skip_connection("ml-feature-normalizer")
skip_on_livy()
skip_on_arrow_devel()
skip_databricks_connect()
test_that("ft_normalizer() default params", {
test_requires_version("3.0.0")
sc <- testthat_spark_connection()
test_default_args(sc, ft_normalizer)
})
test_that("ft_normalizer() param setting", {
test_requires_version("3.0.0")
sc <- testthat_spark_connection()
test_args <- list(
input_col = "foo",
output_col = "bar",
p = 2
)
test_param_setting(sc, ft_normalizer, test_args)
})
test_that("ft_normalizer works properly", {
sc <- testthat_spark_connection()
df <- tribble(
~id, ~V1, ~V2, ~V3,
0, 1, 0.5, -1,
1, 2, 1, 1,
2, 4, 10, 2
)
df_tbl <- sdf_copy_to(sc, df, overwrite = TRUE) %>%
ft_vector_assembler(paste0("V", 1:3), "features")
expect_warning_on_arrow(
norm_data1 <- df_tbl %>%
ft_normalizer("features", "normFeatures", p = 1) %>%
pull(normFeatures)
)
expect_equal(
norm_data1,
list(
c(0.4, 0.2, -0.4),
c(0.5, 0.25, 0.25),
c(0.25, 0.625, 0.125)
)
)
expect_warning_on_arrow(
norm_data2 <- df_tbl %>%
ft_normalizer("features", "normFeatures", p = Inf) %>%
pull(normFeatures)
)
expect_equal(
norm_data2,
list(
c(1, 0.5, -1),
c(1, 0.5, 0.5),
c(0.4, 1, 0.2)
)
)
})
test_that("ft_normalizer errors for bad p", {
sc <- testthat_spark_connection()
expect_error(
ft_normalizer(sc, "features", "normFeatures", p = 0.5),
"`p` must be at least 1\\."
)
})
test_clear_cache()
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