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Activities on my repos (R packages, 2013-04-18 ~ 2022-12-10): (code for generating this plot: https://jokergoo.github.io/spiralize_vignettes/examples.html#github-commits)

code
library(spiralize)
library(grid)

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

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"]
}

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
}
xlim = range(d)

pl = list()
pl[[1]] = grid.grabExpr({
    spiral_initialize_by_time(xlim, verbose = FALSE, normalize_year = TRUE)
    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"), gp = gpar(fontsize = 14))

    for(t in c("2013-01-01", "2014-01-01", "2015-01-01", "2016-01-01", "2017-01-01",
               "2018-01-01", "2019-01-01", "2020-01-01", "2021-01-01", "2022-01-01", "2023-01-01")) {
        spiral_text(t, 0.5, gsub("-\\d+-\\d+$", "", as.character(t)), gp = gpar(fontsize = 8), facing = "inside")
    }
})

for(i in order(sapply(nl, sum), decreasing = TRUE)) {
    pl[[ names(nl)[i] ]] = grid.grabExpr({
        spiral_initialize_by_time(xlim, verbose = FALSE, normalize_year = TRUE)
        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"), gp = gpar(fontsize = 14))

        for(t in c("2013-01-01", "2014-01-01", "2015-01-01", "2016-01-01", "2017-01-01",
                   "2018-01-01", "2019-01-01", "2020-01-01", "2021-01-01", "2022-01-01", "2023-01-01")) {
            spiral_text(t, 0.5, gsub("-\\d+-\\d+$", "", as.character(t)), gp = gpar(fontsize = 8), facing = "inside")
        }
    })
}

library(cowplot)
png("~/test.png", 300*4*1.5, 300*4*1.5, res = 72*1.5)
plot_grid(plotlist = pl, ncol = 4)
dev.off()

test

Zuguang Gu's Projects

bioc-rnaseq icon bioc-rnaseq

Analysis and Interpretation of Bulk RNA-Seq Data using Bioconductor

brew icon brew

:exclamation: This is a read-only mirror of the CRAN R package repository. brew — Templating Framework for Report Generation

bsub icon bsub

Send R code/R scripts/shell commands to LSF cluster without leaving R

cepa icon cepa

Centrality-based pathway enrichment

cola icon cola

A General Framework for Consensus Partitioning

colorout icon colorout

Colorize R output in terminal emulators

cotools icon cotools

NGS tools for Conputational Oncology group in DKFZ

enrichedheatmap icon enrichedheatmap

make enriched heatmap which visualizes the enrichment of genomic signals to specific target regions.

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