topojson_list: Convert many input types with spatial data to TopoJSON as a...

Description Usage Arguments Details Value Examples

View source: R/topojson_list.R

Description

Convert many input types with spatial data to TopoJSON as a list

Usage

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
topojson_list(
  input,
  lat = NULL,
  lon = NULL,
  group = NULL,
  geometry = "point",
  type = "FeatureCollection",
  convert_wgs84 = FALSE,
  crs = NULL,
  object_name = "foo",
  quantization = 0,
  ...
)

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 FeatureCollection (default) or GeometryCollection.

convert_wgs84

Should the input be converted to the standard CRS 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 through topojson_json() to geojson_json(); see geojson_json() for help on what's supported here

Details

Internally, we call topojson_json(), then use an internal function to convert that JSON output to a list

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

Value

a list with TopoJSON

Examples

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
## Not run: 
# From a numeric vector of length 2 to a point
vec <- c(-99.74,32.45)
topojson_list(vec)

# Lists
## From a list
mylist <- list(list(latitude=30, longitude=120, marker="red"),
               list(latitude=30, longitude=130, marker="blue"))
topojson_list(mylist)

## 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_list(vecs, geometry="polygon")

# from data.frame to points
(res <- topojson_list(us_cities[1:2,], lat='lat', lon='long'))
as.json(res)
## guess lat/long columns
topojson_list(us_cities[1:2,])
topojson_list(states[1:3,])
topojson_list(states[1:351,], geometry="polygon", group='group')
topojson_list(canada_cities[1:30,])

# from data.frame to polygons
head(states)
topojson_list(states[1:351, ], lat='lat', lon='long', geometry="polygon", group='group')

# 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_list(sp_poly)

# From SpatialPolygonsDataFrame class
sp_polydf <- as(sp_poly, "SpatialPolygonsDataFrame")
topojson_list(input = sp_polydf)

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

# From SpatialPointsDataFrame class
s <- SpatialPointsDataFrame(cbind(x,y), mtcars[1:5,])
topojson_list(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_list(sl1)
topojson_list(sl12)
as.json(topojson_list(sl12))
as.json(topojson_list(sl12), pretty=TRUE)

# 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_list(sldf)
as.json(topojson_list(sldf))
as.json(topojson_list(sldf), pretty=TRUE)

# From SpatialGrid
x <- GridTopology(c(0,0), c(1,1), c(5,5))
y <- SpatialGrid(x)
topojson_list(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_list(sgdf)

# From SpatialRings
library("rgeos")
r1 <- Ring(cbind(x=c(1,1,2,2,1), y=c(1,2,2,1,1)), ID="1")
r2 <- Ring(cbind(x=c(1,1,2,2,1), y=c(1,2,2,1,1)), ID="2")
r1r2 <- SpatialRings(list(r1, r2))
topojson_list(r1r2)

# From SpatialRingsDataFrame
dat <- data.frame(id = c(1,2), value = 3:4)
r1r2df <- SpatialRingsDataFrame(r1r2, data = dat)
topojson_list(r1r2df)

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

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

# From SpatialCollections
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")
poly <- SpatialPolygons(list(poly1, poly2), 1:2)
coordinates(us_cities) <- ~long+lat
dat <- SpatialCollections(points = us_cities, polygons = poly)
out <- topojson_list(dat)
out[[1]]
out[[2]]

## End(Not run)

# 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_list(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_list(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_list(poly_sf)
}

geojsonio documentation built on Jan. 15, 2021, 3:33 p.m.