def __init__(self):
inputs = [
ComplexInput('resource', 'Resource',
abstract="NetCDF Files or archive (tar/zip) containing netCDF files",
min_occurs=1,
max_occurs=1000,
# maxmegabites=5000,
supported_formats=[
Format('application/x-netcdf'),
Format('application/x-tar'),
Format('application/zip'),
]),
LiteralInput("region", "Region",
# abstract= countries_longname(), # need to handle special non-ascii char in countries.
default='DEU',
data_type='string',
min_occurs=1,
max_occurs=len(countries()),
allowed_values=countries()), # REGION_EUROPE #COUNTRIES
]
###########
# OUTPUTS
###########
outputs = [
ComplexOutput('output_nc', "Subsets",
abstract="Tar archive containing the netCDF files",
as_reference=True,
supported_formats=[Format("application/x-tar")],
),
ComplexOutput('output_factsheet', "Climate Fact Sheet",
abstract="Short overview of the climatological situation of the selected countries",
as_reference=True,
supported_formats=[Format('application/pdf')],
),
ComplexOutput('output_log', 'Logging information',
abstract="Collected logs during process run.",
as_reference=True,
supported_formats=[Format("text/plain")]),
]
super(FactsheetProcess, self).__init__(
self._handler,
identifier="climatefactsheet",
title="Climate Fact Sheet Generator (init)",
version="0.2",
abstract="Returns a pdf with a short overview of the climatological situation for the selected countries",
metadata=[
# {"title": "LSCE", "href": "http://www.lsce.ipsl.fr/en/index.php"},
{"title": "Doc", "href": "http://flyingpigeon.readthedocs.io/en/latest/"},
],
inputs=inputs,
outputs=outputs,
status_supported=True,
store_supported=True
)
def __init__(self):
WPSProcess.__init__(self,
identifier = "segetalflora",
title="Segetal Flora",
version = "0.3",
metadata=[{"title": "Institut Pierre Simon Laplace", "href": "https://www.ipsl.fr/en/"}],
abstract="Species biodiversity of segetal flora. Imput files: variable:tas , domain: EUR-11 or EUR-44",
statusSupported=True,
storeSupported=True
)
self.netcdf_file = self.addComplexInput(
identifier="netcdf_file",
title="NetCDF Files",
abstract="NetCDF File",
minOccurs=1,
maxOccurs=1000,
maxmegabites=500000,
formats=[{"mimeType":"application/x-netcdf"}],
)
self.climate_type = self.addLiteralInput(
identifier="climate_type",
title="Climate type",
abstract="Select climate type",
default='3',
type=type(''),
minOccurs=1,
maxOccurs=8,
allowedValues=["1", "2", "3", "4", "5", "6", "7", "all"] # sem
)
self.culture_type = self.addLiteralInput(
identifier="culture_type",
title="Culture type",
abstract="Select culture type",
default='fallow',
type=type(''),
minOccurs=1,
maxOccurs=8,
allowedValues=["fallow", "intensiv", "extensiv"] # sem
)
self.region = self.addLiteralInput(
identifier="region",
title="Region",
abstract="European Regions ...",
default='FRA',
type=type(''),
minOccurs=0,
maxOccurs=25,
allowedValues=countries()
)
#complex output
#-------------
#self.logout = self.addComplexOutput(
#identifier="logout",
#title="Indice log-file",
#abstract="logfile for segetalflora process",
#metadata=[],
#formats=[{"mimeType":"text/plain"}],
#asReference=True,
#)
self.out_tas = self.addComplexOutput(
title="tas_EUR",
abstract="Tar archive containing the netCDF EUR tas mean files",
formats=[{"mimeType":"application/x-tar"}],
asReference=True,
identifier="out_tas",
)
self.out_segetalflora = self.addComplexOutput(
title="polygons",
abstract="Tar archive containing the netCDF EU-countries polygons segetalflora ",
formats=[{"mimeType":"application/x-tar"}],
asReference=True,
identifier="out_segetalflora",
)
self.out_fieldmeans = self.addComplexOutput(
title="fieldmeans",
abstract="Tar archive containing the netCDF EU-countries fieldmeans segetalflora ",
formats=[{"mimeType":"application/x-tar"}],
asReference=True,
identifier="out_fieldmeans",
)
self.out_plots = self.addComplexOutput(
title="plots",
abstract="Tar archive containing the bokeh plots html files for segetalflora ",
formats=[{"mimeType":"application/x-tar"}],
asReference=True,
identifier="out_plots",
)
def __init__(self):
WPSProcess.__init__(
self,
identifier="indices_percentile",
title="Climate indices -- Percentile",
version="0.9",
abstract=
"Climate indices based on one single input variable and the percentile of a reference period.",
metadata=[
{
'title':
'Documentation',
'href':
'http://flyingpigeon.readthedocs.io/en/latest/descriptions/index.html#climate-indices'
},
{
"title": "ICCLIM",
"href": "http://icclim.readthedocs.io/en/latest/"
},
{
"title":
"Percentile-based indices",
"href":
"http://flyingpigeon.readthedocs.io/en/latest/descriptions/indices.html#percentile-based-indices"
},
],
statusSupported=True,
storeSupported=True)
self.resource = self.addComplexInput(
identifier="resource",
title="Resouce",
abstract="NetCDF File",
minOccurs=1,
maxOccurs=100,
maxmegabites=5000,
formats=[{
"mimeType": "application/x-netcdf"
}],
)
self.indices = self.addLiteralInput(
identifier="indices",
title="Index",
abstract='Select an index',
default='TG',
type=type(''),
minOccurs=1,
maxOccurs=1, # len(indices()),
allowedValues=['TG', 'TN', 'TX'], # indices()
)
self.percentile = self.addLiteralInput(
identifier="percentile",
title="Percentile",
abstract='Select an percentile',
default=90,
type=type('0'),
minOccurs=1,
maxOccurs=1, # len(indices()),
allowedValues=range(1, 100), # indices()
)
self.refperiod = self.addLiteralInput(
identifier="refperiod",
title="Reference Period",
abstract="Time refperiod to retrieve the percentile level",
default="19700101-20101231",
type=type(''),
minOccurs=0,
maxOccurs=1,
)
#self.refperiod = self.addLiteralInput(
#identifier="refperiod",
#title="Reference refperiod",
#abstract="Reference refperiod for climate condition (all = entire timeserie)",
#default=None,
#type=type(''),
#minOccurs=0,
#maxOccurs=1,
#allowedValues=['all','1951-1980', '1961-1990', '1971-2000','1981-2010']
#)
self.groupings = self.addLiteralInput(
identifier="groupings",
title="Grouping",
abstract="Select an time grouping (time aggregation)",
default='yr',
type=type(''),
minOccurs=1,
maxOccurs=len(GROUPING),
allowedValues=GROUPING)
self.polygons = self.addLiteralInput(identifier="polygons",
title="Country subset",
abstract=countries_longname(),
default='DEU',
type=type(''),
minOccurs=0,
maxOccurs=len(countries()),
allowedValues=countries())
self.mosaic = self.addLiteralInput(
identifier="mosaic",
title="Mosaic",
abstract=
"If Mosaic is checked, selected polygons be clipped as a mosaic for each input file",
default=False,
type=type(False),
minOccurs=0,
maxOccurs=1,
)
# complex output
# -------------
self.output = self.addComplexOutput(
identifier="output",
title="Index",
abstract="Calculated index as NetCDF file",
metadata=[],
formats=[{
"mimeType": "application/x-tar"
}],
asReference=True)
def __init__(self):
WPSProcess.__init__(
self,
identifier="subset_countries",
title="Subset countries",
version="0.9",
abstract="Returns only the selected polygon for each input dataset",
metadata=[
{
"title": "LSCE",
"href": "http://www.lsce.ipsl.fr/en/index.php"
},
{
"title": "Documentation",
"href": "http://flyingpigeon.readthedocs.io/en/latest/"
},
],
statusSupported=True,
storeSupported=True)
self.resource = self.addComplexInput(
identifier="resource",
title="Resource",
abstract=
"NetCDF Files or archive (tar/zip) containing netCDF files",
minOccurs=1,
maxOccurs=1000,
maxmegabites=5000,
formats=[{
"mimeType": "application/x-netcdf"
}, {
"mimeType": "application/x-tar"
}, {
"mimeType": "application/zip"
}],
)
self.region = self.addLiteralInput(
identifier="region",
title="Region",
# abstract= countries_longname(), # need to handle special non-ascii char in countries.
default='DEU',
type=type(''),
minOccurs=1,
maxOccurs=len(countries()),
allowedValues=countries() # REGION_EUROPE #COUNTRIES #
)
self.mosaic = self.addLiteralInput(
identifier="mosaic",
title="Mosaic",
abstract=
"If Mosaic is checked, selected polygons will be merged to one Mosaic for each input file",
default=False,
type=type(False),
minOccurs=0,
maxOccurs=1,
)
# self.dimension_map = self.addLiteralInput(
# identifier="dimension_map",
# title="Dimension Map",
# abstract= 'if not ordered in lon/lat a dimension map has to be provided',
# type=type(''),
# minOccurs=0,
# maxOccurs=1
# )
# self.variable = self.addLiteralInput(
# identifier="variable",
# title="Variable",
# abstract="Variable to be expected in the input files (Variable will be detected if not set)",
# default=None,
# type=type(''),
# minOccurs=0,
# maxOccurs=1,
# )
###########
# OUTPUTS
###########
self.output = self.addComplexOutput(
title="Subsets",
abstract="Tar archive containing the netCDF files",
formats=[{
"mimeType": "application/x-tar"
}],
asReference=True,
identifier="output",
)
self.output_netcdf = self.addComplexOutput(
title="Subsets for one dataset",
abstract="NetCDF file with subsets of one dataset.",
formats=[{
"mimeType": "application/x-netcdf"
}],
asReference=True,
identifier="ncout",
)
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 = "subset_countries",
title="Subset netCDF files",
version = "0.3",
abstract="This process returns only the given polygon from input netCDF files.",
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.region = self.addLiteralInput(
identifier="region",
title="Region",
#abstract= countries_longname(), # need to handle special non-ascii char in countries.
default='DEU',
type=type(''),
minOccurs=1,
maxOccurs=len(countries()),
allowedValues=countries() #REGION_EUROPE #COUNTRIES #
)
self.dimension_map = self.addLiteralInput(
identifier="dimension_map",
title="Dimension Map",
abstract= 'if not ordered in lon/lat a dimension map has to be provided',
type=type(''),
minOccurs=0,
maxOccurs=1
)
self.variable = self.addLiteralInput(
identifier="variable",
title="Variable",
abstract="Variable to be expected in the input files (Variable will be detected if not set, )",
default=None,
type=type(''),
minOccurs=0,
maxOccurs=1,
)
self.mosaik = self.addLiteralInput(
identifier="mosaik",
title="Mosaik",
abstract="If Mosaik is checked, selected polygons will be merged to one Mosaik for each input file",
default=False,
type=type(False),
minOccurs=0,
maxOccurs=1,
)
self.output = self.addComplexOutput(
title="Subsets",
abstract="Tar archive containing the netCDF files",
formats=[{"mimeType":"application/x-tar"}],
asReference=True,
identifier="output",
)
def __init__(self):
WPSProcess.__init__(
self,
identifier = "subset_countries",
title="Subset countries",
version = "0.9",
abstract="Returns only the selected polygon for each input dataset",
metadata= [
{"title": "LSCE", "href": "http://www.lsce.ipsl.fr/en/index.php"},
{"title": "Documentation", "href": "http://flyingpigeon.readthedocs.io/en/latest/"},
],
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.region = self.addLiteralInput(
identifier="region",
title="Region",
#abstract= countries_longname(), # need to handle special non-ascii char in countries.
default='DEU',
type=type(''),
minOccurs=1,
maxOccurs=len(countries()),
allowedValues=countries() #REGION_EUROPE #COUNTRIES #
)
self.mosaic = self.addLiteralInput(
identifier="mosaic",
title="Mosaic",
abstract="If Mosaic is checked, selected polygons will be merged to one Mosaic for each input file",
default=False,
type=type(False),
minOccurs=0,
maxOccurs=1,
)
# self.dimension_map = self.addLiteralInput(
# identifier="dimension_map",
# title="Dimension Map",
# abstract= 'if not ordered in lon/lat a dimension map has to be provided',
# type=type(''),
# minOccurs=0,
# maxOccurs=1
# )
self.variable = self.addLiteralInput(
identifier="variable",
title="Variable",
abstract="Variable to be expected in the input files (Variable will be detected if not set)",
default=None,
type=type(''),
minOccurs=0,
maxOccurs=1,
)
self.output = self.addComplexOutput(
title="Subsets",
abstract="Tar archive containing the netCDF files",
formats=[{"mimeType":"application/x-tar"}],
asReference=True,
identifier="output",
)
self.output_netcdf = self.addComplexOutput(
title="Subsets for one dataset",
abstract="NetCDF file with subsets of one dataset.",
formats=[{"mimeType":"application/x-netcdf"}],
asReference=True,
identifier="ncout",
)
def __init__(self):
inputs = [
LiteralInput(
'region',
'Region',
data_type='string',
# abstract= countries_longname(), # need to handle special non-ascii char in countries.
abstract="Country code, see ISO-3166-3:\
https://en.wikipedia.org/wiki/ISO_3166-1_alpha-3#Officially_assigned_code_elements",
min_occurs=1,
max_occurs=len(countries()),
default='DEU',
allowed_values=countries()), # REGION_EUROPE #COUNTRIES
LiteralInput('mosaic',
'Union of multiple regions',
data_type='boolean',
abstract="If True, selected regions will be merged"
" into a single geometry.",
min_occurs=0,
max_occurs=1,
default=False),
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'),
]),
]
outputs = [
ComplexOutput(
'output',
'Tar archive',
abstract="Tar archive of the subsetted netCDF files.",
as_reference=True,
supported_formats=[Format('application/x-tar')]),
ComplexOutput('ncout',
'Example netCDF file',
abstract="NetCDF file with subset for one dataset.",
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(ClippingProcess, self).__init__(
self._handler,
identifier="subset_countries",
title="Subset (World Countries)",
version="0.10",
abstract=
"Return the data whose grid cells intersect the selected countries for each input dataset.",
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="indices_simple",
title="Climate indices -- Simple",
version="0.9",
abstract="Climate indices based on one single input variable.",
metadata=[
{'title': 'Documentation', 'href': 'http://flyingpigeon.readthedocs.io/en/latest/descriptions/index.html#climate-indices'},
{"title": "ICCLIM" , "href": "http://icclim.readthedocs.io/en/latest/"},
{"title": "Simple Indices", "href": "http://flyingpigeon.readthedocs.io/en/latest/descriptions/indices.html"}
],
statusSupported=True,
storeSupported=True
)
self.resource = self.addComplexInput(
identifier="resource",
title="Resouce",
abstract="NetCDF File",
minOccurs=1,
maxOccurs=100,
maxmegabites=5000,
formats=[{"mimeType": "application/x-netcdf"}],
)
self.groupings = self.addLiteralInput(
identifier="groupings",
title="Grouping",
abstract="Select an time grouping (time aggregation)",
default='yr',
type=type(''),
minOccurs=1,
maxOccurs=len(GROUPING),
allowedValues=GROUPING
)
self.indices = self.addLiteralInput(
identifier="indices",
title="Index",
abstract=indices_description(),
default='SU',
type=type(''),
minOccurs=1,
maxOccurs=len(indices()),
allowedValues=indices()
)
self.polygons = self.addLiteralInput(
identifier="polygons",
title="Country subset",
abstract=str(countries_longname()),
type=type(''),
minOccurs=0,
maxOccurs=len(countries()),
allowedValues=countries()
)
self.mosaic = self.addLiteralInput(
identifier="mosaic",
title="Mosaic",
abstract="If Mosaic is checked, selected polygons be clipped as a mosaic for each input file",
default=False,
type=type(False),
minOccurs=0,
maxOccurs=1,
)
# complex output
# -------------
self.output = self.addComplexOutput(
identifier="output",
title="Index",
abstract="Calculated index as NetCDF file",
metadata=[],
formats=[{"mimeType": "application/x-tar"}],
asReference=True
)
self.output_netcdf = self.addComplexOutput(
title="one dataset as example",
abstract="NetCDF file to be dispayed on WMS",
formats=[{"mimeType":"application/x-netcdf"}],
asReference=True,
identifier="ncout",
)
def __init__(self):
inputs = [
ComplexInput(
'resource',
'Resource',
abstract=
"NetCDF Files or archive (tar/zip) containing netCDF files.",
min_occurs=1,
max_occurs=1000,
# maxmegabites=5000,
supported_formats=[
Format('application/x-netcdf'),
Format('application/x-tar'),
Format('application/zip'),
]),
# LiteralInput("indices", "Index",
# abstract='Select an index',
# default='TG',
# data_type='string',
# min_occurs=1,
# max_occurs=1, # len(indices()),
# allowed_values=['TG', 'TN', 'TX'], # indices()
# ),
LiteralInput(
"percentile",
"Percentile",
abstract='Percentile value [1-100].',
default='90',
data_type='integer',
min_occurs=1,
max_occurs=1, # len(indices()),
allowed_values=range(1, 100), # indices()
),
# LiteralInput("refperiod", "Reference Period",
# abstract="Time refperiod to retrieve the percentile level",
# default="19700101-20101231",
# data_type='string',
# min_occurs=0,
# max_occurs=1,
# ),
#
# self.refperiod = self.addLiteralInput(
# identifier="refperiod",
# title="Reference refperiod",
# abstract="Reference refperiod for climate condition (all = entire timeserie)",
# default=None,
# type=type(''),
# minOccurs=0,
# maxOccurs=1,
# allowedValues=['all','1951-1980', '1961-1990', '1971-2000','1981-2010']
# )
# LiteralInput("grouping", "Grouping",
# abstract="Select an time grouping (time aggregation)",
# default='yr',
# data_type='string',
# min_occurs=1,
# max_occurs=1,
# allowed_values=GROUPING
# ),
LiteralInput(
'region',
'Region',
data_type='string',
abstract="Country code, see ISO-3166-3:\
https://en.wikipedia.org/wiki/ISO_3166-1_alpha-3#Officially_assigned_code_elements",
min_occurs=0,
max_occurs=len(countries()),
allowed_values=countries()), # REGION_EUROPE #COUNTRIES
LiteralInput(
"mosaic",
"Mosaic",
abstract=
"If Mosaic is checked, selected polygons be clipped as a mosaic for each input file.",
default='0',
data_type='boolean',
min_occurs=0,
max_occurs=1,
),
]
outputs = [
ComplexOutput(
"output_archive",
"Tar archive",
abstract=
"Tar archive of the netCDF files storing the percentile values.",
supported_formats=[Format("application/x-tar")],
as_reference=True,
),
ComplexOutput(
'ncout',
'Example netCDF file',
abstract=
"NetCDF file storing the percentiles computed over one dataset.",
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(IndicespercentiledaysProcess, self).__init__(
self._handler,
identifier="indices_percentiledays",
title="Climate indices (Daily percentiles)",
version="0.10",
abstract="Climatological percentile for each day of the year "
"computed over the entire dataset.",
metadata=[
{
'title':
'Doc',
'href':
'http://flyingpigeon.readthedocs.io/en/latest/descriptions/\
index.html#climate-indices'
},
{
"title": "ICCLIM",
"href": "http://icclim.readthedocs.io/en/latest/"
},
{
"title":
"Percentile-based indices",
"href":
"http://flyingpigeon.readthedocs.io/en/\
latest/descriptions/indices.html#percentile-based-indices"
},
],
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.",
min_occurs=1,
max_occurs=1000,
# maxmegabites=5000,
supported_formats=[
Format('application/x-netcdf'),
Format('application/x-tar'),
Format('application/zip'),
]),
LiteralInput("indices", "Index",
abstract='Climate index code.',
default='TG',
data_type='string',
min_occurs=1,
max_occurs=1,
allowed_values=indices()
),
LiteralInput("grouping", "Grouping",
abstract="Temporal group over which the index is computed.",
default='yr',
data_type='string',
min_occurs=1,
max_occurs=1, # len(GROUPING),
allowed_values=GROUPING
),
LiteralInput('region', 'Region',
data_type='string',
# abstract= countries_longname(), # need to handle special non-ascii char in countries.
abstract="Country code, see ISO-3166-3:\
https://en.wikipedia.org/wiki/ISO_3166-1_alpha-3#Officially_assigned_code_elements",
min_occurs=0,
max_occurs=len(countries()),
# default='DEU',
allowed_values=countries()), # REGION_EUROPE #COUNTRIES
LiteralInput("mosaic", "Mosaic",
abstract="If Mosaic is checked, selected polygons be clipped as a mosaic for each input file",
default='0',
data_type='boolean',
min_occurs=0,
max_occurs=1,
),
]
outputs = [
ComplexOutput("output_archive", "Tar archive",
abstract="Tar archive of the netCDF files storing the index values.",
supported_formats=[Format("application/x-tar")],
as_reference=True,
),
ComplexOutput('ncout', 'Example netCDF file',
abstract="NetCDF file storing the index computed over one dataset.",
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(IndicessingleProcess, self).__init__(
self._handler,
identifier="indices_single",
title="Climate indices (Single variable)",
version="0.10",
abstract="Climate index calculated from one daily input variable.",
metadata=[
{'title': 'Doc',
'href': 'http://flyingpigeon.readthedocs.io/en/latest/descriptions/\
index.html#climate-indices'},
{"title": "ICCLIM",
"href": "http://icclim.readthedocs.io/en/latest/"},
{"title": "Percentile-based indices", "href": "http://flyingpigeon.readthedocs.io/en/\
latest/descriptions/indices.html#percentile-based-indices"},
],
inputs=inputs,
outputs=outputs,
status_supported=True,
store_supported=True
)
def __init__(self):
WPSProcess.__init__(
self,
identifier = "indices_percentile",
title="Climate indices -- Percentile",
version = "0.1",
abstract="Climate indices based on one single input variable and the percentile of a referece refperiod.",
metadata = [
{'title': 'Documentation', 'href': 'http://flyingpigeon.readthedocs.io/en/latest/descriptions/index.html#climate-indices'},
{"title": "ICCLIM" , "href": "http://icclim.readthedocs.io/en/latest/"},
{"title": "Percentile-based indices", "href": "http://flyingpigeon.readthedocs.io/en/latest/descriptions/indices.html#percentile-based-indices"},
],
statusSupported=True,
storeSupported=True
)
self.resource = self.addComplexInput(
identifier="resource",
title="Resouce",
abstract="NetCDF File",
minOccurs=1,
maxOccurs=100,
maxmegabites=5000,
formats=[{"mimeType":"application/x-netcdf"}],
)
self.indices = self.addLiteralInput(
identifier="indices",
title="Indice",
abstract='Select an indice',
default='TG',
type=type(''),
minOccurs=1,
maxOccurs=1, # len(indices()),
allowedValues=['TG', 'TN', 'TX'], # indices()
)
self.percentile = self.addLiteralInput(
identifier="percentile",
title="Percentile",
abstract='Select an percentile',
default=90,
type=type('0'),
minOccurs=1,
maxOccurs=1, # len(indices()),
allowedValues=range(1,100), # indices()
)
self.refperiod = self.addLiteralInput(
identifier="refperiod",
title="Reference Period",
abstract="Time refperiod to retrieve the percentile level",
default="19700101-20101231",
type=type(''),
minOccurs=0,
maxOccurs=1,
)
#self.refperiod = self.addLiteralInput(
#identifier="refperiod",
#title="Reference refperiod",
#abstract="Reference refperiod for climate condition (all = entire timeserie)",
#default=None,
#type=type(''),
#minOccurs=0,
#maxOccurs=1,
#allowedValues=['all','1951-1980', '1961-1990', '1971-2000','1981-2010']
#)
self.groupings = self.addLiteralInput(
identifier="groupings",
title="Grouping",
abstract="Select an time grouping (time aggregation)",
default='yr',
type=type(''),
minOccurs=1,
maxOccurs=len(GROUPING),
allowedValues=GROUPING
)
self.polygons = self.addLiteralInput(
identifier="polygons",
title="Country subset",
abstract= countries_longname(),
default='DEU',
type=type(''),
minOccurs=0,
maxOccurs=len(countries()),
allowedValues=countries()
)
self.mosaik = self.addLiteralInput(
identifier="mosaik",
title="Mosaik",
abstract="If Mosaik is checked, selected polygons be clipped as a mosaik for each input file",
default=False,
type=type(False),
minOccurs=0,
maxOccurs=1,
)
# complex output
# -------------
self.output = self.addComplexOutput(
identifier="output",
title="Indice",
abstract="Calculated indice as NetCDF file",
metadata=[],
formats=[{"mimeType":"application/x-tar"}],
asReference=True
)
def __init__(self):
WPSProcess.__init__(
self,
identifier = "indices_single",
title="Calculation of climate indice (single variable)",
version = "0.3",
abstract="This process calculates climate indices based on one single variable.",
statusSupported=True,
storeSupported=True
)
self.resource = self.addComplexInput(
identifier="resource",
title="Resouce",
abstract="NetCDF File",
minOccurs=1,
maxOccurs=100,
maxmegabites=5000,
formats=[{"mimeType":"application/x-netcdf"}],
)
self.groupings = self.addLiteralInput(
identifier="groupings",
title="Grouping",
abstract="Select an time grouping (time aggregation)",
default='yr',
type=type(''),
minOccurs=1,
maxOccurs=len(GROUPING),
allowedValues=GROUPING
)
self.indices = self.addLiteralInput(
identifier="indices",
title="Indice",
abstract=indices_description(),
default='SU',
type=type(''),
minOccurs=1,
maxOccurs=len(indices()),
allowedValues=indices()
)
self.polygons = self.addLiteralInput(
identifier="polygons",
title="Country subset",
abstract= countries_longname(),
#default='FRA',
type=type(''),
minOccurs=0,
maxOccurs=len(countries()),
allowedValues=countries()
)
# complex output
# -------------
self.output = self.addComplexOutput(
identifier="output",
title="Indice",
abstract="Calculated indice as NetCDF file",
metadata=[],
formats=[{"mimeType":"application/x-netcdf"}],
asReference=True
)
def __init__(self):
inputs = [
LiteralInput('region', 'Region',
data_type='string',
# abstract= countries_longname(),
# need to handle special non-ascii char in countries.
abstract="Country code, see ISO-3166-3:\
https://en.wikipedia.org/wiki/ISO_3166-1_alpha-3#Officially_assigned_code_elements",
min_occurs=1,
max_occurs=len(countries()),
default='DEU',
allowed_values=countries()),
LiteralInput('mosaic', 'Union of multiple regions',
data_type='boolean',
abstract="If True, selected regions will be merged"
" into a single geometry.",
min_occurs=0,
max_occurs=1,
default=False),
ComplexInput('resource', 'Resource',
abstract='NetCDF Files or archive (tar/zip) containing NetCDF files.',
min_occurs=1,
max_occurs=1000,
supported_formats=[
Format('application/x-netcdf'),
Format('application/x-tar'),
Format('application/zip'),
]),
]
outputs = [
ComplexOutput('output', 'Tar archive',
abstract="Tar archive of the subsetted netCDF files.",
as_reference=True,
supported_formats=[Format('application/x-tar')]
),
ComplexOutput('ncout', 'Example netCDF file',
abstract="NetCDF file with subset for one dataset.",
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(SubsetcountryProcess, self).__init__(
self._handler,
identifier="subset_countries",
title="Subset Countries",
version="0.11",
abstract="Return the data whose grid cells intersect the selected countries for each input dataset.",
metadata=[
Metadata('Doc', 'https://flyingpigeon.readthedocs.io/en/latest/processes_des.html#subset-processes'),
],
inputs=inputs,
outputs=outputs,
status_supported=True,
store_supported=True,
)
