fixed plot_acf() factor issue ModelOriented#159

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: auditor
 Title: Model Audit - Verification, Validation, and Error Analysis 
-Version: 1.3.4
+Version: 1.3.5
 Authors@R: c(
     person("Alicja", "Gosiewska", email = "[email protected]", role = c("aut", "cre"),
       comment = c(ORCID = "0000-0001-6563-5742")),
@@ -10,7 +10,8 @@ Authors@R: c(
       comment = c(ORCID = "0000-0001-6661-5364")),
     person("Tomasz", "Mikołajczyk", role =  c("aut")),
     person("Michal", "Burdukiewicz", role =  c("ctb")),
-    person("Szymon", "Maksymiuk", role =  c("ctb"))
+    person("Szymon", "Maksymiuk", role =  c("ctb")),
+    person("Michal", "Kaminski", role =  c("ctb"))
   )
 Description: Provides an easy to use unified interface for creating validation plots for any model. 
   The 'auditor' helps to avoid repetitive work consisting of writing code needed to create residual plots. 

R/plot_acf.R

@@ -51,11 +51,15 @@ plot_acf <- function(object, ..., variable = NULL, alpha = 0.95) {
   # data frame for ggplot object
   df <- make_dataframe(object, ..., variable = variable, type = "res")
 
-  result_df <- data.frame(acf = numeric(), label = character(), lag = numeric(), ymin = numeric())
-  for (label in unique(df$`_label_`)) {
+
+  result_df <- data.frame(acf = numeric(), label = factor(), lag = numeric(), ymin = numeric())
+
+  label_levels <- levels(df$`_label_`)
+
+  for (label in label_levels) {
     orderedResiduals <- df[which(df$`_label_` == label), "_residuals_"]
     acf <- acf(orderedResiduals, plot = FALSE)
-    result_df <- rbind(result_df, data.frame(acf = acf$acf[-1], label = label, lag = acf$lag[-1], ymin = 0))
+    result_df <- rbind(result_df, data.frame(acf = acf$acf[-1], label = factor(label, levels = label_levels), lag = acf$lag[-1], ymin = 0))
   }
 
   df <- result_df

tests/testthat/objects_for_tests.R

@@ -45,11 +45,13 @@ model_class_glm2 <- glm(factor(y) ~ x3, family=binomial,	data=artifficial_classi
 exp_class_glm2 <- explain(model_class_glm2, data = artifficial_classif, y = artifficial_classif$y, verbose = FALSE)
 exp_lm <- explain(model_lm, label = "lm", data = artifficial_regr, y = artifficial_regr$y, verbose = FALSE)
 exp_glm <- explain(model_glm, label = "glm", data = artifficial_classif_2, y = artifficial_classif_2$y, verbose = FALSE)
+exp_glm2 <- explain(model_glm, label = "glm2", data = artifficial_classif_2, y = artifficial_classif_2$y, verbose = FALSE)
 exp_rf <- explain(model_rf, label="rf", data =artifficial_classif_2, y = artifficial_classif_2$y, verbose = FALSE)
 exp_class_glm <- explain(model_class_glm, label="class glm", data = artifficial_classif, y = artifficial_classif$y, verbose = FALSE)
 
 mr_rf <- model_residual(exp_rf)
 mr_glm <- model_residual(exp_glm)
+mr_glm2 <- model_residual(exp_glm2)
 
 cd_lm <- model_cooksdistance(exp_lm)
 cd_rf <- model_cooksdistance(exp_rf)

tests/testthat/test_plotsR.R

@@ -7,6 +7,7 @@ test_that("plot_acf", {
   expect_is(plot_acf(mr_rf, variable = "_y_"), "gg")
   expect_is(plot_acf(mr_rf, variable = "_y_hat_"), "gg")
   expect_is(plot_acf(mr_rf), "gg")
+  expect_error(plot_acf(mr_rf, mr_glm, mr_glm2), NA)
 })
 
 test_that("plot_autocorrelation", {