def generate_unique_ids(dataset, short_names):
if len(short_names) == 0:
raise ValueError, "There must have at least 1 attribute."
elif len(short_names) == 1:
submarket_ids = dataset[short_names[0]]
else:
attribute_values = column_stack( [dataset.get_attribute_as_column(short_name) for short_name in short_names] )
max_digits = digits( attribute_values.max(axis=0) )
multipler = array([10**d for d in max_digits[1:] + [0]])
submarket_ids = (attribute_values * multipler).sum(axis=1)
return submarket_ids
def generate_unique_ids(dataset, short_names, multipler=[]):
if len(short_names) == 0:
raise ValueError, "There must have at least 1 attribute."
elif len(short_names) == 1:
subgroup_ids = dataset[short_names[0]]
else:
attribute_values = dataset.get_multiple_attributes(short_names)
if not multipler:
max_digits = digits( attribute_values[:,1:].max(axis=0) )
tot_digits = concatenate( (cumsum(max_digits[::-1])[::-1], [0]) )
multipler = 10**tot_digits
subgroup_ids = (attribute_values * multipler).sum(axis=1)
return subgroup_ids, multipler
def generate_unique_ids(dataset, short_names):
if len(short_names) == 0:
raise ValueError, "There must have at least 1 attribute."
elif len(short_names) == 1:
submarket_ids = dataset[short_names[0]]
else:
attribute_values = column_stack([
dataset.get_attribute_as_column(short_name)
for short_name in short_names
])
max_digits = digits(attribute_values.max(axis=0))
multipler = array([10**d for d in max_digits[1:] + [0]])
submarket_ids = (attribute_values * multipler).sum(axis=1)
return submarket_ids
def run(
self,
developmentproject_dataset,
building_dataset,
label_attribute_names=["building_type_id", "zone_id"],
quantity_attribute_names=["residential_units",
"non_residential_sqft"]):
"""Modify buildings to reflect new development projects.
"""
project_labels = None
building_labels = None
if not developmentproject_dataset or developmentproject_dataset.size(
) == 0:
logger.log_warning(
"Empty development project dataset. Skip add_projects_to_buildings."
)
return building_dataset
is_placed_project = ones(developmentproject_dataset.size(),
dtype='bool')
for label_attribute in label_attribute_names:
project_label_attribute = developmentproject_dataset.get_attribute_as_column(
label_attribute)
is_placed_project = logical_and(is_placed_project,
project_label_attribute[:, 0] > 0)
building_lable_attribute = building_dataset.get_attribute_as_column(
label_attribute)
if project_labels is None:
project_labels = project_label_attribute
else:
project_labels = column_stack(
(project_labels, project_label_attribute))
if building_labels is None:
building_labels = building_lable_attribute
else:
building_labels = column_stack(
(building_labels, building_lable_attribute))
max_digits = digits(
row_stack((project_labels, building_labels)).max(axis=0))
multipler = array([10**d for d in max_digits[1:] + [0]])
building_identifier = (building_labels * multipler).sum(axis=1)
project_identifier = (project_labels * multipler).sum(axis=1)
if not all(is_placed_project):
logger.log_warning(
"There are %s projects with %s less than 0; they are not being processed."
% (logical_not(is_placed_project).sum(),
",".join(label_attribute_names)))
project_identifier = project_identifier[is_placed_project]
unique_project_identifier = unique(project_identifier)
for quantity_attribute in quantity_attribute_names:
developmentproject_quantity = developmentproject_dataset.get_attribute(
quantity_attribute)[is_placed_project]
quantity_sum = ndimage.sum(developmentproject_quantity,
labels=project_identifier,
index=unique_project_identifier)
for i in range(unique_project_identifier.size):
if quantity_sum[i] != 0:
this_identifier = unique_project_identifier[i]
this_label = []
remain = this_identifier
for m in multipler:
this_label.append(remain // m)
remain = remain % m
building_index = where(
building_identifier == this_identifier)[0]
#assert building_index.size == 1
if building_index.size == 0:
logger.log_error(
"building with attribute (%s) = (%s) is not in building_dataset"
% (label_attribute_names, this_label))
continue
#for attribute in []:
#data = None
#building_dataset.add_elements(name=quantity_attribute, data = current_values+quantity_sum[i],
#index=building_index)
if building_index.size > 1:
logger.log_warning(
"There are more than 1 building with attributes (%s) = (%s)"
% (label_attribute_names, this_label))
building_index = building_index[0]
current_values = building_dataset.get_attribute_by_index(
quantity_attribute, building_index)
building_dataset.modify_attribute(name=quantity_attribute,
data=current_values +
quantity_sum[i],
index=building_index)
return building_dataset
def run(self, developmentproject_dataset, building_dataset,
label_attribute_names=["building_type_id", "zone_id"],
quantity_attribute_names = ["residential_units", "non_residential_sqft"]):
"""Modify buildings to reflect new development projects.
"""
project_labels = None
building_labels = None
if not developmentproject_dataset or developmentproject_dataset.size() == 0:
logger.log_warning("Empty development project dataset. Skip add_projects_to_buildings.")
return building_dataset
is_placed_project = ones(developmentproject_dataset.size(), dtype='bool')
for label_attribute in label_attribute_names:
project_label_attribute = developmentproject_dataset.get_attribute_as_column(label_attribute)
is_placed_project = logical_and(is_placed_project, project_label_attribute[:,0]>0)
building_lable_attribute = building_dataset.get_attribute_as_column(label_attribute)
if project_labels is None:
project_labels = project_label_attribute
else:
project_labels = column_stack((project_labels, project_label_attribute))
if building_labels is None:
building_labels = building_lable_attribute
else:
building_labels = column_stack((building_labels, building_lable_attribute))
max_digits = digits( row_stack((project_labels, building_labels)).max(axis=0) )
multipler = array([10**d for d in max_digits[1:] + [0]])
building_identifier = (building_labels * multipler).sum(axis=1)
project_identifier = (project_labels * multipler).sum(axis=1)
if not all(is_placed_project):
logger.log_warning("There are %s projects with %s less than 0; they are not being processed." % (logical_not(is_placed_project).sum(),
",".join(label_attribute_names)))
project_identifier = project_identifier[is_placed_project]
unique_project_identifier = unique(project_identifier)
for quantity_attribute in quantity_attribute_names:
developmentproject_quantity = developmentproject_dataset.get_attribute(quantity_attribute)[is_placed_project]
if developmentproject_quantity.sum() == 0: continue
quantity_sum = ndimage.sum(developmentproject_quantity, labels=project_identifier, index=unique_project_identifier)
for i in range(unique_project_identifier.size):
if quantity_sum[i] != 0:
this_identifier = unique_project_identifier[i]
this_label = []
remain = this_identifier
for m in multipler:
this_label.append(remain // m)
remain = remain % m
building_index = where(building_identifier==this_identifier)[0]
#assert building_index.size == 1
if building_index.size == 0:
logger.log_error("building with attribute (%s) = (%s) is not in building_dataset" % (label_attribute_names, this_label) )
continue
#for attribute in []:
#data = None
#building_dataset.add_elements(name=quantity_attribute, data = current_values+quantity_sum[i],
#index=building_index)
if building_index.size > 1:
logger.log_warning("There are more than 1 building with attributes (%s) = (%s)" % (label_attribute_names, this_label) )
building_index = building_index[0]
current_values = building_dataset.get_attribute_by_index(quantity_attribute, building_index)
building_dataset.modify_attribute(name=quantity_attribute, data = current_values+quantity_sum[i],
index=building_index)
return building_dataset
