def run(model_creator_class):
"""Main entry point for specific models. model_creator is an instance of a
class used to set up the model and the data."""
get_options()
if not is_mpi_slave(options):
timer = SimpleTimer()
prev_handler = np.seterrcall(float_err_handler)
prev_err = np.seterr(all='call')
np.seterr(under='ignore')
random.seed(options.seed)
np.random.seed(options.seed)
model_creator = model_creator_class(options)
model = model_creator.get_model()
if not is_mpi_slave(options):
_print_sim_context(model.dataset)
_run_models([model], model.dataset)
ul.tempfeeder_exp().close()
def run(model_creator_class):
"""Main entry point for specific models. model_creator is an instance of a
class used to set up the model and the data."""
get_options()
if not is_mpi_slave(options):
timer = SimpleTimer()
prev_handler = np.seterrcall(float_err_handler)
prev_err = np.seterr(all='call')
np.seterr(under='ignore')
random.seed(options.seed)
np.random.seed(options.seed)
model_creator = model_creator_class(options)
model = model_creator.get_model()
if not is_mpi_slave(options):
_print_sim_context(model.dataset)
_run_models([model], model.dataset)
ul.tempfeeder_exp().close()
def _run_models(models, dataset):
data_desc = dataset.desc
for model in models:
if not is_mpi_slave(options):
print "Optimizing parameters for model", model.name, "."
run_GA(model, options)
if is_mpi_slave(options):
continue
raw_genes = pu.raw_genes(model.genome, strip=True)
print "Best genes found during evolution: ", raw_genes
target, predictions = test_genome(raw_genes, model)
_save_test_prediction(target, predictions, data_desc)
error = concat_and_calc_error(predictions, target, model.error_func)
print "Error on test phase for best genome found, " \
"%s, %i days: %5.4f" % (data_desc, len(predictions), error)
if not options.no_plot:
plot_test_prediction(target, predictions, model.name, data_desc,
model.error_func)
def _run_models(models, dataset):
data_desc = dataset.desc
for model in models:
if not is_mpi_slave(options):
print "Optimizing parameters for model", model.name, "."
run_GA(model, options)
if is_mpi_slave(options):
continue
raw_genes = pu.raw_genes(model.genome, strip=True)
print "Best genes found during evolution: ", raw_genes
target, predictions = test_genome(raw_genes, model)
_save_test_prediction(target, predictions, data_desc)
error = concat_and_calc_error(predictions, target, model.error_func)
print "Error on test phase for best genome found, " \
"%s, %i days: %5.4f" % (data_desc, len(predictions), error)
if not options.no_plot:
plot_test_prediction(target, predictions,
model.name, data_desc, model.error_func)