def test_moving_sum(self):
"""Test moving_sum calculation."""
start_date = datetime(year=2011, month=9, day=6)
end_date = datetime(year=2011, month=9, day=8)
td_step = timedelta(hours=24)
generate_values_kwargs = {'dt_start': start_date,
'dt_stop': end_date,
'td_step': td_step,
'unit': 'AnyUnit',
'value': 1}
# Make start_date and end_date tz aware, just as in rain_stats from
# adapter
start_date = UTC.localize(start_date)
end_date = UTC.localize(end_date)
moving_sum_kwargs = {
'values': generate_values(**generate_values_kwargs),
'td_window': timedelta(hours=1),
'td_value': td_step,
'start_date_utc': start_date,
'end_date_utc': end_date}
# 24 hour data and a 1 hour window, there should be no max_values
self.assertEqual(len(moving_sum(**moving_sum_kwargs)), 0)
# 3 values of 24 hour data and a 24 hour window, there will be 3
# max_values of 1 each
moving_sum_kwargs['td_window'] = timedelta(days=1)
self.assertEqual(len(moving_sum(**moving_sum_kwargs)), 3)
# if there are more values before and after the window, they are
# neglected.
generate_values_kwargs['dt_start'] -= timedelta(days=2)
generate_values_kwargs['dt_stop'] += timedelta(days=2)
moving_sum_kwargs['values'] = generate_values(**generate_values_kwargs)
self.assertEqual(len(moving_sum(**moving_sum_kwargs)), 3)
# if the values are offset compared to the daterange by
# some hours, only 2 values fit within the daterange that is
# exactly two calendar days.
generate_values_kwargs['dt_start'] -= timedelta(hours=7)
generate_values_kwargs['dt_stop'] += timedelta(hours=7)
moving_sum_kwargs['values'] = generate_values(**generate_values_kwargs)
self.assertEqual(len(moving_sum(**moving_sum_kwargs)), 2)
# A 48 hour window should reveal at least the maximum of 2,
# which is the sum of two 24 hour values of 1
moving_sum_kwargs['td_window'] = timedelta(days=2)
ms = moving_sum(**moving_sum_kwargs)
sums = [m['value'] for m in ms]
self.assertEqual(max(sums), 2)
def rain_stats(self,
values,
area_km2,
td_window,
start_date_utc,
end_date_utc):
"""Calculate stats.
Expects utc, returns site timezone datetimes... Sorry."""
logger.debug(('Calculating rain stats for' +
'start=%s, end=%s, td_window=%s') %
(start_date_utc, end_date_utc, td_window))
if not values:
return {
'td_window': td_window,
'max': None,
'start': None,
'end': None,
't': self._t_to_string(None)}
td_value = UNIT_TO_TIMEDELTA[values[0]['unit']]
max_values = moving_sum(values,
td_window,
td_value,
start_date_utc,
end_date_utc)
if max_values:
max_value = max(max_values, key=lambda i: i['value'])
hours = td_window.days * 24 + td_window.seconds / 3600.0
t = herhalingstijd(hours, area_km2, max_value['value'])
else:
max_value = {'value': None,
'datetime_start_utc': None,
'datetime_end_utc': None}
t = None
if max_value['datetime_start_utc'] is not None:
datetime_start_site_tz = max_value[
'datetime_start_utc'].astimezone(self.tz)
else:
datetime_start_site_tz = None
if max_value['datetime_end_utc'] is not None:
datetime_end_site_tz = max_value[
'datetime_end_utc'].astimezone(self.tz)
else:
datetime_end_site_tz = None
return {
'td_window': td_window,
'max': max_value['value'],
'start': datetime_start_site_tz,
'end': datetime_end_site_tz,
't': self._t_to_string(t)}
