Bootstrap Compositional Samples — gc_resample

Draw samples from a valid composition grid to create a "source population" for estimating covariance structure in ILR space. Supports both uniform random sampling and soil texture-aware bootstrapping (if aqp is available).

Usage

gc_resample_compositions(
  composition_grid,
  n = 1000,
  method = "uniform",
  seed = NULL
)

Arguments

composition_grid: A data frame of valid compositions (typically output from gc_expand_bounds()).
n: Number of samples to draw (default 1000).
method: Sampling method: "uniform" (simple random sampling) or "soil_texture" (uses aqp::bootstrapSoilTexture() if available, falls back to uniform if not).
seed: Optional random seed for reproducibility.

Value

A list with:

samples: A data frame of sampled compositions.
method: The method used.
n: Number of samples requested.

Details

Uniform sampling: Performs simple random sampling of row indices without replacement. If n > nrow(composition_grid), samples with replacement.
Soil texture sampling: Attempts to delegate to aqp::bootstrapSoilTexture(). If aqp is not installed, falls back to uniform sampling with a warning.

Examples

# Create a simple composition grid
constraints <- list(
  SAND = list(min = 0, max = 40),
  SILT = list(min = 50, max = 80),
  CLAY = list(min = 10, max = 20)
)
grid <- gc_expand_bounds(constraints, step = 1.0, target_sum = 100)

# Uniform sampling
set.seed(42)
uniform_samps <- gc_resample_compositions(grid, n = 100, method = "uniform")
nrow(uniform_samps$samples)
#> [1] 100