Fix recording and reporting of method execution time

R/Method.R

@@ -182,7 +182,11 @@ Method <- R6::R6Class("Method",
 
     active = list(
         # Time elapsed until converged.
-        duration = function() { return(private$.end_time - private$.start_time) },
+        duration = function() {
+            return(
+                as.numeric(difftime(private$.end_time, private$.start_time, units = "secs"))
+            )
+        },
 
         # Number of iterations performed.
         iteration = function() { return(private$.iteration) },
@@ -208,7 +212,7 @@ Method <- R6::R6Class("Method",
 #' @template summary-Method
 #' @export
 summary.Method <- function(object, ...) {
-    cat("\n", "Method run completed (", as.numeric(round(object$duration, 4)), " sec):", sep = "")
+    cat("\n", "Method run completed (", round(object$duration, 4), " sec):", sep = "")
     cat("\n", " - converged: ", ifelse(object$converged, "yes", "no"), sep = "")
     cat("\n", " - iterations: ", object$iteration, sep = "")
     cat("\n", " - recommendation: ", paste(paste(

R/StepOne.R

@@ -178,7 +178,7 @@ StepOne <- R6::R6Class("StepOne",
             private$.remove_missing()
 
             # Compute how long the simulation took.
-            private$.duration <- Sys.time() - start_time
+            private$.duration <- as.numeric(difftime(Sys.time(), start_time, units = "secs"))
         },
 
         # Compute the statistics for the Monte Carlo simulations.

R/StepThree.R

@@ -181,7 +181,7 @@ StepThree <- R6::R6Class("StepThree",
             }
 
             # Compute how long the bootstrap took.
-            private$.duration <- Sys.time() - start_time
+            private$.duration <- as.numeric(difftime(Sys.time(), start_time, units = "secs"))
         },
 
         # Compute confidence intervals.
@@ -206,7 +206,7 @@ StepThree <- R6::R6Class("StepThree",
             }
 
             # Compute how long the bootstrap took.
-            private$.duration <- Sys.time() - start_time
+            private$.duration <- private$.duration + as.numeric(difftime(Sys.time(), start_time, units = "secs"))
 
             # Extract the confidence intervals for the sufficient sample sizes.
             private$.extract_sufficient_samples(private$.step_2$step_1$statistic_value)

R/StepTwo.R

@@ -7,6 +7,8 @@ StepTwo <- R6::R6Class("StepTwo",
         .interpolation = NULL,
         .cv = NULL,
 
+        .duration = NULL,
+
         # Decide how many DF can be used during the LOOCV.
         .check_df = function(df, monotone) {
             # If we have an I-Spline then we can start 1 degree of freedom lower.
@@ -136,6 +138,9 @@ StepTwo <- R6::R6Class("StepTwo",
         },
 
         fit = function(monotone = TRUE, increasing = TRUE, df = NULL, solver_type = "quadprog", ...) {
+            # Time when the fitting started.
+            start_time <- Sys.time()
+
             # Reset any previous spline before re-fitting.
             private$.clear_spline()
 
@@ -147,6 +152,9 @@ StepTwo <- R6::R6Class("StepTwo",
 
             # Interpolate the entire range used during Step 1.
             private$.interpolate(...)
+
+            # Compute how long the simulation took.
+            private$.duration <- as.numeric(difftime(Sys.time(), start_time, units = "secs"))
         }
     ),
 
@@ -157,7 +165,8 @@ StepTwo <- R6::R6Class("StepTwo",
         cv = function() { return(private$.cv) },
         ssq = function() {
             return(sum((private$.step_1$statistics - private$.spline$fitted) ^ 2))
-        }
+        },
+        duration = function() { return(private$.duration) }
     )
 )
 

R/Validation.R

@@ -96,7 +96,7 @@ Validation <- R6::R6Class("Validation",
 #' @template summary-Validation
 #' @export
 summary.Validation <- function(object, ...) {
-    cat("\n", "Validation completed (", as.numeric(round(object$validator$duration, 4)), " sec):", sep = "")
+    cat("\n", "Validation completed (", round(object$validator$duration, 4), " sec):", sep = "")
     cat("\n", " - sample: ", object$sample, sep = "")
     cat("\n", " - statistic: ", object$statistic, sep = "")
     cat("\n", " - measure at ", object$percentile, " pert.: ", round(object$percentile_value, 3), sep = "")

R/exports.R

@@ -95,7 +95,7 @@ powerly <- function(
 
     # Inform the user about the method status.
     if (verbose) {
-        cat("\n", "Method run completed (", as.numeric(round(method$duration, 4)), " sec):", sep = "")
+        cat("\n", "Method run completed (", round(method$duration, 4), " sec):", sep = "")
         cat("\n", " - converged: ", ifelse(method$converged, "yes", "no"), sep = "")
         cat("\n", " - iterations: ", method$iteration, sep = "")
         cat("\n", " - recommendation: ", method$step_3$samples["50%"], "\n", sep = "")
@@ -153,7 +153,7 @@ validate <- function(
 
     # Information regarding the results of the validation.
     if (verbose) {
-        cat("\n", "Validation completed (", as.numeric(round(validation$validator$duration, 4)), " sec):", sep = "")
+        cat("\n", "Validation completed (", round(validation$validator$duration, 4), " sec):", sep = "")
         cat("\n", " - sample: ", validation$sample, sep = "")
         cat("\n", " - statistic: ", validation$statistic, sep = "")
         cat("\n", " - measure at ", validation$percentile, " pert.: ", round(validation$percentile_value, 3), sep = "")

man-roxygen/powerly.R

@@ -167,7 +167,7 @@
 #' each step of the method for the last and previous iterations.
 #'
 #' Main fields:
-#' - **`$duration`**: The time elapsed during the method run.
+#' - **`$duration`**: The time in seconds elapsed during the method run.
 #' - **`$iteration`**: The number of iterations performed.
 #' - **`$converged`**: Whether the method converged.
 #' - **`$previous`**: The results during the previous iteration.