本文整理汇总了Python中opus_core.session_configuration.SessionConfiguration.delete_computed_attributes方法的典型用法代码示例。如果您正苦于以下问题：Python SessionConfiguration.delete_computed_attributes方法的具体用法？Python SessionConfiguration.delete_computed_attributes怎么用？Python SessionConfiguration.delete_computed_attributes使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类opus_core.session_configuration.SessionConfiguration的用法示例。
在下文中一共展示了SessionConfiguration.delete_computed_attributes方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: run
# 需要导入模块: from opus_core.session_configuration import SessionConfiguration [as 别名]
# 或者: from opus_core.session_configuration.SessionConfiguration import delete_computed_attributes [as 别名]
def run(self, year, condition=None, max_iter=10):
"""
'year' is the current year of the simulation.
'condition' should be a boolean expression defined on any dataset.
The method iterates over the given models until all values of the expression are True.
'max_iter' gives the maximum number of iterations to run, if 'condition' is not fulfilled.
If it is None, there is no limit and thus, the condition must be fulfilled in order to terminate.
If 'condition' is None, the set of models is run only once.
"""
self.config['years'] = (year, year)
if condition is None:
return self.model_system.run_in_same_process(self.config)
dataset_pool = SessionConfiguration().get_dataset_pool()
variable_name = VariableName(condition)
dataset = dataset_pool.get_dataset(variable_name.get_dataset_name())
condition_value = dataset.compute_variables(variable_name, dataset_pool=dataset_pool)
result = None
iter = 1
while not alltrue(condition_value):
result = self.model_system.run_in_same_process(self.config)
if max_iter is None or iter > max_iter:
break
iter = iter + 1
# force to recompute the condition
dataset = SessionConfiguration().get_dataset_pool().get_dataset(variable_name.get_dataset_name())
dataset.delete_computed_attributes()
condition_value = dataset.compute_variables(variable_name,
dataset_pool=SessionConfiguration().get_dataset_pool())
if not alltrue(condition_value):
logger.log_status('%s did not converge. Maximum number of iterations (%s) reached.' % (self.model_name, max_iter))
else:
logger.log_status('%s converged in %s iterations.' % (self.model_name, iter-1))
return result