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 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
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
