benchmarkfcns.multifidelity.currin

benchmarkfcns.multifidelity.currin(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 Currin function. SCORES = currin(X) computes the value of the Currin function at point X. multifidelity.currin accepts a matrix of size M-by-2 and returns a matrix SCORES of size M-by-2. Properties (High-fidelity):

  • Dimensions: 2

  • Recommended domain: [0, 1]^2

Mathematical Definition

Visualization

currin landscape