How to use the pyclustering.samples.definitions.SIMPLE_SAMPLES.SAMPLE_SIMPLE1 function in pyclustering

def testClusteringSampleSimple1(self):
        self.templateClusteringResults(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, [5, 5]);
        self.templateClusteringResults(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1, [10]);

def testClusterAllocationConnWeightSampleSimple1ByCore(self):
        self.templateClustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 0.999, solve_type.FAST, initial_type.RANDOM_GAUSSIAN, True, True, 0.05, None, [5, 5], True);
        self.templateClustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10, 0.999, solve_type.FAST, initial_type.RANDOM_GAUSSIAN, True, True, 0.05, None, [10], True);

def testBicClusterAllocationSampleSimple1(self):
        self.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], splitting_type.BAYESIAN_INFORMATION_CRITERION);

def testClusteringByCore(self):
        self.templateClusteringResults(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, [5, 5], ccore = True);
        self.templateClusteringResults(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1, [10], ccore = True);
        self.templateClusteringResults(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, 3, [5, 8, 10], ccore = True);
        self.templateClusteringResults(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, 1, [23], ccore = True);
        self.templateClusteringResults(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, 4, [10, 10, 10, 30], ccore = True);
        self.templateClusteringResults(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, 1, [60], ccore = True);
        self.templateClusteringResults(SIMPLE_SAMPLES.SAMPLE_SIMPLE4, 5, [15, 15, 15, 15, 15], ccore = True);
        self.templateClusteringResults(SIMPLE_SAMPLES.SAMPLE_SIMPLE4, 1, [75], ccore = True);
        self.templateClusteringResults(SIMPLE_SAMPLES.SAMPLE_SIMPLE5, 4, [15, 15, 15, 15], ccore = True);
        self.templateClusteringResults(SIMPLE_SAMPLES.SAMPLE_SIMPLE5, 1, [60], ccore = True);

def cluster_sample1():
    template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 0.5, 3);

def experiment_execution_time(ccore = False):
    template_clustering([[3.7, 5.5], [6.7, 7.5]], SIMPLE_SAMPLES.SAMPLE_SIMPLE1, ccore);
    template_clustering([[3.5, 4.8], [6.9, 7], [7.5, 0.5]], SIMPLE_SAMPLES.SAMPLE_SIMPLE2, ccore);
    template_clustering([[0.2, 0.1], [4.0, 1.0], [2.0, 2.0], [2.3, 3.9]], SIMPLE_SAMPLES.SAMPLE_SIMPLE3, ccore);
    template_clustering([[1.5, 0.0], [1.5, 2.0], [1.5, 4.0], [1.5, 6.0], [1.5, 8.0]], SIMPLE_SAMPLES.SAMPLE_SIMPLE4, ccore);
    template_clustering([[0.0, 1.0], [0.0, 0.0], [1.0, 1.0], [1.0, 0.0]], SIMPLE_SAMPLES.SAMPLE_SIMPLE5, ccore);
    template_clustering([[1.0, 4.5], [3.1, 2.7]], SIMPLE_SAMPLES.SAMPLE_ELONGATE, ccore);
    template_clustering([[1.0, 3.5], [2.0, 0.5], [3.0, 3.0]], FCPS_SAMPLES.SAMPLE_LSUN, ccore);
    template_clustering([[0.2, 0.2], [0.0, -2.0], [3.0, -3.0], [3.0, 3.0], [-3.0, 3.0], [-3.0, -3.0]], FCPS_SAMPLES.SAMPLE_TARGET, ccore);
    template_clustering([[0.8, 0.2], [3.0, 0.0]], FCPS_SAMPLES.SAMPLE_TWO_DIAMONDS, ccore);  
    template_clustering([[-1.5, 1.5], [1.5, 1.5]], FCPS_SAMPLES.SAMPLE_WING_NUT, ccore); 
    template_clustering([[1.1, -1.7, 1.1], [-1.4, 2.5, -1.2]], FCPS_SAMPLES.SAMPLE_CHAINLINK, ccore);  
    template_clustering([[0.0, 0.0, 0.0], [3.0, 0.0, 0.0], [-2.0, 0.0, 0.0], [0.0, 3.0, 0.0], [0.0, -3.0, 0.0], [0.0, 0.0, 2.5], [0.0, 0.0, -2.5]], FCPS_SAMPLES.SAMPLE_HEPTA, ccore); 
    template_clustering([[1, 0, 0], [0, 1, 0], [0, -1, 0], [-1, 0, 0]], FCPS_SAMPLES.SAMPLE_TETRA, ccore);
    template_clustering([[-0.5, -0.5, -0.5], [0.5, 0.5, 0.5]], FCPS_SAMPLES.SAMPLE_ATOM, ccore);
    template_clustering([[0.5, 0.5], [2.3, 2.9]], FCPS_SAMPLES.SAMPLE_ENGY_TIME, ccore);

def sample_simple_01():
    elbow_analysis(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1, 10)
    elbow_analysis(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1, 10, initializer=random_center_initializer)

def experiment_execution_time(ccore = False):
    template_clustering(2, SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [type_link.SINGLE_LINK]);
    template_clustering(3, SIMPLE_SAMPLES.SAMPLE_SIMPLE2, [type_link.SINGLE_LINK]);
    template_clustering(4, SIMPLE_SAMPLES.SAMPLE_SIMPLE3, [type_link.SINGLE_LINK]);
    template_clustering(5, SIMPLE_SAMPLES.SAMPLE_SIMPLE4, [type_link.SINGLE_LINK]);
    template_clustering(4, SIMPLE_SAMPLES.SAMPLE_SIMPLE5, [type_link.SINGLE_LINK]);
    template_clustering(2, SIMPLE_SAMPLES.SAMPLE_ELONGATE, [type_link.SINGLE_LINK]);
    template_clustering(3, FCPS_SAMPLES.SAMPLE_LSUN, [type_link.SINGLE_LINK]);
    template_clustering(6, FCPS_SAMPLES.SAMPLE_TARGET, [type_link.SINGLE_LINK]);
    template_clustering(2, FCPS_SAMPLES.SAMPLE_TWO_DIAMONDS, [type_link.SINGLE_LINK]);
    template_clustering(2, FCPS_SAMPLES.SAMPLE_WING_NUT, [type_link.SINGLE_LINK]);
    template_clustering(2, FCPS_SAMPLES.SAMPLE_CHAINLINK, [type_link.SINGLE_LINK]);
    template_clustering(7, FCPS_SAMPLES.SAMPLE_HEPTA, [type_link.SINGLE_LINK]);
    template_clustering(4, FCPS_SAMPLES.SAMPLE_TETRA, [type_link.SINGLE_LINK]);
    template_clustering(2, FCPS_SAMPLES.SAMPLE_ATOM, [type_link.SINGLE_LINK]);

def experiment_execution_time(ccore):
    template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1, 2, 0.5, False, ccore);
    template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, 1, 3, 0.5, False, ccore);
    template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, 1, 4, 0.5, False, ccore);
    template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE4, 1, 5, 0.5, False, ccore);
    template_clustering(SIMPLE_SAMPLES.SAMPLE_ELONGATE, 1, 2, 0.5, False, ccore);
    template_clustering(FCPS_SAMPLES.SAMPLE_LSUN, 1, 3, 0.5, True, ccore);
    template_clustering(FCPS_SAMPLES.SAMPLE_TARGET, 1.2, 6, 0.2, True, ccore);
    template_clustering(FCPS_SAMPLES.SAMPLE_TWO_DIAMONDS, 0.2, 2, 0.2, True, ccore);
    template_clustering(FCPS_SAMPLES.SAMPLE_WING_NUT, 0.3, 2, 0.2, True, ccore);
    template_clustering(FCPS_SAMPLES.SAMPLE_CHAINLINK, 0.6, 2, 0.2, True, ccore);
    template_clustering(FCPS_SAMPLES.SAMPLE_HEPTA, 1.2, 7, 0.2, True, ccore);
    template_clustering(FCPS_SAMPLES.SAMPLE_TETRA, 0.5, 4, 0.2, True, ccore);
    template_clustering(FCPS_SAMPLES.SAMPLE_ATOM, 15, 2, 0.2, True, ccore)

def cluster_sample01_init_kmeans():
    template_clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, ema_init_type.KMEANS_INITIALIZATION);