def handle(self, *args, **options):
with open(args[0], 'rU') as f:
# Loop over each row (i.e. Location) in the CSV file.
for r in map(row._make, csv.reader(f)):
# Create a new instance of Location.
if r.parent_uuid:
# It's a child node.
parent = Location.objects.get(uuid=r.parent_uuid)
location = parent.add_child(name=r.name)
else:
# It's a root node.
location = Location.add_root(name=r.name)
# Assign properties.
location.description = r.description
location.geometry_precision = str2float(r.geometry_precision)
point_geometry = point(r)
location.point_geometry = point_geometry
location.show_on_map = True if point_geometry else False
location.relative_location = r.relative_location
location.uuid = r.uuid
location.created = datetime.now(tz=pytz.utc)
# Persist to database.
self.stdout.write("Saving {}.".format(location))
location.save()
def handle(self, *args, **options):
data_sets = DataSet.objects.all()
data_set = data_sets[0] if len(data_sets) > 0 else None
sources = Source.objects.all()
source = sources[0] if len(sources) > 0 else None
parameters = Parameter.objects.filter(code=TEST_PARAMETER_NAME)
parameter = parameters[0] if len(parameters) > 0 else None
if not parameter:
parameter = Parameter(
code=TEST_PARAMETER_NAME,
group="{} group".format(TEST_PARAMETER_NAME),
begin_date=datetime.datetime.now(),
end_date=datetime.datetime.now(),
)
parameter.save()
units = Unit.objects.filter(code=TEST_UNIT_NAME)
unit = units[0] if len(units) > 0 else None
if not unit:
unit = Unit(code=TEST_UNIT_NAME, begin_date=datetime.datetime.now(), end_date=datetime.datetime.now())
unit.save()
locations = Location.objects.filter(name=TEST_LOCATION_NAME)
location = locations[0] if len(locations) > 0 else None
if not location:
location = Location(
name=TEST_LOCATION_NAME,
description="{} description".format(TEST_LOCATION_NAME),
point_geometry=Point(0, 0),
)
location.save_under(None)
timeseriess = Timeseries.objects.filter(name=TEST_TIMESERIES_NAME)
timeseries = timeseriess[0] if len(timeseriess) > 0 else None
if not timeseries:
timeseries = Timeseries(
name=TEST_TIMESERIES_NAME,
description="{} description".format(TEST_TIMESERIES_NAME),
source=source,
parameter=parameter,
unit=unit,
location=location,
)
timeseries.save()
timeseries.data_sets = [data_set]
timeseries.save()
events = timeseries.get_events()
if len(events) == 0:
dates = pd.date_range("1/1/2011", periods=20000, freq="1Min", tz=pytz.UTC)
vals = np.linspace(-np.pi, np.pi, len(dates))
vals = np.sin(vals)
df = pd.DataFrame(vals, index=dates, columns=["value"])
timeseries.set_events(df)
timeseries.save()
