parallel_distance_old.py 文件源码

def _dense_distance_dual(lock, list1, list2, global_idx, shared_arr, dist_function):
    """Parallelize a general computation of a distance matrix.

    Parameters
    ----------
    lock : multiprocessing.synchronize.Lock
        Value returned from multiprocessing.Lock().
    input_list : list
        List of values to compare to input_list[idx] (from 'idx' on).
    shared_arr : array_like
        Numpy array created as a shared object. Iteratively updated with the
        result.
        Example:
            shared_array = np.frombuffer(mp.Array('d', n*n).get_obj()).reshape((n,n))

    Returns
    -------

    """
    list_len = len(list1)
    # PID = os.getpid()
    # print("PID {} takes index {}".format(PID, index_i))
    while global_idx.value < list_len:
        with lock:
            if not global_idx.value < list_len: return
            idx = global_idx.value
            global_idx.value += 1
            # if idx % 100 == 0: progressbar(idx, list_len)
        elem_1 = list1[idx]
        for idx_j in range(len(list2)):
            shared_arr[idx, idx_j] = dist_function(elem_1, list2[idx_j])