R/print.R

In BlasBenito/spatialRF: Easy Spatial Modeling with Random Forest

#' @title Custom print method for random forest models
#' @description Custom print method for models fitted with [rf()], [rf_repeat()], and [rf_spatial()].
#' @param x A model fitted with [rf()], [rf_repeat()], or [rf_spatial()].
#' @param ... Additional arguments for print methods.
#' @return Prints model details to the console.
#' @seealso [print_evaluation()], [print_importance()], [print_moran()], [print_performance()]
#' @examples
#' if(interactive()){
#'
#'  #loading example data
#'  data("plant_richness_df")
#'  data("distance_matrix")
#'
#'  #fitting random forest model
#'  rf.model <- rf(
#'    data = plant_richness_df,
#'    dependent.variable.name = "richness_species_vascular",
#'    predictor.variable.names = colnames(plant_richness_df)[5:21],
#'    distance.matrix = distance_matrix,
#'    distance.thresholds = 0,
#'    n.cores = 1
#'  )
#'
#'  #printing model summary
#'  print(rf.model)
#' }
#' @rdname print
#' @export
#' @importFrom huxtable hux add_colnames set_bold set_all_borders number_format print_screen set_width number_format
print.rf <- function(x, ...) {

  #getting model features

    cat("Model type\n")
    cat("  - Fitted with:                     ", class(x)[2], "()\n", sep="")
    if(inherits(x, "rf_repeat")){
    cat("  - Repetitions:                     ", x$ranger.arguments$repetitions, "\n", sep="")
    }
    if(inherits(x, "rf_spatial")){
    cat("  - rf_spatial() method:             ", x$spatial$method, "\n", sep="")
    }
    cat("  - Response variable:               ", x$ranger.arguments$dependent.variable.name, "\n", sep="")

    cat("\n")
    cat("Random forest parameters\n")
    cat("  - Type:                            ", x$treetype, "\n", sep="")
    cat("  - Number of trees:                 ", x$num.trees, "\n", sep="")
    cat("  - Sample size:                     ", x$num.samples, "\n", sep="")
    cat("  - Number of predictors:            ", x$num.independent.variables, "\n", sep="")
    cat("  - Mtry:                            ", x$mtry, "\n", sep="")
    cat("  - Minimum node size:               ", x$min.node.size, "\n", sep="")
    cat("\n")

    print_performance(x)

    cat("\n")
    cat("Model residuals \n")
    cat("  - Stats: \n")
      residuals.stats <- x$residuals$stats
      residuals.stats <- data.frame(
        Var1 = as.vector(residuals.stats),
        Var2 = names(residuals.stats)
      )

    rownames(residuals.stats) <- residuals.stats$Var2
    residuals.stats$Var2 <- NULL
    residuals.stats <- t(residuals.stats)
    rownames(residuals.stats) <- NULL
    colnames(residuals.stats) <- c("Min.", "1st Q.", "Median", "Mean", "3rd Q.", "Max.")

    residuals.stats <-
      huxtable::hux(residuals.stats) %>%
      huxtable::add_colnames() %>%
      huxtable::set_bold(row = 1, col = huxtable::everywhere, value = TRUE) %>%
      huxtable::set_all_borders(TRUE)
    huxtable::number_format(residuals.stats)[2, ] <- 2
    huxtable::print_screen(residuals.stats, colnames = FALSE)

    cat("  - Normality: \n")
    cat("      - Shapiro-Wilks W:", round(x$residuals$normality$shapiro.w, 3), "\n")
    cat("      - p-value        :", round(x$residuals$normality$p.value, 4), "\n")
    cat("      - Interpretation :", x$residuals$normality$interpretation, "\n")

    if("autocorrelation" %in% names(x$residuals)){
      cat("\n")
      cat("  - Spatial autocorrelation: \n")
      print_moran(x)
    }

    if("variable.importance" %in% names(x)){
      cat("\n")
      cat("Variable importance: \n")
      print_importance(x)
    }

    if(inherits(x, "rf_evaluate")){
      print_evaluation(x)
    }

}