Nothing
options(papaja.mse = TRUE)
test_that(
"transmute_df_into_label()"
, {
# only one df, non-integer df, update label and remove extraneous column:
t_out1 <- apa_print(t.test(formula = yield ~ N, data = npk))
fused_1 <- transmute_df_into_label(t_out1)
expect_identical(
variable_label(fused_1$table$statistic)
, "$t(21.88)$"
)
expect_identical(
colnames(fused_1$table)
, c("estimate", "conf.int", "statistic", "p.value")
)
# only one df, integer df, update label and remove extraneous column:
t_out2 <- apa_print(t.test(formula = yield ~ N, data = npk, var.equal = TRUE))
fused_2 <- transmute_df_into_label(t_out2)
expect_identical(
variable_label(fused_2$table$statistic)
, "$t(22)$"
)
expect_identical(
colnames(fused_2$table)
, c("estimate", "conf.int", "statistic", "p.value")
)
# same df for multiple terms, update label and remove extraneous columns:
between_anova_out <- apa_print(aov(yield ~ N*P, data = npk), estimate = "pes")
fused_out <- transmute_df_into_label(between_anova_out)
expect_identical(
tinylabels::variable_label(fused_out$table$statistic)
, "$F(1, 20)$"
)
expect_identical(
colnames(fused_out$table)
, c("term", "estimate", "statistic", "mse", "p.value")
)
# df vary by term, should result in an error when trying to fuse:
npk2 <- rbind(npk, npk)
npk2$N <- factor(as.integer(npk2$N) + rep(c(0, 2), each = nrow(npk)))
between_anova_out <- apa_print(aov(yield ~ N*P, data = npk2), estimate = "pes")
expect_error(
transmute_df_into_label(between_anova_out)
, fixed = TRUE
, regexp = "Degrees of freedom (in column 'df') vary across table rows."
)
multiple_df <- rbind(t_out1$table, t_out2$table)
expect_error(
transmute_df_into_label(multiple_df)
, regexp = "Degrees of freedom (in column 'df') vary across table rows."
, fixed = TRUE
)
noninteger_df <- rbind(t_out1$table, t_out1$table)
expect_warning(
transmute_df_into_label(noninteger_df)
, regexp = "Column 'df' contains non-integer values."
, fixed = TRUE
)
# If no df columns are present in 'x', simply return 'x' but throw a message
# if check_df = FALSE
apa_no_df <- apa_print(wilcox.test(yield ~ N, data = npk, exact = F))
# No message if check_df == FALSE:
junk <- transmute_df_into_label(apa_no_df, check_df = FALSE)
# By default, expect an informative message:
expect_message(
fused_out <- transmute_df_into_label(apa_no_df)
, fixed = TRUE
, regexp = "There are no df columns to transmute. Returning original input."
)
# Also check that x is not modified:
expect_identical(
apa_no_df
, fused_out
)
}
)
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