# NOT RUN {
lat = c(40.702147,40.718217,40.711614);
lon = c(-74.012318,-74.015794,-73.998284);
center = c(mean(lat), mean(lon));
zoom <- min(MaxZoom(range(lat), range(lon)));
#this overhead is taken care of implicitly by GetMap.bbox();
markers = paste0("&markers=color:blue|label:S|40.702147,-74.015794&markers=color:",
"green|label:G|40.711614,-74.012318&markers=color:red|color:red|",
"label:C|40.718217,-73.998284")
myMap <- GetMap(center=center, zoom=zoom,markers=markers);
#Note that in the presence of markers one often needs to add some extra padding to the
#latitude range to accomodate the extent of the top most marker
if (0){#takes too long to run for CRAN check
#add a path, i.e. polyline:
myMap <- GetMap(center=center, zoom=zoom,
path = paste0("&path=color:0x0000ff|weight:5|40.737102,-73.990318|",
"40.749825,-73.987963|40.752946,-73.987384|40.755823,-73.986397"));
#use implicit geo coding
BrooklynMap <- GetMap(center="Brooklyn", zoom=13)
PlotOnStaticMap(BrooklynMap)
#use implicit geo coding and display labels in Korean:
BrooklynMap <- GetMap(center="Brooklyn", zoom=13, hl="ko")
PlotOnStaticMap(BrooklynMap)
#no highways
ManHatMap <- GetMap(center="Lower Manhattan", zoom=14,
extraURL="&style=feature:road.highway|visibility:off",
destfile = "LowerManhattan.png")
PlotOnStaticMap(ManHatMap)
#reload the map without a new download:
ManHatMap <- GetMap(destfile = "LowerManhattan.png",NEWMAP=FALSE)
PlotOnStaticMap(ManHatMap)
#The example below defines a polygonal area within Manhattan, passed a series of
#intersections as locations:
#myMap <- GetMap(path = paste0("&path=color:0x00000000|weight:5|fillcolor:0xFFFF0033|",
# "8th+Avenue+%26+34th+St,New+York,NY|8th+Avenue+%26+42nd+St,New+York,NY|",
# "Park+Ave+%26+42nd+St,New+York,NY,NY|Park+Ave+%26+34th+St,New+York,NY,NY"),
# destfile = "MyTile3a.png");
#note that since the path string is just appended to the URL you can "abuse" the path
#argument to pass anything to the query, e.g. the style parameter:
#The following example displays a map of Brooklyn where local roads have been changed
#to bright green and the residential areas have been changed to black:
# myMap <- GetMap(center="Brooklyn", zoom=12, maptype = "roadmap",
#path = paste0("&style=feature:road.local|element:geometry|hue:0x00ff00|",
# "saturation:100&style=feature:landscape|element:geometry|lightness:-100"),
# sensor='false', destfile = "MyTile4.png", RETURNIMAGE = FALSE);
#In the last example we set RETURNIMAGE to FALSE which is a useful feature in general
#if png is not installed. In that cases, the images can still be fetched
#and saved but not read into R.
#In the following example we let the Static Maps API determine the correct center and
#zoom level implicitly, based on evaluation of the position of the markers.
#However, to be of use within R we do need to know the values for zoom and
#center explicitly, so it is better practice to compute them ourselves and
#pass them as arguments, in which case meta information on the map tile can be saved as well.
#myMap <- GetMap(markers = paste0("&markers=color:blue|label:S|40.702147,-74.015794&",
# "markers=color:green|label:G|40.711614,-74.012318&markers=color:red|",
# "color:red|label:C|40.718217,-73.998284"),
# destfile = "MyTile1.png", RETURNIMAGE = FALSE);
}
# }
Run the code above in your browser using DataLab