Learn R Programming

geojsonio (version 0.11.3)

topojson_json: Convert many input types with spatial data to TopoJSON as a JSON string

Description

Convert many input types with spatial data to TopoJSON as a JSON string

Usage

topojson_json(
  input,
  lat = NULL,
  lon = NULL,
  group = NULL,
  geometry = "point",
  type = "FeatureCollection",
  convert_wgs84 = FALSE,
  crs = NULL,
  object_name = "foo",
  quantization = 0,
  ...
)

Value

An object of class geo_json (and json)

Arguments

input

Input list, data.frame, spatial class, or sf class. Inputs can also be dplyr tbl_df class since it inherits from data.frame.

lat

(character) Latitude name. The default is NULL, and we attempt to guess.

lon

(character) Longitude name. The default is NULL, and we attempt to guess.

group

(character) A grouping variable to perform grouping for polygons - doesn't apply for points

geometry

(character) One of point (Default) or polygon.

type

(character) The type of collection. One of 'auto' (default for 'sf' objects), 'FeatureCollection' (default for everything else), or 'GeometryCollection'. "skip" skips the coercion with package geojson functions; skipping can save significant run time on larger geojson objects. Spatial objects can only accept "FeatureCollection" or "skip". "skip" is not available as an option for numeric, list, and data.frame classes

convert_wgs84

Should the input be converted to the standard CRS system for GeoJSON (https://tools.ietf.org/html/rfc7946) (geographic coordinate reference system, using the WGS84 datum, with longitude and latitude units of decimal degrees; EPSG: 4326). Default is FALSE though this may change in a future package version. This will only work for sf or Spatial objects with a CRS already defined. If one is not defined but you know what it is, you may define it in the crs argument below.

crs

The CRS of the input if it is not already defined. This can be an epsg code as a four or five digit integer or a valid proj4 string. This argument will be ignored if convert_wgs84 is FALSE or the object already has a CRS.

object_name

(character) name to give to the TopoJSON object created. Default: "foo"

quantization

(numeric) quantization parameter, use this to quantize geometry prior to computing topology. Typical values are powers of ten (1e4, 1e5, ...), default is 0 to not perform quantization. For more information about quantization, see this by Mike Bostock https://stackoverflow.com/questions/18900022/topojson-quantization-vs-simplification/18921214#18921214

...

args passed down to geojson_json(); see geojson_json() for help on what's supported here

Details

The type parameter is automatically converted to type="auto" if a sf, sfc, or sfg class is passed to input

Examples

Run this code
if (FALSE) {
# From a numeric vector of length 2, making a point type
topojson_json(c(-99.74, 32.45), pretty = TRUE)
topojson_json(c(-99.74, 32.45), type = "GeometryCollection")

## polygon type
### this requires numeric class input, so inputting a list will dispatch on the list method
poly <- c(
  c(-114.345703125, 39.436192999314095),
  c(-114.345703125, 43.45291889355468),
  c(-106.61132812499999, 43.45291889355468),
  c(-106.61132812499999, 39.436192999314095),
  c(-114.345703125, 39.436192999314095)
)
topojson_json(poly, geometry = "polygon", pretty = TRUE)

# Lists
## From a list of numeric vectors to a polygon
vecs <- list(c(100.0, 0.0), c(101.0, 0.0), c(101.0, 1.0), c(100.0, 1.0), c(100.0, 0.0))
topojson_json(vecs, geometry = "polygon", pretty = TRUE)

## from a named list
mylist <- list(
  list(latitude = 30, longitude = 120, marker = "red"),
  list(latitude = 30, longitude = 130, marker = "blue")
)
topojson_json(mylist, lat = "latitude", lon = "longitude")

# From a data.frame to points
topojson_json(us_cities[1:2, ], lat = "lat", lon = "long", pretty = TRUE)
topojson_json(us_cities[1:2, ],
  lat = "lat", lon = "long",
  type = "GeometryCollection", pretty = TRUE
)

# from data.frame to polygons
head(states)
## make list for input to e.g., rMaps
topojson_json(states[1:351, ], lat = "lat", lon = "long", geometry = "polygon", group = "group")

# from a geo_list
a <- geojson_list(us_cities[1:2, ], lat = "lat", lon = "long")
topojson_json(a)

# sp classes

## From SpatialPolygons class
library("sp")
poly1 <- Polygons(list(Polygon(cbind(
  c(-100, -90, -85, -100),
  c(40, 50, 45, 40)
))), "1")
poly2 <- Polygons(list(Polygon(cbind(
  c(-90, -80, -75, -90),
  c(30, 40, 35, 30)
))), "2")
sp_poly <- SpatialPolygons(list(poly1, poly2), 1:2)
topojson_json(sp_poly)
topojson_json(sp_poly, pretty = TRUE)

## data.frame to geojson
geojson_write(us_cities[1:2, ], lat = "lat", lon = "long") %>% as.json()

# From SpatialPoints class
x <- c(1, 2, 3, 4, 5)
y <- c(3, 2, 5, 1, 4)
s <- SpatialPoints(cbind(x, y))
topojson_json(s)

## From SpatialPointsDataFrame class
s <- SpatialPointsDataFrame(cbind(x, y), mtcars[1:5, ])
topojson_json(s)

## From SpatialLines class
library("sp")
c1 <- cbind(c(1, 2, 3), c(3, 2, 2))
c2 <- cbind(c1[, 1] + .05, c1[, 2] + .05)
c3 <- cbind(c(1, 2, 3), c(1, 1.5, 1))
L1 <- Line(c1)
L2 <- Line(c2)
L3 <- Line(c3)
Ls1 <- Lines(list(L1), ID = "a")
Ls2 <- Lines(list(L2, L3), ID = "b")
sl1 <- SpatialLines(list(Ls1))
sl12 <- SpatialLines(list(Ls1, Ls2))
topojson_json(sl1)
topojson_json(sl12)

## From SpatialLinesDataFrame class
dat <- data.frame(
  X = c("Blue", "Green"),
  Y = c("Train", "Plane"),
  Z = c("Road", "River"), row.names = c("a", "b")
)
sldf <- SpatialLinesDataFrame(sl12, dat)
topojson_json(sldf)
topojson_json(sldf, pretty = TRUE)

## From SpatialGrid
x <- GridTopology(c(0, 0), c(1, 1), c(5, 5))
y <- SpatialGrid(x)
topojson_json(y)

## From SpatialGridDataFrame
sgdim <- c(3, 4)
sg <- SpatialGrid(GridTopology(rep(0, 2), rep(10, 2), sgdim))
sgdf <- SpatialGridDataFrame(sg, data.frame(val = 1:12))
topojson_json(sgdf)

# From SpatialPixels
library("sp")
pixels <- suppressWarnings(SpatialPixels(SpatialPoints(us_cities[c("long", "lat")])))
summary(pixels)
topojson_json(pixels)

# From SpatialPixelsDataFrame
library("sp")
pixelsdf <- suppressWarnings(
  SpatialPixelsDataFrame(points = canada_cities[c("long", "lat")], data = canada_cities)
)
topojson_json(pixelsdf)

# From sf classes:
if (require(sf)) {
  ## sfg (a single simple features geometry)
  p1 <- rbind(c(0, 0), c(1, 0), c(3, 2), c(2, 4), c(1, 4), c(0, 0))
  poly <- rbind(c(1, 1), c(1, 2), c(2, 2), c(1, 1))
  poly_sfg <- st_polygon(list(p1))
  topojson_json(poly_sfg)

  ## sfc (a collection of geometries)
  p1 <- rbind(c(0, 0), c(1, 0), c(3, 2), c(2, 4), c(1, 4), c(0, 0))
  p2 <- rbind(c(5, 5), c(5, 6), c(4, 5), c(5, 5))
  poly_sfc <- st_sfc(st_polygon(list(p1)), st_polygon(list(p2)))
  topojson_json(poly_sfc)

  ## sf (collection of geometries with attributes)
  p1 <- rbind(c(0, 0), c(1, 0), c(3, 2), c(2, 4), c(1, 4), c(0, 0))
  p2 <- rbind(c(5, 5), c(5, 6), c(4, 5), c(5, 5))
  poly_sfc <- st_sfc(st_polygon(list(p1)), st_polygon(list(p2)))
  poly_sf <- st_sf(foo = c("a", "b"), bar = 1:2, poly_sfc)
  topojson_json(poly_sf)
}

## Pretty print a json string
topojson_json(c(-99.74, 32.45))
topojson_json(c(-99.74, 32.45)) %>% pretty()
}

Run the code above in your browser using DataLab