def predict(request, neironet_id):
net = get_object_or_404(NeuralNet, pk=neironet_id)
try:
loaded_net = loadNet(net.neironet_file)
data_list = []
data_string = ""
for i in range(0, net.number_of_inputs):
value = request.POST['quote_' + str(i)].replace(',', '.').strip()
data_list.append(float(value))
data_string += value + ', '
prediction_result = loaded_net.activate(data_list)[0]
print prediction_result
except (IOError, NeuralNet.DoesNotExist):
# Redisplay the poll voting form.
return render_to_response('neironet_detail.html', {
'net': net,
'error_message': "Wrong net file.",
},
context_instance=RequestContext(request))
else:
pred = Prediction(neiro_net=net,
input_data=data_string[:-2],
output_data=prediction_result,
predicted_on_date=now().date() + timedelta(days=1))
pred.save()
context = RequestContext(request, {
'prediction': pred,
})
# Always return an HttpResponseRedirect after successfully dealing
# with POST data. This prevents data from being posted twice if a
# user hits the Back button.
return HttpResponseRedirect(
reverse('prediction_research.views.prediction_detail',
args=(pred.id, )))
def predict(request, neironet_id):
net = get_object_or_404(NeuralNet, pk=neironet_id)
try:
loaded_net = loadNet(net.neironet_file)
data_list = []
data_string = ""
for i in range(0, net.number_of_inputs):
value = request.POST['quote_' + str(i)].replace(',', '.').strip()
data_list.append(float(value))
data_string += value + ', '
prediction_result = loaded_net.activate(data_list)[0]
print prediction_result
except (IOError, NeuralNet.DoesNotExist):
# Redisplay the poll voting form.
return render_to_response('neironet_detail.html', {
'net': net,
'error_message': "Wrong net file.",
}, context_instance=RequestContext(request))
else:
pred = Prediction(neiro_net=net, input_data=data_string[:-2], output_data=prediction_result,
predicted_on_date=now().date()+timedelta(days=1))
pred.save()
context = RequestContext(request, {
'prediction': pred,
})
# Always return an HttpResponseRedirect after successfully dealing
# with POST data. This prevents data from being posted twice if a
# user hits the Back button.
return HttpResponseRedirect(reverse('prediction_research.views.prediction_detail', args=(pred.id,)))
def makePrediction(self, input_data_list, predicted_on_date, is_auto):
loaded_net = loadNet(self.neuronet_file)
prediction_result = loaded_net.activate(input_data_list)[0]
input_data_string = ", ".join(map(str, input_data_list))
pred = Prediction(neiro_net=self, input_data=input_data_string, output_data=prediction_result,
predicted_on_date=predicted_on_date, prediction_is_automate=is_auto)
pred.save()
def makePrediction(self, input_data_list, predicted_on_date, is_auto):
loaded_net = loadNet(self.neuronet_file)
prediction_result = loaded_net.activate(input_data_list)[0]
input_data_string = ", ".join(map(str, input_data_list))
pred = Prediction(neiro_net=self,
input_data=input_data_string,
output_data=prediction_result,
predicted_on_date=predicted_on_date,
prediction_is_automate=is_auto)
pred.save()
def makeAutomatePrediction():
net_qs = NeuralNet.objects.all()
count_usd_quotes = 4
count_oil_quotes = 2
today = now().date()
quotes_qs = []
if len(net_qs) == 0:
print "No neironets for prediction"
for net in net_qs:
try:
print net.name
loaded_net = loadNet(net.neironet_file)
if Quote.objects.filter(quote_date=today):
prediction_date = today
else:
prediction_date = today - timedelta(days=1)
if len(
Prediction.objects.filter(
neiro_net=net,
prediction_date__gte=today,
prediction_is_automate='Y')) == 0:
quotes_qs = Quote.objects.filter(quote_date__gt=prediction_date - timedelta(days=count_usd_quotes),
quote_date__lte=prediction_date, quote_type='usd') | \
Quote.objects.filter(quote_date__gt=prediction_date - timedelta(days=count_oil_quotes),
quote_date__lte=prediction_date, quote_type='brent')
if len(quotes_qs) == net.number_of_inputs:
quotes_list = []
for quote in quotes_qs.order_by('-quote_type',
'quote_date'):
quotes_list.append(quote.quote_value)
prediction_result = loaded_net.activate(quotes_list)[0]
print prediction_result
data_string = ", ".join(map(str, quotes_list))
pred = Prediction(neiro_net=net,
input_data=data_string,
output_data=prediction_result,
predicted_on_date=prediction_date +
timedelta(days=1),
prediction_is_automate='Y')
pred.save()
else:
print "Not enough parameters for prediction"
else:
print "Today automatic prediction already exist"
except IOError:
print "Neironet file is not exist"