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[SPARK-58548][PS] Use native Spark function for NumPy heaviside #57749

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[SPARK-58548][PS] Use native Spark function for NumPy heaviside #57749

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46e07d7
[SPARK-58548][PS] Use native Spark function for NumPy heaviside
zhengruifeng Aug 4, 2026
a9b5136
nit
zhengruifeng Aug 4, 2026
5fa0b3e
[SPARK-58548][PS] Fix NumPy heaviside formatting
zhengruifeng Aug 5, 2026
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10 changes: 7 additions & 3 deletions python/pyspark/pandas/numpy_compat.py
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Original file line number Diff line number Diff line change
Expand Up @@ -118,9 +118,13 @@
"fmin": lambda c1, c2: F.least(c1, c2).cast("double"),
"fmod": pandas_udf(lambda s1, s2: np.fmod(s1, s2), DoubleType()), # type: ignore[call-overload]
"gcd": pandas_udf(lambda s1, s2: np.gcd(s1, s2), DoubleType()), # type: ignore[call-overload]
"heaviside": pandas_udf( # type: ignore[call-overload]
lambda s1, s2: np.heaviside(s1, s2), DoubleType()
),
"heaviside": lambda c1, c2: F.when(
c1.isNull() | F.isnan(c1.cast("double")),
c1.cast("double"),
)
.when(c1 < 0, F.lit(0.0))
.when(c1 == 0, c2.cast("double"))
.otherwise(F.lit(1.0)),
"hypot": F.hypot,
"lcm": pandas_udf(lambda s1, s2: np.lcm(s1, s2), DoubleType()), # type: ignore[call-overload]
"ldexp": pandas_udf( # type: ignore[call-overload]
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15 changes: 15 additions & 0 deletions python/pyspark/pandas/tests/test_numpy_compat.py
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Expand Up @@ -187,6 +187,21 @@ def test_np_fmax_fmin(self):
expected = np_func(pdf.x1, pdf.x2)
self.assert_eq(result, expected, almost=True)

def test_np_heaviside(self):
for pdf in (
pd.DataFrame({"x1": [-2, -1, 0, 1, 2], "x2": [-2, -1, 0, 1, 2]}),
pd.DataFrame(
{
"x1": [-np.inf, -2.0, -0.0, 0.0, 0.0, 2.0, np.inf, np.nan],
"x2": [2.0, -2.0, -0.0, 0.5, np.nan, np.nan, -0.0, 2.0],
}
),
):
psdf = ps.from_pandas(pdf)
self.assert_eq(
np.heaviside(psdf.x1, psdf.x2), np.heaviside(pdf.x1, pdf.x2), almost=True
)

def test_np_spark_compat_series(self):
from pyspark.pandas.numpy_compat import unary_np_spark_mappings, binary_np_spark_mappings

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