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#' Create a grid schedule for estimate_process_parameters()
#'
#' \code{ldmppr_grids()} constructs a multi-resolution grid schedule used by
#' \code{\link{estimate_process_parameters}}. The returned object is an S3 class
#' with helper methods; see \code{\link{ldmppr_grids-class}}.
#'
#' @param upper_bounds a vector \code{c(b_t, b_x, b_y)} giving the
#' maximum bounds for time and the spatial domain. Grids must lie within these.
#' @param levels a list describing the grid schedule. Each entry can be either:
#' \itemize{
#' \item a numeric length-3 vector \code{c(nx, ny, nt)} (number of points per dimension),
#' \item a list with elements \code{nx}, \code{ny}, \code{nt},
#' \item a list with explicit vectors \code{x}, \code{y}, \code{t}.
#' }
#' @param labels (optional) character vector of length equal to \code{levels}, used
#' only for printing.
#' @param include_endpoints \code{TRUE} or \code{FALSE} indicating; if \code{TRUE} (default) each generated grid uses
#' \code{seq(0, bound, length.out = n)} including endpoints.
#'
#' @return an object of class \code{"ldmppr_grids"}.
#' @export
#'
#' @seealso \code{\link{ldmppr_grids-class}} for methods and details.
#'
#' @examples
#' # A 3-level coarse-to-fine schedule (counts per dimension)
#' g <- ldmppr_grids(
#' upper_bounds = c(1, 50, 50),
#' levels = list(
#' c(25, 25, 25),
#' c(75, 75, 75),
#' c(100, 100, 100)
#' )
#' )
#' g
#' length(g)
#' summary(g)
#'
#' # Explicit vectors (single level)
#' g2 <- ldmppr_grids(
#' upper_bounds = c(1, 50, 50),
#' levels = list(list(
#' x = seq(0, 50, by = 2),
#' y = seq(0, 50, by = 2),
#' t = seq(0, 1, length.out = 30)
#' ))
#' )
#' as.data.frame(g2)
ldmppr_grids <- function(upper_bounds,
levels,
labels = NULL,
include_endpoints = TRUE) {
grids <- .ldmppr_make_grid_schedule(
upper_bounds = upper_bounds,
levels = levels,
labels = labels,
include_endpoints = include_endpoints
)
new_ldmppr_grids(
levels = grids$levels,
upper_bounds = grids$upper_bounds,
labels = grids$labels,
include_endpoints = grids$include_endpoints
)
}
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