Type: Package
Title: 'ggplot2' Pattern Geoms
Version: 1.1.4
Description: Provides 'ggplot2' geoms filled with various patterns. Includes a patterned version of every 'ggplot2' geom that has a region that can be filled with a pattern. Provides a suite of 'ggplot2' aesthetics and scales for controlling pattern appearances. Supports over a dozen builtin patterns (every pattern implemented by 'gridpattern') as well as allowing custom user-defined patterns.
URL: https://github.com/trevorld/ggpattern, https://trevorldavis.com/R/ggpattern/
BugReports: https://github.com/trevorld/ggpattern/issues
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.1
Imports: cli, ggplot2 (≥ 3.5.1), glue, grid, gridpattern (≥ 1.2.2), lifecycle, rlang (≥ 1.1.3), scales, vctrs
Suggests: ambient, dplyr, gganimate, knitr (≥ 1.47), magick, mapproj, maps, png, ragg (≥ 1.2.0), readr, rmarkdown (≥ 2.27), sf (≥ 0.7-3), svglite (≥ 2.1.3), testthat (≥ 2.1.0), vdiffr (≥ 1.0.6)
VignetteBuilder: knitr, ragg, rmarkdown
Collate: 'a-geom-docs.R' 'aaa-ggplot2-compat-plyr.R' 'aaa-ggplot2-ggplot-global.R' 'aaa-ggplot2-performance.R' 'aaa-ggplot2-scale-manual.R' 'aaa-ggplot2-utilities-grid.R' 'aaa-ggplot2-utilities.R' 'geom-.R' 'geom-rect.R' 'geom-bar.R' 'geom-bin2d.R' 'geom-boxplot.R' 'geom-col.R' 'geom-crossbar.R' 'geom-ribbon.R' 'geom-density.R' 'geom-histogram.R' 'geom-polygon.R' 'geom-map.R' 'geom-sf.R' 'geom-tile.R' 'geom-violin.R' 'ggpattern-defunct.R' 'ggpattern-deprecated.R' 'ggpattern-package.R' 'pattern.R' 'polygon_df.R' 'scale-pattern-alpha.R' 'scale-pattern-auto.R' 'scale-pattern-brewer.R' 'scale-pattern-colour.R' 'scale-pattern-gradient.R' 'scale-pattern-grey.R' 'scale-pattern-hue.R' 'scale-pattern-linetype.R' 'scale-pattern-shape.R' 'scale-pattern-size.R' 'scale-pattern-viridis.R' 'scale-pattern.R' 'zxx.r' 'zzz.R'
NeedsCompilation: no
Packaged: 2025-01-28 23:05:53 UTC; trevor
Author: Mike FC [aut], Trevor L. Davis ORCID iD [aut, cre], ggplot2 authors [aut]
Maintainer: Trevor L. Davis <trevor.l.davis@gmail.com>
Repository: CRAN
Date/Publication: 2025-01-29 00:30:02 UTC

ggpattern: 'ggplot2' Pattern Geoms

Description

logo

Provides 'ggplot2' geoms filled with various patterns. Includes a patterned version of every 'ggplot2' geom that has a region that can be filled with a pattern. Provides a suite of 'ggplot2' aesthetics and scales for controlling pattern appearances. Supports over a dozen builtin patterns (every pattern implemented by 'gridpattern') as well as allowing custom user-defined patterns.

Package options

The following ggpattern options may be set globally via base::options():

ggpattern_array_funcs

Set custom “array” pattern functions.

ggpattern_geometry_funcs

Set custom “geometry” pattern functions.

ggpattern_res

Set new default raster resolution default (pixels per inch) for the pattern_res aesthetic.

ggpattern_use_R4.1_clipping

If TRUE use the grid clipping path feature introduced in R v4.1.0 else do a rasterGrob approximation of the clipped pattern.

ggpattern_use_R4.1_features

If TRUE sets the default for all the other ⁠ggpattern_use_R4.1_*⁠ options arguments to TRUE.

ggpattern_use_R4.1_gradients

If TRUE use the grid gradient feature introduced in R v4.1.0 else do a rasterGrob approximation of the gradient pattern.

ggpattern_use_R4.1_masks

If TRUE use the grid mask feature introduced in R v4.1.0. else do a rasterGrob approximation of the masked pattern.

ggpattern_use_R4.1_patterns

If TRUE use the grid pattern feature introduced in R v4.1.0. Available for use in writing custom patterns.

Note to use the R v4.1.0 features one needs R be (at least) version 4.1 and not all graphic devices support any/all these features. See https://www.stat.auckland.ac.nz/~paul/Reports/GraphicsEngine/definitions/definitions.html for more information on the R v4.1.0 grid features.

Author(s)

Maintainer: Trevor L. Davis trevor.l.davis@gmail.com (ORCID)

Authors:

See Also

Useful links:

Geom ggproto objects

Description

Geom ggproto objects that could be extended to create a new geom.

See Also

ggplot2::Geom

Create a polygon_df object from the given coordinates

Description

code using polygon_df should not assume that the first and last point within each id are the same. i.e. they may have to manulaly set a final point equal to the initial point if that is what their graphics system desires

Usage

create_polygon_df(x, y, id = 1L)

Arguments

x, y

coordinates of polygon. not necessarily closed.

id

a numeric vector used to separate locations in x,y into multiple polygons

Value

data.frame with x, y, id columns.

Examples

  df <- create_polygon_df(x = c(0, 0, 1, 1), y = c(0, 1, 1, 0))
  is_polygon_df(df)

Key glyphs for legends

Description

Each geom has an associated function that draws the key when the geom needs to be displayed in a legend. These functions are called ⁠draw_key_*()⁠, where * stands for the name of the respective key glyph. The key glyphs can be customized for individual geoms by providing a geom with the key_glyph argument (see ggplot2::layer() or examples below.)

Usage

draw_key_polygon_pattern(data, params, size, aspect_ratio = get_aspect_ratio())

draw_key_boxplot_pattern(data, params, size, aspect_ratio = get_aspect_ratio())

draw_key_crossbar_pattern(
  data,
  params,
  size,
  aspect_ratio = get_aspect_ratio()
)

Arguments

data

A single row data frame containing the scaled aesthetics to display in this key

params

A list of additional parameters supplied to the geom.

size

Width and height of key in mm.

aspect_ratio

the geom's best guess at what the aspect ratio might be.

Value

A grid grob.

Examples

  if (require("ggplot2")) {

    # 'stripe' pattern example
    df <- data.frame(level = c("a", "b", "c", 'd'), outcome = c(2.3, 1.9, 3.2, 1))
    gg <- ggplot(df) +
      geom_col_pattern(
        aes(level, outcome, pattern_fill = level),
        pattern = 'stripe',
        fill    = 'white',
        colour  = 'black',
        key_glyph = draw_key_polygon_pattern
      ) +
      theme_bw(18) +
      theme(legend.position = 'none') +
      labs(
        title    = "ggpattern::geom_col_pattern()",
        subtitle = "pattern = 'stripe'"
      )
    plot(gg)
  }

ggplot2 geoms with support for pattern fills

Description

All geoms in this package are identical to their counterparts in ggplot2 except that they can be filled with patterns.

Usage

geom_rect_pattern(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  linejoin = "mitre",
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_bar_pattern(
  mapping = NULL,
  data = NULL,
  stat = "count",
  position = "stack",
  ...,
  just = 0.5,
  width = NULL,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_bin_2d_pattern(
  mapping = NULL,
  data = NULL,
  stat = "bin2d",
  position = "identity",
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_bin2d_pattern(
  mapping = NULL,
  data = NULL,
  stat = "bin2d",
  position = "identity",
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_boxplot_pattern(
  mapping = NULL,
  data = NULL,
  stat = "boxplot",
  position = "dodge2",
  ...,
  outliers = TRUE,
  outlier.colour = NULL,
  outlier.color = NULL,
  outlier.fill = NULL,
  outlier.shape = 19,
  outlier.size = 1.5,
  outlier.stroke = 0.5,
  outlier.alpha = NULL,
  notch = FALSE,
  notchwidth = 0.5,
  staplewidth = 0,
  varwidth = FALSE,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_col_pattern(
  mapping = NULL,
  data = NULL,
  position = "stack",
  ...,
  just = 0.5,
  width = NULL,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_crossbar_pattern(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  fatten = 2.5,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_ribbon_pattern(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE,
  outline.type = "both"
)

geom_area_pattern(
  mapping = NULL,
  data = NULL,
  stat = "align",
  position = "stack",
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE,
  ...,
  outline.type = "upper"
)

geom_density_pattern(
  mapping = NULL,
  data = NULL,
  stat = "density",
  position = "identity",
  ...,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE,
  outline.type = "upper"
)

geom_histogram_pattern(
  mapping = NULL,
  data = NULL,
  stat = "bin",
  position = "stack",
  ...,
  binwidth = NULL,
  bins = NULL,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_polygon_pattern(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  rule = "evenodd",
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_map_pattern(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  ...,
  map,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_sf_pattern(
  mapping = aes(),
  data = NULL,
  stat = "sf",
  position = "identity",
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

geom_tile_pattern(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  linejoin = "mitre",
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_violin_pattern(
  mapping = NULL,
  data = NULL,
  stat = "ydensity",
  position = "dodge",
  ...,
  draw_quantiles = NULL,
  trim = TRUE,
  bounds = c(-Inf, Inf),
  scale = "area",
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

Set of aesthetic mappings created by aes(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).

stat

The statistical transformation to use on the data for this layer. When using a ⁠geom_*()⁠ function to construct a layer, the stat argument can be used the override the default coupling between geoms and stats. The stat argument accepts the following:

  • A Stat ggproto subclass, for example StatCount.

  • A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".

  • For more information and other ways to specify the stat, see the layer stat documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

  • The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.

  • A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".

  • For more information and other ways to specify the position, see the layer position documentation.

...

Other arguments passed on to layer()'s params argument. These arguments broadly fall into one of 4 categories below. Notably, further arguments to the position argument, or aesthetics that are required can not be passed through .... Unknown arguments that are not part of the 4 categories below are ignored.

  • Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.

  • When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.

  • Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.

  • The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

linejoin

Line join style (round, mitre, bevel).

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders().

just

Adjustment for column placement. Set to 0.5 by default, meaning that columns will be centered about axis breaks. Set to 0 or 1 to place columns to the left/right of axis breaks. Note that this argument may have unintended behaviour when used with alternative positions, e.g. position_dodge().

width

Bar width. By default, set to 90% of the resolution() of the data.

orientation

The orientation of the layer. The default (NA) automatically determines the orientation from the aesthetic mapping. In the rare event that this fails it can be given explicitly by setting orientation to either "x" or "y". See the Orientation section for more detail.

outliers

Whether to display (TRUE) or discard (FALSE) outliers from the plot. Hiding or discarding outliers can be useful when, for example, raw data points need to be displayed on top of the boxplot. By discarding outliers, the axis limits will adapt to the box and whiskers only, not the full data range. If outliers need to be hidden and the axes needs to show the full data range, please use outlier.shape = NA instead.

outlier.colour, outlier.color, outlier.fill, outlier.shape, outlier.size, outlier.stroke, outlier.alpha

Default aesthetics for outliers. Set to NULL to inherit from the aesthetics used for the box.

In the unlikely event you specify both US and UK spellings of colour, the US spelling will take precedence.

notch

If FALSE (default) make a standard box plot. If TRUE, make a notched box plot. Notches are used to compare groups; if the notches of two boxes do not overlap, this suggests that the medians are significantly different.

notchwidth

For a notched box plot, width of the notch relative to the body (defaults to notchwidth = 0.5).

staplewidth

The relative width of staples to the width of the box. Staples mark the ends of the whiskers with a line.

varwidth

If FALSE (default) make a standard box plot. If TRUE, boxes are drawn with widths proportional to the square-roots of the number of observations in the groups (possibly weighted, using the weight aesthetic).

fatten

A multiplicative factor used to increase the size of the middle bar in geom_crossbar() and the middle point in geom_pointrange().

outline.type

Type of the outline of the area; "both" draws both the upper and lower lines, "upper"/"lower" draws the respective lines only. "full" draws a closed polygon around the area.

binwidth

The width of the bins. Can be specified as a numeric value or as a function that calculates width from unscaled x. Here, "unscaled x" refers to the original x values in the data, before application of any scale transformation. When specifying a function along with a grouping structure, the function will be called once per group. The default is to use the number of bins in bins, covering the range of the data. You should always override this value, exploring multiple widths to find the best to illustrate the stories in your data.

The bin width of a date variable is the number of days in each time; the bin width of a time variable is the number of seconds.

bins

Number of bins. Overridden by binwidth. Defaults to 30.

rule

Either "evenodd" or "winding". If polygons with holes are being drawn (using the subgroup aesthetic) this argument defines how the hole coordinates are interpreted. See the examples in grid::pathGrob() for an explanation.

map

Data frame that contains the map coordinates. This will typically be created using fortify() on a spatial object. It must contain columns x or long, y or lat, and region or id.

draw_quantiles

If not(NULL) (default), draw horizontal lines at the given quantiles of the density estimate.

trim

If TRUE (default), trim the tails of the violins to the range of the data. If FALSE, don't trim the tails.

bounds

Known lower and upper bounds for estimated data. Default c(-Inf, Inf) means that there are no (finite) bounds. If any bound is finite, boundary effect of default density estimation will be corrected by reflecting tails outside bounds around their closest edge. Data points outside of bounds are removed with a warning.

scale

if "area" (default), all violins have the same area (before trimming the tails). If "count", areas are scaled proportionally to the number of observations. If "width", all violins have the same maximum width.

Value

A ggplot2::Geom object.

Pattern Arguments

Not all arguments apply to all patterns.

pattern

Pattern name string e.g. 'stripe' (default), 'crosshatch', 'point', 'circle', 'none'

pattern_alpha

Alpha transparency for pattern. default: 1

pattern_angle

Orientation of the pattern in degrees. default: 30

pattern_aspect_ratio

Aspect ratio adjustment.

pattern_colour

Colour used for strokes and points. default: 'black'

pattern_density

Approximate fill fraction of the pattern. Usually in range [0, 1], but can be higher. default: 0.2

pattern_filename

Image filename/URL.

pattern_fill

Fill colour (or grid::pattern()/gradient fill). default: 'grey80'

pattern_fill2

Second fill colour (or grid::pattern()/gradient fill). default: '#4169E1'

pattern_filter

(Image scaling) filter. default: 'lanczos'

pattern_frequency

Frequency. default: 0.1

pattern_gravity

Image placement. default: 'center'

pattern_grid

Pattern grid type. default: 'square'

pattern_key_scale_factor

Scale factor for pattern in legend. default: 1

pattern_linetype

Stroke linetype. default: 1

pattern_option_1

Generic user value for custom patterns.

pattern_option_2

Generic user value for custom patterns.

pattern_option_3

Generic user value for custom patterns.

pattern_option_4

Generic user value for custom patterns.

pattern_option_5

Generic user value for custom patterns.

pattern_orientation

'vertical', 'horizontal', or 'radial'. default: 'vertical'

pattern_res

Pattern resolution (pixels per inch).

pattern_rot

Rotation angle (shape within pattern). default: 0

pattern_scale

Scale. default: 1

pattern_shape

Plotting shape. default: 1

pattern_size

Stroke line width. default: 1

pattern_spacing

Spacing of the pattern as a fraction of the plot size. default: 0.05

pattern_type

Generic control option

pattern_subtype

Generic control option

pattern_xoffset

Offset the origin of the pattern. Range [0, 1]. default: 0. Use this to slightly shift the origin of the pattern. For most patterns, the user should limit the offset value to be less than the pattern spacing.

pattern_yoffset

Offset the origin of the pattern. Range [0, 1]. default: 0. Use this to slightly shift the origin of the pattern. For most patterns, the user should limit the offset value to be less than the pattern spacing.

Examples

  if (require("ggplot2")) {

    # 'stripe' pattern example
    df <- data.frame(level = c("a", "b", "c", 'd'), outcome = c(2.3, 1.9, 3.2, 1))
    gg <- ggplot(df) +
      geom_col_pattern(
        aes(level, outcome, pattern_fill = level),
        pattern = 'stripe',
        fill    = 'white',
        colour  = 'black'
      ) +
      theme_bw(18) +
      theme(legend.position = 'none') +
      labs(
        title    = "ggpattern::geom_col_pattern()",
        subtitle = "pattern = 'stripe'"
      )
    plot(gg)

    # 'pch' pattern example
    gg <- ggplot(mtcars, aes(as.factor(cyl), mpg)) +
      geom_violin_pattern(aes(fill = as.factor(cyl),
                              pattern_shape = as.factor(cyl)),
        pattern = 'pch',
        pattern_density = 0.3,
        pattern_angle = 0,
        colour  = 'black'
      ) +
      theme_bw(18) +
      theme(legend.position = 'none') +
      labs(
        title    = "ggpattern::geom_violin_pattern()",
        subtitle = "pattern = 'pch'"
      )
    plot(gg)

    # 'polygon_tiling' pattern example
    gg <- ggplot(mtcars) +
       geom_density_pattern(
         aes(
           x            = mpg,
           pattern_fill = as.factor(cyl),
           pattern_type = as.factor(cyl)
         ),
         pattern = 'polygon_tiling',
         pattern_key_scale_factor = 1.2
       ) +
       scale_pattern_type_manual(values = c("hexagonal", "rhombille",
                                  "pythagorean")) +
       theme_bw(18) +
       theme(legend.key.size = unit(2, 'cm')) +
       labs(
         title    = "ggpattern::geom_density_pattern()",
         subtitle = "pattern = 'polygon_tiling'"
       )
    plot(gg)
  }

Defunct data/functions

Description

These data/functions are Defunct in this release of ggpattern.

  1. For magick_filter_names use magick::filter_types() instead.

  2. For magick_gravity_names use magick::gravity_types() instead.

  3. For magick_pattern_intensity_names use gridpattern::names_magick_intensity.

  4. For magick_pattern_names use gridpattern::names_magick.

  5. For magick_pattern_stripe_names use gridpattern::names_magick_stripe.

  6. For placeholder_names use gridpattern::names_placeholder.

Usage

calculate_bbox_polygon_df(...)

convert_img_to_array(...)

convert_polygon_df_to_alpha_channel(...)

convert_polygon_df_to_polygon_grob(...)

convert_polygon_df_to_polygon_sf(...)

convert_polygon_sf_to_polygon_df(...)

create_gradient_img(...)

fetch_placeholder_img(...)

fill_area_with_img(...)

rotate_polygon_df(...)

Arguments

...

Ignored

Test if object is polygon_df or NULL

Description

Test if object is polygon_df or NULL

Usage

is_polygon_df(x)

Arguments

x

object

Value

TRUE if object is polygon_df or NULL

Examples

  df <- create_polygon_df(x = c(0, 0, 1, 1), y = c(0, 1, 1, 0))
  is_polygon_df(df)

Scales for continuous pattern aesthetics

Description

Scales for continuous pattern aesthetics

Usage

scale_pattern_angle_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  range = c(0, 90),
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_angle_discrete(..., range = c(0, 90))

scale_pattern_density_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  range = c(0, 0.5),
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_density_discrete(..., range = c(0, 0.5))

scale_pattern_spacing_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  range = c(0.01, 0.1),
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_spacing_discrete(..., range = c(0.01, 0.1))

scale_pattern_xoffset_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  range = c(0.01, 0.1),
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_xoffset_discrete(..., range = c(0.01, 0.1))

scale_pattern_yoffset_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  range = c(0.01, 0.1),
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_yoffset_discrete(..., range = c(0.01, 0.1))

scale_pattern_aspect_ratio_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  range = c(0.5, 2),
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_aspect_ratio_discrete(..., range = c(0.5, 2))

scale_pattern_key_scale_factor_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  range = c(0.5, 2),
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_key_scale_factor_discrete(..., range = c(0.5, 2))

scale_pattern_scale_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  range = c(0.5, 2),
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_scale_discrete(..., range = c(0.5, 2))

scale_pattern_phase_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  range = NULL,
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_phase_discrete(..., range = NULL)

scale_pattern_frequency_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  range = NULL,
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_frequency_discrete(..., range = NULL)

scale_pattern_res_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  range = NULL,
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_res_discrete(..., range = NULL)

scale_pattern_rot_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  range = c(0, 360),
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_rot_discrete(..., range = c(0, 360))

Arguments

name, breaks, labels, limits, range, trans, guide, ..., transform

See {ggplot2} documentation for more information on scales.

Value

A ggplot2::Scale object.

Examples

  if (require('ggplot2')) {

    # 'stripe' pattern example
    df <- data.frame(level = c('a', 'b', 'c', 'd'),
                     outcome = c(2.3, 1.9, 3.2, 1))
    gg <- ggplot(df) +
      geom_col_pattern(
        aes(level, outcome, pattern_fill = level,
            pattern_density = outcome),
        pattern = 'stripe',
        fill    = 'white',
        colour  = 'black'
      ) +
      theme_bw(18) +
      theme(legend.position = 'none') +
      scale_pattern_density_continuous(range = c(0.1, 0.6)) +
      labs(
        title    = 'ggpattern::geom_col_pattern()',
        subtitle = 'pattern = \'stripe\''
      )
    plot(gg)
  }

Scales for discrete pattern aesthetics

Description

Scales for discrete pattern aesthetics

Usage

scale_pattern_type_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  choices = NULL,
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_type_discrete(..., choices = NULL, guide = "legend")

scale_pattern_subtype_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  choices = NULL,
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_subtype_discrete(..., choices = NULL, guide = "legend")

scale_pattern_filename_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  choices = NULL,
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_filename_discrete(..., choices = NULL, guide = "legend")

scale_pattern_filter_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  choices = c("lanczos", "box", "spline", "cubic"),
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_filter_discrete(
  ...,
  choices = c("lanczos", "box", "spline", "cubic"),
  guide = "legend"
)

scale_pattern_gravity_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  choices = c("center", "north", "south", "east", "west", "northeast", "northwest",
    "southeast", "southwest"),
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_gravity_discrete(
  ...,
  choices = c("center", "north", "south", "east", "west", "northeast", "northwest",
    "southeast", "southwest"),
  guide = "legend"
)

scale_pattern_orientation_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  choices = c("horizontal", "vertical", "radial"),
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_orientation_discrete(
  ...,
  choices = c("horizontal", "vertical", "radial"),
  guide = "legend"
)

scale_pattern_grid_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  choices = c("square", "hex"),
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_grid_discrete(
  ...,
  choices = c("square", "hex"),
  guide = "legend"
)

scale_pattern_units_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  choices = c("snpc", "cm", "inches"),
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_units_discrete(
  ...,
  choices = c("snpc", "cm", "inches"),
  guide = "legend"
)

scale_pattern_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  choices = c("stripe", "crosshatch", "circle"),
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity",
  na.value = "none"
)

scale_pattern_discrete(
  ...,
  choices = c("stripe", "crosshatch", "circle"),
  guide = "legend",
  na.value = "none"
)

Arguments

name, breaks, labels, limits, trans, guide, ..., transform, na.value

See {ggplot2} documentation for more information on scales.

choices

vector of values to choose from.

Value

A ggplot2::Scale object.

Examples

  if (require('ggplot2')) {
    gg <- ggplot(mtcars) +
       geom_density_pattern(
         aes(
           x            = mpg,
           pattern_fill = as.factor(cyl),
           pattern_type = as.factor(cyl)
         ),
         pattern = 'polygon_tiling',
         pattern_key_scale_factor = 1.2
       ) +
       scale_pattern_type_discrete(choices = gridpattern::names_polygon_tiling) +
       theme_bw(18) +
       theme(legend.key.size = unit(2, 'cm')) +
       labs(
         title    = 'ggpattern::geom_density_pattern()',
         subtitle = 'pattern = \'polygon_tiling\''
       )
    plot(gg)
  }

Alpha transparency scales

Description

See ggplot2::scale_alpha() for details.

Usage

scale_pattern_alpha_continuous(..., range = c(0.1, 1))

scale_pattern_alpha(..., range = c(0.1, 1))

scale_pattern_alpha_discrete(...)

scale_pattern_alpha_ordinal(..., range = c(0.1, 1))

Arguments

...

Other arguments passed on to ggplot2::continuous_scale(), ggplot2::binned_scale(), or ggplot2::discrete_scale() as appropriate, to control name, limits, breaks, labels and so forth.

range

Output range of alpha values. Must lie between 0 and 1.

Value

A ggplot2::Scale object.

Examples

  if (require("ggplot2")) {
    # 'stripe' pattern example
    df <- data.frame(level = c("a", "b", "c", 'd'), outcome = c(2.3, 1.9, 3.2, 1))
    gg <- ggplot(df) +
      geom_col_pattern(
        aes(level, outcome, pattern_fill = level, pattern_alpha = outcome),
        pattern_density = 0.6,
        pattern_size = 1.5,
        pattern = 'stripe',
        fill    = 'white',
        colour  = 'black',
        linewidth = 1.5
      ) +
      theme_bw(18) +
      theme(legend.position = 'none') +
      scale_pattern_alpha() +
      labs(
        title    = "ggpattern::geom_col_pattern()",
        subtitle = "pattern = 'stripe'"
      )
    plot(gg)
  }

Sequential, diverging and qualitative colour scales from colorbrewer.org

Description

The brewer scales provides sequential, diverging and qualitative colour schemes from ColorBrewer. These are particularly well suited to display discrete values on a map. See https://colorbrewer2.org for more information.

Usage

scale_pattern_colour_brewer(
  ...,
  type = "seq",
  palette = 1,
  direction = 1,
  aesthetics = "pattern_colour"
)

scale_pattern_fill_brewer(
  ...,
  type = "seq",
  palette = 1,
  direction = 1,
  aesthetics = "pattern_fill"
)

scale_pattern_fill2_brewer(
  ...,
  type = "seq",
  palette = 1,
  direction = 1,
  aesthetics = "pattern_fill2"
)

scale_pattern_colour_distiller(
  ...,
  type = "seq",
  palette = 1,
  direction = -1,
  values = NULL,
  space = "Lab",
  na.value = "grey50",
  guide = guide_colourbar(available_aes = "pattern_colour"),
  aesthetics = "pattern_colour"
)

scale_pattern_fill_distiller(
  ...,
  type = "seq",
  palette = 1,
  direction = -1,
  values = NULL,
  space = "Lab",
  na.value = "grey50",
  guide = guide_colourbar(available_aes = "pattern_fill"),
  aesthetics = "pattern_fill"
)

scale_pattern_fill2_distiller(
  ...,
  type = "seq",
  palette = 1,
  direction = -1,
  values = NULL,
  space = "Lab",
  na.value = "grey50",
  guide = guide_colourbar(available_aes = "pattern_fill2"),
  aesthetics = "pattern_fill2"
)

Arguments

...

Other arguments passed on to ggplot2::discrete_scale(), ggplot2::continuous_scale(), or ggplot2::binned_scale(), for brewer, distiller, and fermenter variants respectively, to control name, limits, breaks, labels and so forth.

palette

If a string, will use that named palette. If a number, will index into the list of palettes of appropriate type. The list of available palettes can found in the Palettes section.

direction, type, aesthetics, values, space, na.value, guide

See ggplot2::scale_colour_brewer for more information.

Details

The brewer scales were carefully designed and tested on discrete data. They were not designed to be extended to continuous data, but results often look good. Your mileage may vary.

Value

A ggplot2::Scale object.

Palettes

The following palettes are available for use with these scales:

Diverging

BrBG, PiYG, PRGn, PuOr, RdBu, RdGy, RdYlBu, RdYlGn, Spectral

Qualitative

Accent, Dark2, Paired, Pastel1, Pastel2, Set1, Set2, Set3

Sequential

Blues, BuGn, BuPu, GnBu, Greens, Greys, Oranges, OrRd, PuBu, PuBuGn, PuRd, Purples, RdPu, Reds, YlGn, YlGnBu, YlOrBr, YlOrRd

Modify the palette through the palette arguement.

Note

The distiller scales extend brewer to continuous scales by smoothly interpolating 7 colours from any palette to a continuous scale. The fermenter scales provide binned versions of the brewer scales.

Examples

  if (require("ggplot2")) {
    df <- data.frame(level = c("a", "b", "c", "d"),
                     outcome = c(2.3, 1.9, 3.2, 1))
    # discrete 'brewer' palette
    gg <- ggplot(df) +
      geom_col_pattern(
        aes(level, outcome, pattern_fill = level),
        pattern = 'stripe',
        fill    = 'white',
        colour  = 'black'
      ) +
      theme_bw(18) +
      scale_pattern_fill_brewer()
    plot(gg)

    # continuous 'distiller' palette
    gg <- ggplot(df) +
      geom_col_pattern(
        aes(level, outcome, pattern_fill = outcome),
        pattern = 'stripe',
        fill    = 'white',
        colour  = 'black'
      ) +
      theme_bw(18) +
      scale_pattern_fill_distiller()
    plot(gg)
  }

Continuous and binned colour scales

Description

See ggplot2::scale_colour_continuous() for more information

Usage

scale_pattern_colour_continuous(
  ...,
  type = getOption("ggplot2.continuous.colour", default = "gradient")
)

scale_pattern_fill_continuous(
  ...,
  type = getOption("ggplot2.continuous.fill", default = "gradient")
)

scale_pattern_fill2_continuous(
  ...,
  type = getOption("ggplot2.continuous.fill", default = "gradient")
)

Arguments

...

Additional parameters passed on to the scale type

type

One of "gradient" (the default) or "viridis" indicating the colour scale to use

Value

A ggplot2::Scale object.

Examples

  if (require("ggplot2")) {
    df <- data.frame(level = c("a", "b", "c", "d"),
                     outcome = c(2.3, 1.9, 3.2, 1))
    gg <- ggplot(df) +
      geom_col_pattern(
        aes(level, outcome, pattern_fill = outcome),
        pattern = 'stripe',
        fill    = 'white',
        colour  = 'black'
      ) +
      theme_bw(18) +
      scale_pattern_fill_continuous()
    plot(gg)
  }

Gradient colour scales

Description

See ggplot2::scale_colour_gradient() for more information

Usage

scale_pattern_colour_gradient(
  ...,
  low = "#132B43",
  high = "#56B1F7",
  space = "Lab",
  na.value = "grey50",
  guide = guide_colourbar(available_aes = "pattern_colour"),
  aesthetics = "pattern_colour"
)

scale_pattern_fill_gradient(
  ...,
  low = "#132B43",
  high = "#56B1F7",
  space = "Lab",
  na.value = "grey50",
  guide = guide_colourbar(available_aes = "pattern_fill"),
  aesthetics = "pattern_fill"
)

scale_pattern_fill2_gradient(
  ...,
  low = "#132B43",
  high = "#56B1F7",
  space = "Lab",
  na.value = "grey50",
  guide = guide_colourbar(available_aes = "pattern_fill2"),
  aesthetics = "pattern_fill2"
)

scale_pattern_colour_gradient2(
  ...,
  low = muted("red"),
  mid = "white",
  high = muted("blue"),
  midpoint = 0,
  space = "Lab",
  na.value = "grey50",
  guide = guide_colourbar(available_aes = "pattern_colour"),
  aesthetics = "pattern_colour"
)

scale_pattern_fill_gradient2(
  ...,
  low = muted("red"),
  mid = "white",
  high = muted("blue"),
  midpoint = 0,
  space = "Lab",
  na.value = "grey50",
  guide = guide_colourbar(available_aes = "pattern_fill"),
  aesthetics = "pattern_fill"
)

scale_pattern_fill2_gradient2(
  ...,
  low = muted("red"),
  mid = "white",
  high = muted("blue"),
  midpoint = 0,
  space = "Lab",
  na.value = "grey50",
  guide = guide_colourbar(available_aes = "pattern_fill2"),
  aesthetics = "pattern_fill2"
)

scale_pattern_colour_gradientn(
  ...,
  colours,
  values = NULL,
  space = "Lab",
  na.value = "grey50",
  guide = guide_colourbar(available_aes = "pattern_colour"),
  aesthetics = "pattern_colour",
  colors
)

scale_pattern_fill_gradientn(
  ...,
  colours,
  values = NULL,
  space = "Lab",
  na.value = "grey50",
  guide = guide_colourbar(available_aes = "pattern_fill"),
  aesthetics = "pattern_fill",
  colors
)

scale_pattern_fill2_gradientn(
  ...,
  colours,
  values = NULL,
  space = "Lab",
  na.value = "grey50",
  guide = guide_colourbar(available_aes = "pattern_fill2"),
  aesthetics = "pattern_fill2",
  colors
)

Arguments

low, high

Colours for low and high ends of the gradient.

space, ..., na.value, aesthetics

See scales::seq_gradient_pal, scale_colour_hue, ggplot2::continuous_scale

guide

Type of legend. Use "colourbar" for continuous colour bar, or "legend" for discrete colour legend.

mid

colour for mid point

midpoint

The midpoint (in data value) of the diverging scale. Defaults to 0.

colours, colors

Vector of colours to use for n-colour gradient.

values

if colours should not be evenly positioned along the gradient this vector gives the position (between 0 and 1) for each colour in the colours vector. See rescale() for a convenience function to map an arbitrary range to between 0 and 1.

Details

⁠scale_*_gradient⁠ creates a two colour gradient (low-high), ⁠scale_*_gradient2⁠ creates a diverging colour gradient (low-mid-high), ⁠scale_*_gradientn⁠ creates a n-colour gradient.

Value

A ggplot2::Scale object.

Examples

  if (require("ggplot2")) {
    df <- data.frame(level = c("a", "b", "c", "d"),
                     outcome = c(2.3, 1.9, 3.2, 1))
    gg <- ggplot(df) +
      geom_col_pattern(
        aes(level, outcome, pattern_fill = outcome),
        pattern = 'stripe',
        fill    = 'white',
        colour  = 'black'
      ) +
      theme_bw(18) +
      scale_pattern_fill_gradient()
    plot(gg)
  }

Sequential grey colour scales

Description

Based on gray.colors(). This is black and white equivalent of scale_pattern_colour_gradient().

Usage

scale_pattern_colour_grey(
  ...,
  start = 0.2,
  end = 0.8,
  na.value = "red",
  aesthetics = "pattern_colour"
)

scale_pattern_fill_grey(
  ...,
  start = 0.2,
  end = 0.8,
  na.value = "red",
  aesthetics = "pattern_fill"
)

scale_pattern_fill2_grey(
  ...,
  start = 0.2,
  end = 0.8,
  na.value = "red",
  aesthetics = "pattern_fill2"
)

Arguments

..., start, end, na.value, aesthetics

See ggplot2::scale_colour_grey for more information

Value

A ggplot2::Scale object.

Examples

  if (require("ggplot2")) {
    df <- data.frame(level = c("a", "b", "c", "d"),
                     outcome = c(2.3, 1.9, 3.2, 1))
    gg <- ggplot(df) +
      geom_col_pattern(
        aes(level, outcome, pattern_fill = level),
        pattern = 'stripe',
        fill    = 'white',
        colour  = 'black'
      ) +
      theme_bw(18) +
      scale_pattern_fill_grey()
    plot(gg)
  }

Evenly spaced colours for discrete data

Description

This is the default colour scale for categorical variables. It maps each level to an evenly spaced hue on the colour wheel. It does not generate colour-blind safe palettes.

Usage

scale_pattern_colour_hue(
  ...,
  h = c(0, 360) + 15,
  c = 100,
  l = 65,
  h.start = 0,
  direction = 1,
  na.value = "grey50",
  aesthetics = "pattern_colour"
)

scale_pattern_fill_hue(
  ...,
  h = c(0, 360) + 15,
  c = 100,
  l = 65,
  h.start = 0,
  direction = 1,
  na.value = "grey50",
  aesthetics = "pattern_fill"
)

scale_pattern_fill2_hue(
  ...,
  h = c(0, 360) + 15,
  c = 100,
  l = 65,
  h.start = 0,
  direction = 1,
  na.value = "grey50",
  aesthetics = "pattern_fill2"
)

Arguments

h, c, l, h.start, direction, ...

See ggplot2::scale_colour_hue

na.value

Colour to use for missing values

aesthetics

Character string or vector of character strings listing the name(s) of the aesthetic(s) that this scale works with. This can be useful, for example, to apply colour settings to the colour and fill aesthetics at the same time, via aesthetics = c("colour", "fill").

Value

A ggplot2::Scale object.

Examples

  if (require("ggplot2")) {
    df <- data.frame(level = c("a", "b", "c", "d"),
                     outcome = c(2.3, 1.9, 3.2, 1))
    gg <- ggplot(df) +
      geom_col_pattern(
        aes(level, outcome, pattern_fill = level),
        pattern = 'stripe',
        fill    = 'white',
        colour  = 'black'
      ) +
      theme_bw(18) +
      scale_pattern_fill_hue()
    plot(gg)
  }

Viridis colour scales from viridisLite

Description

The viridis scales provide colour maps that are perceptually uniform in both colour and black-and-white. They are also designed to be perceived by viewers with common forms of colour blindness. See also https://bids.github.io/colormap/.

Usage

scale_pattern_colour_viridis_d(
  ...,
  alpha = 1,
  begin = 0,
  end = 1,
  direction = 1,
  option = "D",
  aesthetics = "pattern_colour"
)

scale_pattern_fill_viridis_d(
  ...,
  alpha = 1,
  begin = 0,
  end = 1,
  direction = 1,
  option = "D",
  aesthetics = "pattern_fill"
)

scale_pattern_fill2_viridis_d(
  ...,
  alpha = 1,
  begin = 0,
  end = 1,
  direction = 1,
  option = "D",
  aesthetics = "pattern_fill2"
)

scale_pattern_colour_viridis_c(
  ...,
  alpha = 1,
  begin = 0,
  end = 1,
  direction = 1,
  option = "D",
  values = NULL,
  space = "Lab",
  na.value = "grey50",
  guide = guide_colourbar(available_aes = "pattern_colour"),
  aesthetics = "pattern_colour"
)

scale_pattern_fill_viridis_c(
  ...,
  alpha = 1,
  begin = 0,
  end = 1,
  direction = 1,
  option = "D",
  values = NULL,
  space = "Lab",
  na.value = "grey50",
  guide = guide_colourbar(available_aes = "pattern_fill"),
  aesthetics = "pattern_fill"
)

scale_pattern_fill2_viridis_c(
  ...,
  alpha = 1,
  begin = 0,
  end = 1,
  direction = 1,
  option = "D",
  values = NULL,
  space = "Lab",
  na.value = "grey50",
  guide = guide_colourbar(available_aes = "pattern_fill2"),
  aesthetics = "pattern_fill2"
)

Arguments

...

Other arguments passed on to ggplot2::discrete_scale(), ggplot2::continuous_scale(), or ggplot2::binned_scale() to control name, limits, breaks, labels and so forth.

begin, end, alpha, direction, option, values, space, na.value, guide

See ggplot2::scale_colour_viridis_d() for more information

aesthetics

Character string or vector of character strings listing the name(s) of the aesthetic(s) that this scale works with. This can be useful, for example, to apply colour settings to the colour and fill aesthetics at the same time, via aesthetics = c("colour", "fill").

Value

A ggplot2::Scale object.

Examples

  if (require("ggplot2")) {
    df <- data.frame(level = c("a", "b", "c", "d"),
                     outcome = c(2.3, 1.9, 3.2, 1))
    # discrete 'viridis' palette
    gg <- ggplot(df) +
      geom_col_pattern(
        aes(level, outcome, pattern_fill = level),
        pattern = 'stripe',
        fill    = 'white',
        colour  = 'black'
      ) +
      theme_bw(18) +
      scale_pattern_fill_viridis_d()
    plot(gg)

    # continuous 'viridis' palette
    gg <- ggplot(df) +
      geom_col_pattern(
        aes(level, outcome, pattern_fill = outcome),
        pattern = 'stripe',
        fill    = 'white',
        colour  = 'black'
      ) +
      theme_bw(18) +
      scale_pattern_fill_viridis_c()
    plot(gg)
  }

Use values without scaling

Description

Use values without scaling

Usage

scale_pattern_type_identity(..., guide = "none")

scale_pattern_subtype_identity(..., guide = "none")

scale_pattern_angle_identity(..., guide = "none")

scale_pattern_density_identity(..., guide = "none")

scale_pattern_spacing_identity(..., guide = "none")

scale_pattern_xoffset_identity(..., guide = "none")

scale_pattern_yoffset_identity(..., guide = "none")

scale_pattern_alpha_identity(..., guide = "none")

scale_pattern_linetype_identity(..., guide = "none")

scale_pattern_size_identity(..., guide = "none")

scale_pattern_shape_identity(..., guide = "none")

scale_pattern_colour_identity(..., guide = "none")

scale_pattern_fill_identity(..., guide = "none")

scale_pattern_fill2_identity(..., guide = "none")

scale_pattern_aspect_ratio_identity(..., guide = "none")

scale_pattern_key_scale_factor_identity(..., guide = "none")

scale_pattern_filename_identity(..., guide = "none")

scale_pattern_filter_identity(..., guide = "none")

scale_pattern_gravity_identity(..., guide = "none")

scale_pattern_scale_identity(..., guide = "none")

scale_pattern_orientation_identity(..., guide = "none")

scale_pattern_phase_identity(..., guide = "none")

scale_pattern_frequency_identity(..., guide = "none")

scale_pattern_grid_identity(..., guide = "none")

scale_pattern_res_identity(..., guide = "none")

scale_pattern_rot_identity(..., guide = "none")

scale_pattern_units_identity(..., guide = "none")

scale_pattern_identity(..., guide = "none")

Arguments

..., guide

See ggplot2 for documentation on identity scales. e.g. ggplot2::scale_alpha_identity()

Value

A ggplot2::Scale object.

Examples

  if (require('ggplot2')) {
    df <- data.frame(outcome = c(2.3, 1.9, 3.2, 1),
                     pattern_type = sample(gridpattern::names_polygon_tiling, 4))
    gg <- ggplot(df) +
      geom_col_pattern(
        aes(pattern_type, outcome, pattern_fill = pattern_type,
            pattern_type = pattern_type),
        colour  = 'black',
        pattern = 'polygon_tiling',
        pattern_key_scale_factor = 1.2
       ) +
       scale_pattern_type_identity() +
       theme_bw(18) +
       theme(legend.position = 'none') +
       labs(
         x        = 'level',
         title    = 'ggpattern::geom_col_pattern()',
         subtitle = 'pattern = \'polygon_tiling\''
       )
    plot(gg)
  }

Scale for line patterns

Description

Default line types based on a set supplied by Richard Pearson, University of Manchester. Continuous values can not be mapped to line types.

Usage

scale_pattern_linetype(..., na.value = "blank")

scale_pattern_linetype_continuous(...)

scale_pattern_linetype_discrete(..., na.value = "blank")

Arguments

...

see ggplot2::scale_linetype() for more information

na.value

The linetype to use for NA values.

Value

A ggplot2::Scale object.

Examples

  if (require("ggplot2")) {
    # 'stripe' pattern example
    df <- data.frame(level = c("a", "b", "c", 'd'), outcome = c(2.3, 1.9, 3.2, 1))
    gg <- ggplot(df) +
      geom_col_pattern(
        aes(level, outcome, pattern_fill = level, pattern_linetype = level),
        pattern_density = 0.6,
        pattern_size = 1.5,
        pattern = 'stripe',
        fill    = 'white',
        colour  = 'black',
        linewidth = 1.5
      ) +
      theme_bw(18) +
      theme(legend.position = 'none') +
      scale_pattern_linetype() +
      labs(
        title    = "ggpattern::geom_col_pattern()",
        subtitle = "pattern = 'stripe'"
      )
    plot(gg)
  }

Create your own discrete scale

Description

Create your own discrete scale

Usage

scale_pattern_type_manual(..., values, breaks = waiver())

scale_pattern_subtype_manual(..., values, breaks = waiver())

scale_pattern_angle_manual(..., values, breaks = waiver())

scale_pattern_density_manual(..., values, breaks = waiver())

scale_pattern_spacing_manual(..., values, breaks = waiver())

scale_pattern_xoffset_manual(..., values, breaks = waiver())

scale_pattern_yoffset_manual(..., values, breaks = waiver())

scale_pattern_alpha_manual(..., values, breaks = waiver())

scale_pattern_linetype_manual(..., values, breaks = waiver())

scale_pattern_size_manual(..., values, breaks = waiver())

scale_pattern_shape_manual(..., values, breaks = waiver())

scale_pattern_colour_manual(..., values, breaks = waiver())

scale_pattern_fill_manual(..., values, breaks = waiver())

scale_pattern_fill2_manual(..., values, breaks = waiver())

scale_pattern_aspect_ratio_manual(..., values, breaks = waiver())

scale_pattern_key_scale_factor_manual(..., values, breaks = waiver())

scale_pattern_filename_manual(..., values, breaks = waiver())

scale_pattern_filter_manual(..., values, breaks = waiver())

scale_pattern_gravity_manual(..., values, breaks = waiver())

scale_pattern_scale_manual(..., values, breaks = waiver())

scale_pattern_orientation_manual(..., values, breaks = waiver())

scale_pattern_phase_manual(..., values, breaks = waiver())

scale_pattern_frequency_manual(..., values, breaks = waiver())

scale_pattern_grid_manual(..., values, breaks = waiver())

scale_pattern_res_manual(..., values, breaks = waiver())

scale_pattern_rot_manual(..., values, breaks = waiver())

scale_pattern_units_manual(..., values, breaks = waiver())

scale_pattern_manual(..., values, breaks = waiver(), na.value = "none")

Arguments

..., values, breaks, na.value

See ggplot2 for documentation on manual scales. e.g. ggplot2::scale_colour_manual()

Value

A ggplot2::Scale object.

Examples

  if (require('ggplot2')) {
    gg <- ggplot(mtcars) +
       geom_density_pattern(
         aes(
           x            = mpg,
           pattern_fill = as.factor(cyl),
           pattern_type = as.factor(cyl)
         ),
         pattern = 'polygon_tiling',
         pattern_key_scale_factor = 1.2
       ) +
       scale_pattern_type_manual(values = c('hexagonal', 'rhombille',
                                  'pythagorean')) +
       theme_bw(18) +
       theme(legend.key.size = unit(2, 'cm')) +
       labs(
         title    = 'ggpattern::geom_density_pattern()',
         subtitle = 'pattern = \'polygon_tiling\''
       )
    plot(gg)
  }

Scales for shapes, aka glyphs

Description

scale_pattern_shape maps discrete variables to six easily discernible shapes. If you have more than six levels, you will get a warning message, and the seventh and subsequence levels will not appear on the plot. Use scale_pattern_shape_manual() to supply your own values. You can not map a continuous variable to shape unless scale_pattern_shape_binned() is used. Still, as shape has no inherent order, this use is not advised..

Usage

scale_pattern_shape(..., solid = TRUE)

scale_pattern_shape_discrete(..., solid = TRUE)

scale_pattern_shape_ordinal(...)

scale_pattern_shape_continuous(...)

Arguments

...

other arguments passed to discrete_scale()

solid

Should the shapes be solid, TRUE, or hollow, FALSE?

Details

Scales for area or radius

Value

A ggplot2::Scale object.

Examples

  if (require("ggplot2")) {
    # 'pch' pattern example
    gg <- ggplot(mtcars, aes(as.factor(cyl), mpg)) +
      geom_violin_pattern(aes(fill = as.factor(cyl),
                              pattern_shape = as.factor(cyl)),
        pattern = 'pch',
        pattern_density = 0.3,
        pattern_angle = 0,
        colour  = 'black'
      ) +
      theme_bw(18) +
      theme(legend.position = 'none') +
      scale_pattern_shape() +
      labs(
        title    = "ggpattern::geom_violin_pattern()",
        subtitle = "pattern = 'pch'"
      )
    plot(gg)
  }

Scales for area or radius

Description

Scales for area or radius

Usage

scale_pattern_size_continuous(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  range = c(1, 6),
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

scale_pattern_size(
  name = waiver(),
  breaks = waiver(),
  labels = waiver(),
  limits = NULL,
  range = c(1, 6),
  trans = deprecated(),
  guide = "legend",
  ...,
  transform = "identity"
)

Arguments

name, breaks, labels, limits, trans, guide, ..., transform

See ggplot2::scale_size() for more information

range

a numeric vector of length 2 that specifies the minimum and maximum size of the plotting symbol after transformation.

Value

A ggplot2::Scale object.

Examples

  if (require("ggplot2")) {
    # 'circle' pattern example
    df <- data.frame(level = c("a", "b", "c", 'd'), outcome = c(2.3, 1.9, 3.2, 1))
    gg <- ggplot(df) +
      geom_col_pattern(
        aes(level, outcome, pattern_fill = level,
            linewidth = outcome, pattern_size = outcome),
        pattern_density = 0.4,
        pattern_spacing = 0.3,
        pattern = 'circle',
        fill    = 'white',
        colour  = 'black'
      ) +
      theme_bw(18) +
      theme(legend.position = 'none') +
      scale_pattern_size() +
      labs(
        title    = "ggpattern::geom_col_pattern()",
        subtitle = "pattern = 'circle'"
      )
    plot(gg)
  }