def __rfloordiv__(self, other):
if isinstance(other, (ABCSeries, ABCDataFrame, ABCIndexClass)):
return NotImplemented
other = lib.item_from_zerodim(other)
if is_scalar(other):
if isinstance(other, (timedelta, np.timedelta64, Tick)):
other = Timedelta(other)
if other is NaT:
# treat this specifically as timedelta-NaT
result = np.empty(self.shape, dtype=np.float64)
result.fill(np.nan)
return result
# dispatch to Timedelta implementation
result = other.__floordiv__(self._data)
return result
raise TypeError(
"Cannot divide {typ} by {cls}".format(
typ=type(other).__name__, cls=type(self).__name__
)
)
if not hasattr(other, "dtype"):
# list, tuple
other = np.array(other)
if len(other) != len(self):
raise ValueError("Cannot divide with unequal lengths")
elif is_timedelta64_dtype(other):
other = type(self)(other)
# numpy timedelta64 does not natively support floordiv, so operate
# on the i8 values
result = other.asi8 // self.asi8
mask = self._isnan | other._isnan
if mask.any():
result = result.astype(np.int64)
result[mask] = np.nan
return result
elif is_object_dtype(other):
result = [other[n] // self[n] for n in range(len(self))]
result = np.array(result)
return result
else:
dtype = getattr(other, "dtype", type(other).__name__)
raise TypeError(
"Cannot divide {typ} by {cls}".format(
typ=dtype, cls=type(self).__name__
)
)
def __rfloordiv__(self, other):
if isinstance(other, (ABCSeries, ABCDataFrame, ABCIndexClass)):
return NotImplemented
other = lib.item_from_zerodim(other)
if is_scalar(other):
if isinstance(other, (timedelta, np.timedelta64, Tick)):
other = Timedelta(other)
if other is NaT:
# treat this specifically as timedelta-NaT
result = np.empty(self.shape, dtype=np.float64)
result.fill(np.nan)
return result
# dispatch to Timedelta implementation
result = other.__floordiv__(self._data)
return result
raise TypeError("Cannot divide {typ} by {cls}"
.format(typ=type(other).__name__,
cls=type(self).__name__))
if not hasattr(other, "dtype"):
# list, tuple
other = np.array(other)
if len(other) != len(self):
raise ValueError("Cannot divide with unequal lengths")
elif is_timedelta64_dtype(other):
other = type(self)(other)
# numpy timedelta64 does not natively support floordiv, so operate
# on the i8 values
result = other.asi8 // self.asi8
mask = self._isnan | other._isnan
if mask.any():
result = result.astype(np.int64)
result[mask] = np.nan
return result
elif is_object_dtype(other):
result = [other[n] // self[n] for n in range(len(self))]
result = np.array(result)
return result
else:
dtype = getattr(other, "dtype", type(other).__name__)
raise TypeError("Cannot divide {typ} by {cls}"
.format(typ=dtype, cls=type(self).__name__))
def __rfloordiv__(self, other):
if is_scalar(other):
if isinstance(other, self._recognized_scalars):
other = Timedelta(other)
if other is NaT:
# treat this specifically as timedelta-NaT
result = np.empty(self.shape, dtype=np.float64)
result.fill(np.nan)
return result
# dispatch to Timedelta implementation
result = other.__floordiv__(self._ndarray)
return result
raise TypeError(
f"Cannot divide {type(other).__name__} by {type(self).__name__}"
)
if not hasattr(other, "dtype"):
# list, tuple
other = np.array(other)
if len(other) != len(self):
raise ValueError("Cannot divide with unequal lengths")
elif is_timedelta64_dtype(other.dtype):
other = type(self)(other)
# numpy timedelta64 does not natively support floordiv, so operate
# on the i8 values
result = other.asi8 // self.asi8
mask = self._isnan | other._isnan
if mask.any():
result = result.astype(np.float64)
np.putmask(result, mask, np.nan)
return result
elif is_object_dtype(other.dtype):
# error: Incompatible types in assignment (expression has type
# "List[Any]", variable has type "ndarray")
result = [ # type: ignore[assignment]
other[n] // self[n] for n in range(len(self))
]
result = np.array(result)
return result
else:
dtype = getattr(other, "dtype", type(other).__name__)
raise TypeError(f"Cannot divide {dtype} by {type(self).__name__}")
def __rfloordiv__(self, other):
if is_scalar(other):
if isinstance(other, self._recognized_scalars):
other = Timedelta(other)
# mypy assumes that __new__ returns an instance of the class
# github.com/python/mypy/issues/1020
if cast("Timedelta | NaTType", other) is NaT:
# treat this specifically as timedelta-NaT
result = np.empty(self.shape, dtype=np.float64)
result.fill(np.nan)
return result
# dispatch to Timedelta implementation
return other.__floordiv__(self._ndarray)
raise TypeError(
f"Cannot divide {type(other).__name__} by {type(self).__name__}"
)
if not hasattr(other, "dtype"):
# list, tuple
other = np.array(other)
if len(other) != len(self):
raise ValueError("Cannot divide with unequal lengths")
elif is_timedelta64_dtype(other.dtype):
other = type(self)(other)
# numpy timedelta64 does not natively support floordiv, so operate
# on the i8 values
result = other.asi8 // self.asi8
mask = self._isnan | other._isnan
if mask.any():
result = result.astype(np.float64)
np.putmask(result, mask, np.nan)
return result
elif is_object_dtype(other.dtype):
result_list = [other[n] // self[n] for n in range(len(self))]
result = np.array(result_list)
return result
else:
dtype = getattr(other, "dtype", type(other).__name__)
raise TypeError(f"Cannot divide {dtype} by {type(self).__name__}")
def __rfloordiv__(self, other):
if is_scalar(other):
if isinstance(other, (timedelta, np.timedelta64, Tick)):
other = Timedelta(other)
if other is NaT:
# treat this specifically as timedelta-NaT
result = np.empty(self.shape, dtype=np.float64)
result.fill(np.nan)
return result
# dispatch to Timedelta implementation
result = other.__floordiv__(self._data)
return result
raise TypeError(
f"Cannot divide {type(other).__name__} by {type(self).__name__}"
)
if not hasattr(other, "dtype"):
# list, tuple
other = np.array(other)
if is_timedelta64_dtype(other.dtype):
other = type(self)(other)
# numpy timedelta64 does not natively support floordiv, so operate
# on the i8 values
result = other.asi8 // self.asi8
mask = self._isnan | other._isnan
if mask.any():
result = result.astype(np.int64)
result[mask] = np.nan
return result
elif is_object_dtype(other.dtype):
result = [other[n] // self[n] for n in range(len(self))]
result = np.array(result)
return result
else:
dtype = getattr(other, "dtype", type(other).__name__)
raise TypeError(f"Cannot divide {dtype} by {type(self).__name__}")