Patterns ‘stripe’, ‘wave’, ‘crosshatch’, ‘weave’ - Parameters and Examples

suppressPackageStartupMessages({
  library(ggplot2)
  library(ggpattern)
})

Introduction to the ‘stripe’, ‘wave’, ‘crosshatch’, and ‘weave’ patterns

Pattern Parameters

aesthetic description default possible values
pattern_colour Stroke colour ‘grey20’ colour
pattern_fill Fill colour ‘grey80’ colour
pattern_angle Rotation angle 30 angle in degrees
pattern_density Approx. fraction of area the pattern fills 0.2 value in range [0, 1] (fraction)
pattern_spacing Spacing between repetitions of pattern 0.05 value in pattern_units grid units
pattern_xoffset Shift pattern along x axis 0 value in pattern_units grid units
pattern_yoffset Shift pattern along y axis 0 value in pattern_units grid units
pattern_units Pattern grid unit ‘snpc’ grid::unit() unit i.e. ‘snpc’, ‘cm’, and ‘inches’
pattern_alpha Alpha NA value in range [0, 1] or NA
pattern_linetype Stroke linetype 1 linetype
pattern_size Stroke linewidth 1 linewidth
pattern_type Pattern type NA See wave and weave pattern documentation
pattern_subtype Pattern subtype NA See weave pattern documentation
pattern_frequency Frequency 0.1 Frequency of waves in ‘wave’ pattern

There are also a number of parameters for extra control of legend sizing and aspect ratio adjustments. See the ‘Pattern Parameters - Common’ for more information.

Data

Standard data for all the example plots

df <- data.frame(trt = c("a", "b", "c"), outcome = c(2.3, 1.9, 3.2))
df
#>   trt outcome
#> 1   a     2.3
#> 2   b     1.9
#> 3   c     3.2

Vanilla ggplot2

ggplot(df, aes(trt, outcome)) +
  geom_col(aes(fill=trt),colour='black') +
  theme_bw() +
  labs(title = "Plain ggplot2")

Use the {ggpattern} geom

  • Use ggpattern::geom_col_pattern() instead of ggplot2::geom_col().
  • Set pattern = 'stripe'
  • Default legends in ggplot2 are usually too small to show off an example of the pattern, so it will usually be necessary to increase the key size.
ggplot(df, aes(trt, outcome)) +
  geom_col_pattern(aes(fill=trt),colour='black',
                   pattern='stripe') +
  theme_bw() +
  labs(title = "ggpattern") +
  theme(legend.key.size = unit(1.5, 'cm'))

Mixing patterns

  • Often we’ll want to mix patterns.
    To get the legend right we’ll often want to set them with a pattern scale function like ‘pattern_scale_manual()’ instead of simply setting them with the ‘pattern’ aesthetic.
  • Here we’ll use the ‘stripe’ pattern and ‘wave’ pattern.
  • The ‘wave’ pattern supports two subtypes: ‘triangle’ waves (default) have a zig-zag appearance whereas ‘sine’ waves have a curvy appearance.
ggplot(df, aes(trt, outcome)) +
  geom_col_pattern(aes(fill=trt, pattern=trt, pattern_type=trt),colour='black') + 
  theme_bw() +
  labs(title = "Use 'stripe' and 'wave' patterns") + 
  theme(legend.key.size = unit(1.5, 'cm')) +
  scale_pattern_manual(values=c('stripe', 'wave', 'wave')) +
  scale_pattern_type_manual(values=c(NA, 'triangle', 'sine'))

The Density Aesthetic

The aesthetic pattern_density roughly corresponds to the fraction of the filled area which should be covered by the pattern.

In the following plot the density of striping is increased to 50% of the fill area.

ggplot(df, aes(trt, outcome)) +
  geom_col_pattern(
    aes(fill=trt, pattern=trt),
    colour          = 'black', 
    pattern_density = 0.5
  ) +
  theme_bw() +
  labs(title = "Fixed density of 0.5 (50% of the fill area)") + 
  scale_pattern_manual(values=c('stripe', 'crosshatch', 'weave')) +
  theme(legend.key.size = unit(1.5, 'cm'))

Weave types

The ‘weave’ pattern supports a rich set of weave types and subtypes including irregular ‘matt’, ‘twill’ (including ‘herringbone’ and ‘zigzag’ variations), and ‘satin’ weaves . See the weave pattern documentation for more information.

ggplot(df, aes(trt, outcome)) +
  geom_col_pattern(
    aes(pattern_fill2=trt, pattern_type=trt),
    pattern = 'weave',
    colour          = 'black', 
    pattern_density = 1.0,
    pattern_fill = 'grey',
    pattern_key_scale_factor = 0.5,
  ) +
  theme_bw() +
  labs(title = "Some 'weave' types") + 
  scale_pattern_type_manual(values=c('plain', 'twill', 'satin')) +
  theme(legend.key.size = unit(1.5, 'cm'))

The Density Aesthetic as a Mapped Aesthetic

ggplot(df, aes(trt, outcome)) +
  geom_col_pattern(
    aes(fill = trt, pattern_density = trt),
    colour          = 'black', 
    pattern         = 'stripe'
  ) +
  theme_bw() +
  labs(title = "Aesthetic Mapping of 'trt' to Density") + 
  theme(legend.key.size = unit(1.5, 'cm'))

The Density Aesthetic as a Mapped Aesthetic with Manual Scale

scale_pattern_density_manual() can be used to manually control how the variable is mapped to the density.

ggplot(df, aes(trt, outcome)) +
  geom_col_pattern(
    aes(fill = trt, pattern_density = trt),
    colour          = 'black', 
    pattern         = 'stripe'
  ) +
  theme_bw() +
  labs(title = "Aesthetic Mapping of 'trt' to Density") + 
  theme(legend.key.size = unit(1.5, 'cm')) + 
  scale_pattern_density_manual(values = c(a = 0.1, b=0.3, c=0.5))

The Spacing Aesthetic as a Mapped Aesthetic

ggplot(df, aes(trt, outcome)) +
  geom_col_pattern(
    aes(fill = trt, pattern_spacing = trt),
    colour          = 'black', 
    pattern         = 'stripe'
  ) +
  theme_bw() +
  labs(title = "Aesthetic Mapping of 'trt' to Spacing") + 
  theme(legend.key.size = unit(1.5, 'cm'))

The Fill Aesthetic as a Mapped Aesthetic

ggplot(df, aes(trt, outcome)) +
  geom_col_pattern(
    aes(fill = trt, pattern_fill = trt),
    colour          = 'black', 
    pattern         = 'stripe'
  ) +
  theme_bw() +
  labs(title = "Aesthetic Mapping of 'trt' to Pattern Fill") + 
  scale_pattern_fill_viridis_d() + 
  theme(legend.key.size = unit(1.5, 'cm'))