Here is some R code to make the world a bit less rough.
```
library(tidyverse)
library(rnaturalearth)
library(sf)
smoo = function(x,y,s)
predict(smooth.spline(y,spar=s),x)$y
d = ne_coastline(110) |>
st_coordinates() |>
as_tibble() |>
group_by(L1) |>
filter(n() > 4)
for (s in seq(0,1,.01)) {
p = d |> mutate(
i = 1:n(),
X = smoo(i,X,s),
Y = smoo(i,Y,s)) |>
ggplot() +
geom_path(aes(x=X,y=Y,group=L1)) +
theme_void()
show(p)
}
```
#rstats #spatial #maps #gis
spatial
#spatial #programming #commonLisp #leonardoCalculus
https://screwlisp.small-web.org/lispgames/LCKR-organisms-2/
New organisms-2 knowledgebase,starting out with local spatial walking at @mdhughes https://mdhughes.tech/ recommendation that fast access to local neighbors is fundamental.
I.e. I don't want to check every organism in the world to check who is standing next to me. Well, I put that in a knowledgebase in my organisms-2 #KRF here.
Seems to work, pulls in 8 connected and 24 connected neighbors rightly.