benchmarkfcns.dropwave

benchmarkfcns.dropwave(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 Drop-Wave benchmark function. SCORES = dropwave(X) computes the value of the Drop-Wave function at point X. dropwave accepts a matrix of size M-by-2 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: -1

  • Location of global minimum: (0, 0)

  • Number of dimensions: 2

  • Recommended domain: [-5.12, 5.12]^2

  • Number of local minima: many

  • Number of global minima: 1

  • Convexity: non-convex

  • Separability: non-separable

  • Modality: multimodal

  • Symmetry: radial symmetry

  • Differentiable: Yes

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

Mathematical Definition

Visualization

dropwave landscape