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REF: simplify Timedelta arithmetic methods #33978

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Merged
merged 5 commits into from
May 6, 2020
Merged

REF: simplify Timedelta arithmetic methods #33978

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1de6eb8
REF: simplify Timedelta arithmetic methods
jbrockmendel May 4, 2020
d771ce8
Merge branch 'master' of https://github.com/pandas-dev/pandas into re…
jbrockmendel May 4, 2020
bc65058
typo fixup
jbrockmendel May 4, 2020
22ac75f
Merge branch 'master' of https://github.com/pandas-dev/pandas into re…
jbrockmendel May 5, 2020
4a5b057
npcompat
jbrockmendel May 5, 2020
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170 changes: 57 additions & 113 deletions pandas/_libs/tslibs/timedeltas.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,8 @@ PyDateTime_IMPORT
cimport pandas._libs.tslibs.util as util
from pandas._libs.tslibs.util cimport (
is_timedelta64_object, is_datetime64_object, is_integer_object,
is_float_object)
is_float_object, is_array
)

from pandas._libs.tslibs.c_timestamp cimport _Timestamp

Expand Down Expand Up @@ -606,7 +607,7 @@ def _binary_op_method_timedeltalike(op, name):
# We are implicitly requiring the canonical behavior to be
# defined by Timestamp methods.

elif hasattr(other, 'dtype'):
elif is_array(other):
# nd-array like
if other.dtype.kind in ['m', 'M']:
return op(self.to_timedelta64(), other)
Expand Down Expand Up @@ -1347,113 +1348,64 @@ class Timedelta(_Timedelta):
__rsub__ = _binary_op_method_timedeltalike(lambda x, y: y - x, '__rsub__')

def __mul__(self, other):
if hasattr(other, '_typ'):
# Series, DataFrame, ...
if other._typ == 'dateoffset' and hasattr(other, 'delta'):
# Tick offset; this op will raise TypeError
return other.delta * self
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This part is covered by rmul of DateOffset?

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It will go through DateOffset.__rmul__ which will raise TypeError (correctly), yes.

return NotImplemented
if is_integer_object(other) or is_float_object(other):
return Timedelta(other * self.value, unit='ns')

elif util.is_nan(other):
# i.e. np.nan, but also catch np.float64("NaN") which would
# otherwise get caught by the hasattr(other, "dtype") branch
# incorrectly return a np.timedelta64 object.
return NaT
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not checking this, does that give a change in behaviour?

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the util.is_nan case is subsumed by the is_float_object case on L1351

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OK, I see!


elif hasattr(other, 'dtype'):
elif is_array(other):
# ndarray-like
return other * self.to_timedelta64()

elif other is NaT:
raise TypeError('Cannot multiply Timedelta with NaT')

elif not (is_integer_object(other) or is_float_object(other)):
# only integers and floats allowed
return NotImplemented

return Timedelta(other * self.value, unit='ns')
return NotImplemented

__rmul__ = __mul__

def __truediv__(self, other):
if hasattr(other, '_typ'):
# Series, DataFrame, ...
if other._typ == 'dateoffset' and hasattr(other, 'delta'):
# Tick offset
return self / other.delta
return NotImplemented

elif is_timedelta64_object(other):
# convert to Timedelta below
pass

elif util.is_nan(other):
# i.e. np.nan, but also catch np.float64("NaN") which would
# otherwise get caught by the hasattr(other, "dtype") branch
# incorrectly return a np.timedelta64 object.
return NaT
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same here

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same here, subsumed by the is_float_object case on L1370


elif hasattr(other, 'dtype'):
return self.to_timedelta64() / other
if _should_cast_to_timedelta(other):
# We interpret NaT as timedelta64("NaT")
other = Timedelta(other)
if other is NaT:
return np.nan
return self.value / float(other.value)

elif is_integer_object(other) or is_float_object(other):
# integers or floats
return Timedelta(self.value / other, unit='ns')

elif not _validate_ops_compat(other):
return NotImplemented
elif is_array(other):
return self.to_timedelta64() / other

other = Timedelta(other)
if other is NaT:
return np.nan
return self.value / float(other.value)
return NotImplemented

def __rtruediv__(self, other):
if hasattr(other, '_typ'):
# Series, DataFrame, ...
if other._typ == 'dateoffset' and hasattr(other, 'delta'):
# Tick offset
return other.delta / self
return NotImplemented

elif is_timedelta64_object(other):
# convert to Timedelta below
pass

elif util.is_nan(other):
# i.e. np.nan or np.float64("NaN")
raise TypeError("Cannot divide float by Timedelta")
if _should_cast_to_timedelta(other):
# We interpret NaT as timedelta64("NaT")
other = Timedelta(other)
if other is NaT:
return np.nan
return float(other.value) / self.value

elif hasattr(other, 'dtype'):
elif is_array(other):
if other.dtype.kind == "O":
# GH#31869
return np.array([x / self for x in other])
return other / self.to_timedelta64()

elif not _validate_ops_compat(other):
return NotImplemented

other = Timedelta(other)
if other is NaT:
# In this context we treat NaT as timedelta-like
return np.nan
return float(other.value) / self.value
return NotImplemented

def __floordiv__(self, other):
# numpy does not implement floordiv for timedelta64 dtype, so we cannot
# just defer
if hasattr(other, '_typ'):
# Series, DataFrame, ...
if other._typ == 'dateoffset' and hasattr(other, 'delta'):
# Tick offset
return self // other.delta
return NotImplemented
if _should_cast_to_timedelta(other):
# We interpret NaT as timedelta64("NaT")
other = Timedelta(other)
if other is NaT:
return np.nan
return self.value // other.value

elif is_timedelta64_object(other):
# convert to Timedelta below
pass
elif is_integer_object(other) or is_float_object(other):
return Timedelta(self.value // other, unit='ns')

elif hasattr(other, 'dtype'):
elif is_array(other):
if other.dtype.kind == 'm':
# also timedelta-like
return _broadcast_floordiv_td64(self.value, other, _floordiv)
Expand All @@ -1465,50 +1417,27 @@ class Timedelta(_Timedelta):

raise TypeError(f'Invalid dtype {other.dtype} for __floordiv__')

elif is_integer_object(other) or is_float_object(other):
return Timedelta(self.value // other, unit='ns')

elif not _validate_ops_compat(other):
return NotImplemented

other = Timedelta(other)
if other is NaT:
return np.nan
return self.value // other.value
return NotImplemented

def __rfloordiv__(self, other):
# numpy does not implement floordiv for timedelta64 dtype, so we cannot
# just defer
if hasattr(other, '_typ'):
# Series, DataFrame, ...
if other._typ == 'dateoffset' and hasattr(other, 'delta'):
# Tick offset
return other.delta // self
return NotImplemented

elif is_timedelta64_object(other):
# convert to Timedelta below
pass
if _should_cast_to_timedelta(other):
# We interpret NaT as timedelta64("NaT")
other = Timedelta(other)
if other is NaT:
return np.nan
return other.value // self.value

elif hasattr(other, 'dtype'):
elif is_array(other):
if other.dtype.kind == 'm':
# also timedelta-like
return _broadcast_floordiv_td64(self.value, other, _rfloordiv)

# Includes integer array // Timedelta, disallowed in GH#19761
raise TypeError(f'Invalid dtype {other.dtype} for __floordiv__')

elif is_float_object(other) and util.is_nan(other):
# i.e. np.nan
return NotImplemented

elif not _validate_ops_compat(other):
return NotImplemented

other = Timedelta(other)
if other is NaT:
return np.nan
return other.value // self.value
return NotImplemented

def __mod__(self, other):
# Naive implementation, room for optimization
Expand All @@ -1529,6 +1458,21 @@ class Timedelta(_Timedelta):
return div, other - div * self


cdef bint is_any_td_scalar(object obj):
return (
PyDelta_Check(obj) or is_timedelta64_object(obj) or isinstance(obj, Tick)
)


cdef bint _should_cast_to_timedelta(object obj):
"""
Should we treat this object as a Timedelta for the purpose of a binary op
"""
return (
is_any_td_scalar(obj) or obj is None or obj is NaT or isinstance(obj, str)
)


cdef _floordiv(int64_t value, right):
return value // right

Expand Down
3 changes: 2 additions & 1 deletion pandas/tests/scalar/test_nat.py
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Original file line number Diff line number Diff line change
Expand Up @@ -389,7 +389,8 @@ def test_nat_arithmetic_scalar(op_name, value, val_type):
and "times" in op_name
and isinstance(value, Timedelta)
):
msg = "Cannot multiply"
typs = "(Timedelta|NaTType)"
msg = rf"unsupported operand type\(s\) for \*: '{typs}' and '{typs}'"
elif val_type == "str":
# un-specific check here because the message comes from str
# and varies by method
Expand Down
35 changes: 25 additions & 10 deletions pandas/tests/scalar/timedelta/test_arithmetic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -325,7 +325,13 @@ class TestTimedeltaMultiplicationDivision:
def test_td_mul_nat(self, op, td_nat):
# GH#19819
td = Timedelta(10, unit="d")
msg = "cannot use operands with types|Cannot multiply Timedelta with NaT"
typs = "|".join(["numpy.timedelta64", "NaTType", "Timedelta"])
msg = "|".join(
[
rf"unsupported operand type\(s\) for \*: '{typs}' and '{typs}'",
r"ufunc '?multiply'? cannot use operands with types",
]
)
with pytest.raises(TypeError, match=msg):
op(td, td_nat)

Expand Down Expand Up @@ -457,11 +463,11 @@ def test_td_rdiv_na_scalar(self):
result = np.timedelta64("NaT") / td
assert np.isnan(result)

msg = "cannot use operands with types dtype"
msg = r"unsupported operand type\(s\) for /: 'numpy.datetime64' and 'Timedelta'"
with pytest.raises(TypeError, match=msg):
np.datetime64("NaT") / td

msg = "Cannot divide float by Timedelta"
msg = r"unsupported operand type\(s\) for /: 'float' and 'Timedelta'"
with pytest.raises(TypeError, match=msg):
np.nan / td

Expand All @@ -479,7 +485,7 @@ def test_td_rdiv_ndarray(self):
tm.assert_numpy_array_equal(result, expected)

arr = np.array([np.nan], dtype=object)
msg = "Cannot divide float by Timedelta"
msg = r"unsupported operand type\(s\) for /: 'float' and 'Timedelta'"
with pytest.raises(TypeError, match=msg):
arr / td

Expand Down Expand Up @@ -522,6 +528,7 @@ def test_td_floordiv_invalid_scalar(self):
[
r"Invalid dtype datetime64\[D\] for __floordiv__",
"'dtype' is an invalid keyword argument for this function",
r"ufunc '?floor_divide'? cannot use operands with types",
]
)
with pytest.raises(TypeError, match=msg):
Expand Down Expand Up @@ -595,9 +602,14 @@ def test_td_rfloordiv_invalid_scalar(self):
td = Timedelta(hours=3, minutes=3)

dt64 = np.datetime64("2016-01-01", "us")
msg = r"Invalid dtype datetime64\[us\] for __floordiv__"

assert td.__rfloordiv__(dt64) is NotImplemented

msg = (
r"unsupported operand type\(s\) for //: 'numpy.datetime64' and 'Timedelta'"
)
with pytest.raises(TypeError, match=msg):
td.__rfloordiv__(dt64)
dt64 // td

def test_td_rfloordiv_numeric_scalar(self):
# GH#18846
Expand All @@ -606,15 +618,18 @@ def test_td_rfloordiv_numeric_scalar(self):
assert td.__rfloordiv__(np.nan) is NotImplemented
assert td.__rfloordiv__(3.5) is NotImplemented
assert td.__rfloordiv__(2) is NotImplemented
assert td.__rfloordiv__(np.float64(2.0)) is NotImplemented
assert td.__rfloordiv__(np.uint8(9)) is NotImplemented
assert td.__rfloordiv__(np.int32(2.0)) is NotImplemented

msg = "Invalid dtype"
msg = r"unsupported operand type\(s\) for //: '.*' and 'Timedelta"
with pytest.raises(TypeError, match=msg):
td.__rfloordiv__(np.float64(2.0))
np.float64(2.0) // td
with pytest.raises(TypeError, match=msg):
td.__rfloordiv__(np.uint8(9))
np.uint8(9) // td
with pytest.raises(TypeError, match=msg):
# deprecated GH#19761, enforced GH#29797
td.__rfloordiv__(np.int32(2.0))
np.int32(2.0) // td

def test_td_rfloordiv_timedeltalike_array(self):
# GH#18846
Expand Down