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I am working with raxml-ng for the first time, running on a cluster, and my runs stop with the same error multiple times (12 tip tree, ~240 kbp per tip).
terminate called after throwing an instance of 'std::runtime_error'
what(): ERROR in p-inv optimization (LIBPLL-2310): BRENT: initialization failed!
Aborted
This occurred first at bootstrap tree #84 with the command raxml-ng --bootstrap --msa concat.phy --threads 2 --model partition.txt --prefix T2 -log verbose; I restarted it (exact same command, except different prefix) and it ran (reached convergence at 300 BS).
Testing the same data with slightly different command: raxml-ng --all --msa concat.phy --model partition.txt --prefix TEST --seed 2 --threads 8 --bs-metric fbp,tbe -log verbose, the issue occurred at bootstrap tree #351 on two consecutive runs, and then again when I changed switched --all to --bootstrap (this time with the same error but additional terminate called recursively lines). Also tried the --rate-scalers on fix I saw in an earlier closed issue but same result.
Is this a dataset quality issue? Any help is appreciated, thanks!
The text was updated successfully, but these errors were encountered:
I am working with raxml-ng for the first time, running on a cluster, and my runs stop with the same error multiple times (12 tip tree, ~240 kbp per tip).
This occurred first at bootstrap tree #84 with the command
raxml-ng --bootstrap --msa concat.phy --threads 2 --model partition.txt --prefix T2 -log verbose
; I restarted it (exact same command, except different prefix) and it ran (reached convergence at 300 BS).Testing the same data with slightly different command:
raxml-ng --all --msa concat.phy --model partition.txt --prefix TEST --seed 2 --threads 8 --bs-metric fbp,tbe -log verbose
, the issue occurred at bootstrap tree #351 on two consecutive runs, and then again when I changed switched--all
to--bootstrap
(this time with the same error but additionalterminate called recursively
lines). Also tried the--rate-scalers on
fix I saw in an earlier closed issue but same result.Is this a dataset quality issue? Any help is appreciated, thanks!
The text was updated successfully, but these errors were encountered: