scimba_torch.integration.monte_carlo_time

A uniform time sampler for Monte Carlo methods.

Classes

UniformTimeSampler(bound)

A class used to sample uniformly distributed time points within a given bound.
class UniformTimeSampler(bound)[source]

Bases: object

A class used to sample uniformly distributed time points within a given bound.

Parameters:

bound (tuple[float, float]) – A tuple representing the lower and upper bounds for sampling.

Raises:

  • TypeError – If time interval is not a Sequence of two int or float.

  • ValueError – If lower bound is greater than upper bound.

bound

A tuple representing the lower and upper bounds for sampling.

sample(n)[source]

Generate a sample of random numbers within the specified bounds.

Parameters:

n (int) – The number of samples to generate.

Return type:

LabelTensor

Returns:

A tensor containing the generated samples and corresponding labels.

Raises:

  • TypeError – If argument is not an integer.

  • ValueError – If argument is negative.