import numpy as np
a = np.arange(1, 13).reshape((3, 4))
print(a)
# 通过切片获取的sub_a是新获得的数组，即使赋值给新币那辆，但还是原来数组的视图
# 如果修改切片数组中元素的值，会影响原来的数组
sub_a = a[:2, :2]
print(sub_a)
sub_a[0] = 10
print(sub_a)
print(a)
# 可以使用numpy中的copy方法实现，
# 深拷贝
sub_aa = np.copy(a[:2, :2])
sub_aa = 100
print(sub_aa)
print(a)
- 修改数组维度
- 一维到多维
- 多维到一维 reshape ravel flatten
import numpy as np
a = np.arange(1, 25)
print(a)
# def reshape(self, shape, order='C'):
b = a.reshape(4, 6)
print(b)
# 修改为四块两行三列
c = a.reshape(4, 2, 3)
print(c)
# np.reshape(数组， 维度) 六行四列
d = np.reshape(a, (6, 4))
print(d)
# 两块三行四列
f = np.reshape(a, (2, 3, 4))
print(f)
# 多维数组转换为一维reshape ravel flatten
f = f.reshape(-1)
print(f)
f = f.ravel()
print(f)
f = f.flatten()
print(f)
- 拼接
- hstack vstack concatenate
- 一维 二维 三维的concatenate拼接操作
import numpy as np
a = np.array([[1, 2, 3], [4, 5, 6]])
b = np.array([[11, 12, 13], [14, 15, 16]])
print(a)
print(b)
# hstack进行水平拼接
r = np.hstack([a, b])
# r = nconp.hstack((a, b))
print(r)
# vstack进行竖直方向拼接
# r = np.vstack([a, b])
r = np.vstack((a, b))
print(r)
# concatenate链接沿现有轴的数组序列，默认垂直方向拼接axis
# r = np.vstack([a, b])
r = np.concatenate((a, b), axis=0)
print(r)
# 二维数组两个轴 axis=0 axis=1
r = np.concatenate((a, b), axis=1)
print(r)
# 三维数组两个轴 axis=0 axis=1 axis=2
a = np.arange(1, 13).reshape(1, 2, 6)
b = np.arange(101, 113).reshape(1, 2, 6)
r = np.concatenate((a, b), axis=0)
print(r)
r = np.concatenate((a, b), axis=1)
print(r)
r = np.concatenate((a, b), axis=2)
print(r)
