Check updates Andjar into own version

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: ALASCA
 Title: Assorted, Linear ASCA Functions
-Version: 1.0.17
+Version: 1.0.19
 Authors@R: 
     person(given = "Anders H.",
            family = "Jarmund",
@@ -15,7 +15,7 @@ Encoding: UTF-8
 LazyData: true
 ByteCompile: true
 Roxygen: list(markdown = TRUE, r6 = TRUE)
-RoxygenNote: 7.1.2
+RoxygenNote: 7.3.2
 Depends:
   data.table
 Imports:

NAMESPACE

@@ -20,5 +20,6 @@ export(plot_covariate)
 export(plot_covariates)
 export(plot_mm)
 export(plot_val)
+export(predict_scores)
 export(save.AlascaModel)
 export(screeplot)

NEWS.md

@@ -1,3 +1,13 @@
+# ALASCA 1.0.19
+
+* Bug fix: The prediction plots should now work for models with separated effects too
+
+# ALASCA 1.0.18
+
+* Replacing `aes_string()` due to changes in the `ggplot2` package
+* Moved `finalize()` from public to private re changes in the `R6` package
+* Bug fix: Plots all variables instead of subset
+
 # ALASCA 1.0.17
 
 * Minor bug fix related to 1.0.16

R/AlascaModel.R

@@ -19,9 +19,9 @@ AlascaModel <- R6::R6Class("AlascaModel",
     #' @field ignore_missing_covars If TRUE, ignore missing covariate values
     ignore_missing_covars = FALSE,
     #' @field version Version number
-    version = "1.0.17",
+    version = "1.0.19",
     #' @field update_date Date of latest update
-    update_date = "2024-09-13",
+    update_date = "2026-01-16",
 
     # Effect matrices
     #' @field separate_effects If TRUE, try to separate the effects
@@ -256,15 +256,6 @@ AlascaModel <- R6::R6Class("AlascaModel",
       # Build the ALASCA model ----
       self$build_model()
     },
-    finalize = function() {
-      if (self$save_to_disk && !self$minimize_object) {
-        if (self$db_method == "SQLite") {
-          DBI::dbDisconnect(self$db_con)
-        } else {
-          DBI::dbDisconnect(self$db_con, shutdown = TRUE)
-        }
-      }
-    },
     #' @description
     #' Update the current model (used for validation)
     update = function() {
@@ -446,7 +437,7 @@ AlascaModel <- R6::R6Class("AlascaModel",
 
       if (self$equal_baseline) {
         # Must add baselines for missing interactions (baseline x group)
-        baseline_to_add <- self$model_prediction[get(self$effect_terms) %in% self$get_ref(self$effect_terms)]
+        baseline_to_add <- self$model_prediction[self$get_ref(self$effect_terms)]
 
         if (length(self$effect_terms) == 2) {
           # In this case, there are no main effects except time
@@ -844,5 +835,15 @@ AlascaModel <- R6::R6Class("AlascaModel",
       unique(unlist(self$effect_list$terms))
     }
   ),
-  private = list()
+  private = list(
+    finalize = function() {
+      if (self$save_to_disk && !self$minimize_object) {
+        if (self$db_method == "SQLite") {
+          DBI::dbDisconnect(self$db_con)
+        } else {
+          DBI::dbDisconnect(self$db_con, shutdown = TRUE)
+        }
+      }
+    }
+  )
 )

R/AlascaPlot.R

@@ -85,8 +85,7 @@ AlascaPlot <- R6::R6Class("AlascaPlot",
     #' @field type Plot type
     type = "effect",
     initialize = function(model) {
-      self$model <- model
-      self$n_limit <- min(self$n_limit / 2, floor(length(self$model$get_levels("variable")) / 2))
+      self$model   <- model
     },
     call_plot = function(...) {
       inputs <- list(...)
@@ -253,10 +252,10 @@ AlascaPlot <- R6::R6Class("AlascaPlot",
 
       if (is.null(self$loading_group_column)) {
         if (self$model$validate) {
-          g <- ggplot2::ggplot(data_to_plot, ggplot2::aes_string(x = "covar", y = "estimate", ymin = "low", ymax = "high")) +
+          g <- ggplot2::ggplot(data_to_plot, ggplot2::aes(x = .data[["covar"]], y = .data[["estimate"]], ymin = .data[["low"]], ymax = .data[["high"]])) +
             ggplot2::geom_pointrange()
         } else {
-          g <- ggplot2::ggplot(data_to_plot, ggplot2::aes_string(x = "covar", y = "estimate")) +
+          g <- ggplot2::ggplot(data_to_plot, ggplot2::aes(x = .data[["covar"]], y = .data[["estimate"]])) +
             ggplot2::geom_point()
         }
       } else {
@@ -266,16 +265,16 @@ AlascaPlot <- R6::R6Class("AlascaPlot",
         }
         if (self$model$validate) {
           if (self$black_and_white) {
-            g <- ggplot2::ggplot(data_to_plot, ggplot2::aes_string(x = "covar", y = "estimate", ymin = "low", ymax = "high", shape = "covargroup"))
+            g <- ggplot2::ggplot(data_to_plot, ggplot2::aes(x = .data[["covar"]], y = .data[["estimate"]], ymin = .data[["low"]], ymax = .data[["high"]], shape = .data[["covargroup"]]))
           } else {
-            g <- ggplot2::ggplot(data_to_plot, ggplot2::aes_string(x = "covar", y = "estimate", ymin = "low", ymax = "high", shape = "covargroup", color = "covargroup"))
+            g <- ggplot2::ggplot(data_to_plot, ggplot2::aes(x = .data[["covar"]], y = .data[["estimate"]], ymin = .data[["low"]], ymax = .data[["high"]], shape = .data[["covargroup"]], color = .data[["covargroup"]]))
           }
           g <- g + ggplot2::geom_pointrange()
         } else {
           if (self$black_and_white) {
-            g <- ggplot2::ggplot(data_to_plot, ggplot2::aes_string(x = "covar", y = "estimate", shape = "covargroup"))
+            g <- ggplot2::ggplot(data_to_plot, ggplot2::aes(x = .data[["covar"]], y = .data[["estimate"]], shape = .data[["covargroup"]]))
           } else {
-            g <- ggplot2::ggplot(data_to_plot, ggplot2::aes_string(x = "covar", y = "estimate", shape = "covargroup", color = "covargroup"))
+            g <- ggplot2::ggplot(data_to_plot, ggplot2::aes(x = .data[["covar"]], y = .data[["estimate"]], shape = .data[["covargroup"]], color = .data[["covargroup"]]))
           }
 
           g <- g + ggplot2::geom_point()