lidavidm commented on a change in pull request #10349:
URL: https://github.com/apache/arrow/pull/10349#discussion_r693986079
##########
File path: python/pyarrow/tests/test_compute.py
##########
@@ -1299,6 +1301,98 @@ def test_arithmetic_multiply():
assert result.equals(expected)
+@pytest.mark.parametrize("ty", ["round", "mround"])
+def test_round_to_integer(ty):
+ if ty == "round":
+ func = pc.round
+ RoundOptions = pc.RoundOptions
+ elif ty == "mround":
+ func = pc.mround
+ RoundOptions = pc.MRoundOptions
+
+ approx_equals = partial(np.isclose, equal_nan=True)
+ round_modes = [
+ "down", "up", "towards_zero", "towards_infinity", "half_down",
+ "half_up", "half_towards_zero", "half_towards_infinity",
+ "half_to_even", "half_to_odd",
+ ]
+ arr = pa.array([3.2, 3.5, 3.7, 4.5, -3.2, -3.5, -3.7, None])
+ for round_mode in round_modes:
+ options = RoundOptions(round_mode=round_mode)
+ result = func(arr, options=options).to_numpy(zero_copy_only=False)
+ if round_mode == "down":
+ expected_ = [3, 3, 3, 4, -4, -4, -4, None]
+ elif round_mode == "up":
+ expected_ = [4, 4, 4, 5, -3, -3, -3, None]
+ elif round_mode == "towards_zero":
+ expected_ = [3, 3, 3, 4, -3, -3, -3, None]
+ elif round_mode == "towards_infinity":
+ expected_ = [4, 4, 4, 5, -4, -4, -4, None]
+ elif round_mode == "half_down":
+ expected_ = [3, 3, 4, 4, -3, -4, -4, None]
+ elif round_mode == "half_up":
+ expected_ = [3, 4, 4, 5, -3, -3, -4, None]
+ elif round_mode == "half_towards_zero":
+ expected_ = [3, 3, 4, 4, -3, -3, -4, None]
+ elif round_mode == "half_towards_infinity":
+ expected_ = [3, 4, 4, 5, -3, -4, -4, None]
+ elif round_mode == "half_to_even":
+ expected_ = [3, 4, 4, 4, -3, -4, -4, None]
+ elif round_mode == "half_to_odd":
+ expected_ = [3, 3, 4, 5, -3, -3, -4, None]
+
+ expected = pa.array(expected_).to_numpy(zero_copy_only=False)
+ assert all(map(approx_equals, result, expected))
+
+
+def test_round():
+ approx_equals = partial(np.isclose, equal_nan=True)
+ round_ndigits = [-2, -1, 0, 1, 2]
+ arr = pa.array([320, 3.5, 3.075, 4.5, -3.212, -35.1234, -3.045, None])
+ for ndigits in round_ndigits:
+ options = pc.RoundOptions(
+ ndigits=ndigits, round_mode="half_towards_infinity")
+ result = pc.round(arr, options=options).to_numpy(zero_copy_only=False)
+ if ndigits == -2:
+ expected_ = [300, 0, 0, 0, 0, 0, 0, None]
+ elif ndigits == -1:
+ expected_ = [320, 0, 0, 0, 0, -40, 0, None]
+ elif ndigits == 0:
+ expected_ = [320, 4, 3, 5, -3, -35, -3, None]
+ elif ndigits == 1:
+ expected_ = [320, 3.5, 3.1, 4.5, -3.2, -35.1, -3, None]
+ elif ndigits == 2:
+ expected_ = [320, 3.5, 3.08, 4.5, -3.21, -35.12, -3.05, None]
+
+ expected = pa.array(expected_).to_numpy(zero_copy_only=False)
+ assert all(map(approx_equals, result, expected))
+
+
+def test_mround():
+ approx_equals = partial(np.isclose, equal_nan=True)
+ multiples = [-2, -0.05, 0.1, 0, 10, 100]
+ arr = pa.array([320, 3.5, 3.075, 4.5, -3.212, -35.1234, -3.045, None])
+ for multiple in multiples:
+ options = pc.MRoundOptions(
+ multiple=multiple, round_mode="half_towards_infinity")
+ result = pc.mround(arr, options=options).to_numpy(zero_copy_only=False)
+ if multiple == -2:
+ expected_ = [320, 4, 4, 4, -4, -36, -4, None]
+ elif multiple == -0.05:
+ expected_ = [320, 3.5, 3.1, 4.5, -3.2, -35.1, -3.05, None]
+ elif multiple == 0.1:
+ expected_ = [320, 3.5, 3.1, 4.5, -3.2, -35.1, -3, None]
+ elif multiple == 0:
+ expected_ = [0, 0, 0, 0, 0, 0, 0, None]
+ elif multiple == 10:
+ expected_ = [320, 0, 0, 0, 0, -40, 0, None]
+ elif multiple == 100:
+ expected_ = [300, 0, 0, 0, 0, 0, 0, None]
+
+ expected = pa.array(expected_).to_numpy(zero_copy_only=False)
Review comment:
Is there a reason why we have to unset zero_copy_only? False is the
default value anyways.
##########
File path: python/pyarrow/tests/test_compute.py
##########
@@ -1299,6 +1301,98 @@ def test_arithmetic_multiply():
assert result.equals(expected)
+@pytest.mark.parametrize("ty", ["round", "mround"])
+def test_round_to_integer(ty):
+ if ty == "round":
+ func = pc.round
+ RoundOptions = pc.RoundOptions
+ elif ty == "mround":
+ func = pc.mround
+ RoundOptions = pc.MRoundOptions
+
+ approx_equals = partial(np.isclose, equal_nan=True)
+ round_modes = [
+ "down", "up", "towards_zero", "towards_infinity", "half_down",
+ "half_up", "half_towards_zero", "half_towards_infinity",
+ "half_to_even", "half_to_odd",
+ ]
+ arr = pa.array([3.2, 3.5, 3.7, 4.5, -3.2, -3.5, -3.7, None])
+ for round_mode in round_modes:
+ options = RoundOptions(round_mode=round_mode)
+ result = func(arr, options=options).to_numpy(zero_copy_only=False)
+ if round_mode == "down":
+ expected_ = [3, 3, 3, 4, -4, -4, -4, None]
+ elif round_mode == "up":
+ expected_ = [4, 4, 4, 5, -3, -3, -3, None]
+ elif round_mode == "towards_zero":
+ expected_ = [3, 3, 3, 4, -3, -3, -3, None]
+ elif round_mode == "towards_infinity":
+ expected_ = [4, 4, 4, 5, -4, -4, -4, None]
+ elif round_mode == "half_down":
+ expected_ = [3, 3, 4, 4, -3, -4, -4, None]
+ elif round_mode == "half_up":
+ expected_ = [3, 4, 4, 5, -3, -3, -4, None]
+ elif round_mode == "half_towards_zero":
+ expected_ = [3, 3, 4, 4, -3, -3, -4, None]
+ elif round_mode == "half_towards_infinity":
+ expected_ = [3, 4, 4, 5, -3, -4, -4, None]
+ elif round_mode == "half_to_even":
+ expected_ = [3, 4, 4, 4, -3, -4, -4, None]
+ elif round_mode == "half_to_odd":
+ expected_ = [3, 3, 4, 5, -3, -3, -4, None]
+
+ expected = pa.array(expected_).to_numpy(zero_copy_only=False)
+ assert all(map(approx_equals, result, expected))
+
+
+def test_round():
+ approx_equals = partial(np.isclose, equal_nan=True)
+ round_ndigits = [-2, -1, 0, 1, 2]
+ arr = pa.array([320, 3.5, 3.075, 4.5, -3.212, -35.1234, -3.045, None])
+ for ndigits in round_ndigits:
+ options = pc.RoundOptions(
+ ndigits=ndigits, round_mode="half_towards_infinity")
+ result = pc.round(arr, options=options).to_numpy(zero_copy_only=False)
+ if ndigits == -2:
+ expected_ = [300, 0, 0, 0, 0, 0, 0, None]
+ elif ndigits == -1:
+ expected_ = [320, 0, 0, 0, 0, -40, 0, None]
+ elif ndigits == 0:
+ expected_ = [320, 4, 3, 5, -3, -35, -3, None]
+ elif ndigits == 1:
+ expected_ = [320, 3.5, 3.1, 4.5, -3.2, -35.1, -3, None]
+ elif ndigits == 2:
+ expected_ = [320, 3.5, 3.08, 4.5, -3.21, -35.12, -3.05, None]
+
+ expected = pa.array(expected_).to_numpy(zero_copy_only=False)
+ assert all(map(approx_equals, result, expected))
+
+
+def test_mround():
+ approx_equals = partial(np.isclose, equal_nan=True)
+ multiples = [-2, -0.05, 0.1, 0, 10, 100]
+ arr = pa.array([320, 3.5, 3.075, 4.5, -3.212, -35.1234, -3.045, None])
+ for multiple in multiples:
+ options = pc.MRoundOptions(
+ multiple=multiple, round_mode="half_towards_infinity")
+ result = pc.mround(arr, options=options).to_numpy(zero_copy_only=False)
+ if multiple == -2:
+ expected_ = [320, 4, 4, 4, -4, -36, -4, None]
+ elif multiple == -0.05:
+ expected_ = [320, 3.5, 3.1, 4.5, -3.2, -35.1, -3.05, None]
+ elif multiple == 0.1:
+ expected_ = [320, 3.5, 3.1, 4.5, -3.2, -35.1, -3, None]
+ elif multiple == 0:
+ expected_ = [0, 0, 0, 0, 0, 0, 0, None]
+ elif multiple == 10:
+ expected_ = [320, 0, 0, 0, 0, -40, 0, None]
+ elif multiple == 100:
+ expected_ = [300, 0, 0, 0, 0, 0, 0, None]
+
+ expected = pa.array(expected_).to_numpy(zero_copy_only=False)
Review comment:
And this could just be `np.array(...)` instead of bouncing through
PyArrow (though as noted below, you don't even need to do that).
##########
File path: python/pyarrow/tests/test_compute.py
##########
@@ -1299,6 +1301,98 @@ def test_arithmetic_multiply():
assert result.equals(expected)
+@pytest.mark.parametrize("ty", ["round", "mround"])
+def test_round_to_integer(ty):
+ if ty == "round":
+ func = pc.round
+ RoundOptions = pc.RoundOptions
+ elif ty == "mround":
+ func = pc.mround
+ RoundOptions = pc.MRoundOptions
+
+ approx_equals = partial(np.isclose, equal_nan=True)
+ round_modes = [
+ "down", "up", "towards_zero", "towards_infinity", "half_down",
+ "half_up", "half_towards_zero", "half_towards_infinity",
+ "half_to_even", "half_to_odd",
+ ]
+ arr = pa.array([3.2, 3.5, 3.7, 4.5, -3.2, -3.5, -3.7, None])
+ for round_mode in round_modes:
+ options = RoundOptions(round_mode=round_mode)
+ result = func(arr, options=options).to_numpy(zero_copy_only=False)
+ if round_mode == "down":
+ expected_ = [3, 3, 3, 4, -4, -4, -4, None]
+ elif round_mode == "up":
+ expected_ = [4, 4, 4, 5, -3, -3, -3, None]
+ elif round_mode == "towards_zero":
+ expected_ = [3, 3, 3, 4, -3, -3, -3, None]
+ elif round_mode == "towards_infinity":
+ expected_ = [4, 4, 4, 5, -4, -4, -4, None]
+ elif round_mode == "half_down":
+ expected_ = [3, 3, 4, 4, -3, -4, -4, None]
+ elif round_mode == "half_up":
+ expected_ = [3, 4, 4, 5, -3, -3, -4, None]
+ elif round_mode == "half_towards_zero":
+ expected_ = [3, 3, 4, 4, -3, -3, -4, None]
+ elif round_mode == "half_towards_infinity":
+ expected_ = [3, 4, 4, 5, -3, -4, -4, None]
+ elif round_mode == "half_to_even":
+ expected_ = [3, 4, 4, 4, -3, -4, -4, None]
+ elif round_mode == "half_to_odd":
+ expected_ = [3, 3, 4, 5, -3, -3, -4, None]
+
+ expected = pa.array(expected_).to_numpy(zero_copy_only=False)
+ assert all(map(approx_equals, result, expected))
+
+
+def test_round():
+ approx_equals = partial(np.isclose, equal_nan=True)
+ round_ndigits = [-2, -1, 0, 1, 2]
+ arr = pa.array([320, 3.5, 3.075, 4.5, -3.212, -35.1234, -3.045, None])
+ for ndigits in round_ndigits:
+ options = pc.RoundOptions(
+ ndigits=ndigits, round_mode="half_towards_infinity")
+ result = pc.round(arr, options=options).to_numpy(zero_copy_only=False)
+ if ndigits == -2:
+ expected_ = [300, 0, 0, 0, 0, 0, 0, None]
+ elif ndigits == -1:
+ expected_ = [320, 0, 0, 0, 0, -40, 0, None]
+ elif ndigits == 0:
+ expected_ = [320, 4, 3, 5, -3, -35, -3, None]
+ elif ndigits == 1:
+ expected_ = [320, 3.5, 3.1, 4.5, -3.2, -35.1, -3, None]
+ elif ndigits == 2:
+ expected_ = [320, 3.5, 3.08, 4.5, -3.21, -35.12, -3.05, None]
+
+ expected = pa.array(expected_).to_numpy(zero_copy_only=False)
+ assert all(map(approx_equals, result, expected))
+
+
+def test_mround():
+ approx_equals = partial(np.isclose, equal_nan=True)
+ multiples = [-2, -0.05, 0.1, 0, 10, 100]
+ arr = pa.array([320, 3.5, 3.075, 4.5, -3.212, -35.1234, -3.045, None])
+ for multiple in multiples:
+ options = pc.MRoundOptions(
+ multiple=multiple, round_mode="half_towards_infinity")
+ result = pc.mround(arr, options=options).to_numpy(zero_copy_only=False)
+ if multiple == -2:
+ expected_ = [320, 4, 4, 4, -4, -36, -4, None]
+ elif multiple == -0.05:
+ expected_ = [320, 3.5, 3.1, 4.5, -3.2, -35.1, -3.05, None]
+ elif multiple == 0.1:
+ expected_ = [320, 3.5, 3.1, 4.5, -3.2, -35.1, -3, None]
+ elif multiple == 0:
+ expected_ = [0, 0, 0, 0, 0, 0, 0, None]
+ elif multiple == 10:
+ expected_ = [320, 0, 0, 0, 0, -40, 0, None]
+ elif multiple == 100:
+ expected_ = [300, 0, 0, 0, 0, 0, 0, None]
+
+ expected = pa.array(expected_).to_numpy(zero_copy_only=False)
+ assert all(map(approx_equals, result, expected))
Review comment:
nit: it would be more natural to use np.all(np.isclose(arr1, arr2,
equal_nan=True)) instead of using map/partial/all.
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