colors = [plt.cm.Spectral(each)
for each in np.linspace(0, 1, len(unique_labels))]
for k, col in zip(unique_labels, colors):
+ cluster_col = [1, 0, 0, 1]
if k == -1:
# Black used for noise.
col = [0, 0, 0, 1]
# print("Unique label: " + str(k) + " with freq: " + str(labels.tolist().count(k)))
xy = X[class_member_mask & core_samples_mask]
- plt.plot(xy[:, 0], xy[:, 1], 'o',
+ plt.plot(xy[:, 0], xy[:, 1], 'o', markerfacecolor=tuple(cluster_col),
markeredgecolor='k', markersize=10)
xy = X[class_member_mask & ~core_samples_mask]