Description
The ZigguratNormalisedGaussianSampler uses the following method to sample the tail of the Gaussian:
// Note // R = 3.442619855899 // 1 / R = 0.2905... double y; double x; do { y = Math.log(rng.nextDouble()); x = Math.log(rng.nextDouble()) * ONE_OVER_R; } while (y + y < x * x); final double out = R + x; return hz > 0 ? out : out;
In the unlikely event the RNG produces 0 then Math.log(0) is infinity. Two zeros in a row can result in an infinite sample for the tail. This is very unlikely but would be unexpected for a user of the library since a sample should be roughly within +/3.
Note that if the RNG is sampling from the 2^53 dyadic rationals in [0, 1) then the next value is:
Math.log(0x1.0p53) == 36.7368005696771
The largest value x where 2y < x^2 is false is sqrt(2*36.74) = 8.571 and the returned tail would be +/ 12.01. This is very far from the extreme of infinity.
To avoid infinity this can be fixed by:
1. Assuming the RNG is returning a value in [0, 1) and using Math.log(1.0  rng.nextDouble())
2. Generating the double u from a long to ensure the value is in [0, 1) and using 1.0  u.
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RNG148 UnitSphereSampler does not check for infinite length dimension
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