numpy.c_() and numpy.r_()的用法
np.r_是按列连接两个矩阵，就是把两矩阵上下相加，要求列数相等。
np.c_是按行连接两个矩阵，就是把两矩阵左右相加，要求行数相等。
Demo:
1.numpy.c_:
import numpy as np
x = np.arange(12).reshape(3,4)
print('x:',x, x.shape)
y = np.arange(10,22).reshape(3,4)
print('y:',y, y.shape)
z = np.c_[x,y]
print('z:',z, z.shape)
result:
x: [[ 0 1 2 3]
[ 4 5 6 7]
[ 8 9 10 11]] (3, 4)
y: [[10 11 12 13]
[14 15 16 17]
[18 19 20 21]] (3, 4)
z: [[ 0 1 2 3 10 11 12 13]
[ 4 5 6 7 14 15 16 17]
[ 8 9 10 11 18 19 20 21]] (3, 8)
2.numpy.r_用法:
import numpy as np
x = np.arange(12).reshape(3,4)
print('x:',x, x.shape)
y = np.arange(10,22).reshape(3,4)
print('y:',y, y.shape)
z = np.r_[x,y]
print('z:',z, z.shape)
result:
x: [[ 0 1 2 3]
[ 4 5 6 7]
[ 8 9 10 11]] (3, 4)
y: [[10 11 12 13]
[14 15 16 17]
[18 19 20 21]] (3, 4)
z: [[ 0 1 2 3]
[ 4 5 6 7]
[ 8 9 10 11]
[10 11 12 13]
[14 15 16 17]
[18 19 20 21]] (6, 4)
