def create_interaction_dataset(self, agent_set, agents_index, config,
*args, **kwargs):
if config is not None and config.get("estimate", False):
id_name = self.choice_set.get_id_name()[0]
mod_id_name = "__%s__" % id_name
if mod_id_name in agent_set.get_known_attribute_names():
agent_set.set_values_of_one_attribute(
id_name, agent_set.get_attribute(mod_id_name))
result = LocationChoiceModel.create_interaction_dataset(
self, agent_set, agents_index, config, **kwargs)
# select randomly buildings to unplace
ntounplace = int(agents_index.size / 4.0)
#ntounplace = 1
#self.dataset_pool.get_dataset("urbansim_constant")["recent_years"])
#idx = sample_noreplace(agents_index, ntounplace)
tmp = randint(0, agents_index.size, ntounplace)
utmp = unique(tmp)
idx = agents_index[utmp]
logger.log_status("Unplace %s buildings." % utmp.size)
if (mod_id_name not in agent_set.get_known_attribute_names()):
agent_set.add_attribute(name=mod_id_name,
data=array(
agent_set.get_attribute(id_name)))
agent_set.set_values_of_one_attribute(id_name, -1.0 * ones(
(idx.size, )), idx)
return result
return LocationChoiceModel.create_interaction_dataset(
self, agent_set, agents_index, config, **kwargs)
def create_interaction_dataset(self, agent_set, agents_index, config, *args, **kwargs):
if config is not None and config.get("estimate", False):
id_name = self.choice_set.get_id_name()[0]
mod_id_name = "__%s__" % id_name
if mod_id_name in agent_set.get_known_attribute_names():
agent_set.set_values_of_one_attribute(id_name, agent_set.get_attribute(mod_id_name))
result = LocationChoiceModel.create_interaction_dataset(self, agent_set,
agents_index, config, **kwargs)
# select randomly buildings to unplace
ntounplace = int(agents_index.size/4.0)
#ntounplace = 1
#self.dataset_pool.get_dataset("urbansim_constant")["recent_years"])
#idx = sample_noreplace(agents_index, ntounplace)
tmp = randint(0, agents_index.size, ntounplace)
utmp = unique(tmp)
idx = agents_index[utmp]
logger.log_status("Unplace %s buildings." % utmp.size)
if (mod_id_name not in agent_set.get_known_attribute_names()):
agent_set.add_attribute(name=mod_id_name, data=array(agent_set.get_attribute(id_name)))
agent_set.set_values_of_one_attribute(id_name,-1.0*ones((idx.size,)), idx)
return result
return LocationChoiceModel.create_interaction_dataset(self, agent_set,
agents_index, config, **kwargs)
def create_interaction_dataset(self, agent_set, agents_index, config, **kwargs):
if config is not None and config.get("estimate", False):
id_name = self.choice_set.get_id_name()[0]
mod_id_name = "__%s__" % id_name
# This should be only true when reestimating, since the agents for estimation were unplaced
# in the previous run and their original locations were stored in mod_id_name
if mod_id_name in agent_set.get_known_attribute_names():
agent_set.set_values_of_one_attribute(id_name, agent_set.get_attribute(mod_id_name))
result = LocationChoiceModel.create_interaction_dataset(self, agent_set,
agents_index, config, **kwargs)
return result
return LocationChoiceModel.create_interaction_dataset(self, agent_set,
agents_index, config, **kwargs)
def create_interaction_dataset(self, agent_set, agents_index, config,
**kwargs):
if config is not None and config.get("estimate", False):
id_name = self.choice_set.get_id_name()[0]
mod_id_name = "__%s__" % id_name
# This should be only true when reestimating, since the agents for estimation were unplaced
# in the previous run and their original locations were stored in mod_id_name
if mod_id_name in agent_set.get_known_attribute_names():
agent_set.set_values_of_one_attribute(
id_name, agent_set.get_attribute(mod_id_name))
result = LocationChoiceModel.create_interaction_dataset(
self, agent_set, agents_index, config, **kwargs)
return result
return LocationChoiceModel.create_interaction_dataset(
self, agent_set, agents_index, config, **kwargs)
