REF: De-duplicate pieces of datetimelike arithmetic

pandas/core/arrays/datetimelike.py

@@ -246,27 +246,6 @@ def _maybe_mask_results(self, result, fill_value=None, convert=None):
             result[self._isnan] = fill_value
         return result
 
-    def _nat_new(self, box=True):
-        """
-        Return Array/Index or ndarray filled with NaT which has the same
-        length as the caller.
-
-        Parameters
-        ----------
-        box : boolean, default True
-            - If True returns a Array/Index as the same as caller.
-            - If False returns ndarray of np.int64.
-        """
-        result = np.zeros(len(self), dtype=np.int64)
-        result.fill(iNaT)
-        if not box:
-            return result
-
-        attribs = self._get_attributes_dict()
-        if not is_period_dtype(self):
-            attribs['freq'] = None
-        return self._simple_new(result, **attribs)
-
     # ------------------------------------------------------------------
     # Frequency Properties/Methods
 
@@ -361,7 +340,7 @@ def _add_offset(self, offset):
         raise com.AbstractMethodError(self)
 
     def _add_delta(self, other):
-        return NotImplemented
+        raise com.AbstractMethodError(self)
 
     def _add_delta_td(self, other):
         """
@@ -380,7 +359,7 @@ def _add_delta_tdi(self, other):
         Add a delta of a TimedeltaIndex
         return the i8 result view
         """
-        if not len(self) == len(other):
+        if len(self) != len(other):
             raise ValueError("cannot add indices of unequal length")
 
         if isinstance(other, np.ndarray):
@@ -407,7 +386,9 @@ def _add_nat(self):
 
         # GH#19124 pd.NaT is treated like a timedelta for both timedelta
         # and datetime dtypes
-        return self._nat_new(box=True)
+        result = np.zeros(len(self), dtype=np.int64)
+        result.fill(iNaT)
+        return self._shallow_copy(result, freq=None)
 
     def _sub_nat(self):
         """Subtract pd.NaT from self"""
@@ -441,7 +422,7 @@ def _sub_period_array(self, other):
                             .format(dtype=other.dtype,
                                     cls=type(self).__name__))
 
-        if not len(self) == len(other):
+        if len(self) != len(other):
             raise ValueError("cannot subtract arrays/indices of "
                              "unequal length")
         if self.freq != other.freq:

pandas/core/arrays/datetimes.py

@@ -425,10 +425,20 @@ def _assert_tzawareness_compat(self, other):
     # Arithmetic Methods
 
     def _sub_datelike_dti(self, other):
-        """subtraction of two DatetimeIndexes"""
-        if not len(self) == len(other):
+        """subtraction of DatetimeArray/Index or ndarray[datetime64]"""
+        if len(self) != len(other):
             raise ValueError("cannot add indices of unequal length")
 
+        if not isinstance(other, DatetimeArrayMixin):
+            # i.e. np.ndarray; we assume it is datetime64-dtype
+            other = type(self)(other)
+
+        if not self._has_same_tz(other):
+            # require tz compat
+            raise TypeError("{cls} subtraction must have the same "
+                            "timezones or no timezones"
+                            .format(cls=type(self).__name__))
+
         self_i8 = self.asi8
         other_i8 = other.asi8
         new_values = checked_add_with_arr(self_i8, -other_i8,
@@ -459,34 +469,22 @@ def _add_offset(self, offset):
     def _sub_datelike(self, other):
         # subtract a datetime from myself, yielding a ndarray[timedelta64[ns]]
         if isinstance(other, (DatetimeArrayMixin, np.ndarray)):
-            if isinstance(other, np.ndarray):
-                # if other is an ndarray, we assume it is datetime64-dtype
-                other = type(self)(other)
-            if not self._has_same_tz(other):
-                # require tz compat
-                raise TypeError("{cls} subtraction must have the same "
-                                "timezones or no timezones"
-                                .format(cls=type(self).__name__))
-            result = self._sub_datelike_dti(other)
-        elif isinstance(other, (datetime, np.datetime64)):
-            assert other is not NaT
-            other = Timestamp(other)
-            if other is NaT:
-                return self - NaT
+            return self._sub_datelike_dti(other)
+
+        assert isinstance(other, (datetime, np.datetime64))
+        assert other is not NaT
+        other = Timestamp(other)
+        if other is NaT:
+            return self - NaT
+        elif not self._has_same_tz(other):
             # require tz compat
-            elif not self._has_same_tz(other):
-                raise TypeError("Timestamp subtraction must have the same "
-                                "timezones or no timezones")
-            else:
-                i8 = self.asi8
-                result = checked_add_with_arr(i8, -other.value,
-                                              arr_mask=self._isnan)
-                result = self._maybe_mask_results(result,
-                                                  fill_value=iNaT)
-        else:
-            raise TypeError("cannot subtract {cls} and {typ}"
-                            .format(cls=type(self).__name__,
-                                    typ=type(other).__name__))
+            raise TypeError("Timestamp subtraction must have the same "
+                            "timezones or no timezones")
+        i8 = self.asi8
+        result = checked_add_with_arr(i8, -other.value,
+                                      arr_mask=self._isnan)
+        result = self._maybe_mask_results(result,
+                                          fill_value=iNaT)
         return result.view('timedelta64[ns]')
 
     def _add_delta(self, delta):
@@ -508,22 +506,12 @@ def _add_delta(self, delta):
         The result's name is set outside of _add_delta by the calling
         method (__add__ or __sub__)
         """
-        from pandas.core.arrays.timedeltas import TimedeltaArrayMixin
-
         if isinstance(delta, (Tick, timedelta, np.timedelta64)):
             new_values = self._add_delta_td(delta)
         elif is_timedelta64_dtype(delta):
-            if not isinstance(delta, TimedeltaArrayMixin):
-                delta = TimedeltaArrayMixin(delta)
             new_values = self._add_delta_tdi(delta)
-        else:
-            new_values = self.astype('O') + delta
 
-        tz = 'UTC' if self.tz is not None else None
-        result = type(self)(new_values, tz=tz, freq='infer')
-        if self.tz is not None and self.tz is not utc:
-            result = result.tz_convert(self.tz)
-        return result
+        return type(self)(new_values, tz=self.tz, freq='infer')
 
     # -----------------------------------------------------------------
     # Timezone Conversion and Localization Methods

pandas/core/arrays/period.py

@@ -5,7 +5,6 @@
 
 import numpy as np
 
-from pandas._libs import lib
 from pandas._libs.tslib import NaT, iNaT
 from pandas._libs.tslibs.period import (
     Period, IncompatibleFrequency, DIFFERENT_FREQ_INDEX,
@@ -26,7 +25,7 @@
 import pandas.core.common as com
 
 from pandas.tseries import frequencies
-from pandas.tseries.offsets import Tick, DateOffset
+from pandas.tseries.offsets import Tick
 
 from pandas.core.arrays import datetimelike as dtl
 from pandas.core.arrays.datetimelike import DatetimeLikeArrayMixin
@@ -404,13 +403,11 @@ def _add_delta(self, other):
         #  i8 view or _shallow_copy
         if isinstance(other, (Tick, timedelta, np.timedelta64)):
             new_values = self._add_delta_td(other)
-            return self._shallow_copy(new_values)
         elif is_timedelta64_dtype(other):
             # ndarray[timedelta64] or TimedeltaArray/index
             new_values = self._add_delta_tdi(other)
-            return self._shallow_copy(new_values)
-        else:  # pragma: no cover
-            raise TypeError(type(other).__name__)
+
+        return self._shallow_copy(new_values)
 
     @deprecate_kwarg(old_arg_name='n', new_arg_name='periods')
     def shift(self, periods):
@@ -445,48 +442,6 @@ def _time_shift(self, n):
             values[self._isnan] = iNaT
         return self._shallow_copy(values=values)
 
-    def _maybe_convert_timedelta(self, other):
-        """
-        Convert timedelta-like input to an integer multiple of self.freq
-
-        Parameters
-        ----------
-        other : timedelta, np.timedelta64, DateOffset, int, np.ndarray
-
-        Returns
-        -------
-        converted : int, np.ndarray[int64]
-
-        Raises
-        ------
-        IncompatibleFrequency : if the input cannot be written as a multiple
-            of self.freq.  Note IncompatibleFrequency subclasses ValueError.
-        """
-        if isinstance(
-                other, (timedelta, np.timedelta64, Tick, np.ndarray)):
-            offset = frequencies.to_offset(self.freq.rule_code)
-            if isinstance(offset, Tick):
-                # _check_timedeltalike_freq_compat will raise if incompatible
-                delta = self._check_timedeltalike_freq_compat(other)
-                return delta
-        elif isinstance(other, DateOffset):
-            freqstr = other.rule_code
-            base = frequencies.get_base_alias(freqstr)
-            if base == self.freq.rule_code:
-                return other.n
-            msg = DIFFERENT_FREQ_INDEX.format(self.freqstr, other.freqstr)
-            raise IncompatibleFrequency(msg)
-        elif lib.is_integer(other):
-            # integer is passed to .shift via
-            # _add_datetimelike_methods basically
-            # but ufunc may pass integer to _add_delta
-            return other
-
-        # raise when input doesn't have freq
-        msg = "Input has different freq from {cls}(freq={freqstr})"
-        raise IncompatibleFrequency(msg.format(cls=type(self).__name__,
-                                               freqstr=self.freqstr))
-
     def _check_timedeltalike_freq_compat(self, other):
         """
         Arithmetic operations with timedelta-like scalars or array `other`

pandas/core/arrays/timedeltas.py

@@ -216,15 +216,9 @@ def _add_delta(self, delta):
         """
         if isinstance(delta, (Tick, timedelta, np.timedelta64)):
             new_values = self._add_delta_td(delta)
-        elif isinstance(delta, TimedeltaArrayMixin):
-            new_values = self._add_delta_tdi(delta)
         elif is_timedelta64_dtype(delta):
             # ndarray[timedelta64] --> wrap in TimedeltaArray/Index
-            delta = type(self)(delta)
             new_values = self._add_delta_tdi(delta)
-        else:
-            raise TypeError("cannot add the type {0} to a TimedeltaIndex"
-                            .format(type(delta)))
 
         return type(self)(new_values, freq='infer')
 

pandas/core/indexes/period.py

@@ -1,5 +1,5 @@
 # pylint: disable=E1101,E1103,W0232
-from datetime import datetime
+from datetime import datetime, timedelta
 import numpy as np
 import warnings
 
@@ -16,6 +16,8 @@
     pandas_dtype,
     ensure_object)
 
+from pandas.tseries.offsets import DateOffset, Tick
+from pandas.tseries import frequencies
 from pandas.tseries.frequencies import get_freq_code as _gfc
 
 from pandas.core.indexes.datetimes import DatetimeIndex, Int64Index, Index
@@ -726,6 +728,48 @@ def __setstate__(self, state):
 
     _unpickle_compat = __setstate__
 
+    def _maybe_convert_timedelta(self, other):
+        """
+        Convert timedelta-like input to an integer multiple of self.freq
+
+        Parameters
+        ----------
+        other : timedelta, np.timedelta64, DateOffset, int, np.ndarray
+
+        Returns
+        -------
+        converted : int, np.ndarray[int64]
+
+        Raises
+        ------
+        IncompatibleFrequency : if the input cannot be written as a multiple
+            of self.freq.  Note IncompatibleFrequency subclasses ValueError.
+        """
+        if isinstance(
+                other, (timedelta, np.timedelta64, Tick, np.ndarray)):
+            offset = frequencies.to_offset(self.freq.rule_code)
+            if isinstance(offset, Tick):
+                # _check_timedeltalike_freq_compat will raise if incompatible
+                delta = self._check_timedeltalike_freq_compat(other)
+                return delta
+        elif isinstance(other, DateOffset):
+            freqstr = other.rule_code
+            base = frequencies.get_base_alias(freqstr)
+            if base == self.freq.rule_code:
+                return other.n
+            msg = DIFFERENT_FREQ_INDEX.format(self.freqstr, other.freqstr)
+            raise IncompatibleFrequency(msg)
+        elif is_integer(other):
+            # integer is passed to .shift via
+            # _add_datetimelike_methods basically
+            # but ufunc may pass integer to _add_delta
+            return other
+
+        # raise when input doesn't have freq
+        msg = "Input has different freq from {cls}(freq={freqstr})"
+        raise IncompatibleFrequency(msg.format(cls=type(self).__name__,
+                                               freqstr=self.freqstr))
+
 
 PeriodIndex._add_comparison_ops()
 PeriodIndex._add_numeric_methods_disabled()

pandas/tests/indexes/datetimes/test_ops.py

@@ -339,16 +339,6 @@ def test_infer_freq(self, freq):
         tm.assert_index_equal(idx, result)
         assert result.freq == freq
 
-    def test_nat_new(self):
-        idx = pd.date_range('2011-01-01', freq='D', periods=5, name='x')
-        result = idx._nat_new()
-        exp = pd.DatetimeIndex([pd.NaT] * 5, name='x')
-        tm.assert_index_equal(result, exp)
-
-        result = idx._nat_new(box=False)
-        exp = np.array([tslib.iNaT] * 5, dtype=np.int64)
-        tm.assert_numpy_array_equal(result, exp)
-
     def test_nat(self, tz_naive_fixture):
         tz = tz_naive_fixture
         assert pd.DatetimeIndex._na_value is pd.NaT

pandas/tests/indexes/period/test_ops.py

@@ -314,17 +314,6 @@ def test_order(self):
             tm.assert_numpy_array_equal(indexer, exp, check_dtype=False)
             assert ordered.freq == 'D'
 
-    def test_nat_new(self):
-
-        idx = pd.period_range('2011-01', freq='M', periods=5, name='x')
-        result = idx._nat_new()
-        exp = pd.PeriodIndex([pd.NaT] * 5, freq='M', name='x')
-        tm.assert_index_equal(result, exp)
-
-        result = idx._nat_new(box=False)
-        exp = np.array([tslib.iNaT] * 5, dtype=np.int64)
-        tm.assert_numpy_array_equal(result, exp)
-
     def test_shift(self):
         # This is tested in test_arithmetic
         pass

pandas/tests/indexes/timedeltas/test_ops.py

@@ -239,17 +239,6 @@ def test_infer_freq(self, freq):
         tm.assert_index_equal(idx, result)
         assert result.freq == freq
 
-    def test_nat_new(self):
-
-        idx = pd.timedelta_range('1', freq='D', periods=5, name='x')
-        result = idx._nat_new()
-        exp = pd.TimedeltaIndex([pd.NaT] * 5, name='x')
-        tm.assert_index_equal(result, exp)
-
-        result = idx._nat_new(box=False)
-        exp = np.array([iNaT] * 5, dtype=np.int64)
-        tm.assert_numpy_array_equal(result, exp)
-
     def test_shift(self):
         pass  # handled in test_arithmetic.py