| AlascaPlot | R Documentation |
The class contains plot options and the functions for plotting themselves. It can be accessed as obj$splot where obj is an ALASCA object.
Note: The object is typically accessed by plot(obj, ...) where the arguments are passed to the class. The arguments can also be set when the ALASCA model is created by providing arguments with prefix plot. (e.g., plot.my_theme = ...)
modelALASCA model
my_themeTheme for ggplot2 plots
variable_labelText label for the y axis
variableSelected variables to plot
x_labelText label for the x axis
group_labelLegend title
n_binsNumber of bins for histograms
ribbonBoolean. Plot ribbons for uncertainties
bwBoolean. Plot in gray scale
bwBoolean. Same as grayscale
bwBoolean. Same as grayscale
dodgewidthValidated figures have dodged points to avoid overlap
dpiResolution when saving figures. See ggplot2::ggsave()
unitsUnits for figure sizes. See ggplot2::ggsave()
filetypeFile type for saved plots. See ggplot2::ggsave()
loading_group_columnColumn for variable groups
loading_group_labelLegend table for variable groups
sort_by_loading_groupBoolean. Sort loadings within loading group
palette_endImprove contrast by not using the full color space. See scales::viridis_pal()
effect_iEffect(s) to plot
componentComponent(s) to plot
facet_ncolNumber of facet columns. See ggplot2::facet_wrap()
facet_nrowNumber of facet rows. See ggplot2::facet_wrap()
saveBoolean. Whether to save plots
flip_axisBoolean. If TRUE, variabels are plotted along the y axis
x_angleAngle for the x labels
labelsFigure labels, see ggpubr::ggarrange()
typePlot type
plot_prediction()AlascaPlot$plot_prediction()
plot_effect()AlascaPlot$plot_effect()
plot_effect_score()AlascaPlot$plot_effect_score(effect_i = 1, component = 1)
plot_effect_loading()AlascaPlot$plot_effect_loading(effect_i = 1, component = 1)
plot_effect_validation()AlascaPlot$plot_effect_validation()
plot_effect_validation_score()AlascaPlot$plot_effect_validation_score(effect_i = 1, component = 1)
plot_effect_validation_loading()AlascaPlot$plot_effect_validation_loading(effect_i = 1, component = 1)
plot_2D_advanced()AlascaPlot$plot_2D_advanced()
plot_2D()AlascaPlot$plot_2D()
plot_2D_score()AlascaPlot$plot_2D_score()
plot_2D_loading_1()AlascaPlot$plot_2D_loading_1()
plot_2D_loading_2()AlascaPlot$plot_2D_loading_2()
plot_histogram_score()AlascaPlot$plot_histogram_score()
plot_histogram_loading()AlascaPlot$plot_histogram_loading()
plot_histogram()AlascaPlot$plot_histogram()
plot_participants()AlascaPlot$plot_participants(effect_i = 1, component = 1)
new()AlascaPlot$new(model)
call_plot()AlascaPlot$call_plot(...)
plot_scree()AlascaPlot$plot_scree()
plot_residuals()AlascaPlot$plot_residuals()
plot_covars()AlascaPlot$plot_covars()
capitalize()AlascaPlot$capitalize(txt)
prettify_covar()AlascaPlot$prettify_covar(effect, txt)
get_plot_linetypes()AlascaPlot$get_plot_linetypes()
get_plot_shapes()AlascaPlot$get_plot_shapes()
get_plot_palette()AlascaPlot$get_plot_palette()
get_explained_label()AlascaPlot$get_explained_label(effect_i = 1, component = 1, type = "Score")
get_levels()AlascaPlot$get_levels(x)
get_ref()AlascaPlot$get_ref(x)
xflip()AlascaPlot$xflip(flip = TRUE)
clone()The objects of this class are cloneable with this method.
AlascaPlot$clone(deep = FALSE)
deepWhether to make a deep clone.
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