From 03b704283c5e42d93bdbd2a319cdd013e4fbb9cd Mon Sep 17 00:00:00 2001
From: Samuel Viana-Jimenez <sp3c@ac6-100.bullx>
Date: Mon, 8 Jan 2024 12:05:48 +0000
Subject: [PATCH] First set of changes to make these scripts compatible with
 the tagged new version of harp (0.2.0). It has been tested under ATOS with a
 conda environment for producing rds (point_verif.R) and collection of
 verification figures (point_verif_local.R) for the Spain_202205 case.

---
 R/point_verif/point_verif.R           |  51 ++++++------
 R/point_verif/point_verif_local.R     |  58 +++++++-------
 R/visualization/fn_plot_aux_scores.R  |  66 ++++++++--------
 R/visualization/fn_plot_helpers.R     |  40 +++++-----
 R/visualization/fn_plot_point_verif.R | 107 +++++++++++++-------------
 config/config_atos.R                  |  27 ++++---
 config/config_atos.sh                 |   2 +-
 config/config_atos.yml_Spain_202205   |  26 ++++---
 8 files changed, 193 insertions(+), 184 deletions(-)

diff --git a/R/point_verif/point_verif.R b/R/point_verif/point_verif.R
index b8c5383..5dc5c1c 100755
--- a/R/point_verif/point_verif.R
+++ b/R/point_verif/point_verif.R
@@ -73,18 +73,15 @@ run_verif <- function(prm_info, prm_name) {
   
   # Read the forecast
   fcst <- read_point_forecast(
-    start_date    = start_date,
-    end_date      = end_date,
-    fcst_model    = fcst_model,
-    fcst_type     = fcst_type,
-    parameter     = prm_name,
-    lead_time     = lead_time,
-    lags          = lags,
-    by            = by_step,
-    file_path     = fcst_path,
-    vertical_coordinate = vertical_coordinate
-  )
-  
+         dttm=seq_dttm(start_date,end_date,by_step),
+         fcst_model    = fcst_model,
+         fcst_type     = fcst_type,
+         parameter     = prm_name,
+         lead_time     = lead_time,
+         lags          = lags,
+         file_path     = fcst_path,
+         vertical_coordinate = vertical_coordinate
+       )
   # Find the common cases - for upper air parmeters we need to ensure 
   # that the level column  is included in the check
   fcst <- switch(
@@ -98,38 +95,39 @@ run_verif <- function(prm_info, prm_name) {
   # function with a named list containing the arguments. 
   if (!is.null(prm_info$scale_fcst)) {
     fcst <- do.call(
-      scale_point_forecast, 
-      c(list(.fcst = fcst), prm_info$scale_fcst))
+      scale_param,list(fcst, prm_info$scale_obs$scaling, prm_info$scale_obs$new_units, prm_info$scale_obs$mult)
+    )
   }
   
   # Read the observations getting the dates and stations from 
   # the forecast
   obs <- read_point_obs(
-    start_date = first_validdate(fcst),
-    end_date   = last_validdate(fcst),
+    #dttm=seq_dttm(start_date,end_date,by_step),
+    dttm=unique_valid_dttm(fcst),
     parameter  = prm_name,
     obs_path   = obs_path,
-    stations   = pull_stations(fcst),
+    stations   = unique_stations(fcst),
     vertical_coordinate = vertical_coordinate
-  )
-  
+  )  
   # optional rescaling of observations using the scale_obs part of the
   # params list. We use do.call to call the scale_point_forecast 
   # function with a named list containing the arguments.
-  if (!is.null(prm_info$scale_obs)) {
+ if (!is.null(prm_info$scale_obs)) {
     obs <- do.call(
-      scale_point_obs, 
-      c(list(.obs = obs, parameter = prm_name), prm_info$scale_obs)
+      scale_param, list(obs, prm_info$scale_obs$scaling, prm_info$scale_obs$new_units, prm_info$scale_obs$mult, col = {{prm_name}})
     )
   }
   
   # Join observations to the forecast
-  fcst <- join_to_fcst(fcst, obs)
+  fcst <- join_to_fcst(fcst, obs, force=TRUE)
+  #Note by Samuel: Some stop clause is needed here if any of the models 
+  #intersects 0 with the observations' SIDS
+
   # Check for errors removing obs that are more than a certain number 
   # of standard deviations from the forecast. You could add a number 
   # of standard deviations to use in the params list 
   fcst <- check_obs_against_fcst(fcst, prm_name)
-  
+
   # Make sure that grps is a list so that it adds on the vertical 
   # coordinate group correctly
   if (!is.list(grps)) {
@@ -168,15 +166,14 @@ print(params)
 # Use possibly from the purrr package to allow the script to continue
 # if it fails for a parameter - it returns NULL if it fails. See
 # ?safely and ?quietly if you want to retain the errors.
-possible_run_verif <- possibly(run_verif, otherwise = NULL)
-print(possible_run_verif)
+possible_run_verif <- safely(run_verif, otherwise = NULL, quiet= FALSE)
 
 # Use imap from the purrr package to map each element of the params list
 # to the possible_run_verif function. imap passes the element of the list
 # as the first argument and the name of the element as the second.
 verif <- imap(params, possible_run_verif)
 
-# This will be addd in the visualization part
+# This will be added in the visualization part
 # You can open the results in a shiny app using 
 # shiny_plot_point_verif(verif_path)
 
diff --git a/R/point_verif/point_verif_local.R b/R/point_verif/point_verif_local.R
index 4368a21..794beba 100755
--- a/R/point_verif/point_verif_local.R
+++ b/R/point_verif/point_verif_local.R
@@ -13,6 +13,8 @@ library(RColorBrewer) # Some colourmaps (some of which are colourblind friendly)
 library(gridExtra) # For grid arrange
 library(grid) # For grid arrange
 library(pracma) # For logseq
+library(boomer)
+library(mapproj)
 
 ###
 source(Sys.getenv('CONFIG_R'))
@@ -46,6 +48,7 @@ params <- CONFIG$params_details
 start_date <- ifelse(is.null(args$start_date),CONFIG$shared$start_date,args$start_date)
 end_date   <- ifelse(is.null(args$end_date),CONFIG$shared$end_date,args$end_date)
 by_step    <- CONFIG$verif$by_step  #Read from config file
+by_obs_step    <- CONFIG$verif$by_obs_step  #Read from config file
 fcst_model <- CONFIG$verif$fcst_model
 lead_time_str <- CONFIG$verif$lead_time
 lead_time  <- eval(parse(text = lead_time_str))
@@ -57,8 +60,8 @@ verif_path <- CONFIG$verif$verif_path
 grps       <- CONFIG$verif$grps
 plot_output <- CONFIG$post$plot_output #  Load in png archive directory
 
-# Verif results by leadtime for each fcst_cycle (should be default choice?)
-grps <- list(c("leadtime","fcst_cycle"),"leadtime")
+# Verif results by lead_time for each fcst_cycle (should be default choice?)
+grps <- list(c("lead_time","fcst_cycle"),"lead_time")
 
 # Useful functions
 # This does some renaming of groups (those with NA or "00;12", etc.)
@@ -114,14 +117,12 @@ run_verif <- function(prm_info, prm_name) {
   
   # Read the forecast
   fcst <- read_point_forecast(
-    start_date    = start_date,
-    end_date      = end_date,
+    dttm=seq_dttm(start_date,end_date,by_step),
     fcst_model    = fcst_model,
     fcst_type     = fcst_type,
     parameter     = prm_name,
     lead_time     = lead_time,
     lags          = lags,
-    by            = by_step,
     file_path     = fcst_path,
     get_lat_and_lon = TRUE, # Useful when lat/lon missing from vobs files
     vertical_coordinate = vertical_coordinate
@@ -140,18 +141,17 @@ run_verif <- function(prm_info, prm_name) {
   # function with a named list containing the arguments. 
   if (!is.null(prm_info$scale_fcst)) {
     fcst <- do.call(
-      scale_point_forecast, 
-      c(list(.fcst = fcst), prm_info$scale_fcst))
+      scale_param,list(fcst, prm_info$scale_obs$scaling, prm_info$scale_obs$new_units, prm_info$scale_obs$mult)
+    )
   }
   
   # Read the observations getting the dates and stations from 
   # the forecast
   obs <- read_point_obs(
-    start_date = first_validdate(fcst),
-    end_date   = last_validdate(fcst),
+    dttm=seq_dttm(start_date,end_date,by_obs_step),
     parameter  = prm_name,
     obs_path   = obs_path,
-    stations   = pull_stations(fcst),
+    stations   = unique_stations(fcst),
     min_allowed = prm_info$obsmin_val, # If obsmin/max not set, reverts to default
     max_allowed = prm_info$obsmax_val,
     vertical_coordinate = vertical_coordinate
@@ -162,8 +162,7 @@ run_verif <- function(prm_info, prm_name) {
   # function with a named list containing the arguments.
   if (!is.null(prm_info$scale_obs)) {
     obs <- do.call(
-      scale_point_obs, 
-      c(list(.obs = obs, parameter = prm_name), prm_info$scale_obs)
+      scale_param, list(obs, prm_info$scale_obs$scaling, prm_info$scale_obs$new_units, prm_info$scale_obs$mult, col = {{prm_name}})
     )
   }
   
@@ -188,8 +187,9 @@ run_verif <- function(prm_info, prm_name) {
   )
 
   # add valid_hour to fcst
-  #fcst <- mutate_list(fcst,valid_hour=substr(YMDh(validdate),9,10))
-  fcst <- expand_date(fcst,validdate) # Add in valid_year, valid_month, valid_day, valid_hour
+  #fcst <- mutate_list(fcst,valid_hour=substr(YMDh(valid_dttm),9,10))
+  fcst <- expand_date(fcst,valid_dttm) # Add in valid_year, valid_month, valid_day, valid_hour
+  #fcst <- rig(expand_date)(fcst,valid_dttm) # Add in valid_year, valid_month, valid_day, valid_hour  
   fcst <- mutate_list(fcst,valid_hour = sprintf("%02d",valid_hour)) # Convert to character and pad
   # Remove stations that only occur very infrequently (for surface variables only)
   if (is.na(vertical_coordinate)){
@@ -226,28 +226,29 @@ run_verif <- function(prm_info, prm_name) {
   )
   verif <- fn_verif_rename(verif)
   verif_toplot <- verif # Used for passing to plotting script (as it may be modified below)
-  verif_toplot[[2]][["leadtime"]] <- as.character(verif_toplot[[2]][["leadtime"]]) # For plotting purposes
+  verif_toplot[[2]][["lead_time"]] <- as.character(verif_toplot[[2]][["lead_time"]]) # For plotting purposes
+
   
   # Do some additional verif depending on UA parameter
   if (!is.na(vertical_coordinate)){
     # Group by valid_hour for profiles (threshold scores not required)
-    grps_vh  <- lapply(grps_c,function(x) gsub("leadtime","valid_hour",x))
+    grps_vh  <- lapply(grps_c,function(x) gsub("lead_time","valid_hour",x))
     verif_vh <-  get(verif_fn)(
       fcst, prm_name, thresholds = NULL, groupings = grps_vh
     )
     verif_vh <- fn_verif_rename(verif_vh)
       
   } else {
-    # Compute scores as a function of validdate (should take the same format as default leadtime groups)
+    # Compute scores as a function of valid_dttm (should take the same format as default lead_time groups)
     # Assuming threshold scores are not required
-    grps_vd  <- lapply(grps_c,function(x) gsub("leadtime","validdate",x))
+    grps_vd  <- lapply(grps_c,function(x) gsub("lead_time","valid_dttm",x))
     verif_vd <- get(verif_fn)(
       fcst, prm_name, thresholds = NULL, groupings = grps_vd
     )
     verif_vd <- fn_verif_rename(verif_vd)
-
+   
     # Compute scores for each station for map purposes
-    grps_sid  <- lapply(grps_c,function(x) gsub("leadtime","SID",x))
+    grps_sid  <- lapply(grps_c,function(x) gsub("lead_time","SID",x))
     # Replace fcst_cycle by valid_hour
     if ("fcst_cycle" %in% grps_sid[[1]]){
       grps_sid  <- lapply(grps_sid,function(x) gsub("fcst_cycle","valid_hour",x))
@@ -263,12 +264,12 @@ run_verif <- function(prm_info, prm_name) {
     verif_sid <- fn_verif_rename(verif_sid)
     # Need to add lat/lon to the SIDs
     verif_sid <- fn_sid_latlon(verif_sid,fcst)
-  
-    # Flag to compute the standard threshold scores over all leadtimes and add
+    
+    # Flag to compute the standard threshold scores over all lead_times and add
     alllt_thresholds <- TRUE
     if (alllt_thresholds){
-      #  Compute threshold scores over all leadtimes (as done in Monitor) (retain default group structure)
-      grps_nolt <- lapply(grps_c,function(x) x[x != "leadtime"])
+      #  Compute threshold scores over all lead_times (as done in Monitor) (retain default group structure)
+      grps_nolt <- lapply(grps_c,function(x) x[x != "lead_time"])
       grps_nolt <- grps_nolt[lapply(grps_nolt,length)>0] 
       # Note: This will remove character(0) entries but will miss the "All" option for fcst_cycle etc.
       # Hence we add a NULL below (NB: this may not be required with updated version of harp)
@@ -277,10 +278,10 @@ run_verif <- function(prm_info, prm_name) {
         fcst, prm_name, thresholds = prm_info$thresholds, groupings = grps_nolt
       )
       verif_alllt <- fn_verif_rename(verif_alllt)
-      # Add in indication that we use all leadtimes (important for plotting script and for binding below)
-      verif_alllt <- mutate_list(verif_alllt,leadtime = "All") 
+      # Add in indication that we use all lead_times (important for plotting script and for binding below)
+      verif_alllt <- mutate_list(verif_alllt,lead_time = "All") 
       
-      print("Adding threshold scores over all leadtimes")
+      print("Adding threshold scores over all lead_times")
       # Bind rows will match the column names
       verif_toplot[[2]] <- bind_rows(verif_toplot[[2]],verif_alllt[[2]])
     }
@@ -306,7 +307,8 @@ run_verif <- function(prm_info, prm_name) {
 # Use possibly from the purrr package to allow the script to continue
 # if it fails for a parameter - it returns NULL if it fails. See
 # ?safely and ?quietly if you want to retain the errors.
-possible_run_verif <- possibly(run_verif, otherwise = NULL)
+#possibly(run_verif, otherwise = NULL)
+possible_run_verif <- safely(run_verif, otherwise = NULL, quiet= FALSE)
 #possible_run_verif <- run_verif
 #print(possible_run_verif)
 
diff --git a/R/visualization/fn_plot_aux_scores.R b/R/visualization/fn_plot_aux_scores.R
index 39a4e5f..256526d 100755
--- a/R/visualization/fn_plot_aux_scores.R
+++ b/R/visualization/fn_plot_aux_scores.R
@@ -37,15 +37,15 @@ fn_plot_aux_scores <- function(fcst_input,png_archive,station_group_var = "stati
   if (fcst_type == "ens"){
     # Add in ensemble mean and spread
     fcst <- ens_stats(fcst_input)
-    fcst <- bind_fcst(fcst) # Can take a while
+    fcst <- bind(fcst) # Can take a while
     fcst_names <- names(fcst)
-    # TODO: Check in latest version of harp if the same behaviour occurs. When you bind_fcst after using ens_stats,
+    # TODO: Check in latest version of harp if the same behaviour occurs. When you bind() after using ens_stats,
     # the mean and spread are added on as columns ens_mean/spread (these repeat for each member). Thus do some manipulation here
     # to add the mean/spread to the "member" column to tidy things up 
     # TODO: Possibly this is not recommended...may have to revisit
     df_meanspread <- NULL
     for (c_model in models_vec){
-      df_tmp    <- fcst %>% filter(mname == c_model); members_tmp <- unique(df_tmp[["member"]])
+      df_tmp    <- fcst %>% filter(fcst_model == c_model); members_tmp <- unique(df_tmp[["member"]])
       df_tmp    <- df_tmp %>% filter(member == members_tmp[1])
       df_mean   <- df_tmp %>% mutate(member = "mean",forecast = ens_mean)
       df_spread <- df_tmp %>% mutate(member = "spread",forecast = ens_spread)
@@ -54,14 +54,14 @@ fn_plot_aux_scores <- function(fcst_input,png_archive,station_group_var = "stati
     fcst <- bind_rows(fcst,df_meanspread); fcst <- select(fcst,-ens_mean,-ens_spread)
     rm(df_tmp,members_tmp,df_mean,df_spread,df_meanspread)
   } else if (fcst_type == "det"){
-    fcst <- bind_fcst(fcst_input) 
+    fcst <- bind(fcst_input) 
     fcst_names <- names(fcst)
   }
 
   # Add in validhour and station group if they do not exist
   if (!("valid_hour" %in% fcst_names)){
-    #fcst <- mutate(fcst,validhour=substr(YMDh(validdate),9,10))
-    fcst <- expand_date(fcst,validdate)
+    #fcst <- mutate(fcst,validhour=substr(YMDh(valid_dttm),9,10))
+    fcst <- expand_date(fcst,valid_dttm)
     fcst <- mutate_list(fcst,valid_hour = sprintf("%02d",valid_hour))
   }
   if (!(station_group_var %in% fcst_names)){
@@ -74,8 +74,8 @@ fn_plot_aux_scores <- function(fcst_input,png_archive,station_group_var = "stati
   cycles   <- sort(unique(fcst[["fcst_cycle"]]))
   stations <- unique(fcst[[station_group_var]])
   par_unit <- unique(fcst[["units"]])
-  sdate    <- YMDh(first(sort(unique(fcst[["fcdate"]]))))
-  edate    <- YMDh(last(sort(unique(fcst[["fcdate"]]))))
+  sdate    <- YMDh(first(sort(unique(fcst[["fcst_dttm"]]))))
+  edate    <- YMDh(last(sort(unique(fcst[["fcst_dttm"]]))))
   
   # Check if the png_archive points to sdate-edate? If not, create a subdirectory
   d_end <- paste0(sdate,"-",edate)
@@ -88,7 +88,7 @@ fn_plot_aux_scores <- function(fcst_input,png_archive,station_group_var = "stati
   # USER INTERACTION
   #=================================================#
   
-  lt_to_use   <- seq(3,48,3) # What leadtimes to use?
+  lt_to_use   <- seq(3,48,3) # What lead_times to use?
   cycles_oi   <- c("All") # What cycles to plot for?
   stations_oi <- unique(c(stations,"All")) # What stations to plot for?
   fd_adjust   <- 1  # Adjust parameter in freq dist plotting
@@ -164,13 +164,13 @@ fn_plot_aux_scores <- function(fcst_input,png_archive,station_group_var = "stati
   # COMPUTE VARIOUS AUX SCORES
   #=================================================#
   
-  fcst      <- filter(fcst,leadtime %in% lt_to_use)
-  leadtimes <- sort(unique(fcst[["leadtime"]]))
+  fcst      <- filter(fcst,lead_time %in% lt_to_use)
+  lead_times <- sort(unique(fcst[["lead_time"]]))
   
-  if (length(leadtimes)>5){
-    lt_used_fig <- c(leadtimes[1],leadtimes[2],"... ",leadtimes[length(leadtimes)])
+  if (length(lead_times)>5){
+    lt_used_fig <- c(lead_times[1],lead_times[2],"... ",lead_times[length(lead_times)])
   } else {
-    lt_used_fig <- leadtimes
+    lt_used_fig <- lead_times
   }
   
   for (cycle in cycles_oi){
@@ -219,12 +219,12 @@ fn_plot_aux_scores <- function(fcst_input,png_archive,station_group_var = "stati
         
         # Member scores (not really required)
         if (mbr_plots){
-          group_vars <- c("mname","valid_hour","member")
+          group_vars <- c("fcst_model","valid_hour","member")
           vroption_list$score <- "mbrdailyvar"; vroption_list$xgroup <- "valid_hour"; vroption_list$xg_str <- "vh"
           fn_dvar_ts(cc_fcst,group_vars,title_str,subtitle_str,fxoption_list,vroption_list)
           
-          group_vars <- c("mname","validdate","member")
-          vroption_list$score <- "mbrtimeseries"; vroption_list$xgroup <- "validdate"; vroption_list$xg_str <- "vd"
+          group_vars <- c("fcst_model","valid_dttm","member")
+          vroption_list$score <- "mbrtimeseries"; vroption_list$xgroup <- "valid_dttm"; vroption_list$xg_str <- "vd"
           fn_dvar_ts(cc_fcst,group_vars,title_str,subtitle_str,fxoption_list,vroption_list)
           
           vroption_list$xgroup <- "NA"; vroption_list$score <- "mbrfreqdist"; vroption_list$xg_str <- "NA";
@@ -255,13 +255,13 @@ fn_aux <- function(fc,title_str,subtitle_str,fxoption_list,vroption_list){
   }
   
   # Daily Var 
-  group_vars <- c("mname","valid_hour")
+  group_vars <- c("fcst_model","valid_hour")
   vroption_list$xgroup <- "valid_hour"; vroption_list$score <- paste0(cprefix,"dailyvar"); vroption_list$xg_str <- "vh"
   fn_dvar_ts(fc,group_vars,title_str,subtitle_str,fxoption_list,vroption_list)
   
   # Timeseries 
-  group_vars <- c("mname","validdate")
-  vroption_list$xgroup <- "validdate"; vroption_list$score <- paste0(cprefix,"timeseries"); vroption_list$xg_str <- "vd"
+  group_vars <- c("fcst_model","valid_dttm")
+  vroption_list$xgroup <- "valid_dttm"; vroption_list$score <- paste0(cprefix,"timeseries"); vroption_list$xg_str <- "vd"
   fn_dvar_ts(fc,group_vars,title_str,subtitle_str,fxoption_list,vroption_list)
   
   # Frequency distribution 
@@ -291,15 +291,15 @@ fn_dvar_ts <- function(fc,group_vars,title_str,subtitle_str,fxoption_list,vropti
     vroption_list$score <- score
   }
   
-  dv <- fc %>% group_by_at(group_vars) %>% summarise(!!score := mean(forecast), mean_obs = mean(OBS),num_cases=n())
+  dv <- fc %>% group_by_at(group_vars) %>% summarise(!!score := mean(fcst), mean_obs = mean(OBS),num_cases=n())
   
-  # Replace mean_obs by "OBS" in mname (or member)
+  # Replace mean_obs by "OBS" in fcst_model (or member)
   if (grepl("mbr",score_orig)){
     dv_tmp <- filter(dv,member == unique(dv[["member"]][1]))
     dv_tmp <- mutate(dv_tmp,member = "OBS","{score}" := mean_obs)
   } else {
-    dv_tmp <- filter(dv,mname == unique(dv[["mname"]])[1])
-    dv_tmp <- mutate(dv_tmp,mname = "OBS","{score}" := mean_obs)
+    dv_tmp <- filter(dv,fcst_model == unique(dv[["fcst_model"]])[1])
+    dv_tmp <- mutate(dv_tmp,fcst_model = "OBS","{score}" := mean_obs)
   }
   dv <- bind_rows(dv,dv_tmp); dv <- select(dv,-mean_obs)
 
@@ -335,23 +335,23 @@ fn_freqdist <- function(fc,title_str,subtitle_str,fxoption_list,vroption_list){
     fc      <- fc %>% filter(!(member %in% c("mean","spread","OBS")))
     
     p_out <- ggplot()+
-      geom_density(data=fc,aes(x=forecast,group=interaction(mname,member)),color="gray",
+      geom_density(data=fc,aes(x=fcst,group=interaction(fcst_model,member)),color="gray",
                    size=fxoption_list$line_size,adjust=fxoption_list$fd_adjust,alpha=0.5)+
-      geom_density(data=fc_ctrl,aes(x=forecast,group=mname,color="mbr000"),
+      geom_density(data=fc_ctrl,aes(x=fcst,group=fcst_model,color="mbr000"),
                    size=fxoption_list$line_size,adjust=fxoption_list$fd_adjust,alpha=0.5)+
-      geom_density(data=fc_mean,aes(x=forecast,group=mname,color="mean"),
+      geom_density(data=fc_mean,aes(x=fcst,group=fcst_model,color="mean"),
                    size=fxoption_list$line_size,adjust=fxoption_list$fd_adjust,alpha=0.5)+
-      geom_density(data=fc_obs,aes(x=forecast,group=mname,color="OBS"),
+      geom_density(data=fc_obs,aes(x=fcst,group=fcst_model,color="OBS"),
                    size=fxoption_list$line_size,adjust=fxoption_list$fd_adjust,alpha=0.5)+
-      facet_wrap(vars(mname),ncol=min(fxoption_list$num_models,2))+
+      facet_wrap(vars(fcst_model),ncol=min(fxoption_list$num_models,2))+
       labs(x = fxoption_list$par_unit, y = "Relative frequency",color = "",
            title=ptitle,subtitle = subtitle_str)+fxoption_list$ptheme_l
     
   } else {
-    fc_obs <- fc %>% filter(mname == unique(fc[["mname"]][1]))
+    fc_obs <- fc %>% filter(fcst_model == unique(fc[["fcst_model"]][1]))
   
     p_out <- ggplot()+
-      geom_density(data=fc,aes(x=forecast,color=fct_inorder(mname)),size=fxoption_list$line_size,
+      geom_density(data=fc,aes(x=fcst,color=fct_inorder(fcst_model)),size=fxoption_list$line_size,
                    adjust=fxoption_list$fd_adjust)+
       geom_density(data=fc_obs,aes(x=OBS,color="OBS"),size=fxoption_list$line_size,
                    adjust=fxoption_list$fd_adjust)+
@@ -384,9 +384,9 @@ fn_scatterplot <- function(fc,title_str,subtitle_str,fxoption_list,vroption_list
   title_scores <- gsub("_"," ",str_to_title(title_scores))
   ptitle <- paste0(paste0(title_scores,collapse = ", ")," : ",title_str)
   
-  p_scat <- fc %>% ggplot(aes(x=OBS,y=forecast))+
+  p_scat <- fc %>% ggplot(aes(x=OBS,y=fcst))+
     geom_hex(bins=fxoption_list$scat_bins)+
-    facet_wrap(vars((mname)),ncol=min(fxoption_list$num_models,3))
+    facet_wrap(vars((fcst_model)),ncol=min(fxoption_list$num_models,3))
   max_count <- max(ggplot_build(p_scat)$data[[1]]$count)
   br1 <- round(logseq(1,max_count,5),0)
   p_scat <- p_scat +
diff --git a/R/visualization/fn_plot_helpers.R b/R/visualization/fn_plot_helpers.R
index 2a0d7ea..b9dfb1c 100755
--- a/R/visualization/fn_plot_helpers.R
+++ b/R/visualization/fn_plot_helpers.R
@@ -35,8 +35,8 @@ fn_plot_point <- function(verif,title_str,subtitle_str,fxoption_list,vroption_li
     df <- verif
   }
   
-  # A check on the type of xgroup (in case of character type for leadtime and validhour)
-  if ((xgroup %in% names(df)) & (is.character(df[[xgroup]])) & ((xgroup == "leadtime") || (xgroup == "valid_hour"))){
+  # A check on the type of xgroup (in case of character type for lead_time and validhour)
+  if ((xgroup %in% names(df)) & (is.character(df[[xgroup]])) & ((xgroup == "lead_time") || (xgroup == "valid_hour"))){
     df[[xgroup]] <- as.numeric(df[[xgroup]])
   }
   
@@ -49,8 +49,8 @@ fn_plot_point <- function(verif,title_str,subtitle_str,fxoption_list,vroption_li
   # Plot title
   ptitle <- paste0(paste0(title_scores,collapse = ", ")," : ",title_str)
   
-  # Change point size if we are looking at validdate
-  if (xgroup == "validdate"){
+  # Change point size if we are looking at valid_dttm
+  if (xgroup == "valid_dttm"){
     stroke_size = 0; 
     point_size = 0
   }
@@ -61,9 +61,9 @@ fn_plot_point <- function(verif,title_str,subtitle_str,fxoption_list,vroption_li
     models_tmp  <- names(mcolors)
     colours_tmp <- unname(mcolors)
     # Colour table
-    ctab <- data.frame(mname = models_tmp,colour = colours_tmp)
-    colnames(ctab) <- c("mname","colour")
-    plot_point_verif(verif,{{all_scores}}, rank_is_relative = "TRUE", rank_hist_type = "lollipop", colour_by = "mname",
+    ctab <- data.frame(fcst_model = models_tmp,colour = colours_tmp)
+    colnames(ctab) <- c("fcst_model","colour")
+    plot_point_verif(verif,{{all_scores}}, rank_is_relative = "TRUE", rank_hist_type = "lollipop", colour_by = "fcst_model",
                      colour_table = ctab, plot_title = ptitle, plot_subtitle = subtitle_str, legend_position = "top",
                      plot_caption = "none")
     # Save 
@@ -73,8 +73,8 @@ fn_plot_point <- function(verif,title_str,subtitle_str,fxoption_list,vroption_li
     return(p_out)
   } else if (any(grepl("mbr",all_scores))){
     
-    # If looking at validdate, then use only one column
-    if (xgroup == "validdate"){
+    # If looking at valid_dttm, then use only one column
+    if (xgroup == "valid_dttm"){
       ncols = 1
     } else {
       ncols = min(num_models,2)
@@ -82,7 +82,7 @@ fn_plot_point <- function(verif,title_str,subtitle_str,fxoption_list,vroption_li
     
     # Plot all members and facet by model name
     c_score <- gsub("mbr","",all_scores)
-    # If OBS exists as a mname, then add this in
+    # If OBS exists as a fcst_model, then add this in
     df_ctrl <- df %>% filter(member == "mbr000")
     # This deals with the case of dailyvar/timeseries
     if ("OBS" %in% unique(df[["member"]])){
@@ -91,20 +91,20 @@ fn_plot_point <- function(verif,title_str,subtitle_str,fxoption_list,vroption_li
       df <- df %>% filter(!(member %in% c("mean","spread","OBS")))
       
       p_out <- ggplot()+
-        geom_path(data=df,aes(x=get(xgroup),y=get(c_score),group=interaction(mname,member)),
+        geom_path(data=df,aes(x=get(xgroup),y=get(c_score),group=interaction(fcst_model,member)),
                   alpha=0.5,size=line_size,color="gray")+
         geom_path(data=df_ctrl,aes(x=get(xgroup),y=get(c_score),color="mbr000"),size=line_size)+
         geom_path(data=df_mean,aes(x=get(xgroup),y=get(c_score),color="Mean"),size=line_size)+
         geom_path(data=df_obs,aes(x=get(xgroup),y=get(c_score),color="OBS"),size=line_size)+
-        facet_wrap(vars(mname),ncol=ncols)+
+        facet_wrap(vars(fcst_model),ncol=ncols)+
         labs(x = str_to_title(xgroup),y = par_unit,title=ptitle,subtitle=subtitle_str,color="")+ptheme_l
       
     } else {
       p_out <- ggplot()+
-          geom_path(data=df,aes(x=get(xgroup),y=get(c_score),group=interaction(mname,member)),
+          geom_path(data=df,aes(x=get(xgroup),y=get(c_score),group=interaction(fcst_model,member)),
                     alpha=0.5,size=line_size,color="gray")+
           geom_path(data=df_ctrl,aes(x=get(xgroup),y=get(c_score)),color="red",size=line_size)+
-          facet_wrap(vars(mname),ncol=ncols)+
+          facet_wrap(vars(fcst_model),ncol=ncols)+
           labs(x = str_to_title(xgroup),y = par_unit,title=ptitle,subtitle=subtitle_str)+ptheme_l
     }
       
@@ -118,14 +118,14 @@ fn_plot_point <- function(verif,title_str,subtitle_str,fxoption_list,vroption_li
     if (num_scores == 1){
       # Remove Inf/-Inf values which may appear for ens skill scores
       df <- df[!is.infinite(df[[all_scores]]),]
-      p_out <- df %>% ggplot(aes(x=get(xgroup),color=fct_inorder(mname)))+
+      p_out <- df %>% ggplot(aes(x=get(xgroup),color=fct_inorder(fcst_model)))+
         geom_line(aes(y=get(all_scores)),size=line_size)+
         geom_point(aes(y=get(all_scores)),stroke=stroke_size,size=point_size)
     } else if (num_scores == 2){
       # Remove Inf/-Inf values which may appear for ens skill scores
       df <- df[!is.infinite(df[[all_scores[1]]]),]
       df <- df[!is.infinite(df[[all_scores[2]]]),]
-      p_out <- df %>% ggplot(aes(x=get(xgroup),color=fct_inorder(mname)))+
+      p_out <- df %>% ggplot(aes(x=get(xgroup),color=fct_inorder(fcst_model)))+
         geom_line(aes(y=get(all_scores[1]),linetype=title_scores[1]),size=line_size)+
         geom_point(aes(y=get(all_scores[1])),stroke=stroke_size,size=point_size)+
         geom_line(aes(y=get(all_scores[2]),linetype=title_scores[2]),size=line_size)+
@@ -166,8 +166,8 @@ fn_plot_numcases <- function(verif,fxoption_list,vroption_list){
     df <- verif
   }
   
-  # A check on the type of xgroup (in case of character type for leadtime and validhour)
-  if ((xgroup %in% names(df)) & (is.character(df[[xgroup]])) & ((xgroup == "leadtime") || (xgroup == "valid_hour"))){
+  # A check on the type of xgroup (in case of character type for lead_time and validhour)
+  if ((xgroup %in% names(df)) & (is.character(df[[xgroup]])) & ((xgroup == "lead_time") || (xgroup == "valid_hour"))){
     df[[xgroup]] <- as.numeric(df[[xgroup]])
   }
   
@@ -182,7 +182,7 @@ fn_plot_numcases <- function(verif,fxoption_list,vroption_list){
     }
     ylabel <- "Num. cases obs."
   }
-  p_out<- df %>% ggplot(aes(x=get(xgroup),color=fct_inorder(mname)))+
+  p_out<- df %>% ggplot(aes(x=get(xgroup),color=fct_inorder(fcst_model)))+
     geom_line(aes(y=get(ncy)),size=line_size)+
     geom_point(aes(y=get(ncy)),stroke=stroke_size,size=point_size)+
     labs(x = " ",y = ylabel,color = " ",shape = " ")+ptheme_nc+
@@ -198,4 +198,4 @@ fn_plot_numcases <- function(verif,fxoption_list,vroption_list){
   }
   return(p_out)
 }
-#================================================#
\ No newline at end of file
+#================================================#
diff --git a/R/visualization/fn_plot_point_verif.R b/R/visualization/fn_plot_point_verif.R
index 8149e06..b9fd01b 100755
--- a/R/visualization/fn_plot_point_verif.R
+++ b/R/visualization/fn_plot_point_verif.R
@@ -23,10 +23,10 @@ fn_plot_point_verif <- function(harp_verif_input,png_archive,plot_num_cases = TR
 
   if (all(grepl("det_",scores_tables))){
     fcst_type <- "det"
-    model_names <- unique(verif$det_summary_scores$mname)
+    model_names <- unique(verif$det_summary_scores$fcst_model)
   } else if (any(grepl("ens_",scores_tables))){
     fcst_type <- "ens"
-    model_names <- unique(verif$ens_summary_scores$mname)
+    model_names <- unique(verif$ens_summary_scores$fcst_model)
   } else {
     stop("Input does not look like a harpPoint verification object, aborting")
   }
@@ -50,9 +50,9 @@ fn_plot_point_verif <- function(harp_verif_input,png_archive,plot_num_cases = TR
     
     # START OF SURFACE SCORES
     
-    # Scores as a fn of leadtime
+    # Scores as a fn of lead_time
     scores_lt  <- c("bias~rmse")
-    # Scores as a fn of validdate
+    # Scores as a fn of valid_dttm
     scores_vd  <- c("bias~stde") 
     # Scores as a fn of threshold
     scores_th  <- c("threat_score","false_alarm_rate","false_alarm_ratio","kuiper_skill_score",
@@ -64,11 +64,11 @@ fn_plot_point_verif <- function(harp_verif_input,png_archive,plot_num_cases = TR
     # Map scores (combining scores won't work here)
     scores_mp  <- c("bias","rmse")
     
-    # Leadtimes to plot when looking at scores_th
-    #tleadtimes <- c("24","48","All")
-    tleadtimes  <- c("All")
+    # lead_times to plot when looking at scores_th
+    #tlead_times <- c("24","48","All")
+    tlead_times  <- c("All")
     
-    # Cycles to consider when plotting (summary, threshold scores as fn of leadtime, theshold scores as fn of threshold)
+    # Cycles to consider when plotting (summary, threshold scores as fn of lead_time, theshold scores as fn of threshold)
     cycles_summary      <- c("00","12","All")
     cycles_threshold_lt <- c("All")
     cycles_threshold_th <- c("00","12","All")
@@ -76,7 +76,7 @@ fn_plot_point_verif <- function(harp_verif_input,png_archive,plot_num_cases = TR
     # END OF SURFACE SCORES
     
     # START OF UA SCORES
-    # Scores as a fn of leadtime
+    # Scores as a fn of lead_time
     p_scores_lt <- c("bias~rmse")
     
     # Profile scores
@@ -87,22 +87,22 @@ fn_plot_point_verif <- function(harp_verif_input,png_archive,plot_num_cases = TR
     # NB: What groups are considered? 
     # This controls what group to look for in the verif object and then do something sensible from there).
     # There are several options available (note that the "p_*" refers to UA plotting):
-    # 1) "leadtime", "validdate", "threshold", "p_leadtime" - Here the groups are used for the x-axis
+    # 1) "lead_time", "valid_dttm", "threshold", "p_lead_time" - Here the groups are used for the x-axis
     # 2) "SID" - For map scores
     # 3) "p_prof" - For UA profiles
     # 4) "other" - Some special ens scores which are handled by harp's plot_point_verif
     # In general one can leave xgroups as all of the above; if the data does not exist in the verif object,
     # it will simply be skipped
-    xgroups    <- c("leadtime","validdate","threshold","SID","p_leadtime","p_prof")
+    xgroups    <- c("lead_time","valid_dttm","threshold","SID","p_lead_time","p_prof")
 
     # EPS EXPERIMENT
   } else if (fcst_type == "ens"){
     
     # START OF SURFACE SCORES
     
-    # Ensemble scores as a fn of leadtime
+    # Ensemble scores as a fn of lead_time
     scores_lt  <- c("mean_bias~rmse","rmse~spread","crps","fair_crps")
-    # Ensemble scores as a fn of validdate
+    # Ensemble scores as a fn of valid_dttm
     scores_vd  <- c("mean_bias~stde")
     # Ensemble scores as a fn of thresholds
     scores_th  <- c("brier_score","brier_skill_score","fair_brier_score","roc_area")
@@ -127,11 +127,11 @@ fn_plot_point_verif <- function(harp_verif_input,png_archive,plot_num_cases = TR
       scores_mp <- c(scores_mp,"ctrlbias","ctrlrmse")
     }
     
-    # Leadtimes to plot when looking at scores_th
-    #tleadtimes <- c(seq(12,48,12),"All")
-    tleadtimes <- c("All")
+    # lead_times to plot when looking at scores_th
+    #tlead_times <- c(seq(12,48,12),"All")
+    tlead_times <- c("All")
     
-    # Cycle to consider when plotting (summary, threshold scores as fn of leadtime, theshold scores as fn of threshold)
+    # Cycle to consider when plotting (summary, threshold scores as fn of lead_time, theshold scores as fn of threshold)
     cycles_summary      <- c("00","12","All")
     cycles_threshold_lt <- c("All")
     cycles_threshold_th <- c("00","12","All")
@@ -139,7 +139,7 @@ fn_plot_point_verif <- function(harp_verif_input,png_archive,plot_num_cases = TR
     # END OF SURFACE SCORES
     
     # START OF UA SCORES
-    # Scores as a fn of leadtime
+    # Scores as a fn of lead_time
     p_scores_lt <- c("mean_bias~rmse")
     
     # Profile scores
@@ -153,7 +153,7 @@ fn_plot_point_verif <- function(harp_verif_input,png_archive,plot_num_cases = TR
     # ENS OF UA SCORES
     
     # What groups are considered? (see descriptionin "det" section above) 
-    xgroups    <- c("leadtime","validdate","threshold","SID","other","p_leadtime","p_prof")
+    xgroups    <- c("lead_time","valid_dttm","threshold","SID","other","p_lead_time","p_prof")
 
   }
   
@@ -169,8 +169,11 @@ fn_plot_point_verif <- function(harp_verif_input,png_archive,plot_num_cases = TR
   # Get useful attributes
   num_models   <- length(model_names)
   param        <- attr(verif,"parameter")
-  sdate        <- attr(verif,"start_date")
-  edate        <- attr(verif,"end_date")
+  sdate        <- attr(verif,"dttm")[1]
+  sdate        <- format(str_datetime_to_datetime(sdate),"%Y%m%d%H")
+  edate        <- attr(verif,"dttm")[length(attr(verif,"dttm"))]
+  edate        <- format(str_datetime_to_datetime(edate),"%Y%m%d%H")
+  
   # Note: The unit of the parameter is not included in the harp verif object by default (it seems?)
   # It should be manually added as an extra attribute upstream. If not, it will be set to empty
   par_unit     <- attr(verif,"unit") 
@@ -283,10 +286,10 @@ fn_plot_point_verif <- function(harp_verif_input,png_archive,plot_num_cases = TR
     c_ind = TRUE # Just a counter for printing
     
     # Define some options based on the x-axis
-    if (xgroup == "leadtime"){
+    if (xgroup == "lead_time"){
       xg_str <- "lt"
       scores <- scores_lt
-    } else if (xgroup == "validdate"){
+    } else if (xgroup == "valid_dttm"){
       xg_str <- "vd"
       scores <- scores_vd
     } else if (xgroup == "valid_hour"){
@@ -301,7 +304,7 @@ fn_plot_point_verif <- function(harp_verif_input,png_archive,plot_num_cases = TR
     } else if (xgroup == "SID"){
       xg_str <- "mp"
       scores <- scores_mp
-    } else if (xgroup == "p_leadtime"){
+    } else if (xgroup == "p_lead_time"){
       xg_str <- "lt"
       scores <- p_scores_lt
     } else if (xgroup == "p_prof"){
@@ -354,7 +357,7 @@ fn_plot_point_verif <- function(harp_verif_input,png_archive,plot_num_cases = TR
       verif      <- tmp_out$verif
       stations   <- tmp_out$stations
       cycles     <- tmp_out$cycles; cycles <- intersect(cycles,cycles_oi)
-      leadtimes  <- tmp_out$leadtimes; leadtime_vals <- intersect(tleadtimes,leadtimes)
+      lead_times  <- tmp_out$lead_times; lead_time_vals <- intersect(tlead_times,lead_times)
       validhours <- tmp_out$validhours
       station_group_var <- tmp_out$station_group_var
       rm(tmp_out)
@@ -392,21 +395,21 @@ fn_plot_point_verif <- function(harp_verif_input,png_archive,plot_num_cases = TR
             # Plot
             if (c_typ == "threshold"){
               
-              # Here we are either plotting as a fn of leadtime or threshold
+              # Here we are either plotting as a fn of lead_time or threshold
               if (xgroup == "threshold"){
-                loop_values <- leadtime_vals; filter_col  <- "leadtime"
+                loop_values <- lead_time_vals; filter_col  <- "lead_time"
                 verif_III   <- verif_II
-              } else if (xgroup == "leadtime"){
+              } else if (xgroup == "lead_time"){
                 loop_values <- threshold_vals; filter_col  <- "threshold"
-                # Remove case where we have threshold scores over all leadtimes
-                verif_III   <- filter_list(verif_II,leadtime != "All") 
+                # Remove case where we have threshold scores over all lead_times
+                verif_III   <- filter_list(verif_II,lead_time != "All") 
               } 
               for (ii in loop_values){
                 verif_IIII  <- filter_list(verif_III,get(filter_col) == ii)
                 c_subtitle <- paste0(subtitle_str," : ",str_to_title(filter_col)," = ",ii)
                 if (xgroup == "threshold"){
                   vlt = ii; vth = "NA"
-                } else if (xgroup == "leadtime"){
+                } else if (xgroup == "lead_time"){
                   vlt = "NA"
                   if (ii < 0){
                     vth <- paste0("m",abs(ii))
@@ -461,17 +464,17 @@ fn_plot_point_verif <- function(harp_verif_input,png_archive,plot_num_cases = TR
             if (score == "rank_histogram"){
               p_out <- fn_plot_point(verif_II,title_str,subtitle_str,fxoption_list,vroption_list)
             } else {
-              # Loop over all leadtime+threshold pairs
-              for (lt in leadtime_vals){
+              # Loop over all lead_time+threshold pairs
+              for (lt in lead_time_vals){
                 for (th in threshold_vals){
                   verif_III <- verif_II
-                  verif_III[[2]] <- filter(verif_III[[2]],leadtime == lt,threshold == th)
+                  verif_III[[2]] <- filter(verif_III[[2]],lead_time == lt,threshold == th)
                   if (th < 0){
                     vth <- paste0("m",abs(th))
                   } else {
                     vth <- th
                   }
-                  c_subtitle <- paste0(subtitle_str," : Leadtime = ",lt," : Threshold = ",th)
+                  c_subtitle <- paste0(subtitle_str," : lead_time = ",lt," : Threshold = ",th)
                   p_out <- fn_plot_point(verif_III,title_str,c_subtitle,fxoption_list,vroption_list,vlt=lt,vth=vth)
                 }
               }
@@ -535,16 +538,16 @@ fn_plot_point_verif <- function(harp_verif_input,png_archive,plot_num_cases = TR
             } # if validhour exists 
               
           # UA scores
-          } else if ((xgroup %in% c("p_leadtime","p_prof")) & (all(strsplit(score,"~")[[1]] %in% cnames)) & ("p" %in% cnames)){
+          } else if ((xgroup %in% c("p_lead_time","p_prof")) & (all(strsplit(score,"~")[[1]] %in% cnames)) & ("p" %in% cnames)){
            
-            if ((xgroup == "p_leadtime") & ("leadtime" %in% cnames)){
+            if ((xgroup == "p_lead_time") & ("lead_time" %in% cnames)){
               
               if (c_ind){
                 print(paste0("Working on xgroup: ",xgroup))
                 c_ind = FALSE
               }
               
-              vroption_list$xgroup <- "leadtime"
+              vroption_list$xgroup <- "lead_time"
               
               # Get the available pressure levels
               p_levels <- unique(verif_II[[1]][["p"]])
@@ -570,7 +573,7 @@ fn_plot_point_verif <- function(harp_verif_input,png_archive,plot_num_cases = TR
 
               } # pressure levels
               
-            } # if p_leadtime
+            } # if p_lead_time
             
             if ((xgroup == "p_prof") & ("valid_hour" %in% cnames)){
               
@@ -643,11 +646,11 @@ fn_check_verif <- function(df,verif,dfnames){
     cycles <- c("All")
     verif <- verif %>% mutate_list(fcst_cycle = "All")
   }
-  # And check what leadtimes exist
-  if ("leadtime" %in% dfnames){
-    leadtimes <- unique(df[["leadtime"]])
+  # And check what lead_times exist
+  if ("lead_time" %in% dfnames){
+    lead_times <- unique(df[["lead_time"]])
   } else {
-    leadtimes <- "NA"
+    lead_times <- "NA"
   }
   # And check what validhours exist
   if ("valid_hour" %in% dfnames){
@@ -658,7 +661,7 @@ fn_check_verif <- function(df,verif,dfnames){
   return(list("verif" = verif,
               "cycles" = cycles,
               "stations" = stations,
-              "leadtimes" = leadtimes,
+              "lead_times" = lead_times,
               "validhours" = validhours,
               "station_group_var" = station_group_var))
 }
@@ -716,7 +719,7 @@ fn_plot_map <- function(verif,title_str,subtitle_str,fxoption_list,vroption_list
                           legend.position  = "right", 
                           strip.background = element_rect(fill="white"),
                           strip.text       = element_text(size=14))+
-                    facet_wrap(vars(mname),ncol=min(num_models,3))+
+                    facet_wrap(vars(fcst_model),ncol=min(num_models,3))+
                     scale_size_continuous(range = c(0.1, 3))+ # Controls the overall point size
                     labs(title = ptitle,subtitle = subtitle_str,fill = "",size = "")+
                     guides(size="none") # Remove size label from legend
@@ -758,11 +761,11 @@ fn_plot_profile <- function(verif,title_str,subtitle_str,plot_num_cases,fxoption
   
   # Note: No member plotting considered here 
   if (num_scores == 1){
-    p_out <- df %>% ggplot(aes(y=p,color=fct_inorder(mname)))+
+    p_out <- df %>% ggplot(aes(y=p,color=fct_inorder(fcst_model)))+
       geom_path(aes(x=get(all_scores)),size=line_size)+
       geom_point(aes(x=get(all_scores)),stroke=stroke_size,size=point_size)
   } else if (num_scores == 2){
-    p_out <- df %>% ggplot(aes(y=p,color=fct_inorder(mname)))+
+    p_out <- df %>% ggplot(aes(y=p,color=fct_inorder(fcst_model)))+
       geom_path(aes(x=get(all_scores[1]),linetype=title_scores[1]),size=line_size)+
       geom_point(aes(x=get(all_scores[1])),stroke=stroke_size,size=point_size)+
       geom_path(aes(x=get(all_scores[2]),linetype=title_scores[2]),size=line_size)+
@@ -788,7 +791,7 @@ fn_plot_profile <- function(verif,title_str,subtitle_str,plot_num_cases,fxoption
   if (plot_num_cases){
     ncy    <- "num_cases"
     ylabel <- "Num. cases"
-    p_nc <- df %>% ggplot(aes(y=p,color=fct_inorder(mname)))+
+    p_nc <- df %>% ggplot(aes(y=p,color=fct_inorder(fcst_model)))+
       geom_path(aes(x=get(ncy)),size=line_size)+
       geom_point(aes(x=get(ncy)),stroke=stroke_size,size=point_size)+
       labs(y = " ",x = ylabel,color = " ",shape = " ")+ptheme_nc+
@@ -833,11 +836,11 @@ fn_sid_issue_table <- function(df,fxoption_list,vroption_list,vlt="NA",vth="NA")
   png_archive <- fxoption_list$png_archive; sdate <- fxoption_list$sdate;
   edate <- fxoption_list$edate; param <- fxoption_list$param
   
-  mnames       <- unique(df[[1]][["mname"]])
+  fcst_models       <- unique(df[[1]][["fcst_model"]])
   num_stations <- unique(df[[1]][["SID"]])
-  stns_lrmse   <- df[[1]] %>% filter(mname == mnames[1]) %>% arrange(-rmse)
+  stns_lrmse   <- df[[1]] %>% filter(fcst_model == fcst_models[1]) %>% arrange(-rmse)
   ns_val       <- min(10,num_stations) # Info for 10 stations with largest rmse
-  stns_lrmse   <- stns_lrmse[1:ns_val,] %>% select("mname","valid_hour","fcst_cycle","SID","lat","lon","rmse","num_cases")
+  stns_lrmse   <- stns_lrmse[1:ns_val,] %>% select("fcst_model","valid_hour","fcst_cycle","SID","lat","lon","rmse","num_cases")
   stns_lrmse[["rmse"]] <- round(stns_lrmse[["rmse"]],2)
   
   # Get corresponding png name
@@ -847,4 +850,4 @@ fn_sid_issue_table <- function(df,fxoption_list,vroption_list,vlt="NA",vth="NA")
   # Save as a table
   write.table(stns_lrmse,file=file.path(png_archive,tab_fname),sep=",",row.names = FALSE)
 }
-#================================================#
\ No newline at end of file
+#================================================#
diff --git a/config/config_atos.R b/config/config_atos.R
index e6eb07f..d6b0fa9 100644
--- a/config/config_atos.R
+++ b/config/config_atos.R
@@ -34,25 +34,30 @@ conf_get_params_details <- function(){
     Q_thr  <- c(seq(0, 0.15, 0.015))
     SD_thr <- c(0,1,3,6,10, seq(20, 80, 20))
     params <- list(
-    		T2m = list(
+    		MAXT2m = list(
         thresholds = T2m_thr,
-        scale_fcst = list(scale_factor = -273.15, new_units = "degC"),
-        scale_obs  = list(scale_factor = -273.15, new_units = "degC")       
+        scale_fcst = list(scaling = -273.15, new_units = "degC", mult= FALSE),
+        scale_obs  = list(scaling = -273.15, new_units = "degC", mult= FALSE)       
     			),
+                MINT2m = list(
+        thresholds = T2m_thr,
+        scale_fcst = list(scaling = -273.15, new_units = "degC", mult= FALSE),
+        scale_obs  = list(scaling = -273.15, new_units = "degC", mult= FALSE)
+                        ),		   
    		Td2m = list(
         thresholds = T2m_thr,
-        scale_fcst = list(scale_factor = -273.15, new_units = "degC"),
-        scale_obs  = list(scale_factor = -273.15, new_units = "degC")       
+        scale_fcst = list(scaling = -273.15, new_units = "degC", mult= FALSE),
+        scale_obs  = list(scaling = -273.15, new_units = "degC", mult= FALSE)       
     			),
     		Tmax = list(
         thresholds = Tmax_thr,
-        scale_fcst = list(scale_factor = -273.15, new_units = "degC"),
-       scale_obs  = list(scale_factor = -273.15, new_units = "degC")        
+        scale_fcst = list(scaling = -273.15, new_units = "degC", mult= FALSE),
+       scale_obs  = list(scaling = -273.15, new_units = "degC", mult= FALSE)        
     			),    
     	        Tmin = list(
         thresholds = Tmin_thr,
-        scale_fcst = list(scale_factor = -273.15, new_units = "degC"),
-        scale_obs  = list(scale_factor = -273.15, new_units = "degC")        
+        scale_fcst = list(scaling = -273.15, new_units = "degC", mult= FALSE),
+        scale_obs  = list(scaling = -273.15, new_units = "degC", mult= FALSE)        
     			),    
     		S10m = list(
         thresholds = S10m_thr      
@@ -88,8 +93,8 @@ conf_get_params_details <- function(){
         thresholds = SD_thr
          ),
     		T = list(
-       scale_fcst = list(scale_factor = -273.15, new_units = "degC"),
-        scale_obs  = list(scale_factor = -273.15, new_units = "degC"),
+       scale_fcst = list(scaling = -273.15, new_units = "degC", mult= FALSE),
+       scale_obs  = list(scaling = -273.15, new_units = "degC", mult= FALSE),
         vc         = "pressure"                 
     			),
                 Pcp = list (
diff --git a/config/config_atos.sh b/config/config_atos.sh
index 1b307ba..dec9536 100644
--- a/config/config_atos.sh
+++ b/config/config_atos.sh
@@ -1,7 +1,7 @@
 #/bin/bash 
 
 ## load modules 
-module load R/4.0.4
+#module load R/4.0.4
 
 CONFIG_INITIAL=config_atos
  
diff --git a/config/config_atos.yml_Spain_202205 b/config/config_atos.yml_Spain_202205
index 8903c4a..1a9cab1 100644
--- a/config/config_atos.yml_Spain_202205
+++ b/config/config_atos.yml_Spain_202205
@@ -11,7 +11,7 @@ pre:
   by_vobs_step: "1h"
   vfld_template:  #include one for each model if they are different. 
     - "vfld"
-  do_all: TRUE # if true, it will ignore list of parameters and do all that is available in the vfld files
+  do_all: FALSE # if true, it will ignore list of parameters and do all that is available in the vfld files
   params:
     - Pcp
     - AccPcp1h
@@ -44,25 +44,26 @@ pre:
 #Section to define paths for the verification
 # This section will be used by the scripts under verification
 verif:
-  by_step: "6h"
+  by_step: "24h"
+  by_obs_step: "1h"
   fcst_model:
     - AIB_43h221_de
-    - AIB_46h1_de2
     - VAL500m_46h1_de2
-  lead_time: seq(0, 48, 1)
+#    - M05B
+  lead_time: seq(0, 24, 1)
   fcst_type: "det" #det or eps
-  grps: "leadtime"
-  fcst_path: "/perm/sp3c/deode_verif/cases/Spain_202205/FCTABLE"
-  obs_path: "/perm/sp3c/deode_verif/cases/Spain_202205/OBSTABLE"
-  verif_path: "/perm/sp3c/deode_verif/cases/Spain_202205/output/verif_results"
+  grps: "lead_time"
+  fcst_path: "/perm/sp3c/deode_verif20/cases/Spain_202205d/FCTABLE"
+  obs_path: "/perm/sp3c/deode_verif20/cases/Spain_202205d/OBSTABLE"
+  verif_path: "/perm/sp3c/deode_verif20/cases/Spain_202205d/output/verif_results"
 #Section to define the paths for the output
 # This section will be used by the plotting scripts
 post:
-  plot_output: "/perm/sp3c/deode_verif/cases/Spain_202205/output"
-  rds_path: "/perm/sp3c/deode_verif/cases/Spain_202205/verif_rds"
+  plot_output: "/perm/sp3c/deode_verif20/cases/Spain_202205d/output"
+  rds_path: "/perm/sp3c/deode_verif20/cases/Spain_202205d/verif_rds"
 #This section if only for the scorecards
 scorecards:
-  ref_model: AIB_43h221_de
+  ref_model: AIB_46h1_de2
   fcst_model: VAL500m_46h1_de2
   params: 
     - T2m
@@ -84,4 +85,5 @@ scorecards:
     - Td2m                       
     - Tmax                                           
     - Tmin                                               
-    - vis  
+    - vis
+