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Code Issues Projects Releases Packages Wiki Activity Actions 14

bpo-36546: Add more tests and expand docs (#13406)

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Raymond Hettinger 2019-05-18 10:18:29 -07:00 • committed by GitHub
parent 73934b9da0
commit e917f2ed9a
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2 changed files with 48 additions and 21 deletions
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38
Lib/test/test_statistics.py
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@ -2161,17 +2161,18 @@ class TestQuantiles(unittest.TestCase):
# Quantiles should be idempotent
if len(expected) >= 2:
self.assertEqual(quantiles(expected, n=n), expected)
# Cross-check against other methods
if len(data) >= n:
# After end caps are added, method='inclusive' should
# give the same result as method='exclusive' whenever
# there are more data points than desired cut points.
padded_data = [min(data) - 1000] + data + [max(data) + 1000]
self.assertEqual(
quantiles(data, n=n),
quantiles(padded_data, n=n, method='inclusive'),
(n, data),
)
# Cross-check against method='inclusive' which should give
# the same result after adding in minimum and maximum values
# extrapolated from the two lowest and two highest points.
sdata = sorted(data)
lo = 2 * sdata[0] - sdata[1]
hi = 2 * sdata[-1] - sdata[-2]
padded_data = data + [lo, hi]
self.assertEqual(
quantiles(data, n=n),
quantiles(padded_data, n=n, method='inclusive'),
(n, data),
)
# Invariant under tranlation and scaling
def f(x):
return 3.5 * x - 1234.675
@ -2188,6 +2189,11 @@ class TestQuantiles(unittest.TestCase):
actual = quantiles(statistics.NormalDist(), n=n)
self.assertTrue(all(math.isclose(e, a, abs_tol=0.0001)
for e, a in zip(expected, actual)))
# Q2 agrees with median()
for k in range(2, 60):
data = random.choices(range(100), k=k)
q1, q2, q3 = quantiles(data)
self.assertEqual(q2, statistics.median(data))
def test_specific_cases_inclusive(self):
# Match results computed by hand and cross-checked
@ -2233,6 +2239,11 @@ class TestQuantiles(unittest.TestCase):
actual = quantiles(statistics.NormalDist(), n=n, method="inclusive")
self.assertTrue(all(math.isclose(e, a, abs_tol=0.0001)
for e, a in zip(expected, actual)))
# Natural deciles
self.assertEqual(quantiles([0, 100], n=10, method='inclusive'),
[10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0])
self.assertEqual(quantiles(range(0, 101), n=10, method='inclusive'),
[10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0])
# Whenever n is smaller than the number of data points, running
# method='inclusive' should give the same result as method='exclusive'
# after the two included extreme points are removed.
@ -2242,6 +2253,11 @@ class TestQuantiles(unittest.TestCase):
data.remove(max(data))
expected = quantiles(data, n=32)
self.assertEqual(expected, actual)
# Q2 agrees with median()
for k in range(2, 60):
data = random.choices(range(100), k=k)
q1, q2, q3 = quantiles(data, method='inclusive')
self.assertEqual(q2, statistics.median(data))
def test_equal_inputs(self):
quantiles = statistics.quantiles