ggplot2 geoms with support for pattern fills

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)
  }