def handle(self, **options):
grower = GrowerInfo.objects.get(pk=1)
basin = grower.basin_set.all()[0]
self.ds = FewsJdbcDataSource(basin)
tbl = DemandTable()
model = CalculationModel(tbl, self.ds)
now = datetime.datetime.now(pytz.utc)
history = now - datetime.timedelta(days=1)
future = now + datetime.timedelta(days=5)
now = round_date(now)
history = round_date(history)
future = round_date(future)
self.mkplot('history', history, now)
self.mkplot('span', history, future)
self.mkplot('future', now, future)
now = mktim(2012, 8, 5, 8, 0) # some rain fell here
now = round_date(datetime.datetime.now(tz=pytz.utc))
future = now + settings.CONTROLNEXT_FILL_PREDICT_FUTURE
ts = model.predict_fill(now, future, 20, 100, 100)
plot('predict_fill', ts['scenarios']['mean']['prediction'],
ts['history'])
# plot('predict_fill_rain', ts['rain'])
plot('predict_fill_uitstroom',
ts['scenarios']['mean']['intermediate']['uitstroom'])
plot('predict_fill_toestroom',
ts['scenarios']['mean']['intermediate']['toestroom'])
plot('predict_fill_max_uitstroom',
ts['intermediate']['max_uitstroom'])
plot('predict_fill_watervraag', ts['intermediate']['demand'])
def test_calc_model(self):
now = mktim(2012, 8, 5, 8, 0) # some rain fell here
now = round_date(datetime.datetime.now(tz=pytz.utc))
future = now + settings.CONTROLNEXT_FILL_PREDICT_FUTURE
ts = self.model.predict_fill(now, future, 20, 100, 100)
self.assertGreater(len(ts['scenarios']['mean']['prediction']), 10)
def get(self, request, random_url_slug, *args, **kwargs):
try:
self.basin = Basin.objects.filter(
random_url_slug=random_url_slug)[0]
except IndexError:
raise Http404
self.constants = Constants(self.basin)
graph_type = request.GET.get('graph_type', None)
hours_diff = request.GET.get('hours_diff', None) # debug param
# overridable variables for demo purposes
rain_flood_surface = request.GET.get('rain_flood_surface', None)
# debug params
if not rain_flood_surface:
rain_flood_surface = request.GET.get('basin_surface', None)
basin_storage = request.GET.get('basin_storage', None)
reverse_osmosis = request.GET.get('reverse_osmosis', None)
if rain_flood_surface:
try:
# basic validation, if not integer, default value is used
# other validations can be put here, like upper bounds
self.constants.rain_flood_surface = int(rain_flood_surface)
except ValueError:
logger.error("invalid value for rain_flood_surface: %s" %
rain_flood_surface)
if basin_storage:
try:
# basic validation, if not integer, default value is used
# other validations can be put here, like upper bounds
self.constants.max_storage = int(basin_storage)
except ValueError:
logger.error("invalid value for basin_storage: %s" %
basin_storage)
if reverse_osmosis:
try:
# basic validation, if not integer, default value is used
# other validations can be put here, like upper bounds
self.constants.reverse_osmosis = float(reverse_osmosis)
except ValueError:
logger.error("invalid value for reverse_osmosis: %s" %
reverse_osmosis)
osmose_till_date = request.GET.get('osmose_date_till', None)
if osmose_till_date is not None:
date_format = "%d-%m-%Y"
self.constants.osmose_till_date = datetime.datetime.strptime(
osmose_till_date, date_format).date()
# note: t0 is Math.floor() 'ed to a full quarter
t0 = round_date(datetime.datetime.now(pytz.utc))
if hours_diff:
t0 += datetime.timedelta(hours=int(hours_diff))
if graph_type == 'rain':
response_dict = self.rain(t0)
elif graph_type == 'prediction' or graph_type == 'meter_comparison':
outflow_open = request.GET.get('outflowOpen', None)
outflow_closed = request.GET.get('outflowClosed', None)
outflow_capacity = request.GET.get('outflowCapacity', 0)
if outflow_open is not None:
outflow_open = datetime.datetime.fromtimestamp(
int(outflow_open) / 1000, pytz.utc)
if outflow_closed is not None:
outflow_closed = datetime.datetime.fromtimestamp(
int(outflow_closed) / 1000, pytz.utc)
response_dict = self.prediction(
t0, outflow_open, outflow_closed, outflow_capacity)
else:
table = EvaporationTable(self.basin,
self.constants.rain_flood_surface)
future = t0 + settings.CONTROLNEXT_FILL_PREDICT_FUTURE
history = t0 - settings.CONTROLNEXT_FILL_HISTORY
data = table.get_demand_raw(history, future)
result = {
'graph_info': {
'data': self.series_to_js(data),
}
}
response_dict = result
return RestResponse(response_dict)
