97_myPlot_only (#108)

Co-authored-by: 27856297+dependabot-preview[bot]@users.noreply.github.com <27856297+dependabot-preview[bot]@users.noreply.github.com>
Co-authored-by: Daniel Sabanes Bove <danielinteractive@users.noreply.github.com>

.pre-commit-config.yaml

@@ -9,6 +9,7 @@ repos:
         args: [--style_pkg=styler, --style_fun=tidyverse_style]
       - id: roxygenize
         additional_dependencies:
+          - ggplot2
           - devtools
           - shiny
           - checkmate

DESCRIPTION

@@ -22,6 +22,7 @@ BugReports: https://github.com/genentech/phase1b/issues
 Depends:
     R (>= 3.6)
 Suggests:
+    scales,
     rmarkdown,
     bookdown,
     knitr,
@@ -32,6 +33,7 @@ Suggests:
     reshape,
     testthat (>= 3.0.0)
 Imports:
+    ggplot2,
     checkmate,
     devtools,
     lifecycle

NAMESPACE

@@ -6,7 +6,6 @@ export(dbetaMix)
 export(dbetabinom)
 export(dbetabinomMix)
 export(dbetadiff)
-export(myPlot)
 export(myPlotDiff)
 export(oc2)
 export(oc3)
@@ -18,6 +17,7 @@ export(ocRctPostprobDist)
 export(ocRctPredprobDist)
 export(pbetaMix)
 export(pbetadiff)
+export(plotBeta)
 export(plotBounds)
 export(plotDecision)
 export(plotOc)

R/dbetabinom.R

@@ -80,8 +80,8 @@ dbetabinomMix <- Vectorize(dbetabinomMix, vectorize.args = "x")
 #'
 #' @keywords internal
 h_getBetamixPost <- function(x, n, par, weights) {
-  assert_numeric(x, lower = 0, upper = n, finite = TRUE)
-  assert_numeric(n, lower = 0, finite = TRUE)
+  assert_number(x, lower = 0, upper = n, finite = TRUE)
+  assert_number(n, lower = 0, finite = TRUE)
   assert_matrix(par, min.rows = 1, max.cols = 2, mode = "numeric")
   assert_numeric(weights, min.len = 0, len = nrow(par), finite = TRUE)
   # We renormalize weights.

R/plotBeta.R

@@ -2,44 +2,37 @@
 #'
 #' This function will plot the PDF of a beta distribution
 #'
-#' @param alpha first parameter of the Beta distribution
-#' @param beta second parameter of the Beta distribution
-#' @param \dots additional arguments to \code{plot}
-#' @return nothing, only produces the plot as side effect
+#' @inheritParams dbetabinom
+#' @typed alpha : number
+#'  first parameter of the Beta distribution
+#' @typed beta : number
+#'  second parameter of the Beta distribution
+#' @return A beta distribution density plot
 #'
 #' @importFrom graphics axis
 #'
-#' @example examples/myPlot.R
+#' @example examples/plotBeta.R
 #' @export
 #' @keywords graphics
-myPlot <- function(alpha, beta, ...) {
-  grid <- seq(from = 0, to = 1, length = 1000)
-  xticks <- seq(from = 0, to = 1, by = 0.25)
-
-  plot(
-    x = grid,
-    y = dbeta(grid, alpha, beta),
-    ylab = "",
-    xaxt = "n",
-    yaxt = "n",
-    type = "l",
-    xaxs = "i",
-    yaxs = "i",
-    ...
-  )
-
-  graphics::axis(
-    side = 1, at = xticks,
-    labels = paste(xticks * 100, "%", sep = "")
+plotBeta <- function(alpha, beta, ...) {
+  x_support <- seq(from = 0, to = 1, length = 1000)
+  data <- data.frame(
+    grid = x_support,
+    xticks = seq(from = 0, to = 1, by = 0.25),
+    density = dbeta(x_support, alpha, beta)
   )
+  ggplot2::ggplot(data) +
+    ggplot2::geom_line(ggplot2::aes(x = grid, y = density)) +
+    ggplot2::ggtitle(paste("Beta density with alpha =", alpha, "and beta =", beta, "parameters.")) +
+    ggplot2::xlab("response rate") +
+    ggplot2::ylab(quote(f(x))) +
+    ggplot2::theme(axis.ticks.x = ggplot2::element_line(linewidth = 0.5)) +
+    ggplot2::scale_x_continuous(labels = scales::percent_format())
 }
 
-
-
-
 #' Plot Diff Between two Beta distributions
 #'
-#' This function will plot the PDF of a diffience between two Beta distributions
+#' This function will plot the PDF of a difference between two Beta distributions
 #'
 #' @param parY non-negative parameters of the treatment Beta distribution.
 #' @param parX non-negative parameters of the historical control Beta distribution

examples/myPlotDiff.R

@@ -1 +1,8 @@
-myPlotDiff(c(5, 10), c(2, 5), 0.2, 0.05, 1, 0)
+myPlotDiff(
+  parY = c(5, 10),
+  parX = c(2, 5),
+  cut_B = 0.2, # a meaningful improvement threshold
+  cut_W = 0.05, # a poor improvement threshold
+  shade = 1, # paint the two areas under the curve, default: yes. other numbers stands for "no";
+  note = 0
+) # show values of the colored area, default: yes. other numbers stands for "no";

examples/plotBeta.R

@@ -0,0 +1,2 @@
+plotBeta(alpha = 4, beta = 5)
+plotBeta(alpha = 1, beta = 1)

tests/testthat/test-plotBeta.R

@@ -0,0 +1,9 @@
+# plotBetaDist ----
+test_that("plotBeta gives a correct result", {
+  result <- plotBeta(alpha = 4, beta = 5)
+  expect_equal(length(result$data$grid), 1000)
+  expect_numeric(result$data$grid)
+  expect_numeric(result$data$xticks)
+  expect_numeric(result$data$density)
+  expect_identical(result$labels$title, "Beta density with alpha = 4 and beta = 5 parameters.")
+})

tests/testthat/test-predprob.R

@@ -34,7 +34,7 @@ test_that("predprob gives an error when x is a numeric", {
     p = 0.6,
     thetaT = 0.9,
     parE = c(0.6, 0.4)
-  ), "is not a multiple of replacement length")
+  ), "Must have length 1")
 })
 
 test_that("predprob gives an error when K columns of weights exceed rows parE", {

vignettes/introduction.Rmd

@@ -143,6 +143,7 @@ The first time you use `phase1b` on your own computer you will need to download
 and install it, however, subsequent use will only require calling of the R-package.
 ```{r install-phase1b, eval=FALSE}
 install.packages("phase1b")
+install.packages("ggplot2")
 ```
 
 # Getting started {#getting-started}
@@ -153,6 +154,7 @@ following the instructions in the [Installation section](#installation) with the
 following command:
 ```{r load}
 library(phase1b)
+library(ggplot2)
 ```
 Once loaded, you will have access to all of the functions in the `phase1b`
 R-package. To see a list of all of the functions in the `phase1b` R-package,
@@ -644,9 +646,8 @@ a PET-CR rate of 68.75%, then our posterior updating based on the prior distribu
 observed data would lead to a $\text{Beta}(60.75,29.25)$ posterior distribution for the
 novel combination PET-CR rate.
 
-
-Alternatively, we could use the R-package function `myPlot()` to achieve the
-same result, see Figure~\@ref(fig:ex1-prior_myPlot).
+Alternatively, we could use the R-package function `plotBeta()` to achieve the
+same result, see Figure~\@ref(fig:ex1-prior_plotBeta1) and Figure~\@ref(fig:ex1-prior_plotBeta2).
 
 ```{r, echo = FALSE}
 ex1_prior_myplot_cap <- paste(
@@ -655,18 +656,24 @@ ex1_prior_myplot_cap <- paste(
   "control, and a $\text{Beta}(5.75,4.25)$ prior is used for the novel",
   "combination treatment group."
 )
+ex1_prior_myplot_cap <- paste(
+  "The prior distributions for the historical control and novel combination",
+  "treatment group. A $\text{Beta}(75,75)$ prior is used for the historical",
+  "control, and a $\text{Beta}(5.75,4.25)$ prior is used for the novel",
+  "combination treatment group."
+)
 ```
 
-```{r ex1-prior_myPlot, echo=TRUE, fig.cap = ex1_prior_myplot_cap}
-myPlot(75, 75, col = "darkgrey", ylim = c(0, 10), xlab = "PET-CR Rate", lwd = 2)
-par(new = TRUE)
-myPlot(5.75, 4.25, col = "deepskyblue", ylim = c(0, 10), lwd = 2, xlab = "")
-legend("topright", c("Hist. Control", "Novel Combo"),
-  lwd = 2, lty = 1,
-  col = c("darkgrey", "deepskyblue"), bty = "n"
-)
+```{r ex1_prior_plotBeta, echo=TRUE, fig.cap = ex1_prior_myplot_cap}
+plotBeta(alpha = 75, beta = 75, col = "darkgrey", ylim = c(0, 10), xlab = "PET-CR Rate", lwd = 2)
 ```
 
+For the Novel combination, the following posterior has been updated.
+```{r ex1_prior_plotBeta2, fig.cap = ex1_prior_myplot_cap}
+plotBeta(5.75, 4.25, col = "deepskyblue", ylim = c(0, 10), lwd = 2, xlab = "")
+```
+
+
 The following code allows the reader to visualize
 the posterior distribution for the PET-CR rate against the posterior distribution of
 the historical control.
@@ -763,7 +770,7 @@ results <- ocPostprob(
   tL = 0.6,
   tU = 0.8,
   parE = c(1, 1),
-  sim = 10000,
+  sim = 100,
   wiggle = FALSE,
   nnF = c(10, 20, 30)
 )