spikesorting.py 文件源码

def __test_ks(self,x):
        x = x[~np.isnan(x)]
        n = x.size
        x.sort()
        yCDF = np.arange(1,n+1)/float(n)
        notdup = np.hstack([np.diff(x,1),[1]])
        notdup = notdup>0
        x_expcdf = x[notdup]
        y_expcdf = np.hstack([[0],yCDF[notdup]])
        zScores = (x_expcdf-np.mean(x))/np.std(x,ddof=1);
        mu = 0
        sigma = 1
        theocdf = 0.5*erfc(-(zScores-mu)/(np.sqrt(2)*sigma))

        delta1 = y_expcdf[:-1]-theocdf
        delta2 = y_expcdf[1:]-theocdf
        deltacdf = np.abs(np.hstack([delta1,delta2]))
        KSmax = deltacdf.max()
        return KSmax