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plot.n_factors: Add % of variance to plot (#314)
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* Add % of variance to n_factors plot

* lintrs, news, desc

* lintr

* minor x-axis

* Revert "minor x-axis"

This reverts commit 4c12bbf.

* remotes

* lintr

* lintr

* lintr

* wordlist

* lintr

* use GH to avoid warning

* fix

* lintr

* lintr

* styler

---------

Co-authored-by: Daniel <[email protected]>
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@DominiqueMakowski @strengejacke
DominiqueMakowski and strengejacke authored Feb 2, 2024
1 parent d4b4eda commit 5acfa64
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2 changes: 1 addition & 1 deletion DESCRIPTION
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Original file line number Diff line number Diff line change
Expand Up @@ -117,4 +117,4 @@ Config/Needs/website:
rstudio/bslib,
r-lib/pkgdown,
easystats/easystatstemplate
Remotes: easystats/bayestestR
Remotes: easystats/parameters, easystats/bayestestR
7 changes: 7 additions & 0 deletions NEWS.md
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@@ -1,3 +1,10 @@
# see 0.8.2

## Minor Changes

* `plot.n_factors()` now shows a dashed line over the bars, indicating the
cumulate explained variance by the number of factors.

# see 0.8.1

## Major Changes
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5 changes: 4 additions & 1 deletion R/data_plot.R
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Expand Up @@ -132,6 +132,9 @@ add_plot_attributes <- function(x) {
if (!is.null(info$title)) {
out[[length(out) + 1L]] <- ggplot2::labs(title = info$title)
}
if (!is.null(info$subtitle)) {
out[[length(out) + 1L]] <- ggplot2::labs(subtitle = info$subtitle)
}

out
}
Expand Down Expand Up @@ -176,7 +179,7 @@ add_plot_attributes <- function(x) {

#' @keywords internal
.dynGet <- function(x,
ifnotfound = stop(gettextf("%s not found", sQuote(x)), domain = NA),
ifnotfound = stop(gettextf("%s not found", sQuote(x)), domain = NA, call. = FALSE),
minframe = 1L,
inherits = FALSE) {
x <- insight::safe_deparse(x)
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2 changes: 1 addition & 1 deletion R/geom_binomdensity.R
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Expand Up @@ -62,7 +62,7 @@ geom_binomdensity <- function(data,

# Other parameters
data$.side <- ifelse(data[[y]] == y_levels[1], "top", "bottom")
data$.justification <- as.numeric(!(data[[y]] == y_levels[1]))
data$.justification <- as.numeric(data[[y]] != y_levels[1])
data$.scale <- .geom_binomdensity_scale(data, x, y, scale)

# ggdist geom
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52 changes: 31 additions & 21 deletions R/geom_from_list.R
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Expand Up @@ -114,58 +114,68 @@
#' @export
geom_from_list <- function(x, ...) {

Check warning on line 115 in R/geom_from_list.R

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GitHub Actions / lint / lint 

file=R/geom_from_list.R,line=115,col=1,[cyclocomp_linter] Reduce the cyclomatic complexity of this function from 54 to at most 40.
# Additional parameters ------------------------------------------------------
args <- x[!names(x) %in% c("geom", "aes", "data", "width", "height", "position", "show.legend")]
arguments <- x[!names(x) %in% c("geom", "aes", "data", "width", "height", "position", "show.legend")]

if (is.null(x$geom)) {
return(NULL)
}

if (inherits(x$geom, "function")) {
return(do.call(x$geom, args))
return(do.call(x$geom, args = arguments))
}

if (x$geom %in% c("density_2d", "density_2d_filled", "density_2d_polygon")) {
if (!"contour" %in% names(args)) args$contour <- TRUE
if (!"contour_var" %in% names(args)) args$contour_var <- "density"
if (!"contour" %in% names(arguments)) arguments$contour <- TRUE
if (!"contour_var" %in% names(arguments)) arguments$contour_var <- "density"
}

# If they are not geoms, return immediately
if (x$geom == "labs") {
return(do.call(ggplot2::labs, args))
return(do.call(ggplot2::labs, args = arguments))
}
if (x$geom == "guides") {
return(do.call(ggplot2::guides, args))
return(do.call(ggplot2::guides, args = arguments))
}
if (x$geom == "coord_flip") {
return(do.call(ggplot2::coord_flip, args))
return(do.call(ggplot2::coord_flip, args = arguments))
}
if (x$geom == "facet_wrap") {
return(do.call(ggplot2::facet_wrap, args))
return(do.call(ggplot2::facet_wrap, args = arguments))
}
if (x$geom == "facet_grid") {
return(do.call(ggplot2::facet_grid, args))
return(do.call(ggplot2::facet_grid, args = arguments))
}
if (x$geom == "smooth") {
if (!is.null(x$aes)) args$mapping <- do.call(ggplot2::aes, lapply(x$aes, .str_to_sym))
if (!"method" %in% names(args)) args$method <- "loess"
if (!"formula" %in% names(args)) args$formula <- "y ~ x"
return(do.call(ggplot2::geom_smooth, args))
if (!is.null(x$aes)) {
arguments$mapping <- do.call(ggplot2::aes, args = lapply(x$aes, .str_to_sym))
}
if (!"method" %in% names(arguments)) {
arguments$method <- "loess"
}
if (!"formula" %in% names(arguments)) {
arguments$formula <- "y ~ x"
}
return(do.call(ggplot2::geom_smooth, args = arguments))
}

if (startsWith(x$geom, "scale_") || startsWith(x$geom, "theme") || startsWith(x$geom, "see_")) {
return(do.call(x$geom, args))
return(do.call(x$geom, args = arguments))
}

if (startsWith(x$geom, "ggside::")) {
insight::check_if_installed("ggside")
if (!is.null(x$aes)) args$mapping <- do.call(ggplot2::aes, lapply(x$aes, .str_to_sym))
return(do.call(eval(parse(text = x$geom)), args))
if (!is.null(x$aes)) {
arguments$mapping <- do.call(ggplot2::aes, args = lapply(x$aes, .str_to_sym))
}
return(do.call(eval(parse(text = x$geom)), args = arguments))
}

if (startsWith(x$geom, "ggraph::")) {
insight::check_if_installed("ggraph")
if (!is.null(x$aes)) args$mapping <- do.call(ggplot2::aes, lapply(x$aes, .str_to_sym))
return(do.call(eval(parse(text = x$geom)), args))
if (!is.null(x$aes)) {
arguments$mapping <- do.call(ggplot2::aes, args = lapply(x$aes, .str_to_sym))
}
return(do.call(eval(parse(text = x$geom)), args = arguments))
}

# Default parameters
Expand All @@ -179,7 +189,7 @@ geom_from_list <- function(x, ...) {
}

# Default for violin
if (x$geom == "violin") {
if (x$geom == "violin") { # nolint
stat <- "ydensity"
position <- "dodge"
} else if (x$geom == "boxplot") {
Expand Down Expand Up @@ -212,7 +222,7 @@ geom_from_list <- function(x, ...) {

# Aesthetics
if ("aes" %in% names(x)) {
aes_list <- do.call(ggplot2::aes, lapply(x$aes, .str_to_sym))
aes_list <- do.call(ggplot2::aes, args = lapply(x$aes, .str_to_sym))
} else {
aes_list <- NULL
}
Expand All @@ -231,7 +241,7 @@ geom_from_list <- function(x, ...) {
geom = x$geom,
mapping = aes_list,
data = x$data,
params = args,
params = arguments,
show.legend = show.legend,
...
)
Expand Down
60 changes: 30 additions & 30 deletions R/plot.check_collinearity.R
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Original file line number Diff line number Diff line change
Expand Up @@ -69,11 +69,11 @@ plot.see_check_collinearity <- function(x,
xlim <- nrow(x)
if (ylim < 10) ylim <- 10

if (!is.null(ci_data)) {
x <- cbind(x, ci_data)
} else {
if (is.null(ci_data)) {
x$VIF_CI_low <- NA_real_
x$VIF_CI_high <- NA_real_
} else {
x <- cbind(x, ci_data)
}

# make sure legend is properly sorted
Expand Down Expand Up @@ -118,33 +118,33 @@ plot.see_check_collinearity <- function(x,
fill = colors[3],
color = NA,
alpha = 0.15
) +
{
if (!is.null(ci_data)) {
list(
ggplot2::geom_linerange(
linewidth = size_line,
na.rm = TRUE
),
ggplot2::geom_segment(
data = x[x$VIF_CI_high > ylim * 1.15, ],
mapping = aes(
x = .data$x,
xend = .data$x,
y = .data$y,
yend = .data$VIF_CI_high
),
lineend = "round",
linejoin = "round",
arrow = ggplot2::arrow(
ends = "last", type = "closed",
angle = 20, length = ggplot2::unit(0.03, "native")
),
show.legend = FALSE
)
)
}
} +
)

if (!is.null(ci_data)) {
p <- p +
ggplot2::geom_linerange(
linewidth = size_line,
na.rm = TRUE
) +
ggplot2::geom_segment(
data = x[x$VIF_CI_high > ylim * 1.15, ],
mapping = aes(
x = .data$x,
xend = .data$x,
y = .data$y,
yend = .data$VIF_CI_high
),
lineend = "round",
linejoin = "round",
arrow = ggplot2::arrow(
ends = "last", type = "closed",
angle = 20, length = ggplot2::unit(0.03, "native")
),
show.legend = FALSE
)
}

p <- p +
geom_point2(
size = size_point,
na.rm = TRUE
Expand Down
24 changes: 11 additions & 13 deletions R/plot.check_heteroscedasticity.R
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Original file line number Diff line number Diff line change
Expand Up @@ -24,21 +24,19 @@ plot.see_check_heteroscedasticity <- function(x, data = NULL, ...) {

faminfo <- insight::model_info(model)
r <- tryCatch(
{
if (inherits(model, "merMod")) {
stats::residuals(model, scaled = TRUE)
} else if (inherits(model, c("glmmTMB", "MixMod"))) {
sigma <- if (faminfo$is_mixed) {
sqrt(insight::get_variance_residual(model))
} else {
.sigma_glmmTMB_nonmixed(model, faminfo)
}
stats::residuals(model) / sigma
} else if (inherits(model, "glm")) {
stats::rstandard(model, type = "pearson")
if (inherits(model, "merMod")) {
stats::residuals(model, scaled = TRUE)
} else if (inherits(model, c("glmmTMB", "MixMod"))) {
sig <- if (faminfo$is_mixed) {
sqrt(insight::get_variance_residual(model))
} else {
stats::rstandard(model)
.sigma_glmmTMB_nonmixed(model, faminfo)
}
stats::residuals(model) / sig
} else if (inherits(model, "glm")) {
stats::rstandard(model, type = "pearson")
} else {
stats::rstandard(model)
},
error = function(e) {
NULL
Expand Down
4 changes: 2 additions & 2 deletions R/plot.check_model.R
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Original file line number Diff line number Diff line change
Expand Up @@ -209,9 +209,9 @@ plot.see_check_model <- function(x,
pw <- plots(p, n_columns = n_columns)
.safe_print_plots(pw, ...)
invisible(pw)
} else {
return(p)
}

p
}


Expand Down
2 changes: 1 addition & 1 deletion R/plot.check_normality.R
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Original file line number Diff line number Diff line change
Expand Up @@ -68,7 +68,7 @@ plot.see_check_normality <- function(x,
alpha_level = alpha
)
} else {
if (type == "qq") {
if (type == "qq") { # nolint
model_info <- attributes(x)$model_info
if (inherits(model, c("lme", "lmerMod", "merMod", "glmmTMB", "afex_aov", "BFBayesFactor"))) {
res_ <- suppressMessages(sort(stats::residuals(model), na.last = NA))
Expand Down
12 changes: 5 additions & 7 deletions R/plot.check_outliers.R
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Original file line number Diff line number Diff line change
Expand Up @@ -41,9 +41,9 @@ plot.see_check_outliers <- function(x,
...) {
type <- match.arg(type)
influential_obs <- attributes(x)$influential_obs
methods <- attr(x, "methods", exact = TRUE)
outlier_methods <- attr(x, "methods", exact = TRUE)

if (type == "dots" && !is.null(influential_obs) && (is.null(methods) || length(methods) == 1)) {
if (type == "dots" && !is.null(influential_obs) && (is.null(outlier_methods) || length(outlier_methods) == 1)) {
.plot_diag_outliers_new(
influential_obs,
show_labels = show_labels,
Expand All @@ -52,12 +52,10 @@ plot.see_check_outliers <- function(x,
dot_alpha_level = dot_alpha,
colors = colors
)
} else if (length(outlier_methods) == 1) {
.plot_diag_outliers(x, show_labels = show_labels, size_text = size_text, rescale_distance = rescale_distance)
} else {
if (length(methods == 1)) {
.plot_diag_outliers(x, show_labels = show_labels, size_text = size_text, rescale_distance = rescale_distance)
} else {
.plot_outliers_multimethod(x, rescale_distance)
}
.plot_outliers_multimethod(x, rescale_distance)
}
}

Expand Down
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4 comments on commit 5acfa64

@strengejacke
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@IndrajeetPatil I don't understand the error in the vignette

Quitting from lines 284-294 [unnamed-chunk-22] (parameters.Rmd)
Error in `map()`:
ℹ In index: 6.
ℹ With name: vignettes/parameters.Rmd.
Caused by error in `seq_len()`:
! (converted from warning) first element used of 'length.out' argument
Backtrace:
 1. parameters::model_parameters(ma)
 2. parameters:::model_parameters.rma(ma)
 3. parameters:::.model_parameters_generic(...)
 4. parameters:::.add_model_parameters_attributes(...)
 5. parameters:::.format_value_labels(params, model)
 6. insight::get_data(model, source = "mf", verbose = FALSE)

This is a reprex of the affected code.

library(easystats)
#> # Attaching packages: easystats 0.7.0.2 (red = needs update)
#> ✔ bayestestR  0.13.1.7    ✔ correlation 0.8.4.2  
#> ✔ datawizard  0.9.1       ✔ effectsize  0.8.6.6  
#> ✖ insight     0.19.7.10   ✔ modelbased  0.8.6.5  
#> ✔ performance 0.10.8.10   ✔ parameters  0.21.3.9 
#> ✔ report      0.5.8       ✔ see         0.8.1    
#> 
#> Restart the R-Session and update packages with `easystats::easystats_update()`.
library(metafor)
#> Loading required package: Matrix
#> Loading required package: metadat
#> Loading required package: numDeriv
#> 
#> Loading the 'metafor' package (version 4.4-0). For an
#> introduction to the package please type: help(metafor)

options(warn = 2)

mydat <- data.frame(
  effectsize = c(-0.393, 0.675, 0.282, -1.398),
  standarderror = c(0.317, 0.317, 0.13, 0.36)
)

ma <- rma(yi = effectsize, sei = standarderror, method = "REML", data = mydat)
result <- model_parameters(ma)

result
#> Meta-analysis using 'metafor'
#> 
#> Parameter | Coefficient |   SE |         95% CI |     z |      p | Weight
#> -------------------------------------------------------------------------
#> Study 1   |       -0.39 | 0.32 | [-1.01,  0.23] | -1.24 | 0.215  |   9.95
#> Study 2   |        0.68 | 0.32 | [ 0.05,  1.30] |  2.13 | 0.033  |   9.95
#> Study 3   |        0.28 | 0.13 | [ 0.03,  0.54] |  2.17 | 0.030  |  59.17
#> Study 4   |       -1.40 | 0.36 | [-2.10, -0.69] | -3.88 | < .001 |   7.72
#> Overall   |       -0.18 | 0.44 | [-1.05,  0.68] | -0.42 | 0.676  |
#> 
#> Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
#>   using a Wald z-distribution approximation.
plot(result)

Created on 2024-02-02 with reprex v2.1.0

@IndrajeetPatil
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Looks like insight::get_data(model, source = "mf", verbose = FALSE) can't find the required data when evaluated by knitr in a fresh environment?

@strengejacke
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But isn't a reprex also in a fresh environment?

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withr::with_environment(
  new.env(),
  {
    library(easystats)
    library(metafor)

    options(warn = 2)

    mydat <- data.frame(
      effectsize = c(-0.393, 0.675, 0.282, -1.398),
      standarderror = c(0.317, 0.317, 0.13, 0.36)
    )

    ma <- rma(yi = effectsize, sei = standarderror, method = "REML", data = mydat)
    result <- model_parameters(ma)

    print(result)
    plot(result)
  }
)
#> # Attaching packages: easystats 0.7.0.2 (red = needs update)
#> ✔ bayestestR  0.13.1.7    ✔ correlation 0.8.4.2  
#> ✔ datawizard  0.9.1       ✔ effectsize  0.8.6.6  
#> ✖ insight     0.19.7.10   ✔ modelbased  0.8.6.5  
#> ✔ performance 0.10.8.10   ✔ parameters  0.21.3.9 
#> ✔ report      0.5.8       ✔ see         0.8.1    
#> 
#> Restart the R-Session and update packages with `easystats::easystats_update()`.
#> Loading required package: Matrix
#> Loading required package: metadat
#> Loading required package: numDeriv
#> 
#> Loading the 'metafor' package (version 4.4-0). For an
#> introduction to the package please type: help(metafor)
#> Meta-analysis using 'metafor'
#> 
#> Parameter | Coefficient |   SE |         95% CI |     z |      p | Weight
#> -------------------------------------------------------------------------
#> Study 1   |       -0.39 | 0.32 | [-1.01,  0.23] | -1.24 | 0.215  |   9.95
#> Study 2   |        0.68 | 0.32 | [ 0.05,  1.30] |  2.13 | 0.033  |   9.95
#> Study 3   |        0.28 | 0.13 | [ 0.03,  0.54] |  2.17 | 0.030  |  59.17
#> Study 4   |       -1.40 | 0.36 | [-2.10, -0.69] | -3.88 | < .001 |   7.72
#> Overall   |       -0.18 | 0.44 | [-1.05,  0.68] | -0.42 | 0.676  |
#> 
#> Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
#>   using a Wald z-distribution approximation.

Created on 2024-02-02 with reprex v2.1.0

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