pub enum SamplingScheme {
InSample,
OutOfSample,
External,
Historical,
}Expand description
Forward-pass noise source for multi-stage optimization solvers.
Determines where the forward-pass scenario realisations come from.
This is orthogonal to NoiseMethod,
which controls how the opening tree is generated during the backward
pass. SamplingScheme selects the source of forward-pass noise;
NoiseMethod selects the algorithm used to produce backward-pass
openings.
See Input Scenarios §1.8 for the full catalog.
§Examples
use cobre_core::scenario::SamplingScheme;
let scheme = SamplingScheme::InSample;
// SamplingScheme is Copy
let copy = scheme;
assert_eq!(scheme, copy);Variants§
InSample
Forward pass uses the same opening tree generated for the backward pass. This is the default for the minimal viable solver.
OutOfSample
Forward pass generates fresh noise on-the-fly from the same distribution as the opening tree, using an independent seed.
External
Forward pass draws from an externally supplied scenario file.
Historical
Forward pass replays historical inflow realisations in sequence or at random.
Trait Implementations§
Source§impl Clone for SamplingScheme
impl Clone for SamplingScheme
Source§fn clone(&self) -> SamplingScheme
fn clone(&self) -> SamplingScheme
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source. Read more