File size: 8,898 Bytes
aee2f01 ccfbf15 aee2f01 ccfbf15 aee2f01 ccfbf15 aee2f01 ccfbf15 aee2f01 ccfbf15 aee2f01 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 |
{
# ====================================================================
# app.R – interactive demo for the DescriptiveRepresentation calculator
# Upload this single file to a Shiny‑typed Hugging Face Space.
# ====================================================================
# install.packages( "~/Documents/DescriptiveRepresentationCalculator-software/DescriptiveRepresentationCalculator", repos = NULL, type = "source",force = F)
options(error = NULL)
# ====================================================================
# app.R – interactive demo for the Descriptive Representation Viewer
# Upload this single file to a Shiny‑typed Hugging Face Space.
# ====================================================================
options(error = NULL)
suppressPackageStartupMessages({
library(shiny)
library(ggplot2)
library(tidyr)
library(scales)
})
# --------------------------------------------------------------------
# 1. Calculator functions (verbatim from Gerring, Jerzak & Öncel 2024)
# --------------------------------------------------------------------
library( DescriptiveRepresentationCalculator )
# --------------------------------------------------------------------
# 2. Shiny user interface
# --------------------------------------------------------------------
ui <- fluidPage(
# ---- Custom title block ---------------------------------------------------
tags$div(
style = "margin-top: 20px;",
tags$h2("Descriptive Representation Viewer"),
tags$p(
tags$a(href = "https://globalleadershipproject.net/",
tags$span("🔗 GlobalLeadershipProject.net"))
)
),
sidebarLayout(
sidebarPanel(
numericInput("bodyN", "Size of the political body (N):",
value = 50, min = 1, step = 1),
sliderInput("ngroups", "Number of population groups (K):",
min = 2, max = 5, value = 3, step = 1),
uiOutput("popShareInputs"), # K – 1 numeric inputs + note
checkboxInput("hasBody", "I have the body’s member counts", FALSE),
conditionalPanel(
"input.hasBody == true",
uiOutput("bodyCountInputs")
),
actionButton("go", "Compute", class = "btn-primary")
),
mainPanel(
fluidRow(
column(4, verbatimTextOutput("expBox")),
column(4, verbatimTextOutput("obsBox")),
column(4, verbatimTextOutput("relBox"))
),
hr(),
plotOutput("sharePlot", height = "400px"),
hr(),
helpText(
"Indices are based on the Rose Index (a = –0.5, b = 1). ",
"Expected values follow Gerring, Jerzak & Öncel (2024) ",
tags$a("[PDF]",
href = "https://www.cambridge.org/core/services/aop-cambridge-core/"
|> paste0("content/view/7EAEA1CA4C553AB9D76054D1FA9C0840/",
"S0003055423000680a.pdf/the-composition-of-",
"descriptive-representation.pdf"),
target = "_blank")
)
)
)
)
# --------------------------------------------------------------------
# 3. Server logic
# --------------------------------------------------------------------
server <- function(input, output, session) {
# ----- Dynamic numericInputs for the first K‑1 shares ----------------------
output$popShareInputs <- renderUI({
n <- input$ngroups
if (n < 2) return()
tagList(
lapply(seq_len(n - 1), function(i) {
numericInput(
inputId = paste0("share", i),
label = paste("Share of group", LETTERS[i]),
value = round(1 / n, 3),
min = 0, max = 1, step = 0.001
)
}),
tags$p(
sprintf("The share of group %s is automatically set to 1 − (sum of the others).",
LETTERS[n]),
style = "font-style: italic;"
)
)
})
# ----- Dynamic numericInputs for group‑wise body counts --------------------
output$bodyCountInputs <- renderUI({
n <- input$ngroups
lapply(seq_len(n), function(i){
numericInput(
inputId = paste0("count", i),
label = paste("Members of group", LETTERS[i], "in body"),
value = 0, min = 0, step = 1
)
})
})
# ----- Helper producing the full K‑vector of population shares -------------
popShares <- eventReactive(input$go, {
n <- input$ngroups
shares_first <- sapply(seq_len(n - 1),
function(i) input[[paste0("share", i)]])
if (anyNA(shares_first) || any(shares_first < 0)) {
showNotification("All shares must be non‑negative numbers.", type = "error")
return(NULL)
}
remainder <- 1 - sum(shares_first)
if (remainder < -1e-6) {
showNotification("The entered shares exceed 1. Reduce them so that K‑1 shares "
|> paste("sum to at most 1."), type = "error")
return(NULL)
}
shares <- c(shares_first, max(remainder, 0))
setNames(shares, LETTERS[seq_len(n)])
})
# ----- Helper reading body counts into a named vector ----------------------
bodyCounts <- reactive({
req(input$hasBody)
n <- input$ngroups
counts <- sapply(seq_len(n), function(i) input[[paste0("count", i)]])
if (anyNA(counts) || any(counts < 0)) {
showNotification("Body counts must be non‑negative integers.", type = "error")
return(NULL)
}
setNames(counts, LETTERS[seq_len(n)])
})
# ----- Main computation on “Compute” --------------------------------------
observeEvent(input$go, {
validate(need(!is.null(popShares()), "Fix population shares first."))
# Expected representation
expVal <- ExpectedRepresentation(popShares(), input$bodyN)
output$expBox <- renderText(sprintf("Expected representation:\n%.3f", expVal))
# Observed / relative representation (if counts supplied)
if (input$hasBody) {
validate(need(!is.null(bodyCounts()), "Enter valid body counts."))
counts <- bodyCounts()
bodyTotal <- sum(counts)
if (bodyTotal == 0) {
showNotification("Total body member count cannot be zero.", type = "error")
output$obsBox <- renderText("Observed representation:\n—")
output$relBox <- renderText("Relative representation:\n—")
return()
}
if (bodyTotal != input$bodyN) {
showNotification(
sprintf("Sum of counts (%d) differs from N (%d). We use the counts.",
bodyTotal, input$bodyN),
type = "warning", duration = 7
)
}
bodyShares <- counts / bodyTotal
obsVal <- ObservedRepresentation(NULL, popShares(),
BodyShares = bodyShares)
relVal <- RelativeRepresentation(obsVal, expVal)
output$obsBox <- renderText(sprintf("Observed representation:\n%.3f", obsVal))
output$relBox <- renderText(sprintf("Relative representation:\n%.3f", relVal))
} else {
output$obsBox <- renderText("Observed representation:\n—")
output$relBox <- renderText("Relative representation:\n—")
}
}, ignoreNULL = TRUE)
# ----- Bar plot ------------------------------------------------------------
output$sharePlot <- renderPlot({
req(popShares())
# Body shares (only if counts provided)
if (input$hasBody && !is.null(bodyCounts())) {
counts <- bodyCounts()
bodyShares <- counts / sum(counts)
} else {
bodyShares <- rep(NA_real_, length(popShares()))
}
df <- data.frame(
Group = factor(names(popShares()), levels = names(popShares())),
Population = as.numeric(popShares()),
Body = as.numeric(bodyShares)
)
df_long <- pivot_longer(df, -Group, names_to = "Type", values_to = "Share")
ggplot(df_long, aes(Group, Share, fill = Type)) +
geom_col(position = position_dodge(width = 0.6),
width = 0.55, na.rm = TRUE) +
scale_y_continuous(labels = percent_format(accuracy = 1)) +
scale_fill_manual(values = c(Population = "grey60", Body = "steelblue")) +
labs(x = NULL, y = "Share", fill = NULL) +
theme_minimal(base_size = 14) +
theme(legend.position = "bottom")
})
}
# --------------------------------------------------------------------
# 4. Launch the app
# --------------------------------------------------------------------
shinyApp(ui, server)
} |