由矩阵计算得出的numpy数组中的值取整

Question

I have some calculation involving two matrices both represented in numpy arrays. 我有一些涉及两个矩阵的计算，两个矩阵都表示为numpy数组。

After the calculation, i obtain a vector of floats represented in another numpy array. 在计算之后，我获得了另一个numpy数组中表示的floats向量。

I want to round up/down the values in this resultant vector, eg if the calculation gives: 我想向上/向下舍入此结果向量中的值，例如，如果计算给出：

array([1.33333, 2.56, 9.99999, 16.0])

then it should be rounded to: 那么它应该舍入到：

array([1, 3, 10, 16])

What is the fastest way to do this? 最快的方法是什么？

Answer 1

NumPy arrays have a round method: NumPy数组有一个圆形方法：

In [73]: x = np.array([1.33333, 2.56, 9.99999, 16.0])

In [74]: x.round()
Out[76]: array([  1.,   3.,  10.,  16.])