def get_sampling_weights(self, config, agent_set=None, agents_index=None, **kwargs):
where_developable = AgentLocationChoiceModelMember.apply_filter(self, self.filter, None, agent_set,
agents_index)
if self.developable_maximum_unit_variable:
varlist = [self.developable_maximum_unit_variable]
else:
varlist = []
if self.developable_minimum_unit_variable is not None:
varlist.append(self.developable_minimum_unit_variable)
self.choice_set.compute_variables(varlist, dataset_pool = self.dataset_pool)
if self.developable_maximum_unit_variable is not None:
max_capacity = clip_to_zero_if_needed(self.choice_set.get_attribute_by_index(
self.developable_maximum_unit_variable, where_developable),
"get_weights_for_sampling_locations - computing developable_maximum_unit_variable")
else:
max_capacity = ones(where_developable.size) * agent_set.get_attribute(self.units).max()
if self.developable_minimum_unit_variable is not None:
min_capacity = clip_to_zero_if_needed(self.choice_set.get_attribute_by_index(
self.developable_minimum_unit_variable, where_developable),
"get_weights_for_sampling_locations - computing developable_minimum_unit_variable")
else:
min_capacity = zeros(max_capacity.size)
if max_capacity.sum(dtype="float32") == 0:
raise RuntimeError, "There are no choices with any capacity for %s buildings." % agent_set.what
#how many buildings fit in each developable location
max_building_size = sort(max_capacity)[-max(50,int(where_developable.size*0.001))]
proposed_building_sizes = agent_set.get_attribute_by_index(self.units_full_name, agents_index)
if proposed_building_sizes.max() > max_building_size: # change the size if there is not enough space
logger.log_status("Maximum building size: %s" % proposed_building_sizes.max())
self.modify_agents_size(agent_set, minimum(proposed_building_sizes,max_building_size), agents_index)
proposed_building_sizes = agent_set.get_attribute_by_index(self.units_full_name, agents_index)
if self.run_config.get("agent_units_string", None): # needs to be corrected
if VariableName(self.run_config["agent_units_string"]).get_alias() not in agent_set.get_known_attribute_names():
agent_set.compute_variables(self.run_config["agent_units_string"])
self.run_config["agent_units_all"] = agent_set.get_attribute_by_index(self.run_config["agent_units_string"], agents_index)
logger.log_warning("Not enough building capacity. Large building sizes reduced to %s" % max_building_size)
proposed_building_sizes = reshape(proposed_building_sizes, (proposed_building_sizes.size,1))
weight_array = logical_and(proposed_building_sizes >= reshape(min_capacity, (1, min_capacity.size)),
(reshape(max_capacity, (1, max_capacity.size)) >=
proposed_building_sizes))
# for memory reasons, discard columns that have only zeros
keep = where(weight_array.sum(axis=0, dtype=int32))[0]
where_developable = where_developable[keep]
weight_array = take(weight_array, keep, axis=1)
if where_developable.size <= 0:
logger.log_warning("No developable locations available.")
self.filter_index = where_developable
return weight_array
def get_sampling_weights(self,
config,
agent_set=None,
agents_index=None,
**kwargs):
where_developable = AgentLocationChoiceModelMember.apply_filter(
self, self.filter, None, agent_set, agents_index)
if self.developable_maximum_unit_variable:
varlist = [self.developable_maximum_unit_variable]
else:
varlist = []
if self.developable_minimum_unit_variable is not None:
varlist.append(self.developable_minimum_unit_variable)
self.choice_set.compute_variables(varlist,
dataset_pool=self.dataset_pool)
if self.developable_maximum_unit_variable is not None:
max_capacity = clip_to_zero_if_needed(
self.choice_set.get_attribute_by_index(
self.developable_maximum_unit_variable, where_developable),
"get_weights_for_sampling_locations - computing developable_maximum_unit_variable"
)
else:
max_capacity = ones(
where_developable.size) * agent_set.get_attribute(
self.units).max()
if self.developable_minimum_unit_variable is not None:
min_capacity = clip_to_zero_if_needed(
self.choice_set.get_attribute_by_index(
self.developable_minimum_unit_variable, where_developable),
"get_weights_for_sampling_locations - computing developable_minimum_unit_variable"
)
else:
min_capacity = zeros(max_capacity.size)
if max_capacity.sum(dtype="float32") == 0:
raise RuntimeError, "There are no choices with any capacity for %s buildings." % agent_set.what
#how many buildings fit in each developable location
max_building_size = sort(
max_capacity)[-max(50, int(where_developable.size * 0.001))]
proposed_building_sizes = agent_set.get_attribute_by_index(
self.units_full_name, agents_index)
if proposed_building_sizes.max(
) > max_building_size: # change the size if there is not enough space
logger.log_status("Maximum building size: %s" %
proposed_building_sizes.max())
self.modify_agents_size(
agent_set, minimum(proposed_building_sizes, max_building_size),
agents_index)
proposed_building_sizes = agent_set.get_attribute_by_index(
self.units_full_name, agents_index)
if self.run_config.get("agent_units_string",
None): # needs to be corrected
if VariableName(
self.run_config["agent_units_string"]).get_alias(
) not in agent_set.get_known_attribute_names():
agent_set.compute_variables(
self.run_config["agent_units_string"])
self.run_config[
"agent_units_all"] = agent_set.get_attribute_by_index(
self.run_config["agent_units_string"], agents_index)
logger.log_warning(
"Not enough building capacity. Large building sizes reduced to %s"
% max_building_size)
proposed_building_sizes = reshape(proposed_building_sizes,
(proposed_building_sizes.size, 1))
weight_array = logical_and(
proposed_building_sizes >= reshape(min_capacity,
(1, min_capacity.size)),
(reshape(max_capacity,
(1, max_capacity.size)) >= proposed_building_sizes))
# for memory reasons, discard columns that have only zeros
keep = where(weight_array.sum(axis=0, dtype=int32))[0]
where_developable = where_developable[keep]
weight_array = take(weight_array, keep, axis=1)
if where_developable.size <= 0:
logger.log_warning("No developable locations available.")
self.filter_index = where_developable
return weight_array
