Nothing
test_that("jst execution correct, unsupervised, with docvars", {
# The type of tokens doesn't matter for the model, so
# no cleaning here whatsoever. Reduce to 10 documents
# for reduced runtime.
data <- quanteda::dfm(quanteda::data_corpus_inaugural)
data <- quanteda::dfm_sample(data, 10)
model_jst <- jst(data)
expect_true(is.JST.result(model_jst))
top20 <- top20words(model_jst)
theta <- get_parameter(model_jst, "theta")
pi <- get_parameter(model_jst, "pi")
phi <- get_parameter(model_jst, "phi")
expect_is(theta, "data.frame")
expect_equal(nrow(theta), quanteda::ndoc(data))
expect_equal(ncol(theta), 1 + ncol(quanteda::docvars(data)) + 10 * 3)
# docid + docvars + 10 topic * 3 senti
expect_is(pi, "data.frame")
expect_equal(ncol(pi), ncol(quanteda::docvars(data)) + 3) # docvars + 3 senti
expect_equal(rownames(pi), quanteda::docnames(data)) #implies length
expect_is(phi, "data.frame")
expect_equal(nrow(phi), quanteda::nfeat(data) * 10 * 3) #num features * 10 topic * 3 senti
expect_equal(ncol(phi), 4)
})
test_that("jst execution correct, unsupervised, without docvars", {
# The type of tokens doesn't matter for the model, so
# no cleaning here whatsoever. Reduce to 10 documents
# for reduced runtime.
data <- quanteda::dfm(quanteda::data_corpus_inaugural)
quanteda::docvars(data) <- NULL # Remove docvars
data <- quanteda::dfm_sample(data, 10)
model_jst <- jst(data)
expect_true(is.JST.result(model_jst))
top20 <- top20words(model_jst)
theta <- get_parameter(model_jst, "theta")
pi <- get_parameter(model_jst, "pi")
phi <- get_parameter(model_jst, "phi")
expect_is(theta, "data.frame")
expect_equal(nrow(theta), quanteda::ndoc(data))
expect_equal(ncol(theta), 1 + ncol(quanteda::docvars(data)) + 10 * 3)
# docid + docvars + 10 topic * 3 senti
expect_is(pi, "data.frame")
expect_equal(ncol(pi), ncol(quanteda::docvars(data)) + 3) # docvars + 3 senti
expect_equal(rownames(pi), quanteda::docnames(data)) #implies length
expect_is(phi, "data.frame")
expect_equal(nrow(phi), quanteda::nfeat(data) * 10 * 3) #num features * 10 topic * 3 senti
expect_equal(ncol(phi), 4)
})
test_that("jst execution correct, supervised, with docvars", {
# The type of tokens doesn't matter for the model, so
# no cleaning here whatsoever. Reduce to 10 documents
# for reduced runtime.
data <- quanteda::dfm(quanteda::data_corpus_inaugural)
data <- quanteda::dfm_sample(data, 10)
model_jst <- jst(data, paradigm())
expect_true(is.JST.result(model_jst))
top20 <- top20words(model_jst)
top20 <- top20words(model_jst)
theta <- get_parameter(model_jst, "theta")
pi <- get_parameter(model_jst, "pi")
phi <- get_parameter(model_jst, "phi")
expect_is(theta, "data.frame")
expect_equal(nrow(theta), quanteda::ndoc(data))
expect_equal(ncol(theta), 1 + ncol(quanteda::docvars(data)) + 10 * 3)
# docid + docvars + 10 topic * 3 senti
expect_is(pi, "data.frame")
expect_equal(ncol(pi), ncol(quanteda::docvars(data)) + 3) # docvars + 3 senti
expect_equal(rownames(pi), quanteda::docnames(data)) #implies length
expect_is(phi, "data.frame")
expect_equal(nrow(phi), quanteda::nfeat(data) * 10 * 3) #num features * 10 topic * 3 senti
expect_equal(ncol(phi), 4)
})
test_that("jst execution correct, supervised, without docvars", {
# The type of tokens doesn't matter for the model, so
# no cleaning here whatsoever. Reduce to 10 documents
# for reduced runtime.
data <- quanteda::dfm(quanteda::data_corpus_inaugural)
quanteda::docvars(data) <- NULL # Remove docvars
data <- quanteda::dfm_sample(data, 10)
model_jst <- jst(data, paradigm())
expect_true(is.JST.result(model_jst))
top20 <- top20words(model_jst)
top20 <- top20words(model_jst)
theta <- get_parameter(model_jst, "theta")
pi <- get_parameter(model_jst, "pi")
phi <- get_parameter(model_jst, "phi")
expect_is(theta, "data.frame")
expect_equal(nrow(theta), quanteda::ndoc(data))
expect_equal(ncol(theta), 1 + ncol(quanteda::docvars(data)) + 10 * 3)
# docid + docvars + 10 topic * 3 senti
expect_is(pi, "data.frame")
expect_equal(ncol(pi), ncol(quanteda::docvars(data)) + 3) # docvars + 3 senti
expect_equal(rownames(pi), quanteda::docnames(data)) #implies length
expect_is(phi, "data.frame")
expect_equal(nrow(phi), quanteda::nfeat(data) * 10 * 3) #num features * 10 topic * 3 senti
expect_equal(ncol(phi), 4)
})
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