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Merged
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Nov 11, 2021
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TST: make get_upcast_box more flexible #44385

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2 changes: 1 addition & 1 deletion pandas/_testing/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -259,7 +259,7 @@ def box_expected(expected, box_cls, transpose=True):
expected = DatetimeArray(expected)
elif box_cls is TimedeltaArray:
expected = TimedeltaArray(expected)
elif box_cls is np.ndarray:
elif box_cls is np.ndarray or box_cls is np.array:
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umm this is very strange

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we're a bit inconsistent about when we use the class vs the constructor; np.ndarray(foo) doesn't work like np.array(foo)

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ok sure, but should ideally fix this at some point.

expected = np.array(expected)
elif box_cls is to_array:
expected = to_array(expected)
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31 changes: 17 additions & 14 deletions pandas/tests/arithmetic/common.py
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Expand Up @@ -34,26 +34,29 @@ def assert_invalid_addsub_type(left, right, msg=None):
right - left


def get_expected_box(box):
def get_upcast_box(left, right, is_cmp: bool = False):
"""
Get the box to use for 'expected' in a comparison operation.
"""
if box in [Index, array]:
return np.ndarray
return box

Get the box to use for 'expected' in an arithmetic or comparison operation.

def get_upcast_box(box, vector):
"""
Given two box-types, find the one that takes priority.
Parameters
left : Any
right : Any
is_cmp : bool, default False
Whether the operation is a comparison method.
"""
if box is DataFrame or isinstance(vector, DataFrame):

if isinstance(left, DataFrame) or isinstance(right, DataFrame):
return DataFrame
if box is Series or isinstance(vector, Series):
if isinstance(left, Series) or isinstance(right, Series):
if is_cmp and isinstance(left, Index):
# Index does not defer for comparisons
return np.array
return Series
if box is Index or isinstance(vector, Index):
if isinstance(left, Index) or isinstance(right, Index):
if is_cmp:
return np.array
return Index
return box
return tm.to_array


def assert_invalid_comparison(left, right, box):
Expand Down
21 changes: 8 additions & 13 deletions pandas/tests/arithmetic/test_datetime64.py
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Expand Up @@ -43,7 +43,6 @@
from pandas.tests.arithmetic.common import (
assert_invalid_addsub_type,
assert_invalid_comparison,
get_expected_box,
get_upcast_box,
)

Expand All @@ -60,12 +59,12 @@ def test_compare_zerodim(self, tz_naive_fixture, box_with_array):
# Test comparison with zero-dimensional array is unboxed
tz = tz_naive_fixture
box = box_with_array
xbox = get_expected_box(box)
dti = date_range("20130101", periods=3, tz=tz)

other = np.array(dti.to_numpy()[0])

dtarr = tm.box_expected(dti, box)
xbox = get_upcast_box(dtarr, other, True)
result = dtarr <= other
expected = np.array([True, False, False])
expected = tm.box_expected(expected, xbox)
Expand Down Expand Up @@ -147,12 +146,12 @@ def test_dt64arr_nat_comparison(self, tz_naive_fixture, box_with_array):
# GH#22242, GH#22163 DataFrame considered NaT == ts incorrectly
tz = tz_naive_fixture
box = box_with_array
xbox = get_expected_box(box)

ts = Timestamp.now(tz)
ser = Series([ts, NaT])

obj = tm.box_expected(ser, box)
xbox = get_upcast_box(obj, ts, True)

expected = Series([True, False], dtype=np.bool_)
expected = tm.box_expected(expected, xbox)
Expand Down Expand Up @@ -244,10 +243,9 @@ def test_nat_comparisons_scalar(self, dtype, data, box_with_array):
# on older numpys (since they check object identity)
return

xbox = get_expected_box(box)

left = Series(data, dtype=dtype)
left = tm.box_expected(left, box)
xbox = get_upcast_box(left, NaT, True)

expected = [False, False, False]
expected = tm.box_expected(expected, xbox)
Expand Down Expand Up @@ -323,10 +321,10 @@ def test_timestamp_compare_series(self, left, right):

def test_dt64arr_timestamp_equality(self, box_with_array):
# GH#11034
xbox = get_expected_box(box_with_array)

ser = Series([Timestamp("2000-01-29 01:59:00"), Timestamp("2000-01-30"), NaT])
ser = tm.box_expected(ser, box_with_array)
xbox = get_upcast_box(ser, ser, True)

result = ser != ser
expected = tm.box_expected([False, False, True], xbox)
Expand Down Expand Up @@ -417,13 +415,12 @@ def test_dti_cmp_nat(self, dtype, box_with_array):
# on older numpys (since they check object identity)
return

xbox = get_expected_box(box_with_array)

left = DatetimeIndex([Timestamp("2011-01-01"), NaT, Timestamp("2011-01-03")])
right = DatetimeIndex([NaT, NaT, Timestamp("2011-01-03")])

left = tm.box_expected(left, box_with_array)
right = tm.box_expected(right, box_with_array)
xbox = get_upcast_box(left, right, True)

lhs, rhs = left, right
if dtype is object:
Expand Down Expand Up @@ -642,12 +639,11 @@ def test_scalar_comparison_tzawareness(
self, comparison_op, other, tz_aware_fixture, box_with_array
):
op = comparison_op
box = box_with_array
tz = tz_aware_fixture
dti = date_range("2016-01-01", periods=2, tz=tz)
xbox = get_expected_box(box)

dtarr = tm.box_expected(dti, box_with_array)
xbox = get_upcast_box(dtarr, other, True)
if op in [operator.eq, operator.ne]:
exbool = op is operator.ne
expected = np.array([exbool, exbool], dtype=bool)
Expand Down Expand Up @@ -2421,14 +2417,13 @@ def test_dti_addsub_offset_arraylike(
self, tz_naive_fixture, names, op, index_or_series
):
# GH#18849, GH#19744
box = pd.Index
other_box = index_or_series

tz = tz_naive_fixture
dti = date_range("2017-01-01", periods=2, tz=tz, name=names[0])
other = other_box([pd.offsets.MonthEnd(), pd.offsets.Day(n=2)], name=names[1])

xbox = get_upcast_box(box, other)
xbox = get_upcast_box(dti, other)

with tm.assert_produces_warning(PerformanceWarning):
res = op(dti, other)
Expand All @@ -2448,7 +2443,7 @@ def test_dti_addsub_object_arraylike(
dti = date_range("2017-01-01", periods=2, tz=tz)
dtarr = tm.box_expected(dti, box_with_array)
other = other_box([pd.offsets.MonthEnd(), Timedelta(days=4)])
xbox = get_upcast_box(box_with_array, other)
xbox = get_upcast_box(dtarr, other)

expected = DatetimeIndex(["2017-01-31", "2017-01-06"], tz=tz_naive_fixture)
expected = tm.box_expected(expected, xbox)
Expand Down
19 changes: 10 additions & 9 deletions pandas/tests/arithmetic/test_period.py
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Expand Up @@ -27,7 +27,7 @@
from pandas.core.arrays import TimedeltaArray
from pandas.tests.arithmetic.common import (
assert_invalid_comparison,
get_expected_box,
get_upcast_box,
)

# ------------------------------------------------------------------
Expand All @@ -41,12 +41,13 @@ class TestPeriodArrayLikeComparisons:

def test_compare_zerodim(self, box_with_array):
# GH#26689 make sure we unbox zero-dimensional arrays
xbox = get_expected_box(box_with_array)

pi = period_range("2000", periods=4)
other = np.array(pi.to_numpy()[0])

pi = tm.box_expected(pi, box_with_array)
xbox = get_upcast_box(pi, other, True)

result = pi <= other
expected = np.array([True, False, False, False])
expected = tm.box_expected(expected, xbox)
Expand Down Expand Up @@ -78,11 +79,11 @@ def test_compare_invalid_listlike(self, box_with_array, other):

@pytest.mark.parametrize("other_box", [list, np.array, lambda x: x.astype(object)])
def test_compare_object_dtype(self, box_with_array, other_box):
xbox = get_expected_box(box_with_array)
pi = period_range("2000", periods=5)
parr = tm.box_expected(pi, box_with_array)

other = other_box(pi)
xbox = get_upcast_box(parr, other, True)

expected = np.array([True, True, True, True, True])
expected = tm.box_expected(expected, xbox)
Expand Down Expand Up @@ -195,14 +196,15 @@ def test_pi_cmp_period(self):

# TODO: moved from test_datetime64; de-duplicate with version below
def test_parr_cmp_period_scalar2(self, box_with_array):
xbox = get_expected_box(box_with_array)

pi = period_range("2000-01-01", periods=10, freq="D")

val = Period("2000-01-04", freq="D")

expected = [x > val for x in pi]

ser = tm.box_expected(pi, box_with_array)
xbox = get_upcast_box(ser, val, True)

expected = tm.box_expected(expected, xbox)
result = ser > val
tm.assert_equal(result, expected)
Expand All @@ -216,11 +218,10 @@ def test_parr_cmp_period_scalar2(self, box_with_array):
@pytest.mark.parametrize("freq", ["M", "2M", "3M"])
def test_parr_cmp_period_scalar(self, freq, box_with_array):
# GH#13200
xbox = get_expected_box(box_with_array)

base = PeriodIndex(["2011-01", "2011-02", "2011-03", "2011-04"], freq=freq)
base = tm.box_expected(base, box_with_array)
per = Period("2011-02", freq=freq)
xbox = get_upcast_box(base, per, True)

exp = np.array([False, True, False, False])
exp = tm.box_expected(exp, xbox)
Expand Down Expand Up @@ -255,14 +256,14 @@ def test_parr_cmp_period_scalar(self, freq, box_with_array):
@pytest.mark.parametrize("freq", ["M", "2M", "3M"])
def test_parr_cmp_pi(self, freq, box_with_array):
# GH#13200
xbox = get_expected_box(box_with_array)

base = PeriodIndex(["2011-01", "2011-02", "2011-03", "2011-04"], freq=freq)
base = tm.box_expected(base, box_with_array)

# TODO: could also box idx?
idx = PeriodIndex(["2011-02", "2011-01", "2011-03", "2011-05"], freq=freq)

xbox = get_upcast_box(base, idx, True)

exp = np.array([False, False, True, False])
exp = tm.box_expected(exp, xbox)
tm.assert_equal(base == idx, exp)
Expand Down
16 changes: 8 additions & 8 deletions pandas/tests/arithmetic/test_timedelta64.py
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Expand Up @@ -1542,13 +1542,13 @@ def test_tdi_mul_float_series(self, box_with_array):
)
def test_tdi_rmul_arraylike(self, other, box_with_array):
box = box_with_array
xbox = get_upcast_box(box, other)

tdi = TimedeltaIndex(["1 Day"] * 10)
expected = timedelta_range("1 days", "10 days")
expected._data.freq = None
expected = timedelta_range("1 days", "10 days")._with_freq(None)

tdi = tm.box_expected(tdi, box)
xbox = get_upcast_box(tdi, other)

expected = tm.box_expected(expected, xbox)

result = other * tdi
Expand Down Expand Up @@ -2000,14 +2000,15 @@ def test_td64arr_rmul_numeric_array(
):
# GH#4521
# divide/multiply by integers
xbox = get_upcast_box(box_with_array, vector)

tdser = Series(["59 Days", "59 Days", "NaT"], dtype="m8[ns]")
vector = vector.astype(any_real_numpy_dtype)

expected = Series(["1180 Days", "1770 Days", "NaT"], dtype="timedelta64[ns]")

tdser = tm.box_expected(tdser, box_with_array)
xbox = get_upcast_box(tdser, vector)

expected = tm.box_expected(expected, xbox)

result = tdser * vector
Expand All @@ -2026,14 +2027,14 @@ def test_td64arr_div_numeric_array(
):
# GH#4521
# divide/multiply by integers
xbox = get_upcast_box(box_with_array, vector)

tdser = Series(["59 Days", "59 Days", "NaT"], dtype="m8[ns]")
vector = vector.astype(any_real_numpy_dtype)

expected = Series(["2.95D", "1D 23H 12m", "NaT"], dtype="timedelta64[ns]")

tdser = tm.box_expected(tdser, box_with_array)
xbox = get_upcast_box(tdser, vector)
expected = tm.box_expected(expected, xbox)

result = tdser / vector
Expand Down Expand Up @@ -2085,7 +2086,7 @@ def test_td64arr_mul_int_series(self, box_with_array, names):
)

tdi = tm.box_expected(tdi, box)
xbox = get_upcast_box(box, ser)
xbox = get_upcast_box(tdi, ser)

expected = tm.box_expected(expected, xbox)

Expand Down Expand Up @@ -2117,9 +2118,8 @@ def test_float_series_rdiv_td64arr(self, box_with_array, names):
name=xname,
)

xbox = get_upcast_box(box, ser)

tdi = tm.box_expected(tdi, box)
xbox = get_upcast_box(tdi, ser)
expected = tm.box_expected(expected, xbox)

result = ser.__rtruediv__(tdi)
Expand Down