In jokergoo/spiralize: Visualize Data on Spirals

library(knitr)
knitr::opts_chunk$set(
    error = FALSE,
    tidy  = FALSE,
    message = FALSE,
    warning = FALSE,
    fig.width = 7,
    fig.height = 7,
    fig.align = "center",
    fig.retina = 2
)
knitr::knit_hooks$set(pngquant = knitr::hook_pngquant)
knitr::opts_chunk$set(
  message = FALSE,
  dev = "ragg_png",
  fig.align = "center",
  pngquant = "--speed=10 --quality=30"
)
options(width = 100)

library(spiralize)

GitHub commits

This example visualizes my GitHub daily commits from 2013-04-18 to 2021-07-01. The data is retrieved by the following code:

repos = c("GlobalOptions", "GetoptLong", "circlize", "bsub", "pkgndep", "ComplexHeatmap", "EnrichedHeatmap", 
    "HilbertCurve", "gtrellis", "cola", "simplifyEnrichment", "InteractiveComplexHeatmap", "spiralize", "rGREAT")

df_all = data.frame(commits = numeric(0), date = character(0), repo = character(0))
for(r in repos) {
    # go to each repo folder
    setwd(paste0("~/project/development/", r))
    df = read.table(pipe("git log --date=short --pretty=format:%ad | sort | uniq -c"))
    colnames(df) = c("commits", "date")
    df$repo = r

    df_all = rbind(df_all, df)
}

df_all$date = as.Date(df_all$date)

start = min(df_all$date)
end = max(df_all$date)

d = start + seq(1, end - start + 1) - 1
n = numeric(length(d))
nl = lapply(repos, function(x) numeric(length(d)))
names(nl) = repos

for(i in seq_len(nrow(df_all))) {
    ind = as.double(difftime(df_all[i, "date"], start), "days") + 1
    n[ind] = n[ind] + df_all[i, "commits"]

    nl[[ df_all[i, "repo"] ]][ind] = nl[[ df_all[i, "repo"] ]][ind] + df_all[i, "commits"]
}

lt = list(d = d, n = n, nl = nl)

Here d is a vector of dates, n is a vector of daily commits of all packages, and nl is a list of vectors of commits of individual packages.

lt = readRDS(system.file("extdata", "github_commits.rds", package = "spiralize"))
d = lt$d
n = lt$n
nl = lt$nl

I will use points to visualize commits. I first define a simple function to map between commits to point sizes.

calc_pt_size = function(x) {
    pt_size = x
    pt_size[pt_size > 20] = 20
    pt_size[pt_size < 2 & pt_size > 0] = 2
    pt_size
}

Next I make the plot for the total commits and commits for individual pacakges. It is actually very easy to see in which period the package was mostly actively developed.

xlim = range(d)
pl = list()
pl[[1]] = grid.grabExpr({
    spiral_initialize_by_time(xlim, verbose = FALSE)
    spiral_track()
    spiral_points(d, 0.5, pch = 16, size = unit(calc_pt_size(n), "pt"))
    grid.text("All packages", x = 0, y = 1, just = c("left", "top"))
})

for(i in order(sapply(nl, sum), decreasing = TRUE)) {
    pl[[ names(nl)[i] ]] = grid.grabExpr({
        spiral_initialize_by_time(xlim, verbose = FALSE)
        spiral_track()
        spiral_points(d, 0.5, pch = 16, size = unit(calc_pt_size(nl[[i]]), "pt"))
        grid.text(names(nl)[i], x = 0, y = 1, just = c("left", "top"))
    })
}

library(cowplot)
plot_grid(plotlist = pl, ncol = 4)

The spiral_git_commits() function

spiral_git_commits() wraps the code in the previous section. The first argument in the function should be the path of a local git repository. The following shows commit histories of some of my R packages.

spiral_git_commits("~/project/development/ComplexHeatmap")
spiral_git_commits("~/project/development/circlize")
spiral_git_commits("~/project/development/rGREAT")
spiral_git_commits("~/project/development/simona")
spiral_git_commits("~/project/development/spiralize")

Let's check the development activity of several programming languages:

spiral_git_commits("~/test/r-source", commits_range = c(1, 60))

spiral_git_commits("~/test/cpython", commits_range = c(1, 60))

spiral_git_commits("~/test/perl5", commits_range = c(1, 60))

spiral_git_commits("~/test/julia", commits_range = c(1, 60))

jokergoo/spiralize documentation built on June 16, 2024, 4:35 a.m.