def __new__(cls, value=None, **kwargs):
output = object.__new__(cls)
if value == None:
if kwargs:
output.milli = datetime.timedelta(
**kwargs).total_seconds() * 1000
output.month = 0
return output
else:
return None
if is_number(value):
output._milli = float(value) * 1000
output.month = 0
return output
elif is_text(value):
return parse(value)
elif isinstance(value, Duration):
output.milli = value.milli
output.month = value.month
return output
elif isinstance(value, float) and is_nan(value):
return None
else:
from mo_logs import Log
Log.error("Do not know type of object (" +
get_module("mo_json").value2json(value) +
")of to make a Duration")
def __new__(cls, value=None, **kwargs):
output = object.__new__(cls)
if value == None:
if kwargs:
output.milli = datetime.timedelta(**kwargs).total_seconds() * 1000
output.month = 0
return output
else:
return None
if is_number(value):
output._milli = float(value) * 1000
output.month = 0
return output
elif is_text(value):
return parse(value)
elif isinstance(value, Duration):
output.milli = value.milli
output.month = value.month
return output
elif isinstance(value, float) and is_nan(value):
return None
else:
from mo_logs import Log
Log.error("Do not know type of object (" + get_module("mo_json").value2json(value) + ")of to make a Duration")
def average_weekly(y, year):
# RETURN AVERAGE OVER YEAR ENDING JULY 1
min = Date(year).floor(YEAR) - 6 * MONTH
max = min + YEAR
max_seen = min
acc = 0
for value, (start, stop) in zip(deaths[y], _death_dates):
if is_nan(value):
continue
if min < stop < max:
max_seen = stop
if min < start < max:
acc += value
else:
ratio = (stop - min) / WEEK
acc += value * ratio
elif min < start < max:
max_seen = max
ratio = (max - start) / WEEK
acc += value * ratio
if is_nan(acc):
Log.error("not expected")
return acc * WEEK / (max_seen - min)