def test_genome_store_states(genome, model): global activities loci = model.loci target = pd.TimeSeries() predictions = [] test_iter = model.dataset.test_data_iterator() test_number = 1 i = 0 activities = [] for (data_in, data_out) in test_iter(): cln_data = data_in if model.cleaning_disabled else \ model.clean_func(data_in, genome, loci, model.day) activities.append([]) model_out = esn.feedback_with_external_input( cln_data, genome, loci, model.day, reservoir_hook=_state_monitor) error = model.error_func(model_out, data_out) print "Error for test at %s: %f" % (str(model_out.index[0]), error) test_number += 1 target = target.combine_first(data_out) predictions.append(model_out) i += 1 if i == 30: break return target, predictions
def _esn_feedback_with_hook(data, genome, loci, prediction_steps): return esn.feedback_with_external_input( data, genome, loci, prediction_steps, reservoir_hook=_state_monitor)