shortr 1.0.2

Arguments and value

adj.mat → n.mat. The first argument of interest is n.mat, not necessarily a symmetric adjacency matrix of numeric, but a symmetric matrix of numeric corresponding to the symmetric matrix of associations (e.g., of zero-order polychoric correlation coefficients) computed from the set of items comprised in the original version of the said psychometric instrument.
method → algorithm. The third argument of interest is algorithm (rather than method), a character matching either “brute.force” or “simulated.annealing” corresponding to the combinatorial search algorithm.

absolute now always TRUE.
max.iter now always base::ceiling(base::log(stop.temp / start.temp) / base::log(cool.fact)).

base::set.seed() no longer permanently alters the global RNG state. .Random.seed is now saved and restored via base::on.exit().
Progress bars are now closed via base::on.exit(), ensuring cleanup even on early exit or error.
The diagonal of the input matrix is now explicitly set to zero before computation, preventing self-associations from inflating the objective.
NA/NaN values in the input matrix now trigger a warning with a count of affected entries before being replaced with zeros.
Input validation now checks for Inf values, non-numeric entries, non-square matrices, and matrices smaller than 2 × 2.
Scalar parameter validation now checks length, type, and NA status consistently across all parameters.
algorithm now uses base::match.arg() instead of manual %in% checking, supporting partial matching.
SA-specific parameters (start.temp, cool.fact, stop.temp, n.runs, seed) are now validated only when algorithm = "simulated.annealing".
Error messages now use call. = FALSE for cleaner console output.
k = 0 and k = n are now rejected during validation rather than handled as special cases inside the algorithm.
seed now explicitly accepts NULL to skip setting the RNG state.

Subsets are now enumerated incrementally with delta updates to the objective function, replacing the previous approach of generating all candidate subsets in memory via utils::combn(). This reduces memory from O(C(n,k) × k) to O(n) and avoids recomputing the full objective at each step.
When k > n / 2, enumeration is performed over the smaller complement, reducing the number of combinations to evaluate.
The absolute value matrix is now precomputed once, rather than recomputed inside the objective function at every evaluation.
Brute force now detects intractable problems (C(n,k) exceeding .Machine$integer.max) and exits with a recommendation to use simulated annealing, rather than attempting to allocate the full combination matrix.

Swap evaluation now runs in O(n) via a maintained link vector, replacing the previous full matrix subsetting at each step.
The complement set is now maintained incrementally via a logical membership vector, replacing repeated base::setdiff() calls.
Removed the hash environment that stored all visited subsets as character keys, eliminating unbounded memory growth over long runs.