R/mle.R

In ecrc/exageostatR: R Package Demonstrates the R / C Language Interface for Exageostat

#
#
# Copyright (c) 2017-2023 King Abdullah University of Science and Technology
# All rights reserved.
#
# ExaGeoStat-R is a software package provided by KAUST
#
#
#
# @file mle.R
# ExaGeoStat R wrapper functions
#
# @version 1.2.0
#
# @author Sameh Abdulah
# @date 2021-06-20

library(assertthat)

#' Maximum Likelihood Evaluation  using exact method
#' @param data A list of x vector (x-dim), y vector (y-dim), and z observation vector
#' @param kernel: string - kernel  ("ugsm-s", "ugsmn-s",  "bgsfm-s", "bgspm-s", "tgspm-s", "ugsm-st", "bgsm-st")
#' @param dmetric  A string -  distance metric - "euclidean" or "great_circle"
#' @param optimization  A list of opt lb values (clb), opt ub values (cub), tol, max_iters
#' @return vector of three values (theta1, theta2, theta3)
#' @examples
#' seed <- 0 ## Initial seed to generate XY locs.
#' sigma_sq <- 1 ## Initial variance.
#' beta <- 0.1 ## Initial range.
#' nu <- 0.5 ## Initial smoothness.
#' dmetric <- "euclidean" ## "euclidean" or "great_circle" distance.
#' n <- 144 ## The number of locations (n must be a square number, n=m^2).
#' kernel <- "ugsm-s"
#' theta <- c(1, 0.1, 0.5)                                     #Params vector.
#' exageostat_init(hardware = list(ncores = 2, ngpus = 0, ts = 320, lts = 0, pgrid = 1, qgrid = 1)) ## Initiate exageostat instance
#' data <- simulate_data_exact(kernel, theta, dmetric, n, seed) ## Generate Z observation vector
#' ## Estimate MLE parameters (Exact)
#' result <- exact_mle(data, kernel, dmetric, optimization = list(clb = c(0.001, 0.001, 0.001), cub = c(5, 5, 5), tol = 1e-4, max_iters = 1))
#' print(result)
#' exageostat_finalize() ## Finalize exageostat instance
exact_mle <-
    function(data = list(x, y, z),
             kernel=c("ugsm-s", "ugsmn-s",  "bgsfm-s", "bgspm-s", "tgspm-s", "ugsm-st", "bgsm-st"),
             dmetric = c("euclidean", "great_circle"),
             optimization = list(
                                 clb = c(0.001, 0.001, 0.001),
                                 cub = c(5, 5, 5),
                                 tol = 1e-4,
                                 max_iters = 100
                                 )) {
        if (!exists("active_instance") || active_instance == 0) {
            print("No active ExaGeoStatR instance.")
        }
        else {
            kernel  <- check_kernel(kernel)
            dmetric <- arg_check_mle(data, dmetric, optimization)
            n <- length(data$x)
            theta_out2 <- .C(
                             "mle_exact",
                             as.double(data$x),
                             as.integer((n)),
                             as.double(data$y),
                             as.integer((n)),
                             as.double(data$z),
                             as.integer((n)),
                             as.double(optimization$clb),
                             as.integer((3)),
                             as.double(optimization$cub),
                             as.integer((3)),
                             as.integer(kernel),
                             as.integer(dmetric),
                             as.integer(n),
                             as.double(optimization$tol),
                             as.integer(optimization$max_iters),
                             as.integer(ncores),
                             as.integer(ngpus),
                             as.integer(dts),
                             as.integer(pgrid),
                             as.integer(qgrid),
                             theta_out = double(6)
                             )$theta_out

            print("back from mle_exact.")
            newList <-

                list(
                     "sigma_sq" = theta_out2[1],
                     "beta" = theta_out2[2],
                     "nu" = theta_out2[3],
                     "time_per_iter" = theta_out2[4],
                     "total_time" = theta_out2[5],
                     "no_iters" = theta_out2[6]
                     )
            return(newList)
        }
    }