Merge pull request #3 from KWB-R/dev

Set a default for "t_values", use defaults

R/calculate_bear1d.R

@@ -8,7 +8,7 @@
 #' @param C0 initial concentration of the solute (M/L3)
 #' @param D_values coefficient of longitudinal dispersion (L2/T)
 #' @param v_values average linear ground water velocity (L/T)
-#' @param t_values time (T)
+#' @param t_values time (T), default: max(hl_values * max(log_koc_values))
 #' @param x_values flow path distance (L)
 #'
 #' @return Bear 1D results
@@ -35,7 +35,7 @@ calculate_bear1d <- function(
     C0 = 1,
     D_values,
     v_values,
-    t_values,
+    t_values = max(hl_values * max(log_koc_values)),
     x_values
 )
 {

vignettes/Tutorial.Rmd

@@ -22,40 +22,34 @@ knitr::opts_chunk$set(
 ### Budapest Tahi
 
 ```{r Budapest_Tahi}
-hl_values <- c(500, 2000)
-
 bear1d_tahi_combined <- kwb.1dbear::calculate_bear1d(
   n_values = 0.3,
   rs_values = 2.7,
   foc_values = 0.002,
   log_koc_values = c(1, 2.9),
-  hl_values = hl_values,
-  C0 = 1,
+  hl_values = c(500, 2000),
   D_values = 10,
   v_values = 2.14,
   t_values = seq(0, 350, by = 1),
   x_values = 60
 )
 
 # Combine the plots
-print(kwb.1dbear::plot_combined(bear1d_list = bear1d_tahi_combined))
+print(kwb.1dbear::plot_combined(bear1d_tahi_combined))
 
 # Generate heat map
-log_koc_values <- seq(0.1, 6, length.out = 100)
 bear1d_tahi_heatmap <- kwb.1dbear::calculate_bear1d(
   n_values = 0.3,
   rs_values = 2.7,
   foc_values = 0.002,
-  log_koc_values = log_koc_values,
+  log_koc_values = seq(0.1, 6, length.out = 100),
   hl_values = seq(1, 2000, length.out = 100),
-  C0 = 1,
   D_values = 10,
   v_values = 2.14,
-  t_values = max(hl_values * max(log_koc_values)),
   x_values = 60
 )
 
-print(kwb.1dbear::plot_heatmap(bear1d_list = bear1d_tahi_heatmap))
+print(kwb.1dbear::plot_heatmap(bear1d_tahi_heatmap))
 ```
 
 ### Budapest Surany
@@ -67,28 +61,24 @@ bear1d_surany_combined <- kwb.1dbear::calculate_bear1d(
   foc_values = 0.002,
   log_koc_values = c(1, 1.9),
   hl_values = c(500, 2000),
-  C0 = 1,
   D_values = 10,
   v_values = 1.38,
   t_values = seq(0, 700, by = 1),
   x_values = 228
 )
 
 # Combine the plots
-print(kwb.1dbear::plot_combined(bear1d_list = bear1d_surany_combined))
+print(kwb.1dbear::plot_combined(bear1d_surany_combined))
 
 # Generate heat map
-log_koc_values <- seq(0.1, 6, length.out = 100)
 bear1d_surany_heatmap <- kwb.1dbear::calculate_bear1d(
   n_values = 0.3,
   rs_values = 2.7,
   foc_values = 0.002,
-  log_koc_values = log_koc_values,
-  hl_values =  seq(1, 2000, length.out = 100),
-  C0 = 1,
+  log_koc_values = seq(0.1, 6, length.out = 100),
+  hl_values = seq(1, 2000, length.out = 100),
   D_values = 10,
   v_values = 1.38,
-  t_values = max(hl_values * max(log_koc_values)),
   x_values = 228
 )
 
@@ -104,28 +94,24 @@ bear1d_vienna_combined <- kwb.1dbear::calculate_bear1d(
   foc_values = 0.002,
   log_koc_values = c(1, 2.9),
   hl_values = c(500, 2000),
-  C0 = 1,
   D_values = 10,
   v_values = 21.3,
   t_values = seq(0, 350, by = 1),
   x_values = 141
 )
 
 # Combine the plots
-print(kwb.1dbear::plot_combined(bear1d_list = bear1d_vienna_combined))
+print(kwb.1dbear::plot_combined(bear1d_vienna_combined))
 
 # Generate heat map
-log_koc_values <- seq(0.1, 6, length.out = 100)
 bear1d_vienna_heatmap <- kwb.1dbear::calculate_bear1d(
   n_values = 0.15,
   rs_values = 2.7,
   foc_values = 0.002,
-  log_koc_values = log_koc_values,
-  hl_values =  seq(1, 2000, length.out = 100),
-  C0 = 1,
+  log_koc_values = seq(0.1, 6, length.out = 100),
+  hl_values = seq(1, 2000, length.out = 100),
   D_values = 10,
   v_values = 21.3,
-  t_values = max(hl_values * max(log_koc_values)),
   x_values = 141
 )