def optimize_chemist(func_caller,
worker_manager,
budget,
mode=None,
init_pool=None,
acq='hei',
options=None,
reporter='default'):
""" Chemist optimization from a function caller. """
if options is None:
reporter = get_reporter(reporter)
options = load_options(all_chemist_args, reporter=reporter)
# TODO: what is this option?
if acq is not None:
options.acq = acq
if mode is not None:
options.mode = mode
# Initial queries
if not hasattr(options,
'pre_eval_points') or options.pre_eval_points is None:
if init_pool is None:
init_pool = get_initial_pool()
options.get_initial_points = lambda n: init_pool[:n]
return (Chemist(func_caller,
worker_manager,
options=options,
reporter=reporter)).optimise(budget)
def get_mol_opt_arguments():
""" Returns arguments for NN Optimisation. """
ret = Namespace()
ret.ga_init_pool = get_initial_pool()
ret.ga_init_vals = [mol_func(mol) for mol in ret.ga_init_pool]
ret.mol_domain = MolDomain()
return ret
def prep_optimiser_args(obj_func, optimiser_args):
""" Returns the options and reporter. """
reporter = get_reporter('default')
options = load_options(optimiser_args, reporter=reporter)
options.pre_eval_points = get_initial_pool()
options.pre_eval_vals = [obj_func(mol) for mol in options.pre_eval_points]
options.pre_eval_true_vals = options.pre_eval_vals
options_clone = deepcopy(options)
return options, options_clone, reporter
def _set_up_acq_opt_ga(self):
self.ga_init_pool = get_initial_pool()
self.ga_mutation_op = lambda x: x
# In future, implement Domains:
# # The initial pool
# self.ga_init_pool = get_initial_pool(self.domain.get_type())
# # The number of evaluations
if self.get_acq_opt_max_evals is None:
#lead_const = min(5, self.domain.get_dim())**2
lead_const = 25
self.get_acq_opt_max_evals = lambda t: np.clip(
lead_const * int(np.sqrt(t)), 50, 500)
def __init__(self, fitness_func, initial_pool=None, max_pool_size=None):
"""
Params:
:fitness_func: function to optimize over evolution
:initial_pool: just what it says
:max_pool_size: int or None
TODO:
:mutation_op: mutates a given Molecule
:crossover_op: takes two Molecules
and returns one new Molecule
"""
self.fitness_func = fitness_func
self.synth = RexgenForwardSynthesizer()
if initial_pool is None:
initial_pool = get_initial_pool()
self.pool = initial_pool
self.max_pool_size = max_pool_size