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data
data
 
 
models
models
 
 
saving_folder
saving_folder
 
 
README.md
README.md
 
 
RL_to_combine_search_methods.ipynb
RL_to_combine_search_methods.ipynb
 
 
benchmarking_samplers.ipynb
benchmarking_samplers.ipynb
 
 
boltzmann_wealth_model.ipynb
boltzmann_wealth_model.ipynb
 
 
cors_sampler.ipynb
cors_sampler.ipynb
 
 
docker-sir.py
docker-sir.py
 
 
finding_the_parameters_of_a_SIR_model.ipynb
finding_the_parameters_of_a_SIR_model.ipynb
 
 
learning_moments_using_neural_nets.ipynb
learning_moments_using_neural_nets.ipynb
 
 
likelihood_and_posterior_Brock_and_Hommes.ipynb
likelihood_and_posterior_Brock_and_Hommes.ipynb
 
 
main.py
main.py
 
 
overview_of_plotting_functions.ipynb
overview_of_plotting_functions.ipynb
 
 
overview_of_the_different_samplers.ipynb
overview_of_the_different_samplers.ipynb
 
 
particle_swarm_sampler.ipynb
particle_swarm_sampler.ipynb
 
 
slack_stock_price_shock.ipynb
slack_stock_price_shock.ipynb
 
 
tests_on_toy_model.ipynb
tests_on_toy_model.ipynb
 
 

README.md

Examples folder

In this folder you can find several scripts and notebooks that illustrate how to use Black-it. Many of these examples are calibrations of the test models located in the models folder.

The easiest way to experiment with the examples is to clone the git repository

git clone https://github.com/bancaditalia/black-it.git

enter into the examples folder

cd black-it/examples

run the chosen example script

python main.py

or open a Jupyter notebook session

jupyter notebook boltzmann_wealth_model.ipynb

Note that some examples will require you to install other packages in order to run properly, simply follow the instructions provided in the corresponding file.