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Trazar contornos en una cuadrícula irregular

Question

He recorrido páginas y páginas de curvas de nivel en R (incluidas muchas sugerencias sobre stackoverflow) sin éxito. Aquí están mis datos para contornear, incluida la adición de un mapa de Ruanda (los datos constan de 14 valores de longitud, latitud y lluvia como x, y y z):

Lon Lat Rain
28.92   -2.47   83.4
29.02   -2.68   144
29.25   -1.67   134.7
29.42   -2.07   174.9
29.55   -1.58   151.5
29.57   -2.48   224.1
29.6    -1.5    254.3
29.72   -2.18   173.9
30.03   -1.95   154.8
30.05   -1.6    152.2
30.13   -1.97   126.2
30.33   -1.3    98.5
30.45   -1.81   145.5
30.5    -2.15   151.3

Aquí está el código que probé de stackoverflow:

datr <- read.table("Apr0130precip.txt",header=TRUE,sep=",")
x <- datr$x
y <- datr$y
z <- datr$z

require(akima)

fld <- interp(x,y,z)

par(mar=c(5,5,1,1))
filled.contour(fld)

La interpolación falla. Se apreciará la ayuda.

Answer 1

Aquí hay algunas posibilidades diferentes usando los gráficos base R y ggplot . Se generan gráficas de contornos simples y gráficas en la parte superior de los mapas.

Interpolación

library(akima)
fld <- with(df, interp(x = Lon, y = Lat, z = Rain))

base R plot usando filled.contour

filled.contour(x = fld$x,
               y = fld$y,
               z = fld$z,
               color.palette =
                 colorRampPalette(c("white", "blue")),
               xlab = "Longitude",
               ylab = "Latitude",
               main = "Rwandan rainfall",
               key.title = title(main = "Rain (mm)", cex.main = 1))

ggplot básica de ggplot usando geom_tile y stat_contour

library(ggplot2)
library(reshape2)

# prepare data in long format
df <- melt(fld$z, na.rm = TRUE)
names(df) <- c("x", "y", "Rain")
df$Lon <- fld$x[df$x]
df$Lat <- fld$y[df$y]

ggplot(data = df, aes(x = Lon, y = Lat, z = Rain)) +
  geom_tile(aes(fill = Rain)) +
  stat_contour() +
  ggtitle("Rwandan rainfall") +
  xlab("Longitude") +
  ylab("Latitude") +
  scale_fill_continuous(name = "Rain (mm)",
                        low = "white", high = "blue") +
  theme(plot.title = element_text(size = 25, face = "bold"),
        legend.title = element_text(size = 15),
        axis.text = element_text(size = 15),
        axis.title.x = element_text(size = 20, vjust = -0.5),
        axis.title.y = element_text(size = 20, vjust = 0.2),
        legend.text = element_text(size = 10))

ggplot en un mapa de Google creado por ggmap

# grab a map. get_map creates a raster object
library(ggmap)
rwanda1 <- get_map(location = c(lon = 29.75, lat = -2),
                  zoom = 9,
                  maptype = "toner",
                  source = "stamen")
# alternative map
# rwanda2 <- get_map(location = c(lon = 29.75, lat = -2),
#                   zoom = 9,
#                   maptype = "terrain")

# plot the raster map
g1 <- ggmap(rwanda1)
g1

# plot map and rain data
# use coord_map with default mercator projection
g1 + 
  geom_tile(data = df, aes(x = Lon, y = Lat, z = Rain, fill = Rain), alpha = 0.8) +
  stat_contour(data = df, aes(x = Lon, y = Lat, z = Rain)) +
  ggtitle("Rwandan rainfall") +
  xlab("Longitude") +
  ylab("Latitude") +
  scale_fill_continuous(name = "Rain (mm)",
                        low = "white", high = "blue") +
  theme(plot.title = element_text(size = 25, face = "bold"),
        legend.title = element_text(size = 15),
        axis.text = element_text(size = 15),
        axis.title.x = element_text(size = 20, vjust = -0.5),
        axis.title.y = element_text(size = 20, vjust = 0.2),
        legend.text = element_text(size = 10)) +
  coord_map()

ggplot en un mapa creado a partir de shapefile

# Since I don''t have your map object, I do like this instead:
# get map data from
# http://biogeo.ucdavis.edu/data/diva/adm/RWA_adm.zip
# unzip files to folder named "rwanda"

# read shapefile with rgdal::readOGR
# just try the first out of three shapefiles, which seemed to work.
# ''dsn'' (data source name) is the folder where the shapefile is located
# ''layer'' is the name of the shapefile without the .shp extension.

library(rgdal)
rwa <- readOGR(dsn = "rwanda", layer = "RWA_adm0")
class(rwa)
# [1] "SpatialPolygonsDataFrame"

# convert SpatialPolygonsDataFrame object to data.frame
rwa2 <- fortify(rwa)
class(rwa2)
# [1] "data.frame"

# plot map and raindata  
ggplot() + 
  geom_polygon(data = rwa2, aes(x = long, y = lat, group = group),
               colour = "black", size = 0.5, fill = "white") +
  geom_tile(data = df, aes(x = Lon, y = Lat, z = Rain, fill = Rain), alpha = 0.8) +
  stat_contour(data = df, aes(x = Lon, y = Lat, z = Rain)) +
  ggtitle("Rwandan rainfall") +
  xlab("Longitude") +
  ylab("Latitude") +
  scale_fill_continuous(name = "Rain (mm)",
                        low = "white", high = "blue") +
  theme_bw() +
  theme(plot.title = element_text(size = 25, face = "bold"),
        legend.title = element_text(size = 15),
        axis.text = element_text(size = 15),
        axis.title.x = element_text(size = 20, vjust = -0.5),
        axis.title.y = element_text(size = 20, vjust = 0.2),
        legend.text = element_text(size = 10)) +
  coord_map()

La interpolación y el trazado de los datos de lluvia podrían, por supuesto, hacerse de una manera mucho más sofisticada, utilizando las herramientas útiles para datos espaciales en R. Considera mi respuesta un comienzo bastante rápido y fácil.