randtest.py 文件源码

def getfreq(linn, nu):
    val = 0
    for (x, y) in linn:
        if x == nu:
            val = y
    return val


    ''' The focus of this test is the number of times that a particular state occurs in a cumulative sum random walk. The purpose of this test is to detect deviations from the expected number of occurrences of various states in the random walk.'''
    ss = [int(el) for el in binin]
    sc = map(sumi, ss)
    cs = np.cumsum(sc)
    li = []
    for xs in sorted(set(cs)):
        if np.abs(xs) <= 9:
            li.append([xs, len(np.where(cs == xs)[0])])
    j = getfreq(li, 0) + 1
    pval = []
    for xs in xrange(-9, 9 + 1):
        if not xs == 0:
            # pval.append([xs, spc.erfc(np.abs(getfreq(li, xs) - j) / np.sqrt(2 * j * (4 * np.abs(xs) - 2)))])
            pval.append(spc.erfc(np.abs(getfreq(li, xs) - j) / np.sqrt(2 * j * (4 * np.abs(xs) - 2))))
    return pval


    ''' The focus of this test is the frequency of each and every overlapping m-bit pattern. The purpose of the test is to compare the frequency of overlapping blocks of two consecutive/adjacent lengths (m and m+1) against the expected result for a random sequence.'''
    n = len(binin)
    f1a = [(binin + binin[0:m - 1:])[xs:m + xs:] for xs in xrange(n)]
    f1 = [[xs, f1a.count(xs)] for xs in sorted(set(f1a))]
    f2a = [(binin + binin[0:m:])[xs:m + 1 + xs:] for xs in xrange(n)]
    f2 = [[xs, f2a.count(xs)] for xs in sorted(set(f2a))]
    c1 = [1.0 * f1[xs][1] / n for xs in xrange(len(f1))]
    c2 = [1.0 * f2[xs][1] / n for xs in xrange(len(f2))]
    phi1 = reduce(su, map(logo, c1))
    phi2 = reduce(su, map(logo, c2))
    apen = phi1 - phi2
    chisqr = 2.0 * n * (np.log(2) - apen)
    pval = spc.gammaincc(2 ** (m - 1), chisqr / 2.0)
    return pval