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"""!
@brief Unit-tests for SYNC-SOM algorithm.
@authors Andrei Novikov (pyclustering@yandex.ru)
@date 2014-2020
@copyright BSD-3-Clause
"""
import unittest;
# Generate images without having a window appear.
import matplotlib;
matplotlib.use('Agg');
from pyclustering.cluster.syncsom import syncsom;
from pyclustering.utils import read_sample;
from pyclustering.samples.definitions import SIMPLE_SAMPLES;
class SyncsomUnitTest(unittest.TestCase):
def templateLengthSomCluster(self, file, som_map_size, radius, eps):
sample = read_sample(file);
network = syncsom(sample, som_map_size[0], som_map_size[1], radius);
network.process(collect_dynamic = False, order = eps);
# Check unique
som_clusters = network.get_som_clusters();
indexes = set();
for som_cluster in som_clusters:
for index in som_cluster:
assert (index in indexes) is False;
indexes.add(index);
def testSomClusterAllocationSampleSimple1(self):
self.templateLengthSomCluster(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [3, 3], 1.0, 0.99);
def testSomClusterAllocationSampleSimple3(self):
self.templateLengthSomCluster(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, [3, 3], 1.0, 0.99);
def testSomClusterAllocationSampleSimple4(self):
self.templateLengthSomCluster(SIMPLE_SAMPLES.SAMPLE_SIMPLE4, [3, 3], 1.0, 0.99);
def testSomClusterAllocationSampleSimple5(self):
self.templateLengthSomCluster(SIMPLE_SAMPLES.SAMPLE_SIMPLE5, [3, 3], 1.0, 0.99);
def templateLengthProcessData(self, file, som_map_size, radius, eps, expected_cluster_length):
result_testing = False;
# If phases crosses each other because of random part of the network then we should try again.
for _ in range(0, 5, 1):
sample = read_sample(file);
network = syncsom(sample, som_map_size[0], som_map_size[1], radius);
network.process(collect_dynamic = False, order = eps);
clusters = network.get_clusters();
obtained_cluster_sizes = [len(cluster) for cluster in clusters];
if (len(sample) != sum(obtained_cluster_sizes)):
continue;
obtained_cluster_sizes.sort();
expected_cluster_length.sort();
#print(obtained_cluster_sizes, expected_cluster_length);
if (obtained_cluster_sizes != expected_cluster_length):
continue;
# Unit-test is passed
result_testing = True;
break;
assert result_testing;
def testClusterAllocationSampleSimple1ByGeaterAmoutNeurons(self):
self.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [5, 5], 1.0, 0.999, [5, 5]);
def testClusterAllocationSampleSimple1AsSom(self):
self.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [1, 2], 1.0, 0.999, [5, 5]);
def testClusterAllocationSampleSimple1(self):
self.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [2, 2], 1.0, 0.999, [5, 5]);
def testClusterAllocationSampleSimple2(self):
self.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, [5, 5], 1.0, 0.999, [10, 5, 8]);
def testClusterAllocationSampleSimple3(self):
self.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, [5, 5], 1.0, 0.999, [10, 10, 10, 30]);
def testClusterAllocationOneDimensionDataSampleSimple7AsSom(self):
self.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE7, [1, 2], 1.0, 0.999, [10, 10]);
def testClusterAllocationOneDimensionDataSampleSimple7(self):
self.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE7, [3, 3], 1.0, 0.999, [10, 10]);
def testClusterAllocationOneDimensionDataSampleSimple9AsSom(self):
self.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, [1, 2], 1.0, 0.999, [20, 10]);
def testClusterAllocationOneDimensionDataSampleSimple9(self):
self.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, [3, 3], 1.0, 0.999, [20, 10]);
def testShowLayersProcessing(self):
sample = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE1);
network = syncsom(sample, 4, 4, 1.0);
network.process(collect_dynamic = False, order = 0.99);
network.show_som_layer();
network.show_sync_layer();
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