testing.py
7b22df90220dmaster

testing.py
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			"""
			EE-311
			======

			Lab 6: Clustering
			-----------------

			created by Francois Marelli on 04.05.2020
			"""

			import importlib
			import unittest

			import numpy as np
			from sklearn.metrics.pairwise import rbf_kernel

			import homework

			importlib.reload(homework)


			class TestKMeans(unittest.TestCase):
			def setUp(self):
			arrays = np.load("data.npz")
			self.data_X = arrays["data_X"]
			self.data_X2 = arrays["data_X2"]
			self.kernel = arrays["kernel"]
			self.update = arrays["update"]
			self.clusters = arrays["init_clusters"]
			self.distance = arrays["distance"]

			def test_kernel(self):
			_kernel = homework.radial_kernel(self.data_X, self.data_X2)
			np.testing.assert_allclose(
			_kernel, self.kernel, err_msg="\nThe radial kernel is incorrect\n"
			)

			def test_update(self):
			K = np.unique(self.clusters).size
			_update = homework.update_clusters(self.data_X, self.clusters, K, rbf_kernel)
			np.testing.assert_allclose(
			_update, self.update, err_msg="\nThe Lloyd algorigthm update is incorrect\n"
			)

			def test_distance(self):
			_distance = homework.kernel_distance(self.data_X, self.data_X2, rbf_kernel)
			np.testing.assert_allclose(
			_distance,
			self.distance,
			atol=2e-7,
			err_msg="\nThe distance computed using the kernel is incorrect\n",
			)


			if __name__ == "__main__":
			unittest.main()