fix: expand float fuzz coverage and correct discovered inconsistencies

[Theodus]

Which issue does this PR close?

• Closes ScalarValue::eq_array is inconsistent with ScalarValue equality for floating-point values #24431.
• Closes Grouped floating-point MIN and MAX return order-dependent results for NaNs and signed zeros #24432.

Rationale for this change

Two floating-point edge cases produced inconsistent results:

• ScalarValue::eq_array used IEEE equality for floats, while ScalarValue equality uses bit representations. An identical NaN therefore compared unequal, while +0.0 and -0.0 compared equal.
• Grouped floating-point MIN and MAX used partial ordering. With NaNs or signed zeros, results could depend on input order, batching, or partitioning and disagree with the non-grouped accumulators.

Both issues were exposed by generating special floating-point values in fuzz data and adding fuzz coverage for ScalarValue array conversions.

What changes are included in this PR?

• Generate +0.0, -0.0, positive and negative infinities, and NaNs with varied signs and payloads in random Float32 and Float64 test data.
• Add fuzz coverage checking consistency and round trips among ScalarValue::try_from_array, eq_array, to_array, and iter_to_array across supported array types and sliced arrays.
• Make Float16, Float32, and Float64 ScalarValue::eq_array comparisons use the same bitwise equality as ScalarValue::PartialEq.
• Make grouped Float16, Float32, and Float64 MIN/MAX use total ordering and total-order extrema as their initial accumulator values.

Are these changes tested?

Yes. The existing scalar_eq_array test now covers NaNs and signed zeros. New deterministic grouped-accumulator tests cover positive and negative NaNs, signed zeros, and the total-order sentinel values. The scalar conversion and aggregation fuzz tests cover the same paths across randomized arrays and execution configurations.

Are there any user-facing changes?

Yes. ScalarValue::eq_array now uses bitwise float equality, and grouped floating-point MIN and MAX now return deterministic results consistent with DataFusion's existing total-order semantics. There are no API signature changes.

[Jefffrey]

cc @comphead since you worked on something similar before

• feat: Support IEEE 754 negative zero semantics #22835

[codecov-commenter]

Codecov Report

❌ Patch coverage is 76.25000% with 19 lines in your changes missing coverage. Please review.
✅ Project coverage is 81.24%. Comparing base (bb038a6) to head (567e7aa).
⚠️ Report is 2 commits behind head on main.

Files with missing lines	Patch %	Lines
test-utils/src/array_gen/random_data.rs	0.00%	14 Missing ⚠️
datafusion/common/src/scalar/mod.rs	25.00%	1 Missing and 2 partials ⚠️
datafusion/functions-aggregate/src/min_max.rs	96.77%	0 Missing and 2 partials ⚠️

Additional details and impacted files

@@           Coverage Diff            @@
##             main   #24433    +/-   ##
========================================
  Coverage   81.23%   81.24%            
========================================
  Files        1112     1112            
  Lines      390635   390982   +347     
  Branches   390635   390982   +347     
========================================
+ Hits       317350   317650   +300     
- Misses      54650    54687    +37     
- Partials    18635    18645    +10     

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