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, )