bilby.core.sampler.dynesty_utils.propose_differetial_evolution
- bilby.core.sampler.dynesty_utils.propose_differetial_evolution(u, live, n, n_cluster, rstate, mix=0.5, scale=1)[source]
Propose a new point using ensemble differential evolution (ter Braak + (2006)).
\[u_{\rm prop} = u + \gamma (v_{a} - v_{b})\]We consider two choices for \(\gamma\): weighted by
mix.\(\gamma = 1\): this is a mode-hopping mode for efficiently exploring multi-modal spaces
\(\gamma \sim \Gamma\left(\gamma; k=4, \theta=\frac{\kappa}{4}\right)\)
Here \(\kappa = 2.38 / \sqrt{2 n}\) unless specified by the user and we scale by a random draw from a Gamma distribution. The specific distribution was chosen somewhat arbitrarily to have mean and mode close to \(\kappa\) and give good acceptance and autocorrelation times on a subset of problems.
- Parameters:
- u: np.ndarray
The current point.
- live: np.ndarray
The ensemble of live points to select \(v\) from.
- n: int
The number of dimensions being explored
- n_cluster: int
The number of dimensions to run the differential evolution over, the first
n_clusterdimensions are used. The rest are randomly sampled from the prior.- rstate: np.random.RandomState
The random state to use to generate random numbers.
- mix: float
The fraction of proposed points that should follow the specified scale rather than mode hopping.
default=0.5- scale: float
The amount to scale the difference vector by.
default = 2.38 / (2 * n_cluster)**0.5)
- Returns:
- u_prop: np.ndarray
The proposed point.