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
