask.array<chunksize=(360, 2), meta=np.ndarray>\n", | |
| " tmax (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| " tmin (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| " vp (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| "Attributes:\n", | |
| " Conventions: CF-1.6\n", | |
| " NCO: netCDF Operators version 4.9.3 (Homepage = http://nco....\n", | |
| " Version_data: Daymet Data Version 4.0\n", | |
| " Version_software: Daymet Software Version 4.0\n", | |
| " citation: Please see http://daymet.ornl.gov/ for current Daymet ...\n", | |
| " references: Please see http://daymet.ornl.gov/ for current informa...\n", | |
| " source: Daymet Software Version 4.0\n", | |
| " start_year: [1980]</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-b4b06494-f16e-44f7-9d89-08d816af0300' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b4b06494-f16e-44f7-9d89-08d816af0300' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>nv</span>: 2</li><li><span class='xr-has-index'>time</span>: 360</li><li><span class='xr-has-index'>x</span>: 7814</li><li><span class='xr-has-index'>y</span>: 8075</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-7d7f8bec-69c1-41d5-b948-9b66f1d7091a' class='xr-section-summary-in' type='checkbox' checked><label for='section-7d7f8bec-69c1-41d5-b948-9b66f1d7091a' 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</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(505, 977), meta=np.ndarray></div><input id='attrs-b6131d8e-adfe-4625-b8d7-9657899bd60a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b6131d8e-adfe-4625-b8d7-9657899bd60a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b93798a1-12de-47d3-a163-7085f786dcba' class='xr-var-data-in' type='checkbox'><label for='data-b93798a1-12de-47d3-a163-7085f786dcba' 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>latitude coordinate</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><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr><th> Bytes </th><td> 252.39 MB </td> <td> 1.97 MB </td></tr>\n", | |
| " <tr><th> Shape </th><td> (8075, 7814) </td> <td> (505, 977) </td></tr>\n", | |
| " <tr><th> Count </th><td> 129 Tasks </td><td> 128 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=\"166\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"116\" y2=\"0\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"0\" y1=\"7\" x2=\"116\" y2=\"7\" />\n", | |
| " <line x1=\"0\" y1=\"15\" x2=\"116\" y2=\"15\" />\n", | |
| " <line x1=\"0\" y1=\"22\" x2=\"116\" y2=\"22\" />\n", | |
| " <line x1=\"0\" y1=\"30\" x2=\"116\" y2=\"30\" />\n", | |
| " <line x1=\"0\" y1=\"37\" x2=\"116\" y2=\"37\" />\n", | |
| " <line x1=\"0\" y1=\"45\" x2=\"116\" y2=\"45\" />\n", | |
| " <line x1=\"0\" y1=\"52\" x2=\"116\" y2=\"52\" />\n", | |
| " <line x1=\"0\" y1=\"60\" x2=\"116\" y2=\"60\" />\n", | |
| " <line x1=\"0\" y1=\"67\" x2=\"116\" y2=\"67\" />\n", | |
| " <line x1=\"0\" y1=\"75\" x2=\"116\" y2=\"75\" />\n", | |
| " <line x1=\"0\" y1=\"82\" x2=\"116\" y2=\"82\" />\n", | |
| " <line x1=\"0\" y1=\"90\" x2=\"116\" y2=\"90\" />\n", | |
| " <line x1=\"0\" y1=\"97\" x2=\"116\" y2=\"97\" />\n", | |
| " <line x1=\"0\" y1=\"105\" x2=\"116\" y2=\"105\" />\n", | |
| " <line x1=\"0\" y1=\"112\" x2=\"116\" y2=\"112\" />\n", | |
| " <line x1=\"0\" y1=\"120\" x2=\"116\" 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=\"14\" y1=\"0\" x2=\"14\" y2=\"120\" />\n", | |
| " <line x1=\"29\" y1=\"0\" x2=\"29\" y2=\"120\" />\n", | |
| " <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"120\" />\n", | |
| " <line x1=\"58\" y1=\"0\" x2=\"58\" y2=\"120\" />\n", | |
| " <line x1=\"72\" y1=\"0\" x2=\"72\" y2=\"120\" />\n", | |
| " <line x1=\"87\" y1=\"0\" x2=\"87\" y2=\"120\" />\n", | |
| " <line x1=\"101\" y1=\"0\" x2=\"101\" y2=\"120\" />\n", | |
| " <line x1=\"116\" y1=\"0\" x2=\"116\" y2=\"120\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"0.000000,0.000000 116.121362,0.000000 116.121362,120.000000 0.000000,120.000000\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Text -->\n", | |
| " <text x=\"58.060681\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >7814</text>\n", | |
| " <text x=\"136.121362\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,136.121362,60.000000)\">8075</text>\n", | |
| "</svg>\n", | |
| "</td>\n", | |
| "</tr>\n", | |
| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(505, 977), meta=np.ndarray></div><input id='attrs-76403208-e67e-4f14-8e2d-ac5bf288feb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-76403208-e67e-4f14-8e2d-ac5bf288feb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14156ff1-2519-4864-aa36-9df067648936' class='xr-var-data-in' type='checkbox'><label for='data-14156ff1-2519-4864-aa36-9df067648936' 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>longitude coordinate</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><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr><th> Bytes </th><td> 252.39 MB </td> <td> 1.97 MB </td></tr>\n", | |
| " <tr><th> Shape </th><td> (8075, 7814) </td> <td> (505, 977) </td></tr>\n", | |
| " <tr><th> Count </th><td> 129 Tasks </td><td> 128 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=\"166\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"116\" y2=\"0\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"0\" y1=\"7\" x2=\"116\" y2=\"7\" />\n", | |
| " <line x1=\"0\" y1=\"15\" x2=\"116\" y2=\"15\" />\n", | |
| " <line x1=\"0\" y1=\"22\" x2=\"116\" y2=\"22\" />\n", | |
| " <line x1=\"0\" y1=\"30\" x2=\"116\" y2=\"30\" />\n", | |
| " <line x1=\"0\" y1=\"37\" x2=\"116\" y2=\"37\" />\n", | |
| " <line x1=\"0\" y1=\"45\" x2=\"116\" y2=\"45\" />\n", | |
| " <line x1=\"0\" y1=\"52\" x2=\"116\" y2=\"52\" />\n", | |
| " <line x1=\"0\" y1=\"60\" x2=\"116\" y2=\"60\" />\n", | |
| " <line x1=\"0\" y1=\"67\" x2=\"116\" y2=\"67\" />\n", | |
| " <line x1=\"0\" y1=\"75\" x2=\"116\" y2=\"75\" />\n", | |
| " <line x1=\"0\" y1=\"82\" x2=\"116\" y2=\"82\" />\n", | |
| " <line x1=\"0\" y1=\"90\" x2=\"116\" y2=\"90\" />\n", | |
| " <line x1=\"0\" y1=\"97\" x2=\"116\" y2=\"97\" />\n", | |
| " <line x1=\"0\" y1=\"105\" x2=\"116\" y2=\"105\" />\n", | |
| " <line x1=\"0\" y1=\"112\" x2=\"116\" y2=\"112\" />\n", | |
| " <line x1=\"0\" y1=\"120\" x2=\"116\" 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=\"14\" y1=\"0\" x2=\"14\" y2=\"120\" />\n", | |
| " <line x1=\"29\" y1=\"0\" x2=\"29\" y2=\"120\" />\n", | |
| " <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"120\" />\n", | |
| " <line x1=\"58\" y1=\"0\" x2=\"58\" y2=\"120\" />\n", | |
| " <line x1=\"72\" y1=\"0\" x2=\"72\" y2=\"120\" />\n", | |
| " <line x1=\"87\" y1=\"0\" x2=\"87\" y2=\"120\" />\n", | |
| " <line x1=\"101\" y1=\"0\" x2=\"101\" y2=\"120\" />\n", | |
| " <line x1=\"116\" y1=\"0\" x2=\"116\" y2=\"120\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"0.000000,0.000000 116.121362,0.000000 116.121362,120.000000 0.000000,120.000000\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Text -->\n", | |
| " <text x=\"58.060681\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >7814</text>\n", | |
| " <text x=\"136.121362\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,136.121362,60.000000)\">8075</text>\n", | |
| "</svg>\n", | |
| "</td>\n", | |
| "</tr>\n", | |
| "</table></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'>1990-01-16T12:00:00 ... 2019-12-...</div><input id='attrs-be105fd7-62ec-4959-8f65-656a9f977a24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be105fd7-62ec-4959-8f65-656a9f977a24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-672a88e8-9a89-441a-8634-52cbc0b369a9' class='xr-var-data-in' type='checkbox'><label for='data-672a88e8-9a89-441a-8634-52cbc0b369a9' 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>bounds :</span></dt><dd>time_bnds</dd><dt><span>long_name :</span></dt><dd>24-hour day based on local time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(['1990-01-16T12:00:00.000000000', '1990-02-15T00:00:00.000000000',\n", | |
| " '1990-03-16T12:00:00.000000000', ..., '2019-10-16T12:00:00.000000000',\n", | |
| " '2019-11-16T00:00:00.000000000', '2019-12-16T12:00:00.000000000'],\n", | |
| " dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-4.56e+06 -4.559e+06 ... 3.253e+06</div><input id='attrs-5db0fb02-7d15-42a3-bcca-8d87d21a0f29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5db0fb02-7d15-42a3-bcca-8d87d21a0f29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31a388a0-43f3-4b69-889a-a9001413f4be' class='xr-var-data-in' type='checkbox'><label for='data-31a388a0-43f3-4b69-889a-a9001413f4be' 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>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([-4560250., -4559250., -4558250., ..., 3250750., 3251750., 3252750.],\n", | |
| " dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>4.984e+06 4.983e+06 ... -3.09e+06</div><input id='attrs-b347f39f-4458-4384-98eb-a8746ba2dd96' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b347f39f-4458-4384-98eb-a8746ba2dd96' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac16791c-f674-48ad-a465-662a61e3d6a7' class='xr-var-data-in' type='checkbox'><label for='data-ac16791c-f674-48ad-a465-662a61e3d6a7' 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>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ 4984000., 4983000., 4982000., ..., -3088000., -3089000., -3090000.],\n", | |
| " dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cd5ab21a-bc82-45e0-91e6-26b977863a5b' class='xr-section-summary-in' type='checkbox' checked><label for='section-cd5ab21a-bc82-45e0-91e6-26b977863a5b' class='xr-section-summary' >Data variables: <span>(7)</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>lambert_conformal_conic</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b653e4e6-cabb-48b6-b6a2-48f130e61079' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b653e4e6-cabb-48b6-b6a2-48f130e61079' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e49bee3e-6abb-4677-b56d-0f7b50c82fb3' class='xr-var-data-in' type='checkbox'><label for='data-e49bee3e-6abb-4677-b56d-0f7b50c82fb3' 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>false_easting :</span></dt><dd>[0.0]</dd><dt><span>false_northing :</span></dt><dd>[0.0]</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>inverse_flattening :</span></dt><dd>[298.257223563]</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>[42.5]</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>[-100.0]</dd><dt><span>semi_major_axis :</span></dt><dd>[6378137.0]</dd><dt><span>standard_parallel :</span></dt><dd>[25.0, 60.0]</dd></dl></div><div class='xr-var-data'><pre>array(-32767, dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prcp</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray></div><input id='attrs-81c4fc8e-0e2d-4fc7-a57e-8d6e542fb8d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81c4fc8e-0e2d-4fc7-a57e-8d6e542fb8d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a358b2f-10e1-4650-b308-5c1bc425c7dd' class='xr-var-data-in' type='checkbox'><label for='data-9a358b2f-10e1-4650-b308-5c1bc425c7dd' 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>cell_methods :</span></dt><dd>area: mean time: sum within days time: sum over days</dd><dt><span>grid_mapping :</span></dt><dd>lambert_conformal_conic</dd><dt><span>long_name :</span></dt><dd>monthly total precipitation</dd><dt><span>units :</span></dt><dd>mm</dd></dl></div><div class='xr-var-data'><table>\n", | |
| "<tr>\n", | |
| "<td>\n", | |
| "<table>\n", | |
| " <thead>\n", | |
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| " <tr><th> Bytes </th><td> 5.76 kB </td> <td> 5.76 kB </td></tr>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tmax</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray></div><input id='attrs-3f948cad-e316-495c-9f99-439267809f51' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f948cad-e316-495c-9f99-439267809f51' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5e4a4c5-49fe-42cf-a4bb-451a5d128265' class='xr-var-data-in' type='checkbox'><label for='data-d5e4a4c5-49fe-42cf-a4bb-451a5d128265' 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>cell_methods :</span></dt><dd>area: mean time: maximum within days time: mean over days</dd><dt><span>grid_mapping :</span></dt><dd>lambert_conformal_conic</dd><dt><span>long_name :</span></dt><dd>monthly average of daily maximum temperature</dd><dt><span>units :</span></dt><dd>degrees C</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vp</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray></div><input id='attrs-035d6721-24ce-41ab-bcce-e7a7f9c02038' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-035d6721-24ce-41ab-bcce-e7a7f9c02038' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-918f80ac-d7ee-4f5f-aa27-14aec1f6558d' class='xr-var-data-in' type='checkbox'><label for='data-918f80ac-d7ee-4f5f-aa27-14aec1f6558d' 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>cell_methods :</span></dt><dd>area: mean time: mean within days time: mean over days</dd><dt><span>grid_mapping :</span></dt><dd>lambert_conformal_conic</dd><dt><span>long_name :</span></dt><dd>monthly average of daily average vapor pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <tr><th> Bytes </th><td> 90.86 GB </td> <td> 75.00 MB </td></tr>\n", | |
| " <tr><th> Shape </th><td> (360, 8075, 7814) </td> <td> (12, 1250, 1250) </td></tr>\n", | |
| " <tr><th> Count </th><td> 3431 Tasks </td><td> 1470 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n", | |
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| "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-a9d553a5-934f-4e71-b6af-0798dd8350e1' class='xr-section-summary-in' type='checkbox' checked><label for='section-a9d553a5-934f-4e71-b6af-0798dd8350e1' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>NCO :</span></dt><dd>netCDF Operators version 4.9.3 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)</dd><dt><span>Version_data :</span></dt><dd>Daymet Data Version 4.0</dd><dt><span>Version_software :</span></dt><dd>Daymet Software Version 4.0</dd><dt><span>citation :</span></dt><dd>Please see http://daymet.ornl.gov/ for current Daymet data citation information</dd><dt><span>references :</span></dt><dd>Please see http://daymet.ornl.gov/ for current information on Daymet references</dd><dt><span>source :</span></dt><dd>Daymet Software Version 4.0</dd><dt><span>start_year :</span></dt><dd>[1980]</dd></dl></div></li></ul></div></div>" | |
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| "text/plain": [ | |
| "<xarray.Dataset>\n", | |
| "Dimensions: (nv: 2, time: 360, x: 7814, y: 8075)\n", | |
| "Coordinates:\n", | |
| " lat (y, x) float32 dask.array<chunksize=(505, 977), meta=np.ndarray>\n", | |
| " lon (y, x) float32 dask.array<chunksize=(505, 977), meta=np.ndarray>\n", | |
| " * time (time) datetime64[ns] 1990-01-16T12:00:00 ... 20...\n", | |
| " * x (x) float32 -4.56e+06 -4.559e+06 ... 3.253e+06\n", | |
| " * y (y) float32 4.984e+06 4.983e+06 ... -3.09e+06\n", | |
| "Dimensions without coordinates: nv\n", | |
| "Data variables:\n", | |
| " lambert_conformal_conic int16 ...\n", | |
| " prcp (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| " swe (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| " time_bnds (time, nv) datetime64[ns] dask.array<chunksize=(360, 2), meta=np.ndarray>\n", | |
| " tmax (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| " tmin (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| " vp (time, y, x) float32 dask.array<chunksize=(12, 1250, 1250), meta=np.ndarray>\n", | |
| "Attributes:\n", | |
| " Conventions: CF-1.6\n", | |
| " NCO: netCDF Operators version 4.9.3 (Homepage = http://nco....\n", | |
| " Version_data: Daymet Data Version 4.0\n", | |
| " Version_software: Daymet Software Version 4.0\n", | |
| " citation: Please see http://daymet.ornl.gov/ for current Daymet ...\n", | |
| " references: Please see http://daymet.ornl.gov/ for current informa...\n", | |
| " source: Daymet Software Version 4.0\n", | |
| " start_year: [1980]" | |
| ] | |
| }, | |
| "execution_count": 4, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "dss = ds.sel(time=slice('1990','2019')) \n", | |
| "dss" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 5, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "90.861192" | |
| ] | |
| }, | |
| "execution_count": 5, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "dss['prcp'].nbytes/1e9" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 6, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "\u001b[0;31mSignature:\u001b[0m\n", | |
| "\u001b[0mebd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstart_dask_cluster\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n", | |
| "\u001b[0;34m\u001b[0m \u001b[0menvironment\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'pangeo'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
| "\u001b[0;34m\u001b[0m \u001b[0mworker_profile\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Medium Worker'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
| "\u001b[0;34m\u001b[0m \u001b[0mprofile\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'default'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
| "\u001b[0;34m\u001b[0m \u001b[0mregion\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'us-west-2'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
| "\u001b[0;34m\u001b[0m \u001b[0mendpoint\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
| "\u001b[0;34m\u001b[0m \u001b[0mworker_min\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
| "\u001b[0;34m\u001b[0m \u001b[0mworker_max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m20\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
| "\u001b[0;34m\u001b[0m \u001b[0madaptive_scaling\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
| "\u001b[0;34m\u001b[0m \u001b[0mwait_for_cluster\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
| "\u001b[0;34m\u001b[0m \u001b[0mcfile\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
| "\u001b[0;34m\u001b[0m \u001b[0muse_existing_cluster\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
| "\u001b[0;34m\u001b[0m \u001b[0mpropagate_env\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
| "\u001b[0;34m\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", | |
| "\u001b[0;31mDocstring:\u001b[0m <no docstring>\n", | |
| "\u001b[0;31mFile:\u001b[0m ~/shared/users/lib/ebdpy.py\n", | |
| "\u001b[0;31mType:\u001b[0m function\n" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "import os\n", | |
| "import sys\n", | |
| "sys.path.append(os.path.join(os.environ['HOME'],'shared','users','lib'))\n", | |
| "import ebdpy as ebd\n", | |
| "\n", | |
| "?ebd.start_dask_cluster" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 7, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "No Cluster running.\n", | |
| "Starting new cluster.\n", | |
| "Setting Fixed Scaling workers=60\n", | |
| "Reconnect client to clear cache\n", | |
| "client.dashboard_link (for new browser tab/window or dashboard searchbar in Jupyterhub):\n", | |
| "https://jupyter.qhub.esipfed.org/gateway/clusters/62093213ef524bdf9db3c53cb1912be2/status\n", | |
| "Propagating environment variables to workers\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "profile = 'esip-qhub'\n", | |
| "region = 'us-west-2'\n", | |
| "endpoint = f's3.{region}.amazonaws.com'\n", | |
| "ebd.set_credentials(profile=profile, region=region, endpoint=endpoint)\n", | |
| "worker_max = 60\n", | |
| "client,cluster = ebd.start_dask_cluster(profile=profile,worker_max=worker_max, \n", | |
| " region=region, use_existing_cluster=True,\n", | |
| " adaptive_scaling=False, wait_for_cluster=False, \n", | |
| " environment='pangeo', worker_profile='Pangeo Worker', propagate_env=True)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 8, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "application/vnd.jupyter.widget-view+json": { | |
| "model_id": "a4794b2ee7874e8cbfbccd5effcf6596", | |
| "version_major": 2, | |
| "version_minor": 0 | |
| }, | |
| "text/plain": [ | |
| "VBox(children=(HTML(value='<h2>GatewayCluster</h2>'), HBox(children=(HTML(value='\\n<div>\\n<style scoped>\\n …" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "cluster" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "#### Store result in Zarr" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "import fsspec\n", | |
| "fs = fsspec.filesystem('s3', anon=False)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "store = fs.get_mapper('s3://esip-qhub/usgs/daymet3.zarr')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "%%time\n", | |
| "#import dask\n", | |
| "##import dask.array as da\n", | |
| "#with dask.annotate(retries=3):\n", | |
| "\n", | |
| "d_ave = dss[['prcp', 'tmin', 'tmax']].groupby('time.month').mean(dim='time')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "d_ave" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "from dask.distributed import performance_report\n", | |
| "\n", | |
| "with performance_report(filename=\"dask-report.html\"):\n", | |
| " f = client.compute(d_ave.to_zarr(store, mode='w', consolidated=True, compute=False), retries=20)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "client.close();cluster.shutdown()" | |
| ] | |
| } | |
| ], | |
| "metadata": { | |
| "kernelspec": { | |
| "display_name": "Python [conda env:pangeo]", | |
| "language": "python", | |
| "name": "conda-env-pangeo-py" | |
| }, | |
| "language_info": { | |
| "codemirror_mode": { | |
| "name": "ipython", | |
| "version": 3 | |
| }, | |
| "file_extension": ".py", | |
| "mimetype": "text/x-python", | |
| "name": "python", | |
| "nbconvert_exporter": "python", | |
| "pygments_lexer": "ipython3", | |
| "version": "3.8.8" | |
| }, | |
| "widgets": { | |
| "application/vnd.jupyter.widget-state+json": { | |
| "state": {}, | |
| "version_major": 2, | |
| "version_minor": 0 | |
| } | |
| } | |
| }, | |
| "nbformat": 4, | |
| "nbformat_minor": 4 | |
| } |
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