Source code for c3s_magic_wps.processes.wps_drought_indicator

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 .. import runner, util
from .utils import default_outputs, model_experiment_ensemble, outputs_from_plot_names, year_ranges, check_constraints
from .utils import reference_year_ranges

LOGGER = logging.getLogger("PYWPS")


[docs]class DroughtIndicator(Process): def __init__(self): self.variables = ['pr', '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), LiteralInput('ref_dataset', 'Reference Dataset', abstract='Choose a reference dataset like ERA-Interim.', data_type='string', allowed_values=['ERA-Interim'], default='ERA-Interim', min_occurs=1, max_occurs=1), *year_ranges((1990, 1999), start_year=1979, end_year=2018), ] self.plotlist = [] outputs = [ ComplexOutput('spi_plot', 'SPI Histogram plot', abstract='Generated spi histogram plot.', as_reference=True, supported_formats=[Format('image/png')]), ComplexOutput('spei_plot', 'SPEI Histogram plot', abstract='Generated SPEI Histogram plot.', as_reference=True, supported_formats=[Format('image/png')]), ComplexOutput('spi_model', 'SPI Data for the model', abstract='The complete SPI Data for the model.', as_reference=True, supported_formats=[FORMATS.NETCDF]), ComplexOutput('spi_reference', 'SPI Data for the reference model', abstract='The complete SPI Data for the reference model.', as_reference=True, supported_formats=[FORMATS.NETCDF]), ComplexOutput('spei_model', 'SPEI Data for the model', abstract='The complete SPEI Data for the model.', as_reference=True, supported_formats=[FORMATS.NETCDF]), ComplexOutput('spei_reference', 'SPEI Data for the reference model', abstract='The complete SPEI Data for the reference 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(DroughtIndicator, self).__init__( self._handler, identifier="drought_indicator", title="Drought indicator", version=runner.VERSION, abstract="""The drought indicator calculates diagnostics for meteorological drought. The estimated calculation time of this process is 45 minutes for the default values supplied.""", metadata=[ Metadata('ESMValTool', 'http://www.esmvaltool.org/'), Metadata('Documentation', 'https://esmvaltool.readthedocs.io/en/v2.0a2/recipes/recipe_spei.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, reference=request.inputs['ref_dataset'][0].data, ) # automatically determine OBS tier if constraints['reference'] == 'ERA-Interim': constraints['ref_tier'] = '3' else: constraints['ref_tier'] = '2' options = dict() # 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='spei', constraints=constraints, options=options, start_year=start_year, end_year=end_year, 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'], 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, 'drought_indicator_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['spi_plot'].output_format = Format('application/png') response.outputs['spi_plot'].file = runner.get_output(result['plot_dir'], path_filter=os.path.join('diagnostic', 'spi'), name_filter="histplot", output_format="png") response.outputs['spei_plot'].output_format = Format('application/png') response.outputs['spei_plot'].file = runner.get_output(result['plot_dir'], path_filter=os.path.join('diagnostic', 'spei'), name_filter="histplot", output_format="png") response.outputs['spi_model'].output_format = FORMATS.NETCDF response.outputs['spi_model'].file = runner.get_output(result['work_dir'], path_filter=os.path.join('diagnostic', 'spi'), name_filter="CMPI5*spi*", output_format="nc") response.outputs['spi_reference'].output_format = FORMATS.NETCDF response.outputs['spi_reference'].file = runner.get_output(result['work_dir'], path_filter=os.path.join('diagnostic', 'spi'), name_filter="OBS*spi*", output_format="nc") response.outputs['spei_model'].output_format = FORMATS.NETCDF response.outputs['spei_model'].file = runner.get_output(result['work_dir'], path_filter=os.path.join('diagnostic', 'spei'), name_filter="CMPI5*spei*", output_format="nc") response.outputs['spei_reference'].output_format = FORMATS.NETCDF response.outputs['spei_reference'].file = runner.get_output(result['work_dir'], path_filter=os.path.join('diagnostic', 'spei'), name_filter="OBS*spei*", output_format="nc")