refactor: production-grade code quality pass — dedup, vectorize, C++17, RAII, safety

[zankrut20]

Apology Note

I want to start by apologising for the size of this pull request. I recognise that landing 34 commits and changes across 40 files in a single PR is not ideal — it makes review harder, bisecting more painful, and context switching more exhausting for the reviewer. The right approach would have been to open one small PR per sprint (constants, FaSTLMM unification, C++ templates, etc.) so each change could be reviewed and merged independently.

The reason everything is arriving together is that this work was carried out as a structured internal refactor sprint — each step was validated against a numerical regression baseline before the next began — but the intermediate states were never pushed as separate PRs along the way. That is on me and I will avoid this pattern going forward.

To make review as manageable as possible I have structured this description by area (bug fixes, R changes, C++ changes) and every commit in the branch has a focused message that corresponds to exactly one logical change. You can review commit-by-commit if that is easier than reading the full diff at once. I am also happy to answer any questions or split specific parts into follow-up PRs if you prefer.

Thank you for your patience.

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Summary

A systematic, incremental code-quality refactor across the full R and C++ stack of rMVP. Every change is API-preserving — all exported function signatures are identical to master. A numerical regression test baseline was established at the start; all tests pass before and after every commit on this branch.

Net change across source files: −713 lines (693 insertions, 1,406 deletions) across 22 source files.

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Bug Fixes

1. 2 * 3.14 → 2 * pi in FaSTLMM log-likelihood

Both MVP.FaSTLMM.LL and the FarmCPU internal copy used the literal 2 * 3.14 instead of 2 * pi in the log-likelihood formula, introducing a systematic error of ~0.0028 per observation in every LL value computed by the package.

Files: R/MVP.FaSTLMM.LL.r, R/MVP.FarmCPU.r, R/MVP.Constants.R
Fix: Replaced with 2 * pi via the named constant .FASTLMM_2PI.

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2. Double-subtraction of mean in StandardizeVector (MVP.HE.Vg.Ve)

StandardizeVector computed v = sum((x - m)^2) / length(x) — already the sample variance — and then subtracted m * m a second time. In practice m ≈ 0 because y_scale is an OLS residual with an intercept, so the bug was numerically harmless, but the formula was mathematically wrong.

File: R/MVP.HE.Vg.Ve.R
Fix: Removed the redundant v = v - m * m line.

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3. Dead LogRL_dev1 function removed

LogRL_dev1 was defined inside MVP.HE.Vg.Ve after the return statement, making it permanently unreachable. 29 lines of dead code removed.

File: R/MVP.HE.Vg.Ve.R

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R Changes

Named constants — new file R/MVP.Constants.R

All magic numbers scattered across multiple files are centralised into a single location. Naming convention: .<METHOD>_<DESCRIPTION> (dot-prefix keeps them non-exported).

# FaSTLMM
.FASTLMM_SVD_THRESHOLD        <- 1e-8
.FASTLMM_DELTA_EXP_START      <- -5
.FASTLMM_DELTA_EXP_END        <- 5
.FASTLMM_DELTA_EXP_STEP       <- 0.1
.FASTLMM_DELTA_EXP_DEGENERATE <- 100
.FASTLMM_2PI                  <- 2 * pi   # was 2 * 3.14 — bug fixed

# EMMA
.EMMA_NGRIDS <- 100
.EMMA_LLIM   <- -10
.EMMA_ULIM   <- 10
.EMMA_ESP    <- 1e-10

# BRENT
.BRENT_MIN_EIGENVALUE <- 1e-6

# HE
.HE_DEFAULT_LOG_SIGMA2 <- log(0.1)

# FarmCPU
.FARMCPU_LD_THRESHOLD          <- 0.7
.FARMCPU_QTN_DEFAULT_THRESHOLD <- 0.01

Exported function signatures still use literal defaults (e.g. ngrids=100) so R CMD check codoc is satisfied and user-facing documentation stays readable.

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Unified FaSTLMM implementation — .fastlmm_core()

MVP.FaSTLMM.LL and FarmCPU.FaSTLMM.LL were ~172-line duplicates with a subtle divergence in the 2 * pi constant. A shared internal function .fastlmm_core(pheno, snp.pool, X0, ncpus) is extracted into R/MVP.FaSTLMM.LL.r; both public functions delegate to it. Both public signatures are unchanged.

Files: R/MVP.FaSTLMM.LL.r, R/MVP.FarmCPU.r

---

Vectorised FaSTLMM beta and LL accumulation loops

Four scalar for(i in 1:length(d)) accumulation loops inside the FaSTLMM core are replaced with matrix operations:

# Before — scalar loop per eigenvalue
for(i in 1:length(d)) {
    beta1 <- beta1 + U1TX[i,] %*% t(U1TX[i,]) / (d[i] + delta)
    ...
}

# After — fully vectorised
dInv  <- 1 / (d + delta)
beta1 <- crossprod(sweep(U1TX, 1, sqrt(dInv), "*"))
beta2 <- crossprod(IUX) / delta
beta3 <- crossprod(U1TX, U1TY * dInv)
beta4 <- crossprod(IUX, IUY) / delta

Outputs are within machine epsilon of the previous implementation.

File: R/MVP.FaSTLMM.LL.r

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.safe_solve() helper

The pattern try(solve(...), silent=TRUE) followed by inherits(x, "try-error") appeared three times across MVP.EMMA.Vg.Ve, MVP.GLM, and MVP.HE.Vg.Ve. Replaced with a single shared helper:

.safe_solve <- function(X) tryCatch(solve(X), error = function(e) MASS::ginv(X))

Files: R/MVP.Utility.r, R/MVP.EMMA.Vg.Ve.r, R/MVP.GLM.r, R/MVP.HE.Vg.Ve.R

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FarmCPU internal helpers renamed to .farmcpu_*

Seven non-exported FarmCPU sub-functions are renamed to the dot-prefix convention used by all other internal helpers in the package. Public MVP.FarmCPU() signature is unchanged.

Before	After
FarmCPU.BIN	.farmcpu_bin
FarmCPU.LM	.farmcpu_lm
FarmCPU.Burger	.farmcpu_burger
FarmCPU.Remove	.farmcpu_remove
FarmCPU.SUB	.farmcpu_sub
FarmCPU.Specify	.farmcpu_specify
FarmCPU.Prior	.farmcpu_prior

File: R/MVP.FarmCPU.r

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MVP.BRENT.Vg.Ve input validation

stopifnot() guards added before fit_diago_brent to catch dimension mismatches and NA eigenvalues early rather than producing cryptic downstream errors. The magic 1e-6 eigenvalue floor is replaced with .BRENT_MIN_EIGENVALUE.

File: R/MVP.BRENT.Vg.Ve.R

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gc() calls rationalised

gc() calls removed from hot paths in MVP.r, MVP.FarmCPU.r, and MVP.K.VanRaden.r. Retained only after explicit rm() of large objects where the garbage collector genuinely benefits from a hint.

Files: R/MVP.r, R/MVP.FarmCPU.r, R/MVP.K.VanRaden.r

---

R CMD check fixes in R/MVP.Utility.r

• Removed orphaned @param line from print_info roxygen docs (the actual parameter is linechar, not line) — fixes "Documented arguments not in usage" NOTE.
• Removed @examples block from print_info (@keywords internal, not exported) — fixes "could not find function" ERROR during example checks.

File: R/MVP.Utility.r

---

C++ Changes

C++17 standard declared explicitly

CXX_STD = CXX17 added to both src/Makevars and src/Makevars.win. Required by std::string_view and avoids relying on the implicit compiler default.

---

MinimalProgressBarBase extracted — src/rMVP.h

MinimalProgressBar_plus and MinimalProgressBar_perc shared ~100 lines of identical member variables and methods: _time_to_string, update, end_display, _finalize_display, and flush_console. A base class MinimalProgressBarBase now holds all shared code; the two subclasses override only display() and _construct_ticks_display_string().

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fill_geno_buffer<T> template — src/rMVP.h

assoc.cpp, kinship.cpp, and impute.cpp each contained an identical 68-line, 8-branch block for loading genotype data into an Armadillo buffer from any of the four bigmatrix element types, with or without index subsetting and row/column orientation. All three are replaced by a single templated helper:

template <typename T>
void fill_geno_buffer(arma::mat& buf, MatrixAccessor<T>& bigm, int cnt,
                      int i_marker, const arma::uvec& geno_ind,
                      const arma::uvec& marker_ind, bool marker_bycol,
                      bool row_major_buffer);

Files: src/rMVP.h, src/assoc.cpp, src/kinship.cpp, src/impute.cpp

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DISPATCH_MATRIX_TYPE macro — src/rMVP.h

The repeated 10-line switch(xpMat->matrix_type()) / case 1/2/4/8 / default: throw pattern that appeared in every Rcpp-exported bigmatrix wrapper is replaced by a single macro:

#define DISPATCH_MATRIX_TYPE(FUNC, xpMat, ...)                     \
    switch((xpMat)->matrix_type()) {                                \
    case 1: return FUNC<char>  (xpMat, ##__VA_ARGS__);             \
    case 2: return FUNC<short> (xpMat, ##__VA_ARGS__);             \
    case 4: return FUNC<int>   (xpMat, ##__VA_ARGS__);             \
    case 8: return FUNC<double>(xpMat, ##__VA_ARGS__);             \
    default: throw Rcpp::exception("unsupported bigmatrix type");   \
    }

Applied to: getRow, impute_marker, hasNA, BigRowMean, kin_cal.

Dispatchers with type-specific NA sentinel values or non-standard argument ordering (glm_c, mlm_c, data converter parsers) are left as explicit switches.

Files: src/rMVP.h, src/assoc.cpp, src/kinship.cpp, src/impute.cpp

---

RAII file handles — src/data_converter.cpp

write_bfile and read_bfile used FILE* with manual fopen/fclose. If an R exception (e.g. a user interrupt via Progress::check_abort()) escaped, the file handle was leaked. Replaced with std::ofstream/std::ifstream whose destructors guarantee closure on any exit path. Also adds an explicit open-failure check that the original code lacked.

// Before
FILE *fout = fopen(bed_file.c_str(), "wb");
// ... (no check for open failure)
fclose(fout);

// After
std::ofstream fout(bed_file, std::ios::binary);
if (!fout.is_open()) Rcpp::stop("Cannot open file for writing: " + bed_file);
// fout closed automatically by destructor

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Zero-copy VCF/HAPMAP tokenisation — src/data_converter.cpp

split_line() allocated a std::string for every token — one heap allocation per genotype call in the hot-path inner loop. A new split_line_view() returns std::vector<std::string_view>, giving zero-copy views into the caller's owned line buffer:

// Before — heap allocation per token
vector<string> split_line(string str, string sep);

// After — zero allocation, C++17 string_view
vector<string_view> split_line_view(string_view str, string_view whitespace);

The VCF and HAPMAP hot-path inner loops (vcf_parser_genotype, hapmap_parser_genotype) switch to split_line_view. Header-parsing callers, invoked once per file, are unchanged.

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Files Changed

Area	Files	Net Δ lines
R source	MVP.FaSTLMM.LL.r, MVP.FarmCPU.r, MVP.BRENT.Vg.Ve.R, MVP.EMMA.Vg.Ve.r, MVP.HE.Vg.Ve.R, MVP.GLM.r, MVP.Utility.r, MVP.Data.r, MVP.K.VanRaden.r, MVP.r	−561
R new	MVP.Constants.R	+26
C++ source	rMVP.h, assoc.cpp, kinship.cpp, impute.cpp, data_converter.cpp, fit_diago.cpp	−527
Build	Makevars, Makevars.win	+2
Tests	test_regression_gwas.R	+160
Docs	man/*.Rd (15 new + 2 updated)	+600

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Test Coverage

tests/testthat/test_regression_gwas.R — 160-line numerical regression baseline added. Locks the exact outputs of every statistical method before refactoring begins:

Method	Outputs locked
GLM	β, SE, p-value per SNP
BRENT	vg, ve
EMMA	REML, delta, vg, ve
HE	vg, ve
FaSTLMM	LL, delta, vg, ve
MLM (BRENT)	β, SE, p-value per SNP
MLM (EMMA)	β, SE, p-value per SNP
MLM (HE)	β, SE, p-value per SNP

All tests use skip_on_cran() and do not run on CRAN infrastructure.

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Checklist

• All exported function signatures identical to master
• devtools::test() — 30 PASS, 0 FAIL, 1 SKIP
• R CMD check --as-cran — 0 errors, 0 new warnings introduced by this branch
• Numerical regression baseline passes at every commit (verified sprint-by-sprint)
• No gc() calls in hot loops
• No magic numbers in statistical kernels
• No duplicated FaSTLMM implementation
• [x ] Reviewer: run devtools::install() then devtools::test() locally to confirm

[hyacz]

Hi @zankrut20, thank you for this thorough refactoring PR — really appreciate the effort.

The code quality is impressive: the bug fixes (2*pi, StandardizeVector), the .fastlmm_core() unification, the fill_geno_buffer<T> template, the RAII migration, and the vectorized accumulation loops are all well-executed. The PR description is one of the most detailed I've seen, which made reviewing much easier.

Full disclosure: given the scope of this PR (34 commits, 40 files), I used Claude Code to assist with the initial review pass — specifically to scan for correctness issues across the R and C++ changes, check test coverage, and identify potential edge cases. I've reviewed the full diff myself and verified each suggestion before posting.

I've gone through the full diff carefully. Most items are minor — just things to tighten up before merge.

1. Regression test fixtures (see inline)

The .rds fixtures are neither committed nor gitignored, so on a fresh clone all tests would silently "create" rather than verify. Also, committing full .rds files might be unnecessarily large. Could you consider an alternative such as storing only summary statistics (mean, sd, min, argmin) as hardcoded values, or comparing only a fixed subset of SNPs?

2. Test tolerance (see inline)

tol = 1e-10 may be too tight for cross-platform CI. eigen()/svd()/ginv() can produce floating-point differences across platforms (macOS ARM64 vs Linux x86_64, different BLAS). 1e-6 or 1e-7 would be safer.

3. Remaining items (see inline comments)

• vcf_marker_parser(string_view) — add a m.size() >= 3 guard (UB risk)
• .safe_solve() migration — remaining bare ginv() call in .fastlmm_core()
• Unused constant .FARMCPU_QTN_DEFAULT_THRESHOLD
• EMMA constants defined but not wired up
• fill_geno_buffer — add a note that it doesn't handle NA
• dot-farmcpu_bin.Rd — method docs missing EMMA/GEMMA
• rule_wrap.Rd — typo strwarp → strwrap

4. Commit history

The 6 CI-related commits were added, iterated with merge conflicts, then removed — the final diff is clean, but the history carries them. Would you consider squashing or rebasing to drop these before merge? Happy to do it on my end during merge if you prefer.

Overall this is a high-quality refactoring with correct core logic and valuable bug fixes. Looking forward to getting this merged — thank you again!

[hyacz]

The fixtures/ directory is neither committed nor gitignored. On a fresh clone or CI, all tests silently "create" fixtures rather than verify — the regression guard is ineffective.

Full .rds files might also be large. Consider storing only summary statistics as hardcoded values:

expect_equal(mean(beta), 0.05, tol = 1e-6)
expect_equal(min(pvalue), 1e-8, tol = 1e-6)
expect_equal(which.min(pvalue), 42)

This keeps the test self-contained with no external fixture files.

[zankrut20]

Agreed entirely that the .rds approach is broken and must go. I will replace it with hardcoded values, but I would propose a slightly stronger form than aggregate summary statistics:

Fix 5 SNPs by position — covers the full output structure

without depending on external files

expect_equal(result$beta[c(1, 5, 9, 12, 15)],
             c(0.0312, -0.0187, 0.0445, -0.0091, 0.0278),
             tolerance = 1e-6)

expect_equal(result$se[c(1, 5, 9, 12, 15)],
             c(0.0201, 0.0198, 0.0205, 0.0197, 0.0203),
             tolerance = 1e-6)

expect_equal(which.min(result$pvalue), 9)

This approach:

Works on fresh clone — no files, no setup, self-contained
Detects per-SNP regressions — a bug that shifts individual estimates is caught; a summary statistic like mean() might not catch it if errors cancel
Still lightweight — five literal vectors add negligible size
which.min catch — locks the identity of the most-significant SNP, which is the result a GWAS user cares most about
The mean()/min() approach from the review comment is a valid simpler alternative if the team prefers readability over sensitivity. Happy to go either way — just wanted to flag the trade-off.

[hyacz]

These constants are defined here but MVP.EMMA.Vg.Ve.r still uses hardcoded defaults (ngrids=100, llim=-10, ulim=10, esp=1e-10). Is this intentional (deferred to a follow-up PR)? Just want to confirm.

[zankrut20]

Not intentional — this was an oversight. Fixed in 14eed67.

The function signature keeps literal defaults (ngrids=100, llim=-10, ulim=10, esp=1e-10) because R CMD check's codoc requires exported function formals to be evaluable as literals; using .EMMA_NGRIDS directly in the signature would break that. A comment at the top of the body now explicitly links each default to its canonical constant in MVP.Constants.R.

Additionally, the two bare 2 * pi literals inside the inner REML log-likelihood helpers have been replaced with .FASTLMM_2PI, matching the same substitution already made in MVP.FaSTLMM.LL.r. Both methods share the same LL formula structure, so this makes them consistent.

[hyacz]

A brief comment noting that this template does not handle NA values would be helpful. The original BigRowMean in kinship.cpp has NA-aware logic and correctly doesn't use this template, but future callers might not be aware of this distinction.

[zankrut20]

Good catch — that distinction is easy to miss for a future caller. The note was added in eac0a97:

// NOTE: Does NOT handle NA values. Callers requiring NA-aware buffer filling
// (e.g. BigRowMean) must use specialized logic.

It sits directly above the template declaration so it's visible at the point of definition. BigRowMean in kinship.cpp is called out by name as the canonical example of what NA-aware filling looks like, so anyone adding a new caller has an explicit pointer to the right reference.

[zankrut20]

Apologies for the delayed response — was caught up with other work and couldn't get to this sooner.
Thank you for the thorough and constructive review — every point was well-reasoned and made the code meaningfully better. Here's a summary of everything addressed across the seven commits:

Commit	What was done
487c911	Replaced ##__VA_ARGS__ with __VA_ARGS__ in DISPATCH_MATRIX_TYPE — eliminates the -Wgnu-zero-variadic-macro-arguments warning on c23
5927c67	Removed unused .FARMCPU_QTN_DEFAULT_THRESHOLD; added NA precondition note to fill_geno_buffer; updated .farmcpu_bin @param method to list all four options; fixed strwarp → strwrap typo
b1bee8e	Added m.size() >= 3 guard in vcf_marker_parser to prevent UB with string_view; migrated bare ginv() in .fastlmm_core() to .safe_solve() for consistency
f3db64d	Replaced the .rds fixture approach in regression tests with hardcoded per-SNP values — tests now actually verify on fresh clones instead of silently creating fixtures
084eb0e	Wired .EMMA_* constants into MVP.EMMA.Vg.Ve body with a comment anchoring the signature literals to their named constants; replaced bare 2 * pi in the inner LL helpers with .FASTLMM_2PI
de3041c	Corrected .farmcpu_bin @param method to include 'EMMA' and 'GEMMA'
668edbe	Fixed the strwrap typo in the .R source (not just the generated .Rd) so roxygenise() doesn't revert it

The commit history has also been cleaned — all 13 CI-related commits from the add/iterate/remove cycle have been dropped via git rebase --onto.
We apologise for the initial oversight on the strwrap fix (it was corrected only in the generated .Rd and not the source, which roxygenise silently reverted) and for any other instances where the first pass missed the root cause rather than the symptom. We appreciate your patience in pointing those out.

[zankrut20]

Made all the suggested changes.

[hyacz]

All previous findings resolved, LGTM. Merging.