# (0) Init:
rand_seed = 1928
pragma_live_info = True
pragma_live_info_ts = False
fpath_db_in = os.path.join(os.path.dirname(__file__), '..', '..', '..', 'data',
'allegheny-county', 'allegheny-students.sqlite3')
# ----------------------------------------------------------------------------------------------------------------------
# (1) Sites:
sites = Simulation.gen_sites_from_db(
fpath_db_in,
lambda fpath_db:
{'school': Site.gen_from_db(fpath_db, 'schools', 'sp_id', 'school', [])},
pragma_live_info=pragma_live_info,
pragma_live_info_ts=pragma_live_info_ts)
site_home = Site('home')
# ----------------------------------------------------------------------------------------------------------------------
# (2) Probes:
# n_schools = 8
# few_schools = [sites['school'][k] for k in list(sites['school'].keys())[:n_schools]]
#
# probe_grp_size_few_schools = GroupSizeProbe('school', [GroupQry(rel={ Site.AT: s }) for s in few_schools], msg_mode=ProbeMsgMode.DISP)
fpath_db = os.path.join(os.path.dirname(__file__), 'out-test-03c.sqlite3')
os.remove(fpath_sites)
if do_remove_file_groups and os.path.isfile(fpath_groups):
os.remove(fpath_groups)
# ----------------------------------------------------------------------------------------------------------------------
# (1) Sites:
sites = Simulation.gen_sites_from_db(
fpath_db_in, lambda fpath_db: {
'hosp':
Site.gen_from_db(fpath_db, 'hospitals', 'hosp_id', 'hospital',
['workers', 'physicians', 'beds']),
'home_gq':
Site.gen_from_db(fpath_db, 'gq', 'sp_id', 'home',
['gq_type', 'persons']),
'home':
Site.gen_from_db(fpath_db, 'households', 'sp_id', 'home',
['hh_income']),
'school':
Site.gen_from_db(fpath_db, 'schools', 'sp_id', 'school', []),
'work':
Site.gen_from_db(fpath_db, 'workplaces', 'sp_id', 'work', [])
}, fpath_sites)
site_home = Site('home')
# ----------------------------------------------------------------------------------------------------------------------
# (2) Probes:
fpath_db_out = os.path.join(os.path.dirname(__file__), 'out.sqlite3')