context("Visualize clinical data with a scatterplot") library(plotly) library(grDevices) test_that("A scatterplot is correctly created", { data <- data.frame( USUBJID = as.character(seq.int(5)), LBSTRESN = c(39, 93, 10, 31, 13), LBSTRESNBL = c(10, 12, 13, 14, 9), stringsAsFactors = FALSE ) pl <- scatterplotClinData( data = data, xVar = "LBSTRESNBL", xLab = "Actual value at baseline", yVar = "LBSTRESN", yLab = "Actual value at visit X", aesPointVar = list( color = "USUBJID", fill = "USUBJID", group = "USUBJID", stroke = "USUBJID", shape = "USUBJID", alpha = "LBSTRESNBL", size = "LBSTRESNBL" ), aesLineVar = c( list( group = "USUBJID", #color = "USUBJID", alpha = "LBSTRESNBL", linetype = "USUBJID" ), setNames( list("LBSTRESNBL"), ifelse(packageVersion("ggplot2") >= "3.4.0", "linewidth", "size") ) ), idVar = "USUBJID" ) ## check input == output data # extract input data cols <- c("LBSTRESNBL", "LBSTRESN", "USUBJID") dataPointLine <- data[, cols] dataPointLine <- dataPointLine[do.call(order, dataPointLine), ] dataPointLine <- subset(dataPointLine, ! is.na(LBSTRESNBL)) # check data points plData <- plotly_build(pl)$x$data plDataPointsAll <- plData[sapply(plData, function(x) (x$mode == "markers" & !is.null(x$set)))] plDataPoints <- lapply(plDataPointsAll, function(x) data.frame( x = as.numeric(x$x), y = as.numeric(x$y), key = as.character(x$key), stringsAsFactors = FALSE ) ) plDataPoints <- setNames(do.call(rbind, plDataPoints), cols) plDataPoints <- plDataPoints[do.call(order, plDataPoints), ] expect_equal( object = plDataPoints, expected = dataPointLine, check.attributes = FALSE )# all equal, no attributes # check data lines plDataLinesAll <- plData[sapply(plData, function(x) (x$mode == "lines" & !is.null(x$set)))] plDataLines <- lapply(plDataLinesAll, function(x) data.frame( x = as.numeric(x$x), y = as.numeric(x$y), legend = sub("^\\(([^,]*).+", "\\1", x$legendgroup), stringsAsFactors = FALSE ) ) plDataLines <- setNames(do.call(rbind, plDataLines), cols) plDataLines <- plDataLines[do.call(order, plDataLines), ] expect_equal( object = plDataLines, expected = dataPointLine, check.attributes = FALSE )# all equal, no attributes }) test_that('Point parameters are set correctly in a scatterplot', { pl <- scatterplotClinData( data = exampleDataScatter(), xVar = "time", yVar = "response", pointPars = list( color = 'red'), idVar = "subj" ) plData <- plotly_build(pl)$x$data plmarkerData <- plData[[ which( sapply(plData, function(x){ x$mode == 'markers'} ) ) ]] # test color parameter correclty colorRGB <- sub("^rgba\\((\\d{1,},\\d{1,},\\d{1,}),.+", "\\1\\2\\3", plmarkerData$marker$line$color) expect_setequal( object = colorRGB, expected = paste(grDevices::col2rgb('red'), collapse =",") ) }) test_that("Point parameters with 'colour' (UK English spelling) are set correctly in a scatterplot", { expect_silent( pl <- scatterplotClinData( data = exampleDataScatter(), xVar = "time", yVar = "response", pointPars = list(colour = 'red'), idVar = "subj" ) ) plData <- plotly_build(pl)$x$data plmarkerData <- plData[[which(sapply(plData, function(x){x$mode == 'markers'}))]] colorRGB <- sub("^rgba\\((\\d{1,},\\d{1,},\\d{1,}),.+", "\\1\\2\\3", plmarkerData$marker$line$color) expect_equal( object = colorRGB, expected = paste(grDevices::col2rgb('red'), collapse = ",") ) }) test_that('Line parameters are set correctly in a scatterplot', { pl <- scatterplotClinData( data = exampleDataScatter(), xVar = "time", yVar = "response", aesPointVar = list(color = "treat"), aesLineVar = list(group = 'subj'), linePars = list(linetype='dotted'), idVar = "subj" ) plData <- plotly_build(pl)$x$data pllineData <- plData[[ which( sapply(plData, function(x){ x$mode == 'lines'} ) ) ]] expect_equal(pllineData$line$dash , 'dot') }) test_that("Smoothing variables are set correctly in a scatterplot", { exampleData <- exampleDataScatter() plSmoothLayer <- scatterplotClinData( data = exampleData, xVar = "time", yVar = "response", aesSmoothVar = list(group = 'subj'), idVar = "subj", smoothPars = list(se=FALSE) ) plSmoothData <- plotly_build(plSmoothLayer)$x$data plNoSmooth <- scatterplotClinData( data = exampleData, xVar = "time", yVar = "response", idVar = "subj") plNoSmoothData <- plotly_build(plNoSmooth)$x$data # test smoothing line added for each subject lineData <- plSmoothData[[which(sapply(plSmoothData, `[[`, "mode") == "lines")]] lineKeys <- unique(unlist(lineData$key)) lineKeys <- lineKeys[!is.na(lineKeys)] expect_equal( object = lineKeys, expected = unique(exampleData$subj) ) }) test_that("Smoothing parameters are set correctly in a scatterplot", { exampleData <- exampleDataScatter() plSmoothLayer <- scatterplotClinData( data = exampleData, xVar = "time", yVar = "response", pointPars = list( color = 'red'), aesLineVar = list(group = 'subj'), linePars = list(linetype='dotted'), aesSmoothVar = list(group = 'subj'), smoothPars = list(color = 'green', se=TRUE) , idVar = "subj") plSmoothData <- plotly_build(plSmoothLayer)$x$data # no standard error means one plotting layer less plSmoothNoSE <- scatterplotClinData( data = exampleData, xVar = "time", yVar = "response", pointPars = list( color = 'red'), aesLineVar = list(group = 'subj'), linePars = list(linetype='dotted'), aesSmoothVar = list(group = 'subj'), smoothPars = list(color = 'green', se=FALSE), idVar = "subj" ) plSmoothNoSEData <- plotly_build(plSmoothNoSE)$x$data # test that error band parameters added expect_gt( length(plSmoothData), length(plSmoothNoSEData) ) # test that color in smoothing curves is set correctly isLine <- sapply(plSmoothNoSEData, `[[`, "mode") == "lines" colors <- sapply(plSmoothNoSEData[isLine], function(x) x$line$color) colorsRGB <- sub("^rgba\\((\\d{1,},\\d{1,},\\d{1,}),.+", "\\1\\2\\3", colors)[-1] expect_setequal( object = colorsRGB, expected = paste(grDevices::col2rgb('green'), collapse =",") ) } ) test_that("Smoothing layer can be disabled in scatterplot", { exampleData <- exampleDataScatter() plWithSmoothLayer <- scatterplotClinData( data = exampleData, xVar = "time", yVar = "response", pointPars = list( color = 'red'), aesLineVar = list(group = 'subj'), linePars = list(linetype='dotted'), aesSmoothVar = list(group = 'subj'), smoothPars = list(color = 'green', se=TRUE), smoothInclude = TRUE, idVar = "subj" ) dataWithSmooth <- plotly_build(plWithSmoothLayer)$x$data plNoSmoothLayer <- scatterplotClinData( data = exampleData, xVar = "time", yVar = "response", pointPars = list( color = 'red'), aesLineVar = list(group = 'subj'), linePars = list(linetype='dotted'), aesSmoothVar = list(group = 'subj'), smoothPars = list(color = 'green', se=TRUE), smoothInclude = FALSE, idVar = "subj" ) dataNoSmooth <- plotly_build(plNoSmoothLayer)$x$data # test that smoothing layer not included when smoothInclude = FALSE expect_equal( length(dataWithSmooth), length(dataNoSmooth) + 2 # one layer for smooth, 1 for se ) } ) test_that("Reference lines are correctly implemented in a scatterplot", { data <- data.frame( USUBJID = as.character(seq.int(5)), LBSTRESN = c(39, 93, 10, 31, 13), LBSTRESNBL = c(10, 12, 13, 14, 9), LBSTNRLO = 0, LBSTNRHI = 50, VISIT = c("Screening 1", "Screening 1", "Screening 1", "Week 1", "Week 1") ) xLine <- mean(data$LBSTRESNBL) yLine <- mean(data$LBSTRESN) pl <- scatterplotClinData( data = data, xVar = "LBSTRESNBL", yVar = "LBSTRESN", aesPointVar = list(color = "USUBJID"), aesLineVar = list(group = "USUBJID", color = "USUBJID"), facetPars = list(facets = "VISIT"), refLinePars = list( # fixed values, no labels list(slope = 1, intercept = 0, linetype = 1, color = "black", label = FALSE), list(xintercept = xLine), list(yintercept = yLine), list(slope = 1, intercept = 0, linetype = 1, color = "black", label = FALSE), # from aesthetic # default label list(xintercept = "LBSTNRLO", linetype = 2, color = "orange", alpha = 0.5), # custom label: list(yintercept = "LBSTNRHI", linetype = 2, color = "orange", label = "Reference Range Upper Limit"), # combined list(slope = 1, intercept = "LBSTNRLO") ) ) ## check input == output data # extract input values for reference lines dataRefLines <- unique(data[, c("VISIT", "LBSTNRLO", "LBSTNRHI")]) # extract reference lines from output object plData <- plotly_build(pl)$x$data plDataRefLines <- plData[sapply(plData, function(x) (x$mode == "lines" & is.null(x$set)))] # check if lines are in the plot # ideally we should also check if they are in the correct facet # but the mapping facet <-> line doesn't seem to be easily extracted from the plotly_build output isRefLineXInPlot <- all(c(dataRefLines$LBSTNRLO, xLine) %in% unlist(lapply(plDataRefLines, function(x) x$x))) expect_true(isRefLineXInPlot, info = "All specified horizontal lines are plotted.") isRefLineYInPlot <- all(c(dataRefLines$LBSTNRHI, yLine) %in% unlist(lapply(plDataRefLines, function(x) x$y))) expect_true(isRefLineYInPlot, info = "All specified vertical lines are plotted.") }) test_that("Reference lines as numeric with x-variable as character are successfully set in a scatterplot", { data <- data.frame( USUBJID = as.character(seq.int(5)), LBSTRESN = c(39, 93, 10, 31, 13), LBSTNRLO = 0, LBSTNRHI = 50, VISIT = c("Screening 1", "Screening 1", "Screening 1", "Week 1", "Week 1"), stringsAsFactors = FALSE ) expect_error( pl <- scatterplotClinData( data = data, xVar = "VISIT", yVar = "LBSTRESN", refLinePars = list( # from aesthetic list(yintercept = "LBSTNRLO"), # custom label: list(yintercept = "LBSTNRHI") ) ), NA ) # check reference lines plData <- plotly::plotly_build(pl)$x$data plDataRefLines <- plData[sapply(plData, function(x) (x$mode == "lines" & is.null(x$set)))] plDataRefLinesY <- unlist(lapply(plDataRefLines, `[[`, "y")) expect_setequal(object = plDataRefLinesY, expected = c(0, 50)) # check x-axis plDataPoints <- plData[sapply(plData, function(x) (x$mode == "markers" & !is.null(x$set)))] plDataPointsX <- unlist(lapply(plDataPoints, `[[`, "x")) expect_setequal(object = plDataPointsX, expected = c(1, 2)) }) test_that("Reference lines as numeric with x-variable as factor are successfully set in a scatterplot", { data <- data.frame( USUBJID = as.character(seq.int(5)), LBSTRESN = c(39, 93, 10, 31, 13), LBSTNRLO = 0, LBSTNRHI = 50, VISIT = c("Screening 1", "Screening 1", "Screening 1", "Week 1", "Week 1"), stringsAsFactors = TRUE ) expect_error( pl <- scatterplotClinData( data = data, xVar = "VISIT", yVar = "LBSTRESN", refLinePars = list( # from aesthetic list(yintercept = "LBSTNRLO"), # custom label: list(yintercept = "LBSTNRHI") ) ), NA ) # check reference lines plData <- plotly::plotly_build(pl)$x$data plDataRefLines <- plData[sapply(plData, function(x) (x$mode == "lines" & is.null(x$set)))] plDataRefLinesY <- unlist(lapply(plDataRefLines, `[[`, "y")) expect_setequal(object = plDataRefLinesY, expected = c(0, 50)) # check x-axis plDataPoints <- plData[sapply(plData, function(x) (x$mode == "markers" & !is.null(x$set)))] plDataPointsX <- unlist(lapply(plDataPoints, `[[`, "x")) expect_setequal(object = plDataPointsX, expected = c(1, 2)) }) test_that("Axis labels and title are correctly set in a scatterplot", { data <- data.frame( USUBJID = as.character(seq.int(5)), LBSTRESN = c(39, 93, 10, 31, 13), LBSTRESNBL = c(10, 12, 13, 14, 9) ) labelVars <- c( LBSTRESN = "Actual value", LBSTRESNBL = "Actual value at baseline" ) xLab <- paste("Baseline", labelVars["LBSTRESN"]) title <- "Actual value of lab parameter at each visit vs baseline" pl <- scatterplotClinData( data = data, xVar = "LBSTRESNBL", yVar = "LBSTRESN", xLab = xLab, # custom label labelVars = labelVars, title = title ) ## check input == output data # extract labels from output object yLab <- labelVars["LBSTRESN"] plLayout <- plotly_build(pl)$x$layout plLayoutAnnot <- plLayout$annotations # title expect_equal( object = plLayout$title$text, expected = title, check.attributes = FALSE ) # axes labels expect_equal( object = pl$x$layout$xaxis$title$text, expected = xLab, check.attributes = FALSE ) expect_equal( object = pl$x$layout$yaxis$title$text, expected = unname(yLab), check.attributes = FALSE ) }) test_that("Axis variable(s) are correctly included in a scatterplot", { data <- data.frame( LBSTRESNBL = c(10, 12, 13, 14, 9), LBSTRESNBLU = factor("g/L"), USUBJID = as.character(seq.int(5)), LBSTRESN = c(39, 93, 10, 31, 13), LBSTRESU = factor(rep(x = c("mg/mL", "mg/L"), times = c(3, 2))), stringsAsFactors = FALSE ) pl <- scatterplotClinData( data = data, xVar = "LBSTRESNBL", xLabVar = "LBSTRESNBLU", yVar = "LBSTRESN", yLabVar = "LBSTRESU", labelVars = c( LBSTRESNBL = "Actual value at baseline", LBSTRESNBLU = "Baseline Standard Unit", LBSTRESN = "Actual value at visit X", LBSTRESU = "Standard Unit" ) ) plLayout <- plotly::plotly_build(pl)$x$layout # title for the x-axis expect_match( object = plLayout$xaxis$title$text, regexp = "Actual value at baseline.+Baseline Standard Unit: g/L" ) # title for the y-axis expect_match( object = plLayout$yaxis$title$text, regexp = "Actual value at visit X.+Standard Unit: mg/L, mg/mL" ) # general title expect_match( object = plLayout$title$text, regexp = "Actual value at visit X vs Actual value at baseline" ) }) test_that("An interactive table is created in addition to the scatterplot", { data <- data.frame( USUBJID = as.character(seq.int(5)), LBSTRESN = c(39, 93, 10, 31, 13), LBSTRESNBL = c(10, 12, 13, 14, 9) ) res <- scatterplotClinData( data = data, xVar = "LBSTRESNBL", yVar = "LBSTRESN", table = TRUE ) expect_s3_class(res$table, "datatables") }) test_that("The scatterplot is successfully facetted based on a variable", { data <- data.frame( USUBJID = as.character(seq.int(5)), LBSTRESN = c(39, 93, 10, 31, 13), LBSTRESNBL = c(10, 12, 13, 14, 9) ) # facet_wrap: character test high number of facets plWrapSt <- scatterplotClinData( data = data, xVar = "LBSTRESNBL", yVar = "LBSTRESN", aesPointVar = list(color = "USUBJID"), aesLineVar = list(group = "USUBJID", color = "USUBJID"), facetPars = list(facets = "USUBJID"), themePars = list(legend.position = "right") ) expect_s3_class(plWrapSt, "plotly") }) test_that("The scatterplot is successfully facetted based on a formula", { data <- data.frame( USUBJID = as.character(seq.int(5)), LBSTRESN = c(39, 93, 10, 31, 13), LBSTRESNBL = c(10, 12, 13, 14, 9), VISIT = c("Screening 1", "Screening 1", "Screening 1", "Week 1", "Week 1") ) # facet_wrap: formula plWrapFm <- scatterplotClinData( data = data, xVar = "LBSTRESNBL", yVar = "LBSTRESN", aesPointVar = list(color = "USUBJID"), aesLineVar = list(group = "USUBJID", color = "USUBJID"), facetPars = list(facets = as.formula(~VISIT + USUBJID)) ) expect_s3_class(plWrapFm, "plotly") }) test_that("Specified x-axis and y-axis limits are expanded when data is outside of these limits in a scatterplot", { data <- data.frame( USUBJID = as.character(seq.int(5)), LBSTRESN = c(39, 93, 10, 31, 13), LBSTRESNBL = c(10, 12, 13, 14, 9) ) xLim <- c(min(data$LBSTRESNBL) + diff(range(data$LBSTRESNBL))/2, max(data$LBSTRESNBL)) yLim <- c(min(data$LBSTRESN) + diff(range(data$LBSTRESN))/2, max(data$LBSTRESN)) plNoExpandLim <- scatterplotClinData( data = data, xVar = "LBSTRESNBL", yVar = "LBSTRESN", aesPointVar = list(color = "USUBJID"), aesLineVar = list(group = "USUBJID", color = "USUBJID"), xLim = xLim, yLim = yLim, xLimExpandData = FALSE, yLimExpandData = FALSE ) plExpandLim <- scatterplotClinData( data = data, xVar = "LBSTRESNBL", yVar = "LBSTRESN", aesPointVar = list(color = "USUBJID"), aesLineVar = list(group = "USUBJID", color = "USUBJID"), xLim = xLim, yLim = yLim ) expect_gt( object = diff(plotly_build(plExpandLim)$x$layout$xaxis$range), expected = diff(plotly_build(plNoExpandLim)$x$layout$xaxis$range), label = "limits of x-axis expanded from data greater than specified limits" ) expect_gt( object = diff(plotly_build(plExpandLim)$x$layout$yaxis$range), expected = diff(plotly_build(plNoExpandLim)$x$layout$yaxis$range), label = "limits of y-axis expanded from data greater than specified limits" ) }) test_that("A scatterplot with specified hover variables is successfully created", { data <- data.frame( USUBJID = as.character(seq.int(5)), LBSTRESN = c(39, 93, 10, 31, 13), LBSTRESNBL = c(10, 12, 13, 14, 9) ) plOutput <- scatterplotClinData( data = data, xVar = "LBSTRESNBL", yVar = "LBSTRESN", hoverVars = c("LBSTRESNBL", "USUBJID") ) expect_s3_class(plOutput, "plotly") }) test_that("A legend is correctly not included in a scatterplot", { data <- data.frame( USUBJID = as.character(seq.int(5)), LBSTRESN = c(39, 93, 10, 31, 13), LBSTRESNBL = c(10, 12, 13, 14, 9) ) plOutput <- scatterplotClinData( data = data, xVar = "LBSTRESNBL", yVar = "LBSTRESN", themePars = list(legend.position = "none") ) expect_s3_class(plOutput, "plotly") }) test_that("A color palette is correctly set in a scatterplot", { data <- data.frame( DY = c(1, 2, 1, 2), AVAL = c(3, 4, 2, 6), NRIND = c("Normal", "High", "Low", "Normal"), USUBJID = c(1, 1, 2, 2), stringsAsFactors = FALSE ) colorPalette <- c( Low = "purple", Normal = "green", High = "blue" ) pl <- scatterplotClinData( data = data, xVar = "DY", yVar = "AVAL", aesPointVar = list(color = "NRIND"), scalePars = list( list(aesthetic = "colour", values = colorPalette) ) ) plData <- plotly_build(pl)$x$data plData <- lapply(plData, function(x){ data.frame( x = as.numeric(x$x), y = as.numeric(x$y), NRIND = as.character(x$name), color = as.character(x$marker$line$color), stringsAsFactors = FALSE ) }) plData <- do.call(rbind, plData) plData <- plData[do.call(order, plData), ] # plotly specifies color in rgba colorPaletteRGB <- grDevices::col2rgb(colorPalette) colorPaletteRGBA <- paste0( "rgba(", apply(colorPaletteRGB, 2, paste, collapse = ","), ",1)" # + alpha ) names(colorPaletteRGBA) <- colorPalette # extract color for input data: data$color <- colorPaletteRGBA[colorPalette[data$NRIND]] data <- data[, c("DY", "AVAL", "NRIND", "color")] data <- data[do.call(order, data), ] expect_equal( object = plData, expected = data, check.attributes = FALSE ) }) test_that("The default color palette is correctly extracted", { data <- data.frame( DY = c(1, 2, 1, 2), AVAL = c(3, 4, 2, 6), NRIND = c("Normal", "High", "Low", "Normal"), USUBJID = c(1, 1, 2, 2), stringsAsFactors = FALSE ) expect_error( pl <- clinDataReview::scatterplotClinData( data = data, xVar = "DY", yVar = "AVAL", aesPointVar = list(color = "NRIND") ), NA ) # plotly specifies color in rgba colors <- sapply(plotly::plotly_build(pl)$x$data, function(x){ color <- x$marker$line$color color <- sub("rgba\\((.+)\\)$", "\\1", color) color <- strsplit(color, split = ",")[[1]][-4] # (remove transparency) paste(color, collapse = ",") }) # default color palette colorsDefault <- getOption("clinDataReview.colors")(3) colorsDefault <- sapply(colorsDefault, function(color) paste(grDevices::col2rgb(color), collapse = ",") # convert to RGB ) expect_setequal(object = colors, expected = colorsDefault) }) test_that("The x-axis labels are correctly set from variables in the scatterplot", { data <- data.frame( AVISIT = factor( c("Day 4", "Screening"), levels = c("Screening", "Day 4") ), AVAL = c(1, 2), USUBJID = c("1", "2"), n = c("N = 4", "N = 3"), stringsAsFactors = FALSE ) pl <- scatterplotClinData( data = data, xVar = "AVISIT", xLabVars = c("AVISIT", "n"), yVar = "AVAL" ) plXAxis <- plotly_build(pl)$x$layout$xaxis # extract tick labels plXTickLab <- plXAxis$ticktext # and sort them plXTickLab <- plXTickLab[order(plXAxis$tickvals, decreasing = FALSE)] expect_match(object = plXTickLab[1], regexp = "Screening.+N = 3") expect_match(object = plXTickLab[2], regexp = "Day 4.+N = 4") }) test_that("Variables for x-axis labels are correctly combined and ordered if multiple in a scatterplot", { data <- data.frame( AVISIT = factor( c("Day 4", "Screening", "Day 4", "Screening"), levels = c("Screening", "Day 4") ), AVAL = c(1, 2, 3, 4), USUBJID = c("1", "1", "2", "2"), TREAT = factor( c("Compound", "Compound", "Placebo", "Placebo"), levels = c("Placebo", "Compound") ), stringsAsFactors = FALSE ) pl <- scatterplotClinData( data = data, xVar = "AVISIT", xLabVars = c("AVISIT", "TREAT"), yVar = "AVAL" ) plXAxis <- plotly_build(pl)$x$layout$xaxis # extract tick labels plXTickLab <- plXAxis$ticktext # and sort them plXTickLab <- plXTickLab[order(plXAxis$tickvals, decreasing = FALSE)] expect_match(object = plXTickLab[1], regexp = "Screening.+Placebo.+Compound") expect_match(object = plXTickLab[2], regexp = "Day 4.+Placebo.+Compound") }) test_that("A subtitle is correctly set in a scatterplot", { data <- data.frame( DY = c(1, 2, 1, 2), AVAL = c(3, 4, 2, 6), USUBJID = c(1, 1, 2, 2), stringsAsFactors = FALSE ) subtitle <- paste(sample(LETTERS, 100, replace = TRUE), collapse = "") subtitle <- paste(rep(subtitle, 10), collapse = "\n") plSubtitle <- scatterplotClinData( data = data, xVar = "DY", yVar = "AVAL", subtitle = subtitle ) # extract annotation plAnnot <- plotly_build(plSubtitle)$x$layout$annotations plSubtitleAnnot <- lapply(plAnnot, function(xEl) if(hasName(xEl, "text")) xEl[["text"]] ) plSubtitleAnnot <- unlist(plSubtitleAnnot, recursive = TRUE, use.names = FALSE) expect_match(plSubtitleAnnot, gsub("\n", ".*", subtitle)) # check that top margin is increased plNoSubtitle <- scatterplotClinData( data = data, xVar = "DY", yVar = "AVAL" ) expect_gt( object = plotly_build(plSubtitle)$x$layout$margin$t, expected = plotly_build(plNoSubtitle)$x$layout$margin$t ) }) test_that("Extra margin is correctly set for the subtitle in a facetted plot", { data <- data.frame( DY = c(1, 2, 1, 2), AVAL = c(3, 4, 2, 6), USUBJID = c(1, 1, 2, 2), TRT = c("A", "A", "B", "B"), stringsAsFactors = FALSE ) subtitle <- paste(sample(LETTERS, 100, replace = TRUE), collapse = "") subtitle <- paste(rep(subtitle, 10), collapse = "\n") plSubtitleFacet <- scatterplotClinData( data = data, xVar = "DY", yVar = "AVAL", subtitle = subtitle, facetPars = list(facets = "TRT") ) # check that top margin is increased plSubtitleNoFacet <- scatterplotClinData( data = data, xVar = "DY", yVar = "AVAL", subtitle = subtitle ) expect_gt( object = plotly_build(plSubtitleFacet)$x$layout$margin$t, expected = plotly_build(plSubtitleNoFacet)$x$layout$margin$t ) }) test_that("A caption is correctly set in a scatterplot", { data <- data.frame( DY = c(1, 2, 1, 2), AVAL = c(3, 4, 2, 6), USUBJID = c(1, 1, 2, 2), stringsAsFactors = FALSE ) caption <- paste(sample(LETTERS, 100, replace = TRUE), collapse = "") caption <- paste(rep(caption, 10), collapse = "\n") plCaption <- scatterplotClinData( data = data, xVar = "DY", xLab = "TEST", yVar = "AVAL", caption = caption ) # extract annotation plAnnot <- plotly_build(plCaption)$x$layout$annotations plCaptionAnnot <- lapply(plAnnot, function(xEl) if(hasName(xEl, "text")) xEl[["text"]] ) plCaptionAnnot <- unlist(plCaptionAnnot, recursive = TRUE, use.names = FALSE) expect_match(plCaptionAnnot, gsub("\n", ".*", caption)) # check that bottom margin is increased plNoCaption <- scatterplotClinData( data = data, xVar = "DY", yVar = "AVAL" ) expect_gt( object = plotly_build(plCaption)$x$layout$margin$b, expected = plotly_build(plNoCaption)$x$layout$margin$b ) }) test_that("A selection variable is correctly included in a scatterplot", { data <- data.frame( group = factor(c("A", "A", "A", "A", "B"), levels = c("B", "A")), DY = c(1, 2, 1, 2, 3), AVAL = c(3, 4, 2, 6, 5), USUBJID = c(1, 1, 2, 2, 3), stringsAsFactors = FALSE ) res <- scatterplotClinData( data = data, xVar = "DY", yVar = "AVAL", aesLineVar = list(group = "USUBJID"), selectVars = "group" ) # check the output: expect_s3_class(res, "clinDataReview") expect_named(res, expected = c("buttons", "plot")) expect_s3_class(res$plot, "plotly") expect_length(res$buttons, 1) # check button values btnScriptTag <- htmltools::tagQuery(res$buttons)$find("script")$selectedTags() buttonData <- jsonlite::fromJSON(txt = as.character(btnScriptTag[[1]]$children)) expect_equal(object = buttonData$items$value, expected = levels(data$group)) }) test_that("A box to highlight the elements of the ID variable is correctly included in a scatterplot", { data <- data.frame( DY = c(1, 2, 1, 2), AVAL = c(3, 4, 2, 6), USUBJID = c(1, 1, 2, 2), stringsAsFactors = FALSE ) pl <- scatterplotClinData( data = data, xVar = "DY", yVar = "AVAL", idHighlightBox = TRUE ) # check the output: expect_s3_class(pl, "plotly") expect_true(pl$x$highlight$selectize) }) test_that("A watermark is correctly included in a (facetted) scatterplot", { data <- data.frame( USUBJID = as.character(seq.int(5)), LBSTRESN = c(39, 93, 10, 31, 13), LBSTRESNBL = c(10, 12, 13, 14, 9) ) file <- tempfile(pattern = "watermark", fileext = ".png") getWatermark(file = file) pl <- scatterplotClinData( data = data, xVar = "LBSTRESNBL", yVar = "LBSTRESN", facetPars = list(facets = "USUBJID"), watermark = file ) # check that an image has been included below the plot plBuild <- plotly::plotly_build(pl) expect_equal( object = sapply(plBuild$x$layout$images, `[[`, "layer"), expected = "below" ) })