How Do I Select A Row From A Complex Numpy Array?

I have read 10-20 different question/answers and cannot find an example like this. I want to select rows out of a numpy array as follows: test = [ [ [0], np.zeros((250,250)), np.a

Solution 1:

Use list comprehension

just_1s = [el for el in nptest if el[0] == [1]]

But there is actually no need to work with nd.arrays, using the original list is ok

just_1s = [el for el in test if el[0] == [1]]

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If your point is why does one get [] when doing nptest[nptest[:, 0] == [1]] (note that I test [1] instead of 1), I do not know. Because according to me (and Sam Marinelli) it should have worked. We are wrong.

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But if one looks closer, it appears that

just_1s = nptest[ nptest[:,0].tolist().index([1]) ]

works fine but only if [1] is unique. Which is not the case of, e.g. [2].

Solution 2:

This is list produces a (5,3) array of objects:

In [47]: nptest=np.array(test)
In [49]: nptest.shape
Out[49]: (5, 3)
In [50]: nptest.dtype
Out[50]: dtype('O')
In [51]: nptest[:,0]
Out[51]: array([list([0]), list([0]), list([1]), list([2]), list([2])], dtype=object)

The first column is an array (1d) of lists. In my newer numpy version that's more explicit.

Doing an equality test on an array, or even list, of lists is not easy. After trying several things I found this:

In [52]: arow = nptest[:,0]

In [56]: [x[0]==1 for x in arow]
Out[56]: [False, False, True, False, False]
In [57]: mask = [x[0]==1 for x in arow]
In [58]: nptest[mask,:]
Out[58]: 
array([[list([1]),
        array([[ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       ..., 
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.]]),
        array([2, 2])]], dtype=object)

Or we could turn the array of lists into an array of numbers:

In [60]: np.array(arow.tolist())
Out[60]: 
array([[0],
       [0],
       [1],
       [2],
       [2]])
In [61]: np.array(arow.tolist())==1
Out[61]: 
array([[False],
       [False],
       [ True],
       [False],
       [False]], dtype=bool)

Or test for [1] instead of 1. Lists match lists, not their contents.

In [64]: [x==[1] for x in arow]
Out[64]: [False, False, True, False, False]

Solution 3:

I believe the issue is with the expression nptest[:, 0] == 1. You've already shown that nptest[:, 0] returns [[0], [0], [1], [2], [2]] as expected. You can see that none of these values is equal to 1, so nptest[nptest[:, 0] == 1] will be empty. Try nptest[nptest[:, 0] == [1]] instead.