218 lines
7.6 KiB
Python
218 lines
7.6 KiB
Python
|
from __future__ import annotations
|
||
|
|
|
||
|
|
import numpy as np
|
||
|
|
import pytest
|
||
|
|
|
||
|
|
import pandas as pd
|
||
|
|
import pandas._testing as tm
|
||
|
|
from pandas.core import ops
|
||
|
|
from pandas.tests.extension.base.base import BaseExtensionTests
|
||
|
|
|
||
|
|
|
||
|
|
class BaseOpsUtil(BaseExtensionTests):
|
||
|
|
def get_op_from_name(self, op_name: str):
|
||
|
|
return tm.get_op_from_name(op_name)
|
||
|
|
|
||
|
|
def check_opname(self, ser: pd.Series, op_name: str, other, exc=Exception):
|
||
|
|
op = self.get_op_from_name(op_name)
|
||
|
|
|
||
|
|
self._check_op(ser, op, other, op_name, exc)
|
||
|
|
|
||
|
|
def _combine(self, obj, other, op):
|
||
|
|
if isinstance(obj, pd.DataFrame):
|
||
|
|
if len(obj.columns) != 1:
|
||
|
|
raise NotImplementedError
|
||
|
|
expected = obj.iloc[:, 0].combine(other, op).to_frame()
|
||
|
|
else:
|
||
|
|
expected = obj.combine(other, op)
|
||
|
|
return expected
|
||
|
|
|
||
|
|
def _check_op(
|
||
|
|
self, ser: pd.Series, op, other, op_name: str, exc=NotImplementedError
|
||
|
|
):
|
||
|
|
if exc is None:
|
||
|
|
result = op(ser, other)
|
||
|
|
expected = self._combine(ser, other, op)
|
||
|
|
assert isinstance(result, type(ser))
|
||
|
|
self.assert_equal(result, expected)
|
||
|
|
else:
|
||
|
|
with pytest.raises(exc):
|
||
|
|
op(ser, other)
|
||
|
|
|
||
|
|
def _check_divmod_op(self, ser: pd.Series, op, other, exc=Exception):
|
||
|
|
# divmod has multiple return values, so check separately
|
||
|
|
if exc is None:
|
||
|
|
result_div, result_mod = op(ser, other)
|
||
|
|
if op is divmod:
|
||
|
|
expected_div, expected_mod = ser // other, ser % other
|
||
|
|
else:
|
||
|
|
expected_div, expected_mod = other // ser, other % ser
|
||
|
|
self.assert_series_equal(result_div, expected_div)
|
||
|
|
self.assert_series_equal(result_mod, expected_mod)
|
||
|
|
else:
|
||
|
|
with pytest.raises(exc):
|
||
|
|
divmod(ser, other)
|
||
|
|
|
||
|
|
|
||
|
|
class BaseArithmeticOpsTests(BaseOpsUtil):
|
||
|
|
"""
|
||
|
|
Various Series and DataFrame arithmetic ops methods.
|
||
|
|
|
||
|
|
Subclasses supporting various ops should set the class variables
|
||
|
|
to indicate that they support ops of that kind
|
||
|
|
|
||
|
|
* series_scalar_exc = TypeError
|
||
|
|
* frame_scalar_exc = TypeError
|
||
|
|
* series_array_exc = TypeError
|
||
|
|
* divmod_exc = TypeError
|
||
|
|
"""
|
||
|
|
|
||
|
|
series_scalar_exc: type[Exception] | None = TypeError
|
||
|
|
frame_scalar_exc: type[Exception] | None = TypeError
|
||
|
|
series_array_exc: type[Exception] | None = TypeError
|
||
|
|
divmod_exc: type[Exception] | None = TypeError
|
||
|
|
|
||
|
|
def test_arith_series_with_scalar(self, data, all_arithmetic_operators):
|
||
|
|
# series & scalar
|
||
|
|
op_name = all_arithmetic_operators
|
||
|
|
ser = pd.Series(data)
|
||
|
|
self.check_opname(ser, op_name, ser.iloc[0], exc=self.series_scalar_exc)
|
||
|
|
|
||
|
|
def test_arith_frame_with_scalar(self, data, all_arithmetic_operators):
|
||
|
|
# frame & scalar
|
||
|
|
op_name = all_arithmetic_operators
|
||
|
|
df = pd.DataFrame({"A": data})
|
||
|
|
self.check_opname(df, op_name, data[0], exc=self.frame_scalar_exc)
|
||
|
|
|
||
|
|
def test_arith_series_with_array(self, data, all_arithmetic_operators):
|
||
|
|
# ndarray & other series
|
||
|
|
op_name = all_arithmetic_operators
|
||
|
|
ser = pd.Series(data)
|
||
|
|
self.check_opname(
|
||
|
|
ser, op_name, pd.Series([ser.iloc[0]] * len(ser)), exc=self.series_array_exc
|
||
|
|
)
|
||
|
|
|
||
|
|
def test_divmod(self, data):
|
||
|
|
ser = pd.Series(data)
|
||
|
|
self._check_divmod_op(ser, divmod, 1, exc=self.divmod_exc)
|
||
|
|
self._check_divmod_op(1, ops.rdivmod, ser, exc=self.divmod_exc)
|
||
|
|
|
||
|
|
def test_divmod_series_array(self, data, data_for_twos):
|
||
|
|
ser = pd.Series(data)
|
||
|
|
self._check_divmod_op(ser, divmod, data)
|
||
|
|
|
||
|
|
other = data_for_twos
|
||
|
|
self._check_divmod_op(other, ops.rdivmod, ser)
|
||
|
|
|
||
|
|
other = pd.Series(other)
|
||
|
|
self._check_divmod_op(other, ops.rdivmod, ser)
|
||
|
|
|
||
|
|
def test_add_series_with_extension_array(self, data):
|
||
|
|
ser = pd.Series(data)
|
||
|
|
result = ser + data
|
||
|
|
expected = pd.Series(data + data)
|
||
|
|
self.assert_series_equal(result, expected)
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("box", [pd.Series, pd.DataFrame])
|
||
|
|
def test_direct_arith_with_ndframe_returns_not_implemented(
|
||
|
|
self, request, data, box
|
||
|
|
):
|
||
|
|
# EAs should return NotImplemented for ops with Series/DataFrame
|
||
|
|
# Pandas takes care of unboxing the series and calling the EA's op.
|
||
|
|
other = pd.Series(data)
|
||
|
|
if box is pd.DataFrame:
|
||
|
|
other = other.to_frame()
|
||
|
|
if not hasattr(data, "__add__"):
|
||
|
|
request.node.add_marker(
|
||
|
|
pytest.mark.xfail(
|
||
|
|
reason=f"{type(data).__name__} does not implement add"
|
||
|
|
)
|
||
|
|
)
|
||
|
|
result = data.__add__(other)
|
||
|
|
assert result is NotImplemented
|
||
|
|
|
||
|
|
|
||
|
|
class BaseComparisonOpsTests(BaseOpsUtil):
|
||
|
|
"""Various Series and DataFrame comparison ops methods."""
|
||
|
|
|
||
|
|
def _compare_other(self, ser: pd.Series, data, op, other):
|
||
|
|
|
||
|
|
if op.__name__ in ["eq", "ne"]:
|
||
|
|
# comparison should match point-wise comparisons
|
||
|
|
result = op(ser, other)
|
||
|
|
expected = ser.combine(other, op)
|
||
|
|
self.assert_series_equal(result, expected)
|
||
|
|
|
||
|
|
else:
|
||
|
|
exc = None
|
||
|
|
try:
|
||
|
|
result = op(ser, other)
|
||
|
|
except Exception as err:
|
||
|
|
exc = err
|
||
|
|
|
||
|
|
if exc is None:
|
||
|
|
# Didn't error, then should match pointwise behavior
|
||
|
|
expected = ser.combine(other, op)
|
||
|
|
self.assert_series_equal(result, expected)
|
||
|
|
else:
|
||
|
|
with pytest.raises(type(exc)):
|
||
|
|
ser.combine(other, op)
|
||
|
|
|
||
|
|
def test_compare_scalar(self, data, comparison_op):
|
||
|
|
ser = pd.Series(data)
|
||
|
|
self._compare_other(ser, data, comparison_op, 0)
|
||
|
|
|
||
|
|
def test_compare_array(self, data, comparison_op):
|
||
|
|
ser = pd.Series(data)
|
||
|
|
other = pd.Series([data[0]] * len(data))
|
||
|
|
self._compare_other(ser, data, comparison_op, other)
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("box", [pd.Series, pd.DataFrame])
|
||
|
|
def test_direct_arith_with_ndframe_returns_not_implemented(self, data, box):
|
||
|
|
# EAs should return NotImplemented for ops with Series/DataFrame
|
||
|
|
# Pandas takes care of unboxing the series and calling the EA's op.
|
||
|
|
other = pd.Series(data)
|
||
|
|
if box is pd.DataFrame:
|
||
|
|
other = other.to_frame()
|
||
|
|
|
||
|
|
if hasattr(data, "__eq__"):
|
||
|
|
result = data.__eq__(other)
|
||
|
|
assert result is NotImplemented
|
||
|
|
else:
|
||
|
|
raise pytest.skip(f"{type(data).__name__} does not implement __eq__")
|
||
|
|
|
||
|
|
if hasattr(data, "__ne__"):
|
||
|
|
result = data.__ne__(other)
|
||
|
|
assert result is NotImplemented
|
||
|
|
else:
|
||
|
|
raise pytest.skip(f"{type(data).__name__} does not implement __ne__")
|
||
|
|
|
||
|
|
|
||
|
|
class BaseUnaryOpsTests(BaseOpsUtil):
|
||
|
|
def test_invert(self, data):
|
||
|
|
ser = pd.Series(data, name="name")
|
||
|
|
result = ~ser
|
||
|
|
expected = pd.Series(~data, name="name")
|
||
|
|
self.assert_series_equal(result, expected)
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("ufunc", [np.positive, np.negative, np.abs])
|
||
|
|
def test_unary_ufunc_dunder_equivalence(self, data, ufunc):
|
||
|
|
# the dunder __pos__ works if and only if np.positive works,
|
||
|
|
# same for __neg__/np.negative and __abs__/np.abs
|
||
|
|
attr = {np.positive: "__pos__", np.negative: "__neg__", np.abs: "__abs__"}[
|
||
|
|
ufunc
|
||
|
|
]
|
||
|
|
|
||
|
|
exc = None
|
||
|
|
try:
|
||
|
|
result = getattr(data, attr)()
|
||
|
|
except Exception as err:
|
||
|
|
exc = err
|
||
|
|
|
||
|
|
# if __pos__ raised, then so should the ufunc
|
||
|
|
with pytest.raises((type(exc), TypeError)):
|
||
|
|
ufunc(data)
|
||
|
|
else:
|
||
|
|
alt = ufunc(data)
|
||
|
|
self.assert_extension_array_equal(result, alt)
|