import logging
import os
from pywps import FORMATS, ComplexInput, ComplexOutput, Format, LiteralInput, LiteralOutput, Process
from pywps.app.Common import Metadata
from pywps.response.status import WPS_STATUS
from pywps.inout.literaltypes import AllowedValue
from pywps.validator.allowed_value import ALLOWEDVALUETYPE
from .utils import (default_outputs, model_experiment_ensemble, year_ranges, outputs_from_plot_names, check_constraints)
from .. import runner, util
LOGGER = logging.getLogger("PYWPS")
[docs]class CombinedIndices(Process):
def __init__(self):
self.variables = ['pr']
self.frequency = 'mon'
inputs = [
*model_experiment_ensemble(model='MPI-ESM-MR',
experiment='historical',
ensemble='r1i1p1',
max_occurs=1,
required_variables=self.variables,
required_frequency=self.frequency),
*year_ranges((1950, 2005)),
LiteralInput('running_mean',
'Running Mean',
abstract='Length of the window for which the running mean is computed.',
data_type='integer',
allowed_values=AllowedValue(allowed_type=ALLOWEDVALUETYPE.RANGE, minval=1, maxval=365),
default=5),
LiteralInput(
'moninf',
'First month month of the seasonal mean period',
abstract="""First month of the seasonal mean period to be computed, if null the monthly anomalies
will be computed.""",
data_type='string',
allowed_values=['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', 'null'],
default='1'),
LiteralInput(
'monsup',
'Last month month of the seasonal mean period',
abstract="""Last month of the seasonal mean period to be computed, if null the monthly anomalies
will be computed.""",
data_type='string',
allowed_values=['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', 'null'],
default='3'),
LiteralInput('region',
'Region',
abstract='Region over which to calculate the metric.',
data_type='string',
allowed_values=['NAO', 'Nino3', 'Nino3.4', 'Nino4', 'SOI'],
default='NAO'),
LiteralInput('standardized',
'Standardized',
abstract='Boolean indictating if standardization should be computed.',
data_type='boolean',
default=True),
]
outputs = [
ComplexOutput('plot',
'Combined Indices plot',
abstract='Combined Indices plot.',
as_reference=True,
supported_formats=[Format('image/png')]),
ComplexOutput('data',
'Data',
abstract='Generated combined indices data.',
as_reference=True,
supported_formats=[FORMATS.NETCDF]),
ComplexOutput('archive',
'Archive',
abstract='The complete output of the ESMValTool processing as an zip archive.',
as_reference=True,
supported_formats=[Format('application/zip')]),
*default_outputs(),
]
super(CombinedIndices, self).__init__(
self._handler,
identifier="combined_indices",
title="Single and multi-model indices based on area averages",
version=runner.VERSION,
abstract=("Metric showning single and multi model indices based on area averages."
"The estimated calculation time of this process is 1 minute for the default values supplied."),
metadata=[
Metadata('ESMValTool', 'http://www.esmvaltool.org/'),
Metadata(
'Documentation',
'https://esmvaltool.readthedocs.io/en/v2.0a2/recipes/recipe_combined_climate_extreme_index.html', # noqa
role=util.WPS_ROLE_DOC),
],
inputs=inputs,
outputs=outputs,
status_supported=True,
store_supported=True,
)
def _handler(self, request, response):
response.update_status("starting ...", 0)
# build esgf search constraints
constraints = dict(
model=request.inputs['model'][0].data,
experiment=request.inputs['experiment'][0].data,
ensemble=request.inputs['ensemble'][0].data,
)
options = dict(
standardized=request.inputs['standardized'][0].data,
region=request.inputs['region'][0].data,
moninf=request.inputs['moninf'][0].data,
monsup=request.inputs['monsup'][0].data,
running_mean=request.inputs['running_mean'][0].data,
)
# generate recipe
response.update_status("generate recipe ...", 10)
recipe_file, config_file = runner.generate_recipe(
workdir=self.workdir,
diag='combined_indices',
constraints=constraints,
options=options,
start_year=request.inputs['start_year'][0].data,
end_year=request.inputs['end_year'][0].data,
output_format='png',
)
# recipe output
response.outputs['recipe'].output_format = FORMATS.TEXT
response.outputs['recipe'].file = recipe_file
# run diag
response.update_status("running diagnostic (this could take a while)...", 20)
result = runner.run(recipe_file, config_file)
response.outputs['success'].data = result['success']
# log output
response.outputs['log'].output_format = FORMATS.TEXT
response.outputs['log'].file = result['logfile']
# debug log output
response.outputs['debug_log'].output_format = FORMATS.TEXT
response.outputs['debug_log'].file = result['debug_logfile']
if result['success']:
try:
self.get_outputs(result, response)
except Exception as e:
response.update_status("exception occured: " + str(e), 85)
LOGGER.exception('Getting output failed: ' + str(e))
else:
LOGGER.exception('esmvaltool failed!')
response.update_status("exception occured: " + result['exception'], 100)
response.update_status("creating archive of diagnostic result ...", 90)
response.outputs['archive'].output_format = Format('application/zip')
response.outputs['archive'].file = runner.compress_output(
os.path.join(self.workdir, 'output'),
os.path.join(self.workdir, 'combined_indices_result.zip'))
response.update_status("done.", 100)
return response
[docs] def get_outputs(self, result, response):
# result plot
response.update_status("collecting output ...", 80)
response.outputs['plot'].output_format = Format('image/png')
response.outputs['plot'].file = runner.get_output(result['plot_dir'],
path_filter=os.path.join('combine_indices', 'main'),
name_filter="*",
output_format="png")
response.outputs['data'].output_format = FORMATS.NETCDF
response.outputs['data'].file = runner.get_output(result['work_dir'],
path_filter=os.path.join('combine_indices', 'main'),
name_filter="*",
output_format="nc")