Ejemplo n.º 1
0
 def test_simple_cases(self):
     for n in range(2, 10):
         st = msprime.simulate_tree(n)
         self.verify_sparse_tree(st)
     for n in [11, 13, 19, 101]:
         st = msprime.simulate_tree(n)
         self.verify_sparse_tree(st)
Ejemplo n.º 2
0
 def test_models(self):
     # Exponential growth of 0 and constant model should be identical.
     m1 = msprime.ExponentialPopulationModel(alpha=0.0, start_time=0.0)
     m2 = msprime.ConstantPopulationModel(size=1.0, start_time=0.0)
     for n in [2, 10, 100]:
         # TODO this _should_ be the same as running with no population
         # models, but it's not. need to investigate.
         st1 = msprime.simulate_tree(
             n, random_seed=1, population_models=[m1])
         st2 = msprime.simulate_tree(
             n, random_seed=1, population_models=[m2])
         self.assertEqual(st1, st2)
Ejemplo n.º 3
0
def single_locus_example():
    tree = msprime.simulate_tree(5, random_seed=1)
    print(tree)
    tree.draw("_static/simple-tree.svg", show_times=True)
    u = 1
    while u != 0:
        print("node {}: time = {}".format(u, tree.get_time(u)))
        u = tree.get_parent(u)

    print(tree.get_branch_length(7))
Ejemplo n.º 4
0
def draw_tree():
    tree = msprime.simulate_tree(5, random_seed=1, scaled_mutation_rate=0.1)
    print(list(tree.mutations()))
    print(list(tree.nodes()))
    tree.draw("example.svg")
Ejemplo n.º 5
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 def get_tree(self):
     return msprime.simulate_tree(
         10, random_seed=1, scaled_mutation_rate=1)