Increase test coverage

DESCRIPTION

@@ -57,8 +57,9 @@ Config/Needs/verdepcheck: tidyverse/dplyr, mllg/checkmate,
     yihui/knitr, insightsengineering/nestcolor, rstudio/rmarkdown,
     r-lib/testthat, tidyverse/tidyr
 Config/Needs/website: insightsengineering/nesttemplate
+Config/testthat/edition: 3
 Encoding: UTF-8
 Language: en-US
 LazyData: true
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.2
+Config/roxygen2/version: 8.1.1

NAMESPACE

@@ -11,7 +11,9 @@ import(dplyr)
 import(mcr)
 importFrom(ggplot2,ggplot)
 importFrom(magrittr,extract2)
-importFrom(rlang,"!!")
-importFrom(rlang,":=")
-importFrom(rlang,.data)
+importFrom(rlang,
+  "!!",
+  ":=",
+  .data
+)
 importFrom(utils,getFromNamespace)

NEWS.md

@@ -1,6 +1,8 @@
 # goshawk 0.1.19.9001
 
 * `g_scatterplot` was hard deprecated (#267).
+* Code coverage has increased to over 90% (#268).
+* Updated links to teal for the new location (#268).
 
 # goshawk 0.1.19
 

R/g_boxplot.R

@@ -156,7 +156,7 @@
   checkmate::assert_numeric(ylim, len = 2)
 
   # filter input data
   data <- data %>%
     filter(!!sym(param_var) == biomarker)
 
   if (!is.null(unit)) {
@@ -166,12 +166,12 @@
     }
     # extract the most common unit
     # if there are ties, take the use alphabetic order
     tmp_unit <- data %>%
       count(!!sym(unit)) %>%
       top_n(1, n) %>%
       arrange(!!sym(unit)) %>%
       slice(1) %>%
       select(!!sym(unit)) %>%
       as.character()
     if (is.factor(data[[unit]])) {
       unit <- levels(data[[unit]])[as.numeric(tmp_unit)]
@@ -217,7 +217,7 @@
     if (length(x) == 0) {
       return(FALSE)
     }
     return(is.finite(x))
   }
 
   plot1 <- plot1 +
@@ -281,8 +281,6 @@
   }
 
 
-
-
   # Format font size
   if (is_finite(font_size)) {
     plot1 <- plot1 +

R/g_correlationplot.R

@@ -262,19 +262,19 @@
   t_param_var_y <- paste("PARAM", yaxis_param, sep = "_")
   t_lbstresc_var_y <- paste("LBSTRESC", yaxis_param, sep = "_")
 
   xaxis_param_loqs_data <- data %>%
     mutate(
       PARAM = !!sym(t_param_var_x), LBSTRESC = !!sym(t_lbstresc_var_x),
       sym(loq_flag_var) == !!sym(loq_flag_var)
     ) %>%
-    select("PARAM", "LBSTRESC", loq_flag_var)
+    select("PARAM", "LBSTRESC", all_of(loq_flag_var))
 
   yaxis_param_loqs_data <- data %>%
     mutate(
       PARAM = !!sym(t_param_var_y), LBSTRESC = !!sym(t_lbstresc_var_y),
       sym(loq_flag_var) == !!sym(loq_flag_var)
     ) %>%
-    select("PARAM", "LBSTRESC", loq_flag_var)
+    select("PARAM", "LBSTRESC", all_of(loq_flag_var))
 
   # add footnote to identify xaxis assay LLOQ and ULOQ values pulled from data
   caption_loqs_label_x <- h_caption_loqs_label(loqs_data = xaxis_param_loqs_data, flag_var = loq_flag_var)
@@ -345,24 +345,26 @@
         stats::cor(!!sym(yvar), !!sym(xvar), method = "spearman", use = "complete.obs"),
         NA
       ))
+    # To avoid Note: no visible binding for global variable
+    corr <- intercept <- NULL
     plot1 <- plot1 +
       ggplot2::geom_abline(
         data = filter(sub_data, row_number() == 1), # only need to return 1 row within group_by
         ggplot2::aes(intercept = .data$intercept, slope = .data$slope, color = !!sym(trt_group))
       ) +
       ggplot2::geom_text(
         data = filter(sub_data, row_number() == 1),
-        ggplot2::aes_(
+        ggplot2::aes(
           x = -Inf,
           y = Inf,
           hjust = 0,
           vjust = 1,
-          label = ~ ifelse(
+          label = ifelse(
             !is.na(intercept) & !is.na(slope) & !is.na(corr),
             sprintf("y = %.2f+%.2fX\ncor = %.2f", intercept, slope, corr),
-            paste0("Insufficient Data For Regression")
+            "Insufficient Data For Regression"
           ),
-          color = sym(trt_group)
+          color = !!trt_group
         ),
         size = reg_text_size,
         show.legend = FALSE

R/g_lineplot.R

@@ -607,6 +607,6 @@ unique_name <- function(newname, old_names) {
 }
 
 gg_color_hue <- function(n) {
-  hues <- seq(15, 375, length = n + 1)
+  hues <- seq(15, 375, length.out = n + 1)
   grDevices::hcl(h = hues, l = 65, c = 100)[1:n]
 }

README.md

@@ -20,7 +20,7 @@
 
 Longitudinal biomarker/lab visualizations functions. These can be used stand alone but are also called by the
 [teal.goshawk](https://insightsengineering.github.io/teal.goshawk/) package which provides modules to be used
-inside [`teal`](https://insightsengineering.github.io/teal/) applications.
+inside [`teal`](https://pharmaverse.github.io/teal/) applications.
 
 ## Functions
 <!-- markdownlint-disable MD007 MD030 -->
@@ -43,17 +43,3 @@ pak::pkg_install("insightsengineering/goshawk@*release")
 # install.packages("pak")
 pak::pkg_install("insightsengineering/goshawk")
 ```
-
-## Stargazers and Forkers
-
-### Stargazers over time
-
-[![Stargazers over time](https://starchart.cc/insightsengineering/goshawk.svg)](https://starchart.cc/insightsengineering/goshawk)
-
-### Stargazers
-
-[![Stargazers repo roster for @insightsengineering/goshawk](https://reporoster.com/stars/insightsengineering/goshawk)](https://github.com/insightsengineering/goshawk/stargazers)
-
-### Forkers
-
-[![Forkers repo roster for @insightsengineering/goshawk](https://reporoster.com/forks/insightsengineering/goshawk)](https://github.com/insightsengineering/goshawk/network/members)

tests/testthat.R

@@ -0,0 +1,6 @@
+# testthat is a suggested package: only run the tests when it is available.
+if (requireNamespace("testthat", quietly = TRUE)) {
+  library(testthat)
+  library(goshawk)
+  test_check("goshawk")
+}

tests/testthat/helper-data.R

@@ -0,0 +1,91 @@
+# Deterministic, self-contained lab data (ADaM-like) used by all tests.
+# 12 subjects (4 per arm), 3 visits, 2 parameters (CRP, ALT).
+make_adlb <- function() {
+  arms <- c("A: Drug X", "B: Placebo", "C: Combination")
+  subj <- data.frame(
+    USUBJID = sprintf("S-%02d", 1:12),
+    ARM = rep(arms, each = 4),
+    SEX = rep(c("F", "M"), 6),
+    stringsAsFactors = FALSE
+  )
+  visits <- data.frame(
+    AVISITCD = c("BL", "W 1", "W 5"),
+    AVISITCDN = c(0, 1, 5),
+    stringsAsFactors = FALSE
+  )
+  params <- data.frame(
+    PARAMCD = c("CRP", "ALT"),
+    PARAM = c("C-reactive protein", "Alanine transaminase"),
+    AVALU = c("mg/L", "U/L"),
+    ANRLO = c(0.5, 20),
+    ANRHI = c(1.5, 60),
+    stringsAsFactors = FALSE
+  )
+  dat <- merge(merge(subj, visits, by = NULL), params, by = NULL)
+  dat <- dat[order(dat$PARAMCD, dat$USUBJID, dat$AVISITCDN), ]
+  rownames(dat) <- NULL
+
+  idx <- seq_len(nrow(dat))
+  scale_p <- ifelse(dat$PARAMCD == "CRP", 1, 40)
+  dat$AVAL <- round(scale_p * (0.6 + 0.05 * (idx %% 7) + 0.1 * dat$AVISITCDN + 0.02 * sin(idx)), 3)
+  dat$BASE <- round(scale_p * (0.7 + 0.04 * (idx %% 5) + 0.03 * cos(idx)), 3)
+  dat$STUDYID <- "STUDY-1"
+  dat$ARMCD <- c("A", "B", "C")[match(dat$ARM, arms)]
+  dat$TRTORD <- match(dat$ARM, arms)
+  dat$LBSTRESC <- as.character(dat$AVAL)
+  dat$LOQFL <- "N"
+
+  # one lower and one upper limit of quantification per parameter
+  lloq <- dat$USUBJID == "S-01" & dat$AVISITCD == "BL"
+  uloq <- dat$USUBJID == "S-02" & dat$AVISITCD == "W 1"
+  dat$LBSTRESC[lloq & dat$PARAMCD == "CRP"] <- "< 0.5"
+  dat$LBSTRESC[uloq & dat$PARAMCD == "CRP"] <- "> 1.5"
+  dat$LBSTRESC[lloq & dat$PARAMCD == "ALT"] <- "< 20"
+  dat$LBSTRESC[uloq & dat$PARAMCD == "ALT"] <- "> 60"
+  dat$LOQFL[lloq | uloq] <- "Y"
+
+  # one missing CRP result: S-03 at W 5
+  dat$AVAL[dat$USUBJID == "S-03" & dat$AVISITCD == "W 5" & dat$PARAMCD == "CRP"] <- NA_real_
+
+  dat$ARM <- factor(dat$ARM, levels = arms)
+  attr(dat$ARM, "label") <- "Description of Planned Arm"
+  dat$SEX <- factor(dat$SEX)
+  attr(dat$ANRLO, "label") <- "Analysis Normal Range Lower Limit"
+  attr(dat$ANRHI, "label") <- "Analysis Normal Range Upper Limit"
+
+  loqs <- goshawk:::h_identify_loq_values(dat, "LOQFL")
+  dat <- merge(dat, loqs, by = "PARAM", sort = FALSE)
+  dat <- dat[order(dat$PARAMCD, dat$USUBJID, dat$AVISITCDN), ]
+  rownames(dat) <- NULL
+  dat
+}
+
+arm_colors <- c(
+  "A: Drug X" = "#000000",
+  "B: Placebo" = "#3498DB",
+  "C: Combination" = "#E74C3C"
+)
+
+# Wide-format data for g_correlationplot: one row per subject and visit.
+make_corr_data <- function() {
+  adlb <- make_adlb()
+  crp <- adlb[adlb$PARAMCD == "CRP", ]
+  alt <- adlb[adlb$PARAMCD == "ALT", ]
+  key <- c("USUBJID", "AVISITCD")
+  dat <- merge(
+    crp[, c(key, "ARM", "AVAL", "LBSTRESC", "PARAM", "LOQFL", "ANRHI", "ANRLO", "ULOQN", "LLOQN")],
+    alt[, c(key, "BASE", "LBSTRESC", "PARAM", "LOQFL", "ANRHI", "ANRLO", "ULOQN", "LLOQN")],
+    by = key,
+    suffixes = c(".CRP", ".ALT")
+  )
+  names(dat)[names(dat) == "LBSTRESC.CRP"] <- "LBSTRESC_CRP"
+  names(dat)[names(dat) == "LBSTRESC.ALT"] <- "LBSTRESC_ALT"
+  names(dat)[names(dat) == "PARAM.CRP"] <- "PARAM_CRP"
+  names(dat)[names(dat) == "PARAM.ALT"] <- "PARAM_ALT"
+  dat$LOQFL_COMB <- ifelse(dat$LOQFL.CRP == "Y" | dat$LOQFL.ALT == "Y", "Y", "N")
+  dat <- dat[!is.na(dat$AVAL) & !is.na(dat$BASE), ]
+  dat$ARM <- factor(dat$ARM, levels = levels(adlb$ARM))
+  attr(dat$ARM, "label") <- "Description of Planned Arm"
+  rownames(dat) <- NULL
+  dat
+}