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"""!
@brief Examples of usage and demonstration of abilities of genetic algorithm for cluster analysis.
@authors Aleksey Kukushkin (pyclustering@yandex.ru)
@date 2014-2020
@copyright BSD-3-Clause
"""
from pyclustering.samples.definitions import SIMPLE_SAMPLES
from pyclustering.cluster.ga import genetic_algorithm, ga_observer, ga_visualizer
from pyclustering.utils import read_sample
import time
def template_clustering(path,
count_clusters,
chromosome_count,
population_count,
count_mutation_gens,
coeff_mutation_count=0.25,
select_coeff=1.0,
fps=15,
animation=False):
sample = read_sample(path)
algo_instance = genetic_algorithm(data=sample,
count_clusters=count_clusters,
chromosome_count=chromosome_count,
population_count=population_count,
count_mutation_gens=count_mutation_gens,
coeff_mutation_count=coeff_mutation_count,
select_coeff=select_coeff,
observer=ga_observer(True, True, True))
start_time = time.time()
algo_instance.process()
print("Sample: ", path, "\t\tExecution time: ", time.time() - start_time, "\n")
observer = algo_instance.get_observer()
ga_visualizer.show_clusters(sample, observer)
if (animation is True):
ga_visualizer.animate_cluster_allocation(sample, observer, movie_fps=fps, save_movie="clustering_animation.mp4")
# ga_visualizer.animate_cluster_allocation(sample, observer);
def cluster_sample1():
template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1,
count_clusters=2,
chromosome_count=20,
population_count=20,
count_mutation_gens=2)
def cluster_sample2():
template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE2,
count_clusters=3,
chromosome_count=40,
population_count=120,
count_mutation_gens=2)
def cluster_sample3():
template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE3,
count_clusters=4,
chromosome_count=100,
population_count=200,
count_mutation_gens=2,
coeff_mutation_count=0.8,
select_coeff=0.3)
def cluster_sample4():
template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE4,
count_clusters=5,
chromosome_count=100,
population_count=200,
count_mutation_gens=1)
def cluster_sample5():
template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE5,
count_clusters=4,
chromosome_count=40,
population_count=140,
count_mutation_gens=1)
def cluster_sample6():
template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE6,
count_clusters=2,
chromosome_count=20,
population_count=100,
count_mutation_gens=1)
def cluster_sample7():
template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE7,
count_clusters=2,
chromosome_count=20,
population_count=30,
count_mutation_gens=1)
def cluster_sample11():
template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE11,
count_clusters=2,
chromosome_count=20,
population_count=30,
count_mutation_gens=2)
def cluster_sample8():
template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE8,
count_clusters=4,
chromosome_count=50,
population_count=200,
count_mutation_gens=2,
coeff_mutation_count=0.15,
select_coeff=1.0)
def animation_cluster_sample1():
template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1,
count_clusters=2,
chromosome_count=10,
population_count=50,
count_mutation_gens=2,
select_coeff=0.02,
fps=5,
animation=True)
def animation_cluster_sample2():
template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE2,
count_clusters=3,
chromosome_count=30,
population_count=150,
count_mutation_gens=2,
select_coeff=0.02,
fps=8,
animation=True)
def animation_cluster_sample3():
template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE3,
count_clusters=4,
chromosome_count=100,
population_count=150,
count_mutation_gens=2,
coeff_mutation_count=0.8,
select_coeff=0.3,
fps=5,
animation=True)
def animation_cluster_sample4():
template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE4,
count_clusters=5,
chromosome_count=50,
population_count=500,
count_mutation_gens=2,
select_coeff=0.1,
fps=15,
animation=True)
cluster_sample1()
cluster_sample2()
cluster_sample3()
cluster_sample4()
cluster_sample5()
cluster_sample6()
cluster_sample7()
cluster_sample11()
animation_cluster_sample1()
animation_cluster_sample2()
animation_cluster_sample3()
animation_cluster_sample4()
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