'db_input_database':'psrc',
'db_output_database':None,
'cache_directory':cache_directory,
'base_year':2000,
'tables_to_cache':[
'gridcells',
# 'households',
# 'jobs',
]})
#CacheScenarioDatabase().run(gridcell_config)
# step 2 cache water demand data by
dbcon = ScenarioDatabase(database_name = "water_demand_seattle2")
print "Create Storage object."
from opus_core.storage_factory import StorageFactory
storage = StorageFactory().get_storage(type="mysql_storage", storage_location=dbcon)
from waterdemand.datasets.consumption_dataset import ConsumptionDataset
consumption_types = ['wrmr', 'wcsr', 'wrsr'] #'wcmr'
for consumption_type in consumption_types:
consumption = ConsumptionDataset(in_storage = storage, in_table_name=consumption_type+'_grid')
for year in range(1990, 2001):
print "%s %s" % (consumption_type, year)
year_index = where(consumption.get_attribute("billyear") == year)
out_storage = StorageFactory().get_storage(type="flt_storage", storage_location=os.path.join(cache_directory, str(year)))
consumption_subset = DatasetSubset(consumption, year_index)
consumption_subset.write_dataset(out_storage=out_storage, out_table_name=consumption_type.lower())
from urbansim.store.scenario_database import ScenarioDatabase
dbcon = ScenarioDatabase(hostname="trondheim.cs.washington.edu",
username="******",
password="******",
database_name="water_demand_seattle")
print "Create Storage object."
from urbansim.storage_creator import StorageCreator
storage = StorageCreator().build_storage(type="mysql", location=dbcon)
consumption_type = "WRSR"
print "Create ConsumptionDataset object"
from waterdemand.datasets.consumption_dataset import ConsumptionDataset
consumption = ConsumptionDataset(in_storage=storage,
in_table_name=consumption_type + "_grid")
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",
from urbansim.store.scenario_database import ScenarioDatabase
dbcon = ScenarioDatabase(hostname = "trondheim.cs.washington.edu",
username = "******",
password = "******",
database_name = "water_demand_seattle")
print "Create Storage object."
from urbansim.storage_creator import StorageCreator
storage = StorageCreator().build_storage(type="mysql", location=dbcon)
consumption_type = "WRSR"
print "Create ConsumptionDataset object"
from waterdemand.datasets.consumption_dataset import ConsumptionDataset
consumption = ConsumptionDataset(in_storage = storage, in_table_name=consumption_type + "_grid")
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)))
]
})
#CacheScenarioDatabase().run(gridcell_config)
# step 2 cache water demand data by
dbcon = ScenarioDatabase(database_name="water_demand_seattle2")
print "Create Storage object."
from opus_core.storage_factory import StorageFactory
storage = StorageFactory().get_storage(type="mysql_storage",
storage_location=dbcon)
from waterdemand.datasets.consumption_dataset import ConsumptionDataset
consumption_types = ['wrmr', 'wcsr', 'wrsr'] #'wcmr'
for consumption_type in consumption_types:
consumption = ConsumptionDataset(in_storage=storage,
in_table_name=consumption_type +
'_grid')
for year in range(1990, 2001):
print "%s %s" % (consumption_type, year)
year_index = where(consumption.get_attribute("billyear") == year)
out_storage = StorageFactory().get_storage(
type="flt_storage",
storage_location=os.path.join(cache_directory, str(year)))
consumption_subset = DatasetSubset(consumption, year_index)
consumption_subset.write_dataset(
out_storage=out_storage,
out_table_name=consumption_type.lower())