diff --git a/R/calculate_bear1d.R b/R/calculate_bear1d.R index ebf8957..4ef7046 100644 --- a/R/calculate_bear1d.R +++ b/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 ) { diff --git a/man/calculate_bear1d.Rd b/man/calculate_bear1d.Rd index ae89e4e..4fe15de 100644 --- a/man/calculate_bear1d.Rd +++ b/man/calculate_bear1d.Rd @@ -13,7 +13,7 @@ calculate_bear1d( C0 = 1, D_values, v_values, - t_values, + t_values = max(hl_values * max(log_koc_values)), x_values ) } @@ -34,7 +34,7 @@ calculate_bear1d( \item{v_values}{average linear ground water velocity (L/T)} -\item{t_values}{time (T)} +\item{t_values}{time (T), default: max(hl_values * max(log_koc_values))} \item{x_values}{flow path distance (L)} } diff --git a/vignettes/Tutorial.Rmd b/vignettes/Tutorial.Rmd index 7040afb..cc282b8 100644 --- a/vignettes/Tutorial.Rmd +++ b/vignettes/Tutorial.Rmd @@ -22,15 +22,12 @@ 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), @@ -38,24 +35,21 @@ bear1d_tahi_combined <- kwb.1dbear::calculate_bear1d( ) # 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 @@ -67,7 +61,6 @@ 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), @@ -75,20 +68,17 @@ bear1d_surany_combined <- kwb.1dbear::calculate_bear1d( ) # 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 ) @@ -104,7 +94,6 @@ 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), @@ -112,20 +101,17 @@ bear1d_vienna_combined <- kwb.1dbear::calculate_bear1d( ) # 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 )