def template_clustering(data_path, levels, **kwargs):
print("Sample: '%s'." % os.path.basename(data_path))
density_threshold = kwargs.get("density_threshold", 0.0)
amount_threshold = kwargs.get("amount_threshold", 0)
data = read_sample(data_path)
bang_instance = bang(data,
levels,
density_threshold=density_threshold,
amount_threshold=amount_threshold)
bang_instance.process()
clusters = bang_instance.get_clusters()
noise = bang_instance.get_noise()
directory = bang_instance.get_directory()
dendrogram = bang_instance.get_dendrogram()
bang_visualizer.show_blocks(directory)
bang_visualizer.show_dendrogram(dendrogram)
bang_visualizer.show_clusters(data, clusters, noise)
if len(data[0]) == 2:
animator = bang_animator(directory, clusters)
animator.animate()
def template_clustering(data_path, levels, **kwargs):
print("Sample: '%s'." % os.path.basename(data_path))
density_threshold = kwargs.get("density_threshold", 0.0)
amount_threshold = kwargs.get("amount_threshold", 0)
data = read_sample(data_path)
bang_instance = bang(data, levels, density_threshold=density_threshold, amount_threshold=amount_threshold)
bang_instance.process()
clusters = bang_instance.get_clusters()
noise = bang_instance.get_noise()
directory = bang_instance.get_directory()
dendrogram = bang_instance.get_dendrogram()
bang_visualizer.show_blocks(directory)
bang_visualizer.show_dendrogram(dendrogram)
bang_visualizer.show_clusters(data, clusters, noise)
if len(data[0]) == 2:
animator = bang_animator(directory, clusters)
animator.animate()