size=[popsize]*npops,
loci=[nloci],
lociPos=locus_position,
infoFields=['ind_id','fitness','migrate_to'])
pop.evolve(
initOps=[
sim.InitSex(),
sim.IdTagger(),
]+init_geno,
preOps=[
sim.Migrator(
rate=migr2DSteppingStoneRates(
migr, m=width, n=width, diagonal=False, circular=False),
mode=sim.BY_PROBABILITY),
sim.AcgtMutator(rate=[mut_rate], model='JC69'),
sim.PyMlSelector(GammaDistributedFitness(alpha, beta),
output='>>'+selloci_file),
],
matingScheme=sim.RandomMating(
ops=[
sim.IdTagger(),
sim.Recombinator(intensity=recomb_rate,
output=outfile,
infoFields="ind_id"),
] ),
postOps=[
sim.Stat(numOfSegSites=sim.ALL_AVAIL, step=50),
sim.PyEval(r"'Gen: %2d #seg sites: %d\n' % (gen, numOfSegSites)", step=50)
],
gen = generations
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
# This script is an example in the simuPOP user's guide. Please refer to
# the user's guide (http://simupop.sourceforge.net/manual) for a detailed
# description of this example.
#
import simuPOP as sim
pop = sim.Population(size=[2000], loci=1, alleleNames=['A', 'C', 'G', 'T'])
pop.evolve(
initOps=[sim.InitSex(),
sim.InitGenotype(freq=[.1, .1, .1, .7])],
matingScheme=sim.RandomMating(),
preOps=[
sim.AcgtMutator(rate=[1e-4, 0.5], model='K80'),
sim.Stat(alleleFreq=0, step=100),
sim.PyEval(
r"', '.join(['%.3f' % alleleFreq[0][x] for x in range(4)]) + '\n'",
step=100),
],
gen=500)
import simuOpt
simuOpt.setOptions(alleleType='lineage', quiet=True)
import simuPOP as sim
pop = sim.Population(size=10000, loci=[10] * 10, infoFields='ind_id')
# just to make sure IDs starts from 1
sim.IdTagger().reset(1)
pop.evolve(
initOps=[
sim.InitSex(),
sim.InitGenotype(freq=[0.2, 0.3, 0.4, 0.1]),
sim.IdTagger(),
sim.InitLineage(mode=sim.FROM_INFO),
],
# an extremely high mutation rate, just for demonstration
preOps=sim.AcgtMutator(rate=0.01, model='JC69'),
matingScheme=sim.RandomMating(ops=[
sim.IdTagger(),
sim.MendelianGenoTransmitter(),
]),
gen=10)
lin = pop.lineage()
# Number of alleles from each generation
for gen in range(10):
id_start = gen * 10000 + 1
id_end = (gen + 1) * 10000
num_mut = len([x for x in lin if x >= id_start and x <= id_end])
print('Gen %d: %5.2f %%' % (gen, num_mut / (2 * 10000 * 100.) * 100))
barrier=True)
pop.evolve(
initOps=[
sim.InitSex(),
] + init_geno,
preOps=[
sim.PyOperator(lambda pop: rc.increment_time() or True),
sim.Migrator(rate=migr_init,
mode=sim.BY_PROBABILITY,
begin=0,
end=args.switch_time),
sim.Migrator(rate=migr_change,
mode=sim.BY_PROBABILITY,
begin=args.switch_time),
sim.AcgtMutator(rate=[args.sel_mut_rate], model='JC69'),
sim.PyMlSelector(GammaDistributedFitness(args.gamma_alpha,
args.gamma_beta),
output=">>" + selloci_file),
],
matingScheme=sim.RandomMating(ops=[
id_tagger,
sim.Recombinator(intensity=args.recomb_rate,
output=rc.collect_recombs,
infoFields="ind_id"),
]),
postOps=[
sim.Stat(numOfSegSites=sim.ALL_AVAIL, step=50),
sim.PyEval(r"'Gen: %2d #seg sites: %d\n' % (gen, numOfSegSites)",
step=50),
sim.PyOperator(lambda pop: rc.simplify(pop.indInfo("ind_id")) or True,
if loc in self.coefMap:
s = self.coefMap[loc]
else:
s = random.gammavariate(self.alpha, self.beta)
self.coefMap[loc] = s
# print(str(loc)+":"+str(alleles)+"\n")
# needn't return fitness for alleles=(0,0) as simupop knows that's 1
if 0 in alleles:
return 1. - s
else:
return 1. - 2. * s
simu.evolve(initOps=[sim.InitSex(), meioser] + init_geno,
preOps=[
sim.AcgtMutator(rate=[0.0001], model='JC69'),
sim.PyMlSelector(GammaDistributedFitness(alpha, beta),
output='>>sel_loci.txt'),
sim.PyOperator(func=step_gen, param=(1, )),
],
matingScheme=reproduction,
postOps=[
sim.Stat(numOfSegSites=sim.ALL_AVAIL, step=50),
sim.PyEval(
r"'Gen: %2d #seg sites: %d\n' % (gen, numOfSegSites)",
step=50)
],
gen=generations)
pop = simu.population(0)