integers#
- Halton.integers(l_bounds, *, u_bounds=None, n=1, endpoint=False, workers=1)[source]#
- Draw n integers from l_bounds (inclusive) to u_bounds (exclusive), or if endpoint=True, l_bounds (inclusive) to u_bounds (inclusive). - Parameters:
- l_boundsint or array-like of ints
- Lowest (signed) integers to be drawn (unless - u_bounds=None, in which case this parameter is 0 and this value is used for u_bounds).
- u_boundsint or array-like of ints, optional
- If provided, one above the largest (signed) integer to be drawn (see above for behavior if - u_bounds=None). If array-like, must contain integer values.
- nint, optional
- Number of samples to generate in the parameter space. Default is 1. 
- endpointbool, optional
- If true, sample from the interval - [l_bounds, u_bounds]instead of the default- [l_bounds, u_bounds). Defaults is False.
- workersint, optional
- Number of workers to use for parallel processing. If -1 is given all CPU threads are used. Only supported when using - HaltonDefault is 1.
 
- Returns:
- samplearray_like (n, d)
- QMC sample. 
 
 - Notes - It is safe to just use the same - [0, 1)to integer mapping with QMC that you would use with MC. You still get unbiasedness, a strong law of large numbers, an asymptotically infinite variance reduction and a finite sample variance bound.- To convert a sample from \([0, 1)\) to \([a, b), b>a\), with \(a\) the lower bounds and \(b\) the upper bounds, the following transformation is used: \[\text{floor}((b - a) \cdot \text{sample} + a)\]