def update_with_slatkin_test(simconfig, s):
"""
Takes an IndividualSampleClassified object, calculates the slatkin exact test for it,
and updates the existing pergenerationstats_postclassification object.
:param sample:
:return:
"""
class_counts = defaultdict(int)
for indiv in s.sample:
class_counts[indiv.classid] += 1
counts = class_counts.values()
(prob, theta) = montecarlo(simconfig.SLATKIN_MONTECARLO_REPLICATES, counts, len(counts))
# find the proper pergeneration object for this sample, and add the slatkin result
#
record = data.PerGenerationStatsPostclassification.m.find(dict(
classification_id=s.classification_id,
simulation_run_id=s.simulation_run_id,
simulation_time=s.simulation_time,
replication=s.replication,
sample_size=s.sample_size)).one()
data.updateFieldPerGenerationStatsPostclassification(record._id, "class_neutrality_slatkin", prob )
import slatkin counts = [8, 4, 3, 2, 2, 1, 1, 1, 1, 1, 1] (prob, theta) = slatkin.montecarlo(100000, counts, len(counts)) print "prob: %s theta: %s" % (prob, theta) counts = [30, 62, 97, 15, 53, 18, 55, 35, 57, 14866,160, 439, 18, 356, 165, 40, 41, 14, 27, 36, 39, 23, 120, 209] (prob, theta) = slatkin.montecarlo(100000, counts, len(counts)) print "prob: %s theta: %s" % (prob, theta)
def _slatkin_neutrality_for_classes(self, class_counts):
(prob, theta) = montecarlo(self.simconfig.SLATKIN_MONTECARLO_REPLICATES, class_counts, len(class_counts))
return prob
def slatkin_exact_test(count_list):
(prob, theta) = slatkin.montecarlo(100000, count_list, len(count_list))
#log.debug("slatkin prob: %s theta: %s", prob, theta)
return prob
#!/usr/bin/env python from slatkin import montecarlo counts = [8, 4, 3, 2, 2, 1, 1, 1, 1, 1, 1] numalleles = len(counts) (prob,theta) = montecarlo(100000, counts, len(counts)) print "prob: %s theta: %s" % (prob, theta) counts2 = [91, 56, 27, 9, 7, 3, 1] (prob, theta) = montecarlo(100000, counts2, len(counts2)) print "prob: %s theta: %s" % (prob, theta)
def _slatkin_neutrality_for_locus(self, trait_counts):
(prob,
theta) = montecarlo(self.simconfig.SLATKIN_MONTECARLO_REPLICATES,
trait_counts, len(trait_counts))
return prob
def _slatkin_neutrality_for_locus(self, trait_counts):
(prob, theta) = montecarlo(self.simconfig.SLATKIN_MONTECARLO_REPLICATES, trait_counts, len(trait_counts))
return prob