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SobolEngine

class torch.quasirandom.SobolEngine(dimension, scramble=False, seed=None) [source]

The torch.quasirandom.SobolEngine is an engine for generating (scrambled) Sobol sequences. Sobol sequences are an example of low discrepancy quasi-random sequences.

This implementation of an engine for Sobol sequences is capable of sampling sequences up to a maximum dimension of 1111. It uses direction numbers to generate these sequences, and these numbers have been adapted from here.

References

  • Art B. Owen. Scrambling Sobol and Niederreiter-Xing points. Journal of Complexity, 14(4):466-489, December 1998.
  • I. M. Sobol. The distribution of points in a cube and the accurate evaluation of integrals. Zh. Vychisl. Mat. i Mat. Phys., 7:784-802, 1967.
Parameters
  • dimension (Int) – The dimensionality of the sequence to be drawn
  • scramble (bool, optional) – Setting this to True will produce scrambled Sobol sequences. Scrambling is capable of producing better Sobol sequences. Default: False.
  • seed (Int, optional) – This is the seed for the scrambling. The seed of the random number generator is set to this, if specified. Otherwise, it uses a random seed. Default: None

Examples:

>>> soboleng = torch.quasirandom.SobolEngine(dimension=5)
>>> soboleng.draw(3)
tensor([[0.5000, 0.5000, 0.5000, 0.5000, 0.5000],
        [0.7500, 0.2500, 0.7500, 0.2500, 0.7500],
        [0.2500, 0.7500, 0.2500, 0.7500, 0.2500]])
draw(n=1, out=None, dtype=torch.float32) [source]

Function to draw a sequence of n points from a Sobol sequence. Note that the samples are dependent on the previous samples. The size of the result is (n,dimension)(n, dimension) .

Parameters
  • n (Int, optional) – The length of sequence of points to draw. Default: 1
  • out (Tensor, optional) – The output tensor
  • dtype (torch.dtype, optional) – the desired data type of the returned tensor. Default: torch.float32
fast_forward(n) [source]

Function to fast-forward the state of the SobolEngine by n steps. This is equivalent to drawing n samples without using the samples.

Parameters

n (Int) – The number of steps to fast-forward by.

reset() [source]

Function to reset the SobolEngine to base state.

© 2019 Torch Contributors
Licensed under the 3-clause BSD License.
https://pytorch.org/docs/1.7.0/generated/torch.quasirandom.SobolEngine.html