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util-plot-evaluation.R
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util-plot-evaluation.R
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## This file is part of coronet, which is free software: you
## can redistribute it and/or modify it under the terms of the GNU General
## Public License as published by the Free Software Foundation, version 2.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License along
## with this program; if not, write to the Free Software Foundation, Inc.,
## 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
##
## Copyright 2019 by Klara Schlüter <[email protected]>
## Copyright 2021 by Thomas Bock <[email protected]>
## All Rights Reserved.
## / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / /
## Libraries ---------------------------------------------------------------
requireNamespace("ggplot2") ## plotting
requireNamespace("reshape2") ## melting data
## / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / /
## Plots regarding commit edit and editor types ---------------------------------------
#' Produces a barplot showing for every editor the number of commits for which he is only author, only committer, and
#' both author and committer.
#'
#' @param data the project data
#' @param percentage.per.author if \code{TRUE}, the barplot shows the relative number of differently edited commits per
#' author: each bar in the barplot (representing the commits of one editor) is scaled to
#' 100%. Otherwise, the absolute number of commits per author is shown in the plot.
#' [default: FALSE]
#'
#' @return a ggplot2/ggraph plot object
plot.commit.editor.types.by.author = function(data, percentage.per.author = FALSE) {
## get editor data
and = get.committer.and.author.commit.count(data)
or = get.committer.not.author.commit.count(data)
## build data frame as required for plotting
both = data.frame(and[["author.name"]], and[["freq"]])
colnames(both) = c("editor", "author.and.committer")
author = aggregate(or[["freq"]], by = list(or[["author.name"]]), FUN = sum)
colnames(author) = c("editor", "only.author")
committer = aggregate(or[["freq"]], by = list(or[["committer.name"]]), FUN = sum)
colnames(committer) = c("editor", "only.committer")
plot.data = merge(merge(both, author, all = TRUE), committer, all = TRUE)
plot.data[is.na(plot.data)] = 0
## if desired, calculate percentage of editor types per author
if (percentage.per.author) {
name.column = plot.data[1]
value.columns = plot.data[2:4]
## scale data values per author (represented by one line) to 100%
scaled.value.columns = t(apply(value.columns, 1, function(x) {x / sum(x)}))
plot.data = cbind(name.column, scaled.value.columns)
}
## compute order of bars from data: only author < author and committer < only committer
ordered.editors = plot.data[["editor"]][with(plot.data,
order(`only.committer`, `author.and.committer`, `only.author`))]
## prepare data for a stacked barplot (prepare for stacking the editor types)
plot.data = reshape2::melt(plot.data)
names(plot.data) = c("editor", "editor.type", "commit.count")
## draw plot
plot = ggplot2::ggplot(data = plot.data, mapping = ggplot2::aes(x = factor(editor, levels = ordered.editors),
y = `commit.count`, fill = `editor.type`)) +
## use data frame values instead of counting entries
ggplot2::geom_bar(stat = 'identity') +
## rotate y-axis labels by 90 degree
ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90, hjust = 1)) +
## set proper legend items and title
ggplot2::scale_fill_discrete(name = "Commit edit type",
labels = c("author and committer", "only author", "only committer")) +
## add proper axis labels
ggplot2::labs(
x = "Authors",
y = "Commit count"
)
return(plot)
}
#' Produces a barplot showing for how many commits committer and author are the same person and for how many commits
#' committer and author are different.
#'
#' @param data the project data
#' @param relative.y.scale if \code{TRUE}, the y axis shows the percentage of the number of commits of the special edit
#' type with respect to all commits. If \code{FALSE}, the y axis shows the absolut number of
#' commits. [default: FALSE]
#'
#' @return a ggplot2/ggraph plot object
plot.commit.edit.types.in.project = function(data, relative.y.scale = FALSE) {
## get commit count
and = get.committer.and.author.commit.count(data)
or = get.committer.not.author.commit.count(data)
## build data frame as required for plotting
plot.data = data.frame(c("author.!=.committer", "author.=.committer"), c(sum(or[["freq"]]), sum(and[["freq"]])))
colnames(plot.data) = c("edit.types", "commit.count")
## if desired, calculate values for y axis labes showing percentage of all commits
if (relative.y.scale) {
plot.data = cbind(plot.data[1], plot.data[2] / sum(plot.data[2]))
}
## draw plot
plot = ggplot2::ggplot(data = plot.data, mapping = ggplot2::aes(y = `commit.count`, x = `edit.types`)) +
## use data frame values instead of counting entries
ggplot2::geom_bar(stat = 'identity') +
## set proper bar labels
ggplot2::scale_x_discrete(labels = c("author.!=.committer" = "author != committer",
"author.=.committer" = "author = committer")) +
## add proper axis labels
ggplot2::labs(
x = "Edit types",
y = "Commit count"
)
return(plot)
}