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sensitivity.sensitivity_sampling

Sampling-based sensitivity and uncertainty analysis.

This module implements a sampling-based sensitivity and uncertainty analysis approach. Model parameters are varied simultaneously within their bounds, and the resulting distribution of model outputs is analyzed statistically.

Parameter samples are generated using Latin Hypercube Sampling (LHS), assuming independent and uniformly distributed parameters.

For each analysis group and output variable, descriptive statistics are computed, including:

  • mean and median
  • standard deviation and coefficient of variation
  • minimum and maximum
  • lower and upper quantiles (5% and 95%)

Uncertainty is calculated as Ui,j = (Percentile97.5(i,j) - Percentile2.5(i,j)) / Percentile50(i,j)

This approach focuses on uncertainty propagation rather than variance-based sensitivity indices and is therefore complementary to local and Sobol-based methods.

SamplingSensitivityAnalysis 

SamplingSensitivityAnalysis(
    sensitivity_simulation,
    parameters,
    groups,
    results_path,
    N,
    seed=None,
    n_cores=None,
    cache_results=False,
)

Bases: SensitivityAnalysis

Sensitivity/uncertainty analysis based on sampling.

Initialize the sampling analysis with N samples per group.

create_samples 

create_samples()

Create LHS samples.

Latin hypercube sampling (LHS) is a stratified sampling method used to generate near‑random samples from a multidimensional distribution for Monte Carlo simulations and computer experiments.

Assuming uniform distributions within the provided bounds.

Use LHS sampling of parameters.

calculate_sensitivity 

calculate_sensitivity(cache_filename=None, cache=False)

Calculate the sensitivity matrices for sampling sensitivity.

df_sampling_sensitivity 

df_sampling_sensitivity(df_path)

Write the sampling sensitivities as a table to the given path.

plot_data 

plot_data(
    type, show_jitter=True, show_violin=True, **kwargs
)

Boxplots for the sampled output.

plot 

plot(**kwargs)

Boxplots for the Sampling sensitivity.