tests/testthat/test-box.R
In VEuPathDB/plot.data: Create `data.table`s of Ready to Plot Data
context('box')
test_that("box.dt does not fail when there are no complete cases.", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binary1', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cont', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- data.noneComplete[is.na(entity.binary1),]
dt <- box.dt(df, variables, 'none', FALSE, FALSE)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(is.list(dt$label), TRUE)
expect_equal(is.list(dt$min), TRUE)
expect_equal(is.list(dt$q1), TRUE)
expect_equal(is.list(dt$median), TRUE)
expect_equal(is.list(dt$q3), TRUE)
expect_equal(is.list(dt$max), TRUE)
expect_equal(is.list(dt$lowerfence), TRUE)
expect_equal(is.list(dt$upperfence), TRUE)
dt <- box.dt(df, variables, 'none', FALSE, TRUE)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(is.list(dt$label), TRUE)
expect_equal(is.list(dt$min), TRUE)
expect_equal(is.list(dt$q1), TRUE)
expect_equal(is.list(dt$median), TRUE)
expect_equal(is.list(dt$q3), TRUE)
expect_equal(is.list(dt$max), TRUE)
expect_equal(is.list(dt$lowerfence), TRUE)
expect_equal(is.list(dt$upperfence), TRUE)
dt <- box.dt(df, variables, 'none', TRUE, TRUE)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(is.list(dt$label), TRUE)
expect_equal(is.list(dt$min), TRUE)
expect_equal(is.list(dt$q1), TRUE)
expect_equal(is.list(dt$median), TRUE)
expect_equal(is.list(dt$q3), TRUE)
expect_equal(is.list(dt$max), TRUE)
expect_equal(is.list(dt$lowerfence), TRUE)
expect_equal(is.list(dt$upperfence), TRUE)
expect_equal(is.list(dt$mean), TRUE)
dt <- box.dt(df, variables, 'outliers', FALSE, TRUE)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(is.list(dt$label), TRUE)
expect_equal(is.list(dt$min), TRUE)
expect_equal(is.list(dt$q1), TRUE)
expect_equal(is.list(dt$median), TRUE)
expect_equal(is.list(dt$q3), TRUE)
expect_equal(is.list(dt$max), TRUE)
expect_equal(is.list(dt$lowerfence), TRUE)
expect_equal(is.list(dt$upperfence), TRUE)
expect_equal(is.list(dt$outliers), TRUE)
expect_equal(is.list(dt$outliers[[1]]), TRUE)
dt <- box.dt(df, variables, 'all', FALSE, TRUE)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(is.list(dt$label), TRUE)
expect_equal(is.list(dt$min), TRUE)
expect_equal(is.list(dt$q1), TRUE)
expect_equal(is.list(dt$median), TRUE)
expect_equal(is.list(dt$q3), TRUE)
expect_equal(is.list(dt$max), TRUE)
expect_equal(is.list(dt$lowerfence), TRUE)
expect_equal(is.list(dt$upperfence), TRUE)
expect_equal(is.list(dt$rawData), TRUE)
expect_equal(is.list(dt$rawData[[1]]), TRUE)
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binary1', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binary2', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cont', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- data.noneComplete
dt <- box.dt(df, variables, 'none', FALSE, FALSE)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(is.list(dt$label), TRUE)
expect_equal(is.list(dt$min), TRUE)
expect_equal(is.list(dt$q1), TRUE)
expect_equal(is.list(dt$median), TRUE)
expect_equal(is.list(dt$q3), TRUE)
expect_equal(is.list(dt$max), TRUE)
expect_equal(is.list(dt$lowerfence), TRUE)
expect_equal(is.list(dt$upperfence), TRUE)
})
test_that("box.dt() returns a valid plot.data box object", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
expect_is(dt, 'plot.data')
expect_is(dt, 'boxplot')
namedAttrList <- getPDAttributes(dt)
expect_equal(names(namedAttrList),c('variables', 'completeCasesAllVars','completeCasesAxesVars','completeCasesTable','sampleSizeTable','statsTable'))
completeCases <- completeCasesTable(dt)
expect_equal(names(completeCases), c('variableDetails','completeCases'))
expect_equal(nrow(completeCases), 3)
sampleSizes <- sampleSizeTable(dt)
expect_equal(names(sampleSizes), c('entity.cat3','entity.cat4','size'))
expect_equal(nrow(sampleSizes), 3)
expect_equal(names(namedAttrList$statsTable), c('entity.cat4','statistic','pvalue','parameter','method','statsError'))
dt <- box.dt(df, variables, 'all', FALSE, computeStats = T)
expect_is(dt, 'plot.data')
expect_is(dt, 'boxplot')
namedAttrList <- getPDAttributes(dt)
expect_equal(names(namedAttrList),c('variables', 'completeCasesAllVars','completeCasesAxesVars','completeCasesTable','sampleSizeTable','statsTable'))
completeCases <- completeCasesTable(dt)
expect_equal(names(completeCases), c('variableDetails','completeCases'))
expect_equal(nrow(completeCases), 3)
sampleSizes <- sampleSizeTable(dt)
expect_equal(names(sampleSizes), c('entity.cat3','entity.cat4','size'))
expect_equal(nrow(sampleSizes), 3)
expect_equal(names(namedAttrList$statsTable), c('entity.cat4','statistic','pvalue','parameter','method','statsError'))
expect_equal(dt$entity.cat3[[1]], 'cat3_a')
expect_equal(dt$label[[1]], c('cat4_a','cat4_b','cat4_c','cat4_d'))
expect_equal(unlist(lapply(dt$rawData[[1]], length)), c(42,42,29,51))
# Ensure sampleSizeTable and completeCasesTable do not get returned if we do not ask for them.
dt <- box.dt(df, variables, 'all', FALSE, computeStats = T, sampleSizes = FALSE, completeCases = FALSE)
expect_is(dt, 'plot.data')
expect_is(dt, 'boxplot')
namedAttrList <- getPDAttributes(dt)
expect_equal(names(namedAttrList),c('variables','statsTable'))
expect_equal(names(namedAttrList$statsTable), c('entity.cat4','statistic','pvalue','parameter','method','statsError'))
expect_equal(dt$entity.cat3[[1]], 'cat3_a')
expect_equal(dt$label[[1]], c('cat4_a','cat4_b','cat4_c','cat4_d'))
expect_equal(unlist(lapply(dt$rawData[[1]], length)), c(42,42,29,51))
})
test_that("box.dt() returns plot data and config of the appropriate types", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
dt <- box.dt(df, variables, 'none', TRUE)
expect_equal(class(dt$label[[1]]), 'character')
expect_equal(class(dt$min[[1]]), 'numeric')
expect_equal(class(dt$q1[[1]]), 'numeric')
expect_equal(class(dt$median[[1]]), 'numeric')
expect_equal(class(dt$q3[[1]]), 'numeric')
expect_equal(class(dt$max[[1]]), 'numeric')
expect_equal(class(dt$lowerfence[[1]]), 'numeric')
expect_equal(class(dt$upperfence[[1]]), 'numeric')
expect_equal(class(dt$mean[[1]]), 'numeric')
namedAttrList <- getPDAttributes(dt)
expect_equal(class(namedAttrList$completeCasesAllVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$completeCasesAxesVars),c('scalar', 'integer'))
completeCases <- completeCasesTable(dt)
expect_equal(class(unlist(completeCases$variableDetails)), 'character')
expect_equal(class(unlist(completeCases$completeCases)), 'integer')
sampleSizes <- sampleSizeTable(dt)
expect_equal(class(unlist(sampleSizes$entity.cat5)), 'character')
expect_equal(class(unlist(sampleSizes$size)), 'integer')
#w outliers
dt <- box.dt(df, variables, 'outliers', TRUE)
expect_equal(class(dt$label[[1]]), 'character')
expect_equal(class(dt$min[[1]]), 'numeric')
expect_equal(class(dt$q1[[1]]), 'numeric')
expect_equal(class(dt$median[[1]]), 'numeric')
expect_equal(class(dt$q3[[1]]), 'numeric')
expect_equal(class(dt$max[[1]]), 'numeric')
expect_equal(class(dt$lowerfence[[1]]), 'numeric')
expect_equal(class(dt$upperfence[[1]]), 'numeric')
expect_equal(class(dt$mean[[1]]), 'numeric')
#first group has no outliers, want json like [] rather than {}
expect_equal(class(dt$outliers[[1]][[1]]), 'list')
expect_equal(class(dt$outliers[[1]][[3]]), 'numeric')
namedAttrList <- getPDAttributes(dt)
expect_equal(class(namedAttrList$completeCasesAllVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$completeCasesAxesVars),c('scalar', 'integer'))
completeCases <- completeCasesTable(dt)
expect_equal(class(unlist(completeCases$variableDetails)), 'character')
expect_equal(class(unlist(completeCases$completeCases)), 'integer')
sampleSizes <- sampleSizeTable(dt)
expect_equal(class(unlist(sampleSizes$entity.cat5)), 'character')
expect_equal(class(unlist(sampleSizes$size)), 'integer')
#single group
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- testDF[testDF$entity.cat3 == 'cat3_a' & testDF$entity.cat4 == 'cat4_a',]
dt <- box.dt(df, variables, 'none', TRUE)
expect_equal(class(dt$label[[1]]), 'character')
expect_equal(class(dt$min[[1]]), 'numeric')
expect_equal(class(dt$q1[[1]]), 'numeric')
expect_equal(class(dt$median[[1]]), 'numeric')
expect_equal(class(dt$q3[[1]]), 'numeric')
expect_equal(class(dt$max[[1]]), 'numeric')
expect_equal(class(dt$lowerfence[[1]]), 'numeric')
expect_equal(class(dt$upperfence[[1]]), 'numeric')
expect_equal(class(dt$mean[[1]]), 'numeric')
namedAttrList <- getPDAttributes(dt)
expect_equal(class(namedAttrList$completeCasesAllVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$completeCasesAxesVars),c('scalar', 'integer'))
completeCases <- completeCasesTable(dt)
expect_equal(class(unlist(completeCases$variableDetails)), 'character')
expect_equal(class(unlist(completeCases$completeCases)), 'integer')
sampleSizes <- sampleSizeTable(dt)
expect_equal(class(unlist(sampleSizes$entity.cat4)), 'character')
expect_equal(class(unlist(sampleSizes$size)), 'integer')
# With numeric data for the x axis
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'int6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'INTEGER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- testDF
dt <- box.dt(df, variables, 'none', TRUE)
expect_equal(class(dt$label[[1]]), 'character')
expect_equal(class(dt$min[[1]]), 'numeric')
expect_equal(class(dt$q1[[1]]), 'numeric')
expect_equal(class(dt$median[[1]]), 'numeric')
expect_equal(class(dt$q3[[1]]), 'numeric')
expect_equal(class(dt$max[[1]]), 'numeric')
expect_equal(class(dt$lowerfence[[1]]), 'numeric')
expect_equal(class(dt$upperfence[[1]]), 'numeric')
expect_equal(class(dt$mean[[1]]), 'numeric')
namedAttrList <- getPDAttributes(dt)
expect_equal(class(namedAttrList$completeCasesAllVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$completeCasesAxesVars),c('scalar', 'integer'))
completeCases <- completeCasesTable(dt)
expect_equal(class(unlist(completeCases$variableDetails)), 'character')
expect_equal(class(unlist(completeCases$completeCases)), 'integer')
sampleSizes <- sampleSizeTable(dt)
expect_equal(class(unlist(sampleSizes$entity.int6)), 'integer') ## will become a string when written to json
expect_equal(class(unlist(sampleSizes$size)), 'integer')
# With a single numeric box
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'int2', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'INTEGER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- testDF
df[df$entity.int2 == 2] <- 1
dt <- box.dt(df, variables, 'none', TRUE)
expect_equal(class(dt$label[[1]]), 'character')
expect_equal(class(dt$min[[1]]), 'numeric')
expect_equal(class(dt$q1[[1]]), 'numeric')
expect_equal(class(dt$median[[1]]), 'numeric')
expect_equal(class(dt$q3[[1]]), 'numeric')
expect_equal(class(dt$max[[1]]), 'numeric')
expect_equal(class(dt$lowerfence[[1]]), 'numeric')
expect_equal(class(dt$upperfence[[1]]), 'numeric')
expect_equal(class(dt$mean[[1]]), 'numeric')
namedAttrList <- getPDAttributes(dt)
expect_equal(class(namedAttrList$completeCasesAllVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$completeCasesAxesVars),c('scalar', 'integer'))
completeCases <- completeCasesTable(dt)
expect_equal(class(unlist(completeCases$variableDetails)), 'character')
expect_equal(class(unlist(completeCases$completeCases)), 'integer')
sampleSizes <- sampleSizeTable(dt)
expect_equal(class(unlist(sampleSizes$entity.int2)), 'numeric') ## will become a string when written to json
expect_equal(class(unlist(sampleSizes$size)), 'integer')
})
test_that("box.dt() returns an appropriately sized data.table", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
dt <- box.dt(df, variables, 'none', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'mean'))
dt <- box.dt(df, variables, 'outliers', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'outliers'))
dt <- box.dt(df, variables, 'outliers', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'outliers', 'mean'))
dt <- box.dt(df, variables, 'all', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData'))
dt <- box.dt(df, variables, 'all', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData', 'mean'))
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
dt <- box.dt(df, variables, 'none', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'mean'))
dt <- box.dt(df, variables, 'outliers', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'outliers'))
dt <- box.dt(df, variables, 'outliers', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'outliers', 'mean'))
dt <- box.dt(df, variables, 'all', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData'))
dt <- box.dt(df, variables, 'all', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData', 'mean'))
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'int6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'INTEGER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'int7', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),7)
expect_equal(names(dt),c('entity.int7', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
dt <- box.dt(df, variables, 'none', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),7)
expect_equal(names(dt),c('entity.int7', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'mean'))
dt <- box.dt(df, variables, 'outliers', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),7)
expect_equal(names(dt),c('entity.int7', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'outliers'))
dt <- box.dt(df, variables, 'outliers', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),7)
expect_equal(names(dt),c('entity.int7', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'outliers', 'mean'))
dt <- box.dt(df, variables, 'all', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),7)
expect_equal(names(dt),c('entity.int7', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData'))
dt <- box.dt(df, variables, 'all', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),7)
expect_equal(names(dt),c('entity.int7', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData', 'mean'))
# Test single outlier
df <- data.frame('entity.x' = c('group1'), 'entity.y'=c(35.1, 34.2, 36.2, 90.2))
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'x', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'y', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- box.dt(df, variables, 'outliers', FALSE, computeStats = T)
expect_equal(names(dt),c('label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'outliers'))
expect_equal(class(dt$label[[1]]), 'character')
expect_equal(class(dt$min[[1]]), 'numeric')
expect_equal(class(dt$outliers[[1]]), 'list')
# With factors
df <- testDF
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'factor3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- box.dt(df, variables, 'all', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.factor3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData', 'mean'))
expect_equal(class(dt$entity.factor3), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'factor3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- box.dt(df, variables, 'all', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),9)
expect_equal(names(dt),c('panel', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData', 'mean'))
expect_equal(class(dt$panel), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'factor3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'factor6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- box.dt(df, variables, 'all', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),18)
expect_equal(names(dt),c('panel', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData', 'mean'))
expect_equal(class(dt$panel), 'character')
## Collection vars
# Multiple vars to x
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity"),
new("VariableSpec", variableId = "contC", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt), 3)
expect_equal(names(dt),c('entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
expect_equal(unique(dt$label)[[1]], c('contA','contB','contC'))
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'yAxis')@variableId, 'collectionVarValues')
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'xAxis')@variableId, 'collection')
# Multiple vars to facet1
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity"),
new("VariableSpec", variableId = "contC", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt), 3)
expect_equal(names(dt),c('entity.collection', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
expect_equal(dt$entity.collection, c('contA','contB','contC'))
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'yAxis')@variableId, 'collectionVarValues')
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'facet1')@variableId, 'collection')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'computed'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
displayName = "Label",
displayRangeMin = 0,
displayRangeMax = 1,
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity"),
new("VariableSpec", variableId = "contC", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt), 12)
expect_equal(names(dt),c('panel', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
expect_equal(dt$panel[1], 'contA.||.cat4_a')
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'yAxis')@variableId, 'collectionVarValues')
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'facet1')@variableId, 'collection')
index <- which(purrr::map(as.list(attr(dt, 'variables')), function(x) { x@variableSpec@variableId == 'collectionVarValues' }) %in% TRUE)
collectionVM <- attr(dt, 'variables')[[index]]
expect_equal(collectionVM@displayName, paste(variables[[1]]@displayName, 'values'))
expect_equal(collectionVM@displayRangeMin, variables[[1]]@displayRangeMin)
expect_equal(collectionVM@displayRangeMax, variables[[1]]@displayRangeMax)
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'computed'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
displayName = "Label",
displayRangeMin = 0,
displayRangeMax = 1,
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity"),
new("VariableSpec", variableId = "contC", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt), 12)
expect_equal(names(dt),c('panel', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
expect_equal(dt$panel[1], 'cat4_a.||.contA')
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'yAxis')@variableId, 'collectionVarValues')
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'facet2')@variableId, 'collection')
# Handle only one var sent as a collectionVar
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'computed'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
displayName = "Label",
displayRangeMin = 0,
displayRangeMax = 1,
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt), 3)
expect_equal(names(dt),c('entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
expect_equal(unique(dt$label)[[1]], c('contB'))
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'yAxis')@variableId, 'collectionVarValues')
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'xAxis')@variableId, 'collection')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'computed'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
displayName = "Label",
displayRangeMin = 0,
displayRangeMax = 1,
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt), 1)
expect_equal(names(dt),c('entity.collection', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
expect_equal(dt$entity.collection, c('contB'))
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'yAxis')@variableId, 'collectionVarValues')
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'facet1')@variableId, 'collection')
})
test_that("box() returns appropriately formatted json", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
df <- as.data.frame(testDF)
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','statsTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('overlayVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(jsonList$boxplot$data$overlayVariableDetails$variableId[1], 'cat3')
expect_equal(names(jsonList$boxplot$config), c('variables','completeCasesAllVars','completeCasesAxesVars'))
expect_equal(names(jsonList$sampleSizeTable), c('overlayVariableDetails','xVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(jsonList$sampleSizeTable$xVariableDetails$variableId[[1]], 'cat4')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId'))
expect_equal(jsonList$completeCasesTable$variableDetails$variableId, c('cat4', 'contB', 'cat3'))
expect_equal(names(jsonList$statsTable), c('xVariableDetails','statistic','pvalue','parameter','method','statsError'))
expect_equal(jsonList$statsTable$xVariableDetails$variableId[1], 'cat4')
expect_equal(class(jsonList$statsTable$statistic), 'numeric')
expect_equal(class(jsonList$statsTable$statsError), 'character')
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
displayName = "yLabel",
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
displayName = "groupLabel",
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
displayName = "panelLabel",
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','statsTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('overlayVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(jsonList$boxplot$data$overlayVariableDetails$variableId[1], 'cat3')
expect_equal(names(jsonList$boxplot$config), c('variables','completeCasesAllVars','completeCasesAxesVars'))
expect_equal(names(jsonList$boxplot$config$variables$variableSpec), c('variableId','entityId'))
expect_equal(jsonList$boxplot$config$variables$variableSpec$variableId, c('contB','cat3','cat4'))
expect_equal(names(jsonList$sampleSizeTable), c('overlayVariableDetails','xVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(jsonList$sampleSizeTable$xVariableDetails$variableId[[1]], 'cat4')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId','displayLabel'))
expect_equal(jsonList$completeCasesTable$variableDetails$variableId, c('cat4', 'contB', 'cat3'))
expect_equal(names(jsonList$statsTable), c('xVariableDetails','statistic','pvalue','parameter','method','statsError'))
expect_equal(jsonList$statsTable$xVariableDetails$variableId[1], 'cat4')
expect_equal(class(jsonList$statsTable$statistic), 'numeric')
expect_equal(class(jsonList$statsTable$statsError), 'character')
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
# Ensure sampleSizeTable and completeCasesTable are not part of json if we do not ask for them.
# Make sure to also ask for the stats table to check that all goes well with this special box-specific table
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T, sampleSizes = FALSE, completeCases = FALSE)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','statsTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('overlayVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(jsonList$boxplot$data$overlayVariableDetails$variableId[1], 'cat3')
expect_equal(names(jsonList$boxplot$config), c('variables'))
expect_equal(names(jsonList$boxplot$config$variables$variableSpec), c('variableId','entityId'))
expect_equal(jsonList$boxplot$config$variables$variableSpec$variableId, c('contB','cat3','cat4'))
expect_equal(names(jsonList$statsTable), c('xVariableDetails','statistic','pvalue','parameter','method','statsError'))
expect_equal(jsonList$statsTable$xVariableDetails$variableId[1], 'cat4')
expect_equal(class(jsonList$statsTable$statistic), 'numeric')
expect_equal(class(jsonList$statsTable$statsError), 'character')
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
displayName = "yLabel",
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
displayName = "groupLabel",
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
displayName = "panelLabel",
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','statsTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('facetVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(names(jsonList$boxplot$config), c('variables','completeCasesAllVars','completeCasesAxesVars'))
expect_equal(names(jsonList$boxplot$config$variables$variableSpec), c('variableId','entityId'))
expect_equal(names(jsonList$sampleSizeTable), c('facetVariableDetails','xVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId','displayLabel'))
expect_equal(names(jsonList$statsTable), c('facetVariableDetails','statistic','pvalue','parameter','method','statsError'))
expect_equal(jsonList$statsTable$facetVariableDetails[[1]]$variableId, 'cat3')
expect_equal(class(jsonList$statsTable$statistic), 'numeric')
expect_equal(class(jsonList$statsTable$statsError), 'character')
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
displayName = "panelLabel",
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList$boxplot$config$variables$variableSpec), c('variableId','entityId'))
expect_equal(names(jsonList$boxplot$data$overlayVariableDetails), c('variableId','entityId','value'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId','displayLabel'))
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
displayName = "panelLabel",
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, TRUE, NULL, evilMode = 'strataVariables')
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
# no stats table even if requested, when evilMode is 'strataVariables'
expect_equal(names(jsonList), c('boxplot', 'sampleSizeTable', 'completeCasesTable'))
expect_equal(names(jsonList$boxplot$config$variables$variableSpec), c('variableId','entityId'))
expect_equal(names(jsonList$boxplot$data$overlayVariableDetails), c('variableId','entityId','value'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId','displayLabel'))
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','statsTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('overlayVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(names(jsonList$boxplot$config), c('variables','completeCasesAllVars','completeCasesAxesVars'))
expect_equal(names(jsonList$boxplot$config$variables$variableSpec), c('variableId','entityId'))
expect_equal(names(jsonList$sampleSizeTable), c('overlayVariableDetails','xVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId'))
expect_equal(names(jsonList$statsTable), c('xVariableDetails','statistic','pvalue','parameter','method','statsError'))
expect_equal(jsonList$statsTable$xVariableDetails$variableId[1], 'binA')
expect_equal(class(jsonList$statsTable$statistic), 'numeric')
expect_equal(class(jsonList$statsTable$statsError), 'character')
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
displayName = "panelLabel",
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','statsTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
expect_equal(names(jsonList$boxplot$config), c('variables','completeCasesAllVars','completeCasesAxesVars'))
expect_equal(names(jsonList$boxplot$config$variables$variableSpec), c('variableId','entityId'))
expect_equal(names(jsonList$sampleSizeTable), c('xVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId','displayLabel'))
expect_equal(names(jsonList$statsTable), c('statistic','pvalue','parameter','method','statsError'))
expect_equal(class(jsonList$statsTable$statistic), 'integer')
expect_equal(length(jsonList$statsTable$statistic), 1)
expect_equal(class(jsonList$statsTable$statsError), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList$statsTable), c('statistic','pvalue','parameter','method','statsError'))
expect_equal(class(jsonList$statsTable$statistic), 'numeric')
expect_equal(length(jsonList$statsTable$statistic), 1)
expect_equal(class(jsonList$statsTable$statsError), 'character')
# Multiple vars for x and computed variable metadata
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'computed'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
displayName = "Label",
displayRangeMin = 0.5,
displayRangeMax = 1.5,
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('overlayVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(jsonList$boxplot$config$completeCasesAllVars, nrow(df))
expect_equal(jsonList$boxplot$config$completeCasesAxesVars, nrow(df))
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$sampleSizeTable), c('overlayVariableDetails','xVariableDetails','size'))
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId'))
expect_equal(nrow(jsonList$completeCasesTable), 3)
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
# Collection var only
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'computed'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
displayName = "Label",
displayRangeMin = 0.5,
displayRangeMax = 1.5,
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity")
))
)
))
dt <- box.dt(df, variables, 'none', FALSE)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(jsonList$boxplot$config$completeCasesAllVars, nrow(df))
expect_equal(jsonList$boxplot$config$completeCasesAxesVars, nrow(df))
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$sampleSizeTable), c('xVariableDetails','size'))
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId'))
expect_equal(nrow(jsonList$completeCasesTable), 2)
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
# Multiple vars to facet1 and computed variable metadata
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'computed'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
displayName = "Label",
displayRangeMin = 0.5,
displayRangeMax = 1.5,
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats=T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','statsTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('facetVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(jsonList$box$config$completeCasesAllVars, nrow(df))
expect_equal(jsonList$box$config$completeCasesAxesVars, nrow(df))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$sampleSizeTable), c('facetVariableDetails','xVariableDetails','size'))
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId'))
expect_equal(nrow(jsonList$completeCasesTable), 3)
expect_equal(names(jsonList$statsTable), c('facetVariableDetails','statistic','pvalue','parameter','method','statsError'))
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
# Multiple vars to facet2 and computed variable metadata
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats=T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','statsTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('facetVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(jsonList$box$config$completeCasesAllVars, nrow(df))
expect_equal(jsonList$box$config$completeCasesAxesVars, nrow(df))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$sampleSizeTable), c('facetVariableDetails','xVariableDetails','size'))
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId'))
expect_equal(nrow(jsonList$completeCasesTable), 4)
expect_equal(names(jsonList$statsTable), c('facetVariableDetails','statistic','pvalue','parameter','method','statsError'))
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
# With continuous overlay (< 9 values)
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'int6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','statsTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('overlayVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(names(jsonList$boxplot$config), c('variables','completeCasesAllVars','completeCasesAxesVars'))
expect_equal(names(jsonList$boxplot$config$variables$variableSpec), c('variableId','entityId'))
expect_equal(jsonList$box$config$completeCasesAllVars, nrow(df))
expect_equal(jsonList$box$config$completeCasesAxesVars, nrow(df))
expect_equal(names(jsonList$sampleSizeTable), c('overlayVariableDetails','xVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId'))
expect_equal(nrow(jsonList$completeCasesTable), 3)
expect_equal(names(jsonList$statsTable), c('xVariableDetails','statistic','pvalue','parameter','method','statsError'))
expect_equal(jsonList$statsTable$xVariableDetails$variableId[1], 'binA')
expect_equal(class(jsonList$statsTable$statistic), 'numeric')
expect_equal(class(jsonList$statsTable$statsError), 'character')
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
})
test_that("box.dt() returns correct information about missing data", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
# Add nMissing missing values to each column
nMissing <- 10
df <- as.data.frame(lapply(testDF, function(x) {x[sample(1:length(x), nMissing, replace=F)] <- NA; x}))
dt <- box.dt(df, variables, 'none', FALSE)
completecasestable <- completeCasesTable(dt)
# Each entry should equal NROW(df) - nMissing
expect_equal(all(completecasestable$completeCases == nrow(df)-nMissing), TRUE)
# number of completeCases should be <= complete cases for each var
expect_equal(all(attr(dt, 'completeCasesAllVars')[1] <= completecasestable$completeCases), TRUE)
expect_equal(attr(dt, 'completeCasesAxesVars')[1] >= attr(dt, 'completeCasesAllVars')[1], TRUE)
dt <- box.dt(df, variables, points = 'none', mean = FALSE, computeStats = TRUE, evilMode = 'strataVariables')
expect_equal(attr(dt, 'completeCasesAxesVars')[1], sum(!is.na(df$entity.contB) & !is.na(df$entity.cat4)))
## Using naToZero to change some NAs to 0
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
imputeZero = TRUE),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
completecasestable <- completeCasesTable(dt)
# Each entry except 'contB' should equal NROW(df) - nMissing
expect_equal(sum(completecasestable$completeCases == nrow(df)-nMissing), 3)
expect_equal(completecasestable[variableDetails=='entity.contB', completeCases], nrow(df))
# number of completeCases should be < complete cases for each var
expect_true(all(attr(dt, 'completeCasesAllVars')[1] < completecasestable$completeCases))
expect_true(attr(dt, 'completeCasesAxesVars')[1] > attr(dt, 'completeCasesAllVars')[1])
dt <- box.dt(df, variables, points = 'none', mean = FALSE, computeStats = TRUE, evilMode = 'strataVariables')
expect_equal(attr(dt, 'completeCasesAxesVars')[1], sum(!is.na(df$entity.cat4)))
# TODO box cant have evilMode = 'allVariables' bc we cant take median of NA for ex
#dt <- box.dt(df, variables, points = 'none', mean = FALSE, computeStats = TRUE, evilMode = 'allVariables')
#expect_equal(attr(dt, 'completeCasesAllVars')[1], sum(complete.cases(df[, map$id, with=FALSE])))
## Collection vars
# Multiple vars to x
# Add nMissing missing values to each column -- TODO address that setting na to zero above changes df
df <- as.data.frame(lapply(testDF, function(x) {x[sample(1:length(x), nMissing, replace=F)] <- NA; x}))
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity"),
new("VariableSpec", variableId = "contC", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
completecasestable <- completeCasesTable(dt)
# Each entry should equal NROW(df) - nMissing
expect_equal(all(completecasestable$completeCases == nrow(df)-nMissing), TRUE)
# number of completeCases should be < complete cases for each var
expect_true(all(attr(dt, 'completeCasesAllVars')[1] <= completecasestable$completeCases))
expect_true(attr(dt, 'completeCasesAllVars')[1] == nrow(df) - nMissing)
expect_true(attr(dt, 'completeCasesAxesVars')[1] >= attr(dt, 'completeCasesAllVars')[1])
expect_true(attr(dt, 'completeCasesAxesVars')[1] == nrow(df))
# Multiple vars to facet1
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity"),
new("VariableSpec", variableId = "contC", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
completecasestable <- completeCasesTable(dt)
# Each entry should equal NROW(df) - nMissing
expect_equal(all(completecasestable$completeCases == nrow(df)-nMissing), TRUE)
# number of completeCases should be < complete cases for each var
expect_true(all(attr(dt, 'completeCasesAllVars')[1] <= completecasestable$completeCases))
expect_true(attr(dt, 'completeCasesAllVars')[1] == nrow(df) - nMissing)
expect_true(attr(dt, 'completeCasesAxesVars')[1] >= attr(dt, 'completeCasesAllVars')[1])
expect_true(attr(dt, 'completeCasesAxesVars')[1] == nrow(df) - nMissing)
})
test_that("box.dt() returns an appropriately sized statistics table", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
df <- as.data.frame(testDF)
## Kruskal-Wallis
# No overlay, no facets
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
statsTable <- statsTable(dt)
expect_equal(nrow(statsTable), 1)
expect_equal(ncol(statsTable), 5)
expect_equal(names(statsTable), c('statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic[[1]]), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue[[1]]), c('scalar', 'numeric'))
expect_equal(class(statsTable$method[[1]]), c('scalar', 'character'))
expect_equal(class(statsTable$statsError[[1]]), c('scalar', 'character'))
# No overlay, one facet
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
statsTable <- statsTable(dt)
expect_equal(nrow(statsTable), uniqueN(df$entity.cat4))
expect_equal(ncol(statsTable), 6)
expect_equal(names(statsTable), c('entity.cat4', 'statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue), c('scalar', 'numeric'))
expect_equal(class(statsTable$method), c('scalar', 'character'))
expect_equal(class(statsTable$statsError), c('scalar', 'character'))
# With overlay, no facets
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
statsTable <- statsTable(dt)
expect_equal(nrow(statsTable), uniqueN(df$entity.cat6))
expect_equal(ncol(statsTable), 6)
expect_equal(names(statsTable), c('entity.cat6', 'statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue), c('scalar', 'numeric'))
expect_equal(class(statsTable$method), c('scalar', 'character'))
expect_equal(class(statsTable$statsError), c('scalar', 'character'))
# With overlay and facet
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
statsTable <- statsTable(dt)
expect_equal(nrow(statsTable), uniqueN(df$entity.cat6)*uniqueN(df$entity.cat4))
expect_equal(ncol(statsTable), 7)
expect_equal(names(statsTable), c('entity.cat6', 'entity.cat4', 'statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue), c('scalar', 'numeric'))
expect_equal(class(statsTable$method), c('scalar', 'character'))
expect_equal(class(statsTable$statsError), c('scalar', 'character'))
## Wilcoxon
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
# No overlay, no facets
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
statsTable <- statsTable(dt)
expect_equal(nrow(statsTable), 1)
expect_equal(ncol(statsTable), 5)
expect_equal(names(statsTable), c('statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic[[1]]), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue[[1]]), c('scalar', 'numeric'))
expect_equal(class(statsTable$method[[1]]), c('scalar', 'character'))
expect_equal(class(statsTable$statsError[[1]]), c('scalar', 'character'))
# No overlay, one facet
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
statsTable <- statsTable(dt)
expect_equal(nrow(statsTable), uniqueN(df$entity.cat4))
expect_equal(ncol(statsTable), 6)
expect_equal(names(statsTable), c('entity.cat4', 'statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue), c('scalar', 'numeric'))
expect_equal(class(statsTable$method), c('scalar', 'character'))
expect_equal(class(statsTable$statsError), c('scalar', 'character'))
# With overlay, no facets
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
statsTable <- statsTable(dt)
expect_equal(nrow(statsTable), uniqueN(df$entity.binA))
expect_equal(ncol(statsTable), 6)
expect_equal(names(statsTable), c('entity.binA', 'statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue), c('scalar', 'numeric'))
expect_equal(class(statsTable$method), c('scalar', 'character'))
expect_equal(class(statsTable$statsError), c('scalar', 'character'))
# With overlay and facet
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
statsTable <- statsTable(dt)
expect_equal(nrow(statsTable), uniqueN(df$entity.binA)*uniqueN(df$entity.cat4))
expect_equal(ncol(statsTable), 7)
expect_equal(names(statsTable), c('entity.binA', 'entity.cat4', 'statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue), c('scalar', 'numeric'))
expect_equal(class(statsTable$method), c('scalar', 'character'))
expect_equal(class(statsTable$statsError), c('scalar', 'character'))
})
test_that("box.dt() returns same shaped outputs for string cats and num cats.", {
df <- testDF
variables_string <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat7', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt_string <- box.dt(df, variables_string)
variables_num <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'int7', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt_num <- box.dt(df, variables_num)
expect_equal(nrow(dt_string), nrow(dt_num))
expect_equal(names(dt_string), names(dt_num))
expect_equal(lapply(dt_string, function(x) {length(x[[1]])}), lapply(dt_num, function(x) {length(x[[1]])}))
variables_string <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat7', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt_string <- box.dt(df, variables_string)
variables_num <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'int7', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt_num <- box.dt(df, variables_num)
expect_equal(nrow(dt_string), nrow(dt_num))
expect_equal(names(dt_string), names(dt_num))
expect_equal(lapply(dt_string, function(x) {length(x[[1]])}), lapply(dt_num, function(x) {length(x[[1]])}))
})
test_that("empty plotReferences are ignored", {
df <- as.data.frame(testDF)
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
# empty plotReference should be ignored
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
# dt is the right shape, *doesnt* include cat5 in col names
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('entity.cat4', 'entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
statsTable <- statsTable(dt)
# statsTable is the right shape
expect_equal(nrow(statsTable), uniqueN(df$entity.binA)*uniqueN(df$entity.cat4))
expect_equal(ncol(statsTable), 7)
expect_equal(names(statsTable), c('entity.binA', 'entity.cat4', 'statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue), c('scalar', 'numeric'))
expect_equal(class(statsTable$method), c('scalar', 'character'))
expect_equal(class(statsTable$statsError), c('scalar', 'character'))
})
VEuPathDB/plot.data documentation built on Feb. 20, 2025, 6:33 p.m.
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context('box')
test_that("box.dt does not fail when there are no complete cases.", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binary1', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cont', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- data.noneComplete[is.na(entity.binary1),]
dt <- box.dt(df, variables, 'none', FALSE, FALSE)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(is.list(dt$label), TRUE)
expect_equal(is.list(dt$min), TRUE)
expect_equal(is.list(dt$q1), TRUE)
expect_equal(is.list(dt$median), TRUE)
expect_equal(is.list(dt$q3), TRUE)
expect_equal(is.list(dt$max), TRUE)
expect_equal(is.list(dt$lowerfence), TRUE)
expect_equal(is.list(dt$upperfence), TRUE)
dt <- box.dt(df, variables, 'none', FALSE, TRUE)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(is.list(dt$label), TRUE)
expect_equal(is.list(dt$min), TRUE)
expect_equal(is.list(dt$q1), TRUE)
expect_equal(is.list(dt$median), TRUE)
expect_equal(is.list(dt$q3), TRUE)
expect_equal(is.list(dt$max), TRUE)
expect_equal(is.list(dt$lowerfence), TRUE)
expect_equal(is.list(dt$upperfence), TRUE)
dt <- box.dt(df, variables, 'none', TRUE, TRUE)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(is.list(dt$label), TRUE)
expect_equal(is.list(dt$min), TRUE)
expect_equal(is.list(dt$q1), TRUE)
expect_equal(is.list(dt$median), TRUE)
expect_equal(is.list(dt$q3), TRUE)
expect_equal(is.list(dt$max), TRUE)
expect_equal(is.list(dt$lowerfence), TRUE)
expect_equal(is.list(dt$upperfence), TRUE)
expect_equal(is.list(dt$mean), TRUE)
dt <- box.dt(df, variables, 'outliers', FALSE, TRUE)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(is.list(dt$label), TRUE)
expect_equal(is.list(dt$min), TRUE)
expect_equal(is.list(dt$q1), TRUE)
expect_equal(is.list(dt$median), TRUE)
expect_equal(is.list(dt$q3), TRUE)
expect_equal(is.list(dt$max), TRUE)
expect_equal(is.list(dt$lowerfence), TRUE)
expect_equal(is.list(dt$upperfence), TRUE)
expect_equal(is.list(dt$outliers), TRUE)
expect_equal(is.list(dt$outliers[[1]]), TRUE)
dt <- box.dt(df, variables, 'all', FALSE, TRUE)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(is.list(dt$label), TRUE)
expect_equal(is.list(dt$min), TRUE)
expect_equal(is.list(dt$q1), TRUE)
expect_equal(is.list(dt$median), TRUE)
expect_equal(is.list(dt$q3), TRUE)
expect_equal(is.list(dt$max), TRUE)
expect_equal(is.list(dt$lowerfence), TRUE)
expect_equal(is.list(dt$upperfence), TRUE)
expect_equal(is.list(dt$rawData), TRUE)
expect_equal(is.list(dt$rawData[[1]]), TRUE)
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binary1', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binary2', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cont', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- data.noneComplete
dt <- box.dt(df, variables, 'none', FALSE, FALSE)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(is.list(dt$label), TRUE)
expect_equal(is.list(dt$min), TRUE)
expect_equal(is.list(dt$q1), TRUE)
expect_equal(is.list(dt$median), TRUE)
expect_equal(is.list(dt$q3), TRUE)
expect_equal(is.list(dt$max), TRUE)
expect_equal(is.list(dt$lowerfence), TRUE)
expect_equal(is.list(dt$upperfence), TRUE)
})
test_that("box.dt() returns a valid plot.data box object", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
expect_is(dt, 'plot.data')
expect_is(dt, 'boxplot')
namedAttrList <- getPDAttributes(dt)
expect_equal(names(namedAttrList),c('variables', 'completeCasesAllVars','completeCasesAxesVars','completeCasesTable','sampleSizeTable','statsTable'))
completeCases <- completeCasesTable(dt)
expect_equal(names(completeCases), c('variableDetails','completeCases'))
expect_equal(nrow(completeCases), 3)
sampleSizes <- sampleSizeTable(dt)
expect_equal(names(sampleSizes), c('entity.cat3','entity.cat4','size'))
expect_equal(nrow(sampleSizes), 3)
expect_equal(names(namedAttrList$statsTable), c('entity.cat4','statistic','pvalue','parameter','method','statsError'))
dt <- box.dt(df, variables, 'all', FALSE, computeStats = T)
expect_is(dt, 'plot.data')
expect_is(dt, 'boxplot')
namedAttrList <- getPDAttributes(dt)
expect_equal(names(namedAttrList),c('variables', 'completeCasesAllVars','completeCasesAxesVars','completeCasesTable','sampleSizeTable','statsTable'))
completeCases <- completeCasesTable(dt)
expect_equal(names(completeCases), c('variableDetails','completeCases'))
expect_equal(nrow(completeCases), 3)
sampleSizes <- sampleSizeTable(dt)
expect_equal(names(sampleSizes), c('entity.cat3','entity.cat4','size'))
expect_equal(nrow(sampleSizes), 3)
expect_equal(names(namedAttrList$statsTable), c('entity.cat4','statistic','pvalue','parameter','method','statsError'))
expect_equal(dt$entity.cat3[[1]], 'cat3_a')
expect_equal(dt$label[[1]], c('cat4_a','cat4_b','cat4_c','cat4_d'))
expect_equal(unlist(lapply(dt$rawData[[1]], length)), c(42,42,29,51))
# Ensure sampleSizeTable and completeCasesTable do not get returned if we do not ask for them.
dt <- box.dt(df, variables, 'all', FALSE, computeStats = T, sampleSizes = FALSE, completeCases = FALSE)
expect_is(dt, 'plot.data')
expect_is(dt, 'boxplot')
namedAttrList <- getPDAttributes(dt)
expect_equal(names(namedAttrList),c('variables','statsTable'))
expect_equal(names(namedAttrList$statsTable), c('entity.cat4','statistic','pvalue','parameter','method','statsError'))
expect_equal(dt$entity.cat3[[1]], 'cat3_a')
expect_equal(dt$label[[1]], c('cat4_a','cat4_b','cat4_c','cat4_d'))
expect_equal(unlist(lapply(dt$rawData[[1]], length)), c(42,42,29,51))
})
test_that("box.dt() returns plot data and config of the appropriate types", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
dt <- box.dt(df, variables, 'none', TRUE)
expect_equal(class(dt$label[[1]]), 'character')
expect_equal(class(dt$min[[1]]), 'numeric')
expect_equal(class(dt$q1[[1]]), 'numeric')
expect_equal(class(dt$median[[1]]), 'numeric')
expect_equal(class(dt$q3[[1]]), 'numeric')
expect_equal(class(dt$max[[1]]), 'numeric')
expect_equal(class(dt$lowerfence[[1]]), 'numeric')
expect_equal(class(dt$upperfence[[1]]), 'numeric')
expect_equal(class(dt$mean[[1]]), 'numeric')
namedAttrList <- getPDAttributes(dt)
expect_equal(class(namedAttrList$completeCasesAllVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$completeCasesAxesVars),c('scalar', 'integer'))
completeCases <- completeCasesTable(dt)
expect_equal(class(unlist(completeCases$variableDetails)), 'character')
expect_equal(class(unlist(completeCases$completeCases)), 'integer')
sampleSizes <- sampleSizeTable(dt)
expect_equal(class(unlist(sampleSizes$entity.cat5)), 'character')
expect_equal(class(unlist(sampleSizes$size)), 'integer')
#w outliers
dt <- box.dt(df, variables, 'outliers', TRUE)
expect_equal(class(dt$label[[1]]), 'character')
expect_equal(class(dt$min[[1]]), 'numeric')
expect_equal(class(dt$q1[[1]]), 'numeric')
expect_equal(class(dt$median[[1]]), 'numeric')
expect_equal(class(dt$q3[[1]]), 'numeric')
expect_equal(class(dt$max[[1]]), 'numeric')
expect_equal(class(dt$lowerfence[[1]]), 'numeric')
expect_equal(class(dt$upperfence[[1]]), 'numeric')
expect_equal(class(dt$mean[[1]]), 'numeric')
#first group has no outliers, want json like [] rather than {}
expect_equal(class(dt$outliers[[1]][[1]]), 'list')
expect_equal(class(dt$outliers[[1]][[3]]), 'numeric')
namedAttrList <- getPDAttributes(dt)
expect_equal(class(namedAttrList$completeCasesAllVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$completeCasesAxesVars),c('scalar', 'integer'))
completeCases <- completeCasesTable(dt)
expect_equal(class(unlist(completeCases$variableDetails)), 'character')
expect_equal(class(unlist(completeCases$completeCases)), 'integer')
sampleSizes <- sampleSizeTable(dt)
expect_equal(class(unlist(sampleSizes$entity.cat5)), 'character')
expect_equal(class(unlist(sampleSizes$size)), 'integer')
#single group
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- testDF[testDF$entity.cat3 == 'cat3_a' & testDF$entity.cat4 == 'cat4_a',]
dt <- box.dt(df, variables, 'none', TRUE)
expect_equal(class(dt$label[[1]]), 'character')
expect_equal(class(dt$min[[1]]), 'numeric')
expect_equal(class(dt$q1[[1]]), 'numeric')
expect_equal(class(dt$median[[1]]), 'numeric')
expect_equal(class(dt$q3[[1]]), 'numeric')
expect_equal(class(dt$max[[1]]), 'numeric')
expect_equal(class(dt$lowerfence[[1]]), 'numeric')
expect_equal(class(dt$upperfence[[1]]), 'numeric')
expect_equal(class(dt$mean[[1]]), 'numeric')
namedAttrList <- getPDAttributes(dt)
expect_equal(class(namedAttrList$completeCasesAllVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$completeCasesAxesVars),c('scalar', 'integer'))
completeCases <- completeCasesTable(dt)
expect_equal(class(unlist(completeCases$variableDetails)), 'character')
expect_equal(class(unlist(completeCases$completeCases)), 'integer')
sampleSizes <- sampleSizeTable(dt)
expect_equal(class(unlist(sampleSizes$entity.cat4)), 'character')
expect_equal(class(unlist(sampleSizes$size)), 'integer')
# With numeric data for the x axis
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'int6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'INTEGER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- testDF
dt <- box.dt(df, variables, 'none', TRUE)
expect_equal(class(dt$label[[1]]), 'character')
expect_equal(class(dt$min[[1]]), 'numeric')
expect_equal(class(dt$q1[[1]]), 'numeric')
expect_equal(class(dt$median[[1]]), 'numeric')
expect_equal(class(dt$q3[[1]]), 'numeric')
expect_equal(class(dt$max[[1]]), 'numeric')
expect_equal(class(dt$lowerfence[[1]]), 'numeric')
expect_equal(class(dt$upperfence[[1]]), 'numeric')
expect_equal(class(dt$mean[[1]]), 'numeric')
namedAttrList <- getPDAttributes(dt)
expect_equal(class(namedAttrList$completeCasesAllVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$completeCasesAxesVars),c('scalar', 'integer'))
completeCases <- completeCasesTable(dt)
expect_equal(class(unlist(completeCases$variableDetails)), 'character')
expect_equal(class(unlist(completeCases$completeCases)), 'integer')
sampleSizes <- sampleSizeTable(dt)
expect_equal(class(unlist(sampleSizes$entity.int6)), 'integer') ## will become a string when written to json
expect_equal(class(unlist(sampleSizes$size)), 'integer')
# With a single numeric box
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'int2', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'INTEGER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- testDF
df[df$entity.int2 == 2] <- 1
dt <- box.dt(df, variables, 'none', TRUE)
expect_equal(class(dt$label[[1]]), 'character')
expect_equal(class(dt$min[[1]]), 'numeric')
expect_equal(class(dt$q1[[1]]), 'numeric')
expect_equal(class(dt$median[[1]]), 'numeric')
expect_equal(class(dt$q3[[1]]), 'numeric')
expect_equal(class(dt$max[[1]]), 'numeric')
expect_equal(class(dt$lowerfence[[1]]), 'numeric')
expect_equal(class(dt$upperfence[[1]]), 'numeric')
expect_equal(class(dt$mean[[1]]), 'numeric')
namedAttrList <- getPDAttributes(dt)
expect_equal(class(namedAttrList$completeCasesAllVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$completeCasesAxesVars),c('scalar', 'integer'))
completeCases <- completeCasesTable(dt)
expect_equal(class(unlist(completeCases$variableDetails)), 'character')
expect_equal(class(unlist(completeCases$completeCases)), 'integer')
sampleSizes <- sampleSizeTable(dt)
expect_equal(class(unlist(sampleSizes$entity.int2)), 'numeric') ## will become a string when written to json
expect_equal(class(unlist(sampleSizes$size)), 'integer')
})
test_that("box.dt() returns an appropriately sized data.table", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
dt <- box.dt(df, variables, 'none', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'mean'))
dt <- box.dt(df, variables, 'outliers', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'outliers'))
dt <- box.dt(df, variables, 'outliers', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'outliers', 'mean'))
dt <- box.dt(df, variables, 'all', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData'))
dt <- box.dt(df, variables, 'all', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData', 'mean'))
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
dt <- box.dt(df, variables, 'none', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'mean'))
dt <- box.dt(df, variables, 'outliers', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'outliers'))
dt <- box.dt(df, variables, 'outliers', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'outliers', 'mean'))
dt <- box.dt(df, variables, 'all', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData'))
dt <- box.dt(df, variables, 'all', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData', 'mean'))
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'int6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'INTEGER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'int7', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),7)
expect_equal(names(dt),c('entity.int7', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
dt <- box.dt(df, variables, 'none', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),7)
expect_equal(names(dt),c('entity.int7', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'mean'))
dt <- box.dt(df, variables, 'outliers', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),7)
expect_equal(names(dt),c('entity.int7', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'outliers'))
dt <- box.dt(df, variables, 'outliers', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),7)
expect_equal(names(dt),c('entity.int7', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'outliers', 'mean'))
dt <- box.dt(df, variables, 'all', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),7)
expect_equal(names(dt),c('entity.int7', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData'))
dt <- box.dt(df, variables, 'all', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),7)
expect_equal(names(dt),c('entity.int7', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData', 'mean'))
# Test single outlier
df <- data.frame('entity.x' = c('group1'), 'entity.y'=c(35.1, 34.2, 36.2, 90.2))
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'x', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'y', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- box.dt(df, variables, 'outliers', FALSE, computeStats = T)
expect_equal(names(dt),c('label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'outliers'))
expect_equal(class(dt$label[[1]]), 'character')
expect_equal(class(dt$min[[1]]), 'numeric')
expect_equal(class(dt$outliers[[1]]), 'list')
# With factors
df <- testDF
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'factor3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- box.dt(df, variables, 'all', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.factor3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData', 'mean'))
expect_equal(class(dt$entity.factor3), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'factor3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- box.dt(df, variables, 'all', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),9)
expect_equal(names(dt),c('panel', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData', 'mean'))
expect_equal(class(dt$panel), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'factor3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'factor6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- box.dt(df, variables, 'all', TRUE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),18)
expect_equal(names(dt),c('panel', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence', 'rawData', 'mean'))
expect_equal(class(dt$panel), 'character')
## Collection vars
# Multiple vars to x
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity"),
new("VariableSpec", variableId = "contC", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt), 3)
expect_equal(names(dt),c('entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
expect_equal(unique(dt$label)[[1]], c('contA','contB','contC'))
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'yAxis')@variableId, 'collectionVarValues')
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'xAxis')@variableId, 'collection')
# Multiple vars to facet1
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity"),
new("VariableSpec", variableId = "contC", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt), 3)
expect_equal(names(dt),c('entity.collection', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
expect_equal(dt$entity.collection, c('contA','contB','contC'))
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'yAxis')@variableId, 'collectionVarValues')
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'facet1')@variableId, 'collection')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'computed'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
displayName = "Label",
displayRangeMin = 0,
displayRangeMax = 1,
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity"),
new("VariableSpec", variableId = "contC", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt), 12)
expect_equal(names(dt),c('panel', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
expect_equal(dt$panel[1], 'contA.||.cat4_a')
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'yAxis')@variableId, 'collectionVarValues')
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'facet1')@variableId, 'collection')
index <- which(purrr::map(as.list(attr(dt, 'variables')), function(x) { x@variableSpec@variableId == 'collectionVarValues' }) %in% TRUE)
collectionVM <- attr(dt, 'variables')[[index]]
expect_equal(collectionVM@displayName, paste(variables[[1]]@displayName, 'values'))
expect_equal(collectionVM@displayRangeMin, variables[[1]]@displayRangeMin)
expect_equal(collectionVM@displayRangeMax, variables[[1]]@displayRangeMax)
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'computed'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
displayName = "Label",
displayRangeMin = 0,
displayRangeMax = 1,
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity"),
new("VariableSpec", variableId = "contC", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt), 12)
expect_equal(names(dt),c('panel', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
expect_equal(dt$panel[1], 'cat4_a.||.contA')
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'yAxis')@variableId, 'collectionVarValues')
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'facet2')@variableId, 'collection')
# Handle only one var sent as a collectionVar
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'computed'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
displayName = "Label",
displayRangeMin = 0,
displayRangeMax = 1,
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt), 3)
expect_equal(names(dt),c('entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
expect_equal(unique(dt$label)[[1]], c('contB'))
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'yAxis')@variableId, 'collectionVarValues')
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'xAxis')@variableId, 'collection')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'computed'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
displayName = "Label",
displayRangeMin = 0,
displayRangeMax = 1,
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
expect_is(dt, 'data.table')
expect_equal(nrow(dt), 1)
expect_equal(names(dt),c('entity.collection', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
expect_equal(dt$entity.collection, c('contB'))
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'yAxis')@variableId, 'collectionVarValues')
expect_equal(veupathUtils::findVariableSpecFromPlotRef(attr(dt, 'variables'), 'facet1')@variableId, 'collection')
})
test_that("box() returns appropriately formatted json", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
df <- as.data.frame(testDF)
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','statsTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('overlayVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(jsonList$boxplot$data$overlayVariableDetails$variableId[1], 'cat3')
expect_equal(names(jsonList$boxplot$config), c('variables','completeCasesAllVars','completeCasesAxesVars'))
expect_equal(names(jsonList$sampleSizeTable), c('overlayVariableDetails','xVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(jsonList$sampleSizeTable$xVariableDetails$variableId[[1]], 'cat4')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId'))
expect_equal(jsonList$completeCasesTable$variableDetails$variableId, c('cat4', 'contB', 'cat3'))
expect_equal(names(jsonList$statsTable), c('xVariableDetails','statistic','pvalue','parameter','method','statsError'))
expect_equal(jsonList$statsTable$xVariableDetails$variableId[1], 'cat4')
expect_equal(class(jsonList$statsTable$statistic), 'numeric')
expect_equal(class(jsonList$statsTable$statsError), 'character')
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
displayName = "yLabel",
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
displayName = "groupLabel",
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
displayName = "panelLabel",
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','statsTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('overlayVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(jsonList$boxplot$data$overlayVariableDetails$variableId[1], 'cat3')
expect_equal(names(jsonList$boxplot$config), c('variables','completeCasesAllVars','completeCasesAxesVars'))
expect_equal(names(jsonList$boxplot$config$variables$variableSpec), c('variableId','entityId'))
expect_equal(jsonList$boxplot$config$variables$variableSpec$variableId, c('contB','cat3','cat4'))
expect_equal(names(jsonList$sampleSizeTable), c('overlayVariableDetails','xVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(jsonList$sampleSizeTable$xVariableDetails$variableId[[1]], 'cat4')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId','displayLabel'))
expect_equal(jsonList$completeCasesTable$variableDetails$variableId, c('cat4', 'contB', 'cat3'))
expect_equal(names(jsonList$statsTable), c('xVariableDetails','statistic','pvalue','parameter','method','statsError'))
expect_equal(jsonList$statsTable$xVariableDetails$variableId[1], 'cat4')
expect_equal(class(jsonList$statsTable$statistic), 'numeric')
expect_equal(class(jsonList$statsTable$statsError), 'character')
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
# Ensure sampleSizeTable and completeCasesTable are not part of json if we do not ask for them.
# Make sure to also ask for the stats table to check that all goes well with this special box-specific table
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T, sampleSizes = FALSE, completeCases = FALSE)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','statsTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('overlayVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(jsonList$boxplot$data$overlayVariableDetails$variableId[1], 'cat3')
expect_equal(names(jsonList$boxplot$config), c('variables'))
expect_equal(names(jsonList$boxplot$config$variables$variableSpec), c('variableId','entityId'))
expect_equal(jsonList$boxplot$config$variables$variableSpec$variableId, c('contB','cat3','cat4'))
expect_equal(names(jsonList$statsTable), c('xVariableDetails','statistic','pvalue','parameter','method','statsError'))
expect_equal(jsonList$statsTable$xVariableDetails$variableId[1], 'cat4')
expect_equal(class(jsonList$statsTable$statistic), 'numeric')
expect_equal(class(jsonList$statsTable$statsError), 'character')
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
displayName = "yLabel",
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
displayName = "groupLabel",
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
displayName = "panelLabel",
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','statsTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('facetVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(names(jsonList$boxplot$config), c('variables','completeCasesAllVars','completeCasesAxesVars'))
expect_equal(names(jsonList$boxplot$config$variables$variableSpec), c('variableId','entityId'))
expect_equal(names(jsonList$sampleSizeTable), c('facetVariableDetails','xVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId','displayLabel'))
expect_equal(names(jsonList$statsTable), c('facetVariableDetails','statistic','pvalue','parameter','method','statsError'))
expect_equal(jsonList$statsTable$facetVariableDetails[[1]]$variableId, 'cat3')
expect_equal(class(jsonList$statsTable$statistic), 'numeric')
expect_equal(class(jsonList$statsTable$statsError), 'character')
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
displayName = "panelLabel",
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList$boxplot$config$variables$variableSpec), c('variableId','entityId'))
expect_equal(names(jsonList$boxplot$data$overlayVariableDetails), c('variableId','entityId','value'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId','displayLabel'))
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
displayName = "panelLabel",
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, TRUE, NULL, evilMode = 'strataVariables')
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
# no stats table even if requested, when evilMode is 'strataVariables'
expect_equal(names(jsonList), c('boxplot', 'sampleSizeTable', 'completeCasesTable'))
expect_equal(names(jsonList$boxplot$config$variables$variableSpec), c('variableId','entityId'))
expect_equal(names(jsonList$boxplot$data$overlayVariableDetails), c('variableId','entityId','value'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId','displayLabel'))
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','statsTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('overlayVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(names(jsonList$boxplot$config), c('variables','completeCasesAllVars','completeCasesAxesVars'))
expect_equal(names(jsonList$boxplot$config$variables$variableSpec), c('variableId','entityId'))
expect_equal(names(jsonList$sampleSizeTable), c('overlayVariableDetails','xVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId'))
expect_equal(names(jsonList$statsTable), c('xVariableDetails','statistic','pvalue','parameter','method','statsError'))
expect_equal(jsonList$statsTable$xVariableDetails$variableId[1], 'binA')
expect_equal(class(jsonList$statsTable$statistic), 'numeric')
expect_equal(class(jsonList$statsTable$statsError), 'character')
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
displayName = "panelLabel",
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','statsTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
expect_equal(names(jsonList$boxplot$config), c('variables','completeCasesAllVars','completeCasesAxesVars'))
expect_equal(names(jsonList$boxplot$config$variables$variableSpec), c('variableId','entityId'))
expect_equal(names(jsonList$sampleSizeTable), c('xVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId','displayLabel'))
expect_equal(names(jsonList$statsTable), c('statistic','pvalue','parameter','method','statsError'))
expect_equal(class(jsonList$statsTable$statistic), 'integer')
expect_equal(length(jsonList$statsTable$statistic), 1)
expect_equal(class(jsonList$statsTable$statsError), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList$statsTable), c('statistic','pvalue','parameter','method','statsError'))
expect_equal(class(jsonList$statsTable$statistic), 'numeric')
expect_equal(length(jsonList$statsTable$statistic), 1)
expect_equal(class(jsonList$statsTable$statsError), 'character')
# Multiple vars for x and computed variable metadata
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'computed'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
displayName = "Label",
displayRangeMin = 0.5,
displayRangeMax = 1.5,
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('overlayVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(jsonList$boxplot$config$completeCasesAllVars, nrow(df))
expect_equal(jsonList$boxplot$config$completeCasesAxesVars, nrow(df))
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$sampleSizeTable), c('overlayVariableDetails','xVariableDetails','size'))
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId'))
expect_equal(nrow(jsonList$completeCasesTable), 3)
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
# Collection var only
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'computed'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
displayName = "Label",
displayRangeMin = 0.5,
displayRangeMax = 1.5,
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity")
))
)
))
dt <- box.dt(df, variables, 'none', FALSE)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(jsonList$boxplot$config$completeCasesAllVars, nrow(df))
expect_equal(jsonList$boxplot$config$completeCasesAxesVars, nrow(df))
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$sampleSizeTable), c('xVariableDetails','size'))
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId'))
expect_equal(nrow(jsonList$completeCasesTable), 2)
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
# Multiple vars to facet1 and computed variable metadata
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'computed'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
displayName = "Label",
displayRangeMin = 0.5,
displayRangeMax = 1.5,
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats=T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','statsTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('facetVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(jsonList$box$config$completeCasesAllVars, nrow(df))
expect_equal(jsonList$box$config$completeCasesAxesVars, nrow(df))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$sampleSizeTable), c('facetVariableDetails','xVariableDetails','size'))
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId'))
expect_equal(nrow(jsonList$completeCasesTable), 3)
expect_equal(names(jsonList$statsTable), c('facetVariableDetails','statistic','pvalue','parameter','method','statsError'))
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
# Multiple vars to facet2 and computed variable metadata
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats=T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','statsTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('facetVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(jsonList$box$config$completeCasesAllVars, nrow(df))
expect_equal(jsonList$box$config$completeCasesAxesVars, nrow(df))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$sampleSizeTable), c('facetVariableDetails','xVariableDetails','size'))
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId'))
expect_equal(nrow(jsonList$completeCasesTable), 4)
expect_equal(names(jsonList$statsTable), c('facetVariableDetails','statistic','pvalue','parameter','method','statsError'))
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
# With continuous overlay (< 9 values)
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'int6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList), c('boxplot','sampleSizeTable','statsTable','completeCasesTable'))
expect_equal(names(jsonList$boxplot), c('data','config'))
expect_equal(names(jsonList$boxplot$data), c('overlayVariableDetails','label','min','q1','median','q3','max','lowerfence','upperfence'))
expect_equal(names(jsonList$boxplot$config), c('variables','completeCasesAllVars','completeCasesAxesVars'))
expect_equal(names(jsonList$boxplot$config$variables$variableSpec), c('variableId','entityId'))
expect_equal(jsonList$box$config$completeCasesAllVars, nrow(df))
expect_equal(jsonList$box$config$completeCasesAxesVars, nrow(df))
expect_equal(names(jsonList$sampleSizeTable), c('overlayVariableDetails','xVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$xVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails','completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId','entityId'))
expect_equal(nrow(jsonList$completeCasesTable), 3)
expect_equal(names(jsonList$statsTable), c('xVariableDetails','statistic','pvalue','parameter','method','statsError'))
expect_equal(jsonList$statsTable$xVariableDetails$variableId[1], 'binA')
expect_equal(class(jsonList$statsTable$statistic), 'numeric')
expect_equal(class(jsonList$statsTable$statsError), 'character')
expect_equal(class(jsonList$boxplot$data$label[[1]]), 'character')
})
test_that("box.dt() returns correct information about missing data", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
# Add nMissing missing values to each column
nMissing <- 10
df <- as.data.frame(lapply(testDF, function(x) {x[sample(1:length(x), nMissing, replace=F)] <- NA; x}))
dt <- box.dt(df, variables, 'none', FALSE)
completecasestable <- completeCasesTable(dt)
# Each entry should equal NROW(df) - nMissing
expect_equal(all(completecasestable$completeCases == nrow(df)-nMissing), TRUE)
# number of completeCases should be <= complete cases for each var
expect_equal(all(attr(dt, 'completeCasesAllVars')[1] <= completecasestable$completeCases), TRUE)
expect_equal(attr(dt, 'completeCasesAxesVars')[1] >= attr(dt, 'completeCasesAllVars')[1], TRUE)
dt <- box.dt(df, variables, points = 'none', mean = FALSE, computeStats = TRUE, evilMode = 'strataVariables')
expect_equal(attr(dt, 'completeCasesAxesVars')[1], sum(!is.na(df$entity.contB) & !is.na(df$entity.cat4)))
## Using naToZero to change some NAs to 0
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
imputeZero = TRUE),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
completecasestable <- completeCasesTable(dt)
# Each entry except 'contB' should equal NROW(df) - nMissing
expect_equal(sum(completecasestable$completeCases == nrow(df)-nMissing), 3)
expect_equal(completecasestable[variableDetails=='entity.contB', completeCases], nrow(df))
# number of completeCases should be < complete cases for each var
expect_true(all(attr(dt, 'completeCasesAllVars')[1] < completecasestable$completeCases))
expect_true(attr(dt, 'completeCasesAxesVars')[1] > attr(dt, 'completeCasesAllVars')[1])
dt <- box.dt(df, variables, points = 'none', mean = FALSE, computeStats = TRUE, evilMode = 'strataVariables')
expect_equal(attr(dt, 'completeCasesAxesVars')[1], sum(!is.na(df$entity.cat4)))
# TODO box cant have evilMode = 'allVariables' bc we cant take median of NA for ex
#dt <- box.dt(df, variables, points = 'none', mean = FALSE, computeStats = TRUE, evilMode = 'allVariables')
#expect_equal(attr(dt, 'completeCasesAllVars')[1], sum(complete.cases(df[, map$id, with=FALSE])))
## Collection vars
# Multiple vars to x
# Add nMissing missing values to each column -- TODO address that setting na to zero above changes df
df <- as.data.frame(lapply(testDF, function(x) {x[sample(1:length(x), nMissing, replace=F)] <- NA; x}))
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity"),
new("VariableSpec", variableId = "contC", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
completecasestable <- completeCasesTable(dt)
# Each entry should equal NROW(df) - nMissing
expect_equal(all(completecasestable$completeCases == nrow(df)-nMissing), TRUE)
# number of completeCases should be < complete cases for each var
expect_true(all(attr(dt, 'completeCasesAllVars')[1] <= completecasestable$completeCases))
expect_true(attr(dt, 'completeCasesAllVars')[1] == nrow(df) - nMissing)
expect_true(attr(dt, 'completeCasesAxesVars')[1] >= attr(dt, 'completeCasesAllVars')[1])
expect_true(attr(dt, 'completeCasesAxesVars')[1] == nrow(df))
# Multiple vars to facet1
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'collection', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
isCollection = TRUE,
members = new("VariableSpecList", SimpleList(
new("VariableSpec", variableId = "contB", entityId = "entity"),
new("VariableSpec", variableId = "contA", entityId = "entity"),
new("VariableSpec", variableId = "contC", entityId = "entity")
))
),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE)
completecasestable <- completeCasesTable(dt)
# Each entry should equal NROW(df) - nMissing
expect_equal(all(completecasestable$completeCases == nrow(df)-nMissing), TRUE)
# number of completeCases should be < complete cases for each var
expect_true(all(attr(dt, 'completeCasesAllVars')[1] <= completecasestable$completeCases))
expect_true(attr(dt, 'completeCasesAllVars')[1] == nrow(df) - nMissing)
expect_true(attr(dt, 'completeCasesAxesVars')[1] >= attr(dt, 'completeCasesAllVars')[1])
expect_true(attr(dt, 'completeCasesAxesVars')[1] == nrow(df) - nMissing)
})
test_that("box.dt() returns an appropriately sized statistics table", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
df <- as.data.frame(testDF)
## Kruskal-Wallis
# No overlay, no facets
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
statsTable <- statsTable(dt)
expect_equal(nrow(statsTable), 1)
expect_equal(ncol(statsTable), 5)
expect_equal(names(statsTable), c('statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic[[1]]), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue[[1]]), c('scalar', 'numeric'))
expect_equal(class(statsTable$method[[1]]), c('scalar', 'character'))
expect_equal(class(statsTable$statsError[[1]]), c('scalar', 'character'))
# No overlay, one facet
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
statsTable <- statsTable(dt)
expect_equal(nrow(statsTable), uniqueN(df$entity.cat4))
expect_equal(ncol(statsTable), 6)
expect_equal(names(statsTable), c('entity.cat4', 'statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue), c('scalar', 'numeric'))
expect_equal(class(statsTable$method), c('scalar', 'character'))
expect_equal(class(statsTable$statsError), c('scalar', 'character'))
# With overlay, no facets
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
statsTable <- statsTable(dt)
expect_equal(nrow(statsTable), uniqueN(df$entity.cat6))
expect_equal(ncol(statsTable), 6)
expect_equal(names(statsTable), c('entity.cat6', 'statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue), c('scalar', 'numeric'))
expect_equal(class(statsTable$method), c('scalar', 'character'))
expect_equal(class(statsTable$statsError), c('scalar', 'character'))
# With overlay and facet
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
statsTable <- statsTable(dt)
expect_equal(nrow(statsTable), uniqueN(df$entity.cat6)*uniqueN(df$entity.cat4))
expect_equal(ncol(statsTable), 7)
expect_equal(names(statsTable), c('entity.cat6', 'entity.cat4', 'statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue), c('scalar', 'numeric'))
expect_equal(class(statsTable$method), c('scalar', 'character'))
expect_equal(class(statsTable$statsError), c('scalar', 'character'))
## Wilcoxon
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
# No overlay, no facets
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
statsTable <- statsTable(dt)
expect_equal(nrow(statsTable), 1)
expect_equal(ncol(statsTable), 5)
expect_equal(names(statsTable), c('statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic[[1]]), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue[[1]]), c('scalar', 'numeric'))
expect_equal(class(statsTable$method[[1]]), c('scalar', 'character'))
expect_equal(class(statsTable$statsError[[1]]), c('scalar', 'character'))
# No overlay, one facet
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
statsTable <- statsTable(dt)
expect_equal(nrow(statsTable), uniqueN(df$entity.cat4))
expect_equal(ncol(statsTable), 6)
expect_equal(names(statsTable), c('entity.cat4', 'statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue), c('scalar', 'numeric'))
expect_equal(class(statsTable$method), c('scalar', 'character'))
expect_equal(class(statsTable$statsError), c('scalar', 'character'))
# With overlay, no facets
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
statsTable <- statsTable(dt)
expect_equal(nrow(statsTable), uniqueN(df$entity.binA))
expect_equal(ncol(statsTable), 6)
expect_equal(names(statsTable), c('entity.binA', 'statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue), c('scalar', 'numeric'))
expect_equal(class(statsTable$method), c('scalar', 'character'))
expect_equal(class(statsTable$statsError), c('scalar', 'character'))
# With overlay and facet
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
statsTable <- statsTable(dt)
expect_equal(nrow(statsTable), uniqueN(df$entity.binA)*uniqueN(df$entity.cat4))
expect_equal(ncol(statsTable), 7)
expect_equal(names(statsTable), c('entity.binA', 'entity.cat4', 'statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue), c('scalar', 'numeric'))
expect_equal(class(statsTable$method), c('scalar', 'character'))
expect_equal(class(statsTable$statsError), c('scalar', 'character'))
})
test_that("box.dt() returns same shaped outputs for string cats and num cats.", {
df <- testDF
variables_string <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat7', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt_string <- box.dt(df, variables_string)
variables_num <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'int7', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt_num <- box.dt(df, variables_num)
expect_equal(nrow(dt_string), nrow(dt_num))
expect_equal(names(dt_string), names(dt_num))
expect_equal(lapply(dt_string, function(x) {length(x[[1]])}), lapply(dt_num, function(x) {length(x[[1]])}))
variables_string <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat7', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt_string <- box.dt(df, variables_string)
variables_num <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'int7', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt_num <- box.dt(df, variables_num)
expect_equal(nrow(dt_string), nrow(dt_num))
expect_equal(names(dt_string), names(dt_num))
expect_equal(lapply(dt_string, function(x) {length(x[[1]])}), lapply(dt_num, function(x) {length(x[[1]])}))
})
test_that("empty plotReferences are ignored", {
df <- as.data.frame(testDF)
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contB', entityId = 'entity'),
plotReference = new("PlotReference", value = 'yAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
# empty plotReference should be ignored
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL'))
))
dt <- box.dt(df, variables, 'none', FALSE, computeStats = T)
# dt is the right shape, *doesnt* include cat5 in col names
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('entity.cat4', 'entity.cat3', 'label', 'min', 'q1', 'median', 'q3', 'max', 'lowerfence', 'upperfence'))
statsTable <- statsTable(dt)
# statsTable is the right shape
expect_equal(nrow(statsTable), uniqueN(df$entity.binA)*uniqueN(df$entity.cat4))
expect_equal(ncol(statsTable), 7)
expect_equal(names(statsTable), c('entity.binA', 'entity.cat4', 'statistic', 'pvalue', 'parameter', 'method', 'statsError'))
expect_equal(class(statsTable$statistic), c('scalar', 'numeric'))
expect_equal(class(statsTable$pvalue), c('scalar', 'numeric'))
expect_equal(class(statsTable$method), c('scalar', 'character'))
expect_equal(class(statsTable$statsError), c('scalar', 'character'))
})
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