Type: Package
Title: Utility Functions for Plotting
Version: 0.3.5
Date: 2026-02-23
Maintainer: Meng Xu <mengxu98@qq.com>
Description: Provides utility functions for plotting. Includes functions for color manipulation, plot customization, panel size control, data optimization for plots, and layout adjustments.
License: MIT + file LICENSE
URL: https://mengxu98.github.io/thisplot/
BugReports: https://github.com/mengxu98/thisplot/issues
Depends: R (≥ 4.1.0)
Imports: cli, geomtextpath, ggrepel, ggplot2, gtable, igraph, methods, patchwork, stats, thisutils (≥ 0.3.6), utils
Suggests: circlize, dplyr, ggupset, ggVennDiagram, grDevices, grid, htmltools, png, purrr, ragg, scales, stringr, tidyr
Config/Needs/website: mengxu98/thistemplate
Config/testthat/edition: 3
Encoding: UTF-8
RoxygenNote: 7.3.3
Language: en-US
LazyData: true
NeedsCompilation: no
Packaged: 2026-02-23 07:54:44 UTC; mx
Author: Meng Xu ORCID iD [aut, cre]
Repository: CRAN
Date/Publication: 2026-02-23 08:50:02 UTC

Utility Functions for Data Visualization and Plotting

Description

Provides utility functions for data visualization and plotting in R. Includes functions for color manipulation, plot customization, panel size control, data optimization for plots, and layout adjustments. Designed to enhance workflows with ggplot2, patchwork, and ComplexHeatmap.

Author(s)

Meng Xu (Maintainer), mengxu98@qq.com

Source

https://mengxu98.github.io/thisplot/

See Also

Useful links:

Blend two colors using a specified mode

Description

Blend two colors with alpha channels using one of several blending modes: blend, average, screen, or multiply.

Usage

Blend2Color(C1, C2, mode = "blend")

Arguments

C1

A list containing the first color RGB values and alpha channel.

C2

A list containing the second color RGB values and alpha channel.

mode

The blending mode to use. One of "blend", "average", "screen", or "multiply". Default is "blend".

Value

A list containing the blended RGB values and alpha channel.

Blend a list of colors

Description

Blend multiple colors with alpha channels into a single color using a specified blending mode.

Usage

BlendRGBList(Clist, mode = "blend", RGB_BackGround = c(1, 1, 1))

Arguments

Clist

A list of colors, where each color is a list containing RGB values and alpha channel.

mode

The blending mode to use. One of "blend", "average", "screen", or "multiply". Default is "blend".

RGB_BackGround

The background RGB color to composite with. Default is c(1, 1, 1) (white).

Value

A numeric vector of RGB values.

Chinese traditional colors system

Description

A color system based on Chinese traditional colors with 1058 colors.

Usage

ChineseColors()

Value

A ChineseColors object. Detailed information can be found in print.ChineseColors().

See Also

chinese_colors for the dataset of Chinese traditional colors. get_chinese_palettes for getting Chinese color palettes. visual_colors for visualizing any color vector. get_colors for searching colors in dataset and palettes.

Examples

cc <- ChineseColors()
cc

# Get a color by pinyin
get_colors("pinlan")

# By number
get_colors(44)

# By hex code
get_colors("#2B73AF")

# Multiple colors
get_colors("pinlan", "piao")
get_colors(91:100)

# Chinese names
cc$visual_colors(
  title = "Chinese Traditional Colors",
  name_type = "chinese"
)

# pinyin as names
cc$visual_colors(
  loc_range = c(1, 120),
  title = "Chinese Traditional Colors",
  name_type = "pinyin"
)

# rgb as names
cc$visual_colors(
  loc_range = c(1, 120),
  title = "Colors with RGB values",
  name_type = "rgb"
)

# hex as names
cc$visual_colors(
  loc_range = c(1, 120),
  title = "Colors with hex codes",
  name_type = "hex"
)

Convert RGBA color to RGB with background

Description

Convert an RGBA (Red, Green, Blue, Alpha) color to RGB by compositing it with a background color based on the alpha channel.

Usage

RGBA2RGB(RGBA, BackGround = c(1, 1, 1))

Arguments

RGBA

A list containing RGB values and alpha channel.

BackGround

The background RGB color to composite with. Default is c(1, 1, 1) (white).

Value

A numeric vector of RGB values.

Statistic Plot

Description

Visualizes data using various plot types such as bar plots, rose plots, ring plots, pie charts, trend plots, area plots, dot plots, sankey plots, chord plots, venn diagrams, and upset plots.

Usage

StatPlot(
  meta.data,
  stat.by,
  group.by = NULL,
  split.by = NULL,
  bg.by = NULL,
  flip = FALSE,
  NA_color = "grey",
  NA_stat = TRUE,
  keep_empty = FALSE,
  individual = FALSE,
  stat_level = NULL,
  plot_type = c("bar", "rose", "ring", "pie", "trend", "area", "dot", "sankey", "chord",
    "venn", "upset"),
  stat_type = c("percent", "count"),
  position = c("stack", "dodge"),
  palette = "Paired",
  palcolor = NULL,
  alpha = 1,
  bg_palette = "Paired",
  bg_palcolor = NULL,
  bg_alpha = 0.2,
  label = FALSE,
  label.size = 3.5,
  label.fg = "black",
  label.bg = "white",
  label.bg.r = 0.1,
  aspect.ratio = NULL,
  title = NULL,
  subtitle = NULL,
  xlab = NULL,
  ylab = NULL,
  legend.position = "right",
  legend.direction = "vertical",
  theme_use = "theme_this",
  theme_args = list(),
  combine = TRUE,
  nrow = NULL,
  ncol = NULL,
  byrow = TRUE,
  force = FALSE,
  seed = 11
)

Arguments

meta.data

The data frame containing the data to be plotted.

stat.by

The column name(s) in meta.data specifying the variable(s) to be plotted.

group.by

The column name(s) in meta.data specifying the grouping variable(s). Default is NULL.

split.by

The column name in meta.data specifying the variable to split plots by. Default is NULL.

bg.by

The column name in meta.data specifying the background variable for bar plots.

flip

Whether to flip the plot. Default is FALSE.

NA_color

The color to use for missing values.

NA_stat

Whether to include missing values in the plot. Default is TRUE.

keep_empty

Whether to keep empty groups in the plot. Default is FALSE.

individual

Whether to plot individual groups separately. Default is FALSE.

stat_level

The level(s) of the variable(s) specified in stat.by to include in the plot. Default is NULL.

plot_type

The type of plot to create. Can be one of "bar", "rose", "ring", "pie", "trend", "area", "dot", "sankey", "chord", "venn", or "upset".

stat_type

The type of statistic to compute for the plot. Can be one of "percent" or "count".

position

The position adjustment for the plot. Can be one of "stack" or "dodge".

palette

The name of the color palette to use. Default is "Paired".

palcolor

Custom colors to use instead of palette. Default is NULL.

alpha

The transparency level for the plot.

bg_palette

The name of the background color palette to use for bar plots.

bg_palcolor

The color to use in the background color palette.

bg_alpha

The transparency level for the background color in bar plots.

label

Whether to add labels on the plot. Default is FALSE.

label.size

The size of the labels.

label.fg

The foreground color of the labels.

label.bg

The background color of the labels.

label.bg.r

The radius of the rounded corners of the label background.

aspect.ratio

Aspect ratio of the panel. Default is NULL.

title

The title of the plot. Default is NULL.

subtitle

The subtitle of the plot. Default is NULL.

xlab

The label for the x-axis. Default is NULL.

ylab

The label for the y-axis. Default is NULL.

legend.position

The position of the legend. Can be one of "none", "left", "right", "bottom", "top", or a two-element numeric vector. Default is "right".

legend.direction

The direction of the legend. Can be one of "vertical" or "horizontal". Default is "vertical".

theme_use

The theme to use for the plot. Default is "theme_this".

theme_args

Additional arguments to pass to the theme function. Default is list().

combine

Whether to combine multiple plots into one. Default is TRUE.

nrow

Number of rows when combining plots. Default is NULL.

ncol

Number of columns when combining plots. Default is NULL.

byrow

Whether to fill plots by row when combining. Default is TRUE.

force

Whether to force plotting even when variables have more than 100 levels. Default is FALSE.

seed

Random seed for reproducibility. Default is 11.

Examples

set.seed(1)
meta_data <- data.frame(
  Type = factor(
    sample(c("A", "B", "C"),
      50,
      replace = TRUE,
      prob = c(0.5, 0.3, 0.2)
    )
  ),
  Group = factor(sample(c("X", "Y", "Z"), 50, replace = TRUE)),
  Batch = factor(sample(c("B1", "B2"), 50, replace = TRUE))
)
meta_data$Region <- factor(
  ifelse(meta_data$Group %in% c("X", "Y"), "R1", "R2"),
  levels = c("R1", "R2")
)

StatPlot(
  meta_data,
  stat.by = "Type",
  group.by = "Group",
  split.by = "Batch",
  plot_type = "bar",
  position = "dodge"
)

StatPlot(
  meta_data,
  stat.by = "Type",
  group.by = "Group",
  stat_type = "count",
  plot_type = "ring",
  position = "dodge"
)

StatPlot(
  meta_data,
  stat.by = "Type",
  group.by = "Group",
  stat_type = "count"
)

StatPlot(
  meta_data,
  stat.by = "Type",
  plot_type = "pie"
)

StatPlot(
  meta_data,
  stat.by = "Type",
  group.by = "Group",
  stat_type = "count",
  plot_type = "area"
)

StatPlot(
  meta_data,
  stat.by = "Type",
  group.by = "Group",
  plot_type = "dot"
)

StatPlot(
  meta_data,
  stat.by = "Type",
  group.by = "Group",
  stat_type = "count",
  plot_type = "trend"
)

Add a grob to a gtable

Description

Add a grob to a gtable at a specified position (top, bottom, left, or right).

Usage

add_grob(
  gtable,
  grob,
  position = c("top", "bottom", "left", "right", "none"),
  space = NULL,
  clip = "on"
)

Arguments

gtable

A gtable object.

grob

A grob or gtable object to add.

position

The position to add the grob. One of "top", "bottom", "left", "right", or "none".

space

The space to allocate for the grob. If NULL, will be calculated automatically.

clip

The clipping mode. Default is "on".

Value

A gtable object with the grob added.

Convert a color with specified alpha level

Description

Convert a color with specified alpha level

Usage

adjcolors(colors, alpha)

Arguments

colors

Color vectors.

alpha

Alpha level in ⁠[0,1]⁠.

Value

A character vector of hexadecimal color codes with the specified alpha level.

Examples

colors <- c("red", "blue", "green")
adjcolors(colors, 0.5)
ggplot2::alpha(colors, 0.5)

show_palettes(
  list(
    "raw" = colors,
    "adjcolors" = adjcolors(colors, 0.5),
    "ggplot2::alpha" = ggplot2::alpha(colors, 0.5)
  )
)

Adjust graph layout to avoid node overlaps

Description

Adjust the layout of a graph to prevent node overlaps by considering node widths and heights.

Usage

adjustlayout(graph, layout, width, height = 2, scale = 100, iter = 100)

Arguments

graph

An igraph graph object.

layout

A matrix with two columns representing the initial layout coordinates.

width

A numeric vector of node widths.

height

The height constraint for nodes. Default is 2.

scale

The scaling factor for the layout. Default is 100.

iter

The number of iterations for the adjustment algorithm. Default is 100.

Value

A matrix with adjusted layout coordinates.

Convert a plot object to a grob

Description

Convert various plot objects (gList, patchwork, ggplot) to a grob object.

Usage

as_grob(plot, ...)

Arguments

plot

A plot object (gList, patchwork, or ggplot).

...

Additional arguments passed to other functions.

Value

A grob object.

Convert a plot object to a gtable

Description

Convert various plot objects (gtable, grob, patchwork, ggplot) to a gtable object.

Usage

as_gtable(plot, ...)

Arguments

plot

A plot object (gtable, grob, patchwork, or ggplot).

...

Additional arguments passed to other functions.

Value

A gtable object.

Blends a list of colors using the specified blend mode

Description

Blends a list of colors using the specified blend mode

Usage

blendcolors(colors, mode = c("blend", "average", "screen", "multiply"))

Arguments

colors

Color vectors.

mode

Blend mode. One of "blend", "average", "screen", or "multiply".

Value

A character vector of hexadecimal color codes representing the blended color.

Examples

blend <- c(
  "red",
  "green",
  blendcolors(c("red", "green"),
    mode = "blend"
  )
)
average <- c(
  "red",
  "green",
  blendcolors(c("red", "green"),
    mode = "average"
  )
)
screen <- c(
  "red",
  "green",
  blendcolors(c("red", "green"),
    mode = "screen"
  )
)
multiply <- c(
  "red",
  "green",
  blendcolors(c("red", "green"),
    mode = "multiply"
  )
)
show_palettes(
  list(
    "blend" = blend,
    "average" = average,
    "screen" = screen,
    "multiply" = multiply
  )
)

Build a patchwork gtable

Description

Build a gtable from a patchwork object by arranging multiple plots according to the layout specification.

Usage

build_patchwork(
  x,
  guides = "auto",
  table_rows = 18,
  table_cols = 15,
  panel_row = 10,
  panel_col = 8
)

Arguments

x

A patchwork object.

guides

How to handle guides. Default is "auto".

table_rows

The number of rows in the table grid. Default is 18.

table_cols

The number of columns in the table grid. Default is 15.

panel_row

The row index for panels. Default is 10.

panel_col

The column index for panels. Default is 8.

Value

A gtable object.

Check CI environment

Description

Check CI environment

Usage

check_ci_env()

Value

A logical value.

Chinese traditional colors dataset

Description

A dataset containing optimized traditional Chinese colors. These colors are extracted from those books:

Thanks to the author of the blog for providing the data.

Examples

data(chinese_colors)
color_sets <- attr(chinese_colors, "color_sets")
show_palettes(
  list(
    color_sets$ChineseSet8,
    color_sets$ChineseSet16,
    color_sets$ChineseSet32
  )
)

# Use ChineseColors class
cc <- ChineseColors()
cc$visual_colors(
  title = "Chinese Traditional Colors",
  name_type = "chinese"
)

Convert color names to hexadecimal format

Description

Convert color names to hexadecimal RGB color codes.

Usage

col2hex(cname)

Arguments

cname

A character vector of color names.

Value

A character vector of hexadecimal color codes.

Drop unused data in the plot

Description

Drop unused data points from a ggplot or patchwork object while preserving the plot structure. This function keeps only a single row of data for each unique combination of used variables, which can significantly reduce the object size when the original data contains many rows that are not displayed in the plot (e.g., due to scale limits or filtering).

Usage

drop_data(p)

## S3 method for class 'ggplot'
drop_data(p)

## S3 method for class 'patchwork'
drop_data(p)

## Default S3 method:
drop_data(p)

Arguments

p

A ggplot object or a patchwork object.

Value

A ggplot or patchwork object with unused data points removed.

Examples

library(ggplot2)
library(patchwork)
p <- ggplot(
  data = mtcars,
  aes(x = mpg, y = wt, colour = cyl)
) +
  geom_point() +
  scale_x_continuous(limits = c(10, 30)) +
  scale_y_continuous(limits = c(1, 6))
object.size(p)

p_drop <- drop_data(p)
object.size(p_drop)

p / p_drop

Extract grobs from a list

Description

Extract grobs from a named list of grobs based on the specified x and y indices.

Usage

extractgrobs(vlnplots, x_nm, y_nm, x, y)

Arguments

vlnplots

A named list of grobs.

x_nm

A character vector of names for the x dimension.

y_nm

A character vector of names for the y dimension.

x

An integer index for the x dimension.

y

An integer index for the y dimension.

Value

The extracted grob(s).

geom_alluvial

Description

Creates an alluvial plot which visualize flows between nodes. Each observation needs to have a 'x' aesthetic as well as a 'next_x' column which declares where that observation should flow. Also each observation should have a 'node' and a 'next_node' aesthetic which provide information about which group in the y-direction.

Usage

geom_alluvial(
  mapping = NULL,
  data = NULL,
  position = "identity",
  na.rm = FALSE,
  show.legend = NA,
  space = 0,
  width = 0.1,
  smooth = 8,
  inherit.aes = TRUE,
  ...
)

Arguments

mapping

Provide you own mapping. Both x and y need to be numeric.

data

Provide you own data.

position

Change position.

na.rm

Remove missing values.

show.legend

Show legend in plot.

space

Space between nodes in the y-direction.

width

Width of nodes.

smooth

How much smooth should the curve have? More means steeper curve.

inherit.aes

Should the geom inherit aesthetics.

...

Other arguments to be passed to the geom.

Value

A ggplot layer.

geom_alluvial_label

Description

Creates centered labels or text in nodes of your alluvial plot. Needs to have the exact same aesthetics as the call to 'geom_alluvial' to work.

Usage

geom_alluvial_text(
  mapping = NULL,
  data = NULL,
  position = "identity",
  na.rm = FALSE,
  show.legend = NA,
  space = 0,
  width = 0.1,
  inherit.aes = TRUE,
  ...
)

geom_alluvial_label(
  mapping = NULL,
  data = NULL,
  position = "identity",
  na.rm = FALSE,
  show.legend = NA,
  space = 0,
  width = 0.1,
  inherit.aes = TRUE,
  ...
)

Arguments

mapping

Provide you own mapping. Both x and y need to be numeric.

data

Provide you own data.

position

Change position.

na.rm

Remove missing values.

show.legend

Show legend in plot.

space

Space between nodes in the y-direction.

width

Width of nodes.

inherit.aes

Should the geom inherit aesthetics.

...

Other arguments to be passed to the geom.

Details

Other important arguments are; 'space' which provides the space between nodes in the y-direction; 'shift' which shifts nodes in the y-direction.

Value

A ggplot layer.

geom_sankey

Description

Creates a sankey plot which visualize flows between nodes. Each observation needs to have a 'x' aesthetic as well as a 'next_x' column which declares where that observation should flow. Also each observation should have a 'node' and a 'next_node' aesthetic which provide information about which group in the y-direction. By default each row of the data frame is counted to calculate the size of flows. A manual flow value can be added with the 'value' aesthetic.

Usage

geom_sankey(
  mapping = NULL,
  data = NULL,
  position = "identity",
  na.rm = FALSE,
  show.legend = NA,
  space = NULL,
  type = "sankey",
  width = 0.1,
  smooth = 8,
  inherit.aes = TRUE,
  ...
)

Arguments

mapping

Provide you own mapping. Both x and y need to be numeric.

data

Provide you own data.

position

Change position.

na.rm

Remove missing values.

show.legend

Show legend in plot.

space

Space between nodes in the y-direction.

type

Either 'sankey' or 'alluvial'.

width

Width of nodes.

smooth

How much smooth should the curve have? More means steeper curve.

inherit.aes

Should the geom inherit aesthetics.

...

Other arguments to be passed to the geom.

Value

A ggplot layer.

Aesthetics

geom_sankey understand the following aesthetics (required aesthetics are in bold):

- **x0** - **y0** - **a** - **b** - **angle** - m1 - m2 - color - fill - size - linetype - alpha - lineend

Examples

dat <- data.frame(
  Group = c("A", "A", "B", "B", "C"),
  Type = c("X", "Y", "X", "Y", "X")
)
long <- make_long(dat, Group, Type)
ggplot2::ggplot(
  long,
  ggplot2::aes(
    x = x,
    next_x = next_x,
    node = node,
    next_node = next_node,
    fill = node
  )
) +
  geom_sankey() +
  theme_sankey()

geom_sankey_bump

Description

Creates a sankey bump plot which visualize flows between nodes. Each observation needs to have a 'x' aesthetic as well as a 'next_x' column which declares where that observation should flow. Also, each observation should have a 'node' and a 'next_node' aesthetic which provide information about which group in the y-direction.

Usage

geom_sankey_bump(
  mapping = NULL,
  data = NULL,
  position = "identity",
  na.rm = FALSE,
  show.legend = NA,
  smooth = 8,
  type = "sankey",
  inherit.aes = TRUE,
  ...
)

Arguments

mapping

Provide you own mapping. Both x and y need to be numeric.

data

Provide you own data.

position

Change position.

na.rm

Remove missing values.

show.legend

Show legend in plot.

smooth

How much smooth should the curve have? More means steeper curve.

type

Either 'sankey' or 'alluvial'.

inherit.aes

Should the geom inherit aesthetics.

...

Other arguments to be passed to the geom.

Details

Other important arguments are; 'space' which provides the space between nodes in the y-direction; 'shift' which shifts nodes in the y-direction.

Value

A ggplot layer.

geom_sankey_label

Description

Creates centered labels or text in nodes of your sankey plot. Needs to have the exact same aesthetics as the call to 'geom_sankey' to work.

Usage

geom_sankey_label(
  mapping = NULL,
  data = NULL,
  position = "identity",
  na.rm = FALSE,
  show.legend = NA,
  space = NULL,
  type = "sankey",
  width = 0.1,
  inherit.aes = TRUE,
  ...
)

geom_sankey_text(
  mapping = NULL,
  data = NULL,
  position = "identity",
  na.rm = FALSE,
  show.legend = NA,
  space = NULL,
  type = "sankey",
  width = 0.1,
  inherit.aes = TRUE,
  ...
)

Arguments

mapping

Provide you own mapping. Both x and y need to be numeric.

data

Provide you own data.

position

Change position.

na.rm

Remove missing values.

show.legend

Show legend in plot.

space

Space between nodes in the y-direction.

type

Either 'sankey' or 'alluvial'.

width

Width of nodes.

inherit.aes

Should the geom inherit aesthetics.

...

Other arguments to be passed to the geom.

Value

A ggplot layer.

Get Chinese color palettes

Description

Get Chinese color palettes

Usage

get_chinese_palettes(prefix = "Chinese")

Arguments

prefix

The prefix of the palette names. Default is '"Chinese_"'.

Value

A list of Chinese color palettes.

Examples

show_palettes(get_chinese_palettes())

Get colors from Chinese colors dataset or palettes

Description

Search for colors in the Chinese colors dataset and all available palettes. This function can search by palette names, color names (pinyin or Chinese), numbers, or hex codes. It automatically searches in all palettes and reports which palette(s) contain the found colors.

Usage

get_colors(..., palettes = NULL)

Arguments

...

One or more search values. Can be palette names, color names (pinyin or Chinese), numbers, or hex codes. If NULL, using all Chinese colors.

palettes

Optional. A named list of palettes to search in. If NULL (default), searches in all available palettes.

Value

A data frame with class colors containing matching color information. The result is automatically printed using print.colors().

See Also

chinese_colors for the dataset of Chinese traditional colors. get_chinese_palettes for getting Chinese color palettes. ChineseColors for the ChineseColors object.

Examples

get_colors("Paired")

get_colors("#FF7F00")

get_colors("pinlan")
get_colors(44)
get_colors("#2B73AF")

get_colors("cyan", palettes = "ChineseSet64")

Extract legend from a plot

Description

Extract the legend grob from a plot object.

Usage

get_legend(plot)

Arguments

plot

A plot object.

Value

The legend grob.

Get used vars in a ggplot object

Description

Get used vars in a ggplot object

Usage

get_vars(p, reverse = FALSE, verbose = TRUE)

Arguments

p

A ggplot object.

reverse

Whether to return unused vars. Default is FALSE.

verbose

Whether to print the message. Default is TRUE.

Value

A character vector of variable names. If reverse is FALSE, returns used variables; if TRUE, returns unused variables.

Examples

library(ggplot2)
p <- ggplot(
  data = mtcars,
  aes(x = mpg, y = wt, colour = cyl)
) +
  geom_point()
get_vars(p)
get_vars(p, reverse = TRUE)

Draw grobs at specified positions

Description

Draw a list of grobs at specified positions with given widths and heights.

Usage

grid_draw(groblist, x, y, width, height)

Arguments

groblist

A grob or a list of grobs to draw.

x

A numeric vector of x positions for each grob.

y

A numeric vector of y positions for each grob.

width

A numeric vector of widths for each grob.

height

A numeric vector of heights for each grob.

Value

No return value, called for side effects (drawing grobs).

Return the first part of a colors object

Description

Returns the first part of a colors object, similar to head() for data frames.

Usage

## S3 method for class 'colors'
head(x, n = 6L, ...)

Arguments

x

A colors object (data frame with color information).

n

Number of rows to return. Default is 6.

...

Additional arguments passed to head().

Value

A colors object with the first n rows.

Examples

head(get_colors())

head(get_colors(), n = 10)

Make a long data frame for sankey plot

Description

Prepares a 'wide' data frame into a format that 'geom_sankey' or 'geom_alluvial' understands. Useful to show flows between dimensions in dataset.

Usage

make_long(.df, ..., value = NULL)

Arguments

.df

a data frame

...

unquoted columnnames of df that you want to include in the plot.

value

if each row have a weight this weight could be kept by providing column name of weight.

Value

a longer data frame

Estimate the fuzzifier parameter m

Description

Estimate the fuzzifier parameter m for fuzzy clustering based on the data dimensions.

Usage

mestimate(data)

Arguments

data

A matrix or data frame.

Value

The estimated fuzzifier parameter m.

Color palettes collected

Description

This function creates a color palette for a given vector of values.

Usage

palette_colors(
  x,
  n = 100,
  palette = "Paired",
  palcolor = NULL,
  type = c("auto", "discrete", "continuous"),
  matched = FALSE,
  reverse = FALSE,
  NA_keep = FALSE,
  NA_color = "grey80"
)

Arguments

x

A vector of character/factor or numeric values. If missing, numeric values 1:n will be used as x.

n

The number of colors to return for numeric values.

palette

Palette name. All available palette names can be queried with show_palettes.

palcolor

Custom colors used to create a color palette.

type

Type of x. Can be one of "auto", "discrete" or "continuous". The default is "auto", which automatically detects if x is a numeric value.

matched

Whether to return a color vector of the same length as x. Default is FALSE.

reverse

Whether to invert the colors. Default is FALSE.

NA_keep

Whether to keep the color assignment to NA in x. Default is FALSE.

NA_color

Color assigned to NA if NA_keep is TRUE. Default is "grey80".

Value

A character vector of color codes (hexadecimal format) corresponding to the input values x. The length and structure depend on the matched parameter.

See Also

show_palettes, palette_list

Examples

x <- c(1:3, NA, 3:5)
(pal1 <- palette_colors(
  x,
  palette = "Spectral"
))
(pal2 <- palette_colors(
  x,
  palcolor = c("red", "white", "blue")
))
(pal3 <- palette_colors(
  x,
  palette = "Spectral",
  n = 10
))
(pal4 <- palette_colors(
  x,
  palette = "Spectral",
  n = 10,
  reverse = TRUE
))
(pal5 <- palette_colors(
  x,
  palette = "Spectral",
  matched = TRUE
))
(pal6 <- palette_colors(
  x,
  palette = "Spectral",
  matched = TRUE,
  NA_keep = TRUE
))
show_palettes(
  list(pal1, pal2, pal3, pal4, pal5, pal6)
)

# Use Chinese color palettes
palette_colors(
  x = letters[1:5],
  palette = "ChineseRed",
  type = "discrete"
)
palette_colors(
  x = letters[1:5],
  palette = "Chinese",
  type = "discrete"
)

all_palettes <- show_palettes(return_palettes = TRUE)
names(all_palettes)

A list of palettes for use in data visualization

Description

A list of palettes for use in data visualization

Set the panel width/height of a plot to a fixed value

Description

The ggplot object, when stored, can only specify the height and width of the entire plot, not the panel. The latter is obviously more important to control the final result of a plot. This function can set the panel width/height of plot to a fixed value and rasterize it.

Usage

panel_fix(
  x = NULL,
  panel_index = NULL,
  respect = NULL,
  width = NULL,
  height = NULL,
  margin = 1,
  padding = 0,
  units = "in",
  raster = FALSE,
  dpi = 300,
  return_grob = FALSE,
  bg_color = "white",
  save = NULL,
  verbose = FALSE,
  ...
)

panel_fix_overall(
  x,
  panel_index = NULL,
  respect = NULL,
  width = NULL,
  height = NULL,
  margin = 1,
  units = "in",
  raster = FALSE,
  dpi = 300,
  return_grob = FALSE,
  bg_color = "white",
  save = NULL,
  verbose = TRUE
)

Arguments

x

A ggplot object, a grob object, or a combined plot made by patchwork or cowplot package.

panel_index

Specify the panel to be fixed. If NULL, will fix all panels.

respect

Whether row heights and column widths should respect each other.

width

The desired width of the fixed panels.

height

The desired height of the fixed panels.

margin

The margin to add around each panel, in inches. Default is 1.

padding

The padding to add around each panel, in inches. Default is 0.

units

The units in which height, width and margin are given. Can be "mm", "cm", "in", etc. See grid::unit.

raster

Whether to rasterize the panel.

dpi

Plot resolution.

return_grob

Whether to return a grob object instead of a wrapped patchwork object. Default is FALSE.

bg_color

The background color of the plot.

save

NULL or the file name used to save the plot.

verbose

Whether to print the message. Default is TRUE.

...

Additional arguments passed to other functions.

Value

If return_grob is TRUE, returns a gtable object. Otherwise, returns a patchwork object with fixed panel sizes. The returned object has a size attribute containing width, height, and units.

Examples

library(ggplot2)
p <- ggplot(
  data = mtcars, aes(x = mpg, y = wt, colour = cyl)
) +
  geom_point() +
  facet_wrap(~gear, nrow = 2)
# fix the size of panel
panel_fix(
  p,
  width = 5,
  height = 3,
  units = "cm"
)
# rasterize the panel
panel_fix(
  p,
  width = 5,
  height = 3,
  units = "cm",
  raster = TRUE,
  dpi = 90
)

# `panel_fix` will build and render the plot when input a ggplot object.
# so after `panel_fix`, the size of the object will be changed.
object.size(p)
object.size(
  panel_fix(
    p,
    width = 5,
    height = 3,
    units = "cm"
  )
)

Convert a patchwork object to a grob

Description

Convert a patchwork object to a gtable grob by processing annotations and building the patchwork layout.

Usage

patchwork_grob(x, ...)

Arguments

x

A patchwork object.

...

Additional arguments passed to other functions.

Value

A gtable object.

Print ChineseColors object

Description

Print ChineseColors object

Usage

## S3 method for class 'ChineseColors'
print(x, ...)

Arguments

x

A ChineseColors object.

...

Additional arguments.

Value

Details of the ChineseColors object.

Print colors object

Description

Print colors object

Usage

## S3 method for class 'colors'
print(x, ...)

Arguments

x

A colors object (data frame with color information).

...

Additional arguments passed to print.

Value

Details of the colors objec.

Description

Print logo

Usage

## S3 method for class 'thisplot_logo'
print(x, ...)

Arguments

x

Input information.

...

Other parameters.

Value

Print the ASCII logo

Shorten and offset the segment

Description

This function takes a data frame representing segments in a plot and shortens and offsets them based on the provided arguments.

Usage

segements_df(data, shorten_start, shorten_end, offset)

Arguments

data

A data frame containing the segments. It should have columns 'x', 'y', 'xend', and 'yend' representing the start and end points of each segment.

shorten_start

The amount to shorten the start of each segment by.

shorten_end

The amount to shorten the end of each segment by.

offset

The amount to offset each segment by.

Value

The modified data frame with the shortened and offset segments.

Examples

library(ggplot2)
temp_nodes <- data.frame(
  "x" = c(10, 40),
  "y" = c(10, 30)
)
data <- data.frame(
  "x" = c(10, 40),
  "y" = c(10, 30),
  "xend" = c(40, 10),
  "yend" = c(30, 10)
)

ggplot(temp_nodes, aes(x = x, y = y)) +
  geom_point(size = 12) +
  xlim(0, 50) +
  ylim(0, 50) +
  geom_segment(
    data = data,
    aes(x = x, xend = xend, y = y, yend = yend)
  )

ggplot(temp_nodes, aes(x = x, y = y)) +
  geom_point(size = 12) +
  xlim(0, 50) +
  ylim(0, 50) +
  geom_segment(
    data = segements_df(
      data,
      shorten_start = 2,
      shorten_end = 3,
      offset = 1
    ),
    aes(x = x, xend = xend, y = y, yend = yend)
  )

Show the color palettes

Description

This function displays color palettes using ggplot2.

Usage

show_palettes(
  palettes = NULL,
  type = c("discrete", "continuous"),
  index = NULL,
  palette_names = NULL,
  return_names = TRUE,
  return_palettes = FALSE
)

Arguments

palettes

A list of color palettes. Default is NULL.

type

The type of palettes to include. Default is "discrete".

index

The indices of the palettes to include. Default is NULL.

palette_names

The names of the palettes to include. Default is NULL.

return_names

Whether to return the names of the selected palettes. Default is TRUE.

return_palettes

Whether to return the colors of selected palettes. Default is FALSE.

Value

If return_palettes is TRUE, returns a list of color palettes. If return_names is TRUE (default), returns a character vector of palette names. Otherwise, returns NULL (called for side effects to display the plot).

See Also

palette_colors, palette_list

Examples

show_palettes(
  palettes = list(
    c("red", "blue", "green"),
    c("yellow", "purple", "orange")
  )
)
all_palettes <- show_palettes(return_palettes = TRUE)
names(all_palettes)
all_palettes[["simspec"]]
show_palettes(index = 1:10)
show_palettes(
  type = "discrete",
  index = 1:10
)
show_palettes(
  type = "continuous",
  index = 1:10
)
show_palettes(
  palette_names = c(
    "Paired", "nejm", "simspec", "Spectral", "jet", "Chinese"
  ),
  return_palettes = TRUE
)
# Include Chinese palettes via prefix
show_palettes(
  palette_names = c("ChineseRed", "ChineseBlue"),
  return_palettes = TRUE
)

Simple random color selection

Description

Randomly select a specified number of colors from ChineseColors or other palettes.

Usage

simple_colors(n = 10, palette = NULL)

Arguments

n

The number of colors to return. Default is 10.

palette

The name of the palette to use. If NULL (default), colors will be selected from ChineseColors. Otherwise, colors will be selected from the specified palette. Available palette names can be queried with show_palettes.

Value

A character vector of hexadecimal color codes.

Examples

simple_colors()

show_palettes(simple_colors(n = 5))

# Get colors from a specific palette
simple_colors(n = 10, palette = "Paired")
simple_colors(n = 10, palette = "ChineseBlue")
simple_colors(n = 10, palette = "Spectral")

Slim unused data in the plot

Description

Remove unused columns from the data in a ggplot or patchwork object. This function keeps only the columns that are actually used in the plot (e.g., in mappings, aesthetics, or facets), which can significantly reduce the object size when the original data contains many unused columns.

Usage

slim_data(p)

## S3 method for class 'ggplot'
slim_data(p)

## S3 method for class 'patchwork'
slim_data(p)

Arguments

p

A ggplot object or a patchwork object.

Value

A ggplot or patchwork object with unused data columns removed.

Examples

library(ggplot2)
p <- ggplot(
  data = mtcars,
  aes(x = mpg, y = wt, colour = cyl)
) +
  geom_point()
object.size(p)
colnames(p$data)

p_slim <- slim_data(p)
object.size(p_slim)
colnames(p_slim$data)

Standardize data by rows

Description

Standardize each row of a data matrix by subtracting the mean and dividing by the standard deviation.

Usage

standardise(data)

Arguments

data

A matrix or data frame to standardize.

Value

The standardized data with the same structure as input.

Blank theme

Description

This function creates a theme with all elements blank except for axis lines and labels. It can optionally add coordinate axes in the plot.

Usage

theme_blank(
  add_coord = TRUE,
  xlen_npc = 0.15,
  ylen_npc = 0.15,
  xlab = "",
  ylab = "",
  lab_size = 12,
  ...
)

Arguments

add_coord

Whether to add coordinate arrows. Default is TRUE.

xlen_npc

The length of the x-axis arrow in "npc".

ylen_npc

The length of the y-axis arrow in "npc".

xlab

The label of the x-axis.

ylab

The label of the y-axis.

lab_size

The size of the axis labels.

...

Arguments passed to the ggplot2::theme.

Value

A list containing ggplot2 theme objects and annotation objects. If add_coord is TRUE, returns a list with coordinate arrows; otherwise returns a list with theme only.

Examples

library(ggplot2)
p <- ggplot(mtcars, aes(x = wt, y = mpg, colour = factor(cyl))) +
  geom_point()
p + theme_blank()
p + theme_blank(xlab = "x-axis", ylab = "y-axis", lab_size = 16)

Themes for sankey plot

Description

Minimal themes for sankey, alluvial and sankey bump plots

Usage

theme_sankey(
  base_size = 11,
  base_family = "",
  base_line_size = base_size/22,
  base_rect_size = base_size/22
)

theme_alluvial(
  base_size = 11,
  base_family = "",
  base_line_size = base_size/22,
  base_rect_size = base_size/22
)

theme_sankey_bump(
  base_size = 11,
  base_family = "",
  base_line_size = base_size/22,
  base_rect_size = base_size/22
)

Arguments

base_size

Base font size, given in pts.

base_family

Base font family.

base_line_size

Base size for line elements.

base_rect_size

Base size for rect elements.

The default theme for scop plot function.

Description

The default theme for scop plot function.

Usage

theme_this(aspect.ratio = NULL, base_size = 12, ...)

Arguments

aspect.ratio

Aspect ratio of the panel.

base_size

Base font size

...

Arguments passed to the ggplot2::theme.

Value

A ggplot2 theme object (class theme, gg).

Examples

library(ggplot2)
p <- ggplot(
  data = mtcars,
  aes(x = wt, y = mpg, colour = factor(cyl))
) +
  geom_point()
p + theme_this()

Description

The thisplot logo, using ASCII or Unicode characters Use cli::ansi_strip to get rid of the colors.

Usage

thisplot_logo(unicode = cli::is_utf8_output())

Arguments

unicode

Unicode symbols on UTF-8 platforms. Default is cli::is_utf8_output.

Value

A character vector with class thisplot_logo.

References

https://github.com/tidyverse/tidyverse/blob/main/R/logo.R

Examples

thisplot_logo()

Visualize colors in HTML widget

Description

Display a grid of color swatches with optional names or color codes.

Usage

visual_colors(colors, names = NULL, num_per_row = 30, title = NULL)

Arguments

colors

A character vector of hex color codes.

names

Optional. A character vector of names for each color. Default is NULL, which means hex color codes will be displayed. You can pass any labels (e.g., RGB values, custom names) via this parameter.

num_per_row

Number of colors per row. Default is 30.

title

Optional title for the visualization. Default is NULL.

Value

An HTML widget.

Examples

# Visualize a simple color palette
visual_colors(
  colors = c("#FF0000", "#00FF00", "#0000FF"),
  names = c("Red", "Green", "Blue")
)

visual_colors(
  colors = c("#FF0000", "#00FF00"),
  names = c("(255, 0, 0)", "(0, 255, 0)")
)

visual_colors(thisplot::palette_list$Paired)

# Use with ChineseColors
cc <- ChineseColors()
visual_colors(
  colors = cc$blue[1:60],
  title = "Chinese Blue Colors"
)