def run(self, force_rerun=False, **kwargs):
"""
Run the model. If ``force_rerun`` is True, any existing results
will be overwritten.
Additional kwargs are passed to the backend.
"""
# Check that results exist and are non-empty
if hasattr(self, 'results') and self.results.data_vars and not force_rerun:
raise exceptions.ModelError(
'This model object already has results. '
'Use model.run(force_rerun=True) to force'
'the results to be overwritten with a new run.'
)
if (self._model_data.attrs['run.mode'] == 'operate' and
not self._model_data.attrs['allow_operate_mode']):
raise exceptions.ModelError(
'Unable to run this model in operational mode, probably because '
'there exist non-uniform timesteps (e.g. from time masking)'
)
results, self._backend_model, interface = run_backend(
self._model_data, self._timings, **kwargs
)
# Add additional post-processed result variables to results
if results.attrs.get('termination_condition', None) == 'optimal':
results = postprocess.postprocess_model_results(
results, self._model_data, self._timings
)
for var in results.data_vars:
results[var].attrs['is_result'] = 1
self._model_data.update(results)
self._model_data.attrs.update(results.attrs)
if 'run_solution_returned' in self._timings.keys():
self._model_data.attrs['solution_time'] = (
self._timings['run_solution_returned'] -
self._timings['run_start']).total_seconds()
self._model_data.attrs['time_finished'] = (
self._timings['run_solution_returned'].strftime('%Y-%m-%d %H:%M:%S')
)
self.results = self._model_data.filter_by_attrs(is_result=1)
self.backend = interface(self)
def run(self, force_rerun=False, **kwargs):
"""
Run the model. If ``force_rerun`` is True, any existing results
will be overwritten.
Additional kwargs are passed to the backend.
"""
# Check that results exist and are non-empty
if hasattr(self,
'results') and self.results.data_vars and not force_rerun:
raise exceptions.ModelError(
'This model object already has results. '
'Use model.run(force_rerun=True) to force'
'the results to be overwritten with a new run.')
if (self._model_data.attrs['run.mode'] == 'operate'
and not self._model_data.attrs['allow_operate_mode']):
raise exceptions.ModelError(
'Unable to run this model in operational mode, probably because '
'there exist non-uniform timesteps (e.g. from time masking)')
results, self._backend_model, interface = run_backend(
self._model_data, self._timings, **kwargs)
# Add additional post-processed result variables to results
if results.attrs.get('termination_condition', None) == 'optimal':
results = postprocess.postprocess_model_results(
results, self._model_data, self._timings)
for var in results.data_vars:
results[var].attrs['is_result'] = 1
self._model_data.update(results)
self._model_data.attrs.update(results.attrs)
if 'run_solution_returned' in self._timings.keys():
self._model_data.attrs['solution_time'] = (
self._timings['run_solution_returned'] -
self._timings['run_start']).total_seconds()
self._model_data.attrs['time_finished'] = (
self._timings['run_solution_returned'].strftime(
'%Y-%m-%d %H:%M:%S'))
self.results = self._model_data.filter_by_attrs(is_result=1)
self.backend = interface(self)
def run(self, force_rerun=False, **kwargs):
"""
Run the model. If ``force_rerun`` is True, any existing results
will be overwritten.
Additional kwargs are passed to the backend.
"""
# Check that results exist and are non-empty
if hasattr(self, "results") and self.results.data_vars and not force_rerun:
raise exceptions.ModelError(
"This model object already has results. "
"Use model.run(force_rerun=True) to force"
"the results to be overwritten with a new run."
)
if (
self.run_config["mode"] == "operate"
and not self._model_data.attrs["allow_operate_mode"]
):
raise exceptions.ModelError(
"Unable to run this model in operational mode, probably because "
"there exist non-uniform timesteps (e.g. from time masking)"
)
results, self._backend_model, self._backend_model_opt, interface = run_backend(
self._model_data, self._timings, **kwargs
)
# Add additional post-processed result variables to results
if results.attrs.get("termination_condition", None) in ["optimal", "feasible"]:
results = postprocess_results.postprocess_model_results(
results, self._model_data, self._timings
)
self._model_data.attrs.update(results.attrs)
self._model_data = xr.merge(
[results, self._model_data], compat="override", combine_attrs="no_conflicts"
)
self._add_model_data_methods()
self.backend = interface(self)