surrogate.kernels.SpotOptimKernel

surrogate.kernels.SpotOptimKernel(
    theta,
    var_type,
    p_val=2.0,
    metric_factorial='canberra',
)

Kernel designed for SpotOptim’s Kriging with mixed variable support.

It handles continuous (‘float’), integer (‘int’), and categorical (‘factor’) variables similarly to the internal logic of the Kriging class.

The correlation function is defined as: Psi = exp(- (D_ordered + D_factor))

where: D_ordered = sum_j theta_j * |x_ij - y_lj|^p (for ordered variables) D_factor = sum_j theta_j * d(x_ij, y_lj) (for factor variables, d is metric like Canberra)

Parameters

Name	Type	Description	Default
theta	np.ndarray	The correlation parameters (weights). Note: In standard Kriging usage, this corresponds to 10^theta_log. This kernel expects the LINEAR scale theta values (weights), not log.	required
var_type	list of str	List of variable types, e.g. [‘float’, ‘int’, ‘factor’].	required
p_val	float	Power parameter for ordered distance. Defaults to 2.0.	2.0
metric_factorial	str	Metric for factor distance (passed to cdist/pdist). Defaults to ‘canberra’.	'canberra'