Patterns ‘stripe’, ‘wave’, ‘crosshatch’, ‘weave’

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

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

The ‘stripe’ pattern draws a set of (horizontal) straight lines.
The ‘wave’ pattern draws a set of (horizontal) wavy lines.
The ‘crosshatch’ pattern draws a set of vertical lines on top of a set of horizontal lines.
The ‘weave’ pattern draws a set of vertical lines interlaced with a set of horizontal lines.
For more info on these patterns see their {gridpattern} documentation:

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")

A plot using vanilla 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'))

A plot using ggpattern with a patterned geom

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'))

A plot with both a 'stripe' pattern and a 'wave' pattern.

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'))

A plot with the density of striping increased to 50% of fill area

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'))

A plot with 'plain', 'twill', 'satin' weave patterns

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'))

Example plot from using the density aesthetic as a mapped aesthetic.

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))

Example plot from using the density aesthetic as a mapped aesthetic with manual scale.

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'))

Example plot from using the spacing aesthetic as a mapped aesthetic.

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'))

Example plot from using the fill aesthetic as a mapped aesthetic.

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