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Statistics inv_cdf sync with corresponding random module normal distributions (#95265)

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Raymond Hettinger 2022-07-26 02:23:33 -05:00 committed by GitHub
parent b7ce4625fe
commit 4395ff1e6a
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3 changed files with 5 additions and 6 deletions
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2
Lib/statistics.py
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@ -1221,8 +1221,6 @@ class NormalDist:
""" """
if p <= 0.0 or p >= 1.0: if p <= 0.0 or p >= 1.0:
raise StatisticsError('p must be in the range 0.0 < p < 1.0') raise StatisticsError('p must be in the range 0.0 < p < 1.0')
if self._sigma <= 0.0:
raise StatisticsError('cdf() not defined when sigma at or below zero')
return _normal_dist_inv_cdf(p, self._mu, self._sigma) return _normal_dist_inv_cdf(p, self._mu, self._sigma)
def quantiles(self, n=4): def quantiles(self, n=4):

7
Lib/test/test_statistics.py
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@ -2801,9 +2801,10 @@ class TestNormalDist:
iq.inv_cdf(1.0) # p is one iq.inv_cdf(1.0) # p is one
with self.assertRaises(self.module.StatisticsError): with self.assertRaises(self.module.StatisticsError):
iq.inv_cdf(1.1) # p over one iq.inv_cdf(1.1) # p over one
with self.assertRaises(self.module.StatisticsError):
iq = NormalDist(100, 0) # sigma is zero # Supported case:
iq.inv_cdf(0.5) iq = NormalDist(100, 0) # sigma is zero
self.assertEqual(iq.inv_cdf(0.5), 100)
# Special values # Special values
self.assertTrue(math.isnan(Z.inv_cdf(float('NaN')))) self.assertTrue(math.isnan(Z.inv_cdf(float('NaN'))))

2
Modules/_statisticsmodule.c
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@ -31,7 +31,7 @@ _statistics__normal_dist_inv_cdf_impl(PyObject *module, double p, double mu,
/*[clinic end generated code: output=02fd19ddaab36602 input=24715a74be15296a]*/ /*[clinic end generated code: output=02fd19ddaab36602 input=24715a74be15296a]*/
{ {
double q, num, den, r, x; double q, num, den, r, x;
if (p <= 0.0 || p >= 1.0 || sigma <= 0.0) { if (p <= 0.0 || p >= 1.0) {
goto error; goto error;
} }