R/jjcorrmat.b.R
#' @title Correlation Matrix
#' @importFrom R6 R6Class
#' @import jmvcore
#'
jjcorrmatClass <- if (requireNamespace('jmvcore')) R6::R6Class(
"jjcorrmatClass",
inherit = jjcorrmatBase,
private = list(
# init ----
.init = function() {
deplen <- length(self$options$dep)
self$results$plot$setSize(600, 450)
if (!is.null(self$options$grvar)) {
mydata <- self$data
grvar <- self$options$grvar
num_levels <- nlevels(
as.factor(mydata[[grvar]])
)
self$results$plot2$setSize(num_levels * 600, 450)
}
}
# run ----
,
.run = function() {
# Initial Message ----
if ( length(self$options$dep) <= 1 ) {
# TODO ----
todo <- glue::glue(
"<br>Welcome to ClinicoPath
<br><br>
This tool will help you generate Bar Charts.
<br><br>
This function uses ggplot2 and ggstatsplot packages. See documentations <a href = 'https://indrajeetpatil.github.io/ggstatsplot/reference/ggcorrmat.html' target='_blank'>ggcorrmat</a> and <a href = 'https://indrajeetpatil.github.io/ggstatsplot/reference/grouped_ggcorrmat.html' target='_blank'>grouped_ggcorrmat</a>.
<br>
Please cite jamovi and the packages as given below.
<br><hr>"
)
self$results$todo$setContent(todo)
return()
} else {
# TODO ----
todo <- glue::glue(
"<br>You have selected to use a correlation matrix to compare continuous variables.<br><hr>")
self$results$todo$setContent(todo)
if (nrow(self$data) == 0)
stop('Data contains no (complete) rows')
}
}
,
.plot = function(image, ggtheme, theme, ...) {
# the plot function ----
# Error messages ----
if ( length(self$options$dep) <= 1 )
return()
if (nrow(self$data) == 0)
stop('Data contains no (complete) rows')
# Prepare Data ----
mydata <- self$data
# Exclude NA ----
mydata <- jmvcore::naOmit(mydata)
# type of statistics ----
typestatistics <-
jmvcore::constructFormula(terms = self$options$typestatistics)
# define main arguments ----
myvars <- jmvcore::constructFormula(terms = self$options$dep)
myvars <- jmvcore::decomposeFormula(formula = myvars)
myvars <- unlist(myvars)
# originaltheme <- self$options$originaltheme
# ggcorrmat ----
# https://indrajeetpatil.github.io/ggstatsplot/reference/ggcorrmat.html
plot <- ggstatsplot::ggcorrmat(
data = mydata,
cor.vars = myvars,
cor.vars.names = NULL,
output = "plot",
matrix.type = "full",
matrix.method = "square",
type = typestatistics,
beta = 0.1,
k = 2L,
sig.level = 0.05,
conf.level = 0.95,
bf.prior = 0.707,
p.adjust.method = "none",
pch = "cross",
ggcorrplot.args = list(outline.color = "black"),
package = "RColorBrewer",
palette = "Dark2",
colors = c("#E69F00", "white", "#009E73"),
ggplot.component = NULL,
title = NULL,
subtitle = NULL,
caption = NULL,
messages = TRUE
)
# originaltheme <- self$options$originaltheme
#
# if (!originaltheme) {
# plot <- plot + ggtheme
# } else {
# plot <- plot + ggstatsplot::theme_ggstatsplot()
# # ggplot2::theme_bw()
# }
# Print Plot ----
print(plot)
TRUE
}
,
.plot2 = function(image, ggtheme, theme, ...) {
# the plot function ----
# Error messages ----
if ( is.null(self$options$dep) || is.null(self$options$grvar))
return()
if (nrow(self$data) == 0)
stop('Data contains no (complete) rows')
# Prepare Data ----
mydata <- self$data
# Exclude NA ----
mydata <- jmvcore::naOmit(mydata)
# type of statistics ----
typestatistics <-
jmvcore::constructFormula(terms = self$options$typestatistics)
# define main arguments ----
myvars <- jmvcore::constructFormula(terms = self$options$dep)
myvars <- jmvcore::decomposeFormula(formula = myvars)
myvars <- unlist(myvars)
# originaltheme <- self$options$originaltheme
# grouped_ggcorrmat ----
# https://indrajeetpatil.github.io/ggstatsplot/reference/grouped_ggcorrmat.html
if ( !is.null(self$options$grvar) ) {
grvar <- self$options$grvar
plot2 <- ggstatsplot::grouped_ggcorrmat(
data = mydata,
cor.vars = myvars,
cor.vars.names = NULL,
grouping.var = !!rlang::sym(grvar),
title.prefix = NULL,
output = "plot",
plotgrid.args = list(),
title.text = NULL,
title.args = list(size = 16, fontface = "bold"),
caption.text = NULL,
caption.args = list(size = 10),
sub.text = NULL,
sub.args = list(size = 12)
, ggtheme = ggtheme
, ggstatsplot.layer = originaltheme
, type = typestatistics
)
}
# originaltheme <- self$options$originaltheme
#
# if (!originaltheme) {
# plot <- plot + ggtheme
# } else {
# plot <- plot + ggstatsplot::theme_ggstatsplot()
# # ggplot2::theme_bw()
# }
# Print Plot ----
print(plot2)
TRUE
}
)
)