diff --git a/DESCRIPTION b/DESCRIPTION index aba7d8c783df1cead07f0e8c30d8ed992a015c4b..ebb64510c14507414eca7f7d56277461ebb689cb 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,7 +1,7 @@ Package: SWATdoctR Type: Package Title: Finding the right diagnoses and treatments for SWAT+ models -Version: 0.1.8 +Version: 0.1.9 Author: c(person("Svajunas", "Plunge", email = "svajunas_plunge@sggw.edu.pl", role = c("aut")), diff --git a/R/plot_climate.R b/R/plot_climate.R index c35d8090393408a42b5861913bdce90360cf19ee..c6a5913e7ad5294a8caa9c7eff00d7dce138998a 100644 --- a/R/plot_climate.R +++ b/R/plot_climate.R @@ -194,12 +194,12 @@ plot_climate_annual <- function(sim_verify) { legend.background = element_blank(), legend.box.background = element_rect(colour = "black", fill =alpha('white', 0.6))) - gg_et_stat <- plot_stat_text(clim_data_annual, + gg_et_stat <- plot_stat_text(tbl = clim_data_annual, vars = c('pet', 'et', 'ecanopy', 'eplant', 'esoil'), - c(2,1,0,3,4), 'mm', T) - gg_pcp_stat <- plot_stat_text(clim_data_annual, + pos = c(2,1,0,3,4), unit_add = 'mm', add_title = T) + gg_pcp_stat <- plot_stat_text(tbl = clim_data_annual, vars = c('precip', 'rainfall', 'snofall'), - c(5,4,3), 'mm', F) + pos = c(5,4,3), unit_add = 'mm', add_title = F) tmp_stat <- clim_data %>% filter(name %in% c('tmn', 'tmx', 'tmpav')) %>% group_by(name) %>% @@ -209,15 +209,18 @@ plot_climate_annual <- function(sim_verify) { mutate(name = c('tmn day', 'tmpav', 'tmx day'), value_sum = c(val_min[1], val_mean[2], val_max[3])) %>% select(name, value_sum) - gg_tmp_stat <- plot_stat_text(tmp_stat, + gg_tmp_stat <- plot_stat_text(tbl = tmp_stat, vars = c('tmn day', 'tmpav', 'tmx day'), - c(5,4,3), '\u00b0C', F, digit = 1) - gg_rhum_stat <- plot_stat_text(clim_data_annual, vars = c('rhum'), - c(5), '', F, digit = 2, type = 'value_mean') - gg_wnd_stat <- plot_stat_text(clim_data_annual, vars = c('wndspd'), - c(5), '', 'm/s', digit = 2, type = 'value_mean') - gg_slr_stat <- plot_stat_text(clim_data_annual, vars = c('solarad'), - c(5), 'MJ m^-2', F) + pos = c(5,4,3), unit_add = '\u00b0C', add_title = F, + digit = 1) + gg_rhum_stat <- plot_stat_text(tbl = clim_data_annual, vars = c('rhum'), + pos = c(5), unit_add = '', add_title = F, + digit = 2, type = 'value_mean') + gg_wnd_stat <- plot_stat_text(tbl = clim_data_annual, vars = c('wndspd'), + pos = c(5), unit_add = 'm/s', add_title = F, + digit = 2, type = 'value_mean') + gg_slr_stat <- plot_stat_text(tbl = clim_data_annual, vars = c('solarad'), + pos = c(5), unit_add = 'MJ m^-2', add_title = F) gg_et + gg_et_stat + gg_pcp + gg_pcp_stat + gg_tmp + gg_tmp_stat + gg_rhum + gg_rhum_stat + gg_wnd + gg_wnd_stat + @@ -239,7 +242,8 @@ plot_climate_annual <- function(sim_verify) { #' #' @keywords internal #' -plot_stat_text <- function(tbl, vars, pos, unit_add, add_title, digit = 0, type = 'value_sum') { +plot_stat_text <- function(tbl, vars, pos, unit_add, add_title, + digit = 0, type = 'value_sum') { tbl_mean <- tbl %>% filter(name %in% vars) %>% select(name, all_of(type)) %>%