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app.R
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app.R
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library(shiny)
library(magrittr)
library(ggplot2)
library(thesis)
options(tigris_use_cache = TRUE)
# Distribution Plotting UI ----
ui <- fluidPage(
titlePanel("Physaria Spatial Analysis"),
mainPanel(
sidebarPanel(actionButton("resetButton", "Reset Map")),
tabsetPanel(
# Map plot of specimen distribution.
tabPanel(title = "Distribution",
fluidRow(column(width = 6, tableOutput(outputId = "mapRange"))),
fluidRow(
column(12,
plotOutput(
outputId = "mapPlot",
brush = brushOpts(
id = "mapBrush", delay = 500,
resetOnNew = TRUE)
)
)
),
fluidRow(
column(6,
fluidRow(
selectInput(
inputId = "map_color_aes", label = "Mapped Taxa ID",
choices = list("prior_id", "prior_1", "prior_2", "prior_3",
"prior_4", "Taxon_a_posteriori"),
selected = "prior_id")),
hr(),
fluidRow(
checkboxInput(inputId = "spp_find", value = FALSE,
label = "Find individual specimen?"),
textInput(inputId = "collector_id", value = NA,
label = "Collector"),
textInput(inputId = "collection", value = NA,
label = "Collection Number")
)
),
column(6,
plotOutput("mapLegend")
)
)
),
# Reactive table of brushed specimens.
tabPanel("Specimens", tableOutput("specimens"))
)
)
)
# Shiny App Server ----
server <- function(input, output, session) {
# Reactive Specimen Subset
specimens <- reactiveValues(data = NULL)
# Plot Reset ----
observeEvent(input$resetButton, {
specimens$data <- thesis::herbarium_specimens %>%
# Filter specimens without manual aesthetic value specification.
# TODO Report excluded specimens in `Specimens` tab
dplyr::filter(.data = ., .data[[input$map_color_aes]] %in%
names(thesis::spp_color))
})
# Brush Subset ----
observeEvent(input$mapBrush, {
# List of brush coordinates.
brush_dim <- reactive({
brushOpts(input$mapBrush)$id[c("xmin", "xmax", "ymin", "ymax")]
})
# Subset of specimens by brushed dimensions.
specimens$data <- specimens$data %>%
dplyr::filter(
.data$Longitude > brush_dim()$xmin, .data$Longitude < brush_dim()$xmax,
.data$Latitude > brush_dim()$ymin, .data$Latitude < brush_dim()$ymax
)
# Render table of brushed specimens.
output$specimens <- renderTable({
specimens$data %>%
dplyr::select("prior_id", "Taxon_a_posteriori",
"Collector", "Collection_Number")
})
})
# ggplot Reactive ----
plot_map <- reactive({
# ggplot tidy eval in aes_()
legend_id <- input$map_color_aes
ggplot2::ggplot() +
layer_borders(
spl_extent = spl_bbox(specimens$data),
sf_county_color = "black") +
layer_specimens(
specimen_tbl = specimens$data,
id_column = legend_id, shape_aes = TRUE) +
layer_themes(
specimen_tbl = specimens$data,
id_column = legend_id, legend_title = legend_id) +
coord_sf(
xlim = range(spl_bbox(specimens$data)[["Longitude"]]),
ylim = range(spl_bbox(specimens$data)[["Latitude"]])
)
})
# Map Output ----
output$mapPlot <- renderPlot({
req(input$resetButton)
if (input$spp_find == TRUE) {
req(input$collector_id)
req(input$collection)
plot_map() +
spl_id(specimen_tbl = specimens$data,
id_column = input$map_color_aes, shape_aes = input$map_color_aes,
collector = isolate(input$collector_id),
collection = isolate(input$collection)) +
theme(legend.position = "none")
} else {
plot_map() +
theme(legend.position = "none")
}
},
height = function() session$clientData$output_mapPlot_height,
res = 96
)
# Legend Output ----
output$mapLegend <- renderPlot({
if (!is.null(specimens$data)) {
cowplot::plot_grid(
cowplot::get_legend(
plot_map() + guides(col = guide_legend(ncol = 2))
), vjust = 1
)
}
})
}
# Run app ----
shinyApp(ui, server)