def METHOD_NAME(oldL,d,f=.25,m=-2,M=2):
    S=shape(oldL)
    dV = np.random.uniform(0.5*d,2*d,S)
    ii=np.random.normal(0,dV,S)
    ff = np.random.binomial(1,f,S)
    s= oldL + ii*ff    
    s[s>M]=M-(s[s>M]-M)
    s[s<m]=(m-s[s<m])+m
    return s