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@lbesnard
Last active May 15, 2019 04:25
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SOOP TRV (dask, s3fs, xarray, zarr)
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## SOOP TRV examples using s3fs, xarray and zarr\n",
"\n",
"# 1) merging soop trv data in an xarray for one cruise only"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import xarray as xr"
]
},
{
"cell_type": "code",
"execution_count": 2,
"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://127.0.0.1:39221\n",
" <li><b>Dashboard: </b><a href='http://127.0.0.1:43095/status' target='_blank'>http://127.0.0.1:43095/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>12</li>\n",
" <li><b>Cores: </b>96</li>\n",
" <li><b>Memory: </b>397.04 GB</li>\n",
"</ul>\n",
"</td>\n",
"</tr>\n",
"</table>"
],
"text/plain": [
"<Client: scheduler='tcp://127.0.0.1:39221' processes=12 cores=96>"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from dask.distributed import Client\n",
"\n",
"client = Client(\"tcp://127.0.0.1:39221\")\n",
"client"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (TIME: 75815)\n",
"Coordinates:\n",
" * TIME (TIME) datetime64[ns] 2019-05-05T19:46:59 ... 2019-05-14T21:58:35\n",
" LATITUDE (TIME) float64 dask.array<shape=(75815,), chunksize=(75815,)>\n",
" LONGITUDE (TIME) float64 dask.array<shape=(75815,), chunksize=(75815,)>\n",
" DEPTH float64 1.9\n",
"Data variables:\n",
" LATITUDE_quality_control (TIME) float64 dask.array<shape=(75815,), chunksize=(75815,)>\n",
" LONGITUDE_quality_control (TIME) float64 dask.array<shape=(75815,), chunksize=(75815,)>\n",
" CPHL (TIME) float64 dask.array<shape=(75815,), chunksize=(75815,)>\n",
" CPHL_quality_control (TIME) float64 dask.array<shape=(75815,), chunksize=(75815,)>\n",
" PSAL (TIME) float64 dask.array<shape=(75815,), chunksize=(75815,)>\n",
" PSAL_quality_control (TIME) float64 dask.array<shape=(75815,), chunksize=(75815,)>\n",
" TEMP (TIME) float64 dask.array<shape=(75815,), chunksize=(75815,)>\n",
" TEMP_quality_control (TIME) float64 dask.array<shape=(75815,), chunksize=(75815,)>\n",
" TURB (TIME) float64 dask.array<shape=(75815,), chunksize=(75815,)>\n",
" TURB_quality_control (TIME) float64 dask.array<shape=(75815,), chunksize=(75815,)>\n",
"Attributes:\n",
" date_created: 2019-05-14T23:03:17Z\n",
" data_centre: eMarine Information Infrastructure (eMII)\n",
" data_centre_email: info@emii.org.au\n",
" institution: Australian Institute of Marine Science\n",
" file_version: Level 1 - Quality Controlled Data\n",
" file_version_quality_control: Quality controlled data have passed qualit...\n",
" site_code: VNCF\n",
" platform_code: VNCF\n",
" instrument: Wetlabs FLNTU-RT\n",
" instrument_serial_number: FLNTURT-1502\n",
" project: Integrated Marine Observing System (IMOS)\n",
" conventions: IMOS version 1.2\n",
" title: IMOS SOOP-TRV RV Cape Ferguson Trip 7148 F...\n",
" abstract: The Australian Institute of Marine Science...\n",
" source: Wetlabs FLNTU-RT\n",
" keywords: Oceans - Ocean Optics - Fluorescence , Oce...\n",
" references: http://data.aims.gov.au/aimsrtds http://s...\n",
" netcdf_version: 3.6\n",
" quality_control_set: 1\n",
" naming_authority: IMOS\n",
" author: laurent besnard\n",
" author_email: laurent.besnard@utas.edu.au\n",
" principal_investigator: Miles Furnas\n",
" principal_investigator_email: m.furnas@aims.gov.au\n",
" institution_references: http://data.aims.gov.au/aimsrtds http://s...\n",
" citation: The citation in a list of references is: \"...\n",
" acknowledgement: Any users of IMOS data are required to cle...\n",
" distribution_statement: Data may be re-used, provided that related...\n",
" geospatial_vertical_min: 1.9\n",
" geospatial_vertical_max: 1.9\n",
" local_time_zone: 0.0\n",
" time_coverage_start: 2019-05-05T19:46:59Z\n",
" time_coverage_end: 2019-05-14T21:58:35Z\n",
" aims_channel_id: 109226\n",
" metadata_uuid: 8840A909-2D0F-3585-E054-0010E056919A\n",
" Conventions: CF-1.6,IMOS-1.3\n",
" geospatial_lat_max: -18.82318\n",
" geospatial_lat_min: -20.4786\n",
" geospatial_lon_max: 149.1409\n",
" geospatial_lon_min: 147.61874\n",
" cdm_data_type: Trajectory\n",
" vessel_name: Cape-Ferguson\n",
" trip_id: 7148\n",
" history: Wed May 15 09:03:20 2019: ncatted -O -a ce...\n",
" NCO: \"4.5.4\"\n",
" nco_openmp_thread_number: 1"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import s3fs\n",
"\n",
"fs = s3fs.S3FileSystem(anon=True)\n",
"vessel_name = 'VNCF_Cape-Ferguson'\n",
"soop_trv_dir = 'imos-data/IMOS/SOOP/SOOP-TRV/{vessel_name}/By_Cruise/Cruise_START-20190505T194659Z_END-20190514T215835Z/'.format(vessel_name=vessel_name)\n",
"\n",
"soop_trv_dir = fs.walk(soop_trv_dir)\n",
"soop_trv_files = [k for k in soop_trv_dir]\n",
"ds_soop_trv_multi = xr.open_mfdataset([fs.open(soop_trv_files[i]) for i in range(len(soop_trv_files))],engine='h5netcdf')\n",
"ds_soop_trv_multi\n",
"# this is a dataset commpiling 4 NetCDF (one per variable) in a same xarray"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7f0b32203438>]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"ds_soop_trv_multi.TEMP.plot()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 2) merging soop trv data for 2 variables only (TEMP and PSAL)"
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {},
"outputs": [],
"source": [
"import s3fs\n",
"\n",
"fs = s3fs.S3FileSystem(anon=True)\n",
"vessel_name = 'VNCF_Cape-Ferguson'\n",
"soop_trv_dir = 'imos-data/IMOS/SOOP/SOOP-TRV/{vessel_name}/By_Cruise/'.format(vessel_name=vessel_name)\n",
"\n",
"soop_trv_dir = fs.walk(soop_trv_dir)"
]
},
{
"cell_type": "code",
"execution_count": 78,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (TIME: 3123970)\n",
"Coordinates:\n",
" * TIME (TIME) datetime64[ns] 2008-09-30T00:27:27 ... 2010-04-21T22:19:11.999999744\n",
" DEPTH float64 1.9\n",
" LATITUDE (TIME) float64 dask.array<shape=(3123970,), chunksize=(162772,)>\n",
" LONGITUDE (TIME) float64 dask.array<shape=(3123970,), chunksize=(162772,)>\n",
"Data variables:\n",
" LATITUDE_quality_control (TIME) float64 dask.array<shape=(3123970,), chunksize=(162772,)>\n",
" LONGITUDE_quality_control (TIME) float64 dask.array<shape=(3123970,), chunksize=(162772,)>\n",
" CPHL (TIME) float64 dask.array<shape=(3123970,), chunksize=(162772,)>\n",
" CPHL_quality_control (TIME) float64 dask.array<shape=(3123970,), chunksize=(162772,)>\n",
" PSAL (TIME) float64 dask.array<shape=(3123970,), chunksize=(162772,)>\n",
" PSAL_quality_control (TIME) float64 dask.array<shape=(3123970,), chunksize=(162772,)>\n",
" TEMP (TIME) float64 dask.array<shape=(3123970,), chunksize=(162772,)>\n",
" TEMP_quality_control (TIME) float64 dask.array<shape=(3123970,), chunksize=(162772,)>\n",
"Attributes:\n",
" date_created: 2018-12-06T12:17:23Z\n",
" data_centre: eMarine Information Infrastructure (eMII)\n",
" data_centre_email: info@emii.org.au\n",
" institution: Australian Institute of Marine Science\n",
" file_version: Level 1 - Quality Controlled Data\n",
" file_version_quality_control: Quality controlled data have passed qualit...\n",
" site_code: VNCF\n",
" platform_code: VNCF\n",
" instrument: Wetlabs FLNTU-RT\n",
" instrument_serial_number: FLNTURT-753\n",
" project: Integrated Marine Observing System (IMOS)\n",
" conventions: IMOS version 1.2\n",
" title: IMOS SOOP-TRV RV Cape Ferguson Trip 4714 F...\n",
" abstract: The Australian Institute of Marine Science...\n",
" source: Wetlabs FLNTU-RT\n",
" keywords: Oceans - Ocean Optics - Fluorescence , Oce...\n",
" references: http://data.aims.gov.au/aimsrtds http://s...\n",
" netcdf_version: 3.6\n",
" quality_control_set: 1\n",
" naming_authority: IMOS\n",
" author: laurent besnard\n",
" author_email: laurent.besnard@utas.edu.au\n",
" principal_investigator: Miles Furnas\n",
" principal_investigator_email: m.furnas@aims.gov.au\n",
" institution_references: http://data.aims.gov.au/aimsrtds http://s...\n",
" citation: The citation in a list of references is: \"...\n",
" acknowledgement: Any users of IMOS data are required to cle...\n",
" distribution_statement: Data may be re-used, provided that related...\n",
" geospatial_vertical_min: 1.9\n",
" geospatial_vertical_max: 1.9\n",
" local_time_zone: 0.0\n",
" time_coverage_start: 2008-09-30T00:27:27Z\n",
" time_coverage_end: 2008-10-13T09:34:01Z\n",
" aims_channel_id: 8365\n",
" metadata_uuid: b5343281-2bff-420c-9ba3-333fad9acec6\n",
" Conventions: CF-1.6,IMOS-1.3\n",
" geospatial_lat_max: -16.11006\n",
" geospatial_lat_min: -23.2376\n",
" geospatial_lon_max: 151.073\n",
" geospatial_lon_min: 145.48344\n",
" cdm_data_type: Trajectory\n",
" vessel_name: Cape-Ferguson\n",
" trip_id: 4714\n",
" history: Thu Dec 6 23:17:28 2018: ncatted -O -a ce...\n",
" NCO: \"4.5.4\"\n",
" nco_openmp_thread_number: 1"
]
},
"execution_count": 78,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"soop_trv_files = [k for k in soop_trv_dir if 'temperature' in k or 'salinity' in k or 'chlorophyll' in k]\n",
"\n",
"#subset on n files\n",
"n_files = 50\n",
"ds_soop_trv_multi = xr.open_mfdataset([fs.open(soop_trv_files[i]) for i in range(n_files)],engine='h5netcdf')\n",
"\n",
"# all dataset\n",
"#ds_soop_trv_multi = xr.open_mfdataset([fs.open(soop_trv_files[i]) for i in range(len(soop_trv_files))],engine='h5netcdf')\n",
"\n",
"ds_soop_trv_multi\n",
"# this is a dataset commpiling all temperature NetCDF in a same xarray"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7f0a3296bac8>]"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# plot of monthly average\n",
"ds_soop_trv_multi.groupby('TIME.month').mean(dim='TIME').TEMP.plot()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"#ds_soop_trv_multi.persist"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7f0a4c1bc438>]"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"ds_soop_trv_multi.TEMP.plot()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## creation of a zarr dataset"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"import shutil\n",
"def get_encoding(name):\n",
" '''Get encodings from a Zarr archive.\n",
" Arguments:\n",
" - name: the name of the archive.\n",
" Returns:\n",
" - encoding: the encodings of the variables.\n",
" '''\n",
" ds = xr.open_zarr(name)\n",
" encoding = {name: ds[name].encoding for name in list(ds.variables)}\n",
" return encoding\n",
"\n",
"def create_zarr(ds, name, encoding=None):\n",
" '''Create a Zarr archive from an Xarray Dataset.\n",
" Arguments:\n",
" - ds: the Dataset to store.\n",
" - name: the name of the Zarr archive.\n",
" - encoding: the encoding to use for each variable.\n",
" Returns:\n",
" - encoding: the encoding used for each variable.\n",
" '''\n",
" shutil.rmtree(name, ignore_errors=True)\n",
" ds = ds.chunk({name: ds[name].shape for name in list(ds.dims)})\n",
" ds.to_zarr(name, encoding=encoding)\n",
" if encoding is None:\n",
" encoding = get_encoding(name)\n",
" return encoding"
]
},
{
"cell_type": "code",
"execution_count": 79,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'CPHL': {'chunks': (3123970,),\n",
" 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0),\n",
" 'filters': None,\n",
" '_FillValue': 999999.0,\n",
" 'dtype': dtype('float64'),\n",
" 'coordinates': 'LATITUDE DEPTH LONGITUDE'},\n",
" 'CPHL_quality_control': {'chunks': (3123970,),\n",
" 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0),\n",
" 'filters': None,\n",
" '_FillValue': 999999.0,\n",
" 'dtype': dtype('float64'),\n",
" 'coordinates': 'LATITUDE DEPTH LONGITUDE'},\n",
" 'DEPTH': {'chunks': (),\n",
" 'compressor': None,\n",
" 'filters': None,\n",
" '_FillValue': nan,\n",
" 'dtype': dtype('float64')},\n",
" 'LATITUDE': {'chunks': (3123970,),\n",
" 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0),\n",
" 'filters': None,\n",
" '_FillValue': nan,\n",
" 'dtype': dtype('float64')},\n",
" 'LATITUDE_quality_control': {'chunks': (3123970,),\n",
" 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0),\n",
" 'filters': None,\n",
" '_FillValue': nan,\n",
" 'dtype': dtype('float64'),\n",
" 'coordinates': 'LATITUDE DEPTH LONGITUDE'},\n",
" 'LONGITUDE': {'chunks': (3123970,),\n",
" 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0),\n",
" 'filters': None,\n",
" '_FillValue': nan,\n",
" 'dtype': dtype('float64')},\n",
" 'LONGITUDE_quality_control': {'chunks': (3123970,),\n",
" 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0),\n",
" 'filters': None,\n",
" '_FillValue': nan,\n",
" 'dtype': dtype('float64'),\n",
" 'coordinates': 'LATITUDE DEPTH LONGITUDE'},\n",
" 'PSAL': {'chunks': (3123970,),\n",
" 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0),\n",
" 'filters': None,\n",
" '_FillValue': 999999.0,\n",
" 'dtype': dtype('float64'),\n",
" 'coordinates': 'LATITUDE DEPTH LONGITUDE'},\n",
" 'PSAL_quality_control': {'chunks': (3123970,),\n",
" 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0),\n",
" 'filters': None,\n",
" '_FillValue': 999999.0,\n",
" 'dtype': dtype('float64'),\n",
" 'coordinates': 'LATITUDE DEPTH LONGITUDE'},\n",
" 'TEMP': {'chunks': (3123970,),\n",
" 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0),\n",
" 'filters': None,\n",
" '_FillValue': 999999.0,\n",
" 'dtype': dtype('float64'),\n",
" 'coordinates': 'LATITUDE DEPTH LONGITUDE'},\n",
" 'TEMP_quality_control': {'chunks': (3123970,),\n",
" 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0),\n",
" 'filters': None,\n",
" '_FillValue': 999999.0,\n",
" 'dtype': dtype('float64'),\n",
" 'coordinates': 'LATITUDE DEPTH LONGITUDE'},\n",
" 'TIME': {'chunks': (97625,),\n",
" 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0),\n",
" 'filters': None,\n",
" '_FillValue': nan,\n",
" 'units': 'seconds since 2008-09-30 00:27:27',\n",
" 'calendar': 'proleptic_gregorian',\n",
" 'dtype': dtype('float64')}}"
]
},
"execution_count": 79,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"create_zarr(ds_soop_trv_multi, 'soop_trv_ferguson_temp_psal_cphl.zarr')"
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {},
"outputs": [],
"source": [
"zarr_load_trv = xr.open_zarr('soop_trv_ferguson_temp_psal_cphl.zarr')"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 864x504 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#from mpl_toolkits.basemap import Basemap\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"fig, ax = plt.subplots(figsize=(12,7))\n",
"\n",
"lats = zarr_load_trv.LATITUDE\n",
"lons = zarr_load_trv.LONGITUDE\n",
"\n",
"plt.plot(lons,lats)\n",
"\n",
"plt.show()\n",
"## pretty dirty to show all tracks "
]
},
{
"cell_type": "code",
"execution_count": 89,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(17.200000000000003, 0.5, 'Temperature / Deg')"
]
},
"execution_count": 89,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(x=zarr_load_trv.TEMP, \n",
" y=zarr_load_trv.PSAL,\n",
" c=zarr_load_trv.LATITUDE,\n",
" marker='+', linestyle=\"None\", cmap='RdYlBu_r')\n",
"plt.colorbar()\n",
"ax2.set_xlabel('Salinity / PSU')\n",
"ax2.set_ylabel('Temperature / Deg')\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.6.7"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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