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Update warmup/app_v1.R
Browse files- warmup/app_v1.R +524 -0
warmup/app_v1.R
CHANGED
@@ -0,0 +1,524 @@
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1 |
+
# setwd("~/Downloads")
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2 |
+
{
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3 |
+
# app.R
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4 |
+
options(error = NULL)
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5 |
+
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6 |
+
# ------------------------------
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7 |
+
# 1. Load Packages
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8 |
+
# ------------------------------
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9 |
+
library(shiny)
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10 |
+
library(shinydashboard)
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11 |
+
library(leaflet)
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12 |
+
library(raster)
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13 |
+
library(DT)
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14 |
+
library(readr)
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15 |
+
library(dplyr) # For data manipulation
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+
library(ggplot2) # For histogram
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17 |
+
library(RColorBrewer)
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18 |
+
library(sp) # For handling map clicks/extracting raster values
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19 |
+
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20 |
+
# ------------------------------
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21 |
+
# 2. Data & Config
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22 |
+
# ------------------------------
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23 |
+
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24 |
+
# Define time periods corresponding to each band in the GeoTIFF
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25 |
+
time_periods <- c("1990–1992", "1993–1995", "1996–1998", "1999–2001", "2002–2004",
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+
"2005–2007", "2008–2010", "2011–2013", "2014–2016", "2017–2019")
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+
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# Load GeoTIFF data (multi-band)
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29 |
+
wealth_stack <- stack("wealth_map.tif")
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30 |
+
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31 |
+
# Clean up out-of-range values
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32 |
+
wealth_stack[wealth_stack <= 0 | wealth_stack > 1] <- NA
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33 |
+
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+
# Load improvement data (change in IWI by state/province)
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35 |
+
improvement_data <- read_csv("poverty_improvement_by_state.csv")
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36 |
+
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37 |
+
# Pre-calculate the mean IWI for each band (for the "Trends Over Time" chart).
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38 |
+
band_means <- sapply(seq_len(nlayers(wealth_stack)), function(i) {
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39 |
+
vals <- values(wealth_stack[[i]])
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40 |
+
vals <- vals[!is.na(vals)]
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41 |
+
mean(vals)
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42 |
+
})
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43 |
+
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44 |
+
# ------------------------------
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45 |
+
# 3. UI
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46 |
+
# ------------------------------
|
47 |
+
ui <- dashboardPage(
|
48 |
+
# -- Header
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49 |
+
dashboardHeader(
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50 |
+
title = span(
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51 |
+
style = "font-weight: 600; font-size: 16px;",
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52 |
+
a(
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53 |
+
href = "http://aidevlab.org",
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54 |
+
"aidevlab.org",
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55 |
+
target = "_blank",
|
56 |
+
style = "font-family: 'OCR A Std', monospace; color: white; text-decoration: underline;"
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57 |
+
)
|
58 |
+
)
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59 |
+
),
|
60 |
+
|
61 |
+
# -- Sidebar
|
62 |
+
dashboardSidebar(
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63 |
+
sidebarMenu(
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64 |
+
id = "tabs",
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65 |
+
menuItem("Wealth Map", tabName = "mapTab", icon = icon("map")),
|
66 |
+
menuItem("Improvement Data", tabName = "improvementTab", icon = icon("table")),
|
67 |
+
menuItem("Trends Over Time", tabName = "trendTab", icon = icon("chart-line"))
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68 |
+
),
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69 |
+
# Show inputs only for the map tab
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70 |
+
conditionalPanel(
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71 |
+
condition = "input.tabs == 'mapTab'",
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72 |
+
br(),
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73 |
+
# Replaces the old selectInput for time periods with a slider that can animate
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74 |
+
sliderInput(
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75 |
+
inputId = "time_index",
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76 |
+
label = "Select Time Period (Years):",
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77 |
+
min = 1,
|
78 |
+
max = length(time_periods),
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79 |
+
value = 1,
|
80 |
+
step = 1,
|
81 |
+
animate = animationOptions(interval = 1500, loop = TRUE)
|
82 |
+
),
|
83 |
+
# Show the currently selected year range clearly
|
84 |
+
strong("Currently Selected: "),
|
85 |
+
textOutput("current_year_range", inline = TRUE),
|
86 |
+
br(), br(),
|
87 |
+
|
88 |
+
selectInput("color_palette", "Select Color Palette:",
|
89 |
+
choices = c("Viridis" = "viridis",
|
90 |
+
"Plasma" = "plasma",
|
91 |
+
"Magma" = "magma",
|
92 |
+
"Inferno"= "inferno",
|
93 |
+
"Spectral (Brewer)" = "Spectral"),
|
94 |
+
selected = "plasma"),
|
95 |
+
sliderInput("opacity", "Map Opacity:", min = 0.2, max = 1, value = 0.8, step = 0.1)
|
96 |
+
),
|
97 |
+
# ---- Here is the minimal "Share" button HTML + JS inlined in Shiny ----
|
98 |
+
# We wrap it in tags$div(...) and tags$script(HTML(...)) so it is recognized
|
99 |
+
# by Shiny. You can adjust the styling or placement as needed.
|
100 |
+
tags$div(
|
101 |
+
style = "text-align: left; margin: 1em 0 1em 2em;",
|
102 |
+
HTML('
|
103 |
+
<button id="share-button"
|
104 |
+
style="
|
105 |
+
display: inline-flex;
|
106 |
+
align-items: center;
|
107 |
+
justify-content: center;
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108 |
+
gap: 8px;
|
109 |
+
padding: 5px 10px;
|
110 |
+
font-size: 16px;
|
111 |
+
font-weight: normal;
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112 |
+
color: #000;
|
113 |
+
background-color: #fff;
|
114 |
+
border: 1px solid #ddd;
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115 |
+
border-radius: 6px;
|
116 |
+
cursor: pointer;
|
117 |
+
box-shadow: 0 1.5px 0 #000;
|
118 |
+
">
|
119 |
+
<svg width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor"
|
120 |
+
stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
|
121 |
+
<circle cx="18" cy="5" r="3"></circle>
|
122 |
+
<circle cx="6" cy="12" r="3"></circle>
|
123 |
+
<circle cx="18" cy="19" r="3"></circle>
|
124 |
+
<line x1="8.59" y1="13.51" x2="15.42" y2="17.49"></line>
|
125 |
+
<line x1="15.41" y1="6.51" x2="8.59" y2="10.49"></line>
|
126 |
+
</svg>
|
127 |
+
<strong>Share</strong>
|
128 |
+
</button>
|
129 |
+
'),
|
130 |
+
# Insert the JS as well
|
131 |
+
tags$script(
|
132 |
+
HTML("
|
133 |
+
(function() {
|
134 |
+
const shareBtn = document.getElementById('share-button');
|
135 |
+
// Reusable helper function to show a small “Copied!” message
|
136 |
+
function showCopyNotification() {
|
137 |
+
const notification = document.createElement('div');
|
138 |
+
notification.innerText = 'Copied to clipboard';
|
139 |
+
notification.style.position = 'fixed';
|
140 |
+
notification.style.bottom = '20px';
|
141 |
+
notification.style.right = '20px';
|
142 |
+
notification.style.backgroundColor = 'rgba(0, 0, 0, 0.8)';
|
143 |
+
notification.style.color = '#fff';
|
144 |
+
notification.style.padding = '8px 12px';
|
145 |
+
notification.style.borderRadius = '4px';
|
146 |
+
notification.style.zIndex = '9999';
|
147 |
+
document.body.appendChild(notification);
|
148 |
+
setTimeout(() => { notification.remove(); }, 2000);
|
149 |
+
}
|
150 |
+
shareBtn.addEventListener('click', function() {
|
151 |
+
const currentURL = window.location.href;
|
152 |
+
const pageTitle = document.title || 'Check this out!';
|
153 |
+
// If browser supports Web Share API
|
154 |
+
if (navigator.share) {
|
155 |
+
navigator.share({
|
156 |
+
title: pageTitle,
|
157 |
+
text: '',
|
158 |
+
url: currentURL
|
159 |
+
})
|
160 |
+
.catch((error) => {
|
161 |
+
console.log('Sharing failed', error);
|
162 |
+
});
|
163 |
+
} else {
|
164 |
+
// Fallback: Copy URL
|
165 |
+
if (navigator.clipboard && navigator.clipboard.writeText) {
|
166 |
+
navigator.clipboard.writeText(currentURL).then(() => {
|
167 |
+
showCopyNotification();
|
168 |
+
}, (err) => {
|
169 |
+
console.error('Could not copy text: ', err);
|
170 |
+
});
|
171 |
+
} else {
|
172 |
+
// Double fallback for older browsers
|
173 |
+
const textArea = document.createElement('textarea');
|
174 |
+
textArea.value = currentURL;
|
175 |
+
document.body.appendChild(textArea);
|
176 |
+
textArea.select();
|
177 |
+
try {
|
178 |
+
document.execCommand('copy');
|
179 |
+
showCopyNotification();
|
180 |
+
} catch (err) {
|
181 |
+
alert('Please copy this link:\\n' + currentURL);
|
182 |
+
}
|
183 |
+
document.body.removeChild(textArea);
|
184 |
+
}
|
185 |
+
}
|
186 |
+
});
|
187 |
+
})();
|
188 |
+
")
|
189 |
+
)
|
190 |
+
)
|
191 |
+
# ---- End: Minimal Share button snippet ----
|
192 |
+
),
|
193 |
+
|
194 |
+
# -- Body
|
195 |
+
dashboardBody(
|
196 |
+
tags$head(
|
197 |
+
tags$link(rel = "stylesheet", href = "https://fonts.cdnfonts.com/css/ocr-a-std"),
|
198 |
+
# Make the "play" button whiter/brighter
|
199 |
+
tags$style(HTML("
|
200 |
+
body {
|
201 |
+
font-family: 'OCR A Std', monospace !important;
|
202 |
+
}
|
203 |
+
.slider-animate-button {
|
204 |
+
background-color: #ffffff !important;
|
205 |
+
color: #000000 !important;
|
206 |
+
border: 2px solid #000000 !important;
|
207 |
+
border-radius: 5px !important;
|
208 |
+
padding: 5px 10px !important;
|
209 |
+
top: 10px !important;
|
210 |
+
}
|
211 |
+
"))
|
212 |
+
),
|
213 |
+
tabItems(
|
214 |
+
# ---------- MAP TAB ----------
|
215 |
+
tabItem(
|
216 |
+
tabName = "mapTab",
|
217 |
+
fluidRow(
|
218 |
+
# Value Boxes across the top for key stats
|
219 |
+
valueBoxOutput("highest_iwi_vb", width = 4),
|
220 |
+
valueBoxOutput("lowest_iwi_vb", width = 4),
|
221 |
+
valueBoxOutput("avg_iwi_vb", width = 4)
|
222 |
+
),
|
223 |
+
fluidRow(
|
224 |
+
# Map
|
225 |
+
box(
|
226 |
+
title = "Wealth Map of Africa", width = 8, solidHeader = TRUE, status = "primary",
|
227 |
+
leafletOutput("map", height = "550px"),
|
228 |
+
p("Click anywhere on the map to view the time-series of IWI for that specific location (shown below).")
|
229 |
+
),
|
230 |
+
# Histogram
|
231 |
+
box(
|
232 |
+
title = "IWI Distribution (Selected Period)", width = 4, solidHeader = TRUE, status = "info",
|
233 |
+
plotOutput("iwi_histogram", height = "250px"),
|
234 |
+
p("This histogram shows the distribution of the International Wealth Index (IWI) values for the selected time period across Africa."),
|
235 |
+
br(),
|
236 |
+
strong("Note:"),
|
237 |
+
" Wealth estimates for areas without human settlements have been excluded from the analysis."
|
238 |
+
)
|
239 |
+
),
|
240 |
+
# Time series at clicked location
|
241 |
+
fluidRow(
|
242 |
+
box(
|
243 |
+
title = "Time Series at Clicked Location", width = 12, solidHeader = TRUE, status = "warning",
|
244 |
+
plotOutput("clicked_ts_plot", height = "300px"),
|
245 |
+
p("Click on the map to see the full IWI time-series (1990–2019) for that location.")
|
246 |
+
)
|
247 |
+
)
|
248 |
+
),
|
249 |
+
|
250 |
+
# ---------- IMPROVEMENT DATA TAB ----------
|
251 |
+
tabItem(
|
252 |
+
tabName = "improvementTab",
|
253 |
+
fluidRow(
|
254 |
+
box(
|
255 |
+
width = 12, title = "Poverty Improvement by State", status = "primary", solidHeader = TRUE,
|
256 |
+
p("This table shows the estimated improvement in mean IWI between 1990–1992 and 2017–2019 for each province in Africa.
|
257 |
+
The 'Improvement' column indicates the change in IWI over this period. You can sort or filter the table,
|
258 |
+
and use the download button to export the data."),
|
259 |
+
downloadButton("download_data", "Download CSV", icon = icon("download")),
|
260 |
+
br(), br(),
|
261 |
+
DTOutput("improvement_table")
|
262 |
+
)
|
263 |
+
)
|
264 |
+
),
|
265 |
+
|
266 |
+
# ---------- TRENDS OVER TIME TAB ----------
|
267 |
+
tabItem(
|
268 |
+
tabName = "trendTab",
|
269 |
+
fluidRow(
|
270 |
+
box(
|
271 |
+
width = 12, title = "Average Wealth Index Across Africa Over Time", status = "success", solidHeader = TRUE,
|
272 |
+
p("This chart aggregates the mean IWI across all of Africa in each of the ten time periods.
|
273 |
+
It provides a high-level view of how wealth (as measured by IWI) has changed over time."),
|
274 |
+
plotOutput("trend_plot", height = "400px")
|
275 |
+
)
|
276 |
+
)
|
277 |
+
)
|
278 |
+
)
|
279 |
+
)
|
280 |
+
)
|
281 |
+
|
282 |
+
# ------------------------------
|
283 |
+
# 4. Server
|
284 |
+
# ------------------------------
|
285 |
+
server <- function(input, output, session) {
|
286 |
+
|
287 |
+
# ReactiveVal to store the time-series of the last clicked point (across all periods).
|
288 |
+
clicked_point_vals <- reactiveVal(NULL)
|
289 |
+
|
290 |
+
# ----------------------------------
|
291 |
+
# Reactive expression for selected raster layer
|
292 |
+
# ----------------------------------
|
293 |
+
selected_raster <- reactive({
|
294 |
+
req(input$time_index)
|
295 |
+
wealth_stack[[input$time_index]]
|
296 |
+
})
|
297 |
+
|
298 |
+
# ----------------------------------
|
299 |
+
# Custom color palette function
|
300 |
+
# (reactive to user-selected palette)
|
301 |
+
# ----------------------------------
|
302 |
+
color_pal <- reactive({
|
303 |
+
palette_choice <- switch(
|
304 |
+
input$color_palette,
|
305 |
+
"viridis" = "viridis",
|
306 |
+
"plasma" = "plasma",
|
307 |
+
"magma" = "magma",
|
308 |
+
"inferno" = "inferno",
|
309 |
+
# Fallback to a Brewer palette for "Spectral"
|
310 |
+
"Spectral" = "Spectral"
|
311 |
+
)
|
312 |
+
colorNumeric(
|
313 |
+
palette = palette_choice,
|
314 |
+
domain = c(0, 1), # Domain for map: 0 to 1
|
315 |
+
na.color = "transparent"
|
316 |
+
)
|
317 |
+
})
|
318 |
+
|
319 |
+
# ----------------------------------
|
320 |
+
# Display the currently selected time period (year range)
|
321 |
+
# ----------------------------------
|
322 |
+
output$current_year_range <- renderText({
|
323 |
+
time_periods[input$time_index]
|
324 |
+
})
|
325 |
+
|
326 |
+
# ----------------------------------
|
327 |
+
# 1. MAP OUTPUT
|
328 |
+
# ----------------------------------
|
329 |
+
output$map <- renderLeaflet({
|
330 |
+
# We'll create 5 legend steps: 1, 0.75, 0.5, 0.25, 0
|
331 |
+
legend_values <- seq(1, 0, length.out = 5)
|
332 |
+
|
333 |
+
leaflet() %>%
|
334 |
+
addProviderTiles(providers$OpenStreetMap) %>%
|
335 |
+
setView(lng = 20, lat = 0, zoom = 3) %>% # Center on Africa
|
336 |
+
addLegend(
|
337 |
+
position = "bottomright",
|
338 |
+
colors = color_pal()(legend_values),
|
339 |
+
labels = sprintf("%.2f", legend_values),
|
340 |
+
title = "IWI",
|
341 |
+
opacity = 1
|
342 |
+
)
|
343 |
+
})
|
344 |
+
|
345 |
+
# Redraw the raster when inputs change
|
346 |
+
observeEvent(list(input$time_index, input$color_palette, input$opacity), {
|
347 |
+
leafletProxy("map") %>%
|
348 |
+
clearImages() %>%
|
349 |
+
addRasterImage(
|
350 |
+
selected_raster(),
|
351 |
+
colors = color_pal(),
|
352 |
+
opacity = input$opacity,
|
353 |
+
project = TRUE
|
354 |
+
)
|
355 |
+
})
|
356 |
+
|
357 |
+
# ----------------------------------
|
358 |
+
# Handle clicks on the map to show full time-series at that location
|
359 |
+
# ----------------------------------
|
360 |
+
observeEvent(input$map_click, {
|
361 |
+
click <- input$map_click
|
362 |
+
if (!is.null(click)) {
|
363 |
+
lat <- click$lat
|
364 |
+
lng <- click$lng
|
365 |
+
|
366 |
+
# Convert clicked point to SpatialPoints
|
367 |
+
coords <- data.frame(lng = lng, lat = lat)
|
368 |
+
sp_pt <- SpatialPoints(coords, proj4string = CRS("+proj=longlat +datum=WGS84 +no_defs"))
|
369 |
+
|
370 |
+
# Extract values across ALL bands at the clicked location
|
371 |
+
extracted_vals <- raster::extract(wealth_stack, sp_pt)
|
372 |
+
# extracted_vals is a 1x10 matrix if the point is valid
|
373 |
+
if (!is.null(extracted_vals)) {
|
374 |
+
# Convert to numeric vector
|
375 |
+
clicked_point_vals(as.numeric(extracted_vals))
|
376 |
+
} else {
|
377 |
+
# If the point is outside the raster or invalid
|
378 |
+
clicked_point_vals(NULL)
|
379 |
+
}
|
380 |
+
}
|
381 |
+
})
|
382 |
+
|
383 |
+
# Plot the time-series for the clicked location
|
384 |
+
output$clicked_ts_plot <- renderPlot({
|
385 |
+
vals <- clicked_point_vals()
|
386 |
+
if (is.null(vals)) {
|
387 |
+
# No location clicked yet or invalid click
|
388 |
+
plot.new()
|
389 |
+
title("Click on the map to see the IWI time-series here.")
|
390 |
+
return()
|
391 |
+
}
|
392 |
+
|
393 |
+
# If user clicked in a region with all NAs, do not plot
|
394 |
+
if (all(is.na(vals))) {
|
395 |
+
plot.new()
|
396 |
+
title("No data at this location. Try another spot.")
|
397 |
+
return()
|
398 |
+
}
|
399 |
+
|
400 |
+
df <- data.frame(Period = factor(time_periods, levels = time_periods),
|
401 |
+
IWI = vals)
|
402 |
+
|
403 |
+
ggplot(df, aes(x = Period, y = IWI, group = 1)) +
|
404 |
+
geom_line(color = "darkorange", size = 1) +
|
405 |
+
geom_point(color = "darkorange", size = 2) +
|
406 |
+
labs(title = "Time Series of IWI at Clicked Location",
|
407 |
+
x = "Time Period",
|
408 |
+
y = "IWI (0 to 1)") +
|
409 |
+
ylim(0, 1) +
|
410 |
+
theme_minimal(base_size = 14) +
|
411 |
+
theme(axis.text.x = element_text(angle = 45, hjust = 1))
|
412 |
+
})
|
413 |
+
|
414 |
+
# ----------------------------------
|
415 |
+
# 2. HISTOGRAM OUTPUT (for selected time period)
|
416 |
+
# ----------------------------------
|
417 |
+
output$iwi_histogram <- renderPlot({
|
418 |
+
# Extract raster values for histogram
|
419 |
+
r_vals <- values(selected_raster())
|
420 |
+
r_vals <- r_vals[!is.na(r_vals)]
|
421 |
+
|
422 |
+
ggplot(data.frame(iwi = r_vals), aes(x = iwi)) +
|
423 |
+
geom_histogram(binwidth = 0.02, fill = "#2c7bb6", color = "white", alpha = 0.7) +
|
424 |
+
labs(x = "IWI (0 to 1)", y = "Frequency") +
|
425 |
+
theme_minimal(base_size = 14)
|
426 |
+
})
|
427 |
+
|
428 |
+
# ----------------------------------
|
429 |
+
# 3. VALUE BOXES FOR KEY STATS
|
430 |
+
# ----------------------------------
|
431 |
+
# Compute stats for current raster
|
432 |
+
raster_stats <- reactive({
|
433 |
+
r_vals <- values(selected_raster())
|
434 |
+
r_vals <- r_vals[!is.na(r_vals)]
|
435 |
+
list(
|
436 |
+
highest = max(r_vals, na.rm = TRUE),
|
437 |
+
lowest = min(r_vals, na.rm = TRUE),
|
438 |
+
average = mean(r_vals, na.rm = TRUE)
|
439 |
+
)
|
440 |
+
})
|
441 |
+
|
442 |
+
# Highest IWI
|
443 |
+
output$highest_iwi_vb <- renderValueBox({
|
444 |
+
valueBox(
|
445 |
+
value = round(raster_stats()$highest, 3),
|
446 |
+
subtitle = "Highest IWI",
|
447 |
+
icon = icon("arrow-up"),
|
448 |
+
color = "green"
|
449 |
+
)
|
450 |
+
})
|
451 |
+
|
452 |
+
# Lowest IWI
|
453 |
+
output$lowest_iwi_vb <- renderValueBox({
|
454 |
+
valueBox(
|
455 |
+
value = round(raster_stats()$lowest, 3),
|
456 |
+
subtitle = "Lowest IWI",
|
457 |
+
icon = icon("arrow-down"),
|
458 |
+
color = "red"
|
459 |
+
)
|
460 |
+
})
|
461 |
+
|
462 |
+
# Average IWI
|
463 |
+
output$avg_iwi_vb <- renderValueBox({
|
464 |
+
valueBox(
|
465 |
+
value = round(raster_stats()$average, 3),
|
466 |
+
subtitle = "Average IWI",
|
467 |
+
icon = icon("balance-scale"),
|
468 |
+
color = "blue"
|
469 |
+
)
|
470 |
+
})
|
471 |
+
|
472 |
+
# ----------------------------------
|
473 |
+
# 4. IMPROVEMENT DATA TABLE
|
474 |
+
# ----------------------------------
|
475 |
+
output$improvement_table <- renderDT({
|
476 |
+
datatable(
|
477 |
+
improvement_data,
|
478 |
+
filter = "top",
|
479 |
+
options = list(
|
480 |
+
scrollX = TRUE,
|
481 |
+
pageLength = 20,
|
482 |
+
autoWidth = TRUE
|
483 |
+
)
|
484 |
+
)
|
485 |
+
})
|
486 |
+
|
487 |
+
# Download CSV
|
488 |
+
output$download_data <- downloadHandler(
|
489 |
+
filename = function() {
|
490 |
+
paste0("poverty_improvement_", Sys.Date(), ".csv")
|
491 |
+
},
|
492 |
+
content = function(file) {
|
493 |
+
write.csv(improvement_data, file, row.names = FALSE)
|
494 |
+
}
|
495 |
+
)
|
496 |
+
|
497 |
+
# ----------------------------------
|
498 |
+
# 5. TRENDS OVER TIME (line chart of mean IWI across all Africa)
|
499 |
+
# ----------------------------------
|
500 |
+
output$trend_plot <- renderPlot({
|
501 |
+
df <- data.frame(
|
502 |
+
Period = factor(time_periods, levels = time_periods),
|
503 |
+
MeanIWI = band_means
|
504 |
+
)
|
505 |
+
|
506 |
+
ggplot(df, aes(x = Period, y = MeanIWI, group = 1)) +
|
507 |
+
geom_line(color = "#2c7bb6", size = 1.1) +
|
508 |
+
geom_point(color = "#2c7bb6", size = 2) +
|
509 |
+
labs(
|
510 |
+
title = "Average IWI Over Time (Africa)",
|
511 |
+
x = "Time Period",
|
512 |
+
y = "Mean IWI"
|
513 |
+
) +
|
514 |
+
ylim(0, 1) +
|
515 |
+
theme_minimal(base_size = 14) +
|
516 |
+
theme(axis.text.x = element_text(angle = 45, hjust = 1))
|
517 |
+
})
|
518 |
+
}
|
519 |
+
|
520 |
+
# ------------------------------
|
521 |
+
# 6. Run the App
|
522 |
+
# ------------------------------
|
523 |
+
shinyApp(ui = ui, server = server)
|
524 |
+
}
|