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test-ggcorrmat.R
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# cor.vars works with different methods of inputs ------------------------
testthat::test_that(
desc = "cor.vars works with different methods of inputs",
code = {
testthat::skip_on_cran()
# method 1
set.seed(123)
df1 <-
ggstatsplot::ggcorrmat(
data = ggplot2::msleep,
type = "p",
cor.vars = "sleep_total":"awake",
cor.vars.names = c("1", "2", "3", "4"),
p.adjust.method = "BH",
output = "aaa"
)
# method 2
set.seed(123)
df2 <-
suppressWarnings(ggstatsplot::ggcorrmat(
data = ggplot2::msleep,
type = "np",
cor.vars = c("sleep_total":"awake"),
p.adjust.method = "none",
output = "bbbb"
))
# method 3
set.seed(123)
df3 <-
ggstatsplot::ggcorrmat(
data = ggplot2::msleep,
type = "r",
cor.vars = sleep_total:awake,
p.adjust.method = "holm",
output = "ci"
)
# method 4
set.seed(123)
df4 <-
suppressWarnings(ggstatsplot::ggcorrmat(
data = ggplot2::msleep,
type = "bf",
cor.vars = c(sleep_total:awake),
p.adjust.method = "fdr",
output = "hdhfhfh"
))
# check dataframes
testthat::expect_equal(dim(df1), c(6L, 10L))
testthat::expect_equal(dim(df2), c(6L, 9L))
testthat::expect_equal(dim(df3), c(6L, 10L))
testthat::expect_equal(dim(df4), c(6L, 12L))
testthat::expect_identical(unique(df1$parameter1), c("1", "2", "3"))
}
)
# pearson's r without NAs ------------------------------------------------
testthat::test_that(
desc = "checking ggcorrmat - without NAs - pearson's r",
code = {
testthat::skip_on_cran()
# creating the plot
set.seed(123)
p <-
ggstatsplot::ggcorrmat(
data = iris,
type = "p",
title = "Iris dataset",
subtitle = "By Edgar Anderson",
ggstatsplot.layer = FALSE,
sig.level = 0.001,
p.adjust.method = "fdr",
colors = NULL,
k = 4,
ggcorrplot.args = list(
lab_col = "white",
pch.col = "white",
pch.cex = 14
),
messages = TRUE
)
# checking legend title
pb <- ggplot2::ggplot_build(p)
p_legend_title <- pb$plot$plot_env$legend.title
# checking data used to create a plot
dat <- tibble::as_tibble(p$data) %>%
dplyr::mutate_if(
.tbl = .,
.predicate = is.factor,
.funs = ~ as.character(.)
)
# checking dimensions of data
data_dims <- dim(dat)
# testing everything is okay with data
testthat::expect_equal(data_dims, c(16L, 7L))
testthat::expect_equal(dim(pb$data[[1]]), c(16L, 15L))
testthat::expect_equal(length(pb$data), 3L)
testthat::expect_equal(
dat$coef,
c(
1.0000,
-0.1176,
0.8718,
0.8179,
-0.1176,
1.0000,
-0.4284,
-0.3661,
0.8718,
-0.4284,
1.0000,
0.9629,
0.8179,
-0.3661,
0.9629,
1.0000
),
tolerance = 1e-3
)
testthat::expect_equal(dat$Var1[3], "Petal.Length")
testthat::expect_equal(dat$Var2[4], "Sepal.Length")
testthat::expect_equal(dat$signif[1], 1L)
testthat::expect_equal(dat$signif[2], 0L)
testthat::expect_equal(dat$signif[4], 1L)
testthat::expect_equal(dat$signif[5], 0L)
testthat::expect_identical(
unclass(p$plot_env$colors),
c("#1B9E77FF", "#D95F02FF", "#7570B3FF")
)
# checking layers
testthat::expect_equal(pb$plot$layers[[3]]$aes_params$shape, 4L)
testthat::expect_equal(pb$plot$layers[[3]]$aes_params$size, 14L)
testthat::expect_identical(pb$plot$layers[[3]]$aes_params$colour, "white")
# checking plot labels
testthat::expect_identical(p$labels$title, "Iris dataset")
testthat::expect_identical(p$labels$subtitle, "By Edgar Anderson")
testthat::expect_identical(
p_legend_title,
ggplot2::expr(atop(
atop(scriptstyle(bold("sample size:")), italic(n) ~
"=" ~ 150L),
atop(
scriptstyle(bold("correlation:")),
"Pearson"
)
))
)
testthat::expect_identical(
p$labels$caption,
ggplot2::expr(atop(
displaystyle(NULL),
expr = paste(
bold("X"),
" = non-significant at ",
italic("p"),
" < ",
0.001,
" (Adjustment: ",
"Benjamini & Hochberg",
")"
)
))
)
testthat::expect_null(p$labels$xlab, NULL)
testthat::expect_null(p$labels$ylab, NULL)
# checking layer data
testthat::expect_equal(dim(pb$data[[1]]), c(16L, 15L))
testthat::expect_equal(dim(pb$data[[2]]), c(16L, 15L))
testthat::expect_equal(dim(pb$data[[3]]), c(2L, 10L))
# check if number of cells is equal to number of correlations
testthat::expect_equal(
length(unique(dat$Var1))^2,
max(pb$data[[1]]$group)
)
# checking unique number of correlations
testthat::expect_equal(length(unique(pb$data[[1]]$fill)), 7L)
# checking if aesthetic modifications worked
testthat::expect_equal(pb$data[[3]]$shape[1], 4L)
testthat::expect_equal(pb$data[[3]]$size[1], 14L)
testthat::expect_identical(pb$data[[2]]$colour[1], "white")
testthat::expect_identical(pb$data[[3]]$colour[1], "white")
}
)
# robust r with NAs ---------------------------------------------------
testthat::test_that(
desc = "checking ggcorrmat - with NAs - robust r",
code = {
testthat::skip_on_cran()
# creating the plot
set.seed(123)
p <-
ggstatsplot::ggcorrmat(
data = ggplot2::msleep,
type = "r",
sig.level = 0.01,
p.adjust.method = "hommel",
matrix.type = "upper",
messages = FALSE
) +
labs(caption = NULL)
# checking legend title
pb <- ggplot2::ggplot_build(p)
p_legend_title <- pb$plot$plot_env$legend.title
# checking data used to create a plot
dat <- tibble::as_tibble(p$data) %>%
dplyr::mutate_if(
.tbl = .,
.predicate = is.factor,
.funs = ~ as.character(.)
)
# checking dimensions of data
data_dims <- dim(dat)
# testing everything is okay with data
testthat::expect_equal(data_dims, c(15L, 7L))
testthat::expect_equal(dim(pb$data[[1]]), c(15L, 15L))
testthat::expect_equal(dim(pb$data[[2]]), c(15L, 15L))
testthat::expect_equal(length(pb$data), 3L)
testthat::expect_equal(
dat$coef,
c(
0.77,
-0.52,
-0.41,
-1.00,
-0.77,
0.52,
-0.57,
-0.40,
0.88,
0.57,
-0.53,
-0.42,
0.73,
0.53,
0.87
),
tolerance = 1e-3
)
testthat::expect_equal(dat$Var1[3], "sleep_rem")
testthat::expect_equal(dat$Var2[4], "awake")
testthat::expect_equal(
dat$signif,
c(1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1)
)
testthat::expect_identical(
p$plot_env$colors,
c("#E69F00", "white", "#009E73")
)
# checking plot labels
testthat::expect_identical(
p_legend_title,
ggplot2::expr(atop(atop(
atop(scriptstyle(bold("sample size:")), italic(n)[min] ~
"=" ~ 30L),
atop(
italic(n)[mode] ~ "=" ~ 32L,
italic(n)[max] ~ "=" ~ 83L
)
), atop(
scriptstyle(
bold("correlation:")
),
"robust (% bend)"
)))
)
# check if number of cells is *not* equal to number of correlations
testthat::expect_false(
length(unique(dat$Var1))^2 == max(pb$data[[1]]$group)
)
}
)
# spearman's rho with NAs ---------------------------------------------------
testthat::test_that(
desc = "checking ggcorrmat - with NAs - spearman's rho",
code = {
testthat::skip_on_cran()
# creating the plot
set.seed(123)
p <-
suppressWarnings(ggstatsplot::ggcorrmat(
data = ggplot2::msleep,
cor.vars = sleep_total:awake,
cor.vars.names = "sleep_total",
type = "np",
sig.level = 0.01,
p.adjust.method = "hommel",
caption.default = FALSE,
messages = FALSE,
colors = NULL,
package = "wesanderson",
palette = "Rushmore1"
))
# checking legend title
pb <- ggplot2::ggplot_build(p)
p_legend_title <- pb$plot$plot_env$legend.title
# checking data used to create a plot
dat <- tibble::as_tibble(p$data) %>%
dplyr::mutate_if(
.tbl = .,
.predicate = is.factor,
.funs = ~ as.character(.)
)
# checking dimensions of data
data_dims <- dim(dat)
# testing everything is okay with data
testthat::expect_equal(data_dims, c(16L, 7L))
testthat::expect_equal(dat$coef[2], 0.76, tolerance = 1e-3)
testthat::expect_equal(dat$coef[7], -0.33, tolerance = 1e-3)
testthat::expect_equal(dat$coef[9], -0.49, tolerance = 1e-3)
testthat::expect_equal(dat$coef[14], -0.76, tolerance = 1e-3)
testthat::expect_equal(dat$Var1[15], "sleep_cycle")
testthat::expect_equal(dat$Var2[16], "awake")
testthat::expect_equal(dat$signif[1], 1L)
testthat::expect_equal(dat$signif[7], 0L)
testthat::expect_equal(dat$signif[10], 0L)
testthat::expect_equal(dat$signif[11], 1L)
# checking aesthetics
testthat::expect_identical(
unique(pb$data[[1]]$fill),
c("#0B775E", "#57896B", "#E6BE81", "#E1BD6D", "#E7BE87", "#E3BD77", "#8E9C79")
)
testthat::expect_identical(
p_legend_title,
ggplot2::expr(atop(atop(
atop(scriptstyle(bold("sample size:")), italic(n)[min] ~
"=" ~ 32L),
atop(
italic(n)[mode] ~ "=" ~ 32L,
italic(n)[max] ~ "=" ~ 83L
)
), atop(
scriptstyle(
bold("correlation:")
),
"Spearman"
)))
)
}
)