[SPARK-58470][PS] Use native expressions for NumPy trunc

[zhengruifeng]

What changes were proposed in this pull request?

Replace the pandas UDF mapping for NumPy trunc on pandas-on-Spark objects with native Spark expressions. The implementation uses the remainder of the absolute double value and reapplies the sign, preserving nulls, NaN, infinities, and signed zero. Add coverage for these values and fractional positive and negative inputs.

Why are the changes needed?

Spark does not provide a numeric trunc function, but the operation can be evaluated with native expressions without crossing the Python worker boundary.

Does this PR introduce any user-facing change?

No.

How was this patch tested?

• Added parity coverage in NumPyCompatTests.test_np_math_functions.
• Manually verified the native expression for signed zero, fractional values, infinities, NaN, and large doubles.
• Passed Ruff format and lint checks for the changed Python files.
• Focused PySpark tests were not run locally.

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Generated-by: Codex (GPT-5)