adaptive_approximate

pyapprox.surrogates.adaptive_approximate(fun, variable, method, options=None)[source]

Adaptive approximation of a scalar or vector-valued function of one or more variables. These methods choose the samples to at which to evaluate the function being approximated.

Parameters:
funcallable

The function to be minimized

fun(z) -> np.ndarray

where z is a 2D np.ndarray with shape (nvars,nsamples) and the output is a 2D np.ndarray with shaoe (nsamples,nqoi)

methodstring

Type of approximation. Should be one of

  • ‘sparse_grid’

  • ‘polynomial_chaos’

  • ‘gaussian_process’

Returns:
resultpyapprox.surrogates.approximate.ApproximateResult

Result object. For more details see

  • pyapprox.surrogates.approximate.adaptive_approximate_sparse_grid()

  • pyapprox.surrogates.approximate.adaptive_approximate_polynomial_chaos()

  • pyapprox.surrogates.approximate.adaptive_approximate_gaussian_process()