Python库——numpy.split

under 机器学习  tag     Published on February 14th , 2020 at 06:06 am

函数原型

split(ary, indices_or_sections, axis=0)

参数说明

ary 需要切分的数组
indices_or_sections 元组:沿该数代表的位置切分; 数组,为沿轴切分的位置(左开右闭);常数:该数平均切分
axis 沿着哪个维度切,默认=0,为横向切分;为1时,纵向切分

import numpy as np

data = np.arange(9.0)
data1 = np.split(data, 3)
data2 = np.split(data, [3, 5, 6, 10])
print(data1)
print(data2)
[array([ 0.,  1.,  2.]), array([ 3.,  4.,  5.]), array([ 6.,  7.,  8.])]
[array([ 0.,  1.,  2.]),
 array([ 3.,  4.]),
 array([ 5.]),
 array([ 6.,  7.]),
 array([], dtype=float64)]

(3,)的用法

data = np.arange(8.0)
data = np.split(data, (3,))
print(data)
[array([0., 1., 2.]), array([3., 4., 5., 6., 7.])]

用法测试

#!/usr/bin/env python
# _*_ coding: utf-8 _*_
 
import numpy as np
 
# Test 1
A = np.arange(12).reshape(3, 4)
print A
 
# 纵向分割, 分成两部分, 按列分割
print np.split(A, 2, axis = 1)
# 横向分割, 分成三部分, 按行分割
print np.split(A, 3, axis = 0)
 
# Test 1 result
[[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]]
[array([[0, 1],
       [4, 5],
       [8, 9]]), array([[ 2,  3],
       [ 6,  7],
       [10, 11]])]
[array([[0, 1, 2, 3]]), array([[4, 5, 6, 7]]), array([[ 8,  9, 10, 11]])]
 
# Test 2
# 不均等分割
print np.array_split(A, 3, axis = 1)
 
# Test 2 result
[array([[0, 1],
       [4, 5],
       [8, 9]]), array([[ 2],
       [ 6],
       [10]]), array([[ 3],
       [ 7],
       [11]])]
In [5]:
 
# Test 3
# 垂直方向分割
print np.vsplit(A, 3)
# 水平方向分割
print np.hsplit(A, 2)
 
# Test 3 result
[array([[0, 1, 2, 3]]), array([[4, 5, 6, 7]]), array([[ 8,  9, 10, 11]])]
[array([[0, 1],
       [4, 5],
       [8, 9]]), array([[ 2,  3],
       [ 6,  7],
       [10, 11]])]

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  文章最后更新时间为:February 13th , 2020 at 10:06 pm