"""Module Description

This code comes from scipy  < http://www.scipy.org/ >
It calculates two sample ks test

"""

import math


def ksprob(alam):
    """
Computes a Kolmolgorov-Smirnov t-test significance level.  Adapted from
Numerical Recipies.

Usage:   lksprob(alam)
"""
    fac = 2.0
    sum = 0.0
    termbf = 0.0
    a2 = -2.0*alam*alam
    for j in range(1,201):
        term = fac*math.exp(a2*j*j)
        sum = sum + term
        if math.fabs(term) <= (0.001*termbf) or math.fabs(term) < (1.0e-8*sum):
            return sum
        fac = -fac
        termbf = math.fabs(term)
    return 1.0             # Get here only if fails to converge; was 0.0!!


def ks_2samp (data1,data2):
    """
Computes the Kolmogorov-Smirnof statistic on 2 samples.  From
Numerical Recipies in C, page 493.

Usage:   ks_2samp(data1,data2)   data1&2 are lists of values for 2 conditions
Returns: KS D-value, associated p-value
"""
    j1 = 0
    j2 = 0
    fn1 = 0.0
    fn2 = 0.0
    n1 = len(data1)
    n2 = len(data2)
    en1 = n1
    en2 = n2
    d = 0.0
    #data1.sort()
    #data2.sort()
    while j1 < n1 and j2 < n2:
        d1=data1[j1]
        d2=data2[j2]
        if d1 <= d2:
            fn1 = (j1)/float(en1)
            j1 = j1 + 1
        if d2 <= d1:
            fn2 = (j2)/float(en2)
            j2 = j2 + 1
        dt = (fn2-fn1)
        if math.fabs(dt) > math.fabs(d):
            d = dt
    try:
        en = math.sqrt(en1*en2/float(en1+en2))
        prob = ksprob((en+0.12+0.11/en)*abs(d))
    except:
        prob = 1.0
    return d, prob