cosapp.utils.surrogate_models.nn_interpolators.nn_base

Define the NNBase class.

Classes

NNBase(training_points, training_values[, ...])

Base class for common functionality between nearest neighbor interpolants.
class cosapp.utils.surrogate_models.nn_interpolators.nn_base.NNBase(training_points, training_values, num_leaves=2)[source]

Bases: object

Base class for common functionality between nearest neighbor interpolants.

_tpm
ndarray of shape (1 x independent dims) containing the minimum in each dimension of

the training input locations.

Type:

ndarray

_tpr

ndarray of shape (1x independent dims) containing the range of each dimension of the training input locations.

Type:

ndarray

_tvm

ndarray of shape (1 x independent dims) containing the minimum in each dimension of the training output values.

Type:

ndarray

_tvr

ndarray of shape (1x independent dims) containing the range of each dimension of the training output values.

Type:

ndarray

_tp

ndarray of shape (num_points x independent dims) containing normalized training input locations.

Type:

ndarray

_tv

ndarray of shape (num_points x independent dims) containing normalized training output values.

Type:

ndarray

_indep_dims

Number of independent dims

Type:

int

_dep_dims

Number of dependent dims

Type:

int

_ntpts

Number of training points

Type:

int

_KData

KDTree used for finding the nearest neighbors.

Type:

scipy.spatial.cKDTree

_pt_cache

Internal cache of the last found neighbors.

Type:

tuple(ndarray, ndarray, ndarray)