benchmarkfcns.multifidelity.beale

benchmarkfcns.multifidelity.beale(arg0: Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]', 'flags.c_contiguous']) → Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]']

Computes the value of the multi-fidelity Beale function. SCORES = beale(X) computes the value of the Beale function at point X. multifidelity.beale accepts a matrix of size M-by-2 and returns a matrix SCORES of size M-by-2.

Mathematical Definition

\[f(x, y) = (1.5-x+xy)^2+(2.25-x+xy^2)^2+(2.625-x+xy^3)^2\]

Visualization