nemos.basis.RaisedCosineLogEval.evaluate_on_grid#

RaisedCosineLogEval.evaluate_on_grid(n_samples)[source]#

Evaluate the basis set on a grid of equi-spaced sample points.

Parameters:

n_samples (int) – The number of points in the uniformly spaced grid. A higher number of samples will result in a more detailed visualization of the basis functions.

Return type:

Tuple[NDArray, NDArray]

Returns:

  • X – Array of shape (n_samples,) containing the equi-spaced sample points where we’ve evaluated the basis.

  • basis_funcs – Raised cosine basis functions, shape (n_samples, n_basis_funcs)

Examples

>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> from nemos.basis import RaisedCosineLogEval
>>> n_basis_funcs = 5
>>> decay_rates = np.array([0.01, 0.02, 0.03, 0.04, 0.05]) # sample decay rates
>>> window_size=10
>>> ortho_basis = RaisedCosineLogEval(n_basis_funcs)
>>> sample_points, basis_values = ortho_basis.evaluate_on_grid(100)