def generate(seed):
random_state = RandomState(seed)
common_params = dict(variables=50,
constraints=100,
random_state=random_state)
return instances.construct_feasible_bounded(
variable_types=generators.generate_variable_types(
**common_params, prob_integer=random_state.uniform(0.5, 1.0)),
lhs=generators.generate_lhs(
**common_params,
density=random_state.uniform(low=0.1, high=1.0),
pv=random_state.uniform(low=0.0, high=1.0),
pc=random_state.uniform(low=0.0, high=1.0),
coeff_loc=random_state.uniform(low=-2.0, high=2.0),
coeff_scale=random_state.uniform(low=0.1, high=1.0),
),
alpha=generators.generate_alpha(
**common_params,
frac_violations=random_state.uniform(low=0.1, high=1.0),
beta_param=random_state.lognormal(mean=-0.2, sigma=1.8),
mean_primal=0,
std_primal=1,
mean_dual=0,
std_dual=1,
),
beta=generators.generate_beta(**common_params,
basis_split=random_state.uniform(
low=0.0, high=1.0)),
)
