[Python-checkins] NormalDist.inv_cdf(): In-line constants because the variable names were not informative (GH-12446)
Miss Islington (bot)
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Tue Mar 19 15:48:10 EDT 2019
https://github.com/python/cpython/commit/52a594bd0df82f28b1bdb71a75e9c6fc1447f8ae
commit: 52a594bd0df82f28b1bdb71a75e9c6fc1447f8ae
branch: master
author: Raymond Hettinger <rhettinger at users.noreply.github.com>
committer: Miss Islington (bot) <31488909+miss-islington at users.noreply.github.com>
date: 2019-03-19T12:48:04-07:00
summary:
NormalDist.inv_cdf(): In-line constants because the variable names were not informative (GH-12446)
files:
M Lib/statistics.py
diff --git a/Lib/statistics.py b/Lib/statistics.py
index d75bf4e2c387..5ae122a4add9 100644
--- a/Lib/statistics.py
+++ b/Lib/statistics.py
@@ -766,74 +766,61 @@ def inv_cdf(self, p):
q = p - 0.5
if fabs(q) <= 0.425:
- a0 = 3.38713_28727_96366_6080e+0
- a1 = 1.33141_66789_17843_7745e+2
- a2 = 1.97159_09503_06551_4427e+3
- a3 = 1.37316_93765_50946_1125e+4
- a4 = 4.59219_53931_54987_1457e+4
- a5 = 6.72657_70927_00870_0853e+4
- a6 = 3.34305_75583_58812_8105e+4
- a7 = 2.50908_09287_30122_6727e+3
- b1 = 4.23133_30701_60091_1252e+1
- b2 = 6.87187_00749_20579_0830e+2
- b3 = 5.39419_60214_24751_1077e+3
- b4 = 2.12137_94301_58659_5867e+4
- b5 = 3.93078_95800_09271_0610e+4
- b6 = 2.87290_85735_72194_2674e+4
- b7 = 5.22649_52788_52854_5610e+3
r = 0.180625 - q * q
- num = (q * (((((((a7 * r + a6) * r + a5) * r + a4) * r + a3)
- * r + a2) * r + a1) * r + a0))
- den = ((((((((b7 * r + b6) * r + b5) * r + b4) * r + b3)
- * r + b2) * r + b1) * r + 1.0))
+ num = (q * (((((((2.50908_09287_30122_6727e+3 * r +
+ 3.34305_75583_58812_8105e+4) * r +
+ 6.72657_70927_00870_0853e+4) * r +
+ 4.59219_53931_54987_1457e+4) * r +
+ 1.37316_93765_50946_1125e+4) * r +
+ 1.97159_09503_06551_4427e+3) * r +
+ 1.33141_66789_17843_7745e+2) * r +
+ 3.38713_28727_96366_6080e+0))
+ den = ((((((((5.22649_52788_52854_5610e+3 * r +
+ 2.87290_85735_72194_2674e+4) * r +
+ 3.93078_95800_09271_0610e+4) * r +
+ 2.12137_94301_58659_5867e+4) * r +
+ 5.39419_60214_24751_1077e+3) * r +
+ 6.87187_00749_20579_0830e+2) * r +
+ 4.23133_30701_60091_1252e+1) * r + 1.0))
x = num / den
return self.mu + (x * self.sigma)
-
r = p if q <= 0.0 else 1.0 - p
r = sqrt(-log(r))
if r <= 5.0:
- c0 = 1.42343_71107_49683_57734e+0
- c1 = 4.63033_78461_56545_29590e+0
- c2 = 5.76949_72214_60691_40550e+0
- c3 = 3.64784_83247_63204_60504e+0
- c4 = 1.27045_82524_52368_38258e+0
- c5 = 2.41780_72517_74506_11770e-1
- c6 = 2.27238_44989_26918_45833e-2
- c7 = 7.74545_01427_83414_07640e-4
- d1 = 2.05319_16266_37758_82187e+0
- d2 = 1.67638_48301_83803_84940e+0
- d3 = 6.89767_33498_51000_04550e-1
- d4 = 1.48103_97642_74800_74590e-1
- d5 = 1.51986_66563_61645_71966e-2
- d6 = 5.47593_80849_95344_94600e-4
- d7 = 1.05075_00716_44416_84324e-9
r = r - 1.6
- num = ((((((((c7 * r + c6) * r + c5) * r + c4) * r + c3)
- * r + c2) * r + c1) * r + c0))
- den = ((((((((d7 * r + d6) * r + d5) * r + d4) * r + d3)
- * r + d2) * r + d1) * r + 1.0))
+ num = ((((((((7.74545_01427_83414_07640e-4 * r +
+ 2.27238_44989_26918_45833e-2) * r +
+ 2.41780_72517_74506_11770e-1) * r +
+ 1.27045_82524_52368_38258e+0) * r +
+ 3.64784_83247_63204_60504e+0) * r +
+ 5.76949_72214_60691_40550e+0) * r +
+ 4.63033_78461_56545_29590e+0) * r +
+ 1.42343_71107_49683_57734e+0))
+
+ den = ((((((((1.05075_00716_44416_84324e-9 * r +
+ 5.47593_80849_95344_94600e-4) * r +
+ 1.51986_66563_61645_71966e-2) * r +
+ 1.48103_97642_74800_74590e-1) * r +
+ 6.89767_33498_51000_04550e-1) * r +
+ 1.67638_48301_83803_84940e+0) * r +
+ 2.05319_16266_37758_82187e+0) * r + 1.0))
else:
- e0 = 6.65790_46435_01103_77720e+0
- e1 = 5.46378_49111_64114_36990e+0
- e2 = 1.78482_65399_17291_33580e+0
- e3 = 2.96560_57182_85048_91230e-1
- e4 = 2.65321_89526_57612_30930e-2
- e5 = 1.24266_09473_88078_43860e-3
- e6 = 2.71155_55687_43487_57815e-5
- e7 = 2.01033_43992_92288_13265e-7
- f1 = 5.99832_20655_58879_37690e-1
- f2 = 1.36929_88092_27358_05310e-1
- f3 = 1.48753_61290_85061_48525e-2
- f4 = 7.86869_13114_56132_59100e-4
- f5 = 1.84631_83175_10054_68180e-5
- f6 = 1.42151_17583_16445_88870e-7
- f7 = 2.04426_31033_89939_78564e-15
r = r - 5.0
- num = ((((((((e7 * r + e6) * r + e5) * r + e4) * r + e3)
- * r + e2) * r + e1) * r + e0))
- den = ((((((((f7 * r + f6) * r + f5) * r + f4) * r + f3)
- * r + f2) * r + f1) * r + 1.0))
-
+ num = ((((((((2.01033_43992_92288_13265e-7 * r +
+ 2.71155_55687_43487_57815e-5) * r +
+ 1.24266_09473_88078_43860e-3) * r +
+ 2.65321_89526_57612_30930e-2) * r +
+ 2.96560_57182_85048_91230e-1) * r +
+ 1.78482_65399_17291_33580e+0) * r +
+ 5.46378_49111_64114_36990e+0) * r +
+ 6.65790_46435_01103_77720e+0))
+ den = ((((((((2.04426_31033_89939_78564e-15 * r +
+ 1.42151_17583_16445_88870e-7) * r +
+ 1.84631_83175_10054_68180e-5) * r +
+ 7.86869_13114_56132_59100e-4) * r +
+ 1.48753_61290_85061_48525e-2) * r +
+ 1.36929_88092_27358_05310e-1) * r +
+ 5.99832_20655_58879_37690e-1) * r + 1.0))
x = num / den
if q < 0.0:
x = -x
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