Generate a 2D boolean array from tuples

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说谎
说谎 2020-12-11 23:41

How can I generate a 2D boolean array using a list of tuples that shows the indices of the True values?

For example I have the following list of tuples:



        
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  • 2020-12-12 00:01

    Here's an approach using NumPy's linear indexing that works for tuples of any lengths intended to generate multi-dimensional arrays -

    # Convert list of indices to a 2D array version
    idx = np.array(lst)
    
    # Decide on the shape of output array based on the extents, then initialize
    shp = idx.max(0)+1
    out = np.zeros(shp,dtype=bool)
    
    # Using np.put insert 1s in out at places specified by linear indices version
    np.put(out,np.ravel_multi_index(idx.T,shp),1)
    

    Sample input, output -

    In [54]: lst
    Out[54]: [(0, 1, 3), (0, 2, 2), (1, 0, 0), (1, 3, 1), (2, 1, 3)]
    
    In [55]: out
    Out[55]: 
    array([[[False, False, False, False],
            [False, False, False,  True],
            [False, False,  True, False],
            [False, False, False, False]],
    
           [[ True, False, False, False],
            [False, False, False, False],
            [False, False, False, False],
            [False,  True, False, False]],
    
           [[False, False, False, False],
            [False, False, False,  True],
            [False, False, False, False],
            [False, False, False, False]]], dtype=bool)
    
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  • 2020-12-12 00:06

    zip(*...) is a handy way of 'transposing' a list of lists (or tuples). And A[x,y] is the same as A[(x,y)].

    In [397]: lst = [(0,1), (0, 2), (1, 0), (1, 3), (2,1)]
    
    In [398]: tuple(zip(*lst))    # make a tuple of tuples (or lists)
    Out[398]: ((0, 0, 1, 1, 2), (1, 2, 0, 3, 1))
    
    In [399]: A=np.zeros((3,4),dtype=bool)  # make an array of False
    
    In [400]: A[tuple(zip(*lst))] = True  # assign True to the 5 values
    
    In [401]: A
    Out[401]: 
    array([[False,  True,  True, False],
           [ True, False, False,  True],
           [False,  True, False, False]], dtype=bool)
    
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  • 2020-12-12 00:14

    You can use multidimensional indexing for this:

    >>> lst = np.array(lst)
    >>> arr = np.repeat(False, 12).reshape(3, 4)
    >>> arr[lst[:,0], lst[:,1]] = True
    >>> arr
    array([[False,  True,  True, False],
           [ True, False, False,  True],
           [False,  True, False, False]], dtype=bool)
    
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