Build the CNN1D monotone-integral SWRC model — build_swrc

Constructs a Keras model implementing the monotone-integral architecture of Norouzi et al. (2025). The returned list contains two models that share weights:

theta_model — full prediction model (pF query + covariates → theta).
param_model — extracts the saturated water content (theta_s) from covariates only.

Usage

build_swrc_model(n_covariates, hidden = c(128L, 64L), dropout = 0.1, K = 64L)

Arguments

n_covariates: Integer. Number of soil-property covariates (p).
hidden: Integer vector of length 2. Number of filters in the first and second Conv1D layers (default c(128L, 64L)).
dropout: Numeric dropout rate after each Conv1D layer (default 0.10).
K: Integer. Number of knot points for the cumulative integration grid (default 64L).

Value

A named list:

theta_model: Keras model: inputs [Xseq_knots, pf_norm], output shape [N, 2] (theta_hat, theta_s).
param_model: Keras model: input Xseq_knots, output shape [N, 1] (theta_s only).
K: The K value used.
dk: The knot spacing 1 / (K - 1).
knot_grid: Numeric vector of knot positions.

Examples

if (FALSE) { # \dontrun{
mod <- build_swrc_model(n_covariates = 9L)
} # }