VolterraBasis.basis.FEMScalarFeatures

class VolterraBasis.basis.FEMScalarFeatures(basis)[source]

Finite elements features for scalar basis

Wrapper to finite element basis from scikit-fem Parameters ———- basis: skfem basis

A finite element basis. Should be a scalar basis (H1 or global element)

__init__(basis)[source]

Wrapper to finite element basis from scikit-fem Parameters ———- basis: skfem basis

A finite element basis. Should be a scalar basis (H1 or global element)

fit_transform(X, y=None, **fit_params)

Fit to data, then transform it.

Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X.

Parameters:
Xarray-like of shape (n_samples, n_features)

Input samples.

yarray-like of shape (n_samples,) or (n_samples, n_outputs), default=None

Target values (None for unsupervised transformations).

**fit_paramsdict

Additional fit parameters.

Returns:
X_newndarray array of shape (n_samples, n_features_new)

Transformed array.

set_output(*, transform=None)

Set output container.

See Introducing the set_output API for an example on how to use the API.

Parameters:
transform{“default”, “pandas”}, default=None

Configure output of transform and fit_transform.

  • “default”: Default output format of a transformer

  • “pandas”: DataFrame output

  • None: Transform configuration is unchanged

Returns:
selfestimator instance

Estimator instance.

Examples using VolterraBasis.basis.FEMScalarFeatures

Memory Kernel Estimation with the usual GLE

Memory Kernel Estimation with the usual GLE