ABI — Changes Log

2026-07-11 — ABI 2.2.0: HPO terminal lifecycle and owning rich trace

Additive MINOR change: n4m_trial_status_t adds the public terminal value N4M_TRIAL_CANCELLED=4. No function symbol or public struct layout changed. The existing n4m_optimizer_tell_result now persists a structured {code, message, retryable} error for FAILED and CANCELLED; explicit fields use the fail-closed versioned text wire n4m.error.v1|CODE|0-or-1|message. Invalid UTF-8 is rejected before lifecycle mutation; search-space names and string categorical labels are checked at their builder boundaries as well.

The existing n4m_optimizer_get_trials method-result payload retains its five compatibility matrices and adds trace-v1 keys for exact int64 ids, ordered parameters and activation/category metadata, optimizer-global event order, intermediate values, and structured errors. Its result is an owning snapshot whose buffers survive optimizer destruction. Python exposes the payload as owning TrialRecord, TrialParameter, IntermediateValue, and TrialError objects through Optimizer.get_trials(since_id=...).

The already-exported n4m_optimizer_save and n4m_optimizer_load reservations are now activated without a symbol, signature, enum, struct-layout, ABI-version, or SONAME change. They read/write the portable little-endian N4MOPT v1 study checkpoint. Load is transactional and fail-closed for corruption, future versions, excessive sizes/counts, and inconsistent option/search-space/sampler state. Exported-symbol snapshots remain 733/733, and SONAME remains libn4m.so.2.

2026-07-10 — ABI 2.1.0: native HPO optimizer surface (optimization role)

Additive change (MINOR). New role header cpp/include/n4m/optimization.h — a handle-based ask/tell hyperparameter optimizer + typed search space. All sampler/pruner algorithms sit behind reserved enum values (n4m_sampler_kind_t, n4m_pruner_kind_t); F0 implements only random + none, and reserved values return N4M_ERR_NOT_IMPLEMENTED, so Phase-1 samplers/pruners (F1–F4) add no further public symbols. See docs/FINETUNING_F0_PR.md.

31 new N4M_API symbols:

• search space (9): n4m_search_space_create, _destroy, _add_int, _add_float, _add_categorical, _add_ordinal, _add_sorted_tuple, _add_constraint, _num_params.

• optimizer (13): n4m_optimizer_options_init, n4m_optimizer_create, _destroy, _enqueue, _ask, _ask_batch, _tell, _tell_result, _tell_intermediate, _best, _get_trials, _save, _load (_save/_load were reserved in 2.1 and activated by N4MOPT v1 in 2.2 without changing their signatures).

• trial accessors (8): n4m_trial_get_id, _get_int, _get_float, _get_category, _is_active, _get_rung, _get_status, _get_duration.

• pure-native driver (1): n4m_finetune_estimator.

New 4-byte enums (guard-railed in optimization.h): n4m_param_kind_t, n4m_cat_type_t, n4m_constraint_kind_t, n4m_sampler_kind_t, n4m_pruner_kind_t, n4m_opt_direction_t, n4m_eval_mode_t, n4m_metric_t, n4m_liar_kind_t, n4m_trial_status_t. New value struct n4m_optimizer_options_t (forward-compatible via a struct_size prologue).

Later within 2.1.0 (still additive, no symbol/size change): the reserved tail of n4m_optimizer_options_t was narrowed from reserved[64] to two named int32_t fields — max_resource, reduction_factor (for hyperband/asha) — plus reserved[56]. sizeof(n4m_optimizer_options_t) is unchanged (verified C == Python == 120 bytes) and no exported symbol changed, so this is ABI-compatible: callers that zero-initialise via n4m_optimizer_options_init get 0 (= auto/default) for both. All nine n4m_sampler_kind_t values and all five n4m_pruner_kind_t values are now implemented (reserved-value dispatch now only fires for out-of-range enums).

2026-06-14 — ABI 2.0.0: namespace clean break (all method symbols renamed)

Breaking change. Every public method symbol was renamed to the canonical role-based convention n4m_<role>_<leaf><tail>, where role is the top-level ML namespace (augmentation, compose, decomposition, domain_adaptation, ensemble, estimators, feature_selection, lowlevel, metrics, model_selection, outlier_detection, transform), leaf is the catalog leaf, and <tail> is the existing operation suffix preserved byte-for-byte (_fit, _create, _destroy, _transform, _select, _split, _result_get_*, …). No runtime aliases were kept — the terse legacy exports (n4m_pp_*, n4m_aug_*, n4m_split_*, n4m_filter_*, n4m_aom_*, n4m_metric_*, n4m_util_*, n4m_ridge_fit, n4m_pls_fit_simple, …) are gone.

• 566 method symbols renamed (deterministically, from catalog/methods.yaml via proposals/namespace/_build_rename_map.py → _rename_map.tsv; 0 collisions). Examples: n4m_ridge_fit → n4m_estimators_ridge_fit, n4m_pp_snv_create → n4m_transform_snv_create, n4m_pls_fit_simple → n4m_estimators_pls_fit (drop “simple”), n4m_aom_global_result_get_best_score → n4m_model_selection_aom_pls_result_get_best_score, n4m_util_hotelling_t2 → n4m_outlier_detection_hotelling_t2, n4m_metric_rmse → n4m_metrics_regression_metrics_rmse.

• 136 infra symbols unchanged (context, config, matrix view, RNG, model, pipeline, validation plan, method-result, serialization, array, backends).

• The 10 Python-only methods (c_surface: "none") export no C symbol.

• Exported surface total: 702 (566 method + 136 infra). Linux version node bumped N4M_1 → N4M_2; SONAME is now libn4m.so.2.

• Public headers were split into role headers + 2nd-level subheaders (transform/*.h, estimators/*.h, augmentation/*.h, lowlevel.h, …); the umbrella n4m.h keeps the shared infra and includes the role headers. The flat pls.h and the empty category stubs (aom_pop.h, preprocessing.h, models.h, selection.h, splitters.h, filters.h, diagnostics.h, transfer.h, utilities.h, context.h) were deleted (no compat include).

• ABI snapshots regenerated for all three platforms; N4M_ABI_VERSION_* set to 2.0.0. Numerics are unchanged — this is a surface rename only.

2026-06-06 — ABI 1.22.0: PLS CV reference surface

One additive public symbol:

• n4m_pls_cross_validate

This is a C/Python ABI entry point for exact PLS-only cross-validation over one input matrix. The current implementation delegates to the PLS branch of n4m_sweep_run, so candidate scores and CPU/CUDA route counters match the existing sweep path. It is intentionally catalogued as ABI infrastructure, not as a production method. The future fused/batched IKPLS-style multi-chain executor can replace the internals without changing this signature.

2026-06-05 — ABI 1.21.0: CUDA PLS many-design batching config

Two additive public config helpers:

• n4m_config_set_cuda_pls_many_batched

• n4m_config_get_cuda_pls_many_batched

The default remains off. When enabled on a CUDA build, eligible PLS1 moment many-design jobs may use the experimental tiled/strided-batched route that also remains reachable through the N4M_CUDA_PLS_MANY_BATCHED environment fallback. This changes only GPU scheduling and timings; candidate scores remain fold-level exact for the selected scoring path.

2026-06-05 — ABI 1.20.0: CUDA PLS device threshold config

Two additive public config helpers:

• n4m_config_set_cuda_pls_min_device_features

• n4m_config_get_cuda_pls_min_device_features

The default threshold remains 1024 features, matching the conservative historical CUDA PLS1 moment guard. Lower positive values let CPU/CUDA crossover campaigns explicitly test medium-width PLS moment screens on the selected single GPU without recompiling. This changes only route eligibility and timing; candidate scores are unchanged for a given exact scoring path.

2026-06-05 — ABI 1.19.0: CUDA PLS fold scheduling config

Two additive public config helpers:

• n4m_config_set_cuda_pls_parallel_folds

• n4m_config_get_cuda_pls_parallel_folds

When enabled on a CUDA build, eligible exact PLS1 moment CV jobs may run in bounded stream-parallel batches on the single selected GPU. This changes only scheduling and timings; candidate scores are unchanged. Sweep and AOM MethodResults also expose additive scalar counters n_pls_moment_cuda_parallel_fold_batches and n_pls_moment_cuda_parallel_fold_jobs for fit-cost auditing.

2026-06-05 — ABI 1.18.x: strict AOM Gaussian operator kind

No public symbol or result layout change. The public operator enum gains one additive value:

• N4M_OP_GAUSSIAN = 18

This value is accepted by the strict AOM chain sweep and represents a fixed, shape-preserving zero-padding Gaussian convolution with a banded operator-moment descriptor. It is distinct from the full pp_gaussian preprocessing transformer surface.

2026-06-05 — ABI 1.18.x: AOM chain fixed final fit

One additive public symbol:

• n4m_aom_chain_fixed_fit_run(n4m_context_t*, const n4m_config_t*, const n4m_matrix_view_t* X, const n4m_matrix_view_t* Y, const int32_t* chain_offsets, int64_t n_chain_offsets, const int32_t* op_kinds, int64_t n_op_kinds, const int32_t* param_offsets, int64_t n_param_offsets, const double* params, int64_t n_params, int32_t head_id, double param, n4m_method_result_t** out_result)

This fits one already-selected caller-provided strict-linear AOM chain/head/parameter on all rows without running CV. It is a model-building endpoint, not a ranking endpoint: CV score fields are NaN unless a higher-level wrapper injects an externally verified exact-CV score. Python uses this in NativeAOMScreenRefitRegressor after exact-CV refit so reusable model construction no longer repays one-candidate CV.

2026-06-05 — ABI 1.18.x: AOM score-only screen output mode

Two additive public config helpers:

• n4m_config_set_aom_score_only

• n4m_config_get_aom_score_only

When enabled for n4m_aom_sweep_run or n4m_aom_chain_sweep_run, the result keeps the candidate-score table, selected identifiers, route counters and fold ids, but omits selected-model matrices by returning them as 0 x 0. This is an additive output/cost-control knob for large preprocessing ranking passes.

2026-06-04 — ABI 1.18.0: native AOM operator PLS score stack

One additive public symbol (ABI MINOR bump 1.17.0 -> 1.18.0), backward-compatible (no signature/layout change, nothing removed):

• n4m_aom_operator_pls_stack_fit(n4m_context_t*, const n4m_config_t*, const n4m_matrix_view_t* X, const n4m_matrix_view_t* Y, int32_t profile, int32_t cv, const int32_t* fold_ids, int64_t n_fold_ids, const int32_t* components, int64_t n_components, const double* alphas, int64_t n_alphas, double std_penalty, double gap_penalty, n4m_method_result_t** out_result)

This exposes a native strict-linear AOM operator PLS1 score stack. The method builds compact or wide AOM operator banks, fits fold-local PLS1 score projectors per operator, concatenates the scores, selects (n_components, alpha) by train-only CV criterion, and refits the selected stack on all rows with a Ridge head.

The returned n4m_method_result_t carries candidate_scores, fold_scores, oof_predictions, predictions, stack_features, coefficients, intercept, fold_ids and operator_feature_offsets. candidate_scores columns are spec_id, n_components, alpha, mean_oof_rmse, std_oof_rmse, mean_train_rmse, criterion.

Native v1 is single-target (Y.cols == 1) and not yet a fused batched GPU stack. Custom Python operator matrices, shuffled/both CV and baseline admission gating remain in the Python AOMOperatorPLSStack estimator.

The implementation lives in cpp/src/core/aom_operator_pls_stack.cpp and is dispatched from cpp/src/c_api/c_api_method_result.cpp. The symbol is declared in cpp/include/n4m/pls.h, exported in all ABI snapshots, catalogued as aom_pop.operator_pls_stack, wrapped in Python as n4m.aom_operator_pls_stack, and documented in docs/methods/aom_operator_pls_stack.md.

2026-06-04 — ABI 1.17.0: native AOM Ridge OOF simplex blender

One additive public symbol (ABI MINOR bump 1.16.0 -> 1.17.0), backward-compatible (no signature/layout change, nothing removed):

• n4m_aom_ridge_blender_fit(n4m_context_t*, const n4m_config_t*, const n4m_matrix_view_t* X, const n4m_matrix_view_t* Y, int32_t profile, int32_t cv, const int32_t* fold_ids, int64_t n_fold_ids, const double* ridge_lambdas, int64_t n_ridge_lambdas, double regularizer, n4m_method_result_t** out_result)

This exposes a native strict-linear AOM Ridge candidate blender. The method builds compact or wide AOM chain banks, scores each chain/lambda candidate by fold-local OOF Ridge predictions, solves a regularized non-negative simplex blend, and refits all candidates on the full training data for final blended predictions.

The returned n4m_method_result_t carries candidate_scores, weights, oof_predictions, predictions, oof_candidate_predictions, candidate_predictions and fold_ids. candidate_scores columns are candidate_id, chain_id, lambda, cv_rmse, weight.

Native v1 requires strictly positive Ridge lambdas and is not yet a fused batched GPU blender. It builds in CUDA-enabled configurations, but the candidate loop still uses the existing native Ridge path per fold/candidate.

The implementation lives in cpp/src/core/aom_ridge_blender.cpp and is dispatched from cpp/src/c_api/c_api_method_result.cpp. The symbol is declared in cpp/include/n4m/pls.h, exported in all ABI snapshots, catalogued as aom_pop.ridge_blender, wrapped in Python as n4m.aom_ridge_blender, and documented in docs/methods/aom_ridge_blender.md.

2026-06-04 — ABI 1.16.0: user-defined AOM chain sweep

One additive public symbol (ABI MINOR bump 1.15.0 -> 1.16.0), backward-compatible (no signature/layout change, nothing removed):

• n4m_aom_chain_sweep_run(n4m_context_t*, const n4m_config_t*, const n4m_matrix_view_t* X, const n4m_matrix_view_t* Y, int32_t cv, const int32_t* fold_ids, int64_t n_fold_ids, const int32_t* chain_offsets, int64_t n_chain_offsets, const int32_t* op_kinds, int64_t n_op_kinds, const int32_t* param_offsets, int64_t n_param_offsets, const double* params, int64_t n_params, const double* ridge_lambdas, int64_t n_ridge_lambdas, const int32_t* pls_components, int64_t n_pls_components, int32_t heads_mask, n4m_method_result_t** out_result)

This exposes a flat descriptor for caller-provided strict-linear preprocessing chains. chain_offsets partitions op_kinds; param_offsets partitions the flat params payload. Empty chains are rejected; callers use an explicit identity operator for raw spectra. Supported operators are identity, polynomial detrend, Savitzky-Golay smooth/derivative, Norris-Williams, finite difference, Whittaker, FCK and Gaussian.

The result shape matches n4m_aom_sweep_run; candidate_scores columns are candidate_id, chain_id, head_id, param, cv_rmse, and scalar profile is -1 for caller-provided chains.

This is the first ABI-stable arbitrary strict-linear preprocessing-chain surface. It still materializes transformed matrices per chain and uses materialized PLS CV; fused operator-moment updates, batched IKPLS and CUDA kernels remain later acceleration work.

The implementation lives in cpp/src/core/aom_sweep.cpp and is dispatched from cpp/src/c_api/c_api_method_result.cpp. The symbol is declared in cpp/include/n4m/pls.h, catalogued as aom_pop.aom_chain_sweep, wrapped in Python as n4m.aom_chain_sweep_run, and documented in docs/methods/aom_chain_sweep_run.md.

2026-06-04 — ABI 1.15.0: configurable native AOM preprocessing sweep

One additive public symbol (ABI MINOR bump 1.14.0 -> 1.15.0), backward-compatible (no signature/layout change, nothing removed):

• n4m_aom_sweep_run(n4m_context_t*, const n4m_config_t*, const n4m_matrix_view_t* X, const n4m_matrix_view_t* Y, int32_t profile, int32_t cv, const int32_t* fold_ids, int64_t n_fold_ids, const double* ridge_lambdas, int64_t n_ridge_lambdas, const int32_t* pls_components, int64_t n_pls_components, int32_t heads_mask, n4m_method_result_t** out_result)

The symbol applies the native strict-linear AOM compact/wide preprocessing chain bank, then delegates candidate scoring to n4m_sweep_run over Ridge lambdas and/or PLS component counts. It returns candidate_scores, oof_predictions, final predictions, coefficients/intercept and fold ids. candidate_scores has columns candidate_id, chain_id, head_id, param, cv_rmse; head_id is 0 for Ridge and 1 for PLS.

This is a configurable product sweep over the fixed AOM strict-linear banks. It is not yet the arbitrary operator-descriptor layer or fused batched IKPLS/CUDA grinder.

The implementation lives in cpp/src/core/aom_sweep.cpp and is dispatched from cpp/src/c_api/c_api_method_result.cpp. The symbol is declared in cpp/include/n4m/pls.h, exported in all ABI snapshots, catalogued as aom_pop.aom_sweep, wrapped in Python as n4m.aom_sweep_run, and documented in docs/methods/aom_sweep_run.md.

2026-06-04 — ABI 1.14.0: native Ridge/PLS sweep

One additive public symbol (ABI MINOR bump 1.13.0 -> 1.14.0), backward-compatible (no signature/layout change, nothing removed):

• n4m_sweep_run(n4m_context_t*, const n4m_config_t*, const n4m_matrix_view_t* X, const n4m_matrix_view_t* Y, int32_t cv, const int32_t* fold_ids, int64_t n_fold_ids, const double* ridge_lambdas, int64_t n_ridge_lambdas, const int32_t* pls_components, int64_t n_pls_components, int32_t heads_mask, n4m_method_result_t** out_result)

ABI v1 supports exact Ridge CV over row-additive moments where efficient, with a precomputed dual Ridge path when p > n_train. It also supports fold-local materialized PLS component screening through the existing native PLS model path. The returned n4m_method_result_t carries candidate_scores, oof_predictions, final predictions, coefficients/intercept and fold ids. candidate_scores[:,1] is 0 for Ridge and 1 for PLS; param is lambda for Ridge and n_components for PLS.

The fused batched IKPLS/operator-descriptor grinder is not part of ABI v1.

The implementation lives in cpp/src/core/sweep.cpp and is dispatched from cpp/src/c_api/c_api_method_result.cpp. The symbol is declared in cpp/include/n4m/pls.h, exported in all ABI snapshots, catalogued as utilities.sweep, wrapped in Python as n4m.sweep_run, and documented in docs/methods/sweep_run.md.

2026-06-04 — ABI 1.13.0: native row-additive moment substrate

Three additive public symbols (ABI MINOR bump 1.12.0 -> 1.13.0), backward-compatible (no signature/layout change, nothing removed):

• n4m_moments_compute(n4m_context_t*, const n4m_matrix_view_t* X, const n4m_matrix_view_t* Y, n4m_method_result_t** out_result)

• n4m_moments_subset_compute(n4m_context_t*, const n4m_matrix_view_t* X, const n4m_matrix_view_t* Y, const int64_t* row_indices, int64_t n_indices, n4m_method_result_t** out_result)

• n4m_moments_subtract(n4m_context_t*, const n4m_method_result_t* lhs, const n4m_method_result_t* rhs, n4m_method_result_t** out_result)

The result is a n4m_method_result_t carrying raw additive moments (x_sum, y_sum, xtx, xty, yty) and centered moments recomputed from the raw sums (x_mean, y_mean, cxx, cxy, cyy). This gives an exact fold-subtraction primitive for PLS/Ridge screens: compute all rows, compute the held-out rows, subtract raw moments, then recenter on the remaining train rows.

The implementation lives in cpp/src/core/moments.cpp and is dispatched from cpp/src/c_api/c_api_method_result.cpp. The symbols are declared in cpp/include/n4m/pls.h, exported in all ABI snapshots, catalogued as utilities.moments, wrapped in Python as n4m.moments / n4m.moments_train_from_heldout, and documented in docs/methods/moments.md.

2026-06-04 — ABI 1.12.0: native AOM robust-HPO screen

One additive public symbol (ABI MINOR bump 1.11.0 -> 1.12.0), backward-compatible (no signature/layout change, nothing removed):

• n4m_aom_robust_hpo_fit(n4m_context_t*, const n4m_config_t*, const n4m_matrix_view_t* X, const n4m_matrix_view_t* Y, int32_t profile, int32_t cv, int32_t heads_mask, n4m_method_result_t** out_result)

This exposes the product AOM robust-HPO preprocessing screen through the public C ABI. Native v1 screens compact/wide banks of strict-linear, shape-preserving AOM preprocessing chains and Ridge/PLS heads by contiguous K-fold CV RMSE. It returns a n4m_method_result_t carrying in-sample predictions after refitting the selected candidate, transformed-space coefficients, intercept, scalar selection diagnostics and the full candidate_scores matrix (chain_id, head_id, param, mean_cv_rmse).

The implementation lives in cpp/src/core/aom_robust_hpo.cpp and is dispatched from cpp/src/c_api/c_api_method_result.cpp. The symbol is declared in cpp/include/n4m/pls.h, exported in all ABI snapshots, catalogued as aom_pop.robust_hpo, wrapped in Python as n4m.aom_robust_hpo, and documented in docs/methods/aom_robust_hpo.md.

2026-06-03 — ABI 1.11.0: direct (closed-form) Ridge regression

One additive public symbol (ABI MINOR bump 1.10.0 → 1.11.0), backward-compatible (no signature/layout change, nothing removed):

• n4m_ridge_fit(n4m_context_t*, const n4m_config_t*, const n4m_matrix_view_t* X, const n4m_matrix_view_t* Y, const double* lambdas, int64_t n_lambdas, n4m_method_result_t** out_result)

This is a genuine closed-form multi-output Ridge — beta = (Xc'Xc + lambda I)^-1 Xc'Yc on column-centered X/Y with intercept = y_mean - x_mean.beta (the penalty is not applied to the intercept, for sklearn.linear_model.Ridge parity). It is distinct from the pre-existing n4m_ridge_pls_fit (ridge-augmented SIMPLS, rank-truncated by n_components). The solver is chosen automatically by shape (PRIMAL augmented-QR for p ≤ n, DUAL Gram-on-samples for p > n; identical coefficients up to round-off).

Declared with N4M_API in cpp/include/n4m/pls.h (after n4m_continuum_regression_fit), implemented in cpp/src/c_api/c_api_method_result.cpp over the new core kernel cpp/src/core/ridge.cpp. Result keys: coefficients (p×q), intercept (1×q), x_mean, x_scale (1×p), y_mean (1×q), predictions (n×q), scalar rmse, scalar lambda.

Snapshots regenerated for all three platforms via scripts/regen_abi_snapshots.sh --derive (linux from the lib; macos/windows derived = linux minus the N4M_1 version node). n4m_ridge_fit is present in cpp/abi/expected_symbols_{linux,macos,windows}.txt. Header N4M_ABI_VERSION_MINOR and bindings/python/src/n4m/_ffi.py:ABI_VERSION_MINOR both bumped 10 → 11; bump_version.sh --check is green (project version unchanged at 0.98.0).

2026-06-03 — macOS/Windows snapshot correction + cross-platform gate enforced

No ABI surface change (still ABI 1.10.0). This is an audit-trail and CI correction: the 2026-05-30 entry below claimed “Snapshots regenerated for all three platforms”, but expected_symbols_{macos,windows}.txt were in fact a stale, truncated copy of an old Linux nm -D dump — 500 lines, carrying the Linux-only @@N4M_1 version tag (which macOS nm -gU / Windows dumpbin never emit), and missing ~171 symbols (the whole selection / method-result / aom / config family). They were also not diffed by CI on macOS/Windows (only Linux was fail-closed).

Corrected here:

• expected_symbols_{macos,windows}.txt regenerated to the real 671-symbol set — identical to the Linux n4m_* names minus the Linux-only N4M_1 version node (the only legitimate cross-platform difference).

• .github/workflows/abi-check.yml now diffs the committed snapshot fail-closed on all three platforms (macOS diff, Windows Compare-Object set comparison), with LC_ALL=C-pinned sorts so ordering is reproducible.

• Added a SONAME / RPATH-RUNPATH linkage gate to the Linux job (asserts SONAME == libn4m.so.1 and no baked-in absolute search path).

• Added scripts/regen_abi_snapshots.sh — the single canonical regenerator (--check for CI/pre-commit, --derive to produce the macOS/Windows files from the Linux snapshot when only a Linux box is available).

2026-05-18 — Linux export baseline for ABI 1.16.0

build/dev-release/cpp/src/libn4m.so.1.16.0 exports 27 additional n4m_* symbols compared with the previous Linux baseline. Each added symbol is declared with N4M_API in the public header cpp/include/pls4all/p4a.h, so the Linux ABI gate now treats them as intentional public additions:

• n4m_method_result_get_int64_vector

• n4m_mb_pls_fit, n4m_lw_pls_fit, n4m_pls_lda_fit, n4m_pls_logistic_fit, n4m_aom_preprocess_fit

• n4m_variable_select_rank, n4m_interval_select, n4m_stability_select, n4m_uve_select, n4m_spa_select, n4m_cars_select, n4m_random_frog_select, n4m_scars_select, n4m_ga_select, n4m_shaving_select, n4m_bve_select, n4m_t2_select, n4m_wvc_select, n4m_wvc_threshold_select, n4m_emcuve_select, n4m_randomization_select, n4m_bipls_select, n4m_sipls_select, n4m_rep_select, n4m_ipw_select, n4m_st_select

2026-05-30 — ABI 1.10.0: additive RNG-kind config selector

Two additive public symbols (ABI MINOR bump 1.9.0 → 1.10.0), backward-compatible (no signature/layout change, nothing removed):

• n4m_config_set_rng_kind(n4m_config_t*, n4m_rng_kind_t)

• n4m_config_get_rng_kind(const n4m_config_t*, n4m_rng_kind_t*)

New enum n4m_rng_kind_t { N4M_RNG_SPLITMIX64=0 (default), N4M_RNG_PCG64=1, N4M_RNG_MT_R=2, N4M_RNG_NUMPY_MT=3 } selects the RNG engine a stochastic method draws from, so its output can match an external reference library’s exact RNG (numpy default_rng / base R / numpy RandomState) for parity. Default SPLITMIX64 reproduces n4m’s historical streams bit-for-bit — leaving it unset changes nothing. Snapshots regenerated for all three platforms (expected_symbols_{linux,macos,windows}.txt). Engines verified bit-exact: docs/dev/RNG_TIER0_INVENTORY.md, cpp/tests/test_rng_engine.cpp.