Add parallel computing support to antibiogram() and wisca() (#281) (#282)

* Add parallel computing support to antibiogram() and wisca() (#281)

For WISCA: simulations are distributed across (group, chunk) job pairs
via future.apply::future_lapply(), keeping all workers active even when
the regimen count is smaller than nbrOfWorkers(). Sequential fallback
with progress ticker is preserved when parallel = FALSE or workers = 1.

For grouped antibiograms: each group is processed by a separate worker,
mirroring the row-batch approach in as.sir().

Same gate pattern as as.sir() (PR #280): requires a non-sequential
future::plan() to be active; auto-upgrades to parallel = TRUE when a
parallel plan is detected; throws an informative error otherwise.

https://claude.ai/code/session_01FC43syPbzhGmKgrrVNHjnF

* Fix version to 3.0.1.9055 and update CLAUDE.md version formula

Uses origin/${defaultbranch} (with a fetch) instead of the local
branch ref so the commit count is never stale after a merge.

https://claude.ai/code/session_01FC43syPbzhGmKgrrVNHjnF

* Fix non-ASCII characters in antibiogram.R

Replace en/em dashes and non-breaking spaces with ASCII equivalents
to satisfy R CMD check portability requirement.

https://claude.ai/code/session_01FC43syPbzhGmKgrrVNHjnF

* Update auto-generated Rd files after documentation rebuild

https://claude.ai/code/session_01FC43syPbzhGmKgrrVNHjnF

* Move parallel gate to top of antibiogram.default() like sir.R

The gate was inside the wisca==TRUE block, so parallel=TRUE with a
sequential plan was silently ignored for non-WISCA antibiograms.
Now the gate runs unconditionally at the top of the function,
identical to the as.sir() pattern: error on explicit parallel=TRUE
with sequential plan, auto-upgrade when a non-sequential plan is
already active.

https://claude.ai/code/session_01FC43syPbzhGmKgrrVNHjnF

* Fix parallel WISCA returning all NA; strengthen tests; add sequential hint

Bug: lapply() over a factor yields length-1 factor elements (integer
codes), while for() over a factor yields character strings.  The job
list stored j\$group as a factor integer, but the reassembly loop
compared it with identical(j\$group, g) where g was character -- always
FALSE, so no simulation chunks were ever assembled and coverage stayed
NA throughout.

Fix: convert unique_groups to character before building jobs so both
the job list and the reassembly loop use the same type.

Tests: replaced na.rm = TRUE guards with explicit anyNA() checks so the
test suite would have caught the all-NA result immediately.

Also adds a sequential-mode performance hint (analogous to sir.R
lines 1116-1127) when simulations >= 500 and >= 3 regimens.

https://claude.ai/code/session_01FC43syPbzhGmKgrrVNHjnF

---------

Co-authored-by: Claude <noreply@anthropic.com>

man/pca.Rd

@@ -32,7 +32,7 @@ pca(x, ..., retx = TRUE, center = TRUE, scale. = TRUE, tol = NULL,
     standard deviations are less than or equal to \code{tol} times the
     standard deviation of the first component.)  With the default null
     setting, no components are omitted (unless \code{rank.} is specified
-    less than \code{min(dim(x))}.).  Other settings for \code{tol} could be
+    less than \code{min(dim(x))}.).  Other settings for tol could be
     \code{tol = 0} or \code{tol = sqrt(.Machine$double.eps)}, which
     would omit essentially constant components.}