feature/latent samples

[rhayes777]

Analysis now compute a Samples object called latent_samples which comprises latent variables and corresponding sample data such as likelihood and weight.

Latent sample data is output in the same way as sample data using the same methods although not all function calls on samples have been mirrored for latent samples.

More complex models can be expressed by returning '.' separated paths.

e.g.

def compute_latent_variables(self, instance):
    return {"one.two": 3}

...

prior = latent_samples.model.one.two

Priors by GaussianPriors with zero sigma