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 Math.is_number(value):
output._milli = float(value) * 1000
output.month = 0
return output
elif isinstance(value, basestring):
return parse(value)
elif isinstance(value, Duration):
output.milli = value.milli
output.month = value.month
return output
elif isinstance(value, float) and Math.is_nan(value):
return None
else:
from pyLibrary import convert
from pyLibrary.debugs.logs import Log
Log.error("Do not know type of object (" +
convert.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 Math.is_number(value):
output._milli = float(value) * 1000
output.month = 0
return output
elif isinstance(value, basestring):
return parse(value)
elif isinstance(value, Duration):
output.milli = value.milli
output.month = value.month
return output
elif isinstance(value, float) and Math.is_nan(value):
return None
else:
from pyLibrary import convert
from pyLibrary.debugs.logs import Log
Log.error("Do not know type of object (" + convert.value2json(value) + ")of to make a Duration")
def stats(values):
"""
RETURN LOTS OF AGGREGATES
"""
if values == None:
return None
values = values.map(float, includeNone=False)
z = ZeroMoment.new_instance(values)
s = Struct()
for k, v in z.dict.items():
s[k] = v
for k, v in ZeroMoment2Stats(z).items():
s[k] = v
s.max = MAX(values)
s.min = MIN(values)
s.median = pyLibrary.stats.median(values, simple=False)
s.last = values.last()
s.first = values[0]
if Math.is_number(s.variance) and not Math.is_nan(s.variance):
s.std = sqrt(s.variance)
return s
def stats(values):
"""
RETURN LOTS OF AGGREGATES
"""
if values == None:
return None
values = values.map(float, includeNone=False)
z = ZeroMoment.new_instance(values)
s = Dict()
for k, v in z.dict.items():
s[k] = v
for k, v in ZeroMoment2Stats(z).items():
s[k] = v
s.max = MAX(values)
s.min = MIN(values)
s.median = pyLibrary.maths.stats.median(values, simple=False)
s.last = values.last()
s.first = values[0]
if Math.is_number(s.variance) and not Math.is_nan(s.variance):
s.std = sqrt(s.variance)
return s
