from urbansim.datasets.gridcell_dataset import GridcellDataset
from numpy import array
from opus_core.misc import unique
consumption_grid_id = consumption.get_attribute("grid_id")
years = consumption.get_attribute("billyear")
distinct_years = unique(years)
import os
from numpy import where, zeros, arange
cache_directory = "D:/urbansim_cache/water_demand"
for year in arange(1991, 2001):
print year
flt_storage = StorageCreator().build_storage(type="flt", location=os.path.join(cache_directory, str(year)))
gridcells = GridcellDataset(in_storage=flt_storage)
grid_id_idx = array(map(lambda x: gridcells.try_id_mapping(x, -1), consumption_grid_id))
year_idx = where(years==year)[0]
grid_id_idx_for_year = grid_id_idx[year_idx]
for attr in gridcells.get_known_attribute_names():
if attr not in consumption.get_known_attribute_names():
ftype = gridcells.get_attribute(attr).type()
consumption.add_attribute(name=attr, data=zeros(consumption.size(), dtype=ftype))
consumption.modify_attribute(name=attr,
data=gridcells.get_attribute_by_index(attr, grid_id_idx_for_year),
index=year_idx)
# store consumption dataset
out_storage = StorageCreator().build_storage(type="flt", location=cache_directory)
consumption.write_dataset(attributes = consumption.get_known_attribute_names(),
out_storage=out_storage, out_table_name=consumption_type.lower())
import os
from numpy import where, zeros, arange
cache_directory = "D:/urbansim_cache/water_demand"
for year in arange(1991, 2001):
print year
flt_storage = StorageCreator().build_storage(type="flt",
location=os.path.join(
cache_directory,
str(year)))
gridcells = GridcellDataset(in_storage=flt_storage)
grid_id_idx = array(
map(lambda x: gridcells.try_id_mapping(x, -1), consumption_grid_id))
year_idx = where(years == year)[0]
grid_id_idx_for_year = grid_id_idx[year_idx]
for attr in gridcells.get_known_attribute_names():
if attr not in consumption.get_known_attribute_names():
ftype = gridcells.get_attribute(attr).type()
consumption.add_attribute(name=attr,
data=zeros(consumption.size(),
dtype=ftype))
consumption.modify_attribute(name=attr,
data=gridcells.get_attribute_by_index(
attr, grid_id_idx_for_year),
index=year_idx)
# store consumption dataset
out_storage = StorageCreator().build_storage(type="flt",
location=cache_directory)
consumption.write_dataset(attributes=consumption.get_known_attribute_names(),
out_storage=out_storage,
