R10109/testing.py
c7354a4851f2master

testing.py
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			'''
			ee311
			=====

			Lab 1: illustration of linear regression
			----------------------------------------

			created by Michael Liebling 21.2.2020
			based on:
			https://scikit-learn.org/stable/auto_examples/linear_model/plot_ols.html#sphx-glr-auto-examples-linear-model-plot-ols-py
			'''

			import unittest
			import numpy as np
			from sklearn import datasets, linear_model
			import coursework

			import importlib
			importlib.reload(coursework)

			class Test(unittest.TestCase):

			def setUp(self):

			boston_X, boston_y = datasets.load_boston(return_X_y=True)
			boston_X = boston_X[:, np.newaxis, 6]

			self.data_X = boston_X[:20]
			self.data_y = boston_y[:20]
			self.predict_X = np.arange(0, 101, 10)[..., None]

			self.expected = np.load('test_data.npy')


			def test_model_predict(self):
			model = coursework.train(self.data_X, self.data_y)
			prediction = coursework.predict(model, self.predict_X)
			np.testing.assert_array_almost_equal(prediction, self.expected)


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