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Corrects mapping of parent join_keys columns when merging 2 data frames #503

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merged 4 commits into from
Dec 22, 2023
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Corrects mapping of parent join_keys columns when merging 2 data frames #503

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5d26b23
fix: corrects mapping of parent join_keys columns
averissimo Dec 22, 2023
9121212
tests: test mismatch join keys columns
averissimo Dec 22, 2023
223a6c1
tests: removes explicit parents assignment
averissimo Dec 22, 2023
a89a530
bumps version
averissimo Dec 22, 2023
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2 changes: 1 addition & 1 deletion DESCRIPTION
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Original file line number Diff line number Diff line change
Expand Up @@ -45,7 +45,7 @@ Imports:
shinycssloaders (>= 1.0.0),
shinyjs,
shinyWidgets (>= 0.6.2),
teal.data (>= 0.3.0.9018),
teal.data (>= 0.3.0.9029),
teal.logger (>= 0.1.1),
teal.widgets (>= 0.4.0),
utils
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7 changes: 3 additions & 4 deletions R/FilteredDatasetDataframe.R
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Expand Up @@ -122,8 +122,8 @@ DataframeFilteredDataset <- R6::R6Class( # nolint

if (!identical(parent_dataname, character(0))) {
join_keys <- private$join_keys
parent_keys <- names(join_keys)
dataset_keys <- unname(join_keys)
parent_keys <- unname(join_keys)
dataset_keys <- names(join_keys)

y_arg <- if (length(parent_keys) == 0L) {
parent_dataname
Expand Down Expand Up @@ -240,11 +240,10 @@ DataframeFilteredDataset <- R6::R6Class( # nolint
# Gets filter overview subjects number and returns a list
# of the number of subjects of filtered/non-filtered datasets
subject_keys <- if (length(private$parent_name) > 0) {
private$join_keys
names(private$join_keys)
} else {
self$get_keys()
}

dataset <- self$get_dataset()
data_filtered <- self$get_dataset(TRUE)
if (length(subject_keys) == 0) {
Expand Down
37 changes: 29 additions & 8 deletions tests/testthat/test-FilteredData.R
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Expand Up @@ -35,7 +35,6 @@ testthat::test_that("filtered_data$datanames returns character vector of dataset

testthat::test_that("datanames are ordered topologically from parent to child", {
jk <- teal.data::join_keys(teal.data::join_key("parent", "child", c("id" = "id")))
teal.data::parents(jk) <- list(child = "parent")
iris2 <- transform(iris, id = seq_len(nrow(iris)))
filtered_data <- FilteredData$new(
list(
Expand Down Expand Up @@ -94,7 +93,6 @@ testthat::test_that("set_datasets creates FilteredDataset object linked with par
)
)
jk <- teal.data::join_keys(teal.data::join_key("parent", "child", c("id" = "id")))
teal.data::parents(jk) <- list(child = "parent")
iris2 <- transform(iris, id = seq_len(nrow(iris)))
filtered_data <- test_class$new(data_objects = list(), join_keys = jk)
filtered_data$set_dataset(data = head(iris), dataname = "parent")
Expand Down Expand Up @@ -269,10 +267,9 @@ testthat::test_that("get_data returns an object filtered by set filters", {

testthat::test_that("get_data of the child is dependent on the ancestor filter", {
jk <- teal.data::join_keys(
teal.data::join_key("child", "parent", c("id" = "id")),
teal.data::join_key("grandchild", "child", c("id" = "id"))
teal.data::join_key("parent", "child", c("id" = "id")),
teal.data::join_key("child", "grandchild", c("id" = "id"))
)
teal.data::parents(jk) <- list(child = "parent", grandchild = "child")
iris2 <- transform(iris, id = seq_len(nrow(iris)))
filtered_data <- FilteredData$new(
list(
Expand All @@ -292,6 +289,31 @@ testthat::test_that("get_data of the child is dependent on the ancestor filter",
)
})

testthat::test_that("get_data of the child is dependent on the ancestor filter (mismatched columns)", {
jk <- teal.data::join_keys(
teal.data::join_key("parent", "child", c("pk" = "id")),
teal.data::join_key("child", "grandchild", c("id" = "id"))
)
iris2 <- transform(iris, id = seq_len(nrow(iris)))
iris_parent <- dplyr::rename(iris2, pk = "id")
filtered_data <- FilteredData$new(
list(
grandchild = list(dataset = head(iris2)),
child = list(dataset = head(iris2)),
parent = list(dataset = head(iris_parent))
),
join_keys = jk
)
filtered_data$set_filter_state(teal_slices(
teal_slice(dataname = "parent", varname = "pk", selected = c(1, 1), keep_na = FALSE, keep_inf = FALSE)
))

testthat::expect_identical(
shiny::isolate(filtered_data$get_data("grandchild", filtered = TRUE)),
dplyr::filter(iris2, id == 1)
)
})

# get_filter_state ----
testthat::test_that("get_filter_state returns `teal_slices` with features identical to those in input", {
datasets <- FilteredData$new(
Expand Down Expand Up @@ -603,10 +625,9 @@ testthat::test_that("get_filter_overview returns overview data.frame with filter

testthat::test_that("get_filter_overview return counts based on reactive filtering by ancestors", {
jk <- teal.data::join_keys(
teal.data::join_key("child", "parent", c("id" = "id")),
teal.data::join_key("grandchild", "child", c("id" = "id"))
teal.data::join_key("parent", "child", c("id" = "id")),
teal.data::join_key("child", "grandchild", c("id" = "id"))
)
teal.data::parents(jk) <- list(child = "parent", grandchild = "child")
iris2 <- transform(iris, id = seq_len(nrow(iris)))
filtered_data <- FilteredData$new(
list(
Expand Down