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miss-islington merged 1 commit into from
Mar 20, 2019
Merged

bpo-36324: NormalDist() add more tests and update comments #12476

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68 changes: 44 additions & 24 deletions Lib/test/test_statistics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2040,6 +2040,13 @@ def test_compare_to_variance(self):

class TestNormalDist(unittest.TestCase):

# General note on precision: The pdf(), cdf(), and overlap() methods
# depend on functions in the math libraries that do not make
# explicit accuracy guarantees. Accordingly, some of the accuracy
# tests below may fail if the underlying math functions are
# inaccurate. There isn't much we can do about this short of
# implementing our own implementations from scratch.

def test_slots(self):
nd = statistics.NormalDist(300, 23)
with self.assertRaises(TypeError):
Expand All @@ -2062,6 +2069,12 @@ def test_instantiation_and_attributes(self):
with self.assertRaises(statistics.StatisticsError):
statistics.NormalDist(500, -10)

# verify that subclass type is honored
class NewNormalDist(statistics.NormalDist):
pass
nnd = NewNormalDist(200, 5)
self.assertEqual(type(nnd), NewNormalDist)

def test_alternative_constructor(self):
NormalDist = statistics.NormalDist
data = [96, 107, 90, 92, 110]
Expand All @@ -2077,6 +2090,12 @@ def test_alternative_constructor(self):
with self.assertRaises(statistics.StatisticsError):
NormalDist.from_samples([10]) # only one input

# verify that subclass type is honored
class NewNormalDist(NormalDist):
pass
nnd = NewNormalDist.from_samples(data)
self.assertEqual(type(nnd), NewNormalDist)

def test_sample_generation(self):
NormalDist = statistics.NormalDist
mu, sigma = 10_000, 3.0
Expand All @@ -2099,12 +2118,6 @@ def test_sample_generation(self):
self.assertEqual(data2, data4)
self.assertNotEqual(data1, data2)

# verify that subclass type is honored
class NewNormalDist(NormalDist):
pass
nnd = NewNormalDist(200, 5)
self.assertEqual(type(nnd), NewNormalDist)

def test_pdf(self):
NormalDist = statistics.NormalDist
X = NormalDist(100, 15)
Expand Down Expand Up @@ -2151,8 +2164,8 @@ def test_cdf(self):
self.assertEqual(set(map(type, cdfs)), {float})
# Verify montonic
self.assertEqual(cdfs, sorted(cdfs))
# Verify center
self.assertAlmostEqual(X.cdf(100), 0.50)
# Verify center (should be exact)
self.assertEqual(X.cdf(100), 0.50)
# Check against a table of known values
# https://en.wikipedia.org/wiki/Standard_normal_table#Cumulative
Z = NormalDist()
Expand Down Expand Up @@ -2216,10 +2229,11 @@ def test_inv_cdf(self):
p = 1.0 - p
self.assertAlmostEqual(iq.cdf(iq.inv_cdf(p)), p)

# Now apply cdf() first. At six sigmas, the round-trip
# loses a lot of precision, so only check to 6 places.
for x in range(10, 190):
self.assertAlmostEqual(iq.inv_cdf(iq.cdf(x)), x, places=6)
# Now apply cdf() first. Near the tails, the round-trip loses
# precision and is ill-conditioned (small changes in the inputs
# give large changes in the output), so only check to 5 places.
for x in range(200):
self.assertAlmostEqual(iq.inv_cdf(iq.cdf(x)), x, places=5)

# Error cases:
with self.assertRaises(statistics.StatisticsError):
Expand All @@ -2237,6 +2251,9 @@ def test_inv_cdf(self):
iq.sigma = -0.1 # sigma under zero
iq.inv_cdf(0.5)

# Special values
self.assertTrue(math.isnan(Z.inv_cdf(float('NaN'))))

def test_overlap(self):
NormalDist = statistics.NormalDist

Expand Down Expand Up @@ -2275,6 +2292,7 @@ def overlap_numeric(X, Y, *, steps=8_192, z=5):
(NormalDist(-100, 15), NormalDist(110, 15)),
(NormalDist(-100, 15), NormalDist(-110, 15)),
# Misc cases with unequal standard deviations
(NormalDist(100, 12), NormalDist(100, 15)),
(NormalDist(100, 12), NormalDist(110, 15)),
(NormalDist(100, 12), NormalDist(150, 15)),
(NormalDist(100, 12), NormalDist(150, 35)),
Expand Down Expand Up @@ -2305,18 +2323,6 @@ def test_properties(self):
self.assertEqual(X.stdev, 15)
self.assertEqual(X.variance, 225)

def test_unary_operations(self):
NormalDist = statistics.NormalDist
X = NormalDist(100, 12)
Y = +X
self.assertIsNot(X, Y)
self.assertEqual(X.mu, Y.mu)
self.assertEqual(X.sigma, Y.sigma)
Y = -X
self.assertIsNot(X, Y)
self.assertEqual(X.mu, -Y.mu)
self.assertEqual(X.sigma, Y.sigma)

def test_same_type_addition_and_subtraction(self):
NormalDist = statistics.NormalDist
X = NormalDist(100, 12)
Expand All @@ -2340,13 +2346,27 @@ def test_translation_and_scaling(self):
with self.assertRaises(TypeError): # __rtruediv__
y / X

def test_unary_operations(self):
NormalDist = statistics.NormalDist
X = NormalDist(100, 12)
Y = +X
self.assertIsNot(X, Y)
self.assertEqual(X.mu, Y.mu)
self.assertEqual(X.sigma, Y.sigma)
Y = -X
self.assertIsNot(X, Y)
self.assertEqual(X.mu, -Y.mu)
self.assertEqual(X.sigma, Y.sigma)

def test_equality(self):
NormalDist = statistics.NormalDist
nd1 = NormalDist()
nd2 = NormalDist(2, 4)
nd3 = NormalDist()
nd4 = NormalDist(2, 4)
self.assertNotEqual(nd1, nd2)
self.assertEqual(nd1, nd3)
self.assertEqual(nd2, nd4)

# Test NotImplemented when types are different
class A:
Expand Down