analyze: chunk per-plot aggregation across HTCondor jobs

Add a second parallelism axis to giant analyze: each plot's data can now
be split into a configurable number of event_id-disjoint chunks, each
computed as its own HTCondor job, bounding per-job walltime and scan cost
on large rollout/reference files instead of one job re-scanning the
whole file per plot.

Every PlotSpec now splits into compute_partial (runs per (plot, chunk)
job against a chunk-filtered Bundle) and finalize (merges chunks -
elementwise sum for fixed-edge histograms/species shares, concatenate
-then-recompute for specs that derive edges or mean/std from the full
per-event/per-secondary array). Router diagnostics stay chunkable=False
and always run as a single job. giant analyze render now joins every
plot's chunk partials (merge_all) before rendering, transparently.

New: --chunks on `analyze prep`/`analyze submit`, --chunk on
`analyze compute-one`, and a new `analyze merge-one` command.

giant/analysis/render.py

@@ -303,12 +303,16 @@ def render_all(
 def render_run(run_dir: str | Path, *, run_gallery: bool = False) -> list[Path]:
     """Render a prepped run directory: ``<run_dir>/reduced`` → ``<run_dir>/plots``.
 
-    Pulls the rollout provenance (checkpoint, paths, cutoffs) from
-    ``run_meta.json`` into every plot's gallery metadata.
+    First joins every plot's chunk partials (``reduced_partial/<id>__*.json``)
+    into ``reduced/<id>.json`` via ``merge_all`` — a no-op merge when the run
+    wasn't chunked (``n_chunks=1``) — then pulls the rollout provenance
+    (checkpoint, paths, cutoffs) from ``run_meta.json`` into every plot's
+    gallery metadata and renders.
     """
-    from giant.analysis.condor import RunMeta
+    from giant.analysis.condor import RunMeta, merge_all
 
     run_dir = Path(run_dir)
+    merge_all(run_dir)
     meta = RunMeta.load(run_dir / "run_meta.json")
     run_meta = {
         "title": meta.title,