std::rand: add the Sample and IndependentSample traits.

These are a "parameterised" Rand.
std::rand: Add RandSample for Sample-ing Rand types directly.
std::rand: full exponential & normal distributions

Complete the implementation of Exp and Normal started by Exp1 and
StandardNormal by creating types implementing Sample & IndependentSample
with the appropriate parameters.
std::rand: add distributions::Range for generating [lo, hi).

This reifies the computations required for uniformity done by
(the old) `Rng.gen_integer_range` (now Rng.gen_range), so that they can
be amortised over many invocations, if it is called in a loop.

Also, it makes it correct, but using a trait + impls for each type,
rather than trying to coerce `Int` + `u64` to do the right thing. This
also makes it more extensible, e.g. big integers could & should
implement SampleRange.
std::rand: documentation & references.

Most importantly, links to the papers/references for the core
algorithms (the RNG ones & the distribution ones).
std::rand: optimise & document ziggurat.

Before:

    test rand::distributions::bench::rand_exp ... bench: 1399 ns/iter (+/- 124) = 571 MB/s
    test rand::distributions::bench::rand_normal ... bench: 1611 ns/iter (+/- 123) = 496 MB/s

After:

    test rand::distributions::bench::rand_exp ... bench: 712 ns/iter (+/- 43) = 1123 MB/s
    test rand::distributions::bench::rand_normal ... bench: 1007 ns/iter (+/- 81) = 794 MB/s
std::rand: lengthen the RNG benchmarks.

This makes them more representative, as the `bh.iter` is a smaller
percentage of the total time.
std::rand: move Weighted to distributions.

A user constructs the WeightedChoice distribution and then samples from
it, which allows it to use binary search internally.
auto merge of #9810 : huonw/rust/rand3, r=alexcrichton

- Adds the `Sample` and `IndependentSample` traits for generating numbers where there are parameters (e.g. a list of elements to draw from, or the mean/variance of a normal distribution). The former takes `&mut self` and the latter takes `&self` (this is the only difference).
- Adds proper `Normal` and `Exp`-onential distributions
- Adds `Range` which generates `[lo, hi)` generically & properly (via a new trait) replacing the incorrect behaviour of `Rng.gen_integer_range` (this has become `Rng.gen_range` for convenience, it's far more efficient to use `Range` itself)
- Move the `Weighted` struct from `std::rand` to `std::rand::distributions` & improve it
- optimisations and docs