def draw(filename): basename = os.path.basename(filename) name = os.path.splitext(basename)[0] groups1, mean1, var1 = get_diff_average_sims('pairwise_new', filename) groups2, mean2, var2 = get_diff_average_sims('pairwise_sgd', filename) # groups3, mean3, var3 = get_diff_average_sims('pairwise_hp', filename) # groups1, mean1, var1 = get_total_average_sims('pairwise_new', filename) # groups2, mean2, var2 = get_total_average_sims('pairwise_sgd', filename) # groups3, mean3, var3 = get_total_average_sims('pairwise_hp', filename) plt.errorbar(groups1, mean1, yerr=var1, fmt='o', label='synthetic GO') plt.errorbar(groups2, mean2, yerr=var2, fmt='o', label='yeast') # plt.errorbar(groups3, mean3, yerr=var3, fmt='o', label='synthetic HPO') plt.legend() plt.xlabel('Annotation size difference') plt.ylabel('Average similarity') plt.title(get_similarity_name(name)) plt.savefig(DATA_ROOT + name + '.diff.pdf')
def get_correlations(measures, filename): ''' Calculates spearman and pearson correlations for annotation size with mean and annotation size with variance ''' corrs = list() # annots, mean, var = get_total_average_sims(measures, filename) annots, mean, var = get_diff_average_sims(measures, filename) r1, p1 = spearmanr(annots, mean) r2, p2 = spearmanr(annots, var) corrs.append((r1, p1, r2, p2)) r1, p1 = pearsonr(annots, mean) r2, p2 = pearsonr(annots, var) corrs.append((r1, p1, r2, p2)) return corrs