Package 'ggpattern'

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 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)
  }

---

Geom ggproto objects

Description

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

See Also

ggplot2::Geom

---

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 continuous_scale(), binned_scale, or 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',
        size = 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 discrete_scale(), continuous_scale(), or 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 discrete_scale(), continuous_scale(), or 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',
        size = 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)
  }

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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,
            size = 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)
  }

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