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rsignell-usgs/fuse_test.ipynb

Last active July 15, 2018 18:27
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fuse_test.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Read National Water Model data from NetCDF on FUSE"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import xarray as xr\n",
"import pandas as pd\n",
"\n",
"from dask.distributed import Client, progress\n",
"from dask_kubernetes import KubeCluster"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"root = '/s3/noaa-nwm-pds'"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"dates = pd.date_range(start='2018-07-01T00:00', end='2018-07-08T00:00', freq='H')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"cluster = KubeCluster.from_yaml('/home/jovyan/custom-worker-template.yaml')"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"cluster.scale(25);"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"client = Client(cluster)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table style=\"border: 2px solid white;\">\n",
"<tr>\n",
"<td style=\"vertical-align: top; border: 0px solid white\">\n",
"<h3>Client</h3>\n",
"<ul>\n",
" <li><b>Scheduler: </b>tcp://192.168.18.213:43383\n",
" <li><b>Dashboard: </b><a href='/user/rsignell-usgs/proxy/8787/status' target='_blank'>/user/rsignell-usgs/proxy/8787/status</a>\n",
"</ul>\n",
"</td>\n",
"<td style=\"vertical-align: top; border: 0px solid white\">\n",
"<h3>Cluster</h3>\n",
"<ul>\n",
" <li><b>Workers: </b>24</li>\n",
" <li><b>Cores: </b>48</li>\n",
" <li><b>Memory: </b>144.00 GB</li>\n",
"</ul>\n",
"</td>\n",
"</tr>\n",
"</table>"
],
"text/plain": [
"<Client: scheduler='tcp://192.168.18.213:43383' processes=0 cores=0>"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"client"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"urls = ['{}/nwm.{}/forcing_short_range/nwm.t{}z.short_range.forcing.f001.conus.nc'.format(root,a.strftime('%Y%m%d'),a.strftime('%H')) for a in dates]"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"# /s3/noaa-nwm-pds/nwm.20180615/forcing_short_range/nwm.t00z.short_range.forcing.f001.conus.nc"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 4.27 s, sys: 288 ms, total: 4.56 s\n",
"Wall time: 4.64 s\n"
]
}
],
"source": [
"%%time\n",
"ds = xr.open_mfdataset(urls, concat_dim='time')"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (nv: 2, reference_time: 169, time: 169, x: 4608, y: 3840)\n",
"Coordinates:\n",
" * reference_time (reference_time) datetime64[ns] 2018-07-01 ...\n",
" * x (x) float64 -2.304e+06 -2.303e+06 -2.302e+06 ...\n",
" * y (y) float64 -1.92e+06 -1.919e+06 -1.918e+06 ...\n",
" * time (time) datetime64[ns] 2018-07-01T01:00:00 ...\n",
"Dimensions without coordinates: nv\n",
"Data variables:\n",
" time_bounds (time, nv) datetime64[ns] dask.array<shape=(169, 2), chunksize=(1, 2)>\n",
" ProjectionCoordinateSystem (time) |S1 b'' b'' b'' b'' b'' b'' b'' b'' ...\n",
" T2D (time, y, x) float64 dask.array<shape=(169, 3840, 4608), chunksize=(1, 3840, 4608)>\n",
" LWDOWN (time, y, x) float64 dask.array<shape=(169, 3840, 4608), chunksize=(1, 3840, 4608)>\n",
" Q2D (time, y, x) float64 dask.array<shape=(169, 3840, 4608), chunksize=(1, 3840, 4608)>\n",
" U2D (time, y, x) float64 dask.array<shape=(169, 3840, 4608), chunksize=(1, 3840, 4608)>\n",
" V2D (time, y, x) float64 dask.array<shape=(169, 3840, 4608), chunksize=(1, 3840, 4608)>\n",
" PSFC (time, y, x) float64 dask.array<shape=(169, 3840, 4608), chunksize=(1, 3840, 4608)>\n",
" RAINRATE (time, y, x) float32 dask.array<shape=(169, 3840, 4608), chunksize=(1, 3840, 4608)>\n",
" SWDOWN (time, y, x) float64 dask.array<shape=(169, 3840, 4608), chunksize=(1, 3840, 4608)>\n",
"Attributes:\n",
" model_initialization_time: 2018-07-01_00:00:00\n",
" model_output_valid_time: 2018-07-01_01:00:00"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ds"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"var = 'T2D'"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"23.92326144"
]
},
"execution_count": 13,
"metadata": {},
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}
],
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"ds[var].nbytes/1.e9"
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},
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"cell_type": "code",
"execution_count": 14,
"metadata": {},
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"VBox()"
]
},
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],
"source": [
"mean_var = ds[var].mean(dim='time').persist()\n",
"progress(mean_var)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"isub=2\n",
"mean_var[::isub,::isub].plot.imshow(figsize=(8,6));"
]
},
{
"cell_type": "code",
"execution_count": null,
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"%%time\n",
"ds1d = ds[var][:,2000,2000]\n",
"ds1d.plot()"
]
},
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