added hc-plot

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: SWATtunR
 Type: Package
 Title: Soft & Hard Calibration, Validation Package for SWAT+ models
-Version: 0.0.1.9008
+Version: 0.0.1.9009
 Authors@R: c(
     person("Svajunas", "Plunge", , "svajunas.plunge@gmail.com", role = c("aut", "cre"),
         comment = c(ORCID = '0000-0001-8897-3349')),

R/prepare.R

@@ -160,6 +160,7 @@ calculate_wyr <- function(sim) {
 #' obj_tbl <- calculate_performance(sim = sim_flow, obs, "flo_day", c("kge", "nse"), "month", "sum")
 #' }
 #' @keywords calculate
+#' @seealso \code{\link{calculate_performance_2plus}}
 
 calculate_performance <- function(sim, obs, par_name = NULL, perf_metrics = NULL,
                                   period = NULL,
@@ -326,6 +327,8 @@ calculate_performance <- function(sim, obs, par_name = NULL, perf_metrics = NULL
 #' vector_weights = c(0.5, 0.3, 0.2),
 #' perf_metrics = c("nse", "kge", "pbias", "r2", "mae")
 #' }
+#' @keywords calculate
+#' @seealso \code{\link{calculate_performance}}
 
 calculate_performance_2plus <- function(sim, vector_var, list_obs, list_periods = NULL,
                                      vector_weights = NULL,

_pkgdown.yml

@@ -12,3 +12,4 @@ articles:
   navbar: Hard calibration
   contents:
   - hc
+  - hc-plot

vignettes/hc-plot.Rmd

@@ -0,0 +1,10 @@
+---
+title: "Plotting results"
+subtitle: "Plotting SWAT+ model results"
+output: html_document
+bibliography: ref.bib
+---
+
+```{r setup, include=FALSE}
+knitr::opts_chunk$set(echo = TRUE)
+```

vignettes/hc.Rmd

@@ -306,44 +306,21 @@ The performance metrics can also be applied to multiple variables within the sim
 ```{r calc_perf_mv, message = FALSE, warning = FALSE, eval = FALSE, echo = FALSE}
 
 # Example of usage:
-var_to_use <- list("flo_day_52",  "no3_day_52_conc", "gwd_day")
+var_to_use <- c("flo_day_52",  "no3_day_52_conc", "gwd_day")
 var_weights <- c(0.5, 0.3, 0.2) ## The sum of weights should be 1.
 periods <- list(q_cal_period, wq_cal_period, c('2007-01-01', '2011-12-26'))
 
 # Read the another observed data
-# In case you want to use water quality data, read it here before applying the following code.
+# In case you want to use water quality data, read it here before applying the 
+# following code.
 obs2 <- read_csv(wqobs_path) 
 obs3 <- read_csv(gwobs_path) 
 
 # Calculate the performance metrics for each variable separately.
-calculate_performance_mv <- function(sim, vector_var, list_obs, list_periods = NULL, 
-                                        vector_weights = 1, 
-                                        perf_metrics = c("nse", "kge", "pbias", "r2", "mae")){
-  obj_tbl_list <- pmap(list(vector_var, list_obs, list_periods), function(.x, .y, .z){
-    if(!is.NULL(.z)){
-       tmp <- fix_dates(sim, .y, trim_start = .z[1], trim_end = .z[2])
-    }
-    tmp <- fix_dates(sim, .y, trim_start = .z[1], trim_end = .z[2])
-    calculate_performance(tmp$sim, tmp$obs, par_name = .x, 
-                          perf_metrics = perf_metrics)}) %>% 
-    set_names(vector_var)
-  
-  # Calculate the mean of the performance rank for all parameter sets. In this case
-  # the weights for each variable should be defined and result could be used with 
-  # only option 1 in step 8
-  obj_tbl <- map2(obj_tbl_list, vector_weights, function(.x, .y){
-    select(.x, c(run_id, rank_tot)) %>% 
-      mutate(rank_tot = rank_tot * .y)}) %>% 
-    reduce(., left_join, by = 'run_id')%>%
-    mutate(sum_rank = rowSums(across(starts_with("rank_tot")))) %>% 
-    mutate(rank_tot = as.integer(rank(sum_rank))) %>% 
-    select(run_id, rank_tot)
-  
-  return(list(obj_tbl_list = obj_tbl_list, obj_tbl = obj_tbl))
-}
-
-
+obj_tbl_m <- calculate_performance_2plus(sim_flow, var_to_use, 
+                                         list(obs, obs2, obs3), periods, 
+                                         var_weights)
+```
 
 
-```