Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/jhrcook/ggasym
Plots three different color schemes on the top-left and bottom-right triangles and the diagonal of a symmetric matrix
https://github.com/jhrcook/ggasym
asymmetric asymmetric-matrix ggplot ggplot2 matrix plot plotting r
Last synced: 11 days ago
JSON representation
Plots three different color schemes on the top-left and bottom-right triangles and the diagonal of a symmetric matrix
- Host: GitHub
- URL: https://github.com/jhrcook/ggasym
- Owner: jhrcook
- License: gpl-3.0
- Created: 2019-02-20T22:07:33.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2021-07-11T20:45:18.000Z (over 3 years ago)
- Last Synced: 2024-10-12T16:53:17.393Z (27 days ago)
- Topics: asymmetric, asymmetric-matrix, ggplot, ggplot2, matrix, plot, plotting, r
- Language: R
- Homepage: https://jhrcook.github.io/ggasym/index.html
- Size: 27.2 MB
- Stars: 13
- Watchers: 2
- Forks: 3
- Open Issues: 3
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE.md
Awesome Lists containing this project
README
---
output: github_document
---
```{r setup, include=FALSE, message=FALSE, warning=FALSE}
library(knitr)
knitr::opts_chunk$set(
echo = TRUE,
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-"
)
library(dplyr)
library(magrittr)
library(tibble)
library(ggasym)
library(ggplot2)
set.seed(0)
```
# ggasym 
[](https://www.gnu.org/licenses/gpl-3.0)
[](https://cran.r-project.org/package=ggasym)
[](https://cran.r-project.org/package=ggasym)
[](https://github.com/jhrcook/ggasym/actions)
[](https://codecov.io/github/jhrcook/ggasym?branch=master)
## Asymmetric Matrix Plotting in 'ggplot' ##
'ggasym' (pronounced "gg-awesome") plots a symmetric matrix with three different fill aesthetics for the top-left and bottom-right triangles and along the diagonal. It operates within the Grammar of Graphics paradigm implemented in ['ggplot2'](https://ggplot2.tidyverse.org).
Checkout the documentation and vignettes at the pkgdown website
[https://jhrcook.github.io/ggasym/](https://jhrcook.github.io/ggasym/index.html)
For information on using 'ggplot2', start [here](https://ggplot2.tidyverse.org/index.html).
## Download and Installation
'ggasym' is available on CRAN. Use the following command to install.
```r
install.packages("ggasym")
```
You can download and install the latest development version from the GitHub repo.
```r
devtools::install_github("jhrcook/ggasym")
```
And load the package with the standard `library` function.
```{r load_lib}
library(ggasym)
```
## Basic Usage
Here is a basic example. `tib` is a "tibble" (i.e.. fancy "data.frame") of comparisons between groups "A" through "E". There are two values to be plotted, `val_1` and `val_2`, that hold data on the comparison between `g1` and `g2`. `tib` is first passed to `asymmetrise()` to fill in all the missing combinations between `g1` and `g2` such that the symmetric matrix can be built. All added values take the value `NA`. The modified data table is finally passed to `ggplot()` and `geom_asymmat()` is added on. Here, `asymmetrise()` added the rows where `g1` and `g2` are equal, thus will fill the diagonal. I set these values to `val_3`.
```{r example1}
tib <- tibble(
g1 = c("A", "A", "A", "A", "B", "B", "B", "C", "C", "D"),
g2 = c("B", "C", "D", "E", "C", "D", "E", "D", "E", "E"),
val_1 = seq(1, 10, 1),
val_2 = rnorm(10, mean = 0, sd = 3)
)
tib <- asymmetrise(tib, g1, g2)
tib$val_3 <- runif(nrow(tib))
ggplot(tib, aes(x = g1, y = g2)) +
geom_asymmat(aes(fill_tl = val_1, fill_br = val_2, fill_diag = val_3)) +
scale_fill_tl_gradient(low = "lightpink", high = "tomato") +
scale_fill_br_gradient(low = "lightblue1", high = "dodgerblue") +
scale_fill_diag_gradient(low = "yellow", high = "orange3")
```
## New Aesthetics
The new aesthetics `fill_tl`, `fill_br`, and `fill_diag` behave just like the normal `fill`, except that they correspond to the top-left ("tl") and bottom-right ("br") triangles of the matrix, respectively. This package also includes analogous functions for scaling the fill colors such as `scale_fill_tl_gradient2()` and `scale_fill_br_gradientn()` that operate just as expected when using 'ggplot2'.
```{r example2}
ggplot(tib, aes(x = g1, y = g2)) +
geom_asymmat(aes(fill_tl = val_1, fill_br = val_2, fill_diag = val_3)) +
scale_fill_tl_gradient(low = "lightpink", high = "tomato") +
scale_fill_br_gradient2(low = "orange", mid = "white", high = "dodgerblue") +
scale_fill_diag_gradientn(colors = rainbow(25))
```
### Adjusting Colorbars
Of note, with three colorbars, it may be useful to control their position and other properties. This can be done just like normal in 'ggplot2' by passing the correct values to the `guide` parameter in `scale_fill_*_gradient()` ([original documentation](https://ggplot2.tidyverse.org/reference/guide_colourbar.html)). Below are a few of the options where I put the bars horizontal, adjust the ordering, and put the title above each.
```{r adj_colorbars}
ggplot(tib, aes(x = g1, y = g2)) +
geom_asymmat(aes(fill_tl = val_1, fill_br = val_2, fill_diag = val_3)) +
scale_fill_tl_gradient(
low = "lightpink", high = "tomato",
guide = guide_colourbar(
direction = "horizontal",
order = 1,
title.position = "top"
)
) +
scale_fill_br_gradient2(
low = "orange", mid = "white", high = "dodgerblue",
guide = guide_colourbar(
direction = "horizontal",
order = 3,
title.position = "top"
)
) +
scale_fill_diag_gradientn(
colors = rainbow(25),
guide = guide_colourbar(
direction = "horizontal",
order = 2,
title.position = "top"
)
)
```
## Full ggplot2 integration
Since the new geom is a normal 'ggplot2' object, it can be introduced into a standard 'ggplot2' workflow. Note that the labels can be adjusted like normal using the `labs` function and using the `fill_tl`, `fill_br`, and `fill_diag` arguments.
```{r example3}
ggplot(tib, aes(x = g1, y = g2)) +
geom_asymmat(aes(
fill_tl = log(val_1),
fill_br = val_2,
fill_diag = val_3
)) +
scale_fill_tl_gradient(
low = "lightpink", high = "tomato",
guide = guide_colourbar(
direction = "horizontal",
order = 1,
title.position = "top"
)
) +
scale_fill_br_gradient(
low = "lightblue1", high = "dodgerblue",
guide = guide_colourbar(
direction = "horizontal",
order = 3,
title.position = "top"
)
) +
scale_fill_diag_gradient(
low = "grey80", high = "grey20",
guide = guide_colourbar(
direction = "horizontal",
order = 2,
title.position = "top"
)
) +
labs(
fill_tl = "top-left fill",
fill_br = "bottom-right fill",
fill_diag = "diagonal fill",
title = "Example of ggasym"
) +
theme_bw() +
theme(
axis.title = element_blank(),
plot.title = element_text(hjust = 0.5),
panel.background = element_rect(fill = "grey70"),
panel.grid = element_blank()
) +
scale_x_discrete(expand = c(0, 0)) +
scale_y_discrete(expand = c(0, 0))
```
## Faceting
If you have multiple categories, faceting works as expected. The only difference is in the preparation of the data table: you must `group_by()` the value(s) you will facet by before passing to `asymmetrise()`. This is shown below.
```{r facetting_setup}
tib <- tibble(
g1 = rep(c("A", "A", "B"), 2),
g2 = rep(c("B", "C", "C"), 2),
val_1 = seq(1, 6),
val_2 = rnorm(6),
grps = c(1, 1, 1, 2, 2, 2)
)
tib
```
Grouping first by `grps`, the tibble is asymmetrized while retaining the `grps` assignments. I then added values to the diagonal.
```{r grouped_asymm}
tib <- tib %>%
group_by(grps) %>%
asymmetrise(g1, g2) %>%
ungroup()
tib <- tib %>% mutate(val_3 = ifelse(g1 == g2, runif(nrow(tib)), NA))
tib
```
```{r faceting_plot}
ggplot(tib, aes(x = g1, y = g2)) +
geom_asymmat(aes(
fill_tl = log(val_1),
fill_br = val_2,
fill_diag = val_3
)) +
scale_fill_tl_gradient(
low = "lightpink", high = "tomato",
guide = guide_colourbar(
direction = "horizontal",
order = 1,
title.position = "top"
)
) +
scale_fill_br_gradient(
low = "lightblue1", high = "dodgerblue",
guide = guide_colourbar(
direction = "horizontal",
order = 3,
title.position = "top"
)
) +
scale_fill_diag_gradient(
low = "grey80", high = "grey20",
guide = guide_colourbar(
direction = "horizontal",
order = 2,
title.position = "top"
)
) +
labs(
fill_tl = "top-left fill",
fill_br = "bottom-right fill",
fill_diag = "diagonal fill",
title = "Example of faceting with ggasym"
) +
theme_bw() +
theme(
axis.title = element_blank(),
plot.title = element_text(hjust = 0.5),
panel.background = element_rect(fill = "grey70"),
panel.grid = element_blank()
) +
scale_x_discrete(expand = c(0, 0)) +
scale_y_discrete(expand = c(0, 0)) +
facet_grid(. ~ grps)
```
---
## Statistical Test Wrapper
I created a wrapper for handling the results of a statistical test to produce a tibble ready to be plotted with ggasym. Here is a brief example - a more detailed example is shown in the vignette ["Statistical Test Plotting"](https://jhrcook.github.io/ggasym/articles/ggasym-stats.html). Here I test if the median sale price of houses in Austin, Texas is different between any of the years (for more information on the data source: `?ggplot2::txhousing`).
```{r stats_example_prep}
tib <- ggplot2::txhousing %>%
filter(city == "Austin") %>%
mutate(year = as.character(year))
aov_res <- aov(median ~ year, data = tib)
broom::tidy(aov_res)
```
Before plotting, the results of the Tukey post-hoc test are passed to `asymmetrise_stats()` that prepares the data for `geom_asymmat()`. The resulting tibble is then plotted and styled in 'ggplot2'.
```{r stats_example_plot}
asymmat_tib <- asymmetrise_stats(TukeyHSD(aov_res))
ggplot(asymmat_tib, aes(x = x, y = y)) +
geom_asymmat(aes(
fill_tl = estimate,
fill_br = -log10(adj.p.value + 0.0000001)
)) +
scale_fill_tl_gradient2(low = "dodgerblue", high = "tomato") +
scale_fill_br_distiller(type = "seq", palette = "Greens", direction = 1) +
labs(
title = "Median House Prices in Austin",
fill_tl = "diff. in\nmean values",
fill_br = "-log10( adj. p-value )"
) +
theme(
panel.background = element_rect(fill = "grey75"),
panel.grid = element_blank()
) +
scale_x_discrete(expand = c(0, 0)) +
scale_y_discrete(expand = c(0, 0))
```
---
### Thank yous
I would like to thank the team behind ['ggplot2'](https://ggplot2.tidyverse.org) for creating a flexible and powerful package for the R community.
If you see any mistakes (including small typos) *please* open an [issue](https://github.com/jhrcook/ggasym/issues) and leave a quick statement. Do not worry about appearing annoying.