

In [1]:

    
import sys
sys.path.append('../src')
from popgen import *
%matplotlib inline
from ipywidgets import interact

Simple example - Biallelic



In [12]:

    
def drift_pop(num_msats, pop_size):
    m = SinglePop(gens=100)
    m.num_msats = num_msats
    m.pop_size = pop_size
    BasicView(m, [ExpHe()], ['mean'], min_y=[0], max_y=[1])
    m.run()
    
interact(drift_pop, num_msats=(2, 20, 1), pop_size=(30, 530, 50))



In [3]:

    
m = SinglePop(gens=100)
m.num_snps = 11
m.pop_size = 50
BasicView(m, [ExpHe()], ['mean'])
m.run()



In [4]:

    
m = SinglePop(gens=100)
m.num_snps = 5
m.snp_freq = [0.01, 0.05, 0.1, 0.5, 0.9]
m.pop_size = 50
BasicView(m, [ExpHe()], ['mean'])
m.run()

Simple example - Microsatellites



In [5]:

    
m = SinglePop(gens=100)
m.num_msats = 10
m.pop_size = 50
BasicView(m, [ExpHe(), NumAlleles()], ['mean'])
m.run()



In [6]:

    
m = SinglePop(gens=100)
m.num_msats = 10
m.pop_size = 50
m.num_msats = [2, 5, 10, 20]
BasicView(m, [ExpHe(), NumAlleles()], ['mean'])
m.run()

Compare size



In [7]:

    
m = SinglePop(gens=100)
m.num_msats = 10
m.pop_size = [50, 100, 200, 500, 1000]
BasicView(m, [ExpHe(), NumAlleles()], ['mean'])
m.run()

Compare drift



In [8]:

    
m = SinglePop(gens=200)
m.num_msats = 10
m.pop_size = [50, 50, 1000, 1000]
BasicView(m, [ExpHe(), NumAlleles()], ['mean'])
m.run()

Sample size



In [9]:

    
m = SinglePop(gens=50)
m.num_msats = 10
m.pop_size = 500
m.sample_size = [5, 10, 50, 100, 500]
BasicView(m, [ExpHe(), NumAlleles()], ['mean'])
m.run()



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