b0f34cdfd3ec8e41521cfd1b4a19c8dabb51fbbf,scipy/stats/_ksstats.py,,_kolmogn,#Any#Any#Any#,430

Before Change

    if t <= 1.0:  // Ruben-Gambino
        if t <= 0.5:
            return _select_and_pin_prob(0.0, 1.0, cdf=cdf)
        prd = 1.0
        mlt = 2 * t - 1
        for m in range(1, n + 1):
            prd = prd * m * mlt / n
        return _select_and_pin_prob(prd, 1.0 - prd, cdf=cdf)
    if t >= n - 1:  // Ruben-Gambino
        onemx = 1.0 - x
        prob = 2 * onemx**n

After Change

        if n <= 140:
            prob = np.prod(np.arange(1, n+1) * (1.0/n) * (2*t - 1))
        else:
            prob = np.exp(_log_nfactorial_div_n_pow_n(n) + n * np.log(2*t-1))
        return _select_and_clip_prob(prob, 1.0 - prob, cdf=cdf)
    if t >= n - 1:  // Ruben-Gambino
        prob = 2 * (1.0 - x)**n

Instances