Merge branch 'refactor/i43-tidy-eval' into dev

Author: andybeet

DESCRIPTION

@@ -20,8 +20,7 @@ Authors@R:
            role = c("aut"),
            email = "Robert.Gamble@noaa.gov"),
     person(given = "Ryan",family = "Morse", role = c("aut"),
-           email = "ryan.morse@noaa.gov",
-           comment = c(ORCID = "YOUR-ORCID-ID")))
+           email = "ryan.morse@noaa.gov"))
 Description: Atlantis diagnostics functions in this package are used to determine whether the model 
     is meeting defined performance and review criteria. Processing functions are used to format the model output for 
     plotting and diagnostic tests

R/helperfiles.r

@@ -47,14 +47,8 @@ plot_sp <- function(data, col, wrap_col) {
       data[[col]],
       levels = agg_data[[1]][order(agg_data$sum_diet, decreasing = TRUE)]
     )
-    plot <- ggplot2::ggplot(
-      data,
-      ggplot2::aes_(
-        x = ~time,
-        y = ~atoutput,
-        fill = lazyeval::interp(~var, var = as.name(col))
-      )
-    ) +
+    plot <- ggplot2::ggplot(data) +
+      ggplot2::aes(x = time, y = atoutput, fill = .data[[col]]) +
       ggplot2::geom_bar(stat = "identity") +
       ggplot2::scale_fill_manual(
         values = c(

R/load_nc_temp.R

@@ -2,7 +2,7 @@
 #'
 #'@noRd
 
-load_nc_temp = function(
+load_nc_temp <- function(
   nc,
   fgs,
   bps,
@@ -129,7 +129,8 @@ load_nc_temp = function(
   }
   at_data <- list()
   if (report) {
-    pb <- dplyr::progress_estimated(length(search_clean))
+    message("working on loading stuff in nc file")
+    #    pb <- dplyr::progress_estimated(length(search_clean))
   }
   for (i in seq_along(search_clean)) {
     at_data[[i]] <- RNetCDF::var.get.nc(
@@ -367,13 +368,8 @@ load_nc_temp = function(
     result <- result[!min_pools, ]
   }
   if (select_variable == "N" & any(final_agecl == 2)) {
-    # old
-    # result <- result %>%
-    #   dplyr::group_by_("species", "polygon","layer", "time") %>%
-    #   dplyr::summarise_(atoutput = ~sum(atoutput)) %>%
-    #   dplyr::ungroup()
     result <- result %>%
-      dplyr::group_by_("species", "polygon", "layer", "time") %>%
+      dplyr::group_by(species, polygon, layer, time) %>%
       dplyr::summarise(atoutput = sum(atoutput), .groups = "drop")
   }
   if (nrow(result) == 0) {

R/make_atlantis_diagnostic_figures.R

@@ -1306,8 +1306,8 @@ make_atlantis_diagnostic_figures = function(
         grobs[[i]] <- vector("list", length = 2)
       }
       for (i in seq_along(species)) {
-        df_pred <- dplyr::filter_(pred_comb, ~ pred == species[i])
-        df_prey <- dplyr::filter_(prey_comb, ~ prey == species[i])
+        df_pred <- dplyr::filter(pred_comb, pred == species[i])
+        df_prey <- dplyr::filter(prey_comb, prey == species[i])
         grobs[[i]][[1]] <- plot_sp(df_pred, col = "prey", wrap_col = wrap_col)
         grobs[[i]][[2]] <- plot_sp(df_prey, col = "pred", wrap_col = wrap_col)
       }

R/process_atl_output.R

@@ -427,7 +427,7 @@ process_atl_output = function(
     sp.overlap = list()
     biomass.box.invert = list()
     length.age = list()
-
+    message("Reading in 'Nums', 'StructN', 'ResN', 'N'")
     if (large.file == F) {
       vars = list('Nums', 'StructN', 'ResN', 'N')
       group.types = list(groups.age, groups.age, groups.age, groups.bp)
@@ -979,6 +979,7 @@ process_atl_output = function(
     growth.rel.init = list()
     bio.consumed = list()
 
+    message("Reading in 'Eat', 'Grazing', 'Growth'")
     if (large.file == F) {
       vars = list('Eat', 'Grazing', 'Growth')
       group.types = list(groups.age, groups.bp, groups.age)
@@ -1014,28 +1015,20 @@ process_atl_output = function(
         consumed_bio = data_eat %>%
           dplyr::filter(species == pred.names[i]) %>%
           dplyr::left_join(boxvol, by = c('polygon', 'time')) %>%
-          dplyr::mutate_(
-            .dots = stats::setNames(list(~ atoutput * vol), "atoutput")
-          ) %>%
-          dplyr::mutate_(
-            .dots = stats::setNames(list(~ atoutput * bio.conv), "atoutput")
-          ) %>%
+          dplyr::mutate(atoutput = atoutput * vol) %>%
+          dplyr::mutate(atoutput = atoutput * bio.conv) %>%
           dplyr::full_join(
             dplyr::filter(data.dietcheck, pred == pred.names[i]),
             by = c(species = "pred", "time", "agecl")
           ) %>%
-          dplyr::filter_(~ time %in% ts_eat) %>%
-          dplyr::rename_(.dots = c(pred = "species"))
+          dplyr::filter(time %in% ts_eat) %>%
+          dplyr::rename(pred = species)
         bio.consumed[[i]] = consumed_bio %>%
-          dplyr::filter_(~ !is.na(atoutput.x)) %>%
-          dplyr::filter_(~ !is.na(atoutput.y)) %>%
-          dplyr::mutate_(
-            .dots = stats::setNames(list(~ atoutput.x * atoutput.y), "atoutput")
-          ) %>%
-          dplyr::select_(
-            .dots = names(.)[
-              !names(.) %in% c("atoutput.x", "vol", "atoutput.y")
-            ]
+          dplyr::filter(!is.na(atoutput.x)) %>%
+          dplyr::filter(!is.na(atoutput.y)) %>%
+          dplyr::mutate(atoutput = atoutput.x * atoutput.y) %>%
+          dplyr::select(
+            !dplyr::any_of(c("atoutput.x", "vol", "atoutput.y"))
           ) %>%
           dplyr::ungroup()
 
@@ -1203,7 +1196,7 @@ process_atl_output = function(
   }
 
   # Do catch -------------------------------------------------------------------
-
+  message("Reading Catch")
   if (plot.catch | plot.spatial.catch | process.all | plot.all) {
     catch = atlantistools::load_nc(
       param.ls$catch,