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^.*\.Rproj$
^\.Rproj\.user$
^LICENSE\.md$
^README\.Rmd
^\.Rproj\.user$
^\.github$
^\.pre-commit-config\.yaml$
^_pkgdown\.yml$
^codecov\.yml$
^data-raw$
^pkgdown\.css
^docs
^_pkgdown\.yml$
^docs$
^pkgdown$
^pkgdown\.css
^renv$
^renv$
^renv\.lock$
^renv\.lock$
^test-example.R
^test\.R$
^data-raw$

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@ -1,3 +0,0 @@
# source("renv/activate.R")
options(repos = c(CRAN = "https://p3m.dev/cran/__linux__/manylinux_2_28/latest"))
options(renv.config.pak.enabled = TRUE)

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.github/.gitignore vendored
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*.html

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## PR Description
<!-- Please include a summary of the changes and which issue is fixed or what feature is added -->
## Type of change
<!-- Please mark relevant options with [x] -->
- [ ] Bug fix (non-breaking change which fixes an issue)
- [ ] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
- [ ] Documentation update
- [ ] Code refactoring or style updates
## Checklist:
<!-- Please mark relevant options with [x] -->
- [ ] My code follows the style guidelines of this project
- [ ] I have performed a self-review of my own code
- [ ] I have commented my code, particularly in hard-to-understand areas
- [ ] I have made corresponding changes to the documentation
- [ ] My changes generate no new warnings
- [ ] I have added tests that prove my fix is effective or that my feature works
- [ ] New and existing unit tests pass locally with my changes
## Notes for reviewers
<!-- Optional: Any notes or context that would be useful for the reviewer -->
## Automated Checks
The following checks will run automatically on this PR:
- R CMD check
- Documentation updates
- Test coverage
- Linting and style checks

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# For help debugging build failures open an issue on the RStudio community with the 'github-actions' tag.
# https://community.rstudio.com/new-topic?category=Package%20development&tags=github-actions
on:
push:
branches: [main, master]
pull_request:
branches: [main, master]
name: R-CMD-check
jobs:
R-CMD-check:
runs-on: ${{ matrix.config.os }}
name: ${{ matrix.config.os }} (${{ matrix.config.r }})
strategy:
fail-fast: false
matrix:
config:
- {os: windows-latest, r: 'release'}
- {os: macOS-latest, r: 'release'}
- {os: ubuntu-latest, r: 'release'}
- {os: ubuntu-latest, r: 'devel', http-user-agent: 'release'}
env:
R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
RSPM: ${{ matrix.config.rspm }}
GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
steps:
- uses: actions/checkout@v3
- uses: r-lib/actions/setup-pandoc@v2
- uses: r-lib/actions/setup-r@v2
with:
r-version: ${{ matrix.config.r }}
http-user-agent: ${{ matrix.config.http-user-agent }}
use-public-rspm: true
- uses: r-lib/actions/setup-r-dependencies@v2
with:
extra-packages: any::rcmdcheck
needs: check
- name: Document
run: |
install.packages("devtools")
devtools::document()
shell: Rscript {0}
if: github.event_name == 'pull_request'
- uses: r-lib/actions/check-r-package@v2
with:
upload-snapshots: true

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@ -1,40 +0,0 @@
# Workflow for linting and style checks
on:
push:
branches: [main, master]
pull_request:
branches: [main, master]
name: lint
jobs:
lint:
runs-on: ubuntu-latest
env:
GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
steps:
- uses: actions/checkout@v3
- uses: r-lib/actions/setup-r@v2
with:
use-public-rspm: true
- uses: r-lib/actions/setup-r-dependencies@v2
with:
extra-packages: |
any::lintr
any::styler
needs: lint
- name: Lint
run: |
lintr::lint_package()
shell: Rscript {0}
- name: Style check
run: |
if (!styler::style_pkg(dry = TRUE)) {
message("Some files are not properly styled!")
quit(status = 1)
}
shell: Rscript {0}

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@ -1,49 +0,0 @@
# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
on:
push:
branches: [main, master]
pull_request:
release:
types: [published]
workflow_dispatch:
name: pkgdown.yaml
permissions: read-all
jobs:
pkgdown:
runs-on: ubuntu-latest
# Only restrict concurrency for non-PR jobs
concurrency:
group: pkgdown-${{ github.event_name != 'pull_request' || github.run_id }}
env:
GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
permissions:
contents: write
steps:
- uses: actions/checkout@v4
- uses: r-lib/actions/setup-pandoc@v2
- uses: r-lib/actions/setup-r@v2
with:
use-public-rspm: true
- uses: r-lib/actions/setup-r-dependencies@v2
with:
extra-packages: any::pkgdown, local::.
needs: website
- name: Build site
run: pkgdown::build_site_github_pages(new_process = FALSE, install = FALSE)
shell: Rscript {0}
- name: Deploy to GitHub pages 🚀
if: github.event_name != 'pull_request'
uses: JamesIves/github-pages-deploy-action@v4.5.0
with:
clean: false
branch: gh-pages
folder: docs

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@ -1,55 +0,0 @@
# Run test-coverage for visualizeR package
on:
push:
branches: [main, master]
pull_request:
branches: [main, master]
name: test-coverage
jobs:
test-coverage:
runs-on: ubuntu-latest
env:
GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
steps:
- uses: actions/checkout@v3
- uses: r-lib/actions/setup-r@v2
with:
use-public-rspm: true
- uses: r-lib/actions/setup-r-dependencies@v2
with:
extra-packages: |
any::covr
any::remotes
needs: coverage
- name: Install package
run: |
R CMD build .
R CMD INSTALL *.tar.gz
- name: Test coverage
run: |
covr::codecov(
quiet = FALSE,
clean = FALSE,
install_path = file.path(Sys.getenv("RUNNER_TEMP"), "package")
)
shell: Rscript {0}
- name: Show testthat output
if: always()
run: |
## Print out test results details
find . -name 'testthat.Rout*' -exec cat '{}' \; || true
shell: bash
- name: Upload test results
if: failure()
uses: actions/upload-artifact@v4
with:
name: coverage-test-failures
path: ${{ runner.temp }}/package

4
.gitignore vendored
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@ -4,7 +4,3 @@
.httr-oauth
.DS_Store
R/test.R
inst/doc
/.quarto/
docs

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@ -1,93 +0,0 @@
# All available hooks: https://pre-commit.com/hooks.html
# R specific hooks: https://github.com/lorenzwalthert/precommit
repos:
- repo: https://github.com/lorenzwalthert/precommit
rev: v0.4.3.9012
hooks:
- id: style-files
args: [--style_pkg=styler, --style_fun=tidyverse_style]
- id: roxygenize
# roxygen requires loading pkg -> add dependencies from DESCRIPTION
additional_dependencies:
- ggplot2
- rlang
- grDevices
- glue
- scales
- ggtext
- ggrepel
- tidyr
- dplyr
- ggalluvial
- viridisLite
- waffle
- stringr
- checkmate
- forcats
# codemeta must be above use-tidy-description when both are used
# - id: codemeta-description-updated
- id: use-tidy-description
- id: spell-check
exclude: >
(?x)^(
.*\.[rR]|
.*\.feather|
.*\.jpeg|
.*\.pdf|
.*\.png|
.*\.py|
.*\.RData|
.*\.rds|
.*\.Rds|
.*\.Rproj|
.*\.sh|
(.*/|)\.gitignore|
(.*/|)\.gitlab-ci\.yml|
(.*/|)\.lintr|
(.*/|)\.pre-commit-.*|
(.*/|)\.Rbuildignore|
(.*/|)\.Renviron|
(.*/|)\.Rprofile|
(.*/|)\.travis\.yml|
(.*/|)appveyor\.yml|
(.*/|)NAMESPACE|
(.*/|)renv/settings\.dcf|
(.*/|)renv\.lock|
(.*/|)WORDLIST|
\.github/workflows/.*|
data/.*|
)$
- id: readme-rmd-rendered
- id: parsable-R
- id: no-browser-statement
- id: no-print-statement
- id: no-debug-statement
- id: deps-in-desc
- id: pkgdown
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v5.0.0
hooks:
- id: check-added-large-files
args: ["--maxkb=200"]
- id: file-contents-sorter
files: '^\.Rbuildignore$'
- id: end-of-file-fixer
exclude: '\.Rd'
- repo: https://github.com/pre-commit-ci/pre-commit-ci-config
rev: v1.6.1
hooks:
# Only required when https://pre-commit.ci is used for config validation
- id: check-pre-commit-ci-config
- repo: local
hooks:
- id: forbid-to-commit
name: Don't commit common R artifacts
entry: Cannot commit .Rhistory, .RData, .Rds or .rds.
language: fail
files: '\.(Rhistory|RData|Rds|rds)$'
# `exclude: <regex>` to allow committing specific files
ci:
autoupdate_schedule: monthly
skip: [pkgdown]

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@ -1,41 +1,39 @@
Type: Package
Package: visualizeR
Type: Package
Title: What a color! What a viz!
Version: 1.0
Authors@R:
person("Noblet", "Guillaume", , "gnoblet@zaclys.net", role = c("aut", "cre"))
Maintainer: Guillaume Noblet <gnoblet@zaclys.net>
Description: It basically provides colors as hex codes, color palettes,
and some viz functions (graphs and maps).
License: GPL (>= 3)
Version: 0.8.9000
Authors@R: c(
person(
'Noblet', 'Guillaume',
email = 'gnoblet@zaclys.net',
role = c('aut', 'cre')
)
)
URL: https://github.com/gnoblet/visualizeR,
https://gnoblet.github.io/visualizeR/
Depends:
R (>= 4.1.0)
Imports:
checkmate,
dplyr,
forcats,
ggplot2,
ggrepel,
ggtext,
glue,
grDevices,
rlang (>= 0.4.11),
scales,
tidyr
Suggests:
covr,
knitr,
rio,
rmarkdown,
roxygen2,
testthat (>= 3.0.0),
vdiffr,
withr
VignetteBuilder:
knitr
Config/testthat/edition: 3
Maintainer: Guillaume Noblet <gnoblet@zaclys.net>
Description: It basically provides colors as hex codes, color palettes, and some viz functions (graphs and maps).
Depends: R (>= 4.1.0)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.2
RoxygenNote: 7.2.3
Imports:
ggplot2,
rlang (>= 0.4.11),
grDevices,
glue,
scales,
ggtext,
ggrepel,
tidyr,
dplyr,
ggalluvial,
viridisLite,
waffle
Suggests:
knitr,
roxygen2,
sf,
tmap
VignetteBuilder: knitr

104
R/alluvial.R Normal file
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@ -0,0 +1,104 @@
#' @title Simple alluvial chart
#'
#' @param df A data frame.
#' @param from A character column of upstream stratum.
#' @param to A character column of downstream stratum.
#' @param value A numeric column of values.
#' @param group The grouping column to fill the alluvium with.
#' @param alpha Fill transparency. Default to 0.5.
#' @param from_levels Order by given from levels?
#' @param value_title The value/y scale title. Default to NULL.
#' @param group_title The group title. Default to NULL.
#' @param title Plot title. Default to NULL.
#' @param subtitle Plot subtitle. Default to NULL.
#' @param caption Plot caption. Default to NULL.
#' @param rect_color Stratum rectangles' fill color.
#' @param rect_border_color Stratum rectangles' border color.
#' @param rect_text_color Stratum rectangles' text color.
#' @param theme Whatever theme. Default to theme_reach().
#'
#' @return A donut chart to be used parsimoniously
#'
#' @export
alluvial <- function(
df,
from,
to,
value,
group = NULL,
alpha = 0.5,
from_levels = NULL,
value_title = NULL,
group_title = NULL,
title = NULL,
subtitle = NULL,
caption = NULL,
rect_color = cols_reach("white"),
rect_border_color = cols_reach("main_grey"),
rect_text_color = cols_reach("main_grey"),
theme = theme_reach(axis_y = FALSE,
legend_position = "none")
){
if(!is.null(from_levels)) df <- dplyr::mutate(df, "{{from}}" := factor({{ from }}, levels = from_levels))
# General mapping
g <- ggplot2::ggplot(
data = df,
mapping = ggplot2::aes(
y = {{ value }},
axis1 = {{ from }},
axis3 = {{ to }}
)
)
# Add alluvium
g <- g +
ggalluvial::geom_alluvium(
ggplot2::aes(
fill = {{ group }},
color = {{ group }}
),
alpha = alpha)
# Add stratum
g <- g +
ggalluvial::geom_stratum(
fill = rect_color,
color = rect_border_color
)
# Add stratum text
stratum <- ggalluvial::StatStratum
g <- g +
ggplot2::geom_text(
stat = stratum,
ggplot2::aes(label = ggplot2::after_stat(!!rlang::sym("stratum"))),
color = cols_reach("main_grey")
)
# Add title, subtitle, caption, x_title, y_title
g <- g + ggplot2::labs(
y = value_title,
title = title,
subtitle = subtitle,
caption = caption,
fill = group_title,
color = group_title
)
# Remove x-axis
g <- g + ggplot2::theme(
axis.line.x = ggplot2::element_blank(),
axis.ticks.x = ggplot2::element_blank(),
axis.text.x = ggplot2::element_blank(),
axis.title.x = ggplot2::element_blank()
)
g <- g + theme
return(g)
}

452
R/bar.R
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@ -1,35 +1,11 @@
#' @rdname bar
#'
#' @inheritParams bar
#'
#' @param ... Additional arguments passed to `bar()`
#'
#' @export
hbar <- function(
...,
flip = TRUE,
add_text = FALSE,
theme_fun = theme_bar(flip = flip, add_text = add_text)) {
bar(flip = flip, add_text = add_text, theme_fun = theme_fun, ...)
}
#' Simple bar chart
#'
#' `bar()` is a simple bar chart with some customization allowed, in particular the `theme_fun` argument for theming. `hbar()` uses `bar()` with sane defaults for a horizontal bar chart.
#' @title Simple bar chart
#'
#' @param df A data frame.
#' @param x A quoted numeric column.
#' @param y A quoted character column or coercible as a character column.
#' @param group Some quoted grouping categorical column, e.g. administrative areas or population groups.
#' @param facet Some quoted grouping categorical column, e.g. administrative areas or population groups.
#' @param x_rm_na Remove NAs in x?
#' @param y_rm_na Remove NAs in y?
#' @param group_rm_na Remove NAs in group?
#' @param facet_rm_na Remove NAs in facet?
#' @param y_expand Multiplier to expand the y axis.
#' @param add_color Add a color to bars (if no grouping).
#' @param add_color_guide Should a legend be added?
#' @param flip TRUE or FALSE (default). Default to TRUE or horizontal bar plot.
#' @param x A numeric column.
#' @param y A character column or coercible as a character column.
#' @param group Some grouping categorical column, e.g. administrative areas or population groups.
#' @param flip TRUE or FALSE. Default to TRUE or horizontal bar plot.
#' @param percent TRUE or FALSE. Should the x-labels (and text labels if present) be displayed as percentages? Default to TRUE.
#' @param wrap Should x-labels be wrapped? Number of characters.
#' @param position Should the chart be stacked? Default to "dodge". Can take "dodge" and "stack".
#' @param alpha Fill transparency.
@ -39,426 +15,134 @@ hbar <- function(
#' @param title Plot title. Default to NULL.
#' @param subtitle Plot subtitle. Default to NULL.
#' @param caption Plot caption. Default to NULL.
#' @param width Bar width.
#' @param add_text TRUE or FALSE. Add values as text.
#' @param add_text_size Text size.
#' @param add_text_color Text color.
#' @param add_text_font_face Text font_face.
#' @param add_text TRUE or FALSE. Add the value as text.
#' @param add_text_threshold_display Minimum value to add the text label.
#' @param add_text_color Text color.
#' @param add_text_suffix If percent is FALSE, should we add a suffix to the text label?
#' @param add_text_expand_limit Default to adding 10\% on top of the bar.
#' @param add_text_round Round the text label.
#' @param theme_fun Whatever theme function. For no custom theme, use theme_fun = NULL.
#' @param scale_fill_fun Scale fill function. Default to scale_fill_visualizer_discrete().
#' @param scale_color_fun Scale color function. Default to scale_color_visualizer_discrete().
#' @param theme Whatever theme. Default to theme_reach().
#'
#' @inheritParams reorder_by
#'
#' @importFrom rlang `:=`
#' @return A bar chart
#'
#' @export
bar <- function(
df,
x,
y,
group = "",
facet = "",
order = "none",
x_rm_na = TRUE,
y_rm_na = TRUE,
group_rm_na = TRUE,
facet_rm_na = TRUE,
y_expand = 0.1,
add_color = color("cat_5_main_1"),
add_color_guide = TRUE,
flip = FALSE,
wrap = NULL,
position = "dodge",
alpha = 1,
x_title = NULL,
y_title = NULL,
group_title = NULL,
title = NULL,
subtitle = NULL,
caption = NULL,
width = 0.8,
add_text = FALSE,
add_text_size = 4.5,
add_text_color = color("dark_grey"),
add_text_font_face = "bold",
add_text_threshold_display = 0.05,
add_text_suffix = "%",
add_text_expand_limit = 1.2,
add_text_round = 1,
theme_fun = theme_bar(
flip = flip,
add_text = add_text,
axis_text_x_angle = 0,
axis_text_x_vjust = 0.5,
axis_text_x_hjust = 0.5
),
scale_fill_fun = scale_fill_visualizer_discrete(),
scale_color_fun = scale_color_visualizer_discrete()) {
#------ Checks
bar <- function(df, x, y, group = NULL, flip = TRUE, percent = TRUE, wrap = NULL, position = "dodge", alpha = 1, x_title = NULL, y_title = NULL, group_title = NULL, title = NULL, subtitle = NULL, caption = NULL, width = 0.9, add_text = FALSE, add_text_threshold_display = 5, add_text_color = "white", add_text_suffix = "", theme = theme_reach()){
# df is a data frame
checkmate::assert_data_frame(df)
# To do :
# - automate bar width and text size, or at least give the flexibility and still center text
# - add facet possibility
# x and y and group are character
checkmate::assert_character(x, len = 1)
checkmate::assert_character(y, len = 1)
checkmate::assert_character(group, len = 1)
# Prepare group, x and y names
# if (is.null(x_title)) x_title <- rlang::as_name(rlang::enquo(x))
# if (is.null(y_title)) y_title <- rlang::as_name(rlang::enquo(y))
# if (is.null(group_title)) group_title <- rlang::as_name(rlang::enquo(group))
# x and y are columns in df
checkmate::assert_choice(x, colnames(df))
checkmate::assert_choice(y, colnames(df))
if (group != "") {
checkmate::assert_choice(group, colnames(df))
}
# x_rm_na, y_rm_na and group_rm_na are logical scalar
checkmate::assert_logical(x_rm_na, len = 1)
checkmate::assert_logical(y_rm_na, len = 1)
checkmate::assert_logical(group_rm_na, len = 1)
checkmate::assert_logical(facet_rm_na, len = 1)
# flip is a logical scalar
checkmate::assert_logical(flip, len = 1)
# wrap is a numeric scalar or NULL
if (!is.null(wrap)) {
checkmate::assert_numeric(wrap, len = 1, null.ok = TRUE)
}
# alpha is a numeric scalar between 0 and 1
checkmate::assert_numeric(alpha, lower = 0, upper = 1, len = 1)
# add_text is a logical scalar
checkmate::assert_logical(add_text, len = 1)
# add_text_size is a numeric scalar
checkmate::assert_numeric(add_text_size, len = 1)
# add_text_font_face is a character scalar in bold plain or italic
checkmate::assert_choice(add_text_font_face, c("bold", "plain", "italic"))
# add_text_threshold_display is a numeric scalar
checkmate::assert_numeric(add_text_threshold_display, len = 1)
# add_text_suffix is a character scalar
checkmate::assert_character(add_text_suffix, len = 1)
# add_text_expand_limit is a numeric scalar
checkmate::assert_numeric(add_text_expand_limit, len = 1)
# add_text_round is a numeric scalar
checkmate::assert_numeric(add_text_round, len = 1)
# x and y are numeric or character
if (class(df[[y]]) %notin% c("integer", "numeric")) {
rlang::abort(paste0(y, " must be numeric."))
}
if (!any(class(df[[x]]) %in% c("character", "factor"))) {
rlang::abort(paste0(x, " must be character or factor"))
}
# width is a numeric scalar between 0 and 1
checkmate::assert_numeric(width, lower = 0, upper = 1, len = 1)
# Check if position is stack or dodge
if (position %notin% c("stack", "dodge")) {
rlang::abort("Position should be either 'stack' or 'dodge'.")
}
#----- Data wrangling
# facets over group
if (group != "" && facet != "" && group == facet) {
rlang::warn("'group' and 'facet' are the same identical.")
}
# remove NAs using base R
if (x_rm_na) {
df <- df[!(is.na(df[[x]])), ]
}
if (y_rm_na) {
df <- df[!(is.na(df[[y]])), ]
}
if (group != "" && group_rm_na) {
df <- df[!(is.na(df[[group]])), ]
}
if (facet != "" && facet_rm_na) {
df <- df[!(is.na(df[[facet]])), ]
}
# reorder
dir_order <- if (flip && order %in% c("x", "grouped_x")) {
-1
} else if (!flip && order %in% c("x", "grouped_x")) {
1
} else if (flip) {
1
} else {
-1
}
group_order <- if (group != "" || (group == "" && facet == "")) {
group
} else if (group == "" && facet != "") {
facet
}
df <- reorder_by(
df = df,
x = x,
y = y,
group = group_order,
order = order,
dir_order = dir_order
)
# prepare aes
if (group != "") {
# Mapping
g <- ggplot2::ggplot(
df,
mapping = ggplot2::aes(
x = !!rlang::sym(x),
y = !!rlang::sym(y),
fill = !!rlang::sym(group),
color = !!rlang::sym(group)
mapping = ggplot2::aes(x = {{ x }}, y = {{ y }}, fill = {{ group }}, color = {{ group }}
)
)
} else {
g <- ggplot2::ggplot(
df,
mapping = ggplot2::aes(
x = !!rlang::sym(x),
y = !!rlang::sym(y)
)
)
}
# add title, subtitle, caption, x_title, y_title
g <- g +
ggplot2::labs(
# Add title, subtitle, caption, x_title, y_title
g <- g + ggplot2::labs(
title = title,
subtitle = subtitle,
caption = caption,
x = y_title,
y = x_title,
x = x_title,
y = y_title,
color = group_title,
fill = group_title
)
# width
width <- width
dodge_width <- width
# facets
if (facet != "") {
if (flip) {
g <- g +
ggplot2::facet_grid(
rows = ggplot2::vars(!!rlang::sym(facet)),
scales = "free",
space = "free_y"
)
} else {
g <- g +
ggplot2::facet_grid(
cols = ggplot2::vars(!!rlang::sym(facet)),
scales = "free",
space = "free_x"
)
}
}
# should the graph use position_fill?
if (group != "") {
# Should the graph use position_fill?
if (position == "stack"){
g <- g +
ggplot2::geom_col(
g <- g + ggplot2::geom_col(
alpha = alpha,
width = width,
position = ggplot2::position_stack()
)
} else if (position == "dodge"){
g <- g +
ggplot2::geom_col(
g <- g + ggplot2::geom_col(
alpha = alpha,
width = width,
position = ggplot2::position_dodge2(
width = dodge_width,
preserve = "single"
)
preserve = "single")
)
} else{
g <- g +
ggplot2::geom_col(
g <- g + ggplot2::geom_col(
alpha = alpha,
width = width
)
}
} else {
if (position == "stack") {
g <- g +
ggplot2::geom_col(
alpha = alpha,
width = width,
position = ggplot2::position_stack(),
fill = add_color,
color = add_color
)
} else if (position == "dodge") {
g <- g +
ggplot2::geom_col(
alpha = alpha,
width = width,
position = ggplot2::position_dodge2(
width = dodge_width,
preserve = "single"
),
fill = add_color,
color = add_color
#
# Labels to percent and expand scale
if (percent) {
g <- g + ggplot2::scale_y_continuous(
labels = scales::label_percent(
accuracy = 1,
decimal.mark = ",",
suffix = " %"),
expand = c(0.01, 0.1)
)
} else {
g <- g +
ggplot2::geom_col(
alpha = alpha,
width = width,
fill = add_color,
color = add_color
)
}
g <- g + ggplot2::scale_y_continuous(expand = c(0.01, 0.1))
}
# wrap labels on the x scale?
if (!is.null(wrap)) {
g <- g + ggplot2::scale_x_discrete(labels = scales::label_wrap(wrap))
}
# because a text legend should always be horizontal, especially for an horizontal bar graph
# Because a text legend should always be horizontal, especially for an horizontal bar graph
if (flip){
g <- g + ggplot2::coord_flip()
}
# add text to bars
if (flip) {
hjust_flip <- -0.5
} else {
hjust_flip <- 0.5
}
if (flip) {
vjust_flip <- 0.5
} else {
vjust_flip <- -0.5
# Add text to bars
if (flip) hjust_flip <- 1.5 else hjust_flip <- 0.5
if (flip) vjust_flip <- 0.5 else vjust_flip <- 1.5
if (add_text & position != "dodge") {
rlang::abort("Adding text labels and positions different than dodges as not been implemented yet")
}
# function for interactio
interaction_f <- function(group, facet, data) {
if (group == "" && facet == "") {
return(NULL)
} else if (group != "" && facet != "") {
return(interaction(data[[group]], data[[facet]]))
} else if (group != "") {
return(data[[group]])
} else if (facet != "") {
return(data[[facet]])
} else {
return(NULL)
}
}
# Add text labels
if (add_text) {
# add text labels
if (add_text & position == "dodge") {
df$y_threshold <- ifelse(df[[y]] >= add_text_threshold_display, df[[y]], NA)
df <- dplyr::mutate(df, "y_threshold" = ifelse({{ y }} >= add_text_threshold_display, {{ y }}, NA ))
# expand limits
g <- g +
ggplot2::geom_blank(
if (percent) {
g <- g + ggplot2::geom_text(
data = df,
ggplot2::aes(
x = !!rlang::sym(x),
y = !!rlang::sym(y) * add_text_expand_limit,
group = interaction_f(group, facet, df)
)
)
g <- g +
ggplot2::geom_text(
data = df,
ggplot2::aes(
label = ifelse(
is.na(!!rlang::sym("y_threshold")),
NA,
paste0(
round(!!rlang::sym("y_threshold"), add_text_round),
add_text_suffix
)
),
group = interaction_f(group, facet, df)
),
label = scales::label_percent(
accuracy = 1,
decimal.mark = ",",
suffix = " %")(!!rlang::sym("y_threshold")),
group = {{ group }}),
hjust = hjust_flip,
vjust = vjust_flip,
color = add_text_color,
fontface = add_text_font_face,
size = add_text_size,
position = ggplot2::position_dodge2(width = dodge_width)
)
} else if (add_text & position == "stack") {
df$y_threshold <- ifelse(df[[y]] >= add_text_threshold_display, df[[y]], NA)
g <- g +
ggplot2::geom_text(
fontface = "bold",
position = ggplot2::position_dodge(width = dodge_width))
} else {
g <- g + ggplot2::geom_text(
data = df,
ggplot2::aes(
label = ifelse(
is.na(!!rlang::sym("y_threshold")),
NA,
paste0(
round(!!rlang::sym("y_threshold"), add_text_round),
add_text_suffix
)
),
group = interaction_f(group, facet, df)
),
label = paste0(round(!!rlang::sym("y_threshold")), add_text_suffix),
group = {{ group }}),
hjust = hjust_flip,
vjust = vjust_flip,
color = add_text_color,
fontface = add_text_font_face,
size = add_text_size,
position = ggplot2::position_dodge2(width = dodge_width)
)
fontface = "bold",
position = ggplot2::position_dodge(width = dodge_width))
}
}
# y scale tweaks
g <- g +
ggplot2::scale_y_continuous(
# start at 0
expand = ggplot2::expansion(mult = c(0, y_expand)),
# remove trailing 0 and choose accuracy of y labels
labels = scales::label_number(
accuracy = 0.1,
drop0trailing = TRUE,
big.mark = "",
decimal.mark = "."
),
)
# # remove guides for legend if !add_color_guide
if (!add_color_guide) {
g <- g + ggplot2::guides(fill = "none", color = "none")
}
# # add theme fun
if (!is.null(theme_fun)) {
g <- g + theme_fun
}
# # # add scale fun
if (!is.null(scale_fill_fun)) {
g <- g + scale_fill_fun
}
if (!is.null(scale_color_fun)) {
g <- g + scale_color_fun
}
# Add theme
g <- g + theme
return(g)
}

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R/bbox_buffer.R Normal file
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#' @title Bbbox buffer
#'
#' @param sf_obj A `sf` object
#' @param buffer A buffer, either one value or a vector of 4 values (left, bottom, right, top). Default to 0.
#'
#' @return A bbox with a buffer
#'
#' @export
buffer_bbox <- function(sf_obj, buffer = 0){
rlang::check_installed("sf", reason = "Package \"sf\" needed for `buffer_bbox()` to work. Please install it.")
if (!(length(buffer) %in% c(1,4)) | !is.numeric(buffer)) stop("Please provide a numeric buffer of length 1 or 4.")
bbox <- sf::st_bbox(sf_obj)
xrange <- bbox$xmax - bbox$xmin # range of x values
yrange <- bbox$ymax - bbox$ymin # range of y values
bbox_with_buffer <- if (length(buffer) == 1) {
c(
bbox[1] - (buffer * xrange), # xmin - left
bbox[2] - (buffer * yrange), # ymin - bottom
bbox[3] + (buffer * xrange), # xmax - right
bbox[4] + (buffer * yrange) # ymax - top
)
} else if (length(buffer) == 4) {
c(
bbox[1] - (buffer[1] * xrange), # xmin - left
bbox[2] - (buffer[2] * yrange), # ymin - bottom
bbox[3] + (buffer[3] * xrange), # xmax - right
bbox[4] + (buffer[4] * yrange) # ymax - top
)
} else {
print("Missed something while writing the funtion.")
}
}

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@ -1,17 +0,0 @@
#' @title Check if variables are in data frame
#'
#' @param df A data frame
#' @param vars A vector of variable names
#'
#' @return A stop statement
check_vars_in_df <- function(df, vars) {
vars_nin <- setdiff(vars, colnames(df))
if (length(vars_nin) > 0) {
rlang::abort(glue::glue(
"Variables ",
glue::glue_collapse(vars_nin, sep = ", ", last = ", and "),
" not found in data frame."
))
}
}

162
R/color.R
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#' Helpers to extract defined colors as hex codes
#'
#' [color()] returns the requested columns, returns NA if absent. [color_pattern()] returns all colors that start with the pattern.
#'
#' @param ... Character names of colors. If NULL returns all colors.
#' @param unname Boolean. Should the output vector be unnamed? Default to `TRUE`.
#' @section Naming of colors:
#' * All branding colors start with "branding";
#' * All , categorical colors start with ", cat_";
#' * All sequential colors start with "seq_";
#'
#' Then, a number indicates the number of colors that belong to the palettes, a string the name of the palette, and, finally, a number the position of the color. E.g., "seq_5_red_4" would be the 4th color of a continuous palettes of 5 colors in the red band. Exception is made for white, light_grey, dark_grey, and black.
#'
#'
#' @return Hex codes named or unnamed.
#'
#' @export
color <- function(..., unname = TRUE) {
#------ Checks
# unname is a logical scalar
checkmate::assert_logical(unname, len = 1)
# all elements in ... are character strings
dots <- list(...)
if (length(dots) > 0) {
# Check each argument is a single character string
for (i in seq_along(dots)) {
checkmate::assert_string(dots[[i]], .var.name = paste0("Argument #", i))
}
}
#------ Prep
# retrieve colors
cols <- c(...)
# define color vector
colors <- c(
white = "#FFFFFF",
lighter_grey = "#F5F5F5",
light_grey = "#E3E3E3",
dark_grey = "#464647",
light_blue_grey = "#B3C6D1",
grey = "#71716F",
black = "#000000",
cat_2_yellow_1 = "#ffc20a",
cat_2_yellow_2 = "#0c7bdc",
cat_2_light_1 = "#fefe62",
cat_2_light_2 = "#d35fb7",
cat_2_green_1 = "#1aff1a",
cat_2_green_2 = "#4b0092",
cat_2_blue_1 = "#1a85ff",
cat_2_blue_2 = "#d41159",
cat_5_main_1 = "#083d77", # yale blue
cat_5_main_2 = "#4ecdc4", # robin egg blue
cat_5_main_3 = "#f4c095", # peach
cat_5_main_4 = "#b47eb3", # african violet
cat_5_main_5 = "#ffd5ff", # mimi pink
seq_5_main_1 = "#083d77", # yale blue
seq_5_main_2 = "##396492",
seq_5_main_3 = "#6b8bad",
seq_5_main_4 = "#9cb1c9",
seq_5_main_5 = "#ced8e4",
cat_5_ibm_1 = "#648fff",
cat_5_ibm_2 = "#785ef0",
cat_5_ibm_3 = "#dc267f",
cat_5_ibm_4 = "#fe6100",
cat_5_ibm_5 = "#ffb000",
cat_3_aquamarine_1 = "aquamarine2",
cat_3_aquamarine_2 = "cornflowerblue",
cat_3_aquamarine_3 = "brown1",
cat_3_tol_high_contrast_1 = "#215589",
cat_3_tol_high_contrast_2 = "#cfaa34",
cat_3_tol_high_contrast_3 = "#a35364",
cat_8_tol_adapted_1 = "#332e86",
cat_8_tol_adapted_2 = "#50504f",
cat_8_tol_adapted_3 = "#3dab9a",
cat_8_tol_adapted_4 = "#86ccee",
cat_8_tol_adapted_5 = "#ddcb77",
cat_8_tol_adapted_6 = "#ee5859",
cat_8_tol_adapted_7 = "#aa4599",
cat_8_tol_adapted_8 = "#721220",
div_5_orange_blue_1 = "#c85200",
div_5_orange_blue_2 = "#e48646",
div_5_orange_blue_3 = "#cccccc",
div_5_orange_blue_4 = "#6b8ea4",
div_5_orange_blue_5 = "#366785",
div_5_green_purple_1 = "#c85200",
div_5_green_purple_2 = "#e48646",
div_5_green_purple_3 = "#cccccc",
div_5_green_purple_4 = "#6b8ea4",
div_5_green_purple_5 = "#366785"
)
#------ Checks
# Check that if ... is not null, all colors are defined
if (!is.null(cols)) {
if (cols %notallin% names(colors)) {
rlang::abort(c(
"Some colors not defined",
"*" = glue::glue_collapse(
...[which(!... %in% names(cols))],
sep = ", ",
last = ", and "
),
"i" = "Use `color(unname = FALSE)` to see all named available colors."
))
}
}
# ------ Return
if (is.null(cols)) {
cols_to_return <- colors
} else {
cols_to_return <- colors[cols]
}
if (unname) {
cols_to_return <- unname(cols_to_return)
}
return(cols_to_return)
}
#' @rdname color
#'
#' @param pattern Pattern of the start of colors' name.
#'
#' @export
color_pattern <- function(pattern, unname = TRUE) {
#------ Checks
# Check that pattern is a character scalar
checkmate::assert_character(pattern, len = 1)
# Check that unname is a logical scalar
checkmate::assert_logical(unname, len = 1)
#------ Get colors
# Get colors
col <- color(unname = FALSE)
col <- col[startsWith(names(col), pattern)]
if (unname) {
col <- unname(col)
}
# If col is of length 0, warn
if (length(col) == 0) {
rlang::warn(c(
"No colors match the pattern",
"*" = glue::glue("Pattern used is:'{pattern}'"),
"i" = "Use `color(unname = FALSE)` to see all named available colors."
))
}
return(col)
}

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#' @title Function to extract AGORA colors as hex codes
#'
#' @param ... Character names of reach colors. If NULL returns all colors
#' @param unnamed Should the output vector be unnamed? Default to `TRUE`
#'
#' @return An hex code or hex codes named or unnamed
#'
#' @details This function needs to be modified to add colors
#'
#' @export
cols_agora <- function(..., unnamed = TRUE) {
cols <- c(...)
colors_agora <- c(white = "#FFFFFF",
black = "#000000",
main_bordeaux = "#581522",
main_lt_beige = "#DDD8C4",
main_dk_beige = "#B7AD99",
main_lt_grey = "#BCB8B1")
if (is.null(cols)) {
cols_to_return <- colors_agora
} else {
cols_to_return <- colors_agora[cols]
}
if(unnamed){
cols_to_return <- unname(cols_to_return)
}
return(cols_to_return)
}

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R/cols_impact.R Normal file
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#' @title Function to extract IMPACT colors as hex codes
#'
#' @param ... Character names of reach colors. If NULL returns all colors
#' @param unnamed Should the output vector be unnamed? Default to `TRUE`
#'
#' @return An hex code or hex codes named or unnamed
#'
#' @details This function needs to be modified to add colors
#'
#' @export
cols_impact <- function(..., unnamed = TRUE) {
cols <- c(...)
colors_impact <- c(white = "#FFFFFF",
black = "#000000",
main_blue = "#315975",
main_gray = "#58585A")
if (is.null(cols)) {
cols_to_return <- colors_impact
} else {
cols_to_return <- colors_impact[cols]
}
if(unnamed){
cols_to_return <- unname(cols_to_return)
}
return(cols_to_return)
}

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#' @title Function to extract REACH colors as hex codes
#'
#' @param ... Character names of reach colors. If NULL returns all colors
#' @param unnamed Should the output vector be unnamed? Default to `TRUE`
#'
#' @return An hex code or hex codes named or unnamed
#'
#' @details This function needs to be modified to add colors
#'
#' @export
cols_reach <- function(..., unnamed = TRUE) {
cols <- c(...)
colors_reach <- c(
white = "#FFFFFF",
black = "#000000",
main_grey = "#58585A",
main_red = "#EE5859",
main_lt_grey = "#C7C8CA",
main_beige = "#D2CBB8",
iroise_1 = "#DFECEF",
iroise_2 = "#B1D7E0",
iroise_3 = "#699DA3",
iroise_4 = "#236A7A",
iroise_5 = "#0C3842",
red_main_1 = "#AE2829",
red_main_2 = "#D05E5F",
red_main_3 = "#DB9797",
red_main_4 = "#EBC7C8",
red_main_5 = "#FAF2F2",
red_alt_1 = "#792a2e",
red_alt_2 = "#c0474a",
red_alt_3 = "#ee5859",
red_alt_4 = "#f49695",
red_alt_5 = "#f8d6d6",
red_alt_na = "#f8f4f4",
lt_grey_1 = "#C6C6C6",
lt_grey_2 = "#818183",
grey3 = "#E3E3E3",
dk_grey = "#464647",
two_dots_1 = "#706441",
two_dots_2 = "#56b4e9",
two_dots_flashy_1 = "gold1",
two_dots_flashy_2 = "blue2",
three_dots_1 = "aquamarine2",
three_dots_2 = "cornflowerblue",
three_dots_3 = "brown1",
orpink = "#f8aa9b",
pink = "#f5a6a7",
lt_pink = "#F9C6C7",
hot_pink = "#ef6d6f",
mddk_red = "#bf4749",
dk_red = "#782c2e",
orange = "#F69E61",
lt_green = "#B0CFAC",
green = "#84A181",
dk_green = "#526450",
red_less_4_1 = "#f6e3e3",
red_less_4_2 = "#f3b5b6",
red_less_4_3 = "#ee5a59",
red_less_4_4 = "#9d393c",
red_5_1 = "#f6e3e3",
red_5_2 = "#f3b5b6",
red_5_3 = "#ee5a59",
red_5_4 = "#c0474a",
red_5_5 = "#792a2e",
red_less_7_1 = "#f8f4f4",
red_less_7_2 = "#f8d6d6",
red_less_7_3 = "#f49695",
red_less_7_4 = "#ee5a59",
red_less_7_5 = "#c0474a",
red_less_7_6 = "#792a2e",
red_less_7_7 = "#471119",
green_2_1 = "#cce5c9",
green_2_2 = "#55a065",
green_3_1 = "#e6f2e0",
green_3_2 = "#7ebf85",
green_3_3 = "#2d8246",
green_4_1 = "#e6f2e1",
green_4_2 = "#b0d3ab",
green_4_3 = "#4bab5e",
green_4_4 = "#0c592e",
green_5_1 = "#e6f2e1",
green_5_2 = "#b0d3ab",
green_5_3 = "#6bb26a",
green_5_4 = "#229346",
green_5_5 = "#0c592e",
green_6_1 = "#e6f2e0",
green_6_2 = "#b0d3ab",
green_6_3 = "#75c376",
green_6_4 = "#086d38",
green_6_5 = "#0c592e",
green_6_6 = "#0d4420",
green_7_1 = "#fafafa",
green_7_2 = "#e6f2e0",
green_7_3 = "#b0d3ab",
green_7_4 = "#75c376",
green_7_5 = "#40ab5d",
green_7_6 = "#086d38",
green_7_7 = "#0d4420",
artichoke_2_1 = "#b6c8b1",
artichoke_2_2 = "#53755f",
artichoke_3_1 = "#e4f1db",
artichoke_3_2 = "#89a087",
artichoke_3_3 = "#455843",
artichoke_4_1 = "#e4f1db",
artichoke_4_2 = "#b5ceb2",
artichoke_4_3 = "#89a087",
artichoke_4_4 = "#465944",
artichoke_5_1 = "#e4f1db",
artichoke_5_2 = "#b5ceb2",
artichoke_5_3 = "#89a087",
artichoke_5_4 = "#60755f",
artichoke_5_5 = "#465944",
artichoke_6_1 = "#fafafa",
artichoke_6_2 = "#e4f1db",
artichoke_6_3 = "#b5ceb2",
artichoke_6_4 = "#89a087",
artichoke_6_5 = "#60755f",
artichoke_6_6 = "#455843",
artichoke_7_1 = "#fafafa",
artichoke_7_2 = "#e4f1db",
artichoke_7_3 = "#b5ceb2",
artichoke_7_4 = "#9fb89c",
artichoke_7_5 = "#89a087",
artichoke_7_6 = "#60755f",
artichoke_7_7 = "#455843",
blue_2_1 = "#7cb6c4",
blue_2_2 = "#286877 ",
blue_3_1 = "#b9d7de",
blue_3_2 = "#5ca4b4",
blue_3_3 = "#286877",
blue_4_1 = "#dfecef",
blue_4_2 = "#8fc1cc",
blue_4_3 = "#3f96aa",
blue_4_4 = "#286877",
blue_5_1 = "#dfecef",
blue_5_2 = "#8fc1cc",
blue_5_3 = "#3f96aa",
blue_5_4 = "#256a7a",
blue_5_5 = "#0c3842",
blue_6_1 = "#f4fbfe",
blue_6_2 = "#cfe4e9",
blue_6_3 = "#77b2bf",
blue_6_4 = "#4096aa",
blue_6_5 = "#256a7a",
blue_6_6 = "#0c3842",
blue_7_1 = "#f4fbfe",
blue_7_2 = "#b3d5de",
blue_7_3 = "#77b2bf",
blue_7_4 = "#4096aa",
blue_7_5 = "#27768a",
blue_7_6 = "#0c596b",
blue_7_7 = "#0c3842"
)
if (is.null(cols)) {
cols_to_return <- colors_reach
} else {
cols_to_return <- colors_reach[cols]
}
if (unnamed) {
cols_to_return <- unname(cols_to_return)
}
return(cols_to_return)
}

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#' Haïti admin 1 centroids shapefile.
#'
#' A multipoint shapefile of Haiti's admin 1.
#'
#' @format A sf multipoint object with 10 features and 9 fields:
#' \describe{
#' \item{ADM1_PC}{Admin 1 postal code.}
#' \item{ADM1_EN}{Full name in English.}
#' \item{ADM1_FR}{Full name in French.}
#' \item{ADM1_HT}{Full name in Haitian Creole.}
#' \item{ADM0_EN}{Country name in English.}
#' \item{ADM0_FR}{Country name in French.}
#' \item{ADM0_HT}{Country name in Haitian Creole.}
#' \item{ADM0_PC}{Country postal code.}
#' \item{ADM1_FR_UPPER}{Admin 1 French name - uppercase.}
#' \item{geometry}{Multipoint geometry.}
#' }
"centroid_admin1"
#' Indicator admin 1 polygons shapefile.
#'
#' A multipolygon shapefile of Haiti's admin 1 with an indicator column 'opn_dfc'.
#'
#' @format A sf multipoint object with 10 features and 10 fields:
#' \describe{
#' \item{ADM1_PC}{Admin 1 postal code.}
#' \item{admin1}{Admin 1 unique id.}
#' \item{opn_dfc}{Proportion of HHs that reported open defecation as sanitation facility.}
#' \item{ADM1_EN}{Full name in English.}
#' \item{ADM1_FR}{Full name in French.}
#' \item{ADM1_HT}{Full name in Haitian Creole.}
#' \item{ADM0_EN}{Country name in English.}
#' \item{ADM0_FR}{Country name in French.}
#' \item{ADM0_HT}{Country name in Haitian Creole.}
#' \item{ADM0_PC}{Country postal code.}
#' \item{geometry}{Multipolygon geometry.}
#' }
"indicator_admin1"
#' Haïti admin 1 lines shapefile.
#'
#' A multiline shapefile of Haiti's admin 1.
#'
#' @format A sf multiline object with 10 features and 8 fields:
#' \describe{
#' \item{ADM1_EN}{Full name in English.}
#' \item{ADM1_FR}{Full name in French.}
#' \item{ADM1_HT}{Full name in Haitian Creole.}
#' \item{ADM0_EN}{Country name in English.}
#' \item{ADM0_FR}{Country name in French.}
#' \item{ADM0_HT}{Country name in Haitian Creole.}
#' \item{ADM0_PCODE}{Country postal code.}
#' \item{geometry}{Multiline geometry.}
#' }
"line_admin1"
#' Haïti border.
#'
#' A multiline shapefile of Haiti's border.
#'
#' @format A sf multiline objet with 1 feature and 6 fields:
#' \describe{
#' \item{fid_1}{fid_1}
#' \item{uno}{uno}
#' \item{count}{count}
#' \item{x_coord}{x_coord}
#' \item{y_coord}{y_coord}
#' \item{area}{area}
#' \item{geometry}{Multiline geometry.}
#' }
"border_admin0"
#' Haïti frontier with Dominican Republic.
#'
#' A multiline shapefile of Haiti's frontier with Dominican Republic.
#'
#' @format A sf multipoint objet with 4 features and 8 fields:
#' \describe{
#' \item{fid_1}{fid_1}
#' \item{objectid}{objectid}
#' \item{id}{id}
#' \item{fromnode}{fromnode}
#' \item{tonode}{tonode}
#' \item{leftpolygo}{leftpolygo}
#' \item{rightpolygo}{rightpolygo}
#' \item{shape_leng}{shape_leng}
#' \item{geometry}{Multiline geometry.}
#' }
"frontier_admin0"

110
R/donut.R Normal file
View file

@ -0,0 +1,110 @@
#' @title Simple donut chart (to be used parsimoniously), can be a pie chart
#'
#' @param df A data frame.
#' @param x A character column or coercible as a character column. Will give the donut's fill color.
#' @param y A numeric column.
#' @param alpha Fill transparency.
#' @param x_title The x scale title. Default to NULL.
#' @param title Plot title. Default to NULL.
#' @param subtitle Plot subtitle. Default to NULL.
#' @param caption Plot caption. Default to NULL.
#' @param arrange TRUE or FALSE. Arrange by highest percentage first.
#' @param hole_size Hole size. Default to 3. If less than 2, back to a pie chart.
#' @param add_text TRUE or FALSE. Add the value as text.
#' @param add_text_threshold_display Minimum value to add the text label.
#' @param add_text_color Text color.
#' @param add_text_suffix If percent is FALSE, should we add a suffix to the text label?
#' @param theme Whatever theme. Default to theme_reach().
#'
#' @return A donut chart to be used parsimoniously
#'
#' @export
donut <- function(df,
x,
y,
alpha = 1,
x_title = NULL,
title = NULL,
subtitle = NULL,
caption = NULL,
arrange = TRUE,
hole_size = 3,
add_text = TRUE,
add_text_threshold_display = 5,
add_text_color = "white",
add_text_suffix = "", theme = theme_reach(legend_reverse = TRUE)){
# Arrange by biggest prop first ?
if (arrange) df <- dplyr::arrange(
df,
{{ y }}
)
# Get levels for scaling
lev <- dplyr::pull(df, {{ x }})
df <- dplyr::mutate(df, "{{x}}" := factor({{ x }}, levels = lev))
# Mapping
g <- ggplot2::ggplot(
df,
mapping = ggplot2::aes(
x = hole_size,
y = {{ y }},
fill = {{ x }},
color = {{ x }}
)
)
# Add rect
g <- g + ggplot2::geom_col(alpha = alpha)
# Add text labels
if (add_text) {
df <- dplyr::mutate(df, y_treshold = ifelse({{ y }} >= add_text_threshold_display, {{ y }}, NA ))
g <- g +
ggplot2::geom_text(
data = df,
ggplot2::aes(
x = hole_size,
y = !!rlang::sym("y_treshold"),
label = paste0({{ y }}, add_text_suffix)),
color = add_text_color,
position = ggplot2::position_stack(vjust = 0.5))
}
# Add title, subtitle, caption, x_title, y_title
g <- g + ggplot2::labs(
title = title,
subtitle = subtitle,
caption = caption,
fill = x_title,
color = x_title
)
# Transform to polar coordinates and adjust hole
g <- g +
ggplot2::coord_polar(
theta = "y"
)
if (hole_size >= 2) g <- g + ggplot2::xlim(c(1, hole_size + 0.5)) # Try to remove that to see how to make a pie chart
# Add theme
g <- g + theme
# No axis
g <- g + ggplot2::theme(
axis.text = ggplot2::element_blank(),
axis.line = ggplot2::element_blank(),
axis.ticks = ggplot2::element_blank(),
axis.title = ggplot2::element_blank()
)
return(g)
}

View file

@ -22,101 +22,57 @@
#' @param add_text_vjust Vertical adjustment.
#' @param add_text_size Text size.
#' @param add_text_color Text color.
#' @param theme_fun A ggplot2 theme, default to `theme_dumbbell()`
#' @param scale_fill_fun A ggplot2 scale_fill function, default to `scale_fill_visualizer_discrete()`
#' @param scale_color_fun A ggplot2 scale_color function, default to `scale_color_visualizer_discrete()`
#' @param theme A ggplot2 theme, default to `theme_reach()`
#'
#' @return A dumbbell chart.
#' @export
#'
dumbbell <- function(
df,
dumbbell <- function(df,
col,
group_x,
group_y,
point_size = 5,
point_alpha = 1,
segment_size = 2.5,
segment_color = color("light_blue_grey"),
segment_color = cols_reach("main_lt_grey"),
group_x_title = NULL,
group_y_title = NULL,
x_title = NULL,
title = NULL,
subtitle = NULL,
caption = NULL,
line_to_y_axis = FALSE,
line_to_y_axis = TRUE,
line_to_y_axis_type = 3,
line_to_y_axis_width = 0.5,
line_to_y_axis_color = color("dark_grey"),
add_text = FALSE,
line_to_y_axis_color = cols_reach("main_grey"),
add_text = TRUE,
add_text_vjust = 2,
add_text_size = 3.5,
add_text_color = color("dark_grey"),
theme_fun = theme_dumbbell(),
scale_fill_fun = scale_fill_visualizer_discrete(),
scale_color_fun = scale_color_visualizer_discrete()
) {
#------ Checks
# df is a data frame
checkmate::assert_data_frame(df)
# col, group_x, group_y are character
checkmate::assert_character(col, len = 1)
checkmate::assert_character(group_x, len = 1)
checkmate::assert_character(group_y, len = 1)
# col, group_x, group_y are columns in df
checkmate::assert_choice(col, colnames(df))
checkmate::assert_choice(group_x, colnames(df))
checkmate::assert_choice(group_y, colnames(df))
# Check numeric/logical values
checkmate::assert_numeric(point_size, len = 1)
checkmate::assert_numeric(point_alpha, lower = 0, upper = 1, len = 1)
checkmate::assert_numeric(segment_size, len = 1)
checkmate::assert_logical(line_to_y_axis, len = 1)
checkmate::assert_numeric(line_to_y_axis_type, len = 1)
checkmate::assert_numeric(line_to_y_axis_width, len = 1)
checkmate::assert_logical(add_text, len = 1)
checkmate::assert_numeric(add_text_vjust, len = 1)
checkmate::assert_numeric(add_text_size, len = 1)
add_text_color = cols_reach("main_grey"),
theme = theme_reach(palette = "primary")){
# Get group keys
group_x_keys <- df |>
dplyr::group_by(!!rlang::sym(group_x)) |>
dplyr::group_by({{ group_x }}) |>
dplyr::group_keys() |>
dplyr::pull()
# Check if only two groups
if (length(group_x_keys) > 2) {
rlang::abort(
"Cannot draw a dumbbell plot for `group_x` with more than 2 groups"
)
}
if (length(group_x_keys) > 2) rlang::abort("Cannot draw a dumbbell plot for `group_x` with more than 2 groups")
# Pivot long data
df_pivot <- df |>
tidyr::pivot_wider(
id_cols = c(!!rlang::sym(group_y)),
values_from = !!rlang::sym(col),
names_from = !!rlang::sym(group_x)
id_cols = c({{ group_y}}),
values_from = {{ col }},
names_from = {{ group_x }}
)
df_pivot <- df_pivot |>
dplyr::rowwise() |>
dplyr::mutate(
min = min(
!!rlang::sym(group_x_keys[[1]]),
!!rlang::sym(group_x_keys[[2]]),
na.rm = T
),
max = max(
!!rlang::sym(group_x_keys[[1]]),
!!rlang::sym(group_x_keys[[2]]),
na.rm = T
)
) |>
min = min(!!rlang::sym(group_x_keys[[1]]), !!rlang::sym(group_x_keys[[2]]), na.rm = T),
max = max(!!rlang::sym(group_x_keys[[1]]), !!rlang::sym(group_x_keys[[2]]), na.rm = T)) |>
dplyr::ungroup() |>
dplyr::mutate(diff = max - min)
@ -124,20 +80,19 @@ dumbbell <- function(
# Add line
if(line_to_y_axis) {
xend <- min(dplyr::pull(df, !!rlang::sym(col)))
xend <- min(dplyr::pull(df, {{ col }}))
g <- g +
ggplot2::geom_segment(
ggplot2::aes(
x = min,
y = !!rlang::sym(group_y),
yend = !!rlang::sym(group_y)
),
y = {{ group_y }},
yend = {{ group_y }}),
xend = xend,
linetype = line_to_y_axis_type,
linewidth = line_to_y_axis_width,
color = line_to_y_axis_color
)
size = line_to_y_axis_width,
color = line_to_y_axis_color)
}
# Add segment
@ -145,11 +100,10 @@ dumbbell <- function(
ggplot2::geom_segment(
ggplot2::aes(
x = !!rlang::sym(group_x_keys[[1]]),
y = !!rlang::sym(group_y),
y = {{ group_y }},
xend = !!rlang::sym(group_x_keys[[2]]),
yend = !!rlang::sym(group_y)
),
linewidth = segment_size,
yend = {{ group_y }}),
size = segment_size,
color = segment_color
)
@ -158,18 +112,17 @@ dumbbell <- function(
ggplot2::geom_point(
data = df,
ggplot2::aes(
x = !!rlang::sym(col),
y = !!rlang::sym(group_y),
color = !!rlang::sym(group_x),
fill = !!rlang::sym(group_x)
x = {{ col }},
y = {{ group_y }},
color = {{ group_x }},
fill = {{ group_x }}
),
size = point_size,
alpha = point_alpha
)
# Add title, subtitle, caption, x_title, y_title
g <- g +
ggplot2::labs(
g <- g + ggplot2::labs(
title = title,
subtitle = subtitle,
caption = caption,
@ -180,32 +133,29 @@ dumbbell <- function(
)
# Add stat labels to points
if (add_text) {
g <- g +
if(add_text) g <- g +
ggrepel::geom_text_repel(
data = df,
ggplot2::aes(
x = !!rlang::sym(col),
y = !!rlang::sym(group_y),
label = !!rlang::sym(col)
x = {{ col }},
y = {{ group_y}},
label = {{ col }}
),
vjust = add_text_vjust,
size = add_text_size,
color = add_text_color
)
}
# Expan y axis
# g <- g +
# ggplot2::scale_y_discrete(
# group_y_title,
# expand = c(0, 0))
# Add theme
g <- g + theme_fun
# Add scale fun
if (!is.null(scale_fill_fun)) {
g <- g + scale_fill_fun
}
if (!is.null(scale_color_fun)) {
g <- g + scale_color_fun
}
g <- g + theme
return(g)
}

View file

@ -1,25 +1,477 @@
# not in
#' Not In Operator
#' @title Abord bad argument
#'
#' A negation of the `%in%` operator that tests if elements of `a` are not in `b`.
#' @param arg An argument
#' @param must What arg must be
#' @param not Optional. What arg must not be.
#'
#' @param a Vector or value to test
#' @param b Vector to test against
#'
#' @return Logical vector with TRUE for elements of `a` that are not in `b`
`%notin%` <- function(a, b) {
!(a %in% b)
#' @return A stop statement
abort_bad_argument <- function(arg, must, not = NULL) {
msg <- glue::glue("`{arg}` must {must}")
if (!is.null(not)) {
not <- typeof(not)
msg <- glue::glue("{msg}; not {not}.")
}
# not all in
#' Not All In Operator
#'
#' Tests if not all elements of `a` are contained in `b`.
#'
#' @param a Vector to test
#' @param b Vector to test against
#'
#' @return TRUE if at least one element of `a` is not in `b`, otherwise FALSE
`%notallin%` <- function(a, b) {
!(all(a %in% b))
rlang::abort("error_bad_argument",
message = msg,
arg = arg,
must = must,
not = not
)
}
#' @title Stop statement "If not in colnames" with colnames
#'
#' @param .tbl A tibble
#' @param cols A vector of column names (quoted)
#' @param df Provide the tibble name as a character string
#' @param arg Default to NULL.
#'
#' @return A stop statement
if_not_in_stop <- function(.tbl, cols, df, arg = NULL) {
if (is.null(arg)) {
msg <- glue::glue("The following column/s is/are missing in `{df}`:")
} else {
msg <- glue::glue("The following column/s from `{arg}` is/are missing in `{df}`:")
}
if (!all(cols %in% colnames(.tbl))) {
rlang::abort(
c("Missing columns",
"*" =
paste(
msg,
paste(
subvec_not_in(cols, colnames(.tbl)),
collapse = ", "
)
)
)
)
}
}
#' @title Stop statement "If not in vector"
#'
#' @param vec A vector of character strings
#' @param cols A set of character strings
#' @param vec_name Provide the vector name as a character string
#' @param arg Default to NULL.
#'
#' @return A stop statement if some elements of vec are not in cols
if_vec_not_in_stop <- function(vec, cols, vec_name, arg = NULL) {
if (is.null(arg)) {
msg <- glue::glue("The following element/s is/are missing in `{vec_name}`:")
} else {
msg <- glue::glue("The following element/s from `{arg}` is/are missing in `{vec_name}`:")
}
if (!all(cols %in% vec)) {
rlang::abort(
c("Missing elements",
"*" =
paste(
msg,
paste(
subvec_not_in(cols, vec),
collapse = ", "
)
)
)
)
}
}
#' @title Subvec not in
#'
#' @param vector A vector to subset
#' @param set A set-vector
#'
#' @return A subset of vector not in set
subvec_not_in <- function(vector, set) {
vector[!(vector %in% set)]
}
# Map helpers -------------------------------------------------------------
# Thanks to https://github.com/r-tmap/tmap/blob/master/R/map_num2pal.R
pretty_count <- function(x, n, ...) {
x <- na.omit(x)
if (!length(x)) {
return(x)
}
if (!is.integer(x)) x <- as.integer(x)
mn <- min(x)
mx <- max(x)
any0 <- any(x == 0)
if (mn < 0) {
n <- floor(n / 2)
pneg <- -rev(pretty_count(-x[x < 0], n = n, ...)) + 1L
pneg <- pneg[pneg != 0L]
x <- x[x > 0]
any0 <- TRUE
} else {
pneg <- integer()
}
if (any0) x <- x[x != 0L]
p <- pretty(x - 1L, n = n, ...) + 1L
p <- p[(p %% 1) == 0]
p <- p[p != 0L]
if (length(x) < 2) {
if (any0) {
return(c(0L, p))
} else {
return(p)
}
}
step <- p[2] - p[1]
if (p[length(p)] == mx) p <- c(p, mx + step)
if (any0) {
c(pneg, 0L, p)
} else {
c(pneg, p)
}
}
breaks <- pretty_count(indicator_admin1$opn_dfc, n = 5)
style <- "fixed"
#
q <- num2breaks(indicator_admin1$opn_dfc, n = 5, style = style, breaks = breaks, interval.closure = "left", var = var, as.count = T, args = style.args)
breaks_n <- function(breaks, as_count = TRUE)
fancy_breaks(breaks, intervals = TRUE, as.count = TRUE)
fancy_breaks <- function(vec, as.count = FALSE, intervals=FALSE, interval.closure="left", fun=NULL, scientific=FALSE, big.num.abbr = c("mln" = 6, "bln" = 9), prefix = "", suffix = "", text.separator="to", text.less.than=c("less", "than"), text.or.more=c("or", "more"), text.align="left", text.to.columns=FALSE, digits=NA, html.escape = TRUE, ...) {
args <- list(...)
n <- length(vec)
if (!is.null(fun)) {
x <- do.call(fun, list(vec))
} else if (all(is.infinite(vec))) {
x <- as.character(vec)
} else {
# calculate magnitude, needed to determine digits and big number abbreviations
vec_fin <- unique(vec[!is.infinite(vec)])
frm <- gsub(" ", "", sprintf("%20.10f", abs(vec_fin)))
mag <- max(nchar(frm)-11)
if (as.count) {
steps <- (vec[-1] - vec[-n])
vec <- c(vec, vec - 1L, vec + 1L) # needed for: {1, 2, ... 9}
digits <- 0
} else {
# get number of decimals (which is number of decimals in vec, which is reduced when mag is large)
ndec <- max(10 - nchar(frm) + nchar(sub("0+$","",frm)))
if (is.na(digits)) {
digits <- max(min(ndec, 4-mag), 0)
# add sign to frm
frm_sign <- unique(paste0(ifelse(vec_fin<0, "-", "+"), frm))
# test if number of digits is sufficient for unique labels
if (!scientific) {
while (anyDuplicated(substr(frm_sign, 1, nchar(frm_sign)-10 + digits)) && (digits < 10)) {
digits <- digits + 1
}
}
}
}
if (!scientific || as.count) {
# check whether big number abbrevations should be used
ext <- ""
if (!is.na(big.num.abbr[1])) {
big.num.abbr <- sort(big.num.abbr, decreasing = TRUE)
for (i in 1:length(big.num.abbr)) {
o <- unname(big.num.abbr[i])
if (mag>(o+2) || (mag > o && all(vec - floor(vec/(10^o))*(10^o) < 1))) {
vec <- vec / (10^o)
ext <- paste0(" ", names(big.num.abbr)[i])
break
}
}
}
# set default values
if (!("big.mark" %in% names(args))) args$big.mark <- ","
if (!("format" %in% names(args))) args$format <- "f"
if (!("preserve.width" %in% names(args))) args$preserve.width <- "none"
x <- paste(do.call("formatC", c(list(x=vec, digits=digits), args)), ext, sep="")
x <- paste0(prefix, x, suffix)
} else {
if (!("format" %in% names(args))) args$format <- "g"
x <- do.call("formatC", c(list(x=vec, digits=digits), args))
}
if (as.count) {
x1 <- x[1:(n-1)]
x2 <- x[(n+2):(2*n)]
x1p1 <- x[(2*n+1):(3*n-1)]
}
# x <- formatC(vec, format = "f", digits = 0)
# x1 <- x[-n]
# x2 <- formatC(vec[-1] - 1L, format = "f", digits = 0)
# xs <- (vec[-1] - vec[-n])
# x1p1 <- formatC(vec[-n] + 1L, format = "f", digits = 0)
}
if (intervals) {
if (scientific) {
if (as.count) {
# discrete
lbls <- paste("{", x1, "}", sep = "")
lbls[steps == 2] <- paste("{", x1[steps == 2], ", ", x2[steps == 2], "}", sep="")
lbls[steps > 2] <- paste("{", x1[steps > 2], ", ", x1p1[steps > 2], ", ..., ", x2[steps > 2], "}", sep="")
} else {
# continuous
if (interval.closure=="left") {
lbls <- paste("[", x[-n], ", ", x[-1], ")", sep="")
lbls[n-1] <- paste(substr(lbls[n-1], 1, nchar(lbls[n-1])-1), "]", sep="")
} else {
lbls <- paste("(", x[-n], ", ", x[-1], "]", sep="")
lbls[1] <- paste("[", substr(lbls[1], 2, nchar(lbls[1])), sep="")
}
}
} else {
if (as.count) {
lbls <- x1
lbls[steps>1] <- paste(x1[steps>1], x2[steps>1], sep = paste0(" ", text.separator, " "))
if (vec[n]==Inf) lbls[n-1] <- paste(x1[n-1], paste(text.or.more, collapse = " "), sep = " ")
} else {
x[vec==-Inf] <- ""
lbls <- paste(x[-n], x[-1], sep = paste0(" ", text.separator, " "))
if (vec[1]==-Inf) lbls[1] <- paste(paste(text.less.than, collapse = " "), x[2], sep = " ")
if (vec[n]==Inf) lbls[n-1] <- paste(x[n-1], paste(text.or.more, collapse = " "), sep = " ")
}
if (text.to.columns) {
#xtra <- as.numeric(!is.na(text.align) && text.align=="right")
nc1 <- nchar(paste(x[-n], " ", sep = "")) + 1
nc2 <- rep(nchar(paste(text.separator, " ", sep = "")), n-1)
lbls_breaks <- matrix(c(nc1, nc1+nc2), ncol=2)
if (vec[1]==-Inf) {
if (length(text.less.than)==1) {
lbls_breaks[1,] <- rep(nchar(paste(text.less.than[1], " ", sep = "")) + 1, 2)
} else {
lbls_breaks[1,] <- cumsum(c(nchar(paste(text.less.than[1], " ", sep = "")) + 1, nchar(text.less.than[2])+1))
}
}
if (vec[n]==Inf) {
if (length(text.or.more)==1) {
lbls_breaks[n-1,] <- rep(nchar(paste(x[n-1], " ", sep = "")) + 1, 2)
} else {
lbls_breaks[n-1,] <- cumsum(c(nchar(paste(x[n-1], " ", sep = "")) + 1, nchar(text.or.more[1])+1))
}
}
attr(lbls, "brks") <- lbls_breaks
}
}
}
y <- if (intervals) lbls else x
attr(y, "align") <- text.align
y
}
num2breaks <- function(x, n, style, breaks, approx=FALSE, interval.closure="left", var = NULL, as.count = FALSE, args = list()) {
tmapOptions = get("tmapOptions", envir = .TMAP_CACHE)
show.warnings <- tmapOptions$show.warnings
nobs <- sum(!is.na(x))
# create intervals and assign colors
if (style=="fixed") {
q <- list(var=x,
brks=breaks)
if (any(na.omit(x) < min(breaks)) && show.warnings) warning("Values have found that are less than the lowest break", call. = FALSE)
if (any(na.omit(x) > max(breaks)) && show.warnings) warning("Values have found that are higher than the highest break", call. = FALSE)
attr(q, "style") <- "fixed"
attr(q, "nobs") <- nobs
attr(q, "intervalClosure") <- interval.closure
class(q) <- "classIntervals"
} else {
if (nobs==0) {
if (!is.null(var)) {
stop("Numerical variable \"", var, "\" only contains missing values.", call.=FALSE)
} else {
stop("Numerical variable only contains missing values.", call.=FALSE)
}
}
nunique <- length(na.omit(unique(x)))
if (nunique == 1 && style!="pretty" && show.warnings) {
if (!is.null(var)) {
warning("Single unique value found for the variable \"", var, "\", so style set to \"pretty\"", call. = FALSE)
} else {
warning("Single unique value found, so style set to \"pretty\"", call. = FALSE)
}
}
tempx <- nunique <= n
if (tempx) {
x_orig <- x
if (length(na.omit(unique(x))) == 1) x <- pretty(x)
x <- seq(min(x, na.rm = TRUE), max(x, na.rm = TRUE), length.out = n + 1)
}
q <- suppressWarnings(do.call(classInt::classIntervals, c(list(x, n, style= style, intervalClosure=interval.closure), args)))
if (tempx) q$var <- x_orig
}
if (approx && style != "fixed") {
if (n >= length(unique(x)) && style=="equal") {
# to prevent classIntervals to set style to "unique"
q <- list(var=x, brks=seq(min(x, na.rm=TRUE), max(x, na.rm=TRUE), length.out=n))
attr(q, "intervalClosure") <- interval.closure
class(q) <- "classIntervals"
} else {
brks <- q$brks
# to prevent ugly rounded breaks such as -.5, .5, ..., 100.5 for n=101
qm1 <- suppressWarnings(do.call(classInt::classIntervals, c(list(x, n-1, style= style, intervalClosure=interval.closure), args)))
brksm1 <- qm1$brks
qp1 <- suppressWarnings(do.call(classInt::classIntervals, c(list(x, n+1, style= style, intervalClosure=interval.closure), args)))
brksp1 <- qp1$brks
if (min(brksm1) > min(brks) && max(brksm1) < max(brks)) {
q <- qm1
} else if (min(brksp1) > min(brks) && max(brksp1) < max(brks)) {
q <- qp1
}
}
}
q
}
cont_breaks <- function(breaks, n=101) {
x <- round(seq(1, 101, length.out=length(breaks)))
unlist(lapply(1L:(length(breaks)-1L), function(i) {
y <- seq(breaks[i], breaks[i+1], length.out=x[i+1]-x[i]+1)
if (i!=1) y[-1] else y
}), use.names = FALSE)
}
num2breaks <- function(x, n, style = "fixed", breaks, approx = FALSE, interval.closure = "left", var = NULL, as.count = FALSE, args = list()) {
show.warnings <- TRUE
nobs <- sum(!is.na(x))
# create intervals and assign colors
if (style == "fixed") {
q <- list(
var = x,
brks = breaks
)
if (any(na.omit(x) < min(breaks)) && show.warnings) warning("Values have found that are less than the lowest break", call. = FALSE)
if (any(na.omit(x) > max(breaks)) && show.warnings) warning("Values have found that are higher than the highest break", call. = FALSE)
attr(q, "style") <- "fixed"
attr(q, "nobs") <- nobs
attr(q, "intervalClosure") <- interval.closure
class(q) <- "classIntervals"
} else {
if (nobs == 0) {
if (!is.null(var)) {
stop("Numerical variable \"", var, "\" only contains missing values.", call. = FALSE)
} else {
stop("Numerical variable only contains missing values.", call. = FALSE)
}
}
nunique <- length(na.omit(unique(x)))
if (nunique == 1 && style != "pretty" && show.warnings) {
if (!is.null(var)) {
warning("Single unique value found for the variable \"", var, "\", so style set to \"pretty\"", call. = FALSE)
} else {
warning("Single unique value found, so style set to \"pretty\"", call. = FALSE)
}
}
tempx <- nunique <= n
if (tempx) {
x_orig <- x
if (length(na.omit(unique(x))) == 1) x <- pretty(x)
x <- seq(min(x, na.rm = TRUE), max(x, na.rm = TRUE), length.out = n + 1)
}
q <- suppressWarnings(do.call(classInt::classIntervals, c(list(x, n, style = style, intervalClosure = interval.closure), args)))
if (tempx) q$var <- x_orig
}
if (approx && style != "fixed") {
if (n >= length(unique(x)) && style == "equal") {
# to prevent classIntervals to set style to "unique"
q <- list(var = x, brks = seq(min(x, na.rm = TRUE), max(x, na.rm = TRUE), length.out = n))
attr(q, "intervalClosure") <- interval.closure
class(q) <- "classIntervals"
} else {
brks <- q$brks
# to prevent ugly rounded breaks such as -.5, .5, ..., 100.5 for n=101
qm1 <- suppressWarnings(do.call(classInt::classIntervals, c(list(x, n - 1, style = style, intervalClosure = interval.closure), args)))
brksm1 <- qm1$brks
qp1 <- suppressWarnings(do.call(classInt::classIntervals, c(list(x, n + 1, style = style, intervalClosure = interval.closure), args)))
brksp1 <- qp1$brks
if (min(brksm1) > min(brks) && max(brksm1) < max(brks)) {
q <- qm1
} else if (min(brksp1) > min(brks) && max(brksp1) < max(brks)) {
q <- qp1
}
}
}
q
}
breaks[length(breaks)] <- breaks[length(breaks)] + 1L

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@ -1,338 +1,121 @@
#' @rdname lollipop
#'
#' @inheritParams lollipop
#' @param ... Additional arguments passed to `lollipop()`
#'
#' @export
hlollipop <- function(
...,
flip = TRUE,
theme_fun = theme_lollipop(flip = flip)) {
lollipop(flip = flip, theme_fun = theme_fun, ...)
}
#' Simple lollipop chart
#'
#' @description
#' `lollipop()` is a simple lollipop chart (dots connected to the baseline by a segment) with some customization allowed.
#' `hlollipop()` uses `lollipop()` with sane defaults for a horizontal lollipop chart.
#' @title Simple bar chart
#'
#' @param df A data frame.
#' @param x A quoted character column or coercible as a character column.
#' @param y A quoted numeric column.
#' @param group Some quoted grouping categorical column, e.g. administrative areas or population groups.
#' @param facet Some quoted grouping categorical column, e.g. administrative areas or population groups.
#' @param x_rm_na Remove NAs in x?
#' @param y_rm_na Remove NAs in y?
#' @param group_rm_na Remove NAs in group?
#' @param facet_rm_na Remove NAs in facet?
#' @param y_expand Multiplier to expand the y axis.
#' @param add_color Add a color to dots (if no grouping).
#' @param add_color_guide Should a legend be added?
#' @param flip TRUE or FALSE (default). Default to TRUE or horizontal lollipop plot.
#' @param x A numeric column.
#' @param y A character column or coercible as a character column.
#' @param flip TRUE or FALSE. Default to TRUE or horizontal lollipop plot.
#' @param wrap Should x-labels be wrapped? Number of characters.
#' @param alpha Fill transparency for dots.
#' @param arrange TRUE or FALSE. Arrange by highest percentage first.
#' @param point_size Point size.
#' @param point_color Point color.
#' @param point_alpha Point alpha.
#' @param segment_size Segment size.
#' @param segment_color Segment color.
#' @param segment_alpha Segment alpha.
#' @param alpha Fill transparency.
#' @param x_title The x scale title. Default to NULL.
#' @param y_title The y scale title. Default to NULL.
#' @param group_title The group legend title. Default to NULL.
#' @param title Plot title. Default to NULL.
#' @param subtitle Plot subtitle. Default to NULL.
#' @param caption Plot caption. Default to NULL.
#' @param dot_size The size of the dots.
#' @param line_size The size/width of the line connecting dots to the baseline.
#' @param line_color The color of the line connecting dots to the baseline.
#' @param dodge_width Width for position dodge when using groups (controls space between grouped lollipops).
#' @param theme_fun Whatever theme function. For no custom theme, use theme_fun = NULL.
#' @param scale_fill_fun Scale fill function. Default to scale_fill_visualizer_discrete().
#' @param scale_color_fun Scale color function. Default to scale_color_visualizer_discrete().
#' @param add_text TRUE or FALSE. Add the y value as text within the bubble.
#' @param add_text_size Text size.
#' @param add_text_suffix If percent is FALSE, should we add a suffix to the text label?
#' @param add_text_color Added text color. Default to white.
#' @param add_text_fontface Added text font face. Default to "bold".
#' @param theme Whatever theme. Default to theme_reach().
#'
#' @return A bar chart
#'
#' @inheritParams reorder_by
#'
#' @importFrom rlang `:=`
#'
#' @return A ggplot object
#' @export
#' @examples
#' \dontrun{
#' df <- data.frame(x = letters[1:5], y = c(10, 5, 7, 12, 8))
#' # Vertical lollipop
#' lollipop(df, "x", "y")
#' # Horizontal lollipop
#' hlollipop(df, "x", "y")
#' }
lollipop <- function(
df,
lollipop <- function(df,
x,
y,
group = "",
facet = "",
order = "y",
x_rm_na = TRUE,
y_rm_na = TRUE,
group_rm_na = TRUE,
facet_rm_na = TRUE,
y_expand = 0.1,
add_color = color("cat_5_main_1"),
add_color_guide = TRUE,
flip = FALSE,
flip = TRUE,
wrap = NULL,
arrange = TRUE,
point_size = 3,
point_color = cols_reach("main_red"),
point_alpha = 1,
segment_size = 1,
segment_color = cols_reach("main_grey"),
segment_alpha = 1,
alpha = 1,
x_title = NULL,
y_title = NULL,
group_title = NULL,
title = NULL,
subtitle = NULL,
caption = NULL,
dot_size = 4,
line_size = 0.8,
line_color = color("dark_grey"),
dodge_width = 0.9,
theme_fun = theme_lollipop(
flip = flip,
axis_text_x_angle = 0,
axis_text_x_vjust = 0.5,
axis_text_x_hjust = 0.5
),
scale_fill_fun = scale_fill_visualizer_discrete(),
scale_color_fun = scale_color_visualizer_discrete()) {
#------ Checks
add_text = FALSE,
add_text_size = 3,
add_text_suffix = "",
add_text_color = "white",
add_text_fontface = "bold",
theme = theme_reach()){
# df is a data frame
checkmate::assert_data_frame(df)
# x and y and group are character
checkmate::assert_character(x, len = 1)
checkmate::assert_character(y, len = 1)
checkmate::assert_character(group, len = 1)
checkmate::assert_character(facet, len = 1)
# x and y are columns in df
checkmate::assert_choice(x, colnames(df))
checkmate::assert_choice(y, colnames(df))
if (group != "") {
checkmate::assert_choice(group, colnames(df))
}
if (facet != "") {
checkmate::assert_choice(facet, colnames(df))
}
# x_rm_na, y_rm_na and group_rm_na are logical scalar
checkmate::assert_logical(x_rm_na, len = 1)
checkmate::assert_logical(y_rm_na, len = 1)
checkmate::assert_logical(group_rm_na, len = 1)
checkmate::assert_logical(facet_rm_na, len = 1)
# flip is a logical scalar
checkmate::assert_logical(flip, len = 1)
# dodge_width is a numeric scalar
checkmate::assert_numeric(dodge_width, len = 1, lower = 0)
# wrap is a numeric scalar or NULL
if (!is.null(wrap)) {
checkmate::assert_numeric(wrap, len = 1, null.ok = TRUE)
}
# alpha is a numeric scalar between 0 and 1
checkmate::assert_numeric(alpha, lower = 0, upper = 1, len = 1)
# dot_size is a numeric scalar
checkmate::assert_numeric(dot_size, len = 1)
# line_size is a numeric scalar
checkmate::assert_numeric(line_size, len = 1)
# order is a character scalar in valid choices
checkmate::assert_choice(order, c("none", "y", "grouped_y", "x", "grouped_x"))
# x and y are numeric or character
if (class(df[[y]]) %notin% c("integer", "numeric")) {
rlang::abort(paste0(y, " must be numeric."))
}
if (!any(class(df[[x]]) %in% c("character", "factor"))) {
rlang::abort(paste0(x, " must be character or factor"))
}
#----- Data wrangling
# facets over group
if (group != "" && facet != "" && group == facet) {
rlang::warn("'group' and 'facet' are the same identical.")
}
# remove NAs using base R
if (x_rm_na) {
df <- df[!(is.na(df[[x]])), ]
}
if (y_rm_na) {
df <- df[!(is.na(df[[y]])), ]
}
if (group != "" && group_rm_na) {
df <- df[!(is.na(df[[group]])), ]
}
if (facet != "" && facet_rm_na) {
df <- df[!(is.na(df[[facet]])), ]
}
# reorder
dir_order <- if (flip && order %in% c("x", "grouped_x")) {
-1
} else if (!flip && order %in% c("x", "grouped_x")) {
1
} else if (flip) {
1
} else {
-1
}
group_order <- if (group != "" || (group == "" && facet == "")) {
group
} else if (group == "" && facet != "") {
facet
}
df <- reorder_by(
df = df,
x = x,
y = y,
group = group_order,
order = order,
dir_order = dir_order
# Arrange by biggest prop first ?
if (arrange) df <- dplyr::arrange(
df,
{{ y }}
)
# prepare aes
if (group != "") {
# Get levels for scaling
lev <- dplyr::pull(df, {{ x }})
df <- dplyr::mutate(df, "{{x}}" := factor({{ x }}, levels = lev))
# Mapping
g <- ggplot2::ggplot(
df,
mapping = ggplot2::aes(
x = !!rlang::sym(x),
y = !!rlang::sym(y),
fill = !!rlang::sym(group),
color = !!rlang::sym(group)
)
)
} else {
g <- ggplot2::ggplot(
df,
mapping = ggplot2::aes(
x = !!rlang::sym(x),
y = !!rlang::sym(y)
)
)
}
# add title, subtitle, caption, x_title, y_title
g <- g +
ggplot2::labs(
title = title,
subtitle = subtitle,
caption = caption,
x = y_title,
y = x_title,
color = group_title,
fill = group_title
mapping = ggplot2::aes(x = {{ x }}, y = {{ y }}, xend = {{ x }}, yend = 0)
)
# facets
if (facet != "") {
if (flip) {
g <- g +
ggplot2::facet_grid(
rows = ggplot2::vars(!!rlang::sym(facet)),
scales = "free",
space = "free_y"
# Add segment
g <- g + ggplot2::geom_segment(
linewidth = segment_size,
alpha = segment_alpha,
color = segment_color
)
} else {
g <- g +
ggplot2::facet_grid(
cols = ggplot2::vars(!!rlang::sym(facet)),
scales = "free",
space = "free_x"
)
}
}
# Add segments and points
if (group != "") {
# With grouping - use position_dodge for side-by-side display
position_dodge_obj <- ggplot2::position_dodge(width = dodge_width)
g <- g +
ggplot2::geom_linerange(
mapping = ggplot2::aes(
ymin = 0,
ymax = !!rlang::sym(y),
group = !!rlang::sym(group)
),
position = position_dodge_obj,
color = line_color,
linewidth = line_size
) +
ggplot2::geom_point(
position = position_dodge_obj,
size = dot_size,
alpha = alpha
g <- g + ggplot2::geom_point(
size = point_size,
alpha = point_alpha,
color = point_color
)
} else {
# Without grouping
g <- g +
ggplot2::geom_linerange(
mapping = ggplot2::aes(
ymin = 0,
ymax = !!rlang::sym(y)
),
color = line_color,
linewidth = line_size
) +
ggplot2::geom_point(
size = dot_size,
alpha = alpha,
color = add_color,
fill = add_color
)
}
# wrap labels on the x scale?
if (!is.null(wrap)) {
g <- g + ggplot2::scale_x_discrete(labels = scales::label_wrap(wrap))
}
# flip coordinates if needed
# Because a text legend should always be horizontal, especially for an horizontal bar graph
if (flip){
g <- g + ggplot2::coord_flip()
}
# y scale tweaks
g <- g +
ggplot2::scale_y_continuous(
# start at 0
expand = ggplot2::expansion(mult = c(0, y_expand)),
# remove trailing 0 and choose accuracy of y labels
labels = scales::label_number(
accuracy = 0.1,
drop0trailing = TRUE,
big.mark = "",
decimal.mark = "."
),
# Add text labels
if (add_text) {
g <- g + ggplot2::geom_text(
ggplot2::aes(
label = paste0({{ y }}, add_text_suffix)),
size = add_text_size,
color = add_text_color,
fontface = add_text_fontface)
}
# Add title, subtitle, caption, x_title, y_title
g <- g + ggplot2::labs(
title = title,
subtitle = subtitle,
caption = caption,
x = x_title,
y = y_title,
)
# remove guides for legend if !add_color_guide
if (!add_color_guide) {
g <- g + ggplot2::guides(fill = "none", color = "none")
}
# add theme fun
if (!is.null(theme_fun)) {
g <- g + theme_fun
}
# add scale fun
if (!is.null(scale_fill_fun)) {
g <- g + scale_fill_fun
}
if (!is.null(scale_color_fun)) {
g <- g + scale_color_fun
}
# Add theme
g <- g + theme
return(g)
}

355
R/map.R Normal file
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@ -0,0 +1,355 @@
#' Wrapper around `ggplot2::geom_sf()` with sane defaults for plotting choropleth
#'
#' @param poly Multipolygon shape defined by sf package.
#' @param col Numeric attribute to map.
#' @param n The desire number of classes.
#' @param initiative One of "reach", "agora", or "default"
#' @param palette Vector of fill colors as hexadecimal values. For REACH color palettes, it is possible to use `pal_reach()`. For now,'palette' must be changed manually, accordingly to the number of drawn classes.
#' @param style Method to process the color scale for continuous numerical variables. See `classInt::classIntervals()` for details.
#' @param intervals Boolean. TRUE, let's make classes. FALSE, let's use a gradient.
#' @param font_family Font family.
#' @param legend_title Legend title.
#' @param legend_positin Legend position.
#' @param drop Boolean. Drop missing data?
#' @param text_na Legend text for missing data.
#' @param color_na Fill color for missing data.
#'
#' @return A ggplot base choropleth.
#'
#' @export
add_indicator_layer <- function(poly,
col,
n = 5,
initiative = "reach",
palette = "red_5",
style = "pretty",
intervals = TRUE,
font_family = "segoeui",
legend_title = "Proportion (%)",
legend_position = c(0, 0.95),
drop = FALSE,
text_na = "Missing data",
color_na = cols_reach("white")){
#------ Checks and make valid
poly <- sf::st_make_valid(poly)
#------ Other checks
col_name <- rlang::as_name(rlang::enquo(col))
if_not_in_stop(poly, col_name, "poly", "col")
if (!is.numeric(poly[[col_name]])) rlang::abort(glue::glue("{col_name} is not numeric."))
#------ Prepare data
if (intervals) {
classes <- classInt::classIntervals(poly[[col_name]], n = n, style = style)
col_class_name <- paste0(col_name, "_class")
poly <- poly |>
dplyr::mutate("{col_class_name}" := cut({{ col }}, classes$brks, include.lowest = TRUE))
legend_labels <- c(levels(poly[[col_class_name]]), text_na)
discrete <- TRUE
layer <- ggplot2::ggplot() +
ggplot2::geom_sf(data = poly, ggplot2::aes(fill = !!rlang::sym(col_class_name)), color = "transparent") +
scale_fill(initiative = initiative, palette = palette, discrete = discrete, reverse_guide = FALSE, name = legend_title, labels = legend_labels, drop = drop, na.value = color_na)
} else {
discrete <- FALSE
layer <- ggplot2::ggplot() +
ggplot2::geom_sf(data = poly, ggplot2::aes(fill = !!rlang::sym(col_name)), color = "transparent") +
scale_fill(initiative = initiative, palette = palette, discrete = discrete, reverse_guide = FALSE, name = legend_title, na.value = color_na)
}
#------ Make map layer
layer <- layer +
ggplot2::theme_void() +
ggplot2::theme(
# legend.justification defines the edge of the legend that the legend.position coordinates refer to
legend.justification = c(0, 1),
# Set the legend flush with the left side of the plot, and just slightly below the top of the plot
legend.position = legend_position,
# Set fontfamily
text = ggplot2::element_text(family = font_family)
)
return(layer)
}
#' Add admin boundaries (lines) and the legend
#'
#' @param map Is there a previous map layer? Default to NULL.
#' @param lines List of multiline shape defined by sf package.
#' @param colors Vector of hexadecimal codes. Same order as lines.
#' @param labels Vector of labels in the legend. Same order as lines.
#' @param lwds Vector of line widths. Same order as lines.
#' @param title Legend title.
#' @param buffer A buffer, either one value or a vector of 4 values (left, bottom, right, top).
#' @param ... Other arguments to pass to each shape in `tmap::tm_lines()`.
#'
#' @return A tmap layer.
#' @export
#'
add_admin_boundaries <- function(map = NULL, lines, colors, labels, lwds, legend_title = ""){
if(is.null(map)) map <- ggplot2::ggplot()
#------ Check that the length of vectors is identical between arguments
if(!inherits(lines, "list")) rlang::abort("Please provide a list for lines.")
ll <- list(lines, colors, labels, lwds)
if (!all(sapply(ll,length) == length(ll[[1]]))) rlang::abort("lines, colors, labels, lwds do not all have the same length.")
#------ Make valid
lines <- lapply(lines, \(x) sf::st_make_valid(x))
#------ Let's go with all line shapes
for (i in 1:length(lines)) {
lines[[i]] <- lines[[i]] |>
dplyr::mutate(color = colors[[i]],
label = labels[[i]],
lwd = lwds[[i]])
}
layers <- map + ggplot2::geom_sf(data = lines[[1]], ggplot2::aes(color = .data[["label"]], linewidth = .data[["label"]]))
if (length(lines) > 1){
for(i in 2:length(lines)){
data <- lines[[i]]
color <- labels[[i]]
size <- labels[[i]]
layers <- layers + ggplot2::geom_sf(data = data, ggplot2::aes(color = .data[["label"]], linewidth = .data[["label"]]))
}
}
#
layers <- layers +
ggplot2::scale_color_manual(name = legend_title, values = setNames(colors, labels), breaks = labels) +
ggplot2::scale_discrete_manual("linewidth", name = legend_title, values = setNames(lwds, labels), breaks = labels)
return(layers)
}
#' Basic defaults based on `tmap::tm_layout()`
#'
#' @param title Map title.
#' @param legend_position Legend position. Not above the map is a good start.
#' @param frame Boolean. Legend frame?
#' @param legend_frame Legend frame color.
#' @param legend_text_size Legend text size in 'pt'.
#' @param legend_title_size Legend title size in 'pt'.
#' @param title_size Title text size in 'pt'.
#' @param title_fontface Title fontface. Bold if you wanna exemplify a lot what it is about.
#' @param title_color Title font color.
#' @param fontfamily Overall fontfamily. Leelawadee is your precious.
#' @param ... Other arguments to pass to `tmap::tm_layout()`.
#'
#' @return A tmap layer.
#' @export
#'
add_layout <- function(
title = NULL,
legend_position = c(0.02, 0.5),
frame = FALSE,
legend_frame = cols_reach("main_grey"),
legend_text_size = 0.6,
legend_title_size = 0.8,
title_size = 0.9,
title_fontface = "bold",
title_color = cols_reach("main_grey"),
# check.and.fix = TRUE,
fontfamily = "Leelawadee",
...){
layout <- tmap::tm_layout(
title = title,
legend.position = legend_position,
legend.frame = legend_frame,
frame = FALSE,
legend.text.size = legend_text_size,
legend.title.size = legend_title_size,
title.size = title_size,
title.fontface = title_fontface,
title.color = title_color,
fontfamily = fontfamily,
...)
return(layout)
}
#' Wrapper around `tmap::tm_text()` with sane defaults for plotting admin labels.
#'
#' @param point Multipoint shape defined by sf package.
#' @param text Text labels column.
#' @param size Relative size of the text labels.
#' @param fontface Fontface.
#' @param fontfamily Fontfamily. Leelawadee is your precious.
#' @param shadow Boolean. Add a shadow around text labels. Issue opened on Github to request.
#' @param auto_placement Logical that determines whether the labels are placed automatically.
#' @param remove_overlap Logical that determines whether the overlapping labels are removed.
#' @param ... Other arguments to pass to `tmap::tm_text()`.
#'
#' @return A tmap layer.
#' @export
#'
add_text_labels <- function(map = NULL,
point,
text,
size = 0.5,
fontface = "bold",
fontfamily = "Leelawadee",
halo_radius = 0.15,
halo_color = "white",
angle = 0,
force = 0,
force_pull = 0){
if(is.null(map)) map <- ggplot()
col_name <- rlang::as_name(rlang::enquo(text))
layer <- map +
ggspatial::geom_spatial_text_repel(
data = point,
ggplot2::aes(
x = X,
y = Y,
label = !!rlang::sym(col_name)),
crs = sf::st_crs(point)$input,
force = force,
force_pull = force_pull,
size = 3,
angle = angle,
fontface = fontface,
family = fontfamily,
bg.r = halo_radius,
bg.color = halo_color)
return(layer)
}
#' Add a compass
#'
#' @param text_size Relative font size.
#' @param position Position of the compass. Vector of two values, specifying the x and y coordinates.
#' @param color_dark Color of the dark parts of the compass.
#' @param text_color color of the text.
#' @param type Compass type, one of: "arrow", "4star", "8star", "radar", "rose".
#' @param ... Other arguments to pass to `tmap::tm_compass()`.
#'
#' @return A tmap layer.
#' @export
#'
add_compass <- function(text_size = 0.6,
position = c("right", 0.8),
color_dark = cols_reach("black"),
text_color = cols_reach("black"),
type = "4star",
...){
compass <- tmap::tm_compass(
text.size = text_size,
position = position,
color.dark = color_dark,
type = type,
text.color = text_color
)
return(compass)
}
#' Add a scale bar
#'
#' @param text_size Relative font size.
#' @param position Position of the compass. Vector of two values, specifying the x and y coordinates.
#' @param color_dark Color of the dark parts of the compass.
#' @param breaks Breaks of the scale bar. If not specified, breaks will be automatically be chosen given the prefered width of the scale bar. Example: c(0, 50, 100).
#' @param ... Other arguments to pass to `tmap::tm_compass()`.
#'
#' @return A tmap layer.
#' @export
#'
add_scale_bar <- function(text_size = 0.6,
position = c("left", 0.01),
color_dark = cols_reach("black"),
breaks = c(0, 50, 100),
...){
scale_bar <- tmap::tm_scale_bar(
text.size = text_size,
position = position,
color.dark = color_dark,
breaks = breaks,
...
)
return(scale_bar)
}
#' Do you want to credit someone or some institution?
#'
#' @param text Text.
#' @param size Relative text size.
#' @param bg_color Background color.
#' @param position Position. Vector of two coordinates. Usually somewhere down.
#' @param ... Other arguments to pass to `tmap::tm_credits()`.
#'
#' @return A tmap layer.
#' @export
#'
add_credits <- function(text, size = 0.4, bg_color = NA, position = c(0.75, 0.02), ...){
tmap::tm_credits(text,
size = size,
bg.color = bg_color,
position = position,
...)
}

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#' @title Return function to interpolate an AGORA color palette
#'
#' @param palette Character name of a palette in AGORA palettes
#' @param reverse Boolean indicating whether the palette should be reversed
#' @param color_ramp_palette Should the output be a `grDevices::colorRampPalette` function or a vector of hex codes? Default to the former with `TRUE`
#' @param show_palettes Should the ouput be the set of palettes names to pick from? Default to `FALSE`
#' @param ... Additional arguments to pass to colorRampPalette()
#'
#' @return A color palette
#'
#' @export
pal_agora <- function(palette = "main", reverse = FALSE, color_ramp_palette = FALSE, show_palettes = FALSE, ...) {
palettes_agora <- list(
`main` = cols_agora("main_bordeaux", "main_dk_beige", "main_lt_grey", "main_lt_beige"),
`primary` = cols_agora("main_bordeaux", "main_dk_beige"),
`secondary` = cols_agora( "main_lt_grey", "main_lt_beige")
)
if (show_palettes) return(names(palettes_agora))
pal <- palettes_agora[[palette]]
if (reverse) pal <- rev(pal)
if (color_ramp_palette) {
rlang::check_installed("grDevices", reason = "Package \"grDevices\" needed for `pal_agora()` woth 'color_ramp_palette' set to `TRUE` to work. Please install it.")
pal <- grDevices::colorRampPalette(pal, ...)
}
return(pal)
}

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R/pal_fallback.R Normal file
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#' @title Return function to interpolate a fallback palette base on viridis::magma()
#'
#' @param reverse Boolean indicating whether the palette should be reversed
#' @param color_ramp_palette Should the output be a `grDevices::colorRampPalette` function or a vector of hex codes? Default to the latter with `FALSE`
#' @param discrete Boolean. Discrete or not? Default to FALSE.
#' @param n Number of colors in the palette. Default to 5. Passe to `viridis::magma()`
#' @param ... Other parameters to pass to `grDevices::colorRampPalette()`
#'
#' @return A color palette
#'
#' @export
pal_fallback <- function(reverse = FALSE,
color_ramp_palette = FALSE,
discrete = FALSE,
n = 5,
...){
pal <- if(discrete) { viridisLite::viridis(n) } else {viridisLite::magma(n)}
if (reverse) pal <- rev(pal)
if (color_ramp_palette) {
rlang::check_installed("grDevices", reason = "Package \"grDevices\" needed for `pal_fallback()` with 'color_ramp_palette' set to `TRUE` to work. Please install it.")
pal <- grDevices::colorRampPalette(pal, ...)
}
return(pal)
}

34
R/pal_impact.R Normal file
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@ -0,0 +1,34 @@
#' @title Return function to interpolate an IMPACT color palette
#'
#' @param palette Character name of a palette in IMPACT palettes
#' @param reverse Boolean indicating whether the palette should be reversed
#' @param color_ramp_palette Should the output be a `grDevices::colorRampPalette` function or a vector of hex codes? Default to the former with `TRUE`
#' @param show_palettes Should the ouput be the set of palettes names to pick from? Default to `FALSE`
#' @param ... Additional arguments to pass to colorRampPalette()
#'
#' @return A color palette
#'
#' @export
pal_impact <- function(palette = "main", reverse = FALSE, color_ramp_palette = FALSE, show_palettes = FALSE, ...) {
palettes_impact <- list(
`main` = cols_impact("black", "white", "main_blue", "main_grey"),
`primary` = cols_impact("black", "white"),
`secondary` = cols_impact("main_blue", "main_grey")
)
if (show_palettes) return(names(palettes_impact))
pal <- palettes_impact[[palette]]
if (reverse) pal <- rev(pal)
if (color_ramp_palette) {
rlang::check_installed("grDevices", reason = "Package \"grDevices\" needed for `pal_impact()` woth 'color_ramp_palette' set to `TRUE` to work. Please install it.")
pal <- grDevices::colorRampPalette(pal, ...)
}
return(pal)
}

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#' @title Return function to interpolate a REACH color palette
#'
#' @param palette Character name of a palette in REACH palettes
#' @param reverse Boolean indicating whether the palette should be reversed
#' @param color_ramp_palette Should the output be a `grDevices::colorRampPalette` function or a vector of hex codes? Default to the former with `TRUE`
#' @param show_palettes Should the ouput be the set of palettes names to pick from? Default to `FALSE`
#' @param ... Additional arguments to pass to colorRampPalette()
#'
#' @return A color palette
#'
#' @export
pal_reach <- function(palette = "main", reverse = FALSE, color_ramp_palette = FALSE, show_palettes = FALSE, ...) {
palettes_reach <- list(
`main` = cols_reach("main_grey", "main_red", "main_lt_grey", "main_beige"),
`primary` = cols_reach("main_grey", "main_red"),
`secondary` = cols_reach("main_lt_grey", "main_beige"),
`two_dots` = cols_reach("two_dots_1", "two_dots_2"),
`two_dots_flashy` = cols_reach("two_dots_flashy_1", "two_dots_flashy_2"),
`red_main` = cols_reach("red_main_1", "red_main_2", "red_main_3", "red_main_4", "red_main_5"),
`red_main_5` = cols_reach("red_main_1", "red_main_2", "red_main_3", "red_main_4", "red_main_5"),
`red_alt` = cols_reach("red_alt_1", "red_alt_2", "red_alt_3", "red_alt_4", "red_alt_5"),
`red_alt_5` = cols_reach("red_alt_1", "red_alt_2", "red_alt_3", "red_alt_4", "red_alt_5"),
`iroise` = cols_reach("iroise_1", "iroise_2", "iroise_3", "iroise_4", "iroise_5"),
`iroise_5` = cols_reach("iroise_1", "iroise_2", "iroise_3", "iroise_4", "iroise_5"),
`discrete_6` = cols_reach("dk_grey", "red_main_1", "main_beige", "red_main_2", "lt_grey_2", "red_4"),
`red_2` = cols_reach("red_less_4_1", "red_less_4_3"),
`red_3` = cols_reach("red_less_4_1", "red_less_4_2", "red_less_4_3"),
`red_4` = cols_reach("red_less_4_1", "red_less_4_2", "red_less_4_3", "red_less_4_4"),
`red_5` = cols_reach("red_5_1", "red_5_2", "red_5_3", "red_5_4", "red_5_5"),
`red_6` = cols_reach("red_less_7_1", "red_less_2", "red_less_7_3", "red_less_7_4", "red_less_7_5", "red_less_7_6"),
`red_7` = cols_reach("red_less_7_1", "red_less_7_2", "red_less_7_3", "red_less_7_4", "red_less_7_5", "red_less_7_6", "red_less_7_7"),
`green_2` = cols_reach("green_2_1", "green_2_2"),
`green_3` = cols_reach("green_3_1", "green_3_2", "green_3_3"),
`green_4` = cols_reach("green_4_1", "green_4_2", "green_4_3", "green_4_4"),
`green_5` = cols_reach("green_5_1", "green_5_2", "green_5_3", "green_5_4", "green_5_5"),
`green_6` = cols_reach("green_6_1", "green_6_2", "green_6_3", "green_6_4", "green_6_5", "green_6_6"),
`green_7` = cols_reach("green_7_1", "green_7_2", "green_7_3", "green_7_4", "green_7_5", "green_7_6", "green_7_7"),
`artichoke_2` = cols_reach("artichoke_2_1", "artichoke_2_2"),
`artichoke_3` = cols_reach("artichoke_3_1", "artichoke_3_2", "artichoke_3_3"),
`artichoke_4` = cols_reach("artichoke_4_1", "artichoke_4_2", "artichoke_4_3", "artichoke_4_4"),
`artichoke_5` = cols_reach("artichoke_5_1", "artichoke_5_2", "artichoke_5_3", "artichoke_5_4", "artichoke_5_5"),
`artichoke_6` = cols_reach("artichoke_6_1", "artichoke_6_2", "artichoke_6_3", "artichoke_6_4", "artichoke_6_5", "artichoke_6_6"),
`artichoke_7` = cols_reach("artichoke_7_1", "artichoke_7_2", "artichoke_7_3", "artichoke_7_4", "artichoke_7_5", "artichoke_7_6", "artichoke_7_7"),
`blue_2` = cols_reach("blue_2_1", "blue_2_2"),
`blue_3` = cols_reach("blue_3_1", "blue_3_2", "blue_3_3"),
`blue_4` = cols_reach("blue_4_1", "blue_4_2", "blue_4_3", "blue_4_4"),
`blue_5` = cols_reach("blue_5_1", "blue_5_2", "blue_5_3", "blue_5_4", "blue_5_5"),
`blue_6` = cols_reach("blue_6_1", "blue_6_2", "blue_6_3", "blue_6_4", "blue_6_5", "blue_6_6"),
`blue_7` = cols_reach("blue_7_1", "blue_7_2", "blue_7_3", "blue_7_4", "blue_7_5", "blue_7_6", "blue_7_7")
)
if (show_palettes) return(names(palettes_reach))
pal <- palettes_reach[[palette]]
if (reverse) pal <- rev(pal)
if (color_ramp_palette) {
rlang::check_installed("grDevices", reason = "Package \"grDevices\" needed for `pal_reach()` with 'color_ramp_palette' set to `TRUE` to work. Please install it.")
pal <- grDevices::colorRampPalette(pal, ...)
}
return(pal)
}

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@ -1,81 +0,0 @@
#' @title Interpolate a color palette
#'
#' @param palette Character name of a palette in palettes
#' @param reverse Boolean indicating whether the palette should be reversed
#' @param show_palettes Should the ouput be the set of palettes names to pick from? Default to `FALSE`
#' @param ... Additional arguments to pass to colorRampPalette()
#'
#' @return A color palette
#'
#' @export
palette <- function(
palette = "cat_5_main",
reverse = FALSE,
show_palettes = FALSE,
...
) {
#------ Checks
# palette is a character scalar
checkmate::assert_character(palette, len = 1)
# reverse is a logical scalar
checkmate::assert_logical(reverse, len = 1)
# show_palettes is a logical scalar
checkmate::assert_logical(show_palettes, len = 1)
#------ Get colors
# Define palettes
pals <- list(
cat_2_yellow = color_pattern("cat_2_yellow"),
cat_2_light = color_pattern("cat_2_light"),
cat_2_green = color_pattern("cat_2_green"),
cat_2_blue = color_pattern("cat_2_blue"),
cat_5_main = color_pattern("cat_5_main"),
cat_5_ibm = color_pattern("cat_5_ibm"),
cat_3_aquamarine = color_pattern("cat_3_aquamarine"),
cat_3_tol_high_contrast = color_pattern("cat_3_tol_high_contrast"),
cat_8_tol_adapted = color_pattern("cat_8_tol_adapted"),
cat_3_custom_1 = c("#003F5C", "#58508D", "#FFA600"),
cat_4_custom_1 = c("#003F5C", "#7a5195", "#ef5675", "#ffa600"),
cat_5_custom_1 = c("#003F5C", "#58508d", "#bc5090", "#ff6361", "#ffa600"),
cat_6_custom_1 = c(
"#003F5C",
"#444e86",
"#955196",
"#dd5182",
"#ff6e54",
"#ffa600"
),
div_5_orange_blue = color_pattern("div_5_orange_blue"),
div_5_green_purple = color_pattern("div_5_green_purple")
)
# Return if show palettes
if (show_palettes) {
return(names(pals))
}
# palette is in pals
if (palette %notin% names(pals)) {
rlang::abort(c(
"Palette not defined",
"*" = glue::glue(
"Palette `{palette}` is not defined in the `palettes` list."
),
"i" = "Use `palette(show_palettes = TRUE)` to see all available palettes."
))
}
#------ Get palette
pal <- pals[[palette]]
if (reverse) {
pal <- rev(pal)
}
return(pal)
}

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@ -1,79 +0,0 @@
#' Generate color palettes
#'
#' [palette_gen()] generates a color palette and let you choose whether continuous or discrete. [palette_gen_categorical()] and [palette_gen_sequential()] generates respectively discrete and continuous palettes.
#'
#' @param palette Palette name from [palette()].
#' @param type "categorical" or "sequential" or "divergent".
#' @param direction 1 or -1; should the order of colors be reversed?
#' @param ... Additional arguments to pass to [colorRampPalette()] when type is "continuous".
#'
#' @export
palette_gen <- function(palette, type, direction = 1, ...) {
#------ Checks
checkmate::assert_string(palette)
checkmate::assert_choice(type, c("categorical", "sequential", "divergent"))
checkmate::assert_number(direction, lower = -1, upper = 1)
checkmate::assert_true(abs(direction) == 1)
if (type == "categorical") {
return(palette_gen_categorical(palette = palette, direction = direction))
}
if (type %in% c("sequential", "divergent")) {
return(palette_gen_sequential(
palette = palette,
direction = direction,
...
))
}
}
#' @rdname palette_gen
#'
#' @export
palette_gen_categorical <- function(palette = "cat_5_main", direction = 1) {
#------ Checks
checkmate::assert_string(palette)
checkmate::assert_number(direction, lower = -1, upper = 1)
checkmate::assert_true(abs(direction) == 1)
pal <- palette(palette)
f <- function(n) {
if (is.null(n)) {
n <- length(pal)
}
if (n > length(pal)) {
rlang::warn("Not enough colors in this palette!")
}
pal <- if (direction == 1) pal else rev(pal)
pal <- pal[1:n]
return(pal)
}
return(f)
}
#' @rdname palette_gen
#'
#' @export
palette_gen_sequential <- function(palette = "cat_5_main", direction = 1, ...) {
#------ Checks
checkmate::assert_string(palette)
checkmate::assert_number(direction, lower = -1, upper = 1)
checkmate::assert_true(abs(direction) == 1)
pal <- palette(palette)
pal <- if (direction == 1) pal else rev(pal)
grDevices::colorRampPalette(pal, ...)
}

206
R/point.R
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@ -1,18 +1,10 @@
#' @title Simple scatterplot
#' @title Simple point chart
#'
#' @param df A data frame.
#' @param x A quoted numeric column.
#' @param y A quoted numeric column.
#' @param group Some quoted grouping categorical column, e.g. administrative areas or population groups.
#' @param facet Some quoted grouping categorical column.
#' @param facet_scales Character. Either "free" (default) or "fixed" for facet scales.
#' @param x_rm_na Remove NAs in x?
#' @param y_rm_na Remove NAs in y?
#' @param group_rm_na Remove NAs in group?
#' @param facet_rm_na Remove NAs in facet?
#' @param add_color Add a color to points (if no grouping).
#' @param add_color_guide Should a legend be added?
#' @param flip TRUE or FALSE.
#' @param x A numeric column.
#' @param y A character column or coercible as a character column.
#' @param group Some grouping categorical column, e.g. administrative areas or population groups.
#' @param flip TRUE or FALSE. Default to TRUE or horizontal bar plot.
#' @param alpha Fill transparency.
#' @param size Point size.
#' @param x_title The x scale title. Default to NULL.
@ -21,124 +13,31 @@
#' @param title Plot title. Default to NULL.
#' @param subtitle Plot subtitle. Default to NULL.
#' @param caption Plot caption. Default to NULL.
#' @param theme_fun Whatever theme. Default to theme_point(). NULL if no theming needed.
#' @param scale_fill_fun Scale fill function. Default to scale_fill_visualizer_discrete().
#' @param scale_color_fun Scale color function. Default to scale_color_visualizer_discrete().
#' @param theme Whatever theme. Default to theme_reach().
#'
#' @return A bar chart
#'
#' @export
point <- function(
df,
x,
y,
group = "",
facet = "",
facet_scales = "free",
x_rm_na = TRUE,
y_rm_na = TRUE,
group_rm_na = TRUE,
facet_rm_na = TRUE,
add_color = color("cat_5_main_1"),
add_color_guide = TRUE,
flip = TRUE,
alpha = 1,
size = 2,
x_title = NULL,
y_title = NULL,
group_title = NULL,
title = NULL,
subtitle = NULL,
caption = NULL,
theme_fun = theme_point(),
scale_fill_fun = scale_fill_visualizer_discrete(),
scale_color_fun = scale_color_visualizer_discrete()) {
#------ Checks
point <- function(df, x, y, group = NULL, flip = TRUE, alpha = 1, size = 1, x_title = NULL, y_title = NULL, group_title = NULL, title = NULL, subtitle = NULL, caption = NULL, theme = theme_reach()){
# df is a data frame
checkmate::assert_data_frame(df)
# To do :
# - automate bar width and text size, or at least give the flexibility and still center text
# - add facet possibility
# x and y and group are character
checkmate::assert_character(x, len = 1)
checkmate::assert_character(y, len = 1)
checkmate::assert_character(group, len = 1)
# Prepare group, x and y names
# if (is.null(x_title)) x_title <- rlang::as_name(rlang::enquo(x))
# if (is.null(y_title)) y_title <- rlang::as_name(rlang::enquo(y))
# if (is.null(group_title)) group_title <- rlang::as_name(rlang::enquo(group))
# x and y are columns in df
checkmate::assert_choice(x, colnames(df))
checkmate::assert_choice(y, colnames(df))
if (group != "") {
checkmate::assert_choice(group, colnames(df))
}
# x_rm_na, y_rm_na and group_rm_na are logical scalar
checkmate::assert_logical(x_rm_na, len = 1)
checkmate::assert_logical(y_rm_na, len = 1)
checkmate::assert_logical(group_rm_na, len = 1)
checkmate::assert_logical(facet_rm_na, len = 1)
# facet_scales is a character scalar in c("free", "fixed")
checkmate::assert_choice(facet_scales, c("free", "fixed"))
# flip is a logical scalar
checkmate::assert_logical(flip, len = 1)
# alpha is a numeric scalar between 0 and 1
checkmate::assert_numeric(alpha, lower = 0, upper = 1, len = 1)
# size is a numeric scalar
checkmate::assert_numeric(size, len = 1)
# x and y are numeric
if (!any(c("numeric", "integer") %in% class(df[[x]]))) {
rlang::abort(paste0(x, " must be numeric."))
}
if (!any(c("numeric", "integer") %in% class(df[[y]]))) {
rlang::abort(paste0(y, " must be numeric."))
}
#----- Data wrangling
# facets over group
if (group != "" && facet != "" && group == facet) {
rlang::warn("'group' and 'facet' are the same identical.")
}
# remove NAs using base R
if (x_rm_na) {
df <- df[!(is.na(df[[x]])), ]
}
if (y_rm_na) {
df <- df[!(is.na(df[[y]])), ]
}
if (group != "" && group_rm_na) {
df <- df[!(is.na(df[[group]])), ]
}
if (facet != "" && facet_rm_na) {
df <- df[!(is.na(df[[facet]])), ]
}
# prepare aes
if (group != "") {
# Mapping
g <- ggplot2::ggplot(
df,
mapping = ggplot2::aes(
x = !!rlang::sym(x),
y = !!rlang::sym(y),
fill = !!rlang::sym(group),
color = !!rlang::sym(group)
mapping = ggplot2::aes(x = {{ x }}, y = {{ y }}, fill = {{ group }}, color = {{ group }}
)
)
} else {
g <- ggplot2::ggplot(
df,
mapping = ggplot2::aes(
x = !!rlang::sym(x),
y = !!rlang::sym(y)
)
)
}
# add title, subtitle, caption, x_title, y_title
g <- g +
ggplot2::labs(
# Add title, subtitle, caption, x_title, y_title
g <- g + ggplot2::labs(
title = title,
subtitle = subtitle,
caption = caption,
@ -148,64 +47,35 @@ point <- function(
fill = group_title
)
# facets
# facets
if (facet != "") {
if (flip) {
g <- g +
ggplot2::facet_grid(
rows = ggplot2::vars(!!rlang::sym(facet)),
scales = facet_scales,
space = if (facet_scales == "free") "free_y" else "fixed"
)
} else {
g <- g +
ggplot2::facet_grid(
cols = ggplot2::vars(!!rlang::sym(facet)),
scales = facet_scales,
space = if (facet_scales == "free") "free_x" else "fixed"
)
}
}
width <- 0.5
dodge_width <- 0.5
# Should the graph use position_fill?
if (group != "") {
g <- g +
ggplot2::geom_point(
g <- g + ggplot2::geom_point(
alpha = alpha,
size = size
)
} else {
g <- g +
ggplot2::geom_point(
alpha = alpha,
size = size,
color = add_color
)
}
# Labels to percent and expand scale
# if (percent) {
# g <- g + ggplot2::scale_y_continuous(
# labels = scales::label_percent(
# accuracy = 1,
# decimal.mark = ",",
# suffix = " %"),
# expand = c(0.01, 0.1)
# )
# } else {
# g <- g + ggplot2::scale_y_continuous(expand = c(0.01, 0.1))
# }
# # Because a text legend should always be horizontal, especially for an horizontal bar graph
if (flip){
g <- g + ggplot2::coord_flip()
}
# Remove guides for legend if !add_color_guide
if (!add_color_guide) {
g <- g + ggplot2::guides(fill = "none", color = "none")
}
# Add theme
if (!is.null(theme_fun)) {
g <- g + theme_fun
}
# Add scale fun
if (!is.null(scale_fill_fun)) {
g <- g + scale_fill_fun
}
if (!is.null(scale_color_fun)) {
g <- g + scale_color_fun
}
g <- g + theme
return(g)
}

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@ -1,108 +0,0 @@
#' Reorder a Data Frame
#'
#' @param df A data frame to be reordered.
#' @param x A character scalar specifying the column to be reordered.
#' @param y A character scalar specifying the column to order by if ordering by values.
#' @param group A character scalar specifying the grouping column (optional).
#' @param order A character scalar specifying the order type (one of "none", "y", "grouped"). See details.
#' @param dir_order A logical scalar specifying whether to flip the order.
#'
#' @details Ordering takes the following possible values:
#'
#' * "none": No reordering.
#' * "y": Order by values of y.
#' * "grouped_y": Order by values of y and group.
#' * "x": Order alphabetically by x.
#' * "grouped_x": Order alphabetically by x and group.
#'
#'
#' @return The reordered data frame.
#'
#' @examples
#' # Example usage
#' df <- data.frame(col1 = c("b", "a", "c"), col2 = c(10, 25, 3))
#' reorder_by(df, "col1", "col2")
#'
#' @export
reorder_by <- function(df, x, y, group = "", order = "y", dir_order = 1) {
#------ Checks
# df is a data frame
checkmate::assert_data_frame(df)
# x and y are character scalar and in df
checkmate::assert_character(x, len = 1)
checkmate::assert_character(y, len = 1)
checkmate::assert_subset(x, colnames(df))
checkmate::assert_subset(y, colnames(df))
# group is character scalar and in df if not empty
checkmate::assert_character(group, len = 1)
if (group != "") {
checkmate::assert_subset(group, colnames(df))
}
# order is a character scalar in c("none", "y", "grouped")
checkmate::assert_choice(order, c("none", "y", "grouped_y", "x", "grouped_x"))
# dir_order is 1 or -1 (numeric scalar)
checkmate::assert_subset(dir_order, c(1, -1))
# Convert dir_order to decreasing logical flag
dir_order_lgl <- (dir_order == -1)
#------ Reorder
# droplevels first
if (is.factor(df[[x]])) {
df[[x]] <- droplevels(df[[x]])
}
# reording options
if (order == "y") {
# Order by values of y
df <- df[order(df[[y]], decreasing = dir_order_lgl), ]
df[[x]] <- forcats::fct_inorder(df[[x]])
} else if (order == "grouped_y" && group != "") {
# Order by group first, then by values of y
df <- df[
order(
df[[group]],
df[[y]],
decreasing = c(FALSE, dir_order_lgl),
method = "radix"
),
]
df[[x]] <- forcats::fct_inorder(df[[x]])
} else if (order == "grouped_y" && group == "") {
# Fallback to ordering by y if group is empty
rlang::warn("Group is empty. Ordering by y only.")
df <- df[order(df[[y]], decreasing = dir_order_lgl), ]
df[[x]] <- forcats::fct_inorder(df[[x]])
} else if (order == "x") {
# Order alphabetically by x
df <- df[order(df[[x]], decreasing = dir_order_lgl), ]
df[[x]] <- forcats::fct_inorder(df[[x]])
} else if (order == "grouped_x" && group != "") {
# Order by group first, then alphabetically by x
df <- df[
order(
df[[group]],
df[[x]],
decreasing = c(FALSE, dir_order_lgl),
method = "radix"
),
]
df[[x]] <- forcats::fct_inorder(df[[x]])
} else if (order == "grouped_x" && group == "") {
# Fallback to ordering by x if group is empty
rlang::warn("Group is empty. Ordering by x only.")
df <- df[order(df[[x]], decreasing = dir_order_lgl), ]
df[[x]] <- forcats::fct_inorder(df[[x]])
}
# Reset row names
rownames(df) <- NULL
return(df)
}

319
R/scale.R
View file

@ -1,41 +1,119 @@
#' Scale constructors for fill and colors
#'
#' This function is based on [palette()]. If palette is NULL, the used palette will be magma from gpplot2's viridis scale constructors.
#'
#' @inheritParams palette_gen
#' Color scale constructor for REACH or AGORA colors
#'
#' @param initiative Either "reach" or "agora" or "default".
#' @param palette Palette name from `pal_reach()` or `pal_agora()`.
#' @param discrete Boolean indicating whether color aesthetic is discrete or not.
#' @param reverse Boolean indicating whether the palette should be reversed.
#' @param reverse_guide Boolean indicating whether the guide should be reversed.
#' @param title_position Position of the title. See [ggplot2::guide_legend()]'s title.position argument.
#' @param ... Additional arguments passed to [ggplot2::discrete_scale()] if discrete or [ggplot2::scale_fill_gradient()] if continuous.
#' @param ... Additional arguments passed to discrete_scale() or
#' scale_fill_gradient(), used respectively when discrete is TRUE or FALSE.
#'
#' @return A color scale for ggplot
#'
#' @export
scale_color_visualizer_discrete <- function(
palette = "cat_5_main",
direction = 1,
reverse_guide = TRUE,
title_position = NULL,
...) {
if (!(is.null(palette))) {
scale_color <- function(initiative = "reach", palette = "main", discrete = TRUE, reverse = FALSE, reverse_guide = TRUE, ...) {
if (initiative == "reach") {
pal <- pal_reach(palette)
if (is.null(pal)) {
pal <- pal_fallback(
reverse = reverse,
discrete = discrete,
color_ramp_palette = TRUE)
rlang::warn(
c(
paste0("There is no palette '", palette, "' for the selected initiative. Fallback to pal_fallback()."),
"i" = paste0("Use `pal_reach(show_palettes = TRUE)` to see the list of available palettes.")
)
)
if (discrete) palette <- "viridis" else palette <- "magma"
} else {
pal <- pal_reach(
palette = palette,
reverse = reverse,
color_ramp_palette = TRUE,
show_palettes = FALSE
)
}
} else if (initiative == "agora") {
pal <- pal_agora(palette)
if (is.null(pal)) {
pal <- pal_fallback(
reverse = reverse,
discrete = discrete,
color_ramp_palette = TRUE)
rlang::warn(
c(
paste0("There is no palette '", palette, "' for the selected initiative. Fallback to pal_fallback()."),
"i" = paste0("Use `pal_reach(show_palettes = TRUE)` to see the list of available palettes.")
)
)
if (discrete) palette <- "viridis" else palette <- "magma"
} else {
pal <- pal_agora(
palette = palette,
reverse = reverse,
color_ramp_palette = TRUE,
show_palettes = FALSE
)
}
} else if (initiative == "default") {
pal <- pal_fallback(
reverse = reverse,
discrete = discrete,
color_ramp_palette = TRUE)
if (discrete) palette <- "viridis" else palette <- "magma"
} else {
rlang::abort(
c(
paste0("There is no initiative '", initiative, "."),
"i" = paste0("initiative should be either 'reach', 'agora' or 'default'")
)
)
}
if (discrete) {
ggplot2::discrete_scale(
"color",
palette = palette_gen(palette, "categorical", direction),
"colour",
paste0(initiative, "_", palette),
palette = pal,
guide = ggplot2::guide_legend(
title.position = title_position,
title.position = "top",
draw.ulim = TRUE,
draw.llim = TRUE,
# ticks.colour = "#F1F3F5",
ticks.colour = "#F1F3F5",
reverse = reverse_guide
),
...
)
} else {
ggplot2::scale_colour_viridis_d(
direction = direction,
guide = ggplot2::guide_legend(
title.position = title_position,
ggplot2::scale_color_gradientn(
colours = pal(256),
guide = ggplot2::guide_colorbar(
title.position = "top",
draw.ulim = TRUE,
draw.llim = TRUE,
# ticks.colour = "#F1F3F5",
ticks.colour = "#F1F3F5",
reverse = reverse_guide
),
...
@ -43,112 +121,125 @@ scale_color_visualizer_discrete <- function(
}
}
#' @rdname scale_color_visualizer_discrete
#' Fill scale constructor for REACH or AGORA colors
#'
#' @param initiative Either "reach" or "agora" or "default".
#' @param palette Palette name from `pal_reach()` or `pal_agora()`.
#' @param discrete Boolean indicating whether color aesthetic is discrete or not.
#' @param reverse Boolean indicating whether the palette should be reversed.
#' @param reverse_guide Boolean indicating whether the guide should be reversed.
#' @param ... Additional arguments passed to discrete_scale() or
#' scale_fill_gradient(), used respectively when discrete is TRUE or FALSE.
#'
#' @return A fill scale for ggplot.
#'
#' @export
scale_fill_visualizer_discrete <- function(
palette = "cat_5_main",
direction = 1,
reverse_guide = TRUE,
title_position = NULL,
...) {
if (!(is.null(palette))) {
scale_fill <- function(initiative = "reach", palette = "main", discrete = TRUE, reverse = FALSE, reverse_guide = TRUE, ...) {
if (initiative == "reach") {
pal <- pal_reach(palette)
if (is.null(pal)) {
pal <- pal_fallback(
reverse = reverse,
discrete = discrete,
color_ramp_palette = TRUE)
rlang::warn(
c(
paste0("There is no palette '", palette, "' for the selected initiative. Fallback to pal_fallback()."),
"i" = paste0("Use `pal_reach(show_palettes = TRUE)` to see the list of available palettes.")
)
)
if (discrete) palette <- "viridis" else palette <- "magma"
} else {
pal <- pal_reach(
palette = palette,
reverse = reverse,
color_ramp_palette = TRUE,
show_palettes = FALSE
)
}
} else if (initiative == "agora") {
pal <- pal_agora(palette)
if (is.null(pal)) {
pal <- pal_fallback(
reverse = reverse,
discrete = discrete,
color_ramp_palette = TRUE)
rlang::warn(
c(
paste0("There is no palette '", palette, "' for the selected initiative. Fallback to pal_fallback()."),
"i" = paste0("Use `pal_reach(show_palettes = TRUE)` to see the list of available palettes.")
)
)
if (discrete) palette <- "viridis" else palette <- "magma"
} else {
pal <- pal_agora(
palette = palette,
reverse = reverse,
color_ramp_palette = TRUE,
show_palettes = FALSE
)
}
} else if (initiative == "default") {
pal <- pal_fallback(
reverse = reverse,
discrete = discrete,
color_ramp_palette = TRUE)
if (discrete) palette <- "viridis" else palette <- "magma"
} else {
rlang::abort(
c(
paste0("There is no initiative '", initiative, "."),
"i" = paste0("initiative should be either 'reach', 'agora' or 'default'")
)
)
}
if (discrete) {
ggplot2::discrete_scale(
"fill",
palette = palette_gen(palette, "categorical", direction),
paste0(initiative, "_", palette),
palette = pal,
guide = ggplot2::guide_legend(
title.position = title_position,
title.position = "top",
draw.ulim = TRUE,
draw.llim = TRUE,
# ticks.colour = "#F1F3F5",
ticks.colour = "#F1F3F5",
reverse = reverse_guide
),
...
)
} else {
ggplot2::scale_fill_viridis_d(
direction = direction,
guide = ggplot2::guide_legend(
title.position = title_position,
draw.ulim = TRUE,
draw.llim = TRUE,
# ticks.colour = "#F1F3F5",
reverse = reverse_guide
),
...
)
}
}
#' @rdname scale_color_visualizer_discrete
#'
#' @export
scale_fill_visualizer_continuous <- function(
palette = "seq_5_main",
direction = 1,
reverse_guide = TRUE,
title_position = NULL,
...) {
if (!(is.null(palette))) {
pal <- palette_gen(palette, "continuous", direction)
ggplot2::scale_fill_gradientn(
colors = pal(256),
ggplot2::scale_color_gradientn(
colours = pal(256),
guide = ggplot2::guide_colorbar(
title.position = title_position,
title.position = "top",
draw.ulim = TRUE,
draw.llim = TRUE,
# ticks.colour = "#F1F3F5",
reverse = reverse_guide
),
...
)
} else {
ggplot2::scale_fill_viridis_c(
option = "magma",
guide = ggplot2::guide_colorbar(
title.position = title_position,
draw.ulim = TRUE,
draw.llim = TRUE,
# ticks.colour = "#F1F3F5",
reverse = reverse_guide
),
...
)
}
}
#' @rdname scale_color_visualizer_discrete
#'
#' @export
scale_color_visualizer_continuous <- function(
palette = "seq_5_main",
direction = 1,
reverse_guide = TRUE,
title_position = NULL,
...) {
if (!(is.null(palette))) {
pal <- palette_gen(palette, "continuous", direction)
ggplot2::scale_fill_gradientn(
colors = pal(256),
guide = ggplot2::guide_colorbar(
title.position = title_position,
draw.ulim = TRUE,
draw.llim = TRUE,
# ticks.colour = "#F1F3F5",
reverse = reverse_guide
),
...
)
} else {
ggplot2::scale_colour_viridis_c(
option = "magma",
guide = ggplot2::guide_colorbar(
title.position = title_position,
draw.ulim = TRUE,
draw.llim = TRUE,
# ticks.colour = "#F1F3F5",
ticks.colour = "#F1F3F5",
reverse = reverse_guide
),
...

View file

@ -1,97 +0,0 @@
#' Custom Theme for Bar Charts
#'
#' @return A custom theme object.
#'
#'
#' @rdname theme_default
#'
#' @inheritParams bar
#'
#' @export
theme_bar <- function(
flip = TRUE,
add_text = FALSE,
axis_text_x_angle = 0,
axis_text_x_vjust = 0.5,
axis_text_x_hjust = 0.5) {
# If add_text is TRUE, flip is FALSE
if (!flip && !add_text) {
par_axis_text_font_face <- "plain"
par_axis_x <- TRUE
par_axis_y <- TRUE
par_axis_line_y <- FALSE
par_axis_ticks_y <- TRUE
par_axis_text_y <- TRUE
par_axis_line_x <- TRUE
par_axis_ticks_x <- TRUE
par_axis_text_x <- TRUE
par_grid_major_y <- TRUE
par_grid_major_x <- FALSE
par_grid_minor_y <- TRUE
par_grid_minor_x <- FALSE
} else if (flip && !add_text) {
par_axis_text_font_face <- "plain"
par_axis_x <- TRUE
par_axis_y <- TRUE
par_axis_line_y <- TRUE
par_axis_ticks_y <- TRUE
par_axis_text_y <- TRUE
par_axis_line_x <- FALSE
par_axis_ticks_x <- TRUE
par_axis_text_x <- TRUE
par_grid_major_y <- FALSE
par_grid_major_x <- TRUE
par_grid_minor_y <- FALSE
par_grid_minor_x <- TRUE
} else if (!flip && add_text) {
par_axis_text_font_face <- "bold"
par_axis_x <- TRUE
par_axis_y <- TRUE
par_axis_line_y <- FALSE
par_axis_ticks_y <- FALSE
par_axis_text_y <- FALSE
par_axis_line_x <- FALSE
par_axis_ticks_x <- TRUE
par_axis_text_x <- TRUE
par_grid_major_y <- FALSE
par_grid_major_x <- FALSE
par_grid_minor_y <- FALSE
par_grid_minor_x <- FALSE
} else if (flip && add_text) {
par_axis_text_font_face <- "bold"
par_axis_x <- TRUE
par_axis_y <- TRUE
par_axis_line_y <- FALSE
par_axis_ticks_y <- TRUE
par_axis_text_y <- TRUE
par_axis_line_x <- FALSE
par_axis_ticks_x <- FALSE
par_axis_text_x <- FALSE
par_grid_major_y <- FALSE
par_grid_major_x <- FALSE
par_grid_minor_y <- FALSE
par_grid_minor_x <- FALSE
}
# Theme
t <- theme_default(
axis_text_font_face = par_axis_text_font_face,
axis_x = par_axis_x,
axis_y = par_axis_y,
grid_major_y = par_grid_major_y,
grid_major_x = par_grid_major_x,
grid_minor_y = par_grid_minor_y,
grid_minor_x = par_grid_minor_x,
axis_text_y = par_axis_text_y,
axis_line_y = par_axis_line_y,
axis_ticks_y = par_axis_ticks_y,
axis_text_x = par_axis_text_x,
axis_line_x = par_axis_line_x,
axis_ticks_x = par_axis_ticks_x,
axis_text_x_angle = axis_text_x_angle,
axis_text_x_vjust = axis_text_x_vjust,
axis_text_x_hjust = axis_text_x_hjust
)
return(t)
}

View file

@ -1,399 +0,0 @@
#' ggplot2 theme wrapper with fonts and colors
#'
#' @param title_size The size of the title. Defaults to 12.
#' @param title_color Title color.
#' @param title_font_face Title font face. Default to "bold". Font face ("plain", "italic", "bold", "bold.italic").
#' @param title_hjust Title horizontal justification. Default to NULL. Use 0.5 to center the title.
#' @param title_font_family Title font family. Default to "Carlito".
#' @param title_position_to_plot TRUE or FALSE. Positioning to plot or to panel?
#' @param subtitle_font_family Subtitle font family. Default to "Carlito".
#' @param subtitle_size The size of the subtitle. Defaults to 10.
#' @param subtitle_color Subtitle color.
#' @param subtitle_font_face Subtitle font face. Default to "plain". Font face ("plain", "italic", "bold", "bold.italic").
#' @param subtitle_hjust Subtitle horizontal justification. Default to NULL. Use 0.5 to center the subtitle.
#' @param text_font_family Text font family. Default to "Carlito".
#' @param text_size The size of all text other than the title, subtitle and caption. Defaults to 10.
#' @param text_color Text color.
#' @param text_font_face Text font face. Default to "bold". Font face ("plain", "italic", "bold", "bold.italic").
#' @param panel_background_color The color for the panel background color. Default to white.
#' @param panel_border Boolean. Plot a panel border? Default to FALSE.
#' @param panel_border_color A color. Default to REACH main grey.
#' @param legend_position Position of the legend; Default to "right". Can take "right", "left", "top", "bottom" or "none".
#' @param legend_direction Direction of the legend. Default to "vertical". Can take "vertical" or "horizontal".
#' @param legend_justification In addition to legend_direction, place the legend. Can take "left", "bottom", "center", "right", "top".
#' @param legend_title_size Legend title size.
#' @param legend_title_color Legend title color.
#' @param legend_title_font_face Legend title font face. Default to "plain". Font face ("plain", "italic", "bold", "bold.italic").
#' @param legend_title_font_family Legend title font family. Default to "Carlito".
#' @param legend_text_size Legend text size.
#' @param legend_text_color Legend text color.
#' @param legend_text_font_face Legend text font face. Default to "plain". Font face ("plain", "italic", "bold", "bold.italic").
#' @param legend_text_font_family Legend text font family. Default to "Carlito".
#'
#' @param legend_reverse Reverse the color in the guide? Default to TRUE.
#' @param facet_size Facet font size.
#' @param facet_color Facet font color.
#' @param facet_font_face Facet font face. Default to "plain". Font face ("plain", "italic", "bold", "bold.italic").
#' @param facet_font_family Facet font family. Default to "Carlito".
#' @param facet_bg_color Facet background color.
#' @param axis_x Boolean. Do you need x-axis?
#' @param axis_y Boolean. Do you need y-axis?
#' @param axis_text_font_family Axis text font family. Default to "Carlito".
#' @param axis_text_size Axis text size.
#' @param axis_text_color Axis text color.
#' @param axis_text_font_face Axis text font face. Default to "plain". Font face ("plain", "italic", "bold", "bold.italic").
#' @param axis_text_x Boolean. Do you need the text for the x-axis?
#' @param axis_line_x Boolean. Do you need the line for the x-axis?
#' @param axis_ticks_x Boolean. Do you need the line for the x-axis?
#' @param axis_text_x_angle Angle for the x-axis text.
#' @param axis_text_x_vjust Vertical adjustment for the x-axis text.
#' @param axis_text_x_hjust Vertical adjustment for the x-axis text.
#' @param axis_text_y Boolean. Do you need the text for the y-axis?
#' @param axis_line_y Boolean. Do you need the line for the y-axis?
#' @param axis_ticks_y Boolean. Do you need the line for the y-axis?
#' @param axis_title_size Axis title size.
#' @param axis_title_color Axis title color.
#' @param axis_title_font_face Axis title font face. Default to "plain". Font face ("plain", "italic", "bold", "bold.italic").
#' @param grid_major_x Boolean. Do you need major grid lines for x-axis?
#' @param grid_major_y Boolean. Do you need major grid lines for y-axis?
#' @param grid_major_x_size Major X line size.
#' @param grid_major_y_size Major Y line size.
#' @param grid_major_color Major grid lines color.
#' @param grid_minor_x Boolean. Do you need minor grid lines for x-axis?
#' @param grid_minor_y Boolean. Do you need minor grid lines for y-axis?
#' @param grid_minor_x_size Minor X line size.
#' @param grid_minor_y_size Minor Y line size.
#' @param grid_minor_color Minor grid lines color.
#' @param caption_font_family Caption font family. Default to "Carlito".
#' @param caption_font_face Caption font face. Default to "plain". Font face ("plain", "italic", "bold", "bold.italic").
#' @param caption_position_to_plot TRUE or FALSE. Positioning to plot or to panel?
#' @param caption_size The size of the caption. Defaults to 10.
#' @param caption_color Caption color.
#' @param ... Additional arguments passed to [ggplot2::theme()].
#'
#'
#' @description Give some reach colors and fonts to a ggplot.
#'
#' @export
theme_default <- function(
title_font_family = "Carlito",
title_size = 20,
title_color = color("dark_grey"),
title_font_face = "bold",
title_hjust = NULL,
title_position_to_plot = TRUE,
subtitle_font_family = "Carlito",
subtitle_size = 16,
subtitle_color = color("dark_grey"),
subtitle_font_face = "plain",
subtitle_hjust = NULL,
text_font_family = "Carlito",
text_size = 14,
text_color = color("dark_grey"),
text_font_face = "plain",
panel_background_color = "#FFFFFF",
panel_border = FALSE,
panel_border_color = color("dark_grey"),
legend_position = "top",
legend_direction = "horizontal",
legend_justification = "center",
legend_reverse = TRUE,
legend_title_size = 14,
legend_title_color = color("dark_grey"),
legend_title_font_face = "plain",
legend_title_font_family = "Carlito",
legend_text_size = 14,
legend_text_color = color("dark_grey"),
legend_text_font_face = "plain",
legend_text_font_family = "Carlito",
facet_size = 15,
facet_color = color("dark_grey"),
facet_font_face = "bold",
facet_font_family = "Carlito",
facet_bg_color = color("lighter_grey"),
axis_x = TRUE,
axis_y = TRUE,
axis_text_x = TRUE,
axis_line_x = FALSE,
axis_ticks_x = FALSE,
axis_text_y = TRUE,
axis_line_y = TRUE,
axis_ticks_y = TRUE,
axis_text_font_family = "Carlito",
axis_text_size = 14,
axis_text_color = color("dark_grey"),
axis_text_font_face = "plain",
axis_title_size = 15,
axis_title_color = color("dark_grey"),
axis_title_font_face = "plain",
axis_text_x_angle = 0,
axis_text_x_vjust = 0.5,
axis_text_x_hjust = 0.5,
grid_major_x = TRUE,
grid_major_y = FALSE,
grid_major_color = color("dark_grey"),
grid_major_x_size = 0.1,
grid_major_y_size = 0.1,
grid_minor_x = TRUE,
grid_minor_y = FALSE,
grid_minor_color = color("dark_grey"),
grid_minor_x_size = 0.05,
grid_minor_y_size = 0.05,
caption_font_family = "Carlito",
caption_font_face = "plain",
caption_position_to_plot = TRUE,
caption_size = 12,
caption_color = color("dark_grey"),
...) {
# Basic simple theme
theme <- ggplot2::theme_minimal()
theme <- theme +
ggplot2::theme(
# # Text - design
text = ggplot2::element_text(
family = text_font_family,
color = text_color,
size = text_size,
face = text_font_face
),
# Default legend to right position
legend.position = legend_position,
# Defaut legend to vertical direction
legend.direction = legend_direction,
# Text sizes
axis.text = ggplot2::element_text(
size = axis_text_size,
family = axis_text_font_family,
face = axis_text_font_face,
color = axis_text_color
),
axis.title = ggplot2::element_text(
size = axis_title_size,
family = axis_text_font_family,
face = axis_title_font_face,
color = axis_title_color
),
# # Wrap title
plot.title = ggtext::element_textbox_simple(
hjust = title_hjust,
family = title_font_family,
color = title_color,
size = title_size,
face = title_font_face,
width = grid::unit(0.9, "npc"),
margin = ggplot2::margin(b = 10)
),
plot.subtitle = ggtext::element_textbox_simple(
hjust = title_hjust,
family = subtitle_font_family,
color = subtitle_color,
size = subtitle_size,
face = subtitle_font_face,
margin = ggplot2::margin(t = 5, b = 10)
),
plot.caption = ggtext::element_textbox_simple(
size = caption_size,
face = caption_font_face,
family = caption_font_family,
color = caption_color,
margin = ggplot2::margin(t = 10)
),
legend.title = ggplot2::element_text(
size = legend_title_size,
face = legend_title_font_face,
family = legend_title_font_family,
color = legend_title_color
),
legend.text = ggplot2::element_text(
size = legend_text_size,
face = legend_text_font_face,
family = legend_text_font_family,
color = legend_text_color
),
axis.text.x = ggplot2::element_text(
angle = axis_text_x_angle,
vjust = axis_text_x_vjust,
hjust = axis_text_x_hjust
)
)
# Position of title
if (title_position_to_plot) {
theme <- theme +
ggplot2::theme(
plot.title.position = "plot"
)
}
if (caption_position_to_plot) {
theme <- theme +
ggplot2::theme(
plot.caption.position = "plot"
)
}
# Position of caption
# Axis lines ?
if (axis_x & axis_y) {
theme <- theme +
ggplot2::theme(
axis.line = ggplot2::element_line(color = text_color)
)
}
if (!axis_x) {
theme <- theme +
ggplot2::theme(
axis.line.x = ggplot2::element_blank(),
axis.ticks.x = ggplot2::element_blank(),
axis.text.x = ggplot2::element_blank()
)
}
if (!axis_y) {
theme <- theme +
ggplot2::theme(
axis.line.y = ggplot2::element_blank(),
axis.ticks.y = ggplot2::element_blank(),
axis.text.y = ggplot2::element_blank()
)
}
if (!axis_line_x) {
theme <- theme +
ggplot2::theme(
axis.line.x = ggplot2::element_blank()
)
}
if (!axis_ticks_x) {
theme <- theme +
ggplot2::theme(
axis.ticks.x = ggplot2::element_blank()
)
}
if (!axis_text_x) {
theme <- theme +
ggplot2::theme(
axis.text.x = ggplot2::element_blank()
)
}
if (!axis_line_y) {
theme <- theme +
ggplot2::theme(
axis.line.y = ggplot2::element_blank()
)
}
if (!axis_ticks_y) {
theme <- theme +
ggplot2::theme(
axis.ticks.y = ggplot2::element_blank()
)
}
if (!axis_text_y) {
theme <- theme +
ggplot2::theme(
axis.text.y = ggplot2::element_blank()
)
}
# X - major grid lines
if (!grid_major_x) {
theme <- theme +
ggplot2::theme(
panel.grid.major.x = ggplot2::element_blank()
)
} else {
theme <- theme +
ggplot2::theme(
panel.grid.major.x = ggplot2::element_line(
color = grid_major_color,
linewidth = grid_major_x_size
)
)
}
# Y - major grid lines
if (!grid_major_y) {
theme <- theme +
ggplot2::theme(
panel.grid.major.y = ggplot2::element_blank()
)
} else {
theme <- theme +
ggplot2::theme(
panel.grid.major.y = ggplot2::element_line(
color = grid_major_color,
linewidth = grid_major_y_size
)
)
}
# X - minor grid lines
if (!grid_minor_x) {
theme <- theme +
ggplot2::theme(
panel.grid.minor.x = ggplot2::element_blank()
)
} else {
theme <- theme +
ggplot2::theme(
panel.grid.minor.x = ggplot2::element_line(
color = grid_minor_color,
linewidth = grid_minor_x_size
)
)
}
# Y - minor grid lines
if (!grid_minor_y) {
theme <- theme +
ggplot2::theme(
panel.grid.minor.y = ggplot2::element_blank()
)
} else {
theme <- theme +
ggplot2::theme(
panel.grid.minor.y = ggplot2::element_line(
color = grid_minor_color,
linewidth = grid_minor_y_size
)
)
}
if (!panel_border) {
theme <- theme +
ggplot2::theme(
panel.border = ggplot2::element_blank()
)
} else {
theme <- theme +
ggplot2::theme(
panel.border = ggplot2::element_rect(color = panel_background_color)
)
}
# Add facet title text size
theme <- theme +
ggplot2::theme(
strip.text = ggplot2::element_text(
size = facet_size,
family = facet_font_family,
face = facet_font_face,
color = facet_color
),
strip.background = ggplot2::element_rect(
fill = facet_bg_color,
linewidth = 0
)
)
# Other parameters
theme <- theme + ggplot2::theme(...)
return(theme)
}

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@ -1,10 +0,0 @@
#' @title Dumbbell Theme
#' @description Theme for dumbbell charts based on theme_default.
#'
#' @rdname theme_default
#'
#' @export
theme_dumbbell <- function() {
theme_default()
}

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@ -1,82 +0,0 @@
#' Custom Theme for Lollipop Charts
#'
#' @description
#' A custom theme specifically designed for lollipop charts with appropriate grid lines and axis styling
#' based on whether the chart is flipped (horizontal) or not.
#'
#' @param flip Logical indicating whether the lollipop chart is flipped (horizontal). Default is TRUE.
#' @param axis_text_x_angle Angle for x-axis text labels. Default is 0.
#' @param axis_text_x_vjust Vertical justification for x-axis text labels. Default is 0.5.
#' @param axis_text_x_hjust Horizontal justification for x-axis text labels. Default is 0.5.
#'
#' @return A ggplot2 theme object
#'
#' @rdname theme_default
#' @export
#'
#' @examples
#' \dontrun{
#' library(ggplot2)
#' df <- data.frame(x = letters[1:5], y = c(10, 5, 7, 12, 8))
#' ggplot(df, aes(x, y)) +
#' geom_point() +
#' theme_lollipop()
#' }
theme_lollipop <- function(
flip = TRUE,
axis_text_x_angle = 0,
axis_text_x_vjust = 0.5,
axis_text_x_hjust = 0.5) {
# Set parameters based on flip
if (!flip) {
par_axis_text_font_face <- "plain"
par_axis_x <- TRUE
par_axis_y <- TRUE
par_axis_line_y <- FALSE
par_axis_ticks_y <- TRUE
par_axis_text_y <- TRUE
par_axis_line_x <- TRUE
par_axis_ticks_x <- TRUE
par_axis_text_x <- TRUE
par_grid_major_y <- TRUE
par_grid_major_x <- FALSE
par_grid_minor_y <- TRUE
par_grid_minor_x <- FALSE
} else if (flip) {
par_axis_text_font_face <- "plain"
par_axis_x <- TRUE
par_axis_y <- TRUE
par_axis_line_y <- TRUE
par_axis_ticks_y <- TRUE
par_axis_text_y <- TRUE
par_axis_line_x <- FALSE
par_axis_ticks_x <- TRUE
par_axis_text_x <- TRUE
par_grid_major_y <- FALSE
par_grid_major_x <- TRUE
par_grid_minor_y <- FALSE
par_grid_minor_x <- TRUE
}
# Theme
t <- theme_default(
axis_text_font_face = par_axis_text_font_face,
axis_x = par_axis_x,
axis_y = par_axis_y,
grid_major_y = par_grid_major_y,
grid_major_x = par_grid_major_x,
grid_minor_y = par_grid_minor_y,
grid_minor_x = par_grid_minor_x,
axis_text_y = par_axis_text_y,
axis_line_y = par_axis_line_y,
axis_ticks_y = par_axis_ticks_y,
axis_text_x = par_axis_text_x,
axis_line_x = par_axis_line_x,
axis_ticks_x = par_axis_ticks_x,
axis_text_x_angle = axis_text_x_angle,
axis_text_x_vjust = axis_text_x_vjust,
axis_text_x_hjust = axis_text_x_hjust
)
return(t)
}

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@ -1,31 +0,0 @@
#' Custom Theme for Point Charts
#'
#' @param flip Logical. Whether the plot is flipped (horizontal).
#' @param axis_text_x_angle Angle for x-axis text.
#' @param axis_text_x_vjust Vertical justification for x-axis text.
#' @param axis_text_x_hjust Horizontal justification for x-axis text.
#'
#' @rdname theme_default
#'
#' @return A custom theme object.
#'
#' @export
theme_point <- function() {
t <- theme_default(
axis_text_font_face = "plain",
axis_x = TRUE,
axis_y = TRUE,
grid_major_y = TRUE,
grid_major_x = TRUE,
grid_minor_y = FALSE,
grid_minor_x = FALSE,
axis_text_x = TRUE,
axis_line_x = TRUE,
axis_ticks_x = TRUE,
axis_text_x_angle = 0,
axis_text_x_vjust = 0.5,
axis_text_x_hjust = 0
)
return(t)
}

290
R/theme_reach.R Normal file
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@ -0,0 +1,290 @@
#' @title ggplot2 theme with REACH color palettes
#'
#' @param initiative Either "reach" or "default".
#' @param palette Palette name from 'pal_reach()'.
#' @param discrete Boolean indicating whether color aesthetic is discrete or not.
#' @param reverse Boolean indicating whether the palette should be reversed.
#' @param font_family The font family for all plot's texts. Default to "Segoe UI".
#' @param title_size The size of the title. Defaults to 12.
#' @param title_color Title color.
#' @param title_font_face Title font face. Default to "bold". Font face ("plain", "italic", "bold", "bold.italic").
#' @param title_hjust Title horizontal justification. Default to NULL. Use 0.5 to center the title.
#' @param text_size The size of all text other than the title, subtitle and caption. Defaults to 10.
#' @param text_color Text color.
#' @param text_font_face Text font face. Default to "bold". Font face ("plain", "italic", "bold", "bold.italic").
#' @param panel_background_color The color for the panel background color. Default to white.
#' @param panel_border Boolean. Plot a panel border? Default to FALSE.
#' @param panel_border_color A color. Default to REACH main grey.
#' @param legend_position Position of the legend; Default to "right". Can take "right", "left", "top", "bottom" or "none".
#' @param legend_direction Direction of the legend. Default to "vertical". Can take "vertical" or "horizontal".
#' @param legend_title_size Legend title size.
#' @param legend_title_color Legend title color.
#' @param legend_title_font_face Legend title font face. Default to "plain". Font face ("plain", "italic", "bold", "bold.italic").
#' @param legend_text_size Legend text size.
#' @param legend_text_color Legend text color.
#' @param legend_text_font_face Legend text font face. Default to "plain". Font face ("plain", "italic", "bold", "bold.italic").
#' @param legend_reverse Reverse the color in the guide? Default to TRUE.
#' @param title_size The size of the legend title. Defaults to 11.
#' @param title_color Legend title color.
#' @param title_font_face Legend title font face. Default to "plain". Font face ("plain", "italic", "bold", "bold.italic").
#' @param title_position_to_plot TRUE or FALSE. Positioning to plot or to panel?
#' @param axis_x Boolean. Do you need x-axis?
#' @param axis_y Boolean. Do you need y-axis?
#' @param axis_text_size Axis text size.
#' @param axis_text_color Axis text color.
#' @param axis_text_font_face Axis text font face. Default to "plain". Font face ("plain", "italic", "bold", "bold.italic").
#' @param axis_text_x_angle Angle for the x-axis text.
#' @param axis_text_x_vjust Vertical adjustment for the x-axis text.
#' @param axis_text_x_hjust Vertical adjustment for the x-axis text.
#' @param axis_title_size Axis title size.
#' @param axis_title_color Axis title color.
#' @param axis_title_font_face Axis title font face. Default to "plain". Font face ("plain", "italic", "bold", "bold.italic").
#' @param grid_major_x Boolean. Do you need major grid lines for x-axis?
#' @param grid_major_y Boolean. Do you need major grid lines for y-axis?
#' @param grid_major_x_size Major X line size.
#' @param grid_major_y_size Major Y line size.
#' @param grid_major_color Major grid lines color.
#' @param grid_minor_x Boolean. Do you need minor grid lines for x-axis?
#' @param grid_minor_y Boolean. Do you need minor grid lines for y-axis?
#' @param grid_minor_x_size Minor X line size.
#' @param grid_minor_y_size Minor Y line size.
#' @param grid_minor_color Minor grid lines color.
#' @param caption_position_to_plot TRUE or FALSE. Positioning to plot or to panel?
#' @param ... Additional arguments passed to `ggplot2::gg_theme()`.
#'
#'
#' @description Give some reach colors and fonts to a ggplot.
#'
#' @return The base REACH theme
#'
#' @export
theme_reach <- function(
initiative = "reach",
palette = "main",
discrete = TRUE,
reverse = FALSE,
font_family = "Segoe UI",
title_size = 12,
title_color = cols_reach("main_grey"),
title_font_face = "bold",
title_hjust = NULL,
title_position_to_plot = TRUE,
text_size = 10,
text_color = cols_reach("main_grey"),
text_font_face = "plain",
panel_background_color = "#FFFFFF",
panel_border = FALSE,
panel_border_color = cols_reach("main_grey"),
legend_position = "right",
legend_direction = "vertical",
legend_reverse = TRUE,
legend_title_size = 11,
legend_title_color = cols_reach("main_grey"),
legend_title_font_face = "plain",
legend_text_size = 10,
legend_text_color = cols_reach("main_grey"),
legend_text_font_face = "plain",
axis_x = TRUE,
axis_y = TRUE,
axis_text_size = 10,
axis_text_color = cols_reach("main_grey"),
axis_text_font_face = "plain",
axis_title_size = 11,
axis_title_color = cols_reach("main_grey"),
axis_title_font_face = "bold",
axis_text_x_angle = 0,
axis_text_x_vjust = 0.5,
axis_text_x_hjust = 0.5,
grid_major_x = FALSE,
grid_major_y = FALSE,
grid_major_color = cols_reach("main_lt_grey"),
grid_major_x_size = 0.1,
grid_major_y_size = 0.1,
grid_minor_x = FALSE,
grid_minor_y = FALSE,
grid_minor_color = cols_reach("main_lt_grey"),
grid_minor_x_size = 0.05,
grid_minor_y_size = 0.05,
caption_position_to_plot = TRUE,
...
) {
# To do :
# - add facet theming
if (!initiative %in% c("reach", "default"))
rlang::abort(
c(
paste0("There is no initiative '", initiative, " to be used with theme_reach()."),
"i" = paste0("initiative should be either 'reach' or 'default'")
)
)
# Basic simple theme
# theme_reach <- ggplot2::theme_bw()
theme_reach <- ggplot2::theme(
# Title - design
title = ggplot2::element_text(
family = font_family,
color = title_color,
size = title_size,
face = title_font_face
),
# Text - design
text = ggplot2::element_text(
family = font_family,
color = text_color,
size = text_size,
face = text_font_face
),
# Default legend to right position
legend.position = legend_position,
# Defaut legend to vertical direction
legend.direction = legend_direction,
# set panel background color
panel.background = ggplot2::element_rect(
fill = panel_background_color
),
# Remove background for legend key
legend.key = ggplot2::element_blank(),
# Text sizes
axis.text = ggplot2::element_text(
size = axis_text_size,
family = font_family,
face = axis_text_font_face,
color = axis_text_color
),
axis.title = ggplot2::element_text(
size = axis_title_size,
family = font_family,
face = axis_title_font_face,
color = axis_title_color),
# Wrap title
plot.title = ggtext::element_textbox(
hjust = title_hjust
),
plot.subtitle = ggtext::element_textbox(
hjust = title_hjust
),
plot.caption = ggtext::element_textbox(),
legend.title = ggplot2::element_text(
size = legend_title_size,
face = legend_title_font_face,
family = font_family,
color = legend_title_color),
legend.text = ggplot2::element_text(
size = legend_text_size,
face = legend_text_font_face,
family = font_family,
color = legend_text_color
),
axis.text.x = ggplot2::element_text(
angle = axis_text_x_angle,
vjust = axis_text_x_vjust,
hjust = axis_text_x_hjust
)
)
# Position of title
if (title_position_to_plot) theme_reach <- theme_reach +
ggplot2::theme(
plot.title.position = "plot"
)
if (caption_position_to_plot) theme_reach <- theme_reach +
ggplot2::theme(
plot.caption.position = "plot"
)
# Position of caption
# Axis lines ?
if (axis_x & axis_y) {
theme_reach <- theme_reach +
ggplot2::theme(
axis.line = ggplot2::element_line(color = text_color))
}
if (!axis_x) {
theme_reach <- theme_reach +
ggplot2::theme(
axis.line.x = ggplot2::element_blank(),
axis.ticks.x = ggplot2::element_blank(),
axis.text.x = ggplot2::element_blank())
}
if (!axis_y) {
theme_reach <- theme_reach +
ggplot2::theme(
axis.line.y = ggplot2::element_blank(),
axis.ticks.y = ggplot2::element_blank(),
axis.text.y = ggplot2::element_blank())
}
# X - major grid lines
if (!grid_major_x) theme_reach <- theme_reach +
ggplot2::theme(
panel.grid.major.x = ggplot2::element_blank()
) else theme_reach <- theme_reach +
ggplot2::theme(
panel.grid.major.x = ggplot2::element_line(
color = grid_major_color,
linewidth = grid_major_x_size)
)
# Y - major grid lines
if (!grid_major_y) theme_reach <- theme_reach +
ggplot2::theme(
panel.grid.major.y = ggplot2::element_blank()
) else theme_reach <- theme_reach +
ggplot2::theme(
panel.grid.major.y = ggplot2::element_line(
color = grid_major_color,
linewidth = grid_major_y_size)
)
# X - minor grid lines
if (!grid_minor_x) theme_reach <- theme_reach +
ggplot2::theme(
panel.grid.minor.x = ggplot2::element_blank()
) else theme_reach <- theme_reach +
ggplot2::theme(
panel.grid.minor.x = ggplot2::element_line(
color = grid_minor_color,
linewidth = grid_minor_x_size)
)
# Y - minor grid lines
if (!grid_minor_y) theme_reach <- theme_reach +
ggplot2::theme(
panel.grid.minor.y = ggplot2::element_blank()
) else theme_reach <- theme_reach +
ggplot2::theme(
panel.grid.minor.y = ggplot2::element_line(
color = grid_minor_color,
linewidth = grid_minor_y_size)
)
if (!panel_border) theme_reach <- theme_reach +
ggplot2::theme(
panel.border = ggplot2::element_blank()
) else theme_reach <- theme_reach +
ggplot2::theme(
panel.border = ggplot2::element_rect(color = panel_background_color)
)
# Other parameters
theme_reach <- theme_reach + ggplot2::theme(...)
# Add reach color palettes by default
# (reversed guide is defaulted to TRUE for natural reading)
theme_reach <- list(
theme_reach,
scale_color(initiative = initiative, palette = palette, discrete = discrete, reverse = reverse, reverse_guide = legend_reverse),
scale_fill(initiative = initiative, palette = palette, discrete = discrete, reverse = reverse, reverse_guide = legend_reverse)
)
return(theme_reach)
}

79
R/treemap.R Normal file
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@ -0,0 +1,79 @@
#' @title Simple treemap chart
#'
#' @param df A data frame.
#' @param x A character column or coercible as a character column. Will give the treemap's fill color and text.
#' @param y A numeric column of proportions (0 to 100 or 0 to 1).
#' @param tile_border_size Size of the inter-tile space (default to 2).
#' @param tile_start The corner in which to start placing the tiles. One of 'bottomleft' (the default), 'topleft', 'topright' or 'bottomright'. See `treemapify::geom_treemap()`.
#' @param tile_corner_radius The corner radius (defaults to `grid::unit(0, "pt")`). See `treemapify::geom_treemap()`.
#' @param tile_text Boolean. If true, add a text label to each tile (the default). If false, use a side legend only.
#' @param tile_text_size A size (defaults to 20).
#' @param tile_text_color A color (defaults to "white").
#' @param tile_text_threshold_display Minimum value to add the text label to the tile (defaults to 4).
#' @param tile_text_place Where inside the box to place the text. Default is 'bottom'; other options are 'topleft', 'top', 'topright', etc. See `treemapify::geom_treemap()`.
#' @param x_title The x scale title. Default to NULL.
#' @param title Plot title. Default to NULL.
#' @param subtitle Plot subtitle. Default to NULL.
#' @param caption Plot caption. Default to NULL.
#' @param theme Whatever theme. Default to theme_reach().
#'
#' @return A waffle chart
#'
#' @export
treemap <- function(df,
x,
y,
tile_border_size = 2,
tile_start = "topleft",
tile_corner_radius = grid::unit(0, "pt"),
tile_text = TRUE,
tile_text_size = 20,
tile_text_color = "white",
tile_text_threshold_display = 4,
tile_text_place = "middle",
x_title = NULL,
title = NULL,
subtitle = NULL,
caption = NULL,
theme = theme_reach(reverse = TRUE, panel_border = FALSE, axis_x = FALSE, axis_y = FALSE)
){
# Make plot
g <- ggplot2::ggplot(
data = df,
ggplot2::aes(area = {{ y }}, fill = {{ x }}, label = {{ x }}))
# Add tile
g <- g + treemapify::geom_treemap(
size = tile_border_size,
radius = tile_corner_radius,
color = "white",
start = tile_start
)
# Add title, subtitle, caption, x_title, y_title
g <- g + ggplot2::labs(
title = title,
subtitle = subtitle,
caption = caption,
fill = x_title,
)
# Theme
g <- g + theme
# If tile_text, show text on tiles and remove legend
if (tile_text) {
g <- g + treemapify::geom_treemap_text(
place = tile_text_place,
start = tile_start,
min.size = tile_text_threshold_display,
color = tile_text_color,
size = tile_text_size
) +
ggplot2::theme(legend.position = "none")
}
return(g)
}

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@ -2,5 +2,6 @@
"_PACKAGE"
## usethis namespace: start
#' @importFrom rlang :=
## usethis namespace: end
NULL

74
R/waffle.R Normal file
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@ -0,0 +1,74 @@
#' @title Simple waffle chart
#'
#' @param df A data frame.
#' @param x A character column or coercible as a character column. Will give the waffle's fill color.
#' @param y A numeric column (if plotting proportion, make sure to have percentages between 0 and 100 and not 0 and 1).
#' @param n_rows Number of rows. Default to 10.
#' @param size Width of the separator between blocks (defaults to 2).
#' @param x_title The x scale title. Default to NULL.
#' @param x_lab The x scale caption. Default to NULL.
#' @param title Plot title. Default to NULL.
#' @param subtitle Plot subtitle. Default to NULL.
#' @param caption Plot caption. Default to NULL.
#' @param arrange TRUE or FALSE. Arrange by highest percentage first.
#' @param theme Whatever theme. Default to theme_reach().
#'
#' @return A waffle chart
#'
#' @export
waffle <- function(df,
x,
y,
n_rows = 10,
size = 2,
x_title = NULL,
x_lab = NULL,
title = NULL,
subtitle = NULL,
caption = NULL,
arrange = TRUE,
theme = theme_reach(
axis_x = FALSE,
axis_y = FALSE,
legend_position = "bottom",
legend_direction = "horizontal",
title_hjust = 0.5)){
# A basic and not robust check
# - add check between 0 and 1
# Arrange by biggest prop first ?
if (arrange) df <- dplyr::arrange(
df,
dplyr::desc({{ y }})
)
# Mutate to 100
# df <- dplyr::mutate(df, "{{y}}" := {{ y }} * 100)
# Prepare named vector
values <- stats::setNames(dplyr::pull(df, {{ y }}), dplyr::pull(df, {{ x }}))
# Make plot
g <- waffle::waffle(values, xlab = x_lab, rows = n_rows, size = size)
# Add title, subtitle, caption, x_title, y_title
g <- g + ggplot2::labs(
title = title,
subtitle = subtitle,
caption = caption,
fill = x_title,
color = x_title
)
# Basic theme
# g <- g +
# hrbrthemes::theme_ipsum() #+
# waffle::theme_enhance_waffle()
# Add theme
g <- g + theme
return(g)
}

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@ -16,24 +16,20 @@ knitr::opts_chunk$set(
dev.args = list(type = "cairo")
)
desc <- read.dcf("DESCRIPTION")
desc <- setNames(as.list(desc), colnames(desc))
desc = read.dcf('DESCRIPTION')
desc = setNames(as.list(desc), colnames(desc))
```
# `r desc$Package` <img src="man/figures/logo.png" align="right" width="120"/>
<!-- badges: start -->
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# `r desc$Package` <img src="man/figures/logo.png" align="right" alt="" width="120"/>
> `r desc$Title`
`visualizeR` proposes some utils to sane colors, ready-to-go color palettes, and a few visualization functions. The package is thoroughly tested with comprehensive code coverage.
`visualizeR` proposes some utils to get REACH and AGORA colors, ready-to-go color palettes, and a few visualization functions (horizontal hist graph for instance).
## Installation
You can install the last version of visualizeR from [GitHub](https://github.com/) with:
You can install the last version of visualizeR from
[GitHub](https://github.com/) with:
```{r, eval = FALSE}
# install.packages("devtools")
@ -44,46 +40,42 @@ devtools::install_github("gnoblet/visualizeR", build_vignettes = TRUE)
Roadmap is as follows:
- [ ] Full revamp of core functions (colors, pattern, incl. adding test and pre-commit structures)
- [x] Add test coverage reporting via codecov
- [ ] Maintain >80% test coverage across all functions
- [ ] Add other types of plots:
- [ ] Dumbell
- [ ] Waffle
- [ ] Donut
- [ ] Alluvial
- [ ] Option for tag with css code + for titles/subtitles/captions
- [X] Add IMPACT's colors
- [X] Add all color palettes from the internal documentation
- [ ] There remains to be added more-than-7-color palettes and black color palettes
- [X] Add new types of visualization (e.g. dumbbell plot, lollipop plot, etc.)
- [X] Use examples
- [ ] Add some ease-map functions
- [ ] Add some interactive functions (maps and graphs)
- [ ] Consolidate and make errors transparent
## Request
Please, do not hesitate to pull request any new viz or colors or color palettes, or to email request any change ([gnoblet\@zaclys.net](mailto:gnoblet@zaclys.net){.email}).
## Code Coverage
`visualizeR` uses [codecov](https://codecov.io/) for test coverage reporting. You can see the current coverage status by clicking on the codecov badge at the top of this README. We aim to maintain high test coverage to ensure code reliability and stability.
Please, do not hesitate to pull request any new viz or colors or color palettes, or to email request any change (guillaume.noblet@reach-initiative.org or gnoblet@zaclys.net).
## Colors
Functions to access colors and palettes are `color()` or `palette()`. Feel free to pull request new colors.
Color palettes for REACH, AGORA and IMPACT are available. Functions to access colors and palettes are `cols_initiative()` or `pal_initiative()`. For now, the initiative with the most colors and color palettes is REACH. Feel free to pull requests new AGORA and IMPACT colors.
```{r example-colors, eval = TRUE}
library(visualizeR)
# Get all saved colors, named
color(unname = F)[1:10]
# Get all saved REACH colors, named
cols_reach(unnamed = F)[1:10]
# Extract a color palette as hexadecimal codes and reversed
palette(palette = "cat_5_main", reversed = TRUE, color_ramp_palette = FALSE)
pal_reach(palette = "main", reversed = TRUE, color_ramp_palette = FALSE)
# Get all color palettes names
palette(show_palettes = TRUE)
pal_reach(show_palettes = T)
```
## Charts
### Example 1: Bar chart
### Example 1: Bar chart, already REACH themed
```{r example-bar-chart, out.width = '65%', eval = TRUE}
```{r example-bar-chart, out.width = "65%", eval = TRUE}
library(visualizeR)
library(palmerpenguins)
library(dplyr)
@ -91,49 +83,42 @@ df <- penguins |>
group_by(island, species) |>
summarize(
mean_bl = mean(bill_length_mm, na.rm = T),
mean_fl = mean(flipper_length_mm, na.rm = T)
) |>
ungroup()
df_island <- penguins |>
group_by(island) |>
summarize(
mean_bl = mean(bill_length_mm, na.rm = T),
mean_fl = mean(flipper_length_mm, na.rm = T)
) |>
mean_fl = mean(flipper_length_mm, na.rm = T)) |>
ungroup()
# Simple bar chart by group with some alpha transparency
bar(df, "island", "mean_bl", "species", x_title = "Mean of bill length", title = "Mean of bill length by island and species")
bar(df, island, mean_bl, species, percent = FALSE, alpha = 0.6, x_title = "Mean of bill length")
# Flipped / Horizontal
hbar(df, "island", "mean_bl", "species", x_title = "Mean of bill length", title = "Mean of bill length by island and species")
# Using another color palette through `theme_reach()` and changing scale to percent
bar(df, island,mean_bl, species, percent = TRUE, theme = theme_reach(palette = "artichoke_3"))
# Facetted
bar(df, "island", "mean_bl", facet = "species", x_title = "Mean of bill length", title = "Mean of bill length by island and species", add_color_guide = FALSE)
# Not flipped, with text added, group_title, no y-axis and no bold for legend
bar(df, island, mean_bl, species, group_title = "Species", flip = FALSE, add_text = TRUE, add_text_suffix = "%", percent = FALSE, theme = theme_reach(text_font_face = "plain", axis_y = FALSE))
# Flipped, with text, smaller width, and caption
hbar(df = df_island, x = "island", y = "mean_bl", title = "Mean of bill length by island", add_text = T, width = 0.6, add_text_suffix = "mm", add_text_expand_limit = 1.3, add_color_guide = FALSE, caption = "Data: palmerpenguins package.")
```
### Example 2: Scatterplot
### Example 2: Point chart, already REACH themed
```{r example-point-chart, out.width = '65%', eval = TRUE}
# Simple scatterplot
point(penguins, "bill_length_mm", "flipper_length_mm")
At this stage, `point_reach()` only supports categorical grouping colors with the `group` arg.
# Scatterplot with grouping colors, greater dot size, some transparency
point(penguins, "bill_length_mm", "flipper_length_mm", "island", group_title = "Island", alpha = 0.6, size = 3, title = "Bill vs. flipper length", , add_color_guide = FALSE)
```{r example-point-chart, out.width = "65%", eval = TRUE}
# Facetted scatterplot by island
point(penguins, "bill_length_mm", "flipper_length_mm", "species", "island", "fixed", group_title = "Species", title = "Bill vs. flipper length by species and island", add_color_guide = FALSE)
# Simple point chart
point(penguins, bill_length_mm, flipper_length_mm)
# Point chart with grouping colors, greater dot size, some transparency, reversed color palette
point(penguins, bill_length_mm, flipper_length_mm, island, alpha = 0.6, size = 3, theme = theme_reach(reverse = TRUE))
# Using another color palettes
point(penguins, bill_length_mm, flipper_length_mm, island, size = 1.5, x_title = "Bill", y_title = "Flipper", title = "Length (mm)", theme = theme_reach(palette = "artichoke_3", text_font_face = , grid_major_x = TRUE, title_position_to_plot = FALSE))
```
### Example 3: Dumbbell plot
### Example 3: Dumbbell plot, REACH themed
Remember to ensure that your data are in the long format and you only have two groups on the x-axis; for instance, IDP and returnee and no NA values.
```{r example-dumbbell-plot, out.width = '65%', eval = TRUE}
```{r example-dumbbell-plot, out.width = "65%", eval = TRUE}
# Prepare long data
df <- tibble::tibble(
admin1 = rep(letters[1:8], 2),
@ -142,23 +127,31 @@ df <- tibble::tibble(
) |>
dplyr::mutate(stat = round(stat, 0))
# Example, adding a parameter to `theme_reach()` passed on `ggplot2::theme()` to align legend title
# dumbbell(
# df,
# 'stat',
# 'setting',
# 'admin1',
# title = '% of HHs that reported open defecation as sanitation facility',
# group_y_title = 'Admin 1',
# group_x_title = 'Setting'
# )
dumbbell(df,
stat,
setting,
admin1,
title = "% of HHs that reported open defecation as sanitation facility",
group_y_title = "Admin 1",
group_x_title = "Setting",
theme = theme_reach(legend_position = "bottom",
legend_direction = "horizontal",
legend_title_font_face = "bold",
palette = "primary",
title_position_to_plot = FALSE,
legend.title.align = 0.5)) +
# Change legend title position (could be included as part of the function)
ggplot2::guides(
color = ggplot2::guide_legend(title.position = "left"),
fill = ggplot2::guide_legend(title.position = "left")
)
```
### Example 4: donut chart
### Example 4: donut chart, REACH themed (to used once, not twice)
```{r example-donut-plot, out.width = "65%", warning = FALSE}
```{r example-donut-plot, out.width = '65%', warning = FALSE}
# Some summarized data: % of HHs by displacement status
df <- tibble::tibble(
status = c("Displaced", "Non displaced", "Returnee", "Don't know/Prefer not to say"),
@ -166,124 +159,137 @@ df <- tibble::tibble(
)
# Donut
# donut(df,
# status,
# percentage,
# hole_size = 3,
# add_text_suffix = '%',
# add_text_color = color('dark_grey'),
# add_text_treshold_display = 5,
# x_title = 'Displacement status',
# title = '% of HHs by displacement status'
# )
donut(df,
status,
percentage,
hole_size = 3,
add_text_suffix = "%",
add_text_color = cols_reach("dk_grey"),
add_text_treshold_display = 5,
x_title = "Displacement status",
title = "% of HHs by displacement status",
theme = theme_reach(legend_reverse = TRUE,
axis_x = FALSE))
```
### Example 5: Waffle chart
```{r example-waffle-plot, out.width = '65%', warning = FALSE}
### Example 5: waffle chart
```{r example-waffle-plot, out.width = "65%", warning = FALSE}
#
# waffle(df, status, percentage, x_title = 'A caption', title = 'A title', subtitle = 'A subtitle')
waffle(df, status, percentage, x_title = "A caption", title = "A title", subtitle = "A subtitle")
```
### Example 6: Alluvial chart
```{r example-alluvial-plot, out.width = '65%', warning = FALSE}
### Example 6: alluvial chart, REACH themed
```{r example-alluvial-plot, out.width = "65%", warning = FALSE}
# Some summarized data: % of HHs by self-reported status of displacement in 2021 and in 2022
df <- tibble::tibble(
status_from = c(
rep("Displaced", 4),
status_from = c(rep("Displaced", 4),
rep("Non displaced", 4),
rep("Returnee", 4),
rep("Dnk/Pnts", 4)
),
rep("Dnk/Pnts", 4)),
status_to = c("Displaced", "Non displaced", "Returnee", "Dnk/Pnts", "Displaced", "Non displaced", "Returnee", "Dnk/Pnts", "Displaced", "Non displaced", "Returnee", "Dnk/Pnts", "Displaced", "Non displaced", "Returnee", "Dnk/Pnts"),
percentage = c(20, 8, 18, 1, 12, 21, 0, 2, 0, 3, 12, 1, 0, 0, 1, 1)
)
# Alluvial, here the group is the status for 2021
# alluvial(df,
# status_from,
# status_to,
# percentage,
# status_from,
# from_levels = c("Displaced", "Non displaced", "Returnee", "Dnk/Pnts"),
# alpha = 0.8,
# group_title = "Status for 2021",
# title = "% of HHs by self-reported status from 2021 to 2022"
# )
alluvial(df,
status_from,
status_to,
percentage,
status_from,
from_levels = c("Displaced", "Non displaced", "Returnee", "Dnk/Pnts"),
alpha = 0.8,
group_title = "Status for 2021",
title = "% of HHs by self-reported status from 2021 to 2022",
theme = theme_reach(
axis_y = FALSE,
legend_position = "none"))
```
### Example 7: Lollipop chart
```{r example-lollipop-chart, out.width = "65%", warning = FALSE, eval = TRUE}
### Example 7: lollipop chart
```{r example-lollipop-chart, out.width = "65%", warning = FALSE}
library(tidyr)
# Prepare long data
df <- tibble::tibble(
admin1 = replicate(15, sample(letters, 8)) |> t() |> as.data.frame() |> unite("admin1", sep = "") |> dplyr::pull(admin1),
stat = rnorm(15, mean = 50, sd = 15)
) |>
stat = rnorm(15, mean = 50, sd = 15)) |>
dplyr::mutate(stat = round(stat, 0))
# Simple vertical lollipop chart
lollipop(
df = df,
x = "admin1",
y = "stat",
# Make lollipop plot, REACH themed, vertical with 45 degrees angle X-labels
lollipop(df,
admin1,
stat,
arrange = FALSE,
add_text = FALSE,
flip = FALSE,
dot_size = 3,
y_title = "% of HHs",
x_title = "Admin 1",
title = "% of HHs that received humanitarian assistance"
)
title = "% of HHs that reported having received a humanitarian assistance",
theme = theme_reach(axis_text_x_angle = 45,
grid_major_y = TRUE,
grid_major_y_size = 0.2,
grid_major_x = TRUE,
grid_minor_y = TRUE))
# Horizontal lollipop chart with custom colors
hlollipop(
df = df,
x = "admin1",
y = "stat",
dot_size = 4,
line_size = 1,
add_color = color("cat_5_main_2"),
line_color = color("cat_5_main_4"),
# Horizontal, greater point size, arranged by value, no grid, and text labels added
lollipop(df,
admin1,
stat,
arrange = TRUE,
point_size = 10,
point_color = cols_reach("main_beige"),
segment_size = 2,
add_text = TRUE,
add_text_suffix = "%",
y_title = "% of HHs",
x_title = "Admin 1",
title = "% of HHs that received humanitarian assistance"
)
title = "% of HHs that reported having received a humanitarian assistance in the 12 months prior to the assessment",
theme = theme_reach(title_position_to_plot = FALSE))
# Create data for grouped lollipop - using set.seed for reproducibility
set.seed(123)
df_grouped <- tibble::tibble(
admin1 = rep(c("A", "B", "C", "D", "E", "F"), 2),
group = rep(c("Group A", "Group B"), each = 6),
stat = c(rnorm(6, mean = 40, sd = 10), rnorm(6, mean = 60, sd = 10))
) |>
dplyr::mutate(stat = round(stat, 0))
# Grouped lollipop chart with proper side-by-side positioning
lollipop(
df = df_grouped,
x = "admin1",
y = "stat",
group = "group",
order = "grouped_y",
dot_size = 3.5,
line_size = 0.8,
y_title = "Value",
x_title = "Category",
title = "True side-by-side grouped lollipop chart"
)
```
# Horizontal grouped lollipop chart
hlollipop(
df = df_grouped,
x = "admin1",
y = "stat",
group = "group",
dot_size = 3.5,
line_size = 0.8,
y_title = "Category",
x_title = "Value",
title = "Horizontal side-by-side grouped lollipop chart"
## Maps
```{r example-map, out.width = "50%"}
# Add indicator layer
# - based on "pretty" classes and title "Proportion (%)"
# - buffer to add a 10% around the bounding box
map <- add_indicator_layer(
indicator_admin1,
opn_dfc,
buffer = 0.1) +
# Layout - some defaults - add the map title
add_layout("% of HH that reported open defecation as sanitation facility") +
# Admin boundaries as list of shape files (lines) and colors, line widths and labels as vectors
add_admin_boundaries(
lines = list(line_admin1, border_admin0, frontier_admin0),
colors = cols_reach("main_lt_grey", "dk_grey", "black"),
lwds = c(0.5, 2, 3),
labels = c("Department", "Country", "Dominican Rep. frontier"),
title = "Administrative boundaries") +
# Add text labels - centered on admin 1 centroids
add_admin_labels(centroid_admin1, ADM1_FR_UPPER) +
# Add a compass
add_compass() +
# Add a scale bar
add_scale_bar() +
# Add credits
add_credits("Admin. boundaries. : CNIGS \nCoord. system: GCS WGS 1984")
```
```{r map-save, eval = TRUE, include = FALSE, echo = TRUE}
tmap::tmap_save(map,
"man/figures/README-example-map.png",
height = 4.5,
width = 6
)
```
![Once exported with `tmap::tmap_save()`.](man/figures/README-example-map.png)

350
README.md
View file

@ -1,20 +1,13 @@
<!-- README.md is generated from README.Rmd. Please edit that file -->
# visualizeR <img src="man/figures/logo.png" align="right" width="120"/>
# visualizeR <img src="man/figures/logo.png" align="right" alt="" width="120"/>
<!-- badges: start -->
> What a color\! What a viz\!
[![R-CMD-check](https://github.com/gnoblet/visualizeR/actions/workflows/R-CMD-check.yml/badge.svg)](https://github.com/gnoblet/visualizeR/actions/workflows/R-CMD-check.yml)
[![Codecov test
coverage](https://codecov.io/gh/gnoblet/visualizeR/branch/main/graph/badge.svg)](https://app.codecov.io/gh/gnoblet/visualizeR?branch=main)
<!-- badges: end -->
> What a color! What a viz!
`visualizeR` proposes some utils to sane colors, ready-to-go color
palettes, and a few visualization functions. The package is thoroughly
tested with comprehensive code coverage.
`visualizeR` proposes some utils to get REACH and AGORA colors,
ready-to-go color palettes, and a few visualization functions
(horizontal hist graph for instance).
## Installation
@ -30,65 +23,64 @@ devtools::install_github("gnoblet/visualizeR", build_vignettes = TRUE)
Roadmap is as follows:
- [ ] Full revamp of core functions (colors, pattern, incl. adding test
and pre-commit structures)
- [x] Add test coverage reporting via codecov
- [ ] Maintain \>80% test coverage across all functions
- [ ] Add other types of plots:
- [ ] Dumbell
- [ ] Waffle
- [ ] Donut
- [ ] Alluvial
- [ ] Option for tag with css code + for titles/subtitles/captions
- \[X\] Add IMPACTs colors
- \[X\] Add all color palettes from the internal documentation
- \[ \] There remains to be added more-than-7-color palettes and black
color palettes
- \[X\] Add new types of visualization (e.g. dumbbell plot, lollipop
plot, etc.)
- \[X\] Use examples
- \[ \] Add some ease-map functions
- \[ \] Add some interactive functions (maps and graphs)
- \[ \] Consolidate and make errors transparent
## Request
Please, do not hesitate to pull request any new viz or colors or color
palettes, or to email request any change (<gnoblet@zaclys.net>).
## Code Coverage
`visualizeR` uses [codecov](https://codecov.io/) for test coverage
reporting. You can see the current coverage status by clicking on the
codecov badge at the top of this README. We aim to maintain high test
coverage to ensure code reliability and stability.
palettes, or to email request any change
(<guillaume.noblet@reach-initiative.org> or <gnoblet@zaclys.net>).
## Colors
Functions to access colors and palettes are `color()` or `palette()`.
Feel free to pull request new colors.
Color palettes for REACH, AGORA and IMPACT are available. Functions to
access colors and palettes are `cols_initiative()` or
`pal_initiative()`. For now, the initiative with the most colors and
color palettes is REACH. Feel free to pull requests new AGORA and IMPACT
colors.
``` r
library(visualizeR)
# Get all saved colors, named
color(unname = F)[1:10]
#> white lighter_grey light_grey dark_grey light_blue_grey
#> "#FFFFFF" "#F5F5F5" "#E3E3E3" "#464647" "#B3C6D1"
#> grey black cat_2_yellow_1 cat_2_yellow_2 cat_2_light_1
#> "#71716F" "#000000" "#ffc20a" "#0c7bdc" "#fefe62"
# Get all saved REACH colors, named
cols_reach(unnamed = F)[1:10]
#> white black main_grey main_red main_lt_grey main_beige
#> "#FFFFFF" "#000000" "#58585A" "#EE5859" "#C7C8CA" "#D2CBB8"
#> iroise_1 iroise_2 iroise_3 iroise_4
#> "#DFECEF" "#B1D7E0" "#699DA3" "#236A7A"
# Extract a color palette as hexadecimal codes and reversed
palette(palette = "cat_5_main", reversed = TRUE, color_ramp_palette = FALSE)
#> [1] "#083d77" "#4ecdc4" "#f4c095" "#b47eb3" "#ffd5ff"
pal_reach(palette = "main", reversed = TRUE, color_ramp_palette = FALSE)
#> [1] "#58585A" "#EE5859" "#C7C8CA" "#D2CBB8"
# Get all color palettes names
palette(show_palettes = TRUE)
#> [1] "cat_2_yellow" "cat_2_light"
#> [3] "cat_2_green" "cat_2_blue"
#> [5] "cat_5_main" "cat_5_ibm"
#> [7] "cat_3_aquamarine" "cat_3_tol_high_contrast"
#> [9] "cat_8_tol_adapted" "cat_3_custom_1"
#> [11] "cat_4_custom_1" "cat_5_custom_1"
#> [13] "cat_6_custom_1" "div_5_orange_blue"
#> [15] "div_5_green_purple"
pal_reach(show_palettes = T)
#> [1] "main" "primary" "secondary" "two_dots"
#> [5] "two_dots_flashy" "red_main" "red_main_5" "red_alt"
#> [9] "red_alt_5" "iroise" "iroise_5" "discrete_6"
#> [13] "red_2" "red_3" "red_4" "red_5"
#> [17] "red_6" "red_7" "green_2" "green_3"
#> [21] "green_4" "green_5" "green_6" "green_7"
#> [25] "artichoke_2" "artichoke_3" "artichoke_4" "artichoke_5"
#> [29] "artichoke_6" "artichoke_7" "blue_2" "blue_3"
#> [33] "blue_4" "blue_5" "blue_6" "blue_7"
```
## Charts
### Example 1: Bar chart
### Example 1: Bar chart, already REACH themed
``` r
library(visualizeR)
library(palmerpenguins)
library(dplyr)
@ -96,74 +88,61 @@ df <- penguins |>
group_by(island, species) |>
summarize(
mean_bl = mean(bill_length_mm, na.rm = T),
mean_fl = mean(flipper_length_mm, na.rm = T)
) |>
ungroup()
df_island <- penguins |>
group_by(island) |>
summarize(
mean_bl = mean(bill_length_mm, na.rm = T),
mean_fl = mean(flipper_length_mm, na.rm = T)
) |>
mean_fl = mean(flipper_length_mm, na.rm = T)) |>
ungroup()
# Simple bar chart by group with some alpha transparency
bar(df, "island", "mean_bl", "species", x_title = "Mean of bill length", title = "Mean of bill length by island and species")
bar(df, island, mean_bl, species, percent = FALSE, alpha = 0.6, x_title = "Mean of bill length")
```
<img src="man/figures/README-example-bar-chart-1.png" width="65%" />
``` r
# Flipped / Horizontal
hbar(df, "island", "mean_bl", "species", x_title = "Mean of bill length", title = "Mean of bill length by island and species")
# Using another color palette through `theme_reach()` and changing scale to percent
bar(df, island,mean_bl, species, percent = TRUE, theme = theme_reach(palette = "artichoke_3"))
```
<img src="man/figures/README-example-bar-chart-2.png" width="65%" />
``` r
# Facetted
bar(df, "island", "mean_bl", facet = "species", x_title = "Mean of bill length", title = "Mean of bill length by island and species", add_color_guide = FALSE)
# Not flipped, with text added, group_title, no y-axis and no bold for legend
bar(df, island, mean_bl, species, group_title = "Species", flip = FALSE, add_text = TRUE, add_text_suffix = "%", percent = FALSE, theme = theme_reach(text_font_face = "plain", axis_y = FALSE))
```
<img src="man/figures/README-example-bar-chart-3.png" width="65%" />
``` r
### Example 2: Point chart, already REACH themed
# Flipped, with text, smaller width, and caption
hbar(df = df_island, x = "island", y = "mean_bl", title = "Mean of bill length by island", add_text = T, width = 0.6, add_text_suffix = "mm", add_text_expand_limit = 1.3, add_color_guide = FALSE, caption = "Data: palmerpenguins package.")
```
<img src="man/figures/README-example-bar-chart-4.png" width="65%" />
### Example 2: Scatterplot
At this stage, `point_reach()` only supports categorical grouping colors
with the `group` arg.
``` r
# Simple scatterplot
point(penguins, "bill_length_mm", "flipper_length_mm")
# Simple point chart
point(penguins, bill_length_mm, flipper_length_mm)
```
<img src="man/figures/README-example-point-chart-1.png" width="65%" />
``` r
# Scatterplot with grouping colors, greater dot size, some transparency
point(penguins, "bill_length_mm", "flipper_length_mm", "island", group_title = "Island", alpha = 0.6, size = 3, title = "Bill vs. flipper length", , add_color_guide = FALSE)
# Point chart with grouping colors, greater dot size, some transparency, reversed color palette
point(penguins, bill_length_mm, flipper_length_mm, island, alpha = 0.6, size = 3, theme = theme_reach(reverse = TRUE))
```
<img src="man/figures/README-example-point-chart-2.png" width="65%" />
``` r
# Facetted scatterplot by island
point(penguins, "bill_length_mm", "flipper_length_mm", "species", "island", "fixed", group_title = "Species", title = "Bill vs. flipper length by species and island", add_color_guide = FALSE)
# Using another color palettes
point(penguins, bill_length_mm, flipper_length_mm, island, size = 1.5, x_title = "Bill", y_title = "Flipper", title = "Length (mm)", theme = theme_reach(palette = "artichoke_3", text_font_face = , grid_major_x = TRUE, title_position_to_plot = FALSE))
```
<img src="man/figures/README-example-point-chart-3.png" width="65%" />
### Example 3: Dumbbell plot
### Example 3: Dumbbell plot, REACH themed
Remember to ensure that your data are in the long format and you only
have two groups on the x-axis; for instance, IDP and returnee and no NA
@ -178,23 +157,34 @@ df <- tibble::tibble(
) |>
dplyr::mutate(stat = round(stat, 0))
# Example, adding a parameter to `theme_reach()` passed on `ggplot2::theme()` to align legend title
# dumbbell(
# df,
# 'stat',
# 'setting',
# 'admin1',
# title = '% of HHs that reported open defecation as sanitation facility',
# group_y_title = 'Admin 1',
# group_x_title = 'Setting'
# )
dumbbell(df,
stat,
setting,
admin1,
title = "% of HHs that reported open defecation as sanitation facility",
group_y_title = "Admin 1",
group_x_title = "Setting",
theme = theme_reach(legend_position = "bottom",
legend_direction = "horizontal",
legend_title_font_face = "bold",
palette = "primary",
title_position_to_plot = FALSE,
legend.title.align = 0.5)) +
# Change legend title position (could be included as part of the function)
ggplot2::guides(
color = ggplot2::guide_legend(title.position = "left"),
fill = ggplot2::guide_legend(title.position = "left")
)
```
### Example 4: donut chart
<img src="man/figures/README-example-dumbbell-plot-1.png" width="65%" />
### Example 4: donut chart, REACH themed (to used once, not twice)
``` r
# Some summarized data: % of HHs by displacement status
df <- tibble::tibble(
status = c("Displaced", "Non displaced", "Returnee", "Don't know/Prefer not to say"),
@ -202,141 +192,139 @@ df <- tibble::tibble(
)
# Donut
# donut(df,
# status,
# percentage,
# hole_size = 3,
# add_text_suffix = '%',
# add_text_color = color('dark_grey'),
# add_text_treshold_display = 5,
# x_title = 'Displacement status',
# title = '% of HHs by displacement status'
# )
donut(df,
status,
percentage,
hole_size = 3,
add_text_suffix = "%",
add_text_color = cols_reach("dk_grey"),
add_text_treshold_display = 5,
x_title = "Displacement status",
title = "% of HHs by displacement status",
theme = theme_reach(legend_reverse = TRUE))
```
### Example 5: Waffle chart
<img src="man/figures/README-example-donut-plot-1.png" width="65%" />
### Example 5: waffle chart
``` r
#
# waffle(df, status, percentage, x_title = 'A caption', title = 'A title', subtitle = 'A subtitle')
waffle(df, status, percentage, x_title = "A caption", title = "A title", subtitle = "A subtitle")
```
### Example 6: Alluvial chart
<img src="man/figures/README-example-waffle-plot-1.png" width="65%" />
### Example 6: alluvial chart, REACH themed
``` r
# Some summarized data: % of HHs by self-reported status of displacement in 2021 and in 2022
df <- tibble::tibble(
status_from = c(
rep("Displaced", 4),
status_from = c(rep("Displaced", 4),
rep("Non displaced", 4),
rep("Returnee", 4),
rep("Dnk/Pnts", 4)
),
rep("Dnk/Pnts", 4)),
status_to = c("Displaced", "Non displaced", "Returnee", "Dnk/Pnts", "Displaced", "Non displaced", "Returnee", "Dnk/Pnts", "Displaced", "Non displaced", "Returnee", "Dnk/Pnts", "Displaced", "Non displaced", "Returnee", "Dnk/Pnts"),
percentage = c(20, 8, 18, 1, 12, 21, 0, 2, 0, 3, 12, 1, 0, 0, 1, 1)
)
# Alluvial, here the group is the status for 2021
# alluvial(df,
# status_from,
# status_to,
# percentage,
# status_from,
# from_levels = c("Displaced", "Non displaced", "Returnee", "Dnk/Pnts"),
# alpha = 0.8,
# group_title = "Status for 2021",
# title = "% of HHs by self-reported status from 2021 to 2022"
# )
alluvial(df,
status_from,
status_to,
percentage,
status_from,
from_levels = c("Displaced", "Non displaced", "Returnee", "Dnk/Pnts"),
alpha = 0.8,
group_title = "Status for 2021",
title = "% of HHs by self-reported status from 2021 to 2022",
theme = theme_reach(
axis_y = FALSE,
legend_position = "none"))
```
### Example 7: Lollipop chart
<img src="man/figures/README-example-alluvial-plot-1.png" width="65%" />
### Example 7: lollipop chart
``` r
library(tidyr)
# Prepare long data
df <- tibble::tibble(
admin1 = replicate(15, sample(letters, 8)) |> t() |> as.data.frame() |> unite("admin1", sep = "") |> dplyr::pull(admin1),
stat = rnorm(15, mean = 50, sd = 15)
) |>
stat = rnorm(15, mean = 50, sd = 15)) |>
dplyr::mutate(stat = round(stat, 0))
# Simple vertical lollipop chart
lollipop(
df = df,
x = "admin1",
y = "stat",
# Make lollipop plot, REACH themed, vertical with 45 degrees angle X-labels
lollipop(df,
admin1,
stat,
arrange = FALSE,
add_text = FALSE,
flip = FALSE,
dot_size = 3,
y_title = "% of HHs",
x_title = "Admin 1",
title = "% of HHs that received humanitarian assistance"
)
title = "% of HHs that reported having received a humanitarian assistance",
theme = theme_reach(axis_text_x_angle = 45,
grid_major_y = TRUE,
grid_major_y_size = 0.2,
grid_major_x = TRUE,
grid_minor_y = TRUE))
```
<img src="man/figures/README-example-lollipop-chart-1.png" width="65%" />
``` r
# Horizontal lollipop chart with custom colors
hlollipop(
df = df,
x = "admin1",
y = "stat",
dot_size = 4,
line_size = 1,
add_color = color("cat_5_main_2"),
line_color = color("cat_5_main_4"),
# Horizontal, greater point size, arranged by value, no grid, and text labels added
lollipop(df,
admin1,
stat,
arrange = TRUE,
point_size = 10,
point_color = cols_reach("main_beige"),
segment_size = 2,
add_text = TRUE,
add_text_suffix = "%",
y_title = "% of HHs",
x_title = "Admin 1",
title = "% of HHs that received humanitarian assistance"
)
title = "% of HHs that reported having received a humanitarian assistance in the 12 months prior to the assessment",
theme = theme_reach(title_position_to_plot = FALSE))
```
<img src="man/figures/README-example-lollipop-chart-2.png" width="65%" />
``` r
# Create data for grouped lollipop - using set.seed for reproducibility
set.seed(123)
df_grouped <- tibble::tibble(
admin1 = rep(c("A", "B", "C", "D", "E", "F"), 2),
group = rep(c("Group A", "Group B"), each = 6),
stat = c(rnorm(6, mean = 40, sd = 10), rnorm(6, mean = 60, sd = 10))
) |>
dplyr::mutate(stat = round(stat, 0))
# Grouped lollipop chart with proper side-by-side positioning
lollipop(
df = df_grouped,
x = "admin1",
y = "stat",
group = "group",
order = "grouped_y",
dot_size = 3.5,
line_size = 0.8,
y_title = "Value",
x_title = "Category",
title = "True side-by-side grouped lollipop chart"
)
```
<img src="man/figures/README-example-lollipop-chart-3.png" width="65%" />
## Maps
``` r
# Horizontal grouped lollipop chart
hlollipop(
df = df_grouped,
x = "admin1",
y = "stat",
group = "group",
dot_size = 3.5,
line_size = 0.8,
y_title = "Category",
x_title = "Value",
title = "Horizontal side-by-side grouped lollipop chart"
)
# Add indicator layer
# - based on "pretty" classes and title "Proportion (%)"
# - buffer to add a 10% around the bounding box
map <- add_indicator_layer(
indicator_admin1,
opn_dfc,
buffer = 0.1) +
# Layout - some defaults - add the map title
add_layout("% of HH that reported open defecation as sanitation facility") +
# Admin boundaries as list of shape files (lines) and colors, line widths and labels as vectors
add_admin_boundaries(
lines = list(line_admin1, border_admin0, frontier_admin0),
colors = cols_reach("main_lt_grey", "dk_grey", "black"),
lwds = c(0.5, 2, 3),
labels = c("Department", "Country", "Dominican Rep. frontier"),
title = "Administrative boundaries") +
# Add text labels - centered on admin 1 centroids
add_admin_labels(centroid_admin1, ADM1_FR_UPPER) +
# Add a compass
add_compass() +
# Add a scale bar
add_scale_bar() +
# Add credits
add_credits("Admin. boundaries. : CNIGS \nCoord. system: GCS WGS 1984")
```
<img src="man/figures/README-example-lollipop-chart-4.png" width="65%" />
![Once exported with
`tmap::tmap_save()`.](man/figures/README-example-map.png)

View file

@ -1,14 +0,0 @@
comment: false
coverage:
status:
project:
default:
target: auto
threshold: 1%
informational: true
patch:
default:
target: auto
threshold: 1%
informational: true

BIN
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@ -0,0 +1 @@
PROJCS["WGS_1984_UTM_Zone_18N",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-75.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["m",1.0]]

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@ -0,0 +1 @@
GEOGCS["GCS_unknown",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]]

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@ -0,0 +1 @@
GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]]

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@ -0,0 +1 @@
GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]]

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1
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@ -0,0 +1 @@
GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]]

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21
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@ -0,0 +1,21 @@
#------ Border - admin 0
border_admin0 <- sf::st_read("data-raw/border_admin0.shp")
usethis::use_data(border_admin0, overwrite = TRUE)
#------ Frontier - admin 0
frontier_admin0 <- sf::st_read("data-raw/frontier_admin0.shp")
usethis::use_data(frontier_admin0, overwrite = TRUE)
#------ Line - admin 1
line_admin1 <- sf::st_read("data-raw/line_admin1.shp")
usethis::use_data(line_admin1, overwrite = TRUE)
#------ Centroid - admin 1
centroid_admin1 <- sf::st_read("data-raw/centroid_admin1.shp") |>
dplyr::rename(ADM1_FR_UPPER = ADM1_FR_)
usethis::use_data(centroid_admin1, overwrite = TRUE)
#------ Indicator polygon - admin 1
indicator_admin1 <- sf::st_read("data-raw/indicator_admin1.shp")
usethis::use_data(indicator_admin1, overwrite = TRUE)

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@ -1,57 +0,0 @@
aut
Carlito
CMD
codecov
Codecov
coercible
Config
covr
cre
css
Customizable
donut
Donut
dplyr
Dumbell
forcats
ggalluvial
ggplot
ggrepel
ggtext
github
gnoblet
gpplot
grDevices
grey
Guillaume
hbar
hlollipop
horizonal
https
IDP
io
knitr
LazyData
Noblet
pre
README
rio
rlang
rmarkdown
Roadmap
Roboto
roxygen
RoxygenNote
Segoe
stringr
testthat
theming
tidyr
UI
vdiffr
VignetteBuilder
viridis
viridisLite
visualizeR
withr
zaclys

21
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@ -0,0 +1,21 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/internals.R
\name{abort_bad_argument}
\alias{abort_bad_argument}
\title{Abord bad argument}
\usage{
abort_bad_argument(arg, must, not = NULL)
}
\arguments{
\item{arg}{An argument}
\item{must}{What arg must be}
\item{not}{Optional. What arg must not be.}
}
\value{
A stop statement
}
\description{
Abord bad argument
}

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@ -0,0 +1,37 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/map.R
\name{add_admin_boundaries}
\alias{add_admin_boundaries}
\title{Add admin boundaries (lines) and the legend}
\usage{
add_admin_boundaries(
lines,
colors,
labels,
lwds,
title = "",
buffer = NULL,
...
)
}
\arguments{
\item{lines}{List of multiline shape defined by sf package.}
\item{colors}{Vector of hexadecimal codes. Same order as lines.}
\item{labels}{Vector of labels in the legend. Same order as lines.}
\item{lwds}{Vector of line widths. Same order as lines.}
\item{title}{Legend title.}
\item{buffer}{A buffer, either one value or a vector of 4 values (left, bottom, right, top).}
\item{...}{Other arguments to pass to each shape in `tmap::tm_lines()`.}
}
\value{
A tmap layer.
}
\description{
Add admin boundaries (lines) and the legend
}

43
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@ -0,0 +1,43 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/map.R
\name{add_admin_labels}
\alias{add_admin_labels}
\title{Wrapper around `tmap::tm_text()` with sane defaults for plotting admin labels.}
\usage{
add_admin_labels(
point,
text,
size = 0.5,
fontface = "bold",
fontfamily = "Leelawadee",
shadow = TRUE,
auto_placement = FALSE,
remove_overlap = FALSE,
...
)
}
\arguments{
\item{point}{Multipoint shape defined by sf package.}
\item{text}{Text labels column.}
\item{size}{Relative size of the text labels.}
\item{fontface}{Fontface.}
\item{fontfamily}{Fontfamily. Leelawadee is your precious.}
\item{shadow}{Boolean. Add a shadow around text labels. Issue opened on Github to request.}
\item{auto_placement}{Logical that determines whether the labels are placed automatically.}
\item{remove_overlap}{Logical that determines whether the overlapping labels are removed.}
\item{...}{Other arguments to pass to `tmap::tm_text()`.}
}
\value{
A tmap layer.
}
\description{
Wrapper around `tmap::tm_text()` with sane defaults for plotting admin labels.
}

34
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@ -0,0 +1,34 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/map.R
\name{add_compass}
\alias{add_compass}
\title{Add a compass}
\usage{
add_compass(
text_size = 0.6,
position = c("right", 0.8),
color_dark = cols_reach("black"),
text_color = cols_reach("black"),
type = "4star",
...
)
}
\arguments{
\item{text_size}{Relative font size.}
\item{position}{Position of the compass. Vector of two values, specifying the x and y coordinates.}
\item{color_dark}{Color of the dark parts of the compass.}
\item{text_color}{color of the text.}
\item{type}{Compass type, one of: "arrow", "4star", "8star", "radar", "rose".}
\item{...}{Other arguments to pass to `tmap::tm_compass()`.}
}
\value{
A tmap layer.
}
\description{
Add a compass
}

25
man/add_credits.Rd Normal file
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@ -0,0 +1,25 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/map.R
\name{add_credits}
\alias{add_credits}
\title{Do you want to credit someone or some institution?}
\usage{
add_credits(text, size = 0.4, bg_color = NA, position = c(0.75, 0.02), ...)
}
\arguments{
\item{text}{Text.}
\item{size}{Relative text size.}
\item{bg_color}{Background color.}
\item{position}{Position. Vector of two coordinates. Usually somewhere down.}
\item{...}{Other arguments to pass to `tmap::tm_credits()`.}
}
\value{
A tmap layer.
}
\description{
Do you want to credit someone or some institution?
}

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@ -0,0 +1,61 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/map.R
\name{add_indicator_layer}
\alias{add_indicator_layer}
\title{Wrapper around `tmap::tm_polygons()` with sane defaults for plotting indicator values}
\usage{
add_indicator_layer(
poly,
col,
buffer = NULL,
n = 5,
style = "pretty",
palette = pal_reach("red_5"),
as_count = TRUE,
color_na = cols_reach("white"),
text_na = "Missing data",
legend_title = "Proportion (\%)",
legend_text_separator = " - ",
border_alpha = 1,
border_col = cols_reach("lt_grey_1"),
lwd = 1,
...
)
}
\arguments{
\item{poly}{Multipolygon shape defined by sf package.}
\item{col}{Numeric attribute to map.}
\item{buffer}{A buffer, either one value or a vector of 4 values (left, bottom, right, top).}
\item{n}{The desire number of classes.}
\item{style}{Method to process the color scale for continuous numerical variables. See `classInt::classIntervals()` for details.}
\item{palette}{Vector of fill colors as hexadecimal values. For REACH color palettes, it is possible to use `pal_reach()`. For now,'palette' must be changed manually, accordingly to the number of drawn classes.}
\item{as_count}{Boolean. When col is a numeric variable, should it be processed as a count variable? For instance, 0, 1-10, 11-20.}
\item{color_na}{Fill color for missing data.}
\item{text_na}{Legend text for missing data.}
\item{legend_title}{Legend title.}
\item{legend_text_separator}{Text separator for classes. E.g. " to " will give 0, 1 to 10, 11 to 20.}
\item{border_alpha}{Transparency of the border.}
\item{border_col}{Color of the border.}
\item{lwd}{Linewidth of the border.}
\item{...}{Other arguments to pass to `tmap::tm_polygons()`.}
}
\value{
A tmap layer.
}
\description{
Wrapper around `tmap::tm_polygons()` with sane defaults for plotting indicator values
}

49
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@ -0,0 +1,49 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/map.R
\name{add_layout}
\alias{add_layout}
\title{Basic defaults based on `tmap::tm_layout()`}
\usage{
add_layout(
title = NULL,
legend_position = c(0.02, 0.5),
frame = FALSE,
legend_frame = cols_reach("main_grey"),
legend_text_size = 0.6,
legend_title_size = 0.8,
title_size = 0.9,
title_fontface = "bold",
title_color = cols_reach("main_grey"),
fontfamily = "Leelawadee",
...
)
}
\arguments{
\item{title}{Map title.}
\item{legend_position}{Legend position. Not above the map is a good start.}
\item{frame}{Boolean. Legend frame?}
\item{legend_frame}{Legend frame color.}
\item{legend_text_size}{Legend text size in 'pt'.}
\item{legend_title_size}{Legend title size in 'pt'.}
\item{title_size}{Title text size in 'pt'.}
\item{title_fontface}{Title fontface. Bold if you wanna exemplify a lot what it is about.}
\item{title_color}{Title font color.}
\item{fontfamily}{Overall fontfamily. Leelawadee is your precious.}
\item{...}{Other arguments to pass to `tmap::tm_layout()`.}
}
\value{
A tmap layer.
}
\description{
Basic defaults based on `tmap::tm_layout()`
}

31
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@ -0,0 +1,31 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/map.R
\name{add_scale_bar}
\alias{add_scale_bar}
\title{Add a scale bar}
\usage{
add_scale_bar(
text_size = 0.6,
position = c("left", 0.01),
color_dark = cols_reach("black"),
breaks = c(0, 50, 100),
...
)
}
\arguments{
\item{text_size}{Relative font size.}
\item{position}{Position of the compass. Vector of two values, specifying the x and y coordinates.}
\item{color_dark}{Color of the dark parts of the compass.}
\item{breaks}{Breaks of the scale bar. If not specified, breaks will be automatically be chosen given the prefered width of the scale bar. Example: c(0, 50, 100).}
\item{...}{Other arguments to pass to `tmap::tm_compass()`.}
}
\value{
A tmap layer.
}
\description{
Add a scale bar
}

64
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@ -0,0 +1,64 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/alluvial.R
\name{alluvial}
\alias{alluvial}
\title{Simple alluvial chart}
\usage{
alluvial(
df,
from,
to,
value,
group = NULL,
alpha = 0.5,
from_levels = NULL,
value_title = NULL,
group_title = NULL,
title = NULL,
subtitle = NULL,
caption = NULL,
rect_color = cols_reach("white"),
rect_border_color = cols_reach("main_grey"),
rect_text_color = cols_reach("main_grey"),
theme = theme_reach(axis_y = FALSE, legend_position = "none")
)
}
\arguments{
\item{df}{A data frame.}
\item{from}{A character column of upstream stratum.}
\item{to}{A character column of downstream stratum.}
\item{value}{A numeric column of values.}
\item{group}{The grouping column to fill the alluvium with.}
\item{alpha}{Fill transparency. Default to 0.5.}
\item{from_levels}{Order by given from levels?}
\item{value_title}{The value/y scale title. Default to NULL.}
\item{group_title}{The group title. Default to NULL.}
\item{title}{Plot title. Default to NULL.}
\item{subtitle}{Plot subtitle. Default to NULL.}
\item{caption}{Plot caption. Default to NULL.}
\item{rect_color}{Stratum rectangles' fill color.}
\item{rect_border_color}{Stratum rectangles' border color.}
\item{rect_text_color}{Stratum rectangles' text color.}
\item{theme}{Whatever theme. Default to theme_reach().}
}
\value{
A donut chart to be used parsimoniously
}
\description{
Simple alluvial chart
}

View file

@ -1,32 +1,16 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/bar.R
\name{hbar}
\alias{hbar}
\name{bar}
\alias{bar}
\title{Simple bar chart}
\usage{
hbar(
...,
flip = TRUE,
add_text = FALSE,
theme_fun = theme_bar(flip = flip, add_text = add_text)
)
bar(
df,
x,
y,
group = "",
facet = "",
order = "none",
x_rm_na = TRUE,
y_rm_na = TRUE,
group_rm_na = TRUE,
facet_rm_na = TRUE,
y_expand = 0.1,
add_color = color("cat_5_main_1"),
add_color_guide = TRUE,
flip = FALSE,
group = NULL,
flip = TRUE,
percent = TRUE,
wrap = NULL,
position = "dodge",
alpha = 1,
@ -36,55 +20,23 @@ bar(
title = NULL,
subtitle = NULL,
caption = NULL,
width = 0.8,
add_text = FALSE,
add_text_size = 4.5,
add_text_color = color("dark_grey"),
add_text_font_face = "bold",
add_text_threshold_display = 0.05,
add_text_suffix = "\%",
add_text_expand_limit = 1.2,
add_text_round = 1,
theme_fun = theme_bar(flip = flip, add_text = add_text, axis_text_x_angle = 0,
axis_text_x_vjust = 0.5, axis_text_x_hjust = 0.5),
scale_fill_fun = scale_fill_visualizer_discrete(),
scale_color_fun = scale_color_visualizer_discrete()
add_text_suffix = "",
theme = theme_reach()
)
}
\arguments{
\item{...}{Additional arguments passed to `bar()`}
\item{flip}{TRUE or FALSE (default). Default to TRUE or horizontal bar plot.}
\item{add_text}{TRUE or FALSE. Add values as text.}
\item{theme_fun}{Whatever theme function. For no custom theme, use theme_fun = NULL.}
\item{df}{A data frame.}
\item{x}{A quoted numeric column.}
\item{x}{A numeric column.}
\item{y}{A quoted character column or coercible as a character column.}
\item{y}{A character column or coercible as a character column.}
\item{group}{Some quoted grouping categorical column, e.g. administrative areas or population groups.}
\item{group}{Some grouping categorical column, e.g. administrative areas or population groups.}
\item{facet}{Some quoted grouping categorical column, e.g. administrative areas or population groups.}
\item{flip}{TRUE or FALSE. Default to TRUE or horizontal bar plot.}
\item{order}{A character scalar specifying the order type (one of "none", "y", "grouped"). See details.}
\item{x_rm_na}{Remove NAs in x?}
\item{y_rm_na}{Remove NAs in y?}
\item{group_rm_na}{Remove NAs in group?}
\item{facet_rm_na}{Remove NAs in facet?}
\item{y_expand}{Multiplier to expand the y axis.}
\item{add_color}{Add a color to bars (if no grouping).}
\item{add_color_guide}{Should a legend be added?}
\item{percent}{TRUE or FALSE. Should the x-labels (and text labels if present) be displayed as percentages? Default to TRUE.}
\item{wrap}{Should x-labels be wrapped? Number of characters.}
@ -104,26 +56,15 @@ bar(
\item{caption}{Plot caption. Default to NULL.}
\item{width}{Bar width.}
\item{add_text_size}{Text size.}
\item{add_text_color}{Text color.}
\item{add_text_font_face}{Text font_face.}
\item{add_text_threshold_display}{Minimum value to add the text label.}
\item{add_text}{TRUE or FALSE. Add the value as text.}
\item{add_text_suffix}{If percent is FALSE, should we add a suffix to the text label?}
\item{add_text_expand_limit}{Default to adding 10\% on top of the bar.}
\item{add_text_round}{Round the text label.}
\item{scale_fill_fun}{Scale fill function. Default to scale_fill_visualizer_discrete().}
\item{scale_color_fun}{Scale color function. Default to scale_color_visualizer_discrete().}
\item{theme}{Whatever theme. Default to theme_reach().}
}
\value{
A bar chart
}
\description{
`bar()` is a simple bar chart with some customization allowed, in particular the `theme_fun` argument for theming. `hbar()` uses `bar()` with sane defaults for a horizontal bar chart.
Simple bar chart
}

25
man/border_admin0.Rd Normal file
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@ -0,0 +1,25 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{border_admin0}
\alias{border_admin0}
\title{Haïti border.}
\format{
A sf multiline objet with 1 feature and 6 fields:
\describe{
\item{fid_1}{fid_1}
\item{uno}{uno}
\item{count}{count}
\item{x_coord}{x_coord}
\item{y_coord}{y_coord}
\item{area}{area}
\item{geometry}{Multiline geometry.}
}
}
\usage{
border_admin0
}
\description{
A multiline shapefile of Haiti's border.
}
\keyword{datasets}

19
man/buffer_bbox.Rd Normal file
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@ -0,0 +1,19 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/bbox_buffer.R
\name{buffer_bbox}
\alias{buffer_bbox}
\title{Bbbox buffer}
\usage{
buffer_bbox(sf_obj, buffer = 0)
}
\arguments{
\item{sf_obj}{A `sf` object}
\item{buffer}{A buffer, either one value or a vector of 4 values (left, bottom, right, top). Default to 0.}
}
\value{
A bbox with a buffer
}
\description{
Bbbox buffer
}

28
man/centroid_admin1.Rd Normal file
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@ -0,0 +1,28 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{centroid_admin1}
\alias{centroid_admin1}
\title{Haïti admin 1 centroids shapefile.}
\format{
A sf multipoint object with 10 features and 9 fields:
\describe{
\item{ADM1_PC}{Admin 1 postal code.}
\item{ADM1_EN}{Full name in English.}
\item{ADM1_FR}{Full name in French.}
\item{ADM1_HT}{Full name in Haitian Creole.}
\item{ADM0_EN}{Country name in English.}
\item{ADM0_FR}{Country name in French.}
\item{ADM0_HT}{Country name in Haitian Creole.}
\item{ADM0_PC}{Country postal code.}
\item{ADM1_FR_UPPER}{Admin 1 French name - uppercase.}
\item{geometry}{Multipoint geometry.}
}
}
\usage{
centroid_admin1
}
\description{
A multipoint shapefile of Haiti's admin 1.
}
\keyword{datasets}

View file

@ -1,19 +0,0 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/checks.R
\name{check_vars_in_df}
\alias{check_vars_in_df}
\title{Check if variables are in data frame}
\usage{
check_vars_in_df(df, vars)
}
\arguments{
\item{df}{A data frame}
\item{vars}{A vector of variable names}
}
\value{
A stop statement
}
\description{
Check if variables are in data frame
}

View file

@ -1,33 +0,0 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/color.R
\name{color}
\alias{color}
\alias{color_pattern}
\title{Helpers to extract defined colors as hex codes}
\usage{
color(..., unname = TRUE)
color_pattern(pattern, unname = TRUE)
}
\arguments{
\item{...}{Character names of colors. If NULL returns all colors.}
\item{unname}{Boolean. Should the output vector be unnamed? Default to `TRUE`.}
\item{pattern}{Pattern of the start of colors' name.}
}
\value{
Hex codes named or unnamed.
}
\description{
[color()] returns the requested columns, returns NA if absent. [color_pattern()] returns all colors that start with the pattern.
}
\section{Naming of colors}{
* All branding colors start with "branding";
* All , categorical colors start with ", cat_";
* All sequential colors start with "seq_";
Then, a number indicates the number of colors that belong to the palettes, a string the name of the palette, and, finally, a number the position of the color. E.g., "seq_5_red_4" would be the 4th color of a continuous palettes of 5 colors in the red band. Exception is made for white, light_grey, dark_grey, and black.
}

22
man/cols_agora.Rd Normal file
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@ -0,0 +1,22 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/cols_agora.R
\name{cols_agora}
\alias{cols_agora}
\title{Function to extract AGORA colors as hex codes}
\usage{
cols_agora(..., unnamed = TRUE)
}
\arguments{
\item{...}{Character names of reach colors. If NULL returns all colors}
\item{unnamed}{Should the output vector be unnamed? Default to `TRUE`}
}
\value{
An hex code or hex codes named or unnamed
}
\description{
Function to extract AGORA colors as hex codes
}
\details{
This function needs to be modified to add colors
}

22
man/cols_impact.Rd Normal file
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@ -0,0 +1,22 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/cols_impact.R
\name{cols_impact}
\alias{cols_impact}
\title{Function to extract IMPACT colors as hex codes}
\usage{
cols_impact(..., unnamed = TRUE)
}
\arguments{
\item{...}{Character names of reach colors. If NULL returns all colors}
\item{unnamed}{Should the output vector be unnamed? Default to `TRUE`}
}
\value{
An hex code or hex codes named or unnamed
}
\description{
Function to extract IMPACT colors as hex codes
}
\details{
This function needs to be modified to add colors
}

22
man/cols_reach.Rd Normal file
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@ -0,0 +1,22 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/cols_reach.R
\name{cols_reach}
\alias{cols_reach}
\title{Function to extract REACH colors as hex codes}
\usage{
cols_reach(..., unnamed = TRUE)
}
\arguments{
\item{...}{Character names of reach colors. If NULL returns all colors}
\item{unnamed}{Should the output vector be unnamed? Default to `TRUE`}
}
\value{
An hex code or hex codes named or unnamed
}
\description{
Function to extract REACH colors as hex codes
}
\details{
This function needs to be modified to add colors
}

61
man/donut.Rd Normal file
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@ -0,0 +1,61 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/donut.R
\name{donut}
\alias{donut}
\title{Simple donut chart (to be used parsimoniously), can be a pie chart}
\usage{
donut(
df,
x,
y,
alpha = 1,
x_title = NULL,
title = NULL,
subtitle = NULL,
caption = NULL,
arrange = TRUE,
hole_size = 3,
add_text = TRUE,
add_text_treshold_display = 5,
add_text_color = "white",
add_text_suffix = "",
theme = theme_reach(legend_reverse = TRUE)
)
}
\arguments{
\item{df}{A data frame.}
\item{x}{A character column or coercible as a character column. Will give the donut's fill color.}
\item{y}{A numeric column.}
\item{alpha}{Fill transparency.}
\item{x_title}{The x scale title. Default to NULL.}
\item{title}{Plot title. Default to NULL.}
\item{subtitle}{Plot subtitle. Default to NULL.}
\item{caption}{Plot caption. Default to NULL.}
\item{arrange}{TRUE or FALSE. Arrange by highest percentage first.}
\item{hole_size}{Hole size. Default to 3. If less than 2, back to a pie chart.}
\item{add_text}{TRUE or FALSE. Add the value as text.}
\item{add_text_treshold_display}{Minimum value to add the text label.}
\item{add_text_color}{Text color.}
\item{add_text_suffix}{If percent is FALSE, should we add a suffix to the text label?}
\item{theme}{Whatever theme. Default to theme_reach().}
}
\value{
A donut chart to be used parsimoniously
}
\description{
Simple donut chart (to be used parsimoniously), can be a pie chart
}

View file

@ -12,24 +12,22 @@ dumbbell(
point_size = 5,
point_alpha = 1,
segment_size = 2.5,
segment_color = color("light_blue_grey"),
segment_color = cols_reach("main_lt_grey"),
group_x_title = NULL,
group_y_title = NULL,
x_title = NULL,
title = NULL,
subtitle = NULL,
caption = NULL,
line_to_y_axis = FALSE,
line_to_y_axis = TRUE,
line_to_y_axis_type = 3,
line_to_y_axis_width = 0.5,
line_to_y_axis_color = color("dark_grey"),
add_text = FALSE,
line_to_y_axis_color = cols_reach("main_grey"),
add_text = TRUE,
add_text_vjust = 2,
add_text_size = 3.5,
add_text_color = color("dark_grey"),
theme_fun = theme_dumbbell(),
scale_fill_fun = scale_fill_visualizer_discrete(),
scale_color_fun = scale_color_visualizer_discrete()
add_text_color = cols_reach("main_grey"),
theme = theme_reach(palette = "primary")
)
}
\arguments{
@ -77,11 +75,7 @@ dumbbell(
\item{add_text_color}{Text color.}
\item{theme_fun}{A ggplot2 theme, default to `theme_dumbbell()`}
\item{scale_fill_fun}{A ggplot2 scale_fill function, default to `scale_fill_visualizer_discrete()`}
\item{scale_color_fun}{A ggplot2 scale_color function, default to `scale_color_visualizer_discrete()`}
\item{theme}{A ggplot2 theme, default to `theme_reach()`}
}
\value{
A dumbbell chart.

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