How to generate multiple rows of repeated data in Python

Introduction

When doing scientific calculations or simulations, I believe many friends will encounter such problems. For example, we have a one-dimensional array as shown below:

array = [1, 2, 3, 4, 5]

At this point, we want to stack it repeatedly along the y-axis. For example, here we set it 3 times, so that we can get the following array.

[[1. 2. 3. 4. 5.]
 [1. 2. 3. 4. 5.]
 [1. 2. 3. 4. 5.]]

So what should we do?

General method

import numpy as np

array = np.array([1, 2, 3, 4, 5])   # 原始数组
repeat_time = 3  # 沿着y轴堆叠的次数
array_final = np.ones([repeat_time, len(array)])
for i in range(repeat_time):
    array_final[i, :] = array

print(array_final)
"""
result:
[[1. 2. 3. 4. 5.]
 [1. 2. 3. 4. 5.]
 [1. 2. 3. 4. 5.]]
"""

Use np.repeat function

Obviously, the above method is more troublesome. To simplify, we can use the np.repeat() function to implement this function.

import numpy as np

array = np.array([1, 2, 3, 4, 5])  # 原始数组
repeat_time = 3  # 沿着y轴堆叠的次数
array_final = np.repeat(array.reshape(1, -1), axis=0, repeats=repeat_time)
print(array_final)
"""
result:
[[1 2 3 4 5]
 [1 2 3 4 5]
 [1 2 3 4 5]]
"""

For detailed usage of the np.repeat() function, please refer to this article------np.repeat() function.

Use np.meshgrid function

Of course, for this situation, the easiest way is to use np.meshgrid() function to handle it.

import numpy as np

array = np.array([1, 2, 3, 4, 5])  # 原始数组
repeat_time = 3  # 沿着y轴堆叠的次数
array_1 = array.copy()[0:repeat_time]
array_final, array_final1 = np.meshgrid(array, array_1)
print(array_final)
"""
result:
[[1 2 3 4 5]
 [1 2 3 4 5]
 [1 2 3 4 5]]
"""

Of course, there are other methods, such as np.vstack() and np.concatenate() functions, which can achieve this operation. For these two functions, you can view the blog------np.concatenate() function and np.vstack() function.

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