Exemple #1
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def test_biased(biased_data):
    summary = Summary()
    for sample in biased_data:
        summary.add(sample)
    assert summary.mean == approx(74.085)
    assert summary.median == approx(32.0)
    top_3 = summary.mode[:3]
    assert top_3 == [(500, 97), (42, 42), (41, 41)]
Exemple #2
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 def setUp(self):
     self.summary = Summary()
     self.data = [500] * 97
     # Build 903 elements: each value of n occurs n times.
     for i in range(1, 43):
         self.data += [i] * i
     random.shuffle(self.data)
     for sample in self.data:
         self.summary.add(sample)
Exemple #3
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class GIVEN_data_WHEN_1k_samples_THEN_mean_median(unittest.TestCase):
    def setUp(self):
        self.summary = Summary()
        self.data = list(range(1001))
        random.shuffle(self.data)

    def runTest(self):
        for sample in self.data:
            self.summary.add(sample)

        self.assertEqual(500, self.summary.mean)
        self.assertEqual(500, self.summary.median)
Exemple #4
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class GIVEN_Summary_WHEN_1k_samples_THEN_mode(unittest.TestCase):
    def setUp(self):
        self.summary = Summary()
        self.data = [500] * 97
        # Build 903 elements: each value of n occurs n times.
        for i in range(1, 43):
            self.data += [i] * i
        random.shuffle(self.data)
        for sample in self.data:
            self.summary.add(sample)

    def test_mode(self):
        top_3 = self.summary.mode[:3]
        self.assertListEqual([(500, 97), (42, 42), (41, 41)], top_3)
Exemple #5
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def test_flat(flat_data):
    summary = Summary()
    for sample in flat_data:
        summary.add(sample)
    assert summary.mean == 500
    assert summary.median == 500
Exemple #6
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 def setUp(self):
     self.summary = Summary()
     self.data = list(range(1001))
     random.shuffle(self.data)
     for sample in self.data:
         self.summary.add(sample)
Exemple #7
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 def setUp(self):
     self.summary = Summary()
     self.data = list(range(1001))
     random.shuffle(self.data)
def summary_object(flat_data):
    summary = Summary()
    for sample in flat_data:
        summary.add(sample)
    return summary