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90 lines
3.0 KiB
90 lines
3.0 KiB
5 years ago
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import pytest
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from clusterview.algorithms import Algorithms, CentroidGrouping
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from clusterview.colors import Color
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from clusterview.points import Point, PointSet
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@pytest.fixture(autouse=True, scope="function")
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def teardown():
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"""
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Teardown function for after each test. The current pytest best practice
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is to run a setup routine, yield, and then run your teardown routine.
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"""
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yield
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Algorithms.clear_centroids()
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def test_empty_centroids():
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with pytest.raises(ValueError):
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Algorithms.euclidean_grouping(None)
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def test_wrong_point_set():
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centroid_g1 = Point(101, 81, Color.ORANGE, 8, 800, 600)
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centroid_g2 = Point(357, 222, Color.RED, 8, 800, 600)
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centroid_g3 = Point(728, 47, Color.PURPLE, 8, 800, 600)
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centroids = [centroid_g1, centroid_g2, centroid_g3]
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Algorithms.set_centroids(centroids)
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with pytest.raises(ValueError):
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Algorithms.euclidean_grouping(None)
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def test_euclidean_distance():
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centroid_g1 = Point(101, 81, Color.ORANGE, 8, 800, 600)
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centroid_g2 = Point(357, 222, Color.RED, 8, 800, 600)
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centroid_g3 = Point(728, 47, Color.PURPLE, 8, 800, 600)
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centroids = [centroid_g1, centroid_g2, centroid_g3]
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point1_g1 = Point(67, 59, Color.GREY, 8, 800, 600)
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point2_g1 = Point(116, 53, Color.GREY, 8, 800, 600)
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point3_g1 = Point(144, 105, Color.GREY, 8, 800, 600)
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point1_g2 = Point(388, 243, Color.GREY, 8, 800, 600)
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point2_g2 = Point(358, 248, Color.GREY, 8, 800, 600)
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point3_g2 = Point(426, 202, Color.GREY, 8, 800, 600)
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point1_g3 = Point(750, 47, Color.GREY, 8, 800, 600)
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point2_g3 = Point(741, 85, Color.GREY, 8, 800, 600)
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point3_g3 = Point(700, 72, Color.GREY, 8, 800, 600)
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# This PointSet is the PointSet that excludes the centroids.
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point_set = PointSet(8, 800, 600)
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point_set.add_point(67, 59, Color.GREY)
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point_set.add_point(116, 53, Color.GREY)
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point_set.add_point(144, 105, Color.GREY)
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point_set.add_point(388, 243, Color.GREY)
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point_set.add_point(358, 248, Color.GREY)
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point_set.add_point(426, 202, Color.GREY)
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point_set.add_point(750, 47, Color.GREY)
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point_set.add_point(741, 85, Color.GREY)
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point_set.add_point(700, 72, Color.GREY)
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centroid_grouping_1 = CentroidGrouping(centroid_g1,
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[point1_g1, point2_g1, point3_g1])
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centroid_grouping_2 = CentroidGrouping(centroid_g2,
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[point1_g2, point2_g2, point3_g2])
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centroid_grouping_3 = CentroidGrouping(centroid_g3,
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[point1_g3, point2_g3, point3_g3])
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expected = [centroid_grouping_1, centroid_grouping_2, centroid_grouping_3]
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Algorithms.set_centroids(centroids)
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actual = Algorithms.euclidean_grouping(point_set)
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assert len(actual) == len(expected)
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# Since I don't want to figure out what grouping is where I'll accept
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# the linearity of `in`.
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assert centroid_grouping_1 in actual
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assert centroid_grouping_2 in actual
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assert centroid_grouping_3 in actual
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