LebesgueMeasure

class probnum.quad.LebesgueMeasure(domain, input_dim=None, normalized=False)

Bases: IntegrationMeasure

Lebesgue measure on a hyper-rectangle.

Parameters
  • domain (DomainLike) – Domain of integration. Contains lower and upper bound as a scalar or np.ndarray.

  • input_dim (Optional[IntLike]) – Dimension of the integration domain. If not given, inferred from domain.

  • normalized (bool) – Boolean which controls whether or not the measure is normalized (i.e., integral over the domain is one). Defaults to False.

Return type

None

Methods Summary

__call__(points)

Evaluate the density function of the integration measure.

sample(n_sample[, rng])

Sample n_sample points from the integration measure.

Methods Documentation

__call__(points)[source]

Evaluate the density function of the integration measure.

Parameters

points (ndarray) – shape=(n_points, input_dim) – Input locations.

Returns

shape=(n_points,) – Density evaluated at given locations.

Return type

density_evals

sample(n_sample, rng=Generator(PCG64) at 0x7FCE084D3900)[source]

Sample n_sample points from the integration measure.

Parameters
  • n_sample (IntLike) – Number of points to be sampled

  • rng (Optional[Generator]) – Random number generator. Optional. Default is np.random.default_rng().

Returns

shape=(n_sample,input_dim) – Sampled points

Return type

points