athena.kas.KernelActiveSubspaces.fit

KernelActiveSubspaces.fit(inputs=None, outputs=None, gradients=None, weights=None, metric=None)[source]

Compute the kernel based active subspaces given the inputs and the gradients of the model function wrt the input parameters, or given the input/outputs couples. Only two methods are available: ‘exact’ and ‘local’.

Parameters

  • inputs (numpy.ndarray) – array n_samples-by-n_params containing the points in the original parameter space.

  • outputs (numpy.ndarray) – array n_samples-by-1 containing the values of the model function.

  • gradients (numpy.ndarray) – array n_samples-by-n_params containing the gradient samples oriented as rows.

  • weights (numpy.ndarray) – n_samples-by-1 weight vector, corresponds to numerical quadrature rule used to estimate matrix whose eigenspaces define the active subspace.

  • metric (numpy.ndarray) – metric matrix output_dim-by-output-dim for vectorial active subspaces.

Raises

TypeError, ValueError