benchmarkfcns.multifidelity.friedman

benchmarkfcns.multifidelity.friedman(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 Friedman function. SCORES = friedman(X) computes the value of the Friedman function at point X. multifidelity.friedman accepts a matrix of size M-by-5 and returns a matrix SCORES of size M-by-2. Properties (High-fidelity):

  • Dimensions: 5

  • Recommended domain: [0, 1]^5

Mathematical Definition

Visualization

friedman landscape