skopt.sampler
.Hammersly¶
- class skopt.sampler.Hammersly(min_skip=0, max_skip=0, primes=None)[source][source]¶
Creates
Hammersley
sequence samples.The Hammersley set is equivalent to the Halton sequence, except for one dimension is replaced with a regular grid. It is not recommended to generate a Hammersley sequence with more than 10 dimension.
For
dim == 1
the sequence falls back to Van Der Corput sequence.- Parameters
- min_skipint, default=-1
Minimum skipped seed number. When
min_skip != max_skip
and both are > -1, a random number is picked.- max_skipint, default=-1
Maximum skipped seed number. When
min_skip != max_skip
and both are > -1, a random number is picked.- primestuple, default=None
The (non-)prime base to calculate values along each axis. If empty, growing prime values starting from 2 will be used.
References
T-T. Wong, W-S. Luk, and P-A. Heng, “Sampling with Hammersley and Halton Points,” Journal of Graphics Tools, vol. 2, no. 2, 1997, pp. 9 - 24.
Methods
generate
(dimensions, n_samples[, random_state])Creates samples from Hammersly set.
set_params
(**params)Set the parameters of this initial point generator.
- generate(dimensions, n_samples, random_state=None)[source][source]¶
Creates samples from Hammersly set.
- Parameters
- dimensionslist, shape (n_dims,)
List of search space dimensions. Each search dimension can be defined either as
a
(lower_bound, upper_bound)
tuple (forReal
orInteger
dimensions),a
(lower_bound, upper_bound, "prior")
tuple (forReal
dimensions),as a list of categories (for
Categorical
dimensions), oran instance of a
Dimension
object (Real
,Integer
orCategorical
).
- n_samplesint
The order of the Hammersley sequence. Defines the number of samples.
- random_stateint, RandomState instance, or None (default)
Set random state to something other than None for reproducible results.
- Returns
- np.array, shape=(n_dim, n_samples)
Hammersley set.