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"""!
@brief Test templates for SOM-SC clustering module.
@authors Andrei Novikov (pyclustering@yandex.ru)
@date 2014-2020
@copyright BSD-3-Clause
"""
import numpy
import unittest
from pyclustering.cluster.somsc import somsc
from pyclustering.utils import read_sample
from random import random
class SyncnetTestTemplates(unittest.TestCase):
def templateLengthProcessData(self, path_to_file, amount_clusters, expected_cluster_length, ccore):
sample = read_sample(path_to_file)
somsc_instance = somsc(sample, amount_clusters, 100, ccore)
somsc_instance.process()
clusters = somsc_instance.get_clusters()
obtained_cluster_sizes = [len(cluster) for cluster in clusters]
self.assertEqual(len(sample), sum(obtained_cluster_sizes))
if expected_cluster_length is not None:
obtained_cluster_sizes.sort()
expected_cluster_length.sort()
self.assertEqual(obtained_cluster_sizes,expected_cluster_length)
def templateClusterAllocationOneDimensionData(self, ccore_flag):
input_data = [[random()] for i in range(10)] + [[random() + 3] for i in range(10)] + \
[[random() + 5] for i in range(10)] + [[random() + 8] for i in range(10)]
somsc_instance = somsc(input_data, 4, 100, ccore_flag)
somsc_instance.process()
clusters = somsc_instance.get_clusters()
self.assertEqual(len(clusters), 4)
for cluster in clusters:
self.assertEqual(len(cluster), 10)
def predict(self, path_to_file, amount_clusters, points, expected_closest_clusters, ccore):
sample = read_sample(path_to_file)
somsc_instance = somsc(sample, amount_clusters, 100, ccore)
somsc_instance.process()
closest_clusters = somsc_instance.predict(points)
self.assertEqual(len(expected_closest_clusters), len(closest_clusters))
self.assertTrue(numpy.array_equal(numpy.array(expected_closest_clusters), closest_clusters))
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