sampling.mm.mm_improvement_contour

sampling.mm.mm_improvement_contour(
    X_base,
    x1=np.linspace(0, 1, 100),
    x2=np.linspace(0, 1, 100),
    q=2,
    p=2,
)

Generates a contour plot of the Morris-Mitchell improvement over a grid defined by x1 and x2.

Parameters

Name	Type	Description	Default
X_base	np.ndarray	Base design points.	required
x1	np.ndarray	Grid values for the first dimension. Default is np.linspace(0, 1, 100).	np.linspace(0, 1, 100)
x2	np.ndarray	Grid values for the second dimension. Default is np.linspace(0, 1, 100).	np.linspace(0, 1, 100)
q	int	Morris-Mitchell metric parameter. Default is 2.	2
p	int	Morris-Mitchell metric parameter. Default is 2.	2

Returns: None: Displays a contour plot of the Morris-Mitchell improvement.

Examples

>>> import numpy as np
    from spotoptim.sampling.mm import mm_improvement_contour
    X_base = np.array([[0.1, 0.1], [0.2, 0.2], [0.7, 0.7]])
    mm_improvement_contour(X_base)