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author | Raymond Hettinger <rhettinger@users.noreply.github.com> | 2019-03-19 19:48:04 (GMT) |
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committer | Miss Islington (bot) <31488909+miss-islington@users.noreply.github.com> | 2019-03-19 19:48:04 (GMT) |
commit | 52a594bd0df82f28b1bdb71a75e9c6fc1447f8ae (patch) | |
tree | d3d337352adf86d255878d156fc48f5183b1ac32 /Lib/statistics.py | |
parent | fc96e5474a7bda1c5dec66420e4467fc9f7ca968 (diff) | |
download | cpython-52a594bd0df82f28b1bdb71a75e9c6fc1447f8ae.zip cpython-52a594bd0df82f28b1bdb71a75e9c6fc1447f8ae.tar.gz cpython-52a594bd0df82f28b1bdb71a75e9c6fc1447f8ae.tar.bz2 |
NormalDist.inv_cdf(): In-line constants because the variable names were not informative (GH-12446)
Diffstat (limited to 'Lib/statistics.py')
-rw-r--r-- | Lib/statistics.py | 105 |
1 files changed, 46 insertions, 59 deletions
diff --git a/Lib/statistics.py b/Lib/statistics.py index d75bf4e..5ae122a 100644 --- a/Lib/statistics.py +++ b/Lib/statistics.py @@ -766,74 +766,61 @@ class NormalDist: 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 |