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)