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https://github.com/ilia-kosenkov/sciplotr
Tools for scientific ggplot2 plots
https://github.com/ilia-kosenkov/sciplotr
Last synced: 19 days ago
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Tools for scientific ggplot2 plots
- Host: GitHub
- URL: https://github.com/ilia-kosenkov/sciplotr
- Owner: Ilia-Kosenkov
- License: gpl-2.0
- Created: 2019-11-11T10:53:00.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2022-06-05T00:15:59.000Z (over 2 years ago)
- Last Synced: 2024-10-07T08:10:10.549Z (about 1 month ago)
- Language: R
- Size: 342 KB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
[](https://www.tidyverse.org/lifecycle/#experimental)[](https://github.com/Ilia-Kosenkov/primitiveR)
# `sciplotr`
`sciplotr` is built on the basis of
[`ggplot2`](https://github.com/tidyverse/ggplot2) (and includes parts of
the `ggplot2` distributed under
[`GPLv2`](https://github.com/tidyverse/ggplot2/blob/master/LICENSE)).
`sciplotr` provides versions of some `ggplot2` functions (like `theme`,
`facet`, `scale`) that produce more manuscript-oriented plots.
There are also extension methods to work with units (as in
[`grid`](https://github.com/cran/grid)’s `unit`).
## Units support
``` r
library(grid)
library(ggplot2)
library(sciplotr, quietly = TRUE, warn.conflicts = FALSE)
```
## Registered S3 methods overwritten by 'sciplotr':
## method from
## as.character.unit.arithmetic grid
## as.character.unit.list grid
``` r
# {grid}'s way
unit(5, "cm") + unit(1, "pt")
```
## [1] 5cm + 1pt
``` r
# {sciplotr}'s way
# Use `~` to define a single unit
# Use `$` when doing arithmetic
u_(5 ~ cm) + u_(1 ~ pt)
```
## [1] 5cm + 1pt
``` r
u_(5$cm + 1$pt)
```
## [1] 5cm + 1pt
Function `u_` creates units and is best for hard-coded values, e.g.
``` r
u_(1 ~ cm, 2 ~ `in`, 3 ~ pt, 4$mm + 8$mm)
```
## [1] 1cm 2in 3pt 4mm + 8mm
There is a similar `mar_` to create `margin` (which understands `top`,
`bot`, etc.). An accessor `at_` gives access to `margin`’s components by
their names in a `rlang`-ish way.
``` r
# Set vertical margin to 5 cm and horizontal to 10 pt
m <- mar_(v = 5 ~ cm, h = 10 ~ pt)
at_(m, top) + at_(m, left)
```
## [1] 5cm + 10pt
## `gtable`-like methods
[`gtable`](https://github.com/r-lib/gtable) provides tools to manipulate
grobs. `sciplotr` has a few extra functions to inspect layout.
`postprocess_axes` is a handy method that sets up margins of a typical
`ggplot2` plot, that is, modifying heights/widths of axis name grobs,
axis ticks grobs and facet strips. It is possible to produce plots with
**exactly same** plot area sizes to nicely align them in the manuscript.
There are also some other tools of the family `get_grob_*`
## Plotting
`siplotr` has several main plotting-related methods that are derived
from `ggplot2`’s implementations.
- `theme_sci` extends the space of theme parameters of `ggplot2`,
adding several parameters, specific to `sicplotr`,
- `coord_sci` is a copy of `coord_cartesian` (`CoordSci` derives from
`CoordCartesian`), which explicitly plots minor axes ticks (using
grid.minor breaks that can be displayed as grid lines, but not as
ticks),
- `scale_*[_log10]_sci` generate better tick positioning than default
`ggplot2` methods, and work nicely with `coord_sci`,
- `sec_axis_sci` and friends provide better support for secondary axes
and secondary axes minor ticks,
- `facet_sci` works similar to `ggplot2::facet_grid`, but applies
different panel styling and also different strip labeling.
To wrap things up, here is an example
``` r
# Generate strip labels as list of expressions
labeller <- label_f(
.f_left = ~purrr::map(as.list(paste0("hp[", .x$rows$am, "]")), ~parse(text = .x)),
.f_bottom = ~purrr::map(as.list(paste0("mpg[", .x$cols$vs, "]")), ~parse(text = .x)))
# ggplot_sci is equivalent to ggplot() + theme_sci() + coord_sci()
ggplot_sci(mtcars, aes(hp, mpg, col = factor(gear))) +
theme_sci(ticks = -u_(5~pt), facet.lab.x = u_(0.93 ~ npc)) +
geom_point() +
scale_x_sci(name = NULL, sec.axis = dup_axis_sci_weak()) +
scale_y_sci(name = NULL, sec.axis = dup_axis_sci_weak()) +
facet_sci(am ~ vs,
labeller = labeller) -> plt
print(plt)
```
``` r
# This call generates plot with equal margin on all four sides (0.75 + 0.75 cm)
grid.newpage()
grid.draw(postprocess_axes(plt,
axes_margin = mar_(0.75 ~ cm),
text_margin = mar_(0.75 ~ cm, 0.75 ~ cm , 0 ~ npc, 0 ~ npc),
strip_margin = mar_(0 ~ npc, 0 ~ npc, 0.75 ~ cm, 0.75 ~ cm)))
```
Another example shows different secondary axes scales. The main use case
is plots with sophisticated secondary axes, like astrophysical plots
where y-axis shows logarithmic fluxes (e.g. incident energy per unit
time, surface and frequency) and secondary y-axis shows “magnitudes”
(`2.5 * log10(F / F0)`).
``` r
set.seed(1)
data <- data.frame(x = 1:1000, y = 10 ^ runif(1000, 3, 5));
ggplot_sci(data, aes(x, y)) +
geom_point() +
scale_x_sci(sec.axis = sec_axis_sci(~2 * .)) +
scale_y_log10_sci(name = "F",
sec.axis = sec_axis_sci(
~ -2.5 * log10(.) + 20,
name = "m",
breaks_trans = identity_sci_trans()))
```
