python 向量取整数_随机整数向量| 使用Python的线性代数

python 向量取整数

Prerequisite:

先决条件：

Defining a Vector using list
使用列表定义向量
Defining Vector using Numpy
使用Numpy定义向量

Random Integer Vector is a type of vector having a random integer value at each entry. Such types of vectors have a huge importance in Simulation and Machine Learning. Random Integer Vector can be defined by its Upper Limit, Lower Limit, and Length of the Vector (i.e. number of entries).

随机整数向量是在每个条目处具有随机整数值的向量类型。这种类型的向量在仿真和机器学习中具有极其重要的意义。 随机整数向量可以通过其上限，下限和向量的长度(即条目数)来定义。

In this article, we are going to create a random integer vector using inbuilt function numpy.random.randint().

在本文中，我们将使用内置函数numpy.random.randint()创建一个随机整数向量。

Syntax:

句法：

numpy.random.randint(low, up, length)
low - lower limit for choosing random integer value
up - upper limit for choosing random integer value
length - Length of the desired vector

Application:

应用：

Machine Learning
机器学习
Probability
可能性
Constraint Based Programming
基于约束的编程
Monte Carlo Simulation
蒙特卡罗模拟

随机整数向量的Python程序 (Python program for random integer vector)

# Linear Algebra Learning Sequence
# Random Integer Vector
import numpy as np
# Example 1, length 20
t1 = np.random.randint(0,30,20)
print('Example : ', t1)
# Example 2, length 20
t2 = np.random.randint(0,100,20)
print('\n\nExample : ', t2)
# Example 3, length 20
t3 = np.random.randint(0,300,20)
print('\n\nExample : ', t3)
# Example 4, length 30
t4 = np.random.randint(40,45,30)
print('\n\nExample : ', t4)

Output:

输出：

Example :  [ 6  2 14 27 23 12 15  7 23 18 17 16 13 12 19  7 27 21 28 23]
Example :  [65 41 80 12 12 91 10 77 31 66 29 98 11 40 41 52  7 18 80 26]
Example :  [126  14 190  21 259 268 168  88 252 270 243 112 237 2  
38 112 229 106 85  48]
Example :  [44 40 42 40 42 42 44 43 43 42 41 42 42 44 42 41 41 40 
40 42 43 40 42 40 44 44 40 43 40 40]