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Run the soilKey performance benchmark

Source: R/benchmark-performance.R
benchmark_performance.Rd

Generates n synthetic pedons (5 horizons each, with the chemistry / morphology populated for typical Argissolo / Latossolo / Cambissolo cases), calls each classifier on each pedon, and reports per-call latency + total throughput.

Usage

benchmark_performance(
  n = 100L,
  systems = c("wrb2022", "sibcs", "usda"),
  include_familia = FALSE,
  seed = 42L,
  verbose = TRUE
)

Arguments

n

Integer. Number of synthetic pedons to generate. Default 100; pass 1000 or higher for batch-level measurements.

systems

Character vector. Which classifiers to time. Default c("wrb2022", "sibcs", "usda") (all three).

include_familia

Pass-through to classify_sibcs when "sibcs" is in systems. Default FALSE.

seed

RNG seed for reproducibility. Default 42.

verbose

If TRUE (default), prints a per-system summary line.

Value

A list with elements:

summary

data.frame: system, n_pedons, total_seconds, mean_seconds, median_seconds, pedons_per_minute.

per_pedon

data.frame with one row per (pedon, system) call: i, system, seconds, status.

config

list with n, seed, soilKey_version, R_version, platform.

Details

Designed to be a one-shot reproducible benchmark: the synthetic pedons use a fixed RNG seed so timings on the same machine are comparable across releases.

Examples

if (FALSE) { # \dontrun{
bench <- benchmark_performance(n = 100)
bench$summary
#>     system n_pedons total_seconds mean_seconds median_seconds pedons_per_minute
#> 1 wrb2022      100        ~ 5-12      0.05-0.12      ~          ~
#> 2   sibcs      100        ~ 5-15      0.05-0.15      ~          ~
#> 3    usda      100        ~ 4-10      0.04-0.10      ~          ~
} # }