run styler

easystats · Dec 1, 2024 · 13617a3 · 13617a3
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diff --git a/R/data_plot.R b/R/data_plot.R
@@ -85,7 +85,6 @@ data_plot <- function(x, ...) {
 }
 
 
-
 #' Complete figure with its attributes
 #'
 #' The `data_plot()` function usually stores information (such as title, axes
@@ -140,8 +139,6 @@ add_plot_attributes <- function(x) {
 }
 
 
-
-
 #' @keywords internal
 .retrieve_data <- function(x) {
   # retrieve model

diff --git a/R/geom_binomdensity.R b/R/geom_binomdensity.R
@@ -82,8 +82,6 @@ geom_binomdensity <- function(data,
 }
 
 
-
-
 # Utilities ---------------------------------------------------------------
 
 .geom_binomdensity_scale <- function(data, x, y, scale = "auto") {

diff --git a/R/geom_violindot.R b/R/geom_violindot.R
@@ -91,7 +91,6 @@ geom_violindot <- function(mapping = NULL,
   }
 
 
-
   list(
     geom_violinhalf(
       mapping = mapping,

diff --git a/R/plot.check_distribution.R b/R/plot.check_distribution.R
@@ -116,7 +116,6 @@ plot.see_check_distribution <- function(x, size_point = 2, panel = TRUE, ...) {
 }
 
 
-
 #' @export
 plot.see_check_distribution_numeric <- function(x,
                                                 size_point = 2,

diff --git a/R/plot.check_predictions.R b/R/plot.check_predictions.R
@@ -196,7 +196,6 @@ plot.see_performance_pp_check <- function(x,
 }
 
 
-
 .plot_pp_check <- function(x,
                            linewidth,
                            size_point,

diff --git a/R/plot.compare_parameters.R b/R/plot.compare_parameters.R
@@ -188,8 +188,6 @@ plot.see_compare_parameters <- function(x,
 }
 
 
-
-
 #' @export
 data_plot.see_compare_parameters <- function(x, ...) {
   col_coefficient <- grep("^(Coefficient|Log-Odds|Log-Mean|Odds Ratio|Risk Ratio|IRR)\\.", colnames(x))

diff --git a/R/plot.compare_performance.R b/R/plot.compare_performance.R
@@ -51,8 +51,6 @@ data_plot.compare_performance <- function(x, data = NULL, ...) {
 }
 
 
-
-
 # Plot --------------------------------------------------------------------
 #' Plot method for comparing model performances
 #'

diff --git a/R/plot.describe_distribution.R b/R/plot.describe_distribution.R
@@ -24,8 +24,6 @@ data_plot.parameters_distribution <- function(x, data = NULL, ...) {
 }
 
 
-
-
 # Plot --------------------------------------------------------------------
 #' Plot method for describing distributions of vectors
 #'
@@ -107,7 +105,6 @@ plot.see_parameters_distribution <- function(x,
 }
 
 
-
 .plot_see_parameters_distribution <- function(x,
                                               alpha_dispersion,
                                               color_dispersion,

diff --git a/R/plot.equivalence_test.R b/R/plot.equivalence_test.R
@@ -201,8 +201,6 @@ plot.see_equivalence_test <- function(x,
 }
 
 
-
-
 # data frame method --------------------------------
 
 #' @export
@@ -326,7 +324,6 @@ plot.see_equivalence_test_df <- function(x,
 }
 
 
-
 # freq models method --------------------------------
 
 #' @rdname plot.see_equivalence_test

diff --git a/R/plot.estimate_contrasts.R b/R/plot.estimate_contrasts.R
@@ -26,8 +26,6 @@ data_plot.estimate_contrasts <- function(x, data = NULL, ...) {
 }
 
 
-
-
 #' @keywords internal
 .data_contrasts_and_means <- function(contrasts, means, x_name, y_name) {
   polygons <- contrasts
@@ -57,7 +55,6 @@ data_plot.estimate_contrasts <- function(x, data = NULL, ...) {
 }
 
 
-
 # Plot --------------------------------------------------------------------
 
 #' Plot method for estimating contrasts

diff --git a/R/plot.estimate_density.R b/R/plot.estimate_density.R
@@ -234,8 +234,6 @@ plot.see_estimate_density <- function(x,
 }
 
 
-
-
 # Density df --------------------------------------------------------------------
 
 #' @export

diff --git a/R/plot.hdi.R b/R/plot.hdi.R
@@ -13,7 +13,6 @@ data_plot.bayestestR_hdi <- data_plot.hdi
 data_plot.bayestestR_eti <- data_plot.hdi
 
 
-
 #' @keywords internal
 .data_plot_hdi <- function(x,
                            data = NULL,
@@ -132,8 +131,6 @@ data_plot.bayestestR_eti <- data_plot.hdi
 }
 
 
-
-
 #' @keywords internal
 .compute_densities_hdi <- function(x, hdi, name = "Y") {
   hdi <- hdi[order(hdi$CI, decreasing = TRUE), ]
@@ -155,8 +152,6 @@ data_plot.bayestestR_eti <- data_plot.hdi
 }
 
 
-
-
 #' @keywords internal
 .classify_hdi <- function(x, breakpoints, labels, if_lower = TRUE) {
   limits <- list(
@@ -175,9 +170,6 @@ data_plot.bayestestR_eti <- data_plot.hdi
 }
 
 
-
-
-
 # Plot --------------------------------------------------------------------
 
 #' Plot method for uncertainty or credible intervals

diff --git a/R/plot.n_factors.R b/R/plot.n_factors.R
@@ -85,7 +85,6 @@ data_plot.n_factors <- function(x, data = NULL, type = "bar", ...) {
 data_plot.n_clusters <- data_plot.n_factors
 
 
-
 # Plot --------------------------------------------------------------------
 
 #' Plot method for numbers of clusters to extract or factors to retain

diff --git a/R/plot.p_direction.R b/R/plot.p_direction.R
@@ -119,7 +119,6 @@ data_plot.p_direction <- function(x, data = NULL, show_intercept = FALSE, ...) {
 }
 
 
-
 #' @keywords internal
 .compute_densities_pd <- function(x, name = "Y", null = 0) {
   out <- .as.data.frame_density(
@@ -139,7 +138,6 @@ data_plot.p_direction <- function(x, data = NULL, show_intercept = FALSE, ...) {
 }
 
 
-
 # Plot --------------------------------------------------------------------
 
 #' Plot method for probability of direction

diff --git a/R/plot.p_significance.R b/R/plot.p_significance.R
@@ -126,7 +126,6 @@ data_plot.p_significance <- function(x,
 }
 
 
-
 #' @keywords internal
 .compute_densities_ps <- function(x, name = "Y", threshold = 0) {
   out <- .as.data.frame_density(stats::density(x))
@@ -164,7 +163,6 @@ data_plot.p_significance <- function(x,
 }
 
 
-
 # Plot --------------------------------------------------------------------
 
 #' Plot method for practical significance

diff --git a/R/plot.parameters_brms_meta.R b/R/plot.parameters_brms_meta.R
@@ -71,8 +71,6 @@ data_plot.parameters_brms_meta <- function(x, data = NULL, normalize_height = TR
 }
 
 
-
-
 # Plot --------------------------------------------------------------------
 
 #' Plot method for Model Parameters from Bayesian Meta-Analysis

diff --git a/R/plot.parameters_model.R b/R/plot.parameters_model.R
@@ -753,7 +753,6 @@ plot.see_parameters_model <- function(x,
 }
 
 
-
 .meta_measure <- function(meta_measure) {
   switch(meta_measure,
     MD = "Raw Mean Difference",

diff --git a/R/plot.parameters_pca.R b/R/plot.parameters_pca.R
@@ -50,7 +50,6 @@ data_plot.parameters_pca <- function(x, data = NULL, ...) {
 data_plot.parameters_efa <- data_plot.parameters_pca
 
 
-
 # Plot --------------------------------------------------------------------
 
 #' Plot method for principal component analysis

diff --git a/R/plot.parameters_sem.R b/R/plot.parameters_sem.R
@@ -53,7 +53,6 @@ data_plot.parameters_sem <- function(x,
   }
 
 
-
   # Separate labels
   edges$Label_Regression <- ifelse(edges$Component == "Regression", edges$Label, "")
   edges$Label_Correlation <- ifelse(edges$Component == "Correlation", edges$Label, "")
@@ -80,8 +79,6 @@ data_plot.parameters_sem <- function(x,
 }
 
 
-
-
 # Plot --------------------------------------------------------------------
 #' @param threshold_coefficient Numeric, threshold at which value coefficients will be displayed.
 #' @param threshold_p Numeric, threshold at which value p-values will be displayed.

diff --git a/R/plot.point_estimates.R b/R/plot.point_estimates.R
@@ -69,7 +69,6 @@ data_plot.point_estimate <- function(x, data = NULL, ...) {
 data_plot.map_estimate <- data_plot.point_estimate
 
 
-
 # Plot --------------------------------------------------------------------
 
 #' Plot method for point estimates of posterior samples

diff --git a/R/plot.rope.R b/R/plot.rope.R
@@ -62,7 +62,6 @@ data_plot.rope <- function(x, data = NULL, show_intercept = FALSE, ...) {
 }
 
 
-
 # Plot --------------------------------------------------------------------
 
 #' Plot method for Region of Practical Equivalence

diff --git a/R/scale_color_bluebrown.R b/R/scale_color_bluebrown.R
@@ -27,7 +27,6 @@ scale_color_bluebrown <- function(palette = "contrast", discrete = TRUE, reverse
 }
 
 
-
 # Aliases -----------------------------------------------------------------
 
 
@@ -76,13 +75,9 @@ scale_colour_bluebrown_c <- scale_color_bluebrown_c
 scale_colour_bluebrown_d <- scale_color_bluebrown_d
 
 
-
-
-
 # Fill --------------------------------------------------------------------
 
 
-
 #' @rdname scale_color_bluebrown
 #' @export
 scale_fill_bluebrown <- function(palette = "contrast",
@@ -133,9 +128,6 @@ scale_fill_bluebrown_c <- function(palette = "contrast",
 }
 
 
-
-
-
 # Palette --------------------------------------------------------------------
 
 
@@ -175,19 +167,13 @@ bluebrown_colors <- function(...) {
 }
 
 
-
-
 bluebrown_palettes <- list(
   `full` = bluebrown_colors(),
   `contrast` = bluebrown_colors("lightblue", "blue", "darkblue", "grey", "darkbrown", "brown", "lightbrown"),
   `rainbow` = bluebrown_colors("darkblue", "blue", "lightblue", "grey", "lightbrown", "brown", "darkbrown")
 )
 
 
-
-
-
-
 #' Blue-brown design color palette
 #'
 #' The palette based on blue-brown colors.

diff --git a/R/scale_color_colorhex.R b/R/scale_color_colorhex.R
@@ -108,13 +108,9 @@ scale_colour_colorhex_c <- scale_color_colorhex_c
 scale_colour_colorhex_d <- scale_color_colorhex_d
 
 
-
-
-
 # Fill --------------------------------------------------------------------
 
 
-
 #' @rdname scale_color_colorhex
 #' @export
 scale_fill_colorhex <- function(palette = 1014416,
@@ -165,9 +161,6 @@ scale_fill_colorhex_c <- function(palette = 1014416,
 }
 
 
-
-
-
 # Palette --------------------------------------------------------------------
 
 #' Color palettes from <https://www.color-hex.com/>

diff --git a/R/scale_color_flat.R b/R/scale_color_flat.R
@@ -45,7 +45,6 @@ scale_color_flat <- function(palette = "contrast",
 }
 
 
-
 # Aliases -----------------------------------------------------------------
 
 
@@ -94,13 +93,9 @@ scale_colour_flat_c <- scale_color_flat_c
 scale_colour_flat_d <- scale_color_flat_d
 
 
-
-
-
 # Fill --------------------------------------------------------------------
 
 
-
 #' @rdname scale_color_flat
 #' @export
 scale_fill_flat <- function(palette = "contrast",
@@ -151,14 +146,9 @@ scale_fill_flat_c <- function(palette = "contrast",
 }
 
 
-
-
-
 # Palette --------------------------------------------------------------------
 
 
-
-
 # The palette based on flat design colors: https://www.materialui.co/flatuicolors
 flat_colors_list <- c(
   `red` = "#e74c3c",
@@ -205,8 +195,6 @@ flat_colors <- function(...) {
 }
 
 
-
-
 flat_palettes <- list(
   `full` = flat_colors(),
   `ice` = flat_colors("purple", "deep purple", "blue", "light blue"),
@@ -238,10 +226,6 @@ flat_palettes <- list(
 )
 
 
-
-
-
-
 #' Flat UI color palette
 #'
 #' The palette based on [Flat UI](https://materialui.co/flatuicolors).
Original file line number	Diff line number	Diff line change
Expand Up		@@ -82,8 +82,6 @@ geom_binomdensity <- function(data,
		}




		# Utilities ---------------------------------------------------------------

		.geom_binomdensity_scale <- function(data, x, y, scale = "auto") {
Expand Down
-Original file line number
+Diff line change
@@ Expand Up / @@ -91,7 +91,6 @@ geom_violindot <- function(mapping = NULL, @@
       }
       list(
         geom_violinhalf(
           mapping = mapping,
@@ Expand Down @@
Original file line number	Diff line number	Diff line change
Expand Up		@@ -234,8 +234,6 @@ plot.see_estimate_density <- function(x,
		}




		# Density df --------------------------------------------------------------------

		#' @export
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -85,7 +85,6 @@ data_plot.n_factors <- function(x, data = NULL, type = "bar", ...) {
		data_plot.n_clusters <- data_plot.n_factors



		# Plot --------------------------------------------------------------------

		#' Plot method for numbers of clusters to extract or factors to retain
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -71,8 +71,6 @@ data_plot.parameters_brms_meta <- function(x, data = NULL, normalize_height = TR
		}




		# Plot --------------------------------------------------------------------

		#' Plot method for Model Parameters from Bayesian Meta-Analysis
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -50,7 +50,6 @@ data_plot.parameters_pca <- function(x, data = NULL, ...) {
		data_plot.parameters_efa <- data_plot.parameters_pca



		# Plot --------------------------------------------------------------------

		#' Plot method for principal component analysis
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -69,7 +69,6 @@ data_plot.point_estimate <- function(x, data = NULL, ...) {
		data_plot.map_estimate <- data_plot.point_estimate



		# Plot --------------------------------------------------------------------

		#' Plot method for point estimates of posterior samples
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -62,7 +62,6 @@ data_plot.rope <- function(x, data = NULL, show_intercept = FALSE, ...) {
		}



		# Plot --------------------------------------------------------------------

		#' Plot method for Region of Practical Equivalence
Expand Down