medeq.LatticeSampler#

class medeq.LatticeSampler(d, seed=None)[source]#

Bases: object

Parameter sampler following a regular lattice - this also corresponds to a full factorial design of experiments.

MED samplers return values between [0, 1), which can then be upscaled to individual parameter ranges.

Parameters
dint

Sampling dimensionality - i.e. number of parameters.

seedint, optional

Seed for deterministic random sampling.

Examples

Simple, seeded sample generation:

import medeq
sampler = medeq.RandomSampler(3, seed=123)
sampler.sample(5, None)
__init__(d, seed=None)[source]#

Methods

__init__(d[, seed])

sample(n[, med])

sample(n, med=None)[source]#