#!/usr/bin/env python
from math import exp
import logging
from scipy.stats import binom_test
debug = logging.debug
def binomial(n, p):
#calculate the expected maximum number of replicated reads at a single position
x = 1
pvalue = 0
while (binom_test(x,n,p) > 0.00001):
x = x + 1
if x >1:
x= x - 1
return x
def median(list):
'''Will return the median of the list of numbers '''
list.sort()
if len(list) % 2 == 0:
med = (list[int(len(list)/2)]+list[int(len(list)/2-1)])/2
else:
med = list[int((len(list)-1)/2)]
return med
def erfcc(x):
"""Complementary error function."""
z = abs(x)
t = 1. / (1. + 0.5*z)
r = t * exp(-z*z-1.26551223+t*(1.00002368+t*(.37409196+
t*(.09678418+t*(-.18628806+t*(.27886807+
t*(-1.13520398+t*(1.48851587+t*(-.82215223+
t*.17087277)))))))))
if (x >= 0.):
return r
else:
return 2. - r
def ncdf(x):
return 1. - 0.5*erfcc(x/(2**0.5))
