Elamur Groupantsmlab-numerics-bench-sampling
The groupant beside mlab/bench/src/main.rs in the Mova repository: what the code computes, what it never does, how to go back from its outputs, its invariants, cost and checks.
Facts
Implementation material. A Mova code model describes this code at one source revision: partial models, finite checks and their stated scope. It is not a reviewed general exposition, and its labels are shown as written, never raised.
Components
| component | label | where |
|---|---|---|
| approximant | partial | approximant |
| ast | partial | ../syntax.json |
| cost | symbolic source derived | invariant |
| descriptant | present | descriptant |
| invariant | partial | invariant |
| tests | executed bounded checks | tests |
Obernants
The typed relations around the forward model: the behaviour complement (what the code never does), the reverse reconstruction (every input compatible with an output) and specialised views.
| id | type | label | where |
|---|---|---|---|
behavior_complement | behavior_complement | partial source derived model | behavior_complement |
reverse_reconstruction | reverse_reconstruction | partial source derived model | reverse_reconstruction |
zero_data | zero_data | partial source derived model | zero_data |
last_value | last_value | partial source derived model | last_value |
range | range | partial source derived model | range |
resource_gap | resource_gap | partial source derived model | resource_gap |
Model text
descriptant
mlab-numerics-bench-sampling
Lcg::next wrapping-updates u64 and takes upper53 bits; data consumes n² samples; best measures3 callbacks and keeps min duration while overwriting acc each call.
Modeling epoch 2026-10-31
Prospective source reading preceded inline tests. This node records implementation behavior, not a complete MATLAB compatibility contract. Models retain limits discovered in source reading, including real-only projections and warning-only result gates. Synthetic CPU fixtures are independent of frozen suites. No external effects, teacher, corpora or benchmark main are executed.
approximant
Forward relation
Lcg::next wrapping-updates u64 and takes upper53 bits; data consumes n² samples; best measures3 callbacks and keeps min duration while overwriting acc each call.
Executable Rust surrogate gap: no calibrated replacement is attached. Exact test calls are evidence for the reference, not a fast approximant. Numerical approximants would need a named domain, zero convention and metric at supported caps 1/2/5/10%; categorical errors/effects have no percent surrogate here.
invariant
Invariants and cost
u64 wrap and f64 dyadic conversion are defined; duration comparison cannot establish deterministic time.
Cost
O(n²) sampling; exactly3 callback calls plus Instant reads.
Allocation failure, unchecked usize dimension arithmetic and IEEE nonfinite propagation are outside finite fixture guarantees. No measured throughput or global accuracy claim.
models
Typed source models: mlab-numerics-bench-sampling
behavior_complement
Callback count cannot be0,1 or2 on normal return. Seed0 first output excludes using old state's bits. Equal seed/n excludes different data.
reverse_reconstruction
One output loses11 state bits; invertible odd LCG multiplier maps each compatible post-state to a prior seed. best's last result permits arbitrary earlier results and durations consistent with minimum.
zero_data
n0 produces empty Vec without consuming LCG.
last_value
best callback count3 returns last accumulator3, independent of timing winner.
range
top53 integer in[0,2^53) implies output in[-.5,.5).
resource_gap
n*n uses unchecked usize multiplication; huge dimensions are outside helper domain.
tests
Evidence and limits
Selected wave30_tests exercise this source; fragment-specific limits are stated in its operators.
Native command specifications, numeric exits, profile-paired logs, compiled controls and exact-restoration receipts are retained externally in the wave30 numerics run. Tests exercise actual source, not a copied model. The selected finite fixtures do not prove full convergence, backend accuracy on all matrices, resource exhaustion or side-effectful callback behavior.
This page in Markdown → https://md.groupants.elamur.ai/free/en/mova/mlab/bench/src/main.rs.groupant/bench-sampling.groupant/