Nothing

```
context("stm tidiers")
suppressPackageStartupMessages(library(dplyr))
if (require("stm", quietly = TRUE)) {
dat <- data_frame(
document = c("row1", "row1", "row2", "row2", "row2"),
term = c("col1", "col2", "col1", "col3", "col4"),
n = 1:5
)
m <- cast_sparse(dat, document, term)
stm_model <- stm(m, seed = 1234, K = 3, verbose = FALSE)
test_that("can tidy beta matrix", {
td <- tidy(stm_model, matrix = "beta")
expect_is(td, "tbl_df")
expect_equal(colnames(td), c("topic", "term", "beta"))
expect_is(td$term, "character")
expect_is(td$beta, "numeric")
expect_equal(unique(td$topic), 1:3)
expect_gt(nrow(td), 10)
expect_true(all(c("col1", "col2", "col3") %in% td$term))
# all betas sum to 1
summ <- td %>%
count(topic, wt = beta)
expect_lt(max(abs(summ$n - 1)), .000001)
td_log <- tidy(stm_model, matrix = "beta", log = TRUE)
expect_true(all(td_log$beta <= 0))
})
test_that("can tidy gamma matrix", {
td <- tidy(stm_model, matrix = "gamma")
expect_is(td, "tbl_df")
expect_equal(colnames(td), c("document", "topic", "gamma"))
expect_is(td$document, "integer")
expect_is(td$gamma, "numeric")
expect_equal(nrow(td), 6)
expect_equal(unique(td$topic), 1:3)
expect_equal(unique(td$document), 1:2)
# all gammas sum to 1
summ <- td %>%
count(document, wt = gamma)
expect_lt(max(abs(summ$n - 1)), 1e-6)
td_log <- tidy(stm_model, matrix = "gamma", log = TRUE)
expect_true(all(td_log$gamma <= 0))
})
test_that("can augment an stm output", {
skip_if_not_installed("quanteda")
au <- augment(stm_model, dat)
expect_is(au, "tbl_df")
expect_equal(colnames(au), c(colnames(dat), ".topic"))
expect_equal(sort(unique(au$.topic)), 1:3)
# augment output should have same document-term combinations
s <- arrange(au, document, term)
s2 <- dat %>%
arrange(document, term)
expect_equal(s$term, s2$term)
expect_equal(s$document, s2$document)
# can include extra columns
inaug_tidied2 <- dat %>%
mutate(starts_c = stringr::str_detect(term, "^c"))
au2 <- augment(stm_model, data = inaug_tidied2)
expect_equal(au$document, au2$document)
expect_equal(au$term, au2$term)
expect_is(au2$starts_c, "logical")
expect_equal(stringr::str_detect(au2$term, "^c"), au2$starts_c)
})
test_that("can glance an stm output", {
g <- glance(stm_model)
expect_is(g, "tbl_df")
expect_equal(nrow(g), 1)
expect_equal(g$terms, 4)
})
stm_estimate_one_topic <- estimateEffect(c(1) ~ treatment, gadarianFit, gadarian)
test_that("can tidy estimateEffect object with one topic", {
td <- tidy(stm_estimate_one_topic)
expect_is(td, "tbl_df")
expect_equal(colnames(td), c("topic", "term", "estimate", "std.error", "statistic", "p.value"))
expect_is(td$topic, "integer")
expect_is(td$term, "character")
expect_is(td$estimate, "numeric")
expect_is(td$std.error, "numeric")
expect_is(td$statistic, "numeric")
expect_is(td$p.value, "numeric")
expect_equal(unique(td$topic), 1)
expect_equal(nrow(td), 2)
expect_true(all(c("(Intercept)", "treatment") %in% td$term))
})
stm_estimate_three_topic_interaction <- estimateEffect(c(1:3) ~ treatment*s(pid_rep), gadarianFit, gadarian)
test_that("can tidy estimateEffect object with three topics and an interaction term", {
td <- tidy(stm_estimate_three_topic_interaction)
expect_is(td, "tbl_df")
expect_equal(colnames(td), c("topic", "term", "estimate", "std.error", "statistic", "p.value"))
expect_is(td$topic, "integer")
expect_is(td$term, "character")
expect_is(td$estimate, "numeric")
expect_is(td$std.error, "numeric")
expect_is(td$statistic, "numeric")
expect_is(td$p.value, "numeric")
expect_equal(unique(td$topic), c(1:3))
expect_equal(nrow(td), 42) # 14 term combinations for 3 topics
expect_true(all(c("(Intercept)", "treatment", "s(pid_rep)1", "s(pid_rep)2", "s(pid_rep)3", "s(pid_rep)4",
"s(pid_rep)5", "s(pid_rep)6", "treatment:s(pid_rep)1", "treatment:s(pid_rep)2",
"treatment:s(pid_rep)3", "treatment:s(pid_rep)4", "treatment:s(pid_rep)5", "treatment:s(pid_rep)6")
%in% td$term))
})
}
```

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