python将二维数组升为一维数组或二维降为一维方法实例_python

import numpy as np

mulArrays = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
print(list(np.concatenate(mulArrays.reshape((-1, 1), order="F"))))

Out[1]:
[1, 4, 7, 2, 5, 8, 3, 6, 9]

# coding = utf-8
import numpy as np
import random

# 把二维数组转换为一维数组
t1 = np.arange(12)
print(t1)
Out[0]: [ 0  1  2  3  4  5  6  7  8  9 10 11]
t2 = t1.reshape(3, 4)
print(t2)
 
t3 = t2.reshape(t2.shape[0] * t2.shape[1], )
print(t3)
 
t4 = t2.flatten()
print(t4)

import numpy as np
a = np.array([[1, 2], [3, 4], [9, 8]])
b = a.flatten()
print(b)

import numpy as np
a = np.array([[1, 2], [3, 4], [9, 8]])

# 使用库函数
from itertools import chain
a_a = list(chain.from_iterable(a))
print(a_a)

mulArrays = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
print(sum(mulArrays, []))  # [1, 2, 3, 4, 5, 6, 7, 8, 9]

import operator
from functools import reduce
mulArrays = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
print(reduce(operator.add, mulArrays))  # [1, 2, 3, 4, 5, 6, 7, 8, 9]

mulArrays = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
print([i for arr in mulArrays for i in arr])  # [1, 2, 3, 4, 5, 6, 7, 8, 9]

import numpy as np

x = np.arange(20)  # 生成数组
print(x)

result = x.reshape((4, 5))  # 将一维数组变成4行5列  原数组不会被修改或者覆盖
x.resize((2, 10))  # 覆盖原来的数据将新的结果给原来的数组
print(x)