Tutorials

Work in progress!

But here a simple example from our README.md:

from queens.distributions import BetaDistribution, NormalDistribution, UniformDistribution
from queens.drivers import FunctionDriver
from queens.global_settings import GlobalSettings
from queens.iterators import MonteCarloIterator
from queens.main import run_iterator
from queens.models import SimulationModel
from queens.parameters import Parameters
from queens.schedulers import LocalScheduler

if __name__ == "__main__":
    # Set up the global settings
    global_settings = GlobalSettings(experiment_name="monte_carlo_uq", output_dir=".")

    # Set up the uncertain parameters
    x1 = UniformDistribution(lower_bound=-3.14, upper_bound=3.14)
    x2 = NormalDistribution(mean=0.0, covariance=1.0)
    x3 = BetaDistribution(lower_bound=-3.14, upper_bound=3.14, a=2.0, b=5.0)
    parameters = Parameters(x1=x1, x2=x2, x3=x3)

    # Set up the model
    driver = FunctionDriver(parameters=parameters, function="ishigami90")
    scheduler = LocalScheduler(
        experiment_name=global_settings.experiment_name, num_jobs=2, num_procs=4
    )
    model = SimulationModel(scheduler=scheduler, driver=driver)

    # Set up the algorithm
    iterator = MonteCarloIterator(
        model=model,
        parameters=parameters,
        global_settings=global_settings,
        seed=42,
        num_samples=1000,
        result_description={"write_results": True, "plot_results": True},
    )

    # Start QUEENS run
    run_iterator(iterator, global_settings=global_settings)

Resulting in the histogram: