<div dir="ltr"><div><div>Maybe not good quality, but I like this one for my ludic purposes:<br><br>    <a href="https://github.com/lmbarros/sbxs_dlang/blob/master/src/sbxs/rand/rng.d#L283" target="_blank">https://github.com/lmbarros/sbxs_dlang/blob/master/src/sbxs/rand/rng.d#L283</a><br><br></div>It is an implementation of an approximation algorithm that used to be described here:<br><br>    <span class=""><a href="http://home.online.no/~pjacklam/notes/invnorm/">http://home.online.no/~pjacklam/notes/invnorm/</a></span><br><br></div>But appears to be offline right now. On the Wayback Machine:<br><div><br><a href="http://web.archive.org/web/20151030212409/http://home.online.no/~pjacklam/notes/invnorm" target="_blank">    http://web.archive.org/web/20151030212409/http://home.online.no/~pjacklam/notes/invnorm</a><br><br></div><div>LMB<br></div><div><br><div class="gmail_extra"><br><div class="gmail_quote">On Sat, Feb 20, 2016 at 12:01 PM, Andrei Alexandrescu via Digitalmars-d <span dir="ltr"><<a href="mailto:digitalmars-d@puremagic.com" target="_blank">digitalmars-d@puremagic.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">Do we have a good quality converter of uniform numbers to Gaussian-distributed numbers around? -- Andrei<br>
</blockquote></div><br></div></div></div>