benchmarkfcns.rosenbrock

benchmarkfcns.rosenbrock(arg0: Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]', 'flags.c_contiguous']) → Annotated[numpy.typing.NDArray[numpy.float64], '[m, 1]']

Computes the value of the Rosenbrock benchmark function. SCORES = rosenbrock(X) computes the value of the Rosenbrock function at point X. rosenbrock accepts a matrix of size M-by-N and returns a vector SCORES of size M-by-1 in which each row contains the function value for the corresponding row of X. Properties:

  • Global minimum: 0

  • Location of global minimum: (1, 1, …, 1)

  • Number of dimensions: n

  • Recommended domain: [-5, 5]^n

  • Number of local minima: many (the “banana-shaped” valley creates a long, narrow

    region of local minima)

  • Number of global minima: 1

  • Convexity: non-convex

  • Separability: non-separable

  • Modality: unimodal

  • Symmetry: non-symmetric

  • Differentiable: Yes

For more information, please visit: benchmarkfcns.info/doc/rosenbrockfcn

Mathematical Definition

Visualization

rosenbrock landscape