Nothing
test_that("Correct file information is returned", {
# The required files
wp$rf <- c("test.txt")
options("wordpredictor" = wp)
source("./inc.R")
# The test file name
cfn <- paste0(ed, "/test.txt")
# The DataAnalyzer object is created
da <- DataAnalyzer$new(ve = wp$ve)
# The file info is fetched
fi <- da$get_file_info(cfn)
# The line count is checked
expect_equal(fi$file_stats$total_lc, 73)
# The cleanup action is performed
source("./cu.R")
})
test_that("plot_data function works", {
# The required files
wp$rf <- c("n2.RDS")
options("wordpredictor" = wp)
source("./inc.R")
# The n-gram file name
nfn <- paste0(ed, "/n2.RDS")
# The DataAnalyzer object is created
da <- DataAnalyzer$new(nfn, ve = wp$ve)
# The top features plot is checked
df <- da$plot_n_gram_stats(opts = list(
"type" = "top_features",
"n" = 10,
"save_to" = "png",
"dir" = ed
))
# The image file path
fp <- paste0(ed, "/top_features.png")
# Checks that the top feature is in_the
expect_equal(df$pre[1], "in_the")
# Checks that the top feature frequency is 4
expect_equal(df$freq[1], 4)
# Check that the plot file was successfully created
expect_true(file.exists(fp))
# The coverage plot is checked
df <- da$plot_n_gram_stats(opts = list(
"type" = "coverage",
"n" = 10,
"save_to" = "png",
"dir" = ed
))
# The image file path
fp <- paste0(ed, "/coverage.png")
# Checks that the most occuring words are those with frequency 1
expect_equal(df$pre[1], "1")
# Checks that words with frequency 1 make up 95.8% of all words
expect_equal(round(df$freq[1], 1), 95.8)
# Check that the plot file was successfully created
expect_true(file.exists(fp))
# The cleanup action is performed
source("./cu.R")
})
test_that("ngrams with correct frequency are returned", {
# The required files
wp$rf <- c("n2.RDS")
options("wordpredictor" = wp)
source("./inc.R")
# The n-gram file name
nfn <- paste0(ed, "/n2.RDS")
# The DataAnalyzer object is created
da <- DataAnalyzer$new(nfn, ve = wp$ve)
# Bi-grams starting with "and_" are returned
df <- da$get_ngrams(fn = nfn, c = 10, pre = "^and_*")
# The data frame is sorted by frequency
df <- df[order(df$freq, decreasing = T), ]
# The frequency of the bi-gram "and_the"
f <- as.numeric(df[df$pre == "and_the", "freq"])
# The frequency is checked
expect_equal(f, 2)
# The cleanup action is performed
source("./cu.R")
})
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