a375ad2822
* [R] make sure things work for a single split model; fixes #2191 * [R] add option use_int_id to xgb.model.dt.tree * [R] add example of exporting tree plot to a file * [R] set save_period = NULL as default in xgboost() to be the same as in xgb.train; fixes #2182 * [R] it's a good practice after CRAN releases to bump up package version in dev * [R] allow xgb.DMatrix construction from integer dense matrices * [R] xgb.DMatrix: silent parameter; improve documentation * [R] xgb.model.dt.tree code style changes * [R] update NEWS with parameter changes * [R] code safety & style; handle non-strict matrix and inherited classes of input and model; fixes #2242 * [R] change to x.y.z.p R-package versioning scheme and set version to 0.6.4.3 * [R] add an R package versioning section to the contributors guide * [R] R-package/README.md: clean up the redundant old installation instructions, link the contributors guide
100 lines
3.2 KiB
R
100 lines
3.2 KiB
R
require(xgboost)
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require(Matrix)
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context("testing xgb.DMatrix functionality")
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data(agaricus.test, package='xgboost')
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test_data <- agaricus.test$data[1:100,]
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test_label <- agaricus.test$label[1:100]
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test_that("xgb.DMatrix: basic construction", {
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# from sparse matrix
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dtest1 <- xgb.DMatrix(test_data, label=test_label)
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# from dense matrix
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dtest2 <- xgb.DMatrix(as.matrix(test_data), label=test_label)
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expect_equal(getinfo(dtest1, 'label'), getinfo(dtest2, 'label'))
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expect_equal(dim(dtest1), dim(dtest2))
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#from dense integer matrix
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int_data <- as.matrix(test_data)
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storage.mode(int_data) <- "integer"
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dtest3 <- xgb.DMatrix(int_data, label=test_label)
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expect_equal(dim(dtest1), dim(dtest3))
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})
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test_that("xgb.DMatrix: saving, loading", {
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# save to a local file
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dtest1 <- xgb.DMatrix(test_data, label=test_label)
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tmp_file <- tempfile('xgb.DMatrix_')
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expect_true(xgb.DMatrix.save(dtest1, tmp_file))
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# read from a local file
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expect_output(dtest3 <- xgb.DMatrix(tmp_file), "entries loaded from")
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expect_output(dtest3 <- xgb.DMatrix(tmp_file, silent = TRUE), NA)
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unlink(tmp_file)
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expect_equal(getinfo(dtest1, 'label'), getinfo(dtest3, 'label'))
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# from a libsvm text file
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tmp <- c("0 1:1 2:1","1 3:1","0 1:1")
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tmp_file <- 'tmp.libsvm'
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writeLines(tmp, tmp_file)
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dtest4 <- xgb.DMatrix(tmp_file, silent = TRUE)
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expect_equal(dim(dtest4), c(3, 4))
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expect_equal(getinfo(dtest4, 'label'), c(0,1,0))
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unlink(tmp_file)
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})
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test_that("xgb.DMatrix: getinfo & setinfo", {
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dtest <- xgb.DMatrix(test_data)
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expect_true(setinfo(dtest, 'label', test_label))
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labels <- getinfo(dtest, 'label')
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expect_equal(test_label, getinfo(dtest, 'label'))
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expect_true(length(getinfo(dtest, 'weight')) == 0)
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expect_true(length(getinfo(dtest, 'base_margin')) == 0)
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expect_true(setinfo(dtest, 'weight', test_label))
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expect_true(setinfo(dtest, 'base_margin', test_label))
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expect_true(setinfo(dtest, 'group', c(50,50)))
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expect_error(setinfo(dtest, 'group', test_label))
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# providing character values will give a warning
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expect_warning( setinfo(dtest, 'weight', rep('a', nrow(test_data))) )
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# any other label should error
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expect_error(setinfo(dtest, 'asdf', test_label))
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})
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test_that("xgb.DMatrix: slice, dim", {
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dtest <- xgb.DMatrix(test_data, label=test_label)
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expect_equal(dim(dtest), dim(test_data))
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dsub1 <- slice(dtest, 1:42)
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expect_equal(nrow(dsub1), 42)
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expect_equal(ncol(dsub1), ncol(test_data))
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dsub2 <- dtest[1:42,]
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expect_equal(dim(dtest), dim(test_data))
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expect_equal(getinfo(dsub1, 'label'), getinfo(dsub2, 'label'))
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})
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test_that("xgb.DMatrix: colnames", {
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dtest <- xgb.DMatrix(test_data, label=test_label)
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expect_equal(colnames(dtest), colnames(test_data))
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expect_error( colnames(dtest) <- 'asdf')
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new_names <- make.names(1:ncol(test_data))
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expect_silent( colnames(dtest) <- new_names)
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expect_equal(colnames(dtest), new_names)
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expect_silent(colnames(dtest) <- NULL)
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expect_null(colnames(dtest))
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})
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test_that("xgb.DMatrix: nrow is correct for a very sparse matrix", {
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set.seed(123)
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nr <- 1000
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x <- rsparsematrix(nr, 100, density=0.0005)
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# we want it very sparse, so that last rows are empty
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expect_lt(max(x@i), nr)
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dtest <- xgb.DMatrix(x)
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expect_equal(dim(dtest), dim(x))
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})
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