I am able to retrive a Direction map with the below Rscript, but I am unable to find function for making it Interactive.
longitude <- c( 77.605855,77.606800,77.596843,77.575793 )
latitude <- c(12.956580,12.966157, 12.964777,12.964473)
d <- as.data.frame(cbind(longitude,latitude))
map <- get_googlemap(center = c(lon = 77.605855, lat = 12.956580), zoom = 14,
size = c(500, 500), scale = 2,maptype = c("roadmap"),markers = d, path = d)
Below are the functionalities that I need to have in my map.
1. Interactive Zoom.
2. Auto Center so that all the markers are visible.
3. OnClick on the marker I would like to show title -say for Eg. "This is Your Car".
The documentation leaflet referred by #SymbolixAU at the comments helped me to arrive at the solution, below is my code to address my requirements mentioned in the question.
library(leaflet)
longitute <-c(77.605855,77.606800,77.596843,77.596747,77.596296,77.595738,77.594944 )
latitude <- c(12.956580,12.966157, 12.964777,12.964323,12.963570,12.962964, 12.962399)
d <- as.data.frame(cbind(longitute,latitude))
m <- leaflet() %>%
addTiles() %>% # Add default OpenStreetMap map tiles
addMarkers(lng=d$longitute, lat=d$latitude, popup="New Point",)
m<- addPolylines(m , lng = d$longitute, lat = d$latitude)
m
So this is my Output.
Related
I would like to be able to find the centre point between two markers on a map (example below). Is there a function in leaflet or in another package that allows this? Thank you in advance
coor_zone6 <- c(3.16680, 3.16176, 42.46667, 42.46997)
matrice_coord_zone6 <- matrix(coor_zone6, nrow=2, ncol = 2)
colnames(matrice_coord_zone6) <- c("long", "lat")
matrice_coord_zone6 <- data.frame(matrice_coord_zone6)
matrice_coord_zone6$name <- c("M_1","M_3")
leaflet(matrice_coord_zone6) %>%
addMouseCoordinates(epsg = NULL, proj4string = NULL, native.crs = FALSE) %>%
addProviderTiles("Esri.WorldImagery") %>%
addMarkers(lng = ~long, lat = ~lat) %>%
addPolylines(~long, ~lat, popup = ~name)
I have not found any leaflet function that can perform this calculation, but it is not difficult to find the intermediate point between both coordinates.
You must add both longitudes and divide them by 2, you will have to do the same with both latitudes.
In your case, if I have not misunderstood, your first coordinate is (3.16680, 42.46667) and your second coordinate is (3.16176, 42.46997) so the calculation would be as follows:
(3,16680 + 3,16176) / 2 = 3,16428
(42,46667 + 42,46997) / 2 = 42,46832
So the intermediate point would be the following: (3.16428, 42.46832)
I'm trying to add separate images to popups so that as you click on each location, an image specific to that place/popup appears. I've figured out how to get one image in, but it applies to all of the popups on the map instead of just one. I have been trying to use the package leafpop for this, but I can't really figure out how to make it work. Even if I just use one image, nothing appears on the map.
This is what my code looks like for it:
library(leaflet)
library(leafpop)
img = system.file("file/image_name.jpg", package = "jpg")
leaflet(map) %>%
addTiles() %>%
addCircleMarkers(label = map#data$name,
weight = 2,
color = "grey",
fillColor = "red",
fillOpacity = 0.7)%>%
addPopupImages(img, group = "map")
I know there's some bits in there that I'm not quite doing right. At this point, I just want to know if it's even possible to do this the way I'm envisioning. Any help is appreciated.
The images need to be in a vector of the same length as the points passed to leaflet. Here is a reproducible example you can copy paste that will get you started:
library(tidyverse)
library(sf)
library(leaflet)
library(leafpop)
pts <- tibble(x = runif(10, 175, 176),
y = runif(10, -38, -37)) %>%
st_as_sf(coords = c("x", "y"), crs = 4326)
img <- glue::glue("https://github.com/IQAndreas/sample-images/blob/gh-pages/100-100-color/{11:20}.jpg?raw=true")
pts$img <- img
leaflet() %>%
addTiles() %>%
addCircleMarkers(data = pts, group = "pts") %>%
addPopupImages(pts$img, group = "pts")
Figured it out, with the help of Rich Pauloo! This is the code I ended up using the get local image files. It's a little clunky, but it worked out for me:
data_name <- readOGR("data/map_file.kml")
data_name2 <- data.frame(data_name)
pts <- st_as_sf(data.frame(data_name2),
coords = c("coords.x1", "coords.x2"), crs = 4326)
img <- c("images/picture_name.jpg") ##did this for every image I wanted to use, in the order
##that matched up with the data points I wanted them associated with.
pts$img <- img
leaflet() %>%
addTiles() %>%
addCircleMarkers(data = pts, group = "pts") %>%
addPopupImages(pts$img, group = "pts", width = 300)
Sorry if my conventions for writing out code are not quite right for the website. I just wanted to keep things generic and not include any of my file names or anything.
Anyone created a leaflet map in Code Workbook using r-Leaflet? I have a functioning script that runs (also double checked in R) but how do I get it to visualise and then use in a Report etc. I have tried various tweaks on what may get it to run but no success - any ideas
leaflet_map <- function(map_data) {
library(leaflet)
data<-map_data
# first cut the continuous variable into bins
# these bins are now factors
data$Fill_rateLvl <- cut(data$Fill_rate,
c(0,.5,0.6,0.7,0.8,0.9,1), include.lowest = T,
labels = c('<50%', '50-60%', '60-70%', '70-80%', '80-90%','90-100%'))
# then assign a palette to this using colorFactor
# in this case it goes from red for the smaller values to yellow and green
# standard stoplight for bad, good, and best
FillCol <- colorFactor(palette = 'RdYlGn', data$Fill_rateLvl)
m<-leaflet() %>%
addTiles() %>%
addProviderTiles(providers$CartoDB.Positron)%>%
setView(lng = -0, lat = 50, zoom = 8) %>%
addCircleMarkers(data = data, lat = ~lat, lng = ~long,
color = ~FillCol(Fill_rateLvl), popup = data$Lead_employer,
radius = ~sqrt(Fill_rate*50), group = 'Fill rate') %>%
addLegend('bottomright', pal = FillCol, values = data$Fill_rateLvl,
title = 'Fill rate for next two weeks',
opacity = 1)
return(NULL)
}
I am not familiar with R in code workbook, but it sounds to me that you need to materialize your leaflet map as a dataset and then consume it in some sort of map compatible UI.
For example slate has a map widget which is backed by leaflets. You can find documentation and examples for it in https://www.palantir.com/docs/foundry/slate/widgets-map/
I have a map in leaflet in RShiny which have markers plotted and once I click a marker it adds circles to map showing all the related points to the marker.
What I want to do is to set zoom/view of the map in such a way that all the related circles are visible.
The number of circles varies as per markers i.e. some marker have 1 or 2 circles while some have more. Also, the location of circles varies across the USA so they can be placed in one city or another state.
Following is the code I am using to add circles to existing map
proxy <-leafletProxy("map",data = df)%>%
clearMarkers()%>%
addCircleMarkers(lat = ~lat,lng = ~lng,layerId = ~circle_pt,fillColor =
'green',opacity = 0.5,color = 'red',fillOpacity = 1)%>% clearPopups()%>%
addPopups(lat=~lat,lng=~lng,~as.character(circle_pt))
map=original map with markers
df=lat lng of circles with associated properties of selected marker in map
I want to set zoom level as shown in figure 2.
Kindly help me to identify how to calculate optimal zoom level in leaflet in shiny.
Regards,
If you want to set your initial view, you can use:
setView(lng, lat, zoom = zoom_level)
which is straight from the documentation.
Unless you provide more information, nobody will be able to understand the part where you're saying "in such a way that all the related circles are visible."
I'm not sure how you're app works and whats in the original call to leaflet. But maybe the following example might help you.
I store the click on the markers, filter the data according to the clicked layerId, get the min/max lat/long of the resulting data and then use fitBounds() to set the "zoom" level. (You could also use flyToBounds with the same arguments, which should make a smoother transition to the selected markers, but its still too buggy for me at least)
library(shiny)
library(shinyjs)
library(leaflet)
cords <- data.frame(
lng = runif(100, 14, 18),
lat = runif(100, 54, 58),
circle_pt = sample(1:20, size = 100, replace = T)
)
ui <- fluidPage(
leafletOutput("map", height = "700px")
)
server <- function(input, output, session) {
output$map <- renderLeaflet({
leaflet(data = cords) %>%
addTiles() %>%
addCircleMarkers(lat = ~lat,lng = ~lng, layerId = ~circle_pt, fillColor = 'green',
opacity = 0.5,color = 'red',fillOpacity = 1)
})
observeEvent(input$map_marker_click, {
clickid = input$map_marker_click$id
cordsNew = cords[cords$circle_pt==clickid,]
maxLong = max(cordsNew$lng)
maxLat = max(cordsNew$lat)
minLong = min(cordsNew$lng)
minLat = min(cordsNew$lat)
proxy <-leafletProxy("map", data = cordsNew)
proxy %>%
addCircleMarkers(lat = ~lat,lng = ~lng, layerId = ~circle_pt, fillColor = 'green',
opacity = 0.5,color = 'red',fillOpacity = 1) %>%
fitBounds(minLong,minLat,maxLong,maxLat) %>%
clearPopups() %>%
addPopups(lat=~lat,lng=~lng,~as.character(circle_pt))
})
}
shinyApp(ui = ui, server = server)
may be you can define an interval varint <- findInterval() and that pass to setView
varint <- findInterval()
setView(lng= lng,lat = lat, zoom = varint)
in findInterval, try to put some range of data with the distance between all points
EDIT:
try to calculate the distance between the farthest points that appear.
proxy <-leafletProxy("map",data = df) %>%
setView(
lng = click$lng,
lat=click$lat,
zoom=findInterval(someaverageofyourpoints, c(25,75,100,250,400,750,1000))
)
you can sum other values to findinterval, findinterval()+ 1 .. 2.. 4 ...5 for setting zoom level if findintervalset a tiny value
Quick question all.
I have some data in sql server which i have loaded into RStudio. I have made a barchart for the data and now i am using leaflet library with the use of latitude and longitude to plot a point on the map. I want to be able to use popup to show a barchart in it when the user clicks on the point.
BarChart code (maybe this is a problem because i am using googleVis library so not sure if i can use this in the popup. but again this is the most appropriate bar graph i can make and need- other suggestions could be helpful as i am not a professional in R libraries yet)
Switzerland <- sqlQuery(con, "sql query")
SwitzerlandChart <- gvisBarChart(Switzerland, options = list(height=200))
For the graph plot the code is:
m <- leaflet() %>%
addTiles() %>% # Add default OpenStreetMap map tiles
addCircles(lng=8.498868, lat=46.9221, popup=paste(plot(SwitzerlandChart)))
When i run this code it opens a webpage to view my barplot.
Then i run the following:
m #Prints the graph
This prints the graph with the point in the desired location but the popup shows me a webpage instead which also only i can open.
I want to be able to plot the bargraph inside the popup please.
Hope someone can help
Maybe a little late but here's a solution. The addPopups() function in library(leaflet) seems to be able to handle .svg files. Therefore, you could simply save your plot using svg() and then read it again using readLines(). Here's a reproducible example using library(mapview):
library(lattice)
library(mapview)
library(sp)
data(meuse)
coordinates(meuse) <- ~x+y
proj4string(meuse) <- CRS("+init=epsg:28992")
clr <- rep("grey", length(meuse))
fldr <- tempfile()
dir.create(fldr)
pop <- lapply(seq(length(meuse)), function(i) {
clr[i] <- "red"
p <- xyplot(meuse$cadmium ~ meuse$copper,
col = clr, pch = 20, alpha = 0.7)
svg(filename = paste(fldr, "test.svg", sep = "/"),
width = 250 * 0.01334, height = 250 * 0.01334)
print(p)
dev.off()
tst <- paste(readLines(paste(fldr, "test.svg", sep = "/")), collapse = "")
return(tst)
})
mapview(meuse, popup = pop, cex = "cadmium")
You will see that each popup is a scatterplot. As for a leaflet example, consider this:
content <- pop[[1]]
leaflet() %>% addTiles() %>%
addPopups(-122.327298, 47.597131, content,
options = popupOptions(closeButton = FALSE)
)
In case you need the plot to be interactive, you could have a look at library(gridSVG) which is able to produce interactive svg plots from e.g. lattice or ggplot2 plots.
UPDATE:
library(mapview) now has designated functionality for this:
popupGraph: to embed lattice, ggplot2 or interactive hatmlwidgets based plots.
popupImage: to embed local or remote (web) images
This is currently only available in the development version of mapview which can be installed with:
devtools::install_github("environmentalinformatics-marburg/mapview", ref = "develop"
This may be a little late too, but here is a full leaflet implementation. I first create the plot and then use the popupGraph function to add it in.
# make a plot of the two columns in the dataset
p <- xyplot(Home ~ Auto, data = Jun, col = "orange", pch = 20, cex = 2)
# make one for each data point
p <- mget(rep("p", length(Jun)))
# color code it so that the corresponding points are dark green
clr <- rep("orange", length(Jun))
p <- lapply(1:length(p), function(i) {
clr[i] <- "dark green"
update(p[[i]], col = clr)
})
# now make the leaflet map
m1 <- leaflet() %>%
addTiles() %>%
setView(lng = -72, lat = 41, zoom = 8) %>%
# add the markers for the Jun dataset
# use the popupGraph function
addCircleMarkers(data = Jun, lat = ~Lat, lng = ~Lon,
color = ~beatCol(BeatHomeLvl), popup = popupGraph(p),
radius = ~sqrt(BeatHome*50), group = 'Home - Jun') %>%
# layer control
addLayersControl(
overlayGroups = c('Home - Jun'
),
options = layersControlOptions(collapsed = F)
) %>%
# legend for compare to average
addLegend('bottomright', pal = beatCol, values = last$BeatTotalLvl,
title = 'Compare<br>Quote Count to<br>3Mos State Avg',
opacity = 1)
m1
Here is the output.