Note
Go to the end to download the full example code.
Combine many specifications: assisted specification algorithm¶
We combine many specifications, defined in Combination of many specifications. This leads to a total of 432 specifications. The algorithm implemented in the AssistedSpecification object is used to investigate some of these specifications. See Bierlaire and Ortelli (2023).
Michel Bierlaire, EPFL Sun Apr 27 2025, 15:59:08
from IPython.core.display_functions import display
import biogeme.biogeme_logging as blog
from biogeme.assisted import AssistedSpecification
from biogeme.biogeme import BIOGEME
from biogeme.multiobjectives import loglikelihood_dimension
from biogeme.results_processing import EstimationResults, compile_estimation_results
from everything_spec import database, model_catalog
logger = blog.get_screen_logger(level=blog.INFO)
logger.info('Example b07everything_assisted')
PARETO_FILE_NAME = 'b07everything_assisted.pareto'
Example b07everything_assisted
Function verifying that the estimation results are valid.
def validity(results: EstimationResults) -> tuple[bool, str | None]:
"""Function verifying that the estimation results are valid.
The results are not valid if any of the time or cost coefficient is non-negative.
"""
for parameter_index, parameter_name in enumerate(results.beta_names):
parameter_value = results.beta_values[parameter_index]
if 'TIME' in parameter_name and parameter_value >= 0:
return False, f'{parameter_name} = {parameter_value}'
if 'COST' in parameter_name and parameter_value >= 0:
return False, f'{parameter_name} = {parameter_value}'
return True, None
Create the Biogeme object
the_biogeme = BIOGEME(database, model_catalog, generate_html=False, generate_yaml=False)
the_biogeme.model_name = 'b07everything'
Biogeme parameters read from biogeme.toml.
Estimate the parameters using assisted specification algorithm.
assisted_specification = AssistedSpecification(
biogeme_object=the_biogeme,
multi_objectives=loglikelihood_dimension,
pareto_file_name=PARETO_FILE_NAME,
validity=validity,
)
non_dominated_models = assisted_specification.run()
Biogeme parameters read from biogeme.toml.
Pareto set initialized from file with 418 elements [14 Pareto] and 1 invalid elements.
Biogeme parameters read from biogeme.toml.
Model with 4 unknown parameters [max: 50]
*** Estimate b07everything_000000
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time b_cost asc_car Function Relgrad Radius Rho
0 -0.76 -0.77 -0.7 -0.29 8.8e+03 0.04 10 1.1 ++
1 -0.66 -1.2 -0.77 -0.0015 8.7e+03 0.0064 1e+02 1.1 ++
2 -0.65 -1.3 -0.79 0.016 8.7e+03 0.00012 1e+03 1 ++
3 -0.65 -1.3 -0.79 0.016 8.7e+03 4e-08 1e+03 1 ++
default_specification=asc:no_seg;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:logit;train_tt_catalog:linear
The number of possible specifications [432] exceeds the maximum number [100]. A heuristic algorithm is applied.
*** VNS ***
asc:no_seg;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:logit;train_tt_catalog:linear [8670.163118523758, 4]
Initial pareto: 14
Attempt 0/100
Biogeme parameters read from biogeme.toml.
Model with 16 unknown parameters [max: 50]
*** Estimate b07everything_000001
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.22 0.5 -0.0059 -
1 9.5e+03 0.17 0.5 0.49 +
2 8.9e+03 0.066 0.5 0.81 +
3 8.3e+03 0.016 5 0.96 ++
4 8.3e+03 0.016 0.89 -1.7 -
5 8.3e+03 0.036 0.89 0.64 +
6 8.2e+03 0.028 0.89 0.43 +
7 8.2e+03 0.004 8.9 1.1 ++
8 8.2e+03 0.0026 89 1.1 ++
9 8.2e+03 0.00024 8.9e+02 1 ++
10 8.2e+03 3.8e-07 8.9e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 1/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000002
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train lambda_travel_t b_cost_train mu_public b_time_swissmet b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1.1e+04 0.22 0.5 -0.02 -
1 -0.48 -0.2 -0.011 -0.39 1.1 -0.45 1.5 -0.2 0.35 -0.081 -0.089 -0.0075 -0.16 -0.13 9.6e+03 0.17 0.5 0.48 +
2 -0.34 0.059 -0.0025 -0.42 1.1 -0.42 1.4 -0.35 -0.15 -0.17 -0.18 -0.02 -0.28 -0.23 9e+03 0.071 0.5 0.79 +
3 -0.47 0.42 0.029 -0.81 1.1 -0.92 1.8 -0.81 -0.62 -0.32 -0.25 -0.06 -0.62 -0.46 8.5e+03 0.016 5 0.99 ++
4 -0.47 0.42 0.029 -0.81 1.1 -0.92 1.8 -0.81 -0.62 -0.32 -0.25 -0.06 -0.62 -0.46 8.5e+03 0.016 0.7 -0.3 -
5 -0.066 0.42 0.38 -1.2 0.45 -1.6 1.9 -1.3 -0.94 -0.46 -0.074 -0.19 -1 -0.67 8.4e+03 0.018 0.7 0.87 +
6 -0.1 0.52 0.31 -1.6 0.35 -1.4 1.2 -1.5 -0.71 -0.046 -0.25 -0.34 -1.3 -0.54 8.3e+03 0.026 0.7 0.61 +
7 -0.15 0.63 0.48 -2 0.28 -1.6 1.1 -1.6 -0.78 0.048 -0.14 -0.56 -1.4 -0.73 8.3e+03 0.0069 7 1.2 ++
8 -0.21 0.63 0.48 -2.1 0.28 -1.7 1 -1.6 -0.75 0.074 -0.13 -0.56 -1.4 -0.71 8.3e+03 0.0046 70 1.2 ++
9 -0.22 0.63 0.48 -2.1 0.27 -1.7 1 -1.6 -0.74 0.077 -0.13 -0.56 -1.4 -0.71 8.3e+03 0.0024 7e+02 1 ++
10 -0.22 0.75 0.57 -2.3 0.17 -1.7 1 -1.7 -0.77 0.16 -0.13 -0.58 -1.5 -0.78 8.3e+03 0.00053 7e+03 1 ++
11 -0.22 0.75 0.57 -2.3 0.17 -1.7 1 -1.7 -0.77 0.16 -0.13 -0.58 -1.5 -0.78 8.3e+03 2.5e-06 7e+03 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000003
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost mu_public asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.78 -0.33 -0.016 -1 -0.11 1.1 -0.24 1.5 -0.074 -0.1 -0.0096 9.5e+03 0.12 1 0.43 +
1 -0.41 0.67 0.014 -1.2 -0.12 0.96 -1.1 1.6 -0.22 -0.33 -0.05 8.9e+03 0.1 1 0.51 +
2 -0.36 0.41 0.66 -1.2 -0.42 0.41 -0.53 2 0.021 -0.15 -0.62 8.6e+03 0.025 1 0.71 +
3 -0.74 0.55 0.39 -1.3 -0.26 0.63 -0.67 1 0.061 -0.13 -0.62 8.6e+03 0.034 1 0.21 +
4 -0.99 0.83 0.8 -1.6 -0.4 0.46 -0.76 1.1 0.16 -0.1 -0.59 8.5e+03 0.0019 10 1 ++
5 -1.1 0.89 0.81 -1.6 -0.39 0.5 -0.78 1 0.21 -0.12 -0.6 8.5e+03 0.0013 1e+02 1 ++
6 -1.1 0.89 0.81 -1.6 -0.39 0.5 -0.77 1 0.22 -0.12 -0.6 8.5e+03 0.0007 1e+03 1 ++
7 -1.2 0.97 0.94 -1.6 -0.38 0.49 -0.77 1 0.2 -0.1 -0.59 8.5e+03 4.7e-05 1e+04 1 ++
8 -1.2 0.97 0.94 -1.6 -0.38 0.49 -0.77 1 0.2 -0.1 -0.59 8.5e+03 2.9e-08 1e+04 1 ++
Considering neighbor 1/20 for current solution
Attempt 2/100
Biogeme parameters read from biogeme.toml.
Model with 20 unknown parameters [max: 50]
*** Estimate b07everything_000004
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.56 -
1 1e+04 1.5 0.5 0.2 +
2 1e+04 1.5 0.25 0.2 -
3 1e+04 1.5 0.12 0.2 -
4 1e+04 1.5 0.062 -4.2 -
5 9.9e+03 7.1 0.062 0.48 +
6 9.9e+03 7.1 0.031 0.0017 -
7 9.6e+03 1.2 0.031 0.12 +
8 9.6e+03 1.2 0.016 -0.32 -
9 9.3e+03 0.58 0.16 0.92 ++
10 9.3e+03 0.58 0.078 0.92 -
11 9.3e+03 0.58 0.039 -15 -
12 9.3e+03 0.58 0.02 -16 -
13 9.3e+03 0.58 0.0098 -6.7 -
14 9.3e+03 3.5 0.0098 0.56 +
15 9.3e+03 0.11 0.0098 0.88 +
16 9.2e+03 0.44 0.098 0.97 ++
17 9.1e+03 0.41 0.98 1 ++
18 9.1e+03 0.41 0.49 -0.77 -
19 8.7e+03 10 0.49 0.45 +
20 8.7e+03 10 0.24 0.45 -
21 8.7e+03 10 0.12 0.45 -
22 8.7e+03 10 0.061 0.45 -
23 8.7e+03 10 0.031 0.45 -
24 8.7e+03 10 0.015 0.45 -
25 8.7e+03 10 0.0076 0.45 -
26 8.7e+03 10 0.0038 -1.7 -
27 8.7e+03 10 0.0019 -1.1 -
28 8.7e+03 10 0.00095 -0.63 -
29 8.7e+03 10 0.00048 -0.36 -
30 8.7e+03 10 0.00024 -0.065 -
31 8.7e+03 6.6 0.00024 0.51 +
32 8.7e+03 7.8 0.00024 0.3 +
33 8.7e+03 1.4 0.00024 0.85 +
34 8.7e+03 0.19 0.0024 1 ++
35 8.7e+03 1.2 0.024 1 ++
36 8.6e+03 0.16 0.24 1 ++
37 8.3e+03 0.89 0.24 0.62 +
38 8.2e+03 0.22 2.4 0.98 ++
39 8.1e+03 0.091 24 1.1 ++
40 8.1e+03 0.77 24 0.75 +
41 8e+03 0.5 2.4e+02 1.1 ++
42 8e+03 0.5 1.2e+02 1.1 -
43 8e+03 0.5 60 1.1 -
44 8e+03 0.5 30 1.1 -
45 8e+03 0.5 15 1.1 -
46 8e+03 0.5 7.5 1.1 -
47 8e+03 0.5 3.7 1.1 -
48 8e+03 0.5 1.9 -4.9e+02 -
49 8e+03 0.5 0.93 -2e+02 -
50 8e+03 0.5 0.47 -19 -
51 8e+03 0.5 0.23 -1.2 -
52 8e+03 2.4 0.23 0.72 +
53 8e+03 3.2 2.3 1 ++
54 8e+03 3.2 0.39 -3.9 -
55 8e+03 2.4 0.39 0.47 +
56 8e+03 8.4 3.9 0.94 ++
57 8e+03 0.1 39 1 ++
58 8e+03 0.00059 3.9e+02 1 ++
59 8e+03 9.3e-06 3.9e+03 1 ++
60 8e+03 3.1e-06 3.9e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 3/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000005
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di b_cost mu_public b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.28 -
1 -0.28 -0.12 -0.0055 -0.5 -0.073 -0.11 1.3 0.22 0.065 -0.073 -0.065 -0.0048 -0.18 -0.06 9.3e+03 0.072 0.5 0.77 +
2 -0.3 0.13 0.0064 -0.67 -0.15 -0.61 1.3 -0.21 0.14 -0.11 -0.14 -0.021 -0.32 -0.17 8.8e+03 0.039 5 0.97 ++
3 -0.68 0.69 0.81 -1.2 0.34 -0.66 1.7 -1.3 1.2 -0.55 -0.1 -0.37 -0.88 0.36 8.5e+03 0.04 5 0.89 +
4 -0.68 0.76 0.67 -1.5 0.28 -0.78 1 -1.5 1.2 -0.47 -0.14 -0.39 -0.96 0.34 8.4e+03 0.083 5 0.62 +
5 -0.79 0.77 0.68 -1.7 0.24 -0.76 1 -1.6 1.3 -0.44 -0.09 -0.4 -1.1 0.39 8.4e+03 0.011 50 1.1 ++
6 -0.87 0.91 0.86 -1.8 0.44 -0.8 1 -1.8 1.7 -0.48 -0.1 -0.45 -1.2 0.64 8.4e+03 0.00085 5e+02 1 ++
7 -0.87 0.91 0.86 -1.8 0.44 -0.8 1 -1.8 1.7 -0.48 -0.1 -0.45 -1.2 0.64 8.4e+03 5.4e-06 5e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 4/100
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000006
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train square_tt_coef cube_tt_coef b_cost mu_existing asc_car b_time_car b_time_swissmet Function Relgrad Radius Rho
0 0 0 0 0 0 1 0 0 0 1.1e+04 0.4 0.5 -0.22 -
1 -0.27 -0.5 0.00075 0.0073 -0.039 1.2 0.0075 -0.02 0.2 9.4e+03 0.78 0.5 0.88 +
2 -0.27 -0.5 0.00075 0.0073 -0.039 1.2 0.0075 -0.02 0.2 9.4e+03 0.78 0.25 0.88 -
3 -0.27 -0.5 0.00075 0.0073 -0.039 1.2 0.0075 -0.02 0.2 9.4e+03 0.78 0.12 0.88 -
4 -0.27 -0.5 0.00075 0.0073 -0.039 1.2 0.0075 -0.02 0.2 9.4e+03 0.78 0.062 0.88 -
5 -0.27 -0.5 0.00075 0.0073 -0.039 1.2 0.0075 -0.02 0.2 9.4e+03 0.78 0.031 -15 -
6 -0.27 -0.5 0.00075 0.0073 -0.039 1.2 0.0075 -0.02 0.2 9.4e+03 0.78 0.016 -7 -
7 -0.27 -0.5 0.00075 0.0073 -0.039 1.2 0.0075 -0.02 0.2 9.4e+03 0.78 0.0078 -3 -
8 -0.27 -0.51 -0.0071 -0.0005 -0.046 1.2 -0.0003 -0.028 0.19 9.3e+03 0.12 0.0078 0.87 +
9 -0.27 -0.51 -0.0047 -0.00023 -0.053 1.2 -0.0041 -0.036 0.19 9.3e+03 0.073 0.078 1 ++
10 -0.28 -0.54 0.019 -0.00049 -0.12 1.2 -0.041 -0.11 0.19 9.2e+03 0.58 0.78 0.99 ++
11 -0.3 -0.75 0.15 0.00066 -0.9 1.7 -0.15 -0.51 -0.32 8.8e+03 8.1 0.78 0.58 +
12 -0.3 -0.75 0.15 0.00066 -0.9 1.7 -0.15 -0.51 -0.32 8.8e+03 8.1 0.39 0.58 -
13 -0.3 -0.75 0.15 0.00066 -0.9 1.7 -0.15 -0.51 -0.32 8.8e+03 8.1 0.2 0.58 -
14 -0.3 -0.75 0.15 0.00066 -0.9 1.7 -0.15 -0.51 -0.32 8.8e+03 8.1 0.098 0.58 -
15 -0.3 -0.75 0.15 0.00066 -0.9 1.7 -0.15 -0.51 -0.32 8.8e+03 8.1 0.049 0.58 -
16 -0.3 -0.75 0.15 0.00066 -0.9 1.7 -0.15 -0.51 -0.32 8.8e+03 8.1 0.024 0.58 -
17 -0.3 -0.75 0.15 0.00066 -0.9 1.7 -0.15 -0.51 -0.32 8.8e+03 8.1 0.012 0.58 -
18 -0.3 -0.75 0.15 0.00066 -0.9 1.7 -0.15 -0.51 -0.32 8.8e+03 8.1 0.0061 -2.1 -
19 -0.3 -0.75 0.15 0.00066 -0.9 1.7 -0.15 -0.51 -0.32 8.8e+03 8.1 0.0031 -1.2 -
20 -0.3 -0.75 0.15 0.00066 -0.9 1.7 -0.15 -0.51 -0.32 8.8e+03 8.1 0.0015 -0.069 -
21 -0.3 -0.75 0.15 -0.00087 -0.9 1.7 -0.14 -0.51 -0.32 8.6e+03 2.3 0.015 0.95 ++
22 -0.3 -0.75 0.14 -0.0008 -0.89 1.7 -0.14 -0.5 -0.33 8.6e+03 0.41 0.15 1 ++
23 -0.26 -0.72 0.15 -0.00087 -0.81 1.7 -0.15 -0.47 -0.49 8.5e+03 0.016 1.5 0.97 ++
24 -0.26 -0.72 0.15 -0.00087 -0.81 1.7 -0.15 -0.47 -0.49 8.5e+03 0.016 0.28 -1.1 -
25 -0.22 -0.82 0.13 -0.00078 -0.57 1.9 -0.35 -0.54 -0.77 8.5e+03 0.091 2.8 0.94 ++
26 -0.22 -0.82 0.13 -0.00078 -0.57 1.9 -0.35 -0.54 -0.77 8.5e+03 0.091 1.4 0.94 -
27 -0.22 -0.82 0.13 -0.00078 -0.57 1.9 -0.35 -0.54 -0.77 8.5e+03 0.091 0.7 -1.2e+02 -
28 -0.22 -0.82 0.13 -0.00078 -0.57 1.9 -0.35 -0.54 -0.77 8.5e+03 0.091 0.35 -7.9 -
29 -0.29 -1.1 -0.052 -1.9e-05 -0.75 2.2 -0.39 -0.73 -1 8.4e+03 1.5 0.35 0.74 +
30 -0.095 -1.4 -0.064 8.5e-06 -0.54 2.5 -0.51 -0.85 -1.4 8.3e+03 9.3 3.5 1 ++
31 -0.095 -1.4 -0.064 8.5e-06 -0.54 2.5 -0.51 -0.85 -1.4 8.3e+03 9.3 0.51 -13 -
32 -0.095 -1.4 -0.064 8.5e-06 -0.54 2.5 -0.51 -0.85 -1.4 8.3e+03 9.3 0.25 -1.9 -
33 -0.089 -1.7 -0.12 0.00029 -0.64 2.6 -0.46 -1.1 -1.6 8.3e+03 6.2 0.25 0.29 +
34 -0.089 -1.7 -0.12 0.00029 -0.64 2.6 -0.46 -1.1 -1.6 8.3e+03 6.2 0.12 -0.66 -
35 -0.089 -1.7 -0.12 0.00029 -0.64 2.6 -0.46 -1.1 -1.6 8.3e+03 6.2 0.059 -0.76 -
36 -0.089 -1.7 -0.12 0.00029 -0.64 2.6 -0.46 -1.1 -1.6 8.3e+03 6.2 0.029 -0.88 -
37 -0.089 -1.7 -0.12 0.00029 -0.64 2.6 -0.46 -1.1 -1.6 8.3e+03 6.2 0.015 -0.95 -
38 -0.089 -1.7 -0.12 0.00029 -0.64 2.6 -0.46 -1.1 -1.6 8.3e+03 6.2 0.0074 -0.089 -
39 -0.089 -1.7 -0.11 0.0002 -0.64 2.6 -0.46 -1.1 -1.6 8.3e+03 35 0.0074 0.56 +
40 -0.086 -1.7 -0.1 0.0002 -0.64 2.6 -0.47 -1.1 -1.6 8.3e+03 8.5 0.074 0.93 ++
41 -0.049 -1.7 -0.098 0.00017 -0.56 2.6 -0.48 -1.1 -1.6 8.3e+03 6.3 0.74 0.94 ++
42 0.059 -2 -0.11 0.00021 -0.59 2.6 -0.49 -1.3 -1.9 8.3e+03 9.2 7.4 0.92 ++
43 0.075 -2 -0.11 0.00021 -0.61 2.4 -0.49 -1.3 -1.9 8.3e+03 0.9 74 1 ++
44 0.11 -2 -0.11 0.00021 -0.62 2.4 -0.48 -1.3 -1.9 8.3e+03 0.13 7.4e+02 1 ++
45 0.11 -2 -0.11 0.00021 -0.62 2.3 -0.48 -1.3 -1.9 8.3e+03 0.0058 7.4e+03 0.99 ++
46 0.11 -2.1 -0.11 0.00021 -0.62 2.3 -0.47 -1.3 -1.9 8.3e+03 0.0018 7.4e+04 1 ++
47 0.11 -2.1 -0.11 0.00021 -0.62 2.3 -0.47 -1.3 -1.9 8.3e+03 4.6e-05 7.4e+05 1 ++
48 0.11 -2.1 -0.11 0.00021 -0.62 2.3 -0.47 -1.3 -1.9 8.3e+03 2.5e-05 7.4e+06 1 ++
49 0.11 -2.1 -0.11 0.00021 -0.62 2.3 -0.47 -1.3 -1.9 8.3e+03 5.4e-05 7.4e+07 1 ++
50 0.11 -2.1 -0.11 0.00021 -0.62 2.3 -0.47 -1.3 -1.9 8.3e+03 1e-06 7.4e+07 1 ++
Considering neighbor 0/20 for current solution
Attempt 5/100
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000007
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train b_cost mu_public b_time_swissmet asc_car_ref asc_car_diff_GA b_time_car Function Relgrad Radius Rho
0 0 0 0 0 1 0 0 0 0 1.1e+04 0.4 0.5 -0.18 -
1 -0.28 0.023 -0.5 -0.09 1.2 0.22 -0.049 -0.042 -0.14 9.3e+03 0.056 0.5 0.89 +
2 -0.2 0.52 -0.7 -0.59 1.2 -0.28 0.057 -0.54 -0.21 9.1e+03 0.16 0.5 0.9 +
3 -0.4 0.79 -0.99 -0.6 1.7 -0.49 -0.19 -0.65 -0.62 8.6e+03 0.095 0.5 0.69 +
4 -0.53 0.86 -0.79 -0.7 1.9 -0.99 -0.39 -0.76 -0.89 8.4e+03 0.11 0.5 0.49 +
5 -0.61 0.86 -0.92 -0.69 1.9 -1.1 -0.45 -1.3 -0.85 8.3e+03 0.012 5 1.1 ++
6 -0.61 0.86 -0.92 -0.69 1.9 -1.1 -0.45 -1.3 -0.85 8.3e+03 0.012 0.44 -1.4 -
7 -0.62 1 -1.1 -0.7 1.4 -1.2 -0.46 -1.3 -0.87 8.3e+03 0.022 4.4 0.92 ++
8 -0.79 1.2 -1.3 -0.72 1.2 -1.4 -0.49 -1.2 -0.98 8.3e+03 0.012 44 1.2 ++
9 -0.94 1.4 -1.4 -0.73 1 -1.5 -0.5 -1.1 -1 8.3e+03 0.011 4.4e+02 1.2 ++
10 -0.97 1.5 -1.4 -0.72 1 -1.5 -0.49 -1.1 -1 8.3e+03 0.0013 4.4e+03 1.1 ++
11 -0.97 1.5 -1.4 -0.72 1 -1.5 -0.48 -1.1 -1 8.3e+03 0.0013 4.4e+04 1 ++
12 -1 1.5 -1.4 -0.73 1 -1.5 -0.49 -1.1 -1 8.3e+03 1.4e-05 4.4e+05 1 ++
13 -1 1.5 -1.4 -0.73 1 -1.5 -0.49 -1.1 -1 8.3e+03 3.4e-10 4.4e+05 1 ++
Considering neighbor 0/20 for current solution
Attempt 6/100
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000008
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost_train mu_public b_time_swissmet b_time_swissmet b_cost_swissmet asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1.1e+04 0.22 0.5 0.043 -
1 -0.5 0.026 -0.38 -0.2 1.1 -0.45 1.5 -0.2 -0.11 0.35 -0.072 -0.081 -0.16 -0.11 -0.13 9.4e+03 0.17 0.5 0.54 +
2 -0.38 0.19 -0.38 -0.2 1.1 -0.4 1.4 -0.34 -0.19 -0.15 -0.15 -0.2 -0.26 -0.16 -0.21 8.8e+03 0.05 0.5 0.85 +
3 -0.55 0.64 -0.7 -0.38 1.1 -0.73 1.7 -0.71 -0.4 -0.65 -0.33 -0.46 -0.5 -0.34 -0.41 8.4e+03 0.03 5 1 ++
4 -0.55 0.64 -0.7 -0.38 1.1 -0.73 1.7 -0.71 -0.4 -0.65 -0.33 -0.46 -0.5 -0.34 -0.41 8.4e+03 0.03 2.5 1 -
5 -0.55 0.64 -0.7 -0.38 1.1 -0.73 1.7 -0.71 -0.4 -0.65 -0.33 -0.46 -0.5 -0.34 -0.41 8.4e+03 0.03 1.2 -27 -
6 -0.55 0.64 -0.7 -0.38 1.1 -0.73 1.7 -0.71 -0.4 -0.65 -0.33 -0.46 -0.5 -0.34 -0.41 8.4e+03 0.03 0.62 -0.3 -
7 -0.21 0.82 -0.98 -0.5 0.52 -1.1 1.9 -1.1 -0.4 -0.88 -0.49 -0.82 -0.62 -0.67 -0.58 8.2e+03 0.011 6.2 0.96 ++
8 -0.21 0.82 -0.98 -0.5 0.52 -1.1 1.9 -1.1 -0.4 -0.88 -0.49 -0.82 -0.62 -0.67 -0.58 8.2e+03 0.011 0.45 -0.19 -
9 -0.21 0.9 -1.3 -0.5 0.46 -1.2 1.4 -1.3 -0.3 -0.88 -0.31 -1 -0.9 -0.89 -0.55 8.2e+03 0.012 4.5 0.98 ++
10 -0.33 1.2 -1.7 -0.7 0.25 -1.1 1.1 -1.5 -0.3 -0.84 -0.057 -1 -1.1 -0.87 -0.68 8.1e+03 0.011 45 1.1 ++
11 -0.49 1.3 -1.8 -0.84 0.22 -1 1 -1.6 -0.31 -0.84 0.0029 -0.96 -1.1 -0.88 -0.7 8.1e+03 0.0031 4.5e+02 1.2 ++
12 -0.51 1.3 -1.9 -0.85 0.23 -1.1 1 -1.6 -0.31 -0.83 0.011 -0.96 -1.1 -0.88 -0.69 8.1e+03 0.0015 4.5e+03 1 ++
13 -0.53 1.4 -1.9 -0.9 0.2 -1 1 -1.6 -0.31 -0.84 0.013 -0.95 -1.1 -0.89 -0.71 8.1e+03 3.8e-05 4.5e+04 1 ++
14 -0.53 1.4 -1.9 -0.9 0.2 -1 1 -1.6 -0.31 -0.84 0.013 -0.95 -1.1 -0.89 -0.71 8.1e+03 1.6e-08 4.5e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 7/100
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000009
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train b_cost_train mu_public b_time_swissmet b_cost_swissmet asc_car b_time_car b_cost_car Function Relgrad Radius Rho
0 0 0 0 1 0 0 0 0 0 1.1e+04 0.4 0.5 -0.21 -
1 -0.28 -0.48 -0.28 1.5 0.2 0.22 -0.094 -0.24 -0.13 9.8e+03 0.21 0.5 0.39 +
2 -0.14 -0.34 -0.34 1.6 -0.23 -0.28 -0.2 -0.42 -0.23 9.3e+03 0.25 0.5 0.49 +
3 -0.22 -0.53 -0.76 2.1 -0.57 -0.37 -0.29 -0.58 -0.31 8.7e+03 0.026 5 0.91 ++
4 -0.22 -0.53 -0.76 2.1 -0.57 -0.37 -0.29 -0.58 -0.31 8.7e+03 0.026 2.5 -78 -
5 -0.22 -0.53 -0.76 2.1 -0.57 -0.37 -0.29 -0.58 -0.31 8.7e+03 0.026 1.2 -13 -
6 -0.22 -0.53 -0.76 2.1 -0.57 -0.37 -0.29 -0.58 -0.31 8.7e+03 0.026 0.62 -0.65 -
7 0.059 -0.83 -1.4 2.2 -0.93 -0.8 -0.59 -0.89 -0.49 8.5e+03 0.012 6.2 1 ++
8 0.059 -0.83 -1.4 2.2 -0.93 -0.8 -0.59 -0.89 -0.49 8.5e+03 0.012 0.59 -3.4 -
9 0.042 -1 -1.6 1.6 -1.2 -0.89 -0.71 -0.93 -0.66 8.5e+03 0.027 0.59 0.83 +
10 0.0019 -1.1 -1.6 1.4 -1.3 -0.84 -0.66 -1 -0.63 8.4e+03 0.0086 5.9 1.2 ++
11 -0.013 -1.3 -1.8 1 -1.5 -0.8 -0.63 -1.1 -0.66 8.4e+03 0.026 5.9 0.18 +
12 -0.025 -1.4 -1.8 1 -1.5 -0.79 -0.6 -1.1 -0.66 8.4e+03 0.0019 59 1.1 ++
13 -0.032 -1.4 -1.8 1 -1.5 -0.78 -0.6 -1 -0.65 8.4e+03 0.0014 5.9e+02 1 ++
14 -0.032 -1.4 -1.8 1 -1.5 -0.78 -0.6 -1 -0.65 8.4e+03 3.7e-06 5.9e+02 1 ++
Considering neighbor 0/20 for current solution
Considering neighbor 1/20 for current solution
Attempt 8/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000010
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di b_cost_train b_time_swissmet b_time_swissmet b_cost_swissmet asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho
0 -1 0.89 -0.66 -0.43 -0.67 -0.82 -0.54 -0.7 -0.51 -0.57 -0.49 -0.61 -0.67 8.4e+03 0.081 10 1.1 ++
1 -1.1 1.4 -0.93 -0.64 -0.86 -1 -0.78 -0.82 -0.59 -0.89 -0.72 -0.71 -0.58 8.2e+03 0.018 1e+02 1.1 ++
2 -0.98 1.4 -1 -0.73 -0.96 -1.1 -0.83 -0.83 -0.61 -0.97 -0.73 -0.75 -0.6 8.2e+03 0.002 1e+03 1.1 ++
3 -0.96 1.4 -1.1 -0.75 -0.97 -1.1 -0.84 -0.83 -0.61 -0.98 -0.73 -0.75 -0.6 8.2e+03 4e-05 1e+04 1 ++
4 -0.96 1.4 -1.1 -0.75 -0.97 -1.1 -0.84 -0.83 -0.61 -0.98 -0.73 -0.75 -0.6 8.2e+03 2.1e-08 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 9/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000011
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train_re b_time_train_di lambda_travel_t b_cost_train mu_public b_time_swissmet b_time_swissmet b_cost_swissmet asc_car b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho
0 0 0 0 1 0 1 0 0 0 0 0 0 0 1.1e+04 0.22 0.5 0.031 -
1 -0.5 -0.38 -0.19 1.1 -0.45 1.5 -0.2 -0.11 0.35 -0.073 -0.16 -0.11 -0.13 9.4e+03 0.17 0.5 0.53 +
2 -0.36 -0.38 -0.2 1.1 -0.4 1.4 -0.34 -0.19 -0.15 -0.17 -0.26 -0.16 -0.22 8.9e+03 0.054 0.5 0.83 +
3 -0.35 -0.72 -0.39 1.2 -0.83 1.6 -0.7 -0.41 -0.65 -0.42 -0.52 -0.37 -0.48 8.5e+03 0.022 5 1 ++
4 -0.35 -0.72 -0.39 1.2 -0.83 1.6 -0.7 -0.41 -0.65 -0.42 -0.52 -0.37 -0.48 8.5e+03 0.022 2.5 1 -
5 -0.35 -0.72 -0.39 1.2 -0.83 1.6 -0.7 -0.41 -0.65 -0.42 -0.52 -0.37 -0.48 8.5e+03 0.022 1.2 -21 -
6 -0.35 -0.72 -0.39 1.2 -0.83 1.6 -0.7 -0.41 -0.65 -0.42 -0.52 -0.37 -0.48 8.5e+03 0.022 0.62 -0.88 -
7 0.039 -0.86 -0.43 0.84 -1.5 1.6 -0.86 -0.49 -0.83 -0.48 -0.63 -0.62 -0.53 8.4e+03 0.0044 6.2 1.1 ++
8 0.039 -0.86 -0.43 0.84 -1.5 1.6 -0.86 -0.49 -0.83 -0.48 -0.63 -0.62 -0.53 8.4e+03 0.0044 0.51 0.039 -
9 0.22 -1.3 -0.42 0.33 -1.8 1.5 -1.2 -0.28 -1.1 -0.48 -0.85 -0.99 -0.63 8.3e+03 0.01 5.1 0.94 ++
10 0.22 -1.7 -0.51 0.39 -1.6 1 -1.5 -0.34 -0.84 -0.14 -0.93 -0.88 -0.65 8.3e+03 0.02 5.1 0.58 +
11 0.18 -1.8 -0.58 0.3 -1.8 1 -1.4 -0.3 -0.87 -0.11 -0.98 -0.86 -0.69 8.3e+03 0.0042 51 1.1 ++
12 0.33 -2.1 -0.63 0.14 -1.9 1 -1.6 -0.25 -0.88 -0.0049 -1.1 -0.89 -0.77 8.3e+03 0.0012 5.1e+02 0.93 ++
13 0.32 -2.1 -0.63 0.17 -1.9 1 -1.6 -0.26 -0.88 -0.011 -1.1 -0.88 -0.77 8.3e+03 2.5e-05 5.1e+03 1 ++
14 0.32 -2.1 -0.63 0.17 -1.9 1 -1.6 -0.26 -0.88 -0.011 -1.1 -0.88 -0.77 8.3e+03 2e-08 5.1e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 10/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000012
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_train b_cost mu_public b_time_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_time_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.26 -
1 -0.28 0.032 -0.12 -0.0055 -0.5 -0.11 1.2 0.22 -0.068 -0.049 -0.062 -0.0046 -0.17 9.3e+03 0.063 0.5 0.8 +
2 -0.31 0.39 0.11 0.0057 -0.68 -0.61 1.3 -0.19 -0.099 -0.21 -0.13 -0.02 -0.32 8.7e+03 0.053 5 0.96 ++
3 -0.31 0.39 0.11 0.0057 -0.68 -0.61 1.3 -0.19 -0.099 -0.21 -0.13 -0.02 -0.32 8.7e+03 0.053 0.58 -0.54 -
4 -0.51 0.96 0.31 0.044 -1 -0.7 1.6 -0.78 -0.3 -0.43 -0.2 -0.055 -0.78 8.4e+03 0.038 0.58 0.89 +
5 -0.94 0.82 0.31 0.34 -0.98 -0.68 1.8 -1.3 -0.56 -1 -0.053 -0.23 -0.86 8.3e+03 0.0059 0.58 0.89 +
6 -1 1.1 0.31 0.39 -1.2 -0.65 1.2 -1.3 -0.42 -1.1 -0.081 -0.29 -0.96 8.3e+03 0.035 0.58 0.56 +
7 -1.2 1.2 0.44 0.51 -1.3 -0.72 1.1 -1.4 -0.47 -1.1 -0.054 -0.41 -1 8.2e+03 0.0052 5.8 1.1 ++
8 -1.3 1.3 0.5 0.52 -1.4 -0.72 1 -1.4 -0.45 -1.1 -0.051 -0.41 -1 8.2e+03 0.0057 58 1.1 ++
9 -1.3 1.3 0.51 0.52 -1.4 -0.72 1 -1.4 -0.45 -1.1 -0.047 -0.41 -1 8.2e+03 0.0032 5.8e+02 1 ++
10 -1.4 1.4 0.55 0.63 -1.4 -0.73 1 -1.5 -0.46 -1 -0.047 -0.4 -1 8.2e+03 6.5e-05 5.8e+03 1 ++
11 -1.4 1.4 0.55 0.63 -1.4 -0.73 1 -1.5 -0.46 -1 -0.047 -0.4 -1 8.2e+03 4.7e-08 5.8e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 11/100
Biogeme parameters read from biogeme.toml.
Model with 16 unknown parameters [max: 50]
*** Estimate b07everything_000013
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.45 -
1 1e+04 1.3 0.5 0.28 +
2 1e+04 1.3 0.25 0.28 -
3 1e+04 1.3 0.12 0.28 -
4 1e+04 1.3 0.062 -5.3 -
5 1e+04 1.3 0.031 -0.23 -
6 9.5e+03 0.97 0.031 0.86 +
7 9.5e+03 0.97 0.016 -4.9 -
8 9.3e+03 0.37 0.16 0.93 ++
9 9.3e+03 0.37 0.078 -12 -
10 9.3e+03 0.37 0.039 -9.9 -
11 9.3e+03 0.37 0.02 -8.8 -
12 9.3e+03 0.37 0.0098 -8.5 -
13 9.3e+03 0.37 0.0049 -8.9 -
14 9.3e+03 0.37 0.0024 -2.1 -
15 9.3e+03 0.043 0.0024 0.9 +
16 9.3e+03 0.043 0.0012 0.08 -
17 9.3e+03 0.66 0.0012 0.77 +
18 9.3e+03 0.21 0.012 1.1 ++
19 9.3e+03 0.046 0.12 1 ++
20 9.1e+03 1.3 1.2 0.95 ++
21 9.1e+03 1.3 0.61 0.95 -
22 9.1e+03 1.3 0.31 -6.5 -
23 9.1e+03 1.3 0.15 -5.9 -
24 9.1e+03 1.3 0.076 -5.7 -
25 9.1e+03 1.3 0.038 -5.9 -
26 9.1e+03 1.3 0.019 -6.5 -
27 9.1e+03 1.3 0.0095 -7.4 -
28 9.1e+03 1.3 0.0048 -8.3 -
29 9.1e+03 1.3 0.0024 -4.9 -
30 9.1e+03 1.3 0.0012 -1.6 -
31 9.1e+03 1.3 0.0006 0.065 -
32 9.1e+03 0.27 0.0006 0.87 +
33 9.1e+03 0.045 0.006 1 ++
34 9.1e+03 0.14 0.06 1 ++
35 9e+03 0.21 0.6 1 ++
36 8.6e+03 0.28 0.6 0.41 +
37 8.4e+03 6.4 0.6 0.34 +
38 8.4e+03 15 0.6 0.1 +
39 8.4e+03 15 0.3 0.1 -
40 8.4e+03 15 0.15 0.1 -
41 8.4e+03 15 0.075 0.1 -
42 8.4e+03 15 0.037 0.1 -
43 8.4e+03 15 0.019 0.1 -
44 8.4e+03 15 0.0093 -3.3 -
45 8.4e+03 15 0.0047 -2.5 -
46 8.4e+03 15 0.0023 -2 -
47 8.4e+03 15 0.0012 -1.4 -
48 8.4e+03 15 0.00058 -0.8 -
49 8.4e+03 15 0.00029 -0.25 -
50 8.4e+03 15 0.00015 0.041 -
51 8.4e+03 7.7 0.00015 0.59 +
52 8.4e+03 7.7 7.3e-05 -1.7 -
53 8.4e+03 7.7 3.6e-05 -0.31 -
54 8.4e+03 1.6 3.6e-05 0.7 +
55 8.4e+03 0.18 0.00036 1 ++
56 8.4e+03 2.1 0.0036 1 ++
57 8.4e+03 0.23 0.036 1 ++
58 8.3e+03 0.16 0.36 0.99 ++
59 8.2e+03 15 0.36 0.35 +
60 8.2e+03 1.6 3.6 0.92 ++
61 8.2e+03 1.6 0.44 -0.92 -
62 8.1e+03 0.26 4.4 0.91 ++
63 8.1e+03 7.8 44 1.1 ++
64 8.1e+03 0.16 4.4e+02 1.2 ++
65 8.1e+03 0.034 4.4e+03 1.1 ++
66 8.1e+03 0.055 4.4e+04 1 ++
67 8.1e+03 0.00081 4.4e+05 1 ++
68 8.1e+03 0.00015 4.4e+06 1 ++
69 8.1e+03 1.6e-06 4.4e+06 1 ++
Considering neighbor 0/20 for current solution
Attempt 12/100
Biogeme parameters read from biogeme.toml.
Model with 16 unknown parameters [max: 50]
*** Estimate b07everything_000014
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 9.1e+03 0.26 1 0.68 +
1 9.1e+03 0.26 0.5 -0.37 -
2 8.5e+03 0.13 0.5 0.63 +
3 8.3e+03 0.021 0.5 0.73 +
4 8.3e+03 0.0052 5 1 ++
5 8.2e+03 0.0078 50 0.92 ++
6 8.2e+03 0.0002 5e+02 1 ++
7 8.2e+03 1.9e-07 5e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 13/100
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000015
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time square_tt_coef cube_tt_coef b_cost mu_public asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 0 1.1e+04 0.26 0.5 0.098 -
1 -0.5 0.0011 -0.5 0 0 -0.5 1 0.034 -0.5 9.1e+03 4 5 1 ++
2 -0.5 0.0011 -0.5 0 0 -0.5 1 0.034 -0.5 9.1e+03 4 2.5 1 -
3 -0.5 0.0011 -0.5 0 0 -0.5 1 0.034 -0.5 9.1e+03 4 1.2 1 -
4 -0.5 0.0011 -0.5 0 0 -0.5 1 0.034 -0.5 9.1e+03 4 0.62 -6.6 -
5 -0.5 0.0011 -0.5 0 0 -0.5 1 0.034 -0.5 9.1e+03 4 0.31 -2.3 -
6 -0.5 0.0011 -0.5 0 0 -0.5 1 0.034 -0.5 9.1e+03 4 0.16 -1.2 -
7 -0.5 0.0011 -0.5 0 0 -0.5 1 0.034 -0.5 9.1e+03 4 0.078 -1 -
8 -0.5 0.0011 -0.5 0 0 -0.5 1 0.034 -0.5 9.1e+03 4 0.039 -1.4 -
9 -0.5 0.0011 -0.5 0 0 -0.5 1 0.034 -0.5 9.1e+03 4 0.02 -2.2 -
10 -0.5 0.0011 -0.5 0 0 -0.5 1 0.034 -0.5 9.1e+03 4 0.0098 -3.1 -
11 -0.5 0.0011 -0.5 0 0 -0.5 1 0.034 -0.5 9.1e+03 4 0.0049 -4 -
12 -0.5 0.0011 -0.5 0 0 -0.5 1 0.034 -0.5 9.1e+03 4 0.0024 -4.6 -
13 -0.5 0.0011 -0.5 0 0 -0.5 1 0.034 -0.5 9.1e+03 4 0.0012 -2.5 -
14 -0.5 0.0011 -0.5 0 0 -0.5 1 0.034 -0.5 9.1e+03 4 0.00061 -1.3 -
15 -0.5 0.0011 -0.5 0 0 -0.5 1 0.034 -0.5 9.1e+03 4 0.00031 -0.27 -
16 -0.5 0.0014 -0.5 0.00031 -0.00031 -0.5 1 0.034 -0.5 9.1e+03 3.1 0.00031 0.63 +
17 -0.5 0.0014 -0.5 0.00061 -0.00023 -0.5 1 0.034 -0.5 9.1e+03 1.3 0.00031 0.8 +
18 -0.5 0.0014 -0.5 0.00092 -0.00025 -0.5 1 0.033 -0.5 9.1e+03 0.2 0.0031 0.99 ++
19 -0.5 0.0018 -0.5 0.004 -0.00026 -0.5 1 0.033 -0.5 9.1e+03 0.25 0.031 1 ++
20 -0.52 0.0053 -0.53 0.034 -0.0004 -0.5 1 0.029 -0.5 9e+03 0.36 0.31 1 ++
21 -0.64 0.1 -0.83 0.3 -0.0015 -0.52 1.2 -0.015 -0.54 8.8e+03 2.2 0.31 0.36 +
22 -0.61 0.41 -0.88 0.0091 -0.00025 -0.65 1.2 -0.032 -0.62 8.5e+03 6.6 0.31 0.75 +
23 -0.62 0.71 -1.1 -0.0043 -0.00028 -0.67 1.3 -0.12 -0.69 8.3e+03 5.1 3.1 0.97 ++
24 -0.62 0.71 -1.1 -0.0043 -0.00028 -0.67 1.3 -0.12 -0.69 8.3e+03 5.1 1.5 -1.3e+02 -
25 -0.62 0.71 -1.1 -0.0043 -0.00028 -0.67 1.3 -0.12 -0.69 8.3e+03 5.1 0.76 -38 -
26 -0.62 0.71 -1.1 -0.0043 -0.00028 -0.67 1.3 -0.12 -0.69 8.3e+03 5.1 0.38 -3.1 -
27 -0.62 0.71 -1.1 -0.0043 -0.00028 -0.67 1.3 -0.12 -0.69 8.3e+03 5.1 0.19 0.069 -
28 -0.66 0.9 -1.2 -0.081 0.00026 -0.69 1.5 -0.097 -0.74 8.3e+03 12 0.19 0.47 +
29 -0.66 0.9 -1.2 -0.081 0.00026 -0.69 1.5 -0.097 -0.74 8.3e+03 12 0.095 -3.5 -
30 -0.66 0.9 -1.2 -0.081 0.00026 -0.69 1.5 -0.097 -0.74 8.3e+03 12 0.048 -3.4 -
31 -0.66 0.9 -1.2 -0.081 0.00026 -0.69 1.5 -0.097 -0.74 8.3e+03 12 0.024 -3.3 -
32 -0.66 0.9 -1.2 -0.081 0.00026 -0.69 1.5 -0.097 -0.74 8.3e+03 12 0.012 -3.5 -
33 -0.66 0.9 -1.2 -0.081 0.00026 -0.69 1.5 -0.097 -0.74 8.3e+03 12 0.006 -3.8 -
34 -0.66 0.9 -1.2 -0.081 0.00026 -0.69 1.5 -0.097 -0.74 8.3e+03 12 0.003 -4 -
35 -0.66 0.9 -1.2 -0.081 0.00026 -0.69 1.5 -0.097 -0.74 8.3e+03 12 0.0015 -4.1 -
36 -0.66 0.9 -1.2 -0.081 0.00026 -0.69 1.5 -0.097 -0.74 8.3e+03 12 0.00075 -3.1 -
37 -0.66 0.9 -1.2 -0.081 0.00026 -0.69 1.5 -0.097 -0.74 8.3e+03 12 0.00037 -1.6 -
38 -0.66 0.9 -1.2 -0.081 0.00026 -0.69 1.5 -0.097 -0.74 8.3e+03 12 0.00019 -0.42 -
39 -0.66 0.9 -1.2 -0.081 7.1e-05 -0.69 1.5 -0.097 -0.74 8.3e+03 6.8 0.00019 0.76 +
40 -0.66 0.9 -1.2 -0.081 9.1e-05 -0.69 1.5 -0.097 -0.74 8.3e+03 1.1 0.00019 0.89 +
41 -0.66 0.9 -1.2 -0.08 8.7e-05 -0.69 1.5 -0.097 -0.74 8.3e+03 0.066 0.0019 1 ++
42 -0.66 0.9 -1.2 -0.079 7.9e-05 -0.69 1.5 -0.097 -0.74 8.3e+03 0.17 0.019 1 ++
43 -0.65 0.92 -1.2 -0.061 -2.8e-06 -0.69 1.5 -0.11 -0.75 8.3e+03 0.78 0.19 1 ++
44 -0.59 1.1 -1.4 -0.082 8.4e-05 -0.72 1.5 -0.14 -0.83 8.3e+03 3.6 1.9 0.98 ++
45 -0.72 1.4 -2 -0.12 0.00025 -0.74 1 0.11 -1.2 8.2e+03 4.5 1.9 0.55 +
46 -0.81 1.5 -2.1 -0.1 0.00019 -0.72 1.1 0.15 -1.3 8.2e+03 2.2 19 1 ++
47 -0.92 1.5 -2 -0.1 0.00019 -0.71 1 0.15 -1.3 8.2e+03 0.11 1.9e+02 1 ++
48 -0.92 1.5 -2.1 -0.1 0.00019 -0.71 1 0.15 -1.3 8.2e+03 0.014 1.9e+03 1 ++
49 -0.92 1.6 -2.1 -0.1 0.0002 -0.72 1 0.16 -1.3 8.2e+03 0.016 1.9e+04 1 ++
50 -0.92 1.6 -2.1 -0.1 0.0002 -0.72 1 0.16 -1.3 8.2e+03 0.00014 1.9e+05 1 ++
51 -0.92 1.6 -2.1 -0.1 0.0002 -0.72 1 0.16 -1.3 8.2e+03 3.7e-05 1.9e+06 1 ++
52 -0.92 1.6 -2.1 -0.1 0.0002 -0.72 1 0.16 -1.3 8.2e+03 3e-06 1.9e+06 1 ++
Considering neighbor 0/20 for current solution
Attempt 14/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000016
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train lambda_travel_t b_cost_train b_time_swissmet b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car b_cost_car Function Relgrad Radius Rho
0 -0.95 -0.025 -0.021 -0.78 1.6 -0.61 -1 -0.68 -0.28 -0.4 -0.043 -0.75 -0.54 8.9e+03 0.043 1 0.89 +
1 -0.68 0.79 0.15 -1.1 0.87 -1.6 -1.5 -0.82 -0.29 0.0089 -0.18 -1.2 -0.51 8.4e+03 0.023 10 1.1 ++
2 -0.38 0.76 0.7 -1.7 0.46 -1.7 -1.7 -0.77 0.016 -0.12 -0.53 -1.4 -0.67 8.3e+03 0.014 1e+02 1.2 ++
3 -0.25 0.75 0.59 -2.2 0.24 -1.7 -1.7 -0.77 0.12 -0.13 -0.57 -1.5 -0.75 8.3e+03 0.0038 1e+03 1.1 ++
4 -0.23 0.75 0.57 -2.3 0.17 -1.7 -1.7 -0.77 0.15 -0.13 -0.58 -1.5 -0.78 8.3e+03 0.00023 1e+04 1 ++
5 -0.23 0.75 0.57 -2.3 0.17 -1.7 -1.7 -0.77 0.15 -0.13 -0.58 -1.5 -0.78 8.3e+03 7.3e-07 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 15/100
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000017
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 -0.88 0.32 0.24 -0.57 -0.43 -0.85 -0.74 -0.48 -0.0063 -0.4 -0.53 8.6e+03 0.054 10 1.1 ++
1 -0.77 0.61 0.5 -0.94 -0.55 -1.4 -0.86 -0.41 -0.11 -0.58 -0.36 8.4e+03 0.021 1e+02 1.2 ++
2 -0.77 0.73 0.62 -0.99 -0.61 -1.7 -0.91 -0.45 -0.12 -0.61 -0.34 8.3e+03 0.0037 1e+03 1.1 ++
3 -0.77 0.75 0.63 -0.99 -0.62 -1.8 -0.91 -0.45 -0.12 -0.61 -0.34 8.3e+03 0.00011 1e+04 1 ++
4 -0.77 0.75 0.63 -0.99 -0.62 -1.8 -0.91 -0.45 -0.12 -0.61 -0.34 8.3e+03 1e-07 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 16/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000018
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time lambda_travel_t b_cost mu_public asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.78 0.071 -0.34 -0.016 -1 1.1 -0.23 1.5 -0.068 -0.11 -0.098 -0.0092 9.3e+03 0.11 1 0.47 +
1 -0.48 1.1 0.59 0.012 -1.2 0.94 -1.1 1.8 -0.16 -0.47 -0.28 -0.047 8.8e+03 0.15 1 0.3 +
2 -0.48 1.1 0.59 0.012 -1.2 0.94 -1.1 1.8 -0.16 -0.47 -0.28 -0.047 8.8e+03 0.15 0.5 -0.21 -
3 -0.66 0.74 0.25 0.081 -1 0.44 -0.73 2 -0.077 -0.52 -0.13 -0.071 8.3e+03 0.046 0.5 0.75 +
4 -0.46 0.9 0.14 0.34 -1.4 0.43 -0.75 1.5 -0.0028 -0.95 -0.036 -0.19 8.2e+03 0.0078 5 0.95 ++
5 -0.73 1.1 0.32 0.4 -1.5 0.4 -0.71 1.3 0.12 -1.2 -0.084 -0.49 8.2e+03 0.0049 50 1.2 ++
6 -1 1.3 0.45 0.51 -1.6 0.38 -0.72 1.1 0.18 -1.2 -0.076 -0.5 8.2e+03 0.0046 5e+02 1.2 ++
7 -1.2 1.5 0.53 0.57 -1.6 0.36 -0.72 1 0.2 -1.2 -0.07 -0.49 8.2e+03 0.0015 5e+03 1.2 ++
8 -1.2 1.5 0.53 0.57 -1.7 0.37 -0.71 1 0.21 -1.2 -0.068 -0.49 8.2e+03 0.00082 5e+04 1.1 ++
9 -1.3 1.5 0.54 0.57 -1.7 0.35 -0.72 1 0.21 -1.2 -0.068 -0.49 8.2e+03 0.00026 5e+05 1 ++
10 -1.3 1.5 0.54 0.57 -1.7 0.35 -0.72 1 0.21 -1.2 -0.068 -0.49 8.2e+03 2.2e-06 5e+05 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 18 unknown parameters [max: 50]
*** Estimate b07everything_000019
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.38 -
1 9.9e+03 1.5 0.5 0.35 +
2 9.9e+03 1.5 0.25 0.35 -
3 9.9e+03 1.5 0.12 0.35 -
4 9.9e+03 1.5 0.062 0.35 -
5 9.9e+03 1.5 0.031 -1.9 -
6 9.4e+03 0.78 0.31 0.94 ++
7 9.4e+03 0.78 0.16 0.94 -
8 9.4e+03 0.78 0.078 -6 -
9 9.4e+03 0.78 0.039 -8.8 -
10 9.4e+03 0.78 0.02 -12 -
11 9.4e+03 0.78 0.0098 -15 -
12 9.4e+03 0.78 0.0049 -1.8 -
13 9.3e+03 0.42 0.049 0.98 ++
14 9.3e+03 6.1 0.049 0.51 +
15 9.1e+03 0.93 0.049 0.76 +
16 9.1e+03 0.93 0.024 -1.6 -
17 9.1e+03 0.93 0.012 -2.2 -
18 9.1e+03 0.93 0.0061 -3.2 -
19 9.1e+03 0.93 0.0031 -4.2 -
20 9.1e+03 0.93 0.0015 -3.5 -
21 9.1e+03 2.5 0.0015 0.21 +
22 9.1e+03 0.78 0.015 1.1 ++
23 9.1e+03 0.077 0.15 1 ++
24 8.9e+03 0.82 1.5 0.98 ++
25 8.9e+03 0.82 0.76 -2.5 -
26 8.9e+03 0.82 0.38 -0.9 -
27 8.8e+03 6.7 0.38 0.25 +
28 8.5e+03 0.82 0.38 0.51 +
29 8.4e+03 4.1 0.38 0.58 +
30 8.4e+03 4.1 0.19 0.58 -
31 8.4e+03 4.1 0.095 0.58 -
32 8.4e+03 4.1 0.048 0.58 -
33 8.4e+03 4.1 0.024 -4.7 -
34 8.4e+03 4.1 0.012 -3.1 -
35 8.4e+03 4.1 0.006 -2.1 -
36 8.4e+03 4.1 0.003 -0.98 -
37 8.3e+03 5.6 0.003 0.44 +
38 8.3e+03 1.7 0.03 1.2 ++
39 8.3e+03 2.8 0.3 0.91 ++
40 8.2e+03 4.9 0.3 0.79 +
41 8.2e+03 9 0.3 0.39 +
42 8.2e+03 9 0.15 -5.2 -
43 8.2e+03 9 0.075 -4.5 -
44 8.2e+03 9 0.037 -4.4 -
45 8.2e+03 9 0.019 -4.4 -
46 8.2e+03 9 0.0093 -4.7 -
47 8.2e+03 9 0.0047 -4.9 -
48 8.2e+03 9 0.0023 -4.4 -
49 8.2e+03 9 0.0012 -2.6 -
50 8.2e+03 9 0.00058 -1.4 -
51 8.2e+03 9 0.00029 -0.12 -
52 8.2e+03 1.7 0.00029 0.9 +
53 8.2e+03 0.042 0.0029 0.99 ++
54 8.2e+03 0.034 0.029 1 ++
55 8.2e+03 0.28 0.29 1 ++
56 8.1e+03 0.23 2.9 1.1 ++
57 8.1e+03 0.074 29 1 ++
58 8.1e+03 0.13 2.9e+02 1 ++
59 8.1e+03 2.9 2.9e+03 0.91 ++
60 8.1e+03 0.23 2.9e+04 1 ++
61 8.1e+03 0.0024 2.9e+05 1 ++
62 8.1e+03 3.1e-07 2.9e+05 1 ++
Considering neighbor 1/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 20 unknown parameters [max: 50]
*** Estimate b07everything_000020
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.48 -
1 1e+04 1.4 0.5 0.21 +
2 1e+04 1.4 0.25 0.21 -
3 1e+04 1.4 0.12 0.21 -
4 1e+04 1.4 0.062 -4 -
5 9.6e+03 6.3 0.062 0.75 +
6 9.6e+03 6.3 0.031 -0.27 -
7 9.6e+03 6.3 0.016 0.033 -
8 9.5e+03 1 0.016 0.11 +
9 9.5e+03 1 0.0078 -0.22 -
10 9.4e+03 0.56 0.078 0.98 ++
11 9.4e+03 0.56 0.039 -11 -
12 9.4e+03 0.56 0.02 -13 -
13 9.4e+03 0.56 0.0098 -13 -
14 9.4e+03 0.56 0.0049 -6.9 -
15 9.4e+03 2.8 0.0049 0.6 +
16 9.4e+03 0.19 0.0049 0.79 +
17 9.4e+03 0.81 0.0049 0.83 +
18 9.3e+03 0.22 0.049 1 ++
19 9.3e+03 0.23 0.49 1 ++
20 8.8e+03 5 0.49 0.57 +
21 8.8e+03 5 0.24 0.57 -
22 8.8e+03 5 0.12 0.57 -
23 8.8e+03 5 0.061 0.57 -
24 8.8e+03 5 0.031 -5.6 -
25 8.8e+03 5 0.015 -3.6 -
26 8.8e+03 5 0.0076 -2.4 -
27 8.8e+03 5 0.0038 -0.84 -
28 8.6e+03 5.3 0.0038 0.83 +
29 8.6e+03 5.3 0.0019 -0.79 -
30 8.6e+03 5.3 0.00095 -0.53 -
31 8.6e+03 5.3 0.00048 -0.17 -
32 8.6e+03 4.7 0.00048 0.48 +
33 8.6e+03 4.7 0.00024 -0.43 -
34 8.6e+03 4.9 0.00024 0.21 +
35 8.6e+03 4.9 0.00012 -0.092 -
36 8.6e+03 1.8 0.00012 0.62 +
37 8.6e+03 0.23 0.0012 0.96 ++
38 8.6e+03 0.041 0.012 1 ++
39 8.6e+03 0.17 0.12 1 ++
40 8.5e+03 0.088 1.2 0.96 ++
41 8.5e+03 0.088 0.6 -14 -
42 8.5e+03 0.088 0.3 0.087 -
43 8.4e+03 0.26 0.3 0.78 +
44 8.2e+03 0.32 3 0.9 ++
45 8.2e+03 0.33 3 0.67 +
46 8.2e+03 0.33 0.6 -84 -
47 8.2e+03 0.33 0.3 -4.3 -
48 8.1e+03 0.77 0.3 0.49 +
49 8.1e+03 1 3 1 ++
50 8.1e+03 0.38 3 0.3 +
51 8.1e+03 0.37 30 1.2 ++
52 8.1e+03 0.2 3e+02 1 ++
53 8.1e+03 0.2 2.5 -6.3e+02 -
54 8.1e+03 0.2 1.2 -1.3e+02 -
55 8.1e+03 0.2 0.62 -20 -
56 8.1e+03 0.2 0.31 -1.7 -
57 8.1e+03 1.6 0.31 0.83 +
58 8.1e+03 0.29 3.1 1 ++
59 8.1e+03 0.29 0.37 -1.3 -
60 8.1e+03 3.9 0.37 0.71 +
61 8.1e+03 0.81 3.7 0.98 ++
62 8.1e+03 0.1 37 1 ++
63 8.1e+03 0.00078 3.7e+02 1 ++
64 8.1e+03 1e-05 3.7e+03 1 ++
65 8.1e+03 9.8e-07 3.7e+03 1 ++
Considering neighbor 2/20 for current solution
Attempt 17/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000021
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_train lambda_travel_t b_cost mu_public b_time_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_time_car Function Relgrad Radius Rho
0 -1 0.11 -0.4 -0.022 -0.81 1.2 -0.33 1.7 -0.38 -0.31 -0.17 -0.27 -0.016 -0.41 9.6e+03 0.14 1 0.34 +
1 -0.5 1 0.6 0.0065 -0.62 1.1 -0.86 1.9 -0.9 -0.19 -0.39 -0.13 -0.048 -0.47 9.2e+03 0.24 1 0.17 +
2 -0.5 1 0.6 0.0065 -0.62 1.1 -0.86 1.9 -0.9 -0.19 -0.39 -0.13 -0.048 -0.47 9.2e+03 0.24 0.5 -0.26 -
3 -0.8 0.6 0.18 0.057 -0.54 0.98 -0.69 2.4 -1 -0.48 -0.44 -0.26 -0.066 -0.81 8.8e+03 0.12 0.5 0.39 +
4 -0.3 0.74 0.21 0.22 -0.76 0.68 -0.62 2.8 -0.82 -0.16 -0.59 0.0022 -0.1 -0.62 8.5e+03 0.12 0.5 0.43 +
5 -0.28 0.56 0.15 0.22 -0.89 0.45 -0.61 3 -0.93 -0.17 -1.1 -0.078 -0.21 -0.9 8.4e+03 0.015 0.5 0.89 +
6 -0.35 0.68 0.11 0.17 -0.89 0.51 -0.62 2.5 -0.92 -0.25 -1.2 -0.11 -0.25 -0.91 8.3e+03 0.014 5 0.99 ++
7 -0.35 0.68 0.11 0.17 -0.89 0.51 -0.62 2.5 -0.92 -0.25 -1.2 -0.11 -0.25 -0.91 8.3e+03 0.014 0.74 -1.1 -
8 -0.45 0.78 0.28 0.29 -1.3 0.58 -0.69 1.7 -1.3 -0.12 -1.3 -0.037 -0.32 -1.1 8.3e+03 0.02 7.4 1.1 ++
9 -0.62 1.1 0.38 0.39 -1.8 0.32 -0.74 1.2 -1.6 0.088 -1.1 -0.083 -0.45 -1.4 8.2e+03 0.024 74 0.99 ++
10 -0.83 1.3 0.45 0.47 -2 0.29 -0.73 1.1 -1.7 0.13 -1 -0.083 -0.46 -1.4 8.2e+03 0.0061 7.4e+02 1.2 ++
11 -0.93 1.3 0.42 0.46 -2.1 0.31 -0.72 1 -1.7 0.14 -1 -0.084 -0.46 -1.4 8.2e+03 0.0038 7.4e+03 1.1 ++
12 -0.98 1.4 0.47 0.46 -2.2 0.27 -0.74 1 -1.7 0.16 -1 -0.08 -0.46 -1.4 8.2e+03 0.0029 7.4e+04 1 ++
13 -1 1.4 0.52 0.55 -2.3 0.22 -0.74 1 -1.7 0.16 -0.95 -0.081 -0.45 -1.5 8.2e+03 0.0002 7.4e+05 1 ++
14 -1 1.4 0.52 0.55 -2.3 0.22 -0.74 1 -1.7 0.16 -0.95 -0.081 -0.45 -1.5 8.2e+03 2.5e-07 7.4e+05 1 ++
Considering neighbor 0/20 for current solution
Attempt 18/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000022
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st b_cost_train mu_existing asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 -0.49 0.73 0.32 0.011 -1 -0.62 -0.92 1.9 0.25 -0.57 -0.21 -0.052 -0.075 -0.96 9e+03 0.17 1 0.66 +
1 -0.49 0.73 0.32 0.011 -1 -0.62 -0.92 1.9 0.25 -0.57 -0.21 -0.052 -0.075 -0.96 9e+03 0.17 0.5 -0.53 -
2 -0.54 0.62 0.082 0.046 -0.6 -0.39 -0.58 2 -0.25 -0.47 -0.039 -0.12 -0.35 -0.49 8.3e+03 0.041 0.5 0.79 +
3 -0.79 0.88 0.21 0.049 -0.74 -0.56 -0.59 2 -0.37 -0.26 -0.06 -0.38 -0.24 -0.68 8.2e+03 0.0056 5 1.1 ++
4 -0.94 1 0.31 0.21 -0.88 -0.63 -0.76 1.4 -0.36 -0.46 -0.062 -0.41 -0.28 -0.77 8.2e+03 0.0086 5 0.56 +
5 -1 1 0.35 0.26 -0.87 -0.63 -0.77 1.5 -0.37 -0.5 -0.066 -0.43 -0.27 -0.77 8.2e+03 0.00064 50 1 ++
6 -0.99 1 0.35 0.25 -0.87 -0.63 -0.77 1.5 -0.37 -0.49 -0.066 -0.42 -0.27 -0.77 8.2e+03 4.1e-05 5e+02 1 ++
7 -0.99 1 0.35 0.25 -0.87 -0.63 -0.77 1.5 -0.37 -0.49 -0.066 -0.42 -0.27 -0.77 8.2e+03 1.1e-07 5e+02 1 ++
Considering neighbor 0/20 for current solution
Considering neighbor 1/20 for current solution
Attempt 19/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000023
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_time_swissmet b_time_swissmet Function Relgrad Radius Rho
0 -0.51 0.37 -0.69 -0.17 -1 2 0.11 -0.29 -0.23 -0.17 -0.42 -0.38 9.3e+03 0.29 1 0.62 +
1 -0.21 0.69 -0.59 -0.41 0 2.4 -0.35 -0.36 -0.38 -0.51 -0.76 -0.31 8.8e+03 0.24 1 0.36 +
2 -0.55 0.49 -0.69 -0.29 -0.43 3.4 -0.45 -0.28 -0.44 -0.34 -0.75 -0.61 8.3e+03 0.057 1 0.72 +
3 -0.61 0.73 -0.72 -0.58 -0.57 2.4 -0.69 0.15 -0.32 -0.65 -0.83 -0.81 8.2e+03 0.0087 10 0.98 ++
4 -0.61 0.91 -0.9 -0.65 -0.67 1.7 -0.58 -0.12 -0.47 -0.72 -0.94 -0.83 8.2e+03 0.012 1e+02 1 ++
5 -0.67 0.99 -0.92 -0.65 -0.67 1.7 -0.55 -0.36 -0.5 -0.71 -0.96 -0.82 8.2e+03 0.0004 1e+03 1 ++
6 -0.69 1 -0.94 -0.66 -0.69 1.7 -0.55 -0.43 -0.52 -0.71 -0.98 -0.82 8.2e+03 0.00024 1e+04 1 ++
7 -0.69 1 -0.94 -0.66 -0.69 1.7 -0.55 -0.43 -0.52 -0.71 -0.98 -0.82 8.2e+03 2.2e-07 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 20/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000024
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 -0.45 0.011 -0.0098 -1 -0.096 1.3 -0.35 -0.27 -0.18 -0.24 -0.021 -0.27 9e+03 0.062 10 0.93 ++
1 -0.45 0.011 -0.0098 -1 -0.096 1.3 -0.35 -0.27 -0.18 -0.24 -0.021 -0.27 9e+03 0.062 5 -3.8e+05 -
2 -0.45 0.011 -0.0098 -1 -0.096 1.3 -0.35 -0.27 -0.18 -0.24 -0.021 -0.27 9e+03 0.062 2.5 -52 -
3 -0.45 0.011 -0.0098 -1 -0.096 1.3 -0.35 -0.27 -0.18 -0.24 -0.021 -0.27 9e+03 0.062 1.2 -2.5 -
4 -0.4 0.68 0.17 -2 -0.62 0.082 -1.5 -1 -0.42 0.028 -0.2 -0.35 8.5e+03 0.033 1.2 0.74 +
5 -0.28 0.76 0.66 -1.7 -0.55 0.27 -1.8 -0.76 0.013 -0.15 -0.64 -0.51 8.3e+03 0.0071 12 1 ++
6 -0.32 0.75 0.59 -1.6 -0.54 0.35 -1.9 -0.79 -0.063 -0.13 -0.63 -0.5 8.3e+03 0.00032 1.2e+02 1 ++
7 -0.32 0.75 0.59 -1.6 -0.54 0.35 -1.9 -0.79 -0.063 -0.13 -0.63 -0.5 8.3e+03 2e-06 1.2e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 21/100
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000025
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com b_cost asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.96 0.38 0.37 -0.88 0.37 -0.7 -0.27 0.015 -0.33 8.7e+03 0.037 10 1.1 ++
1 -1.2 0.77 0.77 -1.2 0.086 -0.77 0.021 -0.077 -0.53 8.6e+03 0.0079 1e+02 1.1 ++
2 -1.4 0.94 0.93 -1.2 -0.06 -0.78 0.045 -0.079 -0.54 8.6e+03 0.00052 1e+03 1 ++
3 -1.4 0.94 0.93 -1.2 -0.06 -0.78 0.045 -0.079 -0.54 8.6e+03 3.5e-06 1e+03 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000026
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 1 0 0 0 1.1e+04 0.26 0.5 -1.1 -
1 -0.5 -0.42 -0.017 -0.5 -0.14 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 8.8 5 1 ++
2 -0.5 -0.42 -0.017 -0.5 -0.14 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 8.8 2.5 1 -
3 -0.5 -0.42 -0.017 -0.5 -0.14 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 8.8 1.2 1 -
4 -0.5 -0.42 -0.017 -0.5 -0.14 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 8.8 0.62 1 -
5 -0.5 -0.42 -0.017 -0.5 -0.14 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 8.8 0.31 1 -
6 -0.5 -0.42 -0.017 -0.5 -0.14 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 8.8 0.16 1 -
7 -0.5 -0.42 -0.017 -0.5 -0.14 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 8.8 0.078 1 -
8 -0.5 -0.42 -0.017 -0.5 -0.14 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 8.8 0.039 1 -
9 -0.5 -0.42 -0.017 -0.5 -0.14 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 8.8 0.02 1 -
10 -0.5 -0.42 -0.017 -0.5 -0.14 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 8.8 0.0098 1 -
11 -0.5 -0.42 -0.017 -0.5 -0.14 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 8.8 0.0049 -2.6 -
12 -0.5 -0.42 -0.017 -0.5 -0.14 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 8.8 0.0024 -2.1 -
13 -0.5 -0.42 -0.017 -0.5 -0.14 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 8.8 0.0012 -1.6 -
14 -0.5 -0.42 -0.017 -0.5 -0.14 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 8.8 0.00061 -0.94 -
15 -0.5 -0.42 -0.017 -0.5 -0.14 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 8.8 0.00031 -0.18 -
16 -0.5 -0.42 -0.016 -0.5 -0.14 0.00031 -0.00031 -0.11 1.5 0.022 -0.018 -0.0056 9e+03 6 0.00031 0.61 +
17 -0.5 -0.42 -0.016 -0.5 -0.14 0.00031 -0.00031 -0.11 1.5 0.022 -0.018 -0.0056 9e+03 6 0.00015 -0.34 -
18 -0.5 -0.42 -0.016 -0.5 -0.14 0.00031 -0.00031 -0.11 1.5 0.022 -0.018 -0.0056 9e+03 6 7.6e-05 -0.41 -
19 -0.5 -0.42 -0.016 -0.5 -0.14 0.00038 -0.00023 -0.12 1.5 0.022 -0.018 -0.0057 9e+03 1.9 7.6e-05 0.67 +
20 -0.5 -0.42 -0.016 -0.5 -0.14 0.00046 -0.00024 -0.12 1.5 0.022 -0.018 -0.0057 9e+03 0.067 0.00076 1 ++
21 -0.5 -0.42 -0.016 -0.5 -0.14 0.0012 -0.00025 -0.12 1.5 0.022 -0.019 -0.0057 9e+03 0.58 0.0076 1 ++
22 -0.5 -0.42 -0.016 -0.51 -0.14 0.0089 -0.00028 -0.12 1.5 0.018 -0.024 -0.006 9e+03 0.062 0.076 1 ++
23 -0.49 -0.36 -0.016 -0.57 -0.15 0.085 -0.0006 -0.2 1.5 -0.015 -0.073 -0.0087 8.8e+03 0.86 0.76 0.99 ++
24 -0.54 0.4 0.013 -0.96 -0.092 -0.038 -7e-05 -0.78 2.1 0.19 -0.25 -0.065 8.5e+03 14 0.76 0.7 +
25 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00017 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 67 0.76 0.66 +
26 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00017 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 67 0.38 -1.8 -
27 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00017 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 67 0.19 -1 -
28 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00017 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 67 0.095 -0.68 -
29 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00017 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 67 0.048 -0.62 -
30 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00017 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 67 0.024 -0.63 -
31 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00017 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 67 0.012 -0.66 -
32 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00017 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 67 0.006 -0.68 -
33 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00017 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 67 0.003 -0.57 -
34 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00017 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 67 0.0015 -0.53 -
35 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00017 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 67 0.00075 -0.51 -
36 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00017 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 67 0.00037 -0.5 -
37 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00017 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 67 0.00019 -0.5 -
38 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00017 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 67 9.3e-05 -0.18 -
39 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00026 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 25 9.3e-05 0.28 +
40 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00026 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 25 4.7e-05 -0.075 -
41 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00022 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 1.3 0.00047 0.91 ++
42 -0.5 0.38 0.42 -1.2 -0.4 -0.11 0.00021 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 0.19 0.0047 1 ++
43 -0.5 0.38 0.42 -1.2 -0.4 -0.1 0.00019 -0.48 2.5 0.046 0.022 -0.51 8.4e+03 1.3 0.047 1 ++
44 -0.51 0.41 0.4 -1.3 -0.41 -0.093 0.00014 -0.53 2.5 0.04 -0.0092 -0.5 8.4e+03 2.9 0.47 1 ++
45 -0.49 0.45 0.26 -1.6 -0.49 -0.1 0.00018 -0.62 2 0.12 -0.0087 -0.41 8.3e+03 1.6 4.7 1 ++
46 -0.55 0.52 0.33 -1.7 -0.58 -0.1 0.00017 -0.63 1.9 0.15 -0.027 -0.48 8.3e+03 0.028 47 1.1 ++
47 -0.56 0.53 0.34 -1.7 -0.61 -0.1 0.00017 -0.63 1.9 0.16 -0.029 -0.49 8.3e+03 0.0032 4.7e+02 1 ++
48 -0.56 0.53 0.34 -1.7 -0.61 -0.1 0.00017 -0.63 1.9 0.16 -0.029 -0.49 8.3e+03 7e-05 4.7e+03 1 ++
49 -0.56 0.53 0.34 -1.7 -0.61 -0.1 0.00017 -0.63 1.9 0.16 -0.029 -0.49 8.3e+03 6e-06 4.7e+03 1 ++
Considering neighbor 1/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000027
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train b_cost_train mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car b_cost_car b_time_swissmet b_cost_swissmet Function Relgrad Radius Rho
0 -0.49 0.29 0.017 -0.84 -1 1.9 0.12 -0.23 -0.053 -0.66 -0.3 -0.81 -0.78 9.2e+03 0.28 1 0.67 +
1 -0.49 0.29 0.017 -0.84 -1 1.9 0.12 -0.23 -0.053 -0.66 -0.3 -0.81 -0.78 9.2e+03 0.28 0.5 -0.18 -
2 -0.23 0.37 0.08 -0.79 -0.92 2.3 -0.25 -0.02 -0.13 -0.71 -0.44 -1 -0.28 8.5e+03 0.11 0.5 0.73 +
3 -0.46 0.38 0.18 -0.98 -0.76 2.5 -0.49 -0.001 -0.41 -0.68 -0.51 -1.1 -0.49 8.3e+03 0.0058 5 1 ++
4 -0.46 0.38 0.18 -0.98 -0.76 2.5 -0.49 -0.001 -0.41 -0.68 -0.51 -1.1 -0.49 8.3e+03 0.0058 0.65 -1.8 -
5 -0.37 0.45 0.19 -1.2 -0.93 1.8 -0.49 0.02 -0.42 -0.86 -0.56 -1.3 -0.62 8.3e+03 0.0097 0.65 0.79 +
6 -0.43 0.48 0.3 -1.2 -1 1.8 -0.47 -0.031 -0.44 -0.85 -0.58 -1.3 -0.6 8.3e+03 0.0011 6.5 1.1 ++
7 -0.44 0.5 0.31 -1.2 -1.1 1.8 -0.47 -0.034 -0.44 -0.87 -0.59 -1.3 -0.61 8.3e+03 0.00017 65 1 ++
8 -0.44 0.5 0.31 -1.2 -1.1 1.8 -0.47 -0.034 -0.44 -0.87 -0.59 -1.3 -0.61 8.3e+03 1.1e-07 65 1 ++
Considering neighbor 2/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000028
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car b_time_swissmet Function Relgrad Radius Rho
0 -0.83 0.0079 -0.0092 -0.84 1.6 -1 1.7 0.03 -0.22 -0.029 -0.5 -0.57 8.8e+03 0.066 1 0.73 +
1 -0.83 0.0079 -0.0092 -0.84 1.6 -1 1.7 0.03 -0.22 -0.029 -0.5 -0.57 8.8e+03 0.066 0.5 -0.39 -
2 -0.61 0.35 0.032 -0.85 1.2 -0.5 1.9 -0.16 -0.18 -0.077 -0.37 -0.78 8.5e+03 0.036 0.5 0.77 +
3 -0.57 0.54 0.15 -1.2 0.66 -0.72 2.4 -0.066 0.097 -0.2 -0.72 -1.1 8.3e+03 0.02 5 0.97 ++
4 -0.19 0.4 0.2 -1.7 0.053 -0.54 2.7 0.082 -0.0049 -0.42 -1 -1.4 8.3e+03 0.012 5 0.75 +
5 -0.26 0.46 0.23 -1.9 0.17 -0.61 2.2 0.093 -0.015 -0.44 -1.1 -1.4 8.2e+03 0.0041 50 1 ++
6 -0.29 0.47 0.24 -1.9 0.17 -0.62 2.3 0.085 -0.012 -0.43 -1.1 -1.4 8.2e+03 6.4e-05 5e+02 1 ++
7 -0.29 0.47 0.24 -1.9 0.17 -0.62 2.3 0.085 -0.012 -0.43 -1.1 -1.4 8.2e+03 2.9e-07 5e+02 1 ++
Considering neighbor 3/20 for current solution
Attempt 22/100
Considering neighbor 0/20 for current solution
Attempt 23/100
Biogeme parameters read from biogeme.toml.
Model with 6 unknown parameters [max: 50]
*** Estimate b07everything_000029
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_com b_cost mu_existing asc_car Function Relgrad Radius Rho
0 -0.75 -0.84 0.1 -1 1.6 0.35 9e+03 0.12 1 0.77 +
1 -0.75 -0.84 0.1 -1 1.6 0.35 9e+03 0.12 0.5 -0.81 -
2 -0.42 -1 0.093 -0.5 1.9 -0.11 8.6e+03 0.033 0.5 0.79 +
3 -0.37 -0.93 0.24 -0.61 2.2 -0.013 8.5e+03 0.0028 5 0.94 ++
4 -0.37 -0.96 0.21 -0.62 2.1 -0.0089 8.5e+03 0.00017 50 0.99 ++
5 -0.37 -0.96 0.21 -0.62 2.1 -0.0089 8.5e+03 7.5e-07 50 1 ++
Considering neighbor 0/20 for current solution
Attempt 24/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000030
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 -1 0.16 -0.7 -0.073 1.3 -0.46 -0.51 -0.11 -0.54 -0.22 -0.63 -0.085 8.9e+03 0.058 10 0.96 ++
1 -1 0.16 -0.7 -0.073 1.3 -0.46 -0.51 -0.11 -0.54 -0.22 -0.63 -0.085 8.9e+03 0.058 5 -7.9e+05 -
2 -1 0.16 -0.7 -0.073 1.3 -0.46 -0.51 -0.11 -0.54 -0.22 -0.63 -0.085 8.9e+03 0.058 2.5 -42 -
3 -1 0.16 -0.7 -0.073 1.3 -0.46 -0.51 -0.11 -0.54 -0.22 -0.63 -0.085 8.9e+03 0.058 1.2 -0.38 -
4 -0.96 1.4 -1.2 -0.21 1.2 -0.81 -1.1 0.048 -0.24 -0.61 -0.7 -0.0045 8.4e+03 0.016 12 1 ++
5 -0.96 1.4 -1.2 -0.21 1.2 -0.81 -1.1 0.048 -0.24 -0.61 -0.7 -0.0045 8.4e+03 0.016 5.6 -4.5e+07 -
6 -0.96 1.4 -1.2 -0.21 1.2 -0.81 -1.1 0.048 -0.24 -0.61 -0.7 -0.0045 8.4e+03 0.016 2.8 -4.4e+02 -
7 -0.96 1.4 -1.2 -0.21 1.2 -0.81 -1.1 0.048 -0.24 -0.61 -0.7 -0.0045 8.4e+03 0.016 1.4 -12 -
8 -0.96 1.4 -1.2 -0.21 1.2 -0.81 -1.1 0.048 -0.24 -0.61 -0.7 -0.0045 8.4e+03 0.016 0.7 -0.046 -
9 -1.1 1.6 -1.3 -0.31 0.51 -0.71 -1.4 0.029 -0.035 -0.74 -1 -0.016 8.2e+03 0.013 7 0.97 ++
10 -0.66 1.6 -2.2 -0.71 0.097 -0.72 -1.6 -0.88 0.13 -0.96 -1.4 -0.29 8.2e+03 0.0093 70 0.98 ++
11 -0.63 1.6 -2.3 -0.86 0.16 -0.73 -1.6 -0.72 0.14 -1 -1.5 -0.27 8.2e+03 0.00023 7e+02 0.99 ++
12 -0.63 1.6 -2.3 -0.86 0.16 -0.73 -1.6 -0.72 0.14 -1 -1.5 -0.27 8.2e+03 2.3e-06 7e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 25/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000031
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost mu_existing asc_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 1.1e+04 0.26 0.5 -0.42 -
1 0 0 0 0 0 0 1 0 1.1e+04 0.26 0.25 -0.34 -
2 -0.25 -0.25 -0.25 0 0 -0.25 1.2 0.034 9.6e+03 5.2 2.5 1 ++
3 -0.25 -0.25 -0.25 0 0 -0.25 1.2 0.034 9.6e+03 5.2 1.2 1 -
4 -0.25 -0.25 -0.25 0 0 -0.25 1.2 0.034 9.6e+03 5.2 0.62 1 -
5 -0.25 -0.25 -0.25 0 0 -0.25 1.2 0.034 9.6e+03 5.2 0.31 1 -
6 -0.25 -0.25 -0.25 0 0 -0.25 1.2 0.034 9.6e+03 5.2 0.16 1 -
7 -0.25 -0.25 -0.25 0 0 -0.25 1.2 0.034 9.6e+03 5.2 0.078 1 -
8 -0.25 -0.25 -0.25 0 0 -0.25 1.2 0.034 9.6e+03 5.2 0.039 -2.3 -
9 -0.25 -0.25 -0.25 0 0 -0.25 1.2 0.034 9.6e+03 5.2 0.02 -2.9 -
10 -0.25 -0.25 -0.25 0 0 -0.25 1.2 0.034 9.6e+03 5.2 0.0098 -3.5 -
11 -0.25 -0.25 -0.25 0 0 -0.25 1.2 0.034 9.6e+03 5.2 0.0049 -4 -
12 -0.25 -0.25 -0.25 0 0 -0.25 1.2 0.034 9.6e+03 5.2 0.0024 -2.6 -
13 -0.25 -0.25 -0.25 0 0 -0.25 1.2 0.034 9.6e+03 5.2 0.0012 -1.8 -
14 -0.25 -0.25 -0.25 0 0 -0.25 1.2 0.034 9.6e+03 5.2 0.00061 -1 -
15 -0.25 -0.25 -0.25 0 0 -0.25 1.2 0.034 9.6e+03 5.2 0.00031 -0.2 -
16 -0.25 -0.25 -0.25 0.00031 -0.00031 -0.25 1.3 0.034 9.6e+03 3.8 0.00031 0.65 +
17 -0.25 -0.25 -0.25 0.00053 -0.00022 -0.25 1.3 0.034 9.6e+03 2.5 0.00031 0.69 +
18 -0.25 -0.25 -0.25 0.00076 -0.00026 -0.25 1.3 0.034 9.6e+03 0.53 0.0031 0.96 ++
19 -0.25 -0.25 -0.25 0.003 -0.00026 -0.25 1.3 0.034 9.5e+03 0.16 0.031 1 ++
20 -0.28 -0.28 -0.25 0.026 -0.00036 -0.25 1.3 0.035 9.4e+03 0.62 0.31 1 ++
21 -0.5 -0.59 -0.28 0.26 -0.0013 -0.3 1.4 0.039 8.7e+03 1.4 0.31 0.72 +
22 -0.54 -0.66 -0.2 0.077 -0.00056 -0.61 1.6 0.024 8.6e+03 0.37 0.31 0.89 +
23 -0.51 -0.97 -0.15 -0.066 2.9e-05 -0.71 1.8 -0.066 8.5e+03 1.8 3.1 1.1 ++
24 -0.21 -1.4 -0.29 -0.09 0.00013 -0.6 2.1 0.11 8.4e+03 4.7 31 1.1 ++
25 -0.17 -1.6 -0.42 -0.1 0.00019 -0.62 2.1 0.13 8.4e+03 6.1 31 0.88 +
26 -0.19 -1.6 -0.56 -0.099 0.00017 -0.63 2 0.13 8.4e+03 0.023 3.1e+02 1 ++
27 -0.19 -1.6 -0.56 -0.099 0.00017 -0.63 2 0.13 8.4e+03 0.0013 3.1e+03 1 ++
28 -0.19 -1.6 -0.56 -0.099 0.00017 -0.63 2 0.13 8.4e+03 9.9e-06 3.1e+04 1 ++
29 -0.19 -1.6 -0.56 -0.099 0.00017 -0.63 2 0.13 8.4e+03 5.9e-07 3.1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 26/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000032
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train b_cost_train b_time_swissmet b_cost_swissmet asc_car b_time_car b_cost_car Function Relgrad Radius Rho
0 -0.65 -0.79 -0.93 -1 -0.63 -0.47 -0.73 -0.68 8.7e+03 0.08 10 1.1 ++
1 -0.26 -1.3 -1.5 -1.4 -0.76 -0.56 -1 -0.64 8.5e+03 0.026 1e+02 1.2 ++
2 -0.048 -1.4 -1.8 -1.5 -0.78 -0.59 -1.1 -0.66 8.4e+03 0.0041 1e+03 1.1 ++
3 -0.02 -1.4 -1.9 -1.5 -0.79 -0.59 -1.1 -0.66 8.4e+03 0.00011 1e+04 1 ++
4 -0.02 -1.4 -1.9 -1.5 -0.79 -0.59 -1.1 -0.66 8.4e+03 7.9e-08 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 27/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000033
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di square_tt_coef cube_tt_coef b_cost mu_public b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.34 -
1 -0.27 1.5e-05 -0.5 -0.28 0.0033 0.031 -0.039 1 0.2 0.1 0.0071 -0.022 -0.021 -0.009 9.8e+03 1.4 0.5 0.43 +
2 -0.27 1.5e-05 -0.5 -0.28 0.0033 0.031 -0.039 1 0.2 0.1 0.0071 -0.022 -0.021 -0.009 9.8e+03 1.4 0.25 0.43 -
3 -0.27 1.5e-05 -0.5 -0.28 0.0033 0.031 -0.039 1 0.2 0.1 0.0071 -0.022 -0.021 -0.009 9.8e+03 1.4 0.12 0.43 -
4 -0.27 1.5e-05 -0.5 -0.28 0.0033 0.031 -0.039 1 0.2 0.1 0.0071 -0.022 -0.021 -0.009 9.8e+03 1.4 0.062 0.43 -
5 -0.27 1.5e-05 -0.5 -0.28 0.0033 0.031 -0.039 1 0.2 0.1 0.0071 -0.022 -0.021 -0.009 9.8e+03 1.4 0.031 -3.4 -
6 -0.27 0.0048 -0.49 -0.27 -0.0074 -0.00042 -0.049 1 0.18 0.086 0.0015 -0.025 0.00066 -0.018 9.4e+03 0.37 0.31 0.95 ++
7 -0.3 0.16 -0.59 -0.33 0.11 -0.00035 -0.36 1 0.076 -0.0026 -0.11 -0.13 -0.25 -0.13 9e+03 2.4 0.31 0.81 +
8 -0.3 0.16 -0.59 -0.33 0.11 -0.00035 -0.36 1 0.076 -0.0026 -0.11 -0.13 -0.25 -0.13 9e+03 2.4 0.16 -2.2 -
9 -0.3 0.16 -0.59 -0.33 0.11 -0.00035 -0.36 1 0.076 -0.0026 -0.11 -0.13 -0.25 -0.13 9e+03 2.4 0.078 -1.9 -
10 -0.3 0.16 -0.59 -0.33 0.11 -0.00035 -0.36 1 0.076 -0.0026 -0.11 -0.13 -0.25 -0.13 9e+03 2.4 0.039 -2.9 -
11 -0.3 0.16 -0.59 -0.33 0.11 -0.00035 -0.36 1 0.076 -0.0026 -0.11 -0.13 -0.25 -0.13 9e+03 2.4 0.02 -4.3 -
12 -0.3 0.16 -0.59 -0.33 0.11 -0.00035 -0.36 1 0.076 -0.0026 -0.11 -0.13 -0.25 -0.13 9e+03 2.4 0.0098 -5.5 -
13 -0.3 0.16 -0.59 -0.33 0.11 -0.00035 -0.36 1 0.076 -0.0026 -0.11 -0.13 -0.25 -0.13 9e+03 2.4 0.0049 -6.4 -
14 -0.3 0.16 -0.59 -0.33 0.11 -0.00035 -0.36 1 0.076 -0.0026 -0.11 -0.13 -0.25 -0.13 9e+03 2.4 0.0024 -3.2 -
15 -0.3 0.16 -0.59 -0.33 0.11 -0.00035 -0.36 1 0.076 -0.0026 -0.11 -0.13 -0.25 -0.13 9e+03 2.4 0.0012 -1.2 -
16 -0.3 0.16 -0.59 -0.33 0.11 -0.00035 -0.36 1 0.076 -0.0026 -0.11 -0.13 -0.25 -0.13 9e+03 2.4 0.00061 -0.12 -
17 -0.3 0.16 -0.59 -0.33 0.11 -0.00096 -0.36 1 0.075 -0.0032 -0.11 -0.13 -0.25 -0.13 9e+03 1.7 0.00061 0.46 +
18 -0.3 0.16 -0.59 -0.33 0.11 -0.00096 -0.36 1 0.075 -0.0032 -0.11 -0.13 -0.25 -0.13 9e+03 1.7 0.00031 -0.29 -
19 -0.3 0.16 -0.59 -0.33 0.11 -0.00065 -0.36 1 0.075 -0.0035 -0.11 -0.13 -0.25 -0.13 9e+03 1.4 0.00031 0.56 +
20 -0.3 0.16 -0.59 -0.33 0.11 -0.00077 -0.36 1 0.075 -0.0037 -0.11 -0.13 -0.25 -0.13 9e+03 0.36 0.00031 0.89 +
21 -0.3 0.16 -0.59 -0.33 0.11 -0.00074 -0.36 1 0.074 -0.0039 -0.11 -0.13 -0.25 -0.13 9e+03 0.1 0.0031 1 ++
22 -0.3 0.16 -0.59 -0.33 0.11 -0.00076 -0.36 1 0.071 -0.0058 -0.11 -0.13 -0.25 -0.13 8.9e+03 0.24 0.031 1 ++
23 -0.3 0.17 -0.59 -0.33 0.092 -0.00066 -0.38 1 0.041 -0.024 -0.097 -0.13 -0.23 -0.12 8.9e+03 0.074 0.31 1 ++
24 -0.32 0.31 -0.64 -0.35 0.21 -0.0011 -0.56 1 -0.26 -0.21 -0.088 -0.21 -0.26 -0.15 8.6e+03 1.8 0.31 0.78 +
25 -0.33 0.49 -0.6 -0.34 0.34 -0.0018 -0.66 1 -0.44 -0.32 -0.17 -0.29 -0.38 -0.25 8.5e+03 1.4 0.31 0.83 +
26 -0.53 0.79 -0.69 -0.39 0.11 0.00031 -0.79 1.1 -0.4 -0.38 -0.31 -0.45 -0.4 -0.3 8.4e+03 4.4 0.31 0.53 +
27 -0.53 0.79 -0.69 -0.39 0.11 0.00031 -0.79 1.1 -0.4 -0.38 -0.31 -0.45 -0.4 -0.3 8.4e+03 4.4 0.15 0.53 -
28 -0.53 0.79 -0.69 -0.39 0.11 0.00031 -0.79 1.1 -0.4 -0.38 -0.31 -0.45 -0.4 -0.3 8.4e+03 4.4 0.076 0.53 -
29 -0.53 0.79 -0.69 -0.39 0.11 0.00031 -0.79 1.1 -0.4 -0.38 -0.31 -0.45 -0.4 -0.3 8.4e+03 4.4 0.038 -7.4 -
30 -0.53 0.79 -0.69 -0.39 0.11 0.00031 -0.79 1.1 -0.4 -0.38 -0.31 -0.45 -0.4 -0.3 8.4e+03 4.4 0.019 -5.2 -
31 -0.53 0.79 -0.69 -0.39 0.11 0.00031 -0.79 1.1 -0.4 -0.38 -0.31 -0.45 -0.4 -0.3 8.4e+03 4.4 0.0095 -3.6 -
32 -0.53 0.79 -0.69 -0.39 0.11 0.00031 -0.79 1.1 -0.4 -0.38 -0.31 -0.45 -0.4 -0.3 8.4e+03 4.4 0.0048 -2.5 -
33 -0.53 0.79 -0.69 -0.39 0.11 0.00031 -0.79 1.1 -0.4 -0.38 -0.31 -0.45 -0.4 -0.3 8.4e+03 4.4 0.0024 -1.5 -
34 -0.53 0.79 -0.69 -0.39 0.11 0.00031 -0.79 1.1 -0.4 -0.38 -0.31 -0.45 -0.4 -0.3 8.4e+03 4.4 0.0012 -0.14 -
35 -0.54 0.79 -0.69 -0.39 0.11 -0.00088 -0.79 1.1 -0.4 -0.38 -0.31 -0.45 -0.4 -0.3 8.4e+03 2.1 0.0012 0.79 +
36 -0.54 0.79 -0.69 -0.39 0.11 -0.00088 -0.79 1.1 -0.4 -0.38 -0.31 -0.45 -0.4 -0.3 8.4e+03 2.1 0.0006 -2.1 -
37 -0.54 0.79 -0.69 -0.39 0.11 -0.00088 -0.79 1.1 -0.4 -0.38 -0.31 -0.45 -0.4 -0.3 8.4e+03 2.1 0.0003 -1.9 -
38 -0.54 0.79 -0.69 -0.39 0.11 -0.00088 -0.79 1.1 -0.4 -0.38 -0.31 -0.45 -0.4 -0.3 8.4e+03 2.1 0.00015 -0.27 -
39 -0.54 0.79 -0.69 -0.39 0.11 -0.00073 -0.79 1.1 -0.4 -0.38 -0.31 -0.45 -0.4 -0.3 8.4e+03 0.2 0.00015 0.76 +
40 -0.54 0.79 -0.69 -0.39 0.11 -0.00074 -0.79 1.1 -0.4 -0.38 -0.31 -0.45 -0.4 -0.3 8.4e+03 0.025 0.0015 1 ++
41 -0.54 0.8 -0.69 -0.39 0.11 -0.00074 -0.78 1.1 -0.4 -0.38 -0.31 -0.45 -0.4 -0.3 8.4e+03 0.38 0.015 1 ++
42 -0.54 0.8 -0.7 -0.4 0.13 -0.00081 -0.78 1.1 -0.41 -0.38 -0.31 -0.45 -0.39 -0.3 8.3e+03 0.03 0.15 1 ++
43 -0.57 0.89 -0.69 -0.42 0.19 -0.0011 -0.76 1.2 -0.56 -0.42 -0.31 -0.49 -0.39 -0.37 8.3e+03 0.059 1.5 0.93 ++
44 -0.57 0.89 -0.69 -0.42 0.19 -0.0011 -0.76 1.2 -0.56 -0.42 -0.31 -0.49 -0.39 -0.37 8.3e+03 0.059 0.75 -92 -
45 -0.57 0.89 -0.69 -0.42 0.19 -0.0011 -0.76 1.2 -0.56 -0.42 -0.31 -0.49 -0.39 -0.37 8.3e+03 0.059 0.37 -9.3 -
46 -0.57 0.89 -0.69 -0.42 0.19 -0.0011 -0.76 1.2 -0.56 -0.42 -0.31 -0.49 -0.39 -0.37 8.3e+03 0.059 0.19 -0.87 -
47 -0.71 1 -0.74 -0.47 0.0023 -0.00029 -0.77 1.3 -0.61 -0.49 -0.43 -0.58 -0.46 -0.39 8.3e+03 0.38 0.19 0.61 +
48 -0.75 1.1 -0.76 -0.51 0.067 -0.00058 -0.77 1.3 -0.8 -0.54 -0.44 -0.63 -0.5 -0.5 8.2e+03 0.32 1.9 0.93 ++
49 -0.75 1.1 -0.76 -0.51 0.067 -0.00058 -0.77 1.3 -0.8 -0.54 -0.44 -0.63 -0.5 -0.5 8.2e+03 0.32 0.93 -94 -
50 -0.75 1.1 -0.76 -0.51 0.067 -0.00058 -0.77 1.3 -0.8 -0.54 -0.44 -0.63 -0.5 -0.5 8.2e+03 0.32 0.47 -18 -
51 -0.75 1.1 -0.76 -0.51 0.067 -0.00058 -0.77 1.3 -0.8 -0.54 -0.44 -0.63 -0.5 -0.5 8.2e+03 0.32 0.23 -0.48 -
52 -0.9 1.2 -0.92 -0.63 -0.059 -1.2e-05 -0.81 1.4 -1 -0.68 -0.59 -0.78 -0.67 -0.57 8.2e+03 0.25 0.23 0.74 +
53 -0.84 1.2 -1.1 -0.72 -0.058 -2.2e-05 -0.79 1.2 -1.3 -0.71 -0.53 -0.88 -0.78 -0.74 8.2e+03 0.23 2.3 1 ++
54 -0.8 1.5 -1.7 -0.93 -0.11 0.0002 -0.72 1 -1.7 -0.88 -0.53 -1.1 -1.1 -0.78 8.1e+03 5.1 2.3 0.7 +
55 -0.82 1.5 -1.7 -0.93 -0.097 0.00016 -0.77 1 -1.7 -0.87 -0.51 -1.1 -1.1 -0.8 8.1e+03 1 23 1 ++
56 -0.64 1.5 -2.1 -0.85 -0.11 0.00021 -0.8 1 -2 -0.74 -0.51 -1 -1.4 -0.73 8.1e+03 1.7 2.3e+02 1 ++
57 -0.68 1.5 -2.1 -0.76 -0.11 0.0002 -0.8 1 -2.1 -0.59 -0.49 -1 -1.4 -0.63 8.1e+03 0.14 2.3e+03 1 ++
58 -0.65 1.5 -2.2 -0.75 -0.11 0.00021 -0.8 1 -2.1 -0.58 -0.49 -1 -1.4 -0.62 8.1e+03 0.004 2.3e+04 1 ++
59 -0.66 1.5 -2.2 -0.74 -0.11 0.00021 -0.8 1 -2.1 -0.56 -0.49 -1 -1.4 -0.61 8.1e+03 0.00069 2.3e+05 1 ++
60 -0.65 1.5 -2.2 -0.74 -0.11 0.00021 -0.8 1 -2.1 -0.56 -0.49 -1 -1.4 -0.61 8.1e+03 0.0012 2.3e+06 1 ++
61 -0.65 1.5 -2.2 -0.74 -0.11 0.00021 -0.8 1 -2.1 -0.56 -0.49 -1 -1.4 -0.61 8.1e+03 0.0011 2.3e+07 1 ++
62 -0.65 1.5 -2.2 -0.74 -0.11 0.00021 -0.8 1 -2.1 -0.56 -0.49 -1 -1.4 -0.61 8.1e+03 4.9e-06 2.3e+07 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000034
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train square_tt_coef cube_tt_coef b_cost mu_public b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.4 0.5 -0.23 -
1 -0.27 -0.14 -0.0056 -0.5 0.0019 0.019 -0.039 1 0.2 0.0073 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.5 0.68 +
2 -0.27 -0.14 -0.0056 -0.5 0.0019 0.019 -0.039 1 0.2 0.0073 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.25 0.68 -
3 -0.27 -0.14 -0.0056 -0.5 0.0019 0.019 -0.039 1 0.2 0.0073 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.12 0.68 -
4 -0.27 -0.14 -0.0056 -0.5 0.0019 0.019 -0.039 1 0.2 0.0073 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.062 -14 -
5 -0.27 -0.14 -0.0056 -0.5 0.0019 0.019 -0.039 1 0.2 0.0073 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.031 -12 -
6 -0.27 -0.14 -0.0056 -0.5 0.0019 0.019 -0.039 1 0.2 0.0073 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.016 -2.8 -
7 -0.27 -0.13 -0.0053 -0.5 -0.0029 0.003 -0.054 1 0.19 -0.0084 -0.019 -0.0026 -0.0053 9.4e+03 0.39 0.16 0.96 ++
8 -0.27 -0.13 -0.0053 -0.5 -0.0029 0.003 -0.054 1 0.19 -0.0084 -0.019 -0.0026 -0.0053 9.4e+03 0.39 0.078 -12 -
9 -0.27 -0.13 -0.0053 -0.5 -0.0029 0.003 -0.054 1 0.19 -0.0084 -0.019 -0.0026 -0.0053 9.4e+03 0.39 0.039 -9.3 -
10 -0.27 -0.13 -0.0053 -0.5 -0.0029 0.003 -0.054 1 0.19 -0.0084 -0.019 -0.0026 -0.0053 9.4e+03 0.39 0.02 -7.6 -
11 -0.27 -0.13 -0.0053 -0.5 -0.0029 0.003 -0.054 1 0.19 -0.0084 -0.019 -0.0026 -0.0053 9.4e+03 0.39 0.0098 -8.2 -
12 -0.27 -0.13 -0.0053 -0.5 -0.0029 0.003 -0.054 1 0.19 -0.0084 -0.019 -0.0026 -0.0053 9.4e+03 0.39 0.0049 -5.3 -
13 -0.27 -0.13 -0.0053 -0.5 -0.0029 0.003 -0.054 1 0.19 -0.0084 -0.019 -0.0026 -0.0053 9.4e+03 0.39 0.0024 0.095 -
14 -0.27 -0.13 -0.0047 -0.5 -0.00042 0.00059 -0.057 1 0.18 -0.011 -0.022 -0.0051 -0.0078 9.4e+03 0.21 0.024 0.96 ++
15 -0.28 -0.13 -0.0046 -0.51 0.0085 -0.0022 -0.071 1 0.19 -0.022 -0.031 -0.0056 -0.032 9.4e+03 4.6 0.024 0.18 +
16 -0.28 -0.12 -0.0044 -0.53 0.013 -0.00011 -0.087 1 0.19 -0.032 -0.038 -0.0062 -0.057 9.3e+03 0.29 0.024 0.86 +
17 -0.28 -0.12 -0.0041 -0.54 0.024 -0.00076 -0.11 1 0.19 -0.042 -0.047 -0.0069 -0.081 9.3e+03 0.59 0.24 0.96 ++
18 -0.32 -0.041 -0.00086 -0.66 0.13 0.00062 -0.35 1 0.081 -0.12 -0.12 -0.015 -0.31 9.2e+03 2.9 0.24 0.57 +
19 -0.32 -0.041 -0.00086 -0.66 0.13 0.00062 -0.35 1 0.081 -0.12 -0.12 -0.015 -0.31 9.2e+03 2.9 0.12 0.57 -
20 -0.32 -0.041 -0.00086 -0.66 0.13 0.00062 -0.35 1 0.081 -0.12 -0.12 -0.015 -0.31 9.2e+03 2.9 0.061 0.57 -
21 -0.32 -0.041 -0.00086 -0.66 0.13 0.00062 -0.35 1 0.081 -0.12 -0.12 -0.015 -0.31 9.2e+03 2.9 0.031 -11 -
22 -0.32 -0.041 -0.00086 -0.66 0.13 0.00062 -0.35 1 0.081 -0.12 -0.12 -0.015 -0.31 9.2e+03 2.9 0.015 -5.1 -
23 -0.32 -0.041 -0.00086 -0.66 0.13 0.00062 -0.35 1 0.081 -0.12 -0.12 -0.015 -0.31 9.2e+03 2.9 0.0076 -3.4 -
24 -0.32 -0.041 -0.00086 -0.66 0.13 0.00062 -0.35 1 0.081 -0.12 -0.12 -0.015 -0.31 9.2e+03 2.9 0.0038 -2.1 -
25 -0.32 -0.041 -0.00086 -0.66 0.13 0.00062 -0.35 1 0.081 -0.12 -0.12 -0.015 -0.31 9.2e+03 2.9 0.0019 -0.53 -
26 -0.32 -0.039 0.001 -0.66 0.12 -0.0013 -0.35 1 0.079 -0.12 -0.12 -0.017 -0.3 9.1e+03 2.5 0.0019 0.61 +
27 -0.32 -0.039 0.001 -0.66 0.12 -0.0013 -0.35 1 0.079 -0.12 -0.12 -0.017 -0.3 9.1e+03 2.5 0.00095 -0.062 -
28 -0.32 -0.039 0.001 -0.66 0.12 -0.0013 -0.35 1 0.079 -0.12 -0.12 -0.017 -0.3 9.1e+03 2.5 0.00048 0.09 -
29 -0.32 -0.039 0.0015 -0.65 0.12 -0.00081 -0.35 1 0.079 -0.12 -0.12 -0.017 -0.3 9.1e+03 0.12 0.0048 0.97 ++
30 -0.32 -0.038 0.0016 -0.65 0.12 -0.00083 -0.36 1 0.074 -0.12 -0.12 -0.017 -0.3 9.1e+03 0.4 0.048 1 ++
31 -0.32 -0.028 0.0022 -0.65 0.1 -0.00071 -0.37 1 0.026 -0.1 -0.11 -0.018 -0.27 9e+03 0.077 0.48 1 ++
32 -0.34 0.13 0.012 -0.76 0.33 -0.0016 -0.64 1.1 -0.45 -0.08 -0.13 -0.03 -0.32 8.8e+03 2.2 0.48 0.55 +
33 -0.34 0.19 0.017 -0.72 0.35 -0.0018 -0.66 1 -0.49 -0.14 -0.16 -0.037 -0.41 8.7e+03 1.1 4.8 0.97 ++
34 -0.4 0.22 0.024 -0.79 0.34 -0.0017 -0.7 1 -0.53 -0.17 -0.18 -0.046 -0.42 8.6e+03 0.79 48 1 ++
35 -0.4 0.22 0.024 -0.79 0.34 -0.0017 -0.7 1 -0.53 -0.17 -0.18 -0.046 -0.42 8.6e+03 0.79 24 1 -
36 -0.4 0.22 0.024 -0.79 0.34 -0.0017 -0.7 1 -0.53 -0.17 -0.18 -0.046 -0.42 8.6e+03 0.79 12 1 -
37 -0.4 0.22 0.024 -0.79 0.34 -0.0017 -0.7 1 -0.53 -0.17 -0.18 -0.046 -0.42 8.6e+03 0.79 6 1 -
38 -0.4 0.22 0.024 -0.79 0.34 -0.0017 -0.7 1 -0.53 -0.17 -0.18 -0.046 -0.42 8.6e+03 0.79 3 1 -
39 -0.4 0.22 0.024 -0.79 0.34 -0.0017 -0.7 1 -0.53 -0.17 -0.18 -0.046 -0.42 8.6e+03 0.79 1.5 -2.9e+02 -
40 -0.4 0.22 0.024 -0.79 0.34 -0.0017 -0.7 1 -0.53 -0.17 -0.18 -0.046 -0.42 8.6e+03 0.79 0.75 -1.2e+02 -
41 -0.4 0.22 0.024 -0.79 0.34 -0.0017 -0.7 1 -0.53 -0.17 -0.18 -0.046 -0.42 8.6e+03 0.79 0.37 -5.1 -
42 -0.77 0.57 0.089 -1 0.042 -0.00049 -0.86 1 -0.84 -0.42 -0.22 -0.12 -0.58 8.6e+03 1.7 0.37 0.48 +
43 -0.83 0.74 0.21 -1.4 0.036 -0.00036 -0.74 1 -1.2 -0.42 -0.045 -0.19 -0.88 8.5e+03 8.6 3.7 1 ++
44 -0.87 0.74 0.25 -1.6 -0.03 -0.00012 -0.77 1 -1.3 -0.44 -0.081 -0.21 -0.94 8.5e+03 3.9 3.7 0.9 +
45 -0.88 0.74 0.26 -1.6 -0.018 -0.00019 -0.77 1 -1.3 -0.44 -0.08 -0.21 -0.94 8.5e+03 0.24 37 1 ++
46 -0.88 0.74 0.26 -1.6 -0.018 -0.00019 -0.77 1 -1.3 -0.44 -0.08 -0.21 -0.94 8.5e+03 0.24 1.3 -75 -
47 -0.88 0.74 0.26 -1.6 -0.018 -0.00019 -0.77 1 -1.3 -0.44 -0.08 -0.21 -0.94 8.5e+03 0.24 0.67 -8.2 -
48 -0.84 1 0.53 -2.2 -0.11 0.00021 -0.75 1 -1.9 -0.53 -0.11 -0.33 -1.3 8.4e+03 19 0.67 0.43 +
49 -0.85 1 0.53 -2.2 -0.089 0.00011 -0.75 1 -1.9 -0.52 -0.1 -0.33 -1.3 8.4e+03 2.2 6.7 1.1 ++
50 -0.49 0.92 0.87 -2.8 -0.11 0.00022 -0.8 1 -2.3 -0.46 -0.098 -0.46 -1.7 8.4e+03 3.1 67 0.99 ++
51 -0.45 0.91 0.84 -2.9 -0.11 0.0002 -0.8 1 -2.4 -0.46 -0.099 -0.49 -1.7 8.4e+03 0.086 6.7e+02 0.99 ++
52 -0.45 0.91 0.82 -2.9 -0.11 0.0002 -0.8 1 -2.4 -0.46 -0.1 -0.5 -1.7 8.4e+03 0.0012 6.7e+03 1 ++
53 -0.44 0.91 0.82 -2.9 -0.11 0.0002 -0.8 1 -2.4 -0.45 -0.1 -0.51 -1.7 8.4e+03 0.0002 6.7e+04 1 ++
54 -0.44 0.91 0.82 -2.9 -0.11 0.0002 -0.8 1 -2.4 -0.45 -0.1 -0.51 -1.7 8.4e+03 3.1e-06 6.7e+04 1 ++
Considering neighbor 1/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000035
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time b_cost mu_public asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.77 -0.33 -0.016 -1 -0.23 1.5 -0.075 -0.1 -0.0096 9.4e+03 0.12 1 0.46 +
1 -0.44 0.67 0.016 -1.2 -1.1 1.6 -0.18 -0.3 -0.05 8.9e+03 0.087 1 0.54 +
2 -0.61 0.42 0.71 -0.84 -0.55 1.9 -0.15 -0.13 -0.57 8.6e+03 0.018 1 0.75 +
3 -0.8 0.56 0.4 -1.2 -0.74 1 0.016 -0.086 -0.56 8.6e+03 0.033 1 0.13 +
4 -1.2 0.81 0.82 -1.2 -0.77 1.1 0.0048 -0.087 -0.54 8.6e+03 0.002 10 1 ++
5 -1.3 0.89 0.83 -1.3 -0.79 1 0.064 -0.1 -0.54 8.6e+03 0.0013 1e+02 0.99 ++
6 -1.4 0.93 0.88 -1.3 -0.78 1 0.036 -0.074 -0.55 8.6e+03 0.00065 1e+03 1 ++
7 -1.4 0.96 0.95 -1.3 -0.78 1 0.044 -0.079 -0.53 8.6e+03 9.1e-06 1e+04 1 ++
8 -1.4 0.96 0.95 -1.3 -0.78 1 0.044 -0.079 -0.53 8.6e+03 9.9e-10 1e+04 1 ++
Considering neighbor 2/20 for current solution
Attempt 28/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000036
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.68 0.44 0.049 -0.007 -1 0.027 1.6 -0.93 1.8 0.16 -0.31 -0.13 -0.022 8.7e+03 0.055 1 0.7 +
1 -0.68 1.1 0.47 0.2 -1.2 -0.39 0.62 -0.53 2.6 -0.056 -0.66 0.031 -0.28 8.4e+03 0.036 1 0.77 +
2 -0.49 0.84 0.4 0.17 -1.5 -0.33 0.35 -0.51 1.6 0.32 -0.1 -0.087 -0.28 8.2e+03 0.013 1 0.71 +
3 -0.67 1.1 0.34 0.19 -1.4 -0.41 0.3 -0.58 1.7 0.2 -0.43 -0.046 -0.39 8.2e+03 0.0011 10 1 ++
4 -0.78 1.2 0.38 0.26 -1.5 -0.46 0.3 -0.62 1.5 0.22 -0.6 -0.052 -0.42 8.2e+03 0.0012 1e+02 0.91 ++
5 -0.78 1.2 0.38 0.26 -1.5 -0.46 0.3 -0.62 1.5 0.22 -0.63 -0.052 -0.43 8.2e+03 4.1e-05 1e+03 1 ++
6 -0.78 1.2 0.38 0.26 -1.5 -0.46 0.3 -0.62 1.5 0.22 -0.63 -0.052 -0.43 8.2e+03 2e-07 1e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 29/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000037
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train b_cost_train mu_public b_time_swissmet b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 1 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.27 -
1 -0.27 -0.096 -0.0052 -0.46 -0.28 1.5 0.19 0.22 -0.099 -0.089 -0.0065 -0.25 -0.14 9.9e+03 0.22 0.5 0.36 +
2 -0.16 0.17 0.0067 -0.38 -0.36 1.6 -0.23 -0.28 -0.16 -0.17 -0.021 -0.36 -0.19 9.2e+03 0.24 0.5 0.53 +
3 -0.3 0.28 0.031 -0.6 -0.76 2.1 -0.57 -0.38 -0.2 -0.19 -0.043 -0.51 -0.26 8.6e+03 0.073 5 0.94 ++
4 -0.3 0.28 0.031 -0.6 -0.76 2.1 -0.57 -0.38 -0.2 -0.19 -0.043 -0.51 -0.26 8.6e+03 0.073 2.5 -72 -
5 -0.3 0.28 0.031 -0.6 -0.76 2.1 -0.57 -0.38 -0.2 -0.19 -0.043 -0.51 -0.26 8.6e+03 0.073 1.2 -14 -
6 -0.3 0.28 0.031 -0.6 -0.76 2.1 -0.57 -0.38 -0.2 -0.19 -0.043 -0.51 -0.26 8.6e+03 0.073 0.62 -0.94 -
7 -0.36 0.35 0.61 -0.65 -1.3 2.8 -0.94 -0.8 -0.75 -0.11 -0.41 -0.74 -0.51 8.5e+03 0.09 0.62 0.67 +
8 -0.16 0.19 0.082 -0.52 -1.3 3.3 -0.61 -0.87 -0.52 -0.15 -0.68 -0.78 -0.47 8.4e+03 0.014 0.62 0.69 +
9 -0.28 0.28 0.31 -0.6 -1.4 2.6 -0.74 -0.89 -0.56 -0.13 -0.64 -0.82 -0.51 8.4e+03 0.017 6.2 1.1 ++
10 -0.28 0.28 0.31 -0.6 -1.4 2.6 -0.74 -0.89 -0.56 -0.13 -0.64 -0.82 -0.51 8.4e+03 0.017 0.82 -6 -
11 -0.29 0.34 0.21 -0.85 -1.5 1.8 -1 -0.87 -0.57 -0.14 -0.6 -0.92 -0.56 8.4e+03 0.04 0.82 0.83 +
12 -0.38 0.43 0.35 -1 -1.5 1.6 -1.2 -0.85 -0.59 -0.13 -0.56 -0.96 -0.59 8.4e+03 0.01 8.2 1.2 ++
13 -0.38 0.43 0.35 -1 -1.5 1.6 -1.2 -0.85 -0.59 -0.13 -0.56 -0.96 -0.59 8.4e+03 0.01 0.32 -1 -
14 -0.44 0.53 0.38 -1.1 -1.5 1.3 -1.2 -0.82 -0.59 -0.14 -0.56 -0.96 -0.59 8.4e+03 0.014 3.2 1 ++
15 -0.56 0.65 0.54 -1.3 -1.6 1.1 -1.4 -0.8 -0.57 -0.11 -0.53 -1 -0.63 8.4e+03 0.01 32 1.2 ++
16 -0.61 0.72 0.55 -1.4 -1.7 1 -1.4 -0.78 -0.55 -0.11 -0.53 -1 -0.63 8.4e+03 0.0058 3.2e+02 1.3 ++
17 -0.62 0.72 0.55 -1.4 -1.7 1 -1.4 -0.78 -0.54 -0.1 -0.53 -1 -0.63 8.4e+03 0.00075 3.2e+03 1 ++
18 -0.67 0.77 0.67 -1.4 -1.7 1 -1.5 -0.78 -0.55 -0.099 -0.51 -1.1 -0.64 8.4e+03 4.9e-05 3.2e+04 1 ++
19 -0.67 0.77 0.67 -1.4 -1.7 1 -1.5 -0.78 -0.55 -0.099 -0.51 -1.1 -0.64 8.4e+03 1.9e-08 3.2e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 30/100
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000038
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_1st b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.26 0.5 0.072 -
1 -0.4 0.017 -0.5 -0.28 -0.39 1.3 0.27 0.0023 -0.053 -0.023 9.1e+03 0.13 0.5 0.72 +
2 -0.36 0.21 -0.67 -0.36 -0.44 1.3 -0.23 -0.056 -0.2 -0.058 8.6e+03 0.04 5 0.93 ++
3 -0.36 0.21 -0.67 -0.36 -0.44 1.3 -0.23 -0.056 -0.2 -0.058 8.6e+03 0.04 0.76 -1.8 -
4 -0.38 0.97 -0.96 -0.5 -0.95 1.6 -0.76 -0.43 -0.59 -0.29 8.3e+03 0.01 7.6 0.95 ++
5 -0.7 1.2 -1 -0.61 -1 1 -0.85 -0.42 -1.1 -0.34 8.2e+03 0.021 7.6 0.4 +
6 -0.9 1.3 -0.93 -0.67 -1 1.1 -0.87 -0.47 -1.1 -0.34 8.2e+03 0.00079 76 0.98 ++
7 -0.87 1.3 -0.94 -0.66 -1 1.1 -0.87 -0.46 -1.1 -0.34 8.2e+03 5.7e-05 7.6e+02 0.98 ++
8 -0.87 1.3 -0.94 -0.66 -1 1.1 -0.87 -0.46 -1.1 -0.34 8.2e+03 3.8e-07 7.6e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 31/100
Considering neighbor 0/20 for current solution
Attempt 32/100
Biogeme parameters read from biogeme.toml.
Model with 16 unknown parameters [max: 50]
*** Estimate b07everything_000039
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 9e+03 0.091 1 0.66 +
1 8.3e+03 0.0081 10 1 ++
2 8.3e+03 0.0081 5 -1e+06 -
3 8.3e+03 0.0081 2.5 -78 -
4 8.3e+03 0.0081 1.2 -2.7 -
5 8.2e+03 0.024 1.2 0.71 +
6 8.1e+03 0.0039 12 0.9 ++
7 8.1e+03 9e-05 1.2e+02 1 ++
8 8.1e+03 8.8e-08 1.2e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 33/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000040
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_1st b_cost_train mu_public b_cost_swissmet asc_car b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 1 0 0 0 1.1e+04 0.26 0.5 0.06 -
1 -0.4 -0.5 -0.28 -0.39 1.3 0.27 0.0018 -0.024 9.1e+03 0.13 0.5 0.71 +
2 -0.35 -0.68 -0.36 -0.45 1.3 -0.23 -0.073 -0.072 8.7e+03 0.034 5 0.92 ++
3 0.21 -0.8 -0.4 -1.4 1.8 -0.81 -0.63 -0.35 8.5e+03 0.04 50 0.91 ++
4 0.069 -0.81 -0.45 -1.6 1.7 -0.93 -0.64 -0.45 8.4e+03 0.0061 5e+02 1.1 ++
5 0.069 -0.81 -0.45 -1.6 1.7 -0.93 -0.64 -0.45 8.4e+03 0.0061 0.35 -1.3 -
6 -0.03 -0.86 -0.51 -1.6 1.4 -0.93 -0.61 -0.43 8.4e+03 0.011 3.5 0.92 ++
7 -0.042 -0.93 -0.56 -1.7 1.2 -0.94 -0.57 -0.39 8.4e+03 0.0036 35 1.2 ++
8 -0.084 -0.96 -0.6 -1.8 1.1 -0.93 -0.55 -0.37 8.4e+03 0.0025 3.5e+02 1.2 ++
9 -0.11 -0.97 -0.61 -1.8 1.1 -0.93 -0.53 -0.37 8.4e+03 0.00041 3.5e+03 1.1 ++
10 -0.12 -0.97 -0.61 -1.9 1.1 -0.93 -0.53 -0.36 8.4e+03 8.8e-05 3.5e+04 1.1 ++
11 -0.12 -0.97 -0.61 -1.9 1.1 -0.93 -0.53 -0.36 8.4e+03 8.9e-07 3.5e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 34/100
Biogeme parameters read from biogeme.toml.
Model with 18 unknown parameters [max: 50]
*** Estimate b07everything_000041
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 8.7e+03 0.047 1 0.83 +
1 8.2e+03 0.015 10 1 ++
2 8.2e+03 0.038 10 0.62 +
3 8.1e+03 0.003 1e+02 0.99 ++
4 8.1e+03 8.7e-05 1e+03 1 ++
5 8.1e+03 2e-07 1e+03 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000042
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train lambda_travel_t b_cost_train b_time_swissmet b_cost_swissmet asc_car b_time_car b_cost_car Function Relgrad Radius Rho
0 -0.99 -0.73 1.6 -0.55 -1 -0.61 -0.34 -0.77 -0.59 8.9e+03 0.041 1 0.89 +
1 -0.15 -1 1.1 -1.6 -1.1 -0.73 -0.32 -1 -0.45 8.5e+03 0.025 10 1.1 ++
2 0.33 -1.9 0.22 -1.9 -1.9 -0.79 -0.025 -1.6 -0.63 8.4e+03 0.03 10 0.79 +
3 0.39 -2.3 0.19 -1.8 -1.7 -0.77 0.079 -1.4 -0.8 8.3e+03 0.0028 1e+02 1 ++
4 0.4 -2.3 0.16 -1.9 -1.7 -0.77 0.091 -1.5 -0.8 8.3e+03 7.3e-05 1e+03 1 ++
5 0.4 -2.3 0.16 -1.9 -1.7 -0.77 0.091 -1.5 -0.8 8.3e+03 2.2e-08 1e+03 1 ++
Considering neighbor 1/20 for current solution
Attempt 35/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000043
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_com lambda_travel_t b_cost_train b_cost_swissmet asc_car b_cost_car Function Relgrad Radius Rho
0 -0.53 -1 -0.088 1.4 -0.36 -0.36 -0.12 -0.21 8.8e+03 0.051 10 0.95 ++
1 -0.53 -1 -0.088 1.4 -0.36 -0.36 -0.12 -0.21 8.8e+03 0.051 5 -1.3e+05 -
2 -0.53 -1 -0.088 1.4 -0.36 -0.36 -0.12 -0.21 8.8e+03 0.051 2.5 -47 -
3 -0.53 -1 -0.088 1.4 -0.36 -0.36 -0.12 -0.21 8.8e+03 0.051 1.2 -3.2 -
4 0.1 -1.7 -0.49 0.39 -1.6 -0.89 -0.42 -0.27 8.4e+03 0.025 12 0.95 ++
5 0.28 -1.6 -0.53 0.36 -2 -0.79 -0.13 -0.51 8.4e+03 0.0055 1.2e+02 1.1 ++
6 0.31 -1.6 -0.54 0.36 -2.1 -0.8 -0.14 -0.51 8.4e+03 0.00023 1.2e+03 1 ++
7 0.31 -1.6 -0.54 0.36 -2.1 -0.8 -0.14 -0.51 8.4e+03 3.6e-07 1.2e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 36/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000044
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost mu_public asc_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 1.1e+04 0.26 0.5 -0.074 -
1 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 9.1e+03 9.7 5 1.1 ++
2 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 9.1e+03 9.7 2.5 1.1 -
3 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 9.1e+03 9.7 1.2 1.1 -
4 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 9.1e+03 9.7 0.62 1.1 -
5 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 9.1e+03 9.7 0.31 1.1 -
6 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 9.1e+03 9.7 0.16 1.1 -
7 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 9.1e+03 9.7 0.078 -3.7 -
8 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 9.1e+03 9.7 0.039 -4.1 -
9 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 9.1e+03 9.7 0.02 -4.3 -
10 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 9.1e+03 9.7 0.0098 -3.1 -
11 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 9.1e+03 9.7 0.0049 -2.4 -
12 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 9.1e+03 9.7 0.0024 -2 -
13 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 9.1e+03 9.7 0.0012 -1.5 -
14 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 9.1e+03 9.7 0.00061 -0.87 -
15 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 9.1e+03 9.7 0.00031 -0.07 -
16 -0.5 -0.5 -0.5 0.00031 -0.00031 -0.5 1 0.034 9.1e+03 6 0.00031 0.69 +
17 -0.5 -0.5 -0.5 0.00031 -0.00031 -0.5 1 0.034 9.1e+03 6 0.00015 -1.2 -
18 -0.5 -0.5 -0.5 0.00031 -0.00031 -0.5 1 0.034 9.1e+03 6 7.6e-05 -0.77 -
19 -0.5 -0.5 -0.5 0.00038 -0.00023 -0.5 1 0.033 9.1e+03 5.7 7.6e-05 0.39 +
20 -0.5 -0.5 -0.5 0.00046 -0.00026 -0.5 1 0.033 9.1e+03 1.4 7.6e-05 0.82 +
21 -0.5 -0.5 -0.5 0.00053 -0.00025 -0.5 1 0.033 9.1e+03 0.14 0.00076 0.99 ++
22 -0.5 -0.5 -0.5 0.0013 -0.00026 -0.5 1 0.033 9.1e+03 0.32 0.0076 1 ++
23 -0.5 -0.51 -0.5 0.0089 -0.00029 -0.5 1 0.032 9.1e+03 0.14 0.076 1 ++
24 -0.54 -0.57 -0.51 0.085 -0.0006 -0.5 1 0.018 8.9e+03 0.48 0.76 0.98 ++
25 -0.39 -0.85 0.031 0.17 -0.00097 -0.71 1.4 -0.16 8.7e+03 1 0.76 0.62 +
26 -0.39 -0.85 0.031 0.17 -0.00097 -0.71 1.4 -0.16 8.7e+03 1 0.38 -26 -
27 -0.39 -0.85 0.031 0.17 -0.00097 -0.71 1.4 -0.16 8.7e+03 1 0.19 -2.4 -
28 -0.47 -0.93 -0.023 -0.017 -0.00019 -0.73 1.4 -0.12 8.7e+03 1.1 0.19 0.58 +
29 -0.41 -1.1 -0.11 -0.021 -0.00014 -0.73 1.4 -0.16 8.6e+03 10 1.9 1 ++
30 -0.41 -1.1 -0.11 -0.021 -0.00014 -0.73 1.4 -0.16 8.6e+03 10 0.85 -33 -
31 -0.41 -1.1 -0.11 -0.021 -0.00014 -0.73 1.4 -0.16 8.6e+03 10 0.42 -5 -
32 -0.41 -1.1 -0.11 -0.021 -0.00014 -0.73 1.4 -0.16 8.6e+03 10 0.21 -0.5 -
33 -0.43 -1.3 -0.22 -0.074 -1.3e-05 -0.75 1.4 -0.059 8.6e+03 17 0.21 0.48 +
34 -0.43 -1.3 -0.22 -0.074 -1.3e-05 -0.75 1.4 -0.059 8.6e+03 17 0.11 -0.21 -
35 -0.43 -1.3 -0.22 -0.074 -1.3e-05 -0.75 1.4 -0.059 8.6e+03 17 0.053 -0.0045 -
36 -0.43 -1.3 -0.22 -0.074 -1.3e-05 -0.75 1.4 -0.059 8.6e+03 17 0.027 -0.41 -
37 -0.43 -1.3 -0.22 -0.074 -1.3e-05 -0.75 1.4 -0.059 8.6e+03 17 0.013 -0.17 -
38 -0.43 -1.3 -0.22 -0.074 -1.3e-05 -0.75 1.4 -0.059 8.6e+03 17 0.0066 -0.078 -
39 -0.43 -1.3 -0.22 -0.074 -1.3e-05 -0.75 1.4 -0.059 8.6e+03 17 0.0033 -0.055 -
40 -0.43 -1.3 -0.22 -0.074 -1.3e-05 -0.75 1.4 -0.059 8.6e+03 17 0.0017 -0.051 -
41 -0.43 -1.3 -0.22 -0.074 -1.3e-05 -0.75 1.4 -0.059 8.6e+03 17 0.00083 -0.051 -
42 -0.43 -1.3 -0.22 -0.074 -1.3e-05 -0.75 1.4 -0.059 8.6e+03 17 0.00041 -0.051 -
43 -0.43 -1.3 -0.22 -0.074 -1.3e-05 -0.75 1.4 -0.059 8.6e+03 17 0.00021 -0.052 -
44 -0.43 -1.3 -0.22 -0.074 -1.3e-05 -0.75 1.4 -0.059 8.6e+03 17 0.0001 -0.052 -
45 -0.43 -1.3 -0.22 -0.074 9.1e-05 -0.75 1.4 -0.059 8.6e+03 14 0.0001 0.44 +
46 -0.43 -1.3 -0.22 -0.074 9.1e-05 -0.75 1.4 -0.059 8.6e+03 14 5.2e-05 -0.65 -
47 -0.43 -1.3 -0.22 -0.074 3.9e-05 -0.75 1.4 -0.059 8.6e+03 8.5 5.2e-05 0.41 +
48 -0.43 -1.3 -0.22 -0.074 6.2e-05 -0.75 1.4 -0.059 8.6e+03 4.2 5.2e-05 0.64 +
49 -0.43 -1.3 -0.22 -0.074 5.5e-05 -0.75 1.4 -0.059 8.6e+03 0.18 0.00052 0.97 ++
50 -0.43 -1.3 -0.22 -0.073 5.3e-05 -0.75 1.4 -0.059 8.6e+03 0.032 0.0052 1 ++
51 -0.43 -1.3 -0.22 -0.068 3e-05 -0.75 1.4 -0.061 8.6e+03 0.21 0.052 1 ++
52 -0.38 -1.4 -0.24 -0.061 1.6e-06 -0.74 1.3 -0.093 8.6e+03 0.72 0.52 1 ++
53 -0.38 -1.4 -0.24 -0.061 1.6e-06 -0.74 1.3 -0.093 8.6e+03 0.72 0.26 -0.067 -
54 -0.39 -1.6 -0.37 -0.096 0.00014 -0.75 1.3 0.0056 8.6e+03 14 0.26 0.79 +
55 -0.36 -1.9 -0.53 -0.095 0.00015 -0.77 1.1 0.061 8.6e+03 8.1 2.6 0.95 ++
56 -0.42 -2 -0.67 -0.097 0.00016 -0.79 1 0.16 8.6e+03 4.9 26 1 ++
57 -0.45 -2 -0.7 -0.099 0.00017 -0.79 1 0.14 8.6e+03 0.15 2.6e+02 1 ++
58 -0.43 -2.1 -0.88 -0.1 0.00018 -0.79 1 0.17 8.6e+03 0.12 2.6e+03 1 ++
59 -0.44 -2 -0.89 -0.1 0.00017 -0.79 1 0.16 8.6e+03 0.023 2.6e+04 1 ++
60 -0.43 -2.1 -0.9 -0.1 0.00017 -0.79 1 0.16 8.6e+03 0.0022 2.6e+05 1 ++
61 -0.43 -2.1 -0.9 -0.1 0.00017 -0.79 1 0.16 8.6e+03 0.0002 2.6e+06 1 ++
62 -0.43 -2.1 -0.91 -0.1 0.00017 -0.79 1 0.16 8.6e+03 0.001 2.6e+07 1 ++
63 -0.43 -2.1 -0.91 -0.1 0.00017 -0.79 1 0.16 8.6e+03 2.4e-06 2.6e+07 1 ++
Considering neighbor 0/20 for current solution
Attempt 37/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000045
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.26 0.5 0.03 -
1 -0.39 -0.17 -0.0081 -0.5 -0.28 -0.38 1.4 0.25 -0.0083 -0.035 -0.0047 -0.034 9.2e+03 0.14 0.5 0.64 +
2 -0.3 0.066 -0.0015 -0.67 -0.37 -0.43 1.3 -0.25 -0.089 -0.15 -0.019 -0.089 8.7e+03 0.048 0.5 0.89 +
3 -0.35 0.38 0.024 -0.97 -0.51 -0.93 1.5 -0.64 -0.23 -0.28 -0.058 -0.17 8.4e+03 0.017 5 1.1 ++
4 -0.46 0.52 0.43 -0.91 -0.52 -1.5 1.4 -0.9 -0.51 -0.14 -0.51 -0.36 8.3e+03 0.0083 50 1.1 ++
5 -0.62 0.64 0.54 -0.97 -0.59 -1.6 1.1 -0.93 -0.48 -0.13 -0.61 -0.35 8.3e+03 0.0085 5e+02 1 ++
6 -0.7 0.7 0.59 -0.98 -0.61 -1.7 1.1 -0.92 -0.47 -0.12 -0.61 -0.35 8.3e+03 0.0011 5e+03 1.1 ++
7 -0.73 0.72 0.59 -1 -0.62 -1.8 1 -0.91 -0.45 -0.12 -0.61 -0.33 8.3e+03 0.00073 5e+04 1 ++
8 -0.75 0.73 0.59 -0.99 -0.62 -1.8 1 -0.91 -0.45 -0.12 -0.61 -0.34 8.3e+03 9.8e-05 5e+05 1 ++
9 -0.75 0.73 0.59 -0.99 -0.62 -1.8 1 -0.91 -0.45 -0.12 -0.61 -0.34 8.3e+03 2.3e-06 5e+05 1 ++
Considering neighbor 0/20 for current solution
Attempt 38/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000046
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di square_tt_coef cube_tt_coef b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_time_swissmet b_time_swissmet Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.26 -
1 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.5 0.85 +
2 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.25 0.85 -
3 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.12 0.85 -
4 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.062 0.85 -
5 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.031 -32 -
6 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.016 -7.4 -
7 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.0078 -2.2 -
8 -0.27 0.0077 -0.51 -0.079 -0.007 0.00013 -0.046 1.2 -0.0003 -0.03 -0.028 -0.014 0.19 0.054 9.3e+03 0.31 0.078 0.94 ++
9 -0.27 0.039 -0.53 -0.086 0.016 -0.0016 -0.11 1.2 -0.036 -0.053 -0.11 -0.039 0.19 0.067 9.2e+03 6 0.078 0.68 +
10 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.078 0.62 +
11 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.039 0.62 -
12 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.02 0.62 -
13 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.0098 -6.1 -
14 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.0049 -4 -
15 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.0024 -2.3 -
16 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.0012 -0.28 -
17 -0.28 0.081 -0.56 -0.099 0.0014 -0.00019 -0.19 1.3 -0.045 -0.08 -0.16 -0.079 0.14 0.082 9e+03 1.1 0.012 0.96 ++
18 -0.28 0.088 -0.57 -0.1 0.0068 -0.00029 -0.2 1.3 -0.045 -0.085 -0.17 -0.082 0.13 0.083 9e+03 0.32 0.12 0.99 ++
19 -0.28 0.16 -0.61 -0.11 0.057 -0.00047 -0.32 1.4 -0.045 -0.13 -0.2 -0.11 0.028 0.099 8.8e+03 0.23 1.2 0.99 ++
20 -0.28 0.16 -0.61 -0.11 0.057 -0.00047 -0.32 1.4 -0.045 -0.13 -0.2 -0.11 0.028 0.099 8.8e+03 0.23 0.61 -0.95 -
21 -0.18 0.54 -0.57 -0.16 0.24 -0.0012 -0.76 1.7 -0.15 -0.34 -0.56 -0.24 -0.58 0.16 8.6e+03 1.6 0.61 0.29 +
22 -0.18 0.54 -0.57 -0.16 0.24 -0.0012 -0.76 1.7 -0.15 -0.34 -0.56 -0.24 -0.58 0.16 8.6e+03 1.6 0.31 -0.7 -
23 -0.31 0.64 -0.58 -0.22 0.48 -0.0021 -0.58 2 -0.17 -0.38 -0.35 -0.16 -0.67 0.34 8.4e+03 6.9 0.31 0.55 +
24 -0.46 0.75 -0.52 -0.094 0.34 -0.0016 -0.53 2 -0.34 -0.43 -0.34 0.032 -0.57 0.65 8.2e+03 1.4 0.31 0.88 +
25 -0.76 0.89 -0.58 0.061 0.3 -0.0014 -0.57 1.9 -0.5 -0.44 -0.43 0.15 -0.82 0.7 8.1e+03 0.89 3.1 0.96 ++
26 -0.76 0.89 -0.58 0.061 0.3 -0.0014 -0.57 1.9 -0.5 -0.44 -0.43 0.15 -0.82 0.7 8.1e+03 0.89 0.71 -1.2e+02 -
27 -0.76 0.89 -0.58 0.061 0.3 -0.0014 -0.57 1.9 -0.5 -0.44 -0.43 0.15 -0.82 0.7 8.1e+03 0.89 0.36 -15 -
28 -0.77 1.1 -0.84 0.24 0.093 -0.00059 -0.6 1.7 -0.46 -0.36 -0.64 0.34 -1.1 1.1 8.1e+03 0.67 0.36 0.64 +
29 -0.74 1 -1.1 0.26 0.049 -0.00046 -0.62 1.8 -0.49 -0.38 -0.82 0.4 -1.4 1.3 8.1e+03 1.1 3.6 1.2 ++
30 -0.74 1 -1.1 0.26 0.049 -0.00046 -0.62 1.8 -0.49 -0.38 -0.82 0.4 -1.4 1.3 8.1e+03 1.1 0.77 -1.8e+02 -
31 -0.74 1 -1.1 0.26 0.049 -0.00046 -0.62 1.8 -0.49 -0.38 -0.82 0.4 -1.4 1.3 8.1e+03 1.1 0.38 -20 -
32 -0.74 1 -1.1 0.26 0.049 -0.00046 -0.62 1.8 -0.49 -0.38 -0.82 0.4 -1.4 1.3 8.1e+03 1.1 0.19 -0.21 -
33 -0.69 1.1 -1.3 0.21 -0.028 -0.0001 -0.61 1.8 -0.47 -0.37 -0.96 0.37 -1.5 1.3 8.1e+03 2.1 0.19 0.86 +
34 -0.59 1 -1.4 0.24 -0.039 -9.2e-05 -0.6 1.8 -0.46 -0.34 -1.1 0.29 -1.7 1.3 8.1e+03 3 1.9 1 ++
35 -0.59 1 -1.4 0.24 -0.039 -9.2e-05 -0.6 1.8 -0.46 -0.34 -1.1 0.29 -1.7 1.3 8.1e+03 3 0.96 -1.1e+02 -
36 -0.59 1 -1.4 0.24 -0.039 -9.2e-05 -0.6 1.8 -0.46 -0.34 -1.1 0.29 -1.7 1.3 8.1e+03 3 0.48 -14 -
37 -0.59 1 -1.4 0.24 -0.039 -9.2e-05 -0.6 1.8 -0.46 -0.34 -1.1 0.29 -1.7 1.3 8.1e+03 3 0.24 -1.7 -
38 -0.49 1.1 -1.7 0.17 -0.085 8.5e-05 -0.59 1.9 -0.44 -0.34 -1.3 0.34 -1.9 1.2 8.1e+03 13 0.24 0.73 +
39 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.24 0.56 +
40 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.12 -3.6 -
41 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.06 -2.9 -
42 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.03 -2.6 -
43 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.015 -2.5 -
44 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.0075 -2.5 -
45 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.0037 -2.1 -
46 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.0019 -2.1 -
47 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.00094 -2.1 -
48 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.00047 -2.1 -
49 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.00023 -2.2 -
50 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.00012 -2.2 -
51 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 5.9e-05 -1.4 -
52 -0.38 0.99 -1.9 0.17 -0.096 0.00014 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 19 5.9e-05 0.22 +
53 -0.38 0.99 -1.9 0.17 -0.096 0.00017 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 6.9 5.9e-05 0.74 +
54 -0.38 0.99 -1.9 0.17 -0.096 0.00016 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 1 5.9e-05 0.89 +
55 -0.38 0.99 -1.9 0.17 -0.096 0.00016 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 0.012 0.00059 1 ++
56 -0.38 0.99 -1.9 0.17 -0.095 0.00016 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 0.15 0.0059 1 ++
57 -0.38 0.99 -1.9 0.16 -0.094 0.00015 -0.59 1.9 -0.41 -0.29 -1.5 0.16 -2.1 1.1 8e+03 0.011 0.059 1 ++
58 -0.34 1 -2 0.12 -0.096 0.00016 -0.61 1.9 -0.42 -0.31 -1.5 0.18 -2.1 1.1 8e+03 0.13 0.59 1 ++
59 -0.29 1 -2.1 -0.1 -0.1 0.00019 -0.62 1.8 -0.39 -0.39 -1.6 -0.1 -2.2 0.72 8e+03 2.5 5.9 0.97 ++
60 -0.28 1 -2.1 -0.12 -0.1 0.00019 -0.62 1.8 -0.39 -0.35 -1.6 -0.12 -2.2 0.69 8e+03 0.046 59 1 ++
61 -0.28 1 -2.1 -0.13 -0.1 0.00019 -0.62 1.8 -0.39 -0.36 -1.6 -0.14 -2.2 0.67 8e+03 0.00019 5.9e+02 1 ++
62 -0.28 1 -2.1 -0.14 -0.1 0.00019 -0.62 1.8 -0.39 -0.36 -1.6 -0.15 -2.2 0.66 8e+03 0.00014 5.9e+03 1 ++
63 -0.28 1 -2.1 -0.14 -0.1 0.00019 -0.62 1.8 -0.39 -0.36 -1.6 -0.15 -2.2 0.66 8e+03 0.00014 5.9e+04 1 ++
64 -0.28 1 -2.1 -0.14 -0.1 0.00019 -0.62 1.8 -0.39 -0.36 -1.6 -0.15 -2.2 0.65 8e+03 3.3e-05 5.9e+05 1 ++
65 -0.28 1 -2.1 -0.14 -0.1 0.00019 -0.62 1.8 -0.39 -0.36 -1.6 -0.15 -2.2 0.65 8e+03 5e-06 5.9e+05 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000047
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -1.9 -
1 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.023 -
2 -0.25 -0.00017 -0.25 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 1.4 2.5 1 ++
3 -0.25 -0.00017 -0.25 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 1.4 1.2 -4 -
4 -0.25 -0.00017 -0.25 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 1.4 0.62 -2.6 -
5 -0.25 -0.00017 -0.25 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 1.4 0.31 -0.99 -
6 -0.47 0.03 -0.56 0.22 -0.0045 -0.46 0.23 0.049 -0.073 0.023 9.3e+03 12 0.31 0.29 +
7 -0.47 0.03 -0.56 0.22 -0.0045 -0.46 0.23 0.049 -0.073 0.023 9.3e+03 12 0.16 -0.37 -
8 -0.47 0.03 -0.56 0.22 -0.0045 -0.46 0.23 0.049 -0.073 0.023 9.3e+03 12 0.078 -0.13 -
9 -0.47 0.03 -0.56 0.22 -0.0045 -0.46 0.23 0.049 -0.073 0.023 9.3e+03 12 0.039 -0.047 -
10 -0.47 0.03 -0.56 0.22 -0.0045 -0.46 0.23 0.049 -0.073 0.023 9.3e+03 12 0.02 -0.021 -
11 -0.47 0.03 -0.56 0.22 -0.0045 -0.46 0.23 0.049 -0.073 0.023 9.3e+03 12 0.0098 -0.012 -
12 -0.47 0.03 -0.56 0.22 -0.0045 -0.46 0.23 0.049 -0.073 0.023 9.3e+03 12 0.0049 -0.0089 -
13 -0.47 0.032 -0.56 0.23 0.00036 -0.46 0.23 0.051 -0.074 0.025 9.1e+03 6.5 0.0049 0.4 +
14 -0.47 0.032 -0.56 0.23 0.00036 -0.46 0.23 0.051 -0.074 0.025 9.1e+03 6.5 0.0024 -0.42 -
15 -0.46 0.034 -0.56 0.22 -0.0021 -0.46 0.22 0.053 -0.077 0.027 9e+03 4.7 0.0024 0.49 +
16 -0.46 0.035 -0.56 0.22 -0.0017 -0.46 0.22 0.054 -0.077 0.028 9e+03 2.6 0.024 1.3 ++
17 -0.46 0.035 -0.56 0.22 -0.0017 -0.46 0.22 0.054 -0.077 0.028 9e+03 2.6 0.012 -2.2 -
18 -0.46 0.035 -0.56 0.22 -0.0017 -0.46 0.22 0.054 -0.077 0.028 9e+03 2.6 0.0061 -2.9 -
19 -0.46 0.035 -0.56 0.22 -0.0017 -0.46 0.22 0.054 -0.077 0.028 9e+03 2.6 0.0031 -3.4 -
20 -0.46 0.035 -0.56 0.22 -0.0017 -0.46 0.22 0.054 -0.077 0.028 9e+03 2.6 0.0015 -2.4 -
21 -0.46 0.035 -0.56 0.22 -0.0017 -0.46 0.22 0.054 -0.077 0.028 9e+03 2.6 0.00076 -1.3 -
22 -0.46 0.035 -0.56 0.22 -0.0017 -0.46 0.22 0.054 -0.077 0.028 9e+03 2.6 0.00038 0.025 -
23 -0.46 0.035 -0.55 0.22 -0.0013 -0.46 0.22 0.054 -0.078 0.028 9e+03 2.5 0.0038 1 ++
24 -0.46 0.035 -0.55 0.22 -0.0013 -0.46 0.22 0.054 -0.078 0.028 9e+03 2.5 0.0019 -2.7 -
25 -0.46 0.035 -0.55 0.22 -0.0013 -0.46 0.22 0.054 -0.078 0.028 9e+03 2.5 0.00095 -3.3 -
26 -0.46 0.035 -0.55 0.22 -0.0013 -0.46 0.22 0.054 -0.078 0.028 9e+03 2.5 0.00048 -3 -
27 -0.46 0.035 -0.55 0.22 -0.0013 -0.46 0.22 0.054 -0.078 0.028 9e+03 2.5 0.00024 -1.6 -
28 -0.46 0.035 -0.55 0.22 -0.0013 -0.46 0.22 0.054 -0.078 0.028 9e+03 2.5 0.00012 -0.27 -
29 -0.46 0.035 -0.55 0.22 -0.0012 -0.46 0.22 0.054 -0.078 0.028 9e+03 0.11 0.00012 0.79 +
30 -0.46 0.035 -0.55 0.22 -0.0012 -0.46 0.22 0.054 -0.078 0.028 9e+03 0.6 0.0012 1 ++
31 -0.46 0.036 -0.55 0.22 -0.0012 -0.46 0.22 0.055 -0.078 0.028 9e+03 0.11 0.012 1 ++
32 -0.46 0.038 -0.55 0.22 -0.0012 -0.46 0.21 0.057 -0.08 0.031 9e+03 1.3 0.12 1 ++
33 -0.45 0.066 -0.54 0.18 -0.001 -0.47 0.088 0.076 -0.1 0.056 8.9e+03 0.71 1.2 0.98 ++
34 -0.84 1.3 -0.88 -0.0033 -0.00026 -1.1 -0.68 -0.34 -0.42 -0.34 8.3e+03 2 12 1 ++
35 -0.84 1.3 -1.3 -0.012 -0.00019 -1 -0.75 -0.33 -0.95 -0.33 8.2e+03 5.6 1.2e+02 1.1 ++
36 -0.84 1.3 -1.3 -0.012 -0.00019 -1 -0.75 -0.33 -0.95 -0.33 8.2e+03 5.6 60 -8.4e+02 -
37 -0.84 1.3 -1.3 -0.012 -0.00019 -1 -0.75 -0.33 -0.95 -0.33 8.2e+03 5.6 30 -7.1e+02 -
38 -0.84 1.3 -1.3 -0.012 -0.00019 -1 -0.75 -0.33 -0.95 -0.33 8.2e+03 5.6 15 -5.5e+02 -
39 -0.84 1.3 -1.3 -0.012 -0.00019 -1 -0.75 -0.33 -0.95 -0.33 8.2e+03 5.6 7.5 -3.7e+02 -
40 -0.84 1.3 -1.3 -0.012 -0.00019 -1 -0.75 -0.33 -0.95 -0.33 8.2e+03 5.6 3.7 -2.2e+02 -
41 -0.84 1.3 -1.3 -0.012 -0.00019 -1 -0.75 -0.33 -0.95 -0.33 8.2e+03 5.6 1.9 -1.1e+02 -
42 -0.84 1.3 -1.3 -0.012 -0.00019 -1 -0.75 -0.33 -0.95 -0.33 8.2e+03 5.6 0.93 -38 -
43 -0.84 1.3 -1.3 -0.012 -0.00019 -1 -0.75 -0.33 -0.95 -0.33 8.2e+03 5.6 0.47 -11 -
44 -0.84 1.3 -1.3 -0.012 -0.00019 -1 -0.75 -0.33 -0.95 -0.33 8.2e+03 5.6 0.23 -3 -
45 -0.84 1.3 -1.3 -0.012 -0.00019 -1 -0.75 -0.33 -0.95 -0.33 8.2e+03 5.6 0.12 0.033 -
46 -0.87 1.3 -1.4 -0.085 9.1e-05 -1 -0.69 -0.36 -0.96 -0.37 8.2e+03 4.3 0.12 0.66 +
47 -0.86 1.3 -1.6 -0.073 4.5e-05 -1 -0.74 -0.32 -0.96 -0.35 8.2e+03 1 1.2 1 ++
48 -0.86 1.3 -1.6 -0.073 4.5e-05 -1 -0.74 -0.32 -0.96 -0.35 8.2e+03 1 0.41 -1 -
49 -0.76 1.4 -2 -0.11 0.00023 -1 -0.77 -0.28 -1 -0.39 8.2e+03 9.3 0.41 0.62 +
50 -0.59 1.3 -2.2 -0.1 0.00019 -1.1 -0.77 -0.22 -1.1 -0.32 8.2e+03 3.2 4.1 0.91 ++
51 -0.59 1.3 -2.2 -0.11 0.0002 -1.1 -0.77 -0.2 -1.1 -0.34 8.2e+03 0.049 41 0.99 ++
52 -0.6 1.3 -2.2 -0.11 0.0002 -1.1 -0.77 -0.21 -1.1 -0.34 8.2e+03 0.00014 4.1e+02 1 ++
53 -0.6 1.3 -2.2 -0.11 0.0002 -1.1 -0.77 -0.21 -1.1 -0.34 8.2e+03 2e-06 4.1e+02 1 ++
Considering neighbor 1/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000048
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time lambda_travel_t b_cost_train mu_existing asc_car_ref asc_car_diff_GA b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 -0.65 0.21 -1 1.4 -0.55 1.9 0.25 -0.26 0.14 -0.64 9.8e+03 0.23 1 0.43 +
1 -0.65 0.21 -1 1.4 -0.55 1.9 0.25 -0.26 0.14 -0.64 9.8e+03 0.23 0.5 -0.7 -
2 -0.26 0.4 -0.81 1.1 -0.4 1.8 -0.25 -0.38 -0.27 -0.46 8.6e+03 0.11 0.5 0.71 +
3 -0.42 0.67 -0.98 0.7 -0.64 2.3 -0.22 -0.51 -0.25 -0.52 8.2e+03 0.011 5 0.92 ++
4 -0.42 0.67 -0.98 0.7 -0.64 2.3 -0.22 -0.51 -0.25 -0.52 8.2e+03 0.011 0.64 -0.68 -
5 -0.24 1.1 -1.6 0.16 -0.81 1.6 -0.03 -0.34 -0.36 -0.64 8.2e+03 0.0074 0.64 0.75 +
6 -0.32 1 -1.6 0.35 -0.81 1.6 -0.083 -0.49 -0.34 -0.64 8.2e+03 0.0021 6.4 1 ++
7 -0.34 1 -1.5 0.36 -0.81 1.6 -0.09 -0.5 -0.34 -0.64 8.2e+03 1.6e-05 64 1 ++
8 -0.34 1 -1.5 0.36 -0.81 1.6 -0.09 -0.5 -0.34 -0.64 8.2e+03 1.6e-08 64 1 ++
Considering neighbor 2/20 for current solution
Attempt 39/100
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000049
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di square_tt_coef cube_tt_coef b_cost b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.26 -
1 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.5 0.64 +
2 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.25 -8.2 -
3 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.12 -10 -
4 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.062 -13 -
5 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.031 -29 -
6 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.016 -2.3 -
7 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.16 0.97 ++
8 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.078 -14 -
9 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.039 -13 -
10 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.02 -12 -
11 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.0098 -13 -
12 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.0049 -4.1 -
13 -0.27 -0.12 0.0052 -0.52 -0.092 -0.0088 -0.0011 -0.059 0.18 0.067 -0.013 -0.027 -0.022 -0.01 -0.011 9.4e+03 1.8 0.0049 0.71 +
14 -0.27 -0.12 0.0053 -0.52 -0.092 -0.0068 -0.00074 -0.062 0.18 0.068 -0.016 -0.029 -0.022 -0.015 -0.012 9.4e+03 0.46 0.049 1 ++
15 -0.28 -0.11 0.0056 -0.54 -0.097 0.013 -0.00052 -0.095 0.19 0.076 -0.04 -0.047 -0.024 -0.064 -0.026 9.3e+03 0.29 0.49 1 ++
16 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.49 0.5 +
17 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.24 -6.9 -
18 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.12 -7.6 -
19 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.061 -14 -
20 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.031 -5.5 -
21 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.015 -3.6 -
22 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.0076 -2.6 -
23 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.0038 -1.6 -
24 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.0019 -0.28 -
25 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0014 -0.59 -0.11 0.16 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 4.5 0.0019 0.8 +
26 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0014 -0.59 -0.11 0.16 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 4.5 0.00095 -0.7 -
27 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0014 -0.59 -0.11 0.16 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 4.5 0.00048 -0.45 -
28 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0014 -0.59 -0.11 0.16 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 4.5 0.00024 0.021 -
29 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0011 -0.59 -0.11 0.15 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 0.79 0.00024 0.82 +
30 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0011 -0.59 -0.11 0.15 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 0.14 0.0024 1 ++
31 -0.33 0.048 0.015 -0.75 -0.16 0.21 -0.0011 -0.59 -0.12 0.15 -0.13 -0.16 -0.041 -0.41 -0.19 8.9e+03 0.7 0.024 1 ++
32 -0.33 0.052 0.015 -0.75 -0.16 0.2 -0.0011 -0.59 -0.14 0.15 -0.13 -0.15 -0.041 -0.39 -0.19 8.8e+03 0.11 0.24 1 ++
33 -0.33 0.12 0.019 -0.76 -0.17 0.28 -0.0014 -0.64 -0.38 0.16 -0.083 -0.13 -0.045 -0.33 -0.19 8.6e+03 0.48 0.24 0.81 +
34 -0.34 0.26 0.032 -0.72 -0.2 0.4 -0.0019 -0.71 -0.62 0.31 -0.14 -0.17 -0.06 -0.44 -0.2 8.5e+03 0.32 0.24 0.83 +
35 -0.48 0.35 0.051 -0.79 -0.18 0.3 -0.0015 -0.76 -0.57 0.55 -0.21 -0.2 -0.082 -0.44 -0.09 8.5e+03 0.27 0.24 0.85 +
36 -0.66 0.51 0.1 -0.84 -0.078 0.36 -0.0018 -0.77 -0.81 0.64 -0.33 -0.19 -0.12 -0.5 0.096 8.4e+03 0.38 0.24 0.85 +
37 -0.8 0.6 0.15 -0.87 -0.0017 0.33 -0.0016 -0.78 -0.85 0.88 -0.34 -0.11 -0.16 -0.53 0.12 8.4e+03 0.91 0.24 0.74 +
38 -0.99 0.76 0.29 -1.1 0.083 0.17 -0.00098 -0.79 -1.1 0.88 -0.49 -0.15 -0.23 -0.64 0.14 8.4e+03 0.074 0.24 0.84 +
39 -1 0.88 0.48 -1.2 0.14 0.12 -0.00077 -0.78 -1.2 1.1 -0.42 -0.081 -0.31 -0.79 0.34 8.4e+03 0.012 2.4 1.1 ++
40 -1 0.88 0.48 -1.2 0.14 0.12 -0.00077 -0.78 -1.2 1.1 -0.42 -0.081 -0.31 -0.79 0.34 8.4e+03 0.012 0.55 -32 -
41 -1 0.88 0.48 -1.2 0.14 0.12 -0.00077 -0.78 -1.2 1.1 -0.42 -0.081 -0.31 -0.79 0.34 8.4e+03 0.012 0.28 -1.1 -
42 -1 0.86 0.67 -1.5 0.23 0.017 -0.00034 -0.79 -1.5 1.2 -0.49 -0.1 -0.38 -0.96 0.28 8.4e+03 0.22 2.8 1 ++
43 -0.81 0.92 0.88 -2 0.28 -0.054 -4.5e-05 -0.8 -1.9 1.4 -0.42 -0.1 -0.46 -1.3 0.34 8.3e+03 0.8 28 1.2 ++
44 -0.58 0.91 0.85 -2.5 0.2 -0.088 0.00011 -0.8 -2.2 1.2 -0.38 -0.1 -0.48 -1.6 0.21 8.3e+03 0.2 2.8e+02 1.3 ++
45 -0.39 0.89 0.82 -2.8 0.028 -0.1 0.00017 -0.8 -2.4 0.91 -0.35 -0.11 -0.5 -1.7 -0.0096 8.3e+03 1.4 2.8e+03 1.1 ++
46 -0.43 0.9 0.8 -2.8 -0.096 -0.099 0.00016 -0.8 -2.4 0.7 -0.36 -0.11 -0.52 -1.7 -0.16 8.3e+03 0.12 2.8e+04 0.99 ++
47 -0.42 0.9 0.8 -2.8 -0.099 -0.1 0.00016 -0.8 -2.4 0.7 -0.35 -0.11 -0.52 -1.7 -0.17 8.3e+03 0.038 2.8e+05 1 ++
48 -0.42 0.9 0.8 -2.8 -0.11 -0.1 0.00016 -0.8 -2.4 0.68 -0.35 -0.11 -0.51 -1.7 -0.18 8.3e+03 0.067 2.8e+06 1 ++
49 -0.42 0.9 0.8 -2.8 -0.11 -0.1 0.00016 -0.8 -2.4 0.68 -0.35 -0.11 -0.52 -1.7 -0.18 8.3e+03 0.00016 2.8e+07 1 ++
50 -0.42 0.9 0.8 -2.8 -0.11 -0.1 0.00016 -0.8 -2.4 0.68 -0.35 -0.11 -0.52 -1.7 -0.18 8.3e+03 0.00035 2.8e+08 1 ++
51 -0.42 0.9 0.8 -2.8 -0.11 -0.1 0.00016 -0.8 -2.4 0.68 -0.35 -0.11 -0.52 -1.7 -0.18 8.3e+03 1.4e-05 2.8e+09 1 ++
52 -0.42 0.9 0.8 -2.8 -0.11 -0.1 0.00016 -0.8 -2.4 0.68 -0.35 -0.11 -0.52 -1.7 -0.18 8.3e+03 4.2e-07 2.8e+09 1 ++
Considering neighbor 0/20 for current solution
Attempt 40/100
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000050
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train_re b_time_train_di lambda_travel_t b_cost mu_existing asc_car b_time_car_ref b_time_car_diff b_time_swissmet b_time_swissmet Function Relgrad Radius Rho
0 -0.9 -0.79 -0.046 1.7 -1 1.8 -0.0035 -0.55 -0.08 -0.61 -0.11 9e+03 0.087 1 0.67 +
1 -0.9 -0.79 -0.046 1.7 -1 1.8 -0.0035 -0.55 -0.08 -0.61 -0.11 9e+03 0.087 0.5 -0.45 -
2 -0.43 -0.86 -0.11 1.3 -0.5 2 -0.36 -0.41 0.12 -0.77 0.041 8.6e+03 0.052 0.5 0.75 +
3 -0.35 -1.1 -0.16 0.75 -0.64 2.4 -0.1 -0.72 0.25 -0.98 0.14 8.4e+03 0.016 5 0.92 ++
4 -0.35 -1.1 -0.16 0.75 -0.64 2.4 -0.1 -0.72 0.25 -0.98 0.14 8.4e+03 0.016 1.9 -23 -
5 -0.35 -1.1 -0.16 0.75 -0.64 2.4 -0.1 -0.72 0.25 -0.98 0.14 8.4e+03 0.016 0.97 -4.9 -
6 -0.35 -1.1 -0.16 0.75 -0.64 2.4 -0.1 -0.72 0.25 -0.98 0.14 8.4e+03 0.016 0.49 -0.14 -
7 0.044 -1.6 -0.14 0.28 -0.54 2.6 0.074 -0.96 0.22 -1.3 -0.062 8.3e+03 0.011 0.49 0.83 +
8 0.053 -1.8 -0.15 0.1 -0.61 2.4 0.089 -1.1 0.12 -1.3 -0.52 8.3e+03 0.0042 4.9 1 ++
9 0.046 -1.9 -0.14 0.12 -0.62 2.3 0.09 -1.1 0.11 -1.3 -0.48 8.3e+03 0.00019 49 1 ++
10 0.046 -1.9 -0.14 0.12 -0.62 2.3 0.09 -1.1 0.11 -1.3 -0.48 8.3e+03 1.1e-06 49 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000051
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_1st lambda_travel_t b_cost_train mu_public b_cost_swissmet asc_car b_cost_car Function Relgrad Radius Rho
0 0 0 0 1 0 1 0 0 0 1.1e+04 0.26 0.5 0.037 -
1 -0.4 -0.5 -0.28 1 -0.39 1.3 0.27 0.002 -0.023 9.1e+03 0.13 0.5 0.71 +
2 -0.35 -0.67 -0.36 1 -0.45 1.3 -0.23 -0.072 -0.069 8.7e+03 0.034 5 0.92 ++
3 0.54 -1.2 -0.31 0.16 -1.5 1.9 -0.78 -0.46 -0.41 8.5e+03 0.048 5 0.73 +
4 0.34 -1.2 -0.38 0.46 -1.6 1.8 -0.91 -0.44 -0.53 8.4e+03 0.007 50 1.1 ++
5 0.34 -1.2 -0.38 0.46 -1.6 1.8 -0.91 -0.44 -0.53 8.4e+03 0.007 0.4 -0.92 -
6 0.19 -1.2 -0.47 0.55 -1.6 1.4 -0.94 -0.44 -0.52 8.4e+03 0.015 4 0.99 ++
7 0.21 -1.3 -0.51 0.49 -1.8 1.2 -0.91 -0.37 -0.47 8.3e+03 0.0066 40 1.3 ++
8 0.18 -1.4 -0.55 0.47 -1.9 1.1 -0.9 -0.3 -0.45 8.3e+03 0.0055 4e+02 1.2 ++
9 0.14 -1.4 -0.56 0.46 -2 1 -0.88 -0.28 -0.44 8.3e+03 0.0015 4e+03 1.2 ++
10 0.14 -1.4 -0.56 0.46 -2 1 -0.88 -0.28 -0.44 8.3e+03 0.00061 4e+04 1 ++
11 0.15 -1.4 -0.56 0.45 -2 1 -0.88 -0.27 -0.45 8.3e+03 6.1e-06 4e+05 1 ++
12 0.15 -1.4 -0.56 0.45 -2 1 -0.88 -0.27 -0.45 8.3e+03 3e-10 4e+05 1 ++
Considering neighbor 1/20 for current solution
Attempt 41/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000052
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_time_swissmet b_time_swissmet Function Relgrad Radius Rho
0 -0.95 0.39 -0.73 -0.35 1.8 -1 1.8 0.064 -0.33 -0.53 -0.41 -0.63 -0.36 8.8e+03 0.074 1 0.62 +
1 -0.95 0.39 -0.73 -0.35 1.8 -1 1.8 0.064 -0.33 -0.53 -0.41 -0.63 -0.36 8.8e+03 0.074 0.5 -0.081 -
2 -0.59 0.73 -0.67 -0.34 1.4 -0.5 1.9 -0.25 -0.39 -0.28 -0.49 -0.71 -0.47 8.3e+03 0.032 5 0.9 ++
3 -0.59 0.73 -0.67 -0.34 1.4 -0.5 1.9 -0.25 -0.39 -0.28 -0.49 -0.71 -0.47 8.3e+03 0.032 2.5 -1e+02 -
4 -0.59 0.73 -0.67 -0.34 1.4 -0.5 1.9 -0.25 -0.39 -0.28 -0.49 -0.71 -0.47 8.3e+03 0.032 1.2 -5.7 -
5 -0.39 1.1 -1.2 -0.68 0.18 -0.6 2.1 0.016 -0.38 -0.66 -0.79 -1.3 -0.69 8.1e+03 0.018 1.2 0.71 +
6 -0.35 1.2 -1.7 -0.75 0.2 -0.73 1.4 0.14 -0.59 -0.95 -0.82 -1.5 -0.26 8.1e+03 0.011 1.2 0.73 +
7 -0.3 1.1 -1.8 -0.72 0.16 -0.72 1.6 0.14 -0.43 -0.95 -0.81 -1.5 -0.25 8.1e+03 0.0012 12 1.1 ++
8 -0.26 1.1 -1.7 -0.69 0.15 -0.7 1.7 0.13 -0.39 -0.93 -0.79 -1.5 -0.25 8.1e+03 0.00084 1.2e+02 1.1 ++
9 -0.26 1.1 -1.7 -0.69 0.15 -0.7 1.7 0.13 -0.38 -0.93 -0.79 -1.5 -0.25 8.1e+03 2.3e-05 1.2e+03 1 ++
10 -0.26 1.1 -1.7 -0.69 0.15 -0.7 1.7 0.13 -0.38 -0.93 -0.79 -1.5 -0.25 8.1e+03 3.3e-08 1.2e+03 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000053
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st lambda_travel_t b_cost_train mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 -0.54 -0.0056 -0.0089 -0.92 -0.49 1.5 -0.48 2 0.19 -0.071 -0.02 0.092 -0.7 9.6e+03 0.2 1 0.47 +
1 -0.54 -0.0056 -0.0089 -0.92 -0.49 1.5 -0.48 2 0.19 -0.071 -0.02 0.092 -0.7 9.6e+03 0.2 0.5 -0.36 -
2 -0.25 0.33 0.014 -0.55 -0.39 0.97 -0.6 2.2 -0.25 -0.33 -0.059 -0.23 -0.44 8.8e+03 0.16 0.5 0.46 +
3 -0.37 0.13 0.056 -0.76 -0.47 0.77 -0.57 2.7 -0.2 0.047 -0.12 -0.26 -0.6 8.4e+03 0.047 0.5 0.7 +
4 -0.092 0.25 0.084 -1.2 -0.4 0.3 -0.87 2.2 -0.069 -0.068 -0.39 -0.24 -0.56 8.3e+03 0.0088 5 1.1 ++
5 -0.17 0.42 0.19 -1.3 -0.48 0.43 -1.2 1.5 -0.094 -0.059 -0.49 -0.32 -0.68 8.2e+03 0.011 5 0.77 +
6 -0.23 0.49 0.25 -1.3 -0.49 0.43 -1.3 1.6 -0.13 -0.08 -0.52 -0.32 -0.7 8.2e+03 0.00071 50 1 ++
7 -0.23 0.49 0.25 -1.3 -0.49 0.43 -1.3 1.6 -0.13 -0.077 -0.52 -0.31 -0.7 8.2e+03 1.4e-05 5e+02 1 ++
8 -0.23 0.49 0.25 -1.3 -0.49 0.43 -1.3 1.6 -0.13 -0.077 -0.52 -0.31 -0.7 8.2e+03 2.8e-08 5e+02 1 ++
Considering neighbor 1/20 for current solution
Attempt 42/100
Biogeme parameters read from biogeme.toml.
Model with 16 unknown parameters [max: 50]
*** Estimate b07everything_000054
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.25 -
1 9.3e+03 0.07 0.5 0.78 +
2 8.7e+03 0.048 5 0.96 ++
3 8.7e+03 0.048 0.61 -0.46 -
4 8.3e+03 0.044 0.61 0.87 +
5 8.2e+03 0.0043 6.1 0.98 ++
6 8.2e+03 0.0043 0.36 0.079 -
7 8.2e+03 0.015 3.6 1 ++
8 8.1e+03 0.026 36 1 ++
9 8.1e+03 0.0025 3.6e+02 1 ++
10 8.1e+03 0.0001 3.6e+03 1 ++
11 8.1e+03 1.3e-07 3.6e+03 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000055
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com b_cost_train mu_existing asc_car_ref asc_car_diff_GA b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 -0.53 0.33 -1 -0.015 -0.56 2 0.14 -0.33 -0.025 -0.64 9e+03 0.18 1 0.73 +
1 -0.53 0.33 -1 -0.015 -0.56 2 0.14 -0.33 -0.025 -0.64 9e+03 0.18 0.5 -0.094 -
2 -0.16 0.74 -0.72 0.07 -0.62 2.5 -0.3 -0.48 -0.25 -0.43 8.5e+03 0.12 0.5 0.52 +
3 -0.52 0.48 -0.75 0.23 -0.45 2.8 -0.31 0.018 -0.2 -0.48 8.3e+03 0.024 0.5 0.71 +
4 -0.59 0.88 -0.92 0.22 -0.42 2.3 -0.3 -0.076 -0.19 -0.5 8.3e+03 0.007 5 1.2 ++
5 -0.59 0.88 -0.92 0.22 -0.42 2.3 -0.3 -0.076 -0.19 -0.5 8.3e+03 0.007 0.61 -1 -
6 -0.6 0.85 -1 0.085 -0.69 1.7 -0.36 -0.26 -0.26 -0.64 8.3e+03 0.0078 6.1 1 ++
7 -0.61 0.98 -1.1 0.017 -0.74 1.6 -0.3 -0.47 -0.29 -0.65 8.2e+03 0.0014 61 1.1 ++
8 -0.63 1 -1.1 -0.0072 -0.77 1.5 -0.29 -0.56 -0.3 -0.67 8.2e+03 0.00032 6.1e+02 1 ++
9 -0.63 1 -1.1 -0.0072 -0.77 1.5 -0.29 -0.56 -0.3 -0.67 8.2e+03 1.2e-06 6.1e+02 1 ++
Considering neighbor 1/20 for current solution
Attempt 43/100
Biogeme parameters read from biogeme.toml.
Model with 16 unknown parameters [max: 50]
*** Estimate b07everything_000056
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.26 -
1 9.6e+03 1 0.5 0.65 +
2 9.6e+03 1 0.25 0.65 -
3 9.6e+03 1 0.12 0.65 -
4 9.6e+03 1 0.062 -13 -
5 9.6e+03 1 0.031 -19 -
6 9.6e+03 1 0.016 -2.5 -
7 9.4e+03 0.44 0.16 0.97 ++
8 9.4e+03 0.44 0.078 -14 -
9 9.4e+03 0.44 0.039 -12 -
10 9.4e+03 0.44 0.02 -11 -
11 9.4e+03 0.44 0.0098 -11 -
12 9.4e+03 0.44 0.0049 -4.9 -
13 9.4e+03 4.1 0.0049 0.15 +
14 9.4e+03 0.081 0.0049 0.85 +
15 9.4e+03 2.8 0.0049 0.49 +
16 9.4e+03 0.35 0.049 0.98 ++
17 9.3e+03 0.42 0.49 0.99 ++
18 9e+03 6.5 0.49 0.61 +
19 9e+03 6.5 0.24 0.084 -
20 8.7e+03 3.7 0.24 0.88 +
21 8.7e+03 3.7 0.12 -2.7 -
22 8.7e+03 3.7 0.061 -2.2 -
23 8.7e+03 3.7 0.031 -1.8 -
24 8.7e+03 3.7 0.015 -1.9 -
25 8.7e+03 3.7 0.0076 -2.1 -
26 8.7e+03 3.7 0.0038 -1.8 -
27 8.7e+03 3.7 0.0019 -1.1 -
28 8.7e+03 3.7 0.00095 -0.61 -
29 8.7e+03 3.7 0.00048 0.075 -
30 8.7e+03 2.7 0.0048 1 ++
31 8.7e+03 3.1 0.0048 0.8 +
32 8.6e+03 1.3 0.048 0.94 ++
33 8.6e+03 0.64 0.48 1 ++
34 8.5e+03 2.1 0.48 0.78 +
35 8.5e+03 0.32 4.8 1.1 ++
36 8.5e+03 0.32 2.4 1.1 -
37 8.5e+03 0.32 1.2 -2.5e+02 -
38 8.5e+03 0.32 0.6 -62 -
39 8.4e+03 0.18 6 1 ++
40 8.4e+03 0.011 60 1 ++
41 8.4e+03 0.011 0.74 -1.3e+02 -
42 8.4e+03 0.011 0.37 -4.4 -
43 8.4e+03 5.2 0.37 0.6 +
44 8.4e+03 5.2 0.022 -2.7 -
45 8.4e+03 5.2 0.011 -2.9 -
46 8.4e+03 5.2 0.0056 -3.3 -
47 8.4e+03 5.2 0.0028 -3.6 -
48 8.4e+03 5.2 0.0014 -3.8 -
49 8.4e+03 5.2 0.0007 -3.8 -
50 8.4e+03 5.2 0.00035 -1.2 -
51 8.4e+03 5.2 0.00017 -0.34 -
52 8.4e+03 4.1 0.00017 0.42 +
53 8.4e+03 3.4 0.00017 0.29 +
54 8.4e+03 1.7 0.00017 0.63 +
55 8.4e+03 0.13 0.0017 0.96 ++
56 8.4e+03 0.046 0.017 1 ++
57 8.4e+03 0.031 0.17 1 ++
58 8.4e+03 0.013 1.7 1 ++
59 8.4e+03 0.013 0.33 0.093 -
60 8.4e+03 0.12 3.3 1.1 ++
61 8.4e+03 0.12 0.37 -0.44 -
62 8.3e+03 0.2 3.7 1.2 ++
63 8.3e+03 0.2 0.39 -1.1 -
64 8.3e+03 1.2 3.9 1.1 ++
65 8.3e+03 0.45 39 1.1 ++
66 8.3e+03 0.047 3.9e+02 0.99 ++
67 8.3e+03 0.063 3.9e+03 1 ++
68 8.3e+03 0.0028 3.9e+04 1 ++
69 8.3e+03 0.0014 3.9e+05 1 ++
70 8.3e+03 0.0052 3.9e+06 1 ++
71 8.3e+03 0.00077 3.9e+07 1 ++
72 8.3e+03 0.00029 3.9e+08 1 ++
73 8.3e+03 0.00015 3.9e+09 1 ++
74 8.3e+03 3.7e-06 3.9e+09 1 ++
Considering neighbor 0/20 for current solution
Attempt 44/100
Biogeme parameters read from biogeme.toml.
Model with 19 unknown parameters [max: 50]
*** Estimate b07everything_000057
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.22 0.5 -0.0061 -
1 9.5e+03 0.17 0.5 0.49 +
2 8.9e+03 0.066 0.5 0.81 +
3 8.3e+03 0.016 5 0.97 ++
4 8.3e+03 0.016 2.5 0.97 -
5 8.3e+03 0.016 1.2 -8.3 -
6 8.3e+03 0.016 0.62 -0.37 -
7 8.2e+03 0.011 6.2 0.97 ++
8 8.2e+03 0.011 0.45 -0.14 -
9 8.2e+03 0.012 4.5 1.1 ++
10 8.1e+03 0.018 4.5 0.73 +
11 8.1e+03 0.0029 45 1.1 ++
12 8.1e+03 0.00011 4.5e+02 1 ++
13 8.1e+03 1.4e-07 4.5e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 45/100
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000058
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di b_cost_train b_time_swissmet b_time_swissmet b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho
0 -1 0.36 0.15 -0.62 -0.42 -0.96 -0.77 -0.64 -0.74 -0.71 0.021 -0.25 -0.41 -0.63 -0.67 8.6e+03 0.08 10 1.1 ++
1 -0.81 0.62 0.51 -0.98 -0.54 -1.5 -1 -0.83 -0.85 -0.59 -0.12 -0.57 -0.68 -0.76 -0.6 8.3e+03 0.022 1e+02 1.2 ++
2 -0.71 0.74 0.61 -1.1 -0.61 -1.7 -1 -0.87 -0.89 -0.63 -0.12 -0.59 -0.69 -0.79 -0.61 8.3e+03 0.0036 1e+03 1.1 ++
3 -0.69 0.75 0.63 -1.1 -0.63 -1.8 -1 -0.87 -0.89 -0.63 -0.12 -0.59 -0.69 -0.79 -0.61 8.3e+03 0.00011 1e+04 1 ++
4 -0.69 0.75 0.63 -1.1 -0.63 -1.8 -1 -0.87 -0.89 -0.63 -0.12 -0.59 -0.69 -0.79 -0.61 8.3e+03 1.2e-07 1e+04 1 ++
Considering neighbor 0/20 for current solution
Considering neighbor 1/20 for current solution
Attempt 46/100
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000059
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 1 0 1 0 0 0 0 1.1e+04 0.26 0.5 0.033 -
1 -0.4 0.014 -0.5 -0.069 1 -0.39 1.2 0.3 0.00082 -0.049 -0.024 9.1e+03 0.11 0.5 0.8 +
2 -0.4 0.2 -0.75 -0.11 1 -0.49 1.3 -0.2 -0.036 -0.2 -0.052 8.7e+03 0.046 5 0.93 ++
3 -0.4 0.2 -0.75 -0.11 1 -0.49 1.3 -0.2 -0.036 -0.2 -0.052 8.7e+03 0.046 2.5 0.93 -
4 -0.4 0.2 -0.75 -0.11 1 -0.49 1.3 -0.2 -0.036 -0.2 -0.052 8.7e+03 0.046 1.2 -10 -
5 -0.14 1.5 -1.1 -0.36 0.17 -1.1 2.1 -0.78 -0.54 -0.69 -0.46 8.6e+03 0.12 1.2 0.16 +
6 -0.02 0.2 -0.98 -0.34 0.86 -0.98 2.3 -0.7 -0.25 -0.79 -0.57 8.4e+03 0.045 1.2 0.43 +
7 -0.02 0.2 -0.98 -0.34 0.86 -0.98 2.3 -0.7 -0.25 -0.79 -0.57 8.4e+03 0.045 0.62 -1.2 -
8 0.17 0.6 -1 -0.52 0.3 -1 3 -0.76 -0.3 -1.1 -0.65 8.3e+03 0.061 0.62 0.28 +
9 0.07 0.57 -1.1 -0.41 0.41 -1.1 2.3 -0.77 -0.35 -1.4 -0.57 8.2e+03 0.027 6.2 1.1 ++
10 0.07 0.57 -1.1 -0.41 0.41 -1.1 2.3 -0.77 -0.35 -1.4 -0.57 8.2e+03 0.027 0.5 -0.074 -
11 -0.075 0.75 -1.2 -0.43 0.47 -1 1.8 -0.77 -0.21 -1.3 -0.64 8.2e+03 0.016 5 1.2 ++
12 -0.15 0.93 -1.4 -0.5 0.4 -1.1 1.4 -0.77 -0.18 -1.2 -0.53 8.2e+03 0.014 50 1 ++
13 -0.24 1 -1.5 -0.52 0.39 -1.1 1.3 -0.76 -0.14 -1.2 -0.52 8.2e+03 0.0021 5e+02 1.1 ++
14 -0.34 1.2 -1.6 -0.55 0.37 -1.1 1.2 -0.75 -0.1 -1.1 -0.5 8.2e+03 0.0028 5e+03 0.96 ++
15 -0.37 1.2 -1.6 -0.55 0.37 -1.1 1.1 -0.75 -0.095 -1.1 -0.5 8.2e+03 0.00012 5e+04 1 ++
16 -0.39 1.2 -1.6 -0.55 0.37 -1.1 1.1 -0.75 -0.091 -1.1 -0.5 8.2e+03 3.4e-05 5e+05 1 ++
17 -0.39 1.2 -1.6 -0.55 0.37 -1.1 1.1 -0.75 -0.091 -1.1 -0.5 8.2e+03 2.2e-08 5e+05 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000060
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho
0 -0.54 0.18 -1 -0.089 1.4 -0.36 -0.35 -0.11 -0.25 -0.2 8.8e+03 0.049 10 0.96 ++
1 -0.54 0.18 -1 -0.089 1.4 -0.36 -0.35 -0.11 -0.25 -0.2 8.8e+03 0.049 5 -1.7e+06 -
2 -0.54 0.18 -1 -0.089 1.4 -0.36 -0.35 -0.11 -0.25 -0.2 8.8e+03 0.049 2.5 -59 -
3 -0.54 0.18 -1 -0.089 1.4 -0.36 -0.35 -0.11 -0.25 -0.2 8.8e+03 0.049 1.2 -2.1 -
4 -0.54 1.4 -1.8 -0.55 0.29 -1 -0.86 -0.3 -0.74 -0.3 8.2e+03 0.021 12 0.9 ++
5 -0.54 1.4 -1.7 -0.58 0.34 -1.1 -0.73 -0.036 -1.1 -0.49 8.2e+03 0.00098 1.2e+02 1 ++
6 -0.52 1.3 -1.6 -0.57 0.35 -1.2 -0.74 -0.046 -1.1 -0.49 8.2e+03 1.7e-05 1.2e+03 1 ++
7 -0.52 1.3 -1.6 -0.57 0.35 -1.2 -0.74 -0.046 -1.1 -0.49 8.2e+03 4.9e-09 1.2e+03 1 ++
Considering neighbor 1/20 for current solution
Attempt 47/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000061
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train square_tt_coef cube_tt_coef b_cost b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.23 -
1 -0.27 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0072 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.5 0.67 +
2 -0.27 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0072 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.25 -10 -
3 -0.27 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0072 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.12 -12 -
4 -0.27 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0072 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.062 -14 -
5 -0.27 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0072 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.031 -23 -
6 -0.27 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0072 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.016 -2.6 -
7 -0.29 -0.13 0.01 -0.52 -0.014 0.0036 -0.054 0.19 -0.0084 -0.022 -0.017 -0.0054 9.4e+03 0.41 0.16 0.96 ++
8 -0.29 -0.13 0.01 -0.52 -0.014 0.0036 -0.054 0.19 -0.0084 -0.022 -0.017 -0.0054 9.4e+03 0.41 0.078 -13 -
9 -0.29 -0.13 0.01 -0.52 -0.014 0.0036 -0.054 0.19 -0.0084 -0.022 -0.017 -0.0054 9.4e+03 0.41 0.039 -12 -
10 -0.29 -0.13 0.01 -0.52 -0.014 0.0036 -0.054 0.19 -0.0084 -0.022 -0.017 -0.0054 9.4e+03 0.41 0.02 -9.4 -
11 -0.29 -0.13 0.01 -0.52 -0.014 0.0036 -0.054 0.19 -0.0084 -0.022 -0.017 -0.0054 9.4e+03 0.41 0.0098 -9.8 -
12 -0.29 -0.13 0.01 -0.52 -0.014 0.0036 -0.054 0.19 -0.0084 -0.022 -0.017 -0.0054 9.4e+03 0.41 0.0049 -4.7 -
13 -0.29 -0.12 0.011 -0.52 -0.0088 -0.0013 -0.059 0.18 -0.013 -0.027 -0.02 -0.01 9.4e+03 2.4 0.0049 0.59 +
14 -0.29 -0.12 0.011 -0.52 -0.007 -0.00063 -0.062 0.18 -0.016 -0.029 -0.02 -0.015 9.4e+03 0.22 0.049 0.97 ++
15 -0.3 -0.11 0.011 -0.54 0.011 -0.00046 -0.094 0.19 -0.04 -0.047 -0.021 -0.064 9.3e+03 0.085 0.49 1 ++
16 -0.36 0.044 0.018 -0.76 0.21 0.00012 -0.58 -0.11 -0.14 -0.16 -0.036 -0.41 9e+03 3.8 0.49 0.63 +
17 -0.36 0.044 0.018 -0.76 0.21 0.00012 -0.58 -0.11 -0.14 -0.16 -0.036 -0.41 9e+03 3.8 0.24 -6.9 -
18 -0.36 0.044 0.018 -0.76 0.21 0.00012 -0.58 -0.11 -0.14 -0.16 -0.036 -0.41 9e+03 3.8 0.12 -7.3 -
19 -0.36 0.044 0.018 -0.76 0.21 0.00012 -0.58 -0.11 -0.14 -0.16 -0.036 -0.41 9e+03 3.8 0.061 -7.6 -
20 -0.36 0.044 0.018 -0.76 0.21 0.00012 -0.58 -0.11 -0.14 -0.16 -0.036 -0.41 9e+03 3.8 0.031 -8.1 -
21 -0.36 0.044 0.018 -0.76 0.21 0.00012 -0.58 -0.11 -0.14 -0.16 -0.036 -0.41 9e+03 3.8 0.015 -4.6 -
22 -0.36 0.044 0.018 -0.76 0.21 0.00012 -0.58 -0.11 -0.14 -0.16 -0.036 -0.41 9e+03 3.8 0.0076 -3.1 -
23 -0.36 0.044 0.018 -0.76 0.21 0.00012 -0.58 -0.11 -0.14 -0.16 -0.036 -0.41 9e+03 3.8 0.0038 -1.9 -
24 -0.36 0.044 0.018 -0.76 0.21 0.00012 -0.58 -0.11 -0.14 -0.16 -0.036 -0.41 9e+03 3.8 0.0019 -0.59 -
25 -0.36 0.046 0.02 -0.76 0.21 -0.0018 -0.58 -0.11 -0.14 -0.16 -0.038 -0.41 8.9e+03 3.2 0.0019 0.45 +
26 -0.36 0.046 0.02 -0.76 0.2 -0.00066 -0.58 -0.11 -0.14 -0.16 -0.038 -0.41 8.9e+03 3.8 0.0019 0.33 +
27 -0.36 0.046 0.02 -0.76 0.2 -0.00066 -0.58 -0.11 -0.14 -0.16 -0.038 -0.41 8.9e+03 3.8 0.00095 -0.44 -
28 -0.36 0.047 0.021 -0.76 0.2 -0.0016 -0.59 -0.11 -0.14 -0.16 -0.039 -0.4 8.9e+03 2.9 0.00095 0.17 +
29 -0.36 0.047 0.021 -0.76 0.2 -0.0016 -0.59 -0.11 -0.14 -0.16 -0.039 -0.4 8.9e+03 2.9 0.00048 0.06 -
30 -0.36 0.048 0.021 -0.76 0.2 -0.0011 -0.59 -0.11 -0.14 -0.16 -0.04 -0.4 8.9e+03 0.6 0.0048 0.96 ++
31 -0.36 0.048 0.021 -0.76 0.2 -0.0011 -0.59 -0.12 -0.13 -0.16 -0.04 -0.4 8.9e+03 0.12 0.048 1 ++
32 -0.35 0.057 0.022 -0.75 0.18 -0.001 -0.6 -0.16 -0.12 -0.15 -0.04 -0.36 8.8e+03 0.11 0.48 1 ++
33 -0.37 0.24 0.036 -0.81 0.45 -0.0022 -0.72 -0.64 -0.13 -0.16 -0.057 -0.44 8.7e+03 0.45 0.48 0.63 +
34 -0.72 0.51 0.095 -1.1 -0.029 -0.00018 -0.75 -0.8 -0.47 -0.24 -0.12 -0.52 8.7e+03 1.2 0.48 0.17 +
35 -0.68 0.76 0.17 -1.5 0.087 -0.00063 -0.75 -1.3 -0.37 0.044 -0.17 -1 8.5e+03 0.74 0.48 0.64 +
36 -0.68 0.76 0.17 -1.5 0.087 -0.00063 -0.75 -1.3 -0.37 0.044 -0.17 -1 8.5e+03 0.74 0.24 -0.96 -
37 -0.79 0.73 0.21 -1.7 -0.082 7.6e-05 -0.76 -1.3 -0.39 -0.053 -0.19 -1.1 8.5e+03 4.2 0.24 0.56 +
38 -0.75 0.83 0.27 -1.9 -0.049 -6.7e-05 -0.75 -1.6 -0.42 -0.11 -0.22 -1.1 8.4e+03 1.9 2.4 1 ++
39 -0.75 0.83 0.27 -1.9 -0.049 -6.7e-05 -0.75 -1.6 -0.42 -0.11 -0.22 -1.1 8.4e+03 1.9 0.62 -4.3 -
40 -0.74 0.9 0.6 -2.5 -0.12 0.00027 -0.89 -2.2 -0.54 0.028 -0.37 -1.6 8.4e+03 15 0.62 0.21 +
41 -0.37 0.9 0.82 -3 -0.1 0.00019 -0.81 -2.4 -0.44 -0.1 -0.45 -1.8 8.4e+03 9.1 0.62 0.79 +
42 -0.43 0.91 0.81 -2.9 -0.11 0.00021 -0.8 -2.4 -0.46 -0.1 -0.5 -1.8 8.4e+03 1.4 6.2 0.95 ++
43 -0.44 0.91 0.82 -2.9 -0.11 0.0002 -0.8 -2.4 -0.45 -0.1 -0.51 -1.7 8.4e+03 0.051 62 1 ++
44 -0.44 0.91 0.82 -2.9 -0.11 0.0002 -0.8 -2.4 -0.45 -0.1 -0.51 -1.7 8.4e+03 4.6e-05 6.2e+02 1 ++
45 -0.44 0.91 0.82 -2.9 -0.11 0.0002 -0.8 -2.4 -0.45 -0.1 -0.51 -1.7 8.4e+03 1.3e-05 6.2e+03 1 ++
46 -0.44 0.91 0.82 -2.9 -0.11 0.0002 -0.8 -2.4 -0.45 -0.1 -0.51 -1.7 8.4e+03 3.4e-07 6.2e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 48/100
Considering neighbor 0/20 for current solution
Attempt 49/100
Considering neighbor 0/20 for current solution
Attempt 50/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000062
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho
0 -0.98 1 -0.74 -0.62 -0.66 -0.35 -0.49 -0.6 8.5e+03 0.049 10 1.1 ++
1 -0.92 1.3 -1.2 -0.84 -0.73 -0.31 -0.99 -0.38 8.3e+03 0.011 1e+02 1.1 ++
2 -0.86 1.3 -1.3 -1 -0.75 -0.33 -1.1 -0.35 8.3e+03 0.001 1e+03 1.1 ++
3 -0.85 1.3 -1.3 -1 -0.76 -0.33 -1.1 -0.35 8.3e+03 1.7e-05 1e+04 1 ++
4 -0.85 1.3 -1.3 -1 -0.76 -0.33 -1.1 -0.35 8.3e+03 4.9e-09 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 51/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000063
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost mu_public asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.78 0.074 -0.34 -0.016 -1 -0.11 1.1 -0.23 1.5 -0.07 -0.11 -0.1 -0.0095 9.4e+03 0.12 1 0.45 +
1 -0.43 1.1 0.62 0.012 -1.1 -0.12 0.93 -1 1.8 -0.18 -0.47 -0.29 -0.048 9e+03 0.18 1 0.24 +
2 -0.43 1.1 0.62 0.012 -1.1 -0.12 0.93 -1 1.8 -0.18 -0.47 -0.29 -0.048 9e+03 0.18 0.5 -0.17 -
3 -0.66 0.7 0.23 0.074 -0.97 -0.19 0.43 -0.78 2.1 -0.041 -0.5 -0.12 -0.067 8.4e+03 0.058 0.5 0.7 +
4 -0.5 0.87 0.22 0.32 -1.2 -0.47 0.42 -0.68 1.7 0.0091 -1 -0.1 -0.21 8.2e+03 0.0068 5 1.1 ++
5 -0.5 0.87 0.22 0.32 -1.2 -0.47 0.42 -0.68 1.7 0.0091 -1 -0.1 -0.21 8.2e+03 0.0068 0.37 -0.42 -
6 -0.72 1.1 0.33 0.3 -1.4 -0.45 0.37 -0.74 1.4 0.069 -1.2 -0.044 -0.28 8.2e+03 0.0082 3.7 1.1 ++
7 -0.94 1.3 0.44 0.44 -1.5 -0.54 0.36 -0.71 1.2 0.17 -1.2 -0.079 -0.51 8.2e+03 0.005 37 1.2 ++
8 -1.1 1.4 0.51 0.52 -1.6 -0.57 0.34 -0.71 1.1 0.19 -1.2 -0.075 -0.52 8.2e+03 0.0014 3.7e+02 1.2 ++
9 -1.2 1.5 0.55 0.57 -1.6 -0.58 0.33 -0.71 1 0.21 -1.1 -0.072 -0.51 8.2e+03 0.00081 3.7e+03 1.1 ++
10 -1.3 1.5 0.55 0.57 -1.6 -0.58 0.33 -0.71 1 0.22 -1.1 -0.073 -0.51 8.2e+03 0.00016 3.7e+04 1 ++
11 -1.3 1.5 0.55 0.57 -1.6 -0.58 0.33 -0.71 1 0.22 -1.1 -0.073 -0.51 8.2e+03 2.5e-07 3.7e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 52/100
Biogeme parameters read from biogeme.toml.
Model with 7 unknown parameters [max: 50]
*** Estimate b07everything_000064
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time b_cost mu_existing asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -0.77 0.43 -0.89 -1 1.6 0.37 -0.31 8.8e+03 0.11 1 0.8 +
1 -0.77 0.43 -0.89 -1 1.6 0.37 -0.31 8.8e+03 0.11 0.5 -0.052 -
2 -0.63 0.76 -1.1 -0.5 1.8 -0.051 -0.42 8.3e+03 0.022 0.5 0.89 +
3 -0.7 1 -1 -0.59 1.6 0.019 -0.57 8.3e+03 0.0016 5 1 ++
4 -0.74 1.1 -1.1 -0.61 1.5 0.019 -0.69 8.3e+03 0.00012 50 1.1 ++
5 -0.74 1.1 -1.1 -0.61 1.5 0.019 -0.69 8.3e+03 6e-06 50 1 ++
Considering neighbor 0/20 for current solution
Attempt 53/100
Biogeme parameters read from biogeme.toml.
Model with 16 unknown parameters [max: 50]
*** Estimate b07everything_000065
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.39 -
1 1e+04 0.24 0.5 0.32 +
2 9.1e+03 0.15 0.5 0.6 +
3 8.5e+03 0.036 5 0.99 ++
4 8.4e+03 0.011 50 0.97 ++
5 8.4e+03 0.011 0.7 -3.5 -
6 8.3e+03 0.028 0.7 0.84 +
7 8.3e+03 0.0069 7 1.2 ++
8 8.3e+03 0.0069 0.25 -0.27 -
9 8.3e+03 0.0085 2.5 1.1 ++
10 8.3e+03 0.0073 25 1.2 ++
11 8.3e+03 0.0034 2.5e+02 1.3 ++
12 8.3e+03 0.00036 2.5e+03 1 ++
13 8.3e+03 1.9e-05 2.5e+04 1 ++
14 8.3e+03 3.1e-09 2.5e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 54/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000066
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di b_cost b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 -1 0.26 0.11 -0.69 -0.45 -0.73 -0.84 -0.59 -0.65 -0.072 -0.17 -0.43 -0.58 8.6e+03 0.077 10 1.1 ++
1 -0.96 0.67 0.6 -1.1 -0.68 -0.84 -1 -0.82 -0.54 -0.099 -0.54 -0.58 -0.73 8.4e+03 0.022 1e+02 1.2 ++
2 -0.93 0.84 0.75 -1.3 -0.79 -0.86 -1.1 -0.87 -0.56 -0.099 -0.56 -0.58 -0.77 8.4e+03 0.0032 1e+03 1.1 ++
3 -0.92 0.86 0.77 -1.3 -0.8 -0.86 -1.1 -0.87 -0.56 -0.1 -0.56 -0.58 -0.77 8.4e+03 6.6e-05 1e+04 1 ++
4 -0.92 0.86 0.77 -1.3 -0.8 -0.86 -1.1 -0.87 -0.56 -0.1 -0.56 -0.58 -0.77 8.4e+03 5e-08 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 55/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000067
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time square_tt_coef cube_tt_coef b_cost asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -0.54 -
1 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 5 1.1 ++
2 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 2.5 -11 -
3 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 1.2 -8.9 -
4 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.62 -7.4 -
5 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.31 -3.2 -
6 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.16 -1.7 -
7 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.078 -1.5 -
8 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.039 -1.9 -
9 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.02 -2.5 -
10 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.0098 -3.3 -
11 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.0049 -4 -
12 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.0024 -4.9 -
13 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.0012 -2.3 -
14 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.00061 -1.2 -
15 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.00031 -0.22 -
16 -0.5 -0.00028 -0.5 -0.02 -0.5 0.00031 -0.00031 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 2.9 0.00031 0.64 +
17 -0.5 -0.0002 -0.5 -0.02 -0.5 0.00061 -0.00023 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 1.4 0.00031 0.77 +
18 -0.5 -0.00012 -0.5 -0.02 -0.5 0.00092 -0.00026 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 0.14 0.0031 0.99 ++
19 -0.5 0.0007 -0.5 -0.02 -0.5 0.004 -0.00026 -0.14 0.026 -0.078 -0.022 -0.0067 9.2e+03 0.19 0.031 1 ++
20 -0.51 0.0091 -0.49 -0.02 -0.53 0.034 -0.0004 -0.15 0.018 -0.084 -0.03 -0.0071 9.1e+03 0.28 0.31 1 ++
21 -0.56 0.23 -0.32 -0.02 -0.83 0.24 -0.0013 -0.44 0.01 -0.19 -0.1 -0.016 8.8e+03 2.3 0.31 0.75 +
22 -0.64 0.53 -0.096 -0.015 -0.94 0.038 -0.00038 -0.69 0.092 -0.32 -0.13 -0.029 8.5e+03 7.2 0.31 0.82 +
23 -0.86 0.84 0.035 -0.0071 -1.2 -0.0096 -0.00026 -0.72 0.09 -0.45 -0.16 -0.048 8.4e+03 5.9 3.1 1 ++
24 -0.86 0.84 0.035 -0.0071 -1.2 -0.0096 -0.00026 -0.72 0.09 -0.45 -0.16 -0.048 8.4e+03 5.9 1.5 -88 -
25 -0.86 0.84 0.035 -0.0071 -1.2 -0.0096 -0.00026 -0.72 0.09 -0.45 -0.16 -0.048 8.4e+03 5.9 0.76 -13 -
26 -0.86 0.84 0.035 -0.0071 -1.2 -0.0096 -0.00026 -0.72 0.09 -0.45 -0.16 -0.048 8.4e+03 5.9 0.38 -1.3 -
27 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.38 0.11 +
28 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.19 -2.5 -
29 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.095 -1.9 -
30 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.048 -1.5 -
31 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.024 -1.1 -
32 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.012 -1.2 -
33 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.006 -1.6 -
34 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.003 -2 -
35 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.0015 -2.3 -
36 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.00075 -2.6 -
37 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.00037 -2.7 -
38 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.00019 -0.28 -
39 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00044 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 3.2 0.00019 0.89 +
40 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00041 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 0.43 0.0019 0.96 ++
41 -1.1 1.2 0.22 0.019 -1.6 -0.13 0.0004 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 0.26 0.019 1 ++
42 -1.1 1.2 0.22 0.019 -1.6 -0.11 0.00024 -0.71 0.092 -0.6 -0.14 -0.082 8.3e+03 3.6 0.19 0.99 ++
43 -1.1 1.3 0.27 0.04 -1.8 -0.089 0.00011 -0.72 0.13 -0.66 -0.098 -0.099 8.2e+03 7.2 1.9 0.93 ++
44 -1.2 1.4 0.49 0.54 -2.1 -0.12 0.00025 -0.72 0.2 -1.2 -0.059 -0.4 8.2e+03 3.4 1.9 0.88 +
45 -1.3 1.4 0.55 0.59 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.062 -0.46 8.2e+03 4.3 19 1 ++
46 -1.3 1.4 0.55 0.61 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.063 -0.48 8.2e+03 0.27 1.9e+02 1 ++
47 -1.3 1.4 0.55 0.61 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.063 -0.49 8.2e+03 0.0022 1.9e+03 1 ++
48 -1.3 1.4 0.55 0.61 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.063 -0.49 8.2e+03 0.00016 1.9e+04 1 ++
49 -1.3 1.4 0.55 0.61 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.063 -0.49 8.2e+03 0.00045 1.9e+05 1 ++
50 -1.3 1.4 0.55 0.61 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.063 -0.49 8.2e+03 6e-07 1.9e+05 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000068
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -2 -
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.29 -
2 -0.25 -0.00017 -0.15 -0.0057 -0.25 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 2.5 1 ++
3 -0.25 -0.00017 -0.15 -0.0057 -0.25 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 1.2 -4.3 -
4 -0.25 -0.00017 -0.15 -0.0057 -0.25 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 0.62 -2.8 -
5 -0.25 -0.00017 -0.15 -0.0057 -0.25 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 0.31 -1.1 -
6 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.31 0.23 +
7 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.16 -0.33 -
8 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.078 -0.051 -
9 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.039 0.022 -
10 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.02 0.038 -
11 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.0098 0.039 -
12 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.0049 0.036 -
13 -0.44 0.045 -0.2 -0.0092 -0.56 0.23 0.00043 -0.45 0.2 0.044 -0.08 -0.017 -0.006 0.018 9.2e+03 6.5 0.0049 0.39 +
14 -0.44 0.045 -0.2 -0.0092 -0.56 0.23 0.00043 -0.45 0.2 0.044 -0.08 -0.017 -0.006 0.018 9.2e+03 6.5 0.0024 -0.37 -
15 -0.44 0.048 -0.2 -0.0068 -0.56 0.22 -0.002 -0.45 0.2 0.046 -0.083 -0.014 -0.0084 0.021 9.1e+03 3.9 0.0024 0.54 +
16 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.024 1.3 ++
17 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.012 -2.9 -
18 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.0061 -3.6 -
19 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.0031 -3.1 -
20 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.0015 -2 -
21 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.00076 -1.3 -
22 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.00038 -0.19 -
23 -0.44 0.049 -0.19 -0.0064 -0.55 0.22 -0.0013 -0.45 0.2 0.047 -0.084 -0.015 -0.0088 0.021 9e+03 2.1 0.0038 1 ++
24 -0.44 0.049 -0.19 -0.0064 -0.55 0.22 -0.0011 -0.45 0.19 0.048 -0.084 -0.015 -0.0089 0.022 9e+03 5.9 0.0038 0.32 +
25 -0.44 0.05 -0.19 -0.0063 -0.55 0.22 -0.0015 -0.45 0.19 0.048 -0.085 -0.015 -0.0089 0.023 9e+03 2.5 0.0038 0.17 +
26 -0.44 0.05 -0.19 -0.0063 -0.55 0.22 -0.0015 -0.45 0.19 0.048 -0.085 -0.015 -0.0089 0.023 9e+03 2.5 0.0019 -2 -
27 -0.44 0.05 -0.19 -0.0063 -0.55 0.22 -0.0015 -0.45 0.19 0.048 -0.085 -0.015 -0.0089 0.023 9e+03 2.5 0.00095 -1.7 -
28 -0.44 0.05 -0.19 -0.0063 -0.55 0.22 -0.0015 -0.45 0.19 0.048 -0.085 -0.015 -0.0089 0.023 9e+03 2.5 0.00048 -1.1 -
29 -0.44 0.05 -0.19 -0.0063 -0.55 0.22 -0.0015 -0.45 0.19 0.048 -0.085 -0.015 -0.0089 0.023 9e+03 2.5 0.00024 0.039 -
30 -0.44 0.051 -0.19 -0.0061 -0.55 0.22 -0.0012 -0.45 0.19 0.049 -0.085 -0.015 -0.0092 0.023 9e+03 2.1 0.0024 0.98 ++
31 -0.44 0.051 -0.19 -0.0061 -0.55 0.22 -0.0011 -0.45 0.19 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 5.6 0.0024 0.18 +
32 -0.44 0.052 -0.19 -0.006 -0.55 0.22 -0.0013 -0.46 0.18 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 2.5 0.0024 0.33 +
33 -0.44 0.052 -0.19 -0.006 -0.55 0.22 -0.0013 -0.46 0.18 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 2.5 0.0012 -2.7 -
34 -0.44 0.052 -0.19 -0.006 -0.55 0.22 -0.0013 -0.46 0.18 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 2.5 0.0006 -1.9 -
35 -0.44 0.052 -0.19 -0.006 -0.55 0.22 -0.0013 -0.46 0.18 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 2.5 0.0003 -1.3 -
36 -0.44 0.052 -0.19 -0.006 -0.55 0.22 -0.0013 -0.46 0.18 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 2.5 0.00015 -0.18 -
37 -0.44 0.052 -0.19 -0.0059 -0.55 0.22 -0.0012 -0.46 0.18 0.049 -0.086 -0.015 -0.0094 0.024 9e+03 0.59 0.00015 0.86 +
38 -0.44 0.052 -0.19 -0.0059 -0.55 0.22 -0.0012 -0.46 0.18 0.05 -0.086 -0.015 -0.0094 0.024 9e+03 0.1 0.0015 0.99 ++
39 -0.44 0.053 -0.19 -0.0059 -0.55 0.22 -0.0012 -0.46 0.18 0.05 -0.087 -0.015 -0.0094 0.025 9e+03 0.14 0.015 1 ++
40 -0.43 0.057 -0.19 -0.0057 -0.55 0.21 -0.0011 -0.46 0.17 0.052 -0.089 -0.016 -0.0096 0.028 9e+03 0.094 0.15 1 ++
41 -0.41 0.099 -0.14 -0.0044 -0.53 0.17 -0.00097 -0.47 0.019 0.069 -0.12 -0.023 -0.012 0.052 8.9e+03 0.064 1.5 0.97 ++
42 -1.2 1.3 0.36 0.35 -0.78 0.11 -0.00072 -0.92 -0.66 -0.42 -0.35 -0.021 -0.26 -0.25 8.3e+03 0.24 15 1.1 ++
43 -1.2 1.3 0.36 0.35 -0.78 0.11 -0.00072 -0.92 -0.66 -0.42 -0.35 -0.021 -0.26 -0.25 8.3e+03 0.24 0.34 -3.7 -
44 -1.3 1.3 0.34 0.36 -1.1 -0.046 -7.3e-05 -0.97 -0.78 -0.44 -0.46 -0.096 -0.27 -0.3 8.3e+03 0.49 3.4 0.94 ++
45 -1.1 1.1 0.54 0.56 -1.7 -0.08 7.7e-05 -1.1 -0.75 -0.25 -0.96 -0.056 -0.4 -0.34 8.2e+03 1.5 34 1.2 ++
46 -1.1 1.1 0.54 0.56 -1.7 -0.08 7.7e-05 -1.1 -0.75 -0.25 -0.96 -0.056 -0.4 -0.34 8.2e+03 1.5 0.31 -0.12 -
47 -1.1 1.2 0.55 0.56 -2 -0.11 0.00022 -1.1 -0.76 -0.22 -0.98 -0.051 -0.4 -0.37 8.1e+03 10 0.31 0.73 +
48 -0.97 1.2 0.55 0.57 -2.2 -0.11 0.0002 -1.1 -0.77 -0.17 -1 -0.077 -0.44 -0.34 8.1e+03 2 3.1 0.95 ++
49 -0.97 1.1 0.55 0.55 -2.2 -0.11 0.0002 -1.1 -0.77 -0.17 -1 -0.08 -0.46 -0.34 8.1e+03 0.027 31 0.99 ++
50 -0.97 1.1 0.55 0.55 -2.2 -0.11 0.0002 -1.1 -0.77 -0.17 -1 -0.08 -0.47 -0.34 8.1e+03 1e-05 3.1e+02 1 ++
51 -0.97 1.1 0.55 0.55 -2.2 -0.11 0.0002 -1.1 -0.77 -0.17 -1 -0.08 -0.47 -0.34 8.1e+03 6.5e-07 3.1e+02 1 ++
Considering neighbor 1/20 for current solution
Attempt 56/100
Considering neighbor 0/20 for current solution
Attempt 57/100
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000069
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_train b_cost_train mu_existing asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_time_car b_cost_car b_time_swissmet b_cost_swissmet Function Relgrad Radius Rho
0 -0.41 0.31 0.055 -0.00064 -0.65 -0.51 2 0.082 -0.29 -0.11 -0.023 -0.27 -0.097 -0.37 -0.5 9.5e+03 0.35 1 0.64 +
1 -0.41 0.31 0.055 -0.00064 -0.65 -0.51 2 0.082 -0.29 -0.11 -0.023 -0.27 -0.097 -0.37 -0.5 9.5e+03 0.35 0.5 -2.9 -
2 -0.41 0.31 0.055 -0.00064 -0.65 -0.51 2 0.082 -0.29 -0.11 -0.023 -0.27 -0.097 -0.37 -0.5 9.5e+03 0.35 0.25 -0.093 -
3 -0.34 0.35 0.12 0.0046 -0.56 -0.48 2.1 -0.069 -0.31 -0.18 -0.032 -0.52 -0.26 -0.36 -0.39 8.5e+03 0.12 0.25 0.82 +
4 -0.39 0.5 0.16 0.023 -0.77 -0.58 2.2 -0.12 -0.39 -0.13 -0.063 -0.61 -0.34 -0.61 -0.4 8.3e+03 0.017 2.5 1 ++
5 -0.81 0.83 0.32 0.16 -1.1 -0.64 1.7 -0.47 -0.33 -0.041 -0.26 -0.83 -0.53 -1.2 -0.58 8.2e+03 0.012 25 1.1 ++
6 -0.86 0.9 0.35 0.24 -1.2 -0.67 1.7 -0.49 -0.39 -0.04 -0.34 -0.89 -0.58 -1.3 -0.62 8.2e+03 0.0011 2.5e+02 1.1 ++
7 -0.87 0.91 0.36 0.26 -1.2 -0.68 1.6 -0.49 -0.42 -0.04 -0.34 -0.9 -0.58 -1.3 -0.62 8.2e+03 0.0001 2.5e+03 1 ++
8 -0.87 0.91 0.36 0.26 -1.2 -0.68 1.6 -0.49 -0.42 -0.04 -0.34 -0.9 -0.58 -1.3 -0.62 8.2e+03 3.4e-08 2.5e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 58/100
Biogeme parameters read from biogeme.toml.
Model with 6 unknown parameters [max: 50]
*** Estimate b07everything_000070
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time b_cost asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -0.96 1 -0.72 -0.64 -0.31 -0.48 8.5e+03 0.043 10 1.1 ++
1 -1.1 1.4 -1.1 -0.69 -0.0034 -1.1 8.3e+03 0.0087 1e+02 1.1 ++
2 -1.1 1.5 -1.2 -0.7 0.014 -1.3 8.3e+03 0.0003 1e+03 1 ++
3 -1.1 1.5 -1.2 -0.7 0.014 -1.3 8.3e+03 5.2e-07 1e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 59/100
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000071
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 1 0 0 0 0 1.1e+04 0.26 0.5 0.046 -
1 -0.4 0.013 -0.5 -0.39 1.2 0.3 0.00083 -0.048 -0.024 9.1e+03 0.11 0.5 0.81 +
2 -0.41 0.2 -0.77 -0.5 1.3 -0.2 -0.033 -0.2 -0.049 8.7e+03 0.048 5 0.94 ++
3 -0.41 0.2 -0.77 -0.5 1.3 -0.2 -0.033 -0.2 -0.049 8.7e+03 0.048 2.5 -1.1e+02 -
4 -0.41 0.2 -0.77 -0.5 1.3 -0.2 -0.033 -0.2 -0.049 8.7e+03 0.048 1.2 -15 -
5 -0.41 0.2 -0.77 -0.5 1.3 -0.2 -0.033 -0.2 -0.049 8.7e+03 0.048 0.62 -0.65 -
6 -0.35 0.83 -1.2 -0.88 1.4 -0.71 -0.36 -0.55 -0.32 8.3e+03 0.0091 6.2 1 ++
7 -0.53 0.98 -1.2 -1 1.3 -0.76 -0.38 -1 -0.39 8.3e+03 0.0035 62 1.1 ++
8 -0.64 1.1 -1.2 -1 1.2 -0.76 -0.36 -1.1 -0.38 8.3e+03 0.0016 6.2e+02 1.1 ++
9 -0.69 1.1 -1.2 -1 1.1 -0.76 -0.35 -1.1 -0.37 8.3e+03 0.00032 6.2e+03 1.1 ++
10 -0.71 1.2 -1.2 -1 1.1 -0.76 -0.35 -1.1 -0.37 8.3e+03 3.5e-05 6.2e+04 1 ++
11 -0.71 1.2 -1.2 -1 1.1 -0.76 -0.35 -1.1 -0.37 8.3e+03 1.5e-07 6.2e+04 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000072
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.26 0.5 0.049 -
1 -0.4 0.014 -0.5 -0.069 -0.39 1.2 0.3 0.00071 -0.049 -0.025 9.1e+03 0.11 0.5 0.8 +
2 -0.4 0.21 -0.76 -0.12 -0.49 1.3 -0.2 -0.036 -0.2 -0.053 8.7e+03 0.047 5 0.94 ++
3 -0.4 0.21 -0.76 -0.12 -0.49 1.3 -0.2 -0.036 -0.2 -0.053 8.7e+03 0.047 2.5 -1e+02 -
4 -0.4 0.21 -0.76 -0.12 -0.49 1.3 -0.2 -0.036 -0.2 -0.053 8.7e+03 0.047 1.2 -15 -
5 -0.4 0.21 -0.76 -0.12 -0.49 1.3 -0.2 -0.036 -0.2 -0.053 8.7e+03 0.047 0.62 -0.67 -
6 -0.33 0.83 -1.2 -0.2 -0.87 1.4 -0.7 -0.36 -0.55 -0.32 8.3e+03 0.011 6.2 1 ++
7 -0.47 0.92 -1.1 -0.24 -1 1.4 -0.76 -0.39 -1 -0.41 8.3e+03 0.0018 62 1.1 ++
8 -0.59 1.1 -1.2 -0.22 -1 1.2 -0.76 -0.36 -1.2 -0.39 8.3e+03 0.003 62 0.86 +
9 -0.61 1.1 -1.2 -0.21 -1 1.2 -0.76 -0.36 -1.2 -0.39 8.3e+03 3.4e-05 6.2e+02 1 ++
10 -0.62 1.1 -1.2 -0.21 -1 1.2 -0.76 -0.36 -1.2 -0.39 8.3e+03 7.6e-06 6.2e+03 1 ++
11 -0.62 1.1 -1.2 -0.21 -1 1.2 -0.76 -0.36 -1.2 -0.39 8.3e+03 3.3e-10 6.2e+03 1 ++
Considering neighbor 1/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000073
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_1st lambda_travel_t b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 1 0 1 0 0 0 0 1.1e+04 0.26 0.5 0.048 -
1 -0.4 0.017 -0.5 -0.28 1 -0.39 1.3 0.27 0.0024 -0.053 -0.023 9.1e+03 0.13 0.5 0.71 +
2 -0.36 0.21 -0.66 -0.36 1 -0.44 1.3 -0.23 -0.055 -0.19 -0.056 8.6e+03 0.04 5 0.93 ++
3 -0.36 0.21 -0.66 -0.36 1 -0.44 1.3 -0.23 -0.055 -0.19 -0.056 8.6e+03 0.04 0.81 -2 -
4 -0.39 1 -1 -0.53 0.71 -0.99 1.6 -0.8 -0.45 -0.62 -0.31 8.2e+03 0.012 8.1 0.98 ++
5 -0.36 1.2 -1.5 -0.6 0.33 -1.2 1 -0.89 -0.2 -1 -0.47 8.2e+03 0.019 8.1 0.3 +
6 -0.63 1.3 -1.4 -0.63 0.45 -1.1 1.1 -0.84 -0.23 -1.1 -0.43 8.2e+03 0.00079 81 1 ++
7 -0.62 1.3 -1.3 -0.62 0.45 -1.1 1.1 -0.84 -0.23 -1.1 -0.43 8.2e+03 8.9e-06 8.1e+02 1 ++
8 -0.62 1.3 -1.3 -0.62 0.45 -1.1 1.1 -0.84 -0.23 -1.1 -0.43 8.2e+03 3.5e-08 8.1e+02 1 ++
Considering neighbor 2/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000074
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.26 0.5 0 -
1 0 0 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.26 0.25 -0.095 -
2 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 2.5 1 ++
3 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 1.2 1 -
4 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 0.62 -4.1 -
5 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 0.31 -2.3 -
6 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 0.16 -0.22 -
7 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.028 -0.047 0.0075 9.4e+03 11 0.16 0.27 +
8 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.028 -0.047 0.0075 9.4e+03 11 0.078 -0.8 -
9 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.028 -0.047 0.0075 9.4e+03 11 0.039 -0.7 -
10 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.028 -0.047 0.0075 9.4e+03 11 0.02 -0.64 -
11 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.028 -0.047 0.0075 9.4e+03 11 0.0098 -0.55 -
12 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.028 -0.047 0.0075 9.4e+03 11 0.0049 -0.094 -
13 -0.36 0.02 -0.41 -0.084 0.12 0.0011 -0.36 1.1 0.23 0.032 -0.052 0.012 9.2e+03 5.2 0.0049 0.34 +
14 -0.36 0.02 -0.41 -0.084 0.12 0.0011 -0.36 1.1 0.23 0.032 -0.052 0.012 9.2e+03 5.2 0.0024 -0.53 -
15 -0.36 0.022 -0.41 -0.081 0.12 -0.0013 -0.36 1.1 0.23 0.034 -0.054 0.014 9.1e+03 4.7 0.0024 0.61 +
16 -0.36 0.023 -0.42 -0.082 0.12 -0.00087 -0.36 1.1 0.23 0.034 -0.055 0.014 9.1e+03 2.7 0.024 1.3 ++
17 -0.37 0.031 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.036 -0.062 0.017 9.1e+03 5.5 0.024 0.33 +
18 -0.37 0.031 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.036 -0.062 0.017 9.1e+03 5.5 0.012 -2.4 -
19 -0.37 0.031 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.036 -0.062 0.017 9.1e+03 5.5 0.0061 -2 -
20 -0.37 0.031 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.036 -0.062 0.017 9.1e+03 5.5 0.0031 -1.6 -
21 -0.37 0.031 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.036 -0.062 0.017 9.1e+03 5.5 0.0015 -0.95 -
22 -0.37 0.031 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.036 -0.062 0.017 9.1e+03 5.5 0.00076 -0.22 -
23 -0.37 0.032 -0.43 -0.086 0.13 -0.0011 -0.37 1.1 0.2 0.037 -0.063 0.017 9e+03 3 0.00076 0.43 +
24 -0.37 0.032 -0.43 -0.086 0.13 -0.0011 -0.37 1.1 0.2 0.037 -0.063 0.017 9e+03 3 0.00038 -0.71 -
25 -0.37 0.032 -0.44 -0.087 0.13 -0.00069 -0.37 1.1 0.2 0.037 -0.064 0.018 9e+03 5 0.00038 0.39 +
26 -0.37 0.032 -0.44 -0.087 0.13 -0.00069 -0.37 1.1 0.2 0.037 -0.064 0.018 9e+03 5 0.00019 -0.17 -
27 -0.37 0.032 -0.44 -0.087 0.13 -0.00088 -0.37 1.1 0.2 0.037 -0.064 0.018 9e+03 2.6 0.00019 0.33 +
28 -0.37 0.032 -0.44 -0.087 0.13 -0.00088 -0.37 1.1 0.2 0.037 -0.064 0.018 9e+03 2.6 9.5e-05 -0.45 -
29 -0.37 0.032 -0.44 -0.087 0.13 -0.00079 -0.37 1.1 0.2 0.037 -0.064 0.018 9e+03 0.89 9.5e-05 0.68 +
30 -0.37 0.032 -0.44 -0.087 0.13 -0.0008 -0.37 1.1 0.2 0.037 -0.064 0.018 9e+03 0.064 0.00095 1 ++
31 -0.37 0.033 -0.44 -0.087 0.13 -0.00081 -0.37 1.1 0.2 0.037 -0.064 0.018 9e+03 0.39 0.0095 1 ++
32 -0.37 0.036 -0.44 -0.088 0.13 -0.00082 -0.37 1.1 0.19 0.038 -0.067 0.019 9e+03 0.063 0.095 1 ++
33 -0.39 0.07 -0.51 -0.097 0.17 -0.00098 -0.41 1.1 0.098 0.038 -0.097 0.022 8.9e+03 0.19 0.95 0.99 ++
34 -0.47 1 -0.95 -0.11 -0.17 0.00044 -1.1 1.5 -0.78 -0.54 -0.7 -0.38 8.6e+03 18 0.95 0.42 +
35 -0.47 1 -0.95 -0.11 -0.17 0.00044 -1.1 1.5 -0.78 -0.54 -0.7 -0.38 8.6e+03 18 0.48 -0.62 -
36 -0.47 0.92 -1.4 -0.24 0.031 -0.00033 -0.99 1.6 -0.89 -0.55 -0.72 -0.42 8.4e+03 20 0.48 0.22 +
37 -0.47 0.92 -1.4 -0.24 0.031 -0.00033 -0.99 1.6 -0.89 -0.55 -0.72 -0.42 8.4e+03 20 0.24 -6.3 -
38 -0.47 0.92 -1.4 -0.24 0.031 -0.00033 -0.99 1.6 -0.89 -0.55 -0.72 -0.42 8.4e+03 20 0.12 -1.1 -
39 -0.47 0.92 -1.4 -0.24 0.031 -0.00033 -0.99 1.6 -0.89 -0.55 -0.72 -0.42 8.4e+03 20 0.06 -0.047 -
40 -0.46 0.93 -1.4 -0.24 -0.028 -0.00079 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.4e+03 32 0.06 0.13 +
41 -0.46 0.93 -1.4 -0.24 -0.028 -0.00079 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.4e+03 32 0.03 -0.21 -
42 -0.46 0.93 -1.4 -0.24 -0.028 -0.00079 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.4e+03 32 0.015 -0.15 -
43 -0.46 0.93 -1.4 -0.24 -0.028 -0.00079 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.4e+03 32 0.0075 -0.15 -
44 -0.46 0.93 -1.4 -0.24 -0.028 -0.00079 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.4e+03 32 0.0037 -0.15 -
45 -0.46 0.93 -1.4 -0.24 -0.028 -0.00079 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.4e+03 32 0.0019 -0.16 -
46 -0.46 0.93 -1.4 -0.24 -0.028 -0.00079 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.4e+03 32 0.00093 -0.16 -
47 -0.46 0.93 -1.4 -0.24 -0.027 0.00014 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.3e+03 19 0.00093 0.39 +
48 -0.46 0.93 -1.4 -0.24 -0.027 0.00014 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.3e+03 19 0.00047 -0.45 -
49 -0.46 0.93 -1.4 -0.24 -0.028 -0.00032 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.3e+03 13 0.00047 0.4 +
50 -0.46 0.93 -1.4 -0.24 -0.028 -0.00019 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.3e+03 8.1 0.0047 1.4 ++
51 -0.46 0.93 -1.4 -0.24 -0.028 -0.00019 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.3e+03 8.1 0.0023 -2.6 -
52 -0.46 0.93 -1.4 -0.24 -0.028 -0.00019 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.3e+03 8.1 0.0012 -3.1 -
53 -0.46 0.93 -1.4 -0.24 -0.028 -0.00019 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.3e+03 8.1 0.00058 -3.4 -
54 -0.46 0.93 -1.4 -0.24 -0.028 -0.00019 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.3e+03 8.1 0.00029 -3.6 -
55 -0.46 0.93 -1.4 -0.24 -0.028 -0.00019 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.3e+03 8.1 0.00015 -2.2 -
56 -0.46 0.93 -1.4 -0.24 -0.028 -0.00019 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.3e+03 8.1 7.3e-05 -1.1 -
57 -0.46 0.93 -1.4 -0.24 -0.028 -0.00012 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.3e+03 13 7.3e-05 0.32 +
58 -0.46 0.93 -1.4 -0.24 -0.028 -0.00015 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.3e+03 3.3 7.3e-05 0.73 +
59 -0.46 0.93 -1.4 -0.24 -0.028 -0.00014 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.3e+03 0.95 7.3e-05 0.89 +
60 -0.46 0.93 -1.4 -0.24 -0.029 -0.00014 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.3e+03 0.15 0.00073 1 ++
61 -0.46 0.93 -1.4 -0.24 -0.029 -0.00014 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.3e+03 2.1 0.0073 1 ++
62 -0.46 0.93 -1.4 -0.24 -0.037 -0.00011 -0.99 1.5 -0.9 -0.55 -0.72 -0.42 8.2e+03 0.31 0.073 1 ++
63 -0.46 0.94 -1.4 -0.26 -0.11 0.00019 -1 1.5 -0.82 -0.55 -0.72 -0.43 8.2e+03 14 0.073 0.65 +
64 -0.4 0.96 -1.5 -0.32 -0.088 0.00011 -1 1.5 -0.83 -0.48 -0.74 -0.4 8.2e+03 0.65 0.73 1 ++
65 -0.45 1.2 -2.1 -0.89 -0.12 0.00025 -1.1 1 -0.8 -0.24 -1.1 -0.39 8.2e+03 15 0.73 0.38 +
66 -0.5 1.3 -2.1 -1.1 -0.11 0.0002 -1.1 1 -0.77 -0.19 -1.1 -0.35 8.1e+03 8.8 7.3 0.94 ++
67 -0.53 1.3 -2.1 -1.1 -0.11 0.0002 -1.1 1 -0.75 -0.18 -1.1 -0.35 8.1e+03 0.55 73 1 ++
68 -0.54 1.3 -2.1 -1.1 -0.11 0.00021 -1.1 1 -0.76 -0.17 -1.1 -0.35 8.1e+03 0.019 7.3e+02 1 ++
69 -0.56 1.3 -2.1 -1.1 -0.11 0.00021 -1.1 1 -0.76 -0.18 -1.1 -0.36 8.1e+03 0.00064 7.3e+03 1 ++
70 -0.56 1.3 -2.1 -1.1 -0.11 0.00021 -1.1 1 -0.76 -0.18 -1.1 -0.36 8.1e+03 1.3e-06 7.3e+03 1 ++
Considering neighbor 3/20 for current solution
Attempt 60/100
Biogeme parameters read from biogeme.toml.
Model with 18 unknown parameters [max: 50]
*** Estimate b07everything_000075
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.33 -
1 9.5e+03 1.1 0.5 0.7 +
2 9.5e+03 1.1 0.25 0.7 -
3 9.5e+03 1.1 0.12 0.7 -
4 9.5e+03 1.1 0.062 0.7 -
5 9.5e+03 1.1 0.031 -36 -
6 9.5e+03 1.1 0.016 -4 -
7 9.3e+03 3.9 0.016 0.77 +
8 9.3e+03 0.073 0.16 0.9 ++
9 9.1e+03 2.7 1.6 0.9 ++
10 9.1e+03 2.7 0.78 0.9 -
11 9.1e+03 2.7 0.39 0.9 -
12 9.1e+03 2.7 0.2 0.9 -
13 9.1e+03 2.7 0.098 0.9 -
14 9.1e+03 2.7 0.049 -5.8 -
15 9.1e+03 2.7 0.024 -6.3 -
16 9.1e+03 2.7 0.012 -6.8 -
17 9.1e+03 2.7 0.0061 -7.2 -
18 9.1e+03 2.7 0.0031 -4.1 -
19 9.1e+03 2.7 0.0015 -2.1 -
20 9.1e+03 2.7 0.00076 -0.59 -
21 9e+03 2.9 0.00076 0.32 +
22 9e+03 2.9 0.00038 -0.13 -
23 9e+03 1.4 0.00038 0.63 +
24 9e+03 0.31 0.0038 0.92 ++
25 9e+03 0.069 0.038 1 ++
26 9e+03 0.24 0.38 1 ++
27 8.7e+03 2.3 0.38 0.65 +
28 8.7e+03 2.3 0.19 -0.28 -
29 8.4e+03 5.9 0.19 0.86 +
30 8.4e+03 5.9 0.095 -0.41 -
31 8.4e+03 5.9 0.048 -0.4 -
32 8.4e+03 5.9 0.024 -0.66 -
33 8.4e+03 5.9 0.012 -0.98 -
34 8.4e+03 5.9 0.006 -1.2 -
35 8.4e+03 5.9 0.003 -1.4 -
36 8.4e+03 5.9 0.0015 -1.5 -
37 8.4e+03 5.9 0.00075 -1.4 -
38 8.4e+03 5.9 0.00037 -0.7 -
39 8.4e+03 5.9 0.00019 -0.13 -
40 8.4e+03 2 0.00019 0.64 +
41 8.4e+03 0.049 0.0019 0.99 ++
42 8.4e+03 0.31 0.019 1 ++
43 8.4e+03 0.041 0.19 1 ++
44 8.3e+03 0.6 0.19 0.9 +
45 8.2e+03 1.1 0.19 0.83 +
46 8.2e+03 0.47 0.19 0.89 +
47 8.1e+03 0.89 1.9 0.93 ++
48 8.1e+03 0.89 0.93 -2.4e+02 -
49 8.1e+03 0.89 0.47 -34 -
50 8.1e+03 0.031 4.7 1.1 ++
51 8.1e+03 2.2 47 1.1 ++
52 8e+03 5.1 4.7e+02 1.3 ++
53 8e+03 5.1 0.36 -3.3 -
54 8e+03 21 0.36 0.21 +
55 8e+03 5.1 3.6 0.94 ++
56 8e+03 0.67 36 0.97 ++
57 8e+03 0.0022 3.6e+02 1 ++
58 8e+03 0.00015 3.6e+03 1 ++
59 8e+03 0.00041 3.6e+04 1 ++
60 8e+03 1.9e-07 3.6e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 61/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000076
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_1st b_cost mu_public asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -0.84 0.065 -1 -0.58 -0.25 1.6 -0.034 -0.11 9.3e+03 0.13 1 0.43 +
1 -0.37 1.1 -0.76 -0.44 -1.1 1.7 -0.34 -0.52 8.5e+03 0.086 1 0.61 +
2 -0.49 0.54 -0.54 -0.42 -0.62 2.2 -0.25 -1.5 8.3e+03 0.038 1 0.59 +
3 -0.68 0.87 -0.85 -0.35 -0.78 1.2 -0.16 -1.4 8.3e+03 0.023 1 0.23 +
4 -0.81 1.2 -0.79 -0.54 -0.77 1.3 -0.085 -1.3 8.3e+03 0.0021 10 1 ++
5 -0.89 1.2 -0.83 -0.58 -0.78 1.2 -0.051 -1.3 8.3e+03 0.0012 1e+02 1 ++
6 -0.91 1.2 -0.83 -0.58 -0.78 1.2 -0.048 -1.3 8.3e+03 2.1e-05 1e+03 1 ++
7 -0.91 1.2 -0.83 -0.58 -0.78 1.2 -0.048 -1.3 8.3e+03 4.7e-07 1e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 62/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000077
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time b_cost_train mu_existing asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 -0.53 0.26 0.0051 -0.0076 -1 -0.51 1.9 0.16 -0.28 -0.08 -0.02 0.05 -0.61 9.1e+03 0.18 1 0.72 +
1 -0.53 0.26 0.0051 -0.0076 -1 -0.51 1.9 0.16 -0.28 -0.08 -0.02 0.05 -0.61 9.1e+03 0.18 0.5 -0.27 -
2 -0.23 0.65 0.39 0.028 -0.77 -0.61 2.4 -0.17 -0.42 -0.19 -0.073 -0.19 -0.44 8.7e+03 0.16 0.5 0.36 +
3 -0.64 0.37 0.19 0.049 -0.76 -0.4 2.9 -0.19 -0.18 -0.043 -0.14 -0.24 -0.48 8.3e+03 0.039 0.5 0.74 +
4 -0.65 0.68 0.25 0.11 -0.97 -0.49 2.4 -0.37 -0.057 -0.044 -0.25 -0.095 -0.54 8.3e+03 0.0064 5 1.1 ++
5 -0.65 0.68 0.25 0.11 -0.97 -0.49 2.4 -0.37 -0.057 -0.044 -0.25 -0.095 -0.54 8.3e+03 0.0064 0.72 -1.6 -
6 -0.82 0.86 0.32 0.11 -1.1 -0.64 1.7 -0.24 -0.28 -0.089 -0.3 -0.33 -0.66 8.2e+03 0.0097 7.2 1 ++
7 -0.86 0.9 0.37 0.27 -1.1 -0.73 1.6 -0.28 -0.47 -0.035 -0.33 -0.29 -0.66 8.2e+03 0.0021 72 1.1 ++
8 -0.88 0.92 0.38 0.3 -1.1 -0.77 1.5 -0.28 -0.54 -0.033 -0.35 -0.29 -0.67 8.2e+03 0.00026 7.2e+02 1.1 ++
9 -0.88 0.92 0.38 0.3 -1.1 -0.77 1.5 -0.28 -0.54 -0.033 -0.35 -0.29 -0.67 8.2e+03 1.9e-06 7.2e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 63/100
Biogeme parameters read from biogeme.toml.
Model with 7 unknown parameters [max: 50]
*** Estimate b07everything_000078
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train lambda_travel_t b_cost b_time_swissmet asc_car b_time_car Function Relgrad Radius Rho
0 -1 -0.7 1.3 -0.47 -0.52 -0.56 -0.64 8.9e+03 0.059 10 0.95 ++
1 -1 -0.7 1.3 -0.47 -0.52 -0.56 -0.64 8.9e+03 0.059 0.9 -0.047 -
2 -0.45 -1.5 0.73 -0.67 -1.4 0.02 -1.1 8.6e+03 0.027 9 1.1 ++
3 -0.22 -2.3 0.38 -0.78 -1.7 0.061 -1.4 8.5e+03 0.014 90 1.2 ++
4 -0.17 -2.6 0.28 -0.79 -1.7 0.075 -1.4 8.5e+03 0.0016 9e+02 1.1 ++
5 -0.16 -2.6 0.27 -0.8 -1.7 0.077 -1.4 8.5e+03 2.6e-05 9e+03 1 ++
6 -0.16 -2.6 0.27 -0.8 -1.7 0.077 -1.4 8.5e+03 4.3e-09 9e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 64/100
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000079
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di b_cost b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 -0.91 0.83 0.049 0.01 -0.83 -0.15 -0.64 -1 0.27 -0.28 -0.4 -0.17 -0.059 -0.78 -0.038 8.5e+03 0.084 10 1.1 ++
1 -1.3 1.4 0.36 0.43 -1.4 0.68 -0.73 -1.7 2.2 -0.38 -0.78 -0.07 -0.34 -1.1 0.97 8.2e+03 0.027 1e+02 0.99 ++
2 -1.4 1.4 0.52 0.6 -1.5 0.11 -0.75 -1.8 1.1 -0.52 -0.92 -0.084 -0.42 -1.1 0.44 8.1e+03 0.014 1e+02 0.41 +
3 -1.4 1.4 0.54 0.65 -1.5 0.61 -0.76 -1.8 2.2 -0.4 -0.94 -0.08 -0.42 -1.2 0.97 8.1e+03 0.0081 1e+02 0.15 +
4 -1.4 1.4 0.54 0.65 -1.5 0.61 -0.76 -1.8 2.2 -0.4 -0.94 -0.08 -0.42 -1.2 0.97 8.1e+03 0.0081 0.51 -0.05 -
5 -1.4 1.4 0.56 0.64 -1.7 0.4 -0.74 -2 1.7 -0.52 -0.94 -0.079 -0.42 -1.2 0.69 8.1e+03 0.011 0.51 0.54 +
6 -1.4 1.4 0.54 0.64 -1.5 0.33 -0.75 -1.8 1.6 -0.44 -0.94 -0.082 -0.42 -1.2 0.64 8.1e+03 0.00029 5.1 0.98 ++
7 -1.4 1.4 0.54 0.64 -1.5 0.33 -0.75 -1.8 1.6 -0.44 -0.94 -0.082 -0.42 -1.2 0.64 8.1e+03 5e-07 5.1 1 ++
Considering neighbor 0/20 for current solution
Attempt 65/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000080
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train square_tt_coef cube_tt_coef b_cost b_time_swissmet asc_car b_time_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.16 -
1 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.5 0.8 +
2 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.25 -10 -
3 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.12 -12 -
4 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.062 -14 -
5 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.031 -16 -
6 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.016 -5.2 -
7 -0.29 -0.52 0.017 -0.0028 -0.054 0.19 -0.0082 -0.014 9.5e+03 5.2 0.016 0.36 +
8 -0.29 -0.52 0.019 0.00075 -0.061 0.19 -0.014 -0.029 9.4e+03 0.41 0.016 0.66 +
9 -0.29 -0.52 0.019 0.00075 -0.061 0.19 -0.014 -0.029 9.4e+03 0.41 0.0078 -0.85 -
10 -0.29 -0.52 0.019 0.00075 -0.061 0.19 -0.014 -0.029 9.4e+03 0.41 0.0039 -0.93 -
11 -0.29 -0.52 0.019 0.00075 -0.061 0.19 -0.014 -0.029 9.4e+03 0.41 0.002 -1.2 -
12 -0.29 -0.53 0.021 -0.0012 -0.063 0.19 -0.016 -0.031 9.4e+03 1.1 0.002 0.6 +
13 -0.29 -0.53 0.022 -0.00093 -0.064 0.19 -0.017 -0.033 9.4e+03 0.34 0.02 1.1 ++
14 -0.29 -0.53 0.03 -0.00065 -0.078 0.19 -0.026 -0.053 9.3e+03 0.11 0.2 1 ++
15 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.2 0.64 +
16 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.098 -8.6 -
17 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.049 -8.9 -
18 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.024 -11 -
19 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.012 -5.2 -
20 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.0061 -3.5 -
21 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.0031 -2.1 -
22 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.0015 -0.54 -
23 -0.33 -0.63 0.11 -0.0013 -0.23 0.17 -0.11 -0.25 9.2e+03 2.1 0.0015 0.45 +
24 -0.33 -0.63 0.11 -0.0004 -0.23 0.16 -0.11 -0.25 9.2e+03 2.5 0.0015 0.28 +
25 -0.33 -0.63 0.11 -0.0004 -0.23 0.16 -0.11 -0.25 9.2e+03 2.5 0.00076 -0.39 -
26 -0.33 -0.63 0.11 -0.0012 -0.23 0.16 -0.11 -0.24 9.2e+03 1.8 0.00076 0.21 +
27 -0.33 -0.63 0.11 -0.0012 -0.23 0.16 -0.11 -0.24 9.2e+03 1.8 0.00038 0.023 -
28 -0.33 -0.63 0.11 -0.00078 -0.23 0.16 -0.11 -0.24 9.2e+03 0.1 0.00038 0.89 +
29 -0.33 -0.63 0.11 -0.00071 -0.23 0.16 -0.11 -0.24 9.2e+03 0.95 0.0038 0.97 ++
30 -0.33 -0.63 0.11 -0.00077 -0.24 0.16 -0.1 -0.24 9.2e+03 0.098 0.038 1 ++
31 -0.33 -0.63 0.092 -0.00067 -0.26 0.12 -0.093 -0.22 9.1e+03 0.22 0.38 1 ++
32 -0.34 -0.72 0.19 -0.00095 -0.53 -0.26 -0.083 -0.28 8.8e+03 1.9 0.38 0.8 +
33 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.38 0.44 +
34 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.19 -5.4 -
35 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.095 -5.9 -
36 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.048 -7.3 -
37 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.024 -5.5 -
38 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.012 -4.1 -
39 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.006 -3.5 -
40 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.003 -3.1 -
41 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.0015 -2.7 -
42 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.00075 -2.1 -
43 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.00037 -0.88 -
44 -0.32 -0.71 0.48 -0.0022 -0.72 -0.64 -0.2 -0.53 8.7e+03 0.06 0.0037 0.91 ++
45 -0.32 -0.71 0.48 -0.0023 -0.72 -0.64 -0.2 -0.52 8.7e+03 1.2 0.037 1 ++
46 -0.33 -0.72 0.45 -0.0021 -0.72 -0.64 -0.2 -0.49 8.7e+03 0.87 0.37 1 ++
47 -0.5 -0.91 0.079 -0.00062 -0.77 -0.79 -0.51 -0.56 8.7e+03 0.6 0.37 0.4 +
48 -0.39 -1.3 0.084 -0.00061 -0.77 -1.2 -0.51 -0.78 8.6e+03 0.83 3.7 1.1 ++
49 -0.39 -1.3 0.084 -0.00061 -0.77 -1.2 -0.51 -0.78 8.6e+03 0.83 1.9 -1.6e+02 -
50 -0.39 -1.3 0.084 -0.00061 -0.77 -1.2 -0.51 -0.78 8.6e+03 0.83 0.93 -68 -
51 -0.39 -1.3 0.084 -0.00061 -0.77 -1.2 -0.51 -0.78 8.6e+03 0.83 0.47 -8.8 -
52 -0.39 -1.3 0.084 -0.00061 -0.77 -1.2 -0.51 -0.78 8.6e+03 0.83 0.23 -0.023 -
53 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.23 0.69 +
54 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.12 -2.5 -
55 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.058 -2.5 -
56 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.029 -2.3 -
57 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.015 -2.3 -
58 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.0073 -2.5 -
59 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.0036 -2.7 -
60 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.0018 -2.8 -
61 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.00091 -2.9 -
62 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.00045 -1.5 -
63 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.00023 -0.4 -
64 -0.4 -1.5 -0.026 -0.00028 -0.77 -1.3 -0.5 -0.88 8.6e+03 5.2 0.00023 0.17 +
65 -0.4 -1.5 -0.026 -0.00028 -0.77 -1.3 -0.5 -0.88 8.6e+03 5.2 0.00011 -0.57 -
66 -0.4 -1.5 -0.026 -0.00016 -0.77 -1.3 -0.5 -0.88 8.6e+03 0.62 0.0011 0.96 ++
67 -0.4 -1.5 -0.025 -0.00016 -0.77 -1.3 -0.5 -0.88 8.6e+03 0.036 0.011 1 ++
68 -0.4 -1.5 -0.014 -0.00021 -0.77 -1.3 -0.51 -0.88 8.6e+03 0.044 0.11 1 ++
69 -0.33 -1.6 -0.0048 -0.00025 -0.77 -1.4 -0.52 -0.96 8.6e+03 0.024 1.1 0.99 ++
70 -0.33 -1.6 -0.0048 -0.00025 -0.77 -1.4 -0.52 -0.96 8.6e+03 0.024 0.57 -6.2 -
71 -0.33 -1.6 -0.0048 -0.00025 -0.77 -1.4 -0.52 -0.96 8.6e+03 0.024 0.28 -0.12 -
72 -0.28 -1.9 -0.074 4.3e-05 -0.77 -1.5 -0.53 -1.1 8.5e+03 2.3 0.28 0.8 +
73 -0.11 -2.1 -0.064 7.6e-06 -0.78 -1.8 -0.53 -1.3 8.5e+03 0.12 2.8 0.99 ++
74 -0.11 -2.1 -0.064 7.6e-06 -0.78 -1.8 -0.53 -1.3 8.5e+03 0.12 0.65 -5.4 -
75 -0.11 -2.1 -0.064 7.6e-06 -0.78 -1.8 -0.53 -1.3 8.5e+03 0.12 0.33 -0.13 -
76 -0.0096 -2.4 -0.1 0.00017 -0.78 -2 -0.52 -1.5 8.5e+03 6.7 0.33 0.77 +
77 0.2 -2.8 -0.099 0.00017 -0.8 -2.2 -0.52 -1.6 8.5e+03 1.4 3.3 1 ++
78 0.35 -3 -0.11 0.00021 -0.8 -2.4 -0.49 -1.7 8.5e+03 1.6 33 0.93 ++
79 0.34 -3 -0.11 0.0002 -0.8 -2.4 -0.5 -1.7 8.5e+03 0.028 3.3e+02 1 ++
80 0.34 -3 -0.11 0.0002 -0.8 -2.4 -0.5 -1.7 8.5e+03 0.00016 3.3e+03 1 ++
81 0.34 -3 -0.11 0.0002 -0.8 -2.4 -0.5 -1.7 8.5e+03 7.3e-06 3.3e+04 1 ++
82 0.34 -3 -0.11 0.0002 -0.8 -2.4 -0.5 -1.7 8.5e+03 2.7e-06 3.3e+04 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 7 unknown parameters [max: 50]
*** Estimate b07everything_000081
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_1st lambda_travel_t b_cost mu_public asc_car Function Relgrad Radius Rho
0 -0.84 -1 -0.57 1.2 -0.24 1.6 -0.032 9.4e+03 0.12 1 0.4 +
1 -0.048 -0.53 -0.37 0.8 -1.2 2.1 -0.23 9.2e+03 0.18 1 0.15 +
2 -0.18 -0.6 -0.29 0.91 -0.24 2.8 -0.28 8.8e+03 0.07 1 0.55 +
3 -0.13 -0.94 -0.58 0.29 -0.63 1.8 -0.088 8.7e+03 0.011 1 0.83 +
4 -0.18 -1.4 -0.64 0.6 -0.83 1 0.15 8.6e+03 0.032 1 0.42 +
5 -0.47 -1.2 -0.67 0.58 -0.85 1.1 0.075 8.6e+03 0.0012 10 0.97 ++
6 -0.51 -1.2 -0.7 0.57 -0.86 1 0.12 8.6e+03 0.00083 10 0.89 +
7 -0.5 -1.2 -0.7 0.57 -0.86 1 0.11 8.6e+03 2.4e-05 1e+02 1 ++
8 -0.5 -1.2 -0.7 0.57 -0.86 1 0.11 8.6e+03 9.4e-08 1e+02 1 ++
Considering neighbor 1/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000082
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train_re b_time_train_di square_tt_coef cube_tt_coef b_cost_train mu_public b_time_swissmet b_time_swissmet b_cost_swissmet asc_car b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.45 -
1 -0.27 -0.5 -0.071 0.0049 0.049 -0.28 1 0.2 0.046 0.24 0.0069 -0.022 -0.022 -0.0069 1e+04 1.3 0.5 0.28 +
2 -0.27 -0.5 -0.071 0.0049 0.049 -0.28 1 0.2 0.046 0.24 0.0069 -0.022 -0.022 -0.0069 1e+04 1.3 0.25 0.28 -
3 -0.27 -0.5 -0.071 0.0049 0.049 -0.28 1 0.2 0.046 0.24 0.0069 -0.022 -0.022 -0.0069 1e+04 1.3 0.12 0.28 -
4 -0.27 -0.5 -0.071 0.0049 0.049 -0.28 1 0.2 0.046 0.24 0.0069 -0.022 -0.022 -0.0069 1e+04 1.3 0.062 -5.3 -
5 -0.27 -0.5 -0.071 0.0049 0.049 -0.28 1 0.2 0.046 0.24 0.0069 -0.022 -0.022 -0.0069 1e+04 1.3 0.031 -0.22 -
6 -0.24 -0.47 -0.075 -0.026 0.018 -0.24 1 0.17 0.078 0.21 0.013 0.0094 0.0094 -0.038 9.5e+03 0.97 0.031 0.85 +
7 -0.24 -0.47 -0.075 -0.026 0.018 -0.24 1 0.17 0.078 0.21 0.013 0.0094 0.0094 -0.038 9.5e+03 0.97 0.016 -5 -
8 -0.23 -0.46 -0.083 -0.042 0.0024 -0.26 1 0.16 0.093 0.2 -0.0026 -0.0062 -0.0062 -0.054 9.4e+03 0.38 0.16 0.93 ++
9 -0.23 -0.46 -0.083 -0.042 0.0024 -0.26 1 0.16 0.093 0.2 -0.0026 -0.0062 -0.0062 -0.054 9.4e+03 0.38 0.078 -13 -
10 -0.23 -0.46 -0.083 -0.042 0.0024 -0.26 1 0.16 0.093 0.2 -0.0026 -0.0062 -0.0062 -0.054 9.4e+03 0.38 0.039 -11 -
11 -0.23 -0.46 -0.083 -0.042 0.0024 -0.26 1 0.16 0.093 0.2 -0.0026 -0.0062 -0.0062 -0.054 9.4e+03 0.38 0.02 -10 -
12 -0.23 -0.46 -0.083 -0.042 0.0024 -0.26 1 0.16 0.093 0.2 -0.0026 -0.0062 -0.0062 -0.054 9.4e+03 0.38 0.0098 -10 -
13 -0.23 -0.46 -0.083 -0.042 0.0024 -0.26 1 0.16 0.093 0.2 -0.0026 -0.0062 -0.0062 -0.054 9.4e+03 0.38 0.0049 -11 -
14 -0.23 -0.46 -0.083 -0.042 0.0024 -0.26 1 0.16 0.093 0.2 -0.0026 -0.0062 -0.0062 -0.054 9.4e+03 0.38 0.0024 -2 -
15 -0.23 -0.46 -0.086 -0.04 -5.5e-05 -0.26 1 0.15 0.096 0.19 -0.0051 -0.0087 -0.0086 -0.056 9.4e+03 0.073 0.024 0.9 ++
16 -0.23 -0.47 -0.09 -0.031 -0.00043 -0.28 1 0.14 0.1 0.17 -0.0076 -0.02 -0.017 -0.061 9.3e+03 0.23 0.24 0.99 ++
17 -0.26 -0.58 -0.13 0.051 0.00065 -0.4 1.1 -0.0079 0.15 -0.075 -0.053 -0.17 -0.11 -0.13 9.1e+03 2.2 0.24 0.88 +
18 -0.26 -0.58 -0.13 0.051 0.00065 -0.4 1.1 -0.0079 0.15 -0.075 -0.053 -0.17 -0.11 -0.13 9.1e+03 2.2 0.12 0.88 -
19 -0.26 -0.58 -0.13 0.051 0.00065 -0.4 1.1 -0.0079 0.15 -0.075 -0.053 -0.17 -0.11 -0.13 9.1e+03 2.2 0.061 0.88 -
20 -0.26 -0.58 -0.13 0.051 0.00065 -0.4 1.1 -0.0079 0.15 -0.075 -0.053 -0.17 -0.11 -0.13 9.1e+03 2.2 0.031 -12 -
21 -0.26 -0.58 -0.13 0.051 0.00065 -0.4 1.1 -0.0079 0.15 -0.075 -0.053 -0.17 -0.11 -0.13 9.1e+03 2.2 0.015 -6.7 -
22 -0.26 -0.58 -0.13 0.051 0.00065 -0.4 1.1 -0.0079 0.15 -0.075 -0.053 -0.17 -0.11 -0.13 9.1e+03 2.2 0.0076 -4.9 -
23 -0.26 -0.58 -0.13 0.051 0.00065 -0.4 1.1 -0.0079 0.15 -0.075 -0.053 -0.17 -0.11 -0.13 9.1e+03 2.2 0.0038 -3.6 -
24 -0.26 -0.58 -0.13 0.051 0.00065 -0.4 1.1 -0.0079 0.15 -0.075 -0.053 -0.17 -0.11 -0.13 9.1e+03 2.2 0.0019 -1.8 -
25 -0.26 -0.58 -0.13 0.051 0.00065 -0.4 1.1 -0.0079 0.15 -0.075 -0.053 -0.17 -0.11 -0.13 9.1e+03 2.2 0.00095 0.046 -
26 -0.26 -0.58 -0.13 0.05 -0.00031 -0.41 1.1 -0.0088 0.15 -0.076 -0.054 -0.17 -0.11 -0.13 9e+03 1.9 0.0095 0.99 ++
27 -0.26 -0.57 -0.13 0.052 -0.0009 -0.41 1.1 -0.016 0.16 -0.081 -0.057 -0.18 -0.12 -0.14 9e+03 3.4 0.0095 0.21 +
28 -0.26 -0.57 -0.13 0.054 0.00013 -0.41 1.1 -0.025 0.16 -0.086 -0.061 -0.19 -0.12 -0.14 9e+03 2.3 0.0095 0.31 +
29 -0.26 -0.57 -0.13 0.054 0.00013 -0.41 1.1 -0.025 0.16 -0.086 -0.061 -0.19 -0.12 -0.14 9e+03 2.3 0.0048 -4.3 -
30 -0.26 -0.57 -0.13 0.054 0.00013 -0.41 1.1 -0.025 0.16 -0.086 -0.061 -0.19 -0.12 -0.14 9e+03 2.3 0.0024 -3 -
31 -0.26 -0.57 -0.13 0.054 0.00013 -0.41 1.1 -0.025 0.16 -0.086 -0.061 -0.19 -0.12 -0.14 9e+03 2.3 0.0012 -1.4 -
32 -0.26 -0.57 -0.13 0.054 0.00013 -0.41 1.1 -0.025 0.16 -0.086 -0.061 -0.19 -0.12 -0.14 9e+03 2.3 0.0006 -0.064 -
33 -0.26 -0.57 -0.13 0.054 -0.00047 -0.41 1.1 -0.026 0.16 -0.087 -0.061 -0.19 -0.12 -0.14 9e+03 0.5 0.006 0.92 ++
34 -0.25 -0.57 -0.13 0.057 -0.00051 -0.41 1.1 -0.032 0.16 -0.091 -0.063 -0.2 -0.12 -0.15 9e+03 0.063 0.06 1 ++
35 -0.24 -0.56 -0.13 0.085 -0.00061 -0.44 1.1 -0.092 0.16 -0.13 -0.081 -0.25 -0.14 -0.17 8.9e+03 0.15 0.6 0.99 ++
36 -0.23 -0.67 -0.2 0.5 -0.0023 -0.74 1.1 -0.69 0.22 -0.48 -0.14 -0.49 -0.25 -0.25 8.7e+03 0.088 0.6 0.42 +
37 -0.17 -0.71 -0.15 0.24 -0.0013 -1.3 1 -0.8 0.67 -0.51 -0.56 -0.44 -0.032 -0.56 8.4e+03 0.19 6 0.95 ++
38 -0.21 -0.8 0.093 0.21 -0.0012 -1.9 1 -1 0.98 -0.78 -0.63 -0.67 0.25 -0.6 8.3e+03 0.034 60 1.1 ++
39 -0.21 -0.8 0.093 0.21 -0.0012 -1.9 1 -1 0.98 -0.78 -0.63 -0.67 0.25 -0.6 8.3e+03 0.034 1.2 -6.4e+02 -
40 -0.21 -0.8 0.093 0.21 -0.0012 -1.9 1 -1 0.98 -0.78 -0.63 -0.67 0.25 -0.6 8.3e+03 0.034 0.59 -97 -
41 -0.21 -0.8 0.093 0.21 -0.0012 -1.9 1 -1 0.98 -0.78 -0.63 -0.67 0.25 -0.6 8.3e+03 0.034 0.3 -8.8 -
42 -0.22 -1 0.053 0.025 -0.00036 -2 1 -1.3 1.1 -0.82 -0.52 -0.95 0.26 -0.63 8.3e+03 1.2 0.3 0.18 +
43 -0.22 -1 0.055 0.059 -0.00052 -2 1 -1.3 1.1 -0.81 -0.53 -0.96 0.26 -0.64 8.3e+03 0.16 3 1 ++
44 -0.22 -1 0.055 0.059 -0.00052 -2 1 -1.3 1.1 -0.81 -0.53 -0.96 0.26 -0.64 8.3e+03 0.16 0.91 -1.7e+02 -
45 -0.22 -1 0.055 0.059 -0.00052 -2 1 -1.3 1.1 -0.81 -0.53 -0.96 0.26 -0.64 8.3e+03 0.16 0.45 -6.9 -
46 0.086 -1.5 0.22 -0.019 -0.00019 -1.8 1 -1.6 1.3 -0.82 -0.6 -1.2 0.29 -0.61 8.3e+03 0.16 0.45 0.89 +
47 0.052 -1.5 0.18 -0.024 -0.00017 -1.9 1 -1.7 1.3 -0.75 -0.52 -1.2 0.34 -0.63 8.3e+03 0.078 4.5 1 ++
48 0.052 -1.5 0.18 -0.024 -0.00017 -1.9 1 -1.7 1.3 -0.75 -0.52 -1.2 0.34 -0.63 8.3e+03 0.078 2.3 -4.8e+02 -
49 0.052 -1.5 0.18 -0.024 -0.00017 -1.9 1 -1.7 1.3 -0.75 -0.52 -1.2 0.34 -0.63 8.3e+03 0.078 1.1 -1.2e+02 -
50 0.052 -1.5 0.18 -0.024 -0.00017 -1.9 1 -1.7 1.3 -0.75 -0.52 -1.2 0.34 -0.63 8.3e+03 0.078 0.57 -18 -
51 0.052 -1.5 0.18 -0.024 -0.00017 -1.9 1 -1.7 1.3 -0.75 -0.52 -1.2 0.34 -0.63 8.3e+03 0.078 0.28 -1.2 -
52 0.088 -1.8 0.14 -0.076 5.4e-05 -1.9 1 -2 1.3 -0.82 -0.48 -1.5 0.25 -0.66 8.3e+03 0.24 0.28 0.83 +
53 0.088 -1.8 0.14 -0.067 1.3e-05 -1.9 1 -2 1.3 -0.81 -0.48 -1.5 0.25 -0.66 8.3e+03 0.16 2.8 1 ++
54 0.088 -1.8 0.14 -0.067 1.3e-05 -1.9 1 -2 1.3 -0.81 -0.48 -1.5 0.25 -0.66 8.3e+03 0.16 0.7 -19 -
55 0.088 -1.8 0.14 -0.067 1.3e-05 -1.9 1 -2 1.3 -0.81 -0.48 -1.5 0.25 -0.66 8.3e+03 0.16 0.35 -0.57 -
56 0.29 -2.2 0.15 -0.093 0.00013 -1.9 1 -2.2 1.1 -0.8 -0.49 -1.7 0.27 -0.64 8.3e+03 2.1 3.5 0.93 ++
57 0.28 -2.2 0.14 -0.089 0.00011 -1.9 1 -2.2 1.1 -0.8 -0.49 -1.7 0.27 -0.64 8.3e+03 0.13 35 1 ++
58 0.51 -2.6 -0.14 -0.12 0.00025 -1.8 1 -2.5 0.76 -0.78 -0.43 -2 -0.085 -0.65 8.3e+03 8.2 35 0.22 +
59 0.45 -2.5 -0.2 -0.11 0.00019 -1.9 1 -2.4 0.67 -0.79 -0.43 -1.9 -0.18 -0.65 8.3e+03 0.92 3.5e+02 1.1 ++
60 0.44 -2.5 -0.23 -0.1 0.00019 -1.9 1 -2.4 0.61 -0.8 -0.43 -1.9 -0.21 -0.66 8.3e+03 0.055 3.5e+03 1 ++
61 0.45 -2.5 -0.25 -0.11 0.00019 -1.9 1 -2.4 0.57 -0.8 -0.43 -1.9 -0.25 -0.65 8.3e+03 0.011 3.5e+04 0.99 ++
62 0.45 -2.5 -0.26 -0.1 0.00019 -1.9 1 -2.4 0.56 -0.8 -0.43 -1.9 -0.25 -0.65 8.3e+03 0.0032 3.5e+05 1 ++
63 0.45 -2.5 -0.27 -0.11 0.00019 -1.9 1 -2.4 0.55 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 0.00031 3.5e+06 1 ++
64 0.45 -2.5 -0.27 -0.11 0.00019 -1.9 1 -2.4 0.55 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 4.4e-05 3.5e+07 1 ++
65 0.45 -2.5 -0.27 -0.11 0.00019 -1.9 1 -2.4 0.55 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 0.00094 3.5e+08 1 ++
66 0.45 -2.5 -0.27 -0.11 0.00019 -1.9 1 -2.4 0.55 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 4.4e-06 3.5e+08 1 ++
Considering neighbor 2/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 16 unknown parameters [max: 50]
*** Estimate b07everything_000083
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.38 -
1 9.6e+03 0.17 0.5 0.49 +
2 8.7e+03 0.093 0.5 0.78 +
3 8.3e+03 0.02 5 1 ++
4 8.2e+03 0.048 5 0.55 +
5 8.2e+03 0.002 50 0.99 ++
6 8.2e+03 0.0029 5e+02 1 ++
7 8.2e+03 0.0013 5e+03 1 ++
8 8.2e+03 4.4e-05 5e+04 1 ++
9 8.2e+03 3e-08 5e+04 1 ++
Considering neighbor 3/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 20 unknown parameters [max: 50]
*** Estimate b07everything_000084
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.53 -
1 1.1e+04 0.4 0.25 0.02 -
2 9.7e+03 1.1 0.25 0.77 +
3 9.7e+03 1.1 0.12 -6.8 -
4 1.8e+04 5.4 1.2 6.9 ++
5 1.8e+04 5.4 0.62 -0.44 -
6 1.8e+04 5.4 0.31 -0.093 -
7 1.2e+04 2.1 3.1 1.5 ++
8 1.2e+04 2.1 1.6 1.5 -
9 1.2e+04 2.1 0.78 1.5 -
10 1.2e+04 2.1 0.39 1.5 -
11 1.2e+04 2.1 0.2 -1.6 -
12 1.2e+04 2.1 0.098 -0.89 -
13 1.1e+04 2.3 0.098 0.49 +
14 9.5e+03 0.18 0.98 1.2 ++
15 9.5e+03 0.18 0.49 1.2 -
16 9.5e+03 0.18 0.24 1.2 -
17 9.5e+03 0.18 0.12 -9.7 -
18 9.5e+03 0.18 0.061 -7.6 -
19 9.5e+03 0.18 0.031 -6.2 -
20 9.5e+03 0.18 0.015 -3.3 -
21 9.5e+03 1.8 0.015 0.51 +
22 9.4e+03 0.11 0.015 0.63 +
23 9.4e+03 0.11 0.0076 -3.7 -
24 9.4e+03 0.11 0.0038 0.051 -
25 9.4e+03 0.1 0.038 0.97 ++
26 9.3e+03 0.12 0.38 1 ++
27 9.3e+03 0.12 0.19 1 -
28 9.3e+03 0.12 0.095 -11 -
29 9.3e+03 0.12 0.048 -8.9 -
30 9.3e+03 0.12 0.024 -8.4 -
31 9.3e+03 0.12 0.012 -9.5 -
32 9.3e+03 0.12 0.006 -3 -
33 9.3e+03 0.12 0.003 0.098 -
34 9.3e+03 0.072 0.03 0.97 ++
35 9.3e+03 0.072 0.015 -2.1 -
36 9.3e+03 0.072 0.0075 -0.52 -
37 9.3e+03 0.072 0.0037 0.00069 -
38 9.3e+03 1.1 0.0037 0.42 +
39 9.3e+03 0.067 0.0037 0.87 +
40 9.3e+03 0.067 0.0019 -0.23 -
41 9.3e+03 0.81 0.0019 0.38 +
42 9.3e+03 0.064 0.019 0.94 ++
43 9.2e+03 0.32 0.19 1.3 ++
44 9.2e+03 0.32 0.093 -9.9 -
45 9.2e+03 0.32 0.047 -10 -
46 9.2e+03 0.32 0.023 -11 -
47 9.2e+03 0.32 0.012 -14 -
48 9.2e+03 0.32 0.0058 -3 -
49 9.2e+03 0.32 0.0029 -0.17 -
50 9.2e+03 0.2 0.029 0.98 ++
51 9.1e+03 1.6 0.029 0.81 +
52 9.1e+03 0.75 0.029 0.63 +
53 9.1e+03 0.75 0.015 -9.8 -
54 9.1e+03 0.75 0.0073 -4.3 -
55 9.1e+03 0.75 0.0036 -2.2 -
56 9.1e+03 0.75 0.0018 -0.13 -
57 9.1e+03 0.39 0.018 0.97 ++
58 9e+03 0.51 0.18 0.99 ++
59 8.7e+03 0.88 1.8 0.95 ++
60 8.7e+03 0.88 0.91 -8.2 -
61 8.5e+03 0.42 0.91 0.41 +
62 8.5e+03 0.42 0.45 -1.2 -
63 8.3e+03 1.6 0.45 0.62 +
64 8.3e+03 1.6 0.23 -0.31 -
65 8.2e+03 2.1 2.3 0.97 ++
66 8.2e+03 2.1 1.1 -2.6e+02 -
67 8.2e+03 2.1 0.57 -60 -
68 8.2e+03 2.1 0.28 -11 -
69 8.2e+03 2.1 0.14 -3 -
70 8.2e+03 2.1 0.071 -1.4 -
71 8.2e+03 2.1 0.036 -1.4 -
72 8.2e+03 2.1 0.018 -1.4 -
73 8.2e+03 2.1 0.0089 -1.4 -
74 8.2e+03 2.1 0.0044 -1.6 -
75 8.2e+03 2.1 0.0022 -2 -
76 8.2e+03 2.1 0.0011 -2.4 -
77 8.2e+03 2.1 0.00056 -2.6 -
78 8.2e+03 2.1 0.00028 -1.5 -
79 8.2e+03 2.1 0.00014 -0.084 -
80 8.2e+03 0.34 0.00014 0.83 +
81 8.2e+03 0.034 0.0014 0.99 ++
82 8.2e+03 0.076 0.014 1 ++
83 8.2e+03 0.0061 0.14 1 ++
84 8.2e+03 2.2 0.14 0.75 +
85 8.2e+03 6.3 0.14 0.67 +
86 8.2e+03 6.3 0.069 -0.71 -
87 8.2e+03 6.3 0.035 -0.56 -
88 8.2e+03 6.3 0.017 -0.57 -
89 8.2e+03 6.3 0.0087 -0.66 -
90 8.2e+03 6.3 0.0043 -0.73 -
91 8.2e+03 6.3 0.0022 -0.75 -
92 8.2e+03 6.3 0.0011 -0.77 -
93 8.2e+03 6.3 0.00054 -0.78 -
94 8.2e+03 6.3 0.00027 -0.8 -
95 8.2e+03 6.3 0.00014 0.025 -
96 8.2e+03 1.5 0.00014 0.6 +
97 8.2e+03 0.39 0.00014 0.84 +
98 8.2e+03 0.0087 0.0014 1 ++
99 8.2e+03 0.011 0.014 1 ++
100 8.2e+03 0.0063 0.14 1 ++
101 8.2e+03 0.16 1.4 1 ++
102 8.2e+03 0.16 0.46 -5.9 -
103 8.2e+03 6.3 0.46 0.4 +
104 8.1e+03 2.1 4.6 1 ++
105 8.1e+03 0.89 4.6 0.9 +
106 8.1e+03 3.5 46 1 ++
107 8.1e+03 0.28 4.6e+02 1 ++
108 8.1e+03 0.0059 4.6e+03 1 ++
109 8.1e+03 2.4e-05 4.6e+04 1 ++
110 8.1e+03 0.00081 4.6e+05 1 ++
111 8.1e+03 4.1e-08 4.6e+05 1 ++
Considering neighbor 4/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000085
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost mu_public b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 -1 -0.4 -0.023 -0.75 -0.42 1.2 -0.36 1.8 -0.42 -0.22 -0.35 -0.3 -0.017 -0.45 -0.3 1e+04 0.17 1 0.22 +
1 -0.36 0.6 0.0044 -0.42 -0.33 1.1 -0.83 1.7 -0.78 -0.46 -0.2 -0.18 -0.046 -0.3 -0.3 9.3e+03 0.21 1 0.32 +
2 -0.6 0.31 0.11 -0.69 -0.27 1.3 -0.66 2.7 -0.58 -0.4 -0.38 -0.23 -0.083 -0.61 -0.62 9.1e+03 0.15 1 0.18 +
3 -0.6 0.31 0.11 -0.69 -0.27 1.3 -0.66 2.7 -0.58 -0.4 -0.38 -0.23 -0.083 -0.61 -0.62 9.1e+03 0.15 0.5 -6.9 -
4 -0.6 0.31 0.11 -0.69 -0.27 1.3 -0.66 2.7 -0.58 -0.4 -0.38 -0.23 -0.083 -0.61 -0.62 9.1e+03 0.15 0.25 0.048 -
5 -0.36 0.36 0.17 -0.44 -0.26 1.2 -0.68 2.7 -0.66 -0.4 -0.23 -0.14 -0.096 -0.38 -0.49 8.7e+03 0.091 0.25 0.68 +
6 -0.42 0.36 0.32 -0.54 -0.35 0.99 -0.65 2.5 -0.66 -0.39 -0.28 -0.14 -0.19 -0.34 -0.55 8.6e+03 0.031 2.5 1.2 ++
7 -0.42 0.36 0.32 -0.54 -0.35 0.99 -0.65 2.5 -0.66 -0.39 -0.28 -0.14 -0.19 -0.34 -0.55 8.6e+03 0.031 0.74 -0.54 -
8 -0.35 0.29 0.37 -0.88 -0.49 0.68 -0.85 1.7 -0.93 -0.4 -0.26 -0.17 -0.29 -0.41 -0.59 8.5e+03 0.035 7.4 1 ++
9 -0.47 0.48 0.47 -1.3 -0.63 0.58 -0.84 1.3 -1.3 -0.39 -0.013 -0.15 -0.61 -0.67 -0.75 8.4e+03 0.02 74 1.3 ++
10 -0.75 0.71 0.49 -1.7 -0.85 0.41 -0.88 1 -1.4 -0.43 0.075 -0.1 -0.62 -0.83 -0.85 8.4e+03 0.019 7.4e+02 1.3 ++
11 -0.83 0.69 0.49 -1.8 -0.9 0.45 -0.85 1 -1.4 -0.42 0.064 -0.13 -0.62 -0.83 -0.86 8.3e+03 0.006 7.4e+03 1 ++
12 -0.81 0.85 0.72 -2.1 -1 0.24 -0.88 1 -1.6 -0.35 0.15 -0.12 -0.62 -0.97 -0.9 8.3e+03 0.0016 7.4e+04 1 ++
13 -0.83 0.86 0.73 -2.1 -1 0.25 -0.88 1 -1.5 -0.36 0.15 -0.12 -0.62 -0.96 -0.9 8.3e+03 9.8e-06 7.4e+05 1 ++
14 -0.83 0.86 0.73 -2.1 -1 0.25 -0.88 1 -1.5 -0.36 0.15 -0.12 -0.62 -0.96 -0.9 8.3e+03 2e-08 7.4e+05 1 ++
Considering neighbor 5/20 for current solution
Attempt 66/100
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000086
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -2.1 -
1 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.13 -
2 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 2.5 1 ++
3 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 1.2 -5.7 -
4 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 0.62 -4.2 -
5 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 0.31 -1.5 -
6 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 0.16 -0.15 -
7 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.16 0.23 +
8 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.078 -0.79 -
9 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.039 -0.7 -
10 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.02 -0.65 -
11 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.0098 -0.52 -
12 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.0049 -0.087 -
13 -0.36 0.02 -0.41 -0.084 0.12 0.0011 -0.36 0.23 0.033 -0.052 0.013 9.2e+03 5.2 0.0049 0.34 +
14 -0.36 0.02 -0.41 -0.084 0.12 0.0011 -0.36 0.23 0.033 -0.052 0.013 9.2e+03 5.2 0.0024 -0.51 -
15 -0.36 0.022 -0.41 -0.081 0.12 -0.0013 -0.36 0.23 0.036 -0.054 0.016 9.1e+03 4.5 0.0024 0.63 +
16 -0.36 0.023 -0.42 -0.082 0.12 -0.00086 -0.36 0.23 0.036 -0.055 0.016 9.1e+03 2.7 0.024 1.3 ++
17 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.024 0.66 +
18 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.012 -2.7 -
19 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.0061 -2.1 -
20 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.0031 -1.7 -
21 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.0015 -1.1 -
22 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.00076 -0.49 -
23 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.00038 0.068 -
24 -0.37 0.03 -0.44 -0.086 0.14 -0.0009 -0.37 0.21 0.042 -0.063 0.022 9.1e+03 2.6 0.00038 0.62 +
25 -0.37 0.03 -0.44 -0.086 0.14 -0.0009 -0.37 0.21 0.042 -0.063 0.022 9.1e+03 2.6 0.00019 -0.88 -
26 -0.37 0.03 -0.44 -0.086 0.14 -0.0009 -0.37 0.21 0.042 -0.063 0.022 9.1e+03 2.6 9.5e-05 -0.57 -
27 -0.37 0.031 -0.44 -0.086 0.14 -0.00081 -0.37 0.21 0.042 -0.063 0.022 9.1e+03 1.2 9.5e-05 0.64 +
28 -0.37 0.031 -0.44 -0.086 0.14 -0.00083 -0.37 0.21 0.042 -0.063 0.022 9e+03 0.059 0.00095 1 ++
29 -0.37 0.031 -0.44 -0.086 0.14 -0.00083 -0.38 0.2 0.042 -0.064 0.022 9e+03 0.33 0.0095 1 ++
30 -0.38 0.034 -0.45 -0.087 0.14 -0.00085 -0.38 0.19 0.044 -0.067 0.024 9e+03 0.058 0.095 1 ++
31 -0.42 0.065 -0.53 -0.098 0.19 -0.0011 -0.43 0.099 0.057 -0.098 0.038 8.9e+03 0.2 0.95 0.99 ++
32 -0.68 1 -1 -0.23 -0.14 0.00034 -1.2 -0.67 -0.36 -0.61 -0.29 8.5e+03 13 0.95 0.65 +
33 -0.68 1 -1 -0.23 -0.14 0.00034 -1.2 -0.67 -0.36 -0.61 -0.29 8.5e+03 13 0.48 -0.16 -
34 -0.73 1 -1.5 -0.34 -0.025 -0.00013 -1.2 -0.63 -0.4 -0.63 -0.36 8.3e+03 14 0.48 0.46 +
35 -0.73 1 -1.5 -0.34 -0.025 -0.00013 -1.2 -0.63 -0.4 -0.63 -0.36 8.3e+03 14 0.24 -0.39 -
36 -0.7 1.1 -1.7 -0.41 -0.12 0.00022 -1.2 -0.8 -0.3 -0.67 -0.3 8.2e+03 37 0.24 0.44 +
37 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.24 0.62 +
38 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.12 -4.1 -
39 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.06 -4.1 -
40 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.03 -3.8 -
41 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.015 -3.7 -
42 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.0075 -3.6 -
43 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.0037 -3.7 -
44 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.0019 -3.7 -
45 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.00093 -3.7 -
46 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.00047 -2.6 -
47 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.00023 -1.6 -
48 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.00012 -0.72 -
49 -0.56 1.2 -2 -0.56 -0.093 9e-05 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 32 0.00012 0.19 +
50 -0.56 1.2 -2 -0.56 -0.093 9e-05 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 32 5.8e-05 -0.26 -
51 -0.56 1.2 -2 -0.56 -0.093 0.00015 -1.2 -0.81 -0.3 -0.73 -0.35 8.2e+03 17 5.8e-05 0.6 +
52 -0.56 1.2 -2 -0.56 -0.093 0.00013 -1.2 -0.81 -0.3 -0.73 -0.35 8.2e+03 12 5.8e-05 0.42 +
53 -0.56 1.2 -2 -0.56 -0.093 0.00014 -1.2 -0.81 -0.3 -0.73 -0.35 8.2e+03 2.5 5.8e-05 0.85 +
54 -0.56 1.2 -2 -0.56 -0.093 0.00014 -1.2 -0.81 -0.3 -0.73 -0.35 8.2e+03 0.033 0.00058 1 ++
55 -0.56 1.2 -2 -0.56 -0.094 0.00014 -1.2 -0.81 -0.3 -0.73 -0.35 8.2e+03 0.041 0.0058 1 ++
56 -0.56 1.2 -2 -0.56 -0.099 0.00016 -1.2 -0.8 -0.3 -0.73 -0.35 8.2e+03 0.64 0.058 0.97 ++
57 -0.6 1.2 -2 -0.62 -0.1 0.00018 -1.2 -0.78 -0.26 -0.75 -0.34 8.1e+03 0.26 0.58 1 ++
58 -0.57 1.3 -2.1 -1.1 -0.11 0.00021 -1.1 -0.76 -0.18 -1.1 -0.35 8.1e+03 1 5.8 1 ++
59 -0.56 1.3 -2.1 -1.1 -0.11 0.00021 -1.1 -0.76 -0.18 -1.1 -0.36 8.1e+03 0.022 58 1 ++
60 -0.56 1.3 -2.1 -1.1 -0.11 0.00021 -1.1 -0.76 -0.18 -1.1 -0.36 8.1e+03 3.8e-05 5.8e+02 1 ++
61 -0.56 1.3 -2.1 -1.1 -0.11 0.00021 -1.1 -0.76 -0.18 -1.1 -0.36 8.1e+03 1.4e-06 5.8e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 67/100
Biogeme parameters read from biogeme.toml.
Model with 7 unknown parameters [max: 50]
*** Estimate b07everything_000087
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time lambda_travel_t b_cost_train b_cost_swissmet asc_car b_cost_car Function Relgrad Radius Rho
0 -0.53 -1 1.4 -0.36 -0.34 -0.11 -0.2 8.8e+03 0.05 10 0.95 ++
1 0.3 -2.2 -0.018 -1.4 -0.79 -0.19 -0.18 8.6e+03 0.027 10 0.66 +
2 0.34 -1.8 0.2 -2 -0.78 -0.081 -0.51 8.4e+03 0.0086 1e+02 1.1 ++
3 0.29 -1.7 0.37 -2 -0.81 -0.16 -0.49 8.4e+03 0.0016 1e+03 1.1 ++
4 0.27 -1.7 0.39 -2.1 -0.81 -0.17 -0.49 8.4e+03 2.9e-05 1e+04 1 ++
5 0.27 -1.7 0.39 -2.1 -0.81 -0.17 -0.49 8.4e+03 2.4e-08 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 68/100
Biogeme parameters read from biogeme.toml.
Model with 18 unknown parameters [max: 50]
*** Estimate b07everything_000088
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.37 -
1 1e+04 0.24 0.5 0.32 +
2 9e+03 0.15 0.5 0.62 +
3 8.3e+03 0.036 5 0.91 ++
4 8.3e+03 0.036 2.5 -70 -
5 8.3e+03 0.036 1.2 -22 -
6 8.3e+03 0.036 0.62 -3.3 -
7 8.3e+03 0.031 0.62 0.39 +
8 8.2e+03 0.0066 6.2 1 ++
9 8.2e+03 0.0066 0.84 -5.8 -
10 8.2e+03 0.038 0.84 0.29 +
11 8.2e+03 0.0071 8.4 1.1 ++
12 8.2e+03 0.0071 0.37 -2.1 -
13 8.2e+03 0.013 0.37 0.84 +
14 8.2e+03 0.0043 3.7 1.2 ++
15 8.2e+03 0.009 3.7 0.81 +
16 8.2e+03 0.00055 37 1 ++
17 8.2e+03 1.2e-05 3.7e+02 1 ++
18 8.2e+03 1.6e-09 3.7e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 69/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000089
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train b_cost b_time_swissmet asc_car_ref asc_car_diff_GA b_time_car Function Relgrad Radius Rho
0 -0.9 0.86 -0.86 -0.64 -1 -0.35 -0.45 -0.83 8.5e+03 0.081 10 1.1 ++
1 -1.1 1.4 -1.3 -0.72 -1.4 -0.47 -0.89 -1 8.3e+03 0.022 1e+02 1.1 ++
2 -1 1.5 -1.4 -0.73 -1.5 -0.49 -1.1 -1 8.3e+03 0.002 1e+03 1.1 ++
3 -1 1.5 -1.4 -0.73 -1.5 -0.49 -1.1 -1 8.3e+03 1.9e-05 1e+04 1 ++
4 -1 1.5 -1.4 -0.73 -1.5 -0.49 -1.1 -1 8.3e+03 1.7e-09 1e+04 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000090
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train square_tt_coef cube_tt_coef b_cost mu_public b_time_swissmet asc_car_ref asc_car_diff_GA b_time_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.4 0.5 -0.16 -
1 -0.27 -8.7e-05 -0.5 0.0013 0.012 -0.039 1 0.2 0.0074 -0.022 -0.021 9.5e+03 0.71 0.5 0.81 +
2 -0.27 -8.7e-05 -0.5 0.0013 0.012 -0.039 1 0.2 0.0074 -0.022 -0.021 9.5e+03 0.71 0.25 0.81 -
3 -0.27 -8.7e-05 -0.5 0.0013 0.012 -0.039 1 0.2 0.0074 -0.022 -0.021 9.5e+03 0.71 0.12 0.81 -
4 -0.27 -8.7e-05 -0.5 0.0013 0.012 -0.039 1 0.2 0.0074 -0.022 -0.021 9.5e+03 0.71 0.062 -12 -
5 -0.27 -8.7e-05 -0.5 0.0013 0.012 -0.039 1 0.2 0.0074 -0.022 -0.021 9.5e+03 0.71 0.031 -16 -
6 -0.27 -8.7e-05 -0.5 0.0013 0.012 -0.039 1 0.2 0.0074 -0.022 -0.021 9.5e+03 0.71 0.016 -3.8 -
7 -0.29 0.016 -0.52 0.017 -0.0035 -0.054 1 0.19 -0.0082 -0.038 -0.036 9.5e+03 6.4 0.016 0.11 +
8 -0.29 0.017 -0.52 0.017 0.0074 -0.058 1 0.19 -0.011 -0.039 -0.052 9.4e+03 0.89 0.016 0.17 +
9 -0.29 0.017 -0.52 0.017 0.0074 -0.058 1 0.19 -0.011 -0.039 -0.052 9.4e+03 0.89 0.0078 -2.1 -
10 -0.3 0.025 -0.53 0.024 -0.00039 -0.066 1 0.18 -0.019 -0.047 -0.06 9.3e+03 0.075 0.078 0.93 ++
11 -0.31 0.057 -0.56 0.056 -0.00073 -0.13 1 0.17 -0.053 -0.068 -0.14 9.2e+03 0.74 0.78 0.98 ++
12 -0.38 0.49 -0.82 0.18 0.00093 -0.91 1.1 -0.47 -0.15 -0.32 -0.55 8.7e+03 6 0.78 0.65 +
13 -0.38 0.49 -0.82 0.18 0.00093 -0.91 1.1 -0.47 -0.15 -0.32 -0.55 8.7e+03 6 0.39 0.65 -
14 -0.38 0.49 -0.82 0.18 0.00093 -0.91 1.1 -0.47 -0.15 -0.32 -0.55 8.7e+03 6 0.2 0.65 -
15 -0.38 0.49 -0.82 0.18 0.00093 -0.91 1.1 -0.47 -0.15 -0.32 -0.55 8.7e+03 6 0.098 0.65 -
16 -0.38 0.49 -0.82 0.18 0.00093 -0.91 1.1 -0.47 -0.15 -0.32 -0.55 8.7e+03 6 0.049 0.65 -
17 -0.38 0.49 -0.82 0.18 0.00093 -0.91 1.1 -0.47 -0.15 -0.32 -0.55 8.7e+03 6 0.024 -3.7 -
18 -0.38 0.49 -0.82 0.18 0.00093 -0.91 1.1 -0.47 -0.15 -0.32 -0.55 8.7e+03 6 0.012 -2.7 -
19 -0.38 0.49 -0.82 0.18 0.00093 -0.91 1.1 -0.47 -0.15 -0.32 -0.55 8.7e+03 6 0.0061 -1.9 -
20 -0.38 0.49 -0.82 0.18 0.00093 -0.91 1.1 -0.47 -0.15 -0.32 -0.55 8.7e+03 6 0.0031 -0.91 -
21 -0.38 0.49 -0.82 0.17 -0.0021 -0.9 1.1 -0.47 -0.15 -0.32 -0.55 8.6e+03 7.3 0.0031 0.36 +
22 -0.38 0.49 -0.82 0.17 -0.0021 -0.9 1.1 -0.47 -0.15 -0.32 -0.55 8.6e+03 7.3 0.0015 -0.45 -
23 -0.38 0.49 -0.82 0.18 -0.00059 -0.9 1.1 -0.47 -0.15 -0.32 -0.55 8.6e+03 5.9 0.0015 0.35 +
24 -0.38 0.49 -0.82 0.18 -0.00059 -0.9 1.1 -0.47 -0.15 -0.32 -0.55 8.6e+03 5.9 0.00076 -0.28 -
25 -0.38 0.49 -0.82 0.17 -0.0014 -0.9 1.1 -0.47 -0.15 -0.32 -0.55 8.5e+03 2.9 0.00076 0.26 +
26 -0.38 0.49 -0.82 0.17 -0.0014 -0.9 1.1 -0.47 -0.15 -0.32 -0.55 8.5e+03 2.9 0.00038 -0.51 -
27 -0.38 0.49 -0.82 0.18 -0.00097 -0.9 1.1 -0.47 -0.15 -0.32 -0.54 8.5e+03 1 0.00038 0.88 +
28 -0.38 0.49 -0.82 0.18 -0.00099 -0.9 1.1 -0.48 -0.15 -0.32 -0.54 8.5e+03 0.045 0.0038 1 ++
29 -0.38 0.49 -0.82 0.17 -0.00099 -0.9 1.1 -0.48 -0.16 -0.33 -0.54 8.5e+03 0.028 0.038 1 ++
30 -0.39 0.53 -0.82 0.17 -0.00098 -0.88 1.1 -0.52 -0.16 -0.34 -0.54 8.5e+03 0.034 0.38 1 ++
31 -0.49 0.91 -0.87 0.2 -0.0011 -0.62 1.2 -0.83 -0.32 -0.46 -0.64 8.4e+03 0.12 3.8 0.92 ++
32 -0.49 0.91 -0.87 0.2 -0.0011 -0.62 1.2 -0.83 -0.32 -0.46 -0.64 8.4e+03 0.12 1.9 0.92 -
33 -0.49 0.91 -0.87 0.2 -0.0011 -0.62 1.2 -0.83 -0.32 -0.46 -0.64 8.4e+03 0.12 0.95 -82 -
34 -0.49 0.91 -0.87 0.2 -0.0011 -0.62 1.2 -0.83 -0.32 -0.46 -0.64 8.4e+03 0.12 0.48 -21 -
35 -0.49 0.91 -0.87 0.2 -0.0011 -0.62 1.2 -0.83 -0.32 -0.46 -0.64 8.4e+03 0.12 0.24 -3.1 -
36 -0.65 1 -0.96 -0.036 -0.00012 -0.71 1.3 -0.85 -0.39 -0.55 -0.72 8.4e+03 1 0.24 0.52 +
37 -0.67 1.1 -1 0.028 -0.00041 -0.71 1.4 -1.1 -0.42 -0.62 -0.83 8.3e+03 2.7 2.4 0.96 ++
38 -0.67 1.1 -1 0.028 -0.00041 -0.71 1.4 -1.1 -0.42 -0.62 -0.83 8.3e+03 2.7 1.2 -96 -
39 -0.67 1.1 -1 0.028 -0.00041 -0.71 1.4 -1.1 -0.42 -0.62 -0.83 8.3e+03 2.7 0.6 -17 -
40 -0.67 1.1 -1 0.028 -0.00041 -0.71 1.4 -1.1 -0.42 -0.62 -0.83 8.3e+03 2.7 0.3 -0.55 -
41 -0.84 1.1 -1.2 -0.083 0.00014 -0.73 1.4 -1.4 -0.52 -0.79 -1.1 8.3e+03 8.8 0.3 0.62 +
42 -0.71 1.3 -1.5 -0.051 -0.00024 -0.71 1.3 -1.6 -0.48 -0.91 -1.2 8.2e+03 15 0.3 0.35 +
43 -0.71 1.3 -1.5 -0.051 -0.00024 -0.71 1.3 -1.6 -0.48 -0.91 -1.2 8.2e+03 15 0.15 -1 -
44 -0.71 1.3 -1.5 -0.051 -0.00024 -0.71 1.3 -1.6 -0.48 -0.91 -1.2 8.2e+03 15 0.075 -0.83 -
45 -0.71 1.3 -1.5 -0.051 -0.00024 -0.71 1.3 -1.6 -0.48 -0.91 -1.2 8.2e+03 15 0.037 -0.44 -
46 -0.71 1.3 -1.5 -0.051 -0.00024 -0.71 1.3 -1.6 -0.48 -0.91 -1.2 8.2e+03 15 0.019 -0.25 -
47 -0.71 1.3 -1.5 -0.051 -0.00024 -0.71 1.3 -1.6 -0.48 -0.91 -1.2 8.2e+03 15 0.0093 -0.05 -
48 -0.71 1.3 -1.5 -0.06 0.00013 -0.71 1.3 -1.6 -0.47 -0.91 -1.2 8.2e+03 14 0.0093 0.12 +
49 -0.71 1.3 -1.5 -0.06 0.00013 -0.71 1.3 -1.6 -0.47 -0.91 -1.2 8.2e+03 14 0.0047 -4.1 -
50 -0.71 1.3 -1.5 -0.06 0.00013 -0.71 1.3 -1.6 -0.47 -0.91 -1.2 8.2e+03 14 0.0023 -4.3 -
51 -0.71 1.3 -1.5 -0.06 0.00013 -0.71 1.3 -1.6 -0.47 -0.91 -1.2 8.2e+03 14 0.0012 -2.5 -
52 -0.71 1.3 -1.5 -0.06 0.00013 -0.71 1.3 -1.6 -0.47 -0.91 -1.2 8.2e+03 14 0.00058 -1.6 -
53 -0.71 1.3 -1.5 -0.06 0.00013 -0.71 1.3 -1.6 -0.47 -0.91 -1.2 8.2e+03 14 0.00029 -0.77 -
54 -0.71 1.3 -1.5 -0.06 0.00013 -0.71 1.3 -1.6 -0.47 -0.91 -1.2 8.2e+03 14 0.00015 0.056 -
55 -0.71 1.3 -1.5 -0.06 -1.2e-05 -0.71 1.3 -1.6 -0.47 -0.91 -1.2 8.2e+03 2 0.00015 0.8 +
56 -0.71 1.3 -1.5 -0.06 -5.2e-06 -0.71 1.3 -1.6 -0.47 -0.91 -1.2 8.2e+03 0.21 0.0015 0.96 ++
57 -0.71 1.3 -1.5 -0.061 -1.9e-06 -0.71 1.3 -1.6 -0.47 -0.91 -1.2 8.2e+03 0.022 0.015 1 ++
58 -0.72 1.3 -1.5 -0.069 3.2e-05 -0.71 1.3 -1.6 -0.47 -0.91 -1.2 8.2e+03 0.07 0.15 1 ++
59 -0.76 1.2 -1.7 -0.081 8.4e-05 -0.74 1.2 -1.7 -0.47 -0.95 -1.3 8.2e+03 0.35 1.5 1.1 ++
60 -0.73 1.5 -2.2 -0.099 0.00016 -0.74 1 -2.1 -0.43 -1.1 -1.6 8.2e+03 1.5 15 1.1 ++
61 -0.76 1.5 -2.2 -0.098 0.00016 -0.73 1 -2.1 -0.43 -1.1 -1.6 8.2e+03 0.45 1.5e+02 1 ++
62 -0.65 1.6 -2.5 -0.11 0.00022 -0.74 1 -2.4 -0.43 -1.1 -1.8 8.2e+03 1.4 1.5e+03 0.96 ++
63 -0.61 1.5 -2.5 -0.11 0.00021 -0.74 1 -2.4 -0.43 -1 -1.8 8.2e+03 0.04 1.5e+04 1 ++
64 -0.6 1.5 -2.5 -0.11 0.00021 -0.74 1 -2.4 -0.43 -1 -1.8 8.2e+03 0.00094 1.5e+05 1 ++
65 -0.6 1.5 -2.5 -0.11 0.00021 -0.74 1 -2.4 -0.43 -1 -1.8 8.2e+03 0.0018 1.5e+06 1 ++
66 -0.6 1.5 -2.5 -0.11 0.00021 -0.74 1 -2.4 -0.43 -1 -1.8 8.2e+03 2.7e-06 1.5e+06 1 ++
Considering neighbor 1/20 for current solution
Attempt 70/100
Considering neighbor 0/20 for current solution
Attempt 71/100
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000091
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train square_tt_coef cube_tt_coef b_cost_train mu_public b_time_swissmet b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.45 -
1 -0.27 -0.14 -0.0056 -0.5 0.0061 0.059 -0.28 1 0.2 0.24 0.0066 -0.0068 -0.0018 -0.022 -0.0073 1e+04 1.2 0.5 0.23 +
2 -0.27 -0.14 -0.0056 -0.5 0.0061 0.059 -0.28 1 0.2 0.24 0.0066 -0.0068 -0.0018 -0.022 -0.0073 1e+04 1.2 0.25 0.23 -
3 -0.27 -0.14 -0.0056 -0.5 0.0061 0.059 -0.28 1 0.2 0.24 0.0066 -0.0068 -0.0018 -0.022 -0.0073 1e+04 1.2 0.12 0.23 -
4 -0.27 -0.14 -0.0056 -0.5 0.0061 0.059 -0.28 1 0.2 0.24 0.0066 -0.0068 -0.0018 -0.022 -0.0073 1e+04 1.2 0.062 -4.1 -
5 -0.27 -0.14 -0.0054 -0.49 -0.0045 -0.0032 -0.27 1 0.17 0.23 0.0065 -0.0079 -0.002 0.026 -0.0076 9.5e+03 5.1 0.062 0.86 +
6 -0.25 -0.1 -0.004 -0.52 -0.055 0.0035 -0.28 1 0.15 0.17 -0.019 -0.033 -0.0042 -0.006 -0.039 9.4e+03 0.4 0.062 0.59 +
7 -0.25 -0.1 -0.004 -0.52 -0.055 0.0035 -0.28 1 0.15 0.17 -0.019 -0.033 -0.0042 -0.006 -0.039 9.4e+03 0.4 0.031 -14 -
8 -0.25 -0.1 -0.004 -0.52 -0.055 0.0035 -0.28 1 0.15 0.17 -0.019 -0.033 -0.0042 -0.006 -0.039 9.4e+03 0.4 0.016 -11 -
9 -0.25 -0.1 -0.004 -0.52 -0.055 0.0035 -0.28 1 0.15 0.17 -0.019 -0.033 -0.0042 -0.006 -0.039 9.4e+03 0.4 0.0078 -11 -
10 -0.25 -0.1 -0.004 -0.52 -0.055 0.0035 -0.28 1 0.15 0.17 -0.019 -0.033 -0.0042 -0.006 -0.039 9.4e+03 0.4 0.0039 -5.2 -
11 -0.24 -0.097 -9.3e-05 -0.52 -0.059 -0.00044 -0.28 1 0.14 0.16 -0.023 -0.037 -0.0081 -0.0099 -0.043 9.4e+03 0.6 0.0039 0.82 +
12 -0.24 -0.097 -9.2e-05 -0.52 -0.059 -0.00024 -0.28 1 0.14 0.16 -0.023 -0.037 -0.0081 -0.0099 -0.043 9.4e+03 0.18 0.039 1.2 ++
13 -0.24 -0.078 0.00068 -0.53 -0.053 -2.5e-06 -0.3 1 0.12 0.13 -0.034 -0.05 -0.0097 -0.038 -0.059 9.3e+03 0.075 0.39 1 ++
14 -0.25 0.099 0.0085 -0.66 0.099 -0.00014 -0.51 1.1 -0.12 -0.26 -0.12 -0.17 -0.027 -0.31 -0.21 8.9e+03 2.5 0.39 0.89 +
15 -0.25 0.099 0.0085 -0.66 0.099 -0.00014 -0.51 1.1 -0.12 -0.26 -0.12 -0.17 -0.027 -0.31 -0.21 8.9e+03 2.5 0.2 -7.1 -
16 -0.25 0.099 0.0085 -0.66 0.099 -0.00014 -0.51 1.1 -0.12 -0.26 -0.12 -0.17 -0.027 -0.31 -0.21 8.9e+03 2.5 0.098 -7.2 -
17 -0.25 0.099 0.0085 -0.66 0.099 -0.00014 -0.51 1.1 -0.12 -0.26 -0.12 -0.17 -0.027 -0.31 -0.21 8.9e+03 2.5 0.049 -7.6 -
18 -0.25 0.099 0.0085 -0.66 0.099 -0.00014 -0.51 1.1 -0.12 -0.26 -0.12 -0.17 -0.027 -0.31 -0.21 8.9e+03 2.5 0.024 -8.1 -
19 -0.25 0.099 0.0085 -0.66 0.099 -0.00014 -0.51 1.1 -0.12 -0.26 -0.12 -0.17 -0.027 -0.31 -0.21 8.9e+03 2.5 0.012 -9.1 -
20 -0.25 0.099 0.0085 -0.66 0.099 -0.00014 -0.51 1.1 -0.12 -0.26 -0.12 -0.17 -0.027 -0.31 -0.21 8.9e+03 2.5 0.0061 -4.9 -
21 -0.25 0.099 0.0085 -0.66 0.099 -0.00014 -0.51 1.1 -0.12 -0.26 -0.12 -0.17 -0.027 -0.31 -0.21 8.9e+03 2.5 0.0031 -3.3 -
22 -0.25 0.099 0.0085 -0.66 0.099 -0.00014 -0.51 1.1 -0.12 -0.26 -0.12 -0.17 -0.027 -0.31 -0.21 8.9e+03 2.5 0.0015 -1.7 -
23 -0.25 0.099 0.0085 -0.66 0.099 -0.00014 -0.51 1.1 -0.12 -0.26 -0.12 -0.17 -0.027 -0.31 -0.21 8.9e+03 2.5 0.00076 -0.44 -
24 -0.25 0.1 0.0093 -0.66 0.1 -0.0009 -0.51 1.1 -0.12 -0.27 -0.12 -0.17 -0.028 -0.31 -0.21 8.9e+03 2.6 0.00076 0.47 +
25 -0.25 0.1 0.0093 -0.66 0.1 -0.0009 -0.51 1.1 -0.12 -0.27 -0.12 -0.17 -0.028 -0.31 -0.21 8.9e+03 2.6 0.00038 -0.59 -
26 -0.25 0.1 0.0096 -0.66 0.1 -0.00052 -0.51 1.1 -0.12 -0.27 -0.12 -0.17 -0.028 -0.31 -0.21 8.9e+03 2.3 0.00038 0.21 +
27 -0.25 0.1 0.0096 -0.66 0.1 -0.00052 -0.51 1.1 -0.12 -0.27 -0.12 -0.17 -0.028 -0.31 -0.21 8.9e+03 2.3 0.00019 -0.06 -
28 -0.25 0.1 0.0098 -0.66 0.1 -0.00071 -0.51 1.1 -0.12 -0.27 -0.12 -0.17 -0.028 -0.31 -0.21 8.9e+03 0.42 0.00019 0.7 +
29 -0.25 0.1 0.0098 -0.66 0.1 -0.00069 -0.51 1.1 -0.12 -0.27 -0.12 -0.17 -0.028 -0.31 -0.21 8.9e+03 0.047 0.0019 1 ++
30 -0.25 0.1 0.0099 -0.66 0.1 -0.0007 -0.51 1.1 -0.13 -0.27 -0.12 -0.17 -0.028 -0.31 -0.21 8.8e+03 0.25 0.019 1 ++
31 -0.25 0.11 0.01 -0.67 0.11 -0.00073 -0.52 1.1 -0.14 -0.28 -0.12 -0.17 -0.029 -0.31 -0.2 8.8e+03 0.041 0.19 1 ++
32 -0.26 0.17 0.016 -0.69 0.22 -0.0012 -0.63 1.1 -0.33 -0.34 -0.12 -0.16 -0.036 -0.36 -0.22 8.7e+03 0.22 1.9 0.95 ++
33 -0.26 0.17 0.016 -0.69 0.22 -0.0012 -0.63 1.1 -0.33 -0.34 -0.12 -0.16 -0.036 -0.36 -0.22 8.7e+03 0.22 0.95 -9.7 -
34 -0.57 0.48 0.086 -0.59 0.17 -0.00098 -1.6 1.3 -0.81 -0.73 -0.41 -0.24 -0.12 -0.7 -0.39 8.4e+03 1.9 9.5 0.98 ++
35 -0.57 0.48 0.086 -0.59 0.17 -0.00098 -1.6 1.3 -0.81 -0.73 -0.41 -0.24 -0.12 -0.7 -0.39 8.4e+03 1.9 4.8 0.98 -
36 -0.57 0.48 0.086 -0.59 0.17 -0.00098 -1.6 1.3 -0.81 -0.73 -0.41 -0.24 -0.12 -0.7 -0.39 8.4e+03 1.9 2.4 0.98 -
37 -0.57 0.48 0.086 -0.59 0.17 -0.00098 -1.6 1.3 -0.81 -0.73 -0.41 -0.24 -0.12 -0.7 -0.39 8.4e+03 1.9 1.2 -1.9e+02 -
38 -0.57 0.48 0.086 -0.59 0.17 -0.00098 -1.6 1.3 -0.81 -0.73 -0.41 -0.24 -0.12 -0.7 -0.39 8.4e+03 1.9 0.6 -55 -
39 -0.57 0.48 0.086 -0.59 0.17 -0.00098 -1.6 1.3 -0.81 -0.73 -0.41 -0.24 -0.12 -0.7 -0.39 8.4e+03 1.9 0.3 -4.8 -
40 -0.58 0.49 0.22 -0.89 -0.013 -0.00022 -1.5 1.4 -1.1 -0.93 -0.62 -0.053 -0.2 -0.92 -0.59 8.4e+03 1.7 0.3 0.7 +
41 -0.47 0.53 0.33 -1.2 -0.044 -8.2e-05 -1.5 1.6 -1.4 -0.82 -0.6 -0.15 -0.24 -1.1 -0.59 8.3e+03 0.89 3 1.1 ++
42 -0.47 0.53 0.33 -1.2 -0.044 -8.2e-05 -1.5 1.6 -1.4 -0.82 -0.6 -0.15 -0.24 -1.1 -0.59 8.3e+03 0.89 0.72 -11 -
43 -0.47 0.53 0.33 -1.2 -0.044 -8.2e-05 -1.5 1.6 -1.4 -0.82 -0.6 -0.15 -0.24 -1.1 -0.59 8.3e+03 0.89 0.36 -1.8 -
44 -0.35 0.44 0.44 -1.5 -0.099 0.00015 -1.5 1.4 -1.6 -0.84 -0.53 -0.013 -0.31 -1.4 -0.63 8.3e+03 6.7 0.36 0.74 +
45 -0.32 0.58 0.45 -1.9 -0.094 0.00014 -1.6 1.2 -1.9 -0.82 -0.51 -0.18 -0.37 -1.6 -0.6 8.3e+03 1.3 3.6 1.1 ++
46 -0.33 0.66 0.48 -2.1 -0.099 0.00016 -1.7 1 -2.1 -0.77 -0.47 -0.054 -0.41 -1.7 -0.62 8.3e+03 0.83 36 1 ++
47 -0.35 0.69 0.48 -2.2 -0.1 0.00017 -1.7 1 -2.1 -0.77 -0.47 -0.12 -0.42 -1.7 -0.61 8.3e+03 0.029 3.6e+02 1 ++
48 -0.25 0.77 0.63 -2.5 -0.11 0.00023 -1.7 1 -2.4 -0.79 -0.47 -0.13 -0.52 -1.9 -0.62 8.3e+03 2.3 3.6e+03 0.96 ++
49 -0.23 0.76 0.61 -2.6 -0.11 0.00022 -1.7 1 -2.4 -0.8 -0.46 -0.13 -0.55 -1.9 -0.63 8.3e+03 0.024 3.6e+04 1 ++
50 -0.24 0.76 0.61 -2.5 -0.11 0.00022 -1.7 1 -2.4 -0.8 -0.46 -0.13 -0.56 -1.9 -0.63 8.3e+03 0.00039 3.6e+05 1 ++
51 -0.24 0.76 0.61 -2.5 -0.11 0.00022 -1.7 1 -2.4 -0.8 -0.46 -0.13 -0.56 -1.9 -0.63 8.3e+03 1.2e-06 3.6e+05 1 ++
Considering neighbor 0/20 for current solution
Attempt 72/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000092
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train lambda_travel_t b_cost_train mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car b_cost_car b_time_swissmet b_cost_swissmet Function Relgrad Radius Rho
0 -0.72 -0.0095 -0.01 -0.68 1.4 -0.65 2 0.14 -0.14 -0.029 -0.45 -0.1 -0.65 -0.67 9.8e+03 0.24 1 0.49 +
1 -0.72 -0.0095 -0.01 -0.68 1.4 -0.65 2 0.14 -0.14 -0.029 -0.45 -0.1 -0.65 -0.67 9.8e+03 0.24 0.5 -2.9 -
2 -0.72 -0.0095 -0.01 -0.68 1.4 -0.65 2 0.14 -0.14 -0.029 -0.45 -0.1 -0.65 -0.67 9.8e+03 0.24 0.25 -0.031 -
3 -0.56 0.12 -0.005 -0.61 1.4 -0.58 1.9 -0.11 -0.34 -0.037 -0.64 -0.35 -0.66 -0.42 8.6e+03 0.048 0.25 0.86 +
4 -0.45 0.28 0.036 -0.8 1.1 -0.81 2.1 -0.17 -0.18 -0.09 -0.52 -0.38 -0.79 -0.44 8.4e+03 0.017 2.5 1.1 ++
5 0.071 0.38 0.21 -1.8 -0.2 -0.84 2.3 0.23 -0.047 -0.49 -1.2 -0.55 -1.8 -0.53 8.3e+03 0.061 2.5 0.26 +
6 0.07 0.45 0.2 -2.1 -0.036 -1 1.9 0.3 -0.064 -0.52 -1.3 -0.7 -1.5 -0.57 8.2e+03 0.0094 25 1 ++
7 -0.0089 0.47 0.22 -2 0.12 -1 1.8 0.24 -0.057 -0.48 -1.2 -0.69 -1.5 -0.58 8.2e+03 0.00072 2.5e+02 1 ++
8 -0.02 0.48 0.22 -2 0.13 -1.1 1.8 0.23 -0.057 -0.48 -1.2 -0.68 -1.5 -0.59 8.2e+03 2.2e-05 2.5e+03 1 ++
9 -0.02 0.48 0.22 -2 0.13 -1.1 1.8 0.23 -0.057 -0.48 -1.2 -0.68 -1.5 -0.59 8.2e+03 7.7e-08 2.5e+03 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000093
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train_re b_time_train_di b_cost mu_existing asc_car b_time_car_ref b_time_car_diff b_time_swissmet b_time_swissmet Function Relgrad Radius Rho
0 -0.5 -0.68 -0.17 -1 2 0.1 -0.23 -0.17 -0.42 -0.38 9.5e+03 0.3 1 0.6 +
1 -0.5 -0.68 -0.17 -1 2 0.1 -0.23 -0.17 -0.42 -0.38 9.5e+03 0.3 0.5 0.065 -
2 -0.3 -0.67 -0.34 -0.5 2.2 -0.24 -0.42 -0.46 -0.49 -0.24 8.5e+03 0.076 0.5 0.8 +
3 -0.2 -0.81 -0.53 -0.61 2.7 -0.54 -0.32 -0.6 -0.75 -0.65 8.4e+03 0.0079 5 0.97 ++
4 -0.2 -0.93 -0.63 -0.69 2.1 -0.54 -0.4 -0.69 -0.85 -0.77 8.3e+03 0.0078 5 0.86 +
5 -0.22 -0.92 -0.63 -0.68 2.2 -0.53 -0.4 -0.7 -0.84 -0.77 8.3e+03 0.00021 50 1 ++
6 -0.22 -0.92 -0.63 -0.68 2.2 -0.53 -0.4 -0.7 -0.84 -0.77 8.3e+03 4.6e-06 50 1 ++
Considering neighbor 1/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 18 unknown parameters [max: 50]
*** Estimate b07everything_000094
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 1.1e+04 0.4 0.5 -0.53 -
1 1.1e+04 0.4 0.25 0.018 -
2 9.7e+03 1.1 0.25 0.76 +
3 9.7e+03 1.1 0.12 -6.8 -
4 1.8e+04 5.4 1.2 6.9 ++
5 1.8e+04 5.4 0.62 -0.47 -
6 1.8e+04 5.4 0.31 -0.17 -
7 1.2e+04 2.1 3.1 3.3 ++
8 1.2e+04 2.1 1.6 3.3 -
9 1.2e+04 2.1 0.78 3.3 -
10 1.2e+04 2.1 0.39 3.3 -
11 1.2e+04 2.1 0.2 -1.6 -
12 1.2e+04 2.1 0.098 -0.88 -
13 1.1e+04 2.3 0.098 0.49 +
14 9.5e+03 0.19 0.98 1.2 ++
15 9.5e+03 0.19 0.49 1.2 -
16 9.5e+03 0.19 0.24 1.2 -
17 9.5e+03 0.19 0.12 -9.8 -
18 9.5e+03 0.19 0.061 -7.7 -
19 9.5e+03 0.19 0.031 -6.2 -
20 9.5e+03 0.19 0.015 -3.6 -
21 9.5e+03 1.7 0.015 0.53 +
22 9.4e+03 0.11 0.015 0.64 +
23 9.4e+03 0.11 0.0076 -6.3 -
24 9.4e+03 0.11 0.0038 -0.036 -
25 9.4e+03 0.11 0.038 0.97 ++
26 9.3e+03 0.096 0.38 1 ++
27 9.3e+03 0.096 0.19 -14 -
28 9.3e+03 0.096 0.095 -10 -
29 9.3e+03 0.096 0.048 -7.6 -
30 9.3e+03 0.096 0.024 -7.2 -
31 9.3e+03 0.096 0.012 -8.6 -
32 9.3e+03 0.096 0.006 -4 -
33 9.3e+03 0.096 0.003 -0.43 -
34 9.3e+03 0.11 0.03 0.93 ++
35 9.3e+03 0.092 0.3 1 ++
36 9.3e+03 0.092 0.15 -1.3 -
37 9.2e+03 6.1 0.15 0.15 +
38 9.2e+03 6.1 0.075 0.075 -
39 9.1e+03 2 0.075 0.25 +
40 9.1e+03 2 0.037 -8.8 -
41 9.1e+03 2 0.019 -4.3 -
42 9.1e+03 2 0.0093 -2 -
43 9e+03 5.9 0.0093 0.34 +
44 9e+03 1.9 0.0093 0.14 +
45 9e+03 1.9 0.0047 -1.4 -
46 8.9e+03 3.4 0.0047 0.5 +
47 8.9e+03 1.8 0.0047 0.75 +
48 8.9e+03 1.8 0.0023 -2.6 -
49 8.9e+03 1.8 0.0012 -1.1 -
50 8.9e+03 1.8 0.00058 -0.16 -
51 8.9e+03 1.3 0.00058 0.59 +
52 8.9e+03 0.69 0.00058 0.74 +
53 8.9e+03 0.1 0.0058 0.98 ++
54 8.9e+03 0.054 0.058 1 ++
55 8.8e+03 0.16 0.58 1 ++
56 8.5e+03 0.47 5.8 0.93 ++
57 8.5e+03 0.47 2.9 0.93 -
58 8.5e+03 0.47 1.5 -1.1e+02 -
59 8.5e+03 0.47 0.73 -22 -
60 8.5e+03 0.47 0.36 -1.4 -
61 8.4e+03 0.77 0.36 0.68 +
62 8.3e+03 0.52 3.6 1 ++
63 8.3e+03 0.52 0.49 -14 -
64 8.3e+03 0.52 0.24 -1.4 -
65 8.3e+03 0.99 0.24 0.81 +
66 8.3e+03 0.21 2.4 1.1 ++
67 8.3e+03 6.3 2.4 0.24 +
68 8.2e+03 0.024 24 1 ++
69 8.2e+03 1.5 2.4e+02 0.93 ++
70 8.2e+03 0.19 2.4e+03 1 ++
71 8.2e+03 0.00064 2.4e+04 1 ++
72 8.2e+03 4.3e-07 2.4e+04 1 ++
Considering neighbor 2/20 for current solution
Attempt 73/100
Considering neighbor 0/20 for current solution
Attempt 74/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000095
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost_train mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 -0.54 0.0033 -0.0082 -1 -0.087 1.4 -0.51 2 0.16 -0.084 -0.02 0.049 -0.63 9.4e+03 0.19 1 0.58 +
1 -0.54 0.0033 -0.0082 -1 -0.087 1.4 -0.51 2 0.16 -0.084 -0.02 0.049 -0.63 9.4e+03 0.19 0.5 -0.36 -
2 -0.24 0.36 0.019 -0.72 0.035 0.86 -0.65 2.3 -0.22 -0.29 -0.06 -0.23 -0.41 8.8e+03 0.15 0.5 0.46 +
3 -0.32 0.2 0.07 -1 0.008 0.68 -0.6 2.8 -0.18 0.081 -0.13 -0.29 -0.56 8.4e+03 0.038 0.5 0.75 +
4 -0.053 0.36 0.2 -1.4 -0.37 0.22 -0.87 2.3 -0.0089 0.0016 -0.37 -0.26 -0.49 8.3e+03 0.008 5 1 ++
5 -0.089 0.47 0.26 -1.5 -0.38 0.37 -1.2 1.4 0.006 -0.045 -0.5 -0.36 -0.62 8.3e+03 0.014 5 0.63 +
6 -0.14 0.53 0.29 -1.5 -0.35 0.36 -1.3 1.6 -0.046 -0.065 -0.51 -0.36 -0.65 8.2e+03 0.0012 50 1 ++
7 -0.14 0.52 0.28 -1.5 -0.34 0.36 -1.3 1.6 -0.05 -0.061 -0.5 -0.35 -0.64 8.2e+03 9.1e-05 5e+02 1 ++
8 -0.14 0.52 0.28 -1.5 -0.34 0.36 -1.3 1.6 -0.05 -0.061 -0.5 -0.35 -0.64 8.2e+03 3.5e-07 5e+02 1 ++
Considering neighbor 0/20 for current solution
Considering neighbor 1/20 for current solution
Attempt 75/100
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000096
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train lambda_travel_t b_cost_train b_time_swissmet b_cost_swissmet asc_car_ref asc_car_diff_GA b_time_car b_cost_car Function Relgrad Radius Rho
0 -1 0.29 -0.72 1.6 -0.54 -0.99 -0.58 -0.33 -0.45 -0.77 -0.59 8.8e+03 0.043 1 0.9 +
1 -0.7 1.3 -0.94 1.2 -1.1 -1 -0.68 -0.21 -0.73 -0.98 -0.46 8.4e+03 0.022 10 0.95 ++
2 -0.7 1.3 -0.94 1.2 -1.1 -1 -0.68 -0.21 -0.73 -0.98 -0.46 8.4e+03 0.022 0.62 -0.0027 -
3 -0.83 1.3 -1.4 0.54 -1.1 -1.4 -0.81 -0.23 -0.86 -1.3 -0.61 8.2e+03 0.011 6.2 0.96 ++
4 -0.46 1.3 -2.1 0.25 -1 -1.7 -0.72 0.087 -1 -1.5 -0.7 8.2e+03 0.0058 62 1.1 ++
5 -0.42 1.3 -2.3 0.2 -1 -1.7 -0.73 0.12 -1 -1.5 -0.73 8.2e+03 0.00038 6.2e+02 1 ++
6 -0.42 1.3 -2.3 0.2 -1 -1.7 -0.73 0.12 -1 -1.5 -0.73 8.2e+03 2.3e-06 6.2e+02 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000097
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train_re b_time_train_di lambda_travel_t b_cost_train b_time_swissmet b_time_swissmet b_cost_swissmet asc_car b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho
0 -1 -0.69 -0.2 1.7 -0.54 -0.97 -0.55 -0.63 -0.27 -0.69 -0.48 -0.51 8.9e+03 0.047 1 0.85 +
1 -0.26 -0.79 -0.3 1.3 -1.5 -0.84 -0.65 -0.8 -0.41 -0.62 -0.61 -0.42 8.5e+03 0.023 10 1.1 ++
2 -0.26 -0.79 -0.3 1.3 -1.5 -0.84 -0.65 -0.8 -0.41 -0.62 -0.61 -0.42 8.5e+03 0.023 1.3 -7.3 -
3 -0.26 -0.79 -0.3 1.3 -1.5 -0.84 -0.65 -0.8 -0.41 -0.62 -0.61 -0.42 8.5e+03 0.023 0.65 0.02 -
4 -0.18 -1.1 -0.52 0.65 -1.8 -1 -0.63 -0.95 -0.36 -0.86 -0.87 -0.57 8.4e+03 0.0085 6.5 1.2 ++
5 0.34 -2 -0.59 0.084 -1.9 -1.7 -0.15 -0.87 -0.0099 -1.1 -0.89 -0.75 8.3e+03 0.013 6.5 0.81 +
6 0.33 -2.1 -0.63 0.15 -1.9 -1.6 -0.25 -0.88 -0.00088 -1.1 -0.89 -0.78 8.3e+03 0.00053 65 1 ++
7 0.32 -2.1 -0.63 0.17 -1.9 -1.6 -0.26 -0.88 -0.012 -1.1 -0.88 -0.77 8.3e+03 1.6e-05 6.5e+02 1 ++
8 0.32 -2.1 -0.63 0.17 -1.9 -1.6 -0.26 -0.88 -0.012 -1.1 -0.88 -0.77 8.3e+03 6.4e-09 6.5e+02 1 ++
Considering neighbor 1/20 for current solution
Attempt 76/100
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000098
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.64 0.089 -0.0056 -1 1.6 -0.96 1.8 0.16 -0.14 -0.023 8.9e+03 0.06 1 0.68 +
1 -0.44 0.92 0.24 -1.3 0.74 -0.41 2.8 0.067 0.016 -0.3 8.8e+03 0.13 1 0.2 +
2 -0.39 0.037 0.31 -0.53 0.59 -0.27 3.8 -0.038 0.081 -0.37 8.7e+03 0.11 1 0.13 +
3 -0.39 0.037 0.31 -0.53 0.59 -0.27 3.8 -0.038 0.081 -0.37 8.7e+03 0.11 0.5 0.0034 -
4 -0.38 0.4 0.034 -0.8 0.41 -0.43 4.3 -0.11 0.11 -0.2 8.6e+03 0.073 0.5 0.62 +
5 -0.38 0.27 0.18 -0.83 0.56 -0.42 3.8 -0.00083 -0.055 -0.38 8.5e+03 0.016 5 1.1 ++
6 -0.38 0.27 0.18 -0.83 0.56 -0.42 3.8 -0.00083 -0.055 -0.38 8.5e+03 0.016 1.4 -2.5 -
7 -0.45 0.53 -0.029 -1.2 0.32 -0.53 2.4 0.035 0.12 -0.3 8.4e+03 0.023 1.4 0.88 +
8 -0.52 0.49 0.3 -1.3 0.47 -0.61 2 0.13 -0.016 -0.38 8.4e+03 0.0066 14 1.1 ++
9 -0.58 0.53 0.36 -1.3 0.47 -0.62 2 0.14 -0.016 -0.44 8.4e+03 0.00049 1.4e+02 1.1 ++
10 -0.59 0.53 0.37 -1.3 0.47 -0.62 1.9 0.14 -0.017 -0.44 8.4e+03 9.2e-06 1.4e+03 1 ++
11 -0.59 0.53 0.37 -1.3 0.47 -0.62 1.9 0.14 -0.017 -0.44 8.4e+03 1.3e-09 1.4e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 77/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000099
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -0.7 0.27 -1 0.0041 1.6 -0.57 -0.27 -0.24 8.8e+03 0.045 1 0.84 +
1 -1.1 1.3 -1.3 0.036 0.85 -0.79 -0.033 -0.63 8.3e+03 0.013 10 1.1 ++
2 -0.66 1.7 -2 -0.87 -0.062 -0.71 0.32 -1.1 8.3e+03 0.032 10 0.11 +
3 -0.85 1.7 -1.7 -0.61 0.19 -0.71 0.21 -1.2 8.2e+03 0.0037 1e+02 1.1 ++
4 -0.88 1.7 -1.6 -0.59 0.32 -0.71 0.18 -1.2 8.2e+03 0.00099 1e+03 1.1 ++
5 -0.89 1.7 -1.6 -0.58 0.34 -0.71 0.18 -1.2 8.2e+03 1.4e-05 1e+04 1 ++
6 -0.89 1.7 -1.6 -0.58 0.34 -0.71 0.18 -1.2 8.2e+03 4.6e-09 1e+04 1 ++
Considering neighbor 0/20 for current solution
Considering neighbor 1/20 for current solution
Attempt 78/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000100
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di b_cost b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 -0.81 0.2 0.022 -0.88 -0.12 -0.68 -1 0.27 -0.33 -0.24 -0.067 -0.73 -0.041 8.7e+03 0.08 10 1.1 ++
1 -0.88 0.7 0.69 -1.6 0.77 -0.78 -1.7 2.3 -0.42 -0.09 -0.37 -1.1 0.99 8.4e+03 0.031 1e+02 0.97 ++
2 -0.9 0.89 0.84 -1.8 0.25 -0.8 -1.8 1.2 -0.56 -0.1 -0.46 -1.1 0.49 8.4e+03 0.014 1e+02 0.54 +
3 -0.87 0.92 0.87 -1.8 0.61 -0.8 -1.8 2 -0.46 -0.099 -0.45 -1.2 0.84 8.4e+03 0.0058 1e+02 0.39 +
4 -0.88 0.92 0.86 -1.8 0.32 -0.8 -1.8 1.4 -0.5 -0.1 -0.46 -1.1 0.51 8.4e+03 0.0063 1e+02 0.24 +
5 -0.88 0.92 0.87 -1.8 0.45 -0.8 -1.8 1.7 -0.48 -0.1 -0.46 -1.2 0.66 8.4e+03 0.00088 1e+02 0.85 +
6 -0.88 0.92 0.87 -1.8 0.43 -0.8 -1.8 1.6 -0.48 -0.1 -0.46 -1.2 0.63 8.4e+03 4e-05 1e+03 0.97 ++
7 -0.88 0.92 0.87 -1.8 0.43 -0.8 -1.8 1.6 -0.48 -0.1 -0.46 -1.2 0.63 8.4e+03 3.9e-08 1e+03 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000101
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di b_cost b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho
0 -1 0.89 0.041 0.017 -0.71 -0.41 -0.62 -0.88 -0.59 -0.37 -0.41 -0.18 -0.083 -0.6 -0.52 8.4e+03 0.081 10 1.1 ++
1 -1.4 1.3 0.34 0.34 -0.95 -0.63 -0.78 -1.1 -0.79 -0.5 -0.81 -0.07 -0.42 -0.63 -0.7 8.2e+03 0.019 1e+02 1.1 ++
2 -1.4 1.3 0.48 0.51 -1.1 -0.74 -0.8 -1.1 -0.84 -0.51 -0.95 -0.076 -0.48 -0.64 -0.73 8.2e+03 0.0022 1e+03 1.1 ++
3 -1.4 1.3 0.5 0.53 -1.1 -0.76 -0.8 -1.1 -0.84 -0.52 -0.96 -0.077 -0.49 -0.63 -0.73 8.2e+03 4.6e-05 1e+04 1 ++
4 -1.4 1.3 0.5 0.53 -1.1 -0.76 -0.8 -1.1 -0.84 -0.52 -0.96 -0.077 -0.49 -0.63 -0.73 8.2e+03 2e-08 1e+04 1 ++
Considering neighbor 1/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 16 unknown parameters [max: 50]
*** Estimate b07everything_000102
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 9e+03 0.068 1 0.7 +
1 8.4e+03 0.013 10 1.1 ++
2 8.4e+03 0.013 5 -5.5e+05 -
3 8.4e+03 0.013 2.5 -47 -
4 8.4e+03 0.013 1.2 -3.1 -
5 8.2e+03 0.018 1.2 0.83 +
6 8.1e+03 0.0022 12 1 ++
7 8.1e+03 2.6e-05 1.2e+02 1 ++
8 8.1e+03 1e-08 1.2e+02 1 ++
Considering neighbor 2/20 for current solution
Attempt 79/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000103
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_train_re b_time_train_di lambda_travel_t b_cost_train b_time_swissmet b_time_swissmet b_cost_swissmet asc_car b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho
0 -0.99 -0.73 -0.12 1.6 -0.55 -1 -0.18 -0.63 -0.33 -0.75 -0.096 -0.58 8.9e+03 0.04 1 0.9 +
1 -0.15 -0.98 -0.26 1.1 -1.6 -1.2 0.066 -0.73 -0.34 -0.98 -0.059 -0.45 8.5e+03 0.025 10 1.1 ++
2 -0.15 -0.98 -0.26 1.1 -1.6 -1.2 0.066 -0.73 -0.34 -0.98 -0.059 -0.45 8.5e+03 0.025 5 -1.1e+03 -
3 -0.15 -0.98 -0.26 1.1 -1.6 -1.2 0.066 -0.73 -0.34 -0.98 -0.059 -0.45 8.5e+03 0.025 2.5 -38 -
4 -0.15 -0.98 -0.26 1.1 -1.6 -1.2 0.066 -0.73 -0.34 -0.98 -0.059 -0.45 8.5e+03 0.025 1.2 -8.7 -
5 -0.15 -0.98 -0.26 1.1 -1.6 -1.2 0.066 -0.73 -0.34 -0.98 -0.059 -0.45 8.5e+03 0.025 0.62 -0.56 -
6 0.053 -1.5 -0.41 0.5 -1.9 -1.4 -0.066 -0.83 -0.2 -1.3 -0.071 -0.64 8.4e+03 0.011 6.2 1.1 ++
7 0.51 -2.4 -0.68 -0.061 -1.9 -1.7 -1 -0.75 0.17 -1.5 -0.34 -0.82 8.3e+03 0.012 6.2 0.62 +
8 0.47 -2.4 -0.76 0.061 -1.9 -1.6 -0.73 -0.76 0.15 -1.5 -0.29 -0.84 8.3e+03 0.0009 62 1 ++
9 0.44 -2.3 -0.75 0.1 -1.9 -1.6 -0.73 -0.76 0.13 -1.4 -0.29 -0.82 8.3e+03 6.2e-05 6.2e+02 1 ++
10 0.44 -2.3 -0.75 0.1 -1.9 -1.6 -0.73 -0.76 0.13 -1.4 -0.29 -0.82 8.3e+03 5e-08 6.2e+02 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 16 unknown parameters [max: 50]
*** Estimate b07everything_000104
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 8.9e+03 0.046 1 0.82 +
1 8.4e+03 0.022 10 1.1 ++
2 8.4e+03 0.022 0.62 0.093 -
3 8.3e+03 0.011 6.2 1.1 ++
4 8.2e+03 0.006 62 1.1 ++
5 8.2e+03 0.00045 6.2e+02 1 ++
6 8.2e+03 4.3e-06 6.2e+02 1 ++
Considering neighbor 1/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 7 unknown parameters [max: 50]
*** Estimate b07everything_000105
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost asc_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -0.21 -
1 -0.5 -0.5 -0.5 0 0 -0.5 0.034 8.9e+03 4.3 5 1.1 ++
2 -0.5 -0.5 -0.5 0 0 -0.5 0.034 8.9e+03 4.3 2.5 -9.7 -
3 -0.5 -0.5 -0.5 0 0 -0.5 0.034 8.9e+03 4.3 1.2 -7.6 -
4 -0.5 -0.5 -0.5 0 0 -0.5 0.034 8.9e+03 4.3 0.62 -5.9 -
5 -0.5 -0.5 -0.5 0 0 -0.5 0.034 8.9e+03 4.3 0.31 -4.7 -
6 -0.5 -0.5 -0.5 0 0 -0.5 0.034 8.9e+03 4.3 0.16 -3.1 -
7 -0.5 -0.5 -0.5 0 0 -0.5 0.034 8.9e+03 4.3 0.078 -2.4 -
8 -0.5 -0.5 -0.5 0 0 -0.5 0.034 8.9e+03 4.3 0.039 -2.7 -
9 -0.5 -0.5 -0.5 0 0 -0.5 0.034 8.9e+03 4.3 0.02 -3.5 -
10 -0.5 -0.5 -0.5 0 0 -0.5 0.034 8.9e+03 4.3 0.0098 -4.4 -
11 -0.5 -0.5 -0.5 0 0 -0.5 0.034 8.9e+03 4.3 0.0049 -5.2 -
12 -0.5 -0.5 -0.5 0 0 -0.5 0.034 8.9e+03 4.3 0.0024 -4.6 -
13 -0.5 -0.5 -0.5 0 0 -0.5 0.034 8.9e+03 4.3 0.0012 -2.7 -
14 -0.5 -0.5 -0.5 0 0 -0.5 0.034 8.9e+03 4.3 0.00061 -1.3 -
15 -0.5 -0.5 -0.5 0 0 -0.5 0.034 8.9e+03 4.3 0.00031 -0.22 -
16 -0.5 -0.5 -0.5 0.00031 -0.00031 -0.5 0.034 8.9e+03 2.8 0.00031 0.65 +
17 -0.5 -0.5 -0.5 0.00061 -0.00023 -0.5 0.034 8.9e+03 1.2 0.00031 0.8 +
18 -0.5 -0.5 -0.5 0.00092 -0.00026 -0.5 0.034 8.9e+03 0.15 0.0031 0.99 ++
19 -0.5 -0.5 -0.5 0.004 -0.00026 -0.5 0.033 8.9e+03 0.3 0.031 1 ++
20 -0.51 -0.52 -0.51 0.034 -0.00041 -0.5 0.031 8.8e+03 0.23 0.31 1 ++
21 -0.67 -0.79 -0.55 0.066 -0.00054 -0.81 -0.0049 8.6e+03 0.76 3.1 1 ++
22 -0.67 -0.79 -0.55 0.066 -0.00054 -0.81 -0.0049 8.6e+03 0.76 1.5 -3e+02 -
23 -0.67 -0.79 -0.55 0.066 -0.00054 -0.81 -0.0049 8.6e+03 0.76 0.76 -1.3e+02 -
24 -0.67 -0.79 -0.55 0.066 -0.00054 -0.81 -0.0049 8.6e+03 0.76 0.38 -26 -
25 -0.67 -0.79 -0.55 0.066 -0.00054 -0.81 -0.0049 8.6e+03 0.76 0.19 -4.2 -
26 -0.82 -0.98 -0.65 -0.068 2.8e-05 -0.85 -0.0047 8.6e+03 1.3 0.19 0.35 +
27 -0.69 -1.2 -0.77 -0.062 1.3e-05 -0.85 -0.0054 8.5e+03 4.2 1.9 1 ++
28 -0.69 -1.2 -0.77 -0.062 1.3e-05 -0.85 -0.0054 8.5e+03 4.2 0.35 -3.6 -
29 -0.58 -1.5 -0.89 -0.11 0.00019 -0.86 0.12 8.5e+03 16 0.35 0.32 +
30 -0.49 -1.7 -0.82 -0.096 0.00016 -0.87 0.15 8.5e+03 2.6 3.5 0.92 ++
31 -0.51 -1.7 -0.78 -0.094 0.00015 -0.86 0.14 8.5e+03 0.2 35 0.98 ++
32 -0.51 -1.6 -0.78 -0.094 0.00015 -0.87 0.14 8.5e+03 0.0018 3.5e+02 1 ++
33 -0.51 -1.6 -0.78 -0.094 0.00015 -0.86 0.14 8.5e+03 0.00073 3.5e+03 1 ++
34 -0.51 -1.6 -0.79 -0.094 0.00015 -0.86 0.14 8.5e+03 0.026 3.5e+04 1 ++
35 -0.51 -1.6 -0.79 -0.094 0.00015 -0.86 0.14 8.5e+03 8.6e-06 3.5e+05 1 ++
36 -0.51 -1.6 -0.79 -0.094 0.00015 -0.86 0.14 8.5e+03 0.0024 3.5e+06 1 ++
37 -0.51 -1.6 -0.79 -0.094 0.00015 -0.86 0.14 8.5e+03 2.5e-07 3.5e+06 1 ++
Considering neighbor 2/20 for current solution
Attempt 80/100
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000106
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -1.5 -
1 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.051 -
2 -0.25 -0.00017 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.4e+03 1.4 2.5 1 ++
3 -0.25 -0.00017 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.4e+03 1.4 1.2 -5.6 -
4 -0.25 -0.00017 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.4e+03 1.4 0.62 -3 -
5 -0.25 -0.00017 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.4e+03 1.4 0.31 -1.4 -
6 -0.25 -0.00017 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.4e+03 1.4 0.16 0.032 -
7 -0.36 0.019 -0.41 -0.26 0.15 -0.0031 -0.36 0.21 0.041 -0.052 0.022 9.2e+03 9.1 0.16 0.54 +
8 -0.36 0.019 -0.41 -0.26 0.15 -0.0031 -0.36 0.21 0.041 -0.052 0.022 9.2e+03 9.1 0.078 0.085 -
9 -0.38 0.037 -0.48 -0.27 0.12 0.0023 -0.38 0.13 0.059 -0.07 0.042 9.1e+03 5.4 0.078 0.16 +
10 -0.38 0.037 -0.48 -0.27 0.12 0.0023 -0.38 0.13 0.059 -0.07 0.042 9.1e+03 5.4 0.039 -4.2 -
11 -0.38 0.037 -0.48 -0.27 0.12 0.0023 -0.38 0.13 0.059 -0.07 0.042 9.1e+03 5.4 0.02 -2.8 -
12 -0.38 0.037 -0.48 -0.27 0.12 0.0023 -0.38 0.13 0.059 -0.07 0.042 9.1e+03 5.4 0.0098 -2 -
13 -0.38 0.037 -0.48 -0.27 0.12 0.0023 -0.38 0.13 0.059 -0.07 0.042 9.1e+03 5.4 0.0049 -1.1 -
14 -0.39 0.042 -0.48 -0.28 0.11 -0.0026 -0.39 0.13 0.061 -0.075 0.045 9e+03 11 0.0049 0.15 +
15 -0.39 0.043 -0.48 -0.28 0.11 0.0012 -0.39 0.12 0.061 -0.076 0.045 9e+03 5.3 0.0049 0.14 +
16 -0.39 0.043 -0.48 -0.28 0.11 0.0012 -0.39 0.12 0.061 -0.076 0.045 9e+03 5.3 0.0024 -0.6 -
17 -0.39 0.046 -0.49 -0.28 0.11 -0.0013 -0.39 0.12 0.064 -0.078 0.048 8.9e+03 4.2 0.0024 0.65 +
18 -0.39 0.047 -0.49 -0.28 0.11 -0.00081 -0.39 0.12 0.064 -0.079 0.048 8.9e+03 2.4 0.024 1.3 ++
19 -0.4 0.056 -0.5 -0.28 0.12 -0.00053 -0.4 0.093 0.064 -0.088 0.05 8.9e+03 5.5 0.024 0.63 +
20 -0.4 0.056 -0.5 -0.28 0.12 -0.00053 -0.4 0.093 0.064 -0.088 0.05 8.9e+03 5.5 0.012 -3.8 -
21 -0.4 0.056 -0.5 -0.28 0.12 -0.00053 -0.4 0.093 0.064 -0.088 0.05 8.9e+03 5.5 0.0061 -3.9 -
22 -0.4 0.056 -0.5 -0.28 0.12 -0.00053 -0.4 0.093 0.064 -0.088 0.05 8.9e+03 5.5 0.0031 -3.1 -
23 -0.4 0.056 -0.5 -0.28 0.12 -0.00053 -0.4 0.093 0.064 -0.088 0.05 8.9e+03 5.5 0.0015 -1.7 -
24 -0.4 0.056 -0.5 -0.28 0.12 -0.00053 -0.4 0.093 0.064 -0.088 0.05 8.9e+03 5.5 0.00076 -0.72 -
25 -0.4 0.056 -0.5 -0.28 0.12 -0.00053 -0.4 0.093 0.064 -0.088 0.05 8.9e+03 5.5 0.00038 -0.11 -
26 -0.4 0.056 -0.5 -0.29 0.12 -0.00091 -0.4 0.092 0.064 -0.088 0.05 8.9e+03 2.6 0.00038 0.32 +
27 -0.4 0.056 -0.5 -0.29 0.12 -0.00091 -0.4 0.092 0.064 -0.088 0.05 8.9e+03 2.6 0.00019 -0.56 -
28 -0.4 0.056 -0.5 -0.29 0.12 -0.00072 -0.4 0.092 0.063 -0.088 0.05 8.9e+03 1.9 0.00019 0.62 +
29 -0.4 0.056 -0.5 -0.29 0.12 -0.00075 -0.4 0.092 0.063 -0.088 0.05 8.9e+03 0.054 0.0019 1 ++
30 -0.4 0.057 -0.5 -0.29 0.12 -0.00076 -0.4 0.09 0.063 -0.089 0.05 8.9e+03 0.16 0.019 1 ++
31 -0.4 0.064 -0.51 -0.29 0.12 -0.00078 -0.41 0.071 0.063 -0.096 0.051 8.8e+03 0.051 0.19 1 ++
32 -0.44 0.14 -0.61 -0.33 0.18 -0.001 -0.49 -0.12 0.051 -0.17 0.052 8.7e+03 0.12 1.9 0.99 ++
33 -0.44 0.14 -0.61 -0.33 0.18 -0.001 -0.49 -0.12 0.051 -0.17 0.052 8.7e+03 0.12 0.95 -67 -
34 -0.44 0.14 -0.61 -0.33 0.18 -0.001 -0.49 -0.12 0.051 -0.17 0.052 8.7e+03 0.12 0.48 -3.4 -
35 -0.5 0.57 -0.82 -0.41 -0.011 -0.00022 -0.82 -0.6 -0.33 -0.5 -0.22 8.4e+03 0.32 0.48 0.89 +
36 -0.65 1 -1.2 -0.61 -0.022 -0.00017 -1.1 -0.85 -0.41 -0.72 -0.29 8.2e+03 0.15 4.8 1.1 ++
37 -0.65 1 -1.2 -0.61 -0.022 -0.00017 -1.1 -0.85 -0.41 -0.72 -0.29 8.2e+03 0.15 2.4 -3.2e+02 -
38 -0.65 1 -1.2 -0.61 -0.022 -0.00017 -1.1 -0.85 -0.41 -0.72 -0.29 8.2e+03 0.15 1.2 -1.1e+02 -
39 -0.65 1 -1.2 -0.61 -0.022 -0.00017 -1.1 -0.85 -0.41 -0.72 -0.29 8.2e+03 0.15 0.6 -22 -
40 -0.65 1 -1.2 -0.61 -0.022 -0.00017 -1.1 -0.85 -0.41 -0.72 -0.29 8.2e+03 0.15 0.3 -3.1 -
41 -0.65 1 -1.2 -0.61 -0.022 -0.00017 -1.1 -0.85 -0.41 -0.72 -0.29 8.2e+03 0.15 0.15 0.054 -
42 -0.77 1.1 -1.3 -0.69 -0.095 0.00018 -1.2 -0.78 -0.39 -0.75 -0.3 8.2e+03 8.8 0.15 0.74 +
43 -0.69 1.2 -1.5 -0.75 -0.08 1.6e-05 -1.1 -0.87 -0.41 -0.8 -0.34 8.2e+03 14 0.15 0.59 +
44 -0.69 1.2 -1.5 -0.75 -0.08 1.6e-05 -1.1 -0.87 -0.41 -0.8 -0.34 8.2e+03 14 0.075 -0.81 -
45 -0.69 1.2 -1.5 -0.75 -0.08 1.6e-05 -1.1 -0.87 -0.41 -0.8 -0.34 8.2e+03 14 0.037 -0.61 -
46 -0.69 1.2 -1.5 -0.75 -0.08 1.6e-05 -1.1 -0.87 -0.41 -0.8 -0.34 8.2e+03 14 0.019 -0.48 -
47 -0.69 1.2 -1.5 -0.75 -0.08 1.6e-05 -1.1 -0.87 -0.41 -0.8 -0.34 8.2e+03 14 0.0093 -0.52 -
48 -0.69 1.2 -1.5 -0.75 -0.08 1.6e-05 -1.1 -0.87 -0.41 -0.8 -0.34 8.2e+03 14 0.0047 -0.51 -
49 -0.69 1.2 -1.5 -0.75 -0.08 1.6e-05 -1.1 -0.87 -0.41 -0.8 -0.34 8.2e+03 14 0.0023 -0.36 -
50 -0.69 1.2 -1.5 -0.75 -0.08 1.6e-05 -1.1 -0.87 -0.41 -0.8 -0.34 8.2e+03 14 0.0012 -0.31 -
51 -0.69 1.2 -1.5 -0.75 -0.08 1.6e-05 -1.1 -0.87 -0.41 -0.8 -0.34 8.2e+03 14 0.00058 -0.3 -
52 -0.69 1.2 -1.5 -0.75 -0.08 1.6e-05 -1.1 -0.87 -0.41 -0.8 -0.34 8.2e+03 14 0.00029 -0.29 -
53 -0.69 1.2 -1.5 -0.75 -0.08 1.6e-05 -1.1 -0.87 -0.41 -0.8 -0.34 8.2e+03 14 0.00015 -0.29 -
54 -0.69 1.2 -1.5 -0.75 -0.08 1.6e-05 -1.1 -0.87 -0.41 -0.8 -0.34 8.2e+03 14 7.3e-05 -0.29 -
55 -0.69 1.2 -1.5 -0.75 -0.079 8.9e-05 -1.1 -0.87 -0.41 -0.8 -0.34 8.1e+03 8.3 7.3e-05 0.62 +
56 -0.69 1.2 -1.5 -0.75 -0.08 7e-05 -1.1 -0.87 -0.41 -0.8 -0.34 8.1e+03 2 7.3e-05 0.81 +
57 -0.69 1.2 -1.5 -0.75 -0.08 7.4e-05 -1.1 -0.87 -0.41 -0.8 -0.34 8.1e+03 0.071 0.00073 0.98 ++
58 -0.69 1.2 -1.5 -0.75 -0.08 7.7e-05 -1.1 -0.87 -0.41 -0.8 -0.34 8.1e+03 0.015 0.0073 1 ++
59 -0.7 1.2 -1.5 -0.75 -0.086 0.0001 -1.2 -0.87 -0.4 -0.8 -0.34 8.1e+03 0.14 0.073 0.99 ++
60 -0.74 1.2 -1.5 -0.78 -0.096 0.00015 -1.2 -0.85 -0.38 -0.81 -0.33 8.1e+03 1.9 0.73 1 ++
61 -0.73 1.4 -1.8 -0.77 -0.11 0.00019 -1.1 -0.86 -0.31 -1 -0.33 8.1e+03 1.9 7.3 0.99 ++
62 -0.72 1.4 -1.8 -0.77 -0.1 0.00019 -1.1 -0.86 -0.3 -1 -0.32 8.1e+03 0.035 73 1 ++
63 -0.72 1.4 -1.8 -0.77 -0.1 0.00019 -1.1 -0.86 -0.3 -1 -0.32 8.1e+03 7.9e-05 7.3e+02 1 ++
64 -0.72 1.4 -1.8 -0.77 -0.1 0.00019 -1.1 -0.86 -0.3 -1 -0.32 8.1e+03 8e-08 7.3e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 81/100
Considering neighbor 0/20 for current solution
Attempt 82/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000107
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time square_tt_coef cube_tt_coef b_cost asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 0.044 -
1 -0.5 -0.056 -0.5 0 0 -0.33 -0.054 -0.5 9.1e+03 4 5 1 ++
2 -0.5 -0.056 -0.5 0 0 -0.33 -0.054 -0.5 9.1e+03 4 2.5 -10 -
3 -0.5 -0.056 -0.5 0 0 -0.33 -0.054 -0.5 9.1e+03 4 1.2 -8.5 -
4 -0.5 -0.056 -0.5 0 0 -0.33 -0.054 -0.5 9.1e+03 4 0.62 -6.7 -
5 -0.5 -0.056 -0.5 0 0 -0.33 -0.054 -0.5 9.1e+03 4 0.31 -2.5 -
6 -0.5 -0.056 -0.5 0 0 -0.33 -0.054 -0.5 9.1e+03 4 0.16 -1.3 -
7 -0.5 -0.056 -0.5 0 0 -0.33 -0.054 -0.5 9.1e+03 4 0.078 -1.2 -
8 -0.5 -0.056 -0.5 0 0 -0.33 -0.054 -0.5 9.1e+03 4 0.039 -1.6 -
9 -0.5 -0.056 -0.5 0 0 -0.33 -0.054 -0.5 9.1e+03 4 0.02 -2.3 -
10 -0.5 -0.056 -0.5 0 0 -0.33 -0.054 -0.5 9.1e+03 4 0.0098 -3.2 -
11 -0.5 -0.056 -0.5 0 0 -0.33 -0.054 -0.5 9.1e+03 4 0.0049 -4 -
12 -0.5 -0.056 -0.5 0 0 -0.33 -0.054 -0.5 9.1e+03 4 0.0024 -4.6 -
13 -0.5 -0.056 -0.5 0 0 -0.33 -0.054 -0.5 9.1e+03 4 0.0012 -2.5 -
14 -0.5 -0.056 -0.5 0 0 -0.33 -0.054 -0.5 9.1e+03 4 0.00061 -1.3 -
15 -0.5 -0.056 -0.5 0 0 -0.33 -0.054 -0.5 9.1e+03 4 0.00031 -0.27 -
16 -0.5 -0.056 -0.5 0.00031 -0.00031 -0.33 -0.054 -0.5 9.1e+03 2.9 0.00031 0.65 +
17 -0.5 -0.056 -0.5 0.00061 -0.00024 -0.33 -0.054 -0.5 9.1e+03 1.1 0.00031 0.83 +
18 -0.5 -0.056 -0.5 0.00092 -0.00026 -0.33 -0.054 -0.5 9.1e+03 0.15 0.0031 0.99 ++
19 -0.5 -0.055 -0.5 0.004 -0.00026 -0.33 -0.054 -0.5 9.1e+03 0.33 0.031 1 ++
20 -0.52 -0.051 -0.53 0.034 -0.0004 -0.34 -0.055 -0.5 9e+03 0.29 0.31 1 ++
21 -0.67 0.063 -0.83 0.26 -0.0014 -0.45 -0.0092 -0.54 8.7e+03 2.4 0.31 0.64 +
22 -0.77 0.37 -0.93 0.036 -0.00036 -0.66 0.079 -0.64 8.5e+03 7.5 0.31 0.8 +
23 -0.82 0.67 -1.1 0.0066 -0.00033 -0.68 -0.038 -0.73 8.4e+03 5.5 3.1 1 ++
24 -0.82 0.67 -1.1 0.0066 -0.00033 -0.68 -0.038 -0.73 8.4e+03 5.5 1.5 -67 -
25 -0.82 0.67 -1.1 0.0066 -0.00033 -0.68 -0.038 -0.73 8.4e+03 5.5 0.76 -16 -
26 -0.82 0.67 -1.1 0.0066 -0.00033 -0.68 -0.038 -0.73 8.4e+03 5.5 0.38 -0.34 -
27 -1 1.1 -1.4 -0.091 0.00048 -0.73 0.13 -0.82 8.4e+03 15 0.38 0.23 +
28 -1 1.1 -1.4 -0.091 0.00048 -0.73 0.13 -0.82 8.4e+03 15 0.19 -4.3 -
29 -1 1.1 -1.4 -0.091 0.00048 -0.73 0.13 -0.82 8.4e+03 15 0.095 -4.1 -
30 -1 1.1 -1.4 -0.091 0.00048 -0.73 0.13 -0.82 8.4e+03 15 0.048 -3.7 -
31 -1 1.1 -1.4 -0.091 0.00048 -0.73 0.13 -0.82 8.4e+03 15 0.024 -3.9 -
32 -1 1.1 -1.4 -0.091 0.00048 -0.73 0.13 -0.82 8.4e+03 15 0.012 -4.2 -
33 -1 1.1 -1.4 -0.091 0.00048 -0.73 0.13 -0.82 8.4e+03 15 0.006 -4.4 -
34 -1 1.1 -1.4 -0.091 0.00048 -0.73 0.13 -0.82 8.4e+03 15 0.003 -3.7 -
35 -1 1.1 -1.4 -0.091 0.00048 -0.73 0.13 -0.82 8.4e+03 15 0.0015 -2.4 -
36 -1 1.1 -1.4 -0.091 0.00048 -0.73 0.13 -0.82 8.4e+03 15 0.00075 -1.6 -
37 -1 1.1 -1.4 -0.091 0.00048 -0.73 0.13 -0.82 8.4e+03 15 0.00037 -0.51 -
38 -1 1.1 -1.4 -0.091 0.00011 -0.73 0.13 -0.82 8.3e+03 11 0.00037 0.84 +
39 -1 1.1 -1.4 -0.09 0.00014 -0.73 0.13 -0.82 8.3e+03 3.1 0.00037 0.81 +
40 -1 1.1 -1.4 -0.09 0.00013 -0.73 0.13 -0.82 8.3e+03 0.32 0.0037 0.99 ++
41 -1 1.1 -1.4 -0.086 0.00011 -0.73 0.13 -0.82 8.3e+03 0.088 0.037 1 ++
42 -1 1.1 -1.5 -0.065 1.2e-05 -0.72 0.092 -0.83 8.3e+03 1.8 0.37 1 ++
43 -0.97 1.5 -1.7 -0.1 0.00016 -0.71 0.042 -0.93 8.2e+03 16 3.7 0.9 ++
44 -0.91 1.6 -2.1 -0.1 0.0002 -0.7 0.16 -1.1 8.2e+03 6.6 37 0.97 ++
45 -0.93 1.6 -2.1 -0.1 0.00019 -0.72 0.16 -1.2 8.2e+03 2.2 3.7e+02 0.94 ++
46 -0.92 1.6 -2.1 -0.1 0.0002 -0.72 0.16 -1.3 8.2e+03 0.12 3.7e+03 1 ++
47 -0.92 1.6 -2.1 -0.1 0.0002 -0.72 0.16 -1.3 8.2e+03 0.00045 3.7e+04 1 ++
48 -0.92 1.6 -2.1 -0.1 0.0002 -0.72 0.16 -1.3 8.2e+03 4.9e-07 3.7e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 83/100
Biogeme parameters read from biogeme.toml.
Model with 8 unknown parameters [max: 50]
*** Estimate b07everything_000108
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com b_cost mu_existing asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -0.79 0.43 -0.87 0.091 -1 1.6 0.37 -0.31 8.8e+03 0.12 1 0.79 +
1 -0.79 0.43 -0.87 0.091 -1 1.6 0.37 -0.31 8.8e+03 0.12 0.5 -0.11 -
2 -0.63 0.75 -1.1 0.068 -0.5 1.8 -0.06 -0.42 8.3e+03 0.021 0.5 0.89 +
3 -0.7 1 -1 -0.0077 -0.59 1.6 0.019 -0.57 8.3e+03 0.0019 5 1 ++
4 -0.74 1.1 -1.1 -0.016 -0.61 1.5 0.019 -0.69 8.3e+03 0.00013 50 1.1 ++
5 -0.74 1.1 -1.1 -0.019 -0.61 1.5 0.02 -0.72 8.3e+03 8.1e-06 5e+02 1 ++
6 -0.74 1.1 -1.1 -0.019 -0.61 1.5 0.02 -0.72 8.3e+03 9.8e-10 5e+02 1 ++
Considering neighbor 0/20 for current solution
Considering neighbor 1/20 for current solution
Attempt 84/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000109
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -2 -
1 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.29 -
2 -0.25 -0.15 -0.0057 -0.25 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 2.5 1 ++
3 -0.25 -0.15 -0.0057 -0.25 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 1.2 -4.4 -
4 -0.25 -0.15 -0.0057 -0.25 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 0.62 -2.8 -
5 -0.25 -0.15 -0.0057 -0.25 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 0.31 -1.3 -
6 -0.44 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.041 -0.018 -0.0059 0.015 9.4e+03 12 0.31 0.2 +
7 -0.44 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.041 -0.018 -0.0059 0.015 9.4e+03 12 0.16 -0.36 -
8 -0.44 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.041 -0.018 -0.0059 0.015 9.4e+03 12 0.078 -0.067 -
9 -0.44 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.041 -0.018 -0.0059 0.015 9.4e+03 12 0.039 0.012 -
10 -0.44 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.041 -0.018 -0.0059 0.015 9.4e+03 12 0.02 0.031 -
11 -0.44 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.041 -0.018 -0.0059 0.015 9.4e+03 12 0.0098 0.034 -
12 -0.44 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.041 -0.018 -0.0059 0.015 9.4e+03 12 0.0049 0.033 -
13 -0.44 -0.2 -0.0092 -0.56 0.23 0.00043 -0.45 0.2 0.043 -0.018 -0.006 0.017 9.2e+03 6.5 0.0049 0.39 +
14 -0.44 -0.2 -0.0092 -0.56 0.23 0.00043 -0.45 0.2 0.043 -0.018 -0.006 0.017 9.2e+03 6.5 0.0024 -0.38 -
15 -0.44 -0.2 -0.0068 -0.56 0.22 -0.002 -0.45 0.2 0.045 -0.016 -0.0085 0.02 9.1e+03 3.9 0.0024 0.53 +
16 -0.44 -0.19 -0.0067 -0.55 0.22 -0.0016 -0.45 0.2 0.046 -0.016 -0.0085 0.02 9.1e+03 2.5 0.024 1.3 ++
17 -0.44 -0.19 -0.0067 -0.55 0.22 -0.0016 -0.45 0.2 0.046 -0.016 -0.0085 0.02 9.1e+03 2.5 0.012 -3 -
18 -0.44 -0.19 -0.0067 -0.55 0.22 -0.0016 -0.45 0.2 0.046 -0.016 -0.0085 0.02 9.1e+03 2.5 0.0061 -3.6 -
19 -0.44 -0.19 -0.0067 -0.55 0.22 -0.0016 -0.45 0.2 0.046 -0.016 -0.0085 0.02 9.1e+03 2.5 0.0031 -3.2 -
20 -0.44 -0.19 -0.0067 -0.55 0.22 -0.0016 -0.45 0.2 0.046 -0.016 -0.0085 0.02 9.1e+03 2.5 0.0015 -2.1 -
21 -0.44 -0.19 -0.0067 -0.55 0.22 -0.0016 -0.45 0.2 0.046 -0.016 -0.0085 0.02 9.1e+03 2.5 0.00076 -1.3 -
22 -0.44 -0.19 -0.0067 -0.55 0.22 -0.0016 -0.45 0.2 0.046 -0.016 -0.0085 0.02 9.1e+03 2.5 0.00038 -0.2 -
23 -0.44 -0.19 -0.0064 -0.55 0.22 -0.0013 -0.45 0.2 0.046 -0.017 -0.0089 0.021 9.1e+03 2.1 0.0038 1 ++
24 -0.44 -0.19 -0.0063 -0.55 0.22 -0.0011 -0.45 0.19 0.047 -0.017 -0.0089 0.021 9.1e+03 6 0.0038 0.24 +
25 -0.44 -0.19 -0.0063 -0.55 0.22 -0.0011 -0.45 0.19 0.047 -0.017 -0.0089 0.021 9.1e+03 6 0.0019 0.069 -
26 -0.44 -0.19 -0.0063 -0.55 0.22 -0.0011 -0.45 0.19 0.047 -0.017 -0.0089 0.021 9.1e+03 6 0.00095 -0.071 -
27 -0.44 -0.19 -0.0063 -0.55 0.22 -0.0011 -0.45 0.19 0.047 -0.017 -0.0089 0.021 9.1e+03 6 0.00048 -0.16 -
28 -0.44 -0.19 -0.0063 -0.55 0.22 -0.0011 -0.45 0.19 0.047 -0.017 -0.0089 0.021 9.1e+03 6 0.00024 -0.15 -
29 -0.44 -0.19 -0.0061 -0.55 0.22 -0.0013 -0.45 0.19 0.047 -0.017 -0.0092 0.022 9.1e+03 2.4 0.00024 0.27 +
30 -0.44 -0.19 -0.0061 -0.55 0.22 -0.0013 -0.45 0.19 0.047 -0.017 -0.0092 0.022 9.1e+03 2.4 0.00012 -0.3 -
31 -0.44 -0.19 -0.006 -0.55 0.22 -0.0012 -0.45 0.19 0.047 -0.017 -0.0093 0.022 9.1e+03 0.12 0.00012 0.78 +
32 -0.44 -0.19 -0.006 -0.55 0.22 -0.0012 -0.45 0.19 0.047 -0.017 -0.0093 0.022 9.1e+03 0.12 0.0012 1 ++
33 -0.44 -0.19 -0.006 -0.55 0.22 -0.0012 -0.45 0.19 0.047 -0.017 -0.0093 0.022 9.1e+03 0.13 0.012 1 ++
34 -0.43 -0.19 -0.0058 -0.55 0.22 -0.0012 -0.46 0.18 0.049 -0.017 -0.0095 0.024 9e+03 0.098 0.12 1 ++
35 -0.42 -0.15 -0.0047 -0.53 0.18 -0.001 -0.46 0.061 0.064 -0.022 -0.011 0.045 8.9e+03 0.04 1.2 0.98 ++
36 -0.72 0.65 0.46 -0.87 0.0086 -0.00031 -1.5 -0.7 -0.45 -0.037 -0.36 -0.26 8.4e+03 0.59 12 1 ++
37 -0.66 0.73 0.64 -1.3 -0.011 -0.00021 -1.7 -0.8 -0.37 -0.1 -0.47 -0.35 8.3e+03 1.8 1.2e+02 1.2 ++
38 -0.66 0.73 0.64 -1.3 -0.011 -0.00021 -1.7 -0.8 -0.37 -0.1 -0.47 -0.35 8.3e+03 1.8 60 -5.8e+03 -
39 -0.66 0.73 0.64 -1.3 -0.011 -0.00021 -1.7 -0.8 -0.37 -0.1 -0.47 -0.35 8.3e+03 1.8 30 -3.2e+03 -
40 -0.66 0.73 0.64 -1.3 -0.011 -0.00021 -1.7 -0.8 -0.37 -0.1 -0.47 -0.35 8.3e+03 1.8 15 -2e+03 -
41 -0.66 0.73 0.64 -1.3 -0.011 -0.00021 -1.7 -0.8 -0.37 -0.1 -0.47 -0.35 8.3e+03 1.8 7.5 -8.9e+02 -
42 -0.66 0.73 0.64 -1.3 -0.011 -0.00021 -1.7 -0.8 -0.37 -0.1 -0.47 -0.35 8.3e+03 1.8 3.7 -3.9e+02 -
43 -0.66 0.73 0.64 -1.3 -0.011 -0.00021 -1.7 -0.8 -0.37 -0.1 -0.47 -0.35 8.3e+03 1.8 1.9 -1.3e+02 -
44 -0.66 0.73 0.64 -1.3 -0.011 -0.00021 -1.7 -0.8 -0.37 -0.1 -0.47 -0.35 8.3e+03 1.8 0.93 -36 -
45 -0.66 0.73 0.64 -1.3 -0.011 -0.00021 -1.7 -0.8 -0.37 -0.1 -0.47 -0.35 8.3e+03 1.8 0.47 -8.3 -
46 -0.66 0.73 0.64 -1.3 -0.011 -0.00021 -1.7 -0.8 -0.37 -0.1 -0.47 -0.35 8.3e+03 1.8 0.23 -2.5 -
47 -0.72 0.69 0.64 -1.5 -0.11 0.00021 -1.8 -0.74 -0.37 -0.096 -0.48 -0.38 8.3e+03 12 0.23 0.19 +
48 -0.6 0.8 0.64 -1.7 -0.083 8.8e-05 -1.7 -0.82 -0.35 -0.1 -0.48 -0.39 8.3e+03 1.7 2.3 0.91 ++
49 -0.6 0.8 0.64 -1.7 -0.083 8.8e-05 -1.7 -0.82 -0.35 -0.1 -0.48 -0.39 8.3e+03 1.7 0.33 -0.47 -
50 -0.57 0.82 0.65 -2.1 -0.12 0.00024 -1.8 -0.8 -0.27 -0.098 -0.49 -0.37 8.3e+03 11 0.33 0.62 +
51 -0.42 0.77 0.67 -2.3 -0.11 0.00021 -1.8 -0.83 -0.22 -0.13 -0.53 -0.35 8.3e+03 2.2 3.3 0.93 ++
52 -0.43 0.77 0.62 -2.2 -0.11 0.00021 -1.8 -0.83 -0.22 -0.13 -0.58 -0.36 8.3e+03 0.032 33 1 ++
53 -0.42 0.76 0.63 -2.2 -0.11 0.00021 -1.8 -0.83 -0.22 -0.13 -0.59 -0.36 8.3e+03 0.0052 3.3e+02 1 ++
54 -0.42 0.76 0.62 -2.2 -0.11 0.00021 -1.8 -0.83 -0.22 -0.13 -0.6 -0.36 8.3e+03 0.021 3.3e+03 1 ++
55 -0.42 0.76 0.62 -2.2 -0.11 0.00021 -1.8 -0.83 -0.22 -0.13 -0.6 -0.36 8.3e+03 6.9e-05 3.3e+04 1 ++
56 -0.42 0.76 0.62 -2.2 -0.11 0.00021 -1.8 -0.83 -0.22 -0.13 -0.6 -0.36 8.3e+03 0.001 3.3e+05 1 ++
57 -0.42 0.76 0.62 -2.2 -0.11 0.00021 -1.8 -0.83 -0.22 -0.13 -0.6 -0.36 8.3e+03 2.4e-05 3.3e+06 1 ++
58 -0.42 0.76 0.62 -2.2 -0.11 0.00021 -1.8 -0.83 -0.22 -0.13 -0.6 -0.36 8.3e+03 4.4e-05 3.3e+07 1 ++
59 -0.42 0.76 0.62 -2.2 -0.11 0.00021 -1.8 -0.83 -0.22 -0.13 -0.6 -0.36 8.3e+03 2.8e-05 3.3e+08 1 ++
60 -0.42 0.76 0.62 -2.2 -0.11 0.00021 -1.8 -0.83 -0.22 -0.13 -0.6 -0.36 8.3e+03 1.2e-08 3.3e+08 1 ++
Considering neighbor 0/20 for current solution
Attempt 85/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000110
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost_train b_time_swissmet b_time_swissmet b_cost_swissmet asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho
0 -1 0.3 -0.72 -0.12 1.6 -0.55 -0.99 -0.17 -0.6 -0.33 -0.45 -0.76 -0.098 -0.58 8.8e+03 0.039 10 0.9 ++
1 -1 0.3 -0.72 -0.12 1.6 -0.55 -0.99 -0.17 -0.6 -0.33 -0.45 -0.76 -0.098 -0.58 8.8e+03 0.039 5 -4.1e+04 -
2 -1 0.3 -0.72 -0.12 1.6 -0.55 -0.99 -0.17 -0.6 -0.33 -0.45 -0.76 -0.098 -0.58 8.8e+03 0.039 2.5 -21 -
3 -1 0.3 -0.72 -0.12 1.6 -0.55 -0.99 -0.17 -0.6 -0.33 -0.45 -0.76 -0.098 -0.58 8.8e+03 0.039 1.2 -1.5 -
4 -0.82 1.5 -0.95 -0.29 0.98 -1.2 -1.4 0.0057 -0.8 -0.29 -0.88 -1.2 -0.093 -0.47 8.3e+03 0.017 12 0.96 ++
5 -0.82 1.5 -0.95 -0.29 0.98 -1.2 -1.4 0.0057 -0.8 -0.29 -0.88 -1.2 -0.093 -0.47 8.3e+03 0.017 1.4 -2.2 -
6 -0.82 1.5 -0.95 -0.29 0.98 -1.2 -1.4 0.0057 -0.8 -0.29 -0.88 -1.2 -0.093 -0.47 8.3e+03 0.017 0.68 -0.11 -
7 -0.63 1.4 -1.6 -0.5 0.49 -0.93 -1.6 -0.3 -0.71 -0.032 -0.93 -1.4 -0.099 -0.57 8.2e+03 0.012 6.8 1.2 ++
8 -0.37 1.3 -2.2 -0.83 0.12 -1 -1.7 -0.86 -0.72 0.16 -1 -1.6 -0.3 -0.72 8.2e+03 0.0057 68 0.97 ++
9 -0.37 1.3 -2.3 -0.9 0.13 -1.1 -1.6 -0.73 -0.72 0.17 -1 -1.5 -0.29 -0.75 8.2e+03 0.00012 6.8e+02 1 ++
10 -0.37 1.3 -2.3 -0.9 0.13 -1.1 -1.6 -0.73 -0.72 0.17 -1 -1.5 -0.29 -0.75 8.2e+03 8.1e-08 6.8e+02 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000111
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_1st lambda_travel_t b_cost mu_public asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -0.84 0.06 -1 -0.57 1.2 -0.24 1.6 -0.03 -0.11 9.3e+03 0.12 1 0.42 +
1 -0.42 1.1 -0.8 -0.45 0.92 -1.2 1.7 -0.36 -0.54 8.4e+03 0.069 1 0.69 +
2 -0.42 1.1 -0.8 -0.45 0.92 -1.2 1.7 -0.36 -0.54 8.4e+03 0.069 0.5 -0.014 -
3 -0.54 0.97 -0.81 -0.52 0.58 -0.69 1.7 -0.16 -0.61 8.2e+03 0.009 5 0.92 ++
4 -0.54 0.97 -0.81 -0.52 0.58 -0.69 1.7 -0.16 -0.61 8.2e+03 0.009 0.37 0.092 -
5 -0.45 1.1 -1.2 -0.55 0.45 -0.79 1.5 -0.035 -0.9 8.2e+03 0.01 3.7 1 ++
6 -0.61 1.3 -1.2 -0.56 0.42 -0.78 1.3 0.086 -1.2 8.2e+03 0.0048 37 1.1 ++
7 -0.73 1.4 -1.3 -0.57 0.4 -0.78 1.2 0.11 -1.2 8.2e+03 0.0014 3.7e+02 1.2 ++
8 -0.79 1.5 -1.3 -0.58 0.4 -0.78 1.1 0.13 -1.2 8.2e+03 0.00043 3.7e+03 1.1 ++
9 -0.81 1.5 -1.3 -0.59 0.4 -0.78 1.1 0.13 -1.2 8.2e+03 2.1e-05 3.7e+04 1 ++
10 -0.81 1.5 -1.3 -0.59 0.4 -0.78 1.1 0.13 -1.2 8.2e+03 1.3e-07 3.7e+04 1 ++
Considering neighbor 1/20 for current solution
Attempt 86/100
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000112
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_1st lambda_travel_t b_cost_train mu_existing asc_car_ref asc_car_diff_GA b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 -0.69 0.23 -0.97 -0.49 1.5 -0.55 2 0.31 -0.29 0.2 -0.82 1e+04 0.27 1 0.2 +
1 -0.69 0.23 -0.97 -0.49 1.5 -0.55 2 0.31 -0.29 0.2 -0.82 1e+04 0.27 0.5 -1 -
2 -0.43 0.34 -0.97 -0.54 1.4 -0.44 1.8 -0.19 -0.36 -0.24 -0.5 8.5e+03 0.062 0.5 0.9 +
3 -0.48 0.82 -0.94 -0.55 0.92 -0.68 2.1 -0.34 -0.52 -0.21 -0.71 8.2e+03 0.0062 5 1 ++
4 -0.48 0.82 -0.94 -0.55 0.92 -0.68 2.1 -0.34 -0.52 -0.21 -0.71 8.2e+03 0.0062 0.56 -0.77 -
5 -0.42 1 -1.3 -0.69 0.35 -0.6 1.7 -0.19 -0.37 -0.21 -0.69 8.1e+03 0.0081 0.56 0.81 +
6 -0.46 1.1 -1.3 -0.57 0.4 -0.75 1.6 -0.19 -0.43 -0.3 -0.71 8.1e+03 0.0014 5.6 1.1 ++
7 -0.47 1.1 -1.3 -0.58 0.41 -0.79 1.6 -0.19 -0.49 -0.32 -0.73 8.1e+03 0.00019 56 1 ++
8 -0.47 1.1 -1.3 -0.58 0.41 -0.79 1.6 -0.19 -0.49 -0.32 -0.73 8.1e+03 5.1e-07 56 1 ++
Considering neighbor 0/20 for current solution
Attempt 87/100
Biogeme parameters read from biogeme.toml.
Model with 18 unknown parameters [max: 50]
*** Estimate b07everything_000113
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. Function Relgrad Radius Rho
0 9.4e+03 0.34 1 0.65 +
1 9.4e+03 0.34 0.5 -0.89 -
2 9.4e+03 0.34 0.25 -0.012 -
3 9e+03 0.4 0.25 0.3 +
4 8.3e+03 0.049 2.5 1 ++
5 8.2e+03 0.014 25 1.1 ++
6 8.1e+03 0.019 25 0.62 +
7 8.1e+03 0.00056 2.5e+02 1 ++
8 8.1e+03 4.4e-06 2.5e+02 1 ++
Considering neighbor 0/20 for current solution
Attempt 88/100
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000114
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time b_cost_train mu_existing asc_car_ref asc_car_diff_GA b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 -0.54 0.3 -1 -0.54 1.9 0.15 -0.31 -0.00024 -0.62 9.1e+03 0.19 1 0.71 +
1 -0.54 0.3 -1 -0.54 1.9 0.15 -0.31 -0.00024 -0.62 9.1e+03 0.19 0.5 -0.16 -
2 -0.13 0.74 -0.72 -0.6 2.4 -0.3 -0.49 -0.26 -0.46 8.6e+03 0.13 0.5 0.47 +
3 -0.57 0.42 -0.64 -0.41 2.9 -0.29 -0.019 -0.22 -0.45 8.4e+03 0.039 0.5 0.61 +
4 -0.53 0.87 -0.88 -0.45 2.4 -0.31 0.066 -0.18 -0.49 8.3e+03 0.0078 5 1.1 ++
5 -0.53 0.87 -0.88 -0.45 2.4 -0.31 0.066 -0.18 -0.49 8.3e+03 0.0078 0.72 -1.7 -
6 -0.65 0.85 -1 -0.64 1.7 -0.37 -0.29 -0.25 -0.64 8.3e+03 0.0094 7.2 0.95 ++
7 -0.61 0.99 -1.1 -0.73 1.6 -0.3 -0.47 -0.29 -0.65 8.2e+03 0.0016 72 1.1 ++
8 -0.63 1 -1.1 -0.77 1.5 -0.29 -0.56 -0.3 -0.66 8.2e+03 0.00032 7.2e+02 1 ++
9 -0.63 1 -1.1 -0.77 1.5 -0.29 -0.56 -0.3 -0.66 8.2e+03 1.3e-06 7.2e+02 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000115
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st b_cost mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.58 0.11 -0.004 -0.72 -0.47 -1 1.7 0.29 -0.076 -0.023 8.6e+03 0.074 1 0.88 +
1 -0.58 0.11 -0.004 -0.72 -0.47 -1 1.7 0.29 -0.076 -0.023 8.6e+03 0.074 0.5 -0.36 -
2 -0.59 0.46 0.09 -0.71 -0.49 -0.5 2.1 0.083 -0.14 -0.15 8.4e+03 0.028 0.5 0.7 +
3 -0.7 0.45 0.29 -0.7 -0.49 -0.62 2.1 0.017 -0.033 -0.48 8.4e+03 0.0017 5 1 ++
4 -0.77 0.5 0.33 -0.76 -0.52 -0.68 1.8 0.036 -0.039 -0.51 8.4e+03 0.0017 5 0.84 +
5 -0.77 0.5 0.32 -0.75 -0.52 -0.68 1.9 0.033 -0.038 -0.5 8.4e+03 7.8e-05 50 1 ++
6 -0.77 0.5 0.32 -0.75 -0.52 -0.68 1.9 0.033 -0.038 -0.5 8.4e+03 4.2e-07 50 1 ++
Considering neighbor 1/20 for current solution
Attempt 89/100
Considering neighbor 0/20 for current solution
Attempt 90/100
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000116
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com b_cost mu_public asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.77 -0.33 -0.016 -1 -0.11 -0.24 1.6 -0.078 -0.11 -0.0098 9.5e+03 0.12 1 0.43 +
1 -0.4 0.67 0.015 -1.1 -0.14 -1 1.7 -0.2 -0.31 -0.049 8.9e+03 0.1 1 0.49 +
2 -0.57 0.34 0.7 -0.75 -0.21 -0.52 2.1 -0.19 -0.14 -0.58 8.7e+03 0.033 1 0.67 +
3 -0.7 0.46 0.25 -1.1 -0.18 -0.66 1.1 -0.013 -0.1 -0.57 8.6e+03 0.031 1 0.42 +
4 -1 0.74 0.75 -1.2 -0.12 -0.76 1.2 -0.0085 -0.097 -0.55 8.6e+03 0.0015 10 1 ++
5 -1.3 0.9 0.86 -1.3 -0.077 -0.79 1 0.04 -0.077 -0.57 8.6e+03 0.0047 1e+02 0.9 ++
6 -1.4 0.93 0.89 -1.2 -0.08 -0.78 1 0.049 -0.086 -0.56 8.6e+03 0.00032 1e+03 1 ++
7 -1.4 0.94 0.9 -1.3 -0.075 -0.78 1 0.05 -0.079 -0.56 8.6e+03 0.00029 1e+04 1 ++
8 -1.4 0.94 0.9 -1.3 -0.075 -0.78 1 0.05 -0.079 -0.56 8.6e+03 3e-06 1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 91/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000117
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st b_cost_train mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 -0.39 0.41 0.02 -0.94 -0.6 -1 1.8 0.19 -0.27 -0.059 -0.14 -0.9 8.8e+03 0.14 1 0.77 +
1 -0.39 0.41 0.02 -0.94 -0.6 -1 1.8 0.19 -0.27 -0.059 -0.14 -0.9 8.8e+03 0.14 0.5 -0.15 -
2 -0.31 0.28 0.11 -0.66 -0.42 -1 2 -0.31 -0.028 -0.18 -0.31 -0.57 8.3e+03 0.025 0.5 0.84 +
3 -0.44 0.4 0.18 -0.81 -0.52 -1.1 1.8 -0.34 -0.046 -0.43 -0.27 -0.7 8.3e+03 0.0059 5 1.1 ++
4 -0.5 0.48 0.27 -0.87 -0.55 -1.2 1.6 -0.35 -0.058 -0.48 -0.28 -0.74 8.3e+03 0.0016 50 1.1 ++
5 -0.52 0.5 0.3 -0.87 -0.55 -1.2 1.6 -0.35 -0.06 -0.49 -0.28 -0.75 8.3e+03 3.9e-05 5e+02 1 ++
6 -0.52 0.5 0.3 -0.87 -0.55 -1.2 1.6 -0.35 -0.06 -0.49 -0.28 -0.75 8.3e+03 4e-07 5e+02 1 ++
Considering neighbor 0/20 for current solution
Considering neighbor 1/20 for current solution
Attempt 92/100
Biogeme parameters read from biogeme.toml.
Model with 14 unknown parameters [max: 50]
*** Estimate b07everything_000118
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_train lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_time_car b_time_swissmet Function Relgrad Radius Rho
0 -0.87 0.46 -0.018 -0.011 -0.86 1.6 -1 1.8 0.037 -0.34 -0.21 -0.028 -0.52 -0.58 8.7e+03 0.062 1 0.73 +
1 -0.53 1.1 0.63 0.12 -1.1 0.61 -0.2 2.7 -0.083 -0.44 0.15 -0.18 -0.88 -1.4 8.4e+03 0.085 1 0.36 +
2 -0.17 0.45 0.23 0.16 -1.4 0.28 -0.42 3.2 0.19 0.56 -0.1 -0.24 -1 -1.4 8.3e+03 0.049 1 0.3 +
3 -0.34 0.67 0.2 -0.29 -1 0.031 -0.35 4.2 -0.27 -0.07 0.16 -0.23 -0.52 -0.75 8.3e+03 0.054 1 0.16 +
4 -0.14 0.79 0.03 -0.2 -1.4 0.017 -0.45 3.2 0.019 0.23 -0.11 -0.28 -0.82 -1.2 8.2e+03 0.02 10 1.1 ++
5 -0.14 0.79 0.03 -0.2 -1.4 0.017 -0.45 3.2 0.019 0.23 -0.11 -0.28 -0.82 -1.2 8.2e+03 0.02 1.1 -1.6 -
6 -0.24 0.62 0.27 -0.036 -1.7 0.27 -0.54 2.2 0.081 -0.13 -0.00073 -0.43 -1.1 -1.4 8.1e+03 0.017 11 0.96 ++
7 -0.33 0.87 0.27 0.067 -1.9 0.15 -0.59 2 0.14 -0.17 -0.065 -0.36 -1.2 -1.5 8.1e+03 0.0036 1.1e+02 1.1 ++
8 -0.41 0.94 0.31 0.13 -2 0.16 -0.62 1.8 0.15 -0.27 -0.069 -0.36 -1.3 -1.6 8.1e+03 0.0014 1.1e+03 1.1 ++
9 -0.42 0.95 0.31 0.14 -2 0.16 -0.62 1.8 0.15 -0.29 -0.069 -0.36 -1.3 -1.6 8.1e+03 1.5e-05 1.1e+04 1 ++
10 -0.42 0.95 0.31 0.14 -2 0.16 -0.62 1.8 0.15 -0.29 -0.069 -0.36 -1.3 -1.6 8.1e+03 5.8e-08 1.1e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 93/100
Considering neighbor 0/20 for current solution
Attempt 94/100
Biogeme parameters read from biogeme.toml.
Model with 9 unknown parameters [max: 50]
*** Estimate b07everything_000119
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time_ref b_time_diff_com lambda_travel_t b_cost_train mu_existing asc_car b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 -0.63 -1 -0.072 1.4 -0.55 1.9 0.24 0.12 -0.66 1e+04 0.24 1 0.37 +
1 -0.63 -1 -0.072 1.4 -0.55 1.9 0.24 0.12 -0.66 1e+04 0.24 0.5 -0.9 -
2 -0.26 -0.85 -0.0027 1.1 -0.43 1.8 -0.26 -0.29 -0.46 8.7e+03 0.097 0.5 0.75 +
3 -0.19 -0.87 0.078 0.68 -0.93 2.2 -0.32 -0.23 -0.54 8.4e+03 0.02 5 0.98 ++
4 0.23 -1.4 -0.39 0.14 -1.3 1.7 -0.079 -0.33 -0.59 8.3e+03 0.0077 5 0.81 +
5 0.29 -1.5 -0.34 0.39 -1.4 1.7 -0.069 -0.36 -0.64 8.3e+03 0.0039 5 0.87 +
6 0.27 -1.5 -0.33 0.36 -1.4 1.7 -0.073 -0.37 -0.64 8.3e+03 0.00012 50 1 ++
7 0.27 -1.5 -0.33 0.36 -1.4 1.7 -0.073 -0.37 -0.64 8.3e+03 3.1e-07 50 1 ++
Considering neighbor 0/20 for current solution
Attempt 95/100
Biogeme parameters read from biogeme.toml.
Model with 13 unknown parameters [max: 50]
*** Estimate b07everything_000120
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -0.72 -
1 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 5 1.1 ++
2 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 2.5 -7 -
3 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 1.2 -5.9 -
4 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.62 -4.6 -
5 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.31 -3.5 -
6 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.16 -2.9 -
7 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.078 -2.9 -
8 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.039 -3.3 -
9 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.02 -3.7 -
10 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0098 -4.2 -
11 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0049 -3.6 -
12 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0024 -2.5 -
13 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0012 -1.7 -
14 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.00061 -0.97 -
15 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.00031 -0.12 -
16 -0.5 -0.00028 -0.5 -0.02 -0.5 -0.16 0.00031 -0.00031 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 3.8 0.00031 0.68 +
17 -0.5 -0.0002 -0.5 -0.02 -0.5 -0.16 0.00061 -0.00021 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 4 0.00031 0.36 +
18 -0.5 -0.00011 -0.5 -0.02 -0.5 -0.16 0.00092 -0.00027 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 1.7 0.00031 0.77 +
19 -0.5 -2.1e-05 -0.5 -0.02 -0.5 -0.16 0.0012 -0.00026 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 0.23 0.0031 0.98 ++
20 -0.5 0.00086 -0.5 -0.02 -0.5 -0.16 0.0043 -0.00027 -0.14 0.025 -0.079 -0.023 -0.0067 9.2e+03 0.11 0.031 1 ++
21 -0.51 0.0098 -0.49 -0.02 -0.53 -0.17 0.035 -0.0004 -0.15 0.018 -0.084 -0.03 -0.0071 9.1e+03 0.089 0.31 1 ++
22 -0.56 0.24 -0.31 -0.02 -0.83 -0.18 0.22 -0.0012 -0.45 0.011 -0.2 -0.11 -0.017 8.8e+03 1.8 0.31 0.78 +
23 -0.65 0.54 -0.093 -0.016 -0.96 -0.16 0.012 -0.0003 -0.69 0.093 -0.33 -0.13 -0.03 8.5e+03 1.8 0.31 0.8 +
24 -0.86 0.85 0.042 -0.0075 -1.3 -0.2 -0.026 -0.00015 -0.71 0.084 -0.45 -0.16 -0.049 8.3e+03 1.4 3.1 1.1 ++
25 -0.86 0.85 0.042 -0.0075 -1.3 -0.2 -0.026 -0.00015 -0.71 0.084 -0.45 -0.16 -0.049 8.3e+03 1.4 1.5 -91 -
26 -0.86 0.85 0.042 -0.0075 -1.3 -0.2 -0.026 -0.00015 -0.71 0.084 -0.45 -0.16 -0.049 8.3e+03 1.4 0.76 -19 -
27 -0.86 0.85 0.042 -0.0075 -1.3 -0.2 -0.026 -0.00015 -0.71 0.084 -0.45 -0.16 -0.049 8.3e+03 1.4 0.38 -0.76 -
28 -1.1 1.2 0.22 0.018 -1.6 -0.3 -0.13 0.00028 -0.72 0.14 -0.6 -0.11 -0.082 8.3e+03 24 0.38 0.42 +
29 -1.1 1.4 0.38 0.061 -2 -0.49 -0.085 0.00012 -0.74 0.15 -0.71 -0.094 -0.12 8.2e+03 23 0.38 0.68 +
30 -1.1 1.4 0.38 0.061 -2 -0.49 -0.085 0.00012 -0.74 0.15 -0.71 -0.094 -0.12 8.2e+03 23 0.19 -1.6 -
31 -1.1 1.4 0.38 0.061 -2 -0.49 -0.085 0.00012 -0.74 0.15 -0.71 -0.094 -0.12 8.2e+03 23 0.095 -0.57 -
32 -1.1 1.4 0.38 0.061 -2 -0.49 -0.085 0.00012 -0.74 0.15 -0.71 -0.094 -0.12 8.2e+03 23 0.048 -0.15 -
33 -1.1 1.4 0.36 0.071 -2 -0.53 -0.12 0.00022 -0.73 0.17 -0.72 -0.079 -0.12 8.2e+03 48 0.048 0.11 +
34 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.048 0.15 +
35 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.024 -3.1 -
36 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.012 -3.1 -
37 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.006 -2.9 -
38 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.003 -2.8 -
39 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.0015 -2.7 -
40 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.00075 -2.8 -
41 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.00037 -2.8 -
42 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.00019 -2.8 -
43 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 9.3e-05 -1 -
44 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.00021 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 19 9.3e-05 0.63 +
45 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.00022 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 2.8 0.00093 1.1 ++
46 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.00021 -0.74 0.17 -0.75 -0.092 -0.13 8.2e+03 0.055 0.0093 1 ++
47 -1.1 1.5 0.4 0.088 -2 -0.58 -0.11 0.0002 -0.74 0.17 -0.75 -0.087 -0.14 8.2e+03 0.48 0.093 1 ++
48 -1.2 1.5 0.43 0.14 -2 -0.67 -0.11 0.00019 -0.74 0.21 -0.83 -0.08 -0.17 8.2e+03 1.9 0.93 1 ++
49 -1.3 1.5 0.54 0.6 -2 -1.1 -0.11 0.0002 -0.71 0.21 -1.2 -0.077 -0.46 8.1e+03 0.032 9.3 1 ++
50 -1.3 1.5 0.56 0.59 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.064 -0.5 8.1e+03 0.0004 93 1 ++
51 -1.3 1.5 0.55 0.59 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.068 -0.52 8.1e+03 0.00038 9.3e+02 1 ++
52 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.067 -0.52 8.1e+03 0.00014 9.3e+03 1 ++
53 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.067 -0.52 8.1e+03 2.6e-05 9.3e+04 1 ++
54 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.067 -0.52 8.1e+03 9.8e-06 9.3e+05 1 ++
55 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.067 -0.52 8.1e+03 0.00038 9.3e+06 1 ++
56 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.067 -0.52 8.1e+03 3.8e-09 9.3e+06 1 ++
Considering neighbor 0/20 for current solution
Attempt 96/100
Biogeme parameters read from biogeme.toml.
Model with 15 unknown parameters [max: 50]
*** Estimate b07everything_000121
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time square_tt_coef cube_tt_coef b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1.1e+04 0.26 0.5 0 -
1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.26 -
2 -0.25 -0.00017 -0.15 -0.0057 -0.25 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 2.5 1 ++
3 -0.25 -0.00017 -0.15 -0.0057 -0.25 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 1.2 -4.5 -
4 -0.25 -0.00017 -0.15 -0.0057 -0.25 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 0.62 -2.8 -
5 -0.25 -0.00017 -0.15 -0.0057 -0.25 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 0.31 -1.3 -
6 -0.25 -0.00017 -0.15 -0.0057 -0.25 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 0.16 0.093 -
7 -0.35 0.022 -0.17 -0.0075 -0.41 0.11 -0.0026 -0.35 1.1 0.23 0.024 -0.051 -0.012 -0.0039 0.0043 9.2e+03 8.6 0.16 0.56 +
8 -0.35 0.022 -0.17 -0.0075 -0.41 0.11 -0.0026 -0.35 1.1 0.23 0.024 -0.051 -0.012 -0.0039 0.0043 9.2e+03 8.6 0.078 -0.2 -
9 -0.35 0.022 -0.17 -0.0075 -0.41 0.11 -0.0026 -0.35 1.1 0.23 0.024 -0.051 -0.012 -0.0039 0.0043 9.2e+03 8.6 0.039 -0.15 -
10 -0.35 0.022 -0.17 -0.0075 -0.41 0.11 -0.0026 -0.35 1.1 0.23 0.024 -0.051 -0.012 -0.0039 0.0043 9.2e+03 8.6 0.02 -0.15 -
11 -0.35 0.022 -0.17 -0.0075 -0.41 0.11 -0.0026 -0.35 1.1 0.23 0.024 -0.051 -0.012 -0.0039 0.0043 9.2e+03 8.6 0.0098 -0.15 -
12 -0.35 0.022 -0.17 -0.0075 -0.41 0.11 -0.0026 -0.35 1.1 0.23 0.024 -0.051 -0.012 -0.0039 0.0043 9.2e+03 8.6 0.0049 -0.16 -
13 -0.35 0.022 -0.17 -0.0075 -0.41 0.11 -0.0026 -0.35 1.1 0.23 0.024 -0.051 -0.012 -0.0039 0.0043 9.2e+03 8.6 0.0024 -0.025 -
14 -0.35 0.024 -0.17 -0.0051 -0.41 0.11 -0.0002 -0.35 1.1 0.23 0.027 -0.053 -0.014 -0.0063 0.0067 9.1e+03 4.2 0.0024 0.55 +
15 -0.35 0.024 -0.17 -0.0051 -0.41 0.11 -0.0002 -0.35 1.1 0.23 0.027 -0.053 -0.014 -0.0063 0.0067 9.1e+03 4.2 0.0012 -0.74 -
16 -0.35 0.024 -0.17 -0.0051 -0.41 0.11 -0.0002 -0.35 1.1 0.23 0.027 -0.053 -0.014 -0.0063 0.0067 9.1e+03 4.2 0.00061 0.06 -
17 -0.35 0.025 -0.17 -0.0045 -0.41 0.11 -0.00081 -0.35 1.1 0.23 0.027 -0.054 -0.015 -0.0069 0.0073 9.1e+03 1.8 0.00061 0.77 +
18 -0.35 0.025 -0.17 -0.0045 -0.41 0.11 -0.00069 -0.35 1.1 0.22 0.027 -0.054 -0.015 -0.0069 0.0074 9.1e+03 2 0.00061 0.53 +
19 -0.35 0.025 -0.17 -0.0045 -0.41 0.11 -0.00075 -0.35 1.1 0.22 0.027 -0.054 -0.015 -0.0069 0.0074 9.1e+03 0.22 0.0061 0.96 ++
20 -0.35 0.027 -0.17 -0.0044 -0.41 0.12 -0.00075 -0.36 1.1 0.22 0.028 -0.056 -0.016 -0.0071 0.0079 9.1e+03 0.069 0.061 1 ++
21 -0.36 0.05 -0.15 -0.0042 -0.45 0.14 -0.00087 -0.37 1.1 0.16 0.031 -0.074 -0.023 -0.0085 0.012 9e+03 0.22 0.61 1 ++
22 -0.37 0.35 0.088 0.0023 -0.82 0.33 -0.0016 -0.58 1.2 -0.45 -0.04 -0.3 -0.16 -0.027 -0.029 8.6e+03 0.3 0.61 0.83 +
23 -0.37 0.35 0.088 0.0023 -0.82 0.33 -0.0016 -0.58 1.2 -0.45 -0.04 -0.3 -0.16 -0.027 -0.029 8.6e+03 0.3 0.31 -0.76 -
24 -0.47 0.5 0.13 0.01 -0.81 0.022 -0.00036 -0.79 1.2 -0.32 -0.2 -0.39 -0.25 -0.042 -0.16 8.4e+03 0.31 0.31 0.85 +
25 -0.51 0.66 0.23 0.03 -1 0.027 -0.00039 -0.87 1.3 -0.63 -0.25 -0.49 -0.21 -0.064 -0.22 8.3e+03 2.8 3.1 1 ++
26 -0.51 0.66 0.23 0.03 -1 0.027 -0.00039 -0.87 1.3 -0.63 -0.25 -0.49 -0.21 -0.064 -0.22 8.3e+03 2.8 1 -1.1e+02 -
27 -0.51 0.66 0.23 0.03 -1 0.027 -0.00039 -0.87 1.3 -0.63 -0.25 -0.49 -0.21 -0.064 -0.22 8.3e+03 2.8 0.51 -16 -
28 -0.51 0.66 0.23 0.03 -1 0.027 -0.00039 -0.87 1.3 -0.63 -0.25 -0.49 -0.21 -0.064 -0.22 8.3e+03 2.8 0.25 -2.2 -
29 -0.61 0.76 0.24 0.063 -1.3 -0.12 0.00038 -0.99 1.5 -0.66 -0.33 -0.59 -0.17 -0.089 -0.33 8.3e+03 8.8 0.25 0.44 +
30 -0.61 0.76 0.24 0.063 -1.3 -0.12 0.00038 -0.99 1.5 -0.66 -0.33 -0.59 -0.17 -0.089 -0.33 8.3e+03 8.8 0.13 -0.67 -
31 -0.61 0.76 0.24 0.063 -1.3 -0.12 0.00038 -0.99 1.5 -0.66 -0.33 -0.59 -0.17 -0.089 -0.33 8.3e+03 8.8 0.064 -0.63 -
32 -0.61 0.76 0.24 0.063 -1.3 -0.12 0.00038 -0.99 1.5 -0.66 -0.33 -0.59 -0.17 -0.089 -0.33 8.3e+03 8.8 0.032 -0.57 -
33 -0.61 0.76 0.24 0.063 -1.3 -0.12 0.00038 -0.99 1.5 -0.66 -0.33 -0.59 -0.17 -0.089 -0.33 8.3e+03 8.8 0.016 -0.46 -
34 -0.61 0.76 0.24 0.063 -1.3 -0.12 0.00038 -0.99 1.5 -0.66 -0.33 -0.59 -0.17 -0.089 -0.33 8.3e+03 8.8 0.0079 -0.52 -
35 -0.61 0.76 0.24 0.063 -1.3 -0.12 0.00038 -0.99 1.5 -0.66 -0.33 -0.59 -0.17 -0.089 -0.33 8.3e+03 8.8 0.004 -0.78 -
36 -0.61 0.76 0.24 0.063 -1.3 -0.12 0.00038 -0.99 1.5 -0.66 -0.33 -0.59 -0.17 -0.089 -0.33 8.3e+03 8.8 0.002 -1.1 -
37 -0.61 0.76 0.24 0.063 -1.3 -0.12 0.00038 -0.99 1.5 -0.66 -0.33 -0.59 -0.17 -0.089 -0.33 8.3e+03 8.8 0.00099 -1.4 -
38 -0.61 0.76 0.24 0.063 -1.3 -0.12 0.00038 -0.99 1.5 -0.66 -0.33 -0.59 -0.17 -0.089 -0.33 8.3e+03 8.8 0.0005 -1.7 -
39 -0.61 0.76 0.24 0.063 -1.3 -0.12 0.00038 -0.99 1.5 -0.66 -0.33 -0.59 -0.17 -0.089 -0.33 8.3e+03 8.8 0.00025 -1.8 -
40 -0.61 0.76 0.24 0.063 -1.3 -0.12 0.00038 -0.99 1.5 -0.66 -0.33 -0.59 -0.17 -0.089 -0.33 8.3e+03 8.8 0.00012 -1.9 -
41 -0.61 0.76 0.24 0.063 -1.3 -0.12 0.00025 -0.99 1.5 -0.66 -0.33 -0.59 -0.17 -0.089 -0.33 8.3e+03 5 0.00012 0.67 +
42 -0.61 0.76 0.24 0.063 -1.3 -0.12 0.00027 -0.99 1.5 -0.66 -0.33 -0.59 -0.17 -0.089 -0.33 8.3e+03 0.98 0.0012 1.1 ++
43 -0.61 0.76 0.24 0.063 -1.3 -0.12 0.00026 -0.99 1.5 -0.66 -0.33 -0.59 -0.17 -0.089 -0.33 8.3e+03 0.16 0.012 1 ++
44 -0.61 0.76 0.24 0.063 -1.3 -0.11 0.00018 -0.99 1.5 -0.66 -0.33 -0.59 -0.17 -0.089 -0.33 8.2e+03 7.1 0.12 0.97 ++
45 -0.57 0.79 0.29 0.084 -1.4 -0.078 9.2e-05 -0.97 1.5 -0.72 -0.34 -0.62 -0.15 -0.1 -0.37 8.2e+03 11 1.2 0.99 ++
46 -0.57 0.79 0.29 0.084 -1.4 -0.078 9.2e-05 -0.97 1.5 -0.72 -0.34 -0.62 -0.15 -0.1 -0.37 8.2e+03 11 0.46 -1.2 -
47 -0.57 0.79 0.29 0.084 -1.4 -0.078 9.2e-05 -0.97 1.5 -0.72 -0.34 -0.62 -0.15 -0.1 -0.37 8.2e+03 11 0.23 -0.12 -
48 -0.58 0.84 0.31 0.14 -1.7 -0.11 0.00017 -1.1 1.4 -0.75 -0.33 -0.7 -0.083 -0.13 -0.4 8.2e+03 23 0.23 0.62 +
49 -0.58 0.83 0.32 0.2 -1.9 -0.11 0.00023 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 13 0.23 0.71 +
50 -0.58 0.83 0.32 0.2 -1.9 -0.11 0.00023 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 13 0.11 -0.55 -
51 -0.58 0.83 0.32 0.2 -1.9 -0.11 0.00023 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 13 0.057 -0.52 -
52 -0.58 0.83 0.32 0.2 -1.9 -0.11 0.00023 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 13 0.029 -0.84 -
53 -0.58 0.83 0.32 0.2 -1.9 -0.11 0.00023 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 13 0.014 -1.8 -
54 -0.58 0.83 0.32 0.2 -1.9 -0.11 0.00023 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 13 0.0071 -1.4 -
55 -0.58 0.83 0.32 0.2 -1.9 -0.11 0.00023 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 13 0.0036 -1.7 -
56 -0.58 0.83 0.32 0.2 -1.9 -0.11 0.00023 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 13 0.0018 -1.4 -
57 -0.58 0.83 0.32 0.2 -1.9 -0.11 0.00023 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 13 0.00089 -1.3 -
58 -0.58 0.83 0.32 0.2 -1.9 -0.11 0.00023 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 13 0.00045 -1.3 -
59 -0.58 0.83 0.32 0.2 -1.9 -0.11 0.00023 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 13 0.00022 -1.2 -
60 -0.58 0.83 0.32 0.2 -1.9 -0.11 0.00023 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 13 0.00011 -1.2 -
61 -0.58 0.83 0.32 0.2 -1.9 -0.11 0.00023 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 13 5.6e-05 -1.2 -
62 -0.58 0.83 0.32 0.2 -1.9 -0.11 0.00023 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 13 2.8e-05 0.081 -
63 -0.58 0.83 0.32 0.2 -1.9 -0.11 0.0002 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 4.1 2.8e-05 0.89 +
64 -0.58 0.83 0.32 0.2 -1.9 -0.11 0.00019 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 0.8 2.8e-05 0.87 +
65 -0.58 0.83 0.32 0.2 -1.9 -0.1 0.00019 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 0.015 0.00028 1 ++
66 -0.58 0.83 0.32 0.2 -1.9 -0.1 0.00019 -1.1 1.3 -0.8 -0.31 -0.78 -0.087 -0.16 -0.42 8.2e+03 0.015 0.0028 1 ++
67 -0.58 0.84 0.32 0.2 -1.9 -0.1 0.00018 -1.1 1.3 -0.8 -0.31 -0.78 -0.086 -0.16 -0.41 8.2e+03 0.16 0.028 1 ++
68 -0.57 0.86 0.34 0.21 -1.9 -0.1 0.00017 -1.1 1.3 -0.8 -0.28 -0.8 -0.074 -0.17 -0.39 8.2e+03 4.2 0.28 1 ++
69 -0.68 0.99 0.41 0.33 -2.1 -0.11 0.0002 -1.2 1 -0.76 -0.18 -0.98 -0.096 -0.26 -0.33 8.1e+03 0.3 2.8 0.94 ++
70 -0.89 1.1 0.52 0.41 -2.3 -0.11 0.00021 -1.1 1 -0.77 -0.15 -1 -0.059 -0.34 -0.35 8.1e+03 0.069 28 1.1 ++
71 -0.97 1.2 0.55 0.56 -2.2 -0.11 0.0002 -1.1 1 -0.77 -0.17 -1 -0.078 -0.45 -0.34 8.1e+03 0.012 2.8e+02 1 ++
72 -0.97 1.1 0.55 0.55 -2.2 -0.11 0.0002 -1.1 1 -0.77 -0.17 -1 -0.08 -0.47 -0.34 8.1e+03 8.7e-05 2.8e+03 1 ++
73 -0.97 1.1 0.55 0.55 -2.2 -0.11 0.0002 -1.1 1 -0.77 -0.17 -1 -0.08 -0.47 -0.34 8.1e+03 4.9e-06 2.8e+03 1 ++
Considering neighbor 0/20 for current solution
Attempt 97/100
Biogeme parameters read from biogeme.toml.
Model with 12 unknown parameters [max: 50]
*** Estimate b07everything_000122
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho
0 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.26 0.5 0.0042 -
1 -0.39 -0.18 -0.008 -0.5 -0.068 -0.38 1.3 0.28 -0.0096 -0.033 -0.0044 -0.035 9.2e+03 0.12 0.5 0.72 +
2 -0.33 0.057 -0.0014 -0.77 -0.12 -0.48 1.3 -0.22 -0.076 -0.14 -0.019 -0.091 8.7e+03 0.045 5 0.92 ++
3 -0.25 0.62 0.56 -0.93 -0.3 -1.3 1.8 -0.75 -0.56 -0.068 -0.38 -0.39 8.4e+03 0.042 5 0.85 +
4 -0.19 0.37 0.31 -0.9 -0.26 -1.4 1.9 -0.85 -0.5 -0.14 -0.58 -0.51 8.4e+03 0.0012 50 0.95 ++
5 -0.19 0.37 0.31 -0.9 -0.26 -1.4 1.9 -0.85 -0.5 -0.14 -0.58 -0.51 8.4e+03 0.0012 0.46 -2.4 -
6 -0.24 0.44 0.32 -1 -0.28 -1.5 1.5 -0.83 -0.44 -0.079 -0.59 -0.45 8.4e+03 0.01 0.46 0.81 +
7 -0.38 0.55 0.46 -1.1 -0.23 -1.6 1.3 -0.84 -0.43 -0.12 -0.57 -0.42 8.4e+03 0.0035 4.6 1.2 ++
8 -0.5 0.65 0.55 -1.2 -0.19 -1.6 1.2 -0.83 -0.4 -0.11 -0.56 -0.39 8.4e+03 0.0031 46 1.2 ++
9 -0.57 0.69 0.6 -1.2 -0.17 -1.7 1.1 -0.83 -0.39 -0.11 -0.56 -0.38 8.4e+03 0.0006 4.6e+02 1.2 ++
10 -0.61 0.72 0.62 -1.2 -0.16 -1.7 1.1 -0.82 -0.38 -0.1 -0.55 -0.38 8.4e+03 0.00028 4.6e+03 1.1 ++
11 -0.62 0.73 0.63 -1.2 -0.16 -1.7 1.1 -0.82 -0.38 -0.1 -0.55 -0.38 8.4e+03 8.3e-06 4.6e+04 1 ++
12 -0.62 0.73 0.63 -1.2 -0.16 -1.7 1.1 -0.82 -0.38 -0.1 -0.55 -0.38 8.4e+03 7.6e-08 4.6e+04 1 ++
Considering neighbor 0/20 for current solution
Attempt 98/100
Biogeme parameters read from biogeme.toml.
Model with 10 unknown parameters [max: 50]
*** Estimate b07everything_000123
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.59 -0.057 -0.011 -1 -0.036 1.4 -0.52 -0.3 -0.3 -0.019 9e+03 0.073 1 0.88 +
1 -1 0.94 0.11 -1.7 -0.2 0.45 -0.82 0.23 -0.092 -0.13 8.5e+03 0.0056 10 0.94 ++
2 -1.2 0.97 1.2 -1.6 -0.38 0.49 -0.77 0.2 -0.1 -0.54 8.5e+03 0.0015 10 0.84 +
3 -1.2 0.97 0.95 -1.6 -0.38 0.49 -0.77 0.2 -0.1 -0.6 8.5e+03 6.7e-05 1e+02 1 ++
4 -1.2 0.97 0.95 -1.6 -0.38 0.49 -0.77 0.2 -0.1 -0.6 8.5e+03 2.4e-07 1e+02 1 ++
Considering neighbor 0/20 for current solution
Biogeme parameters read from biogeme.toml.
Model with 11 unknown parameters [max: 50]
*** Estimate b07everything_000124
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho
0 -0.66 0.098 -0.0057 -0.99 0.043 1.7 -1 1.8 0.17 -0.14 -0.024 8.9e+03 0.063 1 0.66 +
1 -0.66 0.098 -0.0057 -0.99 0.043 1.7 -1 1.8 0.17 -0.14 -0.024 8.9e+03 0.063 0.5 -0.014 -
2 -0.62 0.34 0.046 -0.89 0.2 1.3 -0.5 2 -0.0028 -0.16 -0.086 8.5e+03 0.027 5 0.97 ++
3 -0.62 0.34 0.046 -0.89 0.2 1.3 -0.5 2 -0.0028 -0.16 -0.086 8.5e+03 0.027 2.5 -65 -
4 -0.62 0.34 0.046 -0.89 0.2 1.3 -0.5 2 -0.0028 -0.16 -0.086 8.5e+03 0.027 1.2 -6.2 -
5 -0.5 0.77 0.34 -1.7 -0.002 0.036 -0.62 2.4 0.061 0.26 -0.38 8.5e+03 0.037 1.2 0.16 +
6 -0.55 0.62 0.46 -1.6 -0.29 0.35 -0.7 1.4 0.26 -0.044 -0.51 8.4e+03 0.015 1.2 0.7 +
7 -0.67 0.61 0.47 -1.4 -0.22 0.44 -0.65 1.7 0.18 -0.022 -0.47 8.4e+03 0.0032 12 1.1 ++
8 -0.59 0.55 0.38 -1.3 -0.16 0.45 -0.63 1.9 0.15 -0.018 -0.46 8.4e+03 0.0014 1.2e+02 1.1 ++
9 -0.59 0.54 0.38 -1.3 -0.16 0.46 -0.63 1.9 0.14 -0.017 -0.45 8.4e+03 9.7e-05 1.2e+03 1 ++
10 -0.59 0.54 0.38 -1.3 -0.16 0.46 -0.63 1.9 0.14 -0.017 -0.45 8.4e+03 5.1e-07 1.2e+03 1 ++
Considering neighbor 1/20 for current solution
Attempt 99/100
Considering neighbor 0/20 for current solution
Pareto file has been updated: b07everything_assisted.pareto
Before the algorithm: 418 models, with 14 Pareto.
After the algorithm: 460 models, with 14 Pareto.
VNS algorithm completed. Postprocessing of the Pareto optimal solutions
Pareto set initialized from file with 422 elements [14 Pareto] and 1 invalid elements.
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000000.iter
Parameter values restored from __b07everything_000000.iter
Starting values for the algorithm: {'asc_train_ref': -0.4573975714775577, 'asc_train_diff_GA': 0.9139811376288225, 'asc_train_diff_one_lugg': 0.3215608760834272, 'asc_train_diff_several_lugg': 0.16499314688652725, 'b_time_train_ref': -2.1238895920685668, 'b_time_train_diff_commuters': -0.14253794778204903, 'square_tt_coef': -0.10234248144617222, 'cube_tt_coef': 0.00018428969578748597, 'b_cost_train': -0.7019858611624399, 'mu_existing': 1.7397759339349839, 'asc_car_ref': -0.34800643665263803, 'asc_car_diff_GA': -0.3031154968280198, 'asc_car_diff_one_lugg': -0.0863723608138404, 'asc_car_diff_several_lugg': -0.3869445069837887, 'b_time_car_ref': -1.6308648105534436, 'b_time_car_diff_commuters': -0.16774567097832702, 'b_cost_car': -0.538603227090099, 'b_time_swissmetro_ref': -2.2076481019951038, 'b_time_swissmetro_diff_commuters': 0.646943753929833, 'b_cost_swissmetro': -0.6283181409645536}
As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file.
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Optimization algorithm has converged.
Relative gradient: 4.3227036916348445e-06
Cause of termination: Relative gradient = 4.3e-06 <= 6.1e-06
Number of function evaluations: 1
Number of gradient evaluations: 1
Number of hessian evaluations: 0
Algorithm: Newton with trust region for simple bound constraints
Number of iterations: 0
Optimization time: 0:00:00.945876
Calculate second derivatives and BHHH
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000001.iter
Parameter values restored from __b07everything_000001.iter
Starting values for the algorithm: {'asc_train_ref': -0.23420164392850729, 'asc_train_diff_GA': 1.0446428367880147, 'b_time_train': -1.993715078400929, 'lambda_travel_time': 0.1565010777053588, 'b_cost': -0.6214193422374116, 'mu_existing': 1.7923196426965602, 'asc_car_ref': 0.11552397056591322, 'asc_car_diff_GA': -0.3505109734592772, 'b_time_car': -1.296260161669425, 'b_time_swissmetro': -1.5554883053457536}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time b_cost asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -1.1 0.99 -0.71 -1.4 -0.29 -0.92 9.5e+03 0.18 1 0.59 +
1 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 1 0.11 +
2 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 0.36 -0.092 -
3 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 0.18 -0.074 -
4 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 0.09 0.0064 -
5 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 0.045 0.041 -
6 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 0.023 0.057 -
7 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 0.011 0.064 -
8 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 0.0056 0.067 -
9 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 0.0028 0.069 -
10 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 0.0014 0.07 -
11 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 0.00071 0.07 -
12 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 0.00035 0.07 -
13 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 0.00018 0.071 -
14 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 8.8e-05 0.071 -
15 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 4.4e-05 0.071 -
16 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 2.2e-05 0.071 -
17 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 1.1e-05 0.071 -
18 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 5.5e-06 0.071 -
19 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 2.8e-06 0.071 -
20 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 1.4e-06 0.071 -
21 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 6.9e-07 0.071 -
22 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 3.4e-07 0.071 -
23 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 1.7e-07 0.071 -
24 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 8.6e-08 0.071 -
25 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 4.3e-08 0.071 -
26 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 2.2e-08 0.071 -
27 -1.4 1.5 -1.4 -1.7 -0.6 -1.3 9.4e+03 0.25 1.1e-08 0.071 -
Optimization algorithm has *not* converged.
Algorithm: Newton with trust region for simple bound constraints
Cause of termination: Trust region is too small: 1.0764610834657073e-08
Number of iterations: 28
Proportion of Hessian calculation: 3/3 = 100.0%
Optimization time: 0:00:00.390328
Calculate second derivatives and BHHH
It seems that the optimization algorithm did not converge. Therefore, the results may not correspond to the maximum likelihood estimator. Check the specification of the model, or the criteria for convergence of the algorithm.
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000002.iter
Parameter values restored from __b07everything_000002.iter
Starting values for the algorithm: {'asc_train_ref': -0.5648115923567126, 'asc_train_diff_GA': 1.1918184924378739, 'b_time_ref': -1.2491700483384707, 'b_time_diff_1st_class': -0.5191428199950433, 'lambda_travel_time': 0.35055111032575903, 'b_cost': -0.6599299096276461, 'mu_existing': 1.5139783161983327, 'asc_car_ref': 0.17512076808505495, 'asc_car_diff_GA': -0.6872852718009602}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 1 0.43 +
1 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 0.5 -6.5 -
2 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 0.25 -0.98 -
3 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 0.12 -0.38 -
4 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 0.062 -1.2 -
5 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 0.031 -0.72 -
6 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 0.016 -0.57 -
7 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 0.0078 -0.51 -
8 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 0.0039 -0.49 -
9 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 0.002 -0.48 -
10 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 0.00098 -0.47 -
11 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 0.00049 -0.47 -
12 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 0.00024 -0.46 -
13 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 0.00012 -0.46 -
14 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 6.1e-05 -0.46 -
15 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 3.1e-05 -0.46 -
16 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 1.5e-05 -0.46 -
17 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 7.6e-06 -0.46 -
18 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 3.8e-06 -0.46 -
19 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 1.9e-06 -0.46 -
20 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 9.5e-07 -0.46 -
21 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 4.8e-07 -0.46 -
22 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 2.4e-07 -0.46 -
23 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 1.2e-07 -0.46 -
24 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 6e-08 -0.46 -
25 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 3e-08 -0.46 -
26 -1.4 1.1 -1 0.35 -0.76 1.6 -0.38 -0.76 1.7e+04 0.16 1.5e-08 -0.46 -
Optimization algorithm has *not* converged.
Algorithm: Newton with trust region for simple bound constraints
Cause of termination: Trust region is too small: 1.4901161193847656e-08
Number of iterations: 27
Proportion of Hessian calculation: 2/2 = 100.0%
Optimization time: 0:00:04.071986
Calculate second derivatives and BHHH
It seems that the optimization algorithm did not converge. Therefore, the results may not correspond to the maximum likelihood estimator. Check the specification of the model, or the criteria for convergence of the algorithm.
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000003.iter
Parameter values restored from __b07everything_000003.iter
Starting values for the algorithm: {'asc_train': -0.652238664271019, 'b_time': -1.2789413398819158, 'b_cost': -0.7897904566401142, 'asc_car': 0.01622793815045202}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
The calculation of second derivatives generated numerical errors.
Iter. Function Relgrad Radius Rho
0 nan 1.8e+308 0.5 0 -
1 nan 1.8e+308 0.25 0 -
2 nan 1.8e+308 0.12 0 -
3 nan 1.8e+308 0.062 0 -
4 nan 1.8e+308 0.031 0 -
5 nan 1.8e+308 0.016 0 -
6 nan 1.8e+308 0.0078 0 -
7 nan 1.8e+308 0.0039 0 -
8 nan 1.8e+308 0.002 0 -
9 nan 1.8e+308 0.00098 0 -
10 nan 1.8e+308 0.00049 0 -
11 nan 1.8e+308 0.00024 0 -
12 nan 1.8e+308 0.00012 0 -
13 nan 1.8e+308 6.1e-05 0 -
14 nan 1.8e+308 3.1e-05 0 -
15 nan 1.8e+308 1.5e-05 0 -
16 nan 1.8e+308 7.6e-06 0 -
17 nan 1.8e+308 3.8e-06 0 -
18 nan 1.8e+308 1.9e-06 0 -
19 nan 1.8e+308 9.5e-07 0 -
20 nan 1.8e+308 4.8e-07 0 -
21 nan 1.8e+308 2.4e-07 0 -
22 nan 1.8e+308 1.2e-07 0 -
23 nan 1.8e+308 6e-08 0 -
24 nan 1.8e+308 3e-08 0 -
25 nan 1.8e+308 1.5e-08 0 -
Optimization algorithm has *not* converged.
Algorithm: Newton with trust region for simple bound constraints
Cause of termination: Trust region is too small: 1.4901161193847656e-08
Number of iterations: 26
Proportion of Hessian calculation: 1/1 = 100.0%
Optimization time: 0:00:02.246924
Calculate second derivatives and BHHH
It seems that the optimization algorithm did not converge. Therefore, the results may not correspond to the maximum likelihood estimator. Check the specification of the model, or the criteria for convergence of the algorithm.
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000004.iter
Parameter values restored from __b07everything_000004.iter
Starting values for the algorithm: {'asc_train_ref': -0.2618466805974923, 'asc_train_diff_GA': 1.0613276997474632, 'b_time_train_ref': -1.7301471964926143, 'b_time_train_diff_1st_class': -0.6851417736053628, 'lambda_travel_time': 0.15427514158930652, 'b_cost': -0.7011893991076099, 'mu_existing': 1.6964559166625877, 'asc_car_ref': 0.1307883751952961, 'asc_car_diff_GA': -0.3797684126660805, 'b_time_car_ref': -0.9304385795076281, 'b_time_car_diff_1st_class': -0.7863969842020704, 'b_time_swissmetro_ref': -1.46784247416871, 'b_time_swissmetro_diff_1st_class': -0.24517628021090718}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car b_time_swissmet Function Relgrad Radius Rho
0 -1.3 0.94 -0.32 0.15 -0.7 1.8 -0.64 -0.47 -0.19 -0.77 1.5e+04 0.12 10 1.2 ++
1 -1.3 0.94 -0.32 0.15 -0.7 1.8 -0.64 -0.47 -0.19 -0.77 1.5e+04 0.12 5 -0.48 -
2 -1.3 0.94 -0.32 0.15 -0.7 1.8 -0.64 -0.47 -0.19 -0.77 1.5e+04 0.12 2.5 -0.44 -
3 -1.3 0.94 -0.32 0.15 -0.7 1.8 -0.64 -0.47 -0.19 -0.77 1.5e+04 0.12 1.2 -1e+02 -
4 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 1.2 0.64 +
5 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 0.62 -93 -
6 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 0.31 -1.7 -
7 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 0.16 -0.52 -
8 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 0.078 -0.6 -
9 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 0.039 -0.22 -
10 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 0.02 -0.15 -
11 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 0.0098 -0.12 -
12 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 0.0049 -0.11 -
13 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 0.0024 -0.1 -
14 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 0.0012 -0.098 -
15 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 0.00061 -0.097 -
16 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 0.00031 -0.096 -
17 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 0.00015 -0.096 -
18 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 7.6e-05 -0.096 -
19 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 3.8e-05 -0.095 -
20 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 1.9e-05 -0.095 -
21 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 9.5e-06 -0.095 -
22 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 4.8e-06 -0.095 -
23 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 2.4e-06 -0.095 -
24 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 1.2e-06 -0.095 -
25 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 6e-07 -0.095 -
26 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 3e-07 -0.095 -
27 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 1.5e-07 -0.095 -
28 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 7.5e-08 -0.095 -
29 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 3.7e-08 -0.095 -
30 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 1.9e-08 -0.095 -
31 -0.012 0.95 0.19 0.15 -1.3 1.4 -0.61 -0.43 -0.25 -0.47 1.2e+04 0.056 9.3e-09 -0.095 -
Optimization algorithm has *not* converged.
Algorithm: Newton with trust region for simple bound constraints
Cause of termination: Trust region is too small: 9.313225746154785e-09
Number of iterations: 32
Proportion of Hessian calculation: 3/3 = 100.0%
Optimization time: 0:00:04.097104
Calculate second derivatives and BHHH
It seems that the optimization algorithm did not converge. Therefore, the results may not correspond to the maximum likelihood estimator. Check the specification of the model, or the criteria for convergence of the algorithm.
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000005.iter
Parameter values restored from __b07everything_000005.iter
Starting values for the algorithm: {'asc_train': -0.37295726674884866, 'b_time': -0.9579800087154183, 'b_cost': -0.6286908253191936, 'mu_existing': 2.0510735367894326, 'asc_car': -0.0013088324487795164}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time b_cost asc_car Function Relgrad Radius Rho
0 -0.62 -1.2 -0.77 -0.0043 8.7e+03 0.0099 10 1.1 ++
1 -0.65 -1.3 -0.79 0.013 8.7e+03 0.0034 1e+02 0.93 ++
2 -0.65 -1.3 -0.79 0.013 8.7e+03 0.0034 0.0088 -0.0093 -
3 -0.66 -1.3 -0.8 0.022 8.7e+03 0.0023 0.0088 0.46 +
4 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 0.0088 0.13 +
5 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 0.0044 2.3e-07 -
6 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 0.0022 3.3e-07 -
7 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 0.0011 5.7e-07 -
8 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 0.00055 1.1e-06 -
9 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 0.00027 2.1e-06 -
10 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 0.00014 4.2e-06 -
11 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 6.9e-05 8.3e-06 -
12 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 3.4e-05 1.6e-05 -
13 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 1.7e-05 3.3e-05 -
14 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 8.6e-06 6.6e-05 -
15 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 4.3e-06 0.00013 -
16 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 2.1e-06 0.00026 -
17 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 1.1e-06 0.00042 -
18 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 5.4e-07 0.00053 -
19 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 2.7e-07 0.00059 -
20 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 1.3e-07 0.00062 -
21 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 6.7e-08 0.00064 -
22 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 3.3e-08 0.00064 -
23 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 1.7e-08 0.00065 -
24 -0.67 -1.3 -0.79 0.03 8.7e+03 0.002 8.4e-09 0.00065 -
Optimization algorithm has *not* converged.
Algorithm: Newton with trust region for simple bound constraints
Cause of termination: Trust region is too small: 8.374050017648238e-09
Number of iterations: 25
Proportion of Hessian calculation: 5/5 = 100.0%
Optimization time: 0:00:00.328026
Calculate second derivatives and BHHH
It seems that the optimization algorithm did not converge. Therefore, the results may not correspond to the maximum likelihood estimator. Check the specification of the model, or the criteria for convergence of the algorithm.
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000006.iter
Parameter values restored from __b07everything_000006.iter
Starting values for the algorithm: {'asc_train_ref': -0.9038763313282766, 'asc_train_diff_GA': 1.6552914558969014, 'b_time': -1.6563317564858036, 'lambda_travel_time': 0.36629389447241995, 'b_cost': -0.7153731414824911, 'asc_car_ref': 0.16967858516599435, 'asc_car_diff_GA': -1.1979863573676826}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
The calculation of second derivatives generated numerical errors.
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_time_swissmet b_time_swissmet Function Relgrad Radius Rho
0 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 0.5 0 -
1 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 0.25 0 -
2 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 0.12 0 -
3 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 0.062 0 -
4 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 0.031 0 -
5 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 0.016 0 -
6 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 0.0078 0 -
7 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 0.0039 0 -
8 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 0.002 0 -
9 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 0.00098 0 -
10 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 0.00049 0 -
11 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 0.00024 0 -
12 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 0.00012 0 -
13 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 6.1e-05 0 -
14 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 3.1e-05 0 -
15 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 1.5e-05 0 -
16 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 7.6e-06 0 -
17 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 3.8e-06 0 -
18 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 1.9e-06 0 -
19 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 9.5e-07 0 -
20 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 4.8e-07 0 -
21 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 2.4e-07 0 -
22 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 1.2e-07 0 -
23 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 6e-08 0 -
24 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 3e-08 0 -
25 -0.9 1.7 0 0 0.37 -0.72 1 0.17 -1.2 0 0 0 0 nan 1.8e+308 1.5e-08 0 -
Optimization algorithm has *not* converged.
Algorithm: Newton with trust region for simple bound constraints
Cause of termination: Trust region is too small: 1.4901161193847656e-08
Number of iterations: 26
Proportion of Hessian calculation: 1/1 = 100.0%
Optimization time: 0:00:06.301246
Calculate second derivatives and BHHH
It seems that the optimization algorithm did not converge. Therefore, the results may not correspond to the maximum likelihood estimator. Check the specification of the model, or the criteria for convergence of the algorithm.
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000007.iter
Parameter values restored from __b07everything_000007.iter
Starting values for the algorithm: {'asc_train_ref': -1.1229147594851039, 'asc_train_diff_GA': 1.5209593515762057, 'b_time': -1.1946913957437961, 'b_cost': -0.7043252913610253, 'asc_car_ref': 0.014325878124396913, 'asc_car_diff_GA': -1.2616903347551596}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_1st lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 0.5 -0.32 -
1 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 0.25 -0.54 -
2 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 0.12 -0.47 -
3 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 0.062 -0.57 -
4 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 0.031 -0.52 -
5 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 0.016 -0.49 -
6 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 0.0078 -0.47 -
7 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 0.0039 -0.46 -
8 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 0.002 -0.46 -
9 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 0.00098 -0.46 -
10 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 0.00049 -0.46 -
11 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 0.00024 -0.46 -
12 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 0.00012 -0.46 -
13 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 6.1e-05 -0.46 -
14 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 3.1e-05 -0.46 -
15 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 1.5e-05 -0.46 -
16 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 7.6e-06 -0.46 -
17 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 3.8e-06 -0.46 -
18 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 1.9e-06 -0.46 -
19 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 9.5e-07 -0.46 -
20 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 4.8e-07 -0.46 -
21 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 2.4e-07 -0.46 -
22 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 1.2e-07 -0.46 -
23 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 6e-08 -0.46 -
24 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 3e-08 -0.46 -
25 -1.1 1.5 0 0 1 -0.7 1 0.014 -1.3 1.5e+04 0.28 1.5e-08 -0.46 -
Optimization algorithm has *not* converged.
Algorithm: Newton with trust region for simple bound constraints
Cause of termination: Trust region is too small: 1.4901161193847656e-08
Number of iterations: 26
Proportion of Hessian calculation: 1/1 = 100.0%
Optimization time: 0:00:04.293321
Calculate second derivatives and BHHH
It seems that the optimization algorithm did not converge. Therefore, the results may not correspond to the maximum likelihood estimator. Check the specification of the model, or the criteria for convergence of the algorithm.
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000008.iter
Parameter values restored from __b07everything_000008.iter
Starting values for the algorithm: {'asc_train_ref': -0.3120452883295302, 'asc_train_diff_GA': 1.001912783496857, 'b_time_train': -2.1492381245026957, 'square_tt_coef': -0.10641934156158749, 'cube_tt_coef': 0.0002092520001895387, 'b_cost': -0.61660744075361, 'mu_existing': 1.807637634920892, 'asc_car_ref': -0.4655164611062701, 'asc_car_diff_GA': -0.372253964913332, 'b_time_car': -1.5410984034803512, 'b_time_swissmetro': -2.1670526549119926}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
The calculation of second derivatives generated numerical errors.
Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost_train mu_existing asc_car_ref asc_car_diff_GA b_cost_car b_cost_swissmet Function Relgrad Radius Rho
0 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 0.5 0 -
1 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 0.25 0 -
2 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 0.12 0 -
3 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 0.062 0 -
4 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 0.031 0 -
5 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 0.016 0 -
6 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 0.0078 0 -
7 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 0.0039 0 -
8 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 0.002 0 -
9 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 0.00098 0 -
10 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 0.00049 0 -
11 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 0.00024 0 -
12 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 0.00012 0 -
13 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 6.1e-05 0 -
14 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 3.1e-05 0 -
15 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 1.5e-05 0 -
16 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 7.6e-06 0 -
17 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 3.8e-06 0 -
18 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 1.9e-06 0 -
19 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 9.5e-07 0 -
20 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 4.8e-07 0 -
21 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 2.4e-07 0 -
22 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 1.2e-07 0 -
23 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 6e-08 0 -
24 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 3e-08 0 -
25 -0.31 1 0 0 -0.11 0.00021 0 1.8 -0.47 -0.37 0 0 nan 1.8e+308 1.5e-08 0 -
Optimization algorithm has *not* converged.
Algorithm: Newton with trust region for simple bound constraints
Cause of termination: Trust region is too small: 1.4901161193847656e-08
Number of iterations: 26
Proportion of Hessian calculation: 1/1 = 100.0%
Optimization time: 0:00:02.102206
Calculate second derivatives and BHHH
It seems that the optimization algorithm did not converge. Therefore, the results may not correspond to the maximum likelihood estimator. Check the specification of the model, or the criteria for convergence of the algorithm.
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000009.iter
Parameter values restored from __b07everything_000009.iter
Starting values for the algorithm: {'asc_train_ref': -0.4750758669253843, 'asc_train_diff_GA': 0.9497388439687479, 'asc_train_diff_one_lugg': 0.31204676668498943, 'asc_train_diff_several_lugg': 0.1585795622354373, 'b_time_train_ref': -2.1305432448751063, 'b_time_train_diff_commuters': -0.1311026217846445, 'square_tt_coef': -0.10189791707216268, 'cube_tt_coef': 0.0001841214429738278, 'b_cost': -0.6202385313174748, 'mu_existing': 1.7914960916476963, 'asc_car_ref': -0.35759748637129496, 'asc_car_diff_GA': -0.2868706859224665, 'asc_car_diff_one_lugg': -0.08555800394819953, 'asc_car_diff_several_lugg': -0.3879147161465016, 'b_time_car_ref': -1.5476990607976204, 'b_time_car_diff_commuters': -0.16122595714026308, 'b_time_swissmetro_ref': -2.2050272112958527, 'b_time_swissmetro_diff_commuters': 0.6559357294287846}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
The calculation of second derivatives generated numerical errors.
Iter. asc_train_ref asc_train_diff_ b_time_train square_tt_coef cube_tt_coef b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car b_time_swissmet Function Relgrad Radius Rho
0 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 0.5 0 -
1 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 0.25 0 -
2 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 0.12 0 -
3 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 0.062 0 -
4 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 0.031 0 -
5 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 0.016 0 -
6 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 0.0078 0 -
7 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 0.0039 0 -
8 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 0.002 0 -
9 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 0.00098 0 -
10 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 0.00049 0 -
11 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 0.00024 0 -
12 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 0.00012 0 -
13 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 6.1e-05 0 -
14 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 3.1e-05 0 -
15 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 1.5e-05 0 -
16 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 7.6e-06 0 -
17 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 3.8e-06 0 -
18 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 1.9e-06 0 -
19 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 9.5e-07 0 -
20 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 4.8e-07 0 -
21 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 2.4e-07 0 -
22 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 1.2e-07 0 -
23 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 6e-08 0 -
24 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 3e-08 0 -
25 -0.48 0.95 0 -0.1 0.00018 -0.62 1.8 -0.36 -0.29 0 0 nan 1.8e+308 1.5e-08 0 -
Optimization algorithm has *not* converged.
Algorithm: Newton with trust region for simple bound constraints
Cause of termination: Trust region is too small: 1.4901161193847656e-08
Number of iterations: 26
Proportion of Hessian calculation: 1/1 = 100.0%
Optimization time: 0:00:04.132282
Calculate second derivatives and BHHH
It seems that the optimization algorithm did not converge. Therefore, the results may not correspond to the maximum likelihood estimator. Check the specification of the model, or the criteria for convergence of the algorithm.
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000010.iter
Parameter values restored from __b07everything_000010.iter
Starting values for the algorithm: {'asc_train_ref': -0.4752913090393947, 'asc_train_diff_GA': 1.0554925502584553, 'b_time_ref': -1.66134935056567, 'b_time_diff_1st_class': -0.663858058218675, 'square_tt_coef': -0.10343782876078673, 'cube_tt_coef': 0.00018946808675818715, 'b_cost_train': -0.7744557366852421, 'mu_existing': 1.5972849438811285, 'asc_car_ref': -0.2714518591530936, 'asc_car_diff_GA': -0.4790308217600427, 'b_cost_car': -0.23820087174260912, 'b_cost_swissmetro': -0.7406619568942464}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train b_time b_cost mu_existing asc_car Function Relgrad Radius Rho
0 0 0 0 1.6 0 1.1e+04 0.27 0.5 0 -
1 0 0 0 1.6 0 1.1e+04 0.27 0.25 0 -
2 0 0 0 1.6 0 1.1e+04 0.27 0.12 0 -
3 0 0 0 1.6 0 1.1e+04 0.27 0.062 0 -
4 0 0 0 1.6 0 1.1e+04 0.27 0.031 0 -
5 0 0 0 1.6 0 1.1e+04 0.27 0.016 0 -
6 0 0 0 1.6 0 1.1e+04 0.27 0.0078 0 -
7 0 0 0 1.6 0 1.1e+04 0.27 0.0039 0 -
8 0 0 0 1.6 0 1.1e+04 0.27 0.002 0 -
9 0 0 0 1.6 0 1.1e+04 0.27 0.00098 0 -
10 0 0 0 1.6 0 1.1e+04 0.27 0.00049 0 -
11 0 0 0 1.6 0 1.1e+04 0.27 0.00024 0 -
12 0 0 0 1.6 0 1.1e+04 0.27 0.00012 0 -
13 0 0 0 1.6 0 1.1e+04 0.27 6.1e-05 0 -
14 0 0 0 1.6 0 1.1e+04 0.27 3.1e-05 0 -
15 0 0 0 1.6 0 1.1e+04 0.27 1.5e-05 0 -
16 0 0 0 1.6 0 1.1e+04 0.27 7.6e-06 0 -
17 0 0 0 1.6 0 1.1e+04 0.27 3.8e-06 0 -
18 0 0 0 1.6 0 1.1e+04 0.27 1.9e-06 0 -
19 0 0 0 1.6 0 1.1e+04 0.27 9.5e-07 0 -
20 0 0 0 1.6 0 1.1e+04 0.27 4.8e-07 0 -
21 0 0 0 1.6 0 1.1e+04 0.27 2.4e-07 0 -
22 0 0 0 1.6 0 1.1e+04 0.27 1.2e-07 0 -
23 0 0 0 1.6 0 1.1e+04 0.27 6e-08 0 -
24 0 0 0 1.6 0 1.1e+04 0.27 3e-08 0 -
25 0 0 0 1.6 0 1.1e+04 0.27 1.5e-08 0 -
Optimization algorithm has *not* converged.
Algorithm: Newton with trust region for simple bound constraints
Cause of termination: Trust region is too small: 1.4901161193847656e-08
Number of iterations: 26
Proportion of Hessian calculation: 1/1 = 100.0%
Optimization time: 0:00:01.098165
Calculate second derivatives and BHHH
It seems that the optimization algorithm did not converge. Therefore, the results may not correspond to the maximum likelihood estimator. Check the specification of the model, or the criteria for convergence of the algorithm.
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000011.iter
Parameter values restored from __b07everything_000011.iter
Starting values for the algorithm: {'asc_train_ref': -0.2789373827601504, 'asc_train_diff_GA': 1.0420781560315255, 'b_time_train_ref': -2.1245138065407816, 'b_time_train_diff_commuters': -0.1420358785105064, 'square_tt_coef': -0.10185924023319654, 'cube_tt_coef': 0.00018545533842829882, 'b_cost': -0.6223625269104859, 'mu_existing': 1.7752125671292573, 'asc_car_ref': -0.3904504926733692, 'asc_car_diff_GA': -0.3580130831366685, 'b_time_car_ref': -1.5512858081143346, 'b_time_car_diff_commuters': -0.15185436935146773, 'b_time_swissmetro_ref': -2.1918933960382256, 'b_time_swissmetro_diff_commuters': 0.6522735604382196}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time lambda_travel_t b_cost asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho
0 -0.98 1 -0.92 2 -1.2 -0.21 -0.49 9.3e+03 0.17 1 0.5 +
1 -1.2 1.4 -1.9 2.9 -1.7 0.17 -0.7 9.2e+03 0.31 1 0.11 +
2 -1.2 1.4 -1.9 2.9 -1.7 0.17 -0.7 9.2e+03 0.31 0.5 0.041 -
3 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 0.5 0.5 +
4 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 0.25 0.012 -
5 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 0.12 0.05 -
6 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 0.062 0.064 -
7 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 0.031 0.034 -
8 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 0.016 0.044 -
9 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 0.0078 0.049 -
10 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 0.0039 0.051 -
11 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 0.002 0.052 -
12 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 0.00098 0.053 -
13 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 0.00049 0.053 -
14 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 0.00024 0.053 -
15 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 0.00012 0.054 -
16 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 6.1e-05 0.054 -
17 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 3.1e-05 0.054 -
18 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 1.5e-05 0.054 -
19 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 7.6e-06 0.054 -
20 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 3.8e-06 0.054 -
21 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 1.9e-06 0.054 -
22 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 9.5e-07 0.054 -
23 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 4.8e-07 0.054 -
24 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 2.4e-07 0.054 -
25 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 1.2e-07 0.054 -
26 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 6e-08 0.054 -
27 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 3e-08 0.054 -
28 -1.7 1.3 -2.4 2.9 -1.6 0.11 -0.72 8.9e+03 0.29 1.5e-08 0.054 -
Optimization algorithm has *not* converged.
Algorithm: Newton with trust region for simple bound constraints
Cause of termination: Trust region is too small: 1.4901161193847656e-08
Number of iterations: 29
Proportion of Hessian calculation: 4/4 = 100.0%
Optimization time: 0:00:01.194700
Calculate second derivatives and BHHH
It seems that the optimization algorithm did not converge. Therefore, the results may not correspond to the maximum likelihood estimator. Check the specification of the model, or the criteria for convergence of the algorithm.
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000012.iter
Parameter values restored from __b07everything_000012.iter
Starting values for the algorithm: {'asc_train_ref': -0.5126372452346357, 'asc_train_diff_GA': 1.200596295949923, 'b_time': -1.5007023068434566, 'lambda_travel_time': 0.3317484278077845, 'b_cost': -0.6075004253010778, 'mu_existing': 1.5766810910633084, 'asc_car_ref': 0.1762413519824659, 'asc_car_diff_GA': -0.6363956921563805}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
The calculation of second derivatives generated numerical errors.
Iter. Function Relgrad Radius Rho
0 nan 1.8e+308 0.5 0 -
1 nan 1.8e+308 0.25 0 -
2 nan 1.8e+308 0.12 0 -
3 nan 1.8e+308 0.062 0 -
4 nan 1.8e+308 0.031 0 -
5 nan 1.8e+308 0.016 0 -
6 nan 1.8e+308 0.0078 0 -
7 nan 1.8e+308 0.0039 0 -
8 nan 1.8e+308 0.002 0 -
9 nan 1.8e+308 0.00098 0 -
10 nan 1.8e+308 0.00049 0 -
11 nan 1.8e+308 0.00024 0 -
12 nan 1.8e+308 0.00012 0 -
13 nan 1.8e+308 6.1e-05 0 -
14 nan 1.8e+308 3.1e-05 0 -
15 nan 1.8e+308 1.5e-05 0 -
16 nan 1.8e+308 7.6e-06 0 -
17 nan 1.8e+308 3.8e-06 0 -
18 nan 1.8e+308 1.9e-06 0 -
19 nan 1.8e+308 9.5e-07 0 -
20 nan 1.8e+308 4.8e-07 0 -
21 nan 1.8e+308 2.4e-07 0 -
22 nan 1.8e+308 1.2e-07 0 -
23 nan 1.8e+308 6e-08 0 -
24 nan 1.8e+308 3e-08 0 -
25 nan 1.8e+308 1.5e-08 0 -
Optimization algorithm has *not* converged.
Algorithm: Newton with trust region for simple bound constraints
Cause of termination: Trust region is too small: 1.4901161193847656e-08
Number of iterations: 26
Proportion of Hessian calculation: 1/1 = 100.0%
Optimization time: 0:00:02.626202
Calculate second derivatives and BHHH
It seems that the optimization algorithm did not converge. Therefore, the results may not correspond to the maximum likelihood estimator. Check the specification of the model, or the criteria for convergence of the algorithm.
Biogeme parameters provided by the user.
*** Initial values of the parameters are obtained from the file __b07everything_000013.iter
Parameter values restored from __b07everything_000013.iter
Starting values for the algorithm: {'asc_train_ref': -0.2546034459957891, 'asc_train_diff_GA': 1.0065214028335148, 'b_time_train_ref': -2.114440443472654, 'b_time_train_diff_commuters': -0.15275489963661779, 'square_tt_coef': -0.1022017713750218, 'cube_tt_coef': 0.0001851248392559568, 'b_cost_train': -0.7051578857135951, 'mu_existing': 1.7280523288503806, 'asc_car_ref': -0.3818055601747537, 'asc_car_diff_GA': -0.37247306921770323, 'b_time_car_ref': -1.631797370998603, 'b_time_car_diff_commuters': -0.15805287500672813, 'b_cost_car': -0.5411413276386515, 'b_time_swissmetro_ref': -2.192492967550753, 'b_time_swissmetro_diff_commuters': 0.6440178099743449, 'b_cost_swissmetro': -0.6302350510248993}
Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds]
** Optimization: Newton with trust region for simple bounds
Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di square_tt_coef cube_tt_coef b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_time_swissmet b_time_swissmet Function Relgrad Radius Rho
0 -0.27 1.1 -2.5 -0.17 -0.45 0.0017 -0.5 1.7 0.62 -0.35 -1.2 -0.13 -2.5 0.61 1.3e+04 54 1 0.14 +
1 -0.27 1.1 -2.5 -0.17 -0.45 0.0017 -0.5 1.7 0.62 -0.35 -1.2 -0.13 -2.5 0.61 1.3e+04 54 0.5 -0.54 -
2 -0.27 1.1 -2.5 -0.17 -0.45 0.0017 -0.5 1.7 0.62 -0.35 -1.2 -0.13 -2.5 0.61 1.3e+04 54 0.25 -0.5 -
3 -0.27 1.1 -2.5 -0.17 -0.45 0.0017 -0.5 1.7 0.62 -0.35 -1.2 -0.13 -2.5 0.61 1.3e+04 54 0.12 -0.5 -
4 -0.27 1.1 -2.5 -0.17 -0.45 0.0017 -0.5 1.7 0.62 -0.35 -1.2 -0.13 -2.5 0.61 1.3e+04 54 0.062 -0.52 -
5 -0.27 1.1 -2.5 -0.17 -0.45 0.0017 -0.5 1.7 0.62 -0.35 -1.2 -0.13 -2.5 0.61 1.3e+04 54 0.031 -0.5 -
6 -0.27 1.1 -2.5 -0.17 -0.45 0.0017 -0.5 1.7 0.62 -0.35 -1.2 -0.13 -2.5 0.61 1.3e+04 54 0.016 -0.19 -
7 -0.27 1.1 -2.5 -0.17 -0.45 0.0017 -0.5 1.7 0.62 -0.35 -1.2 -0.13 -2.5 0.61 1.3e+04 54 0.0078 0.058 -
8 -0.27 1.1 -2.5 -0.17 -0.44 0.0096 -0.5 1.7 0.62 -0.35 -1.2 -0.13 -2.5 0.61 1.1e+04 4.6 0.0078 0.33 +
9 -0.27 1.1 -2.5 -0.17 -0.43 0.0074 -0.5 1.7 0.62 -0.35 -1.2 -0.13 -2.5 0.61 1.1e+04 1.1 0.078 1 ++
10 -0.25 1.1 -2.4 -0.16 -0.35 0.0073 -0.55 1.7 0.6 -0.37 -1.2 -0.083 -2.5 0.61 1.1e+04 13 0.78 1 ++
11 -0.25 1.1 -2.4 -0.16 -0.35 0.0073 -0.55 1.7 0.6 -0.37 -1.2 -0.083 -2.5 0.61 1.1e+04 13 0.39 1 -
12 -0.25 1.1 -2.4 -0.16 -0.35 0.0073 -0.55 1.7 0.6 -0.37 -1.2 -0.083 -2.5 0.61 1.1e+04 13 0.2 1 -
13 -0.25 1.1 -2.4 -0.16 -0.35 0.0073 -0.55 1.7 0.6 -0.37 -1.2 -0.083 -2.5 0.61 1.1e+04 13 0.098 1 -
14 -0.25 1.1 -2.4 -0.16 -0.35 0.0073 -0.55 1.7 0.6 -0.37 -1.2 -0.083 -2.5 0.61 1.1e+04 13 0.049 1 -
15 -0.25 1.1 -2.4 -0.16 -0.35 0.0073 -0.55 1.7 0.6 -0.37 -1.2 -0.083 -2.5 0.61 1.1e+04 13 0.024 1 -
16 -0.25 1.1 -2.4 -0.16 -0.35 0.0073 -0.55 1.7 0.6 -0.37 -1.2 -0.083 -2.5 0.61 1.1e+04 13 0.012 -4.3 -
17 -0.25 1.1 -2.4 -0.16 -0.35 0.0073 -0.55 1.7 0.6 -0.37 -1.2 -0.083 -2.5 0.61 1.1e+04 13 0.0061 -4.1 -
18 -0.25 1.1 -2.4 -0.16 -0.35 0.0073 -0.55 1.7 0.6 -0.37 -1.2 -0.083 -2.5 0.61 1.1e+04 13 0.0031 -0.86 -
19 -0.25 1.1 -2.4 -0.16 -0.36 0.0042 -0.55 1.6 0.6 -0.37 -1.2 -0.083 -2.5 0.61 1e+04 3.5 0.0031 0.85 +
20 -0.25 1.1 -2.4 -0.16 -0.36 0.0042 -0.55 1.6 0.6 -0.37 -1.2 -0.083 -2.5 0.61 1e+04 3.5 0.0015 -0.31 -
21 -0.25 1.1 -2.4 -0.16 -0.36 0.0042 -0.55 1.6 0.6 -0.37 -1.2 -0.083 -2.5 0.61 1e+04 3.5 0.00076 -0.46 -
22 -0.25 1.1 -2.4 -0.16 -0.36 0.0035 -0.55 1.6 0.6 -0.37 -1.2 -0.082 -2.5 0.61 1e+04 6.2 0.00076 0.49 +
23 -0.25 1.1 -2.4 -0.16 -0.35 0.0037 -0.55 1.6 0.6 -0.37 -1.2 -0.082 -2.5 0.61 1e+04 0.98 0.00076 0.82 +
24 -0.25 1.1 -2.4 -0.16 -0.35 0.0036 -0.55 1.6 0.6 -0.37 -1.2 -0.082 -2.5 0.61 1e+04 0.85 0.0076 0.93 ++
25 -0.25 1.1 -2.4 -0.16 -0.35 0.0035 -0.55 1.6 0.6 -0.37 -1.2 -0.082 -2.5 0.61 1e+04 0.36 0.076 0.98 ++
26 -0.17 1.1 -2.3 -0.15 -0.3 0.0026 -0.62 1.6 0.59 -0.38 -1.2 -0.069 -2.5 0.6 9.9e+03 0.87 0.076 0.81 +
27 -0.097 1.2 -2.3 -0.15 -0.32 0.003 -0.69 1.5 0.59 -0.39 -1.1 -0.056 -2.6 0.6 9.7e+03 0.37 0.076 0.64 +
28 -0.028 1.2 -2.2 -0.14 -0.28 0.0023 -0.76 1.5 0.6 -0.41 -1.1 -0.042 -2.7 0.59 9.5e+03 0.35 0.076 0.67 +
29 0.035 1.2 -2.2 -0.13 -0.3 0.0027 -0.84 1.4 0.61 -0.42 -1.1 -0.031 -2.7 0.59 9.4e+03 0.67 0.076 0.54 +
30 0.089 1.2 -2.1 -0.13 -0.26 0.002 -0.92 1.4 0.63 -0.43 -1 -0.02 -2.8 0.59 9.3e+03 1.2 0.076 0.56 +
31 0.14 1.2 -2.1 -0.12 -0.28 0.0023 -0.99 1.3 0.64 -0.44 -1 -0.011 -2.8 0.58 9.3e+03 0.74 0.076 0.46 +
32 0.18 1.3 -2 -0.12 -0.24 0.0017 -1.1 1.3 0.65 -0.45 -0.98 -0.0019 -2.9 0.58 9.2e+03 1.4 0.076 0.38 +
33 0.22 1.3 -2 -0.12 -0.26 0.002 -1.1 1.3 0.67 -0.46 -0.95 0.0048 -2.9 0.58 9.2e+03 0.52 0.076 0.4 +
34 0.22 1.3 -2 -0.12 -0.26 0.002 -1.1 1.3 0.67 -0.46 -0.95 0.0048 -2.9 0.58 9.2e+03 0.52 0.038 -0.18 -
35 0.23 1.3 -2 -0.12 -0.23 0.0016 -1.2 1.3 0.67 -0.47 -0.94 0.0084 -3 0.58 9.2e+03 0.45 0.038 0.18 +
36 0.25 1.3 -2 -0.11 -0.25 0.002 -1.2 1.3 0.68 -0.47 -0.93 0.011 -3 0.58 9.1e+03 0.52 0.038 0.35 +
37 0.25 1.3 -2 -0.11 -0.25 0.002 -1.2 1.3 0.68 -0.47 -0.93 0.011 -3 0.58 9.1e+03 0.52 0.019 0.095 -
38 0.26 1.3 -2 -0.11 -0.24 0.0017 -1.2 1.3 0.68 -0.47 -0.92 0.012 -3 0.58 9.1e+03 0.24 0.019 0.32 +
39 0.27 1.3 -2 -0.11 -0.25 0.0019 -1.3 1.3 0.69 -0.47 -0.92 0.013 -3 0.58 9.1e+03 0.13 0.019 0.27 +
40 0.27 1.3 -2 -0.11 -0.24 0.0017 -1.3 1.3 0.69 -0.48 -0.91 0.015 -3 0.58 9.1e+03 0.11 0.019 0.25 +
41 0.28 1.3 -2 -0.11 -0.24 0.0018 -1.3 1.3 0.69 -0.48 -0.9 0.016 -3 0.58 9.1e+03 0.098 0.019 0.24 +
42 0.29 1.3 -2 -0.11 -0.23 0.0017 -1.3 1.3 0.69 -0.48 -0.9 0.017 -3.1 0.58 9.1e+03 0.11 0.019 0.23 +
43 0.29 1.3 -1.9 -0.11 -0.24 0.0017 -1.3 1.3 0.69 -0.48 -0.89 0.018 -3.1 0.58 9.1e+03 0.1 0.019 0.22 +
44 0.3 1.3 -1.9 -0.11 -0.23 0.0017 -1.4 1.3 0.7 -0.49 -0.89 0.019 -3.1 0.57 9.1e+03 0.11 0.019 0.21 +
45 0.31 1.3 -1.9 -0.11 -0.23 0.0017 -1.4 1.3 0.7 -0.49 -0.88 0.02 -3.1 0.57 9.1e+03 0.1 0.019 0.2 +
46 0.31 1.3 -1.9 -0.11 -0.23 0.0016 -1.4 1.3 0.7 -0.49 -0.88 0.021 -3.1 0.57 9.1e+03 0.1 0.019 0.19 +
47 0.32 1.3 -1.9 -0.11 -0.23 0.0017 -1.4 1.3 0.7 -0.49 -0.88 0.022 -3.1 0.57 9.1e+03 0.13 0.019 0.18 +
48 0.32 1.3 -1.9 -0.11 -0.23 0.0016 -1.4 1.3 0.7 -0.5 -0.87 0.023 -3.1 0.57 9.1e+03 0.1 0.019 0.17 +
49 0.33 1.3 -1.9 -0.11 -0.23 0.0016 -1.4 1.3 0.71 -0.5 -0.87 0.024 -3.1 0.57 9.1e+03 0.6 0.019 0.16 +
50 0.34 1.3 -1.9 -0.11 -0.23 0.0016 -1.5 1.3 0.71 -0.5 -0.86 0.025 -3.2 0.57 9.1e+03 0.1 0.019 0.16 +
51 0.34 1.3 -1.9 -0.11 -0.23 0.0016 -1.5 1.3 0.71 -0.5 -0.86 0.025 -3.2 0.57 9.1e+03 0.87 0.019 0.15 +
52 0.35 1.3 -1.9 -0.11 -0.23 0.0016 -1.5 1.3 0.71 -0.51 -0.85 0.026 -3.2 0.57 9.1e+03 0.1 0.019 0.15 +
53 0.35 1.3 -1.9 -0.11 -0.22 0.0015 -1.5 1.3 0.71 -0.51 -0.85 0.027 -3.2 0.57 9.1e+03 0.31 0.019 0.14 +
54 0.36 1.3 -1.9 -0.11 -0.22 0.0015 -1.5 1.3 0.71 -0.51 -0.85 0.027 -3.2 0.57 9e+03 0.099 0.019 0.14 +
55 0.36 1.3 -1.9 -0.11 -0.22 0.0015 -1.6 1.3 0.71 -0.51 -0.84 0.028 -3.2 0.57 9e+03 0.099 0.019 0.13 +
56 0.37 1.3 -1.9 -0.11 -0.22 0.0015 -1.6 1.3 0.72 -0.52 -0.84 0.028 -3.2 0.57 9e+03 0.099 0.019 0.13 +
57 0.37 1.3 -1.9 -0.11 -0.22 0.0015 -1.6 1.3 0.72 -0.52 -0.84 0.029 -3.2 0.57 9e+03 0.099 0.019 0.12 +
58 0.38 1.3 -1.9 -0.11 -0.22 0.0015 -1.6 1.3 0.72 -0.52 -0.83 0.029 -3.2 0.57 9e+03 0.43 0.019 0.11 +
59 0.38 1.3 -1.9 -0.11 -0.22 0.0015 -1.6 1.3 0.72 -0.52 -0.83 0.03 -3.3 0.57 9e+03 0.098 0.019 0.11 +
60 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.52 -0.82 0.03 -3.3 0.57 9e+03 0.18 0.019 0.11 +
61 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 0.019 0.1 +
62 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 0.0095 0.099 -
63 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 0.0048 0.099 -
64 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 0.0024 0.098 -
65 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 0.0012 0.098 -
66 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 0.0006 0.098 -
67 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 0.0003 0.097 -
68 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 0.00015 0.097 -
69 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 7.5e-05 0.095 -
70 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 3.7e-05 0.091 -
71 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 1.9e-05 0.084 -
72 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 9.3e-06 0.07 -
73 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 4.7e-06 0.039 -
74 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 2.3e-06 -0.027 -
75 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 2.3e-06 0.2 +
76 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 1.2e-06 0.066 -
77 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 1.2e-06 0.18 +
78 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.076 -
79 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.15 +
80 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
81 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
82 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
83 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
84 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
85 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
86 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
87 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
88 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
89 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
90 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
91 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
92 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
93 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
94 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
95 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
96 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
97 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
98 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
99 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
100 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
101 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
102 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
103 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
104 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
105 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
106 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
107 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
108 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
109 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
110 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
111 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
112 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
113 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
114 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
115 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
116 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
117 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
118 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
119 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
120 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
121 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
122 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
123 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
124 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
125 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
126 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
127 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
128 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
129 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
130 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
131 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
132 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
133 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
134 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
135 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
136 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
137 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
138 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
139 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
140 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
141 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
142 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
143 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
144 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
145 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
146 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
147 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
148 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
149 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
150 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
151 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
152 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
153 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
154 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
155 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
156 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
157 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
158 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
159 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
160 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
161 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
162 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
163 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
164 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.12 +
165 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
166 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
167 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
168 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
169 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
170 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
171 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
172 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
173 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
174 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
175 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
176 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
177 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
178 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
179 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
180 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
181 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
182 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
183 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
184 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
185 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
186 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
187 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
188 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
189 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
190 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
191 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
192 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
193 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
194 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
195 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
196 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
197 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
198 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
199 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
200 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.12 +
201 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
202 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
203 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
204 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
205 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
206 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
207 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
208 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
209 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
210 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
211 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
212 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
213 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
214 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
215 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
216 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
217 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
218 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
219 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
220 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
221 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
222 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
223 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
224 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
225 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
226 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
227 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
228 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
229 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
230 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
231 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
232 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
233 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
234 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
235 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
236 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.12 +
237 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
238 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
239 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
240 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
241 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
242 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
243 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
244 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
245 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
246 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
247 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
248 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
249 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
250 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
251 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
252 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
253 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
254 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
255 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
256 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
257 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
258 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
259 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
260 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
261 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
262 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
263 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
264 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
265 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
266 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
267 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
268 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
269 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
270 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
271 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
272 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
273 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
274 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.12 +
275 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
276 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
277 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
278 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
279 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
280 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
281 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
282 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
283 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
284 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
285 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
286 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
287 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
288 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
289 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
290 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
291 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
292 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
293 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
294 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
295 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
296 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
297 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
298 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
299 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
300 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
301 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
302 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
303 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
304 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
305 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
306 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
307 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
308 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
309 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
310 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
311 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
312 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
313 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
314 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
315 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
316 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
317 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
318 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
319 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
320 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
321 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
322 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
323 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
324 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
325 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
326 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
327 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
328 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
329 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
330 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
331 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
332 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
333 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
334 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
335 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
336 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
337 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
338 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
339 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
340 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
341 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
342 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
343 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
344 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
345 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
346 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
347 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
348 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
349 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
350 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
351 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
352 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
353 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
354 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
355 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
356 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
357 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
358 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
359 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
360 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
361 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
362 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
363 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
364 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
365 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
366 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
367 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
368 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
369 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
370 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
371 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
372 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
373 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
374 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
375 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
376 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
377 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
378 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
379 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
380 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
381 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
382 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
383 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
384 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
385 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
386 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
387 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
388 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
389 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
390 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
391 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
392 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
393 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
394 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
395 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
396 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
397 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
398 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
399 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
400 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
401 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
402 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
403 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
404 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
405 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
406 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
407 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
408 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
409 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
410 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
411 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
412 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
413 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
414 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
415 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
416 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
417 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
418 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
419 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
420 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
421 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
422 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
423 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
424 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
425 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
426 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
427 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
428 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
429 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
430 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
431 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
432 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
433 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
434 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
435 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
436 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
437 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
438 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
439 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
440 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
441 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
442 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
443 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
444 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
445 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
446 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
447 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
448 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
449 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
450 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
451 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
452 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
453 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
454 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
455 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
456 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
457 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
458 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
459 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
460 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
461 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
462 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
463 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
464 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
465 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
466 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
467 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
468 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
469 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
470 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
471 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
472 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
473 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
474 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
475 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
476 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
477 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
478 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
479 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
480 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
481 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
482 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
483 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
484 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
485 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
486 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
487 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
488 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
489 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
490 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
491 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
492 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
493 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
494 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
495 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
496 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
497 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
498 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
499 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
500 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
501 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
502 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
503 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
504 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
505 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
506 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
507 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
508 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
509 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
510 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
511 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
512 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
513 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
514 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
515 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
516 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
517 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
518 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
519 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
520 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
521 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
522 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
523 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
524 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
525 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
526 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
527 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
528 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
529 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
530 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
531 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
532 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
533 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
534 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
535 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
536 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
537 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
538 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
539 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
540 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
541 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
542 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
543 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
544 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
545 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
546 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
547 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
548 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
549 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
550 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
551 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
552 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
553 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
554 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
555 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
556 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
557 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
558 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
559 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
560 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
561 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
562 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
563 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
564 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
565 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
566 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
567 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
568 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
569 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
570 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
571 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
572 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
573 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
574 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
575 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
576 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
577 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
578 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
579 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
580 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
581 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
582 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
583 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
584 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
585 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
586 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
587 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
588 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
589 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
590 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
591 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
592 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
593 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
594 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
595 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
596 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
597 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
598 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
599 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
600 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
601 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
602 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
603 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
604 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
605 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
606 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
607 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
608 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
609 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
610 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
611 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
612 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
613 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
614 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
615 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
616 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
617 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
618 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
619 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
620 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
621 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
622 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
623 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
624 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
625 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
626 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
627 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
628 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
629 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
630 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
631 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
632 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
633 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
634 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
635 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
636 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
637 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
638 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
639 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
640 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
641 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
642 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
643 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
644 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
645 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
646 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
647 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
648 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
649 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
650 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
651 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
652 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
653 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
654 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
655 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
656 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
657 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
658 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
659 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
660 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
661 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
662 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
663 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
664 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
665 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
666 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
667 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
668 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
669 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
670 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
671 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
672 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
673 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
674 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
675 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
676 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
677 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
678 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
679 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
680 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
681 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
682 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
683 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
684 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
685 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
686 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
687 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
688 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
689 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
690 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
691 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
692 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
693 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
694 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
695 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
696 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
697 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
698 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
699 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
700 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
701 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
702 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
703 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
704 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
705 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
706 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
707 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
708 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
709 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
710 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
711 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
712 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
713 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
714 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
715 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
716 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
717 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
718 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
719 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
720 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
721 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
722 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
723 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
724 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
725 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
726 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
727 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
728 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
729 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
730 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
731 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
732 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
733 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
734 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
735 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
736 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
737 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
738 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
739 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
740 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
741 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
742 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
743 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
744 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
745 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
746 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
747 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
748 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
749 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
750 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
751 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
752 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
753 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
754 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
755 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
756 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
757 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
758 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
759 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
760 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
761 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
762 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
763 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
764 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
765 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
766 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
767 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
768 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
769 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
770 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
771 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
772 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
773 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
774 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
775 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
776 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
777 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
778 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
779 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
780 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
781 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
782 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
783 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
784 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
785 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
786 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
787 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
788 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
789 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
790 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
791 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
792 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
793 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
794 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
795 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
796 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
797 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
798 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
799 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
800 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
801 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
802 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
803 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
804 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
805 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
806 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
807 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
808 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
809 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
810 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
811 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
812 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
813 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
814 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
815 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
816 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
817 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
818 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
819 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
820 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
821 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
822 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
823 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
824 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
825 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
826 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
827 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
828 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
829 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
830 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
831 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
832 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
833 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
834 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
835 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
836 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
837 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
838 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
839 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
840 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
841 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
842 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
843 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
844 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
845 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
846 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
847 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
848 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
849 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
850 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
851 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
852 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
853 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
854 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
855 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
856 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
857 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
858 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
859 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
860 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
861 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
862 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
863 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
864 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
865 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
866 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
867 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
868 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
869 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
870 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
871 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
872 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
873 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
874 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
875 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
876 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
877 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
878 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
879 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
880 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
881 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
882 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
883 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
884 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
885 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
886 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
887 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
888 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
889 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
890 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
891 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
892 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
893 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
894 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
895 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
896 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
897 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
898 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
899 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
900 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
901 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
902 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
903 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
904 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
905 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
906 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
907 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
908 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
909 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
910 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
911 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
912 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
913 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
914 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
915 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
916 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
917 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
918 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
919 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
920 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
921 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
922 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
923 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
924 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
925 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
926 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
927 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
928 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
929 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
930 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
931 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
932 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
933 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
934 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
935 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
936 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
937 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
938 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
939 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
940 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
941 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
942 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
943 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
944 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
945 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
946 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
947 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
948 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
949 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
950 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
951 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
952 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
953 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
954 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
955 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
956 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
957 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
958 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
959 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
960 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
961 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
962 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
963 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
964 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
965 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
966 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
967 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
968 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
969 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
970 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
971 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
972 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
973 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
974 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
975 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
976 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
977 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
978 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
979 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
980 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
981 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
982 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
983 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
984 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
985 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
986 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
987 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
988 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
989 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
990 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
991 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
992 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
993 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
994 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
995 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
996 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.33 +
997 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.32 +
998 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.11 +
999 0.39 1.3 -1.9 -0.11 -0.22 0.0014 -1.7 1.3 0.72 -0.53 -0.82 0.031 -3.3 0.57 9e+03 0.098 5.8e-07 0.14 +
Optimization algorithm has *not* converged.
Algorithm: Newton with trust region for simple bound constraints
Cause of termination: Maximum number of iterations reached: 1000
Number of iterations: 1000
Proportion of Hessian calculation: 967/967 = 100.0%
Optimization time: 0:01:04.658348
Calculate second derivatives and BHHH
It seems that the optimization algorithm did not converge. Therefore, the results may not correspond to the maximum likelihood estimator. Check the specification of the model, or the criteria for convergence of the algorithm.
Pareto: 14
Considered: 422
Removed: 46
print(f'A total of {len(non_dominated_models)} models have been generated.')
A total of 14 models have been generated.
compiled_results, specs = compile_estimation_results(
non_dominated_models, use_short_names=True
)
display(compiled_results)
Model_000000 ... Model_000013
Number of estimated parameters 20 ... 14
Sample size 10719 ... 10719
Final log likelihood -8009.406 ... -16830.89
Akaike Information Criterion 16058.81 ... 33689.78
Bayesian Information Criterion 16204.41 ... 33791.69
asc_train_ref (t-test) -0.457 (-4.26) ... 0.39 (1.16)
asc_train_diff_GA (t-test) 0.914 (10.3) ... 1.33 (7.69)
asc_train_diff_one_lugg (t-test) 0.322 (4.93) ...
asc_train_diff_several_lugg (t-test) 0.165 (1.06) ...
b_time_train_ref (t-test) -2.12 (-21.3) ... -1.85 (-1.8)
b_time_train_diff_commuters (t-test) -0.143 (-0.887) ... -0.108 (-0.057)
square_tt_coef (t-test) -0.102 (-24.7) ... -0.217 (-40.8)
cube_tt_coef (t-test) 0.000184 (8.21) ... 0.00143 (1.71)
b_cost_train (t-test) -0.702 (-7.6) ...
mu_existing (t-test) 1.74 (17.4) ... 1.25 (14.9)
asc_car_ref (t-test) -0.348 (-4.47) ... 0.721 (1.78)
asc_car_diff_GA (t-test) -0.303 (-2.52) ... -0.528 (-1.98)
asc_car_diff_one_lugg (t-test) -0.0864 (-1.82) ...
asc_car_diff_several_lugg (t-test) -0.387 (-2.17) ...
b_time_car_ref (t-test) -1.63 (-17.3) ... -0.821 (-1.66)
b_time_car_diff_commuters (t-test) -0.168 (-0.909) ... 0.0306 (0.0143)
b_cost_car (t-test) -0.539 (-7.32) ...
b_time_swissmetro_ref (t-test) -2.21 (-24.1) ... -3.28 (-2.44)
b_time_swissmetro_diff_commuters (t-test) 0.647 (2.68) ... 0.574 (0.178)
b_cost_swissmetro (t-test) -0.628 (-12.9) ...
b_time (t-test) ...
b_cost (t-test) ... -1.68 (-7.35)
lambda_travel_time (t-test) ...
b_time_train (t-test) ...
b_time_car (t-test) ...
b_time_swissmetro (t-test) ...
asc_train (t-test) ...
asc_car (t-test) ...
b_time_train_diff_1st_class (t-test) ...
b_time_car_diff_1st_class (t-test) ...
b_time_swissmetro_diff_1st_class (t-test) ...
b_time_ref (t-test) ...
b_time_diff_1st_class (t-test) ...
[38 rows x 14 columns]
Glossary
for short_name, spec in specs.items():
print(f'{short_name}\t{spec}')
Model_000000 asc:GA-LUGGAGE;b_cost_gen_altspec:altspec;b_time:COMMUTERS;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:power
Model_000001 asc:GA;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:logit;train_tt_catalog:linear
Model_000002 asc:GA;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:nested existing;train_tt_catalog:boxcox
Model_000003 asc:GA;b_cost_gen_altspec:altspec;b_time:COMMUTERS;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:power
Model_000004 asc:GA;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:boxcox
Model_000005 asc:no_seg;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:logit;train_tt_catalog:linear
Model_000006 asc:GA;b_cost_gen_altspec:generic;b_time:FIRST;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:boxcox
Model_000007 asc:GA;b_cost_gen_altspec:generic;b_time:FIRST;b_time_gen_altspec:generic;model_catalog:nested existing;train_tt_catalog:boxcox
Model_000008 asc:GA;b_cost_gen_altspec:altspec;b_time:FIRST;b_time_gen_altspec:generic;model_catalog:nested existing;train_tt_catalog:power
Model_000009 asc:GA;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:power
Model_000010 asc:no_seg;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:nested existing;train_tt_catalog:linear
Model_000011 asc:GA;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:logit;train_tt_catalog:boxcox
Model_000012 asc:GA-LUGGAGE;b_cost_gen_altspec:generic;b_time:COMMUTERS;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:power
Model_000013 asc:GA;b_cost_gen_altspec:generic;b_time:COMMUTERS;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:power
Total running time of the script: (9 minutes 8.668 seconds)