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<!-- README.md is generated from README.Rmd. Please edit that file -->ggsvg - Use SVG as points in ggplot <img src="man/figures/logo-ggsvg.png" align="right" width="230"/>
<!-- badges: start --> <!-- badges: end -->ggsvg
is an extension to ggplot to use SVG images for points.
Variables may be aesthetically mapped to features within the SVG using
CSS selectors via the css()
helper function.
What’s in the box
geom_point_svg()
for plotting points with SVG as the glyph (This is a direct analogue togeom_point()
)scale_svg_*()
functions for controlling the aesthetic mapping.scale_svg_default()
is a sensible default for most plots.scale_svg_*
are a shadow set ofggplot2::scale_*()
functions with adaptations needed forcss()
selectors as aesthetics.- E.g.
scale_svg_fill_brewer()
is a direct analogue forggplot2::scale_fill_brewer()
Installation
Install from GitHub.
The {rsvg}
package is used to
convert SVG into an R raster object. This requires at least rsvg(>=
2.3.0).
# install.package('remotes')
install.packages('rsvg')
remotes::install_github('coolbutuseless/ggsvg')
Simple plot
svg_url <- 'https://www.svgrepo.com/download/289000/jellyfish.svg'
svg_txt <- paste(readLines(svg_url), collapse = "\n")
grid::grid.draw( svg_to_rasterGrob(svg_txt) )
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test_df <- data.frame(
x = runif(10),
y = runif(10),
count = sample(3:5, 10, T),
type = sample(c('a', 'b', 'c'), 10, T))
test_df
#> x y count type
#> 1 0.26550866 0.2059746 3 b
#> 2 0.37212390 0.1765568 5 b
#> 3 0.57285336 0.6870228 3 a
#> 4 0.90820779 0.3841037 3 c
#> 5 0.20168193 0.7698414 3 a
#> 6 0.89838968 0.4976992 3 c
#> 7 0.94467527 0.7176185 4 b
#> 8 0.66079779 0.9919061 3 b
#> 9 0.62911404 0.3800352 3 b
#> 10 0.06178627 0.7774452 4 b
ggplot(test_df) +
geom_point_svg(aes(x, y), svg = svg_txt) +
theme_bw()
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Simple plot with mapped size
aesthetic
ggplot(test_df) +
geom_point_svg(aes(x, y, size = type), svg = svg_txt) +
theme_bw()
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Mapping Aesthetics to SVG features with CSS Selectors
Aesthetic values are mapped to SVG features with CSS Selectors.
Snowman SVG
Here is a simple SVG consisting of 2 stacked circles - a big circle on the bottom and a small circle resting on top.
snowman_txt <- '
<svg viewBox="0 0 100 100 ">
<circle id="top" cx="50" cy="20" r="20" fill="brown" stroke="black" />
<circle id="bot" cx="50" cy="70" r="30" fill="brown" stroke="black" />
</svg>
'
grid::grid.draw( svg_to_rasterGrob(snowman_txt, width=800, height=800) )
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css()
helper function
Use the css()
helper function to target aesthetics at selected
elements within and SVG using css(selector, property = value)
E.g.
css("rect.big", stroke = x)
- Targets
<rect>
elements withclass = "big"
- Map values in
x
in data.frame to the SVGstroke
property for these targetted elements.
- Targets
Example
In the following example, two css()
selectors are used within the
geom_point_svg()
call:
css("circle#top", fill=type)
- Targets
<circle>
elements withid = "top"
- Map values in
type
in data.frame to the SVGfill
property for these targetted elements.
- Targets
css("circle#bot", stroke='brown')
- Targets
<circle>
elements withid = "bot"
- Set a constant value of
brown
for the SVGstroke
property for these targetted elements.
- Targets
css("circle", 'stroke-width'=10)
- Targets
<circle>
elements - Set a constant value of
5
for the SVGstroke-wdith
property for these targetted elements.
- Targets
To configure how the variable is mapped to the property on the selected target, you can either use:
scale_svg_default()
for reasonable defaultsscale_svg_*()
family of functions- Note: the
aesthetic
argument must match exactly thecss(...)
call used in thegeom_point_svg()
call.
- Note: the
snowman_txt <- '
<svg viewBox="0 0 100 100 ">
<circle id="top" cx="50" cy="20" r="20" fill="brown" stroke="black" />
<circle id="bot" cx="50" cy="70" r="30" fill="brown" stroke="black" />
</svg>
'
ggplot(test_df) +
geom_point_svg(
aes(x, y, css("circle#top", fill = type)),
css("circle#bot", stroke = 'brown'),
css("circle", 'stroke-width'=10),
svg = snowman_txt
) +
theme_bw() +
scale_svg_fill_brewer(aesthetics = css("circle#top", fill = type), palette = 'Dark2')
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Acknowledgements
- R Core for developing and maintaining the language.
- CRAN maintainers, for patiently shepherding packages onto CRAN and maintaining the repository