Python: Finding a numpy array in a list of numpy arrays

Question

I have a list of 50 numpy arrays called vectors:

[array([0.1, 0.8, 0.03, 1.5], dtype=float32), array([1.2, 0.3, 0.1], dtype=float32), .......]

I also have a smaller list (means) of 10 numpy arrays, all of which are from the bigger list above. I want to loop though each array in means and find its position in vectors.

So when I do this:

for c in means:
        print(vectors.index(c))

I get the error:

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

I've gone through various SO questions and I know why I'm getting this error, but I can't find a solution. Any help?

Thanks!

vectors is a list; vectors.index does v==c for all elements until this test is True. But with array elements v==c returns a boolean array, a True/False value for each element of v. That's the meaning of the ValueError - many boolean values in a context that expects just one. — hpaulj
– hpaulj, Commented Jul 18, 2017 at 17:18

Rakesh Adhikesavan · Accepted Answer · 2017-07-18 17:13:15Z

1

One possible solution is converting to a list.

vectors = np.array([[1, 2, 3], [4, 5, 6], [7,8,9], [10,11,12]], np.int32)

print vectors.tolist().index([1,2,3])

This will return index 0, because [1,2,3] can be found in index 0 of vectors

Th example above is a 2d Numpy array, however you seem to have a list of numpy arrays,

so I would convert it to a list of lists this way:

vectors = [arr.tolist() for arr in vectors]

Do the same for means:

means = [arr.tolist() for arr in means]

Now we are working with two lists of lists:

So your original 'for loop' will work:

for c in means:
    print(vectors.index(c))

edited Jul 18, 2017 at 17:13

answered Jul 18, 2017 at 17:00

Rakesh Adhikesavan

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2 Comments

user4889732 Over a year ago

Hmm, that makes sense. Do you know how I would convert vectors into that format?

Rakesh Adhikesavan Over a year ago

I edited the answer for the correct conversion, let me know if this solution works for you

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