sobol_sampling.py

import numpy as np
from scipy.stats.qmc import Sobol

dimensions = 42 # number of primers
seed = 1424
m = 8
num_codes = 2
sparse_factor = 0.125

def generate_sobol_samples(dimensions, seed, m, num_codes):
  sobol_sampler = Sobol(d=dimensions, seed=seed)
  sobol_samples = sobol_sampler.random_base2(m=m)
  generated_codes = np.floor(sobol_samples * num_codes)
  return generated_codes

def generate_sparse_sobol_samples(dimensions, seed, m, sparse_factor):
  sobol_sampler = Sobol(d=dimensions, seed=seed)
  sobol_samples = sobol_sampler.random_base2(m=m)
  sparse_codes = np.floor(sobol_samples / (1 - sparse_factor))
  return sparse_codes