NumPy numpy.concatenate

NumPy numpy.concatenate

在NumPy中，numpy.concatenate函数用于沿指定轴连接数组序列。它是数组连接的一种方法，可以将多个数组沿指定轴连接在一起，生成一个新的数组。

语法

numpy.concatenate((a1, a2, ...), axis=0, out=None)

参数说明：
– a1, a2, ...：要连接的数组序列
– axis：指定连接的轴，默认为0
– out：指定输出数组

示例代码

示例1：连接一维数组

import numpy as np

a = np.array([1, 2, 3])
b = np.array([4, 5, 6])

result = np.concatenate((a, b))
print(result)

Output:

示例2：连接二维数组

import numpy as np

a = np.array([[1, 2], [3, 4]])
b = np.array([[5, 6], [7, 8]])

result = np.concatenate((a, b))
print(result)

Output:

示例3：指定连接轴

import numpy as np

a = np.array([[1, 2], [3, 4]])
b = np.array([[5, 6], [7, 8]])

result = np.concatenate((a, b), axis=1)
print(result)

Output:

示例4：连接多个数组

import numpy as np

a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
c = np.array([7, 8, 9])

result = np.concatenate((a, b, c))
print(result)

Output:

示例5：连接多维数组

import numpy as np

a = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
b = np.array([[[9, 10], [11, 12]], [[13, 14], [15, 16]]])

result = np.concatenate((a, b))
print(result)

Output:

示例6：指定输出数组

import numpy as np

a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
out = np.zeros(6)

result = np.concatenate((a, b), out=out)
print(result)

Output:

示例7：连接空数组

import numpy as np

a = np.array([])
b = np.array([1, 2, 3])

result = np.concatenate((a, b))
print(result)

Output:

示例8：连接不同维度的数组

import numpy as np

a = np.array([[1, 2], [3, 4]])
b = np.array([5, 6])

result = np.concatenate((a, b))
print(result)

示例9：连接字符串数组

import numpy as np

a = np.array(['geek', 'docs'])
b = np.array(['com'])

result = np.concatenate((a, b))
print(result)

Output:

示例10：连接布尔数组

import numpy as np

a = np.array([True, False])
b = np.array([False, True])

result = np.concatenate((a, b))
print(result)

Output:

示例11：连接浮点数数组

import numpy as np

a = np.array([1.1, 2.2])
b = np.array([3.3, 4.4])

result = np.concatenate((a, b))
print(result)

Output:

示例12：连接复数数组

import numpy as np

a = np.array([1+2j, 3+4j])
b = np.array([5+6j, 7+8j])

result = np.concatenate((a, b))
print(result)

Output:

示例13：连接空数组序列

import numpy as np

a = np.array([])
b = np.array([])

result = np.concatenate((a, b))
print(result)

Output:

示例14：连接多个空数组

import numpy as np

a = np.array([])
b = np.array([])
c = np.array([])

result = np.concatenate((a, b, c))
print(result)

Output:

示例15：连接不同形状的数组

import numpy as np

a = np.array([[1, 2], [3, 4]])
b = np.array([5, 6, 7])

result = np.concatenate((a, b))
print(result)

示例16：连接不同类型的数组

import numpy as np

a = np.array([1, 2])
b = np.array(['geek', 'docs'])

result = np.concatenate((a, b))
print(result)

Output:

示例17：连接不同dtype的数组

import numpy as np

a = np.array([1, 2], dtype=np.int32)
b = np.array([3, 4], dtype=np.float64)

result = np.concatenate((a, b))
print(result)

Output:

示例18：连接不同形状和dtype的数组

import numpy as np

a = np.array([[1, 2], [3, 4]], dtype=np.int32)
b = np.array([5, 6, 7], dtype=np.float64)

result = np.concatenate((a, b))
print(result)

示例19：连接不同维度和dtype的数组

import numpy as np

a = np.array([[1, 2], [3, 4]], dtype=np.int32)
b = np.array([5, 6], dtype=np.float64)

result = np.concatenate((a, b))
print(result)

示例20：连接不同维度和dtype的数组

import numpy as np

a = np.array([1, 2], dtype=np.int32)
b = np.array([[3, 4], [5, 6]], dtype=np.float64)

result = np.concatenate((a, b))
print(result)

总结

通过numpy.concatenate函数，我们可以方便地连接多个数组，实现数组的拼接操作。在使用时需要注意数组的维度、形状和dtype，确保能够正确地连接数组序列。