Apply stored z-standardization to environmental predictors

Re-applies the constants learned by compute_env_scaling() to env. The transformation uses the stored mean/sd only and never recomputes them from env, so calibration and prediction use an identical transformation (the usual pitfall of scale() inside a model formula is avoided).

Usage

apply_env_scaling(env, scaling)

Arguments

env

A data.frame/data.table of raw environmental data.

scaling

The data.frame returned by compute_env_scaling(), or NULL (in which case env is returned unchanged). For a model fit with env_autoscale = TRUE this is model$env_scaling.

Value

env with the scaled predictor columns, as a data.table.

See also

compute_env_scaling, fit

Examples

# reproduce the standardization a model fit with env_autoscale = TRUE used:
env <- data.frame(siteID = 1:3, year = 1L, temp = c(4, 6, 8), prec = c(700, 850, 1000))
scaling <- compute_env_scaling(env)
apply_env_scaling(env, scaling)
#>    siteID  year  temp  prec
#>     <int> <int> <num> <num>
#> 1:      1     1    -1    -1
#> 2:      2     1     0     0
#> 3:      3     1     1     1