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Produces the same shape datamatch::accessEnvDat() returns, so the pipeline runs identically against mock and Copernicus data. Covariates carry the same latitudinal and seasonal structure planted in the mock abundances, so the model has something real to learn.

Usage

generate_mock_covariates(
  config,
  years = NULL,
  months = NULL,
  resolution = 0.25,
  seed = 42
)

Arguments

config

a config list, as returned by load_config()

years

years to generate

months

months to generate

resolution

grid spacing in degrees

seed

random seed

Value

an sf POINT object matching fetch_covariates()'s contract