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The covariance calculation is the most frequently repeated low-level
operation during fitting and prediction. magp implements it
in C++ through Rcpp. This page records a direct comparison
with an independent R implementation of the same calculation.
Clone the repository, install the development package, and run:
The script creates fixed synthetic inputs, times both
implementations, checks their largest absolute numerical difference, and
records sessionInfo(). The complete script is included in
the repository so that the comparison can be repeated on other
computers.
results <- read.csv(system.file(
"benchmarks",
"covariance-engine-results.csv",
package = "magp"
))
knitr::kable(
results,
digits = 4,
caption = "Median elapsed time per covariance calculation."
)| mapping | rows | components | repetitions | r_seconds | rcpp_seconds | speedup | max_abs_difference |
|---|---|---|---|---|---|---|---|
| 2d | 180 | 8 | 3 | 0.125 | 0.0015 | 85.6164 | 0 |
| full | 180 | 8 | 3 | 0.151 | 0.0018 | 83.4254 | 0 |
speedup is the R time divided by the Rcpp time. Timing
depends on the processor, R version, compiler, and system load, so the
recorded values should not be treated as a universal performance
guarantee. The max_abs_difference column is the direct
numerical agreement check for the same inputs and parameters.
The benchmark session details are stored beside the result file:
session_file <- system.file(
"benchmarks",
"covariance-engine-session-info.txt",
package = "magp"
)
cat(paste(readLines(session_file), collapse = "\n"))
#> R version 4.5.2 (2025-10-31)
#> Platform: aarch64-apple-darwin20
#> Running under: macOS Tahoe 26.5.2
#>
#> Matrix products: default
#> BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.1
#>
#> locale:
#> [1] C.UTF-8/C.UTF-8/C.UTF-8/C/C.UTF-8/C.UTF-8
#>
#> time zone: America/New_York
#> tzcode source: internal
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] magp_0.12.0.9000
#>
#> loaded via a namespace (and not attached):
#> [1] compiler_4.5.2 tools_4.5.2 Rcpp_1.1.2These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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