Python NumPy 追加与连接

声明:本页面是StackOverFlow热门问题的中英对照翻译,遵循CC BY-SA 4.0协议,如果您需要使用它,必须同样遵循CC BY-SA许可,注明原文地址和作者信息,同时你必须将它归于原作者(不是我):StackOverFlow 原文地址: http://stackoverflow.com/questions/35932101/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me): StackOverFlow

提示:将鼠标放在中文语句上可以显示对应的英文。显示中英文
时间:2020-08-19 17:09:57  来源:igfitidea点击:

NumPy append vs concatenate

pythonnumpy

提问by Jana

What is the difference between NumPy appendand concatenate?

NumPyappend和 有concatenate什么区别?

My observation is that concatenateis a bit faster and appendflattens the array if axis is not specified.

我的观察是,如果未指定轴,它concatenate会更快一些并且append会使数组变平。

In [52]: print a
[[1 2]
 [3 4]
 [5 6]
 [5 6]
 [1 2]
 [3 4]
 [5 6]
 [5 6]
 [1 2]
 [3 4]
 [5 6]
 [5 6]
 [5 6]]

In [53]: print b
[[1 2]
 [3 4]
 [5 6]
 [5 6]
 [1 2]
 [3 4]
 [5 6]
 [5 6]
 [5 6]]

In [54]: timeit -n 10000 -r 5 np.concatenate((a, b))
10000 loops, best of 5: 2.05 μs per loop

In [55]: timeit -n 10000 -r 5 np.append(a, b, axis = 0)
10000 loops, best of 5: 2.41 μs per loop

In [58]: np.concatenate((a, b))
Out[58]: 
array([[1, 2],
       [3, 4],
       [5, 6],
       [5, 6],
       [1, 2],
       [3, 4],
       [5, 6],
       [5, 6],
       [1, 2],
       [3, 4],
       [5, 6],
       [5, 6],
       [5, 6],
       [1, 2],
       [3, 4],
       [5, 6],
       [5, 6],
       [1, 2],
       [3, 4],
       [5, 6],
       [5, 6],
       [5, 6]])

In [59]: np.append(a, b, axis = 0)
Out[59]: 
array([[1, 2],
       [3, 4],
       [5, 6],
       [5, 6],
       [1, 2],
       [3, 4],
       [5, 6],
       [5, 6],
       [1, 2],
       [3, 4],
       [5, 6],
       [5, 6],
       [5, 6],
       [1, 2],
       [3, 4],
       [5, 6],
       [5, 6],
       [1, 2],
       [3, 4],
       [5, 6],
       [5, 6],
       [5, 6]])

In [60]: np.append(a, b)
Out[60]: 
array([1, 2, 3, 4, 5, 6, 5, 6, 1, 2, 3, 4, 5, 6, 5, 6, 1, 2, 3, 4, 5, 6, 5,
       6, 5, 6, 1, 2, 3, 4, 5, 6, 5, 6, 1, 2, 3, 4, 5, 6, 5, 6, 5, 6])

回答by hpaulj

np.appenduses np.concatenate:

np.append用途np.concatenate

def append(arr, values, axis=None):
    arr = asanyarray(arr)
    if axis is None:
        if arr.ndim != 1:
            arr = arr.ravel()
        values = ravel(values)
        axis = arr.ndim-1
    return concatenate((arr, values), axis=axis)