benchmarkfcns.multifidelity.shubert¶
- benchmarkfcns.multifidelity.shubert(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 Shubert function. SCORES = shubert(X) computes the value of the Shubert function at point X. multifidelity.shubert accepts a matrix of size M-by-N and returns a matrix SCORES of size M-by-2.
Mathematical Definition
\[f(\mathbf{x})=f(x_1, ...,x_n)=\prod_{i=1}^{n}{\left(\sum_{j=1}^5{ cos((j+1)x_i+j)}\right)}\]
Visualization
|
|
|
|
|
|
|
|
|
|