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app-linear-fix-sd-plot.R
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# Initialization -------------------------------------------------------------
# Load libraries. ----
if (!("package:aws.s3" %in% search())) {
suppressMessages(library(aws.s3))
}
if (!("package:shiny" %in% search())) {
suppressMessages(library(shiny))
}
if (!("package:shinythemes" %in% search())) {
suppressMessages(library(shinythemes))
}
if (!("package:shinyjs" %in% search())) {
suppressMessages(library(shinyjs))
}
if (!("package:shinipsum" %in% search())) {
suppressMessages(library(shinipsum))
}
if (!("package:htmltools" %in% search())) {
suppressMessages(library(htmltools))
}
if (!("package:ggplot2" %in% search())) {
suppressMessages(library(ggplot2))
}
if (!("package:leaflet" %in% search())) {
suppressMessages(library(leaflet))
}
if (!("package:sf" %in% search())) {
suppressMessages(library(sf))
}
if (!("package:wesanderson" %in% search())) {
suppressMessages(library(wesanderson))
}
if (!("package:dplyr" %in% search())) {
suppressMessages(library(dplyr))
}
if (!("package:spdplyr" %in% search())) {
suppressMessages(library(spdplyr))
}
if (!("package:readr" %in% search())) {
suppressMessages(library(readr))
}
if (!("package:lubridate" %in% search())) {
suppressMessages(library(lubridate))
}
if (!("package:scales" %in% search())) {
suppressMessages(library(scales))
}
if (!("package:DT" %in% search())) {
suppressMessages(library(DT))
}
# # Debug. #####
# if (Sys.info()["nodename"] == "Home-iMac.local") {
# if (!("package:reactlog" %in% search())) {
# suppressMessages(library(reactlog))
# }
# reactlogReset()
# reactlog_enable()
# }
# Initialization. ----
# # Application title.
# app_title <- paste("DWR-WaS/DET: Division of Water Rights",
# "Water Supply/Demand Exploration Tool")
# Load data from AWS S3 bucket. ----
## Load S3 keys. ----
source("load-s3-keys.R")
## Load Water Right Info. ----
s3load(object = "wasdet-wrinfo.RData",
bucket = "dwr-shiny-apps")
## Load Demand Data. ----
## Load smaller test set if on local machine for testing.
s3load(object = "wasdet-demands-test-set.RData", bucket = "dwr-shiny-apps")
## Load Supply data. ----
s3load(object = "wasdet-supplies.RData",
bucket = "dwr-shiny-apps")
# Load local data. ----
# ## Gage station location information. ----
# station_locs <- read_csv("./common/station-locations.csv")
# Define color and shape aesthetics. ----
# Demand.
wa_demand_order <- ordered(c("Junior Post-14",
"Post-14",
"Statement Demand",
"Environmental Demand"))
wa_demand_pal <- c(wes_palettes$GrandBudapest1[c(2, 1)], "#BEBEBE", "#000000")
names(wa_demand_pal) <- wa_demand_order
map_demand_pal <- colorFactor(palette = wa_demand_pal,
levels = names(wa_demand_pal))
# Water right type.
plot_wrt_pal <- c(wes_palette("Darjeeling1"),
wes_palette("Darjeeling2"))[2:10]
names(plot_wrt_pal) <- sort(unique(wr_info$wr_type))
map_wrt_pal <- colorFactor(palette = plot_wrt_pal,
domain = wr_info$wr_type)
# Priority.
priority_order <- c(c(year(now()):1914),
"Statement Demand", "Environmental Demand")
priority_pal <- c(viridis_pal()(length(c(year(now()):1914))),
"#BEBEBE", "#000000")
names(priority_pal) <- priority_order
map_priority_pal <- colorFactor(palette = priority_pal,
levels = names(priority_pal))
# Historical and Forecast supply.
wa_supply_pal <- colorRampPalette(wes_palette("Rushmore")[3:4])(3)
wa_supply_shapes <- c(15, 16, 17)
# Current-year supply.
cy_supply_pal <- "blue"
# VSD Plot theme.
vsd_plot_theme <- theme(
legend.box = "vertical",
legend.direction = "horizontal",
# strip.text.x = element_text(size = rel(1.5)),
# axis.title = element_text(size = rel(1.2)),
# axis.text = element_text(size = rel(1.2)),
# legend.text = element_text(size = rel(1.2)),
# legend.title = element_text(size = rel(1.2)),
axis.title.x = element_blank()
)
# Mini map icons.
station_icon <- icons(iconUrl = "./www/x-diamond-fill.svg")
# Icon legend for vsd plot.
html_legend <-
"<img src='circle-fill.svg' style='width:8px;height:8px;'> Point of Diversion<br/>
<img src='x-diamond-fill.svg'> Gage Station"
# UI ---------------------------------------------------------------------------
#
# ui <- fluidPage( # Start fluidpage_1
# useShinyjs(),
#
# # Set theme.
# theme = shinytheme("cerulean"),
#
# ## Title bar. ----
# titlePanel(windowTitle = app_title,
# title =
# div(
# img(
# src = "DWR-ENF-Logo-2048.png",
# height = 50,
# ),
# app_title
# )
# ),
#
# # # Prototype Warning.
# # p(paste("Under Development. Do not rely on data used in this dashboard",
# # "until it is officially released."),
# # style = "color:red"),
#
# ## Main Tabs. ----
# navbarPage(title = NULL,
# ### Explore. ----
# tabPanel("Explore",
#
# fluidRow(
# sidebarLayout(
#
# #### Sidebar Panel. ----
# sidebarPanel(width = 2,
#
# ##### Mandatory inputs. ----
#
# ###### Select units to display. ----
# radioButtons(inputId = "units_selected",
# label = "Select Units:",
# choiceNames = list(
# "Cubic Feet per Second (cfs)",
# "Acre-Feet per Day (AF/d)"
# ),
# choiceValues = list(
# "cfs",
# "afd"
# ),
# selected = "cfs"
# ),
#
# ###### Select HUC-8 watershed. ----
# selectInput(inputId = "huc8_selected",
# label = "Select HUC-8 Watershed:",
# choices = NULL,
# selected = NULL,
# multiple = FALSE
# ),
#
# ###### Filter for watersheds with supply information. ----
# checkboxInput(inputId = "supply_filter",
# label = "Filter for watersheds with available supply information",
# value = FALSE
# ),
#
# ###### Select demand scenario(s). ----
# selectizeInput(inputId = "d_scene_selected",
# label = "Select Up To Two Demand Scenarios:",
# choices = NULL,
# selected = NULL,
# multiple = TRUE,
# options = list(maxItems = 2)
# ),
#
# ##### Conditional Inputs. ----
#
# wellPanel(
#
# ###### Select supply scenario(s) for vsd_plot. ----
# selectizeInput(inputId = "s_scene_selected",
# label = "Select Up To Three Supply Scenarios:",
# choices = NULL,
# selected = NULL,
# multiple = TRUE,
# options = list(maxItems = 3)
# ),
#
# ###### Select priority year to slice for vsd_plot. ----
# selectInput(inputId = "priority_selected",
# label = "Select Demand Priority Year:",
# choices = NULL,
# selected = NULL,
# multiple = FALSE),
#
# ###### Select water right types to include in dbwrt_plot. ----
# checkboxGroupInput(inputId = "wrt_selected",
# label = "Select Water Right Type(s) to Display:",
# choices = NULL,
# selected = NULL)
# ),
#
# ##### Copyright. ----
# HTML('<center><img src="waterboards_logo_high_res.jpg", width = "75%"></center>'),
# HTML(paste("<center>©", year(now()),
# "State Water Resources Control Board</center>"))
# ),
#
# #### Main Panel. ----
# mainPanel(width = 10,
#
# # Plot/Data/Watershed map Tabs.
# tabsetPanel(type = "pills",
#
# ##### Plot tabs. ----
# tabPanel("Plots",
# fluidRow(
#
# # Plot column.
# column(width = 7,
# tabsetPanel(id = "plot_tabs",
# type = "pills",
#
# ###### Supply-Demand plot tab. ----
# tabPanel(title = "Supply-Demand Scenarios",
# id = "vsd_tab",
# fluidRow(
# plotOutput(outputId = "vsd_plot")
# )
# ),
#
# ###### Demand by Water right type plot tab. ----
# tabPanel(title = "Demand by Water Right Type",
# id = "dbwrt_tab",
# fluidRow(
# br(),
# plotOutput(outputId = "dbwrt_plot")
# )
# ),
#
# ###### Demand by priority plot tab. ----
# tabPanel(title = "Demand by Priority",
# id = "dbp_tab",
# fluidRow(
# br(),
# plotOutput(outputId = "dbp_plot")
# )
# )
# )
# ),
#
# ##### Mini map column. ----
#
# ###### Mini map. ----
# column(width = 5,
# fluidRow(
# h4("Watershed Location and PODs"),
# leafletOutput(outputId = "mini_map",
# height = "500px",
# width = "95%"),
# br(),
#
# ###### Debug notes. ----
# h3("Debug"),
# textOutput("debug_text")
# )
# )
# )
# ),
#
# ##### Data tab. ----
# tabPanel("Data",
# br(),
# h3("Selected Demand Data"),
# DTOutput(outputId = "demand_data_table")
# ),
#
# ##### California Watershed Map tab. ----
# tabPanel("California Watershed Map",
# br(),
# h3("Coming soon...")
# )
# )
# )
# )
# )
# ),
#
# ### Dataset Information. ----
# navbarMenu("Dataset Information",
# icon = icon("table"),
# tabPanel("Demand Scenarios",
# icon = icon("faucet"),
# "Demand Scenarios", br(),
# "Content Goes Here",br(),br(),
# includeMarkdown("docs/temp_data_descrip.md")),
#
# tabPanel("Supply Scenarios",
# icon = icon("water"),
# "Supply Scenarios", br(),
# "Content Goes Here"),
# tabPanel("Other Data",
# icon = icon("table"),
# "Other Data", br(),
# "Content Goes Here")
# ),
#
# ### About/Help. ----
# navbarMenu("About/Help",
# icon = icon("info-circle"),
# tabPanel("About",
# icon = icon("info-circle"),
# includeMarkdown("docs/ABOUT.md")),
# tabPanel("How To Use The Filters",
# icon = icon("life-ring"),
# "How To Use The Filters", br(),
# "Content Goes Here"),
# tabPanel("FAQ",
# icon = icon("question"),
# "Frequently Asked Question", br(),
# "Content Goes Here"),
#
#
# tabPanel("Report Bugs/Data Issues",
# icon = icon("bug"),
# "link to GitHub repository,",br(),
# "data maintainer contacts?")
# )
# ),
# selected = "Explore"
# ) # end fluidPage_1
#
# # SERVER -----------------------------------------------------------------------
#
# server <- function(input, output, session) {
#
# # Debug. ----
#
# output$debug_text <- renderText({ paste0("DEBUG:",
# "\ninput$huc8_selected is: ",
# input$huc8_selected,
# "\ninput$s_scenario_selected is: ",
# input$s_scenario_selected[1])
# })
#
# # Setup. ----
#
# # Disable units selector until implemented
# disable(id = "units_selected")
# # disable(id = "supply_filter")
# Helper Functions. ----
# Define plot height function to keep facet panels roughly the same height
# whether displaying one or two.
plot_height <-
ifelse(length(input_d_scene_selected) == 1, 480,
ifelse(length(input_d_scene_selected) == 2, 835, "auto"))
# # OBSERVERS. ----
#
# ## Control input selectors. ----
# observe({
# if (input$plot_tabs == "Supply-Demand Scenarios") {
# showElement(id = "s_scene_selected")
# showElement(id = "priority_selected")
# hideElement(id = "wrt_selected")
# } else
# if (input$plot_tabs == "Demand by Water Right Type") {
# hideElement(id = "s_scene_selected")
# hideElement(id = "priority_selected")
# showElement(id = "wrt_selected")
# } else
# if (input$plot_tabs == "Demand by Priority") {
# hideElement(id = "s_scene_selected")
# hideElement(id = "priority_selected")
# showElement(id = "wrt_selected")
# }
# })
## Filter for watersheds that have supply data. ----
# observeEvent(input$supply_filter, {
if (input_supply_filter) {
# choices <- sort(names(demand))
choices <- sort(names(demand)[names(demand) %in% names(supply)])
} else {
choices <- sort(names(demand))
}
# updateSelectInput(session,
# inputId = "huc8_selected",
# choices = choices,
# selected = "Upper San Joaquin")
# })
## Update demand scenario choices. ----
# observeEvent(input$huc8_selected, {
choices <- sort(unique(demand[[input_huc8_selected]]$d_scenario))
# updateSelectizeInput(session,
# inputId = "d_scene_selected",
# choices = choices,
# selected = "Reported Diversions - 2019")
# })
## XXXXXXXXXXXXX Finished to here
## Update supply scenario choices. ----
# observeEvent(input$huc8_selected, {
choices <- sort(unique(supply[[input_huc8_selected]]$s_scenario))
# updateSelectizeInput(session,
# inputId = "s_scene_selected",
# choices = choices,
# selected = NULL)
# })
## Update priority year choices. ----
py_choice_list <- # reactive({
sort(na.omit(unique(demand[[input_huc8_selected]]$p_year)), decreasing = TRUE)
# })
# observeEvent(input$d_scene_selected, {
choices <- py_choice_list[py_choice_list > min(py_choice_list)]
# updateSelectInput(session, "priority_selected",
# choices = choices,
# # selected = max(choices),
# selected = sample(choices, 1))
# })
## Update water right type choices. ----
# observeEvent(input$huc8_selected, {
choices <- unique(demand[[input_huc8_selected]]$wr_type)
# updateCheckboxGroupInput(session = session,
# inputId = "wrt_selected",
# choices = choices,
# selected = choices)
# })
# OUTPUTS. ----
## Supply-Demand Scenario plot (vsd). ----
### Build dataset. ----
## This is where the magic happens.
vsd_plot_data <- # reactive({
bind_rows(
{
# Demand.
filter(demand[[input_huc8_selected]],
d_scenario %in% input_d_scene_selected) %>%
mutate(fill_color = if_else(priority == "Statement Demand",
"Statement Demand",
if_else(priority == "Statement Demand",
"Statement Demand",
if_else(p_year >= input_priority_selected,
"Junior Post-14", "Post-14"))),
fill_color = ordered(fill_color, levels = wa_demand_order)) %>%
group_by(d_scenario, plot_date, fill_color, plot_category) %>%
summarise(af_monthly = sum(af_monthly, na.rm = TRUE),
af_daily = sum(af_daily, na.rm = TRUE),
cfs = sum(cfs, na.rm = TRUE),
.groups = "drop") %>%
mutate(s_scenario = NA) %>%
select(d_scenario,
s_scenario,
plot_date,
fill_color,
af_monthly,
af_daily,
cfs,
plot_category) %>%
# Add boundary points to facilitate barplot vis and correct stacking.
bind_rows(old = .,
new = mutate(.,
plot_date = ceiling_date(x = plot_date,
unit = "month") - 1),
.id = "source") %>%
arrange(plot_date, source)
},
{
# Supply.
filter(supply[[input_huc8_selected]],
s_scenario %in% input_s_scene_selected) %>%
mutate(source = "old",
fill_color = NA,
plot_category = "supply") %>%
full_join(.,
as_tibble(input_d_scene_selected),
by = character()) %>%
select(source,
d_scenario = value,
s_scenario,
plot_date,
fill_color,
af_monthly,
af_daily,
cfs,
plot_category)
}
)
# })
### Render plot. ----
output$vsd_plot <- renderPlot({
# Validate.
validate(
need(input$d_scene_selected,
"No data to plot.\nPlease slelect at least one Demand Scenario.")
)
# Render.
ggplot(data = vsd_plot_data(),
aes(x = plot_date,
y = cfs)) +
# Demand.
geom_area(data = subset(vsd_plot_data(), plot_category == "demand"),
position = "stack",
aes(fill = fill_color)) +
# Supply.
geom_point(data = subset(vsd_plot_data(), plot_category == "supply"),
aes(color = s_scenario,
shape = s_scenario),
size = 7) +
geom_line(data = subset(vsd_plot_data(), plot_category == "supply"),
aes(color = s_scenario),
linetype = "dashed") +
# X axis format.
scale_x_date(date_labels = "%b %d",
date_minor_breaks = "1 month") +
# Y axis format.
scale_y_continuous(labels = comma) +
# Demand legend.
scale_fill_manual(name = "Demand Priority:",
values = wa_demand_pal,
labels = c(paste(input$priority_selected,
"& Junior Post-14 Demand"),
paste(as.numeric(input$priority_selected) -1,
"& Senior Post-14 Demand"),
"Statement Demand")) +
# Supply legend.
scale_shape_manual(name = "Supply Scenario:",
values = wa_supply_shapes) +
scale_color_manual(name = "Supply Scenario:",
values = wa_supply_pal) +
# Facet on demand scenario.
facet_wrap(~ d_scenario,
ncol = 1,
scales = "free_x") +
# Labels.
labs(y = "Cubic Feet per Second (cfs)") +
# Theme.
theme_minimal() +
theme(
plot.title = element_text(size = rel(2.0)),
strip.text.x = element_text(size = rel(2.0)),
axis.title = element_text(size = rel(1.2)),
axis.text = element_text(size = rel(1.2)),
legend.text = element_text(size = rel(1.2)),
legend.title = element_text(size = rel(1.2)),
legend.position = "bottom",
legend.box = "horizontal",
legend.direction = "vertical",
panel.spacing = unit(2, "lines"),
axis.title.x = element_blank()
)
}, height = function() plot_height())
## Demand By Water Right Type Plot (dbwrt). ----
### Build dataset. ----
# Demand by water right type dataset.
wrt_plot_data <- reactive({
demand[[input$huc8_selected]] %>%
filter(d_scenario %in% input$d_scene_selected,
wr_type %in% input$wrt_selected) %>%
group_by(d_scenario,
wr_type,
plot_month = month(plot_date, label = TRUE)) %>%
summarize(af_monthly = sum(af_monthly, na.rm = TRUE),
af_daily = sum(af_daily, na.rm = TRUE),
cfs = sum(cfs, na.rm = TRUE),
.groups = "drop")
})
### Render plot. ----
output$dbwrt_plot <- renderPlot({
# Validate.
validate(
need(input$d_scene_selected,
"No data to plot.\nPlease slelect at least one Demand Scenario."),
need(input$huc8_selected,
"No data to plot.\nPlease slelect a Watershed."),
need(nrow(wrt_plot_data()) > 0,
"No data for selected water right types.")
)
# Render.
ggplot(data = wrt_plot_data(),
aes(x = plot_month,
y = cfs,
fill = wr_type)) +
# Demand bars.
geom_col() +
# Y axis format.
scale_y_continuous(labels = comma) +
# Legend.
scale_fill_manual(name = "Water Right Type:",
values = plot_wrt_pal) +
# labels
labs(title = "Monthly Demand by Water Right Type",
y = "Cubic Feet per Second (cfs)") +
# Facet on demand scenario.
facet_wrap(~ d_scenario,
ncol = 1,
scales = "free_x") +
# Theme.
theme_minimal() +
theme(
plot.title = element_text(size = rel(2.0)),
strip.text.x = element_text(size = rel(2.0)),
axis.title = element_text(size = rel(1.2)),
axis.text = element_text(size = rel(1.2)),
legend.text = element_text(size = rel(1.2)),
legend.title = element_text(size = rel(1.2)),
legend.position = "bottom",
legend.box = "horizontal",
legend.direction = "vertical",
axis.title.x = element_blank())
}, height = function() plot_height()
)
## Demand by Priority plot (dbp). ----
### Build dataset. ----
# Demand by priority dataset.
dbp_plot_data <- reactive({
demand[[input$huc8_selected]] %>%
filter(d_scenario %in% input$d_scene_selected,
wr_type %in% input$wrt_selected) %>%
group_by(d_scenario,
priority,
plot_month = month(plot_date, label = TRUE)) %>%
summarize(af_monthly = sum(af_monthly, na.rm = TRUE),
af_daily = sum(af_daily, na.rm = TRUE),
cfs = sum(cfs, na.rm = TRUE),
.groups = "drop") %>%
mutate(priority = ordered(priority, levels = names(priority_pal)))
})
### Render plot. ----
output$dbp_plot <- renderPlot({
# Render.
ggplot(data = dbp_plot_data(),
aes(x = plot_month,
y = cfs,
fill = priority)) +
# Demand bars.
geom_col() +
# Y axis format.
scale_y_continuous(labels = comma) +
# Legend.
scale_fill_manual(name = "Priority:",
values = priority_pal) +
guides(fill = guide_legend(ncol = 3)) +
# labels
labs(title = "Monthly Demand by Priority",
y = "Cubic Feet per Second (cfs)") +
# Facet on demand scenario.
facet_wrap(~ d_scenario,
ncol = 1,
scales = "free_x") +
# Theme.
theme_minimal() +
theme(
plot.title = element_text(size = rel(2.0)),
strip.text.x = element_text(size = rel(2.0)),
axis.title = element_text(size = rel(1.2)),
axis.text = element_text(size = rel(1.2)),
legend.text = element_text(size = rel(1.2)),
legend.title = element_text(size = rel(1.2)),
axis.title.x = element_blank())
}, height = function() plot_height()
)
## Mini Map. ----
# Filter watershed polygon.
plot_poly <- reactive({
huc8_layer %>% filter(huc8_name %in% input$huc8_selected)
})
# Filter POD points.
pod_points <- reactive({
pods %>%
filter(huc8_name %in% input$huc8_selected) %>%
mutate(vsd_fill_color = if_else(priority == "Statement Demand",
"Statement Demand",
if_else(p_year >= input$priority_selected,
"Junior Post-14", "Post-14")))
})
# Filter gage stations.
station_points <- reactive({
station_locs %>%
filter(huc8_name %in% input$huc8_selected)
})
output$mini_map <- renderLeaflet({
# Validate.
validate(
need(nrow(pod_points()) > 0,
paste0("No Data Available.\n",
"Please select other Watershed(s) or Water Right Type(s)."))
)
# Render.
leaflet() %>%
# Add base map.
addProviderTiles(providers$CartoDB.Positron) %>%
addPolygons(group = "base",
data = plot_poly(),
weight = 3,
col = "blue",
fill = TRUE,
fillOpacity = 0)
})
### Update POD points and legends. ----
observe({
pod_points <- pod_points()
station_points <- station_points()
# Create POD label look-up.
pod_labs <- lapply(seq(nrow(pod_points)), function(i) {
paste0('Water Right ID: ', st_drop_geometry(pod_points[i, "wr_id"]), '<br>',
'Owner: ', st_drop_geometry(pod_points[i, "owner"]), '<br>',
'Water Right Type: ', st_drop_geometry(pod_points[i, "wr_type"]), '<br>',
'Priority: ' , st_drop_geometry(pod_points[i, "priority"]), '<br>',
'Status: ', st_drop_geometry(pod_points[i, "wr_status"])
)
})
station_labs <- lapply(seq(nrow(station_points)), function(i) {
paste0('<b>Station: </b>', station_points[i, "station_id"], '<br>',
'<b>Name: </b>', station_points[i, "station_name"], '<br>',
'<b>Data Provider: </b>', station_points[i, "data_provider"], '<br>',
'<b>', station_points[i, "link"], '</b>')
})
#### vsd plot points. ----
if( input$plot_tabs == "Supply-Demand Scenarios" ) {
leafletProxy(mapId = "mini_map") %>%
clearGroup(group = "content") %>%
clearControls() %>%
# POD points.
addCircleMarkers(group = "content",
data = pod_points,
radius = 4,
fillOpacity = 0.8,
stroke = FALSE,
weight = 2,
fillColor = ~map_demand_pal(vsd_fill_color),
label = lapply(pod_labs, HTML)) %>%
# Gage station markers.
addMarkers(group = "content",
data = station_points(),
lat = ~lat,
lng = ~lng,
icon = station_icon,
popup = lapply(station_labs, HTML)) %>%
# Color legend.
addLegend(position = "topright",
colors = wa_demand_pal[1:3],
labels = c(paste(input$priority_selected, "& Junior Post-14 Demand"),
paste(as.numeric(input$priority_selected) -1, "& Senior Post-14 Demand"),
"Statement Demand"),
title = "Demand Priority",
opacity = 1) %>%
# Shape legend.
addControl(html = html_legend,
position = "bottomleft")
} else
### dbwrt plot points. ----
if( input$plot_tabs == "Demand by Water Right Type" ) {
leafletProxy(mapId = "mini_map") %>%
clearGroup(group = "content") %>%
clearControls() %>%
addCircleMarkers(group = "content",
data = pod_points,
radius = 4,
fillOpacity = 0.8,
stroke = FALSE,
weight = 2,
fillColor = ~map_wrt_pal(wr_type),
label = lapply(pod_labs, HTML)
) %>%
addLegend(position = "topright",
pal = map_wrt_pal,
values = pod_points$wr_type,
title = "Water Right Type",
opacity = 1)
} else
### vbp plot points. ----
if( input$plot_tabs == "Demand by Priority" ) {
leafletProxy(mapId = "mini_map") %>%
clearGroup(group = "content") %>%
clearControls() %>%
addCircleMarkers(group = "content",
data = pod_points,
radius = 4,
fillOpacity = 0.9,
stroke = FALSE,
# weight = 2,
fillColor = ~map_priority_pal(priority),
label = lapply(pod_labs, HTML)
) %>%
addControl(html = "See plot legend for color categories.",
position = "topright")
}
})
## Tables. ----
## Demand data table.
output$demand_data_table <- renderDataTable({
demand[[input$huc8_selected]] %>%
filter(d_scenario %in% input$d_scene_selected,
wr_type %in% input$wrt_selected) %>%
mutate(plot_date = as.integer(month(plot_date))) %>%
rename(month = plot_date) %>%
select(-p_year)
},
filter = "top",
rownames = FALSE)
} # End Server
# APP --------------------------------------------------------------------------
shinyApp(ui = ui,
server = server)