Delete columns from numpy array depending on a condition on a single cell

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一个人的身影
一个人的身影 2020-12-10 05:43

Above all, sorry for my bad English.

I have this array t:

array([[ 0,  1,  2,  0,  4,  5,  6,  7,  8,  9],
       [ 0, 11,  0, 13,  0,          


        
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  • 2020-12-10 05:55

    I got this working like this:

    data = array([[ 0, 1, 2, 0, 4, 5, 6, 7, 8, 9], [ 0, 11, 0, 13, 0, 15, 0, 17, 18, 0]])
    res = array([(a, b,) for a, b in zip(data[0], data[1]) if b]).transpose()
    

    got the result

    In [23]: res
    Out[23]: 
    array([[ 1,  0,  5,  7,  8],
           [11, 13, 15, 17, 18]])
    
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  • 2020-12-10 06:16

    Similar to Juh_, but more expressive, and avoiding some minor unnecessary performance overhead. A grand total of 12 highly pythonic, explicit and unambigious characters. This is really numpy 101; if you are still trying to wrap your head around this, you would do yourself a favor by reading a numpy primer.

    import numpy as np
    a = np.array([[ 0,  1,  2,  0,  4,  5,  6,  7,  8,  9],
                  [ 0, 11,  0, 13,  0, 15,  0, 17, 18,  0]])
    print a[:,a[1]!=0]
    
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  • 2020-12-10 06:17

    With numpy.delete:

    a = np.array([[0, 1, 2, 0, 4, 5, 6, 7, 8, 9], [0, 11, 0, 13, 0, 15, 0, 17, 18, 0]])
    
    indices = [i for (i,v) in enumerate(a[1]) if v==0]
    # [0, 2, 4, 6, 9]
    
    a = np.delete(a, indices, 1)
    # array([[ 1,  0,  5,  7,  8], [11, 13, 15, 17, 18]])
    
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  • 2020-12-10 06:19

    Using np.where:

    >>> t.T[np.where(t[1])].T
    array([[ 1,  0,  5,  7,  8],
           [11, 13, 15, 17, 18]])
    
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  • 2020-12-10 06:20

    Simple (fully numpy) solution:

    import numpy as np
    
    t = np.array([[ 0, 1, 2, 0, 4, 5, 6, 7, 8, 9], [ 0, 11, 0, 13, 0, 15, 0, 17, 18, 0]])
    indices_to_keep = t[1].nonzero()[0]
    
    print t[:,indices_to_keep]
    # [[ 1  0  5  7  8]
    #  [11 13 15 17 18]]
    
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