tests/testthat/test-bettrGetReady.R
In federicomarini/bettr: A Better Way To Explore What Is Best
test_that("bettrGetReady works", {
df <- data.frame(Method = c("M1", "M2", "M3"),
metric1 = c(1, 2, 3),
metric2 = c(3, 1, 2),
metric3 = c(2, 1, NA))
metricInfo <- data.frame(Metric = c("metric1", "metric2", "metric3"),
Group = c("G1", "G2", "G2"))
idInfo <- data.frame(Method = c("M1", "M2", "M3"),
Type = c("T1", "T1", "T2"))
## Check that the function returns an error with incorrect input
## -------------------------------------------------------------------------
.args <- list(bettrSE = NULL, df = df, idCol = "Method",
metrics = c("metric1", "metric2"),
initialWeights = NULL,
initialTransforms = list(),
metricInfo = NULL, metricColors = NULL,
idInfo = NULL, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = FALSE, nbrTopIds = 10,
idTopNGrouping = NULL,
keepIds = NULL,
metricGrouping = NULL, metricCollapseGroup = FALSE,
metricCollapseMethod = "mean")
args <- .args
args$df <- 1
expect_error(do.call(bettrGetReady, args),
"'df' must be of class 'data.frame'")
args <- .args
args$idCol <- 1
expect_error(do.call(bettrGetReady, args),
"'idCol' must be of class 'character'")
args$idCol <- c("Method", "metric1")
expect_error(do.call(bettrGetReady, args),
"'idCol' must have length 1")
args <- .args
args$metrics <- 1
expect_error(do.call(bettrGetReady, args),
"'metrics' must be of class 'character'")
args$metrics <- "missing"
expect_error(do.call(bettrGetReady, args),
"All values in 'metrics' must be one of")
args <- .args
args$initialWeights <- "1"
expect_error(do.call(bettrGetReady, args),
"'initialWeights' must be of class 'numeric'")
args <- .args
args$initialTransforms <- 1
expect_error(do.call(bettrGetReady, args),
"'initialTransforms' must be of class 'list'")
args <- .args
args$metricInfo <- seq(1, 3)
expect_error(do.call(bettrGetReady, args),
"'metricInfo' must be of class 'data.frame'")
args <- .args
args$metricColors <- seq(1, 3)
expect_error(do.call(bettrGetReady, args),
"'metricColors' must be of class 'list'")
args <- .args
args$idInfo <- seq(1, 3)
expect_error(do.call(bettrGetReady, args),
"'idInfo' must be of class 'data.frame'")
args <- .args
args$idColors <- seq(1, 3)
expect_error(do.call(bettrGetReady, args),
"'idColors' must be of class 'list'")
args <- .args
args$scoreMethod <- 1
expect_error(do.call(bettrGetReady, args),
"'scoreMethod' must be of class 'character'")
args$scoreMethod <- c("weighted mean", "weighted median")
expect_error(do.call(bettrGetReady, args),
"'scoreMethod' must have length 1")
args$scoreMethod <- "missing"
expect_error(do.call(bettrGetReady, args),
"All values in 'scoreMethod' must be one of")
args <- .args
args$idOrdering <- 1
expect_error(do.call(bettrGetReady, args),
"'idOrdering' must be of class 'character'")
args$idOrdering <- c("high-to-low", "low-to-high")
expect_error(do.call(bettrGetReady, args),
"'idOrdering' must have length 1")
args$idOrdering <- "missing"
expect_error(do.call(bettrGetReady, args),
"All values in 'idOrdering' must be one of")
args <- .args
args$showOnlyTopIds <- 1
expect_error(do.call(bettrGetReady, args),
"'showOnlyTopIds' must be of class 'logical'")
args$showOnlyTopIds <- c(TRUE, FALSE)
expect_error(do.call(bettrGetReady, args),
"'showOnlyTopIds' must have length 1")
args <- .args
args$nbrTopIds <- TRUE
expect_error(do.call(bettrGetReady, args),
"'nbrTopIds' must be of class 'numeric'")
args$nbrTopIds <- c(1, 2)
expect_error(do.call(bettrGetReady, args),
"'nbrTopIds' must have length 1")
args <- .args
args$idTopNGrouping <- TRUE
expect_error(do.call(bettrGetReady, args),
"'idTopNGrouping' must be of class 'character'")
args$idTopNGrouping <- c("Group", "Group")
expect_error(do.call(bettrGetReady, args),
"'idTopNGrouping' must have length 1")
args <- .args
args$keepIds <- TRUE
expect_error(do.call(bettrGetReady, args),
"'keepIds' must be of class 'character'")
args <- .args
args$metricGrouping <- TRUE
expect_error(do.call(bettrGetReady, args),
"'metricGrouping' must be of class 'character'")
args$metricGrouping <- c("Group", "Group")
expect_error(do.call(bettrGetReady, args),
"'metricGrouping' must have length 1")
args <- .args
args$metricCollapseGroup <- 1
expect_error(do.call(bettrGetReady, args),
"'metricCollapseGroup' must be of class 'logical'")
args$metricCollapseGroup <- c(TRUE, FALSE)
expect_error(do.call(bettrGetReady, args),
"'metricCollapseGroup' must have length 1")
args <- .args
args$metricCollapseMethod <- 1
expect_error(do.call(bettrGetReady, args),
"'metricCollapseMethod' must be of class 'character'")
args$metricCollapseMethod <- c("mean", "max")
expect_error(do.call(bettrGetReady, args),
"'metricCollapseMethod' must have length 1")
args$metricCollapseMethod <- "missing"
expect_error(do.call(bettrGetReady, args),
"All values in 'metricCollapseMethod' must be one of")
args <- .args
df0 <- df
df0$metric2 <- list(seq_len(3), seq_len(2), seq_len(5))
args$df <- df0
expect_error(do.call(bettrGetReady, args),
"Encountered metric that could not be identified")
## Check that the function behaves as expected with valid input
## -------------------------------------------------------------------------
## Mostly defaults
out <- bettrGetReady(bettrSE = NULL, df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = NULL,
initialTransforms = list(),
metricInfo = NULL, metricColors = NULL,
idInfo = NULL, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = FALSE, nbrTopIds = 10,
idTopNGrouping = NULL,
keepIds = NULL,
metricGrouping = NULL, metricCollapseGroup = FALSE,
metricCollapseMethod = "mean")
expect_type(out, "list")
expect_named(out, c("plotdata", "scoredata", "idColors", "metricColors",
"metricGrouping", "metricCollapseGroup", "idInfo",
"metricInfo", "metricGroupCol", "methods", "idCol",
"metricCol", "valueCol", "weightCol", "scoreCol"))
expect_s3_class(out$plotdata, "data.frame")
expect_equal(dim(out$plotdata), c(9, 4))
expect_named(out$plotdata, c("Method", "Metric", "ScaledValue", "Weight"))
expect_equal(out$plotdata$Weight, rep(0.2, 9))
## Factor levels of Method indicate performance ranking
expect_equal(out$plotdata$Method, factor(rep(c("M1", "M2", "M3"),
each = 3),
levels = c("M3", "M1", "M2")))
expect_equal(out$plotdata$Metric, rep(c("metric1", "metric2", "metric3"), 3))
expect_equal(out$plotdata$ScaledValue, c(1, 3, 2, 2, 1, 1, 3, 2, NA))
expect_s3_class(out$scoredata, "data.frame")
expect_equal(dim(out$scoredata), c(3, 2))
expect_named(out$scoredata, c("Method", "Score"))
expect_equal(out$scoredata$Method, c("M3", "M1", "M2"))
expect_equal(out$scoredata$Score, c(2.5, 2, 4/3))
expect_type(out$idColors, "list")
expect_named(out$idColors, "Method")
expect_length(out$idColors$Method, 3)
expect_type(out$metricColors, "list")
expect_named(out$metricColors, "Metric")
expect_length(out$metricColors$Metric, 3)
expect_equal(out$metricGrouping, "---")
expect_false(out$metricCollapseGroup)
expect_null(out$idInfo)
expect_null(out$metricInfo)
expect_equal(out$metricGroupCol, "metricGroup")
expect_equal(out$methods, c("M1", "M2", "M3"))
expect_equal(out$idCol, "Method")
expect_equal(out$metricCol, "Metric")
expect_equal(out$valueCol, "ScaledValue")
expect_equal(out$weightCol, "Weight")
expect_equal(out$scoreCol, "Score")
## Mostly defaults - with bettrSE
se <- assembleSE(df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = NULL,
initialTransforms = list(), metricInfo = NULL,
metricColors = NULL, idInfo = NULL, idColors = NULL)
out <- bettrGetReady(bettrSE = se, df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = NULL,
initialTransforms = list(),
metricInfo = NULL, metricColors = NULL,
idInfo = NULL, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = FALSE, nbrTopIds = 10,
idTopNGrouping = NULL,
keepIds = NULL,
metricGrouping = NULL, metricCollapseGroup = FALSE,
metricCollapseMethod = "mean")
expect_type(out, "list")
expect_named(out, c("plotdata", "scoredata", "idColors", "metricColors",
"metricGrouping", "metricCollapseGroup", "idInfo",
"metricInfo", "metricGroupCol", "methods", "idCol",
"metricCol", "valueCol", "weightCol", "scoreCol"))
expect_s3_class(out$plotdata, "data.frame")
expect_equal(dim(out$plotdata), c(9, 4))
expect_named(out$plotdata, c("Method", "Metric", "ScaledValue", "Weight"))
expect_equal(out$plotdata$Weight, rep(0.2, 9))
## Factor levels of Method indicate performance ranking
expect_equal(out$plotdata$Method, factor(rep(c("M1", "M2", "M3"),
each = 3),
levels = c("M3", "M1", "M2")))
expect_equal(out$plotdata$Metric, rep(c("metric1", "metric2", "metric3"), 3))
expect_equal(out$plotdata$ScaledValue, c(1, 3, 2, 2, 1, 1, 3, 2, NA))
expect_s3_class(out$scoredata, "data.frame")
expect_equal(dim(out$scoredata), c(3, 2))
expect_named(out$scoredata, c("Method", "Score"))
expect_equal(out$scoredata$Method, c("M3", "M1", "M2"))
expect_equal(out$scoredata$Score, c(2.5, 2, 4/3))
expect_type(out$idColors, "list")
expect_named(out$idColors, "Method")
expect_length(out$idColors$Method, 3)
expect_type(out$metricColors, "list")
expect_named(out$metricColors, "Metric")
expect_length(out$metricColors$Metric, 3)
expect_equal(out$metricGrouping, "---")
expect_false(out$metricCollapseGroup)
expect_null(out$idInfo)
expect_null(out$metricInfo)
expect_equal(out$metricGroupCol, "metricGroup")
expect_equal(out$methods, c("M1", "M2", "M3"))
expect_equal(out$idCol, "Method")
expect_equal(out$metricCol, "Metric")
expect_equal(out$valueCol, "ScaledValue")
expect_equal(out$weightCol, "Weight")
expect_equal(out$scoreCol, "Score")
## Recode one variable as categorical
df0 <- df
df0$metric2 <- c("A3", "C1", "F2")
out <- bettrGetReady(bettrSE = NULL, df = df0, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = NULL,
initialTransforms = list(metric2 = list(levels = c("C1", "F2", "A3"))),
metricInfo = NULL, metricColors = NULL,
idInfo = NULL, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = FALSE, nbrTopIds = 10,
idTopNGrouping = NULL,
keepIds = NULL,
metricGrouping = NULL, metricCollapseGroup = FALSE,
metricCollapseMethod = "mean")
expect_type(out, "list")
expect_named(out, c("plotdata", "scoredata", "idColors", "metricColors",
"metricGrouping", "metricCollapseGroup", "idInfo",
"metricInfo", "metricGroupCol", "methods", "idCol",
"metricCol", "valueCol", "weightCol", "scoreCol"))
expect_s3_class(out$plotdata, "data.frame")
expect_equal(dim(out$plotdata), c(9, 4))
expect_named(out$plotdata, c("Method", "Metric", "ScaledValue", "Weight"))
expect_equal(out$plotdata$Weight, rep(0.2, 9))
## Factor levels of Method indicate performance ranking
expect_equal(out$plotdata$Method, factor(rep(c("M1", "M2", "M3"),
each = 3),
levels = c("M3", "M1", "M2")))
expect_equal(out$plotdata$Metric, rep(c("metric1", "metric2", "metric3"), 3))
expect_equal(out$plotdata$ScaledValue, c(1, 3, 2, 2, 1, 1, 3, 2, NA))
expect_s3_class(out$scoredata, "data.frame")
expect_equal(dim(out$scoredata), c(3, 2))
expect_named(out$scoredata, c("Method", "Score"))
expect_equal(out$scoredata$Method, c("M3", "M1", "M2"))
expect_equal(out$scoredata$Score, c(2.5, 2, 4/3))
expect_type(out$idColors, "list")
expect_named(out$idColors, "Method")
expect_length(out$idColors$Method, 3)
expect_type(out$metricColors, "list")
expect_named(out$metricColors, "Metric")
expect_length(out$metricColors$Metric, 3)
expect_equal(out$metricGrouping, "---")
expect_false(out$metricCollapseGroup)
expect_null(out$idInfo)
expect_null(out$metricInfo)
expect_equal(out$metricGroupCol, "metricGroup")
expect_equal(out$methods, c("M1", "M2", "M3"))
expect_equal(out$idCol, "Method")
expect_equal(out$metricCol, "Metric")
expect_equal(out$valueCol, "ScaledValue")
expect_equal(out$weightCol, "Weight")
expect_equal(out$scoreCol, "Score")
## Different weighting -> different levels in out$plotdata$Method
out <- bettrGetReady(bettrSE = NULL, df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = c(metric1 = 0, metric2 = 1, metric3 = 0),
initialTransforms = list(),
metricInfo = NULL, metricColors = NULL,
idInfo = NULL, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = FALSE, nbrTopIds = 10,
idTopNGrouping = NULL,
keepIds = NULL,
metricGrouping = NULL, metricCollapseGroup = FALSE,
metricCollapseMethod = "mean")
expect_type(out, "list")
expect_named(out, c("plotdata", "scoredata", "idColors", "metricColors",
"metricGrouping", "metricCollapseGroup", "idInfo",
"metricInfo", "metricGroupCol", "methods", "idCol",
"metricCol", "valueCol", "weightCol", "scoreCol"))
expect_s3_class(out$plotdata, "data.frame")
expect_equal(dim(out$plotdata), c(9, 4))
expect_named(out$plotdata, c("Method", "Metric", "ScaledValue", "Weight"))
expect_equal(out$plotdata$Weight, rep(c(0, 1, 0), 3))
## Factor levels of Method indicate performance ranking
expect_equal(out$plotdata$Method, factor(rep(c("M1", "M2", "M3"),
each = 3),
levels = c("M1", "M3", "M2")))
expect_equal(out$plotdata$Metric, rep(c("metric1", "metric2", "metric3"), 3))
expect_equal(out$plotdata$ScaledValue, c(1, 3, 2, 2, 1, 1, 3, 2, NA))
expect_s3_class(out$scoredata, "data.frame")
expect_equal(dim(out$scoredata), c(3, 2))
expect_named(out$scoredata, c("Method", "Score"))
expect_equal(out$scoredata$Method, c("M1", "M3", "M2"))
expect_equal(out$scoredata$Score, c(3, 2, 1))
expect_type(out$idColors, "list")
expect_named(out$idColors, "Method")
expect_length(out$idColors$Method, 3)
expect_type(out$metricColors, "list")
expect_named(out$metricColors, "Metric")
expect_length(out$metricColors$Metric, 3)
expect_equal(out$metricGrouping, "---")
expect_false(out$metricCollapseGroup)
expect_null(out$idInfo)
expect_null(out$metricInfo)
expect_equal(out$metricGroupCol, "metricGroup")
expect_equal(out$methods, c("M1", "M2", "M3"))
expect_equal(out$idCol, "Method")
expect_equal(out$metricCol, "Metric")
expect_equal(out$valueCol, "ScaledValue")
expect_equal(out$weightCol, "Weight")
expect_equal(out$scoreCol, "Score")
## Transform metrics
out <- bettrGetReady(bettrSE = NULL, df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = c(metric1 = 1, metric2 = 1, metric3 = 0),
initialTransforms = list(metric2 = list(flip = TRUE),
metric1 = list(transform = "[0,1]")),
metricInfo = NULL,
metricColors = list(Metric = c(metric1 = "blue", metric2 = "green")),
idInfo = NULL, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = FALSE, nbrTopIds = 10,
idTopNGrouping = NULL,
keepIds = NULL,
metricGrouping = NULL, metricCollapseGroup = FALSE,
metricCollapseMethod = "mean")
expect_type(out, "list")
expect_named(out, c("plotdata", "scoredata", "idColors", "metricColors",
"metricGrouping", "metricCollapseGroup", "idInfo",
"metricInfo", "metricGroupCol", "methods", "idCol",
"metricCol", "valueCol", "weightCol", "scoreCol"))
expect_s3_class(out$plotdata, "data.frame")
expect_equal(dim(out$plotdata), c(9, 4))
expect_named(out$plotdata, c("Method", "Metric", "ScaledValue", "Weight"))
expect_equal(out$plotdata$Weight, rep(c(1, 1, 0), 3))
## Factor levels of Method indicate performance ranking
expect_equal(out$plotdata$Method, factor(rep(c("M1", "M2", "M3"),
each = 3),
levels = c("M2", "M3", "M1")))
expect_equal(out$plotdata$Metric, rep(c("metric1", "metric2", "metric3"), 3))
expect_equal(out$plotdata$ScaledValue, c(0, -3, 2, 0.5, -1, 1, 1, -2, NA))
expect_s3_class(out$scoredata, "data.frame")
expect_equal(dim(out$scoredata), c(3, 2))
expect_named(out$scoredata, c("Method", "Score"))
expect_equal(out$scoredata$Method, c("M2", "M3", "M1"))
expect_equal(out$scoredata$Score, c(-0.25, -0.5, -1.5))
expect_type(out$idColors, "list")
expect_named(out$idColors, "Method")
expect_length(out$idColors$Method, 3)
expect_type(out$metricColors, "list")
expect_named(out$metricColors, "Metric")
expect_length(out$metricColors$Metric, 2)
expect_equal(out$metricColors, list(Metric = c(metric1 = "blue", metric2 = "green")))
expect_equal(out$metricGrouping, "---")
expect_false(out$metricCollapseGroup)
expect_null(out$idInfo)
expect_null(out$metricInfo)
expect_equal(out$metricGroupCol, "metricGroup")
expect_equal(out$methods, c("M1", "M2", "M3"))
expect_equal(out$idCol, "Method")
expect_equal(out$metricCol, "Metric")
expect_equal(out$valueCol, "ScaledValue")
expect_equal(out$weightCol, "Weight")
expect_equal(out$scoreCol, "Score")
## Group metrics, only top 2 methods
out <- bettrGetReady(bettrSE = NULL, df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = c(metric1 = 0, metric2 = 1, metric3 = 0,
Group_G1 = 1/5, Group_G2 = 3/5),
initialTransforms = list(),
metricInfo = metricInfo, metricColors = NULL,
idInfo = idInfo, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = TRUE, nbrTopIds = 2,
idTopNGrouping = NULL,
keepIds = NULL,
metricGrouping = "Group", metricCollapseGroup = TRUE,
metricCollapseMethod = "mean")
expect_type(out, "list")
expect_named(out, c("plotdata", "scoredata", "idColors", "metricColors",
"metricGrouping", "metricCollapseGroup", "idInfo",
"metricInfo", "metricGroupCol", "methods", "idCol",
"metricCol", "valueCol", "weightCol", "scoreCol"))
expect_s3_class(out$plotdata, "data.frame")
expect_equal(dim(out$plotdata), c(4, 5))
expect_named(out$plotdata, c("Method", "metricGroup", "ScaledValue",
"Weight", "Metric"))
expect_equal(out$plotdata$Weight, rep(c(1, 3)/5, 2))
## Factor levels of Method indicate performance ranking
expect_equal(out$plotdata$Method, factor(rep(c("M1", "M3"),
each = 2),
levels = c("M3", "M1")))
expect_equal(out$plotdata$Metric, rep(c("G1", "G2"), 2))
expect_equal(out$plotdata$ScaledValue, c(1, 2.5, 3, 2))
expect_s3_class(out$scoredata, "data.frame")
expect_equal(dim(out$scoredata), c(2, 3))
expect_named(out$scoredata, c("Method", "Score", "Type"))
expect_equal(out$scoredata$Method, c("M3", "M1"))
expect_equal(out$scoredata$Score, c(2.25, 2.125))
expect_type(out$idColors, "list")
expect_named(out$idColors, c("Type", "Method"))
expect_length(out$idColors$Method, 3)
expect_type(out$metricColors, "list")
expect_named(out$metricColors, c("Group", "Metric"))
expect_length(out$metricColors$Metric, 3)
expect_equal(out$metricGrouping, "Group")
expect_true(out$metricCollapseGroup)
expect_equal(out$idInfo, idInfo)
expect_equal(out$metricInfo, metricInfo)
expect_equal(out$metricGroupCol, "metricGroup")
expect_equal(out$methods, c("M1", "M2", "M3"))
expect_equal(out$idCol, "Method")
expect_equal(out$metricCol, "Metric")
expect_equal(out$valueCol, "ScaledValue")
expect_equal(out$weightCol, "Weight")
expect_equal(out$scoreCol, "Score")
## Group metrics, only top 2 methods - with bettrSE
se <- assembleSE(df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = c(metric1 = 0, metric2 = 1, metric3 = 0,
Group_G1 = 1/5, Group_G2 = 3/5),
initialTransforms = list(), metricInfo = metricInfo,
metricColors = NULL, idInfo = idInfo, idColors = NULL)
out <- bettrGetReady(bettrSE = se, df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = c(metric1 = 0, metric2 = 1, metric3 = 0,
Group_G1 = 1, Group_G2 = 3),
initialTransforms = list(),
metricInfo = metricInfo, metricColors = NULL,
idInfo = idInfo, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = TRUE, nbrTopIds = 2,
idTopNGrouping = NULL,
keepIds = NULL,
metricGrouping = "Group", metricCollapseGroup = TRUE,
metricCollapseMethod = "mean")
expect_type(out, "list")
expect_named(out, c("plotdata", "scoredata", "idColors", "metricColors",
"metricGrouping", "metricCollapseGroup", "idInfo",
"metricInfo", "metricGroupCol", "methods", "idCol",
"metricCol", "valueCol", "weightCol", "scoreCol"))
expect_s3_class(out$plotdata, "data.frame")
expect_equal(dim(out$plotdata), c(4, 5))
expect_named(out$plotdata, c("Method", "metricGroup", "ScaledValue",
"Weight", "Metric"))
expect_equal(out$plotdata$Weight, rep(c(1, 3)/5, 2))
## Factor levels of Method indicate performance ranking
expect_equal(out$plotdata$Method, factor(rep(c("M1", "M3"),
each = 2),
levels = c("M3", "M1")))
expect_equal(out$plotdata$Metric, rep(c("G1", "G2"), 2))
expect_equal(out$plotdata$ScaledValue, c(1, 2.5, 3, 2))
expect_s3_class(out$scoredata, "data.frame")
expect_equal(dim(out$scoredata), c(2, 3))
expect_named(out$scoredata, c("Method", "Score", "Type"))
expect_equal(out$scoredata$Method, c("M3", "M1"))
expect_equal(out$scoredata$Score, c(2.25, 2.125))
expect_type(out$idColors, "list")
expect_named(out$idColors, c("Type", "Method"))
expect_length(out$idColors$Method, 3)
expect_type(out$metricColors, "list")
expect_named(out$metricColors, c("Group", "Metric"))
expect_length(out$metricColors$Metric, 3)
expect_equal(out$metricGrouping, "Group")
expect_true(out$metricCollapseGroup)
expect_equal(out$idInfo, idInfo, ignore_attr = TRUE)
expect_equal(out$metricInfo, metricInfo, ignore_attr = TRUE)
expect_equal(out$metricGroupCol, "metricGroup")
expect_equal(out$methods, c("M1", "M2", "M3"))
expect_equal(out$idCol, "Method")
expect_equal(out$metricCol, "Metric")
expect_equal(out$valueCol, "ScaledValue")
expect_equal(out$weightCol, "Weight")
expect_equal(out$scoreCol, "Score")
## Group metrics, top 2 methods within each type
out <- bettrGetReady(bettrSE = NULL, df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = c(metric1 = 0, metric2 = 1, metric3 = 0,
Group_G1 = 1/5, Group_G2 = 3/5),
initialTransforms = list(),
metricInfo = metricInfo, metricColors = NULL,
idInfo = idInfo, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = TRUE, nbrTopIds = 2,
idTopNGrouping = "Type",
keepIds = NULL,
metricGrouping = "Group", metricCollapseGroup = TRUE,
metricCollapseMethod = "mean")
expect_type(out, "list")
expect_named(out, c("plotdata", "scoredata", "idColors", "metricColors",
"metricGrouping", "metricCollapseGroup", "idInfo",
"metricInfo", "metricGroupCol", "methods", "idCol",
"metricCol", "valueCol", "weightCol", "scoreCol"))
expect_s3_class(out$plotdata, "data.frame")
expect_equal(dim(out$plotdata), c(6, 5))
expect_named(out$plotdata, c("Method", "metricGroup", "ScaledValue",
"Weight", "Metric"))
expect_equal(out$plotdata$Weight, rep(c(1, 3)/5, 3))
## Factor levels of Method indicate performance ranking
expect_equal(out$plotdata$Method, factor(rep(c("M1", "M2", "M3"),
each = 2),
levels = c("M3", "M1", "M2")))
expect_equal(out$plotdata$Metric, rep(c("G1", "G2"), 3))
expect_equal(out$plotdata$ScaledValue, c(1, 2.5, 2, 1, 3, 2))
expect_s3_class(out$scoredata, "data.frame")
expect_equal(dim(out$scoredata), c(3, 3))
expect_named(out$scoredata, c("Method", "Score", "Type"))
expect_equal(out$scoredata$Method, c("M3", "M1", "M2"))
expect_equal(out$scoredata$Score, c(2.25, 2.125, 1.25))
expect_type(out$idColors, "list")
expect_named(out$idColors, c("Type", "Method"))
expect_length(out$idColors$Method, 3)
expect_type(out$metricColors, "list")
expect_named(out$metricColors, c("Group", "Metric"))
expect_length(out$metricColors$Metric, 3)
expect_equal(out$metricGrouping, "Group")
expect_true(out$metricCollapseGroup)
expect_equal(out$idInfo, idInfo)
expect_equal(out$metricInfo, metricInfo)
expect_equal(out$metricGroupCol, "metricGroup")
expect_equal(out$methods, c("M1", "M2", "M3"))
expect_equal(out$idCol, "Method")
expect_equal(out$metricCol, "Metric")
expect_equal(out$valueCol, "ScaledValue")
expect_equal(out$weightCol, "Weight")
expect_equal(out$scoreCol, "Score")
})
federicomarini/bettr documentation built on Nov. 5, 2024, 4:33 a.m.
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test_that("bettrGetReady works", {
df <- data.frame(Method = c("M1", "M2", "M3"),
metric1 = c(1, 2, 3),
metric2 = c(3, 1, 2),
metric3 = c(2, 1, NA))
metricInfo <- data.frame(Metric = c("metric1", "metric2", "metric3"),
Group = c("G1", "G2", "G2"))
idInfo <- data.frame(Method = c("M1", "M2", "M3"),
Type = c("T1", "T1", "T2"))
## Check that the function returns an error with incorrect input
## -------------------------------------------------------------------------
.args <- list(bettrSE = NULL, df = df, idCol = "Method",
metrics = c("metric1", "metric2"),
initialWeights = NULL,
initialTransforms = list(),
metricInfo = NULL, metricColors = NULL,
idInfo = NULL, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = FALSE, nbrTopIds = 10,
idTopNGrouping = NULL,
keepIds = NULL,
metricGrouping = NULL, metricCollapseGroup = FALSE,
metricCollapseMethod = "mean")
args <- .args
args$df <- 1
expect_error(do.call(bettrGetReady, args),
"'df' must be of class 'data.frame'")
args <- .args
args$idCol <- 1
expect_error(do.call(bettrGetReady, args),
"'idCol' must be of class 'character'")
args$idCol <- c("Method", "metric1")
expect_error(do.call(bettrGetReady, args),
"'idCol' must have length 1")
args <- .args
args$metrics <- 1
expect_error(do.call(bettrGetReady, args),
"'metrics' must be of class 'character'")
args$metrics <- "missing"
expect_error(do.call(bettrGetReady, args),
"All values in 'metrics' must be one of")
args <- .args
args$initialWeights <- "1"
expect_error(do.call(bettrGetReady, args),
"'initialWeights' must be of class 'numeric'")
args <- .args
args$initialTransforms <- 1
expect_error(do.call(bettrGetReady, args),
"'initialTransforms' must be of class 'list'")
args <- .args
args$metricInfo <- seq(1, 3)
expect_error(do.call(bettrGetReady, args),
"'metricInfo' must be of class 'data.frame'")
args <- .args
args$metricColors <- seq(1, 3)
expect_error(do.call(bettrGetReady, args),
"'metricColors' must be of class 'list'")
args <- .args
args$idInfo <- seq(1, 3)
expect_error(do.call(bettrGetReady, args),
"'idInfo' must be of class 'data.frame'")
args <- .args
args$idColors <- seq(1, 3)
expect_error(do.call(bettrGetReady, args),
"'idColors' must be of class 'list'")
args <- .args
args$scoreMethod <- 1
expect_error(do.call(bettrGetReady, args),
"'scoreMethod' must be of class 'character'")
args$scoreMethod <- c("weighted mean", "weighted median")
expect_error(do.call(bettrGetReady, args),
"'scoreMethod' must have length 1")
args$scoreMethod <- "missing"
expect_error(do.call(bettrGetReady, args),
"All values in 'scoreMethod' must be one of")
args <- .args
args$idOrdering <- 1
expect_error(do.call(bettrGetReady, args),
"'idOrdering' must be of class 'character'")
args$idOrdering <- c("high-to-low", "low-to-high")
expect_error(do.call(bettrGetReady, args),
"'idOrdering' must have length 1")
args$idOrdering <- "missing"
expect_error(do.call(bettrGetReady, args),
"All values in 'idOrdering' must be one of")
args <- .args
args$showOnlyTopIds <- 1
expect_error(do.call(bettrGetReady, args),
"'showOnlyTopIds' must be of class 'logical'")
args$showOnlyTopIds <- c(TRUE, FALSE)
expect_error(do.call(bettrGetReady, args),
"'showOnlyTopIds' must have length 1")
args <- .args
args$nbrTopIds <- TRUE
expect_error(do.call(bettrGetReady, args),
"'nbrTopIds' must be of class 'numeric'")
args$nbrTopIds <- c(1, 2)
expect_error(do.call(bettrGetReady, args),
"'nbrTopIds' must have length 1")
args <- .args
args$idTopNGrouping <- TRUE
expect_error(do.call(bettrGetReady, args),
"'idTopNGrouping' must be of class 'character'")
args$idTopNGrouping <- c("Group", "Group")
expect_error(do.call(bettrGetReady, args),
"'idTopNGrouping' must have length 1")
args <- .args
args$keepIds <- TRUE
expect_error(do.call(bettrGetReady, args),
"'keepIds' must be of class 'character'")
args <- .args
args$metricGrouping <- TRUE
expect_error(do.call(bettrGetReady, args),
"'metricGrouping' must be of class 'character'")
args$metricGrouping <- c("Group", "Group")
expect_error(do.call(bettrGetReady, args),
"'metricGrouping' must have length 1")
args <- .args
args$metricCollapseGroup <- 1
expect_error(do.call(bettrGetReady, args),
"'metricCollapseGroup' must be of class 'logical'")
args$metricCollapseGroup <- c(TRUE, FALSE)
expect_error(do.call(bettrGetReady, args),
"'metricCollapseGroup' must have length 1")
args <- .args
args$metricCollapseMethod <- 1
expect_error(do.call(bettrGetReady, args),
"'metricCollapseMethod' must be of class 'character'")
args$metricCollapseMethod <- c("mean", "max")
expect_error(do.call(bettrGetReady, args),
"'metricCollapseMethod' must have length 1")
args$metricCollapseMethod <- "missing"
expect_error(do.call(bettrGetReady, args),
"All values in 'metricCollapseMethod' must be one of")
args <- .args
df0 <- df
df0$metric2 <- list(seq_len(3), seq_len(2), seq_len(5))
args$df <- df0
expect_error(do.call(bettrGetReady, args),
"Encountered metric that could not be identified")
## Check that the function behaves as expected with valid input
## -------------------------------------------------------------------------
## Mostly defaults
out <- bettrGetReady(bettrSE = NULL, df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = NULL,
initialTransforms = list(),
metricInfo = NULL, metricColors = NULL,
idInfo = NULL, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = FALSE, nbrTopIds = 10,
idTopNGrouping = NULL,
keepIds = NULL,
metricGrouping = NULL, metricCollapseGroup = FALSE,
metricCollapseMethod = "mean")
expect_type(out, "list")
expect_named(out, c("plotdata", "scoredata", "idColors", "metricColors",
"metricGrouping", "metricCollapseGroup", "idInfo",
"metricInfo", "metricGroupCol", "methods", "idCol",
"metricCol", "valueCol", "weightCol", "scoreCol"))
expect_s3_class(out$plotdata, "data.frame")
expect_equal(dim(out$plotdata), c(9, 4))
expect_named(out$plotdata, c("Method", "Metric", "ScaledValue", "Weight"))
expect_equal(out$plotdata$Weight, rep(0.2, 9))
## Factor levels of Method indicate performance ranking
expect_equal(out$plotdata$Method, factor(rep(c("M1", "M2", "M3"),
each = 3),
levels = c("M3", "M1", "M2")))
expect_equal(out$plotdata$Metric, rep(c("metric1", "metric2", "metric3"), 3))
expect_equal(out$plotdata$ScaledValue, c(1, 3, 2, 2, 1, 1, 3, 2, NA))
expect_s3_class(out$scoredata, "data.frame")
expect_equal(dim(out$scoredata), c(3, 2))
expect_named(out$scoredata, c("Method", "Score"))
expect_equal(out$scoredata$Method, c("M3", "M1", "M2"))
expect_equal(out$scoredata$Score, c(2.5, 2, 4/3))
expect_type(out$idColors, "list")
expect_named(out$idColors, "Method")
expect_length(out$idColors$Method, 3)
expect_type(out$metricColors, "list")
expect_named(out$metricColors, "Metric")
expect_length(out$metricColors$Metric, 3)
expect_equal(out$metricGrouping, "---")
expect_false(out$metricCollapseGroup)
expect_null(out$idInfo)
expect_null(out$metricInfo)
expect_equal(out$metricGroupCol, "metricGroup")
expect_equal(out$methods, c("M1", "M2", "M3"))
expect_equal(out$idCol, "Method")
expect_equal(out$metricCol, "Metric")
expect_equal(out$valueCol, "ScaledValue")
expect_equal(out$weightCol, "Weight")
expect_equal(out$scoreCol, "Score")
## Mostly defaults - with bettrSE
se <- assembleSE(df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = NULL,
initialTransforms = list(), metricInfo = NULL,
metricColors = NULL, idInfo = NULL, idColors = NULL)
out <- bettrGetReady(bettrSE = se, df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = NULL,
initialTransforms = list(),
metricInfo = NULL, metricColors = NULL,
idInfo = NULL, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = FALSE, nbrTopIds = 10,
idTopNGrouping = NULL,
keepIds = NULL,
metricGrouping = NULL, metricCollapseGroup = FALSE,
metricCollapseMethod = "mean")
expect_type(out, "list")
expect_named(out, c("plotdata", "scoredata", "idColors", "metricColors",
"metricGrouping", "metricCollapseGroup", "idInfo",
"metricInfo", "metricGroupCol", "methods", "idCol",
"metricCol", "valueCol", "weightCol", "scoreCol"))
expect_s3_class(out$plotdata, "data.frame")
expect_equal(dim(out$plotdata), c(9, 4))
expect_named(out$plotdata, c("Method", "Metric", "ScaledValue", "Weight"))
expect_equal(out$plotdata$Weight, rep(0.2, 9))
## Factor levels of Method indicate performance ranking
expect_equal(out$plotdata$Method, factor(rep(c("M1", "M2", "M3"),
each = 3),
levels = c("M3", "M1", "M2")))
expect_equal(out$plotdata$Metric, rep(c("metric1", "metric2", "metric3"), 3))
expect_equal(out$plotdata$ScaledValue, c(1, 3, 2, 2, 1, 1, 3, 2, NA))
expect_s3_class(out$scoredata, "data.frame")
expect_equal(dim(out$scoredata), c(3, 2))
expect_named(out$scoredata, c("Method", "Score"))
expect_equal(out$scoredata$Method, c("M3", "M1", "M2"))
expect_equal(out$scoredata$Score, c(2.5, 2, 4/3))
expect_type(out$idColors, "list")
expect_named(out$idColors, "Method")
expect_length(out$idColors$Method, 3)
expect_type(out$metricColors, "list")
expect_named(out$metricColors, "Metric")
expect_length(out$metricColors$Metric, 3)
expect_equal(out$metricGrouping, "---")
expect_false(out$metricCollapseGroup)
expect_null(out$idInfo)
expect_null(out$metricInfo)
expect_equal(out$metricGroupCol, "metricGroup")
expect_equal(out$methods, c("M1", "M2", "M3"))
expect_equal(out$idCol, "Method")
expect_equal(out$metricCol, "Metric")
expect_equal(out$valueCol, "ScaledValue")
expect_equal(out$weightCol, "Weight")
expect_equal(out$scoreCol, "Score")
## Recode one variable as categorical
df0 <- df
df0$metric2 <- c("A3", "C1", "F2")
out <- bettrGetReady(bettrSE = NULL, df = df0, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = NULL,
initialTransforms = list(metric2 = list(levels = c("C1", "F2", "A3"))),
metricInfo = NULL, metricColors = NULL,
idInfo = NULL, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = FALSE, nbrTopIds = 10,
idTopNGrouping = NULL,
keepIds = NULL,
metricGrouping = NULL, metricCollapseGroup = FALSE,
metricCollapseMethod = "mean")
expect_type(out, "list")
expect_named(out, c("plotdata", "scoredata", "idColors", "metricColors",
"metricGrouping", "metricCollapseGroup", "idInfo",
"metricInfo", "metricGroupCol", "methods", "idCol",
"metricCol", "valueCol", "weightCol", "scoreCol"))
expect_s3_class(out$plotdata, "data.frame")
expect_equal(dim(out$plotdata), c(9, 4))
expect_named(out$plotdata, c("Method", "Metric", "ScaledValue", "Weight"))
expect_equal(out$plotdata$Weight, rep(0.2, 9))
## Factor levels of Method indicate performance ranking
expect_equal(out$plotdata$Method, factor(rep(c("M1", "M2", "M3"),
each = 3),
levels = c("M3", "M1", "M2")))
expect_equal(out$plotdata$Metric, rep(c("metric1", "metric2", "metric3"), 3))
expect_equal(out$plotdata$ScaledValue, c(1, 3, 2, 2, 1, 1, 3, 2, NA))
expect_s3_class(out$scoredata, "data.frame")
expect_equal(dim(out$scoredata), c(3, 2))
expect_named(out$scoredata, c("Method", "Score"))
expect_equal(out$scoredata$Method, c("M3", "M1", "M2"))
expect_equal(out$scoredata$Score, c(2.5, 2, 4/3))
expect_type(out$idColors, "list")
expect_named(out$idColors, "Method")
expect_length(out$idColors$Method, 3)
expect_type(out$metricColors, "list")
expect_named(out$metricColors, "Metric")
expect_length(out$metricColors$Metric, 3)
expect_equal(out$metricGrouping, "---")
expect_false(out$metricCollapseGroup)
expect_null(out$idInfo)
expect_null(out$metricInfo)
expect_equal(out$metricGroupCol, "metricGroup")
expect_equal(out$methods, c("M1", "M2", "M3"))
expect_equal(out$idCol, "Method")
expect_equal(out$metricCol, "Metric")
expect_equal(out$valueCol, "ScaledValue")
expect_equal(out$weightCol, "Weight")
expect_equal(out$scoreCol, "Score")
## Different weighting -> different levels in out$plotdata$Method
out <- bettrGetReady(bettrSE = NULL, df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = c(metric1 = 0, metric2 = 1, metric3 = 0),
initialTransforms = list(),
metricInfo = NULL, metricColors = NULL,
idInfo = NULL, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = FALSE, nbrTopIds = 10,
idTopNGrouping = NULL,
keepIds = NULL,
metricGrouping = NULL, metricCollapseGroup = FALSE,
metricCollapseMethod = "mean")
expect_type(out, "list")
expect_named(out, c("plotdata", "scoredata", "idColors", "metricColors",
"metricGrouping", "metricCollapseGroup", "idInfo",
"metricInfo", "metricGroupCol", "methods", "idCol",
"metricCol", "valueCol", "weightCol", "scoreCol"))
expect_s3_class(out$plotdata, "data.frame")
expect_equal(dim(out$plotdata), c(9, 4))
expect_named(out$plotdata, c("Method", "Metric", "ScaledValue", "Weight"))
expect_equal(out$plotdata$Weight, rep(c(0, 1, 0), 3))
## Factor levels of Method indicate performance ranking
expect_equal(out$plotdata$Method, factor(rep(c("M1", "M2", "M3"),
each = 3),
levels = c("M1", "M3", "M2")))
expect_equal(out$plotdata$Metric, rep(c("metric1", "metric2", "metric3"), 3))
expect_equal(out$plotdata$ScaledValue, c(1, 3, 2, 2, 1, 1, 3, 2, NA))
expect_s3_class(out$scoredata, "data.frame")
expect_equal(dim(out$scoredata), c(3, 2))
expect_named(out$scoredata, c("Method", "Score"))
expect_equal(out$scoredata$Method, c("M1", "M3", "M2"))
expect_equal(out$scoredata$Score, c(3, 2, 1))
expect_type(out$idColors, "list")
expect_named(out$idColors, "Method")
expect_length(out$idColors$Method, 3)
expect_type(out$metricColors, "list")
expect_named(out$metricColors, "Metric")
expect_length(out$metricColors$Metric, 3)
expect_equal(out$metricGrouping, "---")
expect_false(out$metricCollapseGroup)
expect_null(out$idInfo)
expect_null(out$metricInfo)
expect_equal(out$metricGroupCol, "metricGroup")
expect_equal(out$methods, c("M1", "M2", "M3"))
expect_equal(out$idCol, "Method")
expect_equal(out$metricCol, "Metric")
expect_equal(out$valueCol, "ScaledValue")
expect_equal(out$weightCol, "Weight")
expect_equal(out$scoreCol, "Score")
## Transform metrics
out <- bettrGetReady(bettrSE = NULL, df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = c(metric1 = 1, metric2 = 1, metric3 = 0),
initialTransforms = list(metric2 = list(flip = TRUE),
metric1 = list(transform = "[0,1]")),
metricInfo = NULL,
metricColors = list(Metric = c(metric1 = "blue", metric2 = "green")),
idInfo = NULL, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = FALSE, nbrTopIds = 10,
idTopNGrouping = NULL,
keepIds = NULL,
metricGrouping = NULL, metricCollapseGroup = FALSE,
metricCollapseMethod = "mean")
expect_type(out, "list")
expect_named(out, c("plotdata", "scoredata", "idColors", "metricColors",
"metricGrouping", "metricCollapseGroup", "idInfo",
"metricInfo", "metricGroupCol", "methods", "idCol",
"metricCol", "valueCol", "weightCol", "scoreCol"))
expect_s3_class(out$plotdata, "data.frame")
expect_equal(dim(out$plotdata), c(9, 4))
expect_named(out$plotdata, c("Method", "Metric", "ScaledValue", "Weight"))
expect_equal(out$plotdata$Weight, rep(c(1, 1, 0), 3))
## Factor levels of Method indicate performance ranking
expect_equal(out$plotdata$Method, factor(rep(c("M1", "M2", "M3"),
each = 3),
levels = c("M2", "M3", "M1")))
expect_equal(out$plotdata$Metric, rep(c("metric1", "metric2", "metric3"), 3))
expect_equal(out$plotdata$ScaledValue, c(0, -3, 2, 0.5, -1, 1, 1, -2, NA))
expect_s3_class(out$scoredata, "data.frame")
expect_equal(dim(out$scoredata), c(3, 2))
expect_named(out$scoredata, c("Method", "Score"))
expect_equal(out$scoredata$Method, c("M2", "M3", "M1"))
expect_equal(out$scoredata$Score, c(-0.25, -0.5, -1.5))
expect_type(out$idColors, "list")
expect_named(out$idColors, "Method")
expect_length(out$idColors$Method, 3)
expect_type(out$metricColors, "list")
expect_named(out$metricColors, "Metric")
expect_length(out$metricColors$Metric, 2)
expect_equal(out$metricColors, list(Metric = c(metric1 = "blue", metric2 = "green")))
expect_equal(out$metricGrouping, "---")
expect_false(out$metricCollapseGroup)
expect_null(out$idInfo)
expect_null(out$metricInfo)
expect_equal(out$metricGroupCol, "metricGroup")
expect_equal(out$methods, c("M1", "M2", "M3"))
expect_equal(out$idCol, "Method")
expect_equal(out$metricCol, "Metric")
expect_equal(out$valueCol, "ScaledValue")
expect_equal(out$weightCol, "Weight")
expect_equal(out$scoreCol, "Score")
## Group metrics, only top 2 methods
out <- bettrGetReady(bettrSE = NULL, df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = c(metric1 = 0, metric2 = 1, metric3 = 0,
Group_G1 = 1/5, Group_G2 = 3/5),
initialTransforms = list(),
metricInfo = metricInfo, metricColors = NULL,
idInfo = idInfo, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = TRUE, nbrTopIds = 2,
idTopNGrouping = NULL,
keepIds = NULL,
metricGrouping = "Group", metricCollapseGroup = TRUE,
metricCollapseMethod = "mean")
expect_type(out, "list")
expect_named(out, c("plotdata", "scoredata", "idColors", "metricColors",
"metricGrouping", "metricCollapseGroup", "idInfo",
"metricInfo", "metricGroupCol", "methods", "idCol",
"metricCol", "valueCol", "weightCol", "scoreCol"))
expect_s3_class(out$plotdata, "data.frame")
expect_equal(dim(out$plotdata), c(4, 5))
expect_named(out$plotdata, c("Method", "metricGroup", "ScaledValue",
"Weight", "Metric"))
expect_equal(out$plotdata$Weight, rep(c(1, 3)/5, 2))
## Factor levels of Method indicate performance ranking
expect_equal(out$plotdata$Method, factor(rep(c("M1", "M3"),
each = 2),
levels = c("M3", "M1")))
expect_equal(out$plotdata$Metric, rep(c("G1", "G2"), 2))
expect_equal(out$plotdata$ScaledValue, c(1, 2.5, 3, 2))
expect_s3_class(out$scoredata, "data.frame")
expect_equal(dim(out$scoredata), c(2, 3))
expect_named(out$scoredata, c("Method", "Score", "Type"))
expect_equal(out$scoredata$Method, c("M3", "M1"))
expect_equal(out$scoredata$Score, c(2.25, 2.125))
expect_type(out$idColors, "list")
expect_named(out$idColors, c("Type", "Method"))
expect_length(out$idColors$Method, 3)
expect_type(out$metricColors, "list")
expect_named(out$metricColors, c("Group", "Metric"))
expect_length(out$metricColors$Metric, 3)
expect_equal(out$metricGrouping, "Group")
expect_true(out$metricCollapseGroup)
expect_equal(out$idInfo, idInfo)
expect_equal(out$metricInfo, metricInfo)
expect_equal(out$metricGroupCol, "metricGroup")
expect_equal(out$methods, c("M1", "M2", "M3"))
expect_equal(out$idCol, "Method")
expect_equal(out$metricCol, "Metric")
expect_equal(out$valueCol, "ScaledValue")
expect_equal(out$weightCol, "Weight")
expect_equal(out$scoreCol, "Score")
## Group metrics, only top 2 methods - with bettrSE
se <- assembleSE(df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = c(metric1 = 0, metric2 = 1, metric3 = 0,
Group_G1 = 1/5, Group_G2 = 3/5),
initialTransforms = list(), metricInfo = metricInfo,
metricColors = NULL, idInfo = idInfo, idColors = NULL)
out <- bettrGetReady(bettrSE = se, df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = c(metric1 = 0, metric2 = 1, metric3 = 0,
Group_G1 = 1, Group_G2 = 3),
initialTransforms = list(),
metricInfo = metricInfo, metricColors = NULL,
idInfo = idInfo, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = TRUE, nbrTopIds = 2,
idTopNGrouping = NULL,
keepIds = NULL,
metricGrouping = "Group", metricCollapseGroup = TRUE,
metricCollapseMethod = "mean")
expect_type(out, "list")
expect_named(out, c("plotdata", "scoredata", "idColors", "metricColors",
"metricGrouping", "metricCollapseGroup", "idInfo",
"metricInfo", "metricGroupCol", "methods", "idCol",
"metricCol", "valueCol", "weightCol", "scoreCol"))
expect_s3_class(out$plotdata, "data.frame")
expect_equal(dim(out$plotdata), c(4, 5))
expect_named(out$plotdata, c("Method", "metricGroup", "ScaledValue",
"Weight", "Metric"))
expect_equal(out$plotdata$Weight, rep(c(1, 3)/5, 2))
## Factor levels of Method indicate performance ranking
expect_equal(out$plotdata$Method, factor(rep(c("M1", "M3"),
each = 2),
levels = c("M3", "M1")))
expect_equal(out$plotdata$Metric, rep(c("G1", "G2"), 2))
expect_equal(out$plotdata$ScaledValue, c(1, 2.5, 3, 2))
expect_s3_class(out$scoredata, "data.frame")
expect_equal(dim(out$scoredata), c(2, 3))
expect_named(out$scoredata, c("Method", "Score", "Type"))
expect_equal(out$scoredata$Method, c("M3", "M1"))
expect_equal(out$scoredata$Score, c(2.25, 2.125))
expect_type(out$idColors, "list")
expect_named(out$idColors, c("Type", "Method"))
expect_length(out$idColors$Method, 3)
expect_type(out$metricColors, "list")
expect_named(out$metricColors, c("Group", "Metric"))
expect_length(out$metricColors$Metric, 3)
expect_equal(out$metricGrouping, "Group")
expect_true(out$metricCollapseGroup)
expect_equal(out$idInfo, idInfo, ignore_attr = TRUE)
expect_equal(out$metricInfo, metricInfo, ignore_attr = TRUE)
expect_equal(out$metricGroupCol, "metricGroup")
expect_equal(out$methods, c("M1", "M2", "M3"))
expect_equal(out$idCol, "Method")
expect_equal(out$metricCol, "Metric")
expect_equal(out$valueCol, "ScaledValue")
expect_equal(out$weightCol, "Weight")
expect_equal(out$scoreCol, "Score")
## Group metrics, top 2 methods within each type
out <- bettrGetReady(bettrSE = NULL, df = df, idCol = "Method",
metrics = c("metric1", "metric2", "metric3"),
initialWeights = c(metric1 = 0, metric2 = 1, metric3 = 0,
Group_G1 = 1/5, Group_G2 = 3/5),
initialTransforms = list(),
metricInfo = metricInfo, metricColors = NULL,
idInfo = idInfo, idColors = NULL,
scoreMethod = "weighted mean",
idOrdering = "high-to-low",
showOnlyTopIds = TRUE, nbrTopIds = 2,
idTopNGrouping = "Type",
keepIds = NULL,
metricGrouping = "Group", metricCollapseGroup = TRUE,
metricCollapseMethod = "mean")
expect_type(out, "list")
expect_named(out, c("plotdata", "scoredata", "idColors", "metricColors",
"metricGrouping", "metricCollapseGroup", "idInfo",
"metricInfo", "metricGroupCol", "methods", "idCol",
"metricCol", "valueCol", "weightCol", "scoreCol"))
expect_s3_class(out$plotdata, "data.frame")
expect_equal(dim(out$plotdata), c(6, 5))
expect_named(out$plotdata, c("Method", "metricGroup", "ScaledValue",
"Weight", "Metric"))
expect_equal(out$plotdata$Weight, rep(c(1, 3)/5, 3))
## Factor levels of Method indicate performance ranking
expect_equal(out$plotdata$Method, factor(rep(c("M1", "M2", "M3"),
each = 2),
levels = c("M3", "M1", "M2")))
expect_equal(out$plotdata$Metric, rep(c("G1", "G2"), 3))
expect_equal(out$plotdata$ScaledValue, c(1, 2.5, 2, 1, 3, 2))
expect_s3_class(out$scoredata, "data.frame")
expect_equal(dim(out$scoredata), c(3, 3))
expect_named(out$scoredata, c("Method", "Score", "Type"))
expect_equal(out$scoredata$Method, c("M3", "M1", "M2"))
expect_equal(out$scoredata$Score, c(2.25, 2.125, 1.25))
expect_type(out$idColors, "list")
expect_named(out$idColors, c("Type", "Method"))
expect_length(out$idColors$Method, 3)
expect_type(out$metricColors, "list")
expect_named(out$metricColors, c("Group", "Metric"))
expect_length(out$metricColors$Metric, 3)
expect_equal(out$metricGrouping, "Group")
expect_true(out$metricCollapseGroup)
expect_equal(out$idInfo, idInfo)
expect_equal(out$metricInfo, metricInfo)
expect_equal(out$metricGroupCol, "metricGroup")
expect_equal(out$methods, c("M1", "M2", "M3"))
expect_equal(out$idCol, "Method")
expect_equal(out$metricCol, "Metric")
expect_equal(out$valueCol, "ScaledValue")
expect_equal(out$weightCol, "Weight")
expect_equal(out$scoreCol, "Score")
})
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