Merge pull request #25 from nlmixr2/ggplot2-fix

Work with updated ggplot2, and speed up testing
nlmixr2 · Nov 28, 2022 · 85b40df · 85b40df
2 parents 70c52cb + 8463fb8
commit 85b40df
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Showing 5 changed files with 38 additions and 26 deletions.
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -21,7 +21,7 @@ URL: https://github.com/nlmixr2/nlmixr2plot,
     https://nlmixr2.github.io/nlmixr2plot/
 BugReports: https://github.com/nlmixr2/nlmixr2plot/issues/
 Imports:
-    ggplot2,
+    ggplot2 (>= 3.4.0),
     nlmixr2est,
     nlmixr2extra,
     rxode2,

diff --git a/NEWS.md b/NEWS.md
@@ -5,6 +5,7 @@
   could use those names as the basis of figure captions (fix #8).
 * Models without eta values (between subject variability) now have more
   consistent plotting to models with eta values (fix #18).
+* The package was updated to align with changes in ggplot2.
 
 # nlmixr2plot 2.0.7
 

diff --git a/R/plot.nlmixr2.R b/R/plot.nlmixr2.R
@@ -69,7 +69,7 @@
   }
   ggplot2::ggplot(dataPlot, .aes) +
     ggplot2::facet_wrap(~ind) +
-    ggplot2::geom_abline(slope = 1, intercept = 0, col = "red", size = 1.2) +
+    ggplot2::geom_abline(slope = 1, intercept = 0, col = "red", linewidth = 1.2) +
     .logx +
     .logy +
     ggplot2::geom_point(alpha = 0.5) +
@@ -271,9 +271,9 @@ plotCmt <- function(x, cmt) {
 
       .pIndividual <- ggplot2::ggplot(.d1, ggplot2::aes(x = .data$TIME, y = .data$DV)) +
         ggplot2::geom_point() +
-        ggplot2::geom_line(ggplot2::aes(x = .data$TIME, y = .data$IPRED), col = "red", size = 1.2)
+        ggplot2::geom_line(ggplot2::aes(x = .data$TIME, y = .data$IPRED), col = "red", linewidth = 1.2)
       if (any(names(.d1) == "PRED")) {
-        .pIndividual <- .pIndividual + ggplot2::geom_line(ggplot2::aes(x = .data$TIME, y = .data$PRED), col = "blue", size = 1.2)
+        .pIndividual <- .pIndividual + ggplot2::geom_line(ggplot2::aes(x = .data$TIME, y = .data$PRED), col = "blue", linewidth = 1.2)
       }
       .pIndividual <- .pIndividual + ggplot2::facet_wrap(~ID) +
         ggplot2::ggtitle(cmt, sprintf("Individual Plots (%s of %s)", .j, length(.s))) +
@@ -374,7 +374,7 @@ traceplot.nlmixr2FitCore <- function(x, ...) {
     if (!is.null(.niter)) {
       .p0 <-
         .p0 +
-        ggplot2::geom_vline(xintercept = .niter, col = "blue", size = 1.2)
+        ggplot2::geom_vline(xintercept = .niter, col = "blue", linewidth = 1.2)
     }
     .p0 <- .p0 + rxode2::rxTheme()
     return(.p0)

diff --git a/R/plot.nlmixr2AugPred.R b/R/plot.nlmixr2AugPred.R
@@ -71,7 +71,7 @@ plot.nlmixr2AugPred <- function(x, y, ...) {
       dpred <- d1[d1$ind != "Observed", ]
       p3 <-
         ggplot2::ggplot(d1, ggplot2::aes(.data$time, .data$values, col = .data$ind)) +
-        ggplot2::geom_line(data = dpred, size = 1.2) +
+        ggplot2::geom_line(data = dpred, linewidth = 1.2) +
         ggplot2::geom_point(data = dobs) +
         ggplot2::facet_wrap(~id) +
         rxode2::rxTheme() +

diff --git a/tests/testthat/test-plots-cens.R b/tests/testthat/test-plots-cens.R
@@ -1,23 +1,27 @@
 test_that("plot censoring", {
   skip_on_cran()
 
-  dat <- xgxr::case1_pkpd |>
+  dat <-
+    xgxr::case1_pkpd |>
     dplyr::rename(DV=LIDV) |>
     dplyr::filter(CMT %in% 1:2) |>
     dplyr::filter(TRTACT != "Placebo")
 
   doses <- unique(dat$DOSE)
   nid <- 10 # 7 ids per dose group
-  dat2 <- do.call("rbind",
-                  lapply(doses, function(x) {
-                    ids <- dat |>
-                      dplyr::filter(DOSE == x) |>
-                      dplyr::summarize(ids=unique(ID)) |>
-                      dplyr::pull()
-                    ids <- ids[seq(1, nid)]
-                    dat |>
-                      dplyr::filter(ID %in% ids)
-                  }))
+  dat2 <-
+    do.call(
+      "rbind",
+      lapply(doses, function(x) {
+        ids <- dat |>
+          dplyr::filter(DOSE == x) |>
+          dplyr::summarize(ids=unique(ID)) |>
+          dplyr::pull()
+        ids <- ids[seq(1, nid)]
+        dat |>
+          dplyr::filter(ID %in% ids)
+      })
+    )
 
   ## Use 2 compartment model
   cmt2 <- function() {
@@ -44,19 +48,26 @@ test_that("plot censoring", {
   }
 
   ## Check parsing
-  cmt2m <- nlmixr2est::nlmixr(cmt2)
+  suppressMessages(
+    cmt2m <- nlmixr2est::nlmixr(cmt2)
+  )
 
-  fit <-
-    nlmixr2est::nlmixr(
-      cmt2m, dat2, "saem",
-      control=list(print=0),
-      table=nlmixr2est::tableControl(cwres=TRUE, npde=TRUE)
-    )
+  suppressMessages(
+    fit <-
+      nlmixr2est::nlmixr(
+        cmt2m, dat2, "saem",
+        control=nlmixr2est::saemControl(print=0, nBurn = 10, nEm = 20),
+        table=nlmixr2est::tableControl(cwres=TRUE, npde=TRUE)
+      )
+  )
 
   apo <- nlmixr2est::augPred(fit)
   expect_error(plot(apo), NA)
-  expect_error(vpcPlot(fit, stratify="DOSE"), NA)
-  expect_error(vpcPlot(fit, pred_corr=TRUE, stratify="DOSE", log_y=TRUE), NA)
+  expect_error(vpcPlot(fit, stratify="DOSE", n = 10), NA)
+  expect_message(
+    vpcPlot(fit, pred_corr=TRUE, stratify="DOSE", log_y=TRUE, n = 10),
+    regexp = "Prediction-correction cannot be used together with censored data"
+  )
 
   expect_error(plot(fit), NA)