本文整理汇总了Python中opus_core.regression_model.RegressionModel.estimate方法的典型用法代码示例。如果您正苦于以下问题：Python RegressionModel.estimate方法的具体用法？Python RegressionModel.estimate怎么用？Python RegressionModel.estimate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.regression_model.RegressionModel的用法示例。
在下文中一共展示了RegressionModel.estimate方法的4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: estimate
# 需要导入模块: from opus_core.regression_model import RegressionModel [as 别名]
# 或者: from opus_core.regression_model.RegressionModel import estimate [as 别名]
def estimate(self, specification, dataset, outcome_attribute, index=None, **kwargs):
if index is None:
index = arange(dataset.size())
data_objects = kwargs.get("data_objects",{})
if data_objects is not None:
self.dataset_pool.add_datasets_if_not_included(data_objects)
# filter out agents for this group
new_index = self.group_member.get_index_of_my_agents(dataset, index, dataset_pool=self.dataset_pool)
return RegressionModel.estimate(self, specification, dataset, outcome_attribute,
index=index[new_index], **kwargs)示例2: estimate
# 需要导入模块: from opus_core.regression_model import RegressionModel [as 别名]
# 或者: from opus_core.regression_model.RegressionModel import estimate [as 别名]
def estimate(self, specification, dataset, outcome_attribute="urbansim.gridcell.ln_total_land_value", index = None,
procedure="opus_core.estimate_linear_regression", data_objects=None,
estimate_config=None, debuglevel=0):
if data_objects is not None:
self.dataset_pool.add_datasets_if_not_included(data_objects)
if self.filter <> None:
res = Resources({"debug":debuglevel})
index = dataset.get_filtered_index(self.filter, threshold=0, index=index, dataset_pool=self.dataset_pool,
resources=res)
return RegressionModel.estimate(self, specification, dataset, outcome_attribute, index, procedure,
estimate_config=estimate_config, debuglevel=debuglevel)示例3: range
# 需要导入模块: from opus_core.regression_model import RegressionModel [as 别名]
# 或者: from opus_core.regression_model.RegressionModel import estimate [as 别名]
# "demand_lag1"
# "sum_demand_times_2",
"waterdemand.consumption_re.something_like_sum_demand",
)
)
print "Create a model object"
years = range(2001, 2003)
# single
model = RegressionModel()
print "Estimate coefficients - single"
coefficients, other_est_results = model.estimate(specification, consumption,
outcome_attribute="waterdemand.%s.sum_demand" % consumption_type, # if outcome_attribute is opus_core.func.ln(), the simulation results need to take exp()
index=index_est,
procedure="opus_core.estimate_linear_regression",
data_objects=dataset_pool.datasets_in_pool())
"""Simulate over the set of years."""
for year in years:
print "\nSimulate water demand %s" % year
SimulationState().set_current_time(year)
dataset_pool = SessionConfiguration().get_dataset_pool()
dataset_pool.remove_all_datasets()
gridcells = dataset_pool.get_dataset("gridcell")
#create a ConsumptionDataset instance out of gridcells - simulate water demand for every gridcell
resources = Resources({'data':{
"grid_id":gridcells.get_id_attribute(),示例4: estimate
# 需要导入模块: from opus_core.regression_model import RegressionModel [as 别名]
# 或者: from opus_core.regression_model.RegressionModel import estimate [as 别名]
def estimate(self, specification, dataset, outcome_attribute="urbansim.gridcell.logistic_fraction_residential_land", index = None,
procedure="opus_core.estimate_linear_regression", data_objects=None,
estimate_config=None, debuglevel=0):
return RegressionModel.estimate(self, specification, dataset, outcome_attribute, index, procedure, data_objects=data_objects,
estimate_config=estimate_config, debuglevel=debuglevel)