yaocptool.stochastic package

Submodules

yaocptool.stochastic.pce module

class PCEConverter(socp, pc_order=3, n_samples=None, **kwargs)

Bases: object

__init__(socp, pc_order=3, n_samples=None, **kwargs)

Parameters:

• socp (StochasticOCP) – Stochastic Optimal Control Problem
• pc_order (int) – order of the polynomial, for the polynomial approximation. (default: 3)
• n_samples (int) – number of samples of the parameters. If None is provided, the minimum number of samples will be used, depending on the number of uncertain parameters and polynomial order
• kwargs –

convert_socp_to_ocp_with_pce()

n_pol_parameters

n_uncertain

get_ls_factor(n_uncertain, n_samples, pc_order, lamb=0.0)

yaocptool.stochastic.util module

sample_parameter_log_normal_distribution_with_sobol(mean, covariance, n_samples=1)

Sample parameter using Sobol sampling with a log-normal distribution.

Parameters:

• mean –
• covariance –
• n_samples –

Returns:

sample_parameter_normal_distribution_with_sobol(mean, covariance, n_samples=1)

Sample parameter using Sobol sampling with a normal distribution.

Parameters:

• mean –
• covariance –
• n_samples –

Returns:

Module contents