[Python-checkins] bpo-36018: Add special value tests and make minor tweaks to the docs (GH-12096)

Thu Feb 28 12:16:28 EST 2019

https://github.com/python/cpython/commit/ef17fdbc1c274dc84c2f611c40449ab84824607e
commit: ef17fdbc1c274dc84c2f611c40449ab84824607e
branch: master
author: Raymond Hettinger <rhettinger at users.noreply.github.com>
committer: Miss Islington (bot) <31488909+miss-islington at users.noreply.github.com>
date: 2019年02月28日T09:16:25-08:00
summary:
bpo-36018: Add special value tests and make minor tweaks to the docs (GH-12096)
https://bugs.python.org/issue36018
files:
M Doc/library/statistics.rst
M Lib/statistics.py
M Lib/test/test_statistics.py

diff --git a/Doc/library/statistics.rst b/Doc/library/statistics.rst
index a0d4d3910220..8d961b7ca5b1 100644
--- a/Doc/library/statistics.rst
+++ b/Doc/library/statistics.rst
@@ -482,9 +482,9 @@ of applications in statistics, including simulations and hypothesis testing.
 .. class:: NormalDist(mu=0.0, sigma=1.0)
 
 Returns a new *NormalDist* object where *mu* represents the `arithmetic
- mean <https://en.wikipedia.org/wiki/Arithmetic_mean>`_ of data and *sigma*
+ mean <https://en.wikipedia.org/wiki/Arithmetic_mean>`_ and *sigma*
 represents the `standard deviation
- <https://en.wikipedia.org/wiki/Standard_deviation>`_ of the data.
+ <https://en.wikipedia.org/wiki/Standard_deviation>`_.
 
 If *sigma* is negative, raises :exc:`StatisticsError`.
 
@@ -579,7 +579,7 @@ of applications in statistics, including simulations and hypothesis testing.
 :class:`NormalDist` Examples and Recipes
 ----------------------------------------
 
-A :class:`NormalDist` readily solves classic probability problems.
+:class:`NormalDist` readily solves classic probability problems.
 
 For example, given `historical data for SAT exams
 <https://blog.prepscholar.com/sat-standard-deviation>`_ showing that scores
diff --git a/Lib/statistics.py b/Lib/statistics.py
index bab585750d91..e917a5dddd8b 100644
--- a/Lib/statistics.py
+++ b/Lib/statistics.py
@@ -735,7 +735,7 @@ def pdf(self, x):
 return exp((x - self.mu)**2.0 / (-2.0*variance)) / sqrt(tau * variance)
 
 def cdf(self, x):
- 'Cumulative density function: P(X <= x)'
+ 'Cumulative distribution function: P(X <= x)'
 if not self.sigma:
 raise StatisticsError('cdf() not defined when sigma is zero')
 return 0.5 * (1.0 + erf((x - self.mu) / (self.sigma * sqrt(2.0))))
diff --git a/Lib/test/test_statistics.py b/Lib/test/test_statistics.py
index d35cdd8420a3..4adc5e4cbf4a 100644
--- a/Lib/test/test_statistics.py
+++ b/Lib/test/test_statistics.py
@@ -2113,6 +2113,10 @@ def test_pdf(self):
 Y = NormalDist(100, 0)
 with self.assertRaises(statistics.StatisticsError):
 Y.pdf(90)
+ # Special values
+ self.assertEqual(X.pdf(float('-Inf')), 0.0)
+ self.assertEqual(X.pdf(float('Inf')), 0.0)
+ self.assertTrue(math.isnan(X.pdf(float('NaN'))))
 
 def test_cdf(self):
 NormalDist = statistics.NormalDist
@@ -2127,6 +2131,10 @@ def test_cdf(self):
 Y = NormalDist(100, 0)
 with self.assertRaises(statistics.StatisticsError):
 Y.cdf(90)
+ # Special values
+ self.assertEqual(X.cdf(float('-Inf')), 0.0)
+ self.assertEqual(X.cdf(float('Inf')), 1.0)
+ self.assertTrue(math.isnan(X.cdf(float('NaN'))))
 
 def test_properties(self):
 X = statistics.NormalDist(100, 15)
