Recursively builds a tree for proposing new position and momentum

def _build_tree(self, position, momentum, slice_var, direction, depth, stepsize, position0, momentum0):
        """
        Recursively builds a tree for proposing new position and momentum
        """
        if depth == 0:

            position_bar, momentum_bar, candidate_set_size, accept_set_bool =\
                self._initalize_tree(position, momentum, slice_var, direction * stepsize)

            alpha = min(1, self._acceptance_prob(position, position_bar, momentum, momentum_bar))

            return (position_bar, momentum_bar, position_bar, momentum_bar, position_bar,
                    candidate_set_size, accept_set_bool, alpha, 1)

        else:
            (position_backward, momentum_backward, position_forward, momentum_forward, position_bar,
             candidate_set_size, accept_set_bool, alpha, n_alpha) =\
                self._build_tree(position, momentum, slice_var,
                                 direction, depth - 1, stepsize, position0, momentum0)

            if accept_set_bool == 1:
                if direction == -1:
                    # Build tree in backward direction
                    (position_backward, momentum_backward, _, _, position_bar2, candidate_set_size2, accept_set_bool2,
                     alpha2, n_alpha2) = self._build_tree(position_backward, momentum_backward, slice_var, direction,
                                                          depth - 1, stepsize, position0, momentum0)
                else:
                    # Build tree in forward direction
                    (_, _, position_forward, momentum_forward, position_bar2, candidate_set_size2, accept_set_bool2,
                     alpha2, n_alpha2) = self._build_tree(position_forward, momentum_forward, slice_var, direction,
                                                          depth - 1, stepsize, position0, momentum0)

                if np.random.rand() < candidate_set_size2 / (candidate_set_size2 + candidate_set_size):
                    position_bar = position_bar2

                alpha += alpha2
                n_alpha += n_alpha2
                accept_set_bool, candidate_set_size =\
                    self._update_acceptance_criteria(position_forward, position_backward, momentum_forward,
                                                     momentum_backward, accept_set_bool2, candidate_set_size,
                                                     candidate_set_size2)

            return (position_backward, momentum_backward, position_forward, momentum_forward, position_bar,
                    candidate_set_size, accept_set_bool, alpha, n_alpha)