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rng: avoid extreme values in gaussian #8

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rng: avoid extreme values in gaussian
jxy Jan 3, 2023
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github/workflow: use ci/funs.sh in Nim to bootstrap Nim for different…
jxy Jan 3, 2023
b720573
Merge branch 'devel' into gaussian
jxy Jan 3, 2023
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7 changes: 4 additions & 3 deletions src/rng/milcrng.nim
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Original file line number Diff line number Diff line change
Expand Up @@ -148,14 +148,15 @@ proc gaussian*(prn: var RngMilc6): float32 =
result = prn.gset
else:
const
TINY = 9.999999999999999e-308
MAX = 0x01000000.float
SCALE1 = 1.0 / (MAX + 1.0)
var
v: cdouble
p: cdouble
r: cdouble
v = prn.uniform
v = SCALE1 * (prn.uniform * MAX + 1.0)
p = prn.uniform * 2.0 * PI
r = sqrt(-2.0 * ln(v + TINY))
r = sqrt(-2.0 * ln(v))
result = r * cos(p)

# Only needed for non-vectorized RNGs.
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5 changes: 3 additions & 2 deletions src/rng/mrg32k3a.nim
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Expand Up @@ -120,6 +120,7 @@ proc seed*(prn: var MRG32k3a; sed,index: auto) {.inline.} =
seedIndep(prn, ss, index)

proc uniform*(prn:var MRG32k3a):float =
## Uniform random numbers from 0 to 1, excluding 0 and 1.
var p1,p2:float
p1 = a12 * prn.s1[1].float - a13n * prn.s1[0].float
p1 = p1 mod m1
Expand All @@ -145,11 +146,11 @@ proc uniform*(prn:var MRG32k3a):float =
proc gaussian*(prn: var MRG32k3a): float =
## Gaussian normal deviate
## Probability distribution exp( -x*x/2 ), so < x^2 > = 1
const TINY = 9.999999999999999e-308
# uniform excludes 0 and 1
var v,p,r: float
v = prn.uniform
p = prn.uniform * 2.0 * PI
r = sqrt(-2.0 * ln(v + TINY))
r = sqrt(-2.0 * ln(v))
result = r * cos(p)

import maths/types
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