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, year_ranges, model_experiment_ensemble,
outputs_from_plot_names, region, check_constraints)
from .. import runner, util
LOGGER = logging.getLogger("PYWPS")
[docs]class Toymodel(Process):
def __init__(self):
# more correctly the variable depends on the settings
self.variables = ['psl', 'tas']
self.frequency = 'mon'
inputs = [
*model_experiment_ensemble(model='ACCESS1-0',
experiment='historical',
ensemble='r1i1p1',
max_occurs=1,
required_variables=self.variables,
required_frequency=self.frequency),
*year_ranges((1999, 2001)),
LiteralInput('variable',
'Variable',
abstract='Select the variable to simulate.',
data_type='string',
default='psl',
allowed_values=['psl', 'tas']),
*region(-40, 40, 30, 50),
LiteralInput(
'beta',
'Beta',
abstract='User defined underdispersion (beta >= 0).',
data_type='float',
default=0.7,
),
LiteralInput(
'number_of_members',
'Number of members',
abstract='Number of members to be generated.',
data_type='integer',
default=2,
allowed_values=AllowedValue(allowed_type=ALLOWEDVALUETYPE.RANGE, minval=1, maxval=1000),
),
]
# self.plotlist = [
# 'TM90', 'NumberEvents', 'DurationEvents', 'LongBlockEvents', 'BlockEvents', 'ACN', 'CN', 'BI', 'MGI',
# 'Z500', 'ExtraBlock', 'InstBlock'
# ]
outputs = [
# *outputs_from_plot_names(self.plotlist),
ComplexOutput('plot',
'Toy Model plot',
abstract='Generated synthetic model plt.',
as_reference=True,
supported_formats=[Format('image/jpeg')]),
ComplexOutput('model',
'Toy Model',
abstract='Generated synthetic model.',
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(Toymodel, self).__init__(
self._handler,
identifier="toymodel",
title="Toymodel",
version=runner.VERSION,
abstract="""The goal of this diagnostic is to simulate single-model ensembles from an observational dataset
to investigate the effect of observational uncertainty.
The estimated calculation time of this process is 30 seconds for the default values supplied.
""",
metadata=[
Metadata('ESMValTool', 'http://www.esmvaltool.org/'),
Metadata(
'Documentation',
'https://esmvaltool.readthedocs.io/en/v2.0a2/recipes/recipe_toymodel.html',
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(
start_longitude=request.inputs['start_longitude'][0].data,
end_longitude=request.inputs['end_longitude'][0].data,
start_latitude=request.inputs['start_latitude'][0].data,
end_latitude=request.inputs['end_latitude'][0].data,
beta=request.inputs['beta'][0].data,
number_of_members=request.inputs['number_of_members'][0].data,
variable=request.inputs['variable'][0].data,
)
# generate recipe
response.update_status("generate recipe ...", 10)
start_year = request.inputs['start_year'][0].data
end_year = request.inputs['end_year'][0].data
recipe_file, config_file = runner.generate_recipe(
workdir=self.workdir,
diag='toymodel',
constraints=constraints,
options=options,
start_year=start_year,
end_year=end_year,
output_format='jpg',
)
# 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)
else:
LOGGER.exception('esmvaltool failed!')
response.update_status("exception occured: " + result['exception'], 85)
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, 'toymodel_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/jpeg')
response.outputs['plot'].file = runner.get_output(result['plot_dir'],
path_filter=os.path.join('toymodel', 'main'),
name_filter="synthetic*",
output_format="jpg")
response.outputs['model'].output_format = FORMATS.NETCDF
response.outputs['model'].file = runner.get_output(result['work_dir'],
path_filter=os.path.join('toymodel', 'main'),
name_filter="synthetic*",
output_format="nc")