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author | Raymond Hettinger <rhettinger@users.noreply.github.com> | 2019-03-19 21:29:13 (GMT) |
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committer | Miss Islington (bot) <31488909+miss-islington@users.noreply.github.com> | 2019-03-19 21:29:13 (GMT) |
commit | fe13883f01da855967403acab77e0f16707a56cb (patch) | |
tree | bd4175a3015dabdb065ce8a62e6c8d8f6724a69f /Lib/statistics.py | |
parent | 52a594bd0df82f28b1bdb71a75e9c6fc1447f8ae (diff) | |
download | cpython-fe13883f01da855967403acab77e0f16707a56cb.zip cpython-fe13883f01da855967403acab77e0f16707a56cb.tar.gz cpython-fe13883f01da855967403acab77e0f16707a56cb.tar.bz2 |
bpo-36324: Improved code formatting for the NormalDist.inv_cdf rational approximation (GH-12448)
https://bugs.python.org/issue36324
Diffstat (limited to 'Lib/statistics.py')
-rw-r--r-- | Lib/statistics.py | 94 |
1 files changed, 48 insertions, 46 deletions
diff --git a/Lib/statistics.py b/Lib/statistics.py index 5ae122a..e5a6246 100644 --- a/Lib/statistics.py +++ b/Lib/statistics.py @@ -767,60 +767,62 @@ class NormalDist: q = p - 0.5 if fabs(q) <= 0.425: r = 0.180625 - q * q - 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)) + num = (((((((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) * q + 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: r = r - 1.6 - 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)) + 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: r = r - 5.0 - 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)) + 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 |