Fast way to get the combination pair list of the elements in a list.

fast_combinations.py

import numpy as np

def fast_combinations(row : list, self_loops = False) -> np.array:
    """
    Description
    -----------
    Fast way to obtain the combination of all the elements inside a list using Numpy.
    Self connections are present.

    Parameters
    ----------
    row : list
        List of elements to combine.
    
    self_loops : bool, optional
        Specify if self connections are required.
        The default values is 'False'.

    Return
    ------
    np.array : Array containing all the combination pairs of the given elements.

    NOTE
    ----
    Pay attention to the NANS entries. 
    - If you use 'np.nan' as float then the function won't be able to remove it and that value will
    also be used in the combination (longer processing time). Also, it won't remove np.nan self loops, since np.nan != np.nan.
    - None are supported, so if there is a None in the list it will be removed.
    - 'nan' strings are used too, because numpy arrays that have strings will convert np.nan to 'nan'.

    """
    

    if isinstance(row, list):

        row = [val for val in row if val is not None]
    
    else:
    
        row = row.tolist()
        row = [val for val in row if val is not None]

    try:

        if self_loops:

            comb = np.unique(np.sort(np.array(np.meshgrid(row, row)).T.reshape(-1,2)), axis=0)

        else:
            
            comb = np.unique(np.sort(np.array(np.meshgrid(row, row)).T.reshape(-1,2)), axis=0)
            comb = np.delete(comb, np.where(comb[:,0] == comb[:,1]), axis=0)
            comb = np.delete(comb, np.where(comb[:,1] == 'nan'), axis=0)

            if len(comb) == 0:
                return [[None, None]]

        return comb

    except:

        return [[None, None]]