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Add Github Action for R. (#5911)

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* Fix lintr errors.
This commit is contained in:
Jiaming Yuan
2020-07-20 19:23:36 +08:00
committed by GitHub
parent b3d2e7644a
commit 8b1afce316
33 changed files with 589 additions and 544 deletions
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36
R-package/tests/testthat/test_dmatrix.R
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@@ -3,29 +3,29 @@ require(Matrix)
context("testing xgb.DMatrix functionality")
data(agaricus.test, package='xgboost')
test_data <- agaricus.test$data[1:100,]
data(agaricus.test, package = 'xgboost')
test_data <- agaricus.test$data[1:100, ]
test_label <- agaricus.test$label[1:100]
test_that("xgb.DMatrix: basic construction", {
# from sparse matrix
dtest1 <- xgb.DMatrix(test_data, label=test_label)
dtest1 <- xgb.DMatrix(test_data, label = test_label)
# from dense matrix
dtest2 <- xgb.DMatrix(as.matrix(test_data), label=test_label)
dtest2 <- xgb.DMatrix(as.matrix(test_data), label = test_label)
expect_equal(getinfo(dtest1, 'label'), getinfo(dtest2, 'label'))
expect_equal(dim(dtest1), dim(dtest2))
#from dense integer matrix
int_data <- as.matrix(test_data)
storage.mode(int_data) <- "integer"
dtest3 <- xgb.DMatrix(int_data, label=test_label)
dtest3 <- xgb.DMatrix(int_data, label = test_label)
expect_equal(dim(dtest1), dim(dtest3))
})
test_that("xgb.DMatrix: saving, loading", {
# save to a local file
dtest1 <- xgb.DMatrix(test_data, label=test_label)
dtest1 <- xgb.DMatrix(test_data, label = test_label)
tmp_file <- tempfile('xgb.DMatrix_')
expect_true(xgb.DMatrix.save(dtest1, tmp_file))
# read from a local file
@@ -35,12 +35,12 @@ test_that("xgb.DMatrix: saving, loading", {
expect_equal(getinfo(dtest1, 'label'), getinfo(dtest3, 'label'))
# from a libsvm text file
tmp <- c("0 1:1 2:1","1 3:1","0 1:1")
tmp <- c("0 1:1 2:1", "1 3:1", "0 1:1")
tmp_file <- 'tmp.libsvm'
writeLines(tmp, tmp_file)
dtest4 <- xgb.DMatrix(tmp_file, silent = TRUE)
expect_equal(dim(dtest4), c(3, 4))
expect_equal(getinfo(dtest4, 'label'), c(0,1,0))
expect_equal(getinfo(dtest4, 'label'), c(0, 1, 0))
unlink(tmp_file)
})
@@ -61,7 +61,7 @@ test_that("xgb.DMatrix: getinfo & setinfo", {
expect_true(setinfo(dtest, 'weight', test_label))
expect_true(setinfo(dtest, 'base_margin', test_label))
expect_true(setinfo(dtest, 'group', c(50,50)))
expect_true(setinfo(dtest, 'group', c(50, 50)))
expect_error(setinfo(dtest, 'group', test_label))
# providing character values will give a warning
@@ -72,35 +72,35 @@ test_that("xgb.DMatrix: getinfo & setinfo", {
})
test_that("xgb.DMatrix: slice, dim", {
dtest <- xgb.DMatrix(test_data, label=test_label)
dtest <- xgb.DMatrix(test_data, label = test_label)
expect_equal(dim(dtest), dim(test_data))
dsub1 <- slice(dtest, 1:42)
expect_equal(nrow(dsub1), 42)
expect_equal(ncol(dsub1), ncol(test_data))
dsub2 <- dtest[1:42,]
dsub2 <- dtest[1:42, ]
expect_equal(dim(dtest), dim(test_data))
expect_equal(getinfo(dsub1, 'label'), getinfo(dsub2, 'label'))
})
test_that("xgb.DMatrix: slice, trailing empty rows", {
data(agaricus.train, package='xgboost')
data(agaricus.train, package = 'xgboost')
train_data <- agaricus.train$data
train_label <- agaricus.train$label
dtrain <- xgb.DMatrix(data=train_data, label=train_label)
dtrain <- xgb.DMatrix(data = train_data, label = train_label)
slice(dtrain, 6513L)
train_data[6513, ] <- 0
dtrain <- xgb.DMatrix(data=train_data, label=train_label)
dtrain <- xgb.DMatrix(data = train_data, label = train_label)
slice(dtrain, 6513L)
expect_equal(nrow(dtrain), 6513)
})
test_that("xgb.DMatrix: colnames", {
dtest <- xgb.DMatrix(test_data, label=test_label)
dtest <- xgb.DMatrix(test_data, label = test_label)
expect_equal(colnames(dtest), colnames(test_data))
expect_error( colnames(dtest) <- 'asdf')
expect_error(colnames(dtest) <- 'asdf')
new_names <- make.names(1:ncol(test_data))
expect_silent( colnames(dtest) <- new_names)
expect_silent(colnames(dtest) <- new_names)
expect_equal(colnames(dtest), new_names)
expect_silent(colnames(dtest) <- NULL)
expect_null(colnames(dtest))
@@ -109,7 +109,7 @@ test_that("xgb.DMatrix: colnames", {
test_that("xgb.DMatrix: nrow is correct for a very sparse matrix", {
set.seed(123)
nr <- 1000
x <- rsparsematrix(nr, 100, density=0.0005)
x <- rsparsematrix(nr, 100, density = 0.0005)
# we want it very sparse, so that last rows are empty
expect_lt(max(x@i), nr)
dtest <- xgb.DMatrix(x)