Documentation runs @examples code correctly.

IMPORTANT: examples must be written in a self-contained way
They always run from a clean workspace with no global variables.

R/Global.R

@@ -35,6 +35,7 @@ library(scales)
 #' potency estimates and respective CIs of restricted and unrestricted models, and the predictions thereof.
 #' @export
 #' @examples
+#' suppressMessages(source("../../dev/setup.R"))
 #' dat <- data.frame(
 #'   REF1 = c(1547, 1620, 1644, 2504, 3426, 3512, 3401, 3787), REF2 = c(1492, 1536, 1384, 2286, 3046, 3479, 3516, 3497),
 #'   REF3 = c(1468, 1827, 1558, 2252, 3002, 3349, 2945, 3665),
@@ -175,6 +176,7 @@ Fitting_FUNC <- function(ro_new, TransFlag = FALSE) {
 #' @returns A grid object with 2 linearity plots, restricted and unrestricted model.
 #' @export
 #' @examples
+#' suppressMessages(source("../../dev/setup.R"))
 #' data.frame(
 #'   R_dil1 = c(
 #'     10.0651024695491, 10.9844983291817, 10.7635586089293, 10.4597656321327, 10.3898668457823, 10.8171761349909,
@@ -256,6 +258,7 @@ plotSingularity <- function(dat) { # sigmoid,det_sig,
 #' @returns A grid object either of the original scale or the natural log of the readouts.
 #' @export
 #' @examples
+#' suppressMessages(source("../../dev/setup.R"))
 #' dat <- data.frame(
 #'   REF1 = c(1547, 1620, 1644, 2504, 3426, 3512, 3401, 3787), REF2 = c(1492, 1536, 1384, 2286, 3046, 3479, 3516, 3497),
 #'   REF3 = c(1468, 1827, 1558, 2252, 3002, 3349, 2945, 3665),
@@ -490,6 +493,7 @@ plot_f <- function(dat, TransFlag = FALSE) { # sigmoid,det_sig,
 #' @returns A data-frame with readouts and natural log of concentrations.
 #' @export
 #' @examples
+#' suppressMessages(source("../../dev/setup.R"))
 #' as <- 3
 #' bs <- 1
 #' cs <- -4
@@ -546,6 +550,7 @@ Calc_DilRes <- function(as = 3, bs = 1, cs = -4, ds = 10, at = 3, bt = 1, dt = 1
 #' @returns A data-frame with potency estimate, absolute CIs, test result, relative CIs.
 #' @export
 #' @examples
+#' suppressMessages(source("../../dev/setup.R"))
 #' CIRC <- data.frame(
 #'   log_dose = c(
 #'     -2.5, -2.5, -2.5, -3.2, -3.2, -3.2, -3.9, -3.9, -3.9,
@@ -632,6 +637,7 @@ LinPotTab <- function(circles, Lim, PureErrFlag) {
 #' 4) summary of restricted linear model.
 #' @export
 #' @examples
+#' suppressMessages(source("../../dev/setup.R"))
 #' dat <- data.frame(
 #'   R_dil1 = c(10221, 18258, 31993, 49336, 68332, 83527, 95584, 102229),
 #'   R_dil2 = c(10136, 19078, 31925, 49003, 68034, 83776, 95495, 101608),
@@ -854,9 +860,9 @@ ANOVAlintests <- function(ro_new, circles, Lim, PureErrFlag) {
 #' @param indT Index of dilution, where regression starts for test sample.
 #' @returns A grid object of 2 plots of unrestricted and restricted linear PLA models.
 #' @export
-#' @examples
+#' @examplesIf interactive()
-#' circle <- read.csv("~/plateflow/circle.csv")
+#' circle <- read.csv("tests/circle.csv")
-#' all_l2 <- read.csv("~/plateflow/all_l2.csv")
+#' all_l2 <- read.csv("tests/all_l2.csv")
 #' sigmoid <- c(10.0, 10.0, 110.0, 110.0, 1.0, 1.0, -3.5, 0.0)
 #' indS <- 3
 #' indT <- 3
@@ -866,7 +872,6 @@ ANOVAlintests <- function(ro_new, circles, Lim, PureErrFlag) {
 #'   plotT = c(114.213375, 97.588663, 80.963951, 64.339239, 47.714527, 31.102604, 14.477892, -2.095735)
 #' )
 #'
-#'
 #' PlotLinPLA_FUNC(circle, sigmoid, all_l2, pl_df, indS, indT)
 PlotLinPLA_FUNC <- function(circle, sigmoid, all_l2, pl_df, indS, indT) {
   # browser()
@@ -988,6 +993,7 @@ PlotLinPLA_FUNC <- function(circle, sigmoid, all_l2, pl_df, indS, indT) {
 #' 4) summary of restricted linear model.
 #' @export
 #' @examples
+#' suppressMessages(source("../../dev/setup.R"))
 #' ro_new <- data.frame(
 #'   R_dil1 = c(10221, 18258, 31993, 49336, 68332, 83527, 95584, 102229),
 #'   R_dil2 = c(10136, 19078, 31925, 49003, 68034, 83776, 95495, 101608),
@@ -1088,6 +1094,7 @@ pot4plFUNC <- function(ro_new, PureErrFlag) {
 #' @returns A data-frame with the lower and upper CI in anti-log form.
 #' @export
 #' @examples
+#' suppressMessages(source("../../dev/setup.R"))
 #' xs <- 2
 #' xt <- 3.2
 #' se_xt <- 0.34
@@ -1121,6 +1128,7 @@ ParamCI_F <- function(xt, xs, se_xt, se_xs, CoVar, DFs, Conf = 0.975) {
 #' @returns A data-frame with the lower and upper CI in anti-log form.
 #' @export
 #' @examples
+#' suppressMessages(source("../../dev/setup.R"))
 #'
 #' dat <- data.frame(
 #'   REF1 = c(1547, 1620, 1644, 2504, 3426, 3512, 3401, 3787), REF2 = c(1492, 1536, 1384, 2286, 3046, 3479, 3516, 3497),
@@ -1353,7 +1361,7 @@ tests_FUNC <- function(ro_new, Lim, PureErrFlag) {
 #' @returns A data-frame with the analysis of variance.
 #' @export
 #' @examples
-#'
+#' suppressMessages(source("../../dev/setup.R"))
 #' ro_new <- data.frame(
 #'   REF1 = c(1547, 1620, 1644, 2504, 3426, 3512, 3401, 3787), REF2 = c(1492, 1536, 1384, 2286, 3046, 3479, 3516, 3497),
 #'   REF3 = c(1468, 1827, 1558, 2252, 3002, 3349, 2945, 3665),
@@ -1445,7 +1453,8 @@ ANOVA4plUnresfunc <- function(ro_new) {
 #' @returns A data-frame with the concentrations and metadata.
 #' @export
 #' @examples
-#'
+#' suppressMessages(source("../../dev/setup.R"))
+#' 
 #' ro_new <- data.frame(
 #'   REF1 = c(1547, 1620, 1644, 2504, 3426, 3512, 3401, 3787), REF2 = c(1492, 1536, 1384, 2286, 3046, 3479, 3516, 3497),
 #'   REF3 = c(1468, 1827, 1558, 2252, 3002, 3349, 2945, 3665),
@@ -1453,7 +1462,6 @@ ANOVA4plUnresfunc <- function(ro_new) {
 #'   TEST3 = c(1399, 1376, 1588, 1475, 2148, 3083, 2942, 3466), log_dose = c(5.01, 3.401, 2.708, 2.015, 1.32176, 0.62861, -0.0645385, -1.6739764)
 #' )
 #'
-#'
 #' perConcTab(ro_new, noDilSeries = 3)
 perConcTab <- function(ro_new, noDilSeries) {
   Reftab <- ro_new[, c(1:noDilSeries)]
@@ -1489,6 +1497,7 @@ perConcTab <- function(ro_new, noDilSeries) {
 #' @returns A data-frame with the concentrations and metadata.
 #' @export
 #' @examples
+#' suppressMessages(source("../../dev/setup.R"))
 #'
 #' x <- 1
 #' Div <- 3