The sampling() function is now smarter in handling cases where individuals are being scheduled for sampling at the effectively in the same generation as their population is being created. For instance, this can arise when these two events (given as time in years) "collapse" to a single generation in SLiM.
Sometimes (very rarely!) an individual was scheduled for sampling twice. This lead to the final tree sequence having one less individual then requested by the user via the sampling() call, leading to crashes when ts_load-ing the data.
Here is a small test case provided by @moicoll which first reported these issues. The R package can now correctly deal with those problems.
These issues are very complex, and even more so because slendr allows flexible time specification in forward and in backward direction which complicates the sanity checks quite a lot. However, I'll close the issue for now and wait for other bugs to pop up.
# fetch the latest slendr version with the bugfixes implemented
devtools::install_github("bodkan/slendr")
library(slendr)
set.seed(1234)
# this links to my Python setup -- you might do something else
reticulate::use_condaenv("retipy", required = TRUE)
reticulate::py_config()
map <- world(xrange = c(-15, 60), yrange = c(20, 65),crs = "EPSG:3035")
africa <- region("Africa", map, polygon = list(c(-18, 20), c(40, 20), c(30, 33),c(20, 32), c(10, 35), c(-8, 35)))
europe <- region("Europe", map, polygon = list(c(-8, 35), c(-5, 36), c(10, 38), c(20, 35), c(25, 35),c(33, 45), c(20, 58), c(-5, 60), c(-15, 50)))
anatolia <- region("Anatolia", map, polygon = list(c(28, 35), c(40, 35), c(42, 40), c(30, 43), c(27, 40), c(25, 38)))
afr <- population("AFR", parent = "ancestor", time = 52000, N = 3000, map = map, polygon = africa)
ooa <- population("OOA", parent = afr, time = 51000, N = 500, remove = 25000, center = c(33, 30), radius = 400e3) %>%
move(trajectory = list(c(40, 30), c(50, 30), c(60, 40)), start = 50000, end = 40000, snapshots = 20)
ehg <- population("EHG", parent = ooa, time = 28000, N = 1000, remove = 6000, polygon = list(c(26, 55), c(38, 53), c(48, 53), c(60, 53), c(60, 60), c(48, 63), c(38, 63), c(26, 60)))
eur <- population( name = "EUR", parent = ehg, time = 25000, N = 2000, polygon = europe)
ana <- population( name = "ANA", time = 28000, N = 3000, parent = ooa, remove = 4000, center = c(34, 38), radius = 500e3, polygon = anatolia) %>%
expand(by = 2500e3, start = 10000, end = 7000, polygon = join(europe, anatolia), snapshots = 20)
yam <- population( name = "YAM", time = 7000, N = 500, parent = ehg, remove = 2500, polygon = list(c(26, 50), c(38, 49), c(48, 50), c(48, 56), c(38, 59), c(26, 56))) %>%
move(trajectory = list(c(15, 50)), start = 5000, end = 3000, snapshots = 10)
gf <- list(
geneflow(from = ana, to = yam, rate = 0.5, start = 6500, end = 6400, overlap = FALSE),
geneflow(from = ana, to = eur, rate = 0.5, start = 8000, end = 6000),
geneflow(from = yam, to = eur, rate = 0.75, start = 4000, end = 3000))
model <- compile(
populations = list(afr, ooa, ehg, eur, ana, yam),
geneflow = gf,
generation_time = 30,
resolution = 10e3,
competition_dist = 130e3, mate_dist = 100e3,
dispersal_dist = 70e3,
dir = "~/Desktop/moi-model", overwrite = TRUE)
samples1 <- slendr::sampling(
model, times = runif(n = 1000, min = 2500, max = 52000),
list(afr, 1), list(ooa, 1), list(ehg, 1), list(eur, 1), list(ana, 1)
)
print(paste("Nº of samples : ", sum(samples1$n), sep = ""))
samples1 %>% summary() %>% print()
# this no longer crashes because the sampling events inconsistent with
# population split times are now handled by `sampling()` internally
slendr::slim(model,
sequence_length = 1,
recombination_rate = 0,
sampling = samples1,
verbose = TRUE,
save_locations = TRUE,
method = "batch",
seed = 1234,
save_sampling = TRUE)
# we no longer have the issue by some individuals gone missing, breaking
# the loading of tables of individuals
ts <- ts_load(model, recapitate = TRUE, simplify = TRUE,
Ne = 10000, recombination_rate = 0)
# verify we get the same number of samples from the tree sequence
ts_samples(ts) %>% nrow()
This fixes two issues reported in #69:
The
sampling()function is now smarter in handling cases where individuals are being scheduled for sampling at the effectively in the same generation as their population is being created. For instance, this can arise when these two events (given as time in years) "collapse" to a single generation in SLiM.Sometimes (very rarely!) an individual was scheduled for sampling twice. This lead to the final tree sequence having one less individual then requested by the user via the
sampling()call, leading to crashes whents_load-ing the data.Here is a small test case provided by @moicoll which first reported these issues. The R package can now correctly deal with those problems.
These issues are very complex, and even more so because slendr allows flexible time specification in forward and in backward direction which complicates the sanity checks quite a lot. However, I'll close the issue for now and wait for other bugs to pop up.