"""
File: 02-aggregation.py

Michel Bierlaire
Sat Aug 02 2025, 18:41:06
"""

# The objective of this laboratory is to calculate aggregated indicators from a choice model. We consider the model
# specification available in the file `netherlands_model.py`.

# We want to calculate the market shares (and corresponding confidence intervals) for each of the two alternatives in
# the population using sample enumeration.

# We consider four segments of the population, characterized by two age categories  (41 or older, and 40 or younger),
# and gender.

# The census data report the following number $N_g$ of individuals in each segment $g$ of the population.
census = {
    'male_41_more': 4092390,
    'male_40_less': 4151092,
    'female_41_more': 3984028,
    'female_40_less': 4428289,
}


# Question 1: calculate a weight for each entry in the file `netherlands.dat` so that the sample is representative
# of the population.

# Question 2: calculate the market shares for each of the two alternatives. First, the model should be obtained
# from the specification file and the parameters should be estimated. To calculate the choice probability of each
# of the two alternatives, we can use the syntax below:
# ```
# simulate = {
#    'Weight': Weight,
#    'Prob. rail': prob_rail,
#    'Prob. car': prob_car,
# }
#
# biosim = BIOGEME(database, simulate)
# simulated_values = biosim.simulate(results.getBetaValues())
# ```


# Question 3: calculate confidence intervals on the market shares calculated above. Note that, to do so, the model must
# be estimated using bootstrapping as shown below:
# ```
# results_bootstrapping = biogeme.estimate(bootstrap=100)
# ```

# We obtain a sample of values for the parameters. Using simulation, we can calculate the 90% confidence intervals on
# the simulated quantities as follows:
# ```
# betas = biogeme.freeBetaNames()
# b = results_bootstrapping.getBetasForSensitivityAnalysis(betas)
# left, right = biosim.confidenceIntervals(b, 0.9)
# ```

# Question 4: consider a scenario where the cost of rail is decreased by 10%. What would be the market shares (and the
# confidence intervals) under this scenario? To do so, we should first write the choice probability under the proposed
# scenario and then perform the simulation as shown in the previous steps.