def households_transition(households, annual_household_control_totals, year):
ct = annual_household_control_totals.to_frame()
tran = transition.TabularTotalsTransition(ct, 'total_number_of_households')
model = transition.TransitionModel(tran)
hh = households.to_frame(households.local_columns + ['activity_id'])
new, added_hh_idx, empty_dict = \
model.transition(hh, year,)
new.loc[added_hh_idx, "building_id"] = -1
orca.add_table("households", new)
def full_transition(agents,
agent_controls,
year,
settings,
location_fname,
linked_tables=None):
"""
Run a transition model based on control totals specified in the usual
UrbanSim way
Parameters
----------
agents : DataFrameWrapper
Table to be transitioned
agent_controls : DataFrameWrapper
Table of control totals
year : int
The year, which will index into the controls
settings : dict
Contains the configuration for the transition model - is specified
down to the yaml level with a "total_column" which specifies the
control total and an "add_columns" param which specified which
columns to add when calling to_frame (should be a list of the columns
needed to do the transition
location_fname : str
The field name in the resulting dataframe to set to -1 (to unplace
new agents)
linked_tables : dict of tuple, optional
Dictionary of table_name: (table, 'column name') pairs. The column name
should match the index of `agents`. Indexes in `agents` that
are copied or removed will also be copied and removed in
linked tables.
Returns
-------
Nothing
"""
ct = agent_controls.to_frame()
hh = agents.to_frame(agents.local_columns +
settings.get('add_columns', []))
print "Total agents before transition: {}".format(len(hh))
linked_tables = linked_tables or {}
for table_name, (table, col) in linked_tables.iteritems():
print "Total %s before transition: %s" % (table_name, len(table))
tran = transition.TabularTotalsTransition(ct, settings['total_column'])
model = transition.TransitionModel(tran)
new, added_hh_idx, new_linked = model.transition(
hh, year, linked_tables=linked_tables)
new.loc[added_hh_idx, location_fname] = -1
print "Total agents after transition: {}".format(len(new))
orca.add_table(agents.name, new)
for table_name, table in new_linked.iteritems():
print "Total %s after transition: %s" % (table_name, len(table))
orca.add_table(table_name, table)
def full_transition(agents, agent_controls, year, settings, location_fname):
"""
Run a transition model based on control totals specified in the usual
UrbanSim way
Parameters
----------
agents : DataFrameWrapper
Table to be transitioned
agent_controls : DataFrameWrapper
Table of control totals
year : int
The year, which will index into the controls
settings : dict
Contains the configuration for the transition model - is specified
down to the yaml level with a "total_column" which specifies the
control total and an "add_columns" param which specified which
columns to add when calling to_frame (should be a list of the columns
needed to do the transition
location_fname : str
The field name in the resulting dataframe to set to -1 (to unplace
new agents)
Returns
-------
Nothing
"""
ct = agent_controls.to_frame()
hh = agents.to_frame(agents.local_columns + settings['add_columns'])
print "Total agents before transition: {}".format(len(hh))
tran = transition.TabularTotalsTransition(ct, settings['total_column'])
model = transition.TransitionModel(tran)
new, added_hh_idx, new_linked = model.transition(hh, year)
new.loc[added_hh_idx, location_fname] = -1
print "Total agents after transition: {}".format(len(new))
orca.add_table(agents.name, new)