StochasticRunConfig API Reference
Bases: BaseModel
Configuration object for defining stochastic or optimization variable distributions.
Each parameter is described by a tuple specifying the distribution type and its numeric bounds.
Attributes:
| Name | Type | Description |
|---|---|---|
n_samples |
(int, optional)
|
Number of Monte-Carlo samples. |
k_s_scale, k_p, insu_z, insu_dr, insu_k, m_flow, Tin, H, |
|
|
epsilon, alfa, Tgrad, Q, fluid_percent, r_out |
tuple(str, float, float)
|
Triplets defining: [dist_type, dist1, dist2, (optional dist3)] where dist_type ∈ {"normal", "uniform", "lognormal", "triangular"}. |
Notes
if dist_name == "normal": mean, std_dev = dist[1], dist[2]
elif dist_name == "uniform": min, max = dist[1], dist[2]
elif dist_name == "lognormal": mu, sigma = dist[1], dist[2]
elif dist_name == "triangular": min, peak, max = dist[1], dist[2], dist[3]