sample_laplace_distribution() should take multiple random inputs
Currently, sample_laplace_distribution() takes a random double as input, and then extracts the following random values:
- a random sign
- a random value in (0.0, 1.0]
This reduces the precision of the result. For details, see: https://trac.torproject.org/projects/tor/ticket/23061#comment:32
Instead, the function could take a random boolean sign and p, and the transform becomes:
result = mu - b * (sign ? 1.0 : -1.0) * tor_mathlog(1.0 - p);
This would increase the precision by one bit, plus whatever precision is lost in
2.0 * fabs(p - 0.5).
This may have been introduced in dad5eb7e.