tests/testthat/test-histogram.R
In VEuPathDB/plot.data: Create `data.table`s of Ready to Plot Data
context('histogram')
test_that("histogram.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 = 'cont', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- data.noneComplete[is.na(entity.cont),]
dt <- histogram.dt(df, variables, binWidth = .3, value='count', barmode = 'overlay', 'binWidth', NULL)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(as.character(attr$viewport$xMin), "")
expect_equal(is.na(attr$binSlider$min), TRUE)
expect_equal(as.character(attr$summary$min), "")
expect_equal(is.na(attr$binSpec$value), TRUE)
expect_equal(is.list(dt$binLabel), TRUE)
expect_equal(is.list(dt$binStart), TRUE)
expect_equal(is.list(dt$binEnd), TRUE)
expect_equal(is.list(dt$value), TRUE)
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', 'binWidth', NULL)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(as.character(attr$viewport$xMin), "")
expect_equal(is.na(attr$binSlider$min), TRUE)
expect_equal(as.character(attr$summary$min), "")
expect_equal(is.na(attr$binSpec$value), TRUE)
expect_equal(is.list(dt$binLabel), TRUE)
expect_equal(is.list(dt$binStart), TRUE)
expect_equal(is.list(dt$binEnd), TRUE)
expect_equal(is.list(dt$value), TRUE)
dt <- histogram.dt(df, variables, binWidth = .3, value='proportion', barmode = 'overlay', 'binWidth', NULL)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(as.character(attr$viewport$xMin), "")
expect_equal(is.na(attr$binSlider$min), TRUE)
expect_equal(as.character(attr$summary$min), "")
expect_equal(is.na(attr$binSpec$value), TRUE)
expect_equal(is.list(dt$binLabel), TRUE)
expect_equal(is.list(dt$binStart), TRUE)
expect_equal(is.list(dt$binEnd), TRUE)
expect_equal(is.list(dt$value), TRUE)
dt <- histogram.dt(df, variables, binWidth = .3, value='count', barmode = 'stack', 'binWidth', NULL)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(as.character(attr$viewport$xMin), "")
expect_equal(is.na(attr$binSlider$min), TRUE)
expect_equal(as.character(attr$summary$min), "")
expect_equal(is.na(attr$binSpec$value), TRUE)
expect_equal(is.list(dt$binLabel), TRUE)
expect_equal(is.list(dt$binStart), TRUE)
expect_equal(is.list(dt$binEnd), TRUE)
expect_equal(is.list(dt$value), TRUE)
dt <- histogram.dt(df, variables, binWidth = .3, value='count', barmode = 'overlay', 'numBins', NULL)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(as.character(attr$viewport$xMin), "")
expect_equal(is.na(attr$binSlider$min), TRUE)
expect_equal(as.character(attr$summary$min), "")
expect_equal(is.na(attr$binSpec$value), TRUE)
expect_equal(is.list(dt$binLabel), TRUE)
expect_equal(is.list(dt$binStart), TRUE)
expect_equal(is.list(dt$binEnd), TRUE)
expect_equal(is.list(dt$value), TRUE)
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'binary2', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cont', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- data.noneComplete
dt <- histogram.dt(df, variables, binWidth = .3, value='count', barmode = 'overlay', 'binWidth', NULL)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(as.character(attr$viewport$xMin), "")
expect_equal(is.na(attr$binSlider$min), TRUE)
expect_equal(as.character(attr$summary$min), "")
expect_equal(is.na(attr$binSpec$value), TRUE)
expect_equal(is.list(dt$binLabel), TRUE)
expect_equal(is.list(dt$binStart), TRUE)
expect_equal(is.list(dt$binEnd), TRUE)
expect_equal(is.list(dt$value), TRUE)
})
test_that("histogram.dt() returns requested numBins/ binWidth", {
variables <- new("VariableMetadataList", SimpleList(
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 = '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 = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = .3, value='count', barmode = 'overlay', binReportValue, viewport)
expect_equal(round(as.numeric(binSpec(dt)$value),1), .3)
expect_equal(getMode(as.numeric(unlist(dt$binEnd)) - as.numeric(unlist(dt$binStart))), .3)
dt <- histogram.dt(df, variables, binWidth = 1.5, value='count', barmode = 'overlay', binReportValue, viewport)
expect_equal(round(as.numeric(binSpec(dt)$value),1), 1.5)
expect_equal(round(getMode(as.numeric(unlist(dt$binEnd)) - as.numeric(unlist(dt$binStart))),1), 1.5)
binReportValue <- 'numBins'
binWidth <- numBinsToBinWidth(df$entity.contA, 5)
dt <- histogram.dt(df, variables, binWidth = binWidth, value='count', barmode = 'overlay', binReportValue, viewport)
expect_equal(as.numeric(binSpec(dt)$value), 5) # ensure we get the correct number of bins
expect_true(max(as.numeric(unlist(dt$binEnd)) - as.numeric(unlist(dt$binStart)) - binWidth) < 0.1) # Tolerance 0.1
numericLabelsStart <- unlist(lapply(unlist(dt$binLabel), function(x) as.numeric(stringi::stri_split_regex(x, ",|]|\\(|\\[")[[1]][2])))
numericLabelsEnd <- unlist(lapply(unlist(dt$binLabel), function(x) as.numeric(stringi::stri_split_regex(x, ",|]|\\(|\\[|\\)")[[1]][3])))
expect_true(max(numericLabelsEnd - numericLabelsStart) - binWidth < 0.1) # Label tolerance
binReportValue <- 'numBins'
binWidth <- numBinsToBinWidth(df$entity.contA, 15)
dt <- histogram.dt(df, variables, binWidth = binWidth, value='count', barmode = 'overlay', binReportValue, viewport)
expect_equal(as.numeric(binSpec(dt)$value), 15) # ensure we get the correct number of bins
expect_true(max(as.numeric(unlist(dt$binEnd)) - as.numeric(unlist(dt$binStart)) - binWidth) < 0.1) # Tolerance 0.1
numericLabelsStart <- unlist(lapply(unlist(dt$binLabel), function(x) as.numeric(stringi::stri_split_regex(x, ",|]|\\(|\\[")[[1]][2])))
numericLabelsEnd <- unlist(lapply(unlist(dt$binLabel), function(x) as.numeric(stringi::stri_split_regex(x, ",|]|\\(|\\[|\\)")[[1]][3])))
expect_true(max(numericLabelsEnd - numericLabelsStart) - binWidth < 0.1) # Label tolerance
})
test_that("histogram.dt() returns a valid plot.data histogram object", {
variables <- new("VariableMetadataList", SimpleList(
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 = '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 = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'plot.data')
expect_is(dt, 'histogram')
namedAttrList <- getPDAttributes(dt)
expect_equal(names(namedAttrList),c('variables', 'completeCasesAllVars','completeCasesAxesVars','completeCasesTable','sampleSizeTable','summary', 'viewport', 'binSpec', 'binSlider'))
completeCases <- completeCasesTable(dt)
expect_equal(names(completeCases), c('variableDetails','completeCases'))
expect_equal(nrow(completeCases), 3)
sampleSizes <- sampleSizeTable(dt)
expect_equal(names(sampleSizes), c('panel','size'))
expect_equal(nrow(sampleSizes), 12)
expect_equal(names(namedAttrList$summary), c('min','q1','median','mean','q3','max'))
expect_equal(names(viewport(dt)), c('xMin','xMax'))
expect_equal(names(binSlider(dt)), c('min','max','step'))
expect_equal(names(namedAttrList$binSpec), c('type','value'))
expect_equal(round(as.numeric(namedAttrList$binSpec$value),4), 1.8032)
expect_equal(as.character(namedAttrList$binSpec$type), 'binWidth')
variables <- new("VariableMetadataList", SimpleList(
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 = '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 = 'dateA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'DATE'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
viewport <- list('xMin'=min(df$entity.dateA), 'xMax'=max(df$entity.dateA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = 'month', value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'plot.data')
expect_is(dt, 'histogram')
namedAttrList <- getPDAttributes(dt)
expect_equal(names(namedAttrList),c('variables', 'completeCasesAllVars','completeCasesAxesVars','completeCasesTable','sampleSizeTable','summary', 'viewport', 'binSpec', 'binSlider'))
completeCases <- completeCasesTable(dt)
expect_equal(names(completeCases), c('variableDetails','completeCases'))
expect_equal(nrow(completeCases), 3)
sampleSizes <- sampleSizeTable(dt)
expect_equal(names(sampleSizes), c('panel','size'))
expect_equal(nrow(sampleSizes), 12)
expect_equal(names(namedAttrList$summary), c('min','q1','median','mean','q3','max'))
expect_equal(names(viewport(dt)), c('xMin','xMax'))
expect_equal(names(binSlider(dt)), c('min','max','step'))
expect_equal(names(namedAttrList$binSpec), c('type','value','units'))
expect_equal(as.numeric(namedAttrList$binSpec$value),1)
expect_equal(as.character(namedAttrList$binSpec$type),'binWidth')
expect_equal(as.character(namedAttrList$binSpec$unit),'month')
# expect_true(all(grepl('T00:00:00', unlist(dt$binStart))))
# expect_true(all(grepl('T00:00:00', unlist(dt$binEnd))))
# expect_true(!any(grepl('T00:00:00', unlist(dt$binLabel))))
# Ensure sampleSizeTable and completeCasesTable do not get returned if we do not ask for them.
dt <- histogram.dt(df, variables, binWidth = 'month', value='count', barmode = 'overlay', binReportValue, viewport, sampleSizes = FALSE, completeCases = FALSE)
expect_is(dt, 'plot.data')
expect_is(dt, 'histogram')
namedAttrList <- getPDAttributes(dt)
expect_equal(names(namedAttrList),c('variables','summary', 'viewport', 'binSpec', 'binSlider'))
expect_equal(names(namedAttrList$summary), c('min','q1','median','mean','q3','max'))
expect_equal(names(viewport(dt)), c('xMin','xMax'))
expect_equal(names(binSlider(dt)), c('min','max','step'))
expect_equal(names(namedAttrList$binSpec), c('type','value','units'))
expect_equal(as.numeric(namedAttrList$binSpec$value),1)
expect_equal(as.character(namedAttrList$binSpec$type),'binWidth')
expect_equal(as.character(namedAttrList$binSpec$unit),'month')
})
test_that("histogram.dt() returns plot data and config of the appropriate types", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_equal(class(unlist(dt$panel)), 'character')
expect_equal(class(unlist(dt$binLabel)), 'character')
expect_equal(class(unlist(dt$binStart)), 'character')
expect_equal(class(unlist(dt$binEnd)), 'character')
expect_equal(class(unlist(dt$value)), 'integer')
namedAttrList <- getPDAttributes(dt)
expect_equal(class(namedAttrList$completeCasesAllVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$completeCasesAxesVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$summary$min),c('scalar', 'character'))
expect_equal(class(namedAttrList$viewport$xMin),c('scalar', 'character'))
expect_equal(class(namedAttrList$binSlider$min),c('scalar', 'numeric'))
expect_equal(class(namedAttrList$binSpec$type),c('scalar', 'character'))
expect_equal(class(namedAttrList$binSpec$value),c('scalar', 'numeric'))
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$panel)), 'character')
expect_equal(class(unlist(sampleSizes$size)), 'integer')
variables <- new("VariableMetadataList", SimpleList(
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 = '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 = 'dateA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'DATE'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
viewport <- list('xMin'=min(df$entity.dateA), 'xMax'=max(df$entity.dateA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = 'month', value='count', barmode = 'overlay', binReportValue, viewport)
expect_equal(class(unlist(dt$panel)), 'character')
expect_equal(class(unlist(dt$binLabel)), 'character')
expect_equal(class(unlist(dt$binStart)), 'character')
expect_equal(class(unlist(dt$binEnd)), 'character')
expect_equal(class(unlist(dt$value)), 'integer')
namedAttrList <- getPDAttributes(dt)
expect_equal(class(namedAttrList$completeCasesAllVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$completeCasesAxesVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$summary$min),c('scalar', 'character'))
expect_equal(class(namedAttrList$viewport$xMin),c('scalar', 'character'))
expect_equal(class(namedAttrList$binSlider$min),c('scalar', 'numeric'))
expect_equal(class(namedAttrList$binSpec$type),c('scalar', 'character'))
expect_equal(class(namedAttrList$binSpec$value),c('scalar', 'numeric'))
completeCases <- completeCasesTable(dt)
expect_equal(class(unlist(completeCases$variableDetails)), 'character')
expect_equal(class(unlist(completeCases$completeCases)), 'integer')
sampleSizes <- sampleSizeTable(dt)
expect_equal(class(unlist(sampleSizes$panel)), 'character')
expect_equal(class(unlist(sampleSizes$size)), 'integer')
})
test_that("histogram.dt() returns bins according to specified viewport", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
binReportValue <- 'binWidth'
viewport <- list('xMin'=-1.5,'xMax'=2.5)
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
maxBinStart <- as.numeric(max(unlist(lapply(dt$binStart, max))))
expect_true(maxBinStart <= viewport$xMax)
minBinEnd <- as.numeric(min(unlist(lapply(dt$binEnd, min))))
expect_true(minBinEnd >= viewport$xMin)
#figure how to test for expanding to viewport, since we dont explicitly return 0 value bins..
})
test_that("histogram.dt() returns an appropriately sized data.table", {
df <- as.data.frame(testDF)
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('panel', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(all(grepl('.||.', dt$panel, fixed=T)), TRUE)
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport = viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('panel', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(all(grepl('.||.', dt$panel, fixed=T)), TRUE)
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport = viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('panel', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(all(grepl('.||.', dt$panel, fixed=T)), TRUE)
variables <- new("VariableMetadataList", SimpleList(
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 = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('entity.cat3', 'entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('entity.cat3', 'entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('entity.cat3', 'entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
variables <- new("VariableMetadataList", SimpleList(
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 = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'binLabel', 'value', 'binStart', 'binEnd'))
variables <- new("VariableMetadataList", SimpleList(
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 = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),4)
expect_equal(names(dt),c('entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),4)
expect_equal(names(dt),c('entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),4)
expect_equal(names(dt),c('entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('binLabel', 'value', 'binStart', 'binEnd'))
#this for dates
variables <- new("VariableMetadataList", SimpleList(
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 = '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 = 'dateA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'DATE'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
viewport <- list('xMin'=min(df$entity.dateA), 'xMax'=max(df$entity.dateA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('panel', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(all(grepl('.||.', dt$panel, fixed=T)), TRUE)
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('panel', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(all(grepl('.||.', dt$panel, fixed=T)), TRUE)
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('panel', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(all(grepl('.||.', dt$panel, fixed=T)), TRUE)
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'dateA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'DATE'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
viewport <- list('xMin'=min(df$entity.dateA), 'xMax'=max(df$entity.dateA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('entity.cat3', 'entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('entity.cat3', 'entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('entity.cat3', 'entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
variables <- new("VariableMetadataList", SimpleList(
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 = 'dateA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'DATE'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'binLabel', 'value', 'binStart', 'binEnd'))
variables <- new("VariableMetadataList", SimpleList(
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 = 'dateA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'DATE'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),4)
expect_equal(names(dt),c('entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),4)
expect_equal(names(dt),c('entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),4)
expect_equal(names(dt),c('entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'dateA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'DATE'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('binLabel', 'value', 'binStart', 'binEnd'))
# With factors
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'factor3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.factor3', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(class(dt$entity.factor3), 'character')
variables <- new("VariableMetadataList", SimpleList(
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 = '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 = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),9)
expect_equal(names(dt),c('panel', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(class(dt$panel), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'factor6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'factor3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),18)
expect_equal(names(dt),c('panel', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(class(dt$panel), 'character')
})
test_that("histogram() returns appropriately formatted json", {
variables <- new("VariableMetadataList", SimpleList(
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 = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList),c('histogram','sampleSizeTable', 'completeCasesTable'))
expect_equal(names(jsonList$histogram),c('data','config'))
expect_equal(names(jsonList$histogram$data),c('overlayVariableDetails','facetVariableDetails','binLabel','value','binStart','binEnd'))
expect_equal(names(jsonList$histogram$data$overlayVariableDetails),c('variableId','entityId','value'))
expect_equal(jsonList$histogram$data$overlayVariableDetails$variableId[1], 'cat3')
expect_equal(names(jsonList$histogram$config),c('variables','completeCasesAllVars','completeCasesAxesVars','summary','viewport','binSpec','binSlider'))
expect_equal(names(jsonList$histogram$config$variables$variableSpec),c('variableId','entityId'))
expect_equal(jsonList$histogram$config$variables$variableSpec$variableId, c('cat3','cat4','contA'))
expect_equal(names(jsonList$histogram$config$viewport),c('xMin','xMax'))
expect_equal(names(jsonList$histogram$config$binSlider),c('min','max','step'))
expect_equal(names(jsonList$histogram$config$summary),c('min','q1','median','mean','q3','max'))
expect_equal(names(jsonList$sampleSizeTable),c('overlayVariableDetails', 'facetVariableDetails', 'size'))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails', 'completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId', 'entityId'))
expect_equal(jsonList$completeCasesTable$variableDetails$variableId, c('contA', 'cat3', 'cat4'))
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList),c('histogram','sampleSizeTable','completeCasesTable'))
expect_equal(names(jsonList$histogram),c('data','config'))
expect_equal(names(jsonList$histogram$data),c('facetVariableDetails','binLabel','value','binStart','binEnd'))
expect_equal(names(jsonList$histogram$data$facetVariableDetails[[1]]),c('variableId','entityId','value'))
expect_equal(jsonList$histogram$data$facetVariableDetails[[1]]$variableId, c('cat4', 'cat3'))
expect_equal(nrow(jsonList$histogram$data$facetVariableDetails[[1]]), 2)
expect_equal(names(jsonList$histogram$config),c('variables','completeCasesAllVars','completeCasesAxesVars','summary','viewport','binSpec','binSlider'))
expect_equal(names(jsonList$histogram$config$variables$variableSpec),c('variableId','entityId'))
expect_equal(jsonList$histogram$config$variables$variableSpec$variableId, c('cat3','cat4','contA'))
expect_equal(names(jsonList$histogram$config$viewport),c('xMin','xMax'))
expect_equal(names(jsonList$histogram$config$binSlider),c('min','max','step'))
expect_equal(names(jsonList$histogram$config$summary),c('min','q1','median','mean','q3','max'))
expect_equal(names(jsonList$sampleSizeTable),c('facetVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
expect_equal(jsonList$sampleSizeTable$facetVariableDetails[[1]]$variableId, c('cat4', 'cat3'))
expect_equal(names(jsonList$completeCasesTable), c('variableDetails', 'completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId', 'entityId'))
expect_equal(jsonList$completeCasesTable$variableDetails$variableId, c('contA', 'cat4', 'cat3'))
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'stack', binReportValue, viewport)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList),c('histogram','sampleSizeTable','completeCasesTable'))
expect_equal(names(jsonList$histogram),c('data','config'))
expect_equal(names(jsonList$histogram$data),c('facetVariableDetails','binLabel','value','binStart','binEnd'))
expect_equal(names(jsonList$histogram$data$facetVariableDetails[[1]]),c('variableId','entityId','value'))
expect_equal(nrow(jsonList$histogram$data$facetVariableDetails[[1]]), 2)
expect_equal(jsonList$histogram$data$facetVariableDetails[[1]]$variableId, c('cat4', 'cat3'))
expect_equal(names(jsonList$histogram$config),c('variables','completeCasesAllVars','completeCasesAxesVars','summary','viewport','binSpec','binSlider'))
expect_equal(names(jsonList$histogram$config$variables$variableSpec),c('variableId','entityId'))
expect_equal(jsonList$histogram$config$variables$variableSpec$variableId, c('cat3','cat4','contA'))
expect_equal(names(jsonList$histogram$config$viewport),c('xMin','xMax'))
expect_equal(names(jsonList$histogram$config$binSlider),c('min','max','step'))
expect_equal(names(jsonList$histogram$config$summary),c('min','q1','median','mean','q3','max'))
expect_equal(names(jsonList$sampleSizeTable),c('facetVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
expect_equal(jsonList$sampleSizeTable$facetVariableDetails[[1]]$variableId, c('cat4', 'cat3'))
expect_equal(names(jsonList$completeCasesTable), c('variableDetails', 'completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId', 'entityId'))
expect_equal(jsonList$completeCasesTable$variableDetails$variableId, c('contA', 'cat4', 'cat3'))
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
displayName = "facet2Label",
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
displayName = "facet1Label",
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
displayName = "xLabel",
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'stack', binReportValue, viewport)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList),c('histogram','sampleSizeTable','completeCasesTable'))
expect_equal(names(jsonList$histogram),c('data','config'))
expect_equal(names(jsonList$histogram$data),c('facetVariableDetails','binLabel','value','binStart','binEnd'))
expect_equal(names(jsonList$histogram$data$facetVariableDetails[[1]]),c('variableId','entityId','value', 'displayLabel'))
expect_equal(nrow(jsonList$histogram$data$facetVariableDetails[[1]]), 2)
expect_equal(names(jsonList$histogram$config),c('variables','completeCasesAllVars','completeCasesAxesVars','summary','viewport','binSpec','binSlider'))
expect_equal(names(jsonList$histogram$config$variables$variableSpec),c('variableId','entityId'))
expect_equal(names(jsonList$histogram$config$viewport),c('xMin','xMax'))
expect_equal(names(jsonList$histogram$config$binSlider),c('min','max','step'))
expect_equal(names(jsonList$histogram$config$summary),c('min','q1','median','mean','q3','max'))
expect_equal(names(jsonList$sampleSizeTable),c('facetVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails', 'completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId', 'entityId', 'displayLabel'))
variables <- new("VariableMetadataList", SimpleList(
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 = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
displayName = "facet1Label",
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 = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'stack', binReportValue, viewport)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList$histogram$data$facetVariableDetails[[1]]),c('variableId','entityId','value', 'displayLabel'))
expect_equal(names(jsonList$histogram$config$variables$variableSpec),c('variableId','entityId'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId', 'entityId', 'displayLabel'))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
# Ensure sampleSizeTable and completeCasesTable are not part of json if we do not ask for them.
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'stack', binReportValue, viewport, sampleSizes = FALSE, completeCases = FALSE)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList),c('histogram'))
expect_equal(names(jsonList$histogram),c('data','config'))
expect_equal(names(jsonList$histogram$data),c('facetVariableDetails','binLabel','value','binStart','binEnd'))
expect_equal(names(jsonList$histogram$config),c('variables','summary','viewport','binSpec','binSlider'))
expect_equal(names(jsonList$histogram$config$variables$variableSpec),c('variableId','entityId'))
expect_equal(names(jsonList$histogram$config$viewport),c('xMin','xMax'))
expect_equal(names(jsonList$histogram$config$binSlider),c('min','max','step'))
expect_equal(names(jsonList$histogram$config$summary),c('min','q1','median','mean','q3','max'))
# With continuous overlay (< 9 values)
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'int6', 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 = '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 = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList),c('histogram','sampleSizeTable', 'completeCasesTable'))
expect_equal(names(jsonList$histogram),c('data','config'))
expect_equal(names(jsonList$histogram$data),c('overlayVariableDetails','facetVariableDetails','binLabel','value','binStart','binEnd'))
expect_equal(names(jsonList$histogram$data$overlayVariableDetails),c('variableId','entityId','value'))
expect_equal(jsonList$histogram$data$overlayVariableDetails$variableId[1], 'int6')
expect_equal(names(jsonList$histogram$config),c('variables','completeCasesAllVars','completeCasesAxesVars','summary','viewport','binSpec','binSlider'))
expect_equal(names(jsonList$histogram$config$variables$variableSpec),c('variableId','entityId'))
expect_equal(jsonList$histogram$config$variables$variableSpec$variableId, c('int6','cat4','contA'))
expect_equal(names(jsonList$histogram$config$viewport),c('xMin','xMax'))
expect_equal(names(jsonList$histogram$config$binSlider),c('min','max','step'))
expect_equal(names(jsonList$histogram$config$summary),c('min','q1','median','mean','q3','max'))
expect_equal(names(jsonList$sampleSizeTable),c('overlayVariableDetails', 'facetVariableDetails', 'size'))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails', 'completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId', 'entityId'))
expect_equal(jsonList$completeCasesTable$variableDetails$variableId, c('contA', 'int6', 'cat4'))
})
test_that("histogram.dt() returns correct information about missing data", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
# Add nMissing missing values to each column
nMissing <- 10
df <- as.data.frame(lapply(testDF, function(x) {x[sample(1:length(x), nMissing, replace=F)] <- NA; x}))
viewport <- list('xMin'=min(testDF$entity.contA), 'xMax'=max(testDF$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
completecasestable <- completeCasesTable(dt)
# Each entry should equal NROW(df) - nMissing
expect_equal(all(completecasestable$completeCases == nrow(df)-nMissing), TRUE)
# number of completeCases should be <= complete cases for each var
expect_equal(all(attr(dt, 'completeCasesAllVars')[1] <= completecasestable$completeCases), TRUE)
expect_equal(attr(dt, 'completeCasesAxesVars')[1] >= attr(dt, 'completeCasesAllVars')[1], TRUE)
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', binReportValue = binReportValue, viewport = viewport, evilMode = 'strataVariables')
expect_equal(attr(dt, 'completeCasesAxesVars')[1], sum(!is.na(df$entity.contA)))
#dt <- histogram.dt(df, variables, binWidth = NULL, value='count', binReportValue = binReportValue, viewport = viewport, evilMode = 'allVariables')
#expect_equal(attr(dt, 'completeCasesAllVars')[1], sum(complete.cases(df[, map$id, with=FALSE])))
## Using naToZero to change some NAs to 0
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat5', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
imputeZero = TRUE)
))
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
completecasestable <- completeCasesTable(dt)
# Each entry except 'contB' should equal NROW(df) - nMissing
expect_equal(sum(completecasestable$completeCases == nrow(df)-nMissing), 3)
expect_equal(completecasestable[variableDetails=='entity.contA', completeCases], nrow(df))
# number of completeCases should be < complete cases for each var
expect_true(all(attr(dt, 'completeCasesAllVars')[1] < completecasestable$completeCases))
expect_true(attr(dt, 'completeCasesAxesVars')[1] > attr(dt, 'completeCasesAllVars')[1])
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', binReportValue = binReportValue, viewport = viewport, evilMode='strataVariables')
expect_equal(attr(dt, 'completeCasesAxesVars')[1], nrow(df))
})
test_that("histogram.dt does not produce corrupted bins when given TAC data from issue 182", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'values', entityId = NA_character_),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(data.issue182, variables, binWidth = 1, value = 'count', barmode = 'stack', binReportValue = 'binWidth')
# check that there are no NAs (which the client is getting as nulls) in the binLabels
expect_equal(sum(is.na(unlist(dt$binLabel))), 0)
# check that the binStart and binEnd strings are all valid numbers
# (the bug gives values like '24]')
expect_equal(sum(is.na(as.numeric(unlist(dt$binStart)))), 0)
expect_equal(sum(is.na(as.numeric(unlist(dt$binEnd)))), 0)
})
test_that("our bins are always left closed/ inclusive", {
variables <- new("VariableMetadataList", SimpleList(
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 = '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 = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = .3, value='count', barmode = 'overlay', binReportValue, viewport)
expect_equal(all(unlist(lapply(dt$binLabel,substr,1,1)) == '['), TRUE)
})
VEuPathDB/plot.data documentation built on Feb. 20, 2025, 6:33 p.m.
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context('histogram')
test_that("histogram.dt does not fail when there are no complete cases.", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cont', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- data.noneComplete[is.na(entity.cont),]
dt <- histogram.dt(df, variables, binWidth = .3, value='count', barmode = 'overlay', 'binWidth', NULL)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(as.character(attr$viewport$xMin), "")
expect_equal(is.na(attr$binSlider$min), TRUE)
expect_equal(as.character(attr$summary$min), "")
expect_equal(is.na(attr$binSpec$value), TRUE)
expect_equal(is.list(dt$binLabel), TRUE)
expect_equal(is.list(dt$binStart), TRUE)
expect_equal(is.list(dt$binEnd), TRUE)
expect_equal(is.list(dt$value), TRUE)
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', 'binWidth', NULL)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(as.character(attr$viewport$xMin), "")
expect_equal(is.na(attr$binSlider$min), TRUE)
expect_equal(as.character(attr$summary$min), "")
expect_equal(is.na(attr$binSpec$value), TRUE)
expect_equal(is.list(dt$binLabel), TRUE)
expect_equal(is.list(dt$binStart), TRUE)
expect_equal(is.list(dt$binEnd), TRUE)
expect_equal(is.list(dt$value), TRUE)
dt <- histogram.dt(df, variables, binWidth = .3, value='proportion', barmode = 'overlay', 'binWidth', NULL)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(as.character(attr$viewport$xMin), "")
expect_equal(is.na(attr$binSlider$min), TRUE)
expect_equal(as.character(attr$summary$min), "")
expect_equal(is.na(attr$binSpec$value), TRUE)
expect_equal(is.list(dt$binLabel), TRUE)
expect_equal(is.list(dt$binStart), TRUE)
expect_equal(is.list(dt$binEnd), TRUE)
expect_equal(is.list(dt$value), TRUE)
dt <- histogram.dt(df, variables, binWidth = .3, value='count', barmode = 'stack', 'binWidth', NULL)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(as.character(attr$viewport$xMin), "")
expect_equal(is.na(attr$binSlider$min), TRUE)
expect_equal(as.character(attr$summary$min), "")
expect_equal(is.na(attr$binSpec$value), TRUE)
expect_equal(is.list(dt$binLabel), TRUE)
expect_equal(is.list(dt$binStart), TRUE)
expect_equal(is.list(dt$binEnd), TRUE)
expect_equal(is.list(dt$value), TRUE)
dt <- histogram.dt(df, variables, binWidth = .3, value='count', barmode = 'overlay', 'numBins', NULL)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(as.character(attr$viewport$xMin), "")
expect_equal(is.na(attr$binSlider$min), TRUE)
expect_equal(as.character(attr$summary$min), "")
expect_equal(is.na(attr$binSpec$value), TRUE)
expect_equal(is.list(dt$binLabel), TRUE)
expect_equal(is.list(dt$binStart), TRUE)
expect_equal(is.list(dt$binEnd), TRUE)
expect_equal(is.list(dt$value), TRUE)
variables <- new("VariableMetadataList", SimpleList(
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 = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- data.noneComplete
dt <- histogram.dt(df, variables, binWidth = .3, value='count', barmode = 'overlay', 'binWidth', NULL)
attr <- attributes(dt)
expect_equal(attr$completeCasesAllVars[1], 0)
expect_equal(as.character(attr$viewport$xMin), "")
expect_equal(is.na(attr$binSlider$min), TRUE)
expect_equal(as.character(attr$summary$min), "")
expect_equal(is.na(attr$binSpec$value), TRUE)
expect_equal(is.list(dt$binLabel), TRUE)
expect_equal(is.list(dt$binStart), TRUE)
expect_equal(is.list(dt$binEnd), TRUE)
expect_equal(is.list(dt$value), TRUE)
})
test_that("histogram.dt() returns requested numBins/ binWidth", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = .3, value='count', barmode = 'overlay', binReportValue, viewport)
expect_equal(round(as.numeric(binSpec(dt)$value),1), .3)
expect_equal(getMode(as.numeric(unlist(dt$binEnd)) - as.numeric(unlist(dt$binStart))), .3)
dt <- histogram.dt(df, variables, binWidth = 1.5, value='count', barmode = 'overlay', binReportValue, viewport)
expect_equal(round(as.numeric(binSpec(dt)$value),1), 1.5)
expect_equal(round(getMode(as.numeric(unlist(dt$binEnd)) - as.numeric(unlist(dt$binStart))),1), 1.5)
binReportValue <- 'numBins'
binWidth <- numBinsToBinWidth(df$entity.contA, 5)
dt <- histogram.dt(df, variables, binWidth = binWidth, value='count', barmode = 'overlay', binReportValue, viewport)
expect_equal(as.numeric(binSpec(dt)$value), 5) # ensure we get the correct number of bins
expect_true(max(as.numeric(unlist(dt$binEnd)) - as.numeric(unlist(dt$binStart)) - binWidth) < 0.1) # Tolerance 0.1
numericLabelsStart <- unlist(lapply(unlist(dt$binLabel), function(x) as.numeric(stringi::stri_split_regex(x, ",|]|\\(|\\[")[[1]][2])))
numericLabelsEnd <- unlist(lapply(unlist(dt$binLabel), function(x) as.numeric(stringi::stri_split_regex(x, ",|]|\\(|\\[|\\)")[[1]][3])))
expect_true(max(numericLabelsEnd - numericLabelsStart) - binWidth < 0.1) # Label tolerance
binReportValue <- 'numBins'
binWidth <- numBinsToBinWidth(df$entity.contA, 15)
dt <- histogram.dt(df, variables, binWidth = binWidth, value='count', barmode = 'overlay', binReportValue, viewport)
expect_equal(as.numeric(binSpec(dt)$value), 15) # ensure we get the correct number of bins
expect_true(max(as.numeric(unlist(dt$binEnd)) - as.numeric(unlist(dt$binStart)) - binWidth) < 0.1) # Tolerance 0.1
numericLabelsStart <- unlist(lapply(unlist(dt$binLabel), function(x) as.numeric(stringi::stri_split_regex(x, ",|]|\\(|\\[")[[1]][2])))
numericLabelsEnd <- unlist(lapply(unlist(dt$binLabel), function(x) as.numeric(stringi::stri_split_regex(x, ",|]|\\(|\\[|\\)")[[1]][3])))
expect_true(max(numericLabelsEnd - numericLabelsStart) - binWidth < 0.1) # Label tolerance
})
test_that("histogram.dt() returns a valid plot.data histogram object", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'plot.data')
expect_is(dt, 'histogram')
namedAttrList <- getPDAttributes(dt)
expect_equal(names(namedAttrList),c('variables', 'completeCasesAllVars','completeCasesAxesVars','completeCasesTable','sampleSizeTable','summary', 'viewport', 'binSpec', 'binSlider'))
completeCases <- completeCasesTable(dt)
expect_equal(names(completeCases), c('variableDetails','completeCases'))
expect_equal(nrow(completeCases), 3)
sampleSizes <- sampleSizeTable(dt)
expect_equal(names(sampleSizes), c('panel','size'))
expect_equal(nrow(sampleSizes), 12)
expect_equal(names(namedAttrList$summary), c('min','q1','median','mean','q3','max'))
expect_equal(names(viewport(dt)), c('xMin','xMax'))
expect_equal(names(binSlider(dt)), c('min','max','step'))
expect_equal(names(namedAttrList$binSpec), c('type','value'))
expect_equal(round(as.numeric(namedAttrList$binSpec$value),4), 1.8032)
expect_equal(as.character(namedAttrList$binSpec$type), 'binWidth')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'dateA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'DATE'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
viewport <- list('xMin'=min(df$entity.dateA), 'xMax'=max(df$entity.dateA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = 'month', value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'plot.data')
expect_is(dt, 'histogram')
namedAttrList <- getPDAttributes(dt)
expect_equal(names(namedAttrList),c('variables', 'completeCasesAllVars','completeCasesAxesVars','completeCasesTable','sampleSizeTable','summary', 'viewport', 'binSpec', 'binSlider'))
completeCases <- completeCasesTable(dt)
expect_equal(names(completeCases), c('variableDetails','completeCases'))
expect_equal(nrow(completeCases), 3)
sampleSizes <- sampleSizeTable(dt)
expect_equal(names(sampleSizes), c('panel','size'))
expect_equal(nrow(sampleSizes), 12)
expect_equal(names(namedAttrList$summary), c('min','q1','median','mean','q3','max'))
expect_equal(names(viewport(dt)), c('xMin','xMax'))
expect_equal(names(binSlider(dt)), c('min','max','step'))
expect_equal(names(namedAttrList$binSpec), c('type','value','units'))
expect_equal(as.numeric(namedAttrList$binSpec$value),1)
expect_equal(as.character(namedAttrList$binSpec$type),'binWidth')
expect_equal(as.character(namedAttrList$binSpec$unit),'month')
# expect_true(all(grepl('T00:00:00', unlist(dt$binStart))))
# expect_true(all(grepl('T00:00:00', unlist(dt$binEnd))))
# expect_true(!any(grepl('T00:00:00', unlist(dt$binLabel))))
# Ensure sampleSizeTable and completeCasesTable do not get returned if we do not ask for them.
dt <- histogram.dt(df, variables, binWidth = 'month', value='count', barmode = 'overlay', binReportValue, viewport, sampleSizes = FALSE, completeCases = FALSE)
expect_is(dt, 'plot.data')
expect_is(dt, 'histogram')
namedAttrList <- getPDAttributes(dt)
expect_equal(names(namedAttrList),c('variables','summary', 'viewport', 'binSpec', 'binSlider'))
expect_equal(names(namedAttrList$summary), c('min','q1','median','mean','q3','max'))
expect_equal(names(viewport(dt)), c('xMin','xMax'))
expect_equal(names(binSlider(dt)), c('min','max','step'))
expect_equal(names(namedAttrList$binSpec), c('type','value','units'))
expect_equal(as.numeric(namedAttrList$binSpec$value),1)
expect_equal(as.character(namedAttrList$binSpec$type),'binWidth')
expect_equal(as.character(namedAttrList$binSpec$unit),'month')
})
test_that("histogram.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 = '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 = '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 = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_equal(class(unlist(dt$panel)), 'character')
expect_equal(class(unlist(dt$binLabel)), 'character')
expect_equal(class(unlist(dt$binStart)), 'character')
expect_equal(class(unlist(dt$binEnd)), 'character')
expect_equal(class(unlist(dt$value)), 'integer')
namedAttrList <- getPDAttributes(dt)
expect_equal(class(namedAttrList$completeCasesAllVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$completeCasesAxesVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$summary$min),c('scalar', 'character'))
expect_equal(class(namedAttrList$viewport$xMin),c('scalar', 'character'))
expect_equal(class(namedAttrList$binSlider$min),c('scalar', 'numeric'))
expect_equal(class(namedAttrList$binSpec$type),c('scalar', 'character'))
expect_equal(class(namedAttrList$binSpec$value),c('scalar', 'numeric'))
completeCases <- completeCasesTable(dt)
expect_equal(class(unlist(completeCases$variableDetails)), 'character')
expect_equal(class(unlist(completeCases$completeCases)), 'integer')
sampleSizes <- sampleSizeTable(dt)
expect_equal(class(unlist(sampleSizes$panel)), 'character')
expect_equal(class(unlist(sampleSizes$size)), 'integer')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'dateA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'DATE'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
viewport <- list('xMin'=min(df$entity.dateA), 'xMax'=max(df$entity.dateA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = 'month', value='count', barmode = 'overlay', binReportValue, viewport)
expect_equal(class(unlist(dt$panel)), 'character')
expect_equal(class(unlist(dt$binLabel)), 'character')
expect_equal(class(unlist(dt$binStart)), 'character')
expect_equal(class(unlist(dt$binEnd)), 'character')
expect_equal(class(unlist(dt$value)), 'integer')
namedAttrList <- getPDAttributes(dt)
expect_equal(class(namedAttrList$completeCasesAllVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$completeCasesAxesVars),c('scalar', 'integer'))
expect_equal(class(namedAttrList$summary$min),c('scalar', 'character'))
expect_equal(class(namedAttrList$viewport$xMin),c('scalar', 'character'))
expect_equal(class(namedAttrList$binSlider$min),c('scalar', 'numeric'))
expect_equal(class(namedAttrList$binSpec$type),c('scalar', 'character'))
expect_equal(class(namedAttrList$binSpec$value),c('scalar', 'numeric'))
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$panel)), 'character')
expect_equal(class(unlist(sampleSizes$size)), 'integer')
})
test_that("histogram.dt() returns bins according to specified viewport", {
variables <- new("VariableMetadataList", SimpleList(
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 = '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 = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
binReportValue <- 'binWidth'
viewport <- list('xMin'=-1.5,'xMax'=2.5)
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
maxBinStart <- as.numeric(max(unlist(lapply(dt$binStart, max))))
expect_true(maxBinStart <= viewport$xMax)
minBinEnd <- as.numeric(min(unlist(lapply(dt$binEnd, min))))
expect_true(minBinEnd >= viewport$xMin)
#figure how to test for expanding to viewport, since we dont explicitly return 0 value bins..
})
test_that("histogram.dt() returns an appropriately sized data.table", {
df <- as.data.frame(testDF)
variables <- new("VariableMetadataList", SimpleList(
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 = '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 = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('panel', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(all(grepl('.||.', dt$panel, fixed=T)), TRUE)
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport = viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('panel', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(all(grepl('.||.', dt$panel, fixed=T)), TRUE)
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport = viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('panel', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(all(grepl('.||.', dt$panel, fixed=T)), TRUE)
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('entity.cat3', 'entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('entity.cat3', 'entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('entity.cat3', 'entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
variables <- new("VariableMetadataList", SimpleList(
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 = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'binLabel', 'value', 'binStart', 'binEnd'))
variables <- new("VariableMetadataList", SimpleList(
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 = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),4)
expect_equal(names(dt),c('entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),4)
expect_equal(names(dt),c('entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),4)
expect_equal(names(dt),c('entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('binLabel', 'value', 'binStart', 'binEnd'))
#this for dates
variables <- new("VariableMetadataList", SimpleList(
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 = '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 = 'dateA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'DATE'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
viewport <- list('xMin'=min(df$entity.dateA), 'xMax'=max(df$entity.dateA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('panel', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(all(grepl('.||.', dt$panel, fixed=T)), TRUE)
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('panel', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(all(grepl('.||.', dt$panel, fixed=T)), TRUE)
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('panel', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(all(grepl('.||.', dt$panel, fixed=T)), TRUE)
variables <- new("VariableMetadataList", SimpleList(
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 = 'dateA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'DATE'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
viewport <- list('xMin'=min(df$entity.dateA), 'xMax'=max(df$entity.dateA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('entity.cat3', 'entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('entity.cat3', 'entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),12)
expect_equal(names(dt),c('entity.cat3', 'entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
variables <- new("VariableMetadataList", SimpleList(
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 = 'dateA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'DATE'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.cat3', 'binLabel', 'value', 'binStart', 'binEnd'))
variables <- new("VariableMetadataList", SimpleList(
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 = 'dateA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'DATE'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),4)
expect_equal(names(dt),c('entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),4)
expect_equal(names(dt),c('entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),4)
expect_equal(names(dt),c('entity.cat4', 'binLabel', 'value', 'binStart', 'binEnd'))
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'dateA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'DATE'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='count', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'overlay', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('binLabel', 'value', 'binStart', 'binEnd'))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),1)
expect_equal(names(dt),c('binLabel', 'value', 'binStart', 'binEnd'))
# With factors
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
variables <- new("VariableMetadataList", SimpleList(
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 = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),3)
expect_equal(names(dt),c('entity.factor3', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(class(dt$entity.factor3), 'character')
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'factor3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),9)
expect_equal(names(dt),c('panel', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(class(dt$panel), 'character')
variables <- new("VariableMetadataList", SimpleList(
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 = '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 = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth=NULL, value='proportion', barmode = 'stack', binReportValue, viewport)
expect_is(dt, 'data.table')
expect_equal(nrow(dt),18)
expect_equal(names(dt),c('panel', 'binLabel', 'value', 'binStart', 'binEnd'))
expect_equal(class(dt$panel), 'character')
})
test_that("histogram() returns appropriately formatted json", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList),c('histogram','sampleSizeTable', 'completeCasesTable'))
expect_equal(names(jsonList$histogram),c('data','config'))
expect_equal(names(jsonList$histogram$data),c('overlayVariableDetails','facetVariableDetails','binLabel','value','binStart','binEnd'))
expect_equal(names(jsonList$histogram$data$overlayVariableDetails),c('variableId','entityId','value'))
expect_equal(jsonList$histogram$data$overlayVariableDetails$variableId[1], 'cat3')
expect_equal(names(jsonList$histogram$config),c('variables','completeCasesAllVars','completeCasesAxesVars','summary','viewport','binSpec','binSlider'))
expect_equal(names(jsonList$histogram$config$variables$variableSpec),c('variableId','entityId'))
expect_equal(jsonList$histogram$config$variables$variableSpec$variableId, c('cat3','cat4','contA'))
expect_equal(names(jsonList$histogram$config$viewport),c('xMin','xMax'))
expect_equal(names(jsonList$histogram$config$binSlider),c('min','max','step'))
expect_equal(names(jsonList$histogram$config$summary),c('min','q1','median','mean','q3','max'))
expect_equal(names(jsonList$sampleSizeTable),c('overlayVariableDetails', 'facetVariableDetails', 'size'))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails', 'completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId', 'entityId'))
expect_equal(jsonList$completeCasesTable$variableDetails$variableId, c('contA', 'cat3', 'cat4'))
variables <- new("VariableMetadataList", SimpleList(
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 = '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 = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList),c('histogram','sampleSizeTable','completeCasesTable'))
expect_equal(names(jsonList$histogram),c('data','config'))
expect_equal(names(jsonList$histogram$data),c('facetVariableDetails','binLabel','value','binStart','binEnd'))
expect_equal(names(jsonList$histogram$data$facetVariableDetails[[1]]),c('variableId','entityId','value'))
expect_equal(jsonList$histogram$data$facetVariableDetails[[1]]$variableId, c('cat4', 'cat3'))
expect_equal(nrow(jsonList$histogram$data$facetVariableDetails[[1]]), 2)
expect_equal(names(jsonList$histogram$config),c('variables','completeCasesAllVars','completeCasesAxesVars','summary','viewport','binSpec','binSlider'))
expect_equal(names(jsonList$histogram$config$variables$variableSpec),c('variableId','entityId'))
expect_equal(jsonList$histogram$config$variables$variableSpec$variableId, c('cat3','cat4','contA'))
expect_equal(names(jsonList$histogram$config$viewport),c('xMin','xMax'))
expect_equal(names(jsonList$histogram$config$binSlider),c('min','max','step'))
expect_equal(names(jsonList$histogram$config$summary),c('min','q1','median','mean','q3','max'))
expect_equal(names(jsonList$sampleSizeTable),c('facetVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
expect_equal(jsonList$sampleSizeTable$facetVariableDetails[[1]]$variableId, c('cat4', 'cat3'))
expect_equal(names(jsonList$completeCasesTable), c('variableDetails', 'completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId', 'entityId'))
expect_equal(jsonList$completeCasesTable$variableDetails$variableId, c('contA', 'cat4', 'cat3'))
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'stack', binReportValue, viewport)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList),c('histogram','sampleSizeTable','completeCasesTable'))
expect_equal(names(jsonList$histogram),c('data','config'))
expect_equal(names(jsonList$histogram$data),c('facetVariableDetails','binLabel','value','binStart','binEnd'))
expect_equal(names(jsonList$histogram$data$facetVariableDetails[[1]]),c('variableId','entityId','value'))
expect_equal(nrow(jsonList$histogram$data$facetVariableDetails[[1]]), 2)
expect_equal(jsonList$histogram$data$facetVariableDetails[[1]]$variableId, c('cat4', 'cat3'))
expect_equal(names(jsonList$histogram$config),c('variables','completeCasesAllVars','completeCasesAxesVars','summary','viewport','binSpec','binSlider'))
expect_equal(names(jsonList$histogram$config$variables$variableSpec),c('variableId','entityId'))
expect_equal(jsonList$histogram$config$variables$variableSpec$variableId, c('cat3','cat4','contA'))
expect_equal(names(jsonList$histogram$config$viewport),c('xMin','xMax'))
expect_equal(names(jsonList$histogram$config$binSlider),c('min','max','step'))
expect_equal(names(jsonList$histogram$config$summary),c('min','q1','median','mean','q3','max'))
expect_equal(names(jsonList$sampleSizeTable),c('facetVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
expect_equal(jsonList$sampleSizeTable$facetVariableDetails[[1]]$variableId, c('cat4', 'cat3'))
expect_equal(names(jsonList$completeCasesTable), c('variableDetails', 'completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId', 'entityId'))
expect_equal(jsonList$completeCasesTable$variableDetails$variableId, c('contA', 'cat4', 'cat3'))
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
displayName = "facet2Label",
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'),
displayName = "facet1Label",
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 = 'xAxis'),
displayName = "xLabel",
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'stack', binReportValue, viewport)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList),c('histogram','sampleSizeTable','completeCasesTable'))
expect_equal(names(jsonList$histogram),c('data','config'))
expect_equal(names(jsonList$histogram$data),c('facetVariableDetails','binLabel','value','binStart','binEnd'))
expect_equal(names(jsonList$histogram$data$facetVariableDetails[[1]]),c('variableId','entityId','value', 'displayLabel'))
expect_equal(nrow(jsonList$histogram$data$facetVariableDetails[[1]]), 2)
expect_equal(names(jsonList$histogram$config),c('variables','completeCasesAllVars','completeCasesAxesVars','summary','viewport','binSpec','binSlider'))
expect_equal(names(jsonList$histogram$config$variables$variableSpec),c('variableId','entityId'))
expect_equal(names(jsonList$histogram$config$viewport),c('xMin','xMax'))
expect_equal(names(jsonList$histogram$config$binSlider),c('min','max','step'))
expect_equal(names(jsonList$histogram$config$summary),c('min','q1','median','mean','q3','max'))
expect_equal(names(jsonList$sampleSizeTable),c('facetVariableDetails','size'))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails', 'completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId', 'entityId', 'displayLabel'))
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
displayName = "facet1Label",
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'stack', binReportValue, viewport)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList$histogram$data$facetVariableDetails[[1]]),c('variableId','entityId','value', 'displayLabel'))
expect_equal(names(jsonList$histogram$config$variables$variableSpec),c('variableId','entityId'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId', 'entityId', 'displayLabel'))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
# Ensure sampleSizeTable and completeCasesTable are not part of json if we do not ask for them.
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'stack', binReportValue, viewport, sampleSizes = FALSE, completeCases = FALSE)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList),c('histogram'))
expect_equal(names(jsonList$histogram),c('data','config'))
expect_equal(names(jsonList$histogram$data),c('facetVariableDetails','binLabel','value','binStart','binEnd'))
expect_equal(names(jsonList$histogram$config),c('variables','summary','viewport','binSpec','binSlider'))
expect_equal(names(jsonList$histogram$config$variables$variableSpec),c('variableId','entityId'))
expect_equal(names(jsonList$histogram$config$viewport),c('xMin','xMax'))
expect_equal(names(jsonList$histogram$config$binSlider),c('min','max','step'))
expect_equal(names(jsonList$histogram$config$summary),c('min','q1','median','mean','q3','max'))
# With continuous overlay (< 9 values)
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'int6', entityId = 'entity'),
plotReference = new("PlotReference", value = 'overlay'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
outJson <- getJSON(dt, FALSE)
jsonList <- jsonlite::fromJSON(outJson)
expect_equal(names(jsonList),c('histogram','sampleSizeTable', 'completeCasesTable'))
expect_equal(names(jsonList$histogram),c('data','config'))
expect_equal(names(jsonList$histogram$data),c('overlayVariableDetails','facetVariableDetails','binLabel','value','binStart','binEnd'))
expect_equal(names(jsonList$histogram$data$overlayVariableDetails),c('variableId','entityId','value'))
expect_equal(jsonList$histogram$data$overlayVariableDetails$variableId[1], 'int6')
expect_equal(names(jsonList$histogram$config),c('variables','completeCasesAllVars','completeCasesAxesVars','summary','viewport','binSpec','binSlider'))
expect_equal(names(jsonList$histogram$config$variables$variableSpec),c('variableId','entityId'))
expect_equal(jsonList$histogram$config$variables$variableSpec$variableId, c('int6','cat4','contA'))
expect_equal(names(jsonList$histogram$config$viewport),c('xMin','xMax'))
expect_equal(names(jsonList$histogram$config$binSlider),c('min','max','step'))
expect_equal(names(jsonList$histogram$config$summary),c('min','q1','median','mean','q3','max'))
expect_equal(names(jsonList$sampleSizeTable),c('overlayVariableDetails', 'facetVariableDetails', 'size'))
expect_equal(class(jsonList$sampleSizeTable$facetVariableDetails[[1]]$value), 'character')
expect_equal(class(jsonList$sampleSizeTable$overlayVariableDetails$value[[1]]), 'character')
expect_equal(names(jsonList$completeCasesTable), c('variableDetails', 'completeCases'))
expect_equal(names(jsonList$completeCasesTable$variableDetails), c('variableId', 'entityId'))
expect_equal(jsonList$completeCasesTable$variableDetails$variableId, c('contA', 'int6', 'cat4'))
})
test_that("histogram.dt() returns correct information about missing data", {
variables <- new("VariableMetadataList", SimpleList(
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 = '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 = '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 = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
# 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}))
viewport <- list('xMin'=min(testDF$entity.contA), 'xMax'=max(testDF$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
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 <- histogram.dt(df, variables, binWidth = NULL, value='count', binReportValue = binReportValue, viewport = viewport, evilMode = 'strataVariables')
expect_equal(attr(dt, 'completeCasesAxesVars')[1], sum(!is.na(df$entity.contA)))
#dt <- histogram.dt(df, variables, binWidth = NULL, value='count', binReportValue = binReportValue, viewport = viewport, evilMode = 'allVariables')
#expect_equal(attr(dt, 'completeCasesAllVars')[1], sum(complete.cases(df[, map$id, with=FALSE])))
## Using naToZero to change some NAs to 0
variables <- new("VariableMetadataList", SimpleList(
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 = '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 = '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 = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'),
imputeZero = TRUE)
))
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', barmode = 'overlay', binReportValue, viewport)
completecasestable <- completeCasesTable(dt)
# Each entry except 'contB' should equal NROW(df) - nMissing
expect_equal(sum(completecasestable$completeCases == nrow(df)-nMissing), 3)
expect_equal(completecasestable[variableDetails=='entity.contA', completeCases], nrow(df))
# number of completeCases should be < complete cases for each var
expect_true(all(attr(dt, 'completeCasesAllVars')[1] < completecasestable$completeCases))
expect_true(attr(dt, 'completeCasesAxesVars')[1] > attr(dt, 'completeCasesAllVars')[1])
dt <- histogram.dt(df, variables, binWidth = NULL, value='count', binReportValue = binReportValue, viewport = viewport, evilMode='strataVariables')
expect_equal(attr(dt, 'completeCasesAxesVars')[1], nrow(df))
})
test_that("histogram.dt does not produce corrupted bins when given TAC data from issue 182", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'values', entityId = NA_character_),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
dt <- histogram.dt(data.issue182, variables, binWidth = 1, value = 'count', barmode = 'stack', binReportValue = 'binWidth')
# check that there are no NAs (which the client is getting as nulls) in the binLabels
expect_equal(sum(is.na(unlist(dt$binLabel))), 0)
# check that the binStart and binEnd strings are all valid numbers
# (the bug gives values like '24]')
expect_equal(sum(is.na(as.numeric(unlist(dt$binStart)))), 0)
expect_equal(sum(is.na(as.numeric(unlist(dt$binEnd)))), 0)
})
test_that("our bins are always left closed/ inclusive", {
variables <- new("VariableMetadataList", SimpleList(
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat3', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet2'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'cat4', entityId = 'entity'),
plotReference = new("PlotReference", value = 'facet1'),
dataType = new("DataType", value = 'STRING'),
dataShape = new("DataShape", value = 'CATEGORICAL')),
new("VariableMetadata",
variableClass = new("VariableClass", value = 'native'),
variableSpec = new("VariableSpec", variableId = 'contA', entityId = 'entity'),
plotReference = new("PlotReference", value = 'xAxis'),
dataType = new("DataType", value = 'NUMBER'),
dataShape = new("DataShape", value = 'CONTINUOUS'))
))
df <- as.data.frame(testDF)
viewport <- list('xMin'=min(df$entity.contA), 'xMax'=max(df$entity.contA))
binReportValue <- 'binWidth'
dt <- histogram.dt(df, variables, binWidth = .3, value='count', barmode = 'overlay', binReportValue, viewport)
expect_equal(all(unlist(lapply(dt$binLabel,substr,1,1)) == '['), TRUE)
})
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