Comments (2)
origin_position
and dest_position
are the same sfc_column (st_as_sf.sf(x) == x
https://github.com/r-spatial/sf/blob/master/R/sf.R#L69).
Try this:
library(nycflights13)
library(dplyr)
library(rdeck)
library(sf)
library(viridis)
flights_lon_lat <-
flights %>%
left_join(airports,
by = c("origin" = "faa"),
) %>%
left_join(airports,
by = c("dest" = "faa"),
suffix = c("_origin", "_dest")
) %>%
mutate(
origin_position = sfc_point(lon_origin, lat_origin),
dest_position = sfc_point(lon_dest, lat_dest)
)
rdeck() %>%
add_arc_layer(
data = flights_lon_lat,
get_source_position = origin_position,
get_target_position = dest_position,
get_source_color = scale_color_linear(
distance,
viridis(12)
),
get_target_color = scale_color_linear(
distance,
viridis(12)
),
get_height = scale_linear(
distance
),
get_width = 10,
great_circle = TRUE,
blending_mode = "additive"
)
from rdeck.
That data also has many records per arc, hence the terrible performance (and pure white arcs with additive blending). This looks pretty good:
library(nycflights13)
library(dplyr)
library(rdeck)
library(sf)
library(viridis)
flights_lon_lat <-
flights %>%
left_join(airports,
by = c("origin" = "faa"),
) %>%
left_join(airports,
by = c("dest" = "faa"),
suffix = c("_origin", "_dest")
) %>%
group_by(
lon_origin,
lat_origin,
lon_dest,
lat_dest,
distance
) %>%
summarise(count = n(), .groups = "drop") %>%
mutate(
origin_position = sfc_point(lon_origin, lat_origin),
dest_position = sfc_point(lon_dest, lat_dest)
)
rdeck() %>%
add_arc_layer(
data = flights_lon_lat,
get_source_position = origin_position,
get_target_position = dest_position,
get_source_color = scale_color_linear(
distance,
viridis(12)
),
get_target_color = scale_color_linear(
distance,
viridis(12)
),
get_height = scale_linear(
distance
),
get_width = 1,
great_circle = TRUE,
blending_mode = "additive"
)
from rdeck.
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from rdeck.