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"""!
@brief Unit-tests for TTSAS algorithm.
@authors Andrei Novikov (pyclustering@yandex.ru)
@date 2014-2020
@copyright BSD-3-Clause
"""
import unittest;
import matplotlib;
matplotlib.use('Agg');
from pyclustering.cluster.tests.ttsas_template import ttsas_test;
from pyclustering.utils.metric import type_metric, distance_metric;
from pyclustering.samples.definitions import SIMPLE_SAMPLES;
class ttsas_unit_tests(unittest.TestCase):
def testClusteringSampleSimple1(self):
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], False);
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10.0, 20.0, [10], False);
def testClusteringSampleSimple1Euclidean(self):
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], False, metric=distance_metric(type_metric.EUCLIDEAN));
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10.0, 20.0, [10], False, metric=distance_metric(type_metric.EUCLIDEAN));
def testClusteringSampleSimple1EuclideanSquare(self):
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], False, metric=distance_metric(type_metric.EUCLIDEAN_SQUARE));
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10.0, 20.0, [5, 5], False, metric=distance_metric(type_metric.EUCLIDEAN_SQUARE));
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 100.0, 200.0, [10], False, metric=distance_metric(type_metric.EUCLIDEAN_SQUARE));
def testClusteringSampleSimple1Manhattan(self):
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], False, metric=distance_metric(type_metric.MANHATTAN));
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10.0, 20.0, [10], False, metric=distance_metric(type_metric.MANHATTAN));
def testClusteringSampleSimple1Chebyshev(self):
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], False, metric=distance_metric(type_metric.CHEBYSHEV));
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10.0, 20.0, [10], False, metric=distance_metric(type_metric.CHEBYSHEV));
def testClusteringSampleSimple2(self):
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, 1.0, 2.0, [5, 8, 10], False);
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, 10.0, 20.0, [23], False);
def testClusteringSampleSimple3(self):
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, 1.0, 2.0, [10, 10, 10, 30], False);
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, 10.0, 20.0, [60], False);
def testOneDimentionalPoints1(self):
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE7, 1.0, 2.0, [10, 10], False);
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE7, 10.0, 20.0, [20], False);
def testOneDimentionalPoints2(self):
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 1.0, 2.0, [10, 20], False);
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 10.0, 20.0, [30], False);
def testThreeDimentionalPoints(self):
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE11, 1.0, 2.0, [10, 10], False);
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE11, 10.0, 20.0, [20], False);
def testTheSamePoints1(self):
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 1.0, 1.5, [5, 5, 5], False);
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 0.001, 0.002, [5, 5, 5], False);
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 1000, 2000, [15], False);
def testTheSamePoints2(self):
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 1.0, 2.0, [10, 20], False);
ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 10.0, 20.0, [30], False);
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