def __array_wrap__(self, result, context=None):
"""
Gets called after a ufunc. Needs additional handling as
PeriodIndex stores internal data as int dtype
Replace this to __numpy_ufunc__ in future version
"""
if isinstance(context, tuple) and len(context) > 0:
func = context[0]
if (func is np.add):
pass
elif (func is np.subtract):
name = self.name
left = context[1][0]
right = context[1][1]
if (isinstance(left, PeriodIndex)
and isinstance(right, PeriodIndex)):
name = left.name if left.name == right.name else None
return Index(result, name=name)
elif isinstance(left, Period) or isinstance(right, Period):
return Index(result, name=name)
elif isinstance(func, np.ufunc):
if 'M->M' not in func.types:
msg = "ufunc '{0}' not supported for the PeriodIndex"
# This should be TypeError, but TypeError cannot be raised
# from here because numpy catches.
raise ValueError(msg.format(func.__name__))
if is_bool_dtype(result):
return result
# the result is object dtype array of Period
# cannot pass _simple_new as it is
return self._shallow_copy(result, freq=self.freq, name=self.name)
def _delegate_property_get(self, name, *args, **kwargs):
result = getattr(self._data, name)
box_ops = (set(PeriodArray._datetimelike_ops) -
set(PeriodArray._bool_ops))
if name in box_ops:
result = Index(result, name=self.name)
return result
def _sub_period(self, other):
# If the operation is well-defined, we return an object-Index
# of DateOffsets. Null entries are filled with pd.NaT
new_data = PeriodArrayMixin._sub_period(self, other)
# TODO: Should name=self.name be passed here?
return Index(new_data)
def _sub_period(self, other):
if self.freq != other.freq:
msg = _DIFFERENT_FREQ_INDEX.format(self.freqstr, other.freqstr)
raise IncompatibleFrequency(msg)
asi8 = self.asi8
new_data = asi8 - other.ordinal
if self.hasnans:
new_data = new_data.astype(np.float64)
new_data[self._isnan] = np.nan
# result must be Int64Index or Float64Index
return Index(new_data, name=self.name)
def astype(self, dtype, copy=True, how='start'):
dtype = pandas_dtype(dtype)
# We have a few special-cases for `dtype`.
# Failing those, we fall back to astyping the values
if is_datetime64_any_dtype(dtype):
# 'how' is index-speicifc, isn't part of the EA interface.
tz = getattr(dtype, 'tz', None)
return self.to_timestamp(how=how).tz_localize(tz)
result = self._data.astype(dtype, copy=copy)
return Index(result, name=self.name, dtype=dtype, copy=False)
def _sub_period(self, other):
# If the operation is well-defined, we return an object-Index
# of DateOffsets. Null entries are filled with pd.NaT
if self.freq != other.freq:
msg = _DIFFERENT_FREQ_INDEX.format(self.freqstr, other.freqstr)
raise IncompatibleFrequency(msg)
asi8 = self.asi8
new_data = asi8 - other.ordinal
new_data = np.array([self.freq * x for x in new_data])
if self.hasnans:
new_data[self._isnan] = tslib.NaT
return Index(new_data)
def f(self):
base, mult = _gfc(self.freq)
result = get_period_field_arr(alias, self._values, base)
return Index(result, name=self.name)
def _delegate_method(self, name, *args, **kwargs):
result = operator.methodcaller(name, *args, **kwargs)(self._data)
return Index(result, name=self.name)
def f(self):
result = fget(self)
return Index(result, name=self.name)
