reshape（）用于改变数组形状
导入numpy
import numpy as np
定义一个数组
X = np.array([1, 2, 3, 4, 5, 6, 7, 8])
print(X)
输出
[1 2 3 4 5 6 7 8]
reshape 成 2行4列
a = X.reshape(2, 4)
print(a)
输出
[[1 2 3 4]
[5 6 7 8]]
reshape 成 1列 2列
b = X.reshape(-1, 1)
print(b)
c = X.reshape(-1, 2)
print(c)
输出
[[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]]
[[1 2]
[3 4]
[5 6]
[7 8]]
reshape 成 1行 2行
d = X.reshape(1, -1)
print(d)
e = X.reshape(2, -1)
print(e)
结果
[[1 2 3 4 5 6 7 8]]
[[1 2 3 4]
[5 6 7 8]]
reshape函数生成的新数组和原始数组公用一个内存，也就是说，不管是改变新数组还是原始数组的元素，另一个数组也会随之改变：
X = np.array([1, 2, 3, 4, 5, 6, 7, 8])
print(X)
[1 2 3 4 5 6 7 8]
a = X.reshape(2, 4)
print(a)
[[1 2 3 4]
[5 6 7 8]]
X[0] = 777
print(X)
[777 2 3 4 5 6 7 8]
print(a)
[[777 2 3 4]
[ 5 6 7 8]]
