#举个栗子如下:
x_vals = np.linspace(0, 10, 5)
#print(x_vals)
[ 0. 2.5 5. 7.5 10. ]
#转化数组为矩阵
x_vals_column = np.transpose(np.matrix(x_vals))
#print(x_vals_column)
([[ 0 ],
[ 2.5],
[ 5. ],
[ 7.5],
[10. ]])
#生成一个列矩阵如下:
ones_column = np.transpose(np.matrix(np.repeat(1, 5)))
#print(ones_column)
[[1]
[1]
[1]
[1]
[1]]
操作一下,函数功能很明确,将2个矩阵按列合并
A = np.column_stack((x_vals_column, ones_column))
#print(A)
[[ 0. 1. ]
[ 2.5 1. ]
[ 5. 1. ]
[ 7.5 1. ]
[10. 1. ]]
将2个矩阵按行合并
b = np.row_stack((x_vals_column, ones_column))
print(B)
[[ 0. ]
[ 2.5]
[ 5. ]
[ 7.5]
[10. ]
[ 1. ]
[ 1. ]
[ 1. ]
[ 1. ]
[ 1. ]]
版权声明:本文为weixin_38632246原创文章,遵循 CC 4.0 BY-SA 版权协议,转载请附上原文出处链接和本声明。