Make mir.random.algorithm's range work with N-dimensional distributions about mir-random

[n8sh]

I am not sure what the correct interface should be for this in the long run, but for now you can use a wrapper function to convert an ndvariable to a variable:

/++
Converts an N-dimensional variable to a fixed-dimensional variable.
+/
auto specifyDimension(ReturnType, NDVariable)(NDVariable vr)
    if (__traits(isStaticArray, ReturnType) && __traits(compiles, {static assert(NDVariable.isRandomVariable);}))
{
    import mir.random : isSaturatedRandomEngine;
    import mir.random.variable : isRandomVariable;
    static struct V
    {
        enum bool isRandomVariable = true;
        NDVariable vr;
        ReturnType opCall(G)(scope ref G gen) if (isSaturatedRandomEngine!G)
        {
            ReturnType ret;
            vr(gen, ret[]);
            return ret;
        }

        ReturnType opCall(G)(scope G* gen) if (isSaturatedRandomEngine!G)
        {
            return opCall!(G)(*gen);
        }
    }
    static assert(isRandomVariable!V);
    V v = { vr };
    return v;
}

So main from your above example becomes:

void main()
{
    import std.stdio;
    import mir.random : Random, threadLocalPtr;
    import mir.random.ndvariable : multivariateNormalVar;
    import mir.random.algorithm : range;
    import mir.ndslice.slice : sliced;
    import std.range : take;

    auto mu = [10.0, 0.0].sliced;
    auto sigma = [2.0, -1.5, -1.5, 2.0].sliced(2,2);

    Random* rng = threadLocalPtr!Random;
    auto sample = rng
                .range(multivariateNormalVar(mu, sigma).specifyDimension!(double[2]))
                .take(10);
    writeln(sample);
}

Execute this example on run.dlang.io.

[9il]

fixed. see second example for http://docs.random.dlang.io/latest/mir_random_algorithm.html#.RandomRange