eval.py 文件源码

def bootstrap(diffs, B):
        m = multiprocessing.Manager()
        q = m.Queue()
        pool = multiprocessing.Pool()
        rs = pool.map_async(bs_one, [(diffs, q) for _ in xrange(B)])
        pool.close() # No more work
        while (True):
            if (rs.ready()): break

            log.info('Waiting for %d bootstrap samples to finish...' % (B - q.qsize()))
            time.sleep(1)

        assert(q.qsize() == B), "qsize=%d, B=%d" % (q.qsize(), B)
        count = [0] * len(diffs[0])
        for i in xrange(B):
            qres = q.get()
            for j in xrange(len(diffs[0])):
                count[j] += qres[j]
        assert(q.empty())

        return [(c + 1.0) / (B + 1.0) for c in count]    # smoothed p-value