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[R-package] Keep row names in output from predict #4977

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merged 15 commits into from
Apr 5, 2022
Merged

[R-package] Keep row names in output from predict #4977

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d4e5a02
keep row names in prediction output
david-cortes Jan 23, 2022
c962a92
fix test
david-cortes Jan 27, 2022
8a4d71f
fix test
david-cortes Jan 27, 2022
d2470c2
fix test
david-cortes Jan 27, 2022
6e574f2
more tests for row names
david-cortes Mar 23, 2022
2f25779
solve merge conflict
david-cortes Mar 23, 2022
6ee372e
redo badly solved merge conflict
david-cortes Mar 23, 2022
716ce60
comments
david-cortes Mar 27, 2022
dd327e7
update docs
david-cortes Mar 27, 2022
521c65b
solve merge conflict
david-cortes Apr 3, 2022
2782379
missing closing parentheses
david-cortes Apr 3, 2022
42e660f
Merge branch 'master' into Rinterface8
jameslamb Apr 4, 2022
04b743f
explicitly list assertions in each test
jameslamb Apr 4, 2022
896629b
Merge branch 'master' into Rinterface8
jameslamb Apr 4, 2022
ec1c802
move assertions back into shared function
jameslamb Apr 4, 2022
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34 changes: 22 additions & 12 deletions R-package/R/lgb.Booster.R
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Original file line number Diff line number Diff line change
Expand Up @@ -731,6 +731,9 @@ Booster <- R6::R6Class(
#' @param header only used for prediction for text file. True if text file has header
#' @param reshape whether to reshape the vector of predictions to a matrix form when there are several
#' prediction outputs per case.
#'
#' If passing `reshape=TRUE` and `data` has row names, the output will also have those
#' row names.
#' @param params a list of additional named parameters. See
#' \href{https://lightgbm.readthedocs.io/en/latest/Parameters.html#predict-parameters}{
#' the "Predict Parameters" section of the documentation} for a list of parameters and
Expand Down Expand Up @@ -803,19 +806,26 @@ predict.lgb.Booster <- function(object,
))
}

return(
object$predict(
data = newdata
, start_iteration = start_iteration
, num_iteration = num_iteration
, rawscore = rawscore
, predleaf = predleaf
, predcontrib = predcontrib
, header = header
, reshape = reshape
, params = params
)
pred <- object$predict(
data = newdata
, start_iteration = start_iteration
, num_iteration = num_iteration
, rawscore = rawscore
, predleaf = predleaf
, predcontrib = predcontrib
, header = header
, reshape = reshape
, params = params
)

if (reshape && NROW(row.names(newdata))) {
if (is.null(dim(pred))) {
names(pred) <- row.names(newdata)
} else {
row.names(pred) <- row.names(newdata)
}
}
return(pred)
}

#' @name print.lgb.Booster
Expand Down
5 changes: 4 additions & 1 deletion R-package/man/predict.lgb.Booster.Rd
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116 changes: 116 additions & 0 deletions R-package/tests/testthat/test_Predictor.R
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Expand Up @@ -2,6 +2,8 @@ VERBOSITY <- as.integer(
Sys.getenv("LIGHTGBM_TEST_VERBOSITY", "-1")
)

library(Matrix)

test_that("Predictor$finalize() should not fail", {
X <- as.matrix(as.integer(iris[, "Species"]), ncol = 1L)
y <- iris[["Sepal.Length"]]
Expand Down Expand Up @@ -111,3 +113,117 @@ test_that("start_iteration works correctly", {
pred_leaf2 <- predict(bst, test$data, start_iteration = 0L, num_iteration = end_iter + 1L, predleaf = TRUE)
expect_equal(pred_leaf1, pred_leaf2)
})

test_that("predictions keep row names from the data", {
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these tests look great, thank you! To speed up debugging if they break due to changes in future PRs, can you please break them into 3 test cases?

  • "predict() keeps row names from data (binary classification)"
  • "predict() keeps row names from data (multi-class classification)"
  • "predict() keeps row names from data (regression)"

To avoid duplicating test helper code and to make it clear that those methods were written just for these tests, please move them out of the test case and rename them to .expect_has_row_names() and .expect_doesnt_have_row_names().

data("mtcars")
X <- as.matrix(mtcars[, -1L])
y <- as.numeric(mtcars[, 1L])
dtrain <- lgb.Dataset(X, label = y, params = list(max_bins = 5L))
bst <- lgb.train(
data = dtrain
, obj = "regression"
, nrounds = 5L
, verbose = -1L
)

expect_has_row_names <- function(pred) {
if (is.vector(pred)) {
rnames <- names(pred)
} else {
rnames <- row.names(pred)
}
expect_false(is.null(rnames))
expect_true(is.vector(rnames))
expect_equal(row.names(X), rnames)
}

expect_doesnt_have_row_names <- function(pred) {
expect_null(row.names(pred))
}

pred <- predict(bst, X, reshape = TRUE)
expect_has_row_names(pred)
pred <- predict(bst, X, reshape = TRUE, rawscore = TRUE)
expect_has_row_names(pred)
pred <- predict(bst, X, reshape = TRUE, predleaf = TRUE)
expect_has_row_names(pred)
pred <- predict(bst, X, reshape = TRUE, predcontrib = TRUE)
expect_has_row_names(pred)
pred <- predict(bst, X, reshape = FALSE)
expect_doesnt_have_row_names(pred)
Xcopy <- X
row.names(Xcopy) <- NULL
pred <- predict(bst, Xcopy, reshape = TRUE)
expect_doesnt_have_row_names(pred)

Xcsc <- as(X, "CsparseMatrix")
pred <- predict(bst, Xcsc, reshape = TRUE)
expect_has_row_names(pred)
pred <- predict(bst, Xcsc, reshape = TRUE, rawscore = TRUE)
expect_has_row_names(pred)
pred <- predict(bst, Xcsc, reshape = TRUE, predleaf = TRUE)
expect_has_row_names(pred)
pred <- predict(bst, Xcsc, reshape = TRUE, predcontrib = TRUE)
expect_has_row_names(pred)
pred <- predict(bst, Xcsc, reshape = FALSE)
expect_doesnt_have_row_names(pred)
Xcopy <- Xcsc
row.names(Xcopy) <- NULL
pred <- predict(bst, Xcopy, reshape = TRUE)
expect_doesnt_have_row_names(pred)

data(iris)
y <- as.numeric(iris$Species) - 1.0
X <- as.matrix(iris[, names(iris) != "Species"])
row.names(X) <- paste("rname", seq(1L, nrow(X)), sep = "")
dtrain <- lgb.Dataset(X, label = y, params = list(max_bins = 5L))
bst <- lgb.train(
data = dtrain
, obj = "multiclass"
, params = list(num_class = 3L)
, nrounds = 5L
, verbose = -1L
)

pred <- predict(bst, X, reshape = TRUE)
expect_has_row_names(pred)
pred <- predict(bst, X, reshape = TRUE, rawscore = TRUE)
expect_has_row_names(pred)
pred <- predict(bst, X, reshape = TRUE, predleaf = TRUE)
expect_has_row_names(pred)
pred <- predict(bst, X, reshape = TRUE, predcontrib = TRUE)
expect_has_row_names(pred)
pred <- predict(bst, X, reshape = FALSE)
expect_doesnt_have_row_names(pred)
Xcopy <- X
row.names(Xcopy) <- NULL
pred <- predict(bst, Xcopy, reshape = TRUE)
expect_doesnt_have_row_names(pred)

data(agaricus.train, package = "lightgbm")
X <- agaricus.train$data
y <- agaricus.train$label
row.names(X) <- paste("rname", seq(1L, nrow(X)), sep = "")
dtrain <- lgb.Dataset(X, label = y, params = list(max_bins = 5L))
bst <- lgb.train(
data = dtrain
, obj = "binary"
, nrounds = 5L
, verbose = -1L
)

pred <- predict(bst, X, reshape = TRUE)
expect_has_row_names(pred)
pred <- predict(bst, X, reshape = TRUE, rawscore = TRUE)
expect_has_row_names(pred)
pred <- predict(bst, X, reshape = TRUE, predleaf = TRUE)
expect_has_row_names(pred)
pred <- predict(bst, X, reshape = TRUE, predcontrib = TRUE)
expect_has_row_names(pred)
pred <- predict(bst, X, reshape = FALSE)
expect_doesnt_have_row_names(pred)
Xcopy <- X
row.names(Xcopy) <- NULL
pred <- predict(bst, Xcopy, reshape = TRUE)
expect_doesnt_have_row_names(pred)
})