tests/testthat/test-makeLongData.R
In federicomarini/bettr: A Better Way To Explore What Is Best
test_that("long data generation works", {
df <- data.frame(Method = rep(c("A", "B", "C"), each = 3),
Metric = rep(c("m1", "m2", "m3"), 3),
Value = runif(n = 9, min = 0, max = 3)) |>
tidyr::pivot_wider(names_from = Metric, values_from = Value)
metrics <- setdiff(colnames(df), "Method")
metricInfo <- data.frame(Metric = c("m1", "m2", "m3"), num = c(1, 1, 2),
lets3 = c("m", "n", "o"))
idInfo <- data.frame(Method = c("A", "B", "C"), lets = c("a", "b", "b"),
lets2 = c("d", "d", "e"))
## Without grouping
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "---", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
expect_s3_class(ld, "data.frame")
expect_equal(dim(ld), c(9, 3))
expect_named(ld, c("Method", "Metric", "ScaledValue"))
expect_equal(ld$Method, rep(c("A", "B", "C"), each = 3))
expect_equal(ld$Metric, rep(c("m1", "m2", "m3"), 3))
expect_equal(ld$ScaledValue, unlist(c(df[1, -1], df[2, -1], df[3, -1])),
ignore_attr = TRUE)
## With grouping
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "num", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
expect_s3_class(ld, "data.frame")
expect_equal(dim(ld), c(9, 4))
expect_named(ld, c("Method", "Metric", "ScaledValue", "metricGroup"))
expect_equal(ld$Method, rep(c("A", "B", "C"), each = 3))
expect_equal(ld$Metric, rep(c("m1", "m2", "m3"), 3))
expect_equal(ld$metricGroup, rep(c(1, 1, 2), 3))
expect_equal(ld$ScaledValue, unlist(c(df[1, -1], df[2, -1], df[3, -1])),
ignore_attr = TRUE)
## With grouping, don't keep all metrics
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "num", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
expect_s3_class(ld, "data.frame")
expect_equal(dim(ld), c(6, 4))
expect_named(ld, c("Method", "Metric", "ScaledValue", "metricGroup"))
expect_equal(ld$Method, rep(c("A", "B", "C"), each = 2))
expect_equal(ld$Metric, rep(c("m1", "m3"), 3))
expect_equal(ld$metricGroup, rep(c(1, 2), 3))
expect_equal(ld$ScaledValue, unlist(c(df[1, -c(1, 3)], df[2, -c(1, 3)], df[3, -c(1, 3)])),
ignore_attr = TRUE)
})
test_that("adding weights to long data works", {
df <- data.frame(Method = rep(c("A", "B", "C"), each = 3),
Metric = rep(c("m1", "m2", "m3"), 3),
Value = runif(n = 9, min = 0, max = 3)) |>
tidyr::pivot_wider(names_from = Metric, values_from = Value)
metrics <- setdiff(colnames(df), "Method")
metricInfo <- data.frame(Metric = c("m1", "m2", "m3"), num = c(1, 1, 2),
lets3 = c("m", "n", "o"))
idInfo <- data.frame(Method = c("A", "B", "C"), lets = c("a", "b", "b"),
lets2 = c("d", "d", "e"))
## Without grouping
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "---", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
ldw <- .addWeightsToLongData(df = ld, metricCollapseGroup = FALSE,
metricGrouping = "---",
metricGroupCol = "metricGroup",
weights = list(m1_weight = 0.2, m2_weight = 0.3, m3_weight = 0.1,
Metric_m1_weight = 0.1, Metric_m2_weight = 0.5,
Metric_m3_weight = 0.7, num_1_weight = 0.7,
num_2_weight = 0.1, lets3_m_weight = 0.4,
lets3_n_weight = 0.1, lets3_o_weight = 0.9),
weightCol = "Weight", metricCol = "Metric",
metrics = c("m1", "m2", "m3"))
expect_s3_class(ldw, "data.frame")
expect_equal(dim(ldw), c(9, 4))
expect_named(ldw, c("Method", "Metric", "ScaledValue", "Weight"))
expect_equal(ldw$Method, ld$Method)
expect_equal(ldw$Metric, ld$Metric)
expect_equal(ldw$ScaledValue, ld$ScaledValue)
expect_equal(ldw$Weight, c(0.2, 0.3, 0.1, 0.2, 0.3, 0.1, 0.2, 0.3, 0.1))
## With grouping
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "num", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
ldw <- .addWeightsToLongData(df = ld, metricCollapseGroup = TRUE,
metricGrouping = "num",
metricGroupCol = "metricGroup",
weights = list(m1_weight = 0.2, m2_weight = 0.3, m3_weight = 0.1,
Metric_m1_weight = 0.1, Metric_m2_weight = 0.5,
Metric_m3_weight = 0.7, num_1_weight = 0.7,
num_2_weight = 0.1, lets3_m_weight = 0.4,
lets3_n_weight = 0.1, lets3_o_weight = 0.9),
weightCol = "Weight", metricCol = "Metric",
metrics = c("m1", "m2", "m3"))
expect_s3_class(ldw, "data.frame")
expect_equal(dim(ldw), c(9, 5))
expect_named(ldw, c("Method", "Metric", "ScaledValue", "metricGroup", "Weight"))
expect_equal(ldw$Method, ld$Method)
expect_equal(ldw$Metric, ld$Metric)
expect_equal(ldw$ScaledValue, ld$ScaledValue)
expect_equal(ldw$metricGroup, ld$metricGroup)
expect_equal(ldw$Weight, c(0.7, 0.7, 0.1, 0.7, 0.7, 0.1, 0.7, 0.7, 0.1))
## Missing weights -> return NULL
ldw <- .addWeightsToLongData(df = ld, metricCollapseGroup = TRUE,
metricGrouping = "num",
metricGroupCol = "metricGroup",
weights = list(m1_weight = 0.2, m2_weight = 0.3, m3_weight = 0.1,
Metric_m1_weight = 0.1, Metric_m2_weight = 0.5,
Metric_m3_weight = 0.7,
num_2_weight = 0.1, lets3_m_weight = 0.4,
lets3_n_weight = 0.1, lets3_o_weight = 0.9),
weightCol = "Weight", metricCol = "Metric",
metrics = c("m1", "m2", "m3"))
expect_null(ldw)
})
test_that("collapsing long data works", {
df <- data.frame(Method = rep(c("A", "B", "C"), each = 3),
Metric = rep(c("m1", "m2", "m3"), 3),
Value = runif(n = 9, min = 0, max = 3)) |>
tidyr::pivot_wider(names_from = Metric, values_from = Value)
metrics <- setdiff(colnames(df), "Method")
metricInfo <- data.frame(Metric = c("m1", "m2", "m3"), num = c(1, 1, 2),
lets3 = c("m", "n", "o"))
idInfo <- data.frame(Method = c("A", "B", "C"), lets = c("a", "b", "b"),
lets2 = c("d", "d", "e"))
## Without grouping
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "---", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
ldw <- .addWeightsToLongData(df = ld, metricCollapseGroup = FALSE,
metricGrouping = "---",
metricGroupCol = "metricGroup",
weights = list(m1_weight = 0.2, m2_weight = 0.3, m3_weight = 0.1,
Metric_m1_weight = 0.1, Metric_m2_weight = 0.5,
Metric_m3_weight = 0.7, num_1_weight = 0.7,
num_2_weight = 0.1, lets3_m_weight = 0.4,
lets3_n_weight = 0.1, lets3_o_weight = 0.9),
weightCol = "Weight", metricCol = "Metric",
metrics = c("m1", "m2", "m3"))
cld <- .collapseLongData(df = ldw, metricCollapseGroup = FALSE,
metricGrouping = "---", idCol = "Method",
metricGroupCol = "metricGroup",
valueCol = "ScaledValue", weightCol = "Weight",
metricCol = "Metric", collapseMethod = "mean")
expect_equal(ldw, cld)
## With grouping
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "num", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
ldw <- .addWeightsToLongData(df = ld, metricCollapseGroup = TRUE,
metricGrouping = "num",
metricGroupCol = "metricGroup",
weights = list(m1_weight = 0.2, m2_weight = 0.3, m3_weight = 0.1,
Metric_m1_weight = 0.1, Metric_m2_weight = 0.5,
Metric_m3_weight = 0.7, num_1_weight = 0.7,
num_2_weight = 0.1, lets3_m_weight = 0.4,
lets3_n_weight = 0.1, lets3_o_weight = 0.9),
weightCol = "Weight", metricCol = "Metric",
metrics = c("m1", "m2", "m3"))
cld <- .collapseLongData(df = ldw, metricCollapseGroup = TRUE,
metricGrouping = "num", idCol = "Method",
metricGroupCol = "metricGroup",
valueCol = "ScaledValue", weightCol = "Weight",
metricCol = "Metric", collapseMethod = "mean")
expect_s3_class(cld, "data.frame")
expect_equal(dim(cld), c(6, 5))
expect_named(cld, c("Method", "metricGroup", "ScaledValue", "Weight", "Metric"))
expect_equal(cld$metricGroup, cld$Metric)
expect_equal(cld$ScaledValue[cld$Method == "A" & cld$metricGroup == 1],
mean(ldw$ScaledValue[ldw$Method == "A" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "B" & cld$metricGroup == 1],
mean(ldw$ScaledValue[ldw$Method == "B" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "C" & cld$metricGroup == 1],
mean(ldw$ScaledValue[ldw$Method == "C" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "A" & cld$metricGroup == 2],
mean(ldw$ScaledValue[ldw$Method == "A" & ldw$metricGroup == 2]))
expect_equal(cld$ScaledValue[cld$Method == "B" & cld$metricGroup == 2],
mean(ldw$ScaledValue[ldw$Method == "B" & ldw$metricGroup == 2]))
expect_equal(cld$ScaledValue[cld$Method == "C" & cld$metricGroup == 2],
mean(ldw$ScaledValue[ldw$Method == "C" & ldw$metricGroup == 2]))
expect_equal(cld$Weight, c(0.7, 0.1, 0.7, 0.1, 0.7, 0.1))
## With grouping - max collapse
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "num", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
ldw <- .addWeightsToLongData(df = ld, metricCollapseGroup = TRUE,
metricGrouping = "num",
metricGroupCol = "metricGroup",
weights = list(m1_weight = 0.2, m2_weight = 0.3, m3_weight = 0.1,
Metric_m1_weight = 0.1, Metric_m2_weight = 0.5,
Metric_m3_weight = 0.7, num_1_weight = 0.7,
num_2_weight = 0.1, lets3_m_weight = 0.4,
lets3_n_weight = 0.1, lets3_o_weight = 0.9),
weightCol = "Weight", metricCol = "Metric",
metrics = c("m1", "m2", "m3"))
cld <- .collapseLongData(df = ldw, metricCollapseGroup = TRUE,
metricGrouping = "num", idCol = "Method",
metricGroupCol = "metricGroup",
valueCol = "ScaledValue", weightCol = "Weight",
metricCol = "Metric", collapseMethod = "max")
expect_s3_class(cld, "data.frame")
expect_equal(dim(cld), c(6, 5))
expect_named(cld, c("Method", "metricGroup", "ScaledValue", "Weight", "Metric"))
expect_equal(cld$metricGroup, cld$Metric)
expect_equal(cld$ScaledValue[cld$Method == "A" & cld$metricGroup == 1],
max(ldw$ScaledValue[ldw$Method == "A" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "B" & cld$metricGroup == 1],
max(ldw$ScaledValue[ldw$Method == "B" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "C" & cld$metricGroup == 1],
max(ldw$ScaledValue[ldw$Method == "C" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "A" & cld$metricGroup == 2],
max(ldw$ScaledValue[ldw$Method == "A" & ldw$metricGroup == 2]))
expect_equal(cld$ScaledValue[cld$Method == "B" & cld$metricGroup == 2],
max(ldw$ScaledValue[ldw$Method == "B" & ldw$metricGroup == 2]))
expect_equal(cld$ScaledValue[cld$Method == "C" & cld$metricGroup == 2],
max(ldw$ScaledValue[ldw$Method == "C" & ldw$metricGroup == 2]))
expect_equal(cld$Weight, c(0.7, 0.1, 0.7, 0.1, 0.7, 0.1))
## With grouping - min collapse
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "num", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
ldw <- .addWeightsToLongData(df = ld, metricCollapseGroup = TRUE,
metricGrouping = "num",
metricGroupCol = "metricGroup",
weights = list(m1_weight = 0.2, m2_weight = 0.3, m3_weight = 0.1,
Metric_m1_weight = 0.1, Metric_m2_weight = 0.5,
Metric_m3_weight = 0.7, num_1_weight = 0.7,
num_2_weight = 0.1, lets3_m_weight = 0.4,
lets3_n_weight = 0.1, lets3_o_weight = 0.9),
weightCol = "Weight", metricCol = "Metric",
metrics = c("m1", "m2", "m3"))
cld <- .collapseLongData(df = ldw, metricCollapseGroup = TRUE,
metricGrouping = "num", idCol = "Method",
metricGroupCol = "metricGroup",
valueCol = "ScaledValue", weightCol = "Weight",
metricCol = "Metric", collapseMethod = "min")
expect_s3_class(cld, "data.frame")
expect_equal(dim(cld), c(6, 5))
expect_named(cld, c("Method", "metricGroup", "ScaledValue", "Weight", "Metric"))
expect_equal(cld$metricGroup, cld$Metric)
expect_equal(cld$ScaledValue[cld$Method == "A" & cld$metricGroup == 1],
min(ldw$ScaledValue[ldw$Method == "A" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "B" & cld$metricGroup == 1],
min(ldw$ScaledValue[ldw$Method == "B" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "C" & cld$metricGroup == 1],
min(ldw$ScaledValue[ldw$Method == "C" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "A" & cld$metricGroup == 2],
min(ldw$ScaledValue[ldw$Method == "A" & ldw$metricGroup == 2]))
expect_equal(cld$ScaledValue[cld$Method == "B" & cld$metricGroup == 2],
min(ldw$ScaledValue[ldw$Method == "B" & ldw$metricGroup == 2]))
expect_equal(cld$ScaledValue[cld$Method == "C" & cld$metricGroup == 2],
min(ldw$ScaledValue[ldw$Method == "C" & ldw$metricGroup == 2]))
expect_equal(cld$Weight, c(0.7, 0.1, 0.7, 0.1, 0.7, 0.1))
## With grouping - min collapse (with NAs)
df0 <- df
df0$m1[1] <- df0$m2[1] <- NA
ld <- .makeLongData(df = df0, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "num", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
ldw <- .addWeightsToLongData(df = ld, metricCollapseGroup = TRUE,
metricGrouping = "num",
metricGroupCol = "metricGroup",
weights = list(m1_weight = 0.2, m2_weight = 0.3, m3_weight = 0.1,
Metric_m1_weight = 0.1, Metric_m2_weight = 0.5,
Metric_m3_weight = 0.7, num_1_weight = 0.7,
num_2_weight = 0.1, lets3_m_weight = 0.4,
lets3_n_weight = 0.1, lets3_o_weight = 0.9),
weightCol = "Weight", metricCol = "Metric",
metrics = c("m1", "m2", "m3"))
expect_warning(
cld <- .collapseLongData(df = ldw, metricCollapseGroup = TRUE,
metricGrouping = "num", idCol = "Method",
metricGroupCol = "metricGroup",
valueCol = "ScaledValue", weightCol = "Weight",
metricCol = "Metric", collapseMethod = "min"),
"no non-missing arguments to min")
expect_s3_class(cld, "data.frame")
expect_equal(dim(cld), c(6, 5))
expect_named(cld, c("Method", "metricGroup", "ScaledValue", "Weight", "Metric"))
expect_equal(cld$metricGroup, cld$Metric)
expect_equal(cld$ScaledValue[cld$Method == "A" & cld$metricGroup == 1], NA_real_)
expect_equal(cld$ScaledValue[cld$Method == "B" & cld$metricGroup == 1],
min(ldw$ScaledValue[ldw$Method == "B" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "C" & cld$metricGroup == 1],
min(ldw$ScaledValue[ldw$Method == "C" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "A" & cld$metricGroup == 2],
min(ldw$ScaledValue[ldw$Method == "A" & ldw$metricGroup == 2]))
expect_equal(cld$ScaledValue[cld$Method == "B" & cld$metricGroup == 2],
min(ldw$ScaledValue[ldw$Method == "B" & ldw$metricGroup == 2]))
expect_equal(cld$ScaledValue[cld$Method == "C" & cld$metricGroup == 2],
min(ldw$ScaledValue[ldw$Method == "C" & ldw$metricGroup == 2]))
expect_equal(cld$Weight, c(0.7, 0.1, 0.7, 0.1, 0.7, 0.1))
})
federicomarini/bettr documentation built on May 2, 2024, 3:05 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
test_that("long data generation works", {
df <- data.frame(Method = rep(c("A", "B", "C"), each = 3),
Metric = rep(c("m1", "m2", "m3"), 3),
Value = runif(n = 9, min = 0, max = 3)) |>
tidyr::pivot_wider(names_from = Metric, values_from = Value)
metrics <- setdiff(colnames(df), "Method")
metricInfo <- data.frame(Metric = c("m1", "m2", "m3"), num = c(1, 1, 2),
lets3 = c("m", "n", "o"))
idInfo <- data.frame(Method = c("A", "B", "C"), lets = c("a", "b", "b"),
lets2 = c("d", "d", "e"))
## Without grouping
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "---", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
expect_s3_class(ld, "data.frame")
expect_equal(dim(ld), c(9, 3))
expect_named(ld, c("Method", "Metric", "ScaledValue"))
expect_equal(ld$Method, rep(c("A", "B", "C"), each = 3))
expect_equal(ld$Metric, rep(c("m1", "m2", "m3"), 3))
expect_equal(ld$ScaledValue, unlist(c(df[1, -1], df[2, -1], df[3, -1])),
ignore_attr = TRUE)
## With grouping
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "num", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
expect_s3_class(ld, "data.frame")
expect_equal(dim(ld), c(9, 4))
expect_named(ld, c("Method", "Metric", "ScaledValue", "metricGroup"))
expect_equal(ld$Method, rep(c("A", "B", "C"), each = 3))
expect_equal(ld$Metric, rep(c("m1", "m2", "m3"), 3))
expect_equal(ld$metricGroup, rep(c(1, 1, 2), 3))
expect_equal(ld$ScaledValue, unlist(c(df[1, -1], df[2, -1], df[3, -1])),
ignore_attr = TRUE)
## With grouping, don't keep all metrics
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "num", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
expect_s3_class(ld, "data.frame")
expect_equal(dim(ld), c(6, 4))
expect_named(ld, c("Method", "Metric", "ScaledValue", "metricGroup"))
expect_equal(ld$Method, rep(c("A", "B", "C"), each = 2))
expect_equal(ld$Metric, rep(c("m1", "m3"), 3))
expect_equal(ld$metricGroup, rep(c(1, 2), 3))
expect_equal(ld$ScaledValue, unlist(c(df[1, -c(1, 3)], df[2, -c(1, 3)], df[3, -c(1, 3)])),
ignore_attr = TRUE)
})
test_that("adding weights to long data works", {
df <- data.frame(Method = rep(c("A", "B", "C"), each = 3),
Metric = rep(c("m1", "m2", "m3"), 3),
Value = runif(n = 9, min = 0, max = 3)) |>
tidyr::pivot_wider(names_from = Metric, values_from = Value)
metrics <- setdiff(colnames(df), "Method")
metricInfo <- data.frame(Metric = c("m1", "m2", "m3"), num = c(1, 1, 2),
lets3 = c("m", "n", "o"))
idInfo <- data.frame(Method = c("A", "B", "C"), lets = c("a", "b", "b"),
lets2 = c("d", "d", "e"))
## Without grouping
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "---", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
ldw <- .addWeightsToLongData(df = ld, metricCollapseGroup = FALSE,
metricGrouping = "---",
metricGroupCol = "metricGroup",
weights = list(m1_weight = 0.2, m2_weight = 0.3, m3_weight = 0.1,
Metric_m1_weight = 0.1, Metric_m2_weight = 0.5,
Metric_m3_weight = 0.7, num_1_weight = 0.7,
num_2_weight = 0.1, lets3_m_weight = 0.4,
lets3_n_weight = 0.1, lets3_o_weight = 0.9),
weightCol = "Weight", metricCol = "Metric",
metrics = c("m1", "m2", "m3"))
expect_s3_class(ldw, "data.frame")
expect_equal(dim(ldw), c(9, 4))
expect_named(ldw, c("Method", "Metric", "ScaledValue", "Weight"))
expect_equal(ldw$Method, ld$Method)
expect_equal(ldw$Metric, ld$Metric)
expect_equal(ldw$ScaledValue, ld$ScaledValue)
expect_equal(ldw$Weight, c(0.2, 0.3, 0.1, 0.2, 0.3, 0.1, 0.2, 0.3, 0.1))
## With grouping
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "num", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
ldw <- .addWeightsToLongData(df = ld, metricCollapseGroup = TRUE,
metricGrouping = "num",
metricGroupCol = "metricGroup",
weights = list(m1_weight = 0.2, m2_weight = 0.3, m3_weight = 0.1,
Metric_m1_weight = 0.1, Metric_m2_weight = 0.5,
Metric_m3_weight = 0.7, num_1_weight = 0.7,
num_2_weight = 0.1, lets3_m_weight = 0.4,
lets3_n_weight = 0.1, lets3_o_weight = 0.9),
weightCol = "Weight", metricCol = "Metric",
metrics = c("m1", "m2", "m3"))
expect_s3_class(ldw, "data.frame")
expect_equal(dim(ldw), c(9, 5))
expect_named(ldw, c("Method", "Metric", "ScaledValue", "metricGroup", "Weight"))
expect_equal(ldw$Method, ld$Method)
expect_equal(ldw$Metric, ld$Metric)
expect_equal(ldw$ScaledValue, ld$ScaledValue)
expect_equal(ldw$metricGroup, ld$metricGroup)
expect_equal(ldw$Weight, c(0.7, 0.7, 0.1, 0.7, 0.7, 0.1, 0.7, 0.7, 0.1))
## Missing weights -> return NULL
ldw <- .addWeightsToLongData(df = ld, metricCollapseGroup = TRUE,
metricGrouping = "num",
metricGroupCol = "metricGroup",
weights = list(m1_weight = 0.2, m2_weight = 0.3, m3_weight = 0.1,
Metric_m1_weight = 0.1, Metric_m2_weight = 0.5,
Metric_m3_weight = 0.7,
num_2_weight = 0.1, lets3_m_weight = 0.4,
lets3_n_weight = 0.1, lets3_o_weight = 0.9),
weightCol = "Weight", metricCol = "Metric",
metrics = c("m1", "m2", "m3"))
expect_null(ldw)
})
test_that("collapsing long data works", {
df <- data.frame(Method = rep(c("A", "B", "C"), each = 3),
Metric = rep(c("m1", "m2", "m3"), 3),
Value = runif(n = 9, min = 0, max = 3)) |>
tidyr::pivot_wider(names_from = Metric, values_from = Value)
metrics <- setdiff(colnames(df), "Method")
metricInfo <- data.frame(Metric = c("m1", "m2", "m3"), num = c(1, 1, 2),
lets3 = c("m", "n", "o"))
idInfo <- data.frame(Method = c("A", "B", "C"), lets = c("a", "b", "b"),
lets2 = c("d", "d", "e"))
## Without grouping
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "---", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
ldw <- .addWeightsToLongData(df = ld, metricCollapseGroup = FALSE,
metricGrouping = "---",
metricGroupCol = "metricGroup",
weights = list(m1_weight = 0.2, m2_weight = 0.3, m3_weight = 0.1,
Metric_m1_weight = 0.1, Metric_m2_weight = 0.5,
Metric_m3_weight = 0.7, num_1_weight = 0.7,
num_2_weight = 0.1, lets3_m_weight = 0.4,
lets3_n_weight = 0.1, lets3_o_weight = 0.9),
weightCol = "Weight", metricCol = "Metric",
metrics = c("m1", "m2", "m3"))
cld <- .collapseLongData(df = ldw, metricCollapseGroup = FALSE,
metricGrouping = "---", idCol = "Method",
metricGroupCol = "metricGroup",
valueCol = "ScaledValue", weightCol = "Weight",
metricCol = "Metric", collapseMethod = "mean")
expect_equal(ldw, cld)
## With grouping
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "num", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
ldw <- .addWeightsToLongData(df = ld, metricCollapseGroup = TRUE,
metricGrouping = "num",
metricGroupCol = "metricGroup",
weights = list(m1_weight = 0.2, m2_weight = 0.3, m3_weight = 0.1,
Metric_m1_weight = 0.1, Metric_m2_weight = 0.5,
Metric_m3_weight = 0.7, num_1_weight = 0.7,
num_2_weight = 0.1, lets3_m_weight = 0.4,
lets3_n_weight = 0.1, lets3_o_weight = 0.9),
weightCol = "Weight", metricCol = "Metric",
metrics = c("m1", "m2", "m3"))
cld <- .collapseLongData(df = ldw, metricCollapseGroup = TRUE,
metricGrouping = "num", idCol = "Method",
metricGroupCol = "metricGroup",
valueCol = "ScaledValue", weightCol = "Weight",
metricCol = "Metric", collapseMethod = "mean")
expect_s3_class(cld, "data.frame")
expect_equal(dim(cld), c(6, 5))
expect_named(cld, c("Method", "metricGroup", "ScaledValue", "Weight", "Metric"))
expect_equal(cld$metricGroup, cld$Metric)
expect_equal(cld$ScaledValue[cld$Method == "A" & cld$metricGroup == 1],
mean(ldw$ScaledValue[ldw$Method == "A" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "B" & cld$metricGroup == 1],
mean(ldw$ScaledValue[ldw$Method == "B" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "C" & cld$metricGroup == 1],
mean(ldw$ScaledValue[ldw$Method == "C" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "A" & cld$metricGroup == 2],
mean(ldw$ScaledValue[ldw$Method == "A" & ldw$metricGroup == 2]))
expect_equal(cld$ScaledValue[cld$Method == "B" & cld$metricGroup == 2],
mean(ldw$ScaledValue[ldw$Method == "B" & ldw$metricGroup == 2]))
expect_equal(cld$ScaledValue[cld$Method == "C" & cld$metricGroup == 2],
mean(ldw$ScaledValue[ldw$Method == "C" & ldw$metricGroup == 2]))
expect_equal(cld$Weight, c(0.7, 0.1, 0.7, 0.1, 0.7, 0.1))
## With grouping - max collapse
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "num", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
ldw <- .addWeightsToLongData(df = ld, metricCollapseGroup = TRUE,
metricGrouping = "num",
metricGroupCol = "metricGroup",
weights = list(m1_weight = 0.2, m2_weight = 0.3, m3_weight = 0.1,
Metric_m1_weight = 0.1, Metric_m2_weight = 0.5,
Metric_m3_weight = 0.7, num_1_weight = 0.7,
num_2_weight = 0.1, lets3_m_weight = 0.4,
lets3_n_weight = 0.1, lets3_o_weight = 0.9),
weightCol = "Weight", metricCol = "Metric",
metrics = c("m1", "m2", "m3"))
cld <- .collapseLongData(df = ldw, metricCollapseGroup = TRUE,
metricGrouping = "num", idCol = "Method",
metricGroupCol = "metricGroup",
valueCol = "ScaledValue", weightCol = "Weight",
metricCol = "Metric", collapseMethod = "max")
expect_s3_class(cld, "data.frame")
expect_equal(dim(cld), c(6, 5))
expect_named(cld, c("Method", "metricGroup", "ScaledValue", "Weight", "Metric"))
expect_equal(cld$metricGroup, cld$Metric)
expect_equal(cld$ScaledValue[cld$Method == "A" & cld$metricGroup == 1],
max(ldw$ScaledValue[ldw$Method == "A" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "B" & cld$metricGroup == 1],
max(ldw$ScaledValue[ldw$Method == "B" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "C" & cld$metricGroup == 1],
max(ldw$ScaledValue[ldw$Method == "C" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "A" & cld$metricGroup == 2],
max(ldw$ScaledValue[ldw$Method == "A" & ldw$metricGroup == 2]))
expect_equal(cld$ScaledValue[cld$Method == "B" & cld$metricGroup == 2],
max(ldw$ScaledValue[ldw$Method == "B" & ldw$metricGroup == 2]))
expect_equal(cld$ScaledValue[cld$Method == "C" & cld$metricGroup == 2],
max(ldw$ScaledValue[ldw$Method == "C" & ldw$metricGroup == 2]))
expect_equal(cld$Weight, c(0.7, 0.1, 0.7, 0.1, 0.7, 0.1))
## With grouping - min collapse
ld <- .makeLongData(df = df, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "num", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
ldw <- .addWeightsToLongData(df = ld, metricCollapseGroup = TRUE,
metricGrouping = "num",
metricGroupCol = "metricGroup",
weights = list(m1_weight = 0.2, m2_weight = 0.3, m3_weight = 0.1,
Metric_m1_weight = 0.1, Metric_m2_weight = 0.5,
Metric_m3_weight = 0.7, num_1_weight = 0.7,
num_2_weight = 0.1, lets3_m_weight = 0.4,
lets3_n_weight = 0.1, lets3_o_weight = 0.9),
weightCol = "Weight", metricCol = "Metric",
metrics = c("m1", "m2", "m3"))
cld <- .collapseLongData(df = ldw, metricCollapseGroup = TRUE,
metricGrouping = "num", idCol = "Method",
metricGroupCol = "metricGroup",
valueCol = "ScaledValue", weightCol = "Weight",
metricCol = "Metric", collapseMethod = "min")
expect_s3_class(cld, "data.frame")
expect_equal(dim(cld), c(6, 5))
expect_named(cld, c("Method", "metricGroup", "ScaledValue", "Weight", "Metric"))
expect_equal(cld$metricGroup, cld$Metric)
expect_equal(cld$ScaledValue[cld$Method == "A" & cld$metricGroup == 1],
min(ldw$ScaledValue[ldw$Method == "A" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "B" & cld$metricGroup == 1],
min(ldw$ScaledValue[ldw$Method == "B" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "C" & cld$metricGroup == 1],
min(ldw$ScaledValue[ldw$Method == "C" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "A" & cld$metricGroup == 2],
min(ldw$ScaledValue[ldw$Method == "A" & ldw$metricGroup == 2]))
expect_equal(cld$ScaledValue[cld$Method == "B" & cld$metricGroup == 2],
min(ldw$ScaledValue[ldw$Method == "B" & ldw$metricGroup == 2]))
expect_equal(cld$ScaledValue[cld$Method == "C" & cld$metricGroup == 2],
min(ldw$ScaledValue[ldw$Method == "C" & ldw$metricGroup == 2]))
expect_equal(cld$Weight, c(0.7, 0.1, 0.7, 0.1, 0.7, 0.1))
## With grouping - min collapse (with NAs)
df0 <- df
df0$m1[1] <- df0$m2[1] <- NA
ld <- .makeLongData(df = df0, idCol = "Method",
metrics = c("m1", "m2", "m3"),
metricCol = "Metric", valueCol = "ScaledValue",
metricGrouping = "num", metricInfo = metricInfo,
metricGroupCol = "metricGroup")
ldw <- .addWeightsToLongData(df = ld, metricCollapseGroup = TRUE,
metricGrouping = "num",
metricGroupCol = "metricGroup",
weights = list(m1_weight = 0.2, m2_weight = 0.3, m3_weight = 0.1,
Metric_m1_weight = 0.1, Metric_m2_weight = 0.5,
Metric_m3_weight = 0.7, num_1_weight = 0.7,
num_2_weight = 0.1, lets3_m_weight = 0.4,
lets3_n_weight = 0.1, lets3_o_weight = 0.9),
weightCol = "Weight", metricCol = "Metric",
metrics = c("m1", "m2", "m3"))
expect_warning(
cld <- .collapseLongData(df = ldw, metricCollapseGroup = TRUE,
metricGrouping = "num", idCol = "Method",
metricGroupCol = "metricGroup",
valueCol = "ScaledValue", weightCol = "Weight",
metricCol = "Metric", collapseMethod = "min"),
"no non-missing arguments to min")
expect_s3_class(cld, "data.frame")
expect_equal(dim(cld), c(6, 5))
expect_named(cld, c("Method", "metricGroup", "ScaledValue", "Weight", "Metric"))
expect_equal(cld$metricGroup, cld$Metric)
expect_equal(cld$ScaledValue[cld$Method == "A" & cld$metricGroup == 1], NA_real_)
expect_equal(cld$ScaledValue[cld$Method == "B" & cld$metricGroup == 1],
min(ldw$ScaledValue[ldw$Method == "B" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "C" & cld$metricGroup == 1],
min(ldw$ScaledValue[ldw$Method == "C" & ldw$metricGroup == 1]))
expect_equal(cld$ScaledValue[cld$Method == "A" & cld$metricGroup == 2],
min(ldw$ScaledValue[ldw$Method == "A" & ldw$metricGroup == 2]))
expect_equal(cld$ScaledValue[cld$Method == "B" & cld$metricGroup == 2],
min(ldw$ScaledValue[ldw$Method == "B" & ldw$metricGroup == 2]))
expect_equal(cld$ScaledValue[cld$Method == "C" & cld$metricGroup == 2],
min(ldw$ScaledValue[ldw$Method == "C" & ldw$metricGroup == 2]))
expect_equal(cld$Weight, c(0.7, 0.1, 0.7, 0.1, 0.7, 0.1))
})
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.