Software

ts = tskit.load("example.trees")
afs = ts.allele_frequency_spectrum()

ts = msprime.sim_ancestry(
    samples=10, 
    recombination_rate=1e-4, 
    sequence_length=1e6
)
ts = msprime.sim_mutations(ts, rate=1e-6)

sample_data = tsinfer.load(
    "phased_sequence_data.samples"
)
ts = tsinfer.infer(sample_data)

dated_ts = tsdate.date(inferred_ts)

rts = pyslim.recapitate(
    ts, 
    ancestral_Ne=10000
)

let treeseq = tskit::TreeSequence::load(
  &treefile
).unwrap();
let mut tree_iterator = 
  treeseq.tree_iterator(
    tskit::TreeFlags::default()
  ).unwrap();
while let Some(tree) = 
  tree_iterator.next() {
    ...
  }

model = tstrait.trait_model(
  distribution="normal", mean=0, var=1
)
sim_result = tstrait.sim_phenotype(
    ts=ts, num_causal=100, model=model,
    h2=0.3, random_seed=1
)

initialize() {
    initializeTreeSeq();
    initializeMutationRate(1e-8);
    initializeMutationType(
        "m1", 0.5, "e", 0.001
    );
    initializeRecombinationRate(1e-8);
}
1 early() { sim.addSubpop("p1", 500); }
2000 late() { 
    sim.treeSeqOutput("out.trees");
}

pop = fwdpy11.DiploidPopulation(
  100, 1000.0
)
p = {
  "nregions": [],
  "rates": (0.0, 1e-3, None),
  "prune_selected": False,
  "demography": 
    fwdpy11.DiscreteDemography(),
  "simlen": 10 * pop.N + 200,
  ...
}
params = fwdpy11.ModelParams(**p)
fwdpy11.evolvets(rng, pop, params)

  species = stdpopsim.get_species(
      "HomSap"
  )
  model = species.get_demographic_model(
      "OutOfAfrica_3G09"
  )
  contig = species.get_contig("chr22")
  samples = {
      "YRI": 5,
      "CHB": 5,
      "CEU": 0
  }
  engine = stdpopsim.get_engine(
      "msprime"
  )
  ts = engine.simulate(
      model, contig, samples
  )