Python numpy.atleast_1d函数方法的使用

numpy.atleast_1d

numpy.atleast_1d(*arys)     [source]

将输入转换为至少一维的数组。

标量输入被转换为一维数组，而高维输入被保留。

例子

1）标量输入

import numpy as np

a = 5
result = np.atleast_1d(a)
print(result)
# 输出: [5]

2）数组输入

import numpy as np

b = np.array([1, 2, 3])
result = np.atleast_1d(b)
print(result)
# 输出: [1 2 3]

3）多个输入

import numpy as np

c = 4
d = [5, 6]
e = np.array([[7, 8], [9, 10]])

result = np.atleast_1d(c, d, e)
for arr in result:
    print(arr)

# 输出:
# [4]
# [5 6]
# [[ 7  8]
#  [ 9 10]]

4）处理0维数组

import numpy as np

f = np.array(3)
result = np.atleast_1d(f)
print(result)
# 输出: [3]

5）使用示例

import numpy as np

# 将标量转换为至少一维的数组
result1 = np.atleast_1d(1.0)
print(result1)
# 输出: array([1.])

# 输入是多维数组，输出保持不变
x = np.arange(9.0).reshape(3, 3)
result2 = np.atleast_1d(x)
print(result2)
# 输出:
# array([[0., 1., 2.],
#        [3., 4., 5.],
#        [6., 7., 8.]])

# 检查输入与输出是否为同一对象
same_object = np.atleast_1d(x) is x
print(same_object)
# 输出: True

# 多个输入，包括标量和列表
result4 = np.atleast_1d(1, [3, 4])
for arr in result4:
    print(arr)
# 输出:
# array([1])
# array([3, 4])