我有一个运行here的闪亮应用。它在小册子交互式地图上绘制了大约1.2万套公寓和房间,并根据用户输入的地址在地图上添加标记。这是code。对不起,如果没有详细记录。
有两个不同的数据框对象:一个用于公寓(df.apt
),另一个用于房间(df.quartos
)。
但是,由于应用加载了大量数据,因此速度有点慢。我想添加一个资源,只有在用户插入地址后才会绘制数据,并选择一个接近范围(比如,只显示距离输入地址10公里范围内的公寓)。我应该怎么做呢?
library(leaflet)
library(shiny)
library(ggmap)
source("post4-prepararshiny.R") #loads data and helper functions
ui = bootstrapPage(
div(class = "outer",
tags$head(
# Include our custom CSS
includeCSS("styles.css"),
includeScript("gomap.js")
),
tags$style(type = "text/css", "html, body {width:100%;height:100%}"),
leafletOutput("mymap", width = "100%", height = "100%"),
absolutePanel(id = "controls",# class = "panel panel-default",
fixed = TRUE,
draggable = TRUE,
top = 60, left = "auto", right = 20, bottom = "auto",
width = 330, height = "auto",
h2("Buscador OLX"),
textInput(inputId = "userlocation",
label = "Digite um endereço\n com pelo menos rua, número, bairro e cidade",
value = ""),
helpText("Exemplo: Rua Dias da Rocha, 85 - Copacabana, Rio de Janeiro - RJ"),
sliderInput(inputId = "distancia", label = "Escolha a distância em km:",
min = 0, max = 30, value = 15),
actionButton("go", "Buscar"),
helpText("Encontre imóveis para alugar perto de onde você quiser!"),
helpText("Cada ponto no mapa representa um imóvel para alugar.",
"A cor de um ponto é determinada pelo valor do aluguel.",
"Clique em um ponto para ter mais informações sobre o imóvel."),
helpText("Mais informações sobre este app em sillasgonzaga.github.io")
)
),
tags$div(id="cite",
'Dados extraídos do OLX em 12/11/2016.', ' Contato: sillasgonzaga.github.io'
)
)
server = function(input, output, session){
#browser()
output$mymap <- renderLeaflet({
map <- leaflet() %>%
addTiles() %>%
addProviderTiles("OpenStreetMap.BlackAndWhite") %>%
# coordenadas de um ponto em específico
addMarkers(lat = -22.911872, lng = -43.230184,
popup = "Estádio do Maracanã! <br> Apenas um exemplo!") %>%
# plotar apartamentos
addCircleMarkers(data = df.apt,
lng = ~lon, lat = ~lat,
color = ~vetorCoresApt(preco),
opacity = 1.5,
popup = textoPopup(df.apt, "apartamento"),
# Definir nome do grupo para ser usado na camada
group = "Apartamentos") %>%
# plotar quartos
addCircleMarkers(data = df.quartos,
lng = ~lon, lat = ~lat,
color = ~vetorCoresQuarto(preco),
opacity = 1.5,
popup = textoPopup(df.quartos, "quarto"),
group = "Quartos") %>%
addLayersControl(
overlayGroups = c("Apartamentos", "Quartos"),
options = layersControlOptions(collapsed = FALSE),
position = "bottomright"
) %>%
addLegend(pal = vetorCoresApt, values = df.apt$preco,
position = "bottomright")
map
})
observeEvent(input$go, {
v <- geocode(input$userlocation)
leafletProxy('mymap', session) %>% addMarkers(lng = v$lon,lat = v$lat)
})
}
我知道我可以使用函数geosphere::distm()
来计算数据矩阵和数据点之间的距离,如:
coord <- matrix(data = c(df.apt$lon, df.apt$lat), ncol = 2)
distance_vector <- distm(x = coord, y = c(lon = -43.183447, lat = -22.913912), fun = distVincentySphere)
# insert vector into data frame
df.apt$distance <- distance_vector
但是,如何以反应方式执行此操作,以便每次用户单击按钮并更改将用于指示范围的distance
时,我都可以更改sliderInput()
列接近?
P.S。:对于葡萄牙语的代码和评论感到抱歉。
@HubertL回复后,我能够找到解决方案。这是我在server.R
所做的:
distance_apt_reactive <- eventReactive(input$go, {
address_latlon <- geocode(input$userlocation)
dist <- distm(x = matrix(data = c(df.apt$lon, df.apt$lat), ncol = 2),
y = c(lon = address_latlon$lon, lat = address_latlon$lat),
fun = distVincentySphere)
dist <- dist/1000
})
apt_reactive <- reactive({df.apt[distance_reactive() < input$distancia,]})
output$mymap <- renderLeaflet({
map <- leaflet() %>%
addTiles() %>%
addProviderTiles("OpenStreetMap.BlackAndWhite") %>%
setView(lng = mean(df.apt$lon), lat = mean(df.apt$lat), zoom = 11) %>%
addLegend(pal = vetorCoresApt, values = df.apt$preco,
position = "bottomright",
layerId = "legend")
map
})
observe({
leafletProxy("mymap") %>%
clearMarkers() %>%
#addMarkers(lng = myadress()$lon, lat = myadress()$lat) %>%
addCircleMarkers(data = apt_reactive(),
lng = ~lon, lat = ~lat,
color = ~vetorCoresQuarto(preco),
opacity = 1.5,
# adicionar popup
popup = textoPopup(apt_reactive(), "apartamento"),
group = "Apartamentos")
})
答案 0 :(得分:1)
您可以根据与地址的距离添加reactive
来过滤data.frame
:
apt_reactive <- reactive({
address_latlon <- geocode(input$userlocation)
dist <- distm(x = matrix(data = c(df.apt$lon, df.apt$lat), ncol = 2),
y = c(lon = address_latlon$lon, lat = address_latlon$lat),
fun = distVincentySphere)
apt.df[dist < input$distancia,]
})
然后替换
addCircleMarkers(data = df.apt
通过
addCircleMarkers(data = apt_reactive()
(并对quartos_reactive
)
df.quartos
的相同流程