1st draft of complete class-based std.random successor

[Joseph Rushton Wakeling]

On Saturday, 22 March 2014 at 23:56:35 UTC, bearophile wrote:
> They seem good.

Excellent!

There may need to be some attention to the internals of 
uniform01.  Its correctness depends on whether one can always 
trust a float-based RNG to return values in [min, max) or whether 
[min, max] is also going to be supplied by some.

> More ideas:
>
> "Three suggestions for std.random":
> https://d.puremagic.com/issues/show_bug.cgi?id=4851

I think all std.random functions now support a default RNG.  
There were some bugs related to that (e.g. the "can't use 
Xorshift" one) that I fixed last year.

The problem you identify with,

     int r = randomCover(data, rndGen).front;

always returning the same value, is down to the fact that rndGen 
is being copied inside the RandomCover struct by value, so of 
course the original rndGen is never updated and each of these 
calls will produce the same result.  The new std.random2 fixes 
that, because the RNGs are reference types.

However, I'd have thought that

     int r = data.sample(1, rndGen).front;

would have been a more efficient way to implement "choice", as it 
can operate on any input range, as long as it has the .length 
property; and it ought to be _much_ faster than even a single 
call to randomCover.

One could always use this as a default option, with a 
specialization where data is a RandomAccessRange to use the more 
efficient

     int r = data[uniform!"[)"(0, data.length)];

> "Strongly pure random generator":
> https://d.puremagic.com/issues/show_bug.cgi?id=5249

.front and .popFront at least are pure for _all_ the RNGs 
currently implemented in std.random2.generator.  See e.g.:
https://github.com/WebDrake/std.random2/blob/master/std/random2/generator.d#L266-L272
https://github.com/WebDrake/std.random2/blob/master/std/random2/generator.d#L506-L517
https://github.com/WebDrake/std.random2/blob/master/std/random2/generator.d#L821-L834

Of course this is not strongly pure in line with your request, 
but it should enable use of these RNGs in many other scenarios 
where purity is important.

> I hope a gaussian (normal distribution) generator is planned or 
> present.

https://github.com/WebDrake/std.random2/blob/master/std/random2/distribution.d#L326

This is a range implementation; there will also be a function 
implementation, which will probably follow the inefficient 
Box-Muller variant that uses 2 uniform random variates to 
generate a single normal variate (as per the example you posted 
in your feature request).