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Created July 7, 2022 07:09
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problem_summary-2.ipynb
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"Problem:"
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"id": "bfbc8e14-3e0c-42fa-8872-5521cf34aa58",
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"source": [
"import xarray as xr\n",
"import numpy as np"
]
},
{
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"execution_count": 1,
"id": "2c0be694-2f39-425a-bdfe-d5c9c3c016f0",
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"\n",
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],
"source": [
"### Following Paola's instrcution, I've concatenate era5 reanalysis (10v) into one big file\n",
"\n",
"import intake\n",
"from dask.distributed import Client\n",
"\n",
"\n",
"client = Client(n_workers=4)\n",
"client"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "6015ad48-ab8f-4333-9179-6fffeda91ed8",
"metadata": {},
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{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"--> The keys in the returned dictionary of datasets are constructed as follows:\n",
"\t'sub_collection.dataset.product_type'\n"
]
},
{
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"source": [
"cat = intake.cat.nci\n",
"\n",
"era5 = cat.era5\n",
"\n",
"sub = era5.search(sub_collection='era5',dataset='single-levels', product_type='reanalysis',\n",
" parameter='10v', year=[x for x in range(1979,2020)])\n",
"\n",
"ds_dict = sub.to_dataset_dict()\n",
"\n",
"ds = ds_dict['era5.single-levels.reanalysis']\n",
"\n",
"myregion = ds.sel(latitude=slice(0,-60),longitude=slice(100,180))\n",
"\n",
"v10 = myregion['v10']"
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;v10&#x27; (time: 359400, latitude: 241, longitude: 320)&gt;\n",
"dask.array&lt;getitem, shape=(359400, 241, 320), dtype=float32, chunksize=(744, 241, 320), chunktype=numpy.ndarray&gt;\n",
"Coordinates:\n",
" * longitude (longitude) float32 100.0 100.2 100.5 100.8 ... 179.2 179.5 179.8\n",
" * latitude (latitude) float32 0.0 -0.25 -0.5 -0.75 ... -59.5 -59.75 -60.0\n",
" * time (time) datetime64[ns] 1979-01-01 ... 2019-12-31T23:00:00\n",
"Attributes:\n",
" units: m s**-1\n",
" long_name: 10 metre V wind component</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'v10'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 359400</li><li><span class='xr-has-index'>latitude</span>: 241</li><li><span class='xr-has-index'>longitude</span>: 320</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-1495ac5c-ee93-48f9-838c-bba6c55e4a09' class='xr-array-in' type='checkbox' checked><label for='section-1495ac5c-ee93-48f9-838c-bba6c55e4a09' 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&lt;chunksize=(744, 241, 320), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
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" <td> 103.25 GiB </td>\n",
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" <th> Type </th>\n",
" <td> float32 </td>\n",
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"</table></div></div></li><li class='xr-section-item'><input id='section-468aa562-2fc4-406a-82b6-9c1d17ab38ad' class='xr-section-summary-in' type='checkbox' checked><label for='section-468aa562-2fc4-406a-82b6-9c1d17ab38ad' class='xr-section-summary' >Coordinates: <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 class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>100.0 100.2 100.5 ... 179.5 179.8</div><input id='attrs-e69aa3bf-cc20-4a3c-8acb-08f248373b0e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e69aa3bf-cc20-4a3c-8acb-08f248373b0e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7cc36234-0558-449c-b125-83486beceec6' class='xr-var-data-in' type='checkbox'><label for='data-7cc36234-0558-449c-b125-83486beceec6' 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>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([100. , 100.25, 100.5 , ..., 179.25, 179.5 , 179.75], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 -0.25 -0.5 ... -59.75 -60.0</div><input id='attrs-42d5668e-d960-4327-b164-a656feb7a6b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42d5668e-d960-4327-b164-a656feb7a6b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d1fbd96-a621-41ce-8dff-e8012a5523f9' class='xr-var-data-in' type='checkbox'><label for='data-8d1fbd96-a621-41ce-8dff-e8012a5523f9' 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>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ 0. , -0.25, -0.5 , ..., -59.5 , -59.75, -60. ], dtype=float32)</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'>1979-01-01 ... 2019-12-31T23:00:00</div><input id='attrs-c723cb57-d12b-4ea5-bcb3-4a176ab03e79' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c723cb57-d12b-4ea5-bcb3-4a176ab03e79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d14fa79-17ee-4f84-800c-fcec3efa35a5' class='xr-var-data-in' type='checkbox'><label for='data-0d14fa79-17ee-4f84-800c-fcec3efa35a5' 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></dl></div><div class='xr-var-data'><pre>array([&#x27;1979-01-01T00:00:00.000000000&#x27;, &#x27;1979-01-01T01:00:00.000000000&#x27;,\n",
" &#x27;1979-01-01T02:00:00.000000000&#x27;, ..., &#x27;2019-12-31T21:00:00.000000000&#x27;,\n",
" &#x27;2019-12-31T22:00:00.000000000&#x27;, &#x27;2019-12-31T23:00:00.000000000&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a6680285-27cd-455d-a549-b9180a2d787c' class='xr-section-summary-in' type='checkbox' checked><label for='section-a6680285-27cd-455d-a549-b9180a2d787c' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>10 metre V wind component</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray 'v10' (time: 359400, latitude: 241, longitude: 320)>\n",
"dask.array<getitem, shape=(359400, 241, 320), dtype=float32, chunksize=(744, 241, 320), chunktype=numpy.ndarray>\n",
"Coordinates:\n",
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" * latitude (latitude) float32 0.0 -0.25 -0.5 -0.75 ... -59.5 -59.75 -60.0\n",
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"Attributes:\n",
" units: m s**-1\n",
" long_name: 10 metre V wind component"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"v10"
]
},
{
"cell_type": "markdown",
"id": "56ba7282-652d-4d3c-aad5-3e43e7de89ef",
"metadata": {},
"source": [
"Now, I have a list - that contains a series of days, and I'd like to plot the time-mean fields based on those days"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "e23cbef4-8cb1-47a7-9551-a8838be111f7",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"season_title = 'jja'\n",
"inpath = '/g/data/w97/cj0591/txt/box1'+season_title+'/'\n",
"dry = np.loadtxt(inpath+'dry_day_'+season_title,dtype='datetime64')"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "a7a8dfc0-a81b-4730-88f1-80aab71cba20",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['1980-06-02T09:00:00.000000000' '1980-06-03T09:00:00.000000000'\n",
" '1980-06-05T09:00:00.000000000' ... '2019-08-29T09:00:00.000000000'\n",
" '2019-08-30T09:00:00.000000000' '2019-08-31T09:00:00.000000000']\n",
"(2595,)\n"
]
}
],
"source": [
"print(dry)\n",
"print(np.shape(dry))"
]
},
{
"cell_type": "markdown",
"id": "0e0e0821-356e-488c-8426-1ccccf3b6d51",
"metadata": {},
"source": [
"Make a mask that is a single dimension the same size as the time axis, and fill with zeroes"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "8a693ebc-0035-43f0-ad57-891a5d40febc",
"metadata": {},
"outputs": [
{
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (time: 359400)&gt;\n",
"array([0., 0., 0., ..., 0., 0., 0.])\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 1979-01-01 ... 2019-12-31T23:00:00</pre><div class='xr-wrap' style='display:none'><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>: 359400</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-ae952a75-9bd4-4025-a75b-14ac061e6251' class='xr-array-in' type='checkbox' checked><label for='section-ae952a75-9bd4-4025-a75b-14ac061e6251' 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>0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([0., 0., 0., ..., 0., 0., 0.])</pre></div></div></li><li class='xr-section-item'><input id='section-2527ca26-8d08-4df5-9333-08875fac7f21' class='xr-section-summary-in' type='checkbox' checked><label for='section-2527ca26-8d08-4df5-9333-08875fac7f21' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span 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'>1979-01-01 ... 2019-12-31T23:00:00</div><input id='attrs-2e18bf6f-bd44-4424-a007-f548885aeee3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2e18bf6f-bd44-4424-a007-f548885aeee3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72d310b4-76d9-4b3b-8c1c-098beb9fc83a' class='xr-var-data-in' type='checkbox'><label for='data-72d310b4-76d9-4b3b-8c1c-098beb9fc83a' 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></dl></div><div class='xr-var-data'><pre>array([&#x27;1979-01-01T00:00:00.000000000&#x27;, &#x27;1979-01-01T01:00:00.000000000&#x27;,\n",
" &#x27;1979-01-01T02:00:00.000000000&#x27;, ..., &#x27;2019-12-31T21:00:00.000000000&#x27;,\n",
" &#x27;2019-12-31T22:00:00.000000000&#x27;, &#x27;2019-12-31T23:00:00.000000000&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-47de8b5b-94c6-4871-81e2-ea1f1e8d04a3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-47de8b5b-94c6-4871-81e2-ea1f1e8d04a3' 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: 359400)>\n",
"array([0., 0., 0., ..., 0., 0., 0.])\n",
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},
"execution_count": 25,
"metadata": {},
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],
"source": [
"mask = xr.DataArray(np.zeros(len(v10.time)), dims=[\"time\"], coords={\"time\": v10.time})\n",
"mask"
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{
"cell_type": "markdown",
"id": "d6922628-6ea8-4fcb-a500-9d394906d175",
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"source": [
"Now use vectorised indexing to set all the dry locations to be 1"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "1ac9e4fa-4abc-46eb-91ad-ee1846f7c511",
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"source": [
"mask.loc[dict(time=dry)] = 1"
]
},
{
"cell_type": "markdown",
"id": "eeb6e91d-85b4-483f-9641-728a9fc8557f",
"metadata": {},
"source": [
"Confirm there are the correct number of time points that aren't masked out"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "0ff4333d-503c-4ec3-a3cd-9615a59260a9",
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" 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'>&lt;xarray.DataArray ()&gt;\n",
"array(2595.)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-512ce6aa-8964-4b09-9e46-d024fa9650ce' class='xr-array-in' type='checkbox' checked><label for='section-512ce6aa-8964-4b09-9e46-d024fa9650ce' 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>2.595e+03</span></div><div class='xr-array-data'><pre>array(2595.)</pre></div></div></li><li class='xr-section-item'><input id='section-555f8e83-12fa-4ca1-8ee9-6fbc5ba08baf' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-555f8e83-12fa-4ca1-8ee9-6fbc5ba08baf' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-2cbb345d-a1fb-404c-be06-f0af4f540a0e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2cbb345d-a1fb-404c-be06-f0af4f540a0e' 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 ()>\n",
"array(2595.)"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mask.sum()"
]
},
{
"cell_type": "markdown",
"id": "adc18479-4838-46e5-aa8c-da695feb1efc",
"metadata": {},
"source": [
"Use the mask variable with `where`. The `where` will automatically broadcast to the spatial dimensions, and so selects out all spatial points at all dry locations"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "bdce71ef-0d3f-4578-9481-28d79c5adcc3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 1min 28s, sys: 9.21 s, total: 1min 37s\n",
"Wall time: 7min 42s\n"
]
},
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x7f7d153da340>"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"%%time\n",
"v10.where(mask).mean('time').plot()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "857c96c5-1e2d-4b99-ba83-0daaafd5c88d",
"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": "3.9.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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