def secret_post(request):
"""Function left for legacy reasons. TODO: remove after db migration"""
response_data = {}
status = 400
if request.method == "POST":
print request.POST.items()
response_data['result'] = 'OK'
status = 200
try:
point = DataPoint(
node_id = request.POST.get('node_id'),
temperature = request.POST.get('temperature'),
rh = request.POST.get('rh'),
dylos_bin_1 = request.POST.get('dylos_bin_1'),
dylos_bin_2 = request.POST.get('dylos_bin_2'),
dylos_bin_3 = request.POST.get('dylos_bin_3'),
dylos_bin_4 = request.POST.get('dylos_bin_4'),
alphasense_1 = request.POST.get('alphasense_1'),
alphasense_2 = request.POST.get('alphasense_2'),
alphasense_3 = request.POST.get('alphasense_3'),
alphasense_4 = request.POST.get('alphasense_4'),
alphasense_5 = request.POST.get('alphasense_5'),
alphasense_6 = request.POST.get('alphasense_6'),
alphasense_7 = request.POST.get('alphasense_7'),
alphasense_8 = request.POST.get('alphasense_8'),
reading_time = request.POST.get('reading_time'))
point.save()
except Exception as e:
response_data['result'] = 'FAILED'
response_data['msg'] = str(e)
status = 400
return HttpResponse(json.dumps(response_data), content_type="application/json", status=status)
def setUp(self):
self.client = Client()
new_user = get_user_model().objects.create_user(**USER)
new_user.save()
new_data = DataPoint(**DATA_POINT)
new_data.save()
def setUp(self):
new_data = DataPoint(**DATA_POINT)
new_data.save()
new_error = ErrorReport(molecule="CON_24a",
email="*****@*****.**",
urgency=1,
message="This is a message")
new_error.save()
def run_all(force=False):
pred = Predictor.objects.latest()
latest = DataPoint.objects.latest()
if not force and latest.created < pred.created:
logger.info("No Update")
return
logger.info("Loading Data")
X, H**O, LUMO, GAP = DataPoint.get_all_data()
y = numpy.hstack([H**O, LUMO, GAP])
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.1)
logger.info("Building Model")
params = {"gamma": [1e-5, 1e-3, 1e-1, 1e1, 1e3],
"C": [1e-5, 1e-3, 1e-1, 1e1, 1e3]}
inner_model = GridSearchCV(estimator=svm.SVR(kernel="rbf"),
param_grid=params)
model = MultiStageRegression(model=inner_model)
model.fit(X_train, y_train)
errors = numpy.abs(model.predict(X_test) - y_test).mean(0)
logger.info("Errors: %s" % errors)
save_model(model, errors)
def createDataPoints(apps, schema_editor):
old_TemperatureDataPoint = apps.get_model("data", "TemperatureDataPoint")
old_tdps = old_TemperatureDataPoint.objects.all();
DataPoint.objects.bulk_create([
DataPoint(id=x.id, date=x.date, device=x.device) for x in old_TemperatureDataPoint.objects.all()
])
