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@lbesnard
Last active May 15, 2019 01:49
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Accessing FAIMMS netcdf files from S3 via s3fs, using xarray and dask
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Import FAIMMS Air temperature dataset from One Tree Island from S3 bucket\n",
"We re looking into importing from the IMOS s3 buck"
]
},
{
"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: 416066)\n",
"Coordinates:\n",
" LATITUDE float64 -23.5\n",
" LONGITUDE float64 152.1\n",
" * TIME (TIME) datetime64[ns] 2008-11-18T09:00:00 ... 2017-09-17T07:50:00.000000256\n",
"Data variables:\n",
" AIRT (TIME) float64 dask.array<shape=(416066,), chunksize=(1722,)>\n",
" AIRT_quality_control (TIME) float64 dask.array<shape=(416066,), chunksize=(1722,)>\n",
"Attributes:\n",
" date_created: 2017-10-25T19:42:20Z\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 qua...\n",
" site_code: OTIWS\n",
" platform_code: OTIWS\n",
" instrument: Vaisala WXT520\n",
" instrument_serial_number: G0720016\n",
" project: Integrated Marine Observing System (IMOS)\n",
" conventions: IMOS version 1.2\n",
" title: Great Barrier Reef Ocean Observing Syst...\n",
" abstract: The Great Barrier Reef Ocean Observing ...\n",
" source: Vaisala WXT520\n",
" keywords: Oceans | Coastal Processes | Coral Reef...\n",
" references: http://data.aims.gov.au/aimsrtds http:...\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: Scott Bainbridge\n",
" principal_investigator_email: s.bainbridge@aims.gov.au\n",
" institution_references: http://data.aims.gov.au/aimsrtds http:...\n",
" citation: The citation in a list of references is...\n",
" acknowledgement: Any users of IMOS data are required to ...\n",
" distribution_statement: Data may be re-used, provided that rela...\n",
" local_time_zone: 10.0\n",
" time_coverage_start: 2008-11-18T09:00:00Z\n",
" time_coverage_end: 2008-12-01T00:00:00Z\n",
" aims_channel_id: 162\n",
" metadata_uuid: e5aa917e-d559-45b6-be32-52b18542bad2\n",
" Conventions: CF-1.6,IMOS-1.3\n",
" geospatial_lat_max: -23.49787\n",
" geospatial_lat_min: -23.49787\n",
" geospatial_lon_max: 152.05275\n",
" geospatial_lon_min: 152.05275\n",
" history: Thu Oct 26 06:42:20 2017: ncatted -O -a...\n",
" NCO: \"4.5.4\"\n",
" nco_openmp_thread_number: 1\n",
" compliance_checks_passed: cf imos:1.3\n",
" compliance_checker_version: 2.3.1\n",
" compliance_checker_imos_version: 1.1.2"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import s3fs\n",
"\n",
"fs = s3fs.S3FileSystem(anon=True)\n",
"faimms_dir = fs.walk('imos-data/IMOS/FAIMMS/One_Tree_Island/Weather_Station_Platform/air_temperature_channel_162/')\n",
"faimms_qaqc_files = [k for k in faimms_dir if 'FV01' in k]\n",
"ds_faimms_multi = xr.open_mfdataset([fs.open(faimms_qaqc_files[i]) for i in range(len(faimms_qaqc_files))],engine='h5netcdf')\n",
"ds_faimms_multi"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plot the entire timeseries for the last 10 years"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7fbae8bd7128>]"
]
},
"execution_count": 13,
"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_faimms_multi.AIRT.plot()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## creating a ZARR dataset\n",
"see [Continuously extending Zarr datasets](https://medium.com/pangeo/continuously-extending-zarr-datasets-c54fbad3967d)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"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": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'AIRT': {'chunks': (416066,),\n",
" 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0),\n",
" 'filters': None,\n",
" '_FillValue': 999999.0,\n",
" 'dtype': dtype('float64'),\n",
" 'coordinates': 'LONGITUDE LATITUDE'},\n",
" 'AIRT_quality_control': {'chunks': (416066,),\n",
" 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0),\n",
" 'filters': None,\n",
" '_FillValue': 999999.0,\n",
" 'dtype': dtype('float64'),\n",
" 'coordinates': 'LONGITUDE LATITUDE'},\n",
" 'LATITUDE': {'chunks': (),\n",
" 'compressor': None,\n",
" 'filters': None,\n",
" '_FillValue': 999999.0,\n",
" 'dtype': dtype('float64')},\n",
" 'LONGITUDE': {'chunks': (),\n",
" 'compressor': None,\n",
" 'filters': None,\n",
" '_FillValue': 999999.0,\n",
" 'dtype': dtype('float64')},\n",
" 'TIME': {'chunks': (52009,),\n",
" 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0),\n",
" 'filters': None,\n",
" '_FillValue': nan,\n",
" 'units': 'seconds since 2008-11-18 09:00:00',\n",
" 'calendar': 'proleptic_gregorian',\n",
" 'dtype': dtype('float64')}}"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"create_zarr(ds_faimms_multi, 'faimms_one_tree_island_airt.zarr')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Examples on how to load a ZARR dataset into xarray and do some basic computation"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"zarr_load_faimms = xr.open_zarr('faimms_one_tree_island_airt.zarr')"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7fbae8be7198>]"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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MsTC1uQ427djLyk07Yx5bVlxG6R7/fdLXbLFWKc9ds43qiNawWZa//YAwvuA13jobSsM5X2UGHgavKNtTwdLi6IgK3mKURx2MeuAjjn34k5jHTnx0Ouc/8ZW/AgH3T1oEwPclO/nXNJMCNpIa5VEbQTs7+e0RZzh4uOiprznp0em+lmmURx2UR6wO3m9/pbW/JuyEXxRt283yjVZOii27yikL0EYctAkoGYKW2Yw8EqO25zRn9VbKAhjth5mKqmq+/G4z8wJYG2OURxLc+N+5gZQbaRcOmjAswItHbZP6QY0AzMgjeXaVV3L2Y19wzb9nBy1KqHh4yhLOf9J/CwgY5ZEUc1Zv873M579Yud9nMY6NcalWmFK4geooz7SgPMWM7kieiirrmc1b6/+7Vxvbd1fwxXebAim7ulqZMGstj0/bPyvmBwuL94un5iVGeSRBEI3AXW8V7vd5d8X+3lW+yxT+gQf/+WY1V704i//NWhu0KIBZx5AodVatENW7K1+YyQVPfs2Ovf6bj1/5ZjW/eW3eAfuveGEmj0/3J82yUR5JELTtPAykwi2oGSGWREWzDc5sBdOWlrCsuIyPl2xk685y/6MhpwCxRoZhHLXN+H4LABWV/vT0I1lXR6Kz9dv9yRtj1nkkQVgy1EXitxkrFRRoTXjv1+cUcd2YHvv2B2W2qlYY/8yMfZ/7dGjO4g1lfHv3SeQ0zqzjyoOLOWvCY5pKhCBqU11V2K/1RGbk0UB49ZvVvtk6U43iqHUfG8uCyasR7W31XYnlObd+WzjXpQTFjjq8CMsCMBGFjapq5bFPanfT9ysMjlEeDYSd5VU8FzWpbtifSnvifG1A6WCjzWU1k8AXPhWMt0wqsXi9vwvgnOD3SPYVO61xbTz12fe+yGGURwKs2bIraBESws80p6ngqhtNCM3mAGzaYdLTRhJrfmNneXhHHNU+vwphybZolEcCjP3H50GLkBD/+Ni/FeepMOcRTdDrLMKqvMJGzPsU4vqWih0pNzDKI4roNQEAm3eanmE0qfi6BO2xs7cOr5xLn50RykjFQRCrJ3+wNtCxKFwXjkyLRnlE8cEi4zqZitTV8ErU36D4ywdLaz328ZISltmhZw52Pl12YEqE6jD7gvis1ybN3xD/JB8wyiOK2uJZGfYnbL3kul6oGklrJqiDYufeusPmm7hNFtVqZfOMJFy1Dd6PyE3/9rfrA5QkOIzyiGKLMVElRJh0R0VVNX96f3Hc8975dp0P0tROPLPZ58vrjgp8MBEdjidsXP3irH3/3/vOwgAlCQ6jPKLo2qZp0CIcwN7K1Ez09PnyTfz3mzWel/PKjNWs3FyHR5yt6Cp8HlVGrwL+Nk7k02c+/z50Izo/iPWby6Pmh6oPwvsSdozyiCKMYbMTjc2U17KJx5I448KnvubmCd96WkbZngr+3wfLGHlI69rPsReW+d3+TF3obP5s264KPl0WTKC9IHm/8MD7dGAWSKM8wkbCykNEHhKRHBHJFJEPRWSTiFzkpXBB4Hcu8ESoa8VtJK2bNvJYkvDx5PQVbN5Zzm2n9g1alAOYstD5xOYzn/uzwCsWV784k4ue+trXMnfureSetwsP2B8dn8noDmfURC/wEicjj5NUtRQ4HVgL9AJuclMYEeksIh+LyCIRKRSRX9r7/yQii0XkWxF5XURaulluJOu3hy9UxF8+WJbQeX7qvTC8zBtL9/Dkp99z+qCOHNo5fpXwU+Ttuyr4asUWR9ec0Lcdnywp2Zfwy2/eLyzms+X+jnz++uEy1sV4516Zsb+5MwTVrU4+XrIxaBH248rnZ3pehhPlURO57UfAK6rq7M1IjErgN6raFxgJXCci/YCpwABVHQQsBW7zoGwgttkq6MFIoj7u8WzqblIZ4Tv51KcreH2O/2HP//LhMiqrq7np5N4Jne+nSfKjJcVUOVx6fMGILjRKT+O5L/wffZQG4Om1ZEMZT3/2PT8Z1jnm8Tmrt1Jw67tsLN3DtS+FOwnU7a8vYGeI4m6t2LTT8zKcKI+3RWQxMAz4UERyAVe76aq6XlVn2/+XAYuAPFWdoqo1T+YrIN/NciOJZbYK2pAVxsRPCyJS8N737iJ+/eqBuQW8ZPnGHbz6zRouHNE1YScHP+/jlMJi2udkObqmVXYjzjqsExNmFbHNx1AzAK98XXe8JLeprlZuf2M+zRtncOupfWKec/ZjXwBww3/m+ClaUqzbvpuHpywJWgxfSVh5qOqtwBHAMFWtAHYBZ3klmIgUAIOBaCPsZcB73pV74D6/Y9dEE/TIJxZBT2A+NHkxTTLT+cVxPeKfbOPXfdxTUcUnS0o4sV97R9cpcOnobuyuqOI/PnipRbLa5/ht/5u9lm9WbuXWU/vQKs5cXagXCNr8bGRXnvtiJXNWb/W0HD+8FxPFyYR5NnAd8E97VyesUYjriEgzYALwK3uepWb/77FMWy/Vct1VIjJTRGaWlBy4SjXBspO6zkvCJxGOTTJuMnPlFqYsLObqow+hTbPEe/d+PdrPlm1id0UVJ/Xr4Og6VejXKYcjDmnD81+s9NW1+CUfRx5bd5bzwKRFDO3aih8PjW2yiqQqDBNscbjp5N50yGnMrRPmH+Bm7CZeey86wYnZ6lmgHBhlf14L3Oe2QCKSiaU4XlLViRH7x2NN1l+otXR7VfUJVR2mqsNyc3Ndlavg1neZurCYN+YUufq9qUplQMpDVXngvcW0a57F5Ud1c3Rt9CSsV0xZuIHmjTMYeUgbR9fVVOvLjuzG+u179lvF3JB46P3FlO6p5L6xA0hLYCJq1ipve/Nu0LxxJveNHcCS4jIen+ZfgNIgcaI8uqvqQ0AFgKruxuVOsVjd/qeBRar6SMT+U4BbgDNV1dPxdV0/6Of/nsWvXp3rZfExCeNoKKiRx5SFxcxatZVfn9iL7EbhS4RZVa18sGgjx/VpR6MMZ8uoam7pcX3a0bVNNs/4lJfBT2at2sorM9Zw2egC+nbMCVocVzm+b3tOH9SRv320PDCPOT9xUrvLRaQJtteciHQH3E7JNhr4GXCciMy1tx8BfweaA1Ptff9yudyECNrOHyacKA+3VshXVlXzf5MX0z23KT8e6pnPRL2YtWorW3aWOzZZwQ/1Kz1NuGRUAbNXb/Pchu4nlVXV3P7GAjrkNOZXJ/QKWhxPuOuM/jRplM5tE7+NGaG7IeFEedwFTAY6i8hLwIfAzW4Ko6qfqaqo6iBVPczeJqlqD1XtHLHv526Wm7B8QRRKOOc8nISLcCvN6qsz17CiZCe3nNKHjPRwBkeYUriBRulpHNPbudk08o7+eFhnmmdl8OznK12TLWie+2Ili9aXctcZ/WiaFb5RoxvkNs/i9tP68s3KrbwcJ+NfquPE22oqcA5wCfAKltfVJ96IFU5SYeDx0WJ/QspX1hGh9vtNOym49V1Xy9tVXslfPljG8IJWjr2Y/EJVmbKwmNE92tAsicYxUiE3y8rgvOGdmTR//QGrrVORDdv38OjUpRzbO5dTBjgflaUS5w7NZ3SPNjz43mI2hHDRsVs48bYS4FRgqKq+A2SLyOGeSRYQIZxecDT0eHRqYqvR60tdI49J8/cPUe2Gzn3q0+8pKdvLraf2DeUcEMCS4jJWb9nFSf2Taxyjb+klowqoVuXFL1e5IF2w3PvOQiqrlXvOHBDa5+cWIsIfzx5IZbVlpmuo5m4nY//HsNZ5nG9/LgP+4bpEhgNolZ14zCq/vKBilfOPj5d7UtamHXt5fNp3nNK/A0O7tnLlO714od9fUIwIHN+3XVLXR4vUuXU2J/Zrz8szVrO73L/IygW3vkvBre/yiEuL3qYtLeHd+eu5fkwPurTJduU7w07XNk258cRefLComPcWNEyvOSfKY4SqXoe9qlxVtwIHXyS+CC4+oqsv5Yw9rFPC51b5tKIq1oT5n96P3djUt6H+24fL2FNZzU2nJBaGJBG86AxOWbiBIV1a0a5546SujzWau2x0N7btquD1AFzE//pR/TsDeyqquPPNBRzStilXHXOIC1KlDpeN7saAvBzufLOQ7bsaXqIvJ8qjQkTS+cHbKhdIgbWf3pGR5s+krZNhvl8jj7q8raKVSH0k+n7TTl76ejU/Hd6Z7rnN6vFN++N2Xvq1W3dRuK6Uk+oxHxNLeRzerTX9O+WkbK6Pxz75jlWbd3Hv2AFkZaQHLY6vZKSn8eA5g9i6q5w/TloUtDiu46T1+yvwOtBORO4HPgP+6IlUKUKiAQvrixMTsV/rL/wq5+H3l9AoI41fntAz6e84oe+BDbrbfvg1uTuSne+A2EpWRLj8yG4s37gj5XJ9rCjZwb8++Y4zD+3E6B5tgxYnEAbkteDKow7h1Zlr+MLniMVe48Tb6iUs19wHgPXAWFV9zSvBDD+wzcGQd1VdGfVcpCzBHCMAny5NLlTM3DXbeHf+eq486pCkTUEALZpkHrBvQZG7EYinFBbTq30zurVNPhNlbSOL0wZ1JLd5VqC5Ppyiqtz5ZiFZGWncfnr4cq34ya9O6EnXNtnc9vr8A3KzpzIJKQ8RSRORBaq6WFX/oap/V9WGNw4LKU6D1oXNvDEpiQlDVeWBSYto26wRVx5dP1t5347ND9j3+Xfu9QK37ixnxsotSS0MjCS9FjNoVkY6PxvZNdBcH05559v1fLZ8E789uXe9FH9DoHFmOg+cM5BVm3clnJsnFUhIeahqNTBPRLp4LI8hBk6VwXyXe9WxqHQyMZ+ELvt4yUa+/n4Lvzy+Z1JrJiK5790D+zlu6tePFm+kqlo5qX/91p+0rsOr7oIRXWiUEUyuD6eU7ang3ncWMiAvh4tG+uNUEnZGdW/LT4Z15slPV7g+6g0KJ3MeHYFCOwXtWzWbV4KlAn518J0WMyHBnOf1wUnEV6dzQ1XVyoPvLaZb26b89PDw91feL9xAh5zGDMxrUa/vGZhf+/Vtm2UxNqBcH07585SllOzYy/1jB5LuZwaukPO7H/WlVXYjbp34LZU+Rkz2CifK4w9YUW3vAf4csTUowph4yenc9Fvz1nkaFhrw1HNmwqy1LC3ewc0n9ybTozAkbun93eVVTF9Wwkn923u++K0m14df0YGTYUHRdl74ciUXjuiSUGrgg4kW2Zncc1Z/FhSVptT8VW04mTCfFmvzUrggCOPiV6dmq627Kvhosbc5lVtmHzgJDbB5R/1iZe4ur+KRqUsZ3KWlp2Es3JoX+nRZCXsqqus935EIfTvmMKp7G1740t9cH4lSXa38/o0FtG7aiJtOjp0d8GDn1AEdOLFfex6ZupRVm71PFeslTsKTlIlIadS2RkReF5GDa/VPyMltnsWE2d6armqLGDr0vg8O2OeknX72i+/ZULqH20IchiSSKQuLyWmcwYhDWvtS3mWjrVwfk0O4avmVb1Yzb802fn9a35gebgbL9freswaQmZbG716f76gTEzZHGCc2gUeAm4A8rBzivwWeBP4DPOO+aMEQsucDOJfp7MF5fLx4Y71HAXXhxJSW6Klbdpbzz4+/44S+7Ti8m7uNsRdmvMqqaj5cVMzxfdt7Zl6LZl+uj5CZPTbt2Mv/vbeYkYe0ZuxheUGLE2o6tGjMLaf24fPlm/mfg/nJsLVNTmr8Kar6uKqWqWqpqj4B/EhVXwXcCThkiInTCedxQ/KprFbemrfOI4m8WSD594+Ws7O8kltOcd/kcYsH6TtnrtrK1l0V9VpV7pS0NOHSUQXMWb2N2SHK9fHHSYvYXVHFfWMbfuBDN7jg8C4ML2jFfe8uoqQssU5eyHSHI+VRLSLn2Ws+0kTkvIhjYftdSRPGeu+0x9G7Q3MG5OV4arpyNPJI4Aes2bKLF79ayXnDOtOz/YHrMuqLF7GhphQW0ygjjaN7uZvyOB7nhizXx1crNjNxdhFXHnUIPdq5/+waImlpwgPnDGJ3eRV/eLswoWtS2Wx1IVaWv41Asf3/RXZ2wes9kM1gk0y6znMG57OgqJQlG8o8kMhZMqhEznx4yhLS04Rfn+hPhrm9FfUzY1m5OzZwVI+2vic2apaVwU9CkuujvLKaO95YQH6rJvziuORDyByM9GjXjF8c14N3vl3PBwvj5+EJl+pw5m21QlXPUNW2qppr/79cVXer6mdeCulzvQ6mAAAgAElEQVQnIVPuAAzu4tzl8azDOpGRJkz0avTh4n1aULSdN+eu4/Iju9E+x5/VyJkZ9RtiLlxfytqtu+u9MDBZxo8qQFV5IeBcH09/9j3LNu7gD2da6VcNzrj6mO70bt+cO95cQNmeusMQha1tcuJt1cteILjA/jxIRG73TrRgcGK28msY2STT+UvZplkWx/Zux+tzijxZkOQkMGJdt0lVeeC9RbTKzuTqY7q7IFlitG6aVa/rpxQWkyZwfIygi37QuXU2J/XrwMtf+5vrI5K1W3fx1w+XcWK/9oHdh1SnUUYaD44byIbSPbWmNKjBr0CsieLEbPUkcBtQAaCq3wI/9UKoIAnhlEfSnjznDs1jY9lePvMgmqdb3lbTl23i8+WbueH4nuQ09s+9s1Ut61QSZcrCYoZ1bU3bZvVTQvXhsiO7sX13BRPneB9RIBZ3v7XQ+ntm/0DKbygM7tKKS0YV8OJXq5i5ckut56XsyAPIVtUZUfsSD61q8J0xfdrRMjuTCbPdnyyOFWzQKdV2GJIurbO5cIS/MZDq8yKu2bKLRetLAzNZ1TC8oBUD8nJ45rPva1134xVTFxbzwaJifnlCT/JaNvG17IbIb0/qTacWTbh14nz2VqZG5F0nymOTiHTnh2RQ52KFZjd4TLLNQlZGOmce2okphRsojWNPdYqjBqOWlvqNuUUsWl/Kb0/uTaMMf9ZJuMEUe3LzRB9ddGMhIlw2uhvflezkUx9zRewqr+Tutwrp1b4Zlx/ZzbdyGzJNszK47+wBLN+4g8c+/i7mOak88rgOeBzoIyJFwK+AazyRyuAa44bks7eymne/dVfPP/vFyoTPjVXn91RU8ecpSxmY14LTB3Z0RaYODibb62M/nlK4gT4dmtO1TfK5O9xiX66Pz/xbNPi3j5ZTtG03940d6NviyIOBMb3bMfawTjz2yXKWFh/oJZmycx62t9UJQC7QR1WPVNWVnkkWEE4mzIu2+eMmWZ+J+UH5LejRrpnrkXYXbyit1/UvfrmKom27ue1HfUhzKfJq93beN+Zbdpbzzcotvi4MrIuaXB/TlpawfKM3btmRLCsu48npKxg3JN/1KACpgpeOMnec3o9mWRncMuHbA5xSUm7kISI3Rm7A1cCVEZ8bFE4e0AeLvA0+6AYiwrgh+cxctZWVm8IRiG37rgr+/vFyju2dy6ju7qUndZJxMVk+WFRMtdYv3azb1OT68HrRoKpy+xsLaJqVwe9+dHAGPqyqtjIkekWbZlnceUY/5qzexr+/2t8NO2S6I6GRR3N7G4Zlpsqzt58D/bwTzVBDfSvN2MGdEMG7NR9xiFbIj32ynNI9Fa6HIfEj0uyUwmI6tWhM/07OF256xb5cH7PXeprrY+LsIr7+fgu3nNKHNgF6mQXFnooqfvHKbF6MatTPHuxuLK+xh+VxdK9cHpq8mHUR1o2UW2Guqn9Q1T8AbYEhqvobVf0NMBQrQKIh5HRs0YQje7Rlwuwi17xynOQ9ibTVFm3bzbNfrOScwflJrZyvix8P7Zy4TEnchl3llXy6rIST+ncIXfymS0d3Y09FtWe5PrbvquCPkxYxuEtLfjo88fvcUCjdU8Elz85g0vwN3H6atznZRYT7xw6gWuGONxbsUxrhUh3OJsy7AJHdmnKgwFVpDLFxodaMG5JP0bbdzKjDj9wJzhZT/vD/I1OWAnDjSe6HIRnuwAafzC2dvnQTeyurA3fRjYXXuT4een8xW3eVc9/YAa7NUaUKG0v38JPHv2Lmyq385SeHccVR3meg6Nw6m9+e3JsPF2/kHdvZJWQDD0fK40VghojcLSJ3AV8Dz3sjlsFtTu7fgWZZGb6kqK2NRetLmThnLZeOLvBkbYCTJm1EEpO9UxZuoEWTTA4vCOdEsVe5Puau2cbLM1YzflQB/TvVL9VuqrGiZAfn/PMLVm3eydOXDGdsDBOVV6r0klEFHJrfgrvfKmTrzvLQDT2ceFvdD1wKbAW2AZeq6gNeCWb4ATdc9Jo0SudHAzswaf56dpXXf21nMi/Mg+8tJqdxJtce06Pe5dcXpzG0rNwdGzm+bzsyQuqe6kWuj8qqan7/+nzaNc/iRp+CVoaFeWu2ce6/vmRXeRWvXDmSY3yOnpyeJjw4bhDbd1dw/6RFB7QDZx3WyVd5onH0FqjqbFX9f/Y2x21hRKSziHwsIotEpFBEfmnvby0iU0Vkmf3Xs/whITNlu8q4IfnsLK/i/cL690yd2PxV4Yvlm5i2tITrx/SgRT1Dg9QukydfC8CMlVvYvrvCl3SzyeJFro8Xv1pF4bpS7ji9H819DB8TNNOWlnD+k1+R3Sid//38iMDysfftmMPPj+nO/2at5dNl/i0ETYREXHVnu3FOglQCv1HVvsBI4DoR6QfcCnyoqj2BD+3PHhE+7eGWrXN4QWs6t27ChFnuhyupi4qqah54bzF5LZvwsyO8C0PiZBLfKVMKi8nKSOPoXu65FnuB27k+/jxlKUf1bMtpLi3kTAXemFPE5c99Q9c2TZl4zSgOyW0WqDzXH9eDQ9o2TTjvh18kMvLoKyLf1rHNx/LEqjequl5VZ9v/lwGLsNyCz+KH+ZXngbFulHewkZYmnDM4n8+/27SfC2AyOGmml23cwfyi7fzmpF40TiJCsBc4UciqytSFxRzVM5fsRv7m7nCK27k+dldUce9ZB092wKc+XcGvXp3LsIJWvHr1SNr5lCKgLhpnpvPAOQPZtMM7N+xkSER59AHOqGM7HRjltmAiUgAMxpqYb6+q68FSMEA7t8tLhp8M89ZlUVVZvnEHT7sYemLckHxUvcmsVxd9O+akbG7rwnWlFG0LLneHU9zM9XHtsd0paBt8GBavqa5WHpi0iPveXcSPBnbguUsPTzzKsw96dcQhbbhgRJeEz2/uQ4KyuCWoqu/ZZkSkGTAB+JWqliba6xGRq4CrALp0SfxGh4mdeyv54rvNTFu6kU+WlLB2q7shULq0yWZ4QSsmzF7Ltcd2T75H6fCy2051LwxJbXjVOZ5SuIE0gRNSJGdFZK6PG47rWa8kTVcd7b1batBUVFVzy/++ZeKcIn42sit3n9mf9BC6I996ah9e/nr1vs+/PqEXb85dF5g8oXMbEZFMLMXxkqpOtHcXi0hH+3hHrFS4B6CqT6jqMFUdlpvrvWeEG15QqsrS4jKemP4dFz71FYPvmcqVL8xk4uwi+nTI4d6xAziqp7t29nFD8llRspO5a7a5+r114XeebzeZsrCY4QWtad20UdCiJIxbuT5SKdpxMuzcW8kVz89k4pwifnNiL+45K5yKAyCnceY+F/fxR3QNfEToydhGRM5J4LQ9qjop6joBngYWqeojEYfeAsYDD9p/33RL1iAo21PB58ut0cW0JSWs274HgF7tm3HJ6AKO6ZXLsIJWZGVYPcaT+rVnxB8/dK38Hw3qyF1vFTJh9loGd0nOcW38EQXc9Va4JvC8GHms2ryTxRvKuOP01IrEE5nr4/zhXZIe9TUKqVuyG2zZWc6lz33D/LXbePCcgfz08PBbKy4+oisPvLeYs+KERPFjSYgj5SEiXYGeqvqBiDQBMuyJ7WiexGrg66qxRwOTovaNBn4GzBeRufa+32Epjf+KyOXAauDHTuQOGlVl8YYyPllSwidLNjJr1VYqq5VmWRmM7tGGXxzfk2N65dKploVzbuf1zmmcycn9O/D2vPXccXq/fUrKCS2aJO626SRUul8kOmqcaufuCEsU3USpyfVx43/n8enyTUmvUWioE+Vrtuxi/DMzKNq2m39dNDRUgS7rol2OFVOsVXbdo2A/4mAlrDxE5Eqs+YTWQHesuFb/Ao6Pcfp7qnpZnO/7d/Q+Vf2M2hVOrHICpa7ns313BZ8v38QnSzYybWkJxaV7AWvi+IqjDuHY3rkM7drK9XwIiS4cGjc0n7fmreOjRRs5NQk3TCcmO7/MAF646k4pLKZvxxw6t852/bu95vRBnXjgvcU889n3vi9wCzOL1pcy/pkZ7Kmo4t9XjGB4PSMGeOkiXnuZdRO2kcd1wOFY3k+o6jIRien1pKoXxfuyRM4JgmTbOVWlcF0p05aWMG1JCbNWb6WqWmneOIOje+ZyTK9cjumd6/ooIpp4PZIajuzRlvY5WUyYvTY55RGyUAlesGnHXr5ZtYUbjusZtChJ0SgjjYtHduXPU5eyfGMZPdrVP3VwqvPVis1c+cJMmjbK4LWfj6J3B3NPksWJ8tirquU1w1gRySCOghORHwOTVbVMRG4HhgD31azlCCNOJkXL9lTy9rx1fLKkhOnLSigps0YXA/JyuOaY7hzbO5fDOrf0NZxFWoJmhvQ0YezgPJ7+9Hs27dhL2wYQYtttC8uHi4pRJWVcdGNxwYgu/O3j5Tz7+UruP3tg0OIEyuQF67nhP3Pp3KoJL1w+okHnXvejc+dEeUwTkd8BTUTkROBa4O0419yhqq+JyJHAycDDwD+BEUlJGzImF25gcuEGWmZnclTPXI7tlcvRvXLJbR5cQ+xk5HTukHwen7aCN+euc5yLOowjj0QVZ6JMKSwmr2UT+rkcOt5P2jTL4uzD8pgwey03ndyblgmOTBsa//5qFXe8uYDDOrfkmfHDaZVCnnPJ0DjT+w6rkxJuBUqA+VjZBCcBt8e5psr+exrwT1V9E2gwT+2G43sy8dpRzLr9RP52/mDGDc0PVHEApKcn3oD2bN+cQfktPI+0G7YkNkBco/DOvZV8unwTJ4cwd4dTLj2ywNNcH2FGVXl06lJuf2MBY3q34+UrRjYoxdG2Wezf8uhPDvO87ISUh4ikAy+o6pOq+mNVPdf+P16rUCQijwPnAZNEJCvRMoPCiYnpxhN7MaRLq1D5hac7bOjOGZzHwvWlLFrvLCd5CNWBq0xfWkJ5SHN3OKVPhxxG9/Au10dYqapWfvf6Av7fh8s4d2g+j/9saL0WTNaGn32LjxaXAFBpJ3U749DYDjLtmnvv4ZhQS6mqVUCuiDhV2ecB7wOnqOo2LE+tmxx+h68cmp/a+Qqcmm7OPCyPzHTxdPSRiopmysJiWmVnMqyrZwGcfcWrXB9hZU9FFde+NItXZqzm2mO786dzB7nu2RgEb8+zVpRv2Rl8nCsnd3Ml8LmI3CEiN9Zsca5pC8wE9opIFyATWJycqP4gIpycwr1Npz2r1k0bMaZ3O96Yu45KB71SJ6Yov15at3qAFVXVfLiomOP7tg9t7g6njOndjgKXc32Ele27K7j46Rm8X1jMnaf34+ZT+nhqenzn2+BChAThJlyDkzdjHfCOfU3ziK0u3rWveRcrlPoK4D3nYhoS5bg+zmNGjhuaz6Yde5m+rCTha5yMJob61Ht36zWa8f0WSvdUptzCwLpISxMuHd3N1VwfYWTD9j2c968vmbNmK389fzCXOXQESYY9FcGZAoOcjkvY20pV/+D0y1V1P99AERmCNdkeatz22vGTZOZfxvRuR6vsTCbMLuK4Pu43mMs37nD9O2PhKK96HcfeL9xA48w0jurZsBbWnTs0n4enLOHZz1cyJMmwNGFm+cYdjH9mBtt2lfPsJYdzpMsx4cJEvLruRty9eCQ88rAz/H0UvTkpzF7fMdyxlD6TwrojqUWOjTLSOOuwPKYuLGb7rorELnJQN+cXbXcuVFLU/8GpKlMKizm6Z64nk6tB0jQrg5/auT7qm88lbMxZvZUf/+sL9lZW8erVRzRoxQE/1PQgfXWcmK1+izXZfRNwBzAXaz6jViLnRkTktyLyMpa7r8EjkrXtjhuST3llNe/MD85+GwbmF21nQ+keTk6RWEdOufgI93J9hIWPl2zkgie/pnnjTCZcM4oBeant9OIGfnjHJ6w8VHVWxPa5qt5I/MV+kXMjWVhzH2clLa0hLsma3Abk5dCrfbOEva78GBYHwZTCYtLTJKm5o1Sgc+tsTu7fgVdmrGZXeWXQ4tSbCbPWcsXzMzkktykTrhlF1zYNP3EVhMM64iQwYmT0sDRgKFBn9yyZeZIwUF6Zur7wya4sFRHGDcnngfcWs6JkR+B5m5PBjRdqysINHF7QukEtJIvmsiO78d6CDUycXcRFI73LKe8lqsrj01fw4HuLGd2jDf+6aCjNE8381yDYFyYqMAmctDSzsMxUs4Avgd8Al8c6UUT+Yv99W0Teit7qK7TXJDLpPO+uk3yQxDltmia/wn3s4DzSBCbOjp+iNoyLxp28RrHk/37TTpYW73B1YWAYE0gN69qKgXktePbz76muDuGDjEN1tXLvO4t48L3FnD6oI89cMvwgUxwJTJiHLLZVX1XdE7nDXjEeixftvw8nJVXAJLIuwUk+i1ShfU5jjuyZy+tzirjxxF6upY1tkpkaE89TF1oL6E500UU3K4SZ+ESEy44s4NevzmP6shKO7Z1aJrpfvTqXt+at45JRBdx5ej/P0xuHkXi/uHlj73OYO6nZX8TY92WsE1V1lv13Ws0GfAtstf8PNakcy6i+oo8bkkfRtt18tWJznec56djcemqf+gmVIPV9bu8XFtO/Uw75rdzL3ZGoRC9f4W+s0NMGdiK3eRbPfL7S13Ld4K1567j5lN7cdcbBqTgSwY8UtXGVh4h0EJGhWNF0B4vIEHs7FqjzLRORT0Qkx54vmQc8KyKP1HVNGNhYuif+SQ2Uk/t3oHlWBv+bXffEuZNhsV+6uD7FbCzbw+zVWzmpXzBeVn5Hu63J9TF9aQnLimMlAw0vD507iGuP7ZHSnbz6si81RoAyJDLyqAmlng88AvzZ3m7EShFbFy1UtRQ4B3hWVYcCJyQvrj+s3Zq6PvD1rUyNM9M5bVBHJi/YwM69qe+NkygfLtroSe6OMDdwF4zoQqOMNJ79YmXQojjivGGdgxYhcMJQq+IqD1V9XlXHAJeo6piI7UxVnRjn8gwR6YgVIPEdNwQ2eM+4ofnsKq+qM4heGF11na0w31/+KYUb6NI6mz4BZZYLYtFeTa6PiXFGmYbwUVPXg3wLnazzmCAip4nIzSJyZ80W57J7sKLqLlfVb0TkEGBZfQQ21I0bPd1hXVvRtU02E1xqVPzqJSUbJG7H3ko+X76Zk/q1D2yksH57MKPdmlwfhtQiyICINTgJT/Iv4CfAL7Dagx8DdTqJq+prqjpIVa+1P69Q1XH1kDcUFLRxb0I1jIgI5wzO58sVmymqpUccRlfdZJm2pITyqmpOaqCryuuiJteHITUJUoU48ecapaqDRORbVf2DiPwZiGm2EpG/UceISlVvcCinr8TrfIY5qJxblemcIXk8+sFSXp+9luuP61m/L/OpN59sMVMWbqB100a+Rf+NSYBzI5eN7sbny+v2rjOEizBMpTlx1a1xQdolIp2ACqC2eMc1iwlr21KaME+CukXn1tkc3q01E2YXxczd0VAGHuWV1Xy0eCMn9G3nSUbIRNeMBFmjxqTYOg9DBKkQkh14W0RaAn8CZmO1H0/GOlFVn4/8LCJNVXVn0lL6TDzdcBDoDgDOHZLPzRO+ZfbqbQf2ylPcblUj/lcrNlO2p9IzF93bT+vLgqLtzFwV3hwaZq2EIRkSzWGeBnyoqttUdQLWXEcfVa1zwlxEjhCRhcAi+/OhIvJYfYX2mniTUWF+1dxUbKcO7EDjzDTXJs69JpnfPmXhBrIbpXsWwjsjPY22zeKHjDlYOiQGd9hXXwLswyWaw7waa21Hzee9qppIkoa/YK0T2WxfNw84Ogk5Q8XB8qI3b5zJKf078M68deypqNrvmJM6G9bbVV2tTF1YzDG9cmnsYQiVtPBFKDGkOPs6uCmSz2OKiIwThwZ/VV0Ttasq5okhIq7ZKrTNofvzMeOG5lO6p5IPFhW7+r1e4PS3f1u0neLSva4vDIymuHRv3HPCXKcM4UP26Y7UiKp7I/AaUC4ipSJSJiKlca5ZIyKjABWRRiLyW2wTVpiJ9zgOlpEHwKjubemQ0/iAPB8pPuUBWAsD09OE43p7qzx27Im/Uv9gqlOG+hOrvnx2yxhfZXCySLC5qqapaqaq5tifc+Jc9nPgOiAPWAscBlybvLj+EK9dPJhe9PQ04ewheUxftomNZcnF/AprbKspC4sZeUhrWmR7GyE5t3n8OQ8zZ21wwpINVjyyyHrjpek1Fk4WCYqIXCQid9ifO4vI4XEu+zNwvaq2V9V2WAsMUzJM+/4cXG/6uCH5VFUrb839IUVtLPfdoHGipFaU7GD5xh2+BEJMJDy2MVsZnFBqj2YjM4eWJTDCdRMnZqvHgCOAC+zPO4B/xLlmkKru81G0/x9c1wUi8oyIbBSRBRH7DhORr0RkrojMTEBpecrBNPIA6NGuGYd2bsn/IkxXzibMw3fD3i+05nDczN1RG6lQXw7t3DJoEQwO6N3eisEWOfIo3V3hqwxOlMcIVb0Oe7GgrQjixZFOE5F9CwTs0OzxumHPAadE7XsI+IOqHgbcaX/2jLhzHl4WHlLGDclj8YYyCtcl4mQXfr5csZmBeS3o1LKJ52UlpDwDrlRvXjc6WAEMjmhnm0IjnUT87qQ4UR4VIpKO3ekUkVwgXkS1PwNfiMi9InIPVkKpOht+VZ0ObIneDdTMr7QA1uEh8bx2UqEn6TZnDOpEZrowYZaVojaM+TyccpIPo45ECcMtGnlI66BFMCRIjbkq0mzl9wjfifL4K/A60F5E7gc+A/5Y1wWq+gIwDigGSoBzVPXFuq6phV8BfxKRNVhzJrcl8R0JE3/kEYZX3V9aNW3E8X3a8+bcIiqqwhmF1elzOXnAwRcIsS5uOcWfjI+G+lOzdiiBjNmekXB4ElV9SURmAcfbu8aqaly3W1VdCCxMUr4argF+bYeFPw94mhhJpUTkKuAqgC5duiRfWpw26GD1jBk3NJ/JhRuYtqTE0ZzHkT28Wb0djdMRTs92zbwRJAkOhnhpBveoicOWKmYrsNLOptvXeW8s/oHx/BDB9zUg5oS5qj6hqsNUdVhubq5nwhysL/qxvXNp07SR43AlnVuHL4R9z3bNQvUcwyOJIcy0bWZNM2fYQw8vgnkmihNX3TuB54HWQFusfOS3eyVYFOuAY+z/j8MklAqEzPQ0zjysEx8u2si2XeVBi1MvhhX4F349EY+uEOkxQwKcf3gwqXCr7SF/jc5o09RSJpnpEuqRx/nAcFW9W1XvAkYCF7otkIi8AnwJ9BaRtSJyOXAl8GcRmYc1z3KV2+XuJ0NcGb0sPdyMG5JPeVU173y7PmhRDsDJJH6GjwGnOrZoHPecEC6bMdTBiG7BJNCqsrVHzUR5owyrHp8yoKPvc7FOQrKvBBrzQ16PLOA7twVS1fNrOTTU7bKS5eIjCoIWITD6d8qhT4fmLLZXuIaJ7zclFvU/u1E640cVeCuMQz5dVsK4ofmBytCnQ7yAEYagqdb9lUckYR557AUKReQ5EXkWWADsEJG/ishfvREvGOLZwru1beqTJOFDRBg3JNhGrjZqemXx+PLW4+nh42R5IlJVJCi7lzRp5G94C4Nzakaokha9X0OtPF4Hfgd8DHwC/B54jwaSHTCSup5Bh5z4JoiGzlmHdQqlx1n3dokpdQ1hHkS/PNLi8fT4YUGLkBIc1zeY7IsaNfKo6egq/i8hcOKq+3z8sxo+r1w1MmgRAqddTmOO7pXLJ0tKghZlPzKDdHqvg0TmM5plObEge8fxfcOzcDLM5DTOZGBeC+YX+RtxIXrCPMg+nBNvq9NFZI6IbHEQkt3gEjUTY2HhF8f1DFqEA0j0RQrj5HQsG/bByJjetbvYnzcs/6BfyPjC5YdzzuA8mkRH0NVwz3n8BWu9RRsHIdkNLnH3Gf2DFmE/DshpHgLCtG7DKSksuqv8/rS+tR67aGRXrjm2u4/ShI/hBa155CeH7avrQdYbJ8pjDbBAwxiL22XqeiBdQ7jgzWCR8MjDUymSw+gOQ33xex7SiaH1ZmCSiEzD8rwCQFUfcV2qgKnLhJAWxpniEOPn7Uq0F+Z3/yeRCXoz8ohP2LqtG0qTS47mJjWT5GpPmfuJE+VxP1YOj8bED8VuMABw5+n9fCsrlQNWprLJzS9CpjsoKYufm95raqqNBjDn4UR5tFbVkzyTxNAgadMsfgpWv/G9EUqgQKM6DPUhiFGZkzmPD0TkoFYe9589IGgRUg5fe0Mp3AKbkUfq0at98FGZpZb//cCJ8rgOmCwiew5WV92zB+cFLQI/HR5MQLZkSfexUUx8zsNbOZLBTKXFpzpkD65pSNbm1OB3B8TJIsHmXgqSCqSyTd1PWjTJZLudT7lFdqZv5SbubRWuRshgqC+KhnfkIRYXicgd9ufOIhIzr0aqY0wI9ePS0QX7/s/K8C9eUsLPzWfdkUhxpsoZkiFywtxvnJitHgOOAC6wP+8A/uG6RCHAvMf146fDu3DGoZ0YNySfIV1a+lZuKj+3MHVYXrgsnH3CkFmtQhIVILhMgk6MdiNUdYiIzAFQ1a0i0iBddmt7CKGoKylAhxaN+dv5g4MWo1b8boMaR4eSiEGYqtbRvbzLwlkfMszEUK0o/iszJ8qjQkTSsd89EckFqj2RymBIgrAq90RGX2EaeQA8e8lwOrf2M9N0fNo0a5B91XoRZLVxojz+ihWWvZ2I3A+cC9zhiVSGWgnb0D1MJOrQ4Pc9TEQxhK1TPaZPMCHH66JRyKImh+mRhXrOQ1VfwgpR8gCwHhirqv/1SrAgCWMDndvcWmzXLfeHnBXv3nBkUOIYkiSvZezevPHki0+7kOXSCcNgMUgREh55iMiLqvozYHGMfQ2KPRVVMfcHWVmKtu4CYNfeyn37+ndqEZQ4oSRxZ6vgegfNG8d+5cLQEBlSmXBnEtwvJrg9/xGavOJu0qVN+CLn7iy3FNr67cEHYzMkT22TmkZ31GDuhBP2ZRJUSLdtn36Z9+KWIiK3iUgZMMheWV5qf94IvOm5hAHQu0Ps9ZBBmhb6dbRSp3QNoWJLNYI0S9ZWt0ybaUiG/dosenIAABKxSURBVMOTWJ9aNfVnYW5c5aGqD9iry/9kJ4GqSQTVRlVvqzlPRMKVrageXDemB+1zsvjytuOCFmUfY/q047lLh3PNsT2CFiW0pILp549nD4y538x5pB5hemaK/wsGnYQnuS3OKS8CQ+onTjjIaZzJ1787IWgxDuDY3uHzgAkTCXtbeSxHXTRpFHvNR9i8rYIipXLNheCZxeow+XUH3TSOheBWeksq9GwNqUnY1nkERSrdhrCJGtrYVgmQQl2G1MbMe8Qm0YYnO4EV336TSo2mITx0aGG5Lw/olLNvX+jMVobw9DTeuv5Itu4sD1qM0JHo82nVNHwrlcNStwypRf9OLXjnF0fSt2MOm3f6m9kwIeUh1pg6X1XX1HGaac18okWTTFo08S/UucF7jNmqhtS5D2F5ZAPyotd7+TP0SMhspdYs1htxzhnpikQhxrzg4SaVn08Ki+4yqWP9DpO3Ffwgj19mKydzHl+JyHDPJDEY6km4XmVnpLLshnCwz1XXp/KczHmMAa4WkVXATqz6rqo6yBPJQoh5wQ1ekcqjJjdo26wRm3akluU7bI/Mb3GcKI9TPZPCYHCBsL3MTkhh0V2hRZNMozxcwq+1MomEJ6nxASurZXMVEXlGRDaKyIKo/b8QkSUiUigiD7ldriH1SeXeewqLbggJftf/ROY8Xrb/zgJm2n9nRXx2m+eAUyJ3iMgY4CxgkKr2Bx72oNy4mBfc4BVhm3z1m7MOywOgTdOsgCVJfUIz56Gqp9t/u3kvDqjqdBEpiNp9DfCgqu61z9nohyyGusltnkVJmb++5YmSmS5UVKWQ587BrTv4xXE9uOKobmQ3Sp2lZ2FT+KFeYS4irUTkcBE5umbzSrAoegFHicjXIjKtNq8vEblKRGaKyMySkhLXhUhls4gXpIf4flxzTPegRXBEiG+lL4hISikOCN8zC21gRBG5AvglkA/MBUYCXwJ+hJ7NAFrZZQ4H/isih2jUzJCqPgE8ATBs2LDU6XbWg+aNMyjbUxn/REOoCVsv1pB6/LDOIyQT5hH8EqvhXqWqY4DBgPvd+9isBSaqxQygGmjrU9mhJsgm57IjCwIsvW5SreeQFq703IYUJoxRdfeo6h4AEclS1cVAb2/EOoA3sEc4ItILaARs8qnsUPPpzcHlHLnq6O77cquHlRtP7LXf55xa0sAGjRl5GOpNiNPQrhWRllgN+VQReRNY57ZAIvIKljmst4isFZHLgWeAQ2z33f8A46NNVgcrLbKDjXF15+n9ALjD/hsGbji+Z63HqqrDWW2ya8nzYQgvgzu3BKB9Tsg6UGGb81DVs+1/7xaRj4EWwGS3BVLV82s5dJHbZRnqzxmHduKMQzsBcO87CwOWBlY+eBoAf56yJGBJEqN9ThbFpXvJ9CnvtME9OrVsAsCxvcKRpM3vCfykxvCqOs1tQQwGN6ltXFoV0ID10M4t6dL6wDwsNeKEzXPHkDgashm20KzzMBhSmeg2OSir1ZvXjY65P1zNjsEJYVP4YY5tZTCkDLX1BsM2VWZGHqlPWKpUdqMMWmZncvtp/sw/GuVhaNBEN8phmi/Pa9mEvZVVgPG2SkX2rasIWI4a0tOEuXee5Ft5ZpYuDqcO6BC0CAYXqQ5BN/Gpi4cB8PcLBoem12pIgoNc3xvlEYd/XjQ0aBEMLhKGxvqEfu1Z+eBpDO7Sat8+Y7ZKPWoeWRjqVBAY5WFokKTKC/3oTw5jaNdWtMpuFLQoBofUxLoLm7eVX5g5jwZEzRoHA+wqt+cSQt6lP7pXLkf3yg1ajNDTummIlevBqTvMyCMRCtoc6J9vCDdZmVbV3lNRFbAkBjcIm5ccHPRTHkZ5JMInN40xvfoUo9p2q2qWlcHKB0+jUYap6qlMmLzkogmxaJ5i3ihDg+TaY3tw+qCOXDCiCwBTf22lnvngxmOCFMvQgPghf8bBqT7MnIehQdKqaSP+fsGQfZ+7tmlqRo8GV9mnPIIVIzDMyMNgMISeMKzPieaH5EsBCxIQRnkYDIbwE8IGOuSOfJ5jlIfBYAg9IdQd+wizbF5ilIfBNZqahEYGw0GDmTA3uMab1x/J58tNdmCD+4TZoynMsnmJUR4G1+jRrhk92jULWgxDAySMzXOTTGuk3Szr4GxGD85f3cB49CeHMqBTi6DFMBg8I4yd+xP6tufWU/tw0ciuQYsSCEZ5NADOHpwftAgGg6eEMbZVWprw82O6By1GYJgJc4PBEHrGDckLWgRDFEZ5GAyG0JOVaTz5woZRHgaDIVRMuuGooEUwJIBRHgaDIVT065RDXssm++0L45zHwY6ZMDcYDKEjMvTHX88fzOkDOwYnjCEmRnkYDIZQc+ahnYIWwRADY7YyGAyhI4zrOgz7Y5SHwWAwGBxjlIfBYDAYHGOUh8FgMBgcEzrlISLPiMhGEVkQ49hvRURFpG0QshkMBoPBInTKA3gOOCV6p4h0Bk4EVvstkMFg8Je+HZsD0CgjjE2UAUKoPFR1OrAlxqFHgZsJZ3Rmg8HgImMHW7GsTujbLmBJDLUROuURCxE5EyhS1XlBy2IwGLynoE1TAIZ2bR2wJIbaCP0iQRHJBn4PnJTAuVcBVwF06dLFY8kMBoNXDMhrwfSbxtC5dZP4JxsCIRVGHt2BbsA8EVkJ5AOzRaRD9Imq+oSqDlPVYbm5uT6LaTAY3KRLm2wkMk6JIVSEfuShqvOBfYZPW4EMU1WTLNtgMBgCInQjDxF5BfgS6C0ia0Xk8qBlMhgMBsP+hG7koarnxzle4JMoBoPBYKiF0I08DAaDwRB+jPIwGAwGg2OM8jAYDAaDY4zyMBgMBoNjRBto1hURKQOWBC1HFG2BsLkYG5kSw8iUGGGTKWzyQPhl6qqqcRfKhc7bykWWqOqwoIWIRERmGpniY2RKDCNTfMImDzQcmYzZymAwGAyOMcrDYDAYDI5pyMrjiaAFiIGRKTGMTIlhZIpP2OSBBiJTg50wNxgMBoN3NOSRh8FgMBg8IqWVh4QwXnMYZQojYbxPYZTJYAgrKa08CKercWbQAsRCRNKDliGKMNa9UD07EWlr/w3NsxORgqBliEZEholIqPLVisgJIjI0aDkiEZEWEf/Xu6MUxhc4LiIyUkReAu4RkZ5heLlE5AgReQ14WET6hUimewBUtSpoeQBE5HAR+TfwgIgMFJHA66Dd+LwG/ElEjgzy2YlFtp2a4E0Ix7MTkSEi8gHWOxd43QYQkf4i8gVwF9AyaHkARGSwiLwHvA70CFoeABEZISJvAk+JyGUikqUuTHYH/uI6RUQGAH8D3gGKsdLOXmwfC8TsYPd6/g5Mwlql+UvgsoBlGg88D9wuIufZ+wIbqYlImojcBTwFvIc1arwOODRAmUREHgT+xQ/16XogsBzGarHL/thWRK4B6/4FIY99j34PvAL8R1UvrlFmITDz/RJ4XVXPUNWlQcokIuki8gTwJPA48DLQ1z4WWDsrIoOAfwD/A14DjsMlpZZyygMYDSxW1VewHtQu4EIRKVBVDajyDACWquqzwJ+BicBZItIrQJlWY1WUU2yZUNXKoF4uVa0GVgGXqOpLwP1AVyCwXqzd+/oEOFFVnweeBRQoCUomu7HuiKXILgeuEZGWqlodRCNk36NM4DNVfcqWcbCIZLjRe00Gu6FujfWs/m7vO1tE8oEm9mdf67mtUCcDR6nqG8AEYIyINLbrflAMBZar6ovAVKAxVtsA1O8+hV55iMj5IvIHETnT3vU1kC8iPVR1J1ANbAeuhH2V3WuZjhGRERG75gHDROQQW6ZvgJnA1QHK9AmwQVWnAKtE5F57v2+jjxgy/QeYaw+bNwNlQEe/5Iklk6pOVtWtInIU8BVQANwnIif6LY+IpNkjj/W2HCuBacCtItLdr0YoxnP7E5AnIg+LyDfAvcDzInKuH/JEy2Q31LuAo4HjbDPo1cB9wF/sc3x/51R1oqruthvkamApkO21HHXJBLwLnC0i9wPzgXzgryJyiy1z8vdJVUO5AQL8HJgDXIr1IMYD7bEq76fAG8DbwE+B/wMaeyxTc6xRxRbgGaBVxLH7gL/Y/6cBRwL/BDoGIZMtQ806nv5YCra9T88uWqbWNc804pxM4AugV0Ay7btPEfdojP3/pVijkD4B1aVewCP2/2cCpcBsIAvIDEimC4EPgKPtz1djmSA9fX5xZLoZS8H+zP6cZ9epUwOqSxLxzuUDK+D/t3fuIVZVURz+lopvUyxF7EHhu8ZHKJKRiJpB0cMgMzLNMAMt7Z/SCISyQiPCIvKPglAIgkyEkoqQRLGHgaGpKZVED6cHatmYOEaz+mPtGW8SOsc5954z9vvgMOeee849392z7117r7PvPgxsfq7Achqevh/npMeTiO/NCW05Z2l7Hh7vcgKw0iMdtBCYBoxx92VEYFnr7rcA3wCj3P1ElbVOAh8C9wD1wIyK59YDw81sqkcL8TBRmY8W4eTuTe7uZtbR3fcS+c6VAGZ2Y42d7khOla2cEcAv7v6VmfUys/E1dmopp/R3r7tvTvtuIS7AHqu1T6IeGGpmbxOt/i3Ad+7e6O5/FeHkkWq80923pk2bgH5Ut4zO6ASsJtJU/ZLjQWAb0eqvuZMnUg/yRyJL8l91v2ZO6dz7iQDyQ9q0A/gVaGzLCUsVPMxsTup29U2b9hHd5U7uvonodk02s0vSh31D2m8K8Gk18pwVTn3cvZFobW0iekLjzGxY2nUXkZZ5wcwGA1OJlkjnApyGpv2MyAvj7vcD95rZb8DovPPnGZya02Z9geNmNpdoLY7M+/+XsZwquYH4bDQU4UO0IuuJluvY1EC61Kow9DNLGbn7kYpDpxF1K/fg0Vondz8GLCLq9RiLwQXXE72RQpxS4GhK9fxr4M+8XbI6JT4Ankh1/S6ip324TeevfkA8i0C8mQHE6IQm4ADQA1gA3AKMBNa4+36LMeargCfdfWdqrT6bjnvA3Q9U2elhdz+U9hlCpNEa3f2pimOXAMPSMt/d9xXgdMLdn6447jKi3C4EHnT3PUU6pe0rgKXAGiLd90WRTmbWBZhI1KeDwJLUYqulT0tdMrPe7n604nX+9biGTpVl1JyOfZG46Lo0jzJqi1PaPpMYtXcV8HjqaRfmVBFAVgHHUqYkF9pQn7oR81f1JwapLHb3L9skU8083NkWoGP6OxR4Pa13Irqja4m8+GvAbKB3en4NsDytXwRMqpHTS8D60/a9PbkOTv/A5vx555I4dSVa0BcA40vi1D1tuxaYWRKnLqmujQRuLoFPN6BL2t6hJGXUlehJDwJuLYlTD9I1IHK+ptDGcupRIqchFZ+5TsCAvHwKGfefunTLgY5m9i7x5fY3tAwnfQj4CbiSiLDTiQtQK4houz3te4jIB9fCaTFQb2aT3H1L2r7BzEYQQ/R6ApOBfe5+skROUzxaGJ+VxcnMJrv7x3n45OVEXCzfTaRGS+FD1KVc8vc516W8evh5llMuKZTz0Ok9Tn3m9gE/5+FEOklNF+JK/y5iJNJ8YCvxW4TvqWgdEz8gez+tjyKGnG0nfrnZoyCnBcDmiscziJzmq0B/OcmpbD5yklPeTi3nqMaLnqUwJpKG1qXHq9MbnwvsSNs6EHm9dcDlaVsf4OISOL0JXFFx3EQ5yamsPnKSU7WWqr3wGQqjO5Fjbs7fzQJWpPWdwKK0Pg54Q05yak9OZfORk5yqtRQx3cFxj/HqzZO9TePUdBD3ASPMbCMxl87ncpJTe3Iqm4+c5FRNuUIWYrhYB+KCzuC0bTCRnrqOKqWo5CSn/6OPnOSU91LkjwSbiOGRh4BRKXouA5rcfZvHr0XlJKf26lQ2HznJKV9qHa1Oi6bXpELZBswr0kVOcjrffeQkpzyXQn9hbjGF8mxiErg2zbOSF3JqHXJqfz4gp9Yip1b4FBk8hBBCtE9KNTGiEEKI9oGChxBCiMwoeAghhMiMgocQQojMKHgIIYTIjIKHEDlhZn3MbGFaH2hmbxXtJES10FBdIXIi3elyo7vXFawiRNUp5GZQQpynrAQGmdlO4v7VI9y9zuI+7dOJ+YnqgOeJe9vPBhqBm9z9iJkNAl4G+gHHidsY53KbVyHyRmkrIfLjMeCAu48BHj3tuTrgbmA88Axw3N2vBj4B5qR9XiGm2B4LPELcu0GIUqKehxC1YbO7NwANZnYUeCdt301MdNeTuK/7OjNrPqZL7TWFaB0KHkLUhsq5iJoqHjcRn8MOwO+p1yJE6VHaSoj8aAB6ncuB7v4H8K2ZzQCwYHSeckLkiYKHEDnh7oeBj8xsD/DcObzELGCeme0C9gK35eknRJ5oqK4QQojMqOchhBAiMwoeQgghMqPgIYQQIjMKHkIIITKj4CGEECIzCh5CCCEyo+AhhBAiMwoeQgghMvMPqkxPtJKrjL4AAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# seasonal average for June July August\n",
"zarr_load_faimms.sel(TIME=zarr_load_faimms['TIME.season']=='JJA').AIRT.plot()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Creating a climatology dataset"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7fb9eb645a20>]"
]
},
"execution_count": 9,
"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": [
"airt_clim = zarr_load_faimms.groupby('TIME.month').mean(dim='TIME').AIRT\n",
"airt_clim.plot()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## plot anomalies\n",
"The first plot is an anomalie plot of the last decade\n",
"The second plot is an anomalie plot for the year 2017 only"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"airt_anomalie = zarr_load_faimms.groupby('TIME.month') - airt_clim"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7fb9eb627668>]"
]
},
"execution_count": 11,
"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": [
"airt_anomalie.AIRT.plot()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7fbae8c1ce10>]"
]
},
"execution_count": 12,
"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": [
"airt_anomalie.sel(TIME='2017').AIRT.plot()"
]
}
],
"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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