benchmarkfcns.multifidelity.heterogeneous

benchmarkfcns.multifidelity.heterogeneous(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 Heterogeneous (Mainini) function. SCORES = heterogeneous(X) computes the value of the Heterogeneous function at point X. multifidelity.heterogeneous accepts a matrix of size M-by-1 and returns a matrix SCORES of size M-by-2.

Mathematical Definition

\[\begin{aligned}\]

f_{lf}(x) &= sin(30(x - 0.9)^4) cos(2(x - 0.9)) + frac{x - 0.9}{2} \ f_{hf}(x) &= frac{f_{lf}(x) - 1.0 + x}{1.0 + 0.25x} end{aligned}

Visualization

No visualization available for this function.