openvax / vaxrank / 25807635104
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Fix #289: NaN-tolerant Prediction construction + JSON writer (#290)

Two layered fixes for the issue where JSON output crashed on real
HCC1395 data with ``ValueError: Out of range float values are not
JSON compliant``:

**Root cause.** The topiary frame returned by ``mhctools.MHCflurry``
+ ``TopiaryPredictor`` carries NaN in the ``value`` column for
``pMHC_presentation`` rows by design — presentation is a probability
that lives in the ``score`` column, not an IC50. The previous
``predict_epitopes`` row loop fell back from ``affinity`` (NaN) to
``value`` (also NaN) and wrote NaN straight into
``Prediction.value``, poisoning every downstream consumer including
``simplejson`` (strict-mode rejects NaN / Inf).

**Producer fix.** New ``_finite_or_none`` helper in
``vaxrank.epitope_logic`` coerces NaN / Inf / None to None at the
point where ``Prediction.value`` and ``percentile_rank`` get
populated. ``Prediction.value`` now honestly carries either an IC50
(finite) or ``None`` (no IC50 for this kind) — never NaN. Same fix
applied to the WT comparator construction below.

**Writer hardening.** New ``_to_json_nan_tolerant`` wrapper around
``serializable.to_json`` calls ``simplejson.dumps(..., ignore_nan=True)``
so any NaN that slips past the producer guards renders as JSON
``null`` instead of crashing the whole report. Defense in depth for
future predictor adapters or custom score expressions.

**Tests.** ``tests/test_nan_robustness.py`` (9 tests) pins:
- ``_finite_or_none`` semantics (NaN/Inf/None → None; finite passes through)
- ``predict_epitopes`` on a topiary frame with NaN-valued presentation
  rows produces ``Prediction.value=None`` for presentation, never NaN
- ``_to_json_nan_tolerant`` round-trips NaN/Inf as ``null`` in dicts,
  nested dicts, and lists
- Sanity baseline that ``simplejson`` *default* rejects NaN
  (documents why the wrapper exists)

Verified on real data: HCC1395 smoke run (25 PASS somatic variants,
6 HLA-I alleles, mhcflurry default pr... (continued)
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