我想使用np.linalg.norm来计算行向量的范数,然后使用这个范数来规范化行向量,就像我在代码中写的那样。我给向量x一个初始值,但在运行此代码后,我总是得到:
AxisError: axis 1 is out of bounds for array of dimension 1
所以我很困惑,不知道是什么问题。这是我的密码:
import numpy as np
def normalizeRows(x):
x_norm = np.linalg.norm(x, axis=1, keepdims=True)
x_normalized = x / x_norm
return x_normalized
x = np.array([1, 2, 3])
print(normalizeRows(x))
下面是错误:
---------------------------------------------------------------------------
AxisError Traceback (most recent call last)
<ipython-input-16-155a4cdd9bf8> in <module>
10
11 x = np.array([1, 2, 3])
---> 12 print(normalizeRows(x))
13
14
<ipython-input-16-155a4cdd9bf8> in normalizeRows(x)
4
5 def normalizeRows(x):
----> 6 x_norm = np.linalg.norm(x, axis=1, keepdims=True)
7 x_normalized = x / x_norm
8
<__array_function__ internals> in norm(*args, **kwargs)
d:\programs\python39\lib\site-packages\numpy\linalg\linalg.py in norm(x, ord, axis, keepdims)
2558 # special case for speedup
2559 s = (x.conj() * x).real
-> 2560 return sqrt(add.reduce(s, axis=axis, keepdims=keepdims))
2561 # None of the str-type keywords for ord ('fro', 'nuc')
2562 # are valid for vectors
AxisError: axis 1 is out of bounds for array of dimension 1
有人能告诉我为什么这是错误的,以及如何修复它吗?谢谢
这会导致轴错误,因为您的数组是1d数组,并且因为:
“在多维NumPy数组中,轴1是第二个轴。当我们谈论二维和多维数组时,轴1是水平穿过列的轴”,引自link
你所要做的就是把你的轴改成0
相关问题 更多 >
编程相关推荐