def __init__(self):
WPSProcess.__init__(
self,
identifier="weatherregimes_projection",
title="Weather Regimes -- Projection of Weather Regimes",
version="0.9",
metadata=[
{
"title": "LSCE",
"href": "http://www.lsce.ipsl.fr/en/index.php"
},
{
"title": "Documentation",
"href": "http://flyingpigeon.readthedocs.io/en/latest/"
},
],
abstract=
"Weather Regimes detection based on trained reference statistics",
statusSupported=True,
storeSupported=True)
self.resource = self.addComplexInput(
identifier="resource",
title="Resource",
abstract="NetCDF File",
minOccurs=1,
maxOccurs=1000,
maxmegabites=5000,
formats=[{
"mimeType": "application/x-netcdf"
}],
)
self.Rdat = self.addLiteralInput(
identifier="Rdat",
title="R - workspace",
abstract=
"R workspace as output from weather regime reference process",
type=type(''),
minOccurs=1,
maxOccurs=1,
# default=' http://api.gbif.org/v1/occurrence/download/request/0013848-160118175350007.zip'
# maxmegabites=50,
# formats=[{"mimeType":"application/zip"}],
)
self.dat = self.addLiteralInput(
identifier="dat",
title="R - datafile",
abstract=
"R datafile as output from weather regime reference process",
type=type(''),
minOccurs=1,
maxOccurs=1,
# default=' http://api.gbif.org/v1/occurrence/download/request/0013848-160118175350007.zip'
# maxmegabites=50,
# formats=[{"mimeType":"application/zip"}],
)
self.netCDF = self.addLiteralInput(
identifier="netCDF",
title="netCDF reference",
abstract=
"netCDF file as output from weather regime reference process",
type=type(''),
minOccurs=0,
maxOccurs=1,
# default=' http://api.gbif.org/v1/occurrence/download/request/0013848-160118175350007.zip'
# maxmegabites=50,
# formats=[{"mimeType":"application/zip"}],
)
self.season = self.addLiteralInput(
identifier="season",
title="Time region",
abstract=
"Select the months to define the time region (all == whole year will be analysed)",
default="DJF",
type=type(''),
minOccurs=1,
maxOccurs=1,
allowedValues=_TIMEREGIONS_.keys())
self.period = self.addLiteralInput(
identifier="period",
title="Period for weather regime calculation",
abstract="Period for analysing the dataset",
default="19700101-20101231",
type=type(''),
minOccurs=1,
maxOccurs=1,
)
self.anualcycle = self.addLiteralInput(
identifier="anualcycle",
title="Period for annual cycle calculation",
abstract="Period for annual cycle calculation",
default="19700101-19991231",
type=type(''),
minOccurs=1,
maxOccurs=1,
)
####################
# define the outputs
####################
# self.Routput_graphic = self.addComplexOutput(
# identifier="Routput_graphic",
# title="Graphics and Tables",
# abstract="Weather classification pressure map and frequency table",
# formats=[{"mimeType":"image/pdf"}],
# asReference=True,
# )
self.output_pca = self.addComplexOutput(
identifier="output_pca",
title="PCA",
abstract="Principal components",
formats=[{
"mimeType": "text/plain"
}],
asReference=True,
)
self.output_classification = self.addComplexOutput(
identifier="output_classification",
title="classification",
abstract="Weather regime classification",
formats=[{
"mimeType": "application/octet-stream"
}],
asReference=True,
)
self.output_frequency = self.addComplexOutput(
identifier="output_frequency",
title="Frequency",
abstract="Weather regime frequency values per year",
formats=[{
"mimeType": "text/plain"
}],
asReference=True,
)
self.output_netcdf = self.addComplexOutput(
identifier="output_netcdf",
title="netCDF file",
abstract=
"Prepared netCDF file as input for weather regime calculation",
formats=[{
"mimeType": "application/x-netcdf"
}],
asReference=True,
)
self.output_log = self.addComplexOutput(
identifier="output_log",
title="Logging information",
abstract="Collected logs during process run.",
formats=[{
"mimeType": "text/plain"
}],
asReference=True,
)
def __init__(self):
inputs = [
# self.BBox = self.addBBoxInput(
# identifier="BBox",
# title="Bounding Box",
# abstract="coordinates to define the region for weather classification ('EPSG:4326')",
# minOccurs=1,
# maxOccurs=1,
# crss=['EPSG:4326']
# )
# Literal Input Data
# ------------------
# self.BBox = self.addLiteralInput(
# identifier="BBox",
# title="Region",
# abstract="coordinates to define the region: (minlon,maxlon,minlat,maxlat)",
# default='-80,22.5,50,70', # cdo syntax: 'minlon,maxlon,minlat,maxlat' ;
# ocgis syntax (minlon,minlat,maxlon,maxlat)
# type=type(''),
# minOccurs=1,
# maxOccurs=1,
# )
LiteralInput(
"season",
"Time region",
abstract=
"Select the months to define the time region (all == whole year will be analysed)",
default="DJF",
data_type='string',
min_occurs=1,
max_occurs=1,
allowed_values=_TIMEREGIONS_.keys()),
LiteralInput(
'BBox',
'Bounding Box',
data_type='string',
abstract="Enter a bbox: min_lon, max_lon, min_lat, max_lat."
" min_lon=Western longitude,"
" max_lon=Eastern longitude,"
" min_lat=Southern or northern latitude,"
" max_lat=Northern or southern latitude."
" For example: -80,50,20,70",
min_occurs=1,
max_occurs=1,
default='-80,50,20,70',
),
LiteralInput(
"period",
"Period for weatherregime calculation",
abstract="Period for analysing the dataset",
default="19700101-20101231",
data_type='string',
min_occurs=1,
max_occurs=1,
),
LiteralInput(
"anualcycle",
"Period for anualcycle calculation",
abstract="Period for anual cycle calculation",
default="19700101-19991231",
data_type='string',
min_occurs=1,
max_occurs=1,
),
LiteralInput("reanalyses",
"Reanalyses Data",
abstract="Choose a reanalyses dataset for comparison",
default="NCEP_slp",
data_type='string',
min_occurs=1,
max_occurs=1,
allowed_values=_PRESSUREDATA_),
LiteralInput("method",
"Method of annual cycle calculation",
abstract="Method of annual cycle calculation",
default="ocgis",
data_type='string',
min_occurs=1,
max_occurs=1,
allowed_values=['ocgis', 'cdo']),
LiteralInput("sseas",
"Serial or multiprocessing for annual cycle",
abstract="Serial or multiprocessing for annual cycle",
default="multi",
data_type='string',
min_occurs=1,
max_occurs=1,
allowed_values=['serial', 'multi']),
LiteralInput("kappa",
"Nr of Weather regimes",
abstract="Set the number of clusters to be detected",
default='4',
data_type='integer',
min_occurs=1,
max_occurs=1,
allowed_values=range(2, 11)),
]
outputs = [
ComplexOutput(
"Routput_graphic",
"Weather Regime Pressure map",
abstract="Weather Classification",
supported_formats=[Format('image/pdf')],
as_reference=True,
),
ComplexOutput(
"output_pca",
"R - datafile",
abstract="Principal components (PCA)",
supported_formats=[Format('text/plain')],
as_reference=True,
),
ComplexOutput(
"output_classification",
"R - workspace",
abstract="Weather regime classification",
supported_formats=[Format("application/octet-stream")],
as_reference=True,
),
ComplexOutput(
'output_netcdf',
'Subsets for one dataset',
abstract=
"Prepared netCDF file as input for weatherregime calculation",
as_reference=True,
supported_formats=[Format('application/x-netcdf')]),
ComplexOutput('output_log',
'Logging information',
abstract="Collected logs during process run.",
as_reference=True,
supported_formats=[Format('text/plain')]),
]
super(WeatherregimesreanalyseProcess, self).__init__(
self._handler,
identifier="weatherregimes_reanalyse",
title="Weather Regimes (based on reanalyses data)",
abstract=
'k-mean cluster analyse of the pressure patterns. Clusters are equivalent to weather regimes',
version="0.10",
metadata=[
Metadata('LSCE', 'http://www.lsce.ipsl.fr/en/index.php'),
Metadata('Doc',
'http://flyingpigeon.readthedocs.io/en/latest/'),
],
inputs=inputs,
outputs=outputs,
status_supported=True,
store_supported=True,
)
def __init__(self):
WPSProcess.__init__(
self,
identifier="weatherregimes_reanalyse",
title="Weather Regimes -- Reanalyses data",
version="0.9",
metadata=[
{
"title": "LSCE",
"href": "http://www.lsce.ipsl.fr/en/index.php"
},
{
"title": "Documentation",
"href": "http://flyingpigeon.readthedocs.io/en/latest/"
},
],
abstract=
"Weather Regimes based on pressure patterns, fetching selected Realayses Datasets",
statusSupported=True,
storeSupported=True)
# Literal Input Data
# ------------------
self.BBox = self.addBBoxInput(
identifier="BBox",
title="Bounding Box",
abstract=
"coordinates to define the region for weather classification ('EPSG:4326')",
minOccurs=1,
maxOccurs=1,
crss=['EPSG:4326'])
# self.BBox = self.addLiteralInput(
# identifier="BBox",
# title="Region",
# abstract="coordinates to define the region: (minlon,maxlon,minlat,maxlat)",
# default='-80,22.5,50,70', # cdo syntax: 'minlon,maxlon,minlat,maxlat' ;\
# ocgis syntax (minlon,minlat,maxlon,maxlat)
# type=type(''),
# minOccurs=1,
# maxOccurs=1,
# )
self.season = self.addLiteralInput(
identifier="season",
title="Time region",
abstract=
"Select the months to define the time region (all == whole year will be analysed)",
default="DJF",
type=type(''),
minOccurs=1,
maxOccurs=1,
allowedValues=_TIMEREGIONS_.keys())
self.period = self.addLiteralInput(
identifier="period",
title="Period for weatherregime calculation",
abstract="Period for analysing the dataset",
default="19700101-20101231",
type=type(''),
minOccurs=1,
maxOccurs=1,
)
self.anualcycle = self.addLiteralInput(
identifier="anualcycle",
title="Period for anualcycle calculation",
abstract="Period for anual cycle calculation",
default="19700101-19991231",
type=type(''),
minOccurs=1,
maxOccurs=1,
)
self.reanalyses = self.addLiteralInput(
identifier="reanalyses",
title="Reanalyses Data",
abstract="Choose a reanalyses dataset for comparison",
default="NCEP_slp",
type=type(''),
minOccurs=1,
maxOccurs=1,
allowedValues=_PRESSUREDATA_)
self.kappa = self.addLiteralInput(
identifier="kappa",
title="Nr of Weather regimes",
abstract="Set the number of clusters to be detected",
default=4,
type=type(1),
minOccurs=1,
maxOccurs=1,
allowedValues=range(2, 11))
######################
# define the outputs
######################
self.Routput_graphic = self.addComplexOutput(
identifier="Routput_graphic",
title="Weather Regime Pressure map",
abstract="Weather Classification",
formats=[{
"mimeType": "image/pdf"
}],
asReference=True,
)
self.output_pca = self.addComplexOutput(
identifier="output_pca",
title="R - datafile",
abstract="Principal components (PCA)",
formats=[{
"mimeType": "text/plain"
}],
asReference=True,
)
self.output_classification = self.addComplexOutput(
identifier="output_classification",
title="R - workspace",
abstract="Weather regime classification",
formats=[{
"mimeType": "application/octet-stream"
}],
asReference=True,
)
self.output_netcdf = self.addComplexOutput(
identifier="output_netcdf",
title="netCDF reference",
abstract=
"Prepared netCDF file as input for weatherregime calculation",
formats=[{
"mimeType": "application/x-netcdf"
}],
asReference=True,
)
self.output_log = self.addComplexOutput(
identifier="output_log",
title="Logging information",
abstract="Collected logs during process run.",
formats=[{
"mimeType": "text/plain"
}],
asReference=True,
)
def __init__(self):
WPSProcess.__init__(
self,
identifier = "weatherregimes_model",
title = "Weather Regimes -- Climate model data",
version = "0.9",
metadata=[
{"title": "LSCE", "href": "http://www.lsce.ipsl.fr/en/index.php"},
{"title": "Documentation", "href": "http://flyingpigeon.readthedocs.io/en/latest/"},
],
abstract="Weather Regimes based on pressure patterns, fetching selected Realayses Datasets",
statusSupported=True,
storeSupported=True
)
self.resource = self.addComplexInput(
identifier="resource",
title="Resource",
abstract="NetCDF File",
minOccurs=1,
maxOccurs=1000,
maxmegabites=5000,
formats=[{"mimeType":"application/x-netcdf"}],
)
# Literal Input Data
# ------------------
self.BBox = self.addBBoxInput(
identifier="BBox",
title="Bounding Box",
abstract="coordinates to define the region for weather classification",
minOccurs=1,
maxOccurs=1,
crss=['EPSG:4326']
)
# self.BBox = self.addLiteralInput(
# identifier="BBox",
# title="Region",
# abstract="coordinates to define the region: (minlon,maxlon,minlat,maxlat)",
# default='-80,22.5,50,70', # cdo syntax: 'minlon,maxlon,minlat,maxlat' ; ocgis syntax (minlon,minlat,maxlon,maxlat)
# type=type(''),
# minOccurs=1,
# maxOccurs=1,
# )
self.season = self.addLiteralInput(
identifier="season",
title="Time region",
abstract="Select the months to define the time region (all == whole year will be analysed)",
default="DJF",
type=type(''),
minOccurs=1,
maxOccurs=1,
allowedValues= _TIMEREGIONS_.keys()
)
self.period = self.addLiteralInput(
identifier="period",
title="Period for weatherregime calculation",
abstract="Period for analysing the dataset",
default="19700101-20101231",
type=type(''),
minOccurs=1,
maxOccurs=1,
)
self.anualcycle = self.addLiteralInput(
identifier="anualcycle",
title="Period for anualcycle calculation",
abstract="Period for anual cycle calculation",
default="19700101-19991231",
type=type(''),
minOccurs=1,
maxOccurs=1,
)
self.kappa = self.addLiteralInput(
identifier="kappa",
title="Nr of Weather regimes",
abstract="Set the number of clusters to be detected",
default=4,
type=type(1),
minOccurs=1,
maxOccurs=1,
allowedValues=range(2,11)
)
######################
### define the outputs
######################
self.Routput_graphic = self.addComplexOutput(
identifier="Routput_graphic",
title="Weather Regime Pressure map",
abstract="Weather Classification",
formats=[{"mimeType":"image/pdf"}],
asReference=True,
)
self.output_pca = self.addComplexOutput(
identifier="output_pca",
title="R - datafile",
abstract="Principal components (PCA)",
formats=[{"mimeType":"text/plain"}],
asReference=True,
)
self.output_classification = self.addComplexOutput(
identifier="output_classification",
title="R - workspace",
abstract="Weather regime classification",
formats=[{"mimeType":"application/octet-stream"}],
asReference=True,
)
self.output_netcdf = self.addComplexOutput(
identifier="output_netcdf",
title="netCDF reference",
abstract="Prepared netCDF file as input for weatherregime calculation",
formats=[{"mimeType":"application/x-netcdf"}],
asReference=True,
)
def __init__(self):
WPSProcess.__init__(
self,
identifier = "weatherregimes_projection",
title = "Weather Regimes -- Projection of Weather Regimes",
version = "0.9",
metadata=[
{"title": "LSCE", "href": "http://www.lsce.ipsl.fr/en/index.php"},
{"title": "Documentation", "href": "http://flyingpigeon.readthedocs.io/en/latest/"},
],
abstract="Weather Regimes detection based on trained reference statistics",
statusSupported=True,
storeSupported=True
)
self.resource = self.addComplexInput(
identifier="resource",
title="Resource",
abstract="NetCDF File",
minOccurs=1,
maxOccurs=1000,
maxmegabites=5000,
formats=[{"mimeType":"application/x-netcdf"}],
)
self.Rdat = self.addLiteralInput(
identifier="Rdat",
title="R - workspace",
abstract="R workspace as output from weather regime reference process",
type=type(''),
minOccurs=1,
maxOccurs=1,
# default=' http://api.gbif.org/v1/occurrence/download/request/0013848-160118175350007.zip'
# maxmegabites=50,
# formats=[{"mimeType":"application/zip"}],
)
self.dat = self.addLiteralInput(
identifier="dat",
title="R - datafile",
abstract="R datafile as output from weather regime reference process",
type=type(''),
minOccurs=1,
maxOccurs=1,
# default=' http://api.gbif.org/v1/occurrence/download/request/0013848-160118175350007.zip'
# maxmegabites=50,
# formats=[{"mimeType":"application/zip"}],
)
self.netCDF = self.addLiteralInput(
identifier="netCDF",
title="netCDF reference",
abstract="netCDF file as output from weather regime reference process",
type=type(''),
minOccurs=0,
maxOccurs=1,
# default=' http://api.gbif.org/v1/occurrence/download/request/0013848-160118175350007.zip'
# maxmegabites=50,
# formats=[{"mimeType":"application/zip"}],
)
# Literal Input Data
# ------------------
# self.BBox = self.addBBoxInput(
# identifier="BBox",
# title="Bounding Box",
# abstract="coordinates to define the region for weather classification",
# minOccurs=1,
# maxOccurs=1,
# default=[-80,50,22.5,70],
# crss=['EPSG:4326']
# )
# self.BBox = self.addLiteralInput(
# identifier="BBox",
# title="Region",
# abstract="coordinates to define the region: (minlon,maxlon,minlat,maxlat)",
# default='-80,22.5,50,70', # cdo syntax: 'minlon,maxlon,minlat,maxlat' ; ocgis syntax (minlon,minlat,maxlon,maxlat)
# type=type(''),
# minOccurs=1,
# maxOccurs=1,
# )
self.season = self.addLiteralInput(
identifier="season",
title="Time region",
abstract="Select the months to define the time region (all == whole year will be analysed)",
default="DJF",
type=type(''),
minOccurs=1,
maxOccurs=1,
allowedValues= _TIMEREGIONS_.keys()
)
self.period = self.addLiteralInput(
identifier="period",
title="Period for weather regime calculation",
abstract="Period for analysing the dataset",
default="19700101-20101231",
type=type(''),
minOccurs=1,
maxOccurs=1,
)
self.anualcycle = self.addLiteralInput(
identifier="anualcycle",
title="Period for annual cycle calculation",
abstract="Period for annual cycle calculation",
default="19700101-19991231",
type=type(''),
minOccurs=1,
maxOccurs=1,
)
######################
### define the outputs
######################
# self.Routput_graphic = self.addComplexOutput(
# identifier="Routput_graphic",
# title="Graphics and Tables",
# abstract="Weather classification pressure map and frequency table",
# formats=[{"mimeType":"image/pdf"}],
# asReference=True,
# )
self.output_pca = self.addComplexOutput(
identifier="output_pca",
title="PCA",
abstract="Principal components",
formats=[{"mimeType":"text/plain"}],
asReference=True,
)
self.output_classification = self.addComplexOutput(
identifier="output_classification",
title="classification",
abstract="Weather regime classification",
formats=[{"mimeType":"application/octet-stream"}],
asReference=True,
)
self.output_frequency = self.addComplexOutput(
identifier="output_frequency",
title="Frequency",
abstract="Weather regime frequency values per year",
formats=[{"mimeType":"text/plain"}],
asReference=True,
)
self.output_netcdf = self.addComplexOutput(
identifier="output_netcdf",
title="netCDF file",
abstract="Prepared netCDF file as input for weather regime calculation",
formats=[{"mimeType":"application/x-netcdf"}],
asReference=True,
)
def __init__(self):
inputs = [
ComplexInput('resource', 'Resource',
abstract='NetCDF Files or archive (tar/zip) containing netCDF files.',
metadata=[Metadata('Info')],
min_occurs=1,
max_occurs=1000,
supported_formats=[
Format('application/x-netcdf'),
Format('application/x-tar'),
Format('application/zip'),
]),
# BoundingBoxInput('bbox', 'Bounding Box',
# abstract='Bounding box to define the region for weather classification.'
# ' Default: -80, 20, 50, 70.',
# crss=['epsg:4326'],
# min_occurs=0),
LiteralInput("season", "Time region",
abstract="Select the months to define the time region (all == whole year will be analysed)",
default="DJF",
data_type='string',
min_occurs=1,
max_occurs=1,
allowed_values=_TIMEREGIONS_.keys()
),
LiteralInput("period", "Period for weatherregime calculation",
abstract="Period for analysing the dataset",
default="19700101-20101231",
data_type='string',
min_occurs=1,
max_occurs=1,
),
LiteralInput("anualcycle", "Period for anualcycle calculation",
abstract="Period for anual cycle calculation",
default="19700101-19991231",
data_type='string',
min_occurs=1,
max_occurs=1,
),
LiteralInput("kappa", "Nr of Weather regimes",
abstract="Set the number of clusters to be detected",
default='4',
data_type='integer',
min_occurs=1,
max_occurs=1,
allowed_values=range(2, 11)
),
]
outputs = [
ComplexOutput("Routput_graphic", "Weather Regime Pressure map",
abstract="Weather Classification",
supported_formats=[Format('image/pdf')],
as_reference=True,
),
ComplexOutput("output_pca", "R - datafile",
abstract="Principal components (PCA)",
supported_formats=[Format('text/plain')],
as_reference=True,
),
ComplexOutput("output_classification", "R - workspace",
abstract="Weather regime classification",
supported_formats=[Format("application/octet-stream")],
as_reference=True,
),
ComplexOutput('output_netcdf', 'Subsets for one dataset',
abstract="Prepared netCDF file as input for weatherregime calculation",
as_reference=True,
supported_formats=[Format('application/x-netcdf')]
),
ComplexOutput('output_log', 'Logging information',
abstract="Collected logs during process run.",
as_reference=True,
supported_formats=[Format('text/plain')]
),
]
super(WeatherregimesmodelProcess, self).__init__(
self._handler,
identifier="weatherregimes_model",
title="Weather Regimes (based on climate model data)",
abstract='k-mean cluster analyse of the pressure patterns. Clusters are equivalent to weather regimes',
version="0.10",
metadata=[
Metadata('LSCE', 'http://www.lsce.ipsl.fr/en/index.php'),
Metadata('Doc', 'http://flyingpigeon.readthedocs.io/en/latest/'),
],
inputs=inputs,
outputs=outputs,
status_supported=True,
store_supported=True,
)
def __init__(self):
inputs = [
ComplexInput('resource', 'Resource',
abstract='NetCDF Files or archive (tar/zip) containing netCDF files.',
metadata=[Metadata('Info')],
min_occurs=1,
max_occurs=1000,
supported_formats=[
Format('application/x-netcdf'),
Format('application/x-tar'),
Format('application/zip'),
]),
LiteralInput("Rdat", "R - workspace",
abstract="R workspace as output from weather regime reference process",
data_type='string',
min_occurs=1,
max_occurs=1,
),
LiteralInput("dat", "R - datafile",
abstract="R datafile as output from weather regime reference process",
data_type='string',
min_occurs=1,
max_occurs=1,
),
LiteralInput("netCDF", "netCDF reference",
abstract="netCDF file as output from weather regime reference process",
data_type='string',
min_occurs=0,
max_occurs=1,
),
LiteralInput("season", "Time region",
abstract="Select the months to define the time region (all == whole year will be analysed)",
default="DJF",
data_type='string',
min_occurs=1,
max_occurs=1,
allowed_values=_TIMEREGIONS_.keys()
),
LiteralInput("period", "Period for weatherregime calculation",
abstract="Period for analysing the dataset",
default="19700101-20101231",
data_type='string',
min_occurs=1,
max_occurs=1,
),
LiteralInput("anualcycle", "Period for anualcycle calculation",
abstract="Period for anual cycle calculation",
default="19700101-19991231",
data_type='string',
min_occurs=1,
max_occurs=1,
), ]
outputs = [
ComplexOutput("output_pca", "R - datafile",
abstract="Principal components (PCA)",
supported_formats=[Format('text/plain')],
as_reference=True,
),
ComplexOutput("output_classification", "R - workspace",
abstract="Weather regime classification",
supported_formats=[Format("application/octet-stream")],
as_reference=True,
),
ComplexOutput("output_frequency", "Frequency",
abstract="Weather regime frequency values per year",
supported_formats=[Format('text/plain')],
as_reference=True,
),
ComplexOutput('output_netcdf', 'Subsets for one dataset',
abstract="Prepared netCDF file as input for weatherregime calculation",
as_reference=True,
supported_formats=[Format('application/x-netcdf')]
),
ComplexOutput('output_log', 'Logging information',
abstract="Collected logs during process run.",
as_reference=True,
supported_formats=[Format('text/plain')]
),
]
super(WeatherregimesprojectionProcess, self).__init__(
self._handler,
identifier="weatherregimes_projection",
title="Weather Regimes (Projection based on precalculated statistics)",
abstract='k-mean cluster analyse of the pressure patterns. Clusters are equivalent to weather regimes',
version="0.10",
metadata=[
Metadata('LSCE', 'http://www.lsce.ipsl.fr/en/index.php'),
Metadata('Doc', 'http://flyingpigeon.readthedocs.io/en/latest/'),
],
inputs=inputs,
outputs=outputs,
status_supported=True,
store_supported=True,
)
