NEWS.md
This is a minor update to fix tests that were failing after an update to ggplot2 to version 3.5.0.
The reason this is a major update is that now ggplot2 version 3.4.0 or higher is required to avoid errors with grafify. The main difference is that size argument for line widths has been updated to linewidth.
It is easier to plot 2-way ANOVA designs with or without blocking factors in this version with the following updates. There are two new plot_... functions for 1-way and 2-way designs.
plot_4d_ functions can now plot 2-way ANOVAs even if the shapes argument is not provided. Graph is plotted with shape = 21 as default.
plot_4d_point_sd and plot_3d_point_sd functions for plotting 2-way and 1-way ANOVAs without or with blocking factors as mean and SD/SEM/CI95 error bars.
theme_grafify updates:
lineend = square as default for better-looking origingrafify plots by defaultbasesize (default 20)New arguments in violin plots (plot_dotviolin, plot_scatterviolin, plot_3d_scatterviolin and plot_4d_scatterviolin): two separate arguments bthick and vthick to set the line widths of the boxes and violins, respectively. The previous bvthick will still work, so if a value is provided that will be used for line widths of both boxes and violins.
New argument for two-way ANOVA graphs (plot_4d_): the group_wid can be used to change the space between groups along the X-axis (i.e., dodge width). Default group_wid = 0.8 will produce graphs that look similar to those in previous versions of grafify. If group_wid is set to 0, there will be no dodging of the factors along X-axis.
New arguments in before-after plots (i.e., plot_befafter_): bthick and lthick arguments can change line and box line widths independently.
bwid argument) of bars and boxes in plot_4d_ functions is set as 0.7.log10 tick marks:
plot_ functions: the tick marks now scale with the fontsize parameter. Previously, the sizes were set to “cm” units, which did not scale correctly. The long tick mark, middle and short ticks are sized: 7*fontsize/22, 4*fontsize/22 and 4*fontsize/22, respectively (note that the short and mid are the same size). The size (line width) equals fontsize/22, which is the same throughout grafify.plot_logscales function also has the above defaults and now has fontsize = 20 as an additional argument and sizes scale accordingly.log10 tick marks have the same colour as ticks on non-transformed axis (grey20).plot_point_sd now allows all data points to be shown. All points will be plotted with geom_point if the all_alpha setting (opacity for all symbols) is set >0 (it is set to 0 so default graphs will only show the mean of all values). There are also options for all_size and all_jitter to adjust size and overlap.ErrorType argument (default is “SD” error bars) in plot_dotbar_sd, plot_scatterbar_sd, plot_point_sd, plot_3d_scatterbar and plot_4d_scatterbar.plot_lm_predict which used to label Y-axis as pred rather than the correct name of the plotted variable.theme_grafify.plog_qqline based on stat_qq and stat_qqline.plot_histogram which was throwing up warning messages after ggplot2 update. For uniformity with other grafify graphs, histograms now have a black border (like symbol borders in dot/scatter plots).groups argument, which was deprecated several versions before, has been removed from before-after functions.plot_bar_sd deprecated as similar graphs can be plotted with plot_scatterbar_sd with s_alpha = 0.scale_colour_grafify, which broke in v3.0.0.SingleColour argument can now take base R colour names (e.g., “grey25”) in addition to previously available options.plot_grafify_palette can now also plot the quantitative colour schemes.This is a major update for grafify, which now provides wrappers for basic generalised additive models (gam) through the mgcv package. There are a more plot_ functions, a grafify theme for ggplot objects, and simple data wrangling before plotting. There are also updates within all plot_ functions, which are a facet argument, and log-transformations with axis tick marks.
Fit generalised additive models (gam) and get ANOVA tables with two new functions: ga_model and ga_anova. These are mainly for time-series analyses or where an assumption of linear relationship between predictor and outcomes is absent straight lines are not appropriate. Factor-wise smooths are fit with the by argument in mgcv, without or with a random factor. Random factors are also allowed with smooth re smooth. See documentation for mgcv smooths. Model diagnostics can be done with plot_qq_gam and plot_qq_model. Example data included as data_zooplankton is from Lathro RC, 2000.
All plot_ functions now have two major updates:
log10 or log2 with LogYTrans and LogXTrans arguments. X axis transformations are only available for plot_xy_CatGroup and plot_xy_NumGroup. With log10 transformation, log-ticks will also appear. Default axes limits and labels should work in most cases, but if needed, three additional arguments are available: LogYBreaks, LogYLimits and LogYLabels (and respective ones for the X axis).facet argument to add another variable to created faceted plots with the facet_wrap layer in ggplot2. A related argument facet_scales can be used to set Y or X axis scales on faceted panels.New plot functions:
plot_befafter_box is a new before-after plot function that includes a box and whisker plot to show data distribution in addition to lines joining matched data. In addition, both plot_befafter_colour and plot_befafter_shapes offer a box and whiskers summary of data.plot_lm_predict and plot_gam_predict can be used to plot observed (raw) data and predicted data from fitted linear models.plot_logscales is a function to easily perform “log10” or “log2” transformation on X or Y axes of any ggplot2 object along with log-ticks.Table manipulations:
table_x_reorder is a function to reorder levels within a categorical variable. This uses factor from base R stats package to convert a column into a factor and reorders it based on a user-provided vector of group names.table_summary is a wrapper around aggregate (base R) function, which gives mean, median, SD, and counts grouped by one or more variables.A grafify theme for ggplot2: theme_grafify is a modification of theme_classic for making publication-ready grafify-like graphs easily when using ggplot2.
The main motivation behind this update was to simplify the package by reducing the number of exported functions. So some features that were previously in separate functions have been made available more easily via an additional argument to existing functions (e.g. single colour function (plot_..._sc) now offered in respective plot_ function with a new argument (see below). This has uncluttered the namespace of grafify. Most of the other additions are related to colour schemes.
A new SingleColour argument has been added to two-variables plot_ functions to generate graphs with a single colour along the X-axis aesthetic. This means the 8 plot_..._sc functions introduced in v1.5.0 are deprecated, but this feature is still retained in existing plot_ functions. This option also added to plot_3d_ functions for plots of one-way ANOVA data.
Four new colourblind-friendly categorical colour schemes (chosen from cols4all package):
fishy, kelly, r4, safe
Four new quantitative schemes for continuous or divergent colours.
blue_conti, grey_conti
OrBl_div, PrGn_div
All schemes also available through scale_fill.. and scale_colour_... calls to be used on any ggplot2 object.
scale_fill_grafify and scale_colour_grafify (or scale_color_grafify) have been rewritten. These have two new arguments that offer features previously in scale_fill_grafify2/scale_colour_grafify2/ scale_color_grafify_c and scale_fill_grafify_c/scale_colour_grafify_c/ scale_color_grafify_C scale functions. These 6 functions are now deprecated to reduce exported namespace.The new arguments are discrete (logical T/F) to select discrete or continuous palettes, and ColSeq (logical T/F) to pick sequential or distant colours from a chosen palette.
plot_3d_ that incorrectly referred to xcol and shapes arguments.plot_3d_scatterviolin as compared to the other two plot_3d_ functions.posthoc_Trends... functions rewritten with stats::model.frame() to get model data frame as this is a more flexible method.light, bright and muted schemes changed slightly for better separation of colours when next to each other.jitter setting in plot_scaltter_ is set to 0.2 so the graph as plotted with jitter by default.okabe_ito (the all_grafify palette is was just a concatenation of all palettes without real basis in good visualisation). Use one of the other palettes if more than 8 colours are needed (e.g. kelly, which has 20 discreet colours).This is a major update with some new features, bugfixes, and further cleaning up of code with consistent names of arguments in preparation for CRAN submission. Some previous code may not work because of renaming of some arguments for grouping variables in plot_ functions. But older arguments are retained with deprecation warnings in most cases, so old code should largely work.
plot_ functions have a new argument ColSeq (logical TRUE/FALSE) that picks colours sequentially from palette chosen by ColPal when TRUE (default). If set to FALSE, the most distant colours are chosen, as already implemented in scale_..._grafify2 functions.geom_violin. They also get new arguments to set thickness of lines (bvthick) and transparency of boxplots (b_alpha).mixed_model_slopes and mixed_anova_slopes.posthoc_Trends implements the emmeans::emtrends call.plot_ functions now have the ... argument forwarding dots for advanced users to add arguments to ggplot geometries where necessary.plot_grafify_palette function that helps quickly visualise colours in palettes along with their names and hexcodes.plot_bar_sd and plot_bar_sd_sc have a new argument bthick to adjust the thickness of lines of the bars.Group grouping argument in plot_density, plot_histogram and plot_qqline is now called group for consistency with other plot_ functions.Factor argument in post-hoc comparisons functions (posthoc_Pairwise, posthoc_vsRes, and posthoc_Levelwise) renamed as Fixed_Factor to be consistent with mixed_model, simple_model, mixed_anova and simple_anova functions.plot_3d_scatterbar and plot_3d_scatterbox now correctly plot one-way ANOVA designs with randomised blocks with shapes mapped to levels of the random factor, and xcol as the grouping factor as originally intended but incorrectly implemented. This complements plot_4d_scatterbar and plot_4d_scatterbox which take two grouping factors and a random factor.groups in before-after plots is now called match as it is a bit more informative when showing matched data.c_alpha in plot_density and plot_histogram (for colour opacity of colours under the density curve or histogram); opacity of symbols in plot_qqline is still called s_alpha.This update fixes and cleans up code to remove all errors, warnings and notes from devtools::check(). All previous code should still work.
broom.mixed::augment is used to get model residuals than the fortify method as this will be deprecated soon. The broom.mixed package therefore required.lmerTest, but instead forces a mixed model object as lmerModLmerTest object to get F and P values in ANOVA tables from the stats::anova call.magrittr package is required for internal use of pipes (%>%).simple_model and mixed_model was cleaned up so that model outputs are as close to objects generated by native calls to lm or lmer.make_1w_rb_data and make_2w_rb_data functions have been updated to have consistent factor and level names.This version has 8 new plot_ functions ending in _sc for plotting data with two variables wherein the X variable is plotted in a single colour. This contrasts existing versions that plot the X variable with multiple colours chosen from the all_grafify palette. This is convenient when there are too many groups on the X axis and multiple colours are not necessary.
plot_qqmodel will plot a diagnostic Q-Q plot of a simple linear model (generated with simple_model or lm) or mixed effects linear model (generated with mixed_model or lmer) in a single step.
This version “breaks” a few arguments from v0.3.1, therefore is v1.4.1. Specifically, opacity for both symbols and bars/boxes/violins can be set using s_alpha and b_alpha or v_alpha, respectively; previously, only bars/boxes/violin opacity could be set with a single alpha parameter. Old code with just alpha will no longer work, sorry! There are also new graph types and arguments for ANOVAs as below.
New graph types
plot_density and plot_histogram for smooth density or histogram plots through geom_density and geom_histogram respectively.plot_scatterbox and plot_scatterviolin that complement the plot_dot... versions and instead use geom_point with position_jitter. These versions are useful when a large number of data points are needed to be plotted.Updates
simple_anova where the table also has Mean SS.mixed_anova now has two new arguments, one to change method for Df calculation and second to get type I or III SS (default is type II).jitter argument added to plot_3d.. and plot_4d.. functions for consistency with other scatter plots.bwid argument (for adjusting width of bars) added to plot_scatterbar_sd for consistency.Bug fixes in mixed_model and simple_model which now correctly lists the data used in the call field.
plot_4d_scatterbar function which is like plot_4d_scatterbox but plots bar and SD. So there are now two plot_3d_ and plot_4d_ functions.TextXAngle argument to prevent overlap.plot_dot_ functions now have dotthick option to set stroke thickness. This is similar to symthick for scatter/jitter plots.facet_wrap or facet_grid will not draw a box around panel text (unlike the default in theme_classic()).plot_3d_ and plot_4d_ functions draw symbols in black colour.plot_3d_scatterbar and plot_3d_scatterbox, which now correctly use the “shapes” variable to fill colour of bars/boxes and shape of the symbols; symbols are depicted in black.simple_anova generates type II ANOVA table through car::Anova(), so the car package is now a dependency. v0.1.0 and v0.2.0 generated type I ANOVA table through stats::anova().plot_ functions apply the all_grafify colour scheme by default (see plot_ vignettes on how to change colours)plot_xy_NumGroup) or categorical (plot_xy_CatGroup).scale_fill_grafify_c and scale_colour_grafify_c), based on Paul Tol’s variant of YlOrBl scheme.