问题描述
我正在将代码从Matlab转换为Python.Matlab中的代码是:
I am converting a code from Matlab to Python. The code in Matlab is:
x = find(sEdgepoints > 0 & sNorm < lowT);
sEdgepoints(x)=0;
两个数组的大小相同，我基本上是在创建蒙版.
Both arrays are of same size, and I am basically creating a mask.
我阅读了这里 numpy中的nonzero()等同于find()，因此我使用了它.在Python中，我将dstc用于sEdgepoints，将dst用于sNorm.我也直接输入了lowT =60.所以，代码是
I read here that nonzero() in numpy is equivalent to find(), so I used that. In Python, I have dstc for sEdgepoints and dst for sNorm. I have also directly put in lowT = 60. So, the code was
x = np.nonzero(dstc > 0 and dst < 60)
dstc[x] = 0
但是，我收到以下错误消息:
But, I get following error:
Traceback (most recent call last):
File "C:\Python27\Sheet Counter\customsobel.py", line 32, in <module>
x = np.nonzero(dstc > 0 and dst < 60)
ValueError: The truth value of an array with more than one element is
ambiguous. Use a.any() or a.all()
我阅读了有关a.any()/a.all()的用法在这篇文章中，我不确定该如何运作.因此，我有两个问题:1.如果可以，使用哪个数组?2.如果我是正确的但它不起作用，如何转换代码?
I read about the usage of a.any()/a.all() in this post, and I am not sure how that will work. So, I have two questions:1. If it does, which array to use?2. If I am correct and it does not work, how to convert the code?
推荐答案
和进行布尔运算，而numpy希望您进行按位运算，因此必须使用& 即
and does boolean operation and numpy expects you to do bitwise operation, so you have to use & i.e
x = np.nonzero((dstc > 0) & ( dst < 60))
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