def map_word_on_two_pole_axis_for_graph(word, axis, score_graph, path_graph): result = np.zeros(len(axis)) for i, (pole_p, pole_n) in enumerate(axis): if word in path_graph: path_p = shortestPath(path_graph, word, pole_p) path_n = shortestPath(path_graph, word, pole_n) score_p = calculate_similarity_score_using_path( path_p, score_graph) score_n = calculate_similarity_score_using_path( path_n, score_graph) result[i] = calculate_score_on_two_pole_axis(score_p, score_n) print word, pole_p, pole_n, result[i] return result
def map_word_on_one_pole_axis(word, axis, score_graph, path_graph, threshold=None): result = np.zeros(len(axis)) for i, pole in enumerate(axis): if word in path_graph: path = shortestPath(path_graph, word, pole) result[i] = calculate_similarity_score_using_path( path, score_graph, path_graph, threshold=threshold) print word, pole, result[i] return result