[英]Calculating the 3-norm of a matrix in Python
I'm trying to calculate the 3-norm of the matrix y here but I keep getting an error that says我试图在这里计算矩阵 y 的 3 范数,但我一直收到一条错误消息
ValueError: Invalid norm order for matrices.
This is the code that I tried这是我试过的代码
y = np.random.rand(5,1)
print(y)
p = 3
ly = npla.norm(y,p)
print('ly =',ly,)
I'm not sure how to go about calculating the 3-norm here so any help would be appreciated我不确定如何 go 在这里计算 3 范数所以任何帮助将不胜感激
You need to specify axis=0
in the norm
method since you have a 5x1 matrix and you want to calculate the norm over column 1.您需要在norm
方法中指定axis=0
因为您有一个 5x1 矩阵并且您想要计算第 1 列的范数。
If you would have just a python list, it would be okay without.如果你只有一个 python 列表,没有它也没关系。
Cheers!干杯!
As seen in the norm documentation the standard inputs does not include order=3.正如标准文档中所见,标准输入不包括 order=3。
As stated in the post previous you need to add an axis parameter where x=0.如上一篇文章所述,您需要在 x=0 处添加一个轴参数。
try:尝试:
np.linalg.norm(yourMatrix,3,axis=0)
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