def test_multiple_parameter(self):
model = grav.DoublyConstrained(self.dt, 'Origin', 'Destination', 'flows', 'Dij', 'exp')
ss = {'obs_mean_trip_len': 1250.9555521611339,
'pred_mean_trip_len': 1250.9555521684863,
'OD_pairs': 72, 'predicted_flows': 12314322.0,
'avg_dist_trav': 1251.0, 'num_destinations': 9,
'observed_flows': 12314322, 'avg_dist': 1414.0,
'num_origins': 9}
ps = {'beta': {'LL_zero_val': -4.1172103581711941,
'relative_likelihood_stat': 2053596.3814015209,
'standard_error': 4.9177433418433932e-07},
'all_params': {'zero_vals_LL': -4.1172102183395936,
'mle_vals_LL': -4.0338279201692675}}
fs = {'r_squared': 0.89682406680906979,
'srmse': 0.24804939821988789}
es = {'pred_obs_deviance': 0.0314,
'entropy_ratio': 0.8855,
'maximum_entropy': 4.2767,
'max_pred_deviance': 0.2429,
'variance_obs_entropy': 3.667e-08,
'predicted_entropy': 4.0338,
't_stat_entropy': 117.1593,
'max_obs_deviance': 0.2743,
'observed_entropy': 4.0024,
'variance_pred_entropy': 3.516e-08}
sys_stats = stats.sys_stats(model)
self.assertAlmostEqual(model.system_stats['obs_mean_trip_len'], ss['obs_mean_trip_len'], 4)
self.assertAlmostEqual(model.system_stats['pred_mean_trip_len'], ss['pred_mean_trip_len'], 4)
self.assertAlmostEqual(model.system_stats['OD_pairs'], ss['OD_pairs'])
self.assertAlmostEqual(model.system_stats['predicted_flows'], ss['predicted_flows'])
self.assertAlmostEqual(model.system_stats['avg_dist_trav'], ss['avg_dist_trav'])
self.assertAlmostEqual(model.system_stats['num_destinations'], ss['num_destinations'])
self.assertAlmostEqual(model.system_stats['observed_flows'], ss['observed_flows'])
self.assertAlmostEqual(model.system_stats['avg_dist'], ss['avg_dist'], 4)
self.assertAlmostEqual(model.system_stats['num_origins'], ss['num_origins'])
param_stats = stats.param_stats(model)
self.assertAlmostEqual(model.parameter_stats['beta']['LL_zero_val'], ps['beta']['LL_zero_val'], 4)
self.assertAlmostEqual(model.parameter_stats['beta']['relative_likelihood_stat'],
ps['beta']['relative_likelihood_stat'], 4)
self.assertAlmostEqual(model.parameter_stats['beta']['standard_error'], ps['beta']['standard_error'], 4)
self.assertAlmostEqual(model.parameter_stats['all_params']['zero_vals_LL'], ps['all_params']['zero_vals_LL'], 4)
self.assertAlmostEqual(model.parameter_stats['all_params']['mle_vals_LL'], ps['all_params']['mle_vals_LL'], 4)
fit_stats = stats.fit_stats(model)
self.assertAlmostEqual(model.fit_stats['r_squared'], fs['r_squared'], 4)
self.assertAlmostEqual(model.fit_stats['srmse'], fs['srmse'], 4)
ent_stats = stats.ent_stats(model)
self.assertAlmostEqual(model.entropy_stats['pred_obs_deviance'], es['pred_obs_deviance'], 4)
self.assertAlmostEqual(model.entropy_stats['entropy_ratio'], es['entropy_ratio'], 4)
self.assertAlmostEqual(model.entropy_stats['maximum_entropy'], es['maximum_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['max_pred_deviance'], es['max_pred_deviance'], 4)
self.assertAlmostEqual(model.entropy_stats['variance_obs_entropy'], es['variance_obs_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['predicted_entropy'], es['predicted_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['t_stat_entropy'], es['t_stat_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['max_obs_deviance'], es['max_obs_deviance'], 4)
self.assertAlmostEqual(model.entropy_stats['observed_entropy'], es['observed_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['variance_pred_entropy'], es['variance_pred_entropy'], 4)
def test_single_parameter(self):
model = grav.ProductionConstrained(self.dt, 'origins', 'destinations', 'flows',
['pop'], 'Dij', 'pow')
ss = {'obs_mean_trip_len': 736.52834197296534,
'pred_mean_trip_len': 734.40974204773784,
'OD_pairs': 24,
'predicted_flows': 242873.00000000003,
'avg_dist_trav': 737.0,
'num_destinations': 24,
'observed_flows': 242873,
'avg_dist': 851.0,
'num_origins': 1}
ps = {'beta': {'LL_zero_val': -3.057415839736517,
'relative_likelihood_stat': 24833.721614296166,
'standard_error': 0.0052734418614330883},
'all_params': {'zero_vals_LL': -3.1780538303479453,
'mle_vals_LL': -3.0062909275101761},
'pop': {'LL_zero_val': -3.1773474269437778,
'relative_likelihood_stat': 83090.010373874276,
'standard_error': 0.0027673052892085684}}
fs = {'r_squared': 0.60516003720997413,
'srmse': 0.57873206718148507}
es = {'pred_obs_deviance': 0.1327,
'entropy_ratio': 0.5642,
'maximum_entropy': 3.1781,
'max_pred_deviance': 0.1718,
'variance_obs_entropy': 2.55421e-06,
'predicted_entropy': 3.0063,
't_stat_entropy': 66.7614,
'max_obs_deviance': 0.3045,
'observed_entropy': 2.8736,
'variance_pred_entropy': 1.39664e-06}
sys_stats = stats.sys_stats(model)
self.assertAlmostEqual(model.system_stats['obs_mean_trip_len'], ss['obs_mean_trip_len'], 4)
self.assertAlmostEqual(model.system_stats['pred_mean_trip_len'], ss['pred_mean_trip_len'], 4)
self.assertAlmostEqual(model.system_stats['OD_pairs'], ss['OD_pairs'])
self.assertAlmostEqual(model.system_stats['predicted_flows'], ss['predicted_flows'])
self.assertAlmostEqual(model.system_stats['avg_dist_trav'], ss['avg_dist_trav'])
self.assertAlmostEqual(model.system_stats['num_destinations'], ss['num_destinations'])
self.assertAlmostEqual(model.system_stats['observed_flows'], ss['observed_flows'])
self.assertAlmostEqual(model.system_stats['avg_dist'], ss['avg_dist'], 4)
self.assertAlmostEqual(model.system_stats['num_origins'], ss['num_origins'])
param_stats = stats.param_stats(model)
self.assertAlmostEqual(model.parameter_stats['beta']['LL_zero_val'], ps['beta']['LL_zero_val'], 4)
self.assertAlmostEqual(model.parameter_stats['beta']['relative_likelihood_stat'],
ps['beta']['relative_likelihood_stat'], 4)
self.assertAlmostEqual(model.parameter_stats['beta']['standard_error'], ps['beta']['standard_error'], 4)
self.assertAlmostEqual(model.parameter_stats['pop']['LL_zero_val'], ps['pop']['LL_zero_val'], 4)
self.assertAlmostEqual(model.parameter_stats['pop']['relative_likelihood_stat'],
ps['pop']['relative_likelihood_stat'], 4)
self.assertAlmostEqual(model.parameter_stats['pop']['standard_error'], ps['pop']['standard_error'], 4)
self.assertAlmostEqual(model.parameter_stats['all_params']['zero_vals_LL'], ps['all_params']['zero_vals_LL'], 4)
self.assertAlmostEqual(model.parameter_stats['all_params']['mle_vals_LL'], ps['all_params']['mle_vals_LL'], 4)
fit_stats = stats.fit_stats(model)
self.assertAlmostEqual(model.fit_stats['r_squared'], fs['r_squared'], 4)
self.assertAlmostEqual(model.fit_stats['srmse'], fs['srmse'], 4)
ent_stats = stats.ent_stats(model)
self.assertAlmostEqual(model.entropy_stats['pred_obs_deviance'], es['pred_obs_deviance'], 4)
self.assertAlmostEqual(model.entropy_stats['entropy_ratio'], es['entropy_ratio'], 4)
self.assertAlmostEqual(model.entropy_stats['maximum_entropy'], es['maximum_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['max_pred_deviance'], es['max_pred_deviance'], 4)
self.assertAlmostEqual(model.entropy_stats['variance_obs_entropy'], es['variance_obs_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['predicted_entropy'], es['predicted_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['t_stat_entropy'], es['t_stat_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['max_obs_deviance'], es['max_obs_deviance'], 4)
self.assertAlmostEqual(model.entropy_stats['observed_entropy'], es['observed_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['variance_pred_entropy'], es['variance_pred_entropy'], 4)
def test_single_parameter(self):
model = grav.ProductionConstrained(self.dt, 'origins', 'destinations',
'flows', ['pop'], 'Dij', 'pow')
ss = {
'obs_mean_trip_len': 736.52834197296534,
'pred_mean_trip_len': 734.40974204773784,
'OD_pairs': 24,
'predicted_flows': 242873.00000000003,
'avg_dist_trav': 737.0,
'num_destinations': 24,
'observed_flows': 242873,
'avg_dist': 851.0,
'num_origins': 1
}
ps = {
'beta': {
'LL_zero_val': -3.057415839736517,
'relative_likelihood_stat': 24833.721614296166,
'standard_error': 0.0052734418614330883
},
'all_params': {
'zero_vals_LL': -3.1780538303479453,
'mle_vals_LL': -3.0062909275101761
},
'pop': {
'LL_zero_val': -3.1773474269437778,
'relative_likelihood_stat': 83090.010373874276,
'standard_error': 0.0027673052892085684
}
}
fs = {'r_squared': 0.60516003720997413, 'srmse': 0.57873206718148507}
es = {
'pred_obs_deviance': 0.1327,
'entropy_ratio': 0.5642,
'maximum_entropy': 3.1781,
'max_pred_deviance': 0.1718,
'variance_obs_entropy': 2.55421e-06,
'predicted_entropy': 3.0063,
't_stat_entropy': 66.7614,
'max_obs_deviance': 0.3045,
'observed_entropy': 2.8736,
'variance_pred_entropy': 1.39664e-06
}
sys_stats = stats.sys_stats(model)
self.assertAlmostEqual(model.system_stats['obs_mean_trip_len'],
ss['obs_mean_trip_len'], 4)
self.assertAlmostEqual(model.system_stats['pred_mean_trip_len'],
ss['pred_mean_trip_len'], 4)
self.assertAlmostEqual(model.system_stats['OD_pairs'], ss['OD_pairs'])
self.assertAlmostEqual(model.system_stats['predicted_flows'],
ss['predicted_flows'])
self.assertAlmostEqual(model.system_stats['avg_dist_trav'],
ss['avg_dist_trav'])
self.assertAlmostEqual(model.system_stats['num_destinations'],
ss['num_destinations'])
self.assertAlmostEqual(model.system_stats['observed_flows'],
ss['observed_flows'])
self.assertAlmostEqual(model.system_stats['avg_dist'], ss['avg_dist'],
4)
self.assertAlmostEqual(model.system_stats['num_origins'],
ss['num_origins'])
param_stats = stats.param_stats(model)
self.assertAlmostEqual(model.parameter_stats['beta']['LL_zero_val'],
ps['beta']['LL_zero_val'], 4)
self.assertAlmostEqual(
model.parameter_stats['beta']['relative_likelihood_stat'],
ps['beta']['relative_likelihood_stat'], 4)
self.assertAlmostEqual(model.parameter_stats['beta']['standard_error'],
ps['beta']['standard_error'], 4)
self.assertAlmostEqual(model.parameter_stats['pop']['LL_zero_val'],
ps['pop']['LL_zero_val'], 4)
self.assertAlmostEqual(
model.parameter_stats['pop']['relative_likelihood_stat'],
ps['pop']['relative_likelihood_stat'], 4)
self.assertAlmostEqual(model.parameter_stats['pop']['standard_error'],
ps['pop']['standard_error'], 4)
self.assertAlmostEqual(
model.parameter_stats['all_params']['zero_vals_LL'],
ps['all_params']['zero_vals_LL'], 4)
self.assertAlmostEqual(
model.parameter_stats['all_params']['mle_vals_LL'],
ps['all_params']['mle_vals_LL'], 4)
fit_stats = stats.fit_stats(model)
self.assertAlmostEqual(model.fit_stats['r_squared'], fs['r_squared'],
4)
self.assertAlmostEqual(model.fit_stats['srmse'], fs['srmse'], 4)
ent_stats = stats.ent_stats(model)
self.assertAlmostEqual(model.entropy_stats['pred_obs_deviance'],
es['pred_obs_deviance'], 4)
self.assertAlmostEqual(model.entropy_stats['entropy_ratio'],
es['entropy_ratio'], 4)
self.assertAlmostEqual(model.entropy_stats['maximum_entropy'],
es['maximum_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['max_pred_deviance'],
es['max_pred_deviance'], 4)
self.assertAlmostEqual(model.entropy_stats['variance_obs_entropy'],
es['variance_obs_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['predicted_entropy'],
es['predicted_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['t_stat_entropy'],
es['t_stat_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['max_obs_deviance'],
es['max_obs_deviance'], 4)
self.assertAlmostEqual(model.entropy_stats['observed_entropy'],
es['observed_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['variance_pred_entropy'],
es['variance_pred_entropy'], 4)
def test_multiple_parameter(self):
model = grav.DoublyConstrained(self.dt, 'Origin', 'Destination',
'flows', 'Dij', 'exp')
ss = {
'obs_mean_trip_len': 1250.9555521611339,
'pred_mean_trip_len': 1250.9555521684863,
'OD_pairs': 72,
'predicted_flows': 12314322.0,
'avg_dist_trav': 1251.0,
'num_destinations': 9,
'observed_flows': 12314322,
'avg_dist': 1414.0,
'num_origins': 9
}
ps = {
'beta': {
'LL_zero_val': -4.1172103581711941,
'relative_likelihood_stat': 2053596.3814015209,
'standard_error': 4.9177433418433932e-07
},
'all_params': {
'zero_vals_LL': -4.1172102183395936,
'mle_vals_LL': -4.0338279201692675
}
}
fs = {'r_squared': 0.89682406680906979, 'srmse': 0.24804939821988789}
es = {
'pred_obs_deviance': 0.0314,
'entropy_ratio': 0.8855,
'maximum_entropy': 4.2767,
'max_pred_deviance': 0.2429,
'variance_obs_entropy': 3.667e-08,
'predicted_entropy': 4.0338,
't_stat_entropy': 117.1593,
'max_obs_deviance': 0.2743,
'observed_entropy': 4.0024,
'variance_pred_entropy': 3.516e-08
}
sys_stats = stats.sys_stats(model)
self.assertAlmostEqual(model.system_stats['obs_mean_trip_len'],
ss['obs_mean_trip_len'], 4)
self.assertAlmostEqual(model.system_stats['pred_mean_trip_len'],
ss['pred_mean_trip_len'], 4)
self.assertAlmostEqual(model.system_stats['OD_pairs'], ss['OD_pairs'])
self.assertAlmostEqual(model.system_stats['predicted_flows'],
ss['predicted_flows'])
self.assertAlmostEqual(model.system_stats['avg_dist_trav'],
ss['avg_dist_trav'])
self.assertAlmostEqual(model.system_stats['num_destinations'],
ss['num_destinations'])
self.assertAlmostEqual(model.system_stats['observed_flows'],
ss['observed_flows'])
self.assertAlmostEqual(model.system_stats['avg_dist'], ss['avg_dist'],
4)
self.assertAlmostEqual(model.system_stats['num_origins'],
ss['num_origins'])
param_stats = stats.param_stats(model)
self.assertAlmostEqual(model.parameter_stats['beta']['LL_zero_val'],
ps['beta']['LL_zero_val'], 4)
self.assertAlmostEqual(
model.parameter_stats['beta']['relative_likelihood_stat'],
ps['beta']['relative_likelihood_stat'], 4)
self.assertAlmostEqual(model.parameter_stats['beta']['standard_error'],
ps['beta']['standard_error'], 4)
self.assertAlmostEqual(
model.parameter_stats['all_params']['zero_vals_LL'],
ps['all_params']['zero_vals_LL'], 4)
self.assertAlmostEqual(
model.parameter_stats['all_params']['mle_vals_LL'],
ps['all_params']['mle_vals_LL'], 4)
fit_stats = stats.fit_stats(model)
self.assertAlmostEqual(model.fit_stats['r_squared'], fs['r_squared'],
4)
self.assertAlmostEqual(model.fit_stats['srmse'], fs['srmse'], 4)
ent_stats = stats.ent_stats(model)
self.assertAlmostEqual(model.entropy_stats['pred_obs_deviance'],
es['pred_obs_deviance'], 4)
self.assertAlmostEqual(model.entropy_stats['entropy_ratio'],
es['entropy_ratio'], 4)
self.assertAlmostEqual(model.entropy_stats['maximum_entropy'],
es['maximum_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['max_pred_deviance'],
es['max_pred_deviance'], 4)
self.assertAlmostEqual(model.entropy_stats['variance_obs_entropy'],
es['variance_obs_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['predicted_entropy'],
es['predicted_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['t_stat_entropy'],
es['t_stat_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['max_obs_deviance'],
es['max_obs_deviance'], 4)
self.assertAlmostEqual(model.entropy_stats['observed_entropy'],
es['observed_entropy'], 4)
self.assertAlmostEqual(model.entropy_stats['variance_pred_entropy'],
es['variance_pred_entropy'], 4)