def _jit_pairwise_distances(pos1, pos2):
        """Optimized function for calculating the distance between each pair
        of points in positions1 and positions2.

        Does use python mode as fallback, if a scalar and not an array is
        given.
        """
        n1 = pos1.shape[0]
        n2 = pos2.shape[0]
        D = np.empty((n1, n2))

        for i in range(n1):
            for j in range(n2):
                D[i, j] = np.sqrt(((pos1[i] - pos2[j])**2).sum())
        return D
def _jit_pairwise_distances ( pos1 , pos2 ) : n1 = pos1 . shape [ 0 ] n2 = pos2 . shape [ 0 ] D = np . empty ( ( n1 , n2 ) ) for i in range ( n1 ) : for j in range ( n2 ) : D [ i , j ] = np . sqrt ( ( ( pos1 [ i ] - pos2 [ j ] ) ** 2 ) . sum ( ) ) return D
Optimized function for calculating the distance between each pair
        of points in positions1 and positions2.

        Does use python mode as fallback, if a scalar and not an array is
        given.